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Since the launch of China's used car export program in 2019, the scale of vehicle exports has increased significantly, and the level of export facilitation has continued to improve. The number of export regions and enterprises has steadily increased, and the variety of exported vehicle models has become increasingly abundant. Overseas channels have been expanded more widely, and the used car export program has achieved great success. This paper first analyzes the overall situation of China's used car exports based on data from the Ministry of Commerce, using a comparative method. Then, the characteristics of China's used car development are expounded upon, and finally, the potential for China's used car exports is analyzed. This article provides a reference and inspiration for the development of China's used car export industry.

miRNAs alter significantly throughout pregnancy to support the development of the fetus. However, sensitive detection of miRNA remains a challenge. Herein, a reliable miRNA detection approach integrating self-assembly-triggered signal amplification and CRISPR-Cas12a-system cleavage-based color generation is described. The colorimetric approach contains three signal amplification processes. The first signal amplification is formed by the released miRNA in a chain extension process. The produced sequence that is similar to the target miRNA initiates the second signal recycle. Finally, CRISPR-Cas12a-based transcleavage on linker sequences induces the third signal amplification. The method exhibits high sensitivity and a low limit of detection of 254 aM, showing promising prospects in disease diagnosis.

The theory, cardiovascular disease is one of the most common clinical chronic diseases. Modern medicine has confirmed that cardiovascular diseases are caused by the long-term accumulation and deposition of various pathological products caused by a variety of causes, and most of them are non-specific. Cardiovascular events such as acute myocardial infarction and stroke mainly occur in the occurrence process of cardiovascular diseases and cerebrovascular accidents, so the pathogenesis of cardiovascular and cerebrovascular diseases is very complex and difficult to predict. Therefore, this paper carries out the corresponding discussion on it.

The varied use and disposal of silver nanoparticles (AgNPs) has allowed their presence in reclaimed water and sewage sludge, making them possibly available in agricultural soils.

The emergence of supramolecular chemistry is a new era of chemical development. It is a rapidly developing new interdisciplinary subject. Many major achievements have been made. Supramolecular chemistry refers to two molecules (host and guest) or multiple molecules. Under the action of the non-covalent bond between molecules, a highly complex multi-molecular polymer with specific functions and special properties is formed. After literature search, the cyclodextrin and its derivatives are briefly introduced based on references, and the pharmaceutical aspects of cyclodextrin and its derivatives are reviewed in terms of sources, preparation methods, properties, and applications.

Lasiocarpine (LAS) and heliotrine (HEL) are two different ester types of toxic pyrrolizidine alkaloids (PAs): open-chain diester and monoester. However, the pharmacokinetics of these two types of PAs in rats have not been reported. In the present study, two LC-MS/MS methods for determining LAS and HEL were established and validated. The methods exhibited good linearity, accuracy, and precision and were then applied to a comparative pharmacokinetic study. After intravenous administration to male rats at 1 mg/kg, the AUC0-t values of LAS and HEL were 336 ± 26 ng/mL × h and 170 ± 5 ng/mL × h. After oral administration at 10 mg/kg, the AUC0-t of LAS was much lower than that of HEL (18.2 ± 3.8 ng/mL × h vs. 396 ± 18 ng/mL × h), while the Cmax of LAS was lower than that of HEL (51.7 ± 22.5 ng/mL × h vs. 320 ± 26 ng/mL × h). The absolute oral bioavailability of LAS was 0.5%, which was significantly lower than that of HEL (23.3%). The results revealed that the pharmacokinetic behaviors of LAS differed from that of HEL.

