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.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

ObjectiveTo investigate the mechanism of Forsythiae Fructus-Lonicerae Japonicae Flos（FF） in the treatment of acute lung injury（ALI） by investigating the effects of FF on serum metabolomics of rats with ALI. MethodsThirty male SD rats were acclimated for 1 week， and 6 rats were randomly selected as the blank group. The other 24 rats were injected with lipopolysaccharide（LPS） solution by tracheal drip to establish an ALI model. After successful model establishment， the rats were randomly divided into the model group， the FF low-dose group（3.0 g·kg^-1）， the FF high-dose group（6.0 g·kg^-1）， and the dexamethasone group（5 mg·kg^-1）， with six rats in each group. The FF low- and high-dose groups and the dexamethasone group were received daily oral administration of the corresponding drug solution， and the blank group and the model group were gavaged with an equal amount of saline， treatment was administered continuously for 3 d. The pathological conditions of rat lung tissues were evaluated by hematoxylin-eosin（HE） staining， wet/dry mass ratio（W/D） of the lung tissues， and protein concentration in rat bronchoalveolar lavage fluid（BALF）. Metabolomic analysis of rat serum was performed by ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， combined with multivariate statistical analysis， the potential biomarkers of FF in treating ALI were screened by variable importance in the projection（VIP） value>1， P<0.05 from t-test， and log₂fold change（FC）>1 or log₂FC<-1. Kyoto Encyclopedia of Genes and Genomes（KEGG） database combined with MetaboAnalyst were used for pathway analysis of the screened differential metabolites. The protein expression levels of sphingosine-1-phosphate（S1P）， phosphatidylinositol 3-kinase（PI3K）， protein kinase B1（Akt1）， and phosphorylated Akt1（p-Akt1） were examined by Western bolt. The expression levels of interleukin（IL）-6， IL-1β， and tumor necrosis factor（TNF）-α in BALF were detected by enzyme-linked immunosorbent assay（ELISA）. ResultsCompared with the blank group， rats in the model group showed ALI pathological features such as alveolar lumen dilatation， interstitial hemorrhage and massive inflammatory cell infiltration， and the protein concentration in BALF and W/D of the lung tissues were significantly elevated（P<0.01）. Compared with the model group， the low- and high-dose groups of FF as well as the dexamethasone group exhibited reduced pulmonary bronchial hemorrhage in rats， and the protein concentration in BALF and W/D were significantly decreased（P<0.05）， and the lung injury was significantly alleviated. Analysis of rat serum metabolomics revealed that FF downregulated 38 biomarkers. Pathway enrichment analysis showed that FF primarily exerted therapeutic effects through 7 key metabolic pathways， including arginine biosynthesis， sphingomyelin metabolism， alanine， aspartate and glutamate metabolism， taurine and hypotaurine metabolism， α-linolenic acid metabolism， niacin and nicotinamide metabolism， and retinol metabolism. The results of Western bolt and ELISA showed that， compared with the blank group， the model group exhibited significantly elevated expression levels of S1P， PI3K， Akt1 and p-Akt1 proteins in the lung tissues， as well as increased expression levels of IL-6， IL-1β and TNF-α in BALF（P<0.01）. Compared with the model group， the expression levels of the aforementioned indicators were significantly downregulated in the low- and high-dose FF groups as well as the dexamethasone group（P<0.05， P<0.01）. ConclusionFF may play a role in ALI by regulating amino acid metabolism and lipid metabolism， and its mechanism may be related to the inhibition of S1P/PI3K/Akt1 signaling pathway to attenuate the inflammatory response caused by ALI.

