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In this paper we introduce CDL, a software library designed for the analysis of permutations and linear orders subject to various structural restrictions. Prominent examples of these restrictions include pattern avoidance, a topic of interest in both computer science and combinatorics, and never conditions, utilized in social choice and voting theory. CDL offers a range of fundamental functionalities, including identifying the permutations that meet specific restrictions and determining the isomorphism of such sets. To facilitate the exploration of large permutation sets or domains, CDL incorporates multiple search strategies and heuristics.

Abstract In this work, we complete our CT18qed study with the neutron’s photon parton distribution function (PDF), which is essential for the nucleus scattering phenomenology. Two methods, CT18lux and CT18qed, based on the LUXqed formalism and the DGLAP evolution, respectively, to determine the neutron’s photon PDF have been presented. Various low-Q 2 non-perturbative variations have been carefully examined, which are treated as additional uncertainties on top of those induced by quark and gluon PDFs. The impacts of the momentum sum rule as well as isospin symmetry violation have been explored and turned out to be negligible. A detailed comparison with other neutron’s photon PDF sets has been performed, which shows a great improvement in the precision and a reasonable uncertainty estimation. Finally, two phenomenological implications are demonstrated with photon-initiated processes: neutrino-nucleus W-boson production, which is important for the near-future TeV–PeV neutrino observations, and the axion-like particle production at a high-energy muon beam-dump experiment.

Lithium‐excess cation‐disordered rocksalt materials are a promising class of transition metal‐based cathodes that exhibit high specific capacity and energy density. The exceptional performance is achieved through participation of anionic redox in addition to cationic redox reactions in the electrochemistry. However, anionic redox reactions accompanied by oxygen evolution, accelerated electrolyte breakdown, and structural evolution lead to voltage hysteresis and low initial Coulombic efficiency. Herein, an Al2O3 layer with varying thickness has been coated onto a high‐entropy disordered rocksalt oxyfluoride cathode through atomic layer deposition to enhance battery performance. The results indicate that the utilization of a uniform Al2O3 coating improves the capacity retention and rate capability of the cathode, with the performance being strongly dependent on the layer thickness. Further investigation into cathode–electrolyte interfacial reactions reveals that the thin protecting Al2O3 coating can reduce the decomposition of electrolyte on the cathode surface but cannot prevent bulk phase degradation during prolonged cycling. These findings highlight the need for optimized coating design on the disordered rocksalt cathode to improve battery performance.

The extraction of buildings from synthetic aperture radar (SAR) images poses a challenging task in the realm of remote sensing (RS). In recent years, convolutional neural networks (CNNs) have rapidly advanced and found application in the field of RS. Researchers have investigated the potential of CNNs for the semantic segmentation of SAR images, bringing excellent improvements. However, the semantic segmentation of buildings in SAR images still encounters challenges due to the high similarity between features of ground objects and buildings in SAR images, as well as the variability in building structures. In this article, we propose the local–global multiscale fusion network (LGMFNet), based on a dual encoder–decoder structure, for the semantic segmentation of buildings in SAR images. The proposed LGMFNet introduces an auxiliary encoder with a transformer structure to address the limitation of using the main encoder with a CNN structure for global modeling. To embed global dependencies hierarchically into the CNN, we designed the global–local semantic aggregation module (GLSM). The GLSM serves as a bridge between the dual encoders to achieve semantic guidance and coupling from the local to the global level. Furthermore, to bridge the semantic gap between different scales, we designed the multiscale feature fusion network (MSFN) as the decoder. MSFN achieves the interactive fusion of semantic information between various scales by constructing the multiscale feature fusion module. Experimental results demonstrate that the proposed LGMFNet achieves the mIoU of 91.17% on the BIGSARDATA 2023 AISAR competition dataset, outperforming the second-best method by a margin of 0.78%. This evidences the superiority of LGMFNet in comparison to other state-of-the-art methods.

Abstract Tumor immunotherapy, which targets immune checkpoints, presents a promising strategy for the treatment of various cancer types. However, current clinical data indicate challenges in its application to solid tumors. Recent studies have revealed a significant correlation between the degree of immune response in immunotherapy and the tumor microenvironment, particularly with regard to tumor-infiltrating immune cells. Among these immune cells, macrophages, a critical component, are playing an increasingly vital role in tumor immunotherapy. This review focuses on elucidating the role of macrophages within solid tumors and provides an overview of the progress in immunotherapy approaches centered around modulating macrophage responses through various immune factors. Video Abstract

Objectives To investigate the efficacy, safety, pharmacokinetics and pharmacodynamics of nipocalimab in participants with moderate to severe active rheumatoid arthritis (RA) and inadequate response or intolerance to ≥1 antitumour necrosis factor agent.Methods In this phase 2a study, participants with RA seropositive for anticitrullinated protein antibodies (ACPA) or rheumatoid factors were randomised 3:2 to nipocalimab (15 mg/kg intravenously every 2 weeks) or placebo from Weeks 0 to 10. Efficacy endpoints (primary endpoint: change from baseline in Disease Activity Score 28 using C reactive protein (DAS28-CRP) at Week 12) and patient-reported outcomes (PROs) were assessed through Week 12. Safety, pharmacokinetics and pharmacodynamics were assessed through Week 18.Results 53 participants were enrolled (nipocalimab/placebo, n=33/20). Although the primary endpoint did not reach statistical significance for nipocalimab versus placebo, a numerically higher change from baseline in DAS28-CRP at Week 12 was observed (least squares mean (95% CI): –1.03 (–1.66 to –0.40) vs –0.58 (–1.24 to 0.07)), with numerically higher improvements in all secondary efficacy outcomes and PROs. Serious adverse events were reported in three participants (burn infection, infusion-related reaction and deep vein thrombosis). Nipocalimab significantly and reversibly reduced serum immunoglobulin G, ACPA and circulating immune complex levels but not serum inflammatory markers, including CRP. ACPA reduction was associated with DAS28-CRP remission and 50% response rate in American College of Rheumatology (ACR) criteria; participants with a higher baseline ACPA had greater clinical improvement.Conclusions Despite not achieving statistical significance in the primary endpoint, nipocalimab showed consistent, numerical efficacy benefits in participants with moderate to severe active RA, with greater benefit observed for participants with a higher baseline ACPA.Trial registration number NCT04991753.

Abstract Psoriasis vulgaris is the most common form of the four clinical types. However, early diagnosis of psoriasis vulgaris is difficult due to the lack of effective biomarkers. The aim of this study was to screen potential biomarkers for the diagnosis of psoriasis. In our study, we downloaded the original data from GSE30999 and GSE41664, and the autophagy-related genes list from human autophagy database to identify differentially expressed autophagy-related genes (DERAGs) by R software. Then Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for DERAGs. DERAGs were validated by the other four databases (GSE13355, GSE14905, GSE6710, and GSE55201) to screen biomarkers with high diagnostic value for the early diagnosis of psoriasis vulgaris. Finally, DERAGs were verified in our clinical blood samples by ELISA. A total of 12 DERAGs were identified between 123 paired non-lesional and lesional skin samples from patients with psoriasis vulgaris. GO and KEGG enrichment analysis indicated the TORC2 complex was more enriched and the NOD-like receptor signaling pathway was mostly enriched. Three autophagy-related genes (BIRC5, NAMPT and BCL2) were identified through bioinformatics analysis and verified by ELISA in clinical blood samples. And these genes showed high diagnostic value for the early diagnosis of psoriasis vulgaris. We identified three autophagy-related genes (BIRC5, NAMPT and BCL2) with high diagnostic value for the early diagnosis of psoriasis vulgaris through bioinformatics analysis and clinical samples. Therefore, we proposed that BIRC5, NAMPT and BCL2 may be as potential biomarkers for the early diagnosis of psoriasis vulgaris. In addition, BIRC5, NAMPT and BCL2 may affect the development of psoriasis by regulating autophagy.

