Search Results (57,334)

Background/Objectives: As birth weight is related to later obesity risk, its associations with maternal pre-pregnancy body mass index (BMI) and leptin values in serum during pregnancy are of interest for obesity prevention. This study aimed to describe the association of leptin levels in maternal circulation and cord blood as well as pre-pregnancy BMI (pBMI) with infant anthropometry at birth and until the age of four months. Methods: Data on maternal pBMI, at delivery and four months after birth, and on infant weight and length at delivery and at age four months were collected in an observational study in Bangkok, Thailand. In a subgroup of 38 mother–infant dyads, leptin was measured in maternal blood serum at delivery and infant age 4 months and in cord and infant serum at 4 months. Associations were tested with correlation and multiple linear regression analyses in this explorative study. Results: The maternal serum leptin was 32.4 ± 17.8 ng/mL at delivery and 11.1 ± 8.9 ng/mL at four months (p < 0.001 for difference) and correlated (r = 0.45). Cord serum leptin was significantly higher in female than male infants (17.5 ± 9.8 ng/mL vs. 7.7 ± 4.9 ng/mL, p < 0.05) and not related to infant leptin at age four months. There was no significant association between maternal and cord serum leptin levels. Birth weight was strongly associated with pBMI (standardized β = 0.77, p < 0.001) and inversely related to maternal delivery leptin levels (standardized β = −0.44, p = 0.008), while the association with cord serum leptin was not significant. Conclusions: Our findings indicate that pBMI is strongly related to birth weight, while higher maternal leptin concentrations were independently associated with lower birth weight after accounting for pBMI. Cord serum leptin did not significantly correlate with maternal leptin levels and only tended to be positively associated with birth weight. Full article

Invasive non-indigenous species (NIS) are impacting Mediterranean coastal ecosystems, presenting ecological and economic management challenges. This study evaluates the economic viability of processing biomass from wild removals of the NIS pearl oyster, Pinctada radiata (Leach, 1814), into value-added seafood products in Greece. The study explored four product formats under two funding scenarios (Scenario A, full private financing; and Scenario B, 60% public co-financing): frozen, vacuum-packed raw oyster meat; frozen, vacuum-packed, breaded raw oyster meat; steamed, brine-smoked, vacuum-packed oyster meat; and steamed oyster meat preserved in olive oil and Mediterranean herbs. In Scenario A, with full private financing, the cumulative net cash flow (NCF) over five years was €165,402.78, with a profitability index (PI) of 2.93 and a payback period (PP) of 1.71 years. In Scenario B, with 60% public co-financing, the owner’s contribution reduced to €34,320.00. At the same time, the annual after-tax cash flow reached €50,240.56, resulting in a five-year cumulative NCF of €216,882.78, a PI of 7.32, and a PP of 0.68 years. These findings indicate that utilizing biomass from wild removals can be a financially viable strategy for managing NIS. This approach focuses on removal rather than aquaculture or translocation of P. radiata and emphasizes the need for adaptive governance and biodiversity protection to ensure effective population control. The study proposes a replicable bioeconomic model for integrating invasive biomass removal with value-added seafood processing in Mediterranean coastal regions. Full article

