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Abstract. Background:. Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors. Methods:. The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25–70 years old from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020. Results:. The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy. Conclusions:. We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.

Abstract Background TCbHP (taxane + carboplatin + trastuzumab + pertuzumab) is the preferred neoadjuvant therapy regimen for human epidermal growth factor receptor 2 (HER2)-positive breast cancer. However, no consensus exists regarding whether specific populations may be exempt from carboplatin, allowing for de-escalation to the THP (taxane + trastuzumab + pertuzumab) regimen. Additionally, the optimal number of cycles for neoadjuvant THP remains unclear. We compared the efficacy and safety of neoadjuvant TCbHP and THP regimens, providing clinicians with a nuanced perspective to guide their treatment regimen selection. Methods This multicenter real-world study included patients with HER2-positive breast cancer undergoing neoadjuvant TCbHP or THP between March 2019 and February 2023. Efficacy was assessed through the pathological complete response (pCR) rate, while safety was evaluated through monitoring adverse events. Results Among 220 patients, 103 received 6 cycles of TCbHP (TCbHP×6), 83 received 6 cycles of THP (THP×6), and 34 received 4 cycles of THP (THP×4). The TCbHP×6 cohort exhibited a 66% pCR rate compared with 53% in the THP×6 cohort (P = 0.072). Subgroup analysis revealed that in patients aged ≤ 50 years, those with hormone receptor (HR)-negative status, and those with clinical stage T2, the pCR rate of the TCbHP×6 regimen was significantly higher than the THP×6 regimen (P 50, ≤60 years with HR-negative status or clinical stage T2-4. For patients in compromised general condition or lacking the specified indications, the THP×6 regimen emerges as a lower-toxicity alternative with satisfactory efficacy. To ensure treatment efficacy, a minimum of 6 cycles of neoadjuvant THP is required.

Objectives: To assess the efficacy and safety of rifampicin-based triple therapy (rifampicin, isoniazid, and ethambutol) for treating NPM. Methods: This single-center, single-arm, prospective clinical trial was conducted at the Second Hospital of Shandong University (Jinan, China). Patients with pathologically diagnosed granulomatous lobular mastitis and periductal mastitis received triple drugs, i.e., rifampicin (450 mg/day), isoniazid (300 mg/day), and ethambutol (15 mg/kg/day), until complete response or the investigator decided to discontinue treatment. The primary endpoint was the complete response rate (CRR) assessed by the investigator. The secondary endpoints included the overall remission rate (ORR), recurrence rate (RR), and safety. Results: A total of 218 patients were enrolled in the study between January 1, 2013 and October 31, 2020. With a median follow-up time of 48 months, the CRR and the ORR were 78.44% and 94.04%, respectively. While 13 patients (5.96%) demonstrated no response and 19 relapsed (8.72%). Adverse events (AEs) were not common. The most common AEs during treatment were liver dysfunction (1.83%), gastrointestinal reactions (1.83%), fatigue (1.83%), erythema (1.38%), and menstrual disorders (0.92%). Conclusion: Rifampicin, isoniazid, and ethambutol demonstrated promising response rates with acceptable safety profiles in patients with NPM. Further confirmatory trial is warranted in the future. Trial registration: The study was approved by the Ethics Committee of the Second Hospital of Shandong University and retrospectively registered at the China Clinical Trial Registration Center (registration number: ChiCTR2100049591).

Abstract The sediment mixed layer (SML) in the deep ocean is an important interface with a rich diversity of benthic organisms. With increasing ocean mineral exploration, and eventual mining, the effect of sediment mixing on deep ocean ecosystems has raised considerable concern. We evaluate the distribution patterns and driving factors of SML depth in deep ocean nodule fields using naturally occurring 210Pb–226Ra isotopes. Results show that average SML depth has increased in Mn‐nodule fields since the end of the last century. SML processes are associated with significant desorption of 226Ra from sediments, resulting in a departure from radioactive equilibrium. By estimating possible driving factors, we conclude that anthropogenic exploration activities, rather than natural physical and/or biological drivers, are the most likely mechanism for intensified sediment mixing. 210Pb–226Ra disequilibria may be a potential tracer for quantifying the impact of human exploration on deep‐ocean sediment mixing and associated biological and geochemical effects.

Growing African Indigenous Vegetables (AIVs) is an innovative way to address poverty and malnutrition problems in Zambia. Farmers’ bargaining power plays an important role in increasing AIV production and farmers’ income. Based on 300 responses from Zambian AIV farmers, we defined AIV farmers’ bargaining power and analyzed its benefits to farmers and the AIV industry. We used the ordered logistic regression model (OLRM) to analyze the influence of several factors that contribute to farmers’ bargaining power, and then used the interpretative structural modeling (ISM) to analyze the relationship and hierarchical structure between the effects. Four key results and innovations arose from the analysis of the data. First, we defined farmers’ bargaining power through their self-reported bargaining power. Second, we found that the respondents’ bargaining power was significantly influenced by seven variables: age, gender, education, main trading partners, awareness of AIV prices, and distance to the market from the farm. Third, the main trading partners and awareness of AIV prices are surface direct factors, gender, education and distance to the market from the farm are middle indirect relationships, and age, belong to any community are deep root factors. Last, farmers’ bargaining power can be improved through education, especially women’s education level, strengthening farmers’ organization construction, altering some of the farmers’ trading methods, and developing infrastructure. Overall, we found that bargaining power has played an important role in obtaining higher prices, getting faster payment, getting more income from AIV sales, and expanding AIV planting areas for farmers.

Abstract Background Neoadjuvant chemotherapy (NAC) has become a standard treatment strategy for breast cancer (BC). However, owing to the high heterogeneity of these tumors, it is unclear which patient population most likely benefit from NAC. Multi-omics offer an improved approach to uncovering genomic and transcriptomic changes before and after NAC in BC and to identifying molecular features associated with NAC sensitivity. Methods We performed whole-exome and RNA sequencing on 233 samples (including matched pre- and post-treatment tumors) from 50 BC patients with rigorously defined responses to NAC and analyzed changes in the multi-omics landscape. Molecular features associated with NAC response were identified and validated in a larger internal, and two external validation cohorts, as well as in vitro experiments. Results The most frequently altered genes were TP53, TTN, and MUC16 in both pre- and post-treatment tumors. In comparison with pre-treatment tumors, there was a significant decrease in C > A transversion mutations in post-treatment tumors (P = 0.020). NAC significantly decreased the mutation rate (P = 0.006) of the DNA repair pathway and gene expression levels (FDR = 0.007) in this pathway. NAC also significantly changed the expression level of immune checkpoint genes and the abundance of tumor-infiltrating immune and stroma cells, including B cells, activated dendritic cells, γδT cells, M2 macrophages and endothelial cells. Furthermore, there was a higher rate of C > T substitutions in NAC nonresponsive tumors than responsive ones, especially when the substitution site was flanked by C and G. Importantly, there was a unique amplified region at 8p11.23 (containing ADGRA2 and ADRB3) and a deleted region at 3p13 (harboring FOXP1) in NAC nonresponsive and responsive tumors, respectively. Particularly, the CDKAL1 missense variant P409L (p.Pro409Leu, c.1226C > T) decreased BC cell sensitivity to docetaxel, and ADGRA2 or ADRB3 gene amplifications were associated with worse NAC response and poor prognosis in BC patients. Conclusions Our study has revealed genomic and transcriptomic landscape changes following NAC in BC, and identified novel biomarkers (CDKAL1 P409L , ADGRA2 and ADRB3) underlying chemotherapy resistance and poor prognosis, which could guide the development of personalized treatments for BC.

