Miracle-dz/UniFAR-FTUs huggingface dataset:
Dissecting the heterogeneous subcortical brain volume of autism spectrum disorder using community detection

Structural brain alterations found in Autism Spectrum Disorder (ASD) have previously been very heterogeneous, with overall limited effect sizes for every region implicated. In this study, we aimed at exploring the existence of subgroups in ASD, based on neuroanatomic profiles; we hypothesized that effect sizes of case/control difference would be increased in defined subgroups. Using the dataset from the ENIGMA-ASD Working Group (n=2661), exploratory factor analysis (EFA) was applied on seven subcortical volumes of individuals with ASD and controls to uncover the underlying organization of subcortical structures. Based on earlier findings in ADHD patients and controls as well as data availability, we focused on three age groups: boys (aged 4-14 years), male adolescents (aged 14-22 years), and adult men (aged >=22 years). The resulting factor scores were used in a community detection (CD) analysis, to cluster participants into subgroups. Three factors were found in each sample, with the factor structure in adult men differing from that in boys and male adolescents. From the patterns in these factors, CD uncovered four distinct communities in boys and three communities in adolescents and adult men, irrespective of ASD diagnostic status. The effect sizes of case/control comparisons appeared more pronounced than in the whole sample in some communities. Based on subcortical volumes, we succeeded in stratifying our participants into more homogeneous subgroups with similar brain structural patterns. The stratification enhanced our ability to observe case/control differences of subcortical brain volumes in ASD, and may help explain some of the heterogeneity of previous findings in ASD.
Diversity and Function of the Eastern Oyster (Crassostrea virginica) Microbiome

Marine invertebrate microbiomes play important roles in various host and ecological processes. However, a mechanistic understanding of host-microbe interactions is so far only available for a handful of model organisms. Here, an integrated taxonomic and functional analysis of the microbiome of the eastern oyster, Crassostrea virginica, was performed using 16S rRNA gene amplicon profiling, shotgun metagenomics, and genome-scale metabolic reconstruction. A relatively low number of amplicon sequence variants (ASVs) were observed in oyster tissues compared to water samples, while high variability was observed across individual oysters and among different tissue types. Targeted metagenomic sequencing of the gut microbiota led to further characterization of a dominant bacterial taxon, the class Mollicutes, which was captured by the reconstruction of a metagenome-assembled genome (MAG). Genome-scale metabolic reconstruction of the oyster Mollicutes MAG revealed a reduced set of metabolic functions and a high reliance on the uptake of host-derived nutrients. A chitin degradation and an arginine deiminase pathway were unique to the MAG as compared to other closely related Mycoplasma genomes, indicating a distinct mechanism of carbon and energy acquisition by the oyster- associated Mollicutes. A systematic reanalysis of public eastern oyster-derived microbiome data revealed the Mollicutes as a ubiquitous taxon among adult oysters despite their general absence in larvae and biodeposit samples, suggesting potential horizontal transmission via an unknown mechanism. IMPORTANCE Despite well-documented biological significance of invertebrate microbiomes, a detailed taxonomic and functional characterization is frequently missing from many non-model marine invertebrates. By using 16S rRNA gene-based community profiling, shotgun metagenomics, and genome-scale metabolic reconstruction, this study provides an integrated taxonomic and functional analysis of the microbiome of the eastern oyster, Crassostrea virginica. Community profiling revealed a surprisingly low richness, as compared to surrounding seawater, and high variability among different tissue types and individuals. Reconstruction of a Mollicutes MAG enabled the phylogenomic positioning and functional characterization of the oyster-associated Mollicutes. Comparative analysis of the adult oyster gut, biodeposits, and oyster larvae samples indicated the potentially ubiquitous associations of the Mollicutes taxon with adult oysters. To the best of our knowledge, this study represented the first metagenomics derived functional inference of the eastern oyster microbiome. An integrated analytical procedure was developed for the functional characterization of microbiomes in other non-model host species.
A shift to shorter cuticular hydrocarbons causes sexual isolation in the Drosophila americana species group

