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BackgroundEnhanced inflammation and reduced Klotho are common features in chronic kidney disease (CKD). Inflammation induces DNA hypermethylation. This study assessed the performance of inflammatory marker C-C motif chemokine 5 (CCL5) in epigenetic regulation of Klotho expression.MethodsFifty CKD patients and 25 matched controls were enrolled, and serum CCL5 level, sKlotho level, and DNA methylation were evaluated in these subjects. A renal interstitial fibrosis (RIF) model with CKD was induced in mice via unilateral ureteral obstruction (UUO) in vivo and human proximal tubular epithelial (HK-2) cells treated with CCL5 in vitro. 5-aza-2′-deoxycytidine (5-Aza), a DNA methyltransferase inhibitor was given to UUO mice. Hematoxylin and eosin (HE) and Masson trichrome staining were adopted to evaluate renal pathological changes. Methylation-specific PCR was performed to assess DNA methylation of Klotho promoter in the peripheral blood leucocytes (PBLs) from CKD patients and obstructive kidney from UUO mice. CCL5, Klotho, and DNA methyltransferases (DNMTs) were determined by ELISAs, immunofluorescence, or western blotting. HK-2 cells were exposed to CCL5 with or without 5-Aza and stattic, a p-signal transducer and activator of transcription 3 (STAT3) inhibitor, and expressions of p-STAT3, DNMT1, and Klotho were determined by western blotting.ResultsCCL5 upregulation concomitant with Klotho downregulation in serum and global DNA methylation in PBLs were observed in CKD samples. UUO contributed to severe renal interstitial fibrosis and enhanced expressions of fibrotic markers. Moreover, UUO increased the CCL5 level, induced Klotho promoter methylation, suppressed Klotho level, activated p-STAT3 signaling, and upregulated DNMT1 level. A similar observation was made in HK-2 cells treated with CCL5. More importantly, 5-Aza inhibited UUO-induced Klotho hypermethylation, reversed Klotho, downregulated p-STAT3 expressions, and ameliorated RIF in vivo. The consistent findings in vitro were also obtained in HK-2 cells exposed to 5-Aza and stattic.ConclusionThe CCL5/p-STAT3/DNMT1 axis is implicated in epigenetic regulation of Klotho expression in CKD. This study provides novel therapeutic possibilities for reversal of Klotho suppression by CKD.

Two-dimensional (2D) atomic crystal superlattices offer technological opportunities beyond the reach of existing materials. Here, the authors produce 2D atomic crystal molecular superlattices by intercalating O2 molecules into the interlayer space of 2D materials using a soft plasma strategy.

ABSTRACT: In this work, we develop an invertible transport map, called KRnet, for density estimation by coupling the Knothe–Rosenblatt (KR) rearrangement and the flow-based generative model, which generalizes the real-valued non-volume preserving (real NVP) model (arX-iv:1605.08803v3). The triangular structure of the KR rearrangement breaks the symmetry of the real NVP in terms of the exchange of information between dimensions, which not only accelerates the training process but also improves the accuracy significantly. We have also introduced several new layers into the generative model to improve both robustness and effectiveness, including a reformulated affine coupling layer, a rotation layer and a component-wise nonlinear invertible layer. The KRnet can be used for both density estimation and sample generation especially when the dimensionality is relatively high. Numerical experiments have been presented to demonstrate the performance of KRnet.

A state-of-the-art deep domain decomposition method (D3M) based on the variational principle is proposed for partial differential equations (PDEs). The solution of PDEs can be formulated as the solution of a constrained optimization problem, and we design a hierarchical neural network framework to solve this optimization problem. Through decomposing a PDE system into components parts, our D3M builds local neural networks on physical subdomains independently (which can be implemented in parallel), so as to obtain efficient neural network approximations for complex problems. Our analysis shows that the D3M approximation solution converges to the exact solution of the underlying PDEs. The accuracy and the efficiency of D3M are validated and demonstrated with numerical experiments.

