BackgroundHepatocellular carcinoma (HCC) is the most prevalent primary hepatic malignancy worldwide and a leading cause of cancer-related mortality. Transarterial chemoembolization (TACE) is the standard of care for Barcelona Clinic Liver Cancer (BCLC) intermediate-stage HCC; however, treatment response varies considerably among individuals, and a substantial proportion of patients develop TACE refractoriness.ObjectiveThis review systematically examines the current applications of artificial intelligence (AI) in TACE for HCC, encompassing treatment response prediction, survival prognostication, refractoriness prediction, and the underlying molecular mechanisms, while critically appraising methodological quality of the existing literature and delineating TACE-specific future directions.MethodsWe conducted a comprehensive literature search of PubMed, Embase, Web of Science, Scopus, and Google Scholar for studies published through 2025 that investigated AI, machine learning (ML), or deep learning (DL) in TACE response prediction, prognostic stratification, and refractoriness assessment. Included studies were appraised against PROBAST, IBSI, TRIPOD+AI, and CLAIM frameworks.ResultsAI models based on radiomics and DL demonstrated high discriminative performance for predicting TACE outcomes, with meta-analytic area under the receiver operating characteristic curve (AUROC) values ranging from 0.81 to 0.92. Combined clinico-radiological models—incorporating albumin–bilirubin (ALBI) grade, BCLC stage, alpha-fetoprotein (AFP) level, tumor diameter, distribution, and peritumoral arterial-phase enhancement—consistently outperformed single-source models. Convolutional neural networks (CNNs) and gradient-boosting, support-vector-machine, and random-forest models were the consistently top-performing algorithms. However, methodological quality was uneven: most studies showed high or unclear PROBAST risk of bias in the analysis domain, IBSI-compliant feature reporting and public code release were rare, and the generalization gap between internal and external validation cohorts averaged 0.08–0.15 AUROC.ConclusionsAI offers a powerful toolkit for individualized TACE decision-making, with the potential to shift clinical practice from experience-driven to data-driven precision therapy. Nevertheless, critical challenges remain—including insufficient external validation, limited sample sizes, geographic bias, low standardization, and inadequate interpretability—which together necessitate large-scale, multicenter, prospective studies adhering to harmonized reporting standards.

Chronic kidney disease (CKD) often progresses to renal fibrosis, leading to irreversible kidney damage and a decline in renal function. This study explores the therapeutic effects of ultrasound-guided mesenchymal stem cells (MSCs) infusion in CKD, focusing on the regulatory mechanism in macrophage polarization and fibrosis regulation. CKD models were established in Sprague–Dawley rats via intravenous injection of doxorubicin, and MSCs infusion treatment was performed on the renal parenchyma of the model rats under ultrasound guidance. Meanwhile, transforming growth factor beta 1 (TGF-β1)-stimulated HK-2 cells or THP1-derived macrophage were co-cultured with MSCs to establish an in vitro cellular model. RNA sequencing was employed to identify differentially expressed genes. Furthermore, western blotting, immunofluorescence, and ELISA, were carried out to assess fibrosis, inflammation, and macrophage polarization. Ultrasound-guided MSCs infusion into the renal parenchyma effectively alleviated the pathological damage and fibrosis, and promoted M2 macrophage polarization in the renal tissues of CKD model rats. In vitro, co-culture with MSCs also significantly promoted M2 polarization of macrophages, reduced the levels of pro-inflammatory cytokines, and decreased TGF-β1-induced fibrosis in HK-2 cells. Notably, MSCs treatment significantly downregulated serum and glucocorticoid-regulated kinase 1 (SGK1) expression in CKD model rats or cells, while overexpression of SGK1 reversed MSCs-induced M2 macrophage polarization. Mechanistically, MSCs downregulated SGK1 expression to inactivate the downstream nuclear factor kappa-B pathway, which plays a role in inflammation and fibrosis. Ultrasound-guided MSCs injection into the renal parenchyma provides an efficient and precise therapeutic approach for CKD. MSCs promote macrophage M2 polarization and exert anti-fibrotic effects in CKD by downregulating SGK1 expression.