Because sensory signals often evolve rapidly, they could be instrumental in the emergence of reproductive isolation between species. However, pinpointing their specific contribution to isolating barriers, and the mechanisms underlying their divergence, remains challenging. Here we demonstrate sexual isolation due to divergence in chemical signals between members of the Drosophila americana group, dissect its underlying phenotypic and genetic mechanisms, and propose a model of its evolutionary history. Mating trials revealed complete sexual isolation between Drosophila novamexicana males and Drosophila americana texana females, as well as more moderate bi-directional isolation between D. americana subspecies. Mating behavior recordings indicate D. a. texana males have the highest courtship efficiency and, unlike males of the other two species, are accepted by females of all species. Quantification of cuticular hydrocarbon (CHC) profiles, chemosensory signals that are used for species recognition and mate finding in Drosophila, shows that D. a. texana differs from the other two species primarily on the basis of compound carbon chain-length. Moreover, manipulation of male CHC composition via heterospecific perfuming—specifically perfuming D. novamexicana males with D. a. texana males—abolishes their sexual isolation from D. a. texana females. Evaluation of candidate genes for patterns of gene expression reveals a single gene—elongase CG17821—with patterns consistent with a causal role in CHC differences between species. Sequence comparisons indicate D. novamexicana and D. a. americana share a derived CG17821 truncation mutation that could also contribute to their shared “short” CHC phenotype. We present an evolutionary model for the origin and spread of this allele and the consequences for CHC divergence and sexual isolation in this group.
Age-related differences in the role of the prefrontal cortex in sensory-motor training gains: A tDCS study

The ability to process multiple sources of information concurrently is particularly impaired as individuals age and such age-related increases in multitasking costs have been linked to impairments in response selection. Previous neuroimaging studies with young adults have implicated the left hemisphere prefrontal cortex (PFC) as a key neural substrate of response selection. In addition, several transcranial direct current stimulation studies (tDCS) have provided causal evidence implicating this region in response selection and multitasking operations. For example, Filmer at al. (2013b) demonstrated that typically observed response selection learning/training gains in young adults were disrupted via offline transcranial direct current stimulation (tDCS) of left, but not right, PFC. Here, considering evidence of functional dedifferentiation in the brains of older adults, we assessed if this pattern of response selection learning disruption via tDCS to the left PFC is observed in older adults, testing if this region remains a key response selection node as individuals age. In a pre-registered study with 58 older adults, we applied anodal, cathodal, and sham stimulation to left and right PFC, and measured performance as participants trained on low- and high-response selection load tasks. Active stimulation did not disrupt training in older adults as compared to younger adults. However, there was evidence of enhanced training gains via tDCS, which scaled with response selection task difficulty. The results highlight age-related differences in the casual neural substrates that subserve response selection and learning.
The Sperm Centrosome: Its Role and Significance in Nature and Human Assisted Reproduction:

In humans and other non-rodent mammalian species, the sperm's centriole-centrosome complex is an essential component for successful fertilization and serves as template for all centrioles during subsequent cell divisions, embryo development, divisions of most adult somatic cells, as well as in primary cilia formation and functions. Dysfunctions of this complex can be causes for infertility, developmental disorders, and play a role in various adulthood diseases. While assisted reproductive technology (ART) has been able to overcome sperm motility dysfunctions by employing intracytoplasmic sperm injection (ICSI), we currently do not yet have therapies to overcome dysfunctions of the centriole-centrosome complex although several lines of investigations have addressed the causes for centriole-centrosome dysfunctions and implications for sperm aster formation and union of the parental genomes. The present review highlights the importance of the centriole-centrosome complex and its significance for fertilizatio.
Retinal circuits driving a non-image forming visual behavior

Outer retinal circuits that drive non-image forming vision in mammals are unknown. Rods and cones signal light increments and decrements to the brain through the ON and OFF pathways, respectively. Although their contribution to image-forming vision is known, the contributions of the ON and OFF pathway to the pupillary light response (PLR), a non-image forming behavior, are unexplored. Here we use genetically modified mouse lines, to comprehensively define the outer retinal circuits driving the PLR. The OFF pathway, which mirrors the ON pathway in image-forming vision, plays no role in the PLR. We found that rods use the primary rod pathway to drive the PLR at scotopic light levels. At photopic light levels, the primary and secondary rod pathways drive normal PLR. Importantly, we find that cones are unable to compensate for rods. Thus, retinal circuit dynamics allow rods to drive the PLR across a wide range of light intensities.
Effects of Long-Term Meditation Practices on Sensorimotor Rhythm Based BCI Learning

Sensorimotor rhythm (SMR) based brain-computer interfaces (BCIs) provide an alternative pathway for users to perform motor control using motor imagery (MI). Despite the non-invasiveness, ease of use and low cost, this kind of BCI has limitation due to long training times and BCI inefficiency— where a subpopulation cannot generate decodable EEG signals to perform the control task. Meditation is a mental training method to improve mindfulness and awareness, and is reported to have a positive effect on one’s mental state. Here we investigate the behavioral and electrophysiological differences between experienced meditators and meditation naïve subjects in 1-dimensional and 2-dimensional cursor control tasks. We found that within subjects who have room for improvement, meditators outperformed control subjects in both tasks, and there were fewer BCI insufficient subjects in the meditator group. Finally, we also explored the neurophysiological difference between the two groups, and showed that meditators had higher SMR predictor and were better able to generate decodable EEG signals to achieve SMR BCI control.
Label-free imaging and classification of live P. falciparum

