bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inferring personal intake recommendations of phosphorous and potassium for end-stage renal failure patients by simulating with Bayesian hierarchical multivariate model
Authors: Turkia Jari , Schwab Ursula , Hautamäki Ville 
Published: August 2023

AbstractMost end-stage renal disease (ESRD) patients face a risk of malnutrition, partly due to dietary restrictions on phosphorous and, in some cases, potassium intake. These restrictions aim to regulate plasma phosphate and potassium concentrations and prevent the adverse effects of hyperphosphatemia or hyperkalemia. However, individual responses to nutrition are known to vary, highlighting the need for personalized recommendations rather than relying solely on general guidelines. In this study, our objective was to develop a Bayesian hierarchical multivariate model that estimates the individual effects of nutrients on plasma concentrations and to present a recommendation algorithm that utilizes this model to infer personalized dietary intakes capable of achieving normal ranges for all considered concentrations. Considering the limited research on the reactions of ESRD patients, we collected dietary intake data and corresponding laboratory analyses from a cohort of 37 patients. The collected data were used to estimate the common hierarchical model, from which personalized models of the patients’ diets and individual reactions were extracted. The application of our recommendation algorithm revealed substantial variations in phosphorus and potassium intakes recommended for each patient. These personalized recommendations deviate from the general guidelines, suggesting that a notably richer diet may be proposed for certain patients to mitigate the risk of malnutrition. Furthermore, all the participants underwent either hospital, home, or peritoneal dialysis treatments. We explored the impact of treatment type on nutritional reactions by incorporating it as a nested level in the hierarchical model. Remarkably, this incorporation improved the fit of the nutritional effect model by a notable reduction in the normalized root mean square error (NRMSE) from 0.078 to 0.003. These findings highlight the potential for personalized dietary modifications to optimize nutritional status, enhance patient outcomes, and mitigate the risk of malnutrition in the ESRD population.
Key variants via Alzheimer’s Disease Sequencing Project whole genome sequence data
Authors: Wang Yanbing , Sarnowski Chloé , Lin Honghuang , Pitsillides Achilleas N , Heard-Costa Nancy L , Choi Seung Hoan , Wang Dongyu , Bis Joshua C , Blue Elizabeth E ,   Alzheimer’s Disease Neuroimaging Initiative (ADNI), Boerwinkle Eric , De Jager Philip L , Fornage Myriam , Wijsman Ellen M , Seshadri Sudha , Dupuis Josée , Peloso Gina M , DeStefano Anita L ,   Alzheimer’s Disease Sequencing Project (ADSP)
Published: August 2023

AbstractINTRODUCTIONGenome-wide association studies (GWAS) have identified loci associated with Alzheimer’s disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci.METHODSWe performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases=2,184, N controls=2,383) and targeted analyses in sub-populations using WGS data from the Alzheimer’s Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants.RESULTSSeventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses.DISCUSSIONThis study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.
Encyclopaedia of family A DNA polymerases localized in organelles: Evolutionary contribution of bacteria including the proto-mitochondrion
Authors: Harada Ryo , Hirakawa Yoshihisa , Yabuki Akinori , Kim Eunsoo , Yazaki Euki , Kamikawa Ryoma , Nakano Kentaro , Eliáš Marek , Inagaki Yuji 
Published: August 2023

