Early Diagnosis Of Infectious Diseases Research Articles

Chest x-ray images: transfer learning model in COVID-19 detection.

This research aims to develop an effective algorithm for diagnosing COVID-19 in chest X-rays using the transfer learning method and support vector machines. In total, data was collected from 10 clinics, including both large city hospitals and smaller medical institutions. This ensured a diverse range of geographical and demographic information in the sample. An extensive data set was collected, including 10,000 chest X-ray images. 5000 images represent normal cases, 3993 images represent pneumonia cases, and 1007 images represent COVID-19 cases. Machine learning methods were applied to develop a classification model, and the results were compared with seven state-of-the-art models and a lightweight CNN architecture. The results showed that the proposed method achieves high accuracy values (Accuracy): 0.95 for COVID-19, 0.89 for pneumonia, and 0.92 for normal images (p < 0.05). Comparison with other models demonstrates statistically significant superiority of our method in accuracy across all three classes. The EfficientNet-B0 model surpasses our method only in accuracy for normal images with p < 0.01, confirming the advantages of our method. Our method demonstrates high sensitivity values (Sensitivity): 0.96 for COVID-19, 0.88 for pneumonia, and 0.93 for normal images (p < 0.05), outperforming most of the compared models. Correlation analysis showed Pearson coefficients of 0.92, 0.89, and 0.94 for COVID-19, pneumonia, and normal images, respectively, confirming a high degree of consistency between predicted and true class labels. In addition, the model was validated on external datasets to assess its generalizability. This validation confirmed its high level of effectiveness in a variety of clinical settings. This study confirms the importance of applying machine learning methods in medical applications and opens new perspectives for early diagnosis of infectious diseases. The practical application of the obtained results can enhance the efficiency of diagnosis and control the spread of COVID-19, as well as contribute to the development of innovative methods in medical practice.

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.

Integrated High-Throughput Centrifugal Microfluidic Chip Device for Pathogen Detection On-Site.

An integrated and high-throughput device for pathogen detection is crucial in point-of-care testing (POCT), especially for early diagnosis of infectious diseases and preventing the spread of infection. We developed an on-site testing platform that utilizes a centrifugal microfluidic chip and automated device to achieve high-throughput detection. The low-power (<32 W), portable (220 mm × 220 mm × 170 mm, 4 kg) device can complete bacterial lysis, nucleic acid extraction and purification, loop-mediated isothermal amplification (LAMP) reaction, and real-time fluorescence detection. Magnetic beads for nucleic acid adsorption can be mixed by applying electromagnetic fields and centrifugal forces, and the efficiency of nucleic acid extraction is improved by 60% compared to the no-mixing group. The automated nucleic acid extraction process achieves equivalent nucleic acid extraction efficiency in only 40% of the time consumed using the kit protocol. By designing the valve system and disc layout, the maximum speed required for the centrifugal microfluidic chip is reduced to 1500 rpm, greatly reducing the equipment power consumption and size. In detecting E. coli, our platform achieves a limit of detection (LOD) of 102 CFU/mL in 60 min. In summary, our active centrifugal microfluidic platform provides a solution for the integration of complex biological assays on turntables, with great potential in the application of point-of-care diagnosis.

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.

A Comparative Study of "Grafting to" and "Grafting from" Conjugation Methods for the Preparation of Antibody-Temperature-Responsive Polymer Conjugates.

Early diagnosis of infectious diseases is still challenging particularly in a nonlaboratory environment or limited resources areas. Thus, sensitive, inexpensive, and easily handled diagnostic approaches are required. The lateral flow immunoassay (LFIA) is commonly used in the screening of infectious diseases despite its poor sensitivity, especially with low pathogenic loads (early stages of infection). This article introduces a novel polymeric material that might help in the enrichment and concentration of pathogens to overcome the LFIA misdiagnosis. To achieve this, we evaluated the efficiency of introducing poly(N-isopropylacrylamide) (PNIPAAm) into immunoglobulin G (IgG) as a model antibody using two different conjugation methods: grafting to (GT) and grafting from (GF). The IgG-PNIPAAm conjugates were characterized using SDS-PAGE, DLS, and temperature-responsive phase transition behavior. SDS-PAGE analysis revealed that the GF method was more efficient in introducing the polymer than the GT method, with calculated polymer introduction ratios of 61% and 34%, respectively. The GF method proved to be less susceptible to steric hindrance and more efficient in introducing high-molecular-weight polymers into proteins. These results are consistent with previous studies comparing the GT and GF methods in similar systems. This study represents an important step toward understanding how the choice of polymer incorporation method affects the properties of IgG-PNIPAAm conjugates. The synthesized polymer allowed binding and enrichment of mouse IgG that was used as a model antigen with a clear LFIA band. On the basis of our findings, this system might help in improving the sensitivity of simple diagnostics.

