Search Results (417)

Microbiological contamination of food remains a critical global public health concern, contributing to millions of foodborne illness cases each year. Traditional diagnostic methods, particularly culture-based techniques, have been widely employed but are often limited by low sensitivity, insufficient specificity, and lengthy turnaround times. Recent advances in molecular biology, biosensor technology, and analytical chemistry have enabled the development of more rapid and precise diagnostic tools. Among these, Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) has emerged as a transformative method for microbial identification. This review provides a comprehensive overview of the current applications of MALDI-TOF MS in the diagnosis of microbiological contamination in food. The method offers rapid, accurate, and cost-effective identification of microorganisms and is increasingly used in food safety laboratories for the detection of foodborne pathogens, ensuring the safety and quality of food products. We highlight the fundamental principles of MALDI-TOF MS, discuss its methodologies, and examine its advantages, limitations, and future prospects in food microbiology and quality assurance. Full article

Circadian rhythms are intrinsic, with roughly 24 h oscillations that coordinate many physiological functions and are increasingly recognized as key determinants of human health. When these rhythms become misaligned, there is an increased risk for neurodegenerative and psychiatric disorders, metabolic syndrome, sleep disturbances, and even certain cancers. The hormones, melatonin that rises in the evening and cortisol that peaks shortly after awakening, represent crucial biochemical markers of the circadian phase. This review systematically evaluates contemporary techniques for quantifying melatonin and cortisol, comparing biological matrices (blood, saliva, urine) alongside analytical platforms. Special focus is placed on two clinically informative markers: Dim Light Melatonin Onset (DLMO) and the Cortisol Awakening Response (CAR). We compared immunoassays with liquid chromatography tandem mass spectrometry (LC MS/MS), highlighting differences in sensitivity, specificity, and laboratory feasibility. Potential confounders, including ambient light, body posture, and exact sampling times—are discussed in detail, to show the capacity of providing the most reliable results. By emphasizing the need for standardized protocols and controlled sampling conditions, this review provides essential guidance for researchers and clinicians aiming to assess the circadian biomarkers melatonin and cortisol with precision since they can be used in clinical practice as diagnostic and prognostic tools for assessing numerous pathologies. Full article

The COVID-19 pandemic and recent viral outbreaks have highlighted the need for viral diagnostics that balance accuracy with accessibility. While traditional laboratory methods remain essential, point-of-care solutions are critical for decentralized testing at the population level. However, a gap persists between academic proof-of-concept studies and clinically viable tools, with novel technologies remaining inaccessible to clinics due to cost, complexity, training, and logistical constraints. Recent advances in surface functionalization, assay simplification, multiplexing, and performance in complex media have improved the feasibility of both optical and non-optical sensing techniques. These innovations, coupled with scalable manufacturing methods such as 3D printing and streamlined hardware production, pave the way for practical deployment in real-world settings. Additionally, software-assisted data interpretation, through simplified readouts, smartphone integration, and machine learning, enables the broader use of diagnostics once limited to experts. This review explores improvements in viral diagnostic approaches, including colorimetric, optical, and electrochemical assays, showcasing their potential for democratization efforts targeting the clinic. We also examine trends such as open-source hardware, modular assay design, and standardized reporting, which collectively reduce barriers to clinical adoption and the public dissemination of information. By analyzing these interdisciplinary advances, we demonstrate how emerging technologies can mature into accessible, low-cost diagnostic tools for widespread testing. Full article

Accurate, rapid and inexpensive diagnosis of poultry respiratory pathogens remains a challenge, especially in many developing countries. Meanwhile, poultry respiratory pathogens are a major threat to poultry production worldwide, accounting for billions of dollars in economic loss to the sector. Early and accurate diagnosis of these diseases is critical for economic poultry production. Molecular diagnostic methods, including PCR-based techniques, have been developed and used to fill this gap, but unfortunately, these techniques require skilled technicians, relatively costly equipment and reagents and can only be performed in a laboratory setting. This warrants the development of other diagnostic tools, which can be used in the field even by unskilled personnel. In this review, we discussed the genesis, challenges, advances and prospects of loop-mediated isothermal amplification (LAMP) for the detection of poultry respiratory pathogens at the flock side, especially in resource-constrained countries. We highlighted the application of LAMP in routine poultry disease surveillance and early outbreak detection, underscoring its value as a transformative diagnostic tool in poultry production. The development and use of a point-of-care (POC) LAMP assay that can be used to screen for these poultry respiratory pathogens simultaneously enhance disease surveillance and diagnosis. Full article

