Procyon lotor) living around a large Chicago-area zoo, and appeared higher in year 2001 than in 1998 and 2000. We hypothesized that a more lethal variant of the local Canine distemper virus (CDV) lineage had emerged in 2001, and sought the genetic basis that led to increased virulence. However, a more complex model surfaced during preliminary analyses of CDV genomic sequences in infected tissues and of virus isolated in vitro from the raccoons.Mortality rates have differed during distemper outbreaks among free-ranging raccoons (fusion (F) -, phosphoprotein (P) -, and complete hemagglutinin (H) – gene sequences indicated that distinct American CDV lineages caused the distemper epizootics. The 1998 outbreak was caused by viruses that are likely from an old CDV lineage that includes CDV Snyder Hill and Lederle, which are CDV strains from the early 1950's. The 2000 and 2001 viruses appear to stem from the lineage of CDV A75/17, which was isolated in the mid 1970's. Only the 2001 viruses formed large syncytia in brain and/or lung tissue, and during primary isolation in-vitro in Vero cells, demonstrating at least one phenotypic property by which they differed from the other viruses.Phylogenetic analyses of subgenomic CDV Two different American CDV lineages caused the raccoon distemper outbreaks. The 1998 viruses are genetically distant to the 2000/2001 viruses. Since CDV does not cause persistent infections, the cycling of different CDV lineages within the same locale suggests multiple reintroductions of the virus to area raccoons. Our findings establish a precedent for determining whether the perceived differences in mortality rates are actual and attributable in part to inherent differences between CDV strains arising from different CDV lineages. Canine distemper virus (CDV)  is a single-stranded (negative-sense) enveloped RNA virus that is highly contagious and transmitted predominantly by aerosols  and the fusion domain [F-gene sequence can be used to determine phylogenetic relationships between different morbillivirus species, such as the relationship between CDV and the closely related morbillivirus of salt-water seals called Phocine distemper virus-1 (PDV-1) [F-gene analysis would thus help establish whether the virus was authentic CDV and not a related raccoon morbillivirus. Finally, the entire CDV receptorbinding hemagglutinin (H) gene was analyzed, since the H protein is the major determinant of tropism and cytopathogenicity [We first sought to identify the local lineage of CDV through direct sequence analysis of viral RNA (vRNA) in infected raccoon tissues and also attempted virus isolation from the specimens. Virus isolation was important not only to confirm direct sequence analyses but also: (a) because it was possible that direct sequence analyses might not work for various technical reasons, and (b) for future vaccine development in the event that unusual viral variants were detected for which current vaccines were ineffective. Following the example of previous investigators, we tried to obtain the identity of the circulating local CDV by determining the sequence of a subsection of the CDV  lineage , and is  lineage ,24,25. Tn domain . The F-pn domain , and the (PDV-1) . F-gene genicity , and is genicity ,23.Whereas all the viruses were related to American CDV strains, the 1998 and 2001 viruses were clearly resolved by phylogenetic analyses into two genetically distant CDV clusters (lineages). The 2000 virus apparently stems from a sublineage related to the 2001 viruses.Encephalomyocarditis virus (EMCV) in animals 01-2641 and 01-2690, however, was unexpected.In general, the results obtained from gross and histologic examinations of the animals were typical for CDV-induced distemper. Major findings included non-suppurative encephalitis and necrotizing bronchointerstitial pneumonia of variable severity Table . As expeHistologic differences in the CDV lesions were apparent. While lymphoid depletion and characteristic eosinophilic intracytoplasmic inclusions in various epithelial tissues were observed in all years, inclusion bodies were more plentiful in the brain and lung tissues of raccoons examined in year 2001 than those of years 1998 and 2000. Of note, small and large (multinucleated) syncytia were present in the central nervous system and Fig.  and lungrare formation of small stellate syncytia (consisting of 2–3 cells fused together) for viruses isolated from year 1998 and 2000 specimens or frequent larger rounded syncytia typically containing >8 nuclei in viruses from year 2001 [in vivo , only the deduced aa sequences are shown  was also the same in both cladograms. However, while parsimony joined the 01-2641 sequence from an offsite raccoon to the base, the distance based tree grouped this sequence with CDV A75/17. The 2000 virus was also not resolved by either method of analysis. Of the 390 bases, 34 were informative. Derivatives of the 1998 cluster form a distantly related lineage to that of 2001 cluster that is nevertheless rooted in the CDV group when compared to PDV-1 as an outgroup. CDV Lederle appears to be more derived than A9224/14b  raccoon [The 70% majority-rule consensus parsimony Fig.  and neigF-gene and 32 of these were parsimony informative. Both parsimony  while the 2001 isolates were most distant (D = 9% and 10% respectively). Distances within 1998 viruses were low (D ≤ 0.2%); within 2001, distances were slightly higher (D = 1%); and comparing years 1998 with 2000 and 2001, distances were highest (D = 7% to 9% respectively).Noteworthy, P-, F- and H- genes were combined into a single linear sequence and analyzed using parsimony and neighbor-joining algorithms with only PDV-1 as an outgroup, two independent clades are formed, the 1998 clade and the 2000/2001 clade (data not shown). In the later group, both methods join the 2000 sequence (00-2601) at a basal position to the 01-2641 off-site raccoon followed by the 2001 isolates.When the This report shows that different CDV sublineages stemming from at least two genetically distant CDV lineages recently circulated through the local raccoon population. Our conclusion is based on numerous observations: differences in the lesions observed in animal tissues, possible dissimilarities of virulence between the viruses, variation in one viral phenotype in tissue culture (formation of large syncytia by the 2001 viruses), and from the results of nucleotide sequence and phylogenetic analyses. CDV is not maintained in hosts that recover from distemper, and persistent CDV infections do not occur. However, CDV infects a wide range of genera, and though each individual population may be small, the number of alternative host species may be substantial [Since past studies indicated that wild-type CDVs differed according to geographical distribution ,23, we iin vivo and in vitro. Previously, an inverse relationship between the proficiency of syncytium formation and the level of CDV virulence was reported: the more attenuated a strain is, the higher its fusogenicity, and fusogenicity was attributed to the viral H-protein [in vivo and in vitro. However, past notions concerning the inverse relationship between fusogenicity and virulence may be imprecise. Indeed, virulent wild-type CDVs that formed syncytia in Vero cells were recently reported; the same study demonstrated that genetic changes within the H-gene were not required for CDV growth in Vero cells [including the F- and H- proteins [The viruses from year 2001 formed syncytia -protein -34. Therro cells , as was ro cells . Also, nro cells -38, and proteins . Thus, wproteins ,41. It iH-gene phylogenetic analyses  in urban areas. The possibility of reversion to virulence of attenuated CDV exists [s figure  suggest  figures ,5,6 indi results . Becauseequences , it is cthe past . The vacV exists , and a vV exists . We coulV exists , and theBordetella bronchiseptica, and Toxoplasma gondii. It is possible that the increased mortality in 2001 was due to secondary infections with EMCV; however, no lesions attributable to EMCV were observed in pathology exams of the animals of this study, and EMCV was not isolated from all of the 2001 specimens. The significance of isolating EMCV from the brain tissue of animal 01-2641 is thus uncertain.EMCV has been isolated or detected in raccoons before ,45. Howein vitro. The baseline genetic values established here will be helpful toward the development of a contemporary field-based model  for studies on the emergence, evolution, maintenance, and transmission of morbilliviruses, and the efficacy of vaccines against changing viruses.Our findings are especially useful for the molecular epidemiology of CDV in local wildlife, as they provide a molecular basis for CDV surveillance in area wildlife. Whereas it is considered difficult to obtain field isolates of CDV, we succeeded and can now obtain complete viral genomic sequence data . Taken together, we can now monitor viral genetic drift during a long-term study of CDV in local raccoons, and will be able to conduct animal studies with the newly isolated viruses. We can also clone relevant CDV virulence genes, and express and study the biochemical properties of their specific products The 1998 and 2001 distemper outbreaks were caused by two genetically distant American CDV lineages. Since CDV does not cause persistent infections, the cycling of different CDV lineages within the same locale suggests multiple reservoirs were responsible for the reintroduction of the virus to area raccoons. Whereas different susceptible species of the forest preserves and perhaps also some caged animals of the zoo are the most likely reservoirs, our study raises the possibility that vaccines might also be a source of CDV. The perceived differences in mortality rates that occur during intermittent distemper epizootics may be attributed in part to inherent differences between CDV strains.The raccoon tissues used in this study were described previously ; relevanin vitro in MDCK, MV1-Lu, and Vero cells, eliminating the need for virus isolation in specific pathogen-free animals or in primary macrophages or other suitable cells derived thereof [Detailed virus isolation procedures were described previously . Briefly thereof .RNA purification and RT-PCR methods were previously detailed . Brieflyprimary viral isolates [Methods used for nucleic acid sequencing were previously described . Brieflyisolates . The GenP-, F-, and H-gene sequences were constructed using the maximum-parsimony and neighbor-joining algorithms in Phylogeny Analysis Using Parsimony (PAUP) Beta Version 4.0B10 for Macintosh [Phocine distemper virus sequence (PDV-1) was included for outgroup rooting.Phylogenetic trees of the acintosh . Heuristacintosh . Phylogeacintosh ,50. The P-gene