In order to study the deformation of a diaphragm wall and the settlement of surrounding soil under the complicated conditions of the deep and soft soil layer, which is underlying inclined rock and top-down construction method, the construction scheme of suspended diaphragm wall based on the engineering practice of Oujiang North Estuary deep and large foundation pit of Wenzhou S2 railway is proposed, and the research method of numerical simulation is adopted in this article. By using Midas GTS finite element software, a three-dimensional model of deep and large foundation pit excavation with top-down construction method is established, and the internal force, deformation, and surface settlement of surrounding soil of suspended diaphragm wall with different depths into rock (1 m, 2 m, and 4 m) are analyzed. Furthermore, the optimization simulation research on the anchor locking scheme is carried out for the determined footed diaphragm wall. Similarly, the anchor locking scheme at a depth of 1 m into the interface between soil and rock is selected as the supporting scheme of the footed diaphragm wall through the simulation results. The research results of this article can guarantee the safety of diaphragm wall construction of deep and large foundation pit in complex stratum.

Over the past decade, organic–inorganic hybrid perovskite solar cells (PVSCs) have shown unprecedented growth in power conversion efficiency (PCE) from 3.8% to 25.7%. However, intrinsic thermal instability and lead toxicity are obstacles limiting its large–scale commercialization. Thus, all-inorganic CsSnI3 perovskite has drawn remarkable interest owing to its nontoxicity, excellent thermal stability, low-cost fabrication, and spectacular photoelectric characteristics, including ideal bandgap range, long carrier lifetime, and large absorption coefficient. Many studies have shown that the device performances are closely related to the morphology and crystallinity of perovskite films. In this review, the physical properties of CsSnI3 perovskite are summarized. Furthermore, this review primarily narrates the recent progress in optimizing the morphology by various strategies such as additive engineering, composition regulation, and deposition techniques, emphasizing their effects on grain sizes, film uniformity, grain boundary, and defect passivation.

With the wide application of power equipment consisting of high switching frequencies and large current switching devices in the integrated power system on ships, the low-frequency radiation interference caused by the powerful electromagnetic equipment becomes more and more serious. Establishing an equivalent model of radiation interference based on the near-field measurement data is the key to subsequent electromagnetic compatibility design. Due to the large size of the equipment, there will be many measurement points in the near-field measurement area, which leads to long testing times and low modeling efficiency. To solve the above problems, this article first proposes a method of near-field measurement and a modeling method of powerful electromagnetic equipment radiation based on field distribution characteristics. Firstly, the near-field measurement data are obtained by the sparse and uniform sampling of the near-field measurement plane at large sampling intervals. Then, the near-field measuring plane is separated into several regions by the magnetic field’s distribution characteristics. The near-field measurement data required for modeling are obtained by further sampling in the region with a large magnetic field amplitude. Finally, the equivalent radiation model is obtained by the equivalent dipole method. Simulations and experiments show that the method can significantly reduce the amount of measurement data and testing time while improving the efficiency of equivalent radiation modeling and maintaining the accuracy of the modeling.

Tensor completion is a fundamental tool to estimate unknown information from observed data, which is widely used in many areas, including image and video recovery, traffic data completion and the multi-input multi-output problems in information theory. Based on Tucker decomposition, this paper proposes a new algorithm to complete tensors with missing data. In decomposition-based tensor completion methods, underestimation or overestimation of tensor ranks can lead to inaccurate results. To tackle this problem, we design an alternative iterating method that breaks the original problem into several matrix completion subproblems and adaptively adjusts the multilinear rank of the model during optimization procedures. Through numerical experiments on synthetic data and authentic images, we show that the proposed method can effectively estimate the tensor ranks and predict the missing entries.

The accuracy and precision of analyte concentrations measured in whole blood by chemiluminescence immunoassay (CLIA) have been significantly affected by erythrocytes, which leads to poor application of whole blood CLIA in clinical practice. In this work, a chemiluminescence biosensing optical platform for blood hematocrit (HCT) analysis using MAGICL 6000 (Getein Biotechnology, Nanjing, China) was designed, implemented, and fully characterized. The developed method was successfully applied to determine various HCT levels of human blood from 0% to 65%, with a correlation coefficient of 0.9885 compared with the conventional method (Sysmex XE 5000, Kobe, Japan). A mathematical model was developed to quantitatively evaluate the impact of HCT on the results of two sample types (whole blood vs. plasma). Combining the established HCT method and mathematical model with CLIA on MAGICL 6000, the precision was significantly improved by almost 20%. Comparison studies using whole blood samples and corresponding plasma samples showed that the square of the correlation coefficients of troponin I (cTnI), myoglobin (MYO), creatine kinase MB (CK-MB), and N-terminal pro-hormone brain natriuretic peptide (NT-proBNP) were increased to 0.9992, 0.9997, 0.9996, and 0.9994, respectively, showing a great potential for clinical application.

