bluuebunny/crossref_metadata_2025_split huggingface dataset:
spatiAlign: An Unsupervised Contrastive Learning Model for Data Integration of Spatially Resolved Transcriptomics
Authors: Zhang Chao , Liu Lin , Zhang Ying , Li Mei , Fang Shuangsang , Kang Qiang , Chen Ao , Xu Xun , Zhang Yong , Li Yuxiang 
Published: August 2023

AbstractIntegrative analysis of spatially resolved transcriptomics datasets empowers a deeper understanding of complex biological systems. However, integrating multiple tissue sections presents challenges for batch effect removal, particularly when the sections are measured by various technologies or collected at different times. Here, we propose spatiAlign, an unsupervised contrastive learning model that employs the expression of all measured genes and the spatial location of cells, to integrate multiple tissue sections. It enables the joint downstream analysis of multiple datasets not only in low-dimensional embeddings but also in the reconstructed full expression space. In benchmarking analysis, spatiAlign outperforms state-of-the-art methods in learning joint and discriminative representations for tissue sections, each potentially characterized by complex batch effects or distinct biological characteristics. Furthermore, we demonstrate the benefits of spatiAlign for the integrative analysis of time-series brain sections, including spatial clustering, differential expression analysis, and particularly trajectory inference that requires a corrected gene expression matrix.
Comparing the advantages and disadvantages of physics-based and neural network-based modelling for predicting cycling power
Authors: Mayerhofer Patrick , Bajić Ivan , Donelan J. Maxwell 
Published: August 2023

AbstractModels of physical phenomena can be developed using two distinct approaches: using expert knowledge of the underlying physical principles, or using experimental data to train a neural network. Here, our aim was to better understand the advantages and disadvantages of these two approaches. We chose to model cycling power because the physical principles are already well understood. Nine participants followed changes in cycling cadence transmitted through a metronome via earphones and we measured their cadence and power. We then developed and trained a physics-based model and a simple neural network model, where both models had cadence, derivative of cadence, and gear ratio as input, and power as output. We found no significant differences in the prediction performance between the models. The advantages of the neural network model were that, for similar performance, it did not require an understanding of the underlying principles of cycling nor did it require measurements of fixed parameters such as system weight or wheel size. These same features also give the physics-based model the advantage of interpretability, which can be important when scientists want to better understand the process being modelled.
The entropy of resting-state neural dynamics is a marker of general cognitive ability in childhood
Authors: Zdorovtsova Natalia , Young Edward J. , Akarca Danyal , Anwyl-Irvine Alexander ,   The RED Team,   The CALM Team, Astle Duncan E. 
Published: August 2023

1AbstractResting-state network activity has been associated with the emergence of individual differences across childhood development. However, due to the limitations of time-averaged representations of neural activity, little is known about how cognitive and behavioural variability relates to the rapid spatiotemporal dynamics of these networks. Magnetoencephalography (MEG), which records neural activity at a millisecond timescale, can be combined with Hidden Markov Modelling (HMM) to track the spatial and temporal characteristics of transient neural states. We applied HMMs to resting-state MEG data from (n = 46) children aged 8-13, who were also assessed on their cognitive ability and across multiple parent-report measures of behaviour. We found that entropy-related properties of participants’ resting-state time-courses were positively associated with cognitive ability. Additionally, cognitive ability was positively correlated with the probability of transitioning into HMM states involving fronto-parietal and somatomotor activation, and negatively associated with a state distinguished by default-mode network suppression. We discuss how using dynamical measures to characterise rapid, spontaneous patterns of brain activity can shed new light on neurodevelopmental processes implicated in the emergence of cognitive differences in childhood.Significance StatementThere is increasing evidence that the function of resting-state brain networks contributes to individual differences in cognition and behaviour across development. However, the relationship between dynamic, transient patterns of switching between resting-state networks and neurodevelopmental diversity is largely unknown. Here, we show that cognitive ability in childhood is related to the complexity of resting-state brain dynamics. Additionally, we demonstrate that the probability of transitioning into and remaining in certain ‘states’ of brain network activity predicts individual differences in cognitive ability.
BRAND: A platform for closed-loop experiments with deep network models
Authors: Ali Yahia H. , Bodkin Kevin , Rigotti-Thompson Mattia , Patel Kushant , Card Nicholas S. , Bhaduri Bareesh , Nason-Tomaszewski Samuel R. , Mifsud Domenick M. , Hou Xianda , Nicolas Claire , Allcroft Shane , Hochberg Leigh R. , Yong Nicholas Au , Stavisky Sergey D. , Miller Lee E. , Brandman David M. , Pandarinath Chethan 
Published: August 2023

AbstractArtificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in existing real-time frameworks. Researchers need a platform that fully supports high-level languages for running ANNs (e.g., Python and Julia) while maintaining support for languages that are critical for low-latency data acquisition and processing (e.g., C and C++). To address these needs, we introduce the Backend for Realtime Asynchronous Neural Decoding (BRAND). BRAND comprises Linux processes, termednodes, which communicate with each other in agraphvia streams of data. Its asynchronous design allows for acquisition, control, and analysis to be executed in parallel on streams of data that may operate at different timescales. BRAND uses Redis to send data between nodes, which enables fast inter-process communication and supports 54 different programming languages. Thus, developers can easily deploy existing ANN models in BRAND with minimal implementation changes. In our tests, BRAND achieved <600 microsecond latency between processes when sending large quantities of data (1024 channels of 30 kHz neural data in 1-millisecond chunks). BRAND runs a brain-computer interface with a recurrent neural network (RNN) decoder with less than 8 milliseconds of latency from neural data input to decoder prediction. In a real-world demonstration of the system, participant T11 in the BrainGate2 clinical trial performed a standard cursor control task, in which 30 kHz signal processing, RNN decoding, task control, and graphics were all executed in BRAND. This system also supports real-time inference with complex latent variable models like Latent Factor Analysis via Dynamical Systems. By providing a framework that is fast, modular, and language-agnostic, BRAND lowers the barriers to integrating the latest tools in neuroscience and machine learning into closed-loop experiments.
Graph Theoretical Network Structures Underlie Age-Related Differences in the Functional Connectome During Rest and Music Listening
Authors: Belden Alexander , Loui Psyche 
Published: August 2023

AbstractAging is associated with decreased functional connectivity within the default mode network, as well as auditory and reward systems which are involved in music listening. Understanding how music listening affects network organization of the aging brain, both globally and specific to the brain networks, will have implications for designing lifestyle interventions that tap into distinct networks in the brain. Here we apply graph-theory metrics of modularity, global efficiency, clustering coefficients, degrees, and betweenness centrality to compare younger and older adults (YA/OA, N=24 per group) in fMRI connectivity during rest and a music listening task. Results show a less modular but more globally efficient connectome in OAs, especially during music listening, resulting in main effects of group and task, as well as group-by-task interactions. ROI analyses indicated that the posterior cingulate is more centrally located than the medial prefrontal cortex in OAs. Overall, reduced modularity and increased global efficiency with age is in keeping with previously-observed functional reorganizations, and interaction effects show that age-related differences in baseline network organization are reflected in, potentially magnified by, music listening.
Profiling novel lateral gene transfer events in the human microbiome
Authors: Hsu Tiffany Y. , Nzabarushimana Etienne , Wong Dennis , Luo Chengwei , Beiko Robert G. , Langille Morgan , Huttenhower Curtis , Nguyen Long H. , Franzosa Eric A. 
Published: August 2023

