Osteoporosis is a prevalent skeletal condition characterized by reduced bone mass and strength, leading to increased fragility. Buqi-Tongluo (BQTL) decoction, a traditional Chinese medicine (TCM) prescription, has yet to be fully evaluated for its potential in treating bone diseases such as osteoporosis. To investigate the mechanism by which BQTL decoction inhibits osteoclast differentiation in vitro and validate these findings through in vivo experiments. We employed MTS assays to assess the potential proliferative or toxic effects of BQTL on bone marrow macrophages (BMMs) at various concentrations. TRAcP experiments were conducted to examine BQTL's impact on osteoclast differentiation. RT-PCR and Western blot analyses were utilized to evaluate the relative expression levels of osteoclast-specific genes and proteins under BQTL stimulation. Finally, in vivo experiments were performed using an osteoporosis model to further validate the in vitro findings. This study revealed that BQTL suppressed receptor activator of NF-κB ligand (RANKL)-induced osteoclastogenesis and osteoclast resorption activity in vitro in a dose-dependent manner without observable cytotoxicity. The inhibitory effects of BQTL on osteoclast formation and function were attributed to the downregulation of NFATc1 and c-fos activity, primarily through attenuation of the MAPK, NF-κB, and Calcineurin signaling pathways. BQTL's inhibitory capacity was further examined in vivo using an ovariectomized (OVX) rat model, demonstrating a strong protective effect against bone loss. BQTL may serve as an effective therapeutic TCM for the treatment of postmenopausal osteoporosis and the alleviation of bone loss induced by estrogen deficiency and related conditions.
Animals ; NFATC Transcription Factors/genetics* ; Drugs, Chinese Herbal/pharmacology* ; Ovariectomy ; Osteoclasts/metabolism* ; Female ; Osteogenesis/drug effects* ; Rats, Sprague-Dawley ; Rats ; NF-kappa B/genetics* ; Osteoporosis/genetics* ; Signal Transduction/drug effects* ; Bone Resorption/genetics* ; Cell Differentiation/drug effects* ; Humans ; RANK Ligand/metabolism* ; Mitogen-Activated Protein Kinases/genetics* ; Transcription Factors

OBJECTIVES: To analyze the clinical characteristics of diffuse panbronchiolitis (DPB) in children and to enhance the clinical diagnosis and treatment of this disease. METHODS: A retrospective analysis was conducted on the clinical data of 6 children diagnosed with DPB who were hospitalized at The First Affiliated Hospital of Guangzhou Medical University from January 2011 to December 2019. RESULTS: Among the 6 patients, there were 2 males and 4 females; the age at diagnosis ranged from 7 to 12 years. All patients presented with cough, sputum production, and exertional dyspnea, and all had a history of sinusitis. Two cases showed positive serum cold agglutinin tests, and 5 cases exhibited pathological changes consistent with chronic bronchiolitis. High-resolution chest CT in all patients revealed centrilobular nodules diffusely distributed throughout both lungs with a tree-in-bud appearance. Five patients received low-dose azithromycin maintenance therapy, but 3 showed inadequate treatment response. After empirical anti-tuberculosis treatment, non-tuberculous Mycobacteria were found in the bronchoalveolar lavage fluid. Follow-up over 2 years showed 1 case cured, 3 cases significantly improved, and 2 cases partially improved. CONCLUSIONS The clinical presentation of DPB is non-specific and can easily lead to misdiagnosis. In cases where DPB is clinically diagnosed but does not show improvement with low-dose azithromycin treatment, special infections should be considered.
Humans ; Male ; Female ; Bronchiolitis/drug therapy* ; Retrospective Studies ; Child ; Haemophilus Infections/diagnosis*

