Rapid and ultrasensitive detection of pathogen-associated biomarkers is vital for the early diagnosis and therapy of bacterial infections. Herein, we developed a close-packed and ordered Au@AgPt array coupled with a cascade triggering strategy for surface-enhanced Raman scattering (SERS) and colorimetric identification of the Staphylococcus aureus biomarker micrococcal nuclease (MNase) in serum samples. The trimetallic Au@AgPt nanozymes can catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) molecules to SERS-enhanced oxidized TMB (oxTMB), accompanied by the color change from colorless to blue. In the presence of S. aureus, the secreted MNase preferentially cut the nucleobase AT-rich regions of DNA sequences on magnetic beads (MBs) to release alkaline phosphatase (ALP), which subsequently mediated the oxTMB reduction for inducing the colorimetric/SERS signal fade away. Using this "on-to-off" triggering strategy, the target S. aureus can be recorded in a wide linear range with a limit of detection of 38 CFU/mL in the colorimetric mode and 6 CFU/mL in the SERS mode. Meanwhile, the MNase-mediated strategy characterized by high specificity and sensitivity successfully discriminated between patients with sepsis (n = 7) and healthy participants (n = 3), as well as monitored the prognostic progression of the disease (n = 2). Overall, benefiting from highly active and dense "hot spot" substrate, MNase-mediated cascade response strategy, and colorimetric/SERS dual-signal output, this methodology will offer a promising avenue for the early diagnosis of S. aureus infection.

SPECT myocardial perfusion imaging (MPI) can obtain many parameters such as myocardial perfusion, morphology, function and mechanical synchronization in one stop, which has become an essential non-invasive examination technique in the diagnosis and treatment of various cardiovascular diseases (CVD). With the continuous development of cardiac SPECT instrument, imaging scheme and image reconstruction algorithm, its application in the diagnosis and treatment of CVD is expanding. This paper reviews the research progress of qualitative, semi-quantitative and quantitative parameters of SPECT MPI in recent years, and expounds the threshold, influencing factors and application value of various parameters.

SPECT myocardial perfusion imaging (MPI) can obtain many parameters such as myocardial perfusion, morphology, function and mechanical synchronization in one stop, which has become an essential non-invasive examination technique in the diagnosis and treatment of various cardiovascular diseases (CVD). With the continuous development of cardiac SPECT instrument, imaging scheme and image reconstruction algorithm, its application in the diagnosis and treatment of CVD is expanding. This paper reviews the research progress of qualitative, semi-quantitative and quantitative parameters of SPECT MPI in recent years, and expounds the threshold, influencing factors and application value of various parameters.

To evaluate the diagnostic performance of a three-gene (GBP5, DUSP3, and TBP) tuberculosis (TB) score in bacteriologically-negative pulmonary tuberculosis, and to develop and validate a discriminative diagnostic model by integrating inflammatory cytokines (IL-2, IL-5, IL-17, and IFN-γ). A prospective cohort study was conducted, a total of 238 patients admitted to the Affiliated Infectious Disease Hospital of Soochow University from May 2023 to May 2024 were enrolled, including 119 pathogen-negative pulmonary tuberculosis patients and 119 patients with other pulmonary diseases (OPD). The GeneXpert MTB-HR kit was used to detect the three-gene TB scores from residual blood routine samples. The diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis. Concurrent data on 12 inflammatory cytokines were collected from patients. Potential biomarkers were screened using univariate analysis and multivariate logistic regression, and selected features were incorporated into the construction of four machine learning models: logistic regression, support vector machine (SVM), K-nearest neighbors (KNN), and adaptive boosting (AdaBoost). The samples were randomly split into a training set (85%) and a test set (15%). The models were trained on the training set, and their diagnostic performance was validated using the test set. The predictive ability of each model was evaluated based on ROC curve parameters. The results showed that the three-gene TB score alone yielded an AUC of 0.539 (sensitivity: 50.94%, specificity: 60.50%) in distinguishing pathogen-negative pulmonary tuberculosis from OPD. Four non-col-linear inflammatory factors (IL-2, IL-5, IL-17, and IFN-γ) were selected and combined with the three-gene TB score to construct machine learning models. The AdaBoost model demonstrated the best performance, achieving an AUC of 0.893 (sensitivity: 85.4%, specificity: 73.0%) in the training set and an AUC of 0.873 (sensitivity: 88.2%, specificity: 72.2%) in the test set. In conclusion,the AdaBoost diagnostic model integrating the three-gene TB score with inflammatory factors (IL-2, IL-5, IL-17, and IFN-γ) exhibits superior discriminating performance for pathogen-negative pulmonary tuberculosis compared to OPD, significantly outperforming the three-gene TB score alone.

