Background: Chinese herbal pieces are an essential component of traditional Chinese medicine. Accurate identification and classification of these materials are crucial in clinical practice. Objective: This study aims to enhance the recognition efficiency of Chinese herbal pieces using deep learning technology, while addressing the limitations of traditional manual classification methods in terms of both quality and efficiency. Methods: A comprehensive dataset containing 201 types of Chinese herbal pieces was established. Based on Real-time Detection Transformer (RT-DETR), we designed and integrated a Feature-focused Diffusion Network (FDN), resulting in an improved model termed RT-DETR-FDN. The proposed FDN includes a Feature-focus Module and a feature diffusion mechanism, enabling the model to capture more extensive feature information from Chinese herbal pieces and diffuse it across multiple detection scales. Results: Experimental results show that RT-DETR-FDN achieved a precision of 0.925, a recall of 0.943, and an mAP50-95 of 0.851. In addition, the model was compared with representative You Only Look Once series models commonly used in object detection. Compared with these models, RT-DETR-FDN achieved higher recognition accuracy while maintaining a lightweight architecture. Conclusion: This study integrates deep learning with traditional Chinese medicine, providing a more effective solution for the recognition of Chinese herbal pieces.

Processing for deodorization is widely used in the production of animal-derived Chinese medicinal materials. In this study, Heracles Neo ultra-fast gas-phase electronic nose combined with chemometrics was employed to analyze the overall odor difference of Cervi Cornu Pantotrichum(focusing on that derived from Cervus nippon Temminck in this study) before and after processing. The results showed that the electronic nose effectively distinguished between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. HS-GC-MS was used to identify and quantify the volatile components in the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum, and 35 and 37 volatile components were detected in the medicinal materials and decoction pieces, respectively. The medicinal materials and decoction pieces contained 28 common volatile components contributing to the odor of Cervi Cornu Pantotrichum. The odor activity value(OAV) of each volatile component was calculated based on the olfactory threshold and relative content. The results showed that there were 17 key odor substances such as isovaleraldehyde, 2-methylbutanal, isobutyraldehyde, hexanal, and methanethiol in the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. All of them had bad odor and were the main source of the odor of Cervi Cornu Pantotrichum. The results of principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) showed that there were significant differences in volatile components between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. Based on the thresholds of P<0.05 and Variable Importance in Projection(VIP)>1, 21 differential volatile odor components were screened out. Among them, isopentanol, isovaleraldehyde, 2-methylbutanal, n-nonanal, and dimethylamine were the key differential odor compounds between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. The odor compounds and their relative content reduced, and some flavor substances such as esters were produced after processing with wine, which was the main reason for the reduction of the odor after processing of Cervi Cornu Pantotrichum.
Odorants/analysis* ; Electronic Nose ; Gas Chromatography-Mass Spectrometry/methods* ; Animals ; Volatile Organic Compounds/analysis* ; Deer ; Drugs, Chinese Herbal/chemistry*

Macroporous resin adsorption column chromatography, silica gel column chromatography, ODS column chromatography, and semi-preparative high-performance liquid chromatography, combined with analytical methods such as NMR and MS, were employed to separate and identify compounds from the 70% ethanol extract of Ajania purpurea. A total of 30 compounds were isolated and identified, including 13 phenolic acids, 7 coumarins, 2 lignans, 1 flavonoid, 2 sesquiterpenes, 1 steroid, and 4 others. Among them, compounds 1 and 2 were newly discovered compounds, and compounds 4, 6, 8, 12, 14-23, 25, 28, and 30 were isolated from Ajania plants for the first time. Bioactivity screening showed that multiple compounds significantly inhibited the production of nitric oxide in lipopolysaccharide-stimulated RAW264.7 cells in a dose-dependent manner. Furthermore, compound 2 elevated the levels of glutathione in LPS-induced BEAS-2B cells, reduced the expression of pro-inflammatory cytokines such as tumor necrosis factor(TNF)-α, interleukin(IL)-6, and IL-1β, enhanced the mRNA of GPX4, HMOX1, NFE2L2, and enhanced protein levels of GPX4, HO-1, Nrf2, and SLC7A11, demonstrating potential anti-ferroptotic effect.
Mice ; Animals ; Lignans/isolation & purification* ; RAW 264.7 Cells ; Humans ; Nitric Oxide ; Tumor Necrosis Factor-alpha/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; NF-E2-Related Factor 2/metabolism* ; Macrophages/metabolism* ; Interleukin-6/immunology*

