ObjectiveTo comprehensively identify the O-methyltransferase （OMT） genes in Carthamus tinctorius and explore the key OMTs that can catalyze the methylation of flavonoids， providing a basis for understanding the molecular formation mechanism of the structural diversity of flavonoids in C. tinctorius. MethodsThe hidden Markov model was used to systematically identify the type Ⅰ OMTs from the high-quality genome data of C. tinctorius. A suite of bioinformatics tools was employed to systematically analyze the physicochemical properties， gene structure， conserved motifs， chromosomal localization， gene replication events， and collinearity of the identified genes. The target gene was heterologously expressed through the prokaryotic expression system of E. coli， and the protein function was verified by in vitro enzymatic reactions. ResultsA total of 31 type Ⅰ OMTs were identified. CtFOMT1 was successfully cloned and expressed in a soluble form in Escherichia coli. The recombinant protein was purified via Ni²⁺ affinity chromatography to obtain a high-concentration preparation. In vitro enzymatic assays demonstrated that CtFOMT1 utilized S-adenosylmethionine as the methyl donor to catalyze the methylation of the 4′-OH of naringenin， resulting in the production of isosakuranetin. A similar process occurred with the 4′-OH of luteolin， leading to the formation of diosmetin. Subsequent methylation of the 3′-OH group of diosmetin generated 4′-methylchrysoeriol. ConclusionCtFOMT1 can catalyze the methylation of 4′-/3′-OH in the flavonoid skeleton. It is hypothesized that CtFOMT1 may play a role in the biosynthesis of various 4′-/3′-oxymethyl flavonoids in C. tinctorius.

ObjectiveTo investigate the diagnostic value of coagulation function indicators and proteinuria in preeclampsia and its severity assessment. MethodsA total of 239 pregnant women who visited from January 2022 to December 2023 were selected as research subjects. They were divided into healthy control group （n=50）， non-gestational hypertension group （n=39）， and gestational hypertension group （n=150） based on clinical diagnosis. The gestational hypertension group was further subdivided into three subgroups： simple hypertension group （n=50）， mild preeclampsia group （n=50）， and severe preeclampsia group （n=50）. The study compared differences in plasma protein S （PS）， plasma protein C （PC）， fibrin degradation products （FDP）， fibrin monomer （FM）， and proteinuria levels among different groups. The correlation between proteinuria and coagulation function indicators in patients with gestational hypertension was analyzed， and ROC curves were used to analyze the diagnostic efficacy of coagulation indicators and proteinuria for gestational hypertension and different stages of preeclampsia. ResultsThe gestational hypertension group showed lower PS and PC values compared to the non-gestational hypertension group and healthy control group， while FDP， FM values， and proteinuria levels were higher than those in the non-gestational hypertension group and healthy control group （P<0.05）. Significant differences in coagulation indicators and proteinuria levels were observed among pregnant women with different degrees of gestational hypertension （P<0.05）. The AUC values for diagnosing gestational hypertension using PS， PC，FDP， FM， and proteinuria were 0.928， 0.957， 0.968， 0.948， and 0.932 respectively （P<0.000 1）. For diagnosing simple hypertension and mild preeclampsia， the AUC values were 0.875， 0.777， 0.830， 0.679， and 0.936 respectively （P<0.01）. For diagnosing mild and severe preeclampsia， the AUC values were 0.901， 0.776， 0.780， 0.807， and 0.848 respectively （P<0.000 1）. ConclusionCoagulation function indicators and proteinuria show significant differences between healthy pregnant women and those with gestational hypertension. PS， PC， FDP， FM， and proteinuria levels vary among pregnant women with different stages of preeclampsia. The aforementioned indicators exhibit certain diagnostic efficacy for gestational hypertension and preeclampsia.