Since 2008, annual outbreaks of green tides in the Yellow Sea have had severe impacts on tourism, fisheries, water sports, and marine ecology, necessitating effective interception and removal measures. Satellite remote sensing has emerged as a promising tool for monitoring large-scale green tides due to its wide coverage and instantaneous imaging capabilities. Additionally, drift prediction techniques can forecast the location of future green tides based on remote sensing monitoring information. This monitoring and prediction information is crucial for developing an effective plan to intercept and remove green tides. One key aspect of this monitoring information is the green tide distribution envelope, which can be generated automatically and quickly using buffer analysis methods. However, this method produces a large number of envelope vertices, resulting in significant computational burden during prediction calculations. To address this issue, this paper proposes a simplification method based on azimuth difference and side length (SM-ADSL). Compared to the isometric and Douglas–Peucker methods with the same simplification rate, SM-ADSL exhibits better performance in preserving shape and area. The simplified distribution envelope can shorten prediction times and enhance the efficiency of emergency decision-making for green tide disasters.

SBAS-InSAR technology is effective in obtaining surface deformation information and is widely used in monitoring landslides and mining subsidence. However, SBAS-InSAR technology is susceptible to various errors, including atmospheric, orbital, and phase unwrapping errors. These multiple errors pose significant challenges to precise deformation monitoring over large areas. This paper examines the spatial characteristics of these errors and introduces a spatially constrained SBAS-InSAR method, termed SSBAS-InSAR, which enhances the accuracy of wide-area surface deformation monitoring. The method employs multiple stable ground points to create a control network that limits the propagation of multiple types of errors in the interferometric unwrapped data, thereby reducing the impact of long-wavelength signals on local deformation measurements. The proposed method was applied to Sentinel-1 data from parts of Jining, China. The results indicate that, compared to the traditional SBAS-InSAR method, the SSBAS-InSAR method significantly reduced phase closure errors, deformation rate standard deviations, and phase residues, improved temporal coherence, and provided a clearer representation of deformation in time-series curves. This is crucial for studying surface deformation trends and patterns and for preventing related disasters.

PurposeThis study aimed to investigate the factors associated with pathologic node-negativity (ypN0) in patients who received neoadjuvant chemotherapy (NAC) to develop and validate an accurate prediction nomogram.MethodsThe CSBrS-012 study (2010–2020) included female patients with primary breast cancer treated with NAC followed by breast and axillary surgery in 20 hospitals across China. In the present study, 7,711 eligible patients were included, comprising 6,428 patients in the primary cohort from 15 hospitals and 1,283 patients in the external validation cohort from five hospitals. The hospitals were randomly assigned. The primary cohort was randomized at a 3:1 ratio and divided into a training set and an internal validation set. Univariate and multivariate logistic regression analyses were performed on the training set, after which a nomogram was constructed and validated both internally and externally.ResultsIn total, 3,560 patients (46.2%) achieved ypN0, and 1,558 patients (20.3%) achieved pathologic complete response in the breast (bpCR). A nomogram was constructed based on the clinical nodal stage before NAC (cN), ER, PR, HER2, Ki67, NAC treatment cycle, and bpCR, which were independently associated with ypN0. The area under the receiver operating characteristic curve (AUC) for the training set was 0.80. The internal and external validation demonstrated good discrimination, with AUCs of 0.79 and 0.76, respectively.ConclusionWe present a real-world study based on nationwide large-sample data that can be used to effectively screen for ypN0 to provide better advice for the management of residual axillary disease in breast cancer patients undergoing NAC.

The digital development in rural areas has become an important driving force for promoting green production in agriculture. But the lack of digital skills among farmers remains a problem. The main reason why farmers cannot master digital skills well is their lack of digital literacy, which leads to market information asymmetry and the inability to truly distinguish the difference between green production and traditional production. Based on this, this article uses field research methods to collect data from 1,116 farmers in China, calculates agricultural green production efficiency using the SBM model, and empirically tests the relationship between farmers’ digital literacy and green production efficiency in agriculture. The results showed that digital literacy has a significant promoting effect on agricultural green production efficiency. Secondly, it was found that digital literacy can effectively enhance farmers’ cognition of green agricultural products and green production technology adoption. Among them, the effect of cognition of green agricultural products is reflected in farmers’ self-cognition and market cognition. The green production technology adoption is reflected in the breadth and depth of technology adoption. Third, we discuss the effect of different dimensions of digital literacy on agricultural green production efficiency. The effect of the digital literacy on the production efficiency of the five typical green technologies used by farmers is further discussed. Although there are certain differences, overall, they all have a significant promoting effect. It is necessary to comprehensively improve farmers’ digital literacy, bridge the digital divide and promote the green transformation of agricultural production.

With the public land mobile communication network transitioning from the 5G era where information flows freely to the 6G era where everything is interconnected, satellite networks have become a hot development topic all around the world.At the same time, with the improvement of satellite on-board computing capabilities and the integration of computing and satellite networks, cloud network integration has become a new development trend.On the basis of a brief introduction to the current development status of satellite networks and satellite computing, the development roadmap of satellite network development architecture was summarized.Then, a satellite network architecture based on cloud-network integration (i.e.satellite cloud network) was proposed, and the advantages of satellite cloud network architecture from five aspects: computing driven communication enhancement, computing driven network enhancement were analyzed, computing driven service enhancement, computing driven control enhancement, and computing driven management enhancement.

Lutein is widely used in medicine, health care, and food processing due to its antioxidant effects; however, it is difficult for the traditional extraction of lutein using marigolds to meet the increasing market demand for lutein. To achieve high-efficiency lutein production, we investigated the effects of different conditions on the biomass accumulation and lutein yield of Chlorella vulgaris. The optimized cultivation conditions include mixotrophic cultivation using sodium nitrate as a nitrogen source, maintaining a total-organic-carbon-to-total-nitrogen ratio of 12:1, a total-nitrogen-to-total-phosphorus ratio of 10:1, and lighting duration of 24 h. The results of the study indicated that under these specific conditions, Chlorella vulgaris attained a final biomass concentration, biomass productivity, and growth yield of 6.08 g·L−1, 1.00 g·L−1·d−1, and 1.67 g biomass/g TOC, respectively. Additionally, the concentrations of total chlorophyll, carotenoid, lutein, and protein reached 139.20 mg·L−1, 31.87 mg·L−1, 15.02 mg·L−1, and 2.17 g·L−1, respectively, and the content of lutein reached 2.47 mg·g−1. This study supplies a theoretical basis for the industrial application of lutein production using Chlorella vulgaris.

Abstract Submarine groundwater discharge (SGD) can have a profound influence on marine environments and elemental biogeochemical cycles in coastal waters. We have explored the feasibility of using Ba/Ca ratios of benthic foraminiferal shells as a proxy of SGD. Dissolved barium (DBa) displayed enrichment behavior in bottom waters indicating that SGD is a major DBa source in the Changjiang (Yangtze) Estuary. Foraminifera that lived in bottom waters with elevated 222Rn activities (high SGD) showed a larger range of Ba/Ca ratios than those that lived under low bottom water 222Rn activities (low SGD). Our findings support the view that benthic foraminiferal Ba/Ca ratios could be treated as a qualitative proxy of SGD. We propose that in areas where SGD is the main source of DBa, foraminiferal Ba/Ca ratios could be applied for long‐term historical SGD records.

