RESUMO
Spermatogenesis is critical for insect reproduction and is regulated by many different genes. In this study, we found that Forkhead transcription factor Fd59a functions as a key factor in the spermatogenesis of Drosophila melanogaster. Fd59a contains a conversed Forkhead domain, and it is clustered to the FoxD subfamily with other FoxD members from some insect and vertebrate species. Mutations in Fd59a caused swelling in the apical region of the testis. More importantly, fewer mature sperm were present in the seminal vesicle of Fd59a mutant flies compared to the control flies, and the fertility of Fd59a2/2 mutant males was significantly lower than that of the control flies. Immunofluorescence staining showed that the homeostasis of the testis stem cell niche in Fd59a2/2 mutant and Fd59a RNAi flies was disrupted and the apoptosis of sperm bundles was increased. Furthermore, results from RNA sequencing and qRT-PCR suggested that Fd59a can regulate the expression of genes related to reproductive process and cell death. Taken together, our results indicated that Fd59a plays a key role in the spermatogenesis of Drosophila.
RESUMO
Combining the detection of tumor protein markers with the capture of circulating tumor cells (CTCs) represents an ultra-promising approach for early tumor detection. However, current methodologies have not yet achieved the necessary low detection limits and efficient capture. Here, we introduced a novel polypyrrole nanotentacles sensing platform featuring anemone-like structures capable of simultaneously detecting protein biomarkers and capturing CTCs. The incorporation of nanotentacles significantly enhanced the electrode surface area, providing abundant active sites for antibody binding. This enhancement allowed detecting nucleus matrix protein22 (NMP22) and bladder tumor antigen (BTA) with 2.39 and 3.12 pg/mL detection limit, respectively. Furthermore, our developed sensing platform effectively captured MCF-7 cells in blood samples with a detection limit of fewer than 10 cells/mL, attributed to the synergistic multivalent binding facilitated by the specific recognition antibodies and the positive charge on the nanotentacles surface. This sensing platform demonstrated excellent detection capabilities and outstanding capture efficiency, offering a simple, accurate, and efficient strategy for early tumor detection. This article is protected by copyright. All rights reserved.
RESUMO
The therapeutic effects of traditional Chinese medicine (TCM) involve intricate interactions among multiple components and targets. Currently, computational approaches play a pivotal role in simulating various pharmacological processes of TCM. The application of network analysis in TCM research has provided an effective means to explain the pharmacological mechanisms underlying the actions of herbs or formulas through the lens of biological network analysis. Along with the advances of network analysis, computational science has coalesced around the core chain of TCM research: formula-herb-component-target-phenotype-ZHENG, facilitating the accumulation and organization of the extensive TCM-related data and the establishment of relevant databases. Nonetheless, recent years have witnessed a tendency toward homogeneity in the development and application of these databases. Advancements in computational technologies, including deep learning and foundation model, have propelled the exploration and modeling of intricate systems into a new phase, potentially heralding a new era. This review aims to delves into the progress made in databases related to six key entities: formula, herb, component, target, phenotype, and ZHENG. Systematically discussions on the commonalities and disparities among various database types were presented. In addition, the review raised the issue of research bottleneck in TCM computational pharmacology and envisions the forthcoming directions of computational research within the realm of TCM.
RESUMO
Current studies have shown that type I or II interferon-modified mesenchymal stem cells have great potential for the application of tumor-targeted therapy, but the underlying mechanism remains largely elusive. Here, we compared the different effects of IFN-ß and IFN-γ on the antitumor activity of human amniotic fluid-derived mesenchymal stem cells (AFMSCs) and revealed the potential mechanism. In detail, AFMSCs primed with IFN-ß or IFN-ß plus IFN-γ, not IFN-γ, inhibited the proliferation of cancer cells in an immunocompetent mouse H460 subcutaneous model, although they all inhibited the proliferation of cancer cells in an immunocompromised mouse H460 subcutaneous model. TRAIL expressed by IFN-ß- or IFN-γ-primed AFMSCs specifically exerted the antitumor effect of AFMSCs. AFMSCs primed with IFN-γ highly expressed immunosuppressive molecule IDO1, but IFN-ß counteracted the IFN-γ-initiated IDO1 expression. 1-MT (IDO1 inhibitor) decreased TRAIL, but increased IDO1 expression in AFMSCs primed with interferon. As a result, AFMSCs primed with IFN-ß or IFN-γ had the antitumor activity, and 1-MT failed to enhance the antitumor effect of IFN-γ-primed AFMSC in vitro and in the immunocompromised mouse H460 subcutaneous model. Furthermore, the expression of TRAIL in AFMSCs was upregulated by apoptotic cancer cells and this positive feedback intensified the antitumor effects of IFNs-primed AFMSCs. The different target gene expression profiles of AFMSCs regulated by IFN-ß and IFN-γ determined the different antitumor effects of IFN-ß- and IFN-γ-primed AFMSCs on tumor cells. Our finding may help to explore a clinical strategy for cancer intervention by understanding the antitumor mechanisms of MSCs and interferon.