Differentiated cognition of the effects of human activities on typical persistent organic pollutants and bacterioplankton community in drinking water source.

Accelerated urbanization in developing countries led to a typical gradient of human activities (low, moderate and high human activities), which affected the pollution characteristics and ecological functions of aquatic environment. However, the occurrence characteristics of typical persistent organic pollutants, including organochlorine pesticides (OCPs) and polycyclic aromatic hydrocarbons (PAHs), and bacterioplankton associated with the gradient of human activities in drinking water sources is still lacking. Our study focused on a representative case - the upper reaches of the Dongjiang River (Pearl River Basin, China), a drinking water source characterized by a gradient of human activities. A comprehensive analysis of PAHs, OCPs and bacterioplankton in the water phase was performed using gas chromatography-mass spectrometry (GC-MS) and the Illumina platform. Moderate human activity could increase the pollution of OCPs and PAHs due to local agricultural activities. The gradient of human activities obviously influenced the bacterioplankton community composition and interaction dynamics, and low human activity resulted in low bacterioplankton diversity. Co-occurrence network analysis indicated that moderate human activity could promote a more modular organization of the bacterioplankton community. Structural equation models showed that nutrients could exert a negative influence on the composition of bacterioplankton, and this phenomenon did not change with the gradient of human activities. OCPs played a negative role in shaping bacterioplankton composition under the low and high human activities, but had a positive effect under the moderate human activity. In contrast, PAHs showed a strong positive effect on bacterioplankton composition under low and high human activities and a weak negative effect under moderate human activity. Overall, these results shed light on the occurrence characteristics of OCPs, PAHs and their ecological effects on bacterioplankton in drinking water sources along the gradient of human activities.

Degree of human activity exert differentiated influence on conventional and emerging pollutants in drinking water source.

Anthropogenic pollution poses a significant threat to drinking water sources worldwide. Previous studies have focused on the occurrence of pollutants in drinking water sources, but the impact of human activities on different types of pollutants in drinking water sources is still unclear. In this study, we chose the upper reaches of the Dongjiang River (URDR) as a case study to investigate the distribution characteristics of conventional pollutants, pesticides, and antibiotics along the gradient of human intervention. Our findings reveal that human activities can effect both conventional pollutants and emerging pollutants in the URDR to varying degrees. The escalation of human activities correlates with a rising trend in conventional pollutants, such as nitrogen (N) and phosphorus (P). Notably, only C1 (terrestrial humus) in dissolved organic matter (DOM) exhibits this increasing pattern. Pesticide and antibiotic concentrations are highest in areas with moderate and high levels of human activity, respectively, and the degree of eutrophication of drinking water closely follows the gradient of human activity. Our results also indicate that most pesticides pose a significant risk in the URDR, particularly pyrethroid pesticides (PYRs). Out of all antibiotics, only Norfloxacin (NFX) and Penicillin G (PENG) are classified as high-risk, with NFX exhibiting significant variation across different degrees of human activity. C1 and TP were the most important factors affecting the distribution of organophosphorus (OPPs) and PYRs, respectively. In conclusion, varying degrees of human activity exert differentiated influences on conventional and emerging pollutants in drinking water sources.

SynCluster: Reaction Type Clustering and Recommendation Framework for Synthesis Planning.