Idiopathic inflammatory myopathies (IIM) are a class of autoimmune diseases with high heterogeneity that can be divided into different subtypes based on clinical manifestations and myositis-specific autoantibodies (MSAs). However, even in each IIM subtype, the clinical symptoms and prognoses of patients are very different. Thus, the identification of more potential biomarkers associated with IIM classification, clinical symptoms, and prognosis is urgently needed.Plasma and urine samples from 79 newly diagnosed IIM patients (mean disease duration 4 months) and 52 normal control (NC) samples were analysed by high-performance liquid chromatography of quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS)/MS-based untargeted metabolomics. Orthogonal partial least-squares discriminate analysis (OPLS-DA) were performed to measure the significance of metabolites. Pathway enrichment analysis was conducted based on the KEGG human metabolic pathways. Ten machine learning (ML) algorithms [linear support vector machine (SVM), radial basis function SVM, random forest, nearest neighbour, Gaussian processes, decision trees, neural networks, adaptive boosting (AdaBoost), Gaussian naive Bayes and quadratic discriminant analysis] were used to classify each IIM subtype and select the most important metabolites as potential biomarkers.OPLS-DA showed a clear separation between NC and IIM subtypes in plasma and urine metabolic profiles. KEGG pathway enrichment analysis revealed multiple unique and shared disturbed metabolic pathways in IIM main [dermatomyositis (DM), anti-synthetase syndrome (ASS), and immune-mediated necrotizing myopathy (IMNM)] and MSA-defined subtypes (anti-Mi2+, anti-MDA5+, anti-TIF1γ+, anti-Jo1+, anti-PL7+, anti-PL12+, anti-EJ+, and anti-SRP+), such that fatty acid biosynthesis was significantly altered in both plasma and urine in all main IIM subtypes (enrichment ratio 1). Random forest and AdaBoost performed best in classifying each IIM subtype among the 10 ML models. Using the feature selection methods in ML models, we identified 9 plasma and 10 urine metabolites that contributed most to separate IIM main subtypes and MSA-defined subtypes, such as plasma creatine (fold change = 3.344, P = 0.024) in IMNM subtype and urine tiglylcarnitine (fold change = 0.351, P = 0.037) in anti-EJ+ ASS subtype. Sixteen common metabolites were found in both the plasma and urine samples of IIM subtypes. Among them, some were correlated with clinical features, such as plasma hypogeic acid (r = -0.416, P = 0.005) and urine malonyl carnitine (r = -0.374, P = 0.042), which were negatively correlated with the prevalence of interstitial lung disease.In both plasma and urine samples, IIM main and MSA-defined subtypes have specific metabolic signatures and pathways. This study provides useful clues for understanding the molecular mechanisms, searching potential diagnosis biomarkers and therapeutic targets for IIM.

Solar desalination is expected to solve the problem of global water shortage. Yet its stability is plagued by salt accumulation. Here, a paper-based thermal radiation-enabled evaporation system (TREES) is demonstrated to achieve sustainable and highly efficient salt-collecting desalination, featuring a dynamic evaporation front based on the accumulated salt layer where water serves as its own absorber via energy down-conversion. When processing 7 wt % brine, it continuously evaporates water at a high rate─2.25 L m

Under a changing climate, cultivating climate-resilient crops will be critical to maintaining food security. Here, we propose the application of ROS-generating nanoparticles as nanobiostimulants to trigger stress/immune responses, and subsequently increase the stress resilience of plants. We established three regimens of AgNPs-based “stress training”: seed priming (SP), leaf priming (LP), and combined seed- and leaf- priming (SLP). Trained rice seedlings were then exposed to either rice blast fungus (M. oryzae.) or chilling stress (10 ºC). The results show that all “stress training” regimes, particularly SLP significantly enhanced the resistance of rice against the fungal pathogen (lesion size reduced by 82% relative to un-trained control). SLP training also significantly enhanced rice tolerance to cold stress. Under cold conditions, SLP training significantly increased leaf biomass by 35% compared to controls. The mechanisms for the enhanced resilience were investigated with metabolomic and transcriptomic profiling, which show that “stress training” induced considerable metabolic and transcriptional reprogramming in rice leaves. AgNPs-boosted ROS activated stress signaling pathways by oxidative post-translational modifications of stress related kinases, hormones, and transcriptional factors (TFs). These signaling pathways subsequently modulated the expression of defense genes, including specialized metabolites (SMs) biosynthesis genes, cell membrane lipid metabolism genes, and pathogen-plant interaction genes. These AgNPs-triggered metabolic and transcriptional reprogramming enable rice plants to mount a more rapid and intense response to future stresses. This nanobiostimulant-based strategy for increasing the stress resilience of crops will increase yield vigor against a changing climate and will contribute to sustainable agriculture by reducing agrochemical use.

