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CD8 + T cell-mediated cancer clearance is often suppressed by the interaction between inhibitory molecules like PD-1 and PD-L1, an interaction acts like brakes to prevent T cell overreaction under normal conditions but is exploited by tumor cells to escape the immune surveillance. Immune checkpoint inhibitors have revolutionized cancer therapeutics by removing such brakes. Unfortunately, only a minority of cancer patients respond to immunotherapies presumably due to inadequate immunity. Antitumor immunity depends on the activation of the cGAS-STING pathway, as STING-deficient mice fail to stimulate tumor-infiltrating dendritic cells (DCs) to activate CD8 + T cells. STING agonists also enhance natural killer (NK) cells to mediate the clearance of CD8 + T cell-resistant tumors. Therefore STING agonists have been intensively sought after. We previously discovered that manganese (Mn) is indispensable for the host defense against cytosolic dsDNA by activating cGAS-STING. Here we report that Mn is also essential in innate immune sensing of tumors and enhances adaptive immune responses against tumors. Mn-insufficient mice had significantly enhanced tumor growth and metastasis, with greatly reduced tumor-infiltrating CD8 + T cells. Mechanically, Mn 2+ promoted DC and macrophage maturation and tumor-specific antigen presentation, augmented CD8 + T cell differentiation, activation and NK cell activation, and increased memory CD8 + T cells. Combining Mn 2+ with immune checkpoint inhibition synergistically boosted antitumor efficacies and reduced the anti-PD-1 antibody dosage required in mice. Importantly, a completed phase 1 clinical trial with the combined regimen of Mn 2+ and anti-PD-1 antibody showed promising efficacy, exhibiting type I IFN induction, manageable safety and revived responses to immunotherapy in most patients with advanced metastatic solid tumors. We propose that this combination strategy warrants further clinical translation.

Aluminum-containing adjuvants have been used for nearly 100 years to enhance immune responses in billions of doses of vaccines. To date, only a few adjuvants have been approved for use in humans, among which aluminum-containing adjuvants are the only ones widely used. However, the medical need for potent and safe adjuvants is currently continuously increasing, especially those triggering cellular immune responses for cytotoxic T lymphocyte activation, which are urgently needed for the development of efficient virus and cancer vaccines. Manganese is an essential micronutrient required for diverse biological activities, but its functions in immunity remain undefined. We previously reported that Mn2+ is important in the host defense against cytosolic dsDNA by facilitating cGAS-STING activation and that Mn2+ alone directly activates cGAS independent of dsDNA, leading to an unconventional catalytic synthesis of 2′3′-cGAMP. Herein, we found that Mn2+ strongly promoted immune responses by facilitating antigen uptake, presentation, and germinal center formation via both cGAS-STING and NLRP3 activation. Accordingly, a colloidal manganese salt (Mn jelly, MnJ) was formulated to act not only as an immune potentiator but also as a delivery system to stimulate humoral and cellular immune responses, inducing antibody production and CD4+/CD8+ T-cell proliferation and activation by either intramuscular or intranasal immunization. When administered intranasally, MnJ also worked as a mucosal adjuvant, inducing high levels of secretory IgA. MnJ showed good adjuvant effects for all tested antigens, including T cell-dependent and T cell-independent antigens, such as bacterial capsular polysaccharides, thus indicating that it is a promising adjuvant candidate.

Tumor necrosis factor (TNF) drives chronic inflammation and cell death in the intestine, and blocking TNF is a therapeutic approach in inflammatory bowel disease (IBD). Despite this knowledge, the pathways that protect the intestine from TNF are incompletely understood. Here we demonstrate that group 3 innate lymphoid cells (ILC3s) protect the intestinal epithelium from TNF-induced cell death. This occurs independent of interleukin-22 (IL-22), and we identify that ILC3s are a dominant source of heparin-binding epidermal growth factor–like growth factor (HB-EGF). ILC3s produce HB-EGF in response to prostaglandin E2 (PGE2) and engagement of the EP2 receptor. Mice lacking ILC3-derived HB-EGF exhibit increased susceptibility to TNF-mediated epithelial cell death and experimental intestinal inflammation. Finally, human ILC3s produce HB-EGF and are reduced from the inflamed intestine. These results define an essential role for ILC3-derived HB-EGF in protecting the intestine from TNF and indicate that disruption of this pathway contributes to IBD.TNF is an important driver of many inflammatory diseases. Zhou et al. demonstrate ILC3 production of the growth factor HB-EGF protects against TNF-mediated injury of the gut epithelium in inflammatory bowel disease.