Cancer stem cells (CSCs) represent a distinct subpopulation of cells characterized by self-renewal capacity, differentiation potential, and critical roles in driving tumor progression, therapeutic resistance, recurrence, and maintenance of the tumor microenvironment. Targeting CSCs has emerged as a pivotal direction in cancer research, offering novel strategies to overcome drug resistance and prevent metastasis and relapse. Lysosomes, traditionally recognized as central organelles for intracellular degradation and recycling, are indispensable for cellular homeostasis. Dysregulation of lysosomal function is intimately linked to various diseases, including cancer. In tumors, aberrant lysosomal activity can promote malignant progression through mechanisms such as altering metabolic pathways, enhancing lysosomal exocytosis, modulating drug resistance, and interfering with autophagy-lysosomal pathways. Recent studies have underscored the involvement of lysosomes in regulating CSC properties. This review synthesizes findings on lysosomal regulation of CSCs through the following aspects. (1) Lysosomes exert complex and critical bidirectional control over CSC stemness maintenance through three degradation pathways that are dependent on their degradative function. (i) The lysophagy pathway. This pathway exhibits dual roles. Activation can sustain CSC functions; for instance, in glioblastoma, hypoxia upregulates Gal-8 via the STAT3/HIF1α signaling axis to induce autophagy, supporting stem cell survival. In head and neck squamous cell carcinoma, degradation of GSK3β activates the Wnt pathway, enhancing stemness. Conversely, this pathway can suppress stemness by degrading stemness-related proteins such as BMI-1 and OCT4A, thereby impairing CSC self-renewal capacity. (ii) Mitophagy pathway. In non-small cell lung cancer stem cells, mitophagy-related mechanisms, such as the accumulation of mitochondrial DNA (mtDNA) activating the TLR9-Notch1-AMPK signaling axis, have been shown to promote CSC proliferation. (iii) Autophagosome-dependent lysosomal degradation pathway. This pathway directly regulates stemness-related proteins in a bidirectional manner. Enhanced degradative function can promote CSC properties, exemplified by the degradation of NUMB to activate Notch signaling. Conversely, attenuated degradative function can also enhance stemness by stabilizing oncoproteins (e.g., protecting Frizzled-1 from degradation to sustain Wnt signaling) or preventing the degradation of tumor suppressors (e.g., inhibiting Notch degradation). (2) Constituent proteins of lysosomes, including membrane proteins and luminal acid hydrolases, participate in regulating CSC stemness. Regarding membrane proteins, LAMP2A facilitates chaperone-mediated autophagy to maintain stemness in glioblastoma and ovarian cancer. V-ATPase, by maintaining an acidic luminal environment, promotes proliferation and drug resistance in glioma stem cells. Among hydrolases, cathepsins B and L are highly expressed in pancreatic and ovarian cancers and correlate with poor prognosis. Furthermore, targeting lysosomes to induce lysosomal membrane permeabilization (LMP) triggers lysosome-mediated cell death, presenting a potential therapeutic strategy for eradicating CSCs.(3) The acidic luminal environment, single-membrane structure, and the presence of transmembrane transporters (e.g., ABCA3) enable lysosomes to passively trap or actively uptake and sequester chemotherapeutic drugs. Subsequent drug extrusion via exocytosis confers drug resistance. In CSCs, this lysosome-mediated drug sequestration, often cooperating with autophagy, establishes multimodal drug resistance. Therefore, targeting lysosomal function represents a potential strategy to overcome therapy resistance. The central role of lysosomes in regulating CSC stemness and resistance positions them as highly promising therapeutic targets. Strategies aimed at disrupting lysosomal function to selectively eliminate CSCs include: inhibiting the lysosome-autophagy system using agents like IITZ or lovastatin; inducing lysosomal membrane permeabilization (LMP) with compounds such as hexamethylene amiloride to compromise membrane stability; and disrupting the acidic luminal environment using drugs like siramesine or the K/H transport compound 2. In conclusion, lysosomes critically regulate CSC stemness maintenance and drug resistance through degradative pathways, membrane protein functions, luminal hydrolase activities, and drug sequestration mechanisms. This redefines the lysosome from a traditional “waste disposal unit” to a “signal integration center” in CSCs. The duality and context-dependency of lysosomal function in CSCs offer novel insights into the heterogeneity observed across different tumors. Targeting lysosomal vulnerabilities—such as inducing LMP, disrupting acidity, or blocking autophagic flux—provides a strategy to bypass canonical CSC resistance mechanisms and directly trigger cell death. This establishes the lysosome as a key target to overcome CSC-mediated therapy resistance, paving the way for developing diverse candidate drugs and innovative combination therapies in oncology.

Background: Influenza A virus (IAV) is a negative-sense RNA virus of the Orthomyxoviridae family and is the etiological agent of a highly contagious acute respiratory disease that can lead to acute lung injury. Objective: To elucidate the molecular mechanisms of IAV infection, an integrative research approach combining gene expression profiling, multinetwork analysis, and in vivo experimental validations was employed. Methods: First, a series of network-based analyses were performed, including protein-protein interaction network construction, weighted gene co-expression network analysis, and subsequent gene set enrichment analysis, to identify the major underlying mechanisms of IAV infection. Following gene expression analysis, core targets, both direct and indirect regulators, were screened. An IAV (H1N1) strain A/PR/8/34-induced acute lung injury mouse model was constructed for in vivo validations. Batch one included two groups to evaluate findings from the multi-network analysis: Mock (n = 10; 5 males and 5 females) and IAV (n = 10; 5 males and 5 females). Batch two included three groups to assess the role of toll-like receptor 3 (TLR3) in IAV infection: Mock (n = 6; 3 males and 3 females), IAV (n = 6; 3 males and 3 females), and TLR3 inhibitor (n = 6; 3 males and 3 females). Body weight was measured on days 0, 3, and 5 after infection. On day 5, lung tissues were collected to assess viral load and histopathological changes. Key targets were examined using enzyme-linked immunosorbent assay, Western blotting, and immunofluorescence staining, both in sera and lung tissues. Results: IAV infection was significantly associated with dysregulation of the immune-inflammation system, such as the LTR, nucle-otide-binding oligomerization domain-(NOD) like receptor, retinoic acid-inducible gene I-like receptor, and nuclear factor kappa-B signaling pathways. Gene set enrichment analysis further indicated that the TLR and necroptosis signaling pathways played crucial roles in the progression of IAV infection (TLR signaling pathway normalized enrichment score = 2.3941, P = 1.00 × 10 ⁻¹⁰; necroptosis normalized enrichment score = 1.9421, P = 6.21 × 10 ⁻⁷). Among the core targets, TLR3 and mixed lineage kinase domain-like protein (MLKL) may regulate gene expression at the transcriptional level (all P < 0.05). In vivo validation using an IAV (PR8) infected acute lung injury mouse model demonstrated increased viral load and lung index, alveolar structural damage, and inflammatory cell infiltration. Immunofluorescence staining exhibited large gaps in Lamin B1 staining and breaches in Emerin signals following IAV-PR8 infection. Expression levels of TLR3, p-receptor-interacting serine/threonine-protein kinase 3 (RIPK3)/RIPK3, and p-mixed lineage kinase domain-like protein (MLKL)/MLKL proteins in lung tissues, as well as proinflammatory factors and mediators in sera, were significantly elevated after IAV infection. Moreover, enhanced neutrophil infiltration (myeloperoxidase) and citrullinated histone H3 (a neutrophil extracellular trap-specific marker), both established indicators of neutrophil extracellular trap formation, were observed. Notably, treatment with a TLR3 inhibitor significantly ameliorated IAV-induced acute lung injury by regulating necroptosis-related targets. Conclusion: Our study provides network-based in vivo evidence that TLR3-receptor-interacting serine/threonine-protein kinase 3-MLKL-mediated necroptosis may underlie IAV-induced acute lung injury and could serve as a potential therapeutic target in severe influenza cases.

