Trace elements in road-deposited and waterbed sediments in Kogarah Bay, Sydney: Enrichment, sources and fractionation

© 2015 CSIRO. Trace elements (TEs) in road-deposited sediments (RDS) can be transported by stormwater to neighbouring water bodies to cause aquatic pollution. A study was conducted in Kogarah Bay, Sydney, Australia, to assess the possible sources and potential mobility of TEs in RDS and the contribution to the TE load to the adjacent waterbed sediments in canals and the bay. Of the 11 TEs analysed, pseudo-total concentrations of zinc (Zn), copper (Cu), vanadium (V), chromium (Cr), and antimony (Sb) were greatly enriched in RDS over baseline soils (top 10cm depth) collected in bushlands. All TE concentrations in waterbed sediments (top 10cm depth) were similar to those in baseline soils but lower than in RDS. Correlation and principal component analyses revealed that Zn, Cu, Cr and Sb were related to each other in RDS, and probably originated from tyres and brake linings. Vanadium occurred in another component, likely to have originated mainly from road asphalt. Pseudo-total and mobile-fraction (0.1m acetic acid, pH 2.85 extraction) TE concentrations in RDS were: iron>manganese, Zn>Cu, lead>Cr, nickel, V, Sb, cadmium. The potential ecological TE risk was low to medium in RDS but low in baseline soils and waterbed sediments

Digital and circular technologies for climate-smart and sustainable agriculture: The case of Vietnamese coffee

\ua9 Published under licence by IOP Publishing Ltd.This comprehensive article addresses the pressing challenges confronting the global agriculture, primarily driven by climate change and resource constraints. With a focus on promoting climate-smart and sustainable agricultural practices, the study explores the transformative potential of emerging technologies, e.g., the innovative use of digital technologies like Internet of Things, Artificial Intelligence, and Blockchain, showcasing real-world examples of their benefits, and circular technologies, e.g., waste-to-value practices. The challenges of population growth, climate change, environmental impact, and the plight of smallholder farmers are elucidated. Climate-Smart Agriculture initiatives supported by the World Bank Group demonstrate practical efforts in addressing these challenges, aligning with sustainable development goals. Here, we introduce an innovative and smart agriculture (INNSA) platform for the creation and operation of sustainable coffee value chain in Vietnam as a case of study. Thought-provoking questions for future research conclude the review, encouraging interdisciplinary collaboration. In summary, this article provides a compelling case for adopting sustainable agricultural practices through digital and circular technologies, offering a roadmap for global agriculture\u27s transformation and resilience in the face of climate change

Environmentally Responsible Bioengineering for Spore Surface Expression of <em>Helicobacter pylori </em>Antigen

The development of genetic technologies and bioengineering are creating an increasing number of genetically engineered microorganisms with new traits for diverse industrial applications such as vaccines, drugs and pollutant degraders. However, the destiny of genetically engineered bacterial spores released into the environment as long-life organisms has remained a big environmental challenge. In this study, an environmentally responsible and sustainable gene technology solution based on the concept of thymine starvation is successfully applied for cloning and expression of a Helicobacter pylori antigen on Bacillus subtilis spore surface. As an example, a recombinant Bacillus subtilis strain A1.13 has been created from a gene fusion of the corresponding N-terminal fragment of spore coat protein CotB in B. subtilis and the entire urease subunit A (UreA) in H. pylori and the fusion showed a high stability of spore surface expression. The outcomes can open the door for developing highly safe spore vectored vaccines against this kind of pathogen and contributing to reduced potential risks of genetically engineered microorganisms released in the environment

