Screening and comparative characterization of microorganisms from Iranian soil samples showing ω-transaminase activity toward a plethora of substrates

In this study, soil microorganisms from Iran were screened for ω-transaminase (ω-TA) activity based on growth on minimal media containing (rac)-α-methylbenzylamine (rac-α-MBA) as a sole nitrogen source. Then, for the selection of strains with high enzyme activity, a colorimetric o-xylylendiamine assay was conducted. The most promising strains were identified by 16S rDNA sequencing. Five microorganisms showing high ω-TA activity were subjected to determine optimal conditions for ω-TA activity, including pH, temperature, co-solvent, and the specificity of the ω-TA toward different amine donors and acceptors. Among the five screened microorganisms, Bacillus halotolerans turned out to be the most promising strain: Its cell-free extract showed a highly versatile amino donor spectrum toward aliphatic, aromatic chiral amines and a broad range of pH activity. Transaminase activity also exhibited excellent solvent tolerance, with maximum turnover in the presence of 30% (v/v) DMS

Reproducibility and scientific integrity of big data research in urban public health and digital epidemiology: a call to action

The emergence of big data science presents a unique opportunity to improve public-health research practices. Because working with big data is inherently complex, big data research must be clear and transparent to avoid reproducibility issues and positively impact population health. Timely implementation of solution-focused approaches is critical as new data sources and methods take root in public-health research, including urban public health and digital epidemiology. This commentary highlights methodological and analytic approaches that can reduce research waste and improve the reproducibility and replicability of big data research in public health. The recommendations described in this commentary, including a focus on practices, publication norms, and education, are neither exhaustive nor unique to big data, but, nonetheless, implementing them can broadly improve public-health research. Clearly defined and openly shared guidelines will not only improve the quality of current research practices but also initiate change at multiple levels: the individual level, the institutional level, and the international level

Impact of Biofluid Viscosity on Size and Sedimentation Efficiency of the Isolated Microvesicles

Microvesicles are nano-sized lipid vesicles released by all cells in vivo and in vitro. They are released physiologically under normal conditions but their rate of release is higher under pathological conditions such as tumors. Once released they end up in the systemic circulation and have been found and characterized in all biofluids such as plasma, serum, cerebrospinal fluid, breast milk, ascites, and urine. Microvesicles represent the status of the donor cell they are released from and they are currently under intense investigation as a potential source for disease biomarkers. Currently, the “gold standard” for isolating microvesicles is ultracentrifugation, although alternative techniques such as affinity purification have been explored. Viscosity is the resistance of a fluid to a deforming force by either shear or tensile stress. The different chemical and molecular compositions of biofluids have an effect on its viscosity and this could affect movements of the particles inside the fluid. In this manuscript we addressed the issue of whether viscosity has an effect on sedimentation efficiency of microvesicles using ultracentrifugation. We used different biofluids and spiked them with polystyrene beads and assessed their recovery using the Nanoparticle Tracking Analysis. We demonstrate that MVs recovery inversely correlates with viscosity and as a result, sample dilutions should be considered prior to ultracentrifugation when processing any biofluids

