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Background Whole brain radiotherapy (WBRT) is the mainstay of treatment for patients with non-small cell lung cancer (NSCLC) with multiple brain metastases (BMs); however, the BRAIN study showed that the efficacy of WBRT is unsatisfactory. This prospective phase II study aimed to evaluate the efficacy and safety of WBRT combined with anlotinib, a novel anti-angiogenic multi-target tyrosine kinase inhibitor (TKI), in patients with multiple BMs (>3) from advanced NSCLC.Methods Patients with advanced NSCLC with multiple BMs who had received two or more lines of treatment were eligible for enrolment into this study. All patients were treated with anlotinib (8–12 mg, QD, on days 1–14 of a 21-day cycle) combined with WBRT (DT 30 Gy/12 F), followed by maintenance therapy with anlotinib until disease progression or treatment intolerance. The primary endpoint of this study was the intracranial progression-free survival (iPFS). The secondary endpoints were intracranial objective response rate (iORR), intracranial disease control rate (iDCR), overall survival (OS) and treatment safety.Results Between May 2019 and January 2021, 28 patients were enrolled, all of whom were evaluable for efficacy and safety. The median age was 57.7 years, and 46.4% were male. Twenty-five patients had adenocarcinoma (89.3%), six had EGFR mutations (21.4%) and two had ALK mutations (7.1%). The median iPFS was 11.1 months (95% confidence interval (CI): 5.4–16.8 months) and the median OS was 13.4 months (95% CI: 5.2–21.6 months). The iORR was 71.4% (six complete responses + 14 partial responses). The most frequently observed adverse events (AEs) were hypertension (71.4%), fatigue (64.3%), anorexia (46.4%), and foot and hand skin reactions (25.0%). No patients developed ≥ grade 4 AEs. No intracranial haemorrhages occurred during treatment. Dose adjustment due to AEs occurred in 17.9% of patients.Conclusions Anlotinib combined with WBRT is effective and well-tolerated in patients with NSCLC with multiple BMs.

Abstract The scavenging process significantly affects the combustion and emission performance of marine low-speed two-stroke dual-fuel engines. Optimizing scavenging air pressure and temperature can enhance the engine's combustion efficiency and emission control performance, thereby achieving more environmentally friendly and efficient operation of dual-fuel engines. This study focuses on marine low-speed two-stroke dual-fuel engines, analyzing the effects of scavenging air pressure (3.0 bar, 3.25 bar, 3.5 bar, and 3.75 bar) and scavenging air temperature (293 K, 303 K, and 313 K) on engine performance and emission products. The results indicate that scavenging air pressure has a greater impact on engine performance than scavenging air temperature. An increase in scavenging air pressure leads to higher thermal efficiency and power. As the scavenging air pressure increases from 3 to 3.75 bar, the indicated thermal efficiency (ITE) increases from 44.02 to 53.26%, and indicated mean effective pressure (IMEP) increases by approximately 0.35 MPa. Increased scavenging air pressure improves nitrogen oxide (NOx) and hydrocarbons (HC) emissions. For every 0.25 bar increase in scavenging air pressure, NOx emissions decrease by 3.53%, HC emissions decrease by 33.35%, while carbon dioxide (CO2) emissions increase by 0.71%. An increase in scavenging air temperature leads to lower ITE and IMEP. As the air temperature changes from 293 to 313 K, the ITE decreases by approximately 1%, and IMEP decreases by about 0.04 MPa. Increased scavenging air temperature improves CO2 emissions. For every 10 K increase in the air temperature, the CO2 emissions decrease by 0.02%, while NOx emissions increase by 4.84%, HC emissions increase by 34.39%. Therefore, controlling scavenging air pressure is more important than scavenging air temperature in the operational management of marine two-stroke engines. Higher power and lower NOx and HC emissions can be achieved by increasing the scavenging air pressure.

This article proposes an adaptive sliding mode control (SMC) strategy based on stochastic configuring networks (SCNs) to improve the stability of synchronous generator (SG) and virtual synchronous generator (VSG) paralleled microgrid and enhance the dynamic performance. First, derives an equivalent swing equation what coupling of inherent inertia/damping of SG and virtual inertia/damping of VSG, the parameters design problem is established to a stabilization problem of second-order uncertain nonlinear system with bounded uncertainties. Second, an adaptive sliding mode control based on variable-speed reaching law is designed to maintain the second-order nonlinear system stable, and the switch function of adaptive reaching law is improved to reduce system chattering. Then, the stochastic configuring networks is introduced to approximate the nonlinear term, and the approximation ability of SCNs is improved by designing the configuration range of input parameters of hidden layer nodes. The stability of proposed control strategy is proved by Lyapunov theory. Finally, the feasibility and effectiveness of the proposed control strategy are verified by the designed simulations and experiments.