Rapid and ultrasensitive detection of pathogen-associated biomarkers is vital for the early diagnosis and therapy of bacterial infections.Herein,we developed a close-packed and ordered Au@AgPt array coupled with a cascade triggering strategy for surface-enhanced Raman scattering(SERS)and colorimetric identification of the Staphylococcus aureus biomarker micrococcal nuclease(MNase)in serum samples.The trimetallic Au@AgPt nanozymes can catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine(TMB)molecules to SERS-enhanced oxidized TMB(oxTMB),accompanied by the color change from colorless to blue.In the presence of S.aureus,the secreted MNase preferentially cut the nucleobase AT-rich regions of DNA sequences on magnetic beads(MBs)to release alkaline phosphatase(ALP),which subsequently mediated the oxTMB reduction for inducing the colorimetric/SERS signal fade away.Using this"on-to-off"triggering strategy,the target S.aureus can be recorded in a wide linear range with a limit of detection of 38 CFU/mL in the colorimetric mode and 6 CFU/mL in the SERS mode.Meanwhile,the MNase-mediated strategy characterized by high specificity and sensitivity successfully discriminated between patients with sepsis(n=7)and healthy participants(n=3),as well as monitored the prog-nostic progression of the disease(n=2).Overall,benefiting from highly active and dense"hot spot"substrate,MNase-mediated cascade response strategy,and colorimetric/SERS dual-signal output,this methodology will offer a promising avenue for the early diagnosis of S.aureus infection.

To evaluate the diagnostic performance of a three-gene (GBP5, DUSP3, and TBP) tuberculosis (TB) score in bacteriologically-negative pulmonary tuberculosis, and to develop and validate a discriminative diagnostic model by integrating inflammatory cytokines (IL-2, IL-5, IL-17, and IFN-γ). A prospective cohort study was conducted, a total of 238 patients admitted to the Affiliated Infectious Disease Hospital of Soochow University from May 2023 to May 2024 were enrolled, including 119 pathogen-negative pulmonary tuberculosis patients and 119 patients with other pulmonary diseases (OPD). The GeneXpert MTB-HR kit was used to detect the three-gene TB scores from residual blood routine samples. The diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis. Concurrent data on 12 inflammatory cytokines were collected from patients. Potential biomarkers were screened using univariate analysis and multivariate logistic regression, and selected features were incorporated into the construction of four machine learning models: logistic regression, support vector machine (SVM), K-nearest neighbors (KNN), and adaptive boosting (AdaBoost). The samples were randomly split into a training set (85%) and a test set (15%). The models were trained on the training set, and their diagnostic performance was validated using the test set. The predictive ability of each model was evaluated based on ROC curve parameters. The results showed that the three-gene TB score alone yielded an AUC of 0.539 (sensitivity: 50.94%, specificity: 60.50%) in distinguishing pathogen-negative pulmonary tuberculosis from OPD. Four non-col-linear inflammatory factors (IL-2, IL-5, IL-17, and IFN-γ) were selected and combined with the three-gene TB score to construct machine learning models. The AdaBoost model demonstrated the best performance, achieving an AUC of 0.893 (sensitivity: 85.4%, specificity: 73.0%) in the training set and an AUC of 0.873 (sensitivity: 88.2%, specificity: 72.2%) in the test set. In conclusion,the AdaBoost diagnostic model integrating the three-gene TB score with inflammatory factors (IL-2, IL-5, IL-17, and IFN-γ) exhibits superior discriminating performance for pathogen-negative pulmonary tuberculosis compared to OPD, significantly outperforming the three-gene TB score alone.

