Hyperlipidemia is a common metabolic disorder driven by dysregulated lipid metabolism， whose pathological progression involves multifaceted interactions across various signaling pathways， including disrupted cholesterol homeostasis， insulin resistance， chronic inflammation， and oxidative stress. Although existing clinical medications such as statins can effectively reduce low-density lipoprotein cholesterol through single-target inhibition， significant limitations remain in comprehensively improving reverse cholesterol transport， metabolic inflammation， and coordinated regulation of glucose and lipid metabolism. Curcumin， the primary polyphenolic active compound derived from the traditional medicinal herb turmeric， exhibits multi-dimensional pharmacological effects including modulation of lipid metabolism， improvement of insulin sensitivity， suppression of inflammatory responses， and enhancement of antioxidant defense. This review systematically integrates the multi-target regulatory network of curcumin， elucidating its key mechanisms： Balancing the low density lipoprotein receptor/proprotein convertase subtilisin/kexin type 9 （LDLR/PCSK9） signaling pathway to promote reverse cholesterol transport， activating peroxisome proliferator-activated receptor α/γ （PPARα/γ） signaling pathways to coordinate glucolipid metabolic homeostasis， remodeling the gut microbiota-bile acid axis， inhibiting nuclear factor kappa-B （NF-κB）-mediated inflammatory responses， and activating the nuclear factor erythroid 2-related factor 2/antioxidant response element （Nrf2/ARE） antioxidant signaling pathway. Furthermore， supported by clinical research data， the review validates curcumin's therapeutic potential in reducing total cholesterol （TC） and triglyceride （TG） levels， increasing high-density lipoprotein cholesterol （HDL-C）， as well as improving vascular endothelial function and insulin sensitivity. The study highlights the multi-target regulatory properties of curcumin and discusses future clinical applications based on nano-delivery systems and personalized treatment strategies， providing a theoretical basis and novel insights for the prevention and treatment of hyperlipidemia and related metabolic disorders.

ObjectiveTo construct and evaluate various machine learning models for predicting the risk of chronic obstructive pulmonary disease （COPD） in individuals， thereby providing data support for early screening and intervention. MethodsA total of 823 subjects were selected for this study， comprising 142 individuals in the high-risk group for COPD and 681 individuals in the low-risk group. Data collected included demographic characteristics， smoking history， symptoms （such as cough and shortness of breath）， and scores from the Chronic obstructive pulmonary disease screening questionnaire. Four machine learning algorithms—Logistic regression， random forest， support vector machine， and XGBoost—were utilized to construct risk prediction models. The performance of these models was assessed using 5-fold cross-validation， with evaluation metrics including accuracy， precision， recall， F1-score， area under the receiver operating characteristic curve （AUC）， and average precision （AP）. Furthermore， a feature importance analysis was performed. ResultsThe Logistic Regression model exhibited superior performance， achieving an AUC of 0.982 and an AP of 0.939. This was closely followed by the Random Forest model， which recorded an AUC of 0.975 and an AP of 0.890. Feature importance analysis revealed that smoking history， symptoms of shortness of breath， and body weight were significant predictors. All models demonstrated robust performance in identifying low-risk populations； however， variations were observed in their efficacy in identifying high-risk populations. ConclusionMachine learning models have proven effective in identifying individuals at high risk for COPD. Among these， the Logistic regression model exhibits the best overall performance， efficiently identifying high-risk populations and serving as a valuable clinical auxiliary screening tool. Various models， each with distinct performance characteristics， are suited to different clinical screening scenarios， thereby offering targeted decision-making support for the establishment of a hierarchical and intelligent COPD screening pathway.

Objective: To investigate the mechanism of action of Prim-O-glucosylcimifugin (POG) to improve cholesterol metabolism in osteoarthritic (OA) chondrocytes based on the long noncoding RNA nuclear-enriched transcript 1 (lncRNA NEAT1)/microRNA-128-3p (miR-128-3p) pathway. Methods: For in vivo experiments, 60 mice were divided into the normal, sham operation, model, and POG groups using the random number table method, with 15 mice per group. The osteoarthritis mouse model was constructed using the modified Hulth method in the model and POG groups. Mice in the POG group were administered 30 mg/(kg·d)POG by gavage. The other groups were administered an equal amount of normal saline for 8 weeks. The cartilage tissue structure of mice in each group was observed using hematoxylin and eosin staining. Real-time PCR was used to detect changes in the lncRNA NEAT1 and miR-128-3p mRNA expression levels in the cartilage tissues of mice. Western blotting was used to detect the protein expressions of ATP-binding cassette transporter A1 (ABCA1), liver X receptor β (LXRβ), matrix metalloprotein-3 (MMP-3), and B-lymphoblastoma-2-associated X protein (Bax) in articular cartilage of mice. An enzyme-linked immunosorbent assay was used to measure the tumor necrosis factor-α (TNF-α) content in the synovial fluid of mice. A biochemical microplate assay was used to measure the total cholesterol level in the synovial fluid of mice. The in vitro experiments were divided into the negative control, interleukin-1β(IL-1β), IL-1β+ POG, IL-1β+ oe-lncRNA NEAT1, IL-1β+ oe-lncRNA NEAT1 + POG, IL-1β + miR-128-3p inhibition, and IL-1β+ miR-128-3p inhibition+ POG groups. An OA model was established by inducing chondrocytes with IL-1β for 24 h, and 90 mg/L of POG and miR-128-3p inhibitor(50 nmol/L) were administered for 48 h as an intervention. lncRNA NEAT1 expression in chondrocytes was detected using fluorescence in situ hybridization. A dual luciferase assay was used to detect the targeting relationship between lncRNA NEAT1 and miR-128-3p. Lentiviral plasmids overexpressing lncRNA NEAT1 were used to transfect mouse chondrocytes. Real-time PCR was used to detect the effect of lncRNA NEAT1 overexpression on the mRNA level of miR-128-3p in chondrocytes. Western blotting was used to detect ABCA1, LXRβ, MMP-3, and Bax protein expression in chondrocytes after lncRNA NEAT1 overexpression and miR-128-3p inhibition. Results: POG significantly reduced OA cartilage tissue damage. Compared with the model group, the lncRNA NEAT1 mRNA level decreased, whereas the miR-128-3p mRNA level increased in the cartilage tissue of the POG group (P<0.05). Compared with the model group, ABCA1 and LXRβ protein expression increased in the POG group, whereas MMP-3 and Bax protein expression decreased (P<0.05). The TNF-α levels decreased in the POG group compared to the model group (P<0.05). Compared with the model group, the total cholesterol level in the synovial fluid of the joint of mice in the POG group decreased (P<0.05). The mean fluorescence intensity of lncRNA NEAT1 in the IL-1β+ POG group decreased compared with the IL-1β group (P<0.05). The relative luciferase activity in the miR-128-3p mimics group bound to the lncRNA NEAT1-WT plasmid decreased compared with the miR-128-3p negative control group (P<0.05). The lncRNA NEAT1 mRNA levels decreased, whereas the miR-128-3p mRNA levels increased in the IL-1β+ oe-lncRNA NEAT1 + POG group compared with the IL-1β+ oe-lncRNA NEAT1 group (P<0.05). Compared with the IL-1β+ POG group, ABCA1 and LXRβ protein expression decreased, whereas MMP-3 and Bax protein expression increased (P<0.05). Conclusion POG mediates lncRNA NEAT1/miR-128-3p to improve cholesterol metabolism in OA chondrocytes.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

Objective To explore the efficacy of DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy for management of cancer pain and provide reference for its standardized clinical application.Methods and Results Recommendations were formulated based on literature review and expert group discussion,and consensus was reached following expert consultation.The consensus recommendations are comprehensive,covering the entire treatment procedures from preoperative assessment and preparation,surgical operation process,postoperative management and traditional Chinese medicine treatment to individualized treatment planning.The study results showed that the treatment plans combining traditional Chinese with Western medicine effectively alleviated cancer pain,reduced the use of opioid drugs,and significantly improved the quality of life and enhanced immune function of the patients.Postoperative follow-up suggested good treatment tolerance among the patients without serious complications.Conclusion The formulated consensus is comprehensive and can provide reference for clinicians to use DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy.The combined treatment has a high clinical value with a good safety profile for management of cancer pain.

