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Our results support promotion of supplementation of vitamin D among older adults as a cost-saving approach to substantially reduce cancer mortality.An omphalocele is a congenital defect in the abdominal wall characterized by absent abdominal muscles, fascia, and skin. The characteristic ultrasound appearance includes a midline defect with herniation of abdominal contents into the base of the umbilical cord. Other anatomic abnormalities are seen in approximately 50% of cases, most notably cardiac defects (19%-32%). Approximately, 50% of cases are associated with genetic and multiple malformation syndromes including trisomy 13/18, pentalogy of Cantrell and Beckwith-Wiedemann syndrome. Therefore, a thorough evaluation is recommended, including detailed anatomic survey, fetal echocardiogram, genetic counseling, and prenatal diagnostic testing. Overall prognosis depends on the size of the omphalocele, genetic studies, and associated anomalies. Early prenatal diagnosis remains important in order to provide parental counseling and assist in pregnancy management. Delivery should occur at a tertiary care center. Timing and mode of delivery should be based on standard obstetric indications with cesarean delivery reserved for large omphalocele (>5 cm) or those that involve the fetal liver. Neonatal management involves either primary or staged reduction, both of which can be associated with a prolonged neonatal hospitalization.Health and development indicators (HDIs) such as vaccination coverage are regularly measured in many low- and middle-income countries using household surveys, often due to the unreliability or incompleteness of routine data collection systems. Recently, the development of model-based approaches for producing subnational estimates of HDIs using survey data, particularly cluster-level data, has been an active area of research. This is mostly driven by the increasing demand for estimates at certain administrative levels, for example, districts, at which many development goals are set and evaluated. In this study, we explore spatial modeling approaches for producing district-level estimates of vaccination coverage. Specifically, we compare discrete spatial smoothing models which directly model district-level data with continuous Gaussian process (GP) models that utilize geolocated cluster-level data. We adopt a fully Bayesian framework, implemented using the INLA and SPDE approaches. We compare the predictive performance of the models by analyzing vaccination coverage using data from two Demographic and Health Surveys (DHS), namely the 2014 Kenya DHS and the 2015-16 Malawi DHS. We find that the continuous GP models performed well, offering a credible alternative to traditional discrete spatial smoothing models. Our analysis also revealed that accounting for between-cluster variation in the continuous GP models did not have any real effect on the district-level estimates. Our results provide guidance to practitioners on the reliability of these model-based approaches for producing estimates of vaccination coverage and other HDIs.Development of cancer screening biomarkers usually follows the Early Detection Research Network 5-Phase guideline in Pepe et al. A key feature of this guide is that the phased development follows a sequential order, moving to the next phase only when the current phase study is complete and has met its target performance. Motivated by a newly funded Newly onset Diabetes cohort study, we propose a design evaluating new biomarkers to discriminate between cases and controls in the presence of an existing screening test. The proposed design achieves two goals (1) avoiding bias in estimating sensitivity or specificity in predicting cancer at a given time period prior to clinical diagnosis, using data from both screening detected cancers in Phase IV study and clinically diagnosed cancers in Phase III study; and (2) building a panel with biomarkers for Phase III and IV studies based on all data. A simulation study shows that the proposed design outperforms both a conventional method using data in Phase III arm only and a naive method using data in Phase III and IV arms ignoring the difference between the time of screening the detected cancer and the time of clinical diagnosis. The proposed design yields a smaller standard error of the estimation and increases the statistical power to confirm biomarker performance. This proposed method has the potential to shorten the cancer screening biomarker development process, use resources more effectively, and bring benefits to patients quickly.Epidermal growth factor receptor (EGFR) is often overexpressed in head and neck squamous cell carcinoma (HNSCC) and represents a top candidate for targeted HNSCC therapy. However, the clinical effectiveness of current Food and Drug Administration (FDA)-approved drugs targeting EGFR is moderate, and the overall survival rate for HNSCC patients remains low. Therefore, more effective treatments are urgently needed. learn more In this study, we generated a novel diphtheria toxin-based bivalent human epidermal growth factor fusion toxin (bi-EGF-IT) to treat EGFR-expressing HNSCC. Bi-EGF-IT was tested for in vitro binding affinity, cytotoxicity, and specificity using 14 human EGFR-expressing HNSCC cell lines and three human EGFR-negative cancer cell lines. Bi-EGF-IT had increased binding affinity for EGFR-expressing HNSCC compared with the monovalent version (mono-EGF-IT), and both versions specifically depleted EGFR-positive HNSCC, but not EGFR-negative cell lines, in vitro. Bi-EGF-IT exhibited a comparable potency to that of the FDA-approved EGFR inhibitor, erlotinib, for inhibiting HNSCC tumor growth in vivo using both subcutaneous and orthotopic HNSCC xenograft mouse models. When tested in an experimental metastasis model, survival was significantly longer in the bi-EGF-IT treatment group than the erlotinib treatment group, with a significantly reduced number of metastases compared with mono-EGF-IT. In addition, in vivo off-target toxicities were significantly reduced in the bi-EGF-IT treatment group compared with the mono-EGF-IT group. These results demonstrate that bi-EGF-IT is more effective and markedly less toxic at inhibiting primary HNSCC tumor growth and metastasis than mono-EGF-IT and erlotinib. Thus, the novel bi-EGF-IT is a promising drug candidate for further development.