Reliable Differentiation Research Articles

Identification of five Eimeria species in broiler farms in southern Thailand using SYBR Green-based real-time polymerase chain reaction

IntroductionChicken coccidiosis is a globally significant poultry disease caused by Eimeria species, which are highly pathogenic protozoa that impair growth performance and contribute to high morbidity and mortality in the poultry industry. To identify specific Eimeria species, molecular techniques have been developed in several countries as alternatives to conventional diagnostic approaches, which are labor-intensive, time-consuming, and have low accuracy in detecting mixed infections.MethodsThis study aimed to develop a SYBR Green-based real-time polymerase chain reaction assay for the identification of Eimeria species in Thailand, using DNA from five reference species (E. acervulina, E. brunetti, E. maxima, E. necatrix, and E. tenella) and 25 field samples from broiler farms in southern Thailand.ResultsThe assay demonstrated high sensitivity, specificity, and reproducibility. Species-specific melting temperature profiles allowed reliable differentiation of Eimeria DNA from primer-dimers and potential contaminants. Field testing revealed a high prevalence of mixed infections, with E. tenella, E. acervulina, and E. maxima being the most common, whereas E. brunetti and E. necatrix were not detected.DiscussionCompared with conventional gross examination, the SYBR Green-based real-time polymerase chain reaction assay proved to be a more accurate and efficient tool for diagnosing coccidiosis in commercial broiler farms, particularly in detecting subclinical and mixed-species infections.

Utilizing Podocyte Foot Process Morphology for the Identification of Diabetic Nephropathy with or without Minimal Change Disease: Establishment of an Artificial Intelligence-Assisted Diagnostic Model

BackgroundThis study aimed to differentiate whether diabetic nephropathy (DN) is complicated by minimal change disease (MCD) through the differences in podocyte foot process morphology, and subsequently establish an Artificial Intelligence-Assisted (AI-assisted) Diagnostic Model through machine learning of renal tissue electron microscopy images.MethodsPatients diagnosed with DN with nephrotic syndrome and treated in our hospital from January 2014 to December 2023 were selected. Patients were divided into the DN group and the DN with MCD group (DN+MCD group). Podocyte morphology’s diagnostic value was assessed by measuring foot process width and quantifying slit diaphragm changes via Nephrin immunohistochemical staining. This study pioneers developing a machine learning-powered diagnostic model based on renal electron microscopy imaging to differentiate DN cases with or without concurrent MCD.ResultsIn 51 patients, DN+MCD patients exhibited wider podocyte foot processes and reduced Nephrin expression compared to DN. A total of 622 electron microscopy images were used for model establishment and internal validation, while 225 electron microscopy images were used for external validation. A model based on Mobilenetv2 was successfully established, achieving a maximum accuracy of 93.3% in differentiating whether DN is complicated by MCD using a single image. When at least 11 random images were input, stable reports were obtained with an accuracy of 98%. External validation showed that the model had good sensitivity and specificity in differentiating whether DN is complicated by MCD (100%, 83.33%).ConclusionPodocyte foot process morphology has diagnostic value in differentiating whether DN is complicated by MCD. Our AI model addresses the unmet clinical need for reliable differentiation between DN with and without concurrent MCD. Additionally, it establishes a foundational framework for AI-powered analysis of renal imaging data to improve disease diagnosis and prognosis prediction.

Statistical Distributions of Morphologically Classified Defects in Metal Additive Manufacturing with Implications for Fatigue Life Prediction

Metal additive manufacturing (AM) enables the production of complex components but often introduces defects with varied morphology, size, and distribution—factors that significantly affect fatigue performance. This study investigates the role of statistical distributions in defect analysis and discusses their implications for probabilistic fatigue modeling methods. Metrics including the coefficient of determination, Kolmogorov–Smirnov goodness‐of‐fit test, and quantile–quantile plots are employed to evaluate the fit between proposed distributions and actual defect distributions. A novel triplewise comparison method is proposed to quantify overlap among morphological features and enhance defect classification. To assess the influence of distribution choice, a simulation study using synthetic datasets—generated with best‐fit and uniformly applied distributions—demonstrates that accurate distribution selection is critical for reliable feature ranking and defect differentiation. By leveraging these statistical methods, manufacturers can more effectively identify and mitigate critical defects, thereby improving the reliability and industrial applicability of AM technologies.

