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Exercise offers short-term and long-term health benefits, including an increased metabolic rate and energy expenditure in myocardium. The newly-discovered exercise-induced myokine, irisin, stimulates conversion of white into brown adipocytes as well as increased mitochondrial biogenesis and energy expenditure. Remarkably, irisin is highly expressed in myocardium, but its physiological effects in the heart are unknown. The objective of this work is to investigate irisin's potential multifaceted effects on cardiomyoblasts and myocardium. For this purpose, H9C2 cells were treated with recombinant irisin produced in yeast cells (r-irisin) and in HEK293 cells (hr-irisin) for examining its effects on cell proliferation by MTT [3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assay and on gene transcription profiles by qRT-PCR. R-irisin and hr-irisin both inhibited cell proliferation and activated genes related to cardiomyocyte metabolic function and differentiation, including myocardin, follistatin, smooth muscle actin, and nuclear respiratory factor-1. Signal transduction pathways affected by r-irisin in H9C2 cells and C57BL/6 mice were examined by detecting phosphorylation of PI3K-AKT, p38, ERK or STAT3. We also measured intracellular Ca2+ signaling and mitochondrial thermogenesis and energy expenditure in r-irisin-treated H9C2 cells. The results showed that r-irisin, in a certain concentration rage, could activate PI3K-AKT and intracellular Ca2+ signaling and increase cellular oxygen consumption in H9C2 cells. Our study also suggests the existence of irisin-specific receptor on the membrane of H9C2 cells. In conclusion, irisin in a certain concentration rage increased myocardial cell metabolism, inhibited cell proliferation and promoted cell differentiation. These effects might be mediated through PI3K-AKT and Ca2+ signaling, which are known to activate expression of exercise-related genes such as follistatin and myocardin. This work supports the value of exercise, which promotes irisin release.

Viruses have been a long-term source of infectious diseases that can lead to large-scale infections and massive deaths. Especially with the recent highly contagious coronavirus (COVID-19), antiviral drugs were developed nonstop to deal with the emergence of new viruses and subject to drug resistance. Nitrogen-containing heterocycles have compatible structures and properties with exceptional biological activity for the drug design of antiviral agents. They provided a broad spectrum of interference against viral infection at various stages, from blocking early viral entry to disrupting the viral genome replication process by targeting different enzymes and proteins of viruses. This review focused on the synthesis and application of antiviral agents derived from various nitrogen-containing heterocycles, such as indole, pyrrole, pyrimidine, pyrazole, and quinoline, within the last ten years. The synthesized scaffolds target HIV, HCV/HBV, VZV/HSV, SARS-CoV, COVID-19, and influenza viruses.

Distributional semantic models derive computational representations of word meaning from the patterns of co-occurrence of words in text. Such models have been a success story of computational linguistics, being able to provide reliable estimates of semantic relatedness for the many semantic tasks requiring them. However, distributional models extract meaning information exclusively from text, which is an extremely impoverished basis compared to the rich perceptual sources that ground human semantic knowledge. We address the lack of perceptual grounding of distributional models by exploiting computer vision techniques that automatically identify discrete “visual words” in images, so that the distributional representation of a word can be extended to also encompass its co-occurrence with the visual words of images it is associated with. We propose a flexible architecture to integrate text- and image-based distributional information, and we show in a set of empirical tests that our integrated model is superior to the purely text-based approach, and it provides somewhat complementary semantic information with respect to the latter.

