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Dengue virus (DENV) infection is the most prevalent mosquito-borne viral disease. Stroke is a severe manifestation of dengue. However, few large-scale studies have investigated post-dengue risk of stroke. This population-based cohort study included 57,934 newly diagnosed, laboratory-confirmed dengue patients in Taiwan from 2002 to 2015; patients were matched to nondengue individuals by age, sex, and area of residence at a ratio of 1:4 (n = 231,736). We used subdistribution hazard regression to evaluate short-term (≤ 30 days), medium-term (31–365 days), and long-term (1–3 years) risk of stroke after DENV infection. The robustness of the results to unmeasured confounding was assessed with E-values. DENV infection was associated with a significantly increased risk of overall stroke (aSHR 4.51; 95% CI: 3.23–6.32; P < 0.0001; E-value = 8.49), hemorrhagic stroke (aSHR 4.13; 95% CI: 2.20–7.76; P < 0.0001; E-value =7.73), and ischemic stroke (aSHR 3.80; 95% CI: 2.37–6.11; P < 0.0001; E-value = 7.06) within 30 days. Stratified analysis by age showed that the aSHRs for overall stroke, hemorrhagic stroke, and ischemic stroke were larger among dengue patients aged ≥ 65 during the first 30 days. The 30-day risks of overall stroke, hemorrhagic stroke, and ischemic stroke among elderly dengue patients were 6.71, 1.29, and 3.49 per 1000, respectively. No increased risk was observed after 30 days. DENV infection was associated with a significant short-term increased risk of stroke. Clinical practitioners should remain alert to patients with stroke-associated symptoms during epidemic seasons, especially elderly patients. [ABSTRACT FROM AUTHOR]

• A stable rigid-body reference developed for analyzing axial deformations of tunnel faces based on plane strain theory; • A new assumption proposed to address the issues on the registration and deformation vector tracking of non-rigid objects monitored; • A high-accuracy point cloud registration algorithm for the object under a state of plane strain; • Automatic and accurate measurement of tunnel face displacement fields using terrestrial laser scanning data. The instability of tunnel faces is a serious geological hazard, thus requiring monitoring and prediction of the stability of tunnel faces. This paper presents a high-accuracy method for estimating the displacement fields of tunnel faces from terrestrial laser scanning data. The proposed method consists of four parts: i) the development of a stable rigid-body reference under planar strain assumption, ii) the fine alignment of the rigid-body references using the developed local deformation constrained rigid-body assumption (LDC-RBA) and local cross-validation iterative closest point (LCV-ICP) algorithm, iii) the segmentation of tunnel faces using a machine learning classifier, and iv) tracking of tunnel face displacement vectors under the LDC-RBA. Qualitative experimental results demonstrate that the estimated displacement fields of the tunnel face using the proposed method conform to the deformation law. Furthermore, quantitative experimental results indicate that the estimation accuracy of tunnel face displacement fields achieves millimeter-level. [ABSTRACT FROM AUTHOR]

• Core tensor sparsity of a Tucker-2 model is enhanced in a particular Tucker-3 model. • Orthogonality constraint is imposed on the third mode matrix to remove cross-talks. • The proposed model is solved by ADMM and HQS using tensor flattening method. • The proposed method improves estimations of non-sparse spatial components. • Novel features of cross-subject relationship increase the classification accuracy. The Tucker-2 decomposition model can reveal the intrinsic relationship in three-way multi-subject fMRI data by fully utilizing tensor structural information and also provide spatial and temporal evidences at both individual and shared levels. However, the third mode factor matrix of Tucker-2 model is an identity matrix, resulting in insufficient sparseness of the core tensor. In this work, we propose a method to enhance core tensor sparsity within the Tucker-2 model. More precisely, the proposed method is a relaxed approach for the Tucker-2 model by separating a non-identity factor matrix in the third mode from the core tensor. An orthogonality constraint is imposed on the third mode factor matrix to eliminate cross-talks, in addition to low-rank constraints on other factor matrices and sparsity constraint on spatial maps. We represent the propose model by flattened tensors, and solve the model using alternating direction method of multipliers and half quadratic splitting. The third mode factor matrix is updated by the orthogonal Procrustes solution. We show results from simulated fMRI data, task-related fMRI data, and resting-state fMRI data including patients with schizophrenia and controls. These results highlight the improvement of the proposed method at both shared and individual levels, compared with the sparsity-low rank-constraint Tucker-2 model and the generalized Tucker-3 model. Moreover, we show that we can extract the cross-subject relationship (CSR) from the third mode matrix. The proposed method improves the estimations of non-sparse spatial sources. The novel CSR matrix bring 7% improvement of accuracy when classifying schizophrenia patients and healthy controls. [ABSTRACT FROM AUTHOR]