Abstract In this work, we present UV completions of the recently proposed number-changing Co-SIMP freeze-out mechanism. In contrast to the standard cannibalistic-type dark matter picture that occurs entirely in the dark sector, the 3 → 2 process setting the relic abundance in this case requires one Standard Model particle in the initial and final states. This prevents the dark sector from overheating and leads to rich experimental signatures. We generate the Co-SIMP interaction with a dark sector consisting of two scalars, with the mediator coupling to either nucleons or electrons. In either case, the dark matter candidate is naturally light : nucleophilic interactions favor the sub-GeV mass range and leptophilic interactions favor the sub-MeV mass range. Viable thermal models in these lighter mass regimes are particularly intriguing to study at this time, as new developments in low-threshold detector technologies will begin probing this region of parameter space. While particles in the sub-MeV regime can potentially impact light element formation and CMB decoupling, we show that a late-time phase transition opens up large fractions of parameter space. These thermal light dark matter models can instead be tested with dedicated experiments. We discuss the viable parameter space in each scenario in light of the current sensitivity of various experimental probes and projected future reach.

Traditional Chinese medicine (TCM) has been considered, for many years, an important source of medicine to treat different diseases. As a type of TCM, Illicium simonsii Maxim (ISM) is used as an anti-inflammatory, anti-bacterial, and anti-virus. Besides, ISM is also used in the treatment of cancer. In order to evaluate the anti-hepatocellular carcinoma (HCC) activity, petroleum ether extract was prepared from part of the fruit of ISM. First, the compounds of the petroleum ether fraction of Illicium simonsii Maxim (PEIM) were identified using LC-MS/MS analysis. Next, the cell viability and morphological changes were evaluated by MTT assay and Hoechst staining. In addition, the effect of PEIM on the levels of inflammatory factors (TNF-α, IL-1β, and IL-6) was determined using the ELISA kit. Furthermore, apoptosis was evaluated by flow cytometry, and gene expression and the regulation of signaling pathways were investigated, respectively, by real-time fluorescence quantitative PCR (RT-qPCR) and western blot. Results showed that a total of 64 compounds were identified in the PEIM. Additionally, the PEIM had anti-HCC activity against HepG2 cells, in which the half maximal inhibitory concentration (IC50) was 55.03 μg·mL−1. As well, the PEIM was able to modulate the expression of TNF-α, IL-1β, and IL-6, while we also found that it induced HepG2 cell apoptosis through the activation of P53 mRNA and caspase-3 mRNA. Finally, the PEIM possibly downregulated the expression of TLR4, MyD88, p-NF-κBp65, TNF-α, IL-1β, INOS, IL-6, JAK2, STAT3, CyclinD1, CDK4, MDM2, and Bcl-2, and upregulated the expression of P53, P21, Bax, Cytochrome-C, Caspase-9, and Caspase-3 in HepG2 cells. These findings may confirm that the PEIM has possible anti-HCC effects. However, additional studies are required to fully understand the mechanisms of action of the PEIM and the signaling pathways involved in its effects. Moreover, the anti-HCC activity of the PEIM should be studied in vivo, and signaling pathways involved in its effects should be explored to develop the anti-HCC drug.

CD47 and its receptor signal regulatory protein α (SIRPα) act as a dominant antiphagocytic, “don’t eat me” signal. Recent studies reveal CD24 as a novel target for cancer immunotherapy by macrophages in ovarian cancer and breast cancer. However, whether simultaneous blockade of CD47 and CD24 by a bispecific antibody may result in a potential synergy is still unclear. In the present study, we for the first time designed and developed a bispecific antibody fusion protein, PPAB001 for cotargeting CD47 and CD24. Data demonstrate that simultaneous blockade of CD47/SIRPα and CD24/Siglec-10 signaling by PPAB001 potently promoted macrophage phagocytosis of tumor cells. Compared to single CD47 or CD24 targeting agents, PPAB001 was more effective in inhibiting tumor growth in both mouse 4T-1 syngeneic and human SK-OV-3 xenogeneic tumor models. Mechanistically, we found that PPAB001 therapy markedly increased the proportion of tumor-infiltrating macrophages and upregulated interleukin-6 and tumor necrosis factor-α levels that were representative macrophage inflammatory cytokines. Notably, an increased ratio of M1/M2 in tumor-infiltrating macrophages in the mice treated with PPAB001 suggested that the dual blockade may promote the transition of macrophages from M2 to M1. Taken together, our data supported the development of PPAB001 as a novel immunotherapeutic in the treatment of CD47 and CD24 double-positive cancers.

Abstract Accurate and efficient extraction of water body information from remote sensing images is of great help to monitor water resources at the macro level, natural disaster prediction, and water pollution detection and prevention. Although many large models have achieved extremely high accuracy in remote sensing image water segmentation tasks, lightweight models are still a non‐negligible choice for many application scenarios because of the limitation of computing and storage resources. Here, WaterSegformer is described, an efficient and powerful lightweight water body segmentation model based on Segformer‐b0. The Deepmask module is designed to make the model pay more attention to the details in the image and use Lovász loss to improve IoU. In addition, DeepLabv3+ is used as the teacher model to guide the training of the model in the way of relational knowledge distillation. WaterSegformer realizes 95.06% mIoU on the test set with only 6.38 G and 3.72 M of FLOPs and parameters, respectively. Experimental results show that WaterSegformer achieves an excellent balance between accuracy, computational complexity and model size, which is hardware‐friendly, easy to deploy and enables real‐time segmentation. This method provides a new idea for water body information extraction from remote sensing images in practical applications.

This article presents the data utilized in a study focused on identifying an optimal bus dispatching strategy in light of epidemic impacts. The study specifically examines the Xi'an Xiaozhai central business district (CBD) street network, which consists of 33 major signalized intersections and 112 bus stops associated with 12 bus routes. The dataset includes details of intersection and bus stop geospatial data, street segment and intersection design, intersection signal timing plans, bus route operational properties such as dispatching frequencies, fleet sizes, loading bay capacities, and bus-specific parameters. It also encompasses data on passenger boarding and alighting counts, as well as travelers’ origin and destination (O-D) locations, routes, and departure times during three time periods: 10:00-11:00 PM, 1:00-2:00 PM, and 7:00-8:00 PM on Monday, June 7, 2021. These times represent off-peak (10:00 PM–1:00 AM the next day), adjacent-to-peak (9:00–11:00 AM, 1:00–4:00 PM, and 8:00–10:00 PM), and peak (7:00–9:00 AM, 11:00 AM–1:00 PM, and 4:00–8:00 PM) periods, respectively. Data collection involves searching government and organizational records, utilizing Alibaba Cloud's Amap platform, conducting onsite measurements, and performing a field survey. The dataset is a valuable resource for studying the integrated operations of various urban mass transit services, including buses, bus rapid transit (BRT), and fixed guideway transit, under both normal and epidemic-affected travel conditions. Additionally, it can be used to investigate multimodal integrated urban passenger services offered by automobiles, transit, ridesharing, and active transportation modes.

ObjectiveDiabetic kidney disease (DKD) has been reported as a main microvascular complication of diabetes mellitus. Although renal biopsy is capable of distinguishing DKD from Non Diabetic kidney disease(NDKD), no gold standard has been validated to assess the development of DKD.This study aimed to build an auxiliary diagnosis model for type 2 Diabetic kidney disease (T2DKD) based on machine learning algorithms.MethodsClinical data on 3624 individuals with type 2 diabetes (T2DM) was gathered from January 1, 2019 to December 31, 2019 using a multi-center retrospective database. The data fell into a training set and a validation set at random at a ratio of 8:2. To identify critical clinical variables, the absolute shrinkage and selection operator with the lowest number was employed. Fifteen machine learning models were built to support the diagnosis of T2DKD, and the optimal model was selected in accordance with the area under the receiver operating characteristic curve (AUC) and accuracy. The model was improved with the use of Bayesian Optimization methods. The Shapley Additive explanations (SHAP) approach was used to illustrate prediction findings.ResultsDKD was diagnosed in 1856 (51.2 percent) of the 3624 individuals within the final cohort. As revealed by the SHAP findings, the Categorical Boosting (CatBoost) model achieved the optimal performance 1in the prediction of the risk of T2DKD, with an AUC of 0.86 based on the top 38 characteristics. The SHAP findings suggested that a simplified CatBoost model with an AUC of 0.84 was built in accordance with the top 12 characteristics. The more basic model features consisted of systolic blood pressure (SBP), creatinine (CREA), length of stay (LOS), thrombin time (TT), Age, prothrombin time (PT), platelet large cell ratio (P-LCR), albumin (ALB), glucose (GLU), fibrinogen (FIB-C), red blood cell distribution width-standard deviation (RDW-SD), as well as hemoglobin A1C(HbA1C).ConclusionA machine learning-based model for the prediction of the risk of developing T2DKD was built, and its effectiveness was verified. The CatBoost model can contribute to the diagnosis of T2DKD. Clinicians could gain more insights into the outcomes if the ML model is made interpretable.

