Search Results (285)

Background/Objectives: This study was conducted to analyze the associations between vascular endothelial growth factor (VEGF) serum concentrations and immunological biomarkers, inflammatory parameters, classical atherosclerosis risk factors, and cardiovascular manifestations in systemic lupus erythematosus (SLE) patients. Methods: The project included 83 individuals suffering from SLE, with 20 healthy individuals as controls. The serum levels of VEGF were determined through the ELISA method using R&D Systems tests. Laboratory markers, autoantibody profiles, traditional atherosclerotic risk factors, and organ manifestations were evaluated. Atherosclerotic changes were determined based on several indices including carotid intima-media thickness, ankle-brachial index and high resistance index assessments. Results: The reference range of serum VEGF concentrations was established based on the 25th and 75th percentiles obtained in the controls. High VEGF levels were significantly correlated with the presence of selected anti-phospholipid antibodies such as anti-prothrombin (OR = 10.7; 95%CI: 2.1–53.4) and anti-beta2 glycoprotein I (OR = 3.5; 95%CI: 1.1–10.8), as well as cardiac disorders (OR = 8.0; 95%CI: 1.6–39.5). On the other hand, low concentrations of VEGF were significantly related to lower frequencies of anti-double-stranded DNA antibodies (OR = 0.31; 95%CI: 0.11–0.91) and anti-endothelial cell antibodies (OR = 0.30; 95%CI: 0.11–0.85). Patients with low VEGF levels showed significantly reduced risks of atherosclerotic lesions (OR = 0.24; 95%CI: 0.04–0.99) and vasculitis development (OR = 0.17; 95%CI = 0.03–0.91). Conclusions: In conclusion, VEGF’s pathogenetic role in SLE and SLE-related atherothrombosis is manifested in close correlation with aPLs which may enhance their direct impact on endothelium. High VEGF levels are helpful for identifying cardiovascular risk in patients, while low concentrations indicate lower disease activity, as well as a lower risk of organ involvement. Full article

Background: Most of the existing hyperpolarized (HP) ¹³C MRI analyses use univariate rate maps of pyruvate-to-lactate conversion (k_PL), and radiomic-style multiparametric models extracting complex, higher-order features remain unexplored. Purpose: To establish a multivariate framework based on whole abdomen/pelvis HP ¹³C-pyruvate MRI and evaluate the association between multiparametric features of metabolism (MFM) and clinical outcome measures in advanced and metastatic prostate cancer. Methods: Retrospective statistical analysis was performed on 16 participants with metastatic or local-regionally advanced prostate cancer prospectively enrolled in a tertiary center who underwent HP-pyruvate MRI of abdomen or pelvis between November 2020 and May 2023. Five patients were hormone-sensitive and eleven were castration-resistant. GMP-grade [1-¹³C]pyruvate was polarized using a 5T clinical-research DNP polarizer, and HP MRI used a set of flexible vest-transmit, array-receive coils, and echo-planar imaging sequences. Three basic metabolic maps (k_PL, pyruvate summed-over-time, and mean pyruvate time) were created by semi-automatic segmentation, from which 316 MFMs were extracted using an open-source, radiomic-compliant software package. Univariate risk classifier was constructed using a biologically meaningful feature (k_PL,median), and the multivariate classifier used a two-step feature selection process (ranking and clustering). Both were correlated with progression-free survival (PFS) and overall survival (OS) (median follow-up = 22.0 months) using Cox proportional hazards model. Results: In the univariate analysis, patients harboring tumors with lower-k_PL,median had longer PFS (11.2 vs. 0.5 months, p < 0.01) and OS (NR vs. 18.4 months, p < 0.05) than their higher-k_PL,median counterparts. Using a hypothesis-generating, age-adjusted multivariate risk classifier, the lower-risk subgroup also had longer PFS (NR vs. 2.4 months, p < 0.002) and OS (NR vs. 18.4 months, p < 0.05). By contrast, established laboratory markers, including PSA, lactate dehydrogenase, and alkaline phosphatase, were not significantly associated with PFS or OS (p > 0.05). Key limitations of this study include small sample size, retrospective study design, and referral bias. Conclusions: Risk classifiers derived from select multiparametric HP features were significantly associated with clinically meaningful outcome measures in this small, heterogeneous patient cohort, strongly supporting further investigation into their prognostic values. Full article

