bluuebunny/crossref_metadata_2025_split huggingface dataset:
pipemake: A pipeline creation tool using Snakemake for reproducible analysis of biological datasets
Authors: Webb Andrew E. , Wolf Scott W. , Traniello Ian M. , Kocher Sarah D. 
Published: December 2024

AbstractThe exponential growth in biological data generation has created an urgent need for efficient, reproducible computational analysis workflows. Here, we present pipemake, a computational platform designed to streamline the development and implementation of efficient and reproducible Snakemake workflows. pipemake creates modular pipelines that can be seamlessly integrated or removed from the platform without requiring reconfiguration of the core system, enabling flexible adaptation of workflows to different analytical needs across diverse fields. To demonstrate the platform’s capabilities, we created and implemented pipelines to reanalyze two distinct biological datasets. First, we recreated a population genomics analysis of the socially flexible halictid bee,Lasioglossum albipes, using pipemake-generated workflows forde novogenome annotation, processing of variant data, dimensionality reduction, and a genome-wide association study (GWAS). We then used pipemake to analyze behavioral tracking data from the common eastern bumble bee,Bombus impatiens. In both cases, pipemake workflows produced results consistent with published findings while substantially reducing hands-on analysis time. Overall, pipemake’s modular design allows researchers to easily modify existing pipelines or develop new ones without software development expertise. Beyond streamlining workflow creation, pipemake leverages the full Snakemake ecosystem to enable parallel processing, automated error recovery, and comprehensive analysis documentation. These features make pipemake an efficient and accessible solution for analyzing complex biological datasets. pipemake is freely available as a conda package or direct download athttps://github.com/kocherlab/pipemake
dGAMLSS: An exact, distributed algorithm to fit Generalized Additive Models for Location, Scale, and Shape for privacy-preserving population reference charts
Authors: Hu Fengling , Tong Jiayi , Gardner Margaret ,   Lifespan Brain Chart Consortium, Chen Andrew A. , Bethlehem Richard A.I. , Seidlitz Jakob , Li Hongzhe , Alexander-Bloch Aaron , Chen Yong , Shinohara Russell T. 
Published: December 2024

AbstractThere is growing interest in estimating population reference ranges across age and sex to better identify atypical clinically-relevant measurements throughout the lifespan. For this task, the World Health Organization recommends using Generalized Additive Models for Location, Scale, and Shape (GAMLSS) which can model non-linear growth trajectories under complex distributions that address the heterogeneity in human populations.Fitting GAMLSS models requires large, generalizable sample sizes, especially for accurate estimation of extreme quantiles, but obtaining such multi-site data can be challenging due to privacy concerns and practical considerations. In settings where patient data cannot be shared, privacy-preserving distributed algorithms for federated learning can be used, but no such algorithm exists for GAMLSS.We propose distributed GAMLSS (dGAMLSS), a distributed algorithm which can fit GAMLSS models across multiple sites without sharing patient-level data. We demonstrate the effectiveness of dGAMLSS in constructing population reference charts across clinical, genomics, and neuroimaging settings.
Precise and scalable metagenomic profiling with sample-tailored minimizer libraries
Authors: Nyström-Persson Johan , Bapatdhar Nishad , Ghosh Samik 
Published: December 2024

AbstractReference-based metagenomic profiling requires large genome libraries to maximize detection and minimize false positives. However, as libraries grow, classification accuracy suffers, particularly in k-mer-based tools, as the growing overlap in genomic regions among organisms results in more high-level taxonomic assignments, blunting precision. To address this, we propose sample-tailored minimizer libraries, which improve on the minimizer-LCA (lowest common ancestor) classification algorithm from the widely used Kraken 2. In this method, an initial filtering step using a large library removes non-resemblance genomes, followed by a refined classification step using a dynamically built smaller minimizer library. This 2-step classification method shows significant performance improvements compared to the state of the art. We develop a new computational tool called Slacken, a distributed and highly scalable platform based on Apache Spark, to implement the 2-step classification method, which improves speed while keeping the cost per sample comparable to Kraken 2. Specifically, in the CAMI2 “strain madness” samples, the fraction of reads classified at species level increased by 3.5x, while forin silicosamples it increased by 2.2x. The 2-step method achieves the sensitivity of large genomic libraries and the specificity of smaller ones, unlocking the true potential of large reference libraries for metagenomic read profiling.
Systematic Benchmarking of High-Throughput Subcellular Spatial Transcriptomics Platforms
Authors: Ren Pengfei , Zhang Rui , Wang Yunfeng , Zhang Peng , Luo Ce , Wang Suyan , Li Xiaohong , Zhang Zongxu , Zhao Yanping , He Yufeng , Zhang Haorui , Li Yufeng , Gao Zhidong , Zhang Xiuping , Zhao Yahui , Liu Zhihua , Meng Yuanguang , Zhang Zhe , Zeng Zexian 
Published: December 2024

