bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automatic analysis of skull thickness, scalp-to-cortex distance and association with age and sex in cognitively normal elderly
Authors: Zhang Junhao , Treyer Valerie , Sun Junfeng , Zhang Chencheng , Gietl Anton , Hock Christoph , Razansky Daniel , Nitsch Roger M. , Ni Ruiqing ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: January 2023

AbstractPersonalized neurostimulation has been a potential treatment for many brain diseases, which requires insights into brain/skull geometry. Here, we developed an open source efficient pipeline BrainCalculator for automatically computing the skull thickness map, scalp-to-cortex distance (SCD), and brain volume based on T1-weighted magnetic resonance imaging (MRI) data. We examined the influence of age and sex cross-sectionally in 407 cognitively normal older adults (71.9±8.0 years, 60.2% female) from the ADNI. We demonstrated the compatibility of our pipeline with commonly used preprocessing packages and found that BrainSuite Skullfinder was better suited for such automatic analysis compared to FSL Brain Extraction Tool 2 and SPM12- based unified segmentation using ground truth. We found that the sphenoid bone and temporal bone were thinnest among the skull regions in both females and males. There was no increase in regional minimum skull thickness with age except in the female sphenoid bone. No sex difference in minimum skull thickness or SCD was observed. Positive correlations between age and SCD were observed, faster in females (0.307%/y) than males (0.216%/y) in temporal SCD. A negative correlation was observed between age and whole brain volume computed based on brain surface (females -1.031%/y, males -0.998%/y). In conclusion, we developed an automatic pipeline for MR-based skull thickness map, SCD, and brain volume analysis and demonstrated the sex-dependent association between minimum regional skull thickness, SCD and brain volume with age. This pipeline might be useful for personalized neurostimulation planning.
Profiling extracellular vesicles in circulation enables the early detection of ovarian cancer
Authors: Jo Ala , Green Allen , Medina Jamie E. , Iyer Sonia , Ohman Anders W. , McCarthy Eric T. , Reinhardt Ferenc , Gerton Thomas , Demehin Daniel , Mishra Ranjan , Kolin David L. , Zheng Hui , Crum Christopher P. , Weinberg Robert A. , Rueda Bo R. , Castro Cesar M. , Dinulescu Daniela M. , Lee Hahko 
Published: January 2023

ABSTRACTOvarian cancer is a heterogeneous group of tumors in both cell type and natural history. While outcomes are generally favorable when detected early, the most common subtype, high-grade serous carcinoma (HGSOC), typically presents at an advanced stage and portends less favorable prognoses. Its aggressive nature has thwarted early detection efforts through conventional detection methods such as serum CA125 and ultrasound screening and thus inspired the investigation of novel biomarkers. Here, we report the systematic development of an extracellular-vesicle (EV)-based test to detect early-stage HGSOC. Our study is based on emerging insights into HGSOC biology, notably that it arises from precursor lesions within the fallopian tube before traveling to ovarian and/or peritoneal surfaces. To identify HGSOC marker candidates, we established murine fallopian tube (mFT) cells with oncogenic mutations inBrca1/2, Tp53, andPtengenes, and performed proteomic analyses on mFT EVs. The identified markers were then evaluated with an orthotopic HGSOC animal model. In serially-drawn blood samples of tumor-bearing mice, mFT-EV markers increased with tumor initiation, supporting their potential use in early cancer detection. A pilot human clinical study (n= 51) further narrowed EV markers to five candidates, EpCAM, CD24, VCAN, HE4, and TNC. Combined expression of these markers achieved high OvCa diagnostic accuracy (cancer vs. non-cancer) with a sensitivity of 0.89 and specificity of 0.93. The same five markers were also effective in a three-group classification: non-cancer, early-stage (I & II) HGSOC, and late-stage (III & IV) HGSOC. In particular, they differentiated early-stage HGSOC from the rest with a specificity of 0.91. Minimally invasive and repeatable, this EV-based testing could be a versatile and serial tool for informing patient care and monitoring women at high risk for ovarian cancer.
Aging reduces motivation through decreasedBdnfexpression in the ventral tegmental area
Authors: Lei Hanyue Cecilia , Parker Kyle E. , Yuede Carla M. , McCall Jordan G. , Imai Shin-ichiro 
Published: January 2023

