This study evaluated the effects of stroke on regulation of cerebral blood flow in response to fluctuations in systemic blood pressure (BP). The autoregulatory dynamics are difficult to assess because of the nonstationarity and nonlinearity of the component signals.We studied 15 normotensive, 20 hypertensive and 15 minor stroke subjects (48.0 ± 1.3 years). BP and blood flow velocities (BFV) from middle cerebral arteries (MCA) were measured during the Valsalva maneuver (VM) using transcranial Doppler ultrasound.R) and BFV (BFVR) signals. The BP-BFV phase shift was calculated as the difference between the phase corresponding to the BPR and BFVR minimum (maximum) values. BP-BFV phase shifts were significantly different between groups. In the normotensive group, the BFVR minimum and maximum preceded the BPR minimum and maximum, respectively, leading to large positive values of BP-BFV shifts.A new technique, multimodal pressure-flow analysis (MMPF), was implemented to analyze these short, nonstationary signals. MMPF analysis decomposes complex BP and BFV signals into multiple empirical modes, representing their instantaneous frequency-amplitude modulation. The empirical mode corresponding to the VM BP profile was used to construct the continuous phase diagram and to identify the minimum and maximum values from the residual BP (BPIn the stroke and hypertensive groups, the resulting BP-BFV phase shift was significantly smaller compared to the normotensive group. A standard autoregulation index did not differentiate the groups. The MMPF method enables evaluation of autoregulatory dynamics based on instantaneous BP-BFV phase analysis. Regulation of BP-BFV dynamics is altered with hypertension and after stroke, rendering blood flow dependent on blood pressure. Noninvasive assessment of cerebral vasoregulation is a major challenge in medical diagnostics and post-stroke care. Dynamic autoregulatory mechanisms adapt cerebral perfusion to spontaneous variations in intracranial and systemic pressure within a few heartbeats. Decline of cerebral blood flow that occurs with normal aging is further potentiated by presence of risk factors for cerebrovascular disease such as hypertension. Cerebral autoregulation is damaged by acute stroke, rendering cerebral blood flow dependent on blood pressure (BP) -3. The dContinuous monitoring of BFV using transcranial Doppler ultrasound enables assessment of dynamic autoregulation from spontaneous BP and BFV fluctuations , and durAccordingly, we: 1) introduce a new method, multimodal pressure flow analysis (MMPF), based on the Hilbert-Huang transformation , to quanStudies were conducted at the Autonomic Nervous System Laboratory at the Department of Neurology at The Ohio State University and at the SAFE  Laboratory at the Beth Israel Deaconess Medical Center at Harvard Medical School. All subjects signed informed consent, approved by the Institutional Review Boards. Subjects in the stroke and non-stroke groups were recruited from the Neurology Stroke Service and through advertisement. Demographic characteristics are summarized in Table 15 healthy normotensive subjects .20 patients with essential hypertension, controlled by antihypertensive medications (age 49.9 ± 2.0 years).15 subjects with the first minor ischemic stroke (18.3 ± 4.5 months after acute onset) (age 53.1 ± 1.6 years) including 9 subjects treated for hypertension (stroke-hypertensive) and 6 subjects who were normotensive (stroke-normotensive) with no BP treatment. Stroke subjects had a documented infarct on MRI or CT affecting <1/3 of the vascular territory with a minor neurological deficit . The side of the lesion was determined by neurological evaluation and confirmed with MRI and CT. The lesion was in the right hemisphere in 4 and in the left hemisphere in 11 subjects. The infarct types and locations were as follows: small vessel infarcts in 13 subjects and large vessel infarcts in 2 subjects. Cortical infarcts were found in 10 subjects and subcortical infarcts in 5 subjects. Normal carotid Doppler ultrasound study was required for participation. Patients with hemorrhagic strokes, clinically important cardiac disease including major arrhythmias, diabetes and any other systemic illness were excluded. All subjects were carefully screened with a medical history, physical and laboratory examination. Subjects with hypertension (with or without stroke) were treated with antihypertensive agents from the following categories . Antihypertensive medications were gradually tapered over 3 days and discontinued for 3 days prior to the study. Anticoagulants and other medications that did not affect cardiovascular or autonomic nervous system function were allowed.After instructions and several practice sessions, each subject rested for 5 minutes in the supine position. The subject was then asked to take a breath and expire forcefully through a mouthpiece with a small air-leak, maintaining for 15 seconds a pressure of 40 mm Hg monitored on a pressure gauge connected to the mouthpiece. All data were continuously acquired over the 5 minute period during which BP returned to baseline. The VM was repeated twice and the signal showing the more prominent VM oscillation by visual inspection was selected.2 was measured from a mask using an infrared end tidal volume CO2 monitor . The right and left MCAs were insonated from the temporal windows, by placing the 2-MHz probe in the temporal area above the zygomatic arch using a transcranial Doppler ultrasonography system . Each probe was positioned to record the maximal BFV and fixed at a desired angle using a three-dimensional positioning system attached to the light-metal probe holder. Special attention was given to stabilize the probes, since their steady position is crucial for reliable, continuous BFV recordings. BFV and all cardiovascular analog signals were continuously acquired at 200 Hz and exported at 50 Hz for off-line post-processing. Data were visually inspected and occasional extrasystoles and outlier data points were removed using linear interpolation. Fourier transform of the Doppler shift  was used to calculate BFV. BFVs in the MCA correlate with invasive measurements of blood flow with xenon clearance [The experiments were done in the morning or > 2 hours after the last meal. The electrocardiogram was measured from a modified standard lead II or III using a Spacelab Monitor . Beat-to-beat BP was recorded from a finger with a Finapres device , which is based on a photoplethysmographic volume clamp method. During the study protocol, BP was verified by arterial tonometry. With finger position at the heart level and temperature kept constant, the Finapres device can reliably track intraarterial BP changes over prolonged periods of time . Respiralearance , laser Dlearance  and posilearance . Since Mlearance .To quantify the dependency between cerebral blood flow and systemic pressure, we developed a novel computational procedure, called multimodal pressure-flow (MMPF) analysis. The MMPF analysis implemented the Hilbert-Huang transformation  techniquR  BP oscillation induced by the VM. We applied the empirical mode decomposition (EMD) technique developed by Huang et al.  The EMD VM signal to calculate its instantaneous phases. This phase was then used as a reference coordinate both for BP and BFV signals. From this point on, the term phase refers to the phase of the BPVM oscillation during the VM. Unlike the Fourier transform, the Hilbert transform does not assume that signals are composed of superimposed sinusoidal oscillations of constant amplitude and frequency. Real-world biological fluctuations, such as BP and BFV, are not stationary and are better described by analytical methods that can quantify variations of amplitude and frequency.In the next step of the MMPF analysis, we applied the Hilbert transform to the BPS(t) = ∑k Sk (t), where Sk are empirical modes that fulfill certain criteria of the original signal [Mathematically, the first two steps of the MMPF algorithm can be summarized in the following way: Any complex signal s(t) can be represented as the superimposition of more basic (simpler) components: l signal . For eacAk (t), and instantaneous phase, φk (t), can be calculated bywhere the Cauchy principal value is taken in the integral. Instantaneous amplitude, VM profile from the first peak at the beginning of the VM to the subsequent BPVM maximum forms a complete phase cycle from 0–360° over 30–40 seconds. We assigned the first peak at the beginning of the VM to phase 0°, the BPVM minimum during the VM to phase 180° and the subsequent BPVM maximum to phase 360°. To quantify the relationships between BP and BFV signals, we measured the BP-BFV phase shift, defined as the difference between the phase at the BPR minimum (maximum) value and the phase at the BFVR minimum (maximum) value. We have calculated phase values for all data points in this interval and, in principle, we can measure the phase shift at all point of the VM cycle. However, for simplicity, we only calculated the phase shift at the minimum and maximum of these two signals for statistical analysis. Since these BP-BFV phase shifts reflect dynamical changes in peripheral and cerebral vascular tone over the course of the VM, they can be used as a sensitive index of cerebral autoregulation dynamics in normal and pathological conditions.The