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Abstract Positively charged residues are commonly located near the cytoplasm-membrane interface, which is known as the positive-inside rule in membrane topology. The mechanism underlying the function of these charged residues remains poorly understood. Herein, we studied the function of cytoplasmic residues in corin, a type II transmembrane serine protease in cardiovascular biology. We found that the positively charged residue at the cytoplasm-membrane interface of corin was not a primary determinant in membrane topology but probably served as a charge-repulsion mechanism in the endoplasmic reticulum (ER) to prevent interactions with proteins in the ER, including the signal peptidase. Substitution of the positively charged residue with a neutral or acidic residue resulted in corin secretion likely due to signal peptidase cleavage. In signal peptidase-deficient cells, the mutant corin proteins were not secreted but retained in the ER. Similar results were found in the low-density lipoprotein receptor and matriptase-2 that have positively charged residues at and near the cytoplasm-membrane interface. These results provide important insights into the role of the positively charged cytoplasmic residues in mammalian single-pass transmembrane proteins.

Abstract Background Low-density lipoprotein cholesterol (LDL-C) is a well-recognized risk factor for cardiovascular diseases. However, several clinical studies demonstrated an inverse association between LDL-C and mortality risk in patients with acute myocardial infarction (AMI), known as the lipid paradox. This study aims to investigate the potential impact of inflammation on the association between LDL-C levels and mortality risks. Methods A total of 5244 patients with AMI from a large nationwide prospective cohort were included in our analysis. Patients were stratified according to LDL-C quartiles. The primary outcome was all-cause mortality, and the secondary endpoint was cardiac mortality. High-sensitive C-reactive protein (hsCRP) > 3 mg/L was defined as high inflammatory risk. Results During a median follow-up of 2.07 years, 297 mortality events (5.5%) and 227 cardiac mortality events (4.2%) occurred. Patients in the lowest LDL-C quartile had the highest incidence of all-cause mortality (7.3%) and cardiac mortality (5.8%). A U-shaped association between LDL-C levels and mortality risk was observed after multivariable adjustment, which persisted only in patients with high hsCRP levels. In contrast, a linear association between LDL-C and mortality risk was shown in patients with low hsCRP levels. Conclusions AMI patients with lower LDL-C levels had a higher risk of mortality. However, this association was only observed in those with high inflammatory risk. In contrast, the relationship between LDL-C and mortality risk was linear in patients with low inflammatory risk. This suggests the importance of considering inflammation when managing LDL-C levels in AMI patients.

Abstract Background Blocking the RhoA/ROCK II/MLC 2 (Ras homolog gene family member A/Rho kinase II/myosin light chain 2) signaling pathway can initiate neuroprotective mechanisms against neurological diseases such as stroke, cerebral ischemia, and subarachnoid hemorrhage. Nevertheless, it is not clear whether and how disrupting the RhoA/ROCK II/MLC 2 signaling pathway changes the pathogenic processes of the blood–brain barrier (BBB) after intracerebral hemorrhage (ICH). The present investigation included the injection of rat caudal vein blood into the basal ganglia area to replicate the pathophysiological conditions caused by ICH. Methods Scalp acupuncture (SA) therapy was performed on rats with ICH at the acupuncture point “Baihui”‐penetrating “Qubin,” and the ROCK selective inhibitor fasudil was used as a positive control to evaluate the inhibitory effect of acupuncture on the RhoA/ROCK II/MLC 2 signaling pathway. Post‐assessments included neurological deficits, brain edema, Evans blue extravasation, Western blot, quantitative polymerase chain reaction, and transmission electron microscope imaging. Results We found that ROCK II acts as a promoter of the RhoA/ROCK II/MLC 2 signaling pathway, and its expression increased at 6 h after ICH, peaked at 3 days, and then decreased at 7 days after ICH, but was still higher than the pre‐intervention level. According to some experimental results, although 3 days is the peak, 7 days is the best time point for acupuncture treatment. Starting from 6 h after ICH, the neurovascular structure and endothelial cell morphology around the hematoma began to change. Based on the changes in the promoter ROCK II, a 7‐day time point was selected as the breakthrough point for treating ICH model rats in the main experiment. The results of this experiment showed that both SA at “Baihui”‐penetrating “Qubin” and treatment with fasudil could improve the expression of endothelial‐related proteins by inhibiting the RhoA/ROCK II/MLC 2 signaling pathway and reduce neurological dysfunction, brain edema, and BBB permeability in rats. Conclusion This study found that these experimental data indicated that SA at “Baihui”‐penetrating “Qubin” could preserve BBB integrity and neurological function recovery after ICH by inhibiting RhoA/ROCK II/MLC 2 signaling pathway activation and by regulating endothelial cell–related proteins.

Aiming at the removal of native oxide film on 2024-T3 Al alloy before plasma electrolytic oxidation, the methods to reduce the fatigue damage caused by grit blasting are explored. Effects of the grit size and pressure on surface roughness, residual compressive stress (RCS), and fatigue life of the Al alloy are studied. Increasing grit size and pressure leads to the increase in the surface roughness and RCS. Based on the theorem of momentum and tool cutting principle, mechanism of the grits on the craters and RCS is revealed. It is found that the angularness of the small-sized grit results in the formation of long scratches. The grit with high kinetic energy induces the large craters and high RCS. The craters are the primary fatigue crack initiation source. Moreover, the craters with long scratch and large height lead to the premature fatigue failure of the grit blasted specimens. However, Fatigue behavior is insignificantly affected by the RCS. The results provide new insights into the fatigue deterioration mechanism and life optimization of the grit blasted samples. Consequently, a parameter optimization scheme for the fatigue life of the grit blasted Al alloy is proposed.

Mg-Gd-Y-Zn-Zr alloy is an essential high strength weight ratio material in the aerospace field. It has been fabricated gradually using wire-arc additive manufacturing (WAAM), a key integrated preparation technology for large-scale parts. In this investigation, a Mg-9.4Gd-3.3Y-1.75Zn-0.38Zr (wt.%) alloy was prepared by WAAM based in the cold metal transfer (CMT) process. Investigations were conducted into the microstructural evolution and mechanical properties during the solution and aging heat treatment. With an average grain size of 18.30 ± 9.89 μm, the as-deposited Mg-Gd-Y-Zn-Zr alloy is mainly composed of α-Mg matrix, (Mg,Zn)3(Gd,Y) eutectic phase, RE-rich particles, and rare-earth (RE) segregation zone. Following a 12-h heat treatment at 500 °C, the average grain size of the α-Mg matrix showed no appreciable changes. The α-Mg matrix also dissolved the (Mg, Zn)3(Gd, Y) phases, which led to the production of long period stacking ordered (LPSO) phases and the disappearance of the RE-segregation zone. The appearance of the nanoscale β′ phase following aging heat treatment. The deposited alloys had the following tensile properties: 196.5 ± 24 MPa for ultimate tensile strength (UTS), 157.2 ± 14 MPa for yield strength (YS), and 2.08 ± 0.8% for elongation (EL). The formation of LSPO phase can improve the ductility while the formation of nanoscale β′ phase can improve the strength of Mg-Gd-Y-Zn-Zr alloy. Thus, after heat treatment at 500 °C for 12 h, the alloy's EL rose to 9.27 ± 0.94%. After further aging heat treatment for 225 °C at 24h, the alloy's YS rose to 234±3 MPa and its EL was 4.56 ± 0.25%.