Aim:This study aims to identify suitable candidates for axillary sentinel lymph node biopsy (SLNB) or targeted axillary dissection (TAD) among clinical N2 (cN2) triple-negative (TN) or HER2 positive (HER2+）breast cancer patients following neoadjuvant therapy（NAT）.Background: Despite the substantial axillary burden in cN2 breast cancer patients, high pathological response rates can be achieved with NAT in TN or HER2+ subtypes, thus enabling potential downstaging of axillary surgery.Methods: A retrospective analysis was conducted on data from the CSBrS-012 study, screening 709 patients with initial cN2, either HER2+ or TN subtype, from January 1, 2010 to December 31, 2020. The correlation between axillary pathologic complete response (pCR) (yPN0) and breast pCR was examined.Results: Among the 177 cN2 patients who achieved breast pCR through NAT, 138 (78.0 %) also achieved axillary pCR. However, in the 532 initial clinical N2 patients who did not achieve breast pCR, residual axillary lymph node metastasis persisted in 77.4 % (412/532) of cases. The relative risk of residual axillary lymph node metastasis in patients who did not achieve breast pCR was 12.4 (8.1–19.1), compared to those who did achieve breast pCR, P

AbstractBackground Breast abscess is a common and intractable clinical condition and the use of needle aspiration (NA) or incision and drainage (ID) in treatment is controversial. This meta-analysis aimed to systematically compare the clinical effectiveness of NA and ID in treating breast abscesses.Methods The Web of Science, ScienceDirect, PubMed, Cochrane Library, EMBASE, China National Knowledge Infrastructure, and Wanfang Data were searched for randomized controlled trials (RCTs) published from inception to January 7, 2022. The ROB-2 tool assessed risk of bias; the GRADE methodology rated certainty in outcomes; and Stata 16.0 performed data analyses.Results Nine RCTs were included, including 703 patients. The results showed there was no significant difference in cure rate between the two groups (relative risk [RR] = 0.96, 95% confidence interval [CI] [0.86, 1.07]; p = .469), and after subgroup analysis, we found that it was not related to the use of ultrasound guidance or not. There was no significant difference in the recurrence rate (RR = 0.68, 95% CI [0.35, 1.30]; p = .241). Furthermore, the NA group was associated with shorter healing time (weighted mean differences = −11.02, 95% CI [−15.14, −6.90]; p

ABSTRACTNon-caloric artificial sweeteners have been widely permitted as table sugar substitutes with high intensities of sweetness. They can pass through the intestinal tract without significant metabolization and frequently encounter the gut microbiome, which is composed of diverse bacterial species and is a pool of antibiotic resistance genes (ARGs). However, little is known about whether these sweeteners could accelerate the spread of ARGs in the gut microbiome. Here, we established an in vitro conjugation model by using Escherichia coli that carries chromosome-inserted Tn7 lacIq-pLpp-mCherry and plasmid-encoded gfpmut3b gene as the donor and murine fecal bacteria as the recipient. We found that four commonly used artificial sweeteners (saccharin, sucralose, aspartame, and acesulfame potassium) can increase reactive oxygen species (ROS) production and promote plasmid-mediated conjugative transfer to the gut microbiome. Cell sorting and 16S rRNA gene amplicon sequencing analysis of fecal samples reveal that the tested sweeteners can promote the broad-host-range plasmid permissiveness to both Gram-negative and Gram-positive gut bacteria. The increased plasmid permissiveness was also validated with a human pathogen Klebsiella pneumoniae. Collectively, our study demonstrates that non-caloric artificial sweeteners can induce oxidative stress and boost the plasmid-mediated conjugative transfer of ARGs among the gut microbiota and a human pathogen. Considering the soaring consumption of these sweeteners and the abundance of mobile ARGs in the human gut, our results highlight the necessity of performing a thorough risk assessment of antibiotic resistance associated with the usage of artificial sweeteners as food additives.

Space electronic system is the ＆quot;brain＆quot; of aerospace engineering models and the core fi eld of competitive development of major countries around the world.As the most core device in space electronic system, space processor directly aff ects the performance, reliability and safety of aerospace models.On the basis of brief introduced of space electronic systems, fi rstly, the development status of foreign space processors was analyzed, and then the development roadmap of space processors such as SPARC, PowerPC, ARM, RISC V, etc were combed and formed.The development process was summarized into three stages:initial stage, development stage and new stage, considered architecture and performance parameters.Finally, the development trend of space processors in the future was summarized as ＆quot;fi ve modernizations＆quot;: micro system, commercialization, intelligent, ecological and cloud enabled.

Methylmercury is a neurotoxic compound that can enter rice fields through rainfall or irrigation with contaminated wastewater, and then contaminate the human food chain through the consumption of rice. Flooded paddy soil has a porous structure that facilitates air exchange with the atmosphere, but the presence of trace amounts of oxygen in flooded rice field soil and its impact on microbial-mediated formation of methylmercury is still unclear. We compared the microbial communities and their functions in oxygen-depleted and oxygen-limited paddy soil. We discovered that oxygen-limited paddy soil had higher methylmercury concentration, which was strongly correlated with soil properties and methylation potential. Compared with oxygen-depleted soil, oxygen-limited soil altered the microbial composition based on 16 S rRNA sequences, but not based on hgcA sequences. Moreover, oxygen-limited soil enhanced microbial activity significantly, increasing the abundance of more than half of the KEGG pathways, especially the metabolic pathways that might be involved in methylation. Our study unveils how microbial communities influence methylmercury formation in oxygen-limited paddy soil. Environmental implications: This study examined how low oxygen input affects microbial-induced MeHg formation in anaerobic paddy soil. We found that oxygen-limited soil produced more MeHg than oxygen-depleted soil. Oxygen input altered the microbial community structure of 16 S rRNA sequencing in anaerobic paddy soil, but had little impact on the hgcA sequencing community structure. Microbial activity and metabolic functions related to MeHg formation were also higher in oxygen-limited paddy soil. We suggest that oxygen may not be a limiting factor for Hg methylators, and that insufficient oxygen input in flooded paddy soil increases the risk of human exposure to MeHg from rice consumption.

Abstract Background Microalgae protein is considered as a sustainable alternative to animal protein in the future. Using waste for microalgal culture can upgrade low-value raw materials into high-value products, helping to offset the cost of microalgal protein production. In this study we explored the feasibility of using microalgae heterotrophic fermentation to convert broken rice hydrolysate (BRH) into protein. Results The results showed that the increase of BRH supplemental ratio was beneficial to the increase of biomass production but not beneficial to the increase of intracellular protein content. To further improve protein production, the effect of C/N ratio on intracellular protein accumulation was studied. It was found that low C/N ratio was beneficial to the synthesis of glutamate in microalgae cells, which in turn promoted the anabolism of other amino acids and further the protein. When the C/N ratio was 12:1, the biomass productivity and protein content could reach a higher level, which were 0.90 g/L/day and 61.56%, respectively. The obtained Chlorella vulgaris biomass was rich in essential amino acids (41.80%), the essential amino acid index was as high as 89.07, and the lysine content could reach up to 4.05 g/100 g. Conclusions This study provides a theoretical basis and guidance for using Chlorella vulgaris as an industrial fermentation platform to convert broken rice into products with high nutritional value.

