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Abstract Background Pancreatic adenocarcinomas (PAADs) often exhibit a “cold” or immunosuppressive tumor milieu, which is associated with resistance to immune checkpoint blockade therapy; however, the underlying mechanisms are incompletely understood. Here, we aimed to improve our understanding of the molecular mechanisms occurring in the tumor microenvironment and to identify biomarkers, therapeutic targets, and potential drugs to improve PAAD treatment. Methods Patients were categorized according to immunologically hot or cold PAAD subtypes with distinct disease outcomes. Cox regression and weighted correlation network analysis were performed to construct a novel gene signature, referred to as ‘Downregulated in hot tumors, Prognostic, and Immune-Related Genes’ (DPIRGs), which was used to develop prognostic models for PAAD via machine learning (ML). The role of DPIRGs in PAAD was comprehensively analyzed, and biomarker genes able to distinguish PAAD immune subtypes and predict prognosis were identified by ML. The expression of biomarkers was verified using public single-cell transcriptomic and proteomic resources. Drug candidates for turning cold tumors hot and corresponding target proteins were identified via molecular docking studies. Results Using the DPIRG signature as input data, a combination of survival random forest and partial least squares regression Cox was selected from 137 ML combinations to construct an optimized PAAD prognostic model. The effects and molecular mechanisms of DPIRGs were investigated by analysis of genetic/epigenetic alterations, immune infiltration, pathway enrichment, and miRNA regulation. Biomarkers and potential therapeutic targets, including PLEC, TRPV1, and ITGB4, among others, were identified, and the cell type-specific expression of the biomarkers was validated. Drug candidates, including thalidomide, SB-431542, and bleomycin A2, were identified based on their ability to modulate DPIRG expression favorably. Conclusions By combining multiple ML algorithms, we developed a novel prognostic model with excellent performance in PAAD cohorts. ML also proved to be powerful for identifying biomarkers and potential targets for improved PAAD patient stratification and immunotherapy.

Abstract This paper presents an integrated control scheme for enhancing the ride comfort and handling performance of a four-wheel-independent-drive electric vehicle through the coordination of active suspension system (ASS) and anti-lock braking system (ABS). First, a longitudinal-vertical coupled vehicle dynamics model is established by integrating a road input model. Then the coupling mechanisms between longitudinal and vertical vehicle dynamics are analyzed. An ASS-ABS integrated control system is proposed, utilizing an H ∞ controller for ASS to optimize load transfer effect and a neural network sliding mode control for ABS implementation. Finally, the effectiveness of the proposed control scheme is evaluated through comprehensive tests conducted on a hardware-in-loop (HIL) test platform. The HIL test results demonstrate that the proposed control scheme can significantly improve the braking performance and ride comfort compared to conventional ABS control methods.

Metal pollution can cause a decline in female fertility, however, previous studies have focused more on the effect of a single metal on fertility. In this study, we evaluated the effect of metal mixtures on female fertility based on nested case-control samples. The plasma levels of 22 metal elements from 180 women were determined by an inductively coupled plasma mass spectrometer (ICP-MS). Minimum absolute contraction and selection operator (LASSO) penalty regression selected metals with the greatest influence on clinical outcome. Logistic regression was used to analyze the correlation between single metals and fertility while a Bayesian kernel function regression (BKMR) model was used to analyze the effect of mixed metals. Eight metals (Calcium (Ca), Chromium (Cr), Cobalt (Co), Copper (Cu), Zinc (Zn), Rubidium (Rb), Strontium (Sr) and Zirconium (Zr)) were selected by LASSO regression for subsequent analysis. After adjusting for covariates, the logistic model showed that Cu (Odds Ratio(OR):0.33, 95% CI: 0.13 − 0.84) and Co (OR:0.38, 95% CI: 0.15 −0.94) caused a significant reduction in fertility, and identified the protective effect of Zn (OR: 2.96, 95% CI:1.21 −7.50) on fertility. Trend tests showed that increased Cr, Cu, and Rb levels were associated with reduced fertility. The BKMR model showed that Cr, Co, Cu, and Rb had a nonlinear relationship with fertility decline when controlling for the concentrations of other metals and suggested that Cu and Cr might exert an influence on fertility. Analysis showed a negative correlation between Cu, Cr, Co, Rb, and fertility, and a positive correlation between Zn and fertility. Furthermore, we found evidence for the interaction between Cu and Cr. Our findings require further validation and may identify new mechanisms in the future.

