Search

HIV-associated neurocognitive deficits include impaired speed-of-information processing (SIP) and motor functions. There is lack of Cameroonian adult norms for assessing SIP or motor functions. This study of 683 Cameroonians (320 HIV+, 363 HIV-) establishes demographically-adjusted norms for six SIP [Wechsler-Adult-Intelligence-Scale (WAIS)-III Digit Symbol (WAIS-IIIDS) and Symbol Search (WAIS-IIISS), Stroop Color-Naming, Stroop Word-Reading, Trail-Making Test-A (TMT-A), Color Trails-1 (CTT1)], and two motor function [Grooved Pegboard-dominant (GP-DH) and non-dominant (GP-NDH) hands] tests. We assessed viral effects on SIP and motor functions. HIV-infected persons had significantly lower (worse) T scores on GP-DH, WAIS-IIIDS, Stroop Word-Reading, TMT-A; lower motor and SIP summary T scores. Significantly higher proportion of cases (20.7%) than controls (10.3%) had impaired SIP. Male cases had better T scores than female cases on GP-NDH, WAIS-IIIDS, WAIS-IIISS, TMT-A, CTT1; better SIP summary T scores. Antiretroviral therapy (ART) was associated with significantly better T scores on GP-NDH, WAIS-IIIDS, Stroop Color-Naming; better motor and SIP summary T scores. Cases with higher CD4 had better T scores on WAIS-IIIDS, TMT-A, CTT1; better SIP summary T scores. Overall, we demonstrate that HIV infection in Cameroon is associated with deficits in SIP and motor functions; ART and higher CD4 are associated with better cognitive performance. We provide SIP and psychomotor functions normative standards, which will be useful for neurobehavioral studies in Cameroon of diseases affecting the brain.

HIV-associated neurocognitive disorders (HAND) are frequently associated with impaired executive function and verbal fluency. Given limited knowledge concerning HAND in Sub-Saharan-Africa and lack of Cameroonian adult neuropsychological (NP) test norms, we administered four executive function [Halstead Category Test (HCT), Wisconsin Card Sorting Test (WCST), Color Trails-II (CTT2), and Stroop Color-Word-Interference (SCWT)] and three verbal fluency (Category, Action, and Letter Fluency) tests to 742 adult Cameroonians (395 HIV-, 347 HIV+). We developed demographically-corrected NP test norms and examined the effects of HIV and related variables on subjects' executive function and verbal fluency. HIV+ subjects had significantly lower T-scores on CTT2 (P = 0.005), HCT (P = 0.032), WCST (P

Malignant mesothelioma (MM) is a rare aggressive tumor, and bone metastasis often occurs in later stages of this disease. This study aimed to establish a nomogram to predict the prognosis of bone metastasis of patients with MM. Data from the Surveillance, Epidemiology, and End Results database were screened and retrieved. This study included 311 patients with MM with bone metastases. Prognostic factors were analyzed using the Kaplan–Meier method and Cox proportional hazards model. A nomogram for overall survival (OS) was established and evaluated using statistically significant prognostic factors, and cancer-specific survival (CSS) analysis was performed to investigate its prognostic factors. In addition, the metastasis patterns of patients with MM were investigated, and the effects of different sites of metastasis on survival were compared using the Kaplan–Meier method. Age, sex, histological type, and chemotherapy were identified as the independent risk factors for OS. The 1-, 2-, and 3-year areas under the curve of the nomogram were 0.792, 0.774, and 0.928, and 0.742, 0.733, and 0.733 in the training and validation sets, respectively. Compared to OS, histological type, radiotherapy, and chemotherapy were independent risk factors for CSS. Different metastatic sites in MM have significantly different effects on prognosis. [ABSTRACT FROM AUTHOR]

Gas-insulated switchgear (GIS) is widely used across multiple electric stages and different power grid levels. However, the threat from several inevitable faults in the GIS system surrounds us for the safety of electricity use. In order to improve the evaluation ability of GIS system safety, we propose an efficient strategy by using machine learning to conduct SF6 decomposed components analysis (DCA) for further diagnosing discharge fault types in GIS. Note that the empirical probability function of different faults fitted by the Arrhenius chemical reaction model has been investigated into the robust feature engineering for machine learning based GIS diagnosing model. Six machine learning algorithms were used to establish models for the severity of discharge fault and main insulation defects, where identification algorithms were trained by learning the collection dataset composing the concentration of the different gas types (SO2, SOF2, SO2F2, CF4, and CO2, etc.) in the system and their ratios. Notably, multiple discharge fault types coexisting in GIS can be effectively identified based on a probability model. This work would provide a great insight into the development of evaluation and optimization on solving discharge fault in GIS. [ABSTRACT FROM AUTHOR]