bluuebunny/crossref_metadata_2025 huggingface dataset:
Lymphogranuloma Venereum Surveillance in Chlamydia trachomatis Positive Male Rectal Swabs Collected from I Want The Kit in Maryland, United States
Authors: Hardick Justin , Conte Madison , Young Mattlyn , Ramdeep Nisha , Manabe Yukari C , Hamill Matthew M
Published: December 2024

Background

Infection with Chlamydia trachomatis (CT) can have distinct clinical presentations, such as trachoma, or lymphogranuloma venereum (LGV). Certain populations are at greater risk for LGV acquisition and transmission, which requires a longer duration of therapy than other urogenital CT sexually transmitted infections (STIs). Commercial assays are not available in the United States to distinguish LGV from non-LGV serovars.

Methods

LGV real-time PCR was performed on rectal CT-positive samples (N = 93) obtained from men (N = 80) who ordered from a mail-in self-collection STI service between April 2021 and February 2024. pmpH gene sequencing was performed on all samples to confirm LGV versus non-LGV, and multi-locus sequence typing (MLST) was performed on LGV-positive samples (N = 7) for additional confirmation.

Results

LGV was detected in 7.5% (7/93) of samples by real-time PCR, with pmpH sequencing and MLST confirming 100% (7/7) of these results. Overall, pmpH sequencing data was obtained for 92% (86/93) of samples with the following serovar distribution based on BLAST analysis: 54% (47/86) J, 28% (24/86) F, 9% (8/86) E and 8% (7/86) L. No individual had more than one LGV positive sample. No statistically significant associations with demographic factors were identified.

Conclusions

LGV was detected in CT-positive rectal swabs from users of an online, mail-in, self-collect STI testing platform in Maryland. These data suggest that increased LGV reflexive testing may be warranted. These data also illustrate that mail-in programs for routine STI testing may be leveraged for public health surveillance purposes.
Comparison of Chlamydia trachomatis Seroprevalence and Risk Factors for Infection Among Women by Gender/Sex of Sex Partner, United States, 2013–2016
Authors: Paris Keely S. , Khosropour Christine M. , Balkus Jennifer E. , Waters Mary Bridget , Kreisel Kristen M. , Manhart Lisa E.
Published: December 2024

Objectives

Women who report sex with women are thought to have lower risk for Chlamydia trachomatis (CT) infection than women who report sex with men only (WSM-only), but comparisons of lifetime burden are limited.

Methods

Among 1,418 sexually-experienced women aged 18-39 years participating in the National Health and Nutrition Examination Survey (2013-2016), we estimated weighted CT seroprevalence and Wald-based 95% confidence intervals (CI) in women who reported ever having sex with a woman (all reported having sex with men also) (WSWM) compared to WSM-only. We defined seropositivity as detection of Pgp3 antibodies and used stratified Poisson regression with robust standard errors to estimate prevalence ratios.

Results

Over half (58.3%) were White non-Hispanic; 16.2% were WSWM. WSWM were somewhat younger (mean = 27.8 vs. 29.0 years, p = 0.07), younger at sexual debut (mean = 15.6 vs. 17.5 years, p < 0.001), and had more lifetime male sexual partners (mean = 15.9 vs. 6.4, p < 0.001) than WSM-only. Weighted CT seroprevalence was 38.9% (95%CI = 30.4-47.4) in WSWM and 28.6% (95%CI = 24.4-32.9) in WSM-only. Correlates of higher CT seroprevalence in both groups were Black non-Hispanic race/ethnicity, Hispanic ethnicity, and CT infection in the prior year. Having ≥5 lifetime male partners compared to 1-2 partners was associated with higher seroprevalence among WSWM (PR = 4.5; 95%CI = 1.77-11.44) and WSM-only (PR = 2.7; 95%CI = 1.87-3.69). Among WSWM, bisexual identity was associated with lower seroprevalence. Among WSM-only, low income and younger age at sexual debut were associated with higher seroprevalence.

Conclusion

Lifetime CT burden was higher in WSWM than WSM-only. Number of lifetime male partners was the strongest predictor of seropositivity for WSWM.
Targeted Peptide Receptor Radionuclide Therapy With 177Lu-DOTATATE Alters Joints Inflammation
Authors: Usmani Sharjeel , Rasheed Rashid , Ahmed Najeeb , Omar Yehia , Numani Shah P.
Published: December 2024

High and frequent expression of somatostatin receptors in differentiated neuroendocrine neoplasms has paved the way for receptor-based, targeted peptide receptor radionuclide therapy especially for nonoperable or metastatic disease. Besides tumors, radiation, in one form or another, has been tested to treat inflammatory disease as well, and this goes back to the early 1990s when the first case of pneumonia treated with radiation showed complete resolution. Currently, radiotracers help in not only in vivo inflammation detection, characterization, and staging but also, and more importantly, for selection of treatment in individual patients. The same concept could be applied to treatment of infection, by coupling the radioisotopes to ligands that target sterile or nonsterile inflammation. In our case, targeted peptide receptor radionuclide therapy showed remarkable resolution of inflammatory joint disease.
Multiple interacting photonic modes in strongly coupled organic microcavities
Authors: Herrera Felipe , Barnes William L.
Published: December 2024

Room-temperature cavity quantum electrodynamics with molecular materials in optical cavities offers exciting prospects for controlling electronic, nuclear and photonic degrees of freedom for applications in physics, chemistry and materials science. However, achieving strong coupling with molecular ensembles typically requires high molecular densities and substantial electromagnetic-field confinement. These conditions usually involve a significant degree of molecular disorder and a highly structured photonic density of states. It remains unclear to what extent these additional complexities modify the usual physical picture of strong coupling developed for atoms and inorganic semiconductors. Using a microscopic quantum description of molecular ensembles in realistic multimode optical resonators, we show that the emergence of vacuum Rabi splitting in linear spectroscopy is a necessary but not sufficient metric of coherent admixing between light and matter. In low-finesse multi-mode situations, we find that molecular dipoles can be partially hybridized with photonic dissipation channels associated with off-resonant cavity modes. These vacuum-induced dissipative processes ultimately limit the extent of light-matter coherence that the system can sustain.

