Twelve compounds were isolated from the rice fermentation extracts of Penicillium expansum GY618 by silica column chromatography, Sephadex gel column chromatography, ODS column chromatography and semi preparative HPLC methods. They were determined as 11-hydroxyl-penicitrinone F (1), penicitrinone F (2), betulin (3), erythrodiol (4), ergosterol (5), ergost-5α,8α-epidioxy-6,22-dien-3β-ol (6), (5α,8α-epidioxy-(22E,24R)-ergosta-6,9(11),22-trien-3β-ol) (7), 5α,8α-epidioxy-(22E,24R)-23-methylergosta-6,22-dien-3β-ol (8), 5α,8α-epidioxy- 23,24(R)-dimethylcholesta-6,9(11),22-trien-3β-ol (9), dankasterone A (10), (17R)-4-hydroxy-17-methylincisterol (11) and ergosta-4,6,8(14),22-tetraen-3-one (12), through mass spectrometer, nuclear magnetic resonance (NMR) and comparison with the literature. Compound 1 was a new compound and compounds 2-4, 6-12 were isolated from Penicillium expansum fungus for the first time. The tyrosinase inhibitory activity experiment showed that compounds 1, 3 and 12 showed certain inhibitory activity against tyrosinase with IC₅₀ values of (75 ± 9), (69 ± 8) and (64 ± 2) μmol·L^-1, respectively. The IC₅₀ of other compounds were all greater than 100 μmol·L^-1, while IC₅₀ of the positive control kojic acid was (46 ± 4) μmol·L^-1.

BACKGROUND:The Twin-block orthodontic appliance is commonly used for the correction of Class Ⅱ malocclusion.Its mechanism of action in stimulating mandibular growth has been confirmed in many studies,but its impact on maxillary growth is not very clear. OBJECTIVE:By establishing a finite element model to analyze the stress distribution of the maxillary complex,surrounding bone sutures,and maxillary dentition in patients with Class Ⅱ malocclusion wearing Twin-block orthodontic appliances. METHODS:One patient with Class Ⅱ malocclusion who underwent orthodontic treatment at Qingdao Hospital/Qingdao Municipal Hospital of Shandong Rehabilitation University was selected.The bite force data of the patient when wearing the Twin-block orthodontic appliance was measured,and CBCT data were collected.A finite element model was established,including the maxillary complex,peripheral sutures,Twin-block orthodontic appliance,and maxillary dentition.ABAQUS software was used to simulate the stress distribution in the maxilla and maxillary dentition when the patient was wearing the Twin-block appliance. RESULTS AND CONCLUSION:The equivalent stress on the maxillary anterior teeth was significantly smaller than that on the posterior teeth,and the maximum equivalent stress on both sides of the teeth were 4.797 5 Mpa and 8.716 1 Mpa,respectively,which were located at the first premolar.The maximum displacements were presented at the maxillary incisors on both sides of the teeth,which were 0.080 5 mm and 0.081 0 mm,respectively.The maximum equivalent stress on the bone suture was 1.284 Mpa,which was mainly concentrated in the pterygopalatine suture and the frontal-maxillary suture on both sides,and there was almost no difference in the force of the rest of bone sutures;the maximum displacement of the bone suture was 0.07 mm,with the pterygopalatine suture having the largest displacement,followed by the frontal-maxillary suture.The maximal equivalent stress on the maxillary complex was 27.18 Mpa,which was mainly concentrated on both sides of the anterior pyriform foramen of the maxilla,around the nasofrontal suture and around the pterygopalatine suture at the posterior part of the jaws.The maximal displacement of the maxilla was 0.07 mm,which was mainly concentrated on the maxillary alveolar bone.All these findings show that the occlusal force acts on the maxillary complex through the Twin-block appliance,resulting in clockwise rotation of the maxilla and steepening of the dentition plane.Measures should be taken to compensate for this tendency,for example,by considering maxillary molar elongation and intrusion in the process of occlusion,which are not only able to flatten the occlusal plane,but facilitate the mandibular protraction,thereby further improving Class Ⅱ malocclusion orthodontic treatment.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