Zinc is an essential trace element for human and plant growth and development. Exploiting naturally Zn-rich soil resources represents an important pathway to develop green characteristic agriculture, improve the nutritional quality of agricultural products, and advance agricultural sustainability aligned with the United Nations Sustainable Development Goals (SDGs2, 3 and 15). To clarify the geochemical characteristics and bioavailability of soil zinc in cultivated lands of the mid-low hilly region in southwestern Henan, and to scientifically evaluate the exploitation potential of Zn-rich land resources, this study selected the farming area of Fangcheng County, Henan Province, as its research object. Based on 1:50,000 land-quality geochemical survey data, 1602 topsoil samples and 61 paired wheat-grain–root-zone soil samples were collected. Multiple statistical approaches, including descriptive statistics, Universal Kriging spatial interpolation, Pearson correlation analysis and segmented regression, were adopted to systematically investigate Zn concentrations, spatial-distribution patterns, element paragenesis relationships and wheat Zn-accumulation characteristics in cultivated soils. Furthermore, the resource potential of Zn-rich land was assessed according to the Specification for Delineation and Identification of Natural Zn-Rich Land (DD2025-04). The results showed the following: (1) The mean Zn concentration of topsoil was 72.3 mg/kg (N = 1602, after removing 3σ outliers), which was higher than the national soil background value (67 mg/kg). With a coefficient of variation of 23.0%, soil Zn exhibited moderate enrichment and relatively uniform distribution. Its spatial pattern was dominated by geomorphic types, showing a north-high–south-low trend. Significant Zn-enrichment advantages were found in hilly areas, yellow-cinnamon soils, and regions covered by alluvial–proluvial and residual-slope parent materials, whereas Zn concentrations were markedly low in strongly alkaline soils. (2) Soil Zn was significantly positively correlated with Cd (r = 0.62), Cu (r = 0.51), V (r = 0.54) and Fe₂O₃ (r = 0.57), and moderately positively correlated with Se (r = 0.41) and Mo (r = 0.43). These correlations indicate homologous soil-forming parent-material sources and Zn-adsorption–enrichment mechanisms mediated by Fe-Mn oxides. The paragenetic relationship between soil Zn and Cd implies that heavy-metal ecological risks should be considered simultaneously during Zn-rich-land exploitation to guarantee ecological sustainability of cultivated land. (3) The average Zn concentration in wheat grains was 28.48 mg/kg, and the mean bioconcentration factor (BCF) was 0.42 (N = 61, averaged from individual sample-pair ratios), demonstrating a moderate Zn-accumulation capacity of wheat. Only a moderate correlation existed between total soil Zn and wheat-grain Zn, suggesting that high total soil Zn concentrations do not necessarily produce high-Zn crops. (4) Soil pH regulated Zn bioavailability: BCF was positively correlated with pH for samples with pH < 6.5 (R² = 0.116, p = 0.013), while a non-significant negative trend was observed for the subgroup pH ≥ 6.5 (R² = 0.269, p = 0.153). Wheat presented relatively high Zn-accumulation potential under neutral-pH conditions. Nevertheless, the observational dataset cannot confirm pH = 6.5 as a strict optimum threshold, which needs further validation through field-controlled experiments. Either extremely acidic or alkaline conditions may reduce available Zn supply via Zn leaching loss or hydroxide precipitation. (5) In accordance with DD2025-04, Zn-rich soils accounted for 21.85% of the study area, and Zn-enriched wheat grains occupied 21.31%, indicating abundant reserves of Zn-rich land resources. These findings can provide geochemical support for the scientific utilization of Zn-rich cultivated land, industrial layout of Zn-enriched wheat, and precise cultivated-land quality management in the hilly areas of southwestern Henan, promoting sustainable utilization of soil resources and nutrition-sensitive agricultural development. Full article

This study examines tourism-relevant population redistribution across 3214 Spanish mobility areas on four dates in 2021 using aggregated mobile-phone indicators. Because travel purpose is unobserved, the dates are treated as mobility snapshots rather than as a normal-year tourism series. Two descriptive principal components explained 77.58% of the variance in five non-redundant indicators, and non-metric multidimensional scaling recovered similar geometry. A repeated-measures test showed a large joint date effect, F(15, 3194) = 1630.85, p < 0.001, partial η² = 0.885. A comparison of solutions for k = 2–4, based on 100 sub-sampling replications, supported three overlapping exploratory profiles: resident-dispersing (n = 873), broadly connected (n = 992), and summer-receiving (n = 1344). The original expert/AI-assisted heritage score failed external convergent validation and was withdrawn. For 2047 unambiguously mapped areas, it was replaced with a reproducible registry-linked stock of protected immovable heritage assets. In this mapped sub-sample, protected-asset stock was associated with greater summer retention, receiving connectivity, and net population gain. Partial redundancy analysis yielded an incremental R² of 5.01% after population and autonomous-community controls (restricted-permutation p = 0.0005); this value fell to 4.07% with province controls and 3.57% with additional nonlinear and province-specific population adjustment. Because the crosswalk covered 63.8% of areas and disproportionately represented smaller areas, these estimates describe a modest, sample-conditional association rather than a national or causal effect; unmeasured confounding and local spatial dependence remain unresolved. The profiles suggest distinct monitoring priorities but require validation with denser, multi-year data beyond pandemic-affected 2021. Full article

