Forecasting Tunisian type 2 diabetes prevalence to 2027: validation of a simple model.

BACKGROUND: Most projections of type 2 diabetes (T2D) prevalence are simply based on demographic change (i.e. ageing). We developed a model to predict future trends in T2D prevalence in Tunisia, explicitly taking into account trends in major risk factors (obesity and smoking). This could improve assessment of policy options for prevention and health service planning. METHODS: The IMPACT T2D model uses a Markov approach to integrate population, obesity and smoking trends to estimate future T2D prevalence. We developed a model for the Tunisian population from 1997 to 2027, and validated the model outputs by comparing with a subsequent T2D prevalence survey conducted in 2005. RESULTS: The model estimated that the prevalence of T2D among Tunisians aged over 25 years was 12.0% in 1997 (95% confidence intervals 9.6%-14.4%), increasing to 15.1% (12.5%-17.4%) in 2005. Between 1997 and 2005, observed prevalence in men increased from 13.5% to 16.1% and in women from 12.9% to 14.1%. The model forecast for a dramatic rise in prevalence by 2027 (26.6% overall, 28.6% in men and 24.7% in women). However, if obesity prevalence declined by 20% in the 10 years from 2013, and if smoking decreased by 20% over 10 years from 2009, a 3.3% reduction in T2D prevalence could be achieved in 2027 (2.5% in men and 4.1% in women). CONCLUSIONS: This innovative model provides a reasonably close estimate of T2D prevalence for Tunisia over the 1997-2027 period. Diabetes burden is now a significant public health challenge. Our model predicts that this burden will increase significantly in the next two decades. Tackling obesity, smoking and other T2D risk factors thus needs urgent action. Tunisian decision makers have therefore defined two strategies: obesity reduction and tobacco control. Responses will be evaluated in future population surveys

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care

Gender Differences and Effect of Air Pollution on Asthma in Children with and without Allergic Predisposition: Northeast Chinese Children Health Study

BACKGROUND: Males and females exhibit different health responses to air pollution, but little is known about how exposure to air pollution affects juvenile respiratory health after analysis stratified by allergic predisposition. The aim of the present study was to assess the relationship between air pollutants and asthmatic symptoms in Chinese children selected from multiple sites in a heavily industrialized province of China, and investigate whether allergic predisposition modifies this relationship. METHODOLOGY/PRINCIPAL FINDINGS: 30139 Chinese children aged 3-to-12 years were selected from 25 districts of seven cities in northeast China in 2009. Information on respiratory health was obtained using a standard questionnaire from the American Thoracic Society. Routine air-pollution monitoring data was used for particles with an aerodynamic diameter ≤10 µm (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxides (NO(2)), ozone (O(3)) and carbon monoxide (CO). A two-stage regression approach was applied in data analyses. The effect estimates were presented as odds ratios (ORs) per interquartile changes for PM(10), SO(2), NO(2), O(3), and CO. The results showed that children with allergic predisposition were more susceptible to air pollutants than children without allergic predisposition. Amongst children without an allergic predisposition, air pollution effects on asthma were stronger in males compared to females; Current asthma prevalence was related to PM(10) (ORs = 1.36 per 31 µg/m(3); 95% CI, 1.08-1.72), SO(2) (ORs = 1.38 per 21 µg/m(3); 95%CI, 1.12-1.69) only among males. However, among children with allergic predisposition, more positively associations between air pollutants and respiratory symptoms and diseases were detected in females; An increased prevalence of doctor-diagnosed asthma was significantly associated with SO(2) (ORs = 1.48 per 21 µg/m(3); 95%CI, 1.21-1.80), NO(2) (ORs = 1.26 per 10 µg/m(3); 95%CI, 1.01-1.56), and current asthma with O(3) (ORs = 1.55 per 23 µg/m(3); 95%CI, 1.18-2.04) only among females. CONCLUSION/SIGNIFICANCE: Ambient air pollutions were more evident in males without an allergic predisposition and more associations were detected in females with allergic predisposition

Can FDG PET predict radiation treatment outcome in head and neck cancer? Results of a prospective study

