The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is higher among individuals with inflammatory bowel disease (IBD) than in the general population. Emerging evidence indicates that the development of MASLD in patients with IBD may occur independently of traditional metabolic risk factors, suggesting a unique pathophysiological mechanism distinct from conventional MASLD pathways. Bile acids (BAs), which act as critical signaling molecules in enterohepatic circulation, play an essential role in maintaining gastrointestinal homeostasis through bidirectional gut–liver axis communication. These molecules are increasingly recognized as pivotal regulators in the progression of both MASLD and IBD. While previous studies have characterized the dynamics of BA in blood or fecal samples under both conditions, a comprehensive understanding of their metabolic profiles and the associated interactions within the gut–liver axis is still lacking. This review synthesizes current evidence from studies employing BA metabolomics to investigate IBD and MASLD. By focusing on BA signatures, we summarize conserved alterations between these two conditions and their potential mechanisms of disease progression. Our review advances understanding of BA-mediated pathways in IBD and MASLD, providing a foundation for assessing their roles in contributing to the pathogenesis of MASLD in patients with IBD.

Objective:To investigate the nutritional status of esophageal cancer patients and analyze the ability of the modified Patient-Generated Subjective Global Assessment(mPG-SGA)to evaluate nutritional status against the original PG-SGA standard.Method:We enrolled 479 patients newly diagnosed with esophageal cancer at a provincial tertiary hospital in Shenyang from August 2022 to April 2024.Blood samples were analyzed for nutritional indicators,and nutritional status was assessed using both PG-SGA and mPG-SGA.The nutritional assessment ability of mPG-SGA was evaluated using specificity,sensitivity,area under the curve(AUC),weighted kappa coefficient,and correlation analysis.Results:Among the 479 patients,the incidence of moderate-to-severe malnutrition was 74.9%(by PG-SGA)and 72.9%(by mPG-SGA).Using PG-SGA as the standard,mPG-SGA demonstrated sensitivities of 95.4%,100%,and 100%;specificities of 98.5%,92.3%,and 89.5%;and AUC values of 0.997,0.994,and 0.989(all P<0.001)for distinguishing mild vs.moderate-to-severe malnutrition,mild-to-moderate malnutrition,and moderate-to-severe malnutrition,respectively.The overall weighted Kappa coefficient between the scales was 0.898(P<0.001).Conclusion:Malnutrition is highly prevalent among esophageal cancer patients.The mPG-SGA shows strong accuracy and consistency with PG-SGA in assessing nutritional status.Given its simplicity and efficiency,mPG-SGA may become a primary nutritional assessment tool for this population,though further multicenter validation with larger samples is warranted.

Objective To investigate the effects of γ-glutamyl hydrolase(GGH)rs11545078 C＞T polymorphisms on serum concentrations,chemotherapy toxicities of methotrexate(MTX),and prognosis in children with intracranial tumors.Methods Peripheral blood samples were obtained from children with intracranial tumors to extract genome DNA.Matrix-assisted laser desorption/ionization-time of flight mass spectrometry was used to detect the genotypes of GGH rs11545078 C＞T polymorphisms.Fluorescence polarization immunoassay was employed to determine the serum concentrations of MTX.The incidences of toxicities,relapse,and metastasis were recorded after chemotherapy with MTX.The associations of GGH rs11545078 C＞T polymorphisms with concentration-to-dose ratios(C/D ratios),chemotherapy toxicities of MTX,relapse,and metastasis of tumors were analyzed.Results A total of 75 children were included in the present study.The frequencies of rs11545078 CC and CT genotypes were 82.67％and 17.33％,respectively.The frequencies of C and T alleles were 91.33％and 8.67％,respectively.There were no statistically significant differences for these frequencies among the children with intracranial tumors,the children with acute lymphoblastic leukemia,and the health population in Beijing.Children with the CC genotype had higher median C/D ratios of MTX in 24 and 42 h(25.19 and 0.14 μmol·L-1 per g·m-2,respectively),higher metastasis rates(46.77％),and lower relapse rates(17.74％)than those in CT genotype carriers(22.01 and 0.11 μmol·L-1 per g·m-2,38.46％,and 30.77％,respectively),and the differences were no statistically significant(all P＞0.05).The incidences of gastrointestinal disorders(76.92％)in children with the CT genotype were significantly higher than those in CC genotype carriers(45.16％,P＜0.05).There were no statistically significant differences in the incidences of other adverse events between patients with the CC genotype and patients with the CT genotype(all P＞0.05).Conclusion GGH rs11545078 CT might be a risk factor for gastrointestinal disorders in children with intracranial tumors treated with MTX.

