1.Research progress in intervention among children and adolescents suffered from adverse childhood experiences
XU Zixuan,CHEN Yinxing,JIN Jiahui,HUANG Hai,ZHOU Chunyan
Chinese Journal of School Health 2026;47(4):604-608
Abstract
Adverse childhood experiences (ACEs) exposure is a pressing and severe global public health issue. Children and adolescents exposed to multiple ACEs are highly susceptible to toxic stress and impaired physiological functioning, which significantly jeopardize their physical and mental health. Effective prevention and intervention strategies can reduce the prevalence of ACEs and mitigate their severe impacts, thereby minimizing the long term detrimental consequences on future outcomes. The review provides a comprehensive review of intervention strategies across four dimensions: individual, family, school, and public services/policy, so as to establish a theoretical foundation for implementing effective interventions for children and adolescents exposed to adverse childhood experiences.
2.Research progress on interventions for adolescent non suicidal self injury stigma
JIN Jiahui, FANG Qiaofen, MENG Genhua, HUANG Hai, XUE Jiao, XIE Jin, TANG Zhenghua
Chinese Journal of School Health 2026;47(6):908-912
Abstract
Adolescents are a high risk group for non suicidal self injury (NSSI), and the severity of the issue has been increasing. However, stigma originating from self perceptions, the public, and healthcare professionals poses significant barriers to help seeking and recovery among adolescents with NSSI. The paper systematically reviews the main intervention strategies targeting NSSI related stigma in adolescents, along with their effectiveness, from three perspectives: educational approaches, contact based interventions, and public advocacy against stigma, aiming to inform the development of a scientific, effective, and multi stakeholder collaborative integrated intervention framework to provide a basis for reducing and ultimately eliminating stigma associated with adolescent NSSI.
3.Multiparametric MRI to Predict Gleason Score Upgrading and Downgrading at Radical Prostatectomy Compared to Presurgical Biopsy
Jiahui ZHANG ; Lili XU ; Gumuyang ZHANG ; Daming ZHANG ; Xiaoxiao ZHANG ; Xin BAI ; Li CHEN ; Qianyu PENG ; Zhengyu JIN ; Hao SUN
Korean Journal of Radiology 2025;26(5):422-434
Objective:
This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy.
Materials and Methods:
Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP.
Results:
The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001).
Conclusion
Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.
4.Triglyceride-glucose index and homocysteine in association with the risk of stroke in middle-aged and elderly diabetic populations
Xiaolin LIU ; Jin ZHANG ; Zhitao LI ; Xiaonan WANG ; Juzhong KE ; Kang WU ; Hua QIU ; Qingping LIU ; Jiahui SONG ; Jiaojiao GAO ; Yang LIU ; Qian XU ; Yi ZHOU ; Xiaonan RUAN
Shanghai Journal of Preventive Medicine 2025;37(6):515-520
ObjectiveTo investigate the triglyceride-glucose (TyG) index and the level of serum homocysteine (Hcy) in association with the incidence of stroke in type 2 diabetes mellitus (T2DM) patients. MethodsBased on the chronic disease risk factor surveillance cohort in Pudong New Area, Shanghai, excluding those with stroke in baseline survey, T2DM patients who joined the cohort from January 2016 to October 2020 were selected as the research subjects. During the follow-up period, a total of 318 new-onset ischemic stroke patients were selected as the case group, and a total of 318 individuals matched by gender without stroke were selected as the control group. The Cox proportional hazards regression model was used to adjust for confounding factors and explore the serum TyG index and the Hcy biochemical indicator in association with the risk of stroke. ResultsThe Cox proportional hazards regression results showed that after adjusting for confounding factors, the risk of stroke in T2DM patients with 10 μmol·L⁻¹
5.Multiparametric MRI to Predict Gleason Score Upgrading and Downgrading at Radical Prostatectomy Compared to Presurgical Biopsy
Jiahui ZHANG ; Lili XU ; Gumuyang ZHANG ; Daming ZHANG ; Xiaoxiao ZHANG ; Xin BAI ; Li CHEN ; Qianyu PENG ; Zhengyu JIN ; Hao SUN
Korean Journal of Radiology 2025;26(5):422-434
Objective:
This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy.
Materials and Methods:
Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP.
Results:
The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001).
Conclusion
Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.
