Benefits of Fruit and Vegetable Consumption on Prevalence of Metabolic Syndrome Are Independent of Physical Activity Behaviors in Older Adults

Although consumption of fruits and vegetables (FV) is suggested to reduce metabolic risk, there is a paucity of studies taking advantage of objectively assessed physical activity (PA) behaviors when exploring links between FV intake and metabolic syndrome (MetS) in older adults. The aim of the present study was to determine the relationship between FV intake and MetS prevalence in a population of older community-dwelling adults, while considering time spent being sedentary and health-enhancing PA. Prevalence of MetS was determined in a population of 93 men and 152 women (age: 65–70 years). FV intake was determined by self-report and PA behaviors (time spent in moderate-to-vigorous PA (MVPA) and in sedentary) were assessed by accelerometry. Likelihood of having MetS by FV intake was determined using logistic regression with stepwise backward elimination including age, sex, educational level, total energy intake, adherence to MVPA guideline and total sedentary time as covariates. A main finding was that lower FV intakes were significantly related to higher prevalence of MetS (odds ratio [OR]: 1.23; 95% confidence interval [CI]: 1.03–1.47) after considering potential influences by covariates. Additionally, we found that lower intake of vegetables but not fruits was significantly related to higher prevalence of MetS (OR: 1.47; 95%CI: 1.04–2.07). In conclusion, lower intakes of FV in general, and of vegetables in particular, significantly increased likelihood of MetS, regardless of time spent sedentary and adherence to the MVPA guideline. From a public health perspective, our findings emphasize adequate intakes of FV as an independent contributor to metabolic health status in older adults.

Artificial Neural Network (ANN) Modeling of Odor Threshold Property of Diverse Chemical Constituents of Black Tea and Coffee

The authors have developed an artificial neural network model using odor threshold (OT) property data for diverse odorant components present in black tea (76 components) and coffee (46 components). The models were validated in terms of both internal and external validation criteria signifying acceptable results. The authors found the significant features controlling the OT property using Mean Absolute Error (MAE)-based criteria in a backward elimination of descriptors, one in each turn. The present results well-corroborated the previously published PLS-regression based chemometric model results.

CT Angiography-Based Radiomics as a Tool for Carotid Plaque Characterization and Surgery Patient Selection: A Pilot Study

Objectives: Radiomics is a quantitative method able to analyze a high-throughput extraction of minable imaging features. Herein, we aim to develop a CT angiography-based radiomics analysis and machine learning model for carotid plaques to discriminate vulnerable from no vulnerable plaques.Methods: Thirty consecutive patients with carotid atherosclerosis were enrolled in this pilot study. At surgery, a binary classification of plaques was adopted (“hard” vs “soft”). Feature extraction was performed using the R software package Moddicom. Pairwise feature interdependencies were evaluated using the Spearman rank correlation coefficient. A univariate analysis was performed to assess the association between each feature and the plaque classification and chose top-ranked features. The feature predictive value was investigated using binary logistic regression. A stepwise backward elimination procedure was performed to minimize the Akaike information criterion (AIC). The final significant features were used to build the models for binary classification of carotid plaques, including logistic regression (LR), support vector machine (SVM), and classification and regression tree analysis (CART). All models were cross-validated using 5-fold cross validation. Class-specific accuracy, precision, recall and F-measure evaluation metrics were used to quantify classifier output quality.Results: A total of 230 radiomics features were extracted from each plaque. Pairwise Spearman correlation between features reported a high level of correlations, with more than 80% correlating with at least one other feature at |ρ| > 0.8. After a stepwise backward elimination procedure, the entropy and volume features were found to be the most significantly associated with the two plaque groups (p< 0.001), with AUCs of 0.92 and 0.96, respectively. The best performance was registered by the SVM classifier with the RBF kernel, with accuracy, precision, recall and F-score equal to 86.7, 92.9, 81.3 and 86.7%, respectively. The CART classification tree model for the entropy and volume features model achieved 86.7% well-classified plaques and an AUC of 0.987.Conclusion: This pilot study highlighted the potential of CTA-based radiomics and machine learning to discriminate plaque composition. This new approach has the potential to provide a reliable method to improve risk stratification in patients with carotid atherosclerosis.

Comparison of transverse versus longitudinal skin incisions for femoral endarterectomy and patchplasty

Introduction Access to the femoral artery for a femoral endarterectomy and patchplasty (CFE) can be undertaken either through transverse (TI) or longitudinal incision (LI). LIs have been shown in previous studies to have higher groin complications though these were undertaken in multiple types of vascular procedures. We looked at wound complications for patients undergoing elective CFE procedures only with or without angioplasty via TI or LI. Methods All patients who had undergone CFE were retrospectively analysed from a prospective database. Length of stay, wound complications and readmission rates were recorded. Factors for wound complication were looked at using logistic regression with backward elimination. Results 122 CFE procedures were performed (30 TI) over the study period. 92 (76.7%) of patients had a prosthetic patch used, whilst 57 (46.7%) patients underwent an adjunctive endovascular procedure, namely, iliac angioplasty and stenting. Median length of stay was 3 days for both groups. The wound complication rate was 6.7% in the TI group and 22.6% in the LI group. 85.6% of the wound complications were identified after discharge. 6/122 (4.9%) were readmitted for intravenous antibiotics, whilst others were managed in the outpatient setting. TI (aOR = 0.15; 95% 0.03–0.75) and combined open FE with endovascular revascularisation (aOR = 0.33; 95% 0.11–0.95) had protective effects on wound complications. Type of the patch used was not associated with any wound complications ( p = 0.07). Conclusion Compared to traditional LI, TI for CFE and OTA have lower risk of wound complications and reduced readmission rates in our series. We advocate adopting TI as the standard for femoral artery procedures rather than LI.

