A multicenter prospective study on the ESC algorithm for the early diagnosis of non-ST-elevation myocardial infarction.

This study aimed to determine the optimal high-sensitivity cardiac troponin I (hs-cTnI)-based algorithm for early diagnosis of non-ST-elevation myocardial infarction (NSTEMI) in Chinese patients. We prospectively enrolled 1,606 patients with suspected NSTEMI from three emergency departments across China, collecting blood samples at 0, 1, and 3 h post-admission. Patients were classified using the 0/1-h and 0/3-h algorithms. The 2015 and 2020 ESC 0/1-h algorithms rapidly triaged 70% of patients with high negative predictive value (NPV) (99.7%) and sensitivity (99.5%). The 0/3-h algorithm showed higher specificity (93.8%) but lower NPV (96.8%) and sensitivity (91.2%). An optimized 0/1-h algorithm improved specificity to 92.1% while maintaining high NPV (99.7%) and sensitivity (99.2%). Low 30-day and 180-day all-cause mortality and major adverse cardiac event (MACE) rates were observed in rule-out groups for all algorithms. The ESC 0/1-h algorithm is a safe and efficient triage method for patients with suspected NSTEMI, with optimization further enhancing specificity and efficiency for the Chinese population.

Circ_0008146 Exacerbates Ferroptosis via Regulating the miR-342-5p/ACSL4 Axis After Cerebral Ischemic/Reperfusion.

Purpose: Acute ischemic stroke (AIS) has seriously threatened people's health worldwide and there is an urge need for early diagnosis and effective treatment of AIS. This research intended to clarify the regulatory role of circ_0008146/miR-342-5p/ACSL4 axis in AIS. Methods: High-throughput small RNA sequencing analysis was adapted to identify differentially expressed miRNAs between the AIS and control group. The circ_0008146, miR-342-5p, and ACSL4 levels were detected by qRT-PCR. Middle cerebral artery occlusion/reperfusion (MCAO/R) models were constructed in C57BL/6J mice. Assay kits were used to determine Fe2+ levels and a battery of oxidative stress and lipid peroxidation indicators, including ROS, MDA, LPO, SOD and GSH/GSSG ratio. The protein levels of ACSL4 were measured by Western blot. The behavioral function was assessed using neurobehavioral tests. TTC staining was employed to visualize infarction size. Nissl staining was adapted to detect histopathological changes. Receiver operating characteristic curve and correlation analysis were applied to investigate the clinical value and association of miR-342-5p and ACSL4. Results: A total of 44 AIS patients and 49 healthy controls were enrolled in our study. The small RNA sequencing unveiled a significant decrease in miR-342-5p levels in AIS patients. MiR-342-5p inhibited oxidative stress and RSL3-induced ferroptosis after cerebral ischemic/reperfusion injury in vivo by targeting ferroptosis-related gene ACSL4. Circ_0008146 acted as a sponge of miR-342-5p, and overexpression of circ_0008146 increased neurological deficits and brain injury in mice. Circ_0008146 contributed to ferroptosis in cerebral infarction via sponging miR-342-5p to regulate ACSL4. Plasma miR-342-5p and ACSL4 demonstrated significant correlation and good diagnostic value for AIS patients. Conclusion: This study provides the first in vivo evidence to show that circ_0008146 exacerbates neuronal ferroptosis after AIS via the miR-342-5p/ACSL4 axis. Furthermore, miR-342-5p/ACSL4 axis holds promise as a viable therapeutic target and practical biomarkers for AIS patients.

Prostate cancer cell-derived exosomal IL-8 fosters immune evasion by disturbing glucolipid metabolism of CD8+ T cell.