phylogenetic analyses were performed after an alignment of 25 P-gene sequences. Each P-gene sequence consisted of 390 ungapped positions (nucleotides 2154 to 2543 of CDV reference strain Onderstepoort) within the P-gene PCR amplicon. Only the internal 390 bp section of the P-gene PCR amplicon (432 bp) was analyzed because many relevant GenBank entries did not include the entire sequence amplified by the P-gene primers of this study. An additional P-gene sequence for raccoon A9224/14b was obtained from published data currently not deposited at GenBank [F-gene sequences corresponding to nt 5399–5733 (335 bp) of CDV Onderstepoort were analyzed. Unlike the P- and F-genes, the entire H-gene was analyzed since many complete H-gene sequences were available at GenBank. Phocine distemper virus 1 (PDV1) sequences were included in the analyses for outgroup rooting. GenBank . SimilarNone declared.JAL co-conceived, designed, and coordinated the study, isolated virus, participated in the molecular genetic studies and sequence alignment, interpreted data, oversaw the training of technicians, and drafted the manuscript; JD performed phylogenetic analyses, interpreted data, and helped draft the manuscript; MJK performed pathology examinations, provided tissue specimens, helped draft the manuscript, and interpreted data; TPM co-conceived the study, provided serology data, helped draft the manuscript, and interpreted data; MB performed phylogenetic analyses, interpreted data, and helped draft the manuscript; LLH provided serology data and epidemiology perspectives, and helped draft the manuscript; NAS participated in virus isolation, molecular genetic studies, sequence alignment, and proofreading of the manuscript; KEW participated in virus isolation and molecular genetic studies, and MDB, CP, and CMH performed molecular genetic studies. All authors read and approved the final manuscript


Gonadotropin-primed immature rats (GPIR) constitute a widely used model for the study of ovulation. Although the equivalence between the ovulatory process in immature and adult rats is generally assumed, the morphological and functional characteristics of ovulation in immature rats have been scarcely considered. We describe herein the morphological aspects of the ovulatory process in GPIR and their response to classical ovulation inhibitors, such as the inhibitor of prostaglandin (PG) synthesis indomethacin (INDO) and a progesterone (P) receptor (PR) antagonist (RU486). Immature Wistar rats were primed with equine chorionic gonadotropin (eCG) at 21, 23 or 25 days of age, injected with human chorionic gonadotropin (hCG) 48 h later, and sacrificed 16 h after hCG treatment, to assess follicle rupture and ovulation. Surprisingly, GPIR showed age-related ovulatory defects close similar to those in adult rats lacking P and PG actions. Rats primed with eCG at 21 or 23 days of age showed abnormally ruptured corpora lutea in which the cumulus-oocyte complex (COC) was trapped or had been released to the ovarian interstitum, invading the ovarian stroma and blood and lymphatic vessels. Supplementation of immature rats with exogenous P and/or PG of the E series did not significantly inhibit abnormal follicle rupture. Otherwise, ovulatory defects were practically absent in rats primed with eCG at 25 days of age. GPIR treated with INDO showed the same ovulatory alterations than vehicle-treated ones, although affecting to a higher proportion of follicles. Blocking P actions with RU486 increased the number of COC trapped inside corpora lutea and decreased ovulation. The presence of ovulatory defects in GPIR, suggests that the capacity of the immature ovary to undergo the coordinate changes leading to effective ovulation is not fully established in Wistar rats primed with eCG before 25 days of age. Ovulation, the release of mature oocytes from the ovary, requires proteolytic degradation of the follicle wall, as well as the overlying ovarian tissues. This happens through the expression of a series of critical genes, triggered in a precise temporal and spatial pattern by the preovulatory LH surge ,2. It isGonadotropin-primed immature rats (GPIR) constitute a useful model for the study of ovulation. The administration of a single dose of equine chorionic gonadotropin (eCG) to immature animals induces the growth of abundant follicles, that reach preovulatory size in two days. Ovulation is then triggered by a single dose of human chorionic gonadotropin (hCG), thus providing a large number of synchronized ovulatory follicles -25. An aIn order to examine further the role of PG and P in follicle rupture and ovulation, we performed detailed morphological analysis of the ovulatory process in inmature rats primed with gonadotropins at different ages. Surprisingly, these animals showed age-related alterations of the follicle rupture similar to those of adult rats lacking PG and P actions. We report herein the morphological alterations of follicle rupture and ovulation in GPIR and the effects of treatment with P and/or PG of the E series, as well as the response of GPIR to PG synthesis inhibition with INDO and to a PR antagonist RU486), whose inhibitory effects in ovulation are clearly established ,8,13,14.6, whose Wistar female rats bred in the vivarium of the University of Cordoba were used. The day the litters were born was considered as day 0. Litter size was adjusted to 8 pups. The animals were maintained under controlled conditions of light  and temperature (22°C). The animals had free access to pelleted food and tap water. Experimental procedures were approved by the Cordoba University Ethical Committee for animal experimentation and were conducted in accordance with the European Union guidelines for care and use of experimental animals. Indomethacin (INDO), Progesterone (P), equine chorionic gonadotropin (eCG), human chorionic gonadotropin (hCG) and prostaglandins were purchased from Sigma.. The progesterone antagonist RU486 was obtained from Exlegin .Wistar immature rats were injected sc with 10 IU of eCG at 1700 h at 21, 23 or 25 days of age, and 48 h later were injected sc with 10 IU of hCG, a frequently used schedule ,27. BodyImmature rats were primed with eCG at 21 days of age and with hCG 48 h later as described above. In addition, these animals were injected with 100 μg of PGE1 or PGE2, 1 mg of P or 1 mg of P plus 100 μg of PG E1 or PGE2 or vehicles  at 1730 h (30 min after hCG treatment). These dosages were effective, in the same body weight basis, in previous studies in adult rats . The aniImmature rats were primed with eCG at 23 days of age and with hCG 48 h later as described in previous experiments. Indomethacin-treated rats received a sc injection of 0.5 mg of INDO or vehicle (olive oil) at 1200 h at 25 days of age. RU486-treated rats were injected sc with 0.5 mg of RU486 or vehicle (olive oil) at 0900 h at 24 and 25 days of age.The animals (5 per group) were killed at 0900 h on the day following hCG injection (i.e. at 26 days of age) and the ovaries were processed as described above.The right ovaries were serially sectioned (6 μm) and stained with hematoxylin and eosin. All sections were examined under the microscope. The total number of cumulus-oocyte complexes (COCs) per ovary were counted. The number of COCs trapped inside the corpus luteum, released to the ovarian interstitium, retained in the bursal cavity or found in the oviducts, was recorded. COCs released to the ovarian interstitium were clearly recognizable by the presence of the oocyte in metaphase II and the first polar body, dispersed cumulus and follicular fluid. The total number of COCs per ovary matches the total number of corpora lutea (unruptured or not). In addition to absolute values, the number of COCs in each location was expressed as the percentage with respect to the total number of COCs (or corpora lutea) per ovary, to assess ovulatory efficiency, avoiding variability in the total numbers of corpora lutea among the different groups. Unruptured follicles measuring less than 575 μm in diameter, showing signs of atresia, such as irregularities of the granulosa cell layer, presence of apoptotic granulosa cells, as well as lack of dispersion of the cumulus or resumption of meiosis, were not considered.Statistical analysis was performed by ANOVA followed by the Student-Newman-Keuls method for multiple comparison among means. Significance was considered at the 0.05 level.Absolute numbers of COCs, that match the numbers of corpora lutea per ovary, are presented in Table The total number of COCs per ovary was equivalent in rats primed with eCG at 21 days of age and treated with vehicles, P, PGE1, PGE2, P plus PGE1 or P plus PGE2 Table .The total number of COCs per ovary was equivalent in rats treated with vehicle, INDO or RU486 Table . ImmaturGonadotropin-primed immature rats (GPIR) is a popular model for the study of ovulation. In this model, eCG stimulates the growth of a large cohort of follicles, that reach preovulatory size in about 48 h and are then induced to ovulate by hCG ,2,28. EaDefective ovulation in GPIR was related to abnormal follicle rupture. Whereas some LH-driven morphological changes in preovulatory follicles, such as cumulus expansion, resumption of the meiotic process and initial luteinization were present and showed normal features in GPIR, aberrant follicle ruptures were frequently observed. This was indicated by the presence of COCs released to the ovarian interstitium, and of corpora lutea showing rupture of the theca layers at any site of the follicle wall with release of follicular fluid to the ovarian stroma. The presence of follicle ruptures at the basolateral follicle sides suggests that the mechanisms underlying the spatial targeting of follicle rupture at the apex are not fully established in immature rats primed with eCG before 25 days of age. Almost identical ovulatory defects have been previously reported in INDO-treated adult cycling rats that also show abnormally ruptured follicles and proteolytic degradation of perifollicular tissues -9. FurthIt has been clearly established that activation of PR plays a crucial role in ovulation ,11,33-37The end-point of the complex interaction network leading to follicle rupture and COC release, is the expression/activation of proteolytic enzymes, reponsible for extracellular matrix breakdown ,38,39. PIn conclusion, the presence of aberrant ovulations in very young GPIR, closely resembling those in adult rats lacking P and PG actions, strongly suggests that the capacity of the immature ovary to undergo changes leading to effective ovulation is not fully established in Wistar rats primed with eCG before 25 days of age. This should be taken into account when using the GPIR model for studies focused on ovulation.


