To address the clinical and virological significance of a high HTLV-1 proviral load (VL) in practical blood samples from asymptomatic and symptomatic carriers, we simultaneously examined VL and clonal expansion status using polymerase chain reaction (PCR) quantification  and Southern blotting hybridization (SBH) methods.The present study disclosed extremely high VL with highly dense smears with or without oligoclonal bands in SBH. A high VL of 10% or more was observed in 16 (43.2%) of a total of 33 samples . In particular, an extremely high VL of 50% or more was limited to symptomatic carriers whose band findings always contained at least dense smears derived from polyclonally expanded cells infected with HTLV-1. Sequential samples revealed that the VL value was synchronized with the presence or absence of dense smears, and declined at the same time as disappearing dense smears. Dense smears transiently emerged at the active stage of the underlying disease. After disappearance of the smears, several clonal bands became visible and were persistently retained, explaining the process by which the clonality of HTLV-1-infected cells is established. The cases with only oligoclonal bands tended to maintain a stable VL of around 20% for a long time. Two of such cases developed ATL 4 and 3.5 years later, suggesting that a high VL with oligoclonal bands may be a predisposing risk to ATL.The main contributor to extremely high VL seems to be transient emergence of dense smears detected by the sensitivity level of SBH, corresponding to polyclonal expansion of HTLV-1-infected cells including abundant small clones. Major clones retained after disappearance of dense smears stably persist and acquire various malignant characteristics step by step. Human T-cell leukemia virus type-1 (HTLV-1) is thought to infect mainly CD4 T-cells, and to cause T-cell malignancy adult T-cell leukemia (ATL) after a long latency, a degenerative nervous disorder of HTLV-1-associated myelopathy (HAM), and so on . During Accordingly, to address what kind of clonal infected cells contribute to high VL, and clarify unusual ATL or carrier states, we simultaneously analyzed HTLV-1 proviral load and SBH status using the same blood samples. In contrast to the maintenance of stable VL in asymptomatic carriers with no-bands or only faint discrete bands, the VL in symptomatic carriers with complications unrelated HTLV-1 tended to have high VL with dense smears with/without discrete band(s), consisting of mainly polyclonal expansion and partial oligoclonal expansion of the infected cells.The median age of the 29 subjects who donated peripheral blood was 66 years old . No circulating ATL cells were found morphologically or immunophenotyically in any samples, including 8 samples of lymphoma-type ATL employed as a control. Subsequently, all 33 samples were divided into 3 groups; 13 asymptomatic healthy carriers , 12 symptomatic carriers  with complications unrelated to HTLV-1 such as infectious diseases  and immune-disorders  and 8 patients with lymphoma-type ATL. The distribution of SBH band patterns in each group is summarized in Table Although SBH in asymptomatic carriers gave no clonal band with or without very faint Smears, SBH in some symptomatic carriers gave characteristic band patterns, as shown in Figure Clinico-hematological features in 15 cases with a high VL of 10% or more and distinctive band patterns are summarized in Additional file Recent studies including our previous studies ,15 suggeIn the present study, we found that the results of VL and SBH status in healthy carriers were the same as those of the past reports, while there was an extremely high VL with a characteristic band status of high dense smears with or without clonal bands in elderly symptomatic carriers. A VL of 10% or more  was detected in 16 (43.5%) of all samples, 1 (6.3%)/16 asymptomatic healthy carriers, 8 (61.5%)/13 symptomatic carriers unrelated to HTLV-1 and 7(87.5%)/8 patients with lymphoma-type ATL without circulating ATL cells. On the other hand, in SBH analysis, no visible aberrant bands were detectable in low VL samples with less than 10%. All but one of the asymptomatic carriers  were of this pattern. In contrast, the high VL samples with 10% or more displayed distinctive band patterns accompanied by dense smears with or without discrete clonal band(s), indicating that an increase in polyclonally infected-cells corresponding to dense smears contributed to a high VL. As triggering factors for HTLV-1-infected cells, various microbes and abnormal immunity due to aging in symptomatic carriers were suspected. Furthermore, the observations from sequential samples also support the contribution of dense smears to the elevation of VL. This helps explain the process by which the clonality of HTLV-1-infected cells is established after the disappearance of dense smears.It is now recognized that clonal expansion of HTLV-1-infected cells is the norm in nonmalignant disease . In the Taken together, our study supports the idea that extremely high VL mainly results from polyclonal expansion of HTLV-1 infected cells at the sensitive level of SBH.In samples from patients with lymphoma-type ATL without ATL cells, a clonal band(s) was demonstrated in 4 of the 8 patients. Band size between blood and lymph nodes was the same in two of the 4 cases, but no circulating ATL was found. Other aberrant bands, as summarized in Additional file Focusing on not only discrete clonal band(s), but also aberrant smears, it is noteworthy that the emergence of dense smears equivalent to polyclonal expansion of infected cells mainly contributed to a high level VL. However, it is reasonable that a high VL does not consist of only polyclonally expanded infected cells, but included abundant small clones in the cell population, because of sensitivity in SBH. SBH for HTLV-1 could evaluate or monitor the clinical clonal status of HTLV-1-infected cells. Clinically, the distinctive profile of high VL and aberrant band status is expected to monitor or predict some events caused by HTLV-1.Samples were collected from our ATL clinical laboratory, consisting of 16 asymptomatic and 13 symptomatic carriers and 8 patients with lymphoma-type ATL as a control because this type of ATL has no circulating ATL cells. A total of 37 samples were seropositive for HTLV-1 and undetectable morphologically and immunophenotypically for ATL cells, indicating all samples had no evidence of circulating ATL cells.Anti-HTLV-1 antibodies were detected by chemiluminescent enzyme immunoassay . High-molecular-weight DNA was extracted from blood mononuclear cells (MNCs) using a QIAmp DNA Blood Mini kit . VL was quantified by LightCycler Technology  using hydro-probes and previously described primers , with β-EcoR1 and Pst-1. There are four Pst-1 sites but no EcoR1 site within the proviral sequence. Accordingly, if EcoR1-digestion gave no-band or faint smears and Pst-1-digestion gave only three internal bands, the sample was considered to be negative for clonal expansion. When discernible discrete band(s) in the EcoR1-digestion membrane or one or two external band(s) in addition to three internal bands in the Pst-1-digestion membrane were visible, the sample was considered to harbor clonal integrated provirus, implying that the infected cells had expanded clonally. The results of SBH analysis were classified into three patterns; no-band, dense smears and one or more discrete band(s). "Dense" smears were assumed to be distinct from those of common carriers (3 fold< smear density relative to background lane densitiy). The detection sensitivity for clonally infected cells in the SBH assay was 3-5% [SBH analysis was performed as described previously ,19, usinwas 3-5% . The senData were analyzed using Mann-Whitney or Chi-squared tests. Statistical significance was set at p < 0.05.HTLV-1: human T-cell leukemia virus type-1; ATL: adult T-cell Leukemia; VL: HTLV-1 proviral load; SBH: Southern blot hybridization; PCR: polymerase chain reaction.The authors declare that they have no competing interests.SK, DS, and TW conceived this study and provided funding. DS, HH, KY, YY and KT collected samples and carried out the molecular genetic studies. MI, TW, AO and SK analyzed the data and discussed the results. SK organized the study and wrote the manuscript. All authors read and approved the final manuscript.Summary of the main clinical and laboratory data in seropsitive individuals with high VL and aberrant band patterns in SBH, and outcome in Dec 2008. Two cases (#3 and 5) among 8 advanced carriers (cases 1 to 8) developed ATL 4 and 3 years later. Cases 1, 2 and 15: High VL carriers with polyclonal expansion. Cases 3-14; aberrant bands mainly with faint multiple clonal bands, Final diagnosis was based on the integrated findings of an LN SBH test and clinico-pathological examinations. ALCL; anaplastic large cell lymphoma, DLBCL; diffuse large cell B-cell lymphoma, (-) or (+); negative or positive clonal band, S; smear, B; band, NT: not tested, Dx: diagnosis, *: indeterminate for clonal band, **: pathological diagnosis was indeterminate. For the other abbreviations; refer to the context.Click here for file


Fertility is one of the most critical factors controlling biological and financial performance of animal production systems and genetic improvement of lines. The objective of this study was to identify molecular defects in the sperm that are responsible for uncompensable fertility in Holstein bulls. We performed a comprehensive genome wide analysis of single nucleotide polymorphisms (SNP) for bull fertility followed by a second-stage replication in additional bulls for a restricted set of markers.In the Phase I association study, we genotyped the genomic sperm DNA of 10 low-fertility and 10 high-fertility bulls using Bovine SNP Gene Chips containing approximately 10,000 random SNP markers. In these animals, 8,207 markers were found to be polymorphic, 97 of which were significantly associated with fertility (p < 0.01). In the Phase II study, we tested the four most significant SNP from the Phase I study in 101 low-fertility and 100 high-fertility bulls, with two SNPs (rs29024867 and rs41257187) significantly replicated. Rs29024867 corresponds to a nucleotide change of C → G 2,190 bp 3' of the collagen type I alpha 2 gene on chromosome 4, while the rs41257187 (C → T) is in the coding region of integrin beta 5 gene on chromosome 1. The SNP rs41257187 induces a synonymous (Proline → Proline), suggesting disequilibrium with the true causative locus (i), but we found that the incubation of bull spermatozoa with integrin beta 5 antibodies significantly decreased the ability to fertilize oocytes. Our findings suggest that the bovine sperm integrin beta 5 protein plays a role during fertilization and could serve as a positional or functional marker of bull fertility.We have identified molecular markers associated with bull fertility and established that at least one of the genes harboring such variation has a role in fertility. The findings are important in understanding mechanisms of uncompensatory infertility in bulls, and in other male mammals. The findings set the stage for more hypothesis-driven research aimed at discovering the role of variation in the genome that affect fertility and that can be used to identify molecular mechanisms of development. Fertilization is a critical event at the onset of mammalian development. The widespread use of artificial insemination has revealed great variation in fertility among sires . Some maUncompensable infertility defects may result from molecular defects caused by abnormalities in spermatozoal DNA, RNA, or proteins, which impair the ability of spermatozoa to interact with oocytes and induce embryonic development -6. The qRecent advances in animal genome sequencing and associated technologies are providing new insights into the genomics study of gametes and embryos -14. For The objective of the present study was to use a high-throughput and a high-density SNP array to conduct a near-genome-wide association study of bull fertility. Spermatozoa DNA were isolated from well-characterized low fertility (n = 10) and high fertility (n = 10) bulls (Phase I study) and examined for approximately 10,000 SNPs, followed by the screening of the four most significant SNPs in a larger population .