Causal relationship between rheumatoid arthritis and epilepsy in a European population: a univariate and multivariate Mendelian randomization study

BackgroundSeveral previous studies have reported an association between rheumatoid arthritis (RA) and epilepsy, but the causal relationship is unclear. The aim of this study was to assess the connection between RA and epilepsy in a European population using Mendelian randomization (MR).MethodsGenome-wide association study summary data on RA and epilepsy from European populations were included. Univariate MR (UVMR) and multivariate MR were used to investigate the causal relationship between the two conditions. Three analysis methods were applied: inverse variance weight (IVW), MR-Egger, and weighted median, with IVW being the primary method. Cochran Q statistics, MR-PRESSO, MR-Egger intercept, leave-one-out test, and MR-Steiger test were combined for the sensitivity analysis.ResultsUVMR showed a positive association between RA and epilepsy risk (OR=1.038, 95% CI=1.007–1.038, p=0.017) that was supported by sensitivity analysis. Further MVMR after harmonizing the three covariates of hypertension, alcohol consumption, and smoking, confirmed the causal relationship between RA and epilepsy (OR=1.049, 95% CI=1.011–1.087, p=0.010).ConclusionThis study demonstrated that RA is associated with an increased risk of epilepsy. It has emphasized that the monitoring of epilepsy risk in patients diagnosed with RA should be strengthened in clinical practice, and further studies are needed in the future to explore the potential mechanism of action connecting the two conditions

Combined miRNA and mRNA sequencing reveals the defensive strategies of resistant YHY15 rice against differentially virulent brown planthoppers

IntroductionThe brown planthopper (BPH) poses a significant threat to rice production in Asia. The use of resistant rice varieties has been effective in managing this pest. However, the adaptability of BPH to resistant rice varieties has led to the emergence of virulent populations, such as biotype Y BPH. YHY15 rice, which carries the BPH resistance gene Bph15, exhibits notable resistance to biotype 1 BPH but is susceptible to biotype Y BPH. Limited information exists regarding how resistant rice plants defend against BPH populations with varying levels of virulence.MethodsIn this study, we integrated miRNA and mRNA expression profiling analyses to study the differential responses of YHY15 rice to both avirulent (biotype 1) and virulent (biotype Y) BPH.ResultsYHY15 rice demonstrated a rapid response to biotype Y BPH infestation, with significant transcriptional changes occurring within 6 hours. The biotype Y-responsive genes were notably enriched in photosynthetic processes. Accordingly, biotype Y BPH infestation induced more intense transcriptional responses, affecting miRNA expression, defenserelated metabolic pathways, phytohormone signaling, and multiple transcription factors. Additionally, callose deposition was enhanced in biotype Y BPH-infested rice seedlings.DiscussionThese findings provide comprehensive insights into the defense mechanisms of resistant rice plants against virulent BPH, and may potentially guide the development of insect-resistant rice varieties

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A bi-objective model for robust local container drayage problem

Local Container Drayage Problem (LCDP) refers to the optimization of the process of planning and scheduling container trucks between a terminal and customers to offer door-to-door service to customers in a local area. The time required for (un)packing containers at customers’ sites are often relatively long and uncertain due to the current (un)packing work level and unexpected deviations in operational situations, which has a significant influence on the planning and scheduling of the container transportation process. This paper examines the LCDP with Separable tractors and trailers, and additionally with consideration of (un)packing time Uncertainties (LCDPSU). A proactive strategy is employed to tackle the uncertainty by proposing a “model robust” bi-objective optimization model to balance the tradeoff between operational cost, which includes traveling cost and tractor deployment setup cost, and robustness, which is represented as an exponential expression of the time buffer between two stages of each individual task. The deterministic version of our problem is proved to be NP hard, and an Ant Colony Optimization (ACO) scheme is therefore proposed to search for feasible solutions in which the Zoutendijk feasible direction algorithm is embedded in order to tackle the nonlinearity brought in by the robustness of the model. Numerical experiments are conducted to validate the efficiencies and effectivenesses of the proposed models and methods, and managerial implications are drawn from the numerical results

Heat Pipe Thermal Management Based on High-Rate Discharge and Pulse Cycle Tests for Lithium-Ion Batteries

A battery thermal management system (BTMS) ensures that batteries operate efficiently within a suitable temperature range and maintains the temperature uniformity across the battery. A strict requirement of the BTMS is that increases in the battery discharge rate necessitate an increased battery heat dissipation. The advantages of heat pipes (HPs) include a high thermal conductivity, flexibility, and small size, which can be utilized in BTMSs. This paper experimentally examines a BTMS using HPs in combination with an aluminum plate to increase the uniformity in the surface temperature of the battery. The examined system with high discharge rates of 50, 75, and 100 A is used to determine its effects on the system temperature. The results are compared with those for HPs without fins and in ambient conditions. At a 100 A discharge current, the increase in battery temperature using the heat pipe with fins (HPWF) method is 4.8 °C lower than for natural convection, and the maximum temperature difference between the battery surfaces is 1.7 °C and 6.0 °C. The pulse circulation experiment was designed considering that the battery operates with a pulse discharge and temperature hysteresis. The depth of discharge is also considered, and the states-of-charge (SOC) values were 0.2, 0.5, and 0.8. The results of the two heat dissipation methods are compared, and the optimal heat dissipation structure is obtained by analyzing the experimental results. The results show that when the ambient temperature is 37 °C, differences in the SOC do not affect the battery temperature. In addition, the HPWF, HP, and natural convection methods reached stable temperatures of 40.8, 44.3, and the 48.1 °C, respectively the high temperature exceeded the battery operating temperature range

A Temperature Compensation Approach for Micro-Electro-Mechanical Systems Accelerometer Based on Gated Recurrent Unit–Attention and Robust Local Mean Decomposition–Sample Entropy–Time-Frequency Peak Filtering

MEMS accelerometers are significantly impacted by temperature and noise, leading to a considerable compromise in their accuracy. In response to this challenge, we propose a parallel denoising and temperature compensation fusion algorithm for MEMS accelerometers based on RLMD-SE-TFPF and GRU-attention. Firstly, we utilize robust local mean decomposition (RLMD) to decompose the output signal of the accelerometer into a series of product function (PF) signals and a residual signal. Secondly, we employ sample entropy (SE) to classify the decomposed signals, categorizing them into noise segments, mixed segments, and temperature drift segments. Next, we utilize the time-frequency peak filtering (TFPF) algorithm with varying window lengths to separately denoise the noise and mixed signal segments, enabling subsequent signal reconstruction and training. Considering the strong inertia of the temperature signal, we innovatively introduce the accelerometer’s output time series as the model input when training the temperature compensation model. We incorporate gated recurrent unit (GRU) and attention modules, proposing a novel GRU-MLP-attention model (GMAN) architecture. Simulation experiments demonstrate the effectiveness of our proposed fusion algorithm. After processing the accelerometer output signal through the RLMD-SE-TFPF denoising algorithm and the GMAN temperature drift compensation model, the acceleration random walk is reduced by 96.11%, with values of 0.23032 g/h/Hz for the original accelerometer output signal and 0.00895695 g/h/Hz for the processed signal