Tyrosine is mainly degraded in the liver by a series of enzymatic reactions. Abnormal expression of the tyrosine catabolic enzyme tyrosine aminotransferase (TAT) has been reported in patients with hepatocellular carcinoma (HCC). Despite this, aberration in tyrosine metabolism has not been investigated in cancer development. In this work, we conduct comprehensive cross-platform study to obtain foundation for discoveries of potential therapeutics and preventative biomarkers of HCC. We explore data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA), Oncomine and Kaplan Meier plotter (KM plotter) and performed integrated analyses to evaluate the clinical significance and prognostic values of the tyrosine catabolic genes in HCC. We find that five tyrosine catabolic enzymes are downregulated in HCC compared to normal liver at mRNA and protein level. Moreover, low expression of these enzymes correlates with poorer survival in patients with HCC. Notably, we identify pathways and upstream regulators that might involve in tyrosine catabolic reprogramming and further drive HCC development. In total, our results underscore tyrosine metabolism alteration in HCC and lay foundation for incorporating these pathway components in therapeutics and preventative strategies.

Single-cell RNA sequencing (scRNA-seq) can map cell types, states and transitions during dynamic biological processes such as tissue development and regeneration. Many trajectory inference methods have been developed to order cells by their progression through a dynamic process. However, when time series data is available, most of these methods do not consider the available time information when ordering cells and are instead designed to work only on a single scRNA-seq data snapshot. We present Tempora, a novel cell trajectory inference method that orders cells using time information from time-series scRNA-seq data. In performance comparison tests, Tempora inferred known developmental lineages from three diverse tissue development time series data sets, beating state of the art methods in accuracy and speed. Tempora works at the level of cell clusters (types) and uses biological pathway information to help identify cell type relationships. This approach increases gene expression signal from single cells, processing speed, and interpretability of the inferred trajectory. Our results demonstrate the utility of a combination of time and pathway information to supervise trajectory inference for scRNA-seq based analysis.

Background Vulvar cancer (VC) is rare; however, its incidence has steadily increased, likely due to increased human papillomavirus (HPV) infections. HPV infection rates vary significantly with age and ethnicity. Data on the VC incidence in Vietnam are limited. Objectives This study aimed to determine HPV infection rates and high‐risk HPV types (HR‐HPVs) and to model HPV causality in co‐infections using a Proportional Attribution (PropAttr) model in Vietnamese VC patients. Methods We investigated primary VC cases (invasive carcinoma) diagnosed at our hospital during 2020–2021. Tumor samples were tested for HPV using quantitative polymerase chain reaction. Recurrent cases and poor‐quality preserved tumor samples were excluded. HPV infection status, HR‐HPV status, and relevant clinicopathological features were analyzed. To estimate the most likely causative HPV genotype in co‐infected lesions, the PropAttr model was applied, attributing genotypes based on their prevalence in mono‐infections. Model reliability was validated using Spearman's correlation analysis. Results Of the 95 cases, 95% were squamous cell carcinoma, and 40% were clinical stage I. The HPV infection rate was approximately 77% (68.4–85.2), and HPV‐16 was the most common subtype. Patients infected with HPV (mean age: 62.8) were younger than those who were not infected (mean age: 71.4) in univariate (p = 0.004) and multivariate (p < 0.001) analyses. While the vulvar pathohistological type was significantly associated with HPV infection in multivariate analysis (p < 0.001), no significant relationship was observed with other factors in univariate and multivariate analyses. The PropAttr model showed significant correlations between attribution estimates and mono‐infection prevalence (HPV‐16: ρ = 0.806, p < 0.001; HPV‐18: ρ = 0.992, p < 0.001; 12 other HR‐HPVs: ρ = 0.880, p < 0.001). A strong negative correlation between HPV‐16 and 12 other HR‐HPVs (ρ = −0.751, p < 0.001) suggested competitive interactions in genotype assignment. Conclusions The HPV infection rate in Vietnamese VC cases was substantially higher than in other Asian populations, indicating a significant public health burden. Our findings reinforce the importance of expanding national HPV vaccination programs and incorporating advanced attribution models to improve HPV‐related cancer risk assessment.

