Anti-inflammatory and immunoregulatory effects of colistin sulphate on human PBMCs.

In previous studies, CST has been identified as having an immunostimulatory effect on Caenorhabditis elegans and macrophage of rats. Here, we further investigated its immunomodulatory effects on human peripheral blood mononuclear cells (PBMCs). LPS-stimulated PBMCs inflammatory model was established. Flow cytometry was applied to measure phagocytosis of PBMCs. Cytokine mRNA and protein expression levels of LPS-stimulated PBMCs with or without CST were measured by qRT-PCR and ELISA. The transcriptomic profile of CST-treated PBMCs was investigated by RNA-sequencing. Gene Ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) were applied to find potential signalling pathways. PBMCs showed a significant increase in phagocytic activity at 6 h after being incubated with CST at the concentration of 10 µg/mL. In the presence of LPS, CST maintained and promoted the expression of TNF-α and chemokine CCL24. The content of pro-inflammatory cytokines, such as IL-1ß, IL-6 and IFN-γ, which were released from LPS-stimulated PBMCs, was reduced by CST at 6 h. Anti-inflammatory cytokines, such as IL-4, IL-13 and TGF-ß1, were significantly increased by CST at 24 h. A total of 277 differentially expressed immune-related genes (DEIRGs) were detected and cytokine-cytokine receptor interaction was highly enriched. CST presented obvious anti-inflammatory and immunoregulatory effects in LPS-induced PBMCs inflammatory model not only by improving the ability of PBMCs to clear pathogens but also by decreasing pro-inflammatory cytokines and increasing anti-inflammatory cytokines. And the mechanism may be related to cytokine-cytokine receptor interaction.

Alkadiyne-Pyrene Conjugated Frameworks with Surface Exclusion Effect for Ultrafast Seawater Desalination.

Billions of populations are suffering from the supply-demand imbalance of clean water, resulting in a global sustainability crisis. Membrane desalination is a promising method to produce fresh water from saline waters. However, conventional membranes often encounter challenges related to low water permeation, negatively impacting energy efficiency and water productivity. Herein, we achieve ultrafast desalination over the newly developed alkadiyne-pyrene conjugated frameworks membrane supported on a porous copper hollow fiber. With membrane distillation, the membrane exhibits nearly complete NaCl rejection (>99.9%) and ultrahigh fluxes (∼500 L m-2 h-1) from the seawater salinity-level NaCl solutions, which surpass the commercial polymeric membranes with at least 1 order of magnitude higher permeability. Experimental and theoretical investigations suggest that the large aspect ratio of membrane pores and the high evaporation area contribute to the high flux, and the graphene-like hydrophobic surface of conjugated frameworks exhibits complete salt exclusion. The simulations also confirm that the intraplanar pores of frameworks are impermeable for water and ions.

Efficacy and safety of omadacycline for treating complicated skin and soft tissue infections: a meta-analysis of randomized controlled trials.

OBJECTIVE: In the present study, we aimed to compare the clinical efficacy and safety of omadacycline (OMC) with its comparators for the treatment of complicated skin and soft tissue infections (cSSTIs) in adult patients. METHODS: Randomized controlled trials (RCTs) evaluating OMC for cSSTIs were searched in databases of PubMed, Embase, Cochrane, Web of Science, and Clinical Trial, up to July 2022. The primary outcomes were clinical efficacy and microbiological response, with secondary outcome was safety. RESULTS: Four RCTs consisting of 1,757 patients were included, with linezolid (LZD) as a comparator drug. For clinical efficacy, OMC was not inferior to LZD in the modified intent-to-treat (MITT) (OR: 1.24, 95% Cl: [0.93, 1.66], P = 0.15) and clinically evaluable (CE) populations (OR: 1.92, 95% Cl: [0.94, 3.92], P = 0.07). For microbiological response, OMC was numerically higher than LZD in the microbiologically evaluable (ME) (OR: 1.74, 95% Cl: [0.81, 3.74], P = 0.16) and microbiological MITT (micro-MITT) populations (OR: 1.27, 95% Cl: [0.92, 1.76], P = 0.14). No significant difference was found in subpopulations of monomicrobial or polymicrobial mixed infection populations. The mortality and adverse event rates were similar between OMC and LZD. CONCLUSIONS: OMC was as good as LZD in terms of clinical efficacy and microbiological response, and has similar safety issues in treating cSSTIs. OMC might be a promising option for treating cSSTIs in adult patients.

