Randomized controlled trial(RCT) represents the "gold standard" for estimating the causal effects of interventions; however, their implementation in the field of health policy evaluation is frequently hindered by logistical feasibility and ethical constraints. Target Trial Emulation (TTE), a framework originating in clinical epidemiology, facilitates rigorous causal inference from observational data by explicitly emulating the design of an idealized "target trial". Recently, the application of TTE has transitioned from individual-level clinical interventions—such as pharmacological or surgical treatments—to population-level health policy evaluations. This interdisciplinary translation is not a localized conceptual shift but necessitates a series of comprehen-sive methodological adaptations. This paper systematically delineates the core logic of extending the TTEframework into the realm of health policy, providing a profound analysis of the transformation and reconstruction of critical elements, including study units, intervention definitions, time zero, causal estimands, and analytical strategies. Furthermore, it examines the unique challenges inherent in policy contexts, such as policy heterogeneity, staggered adoption, concurrent policy interference, and data granularity limitations. The paper also evaluates the integration of analytical methods, such as instrumental variables (IV) and difference-in-differences (DID), within the TTE framework. This synthesis aims to provide methodological guidance and prospective insights for conducting high-quality policy evaluations using real-world data (RWD).

Ursodeoxycholic acid(UDCA)is a naturally occurring,low-toxicity,and hydrophilic bile acid(BA)in the human body that is converted by intestinal flora using primary BA.Solute carrier family 7 member 11(SLC7A11)functions to uptake extracellular cystine in exchange for glutamate,and is highly expressed in a variety of human cancers.Retroperitoneal liposarcoma(RLPS)refers to liposarcoma originating from the retroperitoneal area.Lipidomics analysis revealed that UDCA was one of the most significantly down-regulated metabolites in sera of RIPS patients compared with healthy subjects.The augmentation of UDCA concentration(≥25 μg/mL)demonstrated a suppressive effect on the proliferation of liposarcoma cells.[15N2]-cystine and[13Cs]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione(GSH)synthesis.Mechanistically,UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis,leading to reactive oxygen species(ROS)accumulation and mitochondrial oxidative damage.Furthermore,UDCA can promote the anti-cancer effects of ferroptosis inducers(Erastin,RSL3),the murine double minute 2(MDM2)inhibitors(Nutlin 3a,RG7112),cyclin dependent kinase 4(CDK4)inhibitor(Abemaciclib),and glutaminase inhibitor(CB839).Together,UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity,and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA.More importantly,in combination with other antitumor chemotherapy or physiotherapy treatments,UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.

AIM:To determine if scutellarin(Scu)provides neuroprotection by reducing neuronal apoptosis in rats subjected to middle cerebral artery occlusion(MCAO)via the inhibition of the JAK2/STAT3 signalling pathway.METHODS:Proteins linked to Scu and ischaemic stroke-induced neuronal apoptosis were identified using the Swiss Tar-get Prediction,PharmMapper,OMIM,and GeneCards databases.Intersecting targets were identified through Venn analy-sis.Protein-protein interaction networks were visualised utilising Cytoscape software,and principal targets were identi-fied.Enrichment analyses of GO functions and KEGG pathways were conducted utilising the Metascape database.Molecu-lar docking of Scu with core targets was performed utilising AutoDock Vina.The neuroprotective effects of Scu were as-sessed in MCAO rats using Zea Longa scoring and the suspension test.JAK2/STAT3 phosphorylation levels and apoptosis-related proteins[cleaved caspase-3(C-caspase-3),caspase-3,Bax,and Bcl-2]were assessed using Western blot and im-munofluorescence staining.The JAK2-specific inhibitor AG490 was employed to further investigate the role of the JAK2/STAT3 signaling pathway.RESULTS:Network pharmacology analysis revealed 832 shared targets,with pathways en-riched in tumor-associated pathways,the JAK/STAT signalling pathway,and the HIF-1 signalling pathway.Molecular docking revealed robust binding affinities of Scu with the ten principal targets.Behavioural assessments utilising Zea Lon-ga scoring and the suspension test demonstrated that Scu markedly enhanced neurological recovery in MCAO rats.Western blot and immunofluorescence analyses demonstrated that phosphorylation levels of JAK2 and STAT3,along with the ex-pression of C-caspase-3,Bax,and Bcl-2,were markedly elevated in the MCAO group relative to the sham group(P<0.05).Post Scu treatment,phosphorylation levels of JAK2 and STAT3,along with C-caspase-3 and Bax expression,were markedly diminished,whereas Bcl-2 expression and fluorescence intensity were substantially increased(P<0.05).In the combined AG490 and Scu treatment group(MCAO+Scu+AG490),the phosphorylation levels of JAK2 and STAT3,as well as the expression of C-caspase-3 and Bax,exhibited no significant difference when compared to the Scu-alone group(P>0.05).Bcl-2 expression and fluorescence intensity were markedly reduced in the combined AG490 and Scu treatment group relative to the Scu-alone group(P<0.05).CONCLUSION:Scu seems to provide neuroprotection in ischaemic stroke by reducing neuronal apoptosis through the inhibition of the JAK2/STAT3 signalling pathway.

