Health outcomes after myocardial infarction: A population study of 56 million people in England.

BACKGROUND: The occurrence of a range of health outcomes following myocardial infarction (MI) is unknown. Therefore, this study aimed to determine the long-term risk of major health outcomes following MI and generate sociodemographic stratified risk charts in order to inform care recommendations in the post-MI period and underpin shared decision making. METHODS AND FINDINGS: This nationwide cohort study includes all individuals aged ≥18 years admitted to one of 229 National Health Service (NHS) Trusts in England between 1 January 2008 and 31 January 2017 (final follow-up 27 March 2017). We analysed 11 non-fatal health outcomes (subsequent MI and first hospitalisation for heart failure, atrial fibrillation, cerebrovascular disease, peripheral arterial disease, severe bleeding, renal failure, diabetes mellitus, dementia, depression, and cancer) and all-cause mortality. Of the 55,619,430 population of England, 34,116,257 individuals contributing to 145,912,852 hospitalisations were included (mean age 41.7 years (standard deviation [SD 26.1]); n = 14,747,198 (44.2%) male). There were 433,361 individuals with MI (mean age 67.4 years [SD 14.4)]; n = 283,742 (65.5%) male). Following MI, all-cause mortality was the most frequent event (adjusted cumulative incidence at 9 years 37.8% (95% confidence interval [CI] [37.6,37.9]), followed by heart failure (29.6%; 95% CI [29.4,29.7]), renal failure (27.2%; 95% CI [27.0,27.4]), atrial fibrillation (22.3%; 95% CI [22.2,22.5]), severe bleeding (19.0%; 95% CI [18.8,19.1]), diabetes (17.0%; 95% CI [16.9,17.1]), cancer (13.5%; 95% CI [13.3,13.6]), cerebrovascular disease (12.5%; 95% CI [12.4,12.7]), depression (8.9%; 95% CI [8.7,9.0]), dementia (7.8%; 95% CI [7.7,7.9]), subsequent MI (7.1%; 95% CI [7.0,7.2]), and peripheral arterial disease (6.5%; 95% CI [6.4,6.6]). Compared with a risk-set matched population of 2,001,310 individuals, first hospitalisation of all non-fatal health outcomes were increased after MI, except for dementia (adjusted hazard ratio [aHR] 1.01; 95% CI [0.99,1.02];p = 0.468) and cancer (aHR 0.56; 95% CI [0.56,0.57];p < 0.001). The study includes data from secondary care only-as such diagnoses made outside of secondary care may have been missed leading to the potential underestimation of the total burden of disease following MI. CONCLUSIONS: In this study, up to a third of patients with MI developed heart failure or renal failure, 7% had another MI, and 38% died within 9 years (compared with 35% deaths among matched individuals). The incidence of all health outcomes, except dementia and cancer, was higher than expected during the normal life course without MI following adjustment for age, sex, year, and socioeconomic deprivation. Efforts targeted to prevent or limit the accrual of chronic, multisystem disease states following MI are needed and should be guided by the demographic-specific risk charts derived in this study.

Risk calculator for incident atrial fibrillation across a range of prediction horizons.

BACKGROUND: The increasing burden of atrial fibrillation (AF) emphasizes the need to identify high-risk individuals for enrolment in clinical trials of AF screening and primary prevention. We aimed to develop prediction models to identify individuals at high-risk of AF across prediction horizons from 6-months to 10-years. METHODS: We used secondary-care linked primary care electronic health record data from individuals aged ≥30 years without known AF in the UK Clinical Practice Research Datalink-GOLD dataset between January 2, 1998 and November 30, 2018; randomly divided into derivation (80%) and validation (20%) datasets. Models were derived using logistic regression from known AF risk factors for incident AF in prediction periods of 6 months, 1-year, 2-years, 5-years, and 10-years. Performance was evaluated using in the validation dataset with bootstrap validation with 200 samples, and compared against the CHA2DS2-VASc and C2HEST scores. RESULTS: Of 2,081,139 individuals in the cohort (1,664,911 in the development dataset, 416,228 in the validation dataset), the mean age was 49.9 (SD 15.4), 50.7% were women, and 86.7% were white. New cases of AF were 7,386 (0.4%) within 6 months, 15,349 (0.7%) in 1 year, 38,487 (1.8%) in 5 years, and 79,997 (3.8%) by 10 years. Valvular heart disease and heart failure were the strongest predictors, and association of hypertension with AF increased at longer prediction horizons. The optimal risk models incorporated age, sex, ethnicity, and 8 comorbidities. The models demonstrated good-to-excellent discrimination and strong calibration across prediction horizons (AUROC, 95%CI, calibration slope: 6-months, 0.803, 0.789-0.821, 0.952; 1-year, 0.807, 0.794-0.819, 0.962; 2-years, 0.815, 0.807-0.823, 0.973; 5-years, 0.807, 0.803-0.812, 1.000; 10-years 0.780, 0.777-0.784, 1.010), and superior to the CHA2DS2-VASc and C2HEST scores. The models are available as a web-based FIND-AF calculator. CONCLUSIONS: The FIND-AF models demonstrate high discrimination and calibration across short- and long-term prediction horizons in 2 million individuals. Their utility to inform trial enrolment and clinical decisions for AF screening and primary prevention requires further study.

