Rapid Identification Of Pathogens Research Articles

Clinical Performance of the LiquidArray® Gastrointestinal VER 1.0 Assay in Patients with Suspected Gastroenteritis

Background/Objectives: Rapid and accurate pathogen identification is essential for the proper management of patients with infectious gastroenteritis, as well as for a better control of disease outbreaks. This observational, non-interventional, single-site study evaluated the diagnostic accuracy of LiquidArray® Gastrointestinal VER 1.0, a multiplex PCR syndromic panel capable of detecting up to 26 clinically relevant enteropathogens. Methods: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and likelihood ratio (LR) were evaluated using stool samples from 1512 patients with suspected gastroenteritis and were compared to seven competitor assays. Results: LiquidArray® Gastrointestinal VER 1.0 showed a very low invalid rate (0.5% at initial testing, down to 0% after repeat) and high sensitivity (>90% for most detected targets) and specificity (>99% for all detected targets). Accordingly, the PPV and NPV were high (>90% for most targets and >99% for all targets, respectively). The analytical performance of LiquidArray® Gastrointestinal VER 1.0 was also excellent as to co-amplification capability, cross-reactivity and assay precision. Conclusions: This study demonstrates the excellent clinical performance of LiquidArray® Gastrointestinal VER 1.0 and its suitability for implementation in clinical routine for the rapid and accurate diagnosis of infectious gastroenteritis.

Clinical Utility of a Multiplex PCR Panel (BioFire Joint Infection®) in the Adjustment of Empiric Antimicrobial Therapy: Experience in Pediatric Osteoarticular Infections.

This study aims to evaluate the impact of the PCR multiplex panel (BioFire JI®) on the diagnosis and management of pediatric osteoarticular infections. This retrospective study analyzed data from pediatric patients diagnosed with osteoarticular infections between January 2023 and April 2024. The effectiveness of the PCR multiplex panel in identifying pathogens was compared with traditional culture methods. In total, 50 patients were identified (66.6% male, 74% under 3 years of age). They were diagnosed as follows: septic arthritis in 46%, osteomyelitis in 26%, and septic osteoarthritis in 22%. An identifiable agent was isolated by conventional culture in 22 cases (44%). Kingella kingae was the predominant pathogen identified, accounting for 50% of cases (11/22), followed by Staphylococcus aureus (9/22). The BioFire JI® Panel PCR demonstrated a sensitivity of 93%, with a specificity of 63% when evaluated against synovial fluid culture as the reference standard. The panel identified seven additional pathogens not detected by conventional culture methods: 2/9 MSSA (22%), 1/1 S. pyogenes (100%), and 4/11 K. kingae (37%), increasing the yield by 14%. The rapid identification of pathogens facilitated timely and targeted therapeutic interventions. The PCR multiplex panel (BioFire JI®) improved the diagnosis of pediatric osteoarticular infections.

Accelerated Detection of Foodborne Pathogens and Toxins: Techniques and Applications – A Review

Pathogens associated with food and their corresponding toxins, including mycotoxins, pose a sig¬nificant threat to public health, leading to various health issues worldwide, particularly affecting infants, young children, and the elderly. The rise in foodborne illnesses highlights the crucial importance of food safety in ensuring a reliable food supply and promoting health. Timely detection of foodborne pathogens, toxins, and mycotoxins is essential for reducing the incidence of foodborne diseases. This review aims to provide comprehensive insights into the methodology for rapid detection, detailing the principles, appli¬cations, advantages, and limitations to enhance current knowledge. Conventional culture-based methods for foodborne pathogen identification are selective and are hindered by significant time demands, labor intensity, challenges from complex sample preparation, delayed results, and the need for specialized per¬sonnel. In contrast, the new emerging detection techniques such as immunological, nucleic acid-based, and biosensor-based methods offer time efficiency, reduced labor, improved accuracy, sensitivity, specificity, and reliability, and are user-friendly. Recently, numerous novel techniques have been developed for the rapid identification of foodborne pathogens, toxins, and mycotoxins, transforming food safety practices. Providing rapid and accurate results is crucial for controlling and managing foodborne disease outbreaks while ensuring food safety. As the global food supply chain becomes more complex, advancing rapid and automated detection methods remains essential for safeguarding food safety and quality, as well as enhanc¬ing public health.

