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Immunotherapy, represented by immune checkpoint inhibitors (ICIs), has greatly improved the clinical efficacy of malignant tumor therapy. ICI-mediated antitumor responses depend on the infiltration of T cells capable of recognizing and killing tumor cells. ICIs are not effective in \"cold tumors\", which are characterized by the lack of T-cell infiltration. To realize the full potential of immunotherapy and solve this obstacle, it is essential to understand the drivers of T-cell infiltration into tumors. We present a critical review of our understanding of the mechanisms underlying \"cold tumors\", including impaired T-cell priming and deficient T-cell homing to tumor beds. \"Hot tumors\" with significant T-cell infiltration are associated with better ICI efficacy. In this review, we summarize multiple strategies that promote the transformation of \"cold tumors\" into \"hot tumors\" and discuss the mechanisms by which these strategies lead to increased T-cell infiltration. Finally, we discuss the application of nanomaterials to tumor immunotherapy and provide an outlook on the future of this emerging field. The combination of nanomedicines and immunotherapy enhances cross-presentation of tumor antigens and promotes T-cell priming and infiltration. A deeper understanding of these mechanisms opens new possibilities for the development of multiple T cell-based combination therapies to improve ICI effectiveness.

Dynamic electric field frequency actuated helical and spiral structures enable a plethora of attributes for advanced photonics and engineering in the contemporary era. Nevertheless, leveraging the frequency responsiveness of adaptive devices and systems within a broad dynamic range and maintaining restrained high-frequency induced heating remain challenging. Herein, we establish a frequency-actuated heliconical soft architecture that is quite distinct from that of common frequency-responsive soft materials. We achieve reversible modulation of the photonic bandgap in a wide spectral range by delicately coupling the frequency-dependent thermal effect, field-induced dielectric torque and elastic equilibrium. Furthermore, an information encoder prototype without the aid of complicated algorithm design is established to analogize an information encoding and decoding process with a more convenient and less costly way. A technique for taming and tailoring the distribution of the pitch length is exploited and embodied in a prototype of a spatially controlled soft photonic cavity and laser emission. This work demonstrates a distinct frequency responsiveness in a heliconical soft system, which may not merely inspire the interest in field-assisted bottom-up molecular engineering of soft matter but also facilitate the practicality of adaptive photonics. Frequency responsiveness within a broad dynamic range in adaptive systems while also reducing high-frequency induced heating remains a challenge for advanced photonics. Here, authors report a frequency-actuated heliconical soft architecture with reversible modulation of the photonic bandgap in a wide spectral range.

Effectively activating macrophages against cancer is promising but challenging. In particular, cancer cells express CD47, a ‘don’t eat me’ signal that interacts with signal regulatory protein alpha (SIRPα) on macrophages to prevent phagocytosis. Also, cancer cells secrete stimulating factors, which polarize tumor-associated macrophages from an antitumor M1 phenotype to a tumorigenic M2 phenotype. Here, we report that hybrid cell membrane nanovesicles (known as hNVs) displaying SIRPα variants with significantly increased affinity to CD47 and containing M2-to-M1 repolarization signals can disable both mechanisms. The hNVs block CD47-SIRPα signaling axis while promoting M2-to-M1 repolarization within tumor microenvironment, significantly preventing both local recurrence and distant metastasis in malignant melanoma models. Furthermore, by loading a stimulator of interferon genes (STING) agonist, hNVs lead to potent tumor inhibition in a poorly immunogenic triple negative breast cancer model. hNVs are safe, stable, drug loadable, and suitable for genetic editing. These properties, combined with the capabilities inherited from source cells, make hNVs an attractive immunotherapy. The application of STING agonists and the blockade of the SIRPα–CD47 signaling axis are emerging immunotherapeutic strategies. Here the authors show that hybrid cellular membrane nanovesicles loaded with a STING agonist or overexpressing high-affinity SIRPα variants can be exploited to promote anti-tumor immune responses.

