Diagnosis Of Infectious Diseases Research Articles

SATCAS: A CRISPR/Cas13a-based simultaneous amplification and testing platform for one-pot RNA detection and SNPs distinguish in clinical diagnosis

The clinical diagnosis of pathogen infectious diseases increasingly requires sensitive and rapid RNA detection technologies. The RNA-guided clustered regularly interspaced short palindromic repeats (CRISPR)/Cas13a system has shown immense potential in molecular diagnostics due to its trans-cleavage activity. However, most Cas13a-based detection methods require an amplicon transcription step, and the multi-step open-tube operations are prone to contamination, limiting their widespread application. Here, we propose an ultrasensitive (single-copy range, ∼aM) and rapid (within 40 min) isothermal one-pot RNA detection platform, termed SATCAS (Simultaneous Amplification and Testing platform based on Cas13a). This method effectively distinguishes viable bacteria (0%–100%) under constant total bacterial conditions, demonstrating its robustness and universality. SATCAS excels in identifying single nucleotide polymorphisms (SNPs), particularly detecting 0.5% drug-resistant mutations. We validated SATCAS by detecting infections in biological samples from 68 HBV, 23 EBV, and 48 SARS-CoV-2 patients, achieving 100% sensitivity, 92.86% specificity, and 97.06% accuracy in HBV infection testing. We anticipate that SATCAS has broad application potential in the early diagnosis, subtyping, drug resistance detection, and point-of-care monitoring of pathogen infectious diseases.

Electrochemical Label-free Methods for Ultrasensitive Multiplex Protein Profiling of Infectious Diseases.

Electrochemical detection methods are the more appropriate detection methods when it comes to the sensitive and specific determination of biomarkers. Biomarkers are the biological targets for disease diagnosis and monitoring. This review focuses on recent advances in label-free detection of biomarkers for infectious disease diagnosis. The current state of the art for rapid detection of infectious diseases and their clinical applications and challenges were discussed. Label-free electroanalytical methods are probably the most promising means to achieve this. We are currently in the early stages of the emerging technology of using label-free electrochemistry of proteins to develop biosensors. To date, antibody-based biosensors have been intensively developed, although many improvements in reproducibility and sensitivity are still needed. Moreover, there is no doubt that a growing number of aptamers and hopefully label-free biosensors based on nanomaterials will soon be used for disease diagnosis and therapy monitoring. And also here in this review article, we have discussed recent developments in the diagnosis of bacterial and viral infections, as well as the current status of the use of label-free electrochemical methods for monitoring inflammatory diseases.

Aptamer and Aptasensor Technology for Diagnosis of Infectious Diseases: A Mini Review

Aptamers are not so new a concept, however, it is scarcely discussed by medical fraternity. Aptamers are potent, new identification molecules set to rope in a new technique in the diagnostic arena. Aptamers have started almost a revolution in diagnostic assays since their discovery in the 90s. (Radu S. Current and previous disease outbreaks around the world, U.S. News & World Report. 2020 Mar 13 [cited 2024 Jun 17]. Available from: https://www.usnews.com/news/best-countries/slideshows/20-pandemic-and-epidemic-diseases-according-to-who) provides an overview of pandemics and epidemics as reported by the WHO. It is interesting to note that several endemic and epidemic diseases viz. Chikungunya, Cholera, Crimean-Congo haemorrhagic fever, Ebola virus disease, Hendra virus infection, Influenza, Lassa fever, Marburg virus disease, Meningitis, MERS-CoV (Middle East Respiratory Syndrome Corona Virus), Monkeypox, Nipah virus infection, Novel coronavirus, Plague, Rift Valley fever, SARS (Severe Acute Respiratory Syndrome), Smallpox, Tularaemia, Yellow fever, and Zika virus disease have been identified by the WHO and are being explored for applicability of aptamer technology in their identification. One of the most important necessities to control epidemic or pandemic diseases is early diagnosis. However, the majority of the diagnostic tests for these diseases are available only in tertiary care centres. The objective of this review is to discuss the potential of aptamer technology to provide undemanding, simple, specific, sensitive, and cost-effective diagnostic assays that are usable in remote and field conditions. Here, we discuss recent advances and approaches in aptamer and aptamer engineering useful in the diagnosis of infectious and non-infectious conditions. This review also discusses a few sensing discoveries which are a gift of advanced engineering and technology using optical and electrochemical aptasensors. It's still a long way to go, and we need to take into account the technological challenges being faced by aptamer-aptasensor technology.

