Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Cardiac fibrosis is characterized by an elevated amount of extracellular matrix (ECM) within the heart. However, the persistence of cardiac fibrosis ultimately diminishes contractility and precipitates cardiac dysfunction. Circular RNAs (circRNAs) are emerging as important regulators of cardiac fibrosis. Here, we elucidate the functional role of a specific circular RNA CELF1 in cardiac fibrosis and delineate a novel feedback loop mechanism. Functionally, circ-CELF1 was involved in enhancing fibrosis-related markers' expression and promoting the proliferation of cardiac fibroblasts (CFs), thereby exacerbating cardiac fibrosis. Mechanistically, circ-CELF1 reduced the ubiquitination-degradation rate of BRPF3, leading to an elevation of BRPF3 protein levels. Additionally, BRPF3 acted as a modular scaffold for the recruitment of histone acetyltransferase KAT7 to facilitate the induction of H3K14 acetylation within the promoters of the Celf1 gene. Thus, the transcription of Celf1 was dramatically activated, thereby inhibiting the subsequent response of their downstream target gene Smad7 expression to promote cardiac fibrosis. Moreover, Celf1 further promoted Celf1 pre-mRNA transcription and back-splicing, thereby establishing a feedback loop for circ-CELF1 production. Consequently, a novel feedback loop involving CELF1/circ-CELF1/BRPF3/KAT7 was established, suggesting that circ-CELF1 may serve as a potential novel therapeutic target for cardiac fibrosis.

Objective:To investigate the association of serum/body fluid heparin-binding protein (HBP) and blood lactate levels with disease severity and their impact on prognosis in intensive care unit (ICU) patients with sepsis.Methods:Clinical data from 100 sepsis patients admitted to Ma'anshan Shiqiye Hospital ICU (January 2023-September 2024) were retrospectively analyzed. According to Sepsis-3.0 criteria, patients were divided into: uncomplicated sepsis (general group, n=28), sepsis with organ failure/hypotension (severe group, n=61), and septic shock (shock group, n=11). Comparisons included serum/body fluid HBP, lactate, APACHE Ⅱ scores, and mortality across severity groups and laboratory parameters between survivors and non-survivors. Logistic regression was used to identify prognostic predictors. Non-normally distributed data were presented as M(Q1,Q3), comparison between groups were completed by Kruskal-Wallis H test and Mann-Whitney U tests. Spearman correlation was used to analyze relationships between biomarkers and APACHE Ⅱ scores. Categorical data were presented as n(%), and comparison between groups were completed by χ2 test or Fisher's exact tests. ROC curves was used to evaluate predictive value. Results:Shock group demonstrated significantly higher serum HBP [13.3 (12.6-16.4) μg/L], infection-site HBP [230.3 (226.3-241.1) μg/L], lactate [5.4 (4.9-5.6) mmol/L], and APACHE Ⅱ[22.0 (21.0-24.0)] than severe group [9.6 (8.9-10.5) μg/L; 208.9 (200.5-216.1) μg/L; 2.7 (2.6-2.8) mmol/L; 18.0 (17.0-19.0)] and general group [7.4 (6.3-8.1) μg/L; 190.6 (180.5-202.1) μg/L; 1.5 (1.4-1.7) mmol/L; 13.0 (12.0-14.0)] (all P<0.001). There was statistically significant difference in the mortality rate during hospita lization among three groups of patients ( χ2=30.49, P<0.001). Mortality was higher in shock group than severe group than general group [72.7% (8/11) vs. 11.5% (7/61) vs. 3.6% (1/28), all P<0.001]. Non-survivors exhibited elevated lactate [4.8 (2.7-5.5) vs. 2.6 (1.7-2.8) mmol/L, Z=-4.13, P=0.001], serum HBP [12.2 (9.2-13.3) vs. 9.3 (7.8-10.4) μg/L, Z=-3.12, P=0.002], and infection-site HBP [226.8 (209.9-237.6) vs. 203.6 (194.0-212.8) μg/L, Z=-4.32, P<0.001] vs. survivors. Serum HBP ( r=0.74), infection-site HBP ( r=0.64), and lactate ( r=0.86) were all positively correlated with APACHE Ⅱ (all P<0.001). After adjusting for age and APACHE Ⅱ, elevated serum HBP ( OR=3.743, 95% CI:1.834-7.640), infection-site HBP ( OR=3.540, 95% CI:1.932-6.486), and lactate ( OR=5.155, 95% CI:1.868-14.229) independently predicted mortality (all P<0.001). Combined biomarker detection showed superior predictive value (AUC=0.909) versus individual markers (serum HBP:0.747, infection-site HBP:0.842, lactate:0.827, all P<0.001). Conclusion:Elevated blood lactate and serum/infection-site HBP levels correlate with sepsis severity and independently predict mortality. The biomarker combination provides optimal prognostic stratification.