Abstract In diesel-ignited natural gas marine dual-fuel engines, the pilot diesel injection timing (PDIT) determines the premixing time and ignition moment of the combustible mixture in the cylinder. The PDIT plays a crucial role in the subsequent development of natural gas flame combustion. In this paper, four PDITs (− 8 °CA, − 6 °CA, − 4 °CA, and − 2 °CA) were studied. The results show that the advancement of PDIT increased the engine's power, thermal efficiency, and natural gas flame spread velocity, and increased NO emissions and CH4 emissions of the marine engine. The PDIT affected the ignition delay period and the rapid combustion period to a greater extent than the slow combustion period and the post combustion period. With each 2 °CA advancement of PDIT, the engine's power increased by 69.87 kW, thermal efficiency increased by 0.42%, radial flame spread velocity increased by 2 m/s, axial flame spread velocity increased by 1.7 m/s, NO emissions increased by 6.1%, and CH4 emissions increased by 3.75%.

Abstract Objective We attempted to identify abnormal immune cell components and signaling pathways in lupus nephritis (LN) and to identify potential therapeutic targets. Methods Differentially expressed genes (DEGs) between LN and normal kidney tissues were identified from bulk transcriptome data, and functional annotation was performed. The phenotypic changes in macrophages and aberrant intercellular signaling communications within immune cells were imputed from LN scRNA-seq data using trajectory analysis and verified using immunofluorescence staining. Finally, lentivirus-mediated overexpression of LGALS9, the gene encoding Galectin 9, in THP-1 cells was used to study the functional effect of this gene on monocytic cells. Results From bulk transcriptome data, a significant activation of interferon (IFN) signaling was observed, and its intensity showed a significantly positive correlation with the abundance of infiltrating macrophages in LN. Analysis of scRNA-seq data revealed 17 immune cell clusters, with macrophages showing the highest enrichment of intercellular signal communication in LN. Trajectory analysis revealed macrophages in LN undergo a phenotypic change from inflammatory patrolling macrophages to phagocytic and then to antigen-presenting macrophages, and secrete various pro-inflammatory factors and complement components. LGALS9 was found significantly upregulated in macrophages in LN, which was confirmed by the immunofluorescence assay. Gene functional study showed that LGALS9 overexpression in THP-1 cells significantly elicited pro-inflammatory activation, releasing multiple immune cell chemoattractants. Conclusion Our results present an important pathophysiological role for macrophages in LN, and our preliminary results demonstrate significant pro-inflammatory effects of LGALS9 gene in LN macrophages.

[This corrects the article DOI: 10.1371/journal.pone.0279886.].

Severe endometrial injury caused by invasive uterine operation and/or endometritis often results in intrauterine adhesions (IUAs), which are named Asherman’s syndrome (AS), further leading to menstrual disorders, infertility and severe complications during pregnancy and delivery. IUAs or AS has been a challenging medical problem. Stem cells are a promising therapeutic modality for endometrial regeneration in patients with refractory AS. Here, we developed a new system of adipose‐derived mesenchymal stem cells (ADMSCs) implantation on silk fibroin/polycaprolactone (SF/PCL) electrospun nanofibers (ADMSCs-SF/PCL) and used it in the damaged endometrium of a rat model. After SF/PCL enhanced the proliferation of transplanted ADMSCs, the results showed that the ADMSCs-SF/PCL system could recover morphology, promote regeneration of the glands and angiogenesis by increasing CD31 expression, and reverse endometrial fibrosis by decreasing TGF-β/Smad expression. In addition, the ADMSCs-SF/PCL system also increased the expression of differentiation and decidualization markers, including HOXA11, HAND2 and FOXO1. Most importantly, the ADMSCs-SF/PCL system could remodel the special immune microenvironment, resulting in dominant NK infiltration and a normal Th1/Th2 bias in the endometrium. Moreover, this treatment had a lower but more persistent effect than estrogen. Thus, the ADMSCs-SF/PCL system enhanced endometrial restoration, suggesting a promising strategy for damaged endometrial regeneration and immune microenvironment remodeling.