Explainable AI decision support improves accuracy during telehealth strep throat screening

BackgroundArtificial intelligence-based (AI) clinical decision support systems (CDSS) using unconventional data, like smartphone-acquired images, promise transformational opportunities for telehealth; including remote diagnosis. Although such solutions’ potential remains largely untapped, providers’ trust and understanding are vital for effective adoption. This study examines how different human–AI interaction paradigms affect clinicians’ responses to an emerging AI CDSS for streptococcal pharyngitis (strep throat) detection from smartphone throat images.MethodsIn a randomized experiment, we tested explainable AI strategies using three AI-based CDSS prototypes for strep throat prediction. Participants received clinical vignettes via an online survey to predict the disease state and offer clinical recommendations. The first set included a validated CDSS prediction (Modified Centor Score) and the second introduced an explainable AI prototype randomly. We used linear models to assess explainable AI’s effect on clinicians’ accuracy, confirmatory testing rates, and perceived trust and understanding of the CDSS.ResultsThe study, involving 121 telehealth providers, shows that compared to using the Centor Score, AI-based CDSS can improve clinicians’ predictions. Despite higher agreement with AI, participants report lower trust in its advice than in the Centor Score, leading to more requests for in-person confirmatory testing.ConclusionsEffectively integrating AI is crucial in the telehealth-based diagnosis of infectious diseases, given the implications of antibiotic over-prescriptions. We demonstrate that AI-based CDSS can improve the accuracy of remote strep throat screening yet underscores the necessity to enhance human–machine collaboration, particularly in trust and intelligibility. This ensures providers and patients can capitalize on AI interventions and smartphones for virtual healthcare.

Nano-immuno-conjugates inspired by hydrophilic perovskite fluorescent spheres and magnetic assisted for detection of hepatitis B surface antigen.

The rampant hepatitis B virus (HBV) seriously endangers human health, and hepatitis B surface antigen (HBsAg) is its early diagnostic marker. Therefore, it is crucial to construct a fast and highly sensitive HBsAg detection method. Based on high-efficiency magnetic separation technology and fluorescent composite material labelling technology, an accurate, fast and sensitive fluorescent immunosensing system for HBsAg detectionwas developed. Immunomagnetic beads constructed from carboxyl-functionalized Fe3O4 nanoparticles (Fe3O4-COOH) with excellent magnetic response performance were used as efficient capture carriers for HBsAg. Immunofluorescence composite microspheres constructed based on ultra-stable polystyrene-coated CsPbBr3 perovskite nanocrystals (CPB@PSAA) with high hydrophilic properties, were excellent fluorescent markers for HBsAg. Using thissensitive sandwich fluorescence sensing system a good linear relationship within the range of 0.2-15ng/mL was established between HBsAg concentrationand fluorescence intensity with alimit of detection (LOD) of 0.05ng/mL. Thesystem obtained satisfactory results when tested on real human serum samples. The magnetic-assisted fluorescence immune-sandwich sensor system has broad application prospects in biomedicine such as rapid and early diagnosis and effective prevention of infectious diseases.