AbstractAge-associated reduced motivation is a hallmark of neuropsychiatric disorders in the elderly. In our rapidly aging societies, it is critical to keep motivation levels high enough to promote healthspan and lifespan. However, how motivation is reduced during aging remains unknown. Here, we used multiple mouse models to evaluate motivation and related affective states in young and old mice. We also compared the effect of social isolation, a common stressor, to those of aging. We found that both social isolation and aging decreased motivation in mice, but thatBdnfexpression in the ventral tegmental area (VTA) was selectively decreased during aging. Furthermore, VTA-specificBdnfknockdown in young mice recapitulated reduced motivation observed in old mice. These results demonstrate that maintainingBdnfexpression in the VTA could promote motivation to engage in effortful activities and potentially prevent age-associated neuropsychiatric disorders.
A scalable platform for functional interrogation of peptide hormones in fish
Authors: Moses Eitan , Harel Itamar 
Published: January 2023

AbstractFish display a remarkable diversity of life-history traits, including body size, age at maturity, and longevity. Although pituitary hormones are conserved mediators of life-history transitions, regulatory networks are less understood in fish. However, the relatively long life-cycles and germline-dependent maturation of classical fish models are less compatible with rapid exploration of adult physiology, particularly in females. Here, we describe a high-throughput platform that combines, for the first time, loss- and gain-of-function of peptide hormones in a naturally short-lived fish. As a proof-of-principle, we first manipulate growth by mutating growth hormone (gh1) in the turquoise killifish (N. furzeri). Next, to rescue growth defects, we designed a vector in which hormones are tagged by a self-cleavable fluorescent reporter, and are ectopically expressed using intramuscular electroporation. A single injection of agh1-T2A-GFPplasmid was sufficient to produce a stable expression of tag-free hormone and rescue growth phenotypes. This, in contrast to current practice for which multiple injections of recombinant hormones are required. We demonstrate the versatility of our platform by rescuing female sterility, which is induced by manipulating the follicle stimulating hormone (fshb). As killifish maturation is germline-independent, both sexes can be explored in genetic models with germline defects. Finally, we describe a doxycycline-inducible system for tunable expression control. Together, this platform significantly advances the state-of-the-art by allowing high-throughput functional dissection of distinct life-history strategies in fish. This method could be multiplexed to facilitate various applications, including optimizing commercially valuable traits in aquaculture, or screening pro-longevity hormonal interventions in aging.
Gentrius: identifying equally scoring trees in phylogenomics with incomplete data
Authors: Chernomor Olga , Elgert Christiane , von Haeseler Arndt 
Published: January 2023

AbstractPhylogenetic trees are routinely built from huge and yet incomplete multi-locus datasets often leading to phylogenetic terraces – topologically distinct equally scoring trees, which induce the same set of per locus subtrees. As typical tree inference software outputs only a single tree, identifying all trees with identical score challenges phylogenomics. Generating all trees from a terrace requires constructing a so-called stand for the corresponding set of induced locus subtrees. Here, we introduce Gentrius – an efficient algorithm that tackles this problem for unrooted trees. Despite stand generation being computationally intractable, we showed on simulated and biological datasets that Gentrius generates stands with millions of trees in feasible time. Depending on the distribution of missing data across species and loci and the inferred phylogeny, the number of equally optimal terrace trees varies tremendously. The strict consensus tree computed from them displays all the branches unaffected by the pattern of missing data. Thus, Gentrius provides an important systematic assessment of phylogenetic trees inferred from incomplete data. Furthermore, Gentrius can aid theoretical research by fostering understanding of tree space structure imposed by missing data.One-Sentence SummaryGentrius - the algorithm to generate a complete stand, i.e. all binary unrooted trees compatible with the same set of subtrees.
3D printed magneto-active microfiber scaffolds for remote stimulation of 3Din vitroskeletal muscle models
Authors: Cedillo-Servin Gerardo , Dahri Ouafa , Meneses João , van Duijn Joost , Sage Fanny , Silva Joana , Pereira André , Magalhães Fernão D. , Malda Jos , Geijsen Niels , Pinto Artur M. , Castilho Miguel 
Published: January 2023

