摘要:目的:观察伴有抑郁症状的心力衰竭患者加用黛力新干预的疗效。方法: 65例用Zung抑郁自评量表检测评测诊断为抑郁症并心力衰竭患者,将患者分为黛力新治疗组及对照组,治疗组在常规治疗基础上加用黛力新(2片/d),治疗1个月后再行Zung抑郁自评量表粗分及24项症状统计,同时观察治疗前后患者心功能改善情况。结果: 35例治疗组患者心功能的改善及Zung抑郁自评量表检测粗分及24项症状改善明显优于对照组。〖HTH〗结论〖HTSS〗: 黛力新使心衰患者的抑郁症状很快得到改善,并提高了心力衰竭的疗效。Abstract: Objective: To observe the curative efficacy of deanxit to the patients suffering by heart failure with depression. Methods: Sixtyfive patients who were diagnosed as depression by Zung Selfrating Depression Scale are into deanxit treatment group and control group,and treatment group receive the treatment with two pieces of deanxit everyday besides the conventional therapy.After a month,we count the Zung selfrating depression scale score and study the24 symptoms,at the same time,we observed the change of cardiac function in the patients. Results:The curative efficacy in the treatment group is better than those in the control group with improvement in cardiac function and Zung selfrating depression scale score and the alleviation for 24 symptoms. Conclusion:Deanxit can alleviate symptoms of depression in patients with heart failure soon and increase the efficacy of heart failure.
目的 调查抑郁症患者疾病应对方式现状，为心理护理干预提供科学依据。 方法 采用问卷调查方式对四川大学华西医院心身障碍病房2012年4月－10月住院的220例抑郁症患者进行一般资料及疾病应对方式调查，并就调查结果进行分析。 结果 抑郁症患者应对方式平均得分（31.5 ± 6.8）分；生活自理能力、兴趣爱好、健康状况及经济状况与应对方式总分存在相关关系（P值分别为0.007、0.000、0.036、0.028）。 结论 抑郁症患者普遍存在应对不良，其生活自理能力、兴趣爱好、健康及经济状况可能是影响抑郁症发展的相关因素。
目的:了解抑郁症患者的生命质量与疾病影响程度,探讨抑郁程度、生命质量和疾病影响程度的关系。方法:运用随意抽样方法,对2007年7～9月在四川大学华西医院心理卫生中心住院的抑郁症患者进行问卷调查。问卷包括:①一般人口学资料;②Zung抑郁自评问卷SDS;③汤旦林生命质量表TD;④美国华盛顿大学卫生服务系1977年编制、我国李君荣、张新平等翻译的疾病影响程度量表SIP。统计方法:采用SPSS10.0软件对数据进行处理,采用频数分析、t检验、相关分析和ANOVA多元线形回归分析。结果:①住院抑郁症患者TDL为60.04+16.95,男女患者无显著性差异(T1=0.726 sig=0.47);②多数抑郁症患者的TDL处于比较差和中下水平抑(比较差占62.7%,中下占17.9%;③患者受疾病影响严重,SIP总平均受损分为40.01+15.74,其中社会心理功能影响平均分为53.86+22.22,其他功能影响平均分为45.09+17.81,躯体功能影响平均分为21.84+14.85;④抑郁症患者TDL、SIP和SDS 有一定关系,分别SDS与TDL的相关系数r=0.248, sig为0.043,SDS与SIP的相关系数r=0.526, sig为0.000;⑤患者的TDL与性别、病程、住院次数、职业、付费方式无显著性相关关系,而与年龄有一定关系(R=0.255,Sjg=0.037);⑥患者的SIP与患者的与年龄、病程、住院次数、付费方式、职业等无显著性关系,Pgt;0.05。而与性别有一定关系,R=0.249,Sjg=0.042。结论:①抑郁症患者的生命质量TDL严重下降,明显低于正常人,而且处于比较差和中下的患者占多数(差为69.6%,中下为17.9%);②抑郁症患者疾病影响严重,SIP功能损失分为40.01+15.74,其中社会心理影响最严重,为53.86+22.22;③郁症患者的SDS与TDL和SIP有明显相关性;④抑郁症患者的TDL与年龄有一定关系,SIP与性别有一定关系。
ObjectiveTo explore the correlation of serum levels of 5-hydroxytryptamine (5-HT) and 5-HT2A receptor gene T102C polymorphism with suicidal behavior by poison in non-depressive patients, in order to diagnose and intervene the suicidal behavior of patients as early as possible. MethodsSixty-two non-depressive patients with the behavior of suicide by poison treated between January 2013 and June 2014 were selected as patient group, and other 66 healthy persons were selected as control group. Peripheral blood in the two groups of patients were collected to test the serum levels of 5-HT with enzyme linked immunosorbent assay, and the 5-HT2A receptor gene T102C polymorphism was detected by polymerase chain reaction-restriction fragment length polymorphism. The data were analyzed by SPSS 19.0 statistically. ResultsThe serum level of 5-HT in the patient group was significantly lower than that in the control group (P<0.001), and the frequency of T102C genotype in the patient group was higher than the control group (χ2=5.533, P=0.013). The distribution of genotype was different, and homozygous mutations of CC in the patient group were higher than the control group (χ2=5.648, P=0.017). ConclusionThe serum levels of 5-HT and 5-HT2A receptor gene T102C polymorphism, and the frequency of T102C genotype may be related to suicidal behavior by poison in non-depressive patients.
