Exosomal circular RNA (circRNAs) are pivotal in cancer biology, and tumor pathophysiology. These stable, non-coding RNAs encapsulated in exosomes participated in cancer progression, tumor growth, metastasis, drug sensitivity and the tumor microenvironment (TME). Their presence in bodily fluids positions them as potential non-invasive biomarkers, revealing the molecular dynamics of cancers. Research in exosomal circRNAs is reshaping our understanding of neoplastic intercellular communication. Exploiting the natural properties of exosomes for targeted drug delivery and disrupting circRNA-mediated pro-tumorigenic signaling can develop new treatment modalities. Therefore, ongoing exploration of exosomal circRNAs in cancer research is poised to revolutionize clinical management of cancer. This emerging field offers hope for significant breakthroughs in cancer care. This review underscores the critical role of exosomal circRNAs in cancer biology and drug resistance, highlighting their potential as non-invasive biomarkers and therapeutic targets that could transform the clinical management of cancer.

Exosomal circular RNA(circRNAs)are pivotal in cancer biology,and tumor pathophysiology.These stable,non-coding RNAs encapsulated in exosomes participated in cancer progression,tumor growth,metas-tasis,drug sensitivity and the tumor microenvironment(TME).Their presence in bodily fluids positions them as potential non-invasive biomarkers,revealing the molecular dynamics of cancers.Research in exosomal circRNAs is reshaping our understanding of neoplastic intercellular communication.Exploiting the natural properties of exosomes for targeted drug delivery and disrupting circRNA-mediated pro-tumorigenic signaling can develop new treatment modalities.Therefore,ongoing exploration of exoso-mal circRNAs in cancer research is poised to revolutionize clinical management of cancer.This emerging field offers hope for significant breakthroughs in cancer care.This review underscores the critical role of exosomal circRNAs in cancer biology and drug resistance,highlighting their potential as non-invasive biomarkers and therapeutic targets that could transform the clinical management of cancer.

The aim of this study was to qualitatively and quantitatively detect coronavirus(CoV)in the feces of bats from Qinghua Cave,Yunnan Province,China.CoV was qualitatively tested with reverse transcription polymerase chain reaction(RT-PCR),and homology and genetic evolution were analyzed with bioinformatics software.The established reverse transcription real-time fluores-cence quantitative PCR(qRT-PCR)method was applied to CoV quantification in bat feces.The positivity rate of CoV in 306 fecal samples collected from the fulvous fruit bat(Rousettus leschenaultia)was 7.8%(24/306)according to RT-PCR.All 24 strains of CoV belonged to β-CoV,and showed a similarity of 86.8%-100.0%at the nucleotide level and 95.2%-100.0%at the amino acid level,with respect to other β-CoV sequences in the NCBI database.The positivity rate of CoV was 18.6%(57/306)according to qRT-PCR,a value higher than that according to RT-PCR(χ2=25.3,P<0.05).The mean β-CoV load was 1.3×103 copies/μL.In conclusion,the bats in Qinghua Cave,Yunnan Province,carried CoV belonging to β-CoV.The established qRT-PCR method achieved good sensitiv-ity,accuracy,reproducibility,and a higher detection rate than that of RT-PCR,and can be used for rapid detection of β-CoV in bats.

The aim of this study was to qualitatively and quantitatively detect coronavirus(CoV)in the feces of bats from Qinghua Cave,Yunnan Province,China.CoV was qualitatively tested with reverse transcription polymerase chain reaction(RT-PCR),and homology and genetic evolution were analyzed with bioinformatics software.The established reverse transcription real-time fluores-cence quantitative PCR(qRT-PCR)method was applied to CoV quantification in bat feces.The positivity rate of CoV in 306 fecal samples collected from the fulvous fruit bat(Rousettus leschenaultia)was 7.8%(24/306)according to RT-PCR.All 24 strains of CoV belonged to β-CoV,and showed a similarity of 86.8%-100.0%at the nucleotide level and 95.2%-100.0%at the amino acid level,with respect to other β-CoV sequences in the NCBI database.The positivity rate of CoV was 18.6%(57/306)according to qRT-PCR,a value higher than that according to RT-PCR(χ2=25.3,P<0.05).The mean β-CoV load was 1.3×103 copies/μL.In conclusion,the bats in Qinghua Cave,Yunnan Province,carried CoV belonging to β-CoV.The established qRT-PCR method achieved good sensitiv-ity,accuracy,reproducibility,and a higher detection rate than that of RT-PCR,and can be used for rapid detection of β-CoV in bats.

