Vitamin D supplementation for cardiometabolic risk markers in pregnant women based on the gestational diabetes mellitus or obesity status : a randomized clinical trial.

PURPOSE: Women with gestational diabetes mellitus (GDM) or obesity are vulnerable to impaired gestational cardiovascular health (CVH) and cardiovascular disease (CVD) in the future. It is unclear if prenatal vitamin D supplementation improves gestational CVH, especially in women at high risk for developing CVD. Our goal was to find out if vitamin D supplementation could protect against gestational CVH, including the women with GDM or obesity. DESIGN: We randomly assigned women with a serum 25(OH)D concentration < 75 nmol/L to receive 1600 IU/d (intervention group) or 400 IU/d (control group) of vitamin D3 for two months at 24-28 weeks' gestation. The primary outcome was gestational CVH marks (lipids, inflammatory cytokines, endothelial function). RESULTS: There were 1537 participants divided into the intervention (N = 766) and control groups (N = 771). No baseline differences existed among study groups in CVH markers. At the two-month visit, the intervention group's HDL-C levels (2.01 ± 0.39 VS 1.96 ± 0.39 mmol/L) were significantly higher than those of the control group, while the hs-CRP levels were significantly lower (3.28 ± 2.02 VS 3.64 ± 2.42 mg/L). Subgroup analysis found that HDL-C, TC, hs-CRP, E-Selectin, and SBP were improved in the intervention group among women with GDM or overweight/obesity, and the improvement was not found in women without GDM or overweight/obesity. Vitamin D supplementation significantly decreased the mean triglyceride-glucose index at the two-month visit in women with GDM. CONCLUSIONS: Vitamin D supplementation at mid-gestation might optimize the gestational CVH status for pregnant women, particularly the women with GDM or obesity, which is advantageous for later-life primary prevention of CVD. CLINICAL TRIAL REGISTRATION: The Chinese Clinical Trial Registry (ChiCTR2100051914, 10/9/2021, Prospective registered, https://www.chictr.org.cn/showproj.aspx?proj=134700 ).

Riemannian Locality Preserving Method for Transfer Learning with Applications on Brain-computer Interface.

Brain-computer interfaces (BCIs) have been widely focused and extensively studied in recent years for their huge prospect of medical rehabilitation and commercial applications. Transfer learning exploits the information in the source domain and applies in another different but related domain (target domain), and is therefore introduced into the BCIs to figure out the inter-subject variances of electroencephalography (EEG) signals. In this article, a novel transfer learning method is proposed to preserve the Riemannian locality of data structure in both the source and target domains and simultaneously realize the joint distribution adaptation of both domains to enhance the effectiveness of transfer learning. Specifically, a Riemannian graph is first defined and constructed based on the Riemannian distance to represent the Riemannian geometry information. To simultaneously align the marginal and conditional distribution of source and target domains and preserve the Riemannian locality of data structure in both domains, the Riemannian graph is embedded in the joint distribution adaptation (JDA) framework and forms the proposed Riemannian locality preserving-based transfer learning (RLPTL). To validate the effect of the proposed method, it is compared with several existing methods on two open motor imagery datasets, and both multi-source domains (MSD) and single-source domains (SSD) experiments are considered. Experimental results show that the proposed method achieves the highest accuracies in MSD and SSD experiments on three datasets and outperforms eight baseline methods, which demonstrates that the proposed method creates a feasible and efficient way to realize transfer learning.

Average Time Consumption Per Character - a Practical Performance Metric for Generic Synchronous BCI Spellers.

OBJECTIVE: The information transfer rate (ITR) is widely accepted as a performance metric for generic brain-computer interface (BCI) spellers, while it is noticeable that the communication speed given by ITR is actually an upper bound which however can never be reached in real systems. A new performance metric is therefore needed. METHODS: In this paper, a new metric named average time consumption per character (ATCPC) is proposed. It quantifies how long it takes on average to type one character using a typical synchronous BCI speller. To analytically derive ATCPC, the real typing process is modelled with a random walk on a graph. Misclassification and backspace are carefully characterized. A close-form formula of ATCPC is obtained through computing the hitting time of the random walk. The new metric is validated through simulated typing experiments and compared with ITR. RESULTS: Firstly, the formula and simulation show a good consistency. Secondly, ITR always tends to overestimate the communication speed, while ATCPC is more realistic. CONCLUSION: The proposed ATCPC metric is valid. SIGNIFICANCE: ATCPC is a qualified substitute for ITR. ATCPC also reveals the great potential of keyboard optimization to further enhance the performance of BCI spellers, which was hardly investigated before.