AI-assisted synthesis planning has emerged as a valuable tool in accelerating synthetic chemistry for the discovery of new drugs and materials. The template-free approach, which showcases superior generalization capabilities, is seen as the mainstream direction in this field. However, it remains unclear whether such an end-to-end approach can achieve problem-solving performance on par with experienced chemists without fully revealing insights into the chemical mechanisms involved. Moreover, there is a lack of unified and chemically inspired frameworks for improving multitask reaction predictions in this area. In this study, we have addressed these challenges by investigating the impact of fine-grained reaction-type labels on multiple downstream tasks and propose a novel framework named SynCluster. This framework incorporates unsupervised clustering cues into the baseline models and identifies plausible chemical subspaces which is compatible with multitask extensions and can serve as model-independent indicators to effectively enhance the performance of multiple downstream tasks. In retrosynthesis prediction, SynCluster achieves significant improvements of 4.1 and 11.0% in top-1 and top-10 prediction accuracy, respectively, compared to the baseline Molecular Transformer, and achieves a notable enhancement of 13.9% in top-10 accuracy when combined with Retroformer. By incorporating simplified molecular-input line-entry system augmentation, our framework achieves higher top-10 accuracy compared to state-of-the-art sequence-based retrosynthesis models and improves over the baseline on the diversity and validity of reactants. SynCluster also achieves 94.9% top-10 accuracy in forward synthesis prediction and 51.5% top-10 Maxfrag accuracy in reagent prediction. Overall, SynCluster provides a fresh perspective with chemical interpretability and reinforcement of domain knowledge in the synthesis design. It offers a promising solution for improving the accuracy and efficiency of AI-assisted synthesis planning and bridges the gap between template-free approaches and the problem-solving abilities of experienced chemists.

Efficacy and safety of SIM0417 (SSD8432) plus ritonavir for COVID-19 treatment: a randomised, double-blind, placebo-controlled, phase 1b trial.

Background: SIM0417 (SSD8432) is an orally administered coronavirus main proteinase (3CLpro) inhibitor with potential anti-SARS-CoV-2 activity. This study aimed to evaluate the efficacy and safety of SIM0417 plus ritonavir (a pharmacokinetic enhancer) in adults with COVID-19. Methods: This was a randomised, double-blind, placebo-controlled, phase 1b study in China. Adults with asymptomatic infection, mild or moderate COVID-19 were randomly assigned (3:3:2) to receive either 750 mg SIM0417 plus 100 mg ritonavir, 300 mg SIM0417 plus 100 mg ritonavir or placebo every 12 h for 10 doses. The main efficacy endpoints included SARS-CoV-2 viral load, proportion of participants with positive SARS-CoV-2 nucleic acid test and time to alleviation of COVID-19 symptoms. This trial is registered with ClinicalTrials.gov, NCT05369676. Findings: Between May 12 and August 29, 2022, 32 participants were enrolled and randomised to high dose group (n = 12), low dose group (n = 12) or placebo (n = 8). The viral load change from baseline in high dose group was statistically lower compared with placebo, with a maximum mean difference of -2.16 ± 0.761 log10 copies/mL (p = 0.0124) on Day 4. The proportion of positive SARS-CoV-2 in both active groups were lower than the placebo. The median time to sustained alleviation of COVID-19 symptoms was 2.0 days in high dose group versus 6.0 days in the placebo group (HR = 3.08, 95% CI 0.968-9.818). SIM0417 plus ritonavir were well tolerated with all adverse events in grade 1. Interpretation: SIM0417 plus ritonavir was generally well tolerated. The efficacy of SIM0417 showed a monotonic dose-response relationship, and the 750 mg SIM0417 plus 100 mg ritonavir was selected as the recommended clinical dose. Funding: The study was funded by Jiangsu Simcere Pharmaceutical Co., Ltd.

MetaRF: attention-based random forest for reaction yield prediction with a few trails.

Artificial intelligence has deeply revolutionized the field of medicinal chemistry with many impressive applications, but the success of these applications requires a massive amount of training samples with high-quality annotations, which seriously limits the wide usage of data-driven methods. In this paper, we focus on the reaction yield prediction problem, which assists chemists in selecting high-yield reactions in a new chemical space only with a few experimental trials. To attack this challenge, we first put forth MetaRF, an attention-based random forest model specially designed for the few-shot yield prediction, where the attention weight of a random forest is automatically optimized by the meta-learning framework and can be quickly adapted to predict the performance of new reagents while given a few additional samples. To improve the few-shot learning performance, we further introduce a dimension-reduction based sampling method to determine valuable samples to be experimentally tested and then learned. Our methodology is evaluated on three different datasets and acquires satisfactory performance on few-shot prediction. In high-throughput experimentation (HTE) datasets, the average yield of our methodology's top 10 high-yield reactions is relatively close to the results of ideal yield selection.