AbstractDNA polymerases (DNAPs) synthesize DNA from deoxyribonucleotides in a semi-conservative manner and serve as the core of DNA replication and repair machineries. In eukaryotic cells, there are two genome-containing organelles, mitochondria and plastids, that were derived from an α-proteobacterium and a cyanobacterium, respectively. Except for rare cases of genome-lacking mitochondria and plastids, both organelles must be served by nucleus-encoded DNAPs that localize and work in them to maintain their genomes. The evolution of organellar DNAPs has yet to be fully understood because of two unsettled issues. First, the diversity of organellar DNAPs has not been elucidated in the full spectrum of eukaryotes. Second, it is unclear when the DNAPs that were used originally in the endosymbiotic bacteria giving rise to mitochondria and plastids were discarded, as the organellar DNAPs known to date show no phylogenetic affinity to those of the extant α-proteobacteria or cyanobacteria. In this study, we identified from diverse eukaryotes 134 family A DNAP sequences, which were classified into 10 novel types, and explored their evolutionary origins. The subcellular localizations of selected DNAPs were further examined experimentally. The results presented here suggest that the diversity of organellar DNAPs has been shaped by multiple transfers of the PolIgene from phylogenetically broad bacteria, and their occurrence in eukaryotes was additionally impacted by secondary plastid endosymbioses. Finally, we propose that the last eukaryotic common ancestor may have possessed two mitochondrial DNAPs, POP and a candidate of the direct descendant of the proto-mitochondrial DNAP, rdxPolA, identified in this study.
Chlorpheniramine Maleate Displays Multiple Modes of Antiviral Action Against SARS-CoV-2: A Mechanistic Study
Authors: Elshaier Yaseen A. M. M. , Mostafa Ahmed , Valerio-Pascua Fernando , Tesch Mari L. , Costin Joshua M. , Rahaghi Franck F. 
Published: August 2023

AbstractChlorpheniramine Maleate (CPM) has been identified as a potential antiviral compound against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). In this study, we investigated the in vitro effects of CPM on key stages of the SARS-CoV-2 replication cycle, including viral adsorption, replication inhibition, and virucidal activity. Our findings demonstrate that CPM exhibits antiviral properties by interfering with viral adsorption, replication, and directly inactivating the virus. Molecular docking analysis revealed interactions between CPM and essential viral proteins, such as the main protease receptor, spike protein receptor, and RNA polymerase. CPM’s interactions were primarily hydrophobic in nature, with an additional hydrogen bond formation in the RNA polymerase active site. These results suggest that CPM has the potential to serve as a multitarget antiviral agent against SARS-CoV-2 and potentially other respiratory viruses. Further investigations are warranted to explore its clinical implications and assess its efficacy in vivo.
3D Printed Ti3C2TxMXene/PCL Scaffolds for Guided Neuronal Growth and Photothermal Stimulation
Authors: Li Jianfeng , Hashemi Payam , Liu Tianyi , Dang Ka My , Brunk Michael G.K. , Mu Xin , Nia Ali Shaygan , Sacher Wesley D. , Feng Xinliang , Poon Joyce K. S. 
Published: August 2023

AbstractThe exploration of neural circuitry is essential for understanding the computational mechanisms and physiology of the brain. Despite significant advances in materials and fabrication techniques, controlling neuronal connectivity and response in three dimensions continues to present a formidable challenge. Here, we present a method for engineering the growth of three-dimensional (3D) neural circuits with the capability for optical stimulation. We fabricated bioactive interfaces by melt electrospinning writing (MEW) of 3D printed polycaprolactone (PCL) scaffolds followed by coating with titanium carbide (Ti3C2TxMXene). Beyond enhancing hydrophilicity, cell adhesion, and electrical conductivity, the Ti3C2TxMXene coating enabled optocapacitance-based neuronal stimulation due to illumination-induced local temperature increases. This work presents a strategy for additive manufacturing of neural tissues with optical control for functional tissue engineering and neural circuit computation.
XVir: A Transformer-Based Architecture for Identifying Viral Reads from Cancer Samples
Authors: Consul Shorya , Robertson John , Vikalo Haris 
Published: August 2023

