Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.

Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.

Biochemistry,as a fundamental course for science and engineering majors related to biology and chemistry,holds a significant position in the curriculum.The course team at Dalian Minzu University is committed to teaching innovation,adopting the outcome-based education(OBE)concept for teaching de-sign and incorporating ideological and political elements,in order to achieve the dual goals of knowledge transmission and value guidance.The team has established a three-dimensional teaching goal of"knowl-edge,morality,and ability",covering"consolidating core knowledge,cultivating moral sentiment,and enhancing innovation ability".Through a multi-dimensional integrated teaching method of"three integra-tions and five combinations",multiple rounds of teaching practice have been carried out in the applied chemistry major using"classification and specificity of enzyme"as an example.The output of teaching re-sults and survey questionnaires show that students highly recognize the teaching design and its"process-based learning"evaluation method,fully reflecting the student-centered teaching idea.Research has shown that OBE design combined with ideological and political elements can effectively promote students' knowl-edge acquisition,moral growth,and innovation ability improvement in the course of Biochemistry.This teaching design not only helps students construct correct worldviews,outlooks on life,and values,but also significantly enhances their innovative thinking and practical abilities.This teaching design can not only ef-fectively improve the teaching quality of the course,but also provide new perspectives and ideas for the teaching design of Biochemistry,realizing the organic integration of professional knowledge imparting and i-deological and political education,and has certain innovation and practical significance.

Biochemistry,as a fundamental course for science and engineering majors related to biology and chemistry,holds a significant position in the curriculum.The course team at Dalian Minzu University is committed to teaching innovation,adopting the outcome-based education(OBE)concept for teaching de-sign and incorporating ideological and political elements,in order to achieve the dual goals of knowledge transmission and value guidance.The team has established a three-dimensional teaching goal of"knowl-edge,morality,and ability",covering"consolidating core knowledge,cultivating moral sentiment,and enhancing innovation ability".Through a multi-dimensional integrated teaching method of"three integra-tions and five combinations",multiple rounds of teaching practice have been carried out in the applied chemistry major using"classification and specificity of enzyme"as an example.The output of teaching re-sults and survey questionnaires show that students highly recognize the teaching design and its"process-based learning"evaluation method,fully reflecting the student-centered teaching idea.Research has shown that OBE design combined with ideological and political elements can effectively promote students' knowl-edge acquisition,moral growth,and innovation ability improvement in the course of Biochemistry.This teaching design not only helps students construct correct worldviews,outlooks on life,and values,but also significantly enhances their innovative thinking and practical abilities.This teaching design can not only ef-fectively improve the teaching quality of the course,but also provide new perspectives and ideas for the teaching design of Biochemistry,realizing the organic integration of professional knowledge imparting and i-deological and political education,and has certain innovation and practical significance.

Colorimetric analysis is a detection and quantification method based on observable color changes in response to analytes,which offers significant advantages including visually detectable signals,straightforward operation,rapid response,and low cost.Consequently,it plays a crucial role in a variety of fields.With increasingly diverse and complex application,colorimetric analysis requires continuous improvement in sensitivity,adaptability to diverse detection environments,and complex data handling capabilities.In recent years,the development of artificial intelligence technology,particularly within its core domain of machine learning(ML),has led to significant advancements in colorimetric analysis.The ML-assisted colorimetric analysis enables high-throughput and high-sensitivity detection,alongside automated analysis,thereby providing novel strategies to overcome the inherent limitations.This review categorized machine learning techniques and summarized their application in colorimetric analysis,introducing two fundamental categories of supervised learning,and unsupervised learning based on the division of core learning paradigms.The research progress of ML-assisted colorimetric analysis in the fields of environmental monitoring,biochemical detection,and food safety were summarized.Finally,the current challenges facing by this research area were analyzed and the research prospect of ML-assisted colorimetric analysis was outlined.

