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Self-rerouting sensor network for electronic skin resilient to severe damage
Non-linear relationship between built environment and non-motorized travel efficiency under the traffic micro-circulation model
The built environment is an important determinant of travel demand and mode choice. Studying the relationship between the built environment and transportation usage can support and assist traffic policy interventions. Previous studies often assumed that this relationship is linear; however, the impact of the built environment on non-motorized travel efficiency may be more complex than the typically modeled linear relationships. This paper focuses on the core area of Chengguan District in Lanzhou City, utilizing multi-source big data including POI, OpenStreetMap, street view images, and built environment data. Using ArcGIS spatial analysis tools combined with the Extreme Gradient Boosting (XGBoost) model, we analyze the non-linear influence mechanisms and threshold effects of the built environment on non-motorized travel efficiency and establish a ranking of the relative importance of all built environment factors. The results indicate that factors such as the branch road/street, land-use mix, land-use density, neighborhood entrance/exit density, bus station density, and dead-end-roads density are key influences on non-motorized travel efficiency. Additionally, based on the non-linear thresholds presented in the partial dependence plots for built environment factors, this paper proposes optimization strategies for small-scale road network patterns, mixed land use, and bus-friendly environments, providing effective threshold ranges and decision-making references for urban planning and traffic management.
Mendelian randomization analysis does not support a causal influence between lipoprotein(A) and immune-mediated inflammatory diseases
SLC29A1 and SLC29A2 are human nicotinamide cell membrane transporters
The impact of visual fidelity on screen-based virtual reality food choices: A randomized pilot study
Objective To understand the impact of fidelity and perceived realism on virtual reality food choices, and task motivation, engagement, and interest. Design Randomized controlled trial. Setting Online. Participants 84 participants recruited from Amazon Mechanical Turk. Intervention Participants were randomly assigned to either a high- (n = 43) or a low- (n = 41) visual fidelity environment and were asked to select foods to have a meal with a friend. Main outcome measures Food choice, motivation of food choices, engagement, and interest. Analysis Simple linear regressions between visual fidelity and perceived realism, and log-linear regressions for visual fidelity or perceived realism on either motivation, interest, or engagement. Poisson models between visual fidelity or perceived realism, and food selections. Results Manipulating visual fidelity was not associated with perceived realism, motivation, interest, or engagement in the food selection task. Perceived realism increased motivation by 0.3% (SE 0.056; p = 0.022), interest by 1.4% (SE 0.002; p<0.001), and engagement by 0.9% (SE 0.001; p<0.001) in the food selection task. High visual fidelity decreased the total number of foods selected (B = 0.216; CI (-0.384; -0.047); p = 0.012). Conclusion and implications Perceived realism, but not visual fidelity, is important for task related factors like motivation, engagement, and interest. Visual fidelity may influence some food selections.
Author Correction: Examinations of effects of socio-demographic features and disease-related data of patients with hemodialysis on the quality of life
Oncolytic reprogramming of tumor microenvironment shapes CD4 T-cell memory via the IL6ra-Bcl6 axis for targeted control of glioblastoma
Abstract Oncolytic viruses (OVs) emerge as a promising cancer immunotherapy. However, the temporal impact on tumor cells and the tumor microenvironment, and the nature of anti-tumor immunity post-therapy remain largely unclear. Here we report that CD4+ T cells are required for durable tumor control in syngeneic murine models of glioblastoma multiforme after treatment with an oncolytic herpes simplex virus (oHSV) engineered to express IL-12. The upregulated MHCII on residual tumor cells facilitates programmed polyfunctional CD4+ T cells for tumor control and for recall responses. Mechanistically, the proper ratio of Bcl-6 to T-bet in CD4+ T cells navigates their enhanced anti-tumor capacity, and a reciprocal IL6ra-Bcl-6 regulatory axis in a memory CD4+ T-cell subset, which requires MHCII signals from reprogrammed tumor cells, tumor-infiltrating and resident myeloid cells, is necessary for the prolonged response. These findings uncover an OV-induced tumor/myeloid-CD4+ T-cell partnership, leading to long-term anti-tumor immune memory, and improved OV therapeutic efficacy.