Abstract Reported in 2004, carbon dots (CDs) have been widely used in various fields due to their excellent optical properties. However, the mechanism of their fluorescence modulation is still a controversial issue, which also seriously affects the further development of carbon dots. In this paper, m‐hydroxybenzaldehyde is used as a raw material to obtain multicolor luminescent CDs by pyrolysis under different reaction conditions, thereby revealing the forbidden band tuning and formation mechanism of CDs. Different acid–base conditions lead to different reaction paths of the precursors, forming molecular fluorophores with different conjugated structures, which aggregate to eventually form CDs and further enhance the photoluminescence of the system by inhibiting the movement of the fluorescent centers.

The Transformer has achieved great success in many computer vision tasks. With the in-depth exploration of it, researchers have found that Transformers can better obtain long-range features than convolutional neural networks (CNN). However, there will be a deterioration of local feature details when the Transformer extracts local features. Although CNN is adept at capturing the local feature details, it cannot easily obtain the global representation of features. In order to solve the above problems effectively, this paper proposes a hybrid model consisting of CNN and Transformer inspired by Visual Attention Net (VAN) and CoAtNet. This model optimizes its shortcomings in the difficulty of capturing the global representation of features by introducing Large Kernel Attention (LKA) in CNN while using the Transformer blocks with relative position self-attention variant to alleviate the problem of detail deterioration in local features of the Transformer. Our model effectively combines the advantages of the above two structures to obtain the details of local features more accurately and capture the relationship between features far apart more efficiently on a large receptive field. Our experiments show that in the image classification task without additional training data, the proposed model in this paper can achieve excellent results on the cifar10 dataset, the cifar100 dataset, and the birds400 dataset (a public dataset on the Kaggle platform) with fewer model parameters. Among them, SE_LKACAT achieved a Top-1 accuracy of 98.01% on the cifar10 dataset with only 7.5M parameters.

The use of floating-point numbers inevitably leads to inaccurate results and, in certain cases, significant program failures. Detecting floating-point errors is critical to ensuring that floating-point programs outputs are proper. However, due to the sparsity of floating-point errors, only a limited number of inputs can cause significant floating-point errors, and determining how to detect these inputs and to selecting the appropriate search technique is critical to detecting significant errors. This paper proposes characteristic particle swarm optimization (CPSO) algorithm based on particle swarm optimization (PSO) algorithm. The floating-point expression error detection tool PSOED is implemented, which can detect significant errors in floating-point arithmetic expressions and provide corresponding input. The method presented in this paper is based on two insights: (1) treating floating-point error detection as a search problem and selecting reliable heuristic search strategies to solve the problem; (2) fully utilizing the error distribution laws of expressions and the distribution characteristics of floating-point numbers to guide the search space generation and improve the search efficiency. This paper selects 28 expressions from the FPBench standard set as test cases, uses PSOED to detect the maximum error of the expressions, and compares them to the current dynamic error detection tools S3FP and Herbie. PSOED detects the maximum error 100% better than S3FP, 68% better than Herbie, and 14% equivalent to Herbie. The results of the experiments indicate that PSOED can detect significant floating-point expression errors.

With the popularization of autonomous vehicle (AV) technology, mixed traffic flows that consist of AVs and human-driven vehicles (HDVs) will appear in the real world. Although many studies of the features of mixed traffic flow have been carefully evaluated, few studies have focused on the effect of aggressive driving performance on mixed traffic flow. This study aims to develop an approach to evaluate the effects of aggressive driving on the stability and capacity performance under the conditions of AV and HDV mixed traffic flow. First, since a car-following model can describe the relationship between vehicles, we calibrate a car-following model for aggressive driving and nonaggressive driving behaviors based on real traffic data and previous research results. Then, in a mixed traffic flow environment, a basic linear stability formula and capacity calculation expression are developed that consider the effects of vehicle order on the capacity. Finally, because the proportion of aggressive driving and aggressive driving parameters may change, nine combinations of three aggressive driving proportions and three driving parameter cases are used for the sensitivity analysis. The results indicate that the effect of aggressive driving on mixed traffic flow is complex. When the proportion of aggressive driving is less than 35%, the increase in the proportion of aggressive driving increases the traffic capacity and reduces the unstable part. However, when the proportion of aggressive driving is greater than 35%, the increase in the proportion of aggressive driving increases the unstable part. When the penetration rate of AVs exceeds 0.490, mixed traffic flow remains stable at all aggressive driving proportions. In addition, the capacity of a mixed traffic flow may be improved as the penetration rate of AVs increases. To a certain extent, these conclusions provide a theoretical basis for formulating different management modes of AVs and HDVs.

Emerging evidence has shown that endoplasmic reticulum (ER) stress promotes sorafenib resistance in hepatocellular carcinoma (HCC). However, the underlying mechanisms are poorly understood. The purpose of this study was to explore the mechanism by which ER stress promotes sorafenib resistance in HCC. We found that pyruvate kinase isoform M2 (PKM2) was highly expressed in human HCC tissues and co-related with worse clinicopathologic features and overall survival. Activation of ER stress positively correlated with PKM2 expression both in HCC tissue samples and tunicamycin (TM)-induced HCC cell lines. PKM2 knockdown increased sorafenib-induced apoptosis and decreased the ability of colony formation, while upregulation of PKM2 reverses this phenomenon. Furthermore, high-throughput sequencing identified that activation of ER stress significantly downregulated the expression of miR-188-5p in HCC cells. According to bioinformatics analysis and dual-luciferase assays, we further confirmed that hnRNPA2B1 is the target gene of miR-188-5p. Downregulating the expression of hnRNPA2B1 with siRNA could decrease the expression of PKM2 and enhance sorafenib-induced apoptosis in HepG2 cells. Our study demonstrated that ER stress could promote sorafenib resistance through upregulating PKM2 via miR-188-5p/hnRNPA2B1. Therefore, targeting the miR-188-5p/hnRNPA2B1/PKM2 pathway and ER stress may prove instrumental in overcoming sorafenib resistance in HCC treatment.

In order to improve the production quality and qualification rate of chips, X-ray nondestructive imaging technology has been widely used in the detection of chip defects, which represents an important part of the quality inspection of products after packaging. However, the current traditional defect detection algorithm cannot meet the demands of high accuracy, fast speed, and real-time chip defect detection in industrial production. Therefore, this paper proposes a new multi-scale feature fusion module (ATSPPF) based on convolutional neural networks, which can more fully extract semantic information at different scales. In addition, based on this module, we design a deep learning model (ATNet) for detecting lead defects in chips. The experimental results show that at 8.2 giga floating point operations (GFLOPs) and 146 frames per second (FPS), mAP0.5 and mAP0.5–0.95 can achieve an average accuracy of 99.4% and 69.3%, respectively, while the detection speed is faster than the baseline yolov5s by nearly 50%.