We study the topological defects in the thermodynamics of regular black strings (from a four-dimensional perspective) that is symmetric under the double Wick rotation and constructed in the high-dimensional spacetime with an extra dimension compactified on a circle. We observe that the thermodynamic phases of regular black strings can be topologically classified by the positive and negative winding numbers (at the defects) which correspond to the thermodynamically stable and unstable branches. This topological classification implies a phase transition due to the decay of a thermodynamically unstable regular black string to another which is thermodynamically stable. We confirm these topological properties of the thermodynamics of regular black strings by investigating their free energy, heat capacity, and Ruppeiner scalar curvature of the state space. The Ruppeiner scalar curvature of regular black strings is found to be always negative, implying that the interactions among the microstructures of regular black strings are only attractive.

Candida infections are a significant source of patient morbidity and mortality. Candida albicans is the most common pathogen causing Candida infections. Candida auris is a newly described pathogen that is associated with multi-drug-resistant candidiasis and candidaemia in humans. The antifungal effects of various essential oils and plant compounds have been demonstrated against human pathogenic fungi. In this study, the effect of cinnamon leaf and bark essential oils (CEOs) was determined against both C. albicans and C. auris. The disc diffusion (direct and vapour) and broth microdilution method was used to determine antifungal activity of the EOs against selected strains (C. albicans ATCC 10231, C. albicans ATCC 2091 and C. auris NCPF 8971) whilst the mode of action and haemolysin activity of the CEOs were determined using electron microscopy and light microscopy. Direct and vapour diffusion assays showed greater inhibitory activity of bark CEO in comparison with leaf CEO. The minimum inhibitory concentrations (MICs) and minimum fungicidal concentrations (MFCs) of bark CEO for all tested strains was below 0.03% (v/v), which was lower than the MICs of the leaf CEO (0.06–0.13%, v/v) dependent on the strain and the MFCs at 0.25% (v/v). In the morphological interference assays, damage to the cell membrane was observed and both CEOs inhibited hyphae formation. The haemolysin production assay showed that CEOs can reduce the haemolytic activity in the tested C. albicans and C. auris strains. At low concentrations, CEOs have potent antifungal and antihaemolytic activities in vitro against C. albicans and C. auris.Key points• Essential oils from Cinnamomum zeylanicum Blume bark and leaf (CBEO and CLEO) demonstrated fungicidal properties at very low concentrations.• The antifungal activity of CBEO was greater than that of CLEO consistent with other recent published literature.• The mode of action of CBEO and CLEO was damage to the membrane of C. albicans and C. auris.• Both CBEO and CLEO inhibited the formation of hyphae and reduced haemolysin production in C. albicans and C. auris.

Dioxin levels in the breast milk of mothers residing near a contaminated former airbase in Vietnam remain much higher than in unsprayed areas, suggesting high perinatal dioxin exposure for their infants. The present study investigated the association of perinatal dioxin exposure with autistic traits in 153 3-year-old children living in a contaminated area in Vietnam. The children were followed up from birth using the neurodevelopmental battery Bayley-III. The high-2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) exposed groups (⩾3.5 pg per g fat) showed significantly higher Autism Spectrum Rating Scale (ASRS) scores for both boys and girls than the mild-TCDD exposed groups, without differences in neurodevelopmental scores. In contrast, the high total dioxin-exposed group, indicated by polychlorinated dibenzo-p-dioxins/furans (PCDDs/Fs)—the toxic equivalents (TEQ) levels⩾17.9 pg-TEQ per g fat, had significantly lower neurodevelopmental scores than the mild-exposed group in boys, but there was no difference in the ASRS scores. The present study demonstrates a specific impact of perinatal TCDD on autistic traits in childhood, which is different from the neurotoxicity of total dioxins (PCDDs/Fs).

Cooperation in the Immune System Genetic studies of plant immunity have been tremendously influenced by Flor's gene-for-gene hypothesis, which posits that a single host resistance gene is matched by a single effector gene from a specific pathogen strain. Important goals for the future are, therefore, to better understand how the inherent trade-off between growth or fertility and immunity is managed in natural populations, to find out whether one can extrapolate from findings in A. thaliana to other species, and to test whether lessons from wild plants such as A. thaliana can be useful in crop breeding.