® program) involving approximately 180 farms milking an average of 850 cows each was used to select the bulls . This program provides certain benefits, including DNA verification of the paternity of offspring and pregnancy diagnoses by veterinary palpation, instead of relying solely on non-return rates 60–90 days after breeding. This depth of data allows an accurate determination of both male and female fertility traits. In addition, this program provides unique research materials to identify molecular markers associated with fertility.Pure Holstein bulls were selected based on their fertility as previously described by Peddinti et al. . BrieflyThe fertility of bulls (Holstein), drawn from a total population of 874 bulls, is based on an average of 788 breeding, ranging from 101 to 11,997. We used the model described by Zwald et al. , which t260/A280 ≥ 1.8) and no degradation were used for the Phase I and Phase II studies.Alta Genetics Inc.  provided frozen semen straws of selected bulls. Thawed spermatozoa were then purified through a Percoll gradient, washed, counted, and pelleted for DNA isolation . DNA wasThe 10 K SNP Bovine Gene Chip  was used to genotype DNA samples (250 ng/μl) of 10 low-fertility and 10 high-fertility bulls. The experiment was carried out at Baylor College of Medicine , and assays utilized molecular inversion probe (MIP) technology, allowing the multiplex detection of single base variants using a 4-color array hybridization assay ,38. The The allelic discrimination technique, based on the TaqMan technology  was performed by scientists at SeqWright, Inc. seqwright.com on DNA samples (4 ng/μl) of 101 low-fertility and 100 high-fertility bulls to validate the Phase I association study. Primer and probe sets were designed on a sequence of 501 nucleotides containing the SNP  using the Primer Express software . The probes were designed and labeled with FAM (6-carboxy-fluorescein) or VIC fluorescent dyes  to match perfectly either one of the alleles  containing primers (900 nM) and probes (200 nM). DNA samples were amplified by 40 times . For each PCR run, negative (no-template) and positive (oligos) controls were added, and each run was preceded or followed by 1-minute incubation at 60°C to determine the background, or final levels of fluorescence, in each reaction. The base calls were made by examining all samples on the allelic discrimination graph, and the Sequence Detection Software  was used to determine the homozygosis or heterozygosis of alleles. All samples were run in triplicates for each SNP allele.The major repository of SNP data in the National Center for Biotechnology Information (NCBI) database (dbSNP), combined with Entrez Genome (NCBI) as well as the Ensembl automatic analysis pipeline, were used to characterize and annotate the markers (SNPs and genes) based on the cattle genome assembly version 3.1. For each SNP, a sequence of 501 nucleotides consisting of the 250 nucleotides immediately upstream and downstream of the SNP allele, were extracted and the best hit in the Bovine 3.1 genome identified using BLASTN. We considered only the hits (i) found on the same chromosome as the query, (ii) with E-values equal or close to 0.00 and (iii) presenting at least 94% alignment with the full length of the query sequence. Furthermore, the same query sequences were used to search for putative transcription factor binding sites through the Transfac-blastX (TRANSFAC Database 7.0 for searching eukaryotic transcription factors).6/ml and incubated with or without the integrin beta 5 antibody . As a control for structural effects of the antibody, spermatozoa (50 × 106/ml) were also incubated with a nonmammalian protein (BIT) antibody (sc-33757: 20 μg/ml). After a 2-hour incubation at 38°C under 5% CO2 in air, spermatozoa were washed twice in fertilization medium and used to fertilize the oocytes. The motility of spermatozoa was comparable before and after the incubation period.Thawed spermatozoa were purified through a Percoll gradient as previously reported . Motile 6 spermatozoa/ml. After 18 hours of co-incubation, oocytes were collected, denuded, washed, fixed, and placed on slides for staining with 0.1% aceto-orcein on slides. The nuclear status of oocytes was observed under a microscope, and the fertilized oocytes (two extruded polar bodies and/or two pronuclei) were counted to assess the fertilization rates.Bovine oocytes were purchased from Bomed Inc. , and maturation took place during the transportation. These oocytes were washed and fertilized with treated and untreated spermatozoa at a final concentration of 10In the Phase I study, the 20 bulls of varied fertility were typed for 9,919 SNP using Affymetrix 10 K Xba 142 2.0 array. A total of 1,712 markers fixed for a single genotype in this sample were excluded from further analysis. Markers were tested for Hardy-Weinberg Equilibrium using a 1 degree of freedom chi-square test. Markers with a p value < 0.05 were flagged as potentially out of HWE, but were used for association analysis.The fertility of the bulls was converted to Z-scores and used as the quantitative trait for the association analysis. Analysis was conducted only at the markers' positions; no attempt at interval mapping was made. At each marker, the mean fertility, scored as a Z-score, was compared between genotypes using single marker regression. If the n for a genotype was 1, the samples were collapsed into the heterozygote. Benjamini- Hochberg FDR was calculated at each marker, adjusting 8,207 tests. A p-value less than 0.01 was set as the threshold of a significant association between the SNP marker and bull fertility; this corresponds to an FDR of 84%. Similar analyses were conducted in Phase II data.The lack of methods to accurately predict sire fertility obliges the artificial insemination (AI) industry to keep and test hundreds of bulls. The selection of such bulls, whose fertility has been evaluated with progeny tests prior to their use in large-scale breeding programs, is costly and can take several years. Recent advances in cattle genome projects and molecular genetic technologies have increased the likelihood of identifying uncompensatory defects impairing the functions of spermatozoa. High-throughput technologies may help pinpoint relationships between a single DNA marker  and economically important traits in dairy cattle. Information about specific SNPs can enhance the efficiency of genetic selection, especially for traits that are (i) too difficult or expensive to measure in all animals and/or (ii) expressed after a long field trial .The most fertile and the least fertile pure Holstein bulls were selected from a pool of 874 available bulls with at least 300 breeding records. These were defined as the representative outliers for their corresponding groups and the scaling of fertility as the deviation from the population average fertility. The average breeding and fertility rates of the 10 low- and 10 high-fertility bulls used in the Phase I association study were 1,974 and -9.2% versus 3,540 and 6.2%, respectively. In the Phase II study, these values were 904 and -4.2% for low-fertility (100), and 994 and 3.4%, for high (101) fertility bulls , and Additional file -2. These most significant markers were selected to test in the Phase II samples.No significant difference was found between the average of SNP call rates in both groups . The HWE test revealed an FDR of 61% corresponding to 790 SNP markers that failed the test (versus the 496 expected at random), but were used for QTL analysis as mentioned above . A total of 1,712 SNP markers were excluded from analysis because they were not polymorphic. In the Phase I samples, the fertility (Z-score) of bulls was used as the quantitative trait for the association analysis of the remaining 8,207 markers. The p-value distribution of the 8,207 markers' test showed a slight deviation from the uniform to left end (near 0) of the distribution, indicating the presence of more putative fertility-associated SNP markers in the data  around the SNPs in the Holstein population is not clear yet, but we believe the LD may extend a good distance (≤ 0.5 Mb) around the markers due to the extensive inbreeding in the population -48. For -4; Phase I) study  population. For example, a genome-wide-association (GWA) study of macular degeneration was successfully replicated when the initial study contained only 96 cases and 50 controls [dy Table  for repldy Table . InteresBos taurus autosome 9, 1, 4 and 10, respectively . Only three SNPs gave valuable information  and rs29024867 . Hence, our findings suggest potential roles of the SNP mutations on regulation of gene expressions as already suggested in other studies -56.Taken together, our results provide novel loci candidates whose associations with the bull fertility have not previously been reported. Because of the great interest of the non-synonymous SNP rs41257187 associated with the ITGB5, we performed a Six Frame Translation of ITGB5 mRNA reference sequence reported on NCBI (NM_174679.2) using the Baylor College of Medicine's HGSC Search Launcher to find the reading frame leading to the amino acid change. We found that the complete ITGB5 protein could be obtained from two different reading frames (+3 or +1) when using the whole length of RNA sequence or the length from the start codon (ATG), respectively. Contrary to the NCBI report, we found that the SNP mutation site (C/T) induced a synonymous amino acid change of a Proline (CCC) to another Proline (CCT) at the position 778 (P778P). The same SNP (rs41257187) inducing a synonymous amino acid change (Proline to Proline) is also reported on the Ensembl database.The interest of integrin beta 5 in our study resided in the role(s) played by the integrin family members during fertilization and embryogenesis. Integrins are known to be expressed in a variety of tissues, including reproductive tissues of mice, humans, pigs and cattle -62.The biological function of the integrin beta 5 subunit is not clearly defined. We tested the potential involvement of ITGB5 isoform on sperm-egg interaction, and the results showed that the percentages of matured oocytes (metaphase II) undergoing a successful fertilization (1–2 PN) with spermatozoa pre-exposed to anti-integrin beta 5 antibody were decreased: 74, 60, and 47% normally fertilized oocytes in the presence of 0, 5, and 20 μg ITGB5/ml, respectively. This dose-dependent inhibition was not attributed to the antibody itself since the pre-exposure of spermatozoa to the non-mammalian protein (BIT) antibody had no effect on the ability of spermatozoa to fertilize the oocytes , standard deviation, minimum and maximum values for the four markers from the Phase II study.Click here for fileTable S2. List of 97 SNP markers associated with fertility (P < 0.01).Click here for file


There are a number of factors  that must be in place for automation to be as effectiveas possible. This paper discusses these factors and their relationship with automation. It evaluates less obvious areas associated with automation, as well as the more established ones, and discusses the premise that it is the integration of all these aspects that truly offers the biggest opportunities.


