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Abstract Background Whether programmed cell death-1/ligand-1 (PD-1/PD-L1) blockade-based neoadjuvant treatment may benefit locally advanced oncogene-mutant non–small cell lung cancer (NSCLC) patients remains controversial. This retrospective study was designed to observe the efficacy and safety of neoadjuvant PD-1/PD-L1 blockade plus chemotherapy versus chemotherapy and corresponding tyrosine kinase inhibitors (TKIs) in patients with resectable oncogene-positive NSCLC. Methods Patients with potential resectable NSCLC harbouring oncogene alterations who had received neoadjuvant treatment were retrospectively recruited, and an oncogene-negative cohort of patients who received neoadjuvant PD-(L)1 blockade-based neoadjuvant treatment was reviewed for comparison during the same period. The primary aim was to observe the treatment efficacy and event-free survival (EFS) of these agents. Safety profile, molecular target, and immunologic factor data, including PD-L1 expression and tumour mutational burden (TMB), were also obtained. Results A total of 46 patients were recruited. Thirty-one of them harboured oncogene alterations, including EGFR, KRAS, ERBB2, ROS1, MET, RET, ALK, and FGFR3 alterations. Among the oncogene-positive patients, 18 patients received neoadjuvant PD-(L)1 blockade immunotherapy plus chemotherapy (oncogene-positive IO group), 13 patients were treated with neoadjuvant chemotherapy and/or corresponding TKIs or TKIs alone (oncogene-positive chemo/TKIs group), and the other 15 patients were oncogene negative and received neoadjuvant PD-(L)1 blockade plus chemotherapy (oncogene-negative IO group). The pathological complete response (pCR) and major pathological response (MPR) rates were 22.2% (4 of 18) and 44.4% (8 of 18) in the oncogene-positive IO group, 0% (P = 0.120) and 23.1% (3 of 13) (P = 0.276) in the oncogene-positive chemo/TKIs group, and 46.7% (7 of 15) (P = 0.163) and 80.0% (12 of 15) (P = 0.072) in the oncogene-negative IO group, respectively. By the last follow-up, the median EFS time had not reached in the oncogene-positive IO group, and was 29.5 months in the oncogene-positive chemo/TKIs group and 38.4 months in the oncogene-negative IO group. Conclusion Compared with chemotherapy/TKIs treatment, neoadjuvant treatment with PD-(L)1 blockade plus platinum-based chemotherapy was associated with higher pCR/MPR rates in patients with partially resectable oncogene-mutant NSCLC, while the pCR/MPR rates were lower than their oncogene-negative counterparts treated with PD-(L)1 blockade-based treatment. Specifically, oncogene alteration types and other predictors of response to immunotherapy should be taken into account in clinical practice.

Abstract Background Liver kinase B1 (LKB1) is frequently mutated in lung adenocarcinoma, and its loss contributes to tumor progression. Methods To identify LKB1 downstream genes that promote lung adenocarcinoma aggressiveness, we performed bioinformatical analysis using publicly available datasets. Results Rab3B was upregulated in LKB1-depleted lung adenocarcinoma cells and suppressed by LKB1 overexpression. CREB protein was enriched at the promoter of Rab3B in lung cancer cells. Silencing of CREB abrogated the upregulation of Rab3B upon LKB1 loss. Immunohistochemistry revealed the elevated expression of Rab3B in lung adenocarcinomas relative to adjacent normal tissues. Upregulation of Rab3B was significantly associated with lymph node metastasis, advanced tumor stage, and reduced overall survival in lung adenocarcinoma patients. Knockdown of Rab3B suppressed and overexpression of Rab3B promoted the proliferation, colony formation, and migration of lung adenocarcinoma cells in vitro. In a mouse xenograft model, Rab3B depletion restrained and Rab3B overexpression augmented the growth of lung adenocarcinoma tumors. Mechanistically, Rab3B interacted with DDX6 and enhanced its protein stability. Ectopic expression of DDX6 significantly promoted the proliferation, colony formation, and migration of lung adenocarcinoma cells. DDX6 knockdown phenocopied the effects of Rab3B depletion on lung adenocarcinoma cells. Additionally, DDX6 overexpression partially rescued the aggressive phenotype of Rab3B-depleted lung adenocarcinoma cells. Conclusion LKB1 deficiency promotes Rab3B upregulation via a CREB-dependent manner. Rab3B interacts with and stabilizes DDX6 protein to accelerate lung adenocarcinoma progression. The Rab3B-DDX6 axis may be potential therapeutic target for lung adenocarcinoma.

Abstract Background To develop a magnetic resonance imaging (MRI)-based radiomics signature for evaluating the risk of soft tissue sarcoma (STS) disease progression. Methods We retrospectively enrolled 335 patients with STS (training, validation, and The Cancer Imaging Archive sets, n = 168, n = 123, and n = 44, respectively) who underwent surgical resection. Regions of interest were manually delineated using two MRI sequences. Among 12 machine learning-predicted signatures, the best signature was selected, and its prediction score was inputted into Cox regression analysis to build the radiomics signature. A nomogram was created by combining the radiomics signature with a clinical model constructed using MRI and clinical features. Progression-free survival was analyzed in all patients. We assessed performance and clinical utility of the models with reference to the time-dependent receiver operating characteristic curve, area under the curve, concordance index, integrated Brier score, decision curve analysis. Results For the combined features subset, the minimum redundancy maximum relevance-least absolute shrinkage and selection operator regression algorithm + decision tree classifier had the best prediction performance. The radiomics signature based on the optimal machine learning-predicted signature, and built using Cox regression analysis, had greater prognostic capability and lower error than the nomogram and clinical model (concordance index, 0.758 and 0.812; area under the curve, 0.724 and 0.757; integrated Brier score, 0.080 and 0.143, in the validation and The Cancer Imaging Archive sets, respectively). The optimal cutoff was − 0.03 and cumulative risk rates were calculated. Data conclusion To assess the risk of STS progression, the radiomics signature may have better prognostic power than a nomogram/clinical model.

This is an article in the field of ceramics and composites. In order to explore the resistance of basalt fiber to acid and alkali corrosion, basalt fiber with or without wetting agent was soaked in 3 mol/L sulfuric acid solution and sodium hydroxide solution, respectively, and the mass loss rate, fracture force retention rate and SEM image of fiber surface were tested. The results showed that with the increase of soaking time, the mass loss rate of basalt fiber with infiltrating agent increased from 1.42% to 7.33%, the fracture force retention rate decreased from 95.34% to 66.49%, the mass loss rate of basalt fiber without infiltrating agent increased from 3.69% to 9.40% and the fracture force retention rate decreased from 88.39% to 53.64%. After soaking in sodium hydroxide solution, the mass loss rate of basalt fiber with wetting-agent increased from 0.40% to 5.41%, the fracture force retention rate decreased from 97.37% to 79.82%, the mass loss rate of basalt fiber without wetting-agent increased from 1.50% to 7.08%, and the fracture force retention rate decreased from 93.42% to 69.85%. Both acid-alkaline corrosion cause fiber quality loss, increase fiber surface defects and reduce fiber breaking force.Sulfuric acid solution with the same concentration corrodes basalt fiber more seriously than sodium hydroxide solution. The soaking agent has a protective effect on the fiber and can slow down the corrosion of acid and alkali on the fiber.

Abstract Objective To establish a model for predicting lymph node metastasis in bladder cancer (BCa) patients. Methods We retroactively enrolled 239 patients who underwent three-phase CT and resection for BCa in two centers (training set, n = 185; external test set, n = 54). We reviewed the clinical characteristics and CT features to identify significant predictors to construct a clinical model. We extracted the hand-crafted radiomics features and deep learning features of the lesions. We used the Minimum Redundancy Maximum Relevance algorithm and the least absolute shrinkage and selection operator logistic regression algorithm to screen features. We used nine classifiers to establish the radiomics machine learning signatures. To compensate for the uneven distribution of the data, we used the synthetic minority over-sampling technique to retrain each machine-learning classifier. We constructed the combined model using the top-performing radiomics signature and clinical model, and finally presented as a nomogram. We evaluated the combined model’s performance using the area under the receiver operating characteristic, accuracy, calibration curves, and decision curve analysis. We used the Kaplan–Meier survival curve to analyze the prognosis of BCa patients. Results The combined model incorporating radiomics signature and clinical model achieved an area under the receiver operating characteristic of 0.834 (95% CI: 0.659–1.000) for the external test set. The calibration curves and decision curve analysis demonstrated exceptional calibration and promising clinical use. The combined model showed good risk stratification performance for progression-free survival. Conclusion The proposed CT-based combined model is effective and reliable for predicting lymph node status of BCa patients preoperatively. Critical relevance statement Bladder cancer is a type of urogenital cancer that has a high morbidity and mortality rate. Lymph node metastasis is an independent risk factor for death in bladder cancer patients. This study aimed to investigate the performance of a deep learning radiomics model for preoperatively predicting lymph node metastasis in bladder cancer patients. Key points • Conventional imaging is not sufficiently accurate to determine lymph node status. • Deep learning radiomics model accurately predicted bladder cancer lymph node metastasis. • The proposed method showed satisfactory patient risk stratification for progression-free survival. Graphical Abstract

Objective This study examined the effects of sildenafil on acute pulmonary embolism (APE) using a rat model. Methods Sprague–Dawley rats were randomly divided into the sham, pulmonary thromboembolism (PTE), and sildenafil groups. The sham and PTE groups received normal saline once daily via gavage for 14 consecutive days, whereas the sildenafil group received sildenafil (0.5 mg/kg/day) once daily via gavage for 14 consecutive days. Autologous emboli were prepared from blood samples collected from the left femoral artery of rats in each group on day 13, and autologous emboli were injected into the jugular vein cannula of rats in the PTE and sildenafil groups on day 14. Sham-treated rats received the same volume of saline. Right systolic ventricular pressure (RVSP) and mean pulmonary arterial pressure (MPAP) were used to assess pulmonary embolism, and western blotting and enzyme-linked immunosorbent assay were used to detect relevant markers. Results The Rho kinase signaling pathway was significantly activated in rats with APE, and sildenafil significantly inhibited this activation. Conclusions Sildenafil protected against APE through inhibiting Rho kinase activity, thereby reducing pulmonary vasoconstriction and decreasing elevated pulmonary arterial pressure. These findings might provide new ideas for the clinical treatment of acute pulmonary thromboembolism.

Abstract The handheld X-ray fluorescence spectrometer (HH-XRF) is commonly used to detect the inorganic elemental composition of pigments on-site. However, the accuracy of in-situ detection results can be affected by the characteristics of the painted surface contaminants and the layered structure of pigments in ancient architectural color paintings. To mitigate this error, a method was proposed that combined the XRF spectra of inorganic pigments with the elemental concentration values obtained through principal component analysis (PCA). Additionally, this study discussed the typical surface contaminants and pigment layering found in color paintings separately. Firstly, experiments were conducted on dust accumulation layers of varying thicknesses. The results indicated that the condition of color paintings after pretreatment of dust accumulation tended to resemble the situation with thin dust accumulation during in-situ testing. A fitting formula was derived to establish a relationship between field testing and laboratory testing results. Secondly, experiments were conducted using various combinations of pigment layers. Based on the findings, it was hypothesized that there was a connection between XRF detection results and the maximum concentration value of a single element (as determined by XRF, in an unmixed or unlayered pigment sample without dust or smoke accumulation). The test results were fitted using a Polynomial formula, providing evidence for the existence of a nonlinear functional relationship between these two variables. Finally, an empirical formula for predicting the concentration values of the top color layer with different base colors was proposed. This study offered a precise method for accurately assessing pigments of ancient architectural color paintings through in-situ testing.

Mullite fiber felt is a promising material that may fulfill the demands of advanced flexible external thermal insulation blankets. However, research on the fabrication and performance of mullite fiber felt with high-temperature resistance and thermal stability is still lacking. In this work, mullite fibers were selected as raw materials for the fabrication of mullite fibrous porous materials with a three-dimensional net structure. Said materials’ high-temperature resistance and thermal stability were investigated by assessing the effects of various heat treatment temperatures (1100 °C, 1300 °C, and 1500 °C) on the phase composition, microstructure, and performance of their products. When the heat treatment temperature was below 1300 °C, both the phase compositions and microstructures of products exhibited stability. The compressive rebound rate of the product before and after 1100 °C reached 92.9% and 84.5%, respectively. The backside temperature of the as-prepared products was 361.6 °C when tested at 1500 °C for 4000 s. The as-prepared mullite fibrous porous materials demonstrated excellent high-temperature resistance, thermal stability, thermal insulation performance, and compressive rebound capacity, thereby indicating the great potential of the as-prepared mullite fibrous porous materials in the form of mullite fiber felt within advanced flexible external thermal insulation blankets.

The porous metal foams are potential to integrate phase change materials (PCMs) to form the shape-stabilized composited PCMs for the applications of thermal energy management and temperature regulation. However, the effect of porosity distribution of foam keeps challenging in designing such PCM-based composites. In this work, the closed-cell graded porosity foams (GPFs) involving various gradient directions and gradient differences of porosity are engineered by shrinking Voronoi tessellations to achieve precisely tunable microstructure. Then the GPF/PW composite is formed by integrating paraffin wax (PW) in each pore and its melting performance is investigated by the computational model, which is validated by the melting experiment of a specific sample. The investigations on the gradient configurations of foams reveal that the gradient direction and gradient difference of porosity have significant influences on the pore-scale melting behavior, liquid fraction variation in time and overall energy storage efficiency of PW. The positive gradient variation along the direction of heating source and the moderate gradient difference, i.e. 20% or 30%, are beneficial to improve the melting behavior of graded models. In contrast to the uniform model, the complete melting time of the graded models can maximum shorten by 5.6%, 3.8% and 3.7% for the bottom, lateral and top heating modes, respectively.

Thermal protection of high temperature turbine restricts the performance of gas turbine. In order to increase turbine inlet temperature, water phase change rotating cooling scheme for turbine was proposed for using the gasification latent heat to improve cooling capacity. Numerical model of phase change rotating cooling was established to study the flow and heat transfer characteristics with Ansys CFX software using SST k-ω turbulence model. Results showed that phase change rotating cooling had good performance for cooling the rotating blades. The temperature drops of blades were more than 400 K with the average heat flux of 2.42 MW/m2. Due to the influence of flow thermal acceleration effect, the outlet pressure of cooling channel reached a maximum value of 7.23 MPa with a mass flow rate of 0.17 g/s. The outlet quality distribution under rotating condition was relatively uniform than nonrotating condition. The temperature increased firstly and then decreased in centripetal channel along phase change process because of pressure variation. Meanwhile, gas-liquid interface disappeared due to the Coriolis force, resulting in higher heat transfer coefficient than static condition. The normalized Nusselt number (Nus) of phase change rotating cooling reached 3.915, much higher than static liquid cooling.

Automatic speech recognition (ASR) has been an active area of research. Training with large annotated datasets is the key to the development of robust ASR systems. However, most available datasets are focused on high-resource languages like English, leaving a significant gap for low-resource languages. Among these languages is Punjabi, despite its large number of speakers, Punjabi lacks high-quality annotated datasets for accurate speech recognition. To address this gap, we introduce three labeled Punjabi speech datasets: Punjabi Speech (real speech dataset) and Google-synth/CMU-synth (synthesized speech datasets). The Punjabi Speech dataset consists of read speech recordings captured in various environments, including both studio and open settings. In addition, the Google-synth dataset is synthesized using Google's Punjabi text-to-speech cloud services. Furthermore, the CMU-synth dataset is created using the Clustergen model available in the Festival speech synthesis system developed by CMU. These datasets aim to facilitate the development of accurate Punjabi speech recognition systems, bridging the resource gap for this important language.

Abstract Hydrogen peroxide (H2O2) production by the electrochemical 2‐electron oxygen reduction reaction (2e− ORR) is a promising alternative to the energy‐intensive anthraquinone process, and single‐atom electrocatalysts show the unique capability of high selectivity toward 2e− ORR against the 4e− one. The extremely low surface density of the single‐atom sites and the inflexibility in manipulating their geometric/electronic configurations, however, compromise the H2O2 yield and impede further performance enhancement. Herein, we construct a family of multiatom catalysts (MACs), on which two or three single atoms are closely coordinated to form high‐density active sites that are versatile in their atomic configurations for optimal adsorption of essential *OOH species. Among them, the Cox–Ni MAC presents excellent electrocatalytic performance for 2e− ORR, in terms of its exceptionally high H2O2 yield in acidic electrolytes (28.96 mol L−1 gcat.−1 h−1) and high selectivity under acidic to neutral conditions in a wide potential region (>80%, 0–0.7 V). Operando X‐ray absorption and density functional theory analyses jointly unveil its unique trimetallic Co2NiN8 configuration, which efficiently induces an appropriate Ni–d orbital filling and modulates the *OOH adsorption, together boosting the electrocatalytic 2e− ORR capability. This work thus provides a new MAC strategy for tuning the geometric/electronic structure of active sites for 2e− ORR and other potential electrochemical processes.

Abstract Background To construct and assess a computed tomography (CT)-based deep learning radiomics nomogram (DLRN) for predicting the pathological grade of bladder cancer (BCa) preoperatively. Methods We retrospectively enrolled 688 patients with BCa (469 in the training cohort, 219 in the external test cohort) who underwent surgical resection. We extracted handcrafted radiomics (HCR) features and deep learning (DL) features from three-phase CT images (including corticomedullary-phase [C-phase], nephrographic-phase [N-phase] and excretory-phase [E-phase]). We constructed predictive models using 11 machine learning classifiers, and we developed a DLRN by combining the radiomic signature with clinical factors. We assessed performance and clinical utility of the models with reference to the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). Results The support vector machine (SVM) classifier model based on HCR and DL combined features was the best radiomic signature, with AUC values of 0.953 and 0.943 in the training cohort and the external test cohort, respectively. The AUC values of the clinical model in the training cohort and the external test cohort were 0.752 and 0.745, respectively. DLRN performed well on both data cohorts (training cohort: AUC = 0.961; external test cohort: AUC = 0.947), and outperformed the clinical model and the optimal radiomic signature. Conclusion The proposed CT-based DLRN showed good diagnostic capability in distinguishing between high and low grade BCa.

Abstract Electrocatalytic hydrogen peroxide (H2O2) production via the two-electron oxygen reduction reaction is a promising alternative to the energy-intensive and high-pollution anthraquinone oxidation process. However, developing advanced electrocatalysts with high H2O2 yield, selectivity, and durability is still challenging, because of the limited quantity and easy passivation of active sites on typical metal-containing catalysts, especially for the state-of-the-art single-atom ones. To address this, we report a graphene/mesoporous carbon composite for high-rate and high-efficiency 2e− oxygen reduction catalysis. The coordination of pyrrolic-N sites -modulates the adsorption configuration of the *OOH species to provide a kinetically favorable pathway for H2O2 production. Consequently, the H2O2 yield approaches 30 mol g−1 h−1 with a Faradaic efficiency of 80% and excellent durability, yielding a high H2O2 concentration of 7.2 g L−1. This strategy of manipulating the adsorption configuration of reactants with multiple non-metal active sites provides a strategy to design efficient and durable metal-free electrocatalyst for 2e− oxygen reduction.

Abstract Workflow scheduling is vital to simultaneously minimize execution cost and makespan for cloud platforms since data dependencies among large-scale workflow tasks and cloud workflow scheduling problem involve large-scale interactive decision variables. So far, the cooperative coevolution approach poses competitive superiority in resolving large-scale problems by transforming the original problems into a series of small-scale subproblems. However, the static transformation mechanisms cannot separate interactive decision variables, whereas the random transformation mechanisms encounter low efficiency. To tackle these issues, this paper suggests a decision-variable-contribution-based adaptive evolutionary cloud workflow scheduling approach (VCAES for short). To be specific, the VCAES includes a new estimation method to quantify the contribution of each decision variable to the population advancement in terms of both convergence and diversity, and dynamically classifies the decision variables according to their contributions during the previous iterations. Moreover, the VCAES includes a mechanism to adaptively allocate evolution opportunities to each constructed group of decision variables. Thus, the decision variables with a strong impact on population advancement are assigned more evolution opportunities to accelerate population to approximate the Pareto-optimal fronts. To verify the effectiveness of the proposed VCAES, we carry out extensive numerical experiments on real-world workflows and cloud platforms to compare it with four representative algorithms. The numerical results demonstrate the superiority of the VCAES in resolving cloud workflow scheduling problems.

Summary: Background: Accurate stratification of recurrence risk for bladder cancer (BCa) is essential for precise individualized therapy. This study aimed to develop and validate a model for predicting the risk of recurrence in BCa patients postoperatively using 3-phase enhanced CT images. Methods: We retrospectively enrolled 874 BCa patients across four centers between January 2006 and December 2021. Patients from one center were used as training set, while the remaining patients went into the validation set. We trained a deep learning (DL) model based on convolutional neural networks using 3-phase enhanced CT images. The resulting prediction scores were entered into Cox regression analysis to obtain DL scores and construct a DL signature. DL scores and clinical features were then used as deep learning radioclinical signature. The predictive performance of DL signature was assessed according to concordance index and area under curve compared with deep learning radioclinical signature, clinical model and a widely accepted staging grading system. Recurrence-free survival (RFS) and overall survival (OS) were also predicted in order to further assess survival benefits. Findings: DL signature showed strong power for predicting recurrence (concordance index, 0.869; area under curve, 0.889) in validation set, outperforming other models and system. In addition, we divided RFS and OS into high and low risk groups by selecting appropriate cutoff values for DL signature, and calculated cumulative recurrence risk rates for both groups. Interpretation: Our proposed DL signature shows promising potential as clinical aid for predicting postoperative recurrence risk in BCa and for stratifying the risk of RFS and OS, which can be applied to guide personalized precision therapy. Funding: There are no sources of funding for this manuscript.

High-performance aqueous zinc ion batteries (ZIBs) are of huge potential in utilizing renewable and clean energy sources. However, the single inorganic or organic cathodes for ZIBs, suffering from poor electron/ion conductivity, limited active sites, and unstable structure, are difficult to achieve this task. Fortunately, the inorganic-organic hybrid strategy shows integrated advantages in overcoming these drawbacks, and a detailed overview of the recent progress of organic-inorganic hybrid cathodes for ZIBs and clear the internal synergy mechanism should be helpful to provide a systematic understanding of the latest progress in this field and further achieve higher Zn-storage performance. Herein, the types and advantages of organic-inorganic hybrid cathodes for ZIBs are first introduced. Secondly, a summarization of the advantages and application of organic-inorganic hybrid cathodes in ZIBs, from promoting the electron/ion conductivity, combining more active sites for Zn-storage, stabilizing structure integrity and improving the overall performances, is presented. Finally, the prospects and challenges of organic-inorganic hybrid cathodes towards ZIBs with much higher performance are presented, which should shed light on the future scientific research and practical application of organic-inorganic hybrid cathodes in energy storage fields.

