bluuebunny/crossref_metadata_2025_split huggingface dataset:
Toxin-mediated depletion of nicotinamide dinucleotides drives persister formation in a human pathogen
Authors: Santi Isabella , Dias Teixeira Raphael , Manfredi Pablo , Spiess Daniel , Mas Guillaume , Klotz Alexander , Zamboni Nicola , Hiller Sebastian , Jenal Urs 
Published: September 2023

AbstractToxin-antitoxin (TA) systems are widespread in bacteria and are implicated in genome stability, virulence, phage defense and persistence. Although TA systems encompass a large variety of molecular activities and cellular targets, their physiological role and regulatory mechanisms are often unclear1,2. Here, we show that a RES domain TA system increases the survival of the human pathogenP. aeruginosaduring antibiotic treatment by generating a subpopulation of highly drug-tolerant persisters. The NatT toxin is an NAD phosphorylase, which leads to strong depletion of NAD and NADP in a subpopulation of cells. Actively growingP. aeruginosacells effectively compensate for toxin-mediated NAD deficiency by inducing the NAD salvage path-way. In contrast, under nutrient-limited conditions, NatT generates NAD-depleted cells that give rise to drug tolerant persisters during outgrowth. Structural and biochemical analyses of active and inactive NatR-NatT complexes reveal how changes in NatR-NatT interaction controls toxin activity and autoregulation. Finally, we show that the NAD precursor nicotinamide blocks NatT activity and eliminates persister formation, exposing powerful metabolic feedback control of toxin activity. The findings that patient isolates containnatTgain-of-function alleles and that NatT increasesP. aeruginosavirulence, argue that NatT contributes toP. aeruginosafitness during infections. These studies provide mechanistic insight into how a TA system promotes pathogen persistence by disrupting essential metabolic pathways during nutrient stress.
The neurovascular coupling in the attention during visual working memory
Authors: Zhang Hao , Hu Yiqing , Li Yang , Li Dongwei , Liu Hanli , Li Xiaoli , Song Yan , Zhao Chenguang 
Published: September 2023

AbstractHow to focus attention during visual working memory (vWM) depends on one’s ability to filter out distractors and expand the scope of targets. Although the spatiotemporal properties of attention processes in WM are well documented, it is still unclear how the mechanisms of neurovascular coupling (NVC) between electroencephalographic (EEG) signals and hemodynamic activity of attention during vWM. To investigate the NVC mechanism underlying attention during vWM, we recorded simultaneous functional near-infrared spectroscopy (fNIRS) and EEG data when humans were performing cued change-detection tasks. The multimodal data showed that the control and scope processes during vWM were involved in similar temporal profiles of frontal theta event-related synchronization (ERS) and posterior contralateral delay activities (CDA), and revealed similar distributions of hemodynamic activation within the frontal eye fields (FEF) and superior parietal lobule (SPL). These task-related features have a common NVC outcome across individuals: the higher EEG features (theta ERS or CDA amplitude), the greater the increment of local oxygenated hemoglobin (HbO) signals within the FEF and SPL. Moreover, when distractors should be filtered out, EEG-informed NVC is involved in a broader range of brain regions in the frontoparietal network (FPN). These results provided unique neurovascular evidence for the mechanisms of attention scope and control in vWM. Interestingly, there might be a negative relationship between behavioral metrics and theta-informed NVC strengths within the FEF for attention control. On a dynamic basis, the NVC features had higher discriminatory power for predicting behavior than EEG features and fNIRS features alone. Together, these results highlight what multimodal approaches can advance our understanding of the role of attention in vWM and how the fluctuations of NVC are associated with actual behavior.
Impossible ecologies: Interaction networks and stability of coexistence in ecological communities
Authors: Meng Yu , Horvát Szabolcs , Modes Carl D. , Haas Pierre A. 
Published: September 2023

