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Abstract Background This study investigated the clinical value of breast magnetic resonance imaging (MRI) radiomics for predicting axillary lymph node metastasis (ALNM) and to compare the discriminative abilities of different combinations of MRI sequences. Methods This study included 141 patients diagnosed with invasive breast cancer from two centers (center 1: n = 101, center 2: n = 40). Patients from center 1 were randomly divided into training set and test set 1. Patients from center 2 were assigned to the test set 2. All participants underwent preoperative MRI, and four distinct MRI sequences were obtained. The volume of interest (VOI) of the breast tumor was delineated on the dynamic contrast-enhanced (DCE) postcontrast phase 2 sequence, and the VOIs of other sequences were adjusted when required. Subsequently, radiomics features were extracted from the VOIs using an open-source package. Both single- and multisequence radiomics models were constructed using the logistic regression method in the training set. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and precision of the radiomics model for the test set 1 and test set 2 were calculated. Finally, the diagnostic performance of each model was compared with the diagnostic level of junior and senior radiologists. Results The single-sequence ALNM classifier derived from DCE postcontrast phase 1 had the best performance for both test set 1 (AUC = 0.891) and test set 2 (AUC = 0.619). The best-performing multisequence ALNM classifiers for both test set 1 (AUC = 0.910) and test set 2 (AUC = 0.717) were generated from DCE postcontrast phase 1, T2-weighted imaging, and diffusion-weighted imaging single-sequence ALNM classifiers. Both had a higher diagnostic level than the junior and senior radiologists. Conclusions The combination of DCE postcontrast phase 1, T2-weighted imaging, and diffusion-weighted imaging radiomics features had the best performance in predicting ALNM from breast cancer. Our study presents a well-performing and noninvasive tool for ALNM prediction in patients with breast cancer.

Abstract The application of blockchain technology to the field of e-commerce has solved many dilemmas, such as low transparency of transactions, hidden risks of data security and high payment costs. Mobile edge computing(MEC) can provide computational power for blockchain, and can meet the demand for high real-time and low latency in e-commerce transaction systems. However, there are still some constraints in the MEC enabled e-commerce consortium blockchain, such as the leakage of user privacy information, low security of consensus algorithm and other security issues. In this paper, we propose a secure transaction model suitable for MEC enabled e-commerce consortium blockchain, aiming to ensure the efficiency of system transaction processing while improving the security of users’ privacy information and transaction data. The model adopts the lightweight Paillier encryption algorithm to protect the security of user privacy information and transaction data to prevent the leakage of user privacy information, and optimizes the security of leader election phase of Raft consensus algorithm by introducing the shamir secret sharing protocol to improve the anti-Byzantine failure capabilities of Raft consensus algorithm. The effectiveness of the scheme proposed in this paper is demonstrated by experimental simulations.

Abstract Background This study investigated the role of Galectin-3 in the degeneration of intervertebral disc cartilage. Methods The patients who underwent lumbar spine surgery due to degenerative disc disease were recruited and divided into Modic I, Modic II, and Modic III; groups. HE staining was used to detect the pathological changes in endplates. The changes of Galectin-3, MMP3, Aggrecan, CCL3, and Col II were detected by immunohistochemistry, RT-PCR, and Western blot. MTT and flow cytometry were used to detect cartilage endplate cell proliferation, cell cycle, and apoptosis. Results With the progression of degeneration (from Modic I to III), the chondrocytes and density of the cartilage endplate of the intervertebral disc decreased, and the collagen arrangement of the cartilage endplate of the intervertebral disc was broken and calcified. Meanwhile, the expressions of Aggrecan, Col II, Galectin-3, Aggrecan, and CCL3 gradually decreased. After treatment with Galectin-3 inhibitor GB1107, the proliferation of rat cartilage end plate cells was significantly reduced (P

