bluuebunny/crossref_metadata_2025 huggingface dataset:
Transcriptome Enhanced Rice Grain Metabolic Model Identifies Histidine Level as a Marker for Grain Chalkiness
Authors: Chowdhury Niaz Bahar , Chandran Anil Kumar Nalini , Walia Harkamal , Saha Rajib
Published: October 2024

Rising temperatures due to global warming can negatively impact rice grain quality and yield. This study investigates the effects of increased warmer night temperatures (WNT), a consequence of global warming, on the quality of rice kernel, particularly grain chalkiness. By integrating computational and experimental approaches, we used a rice grain metabolic network to discover the metabolic factors of chalkiness. For this, we reconstructed the rice grain genome-scale metabolic model (GSM), iOSA3474-G and incorporated transcriptomics data from three different times of the day (dawn, dawn 7h, and dusk) for both control and WNT conditions with iOSA3474-G. Three distinct growth phases: anoxia, normoxia, and hyperoxia, were identified in rice kernels from the GSMs, highlighting the grain-filling pattern under varying oxygen levels. We predicted histidine as a marker of normoxia, during which kernel chalkiness occurs. Moreover, we proposed tyrosine as a marker for the hyperoxic growth phase. We also proposed a potential link between monodehydroascorbate reductase, an enzyme with evolutionary significance dating back to the carboniferous era, in regulating the hyperoxic growth phase. Metabolic bottleneck analysis identified nucleoside diphosphate kinase as a central regulator of metabolic flux under different conditions. These findings provide targeted insights into the complex metabolic network governing rice grain chalkiness under WNT conditions. Integration of GSM and transcriptomics data, enhanced our understanding of the intricate relationship between environmental factors, metabolic processes, and grain quality and also offer markers that can be useful to develop rice with improved resilience.
EGFR and tyrosine kinase inhibitor interactions probed by hydrogen-deuterium exchange and mass spectrometry (HDX-MS)
Authors: Ashtekar Kumar D. , Lemmon Mark A. , Tsutsui Yuko
Published: October 2024

EGFR is one of the primary drug targets for treating non-small cell lung cancer (NSCLC) patients carrying EGFR oncogenic mutations in the tyrosine kinase domain (TKD). Such patients typically receive tyrosine kinase inhibitors (TKIs) to inhibit aberrant activation of EGFR; however, together with the appearance of the TKI-resistant mutations, TKIs’ severe side effects often limit their clinical usage. To develop TKIs with the wild-type sparing effect, the wild-type structures bound to various TKIs ought to be characterized, though comparisons of such crystal structures do not show clear differences. To characterize subtle EGFR TKD structural changes upon TKI binding that cannot be gleaned from crystal structure comparisons, we employed HDX-MS. We show inhibitor-dependent EGFR dynamics that are displayed even among the TKD bound to chemically similar inhibitors. Such inhibitor-dependent structural changes appear to underlie TKI side effects and the selectivity of covalent inhibitors.

Highlights

EGFR shows TKI-dependent dynamics even if TKIs are structurally similar.

The stability of the TKI-encounter complexes correlates with their side effects.

Covalent TKIs disrupt the binding pocket of wild-type EGFR.

The structure of the osimertinib-L858R/T790M complex is extremely rigid.
Mitomycin C Retains Efficacy after Adaptive Laboratory Evolution ofStaphylococcus aureus
Authors: Petersen Maiken Engelbrecht , Khamas Amanda Batoul , Østergaard Lars Jørgen , Jørgensen Nis Pedersen , Meyer Rikke Louise
Published: October 2024

Antibiotic resistance is one of the greatest threats against human health and the misuse and overuse of antibiotics is a key factor driving resistance development. During prolonged antibiotic treatment of chronic infections, the antimicrobial pressure facilitates selection of antibiotic resistance mutations. It has been suggested that using antibiotics in combinations may reduce the emergence of resistance. Furthermore, antibiotic tolerant persister cells may be a reservoir for resistance development, so targeting persister cells with anti-persister drugs could also reduce the emergence of resistance.

In this study, we conducted a 42-day adaptive laboratory evolution experiment usingStaphylococcus aureusexposed to common antibiotics and the anti-persister drug mitomycin C, either alone or in combination. We monitored susceptibility daily and assessed phenotypic changes in growth and biofilm formation in evolved strains. Whole-genome sequencing revealed mutations linked to antibiotic resistance and phenotypic shifts.

Resistance developed rapidly against rifampicin, while ciprofloxacin and daptomycin showed slower resistance emergence. Treatments with vancomycin or mitomycin C resulted in minimal changes in susceptibility. Combination therapies generally delayed resistance, though resistance was not fully prevented. Notably, mitomycin C combined with rifampicin effectively suppressed rifampicin resistance. Sub-inhibitory antibiotic concentrations were associated with both known and novel mutations, including in the nucleotide excision repair system and azoreductase, following mitomycin C treatment—mutations not previously reported.