With the global rise in antimicrobial resistance (AMR), rapid and reliable microbial diagnostics have become more critical than ever. Traditional culture-based and molecular diagnostic techniques often fall short in terms of speed, cost-efficiency, or scalability, particularly in resource-limited settings. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI–TOF MS) has emerged as a transformative tool in clinical microbiology. Its unparalleled speed and accuracy in microbial identification, along with expanding applications in AMR profiling, make it a leading candidate for next-generation diagnostic workflows. This review aims to provide a comprehensive update on recent advances in MALDI–TOF MS, focusing on its technological evolution, clinical applications, and future potential in microbial diagnostics and resistance detection. We conducted a critical synthesis of peer-reviewed literature published over the last decade, with emphasis on innovations in sample preparation, instrumentation, data interpretation, and clinical integration. Key developments in AMR detection, including growth-based assays, resistance biomarker profiling, and machine learning-driven spectral analysis, are discussed. MALDI–TOF MS is increasingly deployed not only in clinical laboratories but also in environmental surveillance, food safety, and military biodefense. Despite challenges such as database variability and limited access in low-income regions, it remains a cornerstone of modern microbial diagnostics and holds promise for future integration into global AMR surveillance systems. Full article

Candida auris (C. auris) is an emerging multidrug-resistant fungal pathogen recognized by the World Health Organization (WHO) as a critical global health threat. Its rapid transmission, high mortality rate, and frequent misidentification in clinical laboratories present significant challenges for diagnosis and infection control. This review provides a comprehensive overview of current and emerging diagnostic methods for C. auris detection, including culture-based techniques, biochemical assays, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), and molecular diagnostics such as PCR and loop-mediated isothermal amplification (LAMP). We evaluate each method’s sensitivity, specificity, turnaround time, and feasibility in clinical and surveillance settings. While culture remains the diagnostic gold standard, it is limited by slow turnaround and phenotypic overlap with related species. Updated biochemical platforms and MALDI-TOF MS with expanded databases have improved identification accuracy. Molecular assays offer rapid, culture-independent detection. Antifungal susceptibility testing (AFST), primarily using broth microdilution, is essential for guiding treatment, although standardized breakpoints remain lacking. This review proposes an integrated diagnostic workflow and discusses key innovations and gaps in current practice. Our findings aim to support clinicians, microbiologists, and public health professionals in improving early detection, containment, and management of C. auris infections. Full article

This study utilizes EnMAP hyperspectral satellite data to map the mineralogical footprints of hydrocarbon microseepage systems induced in the Upper-Red Formation (URF), a clastic Upper Miocene sedimentary sequence in the Qom region (Iran) affected by petroleum leakage from the underlying Alborz reservoir. The Level 2A surface reflectance product of EnMAP was processed using spectral matching and polynomial fitting techniques to characterize diagnostic absorption features associated with microseepage-induced alteration minerals. The identified mineralogical changes include partial to complete bleaching of hematite from redbeds, the formation of secondary goethite, and the development of montmorillonite, calcite, and Fe²⁺-bearing chlorite across the affected zones. Compared to previous studies conducted using ASTER and Sentinel-2 multispectral data, EnMAP demonstrated superior performance in identifying mineralogy and delineating petroleum-affected zones, with results aligning closely with field observations and laboratory spectroscopy. This study highlights the advantages of EnMAP hyperspectral data for mapping diagenetic mineralogical alterations induced in sedimentary strata, facilitating remote sensing-based detection of microseepage, and advancing petroleum exploration in exposed terrains. Full article