BPWe also assessed autoregulation using a standard index, calculated using the second-order differential equation model proposed by Tiecks et al This modR and BFVR values and phases. Two-way analysis of variance was used for side-to-side comparisons of BFV between groups . For the group comparisons, we used the BFVR in the right and left MCAs for the normotensive and hypertensive groups compared to the BFVR in the stroke-side and non-stroke side MCA in the stroke group. Age was different between the groups (p < 0.003). However, age and stroke subtypes had no significant effects when included as co-variants in the analysis. Data are presented as mean ± SE.We used one-way analysis of variance for between-group comparisons of baseline, minimum and maximum BPR and BFVR signals are superimposed on the raw waveforms. For comparison, we show similar signals  for a 48 year old woman with the left temporal stroke in Figure R and BFVR for the right (non-stroke side) MCA and for the left (stroke side) MCA are shown in the bottom three panels as a function of the phase. With normal autoregulation, the BFVR changes precede BPR changes over the course of the VM. Therefore, the phase at the BFVR minimum is smaller than the phase at the BPR minimum. (Phase at the BFVR minimum for the right MCA = 129° and the left MCA = 112° vs. the phase at BPR minimum = 178°.) In contrast, with post-stroke cerebral autoregulation, the phase at the BFVR minimum is similar to the phase at the BPR minimum, suggesting that BFV is dependent on blood pressure. (Phase at the BFVR minimum for the non-stroke MCA = 173° and for the stroke MCA = 180° vs. the phase at BPR minimum = 185°).Figure R values and the phases at the BFVR minimum and maximum values for the right MCA in the normotensive and hypertensive groups and for the non-stroke side MCA in the stroke group. Figure R values and the phases for the left MCA in the normotensive and hypertensive group, and the stroke side MCA in the stroke group. Mean BPR values and corresponding phases are shown in panel C. The phase at BFVR minimum was different between groups for the right (non-stroke side) (p = 0.0005) and left (stroke side) (p = 0.004) MCAs. In the normotensive group, the phase at BFVR minimum was shorter than the phase at BPR minimum. In the stroke group, the phase at BFVR minimum was similar to the phase at BPR minimum. The phase at BFVR minimum was greater in the non-stroke (p = 0.002) and stroke (p = 0.03) MCAs, compared to the normotensive group. In the hypertensive group, the phase at BFVR minimum was also greater for the right (p = 0.0007) and left (p = 0.006) MCAs compared to the normotensive group. No significant differences were found between the stroke and hypertensive groups.Figure R minimum was similar between groups . Average BPR values were higher in the stroke and hypertensive groups compared to the normotensive group at baseline (p = 0.001), at BPR minimum (p = 0.054) and at BPR maximum (p = 0.0001)  Figure . AverageR maximum preceded the phase at BPR maximum  (p = 0.009) and left (stroke side) (p = 0.003) MCAs. In the stroke group, the phase at BFVR maximum was similar to the phase at BPR maximum. The phase was greater for the non-stroke side (p = 0.008) and stroke side (p = 0.03) MCAs, compared to the normotensive group. In the hypertensive group, the phase at BFVR maximum was also greater for the right (p = 0.005) and left (p = 0.009) MCAs compared to the normotensive group. The phase at BPR maximum was similar among groups .In the normotensive group, the phase at BFVm Figure . The phaR and BFVR minimum and between the phases at BPR and BFVR maximum for the right MCA in normotensive and hypertensive groups and for the non-stroke side MCA in the stroke group. The BP-BFV phase shifts at the minimum points were smaller in the stroke and hypertensive groups compared to the normotensive group (p = 0.009). The BP-BFV phase shifts at the maximum points were smaller in stroke and hypertensive groups compared to the normotensive group (p = 0.03). Figure R and BFVR minima was about 60 degrees corresponding to a time difference of about 3.6 seconds. In contrast, in the stroke and hypertensive groups, the time difference between BFV and BP phases was < 0.5 second.Figure The standard autoregulation index was not different between groups and between MCAs in both hemispheres Table . The ratR minima (p = 0.01) and maxima (p = 0.04) were greater in the stroke-normotensive group compared to the normotensive group. For the stroke side MCA, the phases at BFVR minima (p = 0.04) and maxima  were greater in the stroke-normotensive group compared to the normotensive group. The phases at BFVR minima and maxima were not different between the stroke-hypertensive and hypertensive groups for both MCAs. No significant differences were found between the stroke and non-stroke side MCA.In a subset analysis, we separated stroke-normotensive (N = 6) and stroke-hypertensive subjects (N = 9) and compared them to the non-stroke normotensive and hypertensive groups. For the non-stroke side MCA, the phases at BFVR and BFVR amplitudes were computed for each data sample to construct a continuous phase diagram. The BPR and BFVR profiles were similar over the course of the VM, but the phase relationships were different. The autoregulation indices, calculated using the standard methods, did not differentiate the groups.This study introduces a new technique, based on the Hilbert-Huang transformation ,18, termR minimum and maximum were smaller than BPR phases, reflecting an active vasoregulatory process. With delayed or impaired autoregulation, BFV becomes synchronized with blood pressure. In the stroke group, the BFVR and BPR phase diagrams were similar, suggesting that cerebral blood flow was entrained by systemic BP. In the stroke and hypertensive groups, BFV phases at the BFVR minimum and maximum were greater compared to the normotensive group. The BP-BFV phase shifts were smaller in the stroke and hypertensive group, compared to healthy controls.Cerebral vasoregulation compensates for rapid BP and BFV transitions over the course of the VM. A sudden and parallel increase in intrathoracic  and cereMethods evaluating dynamic cerebral autoregulation that use the Fourier transform-based coherence and transfer functions assume a linear relationship between stationary signals. Coherence, phase and gain derived from the transfer function of spontaneous BP and BFV fluctuations have been used to assess autoregulation. These analyses have shown a significant phase lead of cerebral BFV with respect to systemic BP ,20,21. HPrevious studies indicated bilateral impairment of the dynamics of pressure autoregulation after an acute ,3 and suThere are several limitations of this study: 1) The MMPF method was implemented for the VM, which is widely used for clinical autonomic testing. The VM allows noninvasive evaluation of pressure autoregulation, and testing can be completed in less than 5 minutes. However, the VM requires active patient cooperation, and may not be advisable in acute stroke settings where change in intracranial pressure should be avoided. 2) This study evaluated a population of younger subjects with minor stroke. A larger cohort is needed to determine the effects of ischemic stroke subtypes on the dynamics of autoregulation. 3) Age was different between groups; however, it had no significant effect on BP-BFV relationship in our analysis. Aging and cardiovascular risk factors exert significant but distinct effects on regulation of cerebral blood flow. The vasomotor reactivity to hypercarbia declines with aging and hypertension, while the dynamics of pressure regulation can be preserved . This efMultimodal pressure-flow analysis is a new method that enables evaluation of short nonstationary time-series not suitable for Fourier–based techniques. The MMPF method provides high time and frequency resolution and permits construction of instantaneous phase diagrams on a beat-to-beat basis. This method may be particularly useful as a complementary measure of cerebral autoregulation for the short and nonstationary time series acquired during provocative interventions such as the VM. Application of this method reveals that the regulation of BP-BFV dynamics is altered in both hemispheres after minor stroke, rendering blood flow dependent on blood pressure. Hypertension without stroke is also associated with delayed BP-BFV dynamics.BP = blood pressureR = residual BP calculated by MMPF methodBPVM = empirical mode of BP corresponding to the dominant VM oscillationBPBFV = blood flow velocity in the MCAR = residual BFV calculated by MMPF methodBFVEMD = empirical mode decompositionHHT = Hilbert-Huang TransformMCA = middle cerebral arteryMMPF = multimodal pressure-flow analysisVM = Valsalva maneuverThe author(s) declare that they have no competing interests.VN – designed the study, conducted the experiments, participated in the analysis and wrote the first draft of the manuscript. ACY – contributed to the MMPF development and analysis; LL – conducted the data and statistical analysis. ALG – contributed to the method application, data interpretation and manuscript preparation. LAL – contributed to data interpretation and manuscript preparation. CKP – designed and developed MMPF method, contributed to data analysis and manuscript preparation.


