Golgi-targeted NIR fluorescent probe with large stokes shift for real-time monitoring of nitric oxide in depression model.

Depression is a debilitating mental illness that poses a serious threat to human health. Nitric Oxide (NO), as an important gasotransmitter, is closely associated with the pathogenesis of depressive disorders. Effective monitoring of NO fluctuation is beneficial for the diagnosis of depression and therapy assessment of antidepressants. Currently, there is a lack of effective methods for rapidly and sensitively identifying NO and elucidating its relationship with depression diseases. Herein, we developed a NIR dye TJ730-based fluorescent probe TJ730-Golgi-NO incorporating benzenesulfonamide as a Golgi-targeted moiety and the thiosemicarbazide group for NO detection. The probe exhibited turn-on fluorescence ability and a large Stokes shift of 158 nm, which shows high sensitivity, selectivity, and rapid response (<1 min) for NO detection. TJ730-Golgi-NO could detect exogenous and endogenous NO in cells stimulated by Glu and LPS, and target Golgi apparatus. Moreover, we disclose a significant increase of NO in the depression model and a weak fluorescence evidenced in the fluoxetine-treated depression mice. This study provides a competent tool for studying the function of NO and helping improve the effective treatment of depression diseases.

Intelligent diagnosis of major depression disease based on multi-layer brain network.

Introduction: Resting-state brain network with physiological and pathological basis has always been the ideal data for intelligent diagnosis of major depression disease (MDD). Brain networks are divided into low-order networks and high-order networks. Most of the studies only use a single-level network to classify while ignoring that the brain works cooperatively with different levels of networks. This study hopes to find out whether varying levels of networks will provide complementary information in the process of intelligent diagnosis and what impact will be made on the final classification results by combining the characteristics of different networks. Methods: Our data are from the REST-meta-MDD project. After the screening, 1,160 subjects from ten sites were included in this study (597 MDD and 563 normal controls). For each subject, we constructed three different levels of networks according to the brain atlas: the traditional low-order network based on Pearson's correlation (low-order functional connectivity, LOFC), the high-order network based on topographical profile similarity (topographical information-based high-order functional connectivity, tHOFC) and the associated network between them (aHOFC). Two sample t-test is used for feature selection, and then features from different sources are fused. Finally, the classifier is trained by a multi-layer perceptron or support vector machine. The performance of the classifier was evaluated using the leave-one-site cross-validation method. Results: The classification ability of LOFC is the highest among the three networks. The classification accuracy of the three networks combined is similar to the LOFC network. These are seven features chosen in all networks. In the aHOFC classification, six features were selected in each round but not seen in other classifications. In the tHOFC classification, five features were selected in each round but were unique. These new features have crucial pathological significance and are essential supplements to LOFC. Conclusion: A high-order network can provide auxiliary information for low-order networks but cannot improve classification accuracy.

[Acupoints compatibility rules of acupuncture for depression disease based on data mining technology].

Based on data mining technology, the acupoints compatibility rules of acupuncture for depression diseases were explored. The randomized controlled trial (RCT) articles regarding acupuncture for depression diseases published from establishment of database to September 2nd, 2022 were searched in CNKI database, Wangfang database, VIP database, SinoMed database, PubMed, EMbase, Web of Science and Cochrane Library. The use frequency of acupoints, meridian tropism, selection of special acupoints and acupoint association rules for five common depression diseases, including primary depression, post-stroke depression, menopausal syndrome, psychoneurosis and anxiety disorder, were analyzed by Python programming language. Cytoscape software was used to analyze the acupoint association and the disease-acupoint co-occurrence network. As a result, totally 387 articles were included, and 319 acupoints prescriptions for the above five common depression diseases were extracted, involving 159 acupoints. The use frequency of acupoints was 2 574 times in total. The frequently-used acupoints were Baihui (GV 20), Sanyinjiao (SP 6), Taichong (LR 3), Neiguan (PC 6), Shenmen (HT 7), Yintang (GV 24+), Zusanli (ST 36), Hegu (LI 4), Sishencong (EX-HN 1) and Taixi (KI 3), etc. The frequently involved meridians were the governor vessel, foot-taiyang bladder meridian, foot-taiyin spleen meridian, and foot-jueyin liver meridian. The frequency of the special acupoints from high to low was crossing points, five-shu points, yuan-primary points, back-shu points, luo-connecting points, and eight confluent points, etc, which were often used in combination with "Baihui (GV 20)-Yintang (GV 24+)" (the highest degree of association). At the same time, the analysis of the co-occurrence network of depression diseases and acupoints showed that the core acupoints group of acupuncture for depression diseases were Baihui (GV 20), Taichong (LR 3), Shenmen (HT 7), Zusanli (ST 36), Neiguan (PC 6) and Sanyinjiao (SP 6). In conclusion, acupuncture treatment for depression diseases has gradually formed a rule of acupoint compatibility, with special acupoint as the main body and "unblocking the governor vessel, and regulating the spirit and qi " as the main therapeutic principle.