Spore PCR and qPCR Methods for Rapid Detection of Five Colletotrichum Species Responsible for Pepper Anthracnose in Korea

Pepper anthracnose, caused by <i>Colletotrichum</i> spp., leads to a decrease in the quantity of pepper fruit production. Molecular diagnosis is crucial for rapid identification of pathogens and determination of fungicide resistance. However, the traditional process of isolating the pathogen, extracting genomic DNA, and analyzing the gene sequence is time-consuming, which delays rapid diagnosis. In this study, we introduced a method using conidia of <i>Colletotrichum</i> spp. instead of genomic DNA, eliminating the need for DNA extraction or special processing for diagnosis. To elucidate this method, sensitivity was assessed through polymerase chain reaction (PCR) and quantitative real-time PCR (qPCR) tests using internal transcribed spacer-based primer pairs. Both PCR and qPCR tests showed that detection is feasible with just one conidia, with over 1,000 conidia yielding results comparable to approximately 1 pg of genomic DNA. For amplifying the cytochrome b gene for quinone-outside inhibitor fungicide susceptibility testing, detection from a single conidium is achievable, but a stable PCR product is obtained by increasing the number of cycles to 35. Additionally, the addition of 10% grinding fresh chili pepper paste to V8-Juicea gar medium, which is known for inducing conidia rapidly from the isolates, resulted in 3.2 to 6.0 times more conidia compared to the commonly used potato dextrose agar medium, enhancing the potential for swift testing. Taken together, this study presents a direct utilization of pepper anthracnose conidia through PCR or qPCR, offering a valuable technique for amplifying target genes, such as the minimum conidial amount and barcode genes, for molecular identification of anthracnose disease in pepper through PCR and qPCR analysis.

RAPiD: a rapid and accurate plant pathogen identification pipeline for on-site nanopore sequencing.

Nanopore sequencing technology has enabled the rapid, on-site taxonomic identification of samples from anything and anywhere. However, sequencing errors, inadequate databases, as well as the need for bioinformatic expertise and powerful computing resources, have hampered the widespread use of the technology for pathogen identification in the agricultural sector. Here we present RAPiD, a lightweight and accurate real-time taxonomic profiling pipeline. Compared to other metagenomic profilers, RAPiD had a higher classification precision achieved through the use of a curated, non-redundant database of common agricultural pathogens and extensive quality filtering of alignments. On a fungal, bacterial and mixed mock community RAPiD was the only pipeline to detect all members of the communities. We also present a protocol for in-field sample processing enabling pathogen identification from plant sample to sequence within 3 h using low-cost equipment. With sequencing costs continuing to decrease and more high-quality reference genomes becoming available, nanopore sequencing provides a viable method for rapid and accurate pathogen identification in the field. A web implementation of the RAPiD pipeline for real-time analysis is available at https://agrifuture.senckenberg.de.

Clinical evaluation of a highly multiplexed CRISPR-based diagnostic assay for diagnosing lower respiratory tract infection: a prospective cohort study

Objective Accurate and rapid identification of causative pathogens is essential to guide the clinical management of lower respiratory tract infections (LRTIs). Here we conducted a single-centre prospective study in 284 patients suspected of lower respiratory tract infections to evaluate the utility of a nucleic acid test based on highly multiplexed polymerase chain reaction (PCR) and CRISPR-Cas12a. Methods We determined the analytical and diagnostic performance of the CRISPR assay using a combination of reference standards, including conventional microbiological tests (CMTs), metagenomic Next-Generation Sequencing (mNGS), and clinical adjudication by a panel of experts on infectious diseases and microbiology. Results The CRISPR assay showed a higher detection rate (63.0%) than conventional microbiological tests (38.4%) and was lower than metagenomic Next-Generation Sequencing (72.9%). In detecting polymicrobial infections, the positivity rate of the CRISPR assay (19.4%) was higher than conventional microbiological tests (3.5%) and lower than metagenomic Next-Generation Sequencing (28.9%). The overall diagnostic sensitivity of the CRISPR assay (67.8%) was higher than conventional microbiological tests (41.8%), and lower than metagenomic Next-Generation Sequencing (93.2%). Conclusions Considering the low cost, ease of operation, short turnaround time, and broad range of pathogens detected in a single test, the CRISPR assay has the potential to be implemented as a screening tool for the aetiological diagnosis of lower respiratory tract infections patients, especially in cases where atypical bacteria or coinfections are suspected.

