AIM:To analyze the association between mobile phone addiction and high myopia among college students.METHODS:We conducted a cross-sectional questionnaire survey in December 2022 on all students of a university in Shaanxi Province, and the questionnaire included socio-demographic characteristics, mobile phone addiction, high myopia, and lifestyle. Binary Logistic regression model was used to analyze the association between mobile phone addiction and high myopia among college students.RESULTS:A total of 19 952 college students were included. The prevalence of high myopia was 7.31%. The rate of mobile phone addiction was 25.68%, and the mobile phone addiction score was 37.59±13.38. The incidence of high myopia among college students with mobile phone addiction was higher than non-mobile phone addiction(P<0.001). After adjusting for socio-demographic characteristics and lifestyle, the risk of high myopia among college students with mobile phone addiction was 1.274 times(95%CI:1.131-1.434)higher than non-mobile phone addiction. For each point increase of total mobile phone addiction score, withdrawal symptoms score, salience score, social comfort score, and mood changes score, the risk of high myopia among college students increased by 0.9%(95%CI:1.005-1.013), 2.0%(95%CI:1.010-1.030), 2.6%(95%CI:1.010-1.043), 4.8%(95%CI:1.030-1.066), and 3.3%(95%CI:1.014-1.052), respectively.CONCLUSION:Mobile phone addiction is significantly associated with the increased risk of high myopia among college students, and early intervention of mobile phone use may reduce the risk of high myopia among college students.

The TGF-β signaling pathway affects various biological processes of cancers, including proliferation, invasion, metastasis, angiogenesis, and immune escape. Currently, multiple drugs targeting this pathway are in clinical trial stage, which involve three aspects of TGF-β, namely, production, activation, and signal transduction. Based on current evidence, the therapeutic effect of TGF-β monotherapy on advanced solid tumors is limited. Combination therapies that show promising results include combination with PD-1 antibodies, and combination with radiotherapy and chemotherapy. New combination therapies, such as CAR-T therapy modified with TGF-βRII, are also emerging in clinical research. This article systematically reviews the therapeutic strategies targeting TGF-β to provide research basis and ideas for the development of drugs targeting the TGF-β pathway.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

BACKGROUND:Micro-abrasion,at-home whitening combined with infiltration resin have a good effect on dental fluorosis,but the effect of this method on micro-cracks in dental fluorosis is still unclear. OBJECTIVE:To explore the effect of micro-abrasion,at-home whitening combined with infiltration resin on micro-cracked dental fluorosis. METHODS:(1)Clinical research:A total of 23 patients with micro-cracked dental fluorosis,including 255 micro-cracked dental fluorosis,were selected from July 2020 to March 2021 in the Department of Prosthodontics,Stomatology Hospital,Tianjin Medical University.All of them received combined treatment of tooth micro-abrasion,at-home whitening and infiltration resin.The tooth color,tooth sensitivity,and tooth pain threshold were compared before treatment and 1 week and 1 month after treatment.(2)In vitro experiment:60 teeth with fluorosis with at least one crack on the tooth surface were collected and randomly divided into three groups for treatment.The control group was treated without any treatment.The whitening group was treated with micro-abrasion and at-home whitening,and the combined group was treated with micro-abrasion,at-home whitening,and infiltration resin,with 20 teeth in each group.The microhardness of the three groups of teeth samples after treatment was measured. RESULTS AND CONCLUSION:(1)Clinical study:6 months after treatment,among 255 teeth with micro-cracked dental fluorosis,whitening treatment for 207 teeth was significantly effective and whitening treatment for 48 teeth was effective,and the overall treatment efficiency was 100%.With the extension of treatment time,the proportion of moderate and severe dental sensitivity showed a decreasing trend.At 6 months after treatment,255 teeth with dental fluorosis had no severe sensitivity,15 with moderate sensitivity,125 with mild sensitivity,and 115 with no sensitivity,and the difference was significant compared with the sensitivity before treatment(P<0.05).There was no significant difference in the threshold of tooth pain before treatment and 1 week and 6 months after treatment(P>0.05).(2)In vitro experiment:The tooth microhardness of the whitening group was lower than that of the control group and the combined group(P<0.05),but there was no significant difference between the control group and the combined group(P>0.05).(3)The results show that the methods of micro-abrasion,at-home whitening combined with infiltration resin have good clinical efficacy in the treatment of micro-cracked dental fluorosis.

