DNA alkylating agents generally kill tumor cells by covalently binding with DNA to form interstrand or intrastrand cross-links. However, in the case of cisplatin, only a few DNA adducts (<1%) are highly toxic irreparable interstrand cross-links. Furthermore, cisplatin is rapidly detoxified by high levels of intracellular thiols such as glutathione (GSH). Since the discovery of its mechanism of action, people have been looking for ways to directly and efficiently remove intracellular GSH and increase interstrand cross-links to improve drug efficacy and overcome resistance, but there has been little breakthrough. Herein, we hypothesized that the anticancer efficiency of cisplatin can be enhanced through iodo-thiol click chemistry mediated GSH depletion and increased formation of DNA interstrand cross-links via mild hyperthermia triggered by near-infrared (NIR) light. This was achieved by preparing an amphiphilic polymer with platinum(IV) (Pt(IV)) prodrugs and pendant iodine atoms (iodides). The polymer was further used to encapsulate IR780 and assembled into Pt−I−IR780 nanoparticles. Induction of mild hyperthermia (43 °C) at the tumor site by NIR light irradiation had three effects: (1) it accelerated the GSH-mediated reduction of Pt(IV) in the polymer main chain to platinum(II) (Pt(II)); (2) it boosted the iodo-thiol substitution click reaction between GSH and iodide, thereby attenuating the GSH-mediated detoxification of cisplatin; (3) it increased the proportion of highly toxic and irreparable Pt-DNA interstrand cross-links. Therefore, we find that mild hyperthermia induced via NIR irradiation can enhance the killing of cancer cells and reduce the tumor burden, thus delivering efficient chemotherapy.
3D printing, also known as additive manufacturing, is a technology that uses a variety of adhesive materials such as powdered metal or plastic to construct objects based on digital models. Recently, 3D printing technology has been combined with digital medicine, materials science, cytology, and other multidisciplinary fields, especially in the field of orthopedic built-in objects. The development of advanced 3D printing materials continues to meet the needs of clinical precision medicine and customize the most suitable prosthesis for everyone to improve service life and satisfaction. This article introduces the development of 3D printing technology and different types of materials. We also discuss the shortcomings of 3D printing technology and the current challenges, including the poor bionics of 3D printing products, lack of ideal bioinks, product safety, and lack of market supervision. We also prospect the future development trends of 3D printing.
The Chinese government has made great efforts to improve the scale efficiency of land through various measures during recent years, hoping to realize the coordinated developing goal of promoting agricultural benefits and protecting the environment. Statistics show that China’s land scale efficiency has steadily increased, but agricultural nonpoint source (NPS) pollution has also increased, which seems contrary to the expected outcome. Can increasing scale efficiency really curb agricultural NPS pollution? This study uses provincial-level data from China, together with a panel model and spatial econometric model, to investigate the relationship between scale efficiency and agricultural NPS pollution. It is found that the increase of scale efficiency aggravates the agricultural NPS pollution, and the conclusion still holds after considering spatial effect. The results of spatial analysis shows that the agricultural NPS pollution is spatially dependent. Further decomposition of the spatial effect shows that the scale efficiency not only intensifies the local agricultural NPS pollution, but also has a spillover effect (though not statistically significant) on agricultural NPS pollution in the surrounding areas. It is worth noting that financial policy, raising wage income and upgrading industrial structure can effectively curb agricultural NPS pollution in this region and adjacent areas, which also deserves our attention in the control of agricultural NPS pollution. In addition, it is necessary to make financial and fiscal support policies specifically for the governance of agricultural NPS pollution, adjust the distorted prices of input factors such as chemicals and pesticide, and accelerate the transformation of small-sized farmers to family farms, in order to maximize the inhibitory effect of scale efficiency on relieving agricultural NPS pollution.
This study explores the major reasons for Chinese small dairy farms to accept the new organization structure, dairy complex (DC), and the discrepancies between the actual effect and farmers’ perceptions. Our results show that the frequency of milk refusal, herd scale and farmers’ age contribute to farmers’ decision in accepting DCs, while sale price and disease prevention do not have significant influence. Independent farmers’ perceived effects and the actual effects of DCs in improving raw milk safety and price are consistent, but there exists misperception of DCs’ effect in disease prevention.
With the development of smart phones, malicious applications for the Android platform have increased dramatically. The existing Android malicious code analysis methods majorly focus on detection based on signatures, inter-component communication, and other configuration information features. Such methods ignore the effect of the semantic features of the malicious code. Even a few such studies that exist are based on the statistical features of the code for malicious code detection. To address these shortcomings, we (1) use the code semantic structure features to reflect deep semantic information, (2) propose a preprocessing method of APK files to generate graphics that reflect the code semantic features, and (3) introduce the advanced graphical semantics for a graph convolutional network (GCN) model to automatically identify and learn semantics and extract features for malicious code detection. Experiments on a dataset confirm that the proposed method can achieve 95.8% detection accuracy. Compared with the existing methods that adopt configuration information features or statistical features of codes, our method shows higher accuracy.
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