Repairing defects in titanium alloy components is economically justified due to their high cost. In this work, Ti–6Al–4V samples with large area hole defects are repaired by transient liquid-phase sintering. The microstructure and tensile properties after repair have been investigated. The factors of different base powder morphology and the ratio of braze metal are also studied. The results show that by using spherical Ti64 alloy powder with 40 wt% TiZrCuNi braze alloy powder, an overall repair effect with high-density repair zone and good interface combination can be obtained at 960 °C for 3 h. The tensile strength of the as-repaired exceeds that of the matrix, but the elongation is lower than that of the matrix. Finally, the repair experiment conducted at various angles demonstrates this technique's strong practical feasibility.

Background: Fat grafting after breast prostheses removal has been performed widely for the breast augmentation. However, the postoperative complications and clinical safety of these two procedures are still widely concerned. Here, the authors presented two clinical cases of the complications of autologous fat grafting after breast prostheses removal.Methods: two patients visited our outpatient department, the one of them consulted for a 10-day history of fever and swelling of the left breast, the another consulted for the immovable mass in the left breast. Both of them received the surgery of bilateral breast prostheses removal there years ago and received the surgery of autologous fat grafting to the breasts in the year interval between surgeries. Based on the patient's history, physical examination and magnetic resonance imaging (MRI) examination, the fibro-oil cysts and fibrocystic mass formation were observed in patient A and patient B, respectively. Results: Incision and drainage were performed immediately with the patients. In one patient, a delineated capsular sac was revealed upon dissecting the pectoralis major during intraoperative exploration. Within this sac, a substantial quantity of grey-yellow fibro-oil cysts containing yellow. In another patient, upon dissecting the capsular sac, a fibrocystic mass containing necrotic adipose tissue was observed. Histopathological analysis of the fibro-oil cysts and the fibrocystic mass revealed that the surrounding envelope consisted of fibrous cystic parietal tissue enclosing pale and mildly lipid necrotic tissue. Conclusion: These results indicated that the main reason for the occurrence of these complications might be grafting fat into the remaining capsular sac. In a word, while performing the procedure of breast prosthesis removal, it is imperative to thoroughly excise the capsular sac to prevent the creation of residual capsular sac; Autologous fat should be inserted in multiple directions and correct layers. Prior to surgery, thorough preoperative positioning examinations should be conducted to avert the inadvertent injection of autologous fat.

IntroductionThis study evaluates the effectiveness of soil reconstruction and restoration in the Jiangcang coal mining area on the Qinghai-Tibet Plateau, where harsh environmental conditions pose significant challenges to ecological restoration.MethodsTwo phases of ecological restoration were implemented, with outcomes assessed based on vegetation coverage, species diversity, biomass, soil properties, and community similarity.ResultsThe results demonstrate that soil reconstruction significantly improved soil fertility, vegetation coverage, and community stability without noticeable degradation over time. The use of sheep manure increased species diversity by introducing native seeds, addressing the shortage of suitable grass species in alpine areas. Comparatively, the second phase of restoration, which included soil reconstruction, has elevated the vegetation coverage to 80%, matching natural background levels, and has also demonstrated superior outcomes in terms of soil stability, nutrient content, and other aspects compared to traditional methods. While aboveground biomass showed rapid recovery, belowground biomass lagged, indicating a need for longer-term restoration. Restored slopes exhibited higher similarity to natural alpine meadows compared to platforms, suggesting the dominance of the artificially seeded species on the platform areas hinders the reproduction of other species, which is unfavorable for the evolution of vegetation diversity.DiscussionThis study emphasizes the effectiveness of soil reconstruction, organic amendment, and other restoration measures, providing important experience and reference for mine ecological restoration in similar high-altitude mining areas.

IntroductionInvasive Stratified Mucin-producing Carcinoma (ISMC) of the cervix is a newly named cervical adenocarcinoma associated with Human Papilloma virus (HPV). Due to its relative rarity, clinical data, pathological features, and molecular characteristics of ISMC are still under exploration. This study aims to retrospectively analyze the clinical data and pathological features of ISMC patients, summarizing the clinical and pathological morphological characteristics of ISMC. Immunohistochemistry for SLC7A11, SLC3A2, and PD-L1 will be performed on tumor tissues from ISMC patients to preliminarily explore potential therapeutic targets for ISMC.MethodsWe retrospectively reviewed the electronic medical records and pathological slides of 22 ISMC patients, and performed immunohistochemical staining for solute carrier family 7 member 11 (SLC7A11), solute carrier family 3 member 2 (SLC3A2), and programmed death-ligand 1 (PD-L1).ResultsThe patients were aged between 31 and 70 years old. The most common symptoms were abnormal vaginal bleeding and unusual vaginal discharge. HPV testing indicated that the infection rate of HPV type 18 was the highest. All patients underwent extensive hysterectomy and pelvic lymph node dissection. The progression-free survival (PFS) ranged from 3 to 112 months, with a postoperative recurrence rate of 22.7% (5/22). ISMC exhibited diverse characteristic microstructures. Immunohistochemistry results showed that the positive rates of SLC7A11 and SLC3A2 were both 91.0% (20/22). The staining intensity of SLC7A11 in frequent ISMC recurrence cases was significantly stronger than in non-recurrent ISMC cases. PD-L1 positivity was observed in 86.4% (19/22) of cases, defined as having a Combined Positive Score(CPS)≥1.DiscussionISMC demonstrates a high rate of lymph node metastasis and a high recurrence rate, indicating strong invasiveness. Additionally, ISMC exhibits a wide morphological spectrum. SLC7A11, SLC3A2, and PD-L1 are all highly expressed in ISMC tissues. The high expression of SLC7A11 may indicate a high recurrence rate for ISMC. Immunotherapy with checkpoint inhibitors and iron death-related treatments show potential in the treatment of ISMC, with SLC7A11, SLC3A2, and PD-L1 serving as potential therapeutic targets for ISMC.

ABSTRACTThe launch of large language models (LLMs) like ChatGPT in late 2022 and the anticipated arrival of future GPT-x iterations have marked the beginning of the generative artificial intelligence (GAI) era. We conducted a systematic review of how to integrate LLMs including GPT and other GAI models into geospatial science, based on 293 papers obtained from four databases of academic publications – Web of Science (WoS), Scopus, SSRN and arXiv – 26 papers were eventually included for analysis. We statistically outlined the share of domains where LLMs and other GAI models, the type of data that have been used for these models, and the modelling tasks and roles that they play. We also pointed out the challenges and future directions for the next research agenda – along with which we could better position ourselves in the mainstream of science and the cutting-edge research paradigm as others leverage insights from the growing data deluge.

Abstract With the development of open source software (OSS), software reliability has become an important issue. Due to the complexity of OSS development and testing environment, the fault detection rate of OSS will show a variety of changes. The existing OSS reliability models cannot fully adapt to the complex changes of OSS fault detection. In this paper, we proposed a multi-release OSS reliability model based on three-parameter lifetime distribution. The proposed model can effectively adapt to the complicated changes of fault detection in the processes of development and testing of OSS. Experimental results indicate that the proposed model has the better fitting and predictive performance compared with other multi-release OSS reliability models. Moreover, the proposed model can better adapt to the variety of OSS fault detection environment, and assist developers to evaluate the reliability of OSS.

The stress analysis of micro-arc oxidation (MAO) coated aero Al alloys is the basis to reveal the mechanism of fatigue deterioration. To clarify effects of the coating defects on fatigue life, a stress calculation model with micropores and residual stress is established based on shear lag model in this study. The effects of porosity, substrate elastic modulus, coating thickness and residual stress on the stress are explored. The results indicate that the coating porosity and thickness are the critical factor affecting coating normal stress and interfacial shear stress, respectively. In addition, the residual stress significantly affects the interfacial normal stress. The increasing stress caused by low porosity and residual tensile stress and stress concentration at the large-sized defects are the key factors for fatigue degradation.