Analysis of influencing factors and prediction of carbon emissions of typical urban agglomerations in China: a case study of Beijing-Tianjin-Hebei region.

Achieving the "double carbon" goal is a major task and challenge facing China. The emission reduction actions in typical urban agglomerations are of great significance. Based on the consideration of the impact of regional coordinated development, this study analyzed influencing factors and conducted prediction of carbon emissions from terminal energy consumption in the Beijing-Tianjin-Hebei (BTH) region. Firstly, the factors affecting carbon emissions were screened through the STIRPAT model. Then, the paper designs different scenarios and finally uses the genetic algorithm extreme learning machine (GA-ELM) algorithm to predict the carbon emissions of the BTH region, with and without considering the impact of the coordinated development strategy. The research shows that the increase in energy intensity and the improvement of energy consumption structure have the largest promotion effect on carbon emission reduction. At the same time, the significant role of the coordinated development strategy in promoting regional carbon emission reduction was verified. Therefore, the BTH region should adhere to the path of coordinated development, innovate low-carbon technology, and deepen the concept of green consumption to promote the realization of regional carbon emission reduction goals.

Potential influence of overwintering benthic algae on water quality.

Overwintering benthic algae not only directly impact drinking water safety, but also affect the algae recruitment in warm spring seasons. Thus, understanding the characteristics of overwintering benthic algae can provide scientific references for formulating preventative strategies of reasonable water resource. However, they have received less attention. In this study, the spatiotemporal variation of benthic algae and their harmful secondary metabolites were studied from autumn to summer in Qingcaosha Reservoir. Benthic algae (picophytobenthos accounting for 55.42%) had a high biomass during overwintering, and the groups of overwintering benthic algae included pico-Cyanobacteria, pico-Cryptomonas, pico-Chlorophyta, pico-Diatoms, Cyanobacteria, Chlorophyta, Cryptomonas and Diatoms, which were consistent with the planktonic algae species in warm seasons. In oligotrophic or mesotrophic water bodies, micronutrients of iron and manganese were key nutrient factors influencing the biomass of benthic algae. Furthermore, picophytobenthos were important potential contributors of harmful secondary metabolites. The content of microcystins, anatoxin-a, geosmin and 2-methylisoborneol in sediment were 15.75 µg/kg·FW, 48.16 µg/kg·FW, 3.91 ng/kg·FW, and 11.76 ng/kg·FW during winter, which had potential to be released into water bodies to impact water quality. These findings indicate that water quality monitoring programs need to consider sediment in winter as a potential source of toxins and preventative measures to prevent excessive proliferation of algae should be implemented in winter.

What's the cost-effective pattern for rural wastewater treatment?

Inadequate sanitation infrastructure is a global problem that is particularly impacting rural areas. And decentralized wastewater management system is considered as the feasible solution for rural sewage treatment (RuST). However, determining the cost-effective (CE) pattern for decentralized RuST is methodologically challenging because of scarce decision-support tools. In this research, a RuST optimization model (RuST-OM) was developed to gain an insight into the CE pattern of RuST based on the greedy algorithm. This model involves tradeoffs in the economy-of-scale and technology of wastewater treatment system versus the cost and energy consumption of the sewage collection system. The investment associated with the CE pattern for RuST is closely linked to the environmental demand, RuST coverage, topographic complexity, and degree of household dispersion. The cost of the CE pattern falls between the onsite-B and community-based pattern, and this range represents the optimized interval for RuST planning. Nature-based technology is a sustainable alternative for RuST in areas characterized by low or moderate environmental demand. To ensure applicability of the RuST-OM in other countries/regions, built-in datasets (e.g., technology and pipeline design parameters) are designed based on rural area features that can be modified as necessary. This research highlights the utility of the CE pattern for RuST planning, and can serve as a reference for RuST planning around the world.

