Analysis of regional homogeneity and functional connectivity among the depression and bipolar disorder with mixed features patients / 中华放射学杂志

Objective:To investigate the regional homogeneity (ReHo) among the major depressive disorder patients without mixed features (MDD noMF), major depressive disorder with mixed features (MMF), bipolar disorder with mixed features (BMF) and bipolar disorder patients without mixed features (BD noMF) patients, and to explore the brain activity and functional connectivity patterns of the MMF and BMF patients. Methods:This was a cross-sectional study. The MDD noMF patients (MDD noMF group), MMF patients (MMF group), BMF patients (BMF group), BD noMF patients (BD noMF group), and age-and gender-matched healthy controls (HC group) were recruited from Beijing Anding Hospital, Capital Medical University between April, 2021 and June, 2022. All the participants underwent resting-state functional MRI scanning. The ReHo values was computed with the DPABI software based on the MATLAB. Firstly, the difference in ReHo among the patients with MDD noMF, MMF, BMF, BD noMF and HC group were estimated by the analysis of covariance and the post-hoc method (LSD or Games-Howell). And then, the brain regions with significant different ReHo values were selected as the seeds to calculate the functional connectivity with the whole brain. Results:A total of 29 cases in the MDD noMF group, 24 cases in the MMF group, 26 cases in the BMF group, 29 cases in the BD noMF group, and 42 in the HC group were included. The differences in ReHo values in the left fusiform and the left precuneus of the 5 groups were statistically significant ( P<0.05). Among of them, the ReHo values of the left fusiform were lower in the MMF, BMF and BD noMF groups compared with the HC group ( P<0.05), while the ReHo values of the left precuneus in MDD noMF, MMF, BMF and BD noMF groups were higher than that in the HC group ( P<0.05). The ReHo value of the left fusiform was lower in the MMF group compared with the MDD noMF group ( P=0.001); the ReHo value of the left fusiform was lower in the BMF group compared with the MDD noMF and BD noMF groups ( P<0.05). The functional connectivity between the left fusiform and vermis, left insula, right putamen, and left medial superior frontal gyrus, and functional connectivity between the left precuneus and right superior frontal gyrus (dorsolateral) showed significant difference among the MDD noMF, MMF, BMF, BD noMF and HC groups ( P<0.05). Compared with HC group, MDD noMF, MMF, BD noMF groups showed higher functional connectivity between the left fusiform and the vermis, and MDD noMF, MMF, BMF, BD noMF group showed higher functional connectivityy between the the left fusiform and the left insula, left medial superior frontal gyrus and right putamen ( P<0.05). Compared with the MDD noMF group, the MMF, BMF and BD noMF groups showed higher functional connectivity between the left fusiform and the left insula ( P<0.05). Compared with the MDD noMF group, the BMF and BD noMF groups had higher functional connectivity between the left fusiform and the left medial superior frontal gyrus ( P<0.05). The BMF group showed higher functional connectivity of the left fusiform with the right putamen than the MDD noMF and BD noMF groups. Additonally, the BMF and BD noMF groups showed higher functional connectivity between the left precuneus and the right superior frontal gyrus (dorsolateral) than HC, MDD noMF and MMF groups ( P<0.05). Conclusions:MMF and BMF patients have local abnormalities of functional activity synchronization in the left fusiform and precuneus and abnormal functional connectivity patterns with multiple brain regions. MMF and BMF patients have specific neuroimaging features compared to MDD noMF or BD noMF patients and also share similar neuroimaging pathogenesis.

CWLy-RF: A novel approach for identifying cell wall lyases based on random forest classifier.

Drug resistance of pathogenic bacteria has become increasingly serious due to the abuse of antibiotics in recent years. Researchers have found that cell wall lyases are effective antibacterial agents that can specifically recognize target bacteria and degrade bacterial peptidoglycan. Traditional wet experiments are usually expensive, time-consuming and laborious for the identification of lyases. Therefore, there is an urgent need to develop prediction tools based on computer methods to identify lyases quickly and accurately. In this paper, a new predictor, CWLy-RF, is proposed based on the random forest (RF) algorithm to identify cell wall lyases. In this method, we combined three features, namely, 400D, 188D and the composition of k-spaced amino acid group pairs, using mixed-feature representation methods. Afterward, we improved the feature representation ability with the selected top 100 features by using the information gain method and trained a predictive model using RF. The constructed prediction model is evaluated by using 10-fold cross-validation. The accuracy obtained was 96.09%, the AUC was 0.993, the MCC was 0.922, the sensitivity was 94.92%, and the specificity was 97.32%. We have proved that the proposed predictor CWLy-RF is superior to other latest models, and it will hopefully become an effective and useful tool for identifying lyases.

