Search Results (1,785)

Ecotourism in protected areas creates a conservation paradox: tourism revenue funds protection, yet tourism infrastructure simultaneously degrades the wildlife it protects. We examined this paradox in white-faced capuchins (Cebus imitator) in Tortuguero National Park, comparing behaviour across a high-tourism accommodation site (2152 monthly guests) and a strictly regulated terrestrial trail. Using focal animal and sweep sampling methods, we recorded 477 behavioural units across 261 min, analysing locomotion, feeding, and agonistic behaviours through generalized linear models. Primates in accommodation areas exhibited significantly reduced high substrate use (p = 0.005), showed a trend toward increased anthropogenic food reliance (p = 0.070), and higher—but not statistically significant—rates of agonistic behaviours (p > 0.05). The negative correlation between natural foraging and active food supply (r = −0.31) is consistent with anthropogenic provisioning that may alter primate ecological functions. These findings demonstrate that effective conservation in tourism contexts requires integrated management addressing three interconnected challenges: (1) habituation to human presence, (2) food provisioning with cascading consequences, and (3) ecosystem-level degradation through altered primate functions. We recommend evidence-based interventions including secured waste management, enforcement of wildlife feeding prohibitions, and environmental education programs with community participation. Ecotourism sustainability requires managing human–wildlife interactions and integrating local stakeholder perspectives to preserve animal welfare and ecosystem functions essential for conservation. Full article

This study investigates the performance characteristics of U18 semi-professional soccer players by examining both technical load (TL) and physical load (PL) variables across various playing positions during the 2021/2022 Spanish Football U18 National League Championship. Methods: Principal Component Analysis (PCA) was employed to simplify the dataset, which comprised 246 match records from 49 athletes (mean age 17.9 ± 0.7 years; height ~177.6 ± 6.3 cm; body mass ~72.0 ± 7.2 kg) across ten matches. This analytical approach aimed to facilitate a deeper understanding of player performance dynamics. Results: Kaiser–Meyer–Olkin (KMO) values varied across positions (technical load: 0.20–0.93; physical load: 0.27–0.91). This indicates acceptable sampling adequacy for several positional models, but low adequacy for others; therefore, results for positions with low-KMO values should be interpreted cautiously. Factor analysis for both technical and physical load variables identified two components each, explaining substantial total variance (technical load: 63.75–86.65%; and physical load: 71.74–88.92% across position), with significantly high factor correlations (p < 0.001). The findings further indicate that players occupying defensive positions, such as goalkeepers and center-backs, generally exhibit lower levels of physical intensity and technical engagement compared to their counterparts in more dynamic roles, including full-backs, wingers, and forwards. The latter groups demonstrate higher involvement in high-intensity running and offensive actions. Conclusions: The observed performance patterns highlight the necessity for tailored training programs that align with the specific demands of each playing position. This approach is expected to optimize individual player performance and enhance overall tactical efficiency. Furthermore, the study underscores the importance of developing individualized conditioning strategies that address the unique physical and technical requirements inherent to each role on the field. This analytical approach using PCA provides a more structured and data-driven understanding of these positional differences, reinforming the need for tailored training programs and individualized conditioning strategies. Full article

Accurate inflow wind conditions are essential for operational wind farms. However, wind conditions from the Supervisory Control and Data Acquisition (SCADA) system are significantly affected by rotor-induced disturbances and thus cannot reliably represent the true inflow. Although LiDAR can directly measure inflow wind conditions, its data availability is highly sensitive to environmental conditions, frequently leading to insufficient valid samples. Existing studies generally apply the Nacelle Transfer Function (NTF) to empirically correct SCADA wind speed, yet its accuracy remains limited. Consequently, this study proposes a deep learning model for LiDAR-referenced inflow wind condition estimation from SCADA data. First, variations in LiDAR data availability and their influencing factors are systematically analyzed. The deviations and correlations between SCADA data and LiDAR measurements are quantitatively characterized. Subsequently, a deep learning model is developed, employing a time–frequency dual-branch residual network to extract features from SCADA data, while incorporating the Gram matrix as an additional input to provide auxiliary information. Finally, the proposed method is validated using measurements from two offshore turbines with different rated capacities. The results demonstrate that the proposed approach outperforms comparative methods, enabling more accurate estimation of inflow wind speed and direction. Full article

