Understanding Early Childhood Engineering Interest Development as a Family-Level Systems Phenomenon: Findings from the Head Start on Engineering Project

There is growing recognition that interest is critical for engaging and supporting learners from diverse communities in engineering and other science, technology, engineering, and mathematics (STEM) topics. Although interest research has historically focused on older children, studies demonstrate that preschool-age and younger children also develop persistent, individualized interests in different objects, activities, and topics and that these early interests have important implications for ongoing learning and development. Unfortunately, there is relatively little research on engineering learning in early childhood and almost no work specific to the concept of interest. To begin to address this need, we conducted in-depth case study research with 15 English- and Spanish-speaking families and their preschool-age children participating in a family-based engineering education program through a local Head Start organization. Using systems theory to conceptualize interest development as involving the whole family, the study documented how both children and parents developed engineering-related interests through the program and explored the characteristics of and shifts in these interest systems. The qualitative, cross-case analysis highlighted three aspects of family-level interest development that varied across families and over time: (1) parent awareness, knowledge, and values; (2) family re-engagement with engineering activities; and (3) family use of the engineering design process. Shifts were also observed in a subset of the families that potentially signal movement toward deeper, sustained levels of engineering-related interest

A structured approach to hypotheses involving continuous exposures over the life course

© The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association. Background: Epidemiologists are often interested in examining different hypotheses for how exposures measured repeatedly over the life course relate to later-life outcomes. A structured approach for selecting the hypotheses most supported by theory and observed data has been developed for binary exposures. The aim of this paper is to extend this to include continuous exposures and allow for confounding and missing data. Methods: We studied two examples, the association between: (i) maternal weight during pregnancy and birthweight; and (ii) stressful family events throughout childhood and depression in adolescence. In each example we considered several plausible hypotheses including accumulation, critical periods, sensitive periods, change and effect modification. We used least angle regression to select the hypothesis that explained the most variation in the outcome, demonstrating appropriate methods for adjusting for confounders and dealing with missing data. Results: The structured approach identified a combination of sensitive periods: pre-pregnancy weight, and gestational weight gain 0-20 weeks and 20-40 weeks, as the best explanation for variation in birthweight after adjusting for maternal height. A sensitive period hypothesis best explained variation in adolescent depression, with the association strengthening with the proximity of stressful family events. For each example, these models have theoretical support at least as strong as any competing hypothesis. Conclusions: We have extended the structured approach to incorporate continuous exposures, confounding and missing data. This approach can be used in either an exploratory or a confirmatory setting. The interpretation, plausibility and consistency with causal assumptions should all be considered when proposing and choosing life course hypotheses

Relation of maternal prepregnancy body mass index with offspring bone mass in childhood: is there evidence for an intrauterine effect?1234

Background: Evidence indicates that intrauterine skeletal development has implications for bone mass in later life and that maternal fat stores in pregnancy are important for fetal bone mineral accrual

Designing personalised cancer treatments

The concept of personalised medicine for cancer is not new. It arguably began with the attempts by Salmon and Hamburger to produce a viable cellular chemosensitivity assay in the 1970s, and continues to this day. While clonogenic assays soon fell out of favour due to their high failure rate, other cellular assays fared better and although they have not entered widespread clinical practice, they have proved to be very useful research tools. For instance, the ATP-based chemosensitivity assay was developed in the early 1990s and is highly standardised. It has proved useful for evaluating new drugs and combinations, and in recent years has been used to understand the molecular basis of drug resistance and sensitivity to anti-cancer drugs. Recent developments allow unparalleled genotyping and phenotyping of tumours, providing a plethora of targets for the development of new cancer treatments. However, validation of such targets and new agents to permit translation to the clinic remains difficult. There has been one major disappointment in that cell lines, though useful, do not often reflect the behaviour of their parent cancers with sufficient fidelity to be useful. Low passage cell lines — either in culture or xenografts are being used to overcome some of these issues, but have several problems of their own. Primary cell culture remains useful, but large tumours are likely to receive neo-adjuvant treatment before removal and that limits the tumour types that can be studied. The development of new treatments remains difficult and prediction of the clinical efficacy of new treatments from pre-clinical data is as hard as ever. One lesson has certainly been that one cannot buck the biology — and that understanding the genome alone is not sufficient to guarantee success. Nowhere has this been more evident than in the development of EGFR inhibitors. Despite overexpression of EGFR by many tumour types, only those with activating EGFR mutations and an inability to circumvent EGFR blockade have proved susceptible to treatment. The challenge is how to use advanced molecular understanding with limited cellular assay information to improve both drug development and the design of companion diagnostics to guide their use. This has the capacity to remove much of the guesswork from the process and should improve success rates

