bluuebunny/crossref_metadata_2025_split huggingface dataset:
A case report on congenital hypothyroidism and alpha thalassemia in children with anemia and muscle damage as the main manifestation
Authors: Zhang Ying , Li Xuan , Wang Xiao-jun , Yang Ju-pin , Li Ju-mei , Yuan Wen-qian , Dong Yu-ying , Yu Jin-peng , Wen Yu , Liu Ming-wei 
Published: August 2024

Rationale:
This study reports the first case of congenital hypothyroidism (CH) and alpha thalassemia in a child in China, with anemia and muscle damage as the main manifestations. Analyzing and studying this case is of great significance in reducing missed and misdiagnosed CH and will provide a clinical strategy for treating these patients.

Patient concerns:
Child, female, 2 years and 7 months old, the child appeared dispirited, had poor appetite, shallow complexion, reduced activities with anemia, elevated muscle enzymes, height, and growth retardation.

Diagnoses:
The child was diagnosed with CH with alpha thalassemia.

Interventions:
The patient was treated with levothyroxine sodium and anemia correction.

Outcomes:
The children’s current spirit, appetite, red face, normal limb activity, physical development, and intelligence were significantly better than those of normal children of the same age.

Conclusions:
CH with alpha thalassemia, especially anemia and muscle damage as the main manifestations, has not been reported. Administration of levothyroxine sodium is effective in correcting anemia in patients with CH and alpha thalassemia.

Lesson:
Due to CH and alpha thalassemia, there are no specific symptoms and they are prone to missed diagnosis and misdiagnosis. Therefore, patients with anemia and elevated muscle enzyme levels should be routinely tested for thyroid function to diagnose them early and provide proper treatment to avoid negative consequences.
The Level of Psychological Distress Is Associated With Circadian Rhythm, Sleep Quality, and Inflammatory Markers in Adolescent and Young Adults With Gynecological Cancer
Authors: Luo Yating , Duan Yinglong , Zhou Yi , Yi Shuijing , Dai Chanyuan , Luo Xiaofei , Kang Yue , Wan Ziyu , Qin Ning , Zhou Xing , Liu Xiangyu , Xie Jianfei , Cheng Andy S.K. 
Published: August 2024

Background
Adolescent and young adult (AYA) patients with cancer commonly experience psychological distress, with female patients experiencing higher levels of psychological distress.

Objective
The aim of this study was to investigate the relationships among circadian rhythm, sleep quality, inflammatory markers, and psychological distress in AYA patients with gynecological cancer in China.

Methods
This cross-sectional study enrolled 75 AYA patients in treatment for gynecological cancer, 64 of whom completed the Chinese version of the Morningness-Eveningness Questionnaire and the Distress Thermometer. Actigraphy was used to measure their objective sleep parameters: total sleep time, sleep onset latency, and sleep efficiency. Blood samples collected 3 times across 1 day were used to measure the average levels of interleukin 6, C-reactive protein, and tumor necrosis factor α.

Results
The mean score on the Distress Thermometer among respondents was 4.23, which was above the cutoff value for clinically significant psychological distress. High levels of psychological distress may be associated with circadian disturbances, poor sleep quality, and elevated inflammatory markers. In addition, total sleep time, sleep onset latency, and tumor necrosis factor α averages were the dominant predictors of these AYA patients’ psychological distress.

Conclusion
Improving sleep quality and reducing the levels of inflammatory markers may relieve psychological distress among AYA patients with gynecological cancer.

Implications for Practice
Healthcare professionals need to actively focus on circadian rhythm, inflammatory markers, sleep quality, and mental health status in AYA cancer patients to better meet their therapeutic and psychological needs.
Nitrous Oxide Alters Functional Connectivity in Medial Limbic Structures in Treatment-Resistant Major Depression
Authors: Conway Charles R. , Palanca Ben Julian A. , Zeffiro Thomas , Gott Britt M. , Brown Frank , de Leon Victoria , Barnes Linda , Nguyen Thomas , Xiong Willa , Lessov-Schlaggar Christina N. , Espejo Gemma , Mennerick Steven , Zorumski Charles F. , Nagele Peter 
Published: August 2024