Hami melon is a widely consumed fruit worldwide, and its sweetness, characterized by soluble solids content (SSC), is a key indicator of fruit quality and commercial value. In this study, hyperspectral imaging combined with machine learning was systematically applied to develop non-destructive models for SSC prediction in multiple Hami melon varieties. Four varieties, namely ‘Xizhoumi’, ‘Jiashigua’, ‘Jinfenghuang’, and ‘Heimeimao’, with a total of 160 samples, were used as the test materials. Hyperspectral images were collected, and SSC was measured at two pulp positions for each sample (denoted as BRIX1 and BRIX2). After applying preprocessing methods including Standard Normal Variate (SNV) transformation and Savitzky–Golay smoothing, five machine learning models were compared: XGBoost, LightGBM, Random Forest (RF), Support Vector Regression (SVR), and Partial Least Squares Regression (PLSR). Furthermore, an ensemble modeling strategy based on residual predictive deviation (RPD) weighting from the validation set was proposed. The results show that all models could effectively predict SSC, with the ensemble model achieving the best performance: the coefficients of determination (R²) for BRIX1 and BRIX2 were 0.848 and 0.833, the root mean square errors (RMSEs) were 0.992 and 0.899, the Mean Absolute Percentage Errors (MAPEs) were 6.90% and 6.76%, and the RPD values were 2.57 and 2.45, respectively, demonstrating its strong quantitative analysis capability. This performance benefited from three core optimized designs adopted in this study: (1) a multi-cultivar experimental design that verified the stable correlation between sugar-related spectral features and internal SSC across different Hami melon varieties; (2) an RPD-weighted ensemble modeling strategy that balanced the fitting ability and generalization performance of linear and nonlinear models; and (3) a dual-position SSC measurement design that validated the robustness of the model for SSC prediction at different spatial positions in the pulp. This study confirms the feasibility of hyperspectral imaging technology for non-destructive SSC detection in the four tested Hami melon varieties under laboratory-controlled conditions. The proposed ensemble model achieved a marginal but stable improvement in overall prediction accuracy across the tested varieties compared with the optimal single model, providing a preliminary methodological reference and data support for the development of cross-cultivar non-destructive SSC detection models for Hami melon. Full article

Objectives: This study aimed to examine the associations of physiological (VO₂max), morphological (body fat percentage), and behavioral factors (physical activity levels) with life satisfaction among teacher education and preschool education students, with a particular focus on self-rated health as a potential statistical mediator. Methods: The sample consisted of 228 students (95% female; mean age = 21.96 ± 4.24 years). Life satisfaction was assessed using the Satisfaction with Life Scale (SWLS), self-rated health (SRH) with a single-item measure of general health, physical activity (PA) with the IPAQ-SF questionnaire, cardiorespiratory fitness (VO₂max estimate) with the 20 m shuttle run test, and body fat percentage (BF%) with a bioelectrical impedance analyzer. Data were analyzed using hierarchical regression and mediation models with the PROCESS macro (Model 4). Results: SRH accounted for 17.2% of the variance in life satisfaction, emerging as the strongest correlate relative to physiological and morphological indicators. In the primary regression model, total PA accounted for an additional 2.3% of explained variance, whereas in a secondary parallel model, moderate PA accounted for 2.2%. Vigorous PA was not a significant correlate. Mediation analyses indicated that VO₂max was not directly associated with life satisfaction but showed a statistically significant indirect association through SRH. No significant indirect associations were found for BF%, individual activity intensities, or total PA. Conclusions: The results highlight the relevance of perceptual and behavioral health indicators in understanding the relationships among PA, physical fitness, and psychological well-being in this student population. The findings provide preliminary insight into how multiple health-related dimensions may relate to life satisfaction, underscoring the need for longitudinal research before more confident interpretations of practical relevance can be made. Full article