The aim of the study was to develop a menopause-specific, preference-based health-related quality-of-life (HRQoL) index reflecting both menopausal symptoms and potential side-effects of Hormone Replacement Therapy (HRT).The study had three phases: the development of a health state classification, a prospective valuation survey and the estimation of a model to interpolate HRQoL indices for all remaining health states as defined by the classification. A menopausal health state classification was developed with seven dimensions: hot flushes, aching joints/muscles, anxious/frightened feelings, breast tenderness, bleeding, vaginal dryness and undesirable androgenic signs. Each dimension contains between three and five levels and defines a total of 6,075 health states. A sample of 96 health states was selected for the valuation survey. These states were valued by a sample of 229 women aged 45 to 60, randomly selected from 6 general practice lists in Sheffield, UK. Respondents were asked to complete a time trade-off (TTO) task for nine health states, resulting in an average of 16.5 values for each health state.Mean health states valued range from 0.48 to 0.98 . Symptoms, as described by the classification system, can be rank-ordered in terms of their impact (from high to low) on menopausal HRQoL as follows: aching joints and muscles, bleeding, breast tenderness, anxious or frightened feelings, vaginal dryness, androgenic signs. Hot flushes did not significantly contribute to model fit. The preferred model produced a mean absolute error of 0.053, but suffered from bias at both ends of the scale.This article presents an attempt to directly value a condition specific health state classification. The overall fit was disappointing, but the results demonstrate that menopausal symptoms are perceived by patients to have a significant impact on utility. The overall effect is modest compared to the more generic health state descriptions such as the EQ-5D. The resultant algorithm generates a preference-based index that can be used economic evaluation and that reflects the impact of this condition. The increasing demand for economic evaluation of health care interventions has lead to a corresponding rise in the derived demand for evidence on the key parameter inputs into cost effectiveness models. One of those inputs is the health state utility value used to estimate the quality adjusted life years (QALYs) associated with an intervention. This article is concerned with estimating a preference-based measure for generating utility values for menopausal health states.Most preference-based measures of health such as the EQ-5D, SF-6D and the Health Utilities Index 3, have a generic health state descriptive system -3. HowevThe aim of this study is to quantify the impact of menopause-related health problems on health-related quality of life as indicated by a "strength-of-preference" index. This project had three components. The first was to construct a health state classification system for menopausal symptoms based on work by Zoellner and others ; secondlA menopause-specific quality-of-life questionnaire has been developed by Zoellner and colleagues ,15. InitThe application of these criteria resulted in a questionnaire with 22 items grouped into 6 domains, namely 1) psychosocial, (2) physical, (3) vasomotor, (4) sexual, (5) menstrual, and (6) androgenic complaints. In order to derive a health state classification from the former, the most robust item(s) were chosen from each domain. As it was felt important to cover potential side-effects of Hormone Replacement Therapy (HRT), the menstrual domain is represented with two items – 'breast tenderness' and 'vaginal bleeding' – in the classification systems; the latter hence consists of the following seven domains of menopausal health  on a sample of women aged 45 to 60. The key design issues were the sample of health states to be valued, the sample of respondents, the valuation technique and the interview.It is not possible to value all the states defined by the menopausal specific health state classification. However, there is currently little guidance of the selection of states for valuation . Based oEach respondent was asked to value a sample of eight states. These states were selected from the larger sample of 96 using a stratified sampling technique to ensure that each respondent has a mix of mild, moderate and more severe states. The severity of the states has been assessed by summing the dimension levels. The states were then ranked using this sum score and divided into quartiles to identify four severity groups. Two health states have been selected at random without replacement from each severity group to form a set of eight health states. This was done another 11 times to create 12 sets of states. These 12 sets were used an equal number of times in order to ensure that each of the 96 states would be valued an equal number of times.The original aim was to interview 150 respondents, where each respondent valued eight health states. This would mean undertaking 24 sessions with between 6–8 respondents at each session and would have resulted in 1200 observations and an average of 12.5 valuations per state.A previous survey was undertaken in Sheffield (UK) with the main aim of validating the new questionnaire designed to assess the health of women in mid -life. One thousand and eighty women aged 45 to 60 were randomly selected from the lists of 6 GPs in Sheffield (180 women per GP List) and sent the postal questionnaire concerning their menopausal symptoms. Of these 790 (73%) were returned. Five were dropped from further analysis due to incomplete response, so the total number was 785 responders. All responders were sent a summary of the study "Women's Health in Mid life" in December 2001 and asked if they would be interested in participating in a second phase of the study. Out of these 417 women replied saying they would like more information of the phase 2 study.The 6 GP practices signed a consent form agreeing to these women being invited to participate in the valuation survey. Invitation letters were sent by each practice with a Patient information sheet and a Patient consent form. Out of the 417, 229 (55%) attended the interviews and completed a questionnaire.Health states were valued using a variant of the time trade-off technique (TTO). This technique asks the respondent to choose between a fixed period of time (t) in the health state to be valued compared to a shorter period in full health (x). The amount of time spent in full health is varied until the respondent is indifferent between the two alternatives. The value of the health state is then x/t for states better than dead.This study used a self-completed variant of TTO developed by Gudex that uses a titration procedure shown in Table Respondents were invited to attend interview sessions held in a room at the Institute of General Practice in Sheffield (UK). Two researchers experienced in interviewing patients coordinated these sessions. The interview began with the researchers explaining the purpose of the survey and to explain the TTO task. Patients were asked to complete an example and encouraged to ask questions in order to aid in their understanding. Once the respondents were ready, they were then asked to complete all remaining questions on their own. There were 33 such interview sessions in the survey. Respondents were reimbursed for their time and travel with a voucher for £10.The questionnaire had questions on age, occupation, education level, general health, whether or not they had stopped menstruating and if so when, and finally whether or not they continued to take HRT. They were then asked to complete the menopausal health state classification. They then undertook a practice TTO question followed by eight TTO questions. The health states were presented in a random order to avoid the risk of an ordering effect. Finally they were asked to value their own health using a TTO question.The overall aim is to construct a model for predicting health state valuations based on the menopausal health state classification. The data generated by the valuation survey described above has a complex structure, as they are skewed and health state valuations are clustered by respondent. Disentangling the respondent effect is a complex task and can only be tackled at the individual level, where each valuation is regarded as a separate observation, rather than using the mean value for each health state. The former has the advantage of greatly increasing the number of degrees of freedom available for the analysis (from 96 to over 1200) and enabling the analysis of respondent background characteristics on health state valuations.A number of alternative models have been proposed for estimating preference functions from health data ,14,15. Tyij = g (β'xij + θ'rij + δ'zj) + εij     (1)i = 1, 2, ..., n represents individual health state values and j = 1,2, ..., m represents respondents. The dependent variable, yij, is the TTO score for health state i valued by respondent j. x is a vector of binary dummy variables (xδλ) for each level λ of dimension δ of the classification. Level λ = 1 acts as a baseline for each dimension, so in a simple linear model, the intercept represents state 1111111, and summing the coefficients of the 'on' dummies derives the value of all other states.where r term is a vector of terms to account for interactions between the levels of different attributes. z is a vector of personal characteristics that may also affect the value an individual gives to a health state, for example, age, sex and education. The role of personal characteristics is not discussed in this paper. g is a function specifying the appropriate functional form. εij is an error term whose autocorrelation structure and distributional properties depend on the assumptions underlying the particular model used.The This is an additive model, which imposes no further restrictions on the relationship between dimension levels of the classification. For example, it does not enforce an interval scale between the levels of each dimension and does not impose ordinality on the levels.εijεi'j) = 0, i≠i'. This specification ignores the clustering in the data and assumes that each individual health state value is an independent observation, regardless of whether or not it was valued by the same respondent. An improved specification, which takes account of variation both within and between respondents, is the one-way error components random effects model. This model explicitly recognises that n observations on m individuals is not the same as n × m observations on different individuals. Estimation is via generalised least squares (GLS) or maximum likelihood (MLE).OLS assumes a standard zero mean, constant variance error structure, with independent error terms, that is cov – to account for the skewed distribution of health state valuations. Four functional forms are used. Firstly, a Logit transformation and two complementary log-log transformations suggested by Abdalla and Russell. [Finally we consider alternative functional forms – Russell.  These arAll modelling will be done using STATA 7.0 and SPSSWin.The characteristics of the 229 interviewed women are presented on Table Thirty respondents were excluded from the modelling data set, leaving 199. Respondents were excluded due to ambiguity in the responses to the (self-administered) questionnaire. The main sources of ambiguity were the mixing up of responses (e.g. ticks and crosses appearing the wrong way around) and large gaps between the responses with no indication of the appropriate point of indifference. There were also a number of individual responses elicited from 199 respondents that had to be excluded due to similar ambiguities. These exclusions left 1580 health state values across the 96 health states for modelling, a final completion rate of 86% of all questions asked at interview.Descriptive statistics for 50 of the 96 states are presented on Table χ2 = 25585.15, P = 0.000) and Hausman's test suggests random rather than fixed effects is the appropriate specification , therefore only Random Effects (RE) and mean models are presented in Table The Breusch-Pagan test for individual effects suggests these are important (In the RE model (1), the coefficients have the expected negative sign for all main effect dummies except HF2 and VAG2, but neither of these is significant. There are 13 significant coefficients, including the constant term. There are three inconsistencies involving significant coefficients, AJ3 to AJ4, BL2 to BL3 and BL4 to BL5. The mean model has a better explanatory power than the OLS model (not shown), but has only seven significant coefficients that produce just two inconsistencies.The ability of the mean and RE main effects models to predict health state valuations within the data set is presented at the bottom of Table An important problem has been identified by the Ljung-Box statistics that reveal significant autocorrelation in the prediction of all the models. Plots of actual against predicted errors reflect a tendency to over predict at the lower end and under predict at the upper end. The model was re-estimated using a Tobit procedure, but this did not improve the predictive performance of the model. Applications of the logit and complementary log functions also did not improve model performance.The RE and mean models in Table The paper presents the results of a study aiming to estimate preference functions for the menopausal health state classification. The preference models look credible in terms of the coefficients, though there are a number of problems with the models predictive performance. This paper supports the findings of other studies, that it is the feasible to estimate condition specific preference-based indices -14.It was perhaps more ambitious than other published studies in that it attempted to estimate values for a large health state classification, where it was not possible to directly value all states. It was the first study using statistical inference to model health state values. The explanatory power of the models is not high. This is due to the high variability around the health state means, which may have been a result of the self-completed format of the TTO task. It may also have been due to comparatively low number of observations per state.The classification describes health states that are mild compared to the full range of states described by descriptive systems such as the EQ-5D or HUI3 that reflects the nature of the conditions. The specific values found for our instrument have tended to be more skewed at the upper end than the generic measures, such as the EQ-5D. This was also found for a number of other conditions, with the lowest value for Erectile Dysfunction being 0.74  and 0.87A further problem may have arisen from the descriptive system. The 2 or 3 inconsistencies between coefficients may be due to possible ambiguities in the health state classification. The ranking of AJ3 and AJ4 is ambiguous, since it is possible for 4 or more episodes per week of pain to be worse than mild to moderate constant pain. Also for BL, some people may regard irregular bleeding as better than regular bleeding. Such differences of opinion in the population in the ranking ordering of some levels would reduce the fit of the models.Of more concern is the evidence for systematic patterns in the residuals resulting in over prediction at the lower end and under predicting at the upper end of the range. The MVH group was able to solve this problem in their valuation of the EQ-5D by the inclusion of an interaction term. The inclusion of interaction terms in this study had little impact on the problem. The application of various transformations to the dependent variable also did not solve this problem.The models nonetheless provide a basis for valuing menopausal health states using this health state classification. The coefficients are consistent with the cordiality of the health state classification and the size of the mean absolute error of 0.055 to 0.065 is comparable to that achieved in other models . The addThe estimation of preference weights for condition specific quality of life has been questioned by some health economists as to its value . The argThe argument for using condition specific descriptive systems is that they are going to better reflect the impact of the condition on a patient's life. However, provided the descriptive system is valued on the same full health – death scale using the same variant of the same valuation technique using a comparable population sample, then the valuations should be comparable. Any remaining differences in values should be a legitimate consequence of the descriptive system. However, this assumes that the value of a dimension is independent of those dimensions outside of the descriptive system and this requires empirical testing. Despite these arguments, there has been increasing interest in estimating condition specific preference measures of health because the analyst often only has condition specific data and wishes to use them to undertake an economic evaluation, or the analyst feels a generic measure is not appropriate for the condition.The advantages of using a condition specific descriptive system over a generic are that it should be more sensitive to improvements in health. However, the overall fit was disappointing. The results demonstrate that menopausal symptoms are perceived by patients to have a significant impact on utility, but the overall effect is modest compared to the more generic health state descriptions such as the EQ-5D. This research has also demonstrated the problems that can be encountered when trying to value a comparatively mild condition. The resultant algorithm generates a preference-based index that can be used economic evaluation and that reflects the impact of this condition.JB led the project, including the design of the valuation study and undertaking much of the analysis. MP contributed to the design of the valuation survey and undertook the interviews. JR provided a key input into the econometric analyses. YZ designed the menopausal health state classification and contributed to the overall design of the study. All authors contributed to the writing of the paper.


