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Tongue squamous cell carcinoma (TSCC) is a common malignant oral cancer characterized by substantial invasion, a high rate of lymph node and distant metastasis, and a high recurrence rate. This study aims to provide new ideas for the diagnosis and treatment of TSCC patients by exploring the related mechanisms that affect the migration and invasion of TSCC and inhibit the migration and spread of cancer cells. The results indicated the rate of high expression of IL-17 in cancer tissues was greater than that in tongue tissues, and the expression of IL-17 was related to the TNM stage. The expression of IL-17 in Cal-27 cells was greater than that in HOEC. With increasing IL-17 concentration, cell proliferation, migration, and invasion increased, and the apoptosis rate decreased. After adding the IL-17 inhibitor, the cell proliferation, invasion, and migration abilities decreased, the apoptosis rate increased, and the expression of JAK1and p-STAT3 decreased.IL-17 is highly expressed in oral tongue squamous cell carcinoma and is involved in the occurrence and development of TSCC, possibly through the JAK‒Stat signaling pathway. This study provides a new target and theoretical basis for treating tongue squamous cell carcinoma.

Objective This study aimed to compare the stress distribution after folded and single-layer fibular reconstruction with implant-supported restoration for Brown Class Ⅱ mandibular defects using finite element analysis (FEA), to provide a theoretical basis for selecting an optimal mandibular reconstruction strategy in clinical practice. Methods A healthy adult female volunteer from Bengbu Medical University underwent spiral computed tomography (CT) scans of the mandible and fibula. The CT data were imported into Mimics 21.0 software to reconstruct three-dimensional models of the intact mandible, dentition, and fibula. These models were further processed in Geomagic Studio 2014, Materialise 3-matic 18.0, and Exocad to establish FEA models of the intact mandible, as well as single-layer (Model A) and folded (Model B) fibular reconstruction with implant-supported restoration for Brown Class Ⅱ mandibular defects. The geometric models were then imported into Ansys 19.0 software for FEA to evaluate biomechanical characteristics and stress distribution patterns on implants, the reconstructed fibula, and surrounding bone tissues were compared between the two reconstruction methods. Results (1) Under identical loading conditions, stress concentration areas in the intact mandible were observed at the bilateral condylar necks, sigmoid notches, mandibular angles, and junctions between the mandibular body and ramus, with the maximum stress (57.627 MPa) located at the affected-side mandibular angle. (2) In Model A and Model B, the maximum stresses in the residual mandible were 82.619 MPa and 80.842 MPa, respectively, both at the affected-side mandibular angle, representing increases of 43.4% and 40.3% compared to the intact mandible (57.627 MPa). (3) The maximum stress in the reconstructed fibula was 65.31 MPa in Model B, which was lower than the 73.922 MPa in Model A. (4) The maximum stresses in implants 1, 2, and 3 were 19.496 MPa, 50.638 MPa, and 78.747 MPa in Model B, and 32.537 MPa, 99.558 MPa, and 123.14 MPa in Model A, all located at the implant necks. Conclusion Compared with the single-layer fibular flap, the folded fibular flap is a superior choice for the reconstruction of Brown Class Ⅱ mandibular defects with subsequent implant restoration.

Under chronic infections or in tumors, persistent antigen exposure drives CD8 T cell exhaustion, a heterogeneous state encompassing a differentiation continuum from stem-like progenitor (Tpex) cells through transitory effector-like (Tex-int) cells to terminally exhausted (Tex-term) subsets. Among these T cell subsets, Tex-int cells serve as the primary population responsible for direct tumor cell killing. However, the intrinsic regulatory mechanisms that govern the Tpex-to-Tex-int transition remain incompletely defined. In this study, we explore the role of special AT-rich sequence-binding protein 1 (SATB1) in the differentiation of Tex-int cells from their precursors. We observed downregulation of SATB1 during Tpex-to-Tex-int differentiation in tumors. Notably, the genetic ablation of in T cells markedly expanded the population of tumor-infiltrating CD8 T cells (CD8 TILs). Ablating not only promoted the differentiation of Tex-int cells from Tpex cells within the tumor microenvironment but also remodeled T cell differentiation in tumor-draining lymph nodes (TdLNs) by expanding the Tpex pool from tumor-specific memory CD8 T cells (T ) and driving the Tpex1 to Tpex2 transition, thereby augmenting Tex-int production in tumors. Although early-stage Tex-int cells in -deficient mice displayed transient functional impairment relative to controls, this difference was no longer evident in late-stage tumors, where sustained Tex-int accumulation correlated with significantly suppressed tumor growth and prolonged survival. Our results identify SATB1 as a pivotal regulator of exhausted CD8 T cell subset differentiation and suggest its targeting as a promising strategy to expand the Tex-int population for enhanced cancer immunotherapy.

