Objective:To analyze the application value of three-dimensional visualization combined with indocyanine green fluorescence staining in laparoscopic resection of patients with complex liver cancer.Methods:The data of patients with complex liver cancer (liver cancer located in liver segments Ⅶ, Ⅷ, Ⅳa, Ⅴ and caudate lobe) who underwent laparoscopic anatomical liver resection in Zhengzhou University People's Hospital from August 2018 to August 2023 were retrospectively analyzed. A total of 334 patients were enrolled, including 249 males and 85 females, with the age of (57.0±10.6) years. Among the 334 patients, patients who underwent laparoscopic liver resection using three-dimensional visualization combined with indocyanine green fluorescence staining were included in the combined group ( n=128), and the other patients who underwent traditional laparoscopic liver resection were included in the traditional group ( n=206). Propensity score was used to match the preoperative indicators and postoperative pathology between the two groups. The two groups were compared in terms of gender, age, maximum diameter of tumor, alpha-fetoprotein, number of tumors, tumor location, American Society of Anesthesiologists (ASA) grade, operation time, portal occlusion time, intraoperative blood loss, surgical margin and postoperative aspartate transaminase (ALT), alanine transaminase (AST), albumin, total bilirubin, and severe postoperative complications (Clavien-Dindo grade≥grade Ⅲ). The Kaplan-Meier method was used to analyze the prognosis, and the log-rank test was used to compare the survival rate. Results:After propensity score matching, 120 cases were included in the combined group and the traditional group, respectively. There were no significant differences in gender, age, maximum diameter of tumor, alpha-fetoprotein, number of tumors, tumor location, and ASA grade between the two groups (all P>0.05). The intraoperative blood loss in the combined group was 200.0 (150.0, 300.0) ml, and the positive surgical margin rate was 6.7% (8/120), which were lower than 300.0 (150.0, 500.0) ml and 15.8% (19/120) in the traditional group, with statistically significant differences ( Z=-2.43, P=0.015, χ2=5.05, P=0.025). There were no statistically significant differences in the operation time, portal occlusion time, and postoperative ALT, AST, albumin, and total bilirubin between the two groups (all P>0.05). Eight cases (6.7%) in the combined group and 11 cases (9.2%) in the traditional group had severe complications after surgery, and all were discharged after treatment. The 1-, 3-, and 5-year recurrence-free survival rates of the combined group were 83.3%, 61.7%, and 58.3% respectively, while that of the traditional group were 71.7%, 52.5%, and 49.2%, respectively, with significant difference ( χ2=4.57, P=0.031). There was no significant difference in the cumulative survival rate between the combined group and the traditional group ( χ2=0.66, P=0.417). Conclusion:Compared with laparoscopic liver resection, laparoscopic liver resection for patients with complex liver cancer using three-dimensional visualization technology combined with indocyanine green fluorescence staining technology can reduce intraoperative blood loss, positive margin rate, and postoperative recurrence.

