Dehydroandrographolide facilitates M2 macrophage polarization by downregulating DUSP3 to inhibit sepsis-associated acute kidney injury.

BACKGROUND: Sepsis is perceived as lethal tissue damage and significantly increases mortality in combination with acute kidney injury (AKI). M2 macrophages play important roles in the secretion of anti-inflammatory and tissue repair mediators. We aimed to study the role of Dehydroandrographolide (Deh) in sepsis-associated AKI in vitro and in vivo through lipopolysaccharide (LPS)-induced macrophages model and cecal ligation and puncture-induced AKI mice model, and to reveal the mechanism related to M2 macrophage polarization. METHODS: Enzyme-linked immunosorbent assay kits were used to assess the levels of inflammatory factors. Expression of markers related to M1 macrophages and M2 macrophages were analyzed. Additionally, dual specificity phosphatase 3 (DUSP3) expression was tested. Cell apoptosis was evaluated by flow cytometry analysis and terminal-deoxynucleotidyl transferase-mediated nick end labeling staining. Moreover, renal histological assessment was performed by using hematoxylin and eosin staining. RESULTS: Deh reduced inflammation of THP-1-derived macrophages exposed to LPS. Besides, Deh induced the polarization of M1 macrophages to M2 and downregulated DUSP3 expression in THP-1-derived macrophages under LPS conditions. Further, DUSP3 overexpression reversed the impacts of Deh on the inflammation and M2 macrophages polarization of THP-1-derived macrophages stimulated by LPS. Additionally, human proximal tubular epithelial cells (HK-2) in the condition medium from DUSP3-overexpressed THP-1-derived macrophages treated with LPS and Deh displayed decreased viability and increased apoptosis and inflammation. The in vivo results suggested that Deh improved the renal function, ameliorated pathological injury, induced the polarization of M1 macrophages to M2, suppressed inflammation and apoptosis, and downregulated DUSP3 expression in sepsis-induced mice. CONCLUSION: Deh facilitated M2 macrophage polarization by downregulating DUSP3 to inhibit septic AKI.

MetaFormer Baselines for Vision.

MetaFormer, the abstracted architecture of Transformer, has been found to play a significant role in achieving competitive performance. In this paper, we further explore the capacity of MetaFormer, again, by migrating our focus away from the token mixer design: we introduce several baseline models under MetaFormer using the most basic or common mixers, and demonstrate their gratifying performance. We summarize our observations as follows: (1) MetaFormer ensures solid lower bound of performance. By merely adopting identity mapping as the token mixer, the MetaFormer model, termed IdentityFormer, achieves [Formula: see text]80% accuracy on ImageNet-1 K. (2) MetaFormer works well with arbitrary token mixers. When specifying the token mixer as even a random matrix to mix tokens, the resulting model RandFormer yields an accuracy of [Formula: see text]81%, outperforming IdentityFormer. Rest assured of MetaFormer's results when new token mixers are adopted. (3) MetaFormer effortlessly offers state-of-the-art results. With just conventional token mixers dated back five years ago, the models instantiated from MetaFormer already beat state of the art. (a) ConvFormer outperforms ConvNeXt. Taking the common depthwise separable convolutions as the token mixer, the model termed ConvFormer, which can be regarded as pure CNNs, outperforms the strong CNN model ConvNeXt. (b) CAFormer sets new record on ImageNet-1 K. By simply applying depthwise separable convolutions as token mixer in the bottom stages and vanilla self-attention in the top stages, the resulting model CAFormer sets a new record on ImageNet-1 K: it achieves an accuracy of 85.5% at 224 ×224 resolution, under normal supervised training without external data or distillation. In our expedition to probe MetaFormer, we also find that a new activation, StarReLU, reduces 71% FLOPs of activation compared with commonly-used GELU yet achieves better performance. Specifically, StarReLU is a variant of Squared ReLU dedicated to alleviating distribution shift. We expect StarReLU to find great potential in MetaFormer- like models alongside other neural networks. Code and models are available at https://github.com/sail-sg/metaformer.

