Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Sex from Resting-State fMRI Across Multiple Independent Acquired Datasets

Sex is an important biological variable often used in analyzing and describing the functional organization of the brain during cognitive and behavioral tasks. Several prior studies have shown that blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) functional connectivity (FC) can be used to differentiate sex among individuals. Herein, we demonstrate that sex can be further classified with high accuracy using the intrinsic BOLD signal fluctuations from resting-state fMRI (rs-fMRI). We adopted the amplitude of low-frequency fluctuation (ALFF), and the fraction of ALFF (fALFF) features from the automated anatomical atlas (AAL) and Power’s functional atlas as an input to different machine learning (ML) methods. Using datasets from five independently acquired subject cohorts and with eight fMRI scanning sessions, we comprehensively assessed unbiased performance using nested-cross validation for within-sample and across sample accuracies. The results demonstrated high prediction accuracies for the Human Connectome Project (HCP) dataset (area under cure (AUC) > 0.89). The yielded accuracies suggest that sex difference is embodied and well-pronounced in the low-frequency BOLD signal fluctuation. The performance degrades with the heterogeneity of the cohort and suggests that other factors,. e.g. psychiatric disorders and demographics influences the BOLD signal and may interact with the classification of sex. In addition, the results revealed high learning generalizability with the HCP scan, but not across different datasets. The intraclass correlation coefficient (ICC) across HCP scans showed moderate-to-good reliability based on atlas selection (ICC = 0.65 [0.63-0.67] and ICC= 0.78 [0.76-0.80].). We also assessed the effect of scan duration on the predictability of sex and showed that sex differences could be detected even with a short rs-fMRI scan (e.g., 2 minutes). Moreover, we provided statistical maps of the brain regions differentially recruited by or predicting sex using Shapely values and determined an overlap with previous reports of brain response due to sex differences. Altogether, our analysis suggests that sex differences are well-pronounced in rs-fMRI and should be considered seriously in any study design, analysis, or interpretation.
Meta-analysis shows that context-dependent mating behaviour is inconsistent or weak across animals

Animals often need to invest significantly in mating behaviour in order to successfully mate. However, the expression of mating behaviour can be costly, especially in unfavourable environments, so animals are expected to adjust their behaviour in a context-dependent way to mitigate these costs. I systematically searched the literature for studies measuring animal mating behaviour (sexual signalling, response to sexual signals, or the strength of mate choice) in more than one environment, and used a phylogenetically-controlled meta-analysis to identify environmental factors influencing these behaviours. Across 222 studies, the strength of mate choice was significantly context-dependent, and most influenced by population density, population sex ratio, and predation risk. However, the average effect sizes were typically small. The amount of sexual signalling and the strength of response to sexual signals were not significantly related to the environment. Overall, this suggests that the evidence for context-dependent mating behaviour across animals is surprisingly weak.
Solving musculoskeletal biomechanics with machine learning