This article is part of the theme issue ‘The quantum theory of light’.
The not quite Loudon–Fearn–Rarity–Tapster dip and its impact on the development of photonic quantum information
Authors: Rarity John G.
Published: December 2024

This paper presents a short history of the discovery by Rodney Loudon and Heidi Fearn of the counter-intuitive destructive interference effect occurring when two indistinguishable photons meet at a beamsplitter. This effect, commonly known as the Hong Ou Mandel effect, underpins much of present day photonic quantum information processing. Here I try to review its development from inception to present day proposals of million qubit photonic quantum computers.

This article is part of the theme issue ‘The quantum theory of Light’.
Synergy and antagonism in a genome-scale model of metabolic hijacking by bacteriophage
Authors: Rozum Jordan C. , Sineath William , Kim Doo Nam , Bohutskyi Pavlo , Johnson Connah , Evans James , Pollock David , Qian Wei-Jun , Cheung Margaret S. , Wu Ruonan , Feng Song
Published: December 2024

Bacteriophage auxiliary metabolic genes (AMGs) alter host metabolism by hijacking reactions. Previous studies used functional annotations to infer AMG impacts, but how these propagate and interact to affect global metabolism and phage production remains understudied. We demonstrate the first integration of AMGs and phage assembly into a genome-scale metabolic model, using P-HM2 infection ofProchloroccocus marinusMED4 as a test system. Our model predicts that 17 directly hijacked reactions substantially impact over 30% of the metabolism, including carbon fixation, photosynthesis, and nucleotide synthesis. These indirect impacts are synergistically and antagonistically coupled. We find that hijacked reactions are either phage-aligned–shifting feasible reaction velocities in accordance with maximal phage production–or phage-antialigned. Phage-alignment predicts changes to the host-phage biomass Pareto front: phage-aligned reactions limit host growth; phage-antialigned reactions do not. We provide a systems-level understanding of AMG perturbations, revealing nontrivial cascading effects and highlighting their role in shaping microbial functions.
Identification and comparison of orthologous cell types from primate embryoid bodies shows limits of marker gene transferability
Authors: Jocher Jessica , Janssen Philipp , Vieth Beate , Edenhofer Fiona C. , Dietl Tamina , Térmeg Anita , Geuder Johanna , Enard Wolfgang , Hellmann Ines
Published: December 2024

The identification of cell types remains a major challenge. Even after a decade of single-cell RNA sequencing (scRNA-seq), reasonable cell type annotations almost always include manual non-automated steps. The identification of orthologous cell types across species complicates matters even more, but at the same time strengthens the confidence in the assignment. Here, we generate and analyze a dataset consisting of embryoid bodies (EBs) derived from induced pluripotent stem cells (iPSCs) of four primate species: humans, orangutans, cynomolgus, and rhesus macaques. This kind of data includes a continuum of developmental cell types, multiple batch effects (i.e. species and individuals) and uneven cell type compositions and hence poses many challenges. We developed a semi-automated computational pipeline combining classification and marker based cluster annotation to identify orthologous cell types across primates. This approach enabled the investigation of cross-species conservation of gene expression. Consistent with previous studies, our data confirm that broadly expressed genes are more conserved than cell type-specific genes, raising the question how conserved - inherently cell type-specific - marker genes are. Our analyses reveal that human marker genes are less effective in macaques and vice versa, highlighting the limited transferability of markers across species. Overall, our study advances the identification of orthologous cell types across species, provides a well-curated cell type reference for futurein vitrostudies and informs the transferability of marker genes across species.
Synchronous 3D patterning of diverse CNS progenitors generates motor neurons of broad axial identity
Authors: Buchner Felix , Dokuzluoglu Zeynep , Thomas Joshua , Caldarelli Antonio , Kavali Shrutika , Rost Fabian , Grass Tobias , Rodríguez-Muela Natalia
Published: December 2024

In vitro human organoid models have become transformative tools for studying organogenesis, enabling the generation of spinal cord organoids (SCOs) that mimic aspects of spinal cord biology. However, current models do not produce spinal motor neurons (spMNs) with a wide range of axial identities along spinal cord segments within a single structure, limiting their utility in understanding human neural axial specification and the selective vulnerability of spMN subpopulations in motor neuron diseases. Here, we present a novel approach to enhance spMN axial heterogeneity in an advanced SCO model derived from neural stem cells (NSCs) and retinoic acid (RA)-primed neuromesodermal progenitors (NMPs). RA priming guided NMP differentiation into caudal neural progenitors, generating SCOs enriched in spMNs with posterior axial identities. To further diversify spMN populations, we optimized differentiation by synchronously patterning NSCs with RA-primed NMPs. Incorporating an endothelial-like network and skeletal muscle cells enhanced the organoids’ physiological complexity and neural maturation and organoid cell viability. This comprehensive approach, termed CASCO, provides a robust platform to study human spMN specification and model neurodegenerative diseases.
Neuronal alpha-Synuclein Disease stage progression over five years
Authors: Simuni Tanya , Gochanour Caroline , Nair Anuprita R , Brumm Michael C , Coffey Christopher , Poston Kathleen L , Chahine Lana M , Weintraub Daniel , Tanner Caroline M , Gonzalez-Latapi Paulina , Kopil Catherine M , Xiao Yuge , Chowdhury Sohini , Dam Tien , Pagano Gennaro , Stephenson Diane , Siderowf Andrew , Dunn Billy , Marek Kenneth
Published: December 2024