While combination therapy delayed resistance, mitomycin C’s efficacy and ability to prevent rifampicin resistance highlights its potential in combating antibiotic resistance. Further investigation is needed to evaluate the broader application of anti-persister drugs in resistance prevention.
Cis-regulatory mutations co-opting circadian clock regulation underlie naturally selected extreme trait inArabidopsis halleri
Authors: Castanedo Leonardo , Cebula Justyna , Nouet Cécile , Spielmann Julien , Hanikenne Marc , Krämer Ute
Published: October 2024

HEAVY METAL ATPase 4(HMA4) is required for the naturally selected traits of zinc/cadmium hyperaccumulation and hypertolerance of inArabidopsis halleri.Cis-regulatory alterations and tandem triplication ofAhHMA4result in substantially elevated transcript levels compared to the closely related non-tolerant non-hyperaccumulatorArabidopsis thaliana. Here we identifycis-regulatory Metal Hyperaccumulation Elements (MHEs) necessary forAhHMA4promoter activity, employing sequence comparisons and motif elicitation analyses combined with progressive deletions and site-directed mutagenesis of promoter-reporter constructs. We report that the promoters of allAhHMA4gene copies share a distal MHE1 (consensus TGTAAC), and a proximal pair of MHE2s identical or highly similar to the Evening Element (AAAATATCT). Evening elements are known binding sites of Arabidopsis CIRCADIAN CLOCK-ASSOCIATED 1 (CCA1), a phytochrome-regulated transcription factor in the core circadian clock. We show that the promoter of eachAhHMA4gene copy, but not ofAtHMA4, mediates enhanced transcript levels of the reporter and their diel rhythmicity. These functional characteristics areCCA1-dependent and recapitulated by a synthetic reporter construct placing the MHE2 pair into theAtHMA4-promoter sequence context, according to the example of theAhHMA4-1promoter. Consistent with our observations in transgenic reporter lines,AhHMA4transcript levels follow a diel rhythm in wild-typeA. halleriplants. Different fromA. halleri, we identify complex repressive functionalities co-localizing with an upstream lncRNA and an intron in the 5’ untranslated region ofA. thaliana HMA4. In summary, our work exemplifies howcis-regulatory mutations contributed to the evolution of extreme physiological traits through the co-option of the circadian clock regulatory network.
Female Specific Restrictive Cardiomyopathy and Metabolic Dysregulation in transgenic mice expressing a Peptide of the Amino-Terminus of GRK2
Authors: Bledzka Kamila M. , Manaserh Iyad H. , Ifft Amanda D. , Rennison Julie H. , Bohacek Madison , Vasiliauskas Katie M. , Grondolsky Jessica , Ampong Isaac , Van Wagoner David R. , Schumacher Sarah M.
Published: October 2024

Cardiovascular disease and heart failure are a major health challenge, with sex differences in pathophysiology and treatment responses critically influencing patient outcomes. G protein-coupled receptor (GPCR) kinase 2 (GRK2) is a pivotal regulator of cellular signaling whose elevation is a hallmark of heart failure progression. Its complex network of protein interactions impact a wide range of physiological and pathophysiological processes including cardiac function. In this study, we examined the effects of cardiac-restricted expression of an amino-terminal peptide of GRK2 (βARKnt) in female mice subjected to acute and chronic pressure overload. Our findings reveal that that βARKnt affects hypertrophy development and cardiac function differently in female mice than in males, leading to a transition to heart failure not observed in control females or βARKnt males. Notably, the βARKnt female mice exhibited baseline hypertrophy with distinct left atrial morphology, increased fibrosis, and immune cell infiltration compared to the controls, which progressed under chronic stress, indicating adverse cardiac remodeling. Furthermore, βARKnt female mice, unlike males, exhibit impaired tissue respiration following acute pressure overload and altered glucose sensitivity and insulin tolerance, highlighting significant remodeling of cardiac and systemic metabolism.
Evaluating Plant-Microbe Associations in Response to Environmental Stressors to Enhance Salt Marsh Restoration
Authors: Davis Kai A. , McKinney Mary-Margaret S. , Gittman Rachel K. , Peralta Ariane L.
Published: October 2024

Microorganisms can enhance nutrient acquisition or suppress diseases from pathogens, while plants can provide carbon resources and oxygen to root-associated microbes. However, human activities have altered nutrient cycles and disrupted such mutualisms. Therefore, we need to understand how to promote positive plant-microbe associations to aid in restoring coastal wetland ecosystems where human stressors and climate change (e.g., hurricanes, sea-level rise) challenge restoration outcomes. This study examined how salinity stressors influence plant-microbe relationships, where we hypothesize that the presence of microbes will buffer stressor effects. We used a whole sediment inocula approach and exposed marsh cordgrass (Sporobolus alterniflorus) plugs to a replicated factorial experiment with three levels of microbiome addition (microbial inocula, autoclaved microbial inocula, no microbe control) and two levels of salinity (<0.5 psu, 20 psu), replicated ten times. We added microbial inocula from the marsh site with autoclaved soilless media and exposed half the plugs to saltwater (20 psu) and half to freshwater (<0.5 psu). Results revealed that marsh microbial inocula additions during early plant development may ameliorate salinity stressors and could be critical for future restoration efforts. The addition of marsh microbial inocula provided a rescue effect from salinity stress, observed in plant height over time. Aboveground and belowground biomass, bacterial diversity H’, and bacterial evenness J’ were similar across microbial and water treatments; however, water and microbial treatments significantly influenced the bacterial community composition. This work provides evidence that microbiome stewardship buffers against environmental stressors and could promote plant establishment for coastal wetland restoration.
Context-based protein function prediction in bacterial genomes
Authors: Toibazar Daulet , Kulmanov Maxat , Hoehndorf Robert
Published: October 2024

Motivation

The rapid growth of sequencing data from high-throughput technologies has emphasized the need to uncover the functions of unannotated genes. Recent advancements in deep learning algorithms have enabled researchers to utilize various features to predict protein functions. Traditionally, these algorithms treat proteins as independent functional units or consider interactions only at the protein level. However, prokaryotes often preserve specific genomic neighborhoods over evolutionary time, providing valuable context for predicting protein functions. This context can arise from genes near the gene of interest or synteny regions, where the conserved order of genes on chromosomes results from common ancestry.