Circ_0067680 expedites the osteogenic differentiation of human bone marrow-derived mesenchymal stem cells through miR-4429/CTNNB1/Wnt/ß-catenin pathway.

BACKGROUND: Human bone marrow-derived mesenchymal stem cells (hBMSCs) are the primary source of osteoblasts in vivo. Emerging literatures have unveiled that circular RNAs (circRNAs) are actively drawn in the osteogenic differentiation of mesenchymal stem cells (MSCs). This research mainly illuminated the role of circ_0067680 as well as its regulatory mechanism in osteoblastic differentiation. METHODS: In this study, RT-qPCR was to measure the expression of circ_0067680. Functional assays were implemented to assess the role of circ_0067680 in osteogenic differentiation. Besides, RNA pull down, RIP and luciferase reporter assays were carried out to investigate the regulatory mechanism of circ_0067680. RESULTS: Circ_0067680, which derived from its host gene divergent protein kinase domain 2A (C3orf58), was up-regulated during osteogenic differentiation of hBMSCs. Besides, circ_0067680 deficiency impeded the osteoblastic differentiation of hBMSCs. Moreover, circ_0067680 served as a ceRNA via sequestering miR-4429 to regulate the expression of catenin beta 1 (CTNNB1), thereby activating the Wnt/ß-catenin signaling pathway. CONCLUSION: Circ_0067680 accelerated hBMSCs osteogenic differentiation by the miR-4429/CTNNB1/Wnt/ß-catenin signaling, which might be used as a potential biomarker for osteoblastic differentiation.

To centralize or to decentralize? A systematic framework for optimizing rural wastewater treatment planning.

Untreated rural sewage seriously affects the universal access to clean water of rural residents. The lack of decision-support tools in rural sewage treatment (RuST) planning makes it difficult for RuST system to achieve the expected results and is not conducive to the optimal allocation of limited funds. Hence, there is an urgent need to develop a decision-support framework for large-scale RuST planning. For the first time, RuST planning decision-support framework was developed using divide-and-conquer strategy based on rural residents' spatial pattern (RESP) and the optimal pattern of RuST. This framework can be transferred to other countries/regions easily by correcting RESP dataset according to the spatial and environmental characteristics. We confirmed that the variation of RESP made the ideal RuST pattern varied significantly under different topography. And community-based pattern could be the optimal pattern for large-scale RuST planning, when spatial obstacle and RESP were fully considered. The price of onsite sewage treatment facility is the most significant factor for RuST planning. In our selected case, requited onsite facility accounted for 65.51%. For the total investment, the cost of sewer systems accounted for 56.01%, and the average investment in plains, hills, platforms and mountains was 1401, 1803, 1903 and 1859 USD/household, respectively. We expect this research could provide reference for RuST planning in other developing countries/regions all around the world.

Long Noncoding RNA FBXL19-AS1 Expedites Cell Growth, Migration and Invasion in Cervical Cancer by miR-193a-5p/PIN1 Signaling.

BACKGROUND: Cervical cancer is one of the most prevalent malignancies in gynecology with increasing incidence in recent years. Long noncoding RNAs (lncRNAs) have been reported to regulate human cancers including cervical cancer. F-box and leucine-rich repeat protein 19 antisense RNA 1 (FBXL19-AS1) have been unmasked to exert carcinogenic functions in several cancers except cervical cancer. AIM: Present study hammered at investigating the function and mechanism of FBXL19-AS1 in cervical cancer. METHODS: RT-qPCR was utilized to test gene expression. EdU staining, colony formation, transwell, flow cytometry and TUNEL assays were applied for measuring the impact of FBXL19-AS1 on cervical cancer cell functions. Moreover, RIP, RNA pull-down and luciferase reporter assays were utilized for detecting the correlations among FBXL19-AS1, miR-193a-5p and PIN1 (peptidylprolyl cis/trans isomerase, NIMA-interacting 1). RESULTS: FBXL19-AS1 exhibited elevated expression in cervical cancer tissues and cells. Silencing FBXL19-AS1 repressed cell proliferation through arresting cell cycle and stimulating apoptosis, and losing FBXL19-AS1 also restrained cell migration and invasion. Also, we discovered FBXL19-AS1 as a miR-193a-5p sponge, while miR-193a-5p was a tumor inhibitor in cervical cancer. Further, PIN1 was proved as the miR-193a-5p target, and FBXL19-AS1 augmented PIN1 expression in cervical cancer via sequestering miR-193a-5p. Of note, PIN1 accelerated the progression of cervical cancer, and its upregulation counteracted the impacts of depleted FBXL19-AS1 on cervical cancer cell functions. CONCLUSION: FBXL19-AS1 contributes to malignant phenotypes in cervical cancer by sponging miR-193a-5p and regulating PIN1.