Background: This study assessed diet quality and the association between engagement with nutrition support bundles and weight gain among pregnant women having Aboriginal and Torres Strait Islander babies who participated in the Aboriginal Family and Baby Bundles implementation project at two South Australian maternity sites. Methods: Cross-sectional analysis of dietary data was performed using the Australian Recommended Food Score (ARFS) at enrolment, and 24-h food group servings were compared between enrolment and late pregnancy visits. A composite variable for engagement with nutrition support bundles (low vs. high engagement) used initiation, intensity, and duration of engagement criteria. Separate regression models were applied to examine associations between ARFS, adherence to 24-h food serve recommendations, and maternal characteristics at enrolment. An exploratory univariable association between engagement status and gestational weight gain was examined. Results: The median ARFS score at enrolment was 39 (maximum of 62 out of a total of 73). Women aged above 25 years showed significantly higher ARFS compared with those aged 25 years and below (adjusted β coefficient 3.28, 95% CI 0.38, 6.19, p = 0.027). The number of participants meeting the recommended intake of daily fruit serves increased significantly at the late pregnancy visit (McNemar test p value = 0.004). Across pregnancy, consumption of energy-dense soft drinks or snack foods was common (60–68%). Only 15.4% (8/52) of participants showed adequate weight gain, while 26.9% (14/52) showed inadequate weight gain, and 57.7% (30/52) showed excessive weight gain, as per the recommendations for total gestational weight gain. In the high nutrition support engagement group, a higher proportion of adequate weight gain (24.0% vs. 7.4%) and a lower proportion of excessive weight gain were observed (28.0% vs. 85.2%) (p ≤ 0.001) compared with the low engagement group. Conclusions: This study identified sub-optimal diet quality, including high intake of energy-dense food throughout pregnancy and high proportions of inadequate and excessive weight gain among women having Aboriginal babies in South Australia. Further research is needed to determine the most appropriate ways to support healthy eating in pregnancy among women in South Australia. Full article

Scallop mantle, an abundant yet underutilized processing byproduct, holds vast potential for high-value valorization, yet its restricted functional versatility hinders food-grade application. This study systematically analyzed the molecular mechanisms governing the characteristic evolution (physicochemical, structural, and functional) of scallop mantle protein isolates (SMPIs) subjected to alkaline extraction (pH 8–12). Results indicated that extraction pH from 8 to 12 dramatically boosted the yield of SMPIs from 5.01% to 96.29% and increased purity (reaching 96.01% at pH 10.0 before plateauing), alongside increased particle size and surface hydrophobicity, but caused a dark yellow appearance at pH 12. During this process, proteins gradually degraded into small peptide fragments, with α-helix progressively transforming into β-sheet structures. The exposed hydrophobic residues and altered surface charges substantially modulated aggregation, generating highly uniform and dense microstructures at elevated pH. Notably, SMPIs exhibited optimal water absorption capacity, emulsifying stability index (ESI), and foaming stability at extraction pH 10. SMPIs demonstrated superior performance in thermal stability and foaming ability at extraction pH 11. At extraction pH 8, the stable conformation of SMPIs conferred the highest solubility and superior oil absorption capacity. Our research findings will facilitate the utilization of scallop mantle as a customizable resource for specific functionalities under the waste-to-wealth paradigm. Full article