A good non-viral vector is the key to the success of gene delivery and therapy; hence, modified exosomes may overcome the physiological barrier in the delivery in vivo. This study aims to design a novel non-viral vector and verify its gene delivery function in vitro and in vivo for dapper homolog 2 (DACT2) genes. In this study, amphipathicity cationic exosomes with receptor targeted function and DACT2 gene loading function were constructed by exosomes, PEG, glycidyl hexadecyl dimethylammonium chloride, and recombinant VAR2CSA malaria protein (RVP) antibody. Characterizations of RVP antibody and PEG modified cationic lipid exosome (RVP-CL) nanocomplexes were evaluated by dynamic light scattering, atomic force microscopy, FTIR, and so on. The DNA condensation ability and stability were assessed by agarose gel electrophoresis. Cellular uptake efficiency and cytotoxicity in glioma cells were investigated. Furthermore, the tumor suppressive effect was evaluated in vitro and in vivo. The results indicated that RVP-CL had a uniform size of 100–200 nm and positive zeta potential. With high uptake efficiency, RVP-CL can rapidly target, recognize, and enter the glioma cell (KNS-42 and U118 mg) and release the gene. Moreover, RVP-CL/DACT2 can effectively inhibit the growth of glioma cells in vitro and in vivo. The modified cationic exosomes may offer a promising strategy for gene delivery in the treatment of RVP-positive gliomas or other tumors. [ABSTRACT FROM AUTHOR]

Background: The correlation between soluble Klotho (sKlotho) level and vascular calcification (VC) in patients with chronic kidney disease (CKD) remains controversial. Using meta-analysis, we aimed to address this controversy and assess the feasibility of applying sKlotho as a biomarker for VC.Methods: Medical electronic databases were thoroughly searched for eligible publications on the association between sKlotho level and VC in CKD patients. Effectors, including correlation coefficients (r), odds ratios (ORs), hazard ratio (HR) or β-values, and 95% confidence intervals (CIs) were extracted and combined according to study design or effector calculation method. Pooled effectors were generated using both random-effects models and fixed-effects models according to I2-value. Origin of heterogeneity was explored by sensitivity analysis and subgroup analysis.Results: Ten studies with 1,204 participants from a total of 1,199 publications were eligible and included in this meta-analysis. The combined correlation coefficient (r) was [−0.33 (−0.62, −0.04)] with significant heterogeneity (I2 = 89%, p < 0.001) based on Spearman correlation analysis, and this significant association was also demonstrated in subgroups. There was no evidence of publication bias. The combined OR was [3.27 (1.70, 6.30)] with no evidence of heterogeneity (I2 = 0%, p = 0.48) when sKlotho was treated as a categorical variable or [1.05 (1.01, 1.09)] with moderate heterogeneity (I2 = 63%, p = 0.10) when sKlotho was treated as a continuous variable based on multivariate logistic regression. No significant association was observed and the pooled OR was [0.29 (0.01, 11.15)] with high heterogeneity (I2 = 96%, p < 0.001) according to multivariate linear regression analysis. There was an inverse association between sKlotho and parathyroid hormone levels. The combined coefficient (r) was [−0.20 (−0.40, −0.01)] with significant heterogeneity (I2 = 86%, p < 0.001), and without obvious publication bias. No significant association was found between sKlotho and calcium or phosphate levels.Conclusion: There exists a significant association between decreased sKlotho level and increased risk of VC in CKD patients. This raises the possibility of applying sKlotho as a biomarker for VC in CKD populations. Large, prospective, well-designed studies or interventional clinical trials are required to validate our findings.

Semiconducting covalent organic frameworks (COF) with conjugated structures are desired for optoelectric conversion but poor reversibility of bond forming reactions hampers the formation of crystalline structures. Here, the authors synthesise COFs with disubstituted C = C linkages which enable water splitting under visible light irradiation.

Failure probability evaluation for complex physical and engineering systems governed by partial differential equations (PDEs) are computationally intensive, especially when high-dimensional random parameters are involved. Since standard numerical schemes for solving these complex PDEs are expensive, traditional Monte Carlo methods which require repeatedly solving PDEs are infeasible. Alternative approaches which are typically the surrogate based methods suffer from the so-called “curse of dimensionality”, which limits their application to problems with high-dimensional parameters. For this purpose, we develop a novel hierarchical neural hybrid (HNH) method to efficiently compute failure probabilities of these challenging high-dimensional problems. Especially, multifidelity surrogates are constructed based on neural networks with different levels of layers, such that expensive highfidelity surrogates are adapted only when the parameters are in the suspicious domain. The efficiency of our new HNH method is theoretically analyzed and is demonstrated with numerical experiments. From numerical results, we show that to achieve an accuracy in estimating the rare failure probability (e.g., 10-5), the traditional Monte Carlo method needs to solve PDEs more than a million times, while our HNH only requires solving them a few thousand times.

