Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

OBJECTIVE To investigate the clinical efficacy of integrating pharmacists into family health teams （FHTs） for long-term medication therapeutical management （MTM） in stroke patients， and empirically evaluate the service model. METHODS A pharmacist team， jointly established by clinical and community pharmacists from the Affiliated Suzhou Hospital of Nanjing Medical University （hereinafter referred to as “our hospital”）， developed a pharmacist-supported MTM model integrated into FHTs. Using a prospective randomized controlled design， 170 stroke patients discharged from our hospital （July 2022-December 2023） and enrolled in FHTs at Suzhou Runda Community Hospital were randomly divided into trial group （88 cases） and control group （82 cases） according to random number table. The control group received routine FHTs care （without pharmacist involvement in the team collaboration）， while the trial group xhz8405@126.com received 12-month MTM services supported by pharmacists via an information platform. These services specifically included innovative interventions such as personalized medication regimen optimization based on the MTM framework， dynamic medication adherence management， medication safety monitoring， a home medication assessment system， and distinctive service offerings. Outcomes of the 2 grousp were compared before and after intervention， involving medication adherence （adherence rate， adherence score）， compliance rates for stroke recurrence risk factors [blood pressure， low-density lipoprotein cholesterol （LDL-C）]， and incidence of adverse drug reactions （ADR）. RESULTS After 12 months， the trial group exhibited significantly higher medication adherence rates， improved adherence scores， higher compliance rates for blood pressure and LDL-C targets compared to the control group （P＜0.05）. The incidence of ADR in the trial group （4.55%） was significantly lower than that in the control group （8.11%）， though the difference was not statistically significant （P＞ 0.05）. CONCLUSIONS Pharmacist involvement in FHTs to deliver MTM services significantly enhances medication adherence and optimizes risk factor for stroke recurrence， offering practical evidence for advancing pharmaceutical care in chronic disease management under the family doctor system.

BACKGROUND: At present, biopsy is essential for the diagnosis of prostate cancer (PCa) before radical prostatectomy (RP). However, with the development of prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) and multiparametric magnetic resonance imaging (mpMRI), it might be feasible to avoid biopsy before RP. Herein, we aimed to explore the feasibility of avoiding biopsy before RP in patients highly suspected of having PCa after assessment of PSMA PET/CT and mpMRI. METHODS: Between December 2017 and April 2022, 56 patients with maximum standardized uptake value (SUVmax) of ≥4 and Prostate Imaging Reporting and Data System (PI-RADS) ≥4 lesions who received RP without preoperative biopsy were enrolled from two tertiary hospitals. The consistency between clinical and pathological diagnoses was evaluated. Preoperative characteristics were compared among patients with different pathological types, T stages, International Society of Urological Pathology (ISUP) grades, and European Association of Urology (EAU) risk groups. RESULTS: Fifty-five (98%) patients were confirmed with PCa by pathology, including 49 (89%) with clinically significant prostate cancer (csPCa, defined as ISUP grade ≥2 malignancy). One patient was diagnosed with high-grade prostatic intraepithelial neoplasia (HGPIN). CsPCa patients, compared with clinically insignificant prostate cancer (cisPCa) and HGPIN patients, were associated with a higher level of prostate-specific antigen (22.9 ng/mL vs . 10.0 ng/mL, P = 0.032), a lower median prostate volume (32.2 mL vs . 65.0 mL, P = 0.001), and a higher median SUVmax (13.3 vs . 5.6, P <0.001). CONCLUSIONS It might be feasible to avoid biopsy before RP for patients with a high probability of PCa based on PSMA PET/CT and mpMRI. However, the diagnostic efficacy of csPCa with PI-RADS ≥4 and SUVmax of ≥4 is inadequate for performing a procedure such as RP. Further prospective multicenter studies with larger sample sizes are necessary to confirm our perspectives and establish predictive models with PSMA PET/CT and mpMRI.
Humans ; Male ; Prostatectomy/methods* ; Prostatic Neoplasms/diagnosis* ; Middle Aged ; Aged ; Positron Emission Tomography Computed Tomography/methods* ; Biopsy ; Multiparametric Magnetic Resonance Imaging ; Prostate-Specific Antigen/metabolism*