Background

Neuronal alpha-Synuclein Disease (NSD) is defined by presence of an in vivo biomarker of neuronal alpha-synuclein (n-asyn) pathology, independent of presence of clinical syndrome. The NSD integrated staging system (NSD-ISS) describes progression across the disease continuum as stages 0 to 6. The objective of this analysis was to assess 5-year longitudinal change in the NSD-ISS.

Methods

Analysis included a subset of participants from the Parkinson’s Progression Markers Initiative (PPMI) enrolled before 2020 as Parkinson’s disease, prodromal, or healthy controls who met NSD criteria. Staging was defined based on biomarkers of n-asyn and dopaminergic dysfunction in early stages, clinical features (cognition, other non-motor features, and parkinsonism), and increasing degree of functional impairment in stages 3-6. Stages were examined annually for 5 years, along with the determinants of progression and effects of dopaminergic medication.

Findings

576 participants were n-asyn positive and included in the analysis. Of these, 494 were enrolled as Parkinson’s disease, 74 as prodromal and 8 as healthy controls. At baseline 56% of participants were in stage 3, 24% stage 2B, 13% stage 4, 4% stage 2A, and <1% in the other stages. At year 5, the percent of individuals in stage 2B, 3, and 4 were 11%, 50%, and 34% respectively, indicating progression through NSD stages. Median (95% CI) time to next stage increase from baseline was 1·19 (1·07-2·01) for stage 2B, 4·98 (4·07-5·35) for stage 3, and 9·77 (7·04-NA) for stage 4. Progression was driven by functional impairment in predominantly motor domain (95%) for stage 2B to 3, increasing degree of non-motor dysfunction for stage 3 to 4 (46%), and combination of motor, non-motor and cognitive domains for stage 4 to 5. Initiation of dopaminergic medications lead to stage regression in 8% participants in stage 3 and 41% in stage 4.

Interpretation

Our analysis supports the validity of the NSD-ISS in defining stages of disease progression and support the utility of the NSD-ISS as a potential tool to identify clinical trial cohorts for drug development. Further validation in interventional studies is a crucial next step.

Funding

The Michael J. Fox Foundation for Parkinson’s Research (MJFF).
Differential aggregation patterns ofEndozoicomonaswithin tissues of the coralAcropora loripes
Authors: Gotze Cecilie R , Dungan Ashley M , van de Meene Allison , Damjanovic Katarina , Philip Gayle K , Maire Justin , Hoj Lone , Blackall Linda L , van Oppen Madeleine JH
Published: December 2024

Bacteria in the genusEndozoicomonasare well-known coral symbionts commonly found as clusters within tissues of several coral species. Mapping the spatial distribution of these microbial communities is critical to gaining a holistic understanding of the potential role they may play within the coral host. This study focuses on characterising bacterial aggregates associated with the common reef-building coral,Acropora loripes, from the central Great Barrier Reef, Australia. A conventional cultivation-based method was employed to establish a pure culture collection of 11 undescribedEndozoicomonasstrains isolated fromA. loripes. Subsequent 16S rRNA gene sequence analysis revealed their classification into two distinct phylogenetic clades. To resolve their spatial distributionin hospite, clade-specific fluorescencein situhybridisation probes were designed. Aggregates were consistently observed in the gastrodermal tissue layers surrounding the upper and lower gastrovascular cavity and were predominantly formed by cells from the same phylogenetic clade, with a minor proportion of aggregates formed byEndozoicomonasfrom both targeted clades. Furthermore, a clear distinction in aggregation pattern was observed; one clade exhibited clusters with regular and contained growth patterns, whereas the other formed clusters lacking clear boundaries and having irregular shapes. Scanning electron microscopy revealed the presence of a membrane of unknown origin associated with bacterial aggregates in two instances, suggesting potential structural or functional differences in these aggregates. These contrasting morphological features underscore the need for comprehensive investigations into the underlying mechanisms governing bacterial aggregate formation in corals.
Zero-shot retention time prediction for unseen post-translational modifications with molecular structure encodings
Authors: Dens Ceder , Yeung Darien , Krokhin Oleg , Laukens Kris , Bittremieux Wout
Published: December 2024

Mass spectrometry-based proteomics relies on accurate peptide property prediction models to enhance peptide identification and characterization, especially when dealing with peptidoforms. However, current approaches are limited in their ability to generalize to peptides with novel post-translational modifications (PTMs) due to insufficient training data. To address this challenge, we introduce MoSTERT (Molecular Structure Transformer Encoder for Retention Time prediction) and its enhanced variant, MoSTERT-2S, two transformer-based models designed for zero-shot prediction of retention times of peptides with unseen PTMs. Unlike conventional models, MoSTERT encodes peptide residues at the molecular structure level, allowing it to handle diverse PTMs. MoSTERT-2S further improves accuracy by employing a two-step strategy: first predicting the retention time of the unmodified peptide, then estimating the retention time shift induced by the PTMs.

