Search

The retrosplenial cortex (RSC) plays a central role in processing contextual fear conditioning. In addition to corticocortical and thalamocortical projections, the RSC receives subcortical inputs, including a substantial projection from the nucleus incertus in the pontine tegmentum. This GABAergic projection contains the neuropeptide, relaxin-3 (RLN3), which inhibits target neurons via its Gi/o-protein-coupled receptor, RXFP3. To assess this peptidergic system role in contextual fear conditioning, we bilaterally injected the RSC of adult rats with an adeno-associated-virus (AAV), expressing the chimeric RXFP3 agonist R3/I5 or a control AAV, and subjected them to contextual fear conditioning. The R3/I5 injected rats did not display any major differences to control-injected and naïve rats but displayed a significantly delayed extinction. Subsequently, we employed acute bilateral injections of the specific RXFP3 agonist peptide, RXFP3-Analogue 2 (A2), into RSC. While the administration of A2 before each extinction trial had no impact on the extinction process, treatment with A2 before each acquisition trial resulted in delayed extinction. In related anatomical studies, we detected an enrichment of RLN3-immunoreactive nerve fibers in deep layers of the RSC, and a higher level of co-localization of RXFP3 mRNA with vesicular GABA transporter (vGAT) mRNA than with vesicular glutamate transporter-1 (vGLUT1) mRNA across the RSC, consistent with an effect of RLN3/RXFP3 signalling on the intrinsic, inhibitory circuits within the RSC. These findings suggest that contextual conditioning processes in the RSC involve, in part, RLN3 afferent modulation of local inhibitory neurons that provides a stronger memory acquisition which, in turn, retards the extinction process.

Data breaches have become a formidable challenge for business operations in the twenty-first century. The emergence of big data in the ever-growing digital economy has created the necessity to secure critical organizational information. The lack of cybersecurity awareness exposes organizations to potential cyber threats. Thus, this research aims to identify the various dimensions of cybersecurity awareness capabilities. Drawing on the dynamic capabilities framework, the findings of the study show personnel (knowledge, attitude and learning), management (training, culture and strategic orientation) and infrastructure capabilities (technology and data governance) as thematic dimensions to tackle cybersecurity awareness challenges.

This paper proposes a novel hybrid model that combines long short term memory LSTM with light gradient boosting LightGBM to achieve precise onshore wind power prediction in Australia The intermittent nature of renewable energy sources like wind power necessitates accurate forecasting to minimize operational costs and enhance power system reliability and security The hybrid model showcases promising results in forecasting 15 minute interval short term wind generation data Performance is evaluated using root mean squared errors RMSE and means absolute errors MAE and compares the proposed model with neural network NN gated recurrent unit GRU and standalone LSTM The comparative analysis demonstrates the superiority of the proposed hybrid model showing lower error indices with exceptional forecasting capability This hybrid LSTM LightGBM model holds great potential for optimizing renewable energy integration into power systems facilitating cost effective and reliable energy generation

Human relaxin-2 (H2 relaxin) is a peptide hormone with potent vasodilatory and anti-fibrotic effects, which is of interest for the treatment of heart failure and fibrosis. H2 relaxin binds to the Relaxin Family Peptide Receptor 1 (RXFP1). Native H2 relaxin is a two-chain, three-disulfide-bond-containing peptide, which is unstable in human serum and difficult to synthesize efficiently. In 2016, our group developed B7-33, a single-chain peptide derived from the B-chain of H2 relaxin. B7-33 demonstrated poor affinity and potency in HEK cells overexpressing RXFP1; however, it displayed equivalent potency to H2 relaxin in fibroblasts natively expressing RXFP1, where it also demonstrated the anti-fibrotic effects of the native hormone. B7-33 reversed organ fibrosis in numerous pre-clinical animal studies. Here, we detail our efforts towards a minimal H2 relaxin scaffold and attempts to improve scaffold activity through Aib substitution and hydrocarbon stapling to re-create the peptide helicity present in the native H2 relaxin.

