Paclitaxel (PTX), a valuable natural product derived from Taxus species, exhibits remarkable anti-cancer properties. It penetrates nanopores in microtubule walls, interacting with tubulin on the lumen surface and disrupting microtubule dynamics, thereby inducing cytotoxic effects in cancer cells. PTX and its derivatives have gained approval for treating various diseases due to their low toxicity, high efficiency, and broad-spectrum application. The widespread success and expanding applications of PTX have led to increased demand, raising concerns about accessibility. Consequently, researchers globally have focused on developing alternative production methods and applying nanocarriers in PTX delivery systems to enhance bioavailability. This review examines the challenges and advancements in PTX sourcing, production, physicochemical properties, anti-cancer mechanisms, clinical applications, trials, and chemo-immunotherapy. It aims to provide a comprehensive reference for the rational development and effective utilization of PTX.
Humans ; Paclitaxel/pharmacology* ; Antineoplastic Agents, Phytogenic/pharmacology* ; Neoplasms/drug therapy* ; Animals ; Taxus/chemistry*

Objective: To analyze serological and molecular characteristics of asymptomatic HBV infection in HBV surface antigen positive (HBsAg+) blood donors from Dalian. Methods: The prevalence of HBsAg was analyzed among blood donors in Dalian between 2013 and 2022. Randomly selected HBsAg+ blood samples were subjected to HBV serological testing, HBV viral DNA quantification, and HBV genotyping. Results: Over this ten-year period, the prevalence of HBsAg decreased from 1.25% to 0.50% among blood donors in Dalian. Donors who tested positive for HBsAg prior to donation using a rapid test (RT) accounted for 92.5% of all HBsAg+ donors identified. A total of 240 confirmed HBsAg+ blood donors were randomly selected, including 125 donors with positive results and 115 with negative results in the pre-donation rapid test. HBsAg+ donors were mainly males (71.2%), with a median age of 42, and 97.5% of them being first-time donors. Based on HBV serological profiles, three stages of infection were identified: early infection (2.9%), suspected acute hepatitis (0.8%), and chronic infection (96.3%). The dominant HBV genotypes were C (68.9%) and B (28.4%). Among chronic HBV infection individuals, donors infected with HBV genotype B were older than those infected with genotype C (median age: 45y vs 38.5y, P<0.05). Additionally, they showed significantly lower HBsAg levels with a narrower distribution range than those infected with genotype C [median: 23.2 IU/mL (range: <0.05-7 910 IU/mL) vs 968 IU/mL (range: <0.05-3.4×10 ), P<0.05]. However, no significant difference was observed in the HBV DNA loads between these two genotypes (P>0.05). Conclusion: Between 2013 and 2022, the prevalence of HBsAg among blood donors in Dalian showed a year-over-year decline. Chronic infection was predominant among HBsAg+ first-time blood donors. The characteristics of chronic infection in blood donors differed significantly depending on the viral genotype, manifesting as differences in age of infected individuals and HBsAg level distribution.

Objective:To compare the efficacy of various machine learning models in predicting renal function decline after robot-assisted partial nephrectomy(RAPN),and to provide evidence for clinical risk stratification.Methods:This study retrospectively in-cluded the clinical data of 733 patients with renal cell carcinoma undergoing RAPN at the Urology Department of The First Affiliated Hospital of Chongqing Medical University from January 2019 to December 2023.Demographic characteristics,laboratory indicators,and perioperative parameters were integrated to construct seven machine learning models.Key predictors were interpreted using Shap-ley additive explanations(SHAP).Model performance was evaluated using the area under the receiver operating characteristic curve(AUC).Results:The random forest model demonstrated the best predictive performance(AUC=0.84).SHAP analysis identified neutrophil-to-lymphocyte ratio,tumor diameter,the international normalized ratio of prothrombin time,white blood cell count,and in-traoperative blood loss as significant factors influencing postoperative renal function decline.Conclusion:This study provides a poten-tial predictive tool for clinical practice,aiding in identifying high-risk patients and optimizing postoperative management strategies.

