Diagnosis Of Infectious Diseases Research Articles

Clinical applications and challenges of metagenomic next-generation sequencing in the diagnosis of pediatric infectious disease

Abstract Infectious diseases seriously threaten the lives of children. Timely and accurate detection of pathogenic microorganisms and targeted medication are the keys to the diagnosing and treatment of infectious diseases in children. The next-generation metagenomic sequencing technology has attracted great attention in infectious diseases because of its characteristics such as no culture, high throughput, short detection cycle, wide coverage, and a good application prospect. In this paper, we review the studies of metagenomic next-generation sequencing in pediatric infectious diseases and analyze the challenges of its application in pediatric diseases.

Rapid Diagnosis of Pneumocystis jirovecii Pneumonia and Respiratory Tract Colonization by Next-Generation Sequencing

ObjectivesTo describe the epidemiology of Pneumocystis jirovecii pneumonia and colonization diagnosed by next-generation sequencing (NGS) and explore the usefulness of the number of P. jirovecii sequence reads for the diagnosis of P. jirovecii pneumonia.MethodsWe examined the NGS results for P. jirovecii in respiratory samples collected from patients and analysed their clinical, radiological and microbiological characteristics.ResultsAmong 285 respiratory samples collected over a 12-month period (January to December 2022), P. jirovecii sequences were detected in 56 samples from 53 patients. Fifty (94.3%) of the 53 patients were HIV-negative. Following our case definitions, 37 (69.8%) and 16 (30.2%) of the 53 patients had P. jirovecii infection and colonization respectively. P. jirovecii infection was associated with presence of underlying disease with immunosuppression (94.6% vs 18.8%, P < 0.05), positive serum 1,3-β-D-glucan (41.2% vs 0%, P < 0.01) and higher number of P. jirovecii sequence reads (P < 0.005). In contrast, P. jirovecii colonization was associated with the male sex (93.8% vs 54.1%, P < 0.01), another definitive infectious disease diagnosis of the respiratory tract (43.8% vs 2.7%, P < 0.001) and higher survival (100% vs 67.6%, P < 0.01). Although P. jirovecii pneumonia was associated with higher number of P. jirovecii reads in respiratory samples, only a sensitivity of 82.14% and a specificity of 68.75% could be achieved.ConclusionDetection of P. jirovecii sequences in respiratory samples has to be interpreted discreetly. A combination of clinical, radiological and laboratory findings is still the most crucial in determining whether a particular case is genuine P. jirovecii pneumonia.

QCML: Qualified Contrastive Machine Learning methodology for infectious disease diagnosis in CT images

The COVID-19 pandemic has had a terrible effect on human health, and computer-aided diagnostic (CAD) systems for chest computed tomography have emerged as a potential alternative for COVID-19 diagnosis. Yet, since the cost of data annotation may be excessively costly in the medical area, there is a shortage of data that has been annotated. A considerable quantity of labelled data is required in order to train a CAD system to a high level of accuracy. The study aims to describe an automatic and precise COVID-19 diagnostic method that utilizes a restricted amount of labelled CT images to solve this problem. The framework of the system is known as Qualified Contrastive Machine Learning (QCML), and the improvements that we have made may be summed up as follows: 1) In order to make use of all of the image's characteristics, we combine features with a two-dimensional discrete wavelet transform. 2) We employ the COVID-Net encoder with a redesign that focuses on the efficiency of learning and the task specificity of the data. 3) In order to strengthen our capacity to generalize, we have implemented a novel pertaining technique that is based on Qualified Contrastive Machine Learning. 4) In order to get better categorization results, we have included an extra auxiliary work. The application of Qualified Contrastive Machine Learning methodology for infectious disease diagnosis in CT images offers an accuracy of 93.55%, a recall of 91.59%, a precision of 96.92%, and an F1-score of 94.18%, demonstrating the potential for accurate and efficient COVID-19 diagnosis with limited labelled data.

