KinomeMETA: a web platform for kinome-wide polypharmacology profiling with meta-learning.

Kinase-targeted inhibitors hold promise for new therapeutic options, with multi-target inhibitors offering the potential for broader efficacy while minimizing polypharmacology risks. However, comprehensive experimental profiling of kinome-wide activity is expensive, and existing computational approaches often lack scalability or accuracy for understudied kinases. We introduce KinomeMETA, an artificial intelligence (AI)-powered web platform that significantly expands the predictive range with scalability for predicting the polypharmacological effects of small molecules across the kinome. By leveraging a novel meta-learning algorithm, KinomeMETA efficiently utilizes sparse activity data, enabling rapid generalization to new kinase tasks even with limited information. This significantly expands the repertoire of accurately predictable kinases to 661 wild-type and clinically-relevant mutant kinases, far exceeding existing methods. Additionally, KinomeMETA empowers users to customize models with their proprietary data for specific research needs. Case studies demonstrate its ability to discover new active compounds by quickly adapting to small dataset. Overall, KinomeMETA offers enhanced kinome virtual profiling capabilities and is positioned as a powerful tool for developing new kinase inhibitors and advancing kinase research. The KinomeMETA server is freely accessible without registration at https://kinomemeta.alphama.com.cn/.

Ultrastrong Coupling between Polar Distortion and Optical Properties in Ferroelectric MoBr2O2.

Tuning the properties of materials by using external stimuli is crucial for developing versatile smart materials. Strong coupling among the order parameters within a single-phase material constitutes a potent foundation for achieving precise property control. However, cross-coupling is fairly weak in most single materials. Leveraging first-principles calculations, we demonstrate a layered mixed anion compound MoBr2O2 that exhibits electric-field switchable spontaneous polarization and ultrastrong coupling between polar distortion and electronic structures as well as optical properties. It offers feasible avenues of achieving tunable Rashba spin-splitting, electrochromism, thermochromism, photochromism, and nonlinear optics by applying an external electric field to a single domain sample and heating, as well as intense light illumination. Additionally, it exhibits an exceptionally large photostrictive effect. These findings not only showcase the feasibility of achieving multiple order parameter coupling within a single material but also pave the way for comprehensive applications based on property control, such as energy harvesting, information processing, and ultrafast control.

Unveiling Putative Excited State and Transmission of Binding Information in the Fluoride Riboswitch.

Riboswitches regulate downstream gene expression by binding to specific small molecules or ions with multiple mechanisms to transfer the binding information. In the case of the fluoride riboswitch, the transcription termination signal is conveyed through a transient excited state (ES). In this work, we performed conventional molecular dynamics (MD) simulations, totaling 180 µs, to obtain the ES structure and investigate the mechanism underlying information transmission in Mg2+/F- binding within the fluoride riboswitch aptamer. The Mg2+/F- binding pocket exhibits various conformations in its apo form. A series of ES structures were extracted from the MD trajectories of the apo form. The dynamics of the Mg2+/F- binding pocket influenced key pair A40-U48 in ES structures. The pathway connecting the binding pocket to the pair involves interactions between the phosphate groups of U7 and G8 and the nucleobases of G8-C47-U48. Our work presents a structural ensemble of the ES and elucidates a pathway for transferring Mg2+/F- binding information, thereby facilitating the understanding of how the holo-like apo state achieves transcriptional repression.

Central artery pulse pressure, not central arterial stiffness impact on all-cause mortality in patients with viral pneumonia infection.

