Abstract Short form video applications provide a new mode of online participation for college students, but also bring some problematic issues, especially short form video addiction among college students. The article expounds the definition, influencing factors and adverse impacts on physical and mental health of short form video addiction among college student users by systematically reviewing the existing domestic and foreign literature regarding college students short form addiction. Awareness should be raised among families, schools and society regarding college students addiction to short form video, and healthy usage of short form video are encouraged among college students to reduce the risk of addiction to short form video.

Abstract Cyberchondria is a growing mental health concern in the digital age, significantly impacting college students physical and psychological wellbeing as well as their daily functioning. The paper systematically reviews existing domestic and international literature to synthesize key aspects of cyberchondria among college students, including its conceptualization, measurement tools, prevalence, contributing factors, consequences, and intervention approaches. Building on the foundation, the study identifies critical gaps and proposes future research directions. By establishing a comprehensive theoretical framework, the work aims to inform subsequent studies and targeted interventions, ultimately supporting the promotion of mental and physical health among college students affected by cyberchondria.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To explore the clinical characteristics and healthcare burden in patients with McCune-Albright syndrome (MAS).Methods:A cross-sectional study was conducted at the Children′s Hospital, Zhejiang University School of Medicine. Clinical and healthcare burden data were systematically collected through structured questionnaires in 164 children with MAS from February 2022 to May 2023. According to the clinical characteristics, patients were categorized into 3 groups: monosymptomatic, bisymptomatic and trisymptomatic groups. Patients were also divided into 3 groups according to the age of <7, 7-<10 and 10-18 years. Comparative analyses of clinical characteristics and healthcare burden were conducted across age, sex, and symptom categories.Results:The cohort comprised 59 males (36.0%) and 105 females (64.0%) with an age of 4.6 (2.0, 7.4) years. Age stratification revealed 117 cases (71.3%) aged 0-<7 years, 29 cases (17.7%) aged 7-<10 years, and 18 cases (11.0%) aged 10-<18 years. Among monosymptomatic (67 cases, 40.9%), the cohort comprised 32 females (47.8%) and 35 males (52.2%), predominantly presenting with fibrous dysplasia (57 cases, 85.1%). This subgroup showed peak prevalence in the 0-<7 years age range (29 cases (50.9%)). The bisymptomatic cohort (56 cases, 34.1%) consisted of 39 females (69.6%) and 17 males (30.4%), predominantly manifesting fibrous dysplasia with skin hyperpigmentation (25 cases, 44.6%). Peak prevalence occurred in the 0-<7 years subgroup(16 cases (64.0%)). The trisymptomatic cohort (41 cases, 25.0%) consisted of 34 females (82.9%) and 7 males (17.1%), with peak prevalence occurring in the 0-<7 years subgroup (36 cases (87.8%)). The diagnostic journey analysis revealed 94 cases (57.3%) required 1-3 referrals, and 34 cases (20.7%) necessitated >3 referrals from symptom onset to definitive diagnosis. Healthcare expenditure analysis revealed 69 families (42.1%) incurred direct medical costs of 10 000-100 000 CNY, with 11 families (6.7%) exceeding >100 000 CNY. Direct non-medical costs reached of 10 000-100 000 CNY for 62 families (37.8%) and >100 000 CNY for 4 families (2.4%). Productivity loss affected 58 families (35.4%) at 10 000-100 000 CNY and 8 families (4.9%) above 100 000 CNY during the study period.Conclusion:MAS requires increased attention to skeletal manifestations, especially in children aged 0-<7 years. Moreover, the significant financial burden on families necessitates a society-wide support system.