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

Oligodendrocyte lineage cells, including oligodendrocyte precursor cells (OPCs) and oligodendrocytes (OLs), are essential in establishing and maintaining brain circuits. Autophagy is a conserved process that keeps the quality of organelles and proteostasis. The role of autophagy in oligodendrocyte lineage cells remains unclear. The present study shows that autophagy is required to maintain the number of OPCs/OLs and myelin integrity during brain aging. Inactivation of autophagy in oligodendrocyte lineage cells increases the number of OPCs/OLs in the developing brain while exaggerating the loss of OPCs/OLs with brain aging. Inactivation of autophagy in oligodendrocyte lineage cells impairs the turnover of myelin basic protein (MBP). It causes MBP to accumulate in the cytoplasm as multimeric aggregates and fails to be incorporated into integral myelin, which is associated with attenuated endocytic recycling. Inactivation of autophagy in oligodendrocyte lineage cells impairs myelin integrity and causes demyelination. Thus, this study shows autophagy is required to maintain myelin quality during aging by controlling the turnover of myelin components.
Animals ; Autophagy/physiology* ; Oligodendroglia/metabolism* ; Myelin Sheath/physiology* ; Aging/pathology* ; Myelin Basic Protein/metabolism* ; Cell Lineage/physiology* ; Mice ; Oligodendrocyte Precursor Cells ; Mice, Inbred C57BL ; Brain/cytology* ; Cells, Cultured ; Cell Count

BACKGROUND: Stress cardiomyopathy (SCM) currently has a high incidence in older adults, and the theories regarding its causes include "catecholamine myocardial toxicity" and "sympathetic hyperactivation". However, the role of the central nervous system in the pathogenesis of SCM remains unknown. We investigated the role of microglia activation in the paraventricular hypothalamic nucleus (PVN) in the development of SCM. METHODS: An SCM model was created using male Sprague-Dawley (SD) rats, immobilized for 6 h every day for a week. Electrocardiogram, cardiac electrophysiology, and echocardiography examinations were performed to verify the changes in cardiac structure and function in rats with SCM. RNA sequencing was used to explore the changes in the hypothalamus during SCM. In addition, brain and heart tissues were collected to detect microglial activation and sympathetic activity. RESULTS: The main findings were as follows: (1) immobilization stress successfully induced SCM in SD rats; (2) microglia were significantly activated in the hypothalamus, as evidenced by cytosol thickening, increases in the number of microglial branches, and microglia enriched in the PVN; (3) in SCM, the microglia in the PVN exhibited increased central and peripheral cardiac sympathetic activity and increased the expression of neuroinflammatory factors; and (4) it is possible that inhibiting microglial activation could suppress the sympathetic activity of the central nervous system and heart and increase cardiac electrical stability in SCM rats. CONCLUSIONS SCM was induced in SD rats by immobilization stress, acting through the activation of the hypothalamic microglia. The activated microglia were specifically enriched in the PVN, increasing the activity of the central and peripheral sympathetic nervous systems by regulating the expression of neuro-inflammatory factors, mediating dysfunction of the left ventricle, and increasing the susceptibility to ventricular arrhythmias.