The depth to which a Global Navigation Satellite System (GNSS) signal senses soil moisture is set by the electromagnetic power penetration depth (${\delta }_p$), the depth at which the power transmitted into the soil falls to $1/e$, seldom measured directly and instead inferred from dielectric mixing models whose parameters are fitted to permittivity rather than to propagation through real, stratified soil. This work reports a controlled, wideband ($0.3$–6 GHz) Vector Network Analyzer (VNA) experiment in which two identical Left-Handed Circular Polarization (LHCP) spiral antennas measure the reflection ($S_{11}$, $S_{22}$) and transmission ($S_{21}$) of a four-layer silt-loam soil column, a laboratory analogue of GNSS Reflectometry (GNSS-R) and GNSS Transmissometry (GNSS-T) geometries. Soil texture and per-layer moisture were measured, not assumed, with a layered-medium transfer-matrix forward model as the reference from which the depths are derived. In this monostatic, normal-incidence, same-hand circular arrangement the reflection channel was insensitive to the moisture profile due to helicity reversal on specular reflection suppressing the same-hand return by more than 15 dB, below the antenna’s own port reflection, whereas transmission preserved it. This is a configuration effect, not a general limitation of GNSS-R or of an opposite-hand dual-polarized reflectometer. Neither the Peplinski–Dobson nor the Mironov MBSDM model outperformed the other across all bands: Peplinski–Dobson fits best in 27 of the 48 moisture–band cells, whereas MBSDM performs best in the driest and two wettest states and in a few additional bins. Using the best-fitting model per band, and separating the parametric uncertainty of that model from the structural difference between the two, the model-derived ${\delta }_p$ decreases with moisture and frequency: under the driest evaluated state (volumetric moisture content $m_v=10.3\%$) it spans $26.4_{-1.5}^{+1.8}$ cm at 868 MHz, a value higher than the 20 cm of soil actually sampled and therefore an extrapolation of the selected model, to $9.5_{-0.6}^{+0.7}$ cm at $2.2$ GHz, falling at $m_v=20.8\%$ to $15.9_{-0.6}^{+0.6}$ cm and $9.8_{-1.4}^{+2.1}$ cm, respectively. At L1, L2, and L5 carriers, ${\delta }_p\approx 15$–20 cm at $m_v=10.3\%$ and ${\delta }_p\approx 5$–7 cm at $m_v=41.3\%$. A second estimate, in which no dielectric model intervenes, is obtained from the wet-slab thickness sweep, the excess attenuation following from the slope of the differential transmissivity on propagation distance: at $m_v=22.9\%$ it bounds ${\delta }_p$ from above at $20.9_{-1.8}^{+2.2}$ cm at 868 MHz, $12.6_{-0.1}^{+0.1}$ cm at L1, and $9.8_{-0.1}^{+0.1}$ cm at $2.2$ GHz, agreeing to within about one centimeter with the model-derived depths interpolated to the same moisture at the GNSS carriers and at S-band. Throughout, ${\delta }_p$ is a property of the soil alone. It is not the effective sensing depth of a GNSS observation, which also depends on the observation geometry, the polarization, the surface roughness, and the forward model used in the inversion. Full article

Cocrystallization is an effective strategy for modifying the physicochemical properties of active pharmaceutical ingredients (APIs), yet rational coformer selection remains challenging. In this work, we propose an interpretable extension of DeepCocrystal by integrating Principal Component Analysis (PCA) with supramolecular language-based prediction. Picolinamide, nicotinamide, and isonicotinamide were selected as models for APIs due to their diverse hydrogen-bonding capabilities but structural similarity. A curated coformer library was screened computationally, and the molecular descriptor space was analyzed to identify dominant structural drivers of cocrystal compatibility. PCA revealed that cocrystal propensity in the studied systems is primarily governed by hydrogen-bond complementarity, polarity matching, and aromatic surface interactions. The integrated framework is intended to enhance mechanistic interpretability without altering the predictive output of DeepCocrystal. In this setting, the PCA layer functions as a post hoc, unsupervised readout of the descriptor space, so the original ranking and scoring of the predictions remain unchanged. This approach provides a scalable and chemically transparent methodology for rational coformer prioritization and supports data-driven crystal engineering strategies. In addition, a simpler post-filtering strategy based on pK_a values was also applied to the DeepCocrystal predictions to attempt a classification that can exclude salts. Following the pK_a-based post-filtering rules, from the 137 API–coformer pairs classified by DeepCocrystal as positive or as uncertain, that is, all pairs not confidently excluded, 46 pairs retained their classification as high-probability cocrystal-compatible, 39 pairs were assigned the classification of uncertain but salt formation excluded, 11 pairs retained the classification of negative with large uncertainty, 34 pairs were reclassified as belonging to the salt/cocrystal “gray zone”, and 7 pairs were classified as salt-risk candidates. Full article

