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The interplay between plant diversity and environmental response strategies is crucial for ecosystem adaptability and stability. A central focus in modern ecology is elucidating how environmental factors shape plant diversity patterns and regulate species distributions across heterogeneous landscapes. This study employed Joint Species Distribution Model (JSDM) to quantitatively analyze the influence of environmental variables on plant spatial distributions in Gansu Province, China, while examining interspecies interactions under varying conditions. Results demonstrated that environmental factors explained 95.4% of the variance, highlighting their predominant role in determining plant distributions. Habitat type accounted for the largest share of variance (33.5%), followed by elevation (22.1%), mean annual temperature (20.3%), mean annual precipitation (15.1%), and solar radiation (4.4%). Species’ responses to environmental covariates were predominantly independent, with weak phylogenetic correlation (posterior mean: 0.17), reflecting limited ecological niche conservatism at the family level. Geographically, regions such as the northern Qilian foothills, Lanzhou-Baiyin wilderness, Loess Plateau, and Gannan Plateau exhibited negative correlations with most plant families, functioning as critical limiting or driving factors in spatial variability. Additionally, 33.7% of seed plant families showed negative correlations with light intensity, underscoring its role as a major limiting factor. Provincially, competition does not primarily constrain seed plant coexistence in Gansu. Regionally, however, pronounced differences in environmental responses were observed. In the northwest, solar radiation (37%) and precipitation (25%) were dominant drivers of plant distribution, while in the southeast, solar radiation (36.3%) and elevation (34.7%) were predominant. These findings underscore that species co-occurrence patterns are scale-dependent and influenced by regional resource availability. In resource-abundant southeastern areas, plant families displayed positive co-occurrence patterns indicative of mutualistic or symbiotic interactions, whereas resource-scarce northwestern areas experienced intensified negative co-occurrences due to heightened interspecific competition. This study highlights the critical role of environmental gradients in structuring seed plant distributions in Gansu, providing insights into the interaction of ecological adaptation and evolutionary history in shaping plant diversity. By identifying the drivers of plant distribution across heterogeneous environments, this research offers significant implications for biodiversity conservation and plant resource management strategies in Gansu Province, while contributing to a broader understanding of plant-environment dynamics in complex ecosystems.

Background: Cladribine tablets are contraindicated during pregnancy; therefore, safety data on pregnancies exposed to this treatment are limited. CLEAR collects and describes pregnancy outcomes in this understudied population. Objectives: To describe the main features of the CLEAR study design, including the data sources and the methodological approach, and provide a status update. Design: CLEAR is a non-interventional, multi-database, comparative cohort study. Four cohorts are included: pregnancies of women with multiple sclerosis (MS) exposed to cladribine tablets (maternal cohort exposed); pregnancies of women with MS unexposed to any disease-modifying therapy (DMT; maternal cohort unexposed); pregnancies fathered by men with MS exposed to cladribine tablets; and pregnancies fathered by men with MS unexposed to any DMT. Methods: A staggered methodological approach, using data from Denmark, Finland, France, Germany, Norway, Scotland, and Sweden, will be applied to analyze the occurrence of major congenital anomalies (primary outcome) and selected pregnancy outcomes. The first interim analysis (performed using German pregnancy cohorts) was conducted when ⩾75 pregnant women (including 25 women from the maternal cohort exposed) were cumulatively reached across all participating countries. The end of the study period will be established once pregnancy counts reach 149 in the maternal cohort exposed and 298 in the maternal cohort unexposed in all countries combined, or 5 years after pregnancy counts are first assessed (whichever occurs first). Results: As of January 2024, data on pregnancies of women exposed to cladribine tablets ( n = 28–36 (numbers are approximate due to masking of some counts)), and pregnancies of women unexposed to cladribine tablets ( n = 2834) were available from Denmark, Finland, Germany, Scotland, and Sweden. Conclusion: The CLEAR study, using a staggered methodological approach, aims to provide further insight into the safety outcome data for cladribine tablets in pregnant women, as a regulatory commitment with the European Medicines Agency. Trial registration: EU PAS Register number, EUPAS25027.

IntroductionPhosphoinositide-3-kinase (PI3K) is overexpressed in many tumors and is, thus, an ideal target for cancer treatments. Accordingly, there is an urgent need for the development of PI3K inhibitors with high potency and low toxicity.MethodsIn this study, we designed and synthesized a series of 2,4-dimorpholinopyrimidine-5-carbonitrile derivatives, which were evaluated for their PI3K inhibitory potency.Results and discussionCompound 17p demonstrated comparable PI3Kα inhibitory activity (IC50: 31.8 ± 4.1 nM) to the positive control, BKM-120 (IC50: 44.6 ± 3.6 nM). In addition, 17p showed significant inhibitory activity against PI3Kδ (IC50: 15.4 ± 1.9 nM) and significant isoform selectivity against PI3Kβ, PI3Kγ, and mTOR. Furthermore, 17p exhibited good antiproliferative activities against cancer cell activity and good safety in the Ames and hERG tests while having outstanding liver microsomal stability in vitro, with half-lives of 38.5 min in rats and 127.9 min in humans. In addition, in an apoptosis assay, 17p could induce dose-dependent cytotoxicity in the ovarian cancer cell line A2780. In a pharmacokinetic study, 17p was stable (T½: 2.03 h) and showed high bioavailability (46.2%). Collectively, these results indicate that 17p could be a promising PI3K agent for cancer treatment.

Abstract Wildfires, as an environmental filter, are pivotal ecological disturbances that reshape plant communities and soil dynamics, playing a crucial role in regulating biogeographic patterns and ecosystem services. In this study, we aim to explore the effects of wildfires on forest ecosystems, specifically focusing on the plant-soil feedback mechanisms within the northeastern margin of the Qinghai-Tibet Plateau (QTP). Utilizing Partial Least Squares Path Modeling (PLS-PM), we investigated the interrelationships among soil physicochemical properties, enzyme activities, species diversity, and community stability at varying post-fire recovery stages (5, 15, and 23 years). Results indicated that in the early recovery stages, rapid changes in soil properties such as decreased pH (p