6.Multiparametric MRI to Predict Gleason Score Upgrading and Downgrading at Radical Prostatectomy Compared to Presurgical Biopsy
Jiahui ZHANG ; Lili XU ; Gumuyang ZHANG ; Daming ZHANG ; Xiaoxiao ZHANG ; Xin BAI ; Li CHEN ; Qianyu PENG ; Zhengyu JIN ; Hao SUN
Korean Journal of Radiology 2025;26(5):422-434
Objective:
This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy.
Materials and Methods:
Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP.
Results:
The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001).
Conclusion
Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.
7.Multiparametric MRI to Predict Gleason Score Upgrading and Downgrading at Radical Prostatectomy Compared to Presurgical Biopsy
Jiahui ZHANG ; Lili XU ; Gumuyang ZHANG ; Daming ZHANG ; Xiaoxiao ZHANG ; Xin BAI ; Li CHEN ; Qianyu PENG ; Zhengyu JIN ; Hao SUN
Korean Journal of Radiology 2025;26(5):422-434
Objective:
This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy.
Materials and Methods:
Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP.
Results:
The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001).
Conclusion
Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.
8.Multiparametric MRI to Predict Gleason Score Upgrading and Downgrading at Radical Prostatectomy Compared to Presurgical Biopsy
Jiahui ZHANG ; Lili XU ; Gumuyang ZHANG ; Daming ZHANG ; Xiaoxiao ZHANG ; Xin BAI ; Li CHEN ; Qianyu PENG ; Zhengyu JIN ; Hao SUN
Korean Journal of Radiology 2025;26(5):422-434
Objective:
This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy.
Materials and Methods:
Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP.
Results:
The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001).
Conclusion
Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.
9.Analysis of clinical feature and genetic variant in a Chinese Han pedigree affected with Darier′s disease
Shide ZHANG ; Miao JIANG ; Rong LIN ; Jiahui JIN ; Jingjun ZHAO
Chinese Journal of Medical Genetics 2025;42(2):206-211
Objective:To explore the clinical phenotype and genetic characteristics of a Chinese Han pedigree with Darier′s disease(DD).Methods:A DD pedigree, who visited Tongji Hospital of Tongji University on October 22, 2023, was selected as the study subject. Clinical data of the pedigree were collected, and whole-genome exom sequencing was performed on the proband. Suspected variant loci were screened, and Sanger sequencing was used to validate the variant in pedigree members. Bioinformatics analysis was performed on the variant loci. This study was approved by the Medical Ethics Committee of Tongji Hospital of Tongji University(Ethics No.K-W-2024-004).Results:① The proband is a 67-year-old female with clinical features of DD, such as keratotic papules in sebaceous areas. ② Whole-genome exom sequencing revealed a missense variant, c. 68G>A (p.Gly23Glu), in the exon 1 of ATP2A2 gene of the proband. Sanger sequencing showed that the proband′s eldest daughter also carried this variant. This variant was not detected in other pedigree members, indicating a co-segregation of the variant with the disease phenotype in the pedigree. ③ According to the interpretation principles of gene variants by the American College of Medical Genetics and Genomics (ACMG), this variant was classified as pathogenic (PS1+ PM1+ PM2_Supporting+ PP1+ PP3+ PP4). Conclusions:The c. 68G>A (p.Gly23Glu) variant in the ATP2A2 gene may be the genetic cause of the disease in this pedigree. This finding further enriches the genetic variant spectrum in DD patients and provides a basis for clinical diagnosis and genetic counseling for patients.
10.One case of eustachian tube hairy polyp was removed by microscope combined with endoscope.
Jiahui JIN ; Bo CAO ; Huanxin YU ; Feifan QI ; Guangping LIU
Journal of Clinical Otorhinolaryngology Head and Neck Surgery 2025;39(6):578-581
This paper reports the diagnosis and treatment of a child with eustachian hairy polyp. The patient was a female, aged 1 year and 4 months, and visited our clinic due to "intermittent purulent discharge of the left ear, nasal congestion and sleep snoring for 1 year". Preoperative endoscopic examination found white masses at the posterior part of the nasal cavity on both sides. The imaging findings showed masses with streaks and circular-like mixed signal accompanied by slightly uneven enhancement at the left eustachian duct and the posterior wall of the nasopharyngeal cavity, and soft tissue density in the left tympanic antrum. Left modified radical mastoidectomy and radical endoscopic resection surgery for nasopharyngeal tumors was performed under general anesthesia. Histopathological examination revealed polyp of the left eustachian tube hair. The patient's symptoms improved after surgery, and no tumor recurrence was found after 3 months of follow-up.
Humans
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Female
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Eustachian Tube/surgery*
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Polyps/surgery*
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Infant
;
Endoscopy


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