Thoracic staging of lung cancers by 18FDG-PET/CT: impact of artificial intelligence on the detection of associated pulmonary nodules.

This study focuses on automating the classification of certain thoracic lung cancer stages in 3D 18FDG-PET/CT images according to the 9th Edition of the TNM Classification for Lung Cancer (2024). By leveraging advanced segmentation and classification techniques, we aim to enhance the accuracy of distinguishing between T4 (pulmonary nodules) Thoracic M0 and M1a (pulmonary nodules) stages. Precise segmentation of pulmonary lobes using the Pulmonary Toolkit enables the identification of tumor locations and additional malignant nodules, ensuring reliable differentiation between ipsilateral and contralateral spread. A modified ResNet-50 model is employed to classify the segmented regions. The performance evaluation shows that the model achieves high accuracy. The unchanged class has the best recall 93% and an excellent F1 score 91%. The M1a (pulmonary nodules) class performs well with an F1 score of 94%, though recall is slightly lower 91%. For T4 (pulmonary nodules) Thoracic M0, the model shows balanced performance with an F1 score of 87%. The overall accuracy is 87%, indicating a robust classification model.

Development and testing of a set of chromogenic media for rapid diagnosis of bovine mastitis

Introduction. Bovine mastitis remains one of the most prevalent and economically significant diseases in dairy cattle production. Three chromogenic media have been proposed for the diagnosis, each specifically designed for isolation and differentiation of certain mastitis pathogen groups: Medium I is intended for Enterobacteriaceae family bacteria, Medium II – for Staphylococcus genus microorganisms, Medium III – for Streptococcus genus bacteria.Objective. The objective is to evaluate the sensitivity, specificity, differentiation capacities and inhibitory properties of these chromogenic media, and to test the media using milk samples from mastitic cows.Materials and methods. For sensitivity testing, the control strains (Streptococcus agalactiae, Staphylococcus aureus and Escherichia coli) at concentrations of 1×100, 1×101, and 1×102 CFU/mL were used. Microbial growth was assessed following 24-hour incubation at 37 °C. Specificity and differentiation capacities were studied using 22 microbial strains, their growth patterns and colony coloration in chromogenic and control media were compared. Inhibitory properties were determined based on presence/absence of culture growth. The media were evaluated using milk samples from mastitic cows and standardized culturing methods.Results. The chromogenic media demonstrated sensitivity comparable to the control media (Columbia agar supplemented with 5% defibrinated sheep blood), p > 0.05. Medium I enabled reliable color-based differentiation but showed limited inhibitory effects. Medium II ensured selective isolation of staphylococci while effectively suppressing growth of other bacteria. Medium III supported growth of both enterococci and streptococci, including Streptococcus agalactiae. The tests conducted in milk samples confirmed genus level differentiation capability.Conclusion. The developed chromogenic media ensure high-accuracy mastitis diagnosis due to their sensitivity, specificity and differentiation properties. Their implementation makes it possible to cover an extensive range of microorganisms and to selectively isolate the targeted bacterial groups. Further work will be aimed at improving the media for fungal growth suppression and increasing the diagnostic accuracy.

Detachable and Reusable: Reinforced π-Ion Film for Modular Synaptic Reservoir Computing.

Organic electrochemical transistors (OECTs) show significant promise for bioelectronics and neuromorphic computing applications due to their low operating voltage, biocompatibility, and ion-mediated charge transport. However, conventional OECTs with permanently fixed organic semiconductor (OSC) layers lack modularity and reusability for sustainable electronics with e-waste reduction. Here, a novel reinforced π-ion film OECT featuring a detachable and reusable OSC layer that creates a unified composite with dielectric and gate components, establishing a new paradigm for modular device architectures is proposed. Through solvent exchange and mesh-supported gelation, π-ion film exhibits enhanced mechanical stability, detachability, and superior electrical performance. The OECTs demonstrate remarkable 35-day air stability, 50-day storage lifetime, and over 80% performance retention after 600 electrical cycles. Furthermore, the π-ion film OECTs exhibit synaptic behavior with paired-pulse facilitation of 167% and long-term memory retention of 34% maintained synaptic current after 250 s. These characteristics enable reservoir computing applications with a 4-bit encoding scheme for image recognition, processing 16 × 16 pixelated input patterns, demonstrating reliable state differentiation and stable signal retention. Even at lab-scale development, reinforced π-ion film OECTs represent a promising eco-friendly platform for modular, reusable components in next-generation neuromorphic computing systems, aligning with electronic waste reduction policies by enabling component reuse.