Abstract Background The interleukin-23p19-subunit inhibitor guselkumab effectively treats signs and symptoms of psoriatic arthritis (PsA). We evaluated the effect of guselkumab on fatigue. Methods Across two phase 3 trials of guselkumab (DISCOVER-1, DISCOVER-2), patients with active PsA despite standard therapy were randomized to subcutaneous injections of guselkumab 100 mg every 4 weeks (Q4W, N = 373); guselkumab 100 mg at week 0, week 4, and then Q8W (N = 375); or placebo (N = 372) through week 24, after which patients in the placebo group crossed over to guselkumab Q4W. Fatigue was measured as a secondary endpoint using the Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue instrument (range 0–52, higher scores indicate less fatigue). Least-squares mean changes in FACIT-Fatigue scores were compared between treatments using a mixed-effect model for repeated measures. Mediation analysis was used to adjust for indirect effects on fatigue deriving from improvement in other outcomes, including ≥20% improvement in American College of Rheumatology criteria (ACR20; prespecified), minimal disease activity (MDA; post hoc), or C-reactive protein (CRP; post hoc). Results Baseline mean (SD) FACIT-Fatigue scores in DISCOVER-1 (N = 381) and DISCOVER-2 (N = 739), ranging from 29.1 (9.5) to 31.4 (10.1), indicated substantial levels of fatigue relative to the United States general population (43.6 [9.4]). Across studies, mean improvements, and proportions of patients with ≥4-point improvements, in FACIT-Fatigue scores at week 24 with guselkumab Q4W and Q8W (5.6–7.6 and 54–63%, respectively) were larger vs placebo (2.2–3.6 and 35–46%). Improvement in FACIT-Fatigue scores with guselkumab was sustained from week 24 to week 52, with moderate-to-large effect sizes (Cohen’s d = 0.52–0.81 at week 24; 0.66–0.91 at week 52). Mediation analyses demonstrated that substantial proportions of the effects of guselkumab vs placebo on fatigue were direct effect, after adjusting for achievement of ACR20 (Q4W 69–70%, Q8W 12–36% direct effect) or MDA (72–92% across dosing regimens) response or for change in serum CRP concentrations (82–88% across dosing regimens). Conclusions In patients with active PsA, guselkumab 100 mg Q4W or Q8W led to clinically meaningful and sustained improvements in fatigue through 1 year. A substantial portion of the improvement in FACIT-Fatigue scores induced by guselkumab was independent of effects on the achievement of other select outcomes. Trial registration Name of the registry: ClinicalTrials.gov Trial registrations: DISCOVER-1, NCT03162796; DISCOVER-2, NCT03158285 Date of registration: DISCOVER-1, May 22, 2017; DISCOVER-2, May 18, 2017 URLs of the trial registry record: DISCOVER-1, https://clinicaltrials.gov/ct2/show/NCT03162796?term=NCT03162796&draw=1&rank=1 DISCOVER-2, https://clinicaltrials.gov/ct2/show/NCT03158285?term=NCT03158285&draw=2&rank=1

BackgroundC-arm-guided percutaneous puncture balloon compression alone has risk factors of puncture failure, complications, and poor prognosis. Robot-assisted PBC can effectively increase the one-time puncture success rate and improve the safety of the procedure. However, evidence on the superiority of robot-assisted PBC over C-arm-guided PBC alone remains relatively limited.MethodsRetrospective analysis The clinical data of 60 patients with trigeminal neuralgia aged 60 years or older in the Department of Neurosurgery of the Fourth Hospital of Harbin Medical University from January 2021 to October 2021. There were 29 males and 31 females, and the patients’ ages ranged from 60 to 79 years, with an average of 71.63 ± 5.12 years. Two groups were divided according to the surgical method, the C-arm guidance-only group (30 cases, n = 30) and the robot-assisted group (30 cases, n = 30). The success rate of first puncture, total operation time, number of “pear-shaped” balloons, number of C-arm x-ray scans, and immediate postoperative relief rate were recorded in both groups, and follow-up was performed to evaluate the postoperative results and complications. The overall evaluation of postoperative results and complications was performed.ResultsIntraoperative balloon compression was successfully completed in all 60 patients, and the first puncture success rate was higher in the robot-assisted group than in the simple C-arm group, with a significant difference between the two groups (P 0.05). By the final follow-up, the mean VAS score of the robot-assisted group was lower than that of the simple C-arm group, and both were statistically significant (P

High-entropy oxides are an upcoming research topic due to their broad range of possible crystal structures and applications. In this work, we want to present the change in the catalytic properties when using different elements to create a high-entropy spinel. Therefore, we used the nebulized-spray pyrolysis to synthesize the high-entropy spinel (Mn0.2Fe0.2Ni0.2Mg0.2Zn0.2)3O4 and later on exchanged the Mg or the Zn with elements with multiple possible oxidation states, in our example each with Cr or Co. The phase purity, morphology, microstructure and homogeneity were investigated by XRD, SEM and STEM-EDX. Their electrocatalytic performance and stability was measured via oxygen evolution reaction and cyclic voltammetry and compared to IrO2, used as reference. The best performance of the synthesized materials was achieved by (Mn0.2Fe0.2Ni0.2Mg0.2Cr0.2)3O4.

The dual tyrosine kinase (EGFR/HER2) inhibitor lapatinib is currently used to clinically treat HER2-positive breast cancer. However, a majority of patients do not respond to lapatinib therapy within 6 months. Therefore, potentiating the anti-tumor effect of lapatinib by combination treatment has a great potential to overcome the obstacle. Herein, we aim to investigate the anti-tumor activity of lapatinib in combination with brusatol and explore the potential mechanism involved in the combinatorial treatment. Our findings revealed that the Nrf2 inhibitor brusatol potently enhanced the anti-tumor effect of lapatinib against SK-BR-3, SK-OV-3 and AU565 cancer cells in a synergistic manner. Furthermore, we found that lapatinib plus brusatol more effectively decreased Nrf2 level and induced ROS generation in both SK-BR-3 and SK-OV-3 cells. Moreover, we also observed a significant reduction on the phosphorylation of HER2, EGFR, AKT and ERK1/2 in SK-BR-3 and SK-OV-3 cells when treated with lapatinib plus brusatol compared to either agent alone. More importantly, brusatol significantly augmented the anti-tumor effects of lapatinib in the SK-OV-3 xenograft model. In summary, these data provide a potential rationale for the combination of brusatol and lapatinib on the treatment of HER2-positive cancers.

BackgroundShort-term readmission for pediatric pulmonary hypertension (PH) is associated with a substantial social and personal burden. However, tools to predict individualized readmission risk are lacking. This study aimed to develop machine learning models to predict 30-day unplanned readmission in children with PH.MethodsThis study collected data on pediatric inpatients with PH from the Chongqing Medical University Medical Data Platform from January 2012 to January 2019. Key clinical variables were selected by the least absolute shrinkage and the selection operator. Prediction models were selected from 15 machine learning algorithms with excellent performance, which was evaluated by area under the operating characteristic curve (AUC). The outcome of the predictive model was interpreted by SHapley Additive exPlanations (SHAP).ResultsA total of 5,913 pediatric patients with PH were included in the final cohort. The CatBoost model was selected as the predictive model with the greatest AUC for 0.81 (95% CI: 0.77–0.86), high accuracy for 0.74 (95% CI: 0.72–0.76), sensitivity 0.78 (95% CI: 0.69–0.87), and specificity 0.74 (95% CI: 0.72–0.76). Age, length of stay (LOS), congenital heart surgery, and nonmedical order discharge showed the greatest impact on 30-day readmission in pediatric PH, according to SHAP results.ConclusionsThis study developed a CatBoost model to predict the risk of unplanned 30-day readmission in pediatric patients with PH, which showed more significant performance compared with traditional logistic regression. We found that age, LOS, congenital heart surgery, and nonmedical order discharge were important factors for 30-day readmission in pediatric PH.

