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In recent decades, immune checkpoint blockade and chimeric antigen receptor T cell (CAR-T) therapy are two milestone achievements in clinical immunotherapy. However, both show limited efficacies in most solid neoplasms, which necessitates the exploration of new immunotherapeutic modalities. The failure of CAR-T and immune checkpoint blockade in several solid neoplasms is attributed to multiple factors, including low antigenicity of tumor cells, low infiltration of effector T cells, and diverse mechanisms of immunosuppression in the tumor microenvironment. New adoptive cell therapies have been attempted for solid neoplasms, including TCR-T, CAR-natural killer cells (CAR-NK), and CAR-macrophages (CAR-M). Compared to CAR-T, these new adoptive cell therapies have certain advantages in treating solid neoplasms. In this review, we summarized the 40-year evolution of adoptive cell therapies, then focused on the advances of TCR-T, CAR-NK, and CAR-M in solid neoplasms and discussed their potential clinical applications.

A double-cavity Fabry-Perot (F-P) interferometer sensor based on a polymer-filled hollow core fiber (HCF) has been proposed and experimentally verified. The double cavity of the sensor is formed by filling the hollow core fiber with two kinds of polymer materials and curing these materials, with the other end of the hollow core fiber connected to a single-mode fiber (SMF). The three reflective surfaces of the sensor reflect three beams of light, which interfere to form a spectrum with an envelope. By using Fast Fourier Transform (FFT) and a Fourier filter, the spectrum of each cavity can be separated and, based on this, the demodulation matrix of the sensor can be constructed. By controlling the length of the polymer cavity, a single sensor cavity can achieve high temperature and gas pressure sensitivity, with values of 2.05 nm/°C and 17.63 nm/MPa, respectively. More importantly, the sensor can be used under an environment of 40–110 °C and 0–3.0 MPa, with simple fabrication, good robustness, and better stability and repeatability compared to similar sensors. Based on its high sensitivity and large measurement range, this sensor has broad application prospects in industrial manufacturing and harsh environmental monitoring fields.

Background Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors. Macrophages are abundant in the tumor microenvironment, making them an attractive target for therapeutic intervention. While current immunotherapies, including immune checkpoint inhibition (ICI) and chimeric antigen receptor T (CAR-T) cells, have shown limited efficacy in pancreatic cancer, a novel approach involving chimeric antigen receptor macrophages (CAR-M) has, although promising, not been explored in pancreatic cancer. In this study, we first investigated the role of CAR-M cells targeting c-MET in pancreatic cancer. Methods The effectiveness and rationality of c-MET as a target for CAR-M in pancreatic cancer were validated through bioinformatic analyses and immunohistochemical staining of samples from pancreatic cancer patients. We utilized flow cytometry and bioluminescence detection methods to demonstrate the specific binding and phagocytic killing effect of CAR-M on pancreatic cancer cells. Additionally, we observed the process of CAR-M engulfing pancreatic cancer cells using confocal microscopy and a long-term fluorescence live cell imaging system. In an in situ tumor model transplanted into NOD/SCID mice, we administered intraperitoneal injections of CAR-M to confirm its inhibitory function on pancreatic cancer. Furthermore, we validated these findings in human monocyte-derived macrophages (hMDM). Results Bioinformatics and tumor tissue microarray analyses revealed significantly higher expression levels of c-MET in tumor tissues, compared to the paired peritumoral tissues, and higher c-MET expression correlated with worse patient survival. CAR-M cells were engineered using human monocytic THP-1 cell line and hMDM targeting c-MET (CAR-M-c-MET). The CAR-M-c-MET cells demonstrated highly specific binding to pancreatic cancer cells and exhibited more phagocytosis and killing abilities than the pro-inflammatory polarized control macrophages. In addition, CAR-M-c-MET cells synergized with various cytotoxic chemotherapeutic drugs. In a NOD/SCID murine model, intraperitoneally injected CAR-M-c-MET cells rapidly migrated to tumor tissue and substantially inhibited tumor growth, which did not lead to obvious side effects. Cytokine arrays and mRNA sequencing showed that CAR-M-c-MET produced higher levels of immune activators than control macrophages. Conclusions This study provides compelling evidence for the safety and efficacy of CAR-M therapy in treating pancreatic cancer. The results demonstrate that CAR-M-c-MET significantly suppresses pancreatic cancer progression and enhances the effectiveness of cytotoxic chemotherapy. Remarkably, no discernible side effects occur. Further clinical trials are warranted in human pancreatic cancer patients.

