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Zinc (Zn) and Zn alloys have been studied as potential materials for bioresorbable stents (BRSs) in the last decade due to their favorable biodegradability and biocompatibility. However, most Zn alloys lack the necessary combination of strength, ductility, fatigue resistance, corrosion rate (CR), and thermal stability needed for such applications. In this study, nanoparticles made of tungsten carbide (WC) were successfully incorporated into Zn alloyed with 0.5 wt % magnesium (Mg) and evaluated for their suitability for BRS applications. Specifically, the resulting Zn-0.5Mg-WC nanocomposite's microstructure, mechanical properties, in vitro CR, and thermal stability were evaluated. The Zn-0.5Mg-WC nanocomposite had excellent mechanical strength [ultimate tensile strength (UTS) > 250 MPa], elongation to failure (>30%), and a suitable in vitro CR (∼0.02 mm/y) for this clinical application. Moreover, the Zn-0.5Mg-WC nanocomposite survived 10 million cycles of tensile loading (stress ratio, R = 0.053) when the maximum stress was 80% of the yield stress. Its ductility was also retained during a 90-day thermal stability study, indicating an excellent shelf life. Stent prototypes were fabricated using this composition and were successfully deployed during bench testing without fracture. These results show that the Zn-0.5Mg-WC nanocomposite is a promising material for BRS applications. In vivo studies are underway to validate both biocompatibility, stent function, and degradation.

This study introduces a flexible, adhesive-integrated electrode array that was developed to enable non-invasive monitoring of cervical nerve activity. The device uses silver-silver chloride as the electrode material of choice and combines it with an electrode array consisting of a customized biopotential data acquisition unit and integrated graphical user interface (GUI) for visualization of real-time monitoring. Preliminary testing demonstrated this electrode design can achieve a high signal to noise ratio during cervical neural recordings. To demonstrate the capability of the surface electrodes to detect changes in cervical neuronal activity, the cold-pressor test (CPT) and a timed respiratory challenge were employed as stressors to the autonomic nervous system. This sensor system recording, a new technique, was termed Cervical Electroneurography (CEN). By applying a custom spike sorting algorithm to the electrode measurements, neural activity was classified in two ways: (1) pre-to-post CPT, and (2) during a timed respiratory challenge. Unique to this work: (1) rostral to caudal channel position-specific (cephalad to caudal) firing patterns and (2) cross challenge biotype-specific change in average CEN firing, were observed with both CPT and the timed respiratory challenge. Future work is planned to develop an ambulatory CEN recording device that could provide immediate notification of autonomic nervous system activity changes that might indicate autonomic dysregulation in healthy subjects and clinical disease states.

Sleep difficulties, particularly symptoms of insomnia and circadian disruption, are among the primary complaints of gynecologic cancer survivors before, during, and after treatment. Moreover, difficulty sleeping has been linked to poorer health-related quality of life and elevated symptom burden in this population. Although leading behavioral sleep interventions have demonstrated efficacy among cancer survivors, up to 50% of survivors are non-adherent to these treatments, likely because these interventions require labor-intensive behavior and lifestyle changes. Therefore, there is a need for more effective and acceptable approaches to diminish sleep disturbance among cancer survivors. This manuscript describes the methodology of a two-part study guided by the Multiphase Optimization Strategy (MOST) framework to identify a streamlined behavioral sleep intervention for gynecologic cancer survivors. Three candidate intervention components previously shown to decrease sleep disturbance will be evaluated, including sleep restriction, stimulus control, and systematic bright light exposure. Participants will be adult women with a history of non-metastatic gynecologic cancer who have completed primary treatment and who report current poor sleep quality. Fifteen participants will be recruited for Part 1 of the study, which will utilize qualitative methods to identify barriers to and facilitators of intervention adherence. Results will inform changes to the delivery of the candidate intervention components to promote adherence in Part 2, where 80 participants will be recruited and randomized to one of eight conditions reflecting every possible combination of the three candidate intervention components in a full factorial design. Participants will complete assessments at baseline, post-intervention, and 3-months post-intervention. Part 2 results will identify the combination of candidate intervention components that yields the most efficacious yet efficient 6-week intervention for diminishing sleep disturbance. This is the first known study to apply the MOST framework to optimize a behavioral sleep intervention and will yield a resource-efficient treatment to diminish sleep disturbance, improve health-related quality of life, and decrease symptom burden among gynecologic cancer survivors. ClinicalTrials.gov Identifier: NCT05044975.