Ceramic fiber thread is one of the key components in flexible external thermal insulation blankets, and it has been applied in various fields as a flexible ceramic fibrous material with excellent deformability and high-temperature resistance. However, ceramic fiber threads are often subjected to reciprocating friction motion at specific bending angles, making them highly susceptible to abrade and fracture. Enhancing the abrasion resistance performance of ceramic fiber threads under bending conditions is the future trend and remains a significant challenge. Hence, we design and construct a novel polyurethane-modified coating on the ceramic fiber threads to improve their abrasion resistance performance. The effects of the types and concentrations of modifiers on the microstructure, abrasion resistance property, and tensile property of ceramic fiber threads are systematically investigated. The ceramic fiber threads, after modification with hexamethylene diisocyanate waterborne polyurethane (HDI-WPU) with a concentration of 3%, exhibit excellent abrasion resistance properties. The number of friction cycles at fracture of the modified ceramic fiber thread is more than three times, and the tensile strength is more than one and a half times, that of the original ceramic fiber thread, demonstrating the great potential of the HDI-WPU modifier for enhancing the abrasion resistance performance of ceramic fiber threads.

Abstract Carbon nitride, an emerging polymeric semiconductor, has attracted attention in research ranging from photocatalysis to photodetection due to its favorable visible light response and high physicochemical stability. For its practical device application, the fabrication of high‐quality carbon nitride films on substrates is essential. However, conventional methodologies to achieve high polymerization of carbon nitride are often accompanied by its decomposition, significantly compromising the film quality. Herein, we report an ultrafast fabrication of carbon nitride film by laser direct writing (LDW). The instantaneous high temperature and pressure during LDW can efficiently boost the polymerization of carbon nitride and suppress its decomposition, resulting in high‐quality carbon nitride film with excellent mechanical stability with the substrate. Due to the efficient photon‐to‐electron conversion, it exhibits an outstanding photoelectrochemical water splitting and optoelectronic detection capability, even under strong acid/alkaline conditions. This study thus offers a facile and efficient LDW strategy for the rapid fabrication of carbon nitride film photoelectrodes, demonstrating its great feasibility in multifunctional photoelectrical applications, including but not limited to photoelectrochemical water splitting and optoelectronic detection.

Hybrid Deposition and Micro Rolling (HDMR) is a hybrid technology combining in-situ rolling with Wire and Arc Additive Manufacturing (WAAM). With better performance in products than the conventional approach, the advantages in environmental contribution remain to be studied. Traditional methods in environmental evaluation are mostly based on Life Cycle Assessment (LCA), which can have further refinement in a short process like HDMR. This paper proposed a bionic computing method of industrial metabolism, proactively designed the ecological index, and comprehensively evaluated the environmental impact of manufacturing system. Material and energy flows in whole processes were tracked to obtain accurate quantitative data on the energy efficiency and carbon emission scenarios of long and short process manufacturing systems. This paper took the manufacture of a titanium alloy part as an example, the CO2 metabolism and energy metabolism produced by HDMR and Conventional Manufacturing (CM) with a long process were compared. The results show that CO2 emissions of the given part deposited by HDMR is 181.29kg, and that of the same part fabricated by CM is 2612.81kg. The CO2 emission intensities of the given part by HDMR and CM are 7.17kg/kgand 95.32kg/kgrespectively. The total carbon emission and emission intensity of CM are 14.41 times and 13.29 times than that of HDMR respectively. In addition, the manufacturing time of HDMR is reduced by approximately 67% comparing with CM. The material utilization rate of HDMR is 2.6 times higher than that of CM. Therefore, it can be proved that HDMR has huge advantages over conventional manufacturing processes in terms of CO2 emission efficiency and emission intensity, specific energy consumption, energy efficiency, and material utilization. It is an energy-saving, emission-reducing, sustainable green manufacturing process.

Abstract As a type of titanate, the pseudobrookite (MTi2O5/M2TiO5) exhibits a low thermal expansion coefficient and thermal conductivity, as well as excellent dielectric and solar spectrum absorption properties. However, the pseudobrookite is unstable and prone to decomposing below 1200 °C, which limits the practical application of the pseudobrookite. In this paper, the high-entropy pseudobrookite ceramic is synthesized for the first time. The pure high-entropy (Mg,Co,Ni,Zn)Ti2O5 with the pseudobrookite structure and the biphasic high-entropy ceramic composed of the high-entropy pseudobrookite (Cr,Mn,Fe,Al,Ga)2TiO5 and the high-entropy spinel (Cr,Mn,Fe,Al,Ga,Ti)3O4 are successfully prepared by the in-situ solid-phase reaction method. The comparison between the theoretical crystal structure of the pseudobrookite and the aberration-corrected scanning transmission electron microscopy (AC-STEM) images of high-entropy (Mg,Co,Ni,Zn)Ti2O5 shows that the metal ions (M and Ti ions) are disorderly distributed at the A site and the B site in high-entropy (Mg,Co,Ni,Zn)Ti2O5, leading to an unprecedentedly high configurational entropy of high-entropy (Mg,Co,Ni,Zn)Ti2O5. The bulk high-entropy (Mg,Co,Ni,Zn)Ti2O5 ceramics exhibit a low thermal expansion coefficient of 6.35×10−6 K−1 in the temperature range of 25–1400 °C and thermal conductivity of 1.840 W·m−1·K−1 at room temperature, as well as the excellent thermal stability at 200, 600, and 1400 °C. Owing to these outstanding properties, high-entropy (Mg,Co,Ni,Zn)Ti2O5 is expected to be the promising candidate for high-temperature thermal insulation. This work has further extended the family of different crystal structures of high-entropy ceramics reported to date.

Abstract Producing hydrogen peroxide (H2O2) via a two‐electron oxygen reduction reaction (2 e−‐ORR) is a promising alternative to the conventional anthraquinone process, because of its exceptional low‐risk and distributed features. The low yield of H2O2 on typical electrocatalysts, usually associated with limited and vulnerable catalytically active sites on their surface, has been the major restriction for improving the practical viability of this technology. Herein, we report an ultrafast microwave‐based strategy for constructing distant coordination of Co single‐atom sites with secondary fluorene heterodopants on carbon nanotubes, which successfully converts the 2 e−‐ORR active centers from a single Co atom to multiple surrounding carbon atoms, increasing both the quantity and durability of active sites for 2 e−‐ORR. Consequently, a high H2O2 yield of up to 18.6 mol g−1 L−1 has been achieved, accompanied by a Faraday efficiency of 90%. Besides, an accumulative H2O2 concentration of 5.2 g L−1 is obtained after 20 h electrocatalysis, showing the material's high stability and feasibility for practical applications. Density functional theory simulations confirm the optimal adsorption of *OOH on these carbon sites, providing very low kinetic barriers for 2 e−‐ORR. Thus, this work provides a high‐performance electrocatalyst for 2 e−‐ORR, and more importantly strategy for promoting the performance of single‐atom catalysts.

The use of robots to perform tasks in extreme environments instead of humans has gradually become important. For wider applications, robots should be able to adapt to complex environments, such as typical height/width-restricted motion spaces, raised obstacles, and ravines. The structure is the foundation of robot to move and perform tasks. In this study, a variable-attitude robot mechanism is designed and analyzed. With the link leg drive and Mecanum wheel drive, the robot has various configurations and omnidirectional motion capabilities. First, the design and analysis of the wheel drive system are performed, and the mapping relationship between the velocity of the robot and the velocity of the Mecanum wheel is clarified. Second, kinematics of the linkage drive system is analyzed, including the motion space, trajectory characteristics, and the effect of variable axle spacing on the robot motion performance. Subsequently, a simulation is used to verify the rationality of the three motion modes of the robot: walking, wheel drive, and hybrid drive. Finally, a motion simulation of several typical configuration changes in the robot is observed, and the feasibility of the robot mechanism to adapt to a complex environment is verified. This study contributes to the development and application of special advanced robots.

Abstract Layered vanadium oxides are promising cathode materials for zinc‐ion batteries (ZIBs) owing to their high capacity, but the sluggish electron/ion migration kinetics and structural collapse/dissolution severely limit their Zn2+‐storage performance. Herein, poly(3,4‐ethylenedioxythiophene) coated and Mn2+‐intercalated vanadium oxides with rich oxygen vacancies (MnVOH@PEDOT) are prepared as the cathodes for ZIBs. The PEDOT coating, synergistic with oxygen vacancies, tailors the electron conductivity, and the Mn2+‐intercalation enlarges the interlayer spacing for rapid Zn2+‐ions diffusion. In addition, the pre‐intercalated Mn2+‐ions act as “pillars” to stabilize the structure, and the PEDOT coating prevents the direct contact of vanadium oxides with electrolyte to inhibit its dissolution during cycling. Thus, the MnVOH@PEDOT cathode exhibits superior discharge capacity, favorable rate capability (336.0 mAh g−1 at 8 A g−1), and satisfying cyclic durability (84.8% capacity retention over 2000 cycles). This work offers a facile and synergistic design strategy for achieving favorable cathodes for ZIBs.

IntroductionLive stream-watching has become increasingly popular worldwide. Consumers are found to watch streams in a continuous manner. Despite its popularity, there has been limited research investigating why consumers continue to watch streams. Previously, the expectation-confirmation theory (ECT) has been widely adopted to explain users’ continuance intention. However, most current ECT-based models are theoretically incomplete, since they only consider the importance of perceived benefits without considering users’ costs and sacrifices. In this paper, we propose a value-based continuance intention model (called V-ECM), and use it to investigate factors influencing consumers’ continuance intention to watch streams.MethodsOur hypotheses were tested using an online survey of 1,220 consumers with continuance stream-watching experiences.ResultsResults indicate that perceived value, a process of an overall assessment between users’ perceived benefits and perceived sacrifices, is proved to be a better variable than perceived benefits in determining consumers’ continuance watching intention. Also, compared with other ECT-based models, V-ECM is a more comprehensive model to explain and predict consumers’ continuance intention.DiscussionV-ECM theoretically extends ECT-based studies, and it has potential to explain and predict other continuance intentions in online or technology-related contexts. In addition, this paper also discusses practical implications for live streaming platforms with regards to their design, functions and marketing.

BackgroundPulmonary arterial hypertension (PAH) is a fatal disease characterized by pulmonary vascular remodeling and increased pulmonary artery pressure, leading to impaired lung oxygenation, right heart failure, and even death. Although great advances have been made in PAH-targeted medications for pediatric patients, the efficacy and safety of these treatments are controversial.MethodsWe retrieved relevant articles from electronic databases including PubMed, EMBASE, Web of Science, and Cochrane Library until 12 April 2022. To compare the effectiveness and safety of endothelin receptor antagonists (ERAs), phosphodiesterase type 5 Inhibitors (PDE-5i), and prostaglandins (ProA) in the treatment of pediatric PAH, we investigated six hemodynamic parameters, four respiratory parameters, intensive care unit (ICU) stay duration, length of hospital stay, and two safety outcomes.ResultsA total of 27 randomized controlled trials (RCTs) were included in the meta-analysis with 1,574 pediatric participants. The duration of mechanical ventilation was shorter for patients using bosentan, sildenafil, and ProsA, compared with that for patients using the placebo. Bosentan helped to shorten more time for mechanical ventilation than ProsA did, while ProsA was more effective than sildenafil in this respect. As for the length of stay in the ICU, patients administered by ProsA or sildenafil needed shorter ICU stay, compared to those using the placebo, while ProsA was more effective for shortening ICU stay time. In light of safety outcomes, there was a statistically significant difference between the sildenafil and the placebo group. Sildenafil surpassed ProsA in reducing the incidence of pulmonary hypertension (PH) crisis.ConclusionsERAs were more effective than ProsA in shortening the duration of mechanical ventilation, while ProsA were better for shortening the duration of mechanical ventilation and ICU stay than PDE-5i. PDE-5i were found to generate more benefits in decreasing the occurrence of PH crisis, though further investigation is warranted.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=351505.

PURPOSEKnowing the genetic phenotype of gastrointestinal stromal tumors (GISTs) is essential for patients who receive therapy with tyrosine kinase inhibitors. The aim of this study was to develop a radiomic algorithm for predicting GISTs with KIT exon 11 mutation.METHODSWe enrolled 106 patients (80 in the training set, 26 in the validation set) with clinicopathologically confirmed GISTs from two centers. Preoperative and postoperative clinical characteristics were selected and analyzed to construct the clinical model. Arterial phase, venous phase, delayed phase, and tri-phase combined radiomics algorithms were generated from the training set based on contrast-enhanced computed tomography (CE-CT) images. Various radiomics feature selection methods were used, namely least absolute shrinkage and selection operator (LASSO); minimum redundancy maximum relevance (mRMR); and generalized linear model (GLM) as a machine-learning classifier. Independent predictive factors were determined to construct preoperative and postoperative radiomics nomograms by multivariate logistic regression analysis. The performances of the clinical model, radiomics algorithm, and radiomics nomogram in distinguishing GISTs with the KIT exon 11 mutation were evaluated by area under the curve (AUC) of the receiver operating characteristics.RESULTSOf 106 patients who underwent genetic analysis, 61 had the KIT exon 11 mutation. The combined radiomics algorithm was found to be the best prediction model for differentiating the expression status of the KIT exon 11 mutation (AUC = 0.836; 95% confidence interval [CI], 0.640-0.951) in the validation set. The clinical model, and preoperative and postoperative radiomics nomograms had AUCs of 0.606 (95% CI, 0.397-0.790), 0.715 (95% CI, 0.506-0.873), and 0.679 (95% CI, 0.468-0.847), respectively, with the validation set.CONCLUSIONThe radiomics algorithm could distinguish GISTs with the KIT exon 11 mutation based on CE-CT images and could potentially be used for selective genetic analysis to support the precision medicine of GISTs.

Aqueous zinc-ion batteries (ZIBs) have been regarded as a promising alternative to traditional lithium-based batteries due to their intrinsic advantages of safety, low cost, and abundance. However, the strong electrostatic interaction between Zn2+ and the layer-structured cathodes is still a key issue that hinders the batteries from storing more Zn. Herein, we report partially nitrided and cation-doped vanadium oxide for improved Zn storage performance. Specifically, the defects and nitride species that are generated inside the material upon nitriding improve the conductivity of the material and introduce a new Zn storage mechanism. The intercalation of cations, in contrast, widens the interlayer spacing to store more Zn2+ ions and enhances the cycling stability of the material. These merits synergistically lead to significantly enhanced electrochemical Zn2+ ion storage performance, in terms of a high specific capacity of 418.5 mAh·g−1 at a current density of 0.1 A·g−1 and a capacity retention of 81.2% after 500 cycles at 2.0 A·g−1. The new modification strategy for V2O5 suggested in this work could provide insight into the development of high-performance ZIBs.

The world’s energy crisis and environmental pollution are mainly caused by the increase in the use of fossil fuels for energy, which has led scientists to investigate specific cutting-edge devices that can capture the energy present in the immediate environment for subsequent conversion. The predominant form of energy is mechanical energy; it is the most prevalent energy in the environment and can be harvested for conversion into useful, electrical energy. Compared with electromagnetic, electrostatic, magneto strictive, dielectric elastomer and frictional electric transducers, piezoelectric transducers have higher high electrical and mechanical constants, large electromechanical coupling coefficients, high dielectric numbers and low losses and are currently the most dominant method of mechanical energy acquisition. Therefore, the research of piezoelectric transducers has received great attention from the scientific community. This paper reviews the research progress of piezoelectric energy acquisition technology. The main objective of this paper is to compile, discuss and summarize the recent literature on piezoelectric energy harvesting materials and applications. Piezoelectric catalytic materials, piezoelectric supercapacitors (SCs), piezoelectric self-charging devices and piezoelectric electrochemical energy storage are mainly introduced. This review briefly introduces the recent advances in piezoelectric-based catalysts and electrochemical energy storage, concentrating on the attributes of various piezoelectric materials and their uses.

Functional composite phase change materials (CPCMs) are particularly emphasized by integrating PCM particles in building materials for energy-saving applications, due to PCM's excellent temperature adjustment capacity. However, the inherent drawback of low thermal conductivity of PCM decreases its phase-changing efficiency. Finding highly-efficient heat transfer technique becomes quite necessary. This work utilizes small hollow steel balls (HSBs) to encapsulate paraffin to provide a simple and practical solution, not only ensuring sufficient protection to PCM core in alkaline environment but also enhancing heat transfer into PCM. Then the PCM-HSBs aggregates mix with cementitious matrix to fabricate CPCM. The composite thermal conductivity (CTC) is respectively determined by experiment, theory and computational microstructure model precisely representing random morphology of PCM-HSBs in matrix, and a good agreement is observed between them. Then the dependence of CTC on microstructure features is illustrated to identify their roles. Finally, the composite compressive strength (CCS) and failure mode is discussed briefly to establish comprehensive understanding of composite properties. The results show that CTC has a significant increase of 25.84%, while CCS decreases 12.7%, when 15.28% PCM-HSBs are used. The degradation of CCS is mainly attributed to the smooth surface of HSB, which can be roughened by abrasive blasting.

Glioblastoma is the most common primary intracranial tumor and is also one of the most malignant central nervous system tumors. Its characteristics, such as high malignancy, abundant tumor vasculature, drug resistance, and recurrence-prone nature, cause great suffering to glioma patients. Furthermore, glioma stem cells are the primordial cells of the glioma and play a central role in the development of glioma. Integrins—heterodimers composed of noncovalently bound a and ß subunits—are highly expressed in glioma stem cells and play an essential role in the self-renewal, differentiation, high drug resistance, and chemo-radiotherapy resistance of glioma stem cells through cell adhesion and signaling. However, there are various types of integrins, and their mechanisms of function on glioma stem cells are complex. Therefore, this article reviews the feasibility of treating gliomas by targeting integrins on glioma stem cells.

Making sound trade-offs between the energy consumption and the makespan of workflow execution in cloud platforms remains a significant but challenging issue. So far, some works balance workflows’ energy consumption and makespan by adopting multi-objective evolutionary algorithms, but they often regard this as a black-box problem, resulting in the low efficiency of the evolutionary search. To compensate for the shortcomings of existing works, this paper mathematically formulates the cloud workflow scheduling for an infrastructure-as-a-service (IaaS) platform as a multi-objective optimization problem. Then, this paper tailors a knowledge-driven energy- and makespan-aware workflow scheduling algorithm, namely EMWSA. Specifically, a critical task adjustment-based local search strategy is proposed to intelligently adjust some critical tasks to the same resource of their successor tasks, striving to simultaneously reduce workflows’ energy consumption and makespan. Further, an idle gap reuse strategy is proposed to search the optimal energy consumption of each non-critical task without affecting the operation of other tasks, so as to further reduce energy consumption. Finally, in the context of real-world workflows and cloud platforms, we carry out comparative experiments to verify the superiority of the proposed EMWSA by significantly outperforming 4 representative baselines on 19 out of 20 workflow instances.

ObjectivesTo build and evaluate a deep learning radiomics nomogram (DLRN) for preoperative prediction of lung metastasis (LM) status in patients with soft tissue sarcoma (STS).MethodsIn total, 242 patients with STS (training set, n=116; external validation set, n=126) who underwent magnetic resonance imaging were retrospectively enrolled in this study. We identified independent predictors for LM-status and evaluated their performance. The minimum redundancy maximum relevance (mRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm were adopted to screen radiomics features. Logistic regression, decision tree, random forest, support vector machine (SVM), and adaptive boosting classifiers were compared for their ability to predict LM. To overcome the imbalanced distribution of the LM data, we retrained each machine-learning classifier using the synthetic minority over-sampling technique (SMOTE). A DLRN combining the independent clinical predictors with the best performing radiomics prediction signature (mRMR+LASSO+SVM+SMOTE) was established. Area under the receiver operating characteristics curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the performance and clinical applicability of the models.ResultComparisons of the AUC values applied to the external validation set revealed that the DLRN model (AUC=0.833) showed better prediction performance than the clinical model (AUC=0.664) and radiomics model (AUC=0.799). The calibration curves indicated good calibration efficiency and the DCA showed the DLRN model to have greater clinical applicability than the other two models.ConclusionThe DLRN was shown to be an accurate and efficient tool for LM-status prediction in STS.

Abstract Background We sought to evaluate the performance of a computed tomography (CT)-based radiomics nomogram we devised in distinguishing benign from malignant bone tumours. Methods Two hundred and six patients with bone tumours were spilt into two groups: a training set (n = 155) and a validation set (n = 51). A feature extraction process based on 3D Slicer software was used to extract the radiomics features from unenhanced CT images, and least absolute shrinkage and selection operator logistic regression was used to calculate the radiomic score to generate a radiomics signature. A clinical model comprised demographics and CT features. A radiomics nomogram combined with the clinical model and the radiomics signature was constructed. The performance of the three models was comprehensively evaluated from three aspects: identification ability, accuracy, and clinical value, allowing for generation of an optimal prediction model. Results The radiomics nomogram comprised clinical and radiomics signature features. The nomogram model displayed good performance in training and validation sets with areas under the curve of 0.917 and 0.823, respectively. The areas under the curve, decision curve analysis, and net reclassification improvement showed that the radiomics nomogram model could obtain better diagnostic performance than the clinical model and achieve greater clinical net benefits than the clinical and radiomics signature models alone. Conclusions We constructed a combined nomogram comprising a clinical model and radiomics signature as a noninvasive preoperative prediction method to distinguish between benign and malignant bone tumours and assist treatment planning.

Decomposition-based many-objective evolutionary algorithms (D-MaOEAs) are brilliant at keeping population diversity for predefined reference vectors or points. However, studies indicate that the performance of an D-MaOEA strongly depends on the similarity between the shape of the reference vectors (points) and that of the PF (a set of Pareto-optimal solutions symbolizing balance among objectives of many-objective optimization problems) of the many-objective problem (MaOP). Generally, MaOPs with expected PFs are not realistic. Consequently, the inevitable weak similarity results in many inactive subspaces, creating huge difficulties for maintaining diversity. To address these issues, we propose a two-state method to judge the decomposition status according to the number of inactive reference vectors. Then, two novel reference vector adjustment strategies, set as parts of the environmental selection approach, are tailored for the two states to delete inactive reference vectors and add new active reference vectors, respectively, in order to ensure that the reference vectors are as close as possible to the PF of the optimization problem. Based on the above strategies and an efficient convergence performance indicator, an active reference vector-based two-state dynamic decomposition-base MaOEA, referred to as ART-DMaOEA, is developed in this paper. Extensive experiments were conducted on ART-DMaOEA and five state-of-the-art MaOEAs on MaF1-MaF9 and WFG1-WFG9, and the comparative results show that ART-DMaOEA has the most competitive overall performance.

Abstract Linqing brick is quite popular in Chinese history. Currently, identifying the origin of Linqing brick is an important issue to be studied in the field of archeology and architectural history in China. Hand-Held X-ray fluorescence (HH-XRF) spectrometry enables the in situ determination of the main elements in Linqing brick in a rapid non-destructive manner. HH-XRF is important in identifying the origin of Linqing brick. However, HH-XRF could be influenced by certain factors and may be capable of measuring only the element contents of the surface for the bricks in situ. The present study aimed to verify the reliability of HH-XRF and to systematically evaluate the different factors influencing measurement precision and accuracy so that scientific advice could be provided regarding the usage of HH-XRF for this application. Four experiments were performed to determine the influencing factors and assess the reliability through cross-validation using inductively coupled plasma optical emission spectrometry (ICP-OES). Finally, the influence of the different studied factors was studied, and the reliability of HH-XRF was ensured. The facts to consider about the measurement time, cross validation, criteria to select points, treat surface and getting final data and how to avoid the effect of rain, while using this method, are provided.

