bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing the performance and suitability of wastewater based-surveillance for SARS-CoV-2 RNA in public schools
Authors: Acosta Nicole , Beaudet Alex Buchner , Westlund Paul , Hu Jia , Sedaghat Navid , Pradhan Puja , Man Lawrence , Hollman Jordan , Bautista María A. , Waddell Barbara J. , McCalder Janine , Penney Matthew , Chen Jianwei , Meddings Jon , Achari Gopal , Ryan M. Cathryn , Breton Dany , Wood Elizabeth A. , Cabaj Jason L. , Clark Rhonda C. , Frankowski Kevin , Hubert Casey R.J. , Parkins Michael D. 
Published: January 2025

AbstractMunicipal wastewater-based surveillance (WBS) programs for SARS-CoV-2 were valuable tools for epidemiological modelling and informing COVID-19 health policy during the pandemic. We conducted a “near to source” study to assess the capacity and performance of SARS-CoV-2 WBS programs in schools relative to municipal wastewater treatment plants (WWTP). Only 4/17 schools screened had plumbing systems that were amenable to WBS. From December 2020 - March 2021 composite wastewater collected 2X/week from four schools and three municipal WWTP were assessed for SARS-CoV-2 and fecal biomarkers. Schools had lower rates of successful sample collection relative to WWTP (44.7% vs 100%, p<0.001). In a time of low COVID-19 activity, 13/64 of school samples were positive of SARS-CoV-2-N1 vs 100% of WWTP. SARS-CoV-2-N1 detected in school wastewater associated with and preceded clinically identified infections, but did not correlate with rates of overall absenteeism. Notably levels of SARS-CoV-2-N1 and fecal biomarkers were markedly lower in wastewater from schools relative to WWTP. While our SARS-CoV-2 WBS program in schools did generate a leading signal relative to clinical disease, the significantly lower levels of SARS-CoV-2 and fecal biomarkers suggests that toileting habits of children who may avoid defecation at school adversely impact school-based WBS of targets shed in feces.
Multimodal Deep Learning Model to Estimate CT-based Body Composition Measures Using Chest radiographs and Clinical Data
Authors: Alipour Ehsan , Gratzl Samuel , Algohary Ahmad , Lin Hao , Bapat Manoj , Do Duy , Baker Charlotte , Rodriguez Tricia , Cartwright Brianna , Hadlock Jennifer , Tarczy-Hornoch Peter , Oka Anand , Stucky Nicholas 
Published: January 2025

AbstractBody composition metrics such as visceral fat volume, subcutaneous fat volume and skeletal muscle volume, are important predictors for cardiovascular disease, diabetes, and cancer prognosis. Recent advances in artificial intelligence have enabled automatic calculation of body composition metrics from CT scans and MRIs.In this study, we explore using deep learning to estimate body composition metrics from chest radiographs and a small set of variables that are easy to obtain in the clinical environment.A retrospective cohort of patients with concurrent non-contrast abdominal CT scan and chest radiograph was selected using the Truveta dataset. TotalSegmentator was used to delineate various tissue components in the CT scan. Volumetric and mid-l3 level body composition measures including subcutaneous and visceral fat volume, skeletal muscle and bone related indices, and aortic calcification scores were calculated. A multitask, multimodal deep learning model using chest radiographs and select clinical variables was trained to estimate the ground truth body composition metrics. Three data fusion strategies were compared in this process: early, intermediate, and late.Our final cohort consisted of 1,118 patients. Mean age of imaging was 67 years old, mean height was 1.67 meters and mean weight was 78 kgs. The late fusion multimodal model outperformed both unimodal clinical-only and imaging-only models, in addition to the early and intermediate fusion models. It achieved a Pearson correlation of 0.85 in prediction of subcutaneous fat volume and 0.76 and 0.72 in estimating visceral fat volume and vertebral bone volume in the hold-out test set.While previous studies have used artificial intelligence to automate calculation body composition metrics in CT scans and MRIs, we introduce a novel strategy that utilizes simpler imaging modalities. Our models can be used in future studies to calculate body composition metrics for larger cohorts of patients using only a chest radiograph and readily available clinical variables.
Scaling data analyses in cellular cryoET using comprehensive segmentation
Authors: Last Mart G. F. , Voortman Lenard M. , Sharp Thomas H. 
Published: January 2025