To identify the optimal transplantation route for enhancing homing of mesenchymal stem cells (MSCs) to the kidney, thereby ameliorating rat Adriamycin nephropathy (AN). In vivo animal imaging revealed that ultrasound-guided intrarenal-arterial transplantation of GFP-MSCs markedly increased the number of MSCs homing to the kidney compared with the intravenous injection (IV) and renal parenchyma (RP) routes. Multimodal ultrasonography revealed that the renal artery (RA) group exhibited reduced renal parenchymal echogenicity and significantly increased cortical microvascular perfusion compared to the Adriamycin (ADR), IV, and RP groups. Hematoxylin and eosin (H&E) staining, Masson staining, and electron microscopy revealed that the RA group had an enlarged glomerular volume, diminished renal interstitial fibrosis, and attenuated mitochondrial damage compared to the ADR, IV, and RP groups. Western blotting, qRT-PCR and immunohistochemistry further indicated that the RA group mitigated rat AN by downregulating the JAK2, AKT1, and STAT3 signaling pathways more effectively than the ADR, IV, and RP groups did. The above findings indicate that under ultrasound guidance, MSCs transplanted via the renal artery can ameliorate AN-induced renal injury by acting on the JAK/STAT signaling pathway.

[This corrects the article DOI: 10.3389/fonc.2025.1634715.].

BackgroundHepatocellular carcinoma (HCC) ranks among the most prevalent tumors globally. Transcatheter arterial chemoembolization (TACE) serves as the standard treatment for intermediate and advanced stages of HCC. However, patient responses to TACE vary significantly. This study aims to assess the predictive value of combining CT radiomics with inflammatory composite indicators for evaluating the efficacy of initial TACE in HCC patients.MethodsWe included 175 patients with pathologically confirmed HCC, categorizing them into a good efficacy group (95 cases) and a poor efficacy group (80 cases). We compared radiomics features and inflammatory composite indicators between these groups. To identify independent risk factors for predicting TACE efficacy, we performed multivariate Logistic regression analysis. We developed a radiomics prediction model and a clinical prediction model based on inflammatory composite indicators. A combined prediction model was created using selected inflammatory composite indicators and radiomics features, and visualized with a nomogram. We assessed the model's predictive performance using the receiver operating characteristic (ROC) curve, and its stability and authenticity through 1,000 bootstrap resampling. The clinical benefit was evaluated using a decision curve analysis (DCA) curve.ResultsThe multivariate logistic regression analysis revealed that platelet-to-lymphocyte ratio (PLR), maximum tumor diameter, and Radiomics score (Radscore) were independent risk factors for predicting the efficacy of the first TACE in HCC. The clinical model, based on the inflammatory composite index, achieved an AUC of 66.6 for efficacy prediction. The radiomics model, developed from radiomics features, demonstrated an AUC of 76.1. Notably, the combined prediction model, integrating both radiomics features and the inflammatory composite index, achieved an AUC of 80.4.ConclusionCT radiomics, when combined with composite inflammatory indicators, demonstrated high predictive efficacy for the first TACE treatment outcomes in HCC patients. The developed visual nomogram aids clinicians in creating personalized pre-operative treatment plans for these patients.

Diabetic kidney disease (DKD) is the primary global cause of end-stage renal disease. However, the aging-related gene networks driving its progression remain unclear. In this study, we integrated bioinformatics and experiments to screen for age-related hub genes in DKD and explore their diagnostic and therapeutic values. Transcriptomic datasets and aging-related gene databases were combined to obtain candidate differentially expressed genes enriched in the PI3K–Akt and JAK–STAT pathways. LASSO and Random Forest algorithms were applied to screen core hub genes, and a logistic diagnostic model was constructed for verification. Single-cell sequencing was utilized to clarify the main cell populations expressing key genes. Molecular docking and dynamics simulations were performed to analyze the binding stability of candidate drugs and target genes. High-glucose cell models and DKD rat models were established, and RT-qPCR, western blot, and pathological staining assays were used to validate the expression changes of key genes and the regulatory effects of drugs. Nine hub genes (CLU, EGF, SLC16A7, MYC, RPA1, RB1, APOC3, SYK, and NR3C1) were finally screened out. The constructed logistic diagnostic model achieved an AUC of 0.881 in external verification. Glomerular endothelial cells and mesangial cells were identified as the main cell populations expressing these hub genes. Molecular simulation results confirmed the stable binding of fostamatinib to SYK and selexipag to APOC3. In vivo and in vitro validation experiments demonstrated that the two candidate agents could suppress NF-κB pathway activation, inflammatory cytokine release, and cellular senescence. In this study, we identified age-related hub genes, constructed a reliable diagnostic signature, and suggested SYK–fostamatinib and APOC3–selexipag as potential drug-repurposing candidates for DKD, which requires further experimental and clinical validation.

