bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evolution ofSalmonellaChromosomes and Its Influence on Gene Expression and Chromosomal Conformation
Authors: Hu Yueming , Chen Zewei , Sokaribo Akosiererem S. , Zhao Ziyi , Cao Xin , Zhang Junya , Liu Shuhong , Chen Runhong , Deng Yuping , Bao Hongxia , Hui Xinjie , Sun Ming-an , Zhu Guo-Qiang , Liu Shu-Lin , White Aaron P. , Wang Yejun 
Published: December 2024

AbstractSalmonellais one of the most important bacterial pathogens in the world, causing an estimated 120 million infections each year. There is considerable diversity, with ∼2,600 serovars, but it remains unclear how the genomes have evolved as the species and subspecies ofSalmonelladifferentiate. Here, we have reconstructed the ancient orthologous chromosomes of each majorSalmonellalineage and traced their evolutionary process. In total, 911 rearrangement events were identified, with 64% of events occurring in a locus-specific way. Using RNA sequencing and multi-strain association analysis, we demonstrate that genetic rearrangements have a significant effect on gene expression acrossSalmonellalineages. Moreover, we perform chromosome conformation capture (3C) sequencing analysis, which demonstrates large variations for the organization ofterchromosomal interaction domains amongSalmonellalineages. In conclusion, our work delineates the evolutionary trajectory ofSalmonellachromosomes, and demonstrates the influence of rearrangements on gene expression profiles and chromosomal conformation.ImportanceThis study reconstructed the ancient orthologous chromosomes of theSalmonellagenus, species and well-recognized subspecies, by which the trajectory of gene flow caused by genetic rearrangements was delineated chronologically. The rearrangements show apparent ‘hotspot’ distribution property and are enriched with genes important for bacterial fitness. Correlation analysis further disclosed the general influence of the rearrangements on gene expression and the organization and conformation of chromosome interaction domains. The results provide new insights on the evolution ofSalmonellachromosomes, especially the genetic rearrangements and their epigenetic consequences.
Development of aDe NovoProtein Binder that Inhibits the Alpha Kinase eEF2K
Authors: Klupt Kody A. , Belrose Ethan , Jia Zongchao 
Published: December 2024

SUMMARYElongation factor 2 kinase (eEF2K) is calmodulin activated and phosphorylates eEF2, a GTPase, that regulates global translation. When eEF2K phosphorylates eEF2, protein translation is halted. This process may be critical to studying how diseases like cancer dysregulate protein synthesis. eEF2K is an alpha kinase and not targeted by conventional kinase inhibitors. Traditional methods of structure-based drug design are incredibly time consuming and expensive, which may involve screening large libraries of small molecules. We have generatedde novosmall binder proteins (∼10kDa) - using RFDiffusion and ProteinMPNN. One promisingde novobinder protein we produced, ‘CAM1’ binds to a hydrophobic patch on the calmodulin binding domain of eEF2K with nanomolar affinity as determined by isothermal titration calorimetry. This binder,in vitro, significantly reduces eEF2 peptide phosphorylation, comparable to the gold-standard small molecule eEF2K inhibitor, A-484954. The predicted structure of CAM1 is a helical bundle which has been confirmed by circular dichroism spectroscopy. Impressively, CAM1 has a melting temperature >800C, and is produced recombinantly in bacteria, greater than 5 mg / culture liter. We have also determined that CAM1 transfection significantly reduces mammalian HeLa cell proliferation comparable to A-484954 treatment and inhibits the phosphorylation of eEF2. Ourde novobinder, the first to our knowledge to inhibit an alpha kinase, and the first non-competitive eEF2K inhibitor, establishes an alternative method of targeting atypical kinase activity.
Key taxa of the gut microbiome associated with the relationship between environmental sensitivity and inflammation-related biomarkers
Authors: Takasugi Satoshi , Iimura Shuhei , Yasuda Miyabi , Saito Yoshie , Morifuji Masashi 
Published: December 2024

