bluuebunny/crossref_metadata_2025_split huggingface dataset:
scifAI: Explainable machine learning for profiling the immunological synapse and functional characterization of therapeutic antibodies
Authors: Boushehri Sayedali Shetab , Essig Katharina , Chlis Nikolaos-Kosmas , Herter Sylvia , Bacac Marina , Theis Fabian J , Glasmacher Elke , Marr Carsten , Schmich Fabian 
Published: October 2022

AbstractTherapeutic antibodies are widely used to treat severe diseases. Most of them alter immune cells and act within the immunological synapse; an essential cell-to-cell interaction to direct the humoral immune response. Although many antibody designs are generated and evaluated, a high-throughput tool for systematic antibody characterization and prediction of function is lacking. Here, we introduce the first comprehensive open-source framework, scifAI (single-cell imaging flow cytometry AI), for preprocessing, feature engineering and explainable, predictive machine learning on imaging flow cytometry (IFC) data. Additionally, we generate the largest publicly available IFC data set of the human immunological synapse containing over 2.8 million images. Using scifAI, we analyze class frequency- and morphological changes under different immune stimulation. T cell cytokine production across multiple donors and therapeutic antibodies is quantitatively predictedin vitro,linking morphological features with function and demonstrating the potential to significantly impact antibody design. scifAI is universally applicable to IFC data. Given its modular architecture it is straightforward to incorporate into existing workflows and analysis pipelines, e.g. for rapid antibody screening and functional characterization.
Heavy metal pollution characteristics of soil around a copper-nickel mine tailings pond in the northwest arid area of China and evaluation of desert phytoremediation potential
Authors: Shi Jianfei , Jin Zhengzhong , Zhou Zhibin , Wang Xin , Yang Xiaoliang , Qian Wenting 
Published: October 2022

ABSTRACTPhytoextraction and phytostabilization are two mechanisms used by plants to remove and stabilize heavy metals in soil. However, there has been little research on the extraction/stabilization of heavy metals by desert plants in arid areas. This study analyzed eight heavy metals (Cr, Ni, Cu, Zn, Cd, Pb, Mn, and As) in 10 desert plants and their growth matrices. In addition, the single factor pollution index and Nemerow comprehensive pollution index were used to evaluate soil pollution. Based on the biological accumulation factor and the biological concentration factor, the fuzzy evaluation method was used to evaluate plant extraction/stability potentials for heavy metals. The results showed that Cd, Cu, Ni, and Cr in the soil around the tailings pond were at the heavy pollution level, Mn and Pb pollution was moderate, and Zn and As pollution was light. The matrix factorization model showed that Cu and Ni came from industrial pollution; Cd and Cr came from atmospheric deposition and agricultural pollution; Pb came from traffic pollution; and Mn, Zn, and As came from natural sources. The metal contents of the desert plants exceeded the standard for normal plants, of which Cr contents in theAtriplex patensandAmmophila breviligulataFernald aboveground parts were 35.63 and 53.77 mg/kg respectively, and the Ni contents in theKlasea centauroidessubsp.polycephala(Iljin) L. Martins underground parts and theA. breviligulataFernald aboveground parts were 102.67 and 101.67 mg/kg, respectively, exceeding the maximum toxicity threshold for Cr and Ni.Ammophila breviligulataFernald had the highest plant comprehensive extraction coefficient (CEI) and plant comprehensive stability coefficient (CSI) at 0.81 and 0.83 respectively, indicating that it has strong heavy metal extraction and stabilization abilities. Therefore,A. breviligulataFernald can be selected as a remediation species for heavy metal pollution in the soil around tailings reservoir areas.
Episodic long-term memory formation during slow-wave sleep
Authors: Schmidig Flavio J. , Ruch Simon , Henke Katharina 
Published: October 2022

