Objective: To develop a dual-branch deep learning framework for accurate multi-label classification of fundus diseases, addressing the key limitations of insufficient complementary feature extraction and inadequate cross-modal feature fusion in existing automated diagnostic methods. Methods: The fundus multi-label classification dataset with 12 disease categories (FMLC-12) dataset was constructed by integrating complementary samples from Ocular Disease Intelligent Recognition (ODIR) and Retinal Fundus Multi-Disease Image Dataset (RFMiD), yielding 6 936 fundus images across 12 retinal pathology categories, and the framework was validated on both FMLC-12 and ODIR. Inspired by the holistic multi-regional assessment principle of the Five Wheels theory in traditional Chinese medicine (TCM) ophthalmology, the dual-branch multi-label network (DBMNet) was developed as a novel framework integrating complementary visual feature extraction with pathological correlation modeling. The architecture employed a TransNeXt backbone within a dual-branch design: one branch processed red-green-blue (RGB) images to capture color-dependent features, such as vascular patterns and lesion morphology, while the other processed grayscale-converted images to enhance subtle textural details and contrast variations. A feature interaction module (FIM) effectively integrated the multi-scale features from both branches. Comprehensive ablation studies were conducted to evaluate the contributions of the dual-branch architecture and the FIM. The performance of DBMNet was compared against four state-of-the-art methods, including EfficientNet Ensemble, transfer learning-based convolutional neural network (CNN), BFENet, and EyeDeep-Net, using mean average precision (mAP), F1-score, and Cohen's kappa coefficient. Results: The dual-branch architecture improved mAP by 15.44 percentage points over the single-branch TransNeXt baseline, increasing from 34.41% to 44.24%, and the addition of FIM further boosted mAP to 49.85%. On FMLC-12, DBMNet achieved an mAP of 49.85%, a Cohen’s kappa coefficient of 62.14%, and an F1-score of 70.21%. Compared with BFENet (mAP: 45.42%, kappa: 46.64%, F1-score: 71.34%), DBMNet outperformed it by 4.43 percentage points in mAP and 15.50 percentage points in kappa, while BFENet achieved a marginally higher F1-score. On ODIR, DBMNet achieved an F1-score of 85.50%, comparable to state-of-the-art methods. Conclusion DBMNet effectively integrates RGB and grayscale visual modalities through a dual-branch architecture, significantly improving multi-label fundus disease classification. The framework not only addresses the issue of insufficient feature fusion in existing methods but also demonstrates outstanding performance in balancing detection across both common and rare diseases, providing a promising and clinically applicable pathway for standardized, intelligent fundus disease classification.

BACKGROUND:Preliminary research by our group suggests that targeting fibroblast growth factor receptor 1(FGFR1)may be an effective strategy for treating RA. OBJECTIVE:To investigate the effects of an FGFR1 inhibitor(PD173074)on bone destruction in rats with collagen-induced arthritis. METHODS:Twenty-five female Sprague-Dawley rats were randomly divided into five groups:normal control group,model group,methotrexate group,low-dose PD173074 group,and high-dose PD173074 group.Except for the normal control group,rat models of type Ⅱ collagen-induced arthritis were made in each group.After successful modeling,rats were injected intraperitoneally with sterile PBS in the normal and model groups,1.04 mg/kg methotrexate in the methotrexate group,and 5 and 20 mg/kg in the low-dose group and high-dose PD173074 groups,once a week.After 4 weeks of drug administration,clinical symptoms and joint swelling in rats were observed.Micro-CT was used for three-dimensional reconstruction and analysis of the ankle joints.Pathological changes in the ankle joints were observed.Periarticular angiogenesis and the expression of receptor activator of nuclear factor-Κb ligand were detected.The expression levels of p-FGFR1,vascular endothelial growth factor A,and tartrate-resistant acid phosphatase in the synovial membrane were measured.Pathological changes in the liver,spleen,and kidney were observed and liver,spleen,and kidney indices were calculated. RESULTS AND CONCLUSION:PD173074 could alleviate clinical symptoms and joint swelling,delay bone loss,improve bone structure,reduce synovial invasion and cartilage bone erosion,reduce the number of periarticular osteoclasts,inhibit angiogenesis in synovial tissues,reduce the expression of receptor activator of nuclear factor-Κb ligand,and inhibit the expression of FGFR1 phosphorylated protein,tartrate-resistant acid phosphatase and vascular endothelial growth factor A.Pathologic observation of the liver,spleen and kidney in rats showed no obvious toxic side effects after PD173074 treatment.To conclude,the FGFR1 inhibitor can delay the progression of joint inflammation and bone destruction and inhibit angiogenesis in the rat model of type Ⅱ collagen-induced arthritis.The therapeutic effect of PD173074 has been preliminarily validated in the type Ⅱ collagen-induced arthritis model and may act by inhibiting FGFR1 phosphorylation,which provides a direction for the search of new therapeutic targets for rheumatoid arthritis.