Summary: Background: Endovascular therapy (EVT) was demonstrated effective in acute large vessel occlusion (LVO) with large infarction. Revealing subgroups of patients who would or would not benefit from EVT will further inform patient selection for EVT. Methods: This post-hoc analysis of the ANGEL-ASPECT trial, a randomised controlled trial of 456 adult patients with acute anterior-circulation LVO and large infarction, defined by ASPECTS 3–5 or infarct core volume 70–100 mL, enrolled from 46 centres across China, between October 2, 2020 and May 18, 2022. Patients were randomly assigned (1:1) to receiving EVT and medical management or medical management alone. One patient withdrew consent, 455 patients were included in this post-hoc analysis and categorised into 4 subgroups by lower or higher NIHSS (< or ≥16) and smaller or larger infarct core (< or ≥70 mL). Those with lower NIHSS & smaller core, and higher NIHSS & larger core were considered clinical-radiological matched subgroups; otherwise clinical-radiological mismatched subgroups. Primary outcome was 90-day modified Rankin Scale (mRS). ANGEL-ASPECT is registered with ClinicalTrials.gov, NCT04551664. Findings: Overall, 139 (30.5%) patients had lower NIHSS & smaller core, 106 (23.3%) higher NIHSS & larger core, 130 (28.6%) higher NIHSS & smaller core, and 80 (17.6%) lower NIHSS & larger core. There was significant ordinal shift in the 90-day mRS toward a better outcome with EVT in clinical-radiological matched subgroups: lower NIHSS & smaller core (generalised OR, 1.76; 95% CI, 1.18–2.62; p = 0.01) and higher NIHSS & larger core (1.64; 1.06–2.54; 0.01); but not in the two clinical-radiological mismatched subgroups. Interpretation: Our findings suggested that in patients with anterior-circulation LVO and large infarction, EVT was associated with improved 90-day functional outcomes in those with matched clinical and radiological severities, but not in those with mismatched clinical and radiological severities. Simultaneous consideration of stroke severity and infarct core volume may inform patient selection for EVT. Funding: Unrestricted grants from industry [Covidien Healthcare International Trading (Shanghai), Johnson & Johnson MedTech, Genesis MedTech (Shanghai), and Shanghai HeartCare Medical Technology].

Objective: Numerous studies have posited the involvement of serum uric acid (SUA) in the pathogenesis and progression of various cardiovascular diseases, particularly aortic aneurysms. However, the casual effect of SUA level on intracranial aneurysms (IAs) was rarely studied. Consequently, we aimed to explore the causal association between SUA and IAs using Mendelian randomization (MR) analysis. Methods: We conducted a two-sample MR analysis with SUA as the exposure variable and IAs as the outcome variable. Genome-wide association study (GWAS) datasets for SUA were acquired from the Open GWAS catalog, including 389,404 European and 129,405 East Asian individuals. The dataset for IAs was sourced from a meta-analysis of GWASs comprising 317,636 individuals across different ancestral populations (European: 7495 cases and 71,934 controls; East Asian: 3259 cases and 234,948 controls). The MR analyses were performed according to populations (European and East Asian) and IAs status [unruptured IAs (uIAs) or aneurysmal subarachnoid hemorrhage (aSAH)], respectively. The inverse variance weighted (IVW) method was employed as primary analysis to discern causal estimates. Results: Our findings revealed that an elevated genetically predicted SUA level (mg/dL) correlated with an increased risk of IAs among the European population (OR = 1.29 [95%CI:1.05–1.57], P = 0.013) and East Asian population (OR = 1.56 [95%CI: 1.27–1.92], P

Global climate change has led to ocean warming, acidification, hypoxia, and alterations in the biogeochemical circulation, thereby influencing the distribution, abundance, and population patterns of marine organisms. Particularly, oysters, which tend to attach to rocks in intertidal zones, may be more vulnerable to climate change. The Kumamoto oyster, Crassostrea sikamea (Amemiya, 1928), is renowned for its nutritional content, breeding benefits, and ecosystem restoration abilities. Previous research has demonstrated that the geographical range of C. sikamea in China has gradually shifted. In this study, the Maximum Entropy (MaxEnt) model was employed to predict the suitability for C. sikamea under different climate scenarios. We utilized first-hand data collected by our research team over the past 14 years, which consisted of 3030 C. sikamea samples from seven provinces in China. The contribution rate of the environmental variables and the jackknife test revealed that salinity (13–21PSS) and temperature (24.6–25.5 °C) are the primary factors influencing the distribution of C. sikamea. The future distribution shows a south-to-north migration pattern triggered by increased sea temperature, resulting in increased suitability at higher latitudes. The migratory effect is more dramatic under the high-emission scenario (Representative Concentration Pathways 8.5 (RCP8.5)) compared to medium-(RCP4.5/RCP6.0) and low-emission scenarios (RCP2.6) and becomes increasingly evident over time. Model predictions indicated that C. sikamea could maintain its suitability under all climate scenarios until the 2050s. However, by the 2100s, the suitability is expected to shift northward beyond the 33–34°N boundary under RCP2.6, RCP6.0, and RCP8.5, extending to the northern coast of Jiangsu. The suitability of C. sikamea within its habitat may experience a significant decline by the 2050s, followed by a gradual recovery over the next 50 years. The potential northward migration of C. sikamea presents new prospects for oyster aquaculture and artificial reefs establishment in China. However, this migration will inevitably lead to significant impacts on the invaded ecosystems and overall biodiversity.

