Search for Flavoured Multiquarks in a Simple Bag Model

We use a bag model to study flavoured mesonic $(Qq\bar q\bar q)$ and baryonic $({\overline Q}qqqq)$ states, where one heavy quark $Q$ is associated with light quarks or antiquarks, and search for possible stable multiquarks. No bound state is found. However some states lie not too high above their dissociation threshold, suggesting the possibility of resonances, or perhaps bound states in improved models.Comment: REVTEX, VERSION 3.

An evaluation of Cochrane Crowd found that crowdsourcing produced accurate results in identifying randomised trials

BACKGROUND: Filtering the deluge of new research to facilitate evidence synthesis has proven to be unmanageable using current paradigms of search and retrieval. Crowdsourcing, a way of harnessing the collective effort of a 'crowd' of people, has the potential to support evidence synthesis by addressing this information overload created by the exponential growth in primary research outputs. Cochrane Crowd, Cochrane's citizen science platform, offers a range of tasks aimed at identifying studies related to healthcare. Accompanying each task are brief, interactive training modules and agreement algorithms that help ensure accurate collective decision-making. OUR OBJECTIVES WERE: (1) to evaluate the performance of Cochrane Crowd in terms of its accuracy, capacity and autonomy; and (2) to examine contributor engagement across three tasks aimed at identifying randomised trials. STUDY DESIGN: Crowd accuracy was evaluated by measuring the sensitivity and specificity of crowd screening decisions on a sample of titles and abstracts, compared with 'quasi gold-standard' decisions about the same records using the conventional methods of dual screening. Crowd capacity, in the form of output volume, was evaluated by measuring the number of records processed by the crowd, compared with baseline. Crowd autonomy, the capability of the crowd to produce accurate collectively-derived decisions without the need for expert resolution, was measured by the proportion of records that needed resolving by an expert. RESULTS: The Cochrane Crowd community currently has 18,897 contributors from 163 countries. Collectively, the Crowd has processed 1,021,227 records, helping to identify 178,437 reports of randomised trials (RCTs) for Cochrane's Central Register of Controlled Trials. The sensitivity for each task was 99.1% for the randomised controlled trial identification task (RCT ID), 99.7% for the randomised controlled trial identification task of trial from ClinicalTrials.gov (CT ID) and 97.7% for identification of randomised controlled trials from the International Clinical Trials Registry Platform (ICTRP ID). The specificity for each task was 99% for RCT ID, 98.6% for CT ID and 99.1% for ICTRP ID. The capacity of the combined Crowd and machine learning workflow has increased five-fold in six years, compared with baseline. The proportion of records requiring expert resolution across the tasks ranged from 16.6% to 19.7%. CONCLUSION: Cochrane Crowd is sufficiently accurate and scalable to keep pace with the current rate of publication (and registration) of new primary studies. It has also proved to be a popular, efficient and accurate way for a large number of people to play an important voluntary role in health evidence production. Cochrane Crowd is now an established part of Cochrane's effort to manage the deluge of primary research being produced

Transforming Big Data into AI‐ready data for nutrition and obesity research

OBJECTIVE: Big Data are increasingly used in obesity and nutrition research to gain new insights and derive personalized guidance; however, this data in raw form are often not usable. Substantial preprocessing, which requires machine learning (ML), human judgment, and specialized software, is required to transform Big Data into artificial intelligence (AI)- and ML-ready data. These preprocessing steps are the most complex part of the entire modeling pipeline. Understanding the complexity of these steps by the end user is critical for reducing misunderstanding, faulty interpretation, and erroneous downstream conclusions. METHODS: We reviewed three popular obesity/nutrition Big Data sources: microbiome, metabolomics, and accelerometry. The preprocessing pipelines, specialized software, challenges, and how decisions impact final AI- and ML-ready products were detailed. RESULTS: Opportunities for advances to improve quality control, speed of preprocessing, and intelligent end user consumption were presented. CONCLUSIONS: Big Data have the exciting potential for identifying new modifiable factors that impact obesity research. However, to ensure accurate interpretation of conclusions arising from Big Data, the choices involved in preparing AI- and ML-ready data need to be transparent to investigators and clinicians relying on the conclusions

