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A new type of paste filling material was created using fluorogypsum, a byproduct of hydrofluoric acid, as the raw material to address the issue of the filling material's high cost. The effects of five factors, including gangue, fly ash, fluorogypsum, lime content, and mass concentration on the physical and mechanical properties of filling material were also examined. In addition to analyzing slump and extension changes, the filler's mineral composition and microstructure were examined using SEM and XRD examinations. The results show that the best ratio of the developed filling material was 1000g coal gangue, 300g fly ash, 300g fluorogypsum, and 50g lime and mass concentration is 78%, and its compressive strength can reach 4-5MPa at 28 days. Raw materials such as gangue and fly ash will have a certain influence on the mechanical properties of the filling material. The hydration products of the developed filling material prepared by XRD and SEM were ettringite, calcium sulfate dihydrate, and calcium silicate hydrate gel. The new fluorogypsum-based paste filling material can be used to consolidate loose rock strata and fill goaf. It solves the problem of disposal of industrial waste fluoropgypsum and also solves the problem of coal mine gangue stacking, which has a far-reaching influence on ecological environment management.

Pancreatic cancer is among the most lethal malignant neoplasms, and few patients with pancreatic cancer benefit from immunotherapy. We retrospectively analyzed advanced pancreatic cancer patients who received PD-1 inhibitor-based combination therapies during 2019–2021 in our institution. The clinical characteristics and peripheral blood inflammatory markers (neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio [PLR], lymphocyte-to-monocyte ratio [LMR], and lactate dehydrogenase [LDH]) were collected at baseline. Chi-squared and Fisher’s exact tests were used to evaluate relationships between the above parameters and tumor response. Cox regression analyses were employed to assess the effects of baseline factors on patients’ survival and immune-related adverse events (irAEs). Overall, 67 patients who received at least two cycles of PD-1 inhibitor were considered evaluable. A lower NLR was independent predictor for objective response rate (38.1% vs. 15.2%, P = .037) and disease control rate (81.0% vs. 52.2%, P = .032). In our study population, patients with lower LDH had superior progression-free survival (PFS) and overall survival(OS) (mPFS, 5.4 vs. 2.8 months, P

Rating prediction is crucial in recommender systems as it enables personalized recommendations based on different models and techniques, making it of significant theoretical importance and practical value. However, presenting these recommendations in the form of lists raises the challenge of improving the list's quality, making it a prominent research topic. This study focuses on enhancing the ranking quality of recommended items in user lists while ensuring interpretability. It introduces fuzzy membership functions to measure user attributes on a multi-dimensional item label vector and calculates user similarity based on these features for prediction and recommendation. Additionally, the user similarity network is modeled to extract community information, leading to the design of a set of corresponding recommendation algorithms. Experimental results on two commonly used datasets demonstrate the effectiveness of the proposed algorithm in enhancing list ranking quality, reducing prediction errors, and maintaining recommendation diversity and accurate user preference classification. This research highlights the potential of integrating heuristic methods with complex network theory and fuzzy techniques to enhance recommendation system performance with interpretability in mind.

It is becoming increasingly evident that key mechanisms of mesenchymal stem cell (MSC) efficacy appear to associate with paracrine activities, and the delivery of cargos through extracellular vesicles (EVs) controls the mechanistic actions of MSCs. Thus, this study clarified a possible mechanism by which EV-encapsulated NEAT1 from adipose-derived mesenchymal stem cells (ADSCs) might mediate gemcitabine resistance in pancreatic cancer (PCa). Microarray profile suggested a differentially expressed lncRNA NEAT1 in PCa, and we determined its expression in PCa cells. NEAT1 was found to be upregulated in PCa. The binding affinity among NEAT1, miR-491-5p, and Snail was identified through bioinformatic analysis and experimental validation. NEAT1 competitively bound to miR-491-5p to elevate Snail expression and diminish SOCS3 expression. PCa cells were cocultured with EVs extracted from ADSCs, followed by assessment of malignant phenotypes, tumorigenesis, and gemcitabine resistance of PCa cells using gain- or loss-of-function experiments. ADSC-derived EVs carrying NEAT1 promoted PCa cell proliferation, migration, and gemcitabine resistance in vitro and enhanced tumorigenicity in vivo by inhibiting miR-491-5p and SOCS3 and upregulating Snail. Collectively, the findings from our study found a new potential strategy for gemcitabine resistance in PCa by illustrating the mechanistic insights of oncogenic ADSC-derived EVs-loaded NEAT1 via regulating the miR-491-5p/Snail/SOCS3 axis.