Ancient forest plants possess cytotoxic properties causing liver cancer HepG2 cell apoptosis.

Here, we collected 154 plant species in China ancient forests looking for novel efficient bioactive compounds for cancer treatments. We found 600 bioactive phyto-chemicals that induce apoptosis of liver cancer cell in vitro. First, we screen the plant extract's in vitro cytotoxicity inhibition of cancer cell growth using in vitro HepG2 cell lines and MTT cytotoxicity. The results from these initial MTT in vitro cytotoxicity tests show that the most efficient plants towards hepatoma cytoxicity is Cephalotaxus sinensis, mint bush (Elsholtzia stauntonii) and winged spindle tree (Euonymus alatus). We then used in cell-counting kit-8 (CCK-8) to further understand in vivo tumor growth using nude mice and GC-MS and LC-QTOF-MS to analyze the composition of compounds in the extracts. Extracted chemically active molecules analyzed by network pharmacology showed inhibition on the growth of liver cancer cells by acting on multiple gene targets, which is different from the currently used traditional drugs acting on only one target of liver cancer cells. Extracts from Cephalotaxus sinensis, mint bush (Elsholtzia stauntonii) and winged spindle tree (Euonymus alatus) induce apoptosis in hepatoma cancer cell line HepG2 with a killing rate of more than 83% and a tumor size decrease by 62-67% and a killing rate of only 6% of normal hepatocyte LO2. This study highlight efficient candidate species for cancer treatment providing a basis for future development of novel plant-based drugs to help meeting several of the UN SDGs and planetary health.

Utilize multi-metabolic parameters as determinants for prediction of skeletal muscle mass quality in elderly type2 diabetic Chinese patients.

BACKGROUND: Sarcopenia, an age-related disorder characterized by loss of skeletal muscle mass and function, is recently recognized as a complication in elderly patients with type 2 diabetes mellitus (T2DM). Skeletal muscles play a crucial role in glycemic metabolism, utilizing around 80% of blood glucose. Accordingly, we aimed to explore the relationship between glucose metabolism and muscle mass in T2DM. METHODS: We employed the AWGS 2019 criteria for diagnosing low muscle mass and 1999 World Health Organization (WHO) diabetes diagnostic standards. This study included data of 191 individuals aged 60 and above with T2DM of Shanghai Pudong Hospital from November 2021 to November 2022. Fasting C-peptide (FPCP), fasting plasma glucose (FPG), 2-hour postprandial plasma glucose (PPG) and postprandial 2-hour C-peptide (PPCP), glycated hemoglobin A1c (HbA1c), glycated albumin (GA), serum lipids spectrum, renal and hepatic function, hemoglobin, and hormone were measured. Based on the findings of univariate analysis, logistic regression and receiver operating characteristic (ROC) curves were established. RESULTS: Participants with low muscle mass had significantly lower alanine and aspartate aminotransferase, and both FPCP and PPCP levels (P < 0.05). Compared with those without low muscle mass, low muscle mass group had significantly higher FPG, HbA1c, GA levels (P < 0.05). Body fat (BF, OR = 1.181) was an independent risk factor for low muscle mass. PPCP (OR = 0.497), BMI (OR = 0.548), and female (OR = 0.050) were identified as protective factors for low skeletal muscle. The AUC of BMI was the highest, followed by the PPCP, gender and BF (0.810, 0.675, 0.647, and 0.639, respectively), and the AUC of the combination of the above four parameters reached 0.895. CONCLUSIONS: In this cross-sectional study, BMI, Female, and PPCP associated with T2DM were protective factors for low muscle mass. BF was associated with T2DM and risk factor for low muscle mass.

Dual roles of dopaminergic pathways in olfactory learning and memory in the oriental fruit fly, Bactrocera dorsalis.

