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Sleep can affect nonalcoholic fatty liver disease (NAFLD). We investigated the association between sleep duration, sleep quality, and NAFLD. From January to December 2018, 1,073 patients (age: 37.94 ± 10.88, Body Mass Index (BMI): 22.85 ± 3.27) were enrolled. Pittsburgh Sleep Quality Index Questionnaire and Munich Chronotype Questionnaire were used to assess sleep duration, quality, and habits. Ultrasonography was used to diagnose NAFLD. Multivariate logistic regression models were used to calculate the odds ratio (OR) and 95% confidence interval (CI) of the risk of NAFLD by different types of sleep duration and sleep quality. No significant differences in sleep time, sleep quality, and sleep habits between the NAFLD and the non-NAFLD groups were observed (P > 0.05). There was no correlation between sleep duration and NAFLD in the whole cohort. After adjusting for age, exercise, fasting plasma glucose, and BMI, the group with long sleep duration showed a decreased risk of NAFLD in men (OR = 0.01, 95% CI: 0.001–0.27, P = 0.032). However, in all four adjusted models, no correlation between sleep duration, quality, and NAFLD was found in women. In conclusion, sleep duration was significantly and negatively associated with NAFLD in men but not women. Prospective studies are required to confirm this association.

Harnessing data to discover the underlying constitutive relation of phase‐separated polymers can significantly advance the fabrication of high‐performance materials. This work introduces a novel data‐driven method to learn the constitutive equation of diffusional transport of polymers from spatiotemporal density field. In particular, the data‐driven method seamlessly integrated physics‐informed neural networks for inference of approximate solution of diffusivity, and symbolic regression that form explicit expressions of diffusivity. The efficacy and robustness of this method are demonstrated by learning the distinct forms of diffusivity for the phase separation of homopolymer blends with various compositions. In addition, the data‐driven method is generalized to extract the constitutive relation of homogenous chemical potential in the phase separation of homopolymer blends. The data‐driven framework shows the potential for model discovery of nonlinear dynamic system from the spatiotemporal state variables. [ABSTRACT FROM AUTHOR]

A random copolymer (PTBM), utilized as deep ultra-violet (DUV) photoresist, was prepared by reversible addition-fragmentation chain transfer (RAFT) polymerization with tert-butyl methacrylate (tBMA), methyl methacrylate (MMA), triphenylsulfonium p-styrenesulfonate (TPS-SS), and functional poly (sesquicarbonylsiloxanes) (POSS-MA) as the monomer components, and 4-cyano-4-[(dodecylsulfanylthiocarbonyl) sulfanyl]pentanoic acid (CDSPA) as the RAFT reagent. Fourier transform infrared spectroscopy (FT-IR) and proton nuclear magnetic resonance (1H NMR) proved successful synthesis. Ultraviolet absorption spectroscopy (UV) analysis verified the transparency of the polymer in the DUV band. RAFT polymerization kinetics showed that the polymerization rate conformed to the first-order kinetic relationship, and the polymerization process exhibited a typical controlled free radical polymerization behavior. Thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and static thermo-mechanical analysis (TMA) showed that the incorporation of POSS groups improved the thermal properties of the copolymer. According to scanning electron microscopy (SEM) images, the copolymerization of photoacid monomers (TPS-SS) resulted in photoresist copolymers exhibiting good resistance to acid diffusion and low roughness. [ABSTRACT FROM AUTHOR]

Bacterial infection and biofilms cause non-healing chronic wounds and threaten human health. Although antibiotics still play an irreplaceable role to treat infectious diseases in clinics, increasing attention has been paid to the problem of multidrug resistance (MDR). As a novel strategy to deal with bacterial infection, photodynamic antimicrobial therapy (PDAT) has shown promising potential to reduce bacterial infection, and stimuli-responsive nanomaterials have been shown to enhance the antibacterial efficiency and postpone the emergence of drug-resistant bacteria. In this work, we developed a bacterial microenvironment-responsive nanoplatform to eliminate bacteria and bacterial biofilms under 650 nm laser irradiation. Reversible addition–fragmentation chain transfer (RAFT) polymerization was applied to synthesize an H2O2 responsive block copolymer of POEGMA-b-PBMA, and the antibacterial drug of porphyrin TAPP was loaded to form nanoparticles (PT) by a co-assembled approach. At the infection area with overexpressed peroxide, nanoparticles were disintegrated due to the cleaved boronic ester leading to the release of TAPP. Furthermore, the released TAPP became protonated in the acidic infection area (pH = 5.5) and then enhanced its photodynamic antibacterial efficacy by producing higher singlet oxygen (1O2) levels under light irradiation. Both in vitro and in vivo antimicrobial and biofilm elimination experiments demonstrated that the responsive nanoplatform combined with PDAT has tremendous potential for the treatment of infections. [ABSTRACT FROM AUTHOR]