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Mating can trigger different effects on the physiology and behavior of animals, especially in females. These effects can be either beneficial, such as boosting the immune response, or harmful, such as decreasing survival, for example. Cricket females are among the most used models for understanding these life history trade-offs. We recently demonstrated that mated females have a slight cost of reproduction in survival that could be explained if they differed in resource consumption compared to unmated, being able to avoid putative damages of reproduction on self-maintenance. To test whether mating status modulates feeding behavior and self-maintenance (i.e., immunity), we performed two experimental blocks: In the first, we measure the food intake of both virgin and mated females of Gryllus (Gryllus) assimilis (Fabricius, 1775). In the second, we compared the ability to mount an acute immune response (encapsulation) against a nylon filament implant, a widely used method to challenge the insect immune system. Results showed that mated females did not increase food consumption compared to pre-mating period, however, the virgin group (control) drastically decreased the amount of food ingested. Furthermore, no difference in immune response was found between mating status. As mated females ingested more food than those virgins of the same age, we suggest the feeding behavior (i.e., resource acquisition) as one of the used behavioral strategies to maintain immune ability, high oviposition rates, and survival of mated females of G. (G.) assimilis when fed ad libitum.

Study objectivesSuvorexant is an orexin receptor antagonist approved for treating insomnia at a maximum dose of 20 mg. Phase-3 trials evaluated two age-adjusted (non-elderly/elderly) dose-regimes of 40/30 mg and 20/15 mg with the primary focus on 40/30 mg. We report here results from pooled analyses of the 20/15 mg dose-regime, which was evaluated as a secondary objective in the trials.MethodsPrespecified analysis of pooled data from two identical randomized, double-blind, placebo-controlled, parallel-group, 3-month trials in non-elderly (18-64 years) and elderly (≥ 65 years) patients with insomnia. Patients were randomized to suvorexant 20/15 mg (non-elderly/elderly), suvorexant 40/30 mg (non-elderly/elderly), or placebo; by design, fewer patients were randomized to 20/15 mg. Efficacy was assessed by self-reported and polysomnography (PSG; subset of patients) sleep maintenance and onset endpoints.ResultsSuvorexant 20/15 mg (N = 493 treated) was effective compared to placebo (N = 767 treated) on patient-reported and PSG sleep maintenance and onset endpoints at Night-1 (PSG endpoints) / Week-1 (subjective endpoints), Month-1 and Month-3, except for effects on PSG sleep onset at Month-3. Suvorexant 20/15 mg was generally well tolerated, with 3% of patients discontinuing due to adverse events over 3 months vs. 5.2% on placebo. Somnolence was the most common adverse event (6.7% vs. 3.3% for placebo). There was no systematic evidence of rebound or withdrawal signs or symptoms when suvorexant was discontinued after 3 months of nightly use.ConclusionsSuvorexant 20/15 mg improved sleep onset and maintenance over 3 months of nightly treatment and was generally safe and well tolerated.Clinical trial registrationClinicalTrials.gov trial registration numbers: NCT01097616, NCT01097629.

BackgroundSmartwatches enable physicians to monitor symptoms in patients with knee osteoarthritis, their behavior, and their environment. Older adults experience fluctuations in their pain and related symptoms (mood, fatigue, and sleep quality) that smartwatches are ideally suited to capture remotely in a convenient manner. ObjectiveThe aim of this study was to evaluate satisfaction, usability, and compliance using the real-time, online assessment and mobility monitoring (ROAMM) mobile app designed for smartwatches for individuals with knee osteoarthritis. MethodsParticipants (N=28; mean age 73.2, SD 5.5 years; 70% female) with reported knee osteoarthritis were asked to wear a smartwatch with the ROAMM app installed. They were prompted to report their prior night’s sleep quality in the morning, followed by ecological momentary assessments (EMAs) of their pain, fatigue, mood, and activity in the morning, afternoon, and evening. Satisfaction, comfort, and usability were evaluated using a standardized questionnaire. Compliance with regard to answering EMAs was calculated after excluding time when the watch was not being worn for technical reasons (eg, while charging). ResultsA majority of participants reported that the text displayed was large enough to read (22/26, 85%), and all participants found it easy to enter ratings using the smartwatch. Approximately half of the participants found the smartwatch to be comfortable (14/26, 54%) and would consider wearing it as their personal watch (11/24, 46%). Most participants were satisfied with its battery charging system (20/26, 77%). A majority of participants (19/26, 73%) expressed their willingness to use the ROAMM app for a 1-year research study. The overall EMA compliance rate was 83% (2505/3036 responses). The compliance rate was lower among those not regularly wearing a wristwatch (10/26, 88% vs 16/26, 71%) and among those who found the text too small to read (4/26, 86% vs 22/26, 60%). ConclusionsOlder adults with knee osteoarthritis positively rated the ROAMM smartwatch app and were generally satisfied with the device. The high compliance rates coupled with the willingness to participate in a long-term study suggest that the ROAMM app is a viable approach to remotely collecting health symptoms and behaviors for both research and clinical endeavors.