Background: Breast cancer (BC) is the most common malignancy and the leading cause of mortality among women. Various diagnostic tools for early diagnosis and tumor progression detection have helped patients receive precise and timely treatment. This meta-analysis aims to evaluate the accuracy of abbreviated magnetic resonance imaging (ABB-MRI) data in the diagnosis of BC. Methods: The Preferred Reporting Items for Systematic Reviews and Comparative Meta-Analysis for Diagnostic Test Accuracy (PRISMA-DTA) guidelines were followed to perform the meta-analysis. Data from articles published in the last 5 years reporting ABB-MRI as a diagnostic tool were collected by searching the relevant databases using multiple subject keywords and free words. Meta-Disc 1.4 software was used to analyze the data and plot the relevant graphs. Results: We identified 1250 articles while searching the relevant electronic databases. After removing duplicate studies and data, the titles and abstracts of 1149 studies were reviewed. A total of 18 publications that satisfied the inclusion criteria were finally included in the meta-analysis. The calculated pooled specificity and sensitivity were 0.90 and 0.87, respectively. This study confirms the ABB-MRI protocol’s high diagnostic sensitivity and specificity in malignant breast cancer detection. Conclusions: Abbreviated MRI seems to function as a useful supplement because it is highly sensitive and specific, on par with the full MRI scan, as shown in multiple independent studies as well as this pooled analysis. These findings confirm the utility of ABB-MRI in the accurate detection of malignant BC lesions in high-risk women that cannot be detected by mammography or ultrasound.

Purpose: This study aimed to explore the role and molecular mechanism of brain and muscle ARNT-like protein 1 (BMAL1) in hepatocellular carcinoma (HCC), and the effect of melatonin on BMAL1 expression and apoptosis of HCC cells. Methods: We mainly used immunohistochemistry, western blot, cck-8 assays, flow cytometry, wound-healing assay, transwell assay, and RT-qPCR for this research. Results: The expression of BMAL1 protein was frequently up-regulated in the tissues and cell lines of HCC patients. Its high expression was significantly associated with tumor size, tumor differentiation degree, and shorter survival. In addition, cell functional experiments showed that BMAL1 could promote proliferation and migration, and inhibit apoptosis in HCC cell lines. Furthermore, the expression of BMAL1 was related to the endoplasmic reticulum stress (ERS) level. Knockdown of BMAL1 could inhibit the expression of ERS-related protein, while overexpression of BMAL1 led to the increase of ERS-related protein’s level. Low concentration of ERS led to the increase of BMAL1, and a certain degree of ERS in turn inhibited the expression of BMAL1. Melatonin promoted apoptosis of hepatoma cells by inhibiting the expression of BMAL1. Conclusion: BMAL1 plays a key role in HCC patients’ survival and tumor growth, which may be related to its interaction with ERS-related pathways. Melatonin can regulate ERS-related apoptosis resistance by inhibiting BMAL1 expression, promoting apoptosis of HCC cells.

BackgroundExisting studies have shown that sacubitril-valsartan ameliorated atrial remodeling in atrial fibrillation (AF) and favored maintenance of sinus rhythm in patients with AF and heart failure. However, the effect of sacubitril-valsartan in patients with persistent AF is yet unknown. We aimed to evaluate the effect of sacubitril-valsartan on restoration and maintenance of sinus rhythm in patients with persistent AF who underwent electrical cardioversion (ECV).MethodConsecutive patients with persistent AF who underwent ECV between 1 January 2016 and 30 September 2020 were investigated in this retrospective cohort study. All eligible patients were categorized into sacubitril-valsartan users and sacubitril-valsartan non-users based on whether they received treatment with sacubitril-valsartan or not. The endpoint was ineffictive ECV, defined as the composite of failure to terminate AF or any recurrence of AF during 30 days follow-up.ResultsA total of 76 patients were enrolled in this study, including 28 sacubitril-valsartan users and 48 non-users. Within a follow-up of 30 days after ECV, the endpoint had occurred in 7 (25%) of 28 sacubitril-valsartan users and 25 (52%) of 48 non-users. Significantly lower rate of ineffictive ECV in sacubitril-valsartan users compared with non-users was shown in Kaplan-Meier survival curves (P = 0.02; Log-rank test). Multivariate Cox regression analysis indicated that sacubitril-valsartan use (hazard ratio [HR], 0.35; 95% confidence interval [CI], 0.14–0.91), amiodarone use (HR, 0.32; 95% CI, 0.13–0.78), left atrial diameter ≤ 39 mm (HR, 0.21; 95% CI, 0.06–0.71) were independently associated with a decreased rate of ineffective electrical cardioversion.ConclusionUse of sacubitril-valsartan is associated with a significantly decreased risk of ineffective ECV compared with non-users in patients with persistent AF.

This study aims to explore factors affecting passenger car and truck driver injury severity in passenger car-truck crashes. Police-reported crash data from 2007 to 2017 in Canada are collected. Two-vehicle crashes involving one truck and one passenger car are extracted for modeling. Different injury severities are not equally represented. To address the data imbalance issue, this study applies four different data imbalance treatment approaches, including over-sampling, under-sampling, a hybrid method, and a cost-sensitive learning method. To test the performances of different classifiers, five classification models are used, including multinomial logistic regression, Naive Bayes, Classification and Regression Tree, support vector machine, and eXtreme Gradient Boosting (XGBoost). In both the passenger car driver and truck driver injury severity analysis, XGBoost combined with cost-sensitive learning generates the best results in terms of G-mean, area under the curve, and overall accuracy. Additionally, the Shapley Additive Explanations (SHAP) approach is adopted to interpret the result of the best-performing model. Most of the explanatory variables have similar effects on passenger car and truck driver fatality risks. Nevertheless, six variables exhibit opposite effects, including the age of the passenger car driver, crash hour, the passenger car age, road surface condition, weather condition and the truck age. Results of this study could provide some valuable insights for improving truck traffic safety. For instance, properly installing traffic control devices could be an effective way to reduce fatality risks in passenger car-truck crashes. Besides, passenger car drivers should be extremely cautious when driving between midnight to 6 am on truck corridors.

Dried blood spot (DBS) based PCR was considered an inexpensive and feasible method for detecting pathogens in the blood. The DBS carrier filter paper and PCR kits are crucial for accurate diagnosis. We evaluated 4 types of filter papers and 20 PCR kits for DBS samples. The PCR detecting Plasmodium results showed that the minimum detection limit of the 4 filter papers was 1 × 102 parasites/μL, and the positive rates of 20 PCR kits ranged from 0% to 100%. PCR results were satisfactory for detecting Plasmodium falciparum (P. falciparum) and Plasmodium. vivax (P. vivax) in archived DBS samples and Babesia gibsoni (B. gibsoni) in fresh pet DBS samples. Our results provided a useful reference for the detection of blood pathogens with DBS samples and direct PCR, especially for screening the cost-efficacy combination of filter paper and PCR kit in resource-limited areas.

In this study, fresh lotus leaves at two maturity stages were processed to tea products by different methods (white-tea process, green-tea process and black-tea process). The volatile compounds, phytochemical profiles and antioxidant activities of lotus-leaf tea were investigated. A total of 81 volatile components were identified with HS-GC-IMS. The mature lotus-leaf tea showed more volatile compounds than the tender lotus-leaf tea. The lotus leaf treated with the white-tea process had more aroma components than other processing methods. In addition, six types of phenolic compounds, including luteolin, catechin, quercetin, orientin, hyperoside and rutin were identified in the lotus-leaf tea. The mature leaves treated with the green-tea process had the highest levels of TPC (49.97 mg gallic acid/g tea) and TFC (73.43 mg rutin/g tea). The aqueous extract of lotus-leaf tea showed positive scavenging capacities of DPPH and ABTS radicals, and ferric ion reducing power, whereas tender lotus leaf treated with the green-tea process exhibited the strongest antioxidant activity. What is more, the antioxidant activities had a significant positive correlation with the levels of TPC and TFC in lotus-leaf tea. Our results provide a theoretical basis for the manufacture of lotus-leaf-tea products with desirable flavor and health benefits.

