8% according to diagnosis by adjusted ferritin only and in 12.9% according to transferrin saturation. ID indicators were not significantly correlated with low hemoglobin levels. Malaria, fever, and CRP > 5 mg/L were major factors associated with anemia in Popokabaka. Anemia control should focus on treating inflammatory conditions and infectious diseases among children in such settings.The number of family caregivers to individuals with dementia is increasing. Family physicians are often the first point of access to the health care system for individuals with dementia and their caregivers. Caregivers are at an increased risk of developing negative physical, cognitive and affective health problems themselves. Caregivers also describe having unmet needs to help them sustain care in the community. Family physicians are in a unique position to help support caregivers and individuals with dementia, but often struggle with keeping up with best practice dementia service knowledge. The Dementia Wellness Questionnaire was designed to serve as a starting point for discussions between caregivers and family physicians by empowering caregivers to communicate their needs and concerns and to enhance family physicians’ access to specific dementia support information. The DWQ aims to alert physicians of caregiver and patient needs. This pilot study aimed to explore the experiences of physicians and caregivers of people using the Questionnaire in two family medicine clinics in Ontario, Canada. Interviews with physicians and caregivers collected data on their experiences using the DWQ following a 10-month data gathering period. Data was analyzed using content analysis. Results indicated that family physicians may have an improved efficacy in managing dementia by having dementia care case specific guidelines integrated within electronic medical records. By having time-efficient access to tailored supports, family physicians can better address the needs of the caregiver-patient dyad and help support family caregivers in their caregiving role. Caregivers expressed that the Questionnaire helped them remember concerns to bring up with physicians, in order to receive help in a more efficient manner.In this work, the composition of an electrolyte was selected and optimized to induce the formation of hydroxyapatite during Plasma electrolytic oxidation (PEO) treatment on an AZ31 alloy for application in bioabsorbable implants. In detail, the PEO process, called PEO-BIO (Plasma Electrolytic Oxidation-Biocompatible), was performed using a silicate-phosphate-based electrolyte with the addition of calcium oxide in direct-current mode using high current densities and short treatment times. For comparison, a known PEO process for producing anticorrosive coatings, called standard, was applied on the same alloy. The coatings were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD) and XPS analyses. The corrosion performance was evaluated in simulated body fluid (SBF) at 37 °C. The coating produced on the PEO-BIO sample was porous and thicker than the standard PEO one, with zones enriched in Ca and P. The XRD analysis showed the formation of hydroxyapatite and calcium oxides in addition to magnesium-silicon oxide and magnesium oxide in the PEO-BIO sample. read more The corrosion resistance of PEO-BIO sample was comparable with that of a traditional PEO treated sample, and higher than that of the untreated alloy.Machine learning (ML)-based algorithms are playing an important role in cancer diagnosis and are increasingly being used to aid clinical decision-making. However, these commonly operate as ‘black boxes’ and it is unclear how decisions are derived. Recently, techniques have been applied to help us understand how specific ML models work and explain the rational for outputs. This study aims to determine why a given type of cancer has a certain phenotypic characteristic. Cancer results in cellular dysregulation and a thorough consideration of cancer regulators is required. This would increase our understanding of the nature of the disease and help discover more effective diagnostic, prognostic, and treatment methods for a variety of cancer types and stages. Our study proposes a novel explainable analysis of potential biomarkers denoting tumorigenesis in non-small cell lung cancer. A number of these biomarkers are known to appear following various treatment pathways. An enhanced analysis is enabled through a novel mathematical formulation for the regulators of mRNA, the regulators of ncRNA, and the coupled mRNA-ncRNA regulators. Temporal gene expression profiles are approximated in a two-dimensional spatial domain for the transition states before converging to the stationary state, using a system comprised of coupled-reaction partial differential equations. Simulation experiments demonstrate that the proposed mathematical gene-expression profile represents a best fit for the population abundance of these oncogenes. In future, our proposed solution can lead to the development of alternative interpretable approaches, through the application of ML models to discover unknown dynamics in gene regulatory systems.(1) Background Lung cancer is silent in its early stages and fatal in its advanced stages. The current examinations for lung cancer are usually based on imaging. Conventional chest X-rays lack accuracy, and chest computed tomography (CT) is associated with radiation exposure and cost, limiting screening effectiveness. Breathomics, a noninvasive strategy, has recently been studied extensively. Volatile organic compounds (VOCs) derived from human breath can reflect metabolic changes caused by diseases and possibly serve as biomarkers of lung cancer. (2) Methods The selected ion flow tube mass spectrometry (SIFT-MS) technique was used to quantitatively analyze 116 VOCs in breath samples from 148 patients with histologically confirmed lung cancers and 168 healthy volunteers. We used eXtreme Gradient Boosting (XGBoost), a machine learning method, to build a model for predicting lung cancer occurrence based on quantitative VOC measurements. (3) Results The proposed prediction model achieved better performance than other previous approaches, with an accuracy, sensitivity, specificity, and area under the curve (AUC) of 0.