Modeling the effects of land use/land cover changes on river runoff using SWAT models: A case study of the Danjiang River source area, China.

Land use/land cover (LULC) is a crucial factor that directly influences the hydrology and water resources of a watershed. In order to assess the impacts of LULC changes on river runoff in the Danjiang River source area, we analyzed the characteristics of LULC data for three time periods (2000, 2010, and 2020). The LULC changes during these periods were quantified, and three Soil and Water Assessment Tool (SWAT) models were established and combined with eight LULC scenarios to quantitatively analyze the effects of LULC changes on river runoff. The results revealed a decrease in the cropland area and an increase in the forest, grassland, and urban land areas from 2000 to 2020. Grassland, forest, and cropland collectively accounted for over 94% of the total area, and conversions among these land types were frequent. The SWAT models constructed based on the LULC data demonstrated good calibration and validation results. Based on the LULC data in three periods, the area of each LULC type changed slightly, so the simulation results were not significantly different. In the subsequent LULC scenarios, we found that the expansion of cropland, grassland, and urban areas was associated with increased river runoff, while an increase in forest area led to a decrease in river runoff. Among the various LULC types, urban land exerted the greatest influence on changes in river runoff. This study establishes three SWAT models and combines multiple LULC scenarios, which is novel and innovative. It can provide scientific basis for the rational allocation of water resources and the optimization of LULC structure in the Danjiang River source area.

Seasonal nitrate variations, risks, and sources in groundwater under different land use types in a thousand-year-cultivated region, northwestern China.

The global public health concern of nitrate (NO3-) contamination in groundwater is particularly pronounced in irrigated agricultural regions. This paper aims to analyze the spatial distribution of groundwater NO3-, assess potential health risks for local residents, and quantitatively identify nitrate sources during different seasons and land use types in the Jinghuiqu Irrigation District, a region in northwestern China with a longstanding agricultural history. The investigation utilizes hydrochemical parameters, dual isotopic data, and the Bayesian stable isotope mixing model (MixSIAR). The findings underscore significant seasonal variations in the average concentrations of NO3-, with values of 87.72 mg/L and 101.87 mg/L during the wet and dry seasons, respectively. Furthermore, distinct fluctuations in nitrate concentration were observed across different land use types, whereby vegetable lands manifested the maximum concentration. Prolonged exposure to elevated nitrate concentrations may pose potential health risks to residents, especially in the dry season when the non-carcinogenic groundwater nitrate risk surges past its wet season counterpart. The MixSIAR analysis revealed that chemical fertilizers accounted for the majority of nitrate pollution in vegetable lands, both during the dry season (49.6%) and wet season (41.2%). In contrast, manure and sewage contributed significantly to NO3-concentrations in residential land during the wet (74.9%) and dry seasons (67.6%). For croplands, soil nitrogen emerged as a dominant source during the wet season (42.2%), while chemical fertilizers prevailed in the dry season (38.7%). In addition to source variations, the nitrate concentration of groundwater is further affected by hydrogeological conditions, with more permeable aquifers tending to display higher nitrate concentrations. Thus, targeted measures were proposed to modify or impede the nitrogen migration pathway, taking into consideration hydrogeological conditions and incorporating domestic sewage, organic fertilizer, and agricultural management practices.

