bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of land use change and elevation on endemic shrub frogs in a biodiversity hotspot
Authors: Lad Himanshu , Gosavi Ninad , Jithin Vijayan , Naniwadekar Rohit 
Published: May 2024

ABSTRACTAgroforestry, often promoted as a sustainable agriculture practice, is rapidly expanding, often at the cost of primary tropical forests. While agroforestry impacts amphibian diversity negatively, its effects on population demography, microhabitat use and body condition are relatively understudied. This information is crucial for determining and promoting amphibian-friendly land use practices. We compared habitats, population densities, microhabitat use, and body condition of two endemic species of shrub frogs (Pseudophilautus amboliandRaorchestes bombayensis) across 1) elevations (low- and high-elevation forests) and 2) land use categories (cashew, rubber, and low-elevation forests) in the northern part of the Western Ghats Biodiversity Hotspot. Using distance sampling, we demonstrated that abundances of the two shrub frog species differed across elevation categories, withPseudophilautusmore common in low-elevation forests andRaorchestesmore prevalent in high-elevation forests. Both species of frogs exhibited extremely skewed, male-biased sex ratios, with three females for 100 males.Pseudophilautushad lower densities and poor recruitment and exhibited altered microhabitat use in cashew plantations compared to low-elevation forests. Although adult malePseudophilautusdensities in rubber were similar to those in low-elevation forests, they exhibited altered microhabitat use and smaller body sizes than in forests, indicating poor body condition. We demonstrate differential impacts of agroforestry types on shrub frogs. We also demonstrate that distance sampling can be a useful tool for population monitoring of shrub frogs, which comprise almost 25% of the anuran diversity in the Western Ghats. Additionally, there is a need to identify the drivers of extremely skewed sex ratios, which make these species vulnerable to population crashes. Considering the recent downlisting of the two focal species to Least Concern, we advocate for their uplisting to at least Near Threatened status in light of their patchy distribution, negative impacts of rapidly expanding agroforestry plantations and extremely skewed sex ratios.
Ancient genomics reveals a genetic continuum with dual structure in the Classic Copan
Authors: Murray Madeleine , Nakamura Seiichi , Fuentes Melvin , Ogawa Masahiro , Cassidy Lara M. , Gakuhari Takashi , Nakagome Shigeki 
Published: May 2024

AbstractCopan was a major capital at the southeasternmost of the Maya civilization, serving as a crossroads connecting Central and South America. In 426/427 CE, the city witnessed the establishment of a royal dynasty, which endured for approximately 400 years. Despite extensive historical and archaeological records, there remains limited information regarding the genetic origins of people who resided in Copan. Here, we present seven Classic Copan genomes including an enigmatic dynastic ruler and his sacrificed companion. Our analysis identifies a high genetic affinity of the Classic Copan with present-day Maya. Both groups exhibit an admixture of Mesoamerican and South American Farmer (SAF) ancestry, with a shift in a dominant component from SAF to Mesoamerican. At the individual level, commoners show a more prominent SAF ancestry, while the royal individual demonstrates nearly equal contributions from two ancestors. These results highlight a dual ancestral structure in this geographic extreme of the Classic Maya state, uncovering a cline of Mesoamerican ancestry across individuals.
Proteomic analysis to classify extracellular vesicles and plasmodesmata in Arabidopsis cell culture supernatants
Authors: Takei Takahito , Asou Teppei , Hamakawa Nobuteru , Tanaka Sho , Noguchi Ryo , Sumiyoshi Kohei , Sueyoshi Kenji , Imami Koshi , Hamada Takahiro 
Published: May 2024

AbstractThe plant apoplast contains diverse proteins. In this study, we analyzed the extracellular vesicle proteome using cell culture supernatants. Unexpectedly, many plasmodesmata proteins were identified in the extracellular vesicle fraction. The comparison between the cell culture EV proteome and the plasmodesmata proteome revealed that EV and plasmodesmata proteins were indistinguishable. Highly sensitive imaging analyses showed that PDLP3-GFP, a representative plasmodesmata marker, was localized to plasmodesmata, but it was also present as small granules in apoplast regions. Next, we attempted to distinguish EV proteins from plasmodesmata proteins. The step-wise density gradient ultracentrifugation and clustering analysis separated EV protein clusters (represented by tetraspanins and membrane trafficking proteins) from plasmodesmata clusters (represented by PDLPs and PDCBs). These results provide the basis for future explorations of plant plasmodesmata and EVs.
Linking single-cell transcriptomes with secretion using secretion-encoded single-cell sequencing (SEC-seq)
Authors: Langerman Justin , Baghdasarian Sevana , Cheng Rene Yu-Hong , James Richard G. , Plath Kathrin , Carlo Dino Di 
Published: May 2024

