bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leveraging the Red List of Ecosystems for national action on coral reefs through the Kunming-Montreal Global Biodiversity Framework
Authors: Gudka Mishal , Obura David , Treml Eric , Samoilys Melita , Aboud Swaleh , Osuka Kennedy , Mbugua James , Mwaura Jelvas , Karisa Juliet , Knoester Ewout , Musila Peter , Omar Mohamed , Nicholson Emily 
Published: February 2024

AbstractCountries have committed to conserving and restoring ecosystems after signing the Kunming-Montreal Global Biodiversity Framework (GBF). The IUCN Red List of Ecosystems (RLE) will serve as a headline indicator to track progress of countries towards achieving this goal, and to guide action across the GBF’s targets. Using Kenyan coral reefs, we demonstrate how nations implementing the GBF, can use standardised estimates of ecosystem degradation from RLE assessments to support site-specific management decisions. We undertook a reef-by-reef analysis to evaluate the relative severity of decline of four key ecosystem components over the past 50-years: hard corals, macroalgae, parrotfish and groupers. Using the two benthic indicators, we also calculated standardised estimates of state to identify reef sites which maintain a better condition through time relative to adjacent sites. Over the past 50 years, Kenya’s coral reefs have degraded across all four ecosystem components. At more than half the monitored sites both parrotfish and grouper abundance declined by more than 50%, while coral cover and macroalgae-coral ratio declined by at least 30%. This resulted in a Vulnerable threat status for coral reefs in Kenya based on degradation (under criterion D of the RLE). The temporal trends in coral cover revealed four sites which maintained an above average condition over their monitoring history (15-25 years). The results can guide management actions to contribute to at least nine of the 23 GBF targets. For example, we identified several sites with relatively healthy benthic and fish communities as candidate areas for protection measures under Target 3. We also found that Marine Protected Areas and Locally Managed Marine Areas, which restrict fishing and control gears, had lower declines in groupers compared to unmanaged areas, providing further evidence for their expansion. The RLE has a key role to play in monitoring and meeting the goals and targets of the Global Biodiversity Framework, and our work demonstrates how using the wealth of data within these assessments can inform local-scale ecosystem management and amplify the GBF’s impact.
POMC neurons control fertility through differential signaling of MC4R in Kisspeptin neurons
Authors: Talbi Rajae , Stincic Todd L. , Ferrari Kaitlin , Ji Hae Choi , Walec Karol , Medve Elizabeth , Gerutshang Achi , León Silvia , McCarthy Elizabeth A. , Rønnekleiv Oline K. , Kelly Martin J. , Navarro Víctor M. 
Published: February 2024

AbstractInactivating mutations in the melanocortin 4 receptor (MC4R) gene cause monogenic obesity. Interestingly, female patients also display various degrees of reproductive disorders, in line with the subfertile phenotype of MC4RKO female mice. However, the cellular mechanisms by which MC4R regulates reproduction are unknown. Kiss1 neurons directly stimulate gonadotropin-releasing hormone (GnRH) release through two distinct populations; the Kiss1ARHneurons, controlling GnRH pulses, and the sexually dimorphic Kiss1AVPV/PeNneurons controlling the preovulatory LH surge. Here, we show thatMc4rexpressed in Kiss1 neurons regulates fertility in females.In vivo, deletion ofMc4rfrom Kiss1 neurons in female mice replicates the reproductive impairments of MC4RKO mice without inducing obesity. Conversely, reinsertion ofMc4rin Kiss1 neurons of MC4R null mice restores estrous cyclicity and LH pulsatility without reducing their obese phenotype.In vitro, we dissect the specific action of MC4R on Kiss1ARHvs Kiss1AVPV/PeNneurons and show that MC4R activation excites Kiss1ARHneurons through direct synaptic actions. In contrast, Kiss1AVPV/PeNneurons are normally inhibited by MC4R activation except under elevated estradiol levels, thus facilitating the activation of Kiss1AVPV/PeNneurons to induce the LH surge driving ovulation in females. Our findings demonstrate that POMCARHneurons acting through MC4R, directly regulate reproductive function in females by stimulating the “pulse generator” activity of Kiss1ARHneurons and restricting the activation of Kiss1AVPV/PeNneurons to the time of the estradiol-dependent LH surge, and thus unveil a novel pathway of the metabolic regulation of fertility by the melanocortin system.
PCNA unloading is crucial for the bypass of DNA lesions by homologous recombination
Authors: Arbel-Groissman Matan , Liefshitz Batia , Katz Nir , Kuryachiy Maxim , Kupiec Martin 
Published: February 2024