FADD (Fas Associated protein with Death Domain) is a key adaptor molecule transmitting the death signal mediated by death receptors. In addition, this multiple functional protein is implicated in survival/proliferation and cell cycle progression. FADD functions are regulated via cellular sublocalization, protein phosphorylation, and inhibitory molecules. In the present review, we focus on the role of the FADD adaptor in cancer. Increasing evidence shows that defects in FADD protein expression are associated with tumor progression both in mice and humans. Better knowledge of the mechanisms leading to regulation of FADD functions will improve understanding of tumor growth and the immune escape mechanisms, and could open a new field for therapeutic interventions. The FADD gene is located on chromosome 11q13.3 in humans and 7 in mice . For insHuman and mouse FADD genes have the same quite simple organization consisting of two exons  separated by a unique intron of approximately 2 kb. Interestingly, no cap site was reported on the human FADD mRNA [Human and mouse FADD proteins are very similar Figure . They coSince the first role ascribed to FADD was to transmit apoptotic signals through its interaction with death receptors expressed at the cell membrane, it was assumed that FADD protein was exclusively localized in the cytoplasm of the cell. However, a nuclear localization sequence (NLS) and a nuclear export sequence (NES) were recently identified in the human FADD protein Figure , and accin utero at day 12.5 of development, due to underdevelopment, abdominal hemorrhage, and cardiac failure. Moreover, FADD loss of function did not result in a lymphoproliferative disorder as observed in viable Fas mutant mice [The essential role of the FADD molecule was highlighted by generating FADD mutant null mice ,12. Indeant mice ,14. ThesFADD is the main signal transducing intermediate adaptor molecule of several death receptors including Fas, TNF-R1 (tumor necrosis factor receptor 1), DR3 (death receptor 3), TRAIL-R1 , and TRAIL-R2 (DR5) ,12,15. AControl of FADD recruitment to the DISC can occur following several mechanisms depending on the cell type and the death receptor . The besAll the main death receptors described up to now require FADD adaptor for transmitting their apoptotic signal. Consequently, FADD is a central protein that controls multiple essential cellular processes including cellular homeostasis and elimination of pathological cells, particularly during the course of an immune response.in vivo, and increasing evidences suggest that DEF could be artefactual structures resulting from protein over-expression. As a consequence, the ability of endogenous FADD to aggregate and form DEF in normal situation should be reconsidered.Formation of cytoplasmic death effector filaments (DEF) by oligomerization of DED-containing proteins, including FADD, is responsible for death receptor independent cellular apoptosis . Indeed,-/- mice presented a lack of thymocytes compared to wild type animals, with few or no CD4+ CD8+ double positive thymocytes remaining [-/- T lymphocytes [-/- T lymphocytes entered the cell cycle upon mitogenic stimulation, but died during progression through the cell cycle [Beside being a main death adaptor molecule, FADD is also required for T cell proliferation. The first evidence of this property of FADD came from observations made in chimeric FADD knockout mice. Five-week-old chimeric FADDemaining . Moreoveemaining ,26-30. Tphocytes ,29,30. R-/- lymphocytes, resulting in spontaneous entry and progression through the cell cycle of 10% of freshly isolated FADD-/- T cells (as compared to less than 2% of wild type T cells) [In addition to impairing survival during cell division, FADD deficiency also leads to a dysregulation of the cell cycle machinery . The patT cells) .in vivo [+ CD8+ thymocytes and defective progression through the cell cycle [The mechanisms responsible for FADD regulation of cell cycle progression are not fully understood. However, the phosphorylation of the 194 human and 191 mouse Ser of the protein (Figure in vivo . Replacein vivo , includill cycle ,31.Tumor cells are constantly cycling cells. Although it does not seem to directly affect the cell cycle progression, FADD phosphorylation at Ser 194 sensitizes these cells to reagents that induce G2/M arrest such as the Taxol anticancer drug . In huma+/+ RAG-1-/- mice did not [-/- RAG-1+/+ or FADD-/- RAG-1+/- mice, demonstrating that absence of FADD expression was necessary but not sufficient to induce tumor development in this model [in vivo.The role of the FADD adaptor in cancer was initially demonstrated by generating RAG-1 deficient transgenic mice that target expression of a FADD dominant negative mutant in lymphocytes. With age these mice developed thymic lymphoblastic lymphoma, whereas FADD did not . Moreoveis model . These rUsing a mouse model of thyroid adenoma/adenocarcinoma, we showed spontaneous disappearance of FADD protein expression during the course of tumor development . The so de novo AML treated homogeneously, and found that leukemic cells of 2/3 of patients at diagnosis expressed low or no FADD protein [We recently showed that absence of FADD protein expression in cancer cells is also a relevant phenomenon in human malignancies . We look protein . Moreove protein . Importa protein . As a coThe fact that absence of FADD expression was found in different types of tumor cells both in mice and humans strongly suggested that absence of FADD contributed to tumor development. Indeed, lack of FADD protein can confer numerous advantages on pathological cells, which predominantly result in tumor survival/growth gain Figure .-/- TFC as well as FADD-/- AML cells were resistant to Fas- and TNF-α-mediated apoptosis [in vitro, a process requiring FADD molecule expression [Fas, TRAIL-Rs, TNF-R1, DR3, and potentially other receptors use FADD adaptor for transmitting the death signal. Thus, absence of FADD expression in tumor cells must confer multiple resistance of these cells to death receptor cytotoxicity. In agreement with this assumption, we observed that FADDpoptosis , and unppression -42,44,45As described above, absence of FADD allows co-expression of death receptors and ligands without inducing autocrine or paracrine apoptosis of tumor cells. For instance, although the Fas receptor was expressed at all stages of thyroid tumor development in gsp mice, FasL expression was gained with a high expression in adenomatous/adenocarcinomatous glands . Using t+ FADD- adenomatous/adenocarcinomatous thyroid from gsp mice, as well as on human AML cells, may allow both autocrine and paracrine proliferation of these cells [Since the tumor counter-attack hypothesis cannot apply to all types of cancer cells, one could wonder whether other benefits of death ligand expression by tumor cells exists. Previous reports demonstrated that Fas signaling could lead to proliferation instead of apoptosis, depending on the cell type and the environmental conditions -58. For se cells ,37 (FiguAbsence of FADD expression could confer multiple growth advantages on cancer cells Figure , and is Molecules implicated in FADD regulation of expression also represent new therapeutic targets. However, very little is known about the mechanisms leading to absent/low FADD protein expression in tumor cells. In SCC-9 and SCC-25 carcinoma cell lines, carboplatin upregulated FADD protein expression by increasing FADD mRNA . HoweverFADD is mainly known as a key adaptor molecule for numerous death receptors. However, increasing evidences have shown that FADD is a much more complex molecule implicated in apoptosis, survival, cell cycle progression, and proliferation of the cells. Therefore, FADD plays a central role in the frightening control of cell death and life. As a consequence, a defect in the FADD molecule can contribute to the development of diseases, and particularly cancer. Absence of FADD protein expression is a marker of tumor development in the mouse, and a prognostic factor for poor response to chemotherapy in humans. Since FADD deficiency could contribute to several malignancies, in view of its almost ubiquitous pattern of expression, study of the role of FADD in tumor development, growth, and resistance to treatment, and understanding how the expression of this puzzling molecule is regulated, are targets that merit further investigation.LT conceived the review and drafted the manuscript. GC participated in conceiving the review. AB and GC participated in the preparation of the manuscript. All authors read and approved the final manuscript.


Health-Related Quality of Life (HRQoL) measures are becoming increasingly used in clinical trials as primary outcome measures. Investigators are now asking statisticians for advice on how to analyse studies that have used HRQoL outcomes.HRQoL outcomes, like the SF-36, are usually measured on an ordinal scale. However, most investigators assume that there exists an underlying continuous latent variable that measures HRQoL, and that the actual measured outcomes (the ordered categories), reflect contiguous intervals along this continuum.t-test and linear regression that assume Normality and constant variance may not be appropriate. For this reason, conventional statistical advice would suggest that non-parametric methods be used to analyse HRQoL data. The bootstrap is one such computer intensive non-parametric method for analysing data.The ordinal scaling of HRQoL measures means they tend to generate data that have discrete, bounded and skewed distributions. Thus, standard methods of analysis such as the t-tests, linear regression, summary measures and General Linear Models.We used the bootstrap for hypothesis testing and the estimation of standard errors and confidence intervals for parameters, in four datasets (which illustrate the different aspects of study design). We then compared and contrasted the bootstrap with standard methods of analysing HRQoL outcomes. The standard methods included t-test and linear regression are robust to the violations of assumptions that HRQoL data are likely to cause . While particular to our datasets, these findings are likely to generalise to other HRQoL outcomes, which have discrete, bounded and skewed distributions. Future research with other HRQoL outcome measures, interventions and populations, is required to confirm this conclusion.Overall, in the datasets we studied, using the SF-36 outcome, bootstrap methods produce results similar to conventional statistical methods. This is likely because the  Health Related Quality of Life (HRQoL) measures are now frequently used in clinical trials and health services research, both as primary and secondary endpoints . InvestiHRQoL measures such as the Short Form (SF)-36, Nottingham Health Profile (NHP) and European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 are described in Fayers and Machin  and are This ordinal scaling of HRQoL measures means they generate data with discrete, bounded and non-standard distributions, which may lead to several problems in determining sample size and analysing the data ,3. SinceThe bootstrap ,5 is a dt-tests; multiple regression/analysis of covariance (ANCOVA) models fitted via ordinary least squares (OLS); response feature analysis or summary measures such as the Area Under the Curve (AUC) [Conventional methods of analysis of HRQoL outcomes are extensively described in Fayers and Machin  and Fairve (AUC)  and Geneve (AUC) ] fitted ve (AUC) .The remainder of this paper is structured into the following sections. The SF-36 HRQoL outcome is briefly described in Section 2. Section 2 also describes how the bootstrap can be used for hypothesis testing and confidence interval estimation. Section 2 ends with a description of the four example datasets. The results of conventional methods of analysis and bootstrap methods are compared in Section 3. Other issues, such as withdrawals and study sizes are discussed in Section 4. The final section (5) ends with a summary and conclusions.to pull oneself up by one's bootstraps". The phrase is thought to be based on one of the eighteenth century Adventures of Baron Munchausen by Rudolph Erich Raspe. The Baron had fallen to the bottom of a deep lake. Just when it looked like all was lost, he thought to pick himself up by his own bootstraps !bootstrap sample, and each provides an estimate of the parameter of interest, e.g. mean. The "with replacement" means that any observation can be sampled more than once in each bootstrap sample. It is important because sampling without replacement would simply give a random