Browse Articles

Modification of a pencil graphite electrode with halloysite and gold–palladium bimetallic nanoparticles for diclofenac sodium determination

Development and evaluation of a novel lateral flow immunoassay for rapid diagnosis of brucellosis across different animal species

Abstract Brucellosis, a prevalent zoonotic disease, induces substantial economic losses in livestock due to reproductive impairments and high mortality rates; it also presents considerable public health concerns worldwide. The current work highlights the potential application of the developed lateral flow immunochromatographic assay (LFIA) in the rapid and accurate detection of Brucella spp., underscoring its significance in disease management and control. The study investigated the purity of the extracted B. abortus smooth lipopolysaccharides-O (S-LPS-O) using high-performance liquid chromatography (HPLC). Moreover, it delved into the development and assessment of a novel diagnostic kit for Brucella using a recombinant protein A-lateral flow assay in comparison to the RBPT, SAT, MRT, I-ELISA as screening tests, also to C-ELISA, CFT as confirmatory tests. HPLC analysis indicated a distinctive absence of impurities in the extracted S-LPS-O, contrasting with the three peaks observed in the commercial LPS chromatogram. Sensitivity, specificity, and accuracy evaluations were performed, with the LFIA demonstrating promising results, showcasing its potential as a reliable diagnostic tool. Statistical analysis of the LFIA, RBPT, SAT, MRT, ELISA, CFT, and PCR results revealed notable sensitivity, specificity, and accuracy rates, affirming the diagnostic efficacy of the LFIA. The novel layout of the LFIA and the purity of extracted S-LPS-O showcased significant progress in the diagnostic capabilities of the developed LFIA. Moreover, the currently developed LFIA introduces a rapid and reliable diagnostic tool, particularly in resource-limited settings, owing to its ease of use and minimal equipment requirements with its competitively obtained results.

Consolidation process of uncemented backfill slurry in a mine stope considering hydro-geotechnical properties of rockmass in adjacent stopes

Abstract In open stoping with subsequent backfill mining, the filled slurry in one stope is typically surrounded by the rockmass in adjacent stopes. The rockmass generally contain geological faults and joints that can serve as seepage pathways for pore water within the backfill slurry during consolidation process. However, these impacts from the adjacent rockmass were usually simplified to an impermeable or permeable boundary in previous studies. In this paper, numerical modeling with FLAC3D was conducted to investigate the influences of hydro-geotechnical properties of surrounding rockmass on consolidation process of uncemented backfill slurry in a vertical stope. Results show that the pore water pressure (PWP) and effective stresses of backfill slurry confined by rockmass are consistently higher than those obtained by assuming fully permeable boundaries but lower than those derived from impermeable boundary assumptions. A five-fold difference in peak PWP and effective stresses occurs when the rockmass hydraulic conductivity varies from 10–8 m/s to 10–5 m/s. It is reasonable to simplify the rockmass with a low hydraulic conductivity (≤ 10–8 m/s) as an impermeable boundary and that with high hydraulic conductivity (≥ 10–5 m/s) as a permeable boundary. Additionally, a higher porosity and lower initial saturation of the adjacent rockmass promote both PWP dissipation and effective stresses development in backfill slurry, but their influences are less pronounced compared to the effect of hydraulic conductivity. Furthermore, the study discusses the influences of the hydro-geotechnical properties of adjacent rockmass on the lateral earth pressure coefficient of consolidated backfill which is an important parameter for analytical models of stress distribution within backfill. The findings are expected to provide valuable insights into the consolidation behavior of backfill slurry under field conditions and contribute reliable method for barricade design.

Integrated method for multi-UAV task assignment and trajectory planning with deadlock based on Three-dimensional dubins path

Efficacy and safety of GLP-1 agonists in the treatment of T2DM: A systematic review and network meta-analysis

Skin autofluorescence is associated with glycemic variability in type 2 diabetes patients

The influence of civil society’s economic status on environmental protection behaviors from the perspective of environmental sociology

Semi-quantitative evaluation of small organic molecules content in amorphous calcium phosphate

Tocilizumab as a targeted immunomodulatory therapy in the management of severe respiratory illnesses: a multicenter cohort study of COVID-19 patients

Improving lesion detection skills in medical imaging education through enhanced peripheral visual perception

A framework for flood risk zoning and prioritization combining maximum entropy and game theory

The articularis genu as a surrogate for structural determinants of peri-articular myopenia in osteoarthritis

Identification and validation of endoplasmic reticulum autophagy-related potential biomarkers in periodontitis

CDX2 loss in colorectal cancer cells is associated with invasive properties and tumor budding