Quantitative and ultrasensitive detection of four inflammatory biomarkers by gold nanoparticle‐based paper sensor

Four inflammatory biomarkers (CRP, IL‐6, PCT and SAA) have different manifestations and roles in different infectious diseases and stages of infection, and the diagnosis and identification of infectious diseases can be realized through quantitative analysis of these four biomarkers simultaneously. In this study, we developed a colloidal gold nanoparticle (AuNP)‐based multiplex LFA strip using eight highly‐sensitive monoclonal antibodies that simultaneously detected CRP, IL‐6, PCT and SAA in serum within 15 min. And quantitative analysis was achieved with a portable strip reader, the LODs were 2.5 μg/mL, 25.3 pg/mL 0.87 ng/mL and 8.8 μg/mL for CRP, IL‐6, PCT and SAA, while detection ranges were 2.5–200 μg/mL, 25.3–8000 pg/mL 0.87–100 ng/mL and 8.8–200 μg/mL. Moreover, the quantitative colloidal gold assay correlated well with the results of a chemiluminescence immunoassay when testing clinical serum samples. Our developed method was reliable and accurate according to the recovery test results. Therefore, the strip can be used as an alternative method for the simultaneous monitoring of CRP, IL‐6, PCT and SAA in serum samples.

Ultrasensitive detection of the H5N1 nucleic acid fragment by ICP-MS using DNA dendrimer-carried silver nanoparticle labeling.

The importance of avian influenza virus (AIV) detection in clinical diagnosis and prognosis has been deeply recognized. In this study, the ultrasensitive detection of AIV subtype H5N1 was achieved by ICP-MS combined with DNA dendrimer-carried silver nanoparticle (AgNP) labeling. First, a magnetic control system was constructed by anchoring double-strand DNAs (dsDNAs) which contained a complementary sequence of H5N1 and two locked triggers on the surface of magnetic beads (MBs). When H5N1 was present, the two triggers were released and initiated dendrimer hybridization chain reactions which led to the generation of DNA dendrimer-carried AgNPs on the surface of the MBs. Finally, the AgNPs were collected via magnetic separation, digested by nitric acid, and tested using ICP-MS. The signal intensities of 107Ag were positively correlated with the concentrations of H5N1. Notably, the DNA dendrimer assembly contributed to significant signal amplification and good sensitivity with the limit of detection as low as 2.0 × 10-11 mol L-1. Moreover, the method displayed favorable selectivity against mismatched H5N1 and good recoveries in human serum samples. It is a promising analytical tool for the H5N1 virus and other subtypes of AIV, and has potential value in clinical diagnosis and prognosis of infectious diseases.

Mass spectrometry-based metabolomics for the investigation of antibiotic-bacterial interactions.

With the development of analytical technologies especially mass spectrometry, metabolomics is becoming increasingly hot in the field of studying antibiotic-bacterial interactions. On the one hand, metabolomics can reveal metabolic perturbations in bacteria in the presence of antibiotics and expose metabolic mechanisms. On the other hand, through in-depth analysis of bacterial metabolic profiles, biomarkers and bioactive secondary metabolites with great potential as drug precursors can be discovered. This review focuses on the experimental workflow of bacterial metabolomics and its application to study the interaction between bacteria and antibiotics. Metabolomics improves the understanding of antibiotic lethality, reveals metabolic perturbations in antibiotic-resistant bacteria, guides the diagnosis and antibiotic treatment of infectious diseases, and aids in the exploration of antibacterial metabolites in nature. Furthermore, current limitations and directions for future developments in this area are discussed.

Metal Nanoparticle-Based Biosensors for the Early Diagnosis of Infectious Diseases Caused by ESKAPE Pathogens in the Fight against the Antimicrobial-Resistance Crisis.

The species included in the ESKAPE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and the genus Enterobacter) have a high capacity to develop antimicrobial resistance (AMR), a health problem that is already among the leading causes of death and could kill 10 million people a year by 2050. The generation of new potentially therapeutic molecules has been insufficient to combat the AMR "crisis", and the World Health Organization (WHO) has stated that it will seek to promote the development of rapid diagnostic strategies. The physicochemical properties of metallic nanoparticles (MNPs) have made it possible to design biosensors capable of identifying low concentrations of ESKAPE bacteria in the short term; other systems identify antimicrobial susceptibility, and some have been designed with dual activity in situ (bacterial detection and antimicrobial activity), which suggests that, in the near future, multifunctional biosensors could exist based on MNPs capable of quickly identifying bacterial pathogens in clinical niches might become commercially available. This review focuses on the use of MNP-based systems for the rapid and accurate identification of clinically important bacterial pathogens, exhibiting the necessity for exhaustive research to achieve these objectives. This review focuses on the use of metal nanoparticle-based systems for the rapid and accurate identification of clinically important bacterial pathogens.