Highly Sensitive Triple-Network Hydrogels Enable Advanced Sensing for Next-Generation E-Skins.

In this work, a highly sensitive, flexible, and stable hydrogel is developed for electronic skin with a triple-network structure composed of polyacrylamide monomer (PAAM), poly(vinyl alcohol) (PVA), PEDOT:PSS, and Fe3⁺ coordination bonds. The hydrogel exhibits exceptional mechanical and electrical properties, including high tensile strength (91.2kPa), extensibility (1210%), conductivity (178.8 Sm-1 at 200% strain), and long-term durability, achieved through the synergistic effects of hydrogen bonding, dynamic Fe3⁺ coordination, and ionic conductivity. The sensor demonstrates precise and proportional resistance responses to various mechanical stimuli, such as bending, stretching, and tapping motions, enabling accurate detection of joint movements, including the fingers, wrist, and elbow. Furthermore, the hydrogel's fast response and low noise allow for reliable differentiation of motion speeds and the successful transmission of Morse code signals. The long-term stability and cyclic durability of the sensor highlight its robustness for real-time applications. These versatile hydrogels offer a promising platform for wearable electronics, gesture recognition, and human-machine interfaces, paving the way for next-generation interactive sensing technologies. Moreover, the preparation method ensures high reproducibility and scalability, making it suitable for large-scale manufacturing.

The value of Gd-EOB-DTPA-enhanced MRI in the differential diagnosis of HCC with hyperintensity on HBP and FNH.

The aim was to investigate the differential diagnostic potential of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) features and establish a nomogram model for distinguishing hepatocellular carcinoma (HCC) from focal nodular hyperplasia (FNH) presenting with hyperintensity on the hepatobiliary phase (HBP). This retrospective study enrolled 80 patients with pathologically confirmed HCC or FNH who underwent Gd-EOB-DTPA-enhanced MRI between January 2017 and December 2020. All lesions exhibited hyperintensity on HBP. Morphological characteristics, signal patterns, and apparent diffusion coefficient (ADC) values were analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of HCC, adjusting for age and sex. A diagnostic nomogram was subsequently constructed. After adjusting for age and sex, the study showed that nodule-in-nodule hyperintensity on HPB (odds ratio [OR] = 36.46, 95% confidence interval [CI]: 4.01-331.13), an ADC value ≤1.087 × 10-3 mm2/s (OR = 0.004, 95% CI: 0.00-0.06), and the absence of a central scar (OR = 0.04, 95% CI: 0.003-0.40) were independent predictors of HCC. The nomogram incorporating these predictors demonstrated excellent diagnostic performance, with an area under the receiver operating characteristic curve of 0.933 (95% CI: 0.874-0.991). The calibration curve showed optimal agreement between predicted and observed probabilities. Gd-EOB-DTPA-enhanced MRI characteristics combined with ADC values enable reliable differentiation between HBP-hyperintense HCC and FNH. The proposed nomogram model provides a clinically applicable tool for improving diagnostic accuracy in challenging cases.

An Ultrasensitive Wearable Nanosensor for Minimally Invasive Self-Screening of Alzheimer's Disease.

The rising global prevalence of Alzheimer's disease (AD) has emerged as a critical public health challenge, placing strain on families, communities, and healthcare systems. Despite advances in diagnostic methods, current techniques for early AD detection remain limited, often being invasive, costly, and impractical for regular use. Here, we report a fully integrated wearable nanosensor offering an easily accessible and user-friendly strategy for AD screening. This biosensing platform incorporates a microneedle-based interstitial fluid (ISF) sampling device and an ultrasensitive graphene field-effect transistor (GFET) chip, enabling rapid and precise detection of AD biomarkers. Furthermore, this nanosensor was successfully validated in transgenic murine models, demonstrating reliable differentiation between AD and non-AD mouse groups with high specificity. Overall, this study offers a promising alternative tool to the existing invasive and expensive techniques for the AD preliminary screening, paving the way for drug discovery, early diagnosis, and personalized treatment of AD.

