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BackgroundAn extensive amount of information related to the novel coronavirus (COVID-19) pandemic was disseminated by mass and social media in China. To date, there is limited evidence on how this infodemic may influence psychobehavioral responses to the crisis. ObjectiveThe aim of this study is to assess the psychobehavioral responses to the COVID-19 outbreak and examine their associations with mass and social media exposure. MethodsA cross-sectional study among medical and health sciences students from the Fujian Medical University in Fuzhou, China, was conducted between April 6-22, 2020. ResultsA total of 2086 completed responses were received. Multivariable analyses demonstrated that four constructs of the Health Belief Model (HBM)—higher perception of susceptibility (odds ratio [OR] 1.44; 95% CI 1.07-1.94), severity (OR 1.32; 95% CI 1.10-1.59), self-efficacy (OR 1.61; 95% CI 1.21-2.15), and perceived control or intention to carry out prevention measures (OR 1.32; 95% CI 1.09-1.59)—were significantly associated with a higher mass media exposure score, whereas only three constructs—higher perception of severity (OR 1.43; 95% CI 1.19-1.72), self-efficacy (OR 1.85; 95% CI 1.38-2.48), and perceived control or intention to carry out prevention measures (OR 1.32; 95% CI 1.08-1.58)—were significantly associated with a higher social media exposure score. Lower emotional consequences and barriers to carry out prevention measures were also significantly associated with greater mass and social media exposure. Our findings on anxiety levels revealed that 38.1% (n=795; 95% CI 36.0-40.2) of respondents reported moderate-to-severe anxiety. A lower anxiety level was significantly associated with higher mass and social media exposure in the univariable analyses; however, the associations were not significant in the multivariable analyses. ConclusionsIn essence, both mass and social media are useful means of disseminating health messages and contribute to the betterment of psychobehavioral responses to COVID-19. Our findings stress the importance of the credibility of information shared through mass and social media outlets and viable strategies to counter misinformation during a pandemic.

BackgroundThe incidence of cancer pain increases in discharged patients because of discontinued standard treatments and reductions in medication adherence. Motivated by the need for better pain management in discharged patients, we developed a mobile phone app (Pain Guard) to provide continuous treatment information and feedback to discharged cancer patients suffering from pain. ObjectiveThe aim was to design, construct, and test the Pain Guard app in patients managing cancer pain, evaluate the total remission rate of pain and the improvement in quality of life (QoL) to improve pain management for cancer pain patients, and assess patient acceptance of the app. MethodsThis randomized controlled double-arm study involved 58 patients with cancer pain symptoms. Participants were randomly assigned to a group receiving care through the Pain Guard app (n=31) or to a control group (n=27) who received only traditional pharmaceutical care. In a pretest, participants were rated using a baseline cancer pain assessment and QoL evaluation. During treatment, the consumption levels of analgesic drugs were recorded every week. After a 4-week study period, another round of cancer pain assessment and QoL evaluation was conducted. The system’s usability, feasibility, app compliance, and satisfaction were also assessed. Our primary outcome was remission rate of pain, and secondary outcomes were medication adherence, improvements in QoL, frequency of breakthrough cancer pain (BTcP), incidence of adverse reactions, and satisfaction of patients. ResultsAll participants (N=58) successfully completed the study. There were no significant differences in baseline pain scores or baseline QoL scores between groups. At the end of the study, the rate of pain remission in the trial group was significantly higher than that in the control group (P

Due to their variable stiffness characteristics, magnetorheological elastomers (MREs) can be applied for seismic isolators in civil infrastructure systems. The lateral stiffness variation of MRE isolators is affected by the change of MRE shear stiffness. The natural frequency of the MRE-based isolation systems is related to the lateral stiffness of the MRE isolators with the range of lateral stiffness variation of MRE isolators serving as a critical objective to determine the shift ability of natural frequencies of the isolation systems. Here we develop a multiscale computational method to determine the magneto-mechanical coupling of MRE isolators. The field-dependent stiffness variation of the isolators is achieved with the consideration of combined magnetic field and deformation. Effects of MRE microstructural feature (e.g., particle concentrations in chains and between chains) and macroscopic geometry (e.g., thicknesses of MRE laminate and steel) on the magneto-mechanical responses of the isolators are specifically investigated, so as to guide the design of MRE-based isolating structures. The magnetic field and lateral stiffness of several MRE-based isolator prototypes from experiments are obtained by finite element-based shear simulation. Simulation results are quantitatively compared with experimental data, verifying and validating the accuracy and applicability of the proposed method.