Memory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey–Osterrieth complex figure (ROCF) is the state-of-the-art assessment tool for neuropsychologists across the globe to assess the degree of non-verbal visual memory deterioration. To obtain a score, a trained clinician inspects a patient’s ROCF drawing and quantifies deviations from the original figure. This manual procedure is time-consuming, slow and scores vary depending on the clinician’s experience, motivation, and tiredness. Here, we leverage novel deep learning architectures to automatize the rating of memory deficits. For this, we collected more than 20k hand-drawn ROCF drawings from patients with various neurological and psychiatric disorders as well as healthy participants. Unbiased ground truth ROCF scores were obtained from crowdsourced human intelligence. This dataset was used to train and evaluate a multihead convolutional neural network. The model performs highly unbiased as it yielded predictions very close to the ground truth and the error was similarly distributed around zero. The neural network outperforms both online raters and clinicians. The scoring system can reliably identify and accurately score individual figure elements in previously unseen ROCF drawings, which facilitates explainability of the AI-scoring system. To ensure generalizability and clinical utility, the model performance was successfully replicated in a large independent prospective validation study that was pre-registered prior to data collection. Our AI-powered scoring system provides healthcare institutions worldwide with a digital tool to assess objectively, reliably, and time-efficiently the performance in the ROCF test from hand-drawn images.

Spatially continuous fine particulate matter (PM2.5) mapping with hourly updated is essential for monitoring environmental pollution and promoting public health. The intensive observation of geostationary satellite enables accurate estimation of PM2.5 at a fine-scale. However, current estimation models are still limited by their weak transferability and hard to provide a robust hourly PM2.5 estimation. In this research, we aim to estimate the daytime PM2.5 concentrations at fine spatial and temporal resolution (1 km and hourly) in mainland China using an improved deep learning algorithm and the AOD products from geostationary satellite Himwari-8. An Adaptive Spatio-Temporal Multiscale Neural Network (ASTMNN) which contains three sub-networks and an adaptive weight was proposed to capture the spatiotemporal heterogeneity of hourly PM2.5. The three subnetworks of ASTMNN are spatial adjacency module (SaM), temporal adjacency module (TaM) and global module (GM), which used to incorporate the information from spatial neighborhood, temporal neighborhood, and global spatiotemporal range, respectively. And the weight function combines the outputs from the three subnetworks, where the weights were adaptively trained from the model optimization. The proposed model outperformed most current hourly PM2.5 estimation models with the sample-based, time-based, and site-based cross-validation (CV) R2 of 0.94, 0.89 and 0.83, respectively. Besides, we used our PM2.5 product to track extreme dust events. Our findings provide valuable implications for tracking continuous variation in particulate pollution using geostationary satellites.

Summary: Autographiviridae phage HH109 is a lytic Vibrio alginolyticus E110-specific phage, but the molecular mechanism underlying host recognition of this phage remains unknown. In this study, a transposon mutagenesis library of E110 was used to show that several capsular polysaccharide (CPS) synthesis-related genes were linked to the phage HH109 infection. Gene deletion combined with multiple functional assays demonstrated that CPS serves as the receptor for the phage HH109. Deletions of CPS genes caused reduction or loss of capsule and reduced adsorption. Comparative genome analysis revealed that phage-resistant mutants harbored loss-of-function mutations in the previously identified genes responsible for CPS biosynthesis. The tail protein gp02 of phage HH109 was identified as the receptor-binding protein (RBP) on CPS using antibody blocking assay, immunofluorescence staining, and CPS quantification. Additionally, we found that the phage HH109 could degrade approximately 88% of mature biofilms. Our research findings provide a theoretical basis against vibriosis.

Abstract Experiments as Code (ExaC) is a concept for reproducible, auditable, debuggable, reusable, & scalable experiments. Experiments are a crucial tool to understand Human-Building Interactions (HBI) and build a coherent theory around it. However, a common concern for experiments is their auditability and reproducibility. Experiments are usually designed, provisioned, managed, and analyzed by diverse teams of specialists (e.g., researchers, technicians, engineers) and may require many resources (e.g., cloud infrastructure, specialized equipment). Although researchers strive to document experiments accurately, this process is often lacking. Consequently, it is difficult to reproduce these experiments. Moreover, when it is necessary to create a similar experiment, the “wheel is very often reinvented”. It appears easier to start from scratch than trying to reuse existing work. Thus valuable embedded best practices and previous experiences are lost. In behavioral studies, such as in HBI, this has contributed to the reproducibility crisis. To tackle these challenges, we propose the ExaC paradigm, which not only documents the whole experiment, but additionally provides the automation code to provision, deploy, manage, and analyze the experiment. To this end, we define the ExaC concept, provide a taxonomy for the components of a practical implementation, and provide a proof of concept with an HBI desktop VR experiment that demonstrates the benefits of its “as code” representation, that is, reproducibility, auditability, debuggability, reusability, & scalability.

Abstract Software-defined radios (SDRs) are radio frequency transceivers designed to facilitate digital signal processing through the use of vast libraries of open-source software. Here, we assemble a simple data acquisition system whose architecture, based on SDR, allows us to develop a comprehensive suite of tools to study the vibrations of a few-layer graphene nanomechanical resonator. Namely, we measure the cross-spectrum of vibrations in the frequency domain, we measure their energy decay rate in the time domain, we perform vector measurements of their in-phase and quadrature components, and we control their phase using a time-dependent strain field –all with a single measurement platform. Our approach allows us to tailor our experiments at will and gives us control over every stage of data processing. Overall, our versatile system enables measuring a wide range of nanomechanical properties of graphene by customizing the signal acquisition and replacing some analog electrical circuits, such as filters, mixers, and demodulators, by blocks of code.

Cross-domain computing power networks wish to integrate computational and data resources from multiple computing centers, but existing methods do not pay enough attention to cross-domain file and data management.In this paper, a lightweight data access scheme for cross-domain computing power networks was proposed: (1) accessing parallel file system storage resources of remote computing centers through file system protocol conversion; (2) local caching as a supplement to cope with high IOPS applications; and (3) mounting remote or local storage to specified directories through container binding technology.The prototype system based on this scheme had been deployed on highperformance computing centers in multiple universities.The measured data and user experience showed that the scheme in this paper could meet the requirements of common high-performance computing applications.

Accurate and timely crop distribution data are crucial for governments, in order to make related policies to ensure food security. However, agricultural ecosystems are spatially and temporally dynamic systems, which poses a great challenge for accurate crop mapping using fine spatial resolution (FSR) imagery. This research proposed a novel Tri-Dimensional Multi-head Self-Attention Network (TDMSANet) for accurate crop mapping from multitemporal fine-resolution remotely sensed images. Specifically, three sub-modules were designed to extract spectral, temporal, and spatial feature representations, respectively. All three sub-modules adopted a multi-head self-attention mechanism to assign higher weights to important features. In addition, the positional encoding was adopted by both temporal and spatial submodules to learn the sequence relationships between the features in a feature sequence. The proposed TDMSANet was evaluated on two sites utilizing FSR SAR (UAVSAR) and optical (Rapid Eye) images, respectively. The experimental results showed that TDMSANet consistently achieved significantly higher crop mapping accuracy compared to the benchmark models across both sites, with an average overall accuracy improvement of 1.40%, 3.35%, and 6.42% over CNN, Transformer, and LSTM, respectively. The ablation experiments further showed that the three sub-modules were all useful to the TDMSANet, and the Spatial Feature Extraction Module exerted larger impact than the remaining two sub-modules.