Deep Learning-enhanced Hyperspectral Imaging for the Rapid Identification and Classification of Foodborne Pathogens

Background: Bacterial cellulose (BC) is a versatile biomaterial with numerous applications, and the identification of bacterial strains that produce it is of great importance. This study explores the effectiveness of a Stacked Autoencoder (SAE)-based deep learning method for the classification of bacterial cellulose-producing bacteria. Objective: The primary objective of this research is to assess the potential of SAE-based classification models in accurately identifying and classifying bacterial cellulose-producing bacteria, with a particular focus on strain GZ-01. Methods: Strain GZ-01 was isolated and subjected to a comprehensive characterization process, including morphological observations, physiological and biochemical analysis, and 16S rDNA sequencing. These methods were employed to determine the identity of strain GZ-01, ultimately recognized as Acetobacter Okinawa. The study compares the performance of SAE-based classification models to traditional methods like Principal Component Analysis (PCA). Results: The SAE-based classifier exhibits outstanding performance, achieving an impressive accuracy of 94.9% in the recognition and classification of bacterial cellulose-producing bacteria. This approach surpasses the efficacy of conventional PCA in handling the complexities of this classification task. Conclusion: The findings from this research highlight the immense potential of utilizing nanotechnology- driven data analysis methods, such as Stacked Autoencoders, in the realm of bacterial cellulose research. These advanced techniques offer a promising avenue for enhancing the efficiency and accuracy of bacterial cellulose-producing bacteria classification, which has significant implications for various applications in biotechnology and materials science.

Field-Deployable Colorimetric Array for On-Site Diagnosis of Urinary Tract Infection and Identification of Causative Pathogens.

Urinary tract infection (UTI) is a common and prevalent disease caused by a spectrum of pathogens. Lack of access to rapid, portable, and high-quality diagnostics in resource-limited settings aggravates the improper treatment of UTIs, which is also a major driver of antibiotic misuse worldwide. Here, we describe a custom-made portable colorimetric array (PoCA) for reading out polymerase chain reaction (PCR) amplicons, the rationale of which is to transfer the previously developed dsDNA-based photosensitization colorimetric assay (solution) onto paper discs for detection. By integrating mini-LED irradiation and paper discs, the PoCA can read out 96 PCR tests in one pot, thus allowing diagnosis and identification of 12 prevailing UTI pathogens in less than 2 h, coupled with a portable thermal cycler for PCR. After analyzing 200 clinical urine samples, the pathogen profiling accuracy of the PoCA was demonstrated to be higher than the standard urine culture (confirmed with metagenomic next-generation sequencing). The PoCA platform could be used in primary care for rapid UTI diagnosis and pathogen identification.

Advances in plant pathogen detection: integrating recombinase polymerase amplification with CRISPR/Cas systems.

Plant pathogens are causing substantial economic losses and thus became a significant threat to global agriculture. Effective and timely detection methods are prerequisite for combating the damages caused by the plant pathogens. In the realm of plant pathogen detection, the isothermal amplification techniques, e.g., recombinase polymerase amplification (RPA) and loop-mediated isothermal amplification (LAMP), have emerged as a fast, precise, and most sensitive alternative to conventional PCR but they often comprise high rates of non-specific amplification and operational complexity. In recent advancements, clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated nuclease Cas systems, particularly Cas12, have emerged as powerful tools for highly sensitive, specific, and rapid pathogen detection. Exploiting the collateral activities of Cas12, which selectively cleaves single-stranded DNA (ssDNA), novel detection platforms have been developed. The mechanism employs the formation of a triple complex molecule comprising guide RNA, Cas12 enzyme, and the substrate target nucleotide sequence. Upon recognition of the target, Cas12 indiscriminately cleaves the DNA strand, leading to the release of fluorescence from the cleaved ssDNA reporter. Integration of isothermal amplification methods with CRISPR/Cas12 enables one-step detection assays, facilitating rapid pathogen identification within 30min at a single temperature. This integrated RPA-CRISPR/Cas12a approach eliminates the need for RNA extraction and cDNA conversion, allowing direct use of crude plant sap as a template. With an affordable fluorescence visualization system, this portable method achieves 100-fold greater sensitivity than conventional techniques. This review summarizes recent advances in RPA-CRISPR/Cas12a for detecting plant pathogens, covering primer design, field-level portability, and enhanced sensitivity.

