Analgesic effect of flurbiprofen ester and its effect on serum inflammatory factors and Β-endorphin expression in rats with incision pain

Purpose: To study the analgesic effect of flurbiprofen ester in rats with incision pain, and its effect on serum inflammatory factors and β-endorphin expression. Methods: Seventy-five (75) healthy rats with foot contraction threshold induced by basic mechanical stimulation were randomly assigned to control, model control and treatment groups. Flurbiprofen was administered in 3 doses: 5, 10 and 15 mg/kg. Then, 3 mL of ventricular blood was taken from anesthetized rats and the serum levels of tumor necrosis factor-α (TNF- α), interleukin-1 β, interleukin-6 and β-endorphin were measured. The expression of β-endorphin in the spinal cord of rats with lumbar enlargement and ARC was determined. Results: The TNF- α, interleukin-1 β and interleukin-6 concentrations were significantly lower in treatment group than in model rats, and decreased with time and dose (p < 0.05). In the treatment group, the level of serum β-endorphin decreased with increase in dose at 1 h, but increased with increase in dose at 5 h and 10 h (p < 0.05). The levels of β-endorphin in the spinal cord, was significantly lower in model rats than in control rats (p < 0.05). Conclusion: Pre-administration of flurbiprofen ester reduces serum inflammatory factors and upregulates β-endorphin expression in rats with incision pain. Thus, it flurbiprofen exerts analgesic effect. Keywords: Flurbiprofen ester, Incision pain, Rat, Analgesia, Inflammatory factor, β-endorphi

Oral Probiotics Ameliorate the Behavioral Deficits Induced by Chronic Mild Stress in Mice via the Gut Microbiota-Inflammation Axis

In recent years, a burgeoning body of research has revealed links between depression and the gut microbiota, leading to the therapeutic use of probiotics for stress-related disorders. In this study, we explored the potential antidepressant efficacy of a multi-strain probiotics treatment (Lactobacillus helveticus R0052, Lactobacillus plantarum R1012, and Bifidobacterium longum R0175) in a chronic mild stress (CMS) mouse model of depression and determined its probable mechanism of action. Our findings revealed that mice subjected to CMS exhibited anxiety- and depressive-like behaviors in the sucrose preference test, elevated plus maze, and forced swim test, along with increased interferon-γ, tumor necrosis factor-α, and indoleamine 2,3-dioxygenase-1 levels in the hippocampus. Moreover, the microbiota distinctly changed from the non-stress group and was characterized by highly diverse bacterial communities associated with significant reductions in Lactobacillus species. Probiotics attenuated CMS-induced anxiety- and depressive-like behaviors, significantly increased Lactobacillus abundance, and reversed the CMS-induced immune changes in the hippocampus. Thus, the possible mechanism involved in the antidepressant-like activity of probiotics is correlated with Lactobacillus species via the gut microbiota-inflammation-brain axis

LncRNA LCPAT1 Mediates Smoking/ Particulate Matter 2.5-Induced Cell Autophagy and Epithelial-Mesenchymal Transition in Lung Cancer Cells via RCC2

Background/Aims: Ecological studies have shown that air pollution and prevalence of cigarette smoking are positively correlated. Evidence also suggests a synergistic effect of cigarette smoking and PM2.5 exposure (Environmental Particulate Matter ≤ 2.5 µm in diameter) on lung cancer risk. We aimed to evaluate the interaction between smoking prevalence and PM2.5 pollution in relation to lung cancer mortality and determine its underlying mechanisms in vitro. Methods: “MOVER” method was used to analyze the interaction between smoking prevalence and PM2.5 pollution in relation to lung cancer mortality. Cell autophagy and malignant behaviors induced by cigarette smoke extract (CSE) and PM2.5 exposure were examined in vitro. Gene expression was examined by qRT-PCR and western blot. RNA and protein interaction was determined using a RNA binding protein immunoprecipitation assay. Results: An increased risk for lung cancer death (RERI (the relative excess risk) =0.28) was observed with a synergistic interaction between cigarette smoking and PM2.5 pollution. Cell migration, invasion, EMT (epithelial-mesenchymal transition) and autophagy were elevated when lung cancer cells were treated with CSE and PM2.5 in combination. A lncRNA, named lung cancer progression-association transcript 1 (LCPAT1), was up-regulated after the treatment of CSE and PM2.5, and knocking down the lncRNA impaired the effect of CSE and PM2.5 on lung cancer cells. In addition, LCPAT1 was shown to bind to RCC2, and RCC2 mediated the effect of LCPAT1 on cell autophagy, migration, invasion and EMT in lung cancer. Conclusions: Our results suggest that combined exposure to CSE and PM2.5 induces LCPAT1 expression, which up-regulates autophagy, and promotes lung cancer progression via RCC2

CT-Based Risk Factors for Mortality of Patients With COVID-19 Pneumonia in Wuhan, China: A Retrospective Study

