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

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

Weather-it missions: a social network analysis perspective of an online citizen inquiry community

Citizen inquiry is an innovative informal science learning approach, which engages members of the general public in scientific investigations sparked by their personal experience of everyday science, and to which other members can contribute. This paper aims to describe the network of interactions and contributions of Weather-it, an online Citizen Inquiry community accommodated by the nQuire-it platform, which involves people in creating and maintaining their own weather missions (investigations). The interaction patterns within Weather-it are mainly explored through social network analysis of community members and missions. The results indicate the quiet and active members within the community, their splitting into sub-communities, and their contribution and data collection methods and preferences. These results provide in-sight into the behaviour of people in such public engagement projects

Collapsing glomerulopathy in sickle cell disease: a case report

<p>Abstract</p> <p>Introduction</p> <p>Sickle cell disease has been associated with many renal structural and functional abnormalities. Collapsing glomerulopathy or the collapsing variant of focal segmental glomerulosclerosis is a rare clinicopathologic entity in patients with sickle cell disease that requires timely diagnosis and aggressive management.</p> <p>Case presentation</p> <p>In this case report we describe a 21-year-old African-American woman with a medical history of significant sickle cell disease and asthma. She was admitted for pain, decreased urine output, bilateral leg swelling and reported weight gain. During her period of hospitalisation she developed acute renal failure requiring dialysis. Further investigation revealed the collapsing variant of focal segmental glomerulosclerosis.</p> <p>Conclusions</p> <p>Although focal segmental glomerulosclerosis is a common feature of sickle cell nephropathy, the collapsing variant of focal segmental glomerulosclerosis or collapsing glomerulopathy has been rarely documented. Even when other risk factors are controlled, collapsing glomerulopathy has a very poor prognosis. This is a rare case of a patient with massive proteinuria presenting as acute renal failure with a very poor response to corticosteroids and a much faster rate of progression to end-stage renal disease.</p

Interactive metagenomic visualization in a Web browser

<p>Abstract</p> <p>Background</p> <p>A critical output of metagenomic studies is the estimation of abundances of taxonomical or functional groups. The inherent uncertainty in assignments to these groups makes it important to consider both their hierarchical contexts and their prediction confidence. The current tools for visualizing metagenomic data, however, omit or distort quantitative hierarchical relationships and lack the facility for displaying secondary variables.</p> <p>Results</p> <p>Here we present Krona, a new visualization tool that allows intuitive exploration of relative abundances and confidences within the complex hierarchies of metagenomic classifications. Krona combines a variant of radial, space-filling displays with parametric coloring and interactive polar-coordinate zooming. The HTML5 and JavaScript implementation enables fully interactive charts that can be explored with any modern Web browser, without the need for installed software or plug-ins. This Web-based architecture also allows each chart to be an independent document, making them easy to share via e-mail or post to a standard Web server. To illustrate Krona's utility, we describe its application to various metagenomic data sets and its compatibility with popular metagenomic analysis tools.</p> <p>Conclusions</p> <p>Krona is both a powerful metagenomic visualization tool and a demonstration of the potential of HTML5 for highly accessible bioinformatic visualizations. Its rich and interactive displays facilitate more informed interpretations of metagenomic analyses, while its implementation as a browser-based application makes it extremely portable and easily adopted into existing analysis packages. Both the Krona rendering code and conversion tools are freely available under a BSD open-source license, and available from: <url>http://krona.sourceforge.net</url>.</p

Randomized double-blind placebo-controlled trial of sublingual immunotherapy in children with house dust mite allergy in primary care: study design and recruitment

Background. For respiratory allergic disorders in children, sublingual immunotherapy has been developed as an alternative to subcutaneous immunotherapy. Sublingual immunotherapy is more convenient, has a good safety profile and might be an attractive option for use in primary care. A randomized double-blind placebo-controlled study was designed to establish the ef