This paper investigates the impact of bank regulatory capital on Islamic bank risk using bank-level data from 29 countries covering the period from 2004 to 2020. Applying the generalized method of moments technique on dynamic panels, we discover that on average Islamic bank regulatory capital ratios exceed the level required by Basel III. The findings provide evidence in support of the moral hazard hypothesis; that is, there is a negative relationship between capital and risk. They indicate that Islamic banks are better protected against risk when they fulfill Basel III and IFSB regulatory capital requirements. According to our findings, authorities that aim to improve the financial stability of the banking industry should reinforce their policies and oblige banks to adhere to regulatory capital requirements during crises such as Covid-19. Finally, we observe that different risk indicators have diverse correlations with regulatory capital, and that the findings are robust across a variety of estimation methodologies.

Abstract Background Although sexually transmitted infections are regarded as the main cause of tubal infertility, the association between the common vaginal microbiome and female fecundability has yet to be determined. The objective of this study was to find convincing evidence relating to the impact of the vaginal bacterial structure on the fecundability of women planning pregnancy. Methods We recruited women who took part in the Free Pre-pregnancy Health Examination Project from 13 June 2018 to 31 October 2018 (n = 89, phase I) and from 1 November 2018 to 30 May 2020 (n = 389, phase II). We collected pre-pregnancy vaginal swabs from each subject; then, we followed up each subject to acquire the pregnancy-planning outcome in 1 year. In phase I, 16S rRNA gene sequencing was performed to investigate the vaginal bacterial content between the pregnancy and non-pregnancy groups. These findings were verified in phase II by applying a quantitative real-time polymerase chain reaction for the measurement of the absolute abundance of specific species. Cox models were used to estimate fecundability ratios (FR) for each vaginal microbiome type. Results In phase I, 59.6% (53/89) of women became pregnant within 1 year. The principal coordinate analysis showed that the pre-pregnancy vaginal microbial community structures of the pregnant and non-pregnant groups were significantly different (PERMANOVA test, R 2 = 0.025, P = 0.049). The abundance of the genus Lactobacillus in the pregnancy group was higher than that of the non-pregnant group (linear discriminant analysis effect size (LDA) > 4.0). The abundance of the genus Gardnerella in the non-pregnant group was higher than those in the pregnant group (LDA > 4.0). In phase II, female fecundability increased with higher absolute loads of Lactobacillus gasseri (quartile Q4 vs Q1, FR = 1.71, 95%CI 1.02–2.87) but decreased with higher absolute loads of Fannyhessea vaginae (Q4 vs Q1, FR = 0.62, 95%CI 0.38–1.00). Clustering analysis showed that the vaginal microbiome of type D (characterized by a higher abundance of Lactobacillus iners, a lower abundance of Lactobacillus crispatus and Lactobacillus gassri) was associated with a 55% reduction of fecundability (FR = 0.45, 95%CI 0.26–0.76) compared with type A (featuring three Lactobacillus species, low Gardnerella vaginalis and Fannyhessea vaginae abundance). Conclusions This cohort study demonstrated an association between the pre-pregnancy vaginal microbiome and female fecundability. A vaginal microbiome characterized by a higher abundance of L. iners and lower abundances of L. crispatus and L. gasseri appeared to be associated with a lower fecundability. Further research now needs to confirm whether manipulation of the vaginal microenvironment might improve human fecundability.

