Miracle-dz/UniFAR-FTUs huggingface dataset:
Ab initio ro-vibrational Hamiltonian in irreducible tensor formalism: a method for computing energy levels from potential energy surfaces for symmetric-top molecules

A theoretical approach to study ro-vibrational molecular states from a full nuclear Hamiltonian expressed in terms of normal-mode irreducible tensor operators is presented for the first time. Each term of the Hamiltonian expansion can thus be cast in the tensor form in a systematic way using the formalism of ladder operators. Pyramidal XY3 molecules appear to be good candidates to validate this approach which allows taking advantage of the symmetry properties when doubly degenerate vibrational modes are considered. Examples of applications will be given for PH3 where variational calculations have been carried out from our recent potential energy surface [Nikitin et al., J. Chem. Phys. 130, 244312 (2009)].
Emerging Therapeutic Strategies to Restore Regulatory T Cell Control of Islet Autoimmunity in Type 1 Diabetes

Despite many decades of investigation uncovering the autoimmune mechanisms underlying Type 1 Diabetes (T1D), translating these findings into effective therapeutics has proven extremely challenging. T1D is caused by autoreactive T cells that become inappropriately activated and kill the β cells in the pancreas, resulting in insulin insufficiency and hyperglycemia. A large body of evidence supports the idea that the unchecked activation and expansion of autoreactive T cells in T1D is due to defects in immunosuppressive regulatory T cells (Tregs) that are critical for maintaining peripheral tolerance to islet autoantigens. Hence, repairing these Treg deficiencies is a much sought-after strategy to treat the disease. To accomplish this goal in the most precise, effective and safest way possible, restored Treg functions will need to be targeted towards suppressing the autoantigen-specific immune responses only and/or be localized in the pancreas. Here we review the most recent developments in designing Treg therapies that go beyond broad activation or expansion of non-specific polyclonal Treg populations. We focus on two cutting-edge strategies namely ex vivo generation of optimized Tregs for re-introduction in T1D patients vs direct in situ stimulation and restoration of endogenous Treg function.
Different Expressions of Pericardial Fluid MicroRNAs in Patients With Arrhythmogenic Right Ventricular Cardiomyopathy and Ischemic Heart Disease Undergoing Ventricular Tachycardia Ablation

Introduction: Pericardial fluid is enriched with biologically active molecules of cardiovascular origin including microRNAs. Investigation of the disease-specific extracellular microRNAs could shed light on the molecular processes underlying disease development. Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart disease characterized by life-threatening arrhythmias and progressive heart failure development. The current data about the association between microRNAs and ARVC development are limited. Methods and Results: We performed small RNA sequence analysis of microRNAs of pericardial fluid samples obtained during transcutaneous epicardial access for ventricular tachycardia (VT) ablation of six patients with definite ARVC and three post-infarction VT patients. Disease-associated microRNAs of pericardial fluid were identified. Five microRNAs (hsa-miR-1-3p, hsa-miR-21-5p, hsa-miR-122-5p, hsa-miR-206, and hsa-miR-3679-5p) were found to be differentially expressed between patients with ARVC and patients with post-infarction VT. Enrichment analysis of differentially expressed microRNAs revealed their close linkage to cardiac diseases. Conclusion: Our data extend the knowledge of pericardial fluid microRNA composition and highlight five pericardial fluid microRNAs potentially linked to ARVC pathogenesis. Further studies are required to confirm the use of pericardial fluid RNA sequencing in differential diagnosis of ARVC.
Home Learning Environments of Children in Mexico in Relation to Socioeconomic Status