Objective:To investigate the association of serum/body fluid heparin-binding protein (HBP) and blood lactate levels with disease severity and their impact on prognosis in intensive care unit (ICU) patients with sepsis.Methods:Clinical data from 100 sepsis patients admitted to Ma'anshan Shiqiye Hospital ICU (January 2023-September 2024) were retrospectively analyzed. According to Sepsis-3.0 criteria, patients were divided into: uncomplicated sepsis (general group, n=28), sepsis with organ failure/hypotension (severe group, n=61), and septic shock (shock group, n=11). Comparisons included serum/body fluid HBP, lactate, APACHE Ⅱ scores, and mortality across severity groups and laboratory parameters between survivors and non-survivors. Logistic regression was used to identify prognostic predictors. Non-normally distributed data were presented as M(Q1,Q3), comparison between groups were completed by Kruskal-Wallis H test and Mann-Whitney U tests. Spearman correlation was used to analyze relationships between biomarkers and APACHE Ⅱ scores. Categorical data were presented as n(%), and comparison between groups were completed by χ2 test or Fisher's exact tests. ROC curves was used to evaluate predictive value. Results:Shock group demonstrated significantly higher serum HBP [13.3 (12.6-16.4) μg/L], infection-site HBP [230.3 (226.3-241.1) μg/L], lactate [5.4 (4.9-5.6) mmol/L], and APACHE Ⅱ[22.0 (21.0-24.0)] than severe group [9.6 (8.9-10.5) μg/L; 208.9 (200.5-216.1) μg/L; 2.7 (2.6-2.8) mmol/L; 18.0 (17.0-19.0)] and general group [7.4 (6.3-8.1) μg/L; 190.6 (180.5-202.1) μg/L; 1.5 (1.4-1.7) mmol/L; 13.0 (12.0-14.0)] (all P<0.001). There was statistically significant difference in the mortality rate during hospita lization among three groups of patients ( χ2=30.49, P<0.001). Mortality was higher in shock group than severe group than general group [72.7% (8/11) vs. 11.5% (7/61) vs. 3.6% (1/28), all P<0.001]. Non-survivors exhibited elevated lactate [4.8 (2.7-5.5) vs. 2.6 (1.7-2.8) mmol/L, Z=-4.13, P=0.001], serum HBP [12.2 (9.2-13.3) vs. 9.3 (7.8-10.4) μg/L, Z=-3.12, P=0.002], and infection-site HBP [226.8 (209.9-237.6) vs. 203.6 (194.0-212.8) μg/L, Z=-4.32, P<0.001] vs. survivors. Serum HBP ( r=0.74), infection-site HBP ( r=0.64), and lactate ( r=0.86) were all positively correlated with APACHE Ⅱ (all P<0.001). After adjusting for age and APACHE Ⅱ, elevated serum HBP ( OR=3.743, 95% CI:1.834-7.640), infection-site HBP ( OR=3.540, 95% CI:1.932-6.486), and lactate ( OR=5.155, 95% CI:1.868-14.229) independently predicted mortality (all P<0.001). Combined biomarker detection showed superior predictive value (AUC=0.909) versus individual markers (serum HBP:0.747, infection-site HBP:0.842, lactate:0.827, all P<0.001). Conclusion:Elevated blood lactate and serum/infection-site HBP levels correlate with sepsis severity and independently predict mortality. The biomarker combination provides optimal prognostic stratification.

Objective To analyze the potential distribution and quality zoning of Gentiana farreri Balf.f.;To provide a theoretical basis for the conservation,sustainable utilization,and domestication of this Tibetan medicine resource.Methods The MaxEnt model and geographic information system software ArcGIS 10.2 were used to conduct ecological suitability zoning of Gentiana farreri Balf.f.in China through searching online specimen libraries and field investigations.SPSS25.0 software was used to construct a relationship model between indicator components and ecological factors,combined with ArcGIS software spatial analysis technology,to form a quality zoning of Gentiana farreri Balf.f.medicinal material.Results The primary environmental factors influencing the ecological suitability of Gentiana farreri Balf.f.were altitude,precipitation in May,April and December,and the mean monthly diurnal temperature range.The most suitable growth areas for Gentiana farreri Balf.f.were predominantly found at the junction of Gansu,Sichuan and Qinghai provinces,certain parts of Tibet,and selected regions of Sichuan.The southern part of Tibet and the southwestern part of Sichuan were identified as having higher comprehensive quality of Gentiana farreri Balf.f.medicinal materials.Conclusion The findings of this study can serve as a reference for the production planning and quality assessment of Gentiana farreri Balf.f.