Abstract Objective To explore the impact of pre-pregnancy vaginal Mycoplasma hominis (M. hominis) colonization of low abundance on female fecundability. Methods In total, 89 females participating in a pre-pregnancy health examination program were included, and their pregnancy outcomes were followed up for 1 year. Vaginal swabs were collected, 16S rRNA genes were sequenced, and M. hominis colonization was confirmed by qPCR. Cox models were used to estimate the fecundability odds ratio (FOR) for women with M. hominis. Results The prevalence of M. hominis was 22.47% (20/89), and the abundance was relatively low (the cycle thresholds of the qPCR were all more than 25). In terms of the vaginal microbiome, the Simpson index of the positive group was significantly lower than that of the negative group (P = 0.003), which means that the microbiome diversity appeared to increase with M. hominis positivity. The relative abundance of M. hominis was negatively correlated with Lactobacillus crispatus (rho = − 0.24, P = 0.024), but positively correlated with Gardnerella vaginalis, Atopobium vaginae and Prevotella bivia (P all

In China, malignant tumor is the main cause of death in both urban and rural areas. Mesenchymal stem cells (MSCs) have multidirectional differentiation potential, self-renewal ability and good immunomodulatory properties. Exosomes, as important paracrine substances of MSCs, mediate information exchange and transmission between cells in tumor microenvironment and influence the occurrence and development of tumors. Recently, conflicting findings have been reported on the effects of MSCs and their exosomes on tumors. On the one hand, MSCs and their exosomes are tumorigenic and can target specific sites to inhibit tumor growth; On the other hand, there is also evidence that MSCs could affect tumor growth and migration as part of the tumor microenvironment. In this paper, we will review the relationship between MSCs and exosomes and tumorgenesis and development, as well as how MSCs and exosomes play different roles in tumorgenesis and development, in order to provide beneficial help for tumor diagnosis, prognosis and precise treatment.

This paper proposes a background noise adaptive energy-efficient keywords recognition processor with Reusable DNN (RDNN) and reconfigurable architecture. To reduce power consumption while maintaining the recognition accuracy of different background noises, the SNR prediction module determines whether the computing mode is low power consumption mode (LPM) or high performance mode (HPM). In LPM, DNN-shift (shift-based deep neural network) is used to achieve high recognition accuracy in a low background noise environment; in HPM, DNN-8bit (8bit weighted deep neural network) is used to achieve low power consumption in a high background noise environment. And the two modes share most of the hardware, and approximate computing is introduced to further reduce power consumption. Evaluated under 22nm process technology, this work can support up to 10 keywords recognition with the power consumption of $11.2~\mu \text{W}$ for high background noise and $7.3~\mu \text{W}$ for low background noise.

Mammalian transducin-like enhancer of split family proteins (TLEs) are homologous to Drosophila Groucho (Gro) and are essential transcriptional repressors. Seven TLE family members, TLE1-7, have been identified to date. These proteins do not bind DNA directly; instead, they bind a set of transcription factors and thereby inhibit target gene expression. Loss of TLEs in mice usually leads to defective early development; however, TLE functions in developmentally mature cells are unclear. Recent studies have revealed that TLEs are dysregulated in certain human cancer types and may function as oncogenes or tumor suppressors in different contexts. TLE levels also affect the efficacy of cancer treatments and the development of drug resistance. In addition, TLEs play critical roles in the development and function of immune cells, including macrophages and lymphocytes. In this review, we provide updates on the expression, function, and mechanism of TLEs; discuss the roles played by TLEs in tumorigenesis and the inflammatory response; and elaborate on several TLE-associated signaling pathways, including the Notch, Wnt, and MAPK pathways. Finally, we discuss potential strategies for targeting TLEs in cancer therapy.

It is well known that driving while fatigued is dangerous and can lead to serious traffic accidents. However, there is a lack of studies on the mechanism of fatigue. This paper sought to infer changes in the cardiovascular system through hand and head skin temperature peripheral factors via an integrated lumped parameter model. A multi-layer inner structure with variable blood perfusion was used to construct a full-body thermal model. The cardiovascular system model provided blood perfusion using lumped parameters. The peripheral resistance and heart rate in the cardiovascular system model were adjusted to match the experimental temperatures of the head and hands obtained from induced fatigue experiments. The simulation results showed that the heart rate and blood pressure decreased, and the peripheral skin resistance of the hands and head increased after fatigue. A decrease in heart rate and an increase in peripheral resistance affect the magnitude of blood flow to the periphery of the body, leading to a decrease in skin temperature during fatigue. The present integrated model elucidates a key effect of human fatigue on the cardiovascular system, which is expected to help improve the accuracy of fatigue monitoring systems.