To calculate these properties, the methodology identifies an optimal eleven residue window (L = 11), assuming an amino acid angular frequency, θ, fixed at 100°.Integral membrane proteins are the primary targets of novel drugs but are largely without solved structures. As a consequence, hydrophobic moment plot methodology is often used to identify putative transmembrane α-helix forming sequences, the relationship between <μH> and <H>, and the effect of varying of L and / or θ on this relationship, was investigated. Confidence intervals for correlations between <μH> and <H> are established. It is shown, using bootstrapping procedures that the strongest statistically significant correlations exist for small windows where 7 ≤ L ≤ 16. Monte Carlo analysis suggests that this correlation is dependent upon amino acid residue primary structure, implying biological function and indicating that smaller values of L give better characterisation of transmembrane sequences using <μH>. However, varying window size can also lead to different regions within a given sequence being identified as the optimal window for structure / function predictions. Furthermore, it is shown that optimal periodicity varies with window size; the optimum, based on <μH> over the range of window sizes, (7 ≤ L ≤ 16), was at θ = 102° for the transmembrane α-helix data set.Using a data set of 403 transmembrane  A number of α-helical properties have been used as models to study transmembrane α-helices and their structure / function relationships but the most commonly used are those based on the amphiphilicity of protein α-helices with the hydrophobic moment used as a measure of amphiphilicity [Integral membrane proteins are the primary choice as targets when developing new drugs and although clearly of medical relevance, forming 20% – 30% of the gene products of most genomes, these proteins have been structurally determined in only about thirty cases ,2. Whereμ(θ), which provides a measure of the structured partitioning of hydrophilic and hydrophobic residues in a regular repeat structure of period θ. For a structure comprising L consecutive residues, the general form of μ(θ) is given by:To quantify the amphiphilicity of protein secondary structures, Eisenberg and co-workers  introducHj is the hydrophobicity of the jth residue within the sequence, and θ is the angular frequency of the amino acid residues forming the structure. Eisenberg et al., [α-helix, θ is fixed at 100°, and that a segment of eleven consecutive residues, equivalent to three turns of an α-helix, could be used to represent amphiphilic α-helices. These assumptions led to the more generally used measure of α-helix amphiphilicity, the mean hydrophobic moment <μH>, wherewhere  et al.,  assumed μH> = μ(100°)/11<et al., [α-helices. Using this methodology, a putative protein α-helix is characterised according to its maximum <μH> and corresponding mean hydrophobicity, <H>, where this is defined by:As a major extension to the use of the hydrophobic moment, Eisenberg et al.,  introducμH> and <H> are then plotted on the hydrophobic moment plot diagram  and between consecutive residues [θ = 100° for all α-helices is an approximation and could lead to classification difficulties for the methodology. Furthermore, classification difficulties could arise from the arbitrary choice of window length made by the methodology as window length is known to have a profound effect on the relationship between <μH> and <H>[θ and window length are crucial to the classification of amphiphilic α-helices yet the values chosen for these parameters by hydrophobic moment plot analysis are not optimal for the classification of any single subclass.The mean hydrophobic moment is widely used and generally regarded as a good predictor of  certain . A numbe α-helix . Howeverresidues . Clearly> and <H>. It woulμH> in relation to structure / function relationships of the α-helical classes described by hydrophobic moment plot methodology with common examples including: surface active α-helices, transmembrane α-helices and oblique orientated α-helices [α-helical classes have differing optima for θ and window length, not only does this question the validity of results obtained in these studies but also questions the validity of α-helix classification according to hydrophobic moment plot methodology. In this paper we examine the criteria upon which the methodology is based and, in view of their medical relevance, we use transmembrane α-helices as a test data set. These α-helices possess central regions, which are predominantly formed by hydrophobic residues and interact with the membrane lipid core, and end regions, which are primarily formed by hydrophilic residues and reside in the membrane surface regions [α-helices of our data set, we analyse the relationships for the mean hydrophobic moment and window size, angular frequency and the robustness to varying angular frequency. Correlations between the mean hydrophobic moment and mean hydrophobicity of transmembrane α-helices are established, verified and analysed to appraise biological function using resampling Bootstrap and Monte Carlo techniques [A number of studies have considered the significance of <-helices -10. Howe regions . For thechniques ,12.μH>, and its corresponding mean hydrophobicity, <H>, were determined and used to generate the hydrophobic moment plot shown in figure L = 11) introduced by Eisenberg et al., [et al., [H> values less than 0.5 and would not be classified as transmembrane α-helices according to the hydrophobic moment plot taxonomy of Eisenberg et al., [α-helices.A data set of 84 transmembrane proteins were identified within Swiss-Prot and used to generate a set of 403 transmembrane sequences see . All seq[et al.,  but as p[et al.,  there arL ≤ 20) were employed. The values for <μH> and corresponding <H> were plotted as above and the results for window sizes of 7, 9, 16 and 20 are shown in figure μH> and <H> for smaller window sizes but that the level of correlation appears to reduce as window size increases. The sample correlation coefficients for the various window sizes are given in table θ = 100° are shown in table L ≤ 20).The above analysis was repeated except that window sizes varying in the range 7 ≤ L ≤ 0 were emθ = 100° are presented in figure μH> and <H> and if this reflects a biological property of transmembrane sequences, it could be of use in the analysis and prediction of these motifs. It is known that angular frequency for a transmembrane α-helix varies between 95° and 107° [et al., [L ≤ 21) residues, to accommodate the findings of Cornette et al., [θ was therefore varied from 95° to 108° in increments of 1°. Once the optimal window had been obtained, to observe the discriminating effect of θ on <μH>, the <μH> values, denoted by Σ<μH>, were summed for the 403 sequences for each θ. Figure θ, based on the maximum values of Σ<μH> for each window length. It can be seen that as the window size increases the total <μH> reduces approximately linearly until the intermediate size of eleven residues in length. For subsequent larger window sizes, we observe a further near linear reduction trend but at a reduced rate. The optimal angular frequency corresponding to each window size (7 ≤ L ≤ 21) is also given in figure μH>, the window size, L, and the angular frequency, θ, is finally depicted in figure The results of this investigation for and 107° , rather [et al., . For eac et al., , the fixμH> to this fixed angular frequency assumption, and thus, the accuracy of the hydrophobic moment plot analysis for candidate transmembrane sequences, Monte Carlo simulation studies were conducted. Initially, the angular frequency, θ, was assumed to have a mean value, E(θ), fixed at 100° and the angle for each successive residue varied about E(θ). The random variation, X, followed a Normal distribution and six separate simulations were undertaken with X~N, where the standard deviation, σ, was set at 0.1°, 0.3°, 0.5°, 0.7°, 0.9° and 1.1° respectively for each. The process was repeated with the mean value being set at the identified optimal angular frequency for the window size, again, for each of the window sizes in the range (7 ≤ L ≤ 20).To assess the robustness of <θ) = 100° for each window size in the range (7 ≤ L ≤ 21) residues and for the separate standard deviation values, σ = 0.1°, 0.3°, 0.5°, 0.7°, 0.9°, 1.1°. These were compared visually with the original plots obtained under the fixed angular frequency assumption (θ = 100°). In all cases, the bulk properties of the plots were similar irrespective of the level of dispersion introduced by the different values of the standard deviation. The hydrophobic moment plot for L = 15; θ = 100° is provided in figure L = 15; E(θ) = 100°, σ = 0.1°, σ = 0.7° and σ = 1.1°, also present in figure μH> is robust to slight random perturbations about a fixed value. These properties were also observed for the simulation study with the fixed angular frequency assumption being violated about the optimum frequency for each of the window sizes in the range (7 ≤ L ≤ 20) and for each corresponding level of dispersion.Hydrophobic moment plots for variable angular frequency were obtained for E(he range  ≤ L ≤ 21he range  ≤ L ≤ 21L ≤ 20) under the fixed angular frequency assumption of θ = 100°. The calculated sample correlation coefficients were also compared to the point estimates for the original data. In all cases, the values were within the appropriate confidence intervals and were always close to the original sample correlation coefficient values, again providing evidence that <μH> is robust to random variation in angular frequency. The results of this investigation are given in table A more rigorous assessment of the variation was provided by analysis of the sample correlations. These were calculated in each case and compared to the empirically derived 99% confidence intervals established for window sizes in the range  for window sizes (7 ≤ L ≤ 20). There is an obvious damped oscillation present, which can be seen to correspond to the assumed intrinsic periodicity of α-helical secondary structure i.e. 3.6 residues per turn. Figure α-helices in general, is no more than a representative average with a value nearer 102° providing a maximum for an optimum L = 11 residue window in a transmembrane α-helical sequence.It can be seen from figure μH> declines in a near linear fashion with increasing window size with the optimum L = 11 residue window appearing to provide approximately average discrimination for transmembrane α-helices. The bootstrap derived 99% confidence intervals for the correlation coefficients between <μH> and <H> for window sizes in the range (7 ≤ L ≤ 20) showed that there are highly significant linear associations for the smaller window sizes in the range (7 ≤ L ≤ 16). As the magnitude of each of the corresponding sample coefficients is small  and confirmed as transmembrane by extensive analysis of the literature. The sequences were analysed for homology using the sequence alignment program BLAST  [α-helical sequences, each of 21 residues, was established using the algorithm, Top Pred2 .The primary structures of 96 transmembrane proteins were selected from the Swiss-Prot data bank (ch tool)  and twelp Pred2 . In each case, the value of θ, which maximises <μH>, i.e. the value of θ which produces <μH>, was determined and is referred to as the optimal angular frequency for that window size. These procedures were based on previously published work, which identified variations in θ for α-helices [For window sizes ranging from 7 to 20 amino acid residues <-helices .