Background and Objectives: Breast cancer accounts for 12.5% of all new cancer cases in women worldwide. Early detection significantly improves survival rates, but traditional biomarkers like CA 15-3 and HER2 lack sensitivity and specificity, particularly for early-stage disease. Advances in metabolomics and machine learning, particularly explainable artificial intelligence (XAI), offer new opportunities for identifying robust biomarkers and improving diagnostic accuracy. This study aimed to identify and validate serum-based metabolic biomarkers for breast cancer using advanced metabolomic profiling techniques and a Light Gradient Boosting Machine (LightGBM) model. Additionally, SHapley Additive exPlanations (SHAP) were applied to enhance model interpretability and biological insight. Materials and Methods: The study included 103 breast cancer patients and 31 healthy controls. Serum samples underwent liquid and gas chromatography–time-of-flight mass spectrometry (LC-TOFMS and GC-TOFMS). Mutual Information (MI), Sparse Partial Least Squares (sPLS), Boruta, and Multi-Objective Feature Selection (MOFS) approaches were applied to the data for biomarker discovery. LightGBM, AdaBoost, and Random Forest were employed for classification and to identify class imbalance with the Synthetic Minority Oversampling Technique (SMOTE). SHAP analysis ranked metabolites based on their contribution to model predictions. Results: Compared to other feature selection approaches, the MOFS approach was more robust in terms of predictive performance, and metabolites identified by this method were used in subsequent analyses for biomarker discovery. LightGBM outperformed the AdaBoost and Random Forest models, achieving 86.6% accuracy, 89.1% sensitivity, 84.2% specificity, and an F1-score of 87.0%. SHAP analysis identified 2-Aminobutyric acid, choline, and coproporphyrin as the most influential metabolites, with dysregulation of these markers associated with breast cancer risk. Conclusions: This study is among the first to integrate SHAP explainability with metabolomic profiling, bridging computational predictions and biological insights for improved clinical adoption. This study demonstrates the effectiveness of combining metabolomics with XAI-driven machine learning for breast cancer diagnostics. The identified biomarkers not only improve diagnostic accuracy but also reveal critical metabolic dysregulations associated with disease progression. Full article

Camellia oil, rich in monounsaturated fatty acids, squalene, tocopherols, and polyphenols, is highly valued for its nutritional benefits. However, its high market value and regional variations have led to frequent adulteration, highlighting the need for rapid, non-destructive methods for authentication, geographical traceability, and quality assessment. This study employed portable Raman spectroscopy combined with Partial Least Squares Discriminant Analysis (PLS-DA) and Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS) to differentiate camellia oil from other edible oils and evaluate its thermal and photo-oxidative stability. PLS-DA, based on VIP-selected spectral variables, effectively distinguished camellia oil, with Raman bands near 1250 cm⁻¹ and 1650 cm⁻¹ contributing significantly. A unique peak at 1525 cm⁻¹, observed in samples from Gongcheng, Guangxi, was associated with carotenoids and served as a potential marker for geographical traceability. MCR-ALS modeling revealed significant reductions in the 1650 cm⁻¹ and 1525 cm⁻¹ peaks when temperatures exceeded 150 °C, indicating degradation of unsaturated fatty acids and carotenoids. Under UV exposure, the 1525 cm⁻¹ peak declined sharply and nearly disappeared after 24 h, suggesting rapid carotenoid degradation via photooxidation. Extended UV treatment also affected the 1650 cm⁻¹ peak and led to oxidative product accumulation. Overall, this study demonstrates the feasibility of integrating Raman spectroscopy with chemometric analysis for efficient oil classification, traceability, and stability monitoring, offering a valuable tool for food quality control and market supervision. Full article