BackgroundMembrane (m) CD58 is a co-stimulatory ligand that binds to CD2, and the CD2-(m) CD58 axis participates in lymphocyte activation. In addition to mCD58, a soluble form of CD58 (sCD58) has been reported in human serum, urine, and in vitro cell culture supernatants. The role of sCD58 in the tumor immune microenvironment of pancreatic ductal adenocarcinoma (PDAC) is currently unknown.MethodsThe expression and prognostic role of CD58 in PDAC tissues were analyzed using various public databases. Then, the phenomenon of expressional separation of CD58 in PDAC cells induced by macrophages was observed by flow cytometry and ELISA, where the decrease of mCD58 on the membrane surface is accompanied by the increase of sCD58 in the supernatant. The molecular mechanisms of the expressional separation of CD58 were further explored by focusing on the TGF-β signaling pathway. The effects of expressional separation of CD58 on the immune activity and killing ability of T/NK cells for PDAC were determined in co-culture models. Furthermore, subcutaneous tumor-bearing models, lung metastasis models, and intraperitoneal dissemination models were used to confirm the in vitro data. Finally, the diagnostic and prognostic roles of serum sCD58 were determined by using 561 samples from PDAC patients, benign pancreatic disease patients, and healthy controls.ResultsElevated CD58 expression in PDAC tissues was associated with worse clinical outcomes. After co-culture with PDAC cells, macrophages adopted an M2 phenotype, characterized by a high expression level of TGF-β. Co-cultured macrophages could induce the expressional separation of CD58 in PDAC cells. Activation of the TGF-β/Smad2/3 pathway markedly promoted this separation, and pathway inhibition largely blocked it. In vitro and in vivo assays revealed that mCD58 engaged CD2 on T/NK cells, facilitated their activation, enhanced their cytotoxicity, and stimulated the release of the anti-tumoral cytokines IFN-γ and TNF-α. Conversely, local high concentrations of sCD58 accumulation in PDAC tissues interfered with the CD2-CD58 axis by competitively binding CD2, inhibited the activation of T/NK cells, reduced T/NK cytotoxicity, and the secretion of IFN-γ and TNF-α. Furthermore, serum sCD58 levels were higher in the PDAC patients than in the healthy controls or patients with benign pancreatic diseases. sCD58 improved the diagnostic and prognostic power of CA199 in PDAC patients. A combined model incorporating CA199, TGF-β1, and sCD58 yielded an AUC (area under the curve) value of 0.946 for overall diagnosis. In the CA199 negative cohort, the combined model of TGF-β and sCD58 achieved an AUC of 0.955.ConclusionsThis study uncovers a novel vicious crosstalk among macrophages, T/NK cells, and PDAC cells within the tumor microenvironment. Macrophages drive the expressional separation of CD58 via the TGF-β/Smad2/3 signaling pathway. This shift suppresses T/NK-cell activity, allows tumor cells to evade immune killing, and accelerates PDAC progression. In addition, serum sCD58 emerges as a promising diagnostic and prognostic biomarker for PDAC.

We introduce GraphNet, a dataset of 2.7K real-world deep learning computational graphs with rich metadata, spanning six major task categories across multiple deep learning frameworks. To evaluate tensor compiler performance on these samples, we propose the benchmark metric Speedup Score S(t), which jointly considers runtime speedup and execution correctness under tunable tolerance levels, offering a reliable measure of general optimization capability. Furthermore, we extend S(t) to the Error-aware Speedup Score ES(t), which incorporates error information and helps compiler developers identify key performance bottlenecks. In this report, we benchmark the default tensor compilers, CINN for PaddlePaddle and TorchInductor for PyTorch, on computer vision (CV) and natural language processing (NLP) samples to demonstrate the practicality of GraphNet. The full construction pipeline with graph extraction and compiler evaluation tools is available at https://github.com/PaddlePaddle/GraphNet .

Objective and design Chronic low-grade inflammation occurs in diabetic retinopathy (DR), but the underlying mechanism(s) remains (remain) unclear. NLRP3 inflammasome activation is involved in several other inflammatory diseases. Thus, we investigated the role of the NLRP3 inflammasome signaling pathway in the pathogenesis of DR. Methods Diabetes was induced in rats by streptozotocin treatment for 8 weeks. They were treated with NLRP3 shRNA or minocycline during the last 4 weeks. High glucose-exposed human retinal microvascular endothelial cells (HRMECs) were co-incubated with antioxidants or subjected to TXNIP or NLRP3 shRNA interference. Results In high glucose-exposed HRMECs and retinas of diabetic rats, mRNA and protein expression of NLRP3, ASC, and proinflammatory cytokines were induced significantly by hyperglycemia. Upregulated interleukin (IL)-1β maturation, IL-18 secretion, and caspase-1 cleavage were also observed with increased cell apoptosis and retinal vascular permeability, compared with the control group. NLRP3 silencing blocked these effects in the rat model and HRMECs, confirming that inflammasome activation contributed to inflammation in DR. TXNIP expression was increased by reactive oxygen species (ROS) overproduction in animal and cell models, whereas antioxidant addition or TXNIP silencing blocked IL-1β and IL-18 secretion in high glucose-exposed HRMECs, indicating that the ROS–TXNIP pathway mediates NLRP3 inflammasome activation. Minocycline significantly downregulated ROS generation and reduced TXNIP expression, subsequently inhibited NLRP3 activation, and further decreased inflammatory factors, which were associated with a decrease in retinal vascular permeability and cell apoptosis. Conclusions Together, our data suggest that the TXNIP/NLRP3 pathway is a potential therapeutic target for the treatment of DR, and the use of minocycline specifically for such therapy may be a new avenue of investigation in inflammatory disease.

