1.Validating Multicenter Cohort Circular RNA Model for Early Screening and Diagnosis of Gestational Diabetes Mellitus
Shuo MA ; Yaya CHEN ; Zhexi GU ; Jiwei WANG ; Fengfeng ZHAO ; Yuming YAO ; Gulinaizhaer ABUDUSHALAMU ; Shijie CAI ; Xiaobo FAN ; Miao MIAO ; Xun GAO ; Chen ZHANG ; Guoqiu WU
Diabetes & Metabolism Journal 2025;49(3):462-474
Background:
Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed.
Methods:
High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression.
Results:
Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts.
Conclusion
Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.
2.Validating Multicenter Cohort Circular RNA Model for Early Screening and Diagnosis of Gestational Diabetes Mellitus
Shuo MA ; Yaya CHEN ; Zhexi GU ; Jiwei WANG ; Fengfeng ZHAO ; Yuming YAO ; Gulinaizhaer ABUDUSHALAMU ; Shijie CAI ; Xiaobo FAN ; Miao MIAO ; Xun GAO ; Chen ZHANG ; Guoqiu WU
Diabetes & Metabolism Journal 2025;49(3):462-474
Background:
Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed.
Methods:
High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression.
Results:
Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts.
Conclusion
Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.
3.Validating Multicenter Cohort Circular RNA Model for Early Screening and Diagnosis of Gestational Diabetes Mellitus
Shuo MA ; Yaya CHEN ; Zhexi GU ; Jiwei WANG ; Fengfeng ZHAO ; Yuming YAO ; Gulinaizhaer ABUDUSHALAMU ; Shijie CAI ; Xiaobo FAN ; Miao MIAO ; Xun GAO ; Chen ZHANG ; Guoqiu WU
Diabetes & Metabolism Journal 2025;49(3):462-474
Background:
Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed.
Methods:
High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression.
Results:
Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts.
Conclusion
Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.
4.Validating Multicenter Cohort Circular RNA Model for Early Screening and Diagnosis of Gestational Diabetes Mellitus
Shuo MA ; Yaya CHEN ; Zhexi GU ; Jiwei WANG ; Fengfeng ZHAO ; Yuming YAO ; Gulinaizhaer ABUDUSHALAMU ; Shijie CAI ; Xiaobo FAN ; Miao MIAO ; Xun GAO ; Chen ZHANG ; Guoqiu WU
Diabetes & Metabolism Journal 2025;49(3):462-474
Background:
Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed.
Methods:
High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression.
Results:
Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts.
Conclusion
Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.
5.The predictive value of 18F-FDG PET/CT metabolic heterogeneity parameters combined with clinical features for the prognosis of esophageal squamous cell carcinoma before definitive radiochemotherapy
Xiya MA ; Hu JI ; Zehua ZHU ; Bo PAN ; Qiang XIE ; Xiaobo YAO
The Journal of Practical Medicine 2024;40(7):966-971
Objective This study aimed to explore the prognostic value of 18F-FDG PET/CT Metabolic and Heterogeneity Parameters Combined with Clinical Features Before Definitive Chemoradiotherapy(D-CRT)in predicting the prognosis of esophageal squamous cell carcinoma(ESCC)Patients.Methods A retrospective analysis was conducted on clinical data from 106 patients with ESCC who received D-CRT at the first affiliated Hospital of University of Science and Technology of China between January 2017 and December 2021.All patients underwent 18F-FDG PET/CT examination before the treatment.The primary tumor′s metabolic and heterogeneity parameters were obtained through data processing.All patients were followed up for overall survival.The Kaplan-Meier method and Cox proportional hazards models were used to analyze the association between clinical features,tumor metabo-lism and heterogeneity parameters and patient prognosis.Results The 1-and 1.5-year overall survival rates of all patients were 77.4%and 51.9%.The median survival time was 20 months.Univariate analysis showed that N stage,M stage,metabolic tumor volume,total lesion glycolysis,heterogeneity index-2(HI-2),and coefficient of variation with a threshold of 40%maximum standard uptake value(CV40%)were correlated with the prognosis of ESCC(all P<0.05).Multivariate analysis showed that N stage and CV40%were independent predictors of prognosis in patients with ESCC(P = 0.039 and P<0.001,respectively).Conclusion N stage and tumor metabolic heterogeneity parameter CV40%,which offering a degree of predictive value,are closely related to the prognosis of patients with ESCC treated with D-CRT.
