rapid-detection-fecal-antigen-helicobacter-pylori-infection-based-on

Rapid Detection of Fecal Antigen of <em>Helicobacter pylori</em> Infection Based on Double Antibody Sandwich Detection Technology

Helicobacter pylori can be parasitic in gastric mucosa, which can cause a series of gastrointestinal diseases after infection and is closely related to ...

Southern Medical University

 and enterotoxigenic  (ETEC) are major bacterial pathogens of diarrheal disease that is the second leading cause of childhood mortality globally. Currently, it is well known that  spp., and .  are very closely related with many common characteristics. Evolutionarily speaking,  spp., are positioned within the phylogenetic tree of . . Therefore, discrimination of  spp., from .  is very difficult. Many methods have been developed with the aim of differentiating the two species, which include but not limited to biochemical tests, nucleic acids amplification, and mass spectrometry, etc. However, these methods suffer from high false positive rates and complicated operation procedures, which requires the development of novel methods for accurate and rapid identification of  spp., and . . As a low-cost and non-invasive method, surface enhanced Raman spectroscopy (SERS) is currently under intensive study for its diagnostic potential in bacterial pathogens, which is worthy of further investigation for its application in bacterial discrimination. In this study, we focused on clinically isolated .  strains and  species (spp.), that is, . , . , . , and . , based on which SERS spectra were generated and characteristic peaks for  spp., and .  were identified, revealing unique molecular components in the two bacterial groups. Further comparative analysis of machine learning algorithms showed that, the Convolutional Neural Network (CNN) achieved the best performance and robustness in bacterial discrimination capacity when compared with Random Forest (RF) and Support Vector Machine (SVM) algorithms. Taken together, this study confirmed that SERS paired with machine learning could achieve high accuracy in discriminating  spp., from . , which facilitated its application potential for diarrheal prevention and control in clinical settings. Graphical abstract.

Rapid discrimination of  spp. and  label-free surface enhanced Raman spectroscopy coupled with machine learning algorithms.

Central nervous system leukemia (CNSL) is one of the main causes of recurrence and death in patients with acute leukemia. This study aims to dynamically monitor minimal residual disease (MRD) in cerebrospinal fluid and bone marrow of patients with different types of acute leukemia by flow cytometry (FCM), and to compare the timeliness and consistency of MRD detection between the 2 methods to further explore the application value of monitoring MRD in cerebrospinal fluid.

Clinical significance of flow cytometry in detection of minimal residual disease in cerebrospinal fluid.

Bacterial species within the Acinetobacter baumannii-calcoaceticus (Acb) complex are very similar and are difficult to discriminate. Misidentification of these species in human infection may lead to severe consequences in clinical settings. Therefore, it is important to accurately discriminate these pathogens within the Acb complex. Raman spectroscopy is a simple method that has been widely studied for bacterial identification with high similarities. In this study, we combined surfaced-enhanced Raman spectroscopy (SERS) with a set of machine learning algorithms for identifying species within the Acb complex. According to the results, the support vector machine (SVM) model achieved the best prediction accuracy at 98.33% with a fivefold cross-validation rate of 96.73%. Taken together, this study confirms that the SERS-SVM method provides a convenient way to discriminate between A. baumannii, Acinetobacter pittii, and Acinetobacter nosocomialis in the Acb complex, which shows an application potential for species identification of Acinetobacter baumannii-calcoaceticus complex in clinical settings in near future.

Differentiation of closely-related species within Acinetobacter baumannii-calcoaceticus complex via Raman spectroscopy: a comparative machine learning analysis.

Haemoglobinopathy refers to a group of common monogenic inherited conditions associated with variations in the haemoglobin molecule; however, there is relatively limited reporting on abnormal haemoglobinopathy in the Chinese population, especially rare abnormal haemoglobin (Hb). The aim of this study was to explore the clinical characteristics of haemoglobinopathy to supplement data for the epidemiological investigation of Hb variants in Guangdong province of China.

Analysis of the Haematological Phenotype and Molecular Characteristics of Rare Abnormal Haemoglobin.

Yes-associated protein 1 (YAP1) plays a pivotal role in promoting the progression of hepatocellular carcinoma (HCC). Emerging evidence shows that inducing YAP1 degradation represents a promising strategy. Here, we identified USP24 as a bona fide deubiquitinating enzyme for YAP1. USP24 directly interacts with and deubiquitinates YAP1, thereby stabilizing YAP1 protein levels. Clinically, USP24 was significantly upregulated in HCC tissues and correlated with poor patient prognosis. Depletion of USP24 significantly suppressed the proliferation of HCC cells in vitro, which could be rescued by restoration of YAP1. Consistent with these findings, USP24 knockdown inhibited tumor growth in a xenograft mouse model. Overall, our study reveals that the USP24/YAP1 axis plays a critical role in the malignant progression of HCC, thus providing rationale for potential therapeutic interventions for YAP1-driven HCC.

Article	Year
Rapid discrimination of spp. and label-free surface enhanced Raman spectroscopy coupled with machine learning algorithms. Frontiers in microbiology\| PubMed ID: 36970678	2023
Clinical significance of flow cytometry in detection of minimal residual disease in cerebrospinal fluid. Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences\| PubMed ID: 38448377	2023
Differentiation of closely-related species within Acinetobacter baumannii-calcoaceticus complex via Raman spectroscopy: a comparative machine learning analysis. World journal of microbiology & biotechnology\| PubMed ID: 38538920	2024
Analysis of the Haematological Phenotype and Molecular Characteristics of Rare Abnormal Haemoglobin. Molecular genetics & genomic medicine\| PubMed ID: 39262298	2024
USP24 promotes hepatocellular carcinoma progression by deubiquitinating and stabilizing YAP1. Cancer cell international\| PubMed ID: 40287768	2025

Yanfei Luo

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