Prognostic factors affecting the ruptured intracranial aneurysms: A 9-year multicenter study in Fujian, China.

BACKGROUND: A multicenter retrospective study was conducted to explore the factors affecting short-term prognosis and long-term outcomes of intracranial aneurysms (IA) rupture. Further, the prognosis prediction model was constructed based on survival analysis, contributing to the development of prevention strategies for aneurysmal subarachnoid hemorrhage. METHODS: Data of 1280 patients with IA rupture were gathered between 2014 and 2022 in Fujian, China. Logistic regression was implemented to study the short-term prognostic factors of IA rupture. Survival analysis of 911 patients among them was performed to explore the long-term outcome status by Cox risk assessment. Nomogram prognosis models were constructed using R software. RESULTS: The findings displayed that blood type O (OR = 1.79; P = 0.019), high systolic pressure (OR = 1.01; P < 0.001), Glasgow Coma score (GCS) 9-12 (OR = 2.73; P = 0.022), GCS < 9 (OR = 3.222; P = 0.006), diabetes (OR = 2.044; P = 0.040), and high white blood cell count (OR = 1.059, P = 0.040) were core influencing factors for poor short-term prognosis. Survival analysis revealed that age > 60 years (HR = 2.87; P = 0.001), hypertension (HR = 1.95; P = 0.001), conservative (HR = 6.89; P < 0.001) and endovascular treatment (HR = 2.20; P = 0.001), multiple ruptured IAs (HR = 2.37; P = 0.01), Fisher 3 (HR = 1.68; P = 0.09), Fisher 4 (HR = 2.75; P = 0.001), and Hunt-Hess 3 (HR = 0.55; P = 0.05) were the major risk factors for terrible long-term outcomes. CONCLUSIONS: People over 60 years with characteristics of type O blood, high systolic pressure, diabetes, high white blood cell count, and onset GCS < 12 will have more complications and a worse short-term prognosis. Those aged > 60 years with hypertension, conservative and endovascular treatment, multiple ruptured IAs, Fisher ≥ 3 and Hunt-Hess 3 have a greater risk of poor long-term prognosis.

Systematic Analyses of the Resistance Potential of Drugs Targeting SARS-CoV-2 Main Protease.

Drugs that target the main protease (Mpro) of SARS-CoV-2 are effective therapeutics that have entered clinical use. Wide-scale use of these drugs will apply selection pressure for the evolution of resistance mutations. To understand resistance potential in Mpro, we performed comprehensive surveys of amino acid changes that can cause resistance to nirmatrelvir (Pfizer), and ensitrelvir (Xocova) in a yeast screen. We identified 142 resistance mutations for nirmatrelvir and 177 for ensitrelvir, many of which have not been previously reported. Ninety-nine mutations caused apparent resistance to both inhibitors, suggesting likelihood for the evolution of cross-resistance. The mutation with the strongest drug resistance score against nirmatrelvir in our study (E166V) was the most impactful resistance mutation recently reported in multiple viral passaging studies. Many mutations that exhibited inhibitor-specific resistance were consistent with the distinct interactions of each inhibitor in the substrate binding site. In addition, mutants with strong drug resistance scores tended to have reduced function. Our results indicate that strong pressure from nirmatrelvir or ensitrelvir will select for multiple distinct-resistant lineages that will include both primary resistance mutations that weaken interactions with drug while decreasing enzyme function and compensatory mutations that increase enzyme activity. The comprehensive identification of resistance mutations enables the design of inhibitors with reduced potential of developing resistance and aids in the surveillance of drug resistance in circulating viral populations.

Defining the substrate envelope of SARS-CoV-2 main protease to predict and avoid drug resistance.

Coronaviruses can evolve and spread rapidly to cause severe disease morbidity and mortality, as exemplified by SARS-CoV-2 variants of the COVID-19 pandemic. Although currently available vaccines remain mostly effective against SARS-CoV-2 variants, additional treatment strategies are needed. Inhibitors that target essential viral enzymes, such as proteases and polymerases, represent key classes of antivirals. However, clinical use of antiviral therapies inevitably leads to emergence of drug resistance. In this study we implemented a strategy to pre-emptively address drug resistance to protease inhibitors targeting the main protease (Mpro) of SARS-CoV-2, an essential enzyme that promotes viral maturation. We solved nine high-resolution cocrystal structures of SARS-CoV-2 Mpro bound to substrate peptides and six structures with cleavage products. These structures enabled us to define the substrate envelope of Mpro, map the critical recognition elements, and identify evolutionarily vulnerable sites that may be susceptible to resistance mutations that would compromise binding of the newly developed Mpro inhibitors. Our results suggest strategies for developing robust inhibitors against SARS-CoV-2 that will retain longer-lasting efficacy against this evolving viral pathogen.

Associations between meteorological variation and rupture of intracranial aneurysm in Fujian, China: A 5-year multicenter study.