Reducing carbon emissions, upgrading industrial structure, and promoting green total factor productivity are important ways to tackle global climate change. The Yangtze River Economic Belt is an important economic region and industrial corridor in China. Using the panel data of 11 provinces in the Yangtze River Economic Belt from 2006 to 2020, this study calculates industrial green total factor productivity using the super-efficient SBM model, and analyzes its evolution trends in time and space. This study discusses how carbon constraints and industrial structure upgrading affect green total factor productivity by using benchmark regression and the intermediary effect model. The results show that green total factor productivity is fluctuating and rising over time, and is in a gradient decreasing spatial distribution from the Yangtze River Delta to Urban Agglomeration in the Middle Reaches to Chengdu–Chongqing Economic Zone; carbon constraints, industrial structure upgrading, and their synergy have a positive effect on the industrial green total factor productivity; industrial structure upgrading has partial intermediary effects, and can help carbon constraints positively impact on industrial green development. Based on the above results, reducing carbon emission and accelerating industrial structure upgrading are important for achieving economic and ecological sustainability. HIGHLIGHTS Calculate green total factor productivity and analyze trends.; Carbon constraints (ER) are measured by the weighted sum of energy consumption and CO2 emission.; Use different models to analyze the relationship among carbon constraints, industrial structure, and green total factor productivity.; Provide an effective tool for developing carbon emission and green industry management strategies in other regions of the world.;

The digital economy provides a new path to promote industrial structure upgrading. Using panel data from 2011 to 2020 for 85 resource-based cities in China, this paper empirically investigates the impact of the digital economy on industrial structure upgrading and the primary mechanism. The results show that the digital economy is conducive to promoting industrial structure upgrading in resource-based cities, and innovation is the primary mechanism of action. According to the different stages of resource development, we classify resource-based cities into growth, maturity, decline, and regeneration cities, and we further analyze the heterogeneous influence. In terms of influence degree, the digital economy has a more prominent role in promoting industrial structure upgrading in resource-exhausted cities. In addition, we also found that the closer to the provincial capital city, the more pronounced the promotion of the digital economy to the industrial structure upgrading.

Background: /purpose: Periodontal disease is a chronic inflammatory disease that occurs in the tissues that support and attach teeth. There is considerable evidence of a relationship between diabetes and periodontal disease. Emerging studies have reported that myeloid-derived growth factor (MYDGF) can inhibit apoptosis and inflammation. The purpose of this study was to investigate whether MYDGF mediates the role of hyperglycemia in fibroblasts in periodontitis tissues. Materials and methods: Fibroblasts were isolated and cultured from normal gums. Gene expression levels were detected by RT-PCR. The protein level was detected by western blotting. Cell viability was determined by MTT assay. To investigate the role of MYDGF, the plasmid was transfected into fibroblasts. The expression levels of cytokines were determined by ELISA. Results: High glucose can down-regulate the expression of MYDGF in human gingival fibroblasts in a time-dependent manner, and decrease the fibroblast activity. SOD level was decreased and MDA level was increased in gingival fibroblasts by high glucose. High glucose up-regulates pro-apoptotic indicator Bax, down-regulates anti-apototic indicator Bcl-2, and increased endoplasmic reticulum stress related indicators Nox 2, GRP78, ATF6, and PERK. In addition, high glucose increased TNF-α, IL-1β, IL-8 and CXCL1 protein levels in fibroblasts. Our study also found that high glucose inhibits the AKT signaling pathway and activates the nuclear factor κB (NF-κB) pathway. Interestingly, overexpression of MYDGF reversed these effects. Conclusion: MYDGF is down-regulated in gingival fibroblasts induced by high glucose. Overexpression of MYDGF inhibits apoptosis induced by high glucose, inhibits oxidative stress and cytokine secretion of gingival fibroblasts induced by high glucose, and induces AKT pathway activation and NF-κB pathway inhibition.

