Combined probiotic bacteria promotes intestinal epithelial barrier function in interleukin-10-gene-deficient mice

AIM:To investigate the protective effects of combinations of probiotic(Bifico)on interleukin(IL)-10-genedeficient(IL-10 KO)mice and Caco-2 cell monolayers.METHODS:IL-10 KO mice were used to assess the benefits of Bifico in vivo.IL-10 KO and control mice received approximately 1.5×108 cfu/d of Bifico for 4 wk.Colons were then removed and analyzed for epithelial barrier function by Ussing Chamber,while an ELISA was used to evaluate proinflammatory cytokines.The colon epithelial cell line,Caco-2,was used to test the benefit of Bifico in vitro.Enteroinvasive Escherichia coli(EIEC)and the probiotic mixture Bifico,or single probiotic strains,were applied to cultured Caco-2 monolayers.Barrier function was determined by measuring transepithelial electrical resistance and tight junction protein expression.RESULTS:Treatment of IL-10 KO mice with Bifico partially restored body weight,colon length,and epithelial barrier integrity to wild-type levels.In addition,IL-10 KO mice receiving Bifico treatment had reduced mucosal secretion of tumor necrosis factor-αand interferon-γ,and attenuated colonic disease.Moreover,treatment of Caco-2 monolayers with Bifico or singlestrain probiotics in vitro inhibited EIEC invasion and reduced the secretion of proinflammatory cytokines.CONCLUSION:Bifico reduced colon inflammation in IL-10 KO mice,and promoted and improved epithelialbarrier function,enhanced resistance to EIEC invasion,and decreased proinflammatory cytokine secretion.

Probiotic BIFICO cocktail ameliorates Helicobacter pylori induced gastritis

AIM:To determine the protective effect of triple viable probiotics on gastritis induced by Helicobacter pylori(H.pylori) and elucidate the possible mechanisms of protection.METHODS:Colonization of BIFICO strains in the mouse stomach was determined by counting colony-forming units per gram of stomach tissue.After treatment with or without BIFICO,inflammation and H.pylori colonization in the mouse stomach were analyzed by hematoxylin and eosin and Giemsa staining,respectively.Cytokine levels were determined by enzyme-linked immunosorbent assay and Milliplex.The activation of nuclear factor(NF)-κB and MAPK signaling in human gastric epithelial cells was evaluated by Western blot analysis.Quantitative reverse transcription-polymerase chain reaction was used to quantify TLR2,TLR4 and MyD 88 mR NA expression in the mouse stomach.RESULTS:We demonstrated that BIFICO,which contains a mixture of Enterococcus faecalis,Bifidobacterium longum and Lactobacillus acidophilus,was tolerant to the mouse stomach environment and was able to survive both the 8-h and 3-d courses of administration.Although BIFICO treatment had no effect on the colonization of H.pylori in the mouse stomach,it ameliorated H.pylori-induced gastritis by significantly inhibiting the expression of cytokines and chemokines such as TNF-α,IL-1β,IL-10,IL-6,G-CSF and MIP-2(P < 0.05).These results led us to hypothesize that BIFICO treatment would diminish the H.pylori-induced inflammatory response in gastric mucosal epithelial cells in vitro via the NF-κB and MAPK signaling pathways.Indeed,we observed a decrease in the expression of the NF-κB subunit p65 and in the phosphorylation of IκB-α,ERK and p38.Moreover,there was a significant decrease in the production of IL-8,TNF-α,G-CSF and GM-CSF(P <0.05),and the increased expression of TLR2,TLR4 and My D88 induced by H.pylori in the stomach was also significantly reduced following BIFICO treatment(P <0.05).CONCLUSION:Our results suggest that the probiotic cocktail BIFICO can ameliorate H.pylori-induced gastritis by inhibiting the inflammatory response in gastric epithelial cells.