A ubiquitous building block of signaling pathways is a cycle of covalent modification . Our paper explores the kind of information processing and filtering that can be accomplished by this simple biochemical circuit. Signaling cycles are particularly known for exhibiting a highly sigmoidal (ultrasensitive) input–output characteristic in a certain steady-state regime. Here, we systematically study the cycle's steady-state behavior and its response to time-varying stimuli. We demonstrate that the cycle can actually operate in four different regimes, each with its specific input–output characteristics. These results are obtained using the total quasi–steady-state approximation, which is more generally valid than the typically used Michaelis-Menten approximation for enzymatic reactions. We invoke experimental data that suggest the possibility of signaling cycles operating in one of the new regimes. We then consider the cycle's dynamic behavior, which has so far been relatively neglected. We demonstrate that the intrinsic architecture of the cycles makes them act—in all four regimes—as tunable low-pass filters, filtering out high-frequency fluctuations or noise in signals and environmental cues. Moreover, the cutoff frequency can be adjusted by the cell. Numerical simulations show that our analytical results hold well even for noise of large amplitude. We suggest that noise filtering and tunability make signaling cycles versatile components of more elaborate cell-signaling pathways. A cell is subjected to constantly changing environments and time-varying stimuli. Signals sensed at the cell surface are transmitted inside the cell by signaling pathways. Such pathways can transform signals in diverse ways and perform some preliminary information processing. A ubiquitous building block of signaling pathways is a simple biochemical cycle involving covalent modification of an enzyme–substrate pair. Our paper is devoted to fully characterizing the static and dynamic behavior of this simple cycle, an essential first step in understanding the behavior of interconnections of such cycles. It is known that a signaling cycle can function as a static switch, with the steady-state output being an “ultrasensitive” function of the input, i.e., changing from a low to high value for only a small change in the input. We show that there are in fact precisely four major regimes of static and dynamic operation (with ultrasensitive being one of the static regimes). Each regime has its own input–output characteristics. Despite the distinctive features of these four regimes, they all respond to time-varying stimuli by filtering out high-frequency fluctuations or noise in their inputs, while passing through the lower-frequency information-bearing variations. A cell can select the regime and tune the noise-filtering characteristics of the individual cycles in a specific signaling pathway. This tunability makes signaling cycles versatile components of elaborate cell-signaling pathways. Cells rely on chemical interactions to sense, transmit, and process time-varying signals originating in their environment. Because of the inherent stochasticity of chemical reactions, the signals transmitted in cell-signaling pathways are buried in noise. How can cells then differentiate true signals from noise? We examine this in the context of a basic but ubiquitous module in signaling cascades: the signaling cycle. Whereas an individual signaling cycle is simply an element of a large signaling network, understanding its response is an essential first step in characterizing the response of more-elaborate signaling networks to an external stimulus ,2.Each cycle consists of a substrate protein that can be in one of two states: active  or inactive , see Signaling cycles can also require multiple phosphorylations for activation. Furthermore, cycles of phosphorylation are frequently organized into cascades in which the activated substrate protein serves as a kinase for the next cycle. Activation of the first kinase in a cascade can be triggered by a receptor that has received a specific stimulus . In addition, feedback processes may be present. Furthermore, reactions may involve shuttling participating molecules between different cellular compartments, and other spatial effects. The dynamics of signaling cascades have been the subject of active research using modeling and experiments. Theoretical and computational studies of eukaryotic signaling cascades span a broad range of questions, such as those concerning the dynamics of the epidermal growth factor receptor (EGFR)  or apoptIn this paper, our focus will be on the statics and dynamics of the basic, singly modified signaling cycle, with no spatial effects. The seminal contribution of Goldbeter and Koshland considered the steady-state response of this basic cycle and demonstrated that, under appropriate conditions, the response can be in a highly sigmoidal, ultrasensitive regime, or in a hyperbolic regime  . Here, we systematically consider both the steady-state response and the dynamic response to time-varying stimuli. To model the enzymatic reactions in the signaling cycle, we use the total quasi–steady-state approximation (tQSSA) . The tQSTo obtain a fuller picture of the signaling cycle and its function, we then analyze its response to time-varying kinase activity. We demonstrate analytically that the intrinsic architecture of the cycles makes them act—in all four regimes—as tunable low-pass filters for small-enough time-varying deviations of the kinase activity from baseline levels. Numerical simulations show that these analytical results continue to hold quite well even for bigger deviations from baseline level.The four different regimes of the signaling cycle make it a versatile element, able to perform various signaling functions, while its low-pass filtering enables it to operate in noisy environments. These properties may help explain why signaling cycles are so ubiquitous in cell signaling.E1) produces active proteins (A) from the inactive ones (I), and a backward reaction catalyzed by phosphatases  deactivates active proteins:1a (d1) and a2 (d2) are substrate–enzyme association (dissociation) rates, and k1 (k2) is the catalytic rate of the forward (backward) enzymatic reaction. For notational convenience, we shall use the same symbol to denote a chemical species as well as its concentration. The input to the cycle is the total concentration of the active kinase, A.The signaling cycle is modeled by two enzymatic reactions, as illustrated in Saccharomyces cerevisiae and Xenopus oocyte cells , bot, bot35])orted in  and consorted in ).X denotes the concentration of an unbound chemical species and t to emphasize that it is a dynamic variable; however, for notational simplicity, we will omit the time argument in the rest of the paper and simply write A, which is of primary interest, is simply recovered through the expression Instead, we rely on the total quasi–steady-state approximation (tQSSA) ,37–39 s to obtaiion see .Our key equation  simplifiE), and on the MM constant (K) of the enzymatic reaction. The unsaturated (first-order) regime, in which the rate of reaction is linearly proportional to the substrate concentration, occurs when the substrate is much less abundant than the sum of the MM constant of the reaction and the enzyme concentration  of ency see . Interesades see .In this new regime, the output below a given input threshold is zero, and then increases hyperbolically until it reaches its saturation level (approximated by the same expression as the saturation level of an ultrasensitive regime). The output in this regime is close to zero for inputs below a threshold, and increases rapidly to a saturation value, consistent with the results obtained in  using thThe MM approximation fails, however, when the amount of enzyme becomes comparable to that of its substrate. Using the tQSSA, we are able to refine the range of parameter values required for ultrasensitive signaling. The criteria for ultrasensitivity obtained from the MM model , namely n et al.  by more In summary, we have demonstrated that a signaling cycle can operate in four regimes that have qualitatively different steady-state responses to kinase activation. Of the newly identified regimes, the signal-transducing regime is a good candidate for sensing stimuli, when a graded and undistorted response is required. Depending on the slope of its response, which is controlled by parameters of the cycle and can be easily adjusted by the cell to a required level, the input signal may be amplified or diminished. We consider factors influencing the choice of the regime for natural signaling cycles in different cellular processes in the Discussion.The four regimes we consider, although obtained only at extreme parameter values, are actually quite descriptive of the system for a wide range of parameters, and naturally partition the space of possible steady-state behaviors of the signaling cycle into quadrants, as shown Understanding the steady-state response of the cycle is informative, but it is only part of the story; signaling cycles do not necessarily transmit steady inputs, but rather deal with time-dependent signals that reflect changing environmental conditions.Signaling cascades in the cell are activated by receptors, which in turn get activated by ligand binding and inactivated by internalization and other mechanisms. All of these mechanisms produce time-varying signals, and are subjected to noise  due to small numbers of molecules, diffusion, and other effects. How can a cell extract a time-varying signal from noisy stimuli?To address this question, we first study the response of the four regimes to time-varying stimuli. A high-frequency signal is a proxy for the noise in the signal, so understanding how the cycle responds to high frequencies is essential for understanding its response to noise.We studied the cycle's response to oscillating kinase levels at different frequencies and amplitudes: O of the variations in the output , obtained by numerical simulation for three values of a, and as a function of input frequency ω. Invariably, the response is flat and high at low frequencies, but starts to decrease after a particular frequency is reached. These results are very well-described in the case of the smallest a (corresponding to 11% deviations) by the expression obtained analytically using small-signal approximations , the gain and the cutoff frequency can be adjusted independently, thus allowing greater flexibility to the signaling requirements of individual signaling pathways . FurtherIt is easy to understand the origin of the low-pass filtering behavior. First, consider a cycle subjected to a slowly varying input : if the c = 1/ωc. If the stimulation is longer than the switching time, aE0g/ωc. On the other hand, a shorter, transient stimulus, The response of the cycle thus depends on the two timescales: the duration of the stimulus τ = 1/ω and the intrinsic switching time of the cycle τc are unlikely to produce any downstream activation of the pathway, whereas those that stay bound longer than τc activate the pathway. Low-pass filtering can thus perhaps make a signaling cascade more selective to higher-affinity ligands.Interestingly, ligands activate a kinase by binding to it. The results here imply that weak ligands binding for a time interval shorter than τImportantly, low-frequency inputs are proxies for longer input activation, whereas high-frequency inputs are proxies for short, transient activations of the cascade and for high-frequency noise. Because of low-pass filtering, cycles respond to noise less than to signals, and