Development of a novel angiotensin converting enzyme 2 stimulator with broad implications in SARS-CoV2 and type 1 diabetes.

Angiotensin-converting enzyme 2 (ACE2) is protective in cardiovascular disease, lung injury and diabetes yet paradoxically underlies our susceptibility to SARs-CoV2 infection and the fatal heart and lung disease it can induce. Furthermore, diabetic patients have chronic, systemic inflammation and altered ACE2 expression resulting in increased risk of severe COVID-19 and the associated mortality. A drug that could increase ACE2 activity and inhibit cellular uptake of severe acute respiratory syndrome coronavirus 2 (SARs-CoV2), thus decrease infection, would be of high relevance to cardiovascular disease, diabetes and SARs-CoV2 infection.

The relative performance of geometric morphometrics and linear-based methods in the taxonomic resolution of a mammalian species complex.

Morphology-based taxonomic research frequently applies linear morphometrics (LMM) in skulls to quantify species distinctions. The choice of which measurements to collect generally relies on the expertise of the investigators or a set of standard measurements, but this practice may ignore less obvious or common discriminatory characteristics. In addition, taxonomic analyses often ignore the potential for subgroups of an otherwise cohesive population to differ in shape purely due to size differences (or allometry).

Identification of new potential downstream transcriptional targets of the strigolactone pathway including glucosinolate biosynthesis.

Strigolactones regulate shoot branching and many aspects of plant growth, development, and allelopathy. Strigolactones are often discussed alongside auxin because they work together to inhibit shoot branching. However, the roles and mechanisms of strigolactones and how they act independently of auxin are still elusive.

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN.

Deep learning-based models have achieved significant success in detecting cardiac arrhythmia by analyzing ECG signals to categorize patient heartbeats. To improve the performance of such models, we have developed a novel hybrid hierarchical attention-based bidirectional recurrent neural network with dilated CNN (HARDC) method for arrhythmia classification. This solves problems that arise when traditional dilated convolutional neural network (CNN) models disregard the correlation between contexts and gradient dispersion.

Cryptic diversity and spatial genetic variation in the coral and its endosymbionts across the Great Barrier Reef.

Genomic studies are uncovering extensive cryptic diversity within reef-building corals, suggesting that evolutionarily and ecologically relevant diversity is highly underestimated in the very organisms that structure coral reefs. Furthermore, endosymbiotic algae within coral host species can confer adaptive responses to environmental stress and may represent additional axes of coral genetic variation that are not constrained by taxonomic divergence of the cnidarian host. Here, we examine genetic variation in a common and widespread, reef-building coral, , and its associated endosymbiotic algae along the entire expanse of the Great Barrier Reef (GBR).

Experimental and computational insights into the mechanism of FLP mediated selective C-F bond activation.

Frustrated Lewis pairs (FLP) comprising of B(CF) (BCF) and 2,4,6-triphenylpyridine (TPPy), P(-Tol) or tetrahydrothiophene (THT) have been shown to mediate selective C-F activation in both geminal and chemically equivalent distal C-F sites. In comparison to other reported attempts of C-F activation using BCF, these reactions appear surprisingly facile. We investigate this reaction through a combination of experimental and computational chemistry to understand the mechanism of the initial C-F activation event and the origin of the selectivity that prevents subsequent C-F activation in the monoactivated salts.

Field-based adipose tissue quantification in sea turtles using bioelectrical impedance spectroscopy validated with CT scans and deep learning.

Loss of adipose tissue in vertebrate wildlife species is indicative of decreased nutritional and health status and is linked to environmental stress and diseases. Body condition indices (BCI) are commonly used in ecological studies to estimate adipose tissue mass across wildlife populations. However, these indices have poor predictive power, which poses the need for quantitative methods for improved population assessments.

Synthesis of full-length homodimer αD-VxXXB that targets human α7 nicotinic acetylcholine receptors.

αD-Conotoxin VxXXB is a pseudo-homodimer that allosterically inhibits nicotinic acetylcholine receptors (nAChRs) with high potency and selectivity. However, challenges in synthesizing αD-conotoxins have hindered further structure-function studies on this novel class of peptides. To address this gap, we synthesized and characterized its C-terminal domain (CTD) and N-terminal domain (NTD).

