Associations between Aquaglyceroporin Gene Polymorphisms and Risk of Stroke among Patients with Hypertension

Background: Dysregulations ofAQP7andAQP9were found to be related to lipid metabolism abnormality, which had been provento be one of the mechanisms of stroke. However, limited epidemiological studies explore the associations betweenAQP7andAQP9and the risk of stroke among patients with hypertension in China. Aims: We aimed to investigate the associations between genetic variants in AQP7andAQP9and the risk of stroke among patients with hypertension, as well as to explore gene-gene andgene-environment interactions. Methods: Baseline blood samples were drawn from 211 cases with stroke and 633 matched controls. Genomic DNA was extracted by a commercially available kit. Genotyping of 5 single nucleotide polymorphisms (SNPs) in AQP7 (rs2989924, rs3758269, and rs2542743) and AQP9 (rs57139208, rs16939881) was performed by the polymerase chain reaction assay with TaqMan probes. Results: Participants with the rs2989924 GG genotype were found to be with a 1.74-fold increased risk of stroke compared to those with the AA+AG genotype, and this association remained significant after adjustment for potential confounders (odds ratio (OR): 1.74, 95% confidence interval (CI): 1.23-2.46). The SNP rs3758269 CC+TT genotype was found to be with a 33% decreased risk of stroke after multivariate adjustment (OR: 0.67, 95% CI: 0.45-0.99) compared to the rs3758269 CC genotype. The significantly increased risk of stroke was prominent among males, patients aged 60 or above, and participants who were overweight and with a harbored genetic variant in SNP rs2989924. After adjusting potential confounders, the SNP rs3758269 CT+TT genotype was found to be significantly associated with a decreased risk of stroke compared to the CC genotype among participants younger than 60 years old or overweight. No statistically significant associations were observed between genotypes of rs2542743, rs57139208, or rs16939881 with the risk of stroke. Neither interactions nor linkage disequilibrium had been observed in this study. Conclusions: This study suggests that SNPs rs2989924 and rs3758269 are associated with the risk of stroke among patients with hypertension, while there were no statistically significant associations between rs2542743, rs57139208, and rs16939881 and the risk of stroke being observed

Coordinate Channel-Aware Page Mapping Policy and Memory Scheduling for Reducing Memory Interference Among Multimedia Applications

"© 2017 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."[EN] In a modern multicore system, memory is shared among more and more concurrently running multimedia applications. Therefore, memory contention and interference are more andmore serious, inducing system performance degradation significantly, the performance degradation of each thread differently, unfairness in resource sharing, and priority inversion, even starvation. In this paper, we propose an approach of coordinating channel-aware page mapping policy and memory scheduling (CCPS) to reduce intermultimedia application interference in a memory system. The idea is to map the data of different threads to different channels, together with memory scheduling. The key principles of the policies of page mapping and memory scheduling are: 1) the memory address space, the thread priority, and the load balance; and 2) prioritizing a low-memory request thread, a row-buffer hit access, and an older request. We evaluate the CCPS on a variety of mixed single-thread and multithread benchmarks and system configurations, and we compare them with four previously proposed state-of-the-art interference-reducing policies. Experimental results demonstrate that the CCPS improves the performance while reducing the energy consumption significantly; moreover, the CCPS incurs a much lower hardware overhead than the current existing policies.This work was supported in part by the Qing Lan Project; by the National Science Foundation of China under Grant 61003077, Grant 61100193, and Grant 61401147; and by the Zhejiang Provincial Natural Science Foundation under Grant LQ14F020011.Jia, G.; Han, G.; Li, A.; Lloret, J. (2017). Coordinate Channel-Aware Page Mapping Policy and Memory Scheduling for Reducing Memory Interference Among Multimedia Applications. IEEE Systems Journal. 11(4):2839-2851. https://doi.org/10.1109/JSYST.2015.2430522S2839285111

Telepath: Understanding Users from a Human Vision Perspective in Large-Scale Recommender Systems

