Impact of post-operative transoral robotic surgery hemorrhage on adjuvant treatment delays in patients with oropharyngeal squamous cell carcinoma.

OBJECTIVES: Transoral robotic surgery (TORS) for the treatment for oropharyngeal squamous cell carcinoma (SCC) carries a risk of post-operative hemorrhage. Increased time from surgery to completion of adjuvant therapy has been associated with decreased survival. Our objective was to assess for adjuvant treatments delays in patients with post-operative bleeding. Secondarily, to assess post-operative swallowing outcomes. MATERIALS AND METHODS: Retrospective chart review of all patients who underwent TORS from 2014 to 2021 at a tertiary care center. Patient demographics, adjuvant therapy course, treatment-related dysphagia outcomes, incidence and severity of post-operative bleeding were reviewed. RESULTS: 221 patients underwent TORS, 160 (72%) of which were recommended to undergo adjuvant treatment. 33 patients developed post-operative bleeding, of which 22 patients underwent at least partial radiation therapy (RT) where there was an average of 53.0 ± 12 days elapsed from surgery to the initiation of RT. In the control group, 124 completed at least partial adjuvant treatment and there was an average of 55.3 ± 23 days from surgery to start of adjuvant RT. Time to start of RT was not significantly different between the cohorts (p=0.47). 9.1% of patients with bleeding and 23.7% of those without bleeding started radiation therapy within 6 weeks. The odds ratio of requiring a feeding tube during treatment in patients with post-operative bleeding compared to those without was 1.3 (95% C.I. 0.54-3.13). CONCLUSION: Patients with post-operative bleeding following TORS with TAL were not found to have a significantly higher risk of treatment delays or dysphagia burden, independent of hemorrhage severity.

Molecular basis of proteolytic cleavage regulation by the extracellular matrix receptor dystroglycan.

The dystrophin-glycoprotein-complex (DGC), anchored by the transmembrane protein dystroglycan, functions to mechanically link the extracellular matrix and actin cytoskeleton. Breaking this connection is associated with diseases such as muscular dystrophy, yet cleavage of dystroglycan by matrix-metalloproteinases (MMPs) remains an understudied mechanism to disrupt the DGC. We determined the crystal structure of the membrane-adjacent domain (amino acids 491-722) of E. coli expressed human dystroglycan to understand MMP cleavage regulation. The structural model includes tandem immunoglobulin-like (IGL) and sperm/enterokinase/agrin-like (SEAL) domains, which support proteolysis in diverse receptors to facilitate mechanotransduction, membrane protection, and viral entry. The structure reveals a C-terminal extension that buries the MMP site by packing into a hydrophobic pocket, a unique mechanism of MMP cleavage regulation. We further demonstrate structure-guided and disease-associated mutations disrupt proteolytic regulation using a cell-surface proteolysis assay. Thus disrupted proteolysis is a potentially relevant mechanism for "breaking" the DGC link to contribute to disease pathogenesis.

NMR Spectroscopy and Multiscale Modeling Shed Light on Ion-Solvent Interactions and Ion Pairing in Aqueous NaF Solutions.

The balance between ion solvation and ion pairing in aqueous solutions modulates chemical and physical processes from catalysis to protein folding. Yet, despite more than a century of investigation, experimental determination of the distribution of ion-solvation and ion-pairing states remains elusive, even for archetypal systems like aqueous alkali halides. Here, we combine nuclear magnetic resonance (NMR) spectroscopy and multiscale modeling to disentangle ion-solvent interactions from ion pairing in aqueous sodium fluoride solutions. We have developed a high-accuracy method to collect experimental NMR resonance frequencies for both ions as functions of temperature and concentration. Comparison of these data with resonance frequencies for nonassociating salts allows us to differentiate the influence of solvation and ion pairing on NMR spectra. These high-quality experimental NMR data are used to validate our modeling framework comprising polarizable force field molecular dynamics (MD) simulations and quantum chemical calculations of NMR resonance frequencies. Our experimental and theoretical resonance frequency shifts agree over a wide range of temperatures and concentrations. Structural analysis reveals how both trends are dominated by interactions with water molecules. For the more sensitive 19F nucleus, the NMR resonance frequency decreases as hydrogen bonds between fluoride and water molecules are reduced in number with increased temperature and molality. Through a detailed analysis of the theoretical NMR resonance frequencies for both ions, we show that NMR spectroscopy can distinguish both contact ion pairs and single-solvent-separated ion pairs from free ions. This quantitative framework can be applied directly to other systems.

