Search Results (387)

The translation of nucleic acid amplification into practical point-of-care and biosensor-integrated diagnostics is still significantly impeded by the necessity for rapid sample preparation. For this reason, a broad comparison of seven commercially available kits for DNA/RNA extraction containing their temperature-related adjustments was performed. Extracts isolated from SARS-CoV-2-positive nasopharyngeal swabs, viral stocks, as well as laboratory-prepared suspensions of clinically relevant Gram-positive and Gram-negative bacteria were evaluated by recombinase polymerase amplification (RPA) and real-time PCR. In addition, the impact of transport media for SARS-CoV-2 samples was investigated. Extraction performance varied markedly according to the kit, pathogen, sample background. For SARS-CoV-2, rapid extraction was more effective for samples collected in viral transport medium than in inactivation buffer. Across bacterial targets, performance was species dependent, highlighting substantial differences in compatibility between simplified extraction workflows and downstream amplification. Among the rapid methods tested, a simplified QuickExtract protocol (95 °C, 5 min) provided the most consistent overall results, although it did not uniformly match the reference silica-based method for all targets. In conclusion, these results demonstrate that rapid nucleic acid extraction must be thoroughly evaluated as an essential element of the entire sample-to-answer workflow, rather than being chosen as a standalone preprocessing step for point-of-care molecular diagnostics. Full article

Different methods are used today for polysaccharide quantitation, including HPLC and various colorimetric assays. Among these, the anthrone-sulfuric acid assay (anthrone assay) is popular when the sample matrix is suitable, such as in purified polysaccharides and monovalent bulk conjugate components of glycoconjugate vaccines. While relatively safe, quick, and affordable, the anthrone assay requires significant operator time to complete and is not suited to high-throughput processing. Furthermore, the anthrone-sulfuric acid reagent presents a unique challenge to automation efforts due to its corrosive properties. Reported here is an automated anthrone assay via a liquid handling system (LHS). Twenty-three serotypes of pneumococcal (PNU) polysaccharide were quantified with the traditional anthrone assay and subsequently analyzed using the anthrone LHS method. The anthrone LHS method was evaluated for accuracy compared to the manual method and later validated according to ICH Q2 (R2) guidelines. To our knowledge, this is the first fully unattended and corrosion-mitigated anthrone assay validated under ICH Q2 (R2), capable of overnight batch operation. The developed assay can quantify polysaccharides with an accuracy of 81–115%, is precise to a coefficient of variation of <7.0%, and is linear between 30 and 650 µg/mL range (R² ≥ 0.993). The assay can process eight samples per hour, can be utilized in overnight operation, and completes all pipetting, incubation, and data export steps automatically. Full article

Background/Objectives: Mitochondrial DNA (mtDNA) is an important resource for understanding human ancestry, population diversity, and the molecular mechanisms of mitochondrial diseases. However, analyzing mtDNA thoroughly often requires advanced bioinformatics skills and command-line knowledge. To address this challenge, we created Mitochondrial Genome Explorer (MitoGEx), a user-friendly computational pipeline optimized for human mtDNA analysis that combines multiple mtDNA analysis modules within a single graphical user interface. Methods: The platform simplifies key analytical steps, such as quality control, sequence alignment, alignment quality assessment, variant detection, haplogroup classification, and phylogenetic reconstruction. Users can choose between Quick and Advanced modes, which offer default settings or customizable options based on their analysis needs. To demonstrate its effectiveness, we analyzed 15 whole-exome sequencing (WES) samples from Songklanagarind Hospital using MitoGEx. Results: The sequencing data were of high quality, with over 92 percent of bases scoring above a Phred score and consistent GC content across all samples. Variant detection using the GATK mitochondrial pipeline and annotation with ANNOVAR and the MitImpact database revealed multiple high-confidence variants. Haplogroup classification with Haplogrep 3 and phylogenetic analysis with IQ-TREE 2 confirmed diverse maternal lineages within the cohort. Conclusions: Taken together, MitoGEx facilitates mitochondrial genome analysis in a reproducible and accessible manner for both research and clinical bioinformatics applications. The analytical results produced by MitoGEx are concordant with those obtained using standalone bioinformatic tools, demonstrating analytical correctness. By integrating all analysis steps into a single automated workflow, MitoGEx reduces execution time and limits human error inherent to manual, multi-step pipelines. Full article

