bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-throughput biodiversity surveying sheds new light on the brightest of insect taxa
Authors: Iwaszkiewicz-Eggebrecht Ela , Goodsell Robert M. , Bengsson Bengt-Åke , Mutanen Marko , Klinth Mårten , van Dijk Laura , Lukasik Piotr , Miraldo Andreia , Andresson Anders F. , Tack Ayco J. M. , Roslin Tomas , Ronquist Fredrik 
Published: October 2024

AbstractSampling of species-rich taxa followed by DNA metabarcoding is quickly becoming a popular high-throughput method for biodiversity inventories. Unfortunately, we know little about its accuracy and efficiency, as the results mostly pertain to poorly-known organism groups in underexplored environments or regions of the world. Here we ask what an extensive sampling effort based on Malaise trapping and metabarcoding can tell us about the lepidopteran fauna of Sweden – one of the best-understood insect taxa in one of the most-surveyed countries of the world. Specifically, we deployed 197 Malaise traps for a single year across Sweden in a systematic sampling design, then metabarcoded the resulting 4,749 bulk samples, and compared the results to existing data sources. We detected more than half (1,535) of the 2,990 lepidopteran species ever recorded as occurring in Sweden, and 323 species not reported during the sampling period by other data providers. Full-length barcoding of individual specimens confirmed three new species for the country and extensive range extensions for two species. It also corroborated eight genetically distinct COI variants that may represent new species to science, one of which has since been described. Most of the new records are for small and inconspicuous species and poorly surveyed regions, suggesting that they represent previously overlooked components of the fauna. Our findings, corroborated by independent metagenomic analyses, show that DNA metabarcoding can be a highly efficient and accurate method of biodiversity sampling, to the extent that it can generate significant new discoveries even for the most well-known of insect faunas.
In vivo imaging of ferroptosis through nanodynamic changes in lipid membranes
Authors: Sonay Ali Yasin , Mc Larney Benedict Edward , Apfelbaum Elana , Grimm Jan 
Published: October 2024

AbstractFerroptosis emerged as a cell death modality for drug resistant cancer cells, but there are currently no available biomarkers for imaging ferroptosis based therapies. To address this gab, we evaluated the nanodynamic changes in lipid membranes occurring during cell death to explore potential targeting opportunities to image cell death. We nano-sized gaps at late stages of ferroptosis can serve as entry points for dyes that can bind to cellular structures. These changes were accompanied with cellular signaling components similar to platelet activation, with phosphatidyl serine emerging on the surface of the cells and therefore as a potential target for imaging of programed cell death, including ferroptosis. Taking advantage of these changes in cell membrane dynamics, we employed a novel tumor-seeking dye CJ215 that can label apoptotic cells as recently described by us. We show that CJ215 accumulates in ferroptotic cells both in vitro and in vivo by binding to phosphatidyl serine, a process that is prevented by inhibition of ferroptosis. Since phosphatidyl serine exposure also occurs during apoptosis, CJ215 can serve to image both apoptosis and ferroptosis based therapy.
Overt visual attention modulates decision-related signals in ventral and dorsal medial prefrontal cortex
Authors: Shevlin Blair , Gwinn Rachael , Makwana Aidan , Krajbich Ian 
Published: October 2024

AbstractWhen indicating a preference between two options, decision makers are thought to compare and accumulate evidence in an attention-guided process. Little is known about this process’s neural substrates or how visual attention affects the representations of accumulated evidence. We conducted a simultaneous eye-tracking and fMRI experiment in which human subjects gradually learned about the value of two food-lotteries. With this design we were able to extend decisions over a prolonged time-course, manipulate the temporal onset of evidence, and therefore dissociate sampled and accumulated evidence. Consistent with past work, we found correlates of sampled evidence in ventromedial prefrontal cortex (vmPFC), and correlates of accumulated evidence in the prefrontal and parietal cortex. We also found that more gaze at an option increased its choice probability and that gaze amplified sampled-value signals in the vmPFC and ventral striatum. Most importantly, we found that gaze modulated accumulated-value signals in the pre-supplementary motor area (pre-SMA), providing novel evidence that visual attention has lasting effects on decision variables and suggesting that activity in the pre-SMA reflects accumulated evidence and not decision conflict. These results shed new light on the neural mechanisms underlying gaze-driven decision processes.
Zymocin-like killer toxin gene clusters in the nuclear genomes of filamentous fungi
Authors: Heneghan Padraic G. , Salzberg Letal I. , Wolfe Kenneth H. 
Published: October 2024