AbstractLateral gene transfer (LGT) is an important mechanism for genome diversification in microbial populations, including the human microbiome. While prior work has surveyed LGT events in human-associated microbial isolate genomes, the scope and dynamics of novel LGT events arising in personal microbiomes are not well understood, as there are no widely adopted computational methods to detect, quantify, and characterize LGT from complex microbial communities. We addressed this by developing, benchmarking, and experimentally validating a computational method (WAAFLE) to profile novel LGT events from assembled metagenomes. Applying WAAFLE to >2K human metagenomes from diverse body sites, we identified >100K putative high-confidence but previously uncharacterized LGT events (∼2 per assembled microbial genome-equivalent). These events were enriched for mobile elements (as expected), as well as restriction-modification and transport functions typically associated with the destruction of foreign DNA. LGT frequency was quantifiably influenced by biogeography, the phylogenetic similarity of the involved taxa, and the ecological abundance of the donor taxon. These forces manifest as LGT networks in which hub species abundant in a community type donate unequally with their close phylogenetic neighbors. Our findings suggest that LGT may be a more ubiquitous process in the human microbiome than previously described. The open-source WAAFLE implementation, documentation, and data from this work are available athttp://huttenhower.sph.harvard.edu/waafle.
Enhanced generalization and specialization of brain representations of semantic knowledge in healthy aging
Authors: Margolles Pedro , Soto David 
Published: August 2023

AbstractAging is often associated with a decrease in cognitive capacities. However, semantic memory appears relatively well preserved in healthy aging. Both behavioral and neuroimaging studies support the view that changes in brain networks contribute to this preservation of semantic cognition. However, little is known about the role of healthy aging in the brain representation of semantic categories. Here we used pattern classification analyses and computational models to examine the neural representations of living and non-living word concepts. The results demonstrate that brain representations of animacy in healthy aging exhibit increased similarity across categories, even across different task contexts. This pattern of results aligns with the neural dedifferentiation hypothesis that proposes that aging is associated with decreased specificity in brain activity patterns and less efficient neural resource allocation. However, the loss in neural specificity for different categories was accompanied by increased dissimilarity of item-based conceptual representations within each category. Taken together, the age-related patterns of increased generalization and specialization in the brain representations of semantic knowledge may reflect a compensatory mechanism that enables a more efficient coding scheme characterized by both compression and sparsity, thereby helping to optimize the limited neural resources and maintain semantic processing in the healthy aging brain.
A taxon-restricted duplicate ofIroquois3is required for patterning the spider waist
Authors: Setton Emily V. W. , Ballesteros Jesús A. , Blaszczyk Pola O. , Klementz Benjamin C. , Sharma Prashant P. 
Published: August 2023

AbstractThe chelicerate body plan is distinguished from other arthropod groups by its division of segments into two tagmata: the anterior prosoma (“cephalothorax”) and the posterior opisthosoma (“abdomen”). Little is understood about the genetic mechanisms that establish the prosomal-opisthosomal (PO) boundary. To discover these mechanisms, we created high-quality genomic resources for the large-bodied spiderAphonopelma hentzi. We sequenced specific territories along the antero-posterior axis of developing embryos and applied differential gene expression analyses to identify putative regulators of regional identity. After bioinformatic screening for candidate genes that were consistently highly expressed in the posterior segments, we validated the function of highly ranked candidates in the tractable spider modelParasteatoda tepidariorum. Here, we show that an arthropod homolog of the Iroquois complex of homeobox genes is required for proper formation of the boundary between arachnid tagmata. The function of this homolog had not been previously characterized, because it was lost in the common ancestor of Pancrustacea, precluding its investigation in well-studied insect model organisms. Knockdown of the spider copy of this gene, which we designate aswaist-less, inP. tepidariorumresulted in embryos with defects in the PO boundary, incurring discontinuous spider germ bands. We show thatwaist-lessis required for proper specification of dorso-ventral identity in the segments that span the prosoma-opisthosoma boundary, which in adult spiders corresponds to the narrowed pedicel. Our results suggest the requirement of an ancient, taxon-restricted paralog for the establishment of the tagmatic boundary that defines Chelicerata.
Tail length in male versus female fox squirrels (Sciurus niger)
Authors: Nichols Hannah K. , Smith Shaylee K. , Eddington Valerie M. , Calistri-Yeh Adrienne , Kloepper Laura N. , Hilliard Young Vanessa K 
Published: August 2023

