bluuebunny/crossref_metadata_2025_split huggingface dataset:
Translating Ethiopian potato seed networks: identifying strategic intervention points for managing bacterial wilt and other diseases
Authors: Etherton Berea A. , Plex Sulá Aaron I. , Mouafo-Tchinda Romaric A. , Kakuhenzire Rogers , Kassaye Haileab A. , Asfaw Frezer , Kosmakos Vasilios S. , McCoy Richard W. , Xing Yanru , Yao Jiahe , Sharma Kalpana , Garrett Karen A. 
Published: February 2024

AbstractContextInformal seed trade can exacerbate crop disease epidemics. Potato production across Ethiopia is threatened by the spread of seedborne pests and pathogens, particularly by bacterial wilt, caused by theRalstonia solanacearumSpecies Complex (RSSC). The RSSC is commonly dispersed through informal trade of seed potato, with the potential to move long distances across Ethiopia and among trading countries. Efficient disease testing programs and formal seed systems can reduce the risk of disease expansion in a country’s potato cropping system.ObjectiveIn this study, we characterized networks of potato value chain actors. We also identified candidate locations for disease surveillance and management interventions for improved seed systems, and locations at high risk for bacterial wilt establishment. We propose strategies to reduce the spread of bacterial wilt via infected seed.MethodsWe surveyed seed potato stakeholders to characterize interaction networks of potato value chain actors with a special focus on stakeholders engaged in seed potato quality assurance. We collected data regarding Ethiopia’s potato seed systems and analyzed the risk of spread of RSSC and other pathogens across the country through expert knowledge elicitation. Network metrics were used to characterize the informal seed trade system across Ethiopia, simulating pathogen spread across a network through scenario analyses. We characterized potato exports and imports to identify the risk of bacterial wilt movement through Ethiopia’s formal trading partners and neighboring countries where bacterial wilt has not yet been reported.ResultsWare potato farmers and traders were reported to have weak communication with other stakeholders in the potato value chain. In network analyses and simulated epidemics, locations in Agew Awi, Gamo, Gofa, Kembata and Tembaro zones were identified as candidate priorities for national surveillance of pathogen invasion and expansion through management interventions and formal seed system development. Ethiopia has formal trade with Sudan, Southern Sudan, Russia, and other countries where bacterial wilt has not been reported. Ethiopia may be at risk of reintroduction of the RSSC from countries where it is present, like Kenya and India.SignificanceImproving seed systems to manageR. solanacearumand other seedborne pathogens is important for supporting food security and the livelihoods of smallholder farmers in Ethiopia. Implementing surveillance systems and management programs in locations like those identified in Agew Awi, Gamo, Gofa, Kembata, and Tembaro zones, and improving the communication between ware potato traders and other stakeholders, can help to strengthen informal trade of seed potato and mitigate bacterial wilt spread in infected seed.
Skin Sensitisation Case Study: Comparison of Defined Approaches including OECD 497 Guidance
Authors: Ankli Pascal P. , Parween Shaheena , Lopez Béatrice , Daligaux Pierre , Mohorič Tomaž , Darde Thomas , Chesné Christophe , Stockman Nathan , Boglári Csaba , Poon Amanda Y. , Hardy Barry 
Published: February 2024

AbstractCharacterising known and new chemical compounds for skin sensitisation provides a basis for the development of safer products where ingredients are exposed to skin. By including new approaches, such as tiered testing strategies and integrated data analysis, it is possible to develop next generation products adhering to emerging regulations, scientific evidence and animal welfare principles. To ensure data integrity during such assessment the OECD provides characterisation guidelines and Defined Approaches (DAs) to uniform work-flows. In this study we developed and applied the integrated characterisation tool called «SaferSkin™» to compare the results of different DAs for eight compounds and included results obtained from current OECD guidance and emerging methods. We tested two compounds with unclear or indeterminate results with the SENS-IS assay to explore the value of the experiment in strengthening the weight of evidence and arriving at a clearer conclusion.
Mastication while rested does not improve sustained attention in healthy participants conducting short-duration cognitive tasks
Authors: Hansen Devon , Maislin Greg , Day Jon E. L. 
Published: February 2024