We explored the home learning environments of 173 Mexican preschool children (aged 3–6 years) in relation to their numeracy performance. Parents indicated the frequency of their formal home numeracy and literacy activities, and their academic expectations for children’s numeracy and literacy performance. Children completed measures of early numeracy skills. Mexican parent–child dyads from families with either high- or low-socioeconomic status (SES) participated. Low-SES parents (n = 99) reported higher numeracy expectations than high-SES parents (n = 74), but similar frequency of home numeracy activities. In contrast, high-SES parents reported higher frequency of literacy activities. Path analyses showed that operational (i.e., advanced) numeracy activities were positively related to children’s numeracy skills in the high- but not in the low-SES group. These findings improve the understanding of the role of the home environment in different contexts and provide some insights into the sources of the variable patterns of relations between home learning activities and children’s numeracy outcomes. They also suggest that SES is a critical factor to consider in research on children’s home numeracy experiences.
Energy Diversification and Economic Development in Emergent Countries: Evidence From Fourier Function-Driven Bootstrap Panel Causality Test

Energy is a crucial development indicator of production, consumption, and nation-building. However, energy diversification highlighting renewables remains salient in economic development across developing economies. This study explores the economic impact of renewables (RE) and fossil fuel (NRE) utilization in 17 emerging nations. We use annual data with timeframe between 1980 and 2016 and propose a bootstrap panel causality approach with a Fourier function. This allows the examination of multiple structural breaks, cross-section dependence, and heterogeneity across countries. We validate four main hypotheses on the causal links attached to the energy consumption (EC)-growth nexus namely neutrality, conservation, growth, and feedback hypotheses. The findings reveal a causal relationship running from RE to GDP for Brazil, Egypt, Indonesia, Korea, Pakistan, and the Philippines, confirming the growth hypothesis. Besides, the results validate the conservation hypothesis with causality from GDP to RE for China, Colombia, Egypt, Greece, India, Korea, South Africa, and Turkey. We identify causality from NRE to GDP for Pakistan, Mexico, Malaysia, Korea, India, Greece, Egypt, and Brazil; and from GDP to NRE for Thailand, Peru, Malaysia, India, Greece, Egypt, and Colombia. We demonstrate that wealth creation can be achieved through energy diversification rather than relying solely on conventional energy sources.
Immune Cell Infiltration-Based Characterization of Triple-Negative Breast Cancer Predicts Prognosis and Chemotherapy Response Markers

Breast cancer represents the number one cause of cancer-associated mortality globally. The most aggressive molecular subtype is triple negative breast cancer (TNBC), of which limited therapeutic options are available. It is well known that breast cancer prognosis and tumor sensitivity toward immunotherapy are dictated by the tumor microenvironment. Breast cancer gene expression profiles were extracted from the METABRIC dataset and two TNBC clusters displaying unique immune features were identified. Activated immune cells formed a large proportion of cells in the high infiltration cluster, which correlated to a good prognosis. Differentially expressed genes (DEGs) extracted between two heterogeneous subtypes were used to further explore the underlying immune mechanism and to identify prognostic biomarkers. Functional enrichment analysis revealed that the DEGs were predominately related to some processes involved in activation and regulation of innate immune signaling. Using network analysis, we identified two modules in which genes were selected for further prognostic investigation. Validation by independent datasets revealed that CXCL9 and CXCL13 were good prognostic biomarkers for TNBC. We also performed comparisons between the above two genes and immune markers (CYT, APM, TILs, and TIS), as well as cell checkpoint marker expressions, and found a statistically significant correlation between them in both METABRIC and TCGA datasets. The potential of CXCL9 and CXCL13 to predict chemotherapy sensitivity was also evaluated. We found that the CXCL9 and CXCL13 were good predictors for chemotherapy and their expressions were higher in chemotherapy-responsive patients in contrast to those who were not responsive. In brief, immune infiltrate characterization on TNBC revealed heterogeneous subtypes with unique immune features allowed for the identification of informative and reliable characteristics representative of the local immune tumor microenvironment and were potential candidates to guide the management of TNBC patients.
Environmental Temperatures Affect the Gastrointestinal Microbes of the Chinese Giant Salamander