as the noise shifts to higher frequencies, the cycle responds to it less. In summary, analysis of dynamic response demonstrates that (1) the cycle acts as a low-pass filter in all four regimes; (2) the cutoff frequency and the gain of signaling can be adjusted by the cell to achieve better performance ; and (3) low-pass filtering makes signaling cascades insensitive to noise and transient activations. Below, we discuss some biological implications of these findings.Significant effort has been put in the elucidation and characterization of signaling cascades and pathways . Wha. Wha52])Using a deterministic model, we have attempted to provide a systems-level input/output understanding of the signaling cycle, ubiquitous in signaling pathways. After identifying four parameter regimes , their steady-state and dynamic behaviors were analyzed and numerically verified. The results indicate that cycles act as low-pass filters, and that each regime may be useful under different circumstances. Given the values for cycle parameters, one can use our results to determine the regime in which the cycle operates. Unfortunately, the scarcity of parameter values makes it hard to assess which of these regimes is more widely present in signaling pathways. The low-pass filtering behavior of the cycle demonstrates that inputs of the same magnitude, but changing at different speeds, may produce very different outputs, which argues in favor of studying the dynamical properties of signaling pathways.All physical systems stop responding to fast-enough inputs, but what makes the low-pass filtering behavior of the signaling cycle interesting is that it is first-order, with a single cutoff frequency, and that the cutoff frequency can be adjusted by evolution  and by the cell (through changes in gene expression). As such, the signaling cycle is a versatile module with simple dynamics that can be easily tuned for various noise-filtering needs and used to construct signaling networks with more-complicated functions and dynamics.Of the two newly identified regimes, the signal-transducing one is of particular interest because it appears ideal to transmit time-varying intracellular signals without distortion while filtering out high-frequency noise in the input. Furthermore, because it is linear, it opens up the possibility that at least parts of signaling pathways  may be amenable to linear system analysis, a powerful set of tools to understand the properties of arbitrary network structures and motifs . If naturally occurring cycles operate in the signal-transducing regime, then analyzing networks built of these cycles becomes tractable as long as load effects can be neglected.S. cerevisiae and Xenopus operate in saturation . Taken together, these numbers suggest the possibility of a signaling cycle operating in the signal-transducing regime.Can naturally occurring signaling cycles operate in this regime? Although it was demonstrated that certain kinases in or yeast ,55), litor yeast . Phosphaf 0.1 pl ). Data oDifferent signaling cycles, however, may be operating in different regimes, raising two questions: first, which regime is chosen by the cell for a cycle in a particular position in a network for a specific signaling application? Second, what are the advantages and disadvantages of each such regime?To answer the first question, one approach is to determine in vivo concentrations and MM constants of involved enzymes. Unfortunately, these data are often unavailable or scattered throughout publications in the biochemical literature. The applicability of MM constants measured in vitro is also questionable. An alternative experimental approach to establishing what regime a cycle operates in would be to obtain its steady-state response curve and determine which of our four cases it corresponds to. Similarly, one could experimentally obtain the response of the cycle to stimuli of various frequencies and use our dynamic characterization to infer the operating regime. One may, furthermore, be able to estimate some of the biochemical parameters and concentrations of the participating molecules from these experimental response characteristics. The success of such measurements depends on, and hence is limited by, the availability of in vivo single-cell probes for the phosphorylation state of a particular protein.The second question, on advantages and disadvantages of each regime, can be addressed by systematic analysis of cycle properties: steady-state and dynamic response, robustness to fluctuations, etc. By matching these characteristics against the requirements of a particular signaling system, one can suggest the optimal regime for each signaling application. For example, one can think that signaling in retina cells shall be fast and graded, depending on the intensity of adsorbed light. Similarly, gradient sensing in motile cells has to provide graded responses on the timescales required to change direction of motion. On the other hand, signaling of cell fate–determining stimuli and signaling involved in various developmental processes may require an ultrasensitive (“on/off”) response, while imposing much softer constraints on the time it takes to switch the system from off to on state (hours instead of the milliseconds needed in light-sensing). The performance of the signaling regimes in the context of cascades and feedbacks is also important for understanding the rules that govern the choice of a regime for each cycle.For cycles in signaling applications involving all-or-none decisions, such as differentiation, apoptosis, or the cell cycle, it has been argued that ultrasensitive cycles may be useful because they effectively generate a discrete output that is either high or low . When suA signal-transducing cycle, on the other hand, is the best choice to transmit time-dependent signals without distortion, because its output is approximately a scaled, but otherwise undistorted, copy of low-frequency input signals, while noisy input components are filtered out. It is the only cycle that does not distort the input. What the other two regimes might be best at is not clear. The threshold-hyperbolic cycle, however, may prove useful in situations when no activation is desirable below a given input strength and when a graded response is desired for inputs above this threshold.We here considered the effect of temporal noise in kinase levels on the response of the signaling cycle. A more-detailed model should also take into account the intrinsic noise coming from the cycle itself, since it consists of chemical reactions in which the number of molecules per species is small, and thus a deterministic model based on MAK may be inadequate. For example, although the deterministic cycle is known to have a single steady-state solution, Samoilov et al. (see ) found tAchieving a detailed understanding of signaling pathways is an important problem, but is highly limited by the lack of experimental data with enough resolution to support modeling efforts. Nevertheless, having coarse-grained functional characterizations of the possible operating regimes of constituent cycles may permit system-level modeling of networks built of such cycles, despite uncertainties and variations in underlying biochemical parameters and molecular concentrations. Perhaps identifying and analyzing other relevant modules of biological networks, as we have done here for a signaling cycle, will shed some light on their behavior. Similar explorations could be done, for example, on signaling cycles that require multiple phosphorylation events to become active, or on G-protein–coupled receptors.Although characterization of the component modules of a biological network is a necessary and important step toward understanding network operation, it should be kept in mind that the behavior of the network will undoubtedly be considerably richer than that of the individual modules.All analytical expressions were obtained starting from The cycle equation  correspo. Finally, the data in E0)  is a normal random variable with unit variance and zero mean). All the code is available upon request.All numerical analysis was done in Matlab and, unless explicitly mentioned here, is based on the full MAK description of the cycle. The data in For all the dynamic simulations, the steady-state level of the input for the four cycles was chosen such that the steady-state output was about halfway to saturation to allow the cycles to respond as much as possible. Choosing other steady-state values where the slope of the steady state response curve is small would lead to little response. Particular care has to be taken with the ultrasensitive cycle, which has a very small range of inputs where its slope is non-zero, implying that this cycle needs to be finely tuned for it to transmit dynamic information see .Figure S1O of the hyperbolic, signal-transducing, threshold-hyperbolic, and ultrasensitive switches, respectively , shown in O is color-coded and shown as a function of the input amplitude a and frequency w. Output oscillations increase with increasing a and decrease with increasing w, as expected. The four cycles, however, respond very differently to their inputs. The parameters used for the cycles are the same as those in Plots show the output oscillations (808 KB PPT)Click here for additional data file.Text S1(86 KB PDF)Click here for additional data file.Text S2(84 KB PDF)Click here for additional data file.Text S3(152 KB PDF)Click here for additional data file.Text S4(150 KB PDF)Click here for additional data file.Text S5(73 KB PDF)Click here for additional data file.Text S6(72 KB PDF)Click here for additional data file.http://expasy.org/sprot/) [The SwissProt (/sprot/)  accessio


Here the events leading to this discovery are reviewed with particular attention to priority and actual contributions by those involved. Since I would argue that discovering HIV was dependent on the previous discovery of the first human retrovirus HTLV-I, the history of this discovery is also re-examined. The first human retroviruses (HTLV-I) was first reported by Robert C. Gallo and coworkers in 1980 and reconfirmed by Yorio Hinuma and coworkers in 1981. These discoveries were in turn dependent on the previous discovery by Gallo and coworkers in 1976 of interleukin 2 or T-cell growth factor as it was called then. HTLV-II was described by Gallo's group in 1982. A human retrovirus distinct from HTLV-I and HTLV-II in that it was shown to have the morphology of a lentivirus was in my mind described for the first time by Luc Montagnier in an oral presentation at Cold Spring Harbor in September of 1983. This virus was isolated from a patient with lymphadenopathy using the protocol previously described for HTLV by Gallo. The first peer reviewed paper by Montagnier's group of such a retrovirus, isolated from two siblings of whom one with AIDS, appeared in Lancet in April of 1984. However, the proof that a new human retrovirus (HIV-1) was the cause of AIDS was first established in four publications by Gallo's group in the May 4 Unfortunately the omission of the American scientist Robert C. Gallo from the 2008 Nobel Prize in Medicine or Physiology for the discovery of HIV by many has been viewed as a final scientific verdict handed down by the Nobel committee of the Karolinska Institutet on an old controversy between the Institute Pasteur and NIH and that previous settlements were for political reasons only. Also, the decision to omit Gallo has resulted in the resurrection of false allegations in the media that Gallo and coworkers at NIH had rediscovered or even stolen the French HIV isolate previously sent to them from the Pasteur