An emerging assay for rapid diagnosis of live Salmonella Typhimurium by exploiting aqueous/liquid crystal interface

The rapid and accurate identification of live pathogens with high proliferative ability is in great demand to mitigate foodborne infection outbreaks. Herein, we have developed an ultrasensitive image-based aptasensing array to directly detect live Salmonella typhimurium (S.T) cells. This method relies on the long-range orientation of surfactant-decorated liquid crystals (LCs) and the superiority of aptamers (aptST). The self-assembling of hydrophobic surfactant tails leads to a perpendicular/vertical ordered film at the aqueous/LC interface and signal-off response. The addition of aptST perturbed LCs’ ordering into a planar/tilted state at the aqueous phase due to electrostatic interactions between the surfactant with the aptST, and a signal-on response. Following the conformational switch of aptST in the presence of live S. typhimurium, a relative reversing signal-off response was observed upon the target concentration. This aptasensor could promptly confirm the presence of S. typhimurium without intricate DNA-extraction or pre-enrichment stats over a linear range of 1–1.1 × 106 CFU/mL and a detection limit of 1.2 CFU/mL within ∼30 min. These results were successfully validated using molecular and culture-based methods in spiked-milk samples, with a 92.61–104.61 % recovery value. Meanwhile, the flexibility of this portable sensing platform allows for its development and adoption for the precise detection of various pathogens in food and the environment.

Rapid Detection of Uropathogens Using an Integrated Multiplex Digital Nucleic Acid Detection Assay Powered by a Digital-to-Droplet Microfluidic Device.

The digital nucleic acid detection assay features the capability of absolute quantitation without the need for calibration, thereby facilitating the rapid identification of pathogens. Although several integrated digital nucleic acid detection techniques have been developed, there are still constraints in terms of automation and analysis throughput. To tackle these challenges, this study presents a digital-to-droplet microfluidic device comprising a digital microfluidics (DMF) module at the bottom and a droplet microfluidics module at the top. Following sample introduction, the extraction of nucleic acid and the dispensation of nucleic acid elution for mixing with the multiple amplification reagents are carried out in the DMF module. Subsequently, the reaction droplets are transported to the sample inlet of the droplet microfluidic module via a liquid outlet, and then droplet generation in four parallel units within the droplet microfluidics module is actuated by negative pressure generated by a syringe vacuum. The digital-to-droplet microfluidic device was employed to execute an integrated multiplex digital droplet nucleic acid detection assay (imDDNA) incorporating loop-mediated isothermal amplification (LAMP). This assay was specifically designed to enable simultaneous detection of four uropathogens, namely, Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Enterococcus faecalis. The entire process of the imDDNA is completed within 75 min, with a detection range spanning 5 orders of magnitude (9.43 × 10-2.86 × 104 copies μL-1). The imDDNA was employed for the detection of batched clinical specimens, showing a consistency of 91.1% when compared with that of the conventional method. The imDDNA exhibits simplicity in operation and accuracy in quantification, thus offering potential advantages in achieving rapid pathogen detection.

Innovative approaches to microbial identification enhancing accuracy and speed in infectious disease diagnostics

The rapid and accurate identification of microbial pathogens is crucial for effective management of infectious diseases. Traditional methods, though reliable, are often time-consuming. Recent advancements in molecular diagnostics, mass spectrometry, and next-generation sequencing (NGS) have revolutionized the field by enhancing both the speed and accuracy of microbial identification. Polymerase chain reaction (PCR) and its derivatives, such as real-time PCR, enable rapid amplification of genetic material, significantly reducing diagnostic times. Techniques like nucleic acid sequence-based amplification (NASBA) and loop-mediated isothermal amplification (LAMP) further extend these capabilities to resource-limited settings by operating at constant temperatures. Mass spectrometry, particularly matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF), provides rapid and accurate microbial identification by analyzing protein profiles. This method has high throughput, is cost-effective, and offers the ability to detect antimicrobial resistance, significantly impacting clinical decision-making and patient management. NGS technologies offer comprehensive pathogen detection by sequencing entire microbial genomes. This approach is invaluable in diagnosing complex infections, tracking outbreaks, and identifying antibiotic resistance genes, though its high cost and complexity limit widespread use. The integration of these innovative technologies into clinical practice enhances the ability to diagnose and manage infectious diseases effectively. Molecular diagnostics, mass spectrometry, and NGS each bring unique strengths, from rapid and precise pathogen detection to comprehensive genetic analysis and resistance profiling. These advancements contribute to improved patient outcomes and more effective public health strategies. The continued development and implementation of these technologies are essential to address the evolving challenges in microbial diagnostics, paving the way for more precise and personalized approaches in infectious disease management.