ABSTRACTIt is estimated that approximately 15% of cancers world-wide can be linked to viral infections. The viruses that can cause or increase the risk of cancer include human papillomavirus, hepatitis B and C viruses, Epstein-Barr virus, and human immunodeficiency virus, to name a few. The computational analysis of the massive amounts of tumor DNA data, whose collection is enabled by the recent advancements in sequencing technologies, have allowed studies of the potential association between cancers and viral pathogens. However, the high diversity of oncoviral families makes reliable detection of viral DNA difficult and thus, renders such analysis challenging. In this paper, we introduce XVir, a data pipeline that relies on a transformer-based deep learning architecture to reliably identify viral DNA present in human tumors. In particular, XVir is trained on genomic sequencing reads from viral and human genomes and may be used with tumor sequence information to find evidence of viral DNA in human cancers. Results on semi-experimental data demonstrate that XVir is capable of achieving high detection accuracy, generally outperforming state-of-the-art competing methods while being more compact and less computationally demanding.CCS CONCEPTS•Computer systems organization→Embedded systems;Redundancy; Robotics; •Networks→ Network reliability.ACM Reference FormatShorya Consul, John Robertson, and Haris Vikalo. 2023. XVir: A Transformer-Based Architecture for Identifying Viral Reads from Cancer Samples. InProceedings of The Eighth International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC ’23). ACM, New York, NY, USA, 8 pages.
Viscosity Prediction of High-Concentration Antibody Solutions with Atomistic Simulations
Authors: Prass Tobias M. , Garidel Patrick , Blech Michaela , Schäfer Lars V. 
Published: August 2023

AbstractThe computational prediction of the viscosity of dense protein solutions is highly desirable, for example in the early development phase of high-concentration biophar-maceutical formulations where the material needed for experimental determination is typically limited. Here, we use large-scale atomistic molecular dynamics (MD) simulations with explicit solvent tode novopredict the dynamic viscosities of solutions of a monoclonal IgG1 antibody (mAb) from the pressure fluctuations using a Green-Kubo approach. The viscosities at simulated mAb concentrations of 200 mg/ml and 250 mg/ml are compared to the experimental values, which we measured with rotational rheometry. The computational viscosity of 24 mPa s at a mAb concentration of 250 mg/ml matches the experimental value of 23 mPa s obtained at a concentration of 213 mg/ml, indicating slightly different effective concentrations (or activities) in the MD simulations and in the experiments. This difference is assigned to a slight underestimation of the effective mAb-mAb interactions in the simulations, leading to a too loose dynamic mAb network that governs the viscosity. Taken together, the present study demonstrates the feasibility of all-atom MD simulations for predicting the properties of dense mAb solutions and provides detailed microscopic insights into the underlying molecular interactions. At the same time, it also shows that there is room for further improvements and highlights challenges, such as the massive sampling required for computing collective properties of dense biomolecular solutions in the high-viscosity regime with reasonable statistical precision.TOC Graphic
Multi-species benchmark analysis for LC-MS/MS validation and performance evaluation in bottom-up proteomics
Authors: Jumel Tobias , Shevchenko Andrej 
Published: August 2023

ABSTRACTWe present an instrument-independent benchmarking procedure and software (LFQ_bout) for validation and comparative evaluation of the performance of LC-MS/MS and data processing workflows in bottom-up proteomics. It enables back-to-back comparison of common and emerging workflows, e.g. diaPASEF or ScanningSWATH, and evaluates the impact of arbitrary, inadequately documented settings or black-box data processing algorithms. The procedure enhances the overall performance and quantitative accuracy while enabling the detection of major error types.
On the Genetic Origins of Phenotypes in Genome-Wide Association Studies: The SNP Allocation For Estimating Heritability (SAFE-h2) Tool to Explore Additive-only Allelic Effects or Additive and Non-Additive Allelic Effects
Authors: Darbani Behrooz , Nicolaisen Mogens 
Published: August 2023

AbstractPolygenicity requires the inclusion of all SNPs to ensure accurate estimation of SNP heritability. However, SNPs with large associationp-values should be excluded, as they impose biologically meaningless negative contributions to heritability estimates. This is demonstrated with simulated data and validated using real-world datasets. We introduce SAFE-h2as a solution to this dilemma. SAFE-h2performs heritability profiling and establishes ap-value threshold to filter out SNPs with negative contributions. By examining 74 phenotypes across eight species, SAFE-h2revealed an average negative contribution of 30 units, imposed by SNPs from the upper-bounds ofp-value thresholds. SAFE-h2also provides a safep-value interval to minimize false-positive SNP hits and facilitates capturing intra-locus (Ref-alleleSNPi×Ref-alleleSNPi,Ref- alleleSNPi×Alt-alleleSNPi, andAlt-alleleSNPi×Alt-alleleSNPi) additive and non-additive effects within the framework of linear models. The allelic adjustment algorithm of SAFE-h2revealed considerable uncaptured phenotypic variance when relying on additive effects and improved the SNP heritability estimations up to 56 units for 50 phenotypes in six species.
SQUARNA - an RNA secondary structure prediction method based on a greedy stem formation model
Authors: Bohdan Davyd R. , Nikolaev Grigory I. , Bujnicki Janusz M. , Baulin Eugene F. 
Published: August 2023