OBJECTIVES: COVID-19 viral pneumonia can result in increased arterial stiffness, along with cardiac and systemic inflammatory responses. This study aimed to investigate the association between arterial stiffness, inflammation severity, and all-cause mortality in patients with COVID-19. METHODS: In this study, anthropometric data, pneumonia infection severity, and blood tests were analyzed. Arterial stiffness was assessed using the non-invasive assessment indices, including arterial velocity pulse index (AVI) and central arterial pulse pressure (CAPP). Infection volumes and percentages for the whole lungs, most lobes, and most segments were extracted from CT images using artificial intelligence-based quantitative analysis software. The relationship between arterial stiffness, central hemodynamics, and all-cause mortality was investigated. RESULTS: In multivariable Cox regression analysis, high CAPP was significantly associated with all-cause mortality (hazard ratio: 0.263, 95% CI, 0.073-0.945, p = 0.041). Whole lung infection percentages were independently associated with high CAPP, with an area under the curve (AUC) of 0.662 and a specificity of 89.09%. CONCLUSIONS: High CAPP, but not high AVI, demonstrated independent prognostic value for all-cause mortality in patients due to COVID-19 pneumonia infection. Evaluating this parameter could help in risk assessment and improve diagnostic and therapeutic strategies in viral pneumonia infections.

Biochar derivation at low temperature: A novel strategy for harmful resource usage of antibiotic mycelial dreg.

Antibiotic mycelial dreg (AMD) has been categorized as hazardous waste due to the high residual hazardous contaminants. Inappropriate management and disposal of AMD can cause potential environmental and ecological risks. In this study, the potential of pleuromutilin mycelial dreg (PMD) as a novel feedstock for preparing tetracycline hydrochloride (TC) adsorbent was explored to achieve safe management of PMD. The results suggested that residual hazardous contaminants were completely eliminated after pyrolysis. With the increase of pyrolysis temperature, the yields, H/C, O/C, (O + N)/C, and pore size in PMD-derived biochars (PMD-BCs) decreased, while BET surface area and pore volume increased, resulting in the higher stability of the PMD-BCs prepared from higher temperatures. The TC adsorption of the PMD-BCs increased from 27.3 to 46.9 mg/g with the increase of the pyrolysis temperature. Surprisingly, pH value had a strong impact on the TC adsorption, the adsorption capacity of BC-450 increased from 6.5 to 71.1 mg/g when the solution pH value increased from 2 to 10. Lewis acid-base interaction, pore filling, π-π interaction, hydrophobic interaction, and charge-assisted hydrogen bond (CAHB) are considered to drive the adsorption. This work provides a novel pathway for the concurrent detoxification and reutilization of AMD.

Targeted nanoparticles triggered by plaque microenvironment for atherosclerosis treatment through cascade effects of reactive oxygen species scavenging and anti-inflammation.

Inflammatory factors and reactive oxygen species (ROS) are risk factors for atherosclerosis. Many existing therapies use ROS-sensitive delivery systems to alleviate atherosclerosis, which achieved certain efficacy, but cannot eliminate excessive ROS. Moreover, the potential biological safety concerns of carrier materials through chemical synthesis cannot be ignored. Herein, an amphiphilic low molecular weight heparin- lipoic acid conjugate (LMWH-LA) was used as a ROS-sensitive carrier material, which consisted of injectable drug molecules used clinically, avoiding unknown side effects. LMWH-LA and curcumin (Cur) self-assembled to form LLC nanoparticles (LLC NPs) with LMWH as shell and LA/Cur as core, in which LMWH could target P-selectin on plaque endothelial cells and competitively block the migration of monocytes to endothelial cells to inhibit the origin of ROS and inflammatory factors, and LA could be oxidized to trigger hydrophilic-hydrophobic transformation and accelerate the release of Cur. Cur released within plaques further exerted anti-inflammatory and antioxidant effects, thereby suppressing ROS and inflammatory factors. We used ultrasound imaging, pathology and serum analysis to evaluate the therapeutic effect of nanoparticles on atherosclerotic plaques in apoe-/- mice, and the results showed that LLC showed significant anti-atherosclerotic effects. Our finding provided a promising therapeutic nanomedicine for the treatment of atherosclerosis.

Killing Two Birds with One Stone: Accounting for Unfolding Item Response Process and Response Styles Using Unfolding Item Response Tree Models.