AbstractBackgroundIndividual differences in environmental sensitivity are linked to stress-related psychiatric symptoms. In previous research, we found that high environmental sensitivity can be a risk factor for increased inflammation and gut permeability, particularly when gut microbiome diversity is low. However, the specific gut bacterial taxa involved in this interaction remain unclear. This study aimed to identify the key gut microbiome taxa associated with this relationship.MethodsEnvironmental sensitivity, gut microbiome composition, gut permeability (lipopolysaccharide-binding protein, LBP) and inflammation (C-reactive protein, CRP) biomarkers were evaluated in 88 participants.ResultsThe interaction between environmental sensitivity and the relative abundance of the familyMarinifilaceae(genusButyricimonas) was a predictor of CRP levels. Similarly, the interaction between environmental sensitivity and relative abundance of the familyBarnesiellaceae(genusCoprobacter), the familyAkkermansiace(genusAkkermansia), the genusFamily XIII AD3011 group, the genusGCA-900066225, or the genusRuminiclostridium 1predicted LBP levels. Individuals with high environmental sensitivity exhibited elevated CRP or LBP levels when the relative abundance of these taxa was low. Conversely, highly sensitive individuals had lower CRP or LBP levels when the relative abundance of these taxa was high.ConclusionThis study suggests that specific taxa serve as one of the protective factors against inflammation and gut permeability in individuals with high environmental sensitivity.
PathOmCLIP: Connecting tumor histology with spatial gene expression via locally enhanced contrastive learning of Pathology and Single-cell foundation model
Authors: Lee Yongju , Liu Xinhao , Hao Minsheng , Liu Tianyu , Regev Aviv 
Published: December 2024

AbstractTumor morphological features from histology images are a cornerstone of clinical pathology, diagnostic biomarkers, and basic cancer biology research. Spatial transcriptomics, which provides spatially resolved gene expression profiles overlaid on histology images, offers a unique opportunity to integrate morphological and expression features, thereby deepening our understanding of tumor biology. However, spatial transcriptomics experiments with patient samples in either clinical trials or clinical care are costly and challenging, whereas histology images are generated routinely and available for many legacy prospective cohorts of disease progression and outcomes in well-annotated cohorts. Inferring spatial transcriptomics profiles computationally from these histology images would significantly expand our understanding of tumor biology, but paired data for training multi-modal spatial-histology models remains limited. Here, we tackle this challenge by incorporating performant foundation models pre-trained on massive datasets of pathology images and single-cell RNA-Seq, respectively, which provide useful embeddings to underpin multi-modal models. To this end, we developed PathOmCLIP, a model trained with contrastive loss to create a joint-embedding space between a histopathology foundation model and a single-cell RNA-seq foundation model. We incorporate a set transformer to gather localized neighborhood tumor architecture following contrastive training, which further enhances performance and is necessary to obtain robust results. We validate PathOmCLIP across five tumor types and achieve significant performance improvements in gene expression prediction tasks over other methods. PathOmCLIP can be applied to many archived histology images, unlocking valuable clinical information and facilitating new biomarker discoveries.
The Influence of Rurality on Self-Reported Physical Therapy Utilization Among Patients with Severe Chronic Back Pain in the United States
Authors: McLaughlin Kevin H. 
Published: December 2024

AbstractPurposeTo examine the association of rurality and physical therapy utilization among a nationally representative sample of individuals with severe chronic back pain.MethodsThis study utilized a publicly available dataset from the 2019 National Health Information Survey (Adult Sample). Individuals with severe chronic back pain were identified based on survey items examining respondents’ pain frequency and location. Physical therapy utilization was identified based on survey questions asking about pain management strategies utilized over the previous 3 months. Rurality was classified aslarge central metro, large fringe metro, medium and small metro, andnonmetropolitan/rural, based on county of residence. Regression was used to examine the association between rurality and physical therapy utilization, while controlling for relevant covariates. National estimates were calculated using provided weighting variables.ResultsWe identified 2,925 individuals (weighted = 20,468,134) meeting the criteria for severe chronic back pain. We observed that individuals with severe chronic back pain living in nonmetropolitan/rural areas had 34% lower odds of (weighted OR: 0.66, 95% CI: 0.47, 0.92) utilizing physical therapy compared to individuals living in large central metropolitan areas. We did not observe significant differences in the odds of utilizing physical therapy among individuals living in large fringe metropolitan areas or medium-small metropolitan areas.ConclusionsIndividuals living in rural parts of the US have lower odds of using physical therapy for management of their severe chronic back pain. Additional research is needed to examine the factors that contribute to these differences and improve access to care.
A case-cluster of aseptic meningitis associated with a newly identified recombinant echovirus6/CoxsackievirusB1 enterovirus
Authors: Cherabuddi Kartikeya , Tagliamonte Massimiliano S. , Lednicky John A. , Ostrov David A. , Moquin Tracey L. , Thoomkuntla Vishal Kaushik , Bourgeois Brian , Iovine Nicole M. , Myers Paul D. , Salemi Marco , Morris J. Glenn 
Published: December 2024

