Lung cancer is the most prevalent malignant tumor worldwide. For lung cancer patients with multiple intrapulmonary metastases or impaired lung function, complete tumor resection is challenging, and the prognosis is poor. Lung transplantation demonstrates potential therapeutic value in achieving complete tumor resection, improving lung function, and enhancing quality of life. Advances in tumor detection technologies such as positron emission tomography-computed tomography and circulating tumor DNA, along with the development of comprehensive treatment strategies for lung cancer, provide powerful tools for accurately predicting tumor recurrence and treatment outcomes following lung transplantation. The feasibility of lung transplantation as a treatment for lung cancer is receiving increasing attention. This article reviews the history and clinical management of lung transplantation for lung cancer.

ObjectiveTo investigate the protective effects and mechanisms of Bushen Zhuyun prescription （BSZY） on abortion rats with kidney deficiency-corpus luteum inhibition syndrome. MethodsAn abortion rat model with kidney deficiency-corpus luteum inhibition syndrome was constructed. Pregnant mice aged 8-10 weeks were randomly divided into a control group （Control）， a model group （Model）， low-dose BSZY （BSZY-L）， medium-dose BSZY （BSZY-M）， and high-dose BSZY （BSZY-H） groups （2.57， 5.14， 10.28 g·kg^-¹）， and a Zishen Yutai Pill （ZSYT） group （1.575 g·kg^-¹）. Hematoxylin-eosin （HE） staining was used to evaluate histopathological changes in ovarian and decidual tissue of rats in each group. Enzyme-linked immunosorbent assay （ELISA） was employed to measure levels of estrogen （E₂）， progesterone （P）， luteinizing hormone （LH）， prolactin （PRL）， and follicle-stimulating hormone （FSH） in serum. The candidate targets of BSZY were obtained from the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） and Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine （TCMIP） v2.0 databases， while disease targets for recurrent spontaneous abortion （RSA） were retrieved from GeneCards， DrugBank， Online Mendelian Inheritance in Man （OMIM）， and Therapeutic Target Database （TTD）. The intersection targets were identified by the Venny 2.1.0 platform. Pathway enrichment analysis was conducted based on the Metascape database to predict the potential mechanisms of BSZY. Additionally. Western blot was used to verify the effects of BSZY on the expression of estrogen receptor （ERα）， phosphatidylinositol 3-kinase （PI3K）， and protein kinase B （Akt） and explore its protective mechanism on RSA rats. ResultsCompared with the control group， the model group exhibited significantly decreased uterine， ovarian， and embryonic wet weights （P<0.05， P<0.01）， with an abortion rate of 57.18%. The ovarian tissue showed varying degrees of reduction in primordial follicles， primary follicles， mature follicles， and corpora lutea， along with a large number of atretic follicles. The endometrium was thinner， and decidual tissue exhibited cellular edema and disorganized arrangement. In contrast， compared with the model group， the BSZY groups at all doses and the ZSYT group demonstrated increased uterine， ovarian， and embryonic wet weights， along with a reduced abortion rate. The number of primordial follicles， primary follicles， mature follicles， and corpora lutea increased， while atretic follicles decreased. The endometrium thickened， and decidual tissue displayed normal cellular structure with tight arrangement. Additionally， the model group showed significantly decreased levels of E₂， P， PRL， and FSH in serum （P<0.05， P<0.01）， along with a decreasing trend in LH level. In contrast， the BSZY groups at all doses exhibited significantly elevated levels of E₂， P， LH， PRL， and FSH in serum （P<0.05， P<0.01）. Network pharmacology predictions suggested that BSZY may exert protective effects against abortion in rats by activating the ERα/PI3K/Akt signaling pathway. Western blot results confirmed that BSZY significantly upregulated the expression of ERα， PI3K， and p-Akt proteins （P<0.05， P<0.01）. ConclusionBSZY has a protective effect on the abortion rats with kidney deficiency-corpus luteum inhibition syndrome， possibly by activating the ERα/PI3K/Akt signaling pathway to reduce ovarian apoptosis and regulate endocrine function， thereby lowering the abortion rate.