A comparative study of stereo-dependent SSVEP targets and their impact on VR-BCI performance.

Steady-state visual evoked potential brain-computer interfaces (SSVEP-BCI) have attracted significant attention due to their ease of deployment and high performance in terms of information transfer rate (ITR) and accuracy, making them a promising candidate for integration with consumer electronics devices. However, as SSVEP characteristics are directly associated with visual stimulus attributes, the influence of stereoscopic vision on SSVEP as a critical visual attribute has yet to be fully explored. Meanwhile, the promising combination of virtual reality (VR) devices and BCI applications is hampered by the significant disparity between VR environments and traditional 2D displays. This is not only due to the fact that screen-based SSVEP generally operates under static, stable conditions with simple and unvaried visual stimuli but also because conventional luminance-modulated stimuli can quickly induce visual fatigue. This study attempts to address these research gaps by designing SSVEP paradigms with stereo-related attributes and conducting a comparative analysis with the traditional 2D planar paradigm under the same VR environment. This study proposed two new paradigms: the 3D paradigm and the 3D-Blink paradigm. The 3D paradigm induces SSVEP by modulating the luminance of spherical targets, while the 3D-Blink paradigm employs modulation of the spheres' opacity instead. The results of offline 4-object selection experiments showed that the accuracy of 3D and 2D paradigm was 85.67 and 86.17% with canonical correlation analysis (CCA) and 86.17 and 91.73% with filter bank canonical correlation analysis (FBCCA), which is consistent with the reduction in the signal-to-noise ratio (SNR) of SSVEP harmonics for the 3D paradigm observed in the frequency-domain analysis. The 3D-Blink paradigm achieved 75.00% of detection accuracy and 27.02 bits/min of ITR with 0.8 seconds of stimulus time and task-related component analysis (TRCA) algorithm, demonstrating its effectiveness. These findings demonstrate that the 3D and 3D-Blink paradigms supported by VR can achieve improved user comfort and satisfactory performance, while further algorithmic optimization and feature analysis are required for the stereo-related paradigms. In conclusion, this study contributes to a deeper understanding of the impact of binocular stereoscopic vision mechanisms on SSVEP paradigms and promotes the application of SSVEP-BCI in diverse VR environments.

Role of mitochondria in renal ischemia-reperfusion injury.

Acute kidney injury (AKI) induced by renal ischemia-reperfusion injury (IRI) has a high morbidity and mortality, representing a worldwide problem. The kidney is an essential organ of metabolism that has high blood perfusion and is the second most mitochondria-rich organ after the heart because of the high ATP demands of its essential functions of nutrient reabsorption, acid-base and electrolyte balance, and hemodynamics. Thus, these energy-intensive cells are particularly vulnerable to mitochondrial dysfunction. As the bulk of glomerular ultrafiltrate reabsorption by proximal tubules occurs via active transport, the mitochondria of proximal tubules must be equipped for detecting and responding to fluctuations in energy availability to guarantee efficient basal metabolism. Any insults to mitochondrial quality control mechanisms may lead to biological disruption, blocking the clearance of damaged mitochondria and resulting in morphological change and tissue dysfunction. Extensive research has shown that mitochondria have pivotal roles in acute kidney disease, so in this article, we discuss the role of mitochondria, their dynamics and mitophagy in renal ischemia-reperfusion injury.

A Subject-Specific Attention Index Based on the Weighted Spectral Power.