The era of Big Data requires nanophotonic chips to have large information processing capacity. Multiple frequency on-chip nanophotonic devices are highly desirable for density integration, but such devices are more susceptible to structural imperfection because of their nano-scale. Topological photonics provides a robust platform for next-generation nanophotonic chips. Here we give an experimental report of an on-chip nanophotonic topological rainbow realized by employing a translational deformation freedom as a synthetic dimension. The topological rainbow can separate, slow, and trap topological photonic states of different frequencies into different positions. A homemade scattering scanning near-field optical microscope with high resolution is introduced to directly measure the topological rainbow effect of the silicon-based photonic chip. The topological rainbow based on synthetic dimension have no restrictions for optical lattice types, symmetries, materials, wavelength band, and is easy for on-chip integration. This work builds a bridge between silicon chip technologies and topological photonics. Here the authors provide the experimental observation of a topological rainbow in a silicon-based nanophotonic chip. The system is robust against disorders allows to separate and trap topological photonic states of different wavelength into different positions.

Methanol is regarded as an important liquid fuel for hydrogen storage, transportation, and in-situ generation due to its convenient conveyance, high energy density, and low conversion temperature. In this work, an overview of state-of-the-art investigations on methanol reforming is critically summarized, including the detailed introduction of methanol conversion pathways from the perspective of fuel cell applications, various advanced materials design for catalytic methanol conversion, as well as the development of steam methanol reformers. For the section of utilization pathways, reactions such as steam reforming of methanol, partial oxidation of methanol, oxidative steam reforming of methanol, and sorption-enhanced steam methanol reforming were elaborated; For the catalyst section, the strategies to enhance the catalytic activity and other comprehensive performances were summarized; For the reactor section, the newly designed steam methanol reformers were thoroughly described. This review will benefit researchers from both fundamental research and fuel cell applications in the field of catalyzing methanol to hydrogen.

ObjectivesTo utilize a deep learning model for automatic detection of abnormalities in chest CT images from COVID-19 patients and compare its quantitative determination performance with radiological residents.MethodsA deep learning algorithm consisted of lesion detection, segmentation, and location was trained and validated in 14,435 participants with chest CT images and definite pathogen diagnosis. The algorithm was tested in a non-overlapping dataset of 96 confirmed COVID-19 patients in three hospitals across China during the outbreak. Quantitative detection performance of the model was compared with three radiological residents with two experienced radiologists’ reading reports as reference standard by assessing the accuracy, sensitivity, specificity, and F1 score.ResultsOf 96 patients, 88 had pneumonia lesions on CT images and 8 had no abnormities on CT images. For per-patient basis, the algorithm showed superior sensitivity of 1.00 (95% confidence interval (CI) 0.95, 1.00) and F1 score of 0.97 in detecting lesions from CT images of COVID-19 pneumonia patients. While for per-lung lobe basis, the algorithm achieved a sensitivity of 0.96 (95% CI 0.94, 0.98) and a slightly inferior F1 score of 0.86. The median volume of lesions calculated by algorithm was 40.10 cm3. An average running speed of 20.3 s ± 5.8 per case demonstrated the algorithm was much faster than the residents in assessing CT images (all p < 0.017). The deep learning algorithm can also assist radiologists make quicker diagnosis (all p < 0.0001) with superior diagnostic performance.ConclusionsThe algorithm showed excellent performance in detecting COVID-19 pneumonia on chest CT images compared with resident radiologists.Key Points• The higher sensitivity of deep learning model in detecting COVID-19 pneumonia were found compared with radiological residents on a per-lobe and per-patient basis.• The deep learning model improves diagnosis efficiency by shortening processing time.• The deep learning model can automatically calculate the volume of the lesions and whole lung.

The blood-brain barrier breakdown, as a prominent feature after traumatic brain injury, always triggers a cascade of biochemical events like inflammatory response and free radical-mediated oxidative damage, leading to neurological dysfunction. The dynamic monitoring the status of blood-brain barrier will provide potent guidance for adopting appropriate clinical intervention. Here, we engineer a near-infrared-IIb Ag 2 Te quantum dot-based Mn single-atom catalyst for imaging-guided therapy of blood-brain barrier breakdown of mice after traumatic brain injury. The dynamic change of blood-brain barrier, including the transient cerebral hypoperfusion and cerebrovascular damage, could be resolved with high spatiotemporal resolution (150 ms and ~ 9.6 µm). Notably, the isolated single Mn atoms on the surface of Ag 2 Te exhibited excellent catalytic activity for scavenging reactive oxygen species to alleviate neuroinflammation in brains. The timely injection of Mn single-atom catalyst guided by imaging significantly promoted the reconstruction of blood-brain barrier and recovery of neurological function after traumatic brain injury. Monitoring the status of blood-brain barrier (BBB) and inhibiting reactive oxygen species (ROS)-mediated oxidative damage are key issues in the treatment of traumatic brain injury (TBI). Here, the authors design a near-infrared-IIb emitting Mn single-atom catalyst for imaging-guided therapy to alleviate ROS mediated neuroinflammation in the brain and simultaneously obtain timely feedback of therapeutic effect, promoting the reconstruction of BBB and recovery of neurological function after TBI in mice.

