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Abstract Domesticated herbivores are an important agricultural resource that play a critical role in global food security, particularly as they can adapt to varied environments, including marginal lands. An understanding of the molecular basis of their biology would contribute to better management and sustainable production. Thus, we conducted transcriptome sequencing of 100 to 105 tissues from two females of each of seven species of herbivore (cattle, sheep, goats, sika deer, horses, donkeys, and rabbits) including two breeds of sheep. The quality of raw and trimmed reads was assessed in terms of base quality, GC content, duplication sequence rate, overrepresented k-mers, and quality score distribution with FastQC. The high-quality filtered RNA-seq raw reads were deposited in a public database which provides approximately 54 billion high-quality paired-end sequencing reads in total, with an average mapping rate of ~93.92%. Transcriptome databases represent valuable resources that can be used to study patterns of gene expression, and pathways that are related to key biological processes, including important economic traits in herbivores.

Head and neck malignancies are a significant global health concern, with head and neck squamous cell carcinoma (HNSCC) being the sixth most common cancer worldwide accounting for > 90% of cases. In recent years, there has been growing recognition of the potential role of alternative splicing (AS) in the etiology of cancer. Increasing evidence suggests that AS is associated with various aspects of cancer progression, including tumor occurrence, invasion, metastasis, and drug resistance. Additionally, AS is involved in shaping the tumor microenvironment, which plays a crucial role in tumor development and response to therapy. AS can influence the expression of factors involved in angiogenesis, immune response, and extracellular matrix remodeling, all of which contribute to the formation of a supportive microenvironment for tumor growth. Exploring the mechanism of AS events in HNSCC could provide insights into the development and progression of this cancer, as well as its interaction with the tumor microenvironment. Understanding how AS contributes to the molecular changes in HNSCC cells and influences the tumor microenvironment could lead to the identification of new therapeutic targets. Targeted chemotherapy and immunotherapy strategies tailored to the specific AS patterns in HNSCC could potentially improve treatment outcomes and reduce side effects. This review explores the concept, types, processes, and technological advancements of AS, focusing on its role in the initiation, progression, treatment, and prognosis of HNSCC.

To investigate the coupled damage mechanism of blunt impact and bullets penetration after penetrating ballistic plates against human body targets, experiments were conducted using 6.8 mm caliber armor-piercing bullets against gelatin targets with protective coatings. A numerical analysis model was developed to simulate bullet penetration into gelatin with protective coatings, obtaining endpoint characteristic quantities such as bullet velocity changes, changes in energy distribution, pressure, stress, and stress wave variations within the gelatin target after protection. The results indicate that at a velocity of 640 m·s-1, the 6.8 mm caliber armor-piercing round failed to penetrate the ballistic plate yet still caused a blunt impact depression of 37 mm in depth. Under conditions where the bullet did not penetrate the ballistic plate, approximately 80% of the bullet's kinetic energy was absorbed by the ballistic plate. At a velocity of 740 m·s-1, the bullet penetrated the ballistic plate, resulting in a blunt impact depression depth of 56 mm and an instantaneous cavity with a maximum diameter of 60 mm. During the process of penetrating the ballistic plate, approximately 50% of the bullet's kinetic energy was absorbed by the ballistic plate, and about 40% of the remaining kinetic energy transferred into the gelatin during the penetration of the target.

Combination therapy has become the most important treatment for advanced non-small cell lung cancer (NSCLC), which can significantly improve the prognosis of patients. However, poor targeting and adverse reactions limited its clinical application. Here, we constructed an AS1411 aptamer-programmed cell death ligand-1 (PD-L1) siRNA chimera/polyethylenimine/glutamine/β-cyclodextrin/doxorubicin (Chimera/ PEI/Gln/β-CD/DOX) nanoparticle for the combination therapy (chemotherapy combined with immunotherapy). Scanning electron microscopy showed that PEI/Gln/β-CD/DOX nanoparticle was conical, with a diameter of about 250–500 nm. AS1411 aptamer-PD-L1 siRNA chimera can effectively bind NSCLC cells and inhibit PD-L1 expression, further activating T cells and CD8+T cells. Glutamine modification effectively promoted the doxorubicin uptake by cancer cells and induced their apoptosis. Animal experiments showed that our nanoparticles effectively treated the transplanted tumor, and the adverse reactions were reduced. Compared with the Aptamer/β-CD/DOX group, the volume and ki-67 index of transplanted tumors in the Chimera/β-CD/DOX group were significantly decreased, while the apoptosis ratio was increased. Immunohistochemical results showed that Compared with the Aptamer/β-CD/DOX group, the number of T cells and CD8+T cells in the Chimera/β-CD/DOX group was increased by 1.34 and 1.41 times. Glutamine modification enhanced the chemotherapeutic efficacy and anti-tumor immune response in vivo. Our study provided a new method for the combination therapy of lung squamous cell carcinoma.