As an essential cognitive function, attention has been widely studied and various indices based on EEG have been proposed for its convenience and easy availability for real-time attention monitoring. Although existing indices based on spectral power of empirical frequency bands are able to describe the attentional state in some way, the reliability still needs to be improved. This paper proposed a subject-specific attention index based on the weighted spectral power. Unlike traditional indices, the ranges of frequency bands are not empirical but obtained from subject-specific change patterns of spectral power of electroencephalograph (EEG) to overcome the great inter-subject variance. In addition, the contribution of each frequency component in the frequency band is considered different. Specifically, the ratio of power spectral density (PSD) function in attentional and inattentional state is utilized to calculate the weight to enhance the effectiveness of the proposed index. The proposed subject-specific attention index based on the weighted spectral power is evaluated on two open datasets including EEG data of a total of 44 subjects. The results of the proposed index are compared with 3 traditional attention indices using various statistical analysis methods including significance tests and distribution variance measurements. According to the experimental results, the proposed index can describe the attentional state more accurately. The proposed index respectively achieves accuracies of 86.21% and 70.00% at the 1% significance level in both the t-test and Wilcoxon rank-sum test for two datasets, which obtains improvements of 41.38% and 20.00% compared to the best result of the traditional indices. These results indicate that the proposed index provides an efficient way to measure attentional state.

Pioglitazone ameliorates ischemia/reperfusion-induced acute kidney injury via oxidative stress attenuation and NLRP3 inflammasome.

Acute kidney injury (AKI) induced by renal ischemia/reperfusion injury (IRI) is a severe clinical condition. ROS accumulation, antioxidant pathways deficiency, and inflammation are involved in IRI. Pioglitazone (Pio) exerts anti-inflammatory and antioxidant effects. The aim of this study was to explore the protective effects of pioglitazone against IRI-induced AKI. Pathogen-free Sprague-Dawley (SD) rats were arbitrarily divided into four groups: Sham operation group Control (CON) group, CON + Pio group, I/R + Saline group, and I/R + Pio group. In addition, HK-2 cells were subjected to hypoxia and reoxygenation to develop an H/R model for investigation of the protective mechanism of Pio. Pretreatment with pioglitazone in the model rats reduced urea nitrogen and creatinine levels, histopathological scores, and cytotoxicity after IRI. Pioglitazone treatment significantly attenuated renal cell apoptosis, decreased cytotoxicity, increased Bcl-2 expression, and downregulated Bax expression. Besides, the levels of ROS and inflammatory factors, including NLRP3, ASC, pro-IL-1ß, pro-caspase-1, cleaved-caspase-1, TNF-α, IL-6, and IL-1ß, in I/R rats and H/R cells were normalized by the pioglitazone treatment. Pioglitazone improved IRI-induced AKI by attenuating oxidative stress and NLRP3 inflammasome activation. Therefore, pioglitazone has the potential to serve as a novel agent for renal IRI treatment and prevention.

Comparative Study on the Effects of Four Plant Protein Sources on the Liver and Intestinal Health of Largemouth Bass, Micropterus salmoides.

The effects of plant protein sources (PPSs) on the health of the liver and intestine of the largemouth bass, Micropterus salmoides, were compared to verify the potential damaging effects of dietary fiber (DF). A diet containing 55% fish meal (FM) was used as the control. The test diets contained 25% soybean meal (SBM), rapeseed meal (RSM), cottonseed meal, or peanut meal, and the FM content was decreased to 30%. The protein and lipid contents of these five diets were balanced by casein and oil. Fish were raised for 8 weeks. The fish fed the diet containing PPS showed a trend of decreasing growth and apparent digestibility coefficients. The contents of total bile acid, lipid, and collagen in the liver were increased, and the mRNA expression levels of genes encoding inflammatory factors and enzymes involved in de novo fatty acid synthesis and bile acid synthesis were upregulated. Both the lipid and collagen contents in the liver were positively correlated with the DF content in the diet significantly. Morphology and histology showed reduced liver size, hepatic steatosis, and fibrosis in fish fed diets containing PPS. The lowest hepatosomatic index was observed in fish fed the SBM diet, and the most severe damage was observed in fish fed the RSM diet. No obvious histological abnormalities were observed in the hindgut. The bile acid profile in the liver could be used to distinguish the types of PPS very well by Fisher discriminant analysis. These results indicated that 25% of each of the four PPSs in the diet exceeded the tolerance range of largemouth bass and caused liver damage, which might be mediated by bile acid. DF in PPS might be an important agent contributing to liver damage.