Deep learning is a relatively new computational technique for the description of the musculoskeletal dynamics. The experimental relationships of muscle geometry in different postures are the high-dimensional spatial transformations that can be approximated by relatively simple functions, which opens the opportunity for machine learning applications. In this study, we challenged general machine learning algorithms with the problem of approximating the posture-dependent moment arm and muscle length relationships of the human arm and hand muscles. We used two types of algorithms, light gradient boosting machine (LGB) and fully connected artificial neural network (ANN) solving the wrapping kinematics of 33 muscles spanning up to six degrees of freedom (DOF) each for the arm and hand model with 18 DOFs. The input-output training and testing datasets were generated by our previous phenomenological model based on the autogenerated polynomial structures (Sobinov et al., 2019). Both models achieved a similar level of errors: ANN model errors were 0.08±0.05% for muscle lengths and 0.53±0.29% for moment arms, and LGB model made similar errors—0.18±0.06% and 0.13±0.07%, respectively. LGB model reached the training goal with only 10^3 samples, while ANN required 10^6 samples; however, LGB models were about 39 slower than ANN models in the evaluation. The sufficient performance of developed models demonstrates the future applicability of machine learning for musculoskeletal transformations in a variety of applications, such as in advanced powered prosthetics. Author Summary The accurate decoding of arm and hand motor intent from biological signals remains a key challenge. Solving this task with machine learning requires vast posture- and task-dependent data for identifying structural and functional parameters within dynamic musculoskeletal relationships. This problem is related to the curse of dimensionality where the processing complexity grows exponentially with the number of degrees of freedom described by the model. Here, we developed a tool based on artificial neural networks (ANN) to solve the kinematic transformation from posture to muscle path length and muscle moment arms. We used an accurate model of posture-dependent muscle moment arms and length to train and test the ability of ANN to solve this high-dimensional and computationally intense transformation and compare it to the boosted decision tree approach. We demonstrated that model-driven training is an efficient method to handle the encoding of high-dimensional musculoskeletal relationships. Adding muscles to the transformation, which increases the input-output complexity, does not reduce the prediction accuracy and does not require the increase in the number of elements within the network demonstrating the viability of this approach for applications using musculoskeletal biomechanics.
Transcutaneous Vagus Nerve Stimulation in Humans Induces Pupil Dilation and Attenuates Alpha Oscillations

Vagus nerve stimulation (VNS) is widely used to treat drug-resistant epilepsy and depression. While the precise mechanisms mediating its long-term therapeutic effects are not fully resolved, they likely involve locus coeruleus (LC) stimulation via the nucleus of the solitary tract, which receives afferent vagal inputs. In rats, VNS elevates LC firing and forebrain noradrenaline levels, whereas LC lesions suppress VNS therapeutic efficacy. Noninvasive transcutaneous VNS (tVNS) uses electrical stimulation that targets the auricular branch of the vagus nerve at the cymba conchae of the ear. However, the extent to which tVNS mimics VNS remains unclear. Here, we investigated the short-term effects of tVNS in healthy human male volunteers (n = 24), using high-density EEG and pupillometry during visual fixation at rest. We compared short (3.4 s) trials of tVNS to sham electrical stimulation at the earlobe (far from the vagus nerve branch) to control for somatosensory stimulation. Although tVNS and sham stimulation did not differ in subjective intensity ratings, tVNS led to robust pupil dilation (peaking 4–5 s after trial onset) that was significantly higher than following sham stimulation. We further quantified, using parallel factor analysis, how tVNS modulates idle occipital alpha (8–13Hz) activity identified in each participant. We found greater attenuation of alpha oscillations by tVNS than by sham stimulation. This demonstrates that tVNS reliably induces pupillary and EEG markers of arousal beyond the effects of somatosensory stimulation, thus supporting the hypothesis that tVNS elevates noradrenaline and other arousal-promoting neuromodulatory signaling, and mimics invasive VNS. SIGNIFICANCE STATEMENT Current noninvasive brain stimulation techniques are mostly confined to modulating cortical activity, as is typical with transcranial magnetic or transcranial direct/alternating current electrical stimulation. Transcutaneous vagus nerve stimulation (tVNS) has been proposed to stimulate subcortical arousal-promoting nuclei, though previous studies yielded inconsistent results. Here we show that short (3.4 s) tVNS pulses in naive healthy male volunteers induced transient pupil dilation and attenuation of occipital alpha oscillations. These markers of brain arousal are in line with the established effects of invasive VNS on locus coeruleus–noradrenaline signaling, and support that tVNS mimics VNS. Therefore, tVNS can be used as a tool for studying how endogenous subcortical neuromodulatory signaling affects human cognition, including perception, attention, memory, and decision-making; and also for developing novel clinical applications.
Acetylated and hydroxypropylated wheat starch: paste and gel properties compared with modified maize and tapioca starches