This paper proposes a modeling and optimization method for cement clinker calcination process based on gaussian process regression ensemble (EGPR) model and steady-state detection. Firstly, a modeling strategy based on EGPR model is proposed achieve an accurate description of the dynamic relationship between coal consumption, free calcium oxide (f-CaO) and operation status variables. Secondly, a multivariate steady-state detection method based on trend feature extraction is proposed for the characteristics of mixing steady-state data and dynamic data in the clinker calcination process, which achieves steady-state detection of the process and completes data denoising at the same time.Then, the optimization problem is solved using the bayesian optimization (BO) algorithm Finally, the production data of cement companies are used for validation. The results show that the overall modeling and optimization strategy proposed in this paper provides a feasible solution for achieving the optimization of energy consumption in cement clinker calcination process.

In this paper, a graph convolutional network is constructed and applied for bearing fault diagnosis. Specifically, the constant-Q transform (CQT) is first adopted for spectral analysis of vibration signals, where the frequencies are distributed in the logarithmic scale. Varied frequency resolutions can be obtained to satisfy the spectral resolution requirement and reduce signal dimension. Afterwards, the CQT spectrum is modeled by a graph, where nodes are frequency bins and edges reflect the inner relationship of different bins. There are edges between the fundamental and harmonic components. Then, a two-layer graph convolutional network (GCN) is utilized to assess the significance of vibration sources within the mixed signals. Finally, the bearing faults are determined according to the output of the GCN. To the best of our knowledge, this is the first work to model the vibration signal in this graph structure. The advantage of this approach lies in the simplification of edge definitions, facilitating shared connectivity relationships between the fundamental frequency and harmonics. Its performance was compared with another state-of-the-art fault diagnosis model. Experimental results demonstrate that the proposed model obtains higher accuracy, and it is more effective in extracting discriminative features.

Abstract The sealing ring of the external floating roof tank is prone to petroleum gas leakage due to material aging and oil corrosion. Petroleum gas leakage and diffusion easily accumulate above the floating deck. When it is within the explosion limit range, there will be the risk of explosion and fire. To deal with the explosion accident of storage tank caused by the concentration distribution of petroleum gas leakage for the sealing ring, and to study the influence of petroleum gas diffusion and concentration distribution after sealing ring leakage on the control area above the floating deck in the tank farm environment, this paper established numerical models of sealing ring leakage under different liquid level heights for 10 × 104 m3 external floating roof tank. Through numerical calculation, it is found that the diffusion concentration of petroleum gas is related to the wind speed, the range of the control area above the floating deck, and leakage when sealing rings leak at different liquid levels. Through dimensionless analysis, the functional relationship of gas leakage diffusion concentration distribution under different liquid level heights of external floating roof tank sealing rings is verified by numerical calculation results. The results show that the numerical results are consistent with those predicted by the formula.

Objective LncRNA PART1 has been confirmed related to multiple cancer bioactivities mediated with vascular endothelial growth factor signaling. Nevertheless, the role of LncRNA PART1 in esophageal cancer induced angiogenesis remains unclear. The present work focused on assessing LncRNA PART1 effects on esophageal cancer–induced angiogenesis and exploring possible mechanisms. Methods Western blot and immunofluorescence were conducted for identifying EC9706 exosomes. MiR-302a-3p and LncRNA PART1 levels were assessed by real-time quantitative polymerase chain reaction. Cell Counting Kit-8, EdU, wound healing, transwell, and tubule information were adopted for detecting human umbilical vein endothelial cell viability, proliferation, migration, invasion, and tubule information, respectively. Starbase software and dual-luciferase reporter were conducted for predicting and judging the expression interrelation of LncRNA PART1 and its potential target-miR-302a-3p. The same methods were carried out for verifying the inhibiting influences of miR-302a-3p upregulation and its potential target-cell division cycle 25 A. Results LncRNA PART1 levels were upregulated and related to the overall survival of patients in esophageal cancer. EC9706-Exos accelerated human umbilical vein endothelial cell proliferation, migration, invasion, and tubule formation via LncRNA PART1. LncRNA PART1 served as a sponge of miR-302a-3p, then miR-302a-3p targeted cell division cycle 25 A, and EC9706-Exos accelerated human umbilical vein endothelial cell angiogenesis via LncRNA PART1/ miR-302a-3p/cell division cycle 25 A axis. Conclusion EC9706-Exos accelerates human umbilical vein endothelial cell angiogenesis via LncRNA PART1/miR-302a-3p/ cell division cycle 25 A axis, indicating EC9706-Exos may act as a promoter of angiogenesis. Our research will contribute to clarify the mechanism of tumor angiogenesis.