Two research streams on responses to Likert-type items have been developing in parallel: (a) unfolding models and (b) individual response styles (RSs). To accurately understand Likert-type item responding, it is vital to parse unfolding responses from RSs. Therefore, we propose the Unfolding Item Response Tree (UIRTree) model. First, we conducted a Monte Carlo simulation study to examine the performance of the UIRTree model compared to three other models - Samejima's Graded Response Model, Generalized Graded Unfolding Model, and Dominance Item Response Tree model, for Likert-type responses. Results showed that when data followed an unfolding response process and contained RSs, AIC was able to select the UIRTree model, while BIC was biased toward the DIRTree model in many conditions. In addition, model parameters in the UIRTree model could be accurately recovered under realistic conditions, and mis-specifying item response process or wrongly ignoring RSs was detrimental to the estimation of key parameters. Then, we used datasets from empirical studies to show that the UIRTree model could fit personality datasets well and produced more reasonable parameter estimates compared to competing models. A strong presence of RS(s) was also revealed by the UIRTree model. Finally, we provided examples with R code for UIRTree model estimation to facilitate the modeling of responses to Likert-type items in future studies.

Multi-instance learning of graph neural networks for aqueous pKa prediction.

MOTIVATION: The acid dissociation constant (pKa) is a critical parameter to reflect the ionization ability of chemical compounds and is widely applied in a variety of industries. However, the experimental determination of pKa is intricate and time-consuming, especially for the exact determination of micro-pKa information at the atomic level. Hence, a fast and accurate prediction of pKa values of chemical compounds is of broad interest. RESULTS: Here, we compiled a large-scale pKa dataset containing 16 595 compounds with 17 489 pKa values. Based on this dataset, a novel pKa prediction model, named Graph-pKa, was established using graph neural networks. Graph-pKa performed well on the prediction of macro-pKa values, with a mean absolute error around 0.55 and a coefficient of determination around 0.92 on the test dataset. Furthermore, combining multi-instance learning, Graph-pKa was also able to automatically deconvolute the predicted macro-pKa into discrete micro-pKa values. AVAILABILITY AND IMPLEMENTATION: The Graph-pKa model is now freely accessible via a web-based interface (https://pka.simm.ac.cn/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Novel Index System for Assessing Ventricular-Vascular Coupling.

Background: To explore the value of a novel ventricular-vascular coupling index (VVI) system in relation to age, gender and body mass index (BMI). Methods: A total of 239 volunteers with single-center and cross-sectional health screening were enrolled in the study. Subjects were divided according to age (young [18-44 years], middle-age [45-59 years], old [60-80 years]), gender (male, female), and BMI (overweight/obese [BMI ≥ 24], control [BMI < 24]). The left ventricle end-diastolic volume (LVEDV) and left ventricle end-systolic volume (LVESV) provided the left ventricular structure index, while the TDI e ' provided the functional index. Also derived from routine echocardiography were the effective arterial elastance (Ea), left ventricular end-systolic elastance (Ees), and VVI. The novel VVI systems were arterial velocity pulse index (AVI), left ventricular global longitudinal strain (LVGLS), and the AVI to LVGLS ratio (AVI/LVGLS). Results: (1) Middle-age and elderly subjects had higher Ea and lower LVGLS compared to young subjects. AVI and AVI/LVGLS increased progressively from young to middle-age to old subjects. (2) Females had higher Ea, Ees and LVGLS than male subjects. No significant differences in AVI and AVI/LVGLS were observed between males and females. (3) No significant differences in Ea, Ees, VVI, AVI, LVGLS and AVI/LVGLS were observed between the overweight/obese and control groups. (4) AVI/LVGLS was negatively correlated with LVEDV and LVESV and with TDI e ' . LVEDV, LVESV and TDI e ' were independent predictors of AVI/LVGLS. (5) The diagnostic performance of AVI/LVGLS was higher than that of VVI in the young and middle-age groups. The diagnostic efficacy of AVI/LVGLS was higher than that of VVI in the young and old groups, and the diagnostic efficacy of AVI was higher than that of Ea. The difference in diagnostic efficacy between LVGLS and Ees was not statistically significant. The differences in diagnostic efficacy between AVI/LVGLS and VVI, AVI and Ea, and LVGLS and Ees were not statistically significant in the middle-age and old groups. Conclusions: The novel index system of ventricular-vascular coupling described here (AVI, LVGLS, and AVI/LVGLS) was more effective than traditional indexes in detecting differences in cardiovascular function between different ages groups. Clinical Trial Registration: The study protocol was registered on the official website of China Clinical Trial Registration Center (ChiCTR2000035937).