OBJECTIVE To analyze the characteristics of global surgical site infection(SSI)outbreaks and provide references for targeted prevention and control measures.METHODS SSI outbreak events from Jan.1,1990 to Dec.31,2023 were searched from Wanfang Med,CNKI,VIP and PubMed.Data on department distribution dur-ing the outbreak,duration,investigation methods,main causes,transmission modes,pathogen composition and outbreak outcomes were summarized for analysis.RESULTS A total of 111 SSI outbreaks in 20 countries were identi-fied,involving 1 382 patients and 24 deaths.The source of the outbreak was identified in 78 cases,mainly involving med-ical personnel in 27 cases(34.62％),hospital equipment in 19 cases(24.36％),environmental factors in 11 cases(14.10％),workflow factors in 10 cases(12.82％),hospital water factors in 7 cases(8.97％)and disinfectant fac-tors in 4 cases(5.13％).The duration of SSI outbreaks abroad was 5.00(1.50,12.00)months,longer than that in China[1.00(1.00,2.00)month](P＜0.05).In China,the outbreaks mainly occurred in neurosurgery,cardiac surger-y,orthopedics,obstetrics and general surgery,while at abroad,they mainly occurred in cardiac surgery,orthopedics,and involved multiple surgical departments.Environmental hygiene methods were adopted in up to 90.63％of cases in China.Compared with China,analytical epidemiological methods and molecular epidemiological methods were more com-monly used abroad.Targeted measures and strengthened basic measures were implemented for different outbreak sources to terminate the SSI outbreaks.Pulsed-field gel electrophoresis(34 times)was a widely used molecular typing method in outbreak investigations.CONCLUSIONS Based on the analysis of SSI outbreak characteristics and risk factors,it is neces-sary to strengthen medical personnel training and monitoring of special pathogens.At the same time,the epidemiologi-cal investigation capabilities of infection control professionals should be strengthened.

Objective To integrate the Timing It Right(TIR)framework with Phase Ⅰ Cardiac Rehabilitation(CR)strategies to develop a staged,individualized rehabilitation protocol for patients after Transcatheter Aortic Valve Replacement(TAVR)and verify its clinical effectiveness.Methods A quasi-experimental study design was employed.A total of 128 TAVR patients admitted to Kunming Yan'an Hospital between January 2023 and December 2024 were selected as participants and randomly assigned via a random number table to either an intervention group(n=64)or a control group(n=64).The control group received routine care,while the intervention group received TIR theory-based Phase Ⅰ cardiac rehabilitation nursing care in addition to routine care.This intervention was implemented across three stages:diagnostic,perioperative,and discharge preparation period.Comparisons were made between the two groups regarding Left Ventricular Ejection Fraction(LVEF),the 6-Minute Walk Test(6MWT)distance,the incidence of Major Adverse Cardiac and Cerebrovascular Events(MACCE),scores across all domains of the China Questionnaire of Quality of Life in patients with Cardiovascular Diseases(CQQC),and patient satisfaction before and after the intervention.Results After the intervention,the intervention group demonstrated significantly higher LVEF and 6MWT results at both discharge and 3 months postoperatively compared to the control group(P<0.05).The incidence of MACCE was significantly lower in the intervention group(4.84％)than in the control group(13.33％).Scores across all CQQC domains and patient satisfaction were significantly superior in the intervention group than in the control group(P<0.05).Furthermore,The length of ICU stay and total hospitalization duration were significantly shorter in the intervention group compared to the control group(P<0.05).Conclusion Phase I cardiac rehabilitation nursing care based on the Timing It Right theory effectively improves cardiac function and exercise tolerance in TAVR patients,reduces the risk of MACCE.

ObjectiveTo analyze the temporal trend of knockdown resistance (kdr) gene mutations highly correlated with pyrethroid resistance in field populations of Aedes aegypti in Jinghong City of Yunnan Province, and to provide a scientific basis for formulating rational insecticide use strategies. MethodsAdult mosquito samples of Aedes aegypti from 2016 to 2023 and larvae mosquito samples from July 2022 to June 2023 were collected in Jinghong City of Yunnan Province. Allele specific PCR (AS-PCR) was used to measure kdr mutations at amino acid positions 989, 1016 and 1534 of the voltage-gated sodium ion channel (VGSC) gene. Data such as mutation rate and mutation allele frequency were calculated, SPSS software was used to perform trend chi square tests on mutation rate and mutation allele frequency with year and month, as well as comparison of mutation allele frequencies and genotype distributions between the dry and rainy seasons, thereby delineating the temporal trend of kdr gene mutations. ResultsAmong the 173 samples collected from 2016 to 2023, the mutation rates of S989P and V1016G were 100.00% for each year, while the mutation rate of F1534C ranged from 62.50% to 100.00%. The mutation rate and mutation allele frequency of F1534C were increased over the years (χ²=22.079, P<0.001; χ²=42.971, P<0.001). Concurrently, the proportion of the PPGGCC genotype was increased annually (χ²=60.790, P<0.001). Among the 288 samples collected from July 2022 to June 2023, the monthly mutation rates for S989P, V1016G, and F1534C were consistently 100.00%. There was only one type of mutation present, namely S989P+V1016G+F1534C. In the combinations of the three genotypes, the SPGGCC genotype accounted for 1.39% (4/288), the PPGGFC accounted for 2.78% (8/288), and the PPGGCC had the highest proportion at 95.83% (276/288). After tesiting the samples collected in August 2023, the mutation rates of 989, 1016 and 1534 sites of VGSC in females, males, and larvae of the same generation were all 100.00%. ConclusionSince 2016, the gene mutations at S989P and V1016G loci in the VGSC gene of wild Aedes aegypti in Jinghong City have remained consistently at 100.00%, while the mutation rate and mutant allele frequency of F1534C have increased year by year during the testing period. By 2023, the mutation rates at three loci in the VGSC gene of Aedes aegypti in Jinghong City had all reached 100.00%, and neither changes in insect developmental stage nor gender differences during transmission exerted a detectable impact on the mutation rates. In the control of Aedes aegypti in Jinghong City, the use of pyrethroid insecticides should be stopped or reduced, and regular monitoring of kdr genes should be carried out to promptly detect new mutations.

