Miracle-dz/UniFAR-FTUs huggingface dataset:
1,25-dihydroxyvitamin D3 potentiates the innate immune response of peripheral blood mononuclear cells from Japanese Black cattle

1,25-dihydroxyvitamin D3 (1,25(OH)2D3), a bioactive Vitamin D, is known to regulate immune responses in mammals. However, its impact on the innate immune responses of Japanese Black cattle, which are beef cattle endemic to Japan, remains unknown. Thus, in this study, we investigated the effect of 1,25(OH)2D3 on the immune responses of PBMC from Japanese Black cattle. PBMC were cultured with or without 1,25(OH)2D3 for measurement of cell viability, and stimulated with or without 1,25(OH)2D3 and lipopolysaccharide (LPS) for measurement of the gene expressions. As the results, the treatment of 1,25(OH)2D3 increased the cell viability. It also upregulated antibacterial peptides, DEFB10 and LAP with or without LPS stimulation. Moreover, 1,25(OH)2D3 enhanced the inflammatory responses, CXCL8 with LPS stimulation and NOS2 with or without LPS stimulation, while reducing the expression of anti-inflammatory cytokine IL10 with or without LPS stimulation, leading to an inflammatory phenotype. However, in contrast to humans and mice, 1,25(OH)2D3 did not alter the expression of TNF and downregulated TREM1 with LPS treatment. These results suggest that 1,25(OH)2D3 potentiates the innate immune responses of Japanese Black cattle, albeit with different effects and mechanisms as compared to humans and mice.
The Genome-wide Signature of Short-term Temporal Selection

Despite evolutionary biology’s obsession with natural selection, few studies have evaluated multi-generational series of patterns of selection on a genome-wide scale in natural populations. Here, we report on a nine-year population-genomic survey of the microcrustacean Daphnia pulex. The genome-sequences of > 800 isolates provide insights into patterns of selection that cannot be obtained from long-term molecular-evolution studies, including the pervasiveness of near quasi-neutrality across the genome (mean net selection coefficients near zero, but with significant temporal variance about the mean, and little evidence of positive covariance of selection across time intervals), the preponderance of weak negative selection operating on minor alleles, and a genome-wide distribution of numerous small linkage islands of observable selection influencing levels of nucleotide diversity. These results suggest that fluctuating selection is a major determinant of standing levels of variation in natural populations, challenge the conventional paradigm for interpreting patterns of nucleotide diversity and divergence, and motivate the need for the development of new theoretical expressions for the interpretation of population-genomic data. Significance Except for mono/oligogenic traits known in advance to be under strong selection, there is little information on genome-wide patterns of temporal dynamics of allele-frequency changes in well-defined and unmanipulated natural populations. A multi-year survey of a population of the microcrustacean Daphnia pulex provides insight into these matters. Genome-wide analysis of > 800 genetic isolates demonstrates that temporal variation in selection intensity is a major determinant of levels of nucleotide polymorphism and divergence. Most nucleotide sites experience fluctuating selection with mean selection coefficients near zero, with little covariance in the strength of selection across time intervals, and with selection distributed across large numbers of genomic islands of linked sites. These results raise challenges for the conventional interpretation of measures of nucleotide diversity and divergence as indicators of effective population sizes and intensities of positive/negative selection.
Food web complexity modulates environmental impacts on food chain length

Food chain length (FCL), a crucial aspect of biodiversity, has long been debated for its determinants. Previous studies proposed resource availability, disturbance, and ecosystem size as environmental drivers. However, studies using stable isotope approaches have shown inconsistent results, indicating missing links between environmental drivers and FCL. Here, we hypothesized that species richness and motifs (i.e., 3-species subgraphs) modulated environmental effects on FCL. Combining empirical food webs with our N -species food web model, we found that FCL disproportionately changed at low species richness with saturation at high species richness. This functional response was essential to the interdependent effects of disturbance and ecosystem size in our model. Disturbance more strongly regulated FCL in smaller ecosystems, where species richness was low. Similarly, increasing ecosystem size enhanced FCL under strong, but not weak, disturbance regimes. Our study suggests that internal food web structure should deepen our understanding of how FCL changes over environments.
Phages overcome bacterial immunity via diverse anti-defense proteins