Soil heavy metal pollution caused by mineral resource extraction activities poses a serious threat to the ecological environment within and surrounding mining areas. As a highly concealed toxic heavy metal, arsenic (As) urgently requires the establishment of efficient pollution monitoring methods to achieve pollution prevention and control, as well as environmental remediation in mining areas. This study investigated the feasibility of hyperspectral remote sensing inversion for soil heavy metal arsenic based on ZY-1 02E hyperspectral satellite imagery, focusing on a mining area and its surrounding soils in Sanlisha’an, Wuxuan County, Guangxi. Full Constrained Least Squares (FCLS) was employed to separate mixed pixels and enhance soil spectral contributions in ZY-1 02E imagery, thereby mitigating vegetation interference. Six mathematical transformations, including RT, AT, FD, RTFD, ATFD, and SD, were applied to both the original and enhanced spectra to enhance spectral features. The correlations between the transformed spectra, as well as the original image spectra (S), and soil As concentration were analyzed; then the spectra strongly correlated with soil As concentration were selected to construct Ratio Spectral Index (RSI) and Normalized Difference Spectral Index (NDSI). Correlation matrices were calculated between RSI/NDSI indices and As concentration. Sensitive features were screened using an improved Successive Projection Algorithm (SPA). As concentration inversion was also performed with four models: traditional regression models, PLSR and MLR, and ensemble learning models (RF and XGBoost). In the soil contribution-enhanced spectral modeling results, the optimal transformation–index combination is ATFD-NDSI. The performance indicators of each model are as follows: MLR test set R² = 0.65, PLSR test set R² = 0.62, RF test set R² = 0.7, and XGBoost test set R² = 0.64. The results indicate that the ATFD-NDSI-RF ensemble model provides the best performance. By integrating multiple decision trees, RF effectively handles complex nonlinear relationships, thus enhancing the accuracy and generalization ability of predication. The analysis of NDSI–ATFD–RF inversion results based on sampling points indicates that model error correlates with the pollution intensity gradient, showing greater errors, especially in high-concentration areas, but still maintaining strong correlations (tailings reservoir: r = 0.92, forested areas: r = 0.96, and cropland: r = 0.83). The spatial distribution reveals that the inversion results are closely similar to the spatial distribution of IDW interpolation. Areas with high As concentrations are concentrated in the tailings reservoir and in the southeastern part of the study area. The correlation coefficient between the inversion results and IDW interpolation is 0.6, which further verifies that the inversion results effectively reproduce the spatial distribution trend of highly polluted areas. Full article

Objectives: This study aimed to characterize the expression patterns and interrelationship of key fibrosis-related markers—TGF-β1, SMAD2, SMAD3, and fibronectin—in human endometrial tissue, and to explore their potential diagnostic relevance in differentiating intrauterine adhesions (IUAs) from cesarean scar defects (isthmocele), with a particular focus on underlying fibrotic remodeling processes. Methods: Endometrial samples were obtained from women diagnosed with IUAs, isthmocele, or without uterine pathology. Total RNA was extracted from all specimens, and gene expression levels were quantified using real-time quantitative polymerase chain reaction (PCR). Statistical analyses included intergroup comparisons, parametric and non-parametric correlation analysis, multivariable linear and logistic regression models, and receiver operating characteristic (ROC) curve analysis to explore the discriminatory potential of the evaluated markers. Results: Significant positive correlations were observed across the study population between SMAD2 and SMAD3 (r = 0.892; p = 0.001), SMAD2 and TGF-β1 (r = 0.697; p = 0.001), and SMAD3 and TGF-β1 (r = 0.910; p = 0.001), indicating coordinated activation of profibrotic signaling pathways. ROC curve analysis showed high discriminatory performance for isthmocele across all evaluated markers, with area under the curve (AUC) values of 0.976 for SMAD3, 0.961 for TGF-β1, 0.913 for fibronectin, and 0.928 for SMAD2 (all p = 0.001). In contrast, although elevated expression levels of fibrotic markers were observed across different American Fertility Society (AFS) stages in IUAs, these differences did not reach statistical significance. Conclusions: This study provides molecular evidence distinguishing isthmocele from IUAs with respect to fibrosis-related signaling in human endometrial tissue. The markedly elevated and coordinated expression of TGF-β1, SMAD2, SMAD3, and fibronectin in isthmocele reflects activation of post-cesarean fibrotic remodeling pathways. However, given the limited sample size and the exploratory nature of the analyses, larger cohorts and future studies are required to validate these findings and to allow extrapolation of the results to the general population. At this stage, these biomarkers should therefore be regarded as indicators of underlying pathophysiological processes. Full article