AbstractSustained attention is important for optimal neurobehavioral performance, but many biological and environmental factors (e.g., circadian rhythm, distraction, etc.) may cause sustained attention deficits. It has been suggested that mastication (chewing) may ameliorate such deficits. As part of a continuing program to study the effects of mastication under varying conditions of fatigue and cognitive demand, this trial used a randomized, within-subjects, cross-over design to investigate the effect of mastication (gum chewing) on levels of sustained attention. To initially provide data that was ecologically valid for the average person, participants were not sleep deprived or otherwise challenged. Fifty-eight healthy adults (aged 18 – 45 years; 38 females) completed a 5 h in-laboratory daytime study during which time they completed two, 40 min test bouts. Participants completed the Psychomotor Vigilance Test (PVT), the Sustained Attention to Response Task (SART), the Karolinska Sleepiness Scale (KSS) and the Positive and Negative Affect Schedule (PANAS). During one of the two test bouts, participants were instructed to chew a piece of gum at a steady, comfortable rate. The statistical analyses were conducted blind. The primary outcome variable used for analyses was PVT lapses using the transformation square root of lapses plus square root of lapses plus 1 in addition to PVT mean reciprocal response time. Secondary outcome variables were PVT time-on-task slope and SART error score. Using rested participants and moderately fatiguing tasks, we were unable to detect any significant improvement in PVT or SART performance, or in KSS or PANAS ratings. A follow-up study under conditions of sleep deprivation and/or with longer task duration may provide further insight into the countermeasure potential of mastication.
Brain eQTLs of European, African American, and Asian ancestry improve interpretation of schizophrenia GWAS
Authors: Chen Yu , Liu Sihan , Ren Zongyao , Wang Feiran , Jiang Yi , Dai Rujia , Duan Fangyuan , Han Cong , Ning Zhilin , Xia Yan , Li Miao , Yuan Kai , Qiu Wenying , Yan Xiao-Xin , Dai Jiapei , Kopp Richard F. , Huang Jufang , Xu Shuhua , Tang Beisha , Gamazon Eric R. , Bigdeli Tim , Gershon Elliot , Huang Hailiang , Ma Chao , Liu Chunyu , Chen Chao 
Published: February 2024

AbstractResearch on brain expression quantitative trait loci (eQTLs) has illuminated the genetic underpinnings of schizophrenia (SCZ). Yet, the majority of these studies have been centered on European populations, leading to a constrained understanding of population diversities and disease risks. To address this gap, we examined genotype and RNA-seq data from African Americans (AA, n=158), Europeans (EUR, n=408), and East Asians (EAS, n=217). When comparing eQTLs between EUR and non-EUR populations, we observed concordant patterns of genetic regulatory effect, particularly in terms of the effect sizes of the eQTLs. However, 343,737 cis-eQTLs (representing ∼17% of all eQTLs pairs) linked to 1,276 genes (about 10% of all eGenes) and 198,769 SNPs (approximately 16% of all eSNPs) were identified only in the non-EUR populations. Over 90% of observed population differences in eQTLs could be traced back to differences in allele frequency. Furthermore, 35% of these eQTLs were notably rare (MAF < 0.05) in the EUR population. Integrating brain eQTLs with SCZ signals from diverse populations, we observed a higher disease heritability enrichment of brain eQTLs in matched populations compared to mismatched ones. Prioritization analysis identified seven new risk genes (SFXN2,RP11-282018.3,CYP17A1,VPS37B,DENR,FTCDNL1, andNT5DC2), and three potential novel regulatory variants in known risk genes (CNNM2,C12orf65, andMPHOSPH9) that were missed in the EUR dataset. Our findings underscore that increasing genetic ancestral diversity is more efficient for power improvement than merely increasing the sample size within single-ancestry eQTLs datasets. Such a strategy will not only improve our understanding of the biological underpinnings of population structures but also pave the way for the identification of novel risk genes in SCZ.
Gemykibivirus detection in acute encephalitis patients from Nepal
Authors: Tuladhar Eans Tara , Shrestha Smita , Vernon Susan , Droit Lindsay , Mihindukulasuriya Kathie A. , Tamang Mamta , Karki Lata , Ngono Annie Elong , Jha Bimlesh , Awal Bal Krishna , Chalise Bimal Sharma , Jha Runa , Shresta Sujan , Wang David , Manandhar Krishna Das 
Published: February 2024

