Search

The 2022 Compulsory Stage Physical Education and Health Curriculum Standards (2022 Edition) proposed the teaching concept of large units. How to achieve the transformation of the consistency of "learning, practicing, and evaluating" in physical education and health classrooms based on the practice of large unit teaching is a hot topic of discussion in the current reform of physical education and health curriculum teaching, which is of great significance for deepening and promoting the reform of physical education and health curriculum teaching. The article first discusses the logical starting point of the consistency of "learning, practicing, and evaluating" in the physical education unit, and then addresses the four major drawbacks of teaching physical education and health courses: "complexity" (extensive learning of textbook content), "shallowness" (teaching methods are superficial). "scattering" (lack of systematic teaching content), and "disconnection" (disconnection between textbook content). Using the methods of literature review and logical analysis, this paper attempts to construct a content framework for the consistency of "learning, training, and evaluation" in the sports unit. and based on this, proposes a practical path for the consistency of "learning, practicing, and evaluation" in the sports unit: firstly, the concept of "learning", secondly, the task of "training" and the third is the "embedded" evaluation. In order to form a large unit teaching system with clear logic, systematic coherence, vertical connection, and horizontal consistency in the teaching of physical education and health courses, it is beneficial to shift the focus from teacher's "teaching" to student's "learning", promote the implementation of the new curriculum quality oriented teaching concept, help students achieve deep learning in the classroom, and truly implement the development of students' core literacy in physical education and health subjects. [ABSTRACT FROM AUTHOR]

A transmission surface-enhanced infrared absorption spectroscopy (SEIRAS) substrate based on copper foam (CF) was developed for the rapid detection of dithiocarbamate (DTC) pesticides. The transmission SEIRAS substrate was prepared by immersing CF in a mixed solution of a precious metal solution and a polyvinyl pyrrolidone (PVP) solution. Then CF could be in situloaded with precious metal nanoparticles (MNPs) by PVP-modified displacement reaction in seconds. PVP could be helpful for the uniform distribution of MNPs. Experimental parameters were evaluated with 11-mercaptoundecanoic acid (MUA) as a probe molecule, including the concentration of the precious metal solution, the amount of PVP, and the reaction time. Taking CF loaded with gold nanoparticles (Au NPs-CF) as an example, the signal intensity of DTC pesticide (Ziram) could be enhanced by two orders of magnitude, and the R2of the calibration curve was 0.999. In addition, the Pt NPs-CF substrate was applied to the rapid detection of other DTC pesticides (Ferbam). In summary, we have developed a new method to prepare the transmission SEIRAS substrate and apply it to the rapid detection of DTC pesticides in liquid.

Background:Prior studies have revealed promising clinical outcomes of pomalidomide-based (Pom-based) and daratumumab-based (Dara-based) regimens. However, there is limited data directly comparing Pom-based versus Dara-based therapies for relapsed/refractory multiple myeloma (RRMM) in either clinical trials or real-world practice. This study aimed to compare real-world clinical outcomes and safety between Pom-based and Dara-based therapies in patients with RRMM.

Background:An unprecedented nationwide Omicron outbreak hit China in December 2022. Patients with plasma cell disorders have been confirmed to exhibit worse outcomes following COVID-19 infection, although data on the impact of Omicron on this population in China remain scarce. This study aims to report the clinical and epidemiological characteristics of plasma cell disorder patients during this major Omicron outbreak. It also analyzes the association between patient clinical characteristics and clinical course (infection, severity, hospitalization, and time to recovery) of COVID-19.