Preparation d'amidon phosphate acetyle et hydroxypropyle a partir de mais et de ble normaux et comparaison des proprietes des pâtes et des gels. Comparaison de ces memes proprietes avec des echantillons commerciaux d'amidon de mais cireux, tapioca et bles
Measuring the density and viscosity of culture media for optimized computational fluid dynamics analysis of in vitro devices

Culture medium is frequently modelled as water in computational fluid dynamics (CFD) analysis of in vitro culture systems involving flow, such as bioreactors and organ-on-chips. However, culture medium can be expected to have different properties to water due to its higher solute content. Furthermore, cellular activities such as metabolism and secretion of ECM proteins alter the composition of culture medium and therefore its properties during culture. As these properties directly determine the hydromechanical stimuli exerted on cells in vitro, these, along with any changes during culture must be known for CFD modelling accuracy and meaningful interpretation of cellular responses. In this study, the density and dynamic viscosity of DMEM and RPMI-1640 media supplemented with typical concentrations of foetal bovine serum (0, 5, 10 and 20% v/v) were measured to serve as a reference for computational design analysis. Any changes in the properties of medium during culture were also investigated with NCI-H460 and HN6 cell lines. The density and dynamic viscosity of the media increased proportional to the % volume of added foetal bovine serum (FBS). Importantly, the viscosity of 5% FBS-supplemented RPMI-1640 was found to increase significantly after 3 days of culture of NCI-H460 and HN6 cell lines, with distinct differences between magnitude of change for each cell line. Finally, these experimentally-derived values were applied in CFD analysis of a simple microfluidic device, which demonstrated clear differences in maximum wall shear stress and pressure between fluid models. Overall, these results highlight the importance of characterizing model-specific properties for CFD design analysis of cell culture systems.
Myocardial glycogen is increased in sedentary rats fed milk whey protein digests when brought to exhaustion

Sedentary and trained rats fed diets containing either whey protein isolate, whey protein hydrolyzate, or casein, were exhausted in the treadmill. At 24 h post-exhaustion, the myocardial glycogen stores were 80%, and glycogen synthase activity 10%, increased in the sedentary group consuming the hydrolyzate. Whey protein hydrolyzate can be a decisive factor in the increase of myocardial glycogen stores only of the sedentary-exhausted animals. These results show that the whey protein hydrolyzate may protect the heart by preparing the stressed cardiomyocyte to readily synthesize glycogen in the sedentary animal, compared to either the whey protein isolate or casein. Key words: Whey protein peptides, exercise stress, glycogen synthase, glycogen phosphorylase, myocardial glycogen.
Evaluation of the 7 & 7 Synch and 7-day CO-Synch + CIDR ® protocols for estrus synchronization of beef cows prior to fixed-time artificial insemination with conventional or sex-sorted semen