Results

We developed a transformer-based model to pre-train representations of proteins based on their genomic context, and use this model for predicting protein functions. Our results show that context-based protein representations capture context-specific functional semantics and can effectively predict protein functions. We use our model to investigate the influence of phylogenetic distance and homology on the performance of context-dependent function prediction, and find that synteny affects the prediction performance substantially, except for some functions where the function is determined by the genomic context. Our experiments allow us to gain insights into the factors affecting the performance and applicability of context-based function prediction methods across diverse prokaryotic genomes and meta-genomes.

Availability and implementation

The generated model, including all training code and generated data, is freely available athttps://github.com/bio-ontology-research-group/Genomic_context.

Contact

robert.hoehndorf@kaust.edu.sa
Aerotolerant methanogens use seaweed and seagrass metabolites to drive marine methane emissions
Authors: Hall N. , Wong W. W. , Lappan R. , Ricci F. , Glud R. N. , Kawaichi S. , Rotaru A-E. , Greening C. , Cook P. L. M.
Published: October 2024

Methanogenesis is classically thought to be limited to strictly anoxic environments. While oxygenated oceans are a known methane source, it is argued that methanogenesis is driven by methylphosphonate-degrading bacteria or potentially is associated to zooplankton gut microbiomes rather than by methanogenic archaea. Here we show throughin situmonitoring andex situmanipulations that methane is rapidly produced by archaea in frequently oxygenated sandy sediments. By combining biogeochemical, metagenomic, and culture-based experiments, we show this activity is driven by aerotolerant methylotrophic methanogens (Methanococcoidesspp.) broadly distributed in surface layers of sandy sediments, providing evidence of a hidden process contributing to marine methane emissions. Moreover, we show that methane emissions are driven by methylated seaweed and seagrass metabolites, revealing an unexpected feedback loop between eutrophication-driven algal blooms and greenhouse gas emissions.
Less Haste, More Speed: Does delayed blood culture loading lead to adverse incubation time or yield?
Authors: Deas Gavin , Hamilton Fergus , Williams Philip
Published: October 2024

Background

Blood culture remains a vital diagnostic tool in the acutely unwell patient. The UK Standards for Microbiology Investigations (SMI) stipulate pre-analytical requirements that are aimed at increasing yield and reducing turnaround time. The requirement to load blood cultures onto incubators within 4 hours has shown to reduce turnaround time but limited evidence exists as to whether it improves yield.

Methods

We extracted blood culture results including organism growth, time to detection (TTD), location and time of sample collection from 4 hospitals in Southwest England. We then used mixed effects, Bayesian linear and logistic regression models to examine the effect of predictor variables like time to loading (TTL) on the response variable of growth or TTD. We used generalised additive models to explore non-linearity.

Results

449,191 culture sets were analysed, 398,077 of which had enough data to include in the final analysis. 37,255 sets flagged positive (9.36%) of which 21,330 were considered pathogens. Our primary analysis identified a small decrease in yield with each hour delay in loading, OR 0.997 (95% credible interval, CrI 0.994 - 1.001). This effect was largest inStreptococcus pneumoniae, agalactiaeandpyogenes. In our analysis on TTD, culture sets spend 10.98 (95% CrI 7.8 – 13.2) minutes less incubating for each hour delay. There was no convincing non-linearity in either of these effects.

Conclusion

There is a marginal loss of growth for every hour a blood culture is left unincubated, with the loss of recovery ofStreptococcus pyogenesand other streptococci most common. There was no evidence of a reduction in Gram-negatives, anaerobes, or yeasts. There was a small decrease in TTD for delayed sets. This analysis suggests there is only marginal benefit in reducing time to load blood cultures on incubators.

Highlights

The UK SMI stipulates blood cultures be loaded within 4 hours of being taken

The effect on yield has not been determined for delayed loading

We found overall that there was a marginal 0.3% loss of yield per hour delay

There was a significant loss ofStreptococcus pyogenesat 3.2% per hour delay
A qualitative study exploring the diagnostic and treatment journeys of children and young people with gastroduodenal disorders of gut-brain interaction, their families, and the clinicians who care for them
Authors: Humphrey Gayl , Law Mikaela , Keane Celia , Andrews Christopher N , Gharibans Armen , O’Grady Greg
Published: October 2024

Background

Gastroduodenal disorders of gut-brain interaction (DGBI) are prevalent in the paediatric population. Diagnostic pathways and subsequent treatment management approaches for children and young people can be highly variable, leading to diverse patient and clinical experiences. This study explores the DGBI diagnostic experiences of children and their families and the perspectives of clinicians in the New Zealand context.

Methods

Semi-structured interviews were conducted with 12 children with gastroduodenal DGBIs and their families and clinicians who care for children with DGBIs. Interviews were recorded, transcribed, and narratively analysed.

