1.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.
2.Influence mechanism of peer attachment on school adaptation of migrant children: the role of psychological resilience and sense of security
Xiaoyan ZHAO ; Min JIN ; Li HAN ; Birui LI ; Peng WANG ; Zanheng ZOU
Sichuan Mental Health 2025;38(3):273-278
BackgroundMigrant children face many challenges in the process of social change and adaptation to a new environment, especially in school adaptation. Studies have shown that peer attachment plays a vital role in the social adaptation of children and adolescents, while psychological resilience and sense of security, as important psychological resources, also play a moderating and mediating role in individuals' coping with environmental changes. However, there is a lack of systematic research on how peer attachment affects the school adaptation of migrant children through psychological resilience and whether this process is moderated by sense of security. ObjectiveTo explore the relationship between peer attachment and school adaptation of migrant children and to examine the path of psychological resilience and sense of security in it, so as to provide references for improving the school adaptation of migrant children. MethodsUsing cluster sampling method, 695 migrant children in grades 4 to 6 of a primary school in an urban-rural fringe area of Sichuan Province were selected from April 1 to 30, 2022. Assessments were conducted using Revised Inventory for Parent and Peer Attachment (IPPA-R), Resilience Scale for Chinese Adolescents (RSCA), Scale of Sense of Security of Children Left Behind (SSSCLB) and Scale of School Adjustment of Student (SSAS). Process 4.1 was used to examine the role of psychological resilience and sense of security. ResultsA total of 631 (90.79%) valid questionnaires were gathered. There were significant positive correlations among IPPA-R peer attachment subscale score, RSCA score, SSSCLB score and SSAS score (r=0.160~0.600, P<0.01). Peer attachment had a significant positive predictive effect on the school adaptation (β=0.178, P<0.01) and psychological resilience (β=0.518, P<0.01) of migrant children. Psychological resilience had positive predictive effect on the school adaptation (β=0.467, P<0.01). Psychological resilience played a partial mediating role in the relationship between peer attachment and school adaptation, with the mediating effect value was 0.242 (95% CI: 0.184~0.302), accounting for 57.62% of the total effect. Moreover, the interaction term between psychological resilience and sense of security had a significant predictive effect on school adaptation (β=0.103, P<0.01). ConclusionThe psychological resilience of migrant children plays a partial mediating role in the relationship between peer attachment and school adaptation, and the status of sense of security can moderate the relationship between psychological resilience and school adaptation of migrant children.
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.De novo patients with high-volume metastatic hormone-sensitive prostate cancer can benefit from the addition of docetaxel to triplet therapy: Network-analysis and systematic review.
Hanxu GUO ; Chengqi JIN ; Li DING ; Jun XIE ; Jing XU ; Ruiliang WANG ; Hong WANG ; Changcheng GUO ; Jiansheng ZHANG ; Bo PENG ; Xudong YAO ; Jing YUAN ; Bin YANG
Chinese Medical Journal 2025;138(2):231-233
5.Alzheimer's disease diagnosis among dementia patients via blood biomarker measurement based on the AT(N) system.
Tianyi WANG ; Li SHANG ; Chenhui MAO ; Longze SHA ; Liling DONG ; Caiyan LIU ; Dan LEI ; Jie LI ; Jie WANG ; Xinying HUANG ; Shanshan CHU ; Wei JIN ; Zhaohui ZHU ; Huimin SUI ; Bo HOU ; Feng FENG ; Bin PENG ; Liying CUI ; Jianyong WANG ; Qi XU ; Jing GAO
Chinese Medical Journal 2025;138(12):1505-1507
6.Current status of generalized pustular psoriasis: Findings from a multicenter hospital-based survey of 127 Chinese patients.
Haimeng WANG ; Jiaming XU ; Xiaoling YU ; Siyu HAO ; Xueqin CHEN ; Bin PENG ; Xiaona LI ; Ping WANG ; Chaoyang MIAO ; Jinzhu GUO ; Qingjie HU ; Zhonglan SU ; Sheng WANG ; Chen YU ; Qingmiao SUN ; Minkuo ZHANG ; Bin YANG ; Yuzhen LI ; Zhiqiang SONG ; Songmei GENG ; Aijun CHEN ; Zigang XU ; Chunlei ZHANG ; Qianjin LU ; Yan LU ; Xian JIANG ; Gang WANG ; Hong FANG ; Qing SUN ; Jie LIU ; Hongzhong JIN
Chinese Medical Journal 2025;138(8):953-961
BACKGROUND:
Generalized pustular psoriasis (GPP), a rare and recurrent autoinflammatory disease, imposes a substantial burden on patients and society. Awareness of GPP in China remains limited.
METHODS:
This cross-sectional survey, conducted between September 2021 and May 2023 across 14 hospitals in China, included GPP patients of all ages and disease phases. Data collected encompassed demographics, clinical characteristics, economic impact, disease severity, quality of life, and treatment-related complications. Risk factors for GPP recurrence were analyzed.