Metal-doped polymer derived ceramics (PDCs) exhibits multifunctional properties due to the introduction of special metal element; however as one of the cheapest metal element carriers, metal inorganic salts have rarely been reported for the fabrication of metal-doped PDCs. In this article, a novel hydrophilic photosensitive γ-methacryloxypropyl trimethoxy modified polyhydroxymethylsiloxane preceramic polymer was firstly synthesised and three different metal-doped SiOC ceramic lattices with a strut thickness of 200 μm were successfully fabricated using inorganic metal salts as the metal source by digital light processing. The photosensitive coefficient, initial photocuring coefficient and the corresponding working curves were employed to evaluate the photocurable ability of preceramic polymers with different recipes. Results showed that both the metal-containing polymer lattices and the metal-doped SiOC ceramic lattices exhibited high-resolution microstructure and homogeneous metal element distribution, indicating that the inorganic metal salt is an effective metal source for the fabrication of metal-doped PDCs.

Abstract Photoelectrochemical (PEC) water splitting is recognized as a sustainable strategy for hydrogen generation due to its abundant hydrogen source, utilization of inexhaustible solar energy, high‐purity product, and environment‐friendly process. To actualize a practical PEC water splitting, it is paramount to develop efficient, stable, safe, and low‐cost photoelectrode materials. Recently, graphitic carbon nitride (g‐C3N4) has aroused a great interest in the new generation photoelectrode materials because of its unique features, such as suitable band structure for water splitting, a certain range of visible light absorption, nontoxicity, and good stability. Some inherent defects of g‐C3N4, however, seriously impair further improvement on PEC performance, including low electronic conductivity, high recombination rate of photogenerated charges, and limited visible light absorption at long wavelength range. Construction of g‐C3N4‐based nanosized heteroarrays as photoelectrodes has been regarded as a promising strategy to circumvent these inherent limitations and achieve the high‐performance PEC water splitting due to the accelerated exciton separation and the reduced combination of photogenerated electrons/holes. Herein, we summarize in detail the latest progress of g‐C3N4‐based nanosized heteroarrays in PEC water‐splitting photoelectrodes. Firstly, the unique advantages of this type of photoelectrodes, including the highly ordered nanoarray architectures and the heterojunctions, are highlighted. Then, different g‐C3N4‐based nanosized heteroarrays are comprehensively discussed, in terms of their fabrication methods, PEC capacities, and mechanisms, etc. To conclude, the key challenges and possible solutions for future development on g‐C3N4‐based nanosized heteroarray photoelectrodes are discussed.

Abstract Background Evaluation of tissue fibrosis and myocardial hypertrophy in left ventricular (LV) remodeling is the basis of post-treatment evaluation of hypertensive heart disease (HHD). Extracellular volume (ECV) and myocardial strain parameters can indirectly reflect the changes of both. Our objective was to analyze the characteristics of ECV and strain parameters in LV myocardium of HHD with varying degrees of systolic dysfunction, and to explore the changes of both after treatment for hypertension. Methods A total of 62 HHD patients were divided into 3 groups according to ejection fraction (EF

Abstract Background Tumor spread through air spaces (STAS) is a novel pathologic characteristic in lung adenocarcinomas that indicates invasive tumor behavior. We aimed to explore the relationship between Twist, Slug and STAS in lung adenocarcinoma and to investigate the potential relationship between epithelial‐mesenchymal transition (EMT) and STAS. Materials and methods Our study retrospectively analyzed 115 patients with resected lung adenocarcinomas to evaluate the relationship between Twist, Slug and STAS. STAS was diagnosed using hematoxylin‐eosin (H&E) staining. Immunohistochemistry was used to evaluate the expression levels of Slug and Twist. Results In this study, 56 (48.7%) patients had STAS, 40 (34.8%) patients had Slug overexpression, and 28 (24.3%) patients had Twist overexpression. Patients with either STAS or Slug and Twist overexpression experienced poor recurrence‐free survival (RFS) and overall survival (OS). There were significant associations between Twist overexpression, Slug overexpression and the presence of STAS. The logistic model further revealed that pathological stage, Twist overexpression and Slug overexpression were independent risk factors for STAS. A multivariate analysis that contained Twist, Slug, pathologic stage and STAS, showed that pathologic stage and STAS were independent prognostic factors for poor RFS and OS. Another multivariate model that contained Twist, Slug and pathologic stage, showed that pathologic stage, Twist overexpression and Slug overexpression were independent risk factors for poor RFS and OS. In the cohort with STAS, the multivariate analysis showed that pathologic stage and Twist overexpression were independent risk factors for poor survival. The subgroup analysis showed that patients with both Slug overexpression and Twist overexpression with STAS received a poor prognosis. Conclusions STAS, Slug and Twist were correlated with poor RFS and OS in resected lung adenocarcinomas. Additionally, STAS was correlated with the overexpression of Twist and Slug, which could potentially provide information on the mechanism of STAS.

Acute myeloid leukemia (AML) with T lymphoblastic lymphoma (T-LBL) is a hematologic tumor of two origins, myeloid and lymphoblastic, and is relatively rare in the same patient. We report a rare case of AML with T-LBL. After the patient was diagnosed, he received standard chemotherapy, which decreased the primitive bone marrow cell percentage from 84% to 5%; however, the enlarged superficial lymph nodes showed no obvious change in size. Immunohistochemistry revealed the following: cluster of differentiation (CD)3 (+), CD5 (+), CD7 (+), transmission disequilibrium test (TDT) (+), myeloperoxidase (MPO) (−), and lysozyme (Lys) (−). The lymph node morphology and immunohistochemical results indicated T-LBL. Therefore, the final diagnosis was AML with T-LBL, with both diseases occurring independently and concurrently.

Abstract Nitrogen, one of most important elements on the Earth, plays an essential role in shaping the modern society. The natural nitrogen looping, however, is insufficient to satisfy the high demand of the large‐scale human activities. To achieve a more sustainable and efficient utilization of nitrogen, artificial nitrogen looping by photo(electro)catalytic processes has been considered as a feasible strategy. In this context, the rational design on the high‐performance catalysts for nitrogen looping becomes increasingly important and urgent. On this basis, herein, we provide a timely review on the recent progress, achievements, and essential challenges for the artificial nitrogen looping process, mainly including photo(electro)catalytic transformations among dinitrogen, ammonia, gaseous nitrogen oxides, nitrate, and so on. Especially, the photo(electro)catalysts used in various reactions involved in nitrogen looping, including nitrogen reduction reaction, nitrogen oxidation reaction, ammonia oxidation reaction, ammonia decomposition reaction, etc., are systematically introduced. Finally, we hope that this review will help us deepen the understanding of nitrogen looping‐related photo(electro)catalysts, and further pave a way toward the sustainable development on energy and environment.

Abstract Background Gastric cancer is the second most common cause of cancer-related mortality; thus, the mechanisms underlying tumor metastasis and growth in gastric cancer need to be extensively explored. Methods Differentially expressed genes were examined in gastric cancer samples with lymph node metastasis (LNM) and without LNM using mRNA microarray and RT-qPCR. The effects of G antigen 7B (GAGE7B) on the metastasis, growth, and angiogenesis of gastric cancer were investigated in vitro and in vivo. GAGE7B protein expression was detected by immunohistochemical (IHC) analysis. Microarray, RT-qPCR, and western blot assays were performed to detect downstream target genes of GAGE7B. Dual-luciferase reporter and western blot assays were used to identify miRNAs that could negatively regulate GAGE7B. Results GAGE7B was significantly overexpressed in samples with LNM. High expression levels of GAGE7B were associated with advanced clinical stage and poor patient survival. GAGE7B dramatically enhanced the metastasis, growth, and angiogenesis ability of gastric cancer. GAGE7B was further demonstrated to promote the progression of gastric cancer by activating the p38δ/pMAPKAPK2/pHSP27 pathway. However, the GAGE7B-induced p38δ/pMAPKAPK2/pHSP27 pathway was inactivated by miR-30c, as the expression levels of both GAGE7B and p38δ were found to be directly suppressed by miR-30c. Intriguingly, GAGE7B was found to be a ceRNA for p38δ, as it activated the p38δ/pMAPKAPK2/pHSP27 pathway by competitively binding miR-30c. Conclusions GAGE7B may serve as a prognostic indicator in gastric cancer. GAGE7B significantly promotes gastric cancer progression by upregulating the p38δ/pMAPKAPK2/pHSP27 pathway, but it is negatively regulated by miR-30c. GAGE7B and miR-30c may be potential therapeutic targets in gastric cancer.

