Facial expressions of emotions have been shown to modulate early ERP components, in particular the N170. The underlying anatomical structure producing these early effects are unclear. In this study, we examined the N170 enhancement for fearful expressions in healthy controls as well as epileptic patients after unilateral left or right amygdala resection. We observed a greater N170 for fearful faces in healthy participants as well as in individuals with left amygdala resections. By contrast, the effect was not observed in patients who had undergone surgery in which the right amygdala had been removed. This result demonstrates that the amygdala produces an early brain response to fearful faces. This early response relies specifically on the right amygdala and occurs at around 170 ms. It is likely that such increases are due to a heightened response of the extrastriate cortex that occurs through rapid amygdalofugal projections to the visual areas.This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19. 95 patients with confirmed COVID-19 and a total of 465 serial chest CT scans were involved, including 61 moderate patients (moderate group, 319 chest CT scans) and 34 severe patients (severe group, 146 chest CT scans). Conventional CT scoring and deep learning-based quantification were performed for all chest CT scans for two study goals (1) Correlation between these two estimations; (2) Exploring the dynamic patterns using these two estimations between moderate and severe groups. The Spearman’s correlation coefficient between these two estimation methods was 0.920 (p  less then  0.001). predicted pulmonary involvement (CT score and percent of pulmonary lesions calculated using deep learning-based quantification) increased more rapidly and reached a higher peak on 23rd days from symptom onset in severe group, which reached a peak on 18th days in moderate group with faster absorption of the lesions. The deep learning-based quantification for COVID-19 showed a good correlation with the conventional CT scoring and demonstrated a potential benefit in the estimation of disease severities of COVID-19.Alcohol is a consistently identified risk factor for colon cancer. However, the molecular mechanism underlying its effect on normal colon crypt cells remains poorly understood. We employed RNA-sequencing to asses transcriptomic response to ethanol exposure (0.2% volvol) in 3D organoid lines derived from healthy colon (n = 34). Paired regression analysis identified 2,162 differentially expressed genes in response to ethanol. When stratified by colon location, a far greater number of differentially expressed genes were identified in organoids derived from the left versus right colon, many of which corresponded to cell-type specific markers. To test the hypothesis that the effects of ethanol treatment on colon organoid populations were in part due to differential cell composition, we incorporated external single cell RNA-sequencing data from normal colon biopsies to estimate cellular proportions following single cell deconvolution. We inferred cell-type-specific changes, and observed an increase in transit amplifying cells following ethanol exposure that was greater in organoids from the left than right colon, with a concomitant decrease in more differentiated cells. If this occurs in the colon following alcohol consumption, this would lead to an increased zone of cells in the lower crypt where conditions are optimal for cell division and the potential to develop mutations.Conifer wood is an exceptionally stiff and strong material when its cellulose microfibrils are well aligned. However, it is not well understood how the polymer components cellulose, hemicelluloses and lignin co-operate to resist tensile stress in wood. From X-ray scattering, neutron scattering and spectroscopic data, collected under tension and processed by novel methods, the ordered, disordered and hemicellulose-coated cellulose components comprising each microfibril were shown to stretch together and demonstrated concerted, viscous stress relaxation facilitated by water. Different cellulose microfibrils did not all stretch to the same degree. Attempts were made to distinguish between microfibrils showing large and small elongation but these domains were shown to be similar with respect to orientation, crystalline disorder, hydration and the presence of bound xylan. These observations are consistent with a major stress transfer process between microfibrils being shear at interfaces in direct, hydrogen-bonded contact, as demonstrated by small-angle neutron scattering. If stress were transmitted between microfibrils by bridging hemicelluloses these might have been expected to show divergent stretching and relaxation behaviour, which was not observed. However lignin and hemicellulosic glucomannans may contribute to stress transfer on a larger length scale between microfibril bundles (macrofibrils).We have investigated a new metallic core-shell nanowire (NW) geometry of that could be obtained experimentally, that is silicon (Si) and germanium (Ge) NWs with cores constituted by group-10 elements palladium (Pd) and platinum (Pt). These NWs are optimized with two different diameters of 1.5 Å and 2.5 Å. The nanowires having diameter of 1.5 Å show semi-metallic nature with GGA-PBE calculation and metallic nature while spin orbit interaction (SOC) is included. ART0380 The quantum conductance of the NWs increases with the diameter of the nanowire. We have investigated current-voltage (IV) characteristics for the considered NWs. It has been found that current values in accordance with applied voltage show strong dependence on the diameter of the NWs. The optical study of the NWs shows that absorption co-efficient peak moves to lower energies; due to quantum confinement effect. Furthermore, we have extensively studied optical response of Pd and Pt based core-shell NWs in O2 and CO2 environment. Our study on Si and Ge based metallic core/shell NW show a comprehensive picture as possible electron connector in future nano-electronic devices as well as nano gas detector for detecting O2 gas.