Innovative Diagnostics Research Articles

Nanotechnology in COVID-19 and SARS-CoV-2: Advances in Antiviral Therapies and Applications

Innovative diagnostics, therapeutics, and preventive strategies must be developed to combat the emergence of new viral pathogens and the resurgence of known viruses. Using nanotechnology to enhance antiviral therapeutic efficacy through improved drug delivery, targeted viral inhibition, and immune modulation has emerged as a transformative approach to addressing these viral threats. SARS-CoV-2, hemorrhagic viruses, and zoonotic pathogens can be combated with nanotechnology-based platforms, including nanogels, dendrimers, and metal-based nanoparticles. As a result of recent advances in nanoparticle engineering, "smart" systems can respond to viral infection markers, deliver therapeutics to specific sites, and control drug release profiles. Using nanotechnology to develop vaccines, such as mRNA vaccines for COVID-19, can enhance immune responses and accelerate vaccine rollout. Additionally, multifunctional nanomaterials enable early and accurate detection of viral pathogens using antiviral diagnostics. As well as discussing advances in addressing viral resistance, this review examines theranostic applications, integrating diagnostic and therapeutic functionalities within single nanostructures. This study highlights the potential for nanomedicine to revolutionize antiviral therapies, improve treatment outcomes, and develop rapid-response solutions to future viral threats by examining the recent applications of nanotechnology in viral disease management.

50 Years of Antibody Numbering Schemes: A Statistical and Structural Evaluation Reveals Key Differences and Limitations.

The complementarity-determining region (CDR) of antibodies represents the most diverse region both in terms of sequence and structural characteristics, playing the most critical role in antibody recognition and binding for immune responses. Over the past decades, several numbering schemes have been introduced to define CDRs based on sequence. However, the existence of diverse numbering schemes has led to potential confusion, and a comprehensive evaluation of these schemes is lacking. We employ statistical analyses to quantify the diversity of CDRs compared to the framework regions. Comparative analyses across different numbering schemes demonstrate notable variations in CDR definitions. The Kabat and AbM numbering schemes tend to incorporate more conserved residues into their CDR definitions, whereas CDRs defined by the Chothia and IMGT numbering schemes display greater diversity, sometimes missing certain loop residues. Notably, we identify a critical residue, L29, within the kappa light chain CDR1, which appears to act as a pivotal structural point within the loop. In contrast, most numbering schemes designate the topological equivalent point in the lambda light chain as L30, suggesting the need for further refinement in the current numbering schemes. These findings shed light on regional sequence and structural conservation within antibody sequence databases while also highlighting discrepancies stemming from different numbering schemes. These insights yield valuable guidelines for the precise delineation of antibody CDRs and the strategic design of antibody repertoires, with practical implications in developing innovative antibody-based therapeutics and diagnostics.

Advanced biomolecular spectroscopic profiling of cardiovascular disease macromolecular markers: SIL-6, IL-9, LpA, ApoB, PCSK9 and NT-ProBNP for rapid in-situ detection and monitoring

Cardiovascular disease (CVD) remains a major global health concern and a leading cause of morbidity and mortality worldwide. Early-diagnosis and prompt medical attention are crucial in managing and reducing overall impact on health-and-wellbeing, necessitating the development of innovative diagnostics, which transcend traditional methodologies. Raman spectroscopy uniquely provides molecular fingerprinting and structural information, offering insights into biochemical composition. Integration of Raman spectroscopy with advanced machine learning is established as a powerful clinical adjunct for point-of-care detection of CVDs. A non-invasive, label-free spectroscopic platform coupled with neural network algorithm, ‘SKiNET’ has been developed to accurately detect the biomolecular changes within plasma of CVD versus healthy cohorts, enabling rapid diagnosis and longer-term monitoring, where the real-time capabilities provide dynamic assessment of progression, aligning treatment strategies with evolving states. CVD has been detected and classified via SKiNET with 88.6 %-accuracy, 92.9 %-specificity and 85.1 %-sensitivity and with 83.8 %-accuracy. The hybrid RS-SKiNET bio-molecularly specific detection signposted a comprehensive panel of CVD-indicative biomarkers, including SIL-6, IL-9, LpA, ApoB, PCSK9 and NT-ProBNP, offering important insights into disease mechanisms and risk-stratification. This multidimensional technique holds potential for improved patient-and-healthcare management for CVDs, laying the platform toward high-throughput biomolecular profiling of CVD-indicative macromolecular biomarkers, particularly vital for widespread point-of-care diagnostics and monitoring.