Objective:To investigate the clinical value of a fully autonomous ultrasound robot in splenic ultrasound imaging.Methods:A retrospective study was conducted by enrolling 56 adult volunteers from the Third Medical Center of the Chinese PLA General Hospital between February 1-8，2024 as research subjects.A senior physician sequentially performed splenic ultrasound examinations using both the fully autonomous ultrasound robot and a matched portable ultrasound device. The acquired images were randomly coded and scored via a double-blind method by 3 physicians. The differences of the image quality scores and high-quality image proportions between the two groups were compared. Examination durations were recorded and compared between the two groups.Results:Both modalities successfully acquired splenic images in all 56 volunteers. No statistically significant differences were observed in image quality scores among the 3 physicians：（3.52 ± 1.31）points vs.（3.83 ± 1.23）points，（2.77 ± 1.23）points vs.（3.17 ± 1.17）points，and（3.48 ± 0.97）points vs.（3.79 ± 0.94）points（all P>0.05）. The numbers of images scoring ≥ 3 points showed no significant differences：45（80.36%） vs. 50（89.29%），30（53.57%） vs. 38（67.86%），and 48（85.71%） vs. 52（92.86%）（all P>0.05）. The fully autonomous ultrasound robot required significantly longer examination time［（60.86 ± 50.55）s vs.（7.95 ± 4.35）s， t=6.88， P＜0.01］. Conclusions:The fully autonomous ultrasound robot demonstrates comparable image quality and clinically acceptable image proportions to conventional portable ultrasound in splenic examinations. These findings suggest its potential equivalence to operator-dependent ultrasound for splenic imaging，supporting its feasibility as an alternative ultrasound modality despite longer procedural duration.

Fetal malformation of cortical development(MCD)is a group of structural neurological disorders caused by abnormalities in development of cortical layer during embryogenesis,characterized by significant heterogeneity and diversity,which may lead to adverse clinical outcomes such as epilepsy and intellectual disabilities.The progresses in prenatal evaluation on fetal MCD were reviewed in this article.

Objective:To explore the effect of psoas muscle index (PMI) and construct a machine learning model to validate the 180-day prognosis in patients with decompensated liver cirrhosis.Methods:Retrospective data were collected from patients with decompensated liver cirrhosis at Henan Provincial People's Hospital from January 2022 to November 2022. The area of the psoas muscle index (PMI) at the level of the third lumbar vertebra was measured and calculated based on the abdominal X-ray computed tomography images stored in the Eastern China Hospital Information System (HIS). Patients were divided into low PMI and normal PMI groups according to the receiver operating characteristic curve. Patients clinical data and complication status were collected.The general conditions of both groups were compared using a t-test, chi-square test, and Mann-Whitney U test. The Kaplan-Meier method was applied for survival analysis. The outcome variable was 180-day mortality, and variables were selected using Cox and LASSO regression. The dataset was divided into training and testing sets in a 7∶3 ratio. Machine learning algorithms were used to build models in the training set, and model performance was validated by the test set. The model for MELD-Na score was compared with the model for End-Stage Liver Disease score. Results:A total of 298 patients with decompensated liver cirrhosis were included.The MELD scores, Child-Pugh classification, and NRS2002 scores, along with the incidence rate of complications such as ascites, hepatic encephalopathy, infections, and gastrointestinal bleeding, were significantly higher in the low PMI than the normal PMI group, with statistically significant differences ( P<0.05). The area under a receiver operating characteristic curve for the extreme gradient boosting model was higher than traditional clinical scores (MELD score 0.658, MELD_Na score 0.719) in the machine learning model. Furthermore, the application of SHAP results model indicated that PMI, hemoglobin, NRS2002 score, direct bilirubin, and blood ammonia were important factors in predicting the prognosis of patients with decompensated liver cirrhosis. Conclusion:A low PMI is closely related to poorer survival rates and the development of complication rates in patients with decompensated liver cirrhosis. The machine learning prediction model based on this construction, especially extreme gradient boosting, has favorable predictive performance, which is superior to the traditional clinical scoring system and can provide patients with the most accurate risk assessment and individualized treatment plan.