Fibrous porous materials are one of the most commonly used high-temperature insulation materials because of their high porosity and low thermal conductivity. Due to their wide applications in the aerospace and energy industries, the investigation of high-elastic thermally insulating porous materials has attracted increasing attention. In order to improve the elasticity of fibrous porous materials, quartz fibers with high aspect ratio were used as matrix, sodium hexametaphosphate (SHMP) was selected as dispersant. We innovatively reported that a unique three-dimensional skeleton structure was constructed by adjusting the dispersion of fibers in the slurry, and the lightweight, thermal insulating and elastic SiO2 fibrous porous material was then prepared by the compression molding method. The characterization results of zeta potential and absorbance showed that the addition of SHMP was an effective method to enhance the dispersibility of quartz fibers in the slurry. SiO2 fibrous porous materials with 0.4 wt% SHMP content exhibited an ideal three-dimensional skeleton structure, which endowed the porous material with high porosity (89.39%), low density (0.04751 g/cm3), and low thermal conductivity (0.0356 W·m−1·K−1). The three-dimensional skeleton structure formed by overlapping fibers with high aspect ratios endowed the porous material with excellent elasticity. SiO2 fibrous porous materials with 0.4 wt% SHMP content could undergo large strains of 30% and achieved a resilience ratio of 81.69% under the 30th compression cycle. Moreover, after heat treatment at 800 °C, SiO2 fibrous porous materials also maintained good elasticity with a resilience ratio of more than 80%.

Boron-doped carbon nanotubes are a promising candidate for Li storage due to the unique electronic structure and high crystallinity brought by the boron dopants. However, the relatively low Li storage capacity has limited its application in the electrochemical energy storage field, which is mainly caused by the predominantly intact graphitic structure on their surface with limited access points for Li ion entering. Herein, we report a novel B-doped CNTs (py-B-CNTs) film, in which the CNTs possess intrinsically rough surface but flat internal graphitic structure. When used as a flexible anode material for LIBs, this py-B-CNTs film delivers significantly enhanced capacity than the conventional B-doped CNTs or the pristine CNTs films, with good rate capability and excellent cycling performance as well. Moreover, this flexible film also possesses excellent mechanical flexibility, making it capable of being used in a prototype flexible LIB with stable power output upon various bending states.

Background/Aims: The transplantation of cardiac progenitor cells (CPCs) improves neovascularization and left ventricular function after myocardial infarction (MI). The bone morphogenetic protein antagonist Gremlin 2 (Grem2) is required for early cardiac development and cardiomyocyte differentiation. The present study examined the role of Grem2 in CPC differentiation and cardiac repair. Methods: To determine the role of Grem 2 during CPC differentiation, c-Kit+ CPCs were cultured in differentiation medium for different times, and Grem2, Notch1 and Jagged1 expression was determined by RT-PCR and western blotting. Short hairpin RNA was used to silence Grem2 expression, and the expression of cardiomyocyte surface markers was assessed by RT-PCR and immunofluorescence staining. In vivo experiments were performed in a mouse model of left anterior descending coronary artery ligation-induced MI. Results: CPC differentiation upregulated Grem2 expression and activated the Notch1 pathway. Grem2 knockdown inhibited cardiomyocyte differentiation, and this effect was similar to that of Notch1 pathway inhibition in vitro. Jagged1 overexpression rescued the effects of Grem2 silencing. In vivo, Grem2 silencing abolished the protective effects of CPC injection on cardiac fibrosis and function. Conclusions: Grem2 regulates CPC cardiac differentiation by modulating Notch1 signaling. Grem2 enhances the protective effect of CPCs on heart function in a mouse model of MI, suggesting its potential as the rapeutic protein for cardiac repair.

Spherically encapsulated phase change materials (PCMs) are extensively incorporated into matrix material to form composite latent heat storage system for the purposes of saving energy, reducing PCM cost and decreasing space occupation. Although the melting of PCM sphere has been studied comprehensively by experimental and numerical methods, it is still challenging to quantitatively depict the contribution of complex natural convection (NC) to the melting process in a practically simple and acceptable way. To tackle this, a new effective thermal conductivity model is proposed in this work by focusing on the total melting time (TMT) of PCM, instead of tracking the complex evolution of solid–liquid interface. Firstly, the experiment and finite element simulation of the constrained and unconstrained meltings of paraffin sphere are conducted to provide a deep understanding of the NC-driven melting mechanism and exhibit the difference of melting process. Then the dependence of NC on the particle size and heating temperature is numerically investigated for the unconstrained melting which is closer to the real-life physics than the constrained melting. Subsequently, the contribution of NC to the TMT is approximately represented by a simple effective thermal conductivity correlation, through which the melting process of PCM is simplified to involve heat conduction only. The effectiveness of the equivalent thermal conductivity model is demonstrated by rigorous numerical analysis involving NC-driven melting. By addressing the TMT, the present correlation thoroughly avoids tracking the complex evolution of melting front and would bring great convenience to engineering applications.

Abstract Background Gastrointestinal cancer (GI cancer) is a type of cancer that has a high death rate. It has been reported that ACYP2 gene was associated with the development of gastric cancer and colorectal cancer, but it is not clear that the relationship between ACYP2 gene and GI cancer in Chinese Han population. This study aimed to investigate the association between polymorphisms of ACYP2 and GI cancer in the Chinese Han population. Methods We used Agena MassARRAY to determine the genotypes of 1,160 GI cancer patients and 495 healthy controls. The correlation between ACYP2 variants and GI cancer risk was examined by logistic regression analysis. Results We identified that rs6713088 (OR = 1.17, 95% CI: 1.00–1.36, p = 0.047), rs843711 (OR = 1.17, 95 CI: 1.01–1.36, p = 0.035), and rs11896604 (OR = 1.20, 95% CI: 1.00–1.45, p = 0.048) were correlated with an increased risk of GI cancer under allele model. Rs11125529 under the recessive model (OR = 2.05, 95% CI: 1.00–4.23, p = 0.038), rs843711 in recessive model (OR = 1.37, 95% CI: 1.04–1.82, p = 0.026), and rs11896604 under log‐additive model (OR = 1.23, 95% CI: 1.01–1.51, p = 0.042) were associated with an increased risk of GI cancer. Conclusion Our study suggested that polymorphisms of ACYP2 gene might be associated with susceptibility to GI cancer.

Background: Statistics Canada ceased publishing vital statistics on marriage and divorce in 2008, leaving a knowledge gap in these important demographic indicators. Objective: This paper makes the methodological contribution of examining how best to operationalize divorce with tax data, and the substantive contribution of presenting recent trends in divorce in Canada. Methods: We examine trends in divorce using both vital statistics and administrative tax data and compare them during the period for which they are available (through 2008). Then, using administrative tax data, we update trends in divorce through 2016. We examine overall, age-specific, and age-standardized trends in divorce. Results: We document "gray divorce" from the 1990s through 2008 and then flat divorce rates for older adults and a continued decline in divorce for younger adults through 2016. Conclusions: Tax data show a recent decline in divorce trends in Canada. However, there are important limitations to estimating divorce with tax data. We discuss data gaps and make suggestions for more accurate measures of union dissolution. Contribution: Divorce is important for demographers to measure well, and this paper carefully examines recent trends and critically evaluates administrative data's ability to fill the void left by the termination of vital statistics.