Heterogeneity of myeloid cells in common cancers: Single cell insights and targeting strategies.

Tumor microenvironment (TME), is characterized by a complex and heterogenous composition involving a substantial population of immune cells. Myeloid cells comprising over half of the solid tumor mass, are undoubtedly one of the most prominent cell populations associated with tumors. Studies have unambiguously established that myeloid cells play a key role in tumor development, including immune suppression, pro-inflammation, promote tumor metastasis and angiogenesis, for example, tumor-associated macrophages promote tumor progression in a variety of common tumors, including lung cancer, through direct or indirect interactions with the TME. However, due to previous technological constraints, research on myeloid cells often tended to be conducted as studies with low throughput and limited resolution. For example, the conventional categorization of macrophages into M1-like and M2-like subsets based solely on their anti-tumor and pro-tumor roles has disregarded their continuum of states, resulting in an inadequate analysis of the high heterogeneity characterizing myeloid cells. The widespread adoption of single-cell RNA sequencing (scRNA-seq) in tumor immunology has propelled researchers into a new realm of understanding, leading to the establishment of novel subsets and targets. In this review, the origin of myeloid cells in high-incidence cancers, the functions of myeloid cell subsets examined through traditional and single-cell perspectives, as well as specific targeting strategies, are comprehensively outlined. As a result of this endeavor, we will gain a better understanding of myeloid cell heterogeneity, as well as contribute to the development of new therapeutic approaches.

The fate of Arsenic associated with the transformation of iron oxides in soils: The mineralogical evidence.

The influence of iron (oxyhydr)oxides on the transformation and migration of arsenic(As) has garnered significant attention. Previous work has largely focused on the transformation of iron oxides related to As fate at molecular and mechanistic levels. However, studies examining the interplay between As concentration and iron oxides transformation within complex soil system are sparse. This study investigates the transformation of iron oxides in soils with varying As concentration during microbial dissimilatory iron reduction (DIR), employing humic acid (HA) as electron shuttle and assesses the impact on As speciation transformation. Comparative analyses indicate that in soils with high As concentration (>1000 mg/kg), the secondary transformation of iron (oxyhydr)oxides to other forms, such as the conversion of ferrihydrite to goethite and lepidocrocite, or schwertmannite to goethite, is impeded. Consequently, the formation of goethite and lepidocrocite, which would typically re-stabilize As, is inhibited, leading to elevated release of As(III). On the other hand, an increase in magnetite formation in soils with low As concentration (<100 mg/kg) appears to re-stabilize As effectively. Furthermore, the formation of new secondary iron (oxyhydr)oxides in soils with As concentration <200 mg/kg enhances fraction F5, which subsequently contributes to the re-immobilization of As, sequestering it within the soil matrix. This process results in a lower release of As(III) from soils with As concentration below 200 mg/kg. These findings enhance the understanding of the interdependent relationship between the transformation of iron oxides and the fate of As in complex soil systems.

Dynamic Anti-Counterfeiting Labels with Enhanced Multi-Level Information Encryption.

Information encryption is an important means to improve the security of anti-counterfeiting labels. At present, it is still challenging to realize an anti-counterfeiting label with multi-function, high security factor, low production cost, and easy detection and identification. Herein, using inkjet and screen printing technology, we construct a multi-dimensional and multi-level dynamic optical anti-counterfeiting label based on instantaneously luminescent quantum dots and long afterglow phosphor, whose color and luminous intensity varied in response to time. Self-assembled quantum dot patterns with intrinsic fingerprint information endow the label with physical unclonable functions (PUFs), and the information encryption level of the label is significantly improved in view of the information variation in the temporal dimension. Furthermore, the convolutional residual neural networks are used to decode the massive information of PUFs, enabling fast and accurate identification of the anti-counterfeit labels.