Background: Extreme weather events, such as storms, may evoke intense fear in individuals and impair their daily functioning, resulting in significant distress. In Brazil, recent climate-related disasters have highlighted the need to assess storm fear in the population. Objective: This study aimed to translate, adapt, and validate the Storm Fear Questionnaire (SFQ) for the Brazilian context. Methods: Translation and adaptation were conducted, followed by back-translation, review by an expert panel, and acceptability assessment by the target population. For the psychometric evaluation, a sample of 268 postpartum women exposed to a flood in southern Brazil completed the SFQ and the following questionnaires: the Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5), Beck Depression Inventory II (BDI-II), and the Pregnancy Experience Scale—Brief Version (PES-Brief). Results: The instrument showed excellent acceptability in the target population and good content validity. Regarding criterion validity, Pearson correlations indicated high convergence between the SFQ and PCL-5 and moderate convergence with the BDI-II. Regarding construct validity, SFQ scores were significantly higher among postpartum women who had to leave their homes due to the flood or had their houses affected by floodwaters. The first factor generated in the factor analysis explained 35.2% of the variance, with 14 out of 15 items presenting loadings greater than 0.40. Internal consistency was high (α = 0.88). Conclusions: The Brazilian version of the SFQ is a valid and reliable instrument for assessing fear of storms. Future studies are needed to evaluate the instrument’s applicability in diverse populations across the country. Full article

Background: Protein prenylation is crucial for the function of hundreds of proteins. Aberrant protein prenylation can be caused by the aberrant expression of prenyltransferases (PTases), which has been reported for multiple cancer entities. The reasons for aberrant PTase expression in cancer have not yet been investigated. Methods: We analyzed CpG methylation within promoter-associated CpG islands of the PTase genes FNTA, FNTB, PGGT1B, and RABGGTA via bisulfite conversion and pyrosequencing to assess its role in PTase expression and gain deeper insight into the regulation of protein prenylation in cancer. We used DNA from three benign controls (whole blood samples, peripheral blood mononuclear cells, and HEK293) and 19 human cancer cell lines from various origins to assess DNA methylation within PTase gene promoter-associated CpG islands. For a subset of these cell lines, we measured mRNA expression via qPCR and correlated it with DNA methylation. Results: Methylation across all PTase genes ranged from 1.9 ± 0.9% to 11.4 ± 4.0% (mean methylation ± standard deviation) in benign cells, and 2.3 ± 1.0% to 16.0 ± 5.4% in cancer cells. DNA methylation and mRNA expression of PGGT1B correlated inversely (PCC = −0.75; p = 0.005). Conclusions: We saw no general differences between benign and malignant cells, but observed significant differences between non-malignant controls and multiple individual cancer cell lines regarding the methylation of PTase genes. This was prominently seen in PGGT1B in Caki-1 cells, raising the possibility that DNA methylation is involved in the dysregulation of PTase expression in cancer. Full article

Background and Objectives: Prostate cancer exhibits substantial biological heterogeneity. Although several biomarkers reflecting aggressive tumor behavior have been identified, molecular indicators related to biological adaptation to androgen deprivation remain limited. This study aimed to comparatively evaluate ISM-1 and B7-H3 expression in localized prostate cancer (LPC) and the pre-CRPC group (pre-treatment diagnostic biopsy tissue from patients who subsequently developed CRPC), and to investigate their clinicopathological associations in the pre-CRPC group. Materials and Methods: This retrospective study included 30 surgically treated LPC cases and 32 pre-CRPC cases with available prostate tissue samples obtained prior to the development of castration resistance. ISM-1 and B7-H3 expression levels were evaluated immunohistochemically using the H-score method (intensity 0–3 × proportion score 0–3 [0%, 1–19%, 20–50%, >50%]). Expression patterns were compared between LPC and pre-CRPC groups. Within the pre-CRPC group, associations with clinicopathological parameters were evaluated using H-scores as continuous variables, and time to castration resistance was analyzed using Cox regression. Results: ISM-1 expression was generally low in LPC cases, with a median H-score of 0, whereas pre-CRPC biopsy tissues demonstrated a marked increase in ISM-1 expression. B7-H3 expression was higher and more homogeneous in the pre-CRPC group compared with LPC. In the pre-CRPC group, ISM-1 and B7-H3 H-scores showed a strong positive correlation. No statistically significant associations were identified between ISM-1 or B7-H3 expression levels and most conventional clinicopathological parameters; however, both markers differed significantly across Grade Groups. Neither marker showed a statistically significant association with time to castration resistance, although ISM-1 demonstrated a non-significant trend toward a longer time to resistance. Conclusions: ISM-1 and B7-H3 exhibit distinct expression patterns across different stages of prostate cancer but show associated expression profiles in the pre-CRPC group. While B7-H3 appears to reflect aggressive tumor biology, the independent expression pattern of ISM-1 and its non-significant trend toward a longer time to resistance suggest a potential role in the clinical trajectory toward castration resistance. Combined assessment of ISM-1 and B7-H3 may contribute to a better understanding of tumor biology in patients who subsequently develop CRPC. These findings are descriptive and hypothesis-generating. Full article