Background: DanceSport involves intermittent high-intensity efforts that may differ between styles and partners within a dance couple. However, dance-specific relative oxygen uptake (%VO₂max) in elite Standard and Latin dancers remains insufficiently described. Objective: This study aimed to characterize relative oxygen uptake during simulated competition in elite Slovak national team dancers and to examine (i) differences between Latin and Standard styles, (ii) variability across individual dances, and (iii) sex-specific patterns. Methods: Twenty elite dancers (10 couples) participated in the study. Five couples (n = 10 dancers; 5 females and 5 males) specialized in Latin dances, and five couples (n = 10 dancers; 5 females and 5 males) specialized in Standard dances. VO₂max was determined via an incremental treadmill test. During a simulated final round, breath-by-breath gas exchange was recorded using portable spirometry. Style-level differences were analyzed using a two-way ANOVA (Style × Sex), and dance-specific effects were examined using repeated-measures ANOVAs. Results: No significant difference in mean %VO₂max was observed between styles (F_{(1, 16)} = 1.31, p = 0.269, η²_p = 0.076). In the Latin group, relative oxygen uptake differed significantly between dances (F_{(4, 32)} = 22.45, p < 0.001, η²_p = 0.737), with Jive eliciting the highest values (~103–105% VO₂max in males) and Rumba eliciting the lowest values (~88–89% VO₂max). No Dance × Sex interaction was detected in Latin dances (p = 0.526). In the Standard group, a significant Dance × Sex interaction was observed (F_{(4, 32)} = 8.80, p < 0.001, η²_p = 0.524), with male dancers demonstrating higher %VO₂max during Quickstep (~96%) compared with other dances, whereas females showed a more uniform intensity profile (~80–86%). Conclusions: Relative oxygen uptake in DanceSport is highly dance-dependent and shows sex-specific metabolic patterns in Standard dances. Conditioning programs in elite DanceSport should therefore be structured according to individual dance demands and partnership-specific physiological roles. Full article

Growing concern over the presence of microplastics in food has led to the development of numerous methods for their extraction and analysis. However, many of these methods are time-consuming and limited to specific food types. In this study, we present a novel and quick approach involving microwave-assisted acid extraction of microplastics from food, followed by Raman microscopy analysis. The method’s performance was evaluated through determination of its digestion efficiency, particle mass and number recovery, limit of detection (LOD), and the digestion protocol’s effect on polymer physicochemical characteristics. The extraction protocol achieved 99.74–100.01% digestion of four different food matrices within 2 h, with 81.4–110.7% mass and 80–108% number recoveries of added polymer particles, both being within the 80–120% range. Importantly, DSC, TGA, DLS and Raman analyses of added particle polymers showed no significant change in PE, PP and PTFE polymer structure, while some structural changes were found for PET and PMMA. This method’s good analytical performance, high throughput and suitability for quick digestion of several different food matrices make it a promising step towards reliable monitoring of microplastics in food. Full article

