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Autism Spectrum Disorder (ASD) is characterized by early attentional differences that often precede the hallmark symptoms of social communication impairments. Development of novel measures of attentional behaviors may lead to earlier identification of children at risk for ASD. In this work, we first introduce a behavioral measure, Relative Average Look Duration (RALD ), indicating attentional preference to different stimuli, such as social versus nonsocial stimuli; and then study its association with neurophysiological activity. We show that (1) ASD and typically developing (TD) children differ in both (absolute) Average Look Duration (ALD) and RALD to stimuli during an EEG experiment, with the most pronounced differences in looking at social stimuli; and (2) associations between looking behaviors and neurophysiological activity, as measured by EEG, are different for children with ASD versus TD. Even when ASD children show attentional engagement to social content, our results suggest that their underlying brain activity is different than TD children. This study therefore introduces a new measure of social/nonsocial attentional preference in ASD and demonstrates the value of incorporating attentional variables measured simultaneously with EEG into the analysis pipeline.

Electroencephalography (EEG) recordings with visual stimuli require detailed coding to determine the periods of participant’s attention. Here we propose to use a supervised machine learning model and off-the-shelf video cameras only. We extract computer vision-based features such as head pose, gaze, and face landmarks from the video of the participant, and train the machine learning model (multi-layer perceptron) on an initial dataset, then adapt it with a small subset of data from a new participant. Using a sample size of 23 autistic children with and without co-occurring ADHD (attention-deficit/hyperactivity disorder) aged 49–95 months, and training on additional 2560 labeled frames (equivalent to 85.3 s of the video) of a new participant, the median area under the receiver operating characteristic curve for inattention detection was 0.989 (IQR 0.984–0.993) and the median inter-rater reliability (Cohen’s kappa) with a trained human annotator was 0.888. Agreement with human annotations for nine participants was in the 0.616–0.944 range. Our results demonstrate the feasibility of automatic tools to detect inattention during EEG recordings, and its potential to reduce the subjectivity and time burden of human attention coding. The tool for model adaptation and visualization of the computer vision features is made publicly available to the research community.

Live cells are complex information-processing systems that continuously sense their environment and respond dynamically. However, conventional endpoint assays typically require fixation or cell destruction and fail to capture complex temporal changes. Live brightfield imaging offers a scalable, label-free solution that remains underutilized due to particularly low contrast, acute technical batch sensitivity, and the limited availability of robust computational methods for this modality. Leveraging recent self-supervised learning developments, we introduce Live Cell Dynamics (LCD), a novel end-to-end transformer-based pipeline, using novel plane-agnostic augmentation (treating different focal planes as views of the same state) and incorporating cross-batch sampling. LCD addresses brightfield modality challenges and extracts subtle dose- and time-dependent live cell states. Through systematic ablation we evaluate each self-supervised training innovation on a single cell line, measuring phenotypic activity (mean Average Precision) and Mechanism of Action (MoA) classification (F1-score), with 189 compounds in pre-training and 81 in holdout spanning ten MoAs. Our approach outperforms ablated baselines across all doses and timepoints for activity and MoA classification, enables compound polypharmacology detection from multi-dose/timepoint profiles, and supports unsupervised nuclei detection and counting. It leads to training foundation models from continuous live brightfield imaging to detect subtle live cell state changes, enabling scalable, cost-effective drug development.

The article presents various methods for producing mixed heat-resistant binders able to harden in air at normal temperature. The processes of binders synthesis based on hydraulic cements and inorganic refractory industrial waste: aluminium-chromium petrochemical waste and expanded clay dust are considered to create high-temperature heat-resistant binders and concretes based on them. Light concretes with porous aggregates are offered to obtain a highly porous refractory material of air hardening.

The main goal of our study was to determine a set of thawed stallion sperm characteristics that have predictive value for the pregnancy rate (PR) of mares after artificial insemination (AI). DNA fragmentation and survival of sperm during hypothermic storage were studied in addition to routinely determined semen characteristics such as concentration, percentage of motile spermatozoa, and morphology. To estimate DNA fragmentation, a modified hallo assay was applied. Sperm survival was determined within hours as the ability of spermatozoa to maintain progressive motility (PM) during the storage of ejaculate diluted with lactose-chelate-citrate-yolk (LCCY) medium at +4 °C. Strong positive correlation between PR and thawed sperm motility (r = 0.90, p < 0.05) as well as between PR and sperm survival (r = 084, p < 0.05) was revealed. There was also a strong negative correlation between PR and DNA damages in spermatozoa (r = −0.94, p < 0.05). We found no dependence of PR on normal morphology spermatozoa percentage in thawed semen. We concluded that the sperm activity, survival, and DNA fragmentation should be considered as the sufficient reproductive characteristics of semen to evaluate the quality of frozen/thawed sperm and prediction of PR.

Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12–88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen’s d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen’s d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD.

Human parthenogenetic stem cells are derived from the inner cell mass of blastocysts obtained from unfertilized oocytes that have been stimulated to develop without any participation of male gamete. As parthenogenesis does not involve the destruction of a viable human embryo, the derivation and use of human parthenogenetic stem cells does not raise the same ethical concerns as conventional embryonic stem cells. Human parthenogenetic stem cells are similar to embryonic stem cells in their proliferation and multilineage in vitro differentiation capacity. The aim of this study is to derive multipotent neural stem cells from human parthenogenetic stem cells that are stable to passaging and cryopreservation, and have the ability to further differentiate into functional neurons. Immunocytochemistry, quantitative real-time PCR, or FACS were used to confirm that the derived neural stem cells express neural markers such as NES, SOX2 and MS1. The derived neural stem cells keep uniform morphology for at least 30 passages and can be spontaneously differentiated into cells with neuron morphology that express TUBB3 and MAP2, and fire action potentials. These results suggest that parthenogenetic stem cells are a very promising and potentially unlimited source for the derivation of multipotent neural stem cells that can be used for therapeutic applications.

Alterations in regional subcortical brain volumes have been investigated as part of the efforts of an international consortium, ENIGMA, to identify reliable neural correlates of major depressive disorder (MDD). Given that subcortical structures are comprised of distinct subfields, we sought to build significantly from prior work by precisely mapping localized MDD‐related differences in subcortical regions using shape analysis. In this meta‐analysis of subcortical shape from the ENIGMA‐MDD working group, we compared 1,781 patients with MDD and 2,953 healthy controls (CTL) on individual measures of shape metrics (thickness and surface area) on the surface of seven bilateral subcortical structures: nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Harmonized data processing and statistical analyses were conducted locally at each site, and findings were aggregated by meta‐analysis. Relative to CTL, patients with adolescent‐onset MDD (≤ 21 years) had lower thickness and surface area of the subiculum, cornu ammonis (CA) 1 of the hippocampus and basolateral amygdala (Cohen's d = −0.164 to −0.180). Relative to first‐episode MDD, recurrent MDD patients had lower thickness and surface area in the CA1 of the hippocampus and the basolateral amygdala (Cohen's d = −0.173 to −0.184). Our results suggest that previously reported MDD‐associated volumetric differences may be localized to specific subfields of these structures that have been shown to be sensitive to the effects of stress, with important implications for mapping treatments to patients based on specific neural targets and key clinical features.

We report preliminary results of computer vision analysis of caregiver–child interactions during free play with children diagnosed with autism (N = 29, 41–91 months), attention-deficit/hyperactivity disorder (ADHD, N = 22, 48–100 months), or combined autism + ADHD (N = 20, 56–98 months), and neurotypical children (NT, N = 7, 55–95 months). We conducted micro-analytic analysis of ‘reaching to a toy,’ as a proxy for initiating or responding to a toy play bout. Dyadic analysis revealed two clusters of interaction patterns, which differed in frequency of ‘reaching to a toy’ and caregivers’ contingent responding to the child’s reach for a toy by also reaching for a toy. Children in dyads with higher caregiver responsiveness had less developed language, communication, and socialization skills. Clusters were not associated with diagnostic groups. These results hold promise for automated methods of characterizing caregiver responsiveness in dyadic interactions for assessment and outcome monitoring in clinical trials.

One of the main goals of sturgeon aquaculture is the restoration and renewal of wild populations of sturgeon fish in nature, which creates a tension between selective breeding with maintenance of valuable economic traits in a homozygous state and the need to conserve genetic diversity ensuring fitness in natural environments. It is generally assumed that important economic characteristics, such as body weight and size, growth rate, fecundity, etc., as well as fitness in fish, are associated with heterozygosity and genetic polymorphism of some key metabolic enzymes. It remains unclear whether aquaculture conditions can be as a whole selection factor in favor of certain allelic variants of these enzymes. To establish the relationship between some economic traits and enzymatic polymorphism, we studied the distribution of allelic variants of LDH-3, AAT-2, FGM, and Est enzymes in stellate sturgeon reared in aquaculture. We revealed a frequency bias of some allelic variants of the studied enzymes in a cohort of fish from the generation bred in aquaculture compared to the frequencies of those alleles in wild natural populations. Our study suggests that industrial breeding promotes selection in the direction of reducing size but increasing survival rates, which correlates with certain allelic variants.