ObjectiveTo construct a risk prediction model for chronic atrophic gastritis （CAG） that combines disease and syndrome by integrating spleen deficiency and blood stasis syndrome scores， gastric stem cell marker analysis， and network pharmacology and to elucidate the mechanism link between spleen deficiency， blood stasis， and gastric stem cell dysregulation. MethodsA total of 60 patients were stratified into high-risk CAG， low-risk CAG， and non-atrophic groups based on the operative link for gastritis assessment （OLGA）/operative link for gastric intestinal metaplasia assessment （OLGIM） stages. General data and syndrome scores of the patients were collected. Immunohistochemistry was employed to measure the protein levels of leucine-rich repeat-containing G protein-coupled receptor 5 （LGR5）， trefoil factor 2 （TFF2）， and β-catenin in gastric mucosa across groups. Transcriptomic data （GSE130823） from the Gene Expression Omnibus （GEO） database were analyzed to validate the expression of these molecular markers at the gene level. A Firth penalized maximum likelihood logistic regression model was employed to integrate clinical， molecular， and TCM syndrome data to develop a CAG risk prediction model. Finally， network pharmacology analysis was conducted on spleen-invigorating herbs （Astragali Radix， Atractylodis Macrocephalae Rhizoma， and Dioscorea Rhizoma） and blood-activating herbs （Hedyotis diffusa， Salviae Miltiorrhizae Radix et Rhizoma， and Curcumae Rhizoma） to identify overlapping targets between these herbs and differentially expressed genes between low-grade intraepithelial neoplasia （LGIN） and gastritis， thereby clarifying the role of spleen deficiency and blood stasis in CAG progression from a pharmacological perspective. ResultsHigh-risk CAG patients exhibited higher blood stasis scores （4.60±1.50，2.62±1.32， P<0.01）， progressive nuclear accumulation of β-catenin （A 0.28-0.53， P<0.01）， and an increased LGR5⁺/TFF2⁺ ratio （A 1.02-1.92， P<0.01）. Blood stasis scores were correlated with LGR5/TFF2 imbalance （P=0.03） and activation of the Wnt/β-catenin signaling pathway （CTNNB1 increase， log₂=0.78）. The integrated prediction model （blood stasis score≥5 + β-catenin>0.38 + LGR5/TFF2>1.5） outperformed a pure biomarker approach ［Area Under the Curve （AUC） 0.92，0.89， ΔAUC=0.03， P=0.02］. Moreover， network pharmacology revealed 66 overlapping targets between spleen-invigorating/blood-activating herbs and LGIN， which were functionally enriched in mucosal repair and anti-oxidative stress， and negatively correlated with the Wnt/β-catenin signaling pathway （P<0.01）. ConclusionThis study developed an integrated risk prediction model for CAG by combining TCM spleen deficiency and blood stasis syndromes with gastric stem cell molecular markers. Furthermore， it proposed for the first time the "blood stasis-Wnt/β-catenin-stem cell axis" hypothesis， preliminarily elucidating that spleen deficiency and blood stasis may exacerbate gastric stem cell dysregulation and promote malignant transformation of CAG through hypoxia-induced Wnt activation. This provides a theoretical foundation and a translational tool for risk stratification and multi-target TCM intervention in CAG.