Price dispersion: the case of pasta

Scopo della ricerca è indagare la possibilità di utilizzare scanner data sugli acquisti di pasta per costruire indici dei prezzi spaziali bilaterali e multilaterali utilizzando un approccio binario nella loro costruzione.The aim of our research is to explore the possibility of utilizing scanner data on pasta purchases to build bilateral and multilateral spatial price indexes, taking a binary approach in the latter.1 Pasta plays a major role in the Italian diet. Historically, pasta consumption was mainly concentrated in the Southern regions of the country but today pasta is perhaps the product most representative of the eating habits of the Italians. The range of pasta producers runs from firms of longstanding tradition (some of them mainly directed towards local markets, such as Mastromauro in Puglia) to well known international brands (such as Barilla and De Cecco). The marked increase in pasta prices over the last two years has aroused great interest, but with little focus on spatial price diversity. This study stems from the availability of an extremely detailed panel dataset (Nielsen data) on values and quantities of pasta purchased. This data was produced by the use of bar-code scanning at retail outlets and thus includes information which provides weights at an elementary level. The use of scanner data to construct price indexes is not new in literature and there is a widespread consensus on the advantages of this approach in achieving more representative indexes. Average prices (unit values) show a marked spatial price variability: even when only considering the five bestselling products, regional prices vary greatly. The paper is set out as follows: Sect. 2 provides a description of the pasta scanner dataset and briefly looks for price variability; in Sect. 3 the requirements of comparability and representativity in the case of pasta are discussed; Sect. 4 deals with the methods and formulas chosen to obtain indexes for the regional comparisons of prices; Sect. 5 shows empirical results; in Sect. 6 a brief conclusion and suggestions for future work are given

An Insight into the Sex Differences in COVID-19 Patients: What are the Possible Causes?

Studies have reported a sex bias in case fatalities of COVID-19 patients. Moreover, it is observed that men have a higher risk of developing a severe form of the disease compared to women, highlighting the importance of disaggregated data of male and female COVID-19 patients. On the other hand, other factors (eg, hormonal levels and immune functions) also need to be addressed due to the effects of sex differences on the outcomes of COVID-19 patients. An insight into the underlying causes of sex differences in COVID-19 patients may provide an opportunity for better care of the patients or prevention of the disease. The current study reviews the reports concerning with the sex differences in COVID-19 patients. It is explained how sex can affect angiotensin converting enzyme-2 (ACE2), that is a key component for the pathogenesis of COVID-19, and summarized the gender differences in immune responses and how sex hormones are involved in immune processes. Furthermore, the available data about the impact of sex hormones on the immune functions of COVID-19 cases are looked into

The Socio-economic Impacts of Social Media Privacy and Security Challenges

© 2020, Springer Nature Singapore Pte Ltd. Privacy and Security are two major challenges faced by users on social media today. These challenges are experienced in diverse ways and forms by different types of users across the web. While technological solutions are usually implemented to address them, the effects have proven to be limited so far. Despite continuous deployment of technological solutions, the need to evaluate socio-economic impacts of these challenges have also become more imperative. Hence, this paper provides a critical review and analysis of socio-economic impacts of these social media challenges. The research findings reveal significant levels of negative socio-economic impacts and provides an evaluation framework towards defining the scope, thereby identifying appropriate measures for both addressing the challenges and curbing the socio-economic impacts. The findings also demonstrate the need for solutions beyond the use of technology, to employing and deploying solutions from social sciences which deals with behavioral issues and how to address them

Extracellular vesicles and their nucleic acids for biomarker discovery

Extracellular vesicles (EVs) are a heterogenous population of vesicles originate from cells. EVs are found in different biofluids and carry different macromolecules, including proteins, lipids, and nucleic acids, providing a snap shot of the parental cells at the time of release. EVs have the ability to transfer molecular cargoes to other cells and can initiate different physiological and pathological processes. Mounting lines of evidence demonstrated that EVs' cargo and machinery is affected in disease states, positioning EVs as potential sources for the discovery of novel biomarkers. In this review, we demonstrate a conceptual overview of the EV field with particular focus on their nucleic acid cargoes. Current knowledge of EV subtypes, nucleic acid cargo and pathophysiological roles are outlined, with emphasis placed on advantages against competing analytes. We review the utility of EVs and their nucleic acid cargoes as biomarkers and critically assess the newly available advances in the field of EV biomarkers and high throughput technologies. Challenges to achieving the diagnostic potential of EVs, including sample handling, EV isolation, methodological considerations, and bioassay reproducibility are discussed. Future implementation of ‘omics-based technologies and integration of systems biology approaches for the development of EV-based biomarkers and personalized medicine are also considered