Background: Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE), characterised by unpredictable outcomes due to the absence of reliable biomarkers. This hypothesis-generating study aimed to evaluate whether changes in the N-glycosylation of IgG, C3, AGP, and the serum proteins over one year of treatment correlate with clinical and histological features of LN and predict renal outcomes. Methods: Serum samples from 19 treatment-naïve patients with LN were collected at baseline and 12 months post-treatment, in conjunction with per-protocol repeat kidney biopsy. IgG (Fc, Fab, and total), C3, AGP, and total serum glycoproteins were isolated and analysed as either released N-glycans or N-glycopeptides using high-throughput glycomic approaches. Clinical and histological data were obtained at both time points, along with assessments of clinical and histological response at 12 months and long-term renal function. Results: In total, we identified 24/243 increased N-glycosylation traits (2 total IgG, 5 IgG Fc, 7 IgG Fab, 5 serum glycoproteins, 4 AGP, and 1 C3) and 10/243 decreased N-glycosylation traits (7 total IgG, 2 IgG Fc, 1 IgG Fab) following treatment. Baseline AGP IORMIF1N5H6S2F1 showed a positive correlation with eGFR both at baseline (r = 0.64, p = 0.005) and at 12 months (r = 0.51, p = 0.032). Among AGP N-glycosylation traits, IVORMI1N7H8S3 (r = 0.66, p = 0.002; r = 0.48, p = 0.041, respectively), VORMI1N8H9S4 (r = 0.51, p = 0.029; r = 0.49, p = 0.038, respectively), and VORMI1N8H9S4F1 (r = 0.48, p = 0.039; r = 0.49, p = 0.034, respectively) significantly correlated with activity index (AI) at baseline and at 12 months. Presence of cellular crescents at baseline positively correlated with three AGP N-glycosylation traits: IORMISORMIIA1N4H5S2 (r = 0.49, p = 0.036), VORMII1N5H6S3F1 (r = 0.63, p = 0.006), and VORMII1N4H5S2 (r = 0.48, p = 0.046). Total serum N-glycan (structure) N5H4F1 at 12 months was associated with both clinical and histological response to treatment. Delta of total serum N-glycan structure N5H5S1 was independently associated with poor long-term outcome. Conclusions: This study suggests that glycosylation changes over one year of treatment are associated with specific clinical and histological features and both short- and long-term renal outcomes in LN. Given the small cohort size, results should be considered hypothesis-generating warranting further investigation in independent cohorts. Full article

Recent investigations have questioned whether the Toronto Alexithymia Scale (TAS-20) distinguishes alexithymia from general psychological distress, with some researchers positioning the Perth Alexithymia Questionnaire (PAQ) as demonstrating superior discriminant validity. We evaluated both instruments in a community sample enriched with participants having psychiatric diagnoses or a treatment history (N = 681). Participants completed the TAS-20, PAQ, and Depression Anxiety Stress Scales-21 (DASS-21). Both alexithymia measures showed moderate correlations with the DASS-21, suggesting related but distinct constructs. Item-level exploratory factor analysis revealed a factor separation between general emotional dysfunction and distress, with no meaningful cross-loadings for TAS-20 Difficulty Identifying Feelings (DIF) items. At the subscale level, a two-factor solution supported distinct general emotional dysfunction and distress factors. In contrast to two recent investigations, the TAS-20 DIF subscale loaded exclusively on a general emotional dysfunction factor with negligible loading on a distress factor. These findings demonstrate that neither the TAS-20 nor the PAQ is compromised by distress, challenging recent claims of TAS-20 discriminant validity problems and underscoring the importance of replication across diverse samples and analytic methods. Full article