Results

Five children and family themes emerged: 1) how it all started, 2) the impacts symptoms had on child and family life, 3) their experiences with testing and investigations, 4) the perceptions and impacts of challenging clinical relationships, and 5) the uncertainness of trial and error treatments. Clinicians also identified five key themes: 1) navigating the complexity of presenting symptomology, 2) the challenging diagnostic investigation decision-making process, 3) navigating management and treatment approaches, 4) a lack of standardised clinical pathways, and 5) establishing therapeutic relationships with patients and families.

Conclusion

Children, their families, and clinicians confirmed the clinical complexity of DGBIs, the challenges of diagnosis and management, and the stress this places on therapeutic relationships. Clearer diagnostic pathways and new investigations that could provide improved identification and discrimination of DGBIs are needed to minimise the treat-test repeat cycle of care and improve health outcomes.
Predicting 30-Day and 1-Year Mortality in Heart Failure with Preserved Ejection Fraction (HFpEF)
Authors: Shin Ikgyu , Bhatt Nilay , Alashi Alaa , Kandala Keervani , Murugiah Karthik
Published: October 2024

Objectives

To develop and compare prediction models for 30-day and 1-year mortality in Heart failure with preserved ejection fraction (HFpEF) using EHR data, utilizing both traditional and machine learning (ML) techniques.

Background

HFpEF represents 1 in 2 heart failure patients. Predictive models in HFpEF, specifically those derived from electronic health record (EHR) data, are less established.

Methods

Using MIMIC-IV EHR data from 2008-2019, patients aged ≥ 18 years admitted with a primary diagnosis of HFpEF were identified using ICD-9 and 10 codes. Demographics, vital signs, prior diagnoses, and lab data were extracted. Data was partitioned into 80% training, 20% test sets. Prediction models from seven model classes (Support Vector Classifier (SVC), Logistic Regression, Lasso Regression, Elastic Net, Random Forest, Histogram-based Gradient Boosting Classifier (HGBC), and XGBoost) were developed using various imputation and oversampling techniques with 5-fold cross-validation. Model performance was compared using several metrics, and individual feature importance assessed using SHapley Additive exPlanations (SHAP) analysis.

Results

Among 3910 hospitalizations for HFpEF, 30-day mortality was 6.3%, and 1-year mortality was 29.2%. Logistic regression performed well for 30-day mortality (Area Under the Receiver operating characteristic curve (AUC) 0.83), whereas Random Forest (AUC 0.79) and HGBC (AUC 0.78) for 1-year mortality. Age and NT-proBNP were the strongest predictors in SHAP analyses for both outcomes.

Conclusion

Models derived from EHR data can predict mortality after HFpEF hospitalization with comparable performance to models derived from registry or trial data, highlighting the potential for clinical implementation.
Protocol for the Feasibility and Acceptability of Mentalization-based Treatment for Early Adolescents With Depression: A Short-Term Psychotherapy Approach for Patients and Families
Authors: Moran-Kneer Javier , Duarte Javiera , Alkabes-Esquenazi Louise , Solervicens Paula , García Francisca , Arancibia Marcelo , Díaz Francisca , Avalos Nicole
Published: October 2024

Background

Approximately 13.4% of children and adolescents worldwide suffer from depression, with early onset often manifesting before the age of 14 and disproportionately affecting vulnerable groups. The prevalence of adolescent depression has increased since the COVID-19 pandemic, with significant long-term impacts on development, social functioning, and academic performance. Mentalization-based treatment (MBT), particularly the MBT-A model tailored for adolescents, has shown promise in addressing depression by increasing mentalizing capacity. This study explores the feasibility and acceptability of a short-term MBT-A intervention that incorporates both individual and family components to address depression in early adolescents.

Methods:

This feasibility pilot study will recruit 15 adolescents aged 10--14 years who are diagnosed with mild to moderate depression from primary healthcare centers and psychological care clinics in Valparaíso, Chile. The participants will undergo a 12-session MBT-A intervention, which is structured into three phases: joint understanding of the problem, intensive promotion of mentalization, and evaluation of the process. Outcomes will be assessed through mixed methods, including quantitative measures (e.g., recruitment rate, adherence rate, effect size on depressive symptoms) and qualitative interviews with patients, families, and therapists. Discussion: Fostering mentalization in adolescents with depression may reduce depressive symptoms and enhance emotional regulation, benefiting both individuals and their families. This study aims to provide preliminary data to inform the planning of a larger randomized controlled trial (RCT). By incorporating family components, the intervention not only addresses individual symptoms but also promotes supportive family dynamics, which are crucial for sustaining therapeutic gains. This pilot study will identify practical aspects of implementing MBT-A and gather essential data on its feasibility and potential efficacy in a real-world setting.
Prevalence and predictors of microvascular and macrovascular diabetes complications in adult Ugandans: a systematic review and meta-analysis
Authors: Kibirige Davis , Olum Ronald , Turyamureeba William , Morgan Bethan , Kyazze Andrew Peter , Nsubuga Yakobo , Okot Jerom , Lumu William , Bongomin Felix
Published: October 2024

Introduction

There is a growing prevalence of diabetes and related chronic complications in Uganda. We conducted a systematic review and meta-analysis to document the prevalence and predictors of five microvascular and macrovascular diabetes complications in adult Ugandans with diabetes.