Objective:Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions.Methods:Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from the Cancer Hospital of the Chinese Academy of Medical Sciences, Tianjin Central Hospital of Gynecology Obstetrics, Xinmi Maternal and Child Health Hospital of Henan Province, West China Second Affiliated Hospital of Sichuan University, and Heping Hospital Affiliated to Changzhi Medical College collected during April 2014 and March 2015. The hypermethylated gene fragments related to cervical cancer were selected by high-density, high-association, and hypermethylated gene fragment screening and the LASSO regression algorithm. Taking cervical intraepithelial neoplasia grade 2 (CIN2) or more severe lesions as the research outcome, machine learning predictive models based on the random forest (RF), naive Bayes (NB), and support vector machine (SVM) algorithm, respectively, were constructed. A total of 144 outpatient specimens were used as the training set and 80 cervical exfoliated cell specimens from women participating in the cervical cancer screening program were used as the test set to verify the predictive models. Using histological diagnosis results as the gold standard, the detection efficacy for CIN2 or more severe lesions of the three machine learning predictive models were compared with that of the human papilloma virus (HPV) detection and cytological diagnosis.Results:In the training set of 144 cases, there were 34 cases of HPV positivity, with a positive rate of 23.61%. Cytologically, there were 37 cases diagnosed as no intraepithelial lesion or malignancy (NILM), and 107 cases diagnosed as atypical squamous cells of undetermined significance (ASC-US) or above. Histologically, there were 28 cases without cervical intraepithelial neoplasia or benign cervical lesions, 31 cases of CIN1, 18 cases of CIN2, 31 cases of CIN3, and 36 cases of squamous cell carcinoma. Seven hypermethylated gene fragments were selected from 45 genes, and three machine learning prediction models based on the RF, NB, and SVM algorithm, respectively, were constructed. In the validation set of 80 cases, there were 28 cases of HPV positivity, with a positive rate of 35.00%. Cytologically, there were 65 cases diagnosed as NILM and 15 cases as ASC-US or above. Histologically, there were 39 cases without cervical intraepithelial neoplasia or benign cervical lesions, 10 cases of CIN1, 10 cases of CIN2, 11 cases of CIN3, and 10 cases of squamous cell carcinoma. In the validation set, the area under the curve (AUC) values of the RF model, NB model, SVM model, HPV detection, and cytological diagnosis of CIN2 or above were 0.90, 0.88, 0.82, 0.68, and 0.45, respectively. The DeLong test showed that there was no statistically significant difference in the AUC values between the RF, NB, and SVM models (all P＞0.05), and the AUC values of the RF and NB models were higher than that of HPV detection (both P＜0.01), and the AUC values of the RF, NB, and SVM models were higher than that of cytological diagnosis (all P＜0.01). Compared with the NB model, the sensitivity of the RF model was similar (80.65% vs. 77.42%), but the specificity of the NB model was much higher than that of the RF model (93.88% vs. 73.47%). Conclusion:Among the machine learning prediction models for cervical cancer and precancerous lesions constructed based on human DNA methylation, the NB model has good predictive performance for CIN2 and above lesions, and may be used for screening of cervical cancer and precancerous lesions.