Abstract Background This study aimed to investigate the image quality and adverse events (AEs) of ethiodized poppyseed oil (EPO) compared with ioversol as contrast agents in hysterosalpingography (HSG). Methods Two hundred twenty-eight patients underwent HSG were consecutively recruited in this prospective cohort study, and were accordingly divided into EPO group (N = 165) and ioversol group (N = 63). The quality of image was assessed according to the European Guidelines on quality criteria for diagnostic radiographic images. AEs during, within 2 h and at 1-month post-HSG were recorded. Results EPO displayed elevated image quality compared with ioversol including the total image quality score (P 0.05). However, at 1-month post-HSG, the number of patients had unchanged and faded menstrual blood color decreased but the proportion of patients with deepened menstrual color increased in EPO group compared with ioversol group (P = 0.007). In addition, the number of patients had iodine residue in uterine cavity was elevated in EPO group compared with ioversol group (P

The centrifugal electrostatic blowing process proposed in this paper solves the difficult continuous and stable deposition problem in the traditional centrifugal electrostatic spinning process. By establishing a flight deposition model of the centrifugal electrostatic spraying process, CFD is used to simulate and analyze the electrohydrodynamic effect of centrifugal jets, and the driving mechanism is explored. Subsequently, MATLAB is used to obtain the optimal solution conditions, and finally, the establishment of a two-dimensional flight trajectory model is completed and experimentally verified. In addition, the deposition model of the jet is established to clarify the flight trajectory under the multi-field coupling, the stable draft area of the jet is found according to this, and the optimal drafting station is clarified. This research provides new ideas and references for the exploration of the deposition mechanism of the centrifugal electrostatic blowing and electrostatic spinning process.

Changes in decidual macrophage polarization affect local inflammatory microenvironment and lead to adverse pregnancy outcomes. However, the regulatory mechanism of macrophage polarization in preeclampsia (PE) remains unclear. In this study, we found that α7nAChR expression was significantly down-regulated in decidual macrophages in PE patients compared to normal pregnant women, accompanied by a reduced proportion of M2 phenotype and an increased proportion of M1 phenotype; these results suggested that the reduced α7nAChR activity might contribute to changes in the polarization of decidual macrophages. Then, we further investigated the regulatory role of α7nAChR activation by nicotine on decidual macrophage polarization and placental remodeling in the PE-like mouse model. The PE mice were obtained by i.p. injection of 10 µg/kg lipopolysaccharide (LPS) gestational day (GD) 13, and 40 µg/kg LPS daily until GD16. Subcutaneous injection of 1.0 mg/kg nicotine was administrated from GD14 to GD18. Nicotine treatment increased the decreased M2 phenotype and inhibited the increased M1 phenotype in decidua of pregnant mice induced by LPS. The levels of pro-inflammatory cytokines in decidua were higher but the levels of anti-inflammatory cytokines were lower in PE mice compared to the controls, nicotine reversed these changes. The level of choline acetyltransferase (CHAT) was reduced in the LPS-treated group, it was increased following nicotine treatment. Damage of spiral artery remodeling and down-regulation of markers related to trophoblast invasion in placentas were found in PE mice; nicotine improved these pathological structures of placentas. α-bungarotoxin (α-BGT) which is specific antagonist for α7nAChR could abolish the effects of nicotine on decidual macrophage polarization, trophoblast arrangement and vascular structure in placental tissue in PE mice. These results suggest that α7nAChR plays an important regulatory role in maternal-fetal inflammation and placental remodeling in preeclampsia and may provide a theoretical basis for the discovery of new strategies for preeclampsia.

Objective Evaluation of the efficacy and safety of guselkumab, a human monoclonal antibody targeting the interleukin-23p19 subunit, in patients with psoriatic arthritis (PsA) through 1 year.Methods Adults who met ClASsification criteria for Psoriatic ARthritis, with active disease (≥3 swollen and ≥3 tender joints; C reactive protein ≥0.3 mg/dL) despite standard treatment (31% previously received ≤2 tumour necrosis factor inhibitors (TNFi)), were randomised (1:1:1) to guselkumab 100 mg every 4 weeks (Q4W); guselkumab 100 mg at Week0, Week4, then Q8W; or placebo with cross-over to guselkumab 100 mg Q4W at Week24 (PBO→Q4W) through Week48. Clinical efficacy through Week52 (employing non-responder imputation) and adverse events (AEs) through Week60 were evaluated.Results Of 381 treated patients, 90% completed the study. Numerical increases in the proportions of patients achieving ≥20% improvement in ACR criteria (ACR20) were observed post-Week24, reaching 73% (94/128) and 60% (76/127) for Q4W-randomised and Q8W-randomised patients, respectively, by Week52. Proportions of patients achieving ACR50/ACR70/skin responses and minimal/very low disease activity were maintained, as were improvements in physical function and health-related quality of life, through Week52 in guselkumab-randomised patients. Response to guselkumab was maintained in both TNFi-naïve and TNFi-experienced patients. Serious AEs and serious infections occurred in similar proportions of guselkumab Q4W-randomised (3% and 0%) and Q8W-randomised (6% and 2%) patients through Week60, with no new safety concerns versus observations through Week24. No guselkumab-treated patient and two patients receiving placebo died; no study participant developed opportunistic infection or inflammatory bowel disease.Conclusion Guselkumab provided sustained improvement across multiple clinical manifestations of PsA, maintaining a favourable benefit-risk profile, through 1 year regardless of prior TNFi exposure.

We investigate the dynamic performance of traffic flow using a modified optimal velocity car-following model. In the car-following scenarios, the following vehicle must continuously adjust the following distance to the preceding vehicle in real time. A new optimal velocity function incorporating the desired safety distance instead of a preset constant is presented first to describe the abovementioned car-following behavior dynamically. The boundary conditions of the new optimal velocity function are theoretically analyzed. Subsequently, we propose an improved car-following model by combining the heterogeneity of driver’s sensitivity based on the new optimal velocity function and previous car-following model. The stability criterion of the improved model is obtained through the linear analysis method. Finally, numerical simulation is performed to explore the effect of the desired safety distance and the heterogeneity of driver’s sensitivity on the traffic flow. Results show that the proposed model has considerable effects on improving traffic stability and suppressing traffic congestion. Furthermore, the proposed model is compatible with the heterogeneity of driver’s sensitivity and can enhance the average velocity of traffic flow compared with the conventional model. In conclusion, the dynamic performance of traffic flow can be improved by considering the desired safety distance and the heterogeneity of driver’s sensitivity in the car-following model.

This paper is conducted to explore a new characterization method as a supplement to the traditional roughness characterization. The main research includes the extraction and evaluation of damage features of ceramic surface morphology by applying wavelet methods, the extraction of damage features in surface contours by using wavelet analysis, and the quantitative evaluation of damage degree by using damage rate and damage mean spacing. By comparing various fractal dimension calculation methods, a fractal dimension method suitable for calculating the ceramic surface was selected, and the fractal method was used to describe the ceramic surface topography as a whole. By comparing different methods of calculating the fractal dimension and further verifying them with the measured three-dimensional morphology, it is found that the vibrational method is more suitable for calculating the fractal dimension of ceramic surface, and its calculation accuracy is investigated, and the results show that the method is a reliable one. Based on the fractal theory, a mathematical model of surface wear and surface sealing was established. Further study of the model shows that the surface with a large fractal dimension has a good sealing effect; the surface corresponding to the best fractal dimension is the most resistant to wear. The fractal method can characterize the complexity of the surface profile as a whole. The wavelet method can describe the ceramic surface profile from a local perspective, and the combination of the two methods can characterize the ceramic surface well. Finally, the experimental device of the ceramic surface defect detection system is constructed, and the joint debugging of hardware and software is completed. Under different light source intensities, ceramic image samples are collected, and the accuracy detection experiments of sample defective edges are conducted, and the results show that the light source has a small impact on the accuracy of ceramic defective edge detection. The results show that the light source has more influence on the accuracy of scratch detection. The results show that the system constructed in this thesis has good applicability for different ceramic sample detection.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death worldwide. Endoplasmic reticulum stress (ERS) is generally activated in HCC and is important for the sensitivity of HCC to anticancer drugs. ERS-dependent autophagy is a crucial mechanism affecting the sensitivity of HCC to anticancer drugs, but the mechanism by which ERS regulates autophagy is not well understood. Zinc finger protein 263 (ZNF263) is a transcription factor member of the zinc finger family. However, its functional role in HCC remains to be studied. In the current study, we investigated the role of ZNF263 in regulating ERS-induced chemoresistance in HCC and its possible mechanism. We found that ZNF263 was the most significant ERS-specific super-enhancer bounding transcriptional factor and was up-regulated in HCC patients and cell lines. Further, ZNF263 expression correlated with ERS, clinical stage and shorter survival in HCC patients. ZNF263 knockdown by RNA interference results in decreased proliferation, apoptosis resistance, and chemoresistance. Further study showed that ZNF263 increased chemoresistance by activating ERS-related autophagy. In conclusion, our study highlights ZNF263 as a functional ERS-related tumor activator and indicates it as a potential target for HCC therapy.