Synthetic data and ELSI-focused computational checklists-A survey of biomedical professionals' views.

Artificial intelligence (AI) and machine learning (ML) tools are now proliferating in biomedical contexts, and there is no sign this will slow down any time soon. AI/ML and related technologies promise to improve scientific understanding of health and disease and have the potential to spur the development of innovative and effective diagnostics, treatments, cures, and medical technologies. Concerns about AI/ML are prominent, but attention to two specific aspects of AI/ML have so far received little research attention: synthetic data and computational checklists that might promote not only the reproducibility of AI/ML tools but also increased attention to ethical, legal, and social implications (ELSI) of AI/ML tools. We administered a targeted survey to explore these two items among biomedical professionals in the United States. Our survey findings suggest that there is a gap in familiarity with both synthetic data and computational checklists among AI/ML users and developers and those in ethics-related positions who might be tasked with ensuring the proper use or oversight of AI/ML tools. The findings from this survey study underscore the need for additional ELSI research on synthetic data and computational checklists to inform escalating efforts, including the establishment of laws and policies, to ensure safe, effective, and ethical use of AI in health settings.

Placental-origin Disease Diagnosis and Treatment Advances

Placental-origin diseases, stemming from placental dysfunction, impact maternal and fetal health. This article reviews scientific and clinical advancements, emphasizing molecular insights and innovative diagnostics and treatments. It notes that placental issues are associated with signaling pathway dysregulation and epigenetic responses to environmental influences. Clinical tools like Doppler ultrasound and noninvasive DNA testing improve early disease detection. Personalized medicine, considering genetic and lifestyle elements, presents new management strategies. Challenges due to disease diversity and individual differences remain, with a call for future research to focus on biomarker identification, environmental-genetic interactions, and interdisciplinary efforts to advance diagnostics and therapeutics.

Whole Organ Volumetric Sensing Ultrasound Localization Microscopy for Characterization of Kidney Structure.

Glomeruli are the filtration units of the kidney and their function relies heavily on their microcirculation. Despite its obvious diagnostic importance, an accurate estimation of blood flow in the capillary bundle within glomeruli defies the resolution of conventional imaging modalities. Ultrasound Localization Microscopy (ULM) has demonstrated its ability to image in-vivo deep organs in the body. Recently, the concept of sensing ULM or sULM was introduced to classify individual microbubble behavior based on the expected physiological conditions at the micrometric scale. In the kidney of both rats and humans, it revealed glomerular structures in 2D but was severely limited by planar projection. In this work, we aim to extend sULM in 3D to image the whole organ and in order to perform an accurate characterization of the entire kidney structure. The extension of sULM into the 3D domain allows better localization and more robust tracking. The 3D metrics of velocity and pathway angular shift made glomerular mask possible. This approach facilitated the quantification of glomerular physiological parameter such as an interior traveled distance of approximately 7.5 ±0.6 microns within the glomerulus. This study introduces a technique that characterize the kidney physiology which can serve as a method to facilite pathology assessment. Furthermore, its potential for clinical relevance could serve as a bridge between research and practical application, leading to innovative diagnostics and improved patient care.

B-224 Rapid, Extraction-Free, and Portable Molecular Detection of HIV-1 and HCV Directly From Whole Blood