Multi-phase distribution, spatiotemporal variation and risk assessment of antibiotics in a typical urban-rural watershed.

The widespread consumption and continuous discharge of antibiotics have threatened the ecological health of urban-rural watershed. In this study, multi-phase distribution, spatiotemporal variation and ecological risk of 18 antibiotics in rivers and lakes from Suzhou City were investigated based on urban-rural gradient. The total antibiotic concentration in surface water, suspended particulate matter (SPM) and sediments was 39.28-2578 ng/L, 6.16-171.09 ng/L and 12.67-2249 ng/g, respectively. High detection frequency (>76%) and concentration of antibiotics in multi-phase suggested universal pollution. Quinolones (QNs) and tetracycline (TCs) were the dominant antibiotics detected. The partitioning coefficient (KP) value of SPM-water was 1.43-29.93 times larger than sediment-water, indicating that SPM can greatly affect the fate and distribution of antibiotics. Significant positive correlations between antibiotics and environmental parameters (e.g. TOC, TP and TN) revealed combined contamination and similar pollution sources. Antibiotic pollution exhibited evident spatiotemporal variation. For spatial variation, urban area showed more serious antibiotic pollution and greater ecological risk than rural and suburb areas, especially for sediments. Besides, antibiotic level and risk in rivers were higher than lakes. For seasonal variation, in case of surface water, rural area exhibited higher content in winter, while greater content was detected in autumn and spring in urban and suburb areas, respectively. The highest antibiotic content in SPM and sediments was all measured in winter owing to weak degradation ability. Ecological risk assessment based on risk quotients (RQs) indicated that norfloxacin (NFX), ciprofloxacin (CFX) and anhydroerythromycin (ETM-H2O) in surface water presented medium to high risk throughout the entire year, while sulfadiazine (SDZ) and enrofloxacin (EFX) in sediments showed higher accumulation potential. Thus, these five antibiotics were selected as the priority antibiotics for pollution control. In short, this study improves the understanding of antibiotic fates in the urban-rural watershed and provides scientific basis for the authorities to regulate antibiotic pollution.

Comprehensive insights into the occurrence, distribution, risk assessment and indicator screening of antibiotics in a large drinking reservoir system.

Drinking water reservoir is threatened globally due to anthropogenic contamination and thus in need of more attention. Here, we comprehensively investigated the occurrence, distribution and risk assessment of representative antibiotics in a large drinking water reservoir (Fengshuba Reservoir, China). The total concentrations of antibiotics in the water phase, porewater phase, sediment phase and soil phase (drawdown area) were in the ranges of 195-569 ng/L, 47.1-333 ng/L, 114-272 µg/kg and 2.84-77.2 µg/kg, respectively. The dominant antibiotic was CIP in both the water and porewater phases, while it was OTC in the sediment phase. For the water phase, seasonal factor consisting hydrologic condition and pattern of antibiotic use could influence the occurrence level and environmental fate of antibiotics. In contrast, exogenous particles derived from the soils that had used manures during the spring planting season coupled with heavy rainfall was responsible for the occurrence level and composition of antibiotics in the sediment phase. Moreover, Chl-α, NO3-, TP and EC were the most dominant factor influencing the antibiotic distributions in the water phase, porewater phase, sediment phase and soil phase, respectively. Pseudo-partitioning coefficients indicated that PENV and PENG might accumulate more easily into the sediments from the aqueous phase compared with other antibiotics. Risk assessments suggested that TC might pose high risks to the aquatic ecosystem, but the antibiotics presented no risk to the health of consumers. Generally, TC could be used as a promising indicator for evaluating the occurrence and potential risk of antibiotics in Fengshuba Reservoir.