Aerosols are crucial constituents of the atmosphere, with significant impacts on air quality. Aerosol optical depth (AOD) is critical in assessing solar resources and modeling sky radiance. However, comprehensive aerosol studies at a continental scale are limited, and existing methodologies need to consider spatial characteristics. This study develops a spatio-temporal unmixing with heterogeneity (STUH) model to evaluate spatial patterns and temporal trends of atmospheric aerosols across the African continent. The spatio-temporal AOD data cube, comprising monthly averaged MODIS-derived AOD data from 2001 to 2015, was decomposed using spatially non-negative matrix variabilization to explore the spatial determinants and the impacts of their interactions to AOD using a geographically optimal zones-based heterogeneity (GOZH) model. Our findings reveal an increasing trend of aerosol levels across Africa in the past 15 years, combined with the spatio-temporal AOD pattern explained by five abundance variables. We find that in different regions across Africa, the impact of natural variables on AOD was 1.56 to 3.01 times the impact of human variables, with significant spatial variations. These results are essential for understanding the climatic implications of atmospheric aerosols in Africa.

Zebrafish is a highly advantageous model animal for drug screening and toxicity evaluation thanks to its amenability to optical imaging (i.e., transparency), possession of organ structures similar to humans, and the ease with which disease models can be established. However, current zebrafish drug screening technologies and devices suffer from limitations such as low level of automation and throughput, and low accuracy caused by the heterogeneity among individual zebrafish specimens. To address these issues, we herein develop a high-throughput zebrafish drug screening system. This system is capable of maintaining optimal culturing conditions and simultaneously monitoring and analyzing the movement of 288 zebrafish larvae under various external conditions, such as drug combinations. Moreover, to eliminate the effect of heterogeneity, locomotion of participating zebrafish is assessed and grouped before experiments. It is demonstrated that in contrast to the experimental results without pre-selection, which shows ∼20 % damaged motor function (i.e., degree of attenuation), the drug-induced variations among zebrafish with equivalent mobility reaches ∼80 %. Overall, our high-throughput zebrafish drug screening system overcomes current limitations by improving automation, throughput, and accuracy, resulting in enhanced detection of drug-induced variations in zebrafish motor function.

Abstract. Background:. Risk assessment and treatment stratification for three-vessel coronary disease (TVD) remain challenging. This study aimed to investigate the prognostic value of left atrial volume index (LAVI) with the Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) score II, and its association with the long-term prognosis after three strategies (percutaneous coronary intervention [PCI], coronary artery bypass grafting [CABG], and medical therapy [MT]) in patients with TVD. Methods:. This study was a post hoc analysis of a large, prospective cohort of patients with TVD in China, that aimed to determine the long-term outcomes after PCI, CABG, or optimal MT alone. A total of 8943 patients with TVD were consecutively enrolled between 2004 and 2011 at Fuwai Hospital. A total of 7818 patients with available baseline LAVI data were included in the study. Baseline, procedural, and follow-up data were collected. The primary endpoint was major adverse cardiac and cerebrovascular events (MACCE), which was a composite of all-cause death, myocardial infarction (MI), and stroke. Secondary endpoints included all-cause death, cardiac death, MI, revascularization, and stroke. Long-term outcomes were evaluated among LAVI quartile groups. Results:. During a median follow-up of 6.6 years, a higher LAVI was strongly associated with increased risk of MACCE (Q3: hazard ratio [HR] 1.20, 95% confidence interval [CI] 1.06-1.37, P = 0.005; Q4: HR 1.85, 95%CI 1.64-2.09, P

Absolute observation and relative record are two methods in geomagnetic station observation. The actual values of geomagnetic field elements can be obtained after the relative record data is corrected by baseline data. Fluxgate theodolite is one of the basic tools required to obtain baseline values and plays an important role in geomagnetic observations. At present, fluxgate theodolite used in stations requires manual operation, and human factors affect the observation data quality. Because absolute geomagnetic observation cannot be realized in remote areas or areas with harsh environments, some blank areas in the coverage of geomagnetic absolute observation exist. The second phase of the Chinese Meridian Project will carry out automatic geomagnetic absolute observation of magnetic declination and inclination for the first time in China's mainland, which will promote the innovation and development of geomagnetic absolute observation technology. The automatic fluxgate theodolite is a self-developed equipment from China for automatic observation of magnetic declination and inclination. It adopts non-magnetic materials and piezoelectric motors, effectively overcomes and eliminates the systematic errors by optimizing the design, improves the machining process, and compensates for the multi-parameter error algorithm, so as to ensure measurement accuracy. The equipment has been applied to long-term practical observation in stations such as Shexian Station in Hebei Province, Helong Station in Jilin Province, Qianling Station in Shanxi Province and Baijiatuan Station in Beijing. Compared with the observation results of artificial fluxgate theodolite in these stations, the results show that the main performance of the automatic fluxgate theodolite is the same as that of the artificial fluxgate theodolite. The equipment has also passed a precursor equipment standard test from the China Earthquake Administration, and its functions and performance meet the requirements of absolute geomagnetic observation for geomagnetic stations.

Global navigation satellite system (GNSS)reflected signals have been widely used in remote sensing applications. To overcome the low-power budget of GNSS reflected signals, traditional detection strategies involve extending the coherent processing interval (CPI) of a single frame or employing the multiframe detection (MFD) method in which the noncoherent integration is used to accumulate echo energy. In this article, a novel coherent dynamic-programming-based track-before-detect (C-DP-TBD) algorithm is proposed to search and compensate for the interframe phase shift to improve the performance of weak target detection using GNSS reflected signals. The proposed algorithm is included in the two-stage MFD and follows a range-Doppler (RD) map generator. The RD map generator extracts the RD map candidate list for a specific data frame, which contains all of its variants based on the potential phase value and location shifts of the target peak in the RD domain relative to a designated reference frame. Subsequently, the C-DP-TBD processor coherently integrates each variant in this list with the reference frame, removes implausible variants, and selects the most reliable one by comparing all resulting peak signal-to-noise ratios with a preset threshold. The confirmation of the target track in the RD domain is finally achieved by extracting the position of the target peak from every available frame. Compared with traditional motion target detection methods with long CPI and DP-TBD methods, the performance superiority of the proposed algorithm is demonstrated by both simulation and experimental results in which a ferry was employed as a moving target.

Over the past 20 years, improvements in night-time light (NTL) remote sensing have spurred a resurgence of interest in the mapping of human economic activity. Nevertheless, the full potential of NTL data for urban research is constrained by a relatively coarse spatial resolution and the blooming effect. Downscaling NTL data is a potential solution, aiming to obtain fine-resolution nocturnal data with high accuracy. Most existing remotely sensed image fusion techniques were developed for optical remote sensing images taken during the day. When NTL images are compared with optical images, they exhibit a greater quantity of dark (low value) pixels, higher levels of background noise, and a more obvious blooming effect. In this article, we proposed a spatially nonstationary, geostatistical-based downscaling technique [random forest (RF) area-to-point kriging (ATPK)] to downscale NTL data (from 440 m for Delhi and 430 m for LA to 130 m) while accounting explicitly for the point spread function (PSF), thus, dealing with the blooming effect specific to NTL data. We compared several image fusion algorithms for downscaling while reducing the blooming effect. Numerical experiments on two megacities showed that downscaling was improved both numerically and visually by taking the PSF into consideration. During the RF regression, the R2 increased and the root-mean-squared error decreased for both study regions when accounting for the PSF. For the ATPK-based residual part, considering the PSF led to increased accuracy of prediction. The suggested methodology has the potential to increase the detail and accuracy of the NTL data available for modeling socioeconomic phenomena at the city scale, with wide potential for application in future socioeconomic research.