AbstractAcute Encephalitis Syndrome (AES) causes significant morbidity and mortality worldwide. In Nepal, Japanese encephalitis virus (JEV) accounts for ∼ 5-20% of AES cases, but ∼75% of AES cases are of unknown etiology. We identified a gemykibivirus in CSF collected in 2020 from a male child with AES using metagenomic next-generation sequencing. Gemykibiviruses are single stranded, circular DNA viruses in the familyGenomoviridae. The complete genome of 2211 nucleotides was sequenced which shared 98.69% nucleotide identity to its closest relative, Human associated gemykibivirus 2 isolate SAfia-449D. Two real-time PCR assays were designed, and screening of 337 CSF and 164 serum samples from AES patients in Nepal collected in 2020 and 2022 yielded 11 CSF and 1 serum sample that were positive in both PCR assays. Complete genomes of 7 of the positives were sequenced. These results identify a candidate etiologic agent of encephalitis in Nepal.
Relationship between temporal projections and cognition in patients with putaminal hemorrhage
Authors: Jang Sung Ho , Kwon Hyeok Gyu 
Published: February 2024

AbstractBackgroundThe cognitive function is a complex mental process involving the temporal projections (cingulum, superior longitudinal fasciculus[SLF], inferior longitudinal fasciculus[ILF], and uncinate fasciculus[UF]). Therefore, a brain injury involving the temporal projections results in cognitive impairment. However, few studies have reported the pathophysiological mechanisms associated with cognitive impairment in patients with putaminal hemorrhage(PH). In this study, using diffusion tensor tractography(DTT), the relationship between the temporal projections and cognition was analyzed in patients with PH.Methods25 patients with PH were recruited for this study. A Mini-Mental State Examination(MMSE) was conducted twice to evaluate their cognitive function(within one month and six months after onset). The temporal projections(cingulum, SLF, ILF, and UF) were reconstructed and the values of DTT parameters were measured. Pearson correlation and multiple regression analyses were also performed to determine the relationship between the DTT parameters of the temporal projections and the MMSE.ResultsAn analysis of the correlations showed that the fractional anisotropy and fiber number ratio of the UF were correlated with the MMSE performed within one month and six months after onset. In addition, the fiber number of the UF on the MMSE at six months from the onset had an explanatory power of 33% and showed the 0.064 for unstandardized coefficients.ConclusionsUsing DTT, this study demonstrated that among the temporal projections, the state of the UF in patients with PH could be the most significant indicator of cognitive function. Our results suggested that evaluation of the UF using DTT could be useful in predicting the cognitive function following PH.
The Northern Colours: Isolation and Characterisation of 4 Pigment-Producing Bacteria from the Arctic
Authors: Das Jenifar , Singh Ashish Kumar 
Published: February 2024

AbstractDue to the adverse effects of synthetic colours on human health and the environment, there is a rapid shift towards the use of colours from natural sources like plants and microorganisms. Many pigment-producing microorganisms are identified and isolated from extreme environments like glaciers, ice cores, marine surface waters, etc. In this study, we have isolated 4 distinct pigment-producing bacterial strains from an Arctic stone sample collected from the vicinity of the Indian Research StationHimadri(78°55′N11°56′E), located at the International Arctic Research Base, NyÅlesund, Svalbard, Norway. Pigment production was optimised by identifying the right growth medium, temperature, pH, and incubation period. The morphological, cultural, and biochemical characteristics were identified using several experiments like Gram Staining, Catalase Test, Oxydative-Fermentative Test, etc. The objective of this study is to identify novel bacterial strains capable of producing distinct pigments for pharmaceutical and industrial applications.
Differentiation smelling footprints of the Chagas disease vector using an electronic nose based on artificial intelligence algorithms
Authors: Ruiz-Jiménez Luisa F. , Sierra Daniel A. , Ortega B Homero , Rincon-Orozco Bladimiro , Duque Jonny E. 
Published: February 2024