Depletion of CD8+ T cells is a major obstacle in immunotherapy; however, the relevant mechanisms remain largely unknown. Here, we showed that prostate cancer (PCa) cell-derived exosomes hamper CD8+ T cell function by transporting interleukin-8 (IL-8). Compared to the low IL-8 levels detected in immune cells, PCa cells secreted the abundance of IL-8 and further accumulated in exosomes. The delivery of PCa cell-derived exosomes into CD8+ T cells exhausted the cells through enhanced starvation. Mechanistically, exosomal IL-8 overactivated PPARα in recipient cells, thereby decreasing glucose utilization by downregulating GLUT1 and HK2 but increasing fatty acid catabolism via upregulation of CPT1A and ACOX1. PPARα further activates uncoupling protein 1 (UCP1), leading to fatty acid catabolism for thermogenesis rather than ATP synthesis. Consequently, inhibition of PPARα and UCP1 restores CD8+ T cell proliferation by counteracting the effect of exosomal IL-8. This study revealed that the tumor exosome-activated IL-8-PPARα-UCP1 axis harms tumor-infiltrating CD8+ T cells by interfering with energy metabolism.

Phenotype and genotype analysis for Helicobacter pylori antibiotic resistance in outpatients: a retrospective study.

To investigate the antibiotic resistance of Helicobacter pylori (H. pylori) in outpatients and to explore the consistency between genotype and phenotype of H. pylori antibiotic resistance. A retrospective study on outpatients screened with urea breath test for H. pylori infection in Nanjing First Hospital from April 2018 to January 2022. Patients who tested positive underwent a consented upper endoscopy, and the H. pylori infection was confirmed by rapid urease test (RUT) and H. pylori culture. For antibiotic resistance phenotype analysis, the H. pylori strains isolated from gastric biopsy were tested for antibiotic resistance phenotype by the Kirby-Bauer disk diffusion test. In addition, the antibiotic resistance genotype of isolated H. pylori was tested with a real-time polymerase chain reaction. A total of 4,399 patients underwent H. pylori infection screening, and 3,306 H. pylori strains were isolated. The antibiotic resistance phenotype test revealed that the resistance rates of metronidazole (MTZ), clarithromycin (CLR), levofloxacin (LEV), amoxicillin (AMX), furazolidone (FR), and tetracycline (TE) were 74.58%, 48.61%, 34.83%, 0.76%, 0.27%, and 0.09%, respectively. Additionally, the antibiotic resistance genotype test revealed that rdxA gene mutation A610G (92.96%), A91G (92.95%), C92A (93.00%), and G392A (95.07%) were predominant in H. pylori with MTZ resistance; 23S rRNA gene mutation A2143G (86.47%) occurred in most H. pylori with CLR resistance; and gyrA gene mutation 87Ile/Lys/Tyr/Arg (97.32%) and 91Asn/Gly/Tyr (90.61%) were the most popular mutations in strains with LEV resistance. The phenotypic resistance and genotypic resistance to CLR (kappa value = 0.824) and LEV (kappa value = 0.895) were in good agreement. The history of eradication with MTZ, CLR, LEV, and AMX was correlated with H. pylori resistance. In short, this study demonstrated that drug resistance of H. pylori was mainly to MTZ, CLR, and LEV in local outpatients. Three drugs can be selected for increased MICs (Minimum Inhibitory Concentration) via single chromosomal mutations. In addition, the genotype could be used to predict the phenotypic H. pylori resistance to CLR and LEV. IMPORTANCE Helicobacter pylori is a key bacterium that causes stomach diseases. There was a high prevalence of H. pylori in the Chinese population. We analyzed the resistance phenotype and genotype characteristics of H. pylori in 4,399 outpatients at the First Hospital of Nanjing, China. We found a higher resistance rate to metronidazole (MTZ) , clarithromycin (CLR), and levofloxacin (LEV), and the genotype could be used to predict the phenotypic H. pylori resistance to CLR and LEV. This study provides information on H. pylori infection and also provides guidance for clinical doctors' drug treatment.

The Role of N6-Methyladenosine-Associated lncRNAs in the Immune Microenvironment and Prognosis of Colorectal Cancer.