permutation of the original data, with many statistics such as the mean being exactly the same  each in. The standard Normal based intervals are symmetrical about , and hence have shape = 1.00. Shape is a measure of skewness of the CI about the point estimate. A shape > 1.00, implies the CI is positively skewed, with a long tail to the right, whereas shape < 1.00 implies the CI is negatively skewed.'Shape' measures the symmetry of the interval about the point estimate test statistic and a null distribution for the data under the null hypothesis. Given these, we generate bootstrap values of the test statistic under the null distribution for the data and estimate the achieved significance level (ASL) by calculating the proportion of the bootstrap values of the test statistics, which are greater than or equal to the observed value of the test statistic from the original data.Bootstrap methods can also be used for hypothesis testing. The two quantities that we must choose when carrying out a bootstrap hypothesis test are a Several bootstrap test statistics are available for comparing the distribution of sample data in two independent groups. In considering a bootstrap hypothesis for comparing the two means, there is no compelling reason to assume equal variances and so we do not make this assumption. We used a bootstrap test statistic for comparing two means that use only the assumption of a common mean, under the null hypothesis .Table We were interested in seeing whether or not there was a difference in HRQoL in OA patients after TKR surgery compared with pharmacologically treated patients. From previous studies using the SF-36 we know that HRQoL varies with age and gender ,20. SincThe analysis involved using OLS to fit the multiple regression model with six month follow-up HRQoL as the outcome variable and age in years at baseline; gender of the patient ; baseline HRQoL and treatment group variable  as explanatory covariates. The group regression coefficient estimate represents the difference in six-month follow-up HRQoL between the Rheumatology Clinic and TKR Surgery groups after adjustment for the patient's age, gender and baseline HRQoL. A positive value for the regression coefficient indicates the Surgery group has a better mean HRQoL at six months follow-up than the Clinic group after adjustment for the other covariates.Table The regression analysis suggests that at six month follow-up TKR surgical patients have significantly better HRQoL than Rheumatology treated clinic patients on five dimensions of the SF-36  after adjustment for age, gender and baseline HRQoL. As can be seen from Table Qualitatively all of the intervals from the three methods either include or exclude zero so the interpretation of the group regression coefficient is the same. Therefore, again in this example dataset, there appears to be little advantage in using bootstrap case or model based re-sampling to estimate standard errors and confidence intervals compared to conventional methods of confidence interval estimation from the OLS multiple regression model.We are interested in comparing the HRQoL over the one-year follow-up between the Home and Clinic treated groups. The two groups were well matched at baseline for age, gender and HRQoL, except for the RE dimension of the SF-36, where there was some reliable statistical evidence of a difference (p = 0.052).The overall HRQoL of the leg ulcer patients over the 12-month study period (and three HRQoL assessments) can be summarised by the AUC. If we set the time units for the AUC calculation as a fraction of a year, then an AUC value of 100 implies the leg ulcer patient has been in "good health" for the entire 12-month follow-up period. Conversely an AUC value of 0 implies the leg ulcer patient has been in "poor health" for the entire 12-month follow-up period.t-test, the MW test and the bootstrap hypothesis test.Table 7 See  gives thp-values from the t-test and the ASL from the bootstrap hypothesis tests are very similar. None of the p-values for the eight SF-36 dimensions are less than 0.05. Therefore there is no reliable statistical evidence to suggest a difference in mean AUC between the Clinic and Home treated leg-ulcer patients. Only the results of the MW test on the RE dimension of the SF-36 provide (p = 0.071) any evidence of a difference in AUC distributions between the groups, although even this p-value is not statistically significant using the conventional cut-off of 0.05.The t-test with the bootstrap BCa limits. The lengths of the intervals are very similar, although the bootstrap BCa intervals tend to have a non-symmetric shape. All the estimated CIs include zero, again suggesting no evidence of a difference in mean AUC (HRQoL) between the Clinic and Home group patients in the Leg Ulcer study.The table also contrasts the Normal theory based CI estimates from the In the Early RA study, HRQoL assessment was carried out at 0, 8, 16, 24, 32, 40 and 48 weeks. With seven repeated HRQoL measurements, such as this, the best approach is to model the longitudinal data using GLMs.The modelling of longitudinal data takes into account the fact that successive HRQoL assessments by a particular subject are likely to be correlated. We used a marginal model with the Early RA data and used GEEs to estimate the regression coefficients. Marginal models are appropriate when inferences about the population average are the focus. For example, in a clinical trial the average difference between control and treatment is most important, not the difference for any one individual. In a marginal model, the regression of the response on explanatory variables is modelled separately from the within-person correlation.auto- or serial correlation, which is the strength of the association between successive longitudinal measurements of a single HRQoL variable on the same patient.The marginal model is an extension of the linear regression model used with the OA Knee data. Longitudinal models require the specification of the independent (sometimes termed random) if the off diagonal terms of the auto-correlation matrix are zero. The repeated HRQoL observations on the same subject are then independent of each other, and can be regarded as though they were observations from different individuals. On the other hand, if all the correlations are approximately equal or uniform then the matrix of correlation coefficients is termed exchangeable, or compound symmetric. This means that we can re-order (exchange) the successive observations in any way we choose in our data file without affecting the pattern in the correlation matrix. As the time or lag between successive observations increases, the auto-correlation between the observations decreases. A correlation matrix of this form is said to have an autoregressive structure .Several underlying patterns of the auto-correlation matrix are used in the modelling of HRQoL data. The error structure is Table The process of fitting marginal models using GEE begins by assuming the simple independence form for the autocorrelation matrix, and fitting the model as if each assessment were from a different patient. Once this model is obtained the corresponding residuals are calculated and these are then used to estimate the autocorrelation matrix assuming it is of the exchangeable (or autoregressive) type. This matrix is then used to fit the model again, the residuals are once more calculated, and the autocorrelation matrix obtained. The iteration process is repeated until the corresponding regression coefficients that are obtained in the successive models converge or differ little on successive occasions .Fayers and Machin  states,The results with the OA Knee data show that there is little to choose from between the case and model based resampling for the multiple linear regression model for estimating SEs and CIs. Since there was very little difference in the SE and CI estimates from the datasets used, for simplicity one would tend to favour a case based resampling approach. Indeed this was the resampling method for the longitudinal marginal model for the Early RA data.In the longitudinal Early RA for simplicity we used only a simple case based resampling for the marginal model and effectively carried out a stratified random resampling with replacement. That is we sampled with replacement blocks or clusters of each patients' repeated HRQoL responses. In theory, one should be able to use model or residual based resampling for the marginal model. The resampling procedure would be rather complex particularly for autoregressive autocorrelation structures and for unbalanced datasets, with HRQoL assessments at unequally spaced time points. One would have to take into account that the residuals were not independent and uncorrelated, and for the autoregressive correlation structure, that the correlation between residuals within a patient declined over time. This is a very interesting avenue and requires further exploration with other longitudinal datasets.Finally, are the results all that surprising or unexpected? We have shown that the use of bootstrap methods for analysis  appears to offer little advantage compared to standard methods in the four datasets studied.If we assume that there exists an underlying continuous latent variable that quantifies the HRQoL response of interest and that the goal of the analysis is to assess the magnitude of a treatment effect on the HRQoL outcome, by comparing means between groups. Then statistical theory says that if the distribution of the HRQoL data is Normal, so will be the distribution of the sample mean. Much more importantly, even if the distribution of HRQoL data is not Normal, as is frequently the case, that of the sample mean will become closer to a Normal distribution as the sample size gets larger. This is a consequence of the Central Limit Theorem (CLT) . The NoThus, if the investigator is planning a large study and the sample mean is an appropriate summary measure of the HRQoL outcome, then pragmatically there is no need to worry about the distribution of the HRQoL outcome and we can use standard methods to estimate sample sizes and analyse the data. Since dramatic effects are unlikely in HRQoL studies using the SF-36 as an outcome, large samples sizes are likely to be required ,3,6. So So our research using the SF-36 HRQoL outcome and the four datasets has shown that bootstrap methods appear to produce p-values, SEs and CIs similar to conventional methods. When the standard and the bootstrap methods agree, we can be more confident about the inference we are making and this is an important use of the bootstrap [Page 118, [t-test and OLS multiple regression are robust to the violations of assumptions that HRQoL data are likely to cause . While particular to our datasets, these findings are likely to generalise to other HRQoL outcomes, which have discrete, bounded and skewed distributions. They may not generalise to HRQoL studies with smaller sample sizes of less than 100 subjects. Future research with other HRQoL outcome measures, interventions and populations, is required to confirm this conclusion.In the datasets we studied, using the SF-36 as an outcome measure, bootstrap methods produce results similar to conventional statistical methods. This is likely because the Table 7 – Leg Ulcer study simple cross-sectional comparison of AUC for Home vs. Clinic GroupsClick here for file


