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Abstract Purpose This study aims to investigate the association of serum TSH with BMD in Chinese adults with normal thyroid function. Methods These participants were divided into tertiles based on serum TSH levels. Linear regression model and multinomial logistic regression models were used to analyze the associations of continuous BMD and categorical BMD with serum TSH, respectively. Results In women younger than 60 years, BMD decreased with the increase of TSH at normal level, while in women older than 60 years, BMD increased with the increase of TSH at normal level; besides, the BMD of women younger than 60 years old was significantly higher than that of women over 60 years old (156.05 ± 39.34 mg/cm3 vs. 86.95 ± 29.51 mg/cm3, P

BackgroundShuanghuanglian is a Chinese medicine composed of Honeysuckle Flower, Baical Skullcap Root, and Fructus Forsythiae. It has various effects, including anti-inflammatory, antibacterial, antiviral, and immunomodulatory effects. The fermented product of Shuanghuanglian can be used as an antibiotic alternative, as it has similar efficacy, which may improve the immunity, feed intake and utilization efficiency of laying hens, thus improving their production performance. The aim of this study was to optimize the fermentation conditions for Shuanghuanglian using single factor and response surface methodology, evaluate the chemical and microbial composition of the Shuanghuanglian fermentation liquor (SFL), and explore the effects of SFL on the production performance of laying hens.MethodsA total of 288 Xinyang black-feather laying hens (50 week-old) were randomly allocated to four treatments with nine replicates, each replicate containing eight hens, for a total of 37 days trial (including a 7-day adaptation period). The treatments included a control group (0% SFL in drinking water) and drinking water supplemented with 0.3, 0.5, or 0.7% SFL.ResultsThe fermentation optimization conditions for Shuanghuanglian were selected as a solid-to-liquid ratio at 1:7, 3% inoculation quantity, fermentation temperature at 28°C for 5 days, initial pH of 7, 60 mesh (sieved), and rotation speed of 150 r/min. Various bioactive compounds, such as myrtenol, 2-hexyn-1-ol, arsenous acid tris(trimethylsilyl) ester, 3(10)-caren-4-ol, and oxime-, methoxy-phenyl, were detected in SFL. The most abundant bacterial phyla in SFL were Proteobacteria and Firmicutes, with Acinetobacter being the most abundant genus. The most abundant fungal phyla were Phragmoplastophyta and Magnoliophyta. The 0.5 and 0.7% SFL supplementation in water increased egg weight and laying rate, while decreasing the feed-to-egg ratio of laying hens compared with the control group (p 0.05) in albumen height, egg shape index, egg thickness, and yolk color of the eggs.ConclusionSupplementation of SFL under optimized conditions had a positive impact on the production performance of laying hens, especially when the supplementation amount reached 0.5%. This study provides a theoretical basis for the application of Shuanghuanglian in the commercial egg industry.

Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6 inhibitors) can significantly extend tumor response in patients with metastatic luminal A breast cancer, yet intrinsic and acquired resistance remains a prevalent issue. Understanding the molecular features of CDK4/6 inhibitor sensitivity and the potential efficacy of their combination with novel targeted cell death inducers may lead to improved patient outcomes. Herein, we demonstrate that ferroptosis, a form of regulated cell death driven by iron-dependent phospholipid peroxidation, partly underpins the efficacy of CDK4/6 inhibitors. Mechanistically, CDK4/6 inhibitors downregulate the cystine transporter SLC7A11 by inhibiting SP1 binding to the SLC7A11 promoter region. Furthermore, SLC7A11 is identified as critical for the intrinsic sensitivity of luminal A breast cancer to CDK4/6 inhibitors. Both genetic and pharmacological inhibition of SP1 or SLC7A11 enhances cell sensitivity to CDK4/6 inhibitors and synergistically inhibits luminal A breast cancer growth when combined with CDK4/6 inhibitors in vitro and in vivo. Our data highlight the potential of targeting SLC7A11 in combination with CDK4/6 inhibitors, supporting further investigation of combination therapy in luminal A breast cancer.

Abstract Tobacco mosaic virus (TMV; genus Tobamovirus) is one of the most prevailing pathogens that seriously affects the quality and yield of tobacco (Nicotiana tabacum) leaves. Cross-protection using mild strains is a potential strategy for the biological prevention of plant viral diseases. Complementary mutations in attenuated strains may cause attenuated ones to suddenly evolve into virulent strains, which limits the application of cross-protection in practice. To data there has been no study on engineering the complementary mutation sites to generate stable attenuated mutants for cross-protection. In this study, we found that the substitution of the conserved arginine at position 88 (R88) in p126 protein with alanine (A) abolished the cell-to-cell movement and reduced the replication of TMV. However, a spontaneous complementary mutation of serine at position 114 (S114) to lysine (K) in p126 restored TMV virulence. Substitution of S114 with R in p126 restored the systemic infection but not the virulence of TMV, therefore, the mutant TMV-R88A/S114R was an attenuated one. Furthermore, our results showed that TMV-R88A/S114R was a stable attenuated mutant, and could effectively protect tobacco plants against the wild-type TMV infection. This study reports a promising TMV mild mutant for cross-protection in tobacco plants by modifying the complementary mutation site in p126.

Extraction and purification of polysaccharides from the seed kernel of Acer truncatum Bungeto investigate their physicochemical properties and hypoglycemic activity. In the study, the polysaccharide was obtained by water extraction and ethanol precipitation from seed kernel of Acer truncatum Bunge, and the extraction process was optimized by response surface method. The polysaccharide was purified by Sevage deproteinization and column chromatography. The composition and structure of the purified polysaccharide were characterized by infrared spectroscopy, thermogravimetric analysis and ion chromatography, and its hypoglycemic activity was further investigated by the insulin resistance model of liver cancer cell (IR-HepG2). The results showed that the yield of crude polysaccharide (PATM) was 18.17% under the conditions of extraction times 1, liquid-solid ratio 30:1 mL/g, extraction temperature 80 ℃ and extraction time 3.5 h. The purified polysaccharide (PATM-3-1) obtained by the Sevage deproteinization, DEAE-DE cellulose 52 column and SephadexG-100 gel column had the characteristic peak of infrared spectrum of polysaccharide component, and was composed of D-galacturonic acid, L-arabinose, D-galactose, L-rhamnose, D-glucose, D-xylose, D-mannose, D-glucuronic acid, L-fucose, D-ribose and D-glucosamine. The results of hypoglycemic activity experiment in vitro showed that PATM-3-1 had strong α-amylase inhibitory activity, and could significantly (P

In recent years, underground logistics systems have attracted more and more attention from scholars and are considered to be a promising new green and intelligent transportation mode. This paper proposes a yard design problem considering an underground container logistics system. The structure and workflow of the underground container logistics system are analyzed, and key features are recognized for the yard design problem, such as the container block layout direction, the lane configuration in the yard, and the number of container blocks. We formulate the problem into mathematical models under different scenarios of the key features with the comprehensive objective of maximizing the total throughput and minimizing the total operation cost simultaneously. An improved tabu search algorithm is designed to solve the problem. Experimental results show that the proposed algorithm can generate a satisfactory layout design solution for a real-size instance. Our research studies different container yard design options for introducing the underground logistics system into port terminals, which provides an important scientific foundation for promoting the application of underground container logistics systems.