Deep-learning generated B-line score mirrors clinical progression of disease for patients with heart failure.

BACKGROUND: Ultrasound can detect fluid in the alveolar and interstitial spaces of the lung using the presence of artifacts known as B-lines. The aim of this study was to determine whether a deep learning algorithm generated B-line severity score correlated with pulmonary congestion and disease severity based on clinical assessment (as identified by composite congestion score and Rothman index) and to evaluate changes in the score with treatment. Patients suspected of congestive heart failure underwent daily ultrasonography. Eight lung zones (right and left anterior/lateral and superior/inferior) were scanned using a tablet ultrasound system with a phased-array probe. Mixed effects modeling explored the association between average B-line score and the composite congestion score, and average B-line score and Rothman index, respectively. Covariates tested included patient and exam level data (sex, age, presence of selected comorbidities, baseline sodium and hemoglobin, creatinine, vital signs, oxygen delivery amount and delivery method, diuretic dose). RESULTS: Analysis included 110 unique subjects (3379 clips). B-line severity score was significantly associated with the composite congestion score, with a coefficient of 0.7 (95% CI 0.1-1.2 p = 0.02), but was not significantly associated with the Rothman index. CONCLUSIONS: Use of this technology may allow clinicians with limited ultrasound experience to determine an objective measure of B-line burden.

Lower mortality risk associated with remdesivir + dexamethasone versus dexamethasone alone for the treatment of patients hospitalized for COVID-19.

BACKGROUND: Treatment guidelines were developed early in the pandemic when much about COVID-19 was unknown. Given the evolution of SARS-CoV-2, real-world data can provide clinicians with updated information. The objective of this analysis was to assess mortality risk in patients hospitalized for COVID-19 during the Omicron period receiving remdesivir+dexamethasone versus dexamethasone alone. METHODS: A large, multicenter US hospital database was used to identify hospitalized adult patients, with a primary discharge diagnosis of COVID-19 also flagged as "present on admission" treated with remdesivir+dexamethasone or dexamethasone alone from December 2021 to April 2023. Patients were matched 1:1 using propensity score matching and stratified by baseline oxygen requirements. Cox proportional hazards model was used to assess time to 14- and 28-day in-hospital all-cause mortality. RESULTS: A total of 33 037 patients were matched, with most patients ≥65 years old (72%), White (78%), and non-Hispanic (84%). Remdesivir+dexamethasone was associated with lower mortality risk versus dexamethasone alone across all baseline oxygen requirements at 14 days (no supplemental oxygen charges: adjusted hazard ratio [95% CI]: 0.79 [0.72-0.87], low flow oxygen: 0.70 [0.64-0.77], high flow oxygen/non-invasive ventilation: 0.69 [0.62-0.76], invasive mechanical ventilation/extracorporeal membrane oxygen (IMV/ECMO): 0.78 [0.64-0.94]), with similar results at 28 days. CONCLUSIONS: Remdesivir+dexamethasone was associated with a significant reduction in 14- and 28-day mortality compared to dexamethasone alone in patients hospitalized for COVID-19 across all levels of baseline respiratory support, including IMV/ECMO. However, the use of remdesivir+dexamethasone still has low clinical practice uptake. In addition, these data suggest a need to update the existing guidelines.

Marginal zone B cells are required for optimal humoral responses to allograft.