Heavy metal pollution is a gradually growing environmental issue that hinders the growth and development of plants, and also destabilizes soil. Consequently, eco-friendly phytoremediation methods have gained traction, with energy crops emerging as a particularly effective solution. Energy crops not only provide high-quality plant materials for detoxification and remediation of heavy metal pollution, but also possess energy properties conducive to biofuel production. Therefore, this paper delves into the tolerance mechanism of energy crops towards heavy metal toxicity, elucidating processes such as root complex-mediated inhibition of metal migration and response to reactive oxygen species (ROS) through heavy metal-related proteins, enzyme systems, reactive nitrogen species (RNS), and hormones. Moreover, it summarizes the heavy metals remediation mechanisms of energy crops, including uptake, translocation, chelation, immobilization, and sequestration. This paper explores applications of energy crops in heavy metal pollution remediation, emphasizing the methods for efficient biochar remediation and biofuel generation. Furthermore, potential challenges in using energy crops for heavy metal pollution remediation are outlined. By systematically examining the function mechanisms and prospective applications of energy crops in heavy metal pollution bioremediation, this paper serves as a valuable reference for both research and practical implementation in this field.

Abstract In this article, selective laser melting (SLM) equipment is used to print 316L stainless steel parts under different process parameters, and the surface roughness of the parts is measured. Based on back propagation neural networks (BP neural networks, BPNN), the upper surface roughness prediction model is established. The laser power, scanning speed, and scanning interval are used as model input, and the surface roughness of the workpiece is output. This model can easily and quickly predict the surface roughness of SLM metal printing, with high prediction accuracy, and can provide a basis for the optimization of SLM process parameters.

ObjectiveThrombectomy may provide superior results compared to best medical care for acute posterior circulation strokes (PCS). Contact aspiration (CA), stent retriever (SR), and combined SR + CA (SRA) are commonly employed as first-line techniques. However, the optimal strategy and the role of SRA remain uncertain.MethodsSystematic searching was conducted in three databases (PubMed, Embase, and Cochrane). Network meta-analyzes were performed using random-effects models. The reperfusion and clinical outcomes were compared. Pooled outcomes were presented as odds ratios (OR) with 95% confidence intervals (CI). Rankograms with surface under the cumulative ranking curve (SUCRA) were calculated.ResultsSeventeen studies were included, involving a total of 645 patients who received first-line CA, 850 patients who received SR, and 166 patients who received SRA. Regarding final recanalization outcomes, both first-line SRA (OR = 3.2, 95%CI 1.4–11.0) and CA (OR = 2.1, 95%CI 1.3–3.7) demonstrated superiority over SR in achieving successful reperfusion [modified Thrombolysis In Cerebral Infarction (mTICI) 2b-3], with values of SUCRA 91.1, 58.5, and 0.4%, respectively. In addition, first-line SRA showed an advantage in achieving final mTICI 2c/3 compared to CA (OR = 3.6, 95%CI 0.99–16.0) and SR (OR = 6.4, 95%CI 1.3–35.0), with SUCRA value of 98.0, 44.7, and 7.2%, respectively. Regarding reperfusion outcome after the first pass, SRA also achieved a higher rate of mTICI 3 than SR (OR = 4.1, 95%CI 1.3–14.0), while CA did not (SUCRA 97.4, 4.6, 48.0%). In terms of safety outcomes, first-line CA was associated with a lower incidence of symptomatic intracranial hemorrhage (sICH) compared to SR (OR = 0.38, 95%CI 0.1–1.0), whereas the SRA technique did not (SUCRA 15.6, 78.6, 55.9%). Regarding clinical prognosis, first-line CA achieved a higher proportion of functional independence (modified Rankin Scale (mRS) 0–2) at 90 days than SR (OR = 1.4, 95%CI 1.1–1.9), whereas SRA did not (SUCRA 90.5, 17.4, 42.1%).ConclusionFor acute PCS, a first-line CA strategy yielded better results in terms of final successful reperfusion and 90-day functional independence compared to SR. As the combined technique, first-line SRA was associated with superior first-pass and final reperfusion outcomes compared to SR. However, no significant difference was observed in functional independence achieved by first-line SRA compared to the other two strategies. Further high-quality studies are warranted.