The pathogenesis of cardiovascular diseases (CVD) is complex, and dynamic imbalances in protein acylation modification are significantly associated with the development of CVD. In recent years, most studies on exercise-regulated protein acylation modifications to improve cardiovascular function have focused on acetylation and lactylation. Protein acylation modifications are usually affected by exercise intensity. High-intensity exercise directly affects oxidative stress and cellular energy supply, such as changes in ATP and NAD⁺ levels; moderate-intensity exercise is often accompanied by improvements in aerobic metabolism, such as fatty acid β-oxidation and TCA cycle, which modulate mitochondrial biogenesis. The above processes may affect the acylation status of relevant regulatory enzymes and functional proteins, thereby altering their function and activity and triggering signaling cascades to adapt to exercise’s metabolic demands and stresses. Exercise regulates the levels of acylation modifications of H3K9, H3K14, H3K18, and H3K23, which are involved in regulating the transcriptional expression of genes involved in oxidative stress, glycolysis, inflammation, and hypertrophic response by altering chromatin structure and function. Exercise can regulate the acylation modification of non-histone-specific sites in the cardiovascular system involved in mitochondrial function, glycolipid metabolism, fibrosis, protein synthesis, and other biological processes, and participates in the regulation of protein activity and function by altering the stability, localization, and interaction of proteins, and ultimately works together to achieve the improvement of cardiovascular phenotypes and biological functions. Exercise affects acyl donor concentration, acyltransferase, and deacetylase expression and activity by influencing acyl donor concentration, acyltransferase, and deacetylase. Exercise regulates the abundance of acyl donors such as acetyl coenzyme A, propionyl coenzyme A, butyryl coenzyme A, succinyl coenzyme A, and lactoyl coenzyme A by promoting glucose and lipid metabolism and improving intestinal bacterial flora, which in turn affects protein acylation modification, accelerates oxidative decarboxylation of pyruvic acid in the body, and activates the energy-sensing molecule, adenosine monophosphate-activated protein kinase (AMPK), to improve cardiovascular function. Exercise may affect protein acylation modifications in the cardiovascular system by regulating the activity and expression of adenoviral E1A binding protein of 300 kDa (p300)/cyclic adenosine monophosphate response element-binding protein (CBP), general control nonderepressible 5-related N-acetyltransferases (GNAT), and alanyl-transfer t-RNA synthetase (AARS), which in turn improves cardiovascular function. The relationship between exercise and cardiovascular deacetylases has attracted much attention, with SIRT1 and SIRT3 of the silence information regulator (SIRT) family of proteins being the most studied. Exercise may exert transient or long-term stable cardiovascular protective benefits by promoting the enzymatic activity and expression of SIRT1, SIRT3, and HDAC2, inhibiting the enzymatic activity and expression of HDAC4, and mediating the deacylation of metabolic regulation-related enzymes, cytokines, and molecules of signaling pathways. This review introduces the role of protein acylation modification on CVD and the effect of exercise-mediated protein acylation modification on CVD. Based on the existing studies, it analyzes the possible mechanisms of exercise-regulated protein acylation modification to improve CVD from the perspectives of acylation modification donors, acyltransferases, and deacetylases. Deciphering the regulation of cardiovascular protein acylation and modification by exercise and exploring the essential clues to improve cardiovascular disease can enrich the theoretical basis for exercise to promote cardiovascular health. However, it is also significant for developing new cardiovascular disease prevention and treatment targets.