Effectiveness of metagenomic next-generation sequencing in the diagnosis of infectious diseases: A systematic review and meta-analysis

ObjectivesEarly diagnosis of infectious diseases remains a challenge. This study assessed the diagnostic value of mNGS in infections and explored the effect of various factors on the accuracy of mNGS. MethodsAn electronic article search of PubMed, Cochrane Library, and Embase was performed. A total of 85 papers were eligible for inclusion and analysis. Stata 12.0 was used for statistical calculation to evaluate the efficacy of mNGS for the diagnosis of infectious diseases. ResultsThe AUC of 85 studies was 0.88 (95%CI, 0.85-0.90). The AUC of the clinical comprehensive diagnosis and conventional test groups was 0.92 (95%CI, 0.89-0.94) and 0.82 (95%CI, 0.78-0.85), respectively. The results of subgroup analysis indicated that the PLR and NLR were 12.67 (95%CI, 6.01-26.70) and 0.05 (95%CI, 0.03-0.10), respectively, in arthrosis infections. The PLR was 24.41 (95%CI, 5.70-104.58) in central system infections and the NLR of immunocompromised patients was 0.08 (95%CI, 0.01-0.62). ConclusionmNGS demonstrated satisfactory diagnostic performance for infections, especially for bone and joint infections and central system infections. Moreover, mNGS also has a high value in the exclusion of infection in immunocompromised patients.

Smartphone-readable RPA-LFA for the high-sensitivity detection of Leishmania kDNA using nanophosphor reporters.

Early diagnosis of infectious diseases improves outcomes by enabling earlier delivery of effective treatment, and helps prevent further transmission by undiagnosed persons. We demonstrated a proof-of-concept assay combining isothermal amplification and lateral flow assay (LFA) for early diagnosis of cutaneous leishmaniasis, a vector-borne infectious disease that affects ca. 700,000 to 1.2 million people annually. Conventional molecular diagnostic techniques based on polymerase chain reaction (PCR) require complex apparatus for temperature cycling. Recombinase polymerase amplification (RPA) is an isothermal DNA amplification method that has shown promise for use in low-resource settings. Combined with lateral flow assay as the readout, RPA-LFA can be used as a point-of-care diagnostic tool with high sensitivity and specificity, but reagent costs can be problematic. In this work, we developed a highly-sensitive smartphone-based RPA-LFA for the detection of Leishmania panamensis DNA using blue-emitting [(Sr0.625Ba0.375)1.96Eu0.01Dy0.03]MgSi2O7 (SBMSO) persistent luminescent nanophosphors as LFA reporters. The greater detectability of nanophosphors allows the use of a reduced volume of RPA reagents, potentially reducing the cost of RPA-LFA. The limit of detection (LOD) of RPA with gold nanoparticle-based LFA readout is estimated at 1 parasite per reaction, but LOD can be 100-fold better, 0.01 parasites per reaction, for LFA based on SBMSO. This approach may be useful for sensitive and cost-effective point-of-care diagnosis and contribute to improved clinical and economic outcomes, especially in resource-limited settings.

CRV-NET: Robust Intensity Recognition of Coronavirus in Lung Computerized Tomography Scan Images.

The early diagnosis of infectious diseases is demanded by digital healthcare systems. Currently, the detection of the new coronavirus disease (COVID-19) is a major clinical requirement. For COVID-19 detection, deep learning models are used in various studies, but the robustness is still compromised. In recent years, deep learning models have increased in popularity in almost every area, particularly in medical image processing and analysis. The visualization of the human body's internal structure is critical in medical analysis; many imaging techniques are in use to perform this job. A computerized tomography (CT) scan is one of them, and it has been generally used for the non-invasive observation of the human body. The development of an automatic segmentation method for lung CT scans showing COVID-19 can save experts time and can reduce human error. In this article, the CRV-NET is proposed for the robust detection of COVID-19 in lung CT scan images. A public dataset (SARS-CoV-2 CT Scan dataset), is used for the experimental work and customized according to the scenario of the proposed model. The proposed modified deep-learning-based U-Net model is trained on a custom dataset with 221 training images and their ground truth, which was labeled by an expert. The proposed model is tested on 100 test images, and the results show that the model segments COVID-19 with a satisfactory level of accuracy. Moreover, the comparison of the proposed CRV-NET with different state-of-the-art convolutional neural network models (CNNs), including the U-Net Model, shows better results in terms of accuracy (96.67%) and robustness (low epoch value in detection and the smallest training data size).