Materials and Methods

We searched Medline, EMBASE, CINAHL, Cochrane Library, and Africa Journal Online databases. We included studies on the prevalence and predictors of any chronic microvascular or macrovascular diabetes complications of interest. We conducted a random effect meta-analysis to determine the pooled prevalence of each diabetes complication. A narrative review was used to describe the significant predictors.

Results

A total of 20 studies involving 11,400 participants were included. The pooled mean (standard deviation) age of the participants was 54.8 (3.6) years, with the majority being female (pooled proportion of 61.1%, 95% confidence interval [CI] 57.1-65.2). For the microvascular diabetes complications, the pooled prevalence of diabetic neuropathy, retinopathy, and nephropathy was 56.8% (95% CI 44.9-68.7, I2= 98.56%, p<0.001), 19.5% (95% CI 3.9-35.2, I2= 99.60%, p<0.001), and 17.7% (95% CI 7.3-28.0, I2= 99.36%, p<0.001), respectively. For the macrovascular diabetes complications, the pooled prevalence of peripheral arterial disease and diabetic foot disease was 32.2% (95% CI 15.8-48.7, I2= 97.67%, p<0.001) and 5.5% (95% CI 1.7-9.2, I2= 90.22%, p<0.001), respectively.

Hypertension comorbidity, physical inactivity, family history of diabetes, body mass index ≤30 kg/m2, and pregnancy were predictors of diabetic nephropathy in three studies. In two studies, a history of a foot ulcer and age >60 years were predictors of diabetic neuropathy while female sex, hypertension comorbidity, and use of glibenclamide were predictors of peripheral arterial disease.

Discussion

Chronic diabetes complications are very common in adult Ugandans with diabetes, especially diabetic neuropathy and peripheral arterial disease. Regular screening and optimal management of diabetes and its complications should be emphasised in Uganda.
Detection of Acute Myocardial Infarction Using Deep Learning on Lead-I ECG Data
Authors: Davarmanesh Parmida , Lin Qian , Tenison Irene , Jabbour Gabriel , Alam Ridwan
Published: October 2024

Myocardial Infarction (MI) is a major global health concern due to its high mortality and morbidity rates. Early detection of MI is crucial for timely medical intervention and improved patient outcomes. In this study, we investigate the feasibility of predicting MI using lead-I of electrocardiogram (ECG) data, with a focus on practical applications for wearable monitoring systems. Utilizing the PTB-XL dataset, which includes a comprehensive collection of 12-lead ECG recordings with both normal and various MI samples, we employ deep learning techniques to develop a binary classification model. For MI detection using lead-I, we achieved an AUC of 0.92 and an AUPR of 0.82 on the test set. In comparison, using 6-lead and 12-lead configurations both resulted in an AUC of 0.99. These findings demonstrate the potential for detecting MI using only lead-I, as measured by wearable devices. This advancement could significantly enhance clinical outcomes for MI patients by enabling timely detection and intervention.
Sickle cell, thalassemia, and heat: risk estimates and equity policy considerations from an exploratory timeseries study in California
Authors: Pearson Dharshani , Winger Beth Apsel , Ebisu Keita
Published: October 2024

Background

People born with hemoglobinopathies, such as sickle cell disease (SCD) and thalassemia, as well as people who are carriers for these disorders [sickle cell trait (SCT), thalassemia trait or thalassemia minor (TM)], may experience increased symptom-triggers and related illnesses from heat because their cells are susceptible to dehydration. Additionally, historical, and structural injustices could also exacerbate risk vulnerabilities among some communities.

Methods

In this work, we (1) present an overview of biological plausibility linking heat and hemoglobinopathy-related hospitalizations; (2) analyze the relationship between daily apparent temperature and such hospitalizations in California using Patient Discharge Data (PDD) and a two-stage timeseries study design with Poisson regression to estimate a state-wide hospitalization risk estimate; (3) discuss how structural barriers working in conjunction with demographic and genetic factors have conferred added risk to some Californians, thereby presenting deep-seeded equity ramifications.

Results

Our final dataset, restricted to the warm season, consisted of 96,908 daily counts of any hemoglobinopathy, listed as primary or secondary hospital diagnoses in PDD data. For an overall result, we observed an elevated risk of 3.0% (95% CI: 0.6, 5.5) per 10-degree Fahrenheit (°F) increase in apparent temperature at the last 30-day cumulative exposure window. For secondary hospital diagnoses of SCT-associated outcomes, when limited to very populous areas, we observed an elevated association of 7.0% at lag 23 (95% CI: 2.2, 12.1).

Conclusions

We observed excess symptom associations at various heat exposure levels, highlighting the need to examine longer exposure periods and potential care delays (stigma, medical racism, healthcare access). Differences and uncertainties could also stem from other comorbidities, age, genetics, housing and socioeconomic characteristics, or lifestyle variations. Education on the possible links between climate and hemoglobinopathy symptoms, changing demographics, and long overdue research funding may help close the gap in this interconnecting, critical environmental justice issue.

Highlights

People with hemoglobinopathies, or inherited red blood cell abnormalities, can experience health effects from high outdoor temperatures.

Using over 20 years of hospitalization records, we examined a potential relationship among those who have an inherited hemoglobinopathy or those who are carriers.

We found a connection between heat and hemoglobinopathy-related conditions over varying exposure periods lasting up to a month.