Antibody-mediated rejection (AMR) is among the leading causes of graft failure in solid organ transplantation. However, AMR treatment options are limited by incomplete understanding the mechanisms underlying de novo donor specific antibody (DSA) generation. The development of pathogenic isotype-switched DSA in response to transplanted allografts is typically attributed to follicular B cells undergoing germinal center reaction whereas the contribution of other B cell subsets have not been previously addressed. The current study investigated the role of recipient marginal zone (MZ) B cells in DSA responses using a mouse models of heart and renal allotransplantation. MZ B cells rapidly differentiate into antibody-secreting cells in response to allotransplantation. Despite selective depletion of FO B cells in heart allograft recipients, MZ B cells are sufficient for T-dependent IgM and early IgG DSA production. Furthermore, the presence of intact MZ B cell subset is required to support generation of pathogenic isotype-switched DSA in renal allograft recipients containing donor-reactive memory helper T cells. These findings are the first demonstration for the role of MZ B cells in humoral alloimmune responses following solid organ transplantation and identify MZ B cells as a potential therapeutic target for minimizing de novo DSA production and AMR in transplant recipients.

Economic impact of mortality prediction by predictive model at first and second treatment for bovine respiratory disease.

OBJECTIVE: To evaluate a predictive model's ability to determine cattle mortality following first and second treatment for bovine respiratory disease and to understand the differences in net returns comparing predictive models to the status quo. METHODS: 2 boosted decision tree models were constructed, 1 using data known at first treatment and 1 with data known at second treatment. Then, the economic impact of each outcome (true positive, true negative, false positive, and false negative) was estimated using various market values to determine the net return per head of using the predictive model to determine which animals should be culled at treatment. This was compared to the status quo to determine the difference in net return. RESULTS: The models constructed for the prediction of mortality performed with moderate accuracy (areas under the curve > 0.7). The economic analysis found that the models at a high specificity (> 90%) could generate a positive net return in comparison to status quo. CONCLUSIONS: This study showed that predictive models may be a useful tool to make culling decisions and could result in positive net returns. CLINICAL RELEVANCE: Bovine respiratory disease is the costliest health condition experienced by cattle on feed. Feedyard record-keeping systems generate vast amounts of data that could be used in predictive models to make management decisions. It is essential to understand the accuracy of predictions made via machine learning. However, the economic impact of implementing predictive models in a feedyard will influence adoption.

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins.

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

Sex and Age-Specific Analysis of Basketball-Related Shoulder Dislocations in the United States: A National Injury Data Review.

HYPOTHESIS/PURPOSE: Basketball-related shoulder dislocations frequently present to emergency departments (EDs) in the US. This study aimed to identify the primary mechanisms, distributions, and trends of these injuries. METHODS: All data was extracted from the National Electronic Injury Surveillance System (NEISS), a public database representing approximately 100 US EDs. NEISS was queried for all basketball-related injuries and shoulder dislocations from January 1, 2013 to December 31, 2022. Clinical narratives were used to assign injury mechanisms and the presence of player contact. RESULTS: Between 2013 and 2022, 52,417 basketball-related shoulder dislocations were reported. 30.9% of all basketball-related shoulder injuries were dislocations, and 30.5% of all joint dislocations occurred at the shoulder. Basketball-related shoulder dislocations decreased significantly from 2013-2022 (p<.001). From 2019 to 2020, a 31.0% decrease was identified. The most common mechanism of shoulder dislocation was falling (36.9%). Males accounted for 92.5% of all shoulder dislocations. However, females were significantly more likely than males to dislocate their shoulders from player contact (15.5% of female dislocations v. 10.0% of male dislocations, p<.001). Only 0.2% of all dislocations resulted in hospitalization. 10.4% of dislocations resulted from contact with another player. Compared to other age groups, young adults (43.3%) and adolescents (42.7%) presented with the majority of shoulder dislocations. Children were more likely to dislocate their shoulder from sustaining a direct blow (25.5%), while all other age groups were more likely to have fallen. Children were also the most likely to sustain a dislocation involving player contact (23.9%). CONCLUSION: Basketball-related shoulder dislocations decreased significantly from 2013 to 2022. Females and children were significantly more likely to present with a dislocation by sustaining player contact. Across all demographics, teaching athletes how to break their falls safely may decrease rates of dislocation by minimizing impacts on a posteriorly outstretched arm.