Abstract Background Breast cancer (BC) is one of the most prevalent cancers worldwide but its etiology remains unclear. Obesity is recognized as a risk factor for BC, and many obesity-related genes may be involved in its occurrence and development. Research assessing the complex genetic mechanisms of BC should not only consider the effect of a single gene on the disease, but also focus on the interaction between genes. This study sought to construct a gene interaction network to identify potential pathogenic BC genes. Methods The study included 953 BC patients and 963 control individuals. Chi-square analysis was used to assess the correlation between demographic characteristics and BC. The joint density-based non-parametric differential interaction network analysis and classification (JDINAC) was used to build a BC gene interaction network using single nucleotide polymorphisms (SNP). The odds ratio (OR) and 95% confidence interval (95% CI) of hub gene SNPs were evaluated using a logistic regression model. To assess reliability, the hub genes were quantified by edgeR program using BC RNA-seq data from The Cancer Genome Atlas (TCGA) and identical edges were verified by logistic regression using UK Biobank datasets. Go and KEGG enrichment analysis were used to explore the biological functions of interactive genes. Results Body mass index (BMI) and menopause are important risk factors for BC. After adjusting for potential confounding factors, the BC gene interaction network was identified using JDINAC. LEP, LEPR, XRCC6, and RETN were identified as hub genes and both hub genes and edges were verified. LEPR genetic polymorphisms (rs1137101 and rs4655555) were also significantly associated with BC. Enrichment analysis showed that the identified genes were mainly involved in energy regulation and fat-related signaling pathways. Conclusion We explored the interaction network of genes derived from SNP data in BC progression. Gene interaction networks provide new insight into the underlying mechanisms of BC.

The authors map the global distribution of the mixed layer in coastal ocean sediments, based on a neural network model. These observations reveal that mixing can accelerate organic matter degradation and reduce carbon storage in the coastal ocean.

Abstract Background Horizontal gene transfer (HGT) plays a critical role in the spread of antibiotic resistance and the evolutionary shaping of bacterial communities. Conjugation is the most well characterized pathway for the spread of antibiotic resistance, compared to transformation and transduction. While antibiotics have been found to induce HGT, it remains unknown whether non-antibiotic pharmaceuticals can facilitate conjugation at a microbial community-wide level. Results In this study, we demonstrate that several commonly consumed non-antibiotic pharmaceuticals (including carbamazepine, ibuprofen, naproxen and propranolol), at environmentally relevant concentrations (0.5 mg/L), can promote the conjugative transfer of IncP1-α plasmid-borne antibiotic resistance across entire microbial communities. The over-generation of reactive oxygen species in response to these non-antibiotic pharmaceuticals may contribute to the enhanced conjugation ratios. Cell sorting and 16S rRNA gene amplicon sequencing analyses indicated that non-antibiotic pharmaceuticals modulate transconjugant microbial communities at both phylum and genus levels. Moreover, microbial uptake ability of the IncP1-α plasmid was also upregulated under non-antibiotic pharmaceutical exposure. Several opportunistic pathogens, such as Acinetobacter and Legionella, were more likely to acquire the plasmid conferring multidrug resistance. Conclusions Considering the high possibility of co-occurrence of pathogenic bacteria, conjugative IncP1-α plasmids and non-antibiotic pharmaceuticals in various environments (e.g., activated sludge systems), our findings illustrate the potential risk associated with increased dissemination of antibiotic resistance promoted by non-antibiotic pharmaceuticals in complex environmental settings. Video abstract

With the continuous expansion of human activities from the terrestrial to the ocean and space, the countries all over the world have advanced the layout of space-ground integrated information network to provide seamless coverage and ubiquitous connection services.Space-ground integrated information network is the deep integration of space network and terrestrial network, not the expansion of terrestrial network to space environment.Starting from the perspective of integration, firstly the development status, existing problems and challenges of the internet, public land mobile network (PLMN), and space networks were sorted out.Secondly, the research status of the space-ground integrated information network architecture and the development trend of the new network architecture such as cloudification and intelligence was summarized.Thirdly, a communication-networking-computing integrated space-ground integrated information network architecture was proposed from different dimensions: physical architecture, functional architecture (including the integrated communication system, the integrated network system and the integrated information system), physical-functional architecture mapping problem.Finally, the network architecture optimization problem was modeled as a multi-objective optimization problem.It was expected to provide valuable suggestions and references for the research, construction and standardization of space-ground integrated information network.

The lack of fall data for the elderly is a challenging problem in the fall detection community. To date, the fall and activities of daily life simulated by young people have been used in most studies to train and test fall detection algorithms. However, there are differences in movement patterns between young and elderly individuals due to bone aging, which leads to the degradation of the algorithm performance in the elderly population. To solve the above issue, this paper proposes a fall detection algorithm combining Federated Learning and Extreme Learning Machine (Fed-ELM). First, the online extreme learning machine can use a small amount of misclassified user data to update the parameters so that its performance is improved for individual users. Then, Federated Learning is applied to share data information among different users without involving user privacy. In this way, the generalizability of the fall detection algorithm is improved. The performance of the proposed algorithm in different age groups is analyzed by experiments. For young people, the accuracy, sensitivity and specificity reach 96.96%, 94.50% and 99.29%, respectively, and the accuracy on each individual is more than 94%. For elderly individuals, the accuracy, sensitivity and specificity reach 99.07%, 96.00% and 98.33%, respectively, and the accuracy of each individual is more than 96%.

Background: In the era of targeted therapy, whether patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer are exempted from anthracycline usage in the neoadjuvant setting is controversial. Objectives: Our objective was to retrospectively analyze the differences in pathological complete remission (pCR) rates between the anthracycline group and the nonanthracycline group. Design: The CSBrS-012 study (2010–2020) included female primary breast cancer patients with neoadjuvant chemotherapy (NAC) who underwent standard breast and axillary surgery post-NAC. Methods: A logistic proportional hazard model was applied to estimate the association of covariates with pCR. Propensity score matching (PSM) was performed to balance the differences in baseline characteristics, and subgroup analyses were performed using the Cochran–Mantel–Haenszel test. Results: A total of 2507 patients were enrolled: the anthracycline group ( n = 1581, 63%) and the nonanthracycline group ( n = 926, 37%). A pCR was recorded in 17.1% (271/1581) of patients in the anthracycline group and in 29.3% (271/926) in the nonanthracycline group, and the difference in the pCR rate between the two groups was statistically significant [odds ratio (OR) = 2.00, 95% confidence interval (CI) (1.65–2.43); p

IntroductionDenitrification and anammox play the crucial role for N removal processes in coastal ecosystems, but the ecological distribution of denitrifying and anammox microorganisms and their N removal rates in the Yangtze Estuary and its adjacent sea are required in-depth analysis.MethodsHere, we utilized high-throughput sequencing, qPCR, and 15N isotope to reveal the community structure and function of denitrifying and anammox microorganisms in the surface sediments from Yangtze Estuary and adjacent sea.ResultsThe results suggested that the gene abundances of nirS and nirK for denitrifiers were higher than AMX 16S rRNA for anammox bacteria. The genera composition of nirS- and nirK-encoding denitrifiers communities showed different distribution patterns. Furthermore, Candidatus Anammoximicrobium dominated the anammox community, implying the anammox oxidation capacity of the other genera should be noted in marine sediments.DiscussionCompared to anammox, denitrification was the dominant contributor of nitrogen removal process and contributed 73.5% on average. The sediment Chla was the key factor to regulate denitrification and anammox rates, indicating the fresh organic matter was more labile and easier to be utilized by NOx− removal processes.