Estimating forage yield and nutrient composition using hyperspectral remote sensing is a major challenge. However, there is still a lack of comprehensive research on the optimal wavelength for the analysis of various nutrients in pasture. In this research, conducted in Hailar District, Hulunber City, Inner Mongolia Autonomous Region, China, 126 sets of hyperspectral data were collected, covering a spectral range of 350 to 1800 nanometers. The primary objective was to identify key spectral bands for estimating forage dry matter yield (DMY), nitrogen content (NC), neutral detergent fiber (NDF), and acid detergent fiber (ADF) using principal component analysis (PCA), random forests (RF), and SHapley Additive exPlanations (SHAP) analysis methods, and then the RF and Extra-Trees algorithm (ERT) model was used to predict aboveground biomass (AGB) and nutrient parameters using the optimized spectral bands and vegetation indices. Our approach effectively minimizes redundancy in hyperspectral data by selectively employing crucial spectral bands, thus improving the accuracy of forage nutrient estimation. PCA identified the most variable bands at 400 nm, 520–550 nm, 670–720 nm, and 930–950 nm, reflecting their general spectral significance rather than a link to specific forage nutrients. Further analysis using RF feature importance pinpointed influential bands, predominantly within 930–940 nm and 700–730 nm. SHAP analysis confirmed critical bands for DMY (965 nm, 712 nm, and 1652 nm), NC (1390 nm and 713 nm), ADF (1390 nm and 715–725 nm), and NDF (400 nm, 983 nm, 1350 nm, and 1800 nm). The fitting accuracy for ADF estimated using RF was lower (R2 = 0.58), while the fitting accuracy for other indicators was higher (R2 ≥ 0.59). The performance and prediction accuracy of ERT (R2 = 0.63) were noticeably superior to those of RF. In conclusion, our method effectively identifies influential bands, optimizing forage yield and quality estimation.

This paper proposes an optimal resource allocation method. The method is to maximize the Energy Efficiency (EE) for an Energy Harvesting (EH) enabled underlay Cognitive Radio (CR) network. First, we assumed the Secondary Users (SUs) can harvest energy from the surrounding Radio Frequency (RF) signals. Then, we modelled the EE maximisation problem as a joint time and power optimization model. Next, the optimal EH time allocation factor can be calculated. After that the optimal power allocation strategy can be obtain by the fractional programming and Lagrange multiplier method. Finally simulation results show that the proposed iterative method can be better performance advantages compared with the exhaustive method and genetic algorithm. And the EE of this system model is significantly improved compared to the EE model without considering EH.

Accurate reconnaissance of Marine oil spill is very important for emergency management of Marine oil spill accidents. Unmanned aerial vehicles (UAV) is a suitable carrier for offshore oil spill reconnaissance because of its fast deployment speed and low cost. Aiming at the identification accuracy of small oil spill accident in offshore port area and the problem of day and night reconnaissance, this study takes thermal infrared remote sensing images of oil leakage captured by UAV as the research object and proposes an oil spill detection method based on a Gray Level Co-occurrence Matrix (GLCM) and Support Vector Machine (SVM) method. Firstly, the extraction steps of image GLCM feature and the basic principle of SVM classification are studied. Then, the thermal infrared image data collected by UAV is preprocessed, including image filtering, clipping and rotation, and the sample database is generated. Subsequently, GLCM features of the samples were extracted, and the energy and correlation in GLCM were selected as classification features and sent to the SVM classifier to complete the oil spill detection of real-time thermal infrared images. The experimental results show that, compared with Classification and Regression Tree algorithm (CART) and Random Forests of Decision Trees (RF) algorithm, the detection accuracy of the method proposed in this paper reaches 95%, which were 10 and 2 percentage points higher than them respectively. The proposed method in this paper has fast recognition speed and high accuracy, and can provide all-weather recognition of oil spills for the detection of small oil spills in the offshore port area.