Using panel data from 11 provinces from 2003 to 2017 in the Yangtze River Economic Belt, the study explores the spatio-temporal differentiation characteristics and driving forces of coupling coordination of urban land and water resource utilization efficiency by constructing the coupling coordination model and the spatial econometric model. The results show that (1) in terms of time, the situation of inefficient utilization of urban land and water resources was severe. Spatially, the distribution of utilization efficiency of two resources was consistent with the pattern of regional economic development; (2) the coupling coordination degree of urban land and water resources utilization efficiency was mainly of mild disorder type and transitional type, and was in a gradient decreasing spatial distribution from downstream to midstream to the upstream region; (3) the coupling coordination degree of urban land and water resources utilization efficiency presented significantly positive spatial auto-correlation, but the agglomeration trend was weakening; (4) per capita GDP, employment labor force and fixed assets investment were important driving forces for the coordination development of urban land and water resources, while the role of government and the total population had a negative impact on it, and the driving role of the industrial structure had not yet been played. HIGHLIGHTS This study analyzes the spatio-temporal differentiation characteristics of urban land and water resources utilization efficiency.; This study explores the driving forces of coupling coordination degree of urban land and water resources.; This study makes it possible to point out the weak factors, so as to improve the related strategies to help build a harmonious relationship between urban land and water resources.;

The development of the DC distribution system (DCDS) has attracted increasing attention, due to its technological superiorities in integrating new energy sources and DC power loads more friendly and effectively. In this paper, a comprehensive evaluation method is proposed for the medium–low​ voltage DCDS to handle the voltage sag assessment problem. Firstly, the topology structure and control strategy of the DCDS are stated, and the pragmatic characteristics of DC voltage sag on the medium-voltage and low-voltage sides based on the dual active bridge (DAB) converter are analyzed. Then, considering the difference in the evaluation indexes of the low-voltage and medium-voltage sides of the DCDS, a comprehensive evaluation system is established. Further, the analytic hierarchy process (AHP) and criteria importance through intercriteria correlation (CRITIC) weighting method are applied to achieve comprehensive weighting, and the TOPSIS model is used to describe the severity of DC voltage sag. Using MATLAB, a 10 kV/ 750 V DCDS with the DAB is built, and comparative assessments are performed. The results show that the proposed method can reasonably evaluate the DC voltage sag of the low-voltage and medium-voltage sides. Compared to the evaluation schemes based on the single index, the proposed method can more effectively reflect the waveform features of the DC voltage sag, and it is very appropriate for the voltage dip evaluation of the medium–low voltage DCDS.

Cryopreservation of fish semen is a valuable technique for reproductive management in aquaculture. The aim of this study was to evaluate the effect of long-term storage in liquid nitrogen on post-thaw sperm functional parameters of brown-marbled grouper (Epinephelus fuscoguttatus). Samples were cryopreserved in a simple freezing medium (10 % DMSO + 0.3 M Glucose), sperm quality parameters were assessed at different storage periods (one month, one year, 2 years and 3 years). Our results indicated that cryostorage periods had a significant effect on the quality of frozen-thawed spermatozoa. Compared with fresh semen, cryopreserved sample was characterized by an overall decline in motility, viability, mitochondrial membrane potential (MMP), ATP content and increased level of lipid peroxidation with the storage time going on. For the analyzed quality parameters, there were no significant differences in storage time cryopreserved over one month. After 3 years of storage, frozen sperm still showed relatively high total motility, viability and MMP (all over 80 %), yielding acceptable fertilizing capacity close to that of fresh sperm. Therefore, it can be concluded that brown-marbled grouper sperm could be effectively cryopreserved for at least 3 years. The results of this study would be helpful to optimize gamete management in routine hatchery practices.