6.Analysis of risk factors of pleural effusion after spinal separation
Keyi WANG ; Hao QU ; Wen WANG ; Zhaonong YAO ; Xiaowei ZHOU ; Yuhong YAO ; Hengyuan LI ; Peng LIN ; Xiumao LI ; Xiaobo YAN ; Meng LIU ; Xin HUANG ; Nong LIN ; Zhaoming YE
Chinese Journal of Orthopaedics 2024;44(3):169-176
Objective:To investigate the risk factors of pleural effusion after spinal separation surgery for patients with spinal metastatic tumors.Methods:A total of 427 patients with spinal metastatic tumors from January 2014 to January 2022 in the Second Affiliated Hospital of Zhejiang University School of Medicine were retrospectively analyzed. There were 252 males and 175 females, with an average age of 59±12 years (range, 15-87 years). All patients underwent separation surgery. Based on the chest CT within 1 month after surgery, the volume of pleural effusion was measured individually by reconstruction software. Pleural effusion was defined as small volume (0-500 ml), moderate volume (500-1 000 ml), and large volume (above 1 000 ml). Baseline data and perioperative clinical outcomes were compared between the groups, and indicators with statistically significant differences were included in a binary logistic regression analysis to determine the independent risk factors for the development of pleural effusion after isolation of spinal metastatic cancer. Receiver operating characteristic (ROC) curves were conducted to calculate the area under the curve (AUC) for each independent risk factor.Results:All patients successfully completed the operation. Among the 427 patients, there were 35 cases of large pleural effusion, 42 cases of moderate pleural effusion, and 350 cases of small pleural effusion. There were significant differences in tumor size (χ 2=9.485, P=0.013), intraoperative blood loss ( Z=-2.503, P=0.011), blood transfusion ( Z=-2.983, P=0.003), preoperative total protein ( Z=2.681, P=0.007), preoperative albumin ( Z=1.720, P= 0.085), postoperative hemoglobin ( t=2.950, P=0.008), postoperative total protein ( Z=4.192, P<0.001), and postoperative albumin ( t=2.268, P=0.032) in the large pleural effusion group versus the small and moderate pleural effusion group. Logistic regression analysis showed that decreased preoperative albumin ( OR=0.89, P=0.045) and metastases located in the thoracic spine ( OR=4.01, P=0.039) were independent risk factors for the occurrence of large pleural effusion after separation surgery. The ROC curve showed that the AUC and 95% CI for preoperative albumin, lesion location, and the combined model were 0.637 (0.54, 0.74), 0.421 (0.36, 0.48), and 0.883 (0.81, 0.92). The combined predictive model showed good predictive value. Conclusion:The volume of pleural effusion can be measured individually and quantitatively based on chest CT. Decreased preoperative albumin and metastases located in the thoracic spine are independent risk factors for the occurrence of large pleural effusion after separation surgery. The combined prediction of the two factors has better predictive efficacy.
7.The development and implementation of a 3D technology-based female bed urinal
Yanling CHEN ; Hongyan LI ; Xiaobo WANG ; Shanshan XU ; Yuhong YAO ; Ping WANG ; Xiaomei SUN
Chinese Journal of Nursing 2024;59(18):2297-2300
Objective To utilize a 3D technology in the design of a female bed urinal and to evaluate its clinical efficacy.Methods A total of 102 adult female fracture patients with normal urination function admitted to a tertiary hospital in Hangzhou City from October 2022 to June 2023 were included in the study.They were divided into a control group(n=51)and an experimental group(n=51)according to random number method.Patients in control group used a regular urinal,while patients in the experimental group used the 3D technology-based female bed urinal.The level of physical pain caused by urination,the rate of urine immersion in the sacrococcygeal or gluteal cleft and the rate of bed unit or clothing of contamination were compared between the 2 groups.Results There was no significant difference in the rate of bed unit or clothing contamination between the 2 groups(P>0.05).However,the experimental group experienced significantly lower pain caused by urination,a lower rate of urine impregnation in the sacrococcygeal or gluteal fissure(P<0.001),compared to the control group.Conclusion The 3D technology-based female bed urinal has reasonable structure and simple operation,which can significantly reduce the physical pain caused by the change of body position,reduce the incidence of urine immersion events.
8.Advances in targeted delivery of proteolysis targeting chimeras in cancer therapy.
Xiaobo WU ; Jie ZHAO ; Yuan GAO ; Qingxin YAO ; Jianjun XIE
Chinese Journal of Biotechnology 2023;39(9):3628-3643
Small-molecule anticancer drugs inhibited tumor growth based on targeted inhibition of specific proteins, while most of oncogenic proteins are "undruggable". Proteolysis targeting chimeras (PROTAC) is an attractive and general strategy for treating cancer based on targeted degradation of oncogenic proteins. This review briefly describes the peptide-based PTOTAC and small molecule-based PROTAC. Subsequently, we summarize the development of targeted delivery of PROTAC, such as targeting molecule-mediated targeted delivery of PROTAC, nanomaterial-mediated targeted delivery of PROTAC and controllable activation of small-molecular PROTAC prodrug. Such strategies show potential application in improving tumor selectivity, overcoming off-target effect and reducing biotoxicity. At the end, the druggability of PROTAC is prospected.
