Search

Additional file1. Appendix A: Embase search strategy for literature mapping exercise. Appendix B: Ovid MEDLINE search strategy for systematic review. Appendix C: Full results from literature mapping exercise. Appendix D: Risk of bias and measurement property appraisal results. Appendix E: Data extraction table of measurement properties.

This thesis investigated free sugar (FS) intake from snacks and beverages among young Canadian children and compared intake with World Health Organization recommendations that FS intake be limited to

A nomogram was recently published by Sun et al. to predict overall survival (OS) and the additional benefit of concurrent chemoradiation (CCRT) vs. radiotherapy (RT) alone, in stage II NPC treated with conventional RT. We aimed to assess the predictors of OS and to externally validate the nomogram in the IMRT era. We analyzed stage II NPC patients treated with definitive RT alone or CCRT between 2001 and 2011 under the territory-wide Hong Kong NPC Study Group 1301 study. Clinical parameters were studied using the Cox proportional hazards model to estimate OS. The nomogram by Sun et al. was applied with 1000 times bootstrap resampling to calculate the concordance index, and we compared the nomogram predicted and observed 5-year OS. There were 482 patients included. The 5-year OS was 89.0%. In the multivariable analysis, an age &gt, 45 years was the only significant predictor of OS (HR, 1.98, 95%CI, 1.15–3.44). Other clinical parameters were insignificant, including the use of CCRT (HR, 0.99, 95%CI, 0.62–1.58). The nomogram yielded a concordance index of 0.55 (95% CI, 0.49–0.62) which lacked clinically meaningful discriminative power. The nomogram proposed by Sun et al. should be interpreted with caution when applied to stage II NPC patients in the IMRT era. The benefit of CCRT remained controversial.

e18029 Background: Patients with recurrent or metastatic nasopharyngeal cancer (R/M NPC) who failed platinum-based chemotherapy have poor prognoses. We report the clinical activity and safety of bintrafusp alfa, a first-in-class bifunctional fusion protein composed of the extracellular domain of the transforming growth factor (TGF)-βRII receptor fused to a human IgG1 antibody blocking programmed death-ligand 1 (PD-L1), in patients with heavily pretreated R/M NPC. Tumor and plasma-based biomarkers were investigated in an exploratory analysis. Methods: Eligible patients had histologically confirmed NPC that had recurred at distant sites and were not amenable to curative treatment. All patients received at least one prior line of platinum-based chemotherapy for recurrent disease. Patients were treated with bintrafusp alfa (1200mg every 2 weeks) until disease progression. The sample size was estimated to assume a 40% objective response rate (ORR) to bintrafusp alfa compared with 20% for checkpoint inhibitors. Modified Simon two-stage optimal design was used (power, 80%; a = 0.05; P0 = 0.20; P1 = 0.40; n1 = 18; n = 33 with an additional five patients to allow for ineligibility or other reasons). The primary endpoint was ORR and secondary endpoints included survival and toxicity. Expression of PD-L1 in archived tumors, plasma clearance of Epstein-Barr virus (EBV) DNA, plasma clearance of TGF-β, and exosomal PD-L1 were assessed for a potential correlation with ORR. (NCT 04396886). Results: Out of 43 patients screened, 38 patients were enrolled. After a median follow-up of 14.9 months (range: 1.6-23.3 months), the confirmed ORR was 23.7% (95% CI: 12.4-38.8%) (complete response, n = 1; partial response, n = 8). The median treatment duration was 1.8 months (range: 0.5-14.3 months). 8 patients (21.1%) and 2 patients (5.3%) received bintrafusp alfa for > 6 months and > 12 months respectively. The 1-year overall survival (OS) rate was 57.5% (95% CI, 40.2% to 71.5%) and 1-year progression-free survival rate was 23% (95% CI, 10.1% to 39.4%). ORR was higher in patients with a decreasing trend in EBV-DNA at week 4 (40% vs. 6.3%, p = 0.02), whereas high exosomal PD-L1 levels at week 4 were predictive of worse ORR (5.3% vs. 41.7%, p = 0.012). There were no associations between clinical outcome and tissue PD-L1 expression (p = 0.952) or plasma TGF-β clearance (p = 0.28). 16 patients (42.4%) experienced ≥ grade 3 treatment-related adverse events, most commonly anemia (n = 9, 23.7%) and secondary malignancies (n = 4, 10.5%). Conclusions: Bintrafusp alfa has promising activity in heavily pretreated R/M NPC and a favorable 1-year OS rate, though the observed activity was not as high as the study initially aimed. The biomarker results warrant validation in larger cohorts. Clinical trial information: NCT04396886.

Urbanisation and climate change are expected to introduce novel public health, environmental, and sustainability challenges. Epidemiological studies indicate that climate and public health vulnerabilities vary by neighbourhood. However, data at these spatial levels are largely unavailable despite studies demonstrating that geographically aggregated data mask disparities. To address this gap, this dissertation developed and applied high resolution geospatial vulnerability and health indicators across British Columbia (BC), Canada. The first dataset applied principal components analysis to more than 30 measures to map exposures, population sensitivities, adaptive capacities, and overall vulnerabilities of four climate hazards (extreme heat, inland flooding and sea level rise, wildfire smoke, and ground-level ozone) across 4188 dissemination areas in two health regions. A principal components analysis revealed varied opportunities for adaptive capacities across all hazards (16%-47% contribution to variation in overall vulnerability), with the greatest contribution found for flooding (47%). Overall, sensitivity explained the most variance, suggesting strategies targeting age and those with pre-existing health conditions in public health and emergency responses. Building on this result, the second dataset linked mortality data and sociodemographic information in a Bayesian small area model to estimate life expectancy (LE) at birth and 20 causes of mortality over 27 years across 368 Census Tracts (CTs) in Metro Vancouver, BC. The dataset identified spatial LE gaps of more than 10 years that widened in recent years. Absolute inequalities decreased for all diseases except for neoplasms, but relative inequalities increased for all causes. In the final study, difference-in-differences models were applied to the small area mortality data to evaluate relationships with population density and sociodemographic measures to assess optimum density levels, and the effects of density changes over time. At densities above ~9,400 persons per km2, LE began to decrease more rapidly. By cause, densification was linked to decreased mortality for major causes of mortality in the region, such as cardiovascular diseases, neoplasms, and diabetes. Through these three studies, this dissertation provided evidence for the importance of local-level indicators of health, vulnerability, and built environment variables for future and ongoing surveillance of healthy and resilient cities.

Additional file 5.

Additional file 6.

Additional file 2.

Additional file 4.

Artificial neural networks (ANNs) are popular machine learning techniques used to model autonomous agents. Spiking neural networks (SNNs) provide the ability to reproduce spatio-temporal dynamics by transmitting information through action potentials or spikes. Given their more biologically realistic characteristic, they are particularly attractive for modelling biological systems, including the analysis and understanding of biological self organisation. As with many neural models, the difficulty in achieving the desired performance is finding the appropriate parameters settings. A commonly used autonomous approach is given by genetic algorithms (GAs), which provide an evolution-based search technique inspired by natural adaptation processes. The performance of these meta-heuristic search techniques depends on the settings of its hyperparameters, which present a challenging task on their own.In this work, a multi-agent simulation model embedded in NetLogo is investigated. It simulates an artificial ant navigating through a virtual maze with many obstacles in search of food. Through this process the ant is controlled by an SNN, whose parameter optimisation is examined and optimised in this thesis using GAs of two different tools (L2L and BehaviorSearch). Afterwards, a deeper investigation on the optimized SNNs is covered to understand and explain the observed behavior in the simulation.

Additional file 3.