Objective To explore the safety of Yttrium-90 resin microsphere selective internal radiation therapy (⁹⁰Y-SIRT) on malignant liver tumors. Methods A retrospective analysis was conducted on 64 patients with malignant liver tumors who underwent ⁹⁰Y-SIRT from February 2023 to November 2024 at Weifang People’s Hospital. The clinical characteristics of the patients and the occurrence of adverse reactions after treatment were analyzed to assess the safety of ⁹⁰Y-SIRT. Results Among the 64 patients, there were 52 males (81.25%) and 12 females (18.75%); the average age was (56.29±11.08) years. Seven patients (10.94%) had tumors with maximum diameter of less than 5 cm, 38 patients (59.38%) had tumors with maximum diameter of 5-10 cm, and 19 patients (29.68%) had tumors with maximum diameter of greater than 10 cm. There were 47 cases (73.44%) of solitary lesions and 17 cases (26.56%) of multiple lesions; 53 cases (82.81%) were primary liver cancers and 11 cases (17.19%) were metastatic liver cancers. Of the 64 patients, 63 successfully completed the Technetium-99m macroaggregated albumin (^99mTc-MAA) perfusion test and received the ⁹⁰Y-SIRT; one patient received ⁹⁰Y-SIRT after the second ^99mTc-MAA perfusion test due to a work error. The most common adverse reactions included grade 1 alanine aminotransferase (ALT) elevation in 26 cases (40.62%) and grade 2 in 2 cases (9.37%), grade 1 aspartate aminotransferase (AST) elevation in 27 cases (42.18%) and grade 2 in 7 cases (10.93%); grade 1 nausea in 17 cases (26.56%) and grade 2 in 6 cases (9.37%); grade 1 abdominal pain in 12 cases (18.75%), grade 2 in 5 cases (7.81%), and grade 3 in 1 case (1.56%); grade 1 vomiting in 11 cases (17.18%), grade 2 in 5 cases (7.81%), and grade 3 in 1 case (1.56%). Conclusion The adverse reactions of ⁹⁰Y-SIRT for treating malignant liver tumors are mild, indicating good safety.

ObjectiveNeuroinflammation plays a crucial role in both the onset and progression of ischemic stroke, exerting a significant impact on the recovery of the central nervous system. Excessive neuroinflammation can lead to secondary neuronal damage, further exacerbating brain injury and impairing functional recovery. As a result, effectively modulating and reducing neuroinflammation in the brain has become a key therapeutic strategy for improving outcomes in ischemic stroke patients. Among various approaches, targeting immune regulation to control inflammation has gained increasing attention. This study aims to investigate the role of in vitro induced regulatory T cells (Treg cells) in suppressing neuroinflammation after ischemic stroke, as well as their potential therapeutic effects. By exploring the mechanisms through which Tregs exert their immunomodulatory functions, this research is expected to provide new insights into stroke treatment strategies. MethodsNaive CD4⁺ T cells were isolated from mouse spleens using a negative selection method to ensure high purity, and then they were induced in vitro to differentiate into Treg cells by adding specific cytokines. The anti-inflammatory effects and therapeutic potential of Treg cells transplantation in a mouse model of ischemic stroke was evaluated. In the middle cerebral artery occlusion (MCAO) model, after Treg cells transplantation, their ability to successfully migrate to the infarcted brain region and their impact on neuroinflammation levels were examined. To further investigate the role of Treg cells in stroke recovery, the changes in cytokine expression and their effects on immune cell interactions was analyzed. Additionally, infarct size and behavioral scores were measured to assess the neuroprotective effects of Treg cells. By integrating multiple indicators, the comprehensive evaluation of potential benefits of Treg cells in the treatment of ischemic stroke was performed. ResultsTreg cells significantly regulated the expression levels of both pro-inflammatory and anti-inflammatory cytokines in vitro and in vivo, effectively balancing the immune response and suppressing excessive inflammation. Additionally, Treg cells inhibited the activation and activity of inflammatory cells, thereby reducing neuroinflammation. In the MCAO mouse model, Treg cells were observed to accumulate in the infarcted brain region, where they significantly reduced the infarct size, demonstrating their neuroprotective effects. Furthermore, Treg cell therapy notably improved behavioral scores, suggesting its role in promoting functional recovery, and increased the survival rate of ischemic stroke mice, highlighting its potential as a promising therapeutic strategy for stroke treatment. ConclusionIn vitro induced Treg cells can effectively suppress neuroinflammation caused by ischemic stroke, demonstrating promising clinical application potential. By regulating the balance between pro-inflammatory and anti-inflammatory cytokines, Treg cells can inhibit immune responses in the nervous system, thereby reducing neuronal damage. Additionally, they can modulate the immune microenvironment, suppress the activation of inflammatory cells, and promote tissue repair. The therapeutic effects of Treg cells also include enhancing post-stroke recovery, improving behavioral outcomes, and increasing the survival rate of ischemic stroke mice. With their ability to suppress neuroinflammation, Treg cell therapy provides a novel and effective strategy for the treatment of ischemic stroke, offering broad application prospects in clinical immunotherapy and regenerative medicine.