H2 relaxin is a peptide hormone that exerts its biological actions through the G protein-coupled receptor, RXFP1. The numerous important biological functions of H2 relaxin, including potent renal, vasodilatory, cardioprotective, and anti-fibrotic actions, have resulted in considerable interest in its use as a therapeutic for various cardiovascular diseases and other fibrotic indications. Interestingly though, H2 relaxin and RXFP1 have been shown to be overexpressed in prostate cancer, allowing for the downregulation or blocking of relaxin/RXFP1 to decrease prostate tumor growth. These findings suggest the application of an RXFP1 antagonist for the treatment of prostate cancer. However, these therapeutically relevant actions are still poorly understood and have been hindered by the lack of a high-affinity antagonist. In this study, we chemically synthesized three novel H2 relaxin analogues that have complex insulin-like structures with two chains (A and B) and three disulfide bridges. We report here the structure-activity relationship studies on H2 relaxin that resulted in the development of a novel high-affinity RXFP1 antagonist, H2 B-R13HR (∼40 nM), that has only one extra methylene group in the side chain of arginine 13 in the B-chain (ArgB13) of H2 relaxin. Most notably, the synthetic peptide was shown to be active in a mouse model of prostate tumor growth in vivo where it inhibited relaxin-mediated tumor growth. Our compound H2 B-R13HR will be an important research tool to understand relaxin actions through RXFP1 and may be a potential lead compound for the treatment of prostate cancer.

Exenatide was the first marketed GLP-1 receptor agonist for the treatment of type 2 diabetes. Modification to the chemical structure or the formulation has the potential to increase the stability of exenatide. We introduced human complex-type sialyloligosaccharide to exenatide at the native Asn28 position. The synthesis was achieved using both solid phase peptide synthesis (SPPS) and Omniligase-1-mediated chemoenzymatic ligation. The results demonstrate that glycosylation increases the proteolytic stability of exenatide while retaining its full biological activity.

The hormone, relaxin (RLX), exerts various organ-protective effects independently of etiology. However, its complex two-chain and three disulphide bonded structure is a limitation to its preparation and affordability. Hence, a single chain-derivative of RLX, B7-33, was developed and shown to retain the anti-fibrotic effects of RLX in vitro and in vivo. Here, we determined whether B7-33 could retain the other cardioprotective effects of RLX, and also compared its therapeutic efficacy to the ACE inhibitor, perindopril. Adult male 129sv mice were subjected to isoprenaline (ISO; 25 mg/kg/day, s.c)-induced cardiomyopathy, then s.c-treated with either RLX (0.5 mg/kg/day), B7-33 (0.25 mg/kg/day; equivalent dose corrected for MW) or perindopril (1 mg/kg/day) from days 7-14 post-injury. Control mice received saline instead of ISO. Changes in animal body weight (BW) and systolic blood pressure (SBP) were measured weekly, whilst cardiomyocyte hypertrophy and measures of vascular dysfunction and rarefaction, left ventricular (LV) inflammation and fibrosis were assessed at day 14 post-injury. ISO-injured mice had significantly increased LV inflammation, cardiomyocyte hypertrophy, fibrosis, vascular rarefaction and aortic contractility in the absence of any changes in BW or SBP at day 14 post-injury. Both B7-33 and RLX equivalently reduced LV fibrosis and normalised the ISO-induced LV inflammation and cardiomyocyte hypertrophy, whilst restoring blood vessel density and aortic contractility. Comparatively, perindopril lowered SBP and the ISO-induced LV inflammation and vascular rarefaction, but not fibrosis or hypertrophy. As B7-33 retained the cardioprotective effects of RLX and provided rapid-occurring anti-fibrotic effects compared to perindopril, it could be considered as a cost-effective cardioprotective therapy.

Antimicrobial peptides (AMPs) are potentially powerful alternatives to conventional antibiotics in combating multidrug resistance, given their broad spectrum of activity. They mainly interact with cell membranes through surface electrostatic potentials and the formation of secondary structures, resulting in permeability and destruction of target microorganism membranes. Our earlier work showed that two leading AMPs, MSI‐78 (4–20) and pardaxin (1–22), had potent antimicrobial activity against a range of bacteria. It is known that the attachment of moderate‐length lipid carbon chains to cationic peptides can further improve the functionality of these peptides through enhanced interactions with the membrane lipid bilayer, inducing membrane curvature, destabilization, and potential leakage. Thus, in this work, we aimed to investigate the antimicrobial activity, oligomerization propensity, and lipid‐membrane binding interactions of a range of N‐terminal lipidated analogs of MSI‐78 (4–20) and pardaxin (1–22). Molecular modeling results suggest that aggregation of the N‐lipidated AMPs may impart greater structural stability to the peptides in solution and a greater depth of lipid bilayer insertion for the N‐lipidated AMPs over the parental peptide. Our experimental and computational findings provide insights into how N‐terminal lipidation of AMPs may alter their conformations, with subsequent effects on their functional properties in regard to their self‐aggregation behavior, membrane interactions, and antimicrobial activity.