Over the last couple of decades, thyroid cancer cases have dramatically increased in frequency year by year. According to certain research, thyroid cancer may be linked to per-fluoroalkyl and poly-fluoroalkyl substances (PFAS) exposure. Our study aimed to investigate the possible link between thyroid cancer and PFAS exposure. Three researchers have looked up the following electronic databases: PubMed, Embase, Web of Science, Scopus, Cochrane, Science Direct, Chinese BioMedical Literature Database (CBM), Wanfang Database, China Science and Technology Journal Database, and China National Knowledge Infrastructure (CNKI) to get the whole articles before March 2024. In addition, Google Scholar was used as a complementary search engine. Finally, eight articles were included in our meta-analysis. It was shown by our results that the link between thyroid cancer and PFAS exposure was not statistically significant, for perfluorononanoic acid (PFNA), odds ratio (OR): 0.71, 95% confidence interval (95% CI): 0.30–1.12; for perfluorooctane sulfonate (PFOS), OR: 0.89, 95% CI: 0.5–1.28; for PFAS mixtures, OR: 1.10, 95% CI: 0.19–2.01. Furthermore, our study revealed that perfluorooctanoic acid (PFOA) exposure could decrease the risk of thyroid cancer (OR: 0.69, 95% CI: 0.44–0.95). These associations of PFOS and PFNA with thyroid cancer were robust in sensitivity analyses. In conclusion, these results increase our knowledge of the impact of PFAS on the thyroid cancer in a novel manner. At the same time, our study has certain limitations, we encourage the inclusion of more high-quality studies in the future.

Aluminum adjuvants have been used for a century in various vaccines due to its ability to potentiate humoral immunity and safety records since 1920s. Manganese is an essential micronutrient required for diverse biological activities in cells. We previously found that Mn2+ is a strong type I-interferon stimulator activating the cGAS-STING pathway. Herein we report that a colloidal manganese salt (MnJ) is a potent adjuvant to induce both humoral and cellular immune responses, particularly CTL activation. When administrated intranasally, MnJ was also a strong mucosal adjuvant, inducing high levels of IgA antibodies. MnJ strongly promoted dendritic cell maturation and antigen-specific T cell activation. Interestingly, IL-1/-18 induction and release by Mn2+-activated ASC-mediated inflammasomes were not observed. MnJ showed great adjuvant effects to all tested antigens including inactivated viruses, recombinant proteins and peptides by either intramuscular or intranasal immunization. These findings may have implications in developing potent but safe Mn2+-containing vaccines.

Background Human sexuality and mating behaviors have been linked to the subjective importance of olfaction and body odor in one’s life. This study aimed to investigate the relationships between sociosexual orientation, subjective importance of olfaction, and body odor sniffing behavior, and to determine whether there is gender and cultural consistency. Methods 1,904 Chinese college students and additional 861 participants from more general population (410 Chinese and 451 Americans) completed three questionnaires measuring sociosexual orientation, subjective importance of olfaction, and body odor sniffing behavior, respectively. Results The results of Study 1 indicated a significant association between sociosexual orientation, subjective importance of olfaction, and body odor sniffing behavior for both males and females. Besides, the subjective importance of olfaction mediated the relationship between sociosexual orientation and body odor sniffing behavior. Results of Study 2 suggested that the relationships were consistent across cultures. Conclusions This study found positive correlations between sociosexual orientation, the subjective importance of olfaction, and body odor sniffing behavior. Subjective importance of olfaction played a mediating role in the relationship between sociosexual orientation and body odor sniffing behavior, and this relationship was consistent across genders and cultures. These findings provide valuable insights into the role of human mating strategies in olfaction.