Background Diabetic kidney disease (DKD) and Parkinson’s disease (PD) affect different organs but share epidemiological associations and innate immune abnormalities. The extent and cellular basis of reproducible cross-disease transcriptomic convergence remain uncertain. Methods Two DKD glomerular and three PD substantia nigra microarray cohorts were analyzed independently and combined using disease-specific and cross-disease meta-analysis. Independent DKD single-cell RNA-sequencing, PD single-nucleus RNA-sequencing, and spatial transcriptomic datasets were used for cell-type localization and donor- or sample-level analyses. CellChat, Monocle2, scTenifoldKnk, and previously generated UNAGI-compatible outputs were used to evaluate predicted intercellular communication, transcriptional-state continua, in-silico IRF8 perturbation, and compound prioritization. Threshold, leave-one-cohort-out, root-orientation, downsampling, and statistical-unit sensitivity analyses were performed where applicable. Results The original nominal-threshold intersection of 36 genes was not retained after cohort-wise multiple-testing correction. Genome-wide overlap between DKD and PD was limited in the expanded analysis. IRF8 and TLR7 showed positive effect directions in both diseases but did not pass cross-disease false-discovery-rate correction and were therefore treated as exploratory candidates. Donor-level analyses did not detect statistically significant increases in broad myeloid-lineage proportions, although the confidence intervals did not establish equivalence. Selected DKD CCL and TNF interactions were retained in both of two targeted balanced-downsampling iterations, whereas the PD TGF-β signal was sampling-sensitive. Monocle2 identified branched and partially overlapping transcriptional-state continua. Spatial analyses provided marker-supported localization evidence without treating individual spatial observations as independent replicates. In-silico IRF8 deletion predicted regulatory-network changes but was not experimentally validated. NVP-AUY922 was the highest-ranked cross-disease computational candidate, but its association was not significant after correction across the matched compound universe. Conclusions DKD and PD show limited genome-wide overlap but partial convergence of myeloid- and microglia-enriched inflammatory signals associated with IRF8 and TLR7. These findings provide testable hypotheses rather than evidence of a conserved causal pathway or validated cross-disease treatment.

BACKGROUND AND PURPOSE:Renal tubulointerstitial fibrosis (RTF) is an irreversible pathological change that occurs during the end-stage of chronic kidney disease. As a promising new approach, stem cell therapy offers the potential to reverse or ameliorate RTF by promoting cell proliferation in target tissues or through the secretion of relevant substances. However, mesenchymal stem cells (MSCs) that home to renal tissues have reduced proliferation and vitality and a short retention time in the kidneys, which are key factors affecting therapeutic outcomes. Additionally, in vivo real-time tracking of MSCs is not well developed, which significantly obscures our understanding of their potential mechanisms. Nanobubbles (NBs), used as a non-invasive method for auxiliary drug or gene delivery, possess excellent ultrasound imaging capabilities and enhance the penetration of drugs or genes into target tissues under the effect of ultrasound-targeted microbubble destruction (UTMD). Therefore, in this study, aimed to synthesize NBs(stromal cell-derived factor 1 [SDF-1])-MSCs. METHODS:We synthesized NBs containing SDF-1 and harvested MSCs from the bone marrow of Sprague-Dawley rats. Subsequently, NBs(SDF-1) were co-cultured with MSCs to produce SDF-1-loaded nanobubble-tagged MSCs. The NBs(SDF-1)-MSCs were injected into adult male rats to investigate their potential for renal visualization and tracking and to assess their efficacy in promoting MSCs homing to the kidneys for RTF treatment under UTMD. We evaluated the effects of NBs(SDF-1)-MSCs on fluorescence ultrasound dual-modality imaging, as well as their ability to enhance MSCs proliferation, vitality, and retention time in vitro and in vivo. Additionally, we explored the therapeutic effects of NBs(SDF-1)-MSCs in rats treated with doxorubicin. RESULTS:Using in vivo animal models, dual-modality ultrasound imaging, and immunofluorescence testing, we demonstrated that NBs(SDF-1)-MSCs could be tracked in the kidneys for up to 7 days. Protein blotting, quantitative real-time PCR, immunofluorescence, and immunohistochemistry analyses revealed that ultrasound targeted microbubble destruction greatly enhanced the homing of these stem cells to the kidneys, ameliorating chronic kidney disease by mitigating renal tubular fibrosis via the Tumor necrosis factor-β 1(TGF-β)/B-cell lymphoma/leukemia 2 (Bcl2) signaling pathway. CONCLUSION:In this study, we developed a method for in vivo real-time tracking of MSCs loaded with NBs(SDF-1) using dual-modality fluorescence ultrasound imaging, highlighting the therapeutic potential of stem cells and presenting a new therapeutic strategy for treating RTF.