SummaryWe are unresponsive during slow-wave sleep but continue monitoring external events for survival. Our brain wakens us when danger is imminent. If events are non-threatening, our brain might store them for later consideration to improve decision-making. To test this hypothesis, we examined whether novel vocabulary consisting of simultaneously played pseudowords and translation words are encoded/stored during sleep, and which neural-electrical events facilitate encoding/storage. An algorithm for brain-state dependent stimulation selectively targeted word pairs to slow-wave peaks or troughs. Retrieval tests were given 12 and 36 hours later. These tests required decisions regarding the semantic category of previously sleep-played pseudowords. The sleep-played vocabulary influenced awake decision-making 36 hours later, if targeted to troughs. The words’ linguistic processing raised neural complexity. The words’ semantic-associative encoding was supported by increased theta power during the ensuing peak. Fast-spindle power ramped up during a second peak likely aiding consolidation. Hence, new vocabulary played during slow-wave sleep was stored and influenced decision-making days later.
SDRAP for annotating scrambled or rearranged genomes
Authors: Braun Jasper , Neme Rafik , Feng Yi , Landweber Laura F. , Jonoska Nataša 
Published: October 2022

AbstractDNA rearrangements are important in various contexts, such as in vertebrate immunity, and cancer genome instability. The single-celled eukaryoteOxytricha trifallaxundergoes massive and reproducible genome rearrangement during post-zygotic development, making it a compelling model organism to study DNA rearrangements. To date, computational tools for the extraction and analysis of rearrangement annotations lack transparency and rely on assumptions that may not hold for all analyzed data, leading to irreproducibility of results and loss of information through data filtering or misrepresentation.An implementation of a procedure for the annotation and analysis of DNA rearrangement as a web application is discussed and tested. The resulting annotations provide an improvement over previous annotations in the following manner. (a) SDRAP achieves more complete precursor-product mappings than previous software (b) the software allows for full transparency of all parameters used during the annotation and therefore facilitates reproducible results, and (c) this parameter transparency makes SDRAP suitable for comparison of genomic data from different sources, including cancer genomes.This work introduces a theoretical framework and software to systematically extract and analyze annotations from pairs of genome assemblies corresponding to precursor and product rearrangement data. The software makes no assumptions about the structure of the rearrangements, and permits the user to select parameters to suit the data.
Reward modulates visual responses in the superficial superior colliculus of mice
Authors: Baruchin Liad J. , Alleman Matteo , Schröder Sylvia 
Published: October 2022

AbstractThe superficial layers of the superior colliculus (SC) are highly visual and receive direct input from the retina. Nonetheless, neural activity in the superficial SC (sSC) is modulated by locomotion and pupil-linked arousal. Here we show that visual responses of neurons in the sSC are additionally modulated by reward delivered prior to the visual stimulus. We trained mice to perform a visual detection task and recorded the activity of neurons in the SC using two-photon calcium imaging and electrophysiological recordings using high-density silicone probes (Neuropixels). Neurons across all layers of the SC responded to various task events, including reward delivery. However, responses to events like licking or movements did not explain the visual response modulation by reward. Electrophysiological recordings showed that most of the reward modulation occurred in the superficial rather than the deeper layers of the SC. Neurons also exhibited modulation by pupil-linked arousal, which was independent of the reward modulation. Performance of a population decoder to detect visual stimuli improved significantly by reward modulation but not by pupil-linked arousal modulation. Our results indicate that behavioural factors other than locomotion and arousal modulate visual activity in the SC.
Part-night exposure to artificial light at night has more detrimental effects on aphid colonies than fully lit nights
Authors: Heinen Robin , Sanchez-Mahecha Oriana , Bezemer T. Martijn , Dominoni Davide M. , Knappe Claudia , Kollmann Johannes , Kopatsch Anton , Pfeiffer Zoë A. , Schloter Michael , Sturm Sarah , Schnitzler Jörg-Peter , Vlot A. Corina , Weisser Wolfgang W. 
Published: October 2022

AbstractArtificial light at night (ALAN) threatens natural ecosystems globally. While ALAN research is increasing, little is known about how ALAN affects plants and interactions with other organisms. We explored the effects of ALAN on plant defence and plant–insect interactions using barley (Hordeum vulgare) and the English grain aphid (Sitobion avenae). Plants were exposed to ‘full’ or ‘part’ nights of 15–20 lux ALAN, or no ALAN ‘control’ nights, to test the effects of ALAN on plant growth and defence. Although plant growth was only minimally affected by ALAN, aphid colony growth and aphid maturation were reduced significantly by ALAN treatments. Importantly, we found strong differences between full-night and part-night ALAN treatments. Contrary to our expectations, part ALAN had stronger negative effects on aphid colony growth than full ALAN. Defence-associated gene expression was affected in some cases by ALAN, but also positively correlated with aphid colony size, suggesting that the effects of ALAN on plant defences are indirect, and regulated via direct disruption of aphid colonies, rather than via ALAN-induced upregulation of defences. Mitigating ecological side effects of ALAN is a complex problem, as reducing exposure to ALAN increased its negative impact on insect herbivores.
ISPRED-SEQ: Deep neural networks and embeddings for predicting interaction sites in protein sequences
Authors: Manfredi Matteo , Savojardo Castrense , Martelli Pier Luigi , Casadio Rita 
Published: October 2022