Hyperaldosteronism is a common disease that is closely related to endocrine hypertension and other cardiovascular diseases. Cytochrome P450 11B2 (CYP11B2), an important enzyme in aldosterone (ALD) synthesis, is a promising target for the treatment of hyperaldosteronism. However, selective inhibitors targeting CYP11B2 are still lacking due to the high similarity with CYP11B1. In this study, atractylenolide-I (AT-I) was found to significantly reduce the production of ALD but had no effect on cortisol synthesis, which is catalyzed by CYP11B1. Chemical biology studies revealed that due to the presence of Ala320, AT-I is selectively bound to the catalytic pocket of CYP11B2, and the C8/C9 double bond of AT-I can be epoxidized, which then undergoes nucleophilic addition with the sulfhydryl group of Cys450 in CYP11B2. The covalent binding of AT-I disrupts the interaction between heme and CYP11B2 and inactivates CYP11B2, leading to the suppression of ALD synthesis; AT-I shows a significant therapeutic effect for improving hyperaldosteronism.

Optimizing the quantum circuit for implementing Advanced Encryption Standard (AES) is crucial for estimating the necessary resources in attacking AES by the Grover algorithm. Previous studies have reduced the number of qubits required for the quantum circuits of AES-128/-192/-256 from 984/1112/1336 to 270/334/398, which is close to the optimal value of 256/320/384. It becomes a challenging task to further optimize them. AimTaking aim at this task, we find a method for how the quantum circuit of AES S-box can be designed with the help of the automation tool LIGHTER-R. Particularly, the multiplicative inversion in F28, which is the main part of the S-box, is converted into the multiplicative inversion (and multiplication) in F24, then the latter can be implemented by LIGHTER-R because its search space is small enough. By this method, we construct the quantum circuits of S-box for mapping |a⟩|0⟩ to |a⟩|S(a)⟩ and |a⟩|b⟩ to |a⟩|b ⊕ S(a)⟩ with 20 qubits instead of 22 in the previous studies. In addition, we introduce new techniques to reduce the number of qubits required by the S-box circuit for mapping |a⟩ to |S(a)⟩ from 22 in the previous studies to 16. Accordingly, we synthesize the quantum circuits of AES-128/-192/-256 with 264/328/392 qubits, which implies a new record.

Based on panel data from 2000 to 2017 in 29 Chinese provinces, this paper analyzes the impact of industrial structure upgrading on carbon emissions by constructing a spatial panel model and a panel threshold model. The results show that (1) there is a significant spatial correlation between carbon emissions in Chinese provinces, and the carbon emissions of a province are affected by the carbon emissions of surrounding provinces; (2) in China, carbon emissions have a significant time lag feature, and current carbon emissions are largely affected by previous carbon emissions; (3) industrial structure upgrading can effectively promote carbon emission reductions in local areas, and the impact of industrial structure upgrading on carbon emissions has a significant threshold effect. With continued economic development, the promotion effect of industrial structure upgrading on carbon emission reductions will decrease slightly, but this carbon emission reduction effect is still significant. (4) In addition, there is a clear difference between the impact of energy consumption intensity and population size on carbon emissions in short and long terms. In the short term, the increase in energy consumption intensity and the expansion of population size not only increase the carbon emissions of a local area but also increase the carbon emissions of neighboring areas. In the long term, the impact of energy consumption intensity and population size on carbon emissions of neighboring areas will be weakened, but the promotion impact on carbon emissions in local areas will be strengthened. HIGHLIGHTS This paper studies the impact of industrial structure upgrading on carbon emissions in detail.; This paper uses a static spatial panel model and a dynamic spatial panel model for analysis.; This paper uses economic development as a threshold variable to determine whether the impact direction and degree of industrial structure upgrading on carbon emissions will change with economic development.;

Abstract Background Syntaxin4 (STX4) gene encodes the protein STX4, a member of soluble N-ethylmaleimide-sensitive factor attachment protein receptors protein, playing a vital role in cell invadopodium formation and invasion, which is associated with the malignant progression of various human cancers. However, the expression and prognostic significance of STX4 in kidney renal clear cell carcinoma (KIRC) remain to be investigated. Methods In this study, we collected the mRNA expression of STX4 in 535 KIRC patients from The Cancer Genome Atlasthrough the University of California Santa Cruz Xena database platform. Then we explored the expression of STX4 in KIRC, and the relationship with clinicopathological characteristics and prognostic value. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes function enrichment analyses were used to explore the potential mechanism of STX4 in KIRC. qRT-PCR analysis was performed toverify the above results with real world tissue specimens. Results The results indicated that STX4 was up-expressed in KIRC, and were associated with higher histological grade, advanced stage, and poorer prognosis. Moreover, elevated STX4 expression is an independent risk factor for KIRC. qRT-PCR analysis showed that STX4 was significantly elevated in 10 paired of KIRC samples compared to normal samples. Functional enrichment analysis indicated that endo/exocytosis, autophagy, mTOR signaling pathway, and NOD-like receptor signaling pathway were enriched. Conclusions In summary, STX4 is constantly up-expressed in KIRC tissues, associated with a poor prognosis. We suggest that it can be an effective biomarker for the prognosis of KIRC and may be a novel therapeutic target in KIRC.