Artificial intelligence-based solutions for coffee leaf disease classification

Coffee is one of the most widely consumed beverages and the quantity and quality of coffee beans depend significantly on the health and condition of coffee plants, particularly their leaves. The automation of coffee leaf disease classification using AI is an essential need, providing not only economic benefits but also contributing to environmental conservation and creating better conditions for sustainable coffee cultivation. Through the application of AI, early disease detection is facilitated, thereby reducing pest and disease control costs, minimizing crop losses, increasing coffee productivity and product quality, and promoting environmental preservation. Many studies have proposed AI algorithms for coffee disease classification. However, numerous algorithms employ classical algorithms, while some utilize deep learning, the current state-of-the-art in computer vision. The challenge lies in the fact that when using deep learning, a substantial amount of data is required for training. The design of deep learning architectures to enhance model accuracy while still working with a small training dataset remains an area of ongoing research. In this study, we propose deep learning-based method for coffee leaf disease classification. We propose the combination of different deep convolutional neural networks to further improve overall classification performance. Early and late fusion have been conducted to evaluate the effectiveness of the pre-trained model. Our experimental results demonstrate that the ensemble method outperforms single-model approaches, achieving high accuracy and precision in BRACOL coffee disease leaf

Relative efficacy of topical non-steroidal anti-inflammatory drugs and topical capsaicin in osteoarthritis: protocol for an individual patient data meta-analysis

Background Pain is the most troubling issue to patients with osteoarthritis (OA), yet current pharmacological treatments offer only small-to-moderate pain reduction. Current guidelines therefore emphasise the need to identify predictors of treatment response. In line with these recommendations, an individual patient data (IPD) meta-analysis will be conducted. The study aims to investigate the relative treatment effects of topical non-steroidal anti-inflammatory drugs (NSAIDs) and topical capsaicin in OA and to identify patient-level predictors of treatment response. Methods IPD will be collected from randomised controlled trials (RCTs) of topical NSAIDs and capsaicin in OA. Multilevel regression modelling will be conducted to determine predictors for the specific and the overall treatment effect. Discussion Through the identification of treatment responders, this IPD meta-analysis may improve the current understanding of the pain mechanisms in OA and guide clinical decision-making. Identifying and prescribing the treatment most likely to be beneficial for an individual with OA will improve the efficiency of patient management

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

High-Content Chemical and RNAi Screens for Suppressors of Neurotoxicity in a Huntington's Disease Model

To identify Huntington's Disease therapeutics, we conducted high-content small molecule and RNAi suppressor screens using a Drosophila primary neural culture Huntingtin model. Drosophila primary neurons offer a sensitive readout for neurotoxicty, as their neurites develop dysmorphic features in the presence of mutant polyglutamine-expanded Huntingtin compared to nonpathogenic Huntingtin. By tracking the subcellular distribution of mRFP-tagged pathogenic Huntingtin and assaying neurite branch morphology via live-imaging, we identified suppressors that could reduce Huntingtin aggregation and/or prevent the formation of dystrophic neurites. The custom algorithms we used to quantify neurite morphologies in complex cultures provide a useful tool for future high-content screening approaches focused on neurodegenerative disease models. Compounds previously found to be effective aggregation inhibitors in mammalian systems were also effective in Drosophila primary cultures, suggesting translational capacity between these models. However, we did not observe a direct correlation between the ability of a compound or gene knockdown to suppress aggregate formation and its ability to rescue dysmorphic neurites. Only a subset of aggregation inhibitors could revert dysmorphic cellular profiles. We identified lkb1, an upstream kinase in the mTOR/Insulin pathway, and four novel drugs, Camptothecin, OH-Camptothecin, 18β-Glycyrrhetinic acid, and Carbenoxolone, that were strong suppressors of mutant Huntingtin-induced neurotoxicity. Huntingtin neurotoxicity suppressors identified through our screen also restored viability in an in vivo Drosophila Huntington's Disease model, making them attractive candidates for further therapeutic evaluation.National Institutes of Health (U.S.) (grant R01 EB007042)National Institutes of Health (U.S.