Next Generation Infectious Diseases Monitoring Gages via Incremental Federated Learning: Current Trends and Future Possibilities.

Infectious diseases are always alarming for the survival of human life and are a key concern in the public health domain. Therefore, early diagnosis of these infectious diseases is a high demand for modern-era healthcare systems. Novel general infectious diseases such as coronavirus are infectious diseases that cause millions of human deaths across the globe in 2020. Therefore, early, robust recognition of general infectious diseases is the desirable requirement of modern intelligent healthcare systems. This systematic study is designed under Kitchenham guidelines and sets different RQs (research questions) for robust recognition of general infectious diseases. From 2018 to 2021, four electronic databases, IEEE, ACM, Springer, and ScienceDirect, are used for the extraction of research work. These extracted studies delivered different schemes for the accurate recognition of general infectious diseases through different machine learning techniques with the inclusion of deep learning and federated learning models. A framework is also introduced to share the process of detection of infectious diseases by using machine learning models. After the filtration process, 21 studies are extracted and mapped to defined RQs. In the future, early diagnosis of infectious diseases will be possible through wearable health monitoring cages. Moreover, these gages will help to reduce the time and death rate by detection of severe diseases at starting stage.

A simple polystyrene microfluidic device for sensitive and accurate SERS-based detection of infection by malaria parasites.

Early and accurate detection of infection by pathogenic microorganisms, such as Plasmodium, the causative agent of malaria, is critical for clinical diagnosis and ultimately determines the patient's outcome. We have combined a polystyrene-based microfluidic device with an immunoassay which utilises Surface-Enhanced Raman Spectroscopy (SERS) to detect malaria. The method can be easily translated to a point-of-care testing format and shows excellent sensitivity and specificity, when compared to the gold standard for laboratorial detection of Plasmodium infections. The device can be fabricated in less than 30 min by direct patterning on shrinkable polystyrene sheets of adaptable three-dimensional microfluidic chips. To validate the microfluidic system, samples of P. falciparum-infected red blood cell cultures were used. The SERS-based immunoassay enabled the detection of 0.0012 ± 0.0001% parasitaemia in a P. falciparum-infected red blood cell culture supernatant, an ∼7-fold higher sensitivity than that attained by most rapid diagnostic tests. Our approach successfully overcomes the main challenges of the current Plasmodium detection methods, including increased reproducibility, sensitivity, and specificity. Furthermore, our system can be easily adapted for detection of other pathogens and has excellent properties for early diagnosis of infectious diseases, a decisive step towards lowering their high burden on healthcare systems worldwide.

Recent Development in Plasmonic Nanobiosensors for Viral DNA/RNA Biomarkers

Recently, due to the coronavirus pandemic, the need for early diagnosis of infectious diseases, including viruses, is emerging. Though early diagnosis is essential to prevent infection and progression to severe illness, there are few technologies that accurately measure low concentrations of biomarkers. Plasmonic nanomaterials are attracting materials that can effectively amplify various signals, including fluorescence, Raman, and other optical and electromagnetic output. In this review, we introduce recently developed plasmonic nanobiosensors for measuring viral DNA/RNA as potential biomarkers of viral diseases. In addition, we discuss the future perspective of plasmonic nanobiosensors for DNA/RNA detection. This review is expected to help the early diagnosis and pathological interpretation of viruses and other diseases.

Rapid Discrimination of Bacterial Drug Resistivity by Array-Based Cross-Validation Using 2D MoS2.

