Objective: To systematically evaluate risk factors for cardiometabolic multimorbidity (CMM), so as to provide the evidence for formulating CMM prevention and control strategies. Methods: Publications pertaining to the risk factors for CMM were retrieved from databases, including SinoMed, CNKI, Wanfang Data, VIP, PubMed and Cochrane Library from inception to March 31, 2023. Meta-analysis was performed using the software RevMan 5.4 and Stata 16.0, and sensitivity analysis was performed using the leave-one-out method. The publication bias was evaluated using Egger's test. Results: Totally 494 publications were screened, and 20 publications were included in the final analysis, including 13 cohort studies (covering 1 940 000 participants) and 7 cross-sectional studies (covering 13 000 000 participants). Meta-analysis revealed that female (OR=1.54, 95%CI: 1.40-1.71), middle age (OR=3.80, 95%CI: 3.33-4.34), elderly (OR=2.82, 95%CI: 1.48-5.37), urban resident (OR=1.41, 95%CI: 1.27-1.57), higher education level (OR=2.01, 95%CI: 1.35-3.01), higher economic level (OR=1.21, 95%CI: 1.16-1.25), overweight (OR=1.92, 95%CI: 1.64-2.26), obesity (OR=3.01, 95%CI: 2.30-3.93), central obesity (OR=1.70, 95%CI: 1.12-2.56), smoking (OR=1.27, 95%CI: 1.07-1.51), alcohol consumption (OR=1.27, 95%CI: 1.01-1.59), irregular diet (OR=1.10, 95%CI: 1.02-1.18), insufficient intake of vegetables and fruits (OR=1.12, 95%CI: 1.07-1.17), lack of sleep at night (OR=1.17, 95%CI: 1.08-1.27), and depression (OR=1.50, 95%CI: 1.33-1.69) were risk factors for CMM. Sensitivity analysis of effects of central obesity and alcohol consumption were not robust. No publication bias was examined by Egger's test. Conclusions Female, middle age, elderly, urban resident, higher education level, higher economic level, overweight, obesity, central obesity, smoking, alcohol consumption, irregular diet, insufficient intake of vegetables and fruits, lack of sleep at night and depression are risk factors for CMM.

Objective: To conduct a scoping review on prognostic prediction models for patients with comorbidity of chronic diseases, and understand modeling methods, predictive factors and predictive effect of the models, so as to provide the reference for prognostic evaluation on patients with comorbidity of chronic diseases. Methods: Literature on prognostic prediction models for patients with comorbidity of chronic diseases was collected through SinoMed, CNKI, Wanfang Data, VIP, PubMed, Embase, Cochrane Library and Web of Science published from the time of their establishment to November 1, 2023. The quality of literature was assessed using prediction model risk of bias assessment tool (PROBAST), then modeling methods, predictive factors and predictive effects were reviewed. Results: Totally 2 130 publications were retrieved, and nine publications were finally enrolled, with an overall high risk of bias. Thirteen models were involved, with three established using machine learning methods and ten established using logistic regression. The prediction results of four models were death, with main predictive factors being age, gender, body mass index (BMI), Barthel index and pressure ulcers; the prediction results of nine models were rehospitalization, with main predictive factors being age, BMI, hospitalization frequency, duration of hospital stay and hospitalization costs. Eleven models reported the area under the receiver operating characteristic curve (AUC), ranging from 0.663 to 0.991 6; two models reported the C-index, ranging from 0.64 to 0.70. Eight models performed internal validation, one model performed external validation, and four models did not reported verification methods. Conclusions The prognostic prediction models for patients with comorbidity of chronic diseases are established by logistic regression and machine learning methods with common nursing evaluation indicators, and perform well. Laboratory indicators should be considered to add in the models to further improve the predictive effects.

Educating patients to correctly recognize and fulfill their health ethical responsibilities is an important basis for maintaining individual health, constructing a harmonious doctor-patient relationship, and building a healthy China. By combing the domestic and foreign papers on patient ethical responsibility education, this paper summarized the educational elements of patient ethical responsibility education, including the educational subject, educational object, educational content, and educational path. At present, there are limitations in the research on patient ethical responsibility education both domestically and internationally, such as incomplete theoretical system, insufficient empirical research on the transformation from theory to practice, and the lack of educational effectiveness evaluation tools. It is expected to provide useful reference to improve the theoretical system of patient ethical responsibility for future research on patient ethical responsibility education, explore the path of ethical responsibility education and practice, and formulate effective tools for evaluating the effectiveness of ethical responsibility education, and improve patients’ awareness and performance of ethical responsibility.

