Objective:To evaluate the safety and feasibility of radical hepatectomy after conversion therapy in patients with initially unresectable advanced hepatocellular carcinoma (HCC).Methods:Clinical data of 72 patients with initially unresectable advanced HCC admitted to the Department of Hepatobiliary and Pancreatic Surgery, Affiliated Cancer Hospital of Zhengzhou University and the Department of Hepatobi-liary and Pancreatic Surgery, Henan Provincial People's Hospital from January 2020 to July 2024 were retrospectively collected, including 61 males and 11 females, aged (58.4±9.1) years. The clinicopathological data of the patients, such as tumor characteristics, conversion treatment regimens, perioperative data, and follow-up situations were analyzed to evaluate the therapeutic effect and safety.Results:Among the patients, there were five cases of China liver cancer staging Ⅰb, six cases of Ⅱa, 22 cases of Ⅱb, 32 cases of Ⅲa and sevene cases of Ⅲb. There were 53 patients scored as Child-Pugh A and 19 as Child-Pugh B. Conversion treatment fashion included immunotherapy combined with targeted therapy and immunotherapy plus targeted therapy combined with hepatic arterial chemoembolization or hepatic arteryinfusion chemotherapy. Liver resection after conversion therapy was as follows: 16 cases of right hemihepatectomy, 20 cases of left hemihepatectomy, 11 cases of mesohepatectomy, seven cases of right posterior hepatectomy, 1 case of caudate lobectomy, 17 cases of local resection. Postoperative pathology showed that there were 17 cases of pathologic complete response and 55 cases of pathologic partial response. One patient died of liver failure after surgery, while the rest had no major complications. The postoperative hospital stay was (13.1±5.1) d. The follow-up time was 21.5(10.2, 32.1) months. The multivariate Cox analysis demonstrated that pathologic partial response and adjuvant therapy duration shorter than 5 cycles were identified as independent risk factors-affecting both recurrence-free survival and overall survival in patients with HCC undergoing sequential surgery after conversion therapy (all P<0.05). Conclusion:Sequential surgical resection provides survival benefits for patients with initially unresectable and advanced HCC after conversion therapy, which is a safe and effective therapeutic strategy.

Objective:To construct and validate a prediction model for intraoperative hypothermia in general anesthesia surgery patients based on machine learning algorithm.Methods:Convenience sampling was used to retrospectively collect data from 1 075 general anesthesia surgery patients in the First Teaching Hospital of Xinjiang Medical University from March to August 2023, which were randomly divided into modeling set and validation set in the ratio of 7∶3. Combining LASSO regression with the random forest algorithm, intraoperative hypothermia risk factors were screened. Models were constructed based on six machine learning algorithms, Logistic regression, decision tree, support vector machine (SVM) , extreme gradient boosting (XGBoost) , multilayer perceptron (MLP) and K-Nearest Neighbors (KNN) , and evaluate the performance of all models. Web-based dynamic nomogram was developed and interpretable analysis of the optimal model was performed using SHAP graph.Results:According to LASSO regression and random forest algorithm, length of anesthesia, intraoperative blood loss, baseline body temperature, age, intraoperative urine volume, and type of surgery were risk factors for intraoperative hypothermia in patients under general anesthesia, and the difference was statistically significant ( P<0.05) . The areas under the receiver operating characteristic curve for Logistic regression, decision tree, XGBoost, KNN, MLP, and SVM models were 0.777, 0.746, 0.793, 0.743, 0.768, 0.793, and the F1 scores were 0.667, 0.719, 0.861, 0.756, 0.820, and 0.842, respectively. Decision curve showed that the net benefit of the XGBoost model for predicting intraoperative hypothermia in patients was high when the threshold probability was between 0 and 1. A web-based dynamic nomogram was developed with good clinical applicability and generalizability. Conclusions:A dynamic nomogram of intraoperative hypothermia in general anesthesia surgery patients constructed and validated based on the machine learning algorithm can assist medical and nursing staff in identifying patients at high risk of intraoperative hypothermia and implementing personalized interventions.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To construct and validate a prediction model for intraoperative hypothermia in general anesthesia surgery patients based on machine learning algorithm.Methods:Convenience sampling was used to retrospectively collect data from 1 075 general anesthesia surgery patients in the First Teaching Hospital of Xinjiang Medical University from March to August 2023, which were randomly divided into modeling set and validation set in the ratio of 7∶3. Combining LASSO regression with the random forest algorithm, intraoperative hypothermia risk factors were screened. Models were constructed based on six machine learning algorithms, Logistic regression, decision tree, support vector machine (SVM) , extreme gradient boosting (XGBoost) , multilayer perceptron (MLP) and K-Nearest Neighbors (KNN) , and evaluate the performance of all models. Web-based dynamic nomogram was developed and interpretable analysis of the optimal model was performed using SHAP graph.Results:According to LASSO regression and random forest algorithm, length of anesthesia, intraoperative blood loss, baseline body temperature, age, intraoperative urine volume, and type of surgery were risk factors for intraoperative hypothermia in patients under general anesthesia, and the difference was statistically significant ( P<0.05) . The areas under the receiver operating characteristic curve for Logistic regression, decision tree, XGBoost, KNN, MLP, and SVM models were 0.777, 0.746, 0.793, 0.743, 0.768, 0.793, and the F1 scores were 0.667, 0.719, 0.861, 0.756, 0.820, and 0.842, respectively. Decision curve showed that the net benefit of the XGBoost model for predicting intraoperative hypothermia in patients was high when the threshold probability was between 0 and 1. A web-based dynamic nomogram was developed with good clinical applicability and generalizability. Conclusions:A dynamic nomogram of intraoperative hypothermia in general anesthesia surgery patients constructed and validated based on the machine learning algorithm can assist medical and nursing staff in identifying patients at high risk of intraoperative hypothermia and implementing personalized interventions.