Abstract With the increasing trend of global aging, sarcopenia has become a significant public health issue. Goji berry, also known as “Gou qi zi” in China, is a traditional Chinese herb that can enhance the structure and function of muscles and bones. Otherwise, previous excellent publications illustrated that plant-derived exosome-like nanoparticles can exert good bioactive functions in different aging or disease models. Thus, we issued the hypothesis that Gouqi-derived nanovesicles (GqDNVs) may also have the ability to improve skeletal muscle health, though the effect and its mechanism need to be explored. Hence, we have extracted GqDNVs from fresh berries of Lycium barbarum L. (goji) and found that the contents of GqDNVs are rich in saccharides and lipids. Based on the pathway annotations and predictions in non-targeted metabolome analysis, GqDNVs are tightly associated with the pathways in metabolism. In muscle atrophy model mice, intramuscular injection of GqDNVs improves the cross-sectional area of the quadriceps muscle, grip strength and the AMPK/SIRT1/PGC1α pathway expression. After separately inhibiting AMPK or PGC1α in C2C12 cells with dexamethasone administration, we have found that the activated AMPK plays the chief role in improving cell proliferation induced by GqDNVs. Furthermore, the energy-targeted metabolome analysis in the quadriceps muscle demonstrates that the GqDNVs up-regulate the metabolism of amino sugar and nucleotide sugar, autophagy and oxidative phosphorylation process, which indicates the activation of muscle regeneration. Besides, the Spearman rank analysis shows close associations between the quality and function of skeletal muscle, metabolites and expression levels of AMPK and SIRT1. In this study, we provide a new founding that GqDNVs can improve the quality and function of skeletal muscle accompanying the activated AMPK/SIRT1/PGC1α signaling pathway. Therefore, GqDNVs have the effect of anti-aging skeletal muscle as a potential adjuvant or complementary method or idea in future therapy and research. Graphical Abstract

To address the challenges in controlling a Tunnel Boring Machine (TBM) equipped with a V-type propulsion system during excavation, a digging attitude control strategy based on a nonlinear controller is introduced. First, the mathematical models of the V-type propulsion hydraulic system and the propulsion system’s attitude are developed, followed by an analysis of the system’s nonlinearities and susceptibility to strong disturbances. Second, a nonlinear control strategy tailored to the propulsion system’s characteristics is devised to regulate the digging attitude of the V-TBM. Finally, the proposed nonlinear control strategy is validated through comprehensive simulations and experimental evaluations. Simulation results demonstrate that the proposed nonlinear control strategy outperforms traditional PID control in attitude regulation performance. Field experiments reveal that the TBM achieves an average horizontal error of less than 20 mm and a vertical error of less than 22 mm in circular curve boring. This validates the strategy’s effectiveness in enabling rapid tracking and adjustment of the tunnel boring axis, meeting the stringent demands of small-radius curved boring.

Plastic film-bottomed treatment (FBT) is a critical agricultural practice in arid regions, aimed at enhancing crop productivity by improving soil moisture retention and nutrient availability. However, the effects of different depths of film-bottomed treatment (DFBT) on nitrogen (N) absorption and translocation in spring wheat remain inadequately understood. We conducted a field experiment on sandy soil to investigate the effects of different DFBT depths (60, 70, 80, 90, and 100 cm) and on total N absorption amount (TNAA), total N translocation amount (TNTA) in all nutritive organs, grain nitrogen content (GN), and grain yield (GY). Morphological measurements included GY, GN, TNAA, and TNTA in the stem, sheath, leaf, spike axis, kernel husk (SAKH), and culm. The results showed that FBT significantly reduced soil moisture loss, with the 100 cm depth reducing soil leakage by 59.6% (p < 0.001). At the flowering stage, nitrogen derived from fertilizer (NDF) and soil nitrogen (NDS) were significantly higher at the 80 cm depth (p < 0.001). At maturity, the total nitrogen absorption amount (TNAA) and translocation amount (TNTA) in the main stem and across nutrient organs were significantly higher under the 80 cm DFBT (p < 0.001), leading to improved nitrogen use efficiency. The correlation between TNTA and GN was strongest at 80 cm (p < 0.001). Grain yield (GY) and GN were optimized at intermediate depths, particularly at 80 cm, suggesting this depth provides an optimal balance between water retention and drainage efficiency. These findings underscore the importance of optimizing DFBT depth, particularly at 80 cm, to achieve enhanced water retention, efficient nitrogen utilization, and improved crop productivity in arid agricultural systems. This research provides critical insights into sustainable agricultural practices under water-limited conditions, offering practical guidance for improving food security in arid regions.

Forest fires play a pivotal role in influencing ecosystem evolution, exerting a profound impact on plant diversity and community stability. Understanding post-fire recovery strategies holds significant scientific importance for the ecological succession and restoration of forest ecosystems. This study utilized Partial Least Squares Path Modeling (PLS-PM) to investigate dynamic relationships among plant species diversity, phylogenetic diversity, soil properties, and community stability during various recovery stages (5-year, 15-year, and 23-year) following wildfires on the northeastern margin of the Qinghai-Tibet Plateau. The findings revealed: (1) Over time, species richness significantly decreased (p< 0.05 or p< 0.01), while species diversity and dominance increased, resulting in uniform species distribution. Community stability progressively improved, with increased species compositional similarity. (2) Throughout succession, phylogenetic diversity (PD) significantly decreased (p< 0.01), accompanied by rising Mean Pairwise Distance (MPD) and Mean Nearest Taxon Distance (MNTD). Net Relatedness Index (NRI) shifted from positive to negative, indicating an increasing aggregation and dominance of plants with similar evolutionary traits in burned areas. Early succession witnessed simultaneous environmental filtering and competitive exclusion, shifting predominantly to competitive exclusion in later stages. (3) PLS-PM revealed that in the early recovery stage, soil properties mainly affected community stability, while species diversity metamorphosed into the primary factor in the mid-to-late stages. In summary, this study showed that plant diversity and phylogenetic variation were successful in revealing changes in community structure during the succession process. Soil characteristics functioned as selective barriers for plant communities during succession, and community stability underwent a multi-faceted and dynamic process. The soil-plant dynamic feedback continuously enhanced soil conditions and community vegetation structure thereby augmenting stability. Post-fire vegetation gradually transitioned towards the original native state, demonstrating inherent ecological self-recovery capabilities in the absence of secondary disturbances.

Background: The efficacy of mesenchymal stem cells (MSCs) in treating liver fibrosis has been supported by various clinical studies. However, stem cell transplantation is limited in clinical application due to its low survival rate, low liver implantation rate, and possible carcinogenicity. Recently, there has been increasing interest in the use of MSC-exos due to their widespread availability, low immunogenicity, and non-carcinogenic properties. Numerous studies have demonstrated the potential of MSC-exos in treating liver fibrosis and preventing progression to end-stage liver disease.Objective: This study aimed to systematically investigate the efficacy of MSC-exos single administration in the treatment of hepatic fibrosis and the combined advantages of MSC-exos in combination with drug therapy (MSC-exos-drugs).Methods: Data sources included PubMed, Web of Science, Embase, and the Cochrane Library, which were built up to January 2024. The population, intervention, comparison, outcomes, and study design (PICOS) principle was used to screen the literature, and the quality of the literature was evaluated to assess the risk of bias. Finally, the data from each study’s outcome indicators were extracted for a combined analysis.Results: After screening, a total of 18 papers (19 studies) were included, of which 12 involved MSC-exos single administration for the treatment of liver fibrosis and 6 involved MSC-exos-drugs for the treatment of liver fibrosis. Pooled analysis revealed that MSC-exos significantly improved liver function, promoted the repair of damaged liver tissue, and slowed the progression of hepatic fibrosis and that MSC-exos-drugs were more efficacious than MSC-exos single administration. Subgroup analyses revealed that the use of AD-MSC-exos resulted in more consistent and significant efficacy when MSC-exos was used to treat hepatic fibrosis. For MSC-exos-drugs, a more stable end result is obtained by kit extraction. Similarly, infusion through the abdominal cavity is more effective.Conclusion: The results suggest that MSC-exos can effectively treat liver fibrosis and that MSC-exos-drugs are more effective than MSC-exos single administration. Although the results of the subgroup analyses provide recommendations for clinical treatment, a large number of high-quality experimental validations are still needed.Systematic Review Registration: CRD42024516199.