Evaluation on an external dataset demonstrates that MoSTERT-2S achieves state-of-the-art performance, reducing prediction errors compared to existing methods. Its ability to accurately predict retention times for peptides with a wide variety of PTMs not seen during training highlights its potential for advancing proteomic workflows analyzing proteoforms and protein modifications.
Decoding Poultry Vocalizations - Natural Language Processing and Transformer Models for Semantic and Emotional Analysis
Authors: Manikandan Venkatraman , Neethirajan Suresh
Published: December 2024

Deciphering the acoustic “language” of chickens opens new frontiers in animal welfare and ecological informatics, illuminating how subtle vocal signals encode health status, emotional states, and interactions within ecosystems. By uncovering the semantics of these vocalizations, we gain a powerful tool for interpreting their functional vocabulary—how each call serves a purpose within the social and environmental context. Here, we leverage state-of-the-art Natural Language Processing (NLP) and transformer-based models to translate bioacoustic data into meaningful insights. Our approach integrates Wave2Vec 2.0 for raw audio feature extraction with a fine-tuned Bidirectional Encoder Representations from Transformers (BERT) model, pretrained on a broad corpus of animal sounds and adapted to poultry-specific tasks. This novel pipeline decodes poultry vocalizations into interpretable categories—such as distress calls, feeding signals, and mating vocalizations—while revealing subtle emotional nuances often overlooked by traditional spectrogram-based analyses. Achieving 92% accuracy in classifying key vocalization types, our methodology demonstrates the feasibility of real-time, automated monitoring of flock health and stress levels. By continuously tracking this functional vocabulary, farmers can respond proactively to environmental or behavioral changes, enhancing poultry welfare, reducing stress-induced productivity losses, and promoting more sustainable farm management. Beyond its direct agricultural applications, this work enriches our understanding of computational ecology. Gaining access to the semantic foundation of animal calls provides a window into the ecological networks of which poultry are a part, potentially serving as indicators of biodiversity, environmental stressors, and species interactions. In bridging animal behavior, machine learning, and ecosystem analysis, our framework lays a foundation for integrative studies that harness acoustic data to inform ecological decision-making and develop more resilient, ethically aligned agricultural systems.
Beyond community-weighted means: quantifying trait distributions for detecting community assembly patterns
Authors: Melero Yolanda , Stefanescu Constanti , Garcia-Callejas David
Published: December 2024

The distributions of ecological traits are commonly used to infer the processes structuring ecological communities, as these processes (either deterministic or stochastic) select and filter species, leading to distinct trait patterns across communities. Trait distributions are frequently characterised by their average, the community-weighted mean, but increasing evidence exists for non-gaussian trait distributions in empirical communities. In such situations, community-weighted means are insufficient to capture the patterns of community traits and to infer the implied ecological processes. Here we analyse the empirical distributions of 6 functional traits of butterflies from a natural community and a filtered community from a urban area across a period of six years. First, we show that to adequately describe trait distributions, statistical descriptors beyond community-weighted means are needed, as distributions were in all cases clearly non-gaussian. In particular, besides distribution averages and standard deviations, we compute the skewness, kurtosis, the range of trait values, and a multimodality index. Second, we compare this set of descriptors between our natural and filtered communities. We find clear differences between communities, detected in particular by combining the relationships between the skewness, kurtosis, and range of the distributions. These analyses allow us to infer that the filtered community is mostly shaped by deterministic filtering processes, through a mixture of directional and stabilising assembly filters. These patterns are furthermore consistent across the six years of data, providing further evidence of deterministic processes shaping the assembly of our urban butterfly community. Overall, we provide evidence of the ubiquity of non-gaussian trait distributions across natural and filtered communities, propose key descriptors for understanding and comparing such distributions, and identify filtering process structuring these communities.
CD4+ T-cells create a stable mechanical environment for force-sensitive TCR:pMHC interactions
Authors: Schrangl Lukas , Kellner Florian , Platzer René , Mühlgrabner Vanessa , Hubinger Paul , Wieland Josephine , Obst Reinhard , Toca-Herrera José L. , Huppa Johannes B. , Schütz Gerhard J. , Göhring Janett
Published: December 2024

Mechanical forces acting on ligand-engaged T-cell receptors (TCRs) have previously been implicated in T-cell antigen recognition and ligand discrimination, yet their magnitude, frequency, and impact remain unclear. We quantitatively assess forces across various TCR:pMHC pairs with different bond lifetimes at single-molecule resolution, both before and during T-cell activation, on platforms that either include or exclude tangential force registration. Our results imply that CD4+ T-cell TCRs experience significantly lower forces than previously estimated, with only a small fraction of ligand-engaged TCRs being subjected to these forces during antigen scanning. These rare and minute mechanical forces do not impact the global lifetime distribution of the TCR:ligand bond. We propose that the immunological synapse is created as biophysically stable environment to prevent pulling forces from disturbing antigen recognition.
A hybrid micro-ECoG for functionally targeted multi-site and multi-scale investigation
Authors: Jendritza Patrick , Liljemalm Rickard , Stieglitz Thomas , Fries Pascal , Lewis Christopher Murphy
Published: December 2024