Abstract Purpose Interictal epileptiform discharges (IEDs) captured in electroencephalography (EEG) have a high diagnostic value for epileptic patients. Extending the recording time may increase the possibility of obtaining IEDs. The purpose of our research was to determine how long it took for various epileptic individuals to receive their first IEDs. Methods We retrospectively analyzed patients who were diagnosed with epilepsy and had no anti-seizure medications (ASMs) between September 2018 and March 2019 in the neurology department of the First Affiliated Hospital of Xi'an Jiaotong University. Each individual underwent a 24-h long-term video electroencephalographic monitoring (VEM) procedure. Clinical information including age, gender, age of seizure onset, frequency of seizures, the interval between last seizure and VEM, and results of neuroimaging were gathered. We also calculated the times from the start of the VEM to the first definite IEDs. Results A total of 241 patients were examined, including 191 with focal-onset epilepsy and 50 with generalized epilepsy. In individuals with focal-onset epilepsy, the median latency to the first IED was 63.0 min (IQR 19.0–299.0 min), as compared to 30.0 min (IQR 12.5–62.0 min) in patients with generalized epilepsy (p

Abstract Background Insulin resistance is a pivotal risk factor for cardiovascular diseases, and the triglyceride-glucose (TyG) index is a well-established surrogate of insulin resistance. This study aimed to investigate the prognostic value of the TyG index and its ability in therapy guidance in patients with three-vessel disease (TVD). Methods A total of 8862 patients with TVD with available baseline TyG index data were included in the study. The endpoint was major adverse cardiac events (MACE). All patients received coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), or medical therapy (MT) alone reasonably. Results An elevated TyG index was defined as the TyG index greater than 9.51. During a median follow-up of 7.5 years, an elevated TyG index was significantly associated with an increased risk of MACE (adjusted hazard ratio 1.161, 95% confidence interval 1.026–1.314, p = 0.018). The elevated TyG index was shown to have a more pronounced predictive value for MACE in patients with diabetes, but failed to predict MACE among those without diabetes, whether they presented with stable angina pectoris (SAP) or acute coronary syndrome (ACS). Meanwhile, the association between an elevated TyG index and MACE was also found in patients with left main involvement. Notably, CABG conferred a significant survival advantage over PCI in patients with a normal TyG index, but was not observed to be superior to PCI in patients with an elevated TyG index unless the patients had both ACS and diabetes. In addition, the benefit was shown to be similar between MT and revascularisation among patients with SAP and an elevated TyG index. Conclusions The TyG index is a potential indicator for risk stratification and therapeutic decision-making in patients with TVD. Graphical Abstract

Objective: To illustrate the cerebral protective effect of scalp mechanical stimulation (SMS), similar to scalp acupuncture in basic mechanism, on cerebral edema in rats with cerebral hypoperfusion. Methods: First, we screened the strength of SMS by measuring skin temperature and blood perfusion using laser speckle contrast imaging. Next, we observed the cerebral protective effects on cerebral blood perfusion, cerebral edema, and pathological changes in rats with modified two-vessel carotid artery occlusion (2-VO). Furthermore, the apoptosis-related proteins (caspase-3, cleaved-caspase-3) and cerebral edema related proteins [antiglial fibrillary acidic protein (GFAP) and antiaquaporin-4 (AQP4)] were measured via immunohistochemistry and Western blot analysis. Additionally, the correlation between neural apoptosis and AQP4 protein levels was analyzed. Results: We found that 0.5 N was the best SMS intensity suitable for our study. Compared with the control group, 0.5, 1, and 2 N maintained the scalp temperature and improved scalp blood flow (all P

Abstract Objective Polymethylmethacrylate (PMMA) bone cement promotes the development of local thrombi. Our study found that a novel material, ES-PMMA bone cement, can reduce local thrombosis. We used a simple and reproducible animal model to confirm the reduction in local thrombosis and explored the associated molecular mechanism. Methods New Zealand rabbits, which were used to model thrombosis using extracorporeal carotid artery shunts, were divided into the following two groups, with 3 rabbits in each group: the PMMA bone cement group and the ES-PMMA bone cement group. Four hours after modelling, experimental samples, including thrombotic and vascular tissues, were collected. Thrombotic samples from the PMMA group and ES-PMMA group were subjected to lncRNA sequencing, and a lncRNA microarray was used to screen the differentially expressed lncRNAs. The expression of thrombomodulin in endothelial cells was quantified in vascular tissue samples. Differences in the lncRNA expression profiles between the thrombotic samples of the PMMA group and ES-PMMA group were assessed by base-to-base alignment in the intergenic regions of genomes. The lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network was established in light of ceRNA theory. Thrombosis was observed in the PMMA group and ES-PMMA group. Results The thrombotic weight was 0.00706 ± 0.00136 g/cm in the PMMA group and 0.00551 ± 0.00115 g/cm in the ES-PMMA group. Quantitative real-time polymerase chain reaction (RT–q-CR) and Western blotting revealed that the expression of CD40, which can regulate thrombosis in vascular endothelial cells, was significantly lower in the ES-PMMA group than in the PMMA group. High-throughput sequencing was used to identify 111 lncRNAs with lower expression in the ES-PMMA group than in the PMMA group. Through bioinformatics investigation, lncRNA MSTRG22719.16/ocu-miR-326-5p/CD40 binding sites were selected. Fluorescent in situ RNA hybridization (FISH) was performed to verify the lower expression of lncRNA MSTRG.22719.16 in vascular tissues from the ES-PMMA group. A dual-luciferase reporter gene assay was applied to verify that ocu-miR-326-5p binds the CD40 3ʹ-UTR and targets lncRNA MSTRG.22719.16. Conclusion Compared with PMMA bone cement, ES-PMMA bone cement can reduce thrombosis through the lncRNA MSTRG.22719.16/ocu-miR-326-5p/CD40 axis.

Particle reinforced metal matrix composite (PRMMCs) has a complex mesoscopic structure, and the addition of particles can strengthen the metal matrix, which makes the deformation and failure behavior of PRMMCs under load very complicated. The finite element method can quantitatively describe the effect of PRMMCs microstructure parameters on the macroscopic properties of materials, but the key is to establish a representative volume element(RVE) model that can reflect the real mechanical properties of materials. This paper reports and discusses on the construction methods of the RVE model of PRMMCs from three aspects: the geometric modeling of PRMMCs microstructure, the construction of the matrix constitutive equation based on PRMMCs reinforcement mechanism and the interface module. In the end, Abaqus and some of its secondary development functions are introduced.

Abstract Background Polymethylmethacrylate (PMMA) bone cement loaded with enoxaparin sodium (PMMA@ES) has been increasingly highlighted to affect the bone repair of bone defects, but the molecular mechanisms remain unclear. We addressed this issue by identifying possible molecular mechanisms of PMMA@ES involved in femoral defect regeneration based on bioinformatics analysis and network pharmacology analysis. Methods The upregulated genes affecting the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) were selected through bioinformatics analysis, followed by intersection with the genes of ES-induced differentiation of BMSCs identified by network pharmacology analysis. PMMA@ES was constructed. Rat primary BMSCs were isolated and cultured in vitro in the proliferation medium (PM) and osteogenic medium (OM) to measure alkaline phosphatase (ALP) activity, mineralization of the extracellular matrix, and the expression of RUNX2 and OCN using gain- or loss-of-function experiments. A rat femoral bone defect model was constructed to detect the new bone formation in rats. Results ATF2 may be a key gene in differentiating BMSCs into osteoblasts. In vitro cell assays showed that PMMA@ES promoted the osteogenic differentiation of BMSCs by increasing ALP activity, extracellular matrix mineralization, and RUNX2 and OCN expression in PM and OM. In addition, ATF2 activated the transcription of miR-335-5p to target ERK1/2 and downregulate the expression of ERK1/2. PMMA@ES induced femoral defect regeneration and the repair of femoral defects in rats by regulating the ATF2/miR-335-5p/ERK1/2 axis. Conclusion The evidence provided by our study highlighted the ATF2-mediated mechanism of PMMA@ES in the facilitation of the osteogenic differentiation of BMSCs and femoral defect regeneration.