Evaluation of endometrial thickness by transvaginal ultrasound and baseline risk factors as a predictor for endometrial abnormalities in postmenopausal women.

Introduction/purpose: To evaluate the endometrial thickness (ET) as a predictor of endometrial abnormalities in postmenopausal women and whether consideration of baseline risk factors increases diagnostic accuracy.

Methods: This is a retrospective observational study of postmenopausal women presenting with bleeding or thickened endometrium (≥4 mm) on ultrasound, between 2003 and 2012. Risk factors for endometrial abnormality were analysed using logistic regression.

Mesoscopic in vivo human T dataset acquired using quantitative MRI at 7 Tesla.

Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for advancing neuroscience and bridging the resolution gap with animal models.

Selective separation of planar and non-planar hydrocarbons using an aqueous Pd interlocked cage.

Polycyclic aromatic hydrocarbons (PAHs) find multiple applications ranging from fabric dyes to optoelectronic materials. Hydrogenation of PAHs is often employed for their purification or derivatization. However, separation of PAHs from their hydrogenated analogues is challenging because of their similar physical properties.

Enhanced primary care after hospitalization: General practitioner, pharmacist and patient feedback from the REMAIN HOME trial.

Background: Pharmacist and general practitioner (GP) collaborative models of care are continuing to evolve in the Australian primary care setting. The REMAIN HOME study investigated whether a pharmacist integrated into 14 different primary care teams in general practice (the "practice pharmacist model") reduces readmission to hospital for patients prescribed five or more long term medicines or high risk comorbidities. The aim of this paper is to describe the attitudes of GPs, patients, and practice pharmacists towards this model of pharmacist and GP collaboration.

Continuous flow fabrication of green graphene oxide in aqueous hydrogen peroxide.

Highly processible graphene oxide (GO) has a diversity of applications as a material readily dispersed in aqueous media. However, methods for preparing such free-standing GO use hazardous and toxic reagents and generate significant waste streams. This is an impediment for uptake of GO in any application, for developing sustainable technologies and industries, and overcoming this remains a major challenge.

SCMRSA: a New Approach for Identifying and Analyzing Anti-MRSA Peptides Using Estimated Propensity Scores of Dipeptides.

is deemed to be one of the major causes of hospital and community-acquired infections, especially in methicillin-resistant (MRSA) strains. Because antimicrobial peptides have captured attention as novel drug candidates due to their rapid and broad-spectrum antimicrobial activity, anti-MRSA peptides have emerged as potential therapeutics for the treatment of bacterial infections. Although experimental approaches can precisely identify anti-MRSA peptides, they are usually cost-ineffective and labor-intensive.

Mesoporous sodium four-coordinate aluminosilicate nanoparticles modulate dendritic cell pyroptosis and activate innate and adaptive immunity.

Pyroptosis is a programmed cell death widely studied in cancer cells for tumour inhibition, but rarely in dendritic cell (DC) activation for vaccine development. Here, we report the synthesis of sodium stabilized mesoporous aluminosilicate nanoparticles as DC pyroptosis modulators and antigen carriers. By surface modification of sodium-stabilized four-coordinate aluminium species on dendritic mesoporous silica nanoparticles, the resultant Na-Al-DMSN significantly activated DC through caspase-1 dependent pyroptosis pH responsive intracellular ion exchange.

Physical and Chemical Cues at the Nano-Bio Interface for Immunomodulation.

Immunomodulation has made remarkable progress in fighting infectious disease and cancer. Conventionally, immunomodulation largely relies on chemical/biochemical agents, which, unfortunately, suffer from sever off-target adverse effects. Recent insights into nano-bio interactions suggest that nanomaterials can directly participate in immunomodulation.

NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides.

Tumor homing peptides (THPs) play a crucial role in recognizing and specifically binding to cancer cells. Although experimental approaches can facilitate the precise identification of THPs, they are usually time-consuming, labor-intensive, and not cost-effective. However, computational approaches can identify THPs by utilizing sequence information alone, thus highlighting their great potential for large-scale identification of THPs.