Mixed features in DSM-5： problems and solutions / 四川精神卫生

This study contests the mixed states in diagnostic criteria for bipolar disorder and major depressive disorder in the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5）， and attempts to propose possible solutions. At present， the DSM-5 defined “mixed feature specifier” in bipolar disorder faces a number of problems in clinical use， particularly with regard to the classification of incidental features， which poses some clinical difficulties. DSM-5 abandons the previous standard setting which conform to the strict diagnostic thinking that both depression and mania exist together， and primarily captures three or more non-overlapping symptoms of the opposite pole in clinical diagnosis， but the difficulty in diagnosing the states or features resulting from the coexistence of two diametrically opposed symptoms or symptom clusters has still not been effectively addressed. In practice， clinical features of depressive episodes across participants with maniac disorder and manic episodes in depressive disorder within bipolar disorder pedigrees become atypical. Therefore， this paper focuses on the psychopathological features of the mixed profile and conducts analysis in the context of clinical practice and selected research perspectives， so as to propose some potentially constructive ideas to inform the solution of the clinical problems of the mixed states.

Identifying Plant Pentatricopeptide Repeat Coding Gene/Protein Using Mixed Feature Extraction Methods.

Motivation: Pentatricopeptide repeat (PPR) is a triangular pentapeptide repeat domain that plays a vital role in plant growth. In this study, we seek to identify PPR coding genes and proteins using a mixture of feature extraction methods. We use four single feature extraction methods focusing on the sequence, physical, and chemical properties as well as the amino acid composition, and mix the features. The Max-Relevant-Max-Distance (MRMD) technique is applied to reduce the feature dimension. Classification uses the random forest, J48, and naïve Bayes with 10-fold cross-validation. Results: Combining two of the feature extraction methods with the random forest classifier produces the highest area under the curve of 0.9848. Using MRMD to reduce the dimension improves this metric for J48 and naïve Bayes, but has little effect on the random forest results. Availability and Implementation: The webserver is available at: http://server.malab.cn/MixedPPR/index.jsp.

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Factors related to suicidal behavior in patients with bipolar disorder: the effect of mixed features on suicidality.

OBJECTIVES: The aim of the present study was to investigate various risk factors of suicidal behaviors, including the mixed features specifier, in patients with bipolar disorder. METHODS: We retrospectively reviewed medical charts from 2005 to 2014. A total of 334 patients diagnosed with bipolar disorder using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision were enrolled. Subjects were categorized into two groups according to their history of suicidal behavior and the demographic and clinical characteristics of the groups were compared, including the mixed features specifier. We reevaluated the index episode using Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria and classified subjects into an index episode with mixed features group and an index episode without mixed features group. Logistic regression was performed to evaluate significant risk factors associated with suicidal behavior. RESULTS: Suicidal behavior had an independent relationship to mixed features at the index episode using DSM-5 criteria [odds ratio (OR)=3.39; 95% confidence interval (CI): 1.57-7.34] and number of previous depressive episodes (OR=1.62; 95% CI: 1.34-1.95) in bipolar patients. The mixed feature specifier was the strongest risk factor for suicidal behavior in the present study. CONCLUSIONS: This study may help clinicians understand potential risk factors and manage bipolar disorders with suicidal behaviors. Clinicians should carefully monitor patients with bipolar disorder who exhibit numerous depressive episodes or mixed features for suicidal behavior.

A reevaluation of the possibility and characteristics in bipolar mania with mixed features: a retrospective chart review.

The aim of the present study was to reevaluate the feasibility of diagnosing a mixed features behind bipolar mania and to elucidate the clinical characteristics, treatment response, and course of the illness throughout a 12-month follow-up. The subjects (n=171) were inpatients diagnosed with bipolar I disorder, manic, between 2003 and 2010 and were classified into three groups: "mania" (n=67), "mania with probable mixed features" (n=79), and "mania with definite mixed features" (n=25). Diagnoses were in accordance with the Cincinnati criteria, which include the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision characteristics for a major depressive episode, except for agitation and insomnia. The charts of subjects were retrospectively reviewed for demographic and clinical characteristics prior to the index episode, clinical data regarding the index episode, and treatment courses over a 12-month follow-up period. Subjects in the mania with definite mixed features were more likely to be young at admission, to be female, to have a familial affective loading, and to have a history of suicidality relative to the mania. The results of the present study suggest the need for regular assessment of symptoms associated with both polarities during an episode in routine practice.