This paper focuses on the effect of malondialdehyde-induced oxidative modification (MiOM) on the gel properties of duck myofibrillar proteins (DMPs). DMPs were first prepared and treated with oxidative modification at different concentrations of malondialdehyde (0, 0.5, 2.5, 5.0, and 10.0 mmol/L). The physicochemical changes (carbonyl content and free thiol content) and gel properties (gel whiteness, gel strength, water holding capacity, rheological properties, and microstructural properties) were then investigated. The results showed that the content of protein carbonyl content increased with increasing MDA oxidation (p < 0.05), while the free thiol content decreased significantly (p < 0.05). Meanwhile, there was a significant decrease in gel whiteness; the gel strength and water-holding capacity of protein gels increased significantly under a low oxidation concentration of MDA (0–5 mmol/L); however, the gel strength decreased under a high oxidation concentration (10 mmol/L) compared with other groups (0.5–5 mmol/L). The storage modulus and loss modulus of oxidized DMPs also increased with increasing concentrations at a low concentration of MDA (0–5 mmol/L); moreover, microstructural analysis confirmed that the gels oxidized at low concentrations (0.5–5 mmol/L) were more compact and homogeneous in terms of pore size compared to the high concentration or blank group. In conclusion, moderate oxidation of malondialdehyde was beneficial to improve the gel properties of duck; however, excessive oxidation was detrimental to the formation of dense structured gels.

Introduction and objective Oral squamous cell carcinoma (OSCC) is a highly malignant tumor that is prone to lymph node metastasis and distant metastasis. FoxP3 is a specific surface marker of regulatory T cells, and its role in various tumors has been confirmed, which is related to tumor progression and prognosis. However, there are relatively few studies on FoxP3 in OSCC, and the role of FoxP3 in OSCC remains unclear. Materials and methods In this study, the expression of FoxP3 in OSCC was analyzed using data from the TCGA public database. Additionally, 78 OSCC patient samples were analyzed using immunohistochemistry to evaluate the role of FoxP3 in the prognosis of OSCC. The data from TCGA were then investigated using GSEA to explore possible carcinogenic mechanisms. Finally, the online analysis website TIMER was used to analyze the relationship between FoxP3 expression and tumor-associated immune cells. Results The expression of FoxP3 was up-regulated in OSCC tumor tissues, and the expression level was related to the stage of OSCC. The high expression of FoxP3 was associated with better overall survival. FoxP3 expression was positively correlated with the infiltration level of CD4 + T cells, CD8 + T cells, macrophages, neutrophils and dendritic cells. Conclusions FoxP3 plays an important role in the progression of OSCC and may be related to the prognosis of the tumor. Highlights The expression of FoxP3 was up-regulated in oral squamous cell carcinoma tumor tissues. The expression of FoxP3 was related to the stage of oral squamous cell carcinoma. The high expression of FoxP3 was associated with better overall survival. FoxP3 expression was positively correlated with the infiltration level of CD4 + T cells, CD8 + T cells, macrophages, neutrophils and dendritic cells.

Few-shot object detection (FSOD) aims at extending a generic detector for novel object detection with only a few training examples. It attracts great concerns recently due to the practical meanings. Meta-learning has been demonstrated to be an effective paradigm for this task. In general, methods based on meta-learning employ an additional support branch to encode novel examples (a.k.a. support images) into class prototypes, which are then fused with query branch to facilitate the model prediction. However, the class-level prototypes are difficult to precisely generate, and they also lack detailed information, leading to instability in performance.New methods are required to capture the distinctive local context for more robust novel object detection. To this end, we propose to distill the most representative support features into fine-grained prototypes. These prototypes are then assigned into query feature maps based on the matching results, modeling the detailed feature relations between two branches. This process is realized by our Fine-Grained Feature Aggregation (FFA) module. Moreover, in terms of high-level feature fusion, we propose Balanced Class-Agnostic Sampling (B-CAS) strategy and Non-Linear Fusion (NLF) module from differenct perspectives. They are complementary to each other and depict the high-level feature relations more effectively. Extensive experiments on PASCAL VOC and MS COCO benchmarks show that our method sets a new state-of-the-art performance in most settings. Our code is available at https://github.com/wangchen1801/FPD.