In this paper, we propose a nonmonotone Alternative Direction Method (ADM) based on simple conic model for unconstrained optimization. Unlike traditional trust region method, the subproblem in our method is a simple conic model, where the Hessian of the objective function is replaced by a scalar approximation, the trust region subproblem is solved by ADM which was first proposed by Zhu and Ni. When the trial point isn’t accepted by trust region, line search technique is used to find an acceptable point instead of resolving the trust region subproblem. The new method needs less memory capacitance and computational complexity. The global convergence of the algorithm is established under some mild conditions. Numerical results on a series of standard test problems are reported to show the new method is effective and robust.

In this study, we aimed to evaluate the efficacy and safety of tacrolimus-based treatment for immunoglobulin A nephropathy (IgAN). We retrospectively reviewed 127 adult patients with primary IgAN with 24 h urine total protein quantity (24 h UTP) ≥ 1 g and serum creatinine ≤3 mg/dL. All patients were divided into tacrolimus (TAC) and control (non-TAC) groups according to the treatment strategy. Proteinuria remission, remission rate, and adverse events were compared between the two groups. Among the 127 patients, 61 received TAC-based treatment and 66 received non-TAC treatment. TAC group exhibited a more rapid decline in proteinuria than the non-TAC group at 3, 9, and 12 months (p = 0.049, 0.001, and 0.018, respectively). Remission rates at 1, 3, 6, 9, and 12 months were 41.0, 68.9, 80.3, 90.2, and 88.5%, respectively, in the TAC group. These rates were higher than those in the control group at 3, 9, and 12 months (p = 0.030, 0.008, and 0.026, respectively). Complete remission rates at 1, 3, 6, 9, and 12 months were 6.56, 19.7, 37.7, 54.1, and 62.3%, respectively, in the TAC group. These rates were higher than those in the control group at 9 and 12 months (p = 0.013 and 0.008, respectively). The estimated mean time to complete remission was significantly shorter in the TAC group than in the control group (p = 0.028). TAC did not increase the incidence of adverse events. In conclusion, TAC accelerated proteinuria remission in patients with non-rapidly progressive IgAN with no increased risk of adverse events. Further prospective randomized controlled trials are necessary to validate our findings.

The continuous emergence of highly immune evasive SARS-CoV-2 variants, like XBB.1.51,2and XBB.1.163,4, highlights the need to update COVID-19 vaccine compositions. However, immune imprinting induced by wildtype (WT)-based vaccination would compromise the antibody response to Omicron-based boosters5–9. Vaccination strategies that can counter immune imprinting are critically needed. In this study, we investigated the degree and dynamics of immune imprinting in mouse models and human cohorts, especially focusing on the role of repeated Omicron stimulation. Our results show that in mice, the efficacy of single Omicron-boosting is heavily limited by immune imprinting, especially when using variants antigenically distinct from WT, like XBB, while the concerning situation could be largely mitigated by a second Omicron booster. Similarly, in humans, we found that repeated Omicron infections could also alleviate WT-vaccination-induced immune imprinting and generate high neutralizing titers against XBB.1.5 and XBB.1.16 in both plasma and nasal mucosa. By isolating 781 RBD-targeting mAbs from repeated Omicron infection cohorts, we revealed that double Omicron exposure alleviates immune imprinting by generating a large proportion of highly matured and potent Omicron-specific antibodies. Importantly, epitope characterization using deep mutational scanning (DMS) showed that these Omicron-specific antibodies target distinct RBD epitopes compared to WT-induced antibodies, and the bias towards non-neutralizing epitopes observed in single Omicron exposures due to imprinting was largely restored after repeated Omicron stimulation, together leading to a substantial neutralizing epitope shift. Based on the DMS profiles, we identified evolution hotspots of XBB.1.5 RBD and demonstrated the combinations of these mutations could further boost XBB.1.5’s immune-evasion capability while maintaining high ACE2 binding affinity. Our findings suggest the WT component should be abandoned when updating COVID-19 vaccine antigen compositions to XBB lineages, and those who haven’t been exposed to Omicron yet should receive two updated vaccine boosters.

Immunoglobulin heavy chain variable region exons are assembled in progenitor-B cells, from VH, D, and JHgene segments located in separate clusters across theIghlocus. RAG endonuclease initiates V(D)J recombination from a JH-based recombination center (RC). Cohesin-mediated extrusion of upstream chromatin past RC-bound RAG presents Ds for joining to JHs to form a DJH-RC.Ighhas a provocative number and organization of CTCF-binding-elements (CBEs) that can impede loop extrusion. Thus,Ighhas two divergently oriented CBEs (CBE1 and CBE2) in the IGCR1 element between the VHand D/JHdomains, over 100 CBEs across the VHdomain convergent to CBE1, and 10 clustered 3’Igh-CBEs convergent to CBE2 and VHCBEs. IGCR1 CBEs segregate D/JHand VHdomains by impeding loop extrusion-mediated RAG-scanning. Down-regulation of WAPL, a cohesin unloader, in progenitor-B cells neutralizes CBEs, allowing DJH-RC-bound RAG to scan the VH domain and perform VH-to-DJH rearrangements. To elucidate potential roles of IGCR1-based CBEs and 3’Igh-CBEs in regulating RAG-scanning and elucidate the mechanism of the “ordered” transition from D-to-JHto VH-to-DJHrecombination, we tested effects of deleting or inverting IGCR1 or 3’Igh-CBEs in mice and/or progenitor-B cell lines. These studies revealed that normal IGCR1 CBE orientation augments RAG-scanning impediment activity and suggest that 3’Igh-CBEs reinforce ability of the RC to function as a dynamic loop extrusion impediment to promote optimal RAG scanning activity. Finally, our findings indicate that ordered V(D)J recombination can be explained by a gradual WAPL down-regulation mechanism in progenitor B cells as opposed to a strict developmental switch.SIGNIFICANCE STATEMENTTo counteract diverse pathogens, vertebrates evolved adaptive immunity to generate diverse antibody repertoires through a B lymphocyte-specific somatic gene rearrangement process termed V(D)J recombination. Tight regulation of the V(D)J recombination process is vital to generating antibody diversity and preventing off-target activities that can predispose the oncogenic translocations. Recent studies have demonstrated V(D)J rearrangement is driven by cohesin-mediated chromatin loop extrusion, a process that establishes genomic loop domains by extruding chromatin, predominantly, between convergently-oriented CTCF looping factor-binding elements (CBEs). By deleting and inverting CBEs within a critical antibody heavy chain gene locus developmental control region and a loop extrusion chromatin-anchor at the downstream end of this locus, we reveal how these elements developmentally contribute to generation of diverse antibody repertoires.

Supplementary Figures 1-3 from Intratumoral Delivery and Suppression of Prostate Tumor Growth by Attenuated Salmonella enterica serovar typhimurium Carrying Plasmid-Based Small Interfering RNAs

Supplementary Table 1 from Intratumoral Delivery and Suppression of Prostate Tumor Growth by Attenuated Salmonella enterica serovar typhimurium Carrying Plasmid-Based Small Interfering RNAs

The facultative anaerobic, invasive Salmonella enterica serovar typhimurium (S. typhimurium) has been shown to retard the growth of established tumors. We wondered if a more effective antitumor response could be achieved in vivo if these bacteria were used as tools for delivering specific molecular antitumor therapeutics. Constitutively activated transcription factor signal transducer and activator of transcription 3 (STAT3) promotes the survival of a number of human tumors. In this study, we investigated the relative efficacies of attenuated S. typhimurium alone or combined with Stat3-specific small interfering RNA (siRNA) in terms of tumor growth and metastasis. The bacteria preferentially homed into tumors over normal liver and spleen tissues in vivo. S. typhimurium expressing plasmid-based Stat3-specific siRNAs significantly inhibited tumor growth, reduced the number of metastastic organs, and extended the life time for C57BL6 mice bearing an implanted prostate tumor, versus bacterial treatment alone. These results suggest that attenuated S. typhimurium combined with an RNA interference approach might be more effective for the treatment of primary as well as metastatic cancer. [Cancer Res 2007;67(12):5859–64]

In this paper, a new water-bomb wheel modeling method is proposed. Based on the water-bomb wheel model, an expandable robot with a multi-link support structure and water-bomb structure is designed and manufactured. A parameterized kinematics solution method is proposed for this variable-diameter wheel robot, which enables the robot to obtain highly reliable odometer information by fusing encoder and IMU information in all states. Based on the parameterized kinematics solution method, SLAM and autonomous navigation system were implemented using the ROS robot operating system as the software platform, and simulation experiments and physical prototype experiments were carried out.