The operational reliability of the elastic wheel, essential for specialized vehicle mobility on complex terrain, is critically constrained by fatigue failure under multi-axis ground loads. While high-fidelity physics-based simulation provides an accurate assessment, its “one-simulation-per-test” paradigm is inefficient for exploring multi-condition, multi-parameter designs. Conversely, purely data-driven methods are hindered by the scarcity of high-quality fatigue data. This paper proposes LightGBM-CH, an integrated framework that couples Discrete Element Method–Multi-Body Dynamics (DEM-MBD) simulation with an enhanced LightGBM model to overcome these limitations. The framework first converts high-fidelity simulations into a configurable data generator, producing batches of dynamic load–stress response data. A physics-informed feature engineering scheme then extracts 122 discriminative features characterizing six-dimensional loads, fatigue damage metrics, and load–stress coupling. To address the “small-sample, high-dimensional” challenge, a tailored training strategy incorporating robust scaling, correlation-based feature selection, and stability-constrained hyperparameter optimization is developed. Simulation experiments demonstrate that the LightGBM-CH model achieves a determination coefficient of 0.9251 and a root mean square error of 67.06, significantly outperforming benchmark models in accuracy and generalization. The study validates the framework’s engineering efficacy, identifies key influencing factors such as peak–stress ratio, and provides an intelligent, data-informed pathway for fatigue-resistant elastic wheel design. Full article

Background/Objectives: The mental health of Early Childhood Care professionals is of great importance to ensuring the quality of intervention and the well-being of families. The aim of this study was to analyze the relationship between coping strategies, perceived self-efficacy and levels of depression, anxiety and stress in Early Childhood Care professionals. Methods: A study was conducted with a sample of 125 professionals (87% women; M = 33.40, SD = 9.70). Participants completed the Coping Strategies Inventory, the General Self-Efficacy Scale, and the DASS-21. The sample was predominantly female, which should be considered when interpreting the findings. Results: Cognitive restructuring, positive restructuring, and social support were negatively associated with depression, anxiety, and stress, while social withdrawal was positively related to all these variables. Self-efficacy showed high negative correlations with psychological distress and was a strong protective predictor. Emotional expression showed a positive association with depression. Conclusions: Self-efficacy and adaptive coping strategies act as protective factors against psychological distress, while social withdrawal is a significant risk. These findings highlight the need to implement training and prevention programs primarily aimed at enhancing perceived self-efficacy, with adaptive coping strategies acting as behavioral mechanisms through which this protective factor is strengthened and maladaptive responses are reduced. Full article

Background/Objectives: This study examined relationships between diet quality, as determined using three a priori-defined dietary patterns (Healthy Eating Index of 2010 dietary guidelines [HEI-2010], Mediterranean Dietary Pattern [MDP], and Dietary Approaches to Stop Hypertension [DASH]), intestinal permeability, and features of the gut microbiota in a diverse, obese sample. Methods: This was a post hoc, cross-sectional study including 103 healthy, obese individuals (43.8 ± 11.3 years, BMI: 37.5 ± 6.1 kg/m², 64.1% African American). Dietary intake was assessed using the Vioscreen food frequency questionnaire. Intestinal permeability was assessed via urinary sugar excretion and microbiota features were characterized using 16S rRNA gene amplicon sequencing. Relationships between dietary pattern adherence, intestinal permeability, and gut microbiota were assessed using correlation coefficients and a general linear model. Results: Higher dietary pattern scores correlated with lower levels of intestinal permeability measures such as 24 h urinary sucralose (HEI-2010: r = −0.33, p = 0.002; MDP: r = −0.31, p = 0.004; DASH: r = −0.38, p < 0.0001) and 24 h sucralose-to-lactulose ratio (HEI-2010: r = −0.23, p = 0.03; MDP: r = −0.32, p = 0.003; DASH: r = −0.24, p = 0.03). Fruit intake consistently correlated with lower intestinal permeability measures (p < 0.05) across all three dietary patterns. Higher DASH scores correlated with lower Proteobacteria (r = −0.28, p = 0.004) and higher Verrucomicrobia (r = 0.30, p = 0.002) phylum abundance. Conclusions: The current results suggest a potential role for diet quality in promoting intestinal health. Full article