Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of emerging SARS-CoV-2 on total and cause-specific maternal mortality: A natural experiment in Chile during the peak of the outbreak SARS-CoV-2 Impact on Maternal Mortality: Chiles Outbreak Study

Background This study estimated the effects of the SARS-CoV-2 pandemic on maternal death causes in Chile during the outbreak peak between 2020 and 2021. Materials and Methods A natural experiment was conducted using official data on maternal deaths and live births (LBs) between 1997 and 2021. Trend changes in the maternal mortality ratio (MMR) were assessed using segmented regression. The effects of the SARS-CoV-2 outbreak were evaluated using interrupted time series (ITS) and an autoregressive integrated moving average (ARIMA) model to forecast the expected rates on MMR and 95% confidence intervals (95% CI). Findings ITS analysis revealed that the SARS-CoV-2 outbreak impacted the MMR due to indirect causes, with a greater increase in indirect nonrespiratory causes than respiratory causes. The ARIMA forecast was consistent with ITS, showing that the expected MMR for indirect causes was substantially lower than the observed rates (9.65 in 2020 and 7.46/100,000 LBs in 2021). The expected MMR was 3.44 in 2020 and 1.55 in 2021. For nonrespiratory causes, the observed values of the MMR for 2020 (8.77/100.000 LBs) and 2021 (7.46/100.000 LBs) doubled the prediction 4.02 (95% CI: 0.44-7.61) and 3.83 (95% CI: -0.12-7.79). No significant effect was found on direct obstetrical deaths. Interpretation During 2020-2021, there was a rise in the MMR in Chile attributable to SARS-CoV-2. The pandemic contributed to an escalation in the MMR due to indirect causes, particularly nonrespiratory and infectious causes, suggesting that the risk of pregnant women to SARS-CoV-2 was increased from previous comorbidities.
Peripheral innate immunophenotype in neurodegenerative disease: blood-based profiles and links to survival

The innate immune system plays an integral role in the progression of many neurodegenerative diseases. In addition to central innate immune cells (e.g. cerebral microglia), peripheral innate immune cells (e.g. blood monocytes, natural killer cells, and dendritic cells) may also differ in these conditions. However, the characterization of peripheral innate immune cell types across different neurodegenerative diseases remains incomplete. This study aimed to characterize peripheral innate immune profiles using flow cytometry for immunophenotyping of peripheral blood mononuclear cells, in n=148 people with Alzheimer's disease (AD), Frontotemporal Dementia (FTD), Corticobasal syndrome (CBS), Progressive Supranuclear Palsy (PSP), Lewy Body Disease (LBD) as compared to n=37 healthy controls. To compare groups, we used Principal Component Analysis and multivariate Dissimilarity analysis across 19 innate immune cell types. We identified pro-inflammatory profiles that significantly differ between patients with all-cause dementia and healthy controls, with some significant differences between groups. Regression analysis confirmed that time to death following the blood test correlated with the individuals immune profile weighting, positively to TREM2+ and nonclassical monocytes and negatively to classical monocytes. Taken together, these results describe transdiagnostic peripheral immune profiles and highlight the link between prognosis and the monocyte cellular subdivision and function (as measured by surface protein expression). The results suggest that blood-derived innate immune profiles can inform sub-populations of cells relevant for specific neurodegenerative diseases that are significantly linked to accelerated disease progression and worse survival outcomes across diagnoses. Blood-based innate immune profiles may contribute to enhanced precision medicine approaches dementia, helping to identify and monitor therapeutic targets and stratify patients for candidate immunotherapies.
Heritable intraspecific variation among prey in size and movement interact to shape predation risk and potential natural selection

Species’ traits affect consumer-resource interactions with consequences for population dynamics, food webs, and energy flows through ecosystems. Yet, our expectations for how the strengths of consumer-resource interactions scale with species’ traits largely come from interspecific comparisons. It remains unclear whether these interspecific associations hold for intraspecific trait variation among individuals that is subject to natural selection. Few studies have evaluated the heritability of prey traits related to predation risk and their potential genetic correlations to evaluate how selection might operate on intraspecific variation underlying predator-prey interactions. We used outcrossed and then clonally propagated lines of the ciliate Paramecium caudatum to examine variation in morphology and movement behavior, the extent to which this variation was heritable, and how intraspecific differences among lines altered Paramecium susceptibility to predation by the copepod Macrocyclops albidus. We found that the Paramecium lines exhibited heritable variation in body size and movement traits. In contrast to interspecific allometric relationships, body size and movement speed did not covary among clonal lines. The proportion of Paramecium consumed by copepods was positively associated with Paramecium body size and velocity as one might expect from interspecific relationships. However, we also found evidence of an interaction such that greater velocities led to greater predation risk for large body-sized paramecia but did not alter predation risk for smaller body-sized paramecia. The proportion of paramecia consumed was not related to copepod body size. These patterns of predation risk and heritable trait variation in paramecia suggest that copepod predation may act as a selective force that could operate independently on movement speed and body size with the strongest selection against large, high-velocity paramecia. Overall, our results indicate that conclusions drawn from relationships among species in traits and the strengths of consumer-resource interactions need not hold within species. Furthermore, patterns of genetic variation and covariation in traits coupled with their relationships to predation risk can lead to patterns of potential natural selection that would be hard to infer from interspecific patterns alone.
A user-friendly input–output (IO) curve analysis tool for variable brain stimulation responses, particularly evoked potentials in transcranial magnetic stimulation (TMS)