Objective This study was performed to compare the effectiveness of routine Bakri balloon tamponade (BBT) and uterine gauze packing (UGP) during cesarean section in patients with placenta previa. Methods This study involved women with placenta previa who underwent cesarean section with either prophylactic BBT (n = 98) or UGP (n = 64) from January 2016 to December 2018. The clinical variables and pregnancy outcomes were compared between the two groups. Results The estimated intraoperative blood loss was significantly lower in the BBT than UGP group (667 ± 358 vs. 791 ± 360 ml, respectively). Additionally, the proportion of patients who required transfusion was significantly lower in the BBT than UGP group (9/98 vs. 17/64, respectively). The operative duration (97.8 ± 17.7 vs. 108.2 ± 16.9 minutes) and the length of stay (3.79 ± 0.89 vs. 4.12 ± 0.85 days) were significantly shorter in the BBT than UGP group. Conclusions In patients with placenta previa who undergo cesarean section, preventive application of BBT is superior to UGP for decreasing the intraoperative blood loss and transfusion rate. BBT is a more reliable technique to prevent and control postpartum hemorrhage.

Organogenesis, including renal development, requires an appropriate retinoic acid concentration, which is established by differential expression of aldehyde dehydrogenase 1 family member A2 (ALDH1A2) and cytochrome P450 family 26 subfamily A/B/C member 1 (CYP26A1/B1/C1). In the fetal kidney, ALDH1A2 expresses in the developing stroma and renal vesicle and its derivatives but does not present in the ureteric bud. It remains unclear what may contribute to this expression pattern. Here we show that the glycogen synthase kinase 3 alpha/beta (GSK3A/B) inhibitor CHIR99021 significantly represses ALDH1A2 expression in WiT49, which is a Wilms’ tumor cell line that exhibits “triphasic” differential potential and is used as a fetal kidney cell model. CHIR99021 fails to suppress ALDH1A2 as β-catenin is inhibited, suggesting that the downregulation of ALDH1A2 by CHIR99021 is through Wnt/β-catenin signaling. Ectopic expression of mouse Wnt1, Wnt3a, Wnt4, and Wnt9b represses ALDH1A2 expression in WiT49 cells. Using immunohistochemistry, we show an inverse correlation of Aldh1a2 expression with β-catenin in rat E18.5 kidney. ChIP demonstrated that β-catenin is recruited to the ALDH1A2 promoter, the conserved intron1G, and another site within intron 1 of ALDH1A2. Using a luciferase assay, we further show that the ALDH1A2 promoter and the intron1G element are involved in the repression of ALDH1A2 expression by CHIR99021. Our work demonstrates that ALDH1A2 expression can be directly repressed by the Wnt/β-catenin signaling in fetal kidney cells, suggesting that Wnt/β-catenin may play a role in maintaining the expression pattern of ALDH1A2 in the fetal kidney, thus controlling the availability and localization of retinoic acid and regulating aspects of kidney development.

This paper introduces an improved car-following speed (CFS) model that simultaneously considers speed of the lead vehicle, vehicle spacing, and driver’s sensitivity to them. Specifically, the proposed model extends the Helbing-Tilch model and Yang et al. model developed based on the principle of grey relational analysis where vehicle spacing is considered as the primary factor contributing to car-following speed choices. A computational experiment is conducted for model calibration using vehicle spacing, speed, and acceleration data derived from vehicle trajectory data of the Next Generation Simulation (NGSIM) project sponsored by the Federal Highway Administration (FHWA). It shows that speed of the lead vehicle and vehicle spacing significantly affect speed of the lag vehicle. Further, model validation is carried out using an independent NGSIM dataset by comparing vehicle speed predictions made by the calibrated CFS model with Helbing-Tilch model and Yang et al. model as benchmarks. Compared with speed prediction results of the benchmark models, mean relative errors, root mean square errors, and equal coefficient of speed predictions of the CFS model have reduced by 72.41% and 61.85%, 70.14% and 57.99%, and 33.15% and 14.48%, respectively. The findings of model validation reveal that the CFS model could improve the accuracy of speed predictions in the car-following process.

Background/Aims: Long non-coding RNAs (lncRNAs) are thought to play crucial roles in human diseases. However, the function of lncRNAs in hypertrophic scar formation remains poorly understood. Methods: Utilizing qRT-PCR, we explored the expression changes of AC067945.2. Overexpression of AC067945.2 in normal skin fibroblasts was performed by transient plasmid transfection. Western blot was used to check the proteins’ expression changes. Cell Counting Kit-8 (CCK-8) assay and Annexin V/7-AAD staining were used to examine cell proliferation and apoptosis, respectively. mRNA-seq was applied to dissect the differentially expressed mRNAs in AC067945.2 overexpressed cells. We also performed ELISA to detect the VEGF secretion. Results: AC067945.2 was down-regulated in hypertrophic scar tissues. Overexpression of AC067945.2 did not affect cell proliferation, but it mildly promoted early apoptosis in normal skin fibroblasts. Furthermore, AC067945.2 overexpression inhibited the expression of COL1A1, COL1A2, COL3A1 and α-SMA proteins. Transforming growth factor-β1 (TGF-β1) could inhibit the expression of AC067945.2. Based on mRNA-seq data, compared with mRNAs in the control group, 138 mRNAs were differentially expressed, including 14 up-regulated and 124 down-regulated transcripts, in the AC067945.2 overexpression group. Gene ontology and pathway analyses revealed that AC067945.2 overexpression was correlated with developmental processes, binding, extracellular region, and the vascular endothelial cell growth factor (VEGF) and Wnt signalling pathways. ELISA confirmed that AC067945.2 overexpression could repress VEGF secretion. Conclusion: Taken together, our data uncovered the functions of a novel lncRNA AC067945.2, which might help us understand the mechanisms regulated by AC067945.2 in the pathogenesis of hypertrophic scar formation.

Pressure-sensitive films have been used for measurement in micro flow, but thin films have very limited intensity, resulting in poor signal-noise ratio (SNR). This paper presents a pressure-sensitive film whose emission signal is enhanced by silver nanoparticles (AgNPs) based on localized surface plasmon resonance (LSPR). Electronic beam evaporator and annealing furnace are used to fabricate silver nanotexture surface. PtTFPP and polystyrene are dissolved in toluene and then spin-coated on the silver nanotexture surface to prepare the pressure-sensitive films. Signal enhancement of film with AgNPs due to LSPR is analyzed and enhancement effect of samples with different particle sizes and spacer thickness are compared. Pressure and temperature calibrations are performed to assess the sensing performance of pressure-sensitive films. Pressure-sensitive films with AgNPs demonstrate signal enhancement due to LSPR and show promise for measurement in micro flow.

Traffic control and safety hardware such as traffic signs, lighting, signals, pavement markings, guardrails, barriers, and crash cushions form an important and inseparable part of highway infrastructure affecting safety performance. Significant progress has been made in recent decades to develop safety performance functions and crash modification factors for site-specific crash predictions. However, the existing models and methods lack rigorous treatments of safety impacts of time-deteriorating conditions of traffic control and safety hardware. This study introduces a refined method for computing the Safety Index (SI) as a means of crash predictions for a highway segment that incorporates traffic control and safety hardware performance functions into the analysis. The proposed method is applied in a computation experiment using five-year data on nearly two hundred rural and urban highway segments. The root-mean square error (RMSE), Chi-square, Spearman’s rank correlation, and Mann-Whitney U tests are employed for validation.

