BackgroundThis study integrated dietary pattern analysis with serum proteomics to identify diet-related molecular signatures associated with gestational diabetes mellitus (GDM) in Miao pregnant women.MethodsA 1:1 matched case–control study was conducted among 78 Miao pregnant women (39 GDM cases and 39 controls). Dietary patterns were derived using principal component analysis. Serum proteomics was performed using data-independent acquisition mass spectrometry. Associations were evaluated using conditional logistic regression and linear mixed-effects models. LASSO penalized logistic regression was used for exploratory feature selection, followed by nested cross-validation to assess internal discriminative performance and an exploratory multivariable analysis.ResultsHigher adherence to a processed dietary pattern was associated with higher odds of GDM (OR = 2.33, 95% CI: 1.08–5.04). Proteomic analysis identified 34 candidate differentially expressed proteins enriched in lipid metabolism and inflammatory pathways. The processed dietary pattern was inversely associated with APOM (β = −0.308, p = 0.036) and showed a borderline inverse association with SAA4 (β = −0.285, p = 0.052). A leave-one-matched-pair-out nested LASSO feature-selection analysis using all 344 quality-controlled proteins yielded an internal AUC of 0.953 (95% CI: 0.894–0.992). SAA4 was selected in all 39 outer iterations, whereas selection frequencies varied across other proteins. APOM was retained for subsequent exploratory integrative analysis based primarily on its association with the processed dietary pattern, PPI-hub status, and biological relevance.ConclusionA processed dietary pattern was associated with GDM and altered circulating APOM/SAA4 profiles in Miao pregnant women. Nested cross-validation provided an exploratory assessment of proteomic feature stability using all 344 quality-controlled proteins. The resulting internal discrimination should be interpreted cautiously because the upstream QC correction/normalization incorporated GDM group information and was completed before cross-validation. The APOM/SAA4–diet model was developed as a proof-of-concept analysis only and should not be interpreted as a clinically applicable prediction model. Larger independent and prospective cohorts are required for external validation.
IntroductionThe accumulation of advanced glycation end products (AGEs) is a key driver of skin aging, accelerating the process through oxidative stress, inflammation, and disruption of extracellular matrix (ECM) homeostasis. Cerasus serrulata 'Sekiyama' Kanzan cherry blossom (KCB) is rich in bioactive compounds with antioxidant and anti-glycation potential. However, its compositional variations across flowering stages and their functional relevance remain unclear.MethodsThis study systematically characterized the chemical profile of KCB using UPLC-QTOF-MS and monitored six major active components across four flowering stages using UPLC-MS/MS. The anti-glycation, antioxidant, tyrosinase, and collagenase activities of the identified compounds were evaluated in vitro. The protective effects of KCB extract (KCBE) and major active compounds were further investigated in a methylglyoxal (MGO)-induced human skin fibroblast senescence model.ResultsThirteen compounds were identified, including one organic acid, five flavonoid glycosides, and seven phenolic acids. The half-bloom stage (KCB3) contained the highest levels of the six quantified compounds. 1-O-caffeoyl glucoside (CG) was the predominant phenolic acid (8.025 ± 0.203%), while quercetin 3-O-6′′-O-malonyl-β-glucopyranoside (QMG) was the major flavonoid (1.155 ± 0.035%). QMG showed strong anti-glycation activity (IC50 = 0.41 ± 0.01 mM), whereas CG exhibited strong tyrosinase (IC50 = 0.19 ± 0.03 mM) and collagenase inhibition (IC50 = 2.51 ± 0.90 mM). KCBE, QMG, and CG significantly alleviated MGO-induced cellular senescence, reduced intracellular ROS, restored F-actin organization, and promoted type I collagen deposition. These effects were associated with suppression of RAGE/NF-κB signaling, normalization of the Nrf2/HO-1-mediated antioxidant response, and restoration of ECM-related gene expression.DiscussionHalf-bloom KCB exhibits prominent anti-glycation and anti-skin-aging activities, with CG and QMG representing major bioactive constituents. These findings indicate that KCB and its characteristic phenolic acid and flavonoid constituents may have potential as natural functional ingredients for skin health.
