bluuebunny/crossref_metadata_2025_split huggingface dataset:
Remote-Controlled Wireless Bioelectronics for Fluoxetine Therapy to Promote Wound Healing in a Porcine Model
Authors: Li Houpu , Asefifeyzabadi Narges , Schorger Kaelan , Baniya Prabhat , Tebyani Maryam , Barbee Alexie , Yang Hsin-ya , Hee Wan Shen , Gallegos Anthony , Zhu Kan , Recendez Cynthia , Luka George , Kim Sujung , Devarajan Koushik , Nguyen Tiffany , Figuerres Sydnie , Franco Celeste , Aslankoohi Elham , Zhao Min , Isseroff Roslyn Rivkah , Teodorescu Mircea , Rolandi Marco 
Published: January 2025

AbstractWound healing presents a significant challenge in biomedical science, requiring precise therapeutic delivery and real-time monitoring. Bioelectronic systems offer a promising solution but remain largely unexplored for wound care, particularly in large animal models that reflect human healing dynamics. This study introduces a remote controlled wireless bioelectronic platform equipped with an iontophoretic pump to deliver fluoxetine, a selective serotonin reuptake inhibitor that promotes wound repair. In vitro and ex-vivo testing validated efficient on demand fluoxetine delivery. In vivo experiments in a porcine wound model demonstrated clear therapeutic efficacy over 3-day and 7-day periods. The system enhanced healing outcomes, increasing re-epithelialization by 37% (H&E staining), reducing the M1/M2 macrophage ratio by 33%, and stimulating neuronal growth at the wound site. This bioelectronic platform delivers fluoxetine in a controlled, remotely-controlled manner while allowing for wound direct wound imaging that can be used to monitor wound healing progress. Additionally, it allows precise dose and temporal delivery of treatment to enhance the outcome of future large animal wound healing studies.
An integrated and scalable rodent cage system enabling continuous computer vision-based behavioral analysis and AI-enhanced digital biomarker development
Authors: Robertson Timothy L. , Ellis Michael , Bratcher-Petersen Natalie , Ruidiaz Manuel E. , Harada Kevin , Toburen Debra , Oberhauser Juan Pablo , Grzenda Daniel , Peltier Nicole E. , Raza Madison , Benway Jan , Kiros Jamie , Kumar Vivek 
Published: January 2025

1AbstractHome cage monitoring enables continuous observation of animals in familiar environments. It has large utility in preclinical testing, mechanistic studies, animal husbandry, and the general practice of the Replacement, Reduction, Refinement (3R) principles. Despite its acknowledged utility, the broad adoption of home cage monitoring has not been broadly adopted. This is mainly due to the complexity of the tasks that must be solved to have a successful system that includes hardware and sensor development, data management, machine vision expertise, behavioral expertise, support, and user training. Here, we describe the Digital In Vivo System (DIV Sys), a modern end-to-end system for video-based rodent home cage monitoring. The DIV Sys consists of a cloud-based study design, monitoring, display, and visualization app (DIV App), local hardware for data acquisition cages (DAX), a machine learning model for tracking mice (mHydraNet) optimized for speed and accuracy, a study display and visualization app, and an advanced behavior quantification workbench (DIV Data). The platform seamlessly manages terabytes of video data in the cloud and is built around enterprise-level security and data standards. Collaborative tools enable teams across geographical locations to work together. As a demonstration of its utility, we used DIV Sys to analyze over a century of mouse videos across multiple geographic locations. We also characterized home cage behavior of 8 mouse strains and carried out customized video analysis. Together, we present a scalable home cage monitoring system for advanced behavior quantification for the rodent research community.
Detection and quantification of hepatitis A virus titers from wastewater in South Africa and comparison with clinical data from the National Surveillance Database
Authors: Subramoney Kathleen , Gwala Sipho , Phalane Emmanuel , Macheke Mokgaetji , Singh Natasha , Mangena Thabo , Ndlovu Nkosenhle , Msomi Nosihle , Maposa Sibonginkosi , Sankar Chenoa , Els Fiona , Ntuli Phindile , Motloung Mantshali , Mabasa Victor , McCarthy Kerrigan , Yousif Mukhlid 
Published: January 2025