AbstractDoes an ecological community allow stable coexistence? Identifying the general principles that determine the answer to this question is a central problem of theoretical ecology. Random matrix theory approaches have uncovered the general trends of the effect of competitive, mutualistic, and predator-prey interactions between species on stability of coexistence. However, an ecological community is determined not only by the counts of these different interaction types, but also by their network arrangement. This cannot be accounted for in a direct statistical description that would enable random matrix theory approaches. Here, we therefore develop a different approach, of exhaustive analysis of small ecological communities, to show that this arrangement of interactions can influence stability of coexistence more than these general trends. We analyse all interaction networks ofN⩽ 5 species with Lotka–Volterra dynamics by combining exact results forN⩽ 3 species and numerical exploration. Surprisingly, we find that a very small subset of these networks are “impossible ecologies”, in which stable coexistence is non-trivially impossible. We prove that the possibility of stable coexistence in general ecologies is determined by similarly rare “irreducible ecologies”. By random sampling of interaction strengths, we then show that the probability of stable coexistence varies over many orders of magnitude even in ecologies that differ only in the network arrangement of identical ecological interactions. Finally, we demonstrate that our approach can reveal the effect of evolutionary or environmental perturbations of the interaction network. Overall, this work reveals the importance of the full structure of the network of interactions for stability of coexistence in ecological communities.
Personalised Regional Modelling Predicts Tau Progression in the Human Brain
Authors: Chaggar Pavanjit , Vogel Jacob , Pichet Binette Alexa , Thompson Travis B. , Strandberg Olof , Mattsson-Carlgren Niklas , Karlsson Linda , Stomrud Erik , Jbabdi Saad , Magon Stefano , Klein Gregory ,   the Alzheimer’s Disease Neuroimaging Initiative, Hansson Oskar , Goriely Alain 
Published: September 2023

AbstractAggregation of the hyperphosphorylated tau protein is a central driver of Alzheimer’s disease, and its accumulation exhibits a rich spatio-temporal pattern that unfolds during the course of the disease, sequentially progressing through the brain across axonal connections. It is unclear how this spatio-temporal process is orchestrated – namely, to what extent the spread of pathologic tau is governed by transport between brain regions, local production or both. To address this, we develop a mechanistic model from tau PET data to describe tau dynamics along the Alzheimer’s disease timeline. Our analysis reveals longitudinal changes in production and transport dynamics on two independent cohorts, with subjects in early stage of the disease exhibiting transport-dominated spread, consistent with an initial spread of pathologic tau seeds, and subjects in late stage disease (Braak stage 3/4 onwards) characterised primarily by local production of tau. Furthermore, we demonstrate that the model can accurately predict subject-specific longitudinal tau accumulation at a regional level, potentially providing a new clinical tool to monitor and classify patient disease progression.TeaserA mechanistic model reveals tau protein dynamics in Alzheimer’s, showing stage-specific shifts in transport and local production.
An antimicrobial drug recommender system using MALDI-TOF MS and dual-branch neural networks
Authors: De Waele Gaetan , Menschaert Gerben , Waegeman Willem 
Published: September 2023

AbstractTimely and effective use of antimicrobial drugs can improve patient outcomes, as well as help safeguard against resistance development. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is currently routinely used in clinical diagnostics for rapid species identification. Mining additional data from said spectra in the form of antimicrobial resistance (AMR) profiles is, therefore, highly promising. Such AMR profiles could serve as a drop-in solution for drastically improving treatment efficiency, effectiveness, and costs.This study endeavours to develop the first machine learning models capable of predicting AMR profiles for the whole repertoire of species and drugs encountered in clinical microbiology. The resulting models can be interpreted as drug recommender systems for infectious diseases. We find that our dual-branch method delivers considerably higher performance compared to previous approaches. In addition, experiments show that the models can be efficiently fine-tuned to data from other clinical laboratories. MALDI-TOF-based AMR recommender systems can, hence, greatly extend the value of MALDI-TOF MS for clinical diagnostics.All code supporting this study is distributed on PyPI and is packaged under:https://github.com/gdewael/maldi-nn
B cell directed CAR-T cell therapy results in activation of CD8+ cytotoxic CAR-negative bystander T cells in both non-human primates and patients
Authors: Kaminski James , Fleming Ryan A. , Alvarez-Calderon Francesca , McGuckin Connor , Ho Emily E. , Eng Fay , Rui Xianliang , Keskula Paula , Cagnin Lorenzo , Charles Joanne , Zavistaski Jillian , Margossian Steven P. , Kapadia Malika A. , Rottman James B. , Lane Jennifer , Baumeister Susanne H.C. , Tkachev Victor , Shalek Alex K. , Kean Leslie S. , Gerdemann Ulrike 
Published: September 2023

