Abstract Background The association between body mass index (BMI) and Alzheimer's disease (AD) remains controversial. Genetic and environmental factors are now considered contributors to AD risk. However, little is known about the potential interaction between genetic risk and BMI on AD risk. Objective To study the causal relationship between BMI and AD, and the potential interaction between AD genetic risk and BMI on AD risk. Methods and Results Using the UK Biobank database, 475,813 participants were selected for an average follow-up time of more than 10 years. Main findings: 1) there was a nonlinear relationship between BMI and AD risk in participants aged 60 years or older ( p for non-linear < 0.001), but not in participants aged 37–59 years ( p for non-linear = 0.717) using restricted cubic splines; 2) for participants aged 60 years and older, compared with the BMI (23–30 kg/m 2 ) group, the BMI (< 23 kg/m 2 ) group was associated with a higher AD risk (HR = 1.585; 95% CI 1.304–1.928, p < 0.001) and the BMI (> 30 kg/m 2 ) group was associated with a lower AD risk (HR = 0.741; 95% CI 0.618–0.888, p < 0.01) analyzed using the Cox proportional risk model; 3) participants with a combination of high AD genetic risk score (AD-GRS) and BMI (< 23 kg/m 2 ) were associated with the highest AD risk (HR = 3.034; 95% CI 2.057–4.477, p < 0.001). In addition, compared with the BMI (< 23 kg/m 2 ), the higher BMI was associated with a lower risk of AD in participants with the same intermediate or high AD-GRS; 4) there was a reverse causality between BMI and AD when analyzed using bidirectional Mendelian randomization (MR). Conclusion There was a reverse causality between BMI and AD analyzed using MR. For participants aged 60 years and older, the higher BMI was associated with a lower risk of AD in participants with the same intermediate or high AD genetic risk. BMI (23–30 kg/m 2 ) may be a potential intervention for AD.
Background: Ventilator-associated pneumonia (VAP) is a common infection complication in intensive care units (ICU). It not only prolongs mechanical ventilation and ICU and hospital stays, but also increases medical costs and increases the mortality risk of patients. Although many studies have found that thiamine supplementation in critically ill patients may improve prognoses, there is still no research or evidence that thiamine supplementation is beneficial for patients with VAP. The purpose of this study was to determine the association between thiamine and the prognoses of patients with VAP. Methods: This study retrospectively collected all patients with VAP in the ICU from the Medical Information Mart for Intensive Care-IV database. The outcomes were ICU and in-hospital mortality. Patients were divided into the no-thiamine and thiamine groups depending upon whether or not they had received supplementation. Associations between thiamine and the outcomes were tested using Kaplan-Meier (KM) survival curves and Cox proportional-hazards regression models. The statistical methods of propensity-score matching (PSM) and inverse probability weighting (IPW) based on the XGBoost model were also applied to ensure the robustness of our findings. Results: The study finally included 1,654 patients with VAP, comprising 1,151 and 503 in the no-thiamine and thiamine groups, respectively. The KM survival curves indicated that the survival probability differed significantly between the two groups. After multivariate COX regression adjusted for confounding factors, the hazard ratio (95% confidence interval) values for ICU and in-hospital mortality in the thiamine group were 0.57 (0.37, 0.88) and 0.64 (0.45, 0.92), respectively. Moreover, the results of the PSM and IPW analyses were consistent with the original population. Conclusion: Thiamine supplementation may reduce ICU and in-hospital mortality in patients with VAP in the ICU. Thiamine is an inexpensive and safe drug, and so further clinical trials should be conducted to provide more-solid evidence on whether it improves the prognosis of patients with VAP.
Background: Previous studies have suggested that antidiabetic drug use may be associated with amyotrophic lateral sclerosis. However, these studies are limited by many confounding and reverse causality biases. We aimed to determine whether antidiabetic drug use has causal effects on ALS. Methods: Drug-target Mendelian randomization analysis was conducted to evaluate the association between genetic variation in the targets of antidiabetic drugs and ALS risk. The antidiabetic drugs included sulfonylureas, GLP-1 analogues, thiazolidinediones, insulin/insulin analogues, metformin, and SGLT2 inhibitors. Summary statistics for ALS were retrieved from previous genome-wide association studies comprising 27,205 ALS patients and 55,058 controls. The instrumental variables for these drugs are from previous published articles. Results: Genetic variation in SGLT2 inhibition targets was associated with lower risk of ALS (odds ratio [OR] = 0.32, 95% CI = 0.14–0.74; p = 0.008). We did not find that genetic variation in metformin targets was associated with ALS (OR = 1.61, 95% CI = 0.94–2.73; p = 0.081). Nevertheless, mitochondrial complex I, a target of metformin, was associated with a higher risk of ALS (OR = 1.83, 95% CI = 1.01–3.32; p = 0.047). The analysis showed that genetic variation in sulfonylureas, GLP-1 analogues, thiazolidinediones, insulin or insulin analogues targets was not associated with ALS (all p > 0.05). Conclusions: The complex interaction between hypoglycemic, antioxidation, and anti-inflammatory effects may account for the different results across antidiabetic drug types. These findings provide key evidence to guide the use of antidiabetic drugs and will help to identify novel therapeutic targets in ALS.