Developing and identifying effective medications and targets for treating hepatic fibrosis is an urgent priority. Our previous research demonstrated the efficacy of artesunate (ART) in alleviating liver fibrosis by eliminating activated hepatic stellate cells (HSCs). However, the underlying mechanism remains unclear despite these findings. Notably, endocytic adaptor protein (NUMB) has significant implications for treating hepatic diseases, but current research primarily focuses on liver regeneration and hepatocellular carcinoma. The precise function of NUMB in liver fibrosis, particularly its ability to regulate HSCs, requires further investigation. This study aims to elucidate the role of NUMB in the anti-hepatic fibrosis action of ART in HSCs. We observed that the expression level of NUMB significantly decreased in activated HSCs compared to quiescent HSCs, exhibiting a negative correlation with the progression of liver fibrosis. Additionally, ART induced senescence in activated HSCs through the NUMB/P53 tumor suppressor (P53) axis. We identified NUMB as a crucial regulator of senescence in activated HSCs and as a mediator of ART in determining cell fate. This research examines the specific target of ART in eliminating activated HSCs, providing both theoretical and experimental evidence for the treatment of liver fibrosis.
Hepatic Stellate Cells/cytology* ; Liver Cirrhosis/genetics* ; Artesunate/pharmacology* ; Cellular Senescence/drug effects* ; Membrane Proteins/genetics* ; Animals ; Humans ; Nerve Tissue Proteins/genetics* ; Tumor Suppressor Protein p53/genetics* ; Male ; Mice

Inflammatory bowel disease (IBD) is a chronic and recurrent intestinal inflammatory disease, which not only affects the digestive tract, but also involves extraintestinal organs and tissues such as joints and eyes, and ultimately endangers human health and affects the quality of life of patients. With the development of information technology, there is an increasing application of digital therapeutics in the management of IBD. This article aims to comprehensively analyze the characteristics, use, and challenges of digital therapeutics in the management of IBD, and explore its potential to improve treatment adherence, disease surveillance, and improve patients' quality of life.

Objective To develop and validate an automated organoid image segmentation approach based on deep learning for addressing the issues of high misidentification rate,blurred boundary and poor generalization in current organoid segmentation,thereby facilitating researchers to monitor and analyze organoid growth more efficiently.Methods The wavelet scattering coefficient matrix and capsule convolution module were integrated into the U-Net architecture to construct the organoid image segmentation model OrgCapsU-Net which was trained and evaluated on 3 organoid image datasets from different tissue sources.Results Compared with current mainstream segmentation algorithms,OrgCapsU-Net could better distinguish organoid and impurity,and lead to smoother segmentation boundaries,achieving superior performance across 4 evaluation metrics on 3 datasets.Conclusion OrgCapsU-Net delivers excellent segmentation performance and can be applied to organoids from various tissue sources,showing strong potential for applications in the in vitro model establishment,high-throughput drug screening,and personalized medicine.

Objective To explore the circRNA expression level in the urine of patients with lupus nephritis(LN),to construct a diagnostic model for LN,and to evaluate and verify its diagnostic efficacy.Methods A total of 120 patients with LN admitted from January 2022 to January 2024 were selected as the observation group and divided into the training group(n=84)and the validation group(n=36)at a ratio of 7:3.Another 100 healthy individuals who underwent physical examination were selected as the control group.The expression levels of circRNA-0001445,circRNA-002059,hsa-circ-0007385 and hsa-circ-0000006 in urine specimens of patients in the training group and the control group were detected by gene sequencing.Multivariate Logistic regression analysis was used to construct a diagnostic model for LN based on the urinary circRNA expression level.The diagnostic value of individual indicators and combined predictive models were evaluated by receiver operating characteristic(ROC)curve analysis,and then the predictive efficacy of the model was verified by the validation group.Results The expression levels of circRNA-0001445,circRNA-002059,hsa-circ-0007385 and hsa-circ-0000006 in the urine of patients in the training group were all higher than those of the control group(P<0.01).Multivariate Logistic regression analysis found that The expression levels of circRNA-0001445(OR=1.094),circRNA-002059(OR=1.040),hsa-circ-0007385(OR=1.033),and hsa-circ-0000006(OR=1.130)in theurine were independent factor for the diagnosis of LN(P<0.01).ROC curve analysis showed that the areas under the curve of combined model constructed based on the circRNA expression level in the urine were 0.985 and 0.911 in the training group and the validation group,respectively,with sensitivities of 95.00%and 91.67%,and specificities of 99.00%and 89.00%,all of which were higher than the diagnostic efficacy of a single urinary circRNA expression level.Conclusion The diagnostic model of LN constructed based on the expression level of circRNA in the urine has a high diagnostic efficacy,which has been confirmed by internal tests and may provide strong support for clinicians in the early diagnosis of LN.