ABSTRACTNon-coding RNAs play a diverse range of roles in various cellular processes, with their spatial structure being pivotal to their function. The RNA’s secondary structure is a key determinant of its overall fold. Given the scarcity of experimentally determined RNA 3D structures, understanding the secondary structure is vital for discerning the molecule’s function. Currently, there is no universally effective solution for de novo RNA secondary structure prediction. Existing methods are becoming increasingly complex without marked improvements in accuracy, and they often overlook critical elements such as pseudoknots. In this work, we introduce SQUARNA, a novel approach to de novo RNA secondary structure prediction. This method utilizes a simple, greedy stem formation model, addressing many of the limitations inherent in previous tools. Our benchmarks demonstrate that SQUARNA matches the performance of leading methods for single sequence inputs and significantly surpasses existing tools when applied to sequence alignment inputs.
Ancient farmer and steppe pastoralist-related founding lineages contributed to the complex landscape of episodes in the diversification of Chinese paternal lineages
Authors: Wang Mengge , Huang Yuguo , Liu Kaijun , Yuan Haibing , Duan Shuhan , Wang Zhiyong , Wei Lanhai , Yao Hongbing , Sun Qiuxia , Zhong Jie , Tang Renkuan , Chen Jing , Sun Yuntao , Li Xiangping , Su Haoran , Yang Qingxin , Hu Liping , Yun Libing , Yang Junbao , Nie Shengjie , Cai Yan , Yan Jiangwei , Zhou Kun ,   10K_CPGDP Consortium, Wang Chuanchao , Zhu Bofeng , Liu Chao , He Guanglin 
Published: August 2023

AbstractAncient DNA advances have reported the complex genetic history of Eurasians, but how the knowledge of ancient subsistence strategy shifts and population movements influenced the fine-scale paternal genetic structure in East Asia has not been assessed. Here, we reported one integrated Y-chromosome genomic database of 15,530 people, including 1753 ancient people and newly-reported 919 individuals genotyped using our recently-developed targeted sequencing YHSeqY3000 panel, to explore Chinese genomic diversity, population evolutionary tracts and their genetic formation mechanism. We identified four major ancient technological innovations and population movements that shaped the landscape of Chinese paternal lineages. First, the expansion of millet farmers and early East Asians from the Yellow River Basin carrying the major O2/D subclades promoted the formation of the Sino-Tibetan people’s major composition and accelerated the Tibetan Plateau’s permanent occupation. Second, rice farmers’ dispersal from the Yangtze River Valley carrying O1 and some sublineages of O2 contributed significantly to Tai-Kadai, Austronesian, Hmong-Mien, Austroasiatic people and southern Han Chinese. Third, Siberian-related paternal lineages of Q and C originated and boomed from Neolithic hunter-gatherers from the Mongolian Plateau and the Amur River Basin and significantly influenced the gene pools of northern Chinese. Fourth, western Eurasian-derived J, G and R lineages initially spread with Yamnaya steppe pastoralists and other proto-Indo-European people and further widely dispersed via the trans-Eurasian cultural communication along the Eurasian Steppe and the ancient Silk Road, remaining genetic trajectories in northwestern Chinese. Our work provided comprehensive modern and ancient genetic evidence to illuminate the impact of population interaction from the ancient farmer or herder-based societies on the genetic diversity patterns of modern people, revised our understandings of ancestral sources of Chinese paternal lineages, underscored the scientific imperative of the large-scale genomic resources of dense spatiotemporal underrepresented sampling populations to understand human evolutionary history.
Evolutionary analysis of mammalian Rem2, a member of the RGK (Rem, Rem2, Rad, and Gem/Kir) family of small GTPases, reveals the role of selection and epistasis in shaping protein functional constraints
Authors: Lucaci Alexander G , Brew William E , Pond Sergei L Kosakovsky , Moore Anna R 
Published: August 2023