It was recently shown that bacteria employ, apart from CRISPR-Cas and restriction systems, a considerable diversity of phage resistance systems, but it is largely unknown how phages cope with this multilayered bacterial immunity. Here, we analyzed groups of closely related Bacillus phages that showed differential sensitivity to bacterial defense systems, and identified multiple families of anti-defense proteins that inhibit the Gabija, Thoeris, and Hachiman systems. We show that these proteins efficiently cancel the defensive activity when co-expressed with the respective defense system or introduced into phage genomes. Homologs of these anti-defense proteins are found in hundreds of phages that infect taxonomically diverse bacterial species. We show that an anti-Gabija protein, denoted Gad1, blocks the ability of the Gabija defense complex to cleave phage-derived DNA. Our data further reveal an anti-Thoeris protein, denoted Tad2, which is a “sponge” that sequesters the immune signaling molecules produced by Thoeris TIR-domain proteins in response to phage. Our results demonstrate that phages encode an arsenal of anti-defense proteins that can disable a variety of bacterial defense mechanisms.
Robust differentiation in a synthetic stem-cell circuit

Differentiation is a process fundamental to multicellularity. In its simplest form, differentiation converts self-renewing stem cells into non-proliferative cells with specified function. This process is inherently susceptible to mutant takeover — mutant stem cells that never differentiate produce excess proliferative daughter cells, driving cancer-like expansion and decreasing the availability of differentiated cells to the organism. It has been proposed that coupling differentiation to an essential trait can select against these mutants by producing a biphasic fitness curve. This would provide mutant stem cells that do not differentiate with a selective disadvantage. However, this theory has yet to be tested experimentally. Here we use “fitness landscape engineering” to design and construct a synthetic biological model of stem cell differentiation in Escherichia coli with biphasic fitness. We find that this circuit is robust to mutations as predicted. Surprisingly, its optimal differentiation rate is robust to a wide range of environmental pressures. This environmental robustness is driven by transit-amplifying cells that differentiate and proliferate irrespective of environment. These results provide new interpretations for natural differentiation mechanisms and suggest strategies for engineering robust, complex multicellular consortia.
Unsupervised segmentation of 3D microvascular photoacoustic images using deep generative learning

Mesoscopic photoacoustic imaging (PAI) enables label-free visualisation of vascular networks in tissue at high contrast and resolution. The segmentation of vascular networks from 3D PAI data and interpretation of their meaning in the context of physiological and pathological processes is a crucial but time consuming and error-prone task. Deep learning holds potential to solve these problems, but current supervised analysis frameworks require human-annotated ground-truth labels. Here, we overcome the need for ground-truth labels by introducing an unsupervised image-to-image translation deep learning model called the vessel segmentation generative adversarial network (VAN-GAN). VAN-GAN integrates synthetic blood vessel networks that closely resemble real-life anatomy into its training process and learns to replicate the underlying physics of the PAI system in order to learn how to segment vasculature from 3D biomedical images. With a variety of in silico, in vitro and in vivo data, including patient-derived breast cancer xenograft models, we show that VAN-GAN facilitates accurate and unbiased segmentation of 3D vascular networks from PAI data volumes. By leveraging synthetic data to reduce the reliance on manual labelling, VAN-GAN lowers the barrier to entry for high-quality blood vessel segmentation to benefit users in the life sciences applying PAI to studies of vascular structure and function.
Digital dashboards visualizing public health data: a systematic review

Introduction Public health is not only threatened by diseases, pandemics, or epidemics. It is also challenged by deficits in the communication of health information. The current COVID-19 pandemic demonstrates that impressively. One way to deliver scientific data such as epidemiological findings and forecasts on disease spread are dashboards. Considering the current relevance of dashboards for public risk and crisis communication, this systematic review examines the state of research on dashboards in the context of public health risks and diseases. Method Nine electronic databases where searched for peer-reviewed journal articles and conference proceedings. Included articles (n = 65) were screened and assessed by three independent reviewers. Through a methodological informed differentiation between descriptive studies and user studies, the review also assessed the quality of included user studies (n = 18) by use of the Mixed Methods Appraisal Tool (MMAT). Results 65 articles were assessed in regards to the public health issues addressed by the respective dashboards, as well as the data sources, functions and information visualizations employed by the different dashboards. Furthermore, the literature review sheds light on public health challenges and objectives and analyzes the extent to which user needs play a role in the development and evaluation of a dashboard. Overall, the literature review shows that studies that do not only describe the construction of a specific dashboard, but also evaluate its content in terms of different risk communication models or constructs (e.g., risk perception or health literacy) are comparatively rare. Furthermore, while some of the studies evaluate usability and corresponding metrics from the perspective of potential users, many of the studies are limited to a purely functionalistic evaluation of the dashboard by the respective development teams. Conclusion The results suggest that applied research on public health intervention tools like dashboards would gain in complexity through a theory-based integration of user-specific risk information needs. Systematic review registration https://www.crd. york.ac. uk/prospero/display_record. php? RecordID=200178, identifier: CRD42020200178.
How does digital infrastructure affect residents' healthcare expenditures? Evidence from Chinese microdata