Background Motor-evoked potentials (MEPs) are among the few readily observable direct responses to suprathreshold stimuli administered to the brain. They serve for a variety of applications, often in the form of dose–response curves, also called recruitment or input–output (IO) curves. However, MEPs and thus IO curves demonstrate extreme trial-to-trial variability that can exceed more than two decimal orders of magnitude. Recent studies have identified issues in previous statistical analysis of IO curves and introduced better methods, others could quantitatively separate several widely independent variability sources. However, research has failed providing the field with a user-friendly implementation of the methods for analysing such IO curves statistically sound and separating variability so that they were limited to a few research groups. Objective This work intends to provide the latest methods for analysing IO curves and extract variability information in an open-source package so that the community can easily use and adapt them to their own needs. Methods We implemented recent IO curve methods with a graphical user interface and provided the code as well as compiled versions for Mac, Linux, and Windows. Results The application imports typical IO data of individual stimulus–response sets, guides users step by step through the analysis, and allows exporting of the results including figures for post-hoc analysis and documentation. Conclusion This graphical application offers a user-friendly environment for analysing the variability of evoked potentials and its various contributions, catering to the needs of clinical and experimental neuroscientists.
Thermal Tolerance Plasticity and Dynamics of Thermal Tolerance in Eublepharis macularius: Implications for Future Climate-Driven Heat Stress

The intensity and duration of heat waves, as well as average global temperatures, are expected to increase due to climate change. Heat waves can cause physiological stress and reduce fitness in animals. Species can reduce overheating risk through phenotypic plasticity, which allows them to raise their thermal tolerance limits over time. This mechanism could be important for ectotherms whose body temperatures are directly influenced by available environmental temperatures. Geckos are a large, diverse group of ectotherms that vary in their thermal habitats and times of daily activity, which could affect how they physiologically adjust to heat waves. Data on thermal physiology are scarce for reptiles, with only one study in geckos. Understanding thermal tolerance and plasticity, and their relationship, is essential for understanding how some species are able to adjust or adapt to changing temperatures. In this study, we estimated thermal tolerance and plasticity, and their interaction, in the crepuscular gecko, Eublepharis macularius, a species that is emerging as a model for reptile biology. After estimating basal thermal tolerance for 28 geckos, thermal tolerance was measured for each individual a second time at several timepoints (3, 6, or 24 h) to determine thermal tolerance plasticity. We found that thermal tolerance plasticity (1) does not depend on the basal thermal tolerance of the organism, (2) was highest after 6 hours from initial heat shock, and (3) was negatively influenced by individual body mass. Our findings contribute to the increasing body of work focused on understanding the influence of biological and environmental factors on thermal tolerance plasticity in organisms and provide phenotypic data to further investigate the molecular basis of thermal tolerance plasticity in organisms.
Computational investigation of BMAA and its carbamate adducts as potential GluR2 modulators

Beta-N-methylamino-L-alanine (BMAA) is a potential neurotoxic non-protein amino acid, which can reach the human body through the food chain. When BMAA interacts with bicarbonate in the human body, carbamate adducts are produced, which share high structural similarity with the neurotransmitter glutamate. It is believed that the L-carbamate adducts of BMAA bind in the glutamate binding site of glutamate receptor 2 type AMPA iGluR (GluR2) causing neurodegenerative effects of diseases such as Alzheimer’s and Parkinson’s diseases. However, the mechanism of BMAA action and its carbamate adducts bound to GluR2 has not been yet elucidated. Here, we investigate the binding modes and the affinity of BMAA, and its carbamate adducts to GluR2 in comparison to the natural agonist, glutamate, to understand whether these can act as GluR2 modulators. Initially, we perform Molecular Dynamics (MD) simulations of BMAA and its carbamate adducts bound to GluR2 to examine the stability of the ligands in the S1/S2 ligand-binding domain of the receptor. In addition, we perform alchemical free energy calculations to compute the difference in the free energy of binding of the beta-carbamate adduct of BMAA to GluR2 compared to glutamate. Our findings indicate that carbamate adducts of BMAA, and glutamate remain stable in the binding site of the GluR2 compared to BMAA. Additionally, alchemical free energy results reveal that glutamate and the beta-carbamate adduct of BMAA have comparable binding affinity in the GluR2. These results provide a rationale that BMAA carbamate adducts may be in fact the modulators of GluR2 and not BMAA itself.
Functional diversity in the Hsp60 of Sulfolobus acidocaldarius: mosaic of Group I and Group II chaperonin

