A meta-analysis of the Zilongjin tablets for non-small cell lung cancer and its network pharmacology of action against NSCLC and COVID-19.

Objective: To objectively evaluate the efficacy of the Zilongjin tablets in non-small cell lung cancer (NSCLC) and to explore its potential mechanism of action against NSCLC and COVID-19 based on network pharmacology. Methods: The database was searched for randomized controlled trials (RCTs) of the Zilongjin tablets for NSCLC published up to 22 August 2022. The quality of included trials was assessed using Cochrane standard guidelines, and a meta-analysis was performed using Rev Man 5.3. Gene targets for intersections of NSCLC and COVID-19 (the NC) and drugs were obtained from the TCMSP database, HERB database, GeneCards database, and the NCBI database for network pharmacology research. Results: Meta-analysis included 14 articles with 2,430 patients. The meta-analysis showed that the Zilongjin tablets combined with conventional chemotherapy were significantly more effective than chemotherapy alone in the treatment of NSCLC. A total of 29 drug-disease intersecting targets were identified in the network pharmacology. The "ingredient-target-pathway" diagram component-target-pathway network contained 119 nodes and 429 edges, with the majority of targets associated with inflammatory responses. Conclusion: The efficacy and quality of life of the Zilongjin tablets combined conventional chemotherapy for NSCLC were significantly better than chemotherapy alone, alleviating various adverse effects. At the same time, the Zilongjin tablets may modulate the inflammatory response to alleviate NSCLC and COVID-19.

Decoding Physical and Cognitive Impacts of Particulate Matter Concentrations at Ultra-Fine Scales.

The human body is an incredible and complex sensing system. Environmental factors trigger a wide range of automatic neurophysiological responses. Biometric sensors can capture these responses in real time, providing clues about the underlying biophysical mechanisms. In this prototype study, we demonstrate an experimental paradigm to holistically capture and evaluate the interactions between an environmental context and physiological markers of an individual operating that environment. A cyclist equipped with a biometric sensing suite is followed by an environmental survey vehicle during outdoor bike rides. The interactions between environment and physiology are then evaluated though the development of empirical machine learning models, which estimate particulate matter concentrations from biometric variables alone. Here, we show biometric variables can be used to accurately estimate particulate matter concentrations at ultra-fine spatial scales with high fidelity (r2 = 0.91) and that smaller particles are better estimated than larger ones. Inferring environmental conditions solely from biometric measurements allows us to disentangle key interactions between the environment and the body. This work sets the stage for future investigations of these interactions for a larger number of factors, e.g., black carbon, CO2, NO/NO2/NOx, and ozone. By tapping into our body's 'built-in' sensing abilities, we can gain insights into how our environment influences our physical health and cognitive performance.

Preparation and thermal insulation performance of cast-in-situ phosphogypsum wall.

INTRODUCTION: The mass accumulation of phosphogypsum has caused serious environmental pollution, which has become a worldwide problem. Gypsum is a kind of green building material, which is lighter, has better heat and sound insulation performance, and is easier to recycle compared to cement. The application of cast-in-situ phosphogypsum wall could consume a large amount of pollutant, and improve the efficiency of building construction. METHODS: The preparation and thermal insulation performance of cast-in-situ phosphogypsum wall were investigated. The property of phosphogypsum-fly ash-lime (PFL) triad cementing materials, the adaptability of retarders and superplasticizers, and the influences of vitrified microsphere as aggregates were explored. Thus, the optimum mix was proposed. Thermal insulation performance tests and ANSYS simulation of this material was carried out. RESULTS: Optimal structures based on heat channels and the method of calculation determining related parameters were proposed, which achieved a 12.3% reduction in the heat transfer coefficient of the wall. CONCLUSION: With good performance, phosphogypsum could be used in cast-in-situ walls. This paper provides the theoretical basis for the preparation and energy-saving application of phosphogypsum in the walls of buildings.

Stress-strain relationship and seismic performance of cast-in-situ phosphogypsum.

BACKGROUND: Phosphogypsum is a waste by-product during the production of phosphoric acid. It not only occupies landfill, but also pollutes the environment, which becomes an important factor restricting the sustainable development of the phosphate fertilizer industry. Research into cast-in-situ phosphogypsum will greatly promote the comprehensive utilization of stored phosphogypsum. The aim of this study was to clarify the mechanical properties of phosphogypsum. METHODS: Stress-strain relationships of cast-in-situ phosphogypsum were investigated through axial compressive experiments, and seismic performance of cast-in-situ phosphogypsum walls and aerated-concrete masonry walls were simulated based on the experimental results and using finite element analysis. RESULTS: The results showed that the stress-strain relationship fitted into a polynomial equation. Moreover, the displacement ductility index and the energy dissipation index of cast-in-situ phosphogypsum wall were 6.587 and 3.425, respectively. CONCLUSIONS: The stress-strain relationship for earthquake-resistant performance of cast-in-situ phosphogypsum walls is better than that of aerated-concrete masonry walls. The curve of stress-strain relationship and the evaluation of earthquake-resistant performance provide theoretical support for the application of cast-in-situ phosphogypsum in building walls.