Background/Objectives: Anti-amyloid immunotherapies reduce amyloid-β (Aβ) plaques but carry a 15–35% risk of amyloid-related imaging abnormalities (ARIA), particularly in APOE ε4/ε4 carriers. This preliminary observational study evaluated blood Aβ oligomer changes following treatment with the multi-component herbal formula Chongnoi-tang (CNT) and contextualized these findings against natural disease trajectories in National Alzheimer’s Coordinating Center (NACC) and Alzheimer’s Disease Neuroimaging Initiative (ADNI) reference cohorts. Methods: This retrospective pilot cohort included 16 patients with Alzheimer’s spectrum conditions treated with CNT. Blood Aβ oligomers were measured using the AlzOn Plus immunoassay. Primary analysis (n = 13) excluded cases with a ceiling-level baseline value, an intercurrent potentially confounding condition, or no true baseline measurement. Results: Mean blood Aβ oligomer levels decreased by 15.8% ± 13.4% at 6 months (median −20.6%; 95% CI −23.9% to −7.8%; Wilcoxon signed-rank test, p < 0.001; paired Cohen’s dz = 1.07). At each participant’s final available follow-up, all 13 primary-analysis patients had values below baseline. High-risk patients (n = 4) showed a mean 25.7% reduction. Baseline Aβ level and 6-month percent biomarker change exhibited an exploratory, non-significant inverse trend in the Pearson correlation (r = −0.489, p = 0.090) that was weaker and non-significant in the Spearman sensitivity analysis (ρ = −0.300, p = 0.320), consistent with regression to the mean and mathematical coupling as plausible contributors. Importantly, all four APOE ε4/ε4 homozygotes showed Aβ reductions without ARIA-like clinical events. Mini-Mental State Examination (MMSE) worsening occurred in 37.5% (3/8) of CNT-treated patients versus 42.9% (15/35) in propensity-matched NACC controls (p = 0.89); given the small sample, this comparison is inconclusive. Conclusions: In this small, uncontrolled pilot study, CNT was associated with blood Aβ reductions, which should be interpreted as a statistical association rather than confirmed evidence of a treatment effect; no treatment discontinuations due to adverse effects were documented in this small cohort, including among APOE ε4/ε4 carriers. These hypothesis-generating findings warrant further confirmation in prospective randomized controlled trials. Full article

Background: Ciliary neurotrophic factor (CNTF) is a neurotrophic cytokine involved in neuronal survival, synaptic plasticity, and retinal ganglion cell health, and it correlates with different stages of cognitive impairment. Mild cognitive impairment (MCI) is difficult to diagnose, as these patients perform normally on standardized cognitive tests. It is important to diagnose patients with MCI early to prevent its progression and to maintain their quality of life. Alterations in retinal morphology mirror central nervous system pathology, including cognitive impairment. Objective: This cross-sectional study investigates the association between retinal structural changes and plasma CNTF levels and assesses their possible clinical value for screening early cognitive impairment. Methods: Retinal morphology was assessed by optical coherence tomography (OCT), and plasma CNTF was measured by enzyme-linked immunosorbent assay (ELISA) in 69 healthy participants. We correlated retinal biomarkers and CNTF levels with cognitive function as measured by the Montreal Cognitive Assessment (MoCA). Results: CNTF levels were significantly higher in the low MoCA group (median = 287.6, IQR: 235.90–359.7) compared to the normal cognition group (median = 185.90, IQR: 162.1–277.5) (p < 0.001). Average central thickness and retinal nerve fiber layer (RNFL) were positively associated with CNTF (p < 0.05). Conclusions: Our results indicate that CNTF is negatively associated with cognition and positively correlated with RNFL and average central thickness. Screening for MCI with non-invasive OCT imaging and plasma CNTF may aid in the early detection of cognitive impairment. Future pharmacological interventions with CNTF analogs may preserve or even restore cognitive function. Full article

Accurate photovoltaic (PV) power forecasting is essential for enhancing grid stability, optimizing energy management, and facilitating the large-scale integration of renewable energy resources. Although deep learning techniques have demonstrated promising results in PV forecasting, their predictive performance is highly dependent on effective hyperparameter optimization. Furthermore, studies dedicated to field-deployed perovskite photovoltaic systems operating under semi-arid desert climatic conditions remain limited. To address this gap, this study proposes an Adaptive Hybrid Grey Wolf Optimizer–Sparrow Search Algorithm (AH-GWOSSA) deep learning framework for single-step-ahead (5 min lead time) and multi-step power forecasting of a perovskite PV system installed in Mosul, Iraq. A real-world dataset comprising 21,456 valid daytime observations (filtered for solar irradiance > 5.0 W/m²) was collected between November 2025 and April 2026 and partitioned strictly chronologically (70% training, 10% validation, 20% held-out testing). The proposed framework was benchmarked against Persistence, an unoptimized Base LSTM, Standard GRU, CNN-LSTM, standalone GWO, SSA, Random Search, and an ablation Fixed-Weight Hybrid under an equivalent evaluation budget of 160 candidate network trainings. Over 30 independent optimization runs, AH-GWOSSA achieved the lowest mean RMSE of 15.55 W (std. 0.34 W), an MAE of 8.79 W (std. 0.25 W), and the highest mean R² of 0.885 (std. 0.008). Non-parametric Wilcoxon signed-rank testing across 30 paired run-wise RMSE values confirmed a statistically significant improvement over the unoptimized Base LSTM ($W=78.0$, $p=1.8\times {10}^{-6}$ at $\alpha =0.01$). Multi-horizon evaluations (5, 15, 30, 60, and 120 min) demonstrated consistent superiority over Persistence and Base LSTM, with RMSE improvements of up to 39.8% at the 30 min horizon. The findings demonstrate that adaptive hybrid metaheuristic optimization provides a competitive framework for ultra-short-term perovskite PV forecasting, with RMSE improvements of up to 39.8% over Persistence at the 30 min horizon, offering a solid foundation for future smart-grid and battery storage management applications. Full article

