ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

Berberine is a kind of isoquinoline alkaloid extracted from the roots and rhizomes of many medicinal plants,such as Coptis chinensis of Ranunculus family,Phellodendron chinensis of rutaceae family,and Berberine Sanacanthus family.In recent years,with the deepening of research,berberine has shown re-markable prevention and treatment effect in a variety of neuro-psychiatric disease models.This paper summarizes the research progress of berberine in neuropsychiatric diseases and provides theoretical support for further clinical prevention and treatment of neuropsychiatric diseases.

Natural products are an important source for innovative drugs,but unclear molecular targets and mechanisms limit their further development and application.The authors proposed a new method for the target identification of natural products based on proteolysis-targeting chimera(PROTAC)technology and quantitative proteomics,and established the targeted degradomics(TGDO) technology for the identification of weak-affinity tar-gets.This article summarizes the standardized workflow and the application of TGDO for target identification of natural products.

Berberine is a kind of isoquinoline alkaloid extracted from the roots and rhizomes of many medicinal plants,such as Coptis chinensis of Ranunculus family,Phellodendron chinensis of rutaceae family,and Berberine Sanacanthus family.In recent years,with the deepening of research,berberine has shown re-markable prevention and treatment effect in a variety of neuro-psychiatric disease models.This paper summarizes the research progress of berberine in neuropsychiatric diseases and provides theoretical support for further clinical prevention and treatment of neuropsychiatric diseases.

Natural products are an important source for innovative drugs,but unclear molecular targets and mechanisms limit their further development and application.The authors proposed a new method for the target identification of natural products based on proteolysis-targeting chimera(PROTAC)technology and quantitative proteomics,and established the targeted degradomics(TGDO) technology for the identification of weak-affinity tar-gets.This article summarizes the standardized workflow and the application of TGDO for target identification of natural products.

Objective A new occipital bone removal technology was applied to improve the success rate of brain removal.Methods The skull was sawed based on the traditional brain removal technology,and part of the occipital bone was removed downward centered in external occipital protuberance to the foramen magnum,then exposed the telencephalon,cerebellum and posterior medulla oblongata.After that,removed the tentorium cerebelli and cut down the medulla oblongata and the related cranial nerves at the skull base,then removed the brain tissues.Results The removed brain tissues had structurally intact telencephalon,cerebellum and brain stem,clear vessels in the cerebral sulci,and relatively intact optic chiasm,olfactory tracts and vertebro-basilar arteries.Conclusion Brain removal through a fenestration on the external occipital protuberance can effectively preserve the integrity of brain specimens,and improve the success rate of brain removal,which is of great significance for central nervous system teaching and improvement of human brain tissue repositories.

Objective To propose a preventive maintenance strategy of the heating,ventilation and air-conditioning(HVAC)system in pharmacy intravenous admixture services(PIVAS)based on the reliability centered maintenance(RCM)method so as to provide references for PIVAS equipment maintenance.Methods Firstly,a HVAC system RCM review team was formed,and the failure modes and impacts of important functional components of the equipment were analyzed to clarify the consequences of the failure of each functional component under the premise of ensuring the safety and integrity of the equipment and with the goal of minimizing the loss of maintenance downtime and the consumption of maintenance resources.Secondly,with a standardized logical decision-making procedure the preventive maintenance strategy was determined and implemented based on the consequences of functional failure.Finally,statistical analyses were carried out on such equipment indicators as performance parameter qualification rate,failure rate and maintenance cost before and after the RCM method-based strategy was executed,in order to evaluate the efficacy of the strategy.Results The RCM method-based preventive maintenance strategy had the performance qualification rate increased from 97.47%to 99.06%(χ2=24.139,P<0.01),the failure rate decreased from 0.24%to 0.03%(χ2=13.519,P<0.01)and the maintenance cost reduced by 11.5%,from RMB 134,200 to 118,700.Conclusion The RCM method-based preventive maintenance strategy provides reliable equipment for PIVAS and lowers the maintenance cost effectively,and references are given for the development of automated and intelligent equipment maintenance strategies for PIVAS.[Chinese Medical Equipment Journal,2025,46(10):78-83]

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Objective:To investigate the role of WW domain containing E3 ubiquitin protein ligase 1 (WWP1) in enamel development of mice.Methods:Single-cell RNA sequencing data of incisor tissues of postnatal day 7 (P7) mice and mandibular first molar tooth germs of P3.5 mice were used to analyze the expression of Wwp1 in dental epithelial cells. Immunohistochemistry was performed to observe the distribution and expression levels of WWP1 in the epithelium of mouse incisors and mandibular first molar tooth germs. Wwp1 knockout (Wwp1 KO) mice were generated and collected with their control littermates at P1, P7, three mice per group, as well as at P14, P28, 2 months (2M), and 3M, six mice per group. The enamel volumes of molars and incisors were analyzed using micro-CT. Scanning electron microscopy was employed to examine the enamel cross-sections of Wwp1 KO and control mice. Energy dispersive spectroscopy (EDS) was used to analyze the calcium and phosphorus content of the enamel rod of incisors. Immunofluorescence was performed to detect the expression of amelogenin (AMELX) in the ameloblasts of Wwp1 KO and control mice. Additionally, LS-8 ameloblast-like epithelial cells were cultured, and Wwp1 siRNA or overexpression plasmids were transfected to knock down or overexpress WWP1. The protein levels of AMELX were then assessed by Western blotting.Results:Single-cell sequencing result showed a high Wwp1 mRNA expression level in the epithelial cells of mouse incisors and mandibular molar tooth germs. Immunohistochemistry revealed the expression of WWP1 in presecretory, secretory, transitional, and mature ameloblasts. Wwp1 KO mice exhibited enamel developmental defects. The enamel volumes of molars and incisors in Wwp1 KO mice [(0.155±0.016), (0.300±0.017) μm 3] were reduced by 23.95% ( P<0.001) and 28.31% ( P<0.001) compared with the control group [(0.203±0.062), (0.418±0.023) μm 3] respectively. Scanning electron microscopy showed disorganized enamel structures in Wwp1 KO incisors and molars. EDS results showed the weight percent of calcium in the enamel rod of incisors decreased in Wwp1 KO mice [(20.74±0.91)%] compared with the control group [(30.30±3.83)%] ( P<0.001), and the calcium-to-phosphorus ratio decreased in Wwp1 KO mice (1.93±0.01) compared with the control group (2.02±0.01) ( P<0.001). Immunofluorescence showed weaker AMELX expression in ameloblasts of mandibular first molar tooth germs from P1 and P7 Wwp1 KO mice compared with the control group ( P<0.001, P<0.001). In LS-8 cells, Wwp1 knocked-down led to a decrease of AMELX protein expression, while WWP1 overexpression resulted in an increased AMELX protein level. Conclusions:WWP1 promotes ameloblast differentiation and enamel matrix mineralization, playing a critical role in enamel formation.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]