Objective To explore the correlations of high-density lipoprotein cholesterol (HDL-C)/low-density lipoprotein cholesterol (LDL-C) with myocardial infarction (MI), all-cause mortality, haemorrhagic stroke and ischaemic stroke, as well as the joint association of genetic susceptibility and HDL-C/LDL-C with the MI risk. Methods and results This study selected 384 093 participants from the UK Biobank (UKB) database. First, restricted cubic splines indicated non-linear associations of HDL-C/LDL-C with MI, ischaemic stroke and all-cause mortality. Second, a Cox proportional-hazards model indicated that compared with HDL-C/LDL-C=0.4–0.6, HDL-C/LDL-C<0.4 and >0.6 were correlated with all-cause mortality (HR=0.97 for HDL-C/LDL-C<0.4, 95% CI=0.939 to 0.999, p<0.05; HR=1.21 for HDL-C/LDL-C>0.6, 95% CI=1.16 to 1.26, p<0.001) after full multivariable adjustment. HDL-C/LDL-C<0.4 was correlated with a higher MI risk (HR=1.36, 95% CI=1.28 to 1.44, p<0.05) and ischaemic stroke (HR=1.12, 95% CI=1.02 to 1.22, p<0.05) after full multivariable adjustment. HDL-C/LDL-C>0.6 was associated with higher risk haemorrhagic stroke risk after full multivariable adjustment (HR=1.25, 95% CI=1.03 to 1.52, p<0.05). Third, after calculating the coronary heart disease Genetic Risk Score (CHD-GRS) of each participant, the Cox proportional-hazards model indicated that compared with low CHD-GRS and HDL-C/LDL-C=0.4–0.6, participants with a combination of high CHD-GRS and HDL-C/LDL-C<0.4 were associated with the highest MI risk (HR=2.45, 95% CI=2.15 to 2.8, p<0.001). Participants with HDL-C/LDL-C<0.4 were correlated with a higher MI risk regardless of whether they had a high, intermediate or low CHD-GRS. Conclusion In UKB participants, HDL-C/LDL-C ratio of 0.4–0.6 was correlated with lower MI risk, all-cause mortality, haemorrhagic stroke and ischaemic stroke. Participants with HDL-C/LDL-C<0.4 were correlated with a higher MI risk regardless of whether they had a high, intermediate or low CHD-GRS. The clinical significance and impact of HDL-C/LDL-C need to be further verified in future studies.
We studied the first 202 patients with rheumatic mitral stenosis (MS) who underwent percutaneous balloon mitral valvuloplasty (PBMV) with the Inoue balloon catheter for a follow-up (FU) period of 5-11 years. Pre- and post-PBMV and at FU, the mean left atrial pressure was 21.3+/-7.4, 10.2+/-5.6, and 11.2+/-4.1 mm Hg; mean diastolic mitral gradient was 18.4+/-7.3, 2.9+/-3.2, and 5.1+/-4.3 mm Hg; and mitral valve area was 1.0+/-0.3, 2.1+/-0.6, and 1.7+/-0.5 cm2. Functional status improved from New York Heart Association (NYHA) class IV in 3, class III in 119, and class II in 80 pre-PBMV to class I in 163, class II in 37, and class III in 2 post-PBMV, and was class I in 146, class II in 39, and class III in 17 patients at FU. In the 17 patients with NYHA class III at FU, mitral restenosis was the culprit; 4 underwent repeat PBMV, 12 had mitral valve replacement for severe mitral calcification and subvalvular fusion, and 1 refused further intervention. Thus PBMV using the Inoue balloon catheter is an effective method of relieving MS with excellent long-term results in patients without severe mitral calcification and subvalvular fusion.