AbstractCells secrete numerous proteins and other biomolecules into their surroundings to achieve critical functions – from communicating with other cells to blocking the activity of pathogens. Secretion of cytokines, growth factors, extracellular vesicles, and even recombinant biologic drugs defines the therapeutic potency of many cell therapies. However, gene expression states that drive specific secretory phenotypes are largely unknown. We provide a protocol that enables linking the Secretion amount of a target protein EnCoded (SEC) by thousands of single cells with transcriptional sequencing (seq). SEC-seq leverages microscale hydrogel particles called Nanovials to isolate cells and capture their secretions in close proximity, oligonucleotide-labeled antibodies to tag secretions on Nanovials, and flow cytometry and single-cell RNA-sequencing platforms for readout. Cells on Nanovials can be sorted based on viability, secretion amount, or other surface markers without fixation or permeabilization, and cell and secretion-containing Nanovials are directly introduced into microfluidic droplets-in-oil emulsions for single-cell barcoding of cell transcriptomes and secretions. We have used SEC-seq to link T-cell receptor sequences to the relative amount of associated cytokine secretions, surface marker gene expression with a highly secreting and potential regenerative population of mesenchymal stromal cells, and the transcriptome with high immunoglobulin secretion from plasma cells. Nanovial modification and cell loading takes under 4 hours, and once the desired incubation time is over, staining, cell sorting, and emulsion generation for scRNA-seq can also be completed in under 4 hours. By linking gene expression and secretory strength, SEC-seq can expand our understanding of cell secretion, how it is regulated, and how it can be engineered to make better therapies.
Two operational modes of atomic force microscopy reveal similar mechanical properties for homologous regions of dystrophin and utrophin
Authors: Hua Cailong , Slick Rebecca A. , Vavra Joseph , Muretta Joseph M. , Ervasti James M. , Salapaka Murti V. 
Published: May 2024

Duchenne muscular dystrophy (DMD) is a lethal muscle disease caused by the absence of the protein dystrophin. Dystrophin is hypothesized to work as a molecular shock absorber that limits myofiber membrane damage when undergoing reversible unfolding upon muscle stretching and contraction. Utrophin is a dystrophin homologue that is under investigation as a protein replacement therapy for DMD. However, it remains uncertain whether utrophin can mechanically substitute for dystrophin. Here, we compared the mechanical properties of homologous utrophin and dystrophin fragments encoding the N terminus through spectrin repeat 3 (UtrN-R3, DysN-R3) using two operational modes of atomic force microscopy (AFM), constant speed and constant force. Our comprehensive data, including the statistics of force magnitude at which the folded domains unfold in constant speed mode and the time of unfolding statistics in constant force mode, show consistent results. We recover parameters of the energy landscape of the domains and conducted Monte Carlo simulations which corroborate the conclusions drawn from experimental data. Our results confirm that UtrN-R3 expressed in bacteria exhibits significantly lower mechanical stiffness compared to insect UtrN-R3, while the mechanical stiffness of the homologous region of dystrophin (DysN-R3) is intermediate between bacterial and insect UtrN-R3, showing greater similarity to bacterial UtrN-R3.SignificanceDuchenne muscular dystrophy (DMD) is a severe muscle wasting disorder caused by mutations in DMD gene encoding dystrophin. Utrophin, a fetal homologue of dystrophin, is under active investigation as a dystrophin replacement therapy for DMD. However, it is still unknown if it can substitute dystrophin mechanically. Here, we report mechanical properties of both utrophin and dystrophin fragments encoding the N terminus through spectrin repeat 3 (UtrN-R3, DysN-R3) using atomic force microscope (AFM) through two operational modes, constant speed and constant force. Our data, consistent across both modes, confirm that UtrN-R3 expressed in bacteria exhibits significantly lower mechanical stiffness than insect UtrN-R3. Additionally, bacterial DysN-R3 lies between bacterial and insect UtrN-R3 in terms of mechanical properties, leaning closer to bacterial UtrN-R3.
RoCK and ROI: Single-cell transcriptomics with multiplexed enrichment of selected transcripts and region-specific sequencing
Authors: Moro Giulia , Mallona Izaskun , Maillard Joël , Brügger Michael David , Fazilaty Hassan , Szabo Quentin , Valenta Tomas , Handler Kristina , Kerlin Fiona , Moor Andreas E. , Zinzen Robert , Robinson Mark D. , Brunner Erich , Basler Konrad 
Published: May 2024