Chronic atrophic gastritis （CAG）， a common digestive system disease， has an unclear pathogenesis. Currently， it is mostly believed to be related to Helicobacter pylori （Hp） infection， immune factors， dietary factors， bile reflux， long-term use of antibiotics and anti-inflammatory drugs， and other factors. Ferroptosis is a regulated cell death mechanism that is iron-dependent and characterized by disruption of iron metabolism and accumulation of lipid peroxides. More and more studies have found that ferroptosis is closely related to the onset of CAG. Professor LI Diangui， a master of traditional Chinese medicine， first proposed the turbid toxin theory， which holds that spleen deficiency and turbid toxin is the main pathogenic mechanism of CAG. Abnormal iron metabolism regulation is a prerequisite for the accumulation of turbid toxin in CAG， and ferroptosis is in accordance with the pathogenic mechanism （spleen deficiency and turbid toxin） of CAG. This article explores the pathological mechanism of spleen deficiency and turbid toxin in CAG from the perspectives of iron metabolism， oxidative stress， and lipid peroxidation， providing theoretical support of traditional Chinese medicine for the modern research on CAG. It enriches the modern scientific connotation of the turbid toxicity theory and provides new ideas and breakthrough points for the clinical treatment of CAG.

Chronic atrophic gastritis （CAG）， a common digestive system disease， has an unclear pathogenesis. Currently， it is mostly believed to be related to Helicobacter pylori （Hp） infection， immune factors， dietary factors， bile reflux， long-term use of antibiotics and anti-inflammatory drugs， and other factors. Ferroptosis is a regulated cell death mechanism that is iron-dependent and characterized by disruption of iron metabolism and accumulation of lipid peroxides. More and more studies have found that ferroptosis is closely related to the onset of CAG. Professor LI Diangui， a master of traditional Chinese medicine， first proposed the turbid toxin theory， which holds that spleen deficiency and turbid toxin is the main pathogenic mechanism of CAG. Abnormal iron metabolism regulation is a prerequisite for the accumulation of turbid toxin in CAG， and ferroptosis is in accordance with the pathogenic mechanism （spleen deficiency and turbid toxin） of CAG. This article explores the pathological mechanism of spleen deficiency and turbid toxin in CAG from the perspectives of iron metabolism， oxidative stress， and lipid peroxidation， providing theoretical support of traditional Chinese medicine for the modern research on CAG. It enriches the modern scientific connotation of the turbid toxicity theory and provides new ideas and breakthrough points for the clinical treatment of CAG.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

BackgroundGraduate students frequently face life events， many of which may adversely affect their mental well-being. However， the interaction between life events and the development of depression， anxiety， and somatic symptoms remains unclear. ObjectiveTo explore the relationship between life events and the development of depressive， anxiety and somatic symptoms in graduate students， thereby informing prevention strategies for these conditions. MethodsA sample of 6 722 newly enrolled graduate students at a comprehensive university in Southwest China from September to November 2018 was selected. The assessment was conducted using the Adolescent Self-rating Life Events Checklist （ASLEC）， the 7-item Generalized Anxiety Disorder scale-7 item （GAD-7）， the Patient Health Questionnaire Depression Scale-9 item （PHQ-9）， and the Patient Health Questionnaire-15 （PHQ-15）. Network analysis was implemented by using the bootnet and qgraph packages in the R software （version 4.2.3）， with centrality indices calculated to identify core and bridge symptoms within the network. ResultsThe study encompassed a total of 6 171 graduate students， representing 91.80% of the target population. The prevalence rates of anxiety， depressive， and somatic symptoms among graduate students were 12.59% （777/6 171）， 16.63% （1 026/6 171）， and 27.66% （1 707/6 171）， respectively. Network analysis revealed that 'academic stress' was the core symptom with the highest strength and expected influence （both values=1.207）， while 'feeling down， depressed， or hopeless' was the bridge symptom with the highest bridge strength and bridge expected influence （both values=0.454）. There was no significant difference in global network strength and edge weight between women and men （P>0.05）. ConclusionAcademic stress， emerging as the core symptom， assumes a dominant position within the symptom network and exhibits strong interactions with other negative affective states. There was no gender difference in the network structure.