Stratification of skewed populations

In this research an algorithm is derived for stratifying skewed populations which is much simpler to implement than any of those currently available. It is based on the suggestion by numerous researchers in the field that it is desirable when stratifying skewed populations to arrange for equal coefficients of variation in each subinterval. Our new algorithm makes the breaks in geometric progression and achieves near-equal stratum coefficients of variation when the populations are skewed. Simulation studies on real skewed populations have shown that the new method compares favourably to those commonly used in terms of precision of the estimator of the mean. We also apply the geometric method to the Lavallée-Hidiroglou (1988) algorithm, an iterative method designed specifically for skewed populations. We show that by taking geometric boundaries as the starting points results in most cases in quicker convergence of the algorithm and achieves smaller sample sizes than the default starting points for the same precision. Finally, geometric stratification is applied to the Pareto distribution, a typical model of skewed data. We show that if any finite range of this distribution is broken into a given number of strata, with boundaries obtained using geometric progression, then the stratum coefficients of variation are equal

Aging is associated with a prefrontal lateral-medial shift during picture-induced negative affect

The capacity to adaptively respond to negative emotion is in part dependent upon lateral areas of the prefrontal cortex (PFC). Lateral PFC areas are particularly susceptible to age-related atrophy, which affects executive function (EF). We used structural and functional magnetic resonance imaging (MRI) to test the hypothesis that older age is associated with greater medial PFC engagement during processing of negative information, and that this engagement is dependent upon the integrity of grey matter structure in lateral PFC as well as EF. Participants (n = 64, 38–79 years) viewed negative and neutral scenes while in the scanner, and completed cognitive tests as part of a larger study. Grey matter probability (GMP) was computed to index grey matter integrity. FMRI data demonstrated less activity in the left ventrolateral PFC (VLPFC) and greater ventromedial PFC (VMPFC) activity with increasing age during negative-picture viewing. Age did not correlate with amygdala responding. GMP in VLPFC and EF were negatively associated with VMPFC activity. We conclude that this change from lateral to medial PFC engagement in response to picture-induced negative affect reflects decreased reliance on executive function-related processes, possibly associated with reduced grey matter in lateral PFC, with advancing age to maintain emotional functioning

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

An investigation into the utility of guilt by association machine learning algorithms for the prioritization of autism spectrum disorder candidate risk genes

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and communication, and restrictive repetitive behaviours or interests, with extreme phenotypic and genetic heterogeneity. Currently, genetic association studies have identified 90 risk genes with high confidence out of an estimated 1000. Researchers have begun to use machine learning methods leveraging heterogeneous biological network data in attempts to aid in discovery of ASD risk genes. However, the real-world utility of these studies is questionable: network-based machine learners are often biased towards well studied genes because they operate on a principle called “guilty by association.” In this thesis, I evaluate and compare genetic and computation approaches to ASD risk gene prioritization. I demonstrate that network-based computational approaches are adding little additional useful information compared to genetic approaches for prioritization. Furthermore, I demonstrate that gene expression profiles, and generic measures of disease gene likelihood may provide less biased contextual information that can be used to supplement genetic association data to prioritize ASD risk genes. Lastly, I discuss how data quality and data dependence impacts evaluation of machine learning algorithms and genetic association studies.Science, Faculty ofGraduat

Improving late life depression and cognitive control through the use of therapeutic video game technology: A proof‐of‐concept randomized trial