AbstractWhile nitrous oxide (N2O) has demonstrated antidepressant properties in treatment-resistant major depression (TRD), little is known about neural mechanisms mediating these effects. Employing serial resting-state functional magnetic resonance imaging (rs-fMRI), we compared spatiotemporal effects of inhaled N2O on brain functional connectivity in TRD patients (n=14) and non-depressed healthy controls (n=16, CNTL). Participants received sequential, one-hour inhalations of either 50% N2O/oxygen or air/oxygen (placebo), with sessions separated by at least one month in random cross-over order. BOLD-contrast rs-fMRI scans were acquired at three time points: pre-inhalation, 2 hours post-inhalation, and 24 hours post-inhalation. For the rs-fMRI functional connectivity analyses, fivea prioriseeds in medial limbic structures targeted cortical networks implicated in major depression – the salience, anterior and posterior default mode, reward, and cingulo-opercular networks – and a nexus in the dorsal paracingulate region previously identified in MDD (“dorsal nexus”). Depression, dissociation, and psychosis assessments were made before and after inhalations. In TRD patients, functional connectivity was reduced in all seeded networks and the voxel-wise global analysis after N2O exposure. N2O progressivelydecreasedconnectivity in patients with TRD butincreasedconnectivity in healthy controls. In TRD patients, each seeded network demonstrated post-inhalation functional connectivity reductions in the dorsal paracingulate gyrus (“dorsal nexus”). This study further elucidates neural mechanisms underlying the antidepressant properties of N2O, supporting the notion that N2O specifically alters mood-associated brain regions in the depressed brain state by reducing functional connectivity within these brain networks.The trial was registered atClinicalTrials.gov(NCT02994433).One sentence summaryNitrous oxide reduces long-range functional brain connectivity in treatment-resistant major depression, which may underlie its antidepressant action.
Leveraging protein-protein interactions in phenotype prediction through graph neural networks
Authors: Smeriglio Riccardo , Rosell-Mirmi Joana , Radeva Petia , Abante Jordi 
Published: August 2024

AbstractCurrent genotype-to-phenotype models, such as poly-genic risk scores, only account for linear relationships between genotype and phenotype and ignore epistatic interactions, limiting the complexity of the diseases that can be properly characterized. Protein-protein interaction networks have the potential to improve the performance of the models. Moreover, interactions at the protein level can have profound implications in understanding the genetic etiology of diseases and, in turn, for drug development. In this article, we propose a novel approach for phenotype prediction based on graph neural networks (GNNs) that naturally incorporates existing protein interaction networks into the model. As a result, our approach can naturally discover relevant epistatic interactions. We assess the potential of this approach using simulations and comparing it to linear and other non-linear approaches. We also study the performance of the proposed GNN-based methods in predicting Alzheimer’s disease, one of the most complex neurodegenerative diseases, where our GNN approach outperform state of the art methods. In addition, we show that our proposal is able to discover critical interactions in the Alzheimer’s disease. Our findings highlight the potential of GNNs in predicting phenotypes and discovering the underlying mechanisms of complex diseases.
Single-cell analysis identifies distinct CD4+ T cells associated with the pathobiology of pediatric obesity-related asthma
Authors: Thompson David A. , Wabara Yvonne B. , Duran Sarai , Reichenbach Anna , Chen Laura , Collado Kayla , Yon Changsuek , Greally John M. , Rastogi Deepa 
Published: August 2024

AbstractPediatric obesity-related asthma is characterized by non-atopic T helper 1 (Th1) inflammation and steroid resistance. CDC42 upregulation in CD4+T cells underliesTh1 inflammation but the CD4+T cell subtype(s) with CDC42 upregulation and their contribution to steroid resistance are not known. Compared to healthy-weight asthma, obesity-alone and healthy-weight controls, single-cell transcriptomics of obese asthma CD4+T cells revealedCDC42upregulation in 3 clusters comprised of naïve and central memory T cells, which differed from the cluster enriched for Th1 responses that was comprised of effector T cells.NR3C1,coding for glucocorticoid receptor, was downregulated, while genes coding for NLRP3 inflammasome were upregulated, in clusters with CDC42 upregulation and Th1 responses. Conserved genes in these clusters correlated with pulmonary function deficits in obese asthma. These findings suggest that several distinct CD4+T cell subtypes are programmed in obese asthma for CDC42 upregulation, Th1 inflammation, and steroid resistance, and together contribute to obese asthma phenotype.SummaryCD4+T cells from obese children with asthma are distinctly programmed for non-allergic immune responses, steroid resistance and inflammasome activation, that underlie the obese asthma phenotype.
A Design Principle for slow-wave sleep firing pattern with Na+dynamics
Authors: Sato Tomohide R. , Ode Koji L. , Kinoshita Fukuaki L. , Ueda Hiroki R. 
Published: August 2024