Background Limited response to programmed death ligand-1 (PD-L1)/programmed death 1 (PD-1) immunotherapy is a major hindrance of checkpoint immunotherapy in non-small cell lung cancer (NSCLC). The abundance of PD-L1 on the tumor cell surface is crucial for the responsiveness of PD-1/PD-L1 immunotherapy. However, the negative control of PD-L1 expression and the physiological significance of the PD-L1 inhibition in NSCLC immunotherapy remain obscure.Methods Bioinformatics analysis was performed to profile and investigate the long non-coding RNAs that negatively correlated with PD-L1 expression and positively correlated with CD8+T cell infiltration in NSCLC. Immunofluorescence, in vitro PD-1 binding assay, T cell-induced apoptosis assays and in vivo syngeneic mouse models were used to investigate the functional roles of LINC02418 and mmu-4930573I07Rik in regulating anti-PD-L1 therapeutic efficacy in NSCLC. The molecular mechanism of LINC02418-enhanced PD-L1 downregulation was explored by immunoprecipitation, RNA immunoprecipitation (RIP), and ubiquitination assays. RIP, luciferase reporter, and messenger RNA degradation assays were used to investigate the m6A modification of LINC02418 or mmu-4930573I07Rik expression. Bioinformatics analysis and immunohistochemistry (IHC) verification were performed to determine the significance of LINC02418, PD-L1 expression and CD8+T cell infiltration.Results LINC02418 is a negative regulator of PD-L1 expression that positively correlated with CD8+T cell infiltration, predicting favorable clinical outcomes for patients with NSCLC. LINC02418 downregulates PD-L1 expression by enhancing PD-L1 ubiquitination mediated by E3 ligase Trim21. Both hsa-LINC02418 and mmu-4930573I07Rik (its homologous RNA in mice) regulate PD-L1 therapeutic efficacy in NSCLC via Trim21, inducing T cell-induced apoptosis in vitro and in vivo. Furthermore, METTL3 inhibition via N6-methyladenosine (m6A) modification mediated by YTHDF2 reader upregulates hsa-LINC02418 and mmu-4930573I07Rik. In patients with NSCLC, LINC02418 expression is inversely correlated with PD-L1 expression and positively correlated with CD8+T infiltration.Conclusion LINC02418 functions as a negative regulator of PD-L1 expression in NSCLC cells by promoting the degradation of PD-L1 through the ubiquitin-proteasome pathway. The expression of LINC02418 is regulated by METTL3/YTHDF2-mediated m6A modification. This study illuminates the underlying mechanisms of PD-L1 negative regulation and presents a promising target for improving the effectiveness of anti-PD-L1 therapy in NSCLC.

For a wide spectrum of agricultural market participants, building price forecasts of various agricultural commodities has always been a vital project. In this work, we approach this problem for the weekly wholesale price index of edible oil in the Chinese market during a ten-year period of January 1, 2010–January 3, 2020 through the exploration of the non-linear auto-regressive neural network as the forecast model. Specifically, we investigate forecast performance stemming from different settings of models, which include considerations of training algorithms, hidden neurons, delays, and how the data are segmented. With the analysis, a relatively simple model is constructed and it produces performance that is rather accurate and stable. Particularly, performance in terms of relative root mean square errors is 2.80%, 3.01%, and 1.80% for training, validation, and testing, respectively. Forecast results here could be utilized as part of technical analysis and/or combined with other fundamental forecasts as part of policy analysis.

Abstract Objective Inhibitors of cyclin‐dependent kinase 4 and 6 (CDK4/6) are targeted therapeutic drugs for breast cancer treatment. The mechanism of resistance to these inhibitors requires further investigation. Methods We used bioinformatics to screen differentially expressed genes between cells that were susceptible and resistant to CDK4/6 inhibitors. Quantitative real‐time PCR (qRT‐PCR) was used to identify gene expressions in different cell lines. Cell viability, colony formation, cell cycle, and apoptosis assays were used to evaluate the effect of carboxypeptidase vitellogenic like (CPVL) on breast cancer cells under the condition of CDK4/6 inhibitors. Gene set enrichment analysis (GSEA) suggested the potential regulatory pathway of CPVL in breast cancer. Xenograft formation assay was conducted in nude mice to study the role of CPVL in vivo. Results Based on bioinformatics analysis and qRT‐PCR, CPVL was identified more abundantly in cells that were resistant than sensitive to CDK4/6 inhibitors. Overexpressed or knocked down CPVL regulated the effects of CDK4/6 inhibitors in resistant cell lines. GSEA showed that resistance might be induced by CPVL through altered phosphatase and tensin homolog (PTEN)‐related pathways. Our findings showed that CPVL negatively regulates PTEN to impact the anticancer effects of CDK4/6 inhibitors in vitro and in vivo. Conclusion CPVL might be a key factor in regulating breast cancer resistance to CDK4/6 inhibitors.

The global health crisis caused by the COVID-19 pandemic has led to a surge in demand and use of personal protective equipment (PPE) such as masks, putting great pressure on social production and the environment. It is urgent to find an efficient and non-destructive disinfection method for the safe reuse of PPE. This study proposes a PPE disinfection method that uses erythrosine, a U.S. Food and Drug Administration-approved food dye, as photosensitizer to produce singlet oxygen for virus inactivation, and indicates the completion of disinfection by its photobleaching color change. After spraying 100 μL of 10 μM erythrosine on the surface of the mask for 3 times and light exposure for 25 min, the titer of coronavirus decreased by more than 99.999%, and the color of erythrosine on the mask surface disappeared. In addition, the structure of the mask was intact and the filtration efficiency was maintained at > 95% after 10 cycles of erythrosine treatment. Therefore, this disinfection method can provide at least 10 cycles of reuse with the advantages of high safety and convenient, and the completion of disinfection can be indicated by its photobleaching, which is suitable for hospitals and daily life to reduce the consumption of PPE.

Centralized heating is an energy-saving and environmentally friendly way that is strongly promoted by the state. It can improve energy utilization and reduce carbon emissions. However, Centralized heating depends on accurate heat demand forecasting. On the one hand, it is impossible to save energy if over producing, while on the other hand, it is impossible to meet the heat demand of enterprises if there is not enough capacity. Therefore, it is necessary to forecast the future trend of heat consumption, so as to provide a reliable basis for enterprises to reasonably deploy fuel stocks and boiler power. At the same time, it is also necessary to analyze and monitor the steam consumption of enterprises for abnormalities in order to monitor pipeline leakage and enterprise gas theft. Due to the nonlinear characteristics of heat load, it is difficult for traditional forecasting methods to capture data trend. Therefore, it is necessary to study the characteristics of heat loads and explore suitable heat load prediction models. In this paper, industrial steam consumption of a paper manufacturer is used as an example, and steam consumption data are periodically analyzed to study its time series characteristics; then steam consumption prediction models are established based on ARIMA model and LSTM neural network, respectively. The prediction work was carried out in minutes and hours, respectively. The experimental results show that the LSTM neural network has greater advantages in this steam consumption load prediction and can meet the needs of heat load prediction.