BACKGROUND:Although researchers have noted that fibroblast growth factor receptor 1 shows great potential in rheumatoid arthritis bone destruction,there is a lack of reviews related to the potential mechanisms of fibroblast growth factor receptor 1 in rheumatoid arthritis bone destruction. OBJECTIVE:To comprehensively analyze the mechanism of fibroblast growth factor receptor 1 in bone destruction in rheumatoid arthritis by reviewing the relevant literature at both home and abroad. METHODS:We searched the CNKI database using the Chinese search terms"fibroblast growth factor receptor 1,rheumatoid arthritis,bone destruction,bone cells,osteoblasts,osteoclasts,chondrocytes,macrophages,synovial fibroblasts,T cells,vascular endothelial cells."PubMed database was searched using the English search terms"fibroblast growth factor receptor 1,rheumatoid arthritis,bone destruction,osteocytes,osteoblasts,osteoclasts,chondrocytes,macrophages,synovial fibroblasts,T cells,endothelial cells."The search period focused on April 1992 to January 2024.After screening the literature by reading titles,abstracts,and full texts,a total of 82 articles were finally included for review according to inclusion and exclusion criteria. RESULTS AND CONCLUSION:Fibroblast growth factor receptor 1 was found to be widely expressed in bone tissue-associated cells,including osteoblasts,osteoclasts,and osteoclasts.Fibroblast growth factor receptor 1 affects bone remodeling and homeostasis by regulating the function of these cells,as well as promoting the onset and progression of bone destruction in rheumatoid arthritis.Fibroblast growth factor receptor 1 is involved in the inflammatory response of synovial fibroblasts and macrophages and regulates angiogenesis of endothelial cells in synovial tissues.Fibroblast growth factor receptor 1 promotes bone destruction in several ways.Fibroblast growth factor receptor 1 may be a potential causative agent of bone destruction in rheumatoid arthritis and provides a reference for further research on its therapeutic targets.

Periodontal bone defects, primarily caused by periodontitis, are highly prevalent in clinical settings and manifest as bone fenestration, dehiscence, or attachment loss, presenting a significant challenge to oral health. In regenerative medicine, harnessing developmental principles for tissue repair offers promising therapeutic potential. Of particular interest is the condensation of progenitor cells, an essential event in organogenesis that has inspired clinically effective cell aggregation approaches in dental regeneration. However, the precise cellular coordination mechanisms during condensation and regeneration remain elusive. Here, taking the tooth as a model organ, we employed single-cell RNA sequencing to dissect the cellular composition and heterogeneity of human dental follicle and dental papilla, revealing a distinct Platelet-derived growth factor receptor alpha (PDGFRA) mesenchymal stem/stromal cell (MSC) population with remarkable odontogenic potential. Interestingly, a reciprocal paracrine interaction between PDGFRA⁺ dental follicle stem cells (DFSCs) and CD31⁺ Endomucin⁺ endothelial cells (ECs) was mediated by Vascular endothelial growth factor A (VEGFA) and Platelet-derived growth factor subunit BB (PDGFBB). This crosstalk not only maintains the functionality of PDGFRA⁺ DFSCs but also drives specialized angiogenesis. In vivo periodontal bone regeneration experiments further reveal that communication between PDGFRA⁺ DFSC aggregates and recipient ECs is essential for effective angiogenic-osteogenic coupling and rapid tissue repair. Collectively, our results unravel the importance of MSC-EC crosstalk mediated by the VEGFA and PDGFBB-PDGFRA reciprocal signaling in orchestrating angiogenesis and osteogenesis. These findings not only establish a framework for deciphering and promoting periodontal bone regeneration in potential clinical applications but also offer insights for future therapeutic strategies in dental or broader regenerative medicine.
Receptor, Platelet-Derived Growth Factor alpha/metabolism* ; Humans ; Neovascularization, Physiologic/physiology* ; Dental Sac/cytology* ; Single-Cell Analysis ; Transcriptome ; Mesenchymal Stem Cells/metabolism* ; Bone Regeneration ; Animals ; Dental Papilla/cytology* ; Periodontium/physiology* ; Stem Cells/metabolism* ; Regeneration ; Angiogenesis