This study established the HPLC fingerprints, characteristic chromatograms, and a multi-component content determination method for Bidens bipinnata and B. biternata. The chemical pattern recognition analysis was then employed to clarify the characteristic indexes of quality differences between the two original plants of Bidentis Herba, providing a reference for establishing the quality standards of Bidentis Herba. HPLC was launched on an Agilent Poroshell 120 EC-C_(18) chromatographic column(4.6 mm×250 mm, 4 μm) by gradient elution with a mobile phase of 0.1% aqueous phosphoric acid-acetonitrile at a flow rate of 0.7 mL·min~(-1), detection wavelength of 270 nm, column temperature of 25 ℃, and an injection volume of 5 μL. The similarity between the fingerprints of 18 batches of Bidentis Herba samples and the common pattern(R) ranged from 0.572 to 0.933. A total of 23 chromatographic peaks were calibrated. Through comparison with the reference substances, six components(neochlorogenic acid, chlorogenic acid, isochlorogenic acid A, isochlorogenic acid B, rutin, and hyperoside) were identified and subjected to quantitative analysis. The characteristic fingerprints of B. bipinnata and B. biternata were calibrated with 20 and 17 characteristic peaks, respectively. Among them, peaks 8, 9, 22, and 23 were the characteristic peaks of B. bipinnata, and peak 7 was the characteristic peak of B. biternata, which can be used to distinguish the two original plants of Bidentis Herba. The relative standard deviation of the content of the above-mentioned six components ranged from 36% to 123%. The cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) classified the 18 batches of Bidentis Herba samples into two categories. Additionally, through the analysis of variable importance in projection(VIP) under OPLS-DA, three characteristic indexes, rutin, isochlorogenic acid A, and isochlorogenic acid B, were identified. The analytical method established in this study can comprehensively evaluate the consistency of Bidentis Herba samples derived from different original plants, specifically identify the differential components between them, and effectively distinguish the two original plants of Bidentis Herba, providing a basis for the differentiation between different original plants and the quality control of Bidentis Herba.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Bidens/chemistry*