Brain function relies on the coordination of activity across a wide range of spatial and temporal scales. The activity of single neurons depends on their unique pattern of local and long-range connectivity and thus on the coordination of local activity with large-scale patterns of distributed activity across brain-wide networks. Understanding integrated, whole brain function requires new tools capable of recording from anatomically connected populations in distributed brain areas to bridge local and global dynamics. Here, we present high-density, micro-electrocorticography arrays that facilitate multi-scale studies of brain activity. The arrays are hybrid designs that integrate the desirable features of silicone elastomers and polyimide films. The silicone elastomer superstructure provides optical transparency and permits repeated mechanical penetration with rigid linear electrode arrays. The polyimide films provide the capacity for fine feature definition through photolithography. This combination facilitates high-throughput functional mapping of areas of interest to target functionally characterized populations for refined, dense sampling. We demonstrate the suitability of the technique for functional mapping of cortical regions in rats, cats and marmosets and the benefit of the resulting functional maps for targeting functionally defined populations for dense, multi-area laminar recordings. Finally, we demonstrate the utility of the hybrid µECoG to localize optogenetically evoked feedforward excitation in down-stream cortical regions to investigate cortico-cortical interactions. Together, these capabilities make the hybrid µECoG a compelling tool for systems neuroscience.
Comprehensive Analysis of Human Dendritic Spine Morphology and Density: Exploring Diversity of Human Dendritic Spines
Authors: Schünemann Kerstin D , Hattingh Roxanne M , Verhoog Matthijs B , Yang Danqing , Bak Aniella , Peter Sabrina , van Loo Karen M.J. , Wolking Stefan , Kronenberg-Versteeg Deborah , Weber Yvonne , Schwarz Niklas , Raimondo Joseph V , Melvill Roger , Tromp Sean , Butler James , Höllig Anke , Delev Daniel , Wuttke Thomas V , Kampa Björn M , Koch Henner
Published: December 2024

Dendritic spines, small protrusions on neuronal dendrites, play a crucial role in brain function by changing shape and size in response to neural activity. So far,in depthanalysis of dendritic spines in human brain tissue is lacking. This study presents a comprehensive analysis of human dendritic spine morphology and density using a unique dataset from human brain tissue from 27 patients (8 females, 19 males, aged 18-71) undergoing tumor or epilepsy surgery at three neurosurgery sites. We used acute slices and organotypic brain slice cultures to examine dendritic spines, classifying them into the three main morphological subtypes: Mushroom, Thin, and Stubby, via 3D reconstruction using ZEISS arivis Pro software. A deep learning model, trained on 39 diverse datasets, automated spine segmentation and 3D reconstruction, achieving a 74% F1-score and reducing processing time by over 50%. We show significant differences in spine density by sex, dendrite type, and tissue condition. Females had higher spine densities than males, and apical dendrites were denser in spines than basal ones. Acute tissue showed higher spine densities compared to cultured human brain tissue. With time in culture, Mushroom spines decreased, while Stubby and Thin spine percentages increased, particularly from 7-9 to 14 daysin vitro, reflecting potential synaptic plasticity changes. Our study underscores the importance of using human brain tissue to understand unique synaptic properties and shows that integrating deep learning with traditional methods enables efficient large-scale analysis, revealing key insights into sex- and tissue-specific dendritic spine dynamics relevant to neurological diseases.

New and Noteworthy

This study presents a dataset of nearly 4,000 morphologically reconstructed human dendritic spines across different ages, gender, and tissue conditions. The dataset was further used to evaluate a deep learning algorithm for three-dimensional spine reconstruction, offering a scalable method for semi-automated spine analysis across various tissues and microscopy setups. The findings enhance understanding of human neurology, indicating potential connections between spine morphology, brain function, and the mechanisms of neurological and psychiatric diseases.
Impact of early life antibiotic and probiotic treatment on gut microbiome and resistome of very-low-birth-weight preterm infants
Authors: Kiu Raymond , Darby Elizabeth M , Alcon-Giner Cristina , Acuna-Gonzalez Antia , Camargo Anny , Lamberte Lisa E , Phillips Sarah , Sim Kathleen , Shaw Alexander G , Clarke Paul , Schaik Willem van , Kroll J Simon , Hall Lindsay J
Published: December 2024

Preterm infants (<37 weeks’ gestation) are often administered broad-spectrum antibiotics in hospitals due to their vulnerability to severe morbidity, including necrotising enterocolitis and sepsis. However, antibiotics can disrupt the development of early-life microbiota, potentially impairing gut immunity and colonisation resistance. Evidence shows that probiotics (e.g., certainBifidobacteriumstrains) may help restore healthy gut microbiota. In this study, we examined the effects of probiotics and antibiotics on the preterm gut microbiome and resistome in two unique cohorts of 34 very-low-birth-weight, human-milk- fed preterm infants (moderate to very preterm), with one cohort receiving probiotics. Within each group, some infants were treated with antibiotics (benzylpenicillin and/or gentamicin) while others served as non-antibiotic treated controls. We performed shotgun metagenomic sequencing on 93 longitudinal faecal samples from 34 infants, generated >300 metagenome- assembled genomes, and obtained ∼90 isolate genomes through targeted culturomics, enabling analysis of the microbiome/resistome at species and strain levels. Additionally, we investigatedin vitrohorizontal gene transfer (HGT) capacity of preterm infant-derived multidrug-resistant (MDR) pathogenEnterococcusvia neonatal gut models. Overall, probiotic supplementation significantly reduced antibiotic resistance gene prevalence, MDR pathogen load, and helped restore a typical early-life microbiota. However, the persistence of MDR pathogens likeEnterococcus, with high HGT potential, highlights the need for ongoing surveillance in neonatal care. Our findings underscore the complex interactions between antibiotics, probiotics, and HGT in shaping the neonatal microbiome and support further research into probiotics for antimicrobial stewardship in preterm populations.
Visualizing Functional Network Connectivity Differences Using an Explainable Machine-learning Method
Authors: Sendi Mohammad S. E. , Itkyal Vaibhavi S. , Edwards-Swart Sabrina J. , Chun Ji Ye , Mathalon Daniel H. , Ford Judith M. , Preda Adrian , van Erp Theo G.M. , Pearlson Godfrey D. , Turner Jessica A. , Calhoun Vince D.
Published: December 2024