Simultaneous detection of bovine viral diarrhea virus (BVDV) and bovine herpesvirus 1 (BoHV-1) using recombinase polymerase amplification

Bovine viral diarrhea virus (BVDV) is considered to be the most common agent of severe diarrhea in cattle worldwide, causing fever, diarrhea, ulcers, and abortion. Bovine herpesvirus 1 (BoHV-1) is also a major bovine respiratory disease agent that spreads worldwide and causes extensive damage to the livestock industry. Recombinase polymerase amplification (RPA) is a novel nucleic acid amplification method with the advantages of high efficiency, rapidity and sensitivity, which has been widely used in the diagnosis of infectious diseases. A dual RPA assay was developed for the simultaneous detection of BVDV and BoHV-1. The assay was completed at a constant temperature of 37 °C for 30 min. It was highly sensitive and had no cross-reactivity with other common bovine viruses. The detection rate of BVDV RPA in clinical samples (36.67%) was higher than that of PCR (33.33%), the detection rate of BoHV-1 RPA and PCR were equal. Therefore, the established dual RPA assay for BVDV and BoHV-1 could be a potential candidate for use as an immediate diagnostic.

Identification of Microorganism in Infected Wounds by Positively Charged Selective Sensor Array and Deep Learning Algorithm.

Microorganism are ubiquitous and intimately connected with human health and disease management. The accurate and fast identification of pathogenic microorganisms is especially important for diagnosing infections. Herein, three tetraphenylethylene derivatives (S-TDs: TBN, TPN, and TPI) featuring different cationic groups, charge numbers, emission wavelengths, and hydrophobicities were successfully synthesized. Benefiting from distinct cell wall binding properties, S-TDs were collectively utilized to create a sensor array capable of imaging various microorganisms through their characteristic fluorescent signatures. Furthermore, the interaction mechanism between S-TDs and different microorganisms was explored by calculating the binding energy between S-TDs and cell membrane/wall constituents, including phospholipid bilayer and peptidoglycan. Using a combination of the fluorescence sensor array and a deep learning model of residual network (ResNet), readily differentiation of Gram-negative bacteria (G-), Gram-positive bacteria (G+), fungi, and their mixtures was achieved. Specifically, by extensive training of two ResNet models with large quantities of images data from 14 kinds of microorganism stained with S-TDs, identification of microorganism was achieved at high-level accuracy: over 92.8% for both Gram species and antibiotic-resistant species, with 90.35% accuracy for the detection of mixed microorganism in infected wound. This novel method provides a rapid and accurate method for microbial classification, potentially aiding in the diagnosis and treatment of infectious diseases.

Chemically engineered mTOR-nanoparticle blockers enhance antitumour efficacy

Hepatocellular carcinoma (HCC) is a highly prevalent and deadly type of cancer, and although pharmacotherapy remains the cornerstone of treatment, therapeutic outcomes are often unsatisfactory. Pharmacological inhibition of mammalian target of rapamycin (mTOR) has been closely associated with HCC regression. Herein, we covalently conjugated AZD8055, a potent mTORC1/2 blocker, with a small panel of unsaturated fatty acids via a dynamically activating linkage to enable aqueous self-assembly of prodrug conjugates to form mTOR nanoblockers. Cell-based experiments were carried out to evaluate the effects of the nanoblocker against hepatocellular carcinoma (HCC) cells. The orthotopic and subcutaneous HCC mouse models were established to examine its antitumour activity. Among several fatty acids as promoieties, linoleic acid-conjugated self-assembling nanoblocker exhibited optimal size distribution and superior physiochemical properties. Compared with free agents, PEGylated AZD8055 nanoblocker (termed AZD NB) was pharmacokinetically optimized after intravenous administration. Invivo investigations confirmed that AZD NB significantly suppressed tumour outgrowth in subcutaneous HCCLM3 xenograft, Hepatoma-22, and orthotopic Hepa1-6 liver tumour models. Strikingly, treatment with AZD NB, but not free agent, increased intratumour infiltration of IFN-γ+CD8+ T cells and CD8+ memory T cells, suggesting a potential role of the mTOR nanoblocker to remodel the tumour microenvironment. Overall, a single conjugation with fatty acid transformed a hydrophobic mTOR blocker into a systemically injectable nanomedicine, representing a facile and generalizable strategy for improving the therapeutic index of mTOR inhibition-based cancer therapy. The mTOR inhibition by chemically engineered nanoblocker presented here had enhanced efficacy against tumours compared with the pristine drug and thus has the potential to improve the survival outcomes of patients with HCC. Additionally, this new nanosystem derived from co-assembling of small-molecule prodrug entities can serve as a delivery platform for the synergistic co-administration of distinct pharmaceutical agents. This work was supported by the National Natural Science Foundation of China (32171368,81721091), the Zhejiang Provincial Natural Science Foundation of China (LZ21H180001), the Jinan Provincial Laboratory Research Project of Microecological Biomedicine (JNL-2022039c and JNL-2022010B), State Key Laboratory for Diagnosis and Treatment of Infectious Diseases (zz202310), and Natural Science Foundation of Shandong Province (ZR2023ZD59).