OBJECTIVES: To investigate the molecular mechanism by which Lichong Xiaozheng Granules (LCXZ) sensitize ovarian cancer to cisplatin (DDP) treatment. METHODS: LC-MS analysis was used to identify the blood components of LCXZ after its administration in mice via gavage. In a BALB/c mouse model bearing subcutaneous ovarian cancer xenografts, the effects of daily gavage of distilled water (control group), intraperitoneal injection of DDP (5 mg/kg) once a week, or both DDP injection and daily LCXZK gavage (15 g/kg) on tumor growth were evaluated. Histopathological changes in the xenografts and kidneys were assessed with HE staining. RNA-seq was performed to identify the differentially expressed genes followed by KEGG pathway analysis. The changes in mitochondrial ultrastructure and expressions of mitochondrial apoptosis-related were examined with transmission electron microscopy and Western blotting. RESULTS: A total of 218 blood-borne components of LCXZ were detected by LC-MS. In the tumor-bearing mice, treatments with DDP and DDP combined with LCXZ redcued the tumor volume by 60.3% and 72.6% compared with that in the control group, respectively. Transcriptomic analysis revealed significantly upregulated ANT3 expression in both the two treatment groups. Molecular docking indicated that the main active components of LCXZ were capable of binding to adenine nucleotide translocator 3 (ANT3) with binding energies below -6 kcal/mol. Transmission electron microscopy showed obvious mitochondrial swelling and outer-membrane damage in the tumor cells in DDP-treated mice, and these changes were more pronounced in the combined treatment group. The expression levels of BAX, ANT3, cleaved caspase-3 and cleaved caspase-9 were increased, whereas BCL-2 expression was decreased significantly in the tumor cells in both the DDP and DDP+LCXZ groups. CONCLUSIONS LCXZ enhances the therapeutic efficacy of cisplatin against ovarian cancer xenografts in mice by promoting mitochondrial dysfunction and activating apoptotic signaling pathways via upregulating ANT3.
Animals ; Female ; Cisplatin/pharmacology* ; Ovarian Neoplasms/metabolism* ; Apoptosis/drug effects* ; Mitochondria/metabolism* ; Drugs, Chinese Herbal/pharmacology* ; Mice, Inbred BALB C ; Mice ; Rats ; Xenograft Model Antitumor Assays ; Humans ; Cell Line, Tumor ; Antineoplastic Agents/pharmacology*

Hemorrhagic shock is a common clinical emergency that can aggravate cell injury after resuscitation. Astrocytes are crucial for the survival of neurons because they regulate the surrounding ionic microenvironment of neurons. Although hemorrhagic shock and resuscitation (HSR) injury can impair cognition, it remains unclear how this insult directly affects astrocytes. In this study, we established an HSR model by bleeding and re-transfusion in mice. The social interaction test and new object recognition test were applied to evaluate post-operative cognitive changes, and the results suggest that mice experience cognitive impairment following exposure to HSR. In the HSR group, the power spectral density of β and γ oscillations decreased, and the coupling of the θ oscillation phase and γ oscillation amplitude was abnormal, which indicated abnormal neuronal oscillation and cognitive impairment after HSR exposure. In brief, cognitive impairment in mice is strongly correlated with Ca²⁺ signal strength in lateral septum astrocytes following HSR.
Animals ; Astrocytes/metabolism* ; Shock, Hemorrhagic/metabolism* ; Resuscitation/adverse effects* ; Male ; Mice ; Calcium Signaling/physiology* ; Mice, Inbred C57BL ; Septal Nuclei/metabolism* ; Cognitive Dysfunction/etiology* ; Disease Models, Animal ; Cognition Disorders/etiology*

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

Objective:To search,evaluate and integrate the best evidence of preventing fire accident in electrical surgery of domestic and international operating room,so as to provide reference for clinical practice of equipment in electrical surgery of operating room.Methods:This study conducted a literature review for domestically and internationally support systems of clinical decision,guideline websites,websites of nursing professional association,and Chinese-English databases.A series of relative literatures of fire accident in electrical surgery of operating room were included,which focused on clinical decisions,guidelines,evidence summaries,systematic evaluations,and expert consensus.The search period covered from the establishment date of database to November 12,2024,and the included literatures only limited to be English and Chinese publications.Two researchers who received evidence-based training independently evaluated the quality of these literatures,and they extracted and integrated information meeting quality standards according to professional judgment.Results:A total of 4,807 literatures were obtained after preliminary search.Then,a total of 12 research literatures were included,including 1 clinical decision,4 guidelines,1 evidence summary,3 systematic reviews and 3 expert consensus.The 20 best evidences of preventing fire accident in electrical surgery of operating room were summarized from three aspects:risk factors,risk assessment and preventive measures.Conclusion:The best evidence of preventing fire accident in electrical surgery of operating room can provide evidence-based evidences for the standardized management for electrical surgery of operation room,and provide basis for formulating management plan of preventing fire accident in electrical surgery of operation room,and for standardizing practice behavior of medical staffs.The evidence transformation should combined with actual clinical situation,and should reasonably select and prudently apply evidences.