The poor gel-forming ability of myofibrillar proteins in hairtail (Trichiurus haumela) surimi limits its application in high-quality surimi products. This study investigated the effects of dried pumpkin powder (DPP) addition (0, 0.4%, 0.75%, 1.1%, 1.5%, and 1.85%, w/w) on the gel properties, protein conformation, and microstructure of frozen hairtail surimi gels. The results revealed a nonlinear, dose-dependent effect on gel quality. At 1.1% addition, gel hardness and springiness reached maximum values of 313.69 ± 2.54 g and 0.86 ± 0.004, respectively, while water-holding capacity (WHC) significantly increased by 11.21% compared with the control (p < 0.05). Fourier-transform infrared spectroscopy demonstrated a marked reduction in α-helix content with a concomitant increase in random coil content, indicating changes in protein secondary structure that may favor interactions within the protein network. Scanning electron microscopy further revealed that moderate supplementation filled network voids and produced a denser, more homogeneous microstructure, whereas excessive addition (≥1.5%) led to fiber aggregation and structural deterioration. Collectively, moderate pumpkin powder addition—specifically at 1.1%—improves hairtail surimi gel quality, and these improvements may be associated with changes in protein secondary structure and microstructural organization, offering a practical strategy for developing fiber-enriched surimi products. Full article

Esophageal squamous cell carcinoma frequently develops through a prolonged precancerous phase, creating an opportunity for intervention. Zishui Qinggan Yin (ZSQGY) is a multi-component botanical preparation, but its effects in esophageal precancer and its formulation-level chemical profile remain incompletely defined. We monitored a predefined 40-analyte panel by UPLC-Q Exactive/MS in three independently extracted aliquots from the same formulation batch administered to mice. A 4-nitroquinoline-1-oxide model was then evaluated by consensus histopathology, mouse-grouped whole-slide digital pathology, network-based target prioritization, molecular docking, exploratory drug affinity responsive target stability (DARTS), Western blotting, qPCR, and serial-section immunohistochemistry. Signals corresponding to 38 predefined analytes were reported. ZSQGY treatment was associated with a lower-grade lesion pattern in the evaluated mouse-level specimens. Exploratory DARTS was analyzed in two independent n = 6 tissue-background datasets. In the original 4-NQO model-background cohort, ex vivo ZSQGY (100 μg/mL) increased the AKT1-immunoreactive relative-protection signal in five of six lysates (mean 2.04 ± 1.15). In an additional cohort from mice that had received ZSQGY in vivo, ex vivo ZSQGY produced mean relative-protection values of 1.21, 1.75, and 1.92 at 50, 100, and 200 μg/mL, respectively. The nominal exact p value for the 100 μg/mL versus vehicle contrast in the additional exploratory dataset was 0.0313; This exploratory result should be interpreted cautiously. Neither dataset establishes direct binding or in vivo target occupancy. PI3K p110α DARTS was technically inconclusive. Endpoint tissues showed lower AKT, mTOR, S6K1, and 4E-BP1 phosphorylation, together with PTEN-associated changes, reduced Ki-67, increased cleaved caspase-3 staining, and selected downstream transcript changes, including a non-significant downward trend in PARP1. These findings support a preclinical association between ZSQGY treatment, attenuation of esophageal precancer progression, and AKT-centered PI3K/AKT/mTOR pathway modulation. They do not establish direct binding, in vivo target occupancy, pathway necessity, active constituents, or causal mediation. Full article