Background/Objectives: The surgical treatment of basal cell carcinoma (BCC) remains challenging due to the time-consuming, expensive and invasive nature of Mohs micrographic surgery. The objective is to develop a standardized protocol for managing diagnosis, surgery, and margin control within a single patient visit. Methods: Several protocols were tested to establish a “BCC-One-Stop-Shop”, combining in vivo and ex vivo margin mapping of BCC, pre- and postoperatively using Line-field confocal optical coherence tomography (LC-OCT). We introduce an algorithm enabling real-time localization of LC-OCT acquisitions on a previously acquired dermoscopy image. Additionally, an artificial intelligence model provides a BCC probability score based on LC-OCT images. Together, the co-localization algorithm and AI BCC model generate a color-coded visualization of the tumor within the dermoscopy image, allowing precise pre-operative in vivo margin assessment. Results: We found our protocol, the implementation of the co-localization tool and the AI model, to be quick to apply, easy to learn and helpful regarding the initial determination of BCC tumor margins. Patients responded positively to the recognizable visualization of the disease. Conclusions: Pre- and postoperative margin mapping using LC-OCT imaging appears to be effective and feasible and could reduce time, costs, resources, excision sizes and patient burden by sparing additional excision steps in micrographic surgery. The integration of real-time co-localization and the AI-calculated probability score represent meaningful and practical enhancements for routine clinical use. To further evaluate the efficacy and safety of the BCC-One-Stop-Shop-Method and the newly introduced device features, larger-scale studies are warranted and are currently being conducted. Full article

The COVID-19 pandemic critically emphasized the need for rapid, flexible, and decentralized manufacturing solutions to support the urgent demand for essential medical equipment, such as oximeters. Metal wire directed energy deposition—w-DED, also known as w-LMD (wire laser metal deposition)—combines the benefits of high material utilization, increased printing speed, and reduced waste, making it an attractive alternative to traditional powder-based processes, especially under time-sensitive and resource-constrained conditions. This work presents a case study focusing on the design and fabrication of injection molds for oximeter casings using metal-wire-based DED. Martensitic stainless steel AISI-420 wire was employed as feedstock and processed via laser wire additive manufacturing to produce a robust, near-net-shape mold suitable for plastic injection molding. The material was selected due to good corrosion and wear resistance. However, poor ductility and toughness, together with AM-induced anisotropy, were the main challenges to address. Therefore, a multi-step methodology was defined to study the effect of different process parameters, which was validated through printing trials, and the optimum process parameter set was identified. The process enabled the rapid construction of intricate mold geometries, minimizing lead times and allowing for quick design iterations. Microstructural and physical properties such as microhardness of the as-built molds were thoroughly characterized. This case study not only illustrates the technical feasibility of producing functional injection molds via metal w-DED but also outlines its role as a resilient manufacturing pathway, capable of meeting emergent healthcare needs and supporting broader industrial applications in a post-pandemic context. Full article

Exogenous toxic compounds in foods, arising from agricultural practices, environmental contamination, industrial processing, and packaging migration, remain a major global concern for food safety. These contaminants include mycotoxins, veterinary drug residues, antibiotics, pesticides, per- and polyfluoroalkyl substances, heterocyclic aromatic amines, and polycyclic aromatic hydrocarbons, which have multiple adverse effects on human and animal health. The continued presence of these substances highlights the need for reliable exposure assessment, strengthened regulatory frameworks, and advanced analytical methodologies. Food matrices introduce variability in analytical performance, making sample preparation a critical and often limiting step. Conventional extraction techniques such as solid-phase extraction, liquid–liquid extraction, and Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) are still widely applied. Moreover, recent advances have highlighted sustainable alternatives aligned with the principles of green analytical chemistry. In this context, this review provides a comprehensive overview of recent advances (2020–2025) in environmentally friendly extraction techniques for determining exogenous toxic compounds in food samples analyzed by liquid chromatography coupled with mass spectrometry (LC–MS), including their sustainability. Special attention is given to the chemical nature and toxicological relevance of major exogenous organic contaminant families (specialized categories such as hormones and packaging-derived bisphenols were excluded due to distinct migration and metabolic pathways; however, these topics exceed the scope of this manuscript), the analytical challenges associated with different food matrices, and the evolution of extraction and cleanup techniques. Overall, this review integrates analytical robustness, matrix effects, and green metrics to support the development of reliable and more sustainable sample preparation strategies. Full article