OBJECTIVE:Post-resuscitation brain injury is a common sequela after cardiac arrest (CA). Increasing sirtuin1 (SIRT1) has been involved in neuroprotection in oxygen-glucose deprivation (OGD) neurons, and we investigated its mechanism in post-cardiopulmonary resuscitation (CPR) rat brain injury by mediating p65 deacetylation modification to mediate hippocampal neuronal ferroptosis. METHODS:Sprague-Dawley rat CA/CPR model was established and treated with Ad-SIRT1 and Ad-GFP adenovirus vectors, or Erastin. Rat postoperative neurological function, and cognitive and learning abilities were assessed by neurological deficit score and Morris water maze test. Hippocampal neuronal pathological changes and injury were evaluated by H&E and TUNEL staining. Serum brain injury biomarkers and hippocampal inflammatory factors and SIRT1 mRNA levels were determined by ELISA and RT-qPCR. OGD/reoxygenation (OGD/R) rat hippocampal neuron (H19-7) model was established. Cell viability and injury, nuclear factor-kappa B (NF-κB) p65 localization, iron content, and levels of glutathione, malondialdehyde, reactive oxygen species, SIRT1, Ac NF-κB p65 (Lys310), NF-κB p65, ACSL4, glutathione peroxidase 4 and SLC7A11 were measured. RESULTS:In CA/CPR rats, SIRT1 was down-regulated, and SIRT1 overexpression alleviated cerebral injury. SIRT1 overexpression inhibited OGD/R-induced H19-7 cell ferroptosis to ameliorate cell injury, and inactivated the NF-κB pathway by reducing p65 acetylation to hinder its entry into the nucleus. Inactivating the NF-κB pathway reduced OGD/R-induced ferroptosis and alleviated cell injury. SIRT1 alleviated cerebral injury by mediating p65 deacetylation to inhibit hippocampal neuronal ferroptosis mediated by the NF-κB pathway. CONCLUSIONS:SIRT1 inhibited the NF-κB signaling pathway-mediated hippocampal neuronal ferroptosis by mediating p65 deacetylation modification, thereby alleviating brain injury in CA/CPR rats.

OBJECTIVE:Ulcerative colitis (UC), a chronic inflammatory bowel disease, continues to pose substantial challenges in both diagnosis and treatment. The aryl hydrocarbon receptor (AhR) plays a pivotal role in intestinal immune regulation; however, its core regulatory network in the progression of UC remains largely undefined. This study aims to identify core UC-related genes associated with AhR and to validate their expression in dextran sulfate sodium (DSS)-induced murine models, thereby elucidating potential mechanisms underlying UC progression. METHODS:Using the GSE75214 and GSE87466 datasets from the Gene Expression Omnibus (GEO) database, immune cell infiltration was quantified via the CIBERSORT algorithm. Candidate genes were identified through differential expression analysis, weighted gene co-expression network analysis (WGCNA) module selection, and construction of an AhR co-expression network. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed, followed by construction of a protein-protein interaction (PPI) network using STRING and application of two machine learning algorithms to identify AhR-associated hub genes. Finally, the expression of key genes was validated in DSS-induced UC mouse models using real-time quantitative real-time quantitative polymerase chain reaction (RT-qPCR). RESULTS:A total of nine AHR-related shared genes were identified, which were significantly enriched in immune response, amino acid metabolism, and oxidative stress pathways. Through integration of the PPI network and machine learning approaches, three central hub genes (PPARG, IL1B, and IDO1) were identified. Immune infiltration analysis revealed pronounced immune dysregulation during the progression of UC, which may contribute to disease development. Animal experiments confirmed the expression of these three key genes in colonic tissues, and hematoxylin-eosin (H&E) staining revealed extensive infiltration of inflammatory cells, consistent with the bioinformatics findings. CONCLUSION:PPARG, IL1B, and IDO1 were identified as potential key genes closely associated with AHR, suggesting their possible involvement in modulating AhR signaling in UC, thereby offering a theoretical basis for disease diagnosis and therapeutic strategies.