Contains fulltext : 96692.pdf (publisher's version ) (Closed access)PURPOSE: In head and neck cancer (HNC) various treatment strategies have been developed to improve outcome, but selecting patients for these intensified treatments remains difficult. Therefore, identification of novel pretreatment assays to predict outcome is of interest. In HNC there are indications that pretreatment tumour (18)F-fluorodeoxyglucose (FDG) uptake may be an independent prognostic factor. The aim of this study was to assess the prognostic value of FDG uptake and CT-based and FDG PET-based primary tumour volume measurements in patients with HNC treated with (chemo)radiotherapy. METHODS: A total of 77 patients with stage II-IV HNC who were eligible for definitive (chemo)radiotherapy underwent coregistered pretreatment CT and FDG PET. The gross tumour volume of the primary tumour was determined on the CT (GTV(CT)) and FDG PET scans. Five PET segmentation methods were applied: interpreting FDG PET visually (PET(VIS)), applying an isocontour at a standardized uptake value (SUV) of 2.5 (PET(2.5)), using fixed thresholds of 40% and 50% (PET(40%), PET(50%)) of the maximum intratumoral FDG activity (SUV(MAX)) and applying an adaptive threshold based on the signal-to-background (PET(SBR)). Mean FDG uptake for each PET-based volume was recorded (SUV(mean)). Subsequently, to determine the metabolic volume, the integrated SUV was calculated as the product of PET-based volume and SUV(mean). All these variables were analysed as potential predictors of local control (LC), regional recurrence-free survival (RRFS), distant metastasis-free survival (DMFS), disease-free survival (DFS) and overall survival (OS). RESULTS: In oral cavity/oropharynx tumours PET(VIS) was the only volume-based method able to predict LC. Both PET(VIS) and GTV(CT) were able to predict DMFS, DFS and OS in these subsites. Integrated SUVs were associated with LC, DMFS, DFS and OS, while SUV(mean) and SUV(MAX) were not. In hypopharyngeal/laryngeal tumours none of the variables was associated with outcome. CONCLUSION: There is no role yet for pretreatment FDG PET as a predictor of (chemo)radiotherapy outcome in HNC in daily routine. However, this potential application needs further exploration, focusing both on FDG PET-based primary tumour volume, integrated SUV and SUV(MAX) of the primary tumour

Protein Diffusion in Mammalian Cell Cytoplasm

We introduce a new method for mesoscopic modeling of protein diffusion in an entire cell. This method is based on the construction of a three-dimensional digital model cell from confocal microscopy data. The model cell is segmented into the cytoplasm, nucleus, plasma membrane, and nuclear envelope, in which environment protein motion is modeled by fully numerical mesoscopic methods. Finer cellular structures that cannot be resolved with the imaging technique, which significantly affect protein motion, are accounted for in this method by assigning an effective, position-dependent porosity to the cell. This porosity can also be determined by confocal microscopy using the equilibrium distribution of a non-binding fluorescent protein. Distinction can now be made within this method between diffusion in the liquid phase of the cell (cytosol/nucleosol) and the cytoplasm/nucleoplasm. Here we applied the method to analyze fluorescence recovery after photobleach (FRAP) experiments in which the diffusion coefficient of a freely-diffusing model protein was determined for two different cell lines, and to explain the clear difference typically observed between conventional FRAP results and those of fluorescence correlation spectroscopy (FCS). A large difference was found in the FRAP experiments between diffusion in the cytoplasm/nucleoplasm and in the cytosol/nucleosol, for all of which the diffusion coefficients were determined. The cytosol results were found to be in very good agreement with those by FCS

Structure and Dynamics of the G121V Dihydrofolate Reductase Mutant: Lessons from a Transition-State Inhibitor Complex

It is well known that enzyme flexibility is critical for function. This is due to the observation that the rates of intramolecular enzyme motions are often matched to the rates of intermolecular events such as substrate binding and product release. Beyond this role in progression through the reaction cycle, it has been suggested that enzyme dynamics may also promote the chemical step itself. Dihydrofolate reductase (DHFR) is a model enzyme for which dynamics have been proposed to aid in both substrate flux and catalysis. The G121V mutant of DHFR is a well studied form that exhibits a severe reduction in the rate of hydride transfer yet there remains dispute as to whether this defect is caused by altered structure, dynamics, or both. Here we address this by presenting an NMR study of the G121V mutant bound to reduced cofactor and the transition state inhibitor, methotrexate. NMR chemical shift markers demonstrate that this form predominantly adopts the closed conformation thereby allowing us to provide the first glimpse into the dynamics of a catalytically relevant complex. Based on 15N and 2H NMR spin relaxation, we find that the mutant complex has modest changes in ps-ns flexibility with most affected residues residing in the distal adenosine binding domain rather than the active site. Thus, aberrant ps-ns dynamics are likely not the main contributor to the decreased catalytic rate. The most dramatic effect of the mutation involves changes in µs-ms dynamics of the F-G and Met20 loops. Whereas loop motion is quenched in the wild type transition state inhibitor complex, the F-G and Met20 loops undergo excursions from the closed conformation in the mutant complex. These excursions serve to decrease the population of conformers having the correct active site configuration, thus providing an explanation for the G121V catalytic defect

Phase II Trial of Concurrent Sunitinib and Image-Guided Radiotherapy for Oligometastases

