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Abstract Bacteria in the Arthrobacter genus belong to the phylum Actinobacteria and are primarily soil-dwelling. Over 600 bacteriophages infecting Arthrobacter hosts have been isolated and sequenced, and genomic analyses show these phages to be highly diverse with mosaic genome architectures. We describe here a group of 32 Arthrobacter phages grouped in Cluster AZ, isolated on four different Arthrobacter strains all with siphoviral morphologies. The Cluster AZ phages exhibit a spectrum of diversity and can be subdivided into four subclusters. The diversity in minor tail protein and endolysin genes correlates partly with isolation host strain and may be predictive of the host range of these phages. Most of the Cluster AZ phages are temperate, form stable lysogens, and encode an integrase; however, an immunity repressor gene has not been identified. The intracluster diversity was analyzed in-depth at the whole genome level and through individual genes. As more Arthrobacter phages are isolated and analyzed they continue to provide new insights into phage evolution.

This study aims to explore the relationship between four key elements of quality management: teamwork, feedback, motivational barriers, and need analysis, and their contribution to improve innovativeness in the Colombian educational context. Drawing on the concepts of control and learning in the quality management theory and using publicly available responses collected from the Colombian teachers who participated in the TALIS 2018 survey, this research study examines how teachers perceive these elements within their institutions and their potential impact on fostering innovativeness among teachers. The study adopts an empirical approach to analyze these relationships, employing a descriptive and inferential statistical framework to uncover patterns and correlations. By focusing on the school practices in Colombia, the research seeks to provide insights into how quality management practices can drive innovation in educational settings. Findings identify specific patterns in the implementation of these practices and their relationship with innovativeness among teachers, offering actionable recommendations for improving teaching strategies in education to improve quality. This study contributes to the broader understanding of management’s role in teaching and learning, offering valuable implications for policymakers and practitioners in developing countries. The novelty of this work lies in its analyses of TALIS data to assess quality management practices and their direct influence on fostering innovation.

Abstract Reproduction is often more thermally sensitive than survival. Thus, understanding the thermal sensitivity of reproductive interactions is crucial given global warming. However, it is unknown how temperature influences female control over fertilization after mating ( i.e., cryptic female choice). We tested how temperatures relevant to current conditions and climate change projections influence cryptic female choice in a marine fish, Symphodus ocellatus . Under typical conditions, females bias fertilization dynamics to favor dominant males. We find that warmer temperatures decrease female influence on sperm velocity and reduce the expected paternity of dominant males. Our results demonstrate that temperatures relevant to climate change can shift the balance between mate choice and male-male competition. Thus, climate change may influence sexual selection, leading to evolutionary changes in reproductive traits.

Insertion or deletion of one or two base pairs within a coding region causes a frameshift, which has the potential to generate neoepitopes (InDel-generated neoepitopes) that lack a self-counterpart and are entirely novel. Despite the obvious appeal of InDel-generated neoepitopes, and the demonstration of such candidate neoepitopes that can elicit a CD8 T-cell response, no InDel-generated neoepitopes that actually control tumors in vivo have been reported thus far. Here, in a mouse colon carcinoma line, we identify 11 InDels, only one of which generates a neoepitope that elicits tumor control in vivo in models of prophylaxis as well as therapy. Although this neoepitope has no self-counterpart, it has a low affinity (IC50 33,937.60 nM) for its MHC I allele. Despite its low affinity for MHC I, this neoepitope elicits antitumor activity in vivo through CD8 T cells. Furthermore, CD8 T cells elicited by this InDel-generated neoepitope, like the neoepitopes created by point mutations, show notably less exhaustion than classical immunogenic epitopes. Ironically, this InDel-generated neoepitope follows the same rules as noted for most of the tumor control-mediating neoepitopes generated by point mutations that have a poor affinity for MHC I alleles.