Rapid identification of bloodstream infection pathogens and drug resistance using Raman spectroscopy enhanced by convolutional neural networks.

Bloodstream infections (BSIs) are a critical medical concern, characterized by elevated morbidity, mortality, extended hospital stays, substantial healthcare costs, and diagnostic challenges. The clinical outcomes for patients with BSI can be markedly improved through the prompt identification of the causative pathogens and their susceptibility to antibiotics and antimicrobial agents. Traditional BSI diagnosis via blood culture is often hindered by its lengthy incubation period and its limitations in detecting pathogenic bacteria and their resistance profiles. Surface-enhanced Raman scattering (SERS) has recently gained prominence as a rapid and effective technique for identifying pathogenic bacteria and assessing drug resistance. This method offers molecular fingerprinting with benefits such as rapidity, sensitivity, and non-destructiveness. The objective of this study was to integrate deep learning (DL) with SERS for the rapid identification of common pathogens and their resistance to drugs in BSIs. To assess the feasibility of combining DL with SERS for direct detection, erythrocyte lysis and differential centrifugation were employed to isolate bacteria from blood samples with positive blood cultures. A total of 12,046 and 11,968 SERS spectra were collected from the two methods using Raman spectroscopy and subsequently analyzed using DL algorithms. The findings reveal that convolutional neural networks (CNNs) exhibit considerable potential in identifying prevalent pathogens and their drug-resistant strains. The differential centrifugation technique outperformed erythrocyte lysis in bacterial isolation from blood, achieving a detection accuracy of 98.68% for pathogenic bacteria and an impressive 99.85% accuracy in identifying carbapenem-resistant Klebsiella pneumoniae. In summary, this research successfully developed an innovative approach by combining DL with SERS for the swift identification of pathogenic bacteria and their drug resistance in BSIs. This novel method holds the promise of significantly improving patient prognoses and optimizing healthcare efficiency. Its potential impact could be profound, potentially transforming the diagnostic and therapeutic landscape of BSIs.

Portable loop-mediated isothermal amplification device with spectrometric detection for rapid pathogen identification

With the rise in extreme weather due to global warming, coupled with globalization facilitating the spread of infectious diseases, there's a pressing need for portable testing platforms offering simplicity, low cost, and remote transmission, particularly beneficial in resource-limited and non-urban areas. We have developed a portable device using loop-mediated isothermal amplification (LAMP) with spectrometric detection to identify Salmonella Typhimurium DNA. The device utilizes the LinkIt 7697 microcontroller and a microspectrometer to capture and transmit spectral signals in real-time, allowing for improved monitoring and analysis of the reaction progress. We built a hand-held box containing a microspectrometer, thermoelectric cooler, ultraviolet LED, disposable reaction tube, and homemade thermal module, all powered by rechargeable batteries. Additionally, we conducted thorough experiments to ensure temperature accuracy within 1 °C under thermal control, developed a heating module with a LinkIt 7697 IoT development board to heat the DNA mixture to the reaction temperature within 3 min, and integrated foam insulation and a 3D-printed frame to enhance the device's thermal stability. We successfully demonstrated the amplification of Salmonella Typhimurium DNA with an impressive sensitivity of 2.83 × 10−4 ng/μL. A remote webpage interface allows for monitoring the temperature and fluorescence during the LAMP process, improving usability. This portable LAMP device with real-time detection offers a cost-effective solution for detecting Salmonella Typhimurium in food products. Its unique design and capabilities make it a promising tool for ensuring food safety.

SEDphone: Spatial encoding of centrifugal microfluidic disc integrated smartphone-controlled platform via RT/LAMP-CRISPR/Cas12a system for influenza virus subtypes detection

Accurate and rapid identification of multiple pathogens simultaneously is paramount for global public health, including the detection of different influenza virus subtypes. Recently, the development of CRISPR/Cas technology and its combination with isothermal amplification technology has presented promising opportunities for exploiting point-of-care, highly sensitive and specific detection methods. However, there have been several challenges in terms of multiplex detection and compatibility with isothermal amplification technology, especially loop-mediated isothermal amplification (LAMP). In this study, we introduced a multiplex detection platform, named spatial encoding of centrifugal microfluidic disc integrated smartphone-controlled platform (SEDphone), which was based on CRISPR/Cas12a and RT/LAMP technology. Five distinct influenza virus subtypes could be simultaneously identified: influenza A virus H1N1, H3N2, H5N1, H7N9, and influenza B virus. The assay limit of detection reached 10 copies/μL within a 45-minute timeframe. Furthermore, the clinical efficacy was validated by detecting 22 positive and 16 negative clinical samples. We anticipate that this simple yet efficient platform holds significant potential as a versatile multiplex pathogen detection in both research and diagnostic settings.