SUMMARYNon-rapid eye movement (NREM) sleep is characterized by electroencephalography (EEG) signals with high amplitude and low frequency. This signal is thought to originate from the synchronized activity of cortical neurons, showing the alternating bursting state (up state) and resting state (down state). This activity is termed as slow-wave sleep (SWS) firing pattern. We previously proposed the importance of Ca2+-dependent hyperpolarization pathway in generating this firing pattern by introducing the averaged-neuron (AN) model, which describes neuronal activity based on the Hodgkin-Huxley type model. In the AN model, Ca2+-dependent K+channels are involved in the transition from the up to the down state. Here we focus on the intracellular Na+dynamics which are not explicitly described in the AN model. A revised AN model, termed as Na+-centered AN (NAN) model, proposes that the activation of voltage-gated Na+channels leads to intracellular Na+accumulation, which in turn triggers the activation of Na+-dependent K+(KNa) channels or Na+/K+ATPases, resulting in the down state. Changes in the activation kinetics of voltage-gated Na+channels are important in shaping SWS firing pattern as well as explaining the inter-spike interval changes between SWS and AWAKE firing pattern. Mathematically, transition from the up state to the down state occurs in accordance with the change in the number of the fixed point in the dynamical system with the changes in the intracellular Na+concentration. The importance of Na+-dependent pathway is elucidated even with the coexistence of Ca2+-dependent pathway. Subsequent analysis with network model suggests that the result of averaged neuron model with Na+pathway can be extended to the population of neurons. Therefore, our model proposes that voltage-gated Na+channels and Na+-dependent K+channels or Na+/K+ATPases are also the candidate pathways for the generation of SWS firing pattern.
Brain wave dynamics in Hopfield Kuramoto model
Authors: Yao Ruwei , Li Yichao , Yao Xintong , Wang Kang , Qu Jingling , Hong Bo , Zou Xiaolong 
Published: August 2024

AbstractWhole brain neural oscillation activities exhibit multiple wave patterns and seem to be supported by the common circuit network structure. We proposed a Hebbian-like Kuramoto model based entirely on heterogeneous connectivity strength rather than phase delay, which encodes the multiple phase patterns as attractors. We systematically investigated how the model dynamic landscape influenced by attractors and their corresponding eigenvalues, as well as how to control the stability of equilibrium points and the occurrence of high dimension bifurcations. This framework enables us to reproduce the dominant wave activity components in human brain functional MRI signal, and provides a canonical model for the multi body physical system spatio-temporal pattern attractor dynamics.
Biologically-informed Killer cell immunoglobulin-like receptor (KIR) gene annotation tool
Authors: Ford Michael K.B. , Hari Ananth , Zhou Qinghui , Numanagić Ibrahim , Sahinalp S. Cenk 
Published: August 2024

AbstractNatural killer (NK) cells are essential components of the innate immune system, with their activity significantly regulated by Killer cell Immunoglobulin-like Receptors (KIRs). The diversity and structural complexity of KIR genes present significant challenges for accurate genotyping, essential for understanding NK cell functions and their implications in health and disease. Traditional genotyping methods struggle with the variable nature of KIR genes, leading to inaccuracies that can impede immunogenetic research. These challenges extend to high-quality phased assemblies, which have been recently popularized by the Human Pangenome Consortium. This paper introduces BAKIR (Biologically-informed Annotator for KIR locus), a tailored computational tool designed to overcome the challenges of KIR genotyping and annotation on high-quality, phased genome assemblies. BAKIR aims to enhance the accuracy of KIR gene annotations by structuring its annotation pipeline around identifying key functional mutations, thereby improving the identification and subsequent relevance of gene and allele calls. It uses a multi-stage mapping, alignment, and variant calling process to ensure high-precision gene and allele identification, while also maintaining high recall for sequences that are significantly mutated or truncated relative to the known allele database. BAKIR has been evaluated on a subset of the HPRC assemblies, where BAKIR was able to improve many of the associated annotations and call novel variants. BAKIR is freely available on GitHub, offering ease of access and use through multiple installation methods, including pip, conda, and singularity container, and is equipped with a user-friendly command-line interface, thereby promoting its adoption in the scientific community.
Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour
Authors: Schienstock Dominik , Hor Jyh Liang , Devi Sapna , Mueller Scott N. 
Published: August 2024