Human relaxin-2 (H2 relaxin) is therapeutically very important due to its strong anti-fibrotic, vasodilatory, and cardioprotective effects. Therefore, relaxin's receptor, relaxin family peptide receptor 1 (RXFP1), is a potential target for the treatment of fibrosis and related disorders, including heart failure. H2 relaxin has a complex two-chain structure (A and B) and three disulfide bridges. Our laboratory has recently developed B7-33 peptide, a single-chain agonist based on the B-chain of H2 relaxin. However, the peptide B7-33 has a short circulation time in vitro in serum (t1/2 = ~6 min). In this study, we report structure-activity relationship studies on B7-33 utilizing different fatty-acid conjugations at different positions. We have shown that by fatty-acid conjugation with an appropriate spacer length, the in vitro half-life of B7-33 can be increased from 6 min to 60 min. In the future, the lead lipidated molecule will be studied in animal models to measure its PK/PD properties, which will lead to their pre-clinical applications.

The monkeypox virus poses a new pandemic threat while we are still recovering from COVID-19. Despite the fact that monkeypox is not as lethal and contagious as COVID-19, new patient cases are recorded every day. If preparations are not made, a global pandemic is likely. Deep learning (DL) techniques are now showing promise in medical imaging for figuring out what diseases a person has. The monkeypox virus-infected human skin and the region of the skin can be used to diagnose the monkeypox early because an image has been used to learn more about the disease. But there is still no reliable Monkeypox database that is available to the public that can be used to train and test DL models. As a result, it is essential to collect images of monkeypox patients. The "MSID" dataset, short form of "Monkeypox Skin Images Dataset", which was developed for this research, is free to use and can be downloaded from the Mendeley Data database by anyone who wants to use it. DL models can be built and used with more confidence using the images in this dataset. These images come from a variety of open-source and online sources and can be used for research purposes without any restrictions. Furthermore, we proposed and evaluated a modified DenseNet-201 deep learning-based CNN model named MonkeyNet. Using the original and augmented datasets, this study suggested a deep convolutional neural network that was able to correctly identify monkeypox disease with an accuracy of 93.19% and 98.91% respectively. This implementation also shows the Grad-CAM which indicates the level of the model's effectiveness and identifies the infected regions in each class image, which will help the clinicians. The proposed model will also help doctors make accurate early diagnoses of monkeypox disease and protect against the spread of the disease.

Purpose: Despite the availability of several published reviews on the adoption of blockchain (BC) in supply chain (SC), at present, the literature lacks a comprehensive review incorporating the antecedents and consequences of BC adoption. Moreover, the complex adoption of BC in SC, explained with the mediating and moderating relationships, is not fully consolidated. Thus, the aim of this study was to conduct a systematic literature review (SLR) on BC technology adoption (BCTA) in SC by integrating its antecedents and consequences. Design/methodology/approach: Keyword searches were performed in multiple databases resulting 382 articles for evaluation and verification. After careful screening with respect to the purpose of the study and systematic processing of the retrieved articles, a total of 211 peer-reviewed articles were included in this study for review. Findings: Various technological, organisational, individual, social, environmental, operational and economic factors were found as the antecedents of BCTA in SC. In addition, numerous applications of BC Technology (BCT) were identified, including asset management, identity management, transaction management, data management and operations management. Finally, the consequences of BCTA were categorised as operational, risk management, economic and sustainability outcomes. Practical implications: This study can assist relevant decision-makers in managing the factors influencing BCTA and the potential uses of the technology to enhance SC performance. Originality/value: By integrating the antecedents, applications and consequences of BCTA in SC, including the mediators and moderators, an integrated framework was developed that can potentially assist researchers to develop theoretical models. Further, the results of this SLR provide future directions for studying BCTA in supply chain management (SCM).