Institute. Thus, it could be interpreted as if the Nobel committee finally had put right an unjust settlement previously obtained between the French and American scientific groups. There is no doubt or controversy about the fact that the French group was first to isolate this new virus. This is what the Nobel committee chose to award.Two years ago I had the privilege to painstakingly and thoroughly go through all the literature related to the discovery of HIV. Since the motivation for the Prize by the Nobel Committee is very limited and the fact that the Committee members cannot comment on how they came to their decision, I think it is important that the medical community gets the correct historical facts about this important discovery. Therefore, I have written this article. I would say that what I present below is a fair and accurate account on the events and work that led to the discovery of a new virus as the cause of AIDS. Regarding whom should get the credit for the discovery of HIV, this review should enable the reader to come to his or her own conclusion. Mine, however, is different from that of those of my fellow faculty members that presently make up the Nobel Committee for the Nobel Prize in Physiology or Medicine. I will here show that by going through the literature it is evident that Gallo's group was not only first to show that HIV is the cause of AIDS but that the French group had not been able to discover this new virus without the active assistance of, as well as, previous work by Gallo. It will also be evident that Gallo and his associates had no reason to "steal" any French isolate. Last year this journal published another account of the 2008 Nobel Prize .Isolation of a virus means infection, propagation and  transmission of an infectious agent in cultured cells. New viruses, for which there are no susceptible cells in culture, have lately also been detected solely by molecular techniques, e.g. hepatitis C virus by using a random-primed complementary DNA library from an infected patient (Michael Houghton) and subtypes of human papilloma viruses by using hybridization under low stringency and subsequent DNA cloning .The difficulty in isolating a new virus is choosing the right cell culture and detection systems and to obtain specimens containing the virus. With a susceptible cell culture system and a detection system available, isolation of a new virus is not only possible but also rather straightforward. In the case of HIV, before the successful isolation of the first human retrovirus  by Robert C. Gallo , neither2+. Unlike DNA polymerases α and β, the preferred primer-template for DNA-polymerase γ is (dT)≅15·(A)n over (dT)≅15·(dA)n! This third cellular DNA polymerase was independently from Gallo discovered by Art Weissbach and they later named it DNA-polymerase γ[After the discovery of reverse transcriptase from animal oncogenic RNA viruses  a large number of publications on putative discoveries of retrovirus detections in human malignancies appeared in the early 1970-ties. However, they were all either owing to contaminations in the laboratories with animal retroviruses or the mitochondrial DNA-polymerase γ, the latter when the reports were based on reverse transcriptase activity alone. DNA-polymerase γ is a normal cellular DNA polymerase which uses RNA as a primer but not as a template. Therefore, like reverse transcriptase, the activity of DNA-polymerase γ was sensitive to a ribonuclease treatment -5. This ymerase γ.From the numerous and erroneous reports on retroviruses in various human cancers, the notion of human cancer viruses became in ill repute and rather than talking of "human tumor viruses" people in science talked of "human rumor viruses". In fact, as narrated by Gallo in one of his reviews, when GaIn his quest to find a human retrovirus in lymphoma/leukemia Gallo developed sensitive and generalized techniques for the detection of reverse transcriptase to discriminate it from cellular DNA polymerases ,9.To isolate T cell lymphotropic viruses one needs to be able to culture T lymphocytes. Working with conditioned medium to grow lymphocytes, Gallo together with two of his post doctorial fellows Doris Morgan, Frank Ruscetti discovered T cell growth factor (TCGF) later named interleukin 2 (IL-2). Hence, the first report of IL-2/TCGF was by Robert Gallo was published in 1976 . The firI sincerely doubt that anyone would have been looking for a retrovirus as the etiological agent for AIDS had HTLV-I not previously been isolated. I will therefore shortly recapitulate the history of the discovery of this virus.in vitro; demonstrate specific antibodies to the virus in the serum of the patient; demonstrate that proviral DNA could be found integrated in the DNA of the cells from which the virus was isolated; and provide evidence that this was not a one-time affair by showing serological evidence of specific antibodies not only in the patient but in some others as well.Reverse transcriptase activity was detected by Gallo's group in a T-cell line established (using IL-2) from a patients diagnosed originally with mycosis fungoides in1979. To show that this was indeed a new human retrovirus Gallo and coworkers set out to show that the same virus could be isolated from primary tissue samples of the same patient by culturing primary T-cells with IL-2; demonstrate that the virus was novel, i.e., not any of the known animal retroviruses; show it could infect human T cells th 1980 and appeared in the December issue of the same year. The second paper from Gallo and his group  on the isolation of HTLV-I now from fresh cultured cells from a patient with Sezary T-cell leukemia was submitted to Nature on May 1st 1981 and appeared in the November 19th issue of that journal[Most or all these results were obtained by the time Gallo submitted the first paper to PNAS allowing it to quickly be followed with several other reports. The papt journal. In the t journal reportedOn the 26th of June 1981  Hinuma et al. submitted (communicated) a paper to PNAS showing antibodies against an antigen in a T-cell line, MT-1 from a patient with adult T-cell leukemia (ATL), in all 44 patients with ATL examined and in 32 of 40 patients with malignant T-cell lymphomas using indirect immunofluorescence. The antOn July 13th of 1981 Miyoshi et al. (Hinuma last author) submitted a paper to Nature (published December 24th 1981) on the transmission of virus from MT-1 cells  to cord blood cells of a male infant transforming  the latter cells.th 1982 issue of Nature Gallo's group together with the Japanese colleagues Nakao, Miyoshi, Minowada, Yoshida and Ito reported that HTLV-I and ATLV was one and the same virus[In the November 4ame virus and deciAs is evident from the above Gallo was truly the first to isolate the first known human retrovirus and to report it. In 1982, Gallo and co-workers reported the discovery of the second human retrovirus, HTLV-II, in a patient with hairy cell leukemia. However, no malignancy or other disease has yet been clearly linked to the infection of this virus.BRU) for lymphadenopathy virus and BRU from the first three letters of the patient's last name. Since this has been viewed as a seminal paper for the discovery and characterization of HIV, I will here describe this paper in detail.In May of 1983 Françoise Barré-Sinoussi et al. published a paper in Science [2+-dependent and not Mn2+-dependent reverse transcriptase). Virus production continued for 15 days and decreased thereafter, in parallel with the decline of lymphocyte proliferation. A standard and routine procedure in clinical virology when trying to isolate a virus is to passage the cells to fresh ones, usually when the original cells start to die, and particularly if they do not yet show any signs of being infected. Hence, to show virus transmission, cells from patient B.R.U. after three days in culture were also co-cultured with lymphocytes from a healthy donor of the Blood Transfusion Center at the Pasteur Institute. Also with these co-cultures, RT could be detected after 15 days of culture (not before) and amounts of RT remained stable for 15 to 20 days. Transmission of cell-free supernatants from the original culture of B.R.U. cells was successfully obtained using 3-day-old cultures of T lymphocytes from two umbilical cords. There is no mentioning of cytopathic effects in any of the cultures or that fresh T lymphocytes from healthy donors were added to make the virus isolation possible or to save the virus isolate except for the virus transmission experiment described above.Cells from a lymph node of patient B.R.U. was cultured under the conditions described by Gallo,13, i.e.The virus isolate had a density of 1.16 (same as HTLV-I) in a sucrose gradient. Electron micrographs of the virus from the umbilical cord lymphocytes were reported to be of typical C-type virus, i.e. with a spherical core (same as HTLV-I). Of note, HIV is a lenti retrovirus having a conical or cylindrical core structure and does not have type C virus morphology.Two experiments were performed to distinguish the new isolate from HTLV-I. The first was by immunofluorescense using serum from the patient as well as a goat anti HTLV-I p24 (capsid protein) and mouse monoclonal anti HTLV-I p19 (matrix protein). The two latter anti-sera, as well as two HTLV-I producing cell lines were from Robert C. Gallo as acknowledged by the French group in the paper. The sera were tested against two different cultures of normal blood lymphocytes, against the two lines of HTLV-I producing cells, and against virus producing cells from the co-culture of T lymphocytes of patient B.R.U. and the healthy donor and against infected cord blood lymphocytes. In addition cells from a lymph node from a person (patient 2) who presented with multiple adenopathies and who had been in close contact with an AIDS case was also tested. No RT activity was detected in the latter patient's cultured lymphocytes. The anti-HTLV-I sera from Gallo (anti p19 and p24) reacted with the HTLV-I producing cell lines only. Serum from patient B.R.U. reacted with 90–100% of the HTLV-I producing cell lines and with 90–100% of the co-cultured cells from B.R.U and the healthy donor, as well as, the cells from patient 2. The B.R.U. serum reacted with only 0.5 to 2% of the infected umbilical cord lymphocytes. It is noteworthy that B.R.U.'s serum reacted with 90–100% of the co-cultured cells from B.R.U and the healthy donor since we know that only the CD4 positive cells should be infected. The B.R.U.'s serum also reacted with 90–100% of the HTLV-I producing cells! If this were to be due to a possible double infection with HIV and HTLV-I again only CD4 positive cells should be positive. More likely something unrelated to either HIV or HTLV-I was detected by the B.R.U. serum, in my opinion most probably mycoplasma, a common contaminant in cell culture. The 0.5 to 2% positive infected umbilical cord lymphocytes may indicate retrovirus-infected cells. However, the lack of reactivity with the p19 and p24 sera with these cells is not a proof that the B.R.U. virus was not HTLV-I. The few percentages of possibly positive cells could simply have been missed with the specific antibodies but detected with the patient's sera containing antibodies to all viral proteins. The paper does not present any photos of the fluorescent cells.The other experiment performed to distinguish the new virus from HTLV-I was immunoprecipitation of lysates of infected cord lymphocytes, as well as, virus released from the infected cells with the same sera used for immunofluorescense and in addition serum from patient 2. Serum from B.R.U. and patient 2 (whose lymphocytes