The recognition of cutting state of coal-rock is the key technology to realize “unmanned” mining in coal face. In order to realized real-time perception and accurate judgment of coal-rock cutting state information, this paper combined the field test sampling, construction technology of complex coal seam, virtual prototype technology, bidirectional coupling technology, data processing theory, image fusion method, and deep learning theory to carry out multi domain deep fusion experimental research on multi-source heterogeneous data of coal and rock cutting state. The typical complex coal seam containing gangue, inclusion, and minor fault in Yangcun mine of Yanzhou mining area was taken as the engineering object. The high-precision three-dimensional simulation model of the complex coal seam that can update and replace particles was constructed. Based on the simulation results of Discrete Element Method-Multi Flexible Body Dynamics (DEM-MFBD), the one-dimensional original vibration acceleration signals of the key components of the shearer cutting part were determined, including spiral drum, rocker arm shell, and square head. After transforming one-dimensional original signal data into two-dimensional time–frequency images by Short-time Fourier Transform, morphological wavelet image fusion technology was used to realize the effective fusion of characteristic information of spiral drum, rocker arm shell, and square head under different working conditions. Based on the deep learning theory, the DCGAN-RFCNN (Deep Convolutional Generative Adversarial Networks-Random Forest Convolutional Neural Networks) coal and rock cutting state recognition network model was constructed. Combining convolution neural network with random forest recognition classifier, RFCNN coal and rock cutting state recognition classification model was constructed, and the recognition network model was trained to obtain the model recognition results. Through the comparative experimental analysis of the RFCNN network model with different recognition network models and different synthetic sample numbers in the recognition network, the effectiveness of the recognition network model was verified. The results show that: When synthetic samples are not included in each working condition in the RFCNN model, the average recognition rate is 90.641%. With the increase of the number of synthetic samples, the recognition rate of coal and rock cutting state increases. When the number of synthetic samples added to each working condition reaches 5000, the recognition effect is the best, and the average recognition rate reaches 98.344%, which verifies the superiority of enriching the data set by using the improved DCGAN network. Also, the RFCNN outperformed the other variants: it obtained higher recognition accuracy by 25.085, 21.925 and 19.337%, respectively, over SVW, CNN, and AlexNet. Also, the experimental platform of shearer cutting coal and rock was built, where the coal and rock cutting state recognition network was trained and tested based on the migration learning theory. Through the statistical test results, the accuracy of coal and rock cutting state recognition is 98.64%, which realizes the accurate recognition of coal and rock cutting state.

Chronic kidney disease (CKD) is recognized as a serious global health problem due to its high prevalence and all-cause mortality. The aim of this research was to identify critical biomarkers and construct an integrated model for the early prediction of CKD. By using existing RNA-seq data and clinical information from CKD patients from the Gene Expression Omnibus (GEO) database, we applied a computational technique that combined the random forest (RF) and artificial neural network (ANN) approaches to identify gene biomarkers and construct an early diagnostic model. We generated ROC curves to compare the model with other markers and evaluated the associations of selected genes with various clinical properties of CKD. Moreover, we highlighted two biomarkers involved in energy metabolism pathways: pyruvate dehydrogenase kinase 4 (PDK4) and zinc finger protein 36 (ZFP36). The downregulation of the identified key genes was subsequently confirmed in both unilateral ureteral obstruction (UUO) and ischemia reperfusion injury (IRI) mouse models, accompanied by decreased energy metabolism. In vitro experiments and single-cell sequencing analysis proved that these key genes were related to the energy metabolism of proximal tubule cells and were involved in the development of CKD. Overall, we constructed a composite prediction model and discovered key genes that might be used as biomarkers and therapeutic targets for CKD.

