Malaria continues to be a major source of morbidity and mortality in sub-Saharan Africa. Timely, accurate, and effective case management is critical to malaria control. Proactive community case management (ProCCM) is a new strategy in which a community health worker "sweeps" a village, visiting households at defined intervals to proactively provide diagnostic testing and treatment if indicated. Pilot experiments have shown the potential of ProCCM for controlling malaria transmission; identifying the best strategy for administering ProCCM in terms of interval timings and number of sweeps could lead to further reductions in malaria infections. We developed an agent-based simulation to model malaria transmission and the impact of various ProCCM strategies. The model was validated using symptomatic prevalence data from a ProCCM pilot study in Senegal. Various ProCCM strategies were tested to evaluate the potential for reducing parasitologically confirmed symptomatic malaria cases in the Senegal setting. We found that weekly ProCCM sweeps during a 21-week transmission season could reduce cases by 36.3% per year compared with no sweeps. Alternatively, two initial fortnightly sweeps, seven weekly sweeps, and finally four fortnightly sweeps (13 sweeps total) could reduce confirmed malaria cases by 30.5% per year while reducing the number of diagnostic tests and corresponding costs by about 33%. Under a highly seasonal transmission setting, starting the sweeps early with longer duration and higher frequency would increase the impact of ProCCM, though with diminishing returns. The model is flexible and allows decision-makers to evaluate implementation strategies incorporating sweep frequency, time of year, and available budget.

Recently, the Cochrane Library released its anticipated update on physical interventions to control the spread of respiratory viruses, including masks to contain the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).1 The update was widely read and cited, becoming a point of controversy in the public debate about the efficacy of face masks, as it appeared to contradict both public health guidance2 and research.3 The appearance of controversy was in part owing to the methodological approach of Cochrane reviews, which allows inclusion of only randomized controlled trials (RCTs). | | The authors added 11 new RCTs and cluster RCTs, of which six were conducted during the COVID-19 pandemic and evaluated various interventions for hygiene, including face masks and hand washing. Only two of the six studies compared use of face masks with no use of masks: one from Denmark, the DANMASK-19 RCT,4 and one from Bangladesh.5 But even with these limited, additional data, the appearance of disagreement between the Cochrane review results and public health guidance disappears if infectious disease models are applied, because the models calibrate quite well to the new Cochrane data and, when extrapolated, show that masks can reduce respiratory infections significantly.

We updated a published mathematical model of SARS-CoV-2 transmission with laboratory-derived source and wearer protection efficacy estimates for a variety of face masks to estimate their impact on COVID-19 incidence and related mortality in the United States. When used at already-observed population rates of 80% for those ≥65 years and 60% for those <65 years, face masks are associated with 69% (cloth) to 78% (medical procedure mask) reductions in cumulative COVID-19 infections and 82% (cloth) to 87% (medical procedure mask) reductions in related deaths over a 6-month timeline in the model, assuming a basic reproductive number of 2.5. If cloth or medical procedure masks’ source control and wearer protection efficacies are boosted about 30% each to 84% and 60% by cloth over medical procedure masking, fitters, or braces, the COVID-19 basic reproductive number of 2.5 could be reduced to an effective reproductive number ≤ 1.0, and from 6.0 to 2.3 for a variant of concern similar to delta (B.1.617.2).Article Summary Line Adapting a published SARS-CoV-2 transmission model together with updated, laboratory-derived source control and wearer protection efficacy estimates for a variety of face coverings as well as N95 respirators, we demonstrate that community masking as currently practiced has likely reduced cases and deaths and that this benefit can be increased with wider adoption of better performing masks.Competing Interest StatementThe authors have declared no competing interest.Clinical TrialThis is an epidemiological modeling study, not a clinical trialFunding StatementNo external funding was received.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:No IRB was needed as this is an epidemiological modeling study.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data/parameters used in the models are reported in the manuscript. Code is available upon request.