Objective:To analyze the application value of three-dimensional visualization combined with indocyanine green fluorescence staining in laparoscopic resection of patients with complex liver cancer.Methods:The data of patients with complex liver cancer (liver cancer located in liver segments Ⅶ, Ⅷ, Ⅳa, Ⅴ and caudate lobe) who underwent laparoscopic anatomical liver resection in Zhengzhou University People's Hospital from August 2018 to August 2023 were retrospectively analyzed. A total of 334 patients were enrolled, including 249 males and 85 females, with the age of (57.0±10.6) years. Among the 334 patients, patients who underwent laparoscopic liver resection using three-dimensional visualization combined with indocyanine green fluorescence staining were included in the combined group ( n=128), and the other patients who underwent traditional laparoscopic liver resection were included in the traditional group ( n=206). Propensity score was used to match the preoperative indicators and postoperative pathology between the two groups. The two groups were compared in terms of gender, age, maximum diameter of tumor, alpha-fetoprotein, number of tumors, tumor location, American Society of Anesthesiologists (ASA) grade, operation time, portal occlusion time, intraoperative blood loss, surgical margin and postoperative aspartate transaminase (ALT), alanine transaminase (AST), albumin, total bilirubin, and severe postoperative complications (Clavien-Dindo grade≥grade Ⅲ). The Kaplan-Meier method was used to analyze the prognosis, and the log-rank test was used to compare the survival rate. Results:After propensity score matching, 120 cases were included in the combined group and the traditional group, respectively. There were no significant differences in gender, age, maximum diameter of tumor, alpha-fetoprotein, number of tumors, tumor location, and ASA grade between the two groups (all P>0.05). The intraoperative blood loss in the combined group was 200.0 (150.0, 300.0) ml, and the positive surgical margin rate was 6.7% (8/120), which were lower than 300.0 (150.0, 500.0) ml and 15.8% (19/120) in the traditional group, with statistically significant differences ( Z=-2.43, P=0.015, χ2=5.05, P=0.025). There were no statistically significant differences in the operation time, portal occlusion time, and postoperative ALT, AST, albumin, and total bilirubin between the two groups (all P>0.05). Eight cases (6.7%) in the combined group and 11 cases (9.2%) in the traditional group had severe complications after surgery, and all were discharged after treatment. The 1-, 3-, and 5-year recurrence-free survival rates of the combined group were 83.3%, 61.7%, and 58.3% respectively, while that of the traditional group were 71.7%, 52.5%, and 49.2%, respectively, with significant difference ( χ2=4.57, P=0.031). There was no significant difference in the cumulative survival rate between the combined group and the traditional group ( χ2=0.66, P=0.417). Conclusion:Compared with laparoscopic liver resection, laparoscopic liver resection for patients with complex liver cancer using three-dimensional visualization technology combined with indocyanine green fluorescence staining technology can reduce intraoperative blood loss, positive margin rate, and postoperative recurrence.

[Objective]To investigate the regulatory effect and potential mechanisms of isocitrate dehydrogenase 3A(IDH3A)on cardiomyocyte hypertrophy.[Methods]The expression of IDH3A in the myocardium of healthy volunteers(n=10)and patients with heart failure(HF)(n=10),and in the myocardium of mice subjected to transverse aortic constriction(TAC)surgery and sham operation,as well as in phenylephrine(PE)-induced neonatal rat ventricular cardiomyocytes(NRVCs),was assessed by real-time quantitative polymerase chain reaction(RT-qPCR)and Western blot assay.The effect of adenovirus-mediated overexpression of IDH3A on the expression of hypertrophy-related genes in PE-induced NRVCs was also evaluated.The effect of IDH3A on NRVCs area was examined by phalloidin staining assay.A mutant of IDH3A with abolished enzymatic activity,IDH3A_D208A,was generated through site-directed mutagenesis.The impact of this IDH3A mutant on the hypertrophic phenotype,ATP and ROS levels in NRVCs was evaluated to investigate whether the regulatory role of IDH3A in cardiomyocyte hypertrophy was dependent on its enzymatic activity.The effect of exogenous α-ketoglutaric acid(AKG)on cardiomyocyte hypertrophy was also detected by Western blot and phalloidin staining assay,respectively.[Results]IDH3A was significantly decreased in the myocardium of HF patients,in the myocardium of TAC-operated mice,and in PE-induced NRVCs(P=0.005 2,P=0.026 6,P=0.041 3 and P=0.006 6,respectively).Overexpression of IDH3A markedly suppressed the expression of hypertrophy-related genes and the increase of cell size of PE-induced NRVCs(P<0.000 1,P=0.000 1 and P=0.000 2,respectively).The ATP and ROS analysis indicated that IDH3A inhibited the increases of ATP and ROS levels in PE-induced NRVCs(P=0.001 2 and P<0.000 1,respectively),whereas the enzymatically inactive IDH3A mutant lacked this effect.Exogenous AKG provision could,but overexpression of IDH3A mutant failed to suppress PE-induced NRVCs hypertrophy.[Conclusion]IDH3A inhibits cardiomyocyte hypertrophy via elevating AKG level,providing scientific evidence for study on IDH3A-based treatment of cardiac hypertrophy.