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

Aim To explore the mechanisms of PM2.5 exposure exacerbating bleomycin(BLM)-induced idio-pathic pulmonary fibrosis(IFP)by regulating ferropto-sis via nuclear factor 2 related factor 2(Nrf2)/solute carrier family 7 member 11(SLC7A11)/glutathione peroxidase(GPX)4 axis.Methods Forty C57BL/6J mice were randomized into the control,BLM,PM2.5,BLM+PM2.5 and sulforaphane(SFN,Nrf2 agonist)groups,with eight mice in each group.PM2.5 expo-sures were conducted to the BLM-induced IPF mice for two weeks.The lung function was measured,and the content of hydroxyproline(HYP)in lung tissue and the pathomorphology of lungs were observed.Reactive oxygen species(ROS),malondialdehyde(MDA),ferrous ion(Fe2+)and glutathione(GSH)of the lung tissue were measured by ELISA.The mRNA and pro-teins levels of Nrf2,SLC7A11,GPX4,collagen typeⅠ(COL-1),α-smooth muscle actin(α-SMA)were measured by quantitative polymerase chain reaction(qPCR)and Western blot.Results Compared with the control group,the lung function of mice was signif-icantly reduced(P＜0.01)in the BLM and PM2.5 groups,while lung tissue showed the characteristic pathological changes of pulmonary fibrosis such as a large number of inflammatory cell infiltration,alveolar wall fracture,thickening,collagen deposition,and sig-nificantly increased HYP,Fe2+,ROS,MDA(P＜0.05,P＜0.01),genes and proteins of COL-1,α-SMA(P＜0.01);and decreased GSH,Nrf2,SLC7A11,GPX4 genes and proteins(P＜0.05,P＜0.01).The above-mentioned lesions were markedly aggravated in the BLM+PM2.5 group compared with the BLM(P＜0.05)and PM2.5 groups(P＜0.01),and were also improved in the SFN group(P＜0.05,P＜0.01).Conclusions PM2.5 exposures can exac-erbate IPF-induced IPF in mice,and the regulating of Nrf2/SLC7 A1 1/GPX4 axis and ferroptosis might be in-volved in the related mechanisms.

To address the challenge of joint grading caused by the diverse lesion morphologies associated with different stages of diabetic retinopathy,such as hemorrhages,microaneurysms,and neovascularization,which often obscure the lesions of diabetic macular edema,an improved ResNeSt50-based joint grading network is proposed.The modified ResNeSt50 with a novel convolutional operation(partial convolution)replacing the standard 3×3 convolution in the residual blocks is used to extract image features for exploring the specificities of diabetic retinopathy and macular edema.Subsequently,a disease-related attention module is introduced to capture the intrinsic correlation between diabetic retinopathy and macular edema.Experiments conducted on the Messidor and IDRID datasets show that the proposed approach achieves joint accuracies of 83.7%and 64.1%,respectively.The results demonstrate that the proposed algorithm can significantly improve the performance of joint grading for diabetic retinopathy and diabetic macular edema.

To address the challenge of joint grading caused by the diverse lesion morphologies associated with different stages of diabetic retinopathy,such as hemorrhages,microaneurysms,and neovascularization,which often obscure the lesions of diabetic macular edema,an improved ResNeSt50-based joint grading network is proposed.The modified ResNeSt50 with a novel convolutional operation(partial convolution)replacing the standard 3×3 convolution in the residual blocks is used to extract image features for exploring the specificities of diabetic retinopathy and macular edema.Subsequently,a disease-related attention module is introduced to capture the intrinsic correlation between diabetic retinopathy and macular edema.Experiments conducted on the Messidor and IDRID datasets show that the proposed approach achieves joint accuracies of 83.7%and 64.1%,respectively.The results demonstrate that the proposed algorithm can significantly improve the performance of joint grading for diabetic retinopathy and diabetic macular edema.

Aim To explore the mechanisms of PM2.5 exposure exacerbating bleomycin(BLM)-induced idio-pathic pulmonary fibrosis(IFP)by regulating ferropto-sis via nuclear factor 2 related factor 2(Nrf2)/solute carrier family 7 member 11(SLC7A11)/glutathione peroxidase(GPX)4 axis.Methods Forty C57BL/6J mice were randomized into the control,BLM,PM2.5,BLM+PM2.5 and sulforaphane(SFN,Nrf2 agonist)groups,with eight mice in each group.PM2.5 expo-sures were conducted to the BLM-induced IPF mice for two weeks.The lung function was measured,and the content of hydroxyproline(HYP)in lung tissue and the pathomorphology of lungs were observed.Reactive oxygen species(ROS),malondialdehyde(MDA),ferrous ion(Fe2+)and glutathione(GSH)of the lung tissue were measured by ELISA.The mRNA and pro-teins levels of Nrf2,SLC7A11,GPX4,collagen typeⅠ(COL-1),α-smooth muscle actin(α-SMA)were measured by quantitative polymerase chain reaction(qPCR)and Western blot.Results Compared with the control group,the lung function of mice was signif-icantly reduced(P＜0.01)in the BLM and PM2.5 groups,while lung tissue showed the characteristic pathological changes of pulmonary fibrosis such as a large number of inflammatory cell infiltration,alveolar wall fracture,thickening,collagen deposition,and sig-nificantly increased HYP,Fe2+,ROS,MDA(P＜0.05,P＜0.01),genes and proteins of COL-1,α-SMA(P＜0.01);and decreased GSH,Nrf2,SLC7A11,GPX4 genes and proteins(P＜0.05,P＜0.01).The above-mentioned lesions were markedly aggravated in the BLM+PM2.5 group compared with the BLM(P＜0.05)and PM2.5 groups(P＜0.01),and were also improved in the SFN group(P＜0.05,P＜0.01).Conclusions PM2.5 exposures can exac-erbate IPF-induced IPF in mice,and the regulating of Nrf2/SLC7 A1 1/GPX4 axis and ferroptosis might be in-volved in the related mechanisms.

