bluuebunny/crossref_metadata_2025_split huggingface dataset:
Topo-Net: Retinal Image Analysis with Topological Deep Learning
Authors: Ahmed Faisal , Coskunuzer Baris 
Published: February 2024

AbstractThe analysis of fundus images for the early screening of eye diseases is of great clinical importance. Traditional methods for such analysis are time-consuming and expensive as they require a trained clinician. Therefore, the need for a comprehensive and automated clinical decision support system to diagnose and grade retinal diseases has long been recognized. In the past decade, with the substantial developments in computer vision and deep learning, machine learning methods have become highly effective in this field to address this need. However, most of these algorithms face challenges like computational feasibility, reliability, and interpretability.In this paper, our contributions are two-fold. First, we introduce a very powerful feature extraction method for fundus images by employing the latest topological data analysis methods. Through our experiments, we observe that our topological feature vectors are highly effective in distinguishing normal and abnormal classes for the most common retinal diseases, i.e., Diabetic Retinopathy (DR), Glaucoma, and Age-related Macular Degeneration (AMD). Furthermore, these topological features are interpretable, computationally feasible, and can be seamlessly integrated into any forthcoming ML model in the domain. Secondly, we move forward in this direction, constructing a topological deep learning model by integrating our topological features with several deep learning models. Empirical analysis shows a notable enhancement in performance aided by the use of topological features. Remarkably, our model surpasses all existing models, demonstrating superior performance across several benchmark datasets pertaining to two of these three retinal diseases.
SREBP-dependent regulation of lipid homeostasis is required for progression and growth of pancreatic ductal adenocarcinoma
Authors: Ishida Chiaki T. , Myers Stephanie L. , Shao Wei , McGuire Meredith R. , Liu Chune , Kubota Casie S. , Ewachiw Theodore E. , Mukhopadhyay Debaditya , Ke Suqi , Wang Hao , Rasheed Zeshaan A. , Anders Robert A. , Espenshade Peter J. 
Published: February 2024

ABSTRACTMetabolic reprogramming is a necessary component of oncogenesis and cancer progression that solid tumors undergo when their growth outstrips local nutrient supply. The supply of lipids such as cholesterol and fatty acids is required for continued tumor cell proliferation, and oncogenic mutations stimulate de novo lipogenesis to support tumor growth. Sterol regulatory element-binding protein (SREBP) transcription factors control cellular lipid homeostasis by activating genes required for lipid synthesis and uptake. SREBPs have been implicated in the progression of multiple cancers, including brain, breast, colon, liver, and prostate. However, the role the SREBP pathway and its central regulator SREBP cleavage activating protein (SCAP) in pancreatic ductal adenocarcinoma (PDAC) has not been studied in detail. Here, we demonstrated that pancreas-specific knockout ofScaphas no effect on mouse pancreas development or function, allowing for examination of the role forScapin the murine KPC model of PDAC. Notably, heterozygous loss ofScapprolonged survival in KPC mice, and homozygous loss ofScapimpaired PDAC tumor progression. Using subcutaneous and orthotopic xenograft models, we showed that SCAPis required for human PDAC tumor growth. Mechanistically, chemical or genetic inhibition of the SREBP pathway prevented PDAC cell growth under low serum conditions due to a lack of lipid supply. Highlighting the clinical importance of this pathway, the SREBP pathway is broadly required for cancer cell growth, SREBP target genes are upregulated in human PDAC tumors, and increased expression of SREBP targets genes is associated with poor survival in PDAC patients. Collectively, these results demonstrate that SCAP and the SREBP pathway activity are essential for PDAC cell and tumor growthin vitroandin vivo, identifying SCAP as a potential therapeutic target for PDAC.SIGNIFICANCEOur findings demonstrate that SREBP pathway activation is a critical part of the metabolic reprogramming that occurs in PDAC development and progression. Therefore, targeting the SREBP pathway has significant therapeutic potential.
Elastohydrodynamic mechanisms govern beat pattern transitions in eukaryotic flagella
Authors: Veeraragavan Shibani , Parast Farin Yazdan , Nosrati Reza , Prabhakar Ranganathan 
Published: February 2024