Acupoints compatibility rules of acupuncture for depression disease based on data mining technology / 中国针灸

Based on data mining technology, the acupoints compatibility rules of acupuncture for depression diseases were explored. The randomized controlled trial (RCT) articles regarding acupuncture for depression diseases published from establishment of database to September 2nd, 2022 were searched in CNKI database, Wangfang database, VIP database, SinoMed database, PubMed, EMbase, Web of Science and Cochrane Library. The use frequency of acupoints, meridian tropism, selection of special acupoints and acupoint association rules for five common depression diseases, including primary depression, post-stroke depression, menopausal syndrome, psychoneurosis and anxiety disorder, were analyzed by Python programming language. Cytoscape software was used to analyze the acupoint association and the disease-acupoint co-occurrence network. As a result, totally 387 articles were included, and 319 acupoints prescriptions for the above five common depression diseases were extracted, involving 159 acupoints. The use frequency of acupoints was 2 574 times in total. The frequently-used acupoints were Baihui (GV 20), Sanyinjiao (SP 6), Taichong (LR 3), Neiguan (PC 6), Shenmen (HT 7), Yintang (GV 24+), Zusanli (ST 36), Hegu (LI 4), Sishencong (EX-HN 1) and Taixi (KI 3), etc. The frequently involved meridians were the governor vessel, foot-taiyang bladder meridian, foot-taiyin spleen meridian, and foot-jueyin liver meridian. The frequency of the special acupoints from high to low was crossing points, five-shu points, yuan-primary points, back-shu points, luo-connecting points, and eight confluent points, etc, which were often used in combination with "Baihui (GV 20)-Yintang (GV 24+)" (the highest degree of association). At the same time, the analysis of the co-occurrence network of depression diseases and acupoints showed that the core acupoints group of acupuncture for depression diseases were Baihui (GV 20), Taichong (LR 3), Shenmen (HT 7), Zusanli (ST 36), Neiguan (PC 6) and Sanyinjiao (SP 6). In conclusion, acupuncture treatment for depression diseases has gradually formed a rule of acupoint compatibility, with special acupoint as the main body and "unblocking the governor vessel, and regulating the spirit and qi " as the main therapeutic principle.

Are Illness Perceptions Associated With Disease Activity or Psychological Well-Being in Rheumatoid Arthritis? A Study With the Evidence of Confirmatory Factor Analysis.

OBJECTIVES: This study aims to assess the factor structure of the Turkish Revised Illness Perception Questionnaire (IPQ-R) in patients with rheumatoid arthritis (RA) and the relationship of illness perceptions with disease activity and psychological well-being. PATIENTS AND METHODS: One hundred and fifty RA patients (8 males, 142 females; mean age 51.1±12.7 years; range 21 to 81 years) were included in the study. Confirmatory factor analysis was used to test the factor structure of the IPQ-R. Pain was assessed by visual analog scale, disease activity by Disease Activity Score 28, depression by Beck Depression Inventory, global life satisfaction by the Satisfaction with Life Scale, and illness perception by the IPQ-R. RESULTS: Three items (items 12, 18, 19) were deleted because of poor factor loadings. The modified 35-item model showed good reliability and discriminant validity. Beck Depression Inventory scores were correlated with identity, consequences, and emotional representations subscales positively (p<0.001); and with illness coherence subscale negatively (p<0.05). There were positive correlations between Satisfaction with Life Scale scores, and treatment control and illness coherence subscales (p<0.05). Satisfaction with Life Scale scores were negatively correlated with identity, emotional representation, and timeline acute/chronic subscales (p<0.05), and consequences subscale (p<0.001). Disease Activity Score 28 was not correlated with IPQ-R domains (p>0.05). CONCLUSION: The Turkish IPQ-R appears to be a useful clinical assessment tool to evaluate RA-related illness perceptions. RA healthcare should include psychological intervention to strengthen patients' beliefs about their RA regardless of disease activity.