Abstract Background Early diagnosis of human immunodeficiency virus-1 (HIV-1) and hepatitis C virus (HCV) is key to preventing viral transmission and improving linkage to treatment. Isothermal amplification methods, such as reverse transcription looped-mediated amplification (RT-LAMP), have enabled molecular diagnostics to expand beyond centralized laboratories. Despite the advances in molecular point-of-care (POC) testing, many of these tests are costly and still depend on a reliable power-source, specialized equipment, and cold-chain storage, making them impractical for resource-limited settings. To overcome these barriers, there is a need for innovative molecular diagnostics for blood-borne pathogens. Here, we propose a simple, extraction-free, portable workflow for detecting HIV-1 and HCV from whole blood within 40 minutes. Methods We developed singleplex RT-LAMP-based tests using modified published primer sets. Contrived whole blood samples containing HIV-1 or HCV virions were diluted in equal parts water and loaded directly into optimized RT-LAMP master mixes. To mitigate cold-chain storage dependence, RT-LAMP reactions were performed using a lyophilized master mix. The reactions were heated for 30 minutes using a hand-held, battery-powered heating device for simultaneous virion lysis and amplification. For simple visual detection, amplification was coupled with a lateral flow-based dipstick test. The analytical sensitivity of each detection test was evaluated using contrived whole blood samples ranging in HIV-1 and HCV 1a viral loads. Additionally, HCV detection was evaluated on genotypes 1b, 2b, and 3a. For result confirmation, a custom CRISPR-Cas12a-based assay was used to verify the presence or absence of pathogen-specific amplicons following amplification. Results The diagnostic workflow can be completed within 40 minutes, including less than 10 minutes of hands-on time. At optimal conditions, the HIV-1 and HCV 1a singleplex tests had lower limits of detections of 4.89 log10 cp/mL and 3.77 log10 IU/mL, respectively. Evaluation of the published literature showed that these viral loads are within the ranges observed during acute HIV-1 and HCV infection. HCV detection was also observed for genotypes 1b and 3a, albeit at a lower sensitivity than genotype 1a. No detection was observed for genotype 2b, presumably due to the lower viral loads of the samples. No cross-reactivity between the two tests was observed. Conclusions Our proposed workflow allows for rapid detection of blood-borne pathogens without the need for complex equipment or cold-chain storage, showing potential for application in resource-limited settings. Additional validation within a clinical setting using fingerstick blood remains to be tested.

High-resolution AI image dataset for diagnosing oral submucous fibrosis and squamous cell carcinoma

Oral cancer is a global health challenge with a difficult histopathological diagnosis. The accurate histopathological interpretation of oral cancer tissue samples remains difficult. However, early diagnosis is very challenging due to a lack of experienced pathologists and inter- observer variability in diagnosis. The application of artificial intelligence (deep learning algorithms) for oral cancer histology images is very promising for rapid diagnosis. However, it requires a quality annotated dataset to build AI models. We present ORCHID (ORal Cancer Histology Image Database), a specialized database generated to advance research in AI-based histology image analytics of oral cancer and precancer. The ORCHID database is an extensive multicenter collection of high-resolution images captured at 1000X effective magnification (100X objective lens), encapsulating various oral cancer and precancer categories, such as oral submucous fibrosis (OSMF) and oral squamous cell carcinoma (OSCC). Additionally, it also contains grade-level sub-classifications for OSCC, such as well- differentiated (WD), moderately-differentiated (MD), and poorly-differentiated (PD). The database seeks to aid in developing innovative artificial intelligence-based rapid diagnostics for OSMF and OSCC, along with subtypes.

Development and Evaluation of the DMIND Questionnaire: Preparing for AI Integration into an Effective Depression Screening Tool

Objective: Thailand’s mental health crisis is exacerbated by high demand and a shortage of mental health professionals. The research objective was to develop and validate the Detection and Monitoring Intelligence Network for Depression (DMIND) questionnaire, designed to be culturally relevant and easily administered in clinical settings. Crafted with expert input, items specifically conducive to artificial intelligence (AI) analysis were selected to facilitate the future development of an AI-assisted depression scoring model. This approach underscores the tool’s dual utility in both human-led and technology-enhanced diagnostics. Materials and Methods: We enrolled 81 participants from psychiatric and tertiary care hospitals in Bangkok. Participants were assessed using the DMIND questionnaire, followed by the Hamilton Depression Rating Scale (HDRS-17). Statistical analyses included the content validity index (CVI), Cronbach’s alpha, Pearson’s correlation coefficient, Cohen’s kappa, and receiver operating characteristic (ROC) analysis. The Liu method, Youden index, and nearest neighbor method were used to determine the optimal cut-off point Results: The DMIND questionnaire showed strong validity, with an item-level CVI (I-CVI) and scale-level CVI (S-CVI) exceeding 1.0, indicating strong consensus on its relevance and utility. The tool also demonstrated high internal consistency (Cronbach’s alpha = 0.96). ROC analysis showed an AUC of 0.88, indicating high accuracy in depression screening. An optimal cut-off score of 11.5 was identified, balancing predictive value and sensitivity. Conclusion: The DMIND questionnaire represents a significant advancement in innovative mental health diagnostics, addressing unmet clinical needs by providing accurate and efficient assessments capable of AI integration for further enhancing mental health service delivery in Thailand.

