1.Construction of goal management training program and its efficacy for mental health intervention in college students with inattentive attention deficit hyperactivity disorder
Hui HENG ; Yingcan ZHENG ; Ying HE ; Hong SU ; Yunxuan ZHAO ; Feijuan CUI ; Guoyu YANG
Journal of Army Medical University 2025;47(5):480-488
Objective To explore the efficacy of goal management training(GMT)on core symptoms and mental status in college students with attention deficit hyperactivity disorder(ADHD)inattentive type.Methods Delphi method was used to construct a GMT program for college students with inattentive ADHD.Then,totally 68 college students with inattentive ADHD were recruited through advertisements published by hospitals and universities(Second Affiliated Hospital of Army Medical University,and 3 universities in Chongqing from March to June 2024.The subjects were randomly divided into an intervention group(n=34)and a control group(n=34).The intervention group received GMT for 2 h,once a week,for 7 weeks,and the control group did not receive training for the time being.The 2 groups were evaluated within 1 week before and in 7 weeks after intervention by using Adult ADHD Self-Report Scale(ASRS),Dysregulation of Emotions Rating Scale(DERS),Generalized Anxiety Disorde-7(GAD-7),Patient Health Questionnaire-9(PHQ-9),Self-Compassion Scale(SCS),and Satisfaction with Life Scale(SWLS).Results ① The expert authority coefficient(Cr)of 2 rounds of expert consultation was 0.83,with a questionnaire recovery rate of 100%and 95%,respectively,the Kendall's coordination coefficient was 0.081(P<0.01)and 0.226(P<0.01),and the coefficient of variation was<0.3,indicating the results of the expert consultation were reliable.The constructed GMT program includes 1 first-level indicator,7 second-level indicators,and 20 third-level indicators.② After 7 weeks of GMT intervention,the interaction between the 2 groups and time showed that the experimental group obtained significant improvements than the control group in terms of inattention symptoms(Wald Chi-square=28.35,P<0.001),dysregulation of emotions(Wald Chi-square=23.81,P<0.001),anxiety(Wald Chi-square=22.79,P<0.001),depression(Wald Chi-square=20.52,P<0.001),self-compassion(Wald Chi-square=9.36,P<0.01),and life satisfaction(Wald Chi-square=3.97,P<0.05).Conclusion GMT intervention can significantly improve the core symptoms of college students with inattentive ADHD,reduce anxiety and depression levels,enhance their emotion regulation and self-compassion abilities,and improve their life satisfaction.
2.Study on Stability of Catalase Immobilized by Metal-Polyphenol Coordination Polymers
Qin LIU ; Yuan LIN ; Zhao-Hui SU
Chinese Journal of Analytical Chemistry 2025;53(6):1019-1027
The thermal sensitivity of enzymes is a key bottleneck that restricts their practical application,and the development of efficient enzyme stability enhancement technology has important application value.Based on the principle of metal-polyphenol coordination chemistry,this study used tannic acid-ferric ion(TA-FeⅢ)coordination polymer to nano-encapsulate catalase(CAT)and systematically explored its stability enhancement effect.The catalytic activity retention rate of the immobilized enzyme in extreme environments(High temperature,organic solvents,denaturants and pH 3-11)was significantly improved compared with that of the free enzyme,proving that the TA-FeⅢ nanoshell had a significant environmental barrier effect.In the long-term stability test,the immobilized enzyme retained 20%activity after a 30-d storage at room temperature,and its effective activity was prolonged to 8 times that of the free enzyme in the accelerated inactivation test at 37 ℃.In addition,several cyclic catalytic experiments demonstrated that the immobilized enzyme exhibited good reusability,thus broadening its practical application.
7.Rapid characterization and identification of non-volatile components in Rhododendron tomentosum by UHPLC-Q-TOF-MS method.
Su-Ping XIAO ; Long-Mei LI ; Bin XIE ; Hong LIANG ; Qiong YIN ; Jian-Hui LI ; Jie DU ; Ji-Yong WANG ; Run-Huai ZHAO ; Yan-Qin XU ; Yun-Bo SUN ; Zong-Yuan LU ; Peng-Fei TU
China Journal of Chinese Materia Medica 2025;50(11):3054-3069
This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry*
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Chromatography, High Pressure Liquid/methods*
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Drugs, Chinese Herbal/chemistry*
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Mass Spectrometry/methods*
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Plant Leaves/chemistry*
8.Application Value of an AI-based Imaging Feature Parameter Model for Predicting the Malignancy of Part-solid Pulmonary Nodule.
Mingzhi LIN ; Yiming HUI ; Bin LI ; Peilin ZHAO ; Zhizhong ZHENG ; Zhuowen YANG ; Zhipeng SU ; Yuqi MENG ; Tieniu SONG
Chinese Journal of Lung Cancer 2025;28(4):281-290
BACKGROUND:
Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN).
METHODS:
This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models.
RESULTS:
The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability.