Differentiation of SH-SY5Y Cells into Cortical Neuron-like Cells for Tauopathy Modeling and Seeding Assays.

SH-SY5Y cells are widely used as an in vitro neuronal model, yet reliable differentiation protocols tailored for tauopathy research remain limited. Effective differentiation is essential for studying tau aggregation, propagation, and neurodegenerative mechanisms. Here, we present an optimized two-step differentiation protocol for TauP301L-expressing SH-SY5Y cells that enhances neuronal maturation and tauopathy modeling, providing a physiologically relevant system for investigating tau seeding. SH-SY5Y cells expressing TauP301L-EGFP under an inducible system were differentiated using a two-step protocol consisting of retinoic acid (RA) for 72h, followed by brain-derived neurotrophic factor (BDNF) and RA for 72h. Differentiated neurons were then exposed to exogenous P301L tau peptidefibrils to assess their susceptibility to tau seeding and aggregation. Differentiation resulted in increased neurite outgrowth, cholinergic marker expression (ChAT upregulation, TH downregulation), and upregulation of the mature 2N4R tau isoform. Western blot analysis showed increased T22 and pSer262 tauimmunoreactivity in seeded cells, consistent with tau conformational changes and pathological phosphorylation. These findings may reflect early stages of tau misfolding but do not confirm oligomer formation. Seeding also induced neurite remodeling, varicosity formation, and reduced neurite diameter-features consistent with tau-mediated pathology involving cytoskeletal changes, organelle accumulation, or axonal transport defects. This optimized differentiation protocol provides an experimentally tractable tauopathy model for investigating tau propagation and neuronal dysfunctions in a controlled human cell context. Compared to existing SH-SY5Y differentiation methods, our system provides faster neuronal maturation, controlled TauP301L induction, and enhanced tau isoform expression, making it a valuable platform for studying early tau misfolding events and therapeutic interventions in tauopathies.

Enhancing glaucoma diagnosis: Generative adversarial networks in synthesized imagery and classification with pretrained MobileNetV2.

Enhancing glaucoma diagnosis: Generative adversarial networks in synthesized imagery and classification with pretrained MobileNetV2.

Is there a place for ultrasound in diagnosing sarcopenia?

BackgroundSarcopenia is a progressive and generalised skeletal muscle disorder which presents as loss of muscle mass and function and is associated with increased likelihood of adverse outcomes, reduced quality of life and increased mortality. In developed countries, the prevalence of sarcopenia is rising due to increasing life expectancy. Still, in many clinical settings, sarcopenia may be overlooked and undertreated. While several tools are available for assessment of muscle mass and quality, there remains a need for safe, reliable and accurate diagnostic methods which can be implemented for both sarcopenia diagnosis and the evaluation of treatment efficacy.ConclusionsUltrasound is an accessible and non-ionizing imaging technique that can potentially be used for that purpose. Several ultrasound parameters have been identified for their utility to provide assessment of muscle mass, quality and/or muscle function. Ultrasound is gaining recognition as an accurate and reproducible method of muscle mass assessment. However, there are still several limitations that preclude the application of ultrasound in routine clinical practice. Implementing a harmonized measurement protocol and conducting large-scale longitudinal studies on both healthy individuals and various patient cohorts could enable the establishment of clearly defined reference values for individual ultrasound parameters and, in turn, potentially reliable differentiation between normal and sarcopenic states.

A Fragment Insertion of AgDFR Results in a White Flower Phenotype in Arundina graminifolia (Orchidaceae).