Objective To analyze the clinical application of the Donabedian-based structure-process-result three-dimensional quality evaluation model for the prevention of stress injury in bone tumor surgery.Methods A total of 284 patients with bone tumor who were admitted to The Second Affiliated Hospital of Naval Medical University from January 2022 to December 2023 were enrolled and assigned to two groups according to the random number table.The control group received routine nursing.In the observation group,the Donabedian-based structure-process-result three-dimensional quality evaluation model was applied to prevent the stress injury in bone tumor surgery.The indexes of the two groups were compared and analyzed.Results Before intervention,there was no significant difference in scores between the two groups(P>0.05).After intervention,the scores of stress injury behavior,skill and knowledge in the observation group were higher than those in the control group(P<0.05).The incidence of stress injury in the observation group was lower than that in the control group(P<0.05).There was significant difference in nursing satisfaction between the two groups(P<0.05).Conclusion Donabedian-based structure-process-result three-dimensional quality evaluation model can not only enhance the self-care ability of the patients undergoing bone tumor surgery,but also prevent stress injury,thus improving patient satisfaction.

Objective:To compare the clinical outcomes of immediate breast reconstruction using latissimus dorsi flap with implant versus mesh with implant based on BREAST-Q evaluation.Methods:From the clinical database of the First Affiliated Hospital of Nanjing Medical University, the patients who underwent immediate breast reconstruction after total mastectomy from January 2020 to December 2023 were selected as the research subjects. All breast reconstruction surgeries were performed by the same surgeon. Patients were divided into two groups according to surgical methods: the latissimus dorsi muscle flap combined with implant immediate breast reconstruction group (LD group) and the mesh combined with implant immediate breast reconstruction group (mesh group). Patients were followed up in outpatient clinics or by telephone one year after surgery. The BREAST-Q was used to evaluate the surgical outcomes of both groups from four dimensions: psychosocial well-being, sexual well-being, chest-physical well-being, and breast satisfaction. The score range for each dimension was 0-100, with higher scores indicating greater patient satisfaction with quality of life and surgical outcomes. Statistical analysis was performed using SPSS 22.0 software. Normally distributed measurement data were expressed as Mean ± SD, and comparisons between the two groups were performed using independent sample t-test. Count data were expressed as number of cases and percentages, and comparisons between groups were performed using chi-square test or Fisher’s exact test. P<0.05 was considered statistically significant. Results:A total of 123 patients were included, with 59 patients in the LD group and 64 patients in the mesh group. In the LD group, the mean age was (37.7±7.0) years, body mass index (BMI) was (22.6±2.6) kg/m 2, and clinical tumor staging showed 2, 22, 30, and 5 cases for stages 0, Ⅰ, Ⅱ, and Ⅲ, respectively. In the mesh group, the mean age was (39.1±7.0) years, BMI was (22.6±2.8) kg/m 2, and clinical tumor staging showed 1, 25, 38, and 0 cases for stages 0, Ⅰ, Ⅱ, and Ⅲ, respectively. There were no statistically significant differences between the two groups in baseline characteristics including age, BMI, and clinical tumor staging (all P>0.05). One year after surgery, the BREAST-Q result showed no statistically significant differences between the LD group and mesh group in psychosocial well-being [(83.0±19.8) points vs. (80.8±19.3) points] and sexual well-being [(62.1±30.4) points vs. (65.8±25.6) points] (all P>0.05). However, the LD group had lower chest-physical well-being scores than the mesh group [(40.6±9.7) points vs. (45.1±9.6) points, P<0.05], while breast satisfaction scores were higher in the LD group than in the mesh group [(68.0±17.8) points vs. (59.8±12.6) points, P<0.01]. Conclusion:Immediate breast reconstruction by both latissimus dorsi flap with implant and mesh with implant can improve patients’ psychosocial and sexual well-being by enhancing breast appearance. However, LD technique provides better breast satisfaction, while the mesh technique offers advantages in physical well-being of the chest wall and upper body. Surgeons should select the most appropriate breast reconstruction technique based on patients’ anatomical conditions, treatment history, and individual needs to optimize postoperative quality of life and satisfaction.