Background College students are vulnerable to setting long-term trajectories of low physical activity (PA) but are reachable via mobile health fitness tracking (eg, mobile health step counting) and interpersonal support tailored to the college community. However, no studies have statistically isolated the appeal and influence of these intra- and interpersonal components in college-based PA interventions. Objective This study retrospectively examined a college-based PA promotion program at a northeast US public university during the COVID-19 pandemic to (1) test the impact of student status on the use of intervention components and (2) determine whether such use was associated with successful retention and goal achievement in the program. Methods The university used a commercial platform for a 30-day PA promotion program during April 2021 with intrapersonal (step-tracker syncing, education, self-monitoring, and motivational messaging) and interpersonal (friend interactions and team games) components. App use was operationalized as intrapersonal (frequency of opening app, education, and self-monitoring) and interpersonal (friends made in-app and team affiliation and size). Results Campus-wide emails elicited sign-up by 156 undergraduate students, 57 graduate students, and 126 faculty and staff members. Objective 1 yielded the following results: undergraduates used the app less frequently (median 0.8, IQR 0.4-1.7 times per day) than other groups (graduate students: median 1.4, IQR 0.7-2.7 times per day; P=.01; faculty: median 1.3, IQR 0.7-2.7 times per day, H2=14.5; P=.001) but made the same number of friends (median 1-2) and teammates (median 8-9; P=.77 for friends and P=.93 for teammates). Objective 2 yielded the following results: most participants (313/335, 93.4%; 95% CI 90%-96%) were retained for the first 7 days, but by 30 days, retention dropped, most notably for undergraduate students (82/154, 53.2%; 95% CI 45%-61%), followed by graduate students (39/56, 70%; 95% CI 56%-81%) and faculty and staff (93/125, 74.4%; 95% CI 66%-82%; χ22=12.6; P<.001). Retention was associated with app engagement frequency (model hazard ratio 0.56, 95% CI 0.43-0.72; P<.001) and affiliation with a team having high median app engagement and a large size (intracluster correlation coefficient 0.064, 95% CI 0.001-0.164, P=.05). Meeting a daily step goal was associated with app engagement frequency (β=.72, SE=0.21; P=.001), number of friends (β=.40, SE 0.20; P=.04), and an initial motive of maintaining or increasing (rather than starting) PA (β=.99, SE=0.21; P<.001). Conclusions College students, compared with faculty and staff, used the app less frequently, used the app for a shorter duration before abandonment, and met the step goal on fewer days. Engagement with the program was associated with longer retention and better PA outcomes, which were critically modified by the interpersonal engagement. These findings suggest that college students using virtual PA support during times of physical isolation could benefit from more tailored implementation strategies (eg, timed prompts and team reassignments).

ABSTRACT Migratory fishes are renowned for their ability to home to natal streams for spawning. Learned olfactory cues play a critical role in natal homing of Pacific salmon and other fishes, but the underlying chemical signature of streams remains poorly understood after decades of study. The molecules that convey a stream‐specific odour must differ among sites but remain constant over time. Among leading odorant candidates are amino acids; however, little research has assessed the spatial and temporal variability of amino acid profiles in streams. We report a comprehensive chemical study of dissolved amino acids as potential olfactory cues for homing by migratory fish. Specifically, we profiled amino acids in water from 23 streams in the upper Laurentian Great Lakes basin over 2 years. We investigated variation in amino acid profiles (1) among regions and rivers within a year, (2) between years and (3) among sites and across the seasons of migration and early life history within a stream. Liquid‐chromatography tandem mass spectrometry revealed nanomolar concentrations for most of the 20 L‐amino acids measured, above the levels detectable by studied migratory fishes. Moreover, amino acid profiles were temporally stable between 2 years and across an annual season from adult spawning migration through offspring early‐life development within a stream. However, spatial differences in amino acid profiles were evident primarily over large geographic distances (among regions) but not among tributaries within regions or among sites within a stream. Collectively, our results indicate dissolved amino acids may be consistent components of rivers' odorant profiles but suggest additional molecules are likely important for natal homing of migratory fishes to specific spawning sites. We suggest that future studies consider the combined importance of amino acids and molecules from other chemical classes. Understanding the chemical basis of olfactory‐guided natal homing is especially important as human activities could alter the odorant profiles of streams and thereby disrupt fish migrations and negatively impact population recruitment.

Proportional-Integral-Derivative (PID) controllers are prominent due to their superior functionality and ease of use. However, optimizing their parameters presents a significant challenge. Adjusting parameters must be done carefully and cautiously because improper calibration can compromise the system’s stability. Although classic tuning techniques, such as the Ziegler-Nichols (ZN), are frequently employed, their efficiency is restricted due to the intricate and ever- changing nature of the systems, often leading to parameter settings that could be more optimal. Therefore, the need for a more accurate parameter-tuning technique is urgent. Various optimization strategies are used to fine-tune parameters with more precision. These methods include Gray Wolf Optimization (GWO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO). These methods are applied to fine-tune the PID parameters for a Direct Current (DC) motor to achieve optimal performance, and a comparative analysis of the results is conducted. Various fitness functions encompass performance metrics such as rise time, overshoot, peak time, settling time, and mean square error (MSE). These metrics are incorporated into the corresponding optimization approaches to quantitatively assess the controller’s performance. Various test cases have been utilized and the GA outperforms other algorithms ranging from 17% to 28% where rise time, settling time, and MSE are significant in the fitness function.