Integrative analyses identify opportunistic pathogens of patients with lower respiratory tract infections based on metagenomic next-generation sequencing

Lower respiratory tract infections (LRTIs) represent some of the most globally prevalent and detrimental diseases. Metagenomic next-generation sequencing (mNGS) technology has effectively addressed the requirement for the diagnosis of clinical infectious diseases. This study aimed at identifying and classifying opportunistic pathogens from the respiratory tract-colonizing microflora in LRTI patients using data acquired from mNGS analyses. A retrospective study was performed employing the mNGS data pertaining to the respiratory samples derived from 394 LRTIs patients. Linear discriminant analysis effect size (LEfSe) analysis was conducted to discern the discriminant bacteria. Receiver operating characteristic curves (ROC) were established to demonstrate discriminant bacterial behavior to distinguish colonization from infection. A total of 443 discriminant bacteria were identified and segregated into three cohorts contingent upon their correlation profiles, detection frequency, and relative abundance in order to distinguish pathogens from colonizing microflora. Among them, 119 emerging opportunistic pathogens (cohort 2) occupied an average area under the curve (AUC) of 0.976 for exhibiting the most prominent predictability in distinguishing colonization from infection, 39 were colonizing bacteria (cohort 1, 0.961), and 285 were rare opportunistic pathogens (cohort 3, 0.887). The LTRIs patients appeared modular in the form of cohorts depicting complex microbial co-occurrence networks, reduced diversity, and a high degree of antagonistic interactions in the respiratory tract microbiome. The study findings indicate that therapeutic interventions should target interaction networks rather than individual microbes, providing an innovative perspective for comprehending and combating respiratory infections. Conclusively, this study reports a profile of LRTIs-associated bacterial colonization and opportunistic pathogens in a relatively large-scale cohort, which might serve as a reference panel for the interpretation of mNGS results in clinical practice.

Present and Future Applications of Digital PCR in Infectious Diseases Diagnosis.

Infectious diseases account for about 3 million deaths per year. The advent of molecular techniques has led to an enormous improvement in their diagnosis, both in terms of sensitivity and specificity and in terms of the speed with which a clinically useful result can be obtained. Digital PCR, or 3rd generation PCR, is based on a series of technical modifications that result in more sensitive techniques, more resistant to the action of inhibitors and capable of direct quantification without the need for standard curves. This review presents the main applications that have been developed for the diagnosis of viral, bacterial, and parasitic infections and the potential prospects for the clinical use of this technology.

Application value of metagenomic next-generation sequencing in hematological patients with high-risk febrile neutropenia.

Metagenomic next-generation sequencing (mNGS) is a novel non-invasive and comprehensive technique for etiological diagnosis of infectious diseases. However, its practical significance has been seldom reported in the context of hematological patients with high-risk febrile neutropenia, a unique patient group characterized by neutropenia and compromised immune responses. This retrospective study evaluated the results of plasma cfDNA sequencing in 164 hematological patients with high-risk febrile neutropenia. We assessed the diagnostic efficacy and clinical impact of mNGS, comparing it with conventional microbiological tests. mNGS identified 68 different pathogens in 111 patients, whereas conventional methods detected only 17 pathogen types in 36 patients. mNGS exhibited a significantly higher positive detection rate than conventional methods (67.7% vs. 22.0%, P < 0.001). This improvement was consistent across bacterial (30.5% vs. 9.1%), fungal (19.5% vs. 4.3%), and viral (37.2% vs. 9.1%) infections (P < 0.001 for all comparisons). The anti-infective treatment strategies were adjusted for 51.2% (84/164) of the patients based on the mNGS results. mNGS of plasma cfDNA offers substantial promise for the early detection of pathogens and the timely optimization of anti-infective therapies in hematological patients with high-risk febrile neutropenia.