Psilocybin is a hallucinogenic indole alkaloid derived from mushrooms, which is metabolized into psilocin in vivo and exerts biological effects. Clinical studies have shown that psilocybin has the effect of relieving anxiety and depression in cancer patients. Due to its fast onset, significant therapeutic effect, and low addictive nature, psilocybin has the potential to break through the bottleneck of slow action and poor efficacy of existing depression drugs, bringing new hope for the treatment of severe depression and refractory depression. This article will review the pharmacokinetics, antidepressant mechanisms, and research progress of psilocybin, providing a reference for subsequent research.
Objective To explore depression-related biomarkers and potential therapeutic drugs in order to alleviate depression symptoms and improve patients’ quality of life. Methods From November 2022 to January 2024, gene expression profiles of depression patients and healthy volunteers were downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed to identify differentially expressed genes. Enrichment analysis of these genes was conducted, followed by the construction of a protein-protein interaction network. Finally, Cytoscape software with the Cytohubba plugin was used to identify potential key genes, and drug prediction was performed. Results Through differential expression analysis, a total of 110 differentially expressed genes (74 upregulated and 36 downregulated) were identified. Protein-protein interaction network identified 10 key genes, and differential expression analysis showed that 8 of these genes (CPA3, HDC, IL3RA, ENPP3, PTGDR2, VTN, SPP1, and SERPINE1) exhibited significant differences in expression levels between healthy volunteers and patients with depression (P<0.05). Enrichment analysis revealed that the upregulated genes were significantly enriched in pathways related to circadian rhythm, niacin and nicotinamide metabolism, and pyrimidine metabolism, while the downregulated genes were primarily enriched in extracellular matrix-receptor interaction and interleukin-17 signaling pathways. Six overlapping verification genes (SALL2, AKAP12, GCSAML, CPA3, FCRL3, and MS4A3) were obtained across two datasets using the Wayn diagram. Single-cell sequencing analysis indicated that these genes were significantly expressed in astrocytes and neurons. Mendelian randomization analysis suggested that the FCRL3 gene might play a critical role in the development of depression. Drug prediction analysis revealed several potential antidepressant agents, such as cefotiam, harmol, lincomycin, and ribavirin. Conclusions Circadian rhythm, nicotinate and nicotinamide metabolism, and pyrimidine metabolism pathways may represent potential pathogenic mechanisms in depression. Harmol may be a potential therapeutic drug for the treatment of depression.