Healthcare expenditure is only one of the heavy burdens that families face in developing countries. Current research mainly focuses on analyzing the effects of financial policy. There is a lack of studies that examine the understanding and assessment of the impact of digital infrastructure on this issue. In this study, we used the Broadband China policy as a quasi-natural experiment to explore the impact of digital infrastructure on residents' healthcare expenditures in China. Using the differences-in-differences (DID) model and micro-survey data, we found that digital infrastructure has a positive impact on reducing the burden of healthcare expenditure in China. Our findings indicate that residents in cities can save up to 18.8% on healthcare expenses following large-scale digital infrastructure construction. Through mechanism analysis, we found that digital infrastructure reduces residents' healthcare expenditures by improving both commercial insurance availability and the healthcare efficiency of residents. In addition, the effects of digital infrastructure on reducing healthcare expenditure are more pronounced among middle-aged individuals, those with low levels of education, and those with low incomes, which indicates this digital construction wave helps bridge the social gap between the poor and the rich. This study provides compelling evidence of the positive impact of digital society construction on social health and wellbeing.
Two types of redundancy in multimedia learning: a literature review

Regarding the redundancy effect in multimedia learning environments, more consistency is needed in the theoretical assumptions and investigation of this effect. Current research lacks a comprehensive account of different redundant scenarios in which materials facilitate or inhibit learning and provides little conceptual guidance on how learning processes are affected by different types of redundancy. Theoretical assumptions refer to redundancy as a contentual overlap of information provided by the learning material; in this case, processing duplicated information strains the learners’ limited cognitive capacities. Other assumptions refer to the role of processing limitations in working memory channels, including separate processing for visual and verbal information. In this case, an ineffective combination of sources leads to an overload of the limited working memory capacity. This paper reviews empirical research on the redundancy effect (63 studies) and classifies two types of redundancy: (1) content redundancy, and (2) working memory channel redundancy. From an instructional psychology perspective, the analyses reveal four different implementations of redundant scenarios: (1) adding narration to visualizations, (2) adding written text to visualizations, (3) adding written text to narration, and (4) adding written text to narrated visualizations. Regarding the effects of the two redundancy types within these scenarios, analyses indicate positive effects of content redundancy (affected by learners’ prior knowledge), negative effects of working memory channel redundancy (regarding visualizations and written text), and positive effects of working memory channel redundancy (regarding narration and written text). Moreover, results point to factors that might moderate the effect of redundancy and illustrate interactions with existing multimedia effects. Overall, this review provides an overview of the state of empirical research and reveals that the consideration of both redundancy types provides further explanations in this field of research.
Electrically stimulated gene expression under exogenously applied electric fields

Introduction: Electrical stimulation, the application of an electric field to cells and tissues grown in culture to accelerate growth and tight junction formation among endothelial cells, could be impactful in cardiovascular tissue engineering, allotransplantation, and wound healing. Methods: Using Electrical Cell Stimulation And Recording Apparatus (ECSARA), the exploration of the stimulatory influences of electric fields of different magnitude and frequencies on growth and proliferation, trans endothelial electrical resistance (TEER) and gene expression of human endothelia cells (HUVECs) were explored. Results: Within the range of endogenous electrical pulses studied, frequency was found to be more significant (p = 0.05) than voltage in influencing HUVEC gene expression. Localization of Yes Associated Protein (YAP) and expression of CD-144 are shown to be consistent with temporal manifestations of TEER. Discussion: This work introduces the field of electromics, the study of cellular gene expression profiles and their implications under the influence of exogenously applied electric fields. Homology of electrobiology and mechanobiology suggests use of such exogenous cues in tissue and regenerative engineering.
Editorial: Assessment of intraoperative image technologies to optimize clinical outcomes in neurosurgical oncology

COPYRIGHT © 2023 Garcı́a-Garcı́a, Höhne, Martinez-Pérez and Cepeda. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Editorial PUBLISHED 04 May 2023 DOI 10.3389/fonc.2023. 1202240
Left ventricular electrical potential measured by the NOGA XP electromechanical mapping method as a predictor of response to cardiac resynchronization therapy