AbstractAutomation and improved hardware have greatly accelerated the rate of data generation in cryoET. As the field moves towardsquantitative cryoET, the scale of the resulting datasets presents a significant challenge for analysis and interpretation. To explore ways of handling datasets comprising thousands of tomograms, we investigated a comprehensive segmentation strategy – assigning an ontology-based identity to every voxel in a dataset – that is based on the sequential application of multiple convolutional neural networks. Using an openly available dataset of over 1800Chlamydomonas reinhardtiitomograms as a test case, we demonstrate the segmentation of 25 different subcellular features across the full dataset, while requiring only a few seconds of processing time per tomogram. We show how the approach enables the representation of large datasets as searchable databases and propose the usage of ontology-based segmentations for improving two common processing tasks in cryoET. First, we explorecontext-aware particle pickingas a method to retain biological context when selecting particles for subtomogram averaging and other downstream analyses. Secondly, we demonstratearea-selective template matching, where we use segmentation-based masks to avoid redundant computations in template matching and enable >500-fold faster processing in specific cases. To illustrate the utility of the approach, all segmentation results have also been made available online viacryopom.streamlit.app.
Novel Deep Learning Framework for Simultaneous Assessment of Left Ventricular Mass and Longitudinal Strain: Clinical Feasibility and Validation in Patients with Hypertrophic Cardiomyopathy
Authors: Park Jiesuck , Yoon Yeonyee E. , Jang Yeonggul , Jung Taekgeun , Hong Youngtaek , Lee Seung-Ah , Choi Hong-Mi , Hwang In-Chang , Chun Eun Ju , Cho Goo-Yeong , Chang Hyuk-Jae 
Published: January 2025

ABSTRACTAimsThis study aims to present the Segmentation-based Myocardial Advanced Refinement Tracking (SMART) technique, a novel artificial intelligence (AI)-based approach for transthoracic echocardiography (TTE) that incorporates motion tracking and left ventricular (LV) myocardial segmentation throughout the cardiac cycle. The study evaluates its feasibility and accuracy in assessing LV mass (LVM) and global longitudinal strain (LVGLS) in hypertrophic cardiomyopathy (HCM) patients.Methods and resultsThe study included 111 HCM patients (median age: 58 years, 69% male) who underwent TTE and cardiac magnetic resonance imaging (CMR). SMART-derived LVGLS (LVGLSSMART) showed strong correlation with conventional manual LVGLS measurements (LVGLSTTE-EchoPAC; Pearson’s correlation coefficient [PCC] 0.851; mean difference 0 [-2–0]). When compared to CMR as the reference standard for LVM measurement (LVMCMR), conventional dimension-based TTE calculations (LVMTTE-DB) overestimated LVM compared to CMR (PCC 0.652; mean difference: 106 [90–123]), while LVMSMARTdemonstrated excellent agreement with CMR (PCC 0.843; mean difference: 1 [-11–13]). For predicting extensive LGE (≥15% of LVM), LVGLSSMARTand LVMSMARTexhibited comparable predictive performance (AUC: 0.72 and 0.66, respectively) to conventional LVGLS and CMR. Patients identified as high-risk for extensive LGE by LVGLSSMART(≤11%) and LVMSMART(≥166g) had significantly higher rates of adverse outcomes, including heart failure hospitalization, new-onset atrial fibrillation, and defibrillator implantation.ConclusionThe SMART technique provides a comparable evaluation of LVGLS and a more accurate assessment of LVM compared to conventional TTE, with additional predictive value for myocardial fibrosis and adverse outcomes, supporting its utility in HCM management.
Novel Risk Factors for Predicting Immune Effector Cell-Associated Neurotoxicity Syndrome
Authors: Friedman Alec R. , Tozlu Ceren , Gordillo Christian A. , Chan Hei Ton , Reshef Ran , Wesley Sarah Flanagan 
Published: January 2025

