Propensity of aerosol and droplet creation during oculoplastic procedures: A risk assessment with high-speed imaging amidst COVID-19 pandemic

Purpose:The study uses principles of liquid and gas mechanics to verify and quantify the generation of aerosols in oculoplastic procedures, namely surgery using a scalpel, electrosurgical device, and a mechanized drill.Methods:Surgical techniques were performed ex vivo using the electrosurgical device, scalpel, and mechanized drill on the muscle and bone of commercially available chicken. The liquid and gas dynamics were observed using a high-speed high-resolution Photron SA5 camera (0.125 to 8 ms temporal resolution, 0.016 to 0.054 mm/pixel spatial resolution) and stroboscopic lighting (Veritas 120 E LED Constellation). The analysis was performed using in-house algorithms and ImageJ software.Results:The use of a mechanized drill at 35000 rpm and a 3 mm fluted burr generated aerosol with particle size 50 to 550 microns with a spread of 1.8 m radius. Surgical smoke was generated by an electrosurgical device in both cutting and coagulation modes. Dispersion of the smoke could be controlled significantly by the use of suction, mean smoke spread ratio being 0.065 without suction and 0.002 with use of suction within 2 cm.Conclusion:The quantification of the aerosol generation will help surgeons take practical decisions in their surgical techniques in the pandemic era.     

A decoupler-free simple paper microchip capillary electrophoresis device for simultaneous detection of dopamine,epinephrine and serotonin

This paper demonstrates a new and simplified configuration for capillary electrophoresis-amperometric detection (CE-AD) using a paper microfluidic chip incorporating inexpensive wax printing and screen printing based methods and then used for electrophoretic separation and simultaneous in-channel amperometric detection of three clinically relevant neurochemicals in a single run without using any decouplers. Detection of neurochemicals e.g., dopamine, epinephrine and serotonin is crucial for early prediction of neurological disorders including Parkinson''s, Alzheimer''s, dementia, as well as progressive neuro-psychiatric conditions such as depression, anxiety, as well as certain cardiovascular diseases. The plasma concentrations of such neurochemicals are as important as those present in cerebrospinal fluid (CSF) and can be useful for rapid and convenient biosensing. However, simultaneous detection of such neurochemicals in a complex mixture such as human serum requires their separation prior to detection. With the developed microchip, separation and detection of the neurochemicals were exhibited within 650 seconds without pre-treatment and the procedure was validated with spiked fetal bovine serum samples. Beside this, the developed paper microfluidic chip has potential to be integrated in point-of-care diagnosis with onsite detection ability. Moreover, the use of a straight channel capillary, a screen-printed carbon electrode without decoupler, in-channel amperometric detection and low sample volume requirements (2 μL) are shown as additional advantages.

This paper demonstrates a simplified configuration for capillary electrophoresis-amperometric detection using paper microfluidic chip for separation and simultaneous detection of three clinically relevant neurochemicals without using any decouplers.     

YAP insertion signature in South Asia

A total of 2169 samples from 21 tribal populations from different regions of India were scanned for the Y-chromosome Alu polymorphism. This study reports, for the first time, high frequencies (8-65%) of Y Alu polymorphic (YAP) insertion in northeast Indian tribes. All seven Jarawa samples from the Andaman and Nicobar islands had the YAP insertion, in conformity with an earlier study of Andaman Islanders. One isolated case with haplotype E* was found in Dungri Bhill, a western Indian population, while YAP insertion in northeast India and Andaman tribes was found in association with haplotype D* (M168, M174). YAP insertion frequencies reported in the mainland Indian populations are negligible, according to previous studies. Genetic drift may be the causative factor for the variable frequency of the YAP insertion in the mainland populations, while the founder effect may have resulted in the highest incidence of haplotype D among the Andaman Islanders. The results of YAP insertion and the evidence of previous mtDNA studies indicate an early out of Africa migration to the Andaman and Nicobar Islands. The findings of YAP insertion in northeast Indian tribes are very significant for understanding the evolutionary history of the region.     

Urinary metal concentrations among mothers and children in a Mexico City birth cohort study

Personal care product use is a potential source of metals exposure among children, but studies have been limited. We measured urinary concentrations of 10 metals (aluminum, arsenic [As], barium [Ba], cadmium, cobalt [Co], lead [Pb], manganese [Mn], molybdenum [Mo], nickel, and zinc [Zn]) in third trimester pregnant women (n?=?212) and their children at 8–14 years of age (n?=?250). Demographic factors (child sex, age, socioeconomic status, and maternal education), body mass index (BMI) z-score, and child personal care product use in the 24?h prior to urine collection were examined as predictors of urinary metal concentrations. Metals were detected in 80–100% of urine samples, with significant differences in maternal versus childhood levels. However, metal concentrations were not strongly correlated within or between time points. In linear regression models including all demographic characteristics, BMI z-score, and specific gravity, age was associated with higher Co (6% [95% CI: 2, 10]), while BMI z-score was associated with lower Mo (-6% [95% CI: -11, -1). In addition, significantly higher metal concentrations were observed among users of colored cosmetics (Mo: 42% [95% CI: 1, 99]), deodorant (Ba: 28% [3, 58]), hair spray/hair gel (Mn: 22% [3, 45]), and other toiletries (As: 50% [9, 108]), as well as with an increasing number of personal care products used (As: 7% [3, 11]) after adjustment for child sex, age, total number of products used, and specific gravity. However, significantly lower metal concentrations were noted for users of hair cream (As and Zn: -20% [-36, -2] and -21% [-35, -2], respectively), shampoo (Pb: -40% [-62, -7]), and other hair products (Pb: -44% [-65, -9]). We found that personal care product use may be a predictor of exposure to multiple metals among children. Further research is recommended to inform product-specific exposure source identification and related child health risk assessment efforts.     

Alternative evaluation metrics for risk adjustment methods

Risk adjustment is instituted to counter risk selection by accurately equating payments with expected expenditures. Traditional risk‐adjustment methods are designed to estimate accurate payments at the group level. However, this generates residual risks at the individual level, especially for high‐expenditure individuals, thereby inducing health plans to avoid those with high residual risks. To identify an optimal risk‐adjustment method, we perform a comprehensive comparison of prediction accuracies at the group level, at the tail distributions, and at the individual level across 19 estimators: 9 parametric regression, 7 machine learning, and 3 distributional estimators. Using the 2013–2014 MarketScan database, we find that no one estimator performs best in all prediction accuracies. Generally, machine learning and distribution‐based estimators achieve higher group‐level prediction accuracy than parametric regression estimators. However, parametric regression estimators show higher tail distribution prediction accuracy and individual‐level prediction accuracy, especially at the tails of the distribution. This suggests that there is a trade‐off in selecting an appropriate risk‐adjustment method between estimating accurate payments at the group level and lower residual risks at the individual level. Our results indicate that an optimal method cannot be determined solely on the basis of statistical metrics but rather needs to account for simulating plans' risk selective behaviors.