Electroconvulsive therapy (ECT) is an interventional technique capable of highly effective neuromodulation in major depressive disorder (MDD), but its antidepressant mechanism remains unclear. By recording the resting-state electroencephalogram (RS-EEG) of 19 MDD patients before and after ECT, we analyzed the modulation effect of ECT on the resting-state brain functional network of MDD patients from multiple perspectives: estimating spontaneous EEG activity power spectral density (PSD) using Welch algorithm; constructing brain functional network based on imaginary part coherence (iCoh) and calculate functional connectivity; using minimum spanning tree theory to explore the topological characteristics of brain functional network. The results show that PSD, functional connectivity, and topology in multiple frequency bands were significantly changed after ECT in MDD patients. The results of this study reveal that ECT changes the brain activity of MDD patients, which provides an important reference in the clinical treatment and mechanism analysis of MDD.
Depression is a common psychiatric disorder, and approximately 30% patients with depression do not respond effectively to standard antidepressant medication; this condition is termed treatment resistant depression (TRD) and its neurobiological mechanism remains unclear. Neuroimaging techniques can non-invasively explore changes in brain structure, function and metabolism. These techniques have been applied in neurobiological research of TRD and revealed critical abnormalities in brain structure, function and metabolism in fronto-limbic system. In this paper, we reviewed the latest progress in neuroimaging researches on TRD, providing new insight and imaging evidence for further neurobiological studies of TRD.
To enhance the accuracy of computer-aided diagnosis of adolescent depression based on electroencephalogram signals, this study collected signals of 32 female adolescents (16 depressed and 16 healthy, age: 16.3 ± 1.3) with eyes colsed for 4 min in a resting state. First, based on the phase synchronization between the signals, the phase-locked value (PLV) method was used to calculate brain functional connectivity in the θ and α frequency bands, respectively. Then based on the graph theory method, the network parameters, such as strength of the weighted network, average characteristic path length, and average clustering coefficient, were calculated separately (P < 0.05). Next, using the relationship between multiple thresholds and network parameters, the area under the curve (AUC) of each network parameter was extracted as new features (P < 0.05). Finally, support vector machine (SVM) was used to classify the two groups with the network parameters and their AUC as features. The study results show that with strength, average characteristic path length, and average clustering coefficient as features, the classification accuracy in the θ band is increased from 69% to 71%, 66% to 77%, and 50% to 68%, respectively. In the α band, the accuracy is increased from 72% to 79%, 69% to 82%, and 65% to 75%, respectively. And from overall view, when AUC of network parameters was used as a feature in the α band, the classification accuracy is improved compared to the network parameter feature. In the θ band, only the AUC of average clustering coefficient was applied to classification, and the accuracy is improved by 17.6%. The study proved that based on graph theory, the method of feature optimization of brain function network could provide some theoretical support for the computer-aided diagnosis of adolescent depression.
ObjectivesTo comprehensively evaluate the methodological quality and applicability of the results of systematic reviews on acupuncture treatment for primary depression.MethodsWeb of Science, EMbase, PubMed, The Cochrane Library, CNKI, CBM, WanFang Data and VIP databases were electronically searched to collect systematic reviews/meta-analyses on acupuncture treatment for primary depression from inception to December 5th, 2018. Two researchers independently screened and extracted data by using tools of AMSTAR 2 to evaluate the methodological quality, using ROBIS to assess risk of bias, and using CASP-S.R to evaluate the applicability of the results.ResultsA total of 18 systematic reviews/meta-analyses were included, and all focused on acupuncture intervention, including 2 primary outcome indicators. According to AMSTAR 2 evaluation results, there were 4 high quality studies, 12 medium quality studies and 2 low quality studies; ROBIS results found 10 high bias risk studies, 7 low bias risk studies and 1 unclear; CASP-S.R showed only 4 design studies applicable to local individuals, and there were no studies on the relationship between design benefits, hazards and costs.ConclusionsThe quality of systematic reviews/meta-analyses for acupuncture treatment of primary depression is moderate, however with a certain bias. Most studies may not directly benefit local individuals. All studies have no relationship with cost hazards. It is expected for further reviewers to strictly follow systematic evaluation method to improve research quality and reduce bias, while the applicability of the systematic review to individuals from different regions should be considered as well as the relationship between the benefit and cost hazard. In addition, more valid RCTs are required to provide higher quality evidence and explore correlated and comprehensive mechanism.