Rooneysaleh1981

We sought to understand spatial-temporal factors and socioeconomic disparities that shaped U.S. residents' response to COVID-19 as it emerged.

We mined coronavirus-related tweets from January 23rd to March 25th, 2020. We classified tweets by the socioeconomic status of the county from which they originated with the Area Deprivation Index (ADI). We applied topic modeling to identify and monitor topics of concern over time. We investigated how topics varied by ADI and between hotspots and non-hotspots.

We identified 45 topics in 269,556 unique tweets. Topics shifted from early-outbreak-related content in January, to the presidential election and governmental response in February, to lifestyle impacts in March. High-resourced areas (low ADI) were concerned with stocks and social distancing, while under-resourced areas shared negative expression and discussion of the CARES Act relief package. These differences were consistent within hotspots, with increased discussion regarding employment in high ADI hotsportly focus on the interests of those most disproportionately impacted.

The minimal important change (minimal amount of change vs. baseline that a patient recognizes as a clinical change) and minimum clinically important difference (smallest difference between two measurements that are deemed important by patients) are important values to evaluate the clinical relevance of changes over time and differences between groups. This study aims to establish these values for the KOOS-12 at 1year postoperatively.

KOOS-12 scores were calculated from the full-length KOOS completed by patients undergoing primary TKA preoperatively and at 1year follow up. CBL0137 in vivo Minimal important change (MIC) values were estimated using the anchor-based predictive modeling approach and adjustment for the large proportion of improved patients in the study cohort was performed. The MCID was defined as the difference in the mean change in the KOOS-12 between the 'no improvement' and 'little improvement' groups.

A total of 352 patients (161 male191 female) with an overall mean age of 67.9years (standard deviation (SD) 8.2) and a mean body mass index of 31.4kg/m

(SD 6.3) were included 97.1% of patients reported an important improvement, 1.1% reported being about the same and 1.7% reported being importantly worse. The MIC improvement values were 11.5 for Pain, 13.7 for Function, 5.5 for Quality of Life (QoL) and 14.9 for the total KOOS-12 score. MCID values were 13.5 for Pain, 15.2 for Function, 8.0 for QoL and 11.1 for the total KOOS-12 score.

MIC of 14.9 and MCID of 11.1 established in this study can assist clinicians and researchers in the interpretation of within-group changes (MIC) and differences between groups (MCID) at 1year after TKA.

MIC of 14.9 and MCID of 11.1 established in this study can assist clinicians and researchers in the interpretation of within-group changes (MIC) and differences between groups (MCID) at 1 year after TKA.Over the last few years, the intestine has been extensively studied using in vitro microfluidic systems, commonly known as gut-on-a-chip (GOC) devices. This interest has been due not only to the importance of the intestine's proper functions but also to the relationship that this organ and the microbiota that inhabits it has with the rest of the body's organs. The increased complexity of these in vitro systems, together with the need to improve our understanding of intestinal physiology interdependencies, has led to greater focus on the integration of biosensors within these devices. However, the current number of GOC devices with integrated sensors for monitoring relevant physiological parameters are very limited and demand the use of external analytical techniques that delay the analysis and prevent real-time decision-making. This paper reviews the various materials, technologies, and structures that have been used both for mimicking the physiology of the intestine and monitoring relevant physiological parameters, such as permeability of the gut barrier, dissolved oxygen concentration, cytokines profile and the production of microbial short-chain fatty acids. We also propose alternative biosensing techniques demonstrated in other in vitro and lab-on-a-chip devices that could be translated to GOC models. A critical analysis of the requirements, limitations, and current challenges on the microenvironment replication and monitorization of GOC models is included, with a particular focus on the physiological parameters and biomarkers that should be detected simultaneously in real-time to get a proper framework of the gut function that until now, have not received the necessary attention.The COVID-19 pandemic has caused a significant burden since December 2019 that has negatively impacted the global economy owing to the fact that the SARS-CoV-2 virus is fast-transmitting and highly contagious. Efforts have been taken to minimize the impact through strict screening measures in country borders in order to isolate potential virus carriers. Effective fast-screening methods are thus needed to identify infected individuals. The standard diagnostic methods for screening SARS-CoV-2 virus have always been to perform nucleic acid-based and serological tests. However, with each having drawbacks on producing false results at very early or later stage after symptoms onset, supplementary techniques are needed to back up these tests. Surface-enhanced Raman spectroscopy (SERS) as a detection technique has continuously advanced throughout the years in terms of sensitivity and capability to detect ultralow concentration of analytes ranging from single molecule to pathogens, to present as a highly potential alternative to known sensing methods. SERS technology as a candidate for an alternative and supplementary diagnostic method for the viral envelope of SARS-CoV-2 virus is presented, comparing its pros and cons to the standard methods and what other aspects it could offer that the other methods are not capable of. Factors that contribute to the detection effectivity of SERS is also discussed to show the advantages and limitations of this technique. Despite its promising capabilities, challenges like sources of SARS-CoV-2 virus and its variations, reliable SERS spectra, mass production of SERS-active substrates, and compliance to regulations for wide-scale testing scenario are highlighted.