The evaluation of region-specific aroma characteristics in green tea remains critical for quality control. This study systematically analyzed eight Tongcheng Xiaohua tea samples (standard and premium batches) originating from four distinct regions using sensory analysis, electronic nose (E-nose), headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME-GC-MS), and chemometrics. The E-nose results demonstrated that the volatile characteristics of Tongcheng Xiaohua tea exhibit distinct geographical signatures, confirming the regional specificity of its aroma. HS-SPME-GC-MS identified 66 volatile metabolites across samples, with 18 key odorants (OAV > 1) including linalool, geraniol, (Z)-jasmone, and β-ionone driving aroma profiles. The partial least squares–discriminant analysis (PLS-DA) model, combined with variable importance in projection (VIP) scores and OAV, identified seven compounds that effectively differentiate the origins, among which α-pinene and β-cyclocitral emerged as novel markers imparting unique regional characteristics. Further comparative analysis between standard and premium grades revealed 2-methyl butanal, 3-methyl butanal, and dimethyl sulfide as main differential metabolites. Notably, the influence of geographical origin on metabolite profiles was found to be more significant than batch effects. These findings establish a robust analytical framework for origin traceability, quality standardization, and flavor optimization in tea production, providing valuable insights for the tea industry. Full article

Background: Transient tachypnea of the newborn (TTN) is traditionally viewed as a disorder of delayed lung fluid clearance, but emerging evidence suggests inflammatory involvement. Aim: This study investigated systemic inflammatory indices [(systemic immune-inflammation index (SII-i), systemic inflammation response index (SIR-i), neutrophil-to-lymphocyte ratio (NL-r), and platelet-to-lymphocyte ratio (PL-r)] and underlying mechanisms in TTN pathogenesis for the first time. Methods: This retrospective case–control study included 199 neonates (123 with TTN and 76 healthy controls) admitted between 2022 and 2025 to a tertiary care hospital. Complete blood count parameters were collected within the first two hours of life. Inflammatory indices were calculated and compared between groups. Subgroup analyses were conducted based on gestational age (late preterm vs. term) and mode of delivery (cesarean vs. vaginal). Results: Although not statistically significant, TTN infants showed a trend toward higher inflammatory indices with median NL-r (2.54 vs. 1.75, p = 0.197) and SII-i (729,307.83 vs. 373,593.50, p = 0.276). Term TTN infants had higher NL-r (3.08 vs. 2.04, p = 0.022) and SII-i (729,147.74 vs. 538,928.30, p = 0.133) than late preterm infants. SIR-i and NL-r values were higher in the full-term group than in the early-term and late-preterm groups (p = 0.014, p = 0.022, respectively). Cesarean births showed higher NL-r (3.20 vs. 2.33, p = 0.049) and SII-i (p = 0.040) than vaginal deliveries. Strong correlations existed between SII-I, NL-r (r = 0.886, p < 0.01), and SII-i, SIR-i (r = 0.817, p < 0.01). Conclusions: Elevated inflammatory indices in neonates with TTN, particularly in term infants and those delivered vaginally, suggest a supportive/potential role for systemic inflammation in TTN pathophysiology. These markers may serve as potential supplementary markers for risk stratification, though further prospective validation is required to confirm their clinical relevance. These findings suggest that the early assessment of systemic inflammatory indices may assist clinicians in identifying neonates at risk for TTN, thereby guiding initial respiratory support strategies. Full article