INTRA- AND INTER-HOST EVOLUTION OF HUMAN NOROVIRUS IN HEALTHY ADULTS.

Background: Human noroviruses are a leading cause of acute and sporadic gastroenteritis worldwide. The evolution of human noroviruses in immunocompromised persons has been evaluated in many studies. Much less is known about the evolutionary dynamics of human norovirus in healthy adults. Methods: We used sequential samples collected from a controlled human infection study with GI.1/Norwalk/US/68 virus to evaluate intra- and inter-host evolution of a human norovirus in healthy adults. Up to 12 samples from day 1 to day 56 post-challenge were sequenced using a norovirus-specific capture probe method. Results: Complete genomes were assembled, even in samples that were below the limit of detection of standard RT-qPCR assays, up to 28 days post-challenge. Analysis of 123 complete genomes showed changes in the GI.1 genome in all persons, but there were no conserved changes across all persons. Single nucleotide variants resulting in non-synonymous amino acid changes were observed in all proteins, with the capsid VP1 and nonstructural protein NS3 having the largest numbers of changes. Conclusions: These data highlight the potential of a new capture-based sequencing approach to assemble human norovirus genomes with high sensitivity and demonstrate limited conserved immune pressure-driven evolution of GI.1 virus in healthy adults.

Palpitations: Evaluation, Management, and Wearable Smart Devices.

Palpitations are a common symptom described by patients as a feeling of a racing or fluttering heart, a pounding chest, irregular or skipped heartbeats, or a pounding sensation in the neck. They are associated with a low mortality rate; however, recurrent palpitations have been shown to impair quality of life and increase health care use. Common triggers are cardiac disorders, endocrine and metabolic disorders, medication or illicit drug use, or psychosomatic disorders. A detailed history, physical examination, directed laboratory studies, and 12-lead electrocardiography are often sufficient to identify the etiology of palpitations. Additional testing may be indicated to include echocardiography, cardiac stress testing, electrocardiogram monitoring, or electrophysiologic studies to distinguish whether symptoms correlate with cardiac arrhythmia or structural or ischemic heart disease. Management of palpitations is based on the suspected etiology. In most cases of cardiac-induced palpitations, the treatment can include reassurance, education, trigger avoidance, or use of atrioventricular nodal blockers. Tachyarrhythmias may require cardiac ablation. Patients who have palpitations with no arrhythmia causality and no cardiac disease should be reassured; however, screening for psychosomatic disorders should be considered. Wearable smart devices with ambulatory electrocardiogram monitoring technologies are currently available to consumers; these tools have shown diagnostic accuracy for detection of arrhythmias, allowing patients to have greater participation in their health care. Am Fam Physician. 2024; 110(3):259-269.

Extending the defect tolerance of halide perovskite nanocrystals to hot carrier cooling dynamics.

Defect tolerance is a critical enabling factor for efficient lead-halide perovskite materials, but the current understanding is primarily on band-edge (cold) carriers, with significant debate over whether hot carriers can also exhibit defect tolerance. Here, this important gap in the field is addressed by investigating how intentionally-introduced traps affect hot carrier relaxation in CsPbX3 nanocrystals (X = Br, I, or mixture). Using femtosecond interband and intraband spectroscopy, along with energy-dependent photoluminescence measurements and kinetic modelling, it is found that hot carriers are not universally defect tolerant in CsPbX3, but are strongly correlated to the defect tolerance of cold carriers, requiring shallow traps to be present (as in CsPbI3). It is found that hot carriers are directly captured by traps, instead of going through an intermediate cold carrier, and deeper traps cause faster hot carrier cooling, reducing the effects of the hot phonon bottleneck and Auger reheating. This work provides important insights into how defects influence hot carriers, which will be important for designing materials for hot carrier solar cells, multiexciton generation, and optical gain media.

Sleep, Sleep Apnea, and Fatigue in People Living With HIV.