Abstract In colorectal cancer (CRC), tumor buds (TB) are observed histologically as single tumor cell or small tumor cell clusters located mainly at the advancing tumor edge. TB are a marker of poor prognosis and correlate with metastatic disease in CRC patients. They often lack expression of CDX2 and overexpress markers involved in epithelial-mesenchymal transition (EMT). We evaluated the function of CDX2 in CRC proliferation and migration using CRISPR/Cas9 technology and demonstrated a possible link to tumor dissociation and tumor budding. Knocking out CDX2 in CRC cell lines significantly increased migration. Importantly, the observed phenotypes could be rescued by re-expressing CDX2 and by specific CRISPR synergistic activation mediator (SAM) of endogenous CDX2 in CDX2 low expressing CRC cell lines. Multiplex immunofluorescence (mIF) analysis of primary tumor regions compared to TB in a CDX2-positive CRC patient sample as well as patient derived xenografts (PDX) revealed significantly lower CDX2 expression and correlating E-cadherin levels in TB compared to primary tumor regions, in both models. Accordingly, increased invasiveness of CRC CDX2 knockout cells was seen in ex ovo xenografts. Taken together, our results provide further insight into the function of CDX2 in preventing CRC cell migration, tumor budding and tumor aggressiveness.

Unraveling novel variants in the NF1 gene and investigating potential therapeutic strategies

Vitamin E intake mediates the associations of triglyceride-glucose index and its related parameters with phenotypic age acceleration in middle-aged and elderly population

A Multi-kernel CNN model with attention mechanism for classification of citrus plants diseases

Explainable artificial intelligence driven insights into smoking prediction using machine learning and clinical parameters

Abstract Smoking is a leading cause of various health conditions, including cancer and respiratory diseases. Smokers often face medical restrictions such as limitations in blood and organ donation, reduced effectiveness of medications, and increased surgical complications. These impacts underscore the need for early detection of smoking status to enable timely intervention. This study explores the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to predict smoking status based on health parameters, including biosignals and clinical biomarkers. A balanced subset of 2,000 instances was sampled from a publicly available Kaggle dataset comprising clinical and biometric features. Multiple ML models were implemented, including Random Forest Classifier, Logistic Regression, Decision Tree Classifier, K-Nearest Neighbors, CatBoost Classifier, and an Artificial Neural Network. The Random Forest Classifier achieved the better performance with an accuracy of 0.80, precision of 0.80, recall of 0.80, and F1-score of 0.79. To enhance model interpretability, four Explainable Artificial Intelligence (XAI) techniques were applied: Shapley Additive Explanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), QLattice, and Anchor. SHAP identified hemoglobin as the most influential predictor, while LIME, QLattice, and Anchor highlighted the role of gamma-glutamyl transferase (t). Interactions between hemoglobin, GTP, and height were associated with more accurate predictions. The integration of ensemble modeling and multiple XAI approaches offers deeper interpretability than prior studies, providing healthcare providers and policymakers with a robust, transparent decision-support tool for targeted intervention strategies.

Impact of generative AI interaction and output quality on university students’ learning outcomes: a technology-mediated and motivation-driven approach

Regional profiling reveals a distinct glioblastoma infiltrative margin proteome

Abstract Isocitrate dehydrogenase wild-type glioblastoma, a malignant brain tumour of glial origin, confers a poor prognosis with a median survival of 12 to 16 months from diagnosis. Glioblastomas are aggressive tumours that rapidly proliferate and diffusely infiltrate surrounding brain tissue. Current multimodal standard treatment is typically ineffective and despite gross total surgical resection, tumours recur with more aggressive sub-clonal populations of malignant cells. A defining characteristic of glioblastoma is its highly heterogeneous nature and acquirement of somatic mutations advantageous to tumour growth and suppression of apoptotic pathways. Pathogenesis of malignant brain tumours as well as its mode of transformation to a more aggressive subtype is still largely unknown. Although genomic studies have elucidated a plethora of genetic markers associated with glioblastoma subtypes, only a few have been utilised in a clinical setting. One of the emerging approaches to studying glioblastomas is by investigating how an active proteome contributes to its aggressive nature. Furthermore, through activation of specific pathways via post-translational modifications of proteins such as phosphorylation, glioblastomas create an intricate network of signalling pathways which favour tumour growth and proliferation. Here, we investigated the feasibility of diverse methodological approaches to describe abnormal protein signalling across distinct intra-tumour regions of primary glioblastoma tissue, including proliferative core, peripheral rim, and invasive margin. Whilst we observe a broadly comparable proteome relative to the human non-diseased brain, we identify cytoplasmic proteins α-trypsin, actin, apolipoprotein A1 and transthyretin which may putatively be associated with the GBM infiltrative tumour margin.