Structural barriers to care and medical racism may exacerbate health outcomes during heat episodes for some of those who have inherited hemoglobinopathies, highlighting the need for novel strategies to combat disparities in healthcare access and quality of care.
Increased Insular Functional Connectivity During Repetitive Negative Thinking in Major Depression and Healthy Volunteers
Authors: Edwards Landon S , Ganesan Saampras , Tay Jolene , Elliott Eli S , Misaki Masaya , White Evan J , Paulus Martin P , Guinjoan Salvador M , Tsuchiyagaito Aki
Published: October 2024

Background

Repetitive negative thinking (RNT) in major depressive disorder (MDD) involves persistent focus on negative self-related experiences. Resting-state fMRI shows that the functional connectivity (FC) between the insula and the superior temporal sulcus is critical to RNT intensity. This study examines how insular FC patterns differ between resting-state and RNT-induction in MDD and healthy participants (HC).

Methods

Forty-one individuals with MDD and twenty-eight HCs (total n=69) underwent resting-state and RNT-induction fMRI scans. Seed-to-whole brain analysis using insular subregions as seeds was performed.

Results

No diagnosis-by-run interaction effects were observed across insular subregions. MDD participants showed greater FC between bilateral anterior, middle, and posterior insular regions and the cerebellum (z = 4.31 to 6.15). During RNT-induction, both MDD and HC participants demonstrated increased FC between bilateral anterior and middle insula and key brain regions, including prefrontal cortices, parietal lobes, posterior cingulate cortex, and medial temporal gyrus, encompassing the STS (z = 4.47 to 8.31). Higher trait-RNT was associated with increased FC between the right dorsal anterior and middle insula and regions in the DMN and salience network in MDD participants (z = 4.31 to 6.15). Greater state-RNT scores were linked to increased FC in similar insular regions, the bilateral angular gyrus and right middle temporal gyrus (z = 4.47 to 8.31).

Conclusions

Hyperconnectivity in insula subregions during active rumination, especially involving the DMN and salience network, supports theories of heightened self-focused and negative emotional processing in depression. These findings emphasize the neural basis of RNT when actively elicited in MDD.
Impact of Participation Bias on Disease Prevalence Estimation in theAll of UsResearch Program: A Case Study of Ischemic Heart Disease and Stroke
Authors: Lee Younga Heather , Patil Ankita , Clark Cheryl R. , Botero Monik C. , Stein David W. , Karlson Elizabeth W.
Published: October 2024

Importance

Disease prevalence estimation is highly sensitive to sample characteristics shaped by recruitment and data collection strategies. Using follow-up study modules that require active participant engagement may introduce participation bias, affecting the accuracy of disease prevalence estimation.

Objective

To estimate the prevalence of ischemic heart disease (IHD) and stroke using electronic health records (EHR) and the self-reported Personal Medical History (PMH) survey collected in theAll of UsResearch Program.

Design and settings

Cross-sectional study aimed at estimating the prevalence of IHD and stroke among 266,472 participants with EHR in the latest release of theAll of UsRegistered Tier Curated Data Repository (R2022Q4R9).

Main outcomes and measures

Primary outcomes were IHD and stroke, ascertained using expert-curated diagnostic and procedure codes recorded in EHR. Secondary outcomes were IHD and stroke, ascertained using responses from the PMH survey. To mitigate the impact of participation bias in the PMH survey responses, we applied poststratification weighting based on annual household income and education.

Results

Of the 266,472 participants with EHR, 17,054 (6.4%) were identified as having IHD and 7,461 (2.8%) as having stroke based on the EHR definitions. Among PMH survey respondents, the EHR-based prevalence was lower at 5.6% (95% CI, 5.4-5.7) for IHD and 2.2% (95% CI, 2.1-2.3) for stroke, compared to 7.2% (95% CI, 7.0-7.3) for IHD and 3.3% (95% CI, 3.2-3.4) for stroke among non-respondents. The PMH survey-based prevalence among respondents was 5.9% (95% CI, 5.7-6.0) for IHD and 3.6% (95% CI, 3.5-3.7) for stroke, with higher estimates among non-Hispanic White participants after applying poststratification weights.Conclusion and relevance:Our findings suggest that while the currentAll of Uscohort with EHR reflects the general US population for IHD and stroke prevalence, participants completing the PMH survey are skewed toward higher socioeconomic status and medical literacy. Future research should refine bias mitigation strategies when using voluntary follow-up data to estimate disease prevalence in this cohort.

Key Points

Question

What is the prevalence of ischemic heart disease (IHD) and stroke in theAll of UsResearch Program cohort with electronic health records (EHR), and in the subset of these participants who also completed the Personal Medical History (PMH) survey?

Findings

The EHR-based prevalence estimates of IHD and stroke were 6.4% and 2.8%, respectively. They were significantly lower among PMH survey respondents but higher among non-respondents.

Meaning

Participants who complete follow-up study modules, such as the PMH survey, may disproportionately represent those with higher socioeconomic status and better health, potentially leading to an underestimation of IHD and stroke prevalence.
Interethnic Validation of an ECG Image Analysis Software for Detecting Left Ventricular Dysfunction in Emergency Department Population
Authors: Lee Haemin , Kwon Woon Yong , Song Kyoung Jun , Jo You Hwan , Kim Joonghee , Cho Youngjin , Hwang Ji Eun , Choi Yeongho
Published: October 2024

Background

We previously developed and validated an AI-based ECG analysis tool (ECG Buddy) in a Korean population. This study aims to validate its performance in a U.S. population, specifically assessing its LV Dysfunction Score and LVEF-ECG feature for predicting LVEF <40%, using NT-ProBNP as a comparator.