AbstractThe knowledge of protein-protein interaction sites (PPIs) is crucial for protein functional annotation. Here we address the problem focusing on the prediction of putative PPIs having as input protein sequences. The problem is important given the huge volume of sequences compared to experimental and/or computed protein structures. Taking advantage of recently developed protein language models and Deep Neural networks here we describe ISPRED-SEQ, which overpasses state-of-the-art predictors addressing the same problem. ISPRED-SEQ is freely available for testing athttps://ispredws.biocomp.unibo.it.
Eliminate false positives in metagenomic profiling based on type IIB restriction sites
Authors: Sun Zheng , Liu Jiang , Zhang Meng , Wang Tong , Huang Shi , Weiss Scott T. , Liu Yang-Yu 
Published: October 2022

AbstractAccurate species identification and abundance estimation are critical for the interpretation of whole metagenome shotgun sequencing (WMS) data. Numerous computational methods, broadly referred to as metagenomic profilers, have been developed to identify species in microbiome samples by classification of sequencing reads and quantification of their relative abundances. Yet, existing metagenomic profilers typically suffer from false positive identifications and consequently biased relative abundance estimation (as false positives can be accounted for more than 90% of total identified species). Here, we present a new metagenomic profiler MAP2B (MetAgenomicProfiler based on typeIIBrestriction site) to resolve those issues. We first illustrate the pitfalls of using relative abundance as the only feature in determining false positives. We then propose a feature set to distinguish false positives from true positives. By benchmarking the performance in metagenomic profiling using data from CAMI2 (Critical Assessment of Metagenome Interpretation: second round of challenge), we illustrate the superior performance of MAP2B (F1 score ~ 0.93) over existing metagenomic profilers (F1 score ranges from 0.18 to 0.58). We further tested the performance of MAP2B using real WMS data from an ATCC mock community, confirming its superior performance and robustness against sequencing depth. In addition, by leveraging WMS data from an IBD cohort, we demonstrate the taxonomic features obtained by MAP2B can better discriminate disease status and predict metabolomic profiles.
Single-cell analysis of prenatal and postnatal human cortical development
Authors: Velmeshev Dmitry , Perez Yonatan , Yan Zihan , Valencia Jonathan E. , Castaneda-Castellanos David R. , Wang Li , Schirmer Lucas , Mayer Simone , Wick Brittney , Wang Shaohui , Nowakowski Tomasz Jan , Paredes Mercedes , Huang Eric J , Kriegstein Arnold R 
Published: October 2022

AbstractWe analyze more than 700,000 single-nucleus RNA-seq profiles from 106 donors during prenatal and postnatal developmental stages and identify lineage-specific programs that underlie the development of specific subtypes of excitatory cortical neurons, interneurons, glial cell types and brain vasculature. By leveraging single-nucleus chromatin accessibility data, we delineate enhancer-gene regulatory networks and transcription factors that control commitment of specific cortical lineages. By intersecting our results with genetic risk factors for human brain diseases, we identify the cortical cell types and lineages most vulnerable to genetic insults of different brain disorders, especially autism. We find that lineage-specific gene expression programs upregulated in female cells are especially enriched for the genetic risk factors of autism. Our study captures the molecular progression of cortical lineages across human development.One Sentence SummarySingle-cell transcriptomic atlas of human cortical development identifies lineage and sex-specific programs and their implication in brain disorders.
Jag1 Insufficiency Disrupts Neonatal T Cell Differentiation and Impairs Hepatocyte Maturation, Leading to Altered Liver Fibrosis
Authors: Mašek Jan , Filipovic Iva , Hul Noémi Van , Belicová Lenka , Jiroušková Markéta , Oliveira Daniel V. , Frontino Anna Maria , Hankeova Simona , He Jingyan , Turetti Fabio , Iqbal Afshan , Červenka Igor , Sarnová Lenka , Verboven Elisabeth , Brabec Tomáš , Björkström Niklas K. , Gregor Martin , Dobeš Jan , Andersson Emma R. 
Published: October 2022

