Black-spot shell disease is an unresolved disease that decreases pearl quality and threatens pearl oyster survival. In previous studies, the bacterium Tenacibaculum sp. strain Pbs-1 was isolated from diseased Akoya pearl oysters Pinctada fucata, and a rapid, specific, and sensitive loop-mediated isothermal amplification (LAMP) assay for detecting this pathogen was established. This technology has considerable potential for routine diagnosis of strain Pbs-1 in oyster hatcheries and/or pearl farms; therefore, it is vital to identify substances in environmental samples that might inhibit LAMP and to find additives that can reduce the inhibition. In this study, we investigated the effects of six chemicals or proteins, otherwise known as conventional PCR inhibitors, on LAMP, using the DNA of strain Pbs-1 as template: humic acid, urea, iron (III) chloride hexahydrate, melanin, myoglobin, and Ethylenediamine-N,N,N\',N\'-tetraacetic acid, disodium salt, dihydrate (EDTA; pH 6.5). Next, to reduce the effects of identified inhibitors, we tested the addition of bovine serum albumin (BSA) or T4 gene 32 protein (gp32) to the LAMP assay. When 50 ng of DNA template was used, 4 ng/μL of humic acid, 0.05% melanin, and 10 mM of EDTA (pH 6.5) inhibited the LAMP reaction, whereas myoglobin, urea, and FeCl3 had no effect. When 50 pg of DNA template was used, 4 ng/μL of humic acid, 0.05% melanin, 4 μg/μL of myoglobin, 10 μg/μL of urea, and 10 mM of EDTA inhibited the LAMP reaction. Thus, it was shown that the gene-amplification inhibitory effect of melanin, humic acid, and urea could be reduced by adding BSA or gp32 to the LAMP reaction mixture. This technique could be applied as part of a protocol to prevent mass mortalities of pearl oysters; moreover, the results enhance our knowledge about substances that inhibit LAMP and methods to reduce the inhibition, which have rarely been reported.

Fetal growth restriction (FGR) impacts 5%-10% of pregnancies and is associated with increased risk of mortality and morbidity. Although adverse neurodevelopmental outcomes are observed in up to 50% of FGR infants, a diagnosis of FGR does not indicate the level of risk for an individual infant and these infants are not routinely followed up to assess neurodevelopmental outcomes. Identifying FGR infants at increased risk of adverse neurodevelopmental outcomes would greatly assist in providing appropriate support and interventions earlier, resulting in improved outcomes. However, current methods to detect brain injury around the time of birth lack the sensitivity required to detect the more subtle alterations associated with FGR. Blood biomarkers have this potential. This systematic review assessed the current literature on blood biomarkers for identifying FGR infants at increased risk of adverse neurodevelopmental outcomes at >12 months after birth. Four databases were searched from inception to 22 February 2024. Articles were assessed for meeting the inclusion criteria by two reviewers. The quality of the included article was assessed using Quality Assessment of Diagnostic Accuracy Studies-2. A summary of findings is presented as insufficient articles were identified for meta-analysis. Excluding duplicates, 1,368 records were screened with only 9 articles considered for full text review. Only one article met all the inclusion criteria. Quality assessment indicated low risk of bias. Both blood biomarkers investigated in this study, neuron specific enolase and S100B, demonstrated inverse relationships with neurodevelopmental assessments at 2 years. Four studies did not meet all the inclusion criteria yet identified promising findings for metabolites and cytokines which are discussed here. These findings support the need for further research and highlight the potential for blood biomarkers to predict adverse outcomes.
UNASSIGNED: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=369242, Identifier CRD42022369242.

The development of nanozymes (NZ) for the simultaneous detection of multiple target chemicals is gaining paramount attention in the field of food and health sciences, and waste management industries. Nanozymes (NZ) effectively compensate for the environmental vulnerability of natural enzymes. Considering the development gap of NZ with diverse applications, we synthesized versatile Schiff\'s base ligands following a facile route and readily available starting reagents (glutaraldehyde, aminopyridines). DPDI, one of the synthesized ligands, readily reacted with transition metal ions (Cu+2, Ag+1, Zn+2 in specific) under ambient conditions, yielding the corresponding nanoparticles/MOF. The structures of ligands and their products were confirmed using various analytical techniques. The enzymatic efficacy of DPDI-Cu (km 0.25 mM=, Vmax = 10.75 µM/sec) surpassed Tremetese versicolor laccase efficacy (km 0. 5 mM=, Vmax = 2.15 µM/sec). Additionally, DPDI-Cu proved resilient to changing pH, temperature, ionic strength, organic solvent, and storage time compared to laccase and provided reusability. DPDI-Cu proved promising for colorimetric detection of dopamine, epinephrine, catechol, tetracycline, and quercetin. The mechanism of oxidative detection of TC was studied through LC/MS analysis. DPDI-Cu-bentonite composite efficiently adsorbed tetracycline with maximum Langmuir adsorption of 208 mg/g. Moreover, DPDI/Cu and DPDI-Ag nanoparticles possessed antifungal activity exhibiting a minimum inhibitory concentration of 400 µg/mL and 3.12 µg/mL against Aspergillus flavus. Florescent dye tracking and SEM/TEM analysis confirmed that DPDI-Ag caused disruption of the plasma membrane and triggered ROS generation and apoptosis-like death in fungal cells. The DPDI-Ag coating treatment of wheat seeds confirmed the non-phytotoxicity of Ag-NPs.