AbstractVarious tools have been developed to reliably identify, trace and analyze single cells in complex tissues. In recent years, these technologies have been combined with transcriptomic profiling approaches to explore molecular mechanisms that drive development, health, and disease. However, current methods still fall short of profiling single cell transcriptomes comprehensively, with one major challenge being high non-detection rates of specific transcripts and transcript regions. Such information is often crucial to understanding the biology of cells or tissues and includes lowly expressed transcripts, sequence variations and exon junctions. Here, we developed a scRNAseq workflow, RoCK and ROI (Robust Capture of Key transcripts and Regions Of Interest), that tackles these limitations. RoCKseq uses targeted capture to enrich for key transcripts, thereby supporting the detection and identification of cell types and complex phenotypes in scRNAseq experiments. ROIseq directs a subset of reads to a specific region of interest via selective priming to ensure detection. Importantly, RoCK and ROI guarantees efficient retrieval of specific sequence information without compromising overall single cell transcriptome information and our workflow is supported by a novel bioinformatics pipeline to analyze the multimodal information. RoCK and ROI represents a significant enhancement over non-targeted single cell sequencing, particularly when cell categorization depends on transcripts that are missed in standard scRNAseq experiments. In addition, it also allows exploration of biological questions that require assessment of specific sequence elements along the targets to be addressed.
History of recurrent short and long-term coral bleaching events in Indian coral reefs: a systematic review of contrasting bleaching patterns, lessons learned, and future directions
Authors: Thangadurai Thinesh , De Kalyan , Murugesan Sobana , Sivagurunathan P , Peter Riana , Ramasamy Pasiyappazham , Selvin Joseph , Jose Polpass Arul , Bellantuono Anthony 
Published: May 2024

AbstractClimate change has intensified coral bleaching events, leading to widespread coral mortality and threatening the coral reef survival worldwide. However, species susceptibility patterns to bleaching differ spatially and temporally, making it crucial to understand bleaching impact and species susceptibility patterns across latitudinal ranges, particularly from understudied locations. We critically reviewed 23 years of bleaching episodes on Indian coral reefs (four major reefs and other patch reefs) reported from 1998 to 2020 to understand the geographical footprint of bleaching patterns, species susceptibility differences, and their impact. We found that all four major Indian reef systems (Gulf of Kachchh, Gulf of Mannar, Lakshadweep, and the Andaman Islands) have experienced three major bleaching episodes (1998, 2010, and 2016) and multiple short-term bleaching events. Short-term bleaching events (DHWs> four weeks) created differences in species susceptibility, but the disparity among species diminished to long-term bleaching events (DHWs <4 weeks) in all reef sites.Acropora,Porites,Pocillopora,Montipora,andTurninariain the Gulf of Mannar,Porites,andFaviain the Gulf of Kachchh, andAcroporain the Andaman and Lakshadweep were the most vulnerable genera during all the bleaching events. In terms of recovery,Poritesand other massive forms recovered better than branching forms. Furthermore, species susceptibility pattern analysis (winners vs. losers) to 2016 long-term bleaching events found conflicting results from studies (one-time surveys) in the same area. This result indicates that a one-time survey (survey timing) influences results as bleaching events lengthen, necessitating repeated surveys to determine winners and losers. Although inconsistent data from different study sites makes it difficult to create predictive models, data collected over the past 23 years provides critical insight into coral community susceptibility patterns and bleaching impacts, underscoring the need for systematic, uniform surveys in the future.
Maladaptation in cereal crop landraces following a soot-producing climate catastrophe
Authors: McLaughlin Chloee M. , Shi Yuning , Viswanathan Vishnu , Sawers Ruairidh , Kemanian Armen R. , Lasky Jesse R. 
Published: May 2024

