bluuebunny/crossref_metadata_2025_split huggingface dataset:
CD200 depletion in glioma enhances antitumor immunity and induces tumor rejection
Authors: Raphael Itay , Mujeeb Anzar A. , Ampudia-Mesias Elisabet , Sever ReidAnn E. , McClellan Brandon , Frederico Stephen C. , Sneiderman Chaim T. , Mirji Apoorva , Daba Ali , Puerta-Martinez Francisco , Nisnboym Michal , Edwards Wilson B. , Graner Michael , Moertel Christopher L. , Castro Maria G. , Kohanbash Gary , Olin Michael R. 
Published: September 2024

AbstractHigh-grade gliomas are a major health challenge with poor prognosis and high morbidity. Immune-checkpoint inhibitors (ICI) have emerged as promising therapeutic options for several malignancies yet show little efficacy against central nervous system (CNS) tumors. CD200 is a newly recognized immune checkpoint that modulates immune homeostasis. CD200 protein is expressed by a variety of cells, including immune cells and stromal cells, and is overexpressed by many tumors. The shedding of CD200 from tumor cells can create an immunosuppressive environment that dampens anti-tumor immunity by modulating cytolytic activity and cytokine expression both within and outside the tumor microenvironment (TME). While it is well-accepted that CD200 induces a pro-tumorigenic environment through its ability to suppress the immune response, we sought to determine the role of glioma-specific expression of CD200. We show that CD200 is expressed across glioma types, is shed from tumor cells, and increases over time in the serum of patients undergoing immunotherapy. Using CD200 knockout (KO) glioma models, we demonstrated that glioma cell-derived CD200 promotes tumor growth in vivo and in vitro. Notably, CD200 KO gliomas are spontaneously rejected by their host, a process that required a fully functional immune system, including NK and T-cells. Moreover, we report that glioma-derived or brain-injected soluble CD200 contributes to the suppression of antigen-specific CD8 T-cells in the draining lymph nodes (dLNs). Our work provides new mechanistic insights regarding CD200-mediated immunosuppression by gliomas.Statement of significanceWe demonstrate mechanisms of the druggable glioma-derived CD200 checkpoint on tumor growth and immune suppression.
Cross-species brain-wide mapping reveals a conserved and coordinated network engaged by NAc DBS
Authors: Feng Austin Y. , Barbosa Daniel A. N. , Casey Austen B. , Rijsketic Daniel R. , Salgado Juliana S. , Huang Harvey , Malenka Robert C. , Hermes Dora , Miller Kai J. , Halpern Casey H. , Heifets Boris D. 
Published: September 2024

SummaryNucleus accumbens (NAc) deep brain stimulation (DBS) has been increasingly explored as a treatment modality for refractory neuropsychiatric disorders. Uncovering the accumbens network that is engaged by DBS is a critical step forward in understanding how modulating this important node impacts the broader mesocorticolimbic circuit. Using whole-brain clearing and unbiased, brain-wide neural activity mapping, we found that NAc DBS increases neural activity in a coordinated mesocorticolimbic network in mice. Simultaneous intracranial electrophysiology recordings from the human NAc and brief stimulation epochs of homologous mesocorticolimbic nodes revealed similar connectivity. Altogether, these results identify specific connectivity conserved across species within the mesocorticolimbic circuit that may underlie mechanisms of NAc DBS.
Reliable machine learning models in genomic medicine using conformal prediction
Authors: Papangelou Christina , Kyriakidis Konstantinos , Natsiavas Pantelis , Chouvarda Ioanna , Malousi Andigoni 
Published: September 2024