Human reinforcement learning (RL) is characterized by different challenges. Exploration has been studied extensively in multi-armed bandits, while planning has been investigated in multi-step decision tasks. More recent work has added structured rewards to study generalization. However, past studies have often focused on a single one of these aspects, making it hard to compare results. We propose a generative model for constructing correlated trees to provide a unified and scalable method for studying exploration, planning, and generalization in a single task. In an online experiment, we find that people use structure (when provided) to generalize and perform uncertainty-directed exploration, with structure helping more in larger environments. In environments without structure, exploration becomes more random and more planning is needed. All behavioral effects are captured in a single model with recoverable parameters. In conclusion, our results connect past research on human RL in one framework using correlated trees.

Theories of intrinsic motivation describe how behavior is driven by inherent satisfaction beyond only rewarding outcomes. One computational theory quantifies “fun” as the pleasure derived from improving one’s model of the environment. Here, we refine and test this theory by predicting maximal fun occurs when learning progress is also maximal, corresponding to a balance between ability (or knowledge) and task difficulty. Across multiple natural data sets (e.g., “Super Mario Maker”, “Trackmania”, or “Robozzle”), we confirm our prediction that human judgments of fun are highest at intermediate levels of difficulty. We provide further evidence through a number guessing experiment, where we manipulated the learnability of the environment by controlling the variance of the numbers that could be guessed. Both participants’ engagement and model-based analyses confirmed our predictions. Beyond simply exploiting maximal rewards or exploring maximal uncertainty, the constraints of learnability require a balance between challenge and ease.

We developed an innovative 3D printed casing that incorporates a lateral-flow immunoassay, dehydrated signal enhancement reagents, and a sealed buffer chamber. With only the push of a button for signal enhancement, our device detected the SARS-CoV-2 N-protein in 40 min at concentrations as low as 0.1 ng mL-1 in undiluted serum.

This study was the first to investigate the prospective effects of failure mindsets on implicit theories of intelligence (ITI), whose profound effects on learning, motivation, and academic achievement have found increasing support. Participants were 240 Chinese university students (180 females, M[subscript age] = 19.13) who completed a baseline and a 1-year follow-up survey. The cross-lagged panel model supported the study's hypothesis that students' perception of their parents' view of failure as debilitating at baseline predicted their own failure-is-debilitating mindset and entity theory of intelligence at follow-up. However, students' failure-is-debilitating mindset at baseline did not predict their entity theory of intelligence at follow-up. A reciprocal relationship was found between students' perception of their parents' failure-is-debilitating mindset and their entity theory of intelligence. We recommend programs be implemented to educate parents of the value of failure and how their conveying positive views of failure can be constructive to students' trajectory of learning and intellectual growth.

The high prevalence of problematic smartphone use (PSU) among adolescents has raised public concern due to its negative health consequences, such as sleep problems. The current longitudinal study aimed to investigate the prospective effects of PSU and fear of missing out (FoMO) on both bedtime procrastination and sleep duration among Chinese adolescents. Three hundred eighteen Chinese high school students (M.sub.age = 16.92, SD = 0.67) completed an anonymous questionnaire at both baseline and 6-month follow-up. The results of the analyses showed that both PSU and FoMO were correlated with greater bedtime procrastination and shorter sleep duration. However, path analysis revealed that only baseline PSU ([beta] = .11, p < .05) but not baseline FoMO ([beta] = .05, p > .05) predicted bedtime procrastination at the 6-month follow-up, while sleep duration assessed at the follow-up survey was significantly predicted by only baseline bedtime procrastination ([beta] = -.16, p < .01). Our findings support the adverse effect of PSU on adolescent sleep health, while that of FoMO may not be as direct as expected. Future studies with three or more waves of data collection are recommended for properly testing the prospective, probably indirect, effects of PSU, FoMO, and other emotional or cognitive factors on sleep quality., Author(s): Meng Xuan Zhang [sup.1] [sup.2] , Hui Zhou [sup.1] [sup.2] , Hong Mian Yang [sup.1] [sup.2] , Anise M. S. Wu [sup.1] [sup.2] Author Affiliations: (1) grid.437123.0, 0000 0004 [...]