Objectives The aim of the study was to determine whether left ventricular electrical potential measured by electromechanical mapping with the NOGA XP system has predictive value for response to CRT. Background Approximately 30% of patients who undergo cardiac resynchronization therapy do not see the expected effects. Methods The group of 38 patients qualified for CRT implantation were included in the study, of which 33 patients were analyzed. A 15% reduction in ESV after 6 months of pacing was used as a criterion for a positive response to CRT. The mean value and sum of unipolar and bipolar potentials obtained by mapping with the NOGA XP system and their predictive value in relation to the effect of CRT were analyzed using a bulls-eye projection at three levels: 1) the global value of the left ventricular (LV) potentials, 2) the potentials of the individual LV walls and 3) the mean value of the potentials of the individual segments (basal and middle) of the individual LV walls. Results 24 patients met the criterion of a positive response to CRT vs. 9 non-responders. At the global analysis stage, the independent predictors of favorable response to CRT were the sum of the unipolar potential and bipolar mean potential. In the analysis of individual left ventricular walls, the mean bipolar potential of the anterior and posterior wall and in the unipolar system, mean septal potential was found to be an independent predictor of favorable response to CRT. In the detailed segmental analysis, the independent predictors were the bipolar potential of the mid-posterior wall segment and the basal anterior wall segment. Conclusions Measurement of bipolar and unipolar electrical potentials with the NOGA XP system is a valuable method for predicting a favorable response to CRT.
A rising tide lifts all MBOATs: recent progress in structural and functional understanding of membrane bound O-acyltransferases

Acylation modifications play a central role in biological and physiological processes. Across a range of biomolecules from phospholipids to triglycerides to proteins, introduction of a hydrophobic acyl chain can dramatically alter the biological function and cellular localization of these substrates. Amongst the enzymes catalyzing these modifications, the membrane bound O-acyltransferase (MBOAT) family occupies an intriguing position as the combined substrate selectivities of the various family members span all three classes of these biomolecules. MBOAT-dependent substrates are linked to a wide range of health conditions including metabolic disease, cancer, and neurodegenerative disease. Like many integral membrane proteins, these enzymes have presented challenges to investigation due to their intractability to solubilization and purification. However, over the last several years new solubilization approaches coupled with computational modeling, crystallography, and cryoelectron microscopy have brought an explosion of structural information for multiple MBOAT family members. These studies enable comparison of MBOAT structure and function across members catalyzing modifications of all three substrate classes, revealing both conserved features amongst all MBOATs and distinct architectural features that correlate with different acylation substrates ranging from lipids to proteins. We discuss the methods that led to this renaissance of MBOAT structural investigations, our new understanding of MBOAT structure and implications for catalytic function, and the potential impact of these studies for development of new therapeutics targeting MBOAT-dependent physiological processes.
Co-infection of the respiratory epithelium, scene of complex functional interactions between viral, bacterial, and human neuraminidases

The activity of sialic acids, known to play critical roles in biology and many pathological processes, is finely regulated by a class of enzymes called sialidases, also known as neuraminidases. These are present in mammals and many other biological systems, such as viruses and bacteria. This review focuses on the very particular situation of co-infections of the respiratory epithelium, the scene of complex functional interactions between viral, bacterial, and human neuraminidases. This intrinsically multidisciplinary topic combining structural biology, biochemistry, physiology, and the study of host-pathogen interactions, opens up exciting research perspectives that could lead to a better understanding of the mechanisms underlying virus-bacteria co-infections and their contribution to the aggravation of respiratory pathology, notably in the context of pre-existing pathological contexts. Strategies that mimic or inhibit the activity of the neuraminidases could constitute interesting treatment options for viral and bacterial infections.
Closing the academy–Business gap by building intellectual capital in professional formation

Introduction The rapid advances in technology, market pressures, globalization, and, recently, the COVID-19 pandemic show the need to find educational models that respond to these realities while improving the employability levels of young people and promoting economic growth. This research analyzes how the professional formation model, where two learning spaces, the academy, and the company, are combined, promotes the closing of gaps and economic growth, through the development of intellectual capital that arises from this relationship, in an emerging economy such as Colombia. Methods The methodology used corresponds to a qualitative approach, where the vision of the actors involved in the training process at the undergraduate level in Colombia is analyzed through semi-structured interviews, focus groups, and documentary analysis. Results and discussion The results show five major elements to consider for the formation of the intellectual capital required for the success of the relationship and the reduction in the gaps between academia and business: decision-making mechanisms, inter-organizational coordination, knowledge.