Dopamine (DA) is a key regulator of associative learning and memory in both vertebrates and invertebrates, and it is widely believed that DA plays a key role in aversive conditioning in invertebrates. However, the idea that DA is involved only in aversive conditioning has been challenged in recent studies on the fruit fly (Drosophila melanogaster), ants and crabs, suggesting diverse functions of DA modulation on associative plasticity. Here, we present the results of DA modulation in aversive olfactory conditioning with DEET punishment and appetitive olfactory conditioning with sucrose reward in the oriental fruit fly, Bactrocera dorsalis. Injection of DA receptor antagonist fluphenazine or chlorpromazine into these flies led to impaired aversive learning, but had no effect on the appetitive learning. DA receptor antagonists impaired both aversive and appetitive long-term memory retention. Interestingly, the impairment on appetitive memory was rescued not only by DA but also by octopamine (OA). Blocking the OA receptors also impaired the appetitive memory retention, but this impairment could only be rescued by OA, not by DA. Thus, we conclude that in B. dorsalis, OA and DA pathways mediate independently the appetitive and aversive learning, respectively. These two pathways, however, are organized in series in mediating appetitive memory retrieval with DA pathway being at upstream. Thus, OA and DA play dual roles in associative learning and memory retrieval, but their pathways are organized differently in these two cognitive processes - parallel organization for learning acquisition and serial organization for memory retrieval.

Immune scoring model based on immune cell infiltration to predict prognosis in diffuse large B-cell lymphoma.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is genetically heterogeneous in both pathogenesis and clinical symptoms. Most studies on tumor prognosis have not fully considered the role of tumor-infiltrating immune cells. This study focused on the role of tumor-infiltrating immune cells in the prognosis of DLBCL. METHODS: The GSE10846 data set from the National Center for Biotechnology Information's Gene Expression Omnibus was used as the training set, and the GSE53786 data set was used as the validation set. The proportion of immune cells in each sample was calculated with the CIBERSORT algorithm using R software. After 10 immune cells were screened out (activated memory CD4 positive T cells, follicular helper T cells, regulatory T cells, gamma-delta T cells, activated natural killer cells, M0 macrophages, M2 macrophages, resting dendritic cells, and eosinophils) by univariate Cox analysis, Lasso regression and random forest sampling analyses were performed, the intersecting immune cells were selected for multifactor Cox analysis, and a predictive model was constructed combined with clinical information. Predictive performance was assessed using survival analysis and time-dependent receiver operating characteristic curve analysis. RESULTS: In total, 539 samples were included in this study, and samples with p < .05 were retained using CIBERSORT. Univariate Cox analysis yielded 10 cell types that were associated with overall survival. Two kinds of immune cells were obtained by Lasso regression combined with the random forest method and were used to construct a prognostic model combined with clinical information. The reliability of the model was validated in two data sets. CONCLUSIONS: The immune cell-based prediction model constructed by the authors can effectively predict the prognostic outcome of patients with DLBCL, whereas nomogram plots can help clinicians assess the probability of long-term survival.

Dietary Inflammatory Patterns Are Associated With Serum TGs and Insulin in Adults: A Community-Based Study in Taiwan.