The precise discrimination of microbes based on family, class and drug resistivity is essential for the early diagnosis of infectious diseases. Information about the type and strength of drug resistivity can help the analyst to prescribe a suitable antibiotic at the proper dosage to completely eradicate microbes without giving them a chance to gain further resistance. Herein, we propose a sensor array based on the use of cationic two-dimensional MoS2 units and green fluorescence protein as building blocks. Cationic surfaces of receptors with various functionality were suitable for tunable interaction with anionic surfaces of microbes. The array successfully discriminates six different bacterial strains. The versatile ability of the receptors to bind with the wild-type as well as the corresponding ampicillin-resistant strain contributed significantly to rapid detection with high sensitivity. The optimized array was able to classify five different types and three different extents of drug-resistant variants of Escherichia coli by using bacteria cells and lysates. Finally, we have introduced the cross identification method using both bacteria cells and lysates and we found a great enhancement of detection in sensitivity and accuracy. This is the first report of this approach, which can be extended to many other methods for better accuracy in array-based detection.

Multifunctional carbon nanomaterials for diagnostic applications in infectious diseases and tumors.

Infectious diseases (such as Corona Virus Disease 2019) and tumors pose a tremendous challenge to global public health. Early diagnosis of infectious diseases and tumors can lead to effective control and early intervention of the patient's condition. Over the past few decades, carbon nanomaterials (CNs) have attracted widespread attention in different scientific disciplines. In the field of biomedicine, carbon nanotubes, graphene, carbon quantum dots and fullerenes have the ability of improving the accuracy of the diagnosis by the improvement of the diagnostic approaches. Therefore, this review highlights their applications in the diagnosis of infectious diseases and tumors over the past five years. Recent advances in the field of biosensing, bioimaging, and nucleic acid amplification by such CNs are introduced and discussed, emphasizing the importance of their unique properties in infectious disease and tumor diagnosis and the challenges and opportunities that exist for future clinical applications. Although the application of CNs in the diagnosis of several diseases is still at a beginning stage, biosensors, bioimaging technologies and nucleic acid amplification technologies built on CNs represent a new generation of promising diagnostic tools that further support their potential application in infectious disease and tumor diagnosis.

Microfluidic Point-of-Care (POC) Devices in Early Diagnosis: A Review of Opportunities and Challenges.

The early diagnosis of infectious diseases is critical because it can greatly increase recovery rates and prevent the spread of diseases such as COVID-19; however, in many areas with insufficient medical facilities, the timely detection of diseases is challenging. Conventional medical testing methods require specialized laboratory equipment and well-trained operators, limiting the applicability of these tests. Microfluidic point-of-care (POC) equipment can rapidly detect diseases at low cost. This technology could be used to detect diseases in underdeveloped areas to reduce the effects of disease and improve quality of life in these areas. This review details microfluidic POC equipment and its applications. First, the concept of microfluidic POC devices is discussed. We then describe applications of microfluidic POC devices for infectious diseases, cardiovascular diseases, tumors (cancer), and chronic diseases, and discuss the future incorporation of microfluidic POC devices into applications such as wearable devices and telemedicine. Finally, the review concludes by analyzing the present state of the microfluidic field, and suggestions are made. This review is intended to call attention to the status of disease treatment in underdeveloped areas and to encourage the researchers of microfluidics to develop standards for these devices.

High throughput molecularly imprinted polymers based electrochemical nanosensors for point-of-care diagnostics of COVID-19

The importance of early diagnosis of infectious disease has been revealed well by the COVID-19 pandemic. The current methods for testing SARS-CoV-2 mainly utilize biorecognition elements. The process of production of these biorecognition elements is not only tedious, time-consuming but also costly. The molecularly imprinted polymers recently have gained considerable attention as they are stable and also offer high selectivity and specificity than conventional labels. The present review discussed the MIPs-based electrochemical nano-sensors diagnostic of SARS-CoV-2.

Electric field-enhanced electrochemical CRISPR biosensor for DNA detection

DNA detection plays an important role in the rapid screening of cancers and early diagnosis of infectious diseases. Here, we developed a simple, versatile, electric field-enhanced (EFE), electrochemical CRISPR biosensor to detect DNA targets in a homogeneous solution phase. To improve the detection sensitivity, we applied a pulsed electric field to enrich nucleic acids on the electrode surface. The EFE electrochemical CRISPR biosensor takes advantage of the diffusivity difference between electrochemical oligonucleotide probes and CRISPR-cleaved probes toward a negatively charged working electrode, enabling simple and sensitive electrochemical detection of DNA without the need for complicated immobilization processing of electrochemical probes. Our developed CRISPR biosensor directly detects unamplified human papillomavirus-16 (HPV-16) DNA with a sensitivity of 1 pM. Further, the EFE electrochemical CRISPR biosensor coupled with recombinase polymerase amplification (RPA) successfully detects HPV-16 DNA in clinical samples. Thus, the EFE electrochemical CRISPR biosensor provides a simple, robust, and sensitive detection method for nucleic acid-based molecular diagnostics.