AbstractThe DNA Damage Tolerance (DDT) mechanisms allow cells to bypass lesions in the DNA during replication. This allows the cells progress normally through the cell cycle in face of abnormalities in their DNA. PCNA, a homotrimeric sliding clamp complex plays a central role in the coordination of various processes during DNA replication, including the choice of mechanism used during DNA damage bypass. Mono-or poly-ubiquitination of PCNA facilitate an error-prone or an error-free bypass mechanism, respectively. In contrast, SUMOylation recruits the Srs2 helicase, which prevents local homologous recombination. The Elg1 RFC-like complex plays an important role in unloading PCNA from the chromatin. We analyse the interaction of mutations that destabilize PCNA with mutations in the Elg1 clamp unloader and the Srs2 helicase. Our results suggest that in addition to its role as a coordinator of bypass mechanisms, the very presence of PCNA on the chromatin prevents homologous recombination, even in the absence of the Srs2 helicase. Thus, PCNA unloading seems to be a pre-requisite for recombinational repair.
Unveiling chemotherapy-induced immune landscape remodeling and metabolic reprogramming in lung adenocarcinoma by scRNA-sequencing
Authors: Huang Yiwei , Wu Gujie , Bi Guoshu , Cheng Lin , Liang Jiaqi , Li Ming , Zhang Huan , Shan Guangyao , Hu Zhengyang , Chen Zhencong , Lin Zongwu , Jiang Wei , Wang Qun , Xi Junjie , Yin Shanye , Zhan Cheng 
Published: February 2024

AbstractBackgroundChemotherapy is widely used to treat lung adenocarcinoma (LUAD) patients comprehensively. Considering the limitations of chemotherapy due to drug resistance and other issues, it is crucial to explore the impact of chemotherapy and immunotherapy on these aspects.Methods and MaterialsTumor samples from nine LUAD patients, of which four only received surgery and five received neoadjuvant chemotherapy, were subjected to scRNA-seq analysis. In vitro and in vivo assays, including flow cytometry, immunofluorescence, Seahorse assay, and tumor xenograft models, were carried out to validate our findings.ResultsA total of 83,622 cells were enrolled for subsequent analyses. The composition of cell types exhibited high heterogeneity across different groups. Functional enrichment analysis revealed that chemotherapy drove significant metabolic reprogramming in tumor cells and macrophages. We identified two subtypes of macrophages: Anti-mac cells (CD45+CD11b+CD86+) and Pro-mac cells (CD45+CD11b+ARG+) and sorted them by flow cytometry. The proportion of Pro-mac cells in lung adenocarcinoma tissues increased significantly after neoadjuvant chemotherapy. Pro-mac cells promote tumor growth and angiogenesis and also suppress tumor immunity. Moreover, through analyzing the remodeling of T and B cells induced by neoadjuvant therapy, we noted that chemotherapy ignited a relatively more robust immune cytotoxic response towards tumor cells.ConclusionOur study demonstrates that chemotherapy induces metabolic reprogramming within the TME of LUAD, particularly affecting the function and composition of immune cells such as macrophages and T cells. We believe our findings will offer insight into the mechanisms of drug resistance and provide novel therapeutic targets for LUAD in the future.
The genetic consequences of historic climate change on the contemporary population structure of a widespread temperate North American songbird
Authors: Cloutier Alison , Chan David Tsz Chung , Poon Emily Shui Kei , Sin Simon Yung Wa 
Published: February 2024