Abstract Background Lumbar spinal stenosis (LSS) is a common degenerative condition associated with old age. Its incidence continues to increase with the rapidly aging population in China. Treatment for LSS usually begins with conservative treatments, as some patients refuse surgical procedures or have surgery contraindications. Caudal epidural steroid injections (CESIs) and selective nerve root blocks (SNRBs) are two commonly used conservative treatments for LSS, which have proven to be effective at relieving LSS symptoms in many studies. However, there are no randomized controlled trials comparing these two procedures. We planned the first study to assess which one of these two procedures is more effective in treating LSS. We will compare the efficacy of these two treatment methods in terms of duration of symptom relief and recurrence rate. We hope our findings will help clinicians choose an optimal treatment for LSS patients. Methods/design We plan to conduct a 1-year randomized controlled trial that will include a total of 76 subjects. They will be randomly divided into two groups: group A (patients will receive CESIs) and group B (patients will receive SNRBs). Two days before the procedure, we will assess these patients using the Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) pain scale, Oswestry Disability Index (ODI), and numeric rating scale (NRS) for pain. One day, 2 weeks, 3 months, 6 months, and 1 year after the procedure, we will assess the condition of these patients again with the NRS and ODI. Discussion We hope our findings will lay the foundation for the design of further comprehensive studies and help clinicians make a choice between CESIs and SNRBs for LSS patients. Trial registration Chinese Clinical Trial Registry ChiCTR1900028038 . Registered on 8 December 2019

Recently, many spectral-special classification models have emerged one after another in the remote sensing community. These models aim to introduce the spatial information of the pixel to improve the accuracy of the class attribute of the pixel. However, for the spectral-spatial classification algorithms, not all pixels need to introduce the corresponding spatial information since the use of a large amount of spatial information has a costly time. To solve this problem, this paper proposes a robust dual-stage spatial embedding (RDSSE) model for spectral-spatial classification of hyperspectral image, which is composed of the following several main steps: First, an over-segmentation algorithm is employed to cluster original hyperspectral image into many superpixel blocks with shape adaptive characteristics. Then, we design a $k$ -peak criterion to fuse the spectral feature of pixels within and between superpixels. Next, a low time-consumption spectral classifier is introduced to conduct primary classification for a testing pixel to achieve the corresponding probability distribution. Specifically, the difference between the probability of the largest class and that of the second-largest class is served as class confidence. Finally, the predicted label of the low-confidence testing pixels is reclassified based on a high-accuracy spectral-spatial classification method. Experimental results on several real images illustrated that the proposed RDSSE method can obtain superior performance with respect to several competitive methods.

Excessive recoil severely restricts the loading of high-power traditional guns on modern vehicles. To reduce the recoil without breaking the continuous firing mode and reducing the projectile velocity, a recoil reduction method that controls the lateral ejecting of propellant gas by a piston was proposed. The recoil reduction device is symmetric about the barrel axis. First, a one-dimensional two-phase flow model of interior ballistic during the gun firing cycle was established. Next, the MacCormack scheme was used to simulate, and the piston motion was gained. Then the propagation of the rarefaction wave in the barrel was presented. Finally, the propulsion difference between the piston-controlled gun and the traditional gun was discussed. The results showed that the recoil momentum was reduced by 31.80%, and the muzzle velocity was decreased by just 1.30% under the reasonable matching of structural parameters.