ObjectivesPrevious studies have reported that a few inflammatory cytokines have associations with systemic lupus erythematosus (SLE)—for example, IL-6, IL-17, and macrophage inflammatory protein (MIP). This Mendelian randomization was conducted to further assess the causal correlations between 41 inflammatory cytokines and SLE.MethodsThe two-sample Mendelian randomization utilized genetic variances of SLE from a large publicly available genome-wide association study (GWAS) (7,219 cases and 15,991 controls of European ancestry) and inflammatory cytokines from a GWAS summary containing 8,293 healthy participants. Causalities of exposures and outcomes were explored mainly using inverse variance weighted method. In addition, multiple sensitivity analyses including MR-Egger, weighted median, simple mode, weighted mode, and MR-PRESSO were simultaneously applied to strengthen the final results.ResultsThe results indicated that cutaneous T cell-attracting chemokine (CTACK) and IL-17 may be suggestively associated with the risk of SLE (odds ratio, OR: 1.21, 95%CI: 1.04–1.41, p = 0.015; OR: 1.37, 95%CI: 1.03–1.82, p = 0.029). In addition, cytokines including beta nerve growth factor, basic fibroblast growth factor, IL-4, IL-6, interferon gamma-induced protein 10, monokine induced by interferon-gamma, MIP1b, stromal cell-derived factor-1 alpha, and tumor necrosis factor-alpha are suggested to be the consequences of SLE disease (Beta: 0.035, p = 0.014; Beta: 0.021, p = 0.032; Beta: 0.024, p = 0.013; Beta: 0.019, p = 0.042; Beta: 0.040, p = 0.005; Beta: 0.046, p = 0.001; Beta: 0.021, p = 0.029; Beta: 0.019, p = 0.045; Beta: 0.029, p = 0.048).ConclusionThis study suggested that CTACK and IL-17 are probably the factors correlated with SLE etiology, while a couple of inflammatory cytokines are more likely to be involved in SLE development downstream.

Abstract Ferredoxin (Fdx) is regarded as the main electron carrier in biological electron transfer and acts as an electron donor in metabolic pathways of many organisms. Here, we screened a self-sufficient P450-derived reductase PRF with promising production yield of 9OHAD (9α-hydroxy4-androstene-3,17-dione) from AD, and further proved the importance of [2Fe–2S] clusters of ferredoxin-oxidoreductase in transferring electrons in steroidal conversion. The results of truncated Fdx domain in all oxidoreductases and mutagenesis data elucidated the indispensable role of [2Fe–2S] clusters in the electron transfer process. By adding the independent plant-type Fdx to the reaction system, the AD (4-androstene-3,17-dione) conversion rate have been significantly improved. A novel efficient electron transfer pathway of PRF + Fdx + KshA (KshA, Rieske-type oxygenase of 3-ketosteroid-9-hydroxylase) in the reaction system rather than KshAB complex system was proposed based on analysis of protein–protein interactions and redox potential measurement. Adding free Fdx created a new conduit for electrons to travel from reductase to oxygenase. This electron transfer pathway provides new insight for the development of efficient exogenous Fdx as an electron carrier. Graphical Abstract

Abstract In this paper, we present a detailed next-to-leading-order (NLO) study of J/ψ angular distributions in e + e − → J/ψ + η c , χ cJ (J = 0, 1, 2) within the nonrelativistic QCD factorization (NRQCD). The numerical NLO expressions for total and differential cross sections, i.e., dσ d cos θ $$ \frac{d\sigma}{d\cos \theta } $$ = A + B cos2 θ, are both derived. With the inclusion of the newly-calculated QCD corrections to A and B, the α θ (= B/A) parameters in J/ψ + χ c0 and J/ψ + χ c1 are moderately enhanced, while the magnitude of α θJ/ψ+χc2 is significantly reduced; regarding the production of J/ψ + η c , the α θ value remains unchanged. By comparing with experiment, we find the predicted α θJ/ψ+ηc is in good agreement with the Belle measurement; however, α θJ/ψ+χc0 is still totally incompatible with the experimental result, and this discrepancy seems to hardly be cured by proper choices of the charm-quark mass, the renormalization scale, and the NRQCD matrix elements.

Herein, a novel concept was proposed to address the issue that continuous brittle phases degrade the mechanical properties of a brazed joint. In this concept, the continuous brittle phases could become dispersive by inserting a network-like structure to divide the brazing seam spatially. This concept was verified in a specific brazing system, where Ti3SiC2 ceramic and Ti2AlNb alloy were brazed by an AgCu interlayer. Ductile Cu foam with a network-like structure was used to disperse the continuous brittle TiCuSi intermetallic that should have in-situ formed in the Ti3SiC2/AgCu/Ti2AlNb brazed joint. Results show that the effect of Cu foam on dispersing the brittle TiCuSi intermetallic is pronounced. The effects of holding time and pore size on the dispersion effect of Cu foam were investigated. The joint fracture analysis and micro-mechanical properties of phases analysis reveal that the dispersive TiCuSi intermetallic is superior to the continuous one. The reason is that the microstructure of discrete TiCuSi intermetallic surrounded by ductile Ag-based and Cu-based solid solutions has a more robust capacity to accommodate microcracks. Thus the brazed joint is toughened and strengthened.