External stress can disrupt protein homeostasis in organisms, necessitating the involvement of heat shock proteins (Hsps) to restore equilibrium and ensure survival. Unlike other organisms, the thermoacidophilic crenarchaeon Sulfolobus acidocaldarius lacks Hsp100, Hsp90, and Hsp70, possessing only two small heat shock proteins (Hsp14 and Hsp20) and one group II chaperonin, Hsp60. This raises questions about how protein substrates are protected and transferred to Hsp60 for refolding without other chaperones. Our study focused on ATP-dependent Hsp60 in S. acidocaldarius, revealing its formation of oligomeric structures in the presence of ATP. While ATP hydrolysis is not essential for oligomer formation and lid closure, it is crucial for Hsp60’s chaperone activity, effectively folding stress-denatured substrate proteins by stabilizing their folded conformations. The mechanism involves hydrophobic recognition of unfolded substrates, encapsulating and releasing them in a more folded state. Negatively charged inner surface of the ring seems to be responsible for driving the folding of the substrate. Importantly, Hsp14 was found to transfer substrate proteins to Hsp60αβ, orchestrating their refolding into an active state. Beyond protein folding, Hsp60β protects the membrane under stress, contributing to maintaining membrane rigidity. Hsp60 exhibits nested cooperativity in ATPase activity, adapting to ATP concentration changes and interestingly Hsp60β and Hsp60αβ complex shows a mosaic behaviour during ATP hydrolysis belonging to both group I and group II chaperonin respectively. In conclusion, our study provides insights into the intricate mechanisms employed by Hsp60 in S. acidocaldarius to maintain protein homeostasis. It offers a comprehensive understanding of Hsp60’s role in the heat shock response pathway, shedding light on fundamental cellular processes in extremophilic archaea.
Repetitive Learning Control for Body Caudal Undulation with Soft Sensory Feedback

Soft bio-inspired robotics is a growing field of research that seeks to close the gap with animal robustness and adaptability where conventional robots fall short. The embedding of sensors with the capability to discriminate between different body deformation modes is a key technological challenge in soft robotics to enhance robot control – a difficult task for such kinds of systems with high degrees of freedom. The recently conceived Linear Repetitive Learning Estimation Scheme (LRLES) – to be included in the traditional Proportional Integral Derivative (PID) control – is proposed here as a way to compensate for uncertain dynamics on a soft swimming robot, which is actuated with soft pneumatic actuators and equipped with soft sensors providing proprioceptive information pertaining to lateral body caudal bending akin to a goniometer. The proposed controller is derived in detail and experimentally validated, with the experiment consisting of tracking a desired trajectory for bending angle while continuously oscillating with a constant frequency. The results are compared vis a vis those achieved with the traditional PID controller, finding that the PID endowed with the LRLES outperforms the PID controller (though the latter has been separately tuned) and experimentally validating the novel controller’s effectiveness, accuracy, and matching speed.
Individual Differences in Belief Updating and Phasic Arousal Are Related to Psychosis Proneness

Many decisions entail the updating of beliefs about the state of the environment, a process that may go awry in psychosis. When environments are subject to hidden changes in their state, optimal belief updating requires non-linear modulation of sensory evidence, which may be subserved by pupil-linked, phasic arousal. Here, we analyzed behavior and pupil responses during evidence accumulation in a changing environment in a community sample of human participants and assessed their subclinical psychotic experiences (psychosis proneness). Subjects most prone to psychosis showed overall less flexible belief updating profiles, with diminished weighting of late evidence. These same subjects also exhibited overall smaller pupil responses and less reliable pupil encoding of computational variables governing the adaptive belief updating. The observed changes in belief updating and arousal dynamics may account for the emergence of cognitive biases in psychotic psychopathology. Our results open a new window on the pathophysiology of mental disorders.
An oomycete effector co-opts a host RabGAP protein to remodel pathogen interface and subvert defense-related secretion