BackgroundExisting treatments for depression are known to have only modest effects, are insufficiently targeted, and are inconsistently utilized, particularly in older adults. Indeed, older adults with impaired cognitive control networks tend to demonstrate poor response to a majority of existing depression interventions. Cognitive control interventions delivered using entertainment software have the potential to not only target the underlying cerebral dysfunction associated with depression, but to do so in a manner that is engaging and engenders adherence to treatment protocol.MethodsIn this proof-of-concept trial (Clinicaltrials.gov #: NCT02229188), individuals with late life depression (LLD) (22; 60+ years old) were randomized to either problem solving therapy (PST, n = 10) or a neurobiologically inspired digital platform designed to enhance cognitive control faculties (Project: EVO™, n = 12). Given the overlapping functional neuroanatomy of mood disturbances and executive dysfunction, we explored the impact of an intervention targeting cognitive control abilities, functional disability, and mood in older adults suffering from LLD, and how those outcomes compare to a therapeutic gold standard.ResultsEVO participants demonstrated similar improvements in mood and self-reported function after 4 weeks of treatment to PST participants. The EVO participants also showed generalization to untrained measures of working memory and attention, as well as negativity bias, a finding not evident in the PST condition. Individuals assigned to EVO demonstrated 100% adherence.ConclusionsThis study provides preliminary findings that this therapeutic video game targeting cognitive control deficits may be an efficacious LLD intervention. Future research is needed to confirm these findings

A digital intervention targeting cognitive control network dysfunction in middle age and older adults with major depression.

Nonpharmacological interventions targeting putative network mechanisms of major depressive disorder (MDD) may represent novel treatments. This mechanistic study investigates how a video game-like intervention, designed to improve cognitive control network (CCN) functioning by targeting multitasking, influences the CCN of middle-aged and older adults with MDD. The sample consisted of 34 adults aged 45-75 with SCID-defined diagnosis of MDD, Hamilton depression rating scale scores ≥20, and a deficit in cognitive control. Participants were instructed to play at home for 20-25 min per day, at least 5 times per week, for 4 weeks. Evidence of target engagement was defined a priori as >2/3 of participants showing CCN improvement. CCN engagement was defined as a change in a Z score of ≥0.5 on functional magnetic resonance imaging (fMRI) in activation and functional connectivity of the CCN during task-based and resting-state fMRI, respectively. 74% of participants showed a change in activation of the CCN, and 72% showed an increase in resting-state functional connectivity. Sixty-eight percent demonstrated improved cognitive control function, measured as either improvement on sustained attention or working memory performance or reduced self-reported symptoms of apathy on the frontal systems behavioral scale (FrsBe). Participants also reported a significant reduction in mood symptoms measured by PHQ-9. A remotely deployed neuroscience-informed video game-like intervention improves both CCN functions and mood in middle-aged and older adults with MDD. This easily-disseminated intervention may rescue CCN dysfunction present in a substantial subset of middle-aged and older adults with MDD

Treatment with diet and exercise for women with gestational diabetes mellitus diagnosed using iadpsg criteria

Context: Prevalence of gestational diabetes mellitus (GDM) and obesity continue to increase. Objective: This study aimed to ascertain whether diet and exercise is a successful intervention for women with GDM and whether a subset of these women have comparable outcomes to those with normal glucose tolerance (NGT). Design, Setting, and Participants: This was a retrospective cohort study of five antenatal centers along the Irish Atlantic seaboard of 567 women diagnosed with GDM and 2499 women with NGT during pregnancy. Intervention: Diet and exercise therapy on diagnosis of GDM were prescribed and multiple maternal and neonatal outcomes were examined. Results: Infants of women with GDM were more likely to be hypoglycemic (adjusted odds ratio [aOR], 7.25; 95% confidence interval [CI], 2.94-17.9) at birth. They were more likely to be admitted to the neonatal intensive care unit (aOR, 2.16; 95% CI, 1.60-2.91). Macrosomia and large-forgestational-age rates were lower in the GDM group (aOR, 0.48; 95% CI, 0.37-0.64 and aOR, 0.61; 95% CI, 0.46-0.82, respectively). There was no increase in small for gestational age among offspring of women with GDM (aOR, 0.81; 95% CI, 0.49-1.34). Women with diet-treated GDM and body mass index (BMI) <25 kg/m(2) had similar outcomes to those with NGT of the same BMI group. Obesity increased risk for poor pregnancy outcomes regardless of diabetes status. Conclusion: Medical nutritional therapy and exercise for women with GDM may be successful in lowering rates of large for gestational age and macrosomia without increasing small-for-gestational- age rates. Women with GDM and a BMI less than 25kg/m(2) had outcomes similar to those with NGT suggesting that these women could potentially be treated in a less resource intensive setting