AbstractMachine learning and genomic medicine are the mainstays of research in delivering personalized healthcare services for disease diagnosis, risk stratification, tailored treatment, and prediction of adverse effects. However, potential prediction errors in healthcare services can have life-threatening impact, raising reasonable skepticism about whether these applications are beneficial in real-world clinical practices. Conformal prediction is a versatile method that mitigates the risks of singleton predictions by estimating the uncertainty of a predictive model. In this study, we investigate potential applications of conformalized models in genomic medicine and discuss the challenges towards bridging genomic medicine applications with clinical practice. We also demonstrate the impact of a binary transductive model and a regression-based inductive model in predicting drug response and the performance of a multi-class inductive predictor in addressing distribution shifts in molecular subtyping. The main conclusion is that as machine learning and genomic medicine are increasingly infiltrating healthcare services, conformal prediction has the potential to overcome the safety limitations of current methods and could be effectively integrated into uncertainty-informed applications within clinical environments.
Beyond pain: Using Unsupervised Machine Learning to Identify Phenotypic Clusters of Small Fiber Neuropathy
Authors: Murin Peyton J. , Gao Vivian D. , Geisler Stefanie 
Published: September 2024

AbstractBackground and ObjectivesSmall fiber neuropathy (SFN) is characterized by dysfunction and loss of peripheral unmyelinated and thinly myelinated nerve fibers, resulting in a phenotype that includes varying combinations of somatosensory and dysautonomia symptoms, which can be profoundly disabling and lead to decreased quality of life. Treatment aimed mainly at pain reduction, which may not target the underlying pathophysiology, is frequently ineffective. Another impediment to the effective management of SFN may be the significant between-patient heterogeneity. Accordingly, we launched this study to gain insights into the symptomatic variability of SFN and determine if SFN patients can be sub-grouped based on clinical characteristics.MethodsTo characterize the phenotype and investigate how patients with SFN differ from those with large fiber involvement, 105 patients with skin-biopsy proven SFN and 45 with mixed fiber neuropathy (MFN) were recruited. Using unsupervised machine learning, SFN patients were clustered based upon symptom concurrence and severity. Demographics, clinical data, symptoms, and skin biopsy- and laboratory findings were compared between the groups.ResultsMFN- as compared to SFN patients, were more likely to be male, older, had a lower intraepidermal nerve fiber density at the ankle and more frequent abnormal immunofixation. Beyond these differences, symptom prevalence and intensities were similar in the two cohorts. SFN patients comprised three distinct phenotypic clusters, which differed significantly in symptom severity, co-occurrence, localization, and skin biopsy findings. Only one subgroup, constituting about 20% of the patient population, was characterized by intense neuropathic pain, which was always associated with several other SFN symptoms of similarly high intensities. A pauci-symptomatic cluster comprised patients who experienced few SFN symptoms, generally of low to moderate intensity. The largest cluster was characterized by intense fatigue, myalgias and subjective weakness, but lower intensities of burning pain and paresthesia.DiscussionThis data-driven study introduces a new approach to subgrouping patients with SFN. Considering both neuropathic pain and pernicious symptoms beyond pain, we identified three clusters, which may be related to distinct pathophysiological mechanisms. Although additional validation will be required, our findings represent a step towards stratified treatment approaches and, ultimately, personalized treatment.
5-hydroxymethylcytosine Epigenetic Markers in COVID-19-Associated Acute Coronary Syndrome: Insights into Neutrophil Activation and PDE4D Upregulation
Authors: Li Zhongheng , Duolikun Maimaitiyasen , Chen Hangyu , Zhang Lei , Liu Yishuo , Li Ruining , Li Dan , Sun Lijie , Chen Long 
Published: September 2024