Molecular Investigation of Small Ruminant Abortions Using a 10-Plex HRM-qPCR Technique: A Novel Approach in Routine Diagnostics.

The objective of this study was to apply and preliminarily evaluate a High-Resolution Melting (HRM) analysis technique coupled with qPCR, that allows the simultaneous detection of 10 different ruminant abortogenic pathogens, for investigating abortions in sheep and goats throughout Greece. A total of 264 ovine and caprine vaginal swabs were obtained the week following the abortion from aborted females and analyzed using a commercially available kit (ID Gene™ Ruminant Abortion Multiplex HRM, Innovative Diagnostics). Results indicated a high prevalence of Coxiella burnetii and Chlamydophila spp., which were detected in 48.9% and 42.4% of the vaginal swabs, respectively. Results for these most commonly detected pathogens were compared with those of a well-established commercial qPCR kit, with near-perfect agreement. Toxoplasma gondii, Salmonella spp., Brucella spp., Anaplasma phagocytophilum, Campylobacter fetus, and Neospora caninum were also identified, the two latter reported for the first time in the country in small ruminants. Mixed infections occurred in 35.6% of the animals examined. This technique allows for the simultaneous detection of many abortogenic pathogens in an accurate and cost-effective assay. Detection of uncommon or not previously reported pathogens in various cases indicates that their role in ovine and caprine abortions may be underestimated.

Mental Health in Healthcare Workers Post-COVID-19: A Latin American Review and Insights into Personalized Management Strategies.

Over the COVID-19 pandemic, the impact of enduring mental health on healthcare workers has become increasingly evident. This review focuses on post-pandemic mental health challenges faced by healthcare personnel in Latin America. This highlights the persistent burden on healthcare workers, especially women, which is exacerbated by economic disparities, inadequacies in the healthcare system, and ongoing occupational stressors. Our literature review, utilizing databases such as PubMed, Scopus, and Google Scholar, scrutinized the mental health status of healthcare professionals in the region after the pandemic's peak. The analysis indicated sustained levels of psychological distress, with frontline workers and women continuing to be affected disproportionately. These findings emphasize the urgent need for personalized interventions to effectively address the complex mental health challenges in this context. This review advocates strategic interventions, including tailored psychological support, innovative diagnostics, and technological solutions, integrated into patient-centered care models. Such approaches aim to enhance the mental resilience and overall well-being of healthcare professionals across Latin America in the post-COVID era.

Spatial Multi-omics Reveals the Role of the Wnt Modulator, Dkk2, in Palatogenesis’

Multiple genetic and environmental etiologies contribute to the pathogenesis of cleft palate, which is the most common of the inherited disorders of the craniofacial complex. Insights into the molecular mechanisms regulating osteogenic differentiation and patterning in the palate during embryogenesis are limited and needed for the development of innovative diagnostics and cures. This study used the Pax9-/- mouse model with a consistent phenotype of cleft secondary palate to investigate the role of Pax9 in the process of palatal osteogenesis. Although prior research has identified the upregulation of Wnt pathway modulators Dkk1 and Dkk2 in Pax9-/- palate mesenchyme, limitations of spatial resolution and technology restricted a more robust analysis. Here, data from single-nucleus transcriptomics and chromatin accessibility assays validated by in situ highly multiplex targeted single-cell spatial profiling technology suggest a distinct relationship between Pax9+ and osteogenic populations. Loss of Pax9 results in spatially restricted osteogenic domains bounded by Dkk2, which normally interfaces with Pax9 in the mesenchyme. Moreover, the loss of Pax9 leads to a disruption in the normal osteodifferentiaion of palatal osteogenic mesenchymal cells. These results suggest that Pax9-dependent Wnt signaling modulators influence osteogenic programming during palate formation, potentially contributing to the observed cleft palate phenotype.