Systemic lupus erythematosus (SLE) is an autoimmune disease accompanied by various complications, and the exact etiology remains unclear. Treatments for SLE encompass hormone therapy, plasma exchange and immunoadsorption, and targeted biological therapies. Berbamine (BBM), a cellular immunopotentiator with diverse biological functions, has not been reported to have immunomodulatory and therapeutic effects on SLE. The mice were divided into control group, model group, positive control group, low, medium and high BBM groups. In control group, C57BL/6J wild mice received intraperitoneal injection of saline. In model group, MRL/lpr lupus mice were treated with intraperitoneal injection of saline. In positive control group, MRL/lpr lupus mice received intragastric administration of hydroxychloroquine sulfate tablets [Plaquenil, 150 mg/(kg·d)]. In BBM groups, MRL/lpr lupus mice received intragastric administration of different concentration of BBM respectively [20 mg/(kg·d), 50 mg/(kg·d), 100 mg/(kg·d)]. After 8 weeks of treatment, blood was collected from the retro-orbital venous plexus, and ELISA was used to detect the levels of anti-double-stranded DNA (dsDNA) antibodies, antinuclear antibodies (ANA), and anti-small nuclear ribonucleoprotein/Sm (snRNP/Sm) antibodies. Spleen tissues were collected for analysis of Th1/Th2 ratio by flow cytometry. The RNA and protein of spleen were extracted, and the levels of T-box transcription factor T-bet and GATA3 (GATA binding protein 3) mRNA and protein were detected by qRT-PCR and Western blot. The proliferation of white blood cells in the blood was tested by blood routine test. The histopathological changes of kidneys of each group were detected by HE staining. Compared with the model group, the levels of ANA, anti-dsDNA, and anti-snRNP/Sm antibodies were significantly reduced in the BBM-treated groups. The Th1/Th2 ratio was significantly decreased in the model group, but reversed by BBM. Compared with the control group, T-bet expression was significantly downregulated, while GATA3 expression was significantly upregulated in the model group. After BBM intervention, T-bet expression significantly increased, while GATA3 expression decreased compared with the model group. The number of white blood cells significantly decreased in the model group, and increased in the BBM-treated groups. In the model group, the glomerular mesangial and endothelial cells showed significant hyperplasia, clear thrombus was observed in the dilated capillaries, and inflammatory cells infiltrated in the renal interstitium. In medium and high BBM groups, the infiltration of inflammatory cells and capillary thrombosis were significantly decreased. In conclusion, BBM exhibits certain immunomodulatory effects on SLE and promotes the proliferation of white blood cells.
Animals ; Lupus Erythematosus, Systemic/immunology* ; Mice ; Mice, Inbred C57BL ; Mice, Inbred MRL lpr ; Female ; Benzylisoquinolines/pharmacology*

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

AIM:The aim of our study is to investigate the metabolic profile differences during cervical lesion progression and evaluate their potential clinical value in assisting the diagnosis of cervical cancer(CC).METHODS:Ul-tra-high-performance liquid chromatography coupled with high-resolution mass spectrometry(UHPLC-HRMS)was em-ployed to conduct non-targeted metabolomic analysis of cervical swab samples from 43 CC patients,34 high-grade squa-mous intraepithelial lesion(HSIL)patients,and 43 healthy controls.Based on the distinct features among the three groups,principal component analysis(PCA)was used to identify the metabolic differences among CC,HSIL and healthy groups.MetaboAnalyst 5.0 was then employed to perform KEGG pathway enrichment analysis on the differential metabo-lites.Finally,random forest machine learning algorithm was used to construct classification prediction models for distin-guishing CC from healthy,HSIL from healthy,and CC from HSIL.The performance of these models was evaluated using receiver operating characteristic(ROC)curve analysis.RESULTS:A total of 1 543 metabolites were identified across the healthy,HSIL and CC groups after filtration,with 407 metabolites differing between the groups.The study found that metabolite PGE2 was present in all three groups,with its expression levels progressively increasing with the progression of cervical lesions.Differential metabolite enrichment analysis demonstrated that CC is associated with specific cancer-relat-ed metabolic pathways,including the tricarboxylic acid cycle,tyrosine metabolism,tryptophan metabolism,and the pen-tose phosphate pathways.Additionally,the study developed three prediction models based on metabolic products for diag-nosing HSIL and CC:the full model,the simplified model,and the PGE2 model.The results indicated that metabolites ex-hibited strong diagnostic efficiency.Both the full model and the simplified model effectively distinguished CC from HSIL,CC from healthy,and HSIL from healthy.The AUC values for the full model were 0.90,0.92 and 0.84,respectively,while those for the simplified model were 0.81,0.95 and 0.85,respectively.Furthermore,the PEG2 model achieved AUC values of 0.74 and 0.80 for distinguishing CC from healthy and HSIL from healthy,respectively.CONCLUSION:The metabolic profiles of cervical cancer exhibit significant differences during the progression of cervical cancer,and these metabolites hold potential clinical value as biomarkers for cervical lesions.