Objective: To explore the effects of Cldn14 gene knockout on renal metabolism and stone formation in rats，so as to provide reference for research in the field of urinary calium metabolism and stone formation. Methods: Cldn14 gene knockout homozygous rats and wild-type rats of the same age were randomly divided into 4 groups：wild-type control (WC) group，wild-type ethylene glycol (WE) group，gene knockout control (KC) group and gene knockout ethylene glycol (KE) group，with 10 rats in each group.The WE and KE groups were induced with ethylene glycol + ammonium chloride to form kidney stones，while the WC and KC groups received normal saline gavage.After 4 weeks of standard maintenance feeding，the urine samples were collected to detect the venous blood.The kidneys were collected for HE，Pizzolatto's staining and transmission electron microscopy.The protein in renal tissues was extracted to detect the expressions of Claudin16 and Claudin19. Results: Crystal deposition was observed in the renal tubular lumen of the WE and the KE groups，and more crystals were detected in the KE group.The WE group had a large number of intracytoplasmic black crystalline inclusions observed in renal tubular epithelial cells under transmission electron microscope，followed by the KE and KC groups.Compared with WC and WE groups，KC and KE groups had significantly decreased serum calcium and magnesium levels but significantly increased urinary calcium level.In addition，the urinary calcium level was higher in the WE group than in the WC group and higher in the KE group than in the KC group.The KE group had lower level of Claudin16，but there was no significant difference in the level of Claudin19 among the 4 groups(P>0.05). Conclusion: Knockout of Cldn14 gene alone cannot effectively reduce urinary calcium excretion or reduce the risk of stone formation in rats，which may be related to the decrease of Claudin16 level.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To explore the clinical characteristics and healthcare burden in patients with McCune-Albright syndrome (MAS).Methods:A cross-sectional study was conducted at the Children′s Hospital, Zhejiang University School of Medicine. Clinical and healthcare burden data were systematically collected through structured questionnaires in 164 children with MAS from February 2022 to May 2023. According to the clinical characteristics, patients were categorized into 3 groups: monosymptomatic, bisymptomatic and trisymptomatic groups. Patients were also divided into 3 groups according to the age of <7, 7-<10 and 10-18 years. Comparative analyses of clinical characteristics and healthcare burden were conducted across age, sex, and symptom categories.Results:The cohort comprised 59 males (36.0%) and 105 females (64.0%) with an age of 4.6 (2.0, 7.4) years. Age stratification revealed 117 cases (71.3%) aged 0-<7 years, 29 cases (17.7%) aged 7-<10 years, and 18 cases (11.0%) aged 10-<18 years. Among monosymptomatic (67 cases, 40.9%), the cohort comprised 32 females (47.8%) and 35 males (52.2%), predominantly presenting with fibrous dysplasia (57 cases, 85.1%). This subgroup showed peak prevalence in the 0-<7 years age range (29 cases (50.9%)). The bisymptomatic cohort (56 cases, 34.1%) consisted of 39 females (69.6%) and 17 males (30.4%), predominantly manifesting fibrous dysplasia with skin hyperpigmentation (25 cases, 44.6%). Peak prevalence occurred in the 0-<7 years subgroup(16 cases (64.0%)). The trisymptomatic cohort (41 cases, 25.0%) consisted of 34 females (82.9%) and 7 males (17.1%), with peak prevalence occurring in the 0-<7 years subgroup (36 cases (87.8%)). The diagnostic journey analysis revealed 94 cases (57.3%) required 1-3 referrals, and 34 cases (20.7%) necessitated >3 referrals from symptom onset to definitive diagnosis. Healthcare expenditure analysis revealed 69 families (42.1%) incurred direct medical costs of 10 000-100 000 CNY, with 11 families (6.7%) exceeding >100 000 CNY. Direct non-medical costs reached of 10 000-100 000 CNY for 62 families (37.8%) and >100 000 CNY for 4 families (2.4%). Productivity loss affected 58 families (35.4%) at 10 000-100 000 CNY and 8 families (4.9%) above 100 000 CNY during the study period.Conclusion:MAS requires increased attention to skeletal manifestations, especially in children aged 0-<7 years. Moreover, the significant financial burden on families necessitates a society-wide support system.