AbstractThere is growing appreciation for the emergence of CARnegbystander T cells after CAR-T cell infusion. However, their phenotypic and transcriptomic hallmarks and mechanisms of activation remain uncertain. We performed single-cell RNA-Seq (scRNA-Seq) on non-human primate (NHP) and patient-derived T cells to interrogate CARnegT cells following B cell targeted CAR-T cell therapy. In a NHP model, we observed a distinct population of activated CD8+ CARnegT cells emerging during CAR-T cell expansion. These bystander CD8+ CARnegT cells exhibited a unique transcriptional signature with upregulation of NK-cell markers (KIR3DL2, CD160, KLRD1), chemokines and chemokine receptors (CCL5, XCL1, CCR9), and downregulation of naive T cell-associated genes (SELL, CD28). A transcriptionally similar population was identified in patients following Tisangelecleucel infusion. Mechanistic studies revealed that IL-2 and IL-15 exposure induced bystander-like CD8+ T cells. These T cells efficiently killed leukemic cells through a TCR-independent mechanism. Together, these data identify bystander CD8+ T cells as a novel mechanism by which CAR-T cell infusion can induce further anti-leukemic activity, measurable in both NHP and in patients.Statement of SignificanceWe have deeply interrogated CARnegbystander CD8+ T cells during CAR-T cell expansion in non­human primates and patients receiving Tisangelecleucel to identify the unique transcriptomic signature defining these cells, and to determine that IL-2-and IL-15-induced cytotoxic bystander T cells are capable of killing in a TCR-independent manner. These data highlight the potential of bystander T cells for leukemia control and provide a critical foundation for their future analysis.
Phage-bacteria dynamics during the first years of life revealed by trans-kingdom marker gene analysis
Authors: Tisza Michael , Lloyd Richard , Hoffman Kristi , Smith Daniel , Rewers Marian , Cregeen Sara Javornik , Petrosino Joseph F. 
Published: September 2023

AbstractHumans are colonized with commensal bacteria soon after birth, and, while this colonization is affected by lifestyle and other factors, bacterial colonization proceeds through well-studied phases. However, less is known about phage communities in early human development due to small study sizes, inability to leverage large databases, and lack of appropriate bioinformatics tools. In this study, whole genome shotgun sequencing data from the TEDDY study, composed of 12,262 longitudinal samples from 887 children in 4 countries, is reanalyzed to assess phage and bacterial dynamics simultaneously. Reads from these samples were mapped to marker genes from both bacteria and a new database of tens of thousands of phage taxa from human microbiomes. We uncover that each child is colonized by hundreds of different phages during the early years, and phages are more transitory than bacteria. Participants’ samples continually harbor new phage species over time whereas the diversification of bacterial species begins to saturate. Phage data improves the ability for machine learning models to discriminate samples by country. Finally, while phage populations were individual-specific, striking patterns arose from the larger dataset, showing clear trends of ecological succession amongst phages, which correlated well with putative host bacteria. Improved understanding of phage-bacterial relationships may reveal new means by which to shape and modulate the microbiome and its constituents to improve health and reduce disease, particularly in vulnerable populations where antibiotic use and/or other more drastic measures may not be advised.
Do Fossorial Water Voles have a Functional Vomeronasal Organ? A Histological and Immunohistochemical Study
Authors: Ruiz-Rubio Sara , Ortiz-Leal Irene , Torres Mateo V. , Somoano Aitor , Sanchez-Quinteiro Pablo 
Published: September 2023