AbstractBackgroundStudies have reported that 5hmC features in cell-free DNA (cfDNA) could serve as early warning biomarkers for the occurrence and progression of COVID-19, as well as myocardial injury. However, its roles in the occurrence and progression of acute coronary syndrome (ACS) following COVID-19 infection have not been fully studied.MethodsFirstly, we used the 5hmC-Seal technique to obtain genome-wide 5hmC profiles from plasma cfDNA of 24 ACS2N patients (individuals experiencing ACS onset within 2 months after COVID-19 infection), 28 ACS2W patients (individuals experiencing ACS onset beyond 2 months after COVID-19 infection), and 16 ACS patients (patients with ACS without COVID-19 infection). Secondly, we performed GO, KEGG analysis on the differentially expressed genes and identified a series of immune and inflammation related genes. Thirdly, the distribution of immune cells in different groups of patients was studied by immune infiltration analysis. Finally, we performed PPI network analysis on these genes to identify potential key target genes.ResultsIn this study, we firstly found that there was a significant difference in 5hmC levels between ACS2N patients and ACS patients, while the difference between ACS2W and ACS was not significant. Secondly, it was found that neutrophils were abnormally activated in the ACS2N group. Finally, a target gene phosphodiesterase 4D (PDE4D) was found to be highly expressed in the ACS2N group by PPI network analysis of the differential genes and validated with external datasets.ConclusionsOur study suggested that 5hmC markers extracted from plasma cfDNA could differentiate between ACS2N and ACS patients. In addition, we observed that neutrophils exhibited abnormal activation in ACS2N patients. Further analysis showed that COVID-19 infection may affect the occurrence and development of ACS by abnormally up-regulating PDE4D gene expression.
Gonadotrophs have a dual origin, with most derived from pituitary stem cells during minipuberty
Authors: Sheridan Daniel , Chakravarty Probir , Golan Gil , Shiakola Yolanda , Olsen Jessica , Burnett Elise , Galichet Christophe , Mollard Patrice , Melamed Philippa , Lovell-Badge Robin , Rizzoti Karine 
Published: September 2024

AbstractGonadotrophs are the essential pituitary endocrine cells for reproduction. They produce both luteinizing (LH) and follicle-stimulating (FSH) hormones that act on the gonads. Gonadotrophs first appear in the embryonic pituitary, along with other endocrine cell types, and all expand after birth. We show here that most gonadotrophs originate from a population of postnatal pituitary stem cells during minipuberty, while those generated in the embryo are maintained, revealing an unsuspected dual origin of the adult population. This has implications for our understanding of the establishment and regulation of reproductive functions, both in health and in disease.
Cryo-EM uncovers a sequential mechanism for RNA polymerase I pausing and stalling at abasic DNA lesions
Authors: Santos-Aledo Alicia , Plaza-Pegueroles Adrián , Sanz-Murillo Marta , Ruiz Federico M. , Xu Jun , Gil-Carton David , Wang Dong , Fernández-Tornero Carlos 
Published: September 2024

AbstractRNA polymerase I (Pol I) transcribes ribosomal DNA (rDNA) to produce the rRNA precursor, which accounts for up to 60% of the total transcriptional activity in growing cells. Pol I monitors rDNA integrity and influences cell survival, but little is known about how this enzyme processes abasic DNA lesions. Here, we report electron cryo-microscopy (cryo-EM) structures of Pol I at different stages of stalling at abasic sites, supported by in vitro transcription studies. Our results show that templating abasic sites can slow nucleotide addition by base sandwiching between the RNA 3’-end and the Pol I bridge helix. However, the presence of a templating abasic site induces opening of the Pol I cleft for either enzyme dissociation from DNA or for access of A12-Ct into the active site to stimulate RNA cleavage. Nucleotide addition opposite the lesion induces an early translocation intermediate that is different from previously-described RNA polymerase paused states, as DNA bases in the hybrid tilt to form hydrogen bonds with the newly-added RNA base. While in this state nucleotide addition is strongly disfavoured, intrinsic Pol I RNA cleavage activity acts as a failsafe mechanism to minimize lesion bypass. Our results uncover a two-step mechanism leading to persistent Pol I stalling after nucleotide addition opposite Ap sites, which is distinct from arrest by CPD lesions and from Pol II blockage at Ap sites.
Presynapses are mitophagy pit stops that prevent axon degeneration
Authors: Lam Wai Kit , Lindblom Runa S. J. , Milky Bridget , Mazzachi Paris , Hadian-Jazi Marjan , Küng Catharina , Khuu Grace , Uoselis Louise , Nguyen Thanh Ngoc , Skulsuppaisarn Marvin , Saunders Tahnee L. , Schmidt Marlene F. , Dewson Grant , Fogel Adam I. , Bardy Cedric , Lazarou Michael 
Published: September 2024