Currently, there are many works exploring how to more fully and efficiently use multi-scale feature maps of deep convolutional neural networks to improve the performance of object detection. But most of these works are devoted to predicting, respectively, on multi-scale feature maps or blending multi-scale feature maps for enriching representation. In this paper, we present a new method of cross fusing feature, named multi-semantic pyramids (MSP), for detecting different-scale objects. Various scale objects are predicted, respectively, by corresponding semantic pyramids (SP), each SP can produce rich semantic features for predicting via reusing inherent multi-scale feature maps from the network backbone. Through promoting the reuse of inherent feature layers, our MSP can improve detection performance with marginal extra cost. In addition, since the reuse connection of the MSP facilitates the conduction of the gradient, the convergence of the network is greatly improved. The experimental results on the PASCAL VOC and COCO datasets illustrate that our MSP can achieve more competitive detection accuracy.

Satellite-based aerosol optical depth (AOD) data are widely used to estimate land surface PM2.5 concentrations in areas not covered by ground PM2.5 monitoring stations. However, AOD data obtained from satellites are typically at coarse spatial resolutions, limiting their applications on small or medium scales. In this paper, we propose a new two-step approach to estimate 1-km-resolution PM2.5 concentrations in Shanghai using high spatial resolution AOD retrievals from MODIS. In the first step, AOD data are refined to a 1×1km2 resolution via a Bayesian AOD retrieval method. In the second step, a hierarchical Gaussian process model is used to estimate PM2.5 concentrations. We evaluate our approach by model fitting and out-of-sample cross-validation. Our results show that the proposed approach enjoys accurate predictive performance in estimating PM2.5 concentrations.

Although hydrogen embrittlement (HE) behavior has been extensively studied in bulk materials, little is known about H-related deformation and the fracture of nanograined materials. In this study, H segregation and HE mechanisms of nanograined Fe with different grain sizes are unveiled, following the employment of classical molecular dynamics simulations. The H segregation ratio increased, but the local H concentration at the grain boundaries (GBs) decreased with decreases in the grain size at a given bulk H concentration. The results demonstrate that H atoms increased the yield stress of nanograined models irrespective of the grain size. Furthermore, it is revealed that brittle fractures were inhibited, and the resistance to HE increased as the grain size decreased, due to the fact that the small-grain models had a lower local H concentration at the GBs and an enhanced GB-mediated intergranular deformation. These results are a clear indication of the utility of grain refinement to resist H-induced brittle failure.

This paper presents a GPU (Graphics Processing Unit)-accelerated and LTS (Local-time-Step)-based finite volume Shallow Water Model (SWM). The model performance is compared against the other five model versions (Single CPU versions with/without LTS, Multi-CPU versions with/without LTS, and a GPU version) by simulating three flow scenarios: an idealized dam-break flow; an experimental dam-break flow; a field-scale scenario of tidal flows. Satisfactory agreements between simulation results and the available measured data/reference solutions (water level, flow velocity) indicate that all the six SWM versions can well simulate these challenging shallow water flows. Inter-comparisons of the computational efficiency of the six SWM versions indicate the following. First, GPU acceleration is much more efficient than multi-core CPU parallel computing. Specifically, the speed increase in the GPU can be as high as a hundred, whereas those for multi-core CPU are only 2–3. Second, implementing the LTS can bring considerable reduction: the additional maximum speed-ups can be as high as 10 for the single-core CPU/multi-core CPU versions, and as high as five for the GPU versions. Third, the GPU + LTS version is computationally the most efficient in most cases; the multi-core CPU + LTS version may run as fast as a GPU version for scenarios over some intermediate number of cells.