ABSTRACTThe fossorial water vole,Arvicola scherman, is a herbivorous rodent that cause significant agricultural damages. The application of cairomones and alarm pheromones emerges as a promising sustainable method to improve its integrated management. These chemical signals would induce stress responses that could interfere with the species regular reproductive cycles and induce aversive reactions, steering them away from farmlands and meadows. However, there is a paucity of information regarding the water vole vomeronasal system, both in its morphological foundations and its functionality, making it imperative to understand the same for the application of chemical communication in pest control.This study fills the existing gaps in knowledge through a morphological and immunohistochemical analysis of the fossorial water vole vomeronasal organ. The study is primarily microscopic, employing two approaches: histological, using serial sections stained with various dyes (Hematoxylin-Eosin, PAS, Alcian Blue, Nissl), and immunohistochemical, applying various markers that provide morphofunctional and structural information. These procedures have confirmed the presence of a functional vomeronasal system in fossorial water voles, characterized by a high degree of differentiation and a significant expression of cellular markers indicative of active chemical communication in this species.
The Role of ATP Hydrolysis and Product Release in the Translocation Mechanism of SARS-CoV-2 NSP13
Authors: Lawal Monsurat M. , Roy Priti , McCullagh Martin 
Published: September 2023

AbstractIn response to the emergence of COVID-19, caused by SARS-CoV-2, there has been a growing interest in understanding the functional mechanisms of the viral proteins to aid in the development of new therapeutics. Non-structural protein 13 (Nsp13) helicase is an attractive target for antivirals because it is essential for viral replication and has a low mutation rate; yet, the structural mechanisms by which this enzyme binds and hydrolyzes ATP to cause unidirectional RNA translocation remain elusive. Using Gaussian accelerated molecular dynamics (GaMD), we generated a comprehensive conformational ensemble of all substrate states along the ATP-dependent cycle. ShapeGMM clustering of the protein yields four protein conformations that describe an opening and closing of both the ATP pocket and RNA cleft. This opening and closing is achieved through a combination of conformational selection and induction along the ATP cycle. Furthermore, three protein-RNA conformations are observed that implicate motifs Ia, IV, and V as playing a pivotal role in an ATP-dependent inchworm translocation mechanism. Finally, based on a linear discriminant analysis of protein conformations, we identify L405 as a pivotal residue for the opening and closing mechanism and propose a L405D mutation as a way of testing our proposed mechanism. This research enhances our understanding of nsp13’s role in viral replication and could contribute to the development of antiviral strategies.TOC Graphic
POP-UP TCR: Prediction of Previously Unseen Paired TCR-pMHC
Authors: Tickotsky Nili 
Published: September 2023

AbstractMotivationT lymphocytes (T-cells) major role in adaptive immunity drives efforts to elucidate the mechanisms behind T-cell epitope recognition.ResultsWe analyzed solved structures of T-cell receptors (TCRs) and their cognate epitopes and used the data to train a set of machine learning models, POP-UP TCR, that predict the binding of any peptide to any TCR, including peptide and TCR sequences that were not included in the training set. We address biological issues that should be considered in the design of machine learning models for TCR-peptide binding and suggest that models trained only on beta chains give satisfactory predictions. Finally, we apply our models to large data set of TCR repertoires from COVID-19 patients and find that TCRs from patients in severe/critical condition have significantly lower scores for binding SARS-coV-2 epitopes compared to TCRs from moderate patients (p-value <0.001).Availability and ImplementationPOP-Up TCR is available at:https://github.com/NiliTicko/POP-UP-TCRContactnilibrac@bgu.ac.il
Machine Learning-Based Prediction of Free IgE Concentration in Allergic Rhinitis Patients Treated with Allergen Immunotherapy and Omalizumab
Authors: Olanrewaju Kazeem B. , Ngansop Djampou Laura Marthe Emilie 
Published: September 2023