Physicians' awareness of their important role in defusing the obesity epidemic has increased. However, the number of family practitioners who treat obesity problems continues to be low. Self-efficacy refers to the belief in one's ability to organize and execute the courses of action required to produce given attainments. Thus, practitioners who judge themselves incapable of managing obesity do not even try. We hypothesized that practitioners' self-efficacy and motivation would be enhanced as a result of participating in an interactive course designed to enrich their knowledge of obesity management.t-test. The interviews were analyzed by qualitative methods.Twenty-nine family practitioners participated in the course, which was accompanied by qualitative interviews. The difference between the physicians' pre-course and post-course appraisals was tested by paired p < 0.0005). A deeper insight on the practitioners' self-efficacy processes was gained through reflection of the practitioners on their self-efficacy during the interviews.Post-course efficacy appraisals were significantly higher than pre-course appraisals (Up-to-date information and workshops where skills, attitudes and social support were addressed were important in making the program effective. In tht survey  in 2000.Guidelines published in 1996 for the management of obesity recommended setting a modest weight loss and weight maintenance, rather than a targeted ideal weight, as goals . Lately,Many chronic health problems are exacerbated by unhealthy behaviors and harmful environmental conditions. From the psychological perspective, healthful lifestyles and environmental conditions may yield large health benefits. The widespread adoption of a healthier lifestyle rather than medical technologies has resulted in a substantial decline in premature mortality and morbidity . The medSelf-efficacy refers to the belief in one's ability to organize and execute the courses of action required to produce a given attainment . Such beSelf-efficacy is measured by the strength of a subject's beliefs in the ability to execute requisite activities. Social cognitive theory distinguishes among three basic processes of personal change: the adoption, general usage and maintenance over time of new behavioral patterns . EfficacTo our knowledge and after a literature search, no intervention studies have yet been conducted to change the self-efficacy of FPs in Israel towards treating obese people. Among other courses for which physicians usually receive credits towards their annual professional training, a course was offered by the Israeli Academic Medical Council. The course was initiated by the Israeli Association of FPs and recommended by the Medical Professional Journal of FPs in Israel. Registration in the course was open to all FPs. The present research was a preliminary study. This being the case, the first group of FPs who attended the new course participated in it. Though that group contained a small number of subjects, the importance of investigating a new program contribution to FPs self-efficacy for future research was evident.The objectives of the course were to enrich the knowledge of FPs with up-to-date information on obesity and to raise their motivation to treat it. The study objective was to determine if an interactive course would raise the self-efficacy of FPs to treat obesity. It was hypothesized that the self-efficacy of FPs would be enhanced as a result of participating in an interactive obesity-treatment course.Twenty-nine FPs  chose to participate in the course along with other Continuing Medical Education (CME) courses. All participants work as FPs in public health care clinics throughout the country.This study was based on a one group, pre-course – post-course test design, without a control group. It was accompanied by qualitative interviews to validate the results of the data analysis.The strength of the efficacy beliefs of the FPs to treat obesity was estimated by using a five point scale Likert type questionnaire containing nine items Table . The subThe Alpha Cronbach for the reliability of the tests was α = 0.88 for the pre-course test and α = 0.90 for the post-course test Table .The following aspects of structure validity were examined: (a) for the content aspect, the items matched the domain concept map. Final version was rewritten on the basis of experts' and researchers' comments. The items were finally presented in an nonsequential order to make subjects think while reading the questions and not relate to earlier answers; and (b) for the substantive aspect, FPs were interviewed regarding their self-efficacy to assure that the questions were clear and did not require rewording. The interview was a 30 min. open interview. A physician was given open questions such as: "Describe your feelings and thoughts of efficacy to treat obesity" or "How the self-control lectured help your efficacy perceptions". The subject was free to speak openly on the issue. The interview was actually a verbal reflection of thoughts and feelings of the subjects. It was recorded and later on transcribed by the researchers. The interview was analyzed by the constant comparative qualitative method of analysis ,21. Evert-test in order to compare pre and post strength of efficacy beliefs for treating obesity.The present study design used paired Participants answered the questionnaire before the start of the course and at the end of the last session, and a few days later participated in an open interview. The course was interactive and contained 12 clinical and psychological lectures given by experts in all subjects relating to obesity Table . Every lFPs filled in clinical report forms and presented the cases they treated and tools they used. The cases were discussed during the course and feedback was given by colleagues and experts. The course supplied the FPs with knowledge, skills and psychological tools such as: food and physical activity diaries, decision making tools, self-evaluation tools, self-report tools, self-monitoring tools, persuading tools, stimulus control tools and counter-conditioning tools, to treat obesity.Medical knowledge and skills were not examined. The course attempted to raise the self-efficacy of FPs by creating a supportive atmosphere, providing feedback, recalling successful experiences, learning from models, bringing patients into the workshops, discussing sociological and psychological problems and allowing reflection of thoughts and emotions. Studies have shown that reflection enhances metacognitive processes such as: self-monitoring, self-evaluation, self-reaction and attribution ,22-25. St-test  and the results of the qualitative analysis indicate that the criteria derived from the interviews matched those of the questionnaire. When speaking openly, FPs addressed the same issues that made up the domain theoretical concept map.Several researchers have suggested that quantitative efforts in the study of self-efficacy should be complemented by qualitative studies aimed at gaining a deeper understanding of attitudes and emotions -24. The The study showed that acquisition of knowledge and skills enable a person to meet personal standards of merit that tend to heighten beliefs of personal efficacy . In judgThe impact of the questions analyzed in this study extends beyond the issues asked by the questionnaire. New insights were gained through qualitative analysis: FPs analyzed the process they experienced during the course. They described how their efficacy beliefs were enhanced through reflection, feedback and the supportive climate of the course. Studies have shown that reflection enhances self-efficacy processes since self-appraisal of efficacy is structured by experience and reflective thought . FPs repIn summary, an effective program of widespread change in health practices includes four major components. The first is informational and intended to increase the physician's awareness and knowledge of the subject. The second involves development of skills needed to translate informed concerns into effective action. The third is aimed at building a robust sense of self-efficacy to support the exercise of control in the face of difficulties that inevitably arise. This is achieved by providing repeated opportunities for guided practice and corrective feedback in applying the skills in simulated situations that people are likely to encounter. The final component involves creating social support for desired changes. The present program contained all these components.The limitations of the study were the small number of participants and the reliance on one motivated group of FPs. These limitations result from the fact that this was the first course organized by the Israeli Association of Family Physicians on the subject of obesity. It was important to study the effect of the program on FPs self-efficacy for future continuing education and research.We recommend studying the effect of interactive courses on the lifestyle and weight loss of FPs. Future research should consider randomized samples from larger courses and analyses of the correlation between course success and actual FPs performance, FPs' self-efficacy and treatment outcomes e.g: BMI change, Lipids and BP. We also recommend studying the differences in obesity treatment outcomes and in general health feelings between patients whose FPs attended obesity courses and patients whose FPs did not.Practical recommendations for Continuing Medical Education planners would be to focus on workshops rather than on lectures, to enhance those processes the FPs felt less efficacious to go through and to have guidance of Endocrinology experts' as well as Psychology and Education specialists to improve communication with patients and their families in an effort to enhance motivation to loose weight. It is also recommended to bring patients to the workshops to reflect on the treatment they have received.The author(s} declare that they have no competing interests.SK and AF conceived and designed the study, participated in the collection, analysis and interpretation of data and drafted the manuscript. SV Participated in the statistical analysis, interpretation of data and draft of the manuscript. SP participated in the design of the study, data collection and interpretation. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


IGFBP3 gene; one upstream of the promoter and one intronic. We previously reported a hot spot of promoter hypermethylation of IGFBP-3 in human hepatocellular carcinomas and derivative cell lines. As the hot spot locates at the putative upstream p53 consensus sequences, these p53 consensus sequences are really functional is a question to be answered.Insulin-like growth factor binding protein (IGFBP)-3 functions as a carrier of insulin-like growth factors (IGFs) in circulation and a mediator of the growth suppression signal in cells. There are two reported p53 regulatory regions in the In this study, we examined the p53 consensus sequences upstream of the IGFBP-3 promoter for the p53 induced expression of IGFBP-3. Deletion, mutagenesis, and methylation constructs of IGFBP-3 promoter were assessed in the human hepatoblastoma cell line HepG2 for promoter activity.In vitro methylation of these p53 consensus sequences also suppressed IGFBP-3 expression. In contrast, the expression of IGFBP-3 was not affected in the absence of p53 overexpression. Further, we observed by electrophoresis mobility shift assay that p53 binding to the promoter region was diminished when methylated.Deletions and mutations of these sequences completely abolished the expression of IGFBP-3 in the presence of p53 overexpression. From these observations, we conclude that four out of eleven p53 consensus sequences upstream of the IGFBP-3 promoter are essential for the p53 induced expression of IGFBP-3, and hypermethylation of these sequences selectively suppresses p53 induced IGFBP-3 expression in HepG2 cells. Insulin-like growth factor binding protein (IGFBP)-3 is a multifunctional protein ferrying insulin-like growth factors (IGFs) in circulation and mediating growth suppression signals in cells. Serum IGFBP-3 protein (< 5000 ng/ml) complexes with IGFs and an acid labile subunit (ALS), to extend the half lives and modulate the bio-availability of IGFs . While aIGFBP-3 is produced in most tissues, but the main site of production is liver. It is produced by non-parenchymal cells  while parenchymal cells (hepatocytes) do not produce it under normal condition . We postet al. were not confirmed until now dCTP by end filling with Klenow fragment, and used for EMSA. Oligonucleotide DNAs , comprising the promoter sequence of -210/-149, were custom-made , annealed one hour at room temperature, and used as cold competitor in the assay. EMSA was performed in a 20 μl reaction containing 10 mM Tris (pH 7.5), 2.5% Glycerol, 50 mM KCl, 0.1 mM EDTA, 1 mM DTT, and in the presence of 50 ng/μl of double-stranded poly [d(I-C)], 5000 cpm (2 ng) of 32P-labeled probe DNA, and 2.5 μg of H2O2 treated MCF7 nuclear extract . The reaction mixture was incubated at 14°C for 20 min. 20 μl of each reaction mixture was then loaded onto a native 4 % polyacrylamide gel containing 0.5 × Tris-Glycine buffer , and electrophoresed at 14°C, 100 V for 1 hr. For the supershift assay, a p53 antibody  was used.278 bp of the et al. [We identified a hot spot of promoter hypermethylation in human hepatocellular carcinoma and its cell lines in the promoter upstream region of IGFBP-3 Fig. . As methet al. , but difTo confirm the importance of p53 binding sites between -210 to -150, we abrogated one of p53 binding sites by site-directed mutagenesis . But similar patterns compared to site directed mutation were observed. Although the expression of IGFBP-3 was slightly enhanced in the absence of