Atomically dispersed nickel-nitrogen-sulfur species anchored on porous carbon nanosheets for efficient water oxidation

Developing low-cost electrocatalysts to replace precious Ir-based materials is key for oxygen evolution reaction (OER). Here, we report atomically dispersed nickel coordinated with nitrogen and sulfur species in porous carbon nanosheets as an electrocatalyst exhibiting excellent activity and durability for OER with a low overpotential of 1.51 V at 10 mA cm(-2) and a small Tafel slope of 45 mV dec(-1) in alkaline media. Such electrocatalyst represents the best among all reported transition metal- and/or heteroatom-doped carbon electrocatalysts and is even superior to benchmark Ir/C. Theoretical and experimental results demonstrate that the well-dispersed molecular S vertical bar NiNx species act as active sites for catalyzing OER. The atomic structure of S vertical bar NiNx centers in the carbon matrix is clearly disclosed by aberration-corrected scanning transmission electron microscopy and synchrotron radiation X-ray absorption spectroscopy together with computational simulations. An integrated photoanode of nanocarbon on a Fe2O3 nanosheet array enables highly active solar-driven oxygen production

Genomic and vaccine preclinical studies reveal a novel mouse-adapted Helicobacter pylori model for the hpEastAsia genotype in Southeast Asia

\ua9 2024 Crown Copyright.Introduction. Helicobacter pylori infection is a major global health concern, linked to the development of various gastrointestinal diseases, including gastric cancer. To study the pathogenesis of H. pylori and develop effective intervention strategies, appropriate animal pathogen models that closely mimic human infection are essential. Gap statement. This study focuses on the understudied hpEastAsia genotype in Southeast Asia, a region marked by a high H. pylori infection rate. No mouse-adapted model strains has been reported previously. Moreover, it recognizes the urgent requirement for vaccines in developing countries, where overuse of antimicrobials is fuelling the emergence of resistance. Aim. This study aims to establish a novel mouse-adapted H. pylori model specific to the hpEastAsia genotype prevalent in Southeast Asia, focusing on comparative genomic and histopathological analysis of pathogens coupled with vaccine preclinical studies. Methodology. We collected and sequenced the whole genome of clinical strains of H. pylori from infected patients in Vietnam and performed comparative genomic analyses of H. pylori strains in Southeast Asia. In parallel, we conducted preclinical studies to assess the pathogenicity of the mouse-adapted H. pylori strain and the protective effect of a new spore-vectored vaccine candidate on male Mlac:ICR mice and the host immune response in a female C57BL/6 mouse model. Results. Genome sequencing and comparison revealed unique and common genetic signatures, antimicrobial resistance genes and virulence factors in strains HP22 and HP34; and supported clarithromycin-resistant HP34 as a representation of the hpEastAsia genotype in Vietnam and Southeast Asia. HP34-infected mice exhibited gastric inflammation, epithelial erosion and dysplastic changes that closely resembled the pathology observed in human H. pylori infection. Furthermore, comprehensive immunological characterization demonstrated a robust host immune response, including both mucosal and systemic immune responses. Oral vaccination with candidate vaccine formulations elicited a significant reduction in bacterial colonization in the model. Conclusion. Our findings demonstrate the successful development of a novel mouse-adapted H. pylori model for the hpEastAsia genotype in Vietnam and Southeast Asia. Our research highlights the distinctive genotype and pathogenicity of clinical H. pylori strains in the region, laying the foundation for targeted interventions to address this global health burden

Expression of Wnt gene family and frizzled receptors in head and neck squamous cell carcinomas

[Abstract] Genes of the Wnt and Frizzled class, expressed in HNSCC tissue and cell lines, have an established role in cell morphogenesis and differentiation, and also they have oncogenic properties. We studied Wnt and Fz genes as potential tumor-associated markers in HNSCC by qPCR. Expression levels of Wnt and Fz genes in 22 unique frozen samples from HNSCC were measured. We also assessed possible correlation between the expression levels obtained in cancer samples in relation to clinicopathologic outcome. Wnt-1 was not expressed in the majority of the HNSCC studied, whereas Wnt-5A was the most strongly expressed by the malignant tumors. Wnt-10B expression levels were related with higher grade of undifferentiation. Related to Fz genes, Fz-5 showed more expression levels in no-affectation of regional lymph nodes. Kaplan–Meier survival analyses suggest a reduced time of survival for low and high expression of Wnt-7A and Fz-5 mRNA, respectively. qPCR demonstrated that HNSCC express Wnt and Fz members, and suggested that Wnt and Fz signaling is activated in HNSCC cells