μH> versus <H> (hydrophobic moment plots) with θ = 100° were obtained. The corresponding sample correlation coefficients were calculated to identify the effect of window size on the relationship between these variates and hence on their ability to act as discriminators in the prediction of transmembrane α-helices. In addition, for each window size in the range (7 ≤ L ≤ 20) residues and for θ in the range (95° ≤ θ ≤ 108°), the response surface diagram for <μH> was constructed.For window sizes ranging from 7 to 20 amino acid residues, scatterplots of <μH> and <H> for both cases where window size was varied for a fixed value of the angular frequency, and the angular frequency was varied for a fixed window size. The resulting mean hydrophobicity measures were checked for bivariate Normality and non-parametric bootstrap procedures [Statistical confidence intervals were established for the Pearson (Product-Moment) Correlation Coefficient between <ocedures  were useocedures .To provide evidence of the statistical significance of any linear association, the bootstrap bias-corrected and accelerated technique (BCa)  and an aμH> to the fix angular frequency assumption, e.g., θ = 100°, θ was varied randomly about 100° and <μH> was calculated for each of the optimal windows for window sizes (7 ≤ L ≤ 20) for the 403 transmembrane proteins. These calculations were also obtained for similar random variations about the observed optimum angular frequencies, again, for the various window sizes (7 ≤ L ≤ 20). In all cases, it is assumed that the variation follows a Normal distribution with the mean value set at the desired value for θ and with the standard deviation, σ, set at: 0.1°, 0.3°, 0.5°, 0.7°, 0.9° and 1.1° respectively for six separate Monte Carlo simulation studies. The sample correlation coefficients for each simulation were calculated and compared to the empirically derived 99% confidence intervals for the corresponding population values and, in particular, with the point estimates for the original sequences.To assess the robustness of <μH> and <H> for the α-helix forming sequences of our data set are likely to be causal or merely an artefact of amino acid composition. To investigate these possibilities, two additional simulation studies were undertaken. The first looked at spatial arrangements of residues within the primary sequences and the second focused on the effect of amino acid composition on correlations between <μH> and <H>.Given that these data are from an observational study, it is necessary to assess whether any linear associations between <μH> was used to generate a random arrangement.To assess if positional or sequential correlational properties existed for the amino acids within the sequences, the sequence of residues for each of the optimum windows was re-ordered randomly. Artificial sequences were thus generated by random rearrangement or randomisation  of the pμH> and <H> were dependent on sequence composition and not on spatial or sequential correlation, an additional parametric bootstrap simulation study was conducted. Here 403 artificial sequences were created. Each was randomly generated where, for each position, selection was based on the relative abundance of all the residues for the complete 403 optimum windows.To further investigate whether correlations between <μH> and <H> from these newly created sequences were calculated, the associated hydrophobic moment plots obtained and sample correlations calculated. These were inspected to assess whether any linear associations for the original transmembrane data were thus likely to be causal or merely artefactual and whether, from inspection of variation, there was evidence of increased organisation, which could be interpreted as an indication of biological function.In both cases the corresponding <Transmembrane sequence data setClick here for file


The cells were found to differentially partition formaldehyde among the three modules depending on the flux of methanol into the cell. A dynamic mathematical model demonstrated that the kinetic constants of the enzymes involved are sufficient to account for this phenomenon. We demonstrate the role of redundancy in formaldehyde metabolism and have uncovered a new paradigm for coping with toxic, high-flux metabolic intermediates: a dynamic, interconnected metabolic loop.Genome-scale analysis of predicted metabolic pathways has revealed the common occurrence of apparent redundancy for specific functional units, or metabolic modules. In many cases, mutation analysis does not resolve function, and instead, direct experimental analysis of metabolic flux under changing conditions is necessary. In order to use genome sequences to build models of cellular function, it is important to define function for such apparently redundant systems. Here we describe direct flux measurements to determine the role of redundancy in three modules involved in formaldehyde assimilation and dissimilation in a bacterium growing on methanol. A combination of deuterium and  By feeding bacteria methanol labeled with deuterium, the relative contributions of two distinct pathways of formaldehyde metabolism have been demonstrated The availability of large numbers of genome sequences has facilitated metabolic reconstruction based on predicted gene function, in essence, a prediction of the metabolic blueprint of a cell. Such metabolic reconstructions ,2,3 can 1) compounds, or methylotrophy /[+2] of 0.065 ± 0.006). Therefore, although both methylene-H4F production routes operated under both physiological conditions, a significant shift in the ratio of the two routes occurred, up to 100-fold.When labeled with CD1 units into assimilatory metabolism during transitions to and from methylotrophic growth, metabolic shift experiments were performed. One hour after samples were removed from succinate- and methanol-grown cultures for the labeling experiments described above, the remaining portions of the two cultures were harvested, washed, and resuspended into medium containing the other substrate . At four intervals during the transition to each of the new growth substrates  calculated using the concurrent CD3OD and 14C-methanol labeling methods are reported in The relative ratio of the routes provides only one of the parameters needed to understand the metabolic dynamics during this transition; the quantitative flux is also necessary. These values were obtained with labeling . Methanone cycle . The ten4MPT module (flux B), and only a small amount flowed through the direct route (flux F). Of formate made from the H4MPT module (flux B), most (up to 88%) was converted to CO2 via formate oxidation (flux C), and a smaller amount (at least 12%) flowed through the H4F module and into assimilation (flux E), representing at least 90% of the assimilatory carbon. In contrast, for methanol-grown cells (4MPT module (flux B), with up to 30% handled by the direct route (flux F). Only a small portion of the assimilatory carbon (suggested to be about 6%) flowed through the H4F module (flux E), which represented about 3% of the formate generated via the H4MPT module. The remainder of the formate was oxidized to CO2 (flux C). These data indicate that, although the relative contribution of the long route to methylene-H4F formation decreased during the transition to growth on methanol  increases significantly during the transition to growth on methanol. These results confirm the hypothesis of net reductive flux through this module [4F generated during growth on methanol. Therefore, it seemed possible that the H4F module might be required during transitions in and out of methylotrophy, but might not be required for continuous growth on methanol. Given the available genetic techniques, two strategies were employed in an attempt to obtain mutants in one of the key H4F module genes, formate-H4F ligase, during growth on C1 compounds. First, attempts were made to obtain null mutants via allelic exchange with cultures maintained on methanol or methylamine, but these efforts were unsuccessful. Second, cultures of the ΔftfL::kan mutant CM216K.1 [4F module plays an essential role in methylotrophy even after cells have already begun to grow on C1 compounds.The combination of CDs module ,16,17. HCM216K.1  bearing CM216K.1  were groM. extorquens AM1, three interconnected metabolic modules are present, involved in two roles: converting formaldehyde to the key assimilatory intermediate methylene H4F and net oxidation of formaldehyde to CO2. Understanding paradigms for differential roles of redundant modules is central to enabling broadscale metabolic reconstruction from genome sequences. In addition, methylotrophy represents an intriguing example of a metabolic mode in which growth depends on high flux of a toxic metabolite, with subsequent partitioning of that metabolite. Other such modes are known that produce toxic aldehydes, for instance, growth on ethanolamine [In the formaldehyde metabolism of nolamine  and othenolamine . Numerounolamine  and mononolamine . In addinolamine . However14C and deuterium label-tracing strategies, we have defined flux through each metabolic module in methylotrophic metabolism in M. extorquens AM1 during transitions into and out of methylotrophy, in which the flux of formaldehyde into the system changed by a factor of 10. These methods had the dual advantages of possessing sufficient sensitivity to detect flux under all conditions tested, and being free from the requirement of steady-state growth conditions, which allowed the dynamics of growth transitions to be examined. Furthermore, this approach complements a recently developed 13C-labeling method that measures flux through the multicarbon branches of central metabolism [1 fluxes measured here. The approach described here allowed us to test and confirm the hypothesis that the role of the H4F module during growth on C1 compounds is to supply methylene-H4F from formate [Through a combination of tabolism , but is  formate ,16,17, a4F module during growth on methanol, why is this module required under this condition? The results presented here suggest that this requirement is not alleviated even when cells begin to actively grow on methanol. It is possible that this module generates an inducing signal for the serine cycle and, therefore, is necessary to maintain assimilatory flux during growth on methanol. This hypothesis is consistent with the genetic circuit, as two of the genes encoding key enzymes of the H4F module (mtdA and fch) are in an operon with serine-cycle genes and are under the control of a single regulatory protein, QscR [Given the small percentage of total flux into assimilation via the Hin, QscR .M. extorquens AM1 encounters methanol, the methanol oxidation system is at low but significant activity [2 via the H4MPT module and formate dehydrogenase, generating NAD(P)H. Only a trace amount is assimilated, almost all of that through the long route involving formate and H4F intermediates. As the flux of formaldehyde into the system increases, a greater percentage begins to flow through the direct route into assimilatory metabolism. A smooth transition occurs during the induction of the capacity in the system until approximately one-third of the total formaldehyde flows through this route, and assimilatory and dissimilatory metabolism are balanced for rapid growth on methanol  rise above the equilibrium concentration, or utilization of methylene-H4F is sufficient to keep the pool of this metabolite below the equilibrium concentration. At this time, it is not technically feasible to measure the intracellular concentrations of free formaldehyde or methylene-H4F. However, the most likely explanation for high flux through the nonenzymatic condensation of formaldehyde and H4F would be draw-off of the product (methylene-H4F) by the serine cycle. In order to test whether the known kinetic parameters explain the relative utilization of the two methylene-H4F production routes, a kinetic model was constructed and utilized to simulate formaldehyde partitioning during transitions to and from methylotrophic growth. The ability of the model to recapitulate the observed switch in route utilization  was generated using the allelic exchange