p53 overexpression in the methylated construct, it was decreased in the presence of p53 overexpression in the methylated construct  were incubated with HWe have indicated that the p53 binding sites upstream of IGFBP-3 promoter are essential for its induction by p53, and that the induction can be suppressed by promoter hypermethylation in the human hepatoblastoma cell line HepG2. A working model of the p53 action in IGFBP-3 promoter upstream binding sites is summarized in Fig. IGFBP3 is a true tumor suppressor gene. IGFBP3 is a gene that is silenced by biallelic hypermethylation or hypermethylation and loss of heterogeneity (LOH) in human hepatocellular carcinoma. As reported recently [Our observations of promoter hypermethylation in human hepatocellular carcinomas and derivative cell lines (12), and the observations in this report strongly support the notion that recently , we haverecently , prostatrecently , kidneysrecently , and lunrecently , so on. recently , TGF-β /recently -25, or aIGFBP-3 is a ubiquitous, multifunctional protein, whose importance as a carrier of IGFs is evident. The absence of gross loss-of-function mutations of IGFBP-3 observed to date likely underscores its functional importance. We hypothesize that IGFBP-3 is a gene whose basal level of expression is essential for cell survival, but upon induction by p53, high levels of expression of IGFBP-3 induces apoptosis. Alternatively, IGFBP-3 may be a gene that is essential for cell survival when induced by growth hormones or IGFs, but functions as an apoptotic mediator when induced by p53.We observed slight base changes within p53 binding sites strongly influenced the induction of IGFBP-3 by p53. As SNPs that change the expression level of IGFBP-3 were within p53 binding sites , and it We identified the MyoD (-195/-186) and WT1 (-164/-156) binding sites as well as p53 binding sites at the hypermethylation hot spot in HCC by promoter analysis using TRANSFAC (v 4.0). As MyoD is a transcription factor that can induce apoptosis, and WT1 is a tumor suppressor gene, the existence of a binding site for these putative regulator genes in the hot spot of the promoter of IGFBP-3 suggest the possibility that these genes also use IGFBP-3 as a mediator of their actions.We conclude that four out of eleven p53 consensus sequences upstream of the IGFBP-3 promoter are essential for the p53 induced expression of IGFBP-3, and hypermethylation of these sequences selectively suppresses p53 induced IGFBP-3 expression in HepG2 cells. As IGFBP-3 functions downstream of many growth suppressors and its growth suppression effects are drastic, and as it is a small-sized secreted protein, the use of IGFBP-3 in tumor therapy will be a promising option.ALS; acid labile subunit, D-MEM; Dulbecco's modification of Eagle's medium DTT; dithiothreitol, EDTA; ethylenediaminetetra-acetic acid, EMSA; electrophoresis mobility shift assay, FCS; fetal calf serum, HCC; hepatocellular carcinoma, IGF; Insulin-like growth factor, IGFBP-3; Insulin-like growth factor binding protein-3, LOH; loss of heterogeneity, NaB; sodium butyrate, NaB-RE (sodium butyrate-responsive region), PBS; phosphate buffered saline, PCR; polymerase chain reaction, TGF-β; transforming growth factor-β, TNF-α; tumor necrosis factor-α, SEM; standard error of mean, SNP; single nucleotide polymorphism.The author(s) declare that they have no competing interests.TH carried out these studies and manuscript preparation, KN and YI participated plasmid construction and reporter assay, TS and HS participated the EMSA, EY helped the array study, TO participated in the design of the study and performed the statistical analysis. NK conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Honeybees signal the location of food sources to their hive- mates using a "dancing" flight pattern. Translating these patterns, scientists learn what bees perceive Experimental psychologists working with humans have a fundamental advantage over scientists studying the behaviour of other animals. This is because human subjects can give a verbal account of their experience. For example, they can report: ‘These two lights of different colour look equally bright’ or ‘This object looks further away than that one’. Such direct reports facilitate studying how information from the sensory periphery, that is, the sense organs that actually interface with the environment, is processed in the brain.Apis), which have a symbolic ‘language’ that nestmates use to communicate with each other about profitable food sources. By eavesdropping on this communication, scientists have recently obtained a unique perspective into the perceptual world of insects.The perceptual world of animals is often very different from that of humans. Many animals have sensory facilities that we humans lack; for example, insects can see ultraviolet and polarised light. But how they actually perceive the world, based on information from their sensory periphery, is often beyond our grasp. Because animals cannot describe their sensations, our access to them is often based on indirect psychophysical tests, where animal performance depends fundamentally on motivation and training method . HoweverHow does the dance language work? A triumphant scout bee returns from the field, and advertises the location of a newly discovered food source to nestmates. To do this, the forager performs a repetitive sequence of movements, the so-called waggle dance, which is one of the most intriguing examples of complex animal behaviour. The successful forager wiggles her abdomen provocatively from side to side, moving forward in a straight line. Then she runs in a half circle to the left, back to her starting point, performs another straight wiggle run along the path of her first, and then circles to the right . This paIn the 1940s, Nobel laureate Karl von Frisch deciphered the code hidden in this seemingly senseless choreography performed on vertical honeycombs in the darkness of the hive (reviewed in decreased by more than 50%! This clearly shows that bee perception of distance cannot solely be based on energy expenditure, since a longer flight that cost more energy was danced as a shorter ‘distance’ in the waggle run.But how do bees measure the flight distance that they communicate so precisely? It was previously thought they do this by measuring the energy used as they fly . HoweverSo what actually drives the bee odometer? Because the landscape bees pass in flight moves more slowly when bees fly at higher altitudes, The quality of information available about the velocity of the passing landscape will depend, of course, on the sensitivity of the eyes. The eyes of bees contain three types of colour receptors, with maximum sensitivity in the ultraviolet, blue, and green domains of the spectrum . Their ePLoS Biology, With so many external variables influencing distance estimation, it seems unlikely that the honeybee odometer would be very robust in natural conditions. Now, as reported in this issue of But there must be something else beside visual cues. Navigation over water, in the near absence of visible ground features, is extremely difficult without a reliable internal instrument measuring travel speed. This is the case even for us humans with sophisticated measuring devices: malfunctioning air speed indicators have been responsible for several airplane crashes into water, for example Birgenair Flight 301 and AeroPeru Flight 603 in 1996. decrease than when there is an increase in nectar quality of the same magnitude. Such asymmetric perception of gains and losses is well known in humans, where it has been linked to risk-aversive behaviour (Spying on honeybee dances can not only tell us about the cues they use for navigation, but also allows insights into the cognitive architecture that governs other aspects of bee behaviour, such as the assessment of flower quality. We've learned that bees prefer high over low nectar concentrations because this is reflected in their dances. When bees find better nectar, they dance more enthusiastically, that is, the number of dance circuits per minute increases . Howeverehaviour . Unfortu


An online educational module introduces students to concepts of quantitation and numerical simulations in developmental biology Driven by the massive datasets that are generated by “omics” research, the molecular life sciences are entering a new phase. This phase is characterised by a shift in focus from individual genes and their products to networks and whole systems ,2,3. ForThe successful application of quantitative tools in the molecular life sciences requires a good understanding of these tools and sufficient knowledge of the biological system under study. This can be achieved by collaboration between quantitatively trained scientists such as physicists on the one hand and biologists on the other. However, cultural differences hamper such collaboration : even atA more productive approach is therefore to prepare students better for the quantitative nature of the molecular life sciences by integrating quantitative thinking and biology in the life science curriculum. This can be achieved in various ways. For example, a curriculum could be developed in which mathematics, the physical sciences, and biology are introduced together . Howeverhttp://mbedu.fbt.eitn.wau.nl/demo_plos/). Some of the features of this module and the thinking that led to its development are quite general, and so we present the module here as a case study in the hope that this might inspire and guide others to create similar resources.As an example of the integration of quantitative teaching and cutting edge biology, we have implemented an educational module in which numerical simulations are used in an existing course on developmental biology  early during ogenesis . The genSecond, we designed the simulation environment in such a way that biology students with their existing mathematical background can build quantitative models and run numerical simulations themselves. In this environment , studentThird, we wanted to make sure that students would use the simulation environment effectively. Therefore, a clear goal is formulated when students enter the simulation environment. For example, they are asked to make a model that generates a Dpp gradient that fulfills a number of specific criteria, or simulates certain mutants. After running a simulation, students can view feedback that helps them draw conclusions or consider the next step to be taken. If a student's model, for example, generates a gradient that is too shallow, the student has to indicate which change in the model he expects to be useful for generating a steeper gradient. The student then receives an intuitive explanation of the usefulness of the given suggestion. If an increase in the synthesis of one of the proteins, Short gastrulation, is proposed, for example, feedback is given that this could indeed be useful, since there would then be more Short gastrulation available to transport Dpp, such that the gradient can become steeper. In this way, the student is stimulated to carefully consider each step and is provided with sufficient support to decide which is a useful step to follow. In addition, with this type of feedback, explanations are given that relate quantitative changes in the model to qualitative changes in its behaviour, which should increase the student's understanding of the behaviour of the biological model.We consider it important that students, while using the module, are not distracted too much by quantitative issues from the actual biological principles and facts. These have to be mastered in order to obtain a strong biological background. If students want to learn more advanced quantitative skills, they can still follow courses that are specifically aimed at this aspect.Quantitative analysis is already gaining importance in molecular life sciences. Therefore, it is desirable that curriculum changes are implemented in the short term. This poses challenges to faculties, especially to those whose members do not have much, if any, experience with the application of quantitative tools in their own research. Therefore, it may be useful to initially focus on the development of learning materials that are rather self-contained, such that their application requires relatively little competence in quantitative analysis from the teaching staff. If these materials are openly available they can be incorporated rapidly into existing courses, such that even the current generation of students may be better prepared to integrate quantitative thinking and biology in their future research.