BACKGROUND: Dietary patterns related to inflammation have become a focus of disease prevention but the patterns may vary among populations. OBJECTIVES: The study was conducted to determine Taiwanese dietary inflammatory patterns and evaluate their associations with biomarkers of lipid and glucose. METHODS: Data were taken from 5664 community-dwelling individuals aged ≥55 y recruited in 2009-2013 in the Healthy Aging Longitudinal Study in Taiwan (HALST). Dietary data were obtained from an FFQ. An empirical dietary inflammatory pattern (EDIP) was derived from reduced rank regression models that explained the serum high-sensitivity CRP, plasma IL-6, and TNF receptor 1. Cross-sectional associations between dietary scores and biomarkers of total cholesterol (TC); HDL cholesterol; LDL cholesterol; TG; and ratios of TG/HDL cholesterol, TG/TC, fasting glucose, insulin, and HbA1c were analyzed via multiple linear regression and adjusted for major confounders. The false-discovery rate (FDR)-adjusted P < 0.05 was considered statistically significant. Abdominal obesity was defined as a waist circumference of ≥90 cm for men and ≥80 cm for women. RESULTS: Higher EDIP-HALST scores were associated with higher TG (per score increment: 1.62%, 95% CI: 0.58%, 2.76%; PFDR = 0.01), TG/HDL cholesterol (2.01%, 95% CI: 0.67%, 3.37%; PFDR = 0.01), and TG/TC (1.42%, 95% CI: 0.41%, 2.43%; PFDR = 0.01) and nonlinearly associated with insulin, with those in the middle tertile had the highest serum insulin concentrations (means: 5.12 µIU/mL, 95% CI: 4.78, 5.78; PFDR = 0.04) in men, but not in women. No heterogeneity was detected between sexes. The associations with TG (1.23%, 95% CI: 0.19, 2.23%; Ptrend = 0.02), TG/HDL cholesterol (1.62%, 95% CI: 0.30%, 2.96%; Ptrend = 0.02), and TG/TC (1.11%, 95% CI: 0.11%, 2.13%; Ptrend = 0.03) were stronger in participants with abdominal obesity, but were borderline associated in participants with normal abdominal circumferences (all Ptrend = 0.05). CONCLUSIONS: Inflammatory diets, as measured via EDIP-HALST, are associated with serum TG concentration, particularly in participants with abdominal obesity. These findings may suggest that developing disease prevention strategies using dietary inflammatory patterns may be different by populations. J Nutr 20xx;x:xx.

Ampicillin exacerbates acetaminophen-induced acute liver injury by inducing intestinal microbiota imbalance and butyrate reduction.

BACKGROUND AND AIMS: Antibiotics (ATBx) and acetaminophen (APAP) are widely used worldwide. APAP is the most common cause of acute liver injury (ALI) and might be used in combination with ATBx in clinics. However, the impact of ATBx on APAP-induced ALI has rarely been studied. METHODS: First, we compared the effects of seven ATBx on APAP-induced ALI. Then, we analysed faecal, serum and liver samples to investigate the impact of the gut microbiota on this process. Finally, we assessed the role of short-chain fatty acids in this process. RESULTS: In this work, we found that the ALI was significantly aggravated in the mice treated with ampicillin (Amp) instead of other ATBx. Amp exposure reduced the diversity and altered the composition of gut microbiota. The altered gut microbiota aggravated APAP-induced ALF, which was proven by faecal microbiota transplantation from ATBx-treated mice. Metagenomic analysis showed a significantly decreased Lactobacillus abundance in Amp-treated mice. Gavage with Lactobacillus, especially Lactobacillus rhamnosus, significantly reversed the severer ALF induced by APAP and Amp. Moreover, Lactobacillus supplementation increased butyrate-producing clostridia and lowered butyrate levels in Amp-treated mice. In accordance, butyrate supplementation could also alleviate Amp-aggravated ALI. In addition, inhibition of nuclear factor erythroid 2-related factor 2 counteracted the protective effect of butyrate on aggravated ALI induced by Amp and APAP. CONCLUSION: Together, this study revealed a potential health impact of Amp that may exacerbate liver damage when co-exposed to excess APAP.

Host ALDH2 deficiency aggravates nonalcoholic steatohepatitis through gut-liver axis.

Nonalcoholic steatohepatitis (NASH) is the major cause of liver dysfunction. Animal and population studies have shown that mitochondrial aldehyde dehydrogenase (ALDH2) is implicated in fatty liver disease. However, the role of ALDH2 in NASH and the underlying mechanisms remains unclear. To address this issue, ALDH2 knockout (ALDH2-/-) mice and wild-type littermate mice were fed a methionine-and choline-deficient (MCD) diet to induce a NASH model. Fecal, serum, and liver samples were collected and analyzed to investigate the impact of the gut microbiota and bile acids on this process. We found that MCD-fed ALDH2-/- mice exhibited increased serum pro-inflammation cytokines, hepatic inflammation and fat accumulation than their wild-type littermates. MCD-fed ALDH2-/- mice exhibited worsened MCD-induced intestinal inflammation and barrier damage, and gut microbiota disorder. Furthermore, mice receiving microbiota from MCD-fed ALDH2-/- mice had increased severity of NASH compared to those receiving microbiota from MCD-fed wild-type mice. Notably, the intestinal Lactobacillus was significantly reduced in MCD-fed ALDH2-/- mice, and gavage with Lactobacillus cocktail significantly improved MCD-induced NASH. Finally, we found that ALDH2-/- mice had reduced levels of bile salt hydrolase and specific bile acids, especially lithocholic acid (LCA), accompanied by downregulated expression of the intestinal FXR-FGF15 pathway. Supplementation of LCA in ALDH2-/- mice upregulated intestinal FXR-FGF15 pathway and alleviated NASH. In summary, ALDH2 plays a critical role in the development of NASH through modulation of gut microbiota and bile acid. The findings suggest that supplementing with Lactobacillus or LCA could be a promising therapeutic approach for treating NASH exacerbated by ALDH2 deficiency.