Functional network connectivity (FNC) estimated from resting-state functional magnetic resonance imaging showed great information about the neural mechanism in different brain disorders. But previous research has mainly focused on standard statistical learning approaches to find FNC features separating patients from control. Although machine learning approaches provide better models separating controls from patients, it is not straightforward for these approaches to provide intuition on the model and the underlying neural process of each disorder. Explainable machine learning offers a solution to this problem by applying machine learning to understand the neural process behind brain disorders. In this study, we introduce a novel framework leveraging SHapley Additive exPlanations (SHAP) to identify crucial Functional Network Connectivity (FNC) features distinguishing between two distinct population classes. Initially, we validate our approach using synthetic data. Subsequently, applying our framework, we ascertain FNC biomarkers distinguishing between, controls and schizophrenia patients with accuracy of 81.04% as well as middle aged adults and old aged adults with accuracy 71.38%, respectively, employing Random Forest (RF), XGBoost, and CATBoost models. Our analysis underscores the pivotal role of the cognitive control network (CCN), subcortical network (SCN), and somatomotor network (SMN) in discerning individuals with schizophrenia from controls. In addition, our platform found CCN and SCN as the most important networks separating young adults from older.
Tonic ERK signaling regulate the basal lactate production in prepubertal rat Sertoli cell
Authors: Gautam Mukesh , Pradhan Bhola Shankar , Majumdar Subeer S
Published: December 2024

Sertoli cells are the major nurse cells in the testis which regulate the division and differentiation of germ cell by secreting various factors like inhibin B, transferrin and lactate. In this study, we demonstrated that inhibition of extracellular signal-regulated kinase (ERK) leads to an increase in the basal level of lactate. This increase in lactate production was due to the rise in lactate dehydrogenase (LDH) activity and glucose uptake, simultaneously. Moreover, an increase in lactate production wasnot due to the change in mRNA level ofGLU1,GLUT3andLDHA. Importantly, the lactate production was independent of the level of cAMP suggesting that the tonic signaling of ERK is important for the growth factor mediated lactate production. These findings suggest that ERK signaling inhibits lactate production in the absence of any stimulant in rat Sertoli cells to maintain metabolic homeostasis.
Novel approaches to label the surface ofS. aureuswith DBCO for click chemistry-mediated deposition of sensitive cargo
Authors: Baryakova Tsvetelina H. , Segatori Laura , McHugh Kevin J.
Published: December 2024

The strain-promoted alkyne-azide cycloaddition (SPAAC) reaction can be used to modify the surface of bacteria for a variety of applications, including drug delivery, biosensing, and imaging. This is usually accomplished by first installing a small azide group within the peptidoglycan and then delivering exogenous cargo (e.g., a protein or nanoparticle) modified with a cyclooctyne group, such as dibenzocyclooctyne (DBCO), forin situconjugation. However, DBCO is comparatively bulky and hydrophobic, increasing the propensity for some payloads to aggregate. In this study, we sought to invert this paradigm by exploring two novel strategies for incorporating DBCO into the peptidoglycan ofStaphylococcus aureusand compared them to an established approach using DBCO-vancomycin. We demonstrate that DBCO-modified small molecules belonging to all three classes – a sortase peptide substrate (LPETG), two D-alanine derivatives, and vancomycin – can selectively label theS. aureussurface to varying degrees. In contrast to DBCO-vancomycin, the DBCO-D-alanine variants do not adversely affect the growth ofS. aureusor lead to off-target labeling or toxicity in HEK293T cells, even at high concentrations. Finally, we show that, unlike IgG3-Fc labeled with DBCO groups, IgG3-Fc labeled with azide groups is stable (i.e., remains water-soluble) under normal storage conditions, retains its ability to bind the immune receptor CD64, and can be successfully attached to the surface of DBCO-modifiedS. aureus. We believe the labeling strategies explored herein will expand the paradigm of specific, nontoxic SPAAC-mediated labeling of the surface ofS. aureusand other gram-positive bacteria, opening the door for new applications using azido-modified cargo.

GRAPHICAL ABSTRACT
Impact of COVID-19 vaccine doses and viral waves on inflammatory and immunological responses to COVID-19 infections in India
Authors: Sharma Kamal Kant , Partap Uttara , Marathe Yogesh , Shaikh Sanaa , D’Costa Pradeep , Gupta Gaurav , Wang Molin , Fawzi Wafaie W , Kain Kevin C , Mistry Nerges , Dholakia Yatin
Published: December 2024

Background

Investigation of the effect of SARS-CoV-2 variants and COVID-19 vaccination on inflammatory and immune response to SARS-CoV-2 infection is limited in South Asia.

Objectives

We aimed to examine the impact of COVID-19 vaccination and waves of COVID- 19 on inflammatory and immunological biomarkers among COVID-19 patients in India.