BACKGROUND: People living with HIV (PLWH) often report fatigue even when viral load is suppressed. Obstructive sleep apnea (OSA), which is often associated with fatigue, is common in PLWH, but whether OSA explains fatigue in this population is unknown. SETTING: Academic university-affiliated HIV and Sleep Medicine Clinics. METHODS: PLWH, aged 18-65 years, with a body mass index of 20-35 kg/m2 and viral suppression (RNA <200 copies per mL), were recruited to undergo daytime questionnaires, including the Functional Assessment of Chronic Illness Therapy Fatigue Scale and Epworth Sleepiness Scale, 7 days of actigraphy (to determine daily sleep duration and activity amplitude and rhythms), and an in-laboratory polysomnography to assess for the presence and severity of OSA. RESULTS: Of 120 subjects with evaluable data, 90 (75%) had OSA using the American Academy of Sleep Medicine 3% desaturation or arousal criteria, with an apnea-hypopnea index >5/h. There was no difference in Functional Assessment of Chronic Illness Therapy scores between those with and without OSA, although those with OSA did report more daytime sleepiness as measured using the Epworth Sleepiness Scale. In a multivariable model, predictors of fatigue included more variable daily sleep durations and decreased mean activity counts. Sleepiness was predicted by the presence of OSA. CONCLUSION: OSA was very common in our cohort of PLWH, with those with OSA reporting more sleepiness but not more fatigue. Variability in sleep duration was associated with increased fatigue. Further study is needed to determine if treatment of OSA, or an emphasis on sleep consistency and timing, improves symptoms of fatigue in PLWH.

Comparative efficiency of the SWAT model and a deep learning model in estimating nitrate loads at the Tuckahoe creek watershed, Maryland.

Modeling nitrate fate and transport in water sources is an essential component of predictive water quality management. Both mechanistic and data-driven models are currently in use. Mechanistic models, such as SWAT, simulate daily nitrate loads based on the results of simulating water flow. Data-driven models allow one to simulate nitrate loads and water flow independently. Performance of SWAT and deep learning model was evaluated in cases when deep learning model is used in (a) independent simulations of flow series and nitrate concentration series, and (b) in both flow rate and concentration simulations to obtain nitrate load values. The data were collected at the Tuckahoe Creek watershed in Maryland, United States. The data-driven deep learning model was built using long-short-term-memory (LSTM) and three-dimensional convolutional networks (3D Convolutional Networks) to simulate flow rate and nitrate concentration using weather data and imagery to derive leaf area index according to land use. Models were calibrated with data over training period 2014-2017 and validated with data over testing period. SWAT Nash-Sutcliffe efficiency (NSE) was 0.31 and 0.40 for flow rate and -0.26 and -0.18 for the nitrate load rate over training and testing periods, respectively. Three data-driven modeling scenarios were implemented: (1) using the observed flow rate and simulated nitrate concentration, (2) using the simulated flow rate and observed nitrate concentration, and (3) using the simulated flow rate and nitrate concentration. The deep learning model performed better than SWAT in all three scenarios with NSE from 0.49 to 0.58 for training and from 0.28 to 0.80 for testing periods with scenario 1 showing the best results. The difference in performance was most pronounced in fall and winter seasons. The deep learning modeling can be an efficient alternative to mechanistic watershed-scale water quality models provided the regular high-frequency data collection is implemented.

Cellular and molecular determinants of bacterial burden in leprosy granulomas revealed by single-cell multimodal omics.