Recently, small nucleolar RNAs (snoRNAs) have transcended the genomic "noise" to emerge as pivotal molecular markers due to their essential roles in tumor progression. Substantial evidence indicates a strong association between snoRNAs and critical clinical features such as tumor pathology and drug resistance. Historically, snoRNA research has concentrated on two classical mechanisms: 2'-O-ribose methylation and pseudouridylation. This review specifically summarizes the novel regulatory mechanisms and functional patterns of snoRNAs in tumors, encompassing transcriptional, post-transcriptional, and post-translational regulation. We further discuss the synergistic effect between snoRNA host genes (SNHGs) and snoRNAs in tumor progression. More importantly, snoRNAs extensively contribute to the development of tumor cell resistance as oncogenes or tumor suppressor genes. Accordingly, we provide a comprehensive review of the clinical diagnosis and treatment associated with snoRNAs and explore their significant potential as novel drug targets.

Coronary flow capacity (CFC) is a relatively new perfusion index reflecting the vasodilator capacity of the coronary circulation, which can be obtained by a variety of invasive or non-invasive methods. CFC, combining stress myocardial blood flow (sMBF) with coronary flow reserve (CFR), can achieve a more comprehensive assessment of myocardial perfusion, thus providing a strong basis of accurate guide in the diagnosis, risk stratification, and treatment strategy of ischemic heart disease. This article reviews CFC and its significance, clinical application and progress.

Recently,small nucleolar RNAs(snoRNAs)have transcended the genomic"noise"to emerge as pivotal molecular markers due to their essential roles in tumor progression.Substantial evidence indicates a strong association between snoRNAs and critical clinical features such as tumor pathology and drug resistance.Historically,snoRNA research has concentrated on two classical mechanisms:2'-O-ribose methylation and pseudouridylation.This review specifically summarizes the novel regulatory mecha-nisms and functional patterns of snoRNAs in tumors,encompassing transcriptional,post-transcriptional,and post-translational regulation.We further discuss the synergistic effect between snoRNA host genes(SNHGs)and snoRNAs in tumor progression.More importantly,snoRNAs extensively contribute to the development of tumor cell resistance as oncogenes or tumor suppressor genes.Accordingly,we provide a comprehensive review of the clinical diagnosis and treatment associated with snoRNAs and explore their significant potential as novel drug targets.

OBJECTIVE: To review the research progress of the feasibility of a new treatment method for atrophic rhinitis (ATR) based on tissue engineering technology (seed cells, scaffold materials, and growth factors), and provide new ideas for the treatment of ATR. METHODS: The literature related to ATR was extensively reviewed. Focusing on the three aspects of seed cells, scaffold materials, and growth factors, the recent research progress of ATR treatment was reviewed, and the future directions of tissue engineering technology to treat ATR were proposed. RESULTS: The pathogenesis and etiology of ATR are still unclear, and the effectiveness of the current treatments are still unsatisfactory. The construction of a cell-scaffold complex with sustained and controlled release of exogenous cytokines is expected to reverse the pathological changes of ATR, promoting the regeneration of normal nasal mucosa and reconstructing the atrophic turbinate. In recent years, the research progress of exosomes, three-dimensional printing, and organoids will promote the development of tissue engineering technology for ATR. CONCLUSION Tissue engineering technology can provide a new treatment method for ATR.
Humans ; Tissue Engineering/methods* ; Tissue Scaffolds ; Rhinitis, Atrophic ; Printing, Three-Dimensional ; Cytokines