AbstractStudies of widely distributed species can offer insight regarding how past demographic events tied to historic glaciation and ongoing population genetic processes interact to shape contemporaneous patterns of biodiversity at a continental scale. In this study, we used whole-genome resequencing to investigate the current population structure and genetic signatures of past demographic events in the widespread migratory American goldfinch (Spinus tristis). In contrast to the low variation in mitochondrial genomes, a genome-wide panel of >4.5 million single nucleotide polymorphisms (SNPs) strongly supported the existence of eastern and western populations separated by western mountain ranges and additional population structuring within the western clade. Demographic modeling indicated that the eastern and western populations diverged approximately one million years ago, and both populations experienced subsequent population bottlenecks during the last glacial period. Species distribution models showed a severe contraction of suitable habitat for the American goldfinch during this period, with predicted discontinuities that are indicative of multiple, isolated glacial refugia that coincide with present-day population structure. This study highlights the power of genome-level sequencing approaches to deepen our understanding of evolutionary processes in nonmodel wild species and to contribute to efforts assessing how historic demographic events and contemporary factors might influence biodiversity.
Combining radio-telemetry and radar measurements to test optimal foraging in an aerial insectivore bird
Authors: Bloch Itai , Troupin David , Toledo Sivan , Nathan Ran , Sapir Nir 
Published: February 2024

SUMMARYOptimal foraging theory posits that foragers adjust their movements based on prey abundance to optimize food intake. While extensively studied in terrestrial and marine environments, aerial foraging has remained relatively unexplored due to technological limitations. This study, uniquely combining BirdScan-MR1 radar and the ATLAS biotelemetry system, investigates the foraging dynamics of Little Swifts (Apus affinis) in response to insect movements over Israel’s Hula Valley. Insect Movement Traffic Rate (MoTR) substantially varied across days, strongly influencing swift movement. On days with high MoTR, swifts exhibited reduced flight distance, increased colony visit rate, and earlier arrivals at the breeding colony, reflecting a dynamic response to prey availability. However, no significant effects were observed in total foraging duration, flight speed, or daily route length. Notably, as insect abundance increased, inter-individual distances decreased. These findings suggest that Little Swifts optimize their foraging behavior in relation to aerial insect abundance, likely influencing reproductive success and population dynamics. The integration of radar technology and biotelemetry systems provides a unique perspective on the interactions between aerial insectivores and their prey, contributing to a comprehensive understanding of optimal foraging strategies in diverse environments.
Characterisation and comparison of semen microbiota and bacterial load in men with infertility, recurrent miscarriage, or proven fertility
Authors: Mowla Shahriar , Farahani Linda , Tharakan Tharu , Davies Rhianna , Correia Gonçalo D S , Lee Yun S , Kundu Samit , Khanjani Shirin , Sindi Emad , Rai Raj , Regan Lesley , Khalifa Dalia , Henkel Ralf , Minhas Suks , Dhillo Waljit S , Nagi Jara Ben , Bennett Phillip R , MacIntyre David A , Jayasena Channa N 
Published: February 2024

AbstractSeveral studies have associated seminal microbiota abnormalities with male infertility but have yielded differing results owing to their limited sizes or depths of analyses. The semen microbiota during recurrent pregnancy loss (RPL) has not been investigated. Comprehensively assessing the seminal microbiota in men with reproductive disorders could elucidate its potential role in clinical management. We used semen analysis, terminal-deoxynucleotidyl-transferase-mediated-deoxyuridine-triphosphate-nick-end-labelling, Comet DNA fragmentation, luminol ROS chemiluminescence and metataxonomic profiling of semen microbiota by16S rRNA amplicon sequencing in this prospective, cross-section study to investigate composition and bacterial load of seminal bacterial genera and species, semen parameters, reactive oxidative species (ROS), and sperm DNA fragmentation in men with reproductive disorders and proven fathers. 223 men were enrolled included healthy men with proven paternity (n=63), the male partners in a couple encountering RPL (n=46), men with male factor infertility (n=58), and the male partners of couples unexplained infertility (n=56). Rates of high sperm DNA fragmentation, elevated ROS and oligospermia were more prevalent in the study group compared with control. In all groups, semen microbiota clustered into three majorgenera-dominant groups (1, Streptococcus; 2, Prevotella; 3, Lactobacillus and Gardnerella); no species clusters were identified. Group 2 had the highest microbial richness (P<0.001), alpha-diversity (P<0.001), and bacterial load (P<0.0001). Overall bacterial composition or load has not found to associate with semen analysis, ROS or DNA fragmentation. Whilst, global perturbation of the seminal microbiota is not associated with male reproductive disorders, men with unidentified seminalFlavobacteriumare more likely to have abnormal seminal analysis. Future studies may elucidate ifFlavobacteriumreduction has therapeutic potential.
Prior exposure to malaria decreases SARS-CoV-2 mediated mortality in K18-hACE2 mice without influencing viral load in lungs
Authors: Mawatwal Shradha , Mohapatra Amruta , Das Sayani , Ray Aisurya , Mukherjee Ratnadeep , Syed Gulam , Senapati Shantibushan , Ravindran Balachandran 
Published: February 2024