As efficient separation of variables plays a central role in model reduction for nonlinear and nonaffine parameterized systems, we propose a stochastic discrete empirical interpolation method (SDEIM) for this purpose. In our SDEIM, candidate basis functions are generated through a random sampling procedure, and the dimension of the approximation space is systematically determined by a probability threshold. This random sampling procedure avoids large candidate sample sets for high-dimensional parameters, and the probability based stopping criterion can efficiently control the dimension of the approximation space. Numerical experiments are conducted to demonstrate the computational efficiency of SDEIM, which include separation of variables for general nonlinear functions, e.g., exponential functions of the Karhu nen–Loève (KL) expansion, and constructing reduced order models for FitzHugh–Nagumo equations, where symmetry among limit cycles is well captured by SDEIM.

The non-dispersive infrared (NDIR) instruments are widely applied to multicomponent gas detection in many fields. In this paper, a NDIR instrument using the galvanometer modulation is proposed, which has a common optical path for multicomponent gas detection. Compared with the conventional NDIR instrument using the chopper modulation, the proposed instrument with a simpler configuration has better detection efficiency and stability. The proposed instrument has been successfully used to measure the main gas components of vehicle emissions. The NDIR instrument using the galvanometer modulation has great potential for remote sensing application, where multicomponent gas is always spatially inhomogeneous. [ABSTRACT FROM AUTHOR]

A magnetic fluid (MF)-based magnetic field sensor with a filling-splicing fiber structure is proposed. The sensor realizes Mach–Zehnder interference by an optical fiber cascade structure consisting of single mode fiber (SMF), multimode fiber (MMF), and single-hole-dual-core fiber (SHDCF). The core in the cladding and the core in the air hole of SHDCF are used as the reference and sensing light path, respectively, and the air hole of SHDCF is filled with magnetic fluid to realize magnetic field measurement based on magnetic controlled refractive index (RI) characteristics. The theoretical feasibility of the proposed sensing structure is verified by Rsoft simulation, the optimized length of SHDCF is determined by optical fiber light transmission experiment, and the SHDCFs are well fused without collapse through the special parameter setting. The results show that the sensitivity of the sensor is −116.1 pm/Gs under a magnetic field of 0~200 Gs with a good long-term operation stability. The proposed sensor has the advantages of high stability, fast response, simple structure, and low cost, which has development potential in the field of miniaturized magnetic field sensing.

Background MiR-92b was upregulated in gliomas. However, the association of miR-92b with glioma cell apoptosis and survival remains unknown. Methods Proliferation capability of glioma cells upon tranfection with miR-92b mimics or inhibitors was detected by mutiple analyses, including MTT assays, colony formation assay. Apoptosis abilities of glioma cells were detected by flow cytometric analysis. The target of miR-92b was determined by luciferase reporter and western blot. The association of miR-92b with outcome was examined in twenty glioma patients. Results MiR-92b expression was significantly increased in high-grade gliomas compared with lowgrade gliomas, and positively correlated with the degree of glioma infiltration. Overexpression of miR-92b increased cell proliferation, whereas knockdown of miR-92b decreased cell proliferation via modulating the levels of the target, Target prediction analysis and a dual luciferase reporting assay confirmed that the inhibitory protein-coding Dickkopf-3 gene (DKK3) was a direct target of miR-92b. Furthermore, miR-92b could regulate the expression of downstream genes of the Wnt/beta-catenin signaling pathway, such as Bcl2, cmyc and p-c-Jun, in glioma cells. Finally, the increased level of miR-92b expression in highgrade gliomas confers poorer overall survival. Conclusions The present data indicates that miR-92b directly regulate cell proliferation and apoptosis by targeting DKK3 and act as prognostic factors for glioma patients. [ABSTRACT FROM AUTHOR]

Surface-enhanced IR–visible sum frequency generation (SFG) was studied using Ag and Au films over nanospheres (AgFON and AuFON), which provided large area of reproducible nanoscale structures with well-defined morphology. SFG vibrational spectra for a self-assembled monolayer of octadecanethiol were investigated on spheres with diameters ranging from 300 nm to 620 nm. With an input wavelength of 532 nm, a sphere diameter near 360 nm produced the maximum enhancement, which was consistent with the localized surface-plasmon resonant wavelength identified by minimum reflectivity. The measured second-order susceptibility for the asymmetric CH3stretch mode of octadecanethiol was enhanced by up to 27 times on AgFON, which corresponded to an SFG enhancement factor of ∼730. The SFG enhancement factor for AuFON was a quarter of that from AgFON. The SFG enhancement factor for the symmetric CH3mode was about 10 times smaller than that for the asymmetric CH3mode. This difference can be explained by the highly directional electrical-field parallel to the surface, created at the junction between nanospheres. Polarization-dependent studies also indicated that excitations with the electrical field parallel to the surface was the main contribution to the observed surface enhancements, and the electrical field perpendicular to the surface offered little enhancement. [ABSTRACT FROM AUTHOR]

