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Reacting and responding to an external stimulus is an important component of human performance, and they inform us about a participant's neurophysiological capabilities. Our purpose in this study was to determine whether reaction times (REACT), response times (RT), and countermovement jump (CMJ) performance differ when responding to an auditory (AUD) versus visual (VIS) stimulus. Participants were 17 college-aged volunteers (6 females and 11 males; M age = 23.0, SD = 3.4 years; M height = 174.57, SD = 10.37 cm; M body mass = 73.37, SD = 13.48 kg). Participants performed CMJs on force plates immediately upon receiving an AUD or a VIS stimulus. The AUD stimulus was a beep noise, while the VIS stimulus was a light on a screen in front of the participants. We determined REACT for the tibialis anterior (TA), medial gastrocnemius (GM), vastus lateralis (VL), and biceps femoris (BF) muscles to be the amount of time between stimulus onset and the initiation of the muscle's electromyographic (EMG) signal. We determined RT to be the amount of time between stimulus onset and the beginning of the participant's force production. We assessed CMJ performance via ground reaction forces during the unweighting, braking, and propulsive phases of the jump. We quantified EMG amplitude and frequency during each CMJ phase. We found RT to be faster to the AUD versus the VIS stimulus ( p = .007). VL and BF muscles had faster REACT than TA and GM muscles ( p ≤ .007). The AUD stimulus was associated with faster CMJ unweighting phase metrics ( p ≤ .005). Thus, individuals may react and respond faster to an AUD versus VIS stimulus, with limited improvements in their subsequent physical performance., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

RNA sequencing analysis is an important field in the study of extracellular vesicles (EVs), as these particles contain a variety of RNA species that may have diagnostic, prognostic and predictive value. Many of the bioinformatics tools currently used to analyze EV cargo rely on third-party annotations. Recently, analysis of unannotated expressed RNAs has become of interest, since these may provide complementary information to traditional annotated biomarkers or may help refine biological signatures used in machine learning by including unknown regions. Here we perform a comparative analysis of annotation-free and classical read-summarization tools for the analysis of RNA sequencing data generated for EVs isolated from persons with amyotrophic lateral sclerosis (ALS) and healthy donors. Differential expression analysis and digital-droplet PCR validation of unannotated RNAs also confirmed their existence and demonstrates the usefulness of including such potential biomarkers in transcriptome analysis. We show that find-then-annotate methods perform similarly to standard tools for the analysis of known features, and can also identify unannotated expressed RNAs, two of which were validated as overexpressed in ALS samples. We demonstrate that these tools can therefore be used for a stand-alone analysis or easily integrated into current workflows and may be useful for re-analysis as annotations can be integrated post hoc ., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wajnberg, Allain, Roy, Srivastava, Saucier, Morin, Marrero, O’Connell, Ghosh, Lewis, Ouellette and Crapoulet.)

The development of wearable technology, which enables motion tracking analysis for human movement outside the laboratory, can improve awareness of personal health and performance. This study used a wearable smart sock prototype to track foot-ankle kinematics during gait movement. Multivariable linear regression and two deep learning models, including long short-term memory (LSTM) and convolutional neural networks, were trained to estimate the joint angles in sagittal and frontal planes measured by an optical motion capture system. Participant-specific models were established for ten healthy subjects walking on a treadmill. The prototype was tested at various walking speeds to assess its ability to track movements for multiple speeds and generalize models for estimating joint angles in sagittal and frontal planes. LSTM outperformed other models with lower mean absolute error (MAE), lower root mean squared error, and higher R -squared values. The average MAE score was less than 1.138° and 0.939° in sagittal and frontal planes, respectively, when training models for each speed and 2.15° and 1.14° when trained and evaluated for all speeds. These results indicate wearable smart socks to generalize foot-ankle kinematics over various walking speeds with relatively low error and could consequently be used to measure gait parameters without the need for a lab-constricted motion capture system., Competing Interests: The authors declare no competing interests exist., (© The Author(s) 2023.)

Motion capture is the current gold standard for assessing movement of the human body, but laboratory settings do not always mimic the natural terrains and movements encountered by humans. To overcome such limitations, a smart sock that is equipped with stretch sensors is being developed to record movement data outside of the laboratory. For the smart sock stretch sensors to provide valuable feedback, the sensors should have durability of both materials and signal. To test the durability of the stretch sensors, the sensors were exposed to high-cycle fatigue testing with simultaneous capture of the capacitance. Following randomization, either the fatigued sensor or an unfatigued sensor was placed in the plantarflexion position on the smart sock, and participants were asked to complete the following static movements: dorsiflexion, inversion, eversion, and plantarflexion. Participants were then asked to complete gait trials. The sensor was then exchanged for either an unfatigued or fatigued plantarflexion sensor, depending upon which sensor the trials began with, and each trial was repeated by the participant using the opposite sensor. Results of the tests show that for both the static and dynamic movements, the capacitive output of the fatigued sensor was consistently higher than that of the unfatigued sensor suggesting that an upwards drift of the capacitance was occurring in the fatigued sensors. More research is needed to determine whether stretch sensors should be pre-stretched prior to data collection, and to also determine whether the drift stabilizes once the cyclic softening of the materials comprising the sensor has stabilized.

The purpose of this study is to compare masks (non-medical/fabric, surgical, and N95 respirators) on filtration efficiency, differential pressure, and leakage with the goal of providing evidence to improve public health messaging. Masks were tested on an anthropometric face filtration mount, comparing both sealed and unsealed. Overall, surgical and N95 respirators provided significantly higher filtration efficiency (FE) and differential pressure (dP). Leakage comparisons are one of the most significant factors in mask efficiency. Higher weight and thicker fabric masks had significantly higher filtration efficiency. The findings of this study have important implications for communication and education regarding the use of masks to prevent the spread of COVID-19 and other respiratory illnesses, specifically the differences between sealed and unsealed masks. The type and fabric of facial masks and whether a mask is sealed or unsealed has a significant impact on the effectiveness of a mask. Findings related to differences between sealed and unsealed masks are of critical importance for health care workers. If a mask is not completely sealed around the edges of the wearer, FE for this personal protective equipment is misrepresented and may create a false sense of security. These results can inform efforts to educate health care workers and the public on the importance of proper mask fit.

Background: Although participation of patients is essential for completing the training of medical residents, little is known about the relationships among patients' level of knowledge about the role and responsibilities of medical residents, their confidence in residents' abilities, and their acceptance toward receiving care from residents. The study sought to clarify if and how these three patient-resident relationship components are interrelated., Methods: This is a cross-sectional study using a self-administered questionnaire distributed in 2016 to a convenience sample of adult patients (≥ 18 years old) visiting a family medicine teaching clinic. Proportions and chi-square statistics were used to describe and compare groups, respectively., Results: Of the 471 patients who answered the questionnaire, only 28% were found to be knowledgeable about the role of family medicine residents. Between 54% and 83% of patients reported being highly confident in the ability of residents to perform five routine tasks. Of the patients surveyed, 69% agreed to see a resident during their next appointments. Patients with a high level of confidence in residents' abilities were more likely to agree to see a resident during future appointments (p <0.0001). There was no significant association between level of knowledge and either confidence or acceptance., Conclusions: Although the majority of patients had poor knowledge about the role of residents, this was not related to their acceptance of being cared for by residents. A higher level of confidence in residents' ability to perform certain tasks was associated with greater acceptance toward seeing a resident during future appointments., Competing Interests: The authors declare that they do not have conflicts of interest, (© 2021 Babin, Cormier, Champagne, MacIntosh, Saucier, Thibault, Barrieau, Bélanger; licensee Synergies Partners.)