Summary: In this study, we investigated an outbreak of peste des petits ruminants (PPR) at a Hydropotes inermis (water deer) farm in Anhui Province, China. These results demonstrated that PPR viruses (PPRVs) can infect H. inermis and also revealed that virulent lineage II PPRVs exist in China, where they have been responsible for the deaths of wild animals. The government should pay close attention to the threat of PPRV epidemiology in China. [ABSTRACT FROM AUTHOR]

Chilies undergo multiple stages from field production to reaching consumers, making them susceptible to contamination with foreign materials. Visually similar foreign materials are difficult to detect manually or using color sorting machines, which increases the risk of their presence in the market, potentially affecting consumer health. This paper aims to enhance the detection of visually similar foreign materials in chilies using hyperspectral technology, employing object detection algorithms for fast and accurate identification and localization to ensure food safety. First, the samples were scanned using a hyperspectral camera to obtain hyperspectral image information. Next, a spectral pattern recognition algorithm was used to classify the pixels in the images. Pixels belonging to the same class were assigned the same color, enhancing the visibility of foreign object targets. Finally, an object detection algorithm was employed to recognize the enhanced images and identify the presence of foreign objects. Random forest (RF), support vector machine (SVM), and minimum distance classification algorithms were used to enhance the hyperspectral images of the samples. Among them, RF algorithm showed the best performance, achieving an overall recognition accuracy of up to 86% for randomly selected pixel samples. Subsequently, the enhanced targets were identified using object detection algorithms including R-CNN, Faster R-CNN, and YoloV5. YoloV5 exhibited a recognition rate of over 96% for foreign objects, with the shortest detection time of approximately 12 ms. This study demonstrates that the combination of hyperspectral imaging technology, spectral pattern recognition techniques, and object detection algorithms can accurately and rapidly detect challenging foreign objects in chili peppers, including red stones, red plastics, red fabrics, and red paper. It provides a theoretical reference for online batch detection of chili pepper products, which is of significant importance for enhancing the overall quality of chili pepper products. Furthermore, the detection of foreign objects in similar particulate food items also holds reference value.

The prediction of soil properties at different depths is an important research topic for promoting the conservation of black soils and the development of precision agriculture. Mid-infrared spectroscopy (MIR, 2500–25000 nm) has shown great potential in predicting soil properties. This study aimed to explore the ability of MIR to predict soil organic matter (OM) and total nitrogen (TN) at five different depths with the calibration from the whole depth (0–100 cm) or the shallow layers (0–40 cm) and compare its performance with visible and near-infrared spectroscopy (vis-NIR, 350–2500 nm). A total of 90 soil samples containing 450 subsamples (0–10 cm, 10–20 cm, 20–40 cm, 40–70 cm, and 70–100 cm depths) and their corresponding MIR and vis-NIR spectra were collected from a field of black soil in Northeast China. Multivariate adaptive regression splines (MARS) were used to build prediction models. The results showed that prediction models based on MIR (OM: RMSEp = 1.07–3.82 g/kg, RPD = 1.10–5.80; TN: RMSEp = 0.11–0.15 g/kg, RPD = 1.70–4.39) outperformed those based on vis-NIR (OM: RMSEp = 1.75–8.95 g/kg, RPD = 0.50–3.61; TN: RMSEp = 0.12–0.27 g/kg; RPD = 1.00–3.11) because of the higher number of characteristic bands. Prediction models based on the whole depth calibration (OM: RMSEp = 1.09–2.97 g/kg, RPD = 2.13–5.80; TN: RMSEp = 0.08–0.19 g/kg, RPD = 1.86–4.39) outperformed those based on the shallow layers (OM: RMSEp = 1.07–8.95 g/kg, RPD = 0.50–3.93; TN: RMSEp = 0.11–0.27 g/kg, RPD = 1.00–2.24) because the soil sample data of the whole depth had a larger and more representative sample size and a wider distribution. However, prediction models based on the whole depth calibration might provide lower accuracy in some shallow layers. Accordingly, it is suggested that the methods pertaining to soil property prediction based on the spectral library should be considered in future studies for an optimal approach to predicting soil properties at specific depths. This study verified the superiority of MIR for soil property prediction at specific depths and confirmed the advantage of modeling with the whole depth calibration, pointing out a possible optimal approach and providing a reference for predicting soil properties at specific depths.

The reflection phenomenon exhibited by highly reflective surfaces considerably affects the quality of captured images, thereby rendering the task of structured light (SL) 3D reconstruction. In this paper, a polarized SL method is proposed to address the reconstruction issues on high-reflectance surfaces. The SL system we build in this paper involves a four-channel polarizing camera and a digital light processing (DLP) projector equipped with a polarizer in the lens. The built system enables the simultaneous acquisition of four groups of fringe images, each with different brightness differences. Then, a binary time-multiplexing SL method is adopted to obtain four distinct point clouds. Additionally, a fusion algorithm is proposed to merge the four point clouds into a single, precise, and complete point cloud. Several experiments have been conducted to demonstrate that the proposed method is capable of achieving excellent reconstruction outcomes on highly reflective surfaces.