ABSTRACTBackgroundArboreal mammals rely on their tails to aid in balance while maneuvering complex habitats. Females experience additional challenges to locomotion due to reproductive demands including altered body mass and/or body shape, which leads to shifts in center of mass. Without compensation, this may increase the risk of losing balance and falling out of trees. We tested the hypothesis that female squirrels have longer tails than males to offset shifts in center of mass that may result from pregnancy.ResultsMorphological data were collected from 57 fox squirrels (Sciurus niger) in northern Indiana in summer 2019 and 2021. Although our initial t-test analysis of relative tail length (RTL) showed that female squirrels had longer tails than males (p= 0.02), a subsequent ANCOVA that controlled for effect of body length indicated no significant effect of sex on tail length (p= 0.42).ConclusionsThe results of this study demonstrate the potential impacts of different analysis methods on overall understanding of organismal functional morphology and are an important addition to the literature on tail form and function, which remains poorly understood compared to other appendages.
A general trait-based model for multiplex ecological networks
Authors: Hale Kayla R. S. , Thébault Elisa , Valdovinos Fernanda S. 
Published: August 2023

SummaryEcological networks can represent the structure of food webs, energy flow, and the many and diverse types of interactions between species in ecosystems. Despite its tremendous importance for understanding biodiversity, stability, ecosystem functioning, research on ecological networks has traditionally been restricted to subsets of the species or interactions in ecosystems, i.e., “subnetworks” such as pollination networks or food webs. As a result, the structure of “multiplex” networks that include multiple interaction types is mostly unknown and there is no robust, underlying theory to support their study. Some ecological traits, such as body size or length of mouth parts, are well-known as key predictors of different species interactions. These traits are often strongly related to each other due to evolutionary history, allometry, and selection, and this relatedness may constrain the structure of ecological multiplex networks. We use this idea to develop a model that simulates multiplex ecological networks by interconnecting subnetworks using correlated traits. Our model predicts how multiplex network structure, measured as the overlaps between species’ functional roles, is affected by neutral processes, interaction rules, and trait constraints, while the structure of individual subnetworks is independent of these trait correlations. Additionally, our model accurately predicts the structure of an observed multiplex network using existing knowledge on species trait correlations and basic features of known ecological subnetworks. This work will stimulate new studies of the structure and dynamics of complex ecosystems by providing a null expectation for how multiplex ecological networks are structured under different ecological conditions.
Illuminating the Function of the Orphan Transporter, SLC22A10 in Humans and Other Primates
Authors: Yee Sook Wah , Ferrández-Peral Luis , Alentorn Pol , Fontsere Claudia , Ceylan Merve , Koleske Megan L. , Handin Niklas , Artegoitia Virginia M. , Lara Giovanni , Chien Huan-Chieh , Zhou Xujia , Dainat Jacques , Zalevsky Arthur , Sali Andrej , Brand Colin M. , Capra John A. , Artursson Per , Newman John W. , Marques-Bonet Tomas , Giacomini Kathleen M. 
Published: August 2023

AbstractSLC22A10 is classified as an orphan transporter with unknown substrates and function. Here we describe the discovery of the substrate specificity and functional characteristics of SLC22A10. The human SLC22A10 tagged with green fluorescent protein was found to be absent from the plasma membrane, in contrast to the SLC22A10 orthologs found in great apes. Estradiol-17β-glucuronide accumulated in cells expressing great ape SLC22A10 orthologs (over 4-fold, p<0.001). In contrast, human SLC22A10 displayed no uptake function. Sequence alignments revealed two amino acid differences including a proline at position 220 of the human SLC22A10 and a leucine at the same position of great ape orthologs. Site-directed mutagenesis yielding the human SLC22A10-P220L produced a protein with excellent plasma membrane localization and associated uptake function. Neanderthal and Denisovan genomes show human-like sequences at proline 220 position, corroborating that SLC22A10 were rendered nonfunctional during hominin evolution after the divergence from the pan lineage (chimpanzees and bonobos). These findings demonstrate that human SLC22A10 is a unitary pseudogene and was inactivated by a missense mutation that is fixed in humans, whereas orthologs in great apes transport sex steroid conjugates.
THE NEUROPROTECTIVE ROLE OF NICOTINE AND ASCORBIC ACID ON ALUMINIUM CHLORIDE (ALCL3)-INDUCED NEUROTOXICITY IN THE HIPPOCAMPUS OF ADULT MALE WISTER RATS
Authors: Akanbi Kareemat Adebanke , Ilesanmi Aramide 
Published: August 2023