Background: The role of N6-methyladenosine long noncoding RNAs (lncRNAs) in colorectal cancer (CRC) is elusive. Materials and Methods: We identified m6A-associated lncRNAs by using the data gathered from The Cancer Genome Atlas (TCGA) and stratified CRC patients into different subgroups. Cox regression analysis was performed to construct an m6A-associated lncRNA signature. The role of this signature in the immune microenvironment and prognosis was dissected subsequently. Finally, a gene set enrichment analysis (GSEA) was conducted to predict the possible mechanisms based on the signature. Results: Three m6A-associated clusters were constructed from 866 differentially expressed lncRNAs. Cluster 2 had poor prognosis and low immune cell infiltration. An m6A-associated lncRNA signature consisting of 14 lncRNAs was constructed and recognized as an independent prognostic indicator of CRC by using survival analysis and receiver operating characteristic (ROC) curves. The clinical features and immune cell infiltration status were significantly different in patients stratified by the risk score. Furthermore, GSEA showed that the P53 pathway and natural killer cell-mediated cytotoxicity were more enriched in the low-risk group. Conclusion: Our data revealed that m6A-associated lncRNAs could be potential prognostic indicators of immunogenicity in CRC.

Identification of autophagy related genes in predicting the prognosis and aiding 5- fluorouracil therapy of colorectal cancer.

The emergence of 5-Fluorouracil (5-FU) resistance is the barrier to effective clinical outcomes for colorectal cancer (CRC) patients. Autophagy was found to be involved in protecting tumor cells from 5-FU. However, the specific role of autophagy-related genes in CRC 5-FU resistance remains unclear. In this study, HSPB8 among 34 differentially expressed ARGs in CRC was identified to be the hub ARGs in 5-FU resistant which was down-regulated in CRC samples when compared with normal samples but up-regulated in CRC samples with relatively higher lymphatic invasion, later stages and poor prognosis of CRC. Mechanistic analysis demonstrated that due to the recruitment of CAFs, HSPB8 expression was enhanced in CRC cells so that HSPB8 could act together with its co-chaperone BAG3 in autophagy drived 5-FU resistance. Furthermore, the augmented expression level of HSPB8 was found to be significantly correlated to the immune cell infiltration such as Treg cells, macrophages, monocyte and dendritic cells and so on. Our results suggested CAFs driving HSPB8 induced CRC 5-FU resistance by promoting tumor autophagy would provide a new strategy in seeking potential CRC therapeutic target.

Circular RNA Rbms1 inhibited the development of myocardial ischemia reperfusion injury by regulating miR-92a/BCL2L11 signaling pathway.

Acute myocardial infarction (AMI) is characterized by high morbidity and mortality rates. Circular RNAs collectively participate in the initiation and development of AMI. The purpose of this study was to investigate the role of circRbms1 in AMI. Ischemia-reperfusion (I/R) was performed to establish an AMI model. RT-qPCR and Western blotting were performed to detect mRNA and analyze protein expression, respectively. The interaction between miR-92a and circRbms1/BCL2L11 was confirmed by luciferase and RNA pull-down assays. circRbms1 is overexpressed in AMI. However, circRbms1 knockdown alleviated H9c2 cell apoptosis and reduced the release of reactive oxygen species. circRbms1 targeted miR-92a, the downregulation of which alleviated the effects of circRbms1 knockdown and increased oxidative stress and H9c2 cell apoptosis. Moreover, circRbms1 sponged miR-92a to upregulate BCL2L11, which modulated the expression of apoptosis-related genes. circRbms1 participated in myocardial I/R injury by regulating the miR-92a/BCL2L11 signaling pathway, which may provide a new strategy for the treatment of AMI.

Laboratory Testing Implications of Risk-Stratification and Management of COVID-19 Patients.