AbstractWith the ever-increasing complexity of microscopy modalities, it is imperative to have computational workflows that allow researchers to process and perform in-depth quantitative analysis of the resulting images. However, workflows that enable flexible, interactive and intuitive analysis from raw images to analysed data are lacking. We present Cecelia, a toolbox that integrates various open-source packages into a coherent data management suite to make quantitative image analysis accessible for non-specialists.
Miniaturizing, Modifying, and Augmenting Nature’s Proteins with Raygun
Authors: Devkota Kapil , Shonai Daichi , Mao Joey , Soderling Scott , Singh Rohit 
Published: August 2024

AbstractProteins are nature’s versatile nanomachines, but engineering them for enhanced function or novel applications remains challenging. Current methods for protein modification struggle to design sequence alterations, especially insertions and deletions, that preserve structure. Here, we introduce Raygun, a template-guided protein design framework that unlocks efficient miniaturization, modification, and augmentation of existing proteins. Using a novel probabilistic encoding of protein sequences constructed from language model embeddings, Raygun is able to generate diverse candidates with deletions, insertions, and substitutions while maintaining core structural elements. We show that Raygun can shrink proteins by 10-25% (sometimes over 50%) while preserving predicted structural integrity and fidelity, introduce extensive sequence diversity while preserving functional sites, and even expand proteins beyond their natural size. In experimental validation, we successfully miniaturize the fluorescent proteins eGFP and mCherry to synthesize functional variants, two of which are smaller than 96% of fluorescent proteins reported in FPbase. Raygun’s conceptual innovations in template-based protein design open new avenues for protein engineering, potentially catalyzing the development of more efficient molecular tools and therapeutics.
Quantifying transmissibility and dispersion of SARS-CoV-2 variants and subvariants of concern in England
Authors: Swallow Ben , Grier Joshua , Panovska-Griffiths Jasmina 
Published: August 2024

AbstractThe SARS-CoV-2 pandemic was characterised by continual emergence of variants. For improved future pandemic preparedness it is important to understand whether each successive variant has been more infectious and more widely spread. In this paper, we used genetic sequencing data from the COVID-19 Genomics UK Consortium in England and robust statistical models to quantify transmissibility advantage and spatial heterogeneity of successive SARS-CoV-2 variants and their sub-variants circulating between September 2020 and December 2022.Our results show that each variant was progressively more transmissible and more heterogeneously spread. Alpha was 10-40% more transmissible than B.1.177, Delta was 40-100% more transmissible than Alpha, and Omicron was 80-120% more transmissible than the Delta variant. Progressive variants were also more spatially heterogeneous: Alpha was mostly clustered in London and Southeast England, Delta was less clustered and prevalent in both Northwest and Southeast England, while Omicron was dispersed across the country. Successive sub-variants of different clade were more transmissible and spatially spread than the previous ones (e.g. the Omicron BA.1.1 variant was 20-60% more transmissible than the previous Delta AY.4 variant). However, sub-variants of the same clade didn’t differ in transmissibility or spatial spread. Our study improves understanding of transmission intensity and spatial heterogeneity across SARS-CoV-2 variants.Ascertaining the threat posed by emerging variants and across infectious diseases is crucial to be better prepared for the next pandemic. Our method provides a tool for analysis of variant surveillance data, translatable across pathogens and settings, that can capture an emerging variant early and as part of the pandemic preparedness strategy.
Assessing innovative care models for musculoskeletal disorders’ management in the emergency department using Time-Driven Activity-Based Costing
Authors: Gagnon Rose , Perreault Kadija , Guertin Jason R. , Hébert Luc J. , Berthelot Simon 
Published: August 2024

AbstractObjectivesCompare the average cost of an emergency department (ED) visit between three ED care models, namely management by an emergency physician (EP) alone (usual care), management by a primary contact physiotherapist (PT) and an EP (intervention), and management by a PT alone (sensitivity analysis).MethodsCost study (Canadian Public Payer perspective) based on data collected during a pragmatic randomized clinical trial (2018-2019) conducted in an urban Canadian academic ED (CHUL, Quebec City, Canada; n=78, 18-80 years old). Costs incurred for the management of persons presenting to the ED for a minor musculoskeletal disorder (MSKD) were calculated using Time-Driven Activity-Based Costing, in which time invested with a patient determines care costs. The main outcome measure was the average cost of an ED visit. Generalized linear models with Gamma distributions and log links were used to assess whether there were significant differences in average costs between the care models.ResultsMean ED visit cost was $267.08 (2019 $CAD, 95%CI: $212.75, $346.40) for PT and EP management, compared with $245.14 for EP management ($169.46, $336.72), resulting in a non- significant absolute difference of 21.94 CAD/patient ($-87.33, $132.63) between models (p=.60). Sensitivity analyses showed that the average cost of ED management by a PT was $194.38 ($161.50, $234.34), representing a non-significant average saving of 50.76 CAD/patient ($- 156.91, $37.54) compared to EP management.ConclusionThis study is a first step towards a better understanding of the costs incurred by the Canadian Public Payer for the management of persons presenting with MSKDs in the ED. Primary contact physiotherapists have the potential to complement care of MSKD ED patients without increasing healthcare costs.
The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling
Authors: Cornman Andre , West-Roberts Jacob , Camargo Antonio Pedro , Roux Simon , Beracochea Martin , Mirdita Milot , Ovchinnikov Sergey , Hwang Yunha 
Published: August 2024

AbstractBiological language model performance depends heavily on pretraining data quality, diversity, and size. While metagenomic datasets feature enormous biological diversity, their utilization as pretraining data has been limited due to challenges in data accessibility, quality filtering and deduplication. Here, we present the Open MetaGenomic (OMG) corpus, a genomic pretraining dataset totalling 3.1T base pairs and 3.3B protein coding sequences, obtained by combining two largest metagenomic dataset repositories (JGI’s IMG and EMBL’s MGnify). We first document the composition of the dataset and describe the quality filtering steps taken to remove poor quality data. We make the OMG corpus available as a mixed-modality genomic sequence dataset that represents multi-gene encoding genomic sequences with translated amino acids for protein coding sequences, and nucleic acids for intergenic sequences. We train the first mixed-modality genomic language model (gLM2) that leverages genomic context information to learn robust functional representations, as well as coevolutionary signals in protein-protein interfaces and genomic regulatory syntax. Furthermore, we show that deduplication in embedding space can be used to balance the corpus, demonstrating improved performance on downstream tasks. The OMG dataset is publicly hosted on the Hugging Face Hub athttps://huggingface.co/datasets/tattabio/OMGand gLM2 is available athttps://huggingface.co/tattabio/gLM2_650M.
Pressure protein denaturation compared to thermal and chemical unfolding - Analyses with cooperative models
Authors: Seelig Joachim , Seelig Anna 
Published: August 2024

AbstractThe thermodynamics of pressure induced protein unfolding (denaturation) could so far not be directly compared with protein unfolding induced by temperature or chemical agents. Here we provide a new cooperative model for pressure induced protein denaturation, that allows the quantitative comparison of the three denaturing processes based on their free energy, enthalpy, entropy, and cooperativity. As model proteins we use apolipoprotein A-1 and lysozyme. The comparison shows that heat-induced unfolding is the most cooperative process. It is characterized by large positive enthalpies and entropies and (due to enthalpy-entropy compensation) a small negative free energies. Pressure denaturation is less cooperative. The entropies and enthalpies are less positive, and the resulting free energies are more negative. Chemically induced unfolding is least cooperative and shows the most negative free energies, in particular, if guanidinium hydrochloride (exhibiting a high binding affinity to certain proteins) is used as a denaturant. The three unfolding processes not only differ with respect to their cooperativity and the thermodynamic parameters, but also with respect to the volume changes. Whereas thermal and chemical denaturation increase the protein volume, denaturation by pressure reduces the protein volume, suggesting significant structural differences of the denatured proteins. Using cooperative models for protein analyses thus yields significant new insights into the protein unfolding/folding processes.