Manual microscopic inspection of fixed and stained blood smears has remained the gold standard for Plasmodium parasitemia analysis for over a century. Unfortunately, smear preparation consumes time and reagents, while manual microscopy is skill-dependent and labor-intensive. Here, we demonstrate that label-free microscopy combined with deep learning enables both life stage classification and accurate parasitemia quantification. Using a custom-built microscope, we find that deep-ultraviolet light enhances image contrast and resolution, achieving four-category classification of Plasmodium falciparum blood stages at an overall accuracy greater than 99%. To increase accessibility, we extended our method to a commercial brightfield microscope using near-ultraviolet and visible light. Both systems were tested extrinsically by parasitemia titration, revealing superior performance over manually-scored Giemsa-stained smears, and a limit of detection below 0.1%. Our results suggest that label-free microscopy combined with deep learning could eliminate the need for conventional blood smear analysis.
Natural sensory context drives diverse brain-wide activity during C. elegans mating

Natural goal-directed behaviors often involve complex sequences of many stimulus-triggered components. Understanding how brain circuits organize such behaviors requires mapping the interactions between an animal, its environment, and its nervous system. Here, we use continuous brain-wide neuronal imaging to study the full performance of mating by the C. elegans male. We show that as each mating unfolds in its own sequence of component behaviors, the brain operates similarly between instances of each component, but distinctly between different components. When the full sensory and behavioral context is taken into account, unique roles emerge for each neuron. Functional correlations between neurons are not fixed, but change with behavioral dynamics. From the contribution of individual neurons to circuits, our study shows how diverse brain-wide dynamics emerge from the integration of sensory perception and motor actions within their natural context.
Universal Spectrum Explorer: A standalone (web-)application for cross-resource spectrum comparison

Here we present the Universal Spectrum Explorer (USE), a web-based tool based on IPSA for cross-resource (peptide) spectrum visualization and comparison (https://www.proteomicsdb.org/use/). Mass spectra under investigation can either be provided manually by the user (table format), or automatically retrieved from online repositories supporting access to spectral data via the universal spectrum identifier (USI), or requested from other resources and services implementing a newly designed REST interface. As a proof of principle we implemented such an interface in ProteomicsDB thereby allowing the retrieval of spectra acquired within the ProteomeTools project. In addition, USE can retrieve real-time prediction of tandem mass spectra from the deep learning framework Prosit. Comparison results like annotated mirror spectrum plots can be exported from USE as editable scalable high quality vector graphics. The USE was designed and implemented with minimal external dependencies allowing local usage and seamless integration into websites (https://github.com/kusterlab/universal_spectrum_explorer).
Adaptive dating and fast proposals: Revisiting the phylogenetic relaxed clock model

Uncorrelated relaxed clock models enable estimation of molecular substitution rates across lineages and are widely used in phylogenetics for dating evolutionary divergence times. In this article we delved into the internal complexities of the relaxed clock model in order to develop efficient MCMC operators for Bayesian phylogenetic inference. We compared three substitution rate parameterisations, introduced an adaptive operator which learns the weights of other operators during MCMC, and we explored how relaxed clock model estimation can benefit from two cutting-edge proposal kernels: the AVMVN and Bactrian kernels. This work has produced an operator scheme that is up to 65 times more efficient at exploring continuous relaxed clock parameters compared with previous setups, depending on the dataset. Finally, we explored variants of the standard narrow exchange operator which are specifically designed for the relaxed clock model. In the most extreme case, this new operator traversed tree space 40% more efficiently than narrow exchange. The methodologies introduced are adaptive and highly effective on short as well as long alignments. The results are available via the open source optimised relaxed clock (ORC) package for BEAST 2 under a GNU licence (https://github.com/jordandouglas/ORC). Author summary Biological sequences, such as DNA, accumulate mutations over generations. By comparing such sequences in a phylogenetic framework, the evolutionary tree of lifeforms can be inferred. With the overwhelming availability of biological sequence data, and the increasing affordability of collecting new data, the development of fast and efficient phylogenetic algorithms is more important than ever. In this article we focus on the relaxed clock model, which is very popular in phylogenetics. We explored how a range of optimisations can improve the statistical inference of the relaxed clock. This work has produced a phylogenetic setup which can infer parameters related to the relaxed clock up to 65 times faster than previous setups, depending on the dataset. The methods introduced adapt to the dataset during computation and are highly efficient when processing long biological sequences.
Heteroscedastic regression modeling elucidates gene-by-environment interaction