Objective To systematic evaluate the impact of applying the clinical nursing pathway(CNP)on epidural anesthetic analgesia natural delivery.Methods The randomized controlled trial(RCT)and quasi-experimental researches on the application of CNP in epidural anesthetic analgesia natural delivery were retrieved from PubMed,Cochrane Library,Embase,Web of Science,China Knowledge Network database,Wanfang database,VIP and the Chinese Biomedical Literature Database.The retrieval time limit was from January 1,2014,to July 31,2024 with no language limitation.The meta analysis on the included studies was performed by applying RevMan5.4.1.Results A total of 5 RCTs and 2 quasi-experimental studies were in-cluded,involving 979 parturients with deliveries.The meta analysis showed that compared with the conven-tional nursing,CNP could shorten the duration of the first stage of labor(MD=—1.06,95％CI:—1.95——0.17,P=0.02)and the duration of the second stage of labor(MD=—0.12,95％CI:—0.21——0.03,P=0.006);decreased the rate of perineal lateral incision(RR=0.73,95％CI:0.65-0.83,P＜0.001)and inci-dence rate of postpartum urinary retention(RR=0.35,95％CI:0.20-0.63,P＜0.001);and shortened the time to lactation initiation(SMD=—1.52,95％CI:—2.38——0.66,P＜0.001).There was no influence on reducing postpartum 24 h hemorrhage amount(SMD=—0.51,95％CI:—1.23-0.21,P=0.16).The study subjects were divided into the primipara women subgroup and unclassified parturients subgroup.Compared with the conventional nursing group,compared with the conventional nursing,CNP had no impact on the dura-tion of the first stage of labor(MD=—0.32,95％CI:—0.61-0.98,P=0.63)and the duration of the second stage of labor(MD=—0.11,95％CI:—0.25-0.04,P=0.15)in the primipara women subgroup.CNP could reduce the postpartum 24 h hemorrhage volume in the unclassified parturients subgroup(SMD=—1.47,95％CI:—1.72——1.21,P＜0.001).Conclusion Application of CNP in parturients labor analgesia could reduce the perineal lateral incision rate and incidence rate of postpartum urinary retention and shorten the time to lac-tation initiation.Due to the heterogeneity among studies,the impact of CNP on the labor duration and the bleeding amount within postpartum 24 h still requires more high-quality studies to be conducted in the future for verification.

Objective:To analyze the risk factors for clinically relevant delayed gastric emptying (CR-DGE) following laparoscopic pancreaticoduodenectomy (LPD) and to develop a model to predict the postoperative CR-DGE after LPD using the machine-learning approach with multi-model comparison.Methods:Clinical data of 278 patients with tumors located in the pancreatic head and periampullary region undergoing LPD at People’s Hospital of Zhengzhou University from January 2019 to December 2023 were retrospectively analyzed, including 167 males and 111 females, aged 59 (53, 66) years. According to the occurrence of DGE, patients were divided into the CR-DGE group ( n=94) and the non-CR-DGE group ( n=184). Main clinical characteristics were compared between the groups, including pancreatic duct diameter, intraoperative blood loss and operative time. The perioperative indicators were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. Following variable selection, 278 patients were allocated into a training set ( n=222) and a validation set ( n=56) in an 8∶2 ratio. Eight machine learning models were selected to model the training set: random forest, adaptive boosting, light gradient boosting, multilayer perceptron, support vector machine, K-nearest neighbor algorithm, decision tree and complementary set plain bayes. The area under the curve (AUC) of receiver operating characteristic curve of the validation set was utilized to identify the optimal model. The predictive performance of the optimal model was evaluated using calibration plots and decision curve analysis (DCA). The contribution of each feature to the prediction is assessed using Shapley additive explanation (SHAP). Results:Univariate analysis showed statistically significant differences between the CR-DGE and non-CR-DGE groups in terms of age [66(62, 69) years vs. 56(51, 60), years], diabetes [42.6%(40/94) vs. 11.4%(21/184)], level of fibrinogen [3.43(2.74, 4.18) g/L vs. 3.84(3.19, 4.68) g/L], pancreatic duct diameter [2.00(1.50, 2.70) mm vs. 3.40(1.60, 5.00) mm], intraoperative blood loss [300(200, 600) ml vs. 200(150, 300) ml], operative time [472(430, 502) min