An increasing number of studies have shown that warming also influences the animal gut microbiome (altering the community structure and decreasing its diversity), which might further impact host fitness. Here, based on an analysis of the stomach and gut (the entire intestine: from the anterior intestine to the cloaca) microbiome in laboratory larva of giant salamanders (Andrias davidianus) under different living water temperatures (5, 15, and 25°C) at two sample time points (80 and 330 days after the acclimation), we investigated the potential effect of temperature on the gastrointestinal microbiome community. We found the significant Interaction between sampling time and temperature, or type (stomach and gut) on Shannon index in the gastrointestinal microbiome of the giant salamanders. We also found the significant difference in Shannon index among temperature groups within the same sample type (stomach or gut) at each sample time. 10% of variation in microbiome community could be explained by temperature alone in the total samples. Both the stomach and gut microbiomes displayed the highest similarity in the microbiome community (significantly lowest pairwise unweighted Unifrac distance) in the 25-degree group between the two sampling times compared to those in the 5-degree and 15-degree groups. Moreover, the salamanders in the 25°C treatment showed the highest food intake and body mess compared to that of other temperature treatments. A significant increase in the abundance of Firmicutes in the gastrointestinal microbiome on day 330 with increasing temperatures might be caused by increased host metabolism and food consumption. Therefore, we speculate that the high environmental temperature might indirectly affect both alpha and beta diversity of the gastrointestinal microbiome.
The Efficacy and Potential Mechanisms of Metformin in the Treatment of COVID-19 in the Diabetics: A Systematic Review

Introduction Diabetes mellitus (DM) is one of the most common comorbidities among patients with coronavirus disease 2019 (COVID-19) which may exacerbate complications of this new viral infection. Metformin is an anti-hyperglycemic agent with host-directed immune-modulatory effects, which relieve exaggerated inflammation and reduce lung tissue damage. The current systematic review aimed to summarize the available evidence on the potential mechanism of action and the efficacy of metformin in COVID-19 patients with DM. Methods A systematic search was carried out in PubMed/Medline, EMBASE, the Cochrane Controlled Register of Trials (CENTRAL), and Web of Science up to July 30, 2020. The following keywords were used: “COVID-19”, “SARS-CoV-2”, “2019-nCoV”, “metformin”, and “antidiabetic drug”. Results Fourteen studies were included in our systematic review. Three of them were observational with 6,659 participants. Decreasing insulin resistance, reduction of some inflammatory cytokines like IL-6 and TNF-α, modulation of angiotensin-converting enzyme 2 (ACE2) receptor, and improving neutrophil to lymphocyte ratio are some of the potential mechanisms of metformin in COVID-19 patients with DM. Nine out of fourteen articles revealed the positive effect of metformin on the prognosis of COVID-19 in diabetic or even non-diabetic patients. Moreover, different studies have shown that metformin is more effective in women than men. Conclusions The use of metformin may lead to improve the clinical outcomes of patients with mild to moderate SARS-CoV-2, especially in diabetic women. Further observational studies should be conducted to clarify the effects of metformin as a part of the treatment strategy of COVID-19.
Insight Into Seeded Tau Fibril Growth From Molecular Dynamics Simulation of the Alzheimer’s Disease Protofibril Core

Aggregates of the microtubule associated tau protein are a major constituent of neurofibrillary lesions that define Alzheimer’s disease (AD) pathology. Increasing experimental evidence suggests that the spread of tau neurofibrillary tangles results from a prion-like seeding mechanism in which small oligomeric tau fibrils template the conversion of native, intrinsically disordered, tau proteins into their pathological form. By using atomistic molecular dynamics (MD) simulations, we investigate the stability and dissociation thermodynamics of high-resolution cryo-electron microscopy (cryo-EM) structures of both the AD paired-helical filament (PHF) and straight filament (SF). Non-equilibrium steered MD (SMD) center-of-mass pulling simulations are used to probe the stability of the protofibril structure and identify intermolecular contacts that must be broken before a single tau peptide can dissociate from the protofibril end. Using a combination of exploratory metadynamics and umbrella sampling, we investigate the complete dissociation pathway and compute a free energy profile for the dissociation of a single tau peptide from the fibril end. Different features of the free energy surface between the PHF and SF protofibril result from a different mechanism of tau unfolding. Comparison of wild-type tau PHF and post-translationally modified pSer356 tau shows that phosphorylation at this site changes the dissociation free energy surface of the terminal peptide. These results demonstrate how different protofibril morphologies template the folding of endogenous tau in distinct ways, and how post-translational modification can perturb the folding mechanism.
Quantitative Proteomic Analysis in Alveolar Type II Cells Reveals the Different Capacities of RAS and TGF-β to Induce Epithelial–Mesenchymal Transition