BackgroundAggressive fibromatosis is a rare and aggressive soft tissue tumor. The pathologic histomorphology is varied and characterized by fibroblast and myofibroblast differentiation. Aggressive fibromatosis can be classified into extra-abdominal, abdominal wall, and intra-abdominal types. The abdominal wall type is the most common, while originating from the pancreatic region is extremely rare. Therefore, we report a case of a patient with a diagnosis of giant cystic solid aggressive fibromatosis of the pancreas.Case summaryThe patient was a 39-year-old woman who was admitted to the hospital because of left upper abdominal pain that persisted for 20 days. She was in relatively good health with no history of previous illnesses. No additional abnormal manifestations were noted on physical examination. Laparoscopic pancreatic body and tail combined splenectomy was performed under general anesthesia. The postoperative pathologic diagnosis was pancreatic aggressive fibroma. No disease recurrence was observed during the postoperative follow-up period.ConclusionThe primary pancreatic aggressive fibroma is very rare. The clinical presentation lacks specificity, and imaging findings are not quite typical. The definitive diagnosis relies on postoperative pathology and immunohistochemistry. Complete surgical resection is the treatment of choice when possible. Due to its aggressive behavior, regular follow-up is required.

RATIONALE AND OBJECTIVES:Researchers have delved into noninvasive diagnostic methods of renal fibrosis (RF) in chronic kidney disease, including ultrasound (US), magnetic resonance imaging (MRI), and radiomics. However, the value of these diagnostic methods in the noninvasive diagnosis of RF remains contentious. Consequently, the present study aimed to systematically delineate the accuracy of the noninvasive diagnosis of RF. MATERIALS AND METHODS:A systematic search covering PubMed, Embase, Cochrane Library, and Web of Science databases for all data available up to 28 July 2023 was conducted for eligible studies. RESULTS:We included 21 studies covering 4885 participants. Among them, nine studies utilized US as a noninvasive diagnostic method, eight studies used MRI, and four articles employed radiomics. The sensitivity and specificity of US for detecting RF were 0.81 (95% CI: 0.76-0.86) and 0.79 (95% CI: 0.72-0.84). The sensitivity and specificity of MRI were 0.77 (95% CI: 0.70-0.83) and 0.92 (95% CI: 0.85-0.96). The sensitivity and specificity of radiomics were 0.69 (95% CI: 0.59-0.77) and 0.78 (95% CI: 0.68-0.85). CONCLUSIONS:The current early noninvasive diagnostic methods for RF include US, MRI, and radiomics. However, this study demonstrates that US has a higher sensitivity for the detection of RF compared to MRI. Compared to US, radiomics studies based on US did not show superior advantages. Therefore, challenges still exist in the current radiomics approaches for diagnosing RF, and further exploration of optimized artificial intelligence (AI) algorithms and technologies is needed.

Background: The dominant artery blood supply is a characteristic of hepatocellular carcinoma (HCC). However, it is not known whether the blood supply can predict the post-hepatectomy prognosis of patients with HCC. This retrospective study investigated the prognostic value of the portal venous and arterial blood supply estimated on triphasic liver CT (as a portal venous coefficient, PVC, and hepatic arterial coefficient, HAC, respectively) in patients with HCC following hepatectomy. Methods: HCC patients who were tested by triphasic liver CT 2 weeks before hepatectomy and received R0 hepatectomy at the Second Affiliated Hospital, Kunming Medical University between January 1, 2016 and December 31, 2020, were retrospectively screened. Their PVC and HAC, and other variables were analyzed for the prediction of overall survival (OS) and recurrence-free survival (RFS) using the least absolute shrinkage and selection operator and Cox proportional hazard regression models. Results: Four hundred and nineteen patients (53.2 +/- 10.6 years of age and 370 men) were evaluated. A shorter OS was independently associated with higher blood albumin and total bilirubin grade [hazard ratio (HR) 2.020, 95% confidence interval (CI) 1.534- 2.660], higher Barcelona Clinic Liver Cancer (BCLC) stage (HR 1.514, 95% CI 1.290- 1.777), PVC <= 0.386 (HR 1.628, 95% CI 1.149- 2.305), and HAC > 0.029 (HR 1.969, 95% CI 1.380- 2.809). A shorter RFS was independently associated with male (HR 1.652, 95% CI 1.005- 2.716), higher serum alpha-fetoprotein >= 400 ng/mL (HR 1.672, 95% CI 1.236- 2.263), higher BCLC stage (HR 1.516, 95% CI 1.300- 1.768), tumor PVC <= 0.386 (HR 1.641, 95% CI 1.198- 2.249), and tumor HAC > 0.029 (HR 1.455, 95% CI 1.060- 1.997). Conclusion: Tumor PVC or HAC before hepatectomy is valuable for independently predicting postoperative survival of HCC patients.