were RT negative) precipitated a protein of the apparent size of 25,000 from extracts of the infected cord lymphocytes and from the supernatants of these cells. Serum from a healthy donor did not precipitate this protein, nor did the anti HTLV-I p19 or p24 sera. The sera from B.R.U. and patient 2 did not precipitate the p25 protein from an extract of one of the HTLV-I producing cell lines. However, neither did the goat anti HTLV-I serum from what I can determine from the figure presented! Thus, there is no positive control indicating that they indeed had an HTLV antigen to precipitate. If the goat antiserum indeed precipitated a p24 protein from the HTLV-I producing cell extract, the band of p24 precipitated was extremely week, indicating that the serum was not very good at precipitating HTLV-I p24, at least not in the hands of Barré-Sinoussi and coworkers. The HTLV-I producing cells were all infected as opposed to only 0.5 to 2% of the cord blood cells. So, if the cord blood cells were infected with HTLV-I and not a new virus, the goat antiserum would still have had a hard time precipitating any protein! An appropriate control would have been a serum from a HTLV-I infected individual. The size of the protein they precipitated is in fact 24,000, the same as that of HTLV-I. The core protein of both HIV and HTLV-I is 24,000.In reality, in my view there is no evidence whatsoever in this paper that a new human retrovirus has been isolated! With the data presented, the virus they isolated could well have been HTLV-I or in particular HTLV-II. The paper was obviously written in haste, as acknowledged by Montagnier, and conAfter having a first manuscript being rejected by Nature, Gallo suggested to Montagnier to send it to Science and even strongly endorsed the paper to the journal .A more thorough description of the French isolate LAV from patient BRU and two new retrovirus isolates from two patients with AIDS was given at a Cold Spring Harbor meeting held in September of 1983. A proceedings, however not peer reviewed, from the meeting was published not until September of 1984. The oraThe first publication in a peer reviewed journal indicating the isolation of a new retrovirus, distinct from HTLV-I and HTLV-II, isolated from two siblings with hemophilia B of whom one with AIDS, appeared in Lancet in April of 1984 and was written by the French group. Again tIn conclusion, by April of 1984 the Pasteur group headed by Luc Montagnier had reported on a new human T-lymphotropic retrovirus distinct from HTLV-I and HTLV-II as judged by morphology and which was present in a few patients with AIDS and lymphadenopathy, as well as, in people at risk of acquiring AIDS. The virus infected CD4-positive T-lymphocytes, the very cells affected in AIDS. Although clearly associated with AIDS, they had not yet shown that the new virus was an etiological agent, and the only one at that, of this new disease.th of 1984 four papers by Robert C. Gallo's group were published in Science describing a new human retrovirus virus as the probable cause of AIDS. All four papers were submitted the 30th of March 1984. One paper[2+-dependent reverse transcriptase, being transmittable by co-cultivation of T cells with irradiated donor cells or with cell free fluids, having distinct morphology by electron microscopy, and by expressing specific viral antigens (indirect immune fluorescence) using a serum obtained from a patient with pre-AIDS , as well as, antisera prepared against purified, whole disrupted HTLV-III. The 48 HTLV-III isolates were obtained from 18 of 21 tested patients with unexplained lymphadenopathy and leukopenia, with an inverted T4/T8 lymphocyte ratio (designated pre-AIDS), 3 of 4 clinically normal mothers of juvenile AIDS patients, 3 of 8 juvenile AIDS patients, 13 of 43 adult AIDS patients with Kaposis sarcoma, 10 of 21 adults AIDS patients with opportunistic infections, and 1 of 22 clinically normal homosexual donors. Importantly, this homosexual donor, from whom HTLV-III was isolated, developed AIDS six month after the virus isolations were performed. This means that these isolations were performed not later than September of 1983. HTLV-III could not be isolated from any of 115 clinically normal heterosexual donors.On May 4One paper describeIn a second accompanying paper  antibodyThe French group did not detect gp41 in their immune precipitation studies using purified LAV. Their inability to detect this protein in their ELISA or immune precipitation experiments is probably the main reason that their positive scores with AIDS and pre-AIDS sera were so low. HIV is an enveloped virus and hence fragile. Most certainly they had lost the virus envelope in their purification of the virus.Taken together, these two papers from Gallo's group for the first time convincingly demonstrated that AIDS was caused by a new human retrovirus distinct from HTLV-I and HTLV-II. It also provided with a blood test (ELISA) by which blood donors could be screened and a confirmation assay (Western blot) for those who tested positive in the ELISA. The authors speculate that the virus they found could well be the same virus that was previously detected by the French group, but direct comparisons had not yet been performed.A third paper.  describeThe fourth of the Gallo Science papers  describeLastly, a photomontage of electron micrographs of HTLV-I, HTLV-II, and HTLV-III with budding virus particles, immature virus particles and mature virus particles is shown. Although the budding and immature virus particles are very similar for all three viruses, the mature HTLV-III viruses are distinctive from those of HTLV-I and HTLV-II.th, Montagnier's group[th Gallo's group[th of July in Science submitted May 4th 1984. This paper was from Donald Francis group at the Center for Disease Control, Atlanta, in collaboration with Montagnier's group at Pasteur. The assay they used was based on immuno-precipitation. The positive scores were: 51 of 125 (41%) of AIDS patients; 81 of 113 pre-AIDS patients, 0 of CDC workers, and 0 of 189 random blood donors. Of 100 blood samples collected in 1978 from homosexual men in San Francisco, only one was positive as opposed to 12 of 50 such sera collected in 1984.Three more papers on antibody reactivity to LAV/HTLV-III in patients with AIDS or pre-AIDS were published in the summer of 1984. June 9r's group publisheo's group publish o's group publisheth issue of Science (submitted April 6th 1984), Donald Francis' group in collaboration with Montagnier's group reported on the isolation of a retrovirus from a blood donor-recipient pair with AIDS [In the July 6ith AIDS . In an eth 1984 Jay Levy in San Francisco[st) reporting that using the Gallo protocol they had isolated a retrovirus with lenti retrovirus type morphology designated ARV for AIDS associated retrovirus in 22 of 45 patients with AIDS. Positive virus cultures were also received from 5 of 10 patients with lymphadenopathy (pre-AIDS), 3 of 14 male sex partners of AIDS patients, 2 of 9 clinical healthy homosexual men, and 1 of 23 clinically healthy heterosexual men. When tested in immune fluorescence with slides containing acetone fixed cells infected with ARV, HTLV-I or LAV, 78/86 (91%) of AIDS patient's sera were positive to ARV infected cells, 22 of 40 (55%) to LAV, and 8 of 60 (13%) to HTLV-I. None of 56 controls reacted to any of the virus-infected cells. The fixed ARV infected cells were from a cell line (HUT-78) successfully established to continuously produce ARV.On August 24Francisco publishest, 1987, when President Ronald Reagan and French Prime Minister Jacques Chirac signed an agreement to settle the arguments. The financial outcome of the agreement, however, did not turn out to the satisfaction of the French, and when it became clear that the US patented blood test was based on a laboratory contamination of a French virus the deal was re-negotiated in 1994. It should be stated right away that neither of the scientists at the time stood to gain from respective patent.Right before the first public announcement by Barré-Sinoussi at a conference at Cold Spring Harbour in May of 1983 of the Pasteur group's findings, the Pasteur Institute filed a patent for the virus they had isolated. Before going public with the four Science papers, the NIH filed for a patent for the blood test described in one of the papers to be published in May of 1984. The United States patent office quickly allowed the American patent, shortly to be followed by allowances from European patent offices, and a number of American companies started to produce and sell blood tests. The approval of the Pasteur patent was delayed, principally because the French had not reduced their patent to practice, i.e. showed that they had a working blood test in the patent application. This led to a patent feud between the NIH and the Pasteur Institute starting in August of 1985. To solve this feud, the governments of both countries had to become involved. The patent fight came to an end on March 31BRU to Gallo in July of 1983. In May of 1984 Gallo's coworker Sarngadharan brings one of Gallo's five HIV strains (HTLV-IIIB) that grew well in a continuous cell line to Montagniers laboratory in Paris. In July of 1984 Montagnier sends Gallo a second sample of LAVBRU since Gallo had complained that the first didn't grew well at NIH. Gallo then found and reported[BRU (received in July of 1984) and HTLV-IIIB isolated on either side of the Atlantic Ocean where strikingly similar. Gallo's reaction to this was that Montagnier must have contaminated his cultures with the American isolate, i.e. that the Pasteur group had had a so-called "pick-up" of HTLV-IIIB into his poorly replicating LAVBRU. Gallo gave Montagnier a call, but the latter denied that this could have happened in his laboratory. Since the LAVBRU obtained by other laboratories, before HTLV-IIIB had been introduced to the Pasteur laboratory, had a genome more or less identical to the French isolate, it was concluded that the contamination must have happened in Gallo's laboratory. Gallo found this very strange, since LAVBRU replicated very poorly and could not be transferred to a continuously producing cell line like they had achieved with HTLV-IIIB. On Sunday, November 19th, 1989, the Chicago Tribune published a 16 pages account by journalist John Crewdson of the discovery of HIV. The article concludes that HTLV-IIIB is LAVBRU. Crewdson implied in not so subtle words that Gallo had stolen the virus from the French. This started three separate investigations for scientific misconduct by Popovic and Gallo that didn't end until November of 1993.The ground for the feud was the following. Montagnier sent his first isolate LAV reported that HIVBRU received in NIH in 1983, Gallo found that it was different from the LAVBRU received in July of 1984. The original LAVBRU was as expected of the slowly replicating CCR5 co-receptor using genotype whereas LAVBRU from 1984 was of the rapidly replicating CXCR4 using genotype. In fact the 1984 LAVBRU was identical to LAVLAI. Thus, the contamination had originally occurred in the Pasteur laboratory. According to Montagnier at least six other laboratories received the LAI sample (under the name BRU) from his group and experienced the same contamination. [Mycoplasma pirum contamination of the cultures infected with LAVLAI. In his review "A history of HIV discovery" in Science. [M. pirum. As mycoplasmas are common contaminents of cultured cells, an infectious pseudotype virus (LAI associated with M. pirum) may have caused several contaminations between 1983 and 1984 in different laboratories".The explanation came in 1992. Sequencing the original isolate LAVination. . MontagnScience.  