Applications of sequencing technology in clinical microbial infection.

Application of Nanopore Sequencing Technology in the Clinical Diagnosis of Infectious Diseases

Chapter 26 - Development of biosensor-based technology for the detection of pathogenic microorganisms and biomolecules in dairy products

To analyze the role of artificial intelligence technology in the diagnosis and treatment of the COVID-19. To study the application progress and characteristics of artificial intelligence technology in CT image diagnosis, routine outpatient data diagnosis and complication prediction of COVID-19, and analyze the performance of the algorithm and the clinical benefits obtained in the process of diagnosis and treatment. The performance of artificial intelligence technology in assisted diagnosis of the diagnosis and prediction of complications is relatively satisfactory. Artificial intelligence technology can help medical institutions effectively alleviate the shortage of medical resources, improve diagnosis efficiency and treatment quality in the COVID-19 epidemic. Related models have good clinical application value.

This study uses the method of literature review and case analysis to sort out and evaluate the relevant literature, and discusses the specific application of gene detection technology in the diagnosis, treatment and prevention of chronic diseases combined with actual cases. By analyzing the application of gene detection technology in the field of chronic diseases, the role of gene detection technology in early diagnosis, personalized treatment and prevention strategy is discussed. The results show that the gene detection technology has a broad application prospect in the diagnosis and treatment of chronic diseases, which is of great significance to improve the diagnosis and treatment efficiency and the level of personalized medicine, and provides a useful reference for clinicians and researchers.

A novel electrochemical nanogenosensor devoted to clinical analysis is reported for label-free detection of pathogenic microorganisms in the present work. The designed biosensor is composed of graphene oxide-modified disposable pencil graphite electrodes as a sensing platform. Escherichia coli is used as a model case. A 5'-aminohexyl-linked 22-base sequence probe representing the E. coli amplicon is immobilized onto sensor surfaces via carbodiimide chemistry. Hybridization is performed with denatured PCR amplicons of the bacteria. Detection is realized by transduction with the electrochemical impedance spectrometry technique. The selectivity of the designed genosensor is measured using Mycobacterium tuberculosis and Klebsiella pneumoniae sequences. Outstanding sensitivity is achieved with this genosensor array platform with a detection limit of 102 nM. This platform offers promise for rapid, simple, and cost-effective detection of various pathogenic microorganisms.

To assess the value of next‐generation sequencing (NGS) technology in the diagnosis of osteoarticular brucellosis pathogenesis. Fifty eight patients admitted to the Department of Orthopaedics, Hebei Provincial Chest Hospital from January 2021 to January 2023 were retrospectively analyzed, and the patients were classified into 48 cases in the osteoarticular brucellosis group and 10 cases in the nonosteoarticular brucellosis group according to the final clinical diagnosis. All patients underwent serum agglutination test (SAT), CT‐guided puncture or surgical sampling of lesions for bacteriological culture and NGS after admission. The diagnostic efficacy of these three methods for osteoarticular brucellosis was compared using the final clinical diagnosis as the reference standard. Among the 58 patients with suspected osteoarticular brucellosis, 40 cases (68.97%) were positive by NGS, 33 cases (56.89%) by SAT and 10 cases (17.24%) by culture, and the differences were statistically significant (p < 0.05). Using the final clinical diagnosis as a criterion, the sensitivity of NGS, SAT, and culture for the detection of osteoarticular brucellosis was 83.33%, 62.50%, and 20.83%, respectively, the specificity was 100.00%, 70.00%, and 100.00%, the diagnostic accuracy was 86.20%, 63.79%, and 34.49%, and the κ values were 0.799, 0.590, and 0.504, respectively. NGS has a high pathogen detection rate and sensitivity in the pathogenetic diagnosis of patients with osteoarticular brucellosis and can provide clinical guidance for the diagnosis and management of patients with osteoarticular brucellosis.