An experiment was designed to compare the recently developed 7 & 7 Synch and the 7-day CO-Synch + CIDR protocols for synchronization of estrus among beef cows prior to fixed-time artificial insemination (FTAI) with conventional or sex-sorted semen. Bos taurus cows (n = 1538) were blocked based on age and days postpartum (DPP) and randomly assigned to protocol and semen type. Cows treated with the 7-day CO-Synch + CIDR protocol (n = 769) received administration of gonadotropin-releasing hormone (GnRH; 100 μg gonadorelin) and insertion of a 1.38 g intravaginal progesterone releasing insert (CIDR) on Day -10, and administration of prostaglandin F2α (PG; 500 μg cloprostenol) coincident with CIDR removal on Day -3. Cows treated with 7 & 7 Synch (n = 769) received PG and insertion of CIDR on Day -17, GnRH on Day -10, and PG coincident with CIDR removal on Day -3. Estrus detection aids (Estrotect™) were applied to all cows on Day -3, and activation status was recorded at FTAI. Cows received FTAI 66 h after CIDR removal with either conventional (20 × 106 cells per unit) or sex-sorted (4 × 106 cells per unit; SexedULTRA 4M™) semen. A greater proportion of cows expressed estrus (P = 0.01) prior to FTAI following 7 & 7 Synch (82%; 629/769) compared with the 7-day CO-Synch + CIDR (64%; 492/769). Estrus expression was also affected by protocol × DPP (P = 0.0004), with 7 & 7 Synch resulting in a greater increase in the proportion of cows expressing estrus prior to FTAI among cows with greater DPP. Across protocols, body condition score (BCS) affected (P = 0.05) estrus expression, with greater proportion of cows expressing estrus prior to FTAI at greater BCS. Sex-sorted semen resulted in reduced (P < 0.0001) pregnancy rates to FTAI. Irrespective of semen type, greater (P = 0.001) pregnancy rates to FTAI were obtained among cows treated with 7 & 7 Synch (conventional semen: 72% [280/389]; sex-sorted semen: 52% [199/380]) compared with the 7-day CO-Synch + CIDR (conventional semen: 60% [231/383]; sex-sorted semen: 44% [171/386]). In summary, 7 & 7 Synch resulted in an increased proportion of cows expressing estrus prior to FTAI and an increased pregnancy rate to FTAI with conventional and sexed semen. With these results and ease of application, 7 & 7 Synch offers potential as a platform to improve success with fixed-time AI in beef cows.
MRE11 is crucial for malaria transmission and its absence affects expression of interconnected networks of key genes essential for life

The Meiotic Recombination 11 protein (MRE11) plays a key role in DNA damage response and maintenance of genome stability. However, little is known about its function during development of the malaria parasite Plasmodium. Here, we present a functional, ultrastructural and transcriptomic analysis of Plasmodium MRE11 during its life-cycle in both mammalian and mosquito vector hosts. Genetic disruption of Plasmodium berghei mre11 (PbMRE11) results in significant retardation of oocyst development in the mosquito midgut associated with cytoplasmic and nuclear degeneration, along with concomitant ablation of sporogony and subsequent parasite transmission. Further, absence of PbMRE11 results in significant transcriptional downregulation of genes involved in key interconnected biological processes that are fundamental to all eukaryotic life including ribonucleoprotein biogenesis, spliceosome function and iron-sulphur cluster assembly. Overall, our study provides a comprehensive functional analysis of MRE11’s role in Plasmodium development during the mosquito stages and offers a potential target for therapeutic intervention during malaria parasite transmission.
Comparación de la exactitud de valores genómicos de animales predichos a través del análisis con dos modelos alternativos

El valor genomico es la mejor prediccion del valor genotipico de un animal, cuya exactitud varia en funcion de varios factores. Los objetivos de este estudio fueron, mediante simulacion, comparar la exactitud de los valores genomicos de animales predichos a traves del analisis con dos modelos alternativos, y obtener la correlacion genetica entre estos y los valores geneticos verdaderos simulados. Una poblacion con tamano efectivo de 800 individuos fue simulada y se usaron 100 generaciones para generar desequilibrio de ligamiento. Despues se simulo otra poblacion con 14 generaciones, un panel de 53 010 polimorfismos de nucleotido simple (SNP's) ubicados aleatoriamente en 30 cromosomas y 540 loci de caracteristicas cuantitativas. Tambien se simularon los genotipos y fenotipos de 6400 animales usando una heredabilidad=0.40 y considerando solamente los efectos aditivos. Cuatro conjuntos de valores moleculares fueron entrenados con los marcadores SNP's de las generaciones 7 a 10, y los correspondientes valores geneticos ajustados. Cuando la poblacion de entrenamiento (PEn) tuvo tamano mayor, los estimadores de exactitud (R2) fueron mayores. Similarmente, cuando la poblacion de evaluacion (PEv) estuvo mas cerca a la PEn, los estimadores de R2 fueron mayores y se fueron reduciendo cuando la distancia entre PEn y PEv se incrementaba. El estimador de la varianza del error de prediccion (PEV) fue menor (0.15±0.01) cuando PEn y PEv estuvieron mas cerca, independientemente del tamano de PEn, generacion 10 para PEn y generacion 11 para PEv. Por el contrario, el PEV mayor (0.29±0.02) se obtuvo cuando la PEn incluyo los animales de la generacion siete y se evaluo la generacion 14; es decir, cuando la distancia entre PEn y PEv era mayor
Highly potent anti-SARS-CoV-2 multi-DARPin therapeutic candidates