Illumina and Nanopore sequencing in culture-negative samples from suspected lower respiratory tract infection patients.

To evaluate the diagnostic value of metagenomic sequencing technology based on Illumina and Nanopore sequencing platforms for patients with suspected lower respiratory tract infection whose pathogen could not be identified by conventional microbiological tests. Patients admitted to the Respiratory and Critical Care Medicine in Shanghai Ruijin Hospital were retrospectively studied from August 2021 to March 2022. Alveolar lavage or sputum was retained in patients with clinically suspected lower respiratory tract infection who were negative in conventional tests. Bronchoalveolar lavage fluid (BALF) samples were obtained using bronchoscopy. Sputum samples were collected, while BALF samples were not available due to bronchoscopy contraindications. Samples collected from enrolled patients were simultaneously sent for metagenomic sequencing on both platforms. Thirty-eight patients with suspected LRTI were enrolled in this study, consisting of 36 parts of alveolar lavage and 2 parts of sputum. According to the infection diagnosis, 31 patients were confirmed to be infected with pathogens, while 7 patients were diagnosed with non-infectious disease. With regard to the diagnosis of infectious diseases, the sensitivity and specificity of Illumina and Nanopore to diagnose infection in patients were 80.6% vs. 93.5% and 42.9 vs. 28.6%, respectively. In patients diagnosed with bacterial, Mycobacterium, and fungal infections, the positive rates of Illumina and Nanopore sequencer were 71.4% vs. 78.6%, 36.4% vs. 90.9%, and 50% vs. 62.5%, respectively. In terms of pathogen diagnosis, the sensitivity and specificity of pathogens detected by Illumina and Nanopore were 55.6% vs. 77.8% and 42.9% vs. 28.6%, respectively. Among the patients treated with antibiotics in the last 2 weeks, 61.1% (11/18) and 77.8% (14/18) cases of pathogens were accurately detected by Illumina and Nanopore, respectively, among which 8 cases were detected jointly. The consistency between Illumina and diagnosis was 63.9% (23/36), while the consistency between Nanopore and diagnosis was 83.3% (30/36). Between Illumina and Nanopore sequencing methods, the consistency ratio was 55% (22/42) based on pathogen diagnosis. Both platforms play a certain value in infection diagnosis and pathogen diagnosis of CMT-negative suspected LRTI patients, providing a theoretical basis for clinical accurate diagnosis and symptomatic treatment. The Nanopore platform demonstrated potential advantages in the identification of Mycobacterium and could further provide another powerful approach for patients with suspected Mycobacterium infection.

Molecular Imaging Techniques in the Diagnosis and Monitoring of Infectious Diseases

Molecular Imaging Techniques in the Diagnosis and Monitoring of Infectious Diseases

Unraveling the potential of metagenomic next-generation sequencing in infectious disease diagnosis: Challenges and prospects

Unraveling the potential of metagenomic next-generation sequencing in infectious disease diagnosis: Challenges and prospects

Utility of Microbial Cell Free DNA Next-Generation Sequencing for Diagnosis and Management of Infectious Diseases

Utility of Microbial Cell Free DNA Next-Generation Sequencing for Diagnosis and Management of Infectious Diseases

Utilizing Natural Language Processing and Large Language Models in the Diagnosis and Prediction of Infectious Diseases: A Systematic Review

BackgroundNatural Language Processing (NLP) and Large Language Models (LLMs) hold largely untapped potential in infectious disease management. This review explores their current use and uncovers areas needing more attention. MethodsThis analysis followed systematic review procedures, registered with PROSPERO. We conducted a search across major databases including PubMed, Embase, Web of Science, and Scopus, up to December 2023, using keywords related to NLP, LLM, and infectious diseases. We also employed the QUADAS-2 tool for evaluating the quality and robustness of the included studies. ResultsOur review identified 15 studies with diverse applications of NLP in infectious disease management. Notable examples include GPT-4's application in detecting urinary tract infections and BERTweet's use in Lyme Disease surveillance through social media analysis. These models demonstrated effective disease monitoring and public health tracking capabilities. However, the effectiveness varied across studies. For instance, while some NLP tools showed high accuracy in pneumonia detection and high sensitivity in identifying invasive mold diseases from medical reports, others fell short in areas like bloodstream infection management. ConclusionThis review highlights the yet-to-be-fully-realized promise of NLP and LLMs in infectious disease management. It calls for more exploration to fully harness AI's capabilities, particularly in the areas of diagnosis, surveillance, predicting disease courses, and tracking epidemiological trends.