The development of chemoresistance reduces the efficacy of anti‐cancer drugs. Cervical cancer is still one of the most common cancer types in developing countries. The oncogenic protein high mobility group AT‐hook 2 (HMGA2) is involved in the development and progression of tumors, although its role in chemoresistance of cervical cancer remains unclear. Here, we report that HMGA2 is highly expressed in cervical cancer and negatively correlated with cisplatin‐induced cell death. We performed liquid chromatography‐tandem mass spectrometry to demonstrate that HMGA2 has high potential to interact with casein kinase II A1 (CSNK2A1). Moreover, we observed that HMGA2 co‐localizes with CSNK2A1 in the nucleus by immunofluorescence. Binding of HMGA2‐CSNK2A1 was detected by immunoprecipitation assays. In addition, we identified that cisplatin induces an interaction between CSNK2A1 and HMGA2, thereby promoting the phosphorylation of HMGA2. CX‐4945, a CSNK2A1 inhibitor, could inhibit the phosphorylation of HMGA2 and sensitize tumor cells to cisplatin. Our results reveal that CSNK2A1‐dependent HMGA2 phosphorylation may partially underlie cisplatin‐resistance in cervical cancer, suggesting that HMGA2 phosphorylation may have potential as a predicative biomarker and therapeutic target to improve chemotherapeutic efficacy.

Abstract Background Previous studies have evaluated the association of multimorbidity with higher mortality, but epidemiologic data on the association between the disease clusters and all-cause mortality risk are rare. We aimed to examine the relationship between multimorbidity (number/ cluster) and all-cause mortality in Chinese older adults. Methods We conducted a population-based study of 50,100 Chinese participants. Multiple logistic regression analysis was used to estimate the impact of long-term conditions (LTCs) on all-cause mortality. Results The prevalence of multimorbidity was 31.35% and all-cause mortality was 8.01% (50,100 participants). In adjusted models, the odds ratios (ORs) and 95% confidence intervals (CIs) of all-cause mortality risk for those with 1, 2, and ≥ 3 LTCs compared with those with no LTCs was 1.45 (1.32–1.59), 1.72 (1.55–1.90), and 2.15 (1.85–2.50), respectively (P trend

Abstract In this paper, we present a comprehensive study of ϒ inclusive production in Z boson decay, including the first complete next-to-leading-order calculations of the color-octet (CO) contributions. With the inclusion of the newly-calculated remarkable QCD corrections, the CO processes exhibit crucially phenomenological influence on the existing predictions built on the color-singlet mechanism. We also include the exhaustive evaluations of the feed-down contributions, which remained ignored in the literature, and find them to be considerable. Summing up all the contributions, the ℬ Z → ϒ(nS) + X still notably undershoot the data released by the L3 Collaboration.

Objective To evaluate the effects of early ambulation on elderly patients’ postoperative physical functional outcomes, complications, 90‐day readmission rate, and the length of postoperative hospital stay. Methods This is a prospective cohort study conducted between June 2019 and December 2019. The study enrolled 86 elderly patients (39 males) with newly diagnosed lumbar degenerative disease undergoing single‐segment decompression and fusion surgerywere enrolled. Of all 86 patients, 39 voluntarily joined the early ambulation group, and 47 joined the regular ambulation group. The early ambulation group included patients ambulated within 4 h postoperatively, whereas the regular ambulation group included patients who were ambulatory at a minimum of 24 h after surgery. Participants’ baseline characteristics, surgical information, ambulation ability, degree of pain, functional scores, postoperative complications, 90‐day readmission rate, and length of postoperative hospital stay were recorded. Results Participants’ baseline demographic characteristics were balanced between the early ambulation group and the regular ambulation group. The operative time and blood loss were similar between groups. The time before the first‐time ambulation was 4 ± 0.5 h in the early ambulation group and 28 ± 4.5 h in the regular ambulation group. Ambulating distance was significantly longer in the early ambulation group compared with the regular ambulation group on the 1st (63 ± 45 vs 23 ± 60 m), the 2nd (224 ± 100 vs 101 ± 130 m), and the 3rd (280 ± 102.5 vs 190 ± 170 m) ambulation days based on generalized estimating equation analyses. Generalized estimating equation analyses also demonstrated that the ambulating time was longer in the early ambulation group compared with the regular ambulation group on the 1st (10 ± 5 vs 10 ± 5 min), the 2nd (19 ± 7 vs 15 ± 5 min), and the 3rd (22 ± 16.5 vs 27 ± 12 min) ambulation days. Patients in the regular ambulation group experienced a higher degree of pain than the early ambulation group patients, with an odds ratio of 1.627 (P = 0.002). Short‐term functional independence was superior in the early ambulation group, with a lower Roland–Morris disability questionnaire score (P = 0.008) and Oswestry disability index (P