The Potential Value of Ki-67 in Prognostic Classification in Early Low-Risk Endometrial Cancer.

PURPOSE: This study aims to determine the optimal cut-off value of Ki-67 to better predict the recurrence of early low-risk endometrial cancer (EC). METHODS: Seven hundred and forty-eight patients diagnosed with low-risk EC from West China Second Hospital of Sichuan University and the First Affiliated Hospital of Chongqing Medical University were retrospectively analyzed. The receiver operating characteristic curve (ROC) and Youden index were used to calculate the optimal cut-off value of Ki-67 expression. The clinicopathological indexes between two groups divided by cut-off value of Ki-67 were compared. The univariate and multivariate regression analyses were performed to investigate risk factors connected to the recurrence of early low-risk EC. The survival analysis was shown in Kaplan-Meier curve. RESULT: Thirty-three patients were detected with tumor recurrence after primary surgery (4.4%); 33% was the optimal cut-off value of the Ki-67 index. A high Ki-67 was significantly associated with age (P = .002), myometrial invasion (P < .001), and the expression of P53 (P = .007). The multivariate regression analysis verified that Ki67 ≥ 33% was an independent prognostic factor for predicting recurrence. The recurrence-free survival (RFS) and the overall survival (OS) in high Ki-67 group was significantly lower than that in low Ki-67 group (P < .001 and P = .029, respectively). The prognostic values of ER, PR, and P53 in combination with Ki-67 were superior to each single predictor. CONCLUSIONS: The optimal cut-off value of Ki-67 for predicting recurrence is 33%, which quantitatively defines the specific value of Ki-67 that causes high-risk recurrence in early low-risk EC.

Construction of 3D Hierarchical Co3O4@CoFe-LDH Heterostructures with Effective Interfacial Charge Redistribution for Rechargeable Liquid/Solid Zn-Air Batteries.

Constructing three-dimensional (3D) hierarchical heterostructures is an appealing but challenging strategy to improve the performance of catalysts for electrical energy devices. Here, an efficient and robust flexible self-supporting catalyst, interface coupling of ultrathin CoFe-LDH nanosheets and Co3O4 nanowire arrays on the carbon cloth (CC/Co3O4@CoFe-LDH), was proposed for boosting oxygen evolution reaction (OER) in rechargeable liquid/solid Zn-air batteries (ZABs). The strong interfacial interaction between the CoFe-LDH and Co3O4 heterostructures stimulated the charge redistribution in their coupling regions, which improved the electron conductivity and optimized the adsorption free energy of OER intermediates, ultimately boosting the intrinsic OER performance. Besides, the 3D hierarchical nanoarray structure facilitated the exposure of catalytically active centers and rapid electron/mass transfer during the OER process. As such, the CC/Co3O4@CoFe-LDH catalyst achieved excellent OER catalytic activity in alkaline medium, with a small overpotential of 237 mV at 10 mA cm-2, a low Tafel slope of 35.43 mV dec-1, and long-term durability of up to 48 h, significantly outperforming the commercial RuO2 catalyst. More impressively, the liquid and flexible solid-state ZABs assembled by the CC/Co3O4@CoFe-LDH hybrid catalyst as the OER catalyst presented a stable open circuit voltage, large power density, superb cycling life, and satisfactory flexibility, indicating great potential applications in energy technology. This work provides a good guidance for the development of advanced electrocatalysts with heterostructures and an in-depth understanding of electronic modulation at the heterogeneous interface.

