Multimorbidity has become a widely recognized public health problem worldwide. Identifying multimorbidity patterns can improve not only the efficiency of healthcare resource utilization but also patients' prognosis. This article summarizes three common approaches for the identification of multimorbidity patterns: association analysis methods (including association rule mining and network analysis), classification methods (including cluster analysis, latent class analysis, and latent transition analysis), and dimensionality reduction and feature extraction methods (including principal component analysis, factor analysis, and multiple correspondence analysis), introduces the application of these methods using data from the UK Biobank to identify multimorbidity patterns and discusses and compares the results of case analysis to provide reference for the selection of appropriate methods for multimorbidity pattern research.

Various methods for cancer biomarker detection have been developed to realize cancer early diagnosis, precise treatment, and prognosis evaluation. Traditional techniques such as ELISA (enzyme-linked immunosorbent assay)have been widely applied worldwide, but face challenges in standardized wide application due to molecular-level limitations, sensitivity, and application scope. In 2014, the ultra-sensitive Simoa (Single Molecule Array) technology was introduced, breaking through the shortcomings of small-molecule detection. Simoa enables highly efficient detection and quantitative analysis of biomarkers across multiple fields, providing new insights into cancer biomarker tests. Simoa demonstrates significant advantages in biomarker detection and clinical application, with a wide clinical application prospect in the diagnosis and treatment of lung cancer, breast cancer and other cancers, and provides a theoretical basis for the construction of cancer prediction model.

Multimorbidity has become a widely recognized public health problem worldwide. Identifying multimorbidity patterns can improve not only the efficiency of healthcare resource utilization but also patients' prognosis. This article summarizes three common approaches for the identification of multimorbidity patterns: association analysis methods (including association rule mining and network analysis), classification methods (including cluster analysis, latent class analysis, and latent transition analysis), and dimensionality reduction and feature extraction methods (including principal component analysis, factor analysis, and multiple correspondence analysis), introduces the application of these methods using data from the UK Biobank to identify multimorbidity patterns and discusses and compares the results of case analysis to provide reference for the selection of appropriate methods for multimorbidity pattern research.

Various methods for cancer biomarker detection have been developed to realize cancer early diagnosis, precise treatment, and prognosis evaluation. Traditional techniques such as ELISA (enzyme-linked immunosorbent assay)have been widely applied worldwide, but face challenges in standardized wide application due to molecular-level limitations, sensitivity, and application scope. In 2014, the ultra-sensitive Simoa (Single Molecule Array) technology was introduced, breaking through the shortcomings of small-molecule detection. Simoa enables highly efficient detection and quantitative analysis of biomarkers across multiple fields, providing new insights into cancer biomarker tests. Simoa demonstrates significant advantages in biomarker detection and clinical application, with a wide clinical application prospect in the diagnosis and treatment of lung cancer, breast cancer and other cancers, and provides a theoretical basis for the construction of cancer prediction model.