A parallel-stirred tank bioreactor system on a 10 mL-scale automated with a liquid handling station introduces significant benefits in bioprocess analysis and design regarding preserving time, cost, and workload, thereby enabling quick generation of bioprocess results that can be easily scaled up. Although up-to-date approaches enable the online analysis of individual reactors for pH, dissolved oxygen (DO), and optical density (OD), the automated calibration of a new online laser-based infrared OD sensor device and noise reduction are still required. Among the extensive research on the full-data smoothing tools, the Savitzky–Golay (Savgol) filter was determined as the most effective one. Scattered and transmitted online light values were successfully aligned with the reference at-line OD values measured at 600 nm by the liquid handler with a step time of a few hours. The growth of an engineered Gluconobacter oxydans designed for specific whole-cell oxidations has been investigated in two parallel batch process setups with varied sugar types at varying sugar concentrations, combinations of sugars, and altered concentrations of complex media. Simulation of real-time smoothing was applied with a Kalman filter. Rapid adaptation was observed within a few upcoming data points by altering the parameters for the estimation of the noise in the signal. For almost all tested reaction conditions, a successful alignment of the simulation of real-time smoothed online OD with at-line values was achieved. The best growth condition was determined in the presence of 120 g L⁻¹ glucose and 30 g L⁻¹ fructose with the tripled peptone concentration. Under these conditions, OD₆₀₀ increased by 109%, from 2.1 to 4.4, compared to the reference process. Full article

In recent decades, considerable effort has been devoted to developing higher-order schemes for the discretization of convective terms that are both stable and reliable. In this work, the central idea is that the approximation should be made to reflect the physics of pure convection: the transported quantity is advected along streamlines, and information is propagated only in the upwind direction, i.e., the transported property is determined by previous values along the streamline but not by downstream values. In the proposed approach, streamlines on the computational mesh are represented by discrete streamlines, and the method is called the Discrete Streamline Method (DStreaM). A discrete streamline is constructed as a narrow triangle with one vertex at the node where the approximation is sought and two vertices at upstream neighbouring nodes. Discrete streamlines are oriented according to the local flow direction, in a manner similar to skew-upwind schemes, so that consistency with pure convection is ensured for DStreaM. The method is conservative only for uniform meshes with a constant velocity field; for general meshes and non-uniform velocity fields, it is non-conservative, and a non-zero local conservation error remains. The performance of DStreaM is assessed on the following standard test problems: convection of a step profile, a double-step profile, a sinusoidal profile, and the Smith–Hutton problem. DStreaM solutions are compared with those obtained using the first-order upwind scheme and second-order total variation diminishing (TVD) schemes with Minmod, QUICK, and SUPERBEE limiters. Across these benchmarks, high-resolution solution profiles and $L_1/L_2$ error levels comparable to those of the considered TVD schemes are produced by DStreaM. In the DStreaM construction, only local node coordinates and mesh connectivity are used; in this work, implementation is performed on both uniform Cartesian meshes and unstructured triangular meshes generated by a Delaunay triangulation. Representative results are reported with a focus on accuracy, iterative convergence, and conservation limitations. Full article