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometr (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution (HR) mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition, and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Emodin is a hydroxyanthraquinone compound that is widely distributed and has multiple pharmacological activities, including anti-diarrheal, anti-inflammatory, and liver-protective effects. Research indicates that emodin may be one of the main components responsible for inducing hepatotoxicity. However, studies on the mechanisms of liver injury are relatively limited, particularly those related to bile acids(BAs) metabolism. This study aims to systematically investigate the effects of different dosages of emodin on BAs metabolism, providing a basis for the safe clinical use of traditional Chinese medicine(TCM)containing emodin. First, this study evaluated the safety of repeated administration of different dosages of emodin over a 5-week period, with a particular focus on its impact on the liver. Next, the composition and content of BAs in serum and liver were analyzed. Subsequently, qRT-PCR was used to detect the mRNA expression of nuclear receptors and transporters related to BAs metabolism. The results showed that 1 g·kg~(-1) emodin induced hepatic damage, with bile duct hyperplasia as the primary pathological manifestation. It significantly increased the levels of various BAs in the serum and primary BAs(including taurine-conjugated and free BAs) in the liver. Additionally, it downregulated the mRNA expression of farnesoid X receptor(FXR), retinoid X receptor(RXR), and sodium taurocholate cotransporting polypeptide(NTCP), and upregulated the mRNA expression of cholesterol 7α-hydroxylase(CYP7A1) in the liver. Although 0.01 g·kg~(-1) and 0.03 g·kg~(-1) emodin did not induce obvious liver injury, they significantly increased the level of taurine-conjugated BAs in the liver, suggesting a potential interference with BAs homeostasis. In conclusion, 1 g·kg~(-1) emodin may promote the production of primary BAs in the liver by affecting the FXR-RXR-CYP7A1 pathway, inhibit NTCP expression, and reduce BA reabsorption in the liver, resulting in BA accumulation in the peripheral blood. This disruption of BA homeostasis leads to liver injury. Even doses of emodin close to the clinical dose can also have a certain effect on the homeostasis of BAs. Therefore, when using traditional Chinese medicine or formulas containing emodin in clinical practice, it is necessary to regularly monitor liver function indicators and closely monitor the risk of drug-induced liver injury.
Emodin/administration & dosage* ; Bile Acids and Salts/metabolism* ; Animals ; Male ; Liver/injuries* ; Chemical and Drug Induced Liver Injury/genetics* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Rats, Sprague-Dawley ; Mice ; Rats

Poly(lactic-co-glycolide)(PLGA)is a key excipient in long-acting sustained-release preparations,and its degradation properties directly affect the drug release behavior.In this study,PLGA microspheres were prepared by microfluidic techniques,and the morphology changes of the microspheres were observed by scanning electron microscopy(SEM).In alkaline environment,due to the accelerated hydrolysis of ester bonds,the surface of the microspheres was rapidly dissolved and eroded,and the degradation rate was significantly higher than that in acidic environment.High temperature accelerated the degradation of PLGA microspheres.Under neutral and alkaline conditions,the microspheres showed aggregation and adhesion.Under acidic conditions,the microspheres gradually decomposed into irregular fragments.The high ionic strength further promoted the surface corrosion of the microspheres,especially under extreme pH conditions.Simultaneously,PLGA microspheres encapsulating coumarin were prepared to simulate the microsphere formulation.The release rate of coumarin after degradation of the microspheres under different conditions was observed by measuring the absorbance with ultraviolet-visible spectrophotometry.The results were consistent with those of the blank microspheres.This study revealed that the degradation of PLGA microspheres was significantly pH-dependent,temperature sensitive and ion strength responsive.These findings not only helped to understand and optimize the long-term stability and controlled release performance of drug-carrying microspheres,but also provided a theoretical basis for further improvement of PLGA-based drug carrier design.