Objective To investigate the predictive value of pulmonary artery(Pa)to aortic(Ao)diameter ratio(Pa/Ao)for long-term major adverse cardiovascular events(MACEs)in patients with acute decompensated heart failure(ADHF).Methods ADHF patients hospitalized in the Department of Cardiology of Nanjing Drum Tower Hospital from January 2018 to January 2023 were consecutively enrolled.The data of gender,age,past medical history,laboratory examination,echocardiography,chest CT and medication were collected.The diameters of Pa and Ao were measured at the bifurcation of main pulmonary artery on chest CT,and Pa/Ao was calculated.The Kaplan-Meier method was used for survival analysis,and the Log-rank test was used to compare the survival rate between the two groups.Cox proportional hazards regression model was used to analyze the association between Pa/Ao and MACEs,and subgroup analysis was performed according to different age,sex,BMI,B-type natriuretic peptide level,and left ventricular ejection fraction.Results A total of 600 ADHF patients were enrolled,with an average age of 69.6 years and 347(57.8%)males.During a median follow-up of 306(127,624)days,327(54.5%)patients experienced MACEs.The ADHF patients were divided into Pa/Ao<0.93 group and Pa/Ao≥0.93 group according to the analysis of maximum selection rank statistics.Kaplan-Meier curve showed that the incidence of MACEs in Pa/Ao≥0.93 group was significantly higher than that in Pa/Ao<0.93 group(PLog-rank<0.001).Multivariate Cox regression analysis showed that Pa/Ao was an independent predictor of MACEs in ADHF patients(HR=11.62,95%CI:4.91～27.50,P<0.001).Subgroup analysis showed that Pa/Ao had predictive value for different ADHF populations(all P<0.05).Conclusion Elevated Pa/Ao is a predictor of long-term MACEs in ADHF patients.

Objective To investigate the differences in oral and gut microbiota composition among children aged 3-5 years with varying body mass index(BMI)levels in Urumqi,and to provide a scientific basis for early microbiological warning and intervention strategies for childhood obesity.Methods A total of 40 children aged 3-5 years were enrolled.Based on their BMI percentiles,the participants were divided into 4 groups,including the underweight,normal weight,overweight,and obesity groups(n=10 per group).A total of 80 saliva and fecal samples were collected.Microbial community structures were analyzed using 16S rRNA gene sequencing,followed by bioinformatics and statistical analyses.Results Oral microbiota richness,as measured by Chao1 and observed-species indices,differed significantly among the four groups(P=0.004 7 and P=0.005 4,respectively),whereas no significant difference in gut microbiota diversity was observed(P>0.05).Beta diversity analysis revealed a distinct separation in oral microbiota between the normal-weight weight and other groups.At the genus level,obese children exhibited increased abundance in oral Leptotrichia,underweight children showed enrichment of gut Bacteroides,and overweight children showed increased abundance in gut Faecalibacterium and Blautia.Linear discriminant analysis effect size(LEfSe)analysis identified multiple biomarkers,including Prevotellaceae in the oral microbiota of normal-weight children,Catonella in the oral microbiota of obese children,and Clostridiales,Lachnospiraceae,and Hungatella in the gut microbiota of underweight children.Metabolic pathways related to lipopolysaccharide synthesis and amino acid metabolism were significantly upregulated in the microbiota of overweight and obese children.Conclusion Significant differences are observed in the oral and gut microbiota composition among children aged 3-5 years of different BMI levels in Urumqi.Oral microbiota show greater sensitivity to BMI changes.Specific genera,such as Catonella,Leptotrichia,and Prevotellaceae,may be involved in the development of obesity.The microbiota metabolic pathways in children with high BMI are characterized by the core features of inflammation activation and lipid metabolism dysregulation.