Fog computing is one of the rapidly growing platforms with an exponentially increasing demand for real-time data processing. The fog computing market is expected to reach USD 8358 million by the year 2030 with a compound annual growth of 50%. The wide adaptation of fog computing by the industries worldwide is due to the advantages like reduced latency, high operational efficiency, and high-level data privacy. The highly distributed and heterogeneous nature of fog computing leads to significant challenges related to resource management, data security, task scheduling, data privacy, and interoperability. The task typically represents a job generated by the IoT device. The action indicates the way of executing the tasks whose decision is taken by the scheduler. Task scheduling is one of the prominent issues in fog computing which includes the process of effectively scheduling the tasks among fog devices to effectively utilize the resources and meet the Quality of Service (QoS) requirements of the applications. Improper task scheduling leads to increased execution time, overutilization of resources, data loss, and poor scalability. Hence there is a need to do proper task scheduling to make optimal task distribution decisions in a highly dynamic resource-constrained heterogeneous fog computing environment. Flow Q learning (FQL) is a potential form of reinforcement learning algorithm which uses the flow matching policy for action distribution. It can handle complex forms of data and multimodal action distribution which make it suitable for the highly volatile fog computing environment. However, flow Q learning struggles to achieve a proper trade-off between the expressive flow model and a reduction in the Q function, as it relies on a one-step optimization policy that introduces bias into the estimated Q function value. The Tiny Language Model (TLM) is a significantly smaller form of a Large Language Model (LLM) which is designed to operate over the device-constrained environment. It can provide fair and systematic guidance to disproportionally biased deep learning models. In this paper a novel TLM guided flow Q learning framework is designed to address the task scheduling problem in fog computing. The neutrality and fine-tuning capability of the TLM is combined with the quick generable ability of the FQL algorithm. The framework is simulated using the Simcan2Fog simulator considering the dynamic nature of fog environment under finite and infinite resources. The performance is found to be good with respect to parameters like execution time, accuracy, response time, and latency. Further the results obtained are validated using the expected value analysis method which is found to be satisfactory. Full article

Background/Objectives: Aphasia screening tools help healthcare professionals detect aphasia after a stroke. To date, there is no standardized and validated aphasia screening tool available for use in Cyprus. The Cyprus Aphasia Screening Test (CAST) is a newly developed tool for detecting post-stroke aphasia. This study aims to present the main characteristics of the CAST and evaluate its psychometric properties and diagnostic accuracy. Methods: A cross-sectional study was conducted, involving 99 participants divided into three groups as follows: 43 people with stroke-aphasia, 21 with strokes but without aphasia, and 35 healthy controls. Results: The CAST demonstrated excellent internal consistency (Cronbach’s α > 0.967), high test–retest (ICC ≥ 0.983) and interrater (ICC = 0.979) reliability, and verified known-groups validity (p< 0.001). A significant correlation between the total scores of the CAST and the Greek version of the Boston Diagnostic Aphasia Examination (Short Form) confirmed a linear relationship across the two measures (p < 0.001). A ROC curve analysis (AUC = 0.97) identified 36/40 as the cut-off for detecting aphasia. Conclusions: The CAST is a reliable, clinician-administered aphasia screening tool with strong psychometric properties. It is designed to identify post-stroke aphasia and distinguish between stroke patients with and without aphasia. It consists of 10 subtests that assess both language comprehension and production. The CAST is designed for easy scoring and requires minimal equipment, making it well-suited for quick and efficient administration at the bedside. The CAST represents a step forward in aphasia screening for Greek-speaking populations in Cyprus. Full article

Background/Objectives: The inappropriate use of veterinary medicines in feed for food-producing animals can compromise food safety. Intensive animal production is associated with the inappropriate use of antibiotics in feed, at subtherapeutic concentrations, to promote animal growth. It is therefore crucial to develop an effective multi-detection method to ensure that this feed complies with the requirements of European Commission Regulations. This control is essential to ensure consumer protection, as adequate supervision contributes to reducing antimicrobial resistance, a growing concern worldwide. Methods: A literature search was conducted using scientific databases, namely PubMed, ScienceDirect, Scopus and Google Scholar, as well as European Union Regulations. Results: It was observed that the most used standard solution solvents are methanol, acetonitrile, ultrapure water, or mixtures of these solvents. For extraction, the most frequently used solvents include trichloroacetic acid combined with McIlvaine buffer or with acetonitrile, and acetonitrile or methanol combined with formic acid or with ethylenediaminetetraacetic acid disodium (Na₂EDTA). For extraction and purification of the analyte, several steps were verified, such as solid-phase extraction (SPE), dispersive solid-phase extraction (d-SPE), liquid–liquid extraction (LLE), Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS), protein precipitation through freezing and dilution prior to analysis. Liquid chromatography coupled with mass spectrometry is the preferred choice, especially for multiple detection methods. Conclusions: Based on this data, the foundation is established for the development of an appropriate method for the simultaneous extraction of multiple classes of antibiotics, which is applicable to feed different food-production animals. Full article