From April to November 2016, two outbreaks of epidemic keratoconjunctivitis (EKC) occurred successively at primary and middle schools in the Tibet Autonomous Region of China, and a total of 197 clinically diagnosed cases were reported. Real-time PCR analyses confirmed that human adenovirus (HAdV) infection was related to these outbreaks. Further studies involving sequence determination and phylogenetic analysis based on the penton base, hexon, and fiber genes indicated that human adenovirus type 8 (HAdV-8), belonging to species D, was responsible for the outbreaks. This is the first report of a HAdV-8 associated EKC outbreak in mainland of China, and the results of this study are expected to provide support for future research into HAdV-8 in China.

Phytoremediation is a promising means of ameliorating heavy metal pollution through the use of transgenic plants as artificial hyperaccumulators. A novel Streptococcus thermophilus γ-glutamylcysteine synthetase-glutathione synthetase (StGCS-GS) that synthesizes glutathione (GSH) with limited feedback inhibition was overexpressed in sugar beet (Beta vulgaris L.), yielding three transgenic lines (s2, s4 and s5) with enhanced tolerance to different concentrations of cadmium, zinc and copper, as indicated by their increased biomass, root length and relative growth compared with wild-type plants. Transgenic sugar beets accumulated more Cd, Zn and Cu ions in shoots than wild-type, as well as higher GSH and phytochelatin (PC) levels under different heavy metal stresses. This enhanced heavy metal tolerance and increased accumulation were likely due to the increased expression of StGCS-GS and consequent overproduction of both GSH and PC. Furthermore, when multiple heavy metal ions were present at the same time, transgenic sugar beets overexpressing StGCS-GS resisted two or three of the metal combinations (50 μM Cd-Zn, Cd-Cu, Zn-Cu and Cd-Zn-Cu), with greater absorption in shoots. Additionally, there was no obvious competition between metals. Overall, the results demonstrate the explicit role of StGCS-GS in enhancing Cd, Zn and Cu tolerance and accumulation in transgenic sugar beet, which may represent a highly promising new tool for phytoremediation.

Significant computation challenges are emerging as agent-based modeling becomes more complicated and dynamically data-driven. In this context, parallel simulation is an attractive solution when dealing with massive data and computation requirements. Nearly all the available distributed simulation systems, however, do not support geospatial phenomena modeling, dynamic data injection, and real-time visualization. To tackle these problems, we propose a distributed dynamic-data driven simulation and analysis system (4D-SAS) specifically for massive spatial agent-based modeling to support real-time representation and analysis of geospatial phenomena. To accomplish large-scale geospatial problem-solving, the 4D-SAS system was spatially enabled to support geospatial model development and employs high-performance computing to improve simulation performance. It can automatically decompose simulation tasks and distribute them among computing nodes following two common schemes: order division or spatial decomposition. Moreover, it provides streaming channels and a storage database to incorporate dynamic data into simulation models; updating agent context in real-time. A new online visualization module was developed based on a GIS mapping library, SharpMap, for an animated display of model execution to help clients understand the model outputs efficiently. To evaluate the system’s efficiency and scalability, two different spatially explicitly agent-based models, an en-route choice model, and a forest fire propagation model, were created on 4D-SAS. Simulation results illustrate that 4D-SAS provides an efficient platform for dynamic data-driven geospatial modeling, e.g., both discrete multi-agent simulation and grid-based cellular automata, demonstrating efficient support for massive parallel simulation. The parallel efficiency of the two models is above 0.7 and remains nearly stable in our experiments.

Objective: To confirm the anti-NPC effect of sanguinarine (SA) through a series of wet experiments., Methods: NPC cell viability was determined by proliferation experiment. Cell clone formation experiment, cell scratch test, transwell migration and invasion experiment and flow cytometry-based cell apoptosis assay were further performed. In addition, Western blotting was performed to investigate the cell signaling pathway. All the relevant experimental data were statistically processed using SPSS 16.0 software., Results: The results showed that sanguinarine represented a time and dose dependent inhibition effects on NPC cell proliferation including the low differentiated CNE2 cells and high metastatic 5-8F cells, along with the cell cloning ability reduction. In addition, sanguinarine has a certain inhibitory effect on the invasion and migration of NPC cells. Mechanistically, sanguinarine displayed the anti-NPC effects mainly involved into the suppression of mTOR signaling and cell apoptosis, which is closely associated with the tumor growth and metastatic malignancy., Conclusions: Collectively, we discover that sanguinarine is a new high-efficiency anti-NPC monomer of Chinese medicine, with a value for the follow-up pre-clinical research.