Background::In vitro fertilization (IVF) has emerged as a transformative solution for infertility. However, achieving favorable live-birth outcomes remains challenging. Current clinical IVF practices in IVF involve the collection of heterogeneous embryo data through diverse methods, including static images and temporal videos. However, traditional embryo selection methods, primarily reliant on visual inspection of morphology, exhibit variability and are contingent on the experience of practitioners. Therefore, an automated system that can evaluate heterogeneous embryo data to predict the final outcomes of live births is highly desirable. Methods::We employed artificial intelligence (AI) for embryo morphological grading, blastocyst embryo selection, aneuploidy prediction, and final live-birth outcome prediction. We developed and validated the AI models using multitask learning for embryo morphological assessment, including pronucleus type on day 1 and the number of blastomeres, asymmetry, and fragmentation of blastomeres on day 3, using 19,201 embryo photographs from 8271 patients. A neural network was trained on embryo and clinical metadata to identify good-quality embryos for implantation on day 3 or day 5, and predict live-birth outcomes. Additionally, a 3D convolutional neural network was trained on 418 time-lapse videos of preimplantation genetic testing (PGT)-based ploidy outcomes for the prediction of aneuploidy and consequent live-birth outcomes.Results::These two approaches enabled us to automatically assess the implantation potential. By combining embryo and maternal metrics in an ensemble AI model, we evaluated live-birth outcomes in a prospective cohort that achieved higher accuracy than experienced embryologists (46.1% vs. 30.7% on day 3, 55.0% vs. 40.7% on day 5). Our results demonstrate the potential for AI-based selection of embryos based on characteristics beyond the observational abilities of human clinicians (area under the curve: 0.769, 95% confidence interval: 0.709–0.820). These findings could potentially provide a noninvasive, high-throughput, and low-cost screening tool to facilitate embryo selection and achieve better outcomes. Conclusions::Our study underscores the AI model’s ability to provide interpretable evidence for clinicians in assisted reproduction, highlighting its potential as a noninvasive, efficient, and cost-effective tool for improved embryo selection and enhanced IVF outcomes. The convergence of cutting-edge technology and reproductive medicine has opened new avenues for addressing infertility challenges and optimizing IVF success rates.

Aim To investigate the effects of puerarin on the proliferation,migration,and apoptosis of glio-blastoma cells and the underlying mechanisms.Meth-ods Differentially expressed genes associated with gli-oma and mitochondrial disease were analyzed using the GEO database.Cytotoxicity was detected by CCK-8 as-say.Cell migration was detected by the scratch wound healing assay and Transwell assay.Cell proliferation was assessed by EdU assay.Apoptosis level was meas-ured by TUNEL assay.Mitochondrial membrane poten-tial was detected by Mito-Tracker assay.ATP contents were detected using the ATP kit.The protein expres-sion levels were detected by Western blot.Antitumor efficacy of puerarin was analyzed using subcutaneous xenograft.Results There were 178 genes co-related differentially expressed genes in glioma and mitochon-drial disease.Core genes of co-related differentially ex-pressed genes were screened by GO and KEGG enrich-ment analyses,and the interaction networks.Among them,ubiquitin C(UBC)level was highly expressed in tissues of glioma patients.Puerarin could bind to UBC and reduce UBC expression at the animal and cell levels.Puerarin treatment inhibited the growth of glio-ma and decreased cell proliferation,migration and pro-moted cell apoptosis signals.Meantime,puerarin treat-ment also reduced mitochondrial membrane potentials and ATP contents,and down-regulated the levels of UBC related proteins.Conclusion Puerarin inhibits the proliferation,migration and promotes apoptosis of glioma cells.The mechanism of induction of mitochon-drial dysfunction is involved.

Aim To investigate the mechanism of Banxia Baizhu Tianma Decoction(BBTD)in interfer-ing methamphetamine(MA)addiction using network pharmacology.Methods The mechanism of BBTD intervention in MA addiction was analyzed using net-work pharmacology,and MA-dependent SH-SY5Y cell model was further constructed to observe the effects of BBTD on cell model and PI3K-Akt pathway.Results A total of 88 active ingredients and 583 potential tar-gets of BBTD were screened.KEGG analysis showed that BBTD might intervene in MA addiction through PI3K-Akt,cAMP and other pathways.The molecular docking results showed that key active ingredients ex-hibited strong binding ability with core targets of PI3K-Akt pathway.In vitro experiments showed that MA-de-pendent model cells had shorter synapses,tended to be elliptical in morphology,had blurred cell boundaries,showed typical cell damage morphology,and had high intracellular expression of cAMP(P＜0.01)and low expression of 5-HT(P＜0.05).BBTD intervention could counteract the above morphology,cAMP,and 5-HT changes,suggesting that it had therapeutic effects on MA-dependent model cells.Western blot showed that MA modeling elevated the p-PI3K/PI3K(P＜0.05)and p-Akt/Akt(P＜0.01);BBTD inter-vention decreased their relative expression.Conclu-sions Gastrodin and other active ingredients in BBTD have therapeutic effects on MA addiction,and the mechanism may be related to regulation of PI3K-Akt pathway relevant targets.