ObjectiveThe aim of this study was to investigate the prophylactic effects of caloric restriction (CR) on lipopolysaccharide (LPS)-induced septic cardiomyopathy (SCM) and to elucidate the mechanisms underlying the cardioprotective actions of CR. This research aims to provide innovative strategies and theoretical support for the prevention of SCM. MethodsA total of forty-eight 8-week-old male C57BL/6 mice, weighing between 20-25 g, were randomly assigned to 4 distinct groups, each consisting of 12 mice. The groups were designated as follows: CON (control), LPS, CR, and CR+LPS. Prior to the initiation of the CR protocol, the CR and CR+LPS groups underwent a 2-week acclimatization period during which individual food consumption was measured. The initial week of CR intervention was set at 80% of the baseline intake, followed by a reduction to 60% for the subsequent 5 weeks. After 6-week CR intervention, all 4 groups received an intraperitoneal injection of either normal saline or LPS (10 mg/kg). Twelve hours post-injection, heart function was assessed, and subsequently, heart and blood samples were collected. Serum inflammatory markers were quantified using enzyme-linked immunosorbent assay (ELISA). The serum myocardial enzyme spectrum was analyzed using an automated biochemical instrument. Myocardial tissue sections underwent hematoxylin and eosin (HE) staining and immunofluorescence (IF) staining. Western blot analysis was used to detect the expression of protein in myocardial tissue, including inflammatory markers (TNF-α, IL-9, IL-18), oxidative stress markers (iNOS, SOD2), pro-apoptotic markers (Bax/Bcl-2 ratio, CASP3), and SIRT3/SIRT6. ResultsTwelve hours after LPS injection, there was a significant decrease in ejection fraction (EF) and fractional shortening (FS) ratios, along with a notable increase in left ventricular end-systolic diameter (LVESD). Morphological and serum indicators (AST, LDH, CK, and CK-MB) indicated that LPS injection could induce myocardial structural disorders and myocardial injury. Furthermore, 6-week CR effectively prevented the myocardial injury. LPS injection also significantly increased the circulating inflammatory levels (IL-1β, TNF-α) in mice. IF and Western blot analyses revealed that LPS injection significantly up-regulating the expression of inflammatory-related proteins (TNF-α, IL-9, IL-18), oxidative stress-related proteins (iNOS, SOD2) and apoptotic proteins (Bax/Bcl-2 ratio, CASP3) in myocardial tissue. 6-week CR intervention significantly reduced circulating inflammatory levels and downregulated the expression of inflammatory, oxidative stress-related proteins and pro-apoptotic level in myocardial tissue. Additionally, LPS injection significantly downregulated the expression of SIRT3 and SIRT6 proteins in myocardial tissue, and CR intervention could restore the expression of SIRT3 proteins. ConclusionA 6-week CR could prevent LPS-induced septic cardiomyopathy, including cardiac function decline, myocardial structural damage, inflammation, oxidative stress, and apoptosis. The mechanism may be associated with the regulation of SIRT3 expression in myocardial tissue.

Objective To explore the association between oral microbiota and esophageal carcinogenesis. Methods A case-control study design was employed. A total of 309 subjects were recruited, consisting of 159 healthy controls, 32 cases of esophageal basal cell hyperplasia, 32 cases of low-grade intraepithelial neoplasia, 14 cases of high-grade intraepithelial neoplasia, and 72 cases of esophageal squamous cell carcinoma. Tongue swab samples were collected for 16S rRNA sequencing. The α-diversity and β-diversity of the microbiota were analyzed, and the characteristics of the microbial communities at different stages of esophageal carcinogenesis were compared. The strength of the association was expressed by odds ratio (OR) and 95% confidence interval (CI). Results α-diversity analysis indicated significant differences in the observed species number (Sobs) index across various stages of esophageal cancer progression (P<0.001). After adjusting for confounding factors such as age, gender, smoking, and alcohol consumption, the Simpson index was positively correlated with carcinogenesis (P=0.006). β-diversity analysis revealed differences in microbiota structure among the groups. After ordered multinomial logistic regression analysis and adjustment for multiple confounding factors, the relative abundance of Peptostreptococcus (OR: 2.06, 95%CI: 1.22–3.60), Patescibacteria (OR: 1.31, 95%CI: 1.04–1.67), Capnocytophaga (OR: 1.24, 95%CI: 1.05–1.54), and Bacteroidota (OR: 1.02, 95%CI: 1.00–1.05) was positively correlated with carcinogenesis. The relative abundance of Stomatobaculum (OR: 0.57, 95%CI: 0.30–1.00) and Actinobacteriota (OR: 0.95, 95%CI: 0.92–0.98) was negatively correlated with carcinogenesis. Conclusion Specific oral microbiotas are significantly associated with esophageal carcinogenesis, and synergistic or antagonistic interactions may be observed among the microbiota.