Total joint arthroplasty is among the most common surgical procedures performed worldwide, with frequency increasing due to demographic changes. Accelerating the diagnostic process using new techniques is crucial for effective therapy. This pilot study aims to test such innovative technology in the context of periprosthetic joint infection (PJI) using Scattered Light Integrating Collector (SLIC) technology. While we wish to evaluate whether SLIC can be used to reliably detect the status of infection within human tissue samples in the future, our current research focused on building its foundation by evaluating steps of sample preparation that allow for heightened growth depiction. It is, to our knowledge, the first study concerning the usage of solid human tissue samples using the SLIC device. Adult patients presenting with native or periprosthetic joint infections were included in this prospective study. Biopsies were obtained using sequential sampling, and bacterial density was optimized through titration series. Cryopreservation and agents influencing coagulation were investigated. Our study demonstrates that simple pretreatment could aid in detecting pathogen growth in infected tissue samples. Findings showed a clear advantage for no addition of agents affecting coagulation. Additionally, our protocols proved reliable after prolonged cryopreservation at −20 °C for up to 8 weeks, showing no significant difference compared to primary testing. AUC comparison showed comparable results for sample storage at −80 °C for up to 8 weeks. Similar outcomes were seen for samples ranging from 25 µL to 300 µL, with biological replicates displaying higher thresholds for larger volumes without significant differences. This study introduces a simple and quick diagnostic tool for detecting bacterial growth using tissue biopsies and develops an SOP for further research with this innovative technique. The suggested SOP enables SLIC to hint at an underlying bacterial infection within 5 h using joint tissue, offering a possible novel approach in diagnosing periprosthetic joint infections and septic arthritis. While not yet designed to compare sensitivity to other culture methods, it provides a solid basis for further clinical research. Full article

Background/Objectives: The multitude of histological and genetic features of salivary gland malignancies (SGMs) hampers the ability of the doctors’ board to make a clear and quick decision on how aggressively treatment should be initiated. Despite treatment guidelines, it is difficult to determine the appropriate extent and invasiveness of surgery based on preliminary patient data. The aim of this study is to define the factors that have a significant impact on the oncological outcome of SGM treatment and to create an algorithm for finding the combinations of predictors with a particularly unfavorable impact on survival. Methods: A multicenter retrospective analysis was conducted on 2653 patients with salivary gland tumors (SGTs), including 229 with SGMs (parotid 204/229 = 89.1%; submandibular 25/229 = 10.9%), treated at seven Polish university departments from 2015 to 2022. All patients, except those with malignant lymphoma, underwent surgery followed by radiotherapy. Seventeen potential survival-impacting variables were analyzed: thirteen preoperative and four surgical specimens. The preoperative group aids in deciding surgical aggressiveness, while the postoperative group supports decisions on adjuvant treatment escalation. The main outcome measures were disease-free survival (DFS) and overall survival (OS). Results: SGMs constituted 8.63% of all SGTs, with 204 (89%) in the parotid and 25 (11%) in the submandibular glands. The average age was 63.38 years, with a male predominance (54%). Clinical and radiological signs of malignancy were reported in 45.4% and 54.6% of patients, respectively, with facial nerve palsy reported in 13%. Postoperative specimens revealed 23 histological types, and R0 resections were achieved in 168/229 cases (73%). Fifty-six patients (24.5%) died of cancer within five years. Significant survival factors included gender, urban residence, previous chemical and radiation exposure, clinical malignancy symptoms, pT-stage, pN-stage, clinical stage, and resection margins. Conclusions: The prognosis for SGM remains unsatisfactory, which would suggest more aggressive treatment; thus, carefully collected clinical data could support the decision-making process. Significantly worse survival has been demonstrated in the presence of unfavorable clinical factors, so defining new elements of medical history may be a step towards improving treatment outcomes. Full article