MontagniBRU had contaminated a pool of viruses from different AIDS patients. Pooling viruses was the idea of Mika Popovic in order to get the "survival of the fittest" to grow out in the continuous cell line H9, a subclone of the HUT-78 cell line. The virus that grew best was named IIIB because it was from the B-pool of two pools in culture.In Gallo's laboratory LAVB for the blood test and for further characterization of the virus. Had he chosen a Haitian strain, which he also had growing long term in the laboratory at the time, we now know that he would have chosen a virus, which was as much of a prototype strain for HIV-1.Many probably thought that the finding that a contamination had taken place already in the Pasteur laboratory was "convenient" for Gallo. However, to "steal" the French virus Gallo must have had a motive. One would have been that they couldn't culture any virus from AIDS patients and were becoming desperate. However, Gallo had already recognized that the French group was first to isolate a new retrovirus from AIDS patients. More so he endorsed the publication of the first Pasteur paper, which  claimed so. Secondly, Gallo's group already had 48 (sic!) isolates many growing short term in their laboratory of which five were growing in continuous cell lines,26. GallBRU had not yet been growing well enough to make possible comparisons with IIIB when in fact a technician of Popovic's had done so. These charges were later dropped by the ORI. In its decision on the Popovic case the Departmental Appeals Board's Research Integrity Adjudications Panel writes: "One might anticipate that from all this evidence, after all the sound and fury, there would be at last a residue of palpable wrongdoing. This is not the case". It is safe to say that whatever Gallo claimed he had, he had.It has been questioned whether Gallo indeed had all those isolates. Considering that Gallo published this and that he and his laboratory was scrutinized for almost five years by three different investigations, had Gallo not had those isolates he would for sure have been found guilty of scientific misconduct and expelled from the NIH. Going through 13 foot high pile of Gallo's lab records including laboratory note-books, some 10,000 man hours of interviews with laboratory personal and other witnesses, all the Office of Research Integrity  could come up with in criticism was for Mika Popovic that he wrote "ND" in two occasions in one published table (in paper 25), and found him therefore guilty of scientific misconduct. The table legend didn't define "ND" and it was the ORI's understanding that "ND" meant, "not done" and that Popovic indeed had performed the experiment. However, Popovic insisted that by "ND" in his notebook he meant, "not determinable". The paper was written while Popovic was on holiday back in Czechoslovakia. Following Popovic's appeal to the Research Integrity Adjudications Panel the decision of ORI's was reversed. Gallo was temporarily criticized by the ORI for having written a sentence in the discussion of the same paper that LAVThere is no doubt that Luc Montagnier's group at the Pasteur Institute in Paris was the first to isolate the causative agent of AIDS. Montagnier, however, got the idea to try to isolate a retrovirus indirectly from Robert Gallo and Myron Essex. The protocols he used for virus isolation and RT detection were developed by Robert Gallo and the reagents he used to discriminate the new virus from HTLV-I and HTLV-II were obtained from Robert Gallo. Moreover, it is well known that Francoise Barré-Sinoussi had spent time in Robert Gallo's laboratory to learn to culture lymphocytes. Robert Gallo was the first to convincingly show that the new human retrovirus (HIV) was the causative agent of AIDS, and the only one at that. He also was also the first to provide a blood test to screen blood donors for HIV infection. The rapid implementation of the latter in the US and Europe probably saved hundreds of thousands of lives.


The Codon Adaptation Index (CAI) was first developed to measure the synonymous codon usage bias for a DNA or RNA sequence. The CAI quantifies the similarity between the synonymous codon usage of a gene and the synonymous codon frequency of a reference set. that includes a complete set of utilities related with the CAI. The server provides useful important features, such as the calculation and graphical representation of the CAI along either an individual sequence or a protein multiple sequence alignment translated to DNA. The automated calculation of CAI and its expected value is also included as one of the CAIcal tools. The software is also free to be downloaded as a standalone application for local use.We describe here CAIcal, a web-server available at The CAIcal server provides a complete set of tools to assess codon usage adaptation and to help in genome annotation.This article was reviewed by Purificación López-García, Dan Graur, Rob Knight and Shamil Sunyaev. Ever since a relatively high number of DNA sequences were publicly available in databases, several statistical analyses addressing DNA composition have been performed. One of the parameters that first interested the scientist was codon usage . It was The most important contribution that we aim to provide with our server is to tie together several features, previously existing but disseminated throughout the Internet, and some new features related to CAI calculation and analysis, and to implement them into a single and easy-to-use web site., calculates the CAI for a group of sequences using different reference sets and includes a complete set of tools related with codon usage adaptation, e.g. the representation of the CAI along a sequence or multialignment and the estimation of an expected CAI value (eCAI). CAI is calculated following the original method proposed by Sharp and Li [The CAIcal web-server, freely available at p and Li  but usinp and Li . In the The inputs for the server depend on the calculation to be performed. The basic inputs for calculating CAI are the query sequences, the reference set and the genetic code used for translation. The query sequences must be DNA or RNA sequences in fasta format. The server first checks whether the query sequences are a DNA or RNA region that codifies a protein. The reference set required to calculate the CAI can be introduced in a variety of formats, including that of the Codon Usage Database . A direcA number of programs and servers that calculate CAI for a gene or a group of genes are available elsewhere, such as CodonW, EMBOSS , CAIJavaThe server first provides a number of basic calculations that are also available elsewhere:(i) The absolute and synonymous codon usage of a group of DNA sequences and other useful parameters such as length, total G+C content and G+C content at the three codon positions, and the effective number of codons .(ii) The CAI of a DNA sequence or group of sequences. This index measures the adaptation of the synonymous codon usage of a gene to the synonymous codon usage of up to two reference sets that can be chosen by the user.The new features incorporated in this server are:(iii) An expected value of CAI  is deter(iv) The weight of each codon, i.e. the frequency of codon use compared to the frequency of use of the optimal codon for that amino acid in the reference set, can be graphically represented along a DNA sequence using a sliding window defined by the user. This result provides an intuitive visualisation of the changes in the CAI throughout the input and identifies discontinuities that might correlate with informational and/or operational features of the DNA sequence. The CAIscan tool of the CAI Analyser package  allows a(v) A graphical representation can be made of the weight of each codon along a multiple protein alignment that has been translated to a DNA alignment using a unique reference set for all the sequences of the alignment or using a reference set for each sequence. The inputs for this option are a protein multialignment in clustal format, the DNA sequence of each of the sequences of the multialignment with the same identification field between the DNA and protein sequences and one or more codon usage tables to use as reference sets. This result provides a graphical display that enables the protein sequence alignment to be correlated with the informational/compositional content of the DNA sequence that encodes them.The options available in the server are summarized in Figure in silico. The E4 PVs genes available in the databases are therefore very different in length and similarity. Although the genomes of many PVs have been sequenced, information about the expression of their genes or cDNA sequences is only available for a few of them. One of these is HPV1. In this case, the annotation of the HPV1 E4 gene is confirmed by mRNA data [The CAIcal was used to annotate the genomic discontinuity in the E4 gene of human papilomavirus 1 (HPV1). Papillomaviruses (PVs) are a family of small dsDNA viruses that cause a variety of diseases including cervical cancer. The genome of PVs is modular with three different regions, each of which has a different evolutionary rate ,20. ThesRNA data . HoweverRNA data ,20,27, iThe CAIcal server provides a complete set of tools to assess codon usage adaptation and helps to annotate genomic discontinuities such as the donor splicing site of the E4 ORF of papilomaviruses.The authors declare that they have no competing interests.PP designed the server, made the programming task and drafted the manuscript. IGB participated in design of the server, prepared the example, and helped draft the manuscript. SG-V conceived and designed the server, coordinated the project and drafted the manuscript. All authors read and approved the final manuscript.. CAI values are useful for a variety of purposes going from genomic annotation and gene expression analyses to the detection of potential horizontal gene transfer events. Although, as pointed out by the authors, a number of freely available facilities providing the calculation of CAI exist already, this new set of tools offers the possibility to obtain some additional estimates. These include the calculation of expected CAIs from randomly generated sequences with the GC content and amino acid composition of the input sequences that can be compared then with the observed CAIs, as well as measurements of the weight of each codon and their graphical representation. An example of the possible utility of these CAI measurements to test and validate annotations is provided. I find that this group of tools accessible online will be useful to the scientific community. I hope that this web-based server will benefit and get improved with the progressive input and suggestions of a wide variety of users.This article describes a series of tools for the automatic calculation of the codon adaptation index (CAI) and related measurements from input and reference data that have been implemented in a web-based server A very simple and straightforward tool for dealing with codon usage. I have no other comments.et al. describe their CAIcal web server. CAI, the Codon Adaptation Index, is an important concept relating codon usage to gene expression. Although several software tools online already calculate CAI, CAIcal appears to offer a unique combination of functionality that is not easily duplicated using other tools.In this manuscript, Puigbo However, the tool in its current form would appear to be a relatively minor advance over existing tools, and I would strongly encourage the authors to consider an extensive overhaul of the software and the