Tongue coating-dependent superior temporal sulcus remodeling in amnestic mild cognitive impairment.

Tongue coating affects cognition, and cognitive decline at early stage also showed relations to functional and structural remodeling of superior temporal sulcus (STS) in amnestic mild cognitive impairment (aMCI). The potential correlation between disparate cognitive manifestations in aMCI patients with different tongue coatings, and corresponding mechanisms of STS remodeling remains uncharted. In this case-control study, aMCI patients were divided into thin coating (n = 18) and thick coating (n = 21) groups. All participants underwent neuropsychological evaluations and multimodal magnetic resonance imaging. Group comparisons were conducted in clinical assessments and neuroimaging measures of banks of the STS (bankssts). Generalized linear models were constructed to explore relationships between neuroimaging measures and cognition. aMCI patients in the thick coating group exhibited significantly poorer immediate and delayed recall and slower information processing speed (IPS) (P < 0.05), and decreased functional connectivity (FC) of bilateral bankssts with frontoparietal cortices (P < 0.05, AlphaSim corrected) compared to the thin coating group. It was found notable correlations between cognition encompassing recall and IPS, and FC of bilateral bankssts with frontoparietal cortices (P < 0.05, Bonferroni's correction), as well as interaction effects of group × regional homogeneity (ReHo) of right bankssts on the first immediate recall (P < 0.05, Bonferroni's correction). aMCI patients with thick coating exhibited poor cognitive performance, which might be attributed to decreased FC seeding from bankssts. Our findings strengthen the understanding of brain reorganization of STS via which tongue coating status impacts cognition in patients with aMCI.

Breast carcinoma-amplified sequence 2 regulates adult neurogenesis via ß-catenin.

BACKGROUND: Breast carcinoma-amplified sequence 2 (BCAS2) regulates ß-catenin gene splicing. The conditional knockout of BCAS2 expression in the forebrain (BCAS2 cKO) of mice confers impaired learning and memory along with decreased ß-catenin expression. Because ß-catenin reportedly regulates adult neurogenesis, we wondered whether BCAS2 could regulate adult neurogenesis via ß-catenin. METHODS: BCAS2-regulating neurogenesis was investigated by characterizing BCAS2 cKO mice. Also, lentivirus-shBCAS2 was intracranially injected into the hippocampus of wild-type mice to knock down BCAS2 expression. We evaluated the rescue effects of BCAS2 cKO by intracranial injection of adeno-associated virus encoding BCAS2 (AAV-DJ8-BCAS2) and AAV-ß-catenin gene therapy. RESULTS: To show that BCAS2-regulating adult neurogenesis via ß-catenin, first, BCAS2 cKO mice showed low SRY-box 2-positive (Sox2+) neural stem cell proliferation and doublecortin-positive (DCX+) immature neurons. Second, stereotaxic intracranial injection of lentivirus-shBCAS2 knocked down BCAS2 in the hippocampus of wild-type mice, and we confirmed the BCAS2 regulation of adult neurogenesis via ß-catenin. Third, AAV-DJ8-BCAS2 gene therapy in BCAS2 cKO mice reversed the low proliferation of Sox2+ neural stem cells and the decreased number of DCX+ immature neurons with increased ß-catenin expression. Moreover, AAV-ß-catenin gene therapy restored neuron stem cell proliferation and immature neuron differentiation, which further supports BCAS2-regulating adult neurogenesis via ß-catenin. In addition, cells targeted by AAV-DJ8 injection into the hippocampus included Sox2 and DCX immature neurons, interneurons, and astrocytes. BCAS2 may regulate adult neurogenesis by targeting Sox2+ and DCX+ immature neurons for autocrine effects and interneurons or astrocytes for paracrine effects. CONCLUSIONS: BCAS2 can regulate adult neurogenesis in mice via ß-catenin.

A batch copyright scheme for digital image based on deep neural network.

Digital signature and watermarking are effective image copyright protection techniques. However, these methods come with some inherent drawbacks, including the incapacity of carrying information and inevitable fidelity loss, respectively. To improve this situation, this paper proposes a neural network-based image batch copyright protection scheme, with which a copyright message bitstream can be extracted from each registered image while no modifications are introduced. Taking advantage of the pattern extraction capability and the error tolerance of the neural network, the proposed scheme achieves perfect imperceptibility and superior robustness. Moreover, the network's preference for diverse data content makes it especially appropriate for multiple images copyright verification. These claims will be further supported by the experimental results in this paper.