For policymakers and investors, forecasting prices of energy indices has always been an important task. The present work focuses on the Chinese market and explores the daily price forecasting problem for the new energy index in the mainland during the period spanning January 4, 2016 – December 31, 2020. Our analysis is facilitated through the nonlinear autoregressive neural network model and one hundred and twenty model settings are tested in the fields of the algorithm for training the model, the number of hidden neurons utilized, the number of delays utilized, and the ratio utilized for segmenting the price series into different phases. Analysis here leads to the construction of a rather simple model based upon four delays and two hidden neurons with the Levenberg-Marquardt algorithm for training, which generates accurate and stable forecast results, with relative root mean square errors below 1.80% and mean absolute percentage errors below 1.30% across training, validation, and testing phases and for the overall sample. This constructed model also leads to statistically significantly better forecasting performance than a linear autoregressive model at the 1% significance level based upon the modified Diebold-Mariano test. The model built could be used as part of policy analysis for policymakers and decision making for investors. The forecasting results might also benefit design of similar energy indices by offering reference information in terms of price paths projected through the model.

Pancreatic cancer remains one of the most lethal malignancies worldwide. The combination of the first-line standard agent gemcitabine (GEM) with the molecular-targeted drug erlotinib (Er) has emerged as a promising strategy for pancreatic cancer treatment. However, the clinical benefit from this combination is still far from satisfactory due to the unfavorable drug antagonism and the fibrotic tumor microenvironment. Herein, we propose a membrane-camouflaged dual stimuli-responsive delivery system for the co-delivery of GEM and Er into pancreatic cancer cells and tissues to block the antagonism, as well as reshapes profibrotic tumor microenvironment via simultaneous delivery of small interference RNA (siRNA) for synergistic pancreatic cancer treatment. This “all-in-one” delivery system exhibits sensitive GSH and pH-dependent drug release profiles and enhances the inhibitory effects on the proliferation and migration of tumor cells in vitro. Excitingly, the systemic injection of such a biomimetic drug co-delivery system not only resulted in superior inhibitory effects against orthotopic pancreatic tumor and patient-derived tumor (PDX), but also greatly extended the survival rate of tumor-bearing mice. Our findings provide a promising therapeutic strategy against pancreatic cancer through the enhanced synergistic effect of target therapy, chemotherapy and anti-fibrotic therapy, which represents an appealing way for pancreatic cancer treatment.

The spread of antibiotic resistant pathogens and antibiotic resistance genes (ARGs) in the environment poses a serious threat to public health. However, existing methods are difficult to effectively remove antibiotic resistant pathogens and ARGs from the environment. In this study, we synthesized a new acridine-based photosensitizer, 2,7-dibromo-9-mesityl-10-methylacridinium perchlorate (YM-3), by the heavy atom effect, which could photodynamically inactivate antibiotic resistant pathogens and reduce ARGs by generating singlet oxygen (1O2) in an aqueous environment. The 1O2 yield of YM-3 was 4.9 times that of its modified precursor. YM-3 could reduce the culturable number and even the viable counts of methicillin-resistant Staphylococcus aureus and carbapenem-resistant Acinetobacter baumannii to 0 (inactivation rate > 99.99999%) after 2 and 8 h of low-intensity blue light (15 W/m2) irradiation, respectively. After 20 h of light exposure, the copy numbers of ARGs in both bacteria were reduced by 5.80 and 4.48 log, respectively, which might indicate that ARGs had been degraded. In addition, YM-3 still had an efficient bactericidal effect after five inactivation cycle. These characteristics of ultra-low light intensity requirement and efficient bactericidal ability make YM-3 have good application prospects for disinfection in indoor and sunlight environment.

Abstract Risk of metastasis is increased by the presence of chromosome 3 monosomy in uveal melanoma (UM). This study aimed to identify more accurate biomarker for risk of metastasis in UM. A total of 80 patients with UM from TCGA were assigned to two groups based on the metastatic status, and bioinformatic analyses were performed to search for critical genes for risk of metastasis. SLC25A38, located on chromosome 3, was the dominant downregulated gene in metastatic UM patients. Low expression of SLC25A38 was an independent predictive and prognostic factor in UM. The predictive potential of SLC25A38 expression was superior to that of pervious reported biomarkers in both TCGA cohort and GSE22138 cohort. Subsequently, its role in promoting metastasis was explored in vitro and in vivo. Knock-out of SLC25A38 could enhance the migration ability of UM cells, and promote distant metastasis in mice models. Through the inhibition of CBP/HIF-mediated pathway followed by the suppression of pro-angiogenic factors, SLC25A38 was situated upstream of metastasis-related pathways, especially angiogenesis. Low expression of SLC25A38 promotes angiogenesis and metastasis, and identifies increased metastatic risk and worse survival in UM patients. This finding may further improve the accuracy of prognostic prediction for UM.

Although 2D MoS2 alone shows excellent gas-sensing performance, it is prone to stacking when used as the sensitive layer, resulting in insufficient contact with the target gas and lower sensitivity. To solve this, a 2D-MoS2/1D-CuPc heterojunction was prepared with different weight ratios of MoS2 nanosheets to CuPc micro-nanowires, and its room-temperature gas-sensing properties were studied. The response of the 2D-MoS2/1D-CuPc heterojunction to a target gas was related to the weight ratio of MoS2 to CuPc. When the weight ratio of MoS2 to CuPc was 20:7 (7-CM), the gas sensitivity of MoS2/CuPc composites was the best. Compared with the pure MoS2 sensor, the responses of 7-CM to 1000 ppm formaldehyde (CH2O), acetone (C3H6O), ethanol (C2H6O), and 98% RH increased by 122.7, 734.6, 1639.8, and 440.5, respectively. The response of the heterojunction toward C2H6O was twice that of C3H6O and 13 times that of CH2O. In addition, the response time of all sensors was less than 60 s, and the recovery time was less than 10 s. These results provide an experimental reference for the development of high-performance MoS2-based gas sensors.

