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IntroductionSemantic segmentation is effective in dealing with complex environments. However, the most popular semantic segmentation methods are usually based on a single structure, they are inefficient and inaccurate. In this work, we propose a mix structure network called MixSeg, which fully combines the advantages of convolutional neural network, Transformer, and multi-layer perception architectures.MethodsSpecifically, MixSeg is an end-to-end semantic segmentation network, consisting of an encoder and a decoder. In the encoder, the Mix Transformer is designed to model globally and inject local bias into the model with less computational cost. The position indexer is developed to dynamically index absolute position information on the feature map. The local optimization module is designed to optimize the segmentation effect of the model on local edges and details. In the decoder, shallow and deep features are fused to output accurate segmentation results.ResultsTaking the apple leaf disease segmentation task in the real scene as an example, the segmentation effect of the MixSeg is verified. The experimental results show that MixSeg has the best segmentation effect and the lowest parameters and floating point operations compared with the mainstream semantic segmentation methods on small datasets. On apple alternaria blotch and apple grey spot leaf image datasets, the most lightweight MixSeg-T achieves 98.22%, 98.09% intersection over union for leaf segmentation and 87.40%, 86.20% intersection over union for disease segmentation.DiscussionThus, the performance of MixSeg demonstrates that it can provide a more efficient and stable method for accurate segmentation of leaves and diseases in complex environments.

To comprehensively assess the global, regional and national burden of polycystic ovary syndrome (PCOS) in incidence, prevalence, and years lived with disability (DLYs) based on the Global Burden of Disease Study (GBD) 2019. This was a cross-sectional descriptive study. Data on PCOS incidence, prevalence, and DLYs from 1990 to 2019 were obtained from the GBD study 2019. According to the commonwealth income, WHO region, and the sociodemographic index, the estimates were demonstrated along with the estimated annual percentage change (EAPC). The EAPC data were analyzed by four levels of hierarchical clustering and displayed in the world map. The Autoregressive Integrated Moving Average (ARIMA) and Bayesian age-period-cohort (BAPC) model was used to predict the PCOS burden in the next 20 years. From 1990 to 2019, the number of PCOS incidence in one year increased from 1.4 million in 1990 to 2.1 million in 2019 (54.3%). Only the EAPC estimates of incidence in the Region of the Americas decreased, and their aged-standardized incidence rate (ASIR) values were the highest in 1990 and 2019. There was no significant correlation between human development index (HDI) and EAPC. However, when HDI < 0.7, EAPC of incidence and prevalence was positively correlated with HDI, and when HDI > 0.7, EAPC of incidence and prevalence was negatively correlated with HDI. Countries with the middle level HDI have the highest increasing trend of ASIR and age-standardized prevalence rate (ASPR). The 10 to 19 years old group had the highest incidence counts of PCOS globally. Besides, the ARIMA and BAPC model showed the consistent increasing trend of the burden of PCOS. In order to better promote the early diagnosis and treatment, expert consensus and diagnosis criteria should be formulated according to the characteristics of different ethnic groups or regions. It is necessary to emphasize the early screening and actively develop targeted drugs for PCOS.

Previous studies have shown that bufalin exerts antitumor effects through various mechanisms. This study aimed to determine the antineoplastic mechanism of bufalin, an extract of traditional Chinese medicine toad venom, in ovarian cancer. The 3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl tetrazolium bromide (MTT), 5-ethynyl-2'-deoxyuridine (EdU), and colony formation assays were used to investigate the antiproliferative effect of bufalin on the ovarian cancer cell line SK-OV-3. Molecular docking was used to investigate the combination of bufalin and epidermal growth factor receptor (EGFR) protein. Western blotting was performed to detect the expression of EGFR protein and its downstream targets. Bufalin inhibited the proliferation of SK-OV-3 cells in a dose- and time-dependent manner. Bufalin was confirmed to combine with EGFR protein using molecular docking and downregulate expression of EGFR. Bufalin inhibited phosphorylation of EGFR, protein kinase B (AKT), and extracellular signal-regulated kinase (ERK). Bufalin suppresses the proliferation of ovarian cancer cells through the EGFR/AKT/ERK signaling pathway.