Background This study aims to investigate whether a systematic digital training system can improve the learning efficiency of residents in the first-year orthognathic surgery training course and evaluate its effectiveness in teaching orthognathic surgery. Methods A digital training system was applied, and a comparative research approach was adopted. 24 first-year orthognathic surgery residents participated in the experiment as part of their professional skill training. The Experimental group was required to use a digital training system, and the Control group was trained in lectures without digital technologies. Three indicators, including theoretical knowledge and clinical operation, were assessed in tests, and evaluations from instructors were analyzed to evaluate learning efficiency. Results The results showed that the scores in theoretical tests, practical operations, and teacher evaluations, the Experimental groups were all higher than the Control group (P = 0.002 for anatomy, P = 0.000 for operation theory) after using digital technology, except for the understanding of complications (P = 0.771). In addition, the questionnaire survey results showed that the study interest (P = 0.001), self-confidence (P = 0.001), satisfaction (P = 0.002), and academic performance (P = 0.001) of the residents of the Experimental group were higher than those of the Control group. Conclusions The outcomes indicated that the digital training system could benefit orthognathic residents’ learning efficiency, and learning interest and teaching satisfaction will also improve.

Breast cancer (BC) is the most frequently diagnosed cancer and leading cause of the death in women. Current chemotherapy usually results in poor prognosis with low treatment efficacy and high side effects because of weak targeting specificity and fast elicitation of multidrug resistance (MDR). It is emergently needed to develop a novel BC targeting drug delivery formulation for the chemotherapy of BC and drug resistant BC. In our study, we screened out BC targeting 12-mer peptide (BSP1) from a phage-displayed peptide library, then a novel doxorubicin (DOX) delivery formulation (BSP1-Lipo-DOX-miR101) targeting BC automatically was synthesized and used in a series of experiments to test its efficacy of chemotherapy of BC and DOX resistant BC in vitro. The consequently results indicated that BSP1 bound to MCF-7 cells and BC tissues specifically and sensitively with high affinity, the BC automatically targeted drug vehicles exhibited its high specificity for BC targeting, marked suppression for the development of cell motility relevant microstructures, such as the polymerization of the pseudopodia and filopodia in MCF-7 and MCF-7/ADR cells. The novel drug formulation presented the satisfied therapeutic efficacy for BC therapy, particularly for DOX resistant BC in vitro. The results of western blot explored the potential mechanism by that BSP1-Lipo-DOX-miR101 inhibits the expression of EMT (epithelial/endothelial mesenchymal transition) and MDR relevant genes. Our current results provide a novel chemotherapeutic formulation with precise, satisfying therapeutic efficacy to improve the current poor BC clinical prognosis including drug resistant BC.

VSe2 is with high electrical conductivity and high work function, thus it is beneficial for the carrier transport in the optoelectronic devices. However, the performance and mechanism of its effect on the photoelectronic devices conversion efficiency is still beyond understood. In this work, we fabricate VSe2 film between back contact and absorber layer Cu2ZnSn(S,Se)4 (CZTSSe) film. We demonstrate that the VSe2 film in back contact region increases solar cell efficiency by 39%. Besides improving the carrier transport in the back contact region, the increasing can also be attributed to the reduction of the decomposition reaction of CZTSSe during the nucleation of CZTSSe as VSe2 fabricated between back contact and absorber layer. The present work not only provides an effective method to improve the performance of the optoelectronic device, but also shows an attractive application of metallic TMDs in optoelectronic device and solar cell energy generation.

Abstract Background Distinguishing parotid pleomorphic adenoma (PPA) from parotid adenolymphoma (PA) is important for precision treatment, but there is a lack of readily available diagnostic methods. In this study, we aimed to explore the diagnostic value of radiomic signatures based on magnetic resonance imaging (MRI) for PPA and PA. Methods The clinical characteristic and imaging data were retrospectively collected from 252 cases (126 cases in the training cohort and 76 patients in the validation cohort) in this study. Radiomic features were extracted from MRI scans, including T1-weighted imaging (T1WI) sequences and T2-weighted imaging (T2WI) sequences. The radiomic features from three sequences (T1WI, T2WI and T1WI combined with T2WI) were selected using univariate analysis, LASSO correlation and Spearman correlation. Then, we built six quantitative radiomic models using the selected features through two machine learning methods (multivariable logistic regression, MLR, and support vector machine, SVM). The performances of the six radiomic models were assessed and the diagnostic efficacies of the ideal T1-2WI radiomic model and the clinical model were compared. Results The T1-2WI radiomic model using MLR showed optimal discriminatory ability (accuracy = 0.87 and 0.86, F-1 score = 0.88 and 0.86, sensitivity = 0.90 and 0.88, specificity = 0.82 and 0.80, positive predictive value = 0.86 and 0.84, negative predictive value = 0.86 and 0.84 in the training and validation cohorts, respectively) and its calibration was observed to be good (p > 0.05). The area under the curve (AUC) of the T1-2WI radiomic model was significantly better than that of the clinical model for both the training (0.95 vs. 0.67, p

As an emerging industry formed by the integration of multiple industries, the e-sports industry contributes to urban development, economic growth, and promotion of urban image owing to the characteristics of low pollution, strong driving effect, and high social influence. However, the e-sport industry is a new industry with limited studies about the general features, evolutionary mechanism, and spatial dynamics. As an e-sports industry center in China, Shanghai has the most complete e-sports industry chain and the largest industrial scale. This study takes Shanghai as a classical case to explore the spatial evolution process, features, and influencing factors of the e-sports industry using the spatial analysis methods, including the kernel density estimation, nearest neighbor index, and the Kriging spatial interpolation analysis based on the data mining of Shanghai e-sports enterprises from 2006 to 2018. The results show that, first, according to factors such as historical background, policy support, and development characteristics, the e-sports industry in Shanghai can be divided into the initial stage from 2006 to 2010, the rapid development stage from 2010 to 2014, and the explosive growth stage from 2014 to 2018. Second, the spatial distribution of the e-sports industry in Shanghai has evolved from a dual-core aggregation to a multi-core aggregation with the characteristics of central aggregation and simultaneous outward expansion. The south and north are the main directions of the expansion of e-sports enterprises. Third, high-capital e-sports enterprises tend to focus on software parks and universities in the surrounding area. There are currently four high-capital hotspots, namely, Zizhu Science Park in Minhang District, Zhaojiabang Road in Xuhui District, Lantian Enterprise Development Industrial Park in Jiading District, and Tiandi Software parks in Putuo District. These hotspots will have more opportunities to extend more competitive e-sports enterprises in the future because spin-off firms can inherit excellent capabilities from the parent firms. Fourth, based on the analysis framework of agglomeration economy—enterprise spin-off—institutional environment, this study analyzes the evolution mechanism of e-sports industry cluster in Shanghai. The agglomeration economy plays a centripetal role, the enterprise spin-off enables new enterprises to inherit successful routines from the parent company, and the institutional environment is conducive to the formation and management of industries. Compared with previous studies which showed that the government plays a smaller role in promoting the cultural industry, the development of the e-sports industry is affected more by the institutional environment. Finally, at an urban scale, government policy planning has a guiding effect on the location selection of the e-sports industry. High-quality human resources, economic development level, e-sports market environment, and transportation convenience are the key factors for the aggregation of e-sports enterprises. In addition, compared with traditional industries, the e-sports industry has the characteristics of competition as a sporting activity. Furthermore, the excitement of competition and the holding of big e-sports events will have a significant impact on the development of the e-sports industry. This study explores the spatial-temporal pattern, evolution process, influencing factors, and evolution mechanisms of the e-sports industry in Shanghai from the perspective of evolutionary economic geography. This study verifies and enriches the theory of evolutionary economic geography from an empirical perspective, providing a theoretical basis for optimizing the spatial distribution of the e-sports industry, developing an e-sports industry cluster district, and enhancing the urban cultural brand. It also provides a decision-making reference for other cities to develop the e-sports industry.

Spatial structured light (SL) can achieve three-dimensional measurements with a single shot. As an important branch in the field of dynamic reconstruction, its accuracy, robustness, and density are of vital importance. Currently, there is a wide performance gap of spatial SL between dense reconstruction (but less accurate, e.g., speckle-based SL) and accurate reconstruction (but often sparser, e.g., shape-coded SL). The central problem lies in the coding strategy and the designed coding features. This paper aims to improve the density and quantity of reconstructed point clouds by spatial SL whilst also maintaining a high accuracy. Firstly, a new pseudo-2D pattern generation strategy was developed, which can improve the coding capacity of shape-coded SL greatly. Then, to extract the dense feature points robustly and accurately, an end-to-end corner detection method based on deep learning was developed. Finally, the pseudo-2D pattern was decoded with the aid of the epipolar constraint. Experimental results validated the effectiveness of the proposed system.