manuscript before publication. However, I think the present work contains the seeds of a useful contribution to the field and to the literature, and definitely encourage the authors to persevere, perhaps thinking more carefully about the target audience of the software and the paper.More attention needs to be paid to the specific contribution of this work if it is to be published as an independent piece of software. No feature of this tool really appears to be unique, e.g. the plots of CAI along a gene and codon-by-codon are also in Codon Analyser (as the authors note), many tools allow calculation of CAI against a reference set, etc.Authors' response: As we acknowledge in the manuscript, a number of tools are available elsewhere addressing different calculations around CAI. We consider however, that one of the strengths of the CAIcal server is to gather together pre-existing and new features into a single and easy-to-use web site, as you also note in your revision "CAIcal appears to offer a unique combination of functionality that is not easily duplicated using other tools". As an example, after the CAI value of a group of sequences has been calculated, the user can easily (with only a click of the mouse) estimate an expected CAI value for discerning whether the differences in CAI are statistically significant or whether they are merely artifacts. The graphical representation of the CAI value along each sequence can also be easily visualised. In addition, we also want to point out the usability of the server, used to denote here the ease with which people can employ a particular tool. Thus, several of the existing tools that allow calculation of CAI are not web-servers; other require some kind of installation or execution; and some of them provide easy calculations that lack in flexibility. Finally, the server allows to represent the CAI value along a protein multialignment back-translated to DNA, a feature currently not available elsewhere.Similarly, the calculations of the expected CAI values are delegated to another tool, E-CAI, that the authors have previously published, but this is not very clear from the description in the paper. If the sole contribution is to tie together several pre-existing features into a single web site, the authors need to make the case much more clearly that this combination will be of use to end users in a way that the individual pre-existing tools are not.Authors' response: We have added a new sentence in the paper clarifying this point.I think the source code of the standalone version needs a substantial overhaul before publication. It is full of large, error-prone tables of redundant information about genetic codes, for example, which should be dynamically calculated from a compact, standardized and easily verified source (e.g. the NCBI genetic code tables), is essentially without useful comments, mixes presentation and logic, and has many other indicators of poor coding style .Authors' response: Although the main aim of our work was to provide a web-based server for CAI analysis, this was a fair criticism. The source code needed an extensive revision of style and lacked useful comments that could guide the experienced user. We have largely rewritten it and it incorporates now numerous comments about the functionality of each different part. Thus, we have developed the local version 1.3. The source code in the standalone application follows a descendent algorithm rather than several separate applications have simply been pasted together. For the sake of clarity, we have included a file with a detailed description of the CAIcal functions  are the same. In addition, we have compared our results with the results using other existing programs and the results are not significantly different. A file with some tests we made is available from the web site in the FAQs section .The utility of the Monte Carlo approach is also somewhat unclear to me, as it appears that the expected CAI could be calculated analytically, along with confidence intervals, using the multinomial distribution. It is possible that this is not feasible for numerical reasons, but some justification of the approach would be useful.Authors' response: The expected CAI is calculated analytically from the CAI values of 500 randomly generated sequences with the same G+C content and amino acid composition as the query sequences. However, the Monte Carlo approach is used to generate the random sequences, not to calculate the expected CAI. In this sense, please see also Question 15 at the FAQs section of the server .I did not find the example especially compelling, but this is a relatively minor criticism and I understand that it is likely that the authors would want to publish any especially interesting results separately from the description of the tool itself. However, it might be interesting to try to reproduce a well-known conclusion from existing work to show how much easier it is with this workflow than with pre-existing tools. There are many examples in the literature as CAI is such a widely-used technique.The manuscript and the web site need substantial attention to the quality of the English. I have not corrected minor wording and grammatical errors in this version of the manuscript, but if the authors plan to publish this manuscript regardless of the above comments, I would definitely recommend careful attention to detail, and also removing formatting errors such as the text "Sub-heading for this section" on page 3. Overall, I think this is a good first attempt and could ultimately be revised into a useful contribution that is more suitable for publication.Authors' response: After receiving your comments and the comments of the three additional referees, we have decided to rewrite the code, to revise the manuscript and to publish it. We would like to thank you again for your comments. We think that it is not necessary any further overhaul of the software, as we agree that some changes were necessary in the manuscript and in the source code of the standalone version, and have accordingly been performed. We are glad to acknowledge that the code is easier to read after introducing the comments you suggested. Additional changes in the manuscript include also a second revision of the quality of the English following the recommendations by the NIH Fellows Editorial Board, and some clarifications. We sincerely consider that we have addressed the criticism you raised to the previous version of the manuscript.The revised versions of the manuscript and software are significantly improved.This manuscript presents a new online tool to compute codon adaptation index (CAI). Although there are several CAI calculators available online, this new server includes several additional features such as computation of expected CAI and visualization of changes in the CAI along the sequence. The authors also present an analysis of papilomavirus as an example of the server utility. In sum, the manuscript does not report any significant novel scientific findings but presents a tool potentially useful for the research community.


Human T cell lymphotropic type 1 (HTLV-1) was the first human retrovirus discovered and has been associated mainly with two illnesses HAM/TSP has an estimated incidence ranging from 0.25% to 1% after 30–40 years of incubation Despite the publication of several reviews regarding the pathogenesis or molecular biology of HTLV-1 To illustrate our viewpoint, we present one case of HAM/TSP in which several important issues are raised as singularities of the problem. A 29-year-old black woman born in Bahia in northeast Brazil has been living in São Paulo city for several years. When she was 20, she began complaining of lumbar pain and parestesis, initially in one leg and then in both, in addition to miccional urgency and constipation. After 3 years of illness and several visits to doctors, including basic and intermediate complexity level services, she was referred to our service as a suspected case of HTLV-1 disease. The diagnosis of HAM/TSP was confirmed. The patient was using a wheelchair most of the time. Pulse therapy with methylprednisolone was administered three to four times per year, with programmed hospitalization for at least 5 days. Her husband abandoned her, and she lives with her two children in a small one-bedroom house in an area difficult to reach by car. Her only income is the government minimum wage (US$250.00/month), and she is unable to attend a facility for physical therapy. She depends on her friends or relatives to bring her to the clinic appointments.The neurological disease TSP/HAM has no International Classification of Disease (ICD-10) code. In our clinical practice, we use the G04.1 code to designate this condition. This code means Tropical Spastic Paraplegia. In fact, many of our patients, when they need social security assistance, must present one report of ICD-10 by an attending physician. For this reason, we provide an ICD-10 closest to the clinical features of HAM/TSP. The creation of an ICD-10 code specifically for HAM/TSP would solve this problem and avoid any complications for physicians when they provide this report. Furthermore, this specific and more accurate code would also allow for the surveillance of the number of cases in the population, if this condition becomes an obligatory reportable condition by WHO in the future.We believe that the main reason for the low level of knowledge about HAM/TSP is the difficulty of diagnosis. The current guideline was recently updated by experts from several parts of the world Based on our clinical experience here in Brazil, we suggest that HAM/TSP be characterized as a chronic, slowly progressive, spastic paraparesis with bladder disturbances, absent or mild sensory loss and low back pain, and positivity for HTLV-1 antibodies in serum and cerebrospinal fluid Because of the symptoms and signs of HAM/TSP, most patients are referred to or are seen for the first time by neurologists, orthopedists, urologists, or other health professionals involved in the rehabilitation process . These professionals may have little knowledge of HAM/TSP or HTLV-1 infection, and a lack of information regarding this condition may delay the diagnosis. In fact, the mean time for correct diagnosis of HAM/TSP patients in our clinic was 7 years. Carod-Artal et al. found that 17% of the patients who were followed up in the most important rehabilitation hospital in central Brazil  had HAM/TSP diagnosis, with a mean time of diagnosis of 11 years This problem could be addressed by improving the teaching of HTLV during undergraduate training and medical residency in places where HTLV-1 is endemic. In addition, lectures and/or case discussions during national meetings of these specialties could provide better information for these professionals. Furthermore, guidelines such as those released by the US Centers for Disease Control as well as Brazilian HTLV guidelines should be updated and be universally accepted http://www.htlv.com.br). This Web site has information in three languages, Portuguese, Spanish, and English, and for the first year had financial support from the Ministry of Health of Brazil. There is considerable interest in this site, with an average of 5,000 visits per month.One good strategy for providing better information to the public as well as to health care providers is using the Internet. A Web site was created in 2003 with general information regarding HTLV infection and the associated diseases, as well as information for the general public in non-technical terms to address the most frequently asked questions  without adding further stigma on these individuals.