Background: Estimated pulse wave velocity (ePWV) is a non-invasive marker of arterial stiffness with potential relevance for chronic kidney disease (CKD) risk assessment. This study aimed to investigate the association between ePWV and CKD risk in the US and Chinese populations and to evaluate its discriminative performance using machine learning approaches. Methods: Data were obtained from the National Health and Nutrition Examination Survey (NHANES, 2005–2018, weighted n ≈ 100.9 million) and the China Health and Retirement Longitudinal Study (CHARLS, 2011–2015, n = 21,853). In NHANES, CKD was defined according to the 2021 KDIGO criteria as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m² or a urinary albumin-to-creatinine ratio (ACR) ≥ 30 mg/g; in CHARLS, where urinary albumin was not measured, CKD was defined by the eGFR criterion alone, and this difference in case definition was taken into account when interpreting the results. Logistic regression and restricted cubic spline models were used to examine the association between ePWV and CKD, with subgroup analyses stratified by demographic and clinical characteristics. Multiple machine learning models were developed in NHANES and externally validated in CHARLS; model discrimination was assessed using the area under the receiver operating characteristic curve (AUROC), and feature importance was interpreted using SHapley Additive exPlanations (SHAP) values. Results: Higher ePWV was consistently associated with higher odds of CKD in both cohorts (NHANES: odds ratio [OR] = 1.505 per 1 m/s, 95% confidence interval [CI] = 1.459–1.552; CHARLS: OR = 1.434 per 1 m/s, 95% CI = 1.368–1.503; both p < 0.0001), with dose–response relationships observed. Formal interaction tests confirmed significant effect modification by sex (both cohorts) and by BMI and diabetes (NHANES only). Point estimates were higher in men and in NHANES obese and diabetic subgroups, but interactions across smoking and alcohol strata were not statistically significant. Among the machine learning models evaluated, discrimination was moderate and comparable across algorithms (LightGBM: AUROC = 0.804 in internal validation and 0.793 in external validation), and DeLong tests showed no significant difference between LightGBM and XGBoost (p = 0.0655 and 0.0684, respectively). SHAP analysis identified ePWV as the highest-ranking feature, surpassing uric acid, lipid levels, and diabetes history. Using the Youden index, the optimal ePWV cutoff for identifying CKD was 10.15 m/s in NHANES (sensitivity 0.658, specificity 0.695) and 10.568 m/s in CHARLS (sensitivity 0.658, specificity 0.718). Conclusions: Elevated ePWV is significantly associated with eGFR-defined CKD across the US and Chinese populations studied. These findings support ePWV as a potentially useful marker for CKD risk stratification; however, given the cross-sectional design of both cohorts, its predictive value requires confirmation in prospective studies. It is important to emphasize that no non-invasive calculated metric can replace direct measurement of serum creatinine and urinalysis for identifying individuals at risk of CKD in routine clinical practice. Full article

Background: Dietary composition reflects the interplay of individual and contextual factors, yet its relationship with socioeconomic–territorial conditions remains insufficiently characterized in large Latin American cities. Methods: We identified empirical dietary patterns among 3439 adults from the cohort in Mexico City and examined their association with the Social Development Index (SDI), a composite area-level measure of socioeconomic–territorial development. Energy-adjusted food-group intakes were analyzed using k-means clustering, and supervised machine-learning models with SHAP-based interpretation were used to characterize pattern membership. Results: Three dietary patterns—Fresh, Mixed, and Refined—were identified along a continuous dietary gradient primarily differentiated by the relative contribution of fruits and vegetables. SHAP analysis showed that the Fresh pattern was characterized mainly by female sex and older age, the Refined pattern by greater contributions from physical activity, cardiometabolic markers, male sex, and lower SDI values, whereas the Mixed pattern was distinguished primarily by cardiometabolic variables, alcohol intake, and durable-goods ownership. Dietary pattern membership was significantly associated with SDI stratum (${\chi }^2=40.77$, $p<0.001$), although the effect size was small (Cramér’s V = 0.078). The proportion of participants classified in the Fresh pattern increased from 35.7% in the lowest SDI stratum to 51.9% in the highest, whereas the Refined pattern decreased from 44.6% to 34.0%. Supervised models showed limited discriminatory performance (balanced accuracy ≈ 0.40), indicating substantial overlap among patterns despite their distinct multivariable profiles. Conclusions: These findings indicate that dietary variation in this urban population is better represented as a continuum than as sharply separated dietary phenotypes. Full article