Objective: To investigate the effects of oxidized low-density lipoprotein/β2 glycoproteinⅠ/β2 glycoproteinⅠantibody (oxLDL/β2GPⅠ/β2GPⅠ-Ab) complex on the phenotypic transformation and lipid transpoters on the surface of rat thoracic aorta smooth muscle cell line (A7r5), and their correlation with toll-like receptor 4 (TLR4) signaling pathway. Methods: A7r5 cells were stimulated by oxLDL, oxLDL/β2GPⅠ complex, oxLDL/β2GPⅠ-Ab complex, β2GPⅠ/β2GPⅠ-Ab complex and oxLDL/β2GPⅠ/β2GPⅠ-Ab complex respectively, and then total RNA and protein were collected. The expressions of α-smooth muscle actin (α-SMA), macrophage surface marker CD68, galectin-3 (LGALS3), scavenger receptor class B member 3 (CD36) and ATP-binding cassette transporter A1/G1 (ABCA1/ABCG1) were detected by real-time quantitative PCR (RT-qPCR), western blot and immunofluorescence (IF) respectively. The roles of TLR4 and its downstream signaling molecules in the phenotypic transformation and expression changes of lipid transporters of A7r5 cells induced by oxLDL/β2GPⅠ/β2GPⅠ-Ab complex were investigated by the pretreatment of TLR4 blocker TAK-242 (5 μmol/L) or c-Jun N-terminal kinases 1/2 (JNK 1/2) blocker SP600125 (90 nmol/L). Results: The oxLDL/β2GPⅠ/β2GPⅠ-Ab complex significantly increased the levels of CD68 and LGALS3, and decreased the level of α-SMA, while TAK-242 could reverse this phenomenon. The oxLDL/β2GPⅠ/β2GPⅠ-Ab complex could promote the expression of CD36 and inhibit the expression of ABCA1/ABCG1, while TAK-242 and SP600125 could reverse this process. Conclusion The oxLDL/β2GPⅠ/β2GPⅠ-Ab complex promotes the phenotypic transformation of A7r5 cells to macrophage-like cells, regulates the expression of lipid transport-related molecules and enhances the ability of lipids transport into cells. TLR4 and JNK1/2 are closely related to this process.

Objective: To investigate the effects of β2 glycoprotein Ⅰ/anti-β2 glycoprotein Ⅰ complex (β2/aβ2) on oxidized low density lipoprotein (oxLDL)-mediated lipid accumulation and focal adhesion kinase (FAK) activation in THP-1 macrophage, as well as the role of Toll-like receptor 4 (TLR4) during the process. Methods: THP-1 cells were differentiated into THP-1 macrophage by PMA (100 ng/mL). THP-1 macrophages were treated with RPMI 1640 medium, oxLDL, oxLDL+β2/aβ2 or oxLDL+lipopolysaccharide (LPS). The mRNA expressions of lipid transportation molecules, ACAT1, ABCA1 and ABCG1 were detected by RT-qPCR. Intracellular total cholesterol (TC) and free cholesterol (FC) in THP-1 macrophages were evaluated by Trinder assay, then the content and proportion of intracellular cholesteryl ester (CE) were calculated. The expression and phosphorylation of FAK were detected by immune fluorescence, RT-qPCR and western blot. To evaluate the role of TLR4, THP-1 macrophages were pre-treated with or without TLR4 inhibitor TAK-242 (1 μg/mL). Results: β2/aβ2 treatment significantly inhibited oxLDL-mediated lipid accumulation and FAK expression and phosphorylation in THP-1 macrophages, which could be reversed by TLR4 blockage. Conclusion β2/aβ2 inhibits the oxLDL-mediated lipid accumulation and FAK activation of THP-1 macrophage, which is related to the function of TLR4.

