Cervical cancer (CC) is the fourth leading cause of cancer-related deaths among women worldwide in 2022, and conventional treatment modalities offer limited efficacy for patients with advanced or recurrent disease. Natural killer (NK) cells are a subset of lymphocytes capable of non-specifically eliminating tumor cells and virus-infected cells without prior sensitization, and have emerged as a research focus in the field of cancer immunotherapy. However, the systematic elucidation and in-depth analysis are required in the dual regulatory mechanisms of NK cells within the cervical cancer microenvironment and the bottlenecks hindering their clinical translation. This article reviews the application of NK cell-based immunotherapy in CC, summarizes the mechanisms of action and therapeutic advances of NK cells in CC, identifies the major obstacles to current clinical translation, and proposes corresponding solutions.

Objective: To explore the relationship between sleep characteristics, physical activity patterns, with depressive and anxiety symptoms in college students, so as to provide reference for student mental health promotion. Methods: From September to November 2023, a convenience sampling method was used to select 7 954 college students aged 18-22 years from 9 universities in Shanghai, Hubei, and Jiangxi. Assessments were conducted using the International Physical Activity Questionnaire Short-Form (IPAQ-SF), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder Scale-7 (GAD-7), and Pittsburgh Sleep Quality Index (PSQI) to evaluate physical activity, depressive and anxiety symptoms, and sleep quality, respectively. Logistic regression analysis was employed to explore the impact of sleep characteristics and physical activity patterns on depressive and anxiety symptoms and their comorbidity among college students. Results: The detection rates for depressive symptoms, anxiety symptoms, and comorbid depression and anxiety symptoms were 25.67%, 35.39%, and 23.15%, respectively. Factors such as gender, grade, household registration, parental education level, annual family income, family structure, and dietary habits were all associated with the detection rates of depressive and anxiety symptoms and their comorbidity (χ2=4.41-118.39, P<0.05). Physical activity patterns, sleep duration, sleep quality, and sleepwake characteristics were also associated with the occurrence of depressive and anxiety symptoms and their comorbidity (χ2=9.66-627.70, P<0.05). Logistic regression analysis showed that college students who stayed up late and slept less than 7 had the highest risk of depressive and anxiety symptoms and their comorbidity (OR=1.93, 1.85, 1.88, P<0.05). Compared to regular physical activity patterns, insufficient physical activity patterns were associated with an increased risk of depressive and anxiety symptoms (all OR=1.18, P<0.05). Further stratified analysis results showed that the risk of depression, anxiety and their comorbidity increased in college students who stayed up late and slept less than 7 h, went to bed before midnight and slept less than 7 h, or went to bed before midnight and slept more than 7 h but did not have sufficient physical activity (P<0.05). Conclusions Sleep characteristics and physical activity patterns significantly affect depressive and anxiety symptoms in college students. Universities should strengthen sleep management and implement flexible physical activity interventions to help students establish healthy lifestyles.

BACKGROUND:Cannabidiol is effective in ameliorating the body's inflammatory response,but no clear mechanistic studies have been conducted to ameliorate skeletal muscle inflammation induced by exhaustive exercise. OBJECTIVE:To explore the mechanism by which cannabidiol improves skeletal muscle inflammation during exhaustive exercise by using transcriptome sequencing technology. METHODS:Thirty-six Sprague-Dawley rats were randomly divided into six groups:blank control group,exercise coconut oil group,exercise control group,50 mg/kg cannabidiol group,60 mg/kg cannabidiol group,and 70 mg/kg cannabidiol group,with six rats in each group.Except for rats in the blank control group,rats in each group were subjected to swimming exercise for 9 days to produce the exhaustive exercise model.At the end of each swimming exercise,rats in the cannabidiol groups were given 2 mL of fat-soluble cannabidiol at different concentrations(50,60,and 70 mg/kg)by gavage;rats in the exercise coconut oil group were given the same volume of coconut oil by gavage until the end of the exercise on the 9th day;and rats in the blank control group and the exercise control group were not given any special treatment.The levels of inflammatory factors and differentially expressed genes in the skeletal muscle of rats in each group were determined using ELISA and transcriptome sequencing techniques.Differentially expressed genes obtained were subjected to KEGG analysis,and the accuracy of the sequencing data was verified by fluorescence quantitative PCR. RESULTS AND CONCLUSION:The results of ELISA showed that the contents of interleukin-6(P<0.05),tumor necrosis factor-α(P<0.01),interleukin-10 and other inflammatory factors in the exercise group increased significantly compared with the blank control group and the coconut oil group.After cannabidiol intervention,the mass concentrations of interleukin-6 and tumor necrosis factor-α showed a sequential decrease with increasing cannabidiol concentration.By comparing GO and KEGG databases,the functional properties of differentially expressed genes were analyzed,and the results showed that the differentially expressed genes were mainly involved in the tumor necrosis factor signaling pathway and the Toll-like receptor signaling pathway.RT-qPCR results showed that the trends of five randomly selected differentially expressed genes were in agreement with the transcriptome sequencing results.To conclude,cannabidiol can improve skeletal muscle inflammation caused by exhaustive exercise.