Accurate and affordable detection of rifampicin and isoniazid resistance in Tuberculosis sputum specimens by multiplex PCR-multiple probes melting analysis

BackgroundEscalating cases of multidrug-resistant tuberculosis (MDR-TB) pose a major challenge to global TB control efforts, necessitating innovative diagnostics to empower decentralized detection of gene mutations associated with resistance to rifampicin (RIF) and isoniazid (INH) in Mycobacterium tuberculosis (M. tuberculosis) in resource-constrained settings.MethodsCombining multiplex fluorescent PCR and Multiple Probes Melting Analysis, we identified mutations in the rpoB, katG, ahpC and inhA genes from sputum specimens. We first constructed a reference plasmid library comprising 40 prevalent mutations in the target genes’ resistance determining regions and promoters, serving as positive controls. Our assay utilizes a four-tube asymmetric PCR method with specifically designed molecular beacon probes, enabling simultaneous detection of all 40 mutations. We evaluated the assay’s effectiveness using DNA isolated from 50 clinically confirmed M. tuberculosis sputum specimens, comparing our results with those obtained from Sanger sequencing and retrospective validation involving bacteriological culture and phenotypic drug susceptibility testing (pDST). We also included the commercial Xpert MTB/RIF assay for accuracy comparison.ResultsOur data demonstrated remarkable sensitivity in detecting resistance to RIF and INH, achieving values of 93.33% and 95.24%, respectively, with a specificity of 100%. The concordance between our assay and pDST was 98.00%. Furthermore, the accuracy of our assay was comparable to both Sanger sequencing and the Xpert assay. Importantly, our assay boasts a 4.2-h turnaround time and costs only $10 per test, making it an optimal choice for peripheral healthcare settings.ConclusionThese findings highlight our assay’s potential as a promising tool for rapidly, accurately, and affordably detecting MDR-TB.

Evaluation of the Role of Myofibroblast and Fibronectin in the Aetiopathogenesis of Cholesteatoma.

Primary acquired Cholesteatoma is a complex issue for otolaryngologists, with its development mechanisms still unclear due to the intricate anatomy of this region. It's aetiopathogenesis remains poorly understood and this aggressive clinical condition often leads to various complications. Recent research explores myofibroblast and fibronectin's potential roles in pathomechanisms of Cholesteatoma. To determine and analyze the role of myofibroblast and fibronectin in the aetiopathogenesis of Cholesteatoma. In a cross-sectional study at a tertiary care hospital, 30 patients with chronic suppurative otitis media with cholesteatoma were surgically treated, and intraoperative biopsy specimens were collected. These specimens were processed and subjected to histopathological examination, including immunohistochemical staining with Alpha-smooth muscle actin and anti-fibronectin antibody to identify myofibroblast and fibronectin presence. The data were then analyzed to investigate the aetiopathogenesis of cholesteatoma in this cohort. On immunostaining, 25 blocks (83.33%) were positively stained for Alpha-SMA (p-value-0.0007), whereas 29 blocks (96.67%) were positively stained for fibronectin (p-value < 0.0001), suggesting a statistically significant association between the presence of both myofibroblast and fibronectin with cholesteatoma perimatrix. Additionally, a statistically significant association was noted between complications and positive staining for myofibroblast (p-value - 0.0415) and positive staining for fibronectin (p-value-0.0254). Our study indicates that Cholesteatoma retraction and progression are driven by myofibroblast and fibronectin mechanisms, and also links them to disease severity. This understanding opens avenues for innovative diagnostics and treatments targeting these biomarkers.

Environmental exposures, the oral-lung axis and respiratory health: The airway microbiome goes on stage for the personalized management of human lung function.

The human respiratory system is constantly exposed to environmental stimuli, sometimes including toxicants, which can trigger dysregulated lung immune responses that lead to respiratory symptoms, impaired lung function and airway diseases. Evidence supports that the microbiome in the lungs has an indispensable role in respiratory health and disease, acting as a local gatekeeper that mediates the interaction between the environmental cues and respiratory health. Moreover, the microbiome in the lungs is intimately intertwined with the oral microbiome through the oral-lung axis. Here, we discuss the intricate three-way relationship between (i) cigarette smoking, which has strong effects on the microbial community structure of the lung; (ii) microbiome dysbiosis and disease in the oral cavity; and (iii) microbiome dysbiosis in the lung and its causal role in patients suffering chronic obstructive pulmonary disease (COPD), a leading cause of morbidity and mortality worldwide. We highlight exciting outcomes arising from recently established interactions in the airway between environmental exposures, microbiome, metabolites-functional attributes and the host, as well as how these associations have the potential to predict the respiratory health status of the host through an airway microbiome health index. For completion, we argue that incorporating (synthetic) microbial community ecology in our contemporary understanding of lung disease presents challenges and also rises novel opportunities to exploit the oral-lung axis and its microbiome towards innovative airway disease diagnostics, prognostics, patient stratification and microbiota-targeted clinical interventions in the context of current therapies.