AbstractWastewater surveillance is useful for monitoring the prevalence of hepatitis A virus (HAV). We developed and optimized HAV detection and quantification methods for wastewater samples, and applied them to samples collected through a national wastewater surveillance program. Previously identified 5’-untranslated region-targeting primers and probes were used to develop the assay. Serial dilutions of HAV-positive clinical samples were used to validate and determine limits of quantification (LOQ). Retrospective testing of weekly wastewater samples collected through the SARS-CoV-2 wastewater surveillance program at 26 sites in Gauteng (August 2021 to March 2024) were undertaken using ultrafiltration-based concentration, and nucleic acids were extracted using the KingFisher Flex purification system with a wastewater isolation kit. A digital PCR assay was used for HAV detection and quantification (as genome copies/μL). Clinical data from the Surveillance Database Warehouse of the National Health Laboratory Service were compared with wastewater data, epidemiological week-wise and district-wise, to determine correlations between the datasets. Based on the validation results, one partition on the digital PCR (dPCR) platform was equivalent to an LOQ of 0.4 genome copies/μL. In total, 2013 wastewater samples were tested, of which 349 were positive for HAV (17.3%), wherein the majority (304, 87.1%) had the lowest HAV concentration (2.0-2.7 gc/μL, 1-5 partitions), followed by 20 samples (5.7%) with concentrations of 2.8-3.0 gc/μL (6-10 partitions). HAV was detected in 17.1% (241/1170) of the Gauteng samples, and a 26.1% correlation between anti-HAV IgM in clinical samples and HAV in wastewater samples was detected. We successfully developed and optimized a dPCR method to detect and quantify HAV in wastewater samples, and determined its LOQ. Further analysis is required to compare the wastewater data with clinical surveillance data to facilitate appropriate interpretation of the results.
DifferentiatingPeromyscus leucopusbone marrow-derived macrophages for characterization of responses toBorrelia burgdorferiand lipopolysaccharide
Authors: Wells Christopher C. , Petnicki-Ocwieja Tanja , Tan Shumin , Bunnell Stephen C. , Telford Sam R. , Hu Linden T. , Bourgeois Jeffrey S. 
Published: January 2025

AbstractCurrently, most tools utilized in host-pathogen interaction studies depend on the use of human or mouse (Mus musculus) cells and tissues. While these species have led to countless breakthroughs in our understanding of infectious disease, there are undoubtably important biological processes that are missed by limiting studies to these two vertebrate species. For instance, it is well-established that a common North American deermouse,Peromyscus leucopus, has unique interactions with microbes, which likely shape its ability to serve as a critical reservoir for numerous zoonotic pathogens, including a Lyme disease spirochete,Borrelia burgdorferi. In this work, we expand the immunological toolkit to studyP. leucopusbiology by performing the first differentiation of deermouse bone marrow to macrophages usingP. leucopusM-CSF producing HEK293T cells. We find thatP. leucopusBMDMs generated through this method behave broadly very similarly to C57BL/6J macrophages generated with L-929 supernatant, though RNA sequencing revealed modest differences in transcriptomic responses toB. burgdorferiand lipopolysaccharide. In particular, differences inIl10induction and caspase expression were observed between the species.
Role of the clathrin adaptor AP-1 in cell wall integrity and virulence factor secretion in the plant pathogen Botrytis cinerea
Authors: Calvar Glen , Hamandjian Adrien , Crumière Mélanie , Dupuy Jean-William , Moriscot Christine , Gallet Benoit , Gillet François-Xavier , de Vallée Amélie , Rascle Christine , Choquer Mathias , Bruel Christophe , Poussereau Nathalie 
Published: January 2025

AbstractIn filamentous fungi, the secretory pathway plays a key role in polarized growth through the dlivery of vesicles carrying enzymes and components necessary to cell wall synthesis and fungal nutrition. In pathogenic species, it moreover supports the delivery of virulence factors. In metazoa and yeast, the formation of several secretory vesicles occurs at the Golgi apparatus and endosomes through a complex and partially characterized machinery involving clathrin and adaptor proteins such as AP-1. Data on the molecular mechanisms controlling this process are still scarce in filamentous fungi. Using a mutant under-expressing the β-subunit of the heterotetrameric AP-1 clathrin adaptor complex, we investigated the importance of intracellular vesicle trafficking in the phytopathogenic fungusBotrytis cinerea. The mutant exhibits pleiotropic developmental defects, an abnormality in cell wall integrity associated with a mislocalization of the plasma-membrane chitine synthase BcCHSIIIa. Moreover, the AP-1 mutant is affected in the secretion of hydrolytic enzymes and displays a severe defect in pathogenicity. This study confirms the importance of the AP1/clathrin machinery in the secretory pathway ofB. cinerea.
Kun-peng: an ultra-memory-efficient, fast, and accurate pan-domain taxonomic classifier for all
Authors: Chen Qiong , Zhang Boliang , Peng Chen , Huang Jiajun , Shen Xiaotao , Jiang Chao 
Published: January 2025