The absence of tumor antigens leads to a low response rate, which represents a major challenge in immune checkpoint blockade (ICB) therapy. Pyroptosis, which releases tumor antigens and damage‐associated molecular patterns (DAMPs) that induce antitumor immunity and boost ICB efficiency, potentially leads to injury when occurring in normal tissues. Therefore, a strategy and highly efficient agent to induce tumor‐specific pyroptosis but reduce pyroptosis in normal tissues is urgently required. Here, a smart tumor microenvironmental reactive oxygen species (ROS)/glutathione (GSH) dual‐responsive nano‐prodrug (denoted as MCPP) with high paclitaxel (PTX) and photosensitizer purpurin 18 (P18) loading is rationally designed. The ROS/GSH dual‐responsive system facilitates the nano‐prodrug response to high ROS/GSH in the tumor microenvironment and achieves optimal drug release in tumors. ROS generated by P18 after laser irradiation achieves controlled release and induces tumor cell pyroptosis with PTX by chemo‐photodynamic therapy. Pyroptotic tumor cells release DAMPs, thus initiating adaptive immunity, boosting ICB efficiency, achieving tumor regression, generating immunological memory, and preventing tumor recurrence. Mechanistically, chemo‐photodynamic therapy and control‐release PTX synergistically induce gasdermin E (GSDME)‐related pyroptosis. It is speculated that inspired chemo‐photodynamic therapy using the presented nano‐prodrug strategy can be a smart strategy to trigger pyroptosis and augment ICB efficiency. A smart tumor microenvironmental reactive oxygen species/glutathione dual‐responsive nano‐prodrug (denoted as MCPP) with high paclitaxel and photosensitizer purpurin 18 loading is designed. Chemo‐photodynamic therapy using the presented nano‐prodrug strategy can be a smart strategy to trigger pyroptosis and augment the efficiency of immune checkpoint blockade therapy.

Oncolytic viruses (OVs) show promise as a cancer treatment by selectively replicating in tumor cells and promoting antitumor immunity. However, the current immunogenicity induced by OVs for tumor treatment is relatively weak, necessitating a thorough investigation of the mechanisms underlying its induction of antitumor immunity. Here, we show that HSV-1-based OVs (oHSVs) trigger ZBP1-mediated PANoptosis (a unique innate immune inflammatory cell death modality), resulting in augmented antitumor immune effects. Mechanistically, oHSV enhances the expression of interferon-stimulated genes, leading to the accumulation of endogenous Z-RNA and subsequent activation of ZBP1. To further enhance the antitumor potential of oHSV, we conduct a screening and identify Fusobacterium nucleatum outer membrane vesicle ( Fn -OMV) that can increase the expression of PANoptosis execution proteins. The combination of Fn -OMV and oHSV demonstrates potent antitumor immunogenicity. Taken together, our study provides a deeper understanding of oHSV-induced antitumor immunity, and demonstrates a promising strategy that combines oHSV with Fn -OMV. The potential of oncolytic virus (OV) for cancer therapy is limited by the efficiency of immune response induced. Here the authors show that HSV-1-based OV is capable of triggering ZBP1-mediated PANoptosis resulting in effective tumor growth inhibition.

In this work, we study higher bottomonia up to the \\[nL=8S\\], 6P, 5D, 4F, 3G multiplets using the modified Godfrey–Isgur (GI) model, which takes account of color screening effects. The calculated mass spectra of bottomonium states are in reasonable agreement with the present experimental data. Based on spectroscopy, partial widths of all allowed radiative transitions, annihilation decays, hadronic transitions, and open-bottom strong decays of each state are also evaluated by applying our numerical wave functions. Comparing our results with the former results, we point out difference among various models and derive new conclusions obtained in this paper. Notably, we find a significant difference between our model and the GI model when we study D, F, and G and \\[n 4\\] states. Our theoretical results are valuable to search for more bottomonia in experiments, such as LHCb, and forthcoming Belle II.