OBJECTIVE: High-quality scientific evidence underpins public health decision making. The Centers for Disease Control and Prevention (CDC) agency provides scientific data, including during public health emergencies. To understand CDC's contributions to COVID-19 science, we conducted a bibliometric evaluation of publications authored by CDC scientists from January 20, 2020, through January 20, 2022, by using a quality improvement approach (SQUIRE 2.0). METHODS: We catalogued COVID-19 articles with 1 CDC-affiliated author published in a scientific journal and indexed in the World Health Organization's COVID-19 database. We identified priority topic areas from the agency's COVID-19 Public Health Science Agenda by using keyword scripts in EndNote and then assessed the impact of the published articles by using Scopus and Altmetric. RESULTS: During the first 2 years of the agency's pandemic response, CDC authors contributed to 1044 unique COVID-19 scientific publications in 208 journals. Publication topics included testing (n = 853, 82%); prevention strategies (n = 658, 63%); natural history, transmission, breakthrough infections, and reinfections (n = 587, 56%); vaccines (n = 567, 54%); health equity (n = 308, 30%); variants (n = 232, 22%); and post-COVID-19 conditions (n = 44, 4%). Publications were cited 40427 times and received 81921 news reports and 1058893 social media impressions. As the pandemic evolved, CDC adapted to address new scientific questions, including vaccine effectiveness, safety, and access; viral variants, including Delta and Omicron; and health equity. CONCLUSION: The agency's COVID-19 Public Health Science Agenda helped guide impactful scientific activities. CDC continues to evaluate COVID-19 priority topic areas and contribute to development of new scientific work. CDC is committed to monitoring emerging issues and addressing gaps in evidence needed to improve health.

We expanded a published mathematical model of SARS-CoV-2 transmission with complex, age-structured transmission and with laboratory-derived source and wearer protection efficacy estimates for a variety of face masks to estimate their impact on COVID-19 incidence and related mortality in the United States. The model was also improved to allow realistic age-structured transmission with a pre-specified R0 of transmission, and to include more compartments and parameters, e.g. for groups such as detected and undetected asymptomatic infectious cases who mask up at different rates. When masks are used at typically-observed population rates of 80% for those ≥ 65 years and 60% for those < 65 years, face masks are associated with 69% (cloth) to 78% (medical procedure mask) reductions in cumulative COVID-19 infections and 82% (cloth) to 87% (medical procedure mask) reductions in related deaths over a 6-month timeline in the model, assuming a basic reproductive number of 2.5. If cloth or medical procedure masks' source control and wearer protection efficacies are boosted about 30% each to 84% and 60% by cloth over medical procedure masking, fitters, or braces, the COVID-19 basic reproductive number of 2.5 could be reduced to an effective reproductive number ≤ 1.0, and from 6.0 to 2.3 for a variant of concern similar to delta (B.1.617.2). For variants of concern similar to omicron (B.1.1.529) or the sub-lineage BA.2, modeled reductions in effective reproduction number due to similar high quality, high prevalence mask wearing is more modest (to 3.9 and 5.0 from an R(0) = 10.0 and 13.0, respectively). None-the-less, the ratio of incident risk for masked vs. non-masked populations still shows a benefit of wearing masks even with the higher R0 variants.

BACKGROUND: Investigating antecedents of behaviors, such as wearing face coverings, is critical for developing strategies to prevent SARS-CoV-2 transmission. PURPOSE: The purpose of this study was to determine associations between theory-based behavioral predictors of intention to wear a face covering and actual wearing of a face covering in public. METHODS: Data from a cross-sectional panel survey of U.S. adults conducted in May and June 2020 (N = 1,004) were used to test a theory-based behavioral path model. We (a) examined predictors of intention to wear a face covering, (b) reported use of cloth face coverings, and (c) reported use of other face masks (e.g., a surgical mask or N95 respirator) in public. RESULTS: We found that being female, perceived importance of others wanting the respondent to wear a face covering, confidence to wear a face covering, and perceived importance of personal face covering use was positively associated with intention to wear a face covering in public. Intention to wear a face covering was positively associated with self-reported wearing of a cloth face covering if other people were observed wearing cloth face coverings in public at least "rarely" (aOR = 1.43), with stronger associations if they reported "sometimes" (aOR = 1.83), "often" (aOR = 2.32), or "always" (aOR = 2.96). For other types of face masks, a positive association between intention and behavior was only present when observing others wearing face masks "often" (aOR = 1.25) or "always" (aOR = 1.48). CONCLUSIONS: Intention to wear face coverings and observing other people wearing them are important behavioral predictors of adherence to the CDC recommendation to wear face coverings in public.