Objective:To investigate the application value of intraoperative electrocochleography（ECochG） monitoring technique and insertion techniques in cochlear implant（CI） and analyze its relationship with postoperative residual hearing（RH） preservation. Methods:Thirty-one patients（35 ears） who received CI in our hospital from June 2022 to July 2024 were enrolled. The Advanced Bionics Active Insertion Monitoring（AIM） system was used for real-time ECochG monitoring during surgery. Intraoperative cochlear microphonics （CM） waveform changes were recorded and analyzed in relation to postoperative RH preservation. Results:①ECochG recordings were successfully obtained in 34 of 35 ears （97.1%）. ②According to Harris classification, there were 7 ears（20.6%） of Type A（rising）, 7 ears（20.6%） of Type C（declining）, 8 ears（23.5%） of Type CC（fluctuating）, and 12 ears（35.3%） of Type D（no response）. ③The total CM amplitude decrease was significantly moderately correlated with postoperative low-mid frequency hearing loss（r=0.67, P=0.017）. The total CM amplitude decrease was significantly moderately correlated with postoperative low frequency hearing loss（r=0.65, P=0.023）. ④For the mean amplitude variation, the Amax was 30.70 μV, the Amin was 8.64 μV, and the Aend was 18.27 μV. ⑤Sixteen cases completed postoperative follow-up, with an average low-mid frequency（125-1 000 Hz） residual hearing loss of 15.25 dB HL and a RH preservation rate of 87.5%. Conclusion:Intraoperative ECochG monitoring can effectively predict postoperative residual hearing changes, effectively guide surgical manipulation, and improve residual hearing preservation rate.
Humans ; Cochlear Implantation/methods* ; Audiometry, Evoked Response ; Cochlear Implants ; Male ; Female ; Adult ; Middle Aged ; Monitoring, Intraoperative ; Adolescent ; Young Adult ; Minimally Invasive Surgical Procedures ; Child ; Aged ; Postoperative Period

Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

Objective To systematically review the application and effectiveness of deep learning(DL)in diagnosis of mild cogni-tive impairment(MCI)among older adults.Methods PubMed,Web of Science,CNKI and Wanfang databases were searched for literatures related to the application of DL in MCI among older adults,from database inception to December,2024.A scoping review was conducted.The literature screening process followed the Scoping Review Report Specification list,and the quality assess-ment was conducted using the cross-sectional study quality evaluation tool developed by the Evidence-based Health Care Center.Results A total of eleven papers were included,from Italy,USA,South Korea,China,India and Switzerland,involving 11 829 elderly participants,publicated mainly between 2014 and 2024,reflecting the rapid development trend of the field in the last decade,which was in line with the timing of the development of DL technology.The quality scores of the included literatures were all six to seven.The types of studies were all cross-sectional studies with significant cross-disciplinary characteristics,mainly originating from the fields of clinical medicine,biology and neuroimaging.The literature data were mainly based on the Alzheimer's disease Neuroimaging Program database and integrated other data resources.In terms of data type,in addition to brain imaging data,one study based on text data was also included.In terms of models used,five of the studies were mainly based on convolutional neu-ral networks,and the rest used different DL modeling frameworks.The task types contained binary and triple classification.In terms of prediction results,the DL models constructed on multimodal data,such as brain imag-es,could be used to construct high-precision prediction models for MCI classification,and the models were all good,with accuracy more than 70%and AUC values more than 0.7.The diagnostic accuracy of some of the mod-els was more than 90%,and the model with the highest prediction accuracy was the one that used the Biceph-Net lightweight framework,with accuracy close to 100%,and the text analysis model based on Transformer made the AUC value of 0.846,which provided new ideas for the diagnosis of non-imaging data.Conclusion DL can not only provide strong support for the accurate identification of MCI in the elderly,but also provide auxiliary prediction tools for clinicians,which can help delay the progression of the disease and improve the prognosis of patients.