Abstract Background Autosomal dominant polycystic kidney disease (ADPKD) is the leading inheritable cause of end-stage renal disease (ESRD). Mortality data specific to patients with ADPKD is currently lacking; thus, the aim of this study was to estimate mortality in patients with ADPKD. Methods We analyzed data from the United States Renal Data System (USRDS) for patients with ADPKD available during the study period of 01/01/2014–12/31/2016, which included a cohort of patients with non-ESRD chronic kidney disease (CKD) and a cohort of patients with ESRD. Mortality rates with 95% confidence intervals (CIs) were calculated overall and by age group, sex, and race for the full dataset and for a subset of patients aged ≥ 65 years. Adjusted mortality hazard ratios (HRs) were calculated using Cox regression modeling by age group, sex, race, and CKD stage (i.e., non-ESRD CKD stages 1–5) or ESRD treatment (i.e., dialysis and transplant). Results A total of 1,936 patients with ADPKD and non-ESRD CKD and 37,461 patients with ADPKD and ESRD were included in the analysis. Age-adjusted mortality was 18.4 deaths per 1,000 patient-years in the non-ESRD CKD cohort and 37.4 deaths per 1,000 patient-years in the ESRD cohort. As expected, among the non-ESRD CKD cohort, patients in CKD stages 4 and 5 had a higher risk of death than patients in stage 3 (HR = 1.59 for stage 4 and HR = 2.71 for stage 5). Among the ESRD cohort, patients receiving dialysis were more likely to experience death than patients who received transplant (HR = 2.36). Age-adjusted mortality among patients aged ≥ 65 years in the non-ESRD CKD cohort was highest for Black patients (82.7 deaths per 1,000 patient-years), whereas age-adjusted mortality among patients aged ≥ 65 years in the ESRD cohort was highest for White patients (136.1 deaths per 1,000 patient-years). Conclusions Mortality rates specific to patients aged ≥ 65 years suggest racial differences in mortality among these patients in both non-ESRD CKD and ESRD cohorts. These data fill an important knowledge gap in mortality estimates for patients with ADPKD in the United States.

Hyperspectral remote sensing technology is swiftly evolving, prioritizing affordability, enhanced portability, seamless integration, sophisticated intelligence, and immediate processing capabilities. The leading model for classifying hyperspectral images, which relies on convolutional neural networks (CNNs), has proven to be highly effective when run on advanced computing platforms. Nonetheless, the high degree of parameterization inherent in CNN models necessitates considerable computational and storage resources, posing challenges to their deployment in processors with limited capacity like drones and satellites. This paper focuses on advancing lightweight models for hyperspectral image classification and introduces EBCNN, a novel binary convolutional neural network. EBCNN is designed to effectively regulate backpropagation gradients and minimize gradient discrepancies to optimize BNN performance. EBCNN incorporates an adaptive gradient scaling module that utilizes a multi-scale pyramid squeeze attention (PSA) mechanism during the training phase, which can adjust training gradients flexibly and efficiently. Additionally, to address suboptimal training issues, EBCNN employs a dynamic curriculum learning strategy underpinned by a confidence-aware loss function, Superloss, enabling progressive binarization and enhancing its classification effectiveness. Extensive experimental evaluations conducted on five esteemed public datasets confirm the effectiveness of EBCNN. These analyses highlight a significant enhancement in the classification accuracy of hyperspectral images, achieved without incurring additional memory or computational overheads during the inference process.

Multi-Label Classification refers to the classification task where a data sample is associated with multiple labels simultaneously, which is widely used in text classification, image classification, and other fields. Different from the traditional single-label classification, each instance in Multi-Label Classification corresponds to multiple labels, and there is a correlation between these labels, which contains a wealth of information. Therefore, the ability to effectively mine and utilize the complex correlations between labels has become a key factor in Multi-Label Classification methods. In recent years, research on label correlations has shown a significant growth trend internationally, reflecting its importance. Given that, this paper presents a survey on the label correlations in Multi-Label Classification to provide valuable references and insights for future researchers. The paper introduces multi-label datasets across various fields, elucidates and categorizes the concept of label correlations, emphasizes their utilization in Multi-Label Classification and associated subproblems, and provides a prospect for future work on label correlations.

Abstract Surface water monitoring data has spatiotemporal characteristics, and water quality will change with time and space in different seasons and climates. Data of this nature brings challenges to clustering, especially in terms of obtaining the temporal and spatial characteristics of the data. Therefore, this paper proposes an improved TADW algorithm and names it RTADW to obtain the spatiotemporal characteristics of surface water monitoring points. We improve the feature matrix in TADW and input the original time series data and spatial information into the improved model to obtain the spatiotemporal feature vector. When the improved TADW model captures watershed information for clustering, it can simultaneously extract the temporal and spatial characteristics of surface water compared with other clustering algorithms such as the DTW algorithm. We applied the proposed method to multiple different monitoring sites in the Liaohe River Basin, analyzed the spatiotemporal regional distribution of surface water monitoring points. The results show that the improved feature extraction method can better capture the spatiotemporal feature information between surface water monitoring points. Therefore, this method can provide more potential information for cluster analysis of water environment monitoring, thereby providing a scientific basis for watershed zoning management.

