Objective : To investigate the antidepressant effects and the underlying mechanisms of tetrahydrocurcumin(THC) and its nanoparticle formulation(THCN). Methods : Forty-six male ICR mice were randomly divided into Con group, LPS group, THC group, THCN group and SER group. A mouse depression model was established by intraperitoneal administration of LPS. The anxiety and depression-like behaviors of mice were evaluated by open field test(OFT) and forced swimming test(FST). Myelin staining was applied to assess the extent of demyelination in the prefrontal cortex of the mice. The prefrontal cortex and hippocampus were further examined for the expression levels of glial fibrillary acidic protein(GFAP) and Toll-like receptor 4(TLR4) through quantitative immunofluorescence assays. Results : Compared with the Con group, the LPS group showed increased anxiety-like and depressive-like behaviors in both the long-term and short-term experiments(P<0.05); the degree of demyelination increased in the LPS group of the long-term experiment(P<0.01); the expression of GFAP was reduced in the LPS group of the short-term experiment(P<0.01), while the expression of TLR4 increased(P<0.05); the expression of TLR4 decreased in the THC group(P<0.01); the expression of GFAP in the prefrontal cortex of the THCN group was reduced(P<0.01), while the expression of TLR4 increased(P<0.05). Compared with the LPS group, the THC group showed reduced depressive-like behaviors in the long-term experiment(P<0.05), while the anxiety-like and depressive-like behaviors of the THCN group and the SER group were reduced(P<0.05), and the anxiety-like and depressive-like behaviors of the THC group and the THCN group were reduced in the short-term experiment(P<0.05); the degree of demyelination was reduced in the THC group, THCN group and SER group in the long-term experiment(P<0.05); the expression of GFAP increased in the THC group of the short-term experiment(P<0.05), while the expression of TLR4 was reduced(P<0.05), and the expression of GFAP increased in the THCN group(P<0.05). Compared with the THC group, the THCN group and the SER group showed reduced anxiety-like behaviors in the long-term experiment(P<0.05); the expression of GFAP in the prefrontal cortex of the THCN group was reduced in the short-term experiment(P<0.05), while the expression of TLR4 in the hippocampal DG area increased in the short-term experiment(P<0.01). Conclusion Tetrahydrocurcumin and its nanoparticle formulation both exert significant ameliorative effects on depression-like behaviors and demyelination in mice induced by lipopolysaccharide. The antidepressant mechanism of THC appears to be mediated through the down-regulation of TLR4 and the up-regulation of GFAP. The mechanism underlying the antidepressant action of THCN seems predominantly focused on the enhancement of GFAP expression.

OBJECTIVE To establish the fingerprints of Tianma jiannao granules （TJG） and the method for content determination to evaluate the quality of TJG comprehensively combined with chemometric analysis. METHODS High-performance liquid chromatography （HPLC） was used to establish the fingerprints of 13 batches （S1-S3） of TJG and determine the contents of inosine， gastrodin， parishin B and parishin E. Cluster analysis， principal component analysis， and orthogonal partial least squares- discriminant analysis were performed using SPSS 20.0 and SIMCA 18 software； using variable importance projection （VIP） value greater than 1 as a criterion， marker components that affected quality were screened. RESULTS A total of 28 common peaks were identified in the 13 batches of TJG with similarities greater than 0.9， and 7 common peaks were identified， which were gastrodin， p-hydroxybenzyl alcohol， parishin B， parishin E， rhynchophylline， inosine and salidroside. The 13 batches of TJG were clustered into 3 categories， S1-S2， S8-S10 and S12 were clustered into one category； S3 and S7 were clustered into one category； S4-S6， S11 and S13 were clustered into one category. VIP of inosine was greater than 1. The contents of inosine， gastrodin， parishin B and parishin E were 62.637-176.677， 17.821-37.642， 5.748-16.077 and 5.660-13.510 μg/g. CONCLUSIONS The established HPLC fingerprints and content determination method are stable， reliable and highly reproducible， which can be used to evaluate the quality of TJG in combination with chemometric analysis. Inosine may be a marker component that affects the quality of TJG. There are differences in the quality of 13 batches of TJG.