Background: The dominant artery blood supply is a characteristic of hepatocellular carcinoma (HCC). However, it is not known whether the blood supply can predict the post-hepatectomy prognosis of patients with HCC. This retrospective study investigated the prognostic value of the portal venous and arterial blood supply estimated on triphasic liver CT (as portal venous coefficient, PVC and hepatic arterial coefficient, HAC, respectively) in patients with HCC following hepatectomy. Methods: HCC patients who were tested by triphasic liver CT 2-weeks before hepatectomy and received R0 hepatectomy at the Yunnan Province Hepato-bilio-pancreatic Surgical Hospital between January 1, 2016 and December 31, 2020 were retrospectively screened. Their portal venous coefficient (PVC), hepatic arterial coefficient (HAC), and other variables were analyzed for the prediction of overall survival (OS) and recurrence-free survival (RFS) using the least absolute shrinkage and selection operator and COX’s proportional hazard regression models. Results: Four hundred and nineteen patients (53.2 ± 10.6 years of age and 370 men) were evaluated. A shorter OS was independently associated with higher blood albumin and total bilirubin grade [hazard ratio (HR) 2.020, 95% confidence interval (CI) 1.534-2.660], Barcelona Clinic Liver Cancer (BCLC) stage progression (HR 1.514, 95%CI 1.290-1.777), PVC ≤ 0.386 (HR 1.628, 95%CI 1.149-2.305), and HAC > 0.029 (HR 1.969, 95%CI 1.380-2.809). A shorter RFS was independently associated with male (HR 1.652, 95%CI 1.005-2.716), higher serum alpha-fetoprotein ≥ 400 ng/ml (HR 1.672, 95%CI 1.236-2.263), BCLC stage progression (HR 1.516, 95%CI 1.300-1.768), tumor PVC ≤ 0.386 (HR 1.641, 95%CI 1.198-2.249), and tumor HAC > 0.029 (HR 1.455, 95%CI 1.060-1.997). Conclusions: Tumor PVC or HAC before hepatectomy is valuable for independently predicting postoperative survival of HCC patients.

Objective: This review discusses recent experimental and clinical findings related to ferroptosis, with a focus on the role of MSCs. Therapeutic efficacy and current applications of MSC-based ferroptosis therapies are also discussed. Background: Ferroptosis is a type of programmed cell death that differs from apoptosis, necrosis, and autophagy; it involves iron metabolism and is related to the pathogenesis of many diseases, such as Parkinson’s disease, cancers, and liver diseases. In recent years, the use of mesenchymal stem cells (MSCs) and MSC-derived exosomes has become a trend in cell-free therapies. MSCs are a heterogeneous cell population isolated from a diverse range of human tissues that exhibit immunomodulatory functions, regulate cell growth, and repair damaged tissues. In addition, accumulating evidence indicates that MSC-derived exosomes play an important role, mainly by carrying a variety of bioactive substances that affect recipient cells. The potential mechanism by which MSC-derived exosomes mediate the effects of MSCs on ferroptosis has been previously demonstrated. This review provides the first overview of the current knowledge on ferroptosis, MSCs, and MSC-derived exosomes and highlights the potential application of MSCs exosomes in the treatment of ferroptotic conditions. It summarizes their mechanisms of action and techniques for enhancing MSC functionality. Results obtained from a large number of experimental studies revealed that both local and systemic administration of MSCs effectively suppressed ferroptosis in injured hepatocytes, neurons, cardiomyocytes, and nucleus pulposus cells and promoted the survival and regeneration of injured organs. Methods: We reviewed the role of ferroptosis in related tissues and organs, focusing on its characteristics in different diseases. Additionally, the effects of MSCs and MSC-derived exosomes on ferroptosis-related pathways in various organs were reviewed, and the mechanism of action was elucidated. MSCs were shown to improve the disease course by regulating ferroptosis.