Purpose: Fake news on social media about COVID-19 pandemic and its associated issues (e.g. lockdown) caused public panic that lead to supply chain (SC) disruptions, which eventually affect firm performance. The purpose of this study is to understand how social media fake news effects firm performance, and how to mitigate such effects. Design/methodology/approach: Grounded on dynamic capability view (DCV), this study suggests that social media fake news effects firm performance via SC disruption (SCD) and SC resilience (SCR). Moreover, the relation between SCD and SCR is contingent upon SC learning (SCL) – a moderated mediation effect. To validate this complex model, the authors suggest effectiveness of using partial least squares structural equation modeling (PLS-SEM). Using an online survey, the results support the authors’ hypotheses. Findings: The results suggest that social media fake news does not affect firm performance directly. However, the authors’ serial mediation test confirms that SCD and SCR sequentially mediate the relationship between social media fake news and firm performance. In addition, a moderated serial mediation test confirms that a higher level of SCL strengthens the SCD–SCR relationship. Research limitations/implications: This work offers a new theoretical and managerial perspective to understand the effect of fake news on firm performance, in the context of crises, e.g. COVID-19. In addition, this study offers the advancement of PLS as more robust for real-world applications and more advantageous when models are complex. Originality/value: Prior studies in the SC and marketing domain suggest different effects of social media fake news on consumer behavior (e.g. panic buying) and SCD, respectively. This current study is a unique effort that investigates the ultimate effect of fake news on firm performance with complex causal relationships via SCD, SCR and SCL.

Social media (SM) fake news has become a serious concern especially during COVID-19. In this study, we develop a research model to investigate to what extent SM fake news contributes to supply chain disruption (SCD), and what are the different SM affordances that contribute to SM fake news. To test the derived hypotheses with survey data, we have applied partial least square based structural equation modelling (PLS-SEM) technique. Further, to identify how different configurations of SC resilience (SCR) capabilities reduce SCD, we have used fuzzy set qualitative comparative analysis (fsQCA). The results show that SM affordances lead to fake news, which increases consumer panic buying (CPB); CPB in turn increases SCD. In addition, SM fake news directly increases SCD. The moderation test suggests that, SCR capability, as a higher-order construct, decreases the effect of CPB on SCD; however, neither of the capabilities individually moderates. Complimentarily, the fsQCA results suggest that no single capability but their three specific configurations reduce SCD. This work offers a new theoretical perspective to study SCD through SM fake news. Our research advances the knowledge of SCR from a configurational lens by adopting an equifinal means towards mitigating disruption. This research will also assist the operations and SC managers to strategize and understand which combination of resilience capabilities is the most effective in tackling disruptions during a crisis e.g., COVID-19. In addition, by identifying the relative role of different SM affordances, this study provides pragmatic insights into SM affordance measures that combat fake news on SM.

The day is rapidly approaching where current antibiotic therapies will no longer be effective due to the development of multi-drug resistant bacteria. Antimicrobial peptides (AMPs) are a promising class of therapeutic agents which have the potential to help address this burgeoning problem. Proline-rich AMPs (PrAMPs) are a sub-class of AMPs, that have multiple modes of action including modulation of the bacterial protein folding chaperone, DnaK. They are highly effective against Gram-negative bacteria and have low toxicity to mammalian cells. Previously we used an in silico approach to identify new potential PrAMPs from the DRAMP database. Four of these peptides, antibacterial napin, attacin-C, P9, and PP30, were each chemically assembled and characterized. Together with synthetic oncocin as a reference, each peptide was then assessed for antibacterial activity against Gram-negative/Gram-positive bacteria and for in vitro DnaK modulation activity. We observed that these peptides directly modulate DnaK activity independently of eliciting or otherwise an antibiotic effect. Based on our findings, we propose a change to our previously established PrAMP definition to remove the requirement for antimicrobial activity in isolation, leaving the following classifiers: >25% proline, modulation of DnaK AND/OR the 70S ribosome, net charge of +1 or more, produced in response to bacterial infection AND/OR with pronounced antimicrobial activity.