Humans
;
Proteolysis Targeting Chimera
;
Nanostructures
;
Neoplasms/drug therapy*
;
Proteolysis
9.Cryo-EM structures of a prokaryotic heme transporter CydDC.
Chen ZHU ; Yanfeng SHI ; Jing YU ; Wenhao ZHAO ; Lingqiao LI ; Jingxi LIANG ; Xiaolin YANG ; Bing ZHANG ; Yao ZHAO ; Yan GAO ; Xiaobo CHEN ; Xiuna YANG ; Lu ZHANG ; Luke W GUDDAT ; Lei LIU ; Haitao YANG ; Zihe RAO ; Jun LI
Protein & Cell 2023;14(12):919-923
10.Efficacy and safety of mitoxantrone hydrochloride liposome injection in treatment of peripheral T-cell lymphomas: a multicenter, non-interventional, ambispective cohort, real-world study (MOMENT)
Huiqiang HUANG ; Zhiming LI ; Lihong LIU ; Liang HUANG ; Jie JIN ; Hongyan TONG ; Hui ZHOU ; Zengjun LI ; Zhenqian HUANG ; Wenbin QIAN ; Kaiyang DING ; Quande LIN ; Ming HOU ; Yunhong HUANG ; Jingbo WANG ; Pengcheng HE ; Xiuhua SUN ; Xiaobo WANG ; Zunmin ZHU ; Yao LIU ; Jinhai REN ; Huijing WU ; Liling ZHANG ; Hao ZHANG ; Liangquan GENG ; Jian GE ; Ou BAI ; Liping SU ; Guangxun GAO ; Xin LI ; Yanli YANG ; Yijian CHEN ; Aichun LIU ; Xin WANG ; Yi WANG ; Liqun ZOU ; Xiaobing HUANG ; Dongping HUANG ; Shujuan WEN ; Donglu ZHAO ; Jun MA
Journal of Leukemia & Lymphoma 2023;32(8):457-464
Objective:To evaluate the efficacy and safety of mitoxantrone hydrochloride liposome injection in the treatment of peripheral T-cell lymphoma (PTCL) in a real-world setting.Methods:This was a real-world ambispective cohort study (MOMENT study) (Chinese clinical trial registry number: ChiCTR2200062067). Clinical data were collected from 198 patients who received mitoxantrone hydrochloride liposome injection as monotherapy or combination therapy at 37 hospitals from January 2022 to January 2023, including 166 patients in the retrospective cohort and 32 patients in the prospective cohort; 10 patients in the treatment-na?ve group and 188 patients in the relapsed/refractory group. Clinical characteristics, efficacy and adverse events were summarized, and the overall survival (OS) and progression-free survival (PFS) were analyzed.Results:All 198 patients were treated with mitoxantrone hydrochloride liposome injection for a median of 3 cycles (range 1-7 cycles); 28 cases were treated with mitoxantrone hydrochloride liposome injection as monotherapy, and 170 cases were treated with the combination regimen. Among 188 relapsed/refractory patients, 45 cases (23.9%) were in complete remission (CR), 82 cases (43.6%) were in partial remission (PR), and 28 cases (14.9%) were in disease stabilization (SD), and 33 cases (17.6%) were in disease progression (PD), with an objective remission rate (ORR) of 67.6% (127/188). Among 10 treatment-na?ve patients, 4 cases (40.0%) were in CR, 5 cases (50.0%) were in PR, and 1 case (10.0%) was in PD, with an ORR of 90.0% (9/10). The median follow-up time was 2.9 months (95% CI 2.4-3.7 months), and the median PFS and OS of patients in relapsed/refractory and treatment-na?ve groups were not reached. In relapsed/refractory patients, the difference in ORR between patients with different number of treatment lines of mitoxantrone hydrochloride liposome injection [ORR of the second-line, the third-line and ≥the forth-line treatment was 74.4% (67/90), 73.9% (34/46) and 50.0% (26/52)] was statistically significant ( P = 0.008). Of the 198 PTCL patients, 182 cases (91.9%) experienced at least 1 time of treatment-related adverse events, and the incidence rate of ≥grade 3 adverse events was 66.7% (132/198), which was mainly characterized by hematologic adverse events. The ≥ grade 3 hematologic adverse events mainly included decreased lymphocyte count, decreased neutrophil count, decreased white blood cell count, and anemia; non-hematologic adverse events were mostly grade 1-2, mainly including pigmentation disorders and upper respiratory tract infection. Conclusions:The use of mitoxantrone hydrochloride liposome injection-containing regimen in the treatment of PTCL has definite efficacy and is well tolerated, and it is a new therapeutic option for PTCL patients.

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