Cisplatin-based chemotherapy is the current standard care for lung cancer patients; however, drug resistance frequently develops during treatment, thereby limiting therapeutic efficacy.The molecular mechanisms underlying cisplatin resistance remain elusive. In this study, we conducted an analysis of microarray data from the Gene Expression Omnibus (GEO) database under the accession numbers GSE21656, which encompassed expression profiling of cisplatin-resistant H460 (DDP-H460)and the parental cells (H460). Subsequently, we calculated the differentially expressed genes (DEGs) between DDP-H460 and H460. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs demonstrated significant impact on the Rap1, PI3K/AKT and MAPK signaling pathways. Moreover, protein and protein interaction (PPI) network analysis identified PRKCA, DET1, and UBE2N as hub genes that potentially contribute predominantly to cisplatin resistance. Ultimately, PRKCA was selected for validation due to its significant prognostic effect, which predicts unfavorable overall survival and disease-free survival in patients with lung cancer. Network analysis conducted on The Cancer Genome Atlas (TCGA) database revealed a strong gene-level correlation between PRKCA and TP53, CDKN2A, BYR2, TTN, KRAS, and PIK3CA; whereas at the protein level, it exhibited a high correlation with EGFR, Lck, Bcl2, and Syk. The in vitro experiments revealed that PRKCA was upregulated in the cisplatin-resistant A549 cells (DDP-A549), while knockdown of PRKCA increased DDP-A549 apoptosis upon cisplatin treatment. Moreover, we observed that PRKCA knockdown attenuated DDP-A549 proliferation, migration and invasion ability. Western blot analysis demonstrated that PRKCA knockdown downregulated phosphorylation of PI3K expression while upregulated the genes involved in ferroptosis signaling. In summary, our results elucidate the role of PRKCA in acquiring resistance to cisplatin and underscore its potential as a therapeutic target for cisplatin-resistant lung cancer.

Abstract Extracellular vesicles (EVs) play an important role in human and bovine milk composition. According to excellent published studies, it also exerts various functions in the gut, bone, or immune system. However, the effects of milk-derived EVs on skeletal muscle growth and performance have yet to be fully explored. Firstly, the current study examined the amino acids profile in human milk EVs (HME) and bovine milk EVs (BME) using targeted metabolomics. Secondly, HME and BME were injected in the quadriceps of mice for four weeks (1 time/3 days). Then, related muscle performance, muscle growth markers/pathways, and amino acids profile were detected or measured by grip strength analysis, rotarod performance testing, Jenner-Giemsa/H&E staining, Western blotting, and targeted metabolomics, respectively. Finally, HME and BME were co-cultured with C2C12 cells to detect the above-related indexes and further testify relative phenomena. Our findings mainly demonstrated that HME and BME significantly increase the diameter of C2C12 myotubes. HME treatment demonstrates higher exercise performance and muscle fiber densities than BME treatment. Besides, after KEGG and correlation analyses with biological function after HME and BME treatment, results showed L-Ornithine acts as a “notable marker” after HME treatment to affect mouse skeletal muscle growth or functions. Otherwise, L-Ornithine also significantly positively correlates with the activation of the AKT/mTOR pathway and myogenic regulatory factors (MRFs) and can also be observed in muscle and C2C12 cells after HME treatment. Overall, our study not only provides a novel result for the amino acid composition of HME and BME, but the current study also indicates the advantage of human milk on skeletal muscle growth and performance.

Abstract Time series prediction of river water quality is an important method to grasp the changes of river water quality and protect the river water environment. However, due to the time series data of river water quality have strong periodicity, seasonality and nonlinearity, which seriously affects the accuracy of river water quality prediction. In this paper, a new hybrid deep neural network model is proposed for river water quality prediction, which is integrated with Savitaky-Golay (SG) filter, STL time series decomposition method, Self-attention mechanism, and Temporal Convolutional Network (TCN). The SG filter can effectively remove the noise in the time series data of river water quality, and the STL technology can decompose the time series data into trend, seasonal and residual series. The decomposed trend series and residual series are input into the model combining the Self-attention mechanism and TCN respectively for training and prediction. In order to verify the proposed model, this study uses opensource water quality data and private water quality data to conduct experiments, and compares with other water quality prediction models. The experimental results show that our method achieves the best prediction results in the water quality data of two different rivers.

Chinese herbs are a huge treasure trove of natural products and an important source of many active molecules. The theory of traditional Chinese medicine compatibility (TCMC) is widely applied in clinical practice, but its mechanism is still ambiguous. This study aims to open a new window for this predicament by studying the interaction between the main active ingredients from a drug pair. Carrier-free assembly of natural products improves the shortcomings of traditional nanodelivery systems and opens a new path for the development of new nanomaterials. The drug pair “Pueraria and Hedyotis diffusa” has been commonly used in clinical practice, with a predominant therapeutic effect. This study is devoted to the study of the binary small molecule co-assembly of the main active molecules from the drug pair. In this study, we introduce a carrier-free composite gel, formed by the co-assembly of puerarin (PUE) and deacetylasperulosidic acid (DAA) via non-covalent bonds including π–π packing, intermolecular hydrogen bonding, and C=O π interactions. With a strain point 7-fold higher than that of P gel, the P − D gel exhibited favorable rheological properties. The survival rate of SW1990 cells in the P − D group was only 21.39% when the concentration of administration reached 200 μM. It thus demonstrated activity in inhibiting SW1990 cells’ survival, suggesting potential in combating pancreatic cancer. Furthermore, this research offers a valuable concept for enhancing the mechanical properties and bioactivity of hydrogel materials through the utilization of a multi-component natural small molecule co-assembly approach. More importantly, this provides new ideas and methods for the treatment of pancreatic cancer and the analysis of traditional Chinese medicine compatibility theory.

Abstract Background Tolvaptan slows kidney function decline in patients with autosomal dominant polycystic kidney disease (ADPKD) who are at risk of rapid progression. Given that treatment requires commitment to long-term use, we evaluated the effects of tolvaptan discontinuation on the trajectory of ADPKD progression. Methods This was a post hoc analysis of pooled data from two clinical trials of tolvaptan (TEMPO 2:4 [NCT00413777] and TEMPO 3:4 [NCT00428948]), an extension trial (TEMPO 4:4 [NCT01214421]), and an observational study (OVERTURE [NCT01430494]) that enrolled patients from the other trials. Individual subject data were linked longitudinally across trials to construct analysis cohorts of subjects with a tolvaptan treatment duration > 180 days followed by an off-treatment observation period of > 180 days. For inclusion in Cohort 1, subjects were required have ≥ 2 outcome assessments during the tolvaptan treatment period and ≥ 2 assessments during the follow-up period. For Cohort 2, subjects were required to have ≥ 1 assessment during the tolvaptan treatment period and ≥ 1 assessment during the follow-up period. Outcomes were rates of change in estimated glomerular filtration rate (eGFR) and total kidney volume (TKV). Piecewise-mixed models compared changes in eGFR or TKV in the on-treatment and post-treatment periods. Results In the Cohort 1 eGFR population (n = 20), the annual rate of eGFR change (in mL/min/1.73 m2) was -3.18 on treatment and -4.33 post-treatment, a difference that was not significant (P = 0.16), whereas in Cohort 2 (n = 82), the difference between on treatment (-1.89) and post-treatment (-4.94) was significant (P