Antibiotic resistome associated with microbial communities in an integrated wastewater reclamation system.

Antibiotic resistome is a raising concern around the world, especially considering treated wastewater for reclamation. A wastewater reclamation system (WWRS), composed by a treatment system (TS) and a reclaimed system (RS) with supplementation from the treated effluent and considered as an integrated system of treatment and reclamation, was selected in this study. High-throughput qPCR (HT-qPCR) was applied to profile 283 antibiotic resistance genes (ARGs) and 12 mobile genetic elements (MGEs) in the WWRS. A total of 251 ARG and 12 MGE subtypes were detected in the WWRS. The TS exhibited good performance for the removal of ARGs with the number, relative and absolute abundances of ARGs largely decreased (99.07% removal efficiency) in the final effluent, which might be ascribed to biosolid sedimentation. Enhancement of biosolids removal contributed the lessening of ARGs. In the RS, high quality effluent significantly reduced the number and abundance of ARGs along the flow to downstream. MGEs were less reduced in the treated effluent than that of the influent (R2 = -0.16, p > 0.05), and exhibited close connections with ARGs. Arcobacter, Cloacibacterium, Cyanobacteria, Acinetobacter, Flavobacterium and Dechloromonas were the relatively abundant genera in the WWRS, and exhibited significantly correlations with ARGs. Microbial communities and MGEs contributed 65.64% to the changes of ARGs. These two factors may be the main drivers of ARG proliferation in the WWRS. Thus, attention should be paid to MGEs and those abundant genera when considering treated wastewater for reclamation.

Occurrence and fate of antibiotic residues and antibiotic resistance genes in a reservoir with ecological purification facilities for drinking water sources.

Antibiotics and antibiotic resistance genes (ARGs) are emerging contaminants in surface waters, especially drinking water sources, where they can pose a risk to human health and aquatic ecology. The ecological purification facilities constructed in the drinking water reservoirs are intended to safeguard water quality. However, their ability to remove antibiotics and ARGs from the water and the presence of ARGs in such river-reservoir systems have not been comprehensively characterized yet. The occurrence, distribution and spatiotemporal variations in antibiotics, ARGs, and mobile genetic elements (MGEs) were investigated in a representative river-reservoir system in Shanghai, China. A total of 283 ARGs and 12 MGEs were detected in the water using high- throughput quantitative PCR analysis. Antibiotic residues and the absolute abundance of total ARGs and MGEs in reservoir inflow were significantly reduced when water from the river passed through the ecological purification processes in the reservoir. Antibiotics in this river-reservoir system posed only limited risks to the aquatic ecosystem and human health. No significant correlation was observed between the distribution pattern of ARGs and spatiotemporal factors. The dominant ARGs were strongly and significantly correlated with integrons. Through redundancy analysis and variation partitioning analysis, we determined that MGEs were the major driver shifting the distribution of ARGs, and the effects of environmental factors and antibiotic residues were reflected in the joint effects with MGEs. The small ecological reservoir was verified as an effective engineering to mitigate ecological risk in the drinking water source.

Environmental media exert a bottleneck in driving the dynamics of antibiotic resistance genes in modern aquatic environment.