Bamboo orchid (Arundina graminifolia), a fast-growing evergreen terrestrial orchid with year-round flowering capacity, exhibits limited germplasm resources for white floral variants despite its ornamental significance. This study investigates the molecular basis of natural white flower formation through comparative analysis of purple- and white-flowered variants across bud, post-bud, and blooming stages. Histological examination revealed anthocyanin accumulation restricted to two to three upper epidermal cell layers in purple petals, while white petals showed complete pigment absence. Transcriptome profiling coupled with RT-qPCR validation identified eleven differentially expressed structural genes in anthocyanin biosynthesis. Notably, AgDFR expression remained undetectable across all white-flower developmental stages. Sequence analysis demonstrated identical 3030 bp promoter regions of AgDFR between two variants, while white-flower AgDFR coding sequences contained over 107 bp insertion after the 330th nucleotide, causing premature translation termination. Molecular marker validation confirmed the presence of a diagnostic 472 bp fragment in all colored variants (13 purple/pink lines) and its absence in white phenotypes. This study establishes that insertional mutagenesis in AgDFR's coding region underlies natural white flower in A. graminifolia. The developed molecular marker enables reliable differentiation of white-flowered variants from pigmented counterparts, providing valuable tools for germplasm management and breeding programs.

Molecular detection and identification of Trichobilharzia: development of a LAMP, qPCR, and multiplex PCR toolkit

BackgroundCercarial dermatitis (CD), or swimmer’s itch, is a water-borne allergic skin reaction caused by the penetration of the larval stages of bird schistosomes (cercariae) into the skin. Members of the genus Trichobilharzia are the primary causative agents of CD worldwide. Due to the increasing number of cases, CD is regarded as a (re)emerging disease. Outbreaks in recreational waters can significantly impact public health and local economies. Environmental monitoring of Trichobilharzia is crucial for outbreak prediction and public health management. However, conventional methods, such as cercarial shedding and snail dissections, are labour-intensive and lack sensitivity. To overcome these limitations, we present a molecular toolkit that combines loop-mediated isothermal amplification (LAMP), quantitative polymerase chain reaction (qPCR), and multiplex PCR for rapid, sensitive, and accurate detection and identification of Trichobilharzia spp. from various biological samples.MethodsTricho-LAMP and Tricho-qPCR were designed and optimised for Trichobilharzia DNA detection. A multiplex PCR assay was also developed and optimised to identify the three main species causing CD in Europe (Trichobilharzia franki, T. szidati, and T. regenti).ResultsTricho-LAMP specifically detected T. regenti and T. franki at 10−3 ng, and T. szidati at 10−2 ng per reaction with genomic DNA. Using gBlocks synthetic DNA, Tricho-LAMP achieved 100% amplification at 10,000 copies and 85% amplification at 1000 copies, with decreasing success at lower concentrations. Tricho-qPCR showed the highest sensitivity, detecting all species down to 10−4 ng per reaction and showing a limit of detection at 10 copies of synthetic DNA in the reaction. Multiplex PCR allowed reliable species differentiation via gel electrophoresis of the PCR products, but the assay had the lowest sensitivity.ConclusionsWe provide a molecular toolkit consisting of LAMP, qPCR, and multiplex PCR. By exhibiting high sensitivity, Tricho-LAMP and Tricho-qPCR assays are potentially suitable for environmental DNA (eDNA)-based environmental monitoring of bird schistosomes, by both researchers and public health authorities. Multiplex PCR can be used for species determination without the need for further sequencing.Graphical

Diagnosis of Acute Aortic Syndromes Using Computed Tomography

Acute aortic syndrome refers to a group of life-threatening conditions characterized by acute injury to the aortic wall, primarily involving disruption of the intima and media. Acute aortic syndrome encompasses a spectrum of interrelated and overlapping clinical and morphological entities, including classic aortic dissection, intramural hematoma, penetrating aortic ulcer, and limited intimal tear. Differentiation of these variants based on clinical presentation and physical examination findings is not feasible. Imaging plays a pivotal role, and definitive diagnosis and classification of acute aortic syndrome variants are possible only through imaging studies. Multidetector computed tomography, transesophageal echocardiography, and magnetic resonance imaging are the primary imaging modalities used for the diagnosis of acute aortic syndrome, with contrast-enhanced multidetector computed tomography considered the gold standard. When classical imaging signs of a specific type of acute aortic syndrome are present, diagnosis is generally straightforward. However, a broad spectrum of imaging findings exists. In some cases, a single computed tomography scan may not allow for reliable differentiation among acute aortic syndrome variants. This limitation arises from the fact that these pathological entities may occur independently, progress from one to another, or coexist. The pathophysiology and clinical course of intramural hematoma and penetrating atherosclerotic ulcer of the aorta remain subjects of ongoing debate. In particular, the classification of intramural hematoma as a distinct acute aortic syndrome variant continues to be controversial. This article provides a concise overview of the current understanding of the pathophysiology, natural history, prognosis, and multidetector computed tomography-based diagnosis of the less common acute aortic syndrome variants, specifically intramural hematoma and penetrating atherosclerotic ulcer.