Objective: To distinguish COVID-19 patients and non-COVID-19 viral pneumonia patients and classify COVID-19 patients into low-risk and high-risk at admission by laboratory indicators. Materials and methods: In this retrospective cohort, a total of 3,563 COVID-19 patients and 118 non-COVID-19 pneumonia patients were included. There are two cohorts of COVID-19 patients, including 548 patients in the training dataset, and 3,015 patients in the testing dataset. Laboratory indicators were measured during hospitalization for all patients. Based on laboratory indicators, we used the support vector machine and joint random sampling to risk stratification for COVID-19 patients at admission. Based on laboratory indicators detected within the 1st week after admission, we used logistic regression and joint random sampling to develop the survival mode. The laboratory indicators of COVID-10 and non-COVID-19 were also compared. Results: We first identified the significant laboratory indicators related to the severity of COVID-19 in the training dataset. Neutrophils percentage, lymphocytes percentage, creatinine, and blood urea nitrogen with AUC >0.7 were included in the model. These indicators were further used to build a support vector machine model to classify patients into low-risk and high-risk at admission in the testing dataset. Results showed that this model could stratify the patients in the testing dataset effectively (AUC = 0.89). Our model still has good performance at different times (Mean AUC: 0.71, 0.72, 0.72, respectively for 3, 5, and 7 days after admission). Moreover, laboratory indicators detected within the 1st week after admission were able to estimate the probability of death (AUC = 0.95). We identified six indicators with permutation p < 0.05, including eosinophil percentage (p = 0.007), white blood cell count (p = 0.045), albumin (p = 0.041), aspartate transaminase (p = 0.043), lactate dehydrogenase (p = 0.002), and hemoglobin (p = 0.031). We could diagnose COVID-19 and differentiate it from other kinds of viral pneumonia based on these laboratory indicators. Conclusions: Our risk-stratification model based on laboratory indicators could help to diagnose, monitor, and predict severity at an early stage of COVID-19. In addition, laboratory findings could be used to distinguish COVID-19 and non-COVID-19.

Comparative Characterization and Risk Stratification of Asymptomatic and Presymptomatic Patients With COVID-19.

The identification of asymptomatic, non-severe presymptomatic, and severe presymptomatic coronavirus disease 2019 (COVID-19) in patients may help optimize risk-stratified clinical management and improve prognosis. This single-center case series from Wuhan Huoshenshan Hospital, China, included 2,980 patients with COVID-19 who were hospitalized between February 4, 2020 and April 10, 2020. Patients were diagnosed as asymptomatic (n = 39), presymptomatic (n = 34), and symptomatic (n = 2,907) upon admission. This study provided an overview of asymptomatic, presymptomatic, and symptomatic COVID-19 patients, including detection, demographics, clinical characteristics, and outcomes. Upon admission, there was no significant difference in clinical symptoms and CT image between asymptomatic and presymptomatic patients for diagnosis reference. The mean area under the receiver operating characteristic curve (AUC) of the differential diagnosis model to discriminate presymptomatic patients from asymptomatic patients was 0.89 (95% CI, 0.81-0.98). Importantly, the severe and non-severe presymptomatic patients can be further stratified (AUC = 0.82). In conclusion, the two-step risk-stratification model based on 10 laboratory indicators can distinguish among asymptomatic, severe presymptomatic, and non-severe presymptomatic COVID-19 patients on admission. Moreover, single-cell data analyses revealed that the CD8+T cell exhaustion correlated to the progression of COVID-19.

The value of circulating tumor cells with positive centromere probe 8 in the diagnosis of small pulmonary nodules.

Circulating cancer cells (CTCs) can serve as a non-invasive liquid biopsy and provide opportunities for early cancer diagnosis and evaluation. However, the value of CTCs for diagnosis or prognosis of small pulmonary nodules (SPNs) is unclear. Fifty-three patients diagnosed with SPNs with a diameter less than 30 mm by CT examination were enrolled in the study. The CTC numbers, CT examination features, serum tumor marker concentrations, and histopathological characteristics were analyzed. Centromere probe 8 (CEP8) was used as a marker for CTC identification. The CTC numbers were significantly different in patients with malignant and benign SPNs and with early (0/Ⅰa) and advanced (Ⅰb/Ⅱ/Ⅲ) lung cancer stages. ROC analysis showed that the CTC numbers was effective on malignant SNP diagnosis. The combined use of CTCs and the density features of the nodules determined by CT further improved the overall screening, the diagnostic effectiveness for malignant SNPs, and determination of the pTNM (≤Ia vs.>Ia) stage. The CT morphology revealed that large, single, and solid SPNs were associated with significant CTC numbers and the CTC numbers were correlated with malignant histopathology. Using CEP8 as a marker resulted in detection of more CTC numbers in 22 patient samples triple stained for CEP8, EpCAM, and CKs. The CTCs determined by CEP8-positive staining could serve as potential screening and diagnostic markers for malignant SPNs.