AbstractThe present study aims to present the design of an electronic nose capable of learning and differentiating semiochemical signals emitted by insects usable to identify species that transmit Chagas disease. The proposed device used different non-specific resistor gas sensors integrated into a system of artificial intelligence models. To validate the nose, we used eight insect species of the Triatominae subfamily and one population that was a natural carrier of the parasiteTrypanosoma cruzi. Also, the discriminatory capacity of distant species was tested with other insects likeAedes aegypti(arbovirus vector) andSitophilus oryzae(stored grains plague). As a result, the electronic nose was able to differentiate up to gender level with an accuracy of 89.64% and to differentiateRhodnius pallenscesnaturally infected withT. cruziwith less than 1% of error in classification. These results show that our designed device can detect particular smelling footprints, and one electronic nose like that could be a tool to discriminate against insects in the future.
A Workflow for Improved Analysis of Cross-linking Mass Spectrometry Data Integrating Parallel Accumulation-Serial Fragmentation with MeroX and Skyline
Authors: Rojas Echeverri Juan Camilo , Hause Frank , Iacobucci Claudio , Ihling Christian H. , Tänzler Dirk , Shulman Nicholas , Riffle Michael , MacLean Brendan , Sinz Andrea 
Published: February 2024

ABSTRACTCross-linking mass spectrometry (XL-MS) has evolved into a pivotal technique for probing protein interactions. This study describes the implementation of Parallel Accumulation-Serial Fragmentation (PASEF) on timsTOF instruments, enhancing the detection and analysis of protein interactions by XL-MS. Addressing the challenges in XL-MS, such as the interpretation of complex spectra, low abundant cross-linked peptides, and a data acquisition bias, our current study integrates a peptide-centric approach for the analysis of XL-MS data and presents the foundation for integrating data-independent acquisition (DIA) in XL-MS with a vendor-neutral and open-source platform. A novel workflow is described for processing data-dependent analysis (DDA) of PASEF-derived information. For this, software by Bruker Daltonics is used, enabling the conversion of these data into a format that is compatible with MeroX and Skyline software tools. Our approach significantly improves the identification of cross-linked products from complex mixtures, allowing the XL-MS community to overcome current analytical limitations.
Matching dynamically varying forces with multi-motor-unit muscle models: A simulation study
Authors: Murtola T. , Richards C. 
Published: February 2024

AbstractHuman muscles exhibit great versatility, not only generating forces for demanding athleticism, but also for fine motor tasks. While standard musculoskeletal models may reproduce this versatility, they often lack multiple motor units (MUs) and rate-coded control. To investigate how these features affect a muscle’s ability to generate desired force profiles, we performed simulations with nine alternative MU pool models for two cases: 1) a tibialis anterior muscle generating an isometric trapezoidal force profile, and 2) a generic shoulder muscle generating force for a reaching movement whilst undergoing predetermined length changes. We implemented two control strategies, pure feedforward and combined feedforward-feedback, each parameterised using elementary tasks. The results suggest that the characteristics of MU pools have relatively little impact on the pools’ overall ability to match forces across all tasks, although performances for individual tasks varied. Feedback improved performance for nearly all MU pools and tasks, but the physiologically more relevant MU pool types were more responsive to feedback particularly during reaching. While all MU pool models performed well in the conditions tested, we highlight the need to consider the functional characteristics of the control of rate-coded MU pools given the vast repertoire of dynamic tasks performed by muscles.
Predictive simulation of human movement in OpenSim using floating-base task space control
Authors: Pickle Nathaniel T. , Sundararajan Aravind 
Published: February 2024