Data-driven optimization of brittleness index for hydraulic fracturing

Evaluation of brittleness index (BI) is a fundamental principle of a hydraulic fracturing design. A wide variety of BI calculations often baffle field engineers. The traditional value comparison may also not make the best of BI. Moreover, it is often mixed up with the fracability in field applications, thus causing concerns. We, therefore, redefine fracability as the fracturing pressure under certain rock mechanical (mainly brittleness), geological and injecting conditions to clarify the confusion. Then, we propose a data-driven workflow to optimize BIs by controlling the geological and injecting conditions. The machine learning (ML) workflow is employed to predict the fracability (fracturing pressure) based on field measurement. Three representative ML algorithms are applied to average the prediction, aiming to restrict the interference of algorithm performances. The contribution of brittleness on pressure/fracability prediction by error analysis (rather than the traditional method of BI-value comparison) is proposed as the new criterion for optimization. Six classic BI correlations (mineral-, logging- and elastic-based) are evaluated, three of which are optimized for the derivation of a new BI using the backward elimination strategy. The stress ratio (ratio of minimum and maximum horizontal principal stress), representing the geological feature, is introduced into the derived calculation based on the independent variable analysis. The reliability of the new BI is verified by error analyses using data of eight fracturing stages from seven different wells. Approximately 40%~50% of the errors are reduced based on the new BI. The differences among the performances of algorithms are also significantly restrained. The new brittleness index provides a more reliable option for evaluating the brittleness and fracability of the fracturing formation. The machine learning workflow also proposes a promising application scenario of the BI for hydraulic fracturing, which makes more efficient and broader usages of the BI compared with the traditional value comparison.

Diagnostic Criteria for the Painful Swollen Pediatric Knee: Distinguishing Septic Arthritis From Aseptic Effusion in a Non-Lyme Endemic Area

Purpose: The child with a painful swollen knee must be worked-up for possible septic arthritis; the classic clinical prediction algorithms for septic arthritis of the hip may not be the best models to apply to the knee.Materials and methods: This was a retrospective case-control study of 17 years of children presenting to one hospital with a chief complaint of a painful swollen knee, to evaluate the appropriateness of applying a previously described clinical practice algorithm for the hip in differentiating between the septic and aseptic causes of the painful knee effusions. The diagnoses of true septic arthritis, presumed septic arthritis, and aseptic effusion were established, based upon the cultures of synovial fluid, blood cultures, synovial cell counts, and clinical course. Using a logistic regression model, the disease status was regressed on both the demographic and clinical variables.Results: In the study, 122 patients were included: 51 with true septic arthritis, 37 with presumed septic arthritis, and 34 with aseptic knee effusion. After applying a backward elimination, age &lt;5 years and C-reactive protein (CRP) &gt;2.0 mg/dl remained in the model, and predicted probabilities of having septic knee arthritis ranged from 15% for the lowest risk to 95% for the highest risk. Adding a knee aspiration including percent polymorphonucleocytes (%PMN) substantially improved the overall model performance, lowering the lowest risk to 11% while raising the highest risk to 96%.Conclusions: This predictive model suggests that the likelihood of pediatric septic arthritis of the knee is &gt;90% when both “age &lt;5 years” and “CRP &gt; 2.0 mg/dl” are present in a child with a painful swollen knee, though, in the absence of these factors, the risk of septic arthritis remains over 15%. Aspiration of the knee for those patients would be the best next step.

The Predictors of Work-Related Stress: Organizational Justice and Fatalism

The purpose of the current study is to understand the relationship between organizational justice and the effect of the fatalism on work related stress. Although, organizational justice has been found to be a significant predictor of the work related stress in previous studies, fatalism which can be related with work related stress and organizational justice as well, has not been studied before together. In this correlational study, organizational justice, four dimensions of fatalism and job type were considered as predictors and work-related stress was the criterion variable. In total, 100 academics and 66 support staff have participated to this study. Multiple regression analysis with backward elimination was conducted. Results indicated that organizational justice, job type and luck were significant predictors of the work-related stress. While an increase on organizational justice perceptions lowers the work-related stress, luck and work-related stress seem increasing together. Additionally, academic personnel have higher stress levels than support staff. However, superstition, personal control, and predetermination dimensions of the fatalism were not found to be significantly associated with work related stress. Policy improvements were offered in line with the findings and recommendations for future studies were prescribed in discussion.