Optimization on structure and operation parameters of biofilter for decentralized sewage treatment.

Aiming for treating decentralized domestic wastewater in rural China, this study evaluates the effects of ceramsite size and structure, and water recirculation parameters, upon the performance of recirculating biofilter (RBF). RBF shows stable capability of chemical oxygen demand (COD) remediation and ammonia nitrification. In addition, the microbial flora and structures of the various layers in the system are analyzed via high-throughput sequencing in order to study the microbial diversity. The results indicate that while the ceramic particle size has no significant influence on the COD remediation capacity, the ceramics with smaller particle sizes exhibit better ammonia nitrogen (NH4+-N) removal ability, with a first-order linear relationship between the influent ammonia nitrogen load and the effluent NH4+-N concentration in RBF (R2 > 0.64). An increased hydraulic load and intermittent operation are shown to deteriorate the water quality with respect to NH4+-N, while an increased recirculation ratio increases the removal rate of NH4+-N from the effluent. Further, the water distribution time has a stronger effect upon the NH4+-N concentration in the effluent than does the recirculation ratio. Moreover, the microbial structure of the multi-layer recirculating trickle biofilter varies significantly during the process. The results indicate that a high recirculation ratio, long water distribution time, and multi-layer structure will be beneficial for improving the pollutant treatment capacity of RBF.

A new approach to optimizing aeration using XGB-Bi-LSTM via the online monitoring of oxygen transfer efficiency and oxygen uptake rate.

In wastewater treatment plants (WWTPs), aeration is vital for microbial oxygen needs. To achieve carbon neutrality, optimizing aeration for energy and emissions reduction is imperative. Machine learning (ML) is used in wastewater treatment to reveal complex rules in large data sets has become a trend. In this vein, the present paper proposes an aeration optimization approach based on the extreme gradient boosting-bidirectional long short-term memory (XGB-Bi-LSTM) model via the online monitoring of oxygen transfer efficiency (OTE) and oxygen uptake rate (OUR), thus allowing WWTPs to conserve energy and reduce indirect carbon emissions. The approach uses gain algorithm of XGB to calculate the importance of features and identify important parameters, and then uses Bi-LSTM to predict the target with important parameters as features. Operational data from a WWTP in Suzhou, China, is employed to train and test the approach, the performance of which is compared with ML models suitable for regression prediction tasks (XGB, random forest, light gradient boosting machine, gradient boosting and LSTM). Experimental results show the approach requires only a small number of input parameters to achieve good performance and outperforms other machine-learning models. When OTE and dissolved oxygen (DO) are used as features to predict the alpha factor (αF; since diffusers were used, multiply by the pollution factor F), the R-squared (R2) is 0.9977, the root mean square error (RMSE) is 0.0043, the mean absolute percentage error (MAPE) is 0.0069 and the median absolute error (MedAE) is 0.0032. When the predicted αF and the OUR are used as features to predict the air flow rate of an aeration unit, the R2 is 0.9901, the RMSE is 3.6150, the MAPE is 0.0209 and the MedAE is 1.5472. Using our optimized aeration approach, the energy consumption can be reduced by 23%.

Effects of posture on heart rate variability in non-frail and prefrail individuals: a cross-sectional study.