Non-muscle myosin heavy chain 9-related disease (MYH9-RD) is an autosomal dominant disease caused by the mutations of the MYH9 gene encoding the non-muscle mysoin heavy chain ⅡA and leads to abnormal accumulation of myosin in cells. These further causes functional disorders of the blood, eye, ear, kidney, and liver systems. MYH9-RD displays heterogeneous kidney involvement and outcomes, but doctors still lack understandings of the mechanism and treatment strategies, owing to difficulty of conducting renal biopsies. Here, we report a case of MYH9-RD with tail fragments heterozygous mutation, which renal pathology is presented as glomerular minor lesion. Moreover, we reviewed related relevant to strengthen clinical diagnosis and understanding of MYH9-RD.

Using the liquid chromatography-tandem mass spectrometry (LC-MS/MS) to determine the plasma level of Lyso-GL3 in patients with Fabry disease and to analyze the clinical application of the method.

BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to find a light-weight,convenient prediction method through machine learning. METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation. RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the five most important features were acuity,arrival transportation,age,shock index,and respiratory rate. CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.

Objective To explore the key active ingredients and action characteristics of Wenxing Jingjintong Gel Patch in the treatment of rheumatoid arthritis(RA)based on the systematic pharmacology and LC-MS/MS technology.Methods The information of active ingredient from Wenxing Jingjintong Gel Patch was established through LC-MS/MS analysis and literature retrieval.The targets of the active ingredients were predicted using Swiss Target Prediction platform and then mapped with the RA-related targets obtained from GeneCards,DrugBank,and OMIM databases to identify the intersecting targets.The"active ingredients-effective targets"network was constructed through the Cytoscape software.The shared targets were imported into STRING database to construct a protein-protein interaction network.GO function and KEGG pathway enrichment analysis were performed using the Metascape database.Molecular docking studies were conducted using AutoDock software to investigate the interactions between key ingredients and target proteins.Results A total of 142 active ingredients were identified in Wenxing Jingjintong Gel Patch by wsing LC-MS/MS,which were further supplemented to 174 through literature retrieval.There were 175 shared targets between the active ingredients and RA.It was anticipated that Wenxing Jingjintong Gel Patch exerted immune regulation and anti-inflammatory and analgesic effects through the interaction between key active ingredients such as berberine,neobavaisoflavone,and palmatine chloride with key targets,including TNF,IL6,and AKT1 to regulate PI3K/Akt1,JAK/STAT,and MAPK signaling pathways.In 1 152 molecular docking validation,94%of them had binding energies less than-5.0 kcal·mol-1,while 51%of them had binding energies less than-7.0 kcal·mol-1.It was indicated that there was a good binding affinity between the potential active ingredients and core targets.Conclusion This study predicted the active ingredients and action characteristics of Wenxing Jingjintong Gel Patch in the treatment of RA,which provided a theoretical basis for further clinical application and quality control.

Objective To prepare a dissolvable microneedle(DMN)with a tip-layer loaded with hyaluronic acid(HA)modified sinomenine hydrochloride liposomes(HA-SMH-Lip),as well as characterize,evaluate its in vitro transdermal permeability,cellular uptake ability,and anti-inflammatory ability.Methods HA-SMH-Lip-DMNs were prepared by a two-step casting method,and the drug loading capacity was determined using HPLC.The morphology,skin permeation properties and in vitro transdermal ability were investigated by scanning electron microscopy,puncture assay and Franz diffusion cell method.Fluorescent microneedles were prepared by replacing HA-SMH-Lip with fluorescein isothiocyanate liposomes(HA-FITC-Lip/FITC-Lip).The uptake behavior of inflammation cells on HA-FITC-Lip-DMNs/FITC-Lip-DMNs was investigated using a flow cytometer and a fluorescence microscope.To evaluate the anti-inflammatory activity of HA-SMH-Lip-DMNs,the levels of inflammatory factors including nitric oxide(NO),tumor necrosis factor α(TNF-α),interleukin 1β(IL-1β),and IL-10 in cell supernatants were measured using an ELISA kit.Results The prepared HA-SMH-Lip-DMNs have uniform shape and size,integral and visually pleasing array,and an average drug loading of(114.01±1.04)μg.Additionally,they have good puncture ability.The results of in vitro transdermal experiments showed that the accumulated amounts of HA-SMH-Lip-DMNs were(101.47±2.91)μg·cm-2 at 36 hours.Its transdermal ability was better than that of the SMH solution group and SMH liposome group.In vitro cellular uptake results indicated that HA-FITC-Lip-DMNs were more effectively taken up by RAW 264.7 cells(P＜0.01).Compared to the model group,HA-SMH-Lip-DMNs group significantly reduced TNF-α,IL-1β,and NO levels while increase IL-10 levels(P＜0.01).Conclusion The prepared HA-SMH-Lip-DMNs have a complete and beautiful morphology with excellent cellular uptake capability,remarkable in vitro transdermal performance,and potent anti-inflammatory properties.HA-SMH-Lip-DMNs are expected to become a new type of transdermal drug delivery system.