Objective To investigate the effect of transplantation of bone marrow mesenchymal stem cells(BMSCs)via renal artery on programmed necrosis in chronic kidney disease(CKD)rats.Methods 16 SD rats were selected to establish CKD models and randomly divided into chronic kidney disease(B)group and BMSCs treatment(C)group.Another 16 healthy SD rats were randomly divided into normal control(N)group and medium control(A)group.Blood and urine were collected to test biochemical indicators at the first weekend after each group received the intervention.Rats were sacrificed in each group to collect kidneys.Hematoxylin-eosin(HE)and Masson staining were used to observe renal pathological changes.Immunohistochemical method was used to observe the ex-pression of renal programmed necrosis related protein.Western blot was used to analyze the expression level of programmed necrosis-re-lated proteins.Results Compared with group N and group A,the degree of kidney damage and fibrosis in group B and C were signifi-cantly increased(P<0.05);the expressions of RIP1 and RIP3 in group B and C were significantly increased(P<0.05),but after trea-ted by BMSCs,those in group C were significantly lower than those in group B(P<0.05);the expression of caspase8 in group B was significantly decreased and it was significantly increased after treated by BMSCs.The expressions of RIP1,RIP3,and p-MLKL in group B were significantly higher than those in the other groups(P<0.05),and the expressions of those in group C were significantly lower than those in group B after treated by BMSCs(P<0.05).Conclusions Transplantation of BMSCs via renal artery could inhibit the process of programmed necrosis and play an important therapeutic effect in chronic kidney disease.

患者女,23岁,心悸、呼吸困难、下肢麻木 4 h;既往体健.查体:双下肢触觉减退.实验室检查:糖类抗原 125(91.25 U/ml)、糖类抗原 724(13.35 U/ml)及神经元特异性烯醇化酶(262.22 ng/ml)升高.胸椎MRI:T2～T5段椎管内髓外硬膜外见2.4 cm×1.0 cm×4.7 cm呈膨胀性生长的梭形稍低T1WI、稍高T2WI信号病灶(图1A),边界清楚,压迫脊髓,弥散加权成像呈高信号(图1B);增强后病灶轻度不均匀强化(图1C),且多个胸椎椎体及附件信号强化不均;诊断:椎管内髓外硬膜外肿瘤,淋巴瘤并多发椎体转移可能.

Objectives To investigate different radiomics models based on single phase and the different phase combinations of radiomics features from 3D tri-phasic CT to distinguish RO from chRCC.Methods A total of 96 patients (30 RO and 66 chRCC) were enrolled in this study. Radiomics features were extracted from unenhanced phase (UP), corticomedullary phase (CMP), and nephrographic phase (NP) CT images. Feature selection was based on the least absolute shrinkage and selection operator regression (LASSO) method. The selected features were used to develop different radiomics models using logistic regression (LR) analysis, including model 1 (UP), model 2(CMP), model 3(NP), model 4(UP+CMP), model 5(UP+NP), model 6(CMP+NP), and model 7(UP+CMP+NP). The radiomics model demonstrating the highest discrimination performance was utilized to construct the combined model (model 8) with clinical factors. A nomogram based on the model 8 was established. To evaluate the diagnostic performance of the different models, the receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used. Delong's test was utilized to assess the statistical significance of the AUC improvement across the models.Results Among the seven radiomics models, model 7 exhibited the highest AUC of 0.84 (95% CI 0.69, 0.99), and model 7 demonstrated a significantly superior AUC compared to the other radiomics models (all P < 0.05). The AUC values of radiomics models based on two phases (model4, mode5, mode6) were greater than the models based on single phase (model1, mode2, mode3) (all P < 0.05). Model 3 illustrated the best performance of the three radiomics models based on single phase with an AUC of 0.76 (95% CI 0.57, 099). Model 6 illustrated the best performance of the three radiomics models based on two-phases combination with an AUC of 0.83 (0.66, 0.99). Model 8 achieved an AUC of 0.93 (95% CI 0.83, 1.00) which is higher than those all radiomics models.ConclusionRadiomics models based on combination of radiomics features from UP, CMP, and NP can be a useful and promising technique to differentiate RO from chRCC. Moreover, the model combining clinical factors and radiomics features showed better classification performance to distinguish them.