[Display omitted] • RIPK2 functions a critical role in gastric carcinoma-related cachexia development in mice. • Methylnissolin protects against gastric carcinoma-related cachexia by regulating RIPK2. • RIPK2 overexpression blocks lipid homeostasis and reduces lipid biosynthesis in mice. • Methylnissolin suppresses RIPK2-mediated lipid homeostasis dysfunction and decreased lipid biosynthesis. • RIPK2 overexpression decreases the expression of lipogenesis genes in TgRC mice. • Deactivating ASK1 improves lipid homeostasis and inhibits gastric carcinoma-related cachexia. Gastric carcinoma (GC) is one of the most common malignant tumors worldwide, and ranks fifth in incidence and top 5 in tumor-associated mortality. Unfortunately, the molecular mechanisms contributing to GC development are still unclear, urgently requiring more studies. It has been proposed that the multifunctional regulator receptor-interacting protein 2 (RIPK2) is both a regulator that induces stomach cancer and its complications such as cachexia. However, the potential molecular function of RIPK2 on regulation of GC is largely unknown. Moreover, 3,9-di-O-methylnissolin, a flavonoid derived from the roots of Astragalus membranaceus, exhibits protective effects against cancer, inflammation, and bacterial infections. Unfortunately the antineoplastic mechanism of oral exposure of such flavonoid are poorly understood. It remains unknown whether 3,9-di-O-methylnissolin is capable of mitigating GC progression, and potential molecular mechanism. This study aims to provide mechanistic evidence that the 3,9-di-O-methylnissolin-triggered mitigation of GC by repressing RIPK2 activity and its downstream ASK1 signaling. The TCGA database, GEO database, subjects with GC phenotype and GC cell lines were used in this work. 3,9-di-O-methylnissolin intervention reduces stomach cancer cell migration, proliferation and invasion in vitro. Also, 3,9-di-O-methylnissolin confers protection against tumor growth in xenograft model in vivo. Mechanistically, on the other hand, in the para -carcinoma tissue, overexpression of RIPK2 reduces lipogenesis and disturbs lipid homeostasis. Overexpression of RIPK2 activates downstream signaling of ASK1, which in turn downregulates PPARα, a master regulator of lipid metabolism. This process results in lower lipogenesis and downregulation of a set of PPARα target genes. Astragalus membranaceus naturally produces 3,9-di-O-methylnissolin, a bioactive substance that when suppression of ASK1 by methylnissolin reduces RIPK2-induced GC and its related cachexia and restores lipid homeostasis. These findings offer important new understandings of stomach cancer and could aid in the development of treatment plans for gastric carcinoma and cachexia related to cancer. [ABSTRACT FROM AUTHOR]

The human cerebellum emerges as a posterior brain structure integrating neural networks for sensorimotor, cognitive, and emotional processing across the lifespan. Developmental studies of the cerebellar anatomy and function are scant. We examine age-dependent MRI morphometry of the anterior cerebellar vermis , lobules I-V and posterior neocortical lobules VI-VII and their relationship to sensorimotor and cognitive functions. Typically developing children (TDC; n=38; age 9–15) and healthy adults (HAC; n=31; 18–40) participated in high-resolution MRI. Rigorous anatomically informed morphometry of the vermis lobules I-V and VI-VII and total brain volume (TBV) employed manual segmentation computer-assisted FreeSurfer Image Analysis Program [ http://surfer.nmr.mgh.harvard.edu ]. The neuropsychological scores (WASI-II) were normalized and related to volumes of anterior, posterior vermis, and TBV. TBVs were age independent. Volumes of I-V and VI-VII were significantly reduced in TDC. The ratio of VI-VII to I-V (∼60%) was stable across age-groups; I-V correlated with visual-spatial-motor skills; VI-VII with verbal, visual-abstract and FSIQ. In TDC neither anterior I-V nor posterior VI-VII vermis attained adult volumes. The "inverted U" developmental trajectory of gray matter peaking in adolescence does not explain this finding. The hypothesis of protracted development of oligodendrocyte/myelination is suggested as a contributor to TDC's lower cerebellar vermis volumes. [ABSTRACT FROM AUTHOR]