Raman-Activated Cell Ejection for Validating the Reliability of the Raman Fingerprint Database of Foodborne Pathogens

Raman spectroscopy for rapid identification of foodborne pathogens based on phenotype has attracted increasing attention, and the reliability of the Raman fingerprint database through genotypic determination is crucial. In the research, the classification model of four foodborne pathogens was established based on t-distributed stochastic neighbor embedding (t-SNE) and support vector machine (SVM); the recognition accuracy was 97.04%. The target bacteria named by the model were ejected through Raman-activated cell ejection (RACE), and then single-cell genomic DNA was amplified for species analysis. The accuracy of correct matches between the predicted phenotype and the actual genotype of the target cells was at least 83.3%. Furthermore, all anticipant sequencing results brought into correspondence with the species were predicted through the model. In sum, the Raman fingerprint database based on Raman spectroscopy combined with machine learning was reliable and promising in the field of rapid detection of foodborne pathogens.

Clinical evaluation of droplet digital PCR in the early identification of suspected sepsis patients in the emergency department: a prospective observational study.

Rapid and accurate diagnosis of the causative agents is essential for clinical management of bloodstream infections (BSIs) that might induce sepsis/septic shock. A considerable number of suspected sepsis patients initially enter the health-care system through an emergency department (ED), hence it is vital to establish an early strategy to recognize sepsis and initiate prompt care in ED. This study aimed to evaluate the diagnostic performance and clinical value of droplet digital PCR (ddPCR) assay in suspected sepsis patients in the ED. This was a prospective single-centered observational study including patients admitted to the ED from 25 October 2022 to 3 June 2023 with suspected BSIs screened by Modified Shapiro Score (MSS) score. The comparison between ddPCR and blood culture (BC) was performed to evaluate the diagnostic performance of ddPCR for BSIs. Meanwhile, correlative analysis between ddPCR and the inflammatory and prognostic-related biomarkers were conducted to explore the relevance. Further, the health economic evaluation of the ddPCR was analyzed. 258 samples from 228 patients, with BC and ddPCR performed simultaneously, were included in this study. We found that ddPCR results were positive in 48.13% (103 of 214) of episodes, with identification of 132 pathogens. In contrast, BC only detected 18 positives, 88.89% of which were identified by ddPCR. When considering culture-proven BSIs, ddPCR shows an overall sensitivity of 88.89% and specificity of 55.61%, the optimal diagnostic power for quantifying BSI through ddPCR is achieved with a copy cutoff of 155.5. We further found that ddPCR exhibited a high accuracy especially in liver abscess patients. Among all the identified virus by ddPCR, EBV has a substantially higher positive rate with a link to immunosuppression. Moreover, the copies of pathogens in ddPCR were positively correlated with various markers of inflammation, coagulation, immunity as well as prognosis. With high sensitivity and specificity, ddPCR facilitates precision antimicrobial stewardship and reduces health care costs. The multiplexed ddPCR delivers precise and quantitative load data on the causal pathogen, offers the ability to monitor the patient's condition and may serve as early warning of sepsis in time-urgent clinical situations as ED. Early detection and effective administration of antibiotics are essential to improve clinical outcomes for those with life-threatening infection in the emergency department. ddPCR, an emerging tool for rapid and sensitive pathogen identification used as a precise bedside test, has developed to address the current challenges of BSI diagnosis and precise treatment. It characterizes sensitivity, specificity, reproducibility, and absolute quantifications without a standard curve. ddPCR can detect causative pathogens and related resistance genes in patients with suspected BSIs within a span of three hours. In addition, it can identify polymicrobial BSIs and dynamically monitor changes in pathogenic microorganisms in the blood and can be used to evaluate antibiotic efficacy and survival prognosis. Moreover, the copies of pathogens in ddPCR were positively correlated with various markers of inflammation, coagulation, immunity. With high sensitivity and specificity, ddPCR facilitates precision antimicrobial stewardship and reduces health care costs.