Unavoidable issues of micro-arc oxidation (MAO) coated Al alloys are the micro-defects and residual stress generation. Some scientists have reported the effects of micro-defects and residual stress on the fatigue performance of MAO coated samples. However, the influence of the residual stress sign in the MAO coating and substrate beneath the interface on the fatigue damage behavior of the substrate was controversial. Moreover, the coupling mechanism between micro-defects and residual stress on the fatigue performance of the MAO coated samples was nebulous. These present a challenge for the collaborative design of micro-defects and residual stress to optimize fatigue performance. Aiming at the issues, this paper summarized the influencing factors of MAO coatings on the fatigue performance of the substrate. From two aspects of microstructure characterization and stress analysis, the coupling mechanism between micro-defects and residual stress in fatigue failure was elucidated. And the mechanism of the micro-defects and residual stress on the fatigue damage behavior was developed. Finally, strategies to optimize the fatigue performance of MAO coated Al alloys were proposed. The results of this study have great guiding significance in regulating micropores, cracks, interface defects, and residual stress in MAO coatings in order to extend fatigue life.

It is well known that road traffic safety is one of the crucial topics in the field of automotive safety in assisted driving. In the face of complex traffic scenarios, there are still a large number of unsolved problems in the identification of vehicle risk levels. Given the difficulty of obtaining sufficient data for model training in many vehicle risk scenarios, it is important to correctly identify the vehicle risk posed through few-shot testing. The main idea of this method is to learn the class prototype of each risk state of a vehicle through encoding and mapping the vehicle’s characteristic parameters in the risk field and identifying the risk posed by few-shot vehicle lane changes through the application of the training of a prototype network. The latest results improve the efficiency of identifying risk in few-shot lane changes, which can provide practical guidance for risk identification and decision analysis in safe lane-change trigger scenarios based on the expected functional safety and provide theoretical support for the development of L3+ autonomous vehicles.

As one of the forth-generation nuclear energy system reactor types, lead fast reactor has good safety and economical properties due to the stable chemical properties of the coolant and the proliferation characteristics of the fuel, and modular nuclear power faster reactor designed for nuclear plant can further improve the economics of the reactor. In this article, the conceptual design of the lead-based modular power reactors with different power levels loaded with uranium alloy fuel is found to be found that when reactor core size increased to a certain level, the proliferation performance is too high due to the increase of the reactor core size under a specific core life such as 2000EFPD, so at the end of core life, the reactor core still has a large remaining reactivity. The proliferation advantage of the core cannot be fully released during the current core life time. Based on this phenomenon, in this article, we optimized the conceptual design of lead-based modular nuclear power reactor core loaded with uranium alloy fuel, and proposed to choose the appropriate rod to diameter ratio and effective density of fuel based on the power level and life time of the core. By adjusting the amount of uranium and 235U per unit volume, the proliferation performance of the core can be changed to match the power level and life time of the core. So the reactivity of core during the life period does not change, which not only reduce the difficulty of the reactivity control, but also make full use of the proliferation performance of the core. And at the same time, the reasonable rod to diameter ratio can provide safety and design margin for the analysis of thermal and hydraulic safety, and effectively improve the economy and safety of the core.

The deep integration of the digital economy and high-quality energy development is a vital breakthrough in promoting the digital transformation and upgrading of energy, and it is also a critical path to achieving green and low-carbon development. However, the degree of integration of the two has yet to be discovered. This article measures the coupling coordination degree of the digital economy and high-quality energy development using panel data from 30 provinces in China from 2013 to 2020, explores the spatiotemporal evolution characteristics of the coupling coordination degree, and further analyzes the driving factors of the coupling coordination degree. The results show that:(1) The coupling coordination degree shows an upward trend, but there are apparent gradient differences and spatial non-equilibrium features in the coupling coordination degree among provinces. (2) The coupling coordination degree shows a ''parabolic'' spatial trend of ''high east and low west'' in the east-west direction and an ''inverted U-shaped'' spatial trend in the north-south direction. (3) The center of gravity of the coupling coordination degree moves to the southwest, clustering in the northeast-southwest direction and showing a spreading trend in the southeast-northwest direction. (4) The coupling coordination degree has a significant positive spatial correlation, and the cold-hot spot gradually develops into a distribution pattern with the Yangtze River Delta in China as the agglomeration center. (5) Economic development, industrial structure, government behavior, environmental regulation, urbanization, technological innovation, and external openness significantly impact the coupling coordination degree. In addition, economic development and human capital have a positive spatial spillover effect on the coupling coordination degree. Urbanization level and technological innovation have a negative spatial spillover effect on the coupling coordination degree. Accordingly, to promote the coupling and interaction between the digital economy and high-quality energy development, the government should take effective measures in optimizing the industrial structure, scientifically promoting the urbanization process, and enhancing the scientific and technological innovation capacity.

BackgroundChildren living in low and middle-income countries (LMICs) are at greater risk for experiencing adversities that can undermine their health and early development. Recently launched digital early childhood development (ECD) programs attempt to support families with young children in their home environments using digital technologies. However, relatively little is known regarding the effectiveness of these new technologies. ObjectiveThe goal of this study is to rigorously assess the reach, effectiveness, and cost-effectiveness of a newly developed digital ECD platform called Afini. The Afini platform was designed to support parents of young children in low-resource settings to improve ECD and interact with caregivers through messenger services and a chatbot. MethodsThis is a 3-arm cluster randomized controlled trial. In total, 2471 caregivers and their 3- to 9-month-old children were enrolled in the study across 164 study clusters in the San Marcos, Cajabamba, and Cajamarca provinces of Peru. Clusters of participants were randomly assigned to 1 of 3 groups: a control group (72 community clusters and 980 caregiver-child dyads), a home visit intervention group (20 community clusters and 316 caregiver-child dyads), and an Afini intervention group (72 community clusters and 1175 caregiver-child dyads). Families in the control group receive no focused ECD intervention. The home visit group is receiving biweekly home visits by a trained field staff following the national ECD program (Programa Nacional Cuna Más) curriculum and training guidelines. Caregivers in the Afini group are receiving ECD activities and advice through the digital platform. The primary study outcome is children’s overall development at the age of 2.5 years, using the internationally validated long form of the Global Scales for Early Development. Secondary outcomes include caregiver engagement; caregiver mental health; screen time; as well as caregiver reports of children’s motor, cognitive, language, and socioemotional development measured through locally piloted and validated tools. ResultsEnrollment started in September 2021 and ended in March 2023. Endline assessments will take place between August 2023 and September 2024. ConclusionsThis study is, to our knowledge, the first to rigorously assess the effectiveness and cost-effectiveness of digital ECD technologies in LMICs. Given the large number of children in LMICs currently receiving only limited external support, the evaluated platform has the potential to improve the short- and long-term well-being of millions of children and their parents globally. Trial RegistrationClinicalTrials.gov NCT05202106; https://clinicaltrials.gov/ct2/show/NCT05202106 International Registered Report Identifier (IRRID)DERR1-10.2196/50371

With the increasing awareness of the serious pollution from the usage of fossil fuels and the fast advances of technologies, the usage of biomass has been increased significantly. In this review paper, the biomass serving as carbon precursors and the energy has been reviewed including lotus lives, wheat flour, fish scale, fish skin, wax gourd, etc. The formed carbon nanostructures are reviewed together with their applications including the treatment volatile organic compounds (VOCs), heavy metal ions from polluted water, spilled oil, fillers for advanced composites, etc. This paper gives the usage of biomass in a sustainable and green way.