Tumor metastasis depends on the dynamic balance of the actomyosin cytoskeleton. As a key component of actomyosin filaments, non-muscle myosin-IIA disassembly contributes to tumor cell spreading and migration. However, its regulatory mechanism in tumor migration and invasion is poorly understood. Here, we found that oncoprotein hepatitis B X-interacting protein (HBXIP) blocked the myosin-IIA assemble state promoting breast cancer cell migration. Mechanistically, mass spectrometry analysis, co-immunoprecipitation assay and GST-pull down assay proved that HBXIP directly interacted with the assembly-competent domain (ACD) of non-muscle heavy chain myosin-IIA (NMHC-IIA). The interaction was enhanced by NMHC-IIA S1916 phosphorylation via HBXIP-recruited protein kinase PKCβII. Moreover, HBXIP induced the transcription of PRKCB, encoding PKCβII, by coactivating Sp1, and triggered PKCβII kinase activity. Interestingly, RNA sequencing and mouse metastasis model indicated that the anti-hyperlipidemic drug bezafibrate (BZF) suppressed breast cancer metastasis via inhibiting PKCβII-mediated NMHC-IIA phosphorylation in vitro and in vivo. We reveal a novel mechanism by which HBXIP promotes myosin-IIA disassembly via interacting and phosphorylating NMHC-IIA, and BZF can serve as an effective anti-metastatic drug in breast cancer.

Being overweight is a risk for various chronic diseases. Alginate, a soluble dietary fiber extracted from seaweed, has been linked to weight loss with unclear mechanisms. We conducted a double-blind, randomized trial in overweight or normal-weight adults to explore alginate’s weight loss effect and mechanism. Normal-weight or overweight participants were randomized to receive either alginate (15 g/day) or maltodextrin (13.8 g/day) for 14 weeks. Compared to maltodextrin (−0.91 kg; 95% CI, −1.91 to 0.10), alginate helped overweight subjects lose weight (−2.67 kg; 95% CI, −3.89 to −1.46) (P = 0.0017) after 14 weeks. In overweight subjects, alginate increased fecal-conjugated bile acids (taurocholate acid and taurochenodeoxycholic acid) and reduced bile acid-related bacteria (Bacteroides, Oscillibacter and Eubacterium). Our results indicate that alginate decreases weight and increases bile acid excretion in overweight subjects, related to gut microbiota alterations and inhibited intestinal bile acid absorption.

The prognosis for cancer patients has declined dramatically in recent years due to the challenges in treating malignant tumors. Tumor immunotherapy, which includes immune target inhibition and chimeric antigen receptor cell treatment, is currently evolving quickly. Among them, natural killer (NK) cells are gradually becoming another preferred cell immunotherapy after T cell immunotherapy due to their unique killing effects in innate and adaptive immunity. NK cell therapy has shown encouraging outcomes in clinical studies; however, there are still some problems, including limited efficacy in solid tumors, inadequate NK cell penetration, and expensive treatment expenses. Noteworthy benefits of nanomaterials include their chemical specificity, biocompatibility, and ease of manufacturing; these make them promising instruments for enhancing NK cell anti-tumor immune responses. Nanomaterials can promote NK cell homing and infiltration, participate in NK cell modification and non-invasive cell tracking and imaging modes, and greatly increase the effectiveness of NK cell immunotherapy. The introduction of NK cell-based immunotherapy research and a more detailed discussion of nanomaterial research in NK cell-based immunotherapy and molecular imaging will be the main topics of this review.

Mer and c-Met kinases, which are commonly overexpressed in various tumors, are ideal targets for the development of antitumor drugs. This study focuses on the design, synthesis, and evaluation of several 2-substituted aniline pyrimidine derivatives as highly potent dual inhibitors of Mer and c-Met kinases for effective tumor treatment. Compound 18c emerged as a standout candidate, demonstrating robust inhibitory activity against Mer and c-Met kinases, with IC50 values of 18.5 ± 2.3 nM and 33.6 ± 4.3 nM, respectively. Additionally, compound 18c displayed good antiproliferative activities on HepG2, MDA-MB-231, and HCT116 cancer cells, along with favorable safety profiles in hERG testing. Notably, it exhibited exceptional liver microsomal stability in vitro, with a half-life of 53.1 min in human liver microsome. Compound 18c also exhibited dose-dependent cytotoxicity and hindered migration of HCT116 cancer cells, as demonstrated in apoptosis and migration assays. These findings collectively suggest that compound 18c holds promise as a dual Mer/c-Met agent for cancer treatment.

Abstract Anoikis resistance is an essential prerequisite for tumor metastasis, but the underlying molecular mechanisms remain unknown. Herein, we report that the oncoprotein hepatitis B X-interacting protein (HBXIP) is prominently upregulated in breast cancer cells following ECM detachment. Altering HBXIP expression can impair the anchorage-independent growth ability of tumor cells. Mechanistically, HBXIP, which binds to Kelch-like ECH-associated protein 1 (Keap1) to activate nuclear factor E2-related factor 2 (Nrf2), contains a cis-acting antioxidant response element (ARE) in the gene promoter and is a target gene of Nrf2. The HBXIP/Nrf2 axis forms a reciprocal positive feedback loop that reinforces the expression and tumor-promoting actions of each protein. In response to ECM detachment, Nrf2 reduces reactive oxygen species (ROS) accumulation, protects the mitochondrial membrane potential and increases cellular ATP, GSH and NADPH levels to maintain breast cancer cell survival. Meanwhile, the reinforcement of HBXIP induced by Nrf2 inhibits JNK1 activation by inhibiting ubiquitin-mediated degradation of Prdx1, which also plays an essential role in promoting ECM-detached cell survival. Furthermore, a strong positive correlation was identified between HBXIP expression and Prdx1 expression in clinical breast cancer tissues and TCGA Pan-Cancer Atlas clinical data of breast invasive carcinoma based on the cBioPortal cancer genomics database. Co-expression of HBXIP and Prdx1 predicts a poor prognosis for breast cancer patients. Collectively, our findings reveal a significant mechanism by which the HBXIP/Nrf2 feedback loop contributes to anoikis resistance by maintaining redox homeostasis and inhibiting JNK1 activation and support the likely therapeutic value of the HBXIP/Nrf2 axis in breast cancer patients.

Abstract Vehicle re-identification (re-id) aims to solve the problems of matching and identifying the same vehicle under the scenes across multiple surveillance cameras. For public security and intelligent transportation system (ITS), it is extremely important to locate the target vehicle quickly and accurately in the massive vehicle database. However, re-id of the target vehicle is very challenging due to many factors, such as the orientation variations, illumination changes, occlusion, low resolution, rapid vehicle movement, and amounts of similar vehicle models. In order to resolve the difficulties and enhance the accuracy for vehicle re-id, in this work, we propose an improved multi-branch network in which global–local feature fusion, channel attention mechanism and weighted local feature are comprehensively combined. Firstly, the fusion of global and local features is adopted to obtain more information of the vehicle and enhance the learning ability of the model; Secondly, the channel attention module in the feature extraction branch is embedded to extract the personalized features of the targeting vehicle; Finally, the background and noise information on feature extraction is controlled by weighted local feature. The results of comprehensive experiments on the mainstream evaluation datasets including VeRi-776, VRIC, and VehicleID indicate that our method can effectively improve the accuracy of vehicle re-identification and is superior to the state-of-the-art methods.