Objective:To analyze the HIV-1 drug resistance and related influencing factors of HIV antiviral therapy failures.Methods:Plasma samples were collected from the HIV/AIDS patients who had failed after antiviral therapy for one year at least from 2019 to 2020 for drug resistance gene detection and gene subtype determination, and the influencing factors were analyzed.Results:Among 479 successful samples, 284 had drug resistance gene mutation, the success rate of amplification was 84.18%, the mutation rate was 59.29%, the main gene subtype was CRF01_AE. The related factors of drug resistance gene mutation are CD4 + T lymphocyte count (CD4 count) ( χ2=18.01, P<0.001), HIV-1 subtype ( χ2=10.83, P =0.029) and treatment duration (month) ( χ2=6.24, P=0.044)during drug resistance test. Nucleoside reverse transcriptase inhibitor (NRTI)/non-nucleoside reverse transcriptase inhibitor (NNRTI) double resistance accounted for 54.23%, NNRTI drug resistance accounted for 34.86%, protease inhibitor (PI) drug resistance accounted for 4.23%, NRTI drug resistance accounted for 2.82%, PI/NNRTI double drug resistance accounted for 2.46%, PI/NRTI/NNRTI triple drug resistance accounted for 1.41%. NNRTI mutation mainly occurred at K103N, Y181C, G190A sites. NRTI mutation mainly occurred at M184V, K65R, K70R sites. PI mutation mainly occurred at M46L and Q58E sites. High resistance to nevirapine (NVP) accounted for up to 76.76% of patients with NNRTI resistance. Among the patients with NRTI resistance, 46.83% were highly resistant to emtricitabine (FTC)/lamivudine (3TC). There was no high resistance to PI among 284 drug resistant patients. Conclusions:Patients with low CD4 count, longer treatment time, BC subtype and CRF01_AE subtype had a higher incidence of drug resistance mutations in HIV/AIDS patients in Shanxi province. Most of them are mixed with multi-gene coding region mutations and have high resistance to FTC/3TC and NVP.

In order to carry out the " Healthy China 2030″ initiative, accelerate the cloud-based transformation of hospital information platforms, promote the construction of smart hospitals, and improve hospital informatization service capabilities, a tertiary hospital launched a comprehensive cloud-based practice for hospital operations in November 2020. A high-availability medical cloud platform designed for large general hospitals was built, by renting from carriers the Internet data center, installing highly scalable infrastructure, building multi-loop self-healing fiber-optic private network, applying the cloud-based software architecture using microservices and distributed storage, and implementing distributed systems′ full-link log and performance monitoring. In February 2021, the hospital migrated its medical care and operation management services on the cloud, achieving unified management of multiple hospital campuses, and reducing manpower and capital investment in computer room constructions. This practice ensured the continuity of hospital business, promoted the regional medical cooperation and the sinking of high-quality medical resources, and provided a reference for speeding up the promotion of nationwide hospital business to the cloud.

As a designated hospital, Tongji Hospital shoulders the task of diagnosis and treatment of numerous patients of the disease. Based on the medical cloud platform, the hospital has initiated a regional remote diagnosis center; leveraging its IT system, the hospital initiates its epidemic prevention and management mechanism, sets up a self-service system for patients at the fever clinic, launches its online diagnosis and treatment services, and establishes a hospital epidemic supervision platform. By strengthening the informational support needed for epidemic prevention and control, the hospital has enhanced its efficiency of epidemic prevention and control, reducing the risk of cross-infection, and ensuring data security. Its experiences offer references for informationization support for other regions and hospitals in China.

December of 2019 witnessed the outbreak of new coronavirus pneumonia in Wuhan city and a few localities. As a designated hospital, Tongji Hospital is designated as a hospital for the diagnosis and treatment of numerous patients of such a disease. Based on the medical cloud platform, the hospital has initiated a regional remote diagnosis center; based on its IT system, the hospital to operate its epidemic prevention and management mechanism, set up the self-service system for patients at the fever clinic, launched its online diagnosis and treatment services, and established a hospital epidemic supervision platform. By strengthening the informational support needed for epidemic prevention and control, the hospital has enhanced its efficiency of epidemic prevention and control, reducing the risk of cross-infection, and ensuring data security. Its experiences offer references for informationization support for other regions and hospitals in China.

Novel coronavirus pneumonia, which has emerged in Wuhan since the end of 2019, has posed a huge challenge for medical institutions in the city. Rapid completion of a number of cabin hospitals plays a vital role in preventing further spreading of the epidemic, by means of collecting and treating mild patients of the disease. This paper presents the key process of Tongji Hospital in its rapid informatization since it took over a cabin hospital. Based on the network architecture of the Tongji cloud platform, the shared service center is used to share data and integrate services between the cabin hospital and Tongji hospital. This practice can prevent cross-infection and improve service efficiency as well, hence offering a reference for future information infrastructure development of cabin hospitals.