ObjectiveTo explore the association between dietary retinol intake and prognosis of patients with esophageal squamous cell carcinoma.MethodsThe study enrolled 388 cases with primary esophageal squamous cell carcinoma that was pathologically diagnosed in the first affiliated hospital of Fujian medical university and the cancer hospital of Fujian medical university from July 2014 to August 2019. Chi-square test was used to determine the relationship between retinol and patients' characteristics. Kruskal-Wallis rank sum test was used to analyze the relationship between retinol and multiple nutrients. Cox proportional hazards regression model was used to explore the association between dietary retinol and esophageal squamous cell carcinoma.ResultsPatients with esophageal squamous cell carcinoma did not significantly differ in gender， age， TNM stage， tumor length or nutrient intake by different retinol intakes （P>0.05）. Multivariate Cox regression analysis showed that the high retinol intake group had a better prognosis （overal survial：HR=0.279，95%CI：0.150‒0.520，P

Elastography is of great interest in biomechanics and medical imaging due to its nondestructive capability of mapping elasticity of tissues. The elastography framework relies on external excitations which actuate deformation inside an object. The internal response is then acquired and analyzed to map the distribution of elastic moduli. In this paper, with no need of measuring any internal responses, an integrated elastography method is developed which only requires the transmitted responses of applied sound waves. During the process, the tomography image (e.g., CT or MRI) and the applied waves are integrated into a computational model. Following a procedure of inverse analysis, the elasticity of all phases in the object is reconstructed when the computational transmission of waves matches with the measured transmission. The numerical simulation on brain tissues and a demonstration on silicon rubber phantom are conducted to validate the proposed method. Both cases demonstrate that the integrated method successfully predicts the real elasticity of samples. The verification measurements on the phantom further show that the predicted elastic moduli agree well with the experimental results of uniaxial compression testing.