AbstractFree immunoglobulin E (IgE) concentration is a key biomarker for allergic diseases. Prediction of free IgE concentration can help clinicians diagnose and monitor allergic diseases more effectively. In this study, we used machine learning to predict free IgE concentration in the blood serum of patients with allergic rhinitis who received allergen immunotherapy co-administered with omalizumab. The predictors for free IgE concentration were the number of visits for treatment and baseline checking, and treatment groups (1) omalizumab/ragweed, (2) omalizumab/placebo, (3) placebo/ragweed, and (4) placebo/placebo. Several machine learning algorithms (MLA) were trained with the immunotherapy dataset imported from Immune Tolerance Network (ITN) TrialShare into the Orange data mining platform. The decision tree algorithm model amidst the list of MLAs trained and tested was the best performing model for predicting free IgE concentration, with an R-squared of about 0.6. This study demonstrates that machine learning can be used to predict free IgE concentration with high accuracy. This prediction model could be used to help clinicians diagnose and monitor allergic diseases more effectively.
Validation of cardiac image derived input functions for functional PET quantification
Authors: Reed Murray Bruce , Handschuh Patricia Anna , Schmidt Clemens , Murgaš Matej , Gomola David , Milz Christian , Klug Sebastian , Eggerstorfer Benjamin , Aichinger Lisa , Godbersen Godber Mathis , Nics Lukas , Traub-Weidinger Tatjana , Hacker Marcus , Lanzenberger Rupert , Hahn Andreas 
Published: September 2023

AbstractFunctional PET (fPET) is a novel technique for studying dynamic changes in brain metabolism and neurotransmitter signaling. Accurate measurement of the arterial input function (AIF) is crucial for quantification of fPET but traditionally requires invasive arterial blood sampling. While, image-derived input functions (IDIF) offer a non-invasive alternative, they are afflicted by drawbacks stemming from limited spatial resolution and field of view. Therefore, we conceptualized and validated a scan protocol for brain fPET quantified with cardiac IDIF.Twenty healthy individuals underwent fPET/MR scans using [18F]FDG or 6-[18F]FDOPA, with bed motion shuttling between the thorax and brain to capture cardiac IDIF and brain task- induced changes, respectively. Each session included arterial and venous blood sampling for IDIF validation, and participants performed a monetary incentive delay task. IDIFs from fixed- size regions of the left ventricle, ascending and descending aorta, and a composite of all 3 blood pools (3VOI) plus venous blood data (3VOIVB) were compared to the AIF. Quantitative task-specific images from both tracers were compared to assess the performance of each input function.For both radiotracer cohorts, moderate to high agreement was found between IDIFs and AIF in terms of area under the curve (r = 0.64 – 0.89) and quantified outcome parameters (CMRGlu and Ki(r)=0.84–0.99). The agreement further increased for composite IDIFs 3VOI and 3VOIVB for AUC(r)=0.87–0.93) and outcome parameters (r=0.96–0.99). Both methods showed equivalent quantitative values and high spatial overlap with AIF-derived measurements.Our proposed protocol enables accurate non-invasive estimation of the input function with full quantification of task-specific changes, addressing the limitations of IDIF for brain imaging by sampling larger blood pools over the thorax. These advancements increase applicability to virtually any PET scanner and to clinical research settings by reducing experimental complexity and increasing patient comfort.Graphical Abstract
Prevalence of COVID-19 and long COVID - Results from the 2022 Behavioral Risk Factor Surveillance System, 50 states
Authors: Adams Mary L. , Grandpre Joseph 
Published: September 2023

AbstractRecent MMWR results estimate long COVID prevalence at 6.0% in June 2023, while the percentage of those with COVID reporting long COVID was 11.0%. The 2022 Behavioral Risk Factor Surveillance System addressed COVID (positive test) and long COVID (symptoms lasting ≥3 months) in a population-based sample from each state and DC. Results for 385,617 adults indicated 34.4% had ever had COVID, 21.9% of whom reported long COVID, representing 7.4% of all adults. State rates ranged from 25.4% - 40.8% for COVID and 4.1%- 11.1% for long COVID. Groups with high rates for both included women, younger adults, those with children in the household, plus those reporting obesity, asthma, chronic obstructive pulmonary disease (COPD), diabetes, or cardiovascular disease (CVD). Highest adjusted odds ratios for COVID were 2.34 (95% CI 2.20-2.49) for age 18-24 years vs. age 65+ while for long COVID it was 2.81 (2.53-3.13) for 3+ of the 5 conditions. Most frequently reported problems for those with long COVID were fatigue (26.0%), shortness of breath (18.8%), loss of taste or smell (17.2%), and memory problems (9.9%). Results show the need for state-based data and suggest a focus on younger adults is needed to address COVID and long COVID.