A Mitochondria-Dependent Pathway Mediates the Apoptosis of GSE-Induced Yeast

Grapefruit seed extract (GSE), which has powerful anti-fungal activity, can induce apoptosis in S. cerevisiae. The yeast cells underwent apoptosis as determined by testing for apoptotic markers of DNA cleavage and typical chromatin condensation by Terminal Deoxynucleotidyl Transferase–mediated dUTP Nick End Labeling (TUNEL) and 4,6′-diaminidino-2-phenylindole (DAPI) staining and electron microscopy. The changes of ΔΨmt (mitochondrial transmembrane potential) and ROS (reactive oxygen species) indicated that the mitochondria took part in the apoptotic process. Changes in this process detected by metabonomics and proteomics revealed that the yeast cells tenaciously resisted adversity. Proteins related to redox, cellular structure, membrane, energy and DNA repair were significantly increased. In this study, the relative changes in the levels of proteins and metabolites showed the tenacious resistance of yeast cells. However, GSE induced apoptosis in the yeast cells by destruction of the mitochondrial 60 S ribosomal protein, L14-A, and prevented the conversion of pantothenic acid to coenzyme A (CoA). The relationship between the proteins and metabolites was analyzed by orthogonal projections to latent structures (OPLS). We found that the changes of the metabolites and the protein changes had relevant consistency

Microbial Communities in Long-Term, Water-Flooded Petroleum Reservoirs with Different in situ Temperatures in the Huabei Oilfield, China

The distribution of microbial communities in the Menggulin (MGL) and Ba19 blocks in the Huabei Oilfield, China, were studied based on 16S rRNA gene analysis. The dominant microbes showed obvious block-specific characteristics, and the two blocks had substantially different bacterial and archaeal communities. In the moderate-temperature MGL block, the bacteria were mainly Epsilonproteobacteria and Alphaproteobacteria, and the archaea were methanogens belonging to Methanolinea, Methanothermobacter, Methanosaeta, and Methanocella. However, in the high-temperature Ba19 block, the predominant bacteria were Gammaproteobacteria, and the predominant archaea were Methanothermobacter and Methanosaeta. In spite of shared taxa in the blocks, differences among wells in the same block were obvious, especially for bacterial communities in the MGL block. Compared to the bacterial communities, the archaeal communities were much more conserved within blocks and were not affected by the variation in the bacterial communities

Molecular Detection of Anaerobic Ammonium-Oxidizing (Anammox) Bacteria in High-Temperature Petroleum Reservoirs

Anaerobic ammonium-oxidizing (anammox) process plays an important role in the nitrogen cycle of the worldwide anoxic and mesophilic habitats. Recently, the existence and activity of anammox bacteria have been detected in some thermophilic environments, but their existence in the geothermal subterranean oil reservoirs is still not reported. This study investigated the abundance, distribution and functional diversity of anammox bacteria in nine out of 17 high-temperature oil reservoirs by molecular ecology analysis. High concentration (5.31–39.2 mg l−1) of ammonium was detected in the production water from these oilfields with temperatures between 55°C and 75°C. Both 16S rRNA and hzo molecular biomarkers indicated the occurrence of anammox bacteria in nine out of 17 samples. Most of 16S rRNA gene phylotypes are closely related to the known anammox bacterial genera Candidatus Brocadia, Candidatus Kuenenia, Candidatus Scalindua, and Candidatus Jettenia, while hzo gene phylotypes are closely related to the genera Candidatus Anammoxoglobus, Candidatus Kuenenia, Candidatus Scalindua, and Candidatus Jettenia. The total bacterial and anammox bacterial densities were 6.4 ± 0.5 × 103 to 2.0 ± 0.18 × 106 cells ml−1 and 6.6 ± 0.51 × 102 to 4.9 ± 0.36 × 104 cell ml−1, respectively. The cluster I of 16S rRNA gene sequences showed distant identity (<92%) to the known Candidatus Scalindua species, inferring this cluster of anammox bacteria to be a new species, and a tentative name Candidatus “Scalindua sinooilfield” was proposed. The results extended the existence of anammox bacteria to the high-temperature oil reservoirs