Abstract Senescent endothelial cells (ECs) could impair the integrity of the blood vessel endothelium, leading to vascular aging and a series of diseases, such as atherosclerosis, diabetes. Preventing or mitigating EC senescence might serve as a promising therapeutic paradigm for these diseases. Recent studies showed that small extracellular vesicles (sEV) have the potential to transfer bioactive molecules into recipient cells and induce phenotypic changes. Since mesenchymal stem cells (MSCs) have long been postulated as an important source cell in regenerative medicine, herein we investigated the role and mechanism of MSC-derived sEV (MSC-sEV) on EC senescence. In vitro results showed that MSC-sEV reduced senescent biomarkers, decreased senescence-associated secretory phenotype (SASP), rescued angiogenesis, migration and other dysfunctions in senescent EC induced by oxidative stress. In the In vivo natural aging and type-2 diabetes mouse wound-healing models (both of which have senescent ECs), MSC-sEV promoted wound closure and new blood vessel formation. Mechanically, miRNA microarray showed that miR-146a was highly expressed in MSC-sEV and also upregulated in EC after MSC-sEV treatment. miR-146a inhibitors abolished the stimulatory effects of MSC-sEV on senescence. Moreover, we found miR-146a could suppress Src phosphorylation and downstream targets VE-cadherin and Caveolin-1. Collectively, our data indicate that MSC-sEV mitigated endothelial cell senescence and stimulate angiogenesis through miR-146a/Src.

A novel and efficient technique has been designed for the creation of oxygen vacancies on La2Ti2O7 (LTO) nanosheets. This is achieved via a controlled solid-state reaction between NaBH4 and LTO nanosheets. Transmission electron microscopy (TEM) analyses expose that these processed LTO specimens possess a unique crystalline core/amorphous shell structure, represented as La2Ti2O7@La2Ti2O7-x. According to X-ray photoelectron spectroscopy (XPS) observations, there is a notable correlation between the reaction time, temperature, and the concentration of oxygen vacancies. The concentration of these vacancies tends to increase along with the reaction time and temperature. Concurrently, UV-Visible spectra and photocatalytic tests reveal a significant impact of oxygen vacancies on the LTO surface on both light absorption and photocatalytic functionality. Most notably, the LTO nanosheets with engineered oxygen vacancies have demonstrated an exceptional photocatalytic capacity for hydrogen production under visible light. The maximal activity recorded was an impressive 149 μmol g−1 h−1, which is noticeably superior to the performance of the pristine La2Ti2O7.

The rapid drop of frequency under the disturbance is a major threat to the safe and stable operation of a microgrid (MG) system. Emergency load shedding is the main measure to prevent continuous frequency drop and power outage. The existing load shedding strategies have poor adaptability to deal with the problem of MG load shedding under different disturbance situations, and it is difficult to ensure the safe and stable operation of an MG in different operating environments. To address this problem, this paper proposes a data-driven load shedding strategy. First, considering the importance of the load and the frequency recovery time of the system, a load shedding contribution indicator is designed that takes into account the load frequency adjustment effect and the load shedding priority. This contribution indicator is introduced as a load shedding criterion into the reward value function of dueling deep Q learning. Second, considering the suddenness and uncertainty of emergency load shedding, a MG emergency load shedding strategy (ELSS) based on dueling deep Q-learning is proposed. On this basis, the dueling deep Q learning algorithm is used to obtain the load shedding decision with the maximum cumulative reward. Finally, taking the MG load shedding cases in two different scenarios as examples, a simulation study is carried out on a modified IEEE-25 bus MG. The simulation results show that, compared with the model-driven implicit enumeration strategy (IES), the proposed ELSS has superiority in maintaining stable power supply for important loads and reducing load shedding decision-making time and frequency fluctuations.

The computer vision inspection of surface cracks in concrete structures has the characteristics of convenient and efficient 24-h on-site inspection. In this paper, the instance segmentation method and semantic segmentation method are used to realize the surface crack recognition of concrete structures, and a concrete crack detection method based on two different deep learning methods is designed. Experiments show that in scenarios where detection accuracy is required, compared with the Mask Region with Convolutional Neural Network method, the U-Net model improves the model segmentation accuracy through up-sampling and skip connection, and its Recall, Kappa, and Dice are increased by 6.88, 1.94, and 7.72%, respectively. In the scene of positioning requirements, Mask Region with Convolutional Neural Network has a better detection effect than U-Net for very thin and inconspicuous cracks, effectively avoiding the situation of missing cracks.

The development of intelligent indicator film that can detect changes in food quality is a new trend in the food packaging field. The WPNFs-PU-ACN/Gly film was prepared based on whey protein isolate nanofibers (WPNFs). Anthocyanin (ACN) and glycerol (Gly) were used as the color indicator and the plasticizer, respectively, while pullulan (PU) was added to enhance mechanical properties of WPNFs-PU-ACN/Gly edible film. In the study, the addition of ACN improved the hydrophobicity and oxidation resistance of the indicator film; with an increase in pH, the color of the indicator film shifted from dark pink to grey, and its surface was uniform and smooth. Therefore, the WPNFs-PU-ACN/Gly edible film would be suitable for sensing the pH of salmon, which changes with deterioration, as the color change of ACN was completely consistent with fish pH. Furthermore, the color change after being exposed to grey was evaluated in conjunction with hardness, chewiness, and resilience of salmon as an indication. This shows that intelligent indicator film made of WPNFs, PU, ACN, and Gly could contribute to the development of safe food.

A large-scale glass curtain wall (LGCW) attached to a high-rise building is analyzed using the finite element method to investigate the wind resistance performance of the LGCW with and without the high-rise building. The results show that without the high-rise building, the peak wind-induced response occurs in the center of each glass panel of the LGCW, and it gradually decreases away from the center towards the edges of each glass panel. When the high-rise building is included in the finite element model, the additional wind-induced response on the LGCW caused by the deformation of the high-rise building is large at the upper and lower glass panel edges, and gradually decreases toward the panel center. The high-rise building produces great effects on the displacements of the LGCW but weak effects on the stresses, where the peak displacement of the whole LGCW is increased by 40.5%. The influences of key structural parameters, including the lateral stiffness of the high-rise building and the connection stiffness between the large glass curtain wall and the high-rise building, on the wind resistance performance of the LGCW are further investigated. The results demonstrate that the smaller the lateral stiffness of the high-rise building is, the greater the additional responses caused by the deformation of the high-rise building on the LGCW are, and the greater the total load responses of the LGCW are. The smaller the connection stiffness between the LGCW and the high-rise building is, the greater the responses of the independent LGCW are, while the additional responses induced by the deformation of the high-rise building on the LGCW are not significant.

Traditional reinforced concrete piles have high strength and low cost in slope engineering, but the slow forming and long maintenance period make it difficult to meet the needs of emergency and disaster relief tasks, such as landslides caused by rainfall. In this paper, the influence of a new type of polymer anti-slide pile on slope stability under rainfall conditions is studied. With the advantages of fast forming, high strength, simple construction technology, and small disturbance to slope, the new type of anti-slide pile can meet the requirements of emergency and disaster relief tasks. The influence of different rainfall duration, rainfall form, location, and spacing of pile laying on the stability of rainfall slope is explored with fluid-solid coupling analysis. The results show that the slope stability gradually deteriorates with the increase of the peak duration of rainfall intensity. Without rainfall conditions, the reinforcement effect is optimal when the position of pile cloth is 1/2–3/4 L away from the foot of the slope (L is the horizontal length of the slope); with rainfall conditions, when the position of pile cloth is 1/4–1/2 L away from the foot of the slope, the reinforcement effect is optimal. Without rainfall conditions, the reduction of pile spacing can improve the reinforcement effect; with rainfall conditions, the reduction of pile spacing will affect the flow and discharge of seepage rainwater and reduce the reinforcement effect.

Reasonable scheduling is the basic guarantee for an integrated energy system (IES) to achieve coordinated and efficient operation of multi-energies. For an IES including electric and thermal loads, a demand response (DR) model based on a compensation mechanism is established in this article, and scheduling elasticity (SE) of different types of loads is analyzed to guide users to use energies reasonably and economically. On this basis, an optimization model is established for an IES in accordance with the energy consumption and system operation characteristics. In accordance with the dynamic demands of multi-energies, this model aims at meeting all energy demands with the lowest operation cost. It performs the coordinated optimization for the device output power and the power transmission between multi-energies. To solve the problems of the complex solving process and long computation time, a global optimization algorithm based on a polynomial response surface (PRS) metamodel is proposed in this article. The proposed algorithm adopts a response surface method to fit the optimization model and construct a PRS metamodel to estimate the function values instead of the optimization model, thereby avoiding repeatedly calling the original complex objective function and reducing the computation time. The test results verify the effectiveness of the proposed model and algorithm.