AbstractEukaryotic cilia and flagella exhibit complex beating patterns that vary depending on environmental conditions such as fluid viscosity1. These transitions are thought to arise from changes in the internal forcing provided by the axoneme, although the mechanism remains unclear2,3. We demonstrate with simulations of Kirchhoff rods driven internally by active bending moments that a single elastohydrodynamic instability universally explains transitions between planar, quasiplanar, helical, and complex beating patterns due to changes in either the internal forcing, flagellar stiffness and length, or due to changes in the hydrodynamic resistance, either due to the viscosity of the ambient medium or the presence of a plane wall. The beat patterns and transitions are comparable to those exhibited by bull sperm and sea urchin sperm in our experiments and elsewhere3–5. Our results point to a general model that can describe flagellar and ciliary beating across all species. We further show that internal dynein forces can be estimated by comparing simulation results with experimental observations of transitional viscosities. This can potentially lead to diagnostic assays to measure the health of sperm cells based on their beating pattern.
Quantifying the IUCN Red List: Using historical assessments to calculate future extinction risk
Authors: Bates Ryan , Taylor Elizabeth , Sun Yuheng , Gumbs Rikki , Böhm Monika , Gray Claudia , Rosindell James 
Published: February 2024

AbstractThe IUCN Red List of Threatened Species assigns species to discrete categories based on a common set of criteria to capture relative extinction risk. Some quantitative analyses require a continuous probability of extinction not provided by discrete categories. Furthermore, the criteria may not translate to extinction risk in a universal way across species, because some species’ attributes are not incorporated into the criteria. Here we calculate extinction risk using Markov Models parameterised with historical IUCN Red List assessment data, and we provide quantitative extinction risk for use in downstream analyses. We find that taxonomy, body size, and habitat specialism interact with extinction risk in ways not fully captured by the existing categories. For example, an Endangered habitat specialist appears equally at risk compared to a Critically Endangered habitat generalist. We hope our findings will support more accurate quantitative biodiversity analyses of species extinctions and declines using Red List data.
A self-adaptive and versatile tool for eliminating multiple undesirable variations from transcriptome
Authors: Zhang Mengji , Yan Lei , Wang Xinbo , Yuan Yi , Zou Shimin , Yao Sichao , Wang Xinyu , Xu Tian , Chen Bin , Yang Dong 
Published: February 2024

AbstractAccurate identification of true biological signals from diverse undesirable variations in large-scale transcriptomes is essential for downstream discoveries. Herein, we develop a universal deep neural network, called DeepAdapter, to eliminate various undesirable variations from transcriptomic data. The innovation of our approach lies in automatic learning of the corresponding denoising strategies to adapt to different situations. The data-driven strategies are flexible and highly attuned to the transcriptomic data that requires denoising, yielding significant improvement in reducing undesirable variation originating from batches, sequencing platforms, and bio-samples with varied purity beyond manually designed schemes. Comprehensive evaluations across multiple batches, different RNA measurement technologies and heterogeneous bio-samples demonstrate that DeepAdapter can robustly correct diverse undesirable variations and accurately preserve biological signals. Our findings indicate that DeepAdapter can act as a versatile tool for the comprehensive denoising of the large and heterogeneous transcriptome across a wide variety of application scenarios.
Impact of a team-based versus individual clinician-focused training approach on primary healthcare professionals’ intention to have serious illness conversations with patients: a theory informed process evaluation of a cluster randomized trial
Authors: Souza Lucas Gomes , Archambault Patrick , Asmaou Bouba Dalil , Dofara Suélène Georgina , Guay-Bélanger Sabrina , Cortez Ghio Sergio , Gadio Souleymane , Michaels LeAnn , Paquette Jean-Sébastien , Izumi Shigeko (Seiko) , Totten Annette M. , Légaré France ,   The Meta-LARC ACP Cluster Randomized Trial team
Published: February 2024

