1.Longitudinal Association of Changes in Metabolic Syndrome with Cognitive Function: 12-Year Follow-up of the Guangzhou Biobank Cohort Study
Yu Meng TIAN ; Wei Sen ZHANG ; Chao Qiang JIANG ; Feng ZHU ; Ya Li JIN ; Shiu Lun Au YEUNG ; Jiao WANG ; Kar Keung CHENG ; Tai Hing LAM ; Lin XU
Diabetes & Metabolism Journal 2025;49(1):60-79
Background:
The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies.
Methods:
MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function.
Results:
Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores.
Conclusion
Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.
2.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
3.Longitudinal Association of Changes in Metabolic Syndrome with Cognitive Function: 12-Year Follow-up of the Guangzhou Biobank Cohort Study
Yu Meng TIAN ; Wei Sen ZHANG ; Chao Qiang JIANG ; Feng ZHU ; Ya Li JIN ; Shiu Lun Au YEUNG ; Jiao WANG ; Kar Keung CHENG ; Tai Hing LAM ; Lin XU
Diabetes & Metabolism Journal 2025;49(1):60-79
Background:
The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies.
Methods:
MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function.
Results:
Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores.
Conclusion
Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.
4.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
5.Longitudinal Association of Changes in Metabolic Syndrome with Cognitive Function: 12-Year Follow-up of the Guangzhou Biobank Cohort Study
Yu Meng TIAN ; Wei Sen ZHANG ; Chao Qiang JIANG ; Feng ZHU ; Ya Li JIN ; Shiu Lun Au YEUNG ; Jiao WANG ; Kar Keung CHENG ; Tai Hing LAM ; Lin XU
Diabetes & Metabolism Journal 2025;49(1):60-79
Background:
The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies.
Methods:
MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function.
Results:
Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores.
Conclusion
Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.
6.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
7.Longitudinal Association of Changes in Metabolic Syndrome with Cognitive Function: 12-Year Follow-up of the Guangzhou Biobank Cohort Study
Yu Meng TIAN ; Wei Sen ZHANG ; Chao Qiang JIANG ; Feng ZHU ; Ya Li JIN ; Shiu Lun Au YEUNG ; Jiao WANG ; Kar Keung CHENG ; Tai Hing LAM ; Lin XU
Diabetes & Metabolism Journal 2025;49(1):60-79
Background:
The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies.
Methods:
MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function.
Results:
Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores.
Conclusion
Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.
8.Rapid health technology assessment of toripalimab combined with chemotherapy in the treatment of locally advanced or metastatic non-small cell lung cancer
Yuping YANG ; Yuan ZHOU ; Qirui TAI ; Mili SHI ; Yijie SHI ; Jieya WANG ; Huan HU ; Yuan ZHANG ; Yi LIU ; Yue WANG
China Pharmacy 2025;36(20):2593-2598
OBJECTIVE To evaluate the efficacy, safety and cost-effectiveness of toripalimab (Tor) combined with chemotherapy (CT) in the treatment of locally advanced or metastatic non-small cell lung cancer (NSCLC). METHODS PubMed, the Cochrane Library, Embase, Web of Science, CBM, CNKI, Wanfang Data, and Health Technology Assessment (HTA) related websites were searched to collect the HTA reports, systematic reviews/meta-analyses and pharmacoeconomic studies of Tor+CT in the treatment of locally advanced or metastatic NSCLC from database/website inception to March 31, 2025. After data extraction and quality evaluation, the results of the included studies were analyzed descriptively. RESULTS A total of eleven studies were included, involving five systematic reviews/meta-analyses, and six pharmacoeconomic studies. Among the five systematic reviews/ meta-analyses, two were of high quality, while there was one each of moderate, low, and very low quality. All six pharmacoeconomic studies were of good quality. In terms of efficacy, compared with CT, Tor+CT significantly improved patients’ progression-free survival (PFS) and overall survival (P<0.05). In addition, compared with ipilimumab+CT, durvalumab, durvalumab+tremelimumab and sugemalimab+CT, Tor+CT could also improve the PFS (P<0.05). In terms of safety, there was no significant difference in the incidence of grade≥3 adverse events between patients receiving Tor+CT and CT (P>0.05); while Tor+CT had a lower incidence of grade≥3 adverse E-mail: events, compared with camrelizumab+CT, pembrolizumab+ 3233255290@qq.com ipilimumab, nivolumab+CT and atezolizumab+CT (P<0.05).In terms of cost-effectiveness, Tor+CT treatment had certain cost-effectiveness advantages, compared with CT. CONCLUSIONS Compared with CT, other programmed death-1/programmed death-ligand 1 inhibitors alone, or their combination with CT, Tor+CT for the treatment of locally advanced or metastatic NSCLC has good efficacy, safety and cost-effectiveness.