Oral Simnotrelvir for Adult Patients with Mild-to-Moderate Covid-19.

BACKGROUND: Simnotrelvir is an oral 3-chymotrypsin-like protease inhibitor that has been found to have in vitro activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and potential efficacy in a phase 1B trial. METHODS: In this phase 2-3, double-blind, randomized, placebo-controlled trial, we assigned patients who had mild-to-moderate coronavirus disease 2019 (Covid-19) and onset of symptoms within the past 3 days in a 1:1 ratio to receive 750 mg of simnotrelvir plus 100 mg of ritonavir or placebo twice daily for 5 days. The primary efficacy end point was the time to sustained resolution of symptoms, defined as the absence of 11 Covid-19-related symptoms for 2 consecutive days. Safety and changes in viral load were also assessed. RESULTS: A total of 1208 patients were enrolled at 35 sites in China; 603 were assigned to receive simnotrelvir and 605 to receive placebo. Among patients in the modified intention-to-treat population who received the first dose of trial drug or placebo within 72 hours after symptom onset, the time to sustained resolution of Covid-19 symptoms was significantly shorter in the simnotrelvir group than in the placebo group (180.1 hours [95% confidence interval {CI}, 162.1 to 201.6] vs. 216.0 hours [95% CI, 203.4 to 228.1]; median difference, -35.8 hours [95% CI, -60.1 to -12.4]; P = 0.006 by Peto-Prentice test). On day 5, the decrease in viral load from baseline was greater in the simnotrelvir group than in the placebo group (mean difference [±SE], -1.51±0.14 log10 copies per milliliter; 95% CI, -1.79 to -1.24). The incidence of adverse events during treatment was higher in the simnotrelvir group than in the placebo group (29.0% vs. 21.6%). Most adverse events were mild or moderate. CONCLUSIONS: Early administration of simnotrelvir plus ritonavir shortened the time to the resolution of symptoms among adult patients with Covid-19, without evident safety concerns. (Funded by Jiangsu Simcere Pharmaceutical; ClinicalTrials.gov number, NCT05506176.).

Liver indicators affecting the relationship between BMI and hypertension in type 2 diabetes: a mediation analysis.

BACKGROUND: Body mass index (BMI) is an important risk factor for hypertension in diabetic patients. However, the underlying mechanisms remain poorly understood. Although liver-derived biological intermediates may play irreplaceable roles in the pathophysiology of diabetes, few studies have explored them in the association between BMI and hypertension in diabetes. OBJECTIVE: To investigate the role of liver enzymes in mediating the relationship between BIM exposure and hypertension in type 2 diabetes mellitus (T2DM). METHODS: We included a total of 1765 participants from the China National Diabetic Chronic Complications Study Cohort. Associations between liver enzymes and hypertension were estimated using multivariable regression models. The function of liver indicators in the relationship between BMI and hypertension was assessed using mediation analysis. Mediation analysis was conducted, taking into account age, diabetes duration, current smoking, fasting plasma glucose level, glycated hemoglobin, anti-diabetic therapy, and family history of diseases, including diabetes, hypertension, obesity, and hyperlipidemia. RESULTS: For men, the association of BMI with hypertension was partially mediated by alanine aminotransferase (ALT), with a proportion of mediation was 68.67%, by aspartate aminotransferase (AST) was 27.02%, and by γ-glutamyltransferase (GGT) was 38.58%, by AST/ALT was 63.35%; for women, the proportion mediated by ALT was 36.93%, and by AST was 37.47%, and GGT was 44.60%, and AST/ALT was 43.73% for BMI (all P < 0.05). CONCLUSION: The effect of BMI on hypertension is partly mediated by liver indicators (ALT, AST, GGT, and AST/ALT) in diabetic patients. Our results may provide opportunities to identify new targets for hypertension interventions.

Associations between dietary patterns and renal impairment in individuals with diabetes: a cross-sectional study.