BACKGROUND: Frailty is an aging-related syndrome leading to high mortality in older adults. Without effective assessment and prevention of frailty, the incidence of frailty and relevant adverse outcomes will increase by 2050 as worldwide populations age. Although evidence suggested heart rate variability (HRV) is a potential measure of frailty, the role of HRV in frailty assessment remains unclear because of controversial findings. This study examined the effects of posture on HRV parameters in non-frail and prefrail individuals to understand the role of HRV in assessing frailty. METHODS: Forty-six participants aged ≥ 50 years were recruited between April and August 2022. Frailty was defined using Fried's criteria. HRV was measured in standing, sitting, and lying postures, respectively, using a Polar Watch, and analyzed using Kubios HRV Standard 3.5.0 (Kubios). The five most commonly used parameters were examined, including standard deviations of all normal-to-normal intervals (SDNN), root mean square of the successive differences (RMSSD), low frequency (LF), high frequency (HF), and LF/HF. Independent t-tests and Mann-Whitney tests were used for inter-group comparisons. Friedman tests were used for intra-group comparisons across postures. RESULTS: The non-frail group showed significant differences in HRV parameters across postures (all p < 0.05), whereas the prefrail group did not demonstrate any difference (all p > 0.05). The differences in the non-frail group included higher RMSSD and HF in the lying posture compared to those in the standing posture (29.54 vs 21.99 p = 0.003, 210.34 vs 96.34 p = 0.001, respectively), and higher LF and LF/HF in the sitting posture compared to those in the lying posture (248.40 vs 136.29 P = 0.024, 1.26 vs 0.77 p = 0.011, respectively). CONCLUSIONS: The effects of posture on HRV were blunted in the prefrail group, which suggests an impaired cardiac autonomic functioning. Measuring the effects of posture on HRV parameters may contribute to frailty assessment. However, further evidence from larger cohorts and including additional HRV parameters is needed.

Combination of chemical profiling and network pharmacology analysis to investigate the potential mechanism of Li-Zhong-Xiao-Pi granules in the treatment of gastric precancerous lesions.

Li-Zhong-Xiao-Pi granules (LZXP) are effective for treating gastric precancerous lesions (GPL) in traditional Chinese medicine. However, the active compounds of LZXP and their potential therapeutic mechanism in GPL remained unclarified. The purpose of this study is to investigate the chemical composition and potential targets of LZXP. Based on the accurate masses, ion fragments, and literature data, a total of 128 compounds were identified in the LZXP sample using ultra-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) in both positive and negative ion modes, and 28 of these compounds were exactly determined by comparison with authentic reference standards. Meanwhile, 11 typical components were quantified via UPLC during a 24 min period. The linearity, accuracy, stability and recovery of the method were all proven. Through the network pharmacological analysis, six chemicals (quercetin, 4'-hydroxywogonin, sinensetin, 5, 7, 8, 3', 4'-pentamethoxyflavanone, 8-gingerdione and quercetin) were identified as the active ingredients, and five LZXP targets (AKT1, CYP1B1, PTGS2, MMP9 and EGFR) were found to be the crucial molecules in the treatment of GPL. This study provides a systematic and applicable method for the rapid screening and identification of the chemical constituents from LZXP, and an effective understanding the mechanism of LZXP in the treatment of GPL.

Effects of strontium on the morphological and photosynthetic physiological characteristics of Vicia faba seedlings.

The adaptation of plants to strontium (Sr) stress requires a more systematic understanding. In the present study, the morphological and photosynthetic physiological characteristics of Vicia faba seedlings under Sr stress (88Sr, 0-1,000 mg·L-1) were analyzed in solution culture. The results showed that Sr treatment decreased the biomass and root activity of V. faba seedlings significantly, but fortunately, there was almost no root necrosis. In plant morphology, the taproot length, lateral root number, plant height, branching number and internodes number of V. faba were significantly inhibited, thus the apical dominance of taproot and terminal bud was more obvious. The accumulation of Sr resulted in the decrease of leaf area, dry weight, stomatal density and stomatal aperture, while the guard cell length increased, and the specific leaf weight (SLW) increased first and then decreased. These changes in stomatal morphology may be a positive regulation to reduce water loss. In addition, V. faba increased the non-photochemical quenching (NPQ) and the activities of peroxidase (POD) and ascorbate peroxidase (APX) to protect the photosynthetic structure. Low concentration of Sr (250 mg·L-1) promoted the photochemical efficiency and electron transfer of PSII (e.g., increased Fv/Fm, ΦPSII, qP and ETR). However, Sr (250-1,000 mg·L-1) inhibited the net photosynthetic rate (Pn), transpiration rate (Tr) and stomatal conductance (Gs) in leaves. In general, the Pn was affected by both stomatal and non-stomatal factors. Since Sr did not cause significant damage to the PSII function, the non-stomatal factor may be the dark reaction in photosynthesis affected, but this needs to be proved by further studies.