vs. 430(365, 475) min], clinically relevant postoperative pancreatic fistula [34.0%(32/94) vs. 3.8%(7/184)], abdominal fluid accumulation [46.8%(44/94) vs. 12.5%(23/184)], postoperative hemorrhage [20.2%(19/94) vs. 3.3%(6/184)], abdominal infection [28.7%(27/94) vs. 11.4% (21/184)] and duration of postoperative gastrointestinal decompression [4.00 (2.00, 6.00) d vs. 3.00 (2.00, 5.00) d] (all P<0.05). The eleven variables selected via LASSO were incorporated into each of the eight machine learning models. Results demonstrated that the random forest model achieved the highest performance in the validation set, with an AUC of 0.894 (95% CI: 0.800-0.985), accuracy of 0.820 and sensitivity of 0.606. Calibration plots and DCA confirmed the robustness of the random forest model. SHAP analysis indicated that age, pancreatic duct diameter and preoperative aspartate aminotransferase were important predictors in the random forest model. Conclusion:The random forest model developed in this study demonstrated a good predictive performance for CR-DGE after LPD and may assist in the early identification of high-risk patients in clinical practice.

Objective:To analyze the risk factors for clinically relevant delayed gastric emptying (CR-DGE) following laparoscopic pancreaticoduodenectomy (LPD) and to develop a model to predict the postoperative CR-DGE after LPD using the machine-learning approach with multi-model comparison.Methods:Clinical data of 278 patients with tumors located in the pancreatic head and periampullary region undergoing LPD at People’s Hospital of Zhengzhou University from January 2019 to December 2023 were retrospectively analyzed, including 167 males and 111 females, aged 59 (53, 66) years. According to the occurrence of DGE, patients were divided into the CR-DGE group ( n=94) and the non-CR-DGE group ( n=184). Main clinical characteristics were compared between the groups, including pancreatic duct diameter, intraoperative blood loss and operative time. The perioperative indicators were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. Following variable selection, 278 patients were allocated into a training set ( n=222) and a validation set ( n=56) in an 8∶2 ratio. Eight machine learning models were selected to model the training set: random forest, adaptive boosting, light gradient boosting, multilayer perceptron, support vector machine, K-nearest neighbor algorithm, decision tree and complementary set plain bayes. The area under the curve (AUC) of receiver operating characteristic curve of the validation set was utilized to identify the optimal model. The predictive performance of the optimal model was evaluated using calibration plots and decision curve analysis (DCA). The contribution of each feature to the prediction is assessed using Shapley additive explanation (SHAP). Results:Univariate analysis showed statistically significant differences between the CR-DGE and non-CR-DGE groups in terms of age [66(62, 69) years vs. 56(51, 60), years], diabetes [42.6%(40/94) vs. 11.4%(21/184)], level of fibrinogen [3.43(2.74, 4.18) g/L vs. 3.84(3.19, 4.68) g/L], pancreatic duct diameter [2.00(1.50, 2.70) mm vs. 3.40(1.60, 5.00) mm], intraoperative blood loss [300(200, 600) ml vs. 200(150, 300) ml], operative time [472(430, 502) min vs. 430(365, 475) min], clinically relevant postoperative pancreatic fistula [34.0%(32/94) vs. 3.8%(7/184)], abdominal fluid accumulation [46.8%(44/94) vs. 12.5%(23/184)], postoperative hemorrhage [20.2%(19/94) vs. 3.3%(6/184)], abdominal infection [28.7%(27/94) vs. 11.4% (21/184)] and duration of postoperative gastrointestinal decompression [4.00 (2.00, 6.00) d vs. 3.00 (2.00, 5.00) d] (all P<0.05). The eleven variables selected via LASSO were incorporated into each of the eight machine learning models. Results demonstrated that the random forest model achieved the highest performance in the validation set, with an AUC of 0.894 (95% CI: 0.800-0.985), accuracy of 0.820 and sensitivity of 0.606. Calibration plots and DCA confirmed the robustness of the random forest model. SHAP analysis indicated that age, pancreatic duct diameter and preoperative aspartate aminotransferase were important predictors in the random forest model. Conclusion:The random forest model developed in this study demonstrated a good predictive performance for CR-DGE after LPD and may assist in the early identification of high-risk patients in clinical practice.