BackgroundMalnutrition is highly prevalent in patients with colorectal cancer and is associated with adverse postoperative outcomes and shortened survival. However, the comparative predictive performance of commonly used nutritional assessment tools—PG-SGA, ESPEN, and GLIM criteria—remains unclear.MethodsA total of 1,258 patients who underwent radical resection for colorectal cancer were retrospectively enrolled. Malnutrition was diagnosed simultaneously using the PG-SGA, ESPEN, and GLIM criteria. Agreement among the three tools was evaluated using Cohen’s kappa coefficient. Multivariable logistic regression, an exploratory random forest analysis, and Cox proportional hazards models were applied. For the logistic regression models, ROC curve analysis and pairwise AUC comparisons using DeLong’s test were performed; for the Cox models, bootstrap-based C-index comparisons were conducted. Propensity score matching (PSM) was performed for the GLIM criterion as a post hoc sensitivity analysis to explore the association between GLIM-defined malnutrition and clinical outcomes.ResultsThe prevalence of malnutrition defined by PG-SGA, ESPEN, and GLIM was 24.7%, 15.7%, and 29.9%, respectively, with pairwise agreements ranging from moderate to substantial. All three criteria were independent risk factors for postoperative complications, with GLIM having the highest odds ratio (OR = 1.869, p < 0.001). AUC comparison further showed that the GLIM-incorporated model achieved the numerically highest AUC (0.781), with a significantly higher AUC than the ESPEN-based model (p = 0.023), whereas no significant difference was observed between GLIM and PG-SGA (p = 0.172). For OS, PG-SGA (HR = 1.364, p = 0.014) and GLIM (HR = 1.415, p = 0.004) were independent prognostic factors, whereas ESPEN was not (p = 0.129). Bootstrap C-index comparisons showed that the GLIM-based model provided modestly better prognostic discrimination than both the PG-SGA- and ESPEN-based models (both p < 0.05), although the absolute C-index improvement was small (approximately 0.015). After PSM balancing baseline characteristics, GLIM-defined malnutrition remained significantly associated with prolonged postoperative hospital stay, higher complication rates, and reduced 5-year overall survival.ConclusionThe three malnutrition diagnostic criteria are not interchangeable. For postoperative complications, GLIM demonstrated better discriminative ability than ESPEN but was comparable to PG-SGA. For long-term OS, GLIM provided modestly better prognostic discrimination than both PG-SGA and ESPEN, although the absolute improvement was small. These findings support the potential clinical utility of GLIM for perioperative nutritional risk assessment; however, the clinical relevance of these relatively small performance differences warrants further validation.
BackgroundEvidence on the associations between the Mediterranean-Dietary Approaches to Stop Hypertension (DASH) Intervention for Neurodegenerative Delay (MIND) diet adherence, physical activity (PA), and cognitive function in Chinese older adults is limited. This study aimed to examine these associations and their potential interactions among community-dwelling older adults in Henan Province, China.MethodsParticipants were recruited from 17 districts/counties in Henan Province, China, using the multistage stratified probability-proportional-to-size (PPS) sampling method. MIND diet adherence was assessed using a food frequency questionnaire (FFQ), and PA was assessed based on self-reported exercise frequency and duration. Cognitive function was measured using the Chinese version of the Mini-Mental State Examination (MMSE). Weighted generalized linear models (GLMs) were used to examine the associations between MIND diet adherence, PA, and their potential interaction and MMSE scores.ResultsHigher MIND diet scores were significantly associated with higher MMSE scores (β = 0.259, 95% CI: 0.154–0.364, p < 0.001), whereas PA showed no significant independent association (β = 0.016, 95% CI: −0.017 to 0.049, p = 0.335). No significant interaction was observed between MIND diet adherence and PA regarding global cognitive function (β = −0.005, 95% CI: −0.013 to 0.002, p = 0.152). Domain-specific analyses showed significant associations between MIND diet scores and registration, attention and calculation, and recall (all β > 0, all p < 0.05). However, no significant interaction between MIND diet adherence and PA was observed for any domain (all p > 0.05).ConclusionHigher adherence to the MIND diet was independently associated with better cognitive function among community-dwelling older adults in central China. These findings suggest that adherence to the MIND diet may be a practical strategy for promoting cognitive health in aging populations.
BackgroundThe double burden of malnutrition (DBM) refers to the coexistence of different forms of malnutrition, particularly undernutrition or micronutrient deficiencies alongside overweight or obesity, within individuals, households, or populations. This study aimed to: i) determine the prevalence of the double burden of malnutrition defined as the coexistence of anemia and excess weight, among schoolchildren in southern Peru; ii) investigate factors associated with the double burden of malnutrition, excess weight, and central obesity; and iii) characterize the school food environment.MethodsA cross-sectional study was conducted among 656 schoolchildren aged 5–13 years from six schools in the province of Ica, Peru. Height-for-age (HAZ), weight-for-age (WAZ), BMI-for-age (BAZ), waist-to-height ratio (WHtR), and hemoglobin concentration were assessed using standardized criteria. The school food environment was evaluated using a structured observational checklist. Multivariable logistic regression models were used to examine factors associated with DBM, excess weight, and central obesity, while a general linear model assessed factors associated with hemoglobin concentration.ResultsStunting (1.4%), underweight (0.5%) and thinness (1.1%) were uncommon, whereas both excess weight and central obesity (WHtR ≥0.5) affected 50.9% of the schoolchildren. Anemia was identified in 23.5% of participants, and the coexistence of anemia and excess weight (DBM) was observed in 9.9%. After adjustment, anemia was independently associated with lower odds of excess weight, whereas urban residence and older age (11–13 years) were associated with lower odds of central obesity. The school food environment was characterized by the widespread availability of energy-dense, ultra-processed foods and the limited availability of healthier alternatives.ConclusionSchoolchildren in the study population exhibited a nutritional profile characterized by the coexistence of anemia and a high burden of excess weight, consistent with nutritional patterns described in populations undergoing the nutrition transition. These findings provide baseline evidence to support integrated school-based nutrition interventions and evidence-based public health policies aimed at addressing multiple forms of malnutrition.