Selective harvesting of Hotan roses requires distinguishing between buds and blooms for different industrial uses. However, balancing detection accuracy and computational efficiency for edge deployment remains a challenge. This study proposes an integrated framework combining a lightweight detection model, Rose_YOLO, with an adaptive path-planning algorithm, the ROSE algorithm, to address these issues. The Rose_YOLO model optimizes the YOLOv8n architecture by incorporating the C2f-Faster-CGLU module and a Rose_Head detection head to enhance feature extraction while reducing redundancy. The ROSE algorithm integrates an improved genetic algorithm (GA) with a reciprocating search mechanism to dynamically optimize picking sequences based on scene complexity. Experimental results demonstrate that Rose_YOLO achieves a precision of 90.4% and a mAP@0.5 of 96.6% for blooms and a precision of 88.4% with a mAP@0.5 of 91.7% for buds. Compared to the baseline YOLOv8n, the model reduces parameters by 47.46% to 1.579 million, compresses the size to 3.19 MB, and lowers computational complexity to 4.6 GFLOPs. For path planning, the ROSE algorithm generates optimal paths with an average length of 2796.94 pixels, which is 73.1% shorter than the reciprocating algorithm and 51.6% shorter than the standard GA. Furthermore, it achieves an average runtime of only 7.33 ms, significantly outperforming traditional methods with respect to computational speed. In conclusion, the proposed framework achieves a superior balance between lightweight design and detection performance. The successful deployment on edge devices validates its effectiveness in providing real-time visual guidance and efficient path planning, offering a robust technical solution for the automated selective harvesting of roses in complex field environments.

Accurate identification of picking points remains a critical challenge for automated marigold harvesting, primarily due to complex backgrounds and significant pose variations of the flowers. To overcome this challenge, this study proposes SCS-YOLO-Seg, a novel method based on a lightweight segmentation model. The approach enhances the baseline YOLOv8n-seg architecture by replacing its backbone with StarNet and introducing C2f-Star, a novel lightweight feature extraction module. These modifications achieve substantial model compression, significantly reducing the model size, parameter count, and computational complexity (GFLOPs). Segmentation efficiency is further optimized through a dual-path collaborative architecture (Seg-Marigold head). Following mask extraction, picking points are determined by intersecting the optimized elliptical mask fitting results with the stem skeleton. Experimental results demonstrate that SCS-YOLO-Seg effectively balances model compression with segmentation performance. Compared to YOLOv8n-seg, it maintains high accuracy while significantly reducing resource requirements, achieving a picking point identification accuracy of 93.36% with an average inference time of 28.66 ms per image. This work provides a robust and efficient solution for vision systems in automated marigold harvesting.

Ternary organic photovoltaics (OPVs) are fabricated with PBDB-T-2Cl:Y6 (1:1.2, wt/wt) as the host system and extra PC 71 BM as the third component. The PBDB-T-2Cl:Y6 based binary OPVs exhibit a power conversion efficiency (PCE) of 15.49% with a short circuit current ( J SC ) of 24.98 mA cm −2 , an open circuit voltage ( V OC ) of 0.868 V and a fill factor (FF) of 71.42%. A 16.71% PCE is obtained in the optimized ternary OPVs with PBDB-T-2Cl:Y6:PC 71 BM (1:1.2:0.2, wt/wt) active layer, resulting from the synchronously improved J SC of 25.44 mA cm −2 , FF of 75.66% and the constant V OC of 0.868 V. The incorporated PC 71 BM may prefer to mix with Y6 to finely adjust phase separation, domain size and molecular arrangement in ternary active layers, which can be confirmed from the characterization on morphology, 2D grazing incidence small and wide-angle X-ray scattering, as well as Raman mapping. In addition, PC 71 BM may prefer to mix with Y6 to form efficient electron transport channels, which should be conducive to charge transport and collection in the optimized ternary OPVs. This work provides more insight into the underlying reasons of the third component on performance improvement of ternary OPVs, indicating ternary strategy should be an efficient method to optimize active layers for synchronously improving photon harvesting, exciton dissociation and charge transport, while keeping the simple cell fabrication technology.

Human olfactory sensors have a large variety of receptor cells that generate signature responses to various gaseous molecules. Ideally, artificial olfactory sensors should have arrays of diverse sensors. However, it is challenging to monolithically integrate large-scale arrays of different high-performance gas sensors. Here we report biomimetic olfactory chips that integrate nanotube sensor arrays on nanoporous substrates with up to 10,000 individually addressable sensors per chip. The range of sensors is achieved using an engineered material composition gradient. Supported by artificial intelligence, the chips offer a high sensitivity to various gases with excellent distinguishability for mixed gases and 24 distinct odours. We also show that the olfactory chips can be combined with vision sensors on a robot dog to create a system that can identify an object in a blind box. A biomimetic olfactory system that integrates nanotube sensor arrays with up to 10,000 individually addressable sensors per chip can offer high sensitivity to various gases with excellent distinguishability for mixed gases and 24 distinct odours.