Objective: Compare and analyze the results of the domestic Lanyi AH600 glycated hemoglobin analyzer and other different detection systems to understand the comparability of the detection results of different detectors, and establish the best cut point of Lanyi AH600 determination of haemoglobin A1c (HbA1c) in the diagnosis of diabetes. Methods: Multi center cohort study was adopted. The clinical laboratory departments of 18 medical institutions independently collected test samples from their respective hospitals from March to April 2022, and independently completed comparative analysis of the evaluated instrument (Lanyi AH600) and the reference instrument HbA1c. The reference instruments include four different brands of glycosylated hemoglobin meters, including Arkray, Bio-Rad, DOSOH, and Huizhong. Scatter plot was used to calculate the correlation between the results of different detection systems, and the regression equation was calculated. The consistency analysis between the results of different detection systems was evaluated by Bland Altman method. Consistency judgment principles: (1) When the 95% limits of agreement (95% LoA) of the measurement difference was within 0.4% HbA1c and the measurement score was≥80 points, the comparison consistency was good; (2) When the measurement difference of 95% LoA exceeded 0.4% HbA1c, and the measurement score was≥80 points, the comparison consistency was relatively good; (3) The measurement score was less than 80 points, the comparison consistency was poor. The difference between the results of different detection systems was tested by paired sample T test or Wilcoxon paired sign rank sum test; The best cut-off point of diabetes was analyzed by receiver operating characteristic curve (ROC). Results: The correlation coefficient R² of results between Lanyi AH600 and the reference instrument in 16 hospitals is≥0.99; The Bland Altman consistency analysis showed that the difference of 95% LoA in Nanjing Maternity and Child Health Care Hospital in Jiangsu Province (reference instrument: Arkray HA8180) was -0.486%-0.325%, and the measurement score was 94.6 points (473/500); The difference of 95% LoA in the Tibetan Traditional Medical Hospital of TAR (reference instrument: Bio-Rad Variant II) was -0.727%-0.612%, and the measurement score was 89.8 points; The difference of 95% LoA in the People's Hospital of Chongqing Liang Jiang New Area (reference instrument: Huizhong MQ-2000PT) was -0.231%-0.461%, and the measurement score was 96.6 points; The difference of 95% LoA in the Taihe Hospital of traditional Chinese Medicine in Anhui Province (reference instrument: Huizhong MQ-2000PT) was -0.469%-0.479%, and the measurement score was 91.9 points. The other 14 hospitals, Lanyi AH600, were compared with 4 reference instrument brands, the difference of 95% LoA was less than 0.4% HbA1c, and the scores were all greater than 95 points. The results of paired sample T test or Wilcoxon paired sign rank sum test showed that there was no statistically significant difference between Lanyi AH600 and the reference instrument Arkray HA8180 (Z=1.665,P=0.096), with no statistical difference. The mean difference between the measured values of the two instruments was 0.004%. The comparison data of Lanyi AH600 and the reference instrument of all other institutions had significant differences (all P<0.001), however, it was necessary to consider whether it was within the clinical acceptable range in combination with the results of the Bland-Altman consistency analysis. The ROC curve of HbA1c detected by Lanyi AH600 in 985 patients with diabetes and 3 423 patients with non-diabetes was analyzed, the area under curve (AUC) was 0.877, the standard error was 0.007, and the 95% confidence interval 95%CI was (0.864, 0.891), which was statistically significant (P<0.001). The maximum value of Youden index was 0.634, and the corresponding HbA1c cut point was 6.235%. The sensitivity and specificity of diabetes diagnosis were 76.2% and 87.2%, respectively. Conclusion: Among the hospitals and instruments currently included in this study, among these four hospitals included Nanjing Maternity and Child Health Care Hospital in Jiangsu Province (reference instrument: Arkray HA8180), Tibetan Traditional Medical Hospital of TAR (reference instrument: Bio-Rad Variant Ⅱ), the People's Hospital of Chongqing Liang Jiang New Area (reference instrument: Huizhong MQ-2000PT), and the Taihe Hospital of traditional Chinese Medicine in Anhui Province (reference instrument: Huizhong MQ-2000PT), the comparison between Lanyi AH600 and the reference instruments showed relatively good consistency, while the other 14 hospitals involved four different brands of reference instruments: Arkray, Bio-Rad, DOSOH, and Huizhong, Lanyi AH600 had good consistency with its comparison. The best cut point of the domestic Lanyi AH600 for detecting HbA1c in the diagnosis of diabetes is 6.235%.
Pregnancy ; Child ; Humans ; Female ; Glycated Hemoglobin ; Cohort Studies ; Diabetes Mellitus/diagnosis* ; Sensitivity and Specificity ; ROC Curve