ObjectiveTo construct a risk prediction model for chronic atrophic gastritis （CAG） that combines disease and syndrome by integrating spleen deficiency and blood stasis syndrome scores， gastric stem cell marker analysis， and network pharmacology and to elucidate the mechanism link between spleen deficiency， blood stasis， and gastric stem cell dysregulation. MethodsA total of 60 patients were stratified into high-risk CAG， low-risk CAG， and non-atrophic groups based on the operative link for gastritis assessment （OLGA）/operative link for gastric intestinal metaplasia assessment （OLGIM） stages. General data and syndrome scores of the patients were collected. Immunohistochemistry was employed to measure the protein levels of leucine-rich repeat-containing G protein-coupled receptor 5 （LGR5）， trefoil factor 2 （TFF2）， and β-catenin in gastric mucosa across groups. Transcriptomic data （GSE130823） from the Gene Expression Omnibus （GEO） database were analyzed to validate the expression of these molecular markers at the gene level. A Firth penalized maximum likelihood logistic regression model was employed to integrate clinical， molecular， and TCM syndrome data to develop a CAG risk prediction model. Finally， network pharmacology analysis was conducted on spleen-invigorating herbs （Astragali Radix， Atractylodis Macrocephalae Rhizoma， and Dioscorea Rhizoma） and blood-activating herbs （Hedyotis diffusa， Salviae Miltiorrhizae Radix et Rhizoma， and Curcumae Rhizoma） to identify overlapping targets between these herbs and differentially expressed genes between low-grade intraepithelial neoplasia （LGIN） and gastritis， thereby clarifying the role of spleen deficiency and blood stasis in CAG progression from a pharmacological perspective. ResultsHigh-risk CAG patients exhibited higher blood stasis scores （4.60±1.50，2.62±1.32， P<0.01）， progressive nuclear accumulation of β-catenin （A 0.28-0.53， P<0.01）， and an increased LGR5⁺/TFF2⁺ ratio （A 1.02-1.92， P<0.01）. Blood stasis scores were correlated with LGR5/TFF2 imbalance （P=0.03） and activation of the Wnt/β-catenin signaling pathway （CTNNB1 increase， log₂=0.78）. The integrated prediction model （blood stasis score≥5 + β-catenin>0.38 + LGR5/TFF2>1.5） outperformed a pure biomarker approach ［Area Under the Curve （AUC） 0.92，0.89， ΔAUC=0.03， P=0.02］. Moreover， network pharmacology revealed 66 overlapping targets between spleen-invigorating/blood-activating herbs and LGIN， which were functionally enriched in mucosal repair and anti-oxidative stress， and negatively correlated with the Wnt/β-catenin signaling pathway （P<0.01）. ConclusionThis study developed an integrated risk prediction model for CAG by combining TCM spleen deficiency and blood stasis syndromes with gastric stem cell molecular markers. Furthermore， it proposed for the first time the "blood stasis-Wnt/β-catenin-stem cell axis" hypothesis， preliminarily elucidating that spleen deficiency and blood stasis may exacerbate gastric stem cell dysregulation and promote malignant transformation of CAG through hypoxia-induced Wnt activation. This provides a theoretical foundation and a translational tool for risk stratification and multi-target TCM intervention in CAG.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Objective:To explore the characteristics of nutrition self-management of home-based elderly chronic obstructive pulmonary disease (COPD) patients based on user persona, in order to provide reference for accurate home nutrition management.Methods:From July to December 2023, home-based elderly COPD patients in the Department of Respiratory and Critical Care Medicine of General Hospital of Ningxia Medical University were selected by convenience sampling method. The Mini Nutritional Assessment, COPD Assessment Test, Modified Medical Research Council Dyspnea Scale, Physical Activity Rating Scale-3, COPD Patients Self-Management Scale were used to conduct questionnaire survey. The SPSS 26.0 software was used to analyze the influencing factors of patients′ self-management of nutrition. Attributes with statistical significance ( P<0.05) were extracted as labels, and the visualization of patients′ self-management of nutrition portraits was completed in the form of pictures combined with labels. Results:A total of 320 questionnaires were distributed, and 309 valid questionnaires were collected. Among 309 home-based elderly COPD patients, there were 210 males and 99 females with an age of (69.14 ± 6.84) years old. According to the data analysis results, three dimensions of natural attributes, social attributes, and behavioral tracks were artificially extracted to construct three types of nutritional self-management user persona for home-based elderly COPD patients, respectively namely blind management type, independent attempt type, and powerless type.Conclusions:There are great differences in the nutritional status and self-management of home-based elderly patients with COPD. Accurate management measures can be developed based on user persona analysis to improve their nutritional status.