technique described previously [Wild-type uens AM1  and mutauens AM1  containieviously .3OD  to a final concentration of 1 mM was added to washed cultures that had been resuspended to an OD600 = 1 in order to label cell metabolites with deuterium for analysis by GC–MS. After shaking for 20 s at room temperature the 2-ml suspension was added to three volumes of boiling 100% ethanol for instant lysis. Following centrifugation, the soluble fraction was dried, resuspended in distilled H2O, and centrifuged again to remove H2O-insoluble components. The resulting H2O-soluble small molecule fraction was then derivatized with ethyl chloroformate and trifluoroacetic acid as previously described [CDescribed ,23. All −1 to 130 °C, 4 °C min−1 to 155 °C, and then 120 °C min−1 to a final temperature of 300 °C that was held for 5 min. Flow through the column was held constant at 1 ml min−1. The injection volume was 1 μl and the machine was run in splitless mode. The temperature of the inlet was 230 °C, the interface temperature was 270 °C, and the quadrupole temperature was 150 °C. The column utilized was an HP-5MS (Hewlett-Packard).GC–MS experiments were performed using an Agilent 6890 gas chromatograph/Agilent 5973 quadrupole mass selective detector (electron impact ionization) operated at 70 eV equipped with an Agilent 7683 autosampler/injector . The MS was operated in selected ion monitoring mode to detect M/z = 156/157/158/228/229/230 from 7 min to the end of the method. The GC oven temperature started at an initial temperature of 60 °C, ramping at 20 °C min10H14O6NF3) that have lost one or both of the carboxyl ethyl esters. The data were corrected for the natural abundance of heavy isotopes in the derivatized serine fragments, using proportions calculated with Isoform 1.02 . For each sample, the ratio of Δ + 1)/Δ + 2) was calculated for both mass clusters and averaged. The mean and standard error for these data were then calculated for the three replicates of each experiment.GC–MS data were analyzed using Agilent Enhanced ChemStation G1701CA (Hewlett-Packard). The two mass clusters for serine, M/z = 156/157/158, and 228/229/230, represent fragments of ECF–TFAA derivatized serine  was forced to be the same on succinate as on methanol, since this is a fundamental chemical property that is not affected by gene induction. All reverse rate constants were calculated directly from the forward constants, binding constants, and Keq. The spontaneous condensation of formaldehyde with H4MPT was assumed to be negligible under physiological conditions compared to the formaldehyde activating enzyme reaction [The dynamic model of the formaldehyde oxidation and assimilation modules consisted of eight ordinary differential equations, each describing the accumulation of a metabolite involved in the Hterature . In caseectively . Concenthia coli . The parture see , except reaction . All simreaction .Abbreviations as in http://www.ncbi.nlm.nih.gov/Genbank) accession numbers for genes discussed in this paper are dmrA (AY093431), ftfL (AY279316), and glyA (L33463).The GenBank (


The phenomenon of switch-like response to graded input signal is the theme involved in various signaling pathways in living systems. Positive feedback loops or double negative feedback loops embedded with nonlinearity exhibit these switch-like bistable responses. Such feedback regulations exist in insulin signaling pathway as well.In the current manuscript, a steady state analysis of the metabolic insulin-signaling pathway is presented. The threshold concentration of insulin required for glucose transporter GLUT4 translocation was studied with variation in system parameters and component concentrations. The dose response curves of GLUT4 translocation at various concentration of insulin obtained by steady state analysis were quantified in-terms of half saturation constant.We show that, insulin-stimulated GLUT4 translocation can operate as a bistable switch, which ensures that GLUT4 settles between two discrete, but mutually exclusive stable steady states. The threshold concentration of insulin required for GLUT4 translocation changes with variation in system parameters and component concentrations, thus providing insights into possible pathological conditions.A steady state analysis indicates that negative feedback regulation of phosphatase PTP1B by Akt elicits bistability in insulin-stimulated GLUT4 translocation. The threshold concentration of insulin required for GLUT4 translocation and the corresponding bistable response at different system parameters and component concentrations was compared with reported experimental observations on specific defects in regulation of the system. In living systems, extracellular information is processed through signal transduction machinery to appropriately regulate cellular function. This information processing machinery is made up of a complex web of enzyme cascades, allosteric interactions and feedback loops. Depending on their regulatory design these signaling networks elicit diverse responses, but display many common operating principles. A recurring theme in signaling systems is switch-like responses to graded or transient input signal. Various mechanisms are known to generate such all-or-none responses . BistabiInsulin is the most potent anabolic peptide hormone known that elicits myriad biological responses by specifically binding to insulin receptor and simultaneously stimulating multiple signaling pathways to regulate growth, differentiation and metabolism. Insulin maintains glucose homeostasis by stimulating the uptake, utilization and storage of glucose in muscle and adipose tissue, and inhibits hepatic glucose production . DefectsA wide family of glucose-transporter proteins localized in the plasma membrane, facilitate uptake of glucose from the blood into tissues. Among different isoforms, only glucose transporter isoform-4 (GLUT4) is specifically expressed to promote glucose uptake in insulin sensitive tissues, viz. muscle and adipose, and in response to insulin, GLUT4 gets translocated to the plasma membrane from intracellular vesicles . The bioAlthough studies on various cell lines, transgenic and knock-out mice, have helped to uncover and characterize the different components involved in insulin signaling pathway, there are many voids in our understanding of the precise molecular mechanisms of signal transduction and cellular effects of insulin ,17. The In the present work, we have developed a steady state model of insulin signaling to generate dose response curves for fractional translocation of GLUT4 to varying input insulin stimuli. One of the main objectives was to investigate the effect of inherent signaling structure made up of phosphorylation cycles, allosteric interactions and feedback loops on the system level response of insulin on GLUT4 translocation. Furthermore, we were interested in examining whether the regulatory design consisting of positive feedback loops in insulin signaling pathway exhibits bistable response. We solved the steady state equations for the entire metabolic insulin pathway including the positive feedback loops numerically, and found that GLUT4 gets translocated to the plasma membrane in an all-or-none manner in response to a varying concentration of input insulin stimuli. We show that GLUT4 translocation switches between the on-state and off-state and exhibits hysteresis in its response to increasing and decreasing input insulin concentration. This input-output relationship was then studied at various concentration of signaling components and system parameters in order to monitor the range over which this response persisted. We discuss these results by comparing with the known specific defects in regulation of the system (insulin dependent diseases) that lead to improper glucose uptake into the cell.Figure Insulin initiates its biological action by interacting with the insulin receptor, which belongs to a superfamily of tyrosine kinase receptors. On binding to the first insulin molecule, the receptor gets auto-phosphorylated and is dephosphorylated by phosphatase PTP1B . The phop is rate constant and Kmr is Michaelis-Menten constant for dephosphorylation of internalized insulin receptors XIPi and XI2Pi. The term kd is first order degradation rate constant and ks is zero order synthesis rate constant of intracellular receptor Xi. The receptor exocytosis and endocytosis are assumed to be at quasi-equilibrium because of their faster time scales than the synthesis and degradation of receptors ] is equal to 0.75. In absence of feedback effects, PTPt equals PTPmax.where, [PTP]tal AktP . Thus, kThe set of equations given in 'appendix' and in 'methods' section were solved numerically using fsolve program of Matlab (The MathWorks Inc. USA). The accuracy of the simulation was verified by numerically checking the mass balance of all species. The steady state modeling of entire insulin signaling was evaluated including the feedback loops and estimating the fractions of GLUT4 translocated to the plasma membrane for a particular concentration of insulin. Thus, the overall action of insulin on GLUT4 translocation is quantified as,f is fractional GLUT4 on plasma membrane, GM is GLUT4 concentration on plasma membrane and Gt is total GLUT4 concentration with respect to whole cell volume.where, 0.5, insulin concentration required for 50% of GLUT4 to reside on the plasma membrane). This represents two threshold concentrations of insulin required for GLUT4 translocation switching on (GLUT4 translocation to plasma membrane at 0.05 nM) and switching off (GLUT4 translocation from to plasma membrane at 0.01 nM).Fig. The observed hysteresis is characteristic of a bistable response obtained due to negative feedback regulation of upstream signal attenuation enzyme PTP1B by downstream kinase Akt. Experimental data available in the literature indicates a subsensitive response of insulin, requiring ~130 fold change in insulin concentration for the maximal GLUT4 translocation to plasma membrane . Our resTo examine the influence of pathological conditions arising due to variations in protein expression levels on final output response of insulin, we varied the concentration of individual signaling components IRS-1, PI3K, lipids, PKC-ζ, Akt and phosphatases, PTP1B, PTEN and SHIP2 over a wide range. For each case, the dose response curve of fractional GLUT4 on the plasma membrane at various insulin concentrations was obtained and the response was quantified in-terms of half saturation constant. To illustrate this, we consider a case of increase in PTP1B concentration. Fig. Fig. To study the effect of signal attenuation enzymes such as phosphatases on the output response, the concentrations of PTP1B, PTEN and SHIP2 were altered over a wide range, keeping other parameters constant. Fig. The feedback effect of active Akt on PTP1B was studied by increasing the Akt concentration Fig.  and by cThe steady state analysis of metabolic insulin-signaling pathway demonstrated signal amplification as signal propagates down the cascades. The amount of insulin required for 50% activation of insulin receptor, IRS-1, PIP3, Akt, PKC-ζ and GLUT4 was estimated to decrease in presence or absence of feedback loops (results not shown).In addition to genetic variation at the protein expression levels in diseased conditions, mutational changes can also alter the system parameters and thereby modify the final output response. To examine the influence of system parameter values on insulin-stimulated GLUT4 translocation, we have analyzed the performance of insulin signaling pathway to variations in key parameter values such as, dissociation constant and Michaelis-Menten constant. Increase in dissociation constant quantifying the interaction between insulin-receptor and phosphorylated IRS-1-PI3K shows an increase in the half saturation constant indicating higher requirement of