Cancer stem cells (CSCs) play significant roles in cancer development, drug resistance and cancer recurrence. In cancer treatments based on the CSC characteristics and inducing factors, MYC is a promising target for therapeutic molecules. Although it has been regarded as an undrugable target, its stability tightly regulated by the ubiquitin–proteasome system offers a new direction for molecule targeting and cancer treatment. Herein we report our discoveries in this research area, and we have found that deubiquitinase USP45 can directly bind with MYC, resulting in its deubiquitination and stabilization. Further, USP45 overexpressing can upregulate MYC, and this overexpressing can significantly enhance cancer development, cancer cell stemness and drug resistance. Interestingly, without enhancing cancer development, MYC silencing with shRNA can only suppress USP45-induced stemness and drug resistance. Moreover, we have identified that USP45 can be specifically bound and inhibited by a natural small molecule (α-mangostin), in turn significantly suppressing USP45-induced stemness and drug resistance. Since USP45 is significantly expressed in cervical tumors, we have discovered that the combination of α-mangostin and doxorubicin can significantly inhibit USP45-induced cervical tumorigenesis in an animal model. In general, on the basis of our USP45 discoveries on its MYC deubiquitination and α-mangostin inhibition, suppressing USP45 has opened a new window for suppressing cancer development, stemness and drug resistance.

Macrophages play critical roles in tumor progression. In the tumor microenvironment, macrophages display highly diverse phenotypes and may perform antitumorigenic or protumorigenic functions in a context-dependent manner. Recent studies have shown that macrophages can be engineered to transport drug nanoparticles (NPs) to tumor sites in a targeted manner, thereby exerting significant anticancer effects. In addition, macrophages engineered to express chimeric antigen receptors (CARs) were shown to actively migrate to tumor sites and eliminate tumor cells through phagocytosis. Importantly, after reaching tumor sites, these engineered macrophages can significantly change the otherwise immune-suppressive tumor microenvironment and thereby enhance T cell-mediated anticancer immune responses. In this review, we first introduce the multifaceted activities of macrophages and the principles of nanotechnology in cancer therapy and then elaborate on macrophage engineering via nanotechnology or genetic approaches and discuss the effects, mechanisms, and limitations of such engineered macrophages, with a focus on using live macrophages as carriers to actively deliver NP drugs to tumor sites. Several new directions in macrophage engineering are reviewed, such as transporting NP drugs through macrophage cell membranes or extracellular vesicles, reprogramming tumor-associated macrophages (TAMs) by nanotechnology, and engineering macrophages with CARs. Finally, we discuss the possibility of combining engineered macrophages and other treatments to improve outcomes in cancer therapy.

The keyword spotting (KWS) system is one of the most important interfaces between humans and machines since it is usually the start of automatic speech recognition and natural language processing techniques. However, for KWS hardware, it is still a problem to make one specified chip both low power and high performed under multiple scenarios, such as in meeting rooms, on different traffic or in parks and so on, for different scenarios own wide range signal-noise-ratios (SNRs). The problem leads to the requirements of balanced design between KWS system accuracy and the hardware cost under various noise types and levels. To overcome the balanced design and tradeoff problems, a complete KWS processor including an Mel-Frequency Cepstrum Coefficients (MFCC) feature extractor and a quantized Convolutional Neural Network (QCNN) accelerator is proposed for wide SNR range and low-power KWS in this paper. Firstly, the approach to quantize CNNs into QCNNs with high accuracy is proposed with considerations of hardware-software tradeoff. With the tradeoff of KWS system accuracy and hardware cost, the 4bit/8bit dual-working-mode strategy is proposed to keep low hardware cost and high accuracy under different scenarios. To be specific, the training, tuning and validating of the CNNs and QCNNs are taken with the dataset of 10 keywords chosen from the Google Command Speech Dataset (GCSD). Secondly, a serial FFT based MFCC extractor is implemented with low power and small footprint. Finally, with a novel hybrid reuse strategy of input data and network weight, a reconfigurable and approximate computing based QCNN accelerator is designed. Implemented and verified under TSMC 22nm ULL technology, with the area of 1.42mm2, the QCNN accelerator can achieve 5.26μW/9.08μW power consumption in 4bit/8bit work mode with accuracy of 88% and 93% respectively, which is superior to the state-of-the-art processors.