Indirect hemagglutination assay for diagnosing brucellosis: Past, present, and future

Brucellosis is a zoonotic disease that causes enormous losses in livestock production worldwide and has a significant public health impact. None of the brucellosis-free countries is currently able to guarantee their ability to prevent the introduction of the pathogen due to the increase in tourism and the expansion of migration. The timely identification of infected animals is an effective means of preventing brucellosis and minimizing the epidemiological risk. The tube agglutination test, Rose Bengal plate test, complement fixation test, and enzyme-linked immunosorbent assay, which are routinely used to identify seropositive productive animals, have limitations and results that do not always correlate. The indirect hemagglutination assay (IHA) stands out among non-traditional methods because it is affordable, has a simple protocol, and is more reliable than classical serological tests, especially in cases of questionable and/or false-negative results. The diagnostic value of the IHA has long been studied by laboratories in several countries, but mostly by post-soviet research teams; therefore, the results continue to be published in Russian-language journals, ensuring that the local scientific community can access the results. In addition, the efficacy of this test for the diagnosis of brucellosis and other infectious diseases has not yet been reviewed. The purpose of this review was to summarize the results of studies on the development and use of IHA for the diagnosis of brucellosis and to determine the prospects for further improvement Keywords: brucellosis, diagnostic value, indirect hemagglutination assay, prospects for improving the test, serological tests.

Metronidazole Refractory Giardiasis Complicating the Management of Rhabdomyosarcoma in a Child

Giardiasis caused by Giardia duodenalis is one of the leading causes of gastroenteritis, especially in developing countries. The scenario may be further complicated by emerging metronidazole refractory cases worldwide. We present a case of a 2-year-old girl on chemotherapy for metastatic para meningeal rhabdomyosarcoma. She had a 15 day history of persistent diarrhea of foul-smelling loose stools, without fever. Light microscopy of stool wet mounts revealed cysts and trophozoites of Giardia duodenalis. The patient was managed with nitazoxanide after metronidazole proved ineffective clinically. This case highlights the importance of timely diagnosis and management of infectious diseases and rising antimicrobial resistance among parasites.

Diagnostic yield and complications of flexible bronchoscopy performed at Charlotte Maxeke Johannesburg academic hospital: A 5 year restrospective study

Objectives: There is a high incidence of lung diseases but very little data in South Africa relating to bronchoscopy practice. The objectives of the study are to determine the diagnostic yield, indications, and complications as well as determine the effectiveness of biopsy and bronchoalveolar lavage (BAL) in making diagnoses of infectious and non-infectious diseases. Materials and Methods: Six hundred and ninety-two patients were identified and 647 cases were analyzed due to 45 cases with inadequate data for analyses. A single-center retrospective cross-sectional review of patients who underwent bronchoscopy between January 2015 and December 2019 was conducted at the Charlotte Maxeke Johannesburg Academic Hospital. Results: The epidemiology of the subjects showed a significant male predominance (64.14%), with a mean age of 55.9 years of age. The most common indication was suspected malignancy, followed by non-resolving pneumonia, 63.99%, and 14.53%, respectively. A total of 120 (18.55%) patients were diagnosed with a malignancy on biopsy and 83 (12.83%) on BAL. Of all bronchoscopies performed, 85.94% had no complications during or after bronchoscopy, whereas 10.97% were complicated with bleeding. Conclusion: This audit revealed that flexible bronchoscopy is safe and effective and associated with minimal risk. This study revealed the use of bronchoscopy in diagnosing lung malignancies/carcinomas and highlights the necessity of the availability of bronchoscopy.

Exploring hospital resilience protective or risk factors: lessons for future disaster response efforts.