AbstractComprehensive metagenomic sequence classification of diverse environmental samples faces significant computing memory challenges due to exponentially expanding genome databases. Here, we present Kun-peng, featuring a unique ordered 4GB block database design for ultra-efficient resource management, faster processing, and higher accuracy. When benchmarked on mock communities (Amos HiLo, Mixed, and NIST) against Kraken2, Centrifuge, and Sylph. Kun-peng matched Sylph, achieving the highest precision and lowest false-positive rates while demonstrating superior time and memory efficiency among all tested tools. Furthermore, Kun-peng’s efficient database architecture enables the practical utilization of large-scale reference databases that were previously computationally prohibitive. In comprehensive testing across 586 air, water, soil, and human metagenomic samples using an expansive pan-domain database (204,477 genomes, 4.3TB), Kun-peng classified 69.78-94.29% of reads, achieving 38-43% higher classification rates than Kraken2 with the standard database. Unexpectedly, Sylph failed to classify any reads in air samples and left > 99.85% of reads unclassified in water and soil samples. In terms of computational efficiency, Kun-peng processed each sample in 0.2∼11.2 minutes using only 4.0∼35.4GB peak memory. Remarkably, these processing times were comparable to Kraken2 using the standard database (81GB, 5% of the pan-domain database). Memory-wise, Kun-peng required only 35.4GB peak memory with the pan-domain database, representing a 473-fold reduction compared to Kraken2. When compared to Sylph, Kun-peng processes samples up to 46.3 times faster while using up to 20.6 times less memory. Overall, Kun-peng offers an ultra-memory-efficient, fast, and accurate solution for pan-domain metagenomic classifications.
Frequency-tagged fMRI: A platform for fine-grained spatiotemporal analysis of cortical function
Authors: Ngo Geoffrey N. , Rafeh Reebal W. , Muller Lyle E. , Khan Ali R. , Menon Ravi S. , Schmitz Taylor W. , Mur Marieke 
Published: January 2025

AbstractFrequency tagging with functional MRI (ft-fMRI) enables precise mapping of neural dynamics by synchronizing oscillatory stimuli to stimulus-driven blood-oxygen-level-dependent (BOLD) responses. We developed and validated a dual-frequency tagging protocol to dissociate fundamental, multiplexed, and nonlinear intermodulation frequency responses across the human visual cortex at high spatial resolution. Using 3T and 7T fMRI, we reliably detected frequency-tagged BOLD responses at the level of individual vertices, revealing fine-grained cortical topographies and robust temporal synchronization to driving frequencies. Multiplexed responses, encoding multiple frequencies simultaneously, and nonlinear intermodulation components, were spatially dissociable and exhibited reproducible dynamics within and across experimental sessions. These findings establish ft-fMRI as a powerful tool for investigating fine-grained cortical computations, previously inaccessible to traditional fMRI. By bridging the spatiotemporal resolution gap between electrophysiology and fMRI, ft-fMRI provides a versatile platform for studying perception, attention, and multisensory integration in health and disease.
Retinotopic mapping data permit accurate matching of participants across different datasets
Authors: Schwarzkopf D. Samuel , Morgan Catherine A. , Roberts Reece P. , Dakin Steven C. 
Published: January 2025

AbstractPublic sharing of neuroimaging data is becoming increasingly common for the advancement and validation of scientific research. However, this sharing poses challenges regarding privacy and data safety, and associated questions about the ownership of research data. Here we show that a simple pattern correlation algorithm can match nominally deidentified participants across two separate functional magnetic resonance imaging (fMRI) experiments. This re-identification procedure is effective despite functional maps being spatially warped to a common template brain. This work highlights the need for appropriate safeguards against possible misuse of shared neuroimaging data.
A Deep Learning Approach for Culture-Free Bacterial Meningitis Diagnosis and ICU Outcome Prediction
Authors: Chen Rui , Cai Yu , Zhang Sitong , Huo Zirong , Song Mingming , Li Wenqing , Yang Dongyan , Zhang Xi 
Published: January 2025