Abstract Background There has been an increasing interest in understanding the usefulness of wrist-based accelerometer data for physical activity (PA) assessment due to the ease of use and higher user compliance than other body placements. PA assessment studies have relied on machine learning methods which take accelerometer data in forms of variables, or feature vectors. Methods In this work, we introduce automated shape feature derivation methods to transform epochs of accelerometer data into feature vectors. As the first step, recurring patterns in the collected data are identified and placed in a codebook. Similarities between epochs of accelerometer data and codebook’s patterns are the basis of feature calculations. In this paper, we demonstrate supervised and unsupervised approaches to learn codebooks. We evaluated these methods and compared them with the standard statistical measures for PA assessment. The experiments were performed on 146 participants who wore an ActiGraph GT3X+ accelerometer on the right wrist and performed 33 activities of daily living. Results Our evaluations show that the shape feature derivation methods were able to perform comparably with the standard wrist model (F1-score: 0.89) for identifying sedentary PAs (F1-scores of 0.86 and 0.85 for supervised and unsupervised methods, respectively). This was also observed for identifying locomotion activities (F1-scores: 0.87, 0.83, and 0.81 for the standard wrist, supervised, unsupervised models, respectively). All the wrist models were able to estimate energy expenditure required for PAs with low error (rMSE: 0.90, 0.93, and 0.90 for the standard wrist, supervised, and unsupervised models, respectively). Conclusion The automated shape feature derivation methods offer insights into the performed activities by providing a summary of repeating patterns in the accelerometer data. Furthermore, they could be used as efficient alternatives (or additions) for manually engineered features, especially important for cases where the latter fail to provide sufficient information to machine learning methods for PA assessment.

Abstract Background To determine the effectiveness of a low-cost 12-week worksite physical activity intervention targeting a goal of 10,000 steps per day on reducing anthropometric indices, blood pressure indices, and plasma biomarkers of cardiovascular disease (CVD) risk among the employees of a major university. Methods Fifty university employees (n = 43 female, n = 7 male; mean age = 48 ± 10 years) participated in the 12-week physical activity intervention (60 min, 3 day/week). Each session included both aerobic (cardiorespiratory endurance) and muscle-strengthening (resistance) physical activity using existing university facilities and equipment. Anthropometric indices, blood pressure indices, and plasma biomarkers of CVD risk assessed included those for obesity (body mass index), hypertension (systolic blood pressure, SBP; diastolic blood pressure, DBP), dyslipidemia (high-density lipoprotein, HDL; low-density lipoprotein, LDL; total serum cholesterol), and prediabetes (impaired fasting glucose, IFG). Steps per day were assessed using a wrist-worn activity monitor. Participants were given the goal of 10,000 steps per day and categorized as either compliers (≥ 10,000 steps per day on average) or non-compliers (