Treatment with diet and exercise for women with gestational diabetes mellitus diagnosed using iadpsg criteria

Context: Prevalence of gestational diabetes mellitus (GDM) and obesity continue to increase. Objective: This study aimed to ascertain whether diet and exercise is a successful intervention for women with GDM and whether a subset of these women have comparable outcomes to those with normal glucose tolerance (NGT). Design, Setting, and Participants: This was a retrospective cohort study of five antenatal centers along the Irish Atlantic seaboard of 567 women diagnosed with GDM and 2499 women with NGT during pregnancy. Intervention: Diet and exercise therapy on diagnosis of GDM were prescribed and multiple maternal and neonatal outcomes were examined. Results: Infants of women with GDM were more likely to be hypoglycemic (adjusted odds ratio [aOR], 7.25; 95% confidence interval [CI], 2.94-17.9) at birth. They were more likely to be admitted to the neonatal intensive care unit (aOR, 2.16; 95% CI, 1.60-2.91). Macrosomia and large-forgestational-age rates were lower in the GDM group (aOR, 0.48; 95% CI, 0.37-0.64 and aOR, 0.61; 95% CI, 0.46-0.82, respectively). There was no increase in small for gestational age among offspring of women with GDM (aOR, 0.81; 95% CI, 0.49-1.34). Women with diet-treated GDM and body mass index (BMI) <25 kg/m(2) had similar outcomes to those with NGT of the same BMI group. Obesity increased risk for poor pregnancy outcomes regardless of diabetes status. Conclusion: Medical nutritional therapy and exercise for women with GDM may be successful in lowering rates of large for gestational age and macrosomia without increasing small-for-gestational- age rates. Women with GDM and a BMI less than 25kg/m(2) had outcomes similar to those with NGT suggesting that these women could potentially be treated in a less resource intensive setting

Tropomyosin1 isoforms underlie epithelial to mesenchymal plasticity, metastatic dissemination, and resistance to chemotherapy in high-grade serous ovarian cancer

Phenotypic plasticity, defined as the ability of individual cells with stable genotypes to exert different phenotypes upon exposure to specific environmental cues, represent the quintessential hallmark of the cancer cell en route from the primary lesion to distant organ sites where metastatic colonization will occur. Phenotypic plasticity is driven by a broad spectrum of epigenetic mechanisms that allow for the reversibility of epithelial-to-mesenchymal and mesenchymal-to-epithelial transitions (EMT/MET). By taking advantage of the co-existence of epithelial and quasi-mesenchymal cells within immortalized cancer cell lines, we have analyzed the role of EMT-related gene isoforms in the regulation of epithelial mesenchymal plasticity (EMP) in high grade serous ovarian cancer. When compared with colon cancer, a distinct spectrum of downstream targets characterizes quasi-mesenchymal ovarian cancer cells, likely to reflect the different modalities of metastasis formation between these two types of malignancy, i.e. hematogenous in colon and transcoelomic in ovarian cancer. Moreover, upstream RNA-binding proteins differentially expressed between epithelial and quasi-mesenchymal subpopulations of ovarian cancer cells were identified that underlie differential regulation of EMT-related isoforms. In particular, the up- and down-regulation of RBM24 and ESRP1, respectively, represent a main regulator of EMT in ovarian cancer cells. To validate the functional and clinical relevance of our approach, we selected and functionally analyzed the Tropomyosin 1 gene (TPM1), encoding for a protein that specifies the functional characteristics of individual actin filaments in contractile cells, among the ovarian-specific downstream AS targets. The low-molecular weight Tpm1.8/9 isoforms are specifically expressed in patient-derived ascites and promote invasion through activation of EMT and Wnt signaling, together with a broad spectrum of inflammation-related pathways. Moreover, Tpm1.8/9 expression confers resistance to taxane- and platinum-based chemotherapy. Small molecule inhibitors that target the Tpm1 isoforms support targeting Tpm1.8/9 as therapeutic targets for the development of future tailor-made clinical interventions.</p