Visible and infrared image fusion is an important image enhancement technique that aims to generate high-quality fused images with prominent targets and rich textures in extreme environments. However, most of the current image fusion methods have poor visual perception of the generated fused images due to severe degradation of texture details of the visible light images in scenes with extreme lighting, which seriously affects the application of subsequent advanced vision tasks such as target detection and tracking. To address these challenges, this paper bridges the gap between image fusion and advanced vision tasks by proposing an efficient fusion method for mutual enhancement of spatial and radiometric information. First, we design the gradient residual dense block (LGCnet) to improve the description of fine spatial details in the fusion network. Then, we developed a cross-modal perceptual fusion (CMPF) module to facilitate modal interactions in the network, which effectively enhances the fusion of complementary information between different modalities and reduces redundant learning. Finally, we designed an adaptive light-aware network (ALPnet) to guide the training of the fusion network to facilitate the fusion network to adaptively select more effective information for fusion under different lighting conditions. Extensive experiments show that the proposed fusion approach has competitive advantages over six current state-of-the-art deep-learning methods in highlighting target features and describing the global scene.

The Unmanned Aerial Vehicle (UAV) tracking tasks find extensive utility across various applications. However, current Transformer-based trackers are generally tailored for diverse scenarios and lack specific designs for UAV applications. Moreover, due to the complexity of training in tracking tasks, existing models strive to improve tracking performance within limited scales, making it challenging to directly apply lightweight designs. To address these challenges, we introduce an efficient attention mechanism known as Macaron Attention, which we integrate into the existing UAV tracking framework to enhance the model’s discriminative ability within these constraints. Specifically, our attention mechanism comprises three components, fixed window attention (FWA), local squeezing global attention (LSGA), and conventional global attention (CGA), collectively forming a Macaron-style attention implementation. Firstly, the FWA module addresses the multi-scale issue in UAVs by cropping tokens within a fixed window scale in the spatial domain. Secondly, in LSGA, to adapt to the scale variation, we employ an adaptive clustering-based token aggregation strategy and design a “window-to-window” fusion attention model to integrate global attention with local attention. Finally, the CGA module is applied to prevent matrix rank collapse and improve tracking performance. By using the FWA, LSGA, and CGA modules, we propose a brand-new tracking model named MATrack. The UAV123 benchmark is the major evaluation dataset of MATrack with 0.710 and 0.911 on success and precision, individually.

Spinal tuberculosis is a common extrapulmonary type that is often secondary to pulmonary or systemic infections. Mycobacterium tuberculosis infection often leads to the balance of immune control and bacterial persistence. In this study, 64 patients were enrolled and the clinicopathological and immunological characteristics of different age groups were analyzed. Anatomically, spinal tuberculosis in each group mostly occurred in the thoracic and lumbar vertebrae. Imaging before preoperative anti-tuberculosis therapy showed that the proportion of abscesses in the older group was significantly lower than that in the younger and middle-aged groups. However, pathological examination of surgical specimens showed that the proportion of abscesses in the older group was significantly higher than that in the other groups, and there was no difference in the granulomatous inflammation, caseous necrosis, inflammatory necrosis, acute inflammation, exudation, granulation tissue formation, and fibrous tissue hyperplasia. B cell number was significantly lower in the middle-aged and older groups compared to the younger group, while the number of T cells, CD4+ T cells, CD8+ T cells, macrophages, lymphocytes, plasma cells, and NK cells did not differ. Meaningfully, we found that the proportion of IL-10 high expression and TGF-β1 positive in the older group was significantly higher than that in the younger group. TNF-α, CD66b, IFN-γ, and IL-6 expressions were not different among the three groups. In conclusion, there are some differences in imaging, pathological, and immune features of spinal tuberculosis in different age groups. The high expression of IL-10 and TGF-β1 in older patients may weaken their anti-tuberculosis immunity and treatment effectiveness.