<b>Objective:</b> To analyze the microbiological characteristics of patients with severe burns caused by blast in different periods and explore the application value of metagenomics next-generation sequencing (mNGS) in detecting pathogenic microorganisms. <b>Methods:</b> The retrospective observational study was applied. From June 13 to September 13, 2020, twenty-three patients (21 males and 2 females) with severe burns caused by blast who met the inclusion criteria were admitted to the Second Affiliated Hospital of Zhejiang University School of Medicine, with age of (64±5) years and total burn area of (86±14) % total body surface area. Abbreviated burn severity index (ABSI) score, revised Baux score, acute physiology and chronic health status evaluation (APACHE) Ⅱscore, and sequential organ failure assessment (SOFA) score were counted on admission. Within 7, 8-20 and 21-30 d after admission, the complications, infection source and distribution of pathogenic microorganisms in patients were recorded. The detection of pathogenic microorganisms was analyzed, and the difference in detection efficiency between microbial culture method and mNGS was compared. After admission, the infection of overall source distribution of pathogenic microorganisms in patients was analyzed, and the difference in detection efficiency between microbial culture method and mNGS was compared. Data were statistically analyzed with McNemar and Fisher exact probability test. <b>Results:</b> On admission, ABSI score, revised Baux score, APACHE Ⅱ score and SOFA score were (12.6±2.4), (91±22), (26±4), and (10.3±2.3) respectively. Within 7 d after admission, the main complications of patients were inhalation injury, septic shock, and hypoproteinemia. Patients were mainly infected with pathogenic microorganism on wound, blood stream, and lung. Within 8-20 d after admission, the incidence of septic shock was the highest. The incidence of inhalation injury was significantly lower than that of ≤7 d after admission (<i>P</i><0.01), the main source of infection were wound, lung, and blood stream, and the incidence of wound and blood stream infection were significantly lower than that of ≤7 d after admission (<i>P</i><0.01). Within 21-30 d after admission, the incidences of multiple organ failure and acute respiratory distress syndrome were low, the incidence of inhalation injury was significantly lower than that of ≤7 d after admission (<i>P</i><0.01), and the incidence of septic shock was significantly lower than that of ≤7 d after admission (<i>P</i><0.01) and 8-20 d after admission (<i>P</i><0.01). There were only low bloodstream infections, and the incidence of wound infection was significantly lower than that of ≤7 d after admission (<i>P</i><0.01) and 8-20 d after admission (<i>P</i><0.05), and the incidences of lung and blood stream infection were significantly lower than those of ≤7 d after admission (<i>P</i><0.01). Within ≤7 d after admission, gram-positive bacteria were mainly <i>Staphylococcus aureus</i>. Gram-negative bacteria were mainly <i>Klebsiella pneumoniae</i> and <i>Stenotrophomonas maltophilia</i>. The fungi contained only <i>Candida</i>. Within 8-20 d after admission, <i>Staphylococcus aureus</i> was mainly the gram-positive bacteria, and the detection rate of <i>Enterococcus</i> was significantly lower than that of ≤7 d after admission (<i>P</i><0.01). <i>Pseudomonas aeruginosa</i> and <i>Acinetobacter baumannii</i> were the main gram-negative bacteria, and their detection rates were significantly lower than those of ≤7 d after admission (<i>P</i><0.01).There was a new detection of <i>Fusarium</i>. Within 21-30 d after admission, <i>Staphylococcus aureus</i> was the mainly gram-positive bacteria, and the detection rates of <i>Enterococcus</i> and <i>Bacillus</i> were significantly lower than those of ≤7 d after admission (<i>P</i><0.01). <i>Pseudomonas aeruginosa</i> and <i>Acinetobacter baumannii</i> were still the main gram-negative bacteria, and increased with the extension of time after admission. The detection rate of <i>Pseudomonas aeruginosa</i> was significantly higher than that of ≤7 d after admission (<i>P</i><0.01) and 8-20 d after admission (<i>P</i><0.01), and the detection rate of <i>Acinetobacter baumannii</i> was significantly higher than that of ≤7 d after admission (<i>P</i><0.01). The detection rate of <i>Klebsiella pneumoniae</i> was significantly lower than those of ≤7 d after admission (<i>P</i><0.01) and 8-20 d after admission (<i>P</i><0.01). All <i>Candida, Mould, Fusarium</i> were detected. Within ≤7 d and 8-20 d, the consistency between mNGS and bacterial culture was high (<i>κ</i>=0.659, 0.596). Within 21-30 d after admission, the consistency between mNGS and bacterial culture was moderate (<i>κ</i>=0.407). In different time periods, the positive test rate of mNGS was basically constant, while that of microbial culture showed a decline with the extension time after admission. Five hundred and six strains of pathogenic microorganisms were isolated from wound, blood, sputum, and indwelling catheter, and <i>Staphylococcus aureus</i>, <i>Pseudomonas aeruginosa</i>, <i>Acinetobacter baumannii</i>, <i>Klebsiella pneumoniae</i> were the main pathogenic microorganisms. <i>Pseudomonas aeruginosa</i> and <i>Acinetobacter baumannii</i> were the most common in the wound samples, <i>Klebsiella pneumoniae</i> was more often seen in blood samples while <i>Pseudomonas aeruginosa</i> and <i>Acinetobacter baumannii</i> in sputum samples, and <i>Acinetobacter baumannii</i> in indwelling catheter samples were the most common. The detection rates of <i>Pseudomonas aeruginosa</i> in wound and sputum were significantly higher than those of blood (<i>P</i><0.05 or <i>P</i><0.01) and indwelling catheter (<i>P</i><0.01), respectively. The consistency between the overall results of mNGS and microbial culture were moderate (<i>κ</i>=0.556). The consistency between mNGS and microbial culture was high in samples of blood and indwelling catheter (<i>κ</i>=0.631, 0.619), but those were moderate in sputum and wound (<i>κ</i>=0.558, 0.528). <b>Conclusions:</b> The most common infections of patients with severe burn caused by blast injury were wound infection and blood stream infection. With the extension of time after admission, the main pathogenic bacterial strains of patients changed from <i>Staphylococcus aureus</i>, <i>Klebsiella pneumoniae</i>, and <i>Stenotrophomonas maltophilia</i> to <i>Acinetobacter baumannii</i> and <i>Pseudomonas aeruginosa</i>. mNGS showed a higher positive rate of detecting pathogenic microorganisms than conventional microbial culture.