Dead lithium formation in lithium metal batteries:A phase field model

Lithium metal batteries are the most promising choices for next-generation high-energy–density batteries. However, there is little mechanism understanding on lithium dendrite growth during lithium plating and the dead lithium(the main component of inactive lithium) formation during lithium stripping. This work proposed a phase field model to describe the lithium stripping process with dead lithium formation.The coupling of galvanostatic conditions enables the phase field method to accurately match experimental results. The factors influencing the dead lithium formation on the increasing discharge polarization are revealed. Besides, the simulation of the battery polarization curve, the capacity loss peak, and the Coulomb efficiency is realized. This contribution affords an insightful understanding on dead lithium formation with phase field methods, which can contribute general principles on rational design of lithium metal batteries.

Driving lithium to deposit inside structured lithium metal anodes:A phase field model

Lithium metal anode is one of the most important anode materials for next-generation high-specificenergy secondary batteries.Structured lithium metal anodes have received extensive attention in the development of practical lithium metal batteries.Methods of driving lithium metal to deposit inside the pores of structured lithium metal anodes have always been one of the most concerned issues,especially for highly conductive frameworks.An electrochemical phase field theory with galvanostatic lithium plating process is employed in this work,the mechanism that illustrates the preference of lithium metal to deposit at the top of the framework structure has been revealed,and through the simulation analysis of various regulating strategies,the strategies that can efficiently drive lithium to deposit inside structured pores are summarized.This work presents the theoretical calculation and analysis methods that can be used for the rational design of lithium metal batteries.

Evaluation Procedure for Quality Consistency of Generic Nifedipine Extended-Release Tablets Based on the Impurity Profile

A procedure to evaluate the quality consistency of generic drugs based on the impurity profile and the similarity analysis methods was presented in this paper. Nifedipine extended-release tablets from six generic factories of China were used to evaluate the uniformity with the original drug in the study. The procedure includes: choice of chromatographic methods, data collection and conformity test, evaluation of intra-batch similarity of drugs, evaluation of generic drugs with the original drug and weighted similarity evaluation of generic drugs. The data were collected via high-performance liquid chromatography (HPLC), and then calculated by correlation coefficient, cosine, principal component analysis (PCA) and hierarchical clustering analysis (HCA). It is more suitable to use peak areas as the vector when calculating the similarity of impurity profile. After weighting the peak areas of the unspecified impurities in further evaluation of the generic quality, the generic level of different factories was differentiated and the best generic factory was picked out.

Machine Learning-Based Scoring System for Early Prognosis Evaluation of Patients with Coronavirus Disease 2019

Background The global spread of coronavirus disease 2019(COVID-19)continues to threaten human health security,exerting considerable pressure on healthcare systems worldwide.While prognostic models for COVID-19 hospitalized or intensive care patients are currently available,prognostic models developed for large cohorts of thousands of individuals are still lacking.Methods Between February 4 and April 16,2020,we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital,Hubei Province,China.(1)Screening of key prognostic factors:A univariate Cox regression analysis was performed on 2,649 patients in the training set,and factors affecting prognosis were initially screened.Subsequently,a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis.Finally,multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis.(2)Establishment of a scoring system:The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors,calculated the C index,drew calibration curves and drew training set patient survival curves.(3)Verification of the scoring system:The scoring system assessed 1,325 patients in the test set,splitting them into high-and low-risk groups,calculated the C-index,and drew calibration and survival curves.Results The cross-sectional study found that age,clinical classification,sex,pulmonary insufficiency,hypoproteinemia,and four other factors(underlying diseases:blood diseases,malignant tumor;complications:digestive tract bleeding,heart dysfunction)have important significance for the prognosis of the enrolled patients with COVID-19.Herein,we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19.Meanwhile,the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high-and low-risk groups(using a scoring threshold of 117.77,a score below which is considered low risk).The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines(C indexes,0.95 vs.0.89).Conclusions Age,clinical typing,sex,pulmonary insufficiency,hypoproteinemia,and four other factors were important for COVID-19 survival.Compared with general statistical methods,this method can quickly and accurately screen out the relevant factors affecting prognosis,provide an order of importance,and establish a scoring system based on the nomogram model,which is of great clinical significance.