Assessing the capability of YOLO- and transformer-based object detectors for real-time weed detection

Spot spraying represents an efficient and sustainable method for reducing herbicide use in agriculture. Reliable differentiation between crops and weeds, including species-level classification, is essential for real-time application. This study compares state-of-the-art object detection models-YOLOv8, YOLOv9, YOLOv10, and RT-DETR-using 5611 images from 16 plant species. Two datasets were created, dataset 1 with training all 16 species individually and dataset 2 with grouping weeds into monocotyledonous weeds, dicotyledonous weeds, and three chosen crops. Results indicate that all models perform similarly, but YOLOv9s and YOLOv9e, exhibit strong recall (66.58 % and 72.36 %) and mAP50 (73.52 % and 79.86 %), and mAP50-95 (43.82 % and 47.00 %) in dataset 2. RT-DETR-l, excels in precision reaching 82.44 % (dataset 1) and 81.46 % (dataset 2) making it ideal for minimizing false positives. In dataset 2, YOLOv9c attains a precision of 84.76% for dicots and 78.22% recall for Zea mays L.. Inference times highlight smaller YOLO models (YOLOv8n, YOLOv9t, and YOLOv10n) as the fastest, reaching 7.64 ms (dataset 1) on an NVIDIA GeForce RTX 4090 GPU, with CPU inference times increasing significantly. These findings emphasize the trade-off between model size, accuracy, and hardware suitability for real-time agricultural applications.

Quantitative PCCT imaging in differentiating adrenal adenomas from metastases: diagnostic performance and its clinical applications.

To evaluate the potential of Photon counting CT (PCCT) -derived iodine densities and Virtual-Non-Contrast (VNC) reconstructions for the differentiation between adrenal adenomas and adrenal metastases. This retrospective study enrolled 53 PCCT scans of patients with adrenal lesions (29 adenomas, 24 metastases) including early-arterial (ea) and portal-venous (pv) contrast phase. Iodine maps and VNC reconstructions were calculated from the acquired sequences. Using the measured values, several parameters such as relative enhancement (RE), normalized iodine density (NID), and iodine to VNC ratio (IVR) were calculated. In the acquired image series, iodine maps and VNC reconstructions density values were evaluated (adrenal lesion, ipsilateral adrenal tissue, contralateral adrenal tissue, portal vein, descending aorta, inferior vena cava, subcutaneous adipose tissue, in the first lumbar vertebral body, surrounding air, and in the psoas muscle) and compared. In total, the measured structures showed significant variation in density values due to different contrast phases and reconstructions. VNC reconstructions of portal-venous contrast phase showed significant differences in measured density mean values between adrenal adenomas and adrenal metastases (21.64 HU vs. 28.26 HU, p: 0.027, AUC: 0.68). No significant differences between metastases and adenomas were observed in iodine concentration, RE of ea, NID of ea and pv, as IVR of ea. Significant alterations were observed in RE of pv (p: 0.023, AUC: 0.7) and IVR of pv (pv: 0.029, AUC: 0.69). The recent study shows that PCCT derived VNC reconstructions of portal venous contrast phase can be used for reliable differentiation of adrenal adenomas and adrenal metastases and underlines the value of PCCT in oncological imaging.