Objective:To screen the Alzheimer's disease(AD)-related genes and construct its diagnostic model using bioinformatics technology and machine learning(ML)algorithms,to discuss the immunological characteristics of AD patients,and to provide novel biomarkers for AD diagnosis.Methods:The AD-related gene expression dataset GSE125583 was downloaded from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified through differential analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses were performed to explore the biological functions and signaling pathways of DEGs.A protein-protein interaction(PPI)network was constructed,and hub genes were screened using Cytoscape software combined with three ML algorithms:Least Absolute Shrinkage and Selection Operator(LASSO),eXtreme Gradient Boosting(XGBoost),and Random Forest(RF).The screened hub genes were utilized to build an AD diagnostic model via RF,followed by feature importance ranking.The model's efficacy and key genes were evaluated using a test set.Single-sample gene set enrichment analysis(ssGSEA)was used for immune cell infiltration analysis between AD group and control group.Results:Differential analysis identified 1 287 DEGs.The GO functional enrichment analysis results revealed that DEGs were primarily involved in biological functions related to neural signaling,synapses,and vesicles.KEGG signaling pathway enrichment analysis indicated significant enrichment of DEGs in ion transport,neurotransmitter,and ligand-gated channel pathways.Nine overlapping hub genes were screened by the three ML algorithms.In the AD diagnostic model,the top four key genes with highest diagnostic performance were adenylate cyclase-activating polypeptide 1(ADCYAP1),brain-derived neurotrophic factor(BDNF),platelet-derived growth factor receptor β(PDGFRB),and C-X-C motif chemokine receptor 4(CXCR4),with corresponding area under the curve(AUC)values of 0.852,0.795,0.820,and 0.756,respectively.The model achieved an AUC of 0.828,accuracy of 81.25%,sensitivity of 84.40%,and specificity of 71.43%.The immune cell infiltration analysis results demonstrated higher infiltration of macrophages,monocytes,natural killer(NK)cells,and lymphocytes in AD tissue.Among these,NK/natural killer T(NKT)cells and plasmacytoid dendritic cells showed significant correlations with the four key genes(P<0.05).Conclusion:The feature genes screened based on bioinformatics and ML exhibit diagnostic potential for AD.Genes such as ADCYAP1 may serve as potential biomarkers for AD diagnosis,offering significant implications for early prevention and treatment.

One of the basic questions in the aging field is whether there is a fundamental difference between the aging of lower invertebrates and mammals. A major difference between the lower invertebrates and mammals is the abundancy of noncoding RNAs, most of which are not conserved. We have previously identified a noncoding RNA Terc-53 that is derived from the RNA component of telomerase Terc. To study its physiological functions, we generated two transgenic mouse models overexpressing the RNA in wild-type and early-aging Terc-/- backgrounds. Terc-53 mice showed age-related cognition decline and shortened life span, even though no developmental defects or physiological abnormality at an early age was observed, indicating its involvement in normal aging of mammals. Subsequent mechanistic study identified hyaluronan-mediated motility receptor (Hmmr) as the main effector of Terc-53. Terc-53 mediates the degradation of Hmmr, leading to an increase of inflammation in the affected tissues, accelerating organismal aging. adeno-associated virus delivered supplementation of Hmmr in the hippocampus reversed the cognition decline in Terc-53 transgenic mice. Neither Terc-53 nor Hmmr has homologs in C. elegans. Neither do arthropods express hyaluronan. These findings demonstrate the complexity of aging in mammals and open new paths for exploring noncoding RNA and Hmmr as means of treating age-related physical debilities and improving healthspan.
Animals ; Mice ; RNA, Untranslated/metabolism* ; Aging/genetics* ; Mice, Transgenic ; Telomerase/metabolism* ; RNA/genetics* ; Hippocampus/metabolism* ; Humans ; Mice, Inbred C57BL

Ursodeoxycholic acid (UDCA) is a naturally occurring, low-toxicity, and hydrophilic bile acid (BA) in the human body that is converted by intestinal flora using primary BA. Solute carrier family 7 member 11 (SLC7A11) functions to uptake extracellular cystine in exchange for glutamate, and is highly expressed in a variety of human cancers. Retroperitoneal liposarcoma (RLPS) refers to liposarcoma originating from the retroperitoneal area. Lipidomics analysis revealed that UDCA was one of the most significantly downregulated metabolites in sera of RLPS patients compared with healthy subjects. The augmentation of UDCA concentration (≥25 μg/mL) demonstrated a suppressive effect on the proliferation of liposarcoma cells. [¹⁵N₂]-cystine and [¹³C₅]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione (GSH) synthesis. Mechanistically, UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis, leading to reactive oxygen species (ROS) accumulation and mitochondrial oxidative damage. Furthermore, UDCA can promote the anti-cancer effects of ferroptosis inducers (Erastin, RSL3), the murine double minute 2 (MDM2) inhibitors (Nutlin 3a, RG7112), cyclin dependent kinase 4 (CDK4) inhibitor (Abemaciclib), and glutaminase inhibitor (CB839). Together, UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity, and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA. More importantly, in combination with other antitumor chemotherapy or physiotherapy treatments, UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.