Arterial Stiffness, Body Mass Index and Cardiovascular Disease Risk in Chinese Females at Various Ages.

Background: This study investigated the correlation in parameters of arterial stiffness and cardiovascular disease (CVD) risk on age and body mass index (BMI) in Chinese females. Methods: This cross-sectional study enrolled 2220 females. Arterial stiffness was assessed by the measurement of arterial velocity pulse index (AVI) and arterial pressure volume index (API). Individual 10-year cardiovascular risk was calculated for each patient using the Framingham cardiovascular risk score (FCVRS). Results: API and AVI had a significant J-shaped relationship with age. Beginning at the age of 30 years, the API started to increase, while after 49 years, the increase in API was even steeper. AVI increased from the age of 32 years, and increased more rapidly after 56 years. The linear association between API and BMI following adjustment for age was significant ( ß = 0.324, 95% CI 0.247-0.400, p < 0.001). In the total study cohort, FCVRS scores increased by 0.16 scores for every 1 kg/ m 2 increase in BMI and by 0.11 scores for each 1 value increase in API in the age adjusted model. Conclusions: API and BMI correlate with 10-year cardiovascular risk at various ages in females. Regardless of age, overweight females have a higher risk of increased API. Therefore API can be used for the early detection of CVD so that preventive therapy can be instituted in these high risk patients. Clinical Trial Registration: Registered on the official website of the China Clinical Trial Registration Center (20/08/2020, ChiCTR2000035937).

Altered Intestinal Microbial Flora and Metabolism in Patients with Idiopathic Membranous Nephropathy.

INTRODUCTION: Dysbiosis of the intestinal microbiome and related metabolites have been observed in chronic kidney disease, yet their roles in idiopathic membranous nephropathy (IMN) are poorly understood. METHODS: In this study, we describe the variation of intestinal bacteria and fecal metabolites in patients with IMN in Chinese population. Stool samples were collected from 41 IMN patients at the beginning of diagnosis confirmation and 41 gender- and age-matched healthy control (HC). Microbial communities are investigated by sequencing of 16S rRNA genes and functional profiles predicted using Tax4Fun, and the correlation between intestinal bacteria and IMN clinical characteristics is also analyzed. Untargeted metabolomic analysis is performed to explore the relationship between colon's microbiota and fecal metabolites. RESULTS: IMN gastrointestinal microbiota demonstrates lower richness and diversity compared to HC, and exhibits a marked taxonomic and inferred functional dysbiosis when compared to HC. Some genera are closely related to the clinical parameters, such as Citrobacter and Akkermansia. Twenty characteristic microbial biomarkers are selected to establish a disease prediction model with a diagnostic accuracy of 93.53%. Fecal metabolomics shows that tryptophan metabolism is reduced in IMN patients but uremic toxin accumulation in feces is not noticeable. Fecal microbiota transplantation demonstrates that gut dysbiosis impairs gut permeability in microbiota-depleted mice and induces NOD-like receptor activation in the kidneys. CONCLUSIONS: Clarifying the changes in intestinal microbiota in IMN patients will help further know the pathogenesis of this disease, and microbiota-targeted biomarkers will provide a potentially powerful tool for diagnosing and treating IMN.