ABSTRACTBackgroundCluster Randomized Trials (cRTs) conducted in real-world settings face complex challenges due to diverse practices and populations. Process evaluations alongside cRTs can help explain their results by exploring possible causal mechanisms as the trial proceeds.ObjectiveTo conduct a process evaluation alongside a cRT that compared the impact of team-based vs. individual clinician-focused SICP training on primary healthcare professionals’ (PHCPs) intention to have serious illness conversations with patients.MethodsThe cRT involved 45 primary care practices randomized into a team-based (intervention) or individual clinician-focused training program (comparator) and measured primary outcomes at the patient level: days at home and goal of care. Our theory-informed mixed-methods process evaluation alongside the cRT measured intention to have serious illness conversations with patients among the trained PHCPs using the CPD-Reaction tool. Barriers and facilitators to implementing serious illness conversations were identified through open-ended questions and analyzed using the Theoretical Domains Framework. We used the COM-B framework to perform triangulation of data. We reported results using the CONSORT and GRAMMS reporting guidelines.ResultsOf 535 PHCPs from 45 practices, 373 (69.7%) fully completed CPD-Reaction (30.8% between 25-34 years old; 78.0% women; 54.2% had a doctoral degree; 50.1% were primary care physicians). Mean intention scores for the team-based (n=223) and individual clinician-focused arms (n=150) were 5.97 (Standard Error: 0.11) and 6.42 (Standard Error: 0.13), respectively. Mean difference between arms was 0.0 (95% CI −0.30;0.29; p=0.99) after adjusting for age, education and profession. The team-based arm reported barriers with communication, workflow, and more discomfort in having serious illness conversations with patients.ConclusionsTeam-based training did not outperform individual clinician-focused in influencing PHCPs’ intention to have serious illness conversations. Future team-based interventions could foster behaviour adoption by focusing on interprofessional communication, better organized workflows, and better support and training for non-clinician team members.RegistrationClinicalTrials.gov(ID:NCT03577002).
Localization of Human UBE3A Isoform 3 is Highly Sensitive to Amino Acid Substitutions at p.Met21 Position
Authors: van Esbroeck Annelot C. M. , Verhagen Rob F. M. , Biagioni Martina , Fossati Matteo , Distel Ben , Elgersma Ype 
Published: February 2024

AbstractUBE3A encodes three isoforms of Ubiquitin E3 ligase A, which differ in their N-terminal sequence, abundance, and localization. Recently, three individuals diagnosed with Angelman Syndrome have been described who carry a variant that abrogates the start codon of the predominant nuclear isoform 1 (hUBE3A-Iso1p.Met1Thr) and concomitantly results in a missense variant in isoform 3 (hUBE3A-Iso1p.Met21Thr), which we previously reported to be nuclear enriched as well.Here, we studied the effect of the p.Met21Thr variant on hUBE3A-Iso3 localization. Recombinant expression of hUBE3A-Iso3p.Met21Thrin U2-OS and mouse neurons revealed similar UBE3A labelling in the nucleus and cytosol, indicating hUBE3A-Iso3 localization is sensitive to amino acid changes at this position. This finding prompted us to revisit hUBE3A-Iso3 localization, since we previously introduced a p.Met21Ala/p.Met22Ala amino acid substitution in hUBE3A-Iso3 and its mouse orthologue mUBE3A-Iso2 to prevent translation of the shorter hUBE3A-Iso1 and mUBE3A-Iso3 nuclear isoforms. Introduction of silent mutations to disfavour translation of the short UBE3A isoforms enabled us to determine the localization hUBE3A-Iso3 and mUBE3A-Iso2 in the absence of amino acid changes at the p.Met21/p.Met22 position, respectively. Surprisingly, hUBE3A-Iso3 localization shifted from predominant nuclear localization for hUBE3A-Iso3p.Met21Alato a predominant cytosolic localization of the Kozak optimized hUBE3A-Iso3KOZAK, while their mouse orthologues mUBE3A-Iso2p.Met22Alaand mUBE3A-Iso2KOZAKboth localized predominantly to the cytosol.Taken together, these experiments indicate that the localization of human UBE3A-Iso3 is highly sensitive to amino acid substitutions at the p.Met21 position and that variants at this position not only abrogate the translation of hUBE3A-Iso1, but can also change the localization of hUBE3A-Iso3.
Photoprotective melanin is maintained within keratinocytes in a storage lysosome
Authors: Neto Matilde V. , Hall Michael J. , Charneca João , Escrevente Cristina , Seabra Miguel C. , Barral Duarte C. 
Published: February 2024