AbstractICANS is a common form of neurological immunotoxicity from CAR T-cell therapy (CAR-T). While high tumor burden, product type and cell dose are established risk factors, there are many unknowns. Our objective was to characterize novel neurological and non-neurological risk factors for the development of ICANS in subjects who received CAR-T. We retrospectively identified 93 subjects (60% men, mean age 60) who had undergone CD19 or BCMA-targeting CAR-T for hematological malignancy from 2018 to 2023 at a large academic hospital. Incidence of ICANS was 31.2%, high-grade in 9.7%. A low baseline MOCA score (p=0.008) was associated with ICANS when controlled for baseline ferritin, KPS, and age; loss of points on specific cognitive sub-scores was also significant, with poor attention testing of particular concern. Presence of preexisting cerebrovascular disease, active autoimmune disease, and neurological tumor involvement were not associated with increased risk. ICANS was also associated with older age (p=0.024), elevated baseline ferritin (p=0.006), low KPS (p=0.004), and preceding or concurrent CRS of any grade (<0.001). Increasing ferritin between baseline and Day 5+ (p=0.002) was associated with development of high-grade ICANS, along with prior tocilizumab exposure (p=0.015). Subjects who developed any grade of ICANS had higher 90-day mortality than those who did not (p<0.001). Identification of these additional baseline risk factors for ICANS will help identify high-risk patients ahead of treatment and allow for improved preventative planning and early identification of ICANS.Key PointsLow baseline MOCA score is an independent risk factor for ICANS. Impaired baseline attention testing is of particular concern.Baseline cerebrovascular disease, neurological exam focality, and active autoimmune disease are not associated with ICANS.
Associations between epilepsy-related polygenic risk and brain morphology in childhood
Authors: Ngo Alexander , Liu Lang , Larivière Sara , Kebets Valeria , Fett Serena , Weber Clara F. , Royer Jessica , Yu Eric , Rodríguez-Cruces Raúl , Zhang Zhiqiang , Rong Ooi Leon Qi , Yeo B. T. Thomas , Frauscher Birgit , Paquola Casey , Caligiuri Maria Eugenia , Gambardella Antonio , Concha Luis , Keller Simon S. , Cendes Fernando , Yasuda Clarissa L. , Bonilha Leonardo , Gleichgerrcht Ezequiel , Focke Niels K. , Kotikalapudi Raviteja , O’Brien Terence J. , Sinclair Benjamin , Vivash Lucy , Desmond Patricia M. , Lui Elaine , Vaudano Anna Elisabetta , Meletti Stefano , Kälviäinen Reetta , Soltanian-Zadeh Hamid , Winston Gavin P. , Tiwari Vijay K. , Kreilkamp Barbara A. K. , Lenge Matteo , Guerrini Renzo , Hamandi Khalid , Rüber Theodor , Bauer Tobias , Devinsky Orrin , Striano Pasquale , Kaestner Erik , Hatton Sean N. , Caciagli Lorenzo , Kirschner Matthias , Duncan John S. , Thompson Paul M. ,   ENIGMA Consortium Epilepsy Working Group, McDonald Carrie R. , Sisodiya Sanjay M. , Bernasconi Neda , Bernasconi Andrea , Gan-Or Ziv , Bernhardt Boris C. 
Published: January 2025

AbstractTemporal lobe epilepsy with hippocampal sclerosis (TLE-HS) is associated with a complex genetic architecture, but the translation from genetic risk factors to brain vulnerability remains unclear. Here, we examined associations between epilepsy-related polygenic risk scores for HS (PRS-HS) and brain structure in a large sample of neurotypical children, and correlated these signatures with case-control findings in in multicentric cohorts of patients with TLE-HS. Imaging-genetic analyses revealed PRS-related cortical thinning in temporo-parietal and fronto-central regions, strongly anchored to distinct functional and structural network epicentres. Compared to disease-related effects derived from epilepsy case-control cohorts, structural correlates of PRS-HS mirrored atrophy and epicentre patterns in patients with TLE-HS. By identifying a potential pathway between genetic vulnerability and disease mechanisms, our findings provide new insights into the genetic underpinnings of structural alterations in TLE-HS and highlight potential imaging-genetic biomarkers for early risk stratification and personalized interventions.
Maternal motivation overcomes innate fear via prefrontal switching dynamics
Authors: Xie Yunyao , Li Yijia , Du Xinke , Huang Longwen 
Published: January 2025