AbstractRecent advancements in spatial transcriptomics technologies have significantly enhanced resolution and throughput, underscoring an urgent need for systematic benchmarking. To address this, we collected clinical samples from three cancer types – colon adenocarcinoma, hepatocellular carcinoma, and ovarian cancer – and generated serial tissue sections for systematic evaluation. Using these uniformly processed samples, we generated spatial transcriptomics data across five high-throughput platforms with subcellular resolution: Stereo-seq v1.3, Visium HD FFPE, Visium HD FF, CosMx 6K, and Xenium 5K. To establish ground truth datasets, we profiled proteins from adjacent tissue sections corresponding to all five platforms using CODEX and performed single-cell RNA sequencing on the same samples. Leveraging manual cell segmentation and detailed annotations, we systematically assessed each platform’s performance across key metrics, including capture sensitivity, specificity, diffusion control, cell segmentation, cell annotation, spatial clustering, and transcript-protein alignment with adjacent CODEX. The uniformly generated, processed, and annotated multi-omics dataset is valuable for advancing computational method development and biological discoveries. The dataset is accessible via SPATCH, a user-friendly web server for visualization and download (http://spatch.pku-genomics.org/).
Overexpression of Xanthophyll Cycle Genes Leads to Faster NPQ Acclimation in the C4 MonocotSetaria viridis
Authors: Stone William D. , Acosta-Gamboa Lucia , Kang Xiaojun , Zhang Feng , Owens Lauren , Li Li , Thielen Peter M. , Jander Georg , Gore Michael A. , Lawton Thomas J. 
Published: December 2024

AbstractSlow relaxation and induction of Non-Photochemical Quenching (NPQ) limits plant productivity under fluctuating light in C3 plants but it is unknown if this trait extends to C4 plants. Three genes have been implicated in determining NPQ induction and relaxation rates under intermittent leaf shading;VDEandZEPinterconvert the xanthophyll pigments violaxanthin and zeaxanthin, and PsbS regulates the overall level of NPQ. Here we report the overexpression of theArabidopsis thaliana VDE, ZEP, andPsbSin the NADP-Malic Enzyme C4 monocotSetaria viridis. We demonstrate these transgenic plants have faster NPQ induction and relaxation under fluctuating light but observe no impact on Photosystem II photochemistry yield. Under illumination, faster NPQ induction resulted in higher transient NPQ levels and a lower overall chlorophyll fluorescence yield. Together this introduces the potential for lower productivity due to over-quenching of chlorophyll during light fluctuation. Although we observed faster NPQ acclimation rates in our transgenic lines, hyperspectral imaging and pigment analysis suggest that there is little photosynthetic advantage to increasing NPQ acclimation over wildtype due to naturally fast C4 acclimation rates. These results indicate that further work is necessary in evaluating the role of NPQ acclimation in C4 growth dynamics towards the goal of improving crop productivity.
Selective ion binding and uptake shape the microenvironment of biomolecular condensates
Authors: Smokers Iris B. A. , Lavagna Enrico , Freire Rafael V. M. , Paloni Matteo , Voets Ilja K. , Barducci Alessandro , White Paul B. , Khajehpour Mazdak , Spruijt Evan 
Published: December 2024

AbstractBiomolecular condensates modulate various ion-dependent cellular processes and can regulate subcellular ion distributions by selective uptake of ions. However, the molecular grammar governing condensate-ion interactions is poorly understood. Here, we use NMR spectroscopy of ions and model condensate components to quantify and spatially resolve selective ion binding to condensates and show that these interactions follow the law of matching water affinities, resulting in strong binding between proteins and chaotropic anions, and between nucleic acids and kosmotropic cations. Ion uptake into condensates directly follows binding affinities, resulting in selective uptake of strong-binding ions, but exclusion of weak-binding ions. Ion binding further shapes the condensate microenvironment by altering the composition, viscosity and interface potential. Such changes can have profound effects on biochemical processes taking place inside condensates, as we show for RNA duplex formation. Our findings provide a new perspective on the role of condensate-ion interactions in cellular bio- and electrochemistry and may aid design of condensate-targeting therapeutics.
Isopeptor: a tool for detecting intramolecular isopeptide bonds in protein structures
Authors: Costa Francesco , Barringer Rob , Riziotis Ioannis , Andreeva Antonina , Bateman Alex 
Published: December 2024