Objective To propose a heart sound segmentation method based on multi-feature fusion network. Methods Data were obtained from the CinC/PhysioNet 2016 Challenge dataset (a total of 3 153 recordings from 764 patients, about 91.93% of whom were male, with an average age of 30.36 years). Firstly the features were extracted in time domain and time-frequency domain respectively, and reduced redundant features by feature dimensionality reduction. Then, we selected optimal features separately from the two feature spaces that performed best through feature selection. Next, the multi-feature fusion was completed through multi-scale dilated convolution, cooperative fusion, and channel attention mechanism. Finally, the fused features were fed into a bidirectional gated recurrent unit (BiGRU) network to heart sound segmentation results. Results The proposed method achieved precision, recall and F1 score of 96.70%, 96.99%, and 96.84% respectively. Conclusion The multi-feature fusion network proposed in this study has better heart sound segmentation performance, which can provide high-accuracy heart sound segmentation technology support for the design of automatic analysis of heart diseases based on heart sounds.

ObjectiveTo explore the mechanisms of Astragali Radix-Curcumae Rhizoma （HQ-EZ） in alleviating hypercoagulability and inhibiting tumor growth and metastasis by modulating the formation of neutrophil extracellular traps （NETs） via the complement component 5a （C5a）/C5a receptor （C5aR） pathway. MethodForty male C57BL/6 mice were randomized into four groups： Blank， model， HQ-EZ （8.2 g·kg^-1）， and PMX53 （1 mg·kg^-1）. The mouse model of Lewis lung cancer was established in other three groups except the blank group. Mice were administrated with corresponding drugs from day 3 after modeling. Specifically， the HQ-EZ decoction was administrated for 14 consecutive days， while intraperitoneal injection of PMX53 was implemented on days 3， 6， 9， 12， and 15. Mouse body weight and tumor diameter were measured every two days. On the next day of the last administration， lung microCT was performed to observe the tumor metastasis in vivo. Blood samples were collected from the eyeball after anesthetization， and tumor and lungs were collected after the mice were sacrificed. Tumor weight was measured to calculate the tumor growth inhibitory rate. Enzyme-linked immunosorbent assay was employed to measure the levels of C5a， neutrophil elastase （NE）， citrullinated histone-H3 （Cit-H3）， myeloperoxidase （MPO）， matrix metallopeptidase-9 （MMP-9）， NETs， von Willebrand Factor （vWF）， tissue factor （TF）， and P-selectin in the serum and tumor tissue. Terminal-deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling was conducted to assess apoptosis in the tumor tissue. Hematoxylin-eosin staining was conducted to observe lung metastasis， and immunofluorescence （IF） was employed to observe the expression of NETs in the tumor tissue. Western blot was employed to determine the protein levels of C5aR， MPO， and Cit-H3 in the tumor tissue. ResultCompared with the blank group， the model group had nodules in the lung， increased areas with low X-ray transmittance， appearance of nodular foci and multiple hemorrhagic foci in the lungs， and darkening lung color. Furthermore， the modeling elevated the serum levels of C5a， NETs and related proteins， vWF， TF， and P-selectin （P<0.01）. Compared with the model group， HQ-EZ and PMX53 reduced the lung metastases， areas with low X-ray transmittance， and nodules in the lungs and lightened the lung color. Compared with the model group， the two drug intervention groups showed flat tumor growth curves， decreased tumor weight （P<0.01）， increased apoptosis of tumor cells （P<0.01）， lowered levels of C5a， NETs and related proteins， vWF， TF， and P-selectin both in the serum and tumor tissue （P<0.05）， and down-regulated protein levels of C5aR， MPO， and Cit-H3 （P<0.05）. ConclusionHQ-EZ inhibited the expression of NETs by suppressing the C5a/C5aR pathway， thereby alleviating hypercoagulability and inhibiting tumor growth and metastasis.

Objective    To explore the application of Tsetlin Machine (TM) in heart beat classification. Methods    TM was used to classify the normal beats, premature ventricular contraction (PVC) and supraventricular premature beats (SPB) in the 2020 data set of China Physiological Signal Challenge. This data set consisted of the single-lead electro-cardiogram data of 10 patients with arrhythmia. One patient with atrial fibrillation was excluded, and finally data of the other 9 patients were included in this study. The classification results were then analyzed. Results    The classification results showed that the average recognition accuracy of TM was 84.3%, and the basis of classification could be shown by the bit pattern interpretation diagram. Conclusion    TM can explain the classification results when classifying heart beats. The reasonable interpretation of classification results can increase the reliability of the model and facilitate people's review and understanding.