Uncoupling of the center-to-periphery arterial stiffness gradient and pulse pressure amplification in viral pneumonia infection.

OBJECTIVES: Arterial stiffness is a common manifestation of viral pneumonia infections, including COVID-19. Nevertheless, the relationship between the center-to-periphery arterial stiffness gradient and pulse pressure amplification (PPA) in infectious diseases remains unclear. This study aimed to investigate this relationship utilizing arterial pressure volume index (API) and arterial velocity pulse index (AVI) ratio. METHODS: API/AVI and PPA were measured in 219 participants with COVID-19 and 374 normal participants. Multiple linear regression was used to assess the association of API/AVI and PPA, and restricted cubic spline was used to investigate the non-linear relationship between API/AVI and PPA. Receiver operating characteristic curve (ROC) analysis was used to evaluate the effects of API/AVI in identifying COVID-19 infection and severe stage. RESULTS: There was a significant J-shaped relationship between API/AVI and PPA in COVID-19 group, while a M-shaped relationship was observed in normal group. API/AVI decreased rapidly as PPA decreased until API/AVI decreased slowly at PPA of 1.07, and then API/AVI decreased slowly again at PPA of 0.78. ROC results showed that API/AVI demonstrated excellent accuracy in identifying COVID-19 infection (AUC = 0.781) and a high specificity (84.88%) in identifying severe stage. CONCLUSIONS: There was a J-shaped association between the API/AVI and PPA in viral infected patients, while a M-shaped relationship in the normal participants. API/AVI is better for identifying infected and uninfected patients, with a high specificity in identifying those in severe stages of the disease. The attenuation or reversal of API/AVI may be associated with the loss of PPA coupling.

Increased arterial pressure volume index and cardiovascular risk score in China.

BACKGROUND AND OBJECTIVE: The new non-invasive arterial stiffness indices, arterial pressure volume index (API) is explored as a novel marker of residual stress in the wall of the peripheral muscular arteries at zero-stress state in clinical settings. The present study aimed to study the association of API with cardiovascular disease (CVD) risk in China (China-PAR). METHODS: According to China-PAR score, participants were divided into three groups: low risk (< 5%), medium risk (5-9.9%), and high risk (≥ 10.0%). API ≥ 31 was defined as high API, and the incidences of high API were compared. Logistic regression models were used to analyze the risk factors of high API and high risk China-PAR categories. The association between China-PAR and API was analyzed by restrictive cubic spline. RESULTS: The study included 4311 participants. After adjustments for confounding factors, high API was independent factor associated with high risk China-PAR categories, and the probability of high API was 1.366 times higher than that in normal API subjects. While, the independent factors associated with high API were BMI, blood pressure and heart rate. Furthermore, API had a significant U-shaped association with China-PAR. CVD risk was lowest with API of 19 units, the fastest increase at 26 units and the flattest starting point at 59 units. CONCLUSION: API, an indicator of arterial stiffness and residual stress, had a U-shaped association with China-PAR score and might play an important role in predicting CVD risk in Chinese natural populations.

Gender and age disparities in small-to-medium arterial stiffness among the Chinese population.

BACKGROUND AND AIMS: Arterial pressure-volume index (API) is a non-invasive tool for assessing small-to-medium-sized arterial stiffness. This study aimed to investigate the potential age- and sex-related differences in the API and explore the practical implications of such differences. METHODS AND RESULTS: The study analysed 7620 subjects for whom API measurements were available. Linear regression and restrictive cubic spline models were used to investigate the associations between potential risk conditions and the API. Additionally, this study employed a backward stepwise regression method to identify the independent factors associated with a high API. Middle-aged to older women had higher API values and a higher prevalence of high API than men in the same age group. However, the opposite was observed among younger individuals, with women having lower API values than men. This study also identified a J-shaped relationship between API and age, where API values began to increase at a certain age and rapidly increased after that. In women, the API started to increase at 31 years of age and rapidly increased after 54 years of age. In men, the API started to increase at 38 years of age, followed by a rapid increase after 53 years of age. CONCLUSION: This study's observation of a significant age-sex interaction in small-to-medium-sized arterial stiffening offers a valuable explanation for cardiovascular disease risk and provides important parameters for using API measurements to evaluate such risk.