Objective To explore the risk factors for 28-day mortality of sepsis-associated acute kidney injury(SA-AKI)patients and to develop a nomogram risk prediction model.Methods A retrospective cohort study was conducted,involving 184 patients with SA-AKI admitted to the intensive care unit(ICU)of the 940th Hospital of Joint Logistic Support Force of PLA between January 2017 and December 2022.Patients were categorized into survival(n=135)and non-survival(n=49)groups based on 28-day mortality.Clinical data were collected,and statistically significant risk factors were preliminarily screened.Multivariate stepwise logistic regression analysis was performed to identify independent risk factors for 28-day mortality of SA-AKI patients.A nomogram predictive model was constructed using these factors,and internally validated with the Bootstrap method.The receiver operating characteristic curve(ROC curve)was drawn,and the area under the ROC curve(AUC)was calculated to verify the predictive value and accuracy of the model.Results The 28-day mortality rate among 184 SA-AKI patients was 26.6％(49/184).Multivariate stepwise logistic regression analysis identified multiple organ dysfunction syndrome(MODS)(OR=16.393,95％CI 4.317-62.254,P＜0.001),high acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(OR=1.097,95％CI 1.036-1.161,P=0.002),low oxygenation index(OR=0.992,95％CI 0.986-0.998,P=0.015),low neutrophil count(OR=0.912,95％CI 0.860-0.968,P=0.002)and low fibrinogen concentration(OR=0.733,95％CI 0.549-0.978,P=0.034)as independent risk factors.The prediction model equation was P=1/1+e-logit(P),logit(P)=-1.626+2.797×MODS+0.092×AP ACHE Ⅱ+(-0.311)×fibrinogen+(-0.092)×neutrophil count+(-0.008)×oxygenation index.Internal validation with 1000 Bootstrap resamples showed high consistency between predicted and actual values.ROC analysis showed an AUC of 0.911(95％CI 0.868-0.955,P＜0.05)for the model,with 93.9％sensitivity and 78.5％specificity at a cut-off of 0.194.The Hosmer-Lemeshow test confirmed good calibration(P=0.62),and decision-making curve analysis demonstrated clinical utility within the high-risk threshold range(0.1-0.9).Conclusions MODS,high APACHE Ⅱ score,low oxygenation index,low neutrophil count,and low fibrinogen concentration are independent risk factors for 28-day mortality in SA-AKI patients.The developed nomogram risk prediction model may provide important guidance for predicting 28-day mortality in SA-AKI patients.

Objective To screen metabolic core genes in colon cancer based on machine learning algorithms and analyze their functional mechanisms.Methods Data were obtained from The Cancer Genome Atlas(TCGA)database and the Gene Expression Omnibus(GEO)database.The TCGA co-hort included 375 tumor samples and 32 adjacent normal tissue samples,while the GSE39582 cohort comprised 419 tumor samples.Univariate Cox regression analysis combined with random forest,sup-port vector machine recursive feature elimination(SVM-RFE),and least absolute shrinkage and selec-tion operator(LASSO)regression algorithms were employed to screen for metabolic core genes.Re-ceiver operating characteristic(ROC)curves were plotted,and the area under the curve(AUC)was used to evaluate the predictive efficacy of the core genes.Real-time fluorescent quantitative polymerase chain reaction(qRT-PCR)and immunohistochemistry(IHC)methods were adopted to detect the ex-pression of the core genes.The core genes were knocked down to explore their roles in colon cancer.Results Three core genes,namely CPT2,SCP2 and NR3C2,were screened based on machine learning algorithms.According to the comparison results of the AUCs of the ROC curves,NR3C2 exhibited the best predictive efficacy.qRT-PCR detection results showed that NR3C2 mRNA was lowly ex-pressed in colon cancer cell lines;IHC detection results revealed that NR3C2 was lowly expressed in colon cancer tissues.Knocking down NR3C2 significantly promoted the proliferation and migration of colon cancer cells.Conclusion NR3C2 is identified as a core metabolic inhibitory gene in colon cancer by cross-applying three machine learning algorithms,which may provide a new strategy for metabolic targeted therapy.