BACKGROUND: A variety of chronic diseases are affected by diet. To our knowledge, few studies have investigated the relationship between dietary patterns and renal impairment in individuals with diabetes within an Asian population. This study aimed to assess the relationship between renal impairment and dietary patterns in individuals with diabetes within a Chinese population. METHODS: In this cross-sectional survey, we analysed data on 1522 participants with diabetes aged 18 years or older who took part in the China National Diabetic Chronic Complications Study. We utilised the Chinese Diabetes Complications Questionnaire, including the semiquantitative food frequency questionnaire (SQFFQ). We identified three dietary patterns using factor analysis: Chinese traditional, healthy and plant-based dietary patterns, and these dietary patterns were used to classify participants into four groups based on the quartiles of their scores. A decrease in the estimated glomerular filtration rate (eGFR; <60 mL/min/1.73 m2 ) and an increase in the albumin-to-creatinine ratio (ACR; ≥3 mg/mmol) were used as indicators of renal impairment. Binary logistic regression models were used to estimate the odds ratio (OR) of the highest quartile (Q4: high intake levels of each dietary pattern) for renal impairment compared to the lowest quartile (Q1: low intake levels of each dietary pattern). RESULTS: Among the 1522 participants, there was a 5.5% prevalence of low eGFR, with prevalence rates of 5.2% in men and 5.9% in women, yet the prevalence of albuminuria was as high as 47.9%. After adjusting for confounders, participants in Q4 of the plant-based dietary pattern had a smaller OR for renal impairment than those in Q1. CONCLUSIONS: Our findings demonstrated that a plant-based dietary pattern is associated with a reduced risk of renal impairment in a population with diabetes.

A model of hybrid speciation process drawn from three new poplar species originating from distant hybridization between sections.

Although numerous studies have been conducted on hybrid speciation, our understanding of this process remains limited. Through an 18-year systematic investigation of all taxa of Populus on the Qinghai-Tibet Plateau, we discovered three new taxa with clear characteristics of sect. Leucoides. Further evidence was gathered from morphology, whole-genome bioinformatics, biogeography, and breeding to demonstrate synthetically that they all originated from distant hybridization between sect. Leucoides and sect. Tacamahaca. P. gonggaensis originated from the hybridization of P. lasiocarpa with P. cathayana, P. butuoensis from the hybridization of P. wilsonii with P. szechuanica, and P. dafengensis from the hybridization of P. lasiocarpa with P. szechuanica. Due to heterosis, the three hybrid taxa possess greater ecological adaptability than their ancestral species. We propose a hybrid speciation process model that incorporates orthogonal, reverse, and backcrossing events. This model can adequately explain some crucial evolutionary concerns, such as the nuclear-cytoplasmic conflict on phylogeny and the extinction of ancestral species within the distribution range of hybrid species.

Identification of differentially expressed circRNAs in prostate cancer of different clinical stages by RNA sequencing.

Circular RNAs (circRNAs) are linked to cancer, but it's still not clear what role they play in prostatic cancer. Through high-throughput sequencing, the goal of this study was to compare how circRNAs are expressed at different stages of prostate cancer. 12 patients attending the Department of Urology at the Second Affiliated Hospital of Nanchang University between June 2020 and October 2021 were used for RNA sequencing, and 14 patients were used for real-time fluorescent quantitative PCR (qRT-PCR). The expression profiles of prostate cancer circRNAs were constructed by sequencing with the help of next-generation high-throughput sequencing technology, and the differentially expressed circRNAs were analyzed by targeting microRNA (miRNA) loci and Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the genes from which circRNAs originated. Finally, the expression of target circRNAs in two prostate tissues was verified by qRT-PCR. Following high-throughput sequencing, 13,047 circRNAs were identified, and 605 circRNAs with significant differential expression were identified, of which 361 circRNAs were up-regulated, and 244 circRNAs were down-regulated. Analysis of circRNA-originated genes using GO and the KEGG enrichment analysis showed that circRNA host genes can regulate and influence multiple signaling pathways in prostate cancer with important biological functions. And the circRNA-miRNA network was constructed. The highest number of differentially expressed circRNA-binding miRNAs were: hsa_circ_000 7582 (52), hsa_circ_000 6198 (37), hsa_circ_000 6759 (28), hsa_circ_000 5675 (25), and hsa_circ_000 2172 (22). Moreover, we further screened out the circRNA (hsa_circ_0005692) that was significantly differentially expressed and common to all groups and verified by qRT-PCR that the expression of the target circRNA (hsa_circ_0005692) was significantly downregulated in prostate cancer compared with benign prostatic hyperplasia (BPH) tissues.