All-cause and cause-specific mortality in US adults with periodontal diseases: A prospective cohort study.

AIM: This prospective cohort study investigated the association between periodontal diseases (PDs) and all-cause and cause-specific mortality. MATERIALS AND METHODS: We utilized adult participants recruited from six National Health and Nutrition Examination Survey cycles (1999-2014) and linked mortality data from the National Death Index up to December 2019. Baseline clinical periodontal examinations were performed by trained and calibrated examiners. All-cause and cause-specific mortality was modelled through multivariable Cox proportional hazards and Fine-Gray models to account for competing risks. All models were adjusted for demographic and lifestyle variables, clinical measurements and comorbidities. RESULTS: Overall, 15,030 participants were included, with a median length of follow-up of 9 years. Risk of all-cause mortality was 22% greater in people with PD than the control group (adjusted hazard ratio [HR]: 1.22, 95% confidence interval [CI]: 1.12-1.31). Risks of mortality by cardiovascular diseases (CVD), respiratory disease and diabetes were highest in participants with severe PD (CVD-sub-distribution HR [SHR]: 1.38, 95% CI: 1.16-1.64; respiratory-SHR: 1.62, 95% CI: 1.07-2.45; diabetes-SHR: 1.68, 95% CI: 1.12-2.53). CONCLUSIONS: Severe PD is associated with all-cause and cause-specific mortality among US adults after multivariable adjustment.

The Effect of Dexmedetomidine as a Local Anesthetic Adjuvant for Iliac Fascia Compartment Block on Postoperative Delirium in Elderly Patients Undergoing Elective Hip Surgery.

INTRODUCTION: We analyzed the effect of dexmedetomidine (DEX) as a local anesthetic adjuvant on postoperative delirium (POD) in elderly patients undergoing elective hip surgery. METHODS: In this study, 120 patients undergoing hip surgery were enrolled and randomly assigned to two groups: fascia iliaca compartment block with DEX + ropivacaine (the Y group, n = 60) and fascia iliaca compartment block with ropivacaine (the R group, n = 60). The primary outcomes: presence of delirium during the postanesthesia care unit (PACU) period and on the first day (D1), the second day (D2), and the third day (D3) after surgery. The secondary outcomes: preoperative and postoperative C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR), occurrence of insomnia on the preoperative day, day of operation, D1 and D2; HR values of patients in both groups before iliac fascia block (T1), 30 min after iliac fascia block (T2), at surgical incision (T3), 20 min after incision (T4), when they were transferred out of the operating room (T5) and after leaving the recovery room (T6) at each time point; VAS for T1, PACU, D1, D2; the number of patients requiring remedial analgesics within 24 h after blockade and related complications between the two groups. RESULTS: A total of 97 patients were included in the final analysis, with 11 and 12 patients withdrawing from the R and Y groups, respectively. The overall incidence of POD and its incidence in the PACU and ward were all lesser in the Y group than in the R group (p < 0.05). Additionally, fewer cases required remedial analgesia during the PACU period, and more vasoactive drugs were used for maintaining circulatory system stability in the Y group as compared to the R group (p < 0.05). At the same time, the incidence of intraoperative and postoperative bradycardia in the Y group was higher than that in the R group, accompanied by lower postoperative CRP and ESR (all p < 0.05). CONCLUSION: Ultrasound-guided high fascia iliaca compartment block with a combination of ropivacaine and DEX can reduce the incidence of POD, the use of intraoperative opioids and postoperative remedial analgesics, and postoperative inflammation in elderly patients who have undergone hip surgery, indicating that this method could be beneficial in the prevention and treatment of POD.

Acute liver failure caused by high-dose tigecycline: A case report.

High-dose tigecycline is gradually being introduced for the treatment of serious infectious diseases due to the increasing difficulty in treating pan-resistant bacterial infections. However, the safety of high-dose tigecycline is controversial. We report the case of a 76-year-old female patient with cerebral hemorrhage who received high-dose tigecycline (100 mg q12h) with other drugs for ventilator-associated pneumonia. 25 days after admission, she developed acute liver failure, mainly manifested by abnormally high bilirubin, coagulation dysfunction, and gastrointestinal hemorrhage with hemorrhagic shock. According to the updated Roussel Uclaf causality assessment method, the patient's acute liver injury was most likely caused by tigecycline.