There has long been a recognition that place matters in health, from recognition of clusters of yellow fever and cholera in the 1800s to modern day analyses of regional and neighborhood effects on cancer patterns. Here we provide a summary of discussions about current practices in the spatial analysis of georeferenced cancer data by a panel of experts recently convened at the National Cancer Institute. Recently, the North American Association of Central Cancer Registries (NAACCR) formed a Geographic Information Systems (GIS) Task Force that prepared a handbook to aid cancer registry staff in using GIS for the collection, analysis, and presentation of cancer registry data . The firThe purpose of the meeting was to provide guidance from experts in this field who have experience applying these methods to health data, acknowledging that opinion will change as the field continues to evolve. Consensus of recommendations for any technical field is difficult to achieve, but we have attempted to include contributors with a wide-ranging set of backgrounds and experiences in the hope that what is presented represents, if not clear "best practices", at least sound principles for the analysis of spatial health data. This paper introduces motivating ideas and provides a broad overview of an upcoming series of reports by subgroups of the attendees. A listing of initial reports appears in Table Interest in and use of GIS for health data has grown tremendously during the past decade. The recognition of local geographic influences on health date back at least to the development of spot maps of yellow fever and cholera in the earlier-to-mid 1800's . While wIn addition to the impact of the computer revolution is the increasing recognition that all health data are spatial, i.e., referenced to place. A recent call for more widespread use of GIS in the U.K. National Health Service points out that GIS could "act as powerful evidence-based practice tools for early problem detection and solving" . Many heWith the increasing interest in and availability of georeferenced health data comes the need for methods to properly analyze them, taking into account the spatial correlation of outcomes in nearby places. Recognition of spatial influences in statistical inference date back to some of the earliest developments of modern statistical methods leading, for example, to notions of randomized plot designs for agricultural field trials .Development of theoretical methods for spatially referenced data includes point process models ,14, spatApplication of spatial statistical methods is more common now that both GIS and spatial statistical software packages are widely available. While there are several texts focused on statistical methods for spatial health data -25, and We specifically focus on spatial and spatio-temporal statistical methods appropriate for observational human health data, not clinical trials or data from other types of designed experiments. A challenging but common problem with this type of data is the difficulty in obtaining accurate exposure and disease outcome data for the time and place most relevant to that disease. Health consequences are the result of a continuum of multiple and varied exposures which often occur over a long period of time and in various places. How can we capture this complex pattern of exposure over decades and, most important for the topic at hand, to what geographic location do we assign the exposure? A subgroup of meeting attendees discussed the problems of defining "place" and locating appropriate data in detail , offering no information on previous residences or workplace location(s). Accumulating and validating data required for analysis from these multiple sources usually takes longer than the analysis itself, where data validation plays an essential but time-consuming and often overlooked role.Of increasing concern in this field is protecting the privacy and confidentiality of the study subjects. While all researchers agree that this is important, it is often difficult to reconcile these needs with data needs for a proper analysis. In particular, spatial data analysis and mapping of results are often hampered by the lack of specific addresses. Data collection agencies and medical facilities are imposing increasingly strict requirements for data release and often only identify a place  to a broad administrative unit. For example, the recently enacted Health Insurance Portability and Accountability Act (HIPAA) often requires removal of geographic subdivisions smaller than the state, and the National Center for Health Statistics only releases death certificate data aggregated to the county level or for places with large populations. The reportable specificity of location is often not good enough to allow the analysis to answer research questions about the spatial patterns of the disease. Methods are currently being explored that would allow use of specific individual information in the analysis but would mask identifying characteristics in the results reported only at an aggregated level. In addition to such federal reporting restrictions, state and local governments may add additional regulatory requirements.).This said, such regulations need not prohibit spatial analysis of health data completely, rather they change the context within which such analyses may occur. For instance, mutually agreeable memoranda of understanding between analysts and agencies holding data often allow analysis of data with individual-level identifiers provided all reports include only aggregate results. Such memoranda also specify when, if ever, detailed maps of locations may be reported. As an example, the National Cancer Institute's Long Island Breast Cancer Study Project provides a protected environment (on site or remotely accessible) within which registered users may analyze (but not remove) sensitive georeferenced health data (for more information, see In addition to general concerns regarding the analysis of health data, the spatial data analysis of cancer data poses unique challenges. Most cancers develop over a period of 20 to 30 years and are a result of multiple exposures interacting with the individual's genetic susceptibility. Few Americans live in a single place for decades – migration presents the problem of which residential address to use for a case's location. Because latencies differ by cancer type and most likely by an individual's susceptibility, little guidance is available for this question. The rarity of cancer also causes a sparse data problem for analysis, both for detecting clusters in data with high spatial variability and for communication of results without violating confidentiality. John Snow's illustration of his theorized cause of cholera in London via a map of case residences was possible because of the large number of cases in a small geographic area with a single, precisely located exposure . The detDespite such concerns, important discoveries in cancer research do result from spatial data analysis. Although U.S. mortality data had been published in tabular form for many years, it wasn't until mortality rates were mapped in 1975 that spatial patterns emerged, such as the cluster of high oral cancer rates in southeastern states, later found to be due to smokeless tobacco use ,31. LateFinally, in order to ultimately improve public health, the results of the complex analyses of georeferenced cancer data must be disseminated to those in a position to take action, such as state epidemiologists and local cancer control specialists. This audience often needs to obtain statistical data quickly for rapid response to health problems and cannot be expected to have the technical expertise to understand the statistical detail underlying the methods. Statisticians must consider this audience and design maps and reports in such a way as to be easily accessible by them. A forthcoming article in the International Journal of Health Geographics by Bell, Hoskins, and Wartenberg Table  addresseIn closing, participants in the NCI workshop addressed a wide range of topics summarized in Tables


In the UK the health service is investing more than ever before in information technology (IT) and primary care nurses will have to work with computers. Information about patients will be almost exclusively held in electronic patient records; and much of the information about best practice is most readily accessible via computer terminals.To examine the influence of age and nursing profession on the level of computer use.A questionnaire was developed to examine: access, training received, confidence and use of IT. The survey was carried out in a Sussex Primary Care Trust, in the UK.The questionnaire was sent to 109 nurses with a 64% response rate. Most primary care nurses (89%) use their computer regularly at work: 100% of practice nurses daily, compared with 60% of district nurses and 59% of health visitors (p < 0.01). Access to IT was not significantly different between different age groups; but 91% of practice nurses had their own computer while many district nurses and health visitors had to share (p < 0.01). Nurses over 50 had received more training that their younger colleagues (p < 0.01); yet despite this, they lacked confidence and used computers less (p < 0.001). 96% of practice nurses were confident at in using computerised medical records, compared with 53% of district nurses and 44% of health visitors (p < 0.01.) One-to-one training and workshops were the preferred formats for training, with Internet based learning and printed manuals the least popular (p < 0.001).Using computers in the surgery has become the norm for primary care nurses. However, nurses over 50, working out in the community, lack the confidence and skill of their younger and practice based colleagues. In the UK its National Health Service (NHS) is investing in computerisation. Large contracts have been set that will run until 2013 to provide electronic patient records ,5) In adIn this environment primary care professionals will need the skills to read and enter data in computerised medical records, access guidelines and other information on-line, receive alerts about changes in practice via email and use computer as a learning resource. Nurses: practice nurse, district nurses, health visitors, and others, make up a substantial proportion of the primary care workforce. Previous studies have suggested that they have limited access and low levels of confidence and competence in using IT (Information Technology) -11. HoweA literature review was carried out of standard bibliographic data bases: CINAHL, British Nursing Index and Medline to identify any recent publications about use of IT or computerised medical record by practice or district nurses and health visitors. In addition the primary care electronic library (PCEL) , and infThe study took place in a single Primary Care Trust in Sussex, a mixed urban and rural county in southeast England. A Primary Care Trust is a geographically defined locality of approximately 1 – 200,000 people that commissions hospitals, general practitioners and other health providers to deliver comprehensive local NHS healthcare. A PCT can also provide care itself. Most community nurses are employed directly by their PCT, and this PCT is no exception.All the