OBJECTIVE: By exploring the exposure-response relationships between meteorological factors and rupture of intracranial aneurysm (IA) to reveal the influence of meteorological variation on IA rupture under the specific climate in Fujian, China. METHOD: 7515 cases of IA rupture from several municipal medical institutions in Fujian Province as well as local meteorological data during the same period were collected from 2013 to 2017. Poisson regression and Spearman correlation analysis were applied to explore the distribution characteristics of IA rupture and how it is associated with meteorological parameters. Poisson generalized additive model was established to further analyze the exposure-response relationships between meteorological factors and IA rupture, and its hysteresis effects. RESULT: The IA rupture exhibited a negative correlation with temperature (rs = -0.323, 95% CI: -0.539 ~ -0.068) and a positive correlation with atmospheric pressure (rs = 0.397, 95% CI: 0.152-0.597) or pressure difference (rs = 0.296, 95% CI: 0.038-0.517), 21.05 â„ƒ and 1000.14 hPa were the risk thresholds for the onset ascribed to variation in temperature and atmospheric pressure, respectively. Temperature and atmospheric pressure also exerted hysteresis effects on IA rupture. Cold will increase the rupture risk in the subsequent 1-3 days, and high pressure will raise the morbidity in the next 1-2 days. Besides, drastic variations in temperature and atmospheric pressure were also associated with the higher risk of IA rupture in the next 2 days and 1 day, respectively. CONCLUSION: Temperature and atmospheric pressure have a negative and positive correlation with IA rupture in Fujian, China, respectively. Variation in temperature and atmospheric pressure exert different degrees of hysteresis effects on IA rupture.

Determinants of Tourism Stocks During the COVID-19: Evidence From the Deep Learning Models.

This paper examines the determinants of tourism stock returns in China from October 25, 2018, to October 21, 2020, including the COVID-19 era. We propose four deep learning prediction models based on the Back Propagation Neural Network (BPNN): Quantum Swarm Intelligence Algorithms (QSIA), Quantum Step Fruit-Fly Optimization Algorithm (QSFOA), Quantum Particle Swarm Optimization Algorithm (QPSO) and Quantum Genetic Algorithm (QGA). Firstly, the rough dataset is used to reduce the dimension of the indices. Secondly, the number of neurons in the multilayer of BPNN is optimized by QSIA, QSFOA, QPSO, and QGA, respectively. Finally, the deep learning models are then used to establish prediction models with the best number of neurons under these three algorithms for the non-linear real stock returns. The results indicate that the QSFOA-BPNN model has the highest prediction accuracy among all models, and it is defined as the most effective feasible method. This evidence is robust to different sub-periods.

Meteorological Variation Is a Predisposing Factor for Aneurismal Subarachnoid Hemorrhage: A 5-Year Multicenter Study in Fuzhou, China.

OBJECTIVE: The climatic characteristics of aneurysmal subarachnoid hemorrhage (aSAH) have been reported, but consensus has not yet been reached. It is of great significance to elucidate the relationships between meteorological variation and aSAH in regions with specific climate patterns. We analyzed the occurrence of aSAH in the capital city of Fujian Province, China, through a multicenter, 5-year study, and aimed to reveal the meteorological influences on aSAH in the coastal city of eastern Fujian under the subtropical marine monsoon condition. METHODS: A total of 2555 consecutive patients with aSAH in Fuzhou were collected using specialized stroke admission database from January 2013 to December 2017. Meteorological parameters including temperature, atmospheric pressure, and humidity were obtained from China Surface Meteorological Station during the same period. Poisson regression was used to explore the association between meteorological parameters and aSAH to calculate the incidence rate ratios (IRRs) with corresponding 95% confidence intervals (CIs). Generalized additive model analysis further revealed the nonlinear relationships between weather and aSAH. RESULTS: Daily minimum temperature (IRR 0.976, 95% CI 0.958-0.996) and maximum pressure (IRR 1.022, 95% CI 1.001-1.042) were independently correlated with the onset of aSAH. Low temperature (below 16°C) and excessive atmospheric pressure (above 1008 hPa) increased the risk of aSAH. In addition, March in spring and December in winter were the 2 ictus peaks in Fuzhou throughout the year. CONCLUSIONS: Cold and excessive atmospheric pressure are triggers for the occurrence of aSAH; March in spring and December in winter are the predominant onset periods in Fuzhou.

High-Throughput Data Reveals Novel Circular RNAs via Competitive Endogenous RNA Networks Associated with Human Intracranial Aneurysms.

BACKGROUND Little is known about epigenetic regulation of intracranial aneurysms (IAs). Circular non-coding RNAs (circRNAs) play crucial roles in cardiovascular diseases, but they have received scant research attention regarding their relationship with IAs. This study aimed to explore new pathological mechanisms of IA through circRNA expression profiles and to provide novel therapeutic strategies. MATERIAL AND METHODS The comprehensive circRNA and mRNA expression profiles were detected by RNA-Seq in human IA walls and superficial temporal arteries (STAs). The RNA-Seq findings were validated by qRT-PCR. GO and KEGG analyses indicated the functions of these circRNAs. A competing endogenous RNA (ceRNA) network was constructed to reveal the circRNA-miRNA-mRNA relationship. Two newly discovered circRNAs were further detected in peripheral blood of IA patients and healthy people to clarify their expression patterns in the periphery. RESULTS Many differentially expressed circRNAs are closely involved in immune/inflammatory response and cell adhesion/adherens junction. The novel circRNAs (hsa_circ_0072309 and hsa_circ_0008433) regulate DDR2 and MMP2, respectively, which are associated with SMC dysfunction and vascular injury through ceRNA. Moreover, we found differential expression of these 2 circRNAs in the peripheral blood of IA patients, and the expression pattern of hsa_circ_0072309 had central and peripheral consistency. CONCLUSIONS To the best of our knowledge, this is the first study to perform circRNA sequencing analysis of IAs. hsa_circ_0072309 and hsa_circ_0008433 are novel and pivotal circRNAs related to IAs. This study provides new insights into therapeutic targets and biomarkers for IA patients.