As a precious soil resource, black soils in Northeast China are currently facing severe land degradation. Visible and near-infrared spectroscopy (vis-NIR, 350–2500 nm) and mid-infrared spectroscopy (MIR, 2500–25,000 nm) have shown great potential to predict soil properties. However, there is still limited research on using MIR in situ. The aim of this study was to explore the feasibility of in situ MIR for the prediction of soil total nitrogen (TN) and total phosphorus (TP) and to compare its performance with the use of laboratory MIR, as well as the use of in situ and laboratory vis-NIR. A total of 450 samples from 90 soil profiles, along with their in situ and laboratory spectra of MIR and vis-NIR, were collected in a field with ten different tillage and management practices in a typical black soil area of Northeast China. Partial least square regression (PLSR), random forest (RF) and multivariate adaptive regression splines (MARS) were used to generate the calibrations between the spectra and the two properties. The results showed that both MIR and vis-NIR were able to predict the TN whether in laboratory or in situ conditions, but neither of them could predict the TP quantitatively since there was no sensitive band on both spectra regarding the TP. The prediction accuracy of the TN with laboratory spectra was higher than that with in situ spectra, for both vis-NIR and MIR. The optimal prediction accuracy of the TN with laboratory MIR (RMSE = 0.11 g/kg, RPD = 3.12) was higher than that of laboratory vis-NIR (RMSE = 0.14 g/kg, RPD = 2.45). The optimal prediction accuracy of in situ MIR (RMSE = 0.20 g/kg, RPD = 1.80) was lower than that of in situ vis-NIR (RMSE = 0.16 g/kg, RPD = 2.14). The prediction performance of the spectra followed laboratory MIR > laboratory vis-NIR > in situ vis-NIR > in situ MIR. The performance of in situ MIR was relatively poor, mainly due to the fact that MIR was more influenced by soil moisture. This study verified the feasibility of in situ MIR for soil property prediction and provided an approach for obtaining rapid soil information and a reference for soil research and management in black soil areas.

Abstract Aims/Introduction Chronic inflammation is an underlying feature of type 2 diabetes mellitus. Hypovitaminosis D is associated with type 2 diabetes mellitus, but whether it contributes to chronic inflammation is unclear. We examined the effects of vitamin D on various immune markers to evaluate its contribution to systemic inflammation in type 2 diabetes mellitus. Materials and Methods We retrospectively analyzed data from type 2 diabetes mellitus patients, people with prediabetes and control patients without diabetes (n = 9,746). Demographic and clinical variables were evaluated using descriptive statistics and generalized linear regression. A stratified analysis based on total serum vitamin D was also carried out. Results Neutrophil count was a significant predictor of 1,5‐anhydroglucitol and glycated hemoglobin (HbA1c) in patients with prediabetes (1,5‐anhydroglucitol: β = −0.719, P 0.05 for all). Among patients with prediabetes, those who were vitamin D‐deficient had the highest NLR (P = 0.040). Among patients with diabetes, those who were vitamin D‐deficient had the highest neutrophil count (P = 0.001), lowest lymphocyte count (P = 0.016) and highest NLR (P

In recommender systems, measuring user similarity is essential for predicting a user's ratings on items. Most traditional works calculate the similarity based on historical ratings shared between two users, without considering the probability of users' different behaviors. To address this issue, our work designs a similarity measure based on the users' historical behavior probabilities. Based on the similarity method, a complex network of user relationships is modeled. The user degree and community information of the modeled network, as well as the number of shared ratings between users, are used with the proposed similarity measure to design a rating prediction algorithm for recommender systems. Experiments based on MovieLens and Netflix data sets show that this method is effective and can successfully improve the accuracy of rating predictions and reduce the number of neighbors required to achieve the optimal prediction accuracy. Our research shows that in a complex system, the relationship between users can be effectively measured by the users' historical behavior probability, providing a new perspective for future research on similarity measurement.

Centrosome clustering is a promising therapeutic target in cancer but how it is regulated remains unclear. Here, the authors show that in response to DNA damage, ATM/ATR stabilize the centrosome clustering regulator KIFC1 leading to increased clustering efficiency and tumour recurrence.

Abstract Calcium‐ion batteries (CIBs) are considered as promising alternatives in large‐scale energy storage due to their divalent electron redox properties, low cost, and high volumetric/gravimetric capacity. However, the high charge density of Ca2+ contributes to strong electrostatic interaction between divalent Ca2+ and hosting lattice, leading to sluggish kinetics and poor rate performance. Here, in situ formed poly(anthraquinonyl sulfide) (PAQS)@CNT composite is reported as nonaqueous calcium‐ion battery cathode. The enolization redox chemistry of organics has fast redox kinetics, and the introduction of carbon nanotube (CNT) accelerates electron transportation, which contributes to fast ionic diffusion. As the conductivity of the PAQS is enhanced by the increasing content of CNT, the voltage gap is significantly reduced. The PAQS@CNT electrode exhibits specific capacity (116 mAh g−1 at 0.05 A g−1), high rate capacity (60 mAh g−1 at 4 A g−1), and an initial capacity of 82 mAh g−1 at 1 A g−1 (83% capacity retention after 500 cycles). The electrochemical mechanism is proved to be that the PAQS undergoes reduction reaction of their carbonyl bond during discharge and becomes coordinated by Ca2+ and Ca(TFSI)+ species. Computational simulation also suggests that the construction of Ca2+ and Ca(TFSI)+ co‐intercalation in the PAQS is the most reasonable pathway.