ABSTRACTFibrosis is a physiological tissue repair mechanism, but excessive fibrosis can disrupt organ function. Alagille syndrome (ALGS), which is caused by mutations in the Notch ligandJAGGED1, results in bile duct paucity, neonatal cholestasis, and a characteristic fibrotic response. Here, we show thatJag1Ndr/Ndrmice, a model for ALGS, recapitulates ALGS-like pericellular fibrosis. Single-cell RNA-seq and multi-color flow cytometry characterization of the liver and spleen revealed immature hepatocytes and paradoxically low intrahepatic T cell infiltration in cholestaticJag1Ndr/Ndrmice, despite an enrichment in extrahepatic (thymic and splenic) regulatory T cells (Tregs).Jag1Ndr/Ndrlymphocyte immune and fibrotic capacity was tested with adoptive immune cell transplantation intoRag1-/-mice, challenged with dextran sulfate sodium (DSS) or bile duct ligation (BDL). TransplantedJag1Ndr/Ndrlymphocytes were less inflammatory with fewer activated T cells thanJag1+/+lymphocytes, in response to DSS. Cholestasis induced by BDL inRag1-/-mice withJag1Ndr/Ndrlymphocytes resulted in periportal Treg accumulation and three-fold less periportal fibrosis than inRag1-/-mice withJag1+/+lymphocytes. Finally, we show that theJag1Ndr/Ndrhepatocyte expression profile and Treg overrepresentation are corroborated by transcriptomic data from children with ALGS. In sum, these data lead to a model in which Jag1-driven developmental hepatic and immune defects interact to determine the fibrotic process in ALGS.
State-dependent, visually-guided behaviors in the nudibranchBerghia stephanieae
Authors: Quinlan Phoenix D. , Katz Paul S. 
Published: October 2022

AbstractNudibranch molluscs have structurally simple eyes whose behavioral roles have not been established. We tested the effects of visual stimuli on the behavior of the nudibranchBerghia stephanieaeunder different food and hunger conditions. In an arena that was half shaded, animals spent most of their time in the dark, where they also decreased their speed and made more changes in heading. These behavioral differences between the light and dark were less evident in uniformly illuminated or darkened arenas, suggesting that they were not caused by the level of illumination.Berghiaresponded to distant visual targets; animals approached a stripe that was at least 15° wide and 50% darker than the background. They did not approach a stripe that was lighter than the background but approached a stripe that was isoluminant with the background, suggesting the detection of spatial information. Animals travelled in convoluted paths in a featureless arena but straightened their paths when a visual target was present even if they did not approach it, suggesting that visual cues were used for navigation. Individuals were less responsive to visual stimuli when food-deprived or in the presence of a food odor. Furthermore, when given a food odor, they had a weaker preference for the dark and behaved similarly in the light and dark. Thus,Berghiaexhibits visually-guided behaviors that are influenced by odors and hunger state.Summary statementBehavioral analyses demonstrate that the nudibranchBerghia stephanieaeis capable of spatial vision and has visually-guided behaviors that are influenced by olfactory information and hunger state.
3D Digitizing An Animal Organ Could Make It Possible To Work With Anatomy Classes In The Metaverse Or With A 3D-Printed Real-Scale Organ On Demand
Authors: Sumer Dogasav , Ozten Onat , Gungor Mert , Yilmaz Meryem , Nart Ismail , Tastan Cihan 
Published: October 2022