Phenotypic Variation and Bistable Switching in Bacteria

Microbial research generally focuses on clonal populations. However, bacterial cells with identical genotypes frequently display different phenotypes under identical conditions. This microbial cell individuality is receiving increasing attention in the literature because of its impact on cellular differentiation, survival under selective conditions, and the interaction of pathogens with their hosts. It is becoming clear that stochasticity in gene expression in conjunction with the architecture of the gene network that underlies the cellular processes can generate phenotypic variation. An important regulatory mechanism is the so-called positive feedback, in which a system reinforces its own response, for instance by stimulating the production of an activator. Bistability is an interesting and relevant phenomenon, in which two distinct subpopulations of cells showing discrete levels of gene expression coexist in a single culture. In this chapter, we address techniques and approaches used to establish phenotypic variation, and relate three well-characterized examples of bistability to the molecular mechanisms that govern these processes, with a focus on positive feedback.

Natural quorum sensing inhibitors effectively downregulate gene expression of Pseudomonas aeruginosa virulence factors

At present, anti-virulence drugs are being considered as potential therapeutic alternatives and/or adjuvants to currently failing antibiotics. These drugs do not kill bacteria but inhibit virulence factors essential for establishing infection and pathogenesis through targeting non-essential metabolic pathways reducing the selective pressure to develop resistance. We investigated the effect of naturally isolated plant compounds on the repression of the quorum sensing (QS) system which is linked to virulence/pathogenicity in Pseudomonas aeruginosa. Our results show that trans-cinnamaldehyde (CA) and salicylic acid (SA) significantly inhibit expression of QS regulatory and virulence genes in P. aeruginosa PAO1 at sub-inhibitory levels without any bactericidal effect. CA effectively downregulated both the las and rhl QS systems with lasI and lasR levels inhibited by 13- and 7-fold respectively compared to 3- and 2-fold reductions with SA treatment, during the stationary growth phase. The QS inhibitors (QSI) also reduced the production of extracellular virulence factors with CA reducing protease, elastase and pyocyanin by 65%, 22% and 32%, respectively. The QSIs significantly reduced biofilm formation and concomitantly with repressed rhamnolipid gene expression, only trace amount of extracellular rhamnolipids were detected. The QSIs did not completely inhibit virulence factor expression and production but their administration significantly lowered the virulence phenotypes at both the transcriptional and extracellular levels. This study shows the significant inhibitory effect of natural plant-derived compounds on the repression of QS systems in P. aeruginosa

Producing Cochrane systematic reviews—a qualitative study of current approaches and opportunities for innovation and improvement

Background: Producing high-quality, relevant systematic reviews and keeping them up to date is challenging. Cochrane is a leading provider of systematic reviews in health. For Cochrane to continue to contribute to improvements in heath, Cochrane Reviews must be rigorous, reliable and up to date. We aimed to explore existing models of Cochrane Review production and emerging opportunities to improve the efficiency and sustainability of these processes. Methods: To inform discussions about how to best achieve this, we conducted 26 interviews and an online survey with 106 respondents. Results: Respondents highlighted the importance and challenge of creating reliable, timely systematic reviews. They described the challenges and opportunities presented by current production models, and they shared what they are doing to improve review production. They particularly highlighted significant challenges with increasing complexity of review methods; difficulty keeping authors on board and on track; and the length of time required to complete the process. Strong themes emerged about the roles of authors and Review Groups, the central actors in the review production process. The results suggest that improvements to Cochrane's systematic review production models could come from improving clarity of roles and expectations, ensuring continuity and consistency of input, enabling active management of the review process, centralising some review production steps; breaking reviews into smaller "chunks", and improving approaches to building capacity of and sharing information between authors and Review Groups. Respondents noted the important role new technologies have to play in enabling these improvements. Conclusions: The findings of this study will inform the development of new Cochrane Review production models and may provide valuable data for other systematic review producers as they consider how best to produce rigorous, reliable, up-to-date reviews

Portfolio Choice and Transactions Taxes

In a simple portfolio choice model of two assets a foreign exchange transactions tax is implemented. We show that the graph in the mu-sigma[square] range is still a parabola and delineate its characteristics for altering tax rates. We presumed a risk avers investor seeking to minimize investment risks by international diversification of two uncorrelated assets. The main finding is that setting up a portfolio under the new tax condition leads to a higher transaction volume on international financial markets. In contrast, the transactions tax has got a stabilizing character when adjusting the portfolio to increased foreign investment risks