Plant height is a key agronomic trait in soybeans, directly influencing yield potential and agronomic performance. In this study, the tall-stem cultivar Heinong 63 and the dwarf-stem cultivar Longken 3077, along with their F₂ populations, were used as experimental materials. A preliminary mapping using the bulk segregant analysis sequencing (BSA-Seq) approach enabled us to locate the target locus within a 1.8 Mb interval, which was subsequently narrowed to a 48.3 kb region using simple sequence repeat (SSR) and insertion and deletion (InDel) markers. The interval was designated as PH19-31 and contained nine annotated genes. One InDel marker, PL7, was developed within this fine-mapped region. Based on an expression analysis of the nine candidate genes, Glyma.19G230000 and Glyma.19G230200 were identified as potential regulators of plant height in soybeans. This study provides valuable materials and technical support for the cloning of plant height-related genes and the molecular breeding of soybeans. Full article

Oral diseases are highly prevalent among domestic cats, with microbiota dysbiosis as a primary etiological factor. However, effective microbiota-targeted interventions remain limited. This study evaluated the efficacy of a dietary supplement combining propolis and lysozyme (PL) in mitigating feline oral health issues, based on a cohort of 24 cats divided equally into placebo, treatment, and healthy control groups (n = 8 per group). Supragingival microbiota were analyzed via 16S rRNA gene sequencing, alongside assessments of volatile sulfur compounds (VSCs), oral health indices, and systemic inflammatory, oxidative, and immune markers. After 28 days of intervention, cats receiving PL supplementation demonstrated significant improvements, including a 35.4% reduction in VSCs and notable decreases in debris (34.9%), plaque (51.2%), and gingival indices (61.0%). Systemically, MDA and TNF-α levels decreased, while SOD, T-AOC, and IL-4 increased. Microbiota analysis revealed suppression of Porphyromonas and Selenomonas and enrichment of Moraxella and Bergeyella. Reductions in VSCs, gingival index, and TNF-α were correlated with lower Porphyromonas abundance, while Moraxella and Luteimonas were positively associated with antioxidant status. Functional predictions indicated downregulation of virulence-related pathways and increased expression of glutathione reductase. These findings highlight PL’s potential as a natural, microbiota-based intervention that improves feline oral health and modulates the oral–systemic axis, supporting its application in integrative oral care strategies. Full article

This study investigates the impact of using Lactiplantibacillus plantarum and Saccharomyces cerevisiae, either individually or in co-culture, on the fermentation of rose beverage. We comprehensively analyzed the resulting changes in quality characteristics and volatile compound profiles. Fermentation significantly altered the physicochemical properties, appearance, color, and free amino acid/organic acid content. Both microbial strains significantly increased total polyphenols and flavonoid content, with co-fermentation exhibiting a more pronounced effect compared to single-strain fermentations. Furthermore, the volatile compounds in rose beverages fermented with different microorganisms were characterized by an electronic nose (E-nose) and headspace–solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC-MS). E-nose analysis demonstrated distinct volatile profiles distinguishing the four fermentation samples. HS-SPME/GC-MS identified a total of 245 volatile compounds, among which alcohols constituted the most abundant class. Integrating GC-MS data with odor activity value (OAV ≥ 1) analysis pinpointed 34 key aroma compounds. Partial least-squares discriminant analysis (PLS-DA) based on variable importance in projection (VIP) identified eight key volatile markers: eugenol, phenylethyl alcohol, (E)-3,7-dimethyl-2,6-octadienoic acid, methyleugenol, ethyl octanoate, citronellol, D-citronellol, and 2,4-bis(1,1-dimethylethyl)phenol. These findings provide valuable insights into the microbial influence on rose beverage quality and offer a theoretical basis for optimizing industrial fermentation processes. Full article