Abstract Background Poly(D, L-lactic-co-glycolic acid) (PLGA) nanoparticles have potential applications as a vaccine adjuvant and delivery system due to its unique advantages as biodegradability and biocompatibility. Experimental We fabricated cationic solid lipid nanoparticles using PLGA and dimethyl-dioctadecyl-ammonium bromide (DDAB), followed by loading of model antigen OVA (antigen ovalbumin, OVA257-264) to form an OVA@DDAB/PLGA nano-vaccine. And we investigated the intracellular signaling pathway in dendritic cells in vitro and antigen transport pathway and immune response in vivo mediated by an OVA@DDAB/PLGA nano-vaccine. Results In vitro experiments revealed that the antigen uptake of BMDCs after nanovaccine incubation was two times higher than pure OVA or OVA@Al at 12 h. The BMDCs were well activated by p38 MAPK signaling pathway. Furthermore, the nano-vaccine induced antigen escape from lysosome into cytoplasm with 10 times increased cross-presentation activity than those of OVA or OVA@Al. Regarding the transport of antigen into draining lymph nodes (LNs), the nano-vaccine could rapidly transfer antigen to LNs by passive lymphatic drainage and active DC transport. The antigen+ cells in inguinal/popliteal LNs for the nano-vaccine were increased over two folds comparing to OVA@Al and OVA at 12 h. Moreover, the antigen of nano-vaccine stayed in LNs for over 7 days, germinal center formation over two folds higher than those of OVA@Al and OVA. After immunization, the nano-vaccine induced a much higher ratio of IgG2c/IgG1 than OVA@Al. It also effectively activated CD4+ T, CD8+ T and B cells for immune memory with a strong cellular response. Conclusion These results indicated that DDAB/PLGA NP was a potent platform to improve vaccine immunogenicity by p38 signaling pathway in BMDCs, enhancing transport of antigens to LNs, and higher immunity response. Graphical Abstract

Artemisia annua residue (ARR) is a pharmaceutical by-product produced after the extraction of artemisinin; it is rich in protein, crude fat, vitamins, trace elements, and bioactive compounds and contains negligible anti-nutritional factors. The present study aimed to optimize the fermentation conditions of ARR, evaluate the compound and microbial compositions of fermented AAR, and explore its effects on the production performance of laying hens. A total of 288 Xinyang black-feather laying hens were randomly allocated into four treatments for 30 days, including a control group (basal diet) and a basal diet supplemented with 1%, 2%, and 4% fermented AAR, respectively. The results showed that the optimized fermentation conditions of AAR were 80% moisture content, 3% inoculation quantity, 34 °C fermentation for 6 days, initial pH at 8, and 60 mesh (sieving). The compounds of 2-furyl-5-methyl furan, deoxyartemisinin, phytol, n-hexadecanoic acid, aromandendrene, and calarene had higher contents (average 6.86%) in the fermented AAR. The bacteria of Proteobacteria and Firmicutes (average 45.18%) were the most abundant phyla, and Acinetobacter, Bacillus, and Brevundimonas (average 15.87%) were the most abundant genera in the fermented AAR. The fungi of Phragmoplastophyta, Vertebrata, and Ascomycota (average 30.13%) were the most abundant phyla, and Magnoliophyta, Mammalia, Wickerhamomyces-Candida_clade, and Aspergillus were the most abundant genera (average 21.12%) in the fermented AAR. Furthermore, dietary supplementation of fermented AAR increased the average daily feed intake (ADFI), egg weight, and albumen height. Dietary supplementation of 2% and 4% fermented AAR increased the laying rate, while 2% fermented AAR increased the Haugh unit and decreased the feed-to-egg ratio. Collectively, it is concluded that fermented AAR has the potential to become a phytogenic feed additive, and dietary supplementation of 2% fermented AAR had better effects on the production performance of laying hens.

Most existing studies model interdependent networks as simple network systems consisting of two or more undirected subnets, and the interdependent edges between the networks are undirected. However, many real-world interdependent networks are coupled by a directed subnet and an undirected subnet, such as supply chain networks coupled with cyber networks, and cyber manufacturing networks coupled with service networks. Therefore, in this work, we focus on a ubiquitous type of interdependent network—the directed–undirected interdependent network—and research the cascading failures of directed–undirected interdependent networks with different coupling patterns. Owing to the diversity of coupling patterns to realistic interdependent network systems, we introduce two types of interdependent edges (i.e., directed-to-undirected and undirected-to-directed interdependent edges). On this basis, we generated different types of directed–undirected interdependent networks with varying coupling patterns (i.e., one-to-one, one-to-many, and many-to-one) and investigated the cascading failure robustness of these types of networks. Finally, we explored the cascading robustness of directed–undirected interdependent networks under two different attack strategies (single-node attack and multi-node attack). Through extensive experiments, we have obtained some meaningful findings: (1) the cascading robustness of directed–undirected interdependent networks is positively related to the overload tolerance coefficient and load exponential coefficient; (2) high-degree nodes and high-in-degree nodes should be protected to improve the cascading robustness of directed–undirected interdependent networks; (3) the cascading robustness of one-to-many interdependent networks can be improved by adding directed-to-undirected interdependent edges; and the cascading robustness of many-to-one interdependent networks can be improved by adding undirected-to-directed interdependent edges.

Thermal coal price forecasts represent an essential issue to investors and policy makers, given its importance as a strategic energy source. The current work aims at exploring usefulness of non-linear auto-regressive neural networks for this forecast problem based upon a data-set of closing prices recorded on a daily basis of thermal coal traded in China Zhengzhou Commodity Exchange during January 4, 2016 – December 31, 2020, which is an important financial index not sufficiently explored in the literature in terms of its price forecasts. Through testing a variety of model settings over algorithms, delays, hidden neurons, and data splitting ratios, the model that produces performance of good accuracy and stabilities is reached. Particularly, the model has five delays and ten hidden neurons and is constructed with the Levenberg-Marquardt algorithm based on the ratio of 80%–10%–10% of the data for training–validation–testing. It leads to relative root mean square errors of 1.48%, 1.49%, and 1.47% for the training, validation, and testing phases, respectively. Usefulness of neural networks for the price forecast issue of thermal coal is demonstrated. Forecast results here could serve as standalone technical forecasts and be combined with other forecasts when conducting policy analysis that involves forming perspectives of trends in prices.

Abstract Flexible electronic skin with features that include sensing, processing, and responding to stimuli have transformed human–robot interactions. However, more advanced capabilities, such as human‐like self‐protection modalities with a sense of pain, sign of injury, and healing, are more challenging. Herein, a novel, flexible, and robust diffusive memristor based on a copolymer of chlorotrifluoroethylene and vinylidene fluoride (FK‐800) as an artificial nociceptor (pain sensor) is reported. Devices composed of Ag/FK‐800/Pt have outstanding switching endurance >106 cycles, orders of magnitude higher than any other two‐terminal polymer/organic memristors in literature (typically 102–103 cycles). In situ conductive atomic force microscopy is employed to dynamically switch individual filaments, which demonstrates that conductive filaments correlate with polymer grain boundaries and FK‐800 has superior morphological stability under repeated switching cycles. It is hypothesized that the high thermal stability and high elasticity of FK‐800 contribute to the stability under local Joule heating associated with electrical switching. To mimic biological nociceptors, four signature nociceptive characteristics are demonstrated: threshold triggering, no adaptation, relaxation, and sensitization. Lastly, by integrating a triboelectric generator (artificial mechanoreceptor), memristor (artificial nociceptor), and light emitting diode (artificial bruise), the first bioinspired injury response system capable of sensing pain, showing signs of injury, and healing, is demonstrated.