AbstractParental care is altruistic. In natural environments, parents are often faced with challenging environmental conditions, such as severe weather, complex terrain and predatory threats, and therefore need to overcome the fear of adverse conditions to protect and raise the offspring. Although a few studies have reported risk-taking maternal behaviors1–3, it is unknown how maternal motivation and environmental threats are represented and integrated in neural circuits to resolve the conflict and dynamically drive behaviors. Here we report a novel risk-taking maternal behavior paradigm in a semi-naturalistic context, in which a female mouse has to overcome fear and jump off an elevated platform to retrieve pups outside a nest on the ground. We show that while fear of heights reduces the motivation to jump, the presence of pups dramatically facilitates overcoming such fear. A medial prefrontal-periaqueductal gray (mPFC-PAG) pathway is specifically required for the effect of pups on overcoming fear of height, and this circuit integrates conflicting cues about pup and height and encodes motivation to drive risk-taking jumping behaviors. In contrast to cued, fast and predictable reaction timing in typical structured tasks4,5, behaviors in our paradigm are highly spontaneous, characterized by stochastic transitions between low-motivation and high-motivation states. Our data reveal that such spontaneity is shaped by the switching ramping dynamics of neural activity in the motivation-encoding dimension, rather than continuous ramping dynamics. Pup and height cues modulate the switching ramping dynamics to influence, but not immediately evoke behaviors. Together, we propose that the prefrontal-brainstem pathway plays vital roles in encoding altruistic motivation to overcome innate fear, and the switching ramping dynamics might represent a general mechanism that gives rise to spontaneous behaviors in naturalistic and conflicting conditions.
Gonococcal aggregation causes upregulation of genes involved in antibiotic tolerance
Authors: Kraus-Römer Sebastian , Wielert Isabelle , Rathmann Isabel , Volkmann Thorsten E. , Higgins Paul G. , Maier Berenike 
Published: January 2025

AbstractAggregation and biofilm formation can increase the tolerance of bacteria to external stressors, including antibiotic treatment. While resistant bacteria grow at an elevated drug dose, tolerant bacteria survive longer-term treatment. The mechanisms by which aggregation confers tolerance are insufficiently characterized for most organisms, including the human pathogenNeisseria gonorrhoeae. We hypothesize that bacterial aggregation causes upregulation of genes involved in tolerance and that deletion of these genes increases killing rates during antibiotic treatment. To test this hypothesis and identify genes involved in gonococcal tolerance, we compared the transcriptome of aggregating and planktonicN. gonorrhoeaestrains. In general, the transcriptome analysis shows that aggregation causes a strong upregulation of prophage-related genes and a shift towards anaerobic respiration. We generated deletion strains for the twenty most upregulated genes and measured their killing kinetics during treatment with the clinically relevant antibiotics ceftriaxone or ciprofloxacin. We identified five genes and one multigene segment that are involved in gonococcal antibiotic tolerance. These include prophage genes whose deletion affects tolerance differently in aggregating and planktonic strains. Furthermore, deletion of genes encoding a putative multi-drug efflux pump, an alcohol dehydrogenase, and a DNA repair protein reduces tolerance. In summary, we have identified multiple genes that affect antibiotic tolerance and are upregulated in response to aggregation.Author summaryOften bacterial infections recur after antibiotic treatment because not all of the bacteria were killed. The ability to survive treatment by bactericidal drugs is termed tolerance. It is well established that aggregation can increase tolerance by reducing growth and metabolism. However, the genes involved in tolerance are not well characterized, especially in the human pathogenNeisseria gonorrhoeae. Here, we aim to identify such genes by following the hypothesis that aggregation upregulates genes that cross-protectN. gonorrhoeaefrom antibiotic treatment. We show that prophage-associated genes are strongly upregulated in aggregates and that deletion of various phage genes affects tolerance to the currently administered drug, ceftriaxone. We identify three additional genes belonging to different functional classes whose deletion reduces tolerance to ciprofloxacin. Our study is an important step towards understanding the molecular mechanisms of gonococcal antibiotic tolerance. In particular, we propose that prophages could serve as a target for the treatment of tolerant gonococcal infections.
The C terminus of infectious bursal disease virus (IBDV) VP3 encodes a predicted intrinsically disordered region (IDR), which promotes the formation of cytoplasmic puncta and modulates their physical properties
Authors: Brodrick A.J. , Broadbent A. J. 
Published: January 2025