Industrial added value is an important indicator to measure the operation of the real economy.In order to fully mine the value of power data in the current macroeconomic nowcasting, so as to serve the government policy making, the Bagging and Boosting algorithms in machine learning were applied to nowcast industrial added value based on electric power data as well as traditional statistical data.Firstly, traditional statistical data can significantly improve the forecasting effect of the ARIMA model.Secondly, the nowcasting ability of electric power data depends on the selection of electric power indicators, and the proper electric power index is helpful to predict industrial added value more timely and accurately.Thirdly, the prediction ability of electric power data to the industrial added value in the current period may be lower than that in the future, which means the power data is more likely to be used to predict ahead of time.

The process of recognizing the same vehicle in different scenes is called vehicle re-identification. However, due to the different locations of the surveillance cameras, there may be obstacles in the captured vehicle pictures and multiple viewpoints may make the same vehicle look different. In order to effectively reduce the interference of obstacle occlusion, multiple viewpoints, and other factors on vehicle re-identification, in this paper, we propose a multi-fine-grained feature extraction network. While retaining the global information of vehicles, we extract the finegrained features of vehicles precisely by segmenting the vehicle feature map. In addition, we introduce a new evaluation metric mean Inverse Negative Penalty (mINP) to evaluate the vehicle re-identification model more comprehensively. Our method achieves superior accuracy over the state-of-the-art methods on the challenging vehicle datasets: VeRi-776, VehicleID, and VRIC.

Abstract Background The estrogen receptor (ER)-positive breast cancer represents over 80% of all breast cancer cases. Even though adjuvant hormone therapy with tamoxifen (TMX) is saving lives of patients with ER-positive breast cancer, the acquired resistance to TMX anti-estrogen therapy is the main hurdle for successful TMX therapy. Here we address the mechanism for TMX resistance and explore the ways to eradicate TMX-resistant breast cancer in both in vitro and ex vivo experiments. Experimental design To identify compounds able to overcome TMX resistance, we used short-term and long-term viability assays in cancer cells in vitro and in patient samples in 3D ex vivo, analysis of gene expression profiles and cell line pharmacology database, shRNA screen, CRISPR-Cas9 genome editing, real-time PCR, immunofluorescent analysis, western blot, measurement of oxidative stress using flow cytometry, and thioredoxin reductase 1 enzymatic activity. Results Here, for the first time, we provide an ample evidence that a high level of the detoxifying enzyme SULT1A1 confers resistance to TMX therapy in both in vitro and ex vivo models and correlates with TMX resistance in metastatic samples in relapsed patients. Based on the data from different approaches, we identified three anticancer compounds, RITA (Reactivation of p53 and Induction of Tumor cell Apoptosis), aminoflavone (AF), and oncrasin-1 (ONC-1), whose tumor cell inhibition activity is dependent on SULT1A1. We discovered thioredoxin reductase 1 (TrxR1, encoded by TXNRD1) as a target of bio-activated RITA, AF, and ONC-1. SULT1A1 depletion prevented the inhibition of TrxR1, induction of oxidative stress, DNA damage signaling, and apoptosis triggered by the compounds. Notably, RITA efficiently suppressed TMX-unresponsive patient-derived breast cancer cells ex vivo. Conclusion We have identified a mechanism of resistance to TMX via hyperactivated SULT1A1, which renders selective vulnerability to anticancer compounds RITA, AF, and ONC-1, and provide a rationale for a new combination therapy to overcome TMX resistance in breast cancer patients. Our novel findings may provide a strategy to circumvent TMX resistance and suggest that this approach could be developed further for the benefit of relapsed breast cancer patients.

There may be close links among yeast protein (Saccharomyces cerevisiae) supplementation, gut microbiota and skeletal muscle aging. In present study, nineteen-month-old mice received yeast protein (1.0 g/kg/d) for three months by gavage. Histological and ultrasonographical improvements in muscle as well as an increase in myofiber size were observed after yeast protein supplementation. Moreover, yeast protein activated Akt/mTOR/4E-BP1 pathway and regulated myogenic regulatory factors (Myog, Myf4, Myf5, and Myod1) to promote muscle protein synthesis and muscle regeneration and differentiation. Meanwhile, alpha and beta diversities as well as the ratio of Firmicutes and Bacteroidetes were elevated after yeast protein supplementation. Changes in the abundance of gut microbiota after yeast protein supplementation were significantly correlated with glycan biosynthesis and metabolism, amino acid metabolism and lipid metabolism, closely involved in the process of muscle aging. Hence, yeast protein supplementation could contribute to ameliorating muscle aging, which may be associated with gut microbiota.

Deoxynivalenol (DON) is a kind of Fusarium toxin that can cause a variety of toxic effects. DON is mainly metabolized and detoxified by the liver. When the concentration of DON exceeds the metabolic capacity of the liver, it will trigger acute or chronic damage to the liver tissue. Previous studies demonstrated that bone marrow mesenchymal stem-cell-secreted exosomes (BMSC-exos) reduce liver injury. Therefore, we issue a hypothesis that in vitro-cultured rat BMSC-secreted exos could ameliorate liver damage after 2 mg/kg bw/day of DON exposure. In total, 144 lipids were identified in BMEC-exos, including high polyunsaturated fatty acid (PUFA) levels. BMSC-exos treatment alleviated liver pathological changes and decreased levels of alanine aminotransferase, aspartate aminotransferase, inflammatory factors interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and lipid peroxidation. Otherwise, low or high BMSC-exos treatment obviously changes DON-induced hepatic oxylipin patterns. According to the results from our correlation network analysis, Pearson correlation coefficient analysis, and hierarchical clustering analysis, the top 10% oxidized lipids can be classified into two categories: one that was positively correlated with copper–zinc superoxide dismutase (Cu/Zn SOD) and another that was positively correlated with liver injury indicators. Altogether, BMSC-exos administration maintained normal liver function and reduced oxidative damage in liver tissue. Moreover, it could also significantly change the oxylipin profiles under DON conditions.

