We believe that studying membrane protein structures and phase behavior in contrast-matched lipid bilayers will advance both biological and pharmaceutical applications of membrane-associated proteins, biosensors and food science.A molecule, molecular aggregate, or protein that cannot be superimposed on its mirror image presents chirality. Most living systems are organized by chiral building blocks, such as amino acids, peptides, and carbohydrates, and any change in their molecular structure (i.e., handedness or helicity) alters the biochemical and pharmacological functions of the molecules, many of which take place at surfaces. Therefore, studying surface chirogenesis at the nanoscale is fundamentally important and derives various applications. For example, since proteins contain highly ordered secondary structures, the intrinsic chirality can be served as a signature to measure the dynamics of protein adsorption and protein conformational changes at biological surfaces. Furthermore, a better understanding of chiral recognition and separation at bio-nanointerfaces is helpful to standardize chiral drugs and monitor the synthesis of adsorbents with high precision. Thus, exploring the changes in surface chirality with polarized excitations would provide structural and biochemical information of the adsorbed molecules, which has led to the development of label-free and noninvasive measurement tools based on linear and nonlinear optical effects. In this review, the principles and selected applications of linear and nonlinear optical methods for quantifying surface chirality are introduced and compared, aiming to conceptualize new ideas to address critical issues in surface biochemistry.Nanozyme is a type of nanostructured material with intrinsic enzyme mimicking activity, which has been increasingly studied in the biological field. Compared with natural enzymes, nanozymes have many advantages, such as higher stability, higher design flexibility, and more economical production costs. Nanozymes can be used to mimic natural antioxidant enzymes to treat diseases caused by oxidative stress through reasonable design and modification. Oxidative stress is caused by imbalances in the production and elimination of reactive oxygen species (ROS) and reactive nitrogen species (RNS). This continuous oxidative stress can cause damage to some biomolecules and significant destruction to cell structure and function, leading to many physiological diseases. In this paper, the methods to improve the antioxidant properties of nanozymes were reviewed, and the applications of nanozyme antioxidant in the fields of anti-aging, cell protection, anti-inflammation, wound repair, cancer, traumatic brain injury, and nervous system diseases were introduced. Finally, the future challenges and prospects of nanozyme as an ideal antioxidant were discussed.[This corrects the article DOI 10.3389/fpubh.2020.00277.].The rapid advancement in vaccine development represents a critical milestone that will help humanity tackle the COVID-19 pandemic. However, the success of these efforts is not guaranteed, as it relies on the outcomes of national and international vaccination strategies. In this article, we highlight some of the challenges that Romania will face and propose a set of solutions to overcome them. With this in mind, we discuss issues such as the infrastructure of vaccine storage and delivery, the deployment and administration of immunisations, and the public acceptance of vaccines. The ways in which Romanian society will respond to a national COVID-19 vaccination campaign will be contingent on appropriate and timely actions. As many of the problems encountered in Romania are not unique, the proposed recommendations could be adapted and implemented in other countries that face similar issues, thereby informing better practices in the management of the COVID-19 pandemic.Patellofemoral pain syndrome (PFPS) is a common disease of the knee. Despite its high incidence rate, its specific cause remains unclear. The artificial neural network model can be used for computer-aided diagnosis. Traditional diagnostic methods usually only consider a single factor. However, PFPS involves different biomechanical characteristics of the lower limbs. Thus, multiple biomechanical characteristics must be considered in the neural network model. The data distribution between different characteristic dimensions is different. Thus, preprocessing is necessary to make the different characteristic dimensions comparable. However, a general rule to follow in the selection of biomechanical data preprocessing methods is lacking, and different preprocessing methods have their own advantages and disadvantages. Therefore, this paper proposes a multi-input convolutional neural network (MI-CNN) method that uses two input channels to mine the information of lower limb biomechanical data from two mainstream data h an accurate, convenient, and real-time auxiliary diagnosis system for PFPS to prevent misdiagnosis.Background The Coronavirus disease 2019 (COVID-19) pandemic is a major threat to public health and has had a significant impact on all aspects of life. An effective vaccine is the most anticipated resolution. This study aims to evaluate Jordanian intent to be vaccinated. Methods This is a cross-sectional web-based study. Sample characteristics were gathered, and the participants were classified according to the degree of COVID-19 risk based on the categories of the Centers for Disease Control and Prevention (CDC). Participants' KAP toward COVID-19 were assessed, and two scores were calculated knowledge score and practice score. The association between different sample characteristics and these scores was identified using binary logistical regressions. The participants' vaccination intention was evaluated and multinomial logistic regression was applied to identify the predictors of vaccination intention. https://www.selleckchem.com/products/sitagliptin.html Finally, the reasons behind the participants' vaccination refusal/hesitation were determined and categorized into different groups. Results 1,144 participants were enrolled in the study (females = 66.5%). 30.4% of the participants were at high risk of COVID-19 complications, and 27.5% were at medium risk. Overall, participants' knowledge of COVID-19 symptoms, transmission methods, protective measures, and availability of cure were high (median of knowledge score = 17 out of 21). High protective practices were followed by many participants (median of practice score = 7 out of 10). 3.7% of participants were infected, and 6.4% suspected they were infected with the COVID-19 virus. 36.8% of the participants answered "No" when asked if they would take the vaccine once it becomes available, and 26.4% answered, "Not sure." The main reasons for the participants' vaccination refusal or hesitancy were concerns regarding the use of vaccines and a lack of trust in them. Conclusion Participants reported high refusal/hesitancy. Several barriers were identified, and efforts should be intensified to overcome these barriers.