Background::Carotid intima-media thickness (IMT) and diameter, stiffness, and wave reflections, are independent and important clinical biomarkers and risk predictors for cardiovascular diseases. The purpose of the present study was to establish nationwide reference values of carotid properties for healthy Chinese adults and to explore potential clinical determinants.Methods::A total of 3053 healthy Han Chinese adults (1922 women) aged 18-79 years were enrolled at 28 collaborating tertiary centers throughout China between April 2021 and July 2022. The real-time tracking of common carotid artery walls was achieved by the radio frequency (RF) ultrasound system. The IMT, diameter, compliance coefficient, β stiffness, local pulse wave velocity (PWV), local systolic blood pressure, augmented pressure (AP), and augmentation index (AIx) were then automatically measured and reported. Data were stratified by age groups and sex. The relationships between age and carotid property parameters were analyzed by Jonckheere-Terpstra test and simple linear regressions. The major clinical determinants of carotid properties were identified by Pearson’s correlation, multiple linear regression, and analyses of covariance.Results::All the parameters of carotid properties demonstrated significantly age-related trajectories. Women showed thinner IMT, smaller carotid diameter, larger AP, and AIx than men. The β stiffness and PWV were significantly higher in men than women before forties, but the differences reversed after that. The increase rate of carotid IMT (5.5 μm/year in women and 5.8 μm/year in men) and diameter (0.03 mm/year in both men and women) were similar between men and women. For the stiffness and wave reflections, women showed significantly larger age-related variations than men as demonstrated by steeper regression slopes (all P for age by sex interaction <0.05). The blood pressures, body mass index (BMI), and triglyceride levels were identified as major clinical determinants of carotid properties with adjustment of age and sex. Conclusions::The age- and sex-specific reference values of carotid properties measured by RF ultrasound for healthy Chinese adults were established. The blood pressures, BMI, and triglyceride levels should be considered for clinical application of corresponding reference values.

Objective:To establish a machine learning model to predict the risk of post hepatectomy liver dysfunction (PHLD) in patients with hilar cholangiocarcinoma (HCCA).Methods:Clinical data of 203 patients with HCCA undergoing open radical hemihepatectomy in Henan University People's Hospital from January 2017 to December 2023 were retrospectively analyzed, including 112 males and 91 females, aged 63 (55, 69) years. According to the diagnostic criteria for PHLD, patients were divided into two groups: PHLD group ( n=45) and non-PHLD group ( n=158). Clinical data such as age, sex, neutrophil count (NEU), systemic immunoinflammatory index (SII), nutritional prognosis index (PNI), neutrophil to lymphocyte ratio (NLR), operative time and complications were compared between the two groups. The variables with statistically significant difference between the two groups were included in seven machine learning models, namely logistic regression, random forest, extreme gradient boosting, light gradient boosting, decision tree, gaussian naive bayes and support vector machine. The area under receiver operating characteristic curve optimization model was adopted, and Shapliga sum-interpretation method (SHAP) was used to analyze and interpret the final optimal model. Results:There were statistically significant differences in age, preoperative data including management of jaundice, albumin, total bilirubin, aspartate aminotransferase, NEU, SII, PNI, and NLR, operative time, postoperative complication of Dindo-Clavien≥Grade Ⅲ, and the ratio of FLR/TLV between in the two groups (all P<0.05). Finally, it was determined that the prediction performance of the extreme gradient boosting model was the best, with an area under curve of 0.888 (95% CI: 0.776-0.985), an accuracy of 0.854, a sensitivity of 0.506, a specificity of 0.965, an F1 value of 0.625, and a Kappa value of 0.519. SHAP analysis of the extreme gradient boosting model showed that total bilirubin on admission, operation time, postoperative complication of Dindo-Clavien≥grade Ⅲ, SII and NEU were five important factors of this model, which were positively correlated with the occurrence of PHLD in HCCA patients. Conclusion:The extreme gradient boosting model established in this study has a good predictive performance and stability for PHLD in HCCA patients.