insulin over the physiological concentration Fig.  and 6B. In this work we have demonstrated that, the dose response curves of fractional GLUT4 concentration on plasma membrane at various concentration of insulin exhibit hysteresis-a property of bistable systems. The analysis of bistable response in presence of feedback loops was done at varying concentration of signaling components and system parameters in physiological range. The overall response of insulin demonstrated signal amplification as the signal propagates down the cascade, thus requiring less insulin for GLUT4 translocation. The insulin sensitivity increased by increasing the concentration of proteins that amplify the insulin action and decreasing the concentration of proteins that attenuate insulin-signaling pathway. This indicates that the bistability and the half saturation constant are dependent on the component concentrations and system parameters.i) Decreased concentration of phosphorylated insulin receptor and IRS-1 are observed in muscle from morbidly obese subjects Xt = X + Xi + XI + XIP + XI2P + XIPi + XI2Pi + PTP.XIP + A.XI2P + PTP.XIPi + PTP.XI2Pi     [A2]At = A + AP + APB + A.XI2P + PTP.AP + APB.CP2     [A3]CP2t = CP2 + CP3 + CP2' + APB.CP2 + PTEN.CP3 + SHIP2.CP3 + SHIP2.CP3 + E6.CP2' + F.CP3     [A4]Ft = F + FP +CP3F + E8.FP     [A5]SHIP2t = SHIP2 + SHIP2.CP3     [A6]PTENt = PTEN + PTEN.CP3     [A7]PTPt = PTP + PTP.XIP + PTP.AP + PTP.XIPi + PTP.XI2Pi     [A8]Bt = B + APB + CP2.APB     [A9]Et 6= E6 + E6.CP2'     [A10]Et 8= E8 + E8.FP     [A11]Gt = GM + GC     [A12]Equilibrium relationshipsRate expression with pseudo-steady state representation of complexes for modification-demodification cyclesReceptor autophosphorylation and dephosphorylation cycleIRS-1 phosphorylation and dephosphorylation cyclePhosphorylation and Dephosphorylation of PI-4,5-P2, PI-3,4-P2 and PIP3Phosphorylation and Dephosphorylation of Akt + PKC


Over the course of evolution, some organisms have gained many genes and become increasingly complex whereas other, simpler, organisms have survived with comparatively fewer genes.  But where do these “new” genes come from? Evolutionary biologists have long known that duplication of existing genes is an important source of genetic novelty—it is easier to copy and modify an existing gene than to create a completely new one from scratch.Because gene duplication makes such a major contribution to evolution, researchers have attempted to understand the mechanisms of gene duplication, how genes evolve once they become duplicated, and what functional effect gene duplications have for the organism. Recent genomic studies, for example, appear to show that most duplicated genes go through a period of accelerated evolution and also that the presence of duplicated genes adds robustness to the functioning of genomes. In research published in this issue, however, Jerel Davis and Dmitri Petrov look at gene duplication from a different perspective. Rather than asking how genes are duplicated, they asked which genes tend to be “good” at duplicating over the course of evolution. The answer is important for our understanding of the forces underlying gene duplication and will also help us understand why genomes contain duplicates of some genes and not others.Saccharomyces cerevisiae and the worm Caenorhabditis elegans, two model organisms whose genomes have been sequenced. They then looked for the corresponding genes in two distantly related species, the fruitfly and the mosquito, in order to obtain an independent measure of evolutionary rate. This independent measure is vital because of the likelihood that gene duplication itself influences the rate of evolution. After obtaining these rates, the researchers compared the evolutionary rates of duplicated and nonduplicated genes.The authors began by identifying duplicated and nonduplicated gene pairs in the yeast Stated simply, the authors found that slowly evolving  genes are more successful at generating duplicates than faster evolving genes. This is no recent trend—more conserved genes have been better at generating duplicates of themselves consistently over hundreds of million of years.This research challenges the assumption that genes are duplicated in an unbiased manner. In addition, it provides the essential background for other genomic studies of gene duplication. For example, the acceleration of protein evolution upon duplication is likely to be even more dramatic considering that it is the slowly evolving genes that duplicate preferentially.These findings also open up new questions in the study of gene duplication. The authors convincingly demonstrate the bias toward conserved genes in the process of duplication, but how and why does this happen? For a duplicated gene to be retained in a species, the duplicate must be fixed in the population and then must be preserved by natural selection. The preferential duplication of slowly evolving genes might come from a bias in either of these steps, and the authors outline several models for why this might be the case. Further analysis may enable researchers to test these and other models for gene duplication—especially as more sequence data become available—and learn more about this potent phenomenon in genome evolution.


Smoking in pregnancy is a public health problem and effective methods for reducing this are required. Although nicotine replacement therapy (NRT) is effective for smoking cessation in non-pregnant people, there is no direct evidence concerning its effectiveness in pregnancy. Despite this, clinical guidelines recommend the cautious use of NRT during pregnancy. Randomised controlled trials are needed to determine the safety and efficacy of NRT when used by pregnant women for smoking cessation, but the feasibility of recruiting women to such trials is unknown. Consequently, in this study we aimed to determine i) the feasibility of recruiting women to a RCT of NRT in pregnancy as they attend hospital antenatal ultrasound examinations, ii) the proportion of such women who are eligible for and interested in trial enrolment and iii) research staff perceptions of how one method of trial recruitment could be improved.During a one month period, all women attending for antenatal ultrasound examination in an English teaching hospital were asked to complete a questionnaire which determined their eligibility to enrol in a proposed placebo controlled randomised trial investigating the effectiveness of NRT in pregnancy. Women who were eligible to participate were asked whether they would do so and those who accepted enrolment were offered an appointment with a smoking cessation advisor.Over 99% (851/858) of women agreed to complete a questionnaire about smoking habits whilst waiting for ultrasound examinations. 10.3% (88/851) of women attending for antenatal ultrasound fitted eligibility criteria for a proposed RCT of NRT in pregnancy, but only 3.6%  indicated on the questionnaire that they would like to take part in a study involving randomisation to placebo or active patches. Researchers offered trial enrolment to 26 of these 31 women and 96% (25) accepted. Staff recruiting women believed that trial recruitment would be maximised if women attending the ultrasound department knew about trial recruitment before attending and greater staff resources were made available for this. It was also perceived that women generally under-reported the amount they smoked on questionnaires completed whilst waiting in ultrasound department areas.It is feasible to recruit women for a trial of NRT in pregnancy as they wait for antenatal ultrasound examinations. Using similar recruitment methods, researchers can expect to recruit between 24 and 49 women per 1000 approached. Smoking harms unborn children causing intra-uterine growth restriction, preterm birth, miscarriage and perinatal death ,2. DespiTwo trials conducted in pregnant women have shown NRT patches to have no greater effect on smoking cessation than placebo ,8. but nDespite uncertainties about the effects of NRT in pregnancy, there is an expert consensus that NRT use is safer than smoking  which isEthical approval was granted by the Nottingham Research Ethics Committee 2. For one month, one of three research assistants (RAs) was based in the Nottingham City Hospital antenatal ultrasound department for all scanning sessions. All women attending for ultrasound scans were approached by an RA and asked to fill in a self-completion questionnaire (see appendix) which asked their number of weeks gestation and whether or not they smoked at all. Respondents who answered that they smoked cigarettes or tobacco were then asked a series of questions about their smoking behaviour to ascertain whether or not they satisfied eligibility criteria for a proposed RCT  and the practicality of recruitment within the ultrasound clinic setting. Where staff had criticisms, they were encouraged to suggest improvements in procedures. Key points made during this meeting were noted and issues described in the results section are those on which there was consensus.We knew from routinely-collected clinic statistics that over 800 women would attend for antenatal ultrasound scans in a four week period and around 200 of these (25%) would smoke. We hypothesised that 20% of smokers (i.e. approximately 40 or 5% of clinic attenders) would agree to trial randomisation. We believed this a reasonable assumption because in a survey of women attending ante-natal clinics, Ussher found that, amongst women who smoked 10 or more cigarettes daily and who were interested in stopping smoking; 56% were also interested in using NRT . ConsequAll data was entered into an SPSS database and quantitative findings are expressed as simple proportions of all clinic attenders, with 95% CI for the principal outcome.Figure There was consensus amongst RAs and NHS smoking cessation service staff that, if the following problems with study procedures were remedied, the proportion of women interested in trial participation who actually enrolled should increase:• A number of women were interested in study participation but did not have sufficient time to discuss this with the RA in the clinic. These women might have been able to make time to discuss the study if they had known about the likelihood of being approached before attending the ultrasound department.• On occasions, RAs failed to follow up women who had expressed an interest in study participation because they were busy with other duties (e.g. discussing enrolment with another woman).• A number of women who had indicated on their questionnaire that they were interested in participation left the clinic before the RA could discuss enrolment with them. The pilot study did not have the resources to contact these women afterwards.