AbstractThe virus factories (VFs) of infectious bursal disease virus (IBDV) form through liquid-liquid phase separation (LLPS). A major component of the IBDV VF is the nonstructural protein VP3. Here, we predicted the full-length structure of the VP3 monomer and homodimer and employed molecular dynamics simulations to characterize their behavior. We identified the 36 amino acid carboxy(C)-terminus as a highly dynamic intrinsically disordered region (IDR). We then compared the cytoplasmic puncta that were made in the presence of the wild type (wt) VP3 with those made with a VP3 that lacked the C-terminus (VP3ΔC). Using live-cell imaging with fluorescent reporter tagged proteins, we found that VP3ΔC puncta were significantly less numerous (p<0.0001), smaller (p<0.0001), and more irregular in shape than puncta formed in the presence of wt VP3, demonstrating that the VP3 C terminal IDR promoted their formation. Moreover, by fluorescence recovery after photobleaching (FRAP), the VP3ΔC puncta had a significantly reduced mobile fraction (0.29) as compared to full-length VP3 puncta (0.70) (p<0.001), demonstrating that the VP3 C terminal IDR modulated their physical properties. However, the VP3ΔC puncta still exhibited liquid-like fusion events in the cytoplasm and were sensitive to treatment with aliphatic diols. Moreover, VP3 did not form puncta when expressed alone, and the removal of the C terminus did not abolish puncta formation completely. We propose that VP3 forms part of a higher order complex with other biomolecules to drive LLPS, and that the VP3 C terminal IDR modulates the physical properties of the resultant LLPS structures.ImportanceLLPS is a phenomenon of growing interest in cell biology. It is a part of the replication cycles of diverse viruses, but our understanding of the molecular basis that underpins the mechanism of phase separation is incomplete. We previously demonstrated that the birnavirus IBDV, a major agricultural pathogen, exploits LLPS in the formation of its VFs. Here, we have characterized the C-terminal 36 amino acid region of IBDV VP3 bioinformatically and by molecular dynamics simulations and found that it encodes a highly dynamic intrinsically disordered region (IDR). Furthermore, we found this region to promote the formation of cytoplasmic puncta and modulate their physical properties. This work contributes to a more detailed understanding of birnavirus replication at the molecular level, and to the study of LLPS as a phenomenon.
Sialic acid-containing glycolipids extend the receptor repertoire of Enterovirus-D68
Authors: Pereirinha da Silva Ashley K. , van Trijp Jacobus P. , Montenarie Anouk , Fok Jelle , Sooksawasdi Na Ayudhya Syriam , Pieters Roland J. , Boons Geert-Jan , van Riel Debby , de Vries Robert P. , Bauer Lisa 
Published: January 2025

AbstractEnterovirus D68 (EV-D68) emerged as a pathogen of increasing health concern globally, particularly due to its association with outbreaks of severe respiratory diseases and acute flaccid myelitis (AFM) in children. Knowledge regarding the tissue tropism and pathogenesis of EV-D68 within the respiratory tract and central nervous system remains limited, primarily due to an incomplete understanding of the host factors that facilitate EV-D68 entry into host cells. Several cellular receptors involved in EV-D68 infections have been identified, including ICAM-5, sialylated glycoproteins, and heparan sulfate (HS). Here, we investigate the receptor requirement of a panel of EV-D68 strains covering all clades focusing on HS and sialosides utilizing glycan arrays. We found that all EV-D68 strains binding to HS harbour a cell culture adaptative substitution in the structural protein VP1 at position 271 which changes the amino acid into a positive charged one. Glycan array analyses revealed that EV-D68 strains either prefer α2,6-linked sialic acids presented on N-glycans, α2,8 linked sialic acids on gangliosides, or both. Inhibition of glycolipid biosynthesis or multivalent glycolipid mimics confirmed that ganglioside structures serve as entry receptors for certain EV-D68 strains. Lastly, we examined whether EV-D68 strains that bind to HS or glycolipids require different uncoating mechanisms. Bafilomycin A1 minimally affected cell entry of HS-binding EV-D68 strains B2/039 and B2/947 and the ganglioside preferring B1/2013 other viruses were strongly inhibited. Together, we identified that EV-D68 strains can use disialoglycolipids as novel receptors and that different EV-D68 strains show a promiscuous sialic acid binding repertoire.