Background/Objectives: Optimization algorithms are acknowledged to be critical in various fields and dynamical systems since they provide facilitation in identifying and retrieving the most possible solutions concerning complex problems besides improving efficiency, cutting down on costs, and boosting performance. Metaheuristic optimization algorithms, on the other hand, are inspired by natural phenomena, providing significant benefits related to the applicable solutions for complex optimization problems. Considering that complex optimization problems emerge across various disciplines, their successful applications are possible to be observed in tasks of classification and feature selection tasks, including diagnostic processes of certain health problems based on bio-inspiration. Sepsis continues to pose a significant threat to patient survival, particularly among individuals admitted to intensive care units from emergency departments. Traditional scoring systems, including qSOFA, SIRS, and NEWS, often fall short of delivering the precision necessary for timely and effective clinical decision-making. Methods: In this study, we introduce a novel, interpretable machine learning framework designed to predict in-hospital mortality in sepsis patients upon intensive care unit admission. Utilizing a retrospective dataset from a tertiary university hospital encompassing patient records from January 2019 to June 2024, we extracted comprehensive clinical and laboratory features. To address class imbalance and missing data, we employed the Synthetic Minority Oversampling Technique and systematic imputation methods, respectively. Our hybrid modeling approach integrates ensemble-based ML algorithms with deep learning architectures, optimized through the Red Piranha Optimization algorithm for feature selection and hyperparameter tuning. The proposed model was validated through internal cross-validation and external testing on the MIMIC-III dataset as well. Results: The proposed model demonstrates superior predictive performance over conventional scoring systems, achieving an area under the receiver operating characteristic curve of 0.96, a Brier score of 0.118, and a recall of 81. Conclusions: These results underscore the potential of AI-driven tools to enhance clinical decision-making processes in sepsis management, enabling early interventions and potentially reducing mortality rates. Full article

Pancreatic ductal adenocarcinoma (PDAC) presents significant challenges in diagnosis, prevention, and treatment. Predictive biomarkers offer the potential to revolutionize clinical management, particularly in the preoperative setting, but their implementation requires careful consideration of ethical implications. This scoping review analyzes the ethical landscape of using immunohistochemistry (IHC) for molecular subtyping in PDAC, focusing on its utility, accessibility, and potential impact on patient care. We conducted a systematic literature search in the PubMed, Scopus and Google Scholar databases (2015–2025) using COVIDENCE, which identified 130 references. Of these, 79 were reviewed in a full-text format, and 9 ultimately met the inclusion criteria for our analysis. IHC offers several advantages as a companion diagnostic tool. It is relatively inexpensive, widely available in most pathology laboratories, and can be readily integrated into existing clinical workflows. This contrasts with more complex molecular subtyping methods, such as gene expression profiling, which can be costly, require specialized equipment and expertise, and may not be readily accessible in all clinical settings. Furthermore, accurate analysis of gene expression requires the localized targeting of individual cells; therefore, digesting the sample for bulk analysis would be less informative than using spatial localization techniques such as IHC. Because biomarker regulation can occur at the level of transcription or translation, protein-level assessment via IHC is often more accurate than mRNA analysis. Standardized IHC protocols for biomarker assessment are therefore essential for translating the molecular subtyping of PDAC into clinically actionable treatment strategies, especially for aggressive subtypes like basal-like tumors. This readily deployable IHC-based approach can optimize therapy selection, maximizing patient benefits and minimizing exposure to ineffective and potentially toxic treatments. This review critically analyzes the ethical dimensions of this method, grounded in the principles of autonomy, beneficence, non-maleficence, and justice. The review urges the medical community to fully utilize the potential of IHC-driven molecular subtyping to improve outcomes in PDAC, while ensuring equitable and responsible access to the benefits of precision oncology for all patients. Full article

Colorimetric-based biosensors are practical detection devices that can detect the presence and concentration of biomarkers through simple color changes. Conventional laboratory-based tests are highly sensitive but require long processing times and expensive equipment, which makes them difficult to apply for on-site diagnostics. In contrast, the colorimetric method offers advantages for point-of-care testing and real-time monitoring due to its flexibility, simple operation, rapid results, and versatility across many applications. In order to enhance the color change reactions in colorimetric techniques, functional nanomaterials are often integrated due to their desirable intrinsic properties. In this review, the working principles of nanomaterial-based detection strategies in colorimetric systems are introduced. In addition, current signal amplification methods for colorimetric biosensors are comprehensively outlined and evaluated. Finally, the latest trends in artificial intelligence (AI) and machine learning integration into colorimetric-based biosensors, including their potential for technological advancements in the near future, are discussed. Future research is expected to develop highly sensitive and multifunctional colorimetric methods, which will serve as powerful alternatives for point-of-care testing and self-testing. Full article