In our increasingly interconnected world, where intelligent devices continually amass copious personalized multi-modal data, a pressing need arises to deliver high-quality, personalized device-aware services. However, this endeavor presents a multifaceted challenge to prevailing artificial intelligence (AI) systems primarily rooted in the cloud. As these systems grapple with shifting data distributions between the cloud and devices, the traditional approach of fine-tuning-based adaptation (FTA) exists the following issues: the costly and time-consuming data annotation required by FTA and the looming risk of model overfitting. To surmount these challenges, we introduce a Universal On-Device Multi-modal Model Adaptation Framework, revolutionizing on-device model adaptation by striking a balance between efficiency and effectiveness. The framework features the Fast Domain Adaptor (FDA) hosted in the cloud, providing tailored parameters for the Lightweight Multi-modal Model on devices. To enhance adaptability across multi-modal tasks, the AnchorFrame Distribution Reasoner (ADR) minimizes communication costs. Our contributions, encapsulated in the Cloud-Device Collaboration Multi-modal Parameter Generation (CDC-MMPG) framework, represent a pioneering solution for on-Device Multi-modal Model Adaptation (DMMA). Extensive experiments validate the efficiency and effectiveness of our method, particularly in video question answering and retrieval tasks, driving forward the integration of intelligent devices into our daily lives.

Revolutionary advancements in text-to-image models have unlocked new dimensions for sophisticated content creation, such as text-conditioned image editing, enabling the modification of existing images based on textual guidance. This capability allows for the generation of diverse images that convey highly complex visual concepts. However, existing methods primarily focus on generating new images from text-image pairs and struggle to produce fine-grained animations from existing images and textual guidance without fine-tuning. In this paper, we introduce LASER, a tuning-free LLM-driven attention control framework that follows a progressive process: LLM planning, feature-attention injection, and stable animation generation. LASER leverages a large language model (LLM) to refine general descriptions into fine-grained prompts, guiding pre-trained text-to-image models to generate aligned keyframes with subtle variations. The LLM also generates control signals for feature and attention injections, enabling seamless text-guided image morphing for various transformations without additional fine-tuning. By using the same initial noise inversion from the input image, LASER receives LLM-controlled injections during denoising and leverages interpolated text embeddings to produce a series of coherent animation frames. We propose a Text-conditioned Image-to-Animation Benchmark to validate the effectiveness and efficacy of LASER. Extensive experiments demonstrate that LASER achieves impressive results in consistent and efficient animation generation, establishing it as a powerful tool for producing detailed animations and opening new avenues in digital content creation.

Active Domain Adaptation (ADA) aims to maximally boost model adaptation in a new target domain by actively selecting a limited number of target data to annotate.This setting neglects the more practical scenario where training data are collected from multiple sources. This motivates us to target a new and challenging setting of knowledge transfer that extends ADA from a single source domain to multiple source domains, termed Multi-source Active Domain Adaptation (MADA). Not surprisingly, we find that most traditional ADA methods cannot work directly in such a setting, mainly due to the excessive domain gap introduced by all the source domains and thus their uncertainty-aware sample selection can easily become miscalibrated under the multi-domain shifts. Considering this, we propose a Dynamic integrated uncertainty valuation framework(Detective) that comprehensively consider the domain shift between multi-source domains and target domain to detect the informative target samples. Specifically, the leverages a dynamic Domain Adaptation(DA) model that learns how to adapt the model's parameters to fit the union of multi-source domains. This enables an approximate single-source domain modeling by the dynamic model. We then comprehensively measure both domain uncertainty and predictive uncertainty in the target domain to detect informative target samples using evidential deep learning, thereby mitigating uncertainty miscalibration. Furthermore, we introduce a contextual diversity-aware calculator to enhance the diversity of the selected samples. Experiments demonstrate that our solution outperforms existing methods by a considerable margin on three domain adaptation benchmarks.