With the rapid construction of dams worldwide, reservoir system has become a representation of modern aquatic environment. However, the profiles of antibiotic resistance genes (ARGs) and associated factor influencing their dynamics in modern aquatic environment (e.g., water phase, sediment phase, and soil phase) are largely unknown. Here, we comprehensively characterized the diversity, abundance, distribution of ARGs in a large drinking water reservoir using high-throughput quantitative PCR, as well as ranked the factors (e.g., mobile genetic elements (MGEs), bacteria community, bacterial biomass, antibiotics, and basic properties) influencing the profiles of ARGs on the basis of structural equation models (SEMs). Water phase was prone to harbor more diverse ARGs as compared to sediment phase and soil phase, and soil phase in drawdown area was a potential reservoir and hotspot for ARGs. Environmental media partially affected the ARG diversity in modern aquatic environment, while it observably influenced the distributions of ARGs and MGEs and their co-occurrence patterns. The pathways for the proliferation and spread of ARGs in water phase were both the horizontal gene transfer (HGT) and vertical gene transfer (VGT), while the dominant pathways in sediment phase and soil phase were the HGT and VGT, respectively. The SEMs demonstrated that MGEs contributed the most to drive the ARG dynamics in both water phase and sediment phase, while the most dominant factor for this in soil phase was bacterial community. Overall, environmental media exerted a bottleneck in driving the dynamics of ARGs in modern aquatic environment probably via diversifying the MGEs, bacterial community, bacterial biomass, antibiotics and basic properties.

Whole-Exome Sequencing Reveals Frequent Mutations in Chromatin Remodeling Genes in Mammary and Extramammary Paget's Diseases.

Paget's disease (PD) is an intraepidermal adenocarcinoma of the skin at the breast (mammary PD) or urogenital locations (extramammary PD [EMPD]). At present, there is lack of clarity on PD's pathogenesis, the relationship between its subtypes, and its lineage link with the underlying invasive carcinomas. Here we describe that mammary PD and EMPD have similar mutational profiles, with the most frequent recurrent mutations occurring in the chromatin remodeling genes, such as KMT2C (MLL3, 39%) and ARID2 (22%), with additional recurrent somatic mutations detected in genes previously not known to be mutated in cancers, such as CDCC168 (34%), FSIP2 (29%), CASP8AP2 (29%), and BIRC6 (24%). In paired mammary PD and underlying breast carcinoma samples, distinct gene mutations were detected, indicating that they represent independent oncogenic events. Finally, multistage EMPD tissue sequencing revealed KMT2C gene occurring early in EMPD oncogenesis, and that multifocal EMPD samples share the same early gene mutations, suggesting clonal origin of multifocal EMPD. Our results reveal similar genomic landscapes between mammary PD and EMPD, including early aberrations in chromatin remodeling genes. In addition, mammary PD and underlying breast ductal carcinomas represent independent oncogenic events. These findings provide approaches for developing diagnostic tools and therapeutic interventions for PD.

Transcriptome analyses reveal FOXA1 dysregulation in mammary and extramammary Paget's disease.

Paget's disease (PD) is an uncommon intraepithelial adenocarcinoma with unknown pathogenesis. There are two anatomic subtypes: mammary (MPD) and extramammary (EMPD). Little is known about their molecular characteristics. Our objective was to discover novel molecular markers for PD and its subtypes. In the discovery phase, we used transcriptome analyses to uncover the most differentially expressed genes and pathways in EMPD biopsies compared with normal skin. In the validation phase, we performed immunohistochemistry analyses on the most promising marker (FOXA1) and other markers selected from a literature review (GATA3, estrogen receptor [ER], and androgen receptor [AR]) on independent biopsies of MPD (n = 86), EMPD (n = 59), and normal skin (n = 21). Transcriptome analyses revealed 210 genes differentially expressed more than 10-fold between EMPD and normal skin. These genes are involved in mammary and sweat gland development (FOXA1) and immune regulation, as well as epidermal differentiation. Immunohistochemistry staining revealed that FOXA1 was positive in 88% of both MPD and EMPD, whereas GATA3 was positive in 67% of MPD and 77% of EMPD, and ER was positive in 9% of MPD and 19% of EMPD. Finally, AR was positive in 33% of PD and 54% of EMPD. Mammary Paget's disease and EMPD share dysregulation of the glandular developmental regulator gene FOXA1, suggesting similarity in cell-specific transcriptional regulation. Further, FOXA1 may be a useful molecular target for developing PD therapies.