Attentional State Classification Using Amplitude and Phase Feature Extraction Method Based on Filter Bank and Riemannian Manifold.

As a significant aspect of cognition, attention has been extensively studied and numerous measurements have been developed based on brain signal processing. Although existing attentional state classification methods have achieved good accuracy by extracting a variety of handcrafted features, spatial features have not been fully explored. This paper proposes an attentional state classification method based on Riemannian manifold to utilize spatial information. Based on the concept of Riemannian manifold of symmetric positive definite (SPD) matrix, the proposed method exploits the structure of covariance matrix to extract spatial features instead of using spatial filters. Specifically, Riemannian distances from intra-class Riemannian means are extracted as features for their robustness. To fully extend the potential of electroencephalograph (EEG) signal, both amplitude and phase information is utilized. In addition, to solve the variance of frequency bands, a filter bank is employed to process the signal of different frequency bands separately. Finally, features are fed into a support vector machine with a polynomial kernel to obtain classification results. The proposed attentional state classification using amplitude and phase feature extraction method based on filter bank and Riemannian manifold (AP-FBRM) method is evaluated on two open datasets including EEG data of 29 and 26 subjects. According to the experimental results, the optimal set of filter bank and the optimal technique to extract features containing both amplitude and phase information are determined. The proposed method respectively achieves accuracies of 88.06% and 80.00% and outperforms 8 baseline methods, which manifests that the proposed method creates an efficient way to recognize attentional state.

A Novel Hybrid Brain-Computer Interface Combining the Illusion-Induced VEP and SSVEP.

Traditional single-modality brain-computer interface (BCI) systems are limited by their reliance on a single characteristic of brain signals. To address this issue, incorporating multiple features from EEG signals can provide robust information to enhance BCI performance. In this study, we designed and implemented a novel hybrid paradigm that combined illusion-induced visual evoked potential (IVEP) and steady-state visual evoked potential (SSVEP) with the aim of leveraging their features simultaneously to improve system efficiency. The proposed paradigm was validated through two experimental studies, which encompassed feature analysis of IVEP with a static paradigm, and performance evaluation of hybrid paradigm in comparison with the conventional SSVEP paradigm. The characteristic analysis yielded significant differences in response waveforms among different motion illusions. The performance evaluation of the hybrid BCI demonstrates the advantage of integrating illusory stimuli into the SSVEP paradigm. This integration effectively enhanced the spatio-temporal features of EEG signals, resulting in higher classification accuracy and information transfer rate (ITR) within a short time window when compared to traditional SSVEP-BCI in four-command task. Furthermore, the questionnaire results of subjective estimation revealed that proposed hybrid BCI offers less eye fatigue, and potentially higher levels of concentration, physical condition, and mental condition for users. This work first introduced the IVEP signals in hybrid BCI system that could enhance performance efficiently, which is promising to fulfill the requirements for efficiency in practical BCI control systems.

A first-in-human phase 1 study of simnotrelvir, a 3CL-like protease inhibitor for treatment of COVID-19, in healthy adult subjects.

Safe and efficacious antiviral therapeutics are in urgent need for the treatment of coronavirus disease 2019. Simnotrelvir is a selective 3C-like protease inhibitor that can effectively inhibit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated the safety, tolerability, and pharmacokinetics of dose escalations of simnotrelvir alone or with ritonavir (simnotrelvir or simnotrelvir/ritonavir) in healthy subjects, as well as the food effect (ClinicalTrials.gov Identifier: NCT05339646). The overall incidence of adverse events (AEs) was 22.2% (17/72) and 6.3% (1/16) in intervention and placebo groups, respectively. The simnotrelvir apparent clearance was 135-369 L/h with simnotrelvir alone, and decreased significantly to 19.5-29.8 L/h with simnotrelvir/ritonavir. The simnotrelvir exposure increased in an approximately dose-proportional manner between 250 and 750 mg when co-administered with ritonavir. After consecutive twice daily dosing of simnotrelvir/ritonavir, simnotrelvir had a low accumulation index ranging from 1.39 to 1.51. The area under the curve of simnotrelvir increased 44.0 % and 47.3 % respectively, after high fat and normal diet compared with fasted status. In conclusion, simnotrelvir has adequate safety and tolerability. Its pharmacokinetics indicated a trough concentration above the level required for 90 % inhibition of SARS-CoV-2 in vitro at 750 mg/100 mg simnotrelvir/ritonavir twice daily under fasted condition, supporting further development using this dosage as the clinically recommended dose regimen.