AbstractBackgroundEpidemiological evidence for decreased prevalence and/or mortality due to SARS-CoV-2 infections in countries endemic for malaria have been reported. However, such associational studies in human population are limited by known and several unknown confounding factors. The current study, the first of its kind, was designed to seek experimental evidence to test the hypothesis if prior exposure to Plasmodial infections cross-protect against SARS-CoV-2 challenge infection in a murine model, K-18 human ACE2 transgenic mice.MethodsMice that had recovered fromPlasmodium chabaudiinfection 40 days earlier were challenged with a virulent strain of SARS-CoV-2 and viral load in lungs as well as mortality were scored and compared withK18 hACE2mice that had not experienced prior malaria.ResultsThe viral load in lungs 6 days post challenge were comparable in malaria recovered mice and controls suggesting no significant generation of anti-viral immunity. However, mice with prior malaria exposure were significantly protected against SARS-CoV-2 induced mortality. Significant differences were observed in several host immune responses between the two groups when cytokines, chemokines and transcription factors were quantified in lungs. The plasma levels of several cytokines and chemokines were also significantly different between the two groups.ConclusionThe results of the study suggest that prior exposure to malaria protects mice against viral induced mortality in K18 hACE2 transgenic mice challenged with a virulent isolate of SARS- CoV-2 in the absence of demonstrable host immunity inhibiting viral growth in lungs.
Single-particle track colocalization using CoPixie reveals the impact of cancer-associated POT1 mutations on telomerase-telomere interactions
Authors: Prince Samuel , Maguemoun Kamélia , Ferdebouh Mouna , Querido Emmanuelle , Derumier Amélie , Chartrand Pascal 
Published: February 2024

ABSTRACTSingle-particle imaging and tracking can be combined with colocalization analysis to study the dynamic interactions between macromolecules in living cells. Indeed, single-particle tracking has been extensively used to study protein-DNA interactions and dynamics. Still, identification and quantification of binding events at specific genomic loci remains challenging. Herein we describe CoPixie, a new software that identifies colocalization events between a theoretically unlimited number of imaging channels, including single-particle movies. We employed CoPixie with live cell single-molecule imaging of telomerase and telomeres to test the model that cancer-associated POT1 mutations facilitate telomere accessibility. We show that OB-fold mutants POT1-ΔOB, Y223C, D224N or K90E increase telomere accessibility for telomerase interaction and the cumulative dwell-time of telomerase at telomeres. However, unlike POT1-ΔOB or D224N mutants, the POT1 Y223C and K90E mutations also increase the duration of long-lasting telomerase interactions at telomeres. Our data reveal that telomere elongation in cells expressing cancer-associated POT1 mutants arises from the dual impact of these mutations on telomeres accessibility and telomerase retention at telomeres. CoPixie can be used to explore a variety of questions involving macromolecular interactions in living cells, including between proteins and nucleic acids, from multi-color single-particles tracks.
Ensemble automated approaches for producing high quality herbarium digital records
Authors: Guralnick Robert. P. , LaFrance Raphael , Allen Julie M. , Denslow Michael W. 
Published: February 2024

AbstractOne of the slowest steps in digitizing natural history collections is converting labels associated with specimens into a digital data record usable for collections management and research. Recent work has shown a path for semi-automated approaches that can find labels, OCR them and convert the raw OCR text into digital data records. Here we address how raw OCR can be converted into a digital data record via extraction into standardized Darwin Core fields. We first showcase development of a rule-based approach and compare outcomes with a large language model-based approach, in particular ChatGPT4. We next quantified error rates in a set of OCRed labels, determining omission and commission errors for both approaches and documenting other issues. For example, we find that ChatGPT4 will often create field names that are not Darwin Core compliant. Our results suggest that these approaches each have different limitations. Therefore, we developed an ensemble approach that utilizes outputs from both in order to reduce problems from each individual method. An ensemble method reduces issues with field name heterogeneity and strongly reduces information extraction errors. This suggests that such an ensemble method is likely to have particular value for creating digital data records, even for complicated label content, given that longer labels, though more error prone, are still successfully extracted. While human validation is still much needed to ensure the best possible quality, we showcase working solutions to speed digitization of herbarium specimen labels that are likely usable more broadly for all natural history collection types.
RUDEUS, a machine learning classification system to study DNA-Binding proteins
Authors: Medina-Ortiz David , Cabas-Mora Gabriel , Moya-Barría Iván , Soto-Garcia Nicole , Uribe-Paredes Roberto 
Published: February 2024

AbstractDNA-binding proteins are essential in different biological processes, including DNA replication, transcription, packaging, and chromatin remodelling. Exploring their characteristics and functions has become relevant in diverse scientific domains. Computational biology and bioinformatics have assisted in studying DNA-binding proteins, complementing traditional molecular biology methods. While recent advances in machine learning have enabled the integration of predictive systems with bioinformatic approaches, there still needs to be generalizable pipelines for identifying unknown proteins as DNA-binding and assessing the specific type of DNA strand they recognize. In this work, we introduce RUDEUS, a Python library featuring hierarchical classification models designed to identify DNA-binding proteins and assess the specific interaction type, whether single-stranded or double-stranded. RUDEUS has a versatile pipeline capable of training predictive models, synergizing protein language models with supervised learning algorithms, and integrating Bayesian optimization strategies. The trained models have high performance, achieving a precision rate of 95% for DNA-binding identification and 89% for discerning between single-stranded and doublestranded interactions. RUDEUS includes an exploration tool for evaluating unknown protein sequences, annotating them as DNA-binding, and determining the type of DNA strand they recognize. Moreover, a structural bioinformatic pipeline has been integrated into RUDEUS for validating the identified DNA strand through DNA-protein molecular docking. These comprehensive strategies and straightforward implementation demonstrate comparable performance to high-end models and enhance usability for integration into protein engineering pipelines.
Multi-species numerical validation of an efficient algorithm for auditory brainstem response hearing threshold estimation
Authors: Petersen Erik Alan , Shen Yi 
Published: February 2024

AbstractThe Auditory Brainstem Response (ABR) can be used to evaluate hearing sensitivity of animals who are unable to respond to behavioral tasks. However, typical data collection methods are time consuming; decreasing the measurement time may save resources or allow researchers to spend more time on other tasks. Here, an adaptive algorithm is proposed for efficient estimation of ABR thresholds. The algorithm relies on the online update of the predicted hearing threshold from a Gaussian process model as ABR data are collected using iteratively optimized stimuli. To validate the algorithm, ABR threshold estimation is simulated by adaptively sub-sampling pre-collected ABR datasets for which the stimuli were systematically varied in frequency and level. The simulated experiment is performed on 5 datasets of Mouse (2 different datasets), Budgerigar, Gerbil, and Guinea Pig ABRs collected by different laboratories, with a total of 27 ears. The original datasets contain between 68 and 106 stimuli conditions, while the adaptive algorithm is run up to a total of 20 stimuli conditions. The adaptive algorithm ABR threshold estimate is compared against human rater estimates who view the full ABR dataset. The adaptive algorithm threshold matches the human estimates within 10 dB, averaged over frequency, for 19 out of 27 ears. The adaptive procedure is able to provide threshold estimates that are comparable to the human rater estimated thresholds while reducing the measurement time by a factor of 3 to 5. The standard deviation of threshold estimates from successive runs is smaller than the inter-human rater differences, indicating adequate test/retest reliability.