Clinical nomogram prediction model to assess the risk of prolonged ICU length of stay in patients with diabetic ketoacidosis: a retrospective analysis based on the MIMIC-IV database.

BACKGROUND: The duration of hospitalization, especially in the intensive care unit (ICU), for patients with diabetic ketoacidosis (DKA) is influenced by patient prognosis and treatment costs. Reducing ICU length of stay (LOS) in patients with DKA is crucial for optimising healthcare resources utilization. This study aimed to establish a nomogram prediction model to identify the risk factors influencing prolonged LOS in ICU-managed patients with DKA, which will serve as a basis for clinical treatment, healthcare safety, and quality management research. METHODS: In this single-centre retrospective cohort study, we performed a retrospective analysis using relevant data extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Clinical data from 669 patients with DKA requiring ICU treatment were included. Variables were selected using the Least Absolute Shrinkage and Selection Operator (LASSO) binary logistic regression model. Subsequently, the selected variables were subjected to a multifactorial logistic regression analysis to determine independent risk factors for prolonged ICU LOS in patients with DKA. A nomogram prediction model was constructed based on the identified predictors. The multivariate variables included in this nomogram prediction model were the Oxford acute severity of illness score (OASIS), Glasgow coma scale (GCS), acute kidney injury (AKI) stage, vasoactive agents, and myocardial infarction. RESULTS: The prediction model had a high predictive efficacy, with an area under the curve value of 0.870 (95% confidence interval [CI], 0.831-0.908) in the training cohort and 0.858 (95% CI, 0.799-0.916) in the validation cohort. A highly accurate predictive model was depicted in both cohorts using the Hosmer-Lemeshow (H-L) test and calibration plots. CONCLUSION: The nomogram prediction model proposed in this study has a high clinical application value for predicting prolonged ICU LOS in patients with DKA. This model can help clinicians identify patients with DKA at risk of prolonged ICU LOS, thereby enhancing prompt intervention and improving prognosis.

Predicting Inflammatory Arthritis in At-Risk Persons: Development of Scores for Risk Stratification.

BACKGROUND: Inflammatory arthritis (IA) is an immune-related condition defined by the presence of clinical synovitis. Its most common form is rheumatoid arthritis. OBJECTIVE: To develop scores for predicting IA in at-risk persons using multidimensional biomarkers. DESIGN: Prospective observational cohort study. SETTING: Single-center, Leeds, United Kingdom. PARTICIPANTS: Persons with new musculoskeletal symptoms, a positive test result for anticitrullinated protein antibodies, and no clinical synovitis and followed for 48 weeks or more or until IA occurred. MEASUREMENTS: A simple score was developed using logistic regression, and a comprehensive score was developed using the least absolute shrinkage and selection operator Cox proportional hazards regression. Internal validation with bootstrapping was estimated, and a decision curve analysis was done. RESULTS: Of 455 participants, 32.5% (148 of 455) developed IA, and 15.4% (70 of 455) developed it within 1 year. The simple score identified 249 low-risk participants with a false negative rate of 5% (and 206 high-risk participants with a false-positive rate of 72%). The comprehensive score identified 119 high-risk participants with a false-positive rate of 29% (and 336 low-risk participants with a false-negative rate of 19%); 40% of high-risk participants developed IA within 1 year and 71% within 5 years. LIMITATIONS: External validation is required. Recruitment occurred over 13 years, with lower rates of IA in later years. There was geographic variation in laboratory testing and recruitment availability. CONCLUSION: The simple score identified persons at low risk for IA who were less likely to need secondary care. The comprehensive score identified high-risk persons who could benefit from risk stratification and preventive measures. Both scores may be useful in clinical care and should also be useful in clinical trials. PRIMARY FUNDING SOURCE: National Institute for Health and Care Research Leeds Biomedical Research Centre.

Temporal trends of cause-specific mortality after diagnosis of atrial fibrillation.