Prevalence and associated factors of acute gastroenteritis in children and adolescents aged from 6 to 17 years old: a cross-sectional study based on the National Health and Nutrition Examination Survey database 1999-2018.

OBJECTIVE: To explore the prevalence of acute gastroenteritis (AGE) and associated factors in children and adolescents in the USA from 1999 to 2018 using nationally representative data. DESIGN: A retrospective cross-sectional study. SETTING: The National Health and Nutrition Examination Survey (NHANES) database. PARTICIPANTS: 25 361 children and adolescents aged 6-17 years old. PRIMARY AND SECONDARY OUTCOME MEASURES: Whether the patient suffered from AGE. RESULTS: Totally 1882 suffered from AGE. The overall monthly prevalence of AGE in children and adolescents was 7.69%. From 1999 to 2018, the prevalence of AGE in the USA had been decreasing over time. The decreasing trend was observed in all subgroups, including age, gender, body mass index (BMI), education level, poverty index and eating food at the restaurant. There were two small upticks from 2003 to 2007 and 2013 to 2015. AGE was negatively associated with male compared with female (OR=0.86, 95% CI: 0.73 to 0.99, p=0.035), Mexican American (OR=0.82, 95% CI: 0.70 to 0.97, p=0.018) and non-Hispanic Black (OR=0.80, 95% CI: 0.69 to 0.93, p=0.003) compared with non-Hispanic White. AGE was positively associated with obesity compared with underweight and normal weight (OR=1.37, 95% CI: 1.15 to 1.62, p<0.001). CONCLUSION: The monthly prevalence of AGE was 7.69% and showed a downward trend from 1999 to 2018 in the USA.

TNN: Tree Neural Network for Airway Anatomical Labeling.

Detailed anatomical labeling of bronchial trees extracted from CT images can be used as fine-grained maps for intra-operative navigation. To cater to the sparse distribution of airway voxels and large class imbalance in 3D image space, a graph-neural-network-based method is proposed to map branches to nodes in a graph space and assign anatomical labels down to subsegmental level. To address the inherent problem of overlapping distribution of positional and morphological features, especially for subsegmental categories, the proposed method focuses on the relative position between sibling subsegments which is fixed in most cases. The hierarchical nomenclature is represented by multi-level labeling and each category is associated with one or two subtrees in the graph. Hyperedges are used to extract the representation of subtrees while a hypergraph neural network is developed to encode their intrinsic relationship through hyperedge interaction. A filter module is further designed to guide feature aggregation between nodes and hyperedges. With the proposed method, the final accuracies for segmental and subsegmental node classification can achieve 93.6% and 82.0% respectively. The corresponding code is publicly available at https://github.com/haozheng-sjtu/airway-labeling.

LTSP: long-term slice propagation for accurate airway segmentation.

PURPOSE: Bronchoscopic intervention is a widely used clinical technique for pulmonary diseases, which requires an accurate and topological complete airway map for its localization and guidance. The airway map could be extracted from chest computed tomography (CT) scans automatically by airway segmentation methods. Due to the complex tree-like structure of the airway, preserving its topology completeness while maintaining the segmentation accuracy is a challenging task. METHODS: In this paper, a long-term slice propagation (LTSP) method is proposed for accurate airway segmentation from pathological CT scans. We also design a two-stage end-to-end segmentation framework utilizing the LTSP method in the decoding process. Stage 1 is used to generate a coarse feature map by an encoder-decoder architecture. Stage 2 is to adopt the proposed LTSP method for exploiting the continuity information and enhancing the weak airway features in the coarse feature map. The final segmentation result is predicted from the refined feature map. RESULTS: Extensive experiments were conducted to evaluate the performance of the proposed method on 70 clinical CT scans. The results demonstrate the considerable improvements of the proposed method compared to some state-of-the-art methods as most breakages are eliminated and more tiny bronchi are detected. The ablation studies further confirm the effectiveness of the constituents of the proposed method and the efficacy of the framework design. CONCLUSION: Slice continuity information is beneficial to accurate airway segmentation. Furthermore, by propagating the long-term slice feature, the airway topology connectivity is preserved with overall segmentation accuracy maintained.