Clinical challenges and advancements in diagnosing Staphylococcus aureus-associated musculoskeletal infections

Musculoskeletal infections (MSKI) present a significant health challenge, with a rising incidence linked to the aging population and advancements in orthopedic surgical care. Staphylococcus aureus is the most prevalent pathogen associated with orthopedic infections. The conventional culture method for identification of pathogen frequently lacks accuracy and is challenged by false-positive or false-negative results. Inflammatory markers such as the erythrocyte sedimentation rate and C-reactive protein are not site-specific or accurate, as they can be confounded by other medical conditions. Identifying the dominant pathogen and monitoring treatment response following surgical debridement and antibiotics therapy continues to pose challenges. Understanding the pathogenesis of MSKI is crucial for the development of innovative diagnostics and alternative therapeutics. S. aureus immune evasion stands out as a key component of the pathogenic mechanism, complicating clinical decisions. Other unique mechanisms such as biofilm and abscess formation, as well as osteocyte-lacuno canalicular network invasion, underscore the need for aggressive debridement and the complete removal of infected implants and bone tissues. Ongoing efforts focus on exploring and developing innovative diagnostics, such as serum immunoassays, next-generation sequencing of infected tissue, transcriptomics of peripheral blood mononuclear cells, and serum proteomics. These endeavors offer promising avenues for improved diagnostics, medical management, and innovative therapeutics for MSKI.

Prediction of Occult Hemorrhage in the Lower Body Negative Pressure Model: Initial Validation of Machine Learning Approaches.

Detection of occult hemorrhage (OH) before progression to clinically apparent changes in vital signs remains an important clinical problem in managing trauma patients. The resource-intensiveness associated with continuous clinical patient monitoring and rescue from frank shock makes accurate early detection and prediction with noninvasive measurement technology a desirable innovation. Despite significant efforts directed toward the development of innovative noninvasive diagnostics, the implementation and performance of the newest bedside technologies remain inadequate. This poor performance may reflect the limitations of univariate systems based on one sensor in one anatomic location. It is possible that when signals are measured with multiple modalities in multiple locations, the resulting multivariate anatomic and temporal patterns of measured signals may provide additional discriminative power over single technology univariate measurements. We evaluated the potential superiority of multivariate methods over univariate methods. Additionally, we utilized machine learning-based models to compare the performance of noninvasive-only to noninvasive-plus-invasive measurements in predicting the onset of OH. We applied machine learning methods to preexisting datasets derived using the lower body negative pressure human model of simulated hemorrhage. Employing multivariate measured physiological signals, we investigated the extent to which machine learning methods can effectively predict the onset of OH. In particular, we applied 2 ensemble learning methods, namely, random forest and gradient boosting. Analysis of precision, recall, and area under the receiver operating characteristic curve showed a superior performance of multivariate approach to that of the univariate ones. In addition, when using both invasive and noninvasive features, random forest classifier had a recall 95% confidence interval (CI) of 0.81 to 0.86 with a precision 95% CI of 0.65 to 0.72. Interestingly, when only noninvasive features were employed, the results worsened only slightly to a recall 95% CI of 0.80 to 0.85 and a precision 95% CI of 0.61 to 0.73. Multivariate ensemble machine learning-based approaches for the prediction of hemodynamic instability appear to hold promise for the development of effective solutions. In the lower body negative pressure multivariate hemorrhage model, predictions based only on noninvasive measurements performed comparably to those using both invasive and noninvasive measurements.