Objective:To investigate the feasibility of deep learning reconstruction (DLR) algorithm combined with a dual-low protocol (low radiation dose and low contrast medium dose) for thoracoabdominal aortic CT angiography (CTA).Methods:This cross-sectional study prospectively enrolled 56 patients suspected of aortic diseases who underwent aortic CTA at China-Japan Friendship Hospital from June 2023 to June 2024. All patients were randomly divided into two groups: Group A (28 cases) underwent CTA with a tube voltage of 100 kVp, automatic tube current modulation (noise index=10), and a contrast agent dose of 80 ml (flow rate 5 ml/s), with images reconstructed using the three-dimensional adaptive iterative dose reduction algorithm (AIDR). Group B (28 cases) underwent CTA with a tube voltage of 80 kVp, automatic tube current modulation (noise index=25), and a contrast agent dose of 40 ml (flow rate 3.5 ml/s), with images reconstructed using either the deep learning reconstruction algorithm-Advanced intelligent Clear-IQ Engine (AiCE subgroup) or the AIDR (AIDR subgroup). Two physicians evaluated the image quality of the three groups subjectively and objectively. Objective evaluation metrics included CT values, image noise (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) at the ascending aorta, carina-level descending aorta, celiac trunk-origin abdominal aorta, and common iliac bifurcation abdominal aorta carina. Subjective evaluation metrics included image quality and noise scores. Comparisons among the three datasets (Group A, AiCE subgroup, AIDR subgroup) were performed using one-way ANOVA or the Kruskal-Wallis test, with appropriate post-hoc tests for pairwise comparisons.Results:No significant differences were observed in CT values of the ascending aorta, descending aorta, and abdominal aorta between Group A and the AiCE subgroup or the AIDR subgroup ( P0.05). However, significant overall differences were found in SD, SNR, and CNR values for the ascending aorta, descending aorta, and abdominal aorta ( P0.05). Pairwise comparisons revealed that, except for no significant differences in SD, SNR, and CNR values of the ascending and descending aorta between Group A and the AiCE subgroup, and no significant difference in SNR values of the ascending and abdominal aorta between Group A and the AIDR subgroup ( P0.05), all other intergroup comparisons showed statistically significant differences ( P0.05). Significant overall differences were also observed in image quality and noise scores between Group A and the AiCE and AIDR subgroups ( P0.05). Except for no significant differences in image quality and noise scores between Group A and the AiCE subgroup ( P0.05), all other pairwise comparisons showed statistically significant differences ( P0.05). Conclusions:The application of deep learning reconstruction algorithm combined with a dual-low protocol in thoracoabdominal aortic CTA can reduce radiation dose and contrast agent dose while maintaining diagnostic image quality, demonstrating significant clinical value for widespread adoption.

Strengthening the construction of platforms,talents,and disciplines is a crucial strategy to enhance the core competitiveness and promote the high-quality development of national regional medical centers.It outlines the theoretical framework and implementation path for building the"Platform-Talent(Team)-Discipline"develop-ment system during the establishment of the National Regional Medical Center at Henan Children's Hospital Zheng-zhou Children's Hospital.By creating a collaborative innovation platform integrating medical services,education,and research,implementing talent development programs,optimizing mechanisms for talent recruitment,cultivation,and retention,and advancing discipline development projects,the center has achieved significant progress in its core competencies.This exploration provides valuable insights and references for the development of national regional medical centers and the high-quality growth of public hospitals.