Plants have the potential to reduce CO2 concentration, but their photosynthesis is directly influenced by the indoor lighting environment. As a result, the efficiency of indoor plants is limited by indoor lighting environment. In order to explore the effect of lighting environments on the reduction of indoor CO2 concentration by indoor plants, three representative lighting environments were constructed, including a natural lighting environment, a poor lighting environment and an all-day lighting environment, while five common plants were selected to be planted in five transparent sealed chambers. Experimental results show that the lighting environment affected the CO2 concentration largely in transparent sealed chambers. Compared to the transparent sealed chamber without plants, the highest and average CO2 concentrations were increased by from 47.9% to 160.9% and from 21.6% to 132.4% in the poor lighting environment, respectively, while they decreased by from 60.4% to 84.6% and from 71.4% to 89.7% in the all-day lighting environment. This indicated that plants did not purify the indoor air consistently. Among the selected plants, the most suitable houseplant was Scindapsus aureus, followed by Chlorophytum comosum and Bambusa multiplex.

Intramuscular fat (IMF) content is vital for pork quality, serving an important role in economic performance in pig industry. Non-coding RNAs, with mRNAs, are involved in IMF deposition; however, their functions and regulatory mechanisms in porcine IMF remain elusive. This study assessed the whole transcriptome expression profiles of the Longissimus dorsi muscle of pigs with high (H) and low (L) IMF content to identify genes implicated in porcine IMF adipogenesis and their regulatory functions. Hundreds of differentially expressed RNAs were found to be involved in fatty acid metabolic processes, lipid metabolism, and fat cell differentiation. Furthermore, combing co-differential expression analyses, we constructed competing endogenous RNAs (ceRNA) regulatory networks, showing crosstalk among 30 lncRNAs and 61 mRNAs through 20 miRNAs, five circRNAs and 11 mRNAs through four miRNAs, and potential IMF deposition-related ceRNA subnetworks. Functional lncRNAs and circRNAs (such as MSTRG.12440.1, ENSSSCT00000066779, novel_circ_011355, novel_circ_011355) were found to act as ceRNAs of important lipid metabolism-related mRNAs (LEP, IP6K1, FFAR4, CEBPA, etc.) by sponging functional miRNAs (such as ssc-miR-196a, ssc-miR-200b, ssc-miR10391, miR486-y). These findings provide potential regulators and molecular regulatory networks that can be utilized for research on IMF traits in pigs, which would aid in marker-assisted selection to improve pork quality.

Ureaplasma genus (including U. urealyticum and U. parvum) and M. hominis are common opportunistic pathogens in vaginal microenvironments, which would lead to bacterial vaginosis, infertility and adverse pregnancy outcomes. Ascertaining associations between these elements and the vaginal microbiome can help us identify pathogenic mechanisms, and target control measures for different colonization levels. 92 childbearing-age, non-pregnant women were included, with vaginal swabs collected. DNA was extracted and 16S rRNA genes were sequenced using the IlluminaHiseq 2500 platform. A quantitative PCR method quantified bacterial loads. The colonization rates for the Ureaplasma genus and M. hominis were 87.0 ​% (80/92) and 29.3 ​% (27/92), respectively. No M. genitalium was detected. There were no statistical differences for Simpson, Shannon and Chao1 indices between Ureaplasma negative and positive groups (P ​> ​0.05). Based on the quartile classification of relative abundance for Ureaplasma, the third quartile group had the highest relative abundance of Lactobacillus. The Simpson index for the M. hominis positive group was statistically lower than the negative group (P ​= ​0.038). The Lactobacillus abundance appeared to decrease when the M. hominis relative abundance was >0.03 ​%. From a microbiome perspective, Ureaplasma vaginal colonization, at low levels appeared to be harmless, whereas M. hominis colonization was associated with vaginal microbiome changes. Further studies are required to confirm the diagnostic and treatment thresholds for Ureaplasma and M. hominis infections, and to explore in-depth associations between these organisms and the vaginal microbiome.