Objective:To investigate the incidence of venous thromboembolism (VTE) in patients with esophageal cancer (EC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 8 458 EC patients who were admitted to Sichuan Cancer Hospital from January 2017 to December 2021 were collected. There were 6 923 males and 1 535 females, aged (64±9)years. There were 3 187 patients undergoing surgical treatment, and 5 271 cases undergoing non-surgical treatment. Observation indicators: (1) incidence of VTE in EC patients; (2) treatment and outcomes of patients with VTE. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was analyzed using the t test. Measurement data with skewed distribution were represented as M(range), and comparison between groups was analyzed using the nonparameter rank sum test. Count data were expressed as absolute numbers or percentages, and comparison between groups was analyzed using the chi-square test or Fisher exact probability. Comparison of ordinal data was analyzed using the nonparameter rank sum test. Results:(1) Incidence of VTE in EC patients. Of 8 458 EC patients, 175 cases developed VTE, with an incidence rate of 2.069%(175/8 458). Among 175 VTE patients, there were 164 cases of deep venous thrombosis (DVT), 4 cases of pulmonary embolism (PE), 7 cases of DVT and PE. There were 59 surgical patients and 116 non-surgical patients. There was no significant difference in thrombus type between surgical and non-surgical EC patients with VTE ( χ2=1.95, P>0.05). Of 3 187 surgical patients, the incidence of VTE was 1.851%(59/3 187), including an incidence of 0.157%(5/3 187) of PE. PE accounted for 8.475%(5/59) of surgical patients with VTE. Of 5 271 non-surgical patients, the incidence of VTE was 2.201%(116/5 271), including an incidence of 0.114%(6/5 271) of PE. PE accounted for 5.172%(6/116) of non-surgical patients with VTE. There was no significant difference in the incidence of VTE or PE between surgical patients and non-surgical patients ( χ2=1.20, 0.05, P>0.05). (2) Treatment and outcomes of patients with VTE. Among 175 EC patients with VTE, 163 cases underwent drug treatment, and 12 cases did not receive treatment. Among 163 cases with drug therapy, 158 cases underwent anticoagulant therapy, 5 cases were treated with thrombolysis. All the 163 patients were improved and discharged from hospital. Conclusions:The incidence of VTE in patients with EC is relatively low, as 2.069%. There is no significant difference in the incidence of VTE or thrombus type between surgical EC patients and non-surgical EC patients.

Objective To investigate the protective effect of complement 5a receptor 1 (C5aR1) antagonist on ascending urinary tract infection in mice.Methods (1) Female C57BL/6 mice were randomly divided into experimental and control groups:38 mice in each group,and inoculated with E.coli by urethral catheterization to set up the ascending urinary tract infection model.C5aR1 antagonist (W54011 or PMX53) and corresponding control (PBS or control peptide) were initially given either at 2 h before or 3 h after infection by intraperitoneal injection.Mice were sacrificed to assess the infection in bladder and kidney at 24 or 48 h after infection.The bacterial load of bladder and kidney tissue was measured by agar plate assay.The mRNA expression of renal inflammatory factors was detected by real-time RCR.The renal tissue injury and inflammatory cell infiltration were assessed by HE staining and pathological scores.(2) Primary cultured renal tubular epithelial cells were randomly divided into antagonist and control groups to detect and compare the bacterial adhesion to renal tubular epithelial cells in vitro.Results Compared with control groups,the initial delivery of C5aR1 antagonist (W54011 or PMX53) before E.coli inoculation reduced the bacterial load in bladder and kidney tissue 48 h after infection (all P ＜ 0.01).In experimental group given W54011 before infection,the renal pathological scores were reduced (both P ＜ 0.05),as well as renal inflammatory factor expressions:CXCL-1 mRNA,IL-6 mRNA and TNF-o mRNA (all P ＜ 0.05).Compared with corresponding control groups,the initial delivery of PMX53 after E.coli inoculation could also reduce the bacterial load in bladder and kidney tissue 48 h after infection (both P ＜ 0.01).Furthermore,C5aR1 antagonists W54011 and PMX53 could decrease bacteria adhesion to renal tubular epithelial cells in vitro,compared with control groups (both P ＜ 0.05).Conclusions C5aR1 antagonists can significantly attenuate renal tissue injury,ameliorate renal inflammation and the adhesion of bacteria to renal epithelial cells.C5aR1 may be an effective target for the prevention and treatment of urinary tract infection.

A spectrophotometric method for the determination of trace amounts of mercury (Ⅱ ) was described based on the formation of a complicated ion-association complex of Hg (Ⅱ )-Ⅰ-Rhodamine B in ihe presence of polyvinyl alcohol. The maximum absorption of the ion-association complex was at 595nm, Beer's law was obeyed for mercury (Ⅱ ) in the range of 0~5?g/25ml. The apparent molar absorptivity was 7. 36 ?105L/mol?cm. The recovery of mercury was 97. 0% ~ 103. 0%,RSD