ABSTRACTA daycare teacher presented to a local Emergency Department (ED) with complaints of headache, neck stiffness, and fever. Preliminary analysis of cerebral spinal fluid (CSF) raised concerns about meningococcal meningitis and prompted notification of the county health department, which then notified the daycare. Ten children presented to a University referral hospital for evaluation, four of whom were febrile. CSF from the teacher and nasal swabs from the febrile children were all RT-PCR positive for enterovirus. A novel recombinant enterovirus was cultured from the teacher’s CSF and from two of the nasal swabs. The amino-terminal portion of the recombinant virus was derived from an Echovirus E6 with the carboxy-terminal portion originating from a Coxsackievirus B1; recombinant segments were most closely related to similar segments from strains isolated in France. Recombination occurred within the C-2 gene which encodes a multifunctional protein that functions as an RNA-stimulated ATPase associated with virus replication and virion morphogenesis. Structural modeling predicted that the recombinant protein was capable of forming hexameric and heptameric assemblies. Our data highlight the ongoing potential for recombination among enteroviruses groups, leading to modifications within viral proteins which may impact virulence.Brief Article SummaryAfter a daycare teacher was diagnosed with meningitis, ten children were referred by the county health department to a University Hospital for evaluation. Cerebral Spinal Fluid (CSF) from the teacher and nasal swabs from symptomatic children were positive for a novel recombinant enterovirus, with the amino-terminal portion of the virus derived from Echovirus E6 and the carboxy-terminal portion originating from a Coxsackievirus B1.
Machine Learning Analysis of PD-L1 and CD8 Expression Patterns in Penile Squamous Cell Carcinoma: Implications for Immunotherapy
Authors: Canete-Portillo Sofia , Taheri Diana , del Carmen Rodriguez-Peña María , Eich Marie-Lisa , Cocks Margaret , Cubilla Antonio L. , Netto George J. , Chaux Alcides 
Published: December 2024

ABSTRACTIntroductionIn 2023, the US reported an estimated 2,050 new penile squamous cell carcinoma (SCC) cases, with mortality rates rising to 23%. Despite therapeutic advancements, the need to identify molecular and immunotherapeutic targets, especially PD-L1 and CD8, has become increasingly evident as immunotherapy emerges as a promising treatment strategy.MethodsTissue samples from 108 SCC patients were examined using four tissue microarrays (TMA). Alongside the assessment of histologic features and PD-L1 and CD8 expressions, a machine learning model was employed. This model, constructed in Python, leveraged various statistical tests and methodologies to discern the predictive relationships between PD-L1/CD8 expression and pathologic features, with potential implications for immunotherapy selection.ResultsHistologic subtype was predominant in PD-L1 expression in tumor cells, explaining 13.5% variability, whereas combined with host response, it reached 20%. For intratumoral lymphocytes, host response stood out, explaining 11.2% of PD-L1 and 15% of CD8 variability. In peritumoral lymphocytes, host response again dominated, accounting for 21.1% of CD8 variability. These findings align with recent studies showing the importance of immune markers in predicting treatment response and prognosis.ConclusionsThe study highlighted the crucial relationship between penile SCC’s pathologic features and PD-L1/CD8 expression, emphasizing their potential as both prognostic and predictive biomarkers. By integrating traditional histopathology with machine learning, we provide valuable insights for patient stratification and personalized immunotherapeutic strategies in penile SCC.
Depression is Associated with Treatment Response Trajectories in Adults with Prolonged Grief Disorder: A Machine Learning Analysis
Authors: Calderon Adam , Irwin Matthew , Simon Naomi M. , Katherine Shear M. , Mauro Christine , Zisook Sidney , Reynolds Charles F. , Malgaroli Matteo 
Published: December 2024