Cronobacter species are potential pathogens that can contaminate powdered infant formula. C. sakazakii and C. malonaticus are the most common species of Cronobacter associated with infections. This study mined new molecular targets for the detection of C. sakazakii and C. malonaticus by using comparative genome approaches. Specific target genes mngB and ompR were obtained and used to detect C. sakazakii and C. malonaticus, respectively. A novel detection method, termed ladder-shape melting temperature isothermal amplification (LMTIA), was developed and evaluated. The detection limit for pure C. sakazakii DNA was 1 pg per reaction and 1 fg per reaction for C. malonaticus. The C. sakazakii, C. malonaticus, and the reference stains were all correctly identified. The amplicons can be successfully visualized and identified by naked eyes when hydroxy naphthol blue dye (HNB dye) was used in the reaction. Therefore, the LMTIA assays developed in this study showed potential application for microorganism identification and detection.

A new eco-friendly sensor, 3-((6-((4-chlorobenzylidene)amino)pyridin-2-yl)imino)indolin-2-one (CBAPI) was synthesized and well characterized. The CBAPI sensor was employed for detecting Zn2+ and Fe3+ ions. It exhibited a low limit of detection at pH 6.0, with values of 2.90, for Zn2+ and 3.59 nmol L-1 for Fe3+ ions. The sensor demonstrated high selectivity over other interfering cations. Additionally, the high binding constants reflect the great affinity of sensor towards Zn2+ and Fe3+ ions. To further validate its quantification ability for Zn2+ ions, the synthesized CBAPI sensor was used to determine Zn levels in human hair samples, and the results were confirmed using atomic absorption spectroscopy (AAS). The AGREE metric tool was used to assess the method\'s environmental impact and practical applicability. These positive outcomes indicated that the new method for detecting Zn2+ and Fe3+ ions is environmentally friendly and safe for humans. The developed CBAPI sensor represents a potential development in metal ion detection, combining sensitivity, selectivity, and rapidity.

Oleaginous fungi have attracted a great deal of interest for their potency to accumulate high amounts of lipids (more than 20% of biomass dry weight) and polyunsaturated fatty acids (PUFAs), which have a variety of industrial and biological applications. Lipids of plant and animal origin are related to some restrictions and thus lead to attention towards oleaginous microorganisms as reliable substitute resources. Lipids are traditionally biosynthesized intra-cellularly and involved in the building structure of a variety of cellular compartments. In oleaginous fungi, under certain conditions of elevated carbon ratio and decreased nitrogen in the growth medium, a change in metabolic pathway occurred by switching the whole central carbon metabolism to fatty acid anabolism, which subsequently resulted in high lipid accumulation. The present review illustrates the bio-lipid structure, fatty acid classes and biosynthesis within oleaginous fungi with certain key enzymes, and the advantages of oleaginous fungi over other lipid bio-sources. Qualitative and quantitative techniques for detecting the lipid accumulation capability of oleaginous microbes including visual, and analytical (convenient and non-convenient) were debated. Factors affecting lipid production, and different approaches followed to enhance the lipid content in oleaginous yeasts and fungi, including optimization, utilization of cost-effective wastes, co-culturing, as well as metabolic and genetic engineering, were discussed. A better understanding of the oleaginous fungi regarding screening, detection, and maximization of lipid content using different strategies could help to discover new potent oleaginous isolates, exploit and recycle low-cost wastes, and improve the efficiency of bio-lipids cumulation with biotechnological significance.

This review examines the utilization of nanotechnology-based chemosensors for identifying environmental toxic ions. Over recent decades, the creation of nanoscale materials for applications in chemical sensing, biomedical, and biological analyses has emerged as a promising avenue. Nanomaterials play a vital role in improving the sensitivity and selectivity of chemosensors, thereby making them effective tools for monitoring and evaluating environmental contamination. This is due to their highly adjustable size- and shape-dependent chemical and physical properties. Nanomaterials possess distinct surface chemistry, thermal stability, high surface area, and large pore volume per unit mass, which can be harnessed for sensor development. The discussion encompasses different types of nanomaterials utilized in chemosensor design, LOD, their sensing mechanisms, and their efficacy in detecting specific toxic ions. Furthermore, the review explores the progress made, obstacles faced, and future prospects in this rapidly evolving field, highlighting the potential contributions of nanotechnology to the creation of robust sensing platforms for environmental monitoring.