AbstractTunable culture platforms that guide cellular organization and mechanically stimulate skeletal muscle development are still unavailable due to limitations in biocompatibility and actuation triggered without contact. This study reports the rational design and fabrication of magneto-active microfiber meshes with controlled hexagonal microstructures via melt electrowriting (MEW) of a thermoplastic/graphene/iron oxide composite.In situdeposition of iron oxide nanoparticles on oxidized graphene yielded homogeneously dispersed magnetic particles with sizes above 0.5 μm and low aspect ratio, preventing cellular internalization and toxicity. With these fillers, homogeneous magnetic composites with very high magnetic filler content (up to 10 wt.%) were obtained and successfully processed in a solvent-free manner for the first time. MEW of magnetic composites enabled the skeletal muscle-inspired design of hexagonal scaffolds with tunable fiber diameter, reconfigurable modularity, and zonal distribution of magneto-active and nonactive material. Importantly, the hexagonal microstructures displayed elastic deformability under tension, mitigating the mechanical limitations due to high filler content. External magnetic fields below 300 mT were sufficient to trigger out-of-plane reversible deformation leading to effective end-to-end length decrease up to 17%. Moreover, C2C12 myoblast culture on 3D Matrigel/collagen/MEW scaffolds showed that the presence of magnetic particles in the scaffolds did not significantly affect viability after 8 days with respect to scaffolds without magnetic filler. Importantly,in vitroculture demonstrated that myoblasts underwent differentiation at similar rates regardless of the presence of magnetic filler. Overall, these innovative microfiber scaffolds were proven as a magnetically deformable platform suitable for dynamic culture of skeletal muscle with potential forin vitrodisease modeling.
Pre-training with a rational approach for antibody sequence representation
Authors: Gao Xiangrui , Cao Changling , He Chenfeng , Lai Lipeng 
Published: January 2023

ABSTRACTAntibodies represent a specific class of proteins produced by the adaptive immune system in response to pathogens. Mining the information embedded in antibody amino acid sequences can benefit both antibody property prediction and novel therapeutic development. Protein-specific pre-training models have been used to extract latent representations from protein sequences, structural, functional, and homologous information. However, compared to other proteins, antibodies possess unique features that should be incorporated using specifically designed training methods, so there is still room for improvement in pre-training models for antibody sequences. On the one hand, existing protein pre-training models primarily utilize language models without fully considering the differences between protein sequences and language sequences. In this study, we present a Pre-trained model of Antibody sequences trained with a Rational Approach for antibodies (PARA), which employs a strategy conforming to antibody sequence patterns and an advanced natural language processing self-encoding model structure. We demonstrate PARA’s performance on several tasks by comparing it to various published pre-training models of antibodies. The results show that PARA significantly outperforms existing models on these tasks, suggesting that PARA has an advantage in capturing antibody sequence information. We believe that the antibody latent representation provided by PARA can substantially facilitate studies in relevant areas. PARA is available athttps://github.com/xtalpi-xic.
Experimental and computational analysis of REM sleep distributed cortical activity in mice
Authors: Peuvrier Mathias , Fernandez Laura , Crochet Sylvain , Destexhe Alain , Salin Paul 
Published: January 2023