Depression is increasingly prevalent among adolescents and can profoundly impact their lives. However, the early detection of depression is often hindered by the time-consuming diagnostic process and the absence of objective biomarkers. In this study, we propose a novel approach for depression detection based on an affective brain-computer interface (aBCI) and the resting-state electroencephalogram (EEG). By fusing EEG features associated with both emotional and resting states, our method captures comprehensive depression-related information. The final depression detection model, derived through decision fusion with multiple independent models, further enhances detection efficacy. Our experiments involved 40 adolescents with depression and 40 matched controls. The proposed model achieved an accuracy of 86.54% on cross-validation and 88.20% on the independent test set, demonstrating the efficiency of multimodal fusion. In addition, further analysis revealed distinct brain activity patterns between the two groups across different modalities. These findings hold promise for new directions in depression detection and intervention.
Humans ; Male ; Female ; Adolescent ; Case-Control Studies ; Depression/diagnosis* ; Early Diagnosis ; Rest ; Electroencephalography/methods* ; Brain-Computer Interfaces ; Models, Psychological ; Reproducibility of Results ; Affect/physiology* ; Photic Stimulation/methods* ; Video Recording ; Brain/physiopathology*

Mutations in the IARS1 gene are rare in clinical practice， and up to now， only ten cases with detailed clinical and genetic data have been recorded in the literature. This article reports a case of growth retardation， intellectual developmental disorder， hypotonia， and hepatopathy （GRIDHH） associated with single heterozygous mutations in the IARS1 gene and summarizes the clinical and genetic features of GRIDHH， thereby expanding the genetic spectrum of GRIDHH.

Periodontitis and rheumatoid arthritis (RA) are chronic inflammatory diseases that share similar inflammatory mechanisms and characteristics. Programmed cell death (PCD) has recently garnered attention for its crucial role in regulating inflammation and maintaining tissue homeostasis, as well as for its potential to link these two diseases. The various forms of PCD--including apoptosis, pyroptosis, and necroptosis--are closely controlled by signaling pathways such as Toll-like receptor 4 (TLR4) /NF-κB and MAPK. These pathways determine cell fate and influence inflammatory responses, tissue destruction, and repair, and they both play important roles in the pathogenesis of RA and periodontitis. In periodontitis, periodontal pathogens such as Porphyromonas gingivalis (P. gingivalis) and its virulence factors, including lipopolysaccharide (LPS), induce pyroptosis and necroptosis in immune cells such as macrophages via the TLR4/NF-κB pathway, which leads to an excessive release of pro-inflammatory cytokines such as interleukin (IL)-1β and tumor necrosis factor (TNF)-α. Concurrently, these pathogens inhibit the normal apoptotic process of immune cells, such as neutrophils, prolonging their survival, exacerbating immune imbalance, and aggravating periodontal tissue destruction. Similarly, in RA synovial tissue, fibroblast-like synoviocytes (FLS) acquire apoptosis resistance through signaling pathways such as the Bcl-2 family, JAK/STAT, and NF-κB, allowing for the consistent proliferation and secretion of matrix metalloproteinases and pro-inflammatory cytokines. Meanwhile, the continuous activation of pyroptotic pathways in neutrophils and macrophages results in the sustained release of IL-1β, further exacerbating synovial inflammation and bone destruction. Notably, dysregulated PCD fosters inter-organ crosstalk through shared inflammatory mediators and metabolic networks. Damage-associated molecular patterns (DAMPs) and cytokines that originate from periodontal lesions can spread systemically, influencing cell death processes in synovial and immune cells, thereby aggravating joint inflammation and bone erosion. By contrast, systemic inflammation in RA can upregulate osteoclastic activity or interfere with the normal apoptosis of periodontal cells via TNF-α and IL-6, ultimately intensifying periodontal immune imbalance. This review highlights the pivotal bridging role of PCD in the pathogenesis of both periodontitis and RA, providing a reference for therapeutic strategies that target cell death pathways to manage and potentially mitigate these diseases.

Objective:To address the inefficiency, safety hazards, and resource wastage in traditional medical laboratory management, this study proposes a digital laboratory information management system (LIMS) based on Total Quality Management (TQM) principles. The LIMS has been implemented at the National Center for Geriatric Medicine (Huashan) affiliated with Fudan University.Methods:Centered on the principles of " all-staff participation, whole-process control, and comprehensive management", a multidimensional management framework was developed to integrate personnel, equipment, reagents, and safety protocols. The system incorporated IoT, digital twin, and artificial intelligence (AI) technologies to achieve end-to-end digital control. A layered architecture (physical layer, data layer, model layer, etc.) was designed to integrate functional modules such as full lifecycle equipment management, dual-authentication for hazardous chemicals, and intelligent resource scheduling. A 3D digital twin model was deployed to visualize real-time laboratory operations.Results:Post-implementation, equipment reservation frequency and usage duration at the National Center increased by 114% and 124%, respectively, with no safety incidents reported. Equipment sharing utilization reached 85%, and reagent expiration waste decreased by 30%.Conclusions:The system transforms laboratory management from experience-driven to data-driven by breaking data silos and optimizing collaboration mechanisms. It provides a replicable technical pathway and practical insights for the healthcare industry′s digital transformation. However, further improvements are needed in mobile support and system scalability.

Objective:To explore the clinical and pathological features and survival outcomes of patients with early-onset intrahepatic cholangiocarcinoma (EOICC).Methods:This is a multicenter, retrospective cohort study. Data of 1 160 intrahepatic cholangiocarcinoma patients undergoing radical resection in 14 tertiary Grade A hospitals in China from January 2010 to November 2021 were retrospectively collected. The cohort included 632 males and 528 females, aged( M (IQR)) 61 (14) years (range: 22 to 93 years). ICC aged ≤50 years at the time of diagnosis was defined as EOICC and >50 years as late-onset intrahepatic cholangiocarcinoma (LOICC). Of these, there were 247 cases in the EOICC group and 913 cases in the LOICC. The clinical and pathological characteristics of both groups were analyzed and compared using the independent sample t-test, Mann-Whitney U test or Kaplan-Meier method. Univariate and multivariate Cox regression models for patient outcomes were constructed and forest graphed. Results:Compared with the patients in the LOICC group, patients in the EOICC group had lower carcinoembryonic antigen levels (2.5(4.0) μg/L vs. 3.1(5.2)μg/L, U=124 899, P=0.009) and CA19-9 level (63.4(524.7)U/ml vs. 77.9(611.3)U/ml, U=120 320, P=0.013), higher levels of ALT (29(35)U/L vs. 24(26)U/L, U=101 214, P=0.013), a lower score of the Eastern US Cooperative Oncology Group (0 score patients: 54.7% vs. 44.1%, χ2=12.472, P=0.014), higher TNM stage ( χ2=11.807, P=0.038), and proportion of lymph node dissection (62.3% vs. 54.1%, χ2=5.355, P=0.021). Patients in the two groups in sex, first diagnosis symptoms, intrahepatic bile duct stone history, nail protein, albumin, total bilirubin, transaminase, liver function Child-Pugh grade, T stage, stage, N stage, preoperative laparoscopic exploration proportion, tumor diameter, vascular invasion proportion, differentiation, margin, intraoperative bleeding, postoperative complications, postoperative hospital days were no statistical significance (all P>0.05). Patients in the EOICC group had better outcomes than the LOICC group (median survival time: 29.7 months vs. 25.0 months, 3-year overall survival: 45.1% vs. 37.8%, P=0.027). Conclusion:EOICC patients are better than LOICC patients in carcinoembryonic antigen, CA19-9, ALT, physical strength status and TNM stage, and the long-term prognosis is also better than LOICC patients.

Objective To explore the materials and embolization technique employed in precision superselective transarterial embolization for the treatment of acute renal hemorrhage.Methods The data of 50 patients with acute renal hemorrhage who underwent precision superselective transarterial embolization were retrospectively analyzed.The angiographic findings,embolic materials and embolization methods were collected.The main outcome measures were technical success rate,clinical efficacy and renal function.Results In this study,44 patients had positive angiographic findings.The clinical success rate was 90.9%(40/44)after first precision superselective transarterial embolization.In patients of failure of first embolization,3 patients underwent successful repeated embolization and 1 patient refused repeat embolization.Empirical embolization was carried out among the 6 patients with negative angiographic findings.In 32 patients with complete data for estimated glomerular filtration rate(eGFR),there was no statistical difference before and those measured 7 d after precision superselective transarterial embolization.Conclusion Precision superselective transarterial embolization technique is an effective method for the treatment of acute renal hemorrhage,preserving renal function.