Testing of diagnostic test-systems for detection of antibodies to foot-and-mouth disease virus structural proteins with enzyme-linked immunosorbent assay for their serotype specificity

A total of 138 serum samples from pigs and cattle vaccinated against foot-and-mouth disease virus (FMDV) of one or two serotypes or infected with FMDV were used for testing of 24 enzyme-linked immunosorbent assay (ELISA) diagnostic tests-systems for detection of antibodies against FMDV structural proteins produced by 6 manufacturers (Federal Centre for Animal Health, Prionics, IZSLER, Innovative Diagnostics, BIONOTE and MEDIAN Diagnostics) for their serotype-specificity. All used test-systems detected apparent serotype-specific activity (homologous reaction) as well as cross-reacting virus-specific antibodies that was accounted for some reasons related to conservative epitopes in amino acid sequence of FMDV virion capsid VP1–VP3 polypeptides, accessibility of internal conservative epitopes of VP4 polypeptide for the animal’s immune system during virus replication or vaccine antigen (virus) destruction in the animal’s body in the process of immunity development, as well as the pilot anti-FMD vaccine composition, etc. Nevertheless, the analysis of a large data set (about 3,500 tests) showed that the homologous serotype-specific reaction in general was significantly higher and predominant, the proportion of virus-specific non-protective antibodies, including cross-reacting ones, was not significant and did not distort the results of ELISA tests of anti-FMD vaccine for its immunogenicity. Inconclusive test results require confirmation with other serological tests. Complex tests for FMDV using different diagnostic methods such as ELISA with standard and reference test-systems and/or virus neutralization test in cell culture are to be considered as the best option.

Emerging Roles and Mechanisms of RNA Modifications in Neurodegenerative Diseases and Glioma.

Despite a long history of research, neurodegenerative diseases and malignant brain tumor gliomas are both considered incurable, facing challenges in the development of treatments. Recent evidence suggests that RNA modifications, previously considered as static components of intracellular RNAs, are in fact dynamically regulated across various RNA species in cells and play a critical role in major biological processes in the nervous system. Innovations in next-generation sequencing have enabled the accurate detection of modifications on bases and sugars within various RNA molecules. These RNA modifications influence the stability and transportation of RNA, and crucially affect its translation. This review delves into existing knowledge on RNA modifications to offer a comprehensive inventory of these modifications across different RNA species. The detailed regulatory functions and roles of RNA modifications within the nervous system are discussed with a focus on neurodegenerative diseases and gliomas. This article presents a comprehensive overview of the fundamental mechanisms and emerging roles of RNA modifications in these diseases, which can facilitate the creation of innovative diagnostics and therapeutics for these conditions.

Immunoproteomics enable broad identification of new Aspergillus fumigatus antigens in severe equine asthma.

Severe equine asthma (SEA) is a common chronic disease of adult horses with characteristic recurrent airway obstruction and similarities to neutrophilic asthma in humans. As an extrinsic stimulus, hay dust exposure is a major risk factor and induces acute exacerbation in susceptible horses. However, single inducing agents of SEA have hardly been identified on a molecular basis. Aspergillus fumigatus (A. fumigatus) is a common mold species in hay and has been described as a major provoking agent of SEA. Aiming to identify disease-relevant antigens, we analyzed A. fumigatus using an immunoproteomics approach on two-dimensional immunoblots of A.fumigatus protein probed with serum from environmentally matched asthmatic and healthy horses (n=5 pairs). A. fumigatus binding serum immunoglobulins (Pan-Ig), and the isotypes IgG4/7 and IgG3/5 were quantified for each protein spot and then compared between asthmatic and healthy horses. For 21 out of 289 spots serum immunoglobulin (Ig) binding was different between the two groups for Pan-Ig or the isotypes. If differences were detected, Pan-Ig and IgG4/7 binding to the proteins were lower, while IgG3/5 binding was higher in asthmatic than healthy horse sera. Proteins were extracted from the 21 spots of interest and analyzed by liquid chromatography mass spectrometry. Eight prioritized proteins (candidate antigens) were expressed as recombinant proteins. Some of these have been previously described as major or minor A. fumigatus allergens, alongside other proteins, most with hydrolase activity. Recombinant candidate antigens were tested on 1D immunoblots to confirm their relevance as antigens by serum antibody binding. Four proteins (beta-hexosaminidase, class II aldolase/adducin domain protein, glucoamylase, peptide hydrolase B0XX53) showed different antibody binding characteristics between asthmatic and healthy horses and are likely relevant antigens in SEA. Their identification can provide the basis for innovative diagnostics, prevention, or therapeutic approaches. Additionally, a more profound understanding of SEA and its potential underlying mechanisms can be established. Elevated serum IgG3/5 antibodies correlate with T helper cell 2 responses in other equine pathologies, and the recombinant SEA antigens developed here can become instrumental in analyzing the involvement of SEA-specific T cell responses and Ig responses in future studies.