ObjectiveReport our preliminary experience of carotid endarterectomy (CEA) for the treatment of carotid near-occlusion (CNO) with recurrent symptoms.Materials and MethodsRetrospectively analyze the demographics, treatment detail, and outcomes data of 122 patients with CNO from 2014 to 2020. According to whether distal full collapse exists, patients were classified into the full collapse group and the non-full collapse group. The incidence of death, myocardial infarction, stroke, and other variables were compared between the two groups.ResultsA total of 122 patients with CNO and recurrent symptoms were enrolled. The demographics were comparable between the two groups. Thirty-day incidence of primary endpoints was 1.85% in the full collapse group and 4.41% in the non-full collapse group. Twelve-month incidence of primary endpoints was 7.41% in the full collapse group and 4.41% in the non-full collapse group. One re-stenosis occurred in the non-full collapse group 8 months after CEA.ConclusionFor patients with CNO with recurrent symptoms, CEA is not worse than the results described in historical control groups, despite whether distal full collapse exists. The shunt is important to avoid intraoperative hypoperfusion and postoperative hyperperfusion. The long-term results should be further evaluated.

On the basis of growing environment, maize can largely be classified into temperate and tropical groups, leaving extensive genetic variation and evolutionary signatures in the maize genome. To identify candidate genes governing flowering time and photoperiod sensitivity, selective signature analysis and SNP- and haplotype-based GWAS were performed using 39,350 high-quality SNP markers in temperate and tropical maize groups consisting of 410 inbred lines phenotyped in three representative experiments in different latitudes. Selective signature analysis revealed 106 selective-sweep regions containing 423 candidate genes involved mainly in biological regulation and biosynthesis pathways. Among these genes, 25 overlapped with known genes governing flowering time and photoperiod sensitivity and 37 were also detected by GWAS for days to tassel, anthesis-silk interval, and photoperiod sensitivity measured by days to silking. Only two of the candidate genes governing flowering time overlapped selective signals. Most haplotype alleles within significant haplotype loci showed the same direction of effect on flowering time and photoperiod sensitivity. The inbred lines carrying GATT at HapL499 (haplotype locus 499) on chromosome 1 had relatively short flowering times. Lines carrying CA at HapL4054 on chromosome 10, TA at HapL4055 on chromosome 10, and GTTGT at HapL978 on chromosome 2 were less sensitive to photoperiod than lines carrying other haplotype alleles. Haplotype loci associated with flowering time and photoperiod sensitivity explained respectively 17.5%–18.6% and 11.2%–15.5% of phenotypic variation. Candidate genes and favorable haplotypes identified in this study may support the more efficient utilization of maize germplasm groups. Keywords: Selective signature analysis, GWAS, Maize, Flowering time, Photoperiod sensitivity

Sine oculis homeobox 1 (SIX1), a key transcription factor for regulating aerobic glycolysis, participates in the occurrence of various cancer types. However, the role of SIX1 in melanoma and the upstream regulating mechanisms of SIX1 remain to be further investigated. MicroRNAs (miRNAs) have emerged as key regulators in tumorigenesis and progression. Here, we show that miR-489-3p suppresses SIX1 expression by directly targeting its 3′ untranslated region (3′ UTR) in melanoma cells. miR-489-3p suppressed melanoma cell proliferation, migration, and invasion through inhibition of SIX1. Mechanistically, by targeting SIX1, miR-489-3p dampens glycolysis, with decreased glucose uptake, lactate production, ATP generation, and extracellular acidification rate (ECAR), as well as an increased oxygen consumption rate (OCR). Importantly, glycolysis regulated by the miR-489-3p/SIX1 axis is critical for its regulation of melanoma growth and metastasis both in vitro and in vivo. In melanoma patients, miR-489-3p expression is negatively correlated with SIX1 expression. In addition, patients who had increased glucose uptake in tumors and with metastasis assessed by positron emission tomography (PET) scans showed decreased miR-489-3p expression and increased expression of SIX1. Collectively, our study demonstrates the importance of the miR-489-3p/SIX1 axis in melanoma, which can be a potential and a promising therapeutic target in melanoma. Keywords: miR-489-3p, SIX1, melanoma, glycolysis, metabolism

Price forecasting is a key concern for market participants in the agriculture sector. This study explores usefulness of the nonlinear autoregressive neural network (NARNN) and NARNN with exogenous inputs (NARNN–X) for forecasting issues in data sets of daily prices over periods of greater than fifty years for soybeans and soybean oil. The exogenous input in the NARNN–X for prices of soybeans (soybean oil) are prices of soybean oil (soybeans). Through investigating various model settings across the algorithm, delay, hidden neuron, and data splitting ratio, models resulting in accurate and stable performance for these two commodities are arrived at. The overall relative root mean square errors based on the chosen NARNNs (NARNN–Xs) are 1.701% (1.695%) and 1.777% (1.775%) for soybeans and soybean oil, respectively. Usefulness of the machine learning approach for price forecasting issues of the two commodities is demonstrated, as well as potential usefulness of prices of closely related commodities for providing predictive content. Results here could be used on a standalone basis as technical forecasts or combined with fundamental forecasts for forming perspectives of price trends and conducting policy analysis. The empirical framework here should not be difficult to implement, which is an important consideration to many decision makers, and has potential to be generalized for forecasting prices of other commodities.

Abstract The heterojunction photodetector between n‐SrTiO3 (n‐STO) and p‐CuS‐ZnS (p‐CZS) is prepared by a simple chemical bath deposition. The p‐CZS/n‐STO photodetector exhibits excellent self‐powered characteristics under 390‐nm light illumination, including high photosensitivity (on/off ratio of 300), fast response speed (0.7/94.6 ms), and good wavelength selectivity (410‐380 nm). More importantly, the self‐powered n‐STO photodetectors can be regulated by varying the composition of CZS film (p‐CZS, p‐CuS, and n‐ZnS). All devices exhibit a large open‐circuit voltage and show different self‐powered behaviors because of the different built‐in electric fields. The open‐circuit voltages of the CZS/STO, CuS/STO, and ZnS/STO devices are measured to be 0.56, 0.30, and 0.35 V, respectively. This work provides a simple and effective way to fabricate tunable self‐powered photodetectors by varying the composition of the nanocomposite film.

Temporomandibular joints (TMJs) have a biomechanical relationship with dental occlusion. Aberrant occlusion initiates degenerative remodeling responses in TMJ condyles. Aging is a promoting factor of osteoarthritis (OA) development. The aim of this study was to assess the effect of aging on degenerative remodeling in TMJ condyles in response to occlusal biomechanical stimulation caused by the installation of aberrant prostheses and observe rehabilitation after their removal. The experiments involved 84 female C57BL/6J mice (42 at 6 weeks old and 42 at 28 weeks old). A bilateral anterior crossbite (BAC) model was developed, and the TMJs were sampled at 3, 7, and 11 weeks. BAC was removed at 7 weeks in a subset of mice, which accepted BAC treatment at 6 week of age, and maintained for another 4 weeks after BAC removal. TMJ changes were assessed with micro-CT, histomorphology, immunohistochemistry (IHC), and immunofluorescence staining assays. The results showed that BAC induced typical OA-like TMJ lesions that were more severe in the elder groups as evaluated by the acellular zones, clustered chondrocytes, fissures between cartilage and subchondral bone, reductions in matrix amount and the cartilage thickness as revealed by histomorphological measurements, and subchondral bone loss as detected on micro-CT images. IHC indicated significant increases in cleaved caspase-3-expressing cells and decreases in ki67-positive cells in the BAC groups. There were obvious age-dependent changes in the numbers of superficial zone cells and CD90-expressing cells. Supportively, cleaved caspase-3-expressing cells obviously increased, while ki67-expressing cells significantly decreased with aging. In the elder BAC groups, the superficial zone cells such as CD90-expressing cells were greatly reduced. At 11 weeks, the superficial zone cells were almost non-existent, and there were clear serrated injuries on the cartilage surface. BAC removal attenuated the degenerative changes in the condylar cartilage and subchondral bone. Notably, the rescue effect was more pronounced in the younger animals. Our findings demonstrate the impacts of aging on both TMJ degenerative changes in response to BAC and regenerative changes following BAC removal. The reduced number of chondro-progenitor cells in aged TMJ cartilage provides an explanation for this age-related decline in TMJ rehabilitative behaviors.

