UNASSIGNED: There is limited literature on the prevalence of mixed features in patients with depression, especially from countries in Asia. Our aim was to evaluate the prevalence of \"mixed features\" in patients with first-episode depression.
UNASSIGNED: Patients with first-episode depression were evaluated for the presence of mixed features as per the Diagnostic and Statistical Manual (DSM)-5 criteria. They were additionally evaluated on Hamilton Depression Rating Scale (HDRS) and Young Mania Rating Scale (YMRS).
UNASSIGNED: About one-sixth (16%) of the patients fulfilled the DSM-5 criteria for the mixed features specifier. The most common manic/hypomanic clinical feature was increased talkativeness or pressure of speech, followed by elevated expansive mood (12.5%), and inflated self-esteem or grandiosity was the least common feature (8.7%). Those with mixed features had higher prevalence of comorbid tobacco dependence and psychotic symptoms. In terms of frequency of depressive symptoms as assessed on HDRS, compared to those without mixed features, those with mixed features had higher frequency of symptoms such as depressed mood, insomnia during early hours of morning, work and activities, agitation, gastrointestinal somatic symptoms, genital symptoms, hypochondriasis, and poorer insight.
UNASSIGNED: Mixed features specifier criteria were fulfilled by 16% patients with first-episode depression. This finding suggests that the extension of this specifier to depression can be considered as a useful step in understanding the symptom profile of patients with depression.

Bipolar disorder is heterogeneous in phenomenology, illness trajectory, and response to treatment. Despite evidence for the efficacy of multimodal-ity interventions, the majority of persons affected by this disorder do not achieve and sustain full syndromal recovery. It is eagerly anticipated that combining datasets across various information sources (e.g., hierarchical \"multi-omic\" measures, electronic health records), analyzed using advanced computational methods (e.g., machine learning), will inform future diagnosis and treatment selection. In the interim, identifying clinically meaningful subgroups of persons with the disorder having differential response to specific treatments at point-of-care is an empirical priority. This paper endeavours to synthesize salient domains in the clinical characterization of the adult patient with bipolar disorder, with the overarching aim to improve health outcomes by informing patient management and treatment considerations. Extant data indicate that characterizing select domains in bipolar disorder provides actionable information and guides shared decision making. For example, it is robustly established that the presence of mixed features - especially during depressive episodes - and of physical and psychiatric comorbidities informs illness trajectory, response to treatment, and suicide risk. In addition, early environmental exposures (e.g., sexual and physical abuse, emotional neglect) are highly associated with more complicated illness presentations, inviting the need for developmentally-oriented and integrated treatment approaches. There have been significant advances in validating subtypes of bipolar disorder (e.g., bipolar I vs. II disorder), particularly in regard to pharmacological interventions. As with other severe mental disorders, social functioning, interpersonal/family relationships and internalized stigma are domains highly relevant to relapse risk, health outcomes, and quality of life. The elevated standardized mortality ratio for completed suicide and suicidal behaviour in bipolar disorder invites the need for characterization of this domain in all patients. The framework of this paper is to describe all the above salient domains, providing a synthesis of extant literature and recommendations for decision support tools and clinical metrics that can be implemented at point-of-care.

暂无摘要。

A useful scale for identification of mixed features in major depressive episodes (MDE) patients is urgent in China. This study aimed to evaluate the reliability and validity of the Chinese version of the Clinically Useful Depression Outcome Scale supplemented with questions for the DSM-5 mixed features specifier (Chinese-CUDOS-M) in MDE patients.
A total of 152 MDE patients were recruited and assessed using Chinese-CUDOS-M, Patient Health Questionnaire-9 (PHQ-9) and 32-item Hypomania Checklist (HCL-32). Principal component analysis (PCA) and exploratory factor analysis (EFA) were conducted. The predictive validity was calculated by the area under the receiver operating characteristic curve (AUROC).
The Cronbach\'s alpha of Chinese-CUDOS-M was 0.85. PCA showed three common factors with eigenvalue greater than 1; the eigenvalue of factor I was 4.96, with 38.1% of variance explanation. Chinese-CUDOS-M depression subscale was associated with PHQ-9 (r = 0.83, p<0.01), and manic subscale was associated with HCL-32 (r = 0.73, p< 0.01). AUROC of the Chinese-CUDOS-M for patients with mixed depression was 0.90 (95%CI: 0.85-0.95), with a cut-off value of 7, sensitivity of 0.95, and specificity of 0.73. Furthermore, AUROC was 0.88 in patients with major depressive disorder (MDD), with a cut-off value of 7, sensitivity of 0.96, and specificity of 0.71. AUROC was 0.92 in bipolar disorder (BD) depression patients, with a cut-off value of 9, sensitivity of 0.89, and specificity of 0.87.
Our study shows that the Chinese-CUDOS-M can identify mixed features in both MDD and BD depression with satisfactory reliability and validity.