Surgical resection is an important method for treating liver cancer,and postoperative liver failure caused by insufficient liver remnant volume is a key factor limiting the success rate of surgical resection.The portal vein embolization(PVE),through artificially obstructing the portal vein,can induce liver volume enlargement,thus,providing theoretical support for preventing postoperative death due to liver failure.In recent years,many innovations and studies on the limitations of PVE,especially on the problem of postoperative insufficient growth rate of liver tissues,have been made by experts both at home and abroad.In view of this,this paper,through summarizing the relevant literature on PVE,makes a detailed review concerning the clinical application and research progress of PVE.

Objective:The association between air pollutants and the risk of sudden cardiac death (SCD) remains controversial. This study aimed to investigate the relationship between five air pollutants—PM 2.5, PM 2.5–10, PM 10, NO 2, and NO?—and the risk of SCD. Methods:We analyzed data from 460 862 participants in the UK Biobank cohort, all enrolled between 2006 and 2010, with no baseline SCD. Follow-up continued until the study endpoint. Annual average concentrations of the five pollutants were assessed. Associations between pollutants and SCD were evaluated using Cox proportional hazards models, followed by Mendelian randomization (MR) to assess causality.Results:Over a mean follow-up of 12.4 years, 2 662 SCD cases were recorded. After adjusting for confounders, no significant associations were found between air pollutants and SCD risk: PM 2.5 ( HR 1.03, 95% CI 0.99–1.07, P = 0.14), PM 2.5–10 ( HR 1.04, 95% CI 1.00–1.08, P = 0.08), PM 10 ( HR 1.01, 95% CI 0.99–1.03, P = 0.26), NO? ( HR 1.00, 95% CI 0.99–1.00, P = 0.26), and NO x ( HR 1.00, 95% CI 1.00–1.01, P = 0.19). MR analysis further supported the absence of causal relationships: PM 2.5 ( β = -0.149, P = 0.90), PM 2.5–10 ( β = 0.387, P = 0.62), PM 10 ( β = -0.994, P = 0.62), NO? ( β = –0.005, P = 0.99), and NO 2 ( β = –0.827, P = 0.25). Conclusions:This study found no evidence linking PM 2.5, PM 2.5–10, PM 10, NO?, or NO 2 to an increased risk of SCD. Mendelian randomization confirmed the lack of causal associations between these pollutants and SCD.

Objective To observe the value of fetal MRI in diagnosis of duodenal obstruction(DO).Methods A total of 35 fetuses with suspected DO according to MRI were retrospectively included.The length and the maximum diameter of the dilated duodenum were measured,so as site(categorized in descending order from proximal to distal as descending segment,horizontal segment and ascending duodenum/proximal jejunum)and the degree of obstruction(complete or incomplete)were assessed.Taken findings of labor induction specimen,postnatal neonatal surgery or follow-up data as standards,the positive predictive value(PPV)of MRI for diagnosing fetal DO was calculated,while the correlations of the measured parameters of dilated duodenum and the confirmed obstruction site/degree were analyzed.Results Among 35 fetuses,DO was confirmed in 34 fetuses,yielding an overall PPV of 97.14％(34/35)for MRI.In 34 fetuses with confirmed DO,there were 23 with descending DO(DDO),4 with horizontal DO(HDO)and 7 with ascending DO/proximal jejunum obstruction(ADO/PJO),including 12 with complete DO and 22 with incomplete DO.PPV of MRI for diagnosing DDO,HDO and ADO/PJO was 87.50％(21/24),50.00％(2/4)and 100％(7/7),respectively,for diagnosing complete and incomplete DO was 90.00％(9/10)and 84.00％(21/25),respectively.Both the length and the maximum diameter of fetal proximal dilated duodenum showed on MRI were positively correlated with the actual obstruction site(from proximal to distal)(rs=0.736,P＜0.001;rs=0.424,P=0.011,respectively),but had no significant rank correlation with the degree of obstruction(rs=-0.216,P=0.212;rs=-0.285,P=0.097,respectively).Conclusion Fetal MRI could effectively evaluate the length and the maximum diameter of dilated duodenum hence indicating the level and degree of DO.