Methods

We identified emergency department (ED) visits from the MIMIC-IV dataset with information on LVEF <40% or ≥40%, along with matched 12-lead ECG data recorded within 48 hours of the ED visit. The performance of ECG Buddy’s LV Dysfunction Score and LVEF-ECG feature was compared with NT-ProBNP using Receiver Operating Characteristic - Area Under the Curve (ROC-AUC) analysis.

Results

A total of 22,599 ED visits were analyzed. The LV Dysfunction Score had an AUC of 0.905 (95% CI: 0.899 - 0.910), with a sensitivity of 85.4% and specificity of 80.8%. The LVEF-ECG feature had an AUC of 0.908 (95% CI: 0.902 - 0.913), sensitivity 83.5%, and specificity 83.0%. NT-ProBNP had an AUC of 0.740 (95% CI: 0.727 - 0.752), with a sensitivity of 74.8% and specificity of 62.0%. The ECG-based predictors demonstrated superior diagnostic performance compared to NT-ProBNP (all p<0.001).

In the Sinus Rhythm subgroup, the LV Dysfunction Score achieved an AUC of 0.913, and LVEF-ECG had an AUC of 0.917, both outperforming NT-ProBNP (0.748, 95% CI: 0.732 - 0.763, all p<0.001).

Conclusion

ECG Buddy demonstrated superior accuracy compared to NT-ProBNP in predicting LV systolic dysfunction, validating its utility in a U.S. ED population.
Integration of Mendelian Randomization and Genome-wide Association Analysis Reveals Potential Benefits of Cheese Intake on Human Intelligence
Authors: Chen Peng , Cao Zhikang , Feng Jing , Li Zhipeng , Nie Shaoping
Published: October 2024

The brain relies on a range of nutrients for optimal functioning. However, the causal nature between dietary components and human intelligence are still unclear. This study integrates Mendelian randomization (MR) and genome-wide associations analyses to investigate the relationships. The results show that cheese exerts the most remarkable genetic correlation and causal association with cognition-related traits. We conduct a large-scale meta-analysis of genome-wide associations studies (GWAS) consisting of over 800,000 participants and discover 71 genetic determinants for cheese consumption. Additional MR using the GWAS results recovers the causal effects of cheese on all the cognition-related traits, and also reveals its effects on education, psychological states and gene expressions in multiple brain tissues. Additionally, knockout mouse models and pathway enrichment analysis indicate that the loci mapped genes are involved in cognitive functions and brain characteristics. In conclusion, our comprehensive analysis supports the potential benefits of cheese consumption on human intelligence.
Association of echocardiographic cardiac valve calcification with major adverse cardiovascular events in patients on acute myocardial infarction
Authors: Chen Chuyun , Wang Na , Yu Yang , Jia Jia , Fan Fangfang , Yang Ying , Zhang Yan
Published: October 2024

BACKGROUND

The role of cardiac valve calcification (CVC) in secondary prevention post-acute myocardial infarction (AMI) remains unclear. This study investigated the association between CVC and major adverse cardiovascular events (MACE) in AMI.

METHODS AND RESULTS

AMI patients hospitalized in Peking University First Hospital were consecutively enrolled. Participants were grouped according to the measurement of transthoracic echocardiography on admission. According to aortic valve calcification (AVC) and mitral annular calcification (MAC), patients were divided into Group 1 (with no valve calcification), Group 2 (with single valve calcification) and Group 3 (with both valve calcification). The primary endpoint was MACE (defined as a composite of nonfatal stroke, nonfatal myocardial infarction and cardiac death). A cohort of 911 AMI patients was recruited in this retrospective study. There were 513(56.31%), 337(36.99%) and 61(6.70%) in Group 1, Group 2 and Group 3, respectively. During follow-up (median, 5.11 years), 277(30.41%) patients developed MACE, 94(10.32%) had nonfatal stroke, 155(17.01%) had recurrent myocardial infarction (MI) and 106(11.64%) were identified as cardiac death. Comparing with Group 1, the adjusted hazard ratios (HR) for primary endpoint and recurrent MI in Group 3 was 1.61 (1.06, 2.43) and 1.70 (1.00, 2.89), respectively. And the adjusted HR of primary endpoint and cardiac death in moderate and severe AVC group was 1.50 (1.01, 2.23) and 1.97 (1.10, 3.51) compared with non-AVC group.

CONCLUSIONS

AMI patients with CVC were at significantly increased risk of MACE, although existing differences of the position and the severity of calcification. Screening for AVC and MAC is necessary in secondary prevention.

RESEARCH PERSPECTIVE

What Is New?

This study is the first to detail the association between cardiac valve calcification (CVC), specifically aortic valve calcification (AVC) and mitral annular calcification (MAC), with major adverse cardiovascular events (MACE) in patients after an acute myocardial infarction (AMI).

It also identifies the concurrent presence of MAC and AVC as an independent predictor of MACE.

What Are the Clinical Implications?