The analysis of the current economic statistics system shows that the requirements for computing and storage capacity are relatively high. For the previous main controller, it is difficult to meet this basic requirement, but the application of cloud computing technology can solve this problem to a greater extent. Therefore, this paper designs a new economic analysis system based on cloud computing, which can enable small- and medium-sized enterprises to master the business information transmitted by customer economy and improve the quality of monitoring service. Experiments in this paper show that the designed system can reduce the cost of remote communication, interact with SMS, and realize dual channel communication.

Lijuan Zhao, Lin Wu School of Sociology, Wuhan University, Wuhan, Hubei, People’s Republic of ChinaCorrespondence: Lin Wu, School of Sociology, Wuhan University, Wuhan, 430072, People’s Republic of China, Tel +86 136 186 65056, Email wlin@whu.edu.cnPurpose: The study aims to examine whether and how digital activities influence sleep issues among working Chinese youth.Methods: This study used data from the China Family Panel Studies (CFPS) a Chinese population-based survey, and employed the multilevel ordinal logistic regression model (MOLRM) to test the associations between digital engagement (whether to engage in digital activity, frequency, and duration) and sleep issues (bedtime, sleep duration, and quality) among Chinese working youth. Additionally, the restricted cubic spline model (RCSM) was adopted to fit the MOLRM to evaluate the nonlinear relationship between digital activity duration and sleep quality, and thus determine the optimal range of digital activity duration.Results: The analysis included 7849 working young adults. The digital usage rate was 84.11%. Digital use was not significantly associated with average, workday, or free-day sleep duration, after controlling for all potential confounders. However, most digital activity indicators could significantly predict bedtime and sleep quality. Furthermore, the RCSM indicated a non-linear relationship pattern between digital activity duration and sleep quality, with a weekly peak point of 25 h. Age significantly moderated the relationship between digital activity, sleep duration and bedtime. Younger youth who used digital media more frequently and for a longer time tended to sleep later and had shorter sleep duration than older youth.Conclusion: Digital usage significantly predicted later bedtime among Chinese working youth; however, it was not linked with sleep duration on workdays or free days. In parallel, a nonlinear correlation between digital activity duration and sleep quality indicated that appropriate digital activity duration (less than 25 h weekly) may contribute to good sleep quality.Keywords: working youth, digital activity, sleep issues, time shifting, time displacement

The cause of endometriosis, which is characterized by the existence of functional endometrial tissue outside the uterine cavity, is poorly understood. Seminal plasma (SP) is rich in multiple cytokines that may promote endometrial tissue survival. Here, we evaluated the effect of SP on growth of endometrial mesenchymal stem cells (MSCs) from women with endometriosis (E-MSCs) and women without endometriosis (NE-MSCs). Proliferation, cell foci formation, cell cycle progression, and growth marker expression of E- and NE-MSCs were promoted by SP. These effects may be mediated through activation of transforming growth factor beta 1 (TGF-β1), Akt, and p42/44 signaling, which enhances CDK2 and CDK6 expression and accelerates cell cycle progression. Xenografts exposed to SP exhibited a three-fold increase in volume and four-fold increase in weight after 14 days. Our findings demonstrate that TGF-β1 in SP may promote endometrial tissue survival which will allow us to understand the pathogenesis and develop novel approaches for prevention and therapies of endometriosis.

A novel helix hydrogel with a G-quartet structure was synthesized from guanosine (Gua) and its derivative 5'-guanosine monophosphate (5'-GMP) under a molecular crowding environment. The chirality of the hydrogel is adjusted by controlling the gelling speed. The chiral hydrogel can induce an achiral dye Thioflavin T (ThT) to realize circularly polarized fluorescence (CPL). The CPL dissymmetry factor

Chiral CuS NPs were prepared through a ligand-exchange process and CPL-controlled photothermal performance was realized.