Table of contents 01 The eco-toxicological effects of cadmium stress on five ornamental plants Zhouli Liu, Wei Chen, Xingyuan He, Shuai Yu, Weihang Ding 02 Study on the formation and release mechanisms of hydrogen sulfide in Longtan coal mine Jianjun Liu, Yuliang Wu, Kaixiang Fan 03 Coral bleaching in the North Reef of China’s Xisha Islands in 2014 Yuanchao Li, Xinqing Zheng, Shiquan Chen, Haiqun Xie 04 Soil chemical characteristics in a Cunninghamia lanceolata stand suffering from ice-snow damage Jie Li, Zhuomin Wang, Li Xue 05 Diversity of understory vegetation was under a Cunninghamia lanceolata stand suffering from ice-snow damage Zhiyang Lie, Weilong Huang, Tongtong Zhou, Li Xue 06 The effect of water, nitrogen and harvesting time on yield and biomass allocation of Helianthus tuberosus L. Kai Gao, Tiexia Zhu 07 The vertical variation of microbial communities in the sediment of sea cucumber pond Weiteng Mao, Pei Yu, Xinfang Lv, Yunchun Li 08 Indicating significances of alpine plant functional groups to environmental change Peixi Su, Rui Shi 09 Research on the daily CH4 fluxes of soil in summer mangrove community at Yingluogang of Guangxi, China Yong Jiang, Xingbin Chen, Shichu liang 10 Beach protection structures in middle and lower reaches of Yangtze River Junfeng Xu 11 Social responsibility management of large dam project with owner as core: an empirical case in China Jiwei Zhu, Zhao Zhai, Linan Zhou, Yun Le, Li Cao 12 The ecological function value assessment analysis of urban waterfront Jiwei Zhu, Ping Lu, Zhiqian Huang, Bei Zhou 13 Mechanism of diurnal osmotic potential changes and adjustment of three Caragana species in different habitats of the Inner Mongolia Plateau Zhirong Zheng, Shihai Lv, Chaoyang Feng 14 Biodiversity of phytoplankton and environmental influences analysis of Longfeng Wetland, China Nan Song, Yan Liu, Xinxin Lu, Yawen Fan 15 The effect of human activities on culturable soil microbes from Yaoquan Mountain in Wudalianchi, China Jianfei Guan, Jihua Wang, Xueping Zhang

Background/Aims: Long non-coding RNAs (lncRNAs) are thought to play crucial roles in human diseases. However, the function of lncRNAs in hypertrophic scar formation remains poorly understood. Methods: In this study, we investigated the expression of lncRNA8975-1 in hypertrophic scar tissues and fibroblasts by quantitative reverse transcription PCR (qRT-PCR). To investigate its function, overexpression and knockdown of lncRNA8975-1 were performed using lentivirus infection and Stealth RNAi transfection, respectively. Cell proliferation was detected by CCK-8 assay. The protein levels of collagens and alpha-smooth muscle actin (α-SMA) were analysed by western blot. Results: We found that lncRNA8975-1 was overexpressed in hypertrophic scar tissues and dermal fibroblasts. Overexpression of lncRNA8975-1 inhibited cell proliferation and reduced the protein expression levels of COL1A2, COL1A1, COL3A1 and α-SMA in hypertrophic scar fibroblasts, whereas knockdown of lncRNA8975-1 had the opposite effect. Conclusion: Our results show that the long non-coding RNA lncRNA8975-1 is upregulated in hypertrophic scar fibroblasts; furthermore, it inhibits fibroblast proliferation and reduces collagen and α-SMA expression. Further studies on the mechanisms regulated by lncRNA8975-1 would lead to a better understanding of the pathogenesis of hypertrophic scar formation.

Eupatorium adenophorum Spreng. (EA) is a well-known noxious invasive species. Gas chromatography-mass spectrometry (GC-MS) analysis revealed that the essential oil derived from EA (EAEO) is mainly composed of sesquiterpenes. However, the pharmacological value of EAEO in hepatocellular carcinoma (HCC) remains largely unexplored. Herein, we investigated the anti-HCC activities of EAEO, and explored the potential mechanisms of EAEO-induced apoptosis. An MTT assay showed that EAEO inhibited HCC cell proliferation with little toxicity on normal liver cells. Wound healing and FACS assays revealed that EAEO suppressed HCC cell migration and arrested cell cycle, respectively. Moreover, EAEO promoted in vitro HCC cell apoptosis, and EAEO treatment inhibited HepG2 xenografts growth and enhanced apoptotic nucleus of xenografts in HepG2-bearing nude mice. Mechanistically, EAEO significantly decreased the ratio of Bcl-2/Bax and resulted in the activation of caspase-9 and -3. EAEO also reduced the expression of Grp78, which in turn relieved the inhibition of caspase-12 and -7. Meanwhile, EAEO suppressed the phosphorylation of STAT3 and AKT, indicative of its anti-HCC potential. In summary, we determined that EAEO treatment promoted HCC apoptosis via activation of the apoptotic signaling pathway in mitochondria and endoplasmic reticulum, as well as repressed the activity of STAT3 and AKT in HCC cells.

A hit-and-run (HR) crash occurs when the driver of the offending vehicle flees the crash scene without reporting it or aiding the victims. The current study aimed at contributing to existing literatures by comparing factors which might affect the crash severity in HR and non-hit-and-run (NHR) crashes. The data was extracted from the police-reported crash data from September 2017 to August 2018 within the City of Chicago. Two multinomial logistic regression models were established for the HR and NHR crash data, respectively. The odds ratio (OR) of each variable was used to quantify the impact of this variable on the crash severity. In both models, the property damage only (PDO) crash was selected as the reference group, and the injury and fatal crash were chosen as the comparison group. When the injury crash was taken as the comparison group, it was found that 12 variables contributed to the crash severities in both HR and NHR model. The average percentage deviation of OR for these 12 variables was 34%, indicating that compared with property damage, HR crashes were 34% more likely to result in injuries than NHR crashes on average. When fatal crashes were chosen as the comparison group, 2 variables were found to be statistically significant in both the HR and the NHR model. The average percentage deviation of OR for these 2 variables was 127%, indicating that compared with property damage, HR crashes were 127% more likely to result in fatalities than NHR crashes on average.

Background: Recent studies suggest that long non-coding RNAs (lncRNAs) play crucial roles in human diseases. The function of lncRNAs in abnormal scar pathogenesis remains poorly understood. Methods: In this study, we examined the lncRNAs expression profiles among regressive and mature scars following caesarean sections. A total of 30,586 lncRNAs and 26,109 mRNAs were analyzed by microarrays (Human LncRNA Array v3.0, Arraystar, Inc.). Results: In total, we identified 1,871 lncRNAs and 817 mRNAs with differential expression between regressive and mature scar individuals (fold change≥3, p≤0.001). A set of differentially expressed lncRNA transcripts, in particular, lncRNA8975-1, AC097662.2 and RP11-586K2.1, were confirmed using qRT-PCR. Gene ontology and pathway analysis revealed that compared to mature scars, many processes over-represented in regressive scars are related to the immune system. Conclusion: Our results show significantly altered expression profiles of lncRNAs and mRNAs between regressive and mature scars. These transcripts are potential molecular targets for inhibiting abnormal scar formation following caesarean sections.

China as a large export of iron oxide pigments, iron oxide pigments production is out of low level. So in this paper, the effects of different modifiers and dosage on the dispersion of ultrafine iron oxide red pigment in aqueous solution and dry dispersion were studied by dry surface modification method. At the same time, we analyse the mechanism of modifier and iron oxide red. Finally, it is concluded that the best modifier formula for improving the dispersion performance of superfine iron oxide red pigment in aqueous solution and dry state is modifier D3008. Experiments show that the modified ultrafine iron oxide red pigment with the formula is strong, and can have better dispersion stability in aqueous solution.