AbstractZymocin-like killer toxins are anticodon nucleases secreted by some budding yeast species, which kill competitor yeasts by cleaving tRNA molecules. They are encoded by virus-like elements (VLEs), cytosolic linear DNA molecules that are also called killer plasmids. To date, toxins of this type have been found only in budding yeast species (Saccharomycotina). Here, we show that the nuclear genomes of many filamentous fungi (Pezizomycotina) contain small clusters of genes coding for a zymocin-like ribonuclease (γ-toxin), a chitinase (toxin α/β-subunit), and in some cases an immunity protein. The γ-toxins fromFusarium oxysporumandColletotrichum siamenseabolished growth when expressed intracellularly inS. cerevisiae. Phylogenetic analysis of glycoside hydrolase 18 (GH18) domains shows that the chitinase genes in the gene clusters are members of the previously described C-II subgroup of Pezizomycotina chitinases. We propose that the Pezizomycotina gene clusters originated by integration of a yeast-like VLE into the nuclear genome, but this event must have been ancient because (1) phylogenetically, the Pezizomycotina C-II chitinases and the Saccharomycotina VLE-encoded toxin α/β subunit chitinases are sister clades with neither of them nested inside the other, and (2) many of the Pezizomycotina toxin cluster genes contain introns, whereas VLEs do not. One of the toxin gene clusters inFusarium graminearumis a locus that has previously been shown to be under diversifying selection in North American populations of this plant pathogen. We also show that two genera of agaric mushrooms (Basidiomycota) have acquired toxin gene clusters by horizontal transfers from different Pezizomycotina donors.
Improved protein interaction models predict differences in complexes between human cell lines
Authors: Wilkins Gary R. , Lugo-Martinez Jose , Murphy Robert F. 
Published: October 2024

ABSTRACTThe interactions of proteins to form complexes play a crucial role in cell function. Data on protein-protein or pairwise interactions (PPI) typically come from a combination of sample separation and mass spectrometry. Since 2010, several extensive, high-throughput mass spectrometry-based experimental studies have dramatically expanded public repositories for PPI data and, by extension, our knowledge of protein complexes. Unfortunately, challenges of limited overlap between experiments, modality-oriented biases, and prohibitive costs of experimental reproducibility continue to limit coverage of the human protein assembly map, both underscoring the need for and spurring the development of relevant computational approaches.Here, we present a new method for predicting the strength of protein interactions. It addresses two important issues that have limited past PPI prediction approaches: incomplete feature sets and incomplete proteome coverage. For a given collection of protein pairs, we fused data from heterogeneous sources into a feature matrix and identified the minimal set of feature partitions for which a non-empty set of protein pairs had complete values. For each such feature partition, we trained a classifier to predict PPI probabilities. We then calculated an overall prediction for a given protein pair by weighting the probabilities from all models that applied to that pair. Our approach accurately identified known and highly probable PPI, far exceeding the performance of current approaches and providing more complete proteome coverage. We then used the predicted probabilities to assemble complexes using previously-described graph-based tools and clustering algorithms and again obtained improved results. Lastly, we used features for three human cell lines to predict PPI and complex scores and identified complexes predicted to differ between those cell lines.
Ivory-billed Woodpecker and Blue Jay kent comparisons at spectrogram level reveal differences
Authors: Williams John D 
Published: October 2024