Alveolar type II (ATII) epithelial cells function as stem cells, contributing to alveolar renewal, repair and cancer. Therefore, they are a highly relevant model for studying a number of lung diseases, including acute injury, fibrosis and cancer, in which signals transduced by RAS and transforming growth factor (TGF)-β play critical roles. To identify downstream molecular events following RAS and/or TGF-β activation, we performed proteomic analysis using a quantitative label-free approach (LC-HDMSE) to provide in-depth proteome coverage and estimates of protein concentration in absolute amounts. Data are available via ProteomeXchange with identifier PXD023720. We chose ATIIER:KRASV12 as an experimental cell line in which RAS is activated by adding 4-hydroxytamoxifen (4-OHT). Proteomic analysis of ATII cells treated with 4-OHT or TGF-β demonstrated that RAS activation induces an epithelial–mesenchymal transition (EMT) signature. In contrast, under the same conditions, activation of TGF-β signaling alone only induces a partial EMT. EMT is a dynamic and reversible biological process by which epithelial cells lose their cell polarity and down-regulate cadherin-mediated cell–cell adhesion to gain migratory properties, and is involved in embryonic development, wound healing, fibrosis and cancer metastasis. Thus, these results could help to focus research on the identification of processes that are potentially driving EMT-related human disease.
Development and Validation of the Readiness for End-of-Life Conversations (REOLC) Scale

Background: Engaging in end-of-life care considerations is beneficial when the time is right. The purpose of this study is to provide a valid instrument to assess peoples readiness for end-of-life conversations before they are initiated. Materials and Methods: A community sample was recruited in study one for exploratory factor analysis of a 13-item questionnaire. In study two, psychometric properties were analyzed with structural equation modeling in a population affected by cancer. Convergent and discriminant validity were assessed with questionnaires measuring distress, depression, anxiety, fear of progression, and distress of death and dying. Results: In study one (N = 349) exploratory factor analysis resulted in three subscales readiness (α = 0.84), communication (α = 0.76), and values (α = 0.56) with a possible common factor (α = 0.84) for a community sample. In study two (N = 84) the three-factor solution with 13 items was not supported for cancer patients. Factor structure was adapted to 12 items with one common factor readiness (α = 0.87). Model fit was good: χ2(50) = 59.18, p>0.05 (Satorra-Bentler-correction = 1.27), with χ2/df = 1.184, rRMSEA = 0.053 (90%-CI[0.000;0.100]), and rSRMR = 0.072. Convergent validity was supported by moderate correlations to trait gratitude, ratings of readiness to provide a living will or talk with family about the end of life. Divergent validity was supported by no or small correlation with distress, depression, general and death anxiety and fear of progression, respectively. Conclusions: Results support usage of the REOLC Scale in different settings with adapted factor structure. The questionnaire is interpreted as valid and reliable instrument to assess objective readiness for end-of-life conversations.
DNA Methylation Regulates Transcription Factor-Specific Neurodevelopmental but Not Sexually Dimorphic Gene Expression Dynamics in Zebra Finch Telencephalon