Background and PurposeA phase 2 study LAPACT indicated nab-paclitaxel plus gemcitabine (AG) improved outcomes of patients with locally advanced pancreatic cancer (LAPC). Conventional radiotherapy failed to show benefit, indicating high dose to volume with high risk of recurrence is needed. The high dose can be delivered through hypofractionated tomotherapy with simultaneous integrated boost (SIB). However, there is a lack of such prospective trials and more data are needed to validate the role of AG plus hypofractionated tomotherapy with SIB in patients with LAPC.Materials and MethodsPatients with LAPC receiving AG plus tomotherapy at the Nanjing Drum Tower Hospital between 2018 and 2021 were retrospectively analyzed. The treatment was scheduled as follows: nab-paclitaxel 125 mg/m2 plus gemcitabine 1,000 mg/m2 on days 1 and 8 every three weeks for at least two cycles, followed by hypofractionated tomotherapy with SIB (high dose field: 50 Gy/10 fractions, the remainder: 30 Gy/10 fractions). Then patients were given AG until intolerance or disease progression.ResultsOverall, 22 patients completing the chemoradiotherapy were included. The median follow-up was 15.2 months. After the chemoradiotherapy, 5 patients achieved a partial response (PR), 15 had a stable disease (SD), and another 2 patients were with progressive disease (PD). The median progression-free survival (PFS) and overall survival (OS) were 12.8 months (95% confidence interval [CI] 4.3–21.3 months) and 16.3 months (95% CI 10.9–21.6 months), respectively. The optimal carbohydrate antigen (CA) 19-9 response and chemotherapy cycles ≥6 were correlated with favorable PFS and OS. The most common recurrent pattern was peritoneal dissemination (22.7%) and the locoregional recurrence rate was relatively low (4.5%). Treatments were well-tolerated. The most common grade ≥3 adverse event was thrombocytopenia (13.6%).ConclusionThis study demonstrated the feasibility of AG followed by hypofractionated tomotherapy with SIB in patients with LAPC. The hypofractionated tomotherapy with SIB was safe and showed high local control rate. Further study with a larger population to validate our data is underway.

A 33-year-old Chinese woman with a history of immune thrombocytopenic purpura presented with heavy menstrual bleeding. She was found to have thrombocytopenia, plasma ADAMTS13 activity of 0%, and positivity for the plasma ADAMTS13 inhibitor. She was diagnosed with the coexistence of thrombotic thrombocytopenic purpura and immune thrombocytopenic purpura. The patient was treated by plasmapheresis, a glucocorticoid, and rituximab. Her platelet level returned to normal, and she was discharged 28 days after admission. The number of plasmapheresis sessions and the timing of rituximab administration may be the key aspects of management of patients with thrombotic thrombocytopenic purpura who have underlying immune dysfunction caused by diseases such as immune thrombocytopenic purpura.

A multi-scale model is often constructed using different finite elements and consists of a global scale model for the structural system and a few local scale models for critical structural components so that the multi-scale simulation can concurrently exhibit both global performance and local behavior of the structure. To ensure the multi-scale model can best represent the real structure, multi-scale model updating technique shall be developed accordingly. This paper thus presents a multi-scale model updating method for a transmission tower structure using the Kriging meta-model that actually is a surrogate for the multi-scale model. Firstly, the multi-scale model of a transmission tower is established by using beam elements to simulate global structure and solid elements to simulate local joints with bolt connections. Secondly, the multi-objective optimization problem that involves multiple objective functions is established to update key parameters of the multi-scale model so that the errors between the measured and predicted structural dynamic characteristics and multi-scale responses can be minimized. To improve the computational efficiency and accuracy of optimization, the Kriging meta-method is used to find the updated key parameters of the tower after a comparison with other meta-methods is made. Finally, the proposed method is applied to a physical transmission tower model, which has been tested in a laboratory, to demonstrate the feasibility and accuracy of the proposed model-updating method. The updated results show that the proposed updating method can improve the accuracy of the multi-scale model of the tower in both global and local structural responses. [ABSTRACT FROM AUTHOR]

Based on prior work, a cellulase from glycosyl hydrolase family 7 (GHF7) was identified and found to be expressed at a high level in Coptotermes formosanus. To determine the function of GHF7 family members in vivo, we used RNA interference (RNAi) to functionally analyse the exoglucanase gene Pseudotrichonympha grassii cellobiohydrolase gene (PgCBH), which was highly expressed in Pseudotrichonympha grassii, a flagellate found in the hindgut of C. formosanus. In this study, the expression level of PgCBH was down-regulated by RNAi, causing the death of P. grassii, but no effect was observed for other flagellates found in C. formosanus. RNAi also resulted in significantly reduced exoglucanase activity, and no effect was observed for endoglucanase and β-glucosidase activities. This result demonstrated that the PgCBH gene plays a role in the protist lignocellulolytic process and is also important for host survival. PgCBH can be used as a target gene and has potential as a bioinsecticide for use against termites. [ABSTRACT FROM AUTHOR]