Objective:This study aimed to evaluate the value of CT-based radiomics machine learning models in predicting spread through air spaces(STAS)in lung adenocarcinoma(LUAD)and to determine the optimal peritumoral analysis region.Methods:Data from 378 pa-tients who underwent non-small cell lung cancer surgery at Zhejiang Cancer Hospital between January 2013 to January 2017 were retro-spectively analyzed.Logistic regression,random forest,and XGBoost models were constructed using regions extending 0,3,6,9,and 12 mm outward from the tumor margin.Results:The XGBoost model using the 6 mm peritumoral region performed best on the test set,with an AUC-ROC of 0.855(95%CI:0.756-0.950),followed by the XGBoost model using the 9 mm region.Decision curve analysis(DCA)indicated that the XGBoost models for the 6 mm and 9 mm regions had higher net clinical benefits.Feature analysis revealed that some wavelet trans-form features significantly contributed to STAS prediction.Conclusions:This preliminary study suggests that CT-based radiomics machine learning models have predictive value for STAS.The XGBoost model based on the 6 mm peritumoral region demonstrated the best perform-ance,and holds promise in assisting preoperative assessment.

Objective:To investigate the value of MRI perfusion multiple parameters in preoperative classification of glioma and differential diagnosis of single brain metastases.Methods:A retrospective analysis was conducted on 78 patients initially diagnosed with glioma or single brain metastasis admitted to Cangzhou People's Hospital from January 2018 to July 2024,including 36 cases of glioma and 42 cases of single brain metastasis.Preoperative brain magnetic resonance imaging was performed to measure dynamic sensitive contrast magnetic resonance imaging(DSC-MRI),dynamic enhanced magnetic resonance imaging(DCE-MRI),and microvascular diameter imaging(VSI)parameters.Compare multiple parameters of magnetic resonance perfusion in patients with gliomas,solitary brain metastases,and gliomas of different pathological grades.Draw the working characteristic curve of the subjects and calculate the area under the curve(AUC)to analyze the diagnostic value of multi parameter magnetic resonance perfusion for gliomas.Spearman analysis was used to investigate the correlation between multiple parameters of magnetic resonance perfusion and pathological grading of glioma patients.Results:Cerebral blood volume(rCBV),cerebral blood flow(rCBF),volume transport constant(Ktrans),extracellular space volume ratio(Ve)and VSI values of glioma patients were significantly higher than those of single brain metastases,and the differences were statistically significant(t=25.066,26.892,22.856,70.455,27.984,P<0.05).The sensitivity of rCBV,rCBF,Ktrans,Kep,Ve,and VSI in diagnosing gliomas were 79.44%,78.54%,80.11%,63.32%,74.61%,and 77.29%,respectively.The specificity was 77.27%,76.49%,78.14%,61.38%,72.58%,and 75.13%,respectively.The AUC was 0.861,0.843,0.815,0.532,0.883,and 0.762,respectively;The sensitivity,specificity,and AUC of the combined detection of rCBV,rCBF,Ktrans,Kep,Ve,and VSI for diagnosing gliomas were 85.98%,82.24%,and 0.911,respectively.The diagnostic efficacy of the combined detection for gliomas was superior to that of individual indicators(Z=0.431,0.335,0.512,0.408,0.369,0.358,P<0.05).The rCBV,rCBF,Ktrans,Ve and VSI values of patients with grade Ⅰ,Ⅱ,Ⅲ and Ⅳ glioma increased successively,and the comparison between groups was statistically significant(F=119.972,100.884,74.180,74.180,118.485,P<0.05).The values of rCBV,rCBF,Ktrans,Ve and VSI were significantly positively correlated with the pathological grade of glioma patients(r=0.685,0.726,0.745,0.668,0.714,P<0.05).Conclusion:There are great differences in the multiple parameters of MRI perfusion between brain glioma and single brain metastases.Therefore,MRI perfusion multiple parameters have high differential diagnosis value,and are helpful for preoperative diagnosis and pathological classification of brain glioma,and have clinical guiding significance.