Alport syndrome (AS), also known as "eye-ear-kidney syndrome or hereditary nephritis", is a common hereditary disorder. AS is caused by pathogenic mutations of type Ⅳ collagen genes ( COL4α3, COL4α4 and COL4α5), leading to defects in the basement membrane of glomeruli, cochlea, and ocular lens. Patients present with hematuria, proteinuria, and progressive renal failure. With the redefinition of AS and the clinical application of high-throughput sequencing technology, the prevalence of AS may be much higher than the previously recognized. The specific pathogenic mechanism of AS is unknown. Recent studies have showed that type Ⅳ collagen gene mutation may lead to kidney injury by causing abnormal basement membrane components, lipid deposition, energy metabolism disorders, endoplasmic reticulum stress, inflammation and fibrosis. Renin-angiotensin system inhibitor is the main therapy of AS, but the effect is not satisfactory. The new therapeutic strategies mainly include inhibition of abnormal collagen signal transduction, reduction of endoplasmic reticulum stress in podocytes, regulation of energy metabolism, antioxidant stress, anti-inflammation and fibrosis, gene and stem cell therapy. The paper reviewed the research progress on pathogenesis and new therapies of AS.

Objective:To develop an area under curve (AUC)-based nomogram to predict vancomycin-associated nephrotoxicity in critically ill patients.Methods:This retrospective cohort study included adult patients treated with vancomycin in the intensive care unit at a tertiary teaching hospital from January 2015 to December 2017. Baseline clinical characteristics before vancomycin treatment and pharmacokinetic parameters were collected to establish a prediction model of nephrotoxicity. Univariate analysis was used to screen variables, and multivariate logistic regression analysis was used to establish the prediction model and nomogram.Results:A total of 159 patients met the inclusion criteria, sixty-four were included in the final analysis. Sixteen patients (25%, 16/64) developed vancomycin-associated nephrotoxicity. The following variables were incorporated into the prediction model: vancomycin AUC, estimated glomerular filtration rate (GFR), and combined nephrotoxic drugs. The following equation was established to calculate the probability of nephrotoxicity: logit (P)=-4.83+0.009×AUC-2.87×1 (if GFR>60 ml/min)+2.53×1 (if number of combined nephrotoxic drugs≥2). A nomogram was generated based on the equation. The receiver-operating characteristic curve demonstrated that the AUC of the prediction model was 0.927 (95% CI 0.851-1.000). The cut-off value of the probability of nephrotoxicity was 26.48%. The sensitivity and specificity were 87.5% and 87.5% respectively. Conclusion:The incidence of vancomycin-associated nephrotoxicity is high. The AUC-based nomogram can effectively predict vancomycin-associated nephrotoxicity in critically ill patients.

Methods:Two thousand standard sections images werre collected from 2 000 clinical retrospective pediatric hip ultrasound videos from January 2019 to January 2021. All standard sections were annotated by the annotation team through the self-designed software based on Python 3.6 environment for image cross-media data annotation and manual review standardization process with unified standards. Among them, 1 753 were randomly selected for training the deep learning system, and the remaining 247 were used for testing the system. Further, 200 standard sections were randomly selected from the test set, and 8 clinicians independently completed the film reading annotation. The 8 independent results were then compared with the AI results.Results:The testing set consists of 247 patients. Compared with the clinician's measurements, the area under the receiver operating characteristic curve (AUC) of diagnosing hip joint maturity was 0.865, the sensitivity was 76.19%, and the specificity was 96.9%. The AUC of AI system interpretation under Graf detailed typing was 0.575, the sensitivity was 25.90%, the specificity was 89.10%. The 95% LoA of α-angle determined by Bland-Altman method, of -4.7051° to 6.5948° ( Bias -0.94, P<0.001), compared with clinicians' measurements. The 95% LoA of β-angle, of -7.7191 to 6.8777 ( Bias -0.42, P=0.077). Compared with those from 8 clinicians, the results of AI system interpretation were more stable, and the β-angle effect was more prominent. Conclusion:The AI system can quickly and accurately measure the Graf correlation index of standard DDH ultrasonic standard diagnosis plane.