Designing personalised cancer treatments

The concept of personalised medicine for cancer is not new. It arguably began with the attempts by Salmon and Hamburger to produce a viable cellular chemosensitivity assay in the 1970s, and continues to this day. While clonogenic assays soon fell out of favour due to their high failure rate, other cellular assays fared better and although they have not entered widespread clinical practice, they have proved to be very useful research tools. For instance, the ATP-based chemosensitivity assay was developed in the early 1990s and is highly standardised. It has proved useful for evaluating new drugs and combinations, and in recent years has been used to understand the molecular basis of drug resistance and sensitivity to anti-cancer drugs. Recent developments allow unparalleled genotyping and phenotyping of tumours, providing a plethora of targets for the development of new cancer treatments. However, validation of such targets and new agents to permit translation to the clinic remains difficult. There has been one major disappointment in that cell lines, though useful, do not often reflect the behaviour of their parent cancers with sufficient fidelity to be useful. Low passage cell lines — either in culture or xenografts are being used to overcome some of these issues, but have several problems of their own. Primary cell culture remains useful, but large tumours are likely to receive neo-adjuvant treatment before removal and that limits the tumour types that can be studied. The development of new treatments remains difficult and prediction of the clinical efficacy of new treatments from pre-clinical data is as hard as ever. One lesson has certainly been that one cannot buck the biology — and that understanding the genome alone is not sufficient to guarantee success. Nowhere has this been more evident than in the development of EGFR inhibitors. Despite overexpression of EGFR by many tumour types, only those with activating EGFR mutations and an inability to circumvent EGFR blockade have proved susceptible to treatment. The challenge is how to use advanced molecular understanding with limited cellular assay information to improve both drug development and the design of companion diagnostics to guide their use. This has the capacity to remove much of the guesswork from the process and should improve success rates

Detection of ctDNA from dried blood spots after DNA size selection

Background: Recent advances in the study and clinical applications of circulating tumor DNA (ctDNA) are limited by practical considerations of sample collection. Whole genome sequencing (WGS) is increasingly used for analysis of ctDNA, identifying copy-number alterations and fragmentation patterns. We hypothesized that low-depth/shallow WGS (sWGS) data may be generated from minute amounts of cell-free DNA, and that fragment-size selection may remove contaminating genomic DNA from small blood volumes. Dried blood spots have practical advantages for sample collection, may facilitate serial sampling, and could support novel study designs in humans and animal models. Methods: We developed a protocol for the isolation and analysis of cell-free DNA from dried blood spots using filter paper cards and bead-based size selection. DNA extracted and size-selected from dried spots was analyzed using sWGS and PCR. Results: Analyzing a 50L dried blood spot from frozen whole blood of a patient with melanoma, we identified ctDNA based on the presence of tumor-specific somatic copy-number alterations, and found a fragment size profile similar to that observed in plasma DNA. We found alterations in different chromosomes in blood-spots from two patients with high-grade serous ovarian carcinoma. Extending this approach to serial dried blood spots from mouse xenograft models, we detect tumor-derived cell-free DNA and identified ctDNA from the originally grafted ascites. Conclusion: Our data suggest that ctDNA can be detected and monitored in dried blood spots from archived and fresh blood samples, enabling new approaches for sample collection and novel study/trial designs for both patients and in vivo models.The University of Cambridge and Cancer Research UK (grant numbers A20240 and A29580). The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement n.337905. Healthy volunteer samples were provided by the Cambridge Blood and Stem Cell Biobank, which is supported by the Cambridge NIHR Biomedical Research Centre, Wellcome Trust - MRC Stem Cell Institute and the Cambridge Experimental Cancer Medicine Centre, UK

The impact of the COVID-19 pandemic upon pancreatic cancer treatment (CONTACT Study): a UK national observational cohort study.

INTRODUCTION: CONTACT is a national multidisciplinary study assessing the impact of the COVID-19 pandemic upon diagnostic and treatment pathways among patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: The treatment of consecutive patients with newly diagnosed PDAC from a pre-COVID-19 pandemic cohort (07/01/2019-03/03/2019) were compared to a cohort diagnosed during the first wave of the UK pandemic ('COVID' cohort, 16/03/2020-10/05/2020), with 12-month follow-up. RESULTS: Among 984 patients (pre-COVID: n = 483, COVID: n = 501), the COVID cohort was less likely to receive staging investigations other than CT scanning (29.5% vs. 37.2%, p = 0.010). Among patients treated with curative intent, there was a reduction in the proportion of patients recommended surgery (54.5% vs. 76.6%, p = 0.001) and increase in the proportion recommended upfront chemotherapy (45.5% vs. 23.4%, p = 0.002). Among patients on a non-curative pathway, fewer patients were recommended (47.4% vs. 57.3%, p = 0.004) or received palliative anti-cancer therapy (20.5% vs. 26.5%, p = 0.045). Ultimately, fewer patients in the COVID cohort underwent surgical resection (6.4% vs. 9.3%, p = 0.036), whilst more patients received no anti-cancer treatment (69.3% vs. 59.2% p = 0.009). Despite these differences, there was no difference in median overall survival between the COVID and pre-COVID cohorts, (3.5 (IQR 2.8-4.1) vs. 4.4 (IQR 3.6-5.2) months, p = 0.093). CONCLUSION: Pathways for patients with PDAC were significantly disrupted during the first wave of the COVID-19 pandemic, with fewer patients receiving standard treatments. However, no significant impact on survival was discerned

Are we over-treating with checkpoint inhibitors?

Anti-PD-1 antibodies offer potentially life-saving treatment for some cancer patients, but their chronic administration generates high and ever-increasing costs. Despite licensing for long-term use, optimal treatment duration is unknown. We challenge the need for long-term treatment duration, using evidence from melanoma research, both published and in process