TBE-Net: A Deep Network Based on Tree-like Branch Encoder for Medical Image Segmentation.

In recent years, encoder-decoder-based network structures have been widely used in designing medical image segmentation models. However, these methods still face some limitations: 1) The network's feature extraction capability is limited, primarily due to insufficient attention to the encoder, resulting in a failure to extract rich and effective features. 2) Unidirectional stepwise decoding of smaller-sized feature maps restricts segmentation performance. To address the above limitations, we propose an innovative Tree-like Branch Encoder Network (TBE-Net), which adopts a tree-like branch encoder to better perform feature extraction and preserve feature information. Additionally, we introduce the Depth and Width Expansion (D-WE) module to expand the network depth and width at low parameter cost, thereby enhancing network performance. Furthermore, we design a Deep Aggregation Module (DAM) to better aggregate and process encoder features. Subsequently, we directly decode the aggregated features to generate the segmentation map. The experimental results show that, compared to other advanced algorithms, our method, with the lowest parameter cost, achieved improvements in the IoU metric on the TNBC, PH2, CHASE-DB1, STARE, and COVID-19-CT-Seg datasets by 1.6%, 0.46%, 0.81%, 1.96%, and 0.86%, respectively.

Metformin acts on miR-181a-5p/PAI-1 axis in stem cells providing new strategies for improving age-related osteogenic differentiation decline.

A general decline in the osteogenic differentiation capacity of human bone marrow mesenchymal stem cells (hBMSCs) in the elderly is a clinical consensus, with diverse opinions on the mechanisms. Many studies have demonstrated that metformin (MF) significantly protects against osteoporosis and reduces fracture risk. However, the exact mechanism of this effect remains unclear. In this study, we found that the decreased miR-181a-5p expression triggered by MF treatment plays a critical role in recovering the osteogenic ability of aging hBMSCs (derived from elderly individuals). Notably, the miR-181a-5p expression in hBMSCs was significantly decreased with prolonged MF (1000 µM) treatment. Further investigation revealed that miR-181a-5p overexpression markedly impairs the osteogenic ability of hBMSCs, while miR-181a-5p inhibition reveals the opposite result. We also found that miR-181a-5p could suppress the protein translation process of plasminogen activator inhibitor-1 (PAI-1), as evidenced by luciferase assays and western blots. Additionally, low PAI-1 levels were associated with diminished osteogenic ability, whereas high levels promoted it. These findings were further validated in human umbilical cord mesenchymal stem cells (hUCMSCs). Finally, our in vivo experiment with a bone defects rat model confirmed that the agomiR-181a-5p (long-lasting miR-181a-5p mimic) undermined bone defects recovery, while the antagomiR-181a-5p (long-lasting miR-181a-5p inhibitor) significantly promoted the bone defects recovery. In conclusion, we found that MF promotes bone tissue regeneration through the miR-181a-5p/PAI-1 axis by affecting MSC osteogenic ability, providing new strategies for the treatment of age-related bone regeneration disorders.

FCSU-Net: A novel full-scale Cross-dimension Self-attention U-Net with collaborative fusion of multi-scale feature for medical image segmentation.

Recently, ViT and CNNs based on encoder-decoder architecture have become the dominant model in the field of medical image segmentation. However, there are some deficiencies for each of them: (1) It is difficult for CNNs to capture the interaction between two locations with consideration of the longer distance. (2) ViT cannot acquire the interaction of local context information and carries high computational complexity. To optimize the above deficiencies, we propose a new network for medical image segmentation, which is called FCSU-Net. FCSU-Net uses the proposed collaborative fusion of multi-scale feature block that enables the network to obtain more abundant and more accurate features. In addition, FCSU-Net fuses full-scale feature information through the FFF (Full-scale Feature Fusion) structure instead of simple skip connections, and establishes long-range dependencies on multiple dimensions through the CS (Cross-dimension Self-attention) mechanism. Meantime, every dimension is complementary to each other. Also, CS mechanism has the advantage of convolutions capturing local contextual weights. Finally, FCSU-Net is validated on several datasets, and the results show that FCSU-Net not only has a relatively small number of parameters, but also has a leading segmentation performance.

FAFS-UNet: Redesigning skip connections in UNet with feature aggregation and feature selection.

In recent years, the encoder-decoder U-shaped network architecture has become a mainstream structure for medical image segmentation. Its biggest advantage lies in the incorporation of shallow features into deeper layers of the network through skip connections. However, according to our research, there are still some limitations in the skip connection part of the network: (1) The information from the encoder stage is not completely and effectively supplemented to the decoder stage; (2) The decoder receives the supplemented feature information from the encoder indiscriminately, which sometimes leads to the poor performance of the model. Therefore, to effectively address these limitations, we have redesigned the skip connections in UNet using a feature aggregation and feature selection approach. We firstly design the FA module to aggregate all encoder features and perform local multi-scale information extraction to obtain the complete multi-scale aggregated features. Further, we design the FS module to actively perform specific selection of these aggregated features through the decoder, thus effectively guiding the semantic recovery of the decoder. Finally, we conduct experiments on several medical image datasets, and the results show that our method has higher segmentation accuracy compared with other methods.

Clindamycin Administration Increases the Incidence of Collagen-Induced Arthritis in Mice Through the Prolonged Impact of Gut Immunity.