RESULTS:
Among 127 patients (female/male ratio = 1.35:1), the mean age of disease onset was 25 years (1st quartile [Q1]-3rd quartile [Q3]: 11-44 years); 29.2% had experienced GPP for more than 10 years. Recurrence occurred in 75.6% of patients, and nearly half reported no identifiable triggers. Younger age at disease onset ( P = 0.021) and transitioning to plaque psoriasis ( P = 0.022) were associated with higher recurrence rates. The median diagnostic delay was 8 months (Q1-Q3: 2-41 months), and 32.3% of patients reported misdiagnoses. Comorbidities were present in 53.5% of patients, whereas 51.1% experienced systemic complications during treatment. Depression and anxiety affected 84.5% and 95.6% of patients, respectively. During GPP flares, the median Dermatology Life Quality Index score was 19.0 (Q1-Q3: 13.0-23.5). This score showed significant differences between patients with and without systemic symptoms; it demonstrated correlations with both depression and anxiety scores. Treatment costs caused financial hardship in 55.9% of patients, underscoring the burden associated with GPP.
CONCLUSIONS
The substantial disease and economic burdens among Chinese GPP patients warrant increased attention. Patients with early onset disease and those transitioning to plaque psoriasis require targeted interventions to mitigate the high recurrence risk.
Humans
;
Male
;
Female
;
Psoriasis/pathology*
;
Adult
;
Cross-Sectional Studies
;
Adolescent
;
Child
;
Young Adult
;
Quality of Life
;
Middle Aged
;
China/epidemiology*
;
Recurrence
;
Risk Factors
;
Surveys and Questionnaires
;
East Asian People
7.Advances in nanocarrier-mediated cancer therapy: Progress in immunotherapy, chemotherapy, and radiotherapy.
Yue PENG ; Min YU ; Bozhao LI ; Siyu ZHANG ; Jin CHENG ; Feifan WU ; Shuailun DU ; Jinbai MIAO ; Bin HU ; Igor A OLKHOVSKY ; Suping LI
Chinese Medical Journal 2025;138(16):1927-1944
Cancer represents a major worldwide disease burden marked by escalating incidence and mortality. While therapeutic advances persist, developing safer and precisely targeted modalities remains imperative. Nanomedicines emerges as a transformative paradigm leveraging distinctive physicochemical properties to achieve tumor-specific drug delivery, controlled release, and tumor microenvironment modulation. By synergizing passive enhanced permeation and retention effect-driven accumulation and active ligand-mediated targeting, nanoplatforms enhance pharmacokinetics, promote tumor microenvironment enrichment, and improve cellular internalization while mitigating systemic toxicity. Despite revolutionizing cancer therapy through enhanced treatment efficacy and reduced adverse effects, translational challenges persist in manufacturing scalability, longterm biosafety, and cost-efficiency. This review systematically analyzes cutting-edge nanoplatforms, including polymeric, lipidic, biomimetic, albumin-based, peptide engineered, DNA origami, and inorganic nanocarriers, while evaluating their strategic advantages and technical limitations across three therapeutic domains: immunotherapy, chemotherapy, and radiotherapy. By assessing structure-function correlations and clinical translation barriers, this work establishes mechanistic and translational references to advance oncological nanomedicine development.
Humans
;
Neoplasms/radiotherapy*
;
Immunotherapy/methods*
;
Nanoparticles/chemistry*
;
Animals
;
Nanomedicine/methods*
;
Drug Delivery Systems/methods*
;
Drug Carriers/chemistry*
;
Radiotherapy/methods*
8.Research progress on the comorbidity mechanism of sarcopenia and obesity in the aging population.
Hao-Dong TIAN ; Yu-Kun LU ; Li HUANG ; Hao-Wei LIU ; Hang-Lin YU ; Jin-Long WU ; Han-Sen LI ; Li PENG
Acta Physiologica Sinica 2025;77(5):905-924
The increasing prevalence of aging has led to a rising incidence of comorbidity of sarcopenia and obesity, posing significant burdens on socioeconomic and public health. Current research has systematically explored the pathogenesis of each condition; however, the mechanisms underlying their comorbidity remain unclear. This study reviews the current literature on sarcopenia and obesity in the aging population, focusing on their shared biological mechanisms, which include loss of autophagy, abnormal macrophage function, mitochondrial dysfunction, and reduced sex hormone secretion. It also identifies metabolic mechanisms such as insulin resistance, vitamin D metabolism abnormalities, dysregulation of iron metabolism, decreased levels of nicotinamide adenine dinucleotide, and gut microbiota imbalances. Additionally, this study also explores the important role of genetic factors, such as alleles and microRNAs, in the co-occurrence of sarcopenia and obesity. A better understanding of these mechanisms is vital for developing clinical interventions and preventive strategies.
Humans
;
Sarcopenia/physiopathology*
;
Obesity/physiopathology*
;
Aging/physiology*
;
Autophagy/physiology*
;
Insulin Resistance
;
Comorbidity
;
Vitamin D/metabolism*
;
Gonadal Steroid Hormones/metabolism*
;
Gastrointestinal Microbiome
;
Mitochondria
;
MicroRNAs
9.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.
10.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.

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