Does Gender Minority Professional Experience Impact Employment Discrimination? Two Résumé Experiments

We sought to examine perceived gender identity, perceived co-worker discomfort, and salary recommendations for youth counselors with transgender-related work experience. In two experiments conducted in 2016 and 2017, we randomized participants to view 1 of 2 résumés with varying work experience at a camp for transgender youth or a generic youth camp. Study 1 participants were 274 adult festivalgoers at a lesbian, gay, bisexual, and transgender pride festival. Study 2 participants were 296 employed, heterosexual adults aged 35-60 from an online survey panel. In Study 1, viewing the résumé with transgender experience resulted in a statistically significantly higher likelihood of reporting the applicant was gender minority than cisgender (adjusted odds ratio = 3.76, 95% confidence interval [1.32, 10.72],   p = .01), higher but not a statistically significant level of co-worker discomfort (aOR = 1.39, 95% CI [0.83, 2.32], p = .22), and, although not statistically significant, a $2,605 higher salary (95$604, - $5,814], p = .11). In Study 2, we found a statistically significantly greater likelihood of reporting the applicant was gender minority than cisgender (OR = 2.56, 95$1,374 higher salary (95% CI [-$1,931,$4,679], p = .41). Our results indicate the potential for stigma by association for professionals working with marginalized groups and suggest potential pathways through which employment discrimination may exacerbate existing inequities for gender minority people

Novel CYP2C9 Promoter Variants and Assessment of Their Impact on Gene Expression □ S

ABSTRACT There are a considerable number of reports identifying and characterizing genetic variants within the CYP2C9 coding region. Much less is known about polymorphic promoter sequences that also might contribute to interindividual differences in CYP2C9 expression. To address this problem, approximately 10,000 base pairs of CYP2C9 upstream information were resequenced using 24 DNA samples from the Coriell Polymorphism Discovery Resource. Thirty-one single-nucleotide polymorphisms (SNPs) were identified; nine SNPs were novel, whereas 22 were reported previously. Using both sequencing and multiplex single-base extension, individual SNP frequencies were determined in 193 DNA samples obtained from unrelated, selfreported Hispanic Americans of Mexican descent, and they were compared with similar data obtained from a non-Latino white cohort. Significant interethnic differences were observed in several SNP frequencies, some of which seemed unique to the Hispanic population. Analysis using PHASE 2.1 inferred nine common (Ͼ1%) variant haplotypes, two of which included the g.3608CϾT (R144C) CYP2C9*2 and two the g.42614AϾC (I359L) CYP2C9*3 SNPs. Haplotype variants were introduced into a CYP2C9/luciferase reporter plasmid using site-directed mutagenesis, and the impact of the variants on promoter activity assessed by transient expression in HepG2 cells. Both constitutive and pregnane X receptor-mediated inducible activities were measured. Haplotypes 1B, 3A, and 3B each exhibited a 65% decrease in constitutive promoter activity relative to the reference haplotype. Haplotypes 1D and 3B exhibited a 50% decrease and a 40% increase in induced promoter activity, respectively. These data suggest that genetic variation within CYP2C9 regulatory sequences is likely to contribute to differences in CYP2C9 phenotype both within and among different populations

Intelligent Sensors and Monitoring System for Low-Cost Phototherapy Light for Jaundice Treatment.

A prototype of a low-cost phototherapy light system (LPLS) was deployed by the Ateneo Innovation Center (AIC) at a public hospital in Metro Manila, Philippines. It underwent clinical investigation for two years under the supervision of licensed physicians in a public tertiary hospital. This paper presents the process of upgrading the LPLS in order to enhance capabilities and improve efficiency yet remain affordable. The following features were added: (1) a visual and auditory monitoring system in order to remotely oversee the infant from the nurse station; (2) an automation system that stores data about the device\u27s light intensity and bulb temperature and records ambient humidity; (3) an alarm system that activates the warning lights if sensor readings are in critical level and if the bulbs need to be replaced; and (4) a time setting to manually set the time of operation and automatically turn-off the device as programmed The upgrades increased the system\u27s cost but it remained cheaper than the ones commercially available. For deployment in remote or off-grid hospitals, the system was equipped with a solar-powering provision

Design and Development of A-vent: A Low-Cost Ventilator with Cost-Effective Mobile Cloud Caching and Embedded Machine Learning

We designed and developed a low-cost mechanical ventilator prototype that meets the government\u27s minimum viable standards. We substituted alternative off-the-shelf food-grade for the medical-grade parts and improvised some components for our prototype. We cleaned the air from the oxygen tanks and compressors before going to the lung test bag. We designed a solar-powered battery system that can run electronic components for a fail-safe operation. We demonstrated how the AIC Near Cloud system can store air flow rate and air pressure data which were generated during the prototype\u27s operation. We used Embedded Machine Learning in sensors and data processing by using flow and pressure sensors to provide accumulated data that can be utilized in training the machine learning software. The patient-ventilator asynchrony detection model was tested using data generated from the emulated ventilator waveform events that mimic the patient-ventilator asynchrony. A different compression pattern was applied to the test lung and results showed the training, validation, and model testing that yielded 98.7%, 99.1%, and 97.18 percent accuracy, respectively. Having demonstrated that the Tiny ML can be trained to detect anomalies from several data points, we realized the feasibility of detecting ventilator patient vibration anomaly, and unusual acoustic signatures, among others, for future works