CONCLUSIONS
The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
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Humans
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Male
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Female
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Lung Neoplasms/pathology*
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Middle Aged
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Retrospective Studies
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Artificial Intelligence
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Aged
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Tomography, X-Ray Computed
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Adult
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Solitary Pulmonary Nodule/diagnostic imaging*
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ROC Curve
9.Non-pharmacological interventions in chronic prostatitis/chronic pelvic pain syndrome: A network meta-analysis.
Xiao-Hui WEI ; Meng-Yao MA ; Hang SU ; Tong HU ; Yu-Xin ZHAO ; Xing-Chao LIU ; Hong-Yan BI
National Journal of Andrology 2025;31(3):234-245
OBJECTIVE:
To evaluate the efficacy of shockwave therapy, acupuncture, hyperthermia, biofeedback therapy, electrical nerve stimulation, magnetotherapy and ultrasound therapy in the treatment of chronic prostatitis/chronic pelvic pain syndrome(CP/CPPS), and to provide evidence-based support for clinical decision-making.
METHODS:
Two researchers independently searched PubMed, Web of Science, Embase, Cochrane Library, CNKI, Wanfang, VIP and Chinese Biomedical Literature databases for randomized controlled trials(RCTs) on the effects of different interventions on CP/CPPS from the establishment of the databases to August 2024. We evaluated the quality of the included literature and extracted the relevant data according to the Cochrane Handbook for Systematic Reviews of Interventions, followed by network meta-analysis using Revman 5.3, R 4.33 and Stata17 software.
RESULTS:
A total of 25 RCTs involving 1 794 cases were included. The results of network meta-analysis showed that electrical nerve stimulation, shockwave therapy, biofeedback therapy, magnetotherapy, ultrasound therapy and acupuncture were significantly superior to conventional medication and placebo in the total NIH-CPSI scores(P< 0.05), and so were electrical nerve stimulation and shockwave therapy to acupuncture and hyperthermia(P< 0.05), magnetic therapy to hyperthermia, and ultrasound therapy to placebo(P< 0.05). Shockwave therapy, biofeedback therapy, electrical nerve stimulation, magnetotherapy and ultrasound therapy achieved remarkably better clinical efficacy than conventional medication and placebo in the treatment of CP/CPPS, and so did shockwave therapy than electrical nerve stimulation, hyperthermia, ultrasonic therapy, magnetotherapy and acupuncture.
CONCLUSION
For the treatment of CP/CPPS, electrical nerve stimulation is advantageous over the other interventions in improving total NIH-CPSI scores, and shockwave therapy is advantageous in relieving pain symptoms and clinical efficacy. This conclusion, however, needs to be further verified by more high-quality clinical studies.
Humans
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Acupuncture Therapy
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Biofeedback, Psychology
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Chronic Disease
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Electric Stimulation Therapy
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Extracorporeal Shockwave Therapy
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Magnetic Field Therapy
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Pelvic Pain/therapy*
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Prostatitis/therapy*
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Randomized Controlled Trials as Topic
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Ultrasonic Therapy
10.Comparison of Three Drowning-related Plankton Testing Methods in Drowning Diagnosis
Xiao-Feng ZHANG ; Qin SU ; Xiao-Hui CHEN ; Wei-Bin WU ; Dong-Yun ZHENG ; Jian ZHAO ; Ling CHEN ; Qu-Yi XU ; Chao LIU
Journal of Forensic Medicine 2025;41(3):244-251
Objective To compare the application effects of plankton multiplex polymerase chain reac-tion-capillary electrophoresis(PCR-CE),SYBR Green Ⅰ real-time quantitative PCR(qPCR)and microwave digestion-vacuum filtration-automated scanning electron microscopy(MD-VF-Auto SEM)in the diagnosis of drowning.Methods Lung,liver and kidney tissues from 212 drowned corpses and 30 non-drowned corpses were examined respectively by the three drowning-related plankton testing methods,and the detection rates of plankton in each tissue by three methods were compared.Results In drowned corpses,the total detection rates of PCR-CE,qPCR,and MD-VF-Auto SEM were 93.9%,96.2%,and 95.3%,respectively,with no statistically significant difference(P>0.05).The detection rate of lung tissue by MD-VF-Auto SEM(100%)was higher than those of PCR-CE and qPCR(P<0.05),and there was no significant difference in the detection rates of the three methods in liver or kidney tissues(P>0.05).In non-drowning corpses,a small number of diatoms(less than 10 cells/10 g)were detected by MD-VF-Auto SEM method,only in liver and kidney tissues,while the other two methods yielded negative results for all tissues.Conclusion All three methods have good efficacy in the examination of drowned corpses.The MD-VF-Auto SEM method directly observes diatom morpho-logical characteristics through scanning electron microscopy,and the qualitative and quantitative analy-ses are intuitive and accurate.It has great advantages in the examination of difficult degradation samples.The PCR-CE method and qPCR method have a low sample demand(0.5 g),are easy to operate and have short detection time(4-7 h).They are easy to be applied in the grassroots depart-ments and are suitable for the rapid determination of drowned corpses in routin cases.The combina-tion of the two DNA methods with the MD-VF-Auto SEM method can increase the detection rate of plankton,ensuring the reliability of examination results.This combined use is of significant importance in the application of drowning diagnosis.

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