Propagation properties of Airy-Gaussian vortex beams through the gradient-index medium.

Propagation of Airy-Gaussian vortex (AiGV) beams through the gradient-index medium is investigated analytically and numerically with the transfer matrix method. Deriving the analytic expression of the AiGV beams based on the Huygens diffraction integral formula, we obtain the propagate path, intensity and phase distributions, and the Poynting vector of the first- and second-order AiGV beams, which propagate through the paraxial ABCD system. The ballistic trajectory is no longer conventional parabolic but trigonometric shapes in the gradient-index medium. Especially, the AiGV beams represent the singular behavior at the propagation path and the light intensity distribution. The phase distribution and the Poynting vector exhibit in reverse when the AiGV beams through the singularity. As the order increases, the main lobe of the AiGV beams is gradually overlapped by the vortex core. Further, the sidelobe weakens when the AiGV beams propagate nearly to the singularity. Additionally, the figure of the Poynting vector of the AiGV beams proves the direction of energy flow corresponding to the intensity distribution. The vortex of the second-order AiGV beams is larger, and the propagation velocity is faster than that of the first order.

Propagation properties of right-hand circularly polarized Airy-Gaussian beams through slabs of right-handed materials and left-handed materials.

The propagation of right-hand circularly polarized Airy-Gaussian beams (RHCPAiGBs) through slabs of right-handed materials (RHMs) and left-handed materials (LHMs) is investigated analytically and numerically with the transfer matrix method. An approximate analytical expression for the RHCPAiGBs passing through a paraxial ABCD optical system is derived on the basis of the Huygens diffraction integral formula. The intensity and the phase distributions of the RHCPAiGBs through RHMs and LHMs are demonstrated. The influence of the parameter χ0 on the propagation of RHCPAiGBs through RHM and LHM slabs is investigated. The RHCPAiGBs possess transverse-momentum currents, which shows that the physics underlying this intriguing accelerating effect is that of the combined contributions of the transverse spin and transverse orbital currents. Additionally, we go a step further to explore the radiation force including the gradient force and scattering force of the RHCPAiGBs.

Cryopreservation of stallion spermatozoa using different cryoprotectants and combinations of cryoprotectants.

The present study investigates the effects of five cryoprotectants (CPAs) and cryoprotectant combinations on the post-thaw total motility, progressive motility, viability, mitochondrial membrane potential and acrosome integrity in stallion spermatozoa. In Experiment 1, the objective was to compare the impact of different concentrations (2.5%, 3.5% and 5%) of a single CPA, including glycerol (Gly), ethylene glycol (EG), dimethyl sulphoxide (DMSO), methyl formamide (MF), and dimethylformamide (DMF) for stallion spermatozoa cryopreservation. In Experiment 2, two or more CPAs were used to assess whether this improved post-thaw spermatozoa quality. Gly, MF and DMF, were used to prepare seven combinations of freezing extender with different mixtures of cryoprotectant, and the 3.5% Gly, MF and DMF were used as a control group. The results show that post-thaw total motility, progressive motility, viability, and mitochondrial membrane potential for all concentrations of EG and DMSO were less than the 3.5% and 5% Gly and MF and 2.5% and 3.5% DMF (P<0.05). Use of the 3.5% concentration resulted in the greater post-thaw total motility and progressive motility than the 2.5% and 5% concentrations for all CPAs. The results for the use of different combinations of cryoprotectant indicate there are differences in progressive motility and viability. The viability with the use of Gly(2/3)+MF(1/3) was 44.65% and was greater than the Gly(1/3)+MF(1/3)+DMF(1/3) (30.96%), MF(2/3)+DMF(1/3) (35.05%), Gly (32.21%) and MF(33.76%) (P<0.05). The progressive motility with the use of the MF(2/3)+Gly(1/3) combination was 36.0% and was greater than in the DMF (25.0%) and MF(2/3)+DMF(1/3) (22.7%) (P<0.05). These results suggest that using the appropriate cryoprotectant combination instead of a single cryoprotectant can improve horse spermatozoa cryopreservation.