Разработка практического руководства по инфекционным болезням с элементами цифровых технологий

A doctor of any specialty in his practice is faced with an infectious pathology, in connection with which the early diagnosis of infectious diseases is important both from a clinical and epidemiological standpoint. The aim - design and development of a unified practical guide to infectious diseases with elements of digitalization of content on pharmacotherapy. Material and methods. When developing the structure of the practical guide “Tactics of an infectious disease doctor”, prototypes of educational and methodological materials were worked out. The structure of the practical guide included socially significant infectious diseases of viral, bacterial etiology, the most important helminthiases and protozoses, which practitioners of various specialties may encounter, both in inpatient and outpatient settings. Results and discussion. In the practical guide “Tactics of an infectious disease doctor” all nosologies are presented in a unified form: a brief definition of nosologies, characteristics of the etiological agent, epidemic process, clinical classification, examples of the formulation of a diagnosis, diagnosis, organization of medical care, treatment, pharmacotherapy, approximate terms of temporary disability, criteria recovery, rehabilitation, dispensary observation, recommendations for treatment and prevention. The practical guide contains a short guide to medicines. An innovation is the presentation of medicines via a QR code. Also, by means of a QR code, it is possible to switch to the electronic version of the practical guide. Recommendations for the prevention of infectious diseases are given in the form of pictographic diagrams. Conclusion. The practical guide “Tactics of an infectious disease doctor” allows primary care physicians and general practitioners in a short time period to make the optimal decision on the tactics of managing patients with infectious diseases, within the framework of modern clinical guidelines and approaches set out in national guidelines. © 2021 Infectious Diseases: News, Opinions, Training. All rights reserved.

Recent advances in sensitive surface-enhanced Raman scattering-based lateral flow assay platforms for point-of-care diagnostics of infectious diseases

This review reports the recent advances in surface-enhanced Raman scattering (SERS)-based lateral flow assay (LFA) platforms for the diagnosis of infectious diseases. As observed through the recent infection outbreaks of COVID-19 worldwide, a timely diagnosis of the disease is critical for preventing the spread of a disease and to ensure epidemic preparedness. In this regard, an innovative point-of-care diagnostic method is essential. Recently, SERS-based assay platforms have received increasing attention in medical communities owing to their high sensitivity and multiplex detection capability. In contrast, LFAs provide a user-friendly and easily accessible sensing platform. Thus, the combination of LFAs with a SERS detection system provides a new diagnostic modality for accurate and rapid diagnoses of infectious diseases. In this context, we briefly discuss the recent application of LFA platforms for the POC diagnosis of SARS-CoV-2. Thereafter, we focus on the recent advances in SERS-based LFA platforms for the early diagnosis of infectious diseases and their applicability for the rapid diagnosis of SARS-CoV-2. Finally, the key issues that need to be addressed to accelerate the clinical translation of SERS-based LFA platforms from the research laboratory to the bedside are discussed.

Recognising the asymptomatic enemy

Respiratory infections are the leading cause of hospital admission, particularly in patients with chronic conditions, patients who are immunocompromised, and in adults older than 70 years and paediatric patients. These infections cause considerable morbidity and mortality, and subsequently result in high direct and indirect costs, particularly during epidemics and disease outbreaks.1 The early diagnosis of infectious diseases is essential in clinical practice to better manage patients and their close contacts to avoid the spread of disease causing microorganisms.

Infectious Diseases in Internationally Adopted Children and Intercountry Discrepancies Among Screening Protocols, A Narrative Review.

Internationally adopted children (IAC) require thorough health assessments at time of arrival in the host country. As these children are at higher risk for infectious diseases, such as gastrointestinal parasites, tuberculosis, hepatitis, syphilis, and human immunodeficiency virus, early diagnosis of infectious diseases is fundamental for the optimal management of the child and, also, to reduce the risk of transmission to the adopting community. Comparative analysis of the screening protocols adopted in Europe, the United States, and Canada revealed different approaches to the adopted children. A homogeneous and internationally shared standard of care in the management of IAC should be provided.