At present, the phenomenon of excessive pesticide residues in vegetables is prominent, causing widespread concern among all sectors of society. Excavate the influencing factors in the farmers themselves, government, market and society that affect vegetable farmers' green pesticide application behavior, clarify the influence mechanism of influencing factors on vegetable farmers' green pesticide application behavior. The study includes two parts: First, Grounded theory is used to construct a conceptual model that illustrates vegetable farmers' green pesticide application behavior. The second part applies the structural equation modeling to verify the research hypotheses, and reveals various factors in vegetable farmers' green pesticide application behavior (GB). The Results: Behavioral attitude (BA) and behavioral feedback perception (BP) are precursor variables that determine vegetable farmers' green pesticide application motivation (GM), and thus affect vegetable farmers' GB. Government supervision and regulation (GR), and market adjustment guidance (MG) are external factors that regulate the strength of the relationship between GM and GB. It is necessary to further strengthen the reference and normative role of society in vegetable farmers' GB, and provide a driving strategy for vegetable farmers' GB. Thus, it can better improve the quality of pesticide application and ensure vegetable safety.

Agricultural technology extension and social networks are the essential components of formal and informal institutions, respectively, and their influence on agricultural production has been the focus of academics. This article takes conservation tillage technology as an example, based on simple random unduplicated sampling, and uses survey data of 781 farmers in Heilongjiang, Henan, Shandong, and Shanxi provinces of China. This article empirically tests the interaction effects and heterogeneity of agricultural technology extension and social networks on farmers’ adoption of conservation tillage technology and analyzes their substitution effect or complementary effect. The results showed the following: (1) From a single dimension, both agricultural technology extension and social networks can significantly promote farmers’ adoption of conservation tillage technology, and the promotion effect of agricultural technology extension is greater. The average probability of farmers who accept agricultural technology extension and social networks adopting conservation tillage technology increases by 36.49% and 7.09%, respectively. (2) There is a complementary effect between agricultural technology extension and social networks in promoting farmers’ adoption of conservation tillage technology. The two functions complement and support each other, and this complementary effect is more evident in social networks’ reciprocity. (3) Further analysis reveals that the interaction effect between agricultural technology extension and social networks has significant group differences, technology type differences, and regional differences in farmers’ adoption of conservation tillage technology. Therefore, to facilitate the extension and application of conservation tillage technology, efforts need to be made in both agricultural technology extension and social networks, fully leveraging the complementary effects of the two. In addition, differentiated policies and measures should be adopted according to local conditions, and precise policies should be implemented for different groups and technologies.

Submarine groundwater discharge (SGD), including both land-based fresh groundwater that enters the ocean from coastal aquifers as well as recirculated seawater that is continuously recharged and discharged on the seabed, has been considered as an important component of the global water and biogenic element (e.g., nitrogen, phosphorus, silicon and carbon) sources and a significant pathway for material exchange at the land-sea interface of coastal ecosystems. Some researchers reported that SGD associated nutrient additions to coastal waters have caused unwanted ecological issues, including red tides, coastal acidification and hypoxia. Natural radon isotope (222Rn, t1/2 = 3.8 d) is an excellent tracer for studying SGD and other oceanographic processes including air-sea gas exchange, sediment-water diffusion, and earthquake prediction. However, the conventional radon measurement methods suffer many technical disadvantages. We consequently developed a convenient submersible radon determination approach (“OUC-Rn”) using a commercial pulsed ionization chamber (PIC) radon sensor and gas extraction membrane module to produce high precision and high resolution observations. We demonstrate the radon degassing efficiency of the membrane contactor is comparable to the shower-head type air-water exchanger but is independent of operating position. The radon measurement efficiency of the PIC is 2-fold higher than the RAD7 detector and is far less influenced by moisture. We successfully deployed the system in 2.5 meters water depth over a 100 hours period in an anthropogenic influenced bay. Based on our high temporal resolution observations, the SGD flux was estimated to be 0-43.0 cm/d (mean: 25.4 ± 14.5 cm/d). The SGD fluxes pattern plotted together with the tidal variations revealed that tidal pumping may be the main force driving seawater recirculation into aquifers and thus affecting nutrient, carbon and other dissolved matters dynamics in coastal regions.

The concentration and structure of nutrients play a key role in sustaining marine ecosystems. In recent decades, the change in nutrient input from land has led to significant changes in nutrient concentration and structure in the marginal sea and has had an important impact on the coastal ecosystem. Based on historical data from 1984 to 2016, the long-term variations in nutrients and their potential influencing factors, were analyzed in the Changjiang River Estuary. The concentration of dissolved inorganic nitrogen (DIN) increased gradually from 1984 to 2003, but after 2003 the concentration began to decrease. Compared with DIN, the change in dissolved inorganic phosphate (DIP) had a delayed effect and has exhibited a slow downward trend since 2005. The decreases in DIN and DIP are mainly due to the improvement of wastewater treatment efforts and chemical fertilizer use efficiency in recent years. The retention of nutrients by the Three Gorges Reservoir (TGR) has been another important factor since its completion in 2003, especially because the large amount of particulate phosphorus retained by the TGR has led to a significant decrease in the total phosphorus flux into the sea, which is the main reason for the decrease in DIP. The vatiations of DIP and DIN have been instrumental in causing the observed changes of phytoplankton community in the Changjiang River Estuary.

It is crucial to consider regional heterogeneity while analyzing drivers of changes in sectoral water use for developing differentiated and effective demand-regulation strategies in China. By using the logarithmic mean Divisia index method, this study compares dynamic influences of intensity, structure and scale factors on changes in productive and domestic water use during 2003–2017 between Tianjin (a socio-economic developed region) and Hebei (less-developed). The results show that the scale effect stimulated the growth of productive water use in both regions, while structure and intensity effects restrained such growth. The three effects all stimulated the growth of domestic water use in most years in both regions. In both regions, the largest contributor to changes in productive and domestic water use was the scale and intensity effect, respectively. However, in the two regions, the synergies of three effects resulted in different change trends of productive water use, and cumulative contributions of sub-sectors to the intensity, structure and scale effects were not exactly the same. Tianjin and Hebei need to keep on adjusting industrial structure and lowering water-use intensity to control future growth of productive water use and take strict measures to tackle the increasing trend of domestic water use but should have different policy implementation focuses. Highlights The drivers of water-use changes of regions at different socio-economic development stages were compared.; The forces of driving-factors of productive and domestic water use changed with time.; The root cause of changes in productive and domestic water use was not exactly the same in the two regions.; The results are helpful for formulating differentiated water-demand management policies.;

Breast cancer is now the most common cancer worldwide, and it is also the main cause of cancer-related death in women. Survival rates for female breast cancer have significantly improved due to early diagnosis and better treatment. Nevertheless, for patients with advanced or metastatic breast cancer, the survival rate is still low, reflecting a need for the development of new therapies. Mechanistic insights into metastatic breast cancer have provided excellent opportunities for developing novel therapeutic strategies. Although high-throughput approaches have identified several therapeutic targets in metastatic disease, some subtypes such as triple-negative breast cancer do not yet have an apparent tumor-specific receptor or pathway to target. Therefore, exploring new druggable targets in metastatic disease is a high clinical priority. In this review, we summarize the emerging intrinsic therapeutic targets for metastatic breast cancer, including cyclin D-dependent kinases CDK4 and CDK6, the PI3K/AKT/mTOR pathway, the insulin/IGF1R pathway, the EGFR/HER family, the JAK/STAT pathway, poly(ADP-ribose) polymerases (PARP), TROP-2, Src kinases, histone modification enzymes, activated growth factor receptors, androgen receptors, breast cancer stem cells, matrix metalloproteinases, and immune checkpoint proteins. We also review the latest development in breast cancer immunotherapy. Drugs that target these molecules/pathways are either already FDA-approved or currently being tested in clinical trials.