Joint User Association and Deployment Optimization for Energy-Efficient Heterogeneous UAV-Enabled MEC Networks.

Unmanned aerial vehicles (UAVs) providing additional on-demand communication and computing services have become a promising technology. However, the limited energy supply of UAVs, which constrains their service duration, has emerged as an obstacle in UAV-enabled networks. In this context, a novel task offloading framework is proposed in UAV-enabled mobile edge computing (MEC) networks. Specifically, heterogeneous UAVs with different communication and computing capabilities are considered and the energy consumption of UAVs is minimized via jointly optimizing user association and UAV deployment. The optimal transport theory is introduced to analyze the user association sub-problem, and the UAV deployment for each sub-region is determined by a dragonfly algorithm (DA). Simulation results show that the energy consumption performance is significantly improved by the proposed algorithm.

Association of sleep behaviors, insulin resistance surrogates, and the risk of hypertension in Chinese adults with type 2 diabetes mellitus.

Objective: Our aim was to evaluate the association between midday napping, combined sleep quality, and insulin resistance surrogates and the risk of hypertension in patients with type 2 diabetes mellitus (T2DM). Methods: Data were collected using a standardized questionnaire. Binary logistic regression was performed to estimate the odds ratio (OR) and 95% confidence interval (CI) for the risk of hypertension. Systolic and diastolic blood pressure were grouped as categorical variables and unpaired two-sided Student's t-test and Spearman correlation analysis were performed to estimate the association between different blood pressure levels and insulin resistance surrogates. Results: The overall prevalence rate of hypertension was 50%. Age (OR = 1.056, 95% CI:1.044-1.068), poor sleep quality (OR = 1.959, 95% CI:1.393-2.755), hyperlipidemia (OR = 1.821, 95% CI:1.462-2.369), family history of hypertension (OR = 2.811, 95% CI:2.261-3.495), and obesity (OR = 5.515, 95% CI:1.384-21.971) were significantly associated with an increased risk of hypertension. Midday napping for 1-30 min was negatively correlated with the risk of hypertension (OR = 0.534, 95% CI:0.305-0.936, P <0.05). Conclusion: Poor sleep quality and obesity are independent risk factors for hypertension. Midday napping (1-30 min) is associated with a decreased risk of hypertension in patients with T2DM.

A Sliced Parabolic Equation Method to Characterize Maritime Radio Propagation.

For maritime broadband communications, atmospheric ducts can enable beyond line-of-sight communications or cause severe interference. Due to the strong spatial-temporal variability of atmospheric conditions in near-shore areas, atmospheric ducts have inherent spatial heterogeneity and suddenness. This paper aims to evaluate the effect of horizontally inhomogeneous ducts on maritime radio propagation through theoretical analysis and measurement validation. To make better use of meteorological reanalysis data, we design a range-dependent atmospheric duct model. Then, a sliced parabolic equation algorithm is proposed to improve the prediction accuracy of path loss. We derive the corresponding numerical solution and analyze the feasibility of the proposed algorithm under the range-dependent duct conditions. A 3.5 GHz long-distance radio propagation measurement is utilized to verify the algorithm. The spatial distribution characteristics of atmospheric ducts in the measurements are analyzed. Based on actual duct conditions, the simulation results are consistent with the measured path loss. The proposed algorithm outperforms the existing method during the multiple duct periods. We further investigate the influence of different duct horizontal characteristics on the received signal strength.