Purpose: Computed tomography (CT) characteristics associated with critical outcomes of patients with coronavirus disease 2019 (COVID-19) have been reported. However, CT risk factors for mortality have not been directly reported. We aim to determine the CT-based quantitative predictors for COVID-19 mortality.Methods: In this retrospective study, laboratory-confirmed COVID-19 patients at Wuhan Central Hospital between December 9, 2019, and March 19, 2020, were included. A novel prognostic biomarker, V-HU score, depicting the volume (V) of total pneumonia infection and the average Hounsfield unit (HU) of consolidation areas was automatically quantified from CT by an artificial intelligence (AI) system. Cox proportional hazards models were used to investigate risk factors for mortality.Results: The study included 238 patients (women 136/238, 57%; median age, 65 years, IQR 51–74 years), 126 of whom were survivors. The V-HU score was an independent predictor (hazard ratio [HR] 2.78, 95% confidence interval [CI] 1.50–5.17; p = 0.001) after adjusting for several COVID-19 prognostic indicators significant in univariable analysis. The prognostic performance of the model containing clinical and outpatient laboratory factors was improved by integrating the V-HU score (c-index: 0.695 vs. 0.728; p < 0.001). Older patients (age ≥ 65 years; HR 3.56, 95% CI 1.64–7.71; p < 0.001) and younger patients (age < 65 years; HR 4.60, 95% CI 1.92–10.99; p < 0.001) could be further risk-stratified by the V-HU score.Conclusions: A combination of an increased volume of total pneumonia infection and high HU value of consolidation areas showed a strong correlation to COVID-19 mortality, as determined by AI quantified CT

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

The Olfactory Chemosensation of Hematophagous Hemipteran Insects.

As one of the most abundant insect orders on earth, most Hemipteran insects are phytophagous, with the few hematophagous exceptions falling into two families: Cimicidae, such as bed bugs, and Reduviidae, such as kissing bugs. Many of these blood-feeding hemipteran insects are known to be realistic or potential disease vectors, presenting both physical and psychological risks for public health. Considerable researches into the interactions between hemipteran insects such as kissing bugs and bed bugs and their human hosts have revealed important information that deepens our understanding of their chemical ecology and olfactory physiology. Sensory mechanisms in the peripheral olfactory system of both insects have now been characterized, with a particular emphasis on their olfactory sensory neurons and odorant receptors. This review summarizes the findings of recent studies of both kissing bugs (including Rhodnius prolixus and Triatoma infestans) and bed bugs (Cimex lectularius), focusing on their chemical ecology and peripheral olfactory systems. Potential chemosensation-based applications for the management of these Hemipteran insect vectors are also discussed

Organic crystal structure prediction via coupled generative adversarial networks and graph convolutional networks

Organic crystal structures exert a profound impact on the physicochemical properties and biological effects of organic compounds. Quantum mechanics (QM)–based crystal structure predictions (CSPs) have somewhat alleviated the dilemma that experimental crystal structure investigations struggle to conduct complete polymorphism studies, but the high computing cost poses a challenge to its widespread application. The present study aims to construct DeepCSP, a feasible pure machine learning framework for minute-scale rapid organic CSP. Initially, based on 177,746 data entries from the Cambridge Crystal Structure Database, a generative adversarial network was built to conditionally generate trial crystal structures under selected feature constraints for the given molecule. Simultaneously, a graph convolutional attention network was used to predict the density of stable crystal structures for the input molecule. Subsequently, the distances between the predicted density and the definition-based calculated density would be considered to be the crystal structure screening and ranking basis, and finally, the density-based crystal structure ranking would be output. Two such distinct algorithms, performing the generation and ranking functionalities, respectively, collectively constitute the DeepCSP, which has demonstrated compelling performance in marketed drug validations, achieving an accuracy rate exceeding 80% and a hit rate surpassing 85%. Inspiringly, the computing speed of the pure machine learning methodology demonstrates the potential of artificial intelligence in advancing CSP research

The complete mitogenome and phylogeny analysis of Pareuchiloglanis longicauda (Yue, 981) (Siluriformes: Sisoridae)

Pareuchiloglanis longicauda, a Sisorid fish that is distributed in the upper Pearl River. In this study, the complete mitogenome of P. longicauda was sequenced using traditional Sanger sequencing approach. The 16,588 bp genome was consisted of 2 rRNAs, 22tRNAs, 13 protein-coding genes (PCGs) and 1 control region. The 13 PCGs started with a traditional ATG and end with stop codon TAA, TAG, TGA, TA or a single T base. Phylogenetic analysis based on 13 PCGs from 22 species using maximum-likelihood method produced three major clades (Clade I, II and III). Unexpectedly, our mitogenome exhibited only 92.12% identity to the previously published one (GenBank accession no. KP872693) with differences mainly located in the gene region. Furthermore, Pareuchiloglanis did not form a monophyletic genus and P. longicauda had the closest relationship with P. macrotrema. The result suggested that more complete mitogenomes are needed to reveal the phylogenetic placement of Pareuchiloglanis in the family Sisoridae