AbstractIn the skin, melanin is synthesized by melanocytes within melanosomes, and transferred to keratinocytes. After being phagocytosed by keratinocytes, melanin polarizes to supranuclear caps that protect against the genotoxic effects of ultraviolet radiation. We provide evidence that melanin-containing phagosomes undergo a canonical maturation process, with the sequential acquisition of early and late endosomal markers. Subsequently, these phagosomes fuse with active lysosomes, leading to the formation of a melanin-containing phagolysosome that we named melanokerasome. Melanokerasomes achieve juxtanuclear positioning via lysosomal trafficking regulators Rab7 and RILP. Mature melanokerasomes exhibit lysosomal markers, elude connections with the endo/phagocytic pathway, are weakly degradative, retain undigested cargo and are likely tethered to the nuclear membrane. We propose that they represent a lysosomal-derived storage compartment that has exited the lysosome cycle, akin to the formation of lipofuscin in aged cells and dysfunctional lysosomes in lysosomal storage and age-related diseases. This storage lysosome allows melanin to persist for long periods, where it can exert its photoprotective effect efficiently.
Decoding cell identity with multi-scale explainable deep learning
Authors: Zhu Jun , Zhang Zeyang , Xiang Yujia , Xie Beini , Dong Xinwen , Xie Linhai , Zhou Peijie , Yao Rongyan , Wang Xiaowen , Li Yang , He Fuchu , Zhu Wenwu , Zhang Ziwei , Chang Cheng 
Published: February 2024

AbstractCells are the fundamental structural and functional units of life. Studying the definition and composition of different cell types can help us understand the complex mechanisms underlying biological diversity and functionality. The increasing volume of extensive single-cell omics data makes it possible to provide detailed characterisations of cell types. Recently, there has been a rise in deep learning-based approaches that generate cell type labels solely through mapping query data to reference data. However, these approaches lack multi-scale descriptions and interpretations of identified cell types. Here, we propose Cell Decoder, a biological prior knowledge informed model to achieve multi-scale representation of cells. We implemented automated machine learning and post-hoc analysis techniques to decode cell identity. We have shown that Cell Decoder compares favourably to existing methods, offering multi-view interpretability for decoding cell identity and data integration. Furthermore, we have showcased its applicability in uncovering novel cell types and states in both human bone and mouse embryonic contexts, thereby revealing the multi-scale heterogeneity inherent in cell identities.
Deep computer vision reveals the mediation of thermal-melanism and body size by precipitation and sex in a threatened alpine butterfly,Parnassius smintheus
Authors: Shirey Vaughn , Goswami Rhea , Latronica Greg , Goudarzi Arshan , Neupane Naresh , Breed Greg A. , Ries Leslie 
Published: February 2024

AbstractInsect morphologies are strongly tied to selective forces, yet due to variation in these forces and finite resources, insects must strategically invest in select morphologies while deprioritizing others. Melanism and body size may be one such potential trade-off that insects navigate and these two factors are important for fecundity, dispersal, thermoregulation, anti-desiccation, and immunity. In this work, we examined how sex and environmental factors mediate a potential body-size/melanism trade-off in the cold-adapted butterflyParnassius smintheus(Lepidoptera: Papilionidae). We used deep computer vision approaches and museum specimen photography to process over 1,000 images of the species. We found that body-size and melanism are strongly mediated by temperature and elevation (thermal-melanism hypothesis) and that precipitation mediates these slopes for males and females differently. Notably, under the wettest conditions, females exhibit stronger concordance with the thermal-melanism hypothesis while the relationship for males is inverted, suggesting increased competition among males in cold-wet environments. Our results highlight the importance of considering sex when examining how the environment influences intraspecific morphological variation, especially under projected scenarios of global climate change.
DeleteomeTools: Utilizing a compendium of yeast deletion strain transcriptomes to identify co-functional genes
Authors: Neal Maxwell L. , Choudhry Sanjeev K. , Aitchison John D. 
Published: February 2024