Background Fungal keratitis (FK) is a serious corneal disease that was considered as the main cause of vision loss in developing countries. Early diagnosis and timely treatment of FK can significantly strengthen the curative effect and decrease the risk of the blindness. The fungal spectrum varies and is closely associated with climate and geographic location. The clinical characteristics of FK in eastern China are limited. We explored the risk factors, fungal species, characteristics of in vivo confocal microscopy (IVCM), and treatment of FK in a tertiary referral hospital in eastern China. Methods This retrospective study encompassed a thorough analysis of clinical data, IVCM images, and fungal cultures in FK between January 2021 and May 2024. The clinical profiles, microbial characteristics, and therapeutic outcomes of these patients were meticulously analyzed. Results A total of 174 patients were diagnosed with FK. Seven fungal species were identified in 104 culture-positive cases. Fusarium was the most common species (49.04%), followed by Alternaria (23.08%) and Aspergillus (15.38%). 166 (95.4%) patients showed evidence of mycelia or spores in IVCM images. Diverse fungal strains typically showed varied culture characteristics and IVCM expressions. 42 (24.14%) patients were successfully treated with topical medicine alone, and 132 (75.86%) patients needed additional surgical therapies, including intrastromal injections of voriconazole (38.51%), conjunctival pedicle flap surgery (8.05%), lamellar keratoplasty (22.41%), penetrating keratoplasty (4.02%), and enucleation (2.87%). Visual acuity improved in 104 patients (59.77%), but remained unchanged in 36 (20.69%) patients and decreased in 34 patients (19.54%) following active treatment. Conclusions fusarium was the most frequently isolated species, followed by Alternaria and Aspergillus .

Creation of structured light at‐source with determinate orbital angular momentum (OAM) states is a fascinating branch of modern optics, owing to their integrability, wavelength insensitivity, and high mode purity. However, mode degeneracy in spatially column‐symmetric cylindrical coordinate systems leads to a total zero OAM states which seriously limits their development and applications. Here, a strategy is proposed for symmetry breaking of the degenerate OAM states relying on the natural anisotropy of crystal gain, to select the handedness of the spatial spiral phase front and further tunable Raman‐like OAM states by thermal‐driven, experimentally realized arbitrary OAM states from −2ћ to ћ. The concept presented herein clarifies the contribution of intrinsic crystal property to the OAM states and opens a new route for an at‐source solution of structure light with high integrability and controllable OAM states. This work proposes a strategy for symmetry breaking of the degenerate OAM states relying on the natural anisotropy of crystal gain, to select the handedness of the spatial spiral phase front and further tunable Raman‐like OAM states by thermal‐driven, which clarifies the contribution of intrinsic crystal property to the OAM states and opens a new route for an at‐source solution of structure light with high integrability and controllable OAM states.

We investigate the generation of ultraviolet (UV) second-harmonic radiation at the boundary of a UV transparent crystal, which is derived from the automatic partial phase matching of the incident wave and the total internal reflection. By adhering to another UV non-transparent crystal with a larger second-order nonlinear coefficient χ (2) , a nonlinear interface with large disparity in χ (2) is formed and the enhancement of UV second-harmonic radiation is observed experimentally. The intensity of enhanced second harmonic wave generated at the nonlinear interface is up to 11.6 times that at the crystal boundary. As a tunable phase-matching method, it may suggest potential applications in the UV, and even vacuum-UV region.

A camera-based visiometer is a promising atmospheric visibility measurement tool because it can meet some specific demands such as the need for visibility monitoring in a strong way, whereas traditional instruments, such as forward scatter-type sensors and transmissometers, can hardly be widely utilized due to their high cost. The camera-based method is used to measure visibility by recording the luminance contrast of the objects in an image. However, lacking standard conditions, they can hardly obtain absolute measurements even with blackbody objects. In this paper, the errors caused by nonstandard conditions in camera-based visiometers with two artificial black bodies are analyzed. The results show that the luminance contrasts of the two blackbodies are highly dependent on the environmental radiance distribution. The nonuniform sky illuminance can cause a large error in the blackbody contrast estimations, leading to substantial visibility measurement errors. A method based on a support vector machine (SVM) is proposed to classify the visibility under nonstandard conditions to ensure the reliability of the camera-based visiometer. A classification accuracy of 96.77% was achieved for the data containing images depicting different illumination conditions (e.g., a clear sky, cloudy sky, and overcast). The results show that the classifier based on the SVM is an effective and reliable method to estimate visibility under complex conditions.