Strain coupling with ferromagnetism and ferroelectricity plays an important role in the development of multiferroic metal-organic frameworks (MOFs) with strong magnetoelectric coupling, but the underlying mechanisms have not been well understood. Strain coupling and dynamic relaxation in multiferroic MOF with perovskite structure [(CH3)2NH2][Mn(HCOO)3] were investigated using X-ray diffraction (XRD), Raman spectroscopy, Infra-red (IR) spectroscopy, differential scanning calorimetry (DSC), magnetic measurements and dynamic mechanical analysis (DMA). DSC results showed peaks at 183 K and 190 K at the rate of 5 K/min during cooling and heating processes, respectively. Magnetic measurements showed magnetic transition at ∼8.5 K at the heating rate of 2 K/min. Temperature and frequency dependences of elastic properties studied by DMA at frequencies of 0.5 Hz–10 Hz between 140 K and 300 K at heating rate of 2 K/min indicated that the minimum in storage modulus and the maximum in loss modulus and loss factor occurred near 190 K. The peak height of loss modulus and loss factor decreased at higher frequency, and the peak temperature was independent of frequency, showing the features of first-order phase transition. Near 190 K, paraelectric to ferroelectric phase transition triggered by disorder–order transition of alkylammonium cations located in the framework cavities occurred accompanied by the structural phase transition from rhombohedral space group R3-c to monoclinic space group Cc. The elastic anomalies and large energy loss near 190 K were associated with the coupling of the local strain with the freezing of dimethylammonium cation and the freezing of twin walls. Keywords: Metal-organic framework (MOF), Phase transition, Dynamic mechanical analysis (DMA), Elastic modulus, Energy loss

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest solid malignancies and has a poor survival rate worldwide. In this study, we aimed to establish a tumor-infiltrating immune cell-based prognosis signature (IPS) to predict patients’ survival times and aid in the development of targeted therapies or immunotherapies. The abundances of 22 types of immune cells were determined by the CIBERSORT algorithm from ESCC patient gene expression data in the Gene Expression Omnibus (GEO) training set (n = 179) and The Cancer Genome Atlas (TCGA) validation set (n = 95). Then, the IPS was established by using the least absolute shrinkage and selection operator (LASSO) regression method. Kaplan-Meier analysis showed that patients with high IPS scores had significantly worse overall survival times than patients with low IPS scores in both the training set and the validation set (log-rank p = 0.001, and p = 0.050, respectively). Univariate and multivariate Cox regression analyses proved that the IPS was a robust prognostic factor for ESCC, independent of age, sex, tumor node metastasis (TNM) stage, pathology grade, and tumor location. In the mechanistic study, the epithelial-mesenchymal transition (EMT) process was identified by both gene set enrichment analysis (GSEA) and weighted correlation network analysis (WGCNA) as the underlying mechanism by which the IPS affects the prognosis of ESCC. After systematic correlation analyses, we found that M2 macrophages were the only cell type in the IPS significantly correlated with the EMT process. This relationship between M2 macrophage infiltration and the EMT phenotype was also confirmed by our preliminary immunochemistry (IHC) and multiplexed immunofluorescence study. In conclusion, we constructed an IPS that predicts the postoperative prognosis of ESCC patients and uncovered the critical role of M2 macrophages in the interplay between immune status and the EMT phenotype in ESCC.

Thiocyanate could effectively inhibit bacteria in milk and extend the shelf life of milk. However, excessive addition will lead to health risks. Therefore, the determination of thiocyanate in raw milk has received a lot of attention, but the determination could be interfered with by other components in raw milk and the pre-treatment of raw milk is complex. In this study, a new pretreatment method combined with ion chromatography (IC) for rapid and sensitive determination of thiocyanate is proposed. An acetonitrile/(NH4)2SO4 aqueous two-phase system (ATPS) was developed for the separation and enrichment of thiocyanate in raw milk. Response surface methodology was performed to optimize the extraction conditions and an efficient pretreatment were obtained using ATPS composed of 42% acetonitrile (w/w) and 16% (NH4)2SO4 (w/w), with the pH 4.7, and the recovery of thiocyanate reached 107.24 ± 0.5%, and the enrichment ratio was 10.74 ± 0.03. IC was used to establish a thiocyanate enrichment method. The linear range was from 0.05 to 15 mg/L and R2 = 0.998, the limit of detection (LOD) was 0.2 μg/L, the limit of quantification (LQD) was 0.6 μg/L. Hence, it is feasible to combine ATPS with IC for the enrichment and determination of thiocyanate in raw milk.