Two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF MS) was employed to analyze the volatile flavor compounds (VOCs) of Tricholoma matsutake samples from six different geographical regions: CX (Chuxiong), DL (Dali), DQ (Diqing), JL (Yanji), SC (Xiaojin) and XZ (Linzhi). The result indicate that a total of 2730 kinds of VOCs were identified from the fruiting bodies of six T. matsutake samples. The primary types of volatile organic compounds identified were 349 alcohols, 92 aldehydes, 146 carboxylic_acids, 311 esters, 742 organoheterocyclic compounds, 630 hydrocarbons, 381 ketones, 51 organic acids, and 28 derivatives and organosulfur compounds. Furthermore, PCA and PLS-DA analysis from the GC×GC-ToF-MS showed that samples from different regions could be distinguished by their VOCs. Network analysis revealed that 33 aroma compounds were identified as markers for distinguishing the samples from the six regions. The sensory attributes sweet, fruity, green, waxy, and floral were found to be more significant to the flavor profile of T. matsutake. 1-Nonanol, 2-Nonanone, Nonanoic acid, ethyl ester, 1-Undecanol, 2-Undecanone, Octanoic acid, ethyl ester, 2H-Pyran, and tetrahy-dro-4-methyl-2-(2-methyl-1-propenyl)- primarily contribute to the differences in the aroma characteristics among six T. matsutake samples. The results also provide a theoretical and practical foundation for the flavor compounds of these precious edible fungi in different regions. Full article

Background: Mesenchymal stem cell-based therapy may be indicated in ischaemic heart disease. The use of autologous adipose-derived mesenchymal stromal cells (AdMSCs) offers regenerative potential due to their paracrine effects. The aim of this study was to expand and characterise adult human thymus-derived MSCs harvested during open heart surgery with respect to their stem cell and paracrine properties. Methods: Enzymatically and non-enzymatically isolated human thymic AdMSCs (ThyAdMSCs) were cultured in xeno-free media containing pooled human platelet lysate (pPL). MSC characterisation was performed. Ex vivo expanded ThyAdMSCs were differentiated into three lineages. Proliferative capacity and immunomodulatory properties were assessed by proliferation assays and mixed lymphocyte reaction, respectively. Gene expression analysis was performed by qPCR. Results: Both isolation methods yielded fibroblast-like cells with plastic adherence and high proliferation. Flow cytometry revealed distinct expression of MSC markers in the absence of haematopoietic cell surface markers. Ex vivo expanded ThyAdMSCs could be differentiated into adipocytes, osteocytes, and chondrocytes. Activated peripheral blood mononuclear cells were significantly reduced when co-cultured with ThyAdMSCs, indicating their ability to inhibit immune cells in vitro. Gene expression analysis showed significantly less IFNγ and TNFα, indicating an alteration of the activated and pro-inflammatory state in the presence of ThyAdMSCs. Conclusions: These results demonstrate an efficient method to generate AdMSCs from human thymus. These MSCs have a strong immunomodulatory capacity and are, therefore, a promising cell source for regenerative medicine. The culture conditions are crucial for cells to proliferate in culture. Further research could explore the use of ThyAdMSCs or their secretome in surgical procedures. Full article

Background/Objectives: Endothelial cell (EC) culture relies on specialized and commercial media with distinct growth supplement compositions. These media are expensive and must be imported, increasing the time to effective use. Human platelet lysate (PL) and platelet lysate serum (PLS) supplemented media are emerging alternatives to commercial media. Methods: Umbilical cords were collected, and human umbilical vein endothelial cells (HUVEC) were isolated and cultured using different media formulations, using Endothelial Cell Growth, Promocell^® (ECGM-Promocell^®) commercial medium, and media supplemented with PL and PLS. Results: A mixed medium combining DMEM-F12 + PLS and ECGM-Promocell^® maintained EC viability, adhesion, and proliferation. Introducing a PL-derived protein substrate enhanced cell adhesion and proliferation by simulating an extracellular matrix. Flow cytometry revealed positive CD31, CD144, and CD146 markers in cells cultured with ECGM-Promocell^® and the mixed medium, with or without the PL-protein substrate. Conclusions: These findings suggest that the mixed medium, especially with the PL protein substrate, offers a cost-effective and efficient approach for EC culture and proliferation, holding promise for research and therapeutic applications. Full article