Background: The previous studies demonstrated that there might be complex and close relationships among leucine supplementation, gut microbiota, and muscle health, which still needs further investigation.Aims: This study aimed to explore the associations of gut microbiota with muscle health after leucine intake.Methods: In this study, 19-month-old male C57BL/6j mice (n = 12/group) were supplemented with ultrapure water, low dose of leucine (500 mg/kg·d), and high dose of leucine (1,250 mg/kg·d) for 12 weeks by oral gavage. The mice fecal samples in each group before and after supplementation were collected for baseline and endpoint gut microbiota analysis by using 16S rDNA amplicon sequencing. Meanwhile, ultrasound measurement, H&E staining, myofiber cross-sectional area (CSA) measurement, and western blotting were performed in the quadriceps subsequently. The pyruvate levels were detected in feces.Results: Improvement in muscle of histology and ultrasonography were observed after both low and high dose of leucine supplementation. High dose of leucine supplementation could promote skeletal muscle health in aging mice via regulating AMPKα/SIRT1/PGC-1α. The richness and diversities of microbiota as well as enriched metabolic pathways were altered after leucine supplementation. Firmicutes-Bacteroidetes ratio was significantly decreased in high-leucine group. Moreover, pyruvate fermentation to propanoate I were negatively associated with differential species and the pyruvate levels were significantly increased in feces after high dose of leucine supplementation.Conclusions: Chronic high dose of leucine supplementation changed gut microbiota composition and increased pyruvate levels in the feces, which possibly provides a novel direction for promoting muscle health in aging mice.

Rapid recruitment of neutrophils to an inflamed site is one of the hallmarks of an effective host defense mechanism. The main pathway through which this happens is by the innate immune response. Neutrophils, which play an important part in innate immune defense, migrate into lungs through the modulation actions of chemokines to execute a variety of pro-inflammatory functions. Despite the importance of chemokines in host immunity, little has been discussed on their roles in host immunity. A holistic understanding of neutrophil recruitment, pattern recognition pathways, the roles of chemokines and the pathophysiological roles of neutrophils in host immunity may allow for new approaches in the treatment of infectious and inflammatory disease of the lung. Herein, this review aims at highlighting some of the developments in lung neutrophil-immunity by focusing on the functions and roles of CXC/CC chemokines and pattern recognition receptors in neutrophil immunity during pulmonary inflammations. The pathophysiological roles of neutrophils in COVID-19 and thromboembolism have also been summarized. We finally summarized various neutrophil biomarkers that can be utilized as prognostic molecules in pulmonary inflammations and discussed various neutrophil-targeted therapies for neutrophil-driven pulmonary inflammatory diseases.

Breast cancer has surpassed lung cancer as the most commonly diagnosed cancer in women worldwide. Some therapeutic drugs and approaches could cause side effects and weaken the immune system. The combination of conventional therapies and traditional Chinese medicine (TCM) significantly improves treatment efficacy in breast cancer. However, the chemical composition and underlying anti-tumor mechanisms of TCM still need to be investigated. The primary aim of this study is to provide unique insights to screen the natural components for breast cancer therapy using high-throughput transcriptome analysis. Differentially expressed genes were identified based on two conditions: single samples and groups were classified according to their pharmaceutical effect. Subsequently, the sample treated with E. cochinchinensis Lour. generated the most significant DEGs set, including 1,459 DEGs, 805 upregulated and 654 downregulated. Similarly, group 3 treatment contained the most DEGs (414 DEGs, 311 upregulated and 103 downregulated). KEGG pathway analyses showed five significant pathways associated with the inflammatory and metastasis processes in cancer, which include the TNF, IL−17, NF-kappa B, MAPK signaling pathways, and transcriptional misregulation in cancer. Samples were classified into 13 groups based on their pharmaceutical effects. The results of the KEGG pathway analyses remained consistent with signal samples; group 3 presents a high significance. A total of 21 genes were significantly regulated in these five pathways, interestingly, IL6, TNFAIP3, and BRIC3 were enriched on at least two pathways, seven genes (FOSL1, S100A9, CXCL12, ID2, PRS6KA3, AREG, and DUSP6) have been reported as the target biomarkers and even the diagnostic tools in cancer therapy. In addition, weighted correlation network analysis (WGCNA) was used to identify 18 modules. Among them, blue and thistle2 were the most relevant modules. A total of 26 hub genes in blue and thistle2 modules were identified as the hub genes. In conclusion, we screened out three new TCM (R. communis L., E. cochinchinensis Lour., and B. fruticosa) that have the potential to develop natural drugs for breast cancer therapy, and obtained the therapeutic targets.

Spatholobus suberectus Dunn (S. suberectus), has been widely used in traditional medicines plant source of the Leguminosae family. Its vine stem of which plays an important role in the prevention and treatment of various diseases because it contains various flavonoids. Comparative genome analysis suggested well-conserved genomic components and genetic collinearity between the genome of S. suberectus and other genera of Leguminosae such as Glycine max. We discovered two whole genome duplications (WGD) events in S. suberectus and G. max lineage underwent a WGD after speciation from S. suberectus. The determination of expansion and contractions of orthologous gene families revealed 1,001 expanded gene families and 3,649 contracted gene families in the S. suberectus lineage. Comparing to the model plants, many novel flavonoid biosynthesis-related genes were predicted in the genome of S. suberectus, and the expression patterns of these genes in the roots are similar to those in the stems [such as the isoflavone synthase (IFS) genes]. The expansion of IFS from a single copy in the Leguminosae ancestor to four copies in S. suberectus, will accelerate the biosynthesis of flavonoids. MYB genes are widely involved in plant flavonoid biosynthesis and the most abundant member of the TF family in S. suberectus. Activated retrotransponson positive regulates the accumulation of flavonoid in S. suberectus by introducing the cis-elements of tissue-specific expressed MYBs. Our study not only provides significant insight into the evolution of specific flavonoid biosynthetic pathways in S. suberectus, but also would facilitate the development of tools for enhancing bioactive productivity by metabolic engineering in microbes or by molecular breeding for alleviating resource shortage of S. suberectus.

In China, Hongyang Kiwifruit (Actinidia chinesis) is considered to be economically valuable because of its appealing red flesh, unique flavor and beneficial metabolites. A continuous 3-year field experiment was conducted in a private orchard in Dujiangyan, Sichuan Province, China, to determine the effect of different NPK ratios and organic fertilizer application on growth and yield. Approximately 162 vines were selected in a completely random design with nine fertilization treatments (PK; NK; NP; NPK; 2NPK; N2PK; NP2K; NPK + OM (organic matter)). Data on leaf number, leaf area, stem diameter, photosynthetic parameters, leaf N, P and K, chlorophyll content, yield and fruit quality were collected from individual kiwi vines for each treatment during the years 2011–2013. The application of inorganic fertilizer significantly increased fruit yield, leaf number, and leaf area and stem diameter increment as well as leaf photosynthetic rates and the concentrations of N, P and K in the leaves. However, the fruit yields were reduced in the unbalanced fertilizer treatments, NP, NK, and PK and in excess nutrient treatments, 2NPK, N2PK, NP2K, in contrast to the optimum NPK treatment. This was due to lower leaf photosynthetic rates and fewer photo-assimilates being available to the fruit. Moreover, the addition of organic fertilizer along with inorganic fertilizer (optimum NPK) did not increase plant growth, photosynthetic rates or fruit yields compared with only NPK fertilizer application, but significantly enhanced the fruit quality as a result of improving fruit chemical composition, such as soluble solids and reduced sugar.