BACKGROUND: Which cell populations that determine the fate of bacteria in infectious granulomas remain unclear. Leprosy, a granulomatous disease with a strong genetic predisposition, caused by Mycobacterium leprae infection, exhibits distinct sub-types with varying bacterial load and is considered an outstanding disease model for studying host-pathogen interactions. METHODS: We performed single-cell RNA and immune repertoire sequencing on 11 healthy controls and 20 patients with leprosy, and integrated single-cell data with genome-wide genetic data on leprosy. Multiplex immunohistochemistry, and in vitro and in vivo infection experiments were conducted to confirm the multimodal omics findings. FINDINGS: Lepromatous leprosy (L-LEP) granulomas with high bacterial burden were characterised by exhausted CD8+ T cells, and high RGS1 expression in CD8+ T cells was associated with L-LEP. By contrast, tuberculoid leprosy (T-LEP) granulomas with low bacterial burden displayed enrichment in resident memory IFNG+ CD8+ T cells (CD8+ Trm) with high GNLY expression. This enrichment was potentially attributable to the communication between IL1B macrophages and CD8+ Trm via CXCL10-CXCR3 signalling. Additionally, IL1B macrophages in L-LEP exhibited anti-inflammatory phenotype, with high APOE expression contributing to high bacterial burden. Conversely, IL1B macrophages in T-LEP were distinguished by interferon-γ induced GBP family genes. INTERPRETATION: The state of IL1B macrophages and functional CD8+ T cells, as well as the relationship between them, is crucial for controlling bacterial persistence within granulomas. These insights may indicate potential targets for host-directed immunotherapy in granulomatous diseases caused by mycobacteria and other intracellular bacteria. FUNDING: The Key research and development program of Shandong Province (2021LCZX07), Natural Science Foundation of Shandong Province (ZR2023MH046), Youth Science Foundation Cultivation Funding Plan of Shandong First Medical University (Shandong Academy of Medical Sciences) (202201-123), National Natural Science Foundation of China (82471800, 82230107, 82273545, 82304039), the China Postdoctoral Science Foundation (2023M742162), Shandong Province Taishan Scholar Project (tspd20230608), Joint Innovation Team for Clinical & Basic Research (202410), Central guidance for local scientific and technological development projects of Shandong Province (YDZX2023058).

ACTION-ARC Pediatric and Adult Congenital Heart Disease Ventricular Assist Device Adverse Event Definitions-2023.

Adverse events (AEs) experienced by children and adults with congenital heart disease (CHD) on ventricular assist devices (VADs) are sometimes unique to these populations. The Advanced Cardiac Therapies Improving Outcomes Network (ACTION) and the Academic Research Consortium (ARC) aimed to harmonize definitions of pediatric and CHD AEs for use in clinical trials, registries, and regulatory evaluation. Data from the ACTION registry and adjudication committee were used to adapt general mechanical circulatory support ARC definitions. This ACTION-ARC international expert panel of trialists, clinicians, patients, families, statisticians, biomedical engineers, device developers, and regulatory agencies drafted and iterated definitions harmonized to ACTION data and existing literature during sessions conducted between December 2022 and May 2023, followed by dissemination across clinical/research audiences and professional organizations and further revision. Both email-linked, internet-based surveys and in-person discussions were used as a modified Delphi process. Nineteen AE types were identified and defined, including seven new event types and six event types that were deleted and will no longer be collected, achieving consensus. ACTION-ARC paired rigorous development with methodical stakeholder involvement and dissemination to define pediatric VAD AEs to facilitate assimilation of data across future clinical trials and evaluation of devices for VAD-supported children and adults with CHD.

Implications of Cross-Reactivity and Cross-Protection for Pneumococcal Vaccine Development.

Pneumococcal vaccines are a cornerstone for the prevention of pneumococcal diseases, reducing morbidity and mortality in children and adults worldwide. Pneumococcal vaccine composition is based on the polysaccharide capsule of Streptococcus pneumoniae, which is one of the most important identified contributors to the pathogen's virulence. Similarities in the structural composition of polysaccharides included in licensed pneumococcal vaccines may result in cross-reactivity of immune response against closely related serotypes, including serotypes not included in the vaccine. Therefore, it is important to understand whether cross-reactive antibodies offer clinical protection against pneumococcal disease. This review explores available evidence of cross-reactivity and cross-protection associated with pneumococcal vaccines, the challenges associated with the assessment of cross-reactivity and cross-protection, and implications for vaccine design and development.

Study protocol for Early Tracking of Childhood Health determinants (ETCHED): A longitudinal observational life course study.