In response to the challenges of varied sizes and diverse shapes of colorectal polyps,especially with blurred boundaries that often complicates localization and smaller polyps being particularly prone to oversight,a colorectal polyp segmentation algorithm integrating Transformer and convolution is proposed.Transformer is employed to extract global features from images for ensuring the network's capability for global modeling and improving the localization capability for both main polyp regions and vague boundaries.Subsequently,convolution is introduced to augment the network's ability to process polyp details,refining boundary segmentation and enhancing the capture capability for small-sized polyps.Finally,a deep fusion of the features extracted by Transformer and convolution is carried out to realize feature complementarity.The experimental evaluation using CVC-ClinicDB and Kvasir-SEG datasets show that the algorithm has similarity coefficients of 95.4%and 93.2%,and mean intersection over union of 91.3%and 88.6%,respectively.Further tests on the generalization capability of the algorithm are conducted on CVC-ColonDB,CVC-T,and ETIS datasets,in which similarity coefficients of 81.3%,90.9%and 80.1%are obtained.The results indicate a notable improvement in the accuracy of polyp segmentation achieved by the proposed algorithm.

Objective To analyze and verify the role of senescent genes in the treatment,prognosis,and tumor microenvironment(TME)characteristics of osteoblastic osteosarcoma,bioinformatic methods were employed.Methods Senescent genes were obtained from the China National Genome Science database(https://ngdc.cncb.ac.cn/aging/index).The gene expression profile and clinical information of osteosarcoma patients were sourced from the TARGET database(https://ocg.cancer.gov/programs/target),while single-cell RNA-sequencing(scRNA-seq)data was collected from GSE162454 on the Gene Expression Omnibus(GEO)for downstream analysis.Osteosarcoma cells were classified based on scRNA-seq,and differential expression analysis between osteoblasts/chondroblasts and other cell types was conducted to identify differently expressed genes(DEGs).After matching with the senescent genes,prognostic senescent DEGs were identified through univariable and multivariable Cox regression analysis.Subsequently,the osteosarcoma senescent-related model(OSRM)was constructed,and the risk score was calculated.The role of OSRM in treatment,prognosis,and TME of osteosarcoma was further investigated.Results The analysis revealed that GSE162454 contained 6 osteosarcoma samples,with 19933 cells identified after filtering,quality control,and normalization.Seventeen cellular subtypes were identified using uniform manifold approximation and projection(UMAP)methods.A total of 4821 DEGs were found between osteoblasts/chondroblasts and other subtypes,with 132 senescent DEGs obtained after matching with the senescent gene set.In the TARGET database,4 prognostic senescent DEGs[ADH5(alcohol dehydrogenase 5),ARHGAP1(Rho GTPase activating protein 1),APOE(apolipoprotein E),and ATF4(activating transcription factor 4)]were identified through univariable and multivariable Cox analyses to construct OSRM.Based on risk score,patients were stratified into high-and low-risk groups,with the latter showing better prognosis(HR=0.13,95%CI 0.06-0.28,P<0.001)and higher sensitivity to immune checkpoint inhibitors.qRT-PCR and Western blotting confirmed the high expression of senescent genes ADH5(P<0.01),APOE(P<0.01),and ATF4(P<0.05)in the K7M2 osteosarcoma cell line,suggesting the potential for predicting the response to anti-PD-1 immunotherapy for osteosarcoma.Conclusions scRNA-seq facilitated the division of osteosarcoma into 17 cell subtypes.ADH5,ARHGAP1,APOE,and ATF4 emerged as potential cancer-promoting or suppressing senescent genes in osteosarcoma.OSRM was found to be associated with treatment response,prognosis,and TME characteristics,thereby promoting the molecular pathological diagnosis of osteoblastic osteosarcoma and prediction for anti-PD-1 immunotherapy.

In response to the challenge posed by the significant shape and scale variations of tumors and organs in three-dimensional medical images,which often results in low segmentation accuracy,an end-to-end three-dimensional fully convolutional segmentation model is introduced.A dilated cubic integration module is designed to achieve multi-scale integration at different resolution stages,thereby enhancing the recognition capability on complex boundaries.Subsequently,a cross-stage context fusion module is incorporated to merge shallow and deep features,thereby facilitating convergence and more precise localization of the target objects.Finally,features from the encoder are concatenated by the decoder to realize segmentation.The average Dice similarity coefficients reach 85.37%on the brain tumor segmentation dataset and 83.99%on the abdominal organ segmentation dataset.Experimental results indicate that the proposed model exhibits high accuracy in three-dimensional tumor and organ segmentation.