Genomic screening of the general adult population: key concepts for assessing net benefit with systematic evidence reviews.

The detection and prediction of pathogenic microorganisms play a crucial role in the sustainable development of the aquaculture industry. Currently, researchers mainly focus on the prediction of water quality parameters such as dissolved oxygen for early warning. To provide early warning directly from the pathogenic source, this study proposes an innovative approach for the detection and prediction of pathogenic microorganisms based on yellow croaker aquaculture. Specifically, a method based on quantitative polymerase chain reaction (qPCR) is designed to detect the Cryptocaryon irritans (Cri) pathogenic microorganisms. Furthermore, we design a predictive combination model for small samples and high noise data to achieve early warning. After performing wavelet analysis to denoise the data, two data augmentation strategies are used to expand the dataset and then combined with the BP neural network (BPNN) to build the fusion prediction model. To ensure the stability of the detection method, we conduct repeatability and sensitivity tests on the designed qPCR detection technique. To verify the validity of the model, we compare the combined BPNN to long short-term memory (LSTM). The experimental results show that the qPCR method provides accurate quantitative measurement of Cri pathogenic microorganisms, and the combined model achieves a good level. The prediction model demonstrates higher accuracy in predicting Cri pathogenic microorganisms compared to the LSTM method, with evaluation indicators including mean absolute error (MAE), recall rate, and accuracy rate. Especially, the accuracy of early warning is increased by 54.02%.

Application of high-throughput sequencing technologies and analytical tools for pathogen detection in urban water systems: Progress and future perspectives

Objective:The arrival of precision medicine plan brings new opportunities and challenges for patients undergoing precision diagnosis and treatment of malignant tumors. With the development of medical imaging, information on different modality imaging can be integrated and comprehensively analyzed by imaging fusion system. This review aimed to update the application of multimodality imaging fusion technology in the precise diagnosis and treatment of malignant tumors under the precision medicine plan. We introduced several multimodality imaging fusion technologies and their application to the diagnosis and treatment of malignant tumors in clinical practice.Date Sources:The data cited in this review were obtained mainly from the PubMed database from 1996 to 2016, using the keywords of “precision medicine”, “fusion imaging”, “multimodality”, and “tumor diagnosis and treatment”.Study Selection:Original articles, clinical practice, reviews, and other relevant literatures published in English were reviewed. Papers focusing on precision medicine, fusion imaging, multimodality, and tumor diagnosis and treatment were selected. Duplicated papers were excluded.Results:Multimodality imaging fusion technology plays an important role in tumor diagnosis and treatment under the precision medicine plan, such as accurate location, qualitative diagnosis, tumor staging, treatment plan design, and real-time intraoperative monitoring. Multimodality imaging fusion systems could provide more imaging information of tumors from different dimensions and angles, thereby offing strong technical support for the implementation of precision oncology.Conclusion:Under the precision medicine plan, personalized treatment of tumors is a distinct possibility. We believe that multimodality imaging fusion technology will find an increasingly wide application in clinical practice.