AbstractMotivationIntramolecular isopeptide bonds contribute to the structural stability of proteins, and have primarily been identified in domains of bacterial fibrillar adhesins and pili. At present, there is no systematic method available to detect them in newly determined molecular structures. This can result in mis-annotations and incorrect modelling.ResultsHere, we present Isopeptor, a computational tool designed to predict the presence of intramolecular isopeptide bonds in experimentally determined structures. Isopeptor utilizes structure-guided template matching via the Jess software, combined with a logistic regression classifier that incorporates Root Mean Square Deviation (RMSD) and relative solvent accessible area (rASA) as key features. The tool demonstrates a recall of 1.0 and a precision of 0.95 when tested on a Protein Data Bank (PDB) subset of domains known to contain intramolecular isopeptide bonds that have been deposited with incorrectly modelled geometries. Isopeptor’s python-based implementation supports integration into bioinformatics workflows, enabling early detection and prediction of isopeptide bonds during protein structure modelling.Availability and implementationIsopeptor is implemented in python and can be accessed via the command line, through a python API or via a Google Colaboratory implementation (https://colab.research.google.com/github/FranceCosta/Isopeptor_development/blob/main/notebooks/Isopeptide_finder.ipynb). Source code is hosted on GitHub (https://github.com/FranceCosta/isopeptor) and can be installed via the python package installation manager PIP.
Transient dopamine response on medium spiny neuron subtypes in switching approach-avoidance outcomes against action bias-A framework for exploration in action selection
Authors: Anisetty Nitin , Manchanda Rohit 
Published: December 2024

AbstractAn ensemble of direct and indirect pathway medium spiny neurons (dMSN and iMSN), compete via their neural activity to drive the decision to approach or avoid an object, respectively. Dopamine acting as a reward prediction error (RPE) signal causes experience-dependent synaptic changes in dMSN and iMSN, thereby shifting the dominance of neural activity to approach or avoidance signaling. These changes create bias in the striatal neuronal ensemble and restrict the choice to approach or avoidance in further iterations. However, organisms often exhibit behaviour where they choose undesirable actions in anticipation of future reward or avoid desirable actions in anticipation of future risk. These against-bias decisions or exploratory decisions are not accounted for by the existing neuronal framework. To bridge this gap, we postulate that transient ‘motivational’ dopamine released from dopaminergic axons locally at sub-second timescales can cause temporary switch in dominance of neural activity between dMSN and iMSN leading to such adaptive decisions. By accounting for bias towards approach or avoidance or neither through synaptic weightages and accounting for differential affinity of DA to D1R and D2R, changes in dMSN and iMSN excitability at different levels of motivational dopamine was analyzed. Furthermore, the spiking activity of striatal neuronal ensemble comprising of dMSN projecting directly and iMSN projecting indirectly onto the output nuclei of basal ganglia i.e. SNr neurons was simulated. This led to promising findings that demonstrate how SNr neuronal activity can generate outcomes that work against the synaptic bias towards approach or avoidance.Graphical Abstract
Linking technological relatedness to firm innovation: the moderating roles of environmental dynamism, competitiveness and enterprise life cycle
Authors: Sai Fu , Zhu Guilong , Qin Zitao , Zheng Lixun 
Published: December 2024

PurposeGrounded in inter-firm collaboration contexts, this study examines the influence of technological relatedness – encompassing technological similarity and complementarity – on the innovation performance of manufacturing enterprises in emerging economies, with a focus on how environmental dynamism, competitiveness and firm life cycle stages moderate these relationships.Design/methodology/approachThe authors empirically tested the hypotheses based on the data of Chinese listed manufacturing companies from 2006 to 2021.FindingsBoth technological similarity and complementarity positively impact innovation performance. Environmental dynamism enhances the positive effects of technological similarity, while environmental competitiveness amplifies the advantages of technological complementarity. The innovation benefits brought by technological relatedness differ across life cycle stages, with technological similarity preferred at the introduction phase and complementarity preferred at the growth and mature stages.Originality/valueThis study enriches the research on the driving factors of innovation performance from the perspective of technological relatedness. The authors extend the boundaries of technological relatedness research by systematically examining the moderating roles of environmental dynamism, competitiveness and the enterprise life cycle. The findings provide valuable insights for managers in manufacturing enterprises on how to formulate effective partner selection strategies that align with external environmental changes and the stages of enterprise development.
Critical points in the views of G7’s country leaders on national agendas for SDGs and SFDRR
Authors: Sari Bektas , Sen Gulhan 
Published: December 2024