A classification of MRI brain tumor based on two stage feature level ensemble of deep CNN models.

The brain tumor is one of the deadliest cancerous diseases and its severity has turned it to the leading cause of cancer related mortality. The treatment procedure of the brain tumor depends on the type, location and size of the tumor. Relying solely on human inspection for precise categorization can lead to inevitably dangerous situation.

Surface plasmon-driven photoelectrochemical water splitting of a Ag/TiO nanoplate photoanode.

A silver/titanium dioxide nanoplate (Ag/TiO NP) photoelectrode was designed and fabricated from vertically aligned TiO nanoplates (NP) decorated with silver nanoparticles (NPs) through a simple hydrothermal synthesis and electrodeposition route. The electrodeposition times of Ag NPs on the TiO NP were crucial for surface plasmon-driven photoelectrochemical (PEC) water splitting performance. The Ag/TiO NP at the optimal deposition time of 5 min with a Ag element content of 0.

Inhibition of N-type calcium ion channels by tricyclic antidepressants - experimental and theoretical justification for their use for neuropathic pain.

A number of tricyclic antidepressants (TCAs) are commonly prescribed off-label for the treatment of neuropathic pain. The blockade of neuronal calcium ion channels is often invoked to partially explain the analgesic activity of TCAs, but there has been very limited experimental or theoretical evidence reported to support this assertion. The N-type calcium ion channel (Ca2.

Fine-tuning the spike: role of the nature and topology of the glycan shield in the structure and dynamics of the SARS-CoV-2 S.

The dense glycan shield is an essential feature of the SARS-CoV-2 spike (S) architecture, key to immune evasion and to the activation of the prefusion conformation. Recent studies indicate that the occupancy and structures of the SARS-CoV-2 S glycans depend not only on the nature of the host cell, but also on the structural stability of the trimer; a point that raises important questions about the relative competence of different glycoforms. Moreover, the functional role of the glycan shield in the SARS-CoV-2 pathogenesis suggests that the evolution of the sites of glycosylation is potentially intertwined with the evolution of the protein sequence to affect optimal activity.

StackDPPIV: A novel computational approach for accurate prediction of dipeptidyl peptidase IV (DPP-IV) inhibitory peptides.

The development of efficient and effective bioinformatics tools and pipelines for identifying peptides with dipeptidyl peptidase IV (DPP-IV) inhibitory activities from large-scale protein datasets is of great importance for the discovery and development of potential and promising antidiabetic drugs. In this study, we present a novel stacking-based ensemble learning predictor (termed StackDPPIV) designed for identification of DPP-IV inhibitory peptides. Unlike the existing method, which is based on single-feature-based methods, we combined five popular machine learning algorithms in conjunction with ten different feature encodings from multiple perspectives to generate a pool of various baseline models.

Diagnosis of hearing deficiency using EEG based AEP signals: CWT and improved-VGG16 pipeline.

Hearing deficiency is the world's most common sensation of impairment and impedes human communication and learning. Early and precise hearing diagnosis using electroencephalogram (EEG) is referred to as the optimum strategy to deal with this issue. Among a wide range of EEG control signals, the most relevant modality for hearing loss diagnosis is auditory evoked potential (AEP) which is produced in the brain's cortex area through an auditory stimulus.

Posttranslational modifications of α-conotoxins: sulfotyrosine and C-terminal amidation stabilise structures and increase acetylcholine receptor binding.

Conotoxins are peptides found in the venoms of marine cone snails. They are typically highly structured and stable and have potent activities at nicotinic acetylcholine receptors, which make them valuable research tools and promising lead molecules for drug development. Many conotoxins are also highly modified with posttranslational modifications such as proline hydroxylation, glutamic acid gamma-carboxylation, tyrosine sulfation and C-terminal amidation, amongst others.

rMisbeta: A robust missing value imputation approach in transcriptomics and metabolomics data.

Transcriptomics and metabolomics data often contain missing values or outliers due to limitations of the data acquisition techniques. Most of the statistical methods require complete datasets for downstream analysis. A number of methods have been developed for missing value imputation using the classical mean and variance based on maximum likelihood estimators, which are not robust against outliers.