BACKGROUND AND AIMS: Reports of outcomes after atrial fibrillation (AF) diagnosis are conflicting. The aim of this study was to investigate mortality and hospitalization rates following AF diagnosis over time, by cause and by patient features. METHODS: Individuals aged ≥16 years with a first diagnosis of AF were identified from the UK Clinical Practice Research Datalink-GOLD dataset from 1 January 2001, to 31 December 2017. The primary outcomes were all-cause and cause-specific mortality and hospitalization at 1 year following diagnosis. Poisson regression was used to calculate rate ratios (RRs) for mortality and incidence RRs (IRRs) for hospitalization and 95% confidence intervals (CIs) comparing 2001/02 and 2016/17, adjusted for age, sex, region, socio-economic status, and 18 major comorbidities. RESULTS: Of 72 412 participants, mean (standard deviation) age was 75.6 (12.4) years, and 44 762 (61.8%) had ≥3 comorbidities. All-cause mortality declined (RR 2016/17 vs. 2001/02 0.72; 95% CI 0.65-0.80), with large declines for cardiovascular (RR 0.46; 95% CI 0.37-0.58) and cerebrovascular mortality (RR 0.41; 95% CI 0.29-0.60) but not for non-cardio/cerebrovascular causes of death (RR 0.91; 95% CI 0.80-1.04). In 2016/17, deaths caused from dementia (67, 8.0%), outstripped deaths from acute myocardial infarction, heart failure, and acute stroke combined (56, 6.7%, P < .001). Overall hospitalization rates increased (IRR 2016/17 vs. 2001/02 1.17; 95% CI, 1.13-1.22), especially for non-cardio/cerebrovascular causes (IRR 1.42; 95% CI 1.39-1.45). Older, more deprived, and hospital-diagnosed AF patients experienced higher event rates. CONCLUSIONS: After AF diagnosis, cardio/cerebrovascular mortality and hospitalization has declined, whilst hospitalization for non-cardio/cerebrovascular disease has increased.

The nexus between urbanization and ecosystem services balance in China: A coupling perspective.

Urbanization inevitably interfered with the supply and demand of ecosystem services (ESs), which has a crucial impact on the ESs balance. Scientific exploration and clarification of the coupling and decoupling relationship between them can effectively reveal the disturbance of urbanization to the ecosystem, which can help to reasonably manage and protect the ecosystem. Previous studies have paid more attention to the coupling relationship but less attention to the decoupling relationship. This study comprehensively reflected urbanization from the three aspects of construction land, population, and economy and used the evaluation matrix to measure ESs. On this basis, coupling and decoupling analyses were taken to fully clarify the complex relationship between urbanization and ESs balance in China, so as to provide a reference for the formulation of relevant policies. Coupling aspect, the coupling degrees between the proportion of construction land (CLP) and ESs balance index (ESBI) were higher only in the central and eastern plains. The coupling degrees between population density (PD) and ESBI, economic density (ED) and ESBI, and land development index (LDI) and ESBI were only lower in the central and eastern plains than in other regions. Decoupling aspect, strong, weak negative, weak, and strong negative decoupling were the main decoupling types between urbanization and ESs balance in China. Among them, the proportion of the strong decoupling type is much higher than other types, which proves the opposite relationship between the two. Weak decoupling can not only promote economic growth and social development but also protect the ecological environment and biodiversity, which is a type of sustainable development and an ideal state that urbanization should pursue. The results can provide scientific guidance for the formulation of differentiated ecosystem management policies.

[Neutrophil extracellular traps extrusion from neutrophils stably adhered to ICAM-1 by lipoteichoic acid stimulation].

The effect of neutrophil extracellular traps (NETs) on promoting intravascular microthrombi formation and exacerbating the severity of sepsis in patients has gained extensive attention. However, in sepsis, the mechanisms and key signaling molecules mediating NET formation during direct interactions of endothelial cells and neutrophils still need further explored. Herein, we utilized lipoteichoic acid (LTA), a component shared by Gram-positive bacteria, to induce NET extrusion from neutrophils firmly adhered to the glass slides coated with intercellular adhesion molecule-1(ICAM-1). We also used Sytox green to label NET-DNA and Flou-4 AM as the intracellular Ca 2+ signaling indicator to observe the NET formation and fluctuation of Ca 2+ signaling. Our results illustrated that LTA was able to induce NET release from neutrophils firmly attached to ICAM-1-coated glass slides, and the process was time-dependent. In addition, our study indicated that LTA-induced NET release by neutrophils stably adhered to ICAM-1 depended on Ca 2+ signaling but not intracellular reactive oxygen species (ROS). This study reveals NET formation mediated by direct interactions between endothelial ICAM-1 and neutrophils under LTA stimulation and key signaling molecules involved, providing the theoretical basis for medicine development and clinical treatment for related diseases.