On April 3, 2020, the White House Coronavirus Task Force and CDC announced a new behavioral recommendation to help slow the spread of coronavirus disease 2019 (COVID-19) by encouraging the use of a cloth face covering when out in public (1). Widespread use of cloth face coverings has not been studied among the U.S. population, and therefore, little is known about encouraging the public to adopt this behavior. Immediately following the recommendation, an Internet survey sampled 503 adults during April 7-9 to assess their use of cloth face coverings and the behavioral and sociodemographic factors that might influence adherence to this recommendation. The same survey was administered 1 month later, during May 11-13, to another sample of 502 adults to assess changes in the prevalence estimates of use of cloth face coverings from April to May. Within days of the release of the first national recommendation for use of cloth face coverings, a majority of persons who reported leaving their home in the previous week reported using a cloth face covering (61.9%). Prevalence of use increased to 76.4% 1 month later, primarily associated with increases in use among non-Hispanic white persons (54.3% to 75.1%), persons aged >/=65 years (36.6% to 79.2%), and persons residing in the Midwest (43.7% to 73.8%). High rates were observed in April and by May, increased further among non-Hispanic black persons (74.4% to 82.3%), Hispanic or Latino persons (77.3% to 76.2%), non-Hispanic persons of other race (70.8% to 77.3%), persons aged 18-29 years (70.1% to 74.9%) and 30-39 years (73.9% to 84.4%), and persons residing in the Northeast (76.9% to 87.0%). The use of a cloth face covering was associated with theory-derived constructs that indicate a favorable attitude toward them, intention to use them, ability to use them, social support for using them, and beliefs that they offered protection for self, others, and the community. Research is needed to understand possible barriers to using cloth face coverings and ways to promote their consistent and correct use among those who have yet to adopt this behavior.

OBJECTIVE: To advance public health support for the U.S. Department of Housing and Urban Development's smoke-free rule, the Centers for Disease Control and Prevention collaborated with the Georgia Institute of Technology to develop a geospatial mapping tool. The objective was to create a tool state and local public health agencies could use to tailor smoke-free educational materials and cessation interventions for specific public housing development resident populations. RESULTS: The resulting "Extinguish Tool" includes an interactive map of U.S. public housing developments (PHDs) and healthcare facilities that provides detailed information on individual PHDs, their proximity to existing healthcare facilities, and the demographic characteristics of residents. The tool also estimates the number of PHD residents who smoke cigarettes and calculates crude estimates of the potential economic benefits of providing cessation interventions to these residents. The geospatial mapping tool project serves as an example of a collaborative and innovative public health approach to protecting the health and well-being of the nation's two million public housing residents, including 760,000 children, from the harms of tobacco smoking and secondhand smoke exposure in the places where they live, play, and gather.

BACKGROUND: Between 2002 and 2013, the organs of thirteen deceased donors with infectious encephalitis were transplanted, causing infections in 23 recipients. As a consequence, organs from donors showing symptoms of encephalitis (increased probability of infectious encephalitis (IPIE) organs) might be declined. We had previously characterized the risk of IPIE organs using data available to most transplant teams and not requiring special diagnostic tests. If the probability of infection is low, the benefits of a transplant from a donor with suspected infectious encephalitis might outweigh the risk and could be lifesaving for some transplant candidates. METHODS: Using organ transplant data and Cox Proportional Hazards models, we determined liver donor and recipient characteristics predictive of post-transplant or waitlist survival and generated 5-year survival probability curves. We also calculated expected waiting times for an organ offer based on transplant candidate characteristics. Using a limited set of actual cases of infectious encephalitis transmission via transplant, we estimated post-transplant survival curves given an organ from an IPIE donor. RESULTS: 54% (1,256) of patients registered from 2002-2006 who died or were removed from the waiting list due to deteriorated condition within 1 year could have had an at least marginal estimated benefit by accepting an IPIE liver with some probability of infection, with the odds increasing to 86% of patients if the probability of infection was low (5% or less). Additionally, 54% (1,252) were removed from the waiting list prior to their estimated waiting time for a non-IPIE liver and could have benefited from an IPIE liver. CONCLUSION: Improved allocation and utilization of IPIE livers could be achieved by evaluating the patient-specific trade-offs between (i) accepting an IPIE liver and (ii) remaining on the waitlist and accepting a non-IPIE liver after the estimated waiting time. This article is protected by copyright. All rights reserved.

We used an ensemble of statistical methods to build a model that predicts kidney transplant survival and identifies important predictive variables. The proposed model achieved better performance, measured by Harrell's concordance index, than the Estimated Post Transplant Survival model used in the kidney allocation system in the U.S., and other models published recently in the literature. The model has a five-year concordance index of 0.724 (in comparison, the concordance index is 0.697 for the Estimated Post Transplant Survival model, the state of the art currently in use). It combines predictions from random survival forests with a Cox proportional hazards model. The rankings of importance for the model's variables differ by transplant recipient age. Better survival predictions could eventually lead to more efficient allocation of kidneys and improve patient outcomes.

To reduce the risk of HIV, hepatitis B virus (HBV), and hepatitis C virus (HCV) transmission through organ transplantation, donors are universally screened for these infections by nucleic acid tests (NAT). Deceased organ donors are classified as "increased risk" if they engaged in specific behaviors during the 12 months before death. We developed a model to estimate the risk of undetected infection for HIV, HBV, and HCV among NAT-negative donors specific to the type and timing of donors' potential risk behavior to guide revisions to the 12-month timeline. Model parameters were estimated, including risk of disease acquisition for increased-risk groups, number of virions that multiply to establish infection, virus doubling time, and limit of detection by NAT. Monte Carlo simulation was performed. The risk of undetected infection was <1/1,000,000 for HIV after 14 days, for HBV after 35 days, and for HCV after 7 days from the time of most recent potential exposure to the day of a negative NAT. The period during which reported donor risk behaviors result in an "increased risk" designation can be safely shortened. This article is protected by copyright. All rights reserved.

BACKGROUND: There were 13 documented clusters of infectious encephalitis transmission via organ transplant from deceased donors to recipients during 2002-2013. Hence, organs from donors diagnosed with encephalitis are often declined due to concerns about the possibility of infection, given that there is no quick and simple test to detect causes of infectious encephalitis. METHODS: We constructed a database containing cases of infectious and non-infectious encephalitis. Using statistical imputation, cross-validation, and regression techniques, we determined deceased organ donor characteristics, including demographics, signs, symptoms, physical exam, and laboratory findings, predictive of infectious versus non-infectious encephalitis, and developed a calculator which assesses risk of infection. RESULTS: Using up to 12 predictive patient characteristics, (with a minimum of 3, depending on what information is available), the calculator provides the probability that a donor may have infectious versus non-infectious encephalitis, improving the prediction accuracy over current practices. These characteristics include gender, fever, immunocompromised state (other than HIV), cerebrospinal fluid elevation, altered mental status, psychiatric features, cranial nerve abnormality, meningeal signs, focal motor weakness, Babinski's sign, movement disorder, and sensory abnormalities. CONCLUSION: In the absence of definitive diagnostic testing in a potential organ donor, infectious encephalitis can be predicted with a risk score. The risk calculator presented in this paper represents a prototype, establishing a framework that can be expanded to other infectious diseases transmissible through solid organ transplantation. This article is protected by copyright. All rights reserved.

BACKGROUND: In 2013, guidelines were released for reducing the risk of viral bloodborne pathogen transmission through organ transplantation. Eleven criteria were described that result in a donor being designated at increased infectious risk. Human immunodeficiency virus (HIV) and hepatitis C virus (HCV) transmission risk from an increased-risk donor (IRD), despite negative nucleic acid testing (NAT), likely varies based on behavior type and timing. METHODS: We developed a Monte Carlo risk model to quantify probability of HIV among IRDs. The model included NAT performance, viral load dynamics and per-act risk of acquiring HIV by each behavior. The model also quantifies the probability of HCV among IRDs by non-medical intravenous drug use (IVDU). RESULTS: Highest risk is among donors with history of unprotected, receptive anal male-to-male intercourse with partner of unknown HIV status (MSM), followed by sex with HIV-infected partner, IVDU, and sex with a commercial sex worker. CONCLUSION: With NAT screening, the estimated risk of undetected HIV remains small even at 1 day following a risk behavior. The estimated risk for HCV transmission through IVDU is likewise small and decreases quicker with time owing to the faster viral growth dynamics of HCV compared with HIV. These findings may allow for improved organ allocation, utilization, and recipient informed consent.

BACKGROUND: Multiple case definitions are in use to identify chronic fatigue syndrome (CFS). Even when using the same definition, methods used to apply definitional criteria may affect results. The Centers for Disease Control and Prevention (CDC) conducted two population-based studies estimating CFS prevalence using the 1994 case definition; one relied on direct questions for criteria of fatigue, functional impairment and symptoms (1997 Wichita; Method 1), and the other used subscale score thresholds of standardized questionnaires for criteria (2004 Georgia; Method 2). Compared to previous reports the 2004 CFS prevalence estimate was higher, raising questions about whether changes in the method of operationalizing affected this and illness characteristics. METHODS: The follow-up of the Georgia cohort allowed direct comparison of both methods of applying the 1994 case definition. Of 1961 participants (53 % of eligible) who completed the detailed telephone interview, 919 (47 %) were eligible for and 751 (81 %) underwent clinical evaluation including medical/psychiatric evaluations. Data from the 499 individuals with complete data and without exclusionary conditions was available for this analysis. RESULTS: A total of 86 participants were classified as CFS by one or both methods; 44 cases identified by both methods, 15 only identified by Method 1, and 27 only identified by Method 2 (Kappa 0.63; 95 % confidence interval [CI]: 0.53, 0.73 and concordance 91.59 %). The CFS group identified by both methods were more fatigued, had worse functioning, and more symptoms than those identified by only one method. Moderate to severe depression was noted in only one individual who was classified as CFS by both methods. When comparing the CFS groups identified by only one method, those only identified by Method 2 were either similar to or more severely affected in fatigue, function, and symptoms than those only identified by Method 1. CONCLUSIONS: The two methods demonstrated substantial concordance. While Method 2 classified more participants as CFS, there was no indication that they were less severely ill or more depressed. The classification differences do not fully explain the prevalence increase noted in the 2004 Georgia study. Use of standardized instruments for the major CFS domains provides advantages for disease stratification and comparing CFS patients to other illnesses.

Reliable antibody based-assays are needed to evaluate the immunogenicity of current vaccines, impact of altered dosing schemes or of new vaccine formulations. An ideal assay platform would allow multiplex type-specific detection with minimal sample requirement. We used the Meso Scale Discovery (MSD) electrochemiluminescence based detection platform to develop a multiplex direct virus-like particles (VLP) ELISA to detect antibodies to HPV 6, 11, 16, and 18 with a protocol developed for detection using the SI 6000 imager (M4ELISA). MSD prepared the plates in the 7-spot/well format, using the purified VLPs (4 spots) and PBS+BSA pH7.4 (3 blank spots). Three-point titrations and the parallel line method were used to calculate antibody levels. Dynamic range, precision, and stability of pre-printed plates were determined using a panel of previously characterized sera. Cut-off values using children's sera were established using 99% RLU limits based on 4-parameter Johnson Su best fit curve. Results of the M4ELISA were compared to competitive Luminex Immunoassay (cLIA) on n=4454 sera from a predominantly unvaccinated cohort. Using a VLP coating concentration of 80mug/ml with BSA provided the most robust RLU signal for all types. The dynamic range of the assay was about 1000 fold, with assay variability under 25% for each of the four vaccine types. Long-term stability of the plates extended to about 7months from the time plates were received in the laboratory after printing. There was moderate agreement (kappa=0.38-0.54) between M4ELISA and cLIA, with antibody detection for each of the 4 types more frequent with M4ELISA. Quantitative analysis however showed a good correlation between concordant samples by both assays (rho ≥0.6). The MSD platform shows promise for simultaneous quantitation of the antibody responses to four HPV vaccine types in a high-throughput manner.

Detection of multiple human papillomavirus (HPV) types in the genital tract is common. Associations among HPV types may impact HPV vaccination modeling and type replacement. The objectives were to determine the distribution of concurrent HPV type infections in cervicovaginal samples and examine type-specific associations. We analyzed HPV genotyping results from 32,245 cervicovaginal specimens collected from women aged 11 to 83 years in the United States from 2001 through 2011. Statistical power was enhanced by combining 6 separate studies. Expected concurrent infection frequencies from a series of permutation models, each with increasing fidelity to the real data, were compared with the observed data. Statistics were computed based on the distributional properties of the randomized data. Concurrent detection occurred more than expected with 0 or ≥3 HPV types and less than expected with 1 and 2 types. Some women bear a disproportionate burden of the HPV type prevalence. Type associations were observed that exceeded multiple hypothesis corrected significance. Multiple HPV types were detected more frequently than expected by chance and associations among particular HPV types were detected. However vaccine-targeted types were not specifically affected, supporting the expectation that current bivalent/quadrivalent HPV vaccination will not result in type replacement with other high-risk types.

F.W.R. Brambell deduced the existence of a protective receptor for IgG, the neonatal Fc receptor (FcRn), long before its discovery in the early to mid-1990s. With the coincident, explosive development of IgG-based drugs, FcRn became a popular target for tuning the pharmacokinetics of monoclonal antibodies (mAbs). One aspect of Brambell's initial observation, however, that is seldom discussed since the discovery of the receptor, is the compliance in the mechanism that Brambell observed (saturating at 10s-100s of muM concentration), vs. the comparative stiffness of the receptor kinetics (saturating in the nM range for most species). Although some studies reported that increasing the already very high Fc-FcRn affinity at pH 6.0 further improved mAb half-life, in fact the results were mixed, with later studies increasingly implicating non-FcRn-dependent mechanisms as determinants of mAb pharmacokinetics. Mathematical modelling of the FcRn system has also indicated that the processes determining the pharmacokinetics of mAbs have more nuances than had at first been hypothesised. We propose, in keeping with the latest modelling and experimental evidence reviewed here, that the dynamics of endosomal sorting and trafficking have important roles in the compliant salvage mechanism that Brambell first observed nearly 50 years ago, and therefore also in the pharmacokinetics of mAbs. These ideas lead to many open questions regarding the endosomal trafficking of both FcRn and mAbs and also to what properties of a mAb can be altered to achieve an improvement in pharmacokinetics.

SELDI-TOF mass spectrometer's compact size and automated, high throughput design have been attractive to clinical researchers, and the platform has seen steady-use in biomarker studies. Despite new algorithms and preprocessing pipelines that have been developed to address reproducibility issues, visual inspection of the results of SELDI spectra preprocessing by the best algorithms still shows miscalled peaks and systematic sources of error. This suggests that there continues to be problems with SELDI preprocessing. In this work, we study the preprocessing of SELDI in detail and introduce improvements. While many algorithms, including the vendor supplied software, can identify peak clusters of specific mass (or m/z) in groups of spectra with high specificity and low false discover rate (FDR), the algorithms tend to underperform estimating the exact prevalence and intensity of peaks in those clusters. Thus group differences that at first appear very strong are shown, after careful and laborious hand inspection of the spectra, to be less than significant. Here we introduce a wavelet/neural network based algorithm which mimics what a team of expert, human users would call for peaks in each of several hundred spectra in a typical SELDI clinical study. The wavelet denoising part of the algorithm optimally smoothes the signal in each spectrum according to an improved suite of signal processing algorithms previously reported (the LibSELDI toolbox under development). The neural network part of the algorithm combines those results with the raw signal and a training dataset of expertly called peaks, to call peaks in a test set of spectra with approximately 95% accuracy. The new method was applied to data collected from a study of cervical mucus for the early detection of cervical cancer in HPV infected women. The method shows promise in addressing the ongoing SELDI reproducibility issues.