Designing an e-commerce recommender system that serves hundreds of millions of active users is a daunting challenge. From a human vision perspective, there're two key factors that affect users' behaviors: items' attractiveness and their matching degree with users' interests. This paper proposes Telepath, a vision-based bionic recommender system model, which understands users from such perspective. Telepath is a combination of a convolutional neural network (CNN), a recurrent neural network (RNN) and deep neural networks (DNNs). Its CNN subnetwork simulates the human vision system to extract key visual signals of items' attractiveness and generate corresponding activations. Its RNN and DNN subnetworks simulate cerebral cortex to understand users' interest based on the activations generated from browsed items. In practice, the Telepath model has been launched to JD's recommender system and advertising system. For one of the major item recommendation blocks on the JD app, click-through rate (CTR), gross merchandise value (GMV) and orders have increased 1.59%, 8.16% and 8.71% respectively. For several major ads publishers of JD demand-side platform, CTR, GMV and return on investment have increased 6.58%, 61.72% and 65.57% respectively by the first launch, and further increased 2.95%, 41.75% and 41.37% respectively by the second launch.Comment: 8 pages, 11 figures, 1 tabl

A Lightweight Transmission Parameter Selection Scheme Using Reinforcement Learning for LoRaWAN

The number of IoT devices is predicted to reach 125 billion by 2023. The growth of IoT devices will intensify the collisions between devices, degrading communication performance. Selecting appropriate transmission parameters, such as channel and spreading factor (SF), can effectively reduce the collisions between long-range (LoRa) devices. However, most of the schemes proposed in the current literature are not easy to implement on an IoT device with limited computational complexity and memory. To solve this issue, we propose a lightweight transmission-parameter selection scheme, i.e., a joint channel and SF selection scheme using reinforcement learning for low-power wide area networking (LoRaWAN). In the proposed scheme, appropriate transmission parameters can be selected by simple four arithmetic operations using only Acknowledge (ACK) information. Additionally, we theoretically analyze the computational complexity and memory requirement of our proposed scheme, which verified that our proposed scheme could select transmission parameters with extremely low computational complexity and memory requirement. Moreover, a large number of experiments were implemented on the LoRa devices in the real world to evaluate the effectiveness of our proposed scheme. The experimental results demonstrate the following main phenomena. (1) Compared to other lightweight transmission-parameter selection schemes, collisions between LoRa devices can be efficiently avoided by our proposed scheme in LoRaWAN irrespective of changes in the available channels. (2) The frame success rate (FSR) can be improved by selecting access channels and using SFs as opposed to only selecting access channels. (3) Since interference exists between adjacent channels, FSR and fairness can be improved by increasing the interval of adjacent available channels.Comment: 14 pages, 12 figures, 8 tables. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Incidence and factors associated of early non-response in first-treatment and drug-naïve patients with schizophrenia: a real-world study

BackgroundSchizophrenia is a severe and persistent mental condition that causes disability. For subsequent clinical care, it is extremely practical to effectively differentiate between patients who respond to therapy quickly and those who do not. This study set out to document the prevalence and risk factors for patient early non-response.MethodsThe current study included 143 individuals with first-treatment and drug-naïve (FTDN) schizophrenia. Patients were classified as early non-responders based on a Positive and Negative Symptom Scale (PANSS) score reduction of less than 20% after 2 weeks of treatment, otherwise as early responders. Clinical subgroups’ differences in demographic data and general clinical data were compared, and variables related to early non-response to therapy were examined.ResultsTwo weeks later, a total of 73 patients were described as early non-responders, with an incidence of 51.05%. The early non-response subgroup had significantly higher PANSS scores, Positive symptom subscale (PSS) scores, General psychopathology subscale (GPS) scores, Clinical global impression scale - severity of illness (CGI-SI) and Fasting blood glucose (FBG) levels compared to the early-response subgroup. CGI-SI and FBG were risk factors for early non-response.ConclusionHigh rates of early non-response have been seen in FTDN schizophrenia patients, and risk variables for predicting early non-response include CGI-SI scores and FBG levels. However, we need more in-depth studies to confirm the generalizable range of these two parameters

xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein

Protein language models have shown remarkable success in learning biological information from protein sequences. However, most existing models are limited by either autoencoding or autoregressive pre-training objectives, which makes them struggle to handle protein understanding and generation tasks concurrently. We propose a unified protein language model, xTrimoPGLM, to address these two types of tasks simultaneously through an innovative pre-training framework. Our key technical contribution is an exploration of the compatibility and the potential for joint optimization of the two types of objectives, which has led to a strategy for training xTrimoPGLM at an unprecedented scale of 100 billion parameters and 1 trillion training tokens. Our extensive experiments reveal that 1) xTrimoPGLM significantly outperforms other advanced baselines in 18 protein understanding benchmarks across four categories. The model also facilitates an atomic-resolution view of protein structures, leading to an advanced 3D structural prediction model that surpasses existing language model-based tools. 2) xTrimoPGLM not only can generate de novo protein sequences following the principles of natural ones, but also can perform programmable generation after supervised fine-tuning (SFT) on curated sequences. These results highlight the substantial capability and versatility of xTrimoPGLM in understanding and generating protein sequences, contributing to the evolving landscape of foundation models in protein science

Genetic Polymorphisms in Enzymes Involved in One-Carbon Metabolism and Anti-epileptic Drug Monotherapy on Homocysteine Metabolism in Patients With Epilepsy

Aims: To investigate the effects of single nucleotide polymorphisms (SNPs) in genes of one-carbon metabolism (OCM) related enzymes and anti-epileptic drug (AED) monotherapy on homocysteine (Hcy) metabolism in patients with epilepsy, and to further explore specific SNPs that may increase patients' susceptibility to the effects of AEDs on the Hcy imbalance.Method: This case-control study analyzed 279 patients with epilepsy, including patients receiving monotherapy with valproate (VPA) (n = 53), oxcarbazepine (OXC) (n = 71), lamotrigine (LTG) (n = 55), or levetiracetam (LEV) (n = 35) and patients who had not taken any AEDs (controls, n = 65) for at least 6 months. Serum levels of vitamin B12 (vit B12), folate (FA) and Hcy were measured, and 23 SNPs in 13 genes of OCM-related enzymes were genotyped in all patients.Results: Methylenetetrahydrofolate reductase (MTHFR) rs1801133 was associated with elevated serum Hcy levels in patients with epilepsy (P < 0.001), and patients presenting the TT genotype exhibited higher serum Hcy levels than patients with the CC (P < 0.001) or CT (P < 0.001) genotype. A subsequent multiple linear regression analysis showed that AED monotherapy with VPA (vs. control: P = 0.023) or OXC (vs. control: P = 0.041), and genotypes of MTHFR rs1801133 TT (vs. CC: P < 0.001; vs. CT: P < 0.001), transcobalamin 2 (TCN2) rs1801198 CC (vs. GC: P = 0.039) and folate receptor 1 (FOLR1) rs2071010 AA (vs. GA: P = 0.031) were independent risk factors for higher Hcy levels. In the subgroup analysis of patients taking OXC, we found that patients with genotypes of MTHFR rs1801133 TT (vs. CC: P = 0.001; vs. CT: P < 0.001) and TCN2 rs1801198 CC (vs. GC: P = 0.021; vs. GG: P = 0.018) exhibited higher serum Hcy levels.Conclusions: VPA, OXC, and genotypes of MTHFR rs1801133 TT, TCN2 rs1801198 CC, and FOLR1 rs2071010 AA are all independent risk factors for elevated Hcy levels in patients with epilepsy. Moreover, genotypes of MTHFR rs1801133 TT and TCN2 rs1801198 CC may increase patients' susceptibility to the effect of OXC on disrupting Hcy homeostasis

Impact of emission controls on air quality in Beijing during APEC 2014: implications from water-soluble ions and carbonaceous aerosol in PM2.5 and their precursors

