This study attempted to multimodally measure mental workload and validate indicators for estimating mental workload. A simulated computer work composed of mental arithmetic tasks with different levels of difficulty was designed and used in the experiment to measure physiological signals (heart rate, heart rate variability, electromyography, electrodermal activity, and respiration), subjective ratings of mental workload (the NASA Task Load Index) and task performance. The indices from electrodermal activity and respiration had a significant increment as task difficulty increased. There were no significant differences between the average heartbeats and the low-frequency/high-frequency ratio among tasks. The classification of mental workload using combined indices as inputs showed that classification models combining physiological signals and task performance can reach satisfying accuracy at 96.4% and an accuracy of 78.3% when just taking physiological indices as inputs. The present study also shows that ECG and EDA signals have good discriminating power for mental workload detection.Practitioner summary The methods used in this study could be applied to office workers and the findings provide preliminary support and theoretical exploration for follow-up early mental workload detection systems, whose implementation in the real world could beneficially impact worker health and company efficiency.Purpose Derivational morphology and compounds are important aspects of academic vocabulary. However, investigation of the development of expressive derivational and compound morphology using language sampling is sparse. https://www.selleckchem.com/products/Dapagliflozin.html This cross-sectional study used three types of language samples to investigate quantitative and qualitative changes in the spontaneous production of derived words and compounds in early and late elementary-age children as a function of age and discourse type. Method Twenty-three children in two age groups (early elementary, n = 12; late elementary, n = 11) participated. Three types of language samples were elicited conversational (10-min conversation with an adult examiner), narrative ("I tell-you tell" narrative with single picture stimulus combined with a story stem narrative), and expository (explanation of how to play a favorite game or sport with text-based topic prompts). Language samples were transcribed using Systematic Analysis of Language Transcripts (Miller & Chapman, 2012) conventilusions This research provided new insights into academic vocabulary development in elementary school-age children. The clinical usefulness of language sampling to quantitatively and qualitatively assess derivational morphology and compounds was demonstrated. Supplemental Material https//doi.org/10.23641/asha.12170373.This commentary provides a timely evidence-based overview on the impact of COVID-19 on dental care and oral health and identifies gaps in protection of patients and staff in dental settings. Oral symptoms are prominent before fever and cough occur. Dental professionals may play an important role in early identification and diagnosis of patients with COVID-19.Recently reported studies considering nonlinearity in the effects of low-dose space radiation have assumed a nontargeted mechanism. To date, few analyses have been performed to assess whether a nontargeted term is supported by the available data. The Harderian gland data from Alpen et al. (published in 1993 and 1994), and Chang et al. (2016) provide the most diversity of ions and energies in a tumor induction model, including multiple high-energy and charge particles. These data can be used to investigate various nonlinearity assumptions against a linear model, including nontargeted effects in the low-dose region or cell sterilization at high doses. In this work, generalized linear models were used with the log complement link function to analyze the binomial data from the studies independently and combined. While there was some evidence of nonlinearity that was best described by a cell-sterilization model, the linear model was adequate to describe the data. The current data do not support the addition of a nontargeted effects term in any model. While adequate data are available in the low-dose region ( less then 0.5 Gy) to support a nontargeted effects term if valid, additional data in the 1-2 Gy region are necessary to achieve power for cell-sterilization analysis validation. The current analysis demonstrates that the Harderian gland tumor data do not support the use of a nontargeted effects term in human cancer risk models.Radiation pneumonitis is a common complication of thoracic irradiation for lung cancer patients. The healthy gut microbiota plays an important role in the local mucosal defense process as well as pulmonary immunomodulation of the host. However, the effect of the intestinal microbiota on radiation pneumonitis is not well understood. Here we studied how the intestinal microbiota affected the host response to radiation pneumonitis. C57BL/6 mice were administered antibiotics to induce disequilibrium in the gut microbiota, and subsequently irradiated. We found that the intestinal microbiota served as a protective mediator against radiation pneumonitis, as indicated by decreased body weight and increased mortality in antibiotic-treated mice. In mice with gut microbiota disequilibrium, more serious pathological lung damage was observed at two and four weeks postirradiation. Fecal microbiota transplantation into irradiated mice led to improvement from radiation-induced inflammation two weeks postirradiation. High-throughput sequencing of murine feces displayed conversion of flora diversity, bacterial composition and community structure in the absence of normal intestinal flora. We filtered the potentially important species among the gut microbiota and considered that the tissue-type plasminogen activator might be involved in the inflammatory process. This study reveals that the gut microbiota functions as a protective regulator against radiation pneumonitis. Additionally, fecal microbiota transplantation was shown to alleviate lung injury in the irradiated model. The protective role of the healthy gut microbiota and the utilization of the gut-lung axis show potential for innovative therapeutic strategies in radiation-induced lung injury.