The gastrointestinal hormone, insulin-like peptide 5 (INSL5), is found in large intestinal enteroendocrine cells (EEC). One of its functions is to stimulate nerve circuits that increase propulsive activity of the colon through its receptor, the relaxin family peptide 4 receptor (RXFP4). To investigate the mechanisms that link INSL5 to stimulation of propulsion, we have determined the localisation of cells expressing Rxfp4 in the mouse colon, using a reporter mouse to locate cells expressing the gene. The fluorescent signal indicating the location of Rxfp4 expression was in EEC, the greatest overlap of Rxfp4-dependent labelling being with cells containing 5-HT. In fact, > 90% of 5-HT cells were positive for Rxfp4 labelling. A small proportion of cells with Rxfp4-dependent labelling was 5-HT-negative, 11-15% in the distal colon and rectum, and 35% in the proximal colon. Of these, some were identified as L-cells by immunoreactivity for oxyntomodulin. Rxfp4-dependent fluorescence was also found in a sparse population of nerve endings, where it was colocalised with CGRP. We used the RXFP4 agonist, INSL5-A13, to activate the receptor and probe the role of the 5-HT cells in which it is expressed. INSL5-A13 administered by i.p. injection to conscious mice caused an increase in colorectal propulsion that was antagonised by the 5-HT3 receptor blocker, alosetron, also given i.p. We conclude that stimuli that excite INSL5-containing colonic L-cells release INSL5 that, through RXFP4, excites 5-HT release from neighbouring endocrine cells, which in turn acts on 5-HT3 receptors of enteric sensory neurons to elicit propulsive reflexes.

Aim The incidence of major fires is increasing globally, creating extraordinary challenges for governments, managers and conservation scientists. In 2019–2020, Australia experienced precedent‐setting fires that burned over several months, affecting seven states and territories and causing massive biodiversity loss. Whilst the fires were still burning, the Australian Government convened a biodiversity Expert Panel to guide its bushfire response. A pressing need was to target emergency investment and management to reduce the chance of extinctions and maximise the chances of longer‐term recovery. We describe the approach taken to rapidly prioritise fire‐affected animal species. We use the experience to consider the organisational and data requirements for evidence‐based responses to future ecological disasters. Location Forested biomes of subtropical and temperate Australia, with lessons for other regions. Methods We developed assessment frameworks to screen fire‐affected species based on their pre‐fire conservation status, the proportion of their distribution overlapping with fires, and their behavioural/ecological traits relating to fire vulnerability. Using formal and informal networks of scientists, government and non‐government staff and managers, we collated expert input and data from multiple sources, undertook the analyses, and completed the assessments in 3 weeks for vertebrates and 8 weeks for invertebrates. Results The assessments prioritised 92 vertebrate and 213 invertebrate species for urgent management response; another 147 invertebrate species were placed on a watchlist requiring further information. Conclusions The priority species lists helped focus government and non‐government investment, management and research effort, and communication to the public. Using multiple expert networks allowed the assessments to be completed rapidly using the best information available. However, the assessments highlighted substantial gaps in data availability

Antimicrobial peptides (AMPs) are host defense peptides, and unlike conventional antibiotics, they possess potent broad spectrum activities and, induce little or no antimicrobial resistance. They are attractive lead molecules for rational development to improve their therapeutic index. Our current studies examined dimerization of the de novo designed proline-rich AMP (PrAMP), Chex1-Arg20 hydrazide, via C-terminal thiol addition to a series of bifunctional benzene or phenyl tethers to determine the effect of orientation of the peptides and linker length on antimicrobial activity. Antibacterial assays confirmed that dimerization per se significantly enhances Chex1-Arg20 hydrazide action. Greatest advantage was conferred using perfluoroaromatic linkers (tetrafluorobenzene and octofluorobiphenyl) with the resulting dimeric peptides 6 and 7 exhibiting potent action against Gram-negative bacteria, especially the World Health Organization's critical priority-listed multidrug-resistant (MDR)/extensively drug-resistant (XDR) Acinetobacter baumannii as well as preformed biofilms. Mode of action studies indicated these lead PrAMPs can interact with both outer and inner bacterial membranes to affect the membrane potential and stress response. Additionally, 6 and 7 possess potent immunomodulatory activity and neutralise inflammation via nitric oxide production in macrophages. Molecular dynamics simulations of adsorption and permeation mechanisms of the PrAMP on a mixed lipid membrane bilayer showed that a rigid, planar tethered dimer orientation, together with the presence of fluorine atoms that provide increased bacterial membrane interaction, is critical for enhanced dimer activity. These findings highlight the advantages of use of such bifunctional tethers to produce first-in-class, potent PrAMP dimers against MDR/XDR bacterial infections.