OBJECTIVE To analyze the characteristics of global surgical site infection(SSI)outbreaks and provide references for targeted prevention and control measures.METHODS SSI outbreak events from Jan.1,1990 to Dec.31,2023 were searched from Wanfang Med,CNKI,VIP and PubMed.Data on department distribution dur-ing the outbreak,duration,investigation methods,main causes,transmission modes,pathogen composition and outbreak outcomes were summarized for analysis.RESULTS A total of 111 SSI outbreaks in 20 countries were identi-fied,involving 1 382 patients and 24 deaths.The source of the outbreak was identified in 78 cases,mainly involving med-ical personnel in 27 cases(34.62％),hospital equipment in 19 cases(24.36％),environmental factors in 11 cases(14.10％),workflow factors in 10 cases(12.82％),hospital water factors in 7 cases(8.97％)and disinfectant fac-tors in 4 cases(5.13％).The duration of SSI outbreaks abroad was 5.00(1.50,12.00)months,longer than that in China[1.00(1.00,2.00)month](P＜0.05).In China,the outbreaks mainly occurred in neurosurgery,cardiac surger-y,orthopedics,obstetrics and general surgery,while at abroad,they mainly occurred in cardiac surgery,orthopedics,and involved multiple surgical departments.Environmental hygiene methods were adopted in up to 90.63％of cases in China.Compared with China,analytical epidemiological methods and molecular epidemiological methods were more com-monly used abroad.Targeted measures and strengthened basic measures were implemented for different outbreak sources to terminate the SSI outbreaks.Pulsed-field gel electrophoresis(34 times)was a widely used molecular typing method in outbreak investigations.CONCLUSIONS Based on the analysis of SSI outbreak characteristics and risk factors,it is neces-sary to strengthen medical personnel training and monitoring of special pathogens.At the same time,the epidemiologi-cal investigation capabilities of infection control professionals should be strengthened.

Objective:Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions.Methods:Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from the Cancer Hospital of the Chinese Academy of Medical Sciences, Tianjin Central Hospital of Gynecology Obstetrics, Xinmi Maternal and Child Health Hospital of Henan Province, West China Second Affiliated Hospital of Sichuan University, and Heping Hospital Affiliated to Changzhi Medical College collected during April 2014 and March 2015. The hypermethylated gene fragments related to cervical cancer were selected by high-density, high-association, and hypermethylated gene fragment screening and the LASSO regression algorithm. Taking cervical intraepithelial neoplasia grade 2 (CIN2) or more severe lesions as the research outcome, machine learning predictive models based on the random forest (RF), naive Bayes (NB), and support vector machine (SVM) algorithm, respectively, were constructed. A total of 144 outpatient specimens were used as the training set and 80 cervical exfoliated cell specimens from women participating in the cervical cancer screening program were used as the test set to verify the predictive models. Using histological diagnosis results as the gold standard, the detection efficacy for CIN2 or more severe lesions of the three machine learning predictive models were compared with that of the human papilloma virus (HPV) detection and cytological diagnosis.Results:In the training set of 144 cases, there were 34 cases of HPV positivity, with a positive rate of 23.61%. Cytologically, there were 37 cases diagnosed as no intraepithelial lesion or malignancy (NILM), and 107 cases diagnosed as atypical squamous cells of undetermined significance (ASC-US) or above. Histologically, there were 28 cases without cervical intraepithelial neoplasia or benign cervical lesions, 31 cases of CIN1, 18 cases of CIN2, 31 cases of CIN3, and 36 cases of squamous cell carcinoma. Seven hypermethylated gene fragments were selected from 45 genes, and three machine learning prediction models based on the RF, NB, and SVM algorithm, respectively, were constructed. In the validation set of 80 cases, there were 28 cases of HPV positivity, with a positive rate of 35.00%. Cytologically, there were 65 cases diagnosed as NILM and 15 cases as ASC-US or above. Histologically, there were 39 cases without cervical intraepithelial neoplasia or benign cervical lesions, 10 cases of CIN1, 10 cases of CIN2, 11 cases of CIN3, and 10 cases of squamous cell carcinoma. In the validation set, the area under the curve (AUC) values of the RF model, NB model, SVM model, HPV detection, and cytological diagnosis of CIN2 or above were 0.90, 0.88, 0.82, 0.68, and 0.45, respectively. The DeLong test showed that there was no statistically significant difference in the AUC values between the RF, NB, and SVM models (all P＞0.05), and the AUC values of the RF and NB models were higher than that of HPV detection (both P＜0.01), and the AUC values of the RF, NB, and SVM models were higher than that of cytological diagnosis (all P＜0.01). Compared with the NB model, the sensitivity of the RF model was similar (80.65% vs. 77.42%), but the specificity of the NB model was much higher than that of the RF model (93.88% vs. 73.47%). Conclusion:Among the machine learning prediction models for cervical cancer and precancerous lesions constructed based on human DNA methylation, the NB model has good predictive performance for CIN2 and above lesions, and may be used for screening of cervical cancer and precancerous lesions.