AbstractAerosol-producing global catastrophes such as nuclear war, super-volcano eruption, or asteroid strike, although rare, pose a serious threat to human survival. Light-absorbing aerosols would sharply reduce temperature and solar radiation reaching the earth’s surface, decreasing crop productivity including for locally adapted traditional crop varieties, i.e. landraces. Here, we test post-catastrophic climate impacts on barley, maize, rice, and sorghum, four crops with extensive landrace cultivation, under a range of nuclear war scenarios that differ in the amount of black carbon aerosol (soot) injected into the climate model. We used a crop growth model to estimate gradients of environmental stressors that drive local adaptation. We then fit genotype environment associations using high density genomic markers with gradient forest offset (GF offset) methods and predicted maladaptation through time. As a validation, we found that our GF models successfully predicted local adaptation of maize landraces in multiple common gardens across Mexico. We found strong concordance between GF offset and disruptions in climate, and landraces of all tested crop species were predicted to be the most maladapted across space and time where soot-induced climate change was the greatest. We further used our GF models to identify landrace varieties best matched to specific post-catastrophic conditions, indicating potential substitutions for agricultural resilience. We found the best landrace genotype was often far away or in another nation, though countries with more climatic diversity had better within-country substitutions. Our results highlight that a soot-producing catastrophe would result in the global maladaptation of landraces and suggest that current landrace adaptive diversity is insufficient for agricultural resilience in the case of the soot scenarios with the greatest change to climate.
Multiparametric grading of glaucoma severity by histopathology can enable post-mortem substratification of disease state
Authors: Xiang Chuanxi , Raghunathan VijayKrishna , Qiu Yubin , Mehta Manisha , Grosskreutz Cynthia L. , Wilson Christopher W. , Prasanna Ganesh 
Published: May 2024

AbstractNeurodegeneration in glaucoma patients is clinically identified through longitudinal assessment of structure-function changes, including intraocular pressure, cup-to-disc ratios from fundus images, and optical coherence tomography imaging of the retinal nerve fiber layer. Use of human post-mortem ocular tissue for basic research is rising in the glaucoma field, yet there are challenges in assessing disease stage and severity, since tissue donations with informed consent are often unaccompanied by detailed pre-mortem clinical information. Further, the interpretation of disease severity based solely on anatomical and morphological assessments by histology can be affected by differences in death-to-preservation time and tissue processing. These are difficult confounders that cannot be easily controlled. As pathogenesis and molecular mechanisms can vary depending on the stage and severity of glaucoma, there is a need for the field to maximize use of donated tissue to better understand the molecular mechanisms of glaucoma and develop new therapeutic hypotheses. Further, there is a lack of consensus around the molecular RNA and protein markers that can be used to classify glaucoma severity. Here, we describe a multiparametric grading system that combines structural measurements of the retinal nerve fiber layer with linear regression and principal component analyses of molecular markers of retinal ganglion cells and glia (RBPMS, NEFL, IBA1 and GFAP) to stratify post-mortem glaucoma eyes by the severity of disease. Our findings show that a quantitative grading approach can stratify post-mortem glaucoma samples with minimal clinical histories into at least three severity groups and suggest that this type of approach may be useful for researchers aiming to maximize insights derived from eye bank donor tissue.
Harmonising distributed tree inventory datasets across India can fill critical gaps in tropical ecology
Authors: Anujan Krishna , Mohanbabu Neha , Gopal Abhishek , Surendra Akshay , Krishnan Aparna , Jayanth Ankitha , Nair Tanaya , Ongole Shasank , Sankaran Mahesh 
Published: May 2024