DrugSpaceX: a large screenable and synthetically tractable database extending drug space.

One of the most prominent topics in drug discovery is efficient exploration of the vast drug-like chemical space to find synthesizable and novel chemical structures with desired biological properties. To address this challenge, we created the DrugSpaceX (https://drugspacex.simm.ac.cn/) database based on expert-defined transformations of approved drug molecules. The current version of DrugSpaceX contains >100 million transformed chemical products for virtual screening, with outstanding characteristics in terms of structural novelty, diversity and large three-dimensional chemical space coverage. To illustrate its practical application in drug discovery, we used a case study of discoidin domain receptor 1 (DDR1), a kinase target implicated in fibrosis and other diseases, to show DrugSpaceX performing a quick search of initial hit compounds. Additionally, for ligand identification and optimization purposes, DrugSpaceX also provides several subsets for download, including a 10% diversity subset, an extended drug-like subset, a drug-like subset, a lead-like subset, and a fragment-like subset. In addition to chemical properties and transformation instructions, DrugSpaceX can locate the position of transformation, which will enable medicinal chemists to easily integrate strategy planning and protection design.

The Antibiotics Degradation and Its Mechanisms during the Livestock Manure Anaerobic Digestion.

Antibiotics are administered to livestock at subtherapeutic levels to promote growth, and their degradation in manure is slow. High antibiotic concentrations can inhibit bacterial activity. Livestock excretes antibiotics via feces and urine, leading to their accumulation in manure. This can result in the propagation of antibiotic-resistant bacteria and antibiotic resistance genes (ARGs). Anaerobic digestion (AD) manure treatment technologies are gaining popularity due to their ability to mitigate organic matter pollution and pathogens, and produce methane-rich biogas as renewable energy. AD is influenced by multiple factors, including temperature, pH, total solids (TS), substrate type, organic loading rate (OLR), hydraulic retention time (HRT), intermediate substrates, and pre-treatments. Temperature plays a critical role, and thermophilic AD has been found to be more effective in reducing ARGs in manure compared to mesophilic AD, as evidenced by numerous studies. This review paper investigates the fundamental principles of process parameters affecting the degradation of ARGs in anaerobic digestion. The management of waste to mitigate antibiotic resistance in microorganisms presents a significant challenge, highlighting the need for effective waste management technologies. As the prevalence of antibiotic resistance continues to rise, urgent implementation of effective treatment strategies is necessary.

Association of Arterial Stiffness Indices with Framingham Cardiovascular Disease Risk Score.

Purpose: The new non-invasive arterial stiffness indices, arterial velocity pulse index (AVI) and arterial pressure volume index (API) are known to be associated with cardiovascular disease risk. The present study aimed to examine the "dose-response" associations between AVI, API and Framingham cardiovascular disease risk score (FCVRS). Methods: This survey included individuals with arterial stiffness indices collected at age 18 years and older. We used Pearson's correlation coefficients and multivariate linear analyses to evaluate associations of AVI and API to other variables. The associations between FCVRS and AVI, API were analyzed by restrictive cubic spline. Results: 4311 people were included in the full study population, including 2091 males and 2220 females. In restricted cubic spline regression models, AVI or API had significant U-shaped associations with FCVRS, with the lowest risk score of cardiovascular disease was 8 units or 18 units, respectively. After AVI increased to 12 units, FCVRS increased rapidly until AVI was 27 units, and the FCVRS increased relatively flat afterward. For API, results were similar. When API increased to 23 units, the FCVRS increased rapidly, and after API was 52 units, FCVRS increased relatively flat. Conclusions: AVI or API had U-shaped associations with FCVRS. The associations may provide a new perspective for early treatment or lifestyle modifications to prevent cardiovascular diseases.