ABSTRACTAlthough classically Rapid-Eye Movement (REM) sleep is thought to generate desynchronized activity similar to wakefulness, it was found that some brain regions can express Slow Wave activity (SWA), a pattern which is normally typical of slow-wave sleep. To investigate possible underlying mechanisms, we analyze experimental recordings and introduce a computational model of mice cerebral cortex in REM sleep. We characterized the patterns of slow-wave activity across somatosensory and motor areas, and find that the most prominent REM-related SWA is present in the primary (S1) and secondary (S2) somatosensory areas, more rarely seen in motor cortex, and absent from prefrontal cortex or hippocampus. The SWA also tends to be synchronized in S1 and S2. We next investigated possible mechanisms by using a computational model of the mouse brain consisting of adaptive Exponential (AdEx) mean-fields connected together according to the mouse connectome. To compare with experimental data, the local field potential is calculated in each mouse brain region. To reproduce the experiments, we had to assume a heterogeneous level of adaptation in different cortical regions during REM sleep. In these conditions, the model reproduces some of the experimental observations in the somato-motor areas and the other cortical areas. We then used the model to test how the presence of SWA affects cortical responsiveness. Indeed, we find that the areas expressing SWA have diminished evoked responses, which may participate to a diminished responsiveness during REM sleep.
Interaction between mutation type and gene pleiotropy drives parallel evolution in the laboratory
Authors: Ruelens Philip , Wynands Thomas , de Visser J. Arjan G.M. 
Published: January 2023

AbstractWhat causes evolution to be repeatable is a fundamental question in evolutionary biology. Pleiotropy, i.e. the effect of an allele on multiple traits, is thought to enhance repeatability by constraining the number of available beneficial mutations. Additionally, pleiotropy may promote repeatability by allowing large fitness benefits of single mutations via adaptive combinations of phenotypic effects. Yet, this latter evolutionary potential may be reaped solely by specific types of mutations able to realize optimal combinations of phenotypic effects while avoiding the costs of pleiotropy. Here, we address the interaction of gene pleiotropy and mutation type on evolutionary repeatability in a meta-analysis of experimental evolution studies withEscherichia coli. We hypothesize that single-nucleotide polymorphisms are principally able to yield large fitness benefits by targeting highly pleiotropic genes, whereas indels and structural variants provide smaller benefits and are restricted to genes with lower pleiotropy. By using gene connectivity as proxy for pleiotropy, we show that nondisruptive single-nucleotide polymorphisms (SNPs) in highly pleiotropic genes yield the largest fitness benefits, since they contribute more to parallel evolution, especially in large populations, than inactivating SNPs, indels and structural variants. Our findings underscore the importance of considering genetic architecture together with mutation type for understanding evolutionary repeatability.
Cytosolic and mitochondrial translation elongation are coordinated through the molecular chaperone TRAP1 for the synthesis and import of mitochondrial proteins
Authors: Avolio Rosario , Agliarulo Ilenia , Criscuolo Daniela , Sarnataro Daniela , Auriemma Margherita , Pennacchio Sara , Calice Giovanni , Ng Martin Y. , Giorgi Carlotta , Pinton Paolo , Cooperman Barry , Landriscina Matteo , Esposito Franca , Matassa Danilo Swann 
Published: January 2023

ABSTRACTA complex interplay between mRNA translation and cellular respiration has been recently unveiled, but its regulation in humans is poorly characterized in either health or disease. Cancer cells radically reshape both biosynthetic and bioenergetic pathways to sustain their aberrant growth rates. In this regard, we have shown that the molecular chaperone TRAP1 not only regulates the activity of respiratory complexes, behaving alternatively as an oncogene or a tumor suppressor, but also plays a concomitant moonlighting function in mRNA translation regulation. Herein we identify the molecular mechanisms involved, demonstrating that TRAP1: i) binds both mitochondrial and cytosolic ribosomes as well as translation elongation factors, ii) slows down translation elongation rate, and iii) favors localized translation in the proximity of mitochondria. We also provide evidence that TRAP1 is coexpressed in human tissues with the mitochondrial translational machinery, which is responsible for the synthesis of respiratory complex proteins. Altogether, our results show an unprecedented level of complexity in the regulation of cancer cell metabolism, strongly suggesting the existence of a tight feedback loop between protein synthesis and energy metabolism, based on the demonstration that a single molecular chaperone plays a role in both mitochondrial and cytosolic translation, as well as in mitochondrial respiration.
A Generative Model of Memory Construction and Consolidation
Authors: Spens Eleanor , Burgess Neil 
Published: January 2023