The Interferometric Synthetic Aperture Radar (InSAR) has been widely used as a powerful technique for monitoring land surface deformations over the last three decades. InSAR observations can be plagued by atmospheric phase delays; some have a roughly linear relationship with the ground elevation, which can be approximated using a linear model. However, the estimation results of this linear relationship are sometimes affected by phase ramps such as orbital errors, tidal loading, etc. In this study, we present a new approach to estimate the transfer function of vertical stratification phase delays and the transfer function of phase ramps. Our method uses the idea of multi-scale spatial differences to decompose the atmospheric phase delay into the vertical stratification component, phase ramp component, and other features. This decomposition makes the correlation between the vertical stratification phase delays and topography more significant and stable. This can establish the correlation between the different scales and phase ramps. We demonstrate our approach using a synthetic test and two real interferograms. In the synthetic test, the transfer functions estimated by our method were closer to the design values than those estimated by the full interferogram–topography correlation approach and the band-pass filtering approach. In the first real interferogram, out of the 9 sub-regions corrected by the proposed method, 7 sub-regions were outperformed the full interferogram–topography correlation approach, and 8 sub-regions were superior to the band-pass filtering method. Our technique offers a greater correction effect and robustness for coseismic deformation signals in the second real interferogram.

The well pattern and boundary shape of reservoirs determine the distribution of the remaining oil distribution to a large extent, especially for small-scale reservoir blocks. However, it is difficult to replicate experiences from other reservoirs directly to predict the remaining oil distribution because of the variety of irregular boundary shapes and corresponding well patterns. Meanwhile, the regular well pattern can hardly suit irregular boundary shapes. In this paper, we propose a well placement method for undeveloped irregular reservoirs and a multi-step prediction framework to predict both oil saturation and pressure fields for any reservoir shape and well pattern. To boost the physical information of input characteristics, a feature amplification approach based on physical formulae is initially presented. Then, 3D convolution technology is employed for the first time in 3D reservoir prediction to increase the spatial information in the vertical direction of the reservoir in the input. Moreover, to complete the two-field prediction, the concept of multi-task learning is adopted for the first time, improving the rationality of the forecast. Through the loss-based ablation test, we found that the operation we adopt will increase the accuracy of prediction to some extent. By testing on both manually designed and real irregular-shape reservoirs, our method is proven to be an accurate and fast oil saturation prediction method with its prediction loss less than 0.01 and calculation time less than 10 s in the future one year.

Exploring the interaction between water, land, and food (WLF) is a premise guaranteeing to ease resource restrictions and achieve sustainable development in major agricultural production areas. We chose 26 indicators to build a WLF nexus evaluation index system. We used the coupling coordination model to measure the coupling coordination degree of the WLF nexus in 15 prefecture-level cities and 151 counties under the jurisdiction of Hebei Province in 2000, 2005, 2010, 2015, and 2020. Then, the spatial correlation was analyzed using the global and local Moran’s I. Finally, the regional differences and spatiotemporal patterns were analyzed using a spatial gravity center model and kernel density estimation. The results are as follows: (1) In 11 cities, the comprehensive evaluation index of the WLF and of each subsystem shows a fluctuating upward trend. More than 95% of the counties’ comprehensive evaluation indices improved, and the difference between counties in the north and south narrowed after 2010. (2) The spatial pattern of the WLF in counties has evolved from a pattern of “high in the south and low in the north” to “high in the north and low in the south”, with the development speed of the north being higher than that of the south. (3) The coupling coordination degree of the WLF has a positive spatial autocorrelation relationship in different counties; however, the spatial connection eventually deteriorates, and the geographic pattern exhibits “agglomeration decrease” characteristics. In Hebei Province, the WLF coupling coordination rate slowly improves, and there is a significant development gap between counties. Therefore, local conditions should be taken into consideration when implementing measures to reduce the conflict between water, land, and food in actual regional conditions.

The detection and repair of cycle slips are key steps in high-accuracy GNSS (Global Navigation Satellite System) data processing using carrier phase observations. BDS (BeiDou Navigation Satellite System) triple-frequency observations provide better combinations for cycle slip detections and repairs compared to dual-frequency observations. Although a number of algorithms have been developed and may correctly detect cycle slips most of the time, the reliability of empirical thresholds methods cannot be guaranteed. In this study, an adaptive threshold is proposed for three sets of triple-frequency Geometry-Free (GF) pseudorange minus phase combinations to improve the cycle slip detection performance and reduce the false alarm rate of the cycle slip detection by combining the predicted epoch-differenced ionospheric delays under active ionospheric conditions. Moreover, in the cycle slip repair, the integral combined cycle slips are determined by directly rounding the estimated float-combined cycle slips, which will lead to a repair error if the between-epoch ionospheric variation is large. In this study, a new rounding method considering the predicted epoch-differenced ionospheric delays is proposed, and it is proven that the new method has a higher success rate for estimating the integer value of a cycle slip than the traditional method. The performance of the newly proposed method is validated by using static BDS triple-frequency observations that contain simulated cycle slips. BDS triple-frequency observations were collected at 30-s sampling intervals under active ionospheric conditions. The results show that this method can successfully detect and repair all slips of more than one cycle. In addition, dynamic BDS data collected with a vehicle-based receiver at a 1-s sampling intervals are processed, and the results show that the proposed method is also effective in the detection and repair of cycle slips in dynamic data.

The primary factors that impact food safety are the quality and safety of agricultural products. The quality and safety of agricultural products are closely related to farmers’ decision-making behavior. In addition, the decision-making behavior of the government and consumers is the key factor of farmers’ decision-making behavior. The study explores the ideal state among the government, farmers and consumers to promote the improvement of the quality of agricultural products, thereby contributing to food safety. The study includes the government, farmers and consumers in an evolutionary game model to explore game relationships and evolution paths of decision making among the three stakeholders. The dynamic analysis of the decision replication, the stability analysis of strategy evolution, and the numerical simulation experiment verify the following: the evolutionary process of the decision-making behavior of the three stakeholders to an ideal state is affected by many factors, and the value ranges of the different factors have different impacts on the convergence speed of the three stakeholders to an ideal state; When certain conditions are met, the decision-making behaviors of the three stakeholders can evolve to an ideal state, and effective government supervision can promote the transformation of farmers from nongreen to green pesticide application behavior, and encourage consumers to purchase high-quality agricultural products.