AbstractAlthough evidence-based treatments for Prolonged Grief Disorder (PGD) exist, pretreatment characteristics associated with differential improvement trajectories have not been identified. To identify clinical factors relevant to optimizing PGD treatment outcomes, we used unsupervised and supervised machine learning to study treatment effects from a double-blinded, placebo-controlled, randomized clinical trial. Participants were randomized into four treatment groups for 20 weeks: citalopram with grief-informed clinical management, citalopram with prolonged grief disorder therapy (PGDT), pill placebo with PGDT, or pill placebo with clinical management. The trial included 333 PGD patients aged 18–95 years (Mage= 53.9;SD± 14.4), predominantly female (77.4%) and white (84.4%). Symptom trajectories were assessed using latent growth mixture modeling based on Inventory for Complicated Grief scores collected at six time points every 4 weeks. The relationship between patient-level characteristics and assigned trajectories was examined using logistic regression with elastic net regularization based on the administration of citalopram, PGDT, and risk factors for developing PGD. Three distinct response trajectories were identified: lesser severity responders (60%, n = 200), greater severity responders (18.02%, n = 60), and non-responders (21.92%, n = 73). Differences between greater severity responders and non-responders emerged as statistically significant by Week 8. The elastic net model demonstrated acceptable discrimination between responders and non-responders (AUC = .702; accuracy = .684). Higher baseline depression severity, grief-related functional impairment, and absence of PGDT were associated with reduced treatment response likelihood. These findings underscore the importance of early identification of clinical factors to optimize individualized PGD treatment strategies.Trial Registration:clinicaltrials.govIdentifier:NCT01179568.
Severe outcomes and length of stay among people with schizophrenia hospitalized for COVID-19: A population-based retrospective cohort study
Authors: Gronsbell Jessica , Wang John , Thurston Hilary , Gao Jianhui , Shi Yaqi , Train Anthony D. , Butt Debra , Gershon Andrea , O’Neill Braden , Tu Karen 
Published: December 2024

AbstractBackground and HypothesisSchizophrenia is associated with substantial physical and psychiatric comorbidities that increase the risk of severe outcomes in COVID-19 infection. However, few studies have examined the differences in care and outcomes among people with schizophrenia throughout the pandemic. We hypothesized that rates of in-hospital mortality, admission to the intensive care unit (ICU), and length of stay differed among people with and without schizophrenia.Study DesignWe conducted a population-based retrospective cohort study using administrative health data from Ontario, Canada that included individuals hospitalized for COVID-19 between February 2020 and October 2023. We compared mortality, ICU admission, and length of stay using regression models adjusted for age, sex, comorbidities, vaccination status, and sociodemographic characteristics.Study ResultsWe evaluated 66,959 hospital admissions, 4.3% (2,884) of which involved people with schizophrenia. People with schizophrenia had a significantly decreased rate of ICU admission (adjusted OR: 0.74, [0.67, 0.82]), a longer length of stay (adjusted RR: 1.25, [1.21, 1.30]), but a similar risk of mortality (adjusted OR: 1.09, [0.98, 1.22]) as people without schizophrenia. Age modified the relationship between schizophrenia and ICU admission. People with schizophrenia aged 60-75 were substantially less likely to be admitted to the ICU relative to those without (18.4% vs. 26.5%, p < .001).ConclusionsOur findings underscore disparities in care among people with and without schizophrenia. These disparities vary by age and suggest that people with schizophrenia may not be receiving the same level of care as people without schizophrenia hospitalized for COVID-19.
Catalytic inhibition of KAT6/KAT7 enhances the efficacy and overcomes primary and acquired resistance to Menin inhibitors in MLL leukaemia
Authors: Gordon Shellaina J. V. , Perner Florian , MacPherson Laura , Wenge Daniela V. , Bourgeois Wallace , Fennell Katie , Klaus Tabea , Petrovic Jelena , Horvath Jakub , Cao Joan , Lapek John , Uryu Sean , White Jeffrey , Lam Enid Y. N. , Mu Xinmeng Jasmine , Chan Yih-Chih , Gillespie Andrea , Blyth Benjamin , Camerino Michelle A. , Bozikis Ylyva E. , Holze Henrietta , Knezevic Kathy , Balic Jesse , Stupple Paul A. , Street Ian P. , Monahan Brendon J. , Sharma Shikhar , Wainwright Elanor N. , Vassiliadis Dane , Paul Thomas A. , Armstrong Scott A. , Dawson Mark A. 
Published: December 2024