BACKGROUND: The prevalence of childhood obesity and diabetes continues to rise in the United States (US), especially among minority populations. The objective of the Early Tracking of Childhood Health Determinants (ETCHED) study is to investigate the role of adverse fetal and early-life risk exposures that contribute to the development of childhood obesity and metabolic risk. METHODS: ETCHED is a longitudinal observational study of American Indian/Alaska Native (AI/AN) and Hispanic pregnant woman and their offspring. Pregnant mothers ≥ 18 years old are enrolled at a large public hospital system in the southwestern US. Enrolled mothers are followed through pregnancy, delivery, and the maternal/offspring dyad will be followed until the child's 18th birthday. At each maternal visit, questionnaires assessing medical history, diet, physical activity, sleep, perceived stress, and socioeconomic and sociocultural information are obtained. Standard laboratory tests during maternal visits include glycemic measures, lipids, and renal function. Additional bio samples obtained include venous blood samples and cord blood for obesity/metabolic biomarkers and genetic/epigenetic testing, urinalysis, placental tissue for examining functional pathways, breast milk for metabolomics, and stool for metabolites and microbiome analysis. The offspring will have 6 infant/toddler visits at 6-12 weeks, 4 months, 6 months, 18 months, 2 and 3 years respectively. Thereafter, they will undergo comprehensive research visits (major visits) at 4-5 years, 6-9 years, 10-13 years, and 14-17 years. The major visits in children include detailed medical history, anthropometry, developmental assessment, socioeconomic and environmental assessments (food insecurity, family structure, and childcare), feeding and activity, biochemical tests, genetics/epigenetic testing, and ultrasound elastography. Electronic health records will be reviewed for additional clinical information. The primary analysis will constitute estimation of correlation coefficients between continuous variables. The planned study duration in this ongoing study is 23-years. DISCUSSION: This is a life course study that that will examine biological and environmental risk factors for obesity and cardiometabolic risk from the intrauterine period to early childhood and adolescence in a population with high-risk of obesity and type 2 diabetes in the United States. The ETCHED study would also provide a unique opportunity to combine multi-omics and clinical data to create novel integrative models to predict the cardiometabolic risk associated with childhood obesity and possibly identify etiopathogenetic mechanisms and future targets of intervention. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov identifier: NCT03481829. Updated July 19, 2024, https://clinicaltrials.gov/study/NCT03481829?cond=ETCHED&rank=1 .

Preoptic area controls sleep-related seizure onset in a genetic epilepsy mouse model.

In genetic and refractory epileptic patients, seizure activity exhibits sleep-related modulation/regulation and sleep and seizure are intermingled. In this study, by using one het Gabrg2 Q390X KI mice as a genetic epilepsy model and optogenetic method in vivo, we found that subcortical POA neurons were active within epileptic network from the het Gabrg2 Q390X KI mice and the POA activity preceded epileptic (poly)spike-wave discharges(SWD/PSDs) in the het Gabrg2 Q390X KI mice. Meanwhile, as expected, the manipulating of the POA activity relatively altered NREM sleep and wake periods in both wt and the het Gabrg2 Q390X KI mice. Most importantly, the short activation of epileptic cortical neurons alone did not effectively trigger seizure activity in the het Gabrg2 Q390X KI mice. In contrast, compared to the wt mice, combined the POA nucleus activation and short activation of the epileptic cortical neurons effectively triggered or suppressed epileptic activity in the het Gabrg2 Q390X KI mice, indicating that the POA activity can control the brain state to trigger seizure incidence in the het Gabrg2 Q390X KI mice in vivo. In addition, the suppression of POA nucleus activity decreased myoclonic jerks in the Gabrg2 Q390X KI mice. Overall, this study discloses an operational mechanism for sleep-dependent seizure incidence in the genetic epilepsy model with the implications for refractory epilepsy. This operational mechanism also underlies myoclonic jerk generation, further with translational implications in seizure treatment for genetic/refractory epileptic patients and with contribution to memory/cognitive deficits in epileptic patients.