ABSTRACTWe introduce DeleteomeTools, an R package that leverages the Deleteome compendium of yeast single-gene deletion transcriptomes to predict gene function. Primarily, the package provides functions for identifying similarities between the transcriptomic signatures of deletion strains, thereby associating genes of interest with others that may be functionally related. We describe how our software predicted a novel relationship between the yeast nucleoporin Nup170 and the Ctf18-RFC complex, which was confirmed experimentally, revealing a previously unknown link between nuclear pore complexes and the DNA replication machinery. To assess the package’s broader predictive capabilities, we performed a systematic evaluation that tested how well it predicted Gene Ontology (GO) annotations already applied to the subset of genes deleted in Deleteome strains. We show that our package predicted a majority of reported GO:biological processannotations with semantic similarities ranging from moderate to identical. We also discuss how our strategy for quantifying similarity between deletion strains, which relies on differential expression signatures, differs from other approaches that use global expression profiles and why it has the potential to identify functional relationships that might otherwise go undetected.
Statistical modelling of seafood fraud in the Canadian supply chain
Authors: Phillips Jarrett D. , De Vuono-Fraser Fynn A. 
Published: February 2024

AbstractSeafood misrepresentation, encompassing product adulteration, mislabelling, and substitution, among other fraudulent practices, has been rising globally over the past decade, greatly impacting both the loss of important fish species and the behaviour of human consumers alike. While much effort has been spent attempting to localise the extent of seafood mislabelling within the supply chain, strong associations likely existing among key players have prevented timely management and swift action within Canada and the USA in comparison to European nations. To better address these shortcomings, herein frequentist and Bayesian logistic Generalised Linear Models (GLMs) are developed in R and Stan for estimation, prediction and classification of product mislabelling in Metro Vancouver, British Columbia, Canada. Obtained results based on odds ratios and probabilities paint a grim picture and are consistent with general trends found in past studies. This work paves the way to rapidly assess the current state of knowledge surrounding seafood fraud nationally and on a global scale using established statistical methodology.
Complementary human gene interaction maps from radiation hybrids and CRISPRi
Authors: Smith Desmond J. 
Published: February 2024

AbstractThe only comprehensive genetic interaction map of the human genome was constructed using increased gene copy number in radiation hybrid (RH) cells. More recently, interactions restricted to essential genes were identified using loss-of-function alleles made by CRISPRi technology. Here, the two maps are compared to understand their similarities and differences. Both maps overlapped significantly with a database of protein-protein interactions. However, interactions in the RH and CRISPRi datasets had no significant overlap, even though the participating genes overlapped significantly. In addition, the RH map showed highly significant similarity with an interaction map constructed from genome-wide association studies (GWASs), while the CRISPRi map did not. This study reveals the different aspects of the genetic interaction landscape illuminated by gain- and loss-of-function alleles.
Genetic architecture and adaptation of Ladakh highlanders of trans-Himalayas
Authors: Kumar Lomous , Rajpal Richa , Ahlawat Bhavna , Pasupuleti Nagarjuna , Konar Snigdha , Dwivedi Aparna , Kumar Sachin , Spalzin Sonam , Rabyang Stanzen , Thangaraj Kumarasamy , Rai Niraj 
Published: February 2024

AbstractTrans-Himalayan Ladakh has witnessed complex cultural movements and demographic changes since the Neolithic period, which is still continue despite the harsh, inhospitable and cold climate. Although geographically isolated from mainland South Asia, Ladakh has historic trade routes and is well connected and accessible to travelers from Tibet and Central Asia. Despite its rich cultural heritage, a detailed description of the genetic landscape of the Ladakh region is completely lacking, particularly with regard to genome-wide analysis and larger sample sizes. Therefore, in the current study, we genotyped 80 individuals from Kargil and Leh districts of the Union Territory of Ladakh, India. Here, we performed a comprehensive genetic analysis based on allele frequency and haplotype sharing. Our analysis revealed the presence of two distinct genetic lineages in the region with quite distinct genetic composition. The population of Leh Region is more similar to East Asian and Southeast Asian populations. In contrast, the population of the Kargil Region (LDKLA) is more similar to Indo-European populations. Demographic modeling suggests that the Leh group shares a genetic history with Tibetans, while the Kargil group showed great affinities with Kashmiri Muslims, Gujjars and Nepalese Brahmins, and both showed recent admixture. Both groups have experienced a founder event around during 11th to 22nd generations ago, the duration of which coincided with the Mughal invasion. The genome-wide scan for a signal of positive selection revealed genetic signatures of high-altitude adaptation (EPAS1andELMO2) in the Leh population, while in the Kargil population the key gene signatures were associated with immunity and female fertility.