The formation of intermediate and by-products in the synthesis of 4,4′-methylenedimethyldiphenylcarbamate (MDC) by the reaction of 4,4′-methylenedianiline (MDA) and dimethyl carbonate (DMC) over Zn(CH3COO)2 catalyst was studied in this paper. The work would be of importance to deeply understand the reaction mechanism and to further improve the yield of aimed product. The intermediate and by-products were isolated from the reaction mixture and identified. The effects of reaction variables upon the formation of the compounds were examined. The mechanism on formation of the intermediate and by-products was proposed based on the experimental results. [ABSTRACT FROM AUTHOR]

The catalysts were prepared from pseudo-boehmite mixed with dilute nitric acid and calcined at different temperatures. The vapour-phase reaction of furan and hydrogen sulfide was performed in a fixed-bed flow in the presence of catalyst. The catalysts were characterized by XRD, N2 adsorption, FT-IR techniques. The Al2O3 calcined at 550 °C has large surface areas which resulted in high yield of thiophene under the conditions: at atmosphere, reaction temperature 500 °C, the ratio of H2S to Furan about 10 (mol) and LHSV 0.2 h−1. The reaction mechanism was proposed for the synthesis of thiophene from furan and hydrogen sulfide over Al2O3. [ABSTRACT FROM AUTHOR]

We present the first measurement of the buried surface electronic states of the conjugated polymer poly2-methoxy-5-(2‘-ethyl-hexyloxy)-1,4-phenylenevinylene (MEH-PPV) using two-dimensional (2D) IR−visible sum frequency generation (SFG). SFG electronic spectra were obtained by scanning the frequencies of both incident visible and IR beams and used to study the surface electronic transitions associated with the C−C stretching of benzene rings located at the backbone of MEH-PPV. Because of the surface confinement effects, the polymer conformation, and consequently the electronic states, at the film/solid interface are different from those of the bulk film. Theoretical analysis based on an oligomer model was employed to estimate the conjugation-length distributions of MEH-PPV at interfaces. Assuming a Gaussian conjugation-length distribution, it was found that the conjugation-length distribution at the MEH-PPV/solid interface was centered at 5.8 monomer units. Similar surface effects were also observed at the air/polymer interface, with a shorter average conjugation length of 5.1 monomer units. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate repression of Klotho on unilateral ureteral obstruction (UUO)-induced renal fibrosis and endothelial-to-mesenchymal transition (EndoMT) in mice. Renal fibrosis model was established by UUO in C57BL/6 male mice. Recombinant Klotho protein was administered to UUO mice as treatment group, and the mice in sham and UUO group were administered with an equal volume of vehicle. EndoMT biomarkers and TGF-β1/Smad2/Snail1 signaling were examined by immunofluorescence, immunohistochemistry, and western blotting assays. UUO deteriorated kidney function and resulted in increased expression of the mesenchymal marker α-smooth muscle actin and decreased expression of vascular endothelial cadherin, an endothelial marker. Moreover, UUO enhanced TGF-β1, phosphorylated Smad2 (p-Smad2), and Snail1 expression. Interestingly, Klotho treatment suppressed UUO-induced TGF-β1, p-Smad3, and Snail1 expression, which was accompanied by alleviation of the EndoMT process. Our findings demonstrated that Klotho significantly ameliorated EndoMT progression by targeting TGF-β1/Smad/Snail1 signaling in UUO mice, which provides the possibility for Klotho-based therapeutic protection against renal fibrosis.

Perovskite solar cells (PSCs) have received a great deal of attention in the science and technology field due to their outstanding power conversion efficiency (PCE), which increased rapidly from 3.9% to 25.5% in less than a decade, comparable to single crystal silicon solar cells. In the past ten years, much progress has been made, e.g. impressive ideas and advanced technologies have been proposed to enlarge PSC efficiency and stability. However, this outstanding progress has always been referred to as small-area (2) PSCs. Little attention has been paid to the preparation processes and their micro-mechanisms for large-area (>1 cm2) PSCs. Meanwhile, scaling up is an inevitable way for large-scale application of PSCs. Therefore, we firstly summarize the current achievements for high efficiency and stability large-area perovskite solar cells, including precursor composition, deposition, growth control, interface engineering, packaging technology, etc. Then we include a brief discussion and outlook for the future development of large-area PSCs in commercialization.