Abstract The pathogenesis of steroid‐induced avascular necrosis of femoral head (SANFH) is complex, and there is a lack of effective early prevention method. The aim of the present study was to evaluate the effect of dexamethasone (DEX) on the biological behavior of bone marrow mesenchymal stem cells (BMSCs) and to explore the possibility of DEX in the clinical treatment of SANFH. The effect of DEX on the proliferation of BMSCs was evaluated by Counting Kit‐8 assay, western blot assay, and enzyme‐linked immunosorbent assay. Flow cytometry and western blot assay were performed to detect the effect of DEX on the apoptosis of BMSCs. Quantitative real‐time PCR and western blot assay were performed to detect the effect of DEX on the expression of endoplasmic reticulum stress (ERS)‐related genes. Immunoblotting analysis was conducted for detecting the nuclear‐cytoplasmic distribution of Nrf2. DEX could significantly inhibit the proliferation of BMSCs and promote apoptosis of BMSCs. DEX could increase the expression of PERK, ATF6, and IRE1a, and induce nuclear translocation of Nrf2. The addition of ML385 could reverse the effect of DEX on BMSCs. DEX could activate the PERK‐Nrf2 pathway to promote ERS and finally affect the cell proliferation and apoptosis of BMSCs.

Water quality is a significant issue, and its assessment plays an important role in environmental management and pollution control. In this paper, we proposed a comprehensive water quality assessment method which takes into account both absolute and temporal trends in water quality. As the first step, we derived and applied a comprehensive pollution index (CPI) to characterize water pollution in 16 major tributaries to the Danjiangkou Reservoir, located in the upper reaches of the Hanjiang River in China. Next, we used Spearman’s rank correlation analysis to quantify temporal CPI trends in each tributary. As the final step, we conducted principal component analysis (PCA) using data on 8 water quality parameters and the temporal CPI trend from each of the 16 tributaries. The resultant comprehensive water quality assessment method identified tributaries, which stand to improve and threaten water quality in the Danjiangkou Reservoir from both immediate and future perspectives.

Flood disasters are the most frequent and most severe natural disasters in most countries around the world. Reservoir flood operation is an important method to reduce flood losses. When there are multiple reservoirs and flood control points in the basin, it is difficult to use reservoirs separately to fully realize their flood control potential. However, the multi-reservoir joint flood control operation is a multi-objective, multi-constrained, multi-dimensional, nonlinear, and strong-transition feature decision-making problem, and these characteristics make modeling and solving very difficult. Therefore, a large-scale reservoirs flood control operation modeling method is innovatively proposed, and Dynamic Programming (DP) combined with the Progressive Optimality Algorithm (POA) and Particle Swarm Optimization (PSO) methods, DP-POA-PSO, are designed to efficiently solve the optimal operation model. The middle and upper Yangtze River was chosen as a case study. Six key reservoirs in the basin were considered, including Xiluodu (XLD), Xiangjiaba (XJB), Pubugou (PBG), Tingzikou (TZK), Goupitan (GPT), and Three Gorges (TG). Studies have shown that DP-POA-PSO can effectively solve the optimal operation model. Compared with the current operation method, the joint flood control optimal operation makes the flood control point reach the flood control standard, moreover, in the event of the flood with a return period of 1000 years, Jingjiang, the most critical flood control point of the Yangtze River, does not require flood diversion, and the volume of flood diversion in Chenglingji is also greatly reduced.

Natural resistance-associated macrophage protein 1 encoding gene (NRAMP1) plays an important role in immune response against intracellular pathogens. To evaluate the effects of NRAMP1 gene on immune capacity in pigs, tissue expression of NRAMP1 mRNA was observed by real time quantitative polymerase chain reaction (PCR), and the results revealed NRAMP1 expressed widely in nine tissues. One single nucleotide polymorphism (SNP) (ENSSSCG00000025058: g.130 C>T) in exon1 and one SNP (ENSSSCG00000025058: g.657 A>G) in intron1 region of porcine NRAMP1 gene were demonstrated by DNA sequencing and PCR-RFLP analysis. A further analysis of SNP genotypes associated with immune traits including contain of white blood cell (WBC), granulocyte, lymphocyte, monocyte (MO), rate of cytotoxin in monocyte (MC) and CD4/CD8 T lymphocyte subpopulations in blood was carried out in four pig populations including Large White and three Chinese indigenous breeds (Wannan Black, Huai pig and Wei pig). The results showed that the SNP (ENSSSCG00000025058: g.130 C>T) was significantly associated with level of WBC % (p = 0.031), MO% (p = 0.024), MC% (p = 0.013) and CD4−CD8+ T lymphocyte (p = 0.023). The other SNP (ENSSSCG00000025058: g.657 A>G) was significantly associated with the level of MO% (p = 0.012), MC% (p = 0.019) and CD4−CD8+ T lymphocyte (p = 0.037). These results indicate that the NRAMP1 gene can be regarded as a molecular marker for genetic selection of disease susceptibility in pig breeding.