Interleukin-11 (IL-11), a well-known anti-inflammatory factor, provides protection from intestinal epithelium damage caused by physical or chemical factors. However, little is known of the role of IL-11 during viral infections. In this study, IL-11 expression at mRNA and protein levels were found to be high in Vero cells and the jejunum of piglets during porcine epidemic diarrhea virus (PEDV) infection, while IL-11 expression was found to be positively correlated with the level of viral infection. Pretreatment with recombinant porcine IL-11 (pIL-11) was found to suppress PEDV replication in Vero E6 cells, while IL-11 knockdown promoted viral infection. Furthermore, pIL-11 was found to inhibit viral infection by preventing PEDV-mediated apoptosis of cells by activating the IL-11/STAT3 signaling pathway. Conversely, application of a STAT3 phosphorylation inhibitor significantly antagonized the anti-apoptosis function of pIL-11 and counteracted its inhibition of PEDV. Our data suggest that IL-11 is a newfound PEDV-inducible cytokine, and its production enhances the anti-apoptosis ability of epithelial cells against PEDV infection. The potential of IL-11 to be used as a novel therapeutic against devastating viral diarrhea in piglets deserves more attention and study.

Background Lumbar facet joint osteoarthritis (LFJ OA) is a common disease, and there is still a lack of effective disease-modifying therapies. Our aim was to determine the therapeutic effect of hypoxia-treated adipose mesenchymal stem cell (ADSC)-derived exosomes (Hypo-ADSC-Exos) on the protective effect against LFJ OA. Methods The protective effect of Hypo-ADSC-Exos against LFJ OA was examined in lumbar spinal instability (LSI)-induced LFJ OA models. Spinal pain behavioural assessments and CGRP (Calcitonin Gene-Related Peptide positive) immunofluorescence were evaluated. Cartilage degradation and subchondral bone remodelling were assessed by histological methods, immunohistochemistry, synchrotron radiation-Fourier transform infrared spectroscopy (SR-FTIR), and 3D X-ray microscope scanning. Results Hypoxia enhanced the protective effect of ADSC-Exos on LFJ OA. Specifically, tail vein injection of Hypo-ADSC-Exos protected articular cartilage from degradation, as demonstrated by lower FJ OA scores of articular cartilage and less proteoglycan loss in lumbar facet joint (LFJ) cartilage than in the ADSC-Exo group, and these parameters were significantly improved compared to those in the PBS group. In addition, the levels and distribution of collagen and proteoglycan in LFJ cartilage were increased in the Hypo-ADSC-Exo group compared to the ADSC-Exo or PBS group by SR-FTIR. Furthermore, Hypo-ADSC-Exos normalized uncoupled bone remodelling and aberrant H-type vessel formation in subchondral bone and effectively reduced symptomatic spinal pain caused by LFJ OA in mice compared with those in the ADSC-Exo or PBS group. Conclusions Our results show that hypoxia is an effective method to improve the therapeutic effect of ADSC-Exos on ameliorating spinal pain and LFJ OA progression.

Objective Lumbar facet joint (LFJ) degeneration is one of the main causes of low back pain (LBP). Mechanical stress leads to the exacerbation of LFJ degeneration, but the underlying mechanism remains unknown. This study was intended to investigate the mechanism of LFJ degeneration induced by mechanical stress. Methods Here, mice primary chondrocytes were used to screen for key microRNAs induced by mechanical overloading. SA-β-gal staining, qRT-PCR, western blot, and histochemical staining were applied to detect chondrocyte senescence in vitro and in vivo. We also used a dual-luciferase report assay to examine the targeting relationship of miRNA-325-3p (miR-325-3p) and Trp53. By using NSC-207895, a p53 activator, we investigated whether miR-325-3p down-regulated trp53 expression to reduce chondrocyte senescence. A mice bipedal standing model was performed to induce LFJ osteoarthritis. Adeno-associated virus (AAV) was intraarticularly injected to evaluate the effect of miR-325-3p on facet joint degeneration. Results We observed chondrocyte senescence both in human LFJ osteoarthritis tissues and mice LFJ after bipedally standing for 10 weeks. Mechanical overloading could promote chondrocyte senescence and senescence-associated secretory phenotype (SASP) expression. MicroRNA-array analysis identified that miR-325-3p was obviously decreased after mechanical overloading, which was further validated by fluorescence in situ hybridization (FISH) in vivo. Dual-luciferase report assay showed that miR-325-3p directly targeted Trp53 to down-regulated its expression. MiR-325-3p rescued chondrocyte senescence in vitro, however, NSC-207895 reduced this effect by activating the p53/p21 pathway. Intraarticular injection of AAV expressing miR-325-3p decreased chondrocyte senescence and alleviated LFJ degeneration in vivo. Conclusion Our findings suggested that mechanical overloading could reduce the expression of miR-325-3p, which in turn activated the p53/p21 pathway to promote chondrocyte senescence and deteriorated LFJ degeneration, which may provide a promising therapeutic strategy for LFJ degeneration.

Ulcerative colitis (UC) is effectively alleviated by Saccharomyces boulardii (S. boulardii), an important probiotic. Postbiotics, defined as beneficial non-viable microorganisms and/or their components, can potentially improve gut health. In this study, we utilized S. boulardii to prepare postbiotics via freeze-drying and spray-drying methods, characterized the resulting postbiotics, and investigated their efficacy and underlying mechanisms in preventing UC. In a mouse model of UC induced by dextran sulfate sodium (DSS), we found that prevention with two forms of S. boulardii postbiotics alleviated colitis symptoms triggered by DSS, mitigated colon tissue damage, maintained the distribution of intestinal occludin and ZO-1 proteins, and suppressed the secretion and expression of TNF-α, IL-1β, and IL-6 in serum and colon tissues. Additionally, S. boulardii postbiotics mitigated dysbiosis by modulating gut microbiota composition, including the balance between Bacteroidota and Firmicutes (F/B), as well as the levels of Akkermansia, Muribaculaceae, Dubosiella, and Turicibacter. In conclusion, as a novel biotherapeutic agent, S. boulardii postbiotics effectively prevent DSS-induced UC in mice. Compared to live S. boulardii, postbiotics may hold greater potential for UC prevention.

Time-series data are widely applied in real-world scenarios, but the non-stationary nature of their statistical properties and joint distributions over time poses challenges for existing forecasting models. To tackle this challenge, this paper introduces a forecasting model called DFCNformer (De-stationary Fourier and Coefficient Network Transformer), designed to mitigate accuracy degradation caused by non-stationarity in time-series data. The model initially employs a stabilization strategy to unify the statistical characteristics of the input time series, restoring their original features at the output to enhance predictability. Then, a time-series decomposition method splits the data into seasonal and trend components. For the seasonal component, a Transformer-based encoder–decoder architecture with De-stationary Fourier Attention (DSF Attention) captures temporal features, using differentiable attention weights to restore non-stationary information. For the trend component, a multilayer perceptron (MLP) is used for prediction, enhanced by a Dual Coefficient Network (Dual-CONET) that mitigates distributional shifts through learnable distribution coefficients. Ultimately, the forecasts of the seasonal and trend components are combined to generate the overall prediction. Experimental findings reveal that when the proposed model is tested on six public datasets, in comparison with five classic models it reduces the MSE by an average of 9.67%, with a maximum improvement of 40.23%.

Highly sensitive ultraviolet (UV) photodetectors are highly desired for industrial and scientific applications. However, the responsivity of silicon photodiodes in the UV wavelength band is relatively low due to high-density Si/SiO2 interface states. In this paper, a coplanar avalanche photodiode (APD) was developed with a virtual guard ring design. When working in Geiger mode, it exhibited a strong UV response. The responsivity of 4 × 103 A/W (corresponding to a gain of 8 × 106) at 261 nm is measured under the incident power of 0.6 μW with an excess bias of 1.5 V. To the best of our knowledge, the maximum 3-dB bandwidth of 1.4 GHz is the first report ever for a Si APD when working in the Geiger mode in spite of the absence of an integrated CMOS read-out circuit.

Nonconventional luminescent materials (NLMs) which do not contain traditional aromatic chromophores are of great interest due to their unique chemical structures, optical properties, and their potential applications in various areas, such as cellular imaging and chemical sensing. However, most reported NLMs show weak or no emission in dilute solutions, which severely limits their applications. In this work, dynamic hydrogen bonds were utilized to design NLMs with efficient emission in dilute solutions. To further validate the results, polymers P1 and P2 were successfully prepared and investigated. It was found that the luminescence quantum efficiency of P1 and P2 at a concentration of 0.1 mg/mL in water solution was 8.9 and 0.6%, respectively. The high efficiency can be attributed to the fact that polymer P1 has more intra- or intermolecular dynamic hydrogen bonds and other short interactions than P2 in dilute solutions, allowing P1 to achieve the through-space conjugation effect to increase the degree of system conjugation, restrict molecular motion, and decrease nonradiative transitions, which can effectively improve luminescence. In addition, polymer P2 exhibits the characteristics of clustering-triggered emission, excitation wavelength-dependent and concentration-dependent fluorescence properties, excellent photobleaching resistance, low cytotoxicity, and selective recognition of Fe3+. The present study investigates the manipulation of luminescence properties of NLMs in dilute solutions through the modulation of dynamic hydrogen bonds. This approach can serve as a semi-empirical technique for designing and building innovative NLMs in the times ahead.