Aberrant lineage commitment of mesenchymal stem cells (MSCs) in marrow contributes to abnormal bone formation due to reduced osteogenic and increased adipogenic potency. While several major transcriptional factors associated with lineage differentiation have been found during the last few decades, the molecular switch for MSC fate determination and its role in skeletal regeneration remains largely unknown, limiting creation of effective therapeutic approaches. Tribbles homolog 3 (Trb3), a member of tribbles family pseudokinases, is known to exert diverse roles in cellular differentiation. Here, we investigated the reciprocal role of Trb3 in the regulation of osteogenic and adipogenic differentiation of MSCs in the context of bone formation, and examined the mechanisms by which Trb3 controls the adipo-osteogenic balance. Trb3 promoted osteoblastic commitment of MSCs at the expense of adipocyte differentiation. Mechanistically, Trb3 regulated cell-fate choice of MSCs through BMP/Smad and Wnt/β-catenin signals. Importantly, in vivo local delivery of Trb3 using a novel gelatin-conjugated caffeic acid-coated apatite/PLGA (GelCA-PLGA) scaffold stimulated robust bone regeneration and inhibited fat-filled cyst formation in rodent non-healing mandibular defect models. These findings demonstrate Trb3-based therapeutic strategies that favor osteoblastogenesis over adipogenesis for improved skeletal regeneration and future treatment of bone-loss disease. The distinctive approach implementing a scaffold-mediated local gene transfer may further broaden the translational use of targeting specific therapeutic gene related to lineage commitment for clinical bone treatment.

Generating cardiomyocytes (CMs) from human induced pluripotent stem cells (hiPSCs) has represented a significant advance in our ability to model cardiac disease. Current differentiation protocols, however, have limited use due to their production of heterogenous cell populations, primarily consisting of ventricular-like CMs. Here we describe the creation of two chamber-specific reporter hiPSC lines by site-directed genomic integration using CRISPR-Cas9 technology. In the MYL2-tdTomato reporter, the red fluorescent tdTomato was inserted upstream of the 3' untranslated region of the Myosin Light Chain 2 (MYL2) gene in order faithfully label hiPSC-derived ventricular-like CMs while avoiding disruption of endogenous gene expression. Similarly, in the SLN-CFP reporter, Cyan Fluorescent Protein (CFP) was integrated downstream of the coding region of the atrial-specific gene, Sarcolipin (SLN). Purification of tdTomato+ and CFP+ CMs using flow cytometry coupled with transcriptional and functional characterization validated these genetic tools for their use in the isolation of bona fide ventricular-like and atrial-like CMs, respectively. Finally, we successfully generated a double reporter system allowing for the isolation of both ventricular and atrial CM subtypes within a single hiPSC line. These tools provide a platform for chamber-specific hiPSC-derived CM purification and analysis in the context of atrial- or ventricular-specific disease and therapeutic opportunities.

A key question individuals face in any social learning environment is when to innovate alone and when to imitate others. Previous simulation results have found that the best performing groups exhibit an intermediate balance, yet it is still largely unknown how individuals collectively negotiate this balance. We use an immersive collective foraging experiment, implemented in the Minecraft game engine, facilitating unprecedented access to spatial trajectories and visual field data. The virtual environment imposes a limited field of view, creating a natural trade-off between allocating visual attention towards individual search or to look towards peers for social imitation. By analyzing foraging patterns, social interactions (visual and spatial), and social influence, we shine new light on how groups collectively adapt to the fluctuating demands of the environment through specialization and selective imitation, rather than homogeneity and indiscriminate copying of others.