Plasma expression of HIF-1α as novel biomarker for the diagnosis of obstructive sleep apnea-hypopnea syndrome.

BACKGROUND: Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a common breathing disorder during sleep with potential lethality and multi-complications. Polysomnography (PSG) is now the golden standard for the diagnosis obstructive sleep apnea-hypopnea syndrome. However, PSG is expensive and time-consuming. Therefore, it is important to find inexpensive and convenient biomarkers for the diagnosis of OSAHS. OBJECTIVE: The present study aimed to explore the potential diagnostic value of HIF-1α for OSAHS and its clinical significance. METHODS: This study consisted of 368 patients admitted to the sleep laboratory. The patients were classified according to their apnea-hypopnea index (AHI) scores as OSA negative (AHI < 5), mild-moderate (AHI:5-30), and severe OSA (AHI > 30), and severe OSA treated with continuous positive airway pressure (CPAP). qRT-PCR was used to detect mRNA levels in the plasma; Pearson's correlation analysis was performed to analyze the correlation of HIF-1α mRNA level and the clinicopathological factors of OSAHS; ROC curve was constructed to evaluate the diagnostic value of HIF-1α mRNA. RESULTS: HIF-1α mRNA was significantly up-regulated in the plasma of OSAHS patients, especially patients with severe OSAHS. HIF-1α mRNA was positively correlated with the AHI and ODI but negatively correlated with the mean oxygen saturation in patients with OSAHS. Results of ROC curve showed that HIF-1α is a sensitive biomarker for the diagnosis of OSAHS, especially severe OSAHS. CONCLUSIONS: HIF-1α mRNA might be used as s a convenient and inexpensive method for triaging OSAHS patients PSG assessment in the hospital and evaluate the curative effect.

Diagnostic and Differential Diagnostic Significance of Laboratory Markers in Crayfish-Associated Rhabdomyolysis.

CONTEXT: Haff disease is a rare syndrome of myalgia and rhabdomyolysis occurring within 24h of consumption of certain types of cooked freshwater fish or crustacean. OBJECTIVE: The white blood cell count (WBC), plasma creatine kinase (CK), creatine kinase isoenzyme (CK-MB), CK-MB/CK, troponin T (cTnT) and creatinine (Cr) were analyzed as diagnostic markers for crayfish (Procambarus clarkii)-associated rhabdomyolysis (Haff disease). The significance of these laboratory markers in differentiating myocardial injury disease and Haff disease was explored. METHODS: 138 patients with symptoms of acute onset (such as chest pain, muscle pain) and high myocardial enzymes were assigned as the Haff disease group and myocardial injury group, respectively. In parallel, 80 healthy individuals were selected as healthy control. Plasma Cr, CK, and CK-MB levels were detected by the Johnson & Johnson DT60II dry biochemistry analyzer; cTnT level was detected by Roche Elecsys 2010; WBC was detected by Sysmex 5300. RESULTS: The WBC levels in the Haff disease group and myocardial injury diseases group were higher than the healthy control group (P<0.05). The plasma CK, CK-MB levels in Haff disease group were the highest, following by the myocardial injury disease group, and the lowest were in the normal control group. There were also statistically significant differences between two groups (P<0.05): the CK-MB/CK and cTnT's levels in the myocardial injury disease group were higher than those in the Haff disease group and healthy control group (P<0.05); the plasma Cr level in the Haff disease group was lower than that in the myocardial injury disease group and normal control group (P<0.05). CONCLUSION: Our results indicated that WBC, plasma CK, and CK-MB increase significantly, whereas Cr decreases significantly in Haff disease. These laboratory markers may be used for the diagnosis of crayfish-associated rhabdomyolysis. CK may be used as a biomarker to evaluate the severity of Haff disease, while cTnT and CK-MB/CK may be used to differentiate myocardial injury disease and Haff disease.