Methods

This cross-sectional analysis used baseline data from a randomized controlled trial of vitamin D and zinc during COVID-19 infection in India (N=181). Blood samples and data regarding vaccination doses were collected. The second (Delta) or third (Omicron) wave was determined by date of enrolment. Mixed effects linear regression with robust standard errors was used to examine associations between COVID-19 vaccination dose or wave at enrolment and C-Reactive Protein (CRP), ferritin, lactate dehydrogenase (LDH), D-dimer, interleukin-6 (IL-6), angiopoietin-2 (Ang-2), soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), immunoglobulin G (IgG) and immunoglobulin M (IgM).

Results

Compared to no vaccination, full vaccination was associated with lower LDH (P<0.001), D-dimer (P=0.521) and Ang-2 (P=0.046), and higher IgG levels (P<0.001). Partial vaccination was associated with lower IL-6 (P=0.040) and higher IgG (P<0.001). Enrolment during the third wave was associated with lower IL-6 (P<0.001), CRP (P=0.056), IgM (P=0.013), and IgG (P<0.001), but higher D-dimer levels (P<0.001).

Conclusions

COVID-19 vaccination status and SARS-CoV-2 variant influence the inflammatory and immunologic response during SARS-CoV-2 infection, contributing to the severity of clinical presentation.
Single-cell transcriptome-wide Mendelian randomization and colocalization analyses uncover cell-specific mechanisms in atherosclerotic cardiovascular disease
Authors: Ray Anushree , Alabarse Paulo , Malik Rainer , Sargurupremraj Muralidharan , Bernhagen Jürgen , Dichgans Martin , Baumeister Sebastian-Edgar , Georgakis Marios K.
Published: December 2024

Genome-wide association studies (GWAS) have identified numerous genetic loci influencing human disease risk. However, linking these loci to causal genes remains challenging, limiting opportunities for drug target discovery. Transcriptome-wide association studies (TWAS) address this by linking variants to gene expression, but typically rely on bulk RNA sequencing, which lacks cell-specific resolution. Here, we present a single-cell TWAS pipeline combiningcis-Mendelian randomization (MR) with colocalization analyses at the single-cell level. As a case study, we examined how genetically proxied gene expression in immune cells influences atherosclerotic cardiovascular disease (ASCVD) risk. We integrated single-cell expression quantitative trait loci (sc-eQTL) for 14 immune cell types with GWAS for coronary artery disease, large artery atherosclerotic stroke, and peripheral artery disease. Single-cellcis-MR analyses revealed 440 gene-outcome associations across cell types, 84% of which were missed by bulk TWAS, despite a considerably smaller sample size of the sc-eQTL dataset. Of these associations, 17 were replicated with externalcis-eQTLs and demonstrated colocalization with ASCVD GWAS signals. Notably, genetically proxied expression ofLIPAin monocytes was associated with coronary artery disease, large artery atherosclerotic stroke, and subclinical atherosclerosis traits. These findings were confirmed in a phenome-wide association study without evidence of associations with unexpected clinical outcomes. Single-cell RNA sequencing and immunohistochemistry of human carotid plaques revealed highLIPAexpression in plaque macrophages. Our pipeline provides a solution for the discovery of cell-specific expression patterns that drive genetic predisposition to human disease, potentially impacting target selection for cell-tailored therapeutics.
Association of cumulative exposure to triglyceride and remnant cholesterol with the risk of cardiovascular disease in hypertensive patients with target LDL-C
Authors: Guo Shuang , Wang Chi , Hu Taoyu , Lan Lihua , Ge Zhen , Huang Jianxiang , Chen Shuohua , Wu Shouling , Xue Hao
Published: December 2024

Background

The associations of cumulative exposure to triglycerides (cumTG) and remnant cholesterol (cumRC) with cardiovascular disease (CVD) risk in patients with optimal low-density lipoprotein cholesterol (LDL-C) levels remain uncertain. We aimed to explore the relationship between cumTG and cumRC and the risk of CVD in hypertensive patients with target LDL-C.

Methods

A total of 12,086 hypertensive participants with target LDL-C level who completed three health examinations from 2006 to 2010 were enrolled and followed until December 31, 2022. The cumulative burden was derived by multiplying the average level with the interval between two consecutive assessments. The primary outcome included a composite of CVD events (myocardial infarction, ischemic stroke, and hemorrhage stroke). Participants were divided into 4 groups based on the median values of cumTG and cumRC to assess their joint associations. Cox proportional hazard models were used to calculate the hazard ratio (HR) and 95% confidence intervals (CI) between the cumulative burden and CVD risk.

Results

During a median follow-up of 11.95 years, 1,392 participants developed CVD. After multivariable adjustment, compared to the low cumTG/low cumRC group, both the high cumTG/high cumRC group (HR 1.43, 95% CI 1.24‒1.64) and the low cumTG/high cumRC group (HR 1.26, 95% CI 1.07‒1.49), but not the high cumTG/low cumRC group (HR 1.01, 95% CI 0.84‒1.20), were associated with higher risk of CVD.