AbstractDefects in neuronal mitophagy have been linked to neurodegenerative diseases including Parkinson’s disease. However, despite the importance of mitophagy in neuronal homeostasis, the mechanistic basis for neurodegeneration when mitophagy is defective is unclear. Here, using human neurons, we discover that presynapses are mitophagy pit stops for damaged axonal mitochondria. We show that while mitochondrial damage and PINK1/Parkin activation events are distributed throughout axons, mitophagy initiation and autophagosome formation are restricted to presynapses, which we show contain the machineries required for mitophagy. Being the primary sites of axonal mitophagy, presynapses were vulnerable when PINK1/Parkin mitophagy was defective. We observed local cytochromecrelease within presynapses from an accumulation of damaged mitochondria. This resulted in downstream degradative caspase activation, defining a mechanism for neurodegeneration. Pharmacological rescue of axon degeneration was achieved through synthetic upregulation of receptor mediated mitophagy with the clinically approved compound Roxadustat, revealing a potential therapeutic avenue for disease.
Effects of multistability, absorbing boundaries and growth on Turing pattern formation
Authors: Oliver Huidobro Martina , Endres Robert G. 
Published: September 2024

AbstractTuring patterns are a fundamental concept in developmental biology, describing how homogeneous tissues develop into self-organized spatial patterns. However, the classical Turing mechanism, which relies on linear stability analysis, often fails to capture the complexities of real biological systems, such as multistability, non-linearities, growth, and boundary conditions. Here, we explore the impact of these factors on Turing pattern formation, contrasting linear stability analysis with numerical simulations based on a simple reaction-diffusion model, motivated by synthetic gene-regulatory pathways. We demonstrate how non-linearities introduce multistability, leading to unexpected pattern outcomes not predicted by the traditional Turing theory. The study also examines how growth and realistic boundary conditions influence pattern robustness, revealing that different growth regimes and boundary conditions can disrupt or stabilize pattern formation. Our findings are critical for understanding pattern formation in both natural and synthetic biological systems, providing insights into engineering robust patterns for applications in synthetic biology.Author summaryDuring development, tissues self-organize to go from a single cell to a structured organism. In this process, simple chemical reactions lead to the emergence of the intricate designs we see in nature, like the stripes on a zebra or the labyrinths on a brain cortex. Although multiple theories have been proposed to model this phenomenon, one of the most simple and popular ones was introduced in the 1950s by the mathematician Alan Turing. However, his theory oversimplifies the biological conditions and ignores properties such as non-linearities, boundary effects, or growth in the tissue. In this work, we used a combination of mathematical models and computer simulations to investigate how these real-world factors influence pattern formation. Our findings show that when we account for these realistic effects, the patterns that emerge can be very different from what Turing’s theory would predict. Thus, this work may help us better understand the laws behind pattern formation and could have practical applications in tissue engineering for medical or environmental applications.
Controlled and polygynous mating in the black soldier fly: advancing breeding programs utilizing quantitative genetic designs
Authors: Jensen K. , Thormose S.F. , Noer N.K. , Schou T.M. , Kargo M. , Gligorescu A. , Nørgaard J.V. , Hansen L.S. , Zaalberg R.M. , Nielsen H.M. , Kristensen T.N. 
Published: September 2024