This study aims to explore the reliability, validity, and feasibility of Clinically Useful Depression Outcome Scale (CUDOS) in screening mixed features in patients diagnosed with mania.
A total of 109 patients with (hypo-) manic episode were recruited. The reliability of Chinese version of CUDOS (CUDOS-C) were analyzed with Cronbach\'s alpha and intraclass correlation coefficient (ICC). Spearman correlation coefficient was used to analyze the validity by comparing the correlation between CUDOS-C and Patient Health Questionnaire-9 (PHQ-9), 32-item Hypomania Checklist (HCL-32). The score of MINI (hypo-) manic episode with mixed features-DSM-5 Module-Chinese version(MINI-M-C) ≥ 2 was considered as the gold standard of mixed features, and the receiver operating characteristic (ROC) curve analysis was used to calculate the optimal cut-off values of CUDOS-C score.
The Cronbach\'s alpha value of CUDOS-C was 0.898, and the ICC of CUDOS-C test-retest was 0.880 (95% CI: 0.812-0.923, p < .05).The CUDOS-C score was significantly correlated with PHQ-9 score (r = 0.893, p = .000), but not with HCL-32 score(r = 0.088, p = .364).The area under ROC curve was 0.909 (95% CI: 0.855 to 0.963, p < .001) for CUDOS-C identifying mixed features in mania. The optimal cut-off value was 11 with a sensitivity of 0.854 and a specificity of 0.868. The CUDOS-C (score ≥ 12) identified 40.4% of the patients with mixed features, which was higher than those diagnosed by clinicians (18.3%) and screened using MINI-M-C (37.6%).
The results indicate the CUDOS-C is a reliable and valid self-administered questionnaire for assessing depressive symptoms and screening patients with mixed mania.

With the modification of DSM-5 mixed features specifier, a brief scale to screen mixed features in patients with mood disorders is needed in clinical practice. This study aimed to explore the psychometric properties of the Chinese version of the Clinically Useful Depression Outcome Scale supplemented with DSM-5 Mixed subtype (CUDOS-M-C) for the Chinese patients with mood disorders.
Overall, 300 patients with major depressive episode were recruited. All participants were assessed using CUDOS-M-C, Young Mania Rating Scale, Hamilton Anxiety Scale and Montgomery-Asberg Depression Rating Scale. The receiver operating characteristic (ROC) curve analysis was used to calculate the optimal cut-off values of CUDOS-M-C score. The reliability and validity of CUDOS-M-C were examined using Cronbach\'s alpha, intraclass correlation coefficient (ICC) and principal component analysis (PCA).
The results of PCA indicated two-factor structure as the best solution for CUDOS-M-C, which explained 54.82% of cumulative variance. The Cronbach\'s alpha was 0.892 and the ICC was 0.853. The area under the ROC curve of the CUDOS-M-C for participants with mixed depression was 0.927 (p<0.001) and the suitable cut-off value was 8, with a sensitivity of 91.6% and specificity of 79.9%.
Most of the patients were recruited from eastern China and further research with larger sample is warranted. And this study did not perform confirmatory factor analysis to identify the generalization of factor structure of CUDOS-M-C. Besides, the study performed the test-retest reliability of CUDOS-M-C and further analysis is needed to ascertain the patient\'s post-treatment changes.
The CUDOS-M-C demonstrated to have satisfactory psychometric properties as a self-report scale, and could be applied to screen patients with mixed depression in clinical practice.

Systematic data on clinical correlates of mixed features in bipolar disorder are not available, so far. We conducted a systematic review and meta-analysis estimating the association between DSM-5 mixed features and candidate characteristics in depressive and manic/hypomanic episodes.
We included observational studies indexed in the main electronic databases. The association between DSM-5 mixed features and relevant correlates was estimated using odds ratio (OR) and standardized mean difference (SMD) with 95% confidence intervals (CIs), for categorical and continuous variables, respectively. Analyses were based on random effects models.
Eight studies were included, involving 3070 individuals (1495 with a major depressive episode and 1575 with hypo/manic episode). No clinical characteristics were associated with mixed features in subjects with a depressive episode. Among subjects with a manic/hypomanic episode, those with mixed features were more likely to have a history of suicide attempts (OR: 2.37; 95%CI: 1.42 to 3.94; I2=39.7%), co-occurring anxiety disorders (OR: 2.67; 95%CI: 1.28 to 5.57; I2=0%), and a rapid cycling course (OR=4.23; 95%CI: 1.29 to 13.81; I2=0%), with less severe manic symptoms (SMD=-0.40; 95%CI: -0.65 to -0.16; I2=0%).
(1) the heterogeneity of methods across studies and the inconsistency of findings; (2) the limited amount of data on correlates of DSM-5 mixed features; (3) the possible influence of publication bias.
Findings of this meta-analysis show that mixed features among individuals with a manic/hypomanic episode may identify a special clinical population, characterized not only by depressive symptoms, but also by anxiety, rapid cycling, and suicidality.