The involvement of transient receptor potential channels in mast cell activation by microbubbles.

This study was to explore the activation of mast cells by microbubbles, with the focus on transient receptor potential (TRP) channels mediated degranulation and calcium influx. Bone marrow-derived mast cells (BMMCs) were primarily obtained from femurs in mice and induced differentiation for 4 weeks. After the purity identification, BMMCs were contacted by homogeneous microbubbles with the diameter of 1 mm for 1 h. ß-hexosaminidase and histamine levels in supernatants were assessed by enzyme-linked immunosorbent assay (ELISA) and the CD63 expression was tested by flow cytometry. The intracellular calcium binding with Fluo-4 AM dyes in BMMCs was observed under the fluorescence microscope and the mean fluorescence intensity was quantitatively measured by flow cytometry. ß-hexosaminidase release, histamine concentration, CD63 expression and calcium influx were significantly increased in BMMCs group upon microbubble stimulation compared to the control groups. After preconditioning with the available inhibitors and microbubble contact, only transient receptor potential vanilloid 1 (TRPV1) and TRPV4 inhibitors robustly suppressed the microbubble-induced degranulation. Likewise, the elevated fluorescence intensity of cytosolic calcium level was also significantly weaken. The results demonstrated microbubble stimulus effectively promoted BMMCs degranulation, which could be substantially restrained by inhibitors targeted for blocking TRPV1 or TRPV4 channel. The alternation of intracellular calcium level in BMMCs was consistent with the changes of degranulation capacity. It's suggested that the activation of BMMCs by microbubbles may involve specific TRP calcium dependent channels.

Co-expression pattern of SLC transporter genes associated with the immune landscape and clinical outcomes in gastric cancer.

Solute carrier (SLC) transporters play a dual role in the occurrence and progression of tumours by acting as both suppressors and promoters. However, the overall impact of SLC transcriptome signatures on the tumour microenvironment, biological behaviour and clinical stratification of gastric cancer has not been thoroughly investigated. Therefore, we comprehensively analysed the expression profiles of the SLC transporter family members to identify novel molecular subtypes in gastric cancer. We identified two distinct SLC subtypes, SLC-S1 and SLC-S2, using non-negative matrix factorization. These subtypes were markedly linked with the tumour microenvironment landscape, biological pathway activation and distinct clinical features of gastric cancer. Furthermore, a new scoring model, the SLC score, was developed to quantify the SLC subtypes. High SLC scores indicated a pattern of 'SLC-S2', characterized by stromal infiltration and activation, poor prognosis and insensitivity to chemotherapy and immunotherapy, but high sensitivity to imatinib. The SLC score could serve as a supplement to the Tumour Node Metastasis (TNM) staging system to guide personalized treatment strategies and predict prognosis for patients with gastric cancer.

Red Cell Distribution Width-to-Platelet Count Ratio: A Promising Predictor of In-Hospital All-Cause Mortality in Critically Ill Patients with Acute Ischemic Stroke.

INTRODUCTION: The red blood cell distribution width-to-platelet ratio (RPR), a novel inflammatory index, has already been proven as a prognostic factor in some other diseases, but its prognostic effect on critically ill patients with acute ischemic stroke (AIS) has been rarely investigated. This study aimed to investigate the association between RPR and in-hospital mortality in these patients. METHODS: We extracted clinical data from the Medical Information Mart for Intensive Care IV 1.0 database. The primary outcome was in-hospital all-cause mortality of patients with critical AIS. The main independent variable was RPR. To investigate the association between RPR and in-hospital all-cause mortality in patients with critical AIS, multivariable logistic analyses, smooth curve fitting, and stratified analyses were conducted. RESULTS: In total, 2,673 patients with AIS who were admitted to the intensive care unit were included in the study. In the multivariable analysis, in-hospital mortality was positively related to RPR (odds ratio [OR] 1.28, 95% confidence interval [CI] 1.02-1.59). According to the two-piecewise logistic regression model, we found that the inflection point of RPR was 1.89%. To the left of the inflection point (RPR ≤1.89%), we did not detect any relationship between RPR and in-hospital all-cause mortality (OR [95% CI]: 0.73 [0.41, 1.31], p = 0.2884). In contrast, to the right of the inflection point (RPR >1.89%), RPR was positively related to in-hospital all-cause mortality (OR [95% CI]: 1.61 [1.18, 2.19], p = 0.0027). CONCLUSIONS: RPR showed a nonlinear relationship with in-hospital all-cause mortality in patients with critical AIS.