Globally accessible therapeutics against SARS-CoV-2 are urgently needed. Here, we report the generation of the first anti-SARS-CoV-2 DARPin molecules with therapeutic potential as well as rapid large-scale production capabilities. Highly potent multi-DARPin molecules with low picomolar virus neutralization efficacies were generated by molecular linkage of three different mono-DARPin molecules. These multi-DARPin molecules target various domains of the SARS-CoV-2 spike protein, thereby limiting possible viral escape. Cryo-EM analysis of individual mono-DARPin molecules provided structural explanations for the mode of action. Analysis of the protective efficacy of one multi-DARPin molecule in a hamster SARS-CoV-2 infection model demonstrated a significant reduction of pathogenesis. Taken together, the multi-DARPin molecules reported here, one of which is currently entering clinical studies, constitute promising therapeutics against the COVID-19 pandemic.
Integrating barcoded neuroanatomy with spatial transcriptional profiling reveals cadherin correlates of projections shared across the cortex

Functional circuits consist of neurons with diverse axonal projections and gene expression. Understanding the molecular signature of projections requires high-throughput interrogation of both gene expression and projections to multiple targets in the same cells at cellular resolution, which is difficult to achieve using current technology. Here, we introduce BARseq2, a technique that simultaneously maps projections and detects multiplexed gene expression by in situ sequencing. We determined the expression of cadherins and cell-type markers in 29,933 cells, and the projections of 3,164 cells in both the mouse motor cortex and auditory cortex. Associating gene expression and projections in 1,349 neurons revealed shared cadherin signatures of homologous projections across the two cortical areas. These cadherins were enriched across multiple branches of the transcriptomic taxonomy. By correlating multi-gene expression and projections to many targets in single neurons with high throughput, BARseq2 provides a path to uncovering the molecular logic underlying neuronal circuits.
Distinct Cellular Strategies Determine Sensitivity to Mild Drought of Arabidopsis Natural Accessions

The world-wide distribution of Arabidopsis thaliana (Arabidopsis) accessions imposes different types of evolutionary pressures, which contributes to various responses of these accessions to environmental stresses. Drought stress responses have been well studied, particularly in Columbia, a common Arabidopsis accession. However, the reactions to drought stress are complex and our understanding of which of these responses contribute to the plant’s tolerance to mild drought is very limited. Here, we studied the mechanisms by which natural accessions react to mild drought at a physiological and molecular level during early leaf development. We documented variations in mild drought tolerance among natural accessions and used transcriptome sequencing of a drought-sensitive accession, ICE163, and a drought-tolerant accession, Yeg-1, to get insights into the mechanisms underlying this tolerance. This revealed that ICE163 preferentially induces jasmonates and anthocyanin-related pathways, which are beneficial in biotic stress defense, while Yeg-1 has a more pronounced activation of abscisic acid signaling, the classical abiotic stress response. Related physiological traits, including content of proline, anthocyanins and ROS, stomatal closure and cellular leaf parameters, were investigated and linked to the transcriptional responses. We conclude that most of these processes constitute general drought response mechanisms that are regulated similarly in drought-tolerant and -sensitive accessions. However, the capacity to close stomata and maintain cell expansion under mild drought appeared to be major factors that contribute to a better leaf growth under mild drought. One-sentence summary This paper demonstrates that an efficient closure of stomata and maintenance of cell expansion during drought conditions are crucial to maximally preserve plant growth during water deficit.