Quantifying Variation in High-Quality Footwear Replicate Impressions

A footwear impression collected at a crime scene can provide information about the shoe that created it, yielding investigative leads, excluding persons-of-interest, and linking evidence between cases. The analysis of footwear evidence often requires the preparation of test impressions from known exemplar shoes created under controlled laboratory conditions for comparison to questioned impressions. The goal of these comparisons is to evaluate the degree of similarities and differences between the questioned impression and potential sources. Given that this comparison leads to an assessment of the nature and degree of agreement between questioned and known impressions, it is important to characterize the variation that may exist between replicate test impressions created in the laboratory. This study aimed to evaluate the variation that exists within and between test impressions prepared using a static benchtop and a dynamic walking method, as well as explore the potential influence of the wearer’s foot size when using the walking method. To examine this variation, twenty-three participants were recruited to prepare test impressions of two different shoe makes and models in four different manufacturer’s sizes. Five replicate benchtop impressions per make/model/size and three replicate walking impressions per participant/make/model/size were created, resulting in more than 500 test impressions. A total of 150 quality control copies were blindly mixed into the larger dataset, increasing the total to almost 700 test impressions. Reproducible and reliable ground control points, such as the edge of a tread element, defined points of interest on impressions, and the distance between pairs of points was computed as a function of method and foot/shoe size match or mismatch. Physical size differences between measurements from benchtop impressions versus walking impressions of the same shoe were computed, and the largest physical size difference measured was 4.18 mm, which is concerning since the smallest reported physical size difference between manufacturer’s half-sizes is 4.20 mm [1]. Bland-Altman analyses were performed to determine estimates of agreement of measurements and possible bias between methods of impression creation. The methods revealed a systematic bias in that benchtop impressions were always longer and narrower than walking impressions. Additionally, the largest upper bound on the limit of agreement was 4.75 mm, indicating that differences in measurements between benchtop and walking impressions could be as large as 4.75 mm. Analysis of covariance was used to test for a numerical significance between each method used to create test impressions, while controlling for the wearer’s weight. Differences in length measurements from benchtop impressions and from walking impressions created when the manufacturer’s reported shoe size was two sizes smaller than the wearer’s foot size were statistically significantly different from almost all other experimental groups for all impressions. Conversely, the study failed to detect statistically significant differences in width measurements from impressions, indicating that the factor of wearer foot size had a larger impact on toe-to-heel length measurements than on medial-to-lateral ball of the toe width measurements. Results also indicated that of the two outsoles included in this study (the Nike® Downshifter 11 and the Asics® Gel Dedicate 7), differences between Nike® benchtop impressions and Nike® walking impressions were always greater than differences between Asics® benchtop impressions and Asics® walking impressions. Since major differences in outsole chemical composition did not exist for these shoes, the greater change in physical size for the Nike® impressions is hypothesized to be due to other factors beyond the scope of this investigation, such as the depth of tread elements, the composition of the midsole, