Mortality Surveillance for the COVID-19 Pandemic: Review of the Centers for Disease Control and Prevention's Multiple System Strategy.

Mortality surveillance systems can have limitations, including reporting delays, incomplete reporting, missing data, and insufficient detail on important risk or sociodemographic factors that can impact the accuracy of estimates of current trends, disease severity, and related disparities across subpopulations. The Centers for Disease Control and Prevention used multiple data systems during the COVID-19 emergency response-line-level case‒death surveillance, aggregate death surveillance, and the National Vital Statistics System-to collectively provide more comprehensive and timely information on COVID-19‒associated mortality necessary for informed decisions. This article will review in detail the line-level, aggregate, and National Vital Statistics System surveillance systems and the purpose and use of each. This retrospective review of the hybrid surveillance systems strategy may serve as an example for adaptive informational approaches needed over the course of future public health emergencies. (Am J Public Health. Published online ahead of print July 25, 2024:e1-e10. https://doi.org/10.2105/AJPH.2024.307743).

A qualitative study of social accountability translation: from mission to living it.

BACKGROUND: Medical schools are increasingly adopting socially accountable mission and curricula, the realisation of which are dependent on engaging individuals to embody the mission's principles in their everyday activities as doctors. However, little is known about how graduates perceive the efforts taken by their medical school to sensitise them to social accountability values, and how they translate this into their working lives. Our aim was to explore and understand graduate perceptions of how their medical school influenced them to embody a social accountability mission in their working lives. METHODS: This was a qualitative interview study carried out with graduates/alumni [n = 51] of Christian Medical College, Vellore [CMCV], India, a school with a long-established and explicit social-accountability mission. Data coding and analysis were initially inductive and thematic using Braun and Clarke's six step framework. MacIntyre's virtue ethics theory framed secondary analysis, allowing us to consider the relationships between individual and contextual factors. RESULTS: Our participants perceived that CMCV invested heavily in selecting personal qualities aligned with the CMCV mission. They saw that these qualities were reinforced through various practices: [e.g., placements in resource limited and/or remote and rural settings]; community engagement and expectations [e.g., student self-governance]; role modelling [staff and more senior students]. Much emphasis was placed on sustaining these traditions and practices over time, creating a strong sense of identity and belonging among participants, traditions which were fostered further by the alumni network and continued engagement with CMCV post-graduation. CONCLUSIONS: Ensuring social accountable medical education depends on alignment and interactions over time between context and structures, systems and human agents. Further studies are needed to extend understanding of how students from diverse contexts experience socially accountable medical education and translate their educational experience into their thinking and practice after graduation.

Effect of particle size on the dispersion behavior of magnesium stearate blended with microcrystalline cellulose.

The majority of tablets manufactured contain lubricants to reduce friction during ejection. However, especially for plastically deforming materials, e.g., microcrystalline cellulose (MCC), the internal addition of lubricants is known to reduce tablet tensile strength. This reduction is caused by the surface coverage by lubricant particles, the extent of which depends on both process and formulation parameters. Previously published models to predict the lubrication effect on mechanical strength do not account for changes in the excipient particle size. In this study, the impact of both lubricant concentration and mixing time on the tensile strength of tablets consisting of three different grades of MCC and four grades of magnesium stearate (MgSt) was evaluated. By taking into account the particle size of the applied excipients, a unifying relationship between the theoretically estimated surface coverage and compactibility reduction was identified. Evaluating the dispersion kinetics of MgSt as a function of time reveals a substantial impact of the initial surface coverage on the dispersion rate, while the minimal tensile strength was found to be comparable for the majority of formulations. In summary, the presented work extends the knowledge of lubricant dispersion and facilitates the reduction of necessary experiments during the development of new tablet formulations.

T1dCteGui: A User-Friendly Clinical Trial Enrichment Tool to Optimize T1D Prevention Studies by Leveraging AI/ML Based Synthetic Patient Population.

Whereas islet autoantibodies (AAs) are well-established risk factors for developing type 1 diabetes (T1D), there is a lack of biomarkers endorsed by regulators to enrich clinical trial populations for those at risk of developing T1D. As such, the development of therapies that delay or prevent the onset of T1D remains challenging. To address this drug development need, the Critical Path Institute's T1D Consortium (T1DC) acquired patient-level data from multiple observational studies and used a model-based approach to evaluate the utility of islet AAs as enrichment biomarkers in clinical trials. An accelerated failure time model was developed, discussed in our previous publication, which provided the underlying evidence required to receive a qualification opinion for islet AAs as enrichment biomarkers from the European Medicines Agency (EMA) in March 2022. To further democratize the use of the model for scientists and clinicians, we developed a Clinical Trial Enrichment Graphical User Interface. The interactive tool allows users to specify trial participant characteristics, including the percentage of participants with a specific AA combination. Users can specify ranges for participant baseline age, sex, blood glucose measurement from the 120-minute timepoints of an oral glucose tolerance test, and HbA1c. The tool then applies the model to predict the mean probability of a T1D diagnosis for that trial population and renders the results to the user. To ensure adequate data privacy and to make the tool open-source, a deep learning-based generative model was used to generate a cohort of synthetic subjects that underpins the tool.

Disease progression joint model predicts time to type 1 diabetes onset: Optimizing future type 1 diabetes prevention studies.

Clinical trials seeking type 1 diabetes prevention are challenging in terms of identifying patient populations likely to progress to type 1 diabetes within limited (i.e., short-term) trial durations. Hence, we sought to improve such efforts by developing a quantitative disease progression model for type 1 diabetes. Individual-level data obtained from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies were used to develop a joint model that links the longitudinal glycemic measure to the timing of type 1 diabetes diagnosis. Baseline covariates were assessed using a stepwise covariate modeling approach. Our study focused on individuals at risk of developing type 1 diabetes with the presence of two or more diabetes-related autoantibodies (AAbs). The developed model successfully quantified how patient features measured at baseline, including HbA1c and the presence of different AAbs, alter the timing of type 1 diabetes diagnosis with reasonable accuracy and precision (<30% RSE). In addition, selected covariates were statistically significant (p < 0.0001 Wald test). The Weibull model best captured the timing to type 1 diabetes diagnosis. The 2-h oral glucose tolerance values assessed at each visit were included as a time-varying biomarker, which was best quantified using the sigmoid maximum effect function. This model provides a framework to quantitatively predict and simulate the time to type 1 diabetes diagnosis in individuals at risk of developing the disease and thus, aligns with the needs of pharmaceutical companies and scientists seeking to advance therapies aimed at interdicting the disease process.

Enhanced multi-component model to consider the lubricant effect on compressibility and compactibility.

Modeling of structural and mechanical tablet properties consisting of multiple components, based on a minimum of experimental data is of high interest, in order to minimize time- and cost-intensive experimental trials in the development of new tablet formulations. The majority of commonly available models use the compressibility and compactibility of constituent components and establish mixing rules between those components, in order to predict the tablet properties of formulations containing multiple components. However, their applicability is limited to single materials, which form intact tablets (e.g. lactose, cellulose) and therefore, they cannot be applied for lubricants. Lubricants are required in the majority of industrial tablet formulations and usually influence the mechanical strength of tablets. This study combines the multi-component compaction model of Reynolds et al. (2017) with a recently published lubrication model (Puckhaber et al. 2020) to describe the impact of multiple components on a formulation consisting of two diluents and a lubricant. By that, this model combination displays a meaningful extension of existing compaction models and allows the systematic prediction of properties of lubricated multi-component tablets.

Consortium-based approach to receiving an EMA qualification opinion on the use of islet autoantibodies as enrichment biomarkers in type 1 diabetes clinical studies.

The development of medical products that can delay or prevent progression to stage 3 type 1 diabetes faces many challenges. Of note, optimising patient selection for type 1 diabetes prevention clinical trials is hindered by significant patient heterogeneity and a lack of characterisation of the time-varying probability of progression to stage 3 type 1 diabetes in individuals positive for two or more islet autoantibodies. To meet these needs, the Critical Path Institute's Type 1 Diabetes Consortium was launched in 2017 as a pre-competitive public-private partnership between stakeholders from the pharmaceutical industry, patient advocacy groups, philanthropic organisations, clinical researchers, the National Institutes of Health and the Food and Drug Administration. The Type 1 Diabetes Consortium acquired and aggregated data from three longitudinal observational studies, Environmental Determinants of Diabetes in the Young (TEDDY), Diabetes Autoimmunity Study in the Young (DAISY) and TrialNet Pathway to Prevention (TN01), and used analysis subsets of these data to support the model-based qualification of islet autoantibodies as enrichment biomarkers for patient selection in type 1 diabetes prevention trials, including registration studies. The Type 1 Diabetes Consortium has now received a qualification opinion from the European Medicines Agency for the use of these biomarkers, a major success for the field of type 1 diabetes. This endorsement will improve product developers' ability to design clinical trials of agents intended to prevent or delay type 1 diabetes that are reduced in size and/or length, while being adequately powered.

Patients with inflammatory bowel disease at risk of sub-optimal outcomes report poorer biopsychosocial functioning than controls: data from two cross-sectional surveys.

Inflammatory bowel disease (IBD) is a chronic gastrointestinal disorder. Standard treatment focuses on reducing the inflammatory burden, however, not all patients respond adequately to conventional medical therapy. These patients, referred to as Patients at Risk of Suboptimal Outcomes (PARSO), have not been studied collectively. The present study aimed to understand the biopsychosocial characteristics of patients with IBD at risk of sub-optimal outcomes for targeted multi-disciplinary treatment to encourage optimal outcomes. Two cross-sectional online surveys, including 760 PARSO and 208 control (non-PARSO) participants, were conducted and their data combined. Biopsychosocial factors included quality of life, pain, disease activity, wellbeing, fatigue, stress, social support, and sleep difficulties. Results suggest that active disease, quality of life, stress, social support, sleep difficulties, fatigue, wellbeing, smoking status, IBD subtype, and pain are significantly associated with membership in a subgroup of PARSO. We also used logistic regression to explore variables associated with the total likelihood of PARSO status. Overall, the model predicted the at-risk status to a substantial degree (R2-2ll = .41, x2 = 401.53, p < .001). Younger age in years, female sex, Crohn's disease, and greater measured and subjective disease activity significantly increased the likelihood of participants being identified as PARSO; OR CI95% = 0.96 (0.95, 0.97); OR CI95% = 4.46 (2.95, 6.71); OR CI95% = 1.58 (1.05, 2.37); OR CI95% = 3.52 (2.18, 5.69); OR CI95% = 45.99 (14.11, 149.89). A biopsychosocial and personalised approach to IBD care might be necessary to support those at risk of suboptimal outcomes in achieving better long-term wellbeing.

Adrenal infarction secondary to methamphetamine use: a case report and review of the literature.

BACKGROUND: An acute abdomen can have a variety of causes. A commonly missed cause of abdominal pain is direct substance abuse and its sequelae. The use of methamphetamine is rising in the United States resulting in significant morbidity and mortality. There has been no reported case of methamphetamine-induced adrenal infarction based on an extensive review of available literature. CASE PRESENTATION: We present a case of a 34-year-old Hispanic man who presented with acute abdominal pain secondary to adrenal infarction in the setting of methamphetamine use. Left paraumbilical tenderness was present on abdominal examination. Contrast-enhanced CT of the abdomen and pelvis revealed internal hypoenhancement of the left adrenal gland, consistent with acute left adrenal infarction. The patient was managed with enoxaparin and apixaban. CONCLUSION: Substance abuse, especially among young patients, can at times present with acute abdomen. This mandates physicians to be vigilant and take into consideration the history of substance abuse and relevant investigations. Timely diagnosis and management can prevent life-threatening complications.

Leveraging Real-World Data for EMA Qualification of a Model-Based Biomarker Tool to Optimize Type-1 Diabetes Prevention Studies.

The development of therapies to prevent or delay the onset of type 1 diabetes (T1D) remains challenging, and there is a lack of qualified biomarkers to identify individuals at risk of developing T1D or to quantify the time-varying risk of conversion to a diagnosis of T1D. To address this drug development need, the T1D Consortium (i) acquired, remapped, integrated, and curated existing patient-level data from relevant observational studies, and (ii) used a model-based approach to evaluate the utility of islet autoantibodies (AAs) against insulin/proinsulin autoantibody, GAD65, IA-2, and ZnT8 as biomarkers to enrich subjects for T1D prevention. The aggregated dataset was used to construct an accelerated failure time model for predicting T1D diagnosis. The model quantifies presence of islet AA permutations as statistically significant predictors of the time-varying probability of conversion to a diagnosis of T1D. Additional sources of variability that greatly improved the accuracy of quantifying the time-varying probability of conversion to a T1D diagnosis included baseline age, sex, blood glucose measurements from the 120-minute timepoints of oral glucose tolerance tests, and hemoglobin A1c. The developed models represented the underlying evidence to qualify islet AAs as enrichment biomarkers through the qualification of novel methodologies for drug development pathway at the European Medicines Agency (EMA). Additionally, the models are intended as the foundation of a fully functioning end-user tool that will allow sponsors to optimize enrichment criteria for clinical trials in T1D prevention studies.

Prediction of the impact of lubrication on tablet compactibility.

The tableting of most pharmaceutical formulations requires the addition of lubricants to reduce ejection forces, prevent tooling damage and tablet defects. The internal addition of lubricants is known to reduce tablet tensile strength, especially of mainly plastically deforming materials. To date, available models show only limited quantitative predictive accuracy for the influence of lubricant concentration on the mechanical strength of tablets. This study aims to fill this gap and present a model based on the Ryshkewitch-Duckworth equation that can estimate the compactibility profiles of lubricated formulations. Binary mixtures of different diluents (microcrystalline cellulose and lactose) were prepared with common lubricants (magnesium stearate and sodium stearyl fumarate) and subsequently tableted. The resulting compactibility profiles were fitted using the Ryshkewitch-Duckworth equation and the derived fit parameters (kb and σ0) were correlated with the lubricant concentration. Subsequently, an empirical model was established which requires a minimum of experimental data and is able to predict the tensile strength of lubricated diluent tablets. Consequently, the developed empirical model is an interesting and valuable addition to the existing multi-component compacting models available and offers the opportunity to accelerate experimentation in the development of new tablet formulations.

Diagnostic Yield of 8-Hour Video-EEG in Detecting Psychogenic Non-Epileptic Seizures (PNES).

To evaluate the diagnostic yield of the first 8 hours of video-EEG (vEEG) monitoring in detecting Psychogenic Non-Epileptic Seizures (PNES) during the Epilepsy Monitoring Unit (EMU) admission. We performed a retrospective chart review of patients ages ≥4 years who were admitted to the EMU between 2011 and 2018 (n = 616). We calculated the proportion of patients diagnosed with PNES within the first 8 hours of EEG recording and studied the associated risk factors for patients diagnosed with PNES and patients with epileptic seizures (ES). Out of the total 616 patients, 24% (149) patients had an EMU diagnosis of PNES. Of these, 44.3% had at least one typical event within the first 8 hours of vEEG monitoring. A higher incidence was seen within the pediatric subgroup (54.8% had an event within 8 hours). A diagnosis of chronic pain disorder was more common with PNES compared to ES (48.3% versus 16.5%, p < 0.001). A suspicion for PNES documented during an office visit was noted in a high proportion of patients (68.5%) who eventually had a PNES event during EMU. Our study suggests that in a well-selected group of patients (such as a high suspicion of PNES during a physician/neurology office visit), an outpatient 8-hour vEEG could open new avenues for a prompt diagnosis. This could especially be beneficial in hospital settings where there is either a lack of an EMU or a delay in admission to the EMU.

Challenges and opportunities for telehealth assessment during COVID-19: iT-RES, adapting a remote version of the test for rating emotions in speech.

OBJECTIVE: COVID-19 social isolation restrictions have accelerated the need to adapt clinical assessment tools to telemedicine. Remote adaptations are of special importance for populations at risk, e.g. older adults and individuals with chronic medical comorbidities. In response to this urgent clinical and scientific need, we describe a remote adaptation of the T-RES (Oron et al. 2020; IJA), designed to assess the complex processing of spoken emotions, based on identification and integration of the semantics and prosody of spoken sentences. DESIGN: We present iT-RES, an online version of the speech-perception assessment tool, detailing the challenges considered and solution chosen when designing the telehealth tool. We show a preliminary validation of performance against the original lab-based T-RES. STUDY SAMPLE: A between-participants design, within two groups of 78 young adults (T-RES, n = 39; iT-RES, n = 39). RESULTS: i-TRES performance closely followed that of T-RES, with no group differences found in the main trends, identification of emotions, selective attention, and integration. CONCLUSIONS: The design of iT-RES mapped the main challenges for remote auditory assessments, and solutions taken to address them. We hope that this will encourage further efforts for telehealth adaptations of clinical services, to meet the needs of special populations and avoid halting scientific research.

Loneliness and social integration as mediators between physical pain and suicidal ideation among elderly men.

OBJECTIVES: Suicide in the elderly is a complex and significant public health problem. The purpose of our study was to examine the role of loneliness and social integration as potential mediators in the relationship between physical pain and suicidal ideation in the elderly. DESIGN: Descriptive, bivariate correlations, and moderated mediation analyses were performed. SETTING: Personal meetings were held with participants in their homes. PARTICIPANTS: A total of 198 elderly men aged 65 and over. MEASUREMENTS: Self-report measures: Beck Scale for Suicidal Ideation, Physical pain subscale, Multidimensional Social Integration in Later Life Scale, and University of California, Los Angeles (UCLA) Loneliness Scale (Version 3). RESULTS: Our findings showed that the association between physical pain and suicidal ideation was mediated by loneliness and social integration. Further analyses revealed that this mediation model was significant among single, but not married, men. CONCLUSIONS: Physical pain and social factors are both important in understanding suicidality in late life. Elderly single men who experience physical pain may be lonelier and less socially integrated, and these factors may contribute to higher risk of suicidal ideation.

Thermal Manipulation During Embryogenesis Impacts H3K4me3 and H3K27me3 Histone Marks in Chicken Hypothalamus.

Changes in gene activity through epigenetic alterations induced by early environmental challenges during embryogenesis are known to impact the phenotype, health, and disease risk of animals. Learning how environmental cues translate into persisting epigenetic memory may open new doors to improve robustness and resilience of developing animals. It has previously been shown that the heat tolerance of male broiler chickens was improved by cyclically elevating egg incubation temperature. The embryonic thermal manipulation enhanced gene expression response in muscle (P. major) when animals were heat challenged at slaughter age, 35 days post-hatch. However, the molecular mechanisms underlying this phenomenon remain unknown. Here, we investigated the genome-wide distribution, in hypothalamus and muscle tissues, of two histone post-translational modifications, H3K4me3 and H3K27me3, known to contribute to environmental memory in eukaryotes. We found 785 H3K4me3 and 148 H3K27me3 differential peaks in the hypothalamus, encompassing genes involved in neurodevelopmental, metabolic, and gene regulation functions. Interestingly, few differences were identified in the muscle tissue for which differential gene expression was previously described. These results demonstrate that the response to embryonic thermal manipulation (TM) in chicken is mediated, at least in part, by epigenetic changes in the hypothalamus that may contribute to the later-life thermal acclimation.

A network conceptualization of the multiple facets of distress tolerance.

BACKGROUND AND OBJECTIVES: Using a network analysis (NA) approach, the current study examined the relations among different facets of Distress Tolerance (DT). The NA approach quantifies and displays relations among variables in a visual network consisting of nodes (symptoms) and edges (partial correlations between symptoms). DESIGN: An exploratory NA approach evaluated how manifestations of DT uniquely and systematically relate to one another. METHODS: Undergraduate students (N = 288) completed 10 commonly used measures of DT including cognitive, behavioral, and self-report measures. RESULTS: Results indicated all relations in the network were positive apart from social sensitivity and suppression. Further, individual DT facets did not form distinct community structures (nodes that cluster together and thus have stronger relations with each other than other nodes in the network). CONCLUSIONS: The lack of community structures suggests that DT is a general ability to tolerate distress that is comprised of many different facets rather than the idea that DT is hierarchical and comprised of distinct domains; a current debate within the literature. The self-reported ability to tolerate life demands and tasks was the most influential facet in the overall network suggesting the Frustration Discomfort Scale may be the best global measure of DT.

Does emotion matter? The role of alexithymia in violent recidivism: A systematic literature review.

BACKGROUND: Several variables have been evidenced for their association with violent reoffending. Resultant interventions have been suggested, yet the rate of recidivism remains high. Alexithymia, characterised by deficits in emotion processing and verbal expression, might interact with these other risk factors to affect outcomes. AIM: Our goal was to examine the role of alexithymia as a possible moderator of risk factors for violent offender recidivism. Our hypothesis was that, albeit with other risk factors, alexithymia increases the risk of violent reoffending. METHOD: We conducted a systematic literature review, using terms for alexithymia and violent offending and their intersection. RESULTS: (a) No study that directly tests the role of alexithymia in conjunction with other potential risk factors for recidivism and actual violent recidivism was uncovered. (b) Primarily alexithymia researchers and primarily researchers into violence have separately found several clinical features in common between aspects of alexithymia and violence, such as impulsivity (total n = 24 studies). (c) Other researchers have established a relationship between alexithymia and both dynamic and static risk factors for violent recidivism (n = 16 studies). CONCLUSION: Alexithymia may be a possible moderator of risk of violent offence recidivism. Supplementing offenders' rehabilitation efforts with assessments of alexithymia may assist in designing individually tailored interventions to promote desistance among violent offenders.

Intraindividual Dynamic Network Analysis - Implications for Clinical Assessment.

A network analysis approach to psychopathology regards symptoms as mutually interacting components of a multifaceted system (Borsboom & Cramer, 2013). Although several studies using this approach have examined comorbidity between disorders using cross-sectional samples, a direct application of the network analysis approach to intraindividual dynamic relations between symptoms in a complex, comorbid case has not been reported. The current article describes an intraindividual dynamic network analysis (IDNA) approach to understanding the psychopathology of an individual using dynamic (over time) lead-lag interrelations between symptoms. Multivariate time series data were utilized to create and examine an intraindividual, lag-1 network of the partial, day-to-day relations of symptoms in an individual with comorbid mood and anxiety disorders. Characteristics of the network, including centrality indices, stability, dynamic processes between symptoms, and their implications for clinical assessment are described. Additional clinical implications and future directions for IDNA, including the potential incremental validity of this assessment approach for empirically-based idiographic assessment and personalized treatment planning, are discussed. This person-specific IDNA approach may be especially useful in complex and comorbid cases.

Separating Common from Unique Variance Within Emotional Distress: An Examination of Reliability and Relations to Worry.

BACKGROUND: High comorbidity rates among emotional disorders have led researchers to examine transdiagnostic factors that may contribute to shared psychopathology. Bifactor models provide a unique method for examining transdiagnostic variables by modelling the common and unique factors within measures. Previous findings suggest that the bifactor model of the Depression Anxiety and Stress Scale (DASS) may provide a method for examining transdiagnostic factors within emotional disorders. AIMS: This study aimed to replicate the bifactor model of the DASS, a multidimensional measure of psychological distress, within a US adult sample and provide initial estimates of the reliability of the general and domain-specific factors. Furthermore, this study hypothesized that Worry, a theorized transdiagnostic variable, would show stronger relations to general emotional distress than domain-specific subscales. METHOD: Confirmatory factor analysis was used to evaluate the bifactor model structure of the DASS in 456 US adult participants (279 females and 177 males, mean age 35.9 years) recruited online. RESULTS: The DASS bifactor model fitted well (CFI = 0.98; RMSEA = 0.05). The General Emotional Distress factor accounted for most of the reliable variance in item scores. Domain-specific subscales accounted for modest portions of reliable variance in items after accounting for the general scale. Finally, structural equation modelling indicated that Worry was strongly predicted by the General Emotional Distress factor. CONCLUSIONS: The DASS bifactor model is generalizable to a US community sample and General Emotional Distress, but not domain-specific factors, strongly predict the transdiagnostic variable Worry.

An Assessment of Fixed and Native Chromatin Preparation Methods to Study Histone Post-Translational Modifications at a Whole Genome Scale in Skeletal Muscle Tissue.

BACKGROUND: Genomic loci associated with histone marks are typically analyzed by immunoprecipitation of the chromatin followed by quantitative-PCR (ChIP-qPCR) or high throughput sequencing (ChIP-seq). Chromatin can be either cross-linked (X-ChIP) or used in the native state (N-ChIP). Cross-linking of DNA and proteins helps stabilizing their interactions before analysis. Despite X-ChIP is the most commonly used method, muscle tissue fixation is known to be relatively inefficient. Moreover, no protocol described a simple and reliable preparation of skeletal muscle chromatin of sufficient quality for subsequent high-throughput sequencing. Here we aimed to set-up and compare both chromatin preparation methods for a genome-wide analysis of H3K27me3, a broad-peak histone mark, using chicken P. major muscle tissue. RESULTS: Fixed and unfixed chromatin were prepared from chicken muscle tissues (Pectoralis major). Chromatin fixation, shearing by sonication or digestion and immunoprecipitation performed equivalently. High-quality Illumina reads were obtained (q30 > 93%). The bioinformatic analysis of the data was performed using epic, a tool based on SICER, and MACS2. Forty millions of reads were analyzed for both X-ChIP-seq and N-ChIP-seq experiments. Surprisingly, H3K27me3 X-ChIP-seq analysis led to the identification of only 2000 enriched regions compared to about 15,000 regions identified in the case of N-ChIP-seq. N-ChIP-seq peaks were more consistent between replicates compared to X-ChIP-seq. Higher N-ChIP-seq enrichments were confirmed by ChIP-qPCR at the PAX5 and SOX2 loci known to be enriched for H3K27me3 in myotubes and at the loci of common regions of enrichment identified in this study. CONCLUSIONS: Our findings suggest that the preparation of muscle chromatin for ChIP-seq in cross-linked conditions can compromise the systematic analysis of broad histone marks. Therefore, native chromatin preparation should be preferred to cross-linking when a ChIP experiment has to be performed on skeletal muscle tissue, particularly when a broad source signal is considered.