Hospital resilience is essential in responding to disasters, but current research focuses mainly on frameworks and models rather than the protection of resilience and analysis of risk factors during public health emergencies. This study aims to examine the development of resilience in Chinese frontline hospitals during the initial COVID-19 outbreak in 2020, providing insights for future disaster response efforts. We conducted interviews with 26 hospital staff members who were involved in the initial response to the COVID-19 outbreak in China. We used a semi-structured interview approach and employed purposive sampling and snowball sampling techniques. The interview outline was guided by the 'Action Framework' proposed by the World Health Organization (WHO) for responding to infectious disease emergencies. This framework includes dimensions such as command, surveillance, risk communication, medical response, and public health response. We analyzed the collected data using Colaizzi's seven-step data analysis method and the template analysis method. WHO's 'action framework' effectively highlights the factors that contribute to hospital resilience. While medical response, including the availability of materials and facilities, the use of information technology, and the capacity for infectious disease diagnosis and treatment, remains crucial, other important aspects include awareness and beliefs about infections, treatment experience, interdisciplinary collaboration, and more. Additionally, it is essential to establish an intelligent command system, foster trusting partnerships between teams, improve monitoring capabilities for infectious disease agents, enhance risk communication through information synchronization and transparency, strengthen infection control planning, and improve environmental disinfection capabilities for effective public health emergency response. These contradictions significantly impact the enhancement of hospital resilience in dealing with major infectious disease outbreaks. In responding to sudden major infectious diseases, hospitals play a vital role within the healthcare system. Enhancing hospital resilience involves more than just improving treatment capabilities. It also requires effective command coordination at the hospital level, infection control planning, and the deployment of intelligent equipment. Additionally, planning for effective communication and coordination between hospitals, communities, and the national healthcare system can further enhance hospital resilience.

Performance of metagenomic next-generation sequencing in cerebrospinal fluid for diagnosis of tuberculous meningitis.

Purpose. Metagenomic next-generation sequencing (mNGS) has been widely used in the diagnosis of infectious diseases, while its performance in diagnosis of tuberculous meningitis (TBM) is incompletely characterized. The aim of this study was to assess the performance of mNGS in the diagnosis of TBM, and illustrate the sensitivity and specificity of different methods.Methods. We retrospectively recruited TBM patients between January 2021 and March 2023 to evaluate the performance of mNGS on cerebrospinal fluid (CSF) samples, in comparison with conventional microbiological testing, including culturing of Mycobacterium tuberculosis (MTB), acid-fast bacillus (AFB) stain, reverse transcription PCR and Xpert MTB/RIF.Results. Of the 40 enrolled, 34 participants were diagnosed with TBM, including 15(44.12 %) definite and 19(55.88 %) clinical diagnosis based upon clinical manifestations, CSF parameters, brain imaging, pathogen evidence and treatment response. The mNGS method identified sequences of Mycobacterium tuberculosis complex (MTBC) in 11 CSF samples. In patients with definite TBM, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of mNGS were 78.57, 100, 100, 66.67 and 85 %, respectively. Compared to conventional diagnostic methods, the sensitivity of mNGS (78.57 %) was higher than AFB (0 %), culturing (0 %), RT-PCR (60 %) and Xpert MTB/RIF (14.29 %).Conclusions. Our study indicates that mNGS of CSF exhibited an overall improved sensitivity over conventional diagnostic methods for TBM and can be considered a front-line CSF test.

ACM’s transition to an English journal: A leap towards international recognition

The Annals of Clinical Microbiology (Ann Clin Microbiol, ACM) serves as the official journal of the Korean Society of Clinical Microbiology. It is dedicated to publishing research articles encompassing all facets of clinical microbiology, intending to disseminate research findings pertinent to scholarly endeavors within the realm of clinical microbiology for the diagnosis, treatment, and prevention of infections in humans. Clinical microbiology stands as a pivotal discipline for the prevention, diagnosis, and treatment of infectious diseases in modern society. The publication of articles within the domain of clinical microbiology assumes a significant role in the dissemination and progression of advanced medical technology and knowledge. It provides a platform for various issues such as the discovery and treatment of new infectious diseases and the problem of antibiotic resistance. In Korea, this journal stands as the sole academic publication primarily dedicated to clinical microbiology, garnering substantial recognition for its academic contributions in this arena.