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Mercury-carbon relationships in environmental media near artisanal gold mining sites in Guyana.

Elevated atmospheric mercury (Hg) concentrations from artisanal gold mining increase Hg exposure in adjacent forest canopies. Although pools and fluxes of Hg and carbon (C) within environmental media are connected, it is unclear how these Hg/C patterns may differ between areas exposed to high Hg levels and regions remote from emission sources. Here, we compare Hg/C patterns in environmental media (foliage, leaf litter, soil, water, sediment) near artisanal gold mining sites in Guyana with 25 studies worldwide to better understand Hg movement within environmental media. Patterns of Hg/C ratios …

Integrated Transcriptomic and Metabolomic Mining of Candidate Genes for Weevil Resistance in Pea.

The pea weevil (Bruchus pisorum L.) causes severe yield losses in cultivated pea (Pisum sativum L.), yet the molecular basis of host resistance remains unclear. Here, we performed integrated transcriptomic and metabolomic analyses on pods and seeds of resistant (YWD) and susceptible (LW1) pea genotypes to characterize the constitutive defence network against weevils. Extensive transcriptional and metabolic reprogramming was observed in resistant materials, with upregulation of defence pathways and suppression of primary metabolism. Pods directed phenylpropanoid flux toward isoflavonoid biosynt

Trichome acylsugar defenses are equally effective against leaf-mining and free-living insects.

Trichomes, epidermal projections, are crucial components of plant defense systems. Whether these epidermal defenses are effective against leafminers, which infest the internal mesophyll layers, remains unclear. Using the devastating invasive tomato pest, Phthorimaea absoluta (tomato leafminer), and the trichome-rich wild tomato, Solanum pennellii, we demonstrate that trichome-produced acylsugars effectively inhibit the growth of endophagous P. absoluta larvae feeding inside leaves. High-spatial-resolution leaf- and frass-metabolite analysis by matrix-assisted laser desorption/ionization-mass s

Living through the collapse: Post-traumatic adaptation after a mining disaster in Turkey.

Mining accidents are traumatic events that can lead to profound physical, psychological, and relational consequences for workers. In Turkey, frequent mining disasters occur due to high-risk working conditions and inadequate safety measures. While existing literature has explored the traumatic impact of such accidents, there is limited research focusing on the post-traumatic recovery processes of miners who survive these events. This study examines miners' challenges following a disaster, their coping strategies, and potential psychological recovery and growth indicators. Using a phenomenologic…

The tidal wetland restoration goldmine: Prospects and pitfalls of mining confined disposal facilities.

Saltmarshes along the United States South Atlantic Coast, and globally, face critical threats from sea-level rise, edge erosion, ponding and … rowning saltmarshes in the United States. In this perspective article, we explore the potential for mining CDFs to provide the sediment necessary to restore and sustain at-risk saltmarshes. Using publicly available data from the US South Atlantic coast, we estimate that reclaiming sediment from existing CDFs could offset sea-level rise impacts by 2100 fo …

Object-Centric Process Mining of Laparoscopic Cholecystectomy Workflows: Identifying Bottlenecks and Optimization Opportunities.

This study applies object-centric process mining (OCPM) techniques to analyze laparoscopic cholecystectomy (LC) procedures. Traditional process mining techniques are limited in analyzing workflows involving multiple interacting entities (patients, surgeries, anesthesia physical status, etc.).This study aimed to construct an Object-Centric Event Log (OCEL) from LC procedures, discover multientity process patterns, identify workflow bottlenecks, and analyze how patient complexity affects perioperative dynamics.An OCEL representing 1,186 LC cases (1,108 performed, 78 cancelled) from the Universit…

SigMine and OPathDb: a literature-mining pipeline and database of potential opportunistic pathogens.

