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Xuelong Li,1– 3 Yakun Gao,4 Yiyi Liu,1– 3 Ying Wang,1– 3,* Qing Wu1– 3,5,* 1School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, People’s Republic of China; 2Department of Psychiatry, Affiliated Psychological Hospital of Anhui Medical University, Hefei, People’s Republic of China; 3Anhui Mental Health Center, Hefei, People’s Republic of China; 4Affiliated Hospital of Weifang Medical College, Weifang, People’s Republic of China; 5Hefei Fourth People’s Hospital, Hefei, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ying Wang; Qing Wu, Department of Psychiatry, Affiliated Psychological Hospital of Anhui Medical University, 316 Huangshan Road, Hefei, 230000, People’s Republic of China, Tel +86-13866136686 ; +86-13856919530, Email wyinghf@163.com; wuqinghf@163.comPurpose: Identifying patients with bipolar disorder (BD) in manic states (BD-M) who are at a high risk of physical violence is a matter of clinical concern. This retrospective institution-based study aimed to identify simple, rapid, and inexpensive clinical markers of physical violence in patients with BD-M.Patients and Methods: The anonymized sociodemographic variables (sex, age, years of education, marital status) and clinical ones (weight, height, body mass index, blood pressure, the score of BRMS, number of BD episodes, psychotic symptoms, history of violence, biochemical parameters, and blood routine parameters) of 316 BD-M participants were collected, and the risk of physical violence was identified using the Brøset Violence Checklist (BVC). Difference tests, correlation analyses, and multivariate linear regression analysis were performed to identify clinical markers for the risk of physical violence.Results: The participants were categorized into groups at low (49, 15.51%), medium (129, 40.82%), and high (138, 43.67%) risk of physical violence. The number of BD episodes, serum uric acid

Objective: Intracranial arterial calcification (IAC) is a risk factor of ischemic stroke. However, the relationship between IAC patterns and clinical outcome of ischemic stroke remains controversial. We aimed to investigate the correlation between IAC patterns and the effects of reperfusion therapy among acute stroke patients. Methods: Consecutive acute ischemic stroke patients who underwent reperfusion therapy were included. IAC was categorized as intimal or medial. Based on its involvement, IAC was further classified as diffuse or focal. Neurologic dysfunction was assessed by the National Institute of Health stroke scale (NIHSS). Clinical outcome including favorable neurologic outcome (FNO) and early neurologic deterioration (END) were assessed. Results: Of 130 patients, 117 had IAC. Intimal IAC was identified in 74.6% of patients and medial IAC was present in 64.6% of patients. Diffuse IAC was present in 31.5% of patients. All diffuse IACs were medial pattern. Diffuse IAC was associated with higher baseline NIHSS (p = 0.011) and less FNO (p = 0.047). Compared with patients with focal or single diffuse IAC, patients with multiple diffuse IAC had higher baseline NIHSS (p = 0.002) and less FNO (p = 0.024). Multivariable linear regression (p < 0.001) and logistic regression (p = 0.027) suggested that multiple diffuse IAC was associated with higher baseline NIHSS and less FNO. No significant association was found between END and different IAC patterns. Interpretation: Multiple diffuse medial IAC may predict severer neurologic dysfunction and less favorable neurologic outcome after reperfusion therapy in acute stroke patients.

Xuelong Li,1– 3 Yakun Gao,4 Yongmei Wang,2,3,5 Ying Wang,2,3,5,&ast; Qing Wu1– 3,5,&ast; 1School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, People’s Republic of China; 2Department of Psychiatry, Affiliated Psychological Hospital of Anhui Medical University, Hefei, People’s Republic of China; 3Anhui Mental Health Center, Hefei, People’s Republic of China; 4Affiliated Hospital of Weifang Medical College, Weifang, People’s Republic of China; 5Hefei Fourth People’s Hospital, Hefei, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Qing Wu, Department of Psychiatry, Affiliated Psychological Hospital of Anhui Medical University, 316 Huangshan Road, Hefei, 230000, People’s Republic of China, Tel +86-13856919530, Email wuqinghf@163.com Ying Wang, Department of Psychiatry, Affiliated Psychological Hospital of Anhui Medical University, 316 Huangshan Road, Hefei, 230000, People’s Republic of China, Tel +86-13866136686, Email wyinghf@163.comPurpose: Long-term hospitalized patients with schizophrenia (SCZ) are vulnerable to physical illness, leading to impaired life expectancy and treatment outcomes. There are few studies on the influence of non-alcoholic fatty liver disease (NAFLD) in long-term hospitalized patients. This study aimed to investigate the prevalence of and influence factors for NAFLD in hospitalized patients with SCZ.Patients and Methods: This cross-sectional retrospective study included 310 patients who had experienced long-term hospitalization for SCZ. NAFLD was diagnosed based on the results of abdominal ultrasonography. The T-test, Mann–Whitney U-test, correlation analysis, and logistic regression analysis were used to determine the influence factors for NAFLD.Results: Among the 310 patients who had experienced long-term hospitalization for SCZ, the prevalence of NAFLD was 54.84%. Antipsychotic polypharmacy (APP), body mass index (BMI), hypertension

Normalized-Cut (N-Cut) is a famous model of spectral clustering. The traditional N-Cut solvers are two-stage: 1) calculating the continuous spectral embedding of normalized Laplacian matrix; 2) discretization via $K$-means or spectral rotation. However, this paradigm brings two vital problems: 1) two-stage methods solve a relaxed version of the original problem, so they cannot obtain good solutions for the original N-Cut problem; 2) solving the relaxed problem requires eigenvalue decomposition, which has $\mathcal{O}(n^3)$ time complexity ($n$ is the number of nodes). To address the problems, we propose a novel N-Cut solver designed based on the famous coordinate descent method. Since the vanilla coordinate descent method also has $\mathcal{O}(n^3)$ time complexity, we design various accelerating strategies to reduce the time complexity to $\mathcal{O}(|E|)$ ($|E|$ is the number of edges). To avoid reliance on random initialization which brings uncertainties to clustering, we propose an efficient initialization method that gives deterministic outputs. Extensive experiments on several benchmark datasets demonstrate that the proposed solver can obtain larger objective values of N-Cut, meanwhile achieving better clustering performance compared to traditional solvers.