Commodity price comovements are an important issue in economics given their significant implications for food and resource sectors that directly influence social well-being. This study approaches this issue by focusing on daily cash prices of 182 corn markets from the seven largest harvest states in the United States for 2006–2011 by using correlation based hierarchical analysis and synchronization analysis, through which we can determine interactions and interdependence among these prices, heterogeneities in price synchronization, and their changing patterns over time. As the first study of the issue concentrating on prices of hundreds of spatially dispersed markets for a commodity of indubitable economic significance, empirical findings show that the degree of comovements is generally higher after November 2006 but no persistent increase is observed. Different groups of markets are identified, each of which has its members exhibit similar price dynamics. Certain markets show potential of serving as price leaders. Results here benefit food and resource policy analysis and design for economic welfare. The empirical framework has potential of being adapted to network analysis of prices of different commodities.

The wheat straw reinforced composite is considered as a “green composite” as it utilizes biodegradable and recyclable food waste materials as reinforcing materials. Mechanical properties, such as tensile strength and impact toughness, are greatly dependent on the composite content and processing parameters. While compression molding is one of popular methods to fabricate the wheat straw/polypropylene composite, experimental trials to achieve targeted mechanical properties can be time-consuming and expensive. In this work, we develop the Gaussian process regression model to present the relationship among the fiber content, processing parameters of the compression molding, and mechanical performance of wheat straw reinforced polypropylene composites. The model achieves a correlation coefficient of 99.13% (95.68%), a root mean square error of 0.0857 (0.4369), and a mean absolute error of 0.0693 (0.3265) for tensile strength (impact toughness). The models are simple and fast to implement, produce predictions with high accuracy, and thus might be considered as efficient tools for mechanical property estimations. Should data become available, the model may be extended to include other descriptors, such as the wheat straw length, size distribution, and chemical treatment parameters.

Grinding-assisted liquid-phase exfoliation is a widely used method for the preparation of two-dimensional nanomaterials. In this study, N-methylpyrrolidone and acetonitrile, two common grinding solvents, were used during the liquid-phase exfoliation for the preparation of MoS2 nanosheets. The morphology and structure of MoS2 nanosheets were analyzed via scanning electron microscopy, X-ray diffraction, and Raman spectroscopy. The effects of grinding solvents on the gas-sensing performance of the MoS2 nanosheets were investigated for the first time. The results show that the sensitivities of MoS2 nanosheet exfoliation with N-methylpyrrolidone were 2.4-, 1.4-, 1.9-, and 2.7-fold higher than exfoliation with acetonitrile in the presence of formaldehyde, acetone, and ethanol and 98% relative humidity, respectively. MoS2 nanosheet exfoliation with N-methylpyrrolidone also has fast response and recovery characteristics to 50–1000 ppm of CH2O. Accordingly, although N-methylpyrrolidone cannot be removed completely from the surface of MoS2, it has good gas sensitivity compared with other samples. Therefore, N-methylpyrrolidone is preferred for the preparation of gas-sensitive MoS2 nanosheets in grinding-assisted liquid-phase exfoliation. The results provide an experimental basis for the preparation of two-dimensional materials and their application in gas sensors.

The house market has been rapidly growing for the past decade in China, making price forecasting an important issue to the people and policy makers. We approach this problem by exploring neural networks for forecasting of house prices from one hundred major cities for the period of June 2010–May 2019, serving as the first study with such wide coverage for the emerging Chinese market through a machine learning technique. We aim at constructing simple and accurate neural networks as a contribution to pure technical forecasting of house prices. To facilitate the analysis, we investigate different model settings over the algorithm (the Levenberg-Marquardt, scaled conjugate gradient, and Bayesian regularization), delay (from two to six), hidden neuron (two, three, five, and eight), and data spitting ratio (70%–15%–15%, 60%–20%–20%, and 80%–10%–10% for trainingvalidationtesting), and arrive at a rather simple neural network with only four delays and three hidden neurons that leads to stable performance of 1% average relative root mean square error across the one hundred cities for the training, validation, and testing phases. We demonstrate the usefulness of the machine learning approach to the house price forecasting problem in the Chinese market. Our results could be used on a standalone basis or combined with fundamental forecasting in forming perspectives of house price trends and conducting policy analysis. Our empirical framework should not be difficult to deploy, which is an important consideration to many decision makers, and has potential to be generalized for house price forecasting of other cities in China.

We explore the short-run forecasting problem at horizons of 1, 5, 10, 15, and 20 days for three forecasting periods within one year for the Chinese stock index from April 16, 2010, the launch date of the index futures, to May 19, 2014 with daily closing prices. We study forecast performance of 51 individual time series models that are different variations of autoregressive models, (Bayesian) vector autoregressive models, and (Bayesian) vector error correction models, and 41 composite models based on different trimming strategies of these individual models. The composite models, including the previous best forecast, equal-weighted average, inverse mean squared error, bias adjusted mean, shrinkage, and odds matrix approaches, utilize the idea of model boosting to diversify against possible mis-specifications, breaks, and structural changes in individual models, and aim at more robust performance. Across all forecasting horizons and forecasting periods investigated, we arrive at a shrinkage composite model with the shrinkage parameter of 0.25 that is optimal based on the mean squared error. This result is robust against the choice of futures series used in individual models and the pre-processing of structural breaks in data. We also discuss empirical findings at a more granular level, including comparisons of individual models and those of composite forecasts. Our results should fulfill different forecasting users’ information needs for decision making and policy analysis. The empirical framework also has potential of being adapted to similar time series forecasting problems in different fields.

Transparent conducting materials (TCMs) are essential components for a variety of optoelectronic devices, such as photovoltaics, displays and touch screens. In recent years, extensive efforts have been made to develop TCMs with both high electrical conductivity and optical transmittance. Based on material types, they can be mainly categorized into the following classes: metal oxides, metal nanowire networks, carbon-material-based TCMs (graphene and carbon nanotube networks) and conjugated conductive polymers (PEDOT:PSS). This review will discuss the fundamental electrical and optical properties, typical fabrication methods and the applications in solar cells for each class of TCMs and highlight the current challenges and potential future research directions.