This study investigated the molecular mechanisms underlying the involvement of the Notch signaling pathway and autophagy in the development of pulmonary fibrosis in pigeon breeder’s lung (PBL). Rats were divided into control (Ctrl), PBL model (M), M + D (Notch signaling inhibition), M + W (autophagy inhibition), and M + R (autophagy induction) groups. Lyophilized protein powder from pigeon shedding materials was used as an allergen to construct a fibrotic PBL rat model. The mechanism by which Notch signaling regulated autophagy in the pulmonary fibrosis of PBL was investigated by inhibiting the Notch pathway and interfering with autophagy. Pulmonary interstitial fibrosis was significantly greater in the M group and the M + W group than in the M + D and M + R groups. The expression of α-smooth muscle actin was significantly higher in the M, M + D, and M + W groups than in the Ctrl group (P < 0.05). The expression of the cell autophagy markers Beclin1 and LC3 was lower in the M, M + D, and M + W groups than in the Ctrl group (P < 0.05), whereas Beclin1 and LC3 expressions were higher in the M + D and M + R groups than in the M group. The levels of reactive oxygen species in serum and lung tissues were higher in the M, M + D, M + W, and M + R groups than in the Ctrl group (P < 0.05). The Notch signaling pathway is involved in the pathological process of pulmonary fibrosis in the rat model of PBL by regulating autophagy [ABSTRACT FROM AUTHOR]

Based on the historical data of air ozone monitoring of Pearl River Delta from 2016 to 2020, the temporal and spatial variation characteristics of ozone in the Pearl River Delta were analyzed. The results showed that the mean change curves of Q3 in the seven cities in the Pearl River Delta region from 2016 to 2020 were M-shaped, and the change trend was basically the same, except Huizhou and Zhuhai. The over standard rate of daily mean value of Q3 in Jiangmen City from 2016 to 2020 was more than 10%, and the over standard situation of daily mean value of Q3 was serious. In the Pearl River Delta region, the change trend of the monthly mean value of Q3 in the same year was basically the same. On the whole, the mean value from August to November was higher, and the mean value in June was lower. The peak of Q3 concentration appeared between 12:00 and 16:00 in the daytime, and it was generally low at night.

Optimal experimental design (OED) is of great significance in efficient Bayesian inversion. A popular choice of OED methods is based on maximizing the expected information gain (EIG), where expensive likelihood functions are typically involved. To reduce the computational cost, in this work, a novel double-loop Bayesian Monte Carlo (DLBMC) method is developed to efficiently compute the EIG, and a Bayesian optimization (BO) strategy is proposed to obtain its maximizer only using a small number of samples. For Bayesian Monte Carlo posed on uniform and normal distributions, our analysis provides explicit expressions for the mean estimates and the bounds of their variances. The accuracy and the efficiency of our DLBMC and BO based optimal design are validated and demonstrated with numerical experiments.

Three gossypol molecularly imprinted polymers (MIPs) were prepared by bulk polymerization (MIP1), surface layer imprinting using silica gel as the support (MIP2), and the sol-gel process (MIP3). The as-prepared MIPs were characterized by SEM and nitrogen adsorption−desorption techniques to study the morphology structure. The adsorption experiments exhibited that MIP1 had adsorption capacity as high as 564 mg·g−1. The MIP2 showed faster adsorption kinetics than MIP1 and MIP3. The adsorption equilibrium could be reached for gossypol in 40 min. A selectivity study showed that the adsorption capacity of MIPs for gossypol was about 1.9 times higher than that of the structurally-similar analogs ellagic acid and 6.6 times higher than that of the quercetin. It was found that the pseudo-second-order kinetic model and the Freundlich isotherm model were more applicable for the adsorption kinetics and adsorption isotherm of gossypol binding onto the MIP1 and MIP2, respectively. Results suggested that among those three, the MIP2 was a desirable sorbent for rapid adsorption and MIP1 was suitable for selective recognition of gossypol.