Background/Objectives: Strawberries are highly appreciated for their rich phytochemical composition, but rapid postharvest deterioration limits their shelf life and nutritional quality. This study aimed to investigate the metabolic changes occurring in both strawberry fruits and leaves during storage and to evaluate the NADPH oxidase 2 (NOX2) inhibitory potential of strawberry-derived metabolites. Methods: Untargeted LC-MS/MS analysis was conducted on fruit and leaf tissues stored at 8 ± 0.5 °C. A total of 37 metabolites were identified, including organic acids, phenolic acids, flavonoids, and hydroxycinnamic acid derivatives. Multivariate statistical analyses (ANOVA, PLS-DA, and volcano plots) were used to assess temporal and tissue-specific metabolic shifts. Additionally, a machine learning-based predictive model was applied to evaluate the NOX2 inhibitory potential of 24 structurally characterized metabolites. Results: Storage induced significant and tissue-specific metabolic changes. In fruits, malic acid, caffeic acid, and quercetin-3-glucuronide showed notable variations, while ellagic acid aglycone and galloylquinic acid emerged as prominent markers in leaves. The predictive model identified 21 out of 24 metabolites as likely NOX2 inhibitors, suggesting potential antioxidant and anti-inflammatory bioactivity. Conclusions: These findings provide new insights into postharvest biochemical dynamics in both strawberry fruits and leaves. The results highlight the value of leaves as a source of bioactive compounds and support their potential valorization in functional food and nutraceutical applications. Full article

Currently, the main types of roses circulating in China include Jinbian Rose, Kushui Rose and Pingyin Rose. Each type of rose has slight differences in usage and efficacy. There are many varieties of roses, and the quality of rose essential oils varies greatly. Almost no research has systematically studied the essential oils of various roses. In this experiment, three types of roses (Jinbian Rose, Kushui Rose, and Pingyin Rose) were selected as research subjects based on their efficacy and variety in the market. Essential oils were extracted from the three types of roses using hydrodistillation. Gas chromatography-mass spectrometry (GC-MS) was used to qualitatively analyze the volatile substances in the essential oils of different varieties of roses. The three types of rose essential oils were identified and differentiated using chemometric methods (including HCA, PCA, PLS-DA, and OPLS-DA). On the one hand, based on the GC-MS analysis results, 40, 48, and 40 volatile components were detected in Jinbian Rose, Kushui Rose, and Pingyin Rose, respectively. The chemical compositions were primarily dominated by macromolecular compounds such as long-chain alkanes, organic acids, and esters. On the other hand, eight markers with significant identification values were identified to distinguish among the three types of roses. In conclusion, based on GC-MS analysis and chemometric methods, this experiment distinguishes and identifies three types of roses from the perspective of essential oil components for developing an effective strategy for the identification of rose varieties. Full article

Spermatozoa were isolated from the seminal fluid using washing (wash), post-capacitation (POS), and swim-up (SU) techniques, followed by analysis through Surface-Enhanced Raman Spectroscopy (SERS). Density gradient and swim-up methods were applied to 35 semen samples to validate sperm quality. The resulting spectra showed notable variations at 408 cm⁻¹ (S–S stretch attributed to lysozyme) and 728 cm⁻¹ (associated with DNA alterations and methylation). These spectral markers were incorporated into partial least squares discriminant analysis (PLS-DA) models to distinguish among sperm populations prepared by different methods. One PLS-DA model differentiated wash from POS and SU, attaining 86% sensitivity and 91% accuracy. Another model distinguished between POS and SU, achieving 77% sensitivity and 74% accuracy. The combined use of SERS and multivariate analysis offers a promising alternative for assessing sperm quality, supported by motility assessments in 35 validated samples. This approach could enhance both the accuracy and efficiency of reproductive diagnostics. Full article