AbstractTask space control, also known as operational space control, is a useful paradigm for investigating neural control of human movement using predictive simulations. While some efforts have been made to implement task space control in the widely used open-source platform OpenSim, existing implementations do not support floating base kinematics, which is necessary for simulating gait and other types of human movement. Our aim in this work is to fill that gap. In this paper, we describe the theory and implementation of a floating base kinematics task space framework for torque- and muscle-driven simulations in OpenSim. Our framework builds on previous work that was limited to models with a base (i.e., root) segment fixed to ground. In addition, we integrate various algorithms from robotics in order to handle dynamically changing contacts and task prioritization. The framework can be used to generate realistic walking gaits by prescribing a small set of controller gains and gait parameters such as step length, step width and center of mass velocity. Task can be specified as desired positions, rotations, or higher-order feature such as base of support and whole-body angular momentum. We provide several examples to demonstrate how framework is successful in orchestrating a complex hierarchy of tasks that work in concert to perform both balance control and gait generation. The implementation is freely available for roboticists and biomechanists to use with OpenSim.Author summaryRecent advances in computational biomechanics have provided researchers with tools capable of predicting human movement. Previous approaches to simulating human movement required experimental data as input and the simulation would replicate the experimental motion. This conventional approach limited the scientific insights to the specific movement recorded in the laboratory. With predictive approaches, researchers can investigate how a person might respond to various factors, such as reduced muscle strength or an assistive device such as a robotic exoskeleton. Existing approaches for generating predictive simulations utilize optimization-based approaches, which can be time-consuming and difficult to troubleshoot. Task space control is an alternative approach which is widely used in robotics. Conceptually, task space control aims to generate a simulation by specifying “tasks”, such as moving a hand or foot to a desired position, and computing the joint angles required to achieve the task. Here we aim to outline the mathematics behind task space control and demonstrate how task space control can be used to generate simulations of movements such as walking.
Cytometry Masked Autoencoder: An Accurate and Interpretable Automated Immunophenotyper
Authors: Kim Jaesik , Ionita Matei , Lee Matthew , McKeague Michelle L. , Pattekar Ajinkya , Painter Mark M. , Wagenaar Joost , Truong Van , Norton Dylan T. , Mathew Divij , Nam Yonghyun , Apostolidis Sokratis A. , Clendenin Cynthia , Orzechowski Patryk , Jung Sang-Hyuk , Woerner Jakob , Ittner Caroline A.G. , Turner Alexandra P. , Esperanza Mika , Dunn Thomas G. , Mangalmurti Nilam S. , Reilly John P. , Meyer Nuala J. , Calfee Carolyn S. , Liu Kathleen D. , Matthy Michael A. , Swigart Lamorna Brown , Burnham Ellen L. , McKeehan Jeffrey , Gandotra Sheetal , Russel Derek W. , Gibbs Kevin W. , Thomas Karl W. , Barot Harsh , Greenplate Allison R. , Wherry E. John , Kim Dokyoon 
Published: February 2024

AbstractHigh-throughput single-cell cytometry data are crucial for understanding involvement of immune system in diseases and responses to treatment. Traditional methods for annotating cytometry data, specifically manual gating and clustering, face challenges in scalability, robustness, and accuracy. In this study, we propose a cytometry masked autoencoder (cyMAE), which offers an automated solution for immunophenotyping tasks including cell type annotation. The cyMAE model is designed to uphold user-defined cell type definitions, thereby facilitating easier interpretation and cross-study comparisons. The cyMAE model operates on a pre-train and fine-tune approach. In the pre-training phase, cyMAE employsMasked Cytometry Modelling (MCM)to learn relationships between protein markers in immune cells solely based on protein expression, without relying on prior information such as cell identity and cell type-specific marker proteins. Subsequently, the pre-trained cyMAE is fine-tuned on multiple specialized tasks via task-specific supervised learning. The pre-trained cyMAE addresses the shortcomings of manual gating and clustering methods by providing accurate and interpretable predictions. Through validation across multiple cohorts, we demonstrate that cyMAE effectively identifies co-occurrence patterns of bound labeled antibodies, delivers accurate and interpretable cellular immunophenotyping, and improves the prediction of subject metadata status. Specifically, we evaluated cyMAE for cell type annotation and imputation at the cellular-level and SARS-CoV-2 infection prediction, secondary immune response prediction against COVID-19, and prediction of the infection stage in COVID-19 progression at the subject-level. The introduction of cyMAE marks a significant step forward in immunology research, particularly in large-scale and high-throughput human immune profiling. This approach offers new possibilities for predicting and interpreting cellular-level and subject-level phenotypes in both health and disease.