AbstractObjectivesFree radicals induced oxidative stress has been disrupted in the neurological functionality of the hippocampus in relation to aluminium chloride induced neurotoxicity. Ascorbic acid was been used as an antioxidants to prevent the oxidative damage induced by aluminium chloride. Therefore this present study was conducted to evaluate the antioxidant role Ascorbic acid and nicotine against the neurodegenerative consequences associated with aluminium chloride.Materials and methodThirty five (35) adult male Wister rats weighing 130-150g per body weight was used for this study. The rats were randomly grouped into five groups (A, B, C, D, and E) with each group having seven animals. Animals in group A(control group) were fed only water ad libitum for 21 days; animals in group B were administered Aluminium Chloride only with 100mg/kgBW for 21 days; animals in group C were administered aluminium chloride for the first 21 days with 100mg/kgBW, after which nicotine of 14mg/kgBW was administered. Animals in group D was administered with aluminium chloride of 100mg/kgBW for the first 21days after which Ascorbic acid was administered with 100mg/kgBW for the next 21days. Animals in group E were administered with Aluminium chloride, received 100mg/kgBW of Alcl3for the first 21days then 14mg/kgBW Nicotine for 21days follow by administration of 100mg/kgBW of Ascorbic acid for the next 21days, concomitantly.ResultsOxidative stress was observed from the degeneration the antioxidants (catalase, glutathione peroxidase, superoxide dismutase) in animals that were exposed to aluminium chloride. Histological examination showed that the hippocampus microarchitecture of animals exposed to aluminium chloride have a neurodegenerative changes characterized fragmentation, chromatolytic changes as well as some pyknotic changes in the purkinje and granule cell layers with a gross reduction in the cytoplasmic Nissl proteins. Administration of Ascorbic acid and nicotine was said to revert close to all the cytoarchitectural, biochemical, neurochemical, and immunohistochemical alterations induced by aluminium chloride neurotoxicity.ConclusionThe results suggests that the administration of Ascorbic acid and nicotine may have caused a significant ameliorative effect against the neurotoxicity of aluminium chloride.
Modelled impact of Tiny Targets on the distribution and abundance of riverine tsetse
Authors: Vale Glyn A , Hargrove John W , Hope Andrew , Torr Steve J 
Published: August 2023

AbstractBackgroundThe insecticide-treated baits known as Tiny Targets are one of the cheapest means of controlling riverine species of tsetse flies, the vectors of the trypanosomes that cause sleeping sickness in humans. Models of the efficacy of these targets deployed near rivers are potentially useful in planning control campaigns and highlighting the principals involved.Methods and principal findingsWe produced a simple non-seasonal model of the births, deaths, mobility and aging of tsetse, and we programmed it to simulate the impact of seven years of target use against the tsetse,Glossina fuscipes fuscipes, in the riverine habitats of NW Uganda. The model’s outputs matched reality in showing that: (i) good control can be achieved despite the degradation of targets, (ii) local elimination of tsetse is impossible if invasion sources are not tackled, and (iii) with invasion and target degradation it is difficult to detect any effect of control on the age structure of the tsetse population.ConclusionsDespite its simplifications, the model can assist planning and teaching, but allowance should be made for any complications due to seasonality and management challenges associated with greater scale.Author summaryWe produced a simple model of the population dynamics of the riverine tsetse fly,Glossina fuscipes fuscipes, to simulate the field results of controlling this insect for seven years using Tiny Targets, i.e., artificial insecticide-treated baits, in NW Uganda. The model is potentially useful in planning tsetse control and illustrating the principles involved. Thus, it confirmed that targets can give good control, even if the targets degrade so much that they need replacement after six months. It showed that reinvasion can limit severely the efficacy of control campaigns and mask the changes in the age structure of the population. We stress the need to consider the possibility of seasonal complications and problems of managing large scale operations.