practices in this PCT are computerised with computers linked to the patient database located in all consulting and treatment rooms; and most offices. In common with nearly all UK general practice the practice is networked and the network is connected to the internet via a fixed ISDN-2  link. The ISDN (64 K link) actually connects the practices to the NHS own intranet (NHSnet) and via secure gateways to the internet . The NHSThis PCT has a predominantly female (97%) workforce with one-and-a-half times as many nurses in the over 40 age group compared with the national average for nursing . The Nur.A questionnaire was considered the most appropriate way to gather the information required. Two previous studies indicated that primary care nurses appeared willing to complete the questionnaires and provide rich data ,11. The The questions were based on those used in two earlier studies; with the clarity of questions was improved. Especially distinguishing between a clinical computer system (i.e. one that is used to enter data into an electronic patient record) from other "work" computer systems; and, between home and work use. The questionnaire was tested by a pilot group of nurses located in another PCT in a neighbouring county. The pilot group of six nurses were asked to complete the questionnaire on their own. They were then invited to join a discussion group – where the purpose of the study was explained. Then the questions were gone through one by one to identify any ambiguity. The nurses were also invited to suggested alternative or additional questions. They were given SB's contact details should anything come to mind later.Ethical approval was obtained from the local research ethics committee to conduct the study.Primary care nurses were identified using a list provided by the PCT. The questionnaire was sent out with a covering letter explaining the nature of the study. A courier addressed envelope was provided so the questionnaire could be returned without cost. A reminder and second questionnaire was sent out to non-responders.The questionnaire responses were coded and entered into SPSS  for analysis. The results were analysed by age bands and professional grouping as we wished to test whether either of these factors predetermined the level of computer use. Additional comments were entered into Microsoft Word, and the SPSS data from the questionnaire was placed alongside the relevant comments – they were flagged with the professional group and age group of their originator. Microsoft Excel was used to allow them to be sorted by age group and profession.To simplify the analysis only three age-groups were considered: age under 30, 30 to 39, 40 to 49, and 50 and over. There were no nurses under 30, and only one over 60. The nursing professions were divided into: District nurses, health visitors and midwives, practice nurses, and others. In this study qualified nurses who work in the community primarily supporting district nurses or health visitors were analysed as part of that nursing specialist group. The health visitors and community midwives were combined into the "health visitors" group. The term "primary care nurse" is used to embrace all qualified nurses included in this survey; "community nurse" refers to nurses who still do a proportion of their work in patients' homes, Figure There was a 67% (67/105) response rate to the questionnaires. There was some variation between nursing groups: the response from practice nurses was 73% (n = 22/30), for district nurses 51% (n = 17/33), for health visitors and midwives 67% (n = 19/28), and other nurses, community psychiatric nurses and managers 64% (9/14).Computers were readily available to primary care nurses. Over 90% of nurses had access to a personal computer (PC) at work, though for nearly half (45%) this was shared access; home access was even higher – 96%, with very few (12%) describing their access as shared. The remainder had access elsewhere: library, college etc. Not all the computers were connected to the Internet: 11% of those provided a PC at work and 6% at home could not go on line. After taking into account "other" access to the Internet only 3% of primary care nurses lacked access.The pattern of access to computers, the Internet, and receiving training changed with age. The younger nurses had more access to PCs and the Internet at work, while older nurses had higher levels of access at home, and had received more training. These trends are shown in Table 62% of nurses had received some training, although it was often superficial and run in house to provide basic knowledge of how to use the clinical computer system. Some learned from family members, colleagues or were self-taught, in the use of Microsoft Word and Excel. A few respondents received more formal training on the use of Internet for literature searching from a library, evening classes or as part of high education. Open question data shows that the training received are very diverse both in subjects and level of skills:"...two fifteen minute sessions in 1991 when we first got computers, a second when system was updated""...only one day. All other courses since have been at difficult times or locations""...very basic""...not sufficient though""...no formal courses, only shown by colleague when I was new in post""Protected time for PC training would be most valuable – so often this is hurriedly given during the odd 5-minute break rather than in a training session.""...adequate training is really necessary and protected time; 10–15 minutes between patients is not adequate."Respondents were asked to rate their preferred format for ICT training on a 4-point scale: from 0 for least desirable to 3 for highly desirable. The result showed that 'one-to-one' training and workshops were the preferred formats for training, printed manual the least Table .The preferred location for the training reflected the format of training requested Table . Most waConfidence with computers appeared to be age related, with younger nurses having higher levels of confidence across all the areas of competence than their more senior colleagues. However, only two of these trends, use of spread sheets and electronic patient records (EPR) were found to be statistically significant, see Table The raw data also suggested that there was a discernable trend in computer usage with age. 90% of nurses age 30 to 39 years used their workplace computer daily, 70% of those 40 to 49, and only 59.3% of those over 50. This trend was not significant, see Table Colleagues were the most used source of information across all ages and nursing professions. Older nurses tended to use books and journals from their personal collections, and to use libraries. However, the use of libraries, books and journals is quite low.Younger nurses seem to use journals at work or electronic resources more. Neither of these trends, shown in Table Nurses summarised their experiences in access information in a number of free text comments:"don't know where to look", "don't know website address","vast amounts of irrelevant articles under same headings","I am not as good as I should be with CIHNAL, Medline","information not found or not relevant some difficulty sometimes refining the search for specific information""lack of training/unable to access information I am looking for quickly enough – quicker to look in a book""like trying to get a glass of water from Niagara Falls"This study demonstrated that primary care nurses have high levels of access to IT and only a small minority have no access at all. Practice nurses, working within the surgery, all use the computerised medical record and nearly all feel confident to use it; over three-quarters have access to the Internet. However, community bases nurses in the second half of their careers despite receiving more training; have less access and are less confident about computers, especially use of the EPR, and prefer to use paper-based information resources. Across all ages and professions using libraries, reading journals and accessing on-line resources are minority activities. One to one learning in the workplace, and workshops were believed to be the best way to learn, with printed manuals and on-line tutorials of least value.The implication of this study is that community nursing needs more silver surfers. Silver surfers are those over 50 years who enjoy using the Internet. The primary care nurses over 50, despite more training, are still looking for information on paper; using their computers less at work; and less confident in computer use. Market strategies are making the over 50 s the fastest expanding group of Internet users this decade ,18; but The small sample size and single locality of this study are its principal weaknesses. The former prevented any more detailed sub-group analysis, as the groups became too small. A further reminder may have improved the response rate.This study shows that nurses have made enormous strides in acquiring IT skills and access to computers since earlier surveys -12; althFurther research is needed with a larger sample to see if some of the non-statistically significant trends seen in this data become significant in a larger sample drawn from a national sample. It is important for the NHS to understand what input is needed to raise the level of use of the EPR and online information; and how quickly this change can be achieved. What nurses believe to be most effective ways of changing behaviour, and promoting computer use needs to be tested.There is a consensus among primary care nurses of the sort of training they require to improve their computer use. A significant proportion of community nurses in the second half of their careers need this additional support if they are to achieve silver surfer status; and, have the skills needed to work in the new computerised NHS. Studies need to test whether providing the training wanted overcomes the barriers reported. Although primary care nurses have acquired more computer skills than previously reported there is no room for complacency – community nurses need the opportunity to develop into silver surfers.CPHVA Community Practitioners and Health Visitors Association, a representative body of community nurses.EPR Electronic patient record, synonymous with Computerised Medical Record.IT Information TechnologyNHS National Health Service. The UK's state funded health service.PCEL Primary Care electronic Library, an on-line information resource for primary care.PC personal computerPCT Primary Care Trust – organises and commissions care for a locality of about 100,000 population.RCN Royal College of NursingSNOMED CT Systematized Nomenclature of Medicine – Clinical TermsSPSS Statistical Package for Social Sciences – a computerised statistical package.The author(s) declare that they have no competing interests.All authors conceived the study, and contributed to all aspects of the paper. The major contributions of each author is as follows: TC Analysed the data for the study, SB Recruited the nurses, sent out and collated the questionnaire, SdeL helped develop the questionnaire used in a earlier study and wrote the initial draft of the paper.The pre-publication history for this paper can be accessed here:Community nurses access to and use of computers: questionnaireClick here for file