BACKGROUND: Preclinical data suggest that sunitinib enhances the efficacy of radiotherapy. We tested the combination of sunitinib and hypofractionated image-guided radiotherapy (IGRT) in a cohort of patients with historically incurable distant metastases. METHODS: Twenty five patients with oligometastases, defined as 1-5 sites of active disease on whole body imaging, were enrolled in a phase II trial from 2/08 to 9/10. The most common tumor types treated were head and neck, liver, lung, kidney and prostate cancers. Patients were treated with the recommended phase II dose of 37.5 mg daily sunitinib (days 1-28) and IGRT 50 Gy (days 8-12 and 15-19). Maintenance sunitinib was used in 33% of patients. Median follow up was 17.5 months (range, 0.7 to 37.4 months). RESULTS: The 18-month local control, distant control, progression-free survival (PFS) and overall survival (OS) were 75%, 52%, 56% and 71%, respectively. At last follow-up, 11 (44%) patients were alive without evidence of disease, 7 (28%) were alive with distant metastases, 3 (12%) were dead from distant metastases, 3 (12%) were dead from comorbid illness, and 1 (4%) was dead from treatment-related toxicities. The incidence of acute grade ≥ 3 toxicities was 28%, most commonly myelosuppression, bleeding and abnormal liver function tests. CONCLUSIONS: Concurrent sunitinib and IGRT achieves major clinical responses in a subset of patients with oligometastases. TRIAL REGISTRATION: ClinicalTrials.gov NCT00463060

EMF1 and PRC2 Cooperate to Repress Key Regulators of Arabidopsis Development

EMBRYONIC FLOWER1 (EMF1) is a plant-specific gene crucial to Arabidopsis vegetative development. Loss of function mutants in the EMF1 gene mimic the phenotype caused by mutations in Polycomb Group protein (PcG) genes, which encode epigenetic repressors that regulate many aspects of eukaryotic development. In Arabidopsis, Polycomb Repressor Complex 2 (PRC2), made of PcG proteins, catalyzes trimethylation of lysine 27 on histone H3 (H3K27me3) and PRC1-like proteins catalyze H2AK119 ubiquitination. Despite functional similarity to PcG proteins, EMF1 lacks sequence homology with known PcG proteins; thus, its role in the PcG mechanism is unclear. To study the EMF1 functions and its mechanism of action, we performed genome-wide mapping of EMF1 binding and H3K27me3 modification sites in Arabidopsis seedlings. The EMF1 binding pattern is similar to that of H3K27me3 modification on the chromosomal and genic level. ChIPOTLe peak finding and clustering analyses both show that the highly trimethylated genes also have high enrichment levels of EMF1 binding, termed EMF1_K27 genes. EMF1 interacts with regulatory genes, which are silenced to allow vegetative growth, and with genes specifying cell fates during growth and differentiation. H3K27me3 marks not only these genes but also some genes that are involved in endosperm development and maternal effects. Transcriptome analysis, coupled with the H3K27me3 pattern, of EMF1_K27 genes in emf1 and PRC2 mutants showed that EMF1 represses gene activities via diverse mechanisms and plays a novel role in the PcG mechanism

Clotrimazole Preferentially Inhibits Human Breast Cancer Cell Proliferation, Viability and Glycolysis

BACKGROUND: Clotrimazole is an azole derivative with promising anti-cancer effects. This drug interferes with the activity of glycolytic enzymes altering their cellular distribution and inhibiting their activities. The aim of the present study was to analyze the effects of clotrimazole on the growth pattern of breast cancer cells correlating with their metabolic profiles. METHODOLOGY/PRINCIPAL FINDINGS: Three cell lines derived from human breast tissue (MCF10A, MCF-7 and MDA-MB-231) that present increasingly aggressive profiles were used. Clotrimazole induces a dose-dependent decrease in glucose uptake in all three cell lines, with K(i) values of 114.3±11.7, 77.1±7.8 and 37.8±4.2 µM for MCF10A, MCF-7 and MDA-MB-231, respectively. Furthermore, the drug also decreases intracellular ATP content and inhibits the major glycolytic enzymes, hexokinase, phosphofructokinase-1 and pyruvate kinase, especially in the highly metastatic cell line, MDA-MB-231. In this last cell lineage, clotrimazole attenuates the robust migratory response, an effect that is progressively attenuated in MCF-7 and MCF10A, respectively. Moreover, clotrimazole reduces the viability of breast cancer cells, which is more pronounced on MDA-MB-231. CONCLUSIONS/SIGNIFICANCE: Clotrimazole presents deleterious effects on two human breast cancer cell lines metabolism, growth and migration, where the most aggressive cell line is more affected by the drug. Moreover, clotrimazole presents little or no effect on a non-tumor human breast cell line. These results suggest, at least for these three cell lines studied, that the more aggressive the cell is the more effective clotrimazole is