Objective: To explore the preliminary application effect of real-time fluorescence recombinase polymerase amplification (RPA) in the detection of Candida albicans. Methods: (1) Candida albicans standard strain and negative control bacteria of Pseudomonas aeruginosa, Staphylococcus aureus, Acinetobacter baumannii, Escherichia coli, Candida glabrata standard strains of respectively 1 mL were collected and their DNA were extracted by yeast/bacterial genomic kit. The specificity of polymerase chain reaction (PCR), real-time fluorescent quantitative PCR, and real-time fluorescence RPA in detecting Candida albicans were analyzed. (2) One Candida albicans standard strain and one negative control bacteria of Candida glabrata standard strain were collected, resuscitated, and counted. Candida albicans was diluted 10 times to 1×10⁷ to 1×10¹ colony-forming unit (CFU)/mL. The DNA of the two bacteria were extracted as experiment (1). The sensitivity of PCR, real-time fluorescent quantitative PCR, and real-time fluorescence RPA in detecting Candida albicans were analyzed. The number of cycles for amplification curve to reach the threshold in real-time fluorescent quantitative PCR, and time of appearance of specific amplification curve in real-time fluorescence RPA were recorded and compared with the results in PCR. The detection limit and rate of the above-mentioned 3 methods in detecting Candida albicans were analyzed, and the correlation between concentration of Candida albicans in real-time fluorescence RPA and detection time was analyzed. (3) One standard strain of Candida albicans was collected, and the DNA was extracted as experiment (1) and detected by PCR, real-time fluorescent quantitative PCR, and real-time fluorescence RPA. The total detection time of the above-mentioned 3 methods was recorded, respectively. (4) The DNA of 31 clinical samples of suspected Candida albicans infection and 1 clinical sample of Candida albicans collected from cotton swab were extracted, PCR and real-time fluorescence RPA were carried out, and the positive detection rates of the above-mentioned methods were calculated. The DNA of the clinical samples with positive results in both PCR and real-time fluorescence RPA were extracted by yeast/bacterial genomic kit, chelex-100 boiling method, and repeatedly freeze-thawing with liquid nitrogen method, and real-time fluorescence RPA and PCR were carried out. The negative control bacteria was Candida glabrata in real-time fluorescence RPA, while negative control bacteria in PCR were the same as experiment (1). The positive results in PCR and real-time fluorescence RPA were observed and time for amplification curve to reach the fluorescence threshold in real-time fluorescence RPA was recorded, respectively. Data were processed with linear correlation analysis and t test. Results: (1) Three methods showed positive results in detecting standard strain of Candida albicans, and none of the 5 negative control bacteria showed positive results. (2) As the concentration of bacterial solution of Candida albicans decreased, the number of cycles for the amplification curve to reach the threshold increased in real-time fluorescent quantitative PCR, the time for appearance of specific amplification curve prolonged in real-time fluorescence RPA, and brightness of the gel strip weakened in PCR. None of the negative control bacteria in the above-mentioned 3 detection methods showed corresponding positive results. The detection limit of Candida albicans in real-time fluorescence RPA, PCR, and real-time fluorescent quantitative PCR was 1×10¹ CFU/mL. There was a significant negative correlation between the concentration of Candida albicans and the detection time in real-time fluorescence RPA (r=-0.95, P<0.01). The positive detection rates of PCR and real-time fluorescent quantitative PCR for Candida albicans of 1×10¹ to 1×10⁷ CFU/mL were 100%. The positive detection rate of real-time fluorescence RPA for Candida albicans of 1×10¹ CFU/mL was 78%, and the positive detection rate of real-time fluorescence RPA for Candida albicans of 1×10² to 1×10⁷ CFU/mL was 100%. (3) The total time of PCR, real-time fluorescent quantitative PCR, and real-time fluorescence RPA detection for Candida albicans was 133, 93, and 35 min, respectively. (4) The positive detection rate of real-time fluorescence RPA for 31 clinical samples of suspected Candida albicans infection was 32.26% (10/31), which was slightly lower than 35.48% (11/31) of PCR. Eleven clinical samples showed positive results both in real-time fluorescence RPA and PCR detection. No positive result was observed in the negative control bacteria detected both by real-time fluorescence RPA and PCR. The DNA was extracted by yeast/bacterial genomic extraction kit and chelex-100 boiling method for real-time fluorescence RPA detection. The time for the amplification curve to reach the threshold was (438±13) and (462±12) s, respectively, which was close (t=1.32, P>0.05). The DNA was extracted by repeatedly freeze-thawing with liquid nitrogen method for real-time fluorescence RPA, and the time for the amplification curve to reach the threshold in real-time fluorescence RPA was (584±15) s, which was significantly longer than that in the other 2 methods (t=7.55, 6.39, P<0.01). Conclusions Real-time fluorescence RPA has advantages of rapid detection, simple operation, high sensitivity, and good specificity in detecting Candida albicans, which is worthy of clinical application.