Perovskites having the chemical formulae of ABX3 are promising candidates for various electronic, magnetic, and thermal applications. One of the important structural factors is a (the lattice constant), which represents the unit cell size. The variation in the lattice constant is a combined result of interactions between different ions, determined by valence electrons and ionic radii. The size and stability of unit cells have important influences on structural stabilities, bandgap structures, and therefore performance of materials. To obtain the lattice constant of cubic perovskites without going through experimental efforts such as synthesis and measurements, we construct a model based on Gaussian process regressions for cubic perovskite lattice constant predictions. The model utilizes the number of valence electrons as well as ionic radii of alloying elements as predictors. A total of 149 cubic perovskites containing fluorides, chlorides, and bromides with cation combinations of A1+B2+, as well as oxides with cation combinations of A1+B5+, A2+B4+, and A3+B3+ are explored. The model demonstrates good performance in terms of stabilities and accuracy, and thus could be a rapid approach to estimate lattice constants.

Osteoarthritis (OA) is associated with cartilage degeneration, and no effective therapy exists. Here, the authors show that the HPIP protein modulates OA progression by regulating Wnt signaling, and that its knockdown in joints via AAV-mediated gene silencing attentuates pathology.

Membrane filtration is an efficient wastewater treatment technology. However, sludge particles will easily aggregate and deposit upon the membrane surface, which will decrease the water productivity of membrane filaments. Focusing on the influence of velocity on particle behavior, experimental and numerical research was carried out. The k−ε turbulent model, porous media model and DPM model were adopted in the simulation. The flow characteristics including pressure, velocity and particle concentration contour are discussed using different inlet velocities of 0.6, 0.8, 1 m/s. The effects of gravity were also investigated. The final evaluation suggests the best working conditions in three scenarios, which could help to suppress membrane pollution. The results indicate that when the inlet velocity is about 1 m/s, particle deposition is weakest, resulting in better water productivity.

Abstract Background Identifying specific residues for protein-DNA interactions are of considerable importance to better recognize the binding mechanism of protein-DNA complexes. Despite the fact that many computational DNA-binding residue prediction approaches have been developed, there is still significant room for improvement concerning overall performance and availability. Results Here, we present an efficient approach termed PDRLGB that uses a light gradient boosting machine (LightGBM) to predict binding residues in protein-DNA complexes. Initially, we extract a wide variety of 913 sequence and structure features with a sliding window of 11. Then, we apply the random forest algorithm to sort the features in descending order of importance and obtain the optimal subset of features using incremental feature selection. Based on the selected feature set, we use a light gradient boosting machine to build the prediction model for DNA-binding residues. Our PDRLGB method shows better overall predictive accuracy and relatively less training time than other widely used machine learning (ML) methods such as random forest (RF), Adaboost and support vector machine (SVM). We further compare PDRLGB with various existing approaches on the independent test datasets and show improvement in results over the existing state-of-the-art approaches. Conclusions PDRLGB is an efficient approach to predict specific residues for protein-DNA interactions.

Abstract Lymphoma is a heterogeneous disease with varying clinical manifestations and outcomes. Many subtypes of lymphoma, such as Burkitt′s lymphoma and diffuse large B cell lymphoma, are highly aggressive with dismal prognosis even after conventional chemotherapy and radiotherapy. As such, exploring specific biomarkers for lymphoma is of high clinical significance. Herein, a potential marker, CD38, is investigated for differentiating lymphoma. A CD38‐targeting monoclonal antibody (mAb, daratumumab) is then radiolabeled with Zr‐89 and Lu‐177 for theranostic applications. As the diagnostic component, the Zr‐89‐labeled mAb is highly specific in delineating CD38‐positive lymphoma via positron emission tomography (PET) imaging, while the Lu‐177‐labeled mAb serves well as the therapeutic component to suppress tumor growth after a one‐time administration. These results strongly suggest that CD38 is a lymphoma‐specific marker and prove that 89Zr/177Lu‐labeled daratumumab facilitates immunoPET imaging and radioimmunotherapy of lymphoma in preclinical models. Further clinical evaluation and translation of this CD38‐targeted theranostics may be of significant help in lymphoma patient stratification and management.

Recent studies show that the adsorption energy can be used as a descriptor of the catalytic activity in methane direct conversion. We develop Gaussian process regression models to predict DFT-calculated adsorption energies of CH4 related species – CH3, CH2, CH, C, and H – on Cu-based alloys from elements’ readily available physical properties. As compared to conventional first-principle-based methods, the models are simple and fast to implement. They produce predictions with root mean squared errors of below 0.15 eV. The models also present numerical and statistical relationships between fundamental physiochemical parameters of doped elements and adsorption energies. Hence, they might be considered as efficient alternatives to the DFT approach for adsorption energy calculations, which allow for further assessments of certain solid catalysts’ catalytic performance.

Coming along with high water reuse in sustainable and intensive recirculating aquaculture systems (RASs), the waste products of fish in rearing water is continuously accumulated. Nitrate, the final product of biological nitrification processes, which may cause aquatic toxicity to fish in different degrees when exposed for a long time. Therefore, the present study was conducted to evaluate the impact of chronic nitrate exposure on intestinal morphology, immune status, barrier function, and microbiota of juvenile turbot. For that, groups of juvenile turbot were exposed to 0 (control check, CK), 50 (low nitrate, L), 200 (medium nitrate, M), and 400 (high nitrate, H) mg L−1 nitrate-N in small-sized recirculating aquaculture systems. After the 60-day experiment period, we found that exposure to a high concentration of nitrate-N caused obvious pathological damages to the intestine; for instance, atrophy of intestinal microvilli and necrosis in the lamina propria. Quantitative real-time PCR analysis revealed a significant downregulation of the barrier forming tight junction genes like occludin, claudin-like etc. under H treatment (P

As an important thermophysical property, polymers' glass transition temperature, Tg, could sometimes be difficult to determine experimentally. Modeling methods, particularly data-driven approaches, are promising alternatives to predictions of Tg in a fast and robust way. The molecular traceless quadrupole moment and molecule average hexadecapole moment are closely correlated with polymers' Tg. In the current work, these two parameters are used as descriptors in the Gaussian process regression model to predict Tg. We investigate 60 samples with Tg values from 194 K to 440 K. The model provides rapid and low-cost Tg estimations with high accuracy and stability.