Background: Epidemiological research has established associations between various inflammatory cytokines and the occurrence of oral cancer and oropharyngeal cancer (OCPC). We performed a Mendelian randomization (MR) analysis to systematically investigate the causal relationship between inflammatory cytokines and OCPC.Methods: We performed a bidirectional two-sample MR analysis using OCPC from 12 studies (6,034 cases and 6,585 controls) and genome-wide association study (GWAS) results for 41 serum cytokines from 8,293 Finns, respectively. Inverse variance weighting was used as the primary MR method and four additional MR methods (MR Egger, Weighted median, Simple mode, Weighted mode) were used to examine genetic associations between inflammatory traits and OCPC, and Cochran’s Q test, MR-Egger intercept, leave-one-out analysis, funnel plot, and multivariate MR (MVMR) analysis were used to assess the MR results.Results: The results suggested a potential association between high gene expression of Macrophage inflammatory protein-1α (MIP1α/CCL3) and an increased risk of OCPC (Odds Ratio (OR): 1.71, 95% Confidence Interval (CI): 1.09–2.68, p = 0.019). Increasing the expression levels of the interleukin-7 (IL-7) gene by 1 standard deviation reduced the risk of OCPC (OR: 0.64, 95%CI: 0.48–0.86, p = 0.003). In addition, multivariate Mendelian randomization analysis also showed the same results (MIP1α/CCL3, OR: 1.002, 95% CI: 0.919–1.092, p = 0.044; IL-7, OR: 0.997, 95% CI: 0.994–0.999, p = 0.011). Conversely, there was a positive correlation between genetic susceptibility to OCPC and an increase in Interleukin-4 (IL-4) (OR: 1.04, 95%CI: 1.00–1.08, p = 0.027).Conclusion: Our study systematically assessed the association between inflammatory cytokines and the risk of OCPC. We identified two upstream regulatory factors (IL-7 and CCL3) and one downstream effector factor (IL-4) that were associated with OCPC, offering potential avenues for the development of novel treatments.

Double-decker filaments and their eruptions have been widely observed in recent years, but their physical formation mechanism is still unclear. Using high spatiotemporal resolution, multi-wavelength observations taken by the New Vacuum Solar Telescope and the Solar Dynamics Observatory, we show the formation of a double-decker pair of flux rope system by two successive tether-cutting eruptions in a bipolar active region. Due to the combined effect of photospheric shearing and convergence motions around the active region’s polarity inversion line (PIL), the arms of two overlapping inverse-S-shaped short filaments reconnected at their intersection, which created a simultaneous upward-moving magnetic flux rope (MFR) and a downward-moving post-flare-loop (PFL) system striding the PIL. Meanwhile, four bright flare ribbons appeared at the footpoints of the newly formed MFR and the PFL. As the MFR rose, two elongated flare ribbons connected by a relatively larger PFL appeared on either side of the PIL. After a few minutes, another MFR formed in the same way at the same location and then erupted in the same direction as the first one. Detailed observational results suggest that the eruption of the first MFR might experienced a short pause before its successful eruption, while the second MFR was a failed eruption. This implies that the two newly formed MFRs might reach a new equilibrium at relatively higher heights for a while, which can be regarded as a transient double-decker flux rope system. The observations can well be explained by the tether-cutting model, and we propose that two successive confined tether-cutting eruptions can naturally produce a double-decker flux rope system, especially when the background coronal magnetic field has a saddle-like distribution of magnetic decay index profile in height.

Accurately controlling oxygen supply in argon oxygen decarburization (AOD) process is invariably desired for efficient decarburization and reducing alloying elements consumption. Herein, a data‐driven approach using a hybrid model integrating oxygen balance mechanism model and a two‐layer Stacking ensemble learning model is successfully established for predicting oxygen consumption in AOD converter. In this hybrid model, the oxygen balance mechanism model is used to calculate the oxygen consumption based on industrial data. Then the model calculation error is compensated using an optimized two‐layer Stacking model that is identified as (random forest (RF) + XGBoost + ridge regression)‐RF model by evaluating different hybrid model frameworks and Bayesian optimization. The results show that, in comparison to conventional prediction model based on oxygen balance mechanism, the present hybrid model greatly improves the control accuracy of oxygen consumption in AOD industrial production. The hit rate and mean absolute error of the present hybrid model for predicting oxygen consumption are 84.8% and 330 Nm3, respectively, within absolute oxygen consumption prediction error ±600 Nm3 (relative error of 3.8%). This data‐driven approach using the present hybrid model provides one pathway to efficient oxygen consumption control in AOD process. [ABSTRACT FROM AUTHOR]