Objective To explore the characteristics of blood vitamins A, B2, B6, B12, D, E, K1, K2 and folic acid and their correlation with severity in patients with metabolic-related fatty liver disease (MAFLD). Methods　From September to December 2022, a total of 473 cases of residents were recruited through community MAFLD screening activities and their health information was obtained through questionnaire survey and physical examination. The severity of hepatic steatosis was determined with FibroScan, and vitamin concentrations were determined with liquid chromatography-tandem mass spectrometry. Two independent samples' t-tests were used to assess the differences between the two groups, and univariate chi-square tests and multivariate logistic regression analysis were used to explore the related factors of MAFLD. Results　Of the 473 inhabitants, 195 (41.23%, 195/473) met the diagnostic criteria for MAFLD, including mild 43 (22.05%, 43/195) cases of fatty liver, 88 (45.13%, 88/195) cases of moderate fatty liver, and 64 (32.82%, 64/195) cases of severe fatty liver. Using healthy residents collected during the same period as controls, the overall mean of vitamins A, E, K1, and K2 in the MAFLD group was higher than that of the healthy group, with a statistical difference (P<0.05). Furthermore, the concentrations of vitamins A, E, K1 and K2 increased with the severity of fatty liver [R=0.149, P=0.004; R=0.245, P<0.001; R=0.110, P=0.032; R=0.129，P=0.012]. There were statistically significant differences (P<0.05) in the blood levels of vitamin A and E between patients with moderate or severe fatty liver and the healthy population. The blood vitamins K1 and K2 in severe fatty liver patients were also different from those of healthy people (P<0.05). However, there was no significance between folic acid, vitamin D, B2, B6, B12, and MAFLD (P>0.05). Through univariate chi-square analysis and multivariate logistic regression analysis, it was found that male [Wald=5.789, P=0.034，OR=1.598(1.037-2.463)] and vitamin E≥8.13 μg/mL[Wald=14.632，P<0.001，OR=2.378(1.522-3.674)] were risk factors for moderate and severe MAFLD. Conclusions The concentrations of vitamin A, E, and K in the blood are increased in patients with MAFLD compared to the healthy population, and they are positively correlated with the severity of MAFLD. ale gender and high levels of vitamin E may be related to moderate to severe MAFLD.

Postoperative pain seriously affects the recovery process of patients, resulting in prolonged hospital stay and increased care costs. Appropriate application of patient-controlled analgesia devices can effectively relieve perioperative acute pain. In 1994 patient-controlled analgesia began to be used in Peking Union Medical College Hospital, and the Acute Pain Service Working Group was established in 2004. With the cooperation of anesthesiologists and specialist nurses, the group jointly has implemented the whole process and standardized management based on patient-controlled analgesia, and constantly improved and innovated working methods, laying a solid foundation for the development of postoperative pain management. This paper systematically reviews and summarizes the work from the aspects of clinical focus, nursing management experience, promotion and dissemination of pain treatment concepts, and development of acute pain service model under the new situation, with the hope of providing valuable reference for comprehensively strengthening pain management in the process of diagnosis and treatment, and enhancing patients' satisfaction with perioperative analgesia services.

Objective To observe the value of lumbar spine bone marrow MR T1 mapping radiomics for predicting clinical risk of acute lymphoblastic leukemia(ALL)in children.Methods Lumbar bone marrow T1 mappings were prospectively acquired from 77 newly diagnosed ALL children.The volume of interest(VOI)of L3 vertebral body was segmented using 3D Slicer software and 2 060 radiomics features were extracted,and the best features were screened.The children were divided into training and testing sets at the ratio of 8:2.Logistic regression(LR),support vector machine(SVM)and random forest(RF)were used to established radiomics models based on the best features,respectively,which were trained in training set and verified in testing set.The clinical risk was evaluated according to newly diagnosed risk and the response to chemotherapy after MR examination.Receiver operating characteristic(ROC)curve was drawn,and the area under the curve(AUC)was calculated to evaluate the efficacy of each model for predicting clinical risk of ALL in children.Results There were 52 cases in low-medium risk group and 25 in high risk group.The training set consisted of 44 cases of low-medium risk and 17 of high risk,while the testing set consisted of 8 cases of low-medium risk and 8 of high risk.Twelve best features were selected to establish radiomics models.The sensitivity and accuracy of RF model in training set were both 100％,but its sensitivity(50.00％)and accuracy(75.00％)in testing set were both low,which indicating overfitting.The AUC(0.95)of LR model was slightly higher than that of SVM model(0.92)in testing set,but no significantly difference was found(P＞0.05),and the accuracy of these two models was consistent.Conclusion Both lumbar bone marrow T1 mapping LR and SVM radiomics models could be used to predict clinical risk of ALL in children,and LR model had better predictive efficacy.