BackgroundPrognostic biomarker, which can inform the treatment outcome of adjuvant chemotherapy (ACT) after complete resection of early-stage non-small cell lung cancer (NSCLC), is urgently needed for the personalized treatment of these patients.Patients and methodsThe prognostic value of gene expression of the estrogen receptor (ER) on the effect of ACT in completely resected NSCLC was investigated in the present study. Two independent datasets from Gene Expression Omnibus (GEO) with a total of 309 patients were included in this study. The prognostic value of ER gene expression on ACT's efficacy was evaluated by survival analysis and Cox hazards models.ResultsWe found a consistent and significant prognostic value of ERβ (ESR2) expression for ACT's efficacy in completely resected NSCLC in both of the two independent cohorts. After multivariate adjustment, a significant survival benefit of ACT was observed in patients with low expression of ESR2, with a hazard ratio (HR) of 0.19 (95%CI 0.05-0.82, p = 0.026) in the discovery cohort and an HR of 0.27 (95%CI 0.10-0.76, p = 0.012) in the validation group. No significant benefit of ACT in the subgroup of patients with high expression of ESR2 was observed, with an HR of 0.80 (95%CI 0.31-2.09, p = 0.644) in the discovery cohort and an HR of 1.05 (95%CI 0.48-2.29, p = 0.896) in the validation group.ConclusionA significant survival benefit from ACT was observed in patients with low ESR2 expression. No significant survival benefit was observed in patients with high ESR2 expression. Detection of ESR2 expression in NSCLC may help personalize its treatment after complete resection.

Premature ovarian failure (POF) is one of the principal causes of female infertility, and although its causes are complex and diverse, autoimmune deficiency may be involved. Human umbilical cord mesenchymal stem cells (UCMSCs) can be used for tissue regeneration and repair. Therefore, the present study was designed to determine the role of UCMSCs in immune factor-induced POF in rats. In this study, different concentrations of UCMSCs were injected into induced POF rats. Ovarian functions were examined by evaluating the estrus cycle, follicular morphology, hormonal secretion, and the proliferation and apoptosis of granulosa cells. Our results showed that the estrus cycle of rats returned to normal and follicular development was significantly improved after transplantation of UCMSCs. In addition, serum concentrations of 17-estradiol (E2), progesterone (P4), and anti-Müllerian hormone (AMH) increased significantly with treatment. Transplantation of UCMSCs also reduced the apoptosis of granulosa cells and promoted the proliferation of granulosa cells. All of these improvements were dose dependent. Furthermore, the results of related gene expression showed that transplanted human UCMSCs upregulated the expression of Bcl-2, AMH, and FSHR in the ovary of POF rats and downregulated the expression of caspase-3. These results further validated the potential mechanisms of promoting the release of cell growth factors and enhancing tissue regeneration and provide a theoretical basis for the clinical application of stem cells in the treatment of premature ovarian failure.

BACKGROUND: Laboratory studies have shown the anti-tumor effect of metformin on prostate cancer. However, recent epidemiological studies have yielded inconclusive results. METHODS: We searched PubMed database from the inception to May 30 2014 for studies which assessed the effect of metformin use on cancer risk of prostate cancer, biochemical recurrence (BCR) and all-cause mortality of patients with prostate cancer. The pooled results and 95% confidence intervals (CIs) were estimated by random-effect model. RESULTS: Twenty-one studies were eligible according to the inclusion criteria. Based on the pooled results of available observational studies, metformin use was significantly associated with a decreased cancer risk (14 datasets, 963991 male subjects, odds ratio: 0.91, 95% CI: 0.85-0.97) and BCR (6 datasets, 2953 patients, hazard ratio: 0.81, 95% CI: 0.68-0.98) of prostate cancer. However, the association of metformin use with all-cause mortality of patients with prostate cancer was not significant (5 datasets, 9241 patients, hazard ratio: 0.86, 95% CI: 0.64-1.14). CONCLUSION: Results suggest that metformin use appears to be associated with a significant reduction in the cancer risk and BCR of prostate cancer, but not in all-cause mortality of patients with prostate cancer.

With the aim to elucidate the etiology of radioresistance, we explored the genetic alterations in non-radioresistant vs. resistant esophageal cancer cells acquired by long-term fractionated radiation. We found AKR1C3, an aldo-keto reductase expressed seldom in most human tissues, expressed higher in radioresistance-acquired cells. Suppression of AKR1C3 via RNAi or its chemical inhibitors restored the sensitivity of the acquired tumor cells and xenograft BALB/c nude mice to ionizing radiation (IR). Cellular monitoring of the oxidative stress in the AKR1C3-elevated cells indicated that IR-induced ROS accumulation and the concomitant DNA damage was significantly alleviated, and such protective consequence disappeared upon AKR1C3 knockdown. These findings uncover the potential involvement of AKR1C3 in removal of cellular ROS and explain, at least partially, the acquired radioresistance by AKR1C3 overexpression. A retrospective analysis of esophageal carcinomas also indicated a significant expression of AKR1C3 in radio-resistant but not radio-sensitive surgical samples. Our study may provide a potential biomarker for predicting prognosis of radiotherapy and even direct a targeted therapy for esophageal cancer and other tumors.