Immunoglobulin G4-related disease (IgG4-RD) is a systemic fibroinflammatory condition marked by tumefactive lesions, IgG4+ plasma cell-rich infiltrates, storiform fibrosis, and obliterative phlebitis. Its multisystem involvement and overlap with malignancies, infections, and immune disorders complicate diagnosis despite recent classification advances. This study summarizes diagnostic challenges, highlights the role of histopathology as per the 2019 classification criteria established by the American College of Rheumatology and the European League Against Rheumatism (ACR/EULAR), and explores emerging tools to improve diagnostic accuracy. ACR/EULAR classification emphasizes three cardinal histopathological features (storiform fibrosis, obliterative phlebitis, or dense lymphoplasmacytic infiltrates) combined with an IgG4+/IgG+ plasma cell ratio >40% and organ-specific IgG4+ thresholds. While serum IgG4 levels are often elevated, their poor specificity necessitates confirmatory biopsy. Diagnostic limitations include sampling variability due to patchy fibrosis, interobserver discrepancies in immunohistochemical interpretation, and differentiation from mimics like lymphoma. Emerging solutions incorporate novel biomarkers (plasmablasts, anti-annexin A11) and advanced techniques (flow cytometry, digital pathology). Future research directions should focus on AI-assisted pattern recognition, multi-omics profiling, and organ-specific criteria refinement. While histopathology remains the diagnostic cornerstone, a multidisciplinary approach integrating clinical, radiological, and laboratory data is vital. Innovations in biomarkers promise improved diagnostic accuracy and personalized care, balancing novel advancements with foundational pathological evaluation. Full article

Background: FLT3 mutation testing is a key ancillary molecular assay for diagnosing and managing patients with acute myeloid leukemia (AML), including assessing the utility of FLT3 inhibitors during induction chemotherapy. FLT3 PCR utilizing fluorescently labeled primers and capillary electrophoresis readout is the most used technique for the rapid detection of FLT3 internal tandem duplications (ITDs) (including very small ITDs) and tyrosine kinase domain (TKD) mutations. However, capillary electrophoresis (CE) is a relatively lengthy and technically demanding result readout mode that could potentially be replaced by faster alternatives. Methods: Here, we describe the validation of a modified FLT3 PCR assay that uses the Agilent 4200 TapeStation platform for result readouts. This platform generates quantifiable electropherograms and gel images in under two minutes and at a low cost. We validated its ability to detect FLT3-ITD and -TKD mutations using 22 and 18 previously tested patient samples, respectively. Results: The TapeStation 4200 instrument is 100% sensitive, specific, and highly reproducible for post-PCR fragment analysis in detecting FLT3-ITD (greater than 15 bp in size) and TKD mutations in AML patients. Its results are nearly 100% concordant with those obtained from our previously validated NGS and PAGE methods. However, the limitation of this readout mode is its inability to reliably detect FLT3-ITDs smaller than 15 bp in size. Conclusions: Given the widespread use of TapeStation instruments in molecular diagnostics laboratories as part of next-generation sequencing (NGS) workflows, this modified assay is well-suited as a companion test for rapid NGS platforms to detect larger FLT3-ITDs, which are NGS often miscalledor under-called by the NGS bioinformatics algorithms. However, it is not suitable for use as a standalone assay, as it is unable to reliably detect very short FLT3-ITDs. Full article