With reference to the Information and Documentation-Resource Description (GB/T 3792-2021) and Bibliographical Description for Ancient Chinese Books (GB/T 3792.7-2008) and other cataloging standards and rules, drawing on the practical experience of cataloging ancient TCM books, Bibliographical Cataloging for Ancient TCM Books was formulated. This standard specifies the entry items and their order of ancient TCM books, cataloging identifier, cataloging text, cataloging information source, and cataloging item details. The standard can provide standardized and unified guiding principles and methods for the work of ancient TCM books, and promote the sharing and utilization of ancient TCM books.

Pancreatic cancer is characterized by significant drug resistance,and despite continuous advancements in treatment regimens,the 5-year survival rate of patients remains low.The nuclear factor-κB(NF-κB)signaling pathway,frequently mutated in tumors,has been identified as a critical factor in triggering drug resistance.Multiple studies have demonstrated that strategies targeting NF-κB signaling transduction exhibit promising outcomes in pancreatic cancer treatment.Therefore,exploring the relationship between the NF-κB signaling pathway and drug resistance in pancreatic cancer has become a research hotspot in pancreatic cancer treatment.This review summarizes recent advances in the relationship between NF-κB signaling pathway and tumor drug resistance,as well as its role in pancreatic cancer treatment.Specifically,the mechanisms by which the NF-κB signaling pathway mediates drug resistance in pancreatic cancer are elaborated from two perspectives:chemotherapy and immunotherapy,aiming to provide insights for pancreatic cancer treatment and future research.

OBJECTIVES: To investigate the role and mechanism of copper overload-mediated endoplasmic reticulum stress (ERS) in vascular endothelial injury in Kawasaki disease (KD). METHODS: Four-week-old male C57BL/6 mice were randomly divided into four groups: control, KD, KD plus copper chelator tetrathiomolybdate (TTM), and KD plus ERS inhibitor AMG PERK 44 (AMG) (n=20 per group). A KD mouse model was established using Candida albicans extract. Human umbilical vein endothelial cells (HUVECs) were divided into control (intervention with healthy children's serum), KD (intervention with KD patients' serum), and KD+TTM (intervention with KD patients' serum plus 20 µmol/L TTM). Copper deposition in mouse heart tissue was assessed using rubeanic acid staining. Vascular pathological changes were observed using hematoxylin-eosin staining and measurement of abdominal aortic diameter and area. ERS activation was detected by transmission electron microscopy and immunofluorescence. HUVEC viability, apoptosis, and functional changes were evaluated using CCK8, flow cytometry, cell scratch assay, and angiogenesis experiments. ERS marker protein expression levels were measured by Western blot. RESULTS: Compared to the KD group, the KD+TTM and KD+AMG groups showed reduced copper deposition in the vascular wall, decreased swelling of coronary endothelial cells and endoplasmic reticulum, reduced inflammatory cell infiltration, and less abdominal aortic lesion expansion. The abdominal aortic diameter and area, and the fluorescence intensity of ERS marker proteins (GRP78 and CHOP) were significantly lower (P<0.05). Compared to the KD group, the KD+TTM group exhibited increased cell viability, tube number, and scratch healing rate, along with decreased apoptosis rate and expression of ERS marker proteins (GRP78, CHOP, ATF6, and p-PERK) (P<0.05). CONCLUSIONS Copper overload aggravates vascular endothelial injury in KD by activating the ERS pathway. TTM can exert protective effects on the endothelium by regulating copper metabolism and inhibiting the ERS pathway.
Endoplasmic Reticulum Stress ; Copper/toxicity* ; Male ; Mucocutaneous Lymph Node Syndrome/metabolism* ; Animals ; Humans ; Endoplasmic Reticulum Chaperone BiP ; Mice, Inbred C57BL ; Mice ; Human Umbilical Vein Endothelial Cells ; Apoptosis ; Endothelium, Vascular/injuries*