Cardiovascular disease (CVD) remains one of the leading causes of mortality among adults globally, with continuously rising morbidity and mortality rates. Metabolic disorders are closely linked to various cardiovascular diseases and play a critical role in their pathogenesis and progression, involving multifaceted mechanisms such as altered substrate utilization, mitochondrial structural and functional dysfunction, and impaired ATP synthesis and transport. In recent years, the potential role of peroxisome proliferator-activated receptors (PPARs) in cardiovascular diseases has garnered significant attention, particularly peroxisome proliferator-activated receptor alpha (PPARα), which is recognized as a highly promising therapeutic target for CVD. PPARα regulates cardiovascular physiological and pathological processes through fatty acid metabolism. As a ligand-activated receptor within the nuclear hormone receptor family, PPARα is highly expressed in multiple organs, including skeletal muscle, liver, intestine, kidney, and heart, where it governs the metabolism of diverse substrates. Functioning as a key transcription factor in maintaining metabolic homeostasis and catalyzing or regulating biochemical reactions, PPARα exerts its cardioprotective effects through multiple pathways: modulating lipid metabolism, participating in cardiac energy metabolism, enhancing insulin sensitivity, suppressing inflammatory responses, improving vascular endothelial function, and inhibiting smooth muscle cell proliferation and migration. These mechanisms collectively reduce the risk of cardiovascular disease development. Thus, PPARα plays a pivotal role in various pathological processes via mechanisms such as lipid metabolism regulation, anti-inflammatory actions, and anti-apoptotic effects. PPARα is activated by binding to natural or synthetic lipophilic ligands, including endogenous fatty acids and their derivatives (e.g., linoleic acid, oleic acid, and arachidonic acid) as well as synthetic peroxisome proliferators. Upon ligand binding, PPARα activates the nuclear receptor retinoid X receptor (RXR), forming a PPARα-RXR heterodimer. This heterodimer, in conjunction with coactivators, undergoes further activation and subsequently binds to peroxisome proliferator response elements (PPREs), thereby regulating the transcription of target genes critical for lipid and glucose homeostasis. Key genes include fatty acid translocase (FAT/CD36), diacylglycerol acyltransferase (DGAT), carnitine palmitoyltransferase I (CPT1), and glucose transporter (GLUT), which are primarily involved in fatty acid uptake, storage, oxidation, and glucose utilization processes. Advancing research on PPARα as a therapeutic target for cardiovascular diseases has underscored its growing clinical significance. Currently, PPARα activators/agonists, such as fibrates (e.g., fenofibrate and bezafibrate) and thiazolidinediones, have been extensively studied in clinical trials for CVD prevention. Traditional PPARα agonists, including fenofibrate and bezafibrate, are widely used in clinical practice to treat hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) levels. These fibrates enhance fatty acid metabolism in the liver and skeletal muscle by activating PPARα, and their cardioprotective effects have been validated in numerous clinical studies. Recent research highlights that fibrates improve insulin resistance, regulate lipid metabolism, correct energy metabolism imbalances, and inhibit the proliferation and migration of vascular smooth muscle and endothelial cells, thereby ameliorating pathological remodeling of the cardiovascular system and reducing blood pressure. Given the substantial attention to PPARα-targeted interventions in both basic research and clinical applications, activating PPARα may serve as a key therapeutic strategy for managing cardiovascular conditions such as myocardial hypertrophy, atherosclerosis, ischemic cardiomyopathy, myocardial infarction, diabetic cardiomyopathy, and heart failure. This review comprehensively examines the regulatory roles of PPARα in cardiovascular diseases and evaluates its clinical application value, aiming to provide a theoretical foundation for further development and utilization of PPARα-related therapies in CVD treatment.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.