Multi-drug combinations to treat bacterial populations are at the forefront of approaches for infection control and prevention of antibiotic resistance. Although the evolution of antibiotic resistance has been theoretically studied with mathematical population dynamics models, extensions to spatial dynamics remain rare in the literature, including in particular spatial evolution of multi-drug resistance. In this study, we propose a reaction-diffusion system that describes the multi-drug evolution of bacteria based on a drug-concentration rescaling approach. We show how the resistance to drugs in space, and the consequent adaptation of growth rate, is governed by a Price equation with diffusion, integrating features of drug interactions and collateral resistances or sensitivities to the drugs. We study spatial versions of the model where the distribution of drugs is homogeneous across space, and where the drugs vary environmentally in a piecewise-constant, linear and nonlinear manner. Although in many evolution models, per capita growth rate is a natural surrogate for fitness, in spatially-extended, potentially heterogeneous habitats, fitness is an emergent property that potentially reflects additional complexities, from boundary conditions to the specific spatial variation of growth rates. Applying concepts from perturbation theory and reaction-diffusion equations, we propose an analytical metric for characterization of average mutant fitness in the spatial system based on the principal eigenvalue of our linear problem, λ1. This enables an accurate translation from drug spatial gradients and mutant antibiotic susceptibility traits to the relative advantage of each mutant across the environment. Our approach allows one to predict the precise outcomes of selection among mutants over space, ultimately from comparing their λ1 values, which encode a critical interplay between growth functions, movement traits, habitat size and boundary conditions. Such mathematical understanding opens new avenues for multi-drug therapeutic optimization. Author summary: In this study we develop a framework to model multi-drug resistance evolution in space by combining drug-rescaling arguments with a reaction-diffusion type model. In response to multi-drug environmental gradients, each independent mutant can grow and diffuse following an individual spatially-varying growth function and diffusion rate. Applying concepts from perturbation theory and reaction-diffusion models, we propose an analytical metric to quantify average mutant fitness in the spatial system and to predict the outcome of selection. Our findings highlight that in spatially-extended habitats fitness is an emergent property that potentially integrates many complexities, from boundary conditions to environmental variation, as well as individual growth and diffusion traits. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the predictive value of PD-1 expression in T lymphocytes for rehospitalization due to acute exacerbations of COPD (AECOPD) in discharged patients. Methods: 115 participants hospitalized with COPD (average age 71.8 ± 6.0 years) were recruited at Fujian Provincial Hospital. PD1+T lymphocytes proportions (PD1+T%), baseline demographics and clinical data were recorded at hospital discharge. AECOPD re-admission were collected at 1-year follow-up. Kaplan-Meier analysis compared the time to AECOPD readmissions among groups stratified by PD1+T%. Multivariable Cox proportional hazards regression and stratified analysis determined the correlation between PD1+T%, potential confounders, and AECOPD re-admission. ROC and DCA evaluated PD1+T% in enhancing the clinical predictive values of Cox models, BODE and CODEX. Results: 68 participants (59.1%) were AECOPD readmitted, those with AECOPD readmission exhibited significantly elevated baseline PD-1+CD4+T/CD4+T% and PD-1+CD8 + T/CD8 + T% compared to non-readmitted counterparts. PD1+ T lymphocyte levels statistically correlated with BODE and CODEX indices. Kaplan-Meier analysis demonstrated that those in Higher PD1+ T lymphocyte proportions had reduced time to AECOPD readmission (logRank p < 0.05). Cox analysis identified high PD1+CD4+T and PD1+CD8+T ratios as risk factors of AECOPD readmission, with hazard ratios of 1.384(95%CI [1.043–1.725]) and 1.401(95%CI [1.013–1.789]), respectively. Notably, in patients aged < 70 years and with fewer than twice AECOPD episodes in the previous year, high PD1+T lymphocyte counts significantly increased risk for AECOPD readmission(p < 0.05). The AECOPD readmission predictive model, incorporating PD1+T% exhibited superior discrimination to the Cox model, BODE index and CODEX index, AUC of ROC were 0.763(95%CI [0.633–0.893]) and 0.734(95%CI [0.570–0.899]) (DeLong's test p < 0.05).The DCA illustrates that integrating PD1+T% into models significantly enhances the utility in aiding clinical decision-making. Conclusion: Evaluation of PD1+ lymphocyte proportions offer a novel perspective for identifying high-risk COPD patients, potentially providing insights for COPD management. Trial registration: Chinese Clinical Trial Registry (ChiCTR, URL: www.chictr.org.cn/), Registration number: ChiCTR2200055611 Date of Registration: 2022-01-14. [ABSTRACT FROM AUTHOR]

In the context of strong electromagnetic interference environments, the measurement accuracy of the capacitance parameters of transmission lines under power frequency measurement methods is not high. In this paper, a capacitance parameter anti-interference measurement method for transmission lines based on harmonic components is proposed to overcome the impact of power frequency interference. When applying this method, it is first necessary to open-circuit the end of the line under test. Subsequently, apply voltage to the head end of the tested line through a step-up transformer. Due to the saturation of the transformer during no-load conditions, a large number of harmonics are generated, primarily third harmonic. The third harmonic components of voltage and current on the tested transmission line are extracted using the Fourier transform. The proposed method addresses the influence of line distribution effects by establishing a distributed parameter model for long-distance transmission lines. The relevant transmission matrix for the zero-sequence distributed parameters is obtained by combining Laplace transform and similarity transform to solve the transmission line equations. Using synchronous measurement data from the third harmonic components of voltage and current at both ends of the transmission line, combined with the transmission matrix, this method accurately measures the zero-sequence capacitance parameters. The PSCAD/EMTDC simulation results and field test outcomes have demonstrated the feasibility and accuracy of the proposed method for measuring line capacitance parameters under strong electromagnetic interference. [ABSTRACT FROM AUTHOR]

With the rapid development of high-throughput sequencing technology represented by the second generation sequencing technology, whole-genome detection technology has been able to detect data from multiple levels, such as genome, transcriptome and epigenome. Biomass is a complicated regulatory system, involving many levels of complicated regulatory mechanism. Considering the limitation of single omics data analysis in exploring pathogenic factors, integrative multi-omics analysis with linear or nonlinear relationship can provide a new method for the study of the disease. Integrative analysis of multiple omics has widely used in various diseases, including lung cancer, and DNA or gene molecular level is particularly important as a basis for intermolecular correlations and complex networks. Hence, this paper briefly describes integrative analysis of genome, transcriptome and epigenome in lung cancer.