Genotype-by-environment interaction (GxE) occurs when the size of a genetic effect varies systematically across levels of the environment and when the size of an environmental effect varies systematically across levels of the genotype. However, total variance in the phenotype may shift as a function of the moderator irrespective of its etiology such that the proportional effect of the predictor is constant. We expand the traditional GxE regression model for polygenic scores and single locus allele counts to directly account for heteroscedasticity associated with both the genotype and the measured environment, and we derive a test statistic, ξ, for inferring whether GxE can be plausibly attributed to a more general effect of the genetic or environmental moderator on the dispersion of the phenotype. We apply this method to test whether genotype-by-birth year interactions for Body Mass Index (BMI) are distinguishable from general secular increases in the variance of BMI or associations of the genetic predictors (both PGS and individual loci) with BMI variance. We provide software for estimating heteroscedastic GxE regression models and calculating ξ.
Variations of High Molecular Weight Glutenin Subunit 1Ay in Einkorn Wheat

In this paper,the variations of high molecular weight glutenin subunit(HMW-GS) 1Ay in 44 lines of einkorn wheats were investigated by means of sodium dodecyl sulfate polyacrylamide-gel electrophoresis(SDS-PAGE). The expressed 1Ay widely existed in the species including T.urartu,T.boeoticum and T.moncoccum in einkorn wheat.The expressed frequencies of 1Ay in T.urartu,T.boeoticum and T.monococcum were 42.86%,81.25% and 100%,respectively.The polymorphism of 1Ay mobility in the tested species was observed.The six patterns,including the similar and faster subunits compared to 1Dy12,the similar,faster and slower subunits compared to 1Bx7,and the similar subunits to 1By8,were separated in the species.Among them,the mobilites of 1Ay from T.urartu were close to 1Dy12,while those from T.boeoticum and T.monococcum were close to 1Bx7.The distribution of 1Ay wasn't totally related to geographical origin.Within a species,there were variations on the frequencies of expressed 1Ay among different areas.There were variations on the mobilities among lines from same area.The diversity on 1Ay in einkorn wheat may be useful in wheat quality improvement.
Modélisation de la dynamique de l'hématopoïèse normale et pathologique Modelling the dynamics of normal and pathological haematopoiesis

To be able to predict quantitatively onco-haematological treatment outcomes, it is essential to accurately describe the qualitative dynamics of blood cell production, i.e. the time evolution properties for the cell populations — equilibrium, extinction, oscillation or unlimited growth. Here, we review and present examples of several cell population mathematical models for haematopoiesis that played an important role in the understanding of this problem. Thirty years ago, one of the first deterministic mathematical models of haematopoiesis was proposed in which a stem cell population is divided into a proliferating and a quiescent fraction [1]. Four parameters describe the cell cycle: the rate of entry into proliferation, the duration of the proliferative phase and the rate of loss (apoptosis) for the proliferative phase and for the quiescent phase (differentiation). It was shown that an increase in the rate of apoptosis was sufficient to explain the observed oscillations in reticulocyte numbers in haemolytic anaemia. Subsequent models were developed to explain particular dynamics in other blood diseases (reviewed in [5]). Despite early success, new problems, like those arising in onco-haematology, called for different modelling frameworks. Three current approaches are reviewed here. Stochastic models use the probabilistic nature of the fate of blood cells — death, differentiation, mutation — to characterize the structure of the haematopoietic system [16,17]. These models are useful to study the dynamics of rare events (mutations) occurring in small stem cell populations [19]. Spatial models of the bone marrow are being developed to help understanding the role of cell movement and competition for space. These spatial models can be reaction-diffusion equations [28] or multi-agent, individual-centered models [33]. Compartment models address specific questions related to haematotoxicity of various drugs, in the sense that they Hematologie 2008 ; 14 (5) : 339-50 Hematologie, vol. 14, n° 5, septembre-octobre 2008 339 do i: 10 . 1 68 4/ hm a. 20 08 . 0 28 2 © John Libbey Eurotext, 2008 Ti re a p ar t a t ur do not aim at explaining the origin or the dynamics of the diseases but at quantitatively predicting therapeutic outcomes of these drugs [20,21]. We chose to develop four examples of applications of mathematical models in haematopoiesis: periodic physiological haematopoiesis; chronic myeloid leukaemia; spatial competition within the bone marrow; and feedback regulation and self-renewal in the erythroid lineage after stress. These examples have been chosen amongst many others because they appear to be significant illustrations of the different models listed in the review.