Objective:To explore the clinical value of computed tomography(CT)with three-dimensional(3D)reconstruction technique in diagnosis and selecting surgical methods for patients with pituitary tumor.Methods:A retrospective analysis was performed on the clinical data of 82 elderly patients with suspected pituitary tumor at Huanggang Central Hospital between January 2021 and December 2023.All of patients underwent CT examination with 3D reconstruction technique and MRI examination.The postoperatively pathological results were used as the golden standard to compare the diagnostic results and efficiency of CT with 3D reconstruction technique and MRI for pituitary tumor.The differences of the two examination methods were compared in images quality.The clinical value of CT with 3D reconstruction technique for the selection of surgical method was further analyzed.Results:In 82 elderly patients with suspected pituitary tumor,56 cases were confirmed by postoperatively pathological examination,and 49 cases were confirmed by CT with 3D reconstruction technique,and 60 cases were confirmed by MRI.The characteristics of CT imaging were:quasi-circular or circular tumors were the majority,which had clear boundaries,and tumors grew to the side of sella turcica and around of the sella turcica,which accompanied by enlarged pituitary fossa.MRI imaging characteristics of pituitary tumors were as follows:the most of them accompanied with equal T1 and slightly high T2 signals,and there was enhancement of obvious ring,and the snowman sign.There was no significant difference in diagnostic accuracy between CT with 3D reconstruction technique and MRI(P>0.05).The diagnostic specificity of CT with 3D reconstruction technique was 96.15%,which was higher than 76.92%of MRI,while its sensitivity was 85.71%,which was lower than 96.43%of MRI,and the differences were statistically significant(x2=4.413,3.953,P<0.05).There were no significant differences in the maximum transverse diameter and maximum vertical diameter of tumors between CT with 3D reconstruction technique and MRI(P>0.05).Compared with the results of CT with 3D reconstruction technique,all of 56 patients with pituitary tumor adopted resection for pituitary tumor through nasal sphenoid approach.After surgery,2 cases occurred diabetes insipidus,and 1 case occurred intracranial infection and 1 case occurred decline in olfactory function.Conclusion:Both CT with 3D reconstruction technique and MRI have higher diagnostic value for pituitary tumors in the elderly,which can display characteristics of pituitary tumors,and have direct guidance roles for the selection of surgical methods.The diagnostic specificity of CT with 3D reconstruction technique is better.

To explore the application of sequential analysis in post-market safety dynamic surveillance of vaccines. Under the dynamic monitoring data of vaccines post-market approval, this research introduces the fundamental principles of maximizing sequential probability ratio test (MaxSPRT) and Bayesian sequential analysis, employing R software. Through an example of dynamic safety monitoring data of vaccines post-market approval, we analyze using the MaxSPRT and Bayesian sequential analysis. The MaxSPRT identified a safety signal in week 4 ( P<0.05), while Bayesian sequential analysis indicated that the 95% highest density interval for the RR value at week 4 is 1.13-3.27, suggesting the first appearance of a safety signal at week 4. The MaxSPRT and Bayesian sequential analysis effectively leverage continuously accumulating dynamic monitoring data, thereby serving as a valuable method for post-market safety surveillance of vaccines.

Objective To explore the value of machine learning(ML)models based on ultrasonic texture features(TF)of coronary artery for predicting incomplete Kawasaki disease(IKD)in children.Methods Forty-eight children with IKD and 48 children without KD(non-KD)were enrolled with propensity score matching and divided into training set(n=67,34 cases of IKD and 33 cases of non-KD)and test set(n=29,14 of IKD and 15 of non-KD)at the ratio of 7∶3.Based on clinic-laboratory indicators(C-L)in training set and TF obtained with texture analysis of coronary artery ultrasound images,the optimal C-L-related features and TF were selected.Based on the optimal C-L correlated features,TF and their combinations,6 ML models,including random forest(RF),support vector machine(SVM),logistic regression(LR),gradient boosting decision tree(GBDT),decision tree(DT)and eXtreme gradient boosting(XGBoost)were respectively constructed for predicting IKD in children.The models were then trained in training set and validated in test set,and the best C-L ML,TF ML and C-L-TF ML models were selected.The area under the curve(AUC)of the best ML models were compared,and the clinical value of the best TF ML model was observed with decision curve analysis(DCA).Results Totally 3 optimal C-L related features and 8 optimal TF were selected.Among the constructed C-L ML,TF ML and C-L-TF ML models,C-L-LR model,TF-LR model and C-L-TF-SVM model were the optimal ones,with AUC in training set of 0.891,0.985 and 0.965,while in test set of 0.676,0.971 and 0.948,respectively.No significant difference of AUC was found between TF-LR model and C-L-TF-SVM model in both training set and test set(both P＞0.05),which were both greater than those of C-L-LR model(all P＜0.05).TF-LR model achieved higher clinical benefits in both training set and test set.Conclusion Ultrasound TF-LR model of coronary artery could be used to effectively predict IKD in children.