Plasmon Hybridizations in Compound Nanorod-Nanohole Arrays.

This study shows that a hybridized plasmonic mode, represented by an additional transmission peak, in a compound structure consisting of a nanorod embedded in a nanohole can be effectively described as a quasi-dipole oscillator. When two nanorods are introduced into a nanohole, these two quasi-dipoles can couple and hybridize, giving rise to two additional transmission peaks in the enhanced optical transmission spectrum. The relative intensities of these peaks can be controlled by adjusting the incident polarization, while their separations can be tuned by modifying the length of the nanorods. The concept of quasi-dipoles in compound nanohole structures can be further extended to predict the coupling behavior of even more complex compound configurations, such as multiple nanorods within nanoholes, resulting in the generation of multiple hybridization states. Consequently, the shape and response of the transmission peaks can be precisely engineered. This strategy could be used to design nanohole-based metasurfaces for applications such as ultra-thin optical filters, waveplates, polarizers, etc.

Towards mechanistic models of mutational effects: Deep learning on Alzheimer's Aß peptide.

Deep Mutational Scanning (DMS) has enabled multiplexed measurement of mutational effects on protein properties, including kinematics and self-organization, with unprecedented resolution. However, potential bottlenecks of DMS characterization include experimental design, data quality, and depth of mutational coverage. Here, we apply deep learning to comprehensively model the mutational effect of the Alzheimer's Disease associated peptide Aß42 on aggregation-related biochemical traits from DMS measurements. Among tested neural network architectures, Convolutional Neural Networks and Recurrent Neural Networks are found to be the most cost-effective models with high performance even under insufficiently-sampled DMS studies. While sequence features are essential for satisfactory prediction from neural networks, geometric-structural features further enhance the prediction performance. Notably, we demonstrate how mechanistic insights into phenotype may be extracted from the neural networks themselves suitably designed. This methodological benefit is particularly relevant for biochemical systems displaying a strong coupling between structure and phenotype such as the conformation of Aß42 aggregate and nucleation, as shown here using a Graph Convolutional Neural Network (GCN) developed from the protein atomic structure input. In addition to accurate imputation of missing values (which here ranged up to 55% of all phenotype values at key residues), the mutationally-defined nucleation phenotype generated from a GCN shows improved resolution for identifying known disease-causing mutations relative to the original DMS phenotype. Our study suggests that neural network derived sequence-phenotype mapping can be exploited not only to provide direct support for protein engineering or genome editing but also to facilitate therapeutic design with the gained perspectives from biological modeling.

The Australian mulga snake (Pseudechis australis: Elapidae): report of a large case series of bites and review of current knowledge.

BACKGROUND: The mulga snake (Pseudechis australis) is the largest terrestrial venomous snake in Australia. It is capable of inflicting severe and occasionally fatal envenoming, but there have been few studies of P. australis bites. OBJECTIVES: To highlight and reinforce the main features of P. australis envenoming and to provide a clearer picture of the epidemiology of bites from this species. METHODS: Selected case records kept by the Toxinology Dept. (Women's and Children's Hospital, Adelaide, Australia) were reviewed retrospectively to determine definite P. australis bites. INCLUSION CRITERIA: definite cases where the snake was identified by a competent person and/or lab specimens (bite site/urine) tested positive for "black snake" using CSL snake venom detection kit in a locality within the known range of P. australis, but without sympatry with other Pseudechis spp. EXCLUSION CRITERIA: where the snake could not be clearly identified under criteria above. Epidemiological and clinical information was recorded and analysed for the definite cases. RESULTS: A total of 27 cases were identified as definite P. australis bites; there were no fatalities. The median age was 35.5 years (IQR 51-23) and 80% of bites occurred in males. More bites occurred in the warmer months (Dec-March) and in those handling/interfering with snakes. Seven people were bitten whilst asleep at night. 21/27 patients developed systemic envenoming (based on signs, symptoms and laboratory results) and 17 cases received antivenom. Local bite site pain (18) and swelling (17) were common as were non-specific generalised symptoms such as nausea, vomiting and headache. Myotoxicity (11) and anticoagulant coagulopathy (10) occurred frequently; haemolysis was seen in fewer cases (3). Two patients developed local tissue injury around the bite site requiring further treatment. CONCLUSIONS: This study confirms previous reports about P. australis bites with respect to high rates of envenoming, commonly associated with pain and swelling and systemic effects of rhabdomyolysis and anticoagulant coagulopathy. Systemic envenoming, even severe cases, responds well to antivenom therapy. Compared to other Australian snakes, a high proportion of bites occur in people asleep at night. Medically significant local tissue injury around the bite site may occur and may be associated with inappropriate first-aid, particularly the vascular occlusive type.