Photodynamic Inactivation as a Promising Method of Combating Resistant Strains of Staphylococci

Relevance. The development of antimicrobial drugs and alternative methods, technologies and means of prevention, diagnosis and treatment of human infectious diseases caused by antibiotic-resistant microorganisms is one of the priorities of ensuring the biological safety of the country. Aims. To evaluate the bactericidal activity of tetrapyrrole macroheterocycles (porphyrins) at different light irradiation durations in relation to staphylococci, in vitro. Materials and methods. Studied strains of microorganisms: museum strains of microorganisms – S. aureus ATCC 29213, S. epidermidis ATCC 14990 and antibiotic-resistant strains of bacteria of the genus Staphylococcus (n=18) isolated from clinical biomaterial and from environmental objects in a medical organization. The studied chemical compounds are three different compounds of water-soluble asymmetrically substituted porphyrins containing heterocyclic fragments on the periphery of the porphyrin cycle (residues of benzoxazole, N-methylbenzimidazole and benzothiazole). Results. The activity of all three porphyrin compounds in relation to museum strains of staphylococcus and 77.8% of clinical antibiotic-resistant strains (n=14; 95% CI 20.1-97.5) turned out to be maximal (complete lysis) after 10 minutes of irradiation. Conclusions. The tested tetrapyrrole macroheterocycles (porphyrins) exhibit bactericidal activity against museum and clinical strains of staphylococcus, with different levels of antibiotic resistance, which determines Keywords: antibiotic resistance, water-soluble porphyrin, photodynamic inactivation, photosensitizer, photochemistry, staphylococci No conflict of interest to declare.

A Critical Review in Infectious Disease and Mathematical Modelling

Infectious diseases control and prevention relies on a thorough understanding of the factors determining transmission. The transmission dynamics of infectious diseases is susceptible to changes governed by several factors, whose recognition is critical for the rational development of strategies for prevention and control, as well as for developing health policies. This article summarizes the fundamental principles of infectious disease transmission and compartmental models. Basic principles of infectious disease diagnosis, reasons for formulating the infectious diseases and historical facts on epidemics are also reviewed.

A Critical Review in Infectious Disease and Mathematical Modelling

Infectious diseases control and prevention relies on a thorough understanding of the factors determining transmission. The transmission dynamics of infectious diseases is susceptible to changes governed by several factors, whose recognition is critical for the rational development of strategies for prevention and control, as well as for developing health policies. This article summarizes the fundamental principles of infectious disease transmission and compartmental models. Basic principles of infectious disease diagnosis, reasons for formulating the infectious diseases and historical facts on epidemics are also reviewed.

Infections in patients with mantle cell lymphoma.

Advancements in treatments have significantly improved the prognosis for mantle cell lymphoma (MCL), and there is a growing population of survivors with an increased susceptibility to infections. We assessed the incidence of infections by clinical characteristics and treatment both before and after MCL diagnosis in Sweden. Patients with a diagnosis of MCL ≥ 18 years between 2007 and 2019 were included, along with up to 10 matched comparators. Infectious disease diagnosis and anti-infective drug dispensation were identified by the National Patient and the Prescribed Drug Registers, respectively. Patients and comparators were followed from the diagnosis/matching date until death, emigration, or June 30, 2020. Overall, 1559 patients and 15,571 comparators were followed for a median duration of 2.9 and 5 years, respectively. The infection rate among patients was twofold higher, RRadj = 2.14 (2.01-2.27), contrasted to the comparator group. There was a notable rise in infection rates already 4 years before MCL diagnosis, which reached a fourfold increase in the first year after diagnosis and persisted significantly increased for an additional 8 years. Among patients, 69% (n = 1080) experienced at least one infection during the first year of follow-up. Influenza, pneumonia, other bacterial infections, urinary tract infections, and acute upper respiratory infections were the most frequent. Notably, MCL remained to be the primary leading cause of death among patients (57%, n = 467/817). Infections as the main cause of death were rare (2.6%, n = 21). Our study highlights the importance of thoroughly assessing infectious morbidity when appraising new treatments. Further investigations are warranted to explore strategies for reducing infectious disease burden.