• Some women reported heavier smoking to smoking cessation advisors than they recorded on questionnaires. This apparent under-reporting of smoking behaviour may have resulted in some women who were actually eligible for study participation, not being offered study enrolment.We have demonstrated that it is feasible to recruit women to a trial of NRT in pregnancy as they attend antenatal ultrasound appointments. Although almost all women consented to complete a questionnaire enquiring about their smoking habits, only 10% of these were eligible to enrol in an RCT and less than 4% appeared likely to participate in one.Our study provides useful, original information for researchers planning trials of NRT in pregnancy. The two published trials of NRT use in pregnancy give no information about numbers of women were asked to participate but declined. One trial took two years to enrol 250 pregnant women  and the Our findings compliment those of Ussher's survey by providing information about likely participation rates for any randomised controlled trial. Extrapolating our figure of 3.6% indicates that approximately 36 95%CI, 24 to 49) women could be recruited annually to a RCT of NRT in pregnancy from a maternity hospital with 1000 births/pregnancies each year. Researchers planning trials of NRT in pregnancy can use this recruitment rate to inform the planning of studies. Trialists should note, however, that we have measured agreement to be randomised rather than actual randomisation. Additionally, we did not measure the numbers of exclusions amongst women who were interested in participation. Figure 4 to 49 wSome modifications to the recruitment method we used might be needed to maximise trial recruitment rates. Recruitment from antenatal ultrasound waiting areas might be increased if women were sent information about the likelihood of being approached to join any trial before they attended (e.g. sending information out with appointments). Additionally, providing enough resources to ensure that a member of trial staff is always present to ask patients to join a trial is important. This would overcome the problem of missing potentially interested women when the researcher responsible for recruiting is busy enrolling other potential participants. Any recruitment method should also allow for the fact that some women who are interested in participating will not be able to wait in the clinic to discuss this further. Recruitment would, therefore, be enhanced if enough resources were provided to allow research staff to make contact with these women later, visiting them at home if necessary.The observation by smoking cessation service staff that some women admitted smoking more heavily to them than they admitted on questionnaires is consistent with the literature. Aveyard investigated the relationship between urinary cotinine levels and reported numbers of cigarettes smoked during pregnancy and concluded that, at booking, some pregnant women probably minimise the numbers of cigarettes that they report smoking . SimilarTrialists could reduce the impact that under-reporting of heaviness of smoking might have on trial recruitment by avoiding the use of questionnaires to quantify smoking habits. Questionnaires used in recruitment to trials of NRT in pregnancy might be more effective if they merely ask women to disclose whether or not they smoke and if they are interested in using NRT to stop. All who smoke and wish to stop using NRT could then be invited for further discussion of trial entry with a researcher or health professional and during this disclosure a more accurate assessment of heaviness of smoking might be obtained.We have demonstrated that it is feasible to recruit pregnant women to a trial of nicotine replacement therapy in pregnancy in the antenatal ultrasound clinics. Using similar recruitment methods between 24 and 49 pregnant women per 1000 approached are likely to consent to participation in an RCT. RCT(s) of NRT in pregnancy are required and this data will help researchers planning such trials to determine the resources required to answer important questions concerning the effectiveness and safety of NRT in pregnancy.TC has been paid for speaking at a conference by GlaxoSmithKline (GSK); he has also done consultancy work on one occasion for Pharmacia (now Pfizer). JB has been reimbursed by Glaxo Wellcome (now GSK) for attending 2 international conferences, has received a speaker honorarium from Glaxo Wellcome, has been the principal investigator in a clinical trial of nicotine replacement therapy funded by Pharmacia and has undertaken consultancy work for Novartis. All companies manufacture nicotine replacement products but none were involved in this study. All other authors have no conflicts of interest.All authors were involved in various stages of study design. MA liaised with the NHS Stop Smoking and hospital antenatal services, collected data and supervised others in this. TC wrote the paper and all authors commented on drafts and approved final text.The pre-publication history for this paper can be accessed here:


In the early 1990's, a new cell signaling pathway was described. This new paradigm, now known as the JAK/STAT pathway, has been extensively investigated in immune-type cells in response to interferons and interleukins. However, recent evidence suggests that the JAK/STAT pathway also mediates diverse cellular responses to various forms of biological stress including hypoxia/reperfusion, endotoxin, ultraviolet light, and hyperosmolarity. The current literature describing the JAK/STAT pathway's role in cellular stress responses has been reviewed herein, but it is clear that our knowledge in this area is far from complete. In multicellular organisms, every cell comprising every tissue, organ, or organ system constantly strives to maintain homeostasis in the face of destabilizing influences. Whether it is external stimuli such as toxic chemical exposure or changes in oxygen tension, or natural alterations in pH or osmolarity due to normal cellular metabolism, each cell in the body is equipped with the molecular machinery required to sense these environmental changes and respond to them. Because these stressful stimuli can impinge on normal cellular functioning, discrete cellular sensing mechanisms have evolved to maintain homeostasis. For example, ATP depletion caused by hypoxia activates AMPK which phosphorylates multiple downstream targets to switch the cell from a mainly anabolic to catabolic state . SimilarOne interesting question is how do cells translate diverse stressful stimuli into activation of specific molecular pathways? Cellular signaling from membrane to nucleus is typically accomplished through ligand/receptor activation of intracellular second messengers. In many cases these second messengers are kinases which phosphorylate substrates leading to a cascade by which successive macromolecules are triggered. Ultimately, a terminal transcription factor is activated which then translocates to the nucleus to activate specific target genes. This type of cellular signaling has been well-characterized following receptor activation by polypeptide ligands, but some forms of cellular stress such as hypoxia cause activation of specific molecular pathways in the apparent absence of ligand to receptor stimulation. Therefore, there must be alternative routes for direct activation of target genes that circumvents the canonical ligand/receptor/second messenger cascade. One such pathway that may transmit signals to the nucleus by this alternative route is the Janus Activated Kinase/Signal Transducer and Activator of Transcription family of transcription factors (JAK/STAT).The JAK/STAT pathway includes seven functionally related, latent transcription factors (STAT) and four non-receptor tyrosine kinases (JAK) [reviewed in ]. In theWhile signaling through the canonical JAK/STAT pathway has been well-characterized in immune-type cells in response to interleukins and interferons, there is emerging evidence that STATs also mediate cellular responses to various forms of cellular stress. These findings, in addition to mounting evidence suggesting that some STATs are phosphorylated on serine by members of the MAPK family, imply that alternative mechanisms for STAT activation exist. Further, these alternative means of activation may lead to different outcomes with regards to STAT signaling. For example, STAT3 was recently shown to be serine phosphorylated by JNK during UV stress which had a predominately inhibitory role on STAT3 transcriptional activity . Could tin vitro. Thus, the MAPK and STAT pathways appear to converge during periods of cellular stress. In another study, UV light caused STAT1 tyrosine phosphorylation, nuclear accumulation, and DNA binding in keratinocytes [Some of the earliest studies implicating STATs in mediating cell stress responses were performed in cells exposed to UV light. In mouse embryonic fibroblasts (MEFs), UV light treatment resulted in phosphorylation of serine 727 in STAT1 via p38 MAPK ,6. FurthCellular stress can also occur in disease states such as diabetes, which is characterized by vascular dysfunction. For example, prolonged elevated glucose can act as a cell stressor through multiple pathways including hyperosmolarity , proteinDictyostelium, hyperosmotic stress leads to STAT1 phosphorylation without any known involvement of JAK or MAPK [Hyperosmotic stress can also activate STATs. For example, in the slime mold  or MAPK . But mam or MAPK . Interes or MAPK . In thisThe most well-investigated reports linking cellular stress with the JAK/STAT pathway are studies in cardiomyocytes undergoing hypoxia/reperfusion. Like UV light, hypoxia/reperfusion led to p38 MAPK phosphorylation followed by serine 727 phosphorylation of STAT1 which was associated with activation of pro-apoptotic FAS/FASL and caspase-1 . It was In vivo models of hypoxia/reperfusion also implicate STAT5 as a player in responses to cellular stress. But unlike STAT1, STAT5 is thought to be mainly protective by activating anti-apoptotic signals. For example, Yamaura et al. report that genetic deletion of STAT6 but not the STAT5A causes resistance to myocardial ischemia/reperfusion injury [n injury . This ren injury ,26. Studn injury ,28 but in injury .Although not as well studied as hypoxia/reperfusion or osmotic stress, reactive oxygen species have also been shown to activate the JAK/STAT pathway. Oxidative stress, such as might occur in diabetes and cardiovascular disease, was shown to activate HSP70 in smooth muscle cells in a JAK-dependent manner . This reTaken together, the studies reviewed herein support a role for the JAK/STAT pathway in various forms of cellular stress and relate perturbed JAK/STAT signaling to potential disease states. However, consistent with some of the current ideas about STAT biology, it is clear that cellular stress seems to activate STATs in ways that can be both detrimental to and supportive of cell survival. For example, STAT1 activation by hypoxia-reperfusion injury activates cell death pathways, while STAT5 activation by the same type of stressor seems to promote cell survival pathways. Thus, STATs may have evolved to fulfil both sides of a "yin and yang" type mechanism where either death or survival pathways can be activated depending on the strength or type of cellular stressor . This maThe most intriguing aspect of many cellular stress-activated pathways is the apparent absence of ligand-to-receptor stimulation. But the cell must somehow "sense" changes in the external milieu and transmit these signals to the nucleus. How does it do this? Two such examples of this type of cellular sensing are activation of a well-described transcription factor known as HIF-1α (hypoxia-inducible factor), and another is the cellular thermostat called HSF (heat shock factor). In the case of HIF, enzymatic modification by an enzyme requiring oxygen as a cofactor is responsible for HIF activation and switching on of target genes when cells are stressed by low oxygen . For HSFIs it possible that STATs can also act as a cellular rheostat of various stressors? Recent suggestions that STATs can be post-translationally modified in ways other than phosphorylation  make this a possibility . For exain vivo may prove to be of therapeutic value.Finally, while our understanding of a stress-related p38/STAT1 (pSER) pathway seems to be taking shape, very few studies have investigated the role of serine phosphorylation of other STATs and what the upstream kinase (s) may be during cellular stress. Future studies might focus on identifying whether serine phosphorylation is common to other STATs during cellular stress and how this might relate to activation or inactivation of target genes. Other questions to be answered are what is the function of unphosphorylated STAT dimers found in the nucleus of unstimulated cells and how might other STAT post-translational modifications (other than phosphorylation) mediate STAT signaling beyond the canonical JAK/STAT pathways -41. Answ