China is moving toward the important goal of being a green and low-carbon country, and the current severity level of population aging is of particular concern to the government. Aging, renewable energy consumption, and technological progress are closely linked. In this research, a panel vector autoregressive (PVAR) model is employed to investigate the long-run equilibrium relationship between population aging, renewable energy consumption and agricultural green total factor productivity using panel data for 30 Chinese provinces (cities) from 2000 to 2019. The findings reveal that, in the long run, both population aging and renewable energy use have considerable positive impacts on agricultural green total factor productivity. In addition, in order to more intuitively understand the impact of population aging and renewable energy consumption on agricultural green total factor productivity, the analysis adopts the impulse response function and variance decomposition. The contributions of population aging and renewable energy consumption to agricultural green total factor productivity are 2.23% and 0.56%, respectively, when the lag period is chosen to be 15, which implies that population aging and renewable energy use will continuously contribute to agricultural green total factor productivity. The study results have significant theoretical implications for understanding China’s aging population structure and current renewable energy use. Given the above results, this study puts forward countermeasures and suggestions from four aspects: improving agricultural infrastructure, increasing agricultural technology investment, increasing the stock of agricultural human capital and strengthening international cooperation.

Deoxynivalenol (DON) is a kind of Fusarium toxin that can cause a variety of toxic effects. Oxidative stress and DNA damage play a critical role in the toxicity of DON. However, previous studies focused more on acute toxicity in vivo/vitro models and lacked subchronic toxicity study in vivo. The potentially harmful effect of DON given at doses comparable to the daily human consumption in target organs, especially the liver, which is the main detoxification organ of DON, is also still not fully understood. Otherwise, Heme Oxygenase-1 (HO-1) has also reduced cell damage under the DON condition according to our previous study. Therefore, we used a rodent model that mimicked daily human exposure to DON and further explored its mechanism of toxic effects on liver tissue and Hepa 1–6 cell line. We also used adeno-associated virus (AAV)-modified HO-1 expressing by tail vein injection and constructed lentivirus-Hepa 1–6 cell line for mimicking HO-1 protective ability under the DON condition. The main results showed that both 30 d and 90 d exposures of DON could cause low-grade inflammatory infiltration around hepatic centrilobular veins. The reactive oxygen species (ROS) and 8-hydroxy-2 deoxyguanosine (8-OHdG) increased during DON exposure, indicating oxidation stress and DNA damage. Significantly, AAV-mediated liver-specific overexpression of HO-1 reduced DON-induced liver damage and indirectly protected the abilities of antioxidant enzyme/DNA damage repair system, while AAV-mediated silence of HO-1 produced the opposite effect. In addition, we found that overexpression of HO-1 could enhance autophagy and combined it with an antioxidant enzyme/DNA damage repair system to inhibit DON-induced hepatocyte damage. Altogether, these data suggest that HO-1 reduces the oxidative stress and DNA damage caused by DON sub-chronic exposure through maintaining DNA repair, antioxidant activity, as well as autophagy.

Abstract Background Illicium verum is widely cultivated in southern China especially in Guangxi province. Its fruits has been traditionally used in Chinese medicine. In recent years, it has been the industrial source of shikimic acid. Usually the residues after extracting shikimic acid are treated as waste. Thus, the aim of this study was to optimize the extraction conditions of cellulase-ultrasonic assisted extraction technology for flavonoids from I. verum residues. Results The optimum extraction conditions with a maximum flavonoids yield of 14.76 % are as follows: the concentration of ethanol is 51.14 %, the liquid–solid ratio is 20.52 mL/g, the enzymatic hydrolysis pH is 5.303, the sonication time is 60 min, the enzyme solution temperature is kept at 45 °C, the amount of added enzyme is 70 mg/g, the enzymatic hydrolysis time is 2 h and the crushed mesh size is 0.355–0.85 mm. Conclusions The data indicate that the cellulase-ultrasonic assisted extraction technology has the potential be used for the industrial production of flavonoids from I. verum.

Twelve phenolics, including the three new compounds balanophonin C (1), balanophonin D (2), balanophonin E (3), were isolated from the seeds of Lithocarpus pachylepis. Their structures were elucidated by various spectroscopic techniques (UV, IR, MS, 1D and 2D NMR). Compounds 1–9 were evaluated for their anti-inflammatory activities on lipopolysaccharide (LPS)-induced nitric oxide (NO) production in RAW 264.7 and showed moderate inhibitory activities, with IC50 values ranging from 10.9 to 34.7 μM.

Localization is an essential service in most of the wireless sensor network (WSN) applications. This paper focuses on utilizing the moving passive event to achieve the network localizability in an initially nonlocalizable network. The hybrid TDOA and distance measurement is firstly used in the network localizability. We propose the sufficient conditions in terms of node localizability and network localizability, respectively. Besides, a more promising TDOA estimation approach, which is approximately synchronization-free, is proposed to well support our localization approach. We design a corresponding algorithm in distributed manner for the implementation of our approach. Compared with the current works, our approach requires no extra hardware cost and any adjustment of the current topology of the network and hence is more feasible in practice. We evaluate the performance of our approach via extensive simulations on a one-thousand-node network. Simulation results show that our TDOA estimation approach achieves the accuracy of 0.1 milliseconds. More than 90% nodes can be localized within 0.04 r , where r denotes the ranging radius of a sensor.

Purpose. To estimate the US prevalence of Peyronie's disease (PD) from patient-reported data and to identify diagnosis and treatment patterns. Methods. 11,420 US males ≥18 years old completed a brief web-based survey regarding the presence of PD, past treatments, and penile symptoms (Phase 1). Phase 1 respondents with PD diagnosis, history of treatment, or PD-related symptoms then completed a disease-specific survey (Phase 2). Results. Estimated prevalence of PD ranged from 0.5% (diagnosis of PD) to 13% (diagnosis, treatment, or penile symptoms). Thirty-six percent of Phase 2 participants reported that penile symptoms interfered with sexual activities. Of participants who sought treatment for penile symptoms (𝑛=128), 73% initially saw a primary care physician, 74% did not receive treatment from their first doctor, and 92% were not diagnosed with PD. Conclusions. PD may be underdiagnosed/undertreated in the US. Improved awareness is needed of PD symptoms and treatment options among health care professionals.