Pathogens have evolved sophisticated mechanisms to manipulate host cell membrane dynamics, a crucial adaptation to survive in hostile environments shaped by innate immune responses. Plant- derived membrane interfaces, engulfing invasive hyphal projections of fungal and oomycete pathogens, are prominent junctures dictating infection outcomes. Understanding how pathogens transform these host-pathogen interfaces to their advantage remains a key biological question. Here, we identified a conserved effector, secreted by plant pathogenic oomycetes, that co-opts a host Rab GTPase-activating protein (RabGAP), TBC1D15L, to remodel the host-pathogen interface. The effector, PiE354, hijacks TBC1D15L as a susceptibility factor to usurp its GAP activity on Rab8a—a key Rab GTPase crucial for defense-related secretion. By hijacking TBC1D15L, PiE354 purges Rab8a from the plasma membrane, diverting Rab8a-mediated immune trafficking away from the pathogen interface. This mechanism signifies an uncanny evolutionary adaptation of a pathogen effector in co- opting a host regulatory component to subvert defense-related secretion, thereby providing unprecedented mechanistic insights into the reprogramming of host membrane dynamics by pathogens.
Transformation of human chondrocytes with copper-containing metal-organic biohybrids (MOBs)

Copper is involved in the biosynthesis of collagen, however soluble copper salts dissipate quickly and copper nanoparticles are cytotoxic. Here we added a novel copper-containing nanomaterial (CuHARS) to assess human chondrocyte function in the presence of copper. Human dermal fibroblasts (HDFs) were also treated as a control. Chondrocyte response to CuHARS was assessed by chronic nanomaterial treatment (30 µg/ml) followed by digital microscopy and image analysis of cellular features compared to normal chondrocytes. Unexpectedly, chronic CuHARS treatment of human chondrocytes transformed cells over time to cells with extremely elongated and variegated processes and lower proliferation rates compared to normal chondrocytes. In these transformed cells, which we named 3G, shedding of fine processes was observed over time and collected supernatants demonstrated elevated collagen levels compared to normal cell culture media. In contrast to chondrocytes, HDFs treated with CuHARS showed attenuated changes in morphology, and notably retained a prominent ability for continued proliferation. These results demonstrate that a copper-containing biohybrid material (CuHARS) can stably transform human chondrocytes with highly altered morphology, lower proliferation rates, and altered membrane dynamics compared to normal chondrocytes. In contrast, human dermal fibroblasts demonstrated attenuated changes in morphology, and retained an enhanced ability for proliferation.
Connectivity and functional diversity of different temporo-occipital nodes for action perception

The temporo-occipital cortex (TOC) plays a key role in body and action perception, but current understanding of its functions is still limited. TOC body regions are heterogeneous and their role in action perception is poorly understood. This study adopted data-driven approaches to region selectivity and investigated the connectivity of TOC nodes and the functional network sensitivity for different whole body action videos. In two human 7T fMRI experiments using independent component analysis, four adjacent body selective nodes were detected within the TOC network with distinct connectivity profiles and functional roles. Action type independent connectivity was observed for the posterior-ventral node to the visual cortex, the posterior-dorsal node to the precuneus and the anterior nodes to the frontal cortex. Action specific connectivity modulations were found in middle frontal gyrus for the aggressive condition with increased connectivity to the anterior node and decreased connectivity to the posterior-dorsal node. But for the defensive condition, node-nonspecific enhancement was found for the TOC-cingulate connectivity. By addressing the issue of multiple nodes in the temporo-occipital network we show a functional dissociation of different body selective centres related to the action type and a potential hierarchy within the TOC body network.
Through the lens of causal inference: Decisions and pitfalls of covariate selection

The critical importance of justifying the inclusion of covariates is a facet often overlooked in data analysis. While the incorporation of covariates typically follows informal guidelines, we argue for a comprehensive exploration of underlying principles to avoid significant statistical and interpretational challenges. Our focus is on addressing three common yet problematic practices: the indiscriminate lumping of covariates, the lack of rationale for covariate inclusion, and the oversight of potential issues in result reporting. These challenges, prevalent in neuroimaging models involving covariates such as reaction time, demographics, and morphometric measures, can introduce biases, including overestimation, underestimation, masking, sign flipping, or spurious effects. Our exploration of causal inference principles underscores the pivotal role of domain knowledge in guiding covariate selection, challenging the common reliance on statistical measures. This understanding carries implications for experimental design, model-building, and result interpretation. We draw connections between these insights and reproducibility concerns, specifically addressing the selection bias resulting from the widespread practice of strict thresholding, akin to the logical pitfall associated with “double dipping. ” Recommendations for robust data analysis involving covariates encompass explicit research question statements, justified covariate inclusions/exclusions, centering quantitative variables for interpretability, appropriate reporting of effect estimates, and advocating a “highlight, don’t hide” approach in result reporting. These suggestions are intended to enhance the robustness, transparency, and reproducibility of covariate-driven analyses, encompassing investigations involving consortium datasets such as ABCD and UK Biobank. We discuss how researchers can use a transparent depiction of the covariate relationships to enhance the ethos of open science and promote research reproducibility.