Conversion of unstructured biomedical literature into structured knowledge for identifying cross-domain associations between biological entities remains a challenging task. SigMine is an automated pipeline constructed to mine biomedical literature to identify significantly associated biological entities. SigMine performs biomedical entity recognition from PMC articles using the EuropePMC Annotation API. Advanced entity recognition was performed using Python scripting, NCBI E-Utilities, and an n-gram algorithm followed by extensive data cleaning and mapping against standard databases. Statistic

Genome mining reveals the unique function of UbiA-type prenyltransferase in Laetiporus sulphureus.

Eight UbiA-type prenyltransferases were mined in Laetiporus sulphureus by bioinformatic analysis, and phylogenetic analysis showed that they have unique functions. Through heterologous expression in Aspergillus oryzae and addition of exogenous hydroquinone (HYQ, 2) substrate, it was found that LaPT3 could transfer isoprenyl groups on 2. Substrate specificity studies revealed that LaPT3 was substrate specific and could only transfer dimethylallyl diphosphate (DMAPP) using 2 as substrate to produce the product 2-(3-methylbut-2-en-1-yl) benzene-1,4-diol (1). The key active sites of LaPT3 were ana

Dysesthesia associated with GLP-1 agonist therapies: data-mining analysis and literature review.

PURPOSE: An increasing number of anecdotal reports on social media platforms and medical blogs describe dysesthesia, particularly burning skin sensations, in association with glucagon-like peptide-1 receptor (GLP-1R) agonists. We performed a pharmacovigilance data-mining analysis to characterise cases of dysesthesia related to GLP-1R. METHODS: We conducted a disproportionality analysis using VigiBase data on GLP-1R (Anatomical Therapeutic Chemical classification: ATC code A10BJ) and tirzepatide, focusing on the HLT (High Level Term) "Paraesthesia and dysesthesia", with the Information Compone…

An upper bound on uranium-mining radon contributions to regional environmental 210Pb inventories.

Radon releases from uranium-mining legacies are commonly evaluated in relation to inhalation exposure. Here, the separate question is whether the 210Pb produced from sustained legacy releases could perturb the inventories used to date and interpret soils, sediments, peat and other environmental archives. This paper bounds that possibility and tests the natural-meteoric provenance assumption underlying regional excess-210Pb interpretation. Because decay-chain mass balance conserves atoms rather than activity, conversion from a 3.8-day radionuclide to a 22.3-year radionuclide reduces the associa…

Computational mass spectrometry and genome mining guided discovery of metallophores produced by Microbulbifer.

Iron is an essential component of cellular biology. Thus, iron's low bioavailability is a key evolutionary pressure guiding microbial dynami … an unprecedented longer chain length acylation on the central spermidine moiety. We applied genome mining methods to describe the biosynthesis of these compounds. Using metal infusion mass spectrometry, we show that bulbichelins bind a variety of metals. Notably, neither of these compounds were produced in a co-culture of Microbulbifer with coral-derive …

Полифенолы и нейродегенеративные заболевания: понимание знаний, механистические свидетельства и новые виды применения в области питания.

Полифенолы представляют собой разнообразную группу биоактивных веществ растительного происхождения, которые были исследованы в качестве многоцелевых возможностей для потенциальной профилактики и лечения нейродегенеративных заболеваний (НДИ). Мы провели комплексный библиометрический и механистический обзор, охватывающий 12 классов полифенола и семь основных НИЗ, с использованием записей из PubMed, Embase, Cochrane Bibrary и Web of Science (1940-2024). Для картирования исследовательских ландшафтов и новых тем использовались ключевые слова, анализы по группам и модели BERTopic. Механистические до

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… JBYW-AII-2024-09: “Research on Knowledge Mining and Precision Services of Functional Foods Driven by Digital Intelligence”). …

Artificial intelligence in kidney disease and dialysis: from data mining to clinical impact.

PURPOSE OF REVIEW: Artificial intelligence (AI) and machine learning (ML) are rapidly transforming healthcare, but their adoption in nephrology and dialysis remains relatively limited. RECENT FINDINGS: This review highlights key applications of AI in kidney disease, including prognostic modeling, imaging, personalized anemia and fluid management, patient engagement, and research acceleration. While numerous studies demonstrate improved prediction accuracy and clinical insights, translation into routine practice is rare. Examples such as the Anemia Control Model (ACM) demonstrate that AI can s

Analyzing multidrug resistance patterns across the food supply chain using association rule mining.