Objective:To establish a machine learning model to predict the risk of post hepatectomy liver dysfunction (PHLD) in patients with hilar cholangiocarcinoma (HCCA).Methods:Clinical data of 203 patients with HCCA undergoing open radical hemihepatectomy in Henan University People's Hospital from January 2017 to December 2023 were retrospectively analyzed, including 112 males and 91 females, aged 63 (55, 69) years. According to the diagnostic criteria for PHLD, patients were divided into two groups: PHLD group ( n=45) and non-PHLD group ( n=158). Clinical data such as age, sex, neutrophil count (NEU), systemic immunoinflammatory index (SII), nutritional prognosis index (PNI), neutrophil to lymphocyte ratio (NLR), operative time and complications were compared between the two groups. The variables with statistically significant difference between the two groups were included in seven machine learning models, namely logistic regression, random forest, extreme gradient boosting, light gradient boosting, decision tree, gaussian naive bayes and support vector machine. The area under receiver operating characteristic curve optimization model was adopted, and Shapliga sum-interpretation method (SHAP) was used to analyze and interpret the final optimal model. Results:There were statistically significant differences in age, preoperative data including management of jaundice, albumin, total bilirubin, aspartate aminotransferase, NEU, SII, PNI, and NLR, operative time, postoperative complication of Dindo-Clavien≥Grade Ⅲ, and the ratio of FLR/TLV between in the two groups (all P<0.05). Finally, it was determined that the prediction performance of the extreme gradient boosting model was the best, with an area under curve of 0.888 (95% CI: 0.776-0.985), an accuracy of 0.854, a sensitivity of 0.506, a specificity of 0.965, an F1 value of 0.625, and a Kappa value of 0.519. SHAP analysis of the extreme gradient boosting model showed that total bilirubin on admission, operation time, postoperative complication of Dindo-Clavien≥grade Ⅲ, SII and NEU were five important factors of this model, which were positively correlated with the occurrence of PHLD in HCCA patients. Conclusion:The extreme gradient boosting model established in this study has a good predictive performance and stability for PHLD in HCCA patients.

Purpose To prepare biomimetic targeted nanobubbles(NBs)named IR780-RBCM@NBs and explore the ability of performing ultrasound enhancement,escaping immune surveillance and targeting tumor cells.Materials and Methods The red blood cell membrane(RBCM)was extracted from mouse blood,the IR780-RBCM@NBs were prepared by modified membrane hydration method,the physical and chemical properties of nanobubbles were detected.In vitro,self-made equipment was used to test the contrast-enhanced ultrasound imaging ability of the nanobubbles.Laser confocal fluorescence microscopy was used to observe the characteristics of the nanobubbles retaining CD47 on the RBCM surface,and further to observe the phagocytosis of the nanobubbles by macrophages and the targeting ability of the nanobubbles to different tumor cells.Results The newly prepared IR780-RBCM@NBs had the appearance of emulsion,the particle size was about(522.4±58.6)nm and the dispersity was good.It was spherical in uniform size under the microscope.IR-780 could be detected on the nanobubbles,which had the dual-mode imaging capabilities of near-infrared fluorescence imaging and contrast-enhanced ultrasound imaging.The RBCM-specific protein CD47 could be detected on the surface of the nanobubbles.The nanobubbles exhibited excellent immune phagocytic escape function and high efficiency to target different tumor cells.Conclusion Newly prepared biomimetic targeted IR780-RBCM@NBs,with good performance,can escape immune phagocytosis and efficiently target tumors,providing a new idea for molecular targeted accurate diagnosis and treatment of tumors.