ABSTRACTUnderstanding the molecular pathogenesis of MLL fusion oncoprotein (MLL-FP) leukaemia has spawned epigenetic therapies that have improved clinical outcomes in this often-incurable disease. Using genetic and pharmacological approaches, we define the individual and combined contribution of KAT6A, KAT6B and KAT7, in MLL-FP leukaemia. Whilst inhibition of KAT6A/B is efficacious in some pre-clinical models, simultaneous targeting of KAT7, with the novel inhibitor PF-9363, increases the therapeutic efficacy. KAT7 interacts with Menin and the MLL complex and is co-localised at chromatin to co-regulate the MLL-FP transcriptional program. Inhibition of KAT6/KAT7 provides an orthogonal route to targeting Menin to disable the transcriptional activity of MLL-FP. Consequently, combined inhibition rapidly evicts the MLL-FP from chromatin, potently represses oncogenic transcription and overcomes primary resistance to Menin inhibitors. Moreover, PF-9363 or genetic depletion of KAT7 can also overcome acquired genetic/non-genetic resistance to Menin inhibition. These data provide the molecular rationale for rapid clinical translation of combination therapy in MLL-FP leukaemia.
The Swiss Army Knife of Alginate Manipulation – A Gut Bacterium Alginate Lyase with Diverse Catalytic Activities
Authors: Tandrup Tobias , Rivas-Fernández José Pablo , Madsen Mikkel , Rønne Mette E. , Petersen Agnes B. , Klau Leesa J. , Tøndervik Anne , Wilkens Casper , Aachmann Finn L. , Rovira Carme , Svensson Birte 
Published: December 2024

AbstractThe alginate-degrading enzymeBoPL38 of the human gut bacteriumBacteroides ovatusCP926 degrades the three polysaccharide structures found in alginate, a major constituent of brown macroalgae with numerous industrial applications. However, the detailed mechanisms of alginate-degrading enzymes remain unclear. Crystal structures ofBoPL38 complexes with alginate oligosaccharides, now shed light on the enzyme’s catalytic machinery. QM/MM simulations reveal distinct conformational and reaction pathways, highlighting different transition states for mannuronate and guluronate conversion. C5 proton abstraction at subsite +1 by Y298 and H243 facilitatessyn-andanti-β-elimination reactions, respectively. Substrate recognition relies on R292 distorting the sugar at subsite +1 into a preactivated conformation, while stabilizing the active site tunnel through a salt bridge. Furthermore, NMR spectroscopy found thatBoPL38 also catalyze mannuronate to guluronate epimerization in addition to its lyase function, thereby paving the way for future enzymatic alginate modification.
Analysis of natural structures and chemical mapping data reveals local stability compensation in RNA
Authors: Cornwell-Arquitt Robert L. , Nigh Riley , Hathaway Michael T. , Yesselman Joseph D. , Hendrix David A. 
Published: December 2024

AbstractRNA molecules adopt complex structures that perform essential biological functions across all forms of life, making them promising candidates for therapeutic applications. However, our ability to design new RNA structures remains limited by an incomplete understanding of their folding principles. While global metrics such as the minimum free energy are widely used, they are at odds with naturally occurring structures and incompatible with established design rules. Here, we introduce local stability compensation (LSC), a principle that RNA folding is governed by the local balance between destabilizing loops and their stabilizing adjacent stems, challenging the focus on global energetic optimization. Analysis of over 100, 000 RNA structures revealed that LSC signatures are particularly pronounced in bulges and their adjacent stems, with distinct patterns across different RNA families that align with their biological functions. To validate LSC experimentally, we systematically analyzed thousands of RNA variants using DMS chemical mapping. Our results demonstrate that stem reactivity correlates strongly with LSC (R² = 0.458 for hairpin loops) and that structural perturbations affect folding primarily within ∼6 nucleotides from the loop. These findings establish LSC as a fundamental principle that could enhance the rational design of functional RNAs.Graphical Abstract