ABSTRACTIn many Vibrio species, virulence is regulated by quorum sensing, which is regulated by a complex, multichannel, two-component phosphorelay circuit. Through this circuit, sensor kinases transmit sensory information to the phosphotransferase LuxU via a phosphotransfer mechanism, which in turn transmits the signal to the response regulator LuxO. For Vibrio parahaemolyticus, type III secretion system 1 (T3SS1) is required for cytotoxicity, but it is unclear how quorum sensing regulates T3SS1 expression. Herein, we report that a hybrid histidine kinase, ArcB, instead of LuxU, and sensor kinase LuxQ and response regulator LuxO, collectively orchestrate T3SS1 expression in V. parahaemolyticus. Under high oxygen conditions, LuxQ can interact with ArcB directly and phosphorylates the Hpt domain of ArcB. The Hpt domain of ArcB phosphorylates the downstream response regulator LuxO instead of ArcA. LuxO then activates transcription of the T3SS1 gene cluster. Under hypoxic conditions, ArcB autophosphorylates and phosphorylates ArcA, whereas ArcA does not participate in regulating the expression of T3SS1. Our data provides evidence of an alternative regulatory path involving the quorum sensing phosphorelay and adds another layer of understanding about the environmental regulation of gene expression in V. parahaemolyticus.

Abstract Mechanical properties of red blood cells (RBCs) change during their senescence which supports numerous physiological or pathological processes in circulatory systems by providing crucial cellular mechanical environments of hemodynamics. However, quantitative studies on the aging and variations of RBC properties are largely lacking. Herein, we investigate morphological changes, softening or stiffening of single RBCs during aging using an in vitro mechanical fatigue model. Using a microfluidic system with microtubes, RBCs are repeatedly subjected to stretch and relaxation as they squeeze into and out of a sudden contraction region. Geometric parameters and mechanical properties of healthy human RBCs are characterized systematically upon each mechanical loading cycle. Our experimental results identify three typical shape transformations of RBCs during mechanical fatigue, which are all strongly associated with the loss of surface area. We constructed mathematical models for the evolution of surface area and membrane shear modulus of single RBCs during mechanical fatigue, and quantitatively developed an ensemble parameter to evaluate the aging status of RBCs. This study provides not only a novel in vitro fatigue model for investigating the mechanical behavior of RBCs, but also an index closely related to the age and inherent physical properties for a quantitative differentiation of individual RBCs.

Abstract New satellite remote sensing and machine learning techniques offer untapped possibilities to monitor global biodiversity with unprecedented speed and precision. These efficiencies promise to reveal novel ecological insights at spatial scales which are germane to the management of populations and entire ecosystems. Here, we present a robust transferable deep learning pipeline to automatically locate and count large herds of migratory ungulates (wildebeest and zebra) in the Serengeti-Mara ecosystem using fine-resolution (38-50 cm) satellite imagery. The results achieve accurate detection of nearly 500,000 individuals across thousands of square kilometers and multiple habitat types, with an overall F1-score of 84.75% (Precision: 87.85%, Recall: 81.86%). This research demonstrates the capability of satellite remote sensing and machine learning techniques to automatically and accurately count very large populations of terrestrial mammals across a highly heterogeneous landscape. We also discuss the potential for satellite-derived species detections to advance basic understanding of animal behavior and ecology.

Objective: To explore the mechanism and related active components of Yishen Daluo decoction (YSDLD) in treating multiple sclerosis (MS). Methods: Targets of YSDLD were collected through the TCMSP, Chemistry, and TCMID databases. The MS targets were collected through OMIM, DrugBank, Gencards, TTD, and Pharmgkb databases. We built “component–target” network diagrams and protein–protein interaction (PPI) diagrams and performed topological analysis. The targets were subjected to GO and KEGG enrichment analysis. Molecular docking verification was conducted on selected targets and molecules. Finally, in vitro experiments were conducted. BV2 cells were induced by lipopolysaccharide for model establishment. CCK8 experiment was conducted to explore the effect of YSDLD and RT-qPCR technology was used to explore the expression of key targets. Results: There were 184 active components in YSDLD and 898 targets of its action. There were 940 MS targets, and 215 targets were shared by YSDLD and MS. According to the “component–target” diagram, the top five key components included quercetin, kaempferol, beta-sitosterol, stigmasterol, and naringenin. IL-6, IL-1β, TNF-α, AKT1, and VEGFA were the important targets identified by PPI network topology analysis. A total of 564 functions were identified by GO enrichment analysis (P

Abstract Background Malnutrition and inflammation are associated with adverse clinical outcomes in patients with diabetes or coronary artery disease (CAD). Prognostic nutritional index (PNI) is a comprehensive and simple indicator reflecting nutritional condition and immunological status. Whether there is a crosstalk between nutritional-immunological status and diabetes status for the impact on the prognosis of coronary artery disease (CAD) is unclear. Methods A total of 9429 consecutive CAD patients undergoing percutaneous coronary intervention were grouped by diabetes status [diabetes (DM) and non-diabetes (non-DM)] and preprocedural PNI level [high PNI (H-PNI) and low PNI (L-PNI)] categorized by the statistically optimal cut-off value of 48.49. The primary endpoint was all-cause death. Results During a median follow-up of 5.1 years (interquartile range: 5.0–5.1 years), 366 patients died. Compared with the non-DM/H-PNI group, the DM/L-PNI group yielded the highest risk of all-cause death (adjusted hazard ratio: 2.65, 95% confidence interval: 1.97–3.56, p

Abstract Background The “missing” link of complex and multifaceted interplay among endogenous retroviruses (ERVs) transcription, chronic immuno-inflammation, and the development of psychiatric disorders is still far from being completely clarified. The present study was aimed to investigate the mechanism of protective role of inhibiting ERVs on reversing microglial immuno-inflammation in basolateral amygdala (BLA) in chronic stress-induced negative emotional behaviors in mice. Methods Male C57BL/6 mice were exposed to chronic unpredictable mild stress (CUMS) for 6 w. Negative emotional behaviors were comprehensively investigated to identify the susceptible mice. Microglial morphology, ERVs transcription, intrinsic nucleic acids sensing response, and immuno-inflammation in BLA were assessed. Results Mice with chronic stress were presented as obviously depressive- and anxiety-like behaviors, and accompanied with significant microglial morphological activation, murine ERVs genes MuERV-L, MusD, and IAP transcription, cGAS–IFI16–STING pathway activation, NF-κB signaling pathway priming, as well as NLRP3 inflammasome activation in BLA. Antiretroviral therapy, pharmacological inhibition of reverse transcriptases, as well as knocking-down the ERVs transcriptional regulation gene p53 significantly inhibited microglial ERVs transcription and immuno-inflammation in BLA, as well as improved the chronic stress-induced negative emotional behaviors. Conclusions Our results provided an innovative therapeutic approach that targeting ERVs-associated microglial immuno-inflammation may be beneficial to the patients with psychotic disorders.