The profound influence of gut flora on host immune system and its link with autoimmune disorders have been established. However, the role of certain antibiotic in progression of autoimmune disorder is still confusing. Here, we employed a collagen-induced arthritis (CIA) model to explore the role of clindamycin administration in different scenarios. In the first scenario, mice treated with antibiotics for 4 weeks were performed with the induction of CIA immediately. The results showed that clindamycin administration promoted the incidence and severity of CIA, while the recipients of vancomycin showed completed tolerance. We also found that increased gut-associated Th1 and Th17 cells might be related to the subsequent expansion of collagen-specific immune response. In the second scenario, mice treated with antibiotics for 4 weeks were performed with CIA induction 4 weeks later. Notably, clindamycin administration showed a prolonged impact on the incidence and severity of CIA, as well as the gut immunity as compared to vancomycin administration. In addition, antibody depletion of integrin α4ß7 systemically resulted in an impaired CIA response, underlining the influence of gut immunity. In the mice that received clindamycin, the abundance of anaerobic bacteria was significantly decreased and showed little recovery at 4 weeks later. Our observations highlighted the different characteristics of antibiotic administration on the development of autoimmune disorders and indicated its link with gut immunity.

Leukotriene D4 induces cellular senescence in osteoblasts.

Aging is associated with the development of osteoporosis, in which cellular senescence in osteoblasts plays a key role. Leukotriene D4 (LTD4), an important cysteinyl leukotriene (cysLT), is a powerful pro-inflammatory mediator formed from arachidonic acid. However, little information regarding the effects of LTD4 on the pathogenesis of osteoporosis has been reported before. In the present study, we defined the physiological roles of LTD4 in cellular senescence in osteoblasts. Our results indicate that LTD4 treatment decreased the expression of SIRT1 in a dose-dependent manner in MC3T3-E1 osteoblastic cells. Additionally, LTD4 significantly increased the expression of p53, p21 and plasminogen activator inhibitor-1 (PAI-1). LTD4 was also found to elevate the activity of ß-galactosidase (SA-ß-Gal) but to prevent BrdU incorporation. Our results indicate that cysteinyl leukotriene receptor 1 (cysLT1R) could be detected in MC3T3-E1 osteoblastic cells at both the mRNA and protein levels. However, cysLT2R was not expressed in these cells. Interestingly, we found that knockdown of cysLT1R or use of the selective cysLT1R antagonist montelukast abolished the LTD4-induced reduction in SIRT1 and increase in p53, p21, and PAI-1. Notably, knockdown of cysLT1R by transfection with cysLT1R siRNA or treatment with montelukast attenuated the LTD4-induced increase in SA-ß-Gal activity. Our study shows for the first time that LTD4 has a significant impact on cellular senescence in osteoblasts.

The cysteinyl leukotriene receptor 1 (CysLT1R) antagonist montelukast suppresses matrix metalloproteinase-13 expression induced by lipopolysaccharide.

Bacterial products such as LPS are critical factors responsible for bone destruction. MMP-13, a member of the matrix metalloproteinase family, plays a critical role in the proteolytic degradation of extracellular matrix components, which includes collagen fibrils in the bone matrix. Montelukast is a selective cysteinyl leukotrienes receptor 1 (cysLT1R) antagonist used clinically for the treatment of asthma, as it reduces eosinophilic inflammation in airways. This study aims to explore the role of montelukast in regulating MMP-13 expression induced by LPS in osteoblasts. Our results indicate that LPS stimulated cysLT1R expression in mouse MC3T3-E1 osteoblasts in a dose- and time-dependent manner. Notably, LPS-induced up-regulation of MMP-13 was ameliorated by treatment with montelukast in a dose-dependent manner. Furthermore, treatment with montelukast stimulated the expression of SOCS3, an inhibitor of MMP-13. Silencing of SOCS3 abolished the inhibitory effects of montelukast on MMP-13 expression. Mechanistically, we found that montelukast suppressed LPS-induced nuclear translocation of NF-κB p65 as well as NF-κB transcriptional activity by inhibiting the phosphorylation and degradation of IκBα. These data suggest that montelukast can modulate inflammatory events in bone diseases.

Antagonism of cysteinyl leukot-riene receptor 1 (cysLT1R) by montelukast regulates differentiation of MC3T3-E1 cells under overloaded mechanical environment.

Long-term exposure to overloaded mechanical environment induces bone fatigue damage symptoms and osteoblast damages. Montelukast is a selective cysteinyl leukot-riene receptor 1 (cysLT1R) antagonist, which has been used for the treatment of bronchial asthma in clinics. In the current study, we have identified a novel pharmacological role of montelukast by finding that it has protective properties against overload damage in osteoblastic MC3T3-E1 cells. Firstly, our results show that CysLT1R is expressed in MC3T3-E1 cells. Mechanical tensile strain of 5000-7000 µÎµ resulted in a significant upregulation of CysLT1R in osteoblastic MC3T3-E1 cells in an intensity dependent manner. Secondly, MTT assay indicates that loading with 5000 µÎµ mechanical strain inhibited cell proliferation, which was suppressed by montelukast treatment. Furthermore, montelukast promotes cell differentiation by increasing the expression of ALP and RUNX2. Alizarin Red S staining assay showed that montelukast abolished the inhibitory effects of overload mechanics on osteoblast mineralization. Mechanistically, the effect of montelukast on osteoblastic differentiation acted by activating the extracellular regulated protein kinases (ERK) pathway. The obtained results suggested that montelukast promotes proliferation and differentiation in osteoblasts exposed to overload mechanics.