AbstractBackgroundCerebrospinal fluid (CSF) culture is essential for diagnosing neuroinfectious diseases such as meningitis, where clinical symptoms alone cannot reliably confirm the diagnosis or differentiate bacterial from non-bacterial causes. However, traditional CSF cultures are time-consuming and often lack sensitivity, particularly after antibiotic treatment. This study applies machine learning to expedite diagnosis and enhance the accuracy of outcome predictions for patients with suspected neuroinfectious diseases.MethodsTraining and validation datasets were derived from the MIMIC-III and MIMIC-IV databases, respectively, focusing on patients undergoing CSF bacterial culture. CNN, FCN, and RF classifiers were trained using integrated test results and clinical data to predict CSF culture outcomes. CSF culture result labels were redefined based on clinical guidelines for bacterial meningitis diagnosis to address false negatives caused by prior antibiotic treatment. Unstructured text data were encoded using BioBERT embeddings, combined with structured laboratory data, and processed through CNN, FCN, or LSTM layers to develop multimodal neural networks for predicting clinical outcomes. Class imbalance was mitigated, and text data sources were optimized for interchangeability.ResultsFor CSF culture diagnostic predictions, 9261 cases were analyzed, including 245 initial culture-positive and 9016 culture-negative results. Label correction increased the positive cases to 404, with 8857 negatives. The FCN model showed the best performance post-label correction, achieving an AUC of 0.891, accuracy of 0.867, sensitivity of 0.833, and specificity of 0.868. In survival prediction analysis (5795 cases: 5500 survivors, 295 in-hospital deaths), the optimized multimodal neural network with CNN layers achieved an AUC of 0.933, accuracy of 0.850, sensitivity of 0.847, and specificity of 0.850. Models trained without text data showed diminished performance. Independent validation datasets confirmed the model’s robustness, yielding comparable results.ConclusionsThe multimodal machine learning models demonstrated strong efficacy in predicting CSF culture outcomes, supporting the diagnosis of bacterial meningitis, and in forecasting ICU survival outcomes. Integrating these models into a clinical decision support system could empower ICU clinicians with timely, data-driven insights, enabling culture-independent diagnostics and enhancing patient management.
Silaffins-Driven Genetic Engineering of Diatom Cell Walls: Insight into Biosilica Morphology and Nanomaterial Design
Authors: Qiao Tengsheng , Wang Lulu , Zhao Yan , Li Yun , Yang Guanpin , Zhu Baohua , Pan Kehou 
Published: January 2025

AbstractDiatoms synthesize silica cell walls (frustules) with genetically encoded morphologies, ranging from nanopatterns to micropatterns, that far exceed current synthetic chemistry. Silaffins, a family of phosphoproteins undergoing complex post-translational modifications, have been isolated from frustules and shown to facilitate and regulate biosilica formationin vitrowith long-chain polyamines. However, their particular role in frustule morphogenesis and functionality remains unclear. In this study, functions of two representativesilaffins,TpSil1andTpSil3, were investigated in the model organismThalassiosira pseudonanausing gene overexpression and CRISPR/Cas9-mediated knockout approaches. Due to high sequence homology,TpSil2was concurrently disrupted inTpSil1knockout strains, while the homozygous knockout ofTpSil3proved to be lethal. Quantitative morphological analysis revealed distinct yet complementary roles: TpSil3 governs both microscale overall size and mesoscale features, including macropore (fultoportula) density and mesopore (cribrum pore) pattern, whereas TpSil1/2 exclusively contribute to macropore morphogenesis and mesopore density. Overexpression ofsilaffinsincreased silica deposition, while knockouts exhibited reduced silicification but enhanced cell growth and photosynthetic efficiency. Furthermore, these genetic modifications significantly influenced the physicochemical and optical properties of bulk frustules, potentially enhancing the hemostatic, catalytic and photonic performances, thereby positioning them as versatile candidates for a wide range of biotechnological and industrial applications. Collectively, our findings elucidate the distinct roles ofTpSil1/2andTpSil3in diatom physiology and frustule morphology, highlighting a promising pathway for engineering nanostructured silica materials with tailored properties through synthetic biology.
RGB color indices as proxy for symbiont cell density and chlorophyll content during coral bleaching
Authors: Ferrara Erik Francesco , Bauer Lavinia , Puntin Giulia , Bautz Friederike , Celayir Sibel , Do Marie-Sa , Eck Frederik , Heider Melissa , Wissel Pia , Arnold Angelina , Wilke Thomas , Reichert Jessica , Ziegler Maren 
Published: January 2025