Background: Pathology is essential for cancer diagnosis, bridging clinical and surgical fields, and requires adequate infrastructure, technology, and skilled staff to meet standards of care. In Romania, healthcare underfunding limits pathology laboratories’ capacity to provide timely and accurate diagnoses, leading to delays that could negatively impact treatment and patient outcomes. Our study aimed to assess the status of publicly funded pathology laboratories in Romania and identify key areas for improvement. Methods: We analyzed public hospitals in Romania, excluding specialized and non-general care institutions, to evaluate pathology laboratories. A 10-item survey was distributed over 12 months via email, phone, administrative offices, and professional networks to pathologists working in these laboratories, regardless of their hierarchical position. A total of 154 pathology services were represented. The questionnaire assessed technical capabilities, diagnostic techniques, automation, staffing, infrastructure, and satisfaction with funding and resources. Responses were gathered with both predefined and open-text fields to capture comprehensive insights. Results: The findings revealed that many pathology laboratories faced significant challenges, including a lack of automation, limited integration of modern technologies, and barriers to digitalization. Despite these issues, pathologists reported higher-than-expected levels of satisfaction with their laboratories. Conclusions: A comprehensive understanding of existing practices is necessary to drive the modernization of pathology services, establish national standards, and improve collaboration both within and across specialties. Without such foundational insight, efforts to enhance the integration and effectiveness of pathology services are likely to remain constrained. Full article

Viroids are subviral plant pathogens composed of non-coding, small, circular, single-stranded RNAs that parasitize the transcriptional machinery of their host cells. For many years, viroid-induced diseases were mistakenly attributed to viruses due to similarities in symptoms and pathogenic behavior. However, advances in molecular biology over the past sixty years have clearly distinguished viroids from viruses and other pathogens in terms of genetic composition, structural features, and replication mechanisms. Citrus trees in the Mediterranean region appear to have been associated with viroid infections since ancient times. Nevertheless, the use of propagation material harboring asymptomatic viroid infections allowed for continued production of high-quality fruit. This delicate equilibrium was disrupted with the spread of novel citrus pathogens, prompting the adoption of new horticultural practices that emphasized the elimination of citrus pathogens—including viroids—from propagation material. Concurrently, a contrasting approach emerged in the late 1960s: the experimental use of “graft-transmissible dwarfing agents”—later identified as citrus viroids—to control citrus tree size. Our lab initiated work on citrus viroid-induced dwarfing in the early 1980s and continued this line of research for nearly two decades. Eventually, we concluded that it was impractical to simultaneously promote rigorous sanitation protocols while advocating for the use of viroids to induce dwarfing. This review summarizes key biological and molecular aspects of citrus and avocado viroids investigated in our laboratory, including the development of diagnostic techniques and the exploration of viroid-induced dwarfing as a horticultural tool. Full article

Foot-and-mouth disease (FMD) is a devastating infectious viral disease of cloven-hoofed animals. Differentiating FMD from other vesicular diseases is difficult based on only clinical symptoms, requiring an appropriate laboratory diagnostic test. The double-antibody sandwich (DAS)-ELISA is a reliable diagnostic technique for antigen detection and serotyping of FMDV. However, classical DAS-ELISAs use polyclonal antibodies (pAbs), which are inconsistent in yields and limited in large-scale applications compared to hybridoma cell-secreted laboratory-made monoclonal antibodies (mAbs). Therefore, this study aimed to develop simplified and sensitive FMD serotype-specific DAS-ELISAs using HRP-conjugated mAbs and a TMB substrate. Six FMDV serotype-specific mAb-DAS-ELISAs were developed. All assays were optimized using BEI-inactivated FMD antigens. Real-time reverse-transcriptase PCR (RRT-PCR) was also used to verify the detection efficiency of all assays. Known negative and positive 10% tissue suspensions of different animal origins were examined to calculate the diagnostic specificity (DSp) and sensitivity (DSe). Serotype-specific mAb-DAS-ELISAs demonstrated 100%, 97%, 97%, 99%, 99%, and 94% DSp and 100%, 95%, 90%, 95%, 100%, and 100% DSe for serotypes O, A, Asia-1, SAT-1, SAT-2, and SAT-3, respectively. The detection efficiency of mAb-DAS-ELISAs was better than that of classical DAS-ELISAs. Also, all assays demonstrated minimal cross-reactivity and optimal reproducibility. Therefore, the mAb-DAS-ELISAs developed in this study could be useful for detecting and serotyping FMDV and ultimately replacing the classical DAS-ELISA. Full article