The computed tomography image spectrometer (CTIS) is a snapshot hyperspectral imaging technique, which enables hyperspectral image acquisition in a dynamic scene. However, traditional image reconstruction methods with no explicit constraints will introduce high-frequency noise. The low-rank property has been used in hyperspectral image denoising and achieved great effects. We develop an effective method of low-rank estimation (LRE) for CTIS image reconstruction, which shows significant improvements in both the image quality and the spectral quality of the reconstructed image. Compared with the traditional methods, the peak signal-to-noise ratio of the LRE hyperspectral image can be increased by 8 dB, and the spectral-angular mapping can be decreased by 4 times. [ABSTRACT FROM AUTHOR]

Reliable typing of yeast strains is of great importance to the alcoholic beverage industry to ensure a reliable fermentation process and high-quality products. Saccharomyces cerevisiae is the most used yeast species in wine, sake, and ale beer fermentation, whereas Saccharomyces uvarum is more commonly used for cider fermentation and, due to its cryotolerance, white wine production. We propose a promising method for species identification and strain discrimination of S. cerevisiae and S. uvarum using Raman spectroscopy in combination with convolutional neural networks (CNNs). Raman spectra collected from various S. cerevisiae and S. uvarum strains were accurately classified at the species level using random forest. Cultivation time and temperature did not significantly affect the spectral reproducibility and discrimination capability. An overall accuracy of 91.9% was achieved to discriminate 27 yeast isolates at the strain level using a CNN model. Raman-CNN further identified eight yeast isolates spiked in grape juice with an accuracy of 98.1%. Raman spectral signatures derived from diverse protein and lipid compositions may contribute to this discrimination. The proposed approach also precisely predicted the concentration of a specific yeast strain within a yeast mixture with an R² of 0.9913 and an average error of 4.09%. The entire analysis can be completed within 1 hour following cultivation and only requires simple sample preparation and low consumable cost. Taken together, Raman spectroscopy coupled with CNN is a robust, accurate, and reliable approach for typing of fermentation yeast strains. IMPORTANCE The use of S. cerevisiae and S. uvarum yeast starter cultures is a common practice in the alcoholic beverage fermentation industry. As yeast strains from different or the same species have variable fermentation properties, rapid and reliable typing of yeast strains plays an important role in the final quality of the product. In this study, Raman spectroscopy combined with CNN achieved accurate identification of S. cerevisiae and S. uvarum isolates at both the species and strain levels in a rapid, non-destructive, and easy-to-operate manner. This approach can be utilized to test the identity of commercialized dry yeast products and to monitor the diversity of yeast strains during fermentation. It provides great benefits as a high-throughput screening method for agri-food and the alcoholic beverage fermentation industry. This proposed method has the potential to be a powerful tool to discriminate S. cerevisiae and S. uvarum strains in taxonomic, ecological studies and fermentation applications. [ABSTRACT FROM AUTHOR]

It is challenging to estimate the air exchange rate (AER) dynamically in naturally ventilated livestock buildings such as dairy houses due to the influence of complex and variable outdoor environmental factors, large opening ratios, and the confusion of inflow and outflow at openings. This makes it difficult to efficiently regulate the opening ratio to meet the ventilation requirements in naturally ventilated livestock buildings. In this study, the air exchange rates of naturally ventilated cattle houses (NVCHs) in different seasons and opening ratios were obtained through field measurements and computational fluid dynamics (CFD) simulations. A fast and efficient machine learning framework was proposed and examined to predict AER based on the gradient boosting decision tree (GBDT) combined with Bayesian optimization. Compared with commonly used machine learning models such as multilayer perceptrons (MLPs) and support vector machines (SVMs), the proposed GBDT model has higher prediction accuracy and can avoid falling easily into local optima. Compared with the existing mechanical model based on the Bernoulli equation, the proposed GBDT model showed a slightly higher prediction than the mechanistic model and was much easier to use in AER estimation when inputting easily collected environmental factors in practical applications. Using Bayesian optimization could dramatically reduce the computing time when determining the optimal hyperparameter for establishing the GBDT model, dramatically saving on computing resources. Based on the Bayesian optimized GBDT model, the desirable opening ratio of the side curtain can be determined for automatically regulating the AER of cattle houses in future applications. [ABSTRACT FROM AUTHOR]

The article focuses on oligomeric semiconducting nanozyme with ultrafast electron transfers alleviates acute brain injury. Topics include the artificial enzymes have attracted wide interest in disease diagnosis and biotechnology due to high stability, easy synthesis, and cost effectiveness, and the oligomeric nanozyme (O-NZ) with ultrafast electron transfer.