To promote the understanding of the requirements of sheet for oral solid preparation in the Pharmacopoeia of the People's Republic of China(2025 edition)and improve the quality control level of related parties in production and use,the key quality control items specified in Pharmacopoeia of the People's Republic of China and the testing points were analyzed and discussed combined with the current situation of sheet for oral solid preparation industry and relevant standards at home and abroad.Suggestion was given that quality control should be carried out according to product characteristics,application,production process,and risk assessment,and reasonable limits should be set.

Objective To investigate the status of oral frailty(OF)in patients who underwent chemotherapy for lung cancer,identify key factors influencing OF,and develop a risk prediction model.Methods Using convenience sampling,431 lung cancer inpatient were recruited from three Tier-IIIA hospitals in Jiangsu Province between September and November 2024 as the training cohort.The patients were divided into OF and non-OF groups.Relevant data were compared between the two groups.Multifactorial logistic regression analysis was performed to determine factors that associated with OF,and a risk prediction model was created accordingly.Receiver operating characteristic(ROC)curve analysis was used to predict model performance.In December 2024,additional 185 patients from one other Tier-IIIA hospitals were recruited to validate the developed model.Results The prevalence of OF among lung-cancer patients undergoing chemotherapy was 58.93%.Following listed items were identified as the risk factors of OF(all P<0.05):older in age(OR=3.420),poor education(OR=0.030),brain metastasis(OR=7.880),high nutritional risk screening 2002 score(OR=1.550),elevated C-reactive protein(OR=1.100),and elevated lactate dehydrogenase(OR=1.010).ROC area under the curve(AUC)of the model was 0.860(95%CI:0.830-0.900)in modelling cohort and 0.840(95%CI:0.780-0.900)in validation cohort.Hosmer-Lemeshow goodness-of-fit test yielded χ 2=4.870,P=0.770 for the training set and χ 2=2.770,P=0.950 for the validation set.Conclusion The risk prediction model for OF developed in this study demonstrates a good predictive performance and can facilitate early identification of high-risk patients,thereby providing a scientific basis for clinical interventions.

Objective To explore the clinical features,diagnosis,and treatment of Mycobacterium senegalense infection.Methods We reported a case of postoperative wound infection caused by M.senegalense in a patient who underwent spinal intradural tumor surgery at Beijing Tsinghua Changgung Hospital.CNKI,Wanfang,VIP,and PubMed databases were searched from inception to April 1,2024 using keywords Mycobacterium senegalense both in Chinese and English to identify relevant reports.Thirteen eligible articles were retrieved,including 1 in Chinese and 12 in English.The clinical data of the 13 cases of M.senegalense infection were reviewed and analyzed.Results A case of postoperative wound infection caused by M.senegalense was reported in a patient who underwent spinal intradural tumor surgery.The patient was a 53-year-old male.He was previously healthy.The patient was initially treated for schwannoma by resection of an intraspinal space-occupying lesion at another hospital.Two weeks after the operation,the skin surrounding the surgical incision became redness,swelling,and pain.The patient did not have fever.M.senegalense was identified from pus culture.The patient was treated with doxycycline,moxifloxacin,and clarithromycin combination therapy,as well as wound disinfection and dressing changes.The infected wound subsequently healed.Among the 13 patients with M.senegalense infection,30.8％(4/13)were males and 69.2％(9/13)were females.The average age of patients was(51.6±17.7)years.The reported cases included skin and soft tissue infection(7 cases),bloodstream infection(2 cases),artificial joint infection(2 cases),and one case each of osteomyelitis and prosthetic infection.About half(46.2％,6/13)of the patients were immunosuppressed.Most(76.9％,10/13)of the patients were infected after surgery and trauma.Antimicrobial susceptibility test showed that all of the M.senegalense isolates were susceptible to amikacin,ciprofloxacin,clarithromycin and doxycycline.Conclusions M.senegalense infection is rarely reported.It primarily occurs following surgical procedures or trauma.Appropriate and adequate antibiotic combination therapy based on antimicrobial susceptibility testing generally results in favorable outcomes.