AbstractGlobal analyses of tree diversity and function are strongly biased geographically, with poor representation from forests of the Indian subcontinent. Even though data from India - representing two-thirds of the subcontinent and spanning a wide range of tree-based biomes - exists, a barrier to syntheses is the absence of accessible and standardised data. Further, with increasing human footprint across ecosystems, data from Indian landscapes, with their long history of human-nature interactions is a key link to understand the future of tropical forested landscapes. Given the long history of human-nature interactions and high human footprint in the region, accessible and standardized data from the subcontinent can enable understanding the future of tropical landscapes under increasing human footprints globally.Combining literature searches with manual data retrieval, we assembled the INdia Tree Inventory dataset, INvenTree. INvenTree is the largest meta-dataset of peer-reviewed publications (n = 465) from 1991-2023 on geolocated plot-based tree inventories of multispecies communities from Indian ecosystems, in aggregate covering 4653.64 ha and all of its woody biomes.Using INvenTree, we show extensive sampling across tropical moist and dry forests, the dominant ecosystem types in the country. However, most studies have low sampling effort (median sampled area = 2 ha) and data across studies is not openly accessible (73.33 % of studies representing 83.43% of the sampled area), potentially hindering inclusion into regional or global syntheses.Significantly, we show majority authorship from within the country; 82.8% of corresponding authors were from India and 73.33% of the studies had all authors affiliated with Indian institutions. We also identify ecological and conservation sampling priority regions based on forest cover and forest loss and set a blueprint for future sampling efforts in the country.Based on extensive Indian scholarship in forest ecology showcased through the INvenTree dataset, we see opportunity for regional collaboration to create scientific inferences that are larger and scalable, while prioritising data and knowledge equity. Harmonising these existing datasets, and synthesising historic and grey literature, will contribute enormously to understanding the human dimension of tropical ecology as well as informing regional management and conservation.
CoNECo: A Corpus for Named Entity recognition and normalization of protein Complexes
Authors: Nastou Katerina , Koutrouli Mikaela , Pyysalo Sampo , Jensen Lars Juhl 
Published: May 2024

AbstractMotivationDespite significant progress in biomedical information extraction, there is a lack of resources for Named Entity Recognition (NER) and Normalization (NEN) of protein-containing complexes. Current resources inadequately address the recognition of protein-containing complex names across different organisms, underscoring the crucial need for a dedicated corpus.ResultsWe introduce the Complex Named Entity Corpus (CoNECo), an annotated corpus for NER and NEN of complexes. CoNECo comprises 1,621 documents with 2,052 entities, 1,976 of which are normalized to Gene Ontology. We divided the corpus into training, development, and test sets and trained both a transformer-based and dictionary-based tagger on them. Evaluation on the test set demonstrated robust performance, with F1-scores of 73.7% and 61.2%, respectively. Subsequently, we applied the best taggers for comprehensive tagging of the entire openly accessible biomedical literature.AvailabilityAll resources, including the annotated corpus, training data, and code, are available to the community through Zenodohttps://zenodo.org/records/11263147and GitHubhttps://zenodo.org/records/10693653.
Gene2role: a role-based gene embedding method for comparative analysis of signed gene regulatory networks
Authors: Zeng Xin , Liu Shu , Liu Bowen , Zhang Weihang , Xu Wanzhe , Toriumi Fujio , Nakai Kenta 
Published: May 2024

AbstractMotivationUnderstanding the dynamics of gene regulatory networks (GRNs) across various cellular states is crucial for deciphering the underlying mechanisms governing cell behavior and functionality. However, current comparative analytical methods, which often focus on simple topological information such as the degree of genes, are limited in their ability to fully capture the similarities and differences among the complex GRNs.ResultsWe present Gene2role, a gene embedding approach that leverages multi-hop topological information from genes within signed GRNs. Initially, we demonstrated the effectiveness of Gene2role in capturing the intricate topological nuances of genes using GRNs inferred from four distinct data sources. Then, applying Gene2role to integrated GRNs allowed us to identify genes with significant topological changes across cell types or states, offering a fresh perspective beyond traditional differential gene expression analysis. Additionally, we quantified the stability of gene modules between two cellular states by measuring the changes in the gene embeddings within these modules. In conclusion, our method augments the existing toolkit for probing the dynamic regulatory landscape, thereby opening new avenues for understanding gene behavior and interaction patterns across cellular transitions.