Despite recent improvements in the comprehensive therapy of malignancy, metastatic colorectal cancer (mCRC) continues to have a poor prognosis. Notably, 5% of mCRC cases harbor Erb-B2 receptor tyrosine kinase 2 (ERBB2) alterations. ERBB2, commonly referred to as human epidermal growth factor receptor 2, is a member of the human epidermal growth factor receptor family of protein tyrosine kinases. In addition to being a recognized therapeutic target in the treatment of gastric and breast malignancies, it is considered crucial in the management of CRC. In this review, we describe the molecular biology of ERBB2 from the perspective of biomarkers for mCRC-targeted therapy, including receptor structures, signaling pathways, gene alterations, and their detection methods. We also discuss the relationship between ERBB2 aberrations and the underlying mechanisms of resistance to anti-EGFR therapy and immunotherapy tolerance in these patients with a focus on novel targeted therapeutics and ongoing clinical trials. This may aid the development of a new standard of care in patients with ERBB2-positive mCRC.

Charged photovoltaic glass produces an electrostatic field. The electrostatic field exerts an electrostatic force on dust particles, thus making more dust particles deposited on the glass. In this paper, the contact electrification between the deposited dust particles and the photovoltaic glass is studied. Meanwhile, the surface charge density model of the photovoltaic glass and the electrostatic force of charged particles are analyzed. The results show that with the increasing of the particle impact speed and the inclination angle of the photovoltaic panel, the charges on particles increase to different degrees. Under a given condition, the electrostatic forces acting on the charged particles at different positions above the glass plate form a bell-shaped distribution at a macro level, and present a maximum value in the center of the plate. As the distance between the particle and the charged glass decreases, the electrostatic force exerted on the particle increases significantly and fluctuates greatly. However, its mean value is still higher than the force caused by gravity and the adhesion force, reported by some studies. Therefore, we suggest that photovoltaic glass panels used in the severe wind-sand environment should be made of an anti-static transparent material, which can lessen the dust particles accumulated on the panels.

The urban spatial structure is a key feature of the distribution of social and economic resources. The spatial structure of an urban agglomeration is an abstract relationship expression of urbanization. Urban agglomerations develop for multiple reasons, including urban planning and natural evolution. To date, most research related to urban agglomeration has been based on single data source, which is a limitation. This research aims to propose a spatial structure identification method for urban agglomerations via a complex network based on nighttime light data and railway data. Firstly, we extracted the urban built-up area using defense meteorological satellite program/operational line scanner (DMSP/OLS) data, and divided it into urban objects to obtain the nighttime light urban network (NLUN) by borough. Secondly, we aggregated railway stations at municipal level using railway operation data to obtain the railway urban network (RUN). Following this, we established a composite urban network (CUN) consisting of the NLUN and the RUN based on the composite adjacency matrix. Finally, the Louvain algorithm and the comprehensive strength index (CSI) were used to detect the communities and central nodes of the CUN and obtain the urban agglomerations and core cities. The results show that urban agglomeration identification based on the CUN has the best accuracy, which is 5.72% and 15.94% higher than that of the NLUN and RUN, respectively. Core cities in the urban agglomeration identified by the CSI in the CUN are at least 3.04% higher than those in the single-source urban network. In addition, the distribution pattern of Chinese urban agglomerations in the study area is expressed as “three vertical”, and the development level of urban agglomeration shows an unbalanced trend.

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