Performance of search strategies to retrieve systematic reviews of diagnostic test accuracy from the Cochrane Library.

AIM: To compare the performance of search strategies to retrieve systematic reviews of diagnostic test accuracy from The Cochrane Library. METHODS: Databases of Cochrane Database of Systematic Reviews and Cochrane Database of Abstracts of Reviews of Effects in the Cochrane Library were searched for systematic reviews of diagnostic test accuracy published between 2008 and 2012 through nine search strategies. Each strategy consists of one group or combination of groups of searching filters about diagnostic test accuracy. Four groups of diagnostic filters were used. The strategy combing all the filters was used as the reference to determine the sensitivity, precision, and the sensitivity × precision product for another eight strategies. RESULTS: The reference strategy retrieved 8029 records, of which 832 were eligible. The strategy only composed of MeSH terms about "accuracy measures" achieved the highest values in both precision (69.71%) and product (52.45%) with a moderate sensitivity (75.24%). The combination of MeSH terms and free text words about "accuracy measures" contributed little to increasing the sensitivity. Strategies composed of filters about "diagnosis" had similar sensitivity but lower precision and product to those composed of filters about "accuracy measures." MeSH term "exp'diagnosis'" achieved the lowest precision (9.78%) and product (7.91%), while its hyponym retrieved only half the number of records at the expense of missing 53 target articles. The precision was negatively correlated with sensitivities among the nine strategies. CONCLUSIONS: Compared to the filters about "diagnosis," the filters about "accuracy measures" achieved similar sensitivities but higher precision. When combining both terms, sensitivity of the strategy was enhanced obviously. The combination of MeSH terms and free text words about the same concept seemed to be meaningless for enhancing sensitivity.

The difference between oats and beta-glucan extract intake in the management of HbA1c, fasting glucose and insulin sensitivity: a meta-analysis of randomized controlled trials.

Increasing oats and beta-glucan extract intake has been associated with improved glycemic control, which is associated with the reduction in the development of diabetes. This study aims to assess the different effects between oat (whole and bran) and beta-glucan extract intake on glycemic control and insulin sensitivity. PubMed, Embase, Medline, The Cochrane Library, CINAHL and Web of Science were searched up to February 2014. We included randomized controlled trials with interventions that lasted at least four weeks that compared oats and beta-glucan (extracted from oats or other sources) intake with a control. A total of 1351 articles were screened for eligibility, and relevant data were extracted from 18 studies (n = 1024). Oat product dose ranged from 20 g d(-1) to 136 g d(-1), and beta-glucan extract dose ranged from 3 g d(-1) to 10 g d(-1). Compared with the control, oat intake resulted in a greater decrease in fasting glucose and insulin of subjects (P < 0.05), but beta-glucan extract intake did not. Furthermore, oat intake resulted in a greater decrease in glycosylated hemoglobin (HbA1c) (P < 0.001, I(2) = 0%) and fasting glucose (P < 0.001, I(2) = 68%) after removing one study using a concentrate and a different design and fasting insulin of type 2 diabetes (T2D) (P < 0.001, I(2) = 0%). The intake of oats and beta-glucan extracted from oats were effective in decreasing fasting glucose (P = 0.007, I(2) = 91%) and fasting insulin of T2D (P < 0.001, I(2) = 0%) and tented to lower HbA1c (P = 0.09, I(2) = 92%). Higher consumption of whole oats and oat bran, but not oat or barley beta-glucan extracts, are associated with lower HbA1c, fasting glucose and fasting insulin of T2D, hyperlipidaemic and overweight subjects, especially people with T2D, which supports the need for clinical trials to evaluate the potential role of oats in approaching to the management of glycemic control and insulin sensitivity of diabetes or metabolic syndrome subjects.