Song learning in zebra finches (Taeniopygia guttata) is a prototypical example of a complex learned behavior, yet knowledge of the underlying molecular processes is limited. Therefore, we characterized transcriptomic (RNA-sequencing) and epigenomic (RRBS, reduced representation bisulfite sequencing; immunofluorescence) dynamics in matched zebra finch telencephalon samples of both sexes from 1 day post hatching (1 dph) to adulthood, spanning the critical period for song learning (20 and 65 dph). We identified extensive transcriptional neurodevelopmental changes during postnatal telencephalon development. DNA methylation was very low, yet increased over time, particularly in song control nuclei. Only a small fraction of the massive differential expression in the developing zebra finch telencephalon could be explained by differential CpG and CpH DNA methylation. However, a strong association between DNA methylation and age-dependent gene expression was found for various transcription factors (i.e., OTX2, AR, and FOS) involved in neurodevelopment. Incomplete dosage compensation, independent of DNA methylation, was found to be largely responsible for sexually dimorphic gene expression, with dosage compensation increasing throughout life. In conclusion, our results indicate that DNA methylation regulates neurodevelopmental gene expression dynamics through steering transcription factor activity, but does not explain sexually dimorphic gene expression patterns in zebra finch telencephalon.
Automatic layered RGB-D scene flow estimation with optical flow field constraint

: Scene flow estimation with RGB-D frames is receiving increasing attention in digital video processing and computer vision due to the widespread use of depth sensors. Existing methods based on object segmentation have shown their effectiveness for object occlusion and large displacement. However, improper segmentation often causes incomplete segmented areas or incorrect edges, which will result in inaccurate occlusion inference and scene flow estimation. To this end, an automatic layered RGB-D scene flow estimation method is proposed, which achieves more accurate layering of objects in depth image by exploring motion information. The authors exploit super-pixel segmentation for initial layering, which is beneficial for preserving edges and integrity of the objects. Furthermore, an optical flow which is highly correlated with the scene is also used for automatic layering. Finally, the utilisation of super-pixel segmentation and motion information would ensure the integrity of the object area and improve the accuracy of scene flow. They have validated their approach both qualitatively and quantitatively on several public datasets. Experimental results show that the proposed method is able to preserve the integrity of the object and achieve lower root mean square error and average angular error as compared with the current state-of-the-art algorithms.
Novel superpixel-based algorithm for segmenting lung images via convolutional neural network and random forest

Accurately segmenting lungs from CT images is a fundamental step for quantitative analysis of lung diseases. However, it is still a challenging task because of some interferential factors, such as juxta-pleural nodules, pulmonary inflammation, as well as individual anatomical varieties. In this study, with the combination of a superpixel approach and a hybrid model composed of convolutional neural network and random forest (CNN-RF), the authors propose a novel algorithm to segment lungs from CT images in an automatic and accurate fashion. The authors' lung segmentation covers three main stages: image preprocessing, lung segmenting and segmentation refining. A lung CT image denoised with a fractional-order grey similarity approach is first segmented to a set of superpixels, and the CNN-RF model is then employed to classify the superpixels and identify lungs from the CT image. The segmentation result is further refined by separating the left and right lungs, eliminating trachea, and correcting lung contours. Experiments show that their algorithm can generate more accurate lung segmentation results with 94.98% Jaccard's index and 97.99% Dice similarity coefficient, compared with ground truths, and it achieved better results compared with several feature-based machine learning techniques and current methods on lung segmentation.
A Multi-Floor Indoor Pedestrian Localization Method Using Landmarks Detection for Different Holding Styles

-e pedestrian dead reckoning (PDR) technique is widely used due to its ease of implementation on portable devices such as smartphones. However, the position error that accumulates over time is the main drawback of this technology. In this paper, we propose a fusion method combining a PDR technique and the landmark recognition methods for multi-floor indoor environments using a smartphone in different holding styles. -e proposed method attempts to calibrate the position of a pedestrian by detecting whether the pedestrian passes by specific locations called landmarks. -ree kinds of landmarks are defined, which are the WiFi, the turning, and the stairs landmarks, and the detection methods for each landmark are proposed. Besides, an adaptive floor detection method using a barometer and a WiFi fingerprinting technique is suggested for tracking a pedestrian in a multifloor building. -e developed system can track the pedestrian holding a smartphone in four styles. -e results of the experiment conducted by three subjects changing the holding style in a three-floor building show the superior performance of the proposed method. It reduces the error rate of positioning results to less than 57.51% compared with the improved PDR alone system.