BACKGROUND: Surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI) is a proteomics tool for biomarker discovery and other high throughput applications. Previous studies have identified various areas for improvement in preprocessing algorithms used for protein peak detection. Bottom-up approaches to preprocessing that emphasize modeling SELDI data acquisition are promising avenues of research to find the needed improvements in reproducibility. RESULTS: We studied the properties of the SELDI detector intensity response to matrix only runs. The intensity fluctuations and noise observed can be characterized by a natural exponential family with quadratic variance function (NEF-QVF) class of distributions. These include as special cases many common distributions arising in practice (e.g.- normal, Poisson). Taking this model into account, we present a modified Antoniadis-Sapatinas wavelet denoising algorithm as the core of our preprocessing program, implemented in MATLAB. The proposed preprocessing approach shows superior peak detection sensitivity compared to MassSpecWavelet for false discovery rate (FDR) values less than 25%. CONCLUSIONS: The NEF-QVF detector model requires that certain parameters be measured from matrix only spectra, leaving implications for new experiment design at the trade-off of slightly increased cost. These additional measurements allow our preprocessing program to adapt to changing noise characteristics arising from intralaboratory and across-laboratory factors. With further development, this approach may lead to improved peak prediction reproducibility and nearly automated, high throughput preprocessing of SELDI data.

Serotonergic neurotransmission plays a key role in the pathophysiology of neuropsychiatric illnesses. The functional significance of a promoter polymorphism, -1438G/A (rs6311), in one of the major genes of this system (serotonin receptor 2A, HTR2A) remains poorly understood in the context of epigenetic factors, transcription factors and endocrine influences. We used functional and structural equation modeling (SEM) approaches to assess the contributions of the polymorphism (rs6311), DNA methylation and clinical variables to HTR2A expression in chronic fatigue syndrome (CFS) subjects from a population-based study. HTR2A was up-regulated in CFS through allele-specific expression modulated by transcription factors at critical sites in its promoter: an E47 binding site at position -1,438, (created by the A-allele of rs6311 polymorphism), a glucocorticoid receptor (GR) binding site encompassing a CpG at position -1,420, and Sp1 binding at CpG methylation site -1,224. Methylation at -1,420 was strongly correlated with methylation at -1,439, a CpG site that is dependent upon the G-allele of rs6311 at position -1,438. SEM revealed a strong negative interaction between E47 and GR binding (in conjunction with cortisol level) on HTR2A expression. This study suggests that the promoter polymorphism (rs6311) can affect both transcription factor binding and promoter methylation, and this along with an individual's stress response can impact the rate of HTR2A transcription in a genotype and methylation-dependent manner. This study can serve as an example for deciphering the molecular determinants of transcriptional regulation of major genes of medical importance by integrating functional genomics and SEM approaches. Confirmation in an independent study population is required.

The recent article by Jason, Najar, Porter, and Reh, "Evaluating the Centers for Disease Control's Empirical Chronic Fatigue Syndrome Case Definition" (2009; Journal of Disability Policy Studies, 20:2, 93L100) attempted to critically explore several pertinent issues concerning diagnosing chronic fatigue syndrome (CFS). Most of these issues have been brewing since international adoption of the 1994 CFS case definition by Fukuda et al., and it is high time to address them in a peer-reviewed and public forum.