How to Tailor Structural Colors for Extended Visibility and White Light Generation Employing Direct Laser Interference Patterning

The appearance of a surface can be controlled by creating periodic microstructures designed to diffract light and produce structural colors. Nevertheless, since structural coloration is based on diffraction, the produced colors have a strong dependence on the viewing angle and absence of coloration takes place while tilting the samples. In this work direct laser interference patterning is used to firstly provide transparent polymer sheets a structural coloration with a high‐range observation angle, and secondly to demonstrate the combination of structural colors, producing a white coloring effect. The employed approaches are based on the fabrication of micro‐gratings with multiple periods in the same structured area and on the engineering of the diffraction orders of the diffraction spectrum. The patterned surfaces are characterized by confocal microscopy and angular spectrometry in reflection mode. The morphological characterization shows homogeneous surface patterns, while the spectral results demonstrate that combining four spatial periods on a single patterned surface, a white appearance is obtained over an angular observation range higher than 30°. The experimental results are supported by theoretical predictions by means of generalized formulas based on the diffraction of light.     

Toys will be toys: gendered interaction frames in the Toy Story trilogy

The following qualitative textual analysis examined female characters within the Toy Story trilogy and used grounded theory to explore themes between female characters and male characters based on their interactions. The study, built upon past literature in gaze theory, revealed six distinct interaction themes between female and male characters. Findings included that female characters were often emotionally supportive of male characters, were lusted after by male characters, were romantically aggressive towards male characters, and were paired with male characters at the conclusion of each film. Changes in themes throughout the trilogy and the presence of these themes in children’s media, and in relation to existing theory, are also discussed.     

HE4 as a predictor of adjuvant chemotherapy resistance and survival in patients with epithelial ovarian cancer

The aim of this study was to investigate the value of serum human epididymis protein 4 (HE4) and HE4 tissue protein expression to predict tumor resistance to adjuvant chemotherapy, progression‐free survival (PFS), and overall survival in patients with epithelial ovarian cancer (EOC). Consecutive inclusion of 198 patients diagnosed with EOC was conducted. Blood samples were collected prior to surgery and tissue samples during surgery. Patient data were registered prospectively in the Danish Gynecologic Cancer Database. The association between serum HE4 and HE4 tissue protein expression, resistance to adjuvant chemotherapy, PFS, and overall survival were analyzed in univariate analyses and in multivariate analyses adjusted for age, performance score, surgical outcome, stage, grade, and histological subtype. Serum HE4 levels predicted chemotherapy resistance, PFS, and overall survival correlated significantly (p < 0.001) in the univariate analyses; but after adjustment in a multivariate model, serum HE4 was insignificant, except in a subgroup analysis of postmenopausal women, where serum HE4 significantly predicted resistance to chemotherapy and progression‐free survival. HE4 tissue protein expression predicted PFS (p = 0.022) and overall survival (p = 0.047) in the univariate analysis, while HE4 tissue protein expression failed to predict these outcomes in the adjusted multivariate analyses. Serum HE4 or HE4 tissue protein expression are not independent factors of chemotherapy resistance or survival in patients with EOC, but serum HE4 might predict chemotherapy resistance and PFS in postmenopausal women.     

A Computer-Aided Decision Support System for Detection and Localization of Cutaneous Vasculature in Dermoscopy Images Via Deep Feature Learning

Vascular structures of skin are important biomarkers in diagnosis and assessment of cutaneous conditions. Presence and distribution of lesional vessels are associated with specific abnormalities. Therefore, detection and localization of cutaneous vessels provide critical information towards diagnosis and stage status of diseases. However, cutaneous vessels are highly variable in shape, size, color and architecture, which complicate the detection task. Considering the large variability of these structures, conventional vessel detection techniques lack the generalizability to detect different vessel types and require separate algorithms to be designed for each type. Furthermore, such techniques are highly dependent on precise hand-crafted features which are time-consuming and computationally inefficient. As a solution, we propose a data-driven feature learning framework based on stacked sparse auto-encoders (SSAE) for comprehensive detection of cutaneous vessels. Each training image is divided into small patches of either containing or non-containing vasculature. A multilayer SSAE is designed to learn hidden features of the data in hierarchical layers in an unsupervised manner. The high-level learned features are subsequently fed into a classifier which categorizes each patch into absence or presence of vasculature and localizes vessels within the lesion. Over a test set of 3095 patches derived from 200 images, the proposed framework demonstrated superior performance of 95.4% detection accuracy over a variety of vessel patterns; outperforming other techniques by achieving the highest positive predictive value of 94.7%. The proposed Computer-Aided Diagnosis (CAD) framework can serve as a decision support system assisting dermatologists for more accurate diagnosis, especially in teledermatology applications in remote areas.     

Openness to experience predicts intrinsic value shifts after deliberating one’s own death

Individual differences that might moderate processes of value shifting during and after deliberating one’s own death remain largely unexplored. Two studies measured participants’ openness and relative intrinsic-to-extrinsic value orientation (RIEVO) before randomly assigning them to conditions in which they wrote about their own death or dental pain for 6 days, after which RIEVO was assessed again up to 12 days later. When participants confronted thoughts about their own death over a sustained period, high openness to experience helped them shift toward intrinsic values. Implications for understanding openness’ role in value reorientation from existential deliberation processes are discussed.     

Functional studies and rare variant screening of SLC1A1/EAAC1 in males with obsessive-compulsive disorder

Several studies have found that the neuronal glutamate transporter gene SLC1A1/EAAC1 is associated with obsessive-compulsive disorder (OCD), with a stronger association in males. Previous studies have primarily focused on common single-nucleotide polymorphisms, rather than rare functional variants that are likely to have larger effects. We screened 184 males with OCD for rare variation in SLC1A1 exons; however, no new coding variation was found. When combined with previous screens, only one SLC1A1 amino acid variant has been detected among the 841 individuals screened, which is less than for other neurotransmitter transporter genes (P=0.0001). We characterized the function of the one SLC1A1 missense variant reported previously in OCD, Thr164Ala, and found that the Ala164 allele leads to decreased Vmax and Km (P<0.0001) in transfected human embryonic kidney cells. Further work will be necessary to understand the impact of this rare SLC1A1/EAAC1 Ala164 variant on neuronal function and circuitry relevant to OCD.