The PainSMART project: Protocol for a research program on effectiveness, mechanisms of effect and patient-practitioner experiences of the PainSMART-strategy as an adjunct to usual primary care physiotherapy management for musculoskeletal pain
Background Musculoskeletal pain (MSKP) disorders entail a significant burden for individuals and healthcare systems. The PainSMART-strategy has been developed aiming to reduce divergences between patients and healthcare practitioners in their understanding of MSKP by providing a shared basis for communication and to facilitate patients’ self-management of MSKP. The objective of the PainSMART-project is to evaluate the effects of the PainSMART-strategy as an adjunct to usual physiotherapy management compared to usual physiotherapy management alone. Methods The PainSMART-project is a research program with a collective suite of studies utilising mixed methods, centred around a randomised controlled trial (ClinicalTrials.gov NCT06187428). Subjects: Adults (18 years or older) seeking primary care for MSKP who are triaged and booked for an initial physiotherapy consultation at five primary care physiotherapy departments within the Swedish public healthcare regions of Östergötland and Jönköping. A total of 490 subjects will be randomised to receive one of two possible interventions. Interventions Both groups will receive usual physiotherapy management for benign MSKP. The intervention group will also receive the PainSMART-strategy consisting of an educational film, reflection and reinforcement of the film’s key messages prior to the initial physiotherapy consultation and a patient-practitioner discussion based on the film. Outcome The primary outcome is 1) between group mean change over time from baseline to 24 hours post initial physiotherapy consultation and baseline to 3 months regarding self-reported average pain intensity and pain self-efficacy. Secondary outcomes include similar measurements for MSKP illness perception, reassurance of benign nature, pain coping, physical activity, analgesic medication use, sick leave, healthcare use and direct healthcare costs. Physiotherapist and patient reported experience measures and qualitative evaluation of the effects of the PainSMART-strategy on communication at the initial physiotherapy consultation will also be explored. Discussion This study will investigate potential added effects of PainSMART-strategy upon usual primary care physiotherapy for MSKP.
A thin, wideband transmissive cross polarization converter
Fire-driven disruptions of global soil biochemical relationships
Correction: Exome sequencing reveals IFT172 variants in patients with non-syndromic cholestatic liver disease
Risk factor assessment of prediabetes and diabetes based on epidemic characteristics in new urban areas: a retrospective and a machine learning study
In situ osteogenic activation of mesenchymal stem cells by the blood clot biomimetic mechanical microenvironment
Correction: Factors affecting the relapse of maxilla and soft tissues of nose, upper lip and velopharyngeal structures after maxillary advancement in cleft patients
A study on the effect of blue light on kidney stone formation in rats via the brain-kidney axis
Machine learning photodynamics decode multiple singlet fission channels in pentacene crystal
Abstract Crystalline pentacene is a model solid-state light-harvesting material because its quantum efficiencies exceed 100% via ultrafast singlet fission. The singlet fission mechanism in pentacene crystals is disputed due to insufficient electronic information in time-resolved experiments and intractable quantum mechanical calculations for simulating realistic crystal dynamics. Here we combine a multiscale multiconfigurational approach and machine learning photodynamics to understand competing singlet fission mechanisms in crystalline pentacene. Our simulations reveal coexisting charge-transfer-mediated and coherent mechanisms via the competing channels in the herringbone and parallel dimers. The predicted singlet fission time constants (61 and 33 fs) are in excellent agreement with experiments (78 and 35 fs). The trajectories highlight the essential role of intermolecular stretching between monomers in generating the multi-exciton state and explain the anisotropic phenomenon. The machine-learning-photodynamics resolved the elusive interplay between electronic structure and vibrational relations, enabling fully atomistic excited-state dynamics with multiconfigurational quantum mechanical quality for crystalline pentacene.
Correction: Neural recordings can differentiate between spontaneously metastasizing melanomas and melanomas with low metastatic potential
High sensitivity flexible strain sensor for motion monitoring based on MWCNT@MXene and silicone rubber
Abstract Research on flexible strain sensors has grown rapidly and is widely applied in the fields of soft robotics, body motion detection, wearable sensors, health monitoring, and sports. In this study, MXene was successfully synthesized in powder form and combined with multi-walled carbon nanotube (MWCNT) to develop MWCNT@MXene conductive network-based flexible strain sensors with silicone rubber (SR) substrate. Combining MWCNTs with MXene as a conductive material has been shown to significantly improve the sensor performance, due to MXene’s high conductivity properties that strengthen the MWCNT conductive pathway, increase sensitivity, and improve sensor stability. The sensor is fabricated by a sandwich method consisting of three layers, which enables more accurate and reliable detection of strain changes. The main innovation of this research is the utilization of MWCNT@MXene as a conductive material that optimizes the performance of flexible strain sensors, overcomes the limitations of previous materials, and makes it a more effective solution for long-term applications. Furthermore, the sensor was evaluated to test its performance through sensitivity, linearity, response time, and durability tests. The results showed that the sensor exhibited excellent performance with a high sensitivity of 39.97 over a strain range of 0-100% and excellent linearity (0.99) over a strain of 0–50%. The sensor also has a fast response time of about 70 ms, it also has good stability during low (1–5%) and high (20–100%) strain cycle testing and can withstand up to 1200 loading and unloading cycles. In addition, the sensor effectively detects a wide range of body movements, including finger, wrist and knee movements. These findings show that the electromechanical properties of strain sensors are significantly improved through the use of MWCNT@MXene as a conductive material, so these sensors are considered a promising solution for applications in wearables and body motion monitoring.