AbstractCoral bleaching, the breakdown of the symbiosis between the coral host and endosymbiotic microalgae, is the main cause of widespread coral reef degradation. Current methods for assessing coral health based on visual appearance, such as the use of color reference cards, are limited by subjective human color perception and low resolution. Digital photography with RGB (Red, Green, Blue) color channel analyses offers a fast, non-invasive, and standardized alternative to estimate physiological parameters. However, the link between coral color and physiological parameters during bleaching may vary depending on the type of stressor. While such approaches are extensively used in plant studies, their application in estimating Symbiodiniaceae cell density and chlorophyll content in corals requires further attention. In this study, we analyzed the correlation between Symbiodiniaceae cell density and chlorophyll content across three coral species (Acropora muricata,Pocillopora verrucosa,andStylophora pistillata) with 19 color indices derived from the RGB channels currently established as predictors of chlorophyll content in plants. Corals were exposed to three bleaching conditions (acute short-term and chronic long-term heat stress and menthol bleaching) to identify the best color indices for assessing coral health through image analysis. We found that the Red index had the strongest linear correlation with symbiont cell density and chlorophyll content across species (R2up to 0.97), so that relative changes in this color index can be directly interpreted as corresponding changes in tissue parameters. To train a model that predicts symbiont densities of a distinct sample set using the Red index, we found 10 to 12 samples to be sufficient to achieve an accuracy of > 95 % of the models trained on the full datasets. This research contributes to improved image analysis as a reliable and non-invasive tool for monitoring, by providing guidelines for a systematic use of RGB data to interpret coral health.
Parallel evolution ofLRP2gene mediating telescope-eye and celestial-eye in goldfish
Authors: Li Rongni , Zhang Bo , Sun Yansheng , Li Jingyi 
Published: January 2025

AbstractAfter the intensive artificial selection, the development of celestial-eye in goldfish involves the protuberating and turning upwards of eyeballs, and also degeneration of the retinal. Thus, the celestial-eye goldfish provides an excellent model for both evolutionary and human ocular disease studies. Here, two mapping populations with segregating eye phenotypes in the offspring goldfish were constructed. Though whole genome sequencing using individual samples from the parents and pooled samples from the offspring, and RNA-seq for eyeball samples from pure goldfish lines, a premature stop codon in Exon 38 ofLRP2gene was identified as the top candidate mutation that is responsible for celestial-eye in goldfish. Fatty acid metabolisms and epidermal cells, especially keratocytes related functions were inhibited in the eyeballs of celestial-eye, while inflammatory reactions and extracellular matrix secreting were stimulated. These suggest the dysfunction of cornea in the celestial-eye, and same for retinal, which could be the results of the truncated LRP2 protein. Besides, evidence was provided that not all the goldfish lines share the same causal mutation for celestial-eye, while the same geneLRP2is in charge of the similar phenotypes (celestial-eye and telescope-eye) in goldfish but no shared mutation. Therefore, those mutations and the associated phenotypes exhibit parallel evolutions in molecular level under artificial selections. Overall, the candidate mutation for celestial-eye in goldfish was identified by this study, and further analyses provide insights into the developmental and evolutionary processes of morphological changes in the eyes of goldfish.Author SummaryAs the first domesticated ornamental fish, goldfish is now worldwide spread and has undergone intensively artificial selections for morphological variations. Among them, celestial-eye is one of the most unique traits for goldfish, which consists of enlarged and protuberant eyes while the eyeballs turning upwards and thus suitable for top viewing in pots. In this study, we have identified that a single nucleotide mutation resulting in disrupted function ofLRP2gene, is responsible for the celestial-eye phenotype. Together with our transcriptome analysis, the genetic and cellular mechanisms for celestial-eye in goldfish were reported for the first time, which provides fundamental knowledge for further studies about the development of eyes in fish and also for ophthalmic diseases in humans. In the aspect of evolution, our study and previous studies reported different truncated LRP2 proteins in charge of celestial-eye and telescope-eye, respectively, which are excellent materials to understand the mechanisms of parallel evolution in molecular level, i.e., independent artificial selections resulting in mutations of the same gene.