AbstractA representative audio file for Blue Jay (Cyanocitta cristata), that is thought to be most similar to suspected kent sounds of the Ivory-billed Woodpecker (Campephilus principalis), was examined at the spectrogram level. A total of 136 other Blue Jay files were looked at and compared to kents (n>200) from six Ivory-billed Woodpecker expeditions. At this precision, differences are seen such that these two species cannot be mistaken for each other.
Microglial states determine lesion dynamics in multiple sclerosis
Authors: van den Bosch Aletta M.R. , Khoo Jia Hui , Lu Zhigang , Liang Han , Wever Dennis , Pu Li , Eggen Bart J.L. , Uhlén Mathias , Smolders Joost , Hamann Jörg , Shang Zhouchun , Mulder Jan , Huitinga Inge 
Published: October 2024

Summary paragraphMultiple sclerosis (MS) is a neuroinflammatory disease of the central nervous system, characterized by demyelinating lesions1. Lesion expansion contributes to progression and increased disability, while remyelination can recover neurological deficits. However, mechanisms driving lesion dynamics are largely unclear, hindering the development of effective therapeutics. We propose that distinct states of microglia are involved in lesion expansion and remyelination2,3. Using Stereo-seq, an RNA capture based high-resolution spatial transcriptomics technology with single-cell resolution, on post-mortem human brain tissue, we compared mixed active/inactive lesions with lipid-laden foamy microglia with lesions containing ramified microglia. We identified distinct cellular and molecular mechanisms underlying lesion activity and remyelination, linked to microglia phenotypes and states. Lesions with foamy microglia were characterized by elevated immune activation, increased lymphocyte densities, upregulated immunoglobulin production (IGHG1,IGHG3), increased complement system activity, indication of iron dysregulation (FTL,FTH1), and increased demyelination. In contrast, lesions with ramified microglia exhibited gene expression profiles indicative of myelin stability (ABCA2,QKI) and neuro-axonal protection, fostering an environment conducive to repair and remyelination. Our findings highlight the role of microglial states in lesion expansion and repair in MS and offer promising avenues for the development of therapeutic approaches aimed at preventing MS disability progression.
Human-mouse proteomics reveals the shared pathways in Alzheimer’s disease and delayed protein turnover in the amyloidome
Authors: Yarbro Jay M. , Han Xian , Dasgupta Abhijit , Yang Ka , Liu Danting , Shrestha Him K. , Zaman Masihuz , Wang Zhen , Yu Kaiwen , Lee Dong Geun , Vanderwall David , Niu Mingming , Sun Huan , Xie Boer , Chen Ping-Chung , Jiao Yun , Zhang Xue , Wu Zhiping , Fu Yingxue , Li Yuxin , Yuan Zuo-Fei , Wang Xusheng , Poudel Suresh , Vagnerova Barbora , He Qianying , Tang Andrew , Ronaldson Patrick T. , Chang Rui , Yu Gang , Liu Yansheng , Peng Junmin 
Published: October 2024

AbstractMurine models of Alzheimer’s disease (AD) are crucial for elucidating disease mechanisms but have limitations in fully representing AD molecular complexities. We comprehensively profiled age-dependent brain proteome and phosphoproteome (n> 10,000 for both) across multiple mouse models of amyloidosis. We identified shared pathways by integrating with human metadata, and prioritized novel components by multi-omics analysis. Collectively, two commonly used models (5xFAD and APP-KI) replicate 30% of the human protein alterations; additional genetic incorporation of tau and splicing pathologies increases this similarity to 42%. We dissected the proteome-transcriptome inconsistency in AD and 5xFAD mouse brains, revealing that inconsistent proteins are enriched within amyloid plaque microenvironment (amyloidome). Determining the 5xFAD proteome turnover demonstrates that amyloid formation delays the degradation of amyloidome components, including Aβ-binding proteins and autophagy/lysosomal proteins. Our proteomic strategy defines shared AD pathways, identify potential new targets, and underscores that protein turnover contributes to proteome-transcriptome discrepancies during AD progression.
Pre-processing annotated homologous regions in protein sequences concerning machine-learning applications
Authors: Malhis Nawar 
Published: October 2024