Methodological evaluation of systematic reviews based on the use of artificial intelligence systems in chest radiography

IntroductionIn recent years, systems that use artificial intelligence (AI) in medical imaging have been developed, such as the interpretation of chest X-ray to rule out pathology. This has produced an increase in systematic reviews (SR) published on this topic. This article aims to evaluate the methodological quality of SRs that use AI for the diagnosis of thoracic pathology by simple chest X-ray. Material and methodsSRs evaluating the use of AI systems for the automatic reading of chest X-ray were selected. Searches were conducted (from inception to May 2022): PubMed, EMBASE, and the Cochrane Database of Systematic Reviews. Two investigators selected the reviews. From each SR, general, methodological and transparency characteristics were extracted. The PRISMA statement for diagnostic tests (PRISMA-DTA) and AMSTAR-2 were used. A narrative synthesis of the evidence was performed. Protocol registry: Open Science Framework: https://osf.io/4b6u2/. ResultsAfter applying the inclusion and exclusion criteria, 7 SRs were selected (mean of 36 included studies per review). All the included SRs evaluated “deep learning” systems in which chest X-ray was used for the diagnosis of infectious diseases. Only 2 (29%) SRs indicated the existence of a review protocol. None of the SRs specified the design of the included studies or provided a list of excluded studies with their justification. Six (86%) SRs mentioned the use of PRISMA or one of its extensions. The risk of bias assessment was performed in 4 (57%) SRs. One (14%) SR included studies with some validation of AI techniques. Five (71%) SRs presented results in favour of the diagnostic capacity of the intervention. All SRs were rated "critically low" following AMSTAR-2 criteria. ConclusionsThe methodological quality of SRs that use AI systems in chest radiography can be improved. The lack of compliance in some items of the tools used means that the SRs published in this field must be interpreted with caution.

Functional probes for the diagnosis and treatment of infectious diseases

AbstractInfectious diseases present significant challenges to global health, thereby extensively affecting both human society and the economy. In recent years, functional probes have demonstrated remarkable potential as crucial biomedical media for the research and treatment of infectious diseases. Their applications in the realm of infectious diseases include pathogen detection, exploration of biological mechanisms, and development of anti‐infective drugs. This review provides a concise introduction to the severity, classification, and pathogenesis of infectious diseases. Subsequently, we examined the distinctiveness and design strategies of functional probes for diagnosing and treating infectious diseases, shedding light on their design rationale using typical examples. We discuss the current status and challenges associated with the clinical implementation of functional probes. Furthermore, we explored the prospects of using these probes for the diagnosis and treatment of infectious diseases. This review aims to offer novel insights into the design of diagnostic probes for infectious diseases and broaden their applications in disease treatment.

Bacterial DNA enrichment for low-inoculum fracture-related infection diagnostic using high-throughput sequencing

One of the main barriers for the implementation of metagenomic sequencing in routine diagnosis of infectious diseases is the presence of host DNA. While several enrichment methods are likely to overcome this issue, their effectiveness for specimens such as bone in the case of chronic infections remains to be determined. We compared the relevance of two methods for bacterial DNA enrichment when compared to a reference protocol during pretreatment of bone samples from fracture-related infections before HTS by both Illumina Miseq and Oxford Nanopore Technology (ONT). The bacterial/human DNA ratio was higher for either protocols than the reference technique (p = 0.00012), without any significant difference between them. HTS sensitivity over culture ranged from 21.7 % to 85 %. The ability of the studied protocols to improve the bacterial/human DNA ratio depends on the sequencing technique employed. In this context, there is room for improvement in enhancing the sensitivity of HTS for diagnostic purpose.