Can biomarkers predict successful tapering of conventional disease-modifying therapy in rheumatoid arthritis patients in stable remission?

OBJECTIVES: Specific guidelines for managing RA patients in clinical remission for ≥6 months on cs-DMARDs are lacking. Tapering of treatment is encouraged, however, without validated biomarkers for success. We aimed to assess the rate of sustained remission after 12 months in patients who either (i) followed structured cs-DMARD tapering or (ii) continued therapy, focusing on the added value of biomarkers as predictors of outcome. METHODS: RA patients fulfilling 3v-DAS28CRP<2.6 for ≥6 months on stable cs-DMARD therapy were included. Patients were offered structured tapering, with 117 accepting tapering and 83 continuing therapy. Clinical, ultrasound, immunological (T-cell subsets) and patient-reported outcome (PRO) data were collected. The primary endpoint was the proportion of patients in sustained remission without relapse after 12 months. Regression analyses were used to identify predictors of sustained remission. RESULTS: Of those who tapered, 64% remained in clinical remission after 12 months compared with 80% (p=0.018) of patients on stable treatment. In the tapering group, higher levels of CRP, TJC, % inflammation-related T-cell (IRC) and PROs were associated with flare (all p<0.05), with a trend for total PD (p=0.066). A model predicting sustained remission retained RAQoL, total PD and IRC (85% accuracy, AUROC=0.893, p<0.0001). In the non-tapering group, higher CRP, ESR, SJC and shorter disease duration (all p<0.05) were associated with flare, with no parameter able to predict sustained remission. CONCLUSIONS: In the tapering group, the combination of clinical, PRO, US and T-cell parameters demonstrated added value for predicting sustained remission compared with clinical parameters alone. These data may inform best tapering practice.

The molecular mechanism of non-covalent inhibitor WU-04 targeting SARS-CoV-2 3CLpro and computational evaluation of its effectiveness against mainstream coronaviruses.

There is an urgent need for highly effective therapeutic agents to interrupt the continued spread of SARS-CoV-2. As a pivotal protease in the replication process of coronaviruses, the 3CLpro protein is considered as a potential target of drug development to stop the spread and infection of the virus. In this work, molecular dynamics (MD) simulations were used to elucidate the molecular mechanism of a novel and highly effective non-covalent inhibitor, WU-04, targeting the SARS-CoV-2 3CLpro protein. The difference in dynamic behavior between the apo-3CLpro and the holo-3CLpro systems suggests that the presence of WU-04 inhibits the motion amplitude of the 3CLpro protein relative to the apo-3CLpro system, thus maintaining a stable conformational binding state. The energy calculations and interaction analysis show that the hot-spot residues Q189, M165, M49, E166, and H41 and the warm-spot residues H163 and C145 have a strong binding capacity to WU-04 by forming multiple hydrogen bonds and hydrophobic interactions, which stabilizes the binding of the inhibitor. After that, the resistance of WU-04 to the six SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, Lambda, and Omicron) and two other mainstream coronavirus (SARS-CoV and MERS-CoV) 3CLpro proteins was further investigated. Excitingly, the slight difference in energy values relative to the SARS-CoV-2 system indicates that WU-04 is still highly effective against the coronaviruses, which becomes crucial evidence that WU-04 is a pan-inhibitor of the 3CLpro protein in various SARS-CoV-2 variants and other mainstream coronaviruses. The study will hopefully provide theoretical insights for the future rational design and improvement of novel non-covalent inhibitors targeting the 3CLpro protein.

Investigation on the interaction mechanism of different SARS-CoV-2 spike variants with hACE2: insights from molecular dynamics simulations.