9.Clinical Characteristics and Prognosis Analysis of Patients with Extranasal NK/T-Cell Lymphoma: A Multicenter Retrospective Study of Huaihai Lymphoma Working Group.
Hui-Rong SHAN ; Qing ZHANG ; Ling WANG ; Yu-Ye SHI ; Yu-Qing MIAO ; Tai-Gang ZHU ; Jing-Jing YE ; Xu-Dong ZHANG ; Liang WANG ; Zi-Yuan SHEN ; Wei SANG
Journal of Experimental Hematology 2025;33(1):93-100
OBJECTIVE:
To explore the clinical characteristics and prognostic factors of patients with extranasal NK/T-cell lymphoma (NKTCL).
METHODS:
The clinical data of 138 patients with NKTCL diagnosed in 10 medical centers of Huaihai Lymphoma Working Group from June 2015 to April 2021 were collected and analyzed retrospectively. The differences in clinicopathological characteristics of patients with different involvement and efficacy of pegaspargase regimen were compared, as well as perform survival analysis.
RESULTS:
A total of 138 extranasal NKTCL patients were included, with a median age of 46 years, and the ratio of males to females was approximately 2∶1. There were 39 patients with gastrointestinal involvement, 32 patients with oropharyngeal involvement, 17 patients with skin involvement, 11 patients with lymph node involvement, 11 patients with orbital involvement, and 28 patients with other parts involvement. Patients with skin involvement had a higher proportion of advanced disease and a lower proportion of CD56 positive rate compared to those with oropharyngeal involvement. Among the patients with gastrointestinal involvement, the survival rate of patients who received pegaspargase regimen was significantly higher than those who were treated without pegaspargase (P < 0.01). Multivariate analysis showed that serum creatinine was an independent prognostic factor for patients with skin involvement ( HR =1.027, 95%CI : 1.001-1.054, P =0.040), ECOG PS and EBV DNA were independent prognostic factors for patients with gastrointestinal involvement ( HR =2.635, 95%CI : 1.096-6.338, P =0.030; HR =4.772, 95% CI : 1.092-20.854, P =0.038), and ECOG PS and CA stage were independent prognostic factors for patients with oropharyngeal involvement ( HR =13.875, 95%CI : 2.517-76.496, P =0.002; HR =20.261, 95%CI : 2.466-166.470, P =0.005).
CONCLUSION
The clinicopathological characteristics of extranasal NKTCL patients with different sites of involvement are vary, and effective individualized treatment need to be further explored.
Adult
;
Aged
;
Female
;
Humans
;
Male
;
Middle Aged
;
Asparaginase/therapeutic use*
;
Lymphoma, Extranodal NK-T-Cell/pathology*
;
Prognosis
;
Retrospective Studies
;
Survival Rate
;
Polyethylene Glycols
10.Diffusion-based generative drug-like molecular editing with chemical natural language.
Jianmin WANG ; Peng ZHOU ; Zixu WANG ; Wei LONG ; Yangyang CHEN ; Kyoung Tai NO ; Dongsheng OUYANG ; Jiashun MAO ; Xiangxiang ZENG
Journal of Pharmaceutical Analysis 2025;15(6):101137-101137
Recently, diffusion models have emerged as a promising paradigm for molecular design and optimization. However, most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geometries, with limited research on molecular sequence diffusion models. The International Union of Pure and Applied Chemistry (IUPAC) names are more akin to chemical natural language than the Simplified Molecular Input Line Entry System (SMILES) for organic compounds. In this work, we apply an IUPAC-guided conditional diffusion model to facilitate molecular editing from chemical natural language to chemical language (SMILES) and explore whether the pre-trained generative performance of diffusion models can be transferred to chemical natural language. We propose DiffIUPAC, a controllable molecular editing diffusion model that converts IUPAC names to SMILES strings. Evaluation results demonstrate that our model outperforms existing methods and successfully captures the semantic rules of both chemical languages. Chemical space and scaffold analysis show that the model can generate similar compounds with diverse scaffolds within the specified constraints. Additionally, to illustrate the model's applicability in drug design, we conducted case studies in functional group editing, analogue design and linker design.

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