Metagenomic next-generation sequencing reveals co-infection with Legionella pneumophila and Fusobacterium necrophorum in a patient with severe pneumonia: a case report

BackgroundLegionella pneumonia is one of the most severe types of atypical pneumonia, impairing multiple organ systems, posing a threat to life. Diagnosing Legionella pneumonia is challenging due to difficulties in culturing the bacteria and limitations in immunoassay sensitivity and specificity.Case presentationThis paper reports a rare case of sepsis caused by combined infection with Legionella pneumophila and Fusobacterium necrophorum, leading to respiratory failure, acute kidney injury, acute liver injury, myocardial damage, and electrolyte disorders. In addition, we systematically reviewed literature on patients with combined Legionella infections, analyzing their clinical features, laboratory results and diagnosis.ConclusionsFor pathogens that require prolonged incubation periods and are less sensitive to conventional culturing methods, metagenomic next-generation sequencing (mNGS) can be a powerful supplement to pathogen screening and plays a significant role in the auxiliary diagnosis of complex infectious diseases.

Optimizing Early Diagnosis of Infectious Diseases in Migrant and Refugee Children: An Overview of Best Practices and Strategies.

Optimizing Early Diagnosis of Infectious Diseases in Migrant and Refugee Children: An Overview of Best Practices and Strategies.

An Automated Versatile Diagnostic Workflow for Infectious Disease Detection in Low-Resource Settings.

Laboratory automation effectively increases the throughput in sample analysis, reduces human errors in sample processing, as well as simplifies and accelerates the overall logistics. Automating diagnostic testing workflows in peripheral laboratories and also in near-patient settings -like hospitals, clinics and epidemic control checkpoints- is advantageous for the simultaneous processing of multiple samples to provide rapid results to patients, minimize the possibility of contamination or error during sample handling or transport, and increase efficiency. However, most automation platforms are expensive and are not easily adaptable to new protocols. Here, we address the need for a versatile, easy-to-use, rapid and reliable diagnostic testing workflow by combining open-source modular automation (Opentrons) and automation-compatible molecular biology protocols, easily adaptable to a workflow for infectious diseases diagnosis by detection on paper-based diagnostics. We demonstrated the feasibility of automation of the method with a low-cost Neisseria meningitidis diagnostic test that utilizes magnetic beads for pathogen DNA isolation, isothermal amplification, and detection on a paper-based microarray. In summary, we integrated open-source modular automation with adaptable molecular biology protocols, which was also faster and cheaper to perform in an automated than in a manual way. This enables a versatile diagnostic workflow for infectious diseases and we demonstrated this through a low-cost N. meningitidis test on paper-based microarrays.

Clinical usefulness of metagenomic next-generation sequencing for Talaromyces marneffei diagnosis in China: a retrospective study.

Metagenomic next-generation sequencing (mNGS) has been widely used in the diagnosis of infectious diseases. However, studies on Talaromyces marneffei detection using mNGS remain scarce. Therefore, this study aimed to explore the diagnostic performance of mNGS in T. marneffei. Between March 2021 and June 2023, patients who were discharged with a final diagnosis of talaromycosis, or confirmed T. marneffei infection by mNGS, culture or pathological examination were included in the study. Culture and mNGS were performed simultaneously for all patients. Clinical data were retrieved for analysis. A total of 78 patients were enrolled, with 40 in the talaromycosis group and 38 in the suspected-talaromycosis group. In the talaromycosis group, mNGS showed a higher positivity rate(40/40, 100.0%) compared to culture(34/40, 85.0%)(P = 0.111). All patients in the suspected-talaromycosis group tested negative via culture, while mNGS yielded positive results. The T. marneffei reads in the talaromycosis group were significantly higher than in the suspected-talaromycosis group (4399 vs. 28, P < 0.001). In the suspected-talaromycosis group, of the four patients with low reads who did not receive antifungal therapy, one died and one lung lesion progressed; most patients(31/34, 91.2%) recovered after receiving appropriate antifungal therapy. mNGS proves to be a rapid and highly sensitive method for detecting T. marneffei. Higher reads of T. marneffei correspond to a higher likelihood of infection. However, cases with low reads necessitate a comprehensive approach, integrating clinical manifestations, laboratory tests, and imaging examinations to confirm T. marneffei infection.