Stringent emission controls during the Asia Pacific Economic Cooperation Summit (APEC; November 5–11, 2014) provide a valuable opportunity to examine the impact of such measures on the chemical properties of PM2.5 and other air pollutants. Here, we measured the water-soluble inorganic ions (WSII) and carbonaceous species in PM2.5, NH3 and NO2 at multiple sites in Beijing between September and November 2014. Relative to the pre-APEC period (September and October 2014), significant reductions in the average concentrations of WSII (69% for NO3−, 68% for SO42−, 78% for NH4+, and 29–71% for other species), elemental carbon (EC, 43%) and organic carbon (OC, 45%) in PM2.5 were found during the APEC period. The contributions of secondary inorganic ions (SIA, including SO42−, NO3−, and NH4+) to PM2.5 were significantly lower during the APEC period (9–44%), indicating a combination of lower gaseous precursor emissions and a relative weak secondary aerosol formation. Ion-balance calculations indicated that the PM2.5 sample in the pre-APEC period was alkaline but was acidic during the APEC period. Relatively lower mean concentrations of EC (1.5 μg m−3), OC (10.5 μg m−3), secondary organic carbon (SOC, 3.3 μg m−3), secondary organic aerosol (SOA, 5.9 μg m−3) and primary organic aerosol (POA, 10.0 μg m−3) appeared during the APEC period. The average concentrations of NH3 and NO2 at all road sites were significantly reduced by 48 and 60% during the APEC period, which is consistent with clear reductions in satellite NH3 columns over Beijing city in the same period. This finding suggests that reducing traffic emissions could be a feasible method to control urban NH3 pollution. During the APEC period, concentrations of PM2.5, PM10, NO2, SO2 and CO from the Beijing city monitoring network showed significant reductions at urban (20–60%) and rural (18–57%) sites, whereas O3 concentrations increased significantly (by 93% and 53%, respectively). The control measures taken in the APEC period substantially decreased PM2.5 pollution but can increase ground O3, which also merits attention

Characteristics of ammonia, acid gases, and PM_2.5 for three typical land-use types in the North China Plain

Air pollution is one of the most serious environmental problems in China due to its rapid economic development alongside a very large consumption of fossil fuel, particularly in the North China Plain (NCP). During the period 2011–2014, we integrated active and passive sampling methods to perform continuous measurements of NH3, HNO3, NO2, and PM2.5 at two urban, one suburban, and two rural sites in the NCP. The annual average concentrations of NH3, NO2, and HNO3 across the five sites were in the ranges 8.5–23.0, 22.2–50.5, and 5.5–9.7 μg m−3, respectively, showing no significant spatial differences for NH3 and HNO3 but significantly higher NO2 concentration at the urban sites. At each site, annual average concentrations of NH3 and NO2 showed increasing and decreasing trends, respectively, while there was no obvious trend in annual HNO3 concentrations. Daily PM2.5 concentrations ranged from 11.8 to 621.0 μg m−3 at the urban site, from 19.8 to 692.9 μg m−3 at the suburban site, and from 23.9 to 754.5 μg m−3 at the two rural sites, with more than 70 % of sampling days exceeding 75 μg m−3. Concentrations of water-soluble ions in PM2.5 ranked differently between the non-rural and rural sites. The three dominant ions were NH4 +, NO3 −, and SO4 2− and mainly existed as (NH4)2SO4, NH4HSO4, and NH4NO3, and their concentrations averaged 48.6 ± 44.9, 41.2 ± 40.8, and 49.6 ± 35.9 μg m−3 at the urban, suburban, and rural sites, respectively. Ion balance calculations indicated that PM2.5 was neutral at the non-rural sites but acidic at the rural sites. Seasonal variations of the gases and aerosols exhibited different patterns, depending on source emission strength and meteorological conditions. Our results suggest that a feasible pathway to control PM2.5 pollution in the NCP should target ammonia and acid gases together