A novel heterojunction structured composite photocatalyst CdS/Au/g-C3N4 has been developed by depositing CdS/Au with a core (Au)-shell (CdS) structure on the surface of g-C3N4. The photocatalytic hydrogen production activity of the developed photocatalyst was evaluated under visible-light irradiation (λ > 420 nm) using methanol as a sacrificial reagent. As a result, its activity is about 125.8 times higher than that of g-C3N4 and is even much higher than that of Pt/g-C3N4. The enhancement in photocatalytic activity is attributed to efficient separation of the photoexcited charges due to the anisotropic junction in the CdS/Au/g-C3N4 system.

We investigated the safety and nutritional value of biogas residue left after the production of biogas from wastewater. In Exp. 1, ninety- six female mice were selected for acute oral toxicity testing and randomly allocated to 4 treatment groups, which received distilled water (control) or the biogas residue solution at 1 g/mL, 5 g/mL, or 15 g/mL. Activity levels and serum biochemical parameters were measured after 24 hours. In Exp. 2, eighty mice were divided into 2 treatment groups for subacute and sub-chronic toxicity testing, which received either a control group diet or the biogas residue diet (20% biogas residue). In Exp. 3, to test the nutritional value of the biogas residue, four pigs were fed either a low-casein corn starch-based diet or a semi-purified diet with biogas residue as the only source of protein, and the apparent and true digestibility of crude protein and amino acids, apparent metabolic energy, and digestible energy were measured. Group differences in serum parameters and mouse weight gain were not significant 24 hours after biogas residue solution gavage, and the viscera appeared normal. At day 30 of the observation period, changes in serum biochemical parameters were not significant, but the mean spleen index of mice treated with biogas residue was greater (P

Winter hardiness is an important trait for grapevine breeders and producers, so identification of the regulatory mechanisms involved in cold acclimation is of great potential value. The work presented here involves the identification of two grapevine ICE gene homologs, VaICE1 and VaICE2, from an extremely cold-tolerant accession of Chinese wild-growing Vitis amurnensis, which are phylogenetically related to other plant ICE1 genes. These two structurally different ICE proteins contain previously reported ICE-specific amino acid motifs, the bHLH-ZIP domain and the S-rich motif. Expression analysis revealed that VaICE1 is constitutively expressed but affected by cold stress, unlike VaICE2 that shows not such changed expression as a consequence of cold treatment. Both genes serve as transcription factors, potentiating the transactivation activities in yeasts and the corresponding proteins localized to the nucleus following transient expression in onion epidermal cells. Overexpression of either VaICE1 or VaICE2 in Arabidopsis increase freezing tolerance in nonacclimated plants. Moreover, we show that they result in multiple biochemical changes that were associated with cold acclimation: VaICE1/2-overexpressing plants had evaluated levels of proline, reduced contents of malondialdehyde (MDA) and decreased levels of electrolyte leakage. The expression of downstream cold responsive genes of CBF1, COR15A, and COR47 were significantly induced in Arabidopsis transgenically overexpressing VaICE1 or VaICE2 upon cold stress. VaICE2, but not VaICE1 overexpression induced KIN1 expression under cold-acclimation conditions. Our results suggest that VaICE1 and VaICE2 act as key regulators at an early step in the transcriptional cascade controlling freezing tolerance, and modulate the expression levels of various low-temperature associated genes involved in the C-repeat binding factor (CBF) pathway.