Studies have shown that gut microbiota metabolites can enter the central nervous system via the blood-spinal cord barrier and cause neuroinflammation, thus constituting secondary injury after spinal cord injury. To investigate the correlation between gut microbiota and metabolites and the possible mechanism underlying the effects of gut microbiota on secondary injury after spinal cord injury, in this study, we established mouse models of T8–T10 traumatic spinal cord injury. We used 16S rRNA gene amplicon sequencing and metabolomics to reveal the changes in gut microbiota and metabolites in fecal samples from the mouse model. Results showed a severe gut microbiota disturbance after spinal cord injury, which included marked increases in pro-inflammatory bacteria, such as Shigella, Bacteroides, Rikenella, Staphylococcus, and Mucispirillum and decreases in anti-inflammatory bacteria, such as Lactobacillus, Allobaculum, and Sutterella. Meanwhile, we identified 27 metabolites that decreased and 320 metabolites that increased in the injured spinal cord. Combined with pathway enrichment analysis, five markedly differential amino acids (L-leucine, L-methionine, L-phenylalanine, L-isoleucine and L-valine) were screened out, which play a pivotal role in activating oxidative stress and inflammatory responses following spinal cord injury. Integrated correlation analysis indicated that the alteration of gut microbiota was related to the differences in amino acids, which suggests that disturbances in gut microbiota might participate in the secondary injury through the accumulation of partial metabolites that activate oxidative stress and inflammatory responses. Findings from this study provide a new theoretical basis for improving the secondary injury after spinal cord injury through fecal microbial transplantation.

Owing to the global coverage and high visibility of global navigation satellite systems (GNSS), passive radar using GNSS satellites as transmitters of opportunity has shown great potential for moving target detection, and its possibility to detect short-range maritime targets has been verified. Nevertheless, the existing methods always require tens of seconds for echo integration, which is not ideal for the detection of targets with high maneuverability. To solve this problem, a bistatic configuration using BeiDou geostationary earth orbit (GEO) satellites as illuminators of opportunity, which is suited for short-time coherent integration of echo signals, is presented. In addition, the corresponding signal processing method is introduced. To achieve a more continuous trajectory of the target, a method used to fuse range-Doppler maps obtained individually from multiple BeiDou GEO satellites is also described. The effectiveness and functionality of our proposed algorithms are demonstrated with an experiment in which a ferry was used as a moving target and its real-time location data were adopted as a reference.

Accurate extraction of urban green space is critical for preserving urban ecological balance and enhancing urban life quality. However, due to the complex urban green space morphology (e.g., different sizes and shapes), it is still challenging to extract green space effectively from high-resolution image. To address this issue, we proposed a novel hybrid method, Multi-scale Feature Fusion and Transformer Network (MFFTNet), as a new deep learning approach for extracting urban green space from high-resolution (GF-2) image. Our method was characterized by two aspects: (1) a multi-scale feature fusion module and transformer network that enhanced the recovery of green space edge information and (2) vegetation feature (NDVI) that highlighted vegetation information and enhanced vegetation boundaries identification. The GF-2 image was utilized to build two urban green space labeled datasets, namely Greenfield and Greenfield2. We compared the proposed MFFTNet with the existing popular deep learning models (like PSPNet, DensASPP, etc.) to evaluate the effectiveness of MFFTNet by the Mean Intersection Over Union (MIOU) benchmark on Greenfield, Greenfield2, and a public dataset (WHDLD). Experiments on Greenfield2 showed that MFFTNet can achieve a high MIOU (86.50%), which outperformed deep learning networks like PSPNet and DensASPP by 0.86% and 3.28%, respectively. Meanwhile, the MIOU of MFFTNet incorporating vegetation feature (NDVI) was further achieved to 86.76% on Greenfield2. Our experimental results demonstrate that the proposed MFFTNet with vegetation feature (NDVI) outperforms the state-of-the-art methods in urban green space segmentation.

Accurate urban land cover information is crucial for effective urban planning and management. While convolutional neural networks (CNNs) demonstrate superior feature learning and prediction capabilities using image-level annotations, the inherent mixed-category nature of input image patches leads to classification errors along object boundaries. Fully convolutional neural networks (FCNs) excel at pixel-wise fine segmentation, making them less susceptible to heterogeneous content, but they require fully annotated dense image patches, which may not be readily available in real-world scenarios. This paper proposes an object-based semi-supervised spatial attention residual UNet (OS-ARU) model. First, multiscale segmentation is performed to obtain segments from a remote sensing image, and segments containing sample points are assigned the categories of the corresponding points, which are used to train the model. Then, the trained model predicts class probabilities for all segments. Each unlabeled segment’s probability distribution is compared against those of labeled segments for similarity matching under a threshold constraint. Through label propagation, pseudo-labels are assigned to unlabeled segments exhibiting high similarity to labeled ones. Finally, the model is retrained using the augmented training set incorporating the pseudo-labeled segments. Comprehensive experiments on aerial image benchmarks for Vaihingen and Potsdam demonstrate that the proposed OS-ARU achieves higher classification accuracy than state-of-the-art models, including OCNN, 2OCNN, and standard OS-U, reaching an overall accuracy (OA) of 87.83% and 86.71%, respectively. The performance improvements over the baseline methods are statistically significant according to the Wilcoxon Signed-Rank Test. Despite using significantly fewer sparse annotations, this semi-supervised approach still achieves comparable accuracy to the same model under full supervision. The proposed method thus makes a step forward in substantially alleviating the heavy sampling burden of FCNs (densely sampled deep learning models) to effectively handle the complex issue of land cover information identification and classification.

Despite the partial disclosure of driving scenario knowledge graphs, they still fail to meet the comprehensive needs of intelligent connected vehicles for driving knowledge. Current issues include the high complexity of pattern layer construction, insufficient accuracy of information extraction and fusion, and limited performance of knowledge reasoning models. To address these challenges, a hybrid knowledge graph method was adopted in the construction of a driving scenario knowledge graph (DSKG). Firstly, core concepts in the field were systematically sorted and classified, laying the foundation for the construction of a multi-level classified knowledge graph top-level ontology. Subsequently, by deeply exploring and analyzing the Traffic Genome data, 34 entities and 51 relations were extracted and integrated with the ontology layer, achieving the expansion and updating of the knowledge graph. Then, in terms of knowledge reasoning models, an analysis of the training results of the TransE, Complex, Distmult, and Rotate models in the entity linking prediction task of DSKG revealed that the Distmult model performed the best in metrics such as hit rate, making it more suitable for inference in DSKG. Finally, a standardized and widely applicable driving scenario knowledge graph was proposed. The DSKG and related materials have been publicly released for use by industry and academia.

Combinatorial drug therapy has emerged as a critically important strategy in medical research and patient treatment and involves the use of multiple drugs in concert to achieve a synergistic effect. This approach can enhance therapeutic efficacy while simultaneously mitigating adverse side effects. However, the process of identifying optimal drug combinations, including their compositions and dosages, is often a complex, costly, and time-intensive endeavor. To surmount these hurdles, we propose a novel microfluidic device capable of simultaneously generating multiple drug concentration gradients across an interlinked array of culture chambers. This innovative setup allows for the real-time monitoring of live cell responses. With minimal effort, researchers can now explore the concentration-dependent effects of single-agent and combination drug therapies. Taking neural stem cells (NSCs) as a case study, we examined the impacts of various growth factors—epithelial growth factor (EGF), platelet-derived growth factor (PDGF), and fibroblast growth factor (FGF)—on the differentiation of NSCs. Our findings indicate that an overdose of any single growth factor leads to an upsurge in the proportion of differentiated NSCs. Interestingly, the regulatory effects of these growth factors can be modulated by the introduction of additional growth factors, whether singly or in combination. Notably, a reduced concentration of these additional factors resulted in a decreased number of differentiated NSCs. Our results affirm that the successful application of this microfluidic device for the generation of multi-drug concentration gradients has substantial potential to revolutionize drug combination screening. This advancement promises to streamline the process and accelerate the discovery of effective therapeutic drug combinations.