ObjectiveThis study aimed to explore the correlation between the quality of life （QOL） and different traditional Chinese medicine （TCM） syndromes in patients with myasthenia gravis （MG）， identifying potential influencing factors to provide new insights for clinical interventions and improving the QOL of patients with MG. MethodsA questionnaire survey was conducted on 93 adults with MG who visited the Department of Neurology at the Affiliated Hospital of Changchun University of Chinese Medicine from March 2023 to January 2024. Statistical analysis was performed on the clinical data collected using SPSS 24.0 software. ResultsAmong the 93 patients with MG， the average score for myasthenia gravis quality of life-15 （MGQOL-15） was 17.65±6.27， and that for the 36-item short form health survey （SF-36） was （106.13±11.83） scores. The QOL was rated as good for 16 patients and moderate for 77 patients. There were no statistically significant differences in the scores of MGQOL-15， SF-36， and their individual scales by gender or education level. Age showed statistically significant differences in MGQOL-15 and the role physical （RP） scale （P<0.05）， and occupational type showed significant differences in the vitality （VT） scale （P<0.01）. The Myasthenia Gravis Foundation of America （MGFA） classification had statistical significance on the total SF-36 score （P<0.01）， VT scale （P<0.01）， role emotional （RE） scale （P<0.05）， social functioning （SF） scale （P<0.05）， and physical functioning （PF） scale （P<0.01）. Among patients with different TCM syndromes， there were significant differences in MGQOL-15 scores （F=4.919， P<0.01）. Moreover， significant differences were observed in SF-36 scores （P<0.01）， VT scale （P<0.01）， RE scale （P<0.05）， mental health （MH） scale （P<0.01）， and SF scale （P<0.05）. ConclusionFactors affecting the QOL of patients with MG include age， occupational type， and clinical classification of MG. Specifically， a greater impact on the QOL of older patients is observed， while physical laborers have a poorer QOL compared to non-physical laborers. Patients classified as MGFA type Ⅱ and higher have a poorer QOL. Additionally， there is a potential correlation between the QOL and TCM syndromes， with patients presenting with spleen and kidney Qi deficiency having a lower QOL than those with spleen and stomach Qi deficiency or Qi and Yin deficiency， which is particularly evident in the VT， RE， MH， and SF scales.

Objective To investigate the value of artificial intelligence-assisted compressed sensing (ACS) technology for intravenous gadolinium contrast-enhanced magnetic resonance imaging of the inner ear using three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) sequence. Methods The patients received gadolinium contrast-enhanced magnetic resonance imaging using ACS and united compressed sensing (uCS) 3D-FLAIR at Zhongshan Hospital, Fudan University from January to November 2024 were prospectively enrolled. The repetition time was 16 000 ms, and acquisition time was 6 min 40 s and 10 min 24 s in ACS 3D-FLAIR and uCS 3D-FLAIR, respectively. The images on the two sequences were evaluated independently by two radiologists. The image quality of the two sequences was subjectively evaluated and compared. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between the two sequences. The grading consistencies using two sequences and between the two doctors were analyzed. Results There was no statistically difference in subjective score of image quality between the two sequences. SNR and CNR of the ACS 3D-FLAIR sequence were significantly higher than those of the uCS 3D-FLAIR sequence (P＜0.001). The kappa values of grades of cochlear and vestibular endolymphatic hydrops were 0.942 and 0.888 using two sequences (P＜0.001). The kappa values of grades of cochlear and vestibular endolymphatic hydrops using the ACS 3D-FLAIR sequence between the two doctors were 0.784 and 0.831, respectively (P＜0.001); the kappa values of grades of cochlear and vestibular endolymphatic hydrops using uCS 3D-FLAIR sequence between the two doctors were 0.725 and 0.756, respectively (P＜0.001). Conclusions ACS 3D-FLAIR could provide higher SNR and CNR than uCS 3D-FLAIR, and is more suitable for intravenous gadolinium contrast-enhanced magnetic resonance imaging of the inner ear; the endolymphatic hydrops grades using ACS 3D-FLAIR is similar to use uCS 3D-FLAIR.

Objective: To investigate the nutritional status and influencing factors among Tibetan and Mongolian children and adolescents aged 7-18 years in high-altitude regions, so as to provide evidence for early prevention and control of malnutrition in this population. Methods: From May to June 2022, a cluster sampling method was employed to recruit 1 019 Tibetan and Mongolian children and adolescents aged 7-18 years from two primary and secondary schools in Golmud City. Physical examinations, dietary frequency questionnaires, and physical activity assessments were conducted. Nutritional status was classified as obesity, combined overweight/obesity, underweight, or central obesity according to national standards including Screening for Overweight and Obesity among School-age Children and Adolescents, Screening Standard for Malnutrition of School-age Children and Adolescents, Blue Book on Obesity Prevention and Control in China. Chi-square tests, t-test and Logistic regression analyses were performed to identify factors associated with different nutritional statuses. Results: The detection rates of obesity, combined overweight/obesity, underweight, and central obesity were 8.0%, 18.1%, 5.2%, and 19.7%, respectively. The height of children and adolescents across all age groups was generally lower than the national standard values. Tibetan participants exhibited significantly lower height-for-age Z-scores (HAZ)(9-10, 13-17 years, Z =2.01, 2.78, 4.16, 3.38, 4.12, 3.63, 3.00) and BMI-for-age Z-scores (BAZ) compared to Mongolian participants ( Z =-2.95, -2.47, -2.31, -2.89, -2.14, -2.17)( P < 0.05 ). Multivariate Logistic regression revealed that Mongolian children and adolescents had higher risks of obesity ( OR =2.20) and combined overweight/obesity ( OR = 2.18 ) ( P <0.05). Additionally, insufficient moderate-to-vigorous physical activity (MVPA) was associated with an increased risk of central obesity ( OR =1.48, P <0.05), compared with children and adolescents who meet the standard of MVPA. Conclusions The rates of overweight and obesity among Tibetan and Mongolian children and adolescents in Golmud City are higher, influenced by multiple factors. Nutrition interventions and physical activity strategies tailored to ethnic characteristics should be implemented, with emphasis on promoting MVPA to improve nutritional outcomes in this population.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.