We used the machine learning method association rule mining to analyze multidrug resistance (MDR) among cattle-associated Escherichia coli along the food supply chain in the USA. All datasets were stratified by year, source, and resistance indicator (genotypic/phenotypic). Pruned rulesets were compared by calculating the proportion of rules from a comparison ruleset that are captured in a reference ruleset. Rulesets were compared across years within each source and indicator type to quantify how MDR patterns change over time. At the class level, on average nearly 50 % or more of the MDR patter…

Evaluation of attitudes of university students towards artificial intelligence using data mining methods.

This study analyzes university students' attitudes towards artificial intelligence. Within the scope of the research, the data obtained from 1379 students through scale application were classified into three classes as "Insufficient", "Sufficient" and "Strongly Sufficient" according to their attitudes towards artificial intelligence. The data was classified by data mining methods. For this purpose, MLP, Decision Tree, KNN, XGBoost, Random Forest, CatBoost and SVM algorithms were used. The performance of the model was evaluated with a 5-fold cross-validation method. For each algorithm, basic me…

Clay Nanomaterials Sorbents for Cleaner Water: A Sustainable Application for the Mining Industry.

The increasing shortage of drinking water, driven by reduced rainfall and the intensification of industrial and agricultural activities, has raised justified concerns about the quantity and quality of available water resources. These sectors not only demand high water consumption but also discharge large amounts of toxic substances such as organic matter, metal ions and inorganic anions, posing risks to both public health and the environment. This study evaluated the effectiveness of clay-based nanomaterials in the treatment of contaminated industrial wastewater from the mining sector. The mat…

Uncovering the Molecular Landscape of Tetracycline Family Natural Products through Bacterial Genome Mining.

Tetracycline (TC) family natural products have attracted significant attention due to their diverse chemical structures and important role in drug development. As one of the most successful classes of drugs, TC antibiotics have been used clinically for over 70 years and remain crucial in treating infections. Despite their importance, systematic exploration of novel TC natural products has been limited, leaving the molecular landscape of the TC family poorly understood and hindering further development of these compounds for therapeutic applications. Here, we developed a targeted strategy to id

Symptoms affecting the development of diabetes: analysis of risk factors with data mining.

OBJECTIVE: Diabetes is one of the most common chronic health threats worldwide. Early detection of diabetes is difficult and diagnosis and treatment processes can be costly. Data mining techniques offer powerful tools for predictive analysis and knowledge extraction from large data sets. This study aims to identify symptoms that collectively influence the development of diabetes by data mining and identify risk parameters for early detection. MATERIALS AND METHODS: The study uses a dataset of 520 patient records collected from Sylhet Diabetes Hospital in Sylhet, Bangladesh. This dataset is ba…

SciLinker: a large-scale text mining framework for mapping associations among biological entities.

INTRODUCTION: The biomedical literature is the go-to source of information regarding relationships between biological entities, including ge … mong biological entities from scientific literature. CONCLUSION: SciLinker represents a novel text mining approach that extracts and quantifies associations between biomedical entities through co-occurrence analysis and relationship extraction from PubMed abstracts. Its modular design enables expansion to additional entities and text corpora, making it …

Mining of candidate genes related to prolificacy in Jining grey goats using transcriptomics.

BACKGROUND: The Jining grey goat is a renowned local goat breed in China that has exceptional reproductive performance; thereby, it serves as an ideal animal model for studying prolificacy in goats. Recent research on the reproductive traits of Jining grey goats has focused primarily on variations in the expression of key genes, hormone regulatory mechanisms, and breeding techniques, with the aim of enhancing reproductive performance through molecular marker-assisted breeding. METHODS: In this study, 8 healthy adult female Jining grey goats of similar age and weight were selected. Ovarian and