Understanding combining ability and heterosis among diverse maize germplasm resources is important for breeding hybrid maize (Zea mays L.). Using 28 temperate and 23 tropical maize inbreds that represent different ecotypes and worldwide diversity of maize germplasm, we first developed a large-scale multiple-hybrid population (MHP) with 724 hybrids, which could be divided into three subsets, 325 temperate diallel hybrids and 136 tropical diallel hybrids generated in Griffing IV, and 263 temperate by tropical hybrids generated in NCD II. All the parental lines and hybrids were evaluated for 11 traits in replicated tests across two locations and three years. Several widely used inbreds showed strong general combining ability (GCA), and their derived hybrids showed strong specific combining ability (SCA). Heterosis is a quantifiable, trait-dependent and environment-specific phenotype, and the response of parental lines and their hybrids to environments resulted in various levels of heterosis. For all the tested traits except plant height and hundred grain weight (HGW), NCD II (temperate × tropical) hybrids showed higher average heterosis than the temperate and tropical diallel hybrids, with higher hybrid performance for ear length, ear diameter, and HGW. Tropical maize germplasm can be used to improve the yield potential for temperate lines. Grain number per row and grain number per ear were two most important traits that determined yield heterosis, which can be used as direct selection criteria for yield heterosis. The hybrids from heterotic groups, Reid × SPT, Reid × LRC, SPT × PA, and Lancaster × LRC, contributed highly significant positive SCA effects and strong heterosis to yield-related traits, and the heterotic patterns identified in this study were potentially useful for commercial maize breeding. Heterosis was more significantly and positively correlated with SCA than GCA, indicating that SCA can be used in heterosis prediction to develop potential hybrids in commercial maize breeding. The results of the present study not only contribute to developing breeding strategies, but also improve targeted breeding efficiency by using both temperate and tropical maize to broaden genetic basis. Large sets of parental lines with available genotypic information can be shared and used in worldwide hybrid breeding programs through an open-source breeding strategy. Potential applications of the reported results in developing hybrid maize breeding strategies were also discussed.

Trelagliptin inhibits the enzyme dipeptidyl-4 (DPP-4) to treat type 2 diabetes and it may possess the potential to improve insulin resistance. However, the molecular mechanism is not known. In this study, the effect of trelagliptin succinate in improving insulin resistance was investigated. The differentiation system of 3T3-L1 mouse preadipocytes was used to determine the content of adipokines and the content of GLUT4 in the outer membrane. The expression of AKT, P-AKT, IRS-1 and P-IRS-1 in differentiated 3T3-L1 adipocytes was determined by western blotting. Our results demonstrated that trelagliptin succinate increased the expression of AKT, P-AKT, IRS-1 and P-IRS-1 in the PI-3K/AKT insulin signaling pathway. These events promote the trans-membrane function of GLUT4 and concomitant glucose intake in adipocytes. In addition, the secretion of free fatty acids and resistin were decreased. In conclusion, our study suggested that trelagliptin succinate improved insulin resistance in adipocytes via regulation of PI-3K/AKT/GLUT4 insulin signaling pathway.

The Gaussian process regression model is developed as a machine learning tool to find statistical correlations among lattice constants, a0, of half-Heusler compounds, ionic radii, and Pauling electronegativity of their alloying elements. Nearly 140 half-Heusler samples, containing alloying elements of Cr, Mn, Fe, Co, Ni, Rh, Ti, V, Al, Ga, In, Si, Ge, Sn, P, As, and Sb, are explored for this purpose. The modeling approach demonstrates a high degree of accuracy and stability, contributing to efficient and low-cost estimations of lattice constants of half-Heusler compounds.

Solid-state refrigeration techniques have drawn increasing attention due to their potential for improving the energy efficiency of refrigeration and temperature-control systems without using harmful gas as in conventional gas compression techniques. Research on magnetocaloric lanthanum manganites with near-room-temperature Curie temperature shows promising results for development of magnetic refrigeration devices. Chemical substitutions are one of the most effective methods to tune the magnetocaloric effect, represented by the maximum magnetic entropy change (MMEC), through the incorporation of various lanthanides, rare-earth elements, alkali metals, alkaline-earth metals, transition metals, and other elements. Some theories based on lattice distortions and double-exchange interactions show that ionic radii of the dopants and final compositions correlate with the MMEC, but the correlations are generally limited to A-site substitutions and become less applicable to multi-doped manganites than single-doped ones. In this work, the Gaussian process regression model is developed as a machine learning tool to find statistical correlations between the MMEC and structural parameters among lanthanum manganites. More than 70 lattices, cubic, pseudocubic, orthorhombic, and rhombohedral, with the MMEC ranging from 0.65 J kg−1 K−1 to 8.00 J kg−1 K−1 under a field change of 5 T are explored for this purpose. Structural parameters utilized as descriptors include ionic radii at both A- and B-sites, ⟨Mn–O⟩ bond length, ⟨Mn–O–Mn⟩ bond angle, and compositions consisting of up to six elements. The modeling approach demonstrates a high degree of accuracy and stability, contributing to efficient and low-cost estimations of the magnetocaloric effect.

Genomic selection (GS) as a promising molecular breeding strategy has been widely implemented and evaluated for plant breeding, because it has remarkable superiority in enhancing genetic gain, reducing breeding time and expenditure, and accelerating the breeding process. In this study the factors affecting prediction accuracy (rMG) in GS were evaluated systematically, using six agronomic traits (plant height, ear height, ear length, ear diameter, grain yield per plant and hundred-kernel weight) evaluated in one natural and two biparental populations. The factors examined included marker density, population size, heritability, statistical model, population relationships and the ratio of population size between the training and testing sets, the last being revealed by resampling individuals in different proportions from a population. Prediction accuracy continuously increased as marker density and population size increased and was positively correlated with heritability; rMG showed a slight gain when the training set increased to three times as large as the testing set. Low predictive performance between unrelated populations could be attributed to different allele frequencies, and predictive ability and prediction accuracy could be improved by including more related lines in the training population. Among the seven statistical models examined, including ridge regression best linear unbiased prediction (RR-BLUP), genomic BLUP (GBLUP), BayesA, BayesB, BayesC, Bayesian least absolute shrinkage and selection operator (Bayesian LASSO), and reproducing kernel Hilbert space (RKHS), the RKHS and additive-dominance model (Add + Dom model) showed credible ability for capturing non-additive effects, particularly for complex traits with low heritability. Empirical evidence generated in this study for GS-relevant factors will help plant breeders to develop GS-assisted breeding strategies for more efficient development of varieties. Keywords: Marker density, Population size, Population relationship, Zea mays

Cryptotanshinone (CTS) has emerged as an anti-inflammatory agent in osteoarthritis (OA). However, the molecular mechanism underlying its potent therapeutic effect on OA remains largely unknown. MicroRNAs (miRNAs) act as crucial regulators in maintaining cartilage homeostasis. To investigate whether CTS protects against developing OA through regulation of miRNAs, we examined the potential CTS-mediated miRNA molecules using microarray analysis. We found that CTS significantly promoted miR-106a-5p expression in chondrocytes. Using the OA mouse model created by anterior cruciate ligament transection, we revealed that intra-articular injection of miR-106a-5p agomir attenuated OA. In addition, miR-106a-5p inhibited GLI-similar 3 (GLIS3) production by directly targeting the 3′ untranslated region. CTS promoted miR-106a-5p expression through recruitment of a member of the paired box (PAX) family of transcription factors, PAX5, to the miR-106a-5p promoter. Inhibition of PAX5 mimicked the effect of miR-106a-5p and abolished the CTS ability to regulate miR-106a-5p expression. In OA patients, miR-106-5p is downregulated which is accompanied by downregulation of PAX5 and upregulation of GLIS3. Collectively, these data highlight that the PAX5/miR-106a-5p/GLIS3 axis acts as a novel pleiotropic regulator in CTS-mediated OA cartilage protection, suggesting that miR-106a-5p and PAX5 activation and GLIS3 inhibition might be useful and attractive for therapeutic strategies to treat OA patients.