AbstractRad And Gem-Like GTP-Binding Protein 2 (Rem2), is a member of the RGK family of Ras-like GTPases and has been identified in various mammalian species.Rem2has been implicated in Huntington’s disease and Long QT Syndrome and is highly expressed in the brain and in endocrine cells. In this study, we examined the evolutionary history ofRem2across mammals, focusing on the role of purifying selection and epistasis in shaping its sequence and structure. In our analysis ofRem2sequences across 175 mammalian species, we found evidence for strong purifying selection in 70% of non-invariant codon sites of the protein, characteristic of essential proteins that play critical roles in biological processes and is consistent withRem2’s role in the regulation of neuronal development and function. We inferred epistatic effects in 49 pairs of coevolving codon sites inRem2,some of which are predicted to have deleterious effects on human health. Additionally, we reconstructed the ancestral evolutionary history of mammalianRem2using protein structure prediction of extinct and extant sequences. This analysis revealed the dynamics of how substitutions that change the genetic distance of Rem2 can impact protein structure in variable regions while maintaining core functional mechanisms. By understanding the selective pressures, protein- and genetic-interactions that have shaped the sequence and structure of the Rem2 protein, we may gain a stronger understanding of its biological and functional constraints.
Absence of chromosome axis proteins recruitment prevents meiotic recombination chromosome-wide in the budding yeastLachancea kluyveri
Authors: Legrand Sylvain , Saifudeen Asma , Bordelet Hélène , Vernerey Julien , Guille Arnaud , Bignaut Amaury , Thierry Agnès , Acquaviva Laurent , Gaudin Maxime , Sanchez Aurore , Johnson Dominic , Friedrich Anne , Schacherer Joseph , Neale Matthew , Borde Valérie , Koszul Romain , Llorente Bertrand 
Published: August 2023

AbstractMeiotic recombination shows broad variations across species and along chromosomes, and is often suppressed at and around genomic regions determining sexual compatibility such as mating type loci in fungi. Here we show that the absence of Spo11-DSBs and meiotic recombination on Lakl0C-left, the chromosome arm containing the sex locus of theLachancea kluyveribudding yeast, results from the absence of recruitment of the two chromosome axis proteins Red1 and Hop1, essential for proper Spo11-DSBs formation. Furthermore, cytological observation of spread pachytene meiotic chromosomes reveals that Lakl0C-left does not undergo synapsis. However, we show that the behavior of Lakl0C-left is independent of its particularly early replication timing and is not accompanied by any peculiar chromosome structure as detectable by Hi-C in this yet poorly studied yeast. Finally, we observed an accumulation of heterozygous mutations on Lakl0C-left and a sexual dimorphism of the haploid meiotic offspring, supporting a direct effect of this absence of meiotic recombination onL. kluyverigenome evolution and fitness. Because suppression of meiotic recombination on sex chromosomes is widely observed across eukaryotes, the novel mechanism for recombination suppression described here may apply to other species, with the potential to impact sex chromosome evolution.
Metabolic Trade-offs can Reverse the Resource-Diversity Relationship
Authors: Miller Zachary R. , O’Dwyer James P. 
Published: August 2023

AbstractFor species that partition resources, the classic expectation is that increasing resource diversity allows for increased species diversity. On the other hand, for neutral species, such as those competing equally for a single resource, diversity reflects a balance between the rate of introduction of novelty (for example by immigration or speciation) and the rate of extinction. Recent models of microbial metabolism have identified scenarios where metabolic trade-offs among species partitioning multiple resources can produce emergent neutral-like dynamics. In this hybrid scenario, one might expect that both resource diversity and immigration will act to boost species diversity. We show, however, that the reverse may be true: when metabolic trade-offs hold and population sizes are sufficiently large, increasing resource diversity can act to reduce species diversity, sometimes drastically. This reversal is explained by a generic transition between neutral- and niche-like dynamics, driven by the diversity of resources. The inverted resource-diversity relationship that results may be a signature of consumer-resource systems with strong metabolic trade-offs.