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Abstract Immunotherapy has shown marked progress in promoting systemic anti-colorectal cancer (CRC) clinical effects. For further effectively sensitizing CRC to immunotherapy, we have engineered a pH-sensitive zeolitic imidazolate framework-8 (CS/NPs), capable of efficient cGAS-STING pathway activation and immune checkpoint blockade, by encapsulating the chemotherapeutic mitoxantrone (MTX) and immunomodulator thymus pentapeptide (TP5) and tailoring with tumor-targeting chondroitin sulfate (CS). In this nanoframework, CS endows CS/NPs with specific tumor-targeting activity and reduced systemic toxicity. Of note, the coordinated Zn2+ disrupts glycolytic processes and downregulates the expression of glucose transporter type 1 (GLUT1), thus depriving the cancer cells of their energy. Zn2+ further initiates the adenosine 5’-monophosphate activated protein kinase (AMPK) pathway, which leads to PD-L1 protein degradation and sensitizes CRC cells to immunotherapy. Moreover, the damaged double-stranded DNA during MTX treatment activates the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway, which works together with TP5 induced the proliferation and differentiation of T lymphocytes and dendritic cells to further enhance the anti-CRC immune response. Therefore, CS/NPs efficiently sensitize cells to chemotherapy and stimulate systemic antitumor immune responses both in vitro and in vivo, representing a promising strategy to increase the feasibility of CRC immunotherapy. Graphical Abstract

Abstract Doxorubicin’s antitumor effectiveness may be constrained with ineffective tumor penetration, systemic adverse effects, as well as drug resistance. The co-loading of immune checkpoint inhibitors and doxorubicin into liposomes can produce synergistic benefits and address problems, including quick drug clearance, toxicity, and low drug penetration efficiency. In our previous study, we modified a nanobody targeting CTLA-4 onto liposomes (LPS-Nb36) to be an extremely potent CTLA-4 signal blocker which improve the CD8+ T-cell activity against tumors under physiological conditions. In this study, we designed a drug delivery system (LPS-RGD-Nb36-DOX) based on LPS-Nb36 that realized the doxorubicin and anti-CTLA-4 Nb co-loaded and RGD modification, and was applied to antitumor therapy. We tested whether LPS-RGD-Nb36-DOX could targets the tumor by in vivo animal photography, and more importantly, promote cytotoxic T cells proliferation, pro-inflammatory cytokine production, and cytotoxicity. Our findings demonstrated that the combination of activated CD8+ T cells with doxorubicin/anti-CTLA-4 Nb co-loaded liposomes can effectively eradicate tumor cells both in vivo and in vitro. This combination therapy is anticipated to have synergistic antitumor effects. More importantly, it has the potential to reduce the dose of chemotherapeutic drugs and improve safety.

Biodiversity is a vital aspect of an ecosystem and investigating its formation and maintenance is vital. Maintaining biodiversity notably requires a clear understanding of the mechanisms underlying species coexistence. However, in the Anthropocene, the absence of large carnivores in most areas has reduced the number of relatively intact ecosystems suitable for coexistence research. The mountains of Southwest China, a biodiversity hotspot with relatively low anthropogenic disturbance, offer a potentially suitable area for studying carnivore coexistence, especially in the Xinlong region in Sichuan. To understand the mechanisms underlying the coexistence of small carnivores, we used infrared cameras to investigate their spatiotemporal activity. We explored interspecific niche differentiation and small carnivore' responses to top predators and human disturbances using occupancy modeling and avoidance-attraction ratios (AARs). The results were as follows: (1) different small carnivores exhibited unique spatial and temporal responses to top predators, with leopard cats (Prionailurus bengalensis) preferring to occupy areas occupied by leopards (Panthera pardus), whereas yellow-throated martens (Martes flavigula) and red foxes (Vulpes vulpes) remained spatially independent of leopards; (2) human activities did not significantly affect the spatial activities of small carnivores, but small carnivores exhibited time-resistant behavior toward humans and domestic cattle; and (3) we observed temporal and spatial avoidance between leopard cats and other small carnivores (yellow-throated martens and red foxes). Overall, our study highlights the complex and unexpected behavioral responses and survival strategies of animals within an integrated community. In the future, we aim to further investigate the mechanisms underlying the formation of wildlife communities in this region and to elucidate the potential roles of human activities within this ecological community.

Hyperspectral target detection (HTD) is a crucial aspect of remote sensing applications, aiming to identify targets in hyperspectral images (HSIs) based on their known prior spectral signatures. However, the spectral variability resulting from various imaging conditions in multi-temporal hyperspectral images poses a challenge to both classical and deep learning (DL) methods. To overcome the limitations imposed by spectral variability, an implicit contrastive learning-based target detector (ICLTD) is proposed to exploit in-scene spectra in an unsupervised way. First, only prior spectra are utilized for explicit supervision, while an implicit contrastive learning module (ICLM) is designed to normalize the feature distributions of prior and in-scene spectra. This paper theoretically demonstrates that the ICLM can transfer the gradients from prior spectral features to those of in-scene spectra based on their feature similarities and differences. Because of transferred gradient signals, the ICLTD is regularized to extract similar representations for the prior and in-scene target spectra, while augmenting feature differences between the target and background spectra. Additionally, a local spectral similarity constraint (LSSC) is proposed to enhance the capability of scene adaptation by leveraging the spectral similarities among in-scene targets. To validate the performance of the ICLTD under spectral variability, multi-temporal HSIs captured under various imaging conditions are collected to generate prior spectra and in-scene spectra. Comparative evaluations against several DL detectors and classical methods reveal the superior performance of the ICLTD in achieving a balance between target detectability and background suppressibility under spectral variability.