Di(2-ethylhexyl) phthalate (DEHP) is commonly used as a plasticizer in various industrial and household plastic products, ensuring widespread human exposures. Its routine detection in human bio-fluids and the propensity of its monoester metabolite to activate peroxisome proliferator activated receptor-α (PPARα) and perturb lipid metabolism implicate it as a metabolic disrupter. In this study we evaluated the effects of DEHP exposure on hepatic levels of free CoA and various CoA esters, while also confirming the metabolic activation to CoA esters and partial β-oxidation of a DEHP metabolite (2-ethyhexanol). Male Wistar rats were exposed via diet to 2% (w/w) DEHP for fourteen-days, following which hepatic levels of free CoA and various CoA esters were identified using liquid chromatography-mass spectrometry. DEHP exposed rats showed significantly elevated free CoA and increased levels of physiological, DEHP-derived and unidentified CoA esters. The physiological CoA ester of malonyl-CoA and DEHP-derived CoA ester of 3-keto-2-ethylhexanoyl-CoA were the most highly elevated, at eighteen- and ninety eight-times respectively. We also detected sixteen unidentified CoA esters which may be derivative of DEHP metabolism or induction of other intermediary metabolism metabolites. Our results demonstrate that DEHP is a metabolic disrupter which affects production and sequestration of CoA, an essential cofactor of oxidative and biosynthetic reactions.

Background: For over 20 years, normative data has guided the prescription of physical activity. This data has since been applied to research and used to plan interventions. While this data seemingly provides accurate estimates of the metabolic cost of daily activities in young adults, the accuracy of use among older adults is less clear. As such, a thorough evaluation of the metabolic cost of daily activities in community dwelling adults across the lifespan is needed. Methods: The Metabolic Costs of Daily Activity in Older Adults Study is a cross-sectional study designed to compare the metabolic cost of daily activities in 250 community dwelling adults across the lifespan. Participants (20 + years) performed 38 common daily activities while expiratory gases were measured using a portable indirect calorimeter (Cosmed K4b2). The metabolic cost was examined as a metabolic equivalent value (O2 uptake relative to 3.5 mL min−1 kg−1), a function of work rate – metabolic economy, and a relative value of resting and peak oxygen uptake. Results: The primary objective is to determine age-related differences in the metabolic cost of common lifestyle and exercise activities. Secondary objectives include (a) investigating the effect of functional impairment on the metabolic cost of daily activities, (b) evaluating the validity of perception-based measurement of exertion across the lifespan, and (c) validating activity sensors for estimating the type and intensity of physical activity. Conclusion: Results of this study are expected to improve the effectiveness by which physical activity and nutrition is recommended for adults across the lifespan.

Collaboration is the heart of online learning. Interaction among course participants brings excitement to the online environment and creates knowledge as a group activity. Impediments to active collaboration reduce group, as well as individual, potentialities. Past studies of online discussions have found differences in the style of female and male conversations that could impede the learning process. The conversational styles of female and male students in two online principles of economics classes were analyzed in the present study. The null hypothesis posited no difference in the styles of online discourse between female and male students. The null hypothesis was rejected, implying gender differences in conversational styles. The tone of male postings was more optimistic than the tone of female postings. Female conversations used words revealing social isolation and the rejection of social norms. The paper also discussed the issue of the male X-factor in the principles of economics from a sociolinguistic perspective.

Past studies of online discourse found social presence to be a critical element in the learning process. Social presence connotes the extent to which students perceive themselves as intellectually connected to the other participants in an online dialogue. Impediments to the development of social presence can disrupt knowledge formation as a group activity. This study analyzed differences in the language styles of men and women as one such impediment. When students self-categorize by gender, the expository speaking style of men may crowd out the epistolary style of women, leading women to cognitively disengage from the group learning process. However, in online course environments, where self-categorization is by shared identity, such crowding out is less likely to occur. This study found no evidence of a male crowding-out effect.

Studies of the effect of gender on student performance in the introductory finance course have produced puzzling results. Some find that females are less successful than males while others conclude that gender is inconsequential as a determinant of student performance. Interestingly, no study finds that females outperform males in introductory finance. We hypothesize that these ambiguities occur because previous studies have not considered the distribution of brain-types by gender. Using a dichotomous gender variable in performance models confounds the interpretation of gender by commingling different brain-types in the same gender category. While there are strong reasons to believe that males and females have different brain-types, considerable overlap exists in the statistical distributions. This paper asks which brain-types are more successful in the introductory business finance course and whether these brain-types can be associated with a particular gender. [ABSTRACT FROM AUTHOR]

Examines online discussions using lexical scoring techniques. Suggests that online conversations become more sophisticated as learners interact with each other over the duration of a course, that collaboration among learners fosters the social construction of knowledge and that evidence of such knowledge-building activities is embodied in the tone of the group discussions. (Author/AEF)