Abstract Background Pregnancy-associated breast cancer (PABC) is defined as breast cancer that is diagnosed during pregnancy and/or the postpartum period. Definitions of the duration of the postpartum period have been controversial, and this variability may lead to diverse results regarding prognosis. Moreover, evidence on the dose-response association between the time from the last pregnancy to breast cancer diagnosis and overall mortality has not been synthesized. Methods We systematically searched PubMed, Embase, and the Cochrane Library for observational studies on the prognosis of PABC published up to June 1, 2019. We estimated summary-adjusted hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs). Subgroup analyses based on diagnosis time, PABC definition, geographic region, year of publication and estimation procedure for HR were performed. Additionally, dose-response analysis was conducted by using the variance weighted least-squares regression (VWLS) trend estimation. Results A total of 54 articles (76 studies) were included in our study. PABC was associated with poor prognosis for overall survival (OS), disease-free survival (DFS) and cause-specific survival (CSS), and the pooled HRs with 95% CIs were 1.45 (1.30–1.63), 1.39 (1.25–1.54) and 1.40 (1.17–1.68), respectively. The corresponding reference category was non-PABC patients. According to subgroup analyses, the varied definition of PABC led to diverse results. The dose-response analysis indicated a nonlinear association between the time from the last delivery to breast cancer diagnosis and the HR of overall mortality (P

BackgroundLeptin (LEP) plays a physiological role through its specific receptor (LEPR) and is involved in the occurrence and development of breast cancer. Our current study aimed at determining the influence of single-nucleotide polymorphisms (SNPs) in the genes coding for LEP and LEPR on breast cancer risk.MethodsIn the present study, 963 breast cancer cases and 953 controls were enrolled. Five SNPs of LEP and two of LEPR were chosen to evaluate the correlation of selected SNPs with breast cancer susceptibility among women in northern and eastern China. Analyses were further stratified by body mass index (BMI), waist–hip rate (WHR), estrogen receptor, and progesterone receptor status. The expression patterns of risk variant-associated genes were detected by expression quantitative trait locus (eQTL) analysis with eQTLGen and The Cancer Genome Atlas database.ResultsThere were significant differences between breast cancer cases and control groups in the menopausal status and family history of breast cancer. Two SNPs (rs1137101 and rs4655555) of the LEPR gene decreased overall breast cancer risk, and other five SNPs showed no significant association with breast cancer risk. rs1137101 (GA vs. GG; adjusted OR = 0.719, 95% CI = 0.578–0.894, p = 0.003) and rs4655555 (TT vs. AA; adjusted OR = 0.574, 95% CI = 0.377–0.873, p = 0.009) significantly decreased breast cancer risk after Bonferroni correction for multiple testing. In subgroup analyses, the GA and GA + AA genotypes of LEPR rs1137101 associated with decreased breast cancer risk in the subgroup of BMI ≤ 24 kg/m2 or WHR ≥ 0.85 after Bonferroni correction. Furthermore, we found that the expressions of rs4655555-associated gene LEPR and leptin receptor overlapping transcript (LEPROT) were upregulated in breast cancer tumor tissues compared with adjacent normal tissues, and a higher expression of LEPR in tumor tissues was correlated with poor prognosis of breast cancer patients using The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) data.ConclusionOur study demonstrated that the polymorphisms rs1137101 and rs4655555 located in the LEPR gene decreased breast cancer risk in Chinese females, which might be a research-worthy bio-diagnostic marker and applied for early prediction and risk assessment of breast cancer.

ABSTRACT Increases in bone mineral density (BMD) with osteoporosis treatment are associated with reduced fracture risk. Increasing BMD is therefore a goal of osteoporosis therapy. Here, we compare the probability of achieving a T‐score of > −2.5 over 3 years at the total hip (TH) or lumbar spine (LS) in women with osteoporosis, ≥55 years of age, after the following treatment sequences: 1 year romosozumab followed by 2 years denosumab (FRAME and FRAME extension trials), 1 year romosozumab followed by 2 years alendronate, or alendronate‐only for 3 years (ARCH trial). Probabilities of attaining the BMD target within 1 year of treatment were also determined. At both skeletal sites, in women with a baseline Tscore ≥ −2.7, there was >50% probability of achieving the BMD target with any 3‐year regimen. The probability of achieving the target BMD in those with a baseline TH Tscore equal to −3.0 was 61% with romosozumab/denosumab, 38% with romosozumab/alendronate, and 9% with alendronate. In those with a baseline LS Tscore equal to −3.0, the probability of achieving a T‐score > −2.5 was 93% with romosozumab/denosumab, 81% with romosozumab/alendronate, and 55% with alendronate. With 1 year of treatment, in patients with a baseline TH T‐score equal to −2.7, the probability of reaching the target Tscore with romosozumab was 71% to 78% and 38% with alendronate. For patients with an initial LS T‐score equal to −3.0, the probability of achieving the target T‐score over 1 year was 85% to 86% with romosozumab and 25% for alendronate. Our findings suggest baseline BMD and the probability of achieving BMD T‐score goals are factors to consider when selecting initial treatment for patients with osteoporosis. As baseline T‐score falls below −2.7 (TH) and −3.0 (LS), alendronate has

Hsp chaperones stabilize the inactive conformation of androgen receptor (AR) and are released upon hormone-induced AR activation. Here, the authors locate the Hsp binding region on AR, and show that Hsp70 reduces AR aggregation and promotes AR degradation in cellular and mouse models of a neuromuscular disorder.

Abstract Background Considering the lack of efficient breast cancer prediction models suitable for general population screening in China. We aimed to develop a risk prediction model to identify high-risk populations, to help with primary prevention of breast cancer among Han Chinese women. Methods A cause-specific competing risk model was used to develop the Han Chinese Breast Cancer Prediction model. Data from the Shandong Case-Control Study (328 cases and 656 controls) and Taixing Prospective Cohort Study (13,176 participants) were used to develop and validate the model. The expected/observed (E/O) ratio and C-statistic were calculated to evaluate calibration and discriminative accuracy of the model, respectively. Results Compared with the reference level, the relative risks (RRs) for highest level of number of abortions, age at first live birth, history of benign breast disease, body mass index (BMI), family history of breast cancer, and life satisfaction scores were 6.3, 3.6, 4.3, 1.9, 3.3, 2.4, respectively. The model showed good calibration and discriminatory accuracy with an E/O ratio of 1.03 and C-statistic of 0.64. Conclusions We developed a risk prediction model including fertility status and relevant disease history, as well as other modifiable risk factors. The model demonstrated good calibration and discrimination ability.

Breast cancer is one of the most common cancers diagnosed in women. For preventive diagnosis, feature selection is an essential step to construct the breast cancer classifier. The features of a real breast cancer dataset are usually composed of discrete and continuous ones. Also, the Area Under the Curve (AUC) of the receiver operating characteristic receives more attention in such a medical field. The existing research work is insufficient to take into account both the hybrid trait of the features and the specific classification objective. We have proposed a wrapper method, i.e., a integrated framework in which Bayesian classifiers are embedded for the feature selection of breast cancer datasets. To deal with both the discrete features and the continuous features, we adopt the naive approach for the discrete features but the kernel probability density estimation for the continuous ones, respectively, which leads to feature-type-aware hybrid Bayesian classifiers. All the classifiers are fed with different feature subsets and evaluated by their AUC metrics as the fitness indexes. Thus, with the genetic algorithm, we can obtain a near optimal feature subset, which yields a good AUC metric with its corresponding classifiers. Moreover, the one-class F-score is used to help enhance the convergence of the algorithm. Experiments are done both with the continuous Wisconsin diagnostic breast cancer dataset and the real breast cancer dataset for Chinese women. The results prove that the proposed wrapper is feasible, accurate and efficient, compared with the related genetic algorithm based approaches.