Since the COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), SARS-CoV-2 has evolved by acquiring genomic mutations, resulting in the recent emergence of several SARS-CoV-2 variants with improved transmissibility and infectivity relative to the original strain. An underlying mechanism may be the increased ability of the mutants to bind the receptor proteins and infect the host cell. In this work, we implemented all-atom molecular dynamics (MD) simulations to study the binding and interaction of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein singly (D614G), doubly (D614G + L452R and D614G + N501Y), triply (D614G + N501Y + E484K), and quadruply (D614G + N501Y + E484K + K417T) mutated variants with the human angiotensin-converting enzyme 2 (hACE2) receptor protein in the host cell. A combination of multiple analysis approaches elucidated the effects of mutations and the extent of molecular divergence from multiple perspectives, including the dynamic correlated motions, interaction patterns, dominant motions, free energy landscape, and charge distribution on the electrostatic potential surface between the hACE2 and all RBD variants. Moreover, free energy calculations using the MM/PBSA method evaluated the binding affinity between these RBD variants and hACE2. The results showed that the D614G + N501Y + E484K variant possessed the lowest free energy value (highest affinity) compared to the D614G + N501Y + E484K + K417T, D614G + L452R, D614G + N501Y, and D614G mutants. The residue-based energy decomposition also indicated that the energy contribution of residues at the mutation site to the total binding energy was highly variable. The interaction mechanisms between the different RBD variants and hACE2 elucidated in this study will provide some insights into the development of drugs targeting the new SARS-CoV-2 variants.

In silico design of miniprotein to inhibit SARS-CoV-2 variant Omicron spike protein.

Omicron is a novel variant of SARS-CoV-2 that is currently spreading globally as the dominant strain. The virus first enters the host cell through the receptor binding domain (RBD) of the spike protein by interacting with the angiotensin-converting enzyme 2 (ACE2). Thus, the RBD protein is an ideal target for the design of drugs against the Omicron variant. Here, we designed several miniprotein inhibitors in silico to combat the SARS-CoV-2 Omicron variant using single- and double-point mutation approaches, based on the structure of the initial inhibitor AHB2. Also, two parallel molecular dynamics (MD) simulations were performed for each system to reproduce the calculated results, and the binding free energy was evaluated with the MM/PBSA method. The evaluated values showed that all inhibitors, including AHB2, M7E, M7E + M43W, and M7E + M43Y, were energetically more beneficial to the binding with the RBD than ACE2. In particular, the mutant inhibitor M7E + M43Y possessed the highest binding affinity to RBD and was selected as the most promising "best" inhibitor among all inhibitors. In addition, the combination of multiple analysis methods, such as free energy landscape analysis (FEL), principal component analysis (PCA), dynamic cross-correlation matrix analysis (DCCM), and hydrogen bond, salt bridge, and hydrophobic interaction analysis, also demonstrated that the mutations significantly affect the dynamical behavior and binding pattern of the inhibitor binding to the RBD protein. The current work suggested that miniprotein inhibitors can form stable complex structures with the RBD protein and exert a blocking or inhibitory effect on the SARS-CoV-2 variant Omicron. In conclusion, this study has identified several novel mutant inhibitors with enhanced affinity to the RBD protein, and provided potential guidance and insights for the rational design of therapeutic approaches for the new SARS-CoV-2 variant Omicron.

Application effect of an artificial intelligence-based fundus screening system: evaluation in a clinical setting and population screening.

BACKGROUND: To investigate the application effect of artificial intelligence (AI)-based fundus screening system in real-world clinical environment. METHODS: A total of 637 color fundus images were included in the analysis of the application of the AI-based fundus screening system in the clinical environment and 20,355 images were analyzed in the population screening. RESULTS: The AI-based fundus screening system demonstrated superior diagnostic effectiveness for diabetic retinopathy (DR), retinal vein occlusion (RVO) and pathological myopia (PM) according to gold standard referral. The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of three fundus abnormalities were greater (all > 80%) than those for age-related macular degeneration (ARMD), referable glaucoma and other abnormalities. The percentages of different diagnostic conditions were similar in both the clinical environment and the population screening. CONCLUSIONS: In a real-world setting, our AI-based fundus screening system could detect 7 conditions, with better performance for DR, RVO and PM. Testing in the clinical environment and through population screening demonstrated the clinical utility of our AI-based fundus screening system in the early detection of ocular fundus abnormalities and the prevention of blindness.