PurposeDisasters are catastrophic events that result in loss of life, injury and significant disruptions to everyday life. Unsustainable poverty, crises and migration policies worsen them. This study aimed to evaluate the critical perspectives of G7’s country leaders regarding their national agendas in 2022, focusing on the sustainable development goals (SDGs) and the Sendai Framework for Disaster Risk Reduction (SFDRR).Design/methodology/approachThis study utilized document analysis, one of the qualitative research methods. Using purposive sampling, we analyzed 20,215 words of X (Twitter) data from G7’s country leaders between January 1 and December 31, 2022, with a thematic approach using MAXQDA qualitative software. MAXQDA applied Code Cloud, Code Matrix Browser, Word Frequencies and MaxMaps Code Models tests. Results are presented based on codes, categories and themes identified during analysis.FindingsThe G7’s country leaders emphasized peace, justice and strong institutions as their SDGs priority. However, it was observed that developed nations often overlooked critical issues such as hunger, quality education and inequality in their agendas in 2022. Based on SFDRR, the leaders addressed crisis response and recovery topics, but it is crucial to note that there is a need for a shift towards proactive measures in their disaster policies. The study also noted limited coverage of migration issues affecting many countries globally. There is an urgent need to address hunger, provide quality education and reduce inequality worldwide.Research limitations/implicationsThis study has several limitations: Former Italian Prime Minister Mario Draghi did not have an X (Twitter) account in 2022, and the data only reflect the situation in 2022. Also, simply analyzing statements does not necessarily indicate what these countries support and promote in practice. However, this study could be enhanced by including analyses of funding allocations for projects that target various SDGs and SFDRR objectives. Lastly, this study focused on the strategic policy statements made by representatives of different countries. It does not include tactical and operational disaster management processes, which is a limitation because it is difficult to provide a broader perspective.Practical implicationsDeveloped countries’ approaches to disaster and development policies are essential for disaster risk reduction strategies. Future analyses of funding allocations for projects targeting various SDGs and SFDRR objectives can lead to practical implications.Originality/valueThe authors present a critical viewpoint on the SDGs and SFDRR perspectives of G7’s country leaders. As developed countries possess significant resources and capabilities, they should set a positive example in the global implementation of disaster policies. Consequently, their annual official statements are a valuable guide for disaster policymakers and practitioners.
Understanding esports player preferences: which self-definitional needs drive their satisfaction?
Authors: Wang Weisha , Liu Wentong , Hang Haiming , Chen Zhifeng 
Published: December 2024

PurposeEsports is emerging as a global sensation, yet its distinctive nature complicates our understanding of players' motivations. This study leverages self-hierarchy and self-determination theories to examine the motivations that define players at individual, relational, and community levels, seeking to identify which motivations are most valued.Design/methodology/approachA mixed-method approach was employed, focusing on Honor of Kings esports players in China to explore the answers to the research questions. First, semi-structured interviews were conducted to uncover self-definitional motivations at various levels. Second, a quantitative study was conducted with 607 regular Honor of Kings players to empirically examine the effects of the identified motivations on satisfaction.FindingsThe qualitative and quantitative data results reveal that self-efficacy and self-worth at the individual level, recognition and emotional attachment from close others at the relational-self level, and cocreation and belongingness at the collective level positively influence game satisfaction. More importantly, self-definitional motivations at the relational level are valued the most. Additionally, identification with a game character moderates the effects of self-definitional motivation at the collective level and emotional attachment at the relational-self level.Originality/valueThis research delves into players' motivations for engaging with Honor of Kings, anchored in self-hierarchy and self-determination theories. It uncovers that motivations rooted in different aspects of self-identity have distinct associations with players’ satisfaction level. This suggests a vital strategy for game designers and operators to adopt: to enhance player satisfaction, they should specifically address and emphasize the aspects of self-identity that matter most to their audience.
The missing link: knowledge hiding behavior and project performance
Authors: Nauman Shazia , Tahir Muhammad Zain , Ali Fouzia Hadi , Sumbal Muhammad Saleem Ullah Khan 
Published: December 2024

PurposeThis study examines how project leaders’ knowledge hiding influences project performance via project employee creativity, employing the conservation of resources theory. Further, we investigate how mastery motivational climate (MMC) moderates the project employee creativity and project performance relationship.Design/methodology/approachEmploying purposive sampling design, two-wave data (N = 245) was collected with a gap of three weeks from employees working in R&D departments in private software development project-based organizations located in Lahore, Pakistan.FindingsResults suggest that leaders’ knowledge hiding does impede project employee creativity and negatively influence project performance. In addition, MMC was found to accentuate the relationship between project employee creativity and project performance.Practical implicationsThis study offers notable insights into the knowledge hiding literature from a top-down perspective within the project management domain relating to IT projects. This study’s findings pose implications for practitioners and project-based organizations who are interested in counteracting the adverse effects of knowledge hiding on project performance.Originality/valueThis study proposes a novel approach to job design by considering resource scarcity caused by a leader’s knowledge hiding as a job demand, along with the achievement goal perspective driven by a mastery or goal orientation. To understand these two perspectives, we rely on the conservation of resources (COR) theory to describe how a leader’s knowledge hiding affects project performance through project employee creativity, moderated by mastery motivational climate.