High-cost carbon sources are not economical or sustainable for the heterotrophic culture of Chlorella vulgaris. In order to reduce the cost, this study used sweet sorghum extract (SE) and its enzymatic hydrolysate (HSE) as alternative carbon sources for the heterotrophic culture of Chlorella vulgaris. Under the premise of the same total carbon concentration, the value-added product production performance of Chlorella vulgaris cultured in HSE (supplemented with nitrogen sources and minerals) was much better than that in the glucose medium. The conversion rate of the total organic carbon and the utilization rate of the total nitrogen were both improved in the HSE system. The biomass production and productivity using HSE reached 2.51 g/L and 0.42 g/L/d, respectively. The production of proteins and lipids using HSE reached 1.17 and 0.35 g/L, respectively, and the production of chlorophyll-a, carotenoid, and lutein using HSE reached 30.42, 10.99, and 0.88 mg/L, respectively. The medium cost using HSE decreased by 69.61% compared to glucose. This study proves the feasibility and practicability of using HSE as a carbon source for the low-cost heterotrophic culture of Chlorella vulgaris.

This study was to assess the prognosis stratification of the clinical-pathologic staging system incorporating estrogen receptor (ER)-negative disease, the nuclear grade 3 tumor pathology (CPS + EG), Neo-Bioscore, and a modified Neo-Bioscore system in breast cancer patients after preoperative systemic therapy (PST). A retrospective multicenter cohort study was conducted from 12 participating hospitals’ databases from 2006 to 2015. Five-year disease free survival (DFS), disease specific survival (DSS), and overall survival (OS) were calculated using Kaplan–Meier Method. Area under the curve (AUC) of the three staging systems was compared. Wald test and maximum likelihood estimates in Cox proportional hazards model were used for multivariate analysis. A total of 1,077 patients were enrolled. The CPS + EG, Neo-Bioscore, and modified Neo-Bioscore could all stratify the DFS, DSS, and OS (all P < 0.001). While in the same stratum of Neo-Bioscore scores 2 and 3, the HER2-positive patients without trastuzumab therapy had much poorer DSS (P = 0.013 and P values < 0.01, respectively) as compared to HER2-positive patients with trastuzumab therapy and HER2-negative patients. Only the modified Neo-Bioscore had a significantly higher stratification of 5-year DSS than PS (AUC 0.79 vs. 0.65, P = 0.03). So, the modified Neo-Bioscore could circumvent the limitation of CPS + EG or Neo-Bioscore.Clinical Trial RegistrationClinicalTrials.gov, identifier NCT03437837.

The ubiquity of micropollutants (MPs) in aquatic environments has attracted increasing concern for public health and ecological security. Compared to conventional biological treatment, photocatalytic processes show more efficiency in degrading MPs, but they require expensive materials and complicated synthesis processes. This study developed an economic photocatalytic process to degrade micropollutants. We synthesized urea-based graphitic carbon nitride (g-C3N4) by a facile one-step pyrolysis method and evaluated the photocatalytic efficiency of carbamazepine (CBZ). Under simulated solar irradiation, g-C3N4 could achieve 100% removal efficiency of 0.1 mg/L CBZ in spiked wastewater effluent within 15 min, and 86.5% removal efficiency in wastewater influent after 20 min of irradiation. The porous structure of g-C3N4 promoted effective charge separation and mass transport of CBZ near the catalyst surface, enabling a high kinetic rate (0.3662 min −1). Reactive oxygen species trapping experiments revealed that superoxide radicals (O2 •-) and holes (h+) were the major active radicals. Electron paramagnetic resonance (EPR) further confirmed the presence of O2•-, • OH, 1O2 and holes. The pH, light intensity and initial CBZ concentration were found to have significant impacts on the removal efficiency of CBZ. Possible reaction intermediates were identified and the degradation pathway was proposed. Multiple MPs were selected to further demonstrate photocatalytic efficiency of g-C3N4. The facile synthesis, superior efficiency, and versatility of g-C3N4 make it a promising catalyst for application in tertiary wastewater treatment processes.

Hairpin curves are often employed in alignment layout and an important feature that identifies dangerous driving conditions for mountain roads. However, driving behaviors at hairpin curves remain ambiguous. Field driving tests were conducted in this study on one two-lane mountain road with 11 hairpin curves. Vehicle-mounted equipment was utilized to collect track and lateral distance between the wheels and the lane markings under naturally driving conditions. Track morphology and patterns, risks, and road crash mechanisms were analyzed. The main findings are as follows. Curve cutting was a typical method for negotiating hairpin curves, was observed for left and right turns, and can be classified into three types based on the location of the cutting point, namely, cutting at curve entry, cutting at curve middle, and cutting at curve exit. Based on the lateral positional relationships between tracks and lane markings, six track patterns are determined for left turns and four track patterns for right turns. When passing a right turn by cutting the curve, a driver occupied the right shoulder of the turn; therefore, there is a risk of colliding with the mountain or the guardrail. When making a left turn into hairpin curves, a driver occupied the right shoulder on curve exit, resulting in running off the road or colliding with the guardrail. More than 70% and 60% of drivers occupied the opposite lane when turning right and turning left, respectively, into a hairpin turn, which led to intertwining between the tracks in the two driving directions and therefore a risk of potential collisions.

Abstract Symptoms of eutrophication (including biodiversity loss, harmful algal blooms, and hypoxia) are an increasing problem in Chinese seas. Nutrient enrichment is primarily caused by accelerated human activities that cause nutrient pollution of the aquatic environment. In this study, the Integrated Model to Assess the Global Environment–Global Nutrient Model (IMAGE‐GNM) was used to estimate nitrogen inputs from river discharge, submarine fresh groundwater discharge, and mariculture, and TM5‐FAst Scenario Screening Tool (TM5‐FASST) for atmospheric nitrogen deposition to the three Large Marine Ecosystems (LMEs, i.e., Yellow Sea/Bohai Sea, YS/BS; East China Sea, ECS; South China Sea, SCS) bordered by China and several other countries for the period 1970–2010. China's river nitrogen export was the largest nitrogen source in YS/BS and ECS. In SCS, however, China and other countries contributed equally and although decreasing, the proportion of natural sources remain considerable. The total nitrogen inputs to YS/BS (1.0 to 4.1 Tg year−1), ECS (1.3 to 5.5 Tg year−1), and SCS (2.1 to 5.8 Tg year−1) increased rapidly during 1970–2010. River export is dominated by agriculture; nitrogen inputs from atmospheric deposition and mariculture have been increasing rapidly in recent years. Considering only the coastal zone of the three LMEs, our results show that the total nitrogen inputs are strongly concentrated spatially in areas close to river mouths and those confined regions with mariculture production. To sustain the food production and economic growth in the coming decades, nitrogen inputs may increase further, depending on future eutrophication mitigation policies.

Geometrical model is an important part of the CALPHAD method and has been widely used for the prediction of physicochemical properties of multicomponent systems. However, most of the researches are focused on the comparison of the predicted results by various geometrical models, and very few studies have analyzed the underlying causes of these differences. In this paper, we will discuss the factors affecting the predicted results of geometrical models by analyzing the whole calculation procedures. When the experimental data is constant, it is found that the predicted results are mainly affected by two factors, which can be concluded as the fitting order of Redlich-Kister equation and the selection rules of three representative points. The influences of the two factors are analyzed in the viscosity prediction of Au-Cu-Ag ternary system.