Objective:To improve the prognosis stratification, especially early mortality(EM), of elderly patients with newly diagnosed multiple myeloma(NDMM).Methods:In this retrospective study, univariate and multivariate Cox regression analysis were conducted to identify the independent prognostic factors associated with overall survival(OS)and the chi-square test and multivariate Logistic analysis were used to identify the prognostic factors associated with EM in 223 elderly patients(age≥65 years)with NDMM from three centers in the country.Results:Increased NT-pro-BNP(≥300 pg/ml), ECOG-PS≥2 and stage Ⅲ R-ISS were identified as three independent adverse prognostic factors of OS.The rates of EM3, EM6, EM12 and EM24 were 12.1%, 20.1%, 32.2% and 60%, respectively.The most common cause for EM6(particularly EM3)was disease-related complications resulting from ineligibility for treatment due to poor physical performance, severe organ dysfunction or treatment discontinuation due to treatment intolerance, while the most common cause for EM12(particularly EM24)was disease progression or relapse mainly as a result of inadequate treatment.R-ISS staging failed to predict EM, while decreased eGFR, ECOG-PS≥2, and increased NT-pro-BNP were able to estimate the risk of EM, with increased NT-pro-BNP as a common independent factor for EM12( P=0.03)and EM24( P=0.015). Conclusions:R-ISS staging, which primarily reflects MM biology, cannot predict EM.However, factors such as NT-pro-BNP, eGFR and ECOG-PS associated with frailty and impairment of organ functions can be used to estimate the risk of EM, among which NT-pro-BNP may be the most important independent factor for EM.Therefore, incorporation of these frailty-related biomarkers into R-ISS staging may be able to more precisely estimate the prognosis and particularly early death of elderly patients with NDMM.

Objective: To investigate the status and influencing factors of health literacy of middle school students in Yinchuan City, to provide reference for health literacy improvement of middle school students in this region. Methods: Using stratified cluster sampling method, 2 003 middle school students from three districts of Yinchuan were investigated to complete the questionnaire survey.The survey included basic characteristics, health literacy and screen time status. Results: The total score of Chinese Adolescent Interactive Health Literacy Questionnaire was(101.3±17.5). The proportion of high, medium and low level of health literacy were 25.0%, 51.2% and 23.9% respectively;the proportion of long screen time exposure among middle school students was 52.5%. The health literacy level of junior middle school students, middle school students with father or mother education level of high school or above and appropriate screen time were higher than those of the corresponding group（χ 2=49.90，14.59，16.53，46.73，P<0.01）. Logistic regression analysis showed that education group, grade, father s or mother s education level and long screen time exposure were associated with middle school students health literacy level(P<0.05). Conclusion The health literacy level of middle school students in Yinchuan City needs to be further improved and targeted health education should be carried out from school, family and society.

Objective:To investigate risk factors for early mortality (EM) in patients with newly diagnosed multiple myeloma (NDMM) and to build an EM-predictive model.Methods:In a cohort of 275 patients with NDMM, risk factors for EM at 6, 12, and 24 months after diagnosis (EM6, EM12, and EM24, respectively) were determined to establish a model to predict EM.Results:The rates of EM6, EM12, and EM24 were 5.5% , 12.7% , and 30.2% , respectively. The most common cause for EM was disease progression/relapse, accounting for 60.0% , 77.1% , and 84.3% of EM6, EM12, and EM24, respectively. EM6 was associated with corrected serum calcium >2.75 mmol/L and platelet count <100×10 9/L, whereas risk factors for EM12 included age >75 years, ISS Ⅲ, R-ISS Ⅲ, corrected serum calcium >2.75 mmol/L, serum creatinine >177 μmol/L, platelet count <100×10 9/L, and bone marrow plasma cell ratio ≥ 60% . In addition to the risk factors for EM12, EM24 was also associated with male sex and 1q21 gain. By multivariate analysis, age >75 years, platelet count <100×10 9/L, and 1q21 gain were independent risk factors for EM24 but there were no independent risk factors significantly associated with EM6 and EM12. Using a scoring system including these three risk factors, a Cox model for EM24 was generated to distinguish patients with low (score<3) and high (score ≥ 3) risk. The sensitivity and specificity of the model were 20.7% and 99.2% , respectively. Further, an internal validation performed in a cohort of 183 patients with NDMM revealed that the probability of EM24 in high-risk patients was 26 times higher than that in low-risk patients. Moreover, this model was also able to predict overall survival. The median overall survival of patients with scores of 0, 1, 2, 3, 4, and 5 were 59, 41, 22, 17.5, and 16 months, respectively. Conclusion:In the study cohort, the EM6, EM12, and EM24 rates were 5.5% , 12.7% , and 30.2% , respectively, and disease progression or relapse were main causes of EM. An EM24-predictive model built on three independent risk factors for EM24 (age>75 years, platelet count<100×10 9/L, and 1q21 gain) might predict EM risk and overall survival.