Objective:To evaluate the effect of digital design combined with 3D printing technology in the repair of mandibular defects with fibular myocutaneous flap.Methods:From July 2017 to August 2022, 25 patients with mandibular defects repaired by fibular musculocutaneous flap after oral tumor surgery were retrospectively analyzed. The cohort consisted of 25 patients (16 male, 9 female) aged 19-68 (42.5±5.3) years. The patients were divided into two groups according to different fibula shaping methods: Study group (11 cases): digital design combined with 3D printing technology was used for fibula shaping; Control group (14 cases): conventional fibula shaping was performed based on the surgeon's experience.Results:The fibula shaping time in the study group was (51.2±4.2) min, which was shorter than that in the control group (79.1±8.0) min ( P<0.001). The study group showed higher satisfaction scores for facial appearance compared to the control group [(8.3±0.8) vs (6.9±0.6) points, P<0.001]. The survival rates were 11/11 in the study group and 13/14 in the control group, with a significantly higher survival rate observed in the study group ( P<0.001). At 3 months postoperatively, the mouth opening measurements were (3.5±0.2) cm in the study group and (3.5±0.1) cm in the control group, showed no statistically significant difference ( P=0.334). Conclusion:The application of digital design combined with 3D printing technology in fibula musculocutaneous flap reconstruction of mandibular defects reduces fibula shaping time, improves flap survival rates, and yields higher patient satisfaction with facial aesthetics.

In recent years,the market share of food and medicine homology substances has continued to grow,and various types of contamination issues have become the focus of attention both inside and outside the industry.The contamination not only affects the original medicinal quality,but also leads to the accumulation of toxic substances in the human body,causing acute and chronic severe hazards such as vomiting,poisoning and cancer.Therefore,the development of biosensors that can conveniently,accurately and sensitively detect various pollutants in food and medicine homology substances has become a research hotspot.Aptasensors based on metal-organic frameworks(MOFs)with advantages such as strong specificity,rapid response and simple operation,have been widely used in detection of various pollutants.This review focused on the research progress of aptasensors based on MOFs for detection of food and medicine homology contamination in the past few years,and provided a detailed comparison and analysis for detection of chemical pollutants(such as pesticide residues,heavy metal residues,mycotoxins,etc.)and microbial contamination in food and medicine homology substances.Besides,the development trend and possible challenges of MOFs aptasensors in detection of food and medicine homology substances in the future were discussed,which was anticipated to provide a reference for the development of new MOFs aptasensors.

6-Thioguanine(6-TG)is an antineoplastic agent used in treatment of acute leukemia.However,significant interindividual variability in dosing regimens and frequent clinical manifestations of hepatotoxicity and myelosuppression as adverse effects have affected its therapeutic efficacy.Consequently,the development of rapid analytical methods for 6-TG in clinical samples,enabling continuous therapeutic drug monitoring of plasma concentrations,holds substantial significance in optimizing dosage regimens,mitigating adverse reactions,and investigating drug metabolism mechanisms.In this study,multi-tipped gold nanostars(AuNSs)were prepared.With bis-(p-sulfonylphenyl)phenylphosphine molecule as the protecting agent and internal standard molecule,the AuNSs were assembled onto a highly sensitive surface-enhanced Raman(SERS)substrate for developing a ratio-based SERS quantitative analysis method for 6-TG in serum.The AuNSs containing multiple tips and gaps exhibited strong local surface plasmon resonance effect and SERS activity,ensuring the sensitivity of the analytical method.Furthermore,the introduction of internal standard molecules could improve the reproducibility,which guaranteed this method suitable for rapid analysis of drug molecules in complex samples.Quantitative analysis of 6-TG was achieved with linear detetion range of 1.0×10?4-1.0 mmol/L.In the spiked recovery experiments of serum,the RSD was less than 5.32%,and the recoveries were 94%-104%,which proved that this method could be used for rapid quantitative determination of 6-TG in serum.This method provided a powerful tool for studying drug pharmacokinetics,which could promote the optimization of the usage methods of anti-cancer drugs,and it was expected to further enhance the clinical efficacy and safety of 6-TG,enabling it to achieve the best therapeutic effect.