A Comprehensive Review of Innovative Paradigms in Microbial Detection and Antimicrobial Resistance: Beyond Traditional Cultural Methods.

Microbial detection and antimicrobial resistance (AMR) surveillance are critical components of public health efforts to combat infectious diseases and preserve the efficacy of antimicrobial agents. While foundational in microbial identification, traditional cultural methods are often laborious, time-consuming, and limited in their ability to detect AMR markers. In response to these challenges, innovative paradigms have emerged, leveraging advances in molecular biology, genomics, proteomics, nanotechnology, and bioinformatics. This comprehensive review provides an overview of innovative approaches beyond traditional cultural methods for microbial detection and AMR surveillance. Molecular-based techniques such as polymerase chain reaction (PCR) and next-generation sequencing (NGS) offer enhanced sensitivity and specificity, enabling the rapid identification of microbial pathogens and AMR determinants. Mass spectrometry-based methods provide rapid and accurate detection of microbial biomarkers, including matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) and biosensor technologies. Nanotechnology approaches, such as nanoparticle-based assays and nanopore sequencing, offer novel platforms for sensitive and label-free detection of pathogens and AMR markers. Embracing these innovative paradigms holds immense promise for improving disease diagnosis, antibiotic stewardship, and AMR containment efforts. However, challenges such as cost, standardization, and integration with existing healthcare systems must be addressed to realize the full potential of these technologies. By fostering interdisciplinary collaboration and innovation, we can strengthen our ability to detect, monitor, and combat AMR, safeguarding public health for generations.

Assessment of the Clinical Utility of the FilmArrayTM Gastrointestinal Panel for Detecting Gastrointestinal Pathogens.

Gastrointestinal infections present a significant public health concern as they lead to diverse clinical presentations and healthcare challenges. The rapid and accurate identification of causative pathogens is imperative for effective patient management. This study aimed to assess the clinical utility of the FilmArrayTM Gastrointestinal (GI) Panel for detecting gastrointestinal pathogens. Between November 1, 2022, and December 31, 2023, we analysed gastrointestinal specimens collected from a cohort of patients aged 21 to 91 at Asia University Hospital. These specimens were analyzed using the FilmArrayTM GI Panel. The study included 76 patients for whom the FilmArrayTM GI assay was conducted, with 40 (52.6%) showing positive results. Among the positive specimens, 23 (57.5%) had a single pathogen, while the remaining 17 (42.5%) had multiple pathogens. The remaining 36 (47.4%) specimens showed no pathogens. The overall positivity rate of the specimens was 52.6%. The most frequently detected pathogens included Salmonella, Clostridium difficile (toxin A/B), and Enteropathogenic Escherichia coli (EPEC). This study underscores the clinical value of the FilmArrayTM GI assay as a rapid and reliable tool for diagnosing gastrointestinal infections. Its capacity to detect multiple pathogens simultaneously enhances diagnostic accuracy and gives information to use in clinical decision-making. We strongly recommend its integration into clinical practice to expedite the diagnosis and management of gastrointestinal infections, ultimately leading to improved patient care and healthcare efficiency.

Application of Next-Generation Sequencing (NGS) Techniques for Selected Companion Animals.

Next-Generation Sequencing (NGS) techniques have revolutionized veterinary medicine for cats and dogs, offering insights across various domains. In veterinary parasitology, NGS enables comprehensive profiling of parasite populations, aiding in understanding transmission dynamics and drug resistance mechanisms. In infectious diseases, NGS facilitates rapid pathogen identification, characterization of virulence factors, and tracking of outbreaks. Moreover, NGS sheds light on metabolic processes by elucidating gene expression patterns and metabolic pathways, essential for diagnosing metabolic disorders and designing tailored treatments. In autoimmune diseases, NGS helps identify genetic predispositions and molecular mechanisms underlying immune dysregulation. Veterinary oncology benefits from NGS through personalized tumor profiling, mutation analysis, and identification of therapeutic targets, fostering precision medicine approaches. Additionally, NGS plays a pivotal role in veterinary genetics, unraveling the genetic basis of inherited diseases and facilitating breeding programs for healthier animals. Physiological investigations leverage NGS to explore complex biological systems, unraveling gene-environment interactions and molecular pathways governing health and disease. Application of NGS in treatment planning enhances precision and efficacy by enabling personalized therapeutic strategies tailored to individual animals and their diseases, ultimately advancing veterinary care for companion animals.