Background: Patients with metabolic syndrome (MetS) have a higher risk of developing cardiovascular diseases (CVD). However, controversy exists about the impact of MetS on the prognosis of patients with CVD. Methods: Pubmed, Cochrane library, and EMBASE databases were searched. Cohort Studies and randomized controlled trials post hoc analyses that evaluated the impact of MetS on prognosis in patients (≥18 years) with CVD were included. Relative risk (RR), hazard rate (HR) and 95% confidence intervals (CIs) were calculated for each individual study by random-effect model. Subgroup analysis and meta-regression analysis was performed to explore the heterogeneity. Results: 55 studies with 16,2450 patients were included. Compared to patients without MetS, the MetS was associated with higher all-cause death [RR, 1.220, 95% CI (1.103 to 1.349), P , 0.000], CV death [RR, 1.360, 95% CI (1.152 to 1.606), P , 0.000], Myocardial Infarction [RR, 1.460, 95% CI (1.242 to 1.716), P , 0.000], stroke [RR, 1.435, 95% CI (1.131 to 1.820), P , 0.000]. Lower high-density lipoproteins (40/50) significantly increased the risk of all-cause death and CV death. Elevated fasting plasma glucose (FPG) (>100 mg/dl) was associated with an increased risk of all-cause death, while a higher body mass index (BMI>25 kg/m 2 ) was related to a reduced risk of all-cause death. Conclusions: MetS increased the risk of cardiovascular-related adverse events among patients with CVD. For MetS components, there was an increased risk in people with low HDL-C and FPG>100 mg/dl. Positive measures should be implemented timely for patients with CVD after the diagnosis of MetS, strengthen the prevention and treatment of hyperglycemia and hyperlipidemia.
Many high quality studies have emerged from public databases, such as Surveillance, Epidemiology, and End Results (SEER), National Health and Nutrition Examination Survey (NHANES), The Cancer Genome Atlas (TCGA), and Medical Information Mart for Intensive Care (MIMIC); however, these data are often characterized by a high degree of dimensional heterogeneity, timeliness, scarcity, irregularity, and other characteristics, resulting in the value of these data not being fully utilized. Data-mining technology has been a frontier field in medical research, as it demonstrates excellent performance in evaluating patient risks and assisting clinical decision-making in building disease-prediction models. Therefore, data mining has unique advantages in clinical big-data research, especially in large-scale medical public databases. This article introduced the main medical public database and described the steps, tasks, and models of data mining in simple language. Additionally, we described data-mining methods along with their practical applications. The goal of this work was to aid clinical researchers in gaining a clear and intuitive understanding of the application of data-mining technology on clinical big-data in order to promote the production of research results that are beneficial to doctors and patients.
Recent works have been exploring the scaling laws in the field of Embodied AI. Given the prohibitive costs of collecting real-world data, we believe the Simulation-to-Real (Sim2Real) paradigm is a crucial step for scaling the learning of embodied models. This paper introduces project GRUtopia, the first simulated interactive 3D society designed for various robots. It features several advancements: (a) The scene dataset, GRScenes, includes 100k interactive, finely annotated scenes, which can be freely combined into city-scale environments. In contrast to previous works mainly focusing on home, GRScenes covers 89 diverse scene categories, bridging the gap of service-oriented environments where general robots would be initially deployed. (b) GRResidents, a Large Language Model (LLM) driven Non-Player Character (NPC) system that is responsible for social interaction, task generation, and task assignment, thus simulating social scenarios for embodied AI applications. (c) The benchmark, GRBench, supports various robots but focuses on legged robots as primary agents and poses moderately challenging tasks involving Object Loco-Navigation, Social Loco-Navigation, and Loco-Manipulation. We hope that this work can alleviate the scarcity of high-quality data in this field and provide a more comprehensive assessment of Embodied AI research. The project is available at https://github.com/OpenRobotLab/GRUtopia.
Obesity rates have nearly tripled in the past 50 years, and by 2030 more than 1 billion individuals worldwide are projected to be obese. This creates a significant economic strain due to the associated non-communicable diseases. The root cause is an energy expenditure imbalance, owing to an interplay of lifestyle, environmental, and genetic factors. Obesity has a polygenic genetic architecture; however, single genetic variants with large effect size are etiological in a minority of cases. These variants allowed the discovery of novel genes and biology relevant to weight regulation and ultimately led to the development of novel specific treatments.
In the fields of CNN, there exists many multiply applications with one fixed operand. In view of such characteristics, this paper proposes a preprocessing-based power-efficient approximate multiplier (PPBAM) design for CNN. In the proposed design, the fixed operand is preprocessed to avoid additional dynamic power consumption due to repeated processing. To reduce the number of the partial products, the first '1' of both two operands are found and then the operands are truncated by a method named weak rounding. What's more, a sub multiplier array utilizing an approximate 4:2 compressor are proposed to calculate the truncation results with low power. The experimental results show that, with the same accuracy, on average, our design has a 30% improvement in power consumption compared with state-of-the-art approximate multiplier designs without additional latency and area.
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