MicroRNA expression in exhaled breath condensate differentiates between asthma and chronic obstructive pulmonary disease

Asthma and chronic obstructive pulmonary disease (COPD) have many common clinical characteristics, thus making reliable differentiation between these two challenging. The goal of this study is to determine the clinical value of exhaled breath condensate (EBC) derived miRNAs to discriminate between asthma and COPD. This cross-sectional study included 65 subjects each with asthma (mean/SD age: 39/13 years, Malen/%: 27/42%), COPD (mean/SD age: 61/9 years, Malen/%: 53/81%) and healthy controls (mean/SD age: 34.4/12 years, Malen/%: 50/77%). EBC was collected using R-tubes and 40 EBC samples from each group were used for miRNA profiling. Profiling data was curated and the most highly expressed miRNAs were shortlisted for further validation. Selected microRNAs were subsequently validated using quantitative-PCR in an independent set of 25 subjects from both disease groups. A total of 103 miRNAs were significantly upregulated in the EBC of asthma patients and 97 miRNAs were upregulated in the EBC of COPD patients compared to control group. However, miR-512-3p was downregulated and miR-517c was upregulated in COPD compared with asthma. The top unique miRNAs were shortlisted for further validation. Of these, miR-375 was upregulated in asthma, while miR-297, miR-367 and miR-539 were upregulated in COPD compared with healthy controls. Further, miR-512-3p was down-regulated and miR-517c was upregulated in COPD compared with asthma. The comparison exhibited excellent discriminatory power with 100% differential expression of miR-512-3p and miR-517c secreted by respiratory cells, they could be quantitated in EBC samples and used to differentiate between asthma and COPD.

Simultaneous Detection of Classical and African Swine Fever Viruses by Duplex Taqman Real-Time PCR Assay in Pigs Infected with Both Diseases.

The increasing spread of African swine fever (ASF) in recent years and the presence of classical swine fever (CSF) subclinical forms in endemic countries suggests that the possibility of coinfection with ASF virus (ASFV) and CSF virus (CSFV) in pigs cannot be ruled out in areas where both diseases are prevalent. Thus, rapid and reliable diagnosis through molecular testing is essential for the timely implementation of control measures to prevent the spread of these devastating swine diseases. Here, we have coupled two of the most validated PCR assays for the detection of CSFV and ASFV in a single reaction tube. The combination of the two tests for the detection of two target nucleic acids did not affect the analytical sensitivity, and the duplex RT-qPCR assay was comparable with the standard molecular techniques. The detection limits for CSFV RNA and ASFV DNA were 0.12 TCID50/reaction and 0.25 TCID50/reaction, respectively. The test showed high repeatability and reproducibility, the coefficient of variation was below 2%, and excellent performance was demonstrated in clinical samples. The duplex assay shows great potential to become a robust diagnostic tool for the rapid and reliable detection and differentiation of CSFV and ASFV in areas where both viruses may be circulating.

Сравне- ние метаболомного профиля ликвора и плазмы крови пациентов с ремиттирующим рассеянным склерозом

INTRODUCTION. Multiple sclerosis is a chronic demyelinating neurodegenerative disease of the central nervous system of autoimmune origin. Molecular processes associated with the onset and progression of multiple sclerosis, as well as its etiology, have not been sufficiently studied. The profile of final and intermediate metabolic products (metabolome) is a reflection of metabolic processes that can shed light on the pathophysiological basis of multiple sclerosis and improve the diagnostic and therapeutic aspects of clinical practice. AIM. Evaluation of the profile of low-molecular metabolites of cerebrospinal fluid and blood plasma in patients with relapsingremitting multiple sclerosis using liquid chromatography with mass spectrometric detection. MATERIALS AND METHODS. The study included 16 patients suffering from various subtypes of multiple sclerosis. Blood plasma and cerebrospinal fluid were collected from the patients for metabolomic analysis. RESULTS AND DISCUSSION. 24 metabolites were identified that allow reliable differentiation between the stages of relapsingremitting multiple sclerosis. The metabolites combined into profiles reflect the predominant involvement of the proinflammatory link during exacerbation of relapsing-remitting multiple sclerosis, and the remyelination link during remission. CONCLUSION. The obtained metabolite profiles indicate differences in the prevailing pathophysiological processes, and individual metabolites can be used as markers of the activity of the inflammatory process of multiple sclerosis.