AbstractIn animal breeding programs, utilizing quantitative genetic designs such as the full-/half-sibling design is fundamental. A full-/half-sibling design demands that mating can be controlled, and individuals can be tracked, enabling construction of a pedigree. In nature, black soldier fly (Hermetia illucensL.) males are reported to gather in lekking groups to engage in competitive displays and courtship rituals before mating, and this lekking behavior is described as crucial for mating in this species. We show that a randomly chosen male and a randomly chosen virgin female can readily mate under LED lights in a small container at 28 °C and 70% RH, demonstrating the ability to mate selected pairs. For males given access to four females, all mated and the time until first mating was considerably shorter than for males given only one female, where 80% of the males mated. Furthermore, when adding four virgin females to a single male, males successfully mated all four females in 52% of cases within our four-hour trial, with 96% of males mating at least twice. Number of matings observed for a male correlated with the number of females from the container that laid an egg clutch, and almost all egg clutches produced offspring. Observed mating thus lead to fertilization, and consecutive matings were with new females resulting in full- and half-sibling offspring. Males with four females that mated a second female did so at a median time of less than three minutes upon ending previous mating, showing that polygynous mating occurred rapidly in this setup. Our findings pave the way for movingH. illucensbreeding programs beyond mass selection towards advanced selective breeding designs where controlled mating is typically required. Such designs enable selection for multiple traits simultaneously while controlling inbreeding and can drastically increase rates of selection responses compared to mass selection.
Automated measurement of cardiomyocyte monolayer contraction using the Exeter Multiscope
Authors: Mohanan Sharika , Horsell David , Watters Taylor , Ghasemi Mohammadreza , Henderson Lewis , Müllenbroich Caroline , Bub Gil , Burton Francis , Smith Godfrey , Corbett Alexander D. 
Published: September 2024

ABSTRACTWe apply a novel microscope architecture, the Exeter Multiscope, to the problem of acquiring image data in rapid succession from nine wells of a 96 well plate. We demonstrate that the new microscope can detect contraction in cardiomyocyte monolayers which have been plated into these wells. Each well is sampled using 500 × 500 pixels across a 1.4 × 1.4 mm field of view, acquired in three colours at 3.7 Hz per well. The use of multiple illumination wavelengths provides post-hoc focus selection, further increasing the level of automation. The performance of the Exeter Multiscope is benchmarked against industry standard methods using a commercial microscope with a motorised stage and demonstrates that the Multiscope can acquire data almost 40 times faster. The data from both Multiscope and the commercial systems are processed by a ‘pixel variance’ algorithm that uses information from the pixel value variability over time to determine the timing and amplitude of tissue contraction. This algorithm is also benchmarked against an existing algorithm that employs an absolute difference measure of tissue contraction.
Protocol for Simulating the Effect of THz Electromagnetic Field on Ion Channels
Authors: Xue Lingfeng , Song Zigang , Ouyang Qi , Song Chen 
Published: September 2024

AbstractTerahertz (THz) electromagnetic fields are increasingly recognized for their crucial roles in various aspects of medical research and treatment. Recent computational studies have demon-strated that THz waves can modulate ion channel function by interacting with either the channel proteins or the bound ions through distinct mechanisms. Here we outline a universal simulation protocol to identify the THz frequencies that may affect ion channels, which consists of frequency spectrum analysis and ion conductance analysis. Following this protocol, we studied the effect of THz field on a CaVchannel and found a broad frequency band in 1 to 20 THz range. We believe that this protocol, along with the identified characteristic frequencies, will provide a theoretical foundation for future terahertz experimental studies.
High-quality peptide evidence for annotating non-canonical open reading frames as human proteins
Authors: Deutsch Eric W , Kok Leron W , Mudge Jonathan M , Ruiz-Orera Jorge , Fierro-Monti Ivo , Sun Zhi , Abelin Jennifer G , Alba M Mar , Aspden Julie L , Bazzini Ariel A , Bruford Elspeth A , Brunet Marie A , Calviello Lorenzo , Carr Steven A , Carvunis Anne-Ruxandra , Chothani Sonia , Clauwaert Jim , Dean Kellie , Faridi Pouya , Frankish Adam , Hubner Norbert , Ingolia Nicholas T , Magrane Michele , Martin Maria Jesus , Martinez Thomas F , Menschaert Gerben , Ohler Uwe , Orchard Sandra , Rackham Owen , Roucou Xavier , Slavoff Sarah A , Valen Eivind , Wacholder Aaron , Weissman Jonathan S , Wu Wei , Xie Zhi , Choudhary Jyoti , Bassani-Sternberg Michal , Vizcaíno Juan Antonio , Ternette Nicola , Moritz Robert L , Prensner John R , van Heesch Sebastiaan 
Published: September 2024

AbstractA major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.