Schistosomiasis in the People's Republic of China - down but not out.

Schistosomiasis has been subjected to extensive control efforts in the People's Republic of China (China) which aims to eliminate the disease by 2030. We describe baseline results of a longitudinal cohort study undertaken in the Dongting and Poyang lakes areas of central China designed to determine the prevalence of Schistosoma japonicum in humans, animals (goats and bovines) and Oncomelania snails utilizing molecular diagnostics procedures. Data from the Chinese National Schistosomiasis Control Programme (CNSCP) were compared with the molecular results obtained.Sixteen villages from Hunan and Jiangxi provinces were surveyed; animals were only found in Hunan. The prevalence of schistosomiasis in humans was 1.8% in Jiangxi and 8.0% in Hunan determined by real-time polymerase chain reaction (PCR), while 18.3% of animals were positive by digital droplet PCR. The CNSCP data indicated that all villages harboured S. japonicum-infected individuals, detected serologically by indirect haemagglutination assay (IHA), but very few, if any, of these were subsequently positive by Kato-Katz (KK).Based on the outcome of the IHA and KK results, the CNSCP incorporates targeted human praziquantel chemotherapy but this approach can miss some infections as evidenced by the results reported here. Sensitive molecular diagnostics can play a key role in the elimination of schistosomiasis in China and inform control measures allowing for a more systematic approach to treatment.

An In Vivo Data-Based Computational Study on Sitting-Induced Hemodynamic Changes in the External Iliac Artery.

Although sedentary behavior (characterized by prolonged sitting without otherwise being active in daily life) is widely regarded as a risk factor for peripheral artery disease (PAD), underlying biomechanical mechanisms remain insufficiently understood. In this study, geometrical models of ten external iliac arteries were reconstructed based on angiographic data acquired from five healthy young subjects resting in supine and sitting (mimicked by side lying with bent legs) positions, respectively, which were further combined with measured blood flow velocity waveforms in the common iliac arteries (with each body posture being maintained for 30 min) to build computational models for simulating intra-arterial hemodynamics. Morphological analyses showed that the external iliac arteries suffered from evident bending deformation upon the switch of body posture from supine to sitting. Measured blood flow velocity waveforms in the sitting position exhibited a marked decrease in mean flow velocity while increase in retrograde flow ratio compared with those in the supine position. Hemodynamic computations further revealed that sitting significantly altered blood flow patterns in the external iliac arteries, leading to a marked enlargement of atheroprone wall regions exposed to low and oscillatory wall shear stress (WSS), and enhanced multidirectional disturbance of WSS that may further impair endothelial function. In summary, our study demonstrates that prolonged sitting induces atheropromoting hemodynamic changes in the external iliac artery due to the combined effects of vascular bending deformation and changes in flow velocity waveform, which may provide important insights for understanding the involvement of biomechanical factors in sedentary behavior-related PAD.

A Novel Auto-Synthesis Dataset Approach for Fitting Recognition Using Prior Series Data.

To address power transmission line (PTL) traversing complex environments leading to data collection being difficult and costly, we propose a novel auto-synthesis dataset approach for fitting recognition using prior series data. The approach mainly includes three steps: (1) formulates synthesis rules by the prior series data; (2) renders 2D images based on the synthesis rules utilizing advanced virtual 3D techniques; (3) generates the synthetic dataset with images and annotations obtained by processing images using the OpenCV. The trained model using the synthetic dataset was tested by the real dataset (including images and annotations) with a mean average precision (mAP) of 0.98, verifying the feasibility and effectiveness of the proposed approach. The recognition accuracy by the test is comparable with training by real samples and the cost is greatly reduced to generate synthetic datasets. The proposed approach improves the efficiency of establishing a dataset, providing a training data basis for deep learning (DL) of fitting recognition.