UNASSIGNED: Treatment-resistant depression (TRD) and treatment-resistant bipolar depression (TRBD) poses a significant clinical and societal burden, relying on different operational definitions and treatment approaches. The detection of clinical predictors of resistance is elusive, soliciting clinical subtyping of the depressive episodes, which represents the goal of the present study.
UNASSIGNED: A hundred and thirty-one depressed outpatients underwent psychopathological evaluation using major rating tools, including the Hamilton Rating Scale for Depression, which served for subsequent principal component analysis, followed-up by cluster analysis, with the ultimate goal to fetch different clinical subtypes of depression.
UNASSIGNED: The cluster analysis identified two clinically interpretable, yet distinctive, groups among 53 bipolar (resistant cases = 15, or 28.3%) and 78 unipolar (resistant cases = 20, or 25.6%) patients. Among the MDD patients, cluster \"1\" included the following components: \"Psychic symptoms, depressed mood, suicide, guilty, insomnia\" and \"genitourinary, gastrointestinal, weight loss, insight\". Altogether, with broadly defined \"mixed features,\" this latter cluster correctly predicted treatment outcome in 80.8% cases of MDD. The same \"broadly-defined\" mixed features of depression (namely, the standard Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition-DSM-5-specifier plus increased energy, psychomotor activity, irritability) correctly classified 71.7% of BD cases, either as TRBD or not.
UNASSIGNED: Small sample size and high rate of comorbidity.
UNASSIGNED: Although relying on different operational criteria and treatment history, TRD and TRBD seem to be consistently predicted by broadly defined mixed features among different clinical subtypes of depression, either unipolar or bipolar cases. If replicated by upcoming studies to encompass also biological and neuropsychological measures, the present study may aid in precision medicine and informed pharmacotherapy.

The thermostability of proteins is a key factor considered during enzyme engineering, and finding a method that can identify thermophilic and non-thermophilic proteins will be helpful for enzyme design. In this study, we established a novel method combining mixed features and machine learning to achieve this recognition task. In this method, an amino acid reduction scheme was adopted to recode the amino acid sequence. Then, the physicochemical characteristics, auto-cross covariance (ACC), and reduced dipeptides were calculated and integrated to form a mixed feature set, which was processed using correlation analysis, feature selection, and principal component analysis (PCA) to remove redundant information. Finally, four machine learning methods and a dataset containing 500 random observations out of 915 thermophilic proteins and 500 random samples out of 793 non-thermophilic proteins were used to train and predict the data. The experimental results showed that 98.2% of thermophilic and non-thermophilic proteins were correctly identified using 10-fold cross-validation. Moreover, our analysis of the final reserved features and removed features yielded information about the crucial, unimportant and insensitive elements, it also provided essential information for enzyme design.

Major Depressive Episode (MDE) is a transdiagnostic nosographic construct straddling Major Depressive (MDD) and Bipolar Disorder (BD). Prognostic and treatment implications warrant a differentiation between these two disorders. Network analysis is a novel approach that outlines symptoms interactions in psychopathological networks. We investigated the interplay among depressive and mixed symptoms in acutely depressed MDD/BD patients, using a data-driven approach. We analyzed 7 DSM-IV-TR criteria for MDE and 14 researched-based criteria for mixed features (RBDC) in 2758 acutely depressed MDD/BD patients from the BRIDGE-II-Mix study. The global network was described in terms of symptom thresholds and symptom centrality. Symptom endorsement rates were compared across diagnostic subgroups. Subsequently, MDD/BD differences in symptom-network structure were examined using permutation-based network comparison test. Mixed symptoms were the most central and highly interconnected nodes in the network, particularly agitation followed by irritability. Despite mixed symptoms, appetite gain and hypersomnia were significantly more endorsed in BD patients, associations between symptoms were highly correlated across MDD/BD (Spearman\'s r = 0.96, p<0.001). Network comparison tests showed no significant differences among MDD/BD in network strength, structure, or specific edges, with strong edges correlations (0.66-0.78). Upstream differences in MDD/BD may produce similar symptoms networks downstream during acute depression. Yet, mixed symptoms, appetite gain and hypersomnia are associated to BD rather than MDD. Symptoms during mixed-MDE might aggregate according to 2 different clusters, suggesting a possible stratification within mixed states. Future symptom-based studies should implement clinical, longitudinal, and biological factors, in order to establish tailored therapeutic strategies for acute depression.