ABSTRACTOrgan scanning is not a novel technology but the unique part of this study is to eliminate the need for expensive devices by using free iOS/Android applications. The apps allow users to create high-quality 3D models from photos taken with a phone or tablet. Metaverse and 3D digitization are the future of technology. Implementation of these approaches into the anatomy can change education style. Also, 3D printing technology along with the digitization of real-sized organs enables researchers and clinicians to study with 3D printed organs in class, even with augmented reality glasses. In this study, we first aimed to 3D digitized an animal organ with its real sizes to print in a 3D printer. Next, we wanted to digitize decellularized form of the organ, which suggests researchers study extracellular matrix and vascularization. This digitization of the different organ forms can improve the progression of artificial organ studies. Free and easy-to-use iOS or Android applications for 3D digitization enable medical students to study not only animal organs but cadavers. Hereby, we are suggesting organ scanning can be done on a daily basis in a standard laboratory. It is aimed to enable medical students to work effectively in anatomy lessons in Metaverse or in real cases, thanks to the anatomical library created with the accessibility brought by easy usability.
Cell cycle alterations associate with a redistribution of mutation rates across chromosomal domains in human cancers
Authors: Salvadores Marina , Supek Fran 
Published: October 2022

AbstractSomatic mutations in human cells have a highly heterogeneous genomic distribution, with increased burden in late-replication time (RT), heterochromatic domains of chromosomes. This regional mutation density (RMD) landscape is known to vary between cancer types, in association with tissue-specific RT or chromatin organization. Here, we hypothesized that regional mutation rates additionally vary between individual tumors in a manner independent of cell type, and that recurrent alterations in DNA replication programs and/or chromatin organization may underlie this. Here, we identified various RMD signatures that describe a global genome-wide mutation redistribution across many megabase-sized domains in >4000 tumors. We identified two novel global RMD signatures of somatic mutation landscapes that were universally observed across various cancer types. First, we identified a mutation rate redistribution preferentially affecting facultative heterochromatin, Polycomb-marked domains, and enriched in subtelomeric regions. This RMD signature strongly reflects regional plasticity in DNA replication time and in heterochromatin domains observed across tumors and cultured cells, which was linked with a stem-like phenotype and a higher expression of cell cycle genes. Consistently, occurrence of this global mutation pattern in cancers is associated with altered cell cycle control via loss of activity of theRB1tumor suppressor gene. Second, we identified another independant global RMD signature associated with loss-of-function of theTP53pathway, mainly affecting the redistribution of mutation rates away from late RT regions. The local mutation supply towards 26%-75% cancer driver genes is altered in the tumors affected by the global RMD signatures detected herein, including additionally a known pattern of a general loss of mutation rate heterogeneity due to DNA repair failures that we quantify. Our study highlights that somatic mutation rates at the domain scale are variable across tumors in a manner associated with loss of cell cycle control viaRB1orTP53, which may trigger the local remodeling of chromatin state and the RT program in cancers.
Genes vary greatly in their propensity for collateral fitness effects of mutations
Authors: Mehlhoff Jacob D. , Ostermeier Marc 
Published: October 2022

AbstractMutations can have deleterious fitness effects when they decrease protein specific activity or decrease active protein abundance. Mutations will also be deleterious when they cause misfolding or misinteractions that are toxic to the cell (i.e., independent of whether the mutations affect specific activity and abundance). The extent to which protein evolution is shaped by these and other collateral fitness effects is unclear in part because little is known of their frequency and magnitude. Using deep mutational scanning (DMS), we previously found at least 42% of missense mutations in theTEM-1β-lactamase antibiotic resistance gene cause deleterious collateral fitness effects. Here, we used DMS to comprehensively determine the collateral fitness effects of missense mutations in three genes encoding the antibiotic resistance proteins New Delhi metallo-β-lactamase (NDM-1), chloramphenicol acetyltransferase I (CAT-I), and 2”-aminoglycoside nucleotidyltransferase (AadB).AadB(20%),CAT-I(0.9%), andNDM-1 (0.2%) were less susceptible to deleterious collateral fitness effects thanTEM-1(42%) indicating that genes have different propensities for these effects. As was observed withTEM-1, all the studied deleteriousaadBmutants increased aggregation. However, aggregation did not correlate with collateral fitness effects for many of the deleterious mutants ofCAT-IandNDM-1. Select deleterious mutants caused unexpected phenotypes to emerge. The introduction of internal start codons inCAT-1caused loss of the episome and a mutation inaadBmade its cognate antibiotic essential for growth. Our study illustrates how the complexity of the cell provides a rich environment for collateral fitness effects and new phenotypes to emerge.