AbstractEpisodic memories are (re)constructed, combining unique features with familiar schemas, share neural substrates with imagination, and show schema-based distortions that increase with consolidation. Here we present a computational model in which hippocampal replay (from an autoassociative network) trains generative models (variational autoencoders) in neo-cortex to (re)create sensory experiences via latent variable representations in entorhinal, medial prefrontal, and anterolateral temporal cortices. Simulations show effects of memory age and hippocampal lesions in agreement with previous models, but also provide mechanisms for se-mantic memory, imagination, episodic future thinking, relational inference, and schema-based distortions including boundary extension. The model explains how unique sensory and predict-able conceptual or schematic elements of memories are stored and reconstructed by efficiently combining both hippocampal and neocortical systems, optimising the use of limited hippocam-pal storage for new and unusual information. Overall, we believe hippocampal replay training neocortical generative models provides a comprehensive account of memory construction, ima-gination and consolidation.
A systematic mapping of the genomic and proteomic variation associated with monogenic diabetes
Authors: Kuznetsova Ksenia , Vašíček Jakub , Skiadopoulou Dafni , Molnes Janne , Udler Miriam , Johansson Stefan , Njølstad Pål Rasmus , Manning Alisa , Vaudel Marc 
Published: January 2023

AbstractAimsMonogenic diabetes is characterized as a group of diseases caused by rare variants in single genes. Multiple genes have been described to be responsible for monogenic diabetes, but the information on the variants is not unified among different resources. In this work, we aimed to develop an automated pipeline that collects all the genetic variants associated with monogenic diabetes from different resources, unify the data and translate the genetic sequences to the proteins.MethodsThe pipeline developed in this work is written in Python with the use of Jupyter notebook. It consists of 6 modules that can be implemented separately. The translation step is performed using the ProVar tool also written in Python. All the code along with the intermediate and final results is available for public access and reuse.ResultsThe resulting database had 2701 genomic variants in total and was divided into two levels: the variants reported to have an association with monogenic diabetes and the variants that have evidence of pathogenicity. Of them, 2565 variants were found in the ClinVar database and the rest 136 were found in the literature showing that the overlap between resources is not absolute.ConclusionsWe have developed an automated pipeline for collecting and harmonizing data on genetic variants associated with monogenic diabetes. Furthermore, we have translated variant genetic sequences into protein sequences accounting for all protein isoforms and their variants. This allows researchers to consolidate information on variant genes and proteins associated with monogenic diabetes and facilitates their study using proteomics or structural biology. Our open and flexible implementation using Jupyter notebooks enables tailoring and modifying the pipeline and its application to other rare diseases.Research in contextMonogenic diabetes is a group of Mendelian diseases with an autosomal-dominant pattern of inheritance.Monogenic diabetes is mainly caused by rare genetic variants that are usually evaluated manually.The data on the variants are stored in several resources and are not unified in terms of the genomic coordinates, alleles, and variant annotation.What can be done for the systematic evaluation of the variants and their protein consequences?In this work, we have created an automated Jupyter notebook-based pipeline for the collection and unification of the variants associated with monogenic diabetes.The database of the genetic variants was created and translated to all possible variant protein sequences.These results will be used for the analysis of proteomics data and protein structure modeling.
Minimal impact of proprioceptive loss on implicit sensorimotor adaptation and perceived movement outcome
Authors: Tsay Jonathan S. , Chandy Anisha M. , Chua Romeo , Miall R. Chris , Cole Jonathan , Farnè Alessandro , Ivry Richard B. , Sarlegna Fabrice R. 
Published: January 2023

AbstractImplicit sensorimotor adaptation keeps our movements well-calibrated amid changes in the body and environment. We have recently postulated that implicit adaptation is driven by a perceptual error: the difference between the desired and perceived movement outcome. According to this perceptual re-alignment model, implicit adaptation ceases when the perceived movement outcome – a multimodal percept determined by a prior belief conveying the intended action, the motor command, and feedback from proprioception and vision – is aligned with the desired movement outcome. Here, we examined the role of proprioception in implicit motor adaptation and perceived movement outcome by examining individuals who lack proprioception. We used a modified visuomotor rotation task designed to isolate implicit adaptation and probe perceived outcome throughout the experiment. Surprisingly, implicit adaptation and perceived outcome were minimally impacted by deafferentation, posing a challenge to the perceptual re-alignment model of implicit adaptation.