Conclusions

In hypertensive patients who met the target level of LDL-C, the cumulative burden of RC was a risk factor for CVD and exhibited a stronger association with CVD risk compared to cumulative triglycerides burden.
AI-based Detection of Central Retinal Artery Occlusion within 4.5 hours on Standard Fundus Photographs
Authors: Gungor Ayse , Sarbout Ilias , Gilbert Aubrey L. , Hamann Steffen , Lebranchu Pierre , Hobeanu Cristina , Gohier Philippe , Vignal-Clermont Catherine , Dumitrascu Oana M. , Cohen Salomon-Yves , Lagrèze Wolf A. , Feltgen Nicolas , van der Heide Frank , Lamirel Cédric , Jonas Jost B. , Obadia Michael , Racoceanu Daniel , Milea Dan
Published: December 2024

Background

Prompt diagnosis of acute central retinal artery occlusion (CRAO) is crucial for therapeutic management and secondary prevention of associated neurological co-morbidities. However, most stroke centers lack on-site ophthalmic expertise prior to considering fibrinolytic treatments. We aimed to develop, train, and test a deep learning system (DLS) able to accurately detect hyper-acute CRAO on retinal color fundus photographs, during the critical treatment window of 4.5 hours after visual loss. We also evaluated the diagnostic performance of the DLS within 24 hours after visual loss, aiming to improve secondary prevention of stroke after CRAO.

Methods

Our retrospective, multicenter, multiethnic study included 1,322 color fundus photographs from 771 patients with various causes of acute visual loss, including CRAO, central retinal vein occlusion, non-arteritic anterior ischemic optic neuropathy, and healthy controls. Photographs were collected from 9 expert neuro-ophthalmology centers in 6 countries, including 3 randomized clinical trials. Training was performed on 1,039 photographs (517 patients), followed by testing on two datasets to discriminate CRAO cases at (i) hyper-acute stage (54 photographs, 54 patients) and (ii) within 24 hours after visual loss (110 photographs, 109 patients).

Results

The DLS achieved an area under the receiver operating characteristic curve (AUC) of 0.96 (95% confidence interval [CI], 0.95-0.98), a sensitivity of 92.6% (95% CI, 87.0-98.0), and a specificity of 85.0% (95% CI, 81.8-92.8) for detecting CRAO at hyper-acute stage, with similar results for CRAO diagnosis within 24 hours. The DLS outperformed neurologists on a subset of testing dataset at hyper-acute stage (120 photographs from 120 patients).

Conclusions

A DLS can accurately detect hyper-acute CRAO on retinal photographs within a time-window compatible with urgent fibrinolysis. Delayed diagnosis (24h) did not alter the ability of the DLS to accurately identify CRAO. If further validated, such systems could improve patient selection for fibrinolytic trials and optimize secondary stroke prevention.

Clinical Trial Registration:URL:https://www.clinicaltrials.gov; Unique identifier:NCT06390579.
SpaceExpress: a method for comparative spatial transcriptomics based on intrinsic coordinate systems of tissues
Authors: Kim Yeojin , Ojha Abhishek , Schrader Alex , Lee Juyeon , Wu Zijun , Traniello Ian M , Robinson Gene E , Han Hee Sun , Zhao Sihai D , Sinha Saurabh
Published: December 2024

Spatial transcriptomics (ST) technologies have enabled new explorations into the spatial organization of tissues and their functional implications. However, one of the most fundamental analyses – comparative analysis of spatial gene expression across phenotypes – remains a formidable challenge. We introduce SpaceExpress, a novel statistical tool for detecting phenotype-associated changes in spatial expression patterns. SpaceExpress employs a neural network to embed multiple ST samples in a common latent space, enabling robust cross-sample comparisons despite structural and technical variations. It then uses spline regression to test differential spatial expression of genes between conditions, with rigorous false discovery control and handling of multiple replicates per condition. It includes visualization tools to help interpret spatial pattern differences. We demonstrate the tool’s effectiveness on synthetic and real ST datasets, revealing mechanistic insights into behavior-related neurogenomic changes in honey bees and mice. Our work extends the highly influential paradigm of differential gene expression analysis to spatial omics.
Modification of the microstructure of the CERN- CLEAR-VHEE beam at the picosecond scale modifies ZFE morphogenesis but has no impact on hydrogen peroxide production
Authors: Kacem Houda , Kunz Louis , Korysko Pierre , Ollivier Jonathan , Tsoutsou Pelagia , Martinotti Adrien , Rieker Vilde , Bateman Joseph , Farabolini Wilfrid , Baldacchino Gérard , Loo Billy W. , Limoli Charles L. , Dosanjh Manjit , Corsini Roberto , Vozenin Marie-Catherine
Published: December 2024

FLASH has emerged as a significant breakthrough for the future of radiation oncology, as it reduces complications while preserving the tumor killing efficacy. To define the beam parameters for future clinical translation, Very High Energy Electrons (VHEE) delivered at CLEAR and able to reach deep seated tumors were used in conjunction with a FLASH-validated Intermediate Energy Electron (IIE) beam and a 160-225 keV X-ray beam, collectively able to deliver dose rates spanning from 1 Gy/min to 1011Gy/s. High-throughput chemical assays were used to investigate radiochemical effects of FLASH, while zebrafish embryos served as a model to evaluate its impact on biological outcomes and morphogenesis. This study is the first comprehensive exploration investigating the impact of a large range of dose rates and various temporal parameters from early physico-chemical events to a complex biological system. Data derived at CLEAR revealed that the intensity of the bunch is a critical factor for observing the sparing effect of FLASH and uncovered an unforeseen biological response when electrons are delivered over the picosecond timescale. Present data also suggests that scanning with high intensity beamlets will be optimal for the future clinical translation of FLASH.

Highlights

To investigate the physics parameters required to trigger the FLASH sparing effect, CLEAR/VHEE/CERN beam macro/microstructure was varied. We show that delivery at the picosecond scale:

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reduces alteration in the morphogenesis of zebrafish embryos, but

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has no impact on secondary hydrogen peroxide production,

Graphical abstract