Leukemia is a rare but fatal cancer of the blood. This cancer arises from abnormal bone marrow cells and requires prompt diagnosis for effective treatment and positive patient prognosis. Traditional diagnostic methods (e.g., microscopy, flow cytometry, and biopsy) pose challenges in both accuracy and time, demanding an inquisition on the development and use of deep learning (DL) models, such as convolutional neural networks (CNN), which could allow for a faster and more exact diagnosis. Using specific, objective criteria, DL might hold promise as a tool for physicians to diagnose leukemia. The purpose of this review was to report the relevant available published literature on using DL to diagnose leukemia. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, articles published between 2010 and 2023 were searched using Embase, Ovid MEDLINE, and Web of Science, searching the terms \"leukemia\" AND \"deep learning\" or \"artificial neural network\" OR \"neural network\" AND \"diagnosis\" OR \"detection.\" After screening retrieved articles using pre-determined eligibility criteria, 20 articles were included in the final review and reported chronologically due to the nascent nature of the phenomenon. The initial studies laid the groundwork for subsequent innovations, illustrating the transition from specialized methods to more generalized approaches capitalizing on DL technologies for leukemia detection. This summary of recent DL models revealed a paradigm shift toward integrated architectures, resulting in notable enhancements in accuracy and efficiency. The continuous refinement of models and techniques, coupled with an emphasis on simplicity and efficiency, positions DL as a promising tool for leukemia detection. With the help of these neural networks, leukemia detection could be hastened, allowing for an improved long-term outlook and prognosis. Further research is warranted using real-life scenarios to confirm the suggested transformative effects DL models could have on leukemia diagnosis.

Cystoid macular edema (CME) is a sight-threatening condition often associated with inflammatory and diabetic diseases. Early detection is crucial to prevent irreversible vision loss. Artificial intelligence (AI) has shown promise in automating CME diagnosis through optical coherence tomography (OCT) imaging, but its utility needs critical evaluation. This systematic review assesses the application of AI to diagnosis CME, specifically focusing on disorders like postoperative CME (Irvine Gass syndrome) and retinitis pigmentosa without obvious vasculopathy, using OCT imaging. A comprehensive search was conducted across 6 databases (PubMed, Scopus, Web of Science, Wiley, ScienceDirect, and IEEE) from 2018 to November, 2023. Twenty-three articles met the inclusion criteria and were selected for in-depth analysis. We evaluate AI\'s role in CME diagnosis and its performance in \"detection\", \"classification\" and \"segmentation\" of OCT retinal images. We found that convolutional neural network (CNN)-based methods consistently outperformed other machine learning techniques, achieving an average accuracy of over 96% in detecting and identifying CME from OCT images. Despite certain limitations such as dataset size and ethical concerns, the synergy between AI and OCT, particularly through CNNs, holds promise for significantly advancing CME diagnostics.

BACKGROUND: Cocaine may be applied to decongest the nasal mucosa before nasotracheal intubation, but patients risk a criminal offence if cocaine is detected when patients drive a car shortly after surgery. We aimed to evaluate whether benzoylecgonine levels in saliva exceeded the cut-off point 24 h after administration in patients undergoing nasotracheal intubation and whether cocaine would be detectable above the Danish legal fixed limit in blood samples 1 and 24 h after surgery.
METHODS: We conducted a prospective study following approval from the local research ethics committee and the national medicine agency. Written informed consent was obtained from all patients. We included patients scheduled for surgery under general anaesthesia with nasotracheal intubation. They received 80 mg cocaine as a nasal spray 5 min before induction and nasotracheal intubation. The primary outcome was a dichotomous assessment of benzoylecgonine levels in saliva samples measured 24 h after administration of nasal cocaine with a cut-off limit of 200 ng/mL. Secondary outcomes were dichotomous assessments of cocaine in whole blood samples measured 1 and 24 h after administration of nasal cocaine with a cut-off limit of 0.01 mg/kg.
RESULTS: Overall, 70 patients had valid saliva samples and 75 had valid blood samples 24 h after cocaine administration. Benzoylecgonine in saliva was traceable above the cut-off in 9/70 patients (13%; CI95%: 6% to 23%), and cocaine in blood was detected above the cut-off in 2/75 patients (3%; CI95%: 0.3% to 9%).
CONCLUSIONS: We found benzoylecgonine traceable in saliva in 13% of patients and cocaine traceable in blood in 3% of patients 24 h after administration of 80 mg nasal cocaine. Patients should be informed when receiving cocaine and advised not to drive for at least 24 h.