Objective To observe the effects of distance training on patients with continuous ambulatory peritoneal dialysis (CAPD) during the transmission control of the COVID-19 epidemic in China. Materials and methods CAPD patients from Xijing Hospital received a traditional training before the transmission control of COVID-19 epidemic, while they received a distance training dominated by WeChat and telephone during the transmission control of COVID-19 epidemic in China. Incidence and cure rate of PD-related peritonitis and catheter-related non-infectious complications were compared. All patients were followed up for 30 days from the date of complication. Results PD-related peritonitis, catheter displacement, and catheter occlusion had no significant difference, and the cure rate of PD-related peritonitis, catheter displacement, and catheter occlusion also had no significant difference in two comparisons despite the cure rate of PD-related peritonitis being slightly higher before (90.9%) than during (80%) the transmission control of COVID-19 epidemic. Conclusion Distance training mode had a similar effect compared to the traditional training mode in the prevention and treatment of PD-related peritonitis and catheter-related non-infectious complications. Practice implications Distance training model is an effective training mode that can be implemented in a short time during the epidemic period of serious infectious diseases.

This work introduces an eco-friendly, efficient, and low-cost approach for the removal of hazardous inorganic bromides and the recovery of a high-purity NaBr product from waste printed circuit board smelting ash via a mechano-chemical technology.

Under an appropriate exposure dose, AgNPs provide positive impacts on rice tillering, yield, grain metabolite profile, and soil bacteria.

Estrogen combined with physical barrier therapy may be a prospective method to repair a damaged endometrium and prevent postsurgical re-adhesion in the treatment of intrauterine adhesions (IUAs), but there lacks a suitable scaffold with good biocompatibility, appropriate mechanical properties, and drug-releasing kinetics. Herein, a mechanically robust and stable barrier based on the poly(hydroxyethyl methacrylate) (PHEMA) hydrogel combined with estradiol-loaded mesoporous silica is designed. The network is formed by covalent bonds and noncovalent coordination bonds, which endow the hydrogel with superior mechanical properties to most reported PHEMA-based hydrogels. Meanwhile, the covalent bonds impart excellent stability to the hydrogel, which maintains its structure and mechanical properties in a simulated uterine fluid for 30 days. The excellent mechanical properties and stability are comparable to those of a typical barrier material intrauterine device (IUD), enabling the hydrogel to be retained in the uterus and removed intact like an IUD.

Seeds are facing harsher environments due to the changing climate. Improving seeds' stress resilience is critical to reduce yield loss. Here, we propose that using ROS-generating nanoparticles (NPs) to prestimulate seeds would enhance the stress resilience of seeds and seedlings through triggering stress/immune responses. We examined this hypothesis by exposing AgNPs-primed rice (

Salt stress is a major abiotic stress affecting plant growth and crop yield. For the successful cultivation of alfalfa (Medicago sativa L.), a key legume forage, in saline-affected areas, it’s essential to explore genetic modifications to improve salt-tolerance.Transcriptome assay of two comparative alfalfa genotypes, Adina and Zhaodong, following a 4 h and 8 h’s 300 mM NaCl treatment was conducted in this study in order to investigate the molecular mechanism in alfalfa under salt stress conditions. Results showed that we obtained 875,023,571 transcripts and 662,765,594 unigenes were abtained from the sequenced libraries, and 520,091 assembled unigenes were annotated in at least one database. Among them, we identified 1,636 differentially expression genes (DEGs) in Adina, of which 1,426 were up-regulated and 210 down-regulated, and 1,295 DEGs in Zhaodong, of which 565 were up-regulated and 730 down-regulated. GO annotations and KEGG pathway enrichments of the DEGs based on RNA-seq data indicated that DEGs were involved in (1) ion and membrane homeostasis, including ABC transporter, CLC, NCX, and NHX; (2) Ca2+ sensing and transduction, including BK channel, EF-hand domain, and calmodulin binding protein; (3) phytohormone signaling and regulation, including TPR, FBP, LRR, and PP2C; (4) transcription factors, including zinc finger proteins, YABBY, and SBP-box; (5) antioxidation process, including GST, PYROX, and ALDH; (6) post-translational modification, including UCH, ubiquitin family, GT, MT and SOT. The functional roles of DEGs could explain the variations in salt tolerance performance observed between the two alfalfa genotypes Adina and Zhaodong. Our study widens the understanding of the sophisticated molecular response and tolerance mechanism to salt stress, providing novel insights on candidate genes and pathways for genetic modification involved in salt stress adaptation in alfalfa.