Recently, strontium (Sr) pollution has become a global environmental problem. There is still a lack of systematic understanding of plant morphological and physiological responses to Sr stress. Therefore, V. faba, a Sr-accumulation plant, was used as the experimental material to systematically understand the adaptation characteristics of plants to Sr stress, which provide reference for the application of plants in the remediation of Sr pollution.

An Enhanced RIME Optimizer with Horizontal and Vertical Crossover for Discriminating Microseismic and Blasting Signals in Deep Mines.

Real-time monitoring of rock stability during the mining process is critical. This paper first proposed a RIME algorithm (CCRIME) based on vertical and horizontal crossover search strategies to improve the quality of the solutions obtained by the RIME algorithm and further enhance its search capabilities. Then, by constructing a binary version of CCRIME, the key parameters of FKNN were optimized using a binary conversion method. Finally, a discrete CCRIME-based BCCRIME was developed, which uses an S-shaped function transformation approach to address the feature selection issue by converting the search result into a real number that can only be zero or one. The performance of CCRIME was examined in this study from various perspectives, utilizing 30 benchmark functions from IEEE CEC2017. Basic algorithm comparison tests and sophisticated variant algorithm comparison experiments were also carried out. In addition, this paper also used collected microseismic and blasting data for classification prediction to verify the ability of the BCCRIME-FKNN model to process real data. This paper provides new ideas and methods for real-time monitoring of rock mass stability during deep well mineral resource mining.

Association between periodontitis treatment and dementia in Taiwanese adults.

BACKGROUND: The chronic systemic inflammatory response in periodontitis may be a potential risk factor for dementia, especially in adults. This study determined the association between periodontal treatment and dementia in adults and evaluated the effect of regular scaling treatment on the risk of dementia in this population. METHODS: This case-control study identified 18,930 patients with a dementia-related diagnosis from the Taiwan National Health Insurance Research Database. Scaling and periodontal emergency treatments were evaluated after 1 year and 3 years. Using multivariable logistic regression analysis to evaluate the association between periodontal emergency treatment and dementia risk. RESULTS: The results showed that scaling treatment rates were lower in the dementia cohort than the non-dementia cohort after 1 and 3 years. Patients who received periodontal emergency treatment within 3 years had a significantly increased risk of dementia. Furthermore, patients with periodontitis who did not receive scaling treatment within 3 years had a higher risk of dementia than patients without periodontitis (OR, 1.22; 95% CI, 1.10-1.35). CONCLUSION: This study demonstrated that periodontitis and dementia are associated, and that periodontitis is a risk factor for dementia in adults. The risk of dementia was dependent on the periodontal health status of adults, and our findings suggest that regular scaling can reduce the incidence of dementia in adults. Therefore, regular and routine scaling treatment is suggested for adults.

Boosted crow search algorithm for handling multi-threshold image problems with application to X-ray images of COVID-19.

COVID-19 is pervasive and threatens the safety of people around the world. Therefore, now, a method is needed to diagnose COVID-19 accurately. The identification of COVID-19 by X-ray images is a common method. The target area is extracted from the X-ray images by image segmentation to improve classification efficiency and help doctors make a diagnosis. In this paper, we propose an improved crow search algorithm (CSA) based on variable neighborhood descent (VND) and information exchange mutation (IEM) strategies, called VMCSA. The original CSA quickly falls into the local optimum, and the possibility of finding the best solution is significantly reduced. Therefore, to help the algorithm avoid falling into local optimality and improve the global search capability of the algorithm, we introduce VND and IEM into CSA. Comparative experiments are conducted at CEC2014 and CEC'21 to demonstrate the better performance of the proposed algorithm in optimization. We also apply the proposed algorithm to multi-level thresholding image segmentation using Renyi's entropy as the objective function to find the optimal threshold, where we construct 2-D histograms with grayscale images and non-local mean images and maximize the Renyi's entropy on top of the 2-D histogram. The proposed segmentation method is evaluated on X-ray images of COVID-19 and compared with some algorithms. VMCSA has a significant advantage in segmentation results and obtains better robustness than other algorithms. The available extra info can be found at https://github.com/1234zsw/VMCSA.