3D printing technology is an increasing approach consisting of material manufacturing through the selective incremental delamination of materials to form a 3D structure to produce products. This technology has different advantages, including low cost, short time, diversification, and high precision. Widely adopted additive manufacturing technologies enable the creation of diagnostic tools and expand treatment options. Coupled with its rapid deployment, 3D printing is endowed with high customizability that enables users to build prototypes in shorts amounts of time which translates into faster adoption in the medical field. This review mainly summarizes the application of 3D printing technology in the diagnosis and treatment of cancer, including the challenges and the prospects combined with other technologies applied to the medical field.

To explore the key technical points and value of cell transfer technology in the diagnosis of micro-volume cell fluid. In the study, 32 micro-volume cell fluid samples with the diagnosis of tumor or atypical cells in the Department of Pathology, Peking University First Hospital were collected from September 2024 to June 2025. The cells on the ThinPrep cytology test (TCT) slides were divided into several sections and transferred to corresponding slides for immunocytochemistry (ICC) and special staining. Hematoxylin-eosin (HE) staining slides before and after transfer were compared to evaluate the performance of cell transfer technology in maintaining the consistency of cell morphology. The re-diagnosis referring to the results of ICC and special staining of transfer slides were made. The diagnosis before and after cell transfer was compared to evaluate the value of technology in improving the differential diagnostic accuracy. A total of 140 cell transfer slides were prepared from the 32 samples. Among them, 32 HE-stained slides were consistent with the original TCT slides in terms of staining quality, cell morphology and arrangement, with a success rate of 100%; 99 transfer slides were immuno-stained, of which 91 had accurate color and position of positivity and clear background of negativity, with a success rate of 91.91%; 9 special-stained slides had sharp color contrast and clear background, with a success rate of 100%. With the help of ICC and special staining results of transfer slides, 26 of the 32 samples were accurately diagnosed, including 18 cases of malignant tumors and 8 cases of non-neoplastic lesions; 6 cases remained undiagnosed, including four due to ICC staining failure and two due to too few cells. Compared with the original cytological diagnosis, a definitive differential diagnosis was obtained in 81.25% of cases after cell transfer. The application of cell transfer technology in TCT samples is feasible in clinical practice and is suitable for cases requiring ICC and special staining for auxiliary diagnosis. It can significantly improve the differential diagnostic accuracy for the micro-volume cell fluid samples, which is invaluable for the special cases which pathological diagnosis can only be made based on the micro-volume cell fluid samples because no more tissue sample is available.

The combination of artificial intelligence (AI) technology and medicine is an important milestone in the development of modern medicine, which realizes the digitalization and intelligence for clinicians in the process of diagnosis and treatment. This is not a competition between human and machine, but a collaborative progress and development. The incidence of colorectal cancer remains high in China. The introduction of AI technology in lymph node metastasis, circumferential resection margin, neoadjuvant therapy, genetic diagnosis, radiomics, pathological assistance and colonoscopy diagnosis has further improved the diagnosis and treatment, as well as the evaluation and prediction of the disease of colorectal cancer. This article will review and comment on the application of AI technology in colorectal cancer staging, neoadjuvant therapy, gene diagnosis, pathological assistance and other aspects.

Ultrasound technology is widely used in the diagnosis and evaluation of kidney diseases and in guiding some invasive procedures. Ultrasound has the advantages of low price, no radiation, convenience, and being easy to operate compared with other imaging methods. In recent years, new ultrasound technology has been developed. For example, studies have shown that ultrasound can protect against acute kidney injury and chronic kidney disease by activating the spleen cholinergic anti-inflammatory pathway. Through microbubble technology, contrast-enhanced ultrasound can more accurately assess the nature of renal lesions. Ultrasound-targeted microbubbles can also direct the release of drugs and genes to the lesions of interest. This article will review the research progress of ultrasound technology in the diagnosis and treatment of kidney diseases. Key words: Ultrasound; Kidney disease; Diagnosis and treatment; Progress