The stud y suggests that screening for AVC and MAC post-AMI could help identify patients at higher risk of MACE, leading to more targeted preventive care and potentially improving outcomes.
Kidney Status and Events Preceding Death in Heart Failure: A Real-world Nationwide Study
Authors: Anjum Deewa Zahir , Garred Caroline Hartwell , Carlson Nicholas , Fosbol Emil , Elmegaard Mariam , Jhund Pardeep S. , McMurray John J.V. , Petrie Mark C. , Kober Lars , Schou Morten
Published: October 2024

Background

Chronic kidney disease (CKD) is a frequent comorbidity in heart failure (HF) patients, affecting prognosis and mortality. This study investigates the relationship between kidney function and adverse kidney events preceding death in HF patients.

Methods

We analyzed registry data of HF patients who died between 2014 and 2021, with at least one year of HF diagnosis. Adverse kidney events, including acute kidney injury (AKI) and end- stage kidney disease (ESKD), were assessed. Patients were grouped by estimated glomerular filtration rate (eGFR) one year before death: eGFR≥60, eGFR 30-59, and eGFR<30.

Results

Among 36,435 HF patients who died, 37% had eGFR≥60, 46% had eGFR 30-59, and 17% had eGFR<30 one year before death. Median age was 81 years, and 61.2% were men. Adverse kidney events occurred in 13.1% of patients. AKI was inversely related to kidney function, affecting 6.5% (95% confidence interval 6.1-6.9) of those with eGFR≥60, 7.0% (6.6.-7.4) with eGFR 30-59, and 21.9% (20.9-22.9) with eGFR<30. ESKD occurred in 0.7%(0.6-0.9), 2.6% (2.4-2.8), and 35.5% (34.3-36.7) of patients in the respective eGFR categories. In the last three months before death, kidney function notably declined, with increased chronic kidney replacement therapy. Factors associated with higher adverse kidney events included younger age, male sex, in-hospital death, and greater frailty.

Conclusions

In HF patients, AKI and ESKD are common in the last year of life, particularly in those with lower baseline eGFR, with kidney decline accelerating in the final months.
Automated Leg Dystonia Diagnosis in Children with Cerebral Palsy Using Machine Learning
Authors: Bajpai Rishabh , Rust Alyssa , Lott Emma , Kim Susie , Gandham Sushma , Chintalapati Keerthana , Blackburn Joanna , Gelineau-Morel Rose , Kruer Michael C. , Mingbundersuk Dararat , O Malley Jennifer , Tochen Laura , Waugh Jeff , Wu Steve , Feyma Timothy , Aravamuthan Bhooma Rajagopalan
Published: October 2024

Importance: Dystonia in cerebral palsy (CP) is common and debilitating but under-diagnosed, particularly in the legs. Only 13% of children with CP and leg dystonia have that dystonia diagnosed in clinic. Yet, early and accurate dystonia diagnosis is critical for appropriate treatment selection. Objective: To facilitate automated leg dystonia diagnosis in CP, our objective was to develop open-source software that used machine learning (ML) models and clinically available video data. Design, Setting, and Participants: In this cross-sectional study, videos of children with CP (age 5 and older) doing a seated alternating hand open-close task were acquired between 1/1/2020 and 12/14/23 from two tertiary care CP centers (193 videos from Center 1, 30 videos from 2). These videos were assessed for leg dystonia by 8 pediatric movement disorders physicians (gold-standard diagnosis by expert consensus). Movement features they cited when identifying dystonia were extracted from their consensus-building discussions using conventional content analysis and were then quantified from the videos leveraging our open-source software. Quantified features from 163 videos from Center 1 were used to train ML models (4664 models based on 11 ML algorithms) which were then tested on 30 videos from Center 1 and 30 videos from Center 2. Main Outcome(s) and Measure(s): Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of ML models were computed as compared to gold-standard leg dystonia diagnosis by expert consensus. Results: Expert-cited quantifiable movements associated with dystonia diagnosis were used to identify 63 kinematics features to extract from videos. Feature importance analysis showed that variance features had higher importance than amplitude features. ML models achieved 84% sensitivity, 84% specificity, 84% PPV, 85% NPV, and 84% accuracy for identifying leg dystonia in testing videos from Center 1 and 100% sensitivity, 67% specificity, 75% PPV, 100% NPV, and 83% accuracy for identifying leg dystonia in videos from Center 2. However, for videos where at least 60% of experts agreed regarding the presence or absence of dystonia (n=23/30 from Center 2), ML models were 100% accurate for identifying leg dystonia. Conclusions/Significance: We have developed open-source software that can use clinically acquired videos to identify leg dystonia in children with CP. These methods may be useful for facilitating clinical dystonia diagnosis in children with CP.
Comprehensive identification of plasma membrane repair proteins revealed spatiotemporal cellular responses to plasma membrane damage
Authors: Yamazaki Yuta , Kono Keiko
Published: October 2024

Damage to the plasma membrane (PM) is common in all types of cells. PM repair processes, including exocytosis and endocytosis, are not mutually exclusive; rather, they collaborate to repair the wound. However, the temporal coordination between the repair processes remains poorly understood. Here, by comprehensively identifying PM repair proteins, we resolved the temporal PM repair processes at the damage site inSaccharomyces cerevisiae. Of the 80 repair proteins identified, 72 proteins were previously unreported repair protein candidates. We showed that polarity establishment, polarized exocytosis, and clathrin-mediated endocytosis (CME) occur in a specific temporal order at the damage site. Furthermore, we showed that polarized exocytosis and CME are coupled at the damage site, delivering PM repair proteins with transmembrane domains between the growing bud site and the damage site. This study provides insights into the temporal dynamics of coordinated cellular response to PM damage.