AbstractWhile annotated protein sequences are widely used in machine learning applications, pre-processing these sequences regarding homology is mainly limited to clustering complete sequences based on global alignment without considering their annotations. Here, I am introducing new tools that identify all possible local homologies between annotated sequences within the same or across two datasets and then resolve these homologies.Availabilityorca.msl.ubc.ca/nmshare/ham.tar.gz
NewtCap: an efficient target capture approach to boost genomic studies in Salamandridae (True Salamanders and Newts)
Authors: de Visser Manon Chantal , France James , McCartney-Melstad Evan , Bucciarelli Gary M. , Theodoropoulos Anagnostis , Shaffer Howard Bradley , Wielstra Ben 
Published: October 2024

AbstractSalamanders have large and complex genomes, hampering whole genome sequencing, but reduced representation sequencing provides a feasible alternative. We present NewtCap: a sequence capture bait set that targets c.7k coding regions across the genomes of all True Salamanders and Newts (the family Salamandridae, also known as ‘salamandrids’). We test the efficacy of NewtCap, originally designed for the EurasianTriturusnewts, in 30 species, belonging to 17 different genera, that cover all main Salamandridae lineages. We also test NewtCap in two other salamander families. We discover that NewtCap performs well across all Salamandridae lineages (but not in the salamander families Ambystomatidae and Hynobiidae). As expected, the amount of genetic divergence from the genusTrituruscorrelates negatively to capture efficacy and mapping success. However, this does not impede our downstream analyses. We showcase the potential of NewtCap in the contexts of; 1) phylogenomics, by reconstructing the phylogeny of Salamandridae, 2) phylogeography, by sequencing the four closely related species comprising the genusTaricha, 3) hybrid zone analysis, by genotyping twoLissotritonspecies and different classes of interspecific hybrids, and 4) conservation genetics, by comparingTriturus ivanbureschisamples from several wild populations and one captive-bred population. Overall, NewtCap has the potential to boost straightforward, reproducible, and affordable genomic studies, tackling both fundamental and applied research questions across salamandrids.
Early perturbations to fluid homeostasis alter development of hypothalamic feeding circuits with context-specific changes in ingestive behavior
Authors: Sweet Serena R. , Biddinger Jessica E. , Zimmermann Jessie B. , Yu Gina L. , Simerly Richard B. 
Published: October 2024

SUMMARYDrinking and feeding are tightly coordinated homeostatic events and the paraventricular nucleus of the hypothalamus (PVH) represents a possible node of neural integration for signals related to energy and fluid homeostasis. We usedTRAP2;Ai14and Fos labeling to visualize neurons in the PVH and median preoptic nucleus (MEPO) responding to both water deprivation and hunger. Moreover, we determined that structural and functional development of dehydration-sensitive inputs to the PVH from the MEPO precedes those of agouti-related peptide (AgRP) neurons, which convey hunger signals and are known to be developmentally programmed by nutrition. We also determined that osmotic hyperstimulation of neonatal mice led to enhanced AgRP inputs to the PVH in adulthood, as well as disruptions to ingestive behaviors during high-fat diet feeding and dehydration-anorexia. Thus, development of feeding circuits is impacted not only by nutritional signals, but also by early perturbations to fluid homeostasis with context-specific consequences for coordination of ingestive behavior.
Planarians Develop Radiotolerance to Recurrent Ionizing Radiation Exposure
Authors: Barghouth Paul G. , Ziman Benjamin , Maciel Eli Isael , Karabinis Peter , Rojas Salvador , Flores Natasha M. , Pfister Edelweiss , Oviedo Néstor J. 
Published: October 2024

AbstractExposure to ionizing radiation can induce DNA fragmentation, leading to double-strand breaks, the most toxic form of DNA damage. Some organisms have developed mechanisms to overcome the adverse effects of ionizing radiation by enhancing DNA protection and repair. However, the underlying mechanisms driving radiation resistance to maintain genomic integrity and function remain poorly understood. Here, we provide evidence for the development of radiotolerance in the flatworm planarianSchmidtea mediterranea. We implemented a strategy to select animals capable of overcoming repeated rounds of ionizing radiation exposure. We demonstrate that planarians initially exposed to higher amounts of sub-lethal radiation can adapt, gaining the ability to recover reproductive capabilities faster than animals initially exposed to lower amounts of sub-lethal radiation. Our findings show that DNA integrity is reestablished in about one week after five cycles of sub-lethal ionizing radiation exposure. Planarian stem cells, known as neoblasts, can repair repeated DNA double-strand breaks by activating Rad51-mediated homologous recombination. The expression of the neoblast markersmedpiwi-1and the mitotic activity reach levels similar to unirradiated animals between two and three weeks post-radiation. We describe that planarians develop radiotolerance through recurrent ionizing radiation exposure over several years and survive without apparent functional or morphological defects for an undetermined time.
The potential use of immersive virtual environments for collecting and archiving heritage gameplay activities in digital libraries
Authors: Lau Kung Wong 
Published: October 2024

Purpose
This paper aims to discuss and propose the potential use of immersive virtual environments (IVEs) for archiving and collecting heritage gameplay activities in digital libraries, which is expected to triangulate further discussions on the said knowledge scopes.

Design/methodology/approach
The key question of this paper is, how we can preserve and revitalize fading heritage game activities in digital libraries? To answer this, the paper is going to understand the applications of IVEs in heritage studies; the use of telepresence experiences in IVEs for activity-based collection; the creation of virtual and telepresence experiences in digital libraries; and a proposed use of IVEs for archiving heritage gameplay activities.

Findings
The applications of IVEs and/or other virtual technologies have certainly been gaining positive feedback about their ability to provide vivid images of artefacts and art pieces; perform a high level of interactivity between the exhibits and visitors; enhance visitors’ sense of immersion that evoke their memories of heritage issues; facilitate visitors’ learning process in libraries; increase enjoyment in digital libraries. As mentioned in the previous section, the activity-based historical collection, for instance, the heritage gameplay activities, can be preserved and archived vividly using IVEs.

Research limitations/implications
This paper is explorative, there is no empirical result for generalization.

Originality/value
This paper aims to provide librarians with valuable insight to apply IVEs for archiving and collecting heritage gameplay activities. Setting up a new type of digital library is affected greatly by the openness of librarians, visitors’ expectations and a whole lot of things that are happening around the technological world and digital culture. This paper addresses the applications of IVEs in heritage studies, the importance of creating virtual and telepresence experiences for library visits as well as proposing the use of IVEs for archiving heritage gameplay activities.
A neural network approach for unstructured mesh quality evaluation
Authors: Chen Xinhai , Wang Zhichao , Liu Yang , Pang Yufei , Chen Bo , Chen Jianqiang , Gong Chunye , Liu Jie 
Published: October 2024

PurposeThe quality of the unstructured mesh has a considerable impact on the stability and accuracy of aerodynamic simulation in computational fluid dynamics (CFD). Typically, engineers spend a significant portion of their time on mesh quality evaluation to ensure a valid, high-quality mesh. The extensive manual interaction and a priori knowledge required to undertake an accurate and timely evaluation process have become a bottleneck in the idealized efficient CFD workflow. This paper aims to introduce a neural network-based quality evaluation approach for unstructured meshes to enable higher efficiency and the level of automation.Design/methodology/approachThe paper investigates the capability of deep neural networks for the quality evaluation of unstructured meshes. For training the network, we build a training dataset for mesh quality learning algorithms. The dataset contains a rich variety of unstructured aircraft meshes with different mesh sizes, densities, cell distribution, growth ratios and cell numbers to ensure its diversity and availability. We also design a neural network, AircraftNet, to learn the effect of mesh quality on the convergent properties of the numerical solutions. The proposed network directly manipulates raw point data in mesh source files rather than passing it to an intermediate data representation. During training, AircraftNet extracts non-linear quality features from high-dimensional data spaces and then automatically predicts the overall quality of the input unstructured mesh.FindingsThe paper provides a series of experimental results on GPUs. It shows that AircraftNet is able to effectively analyze the quality-related features like mesh density and distribution from the extracted features and achieve high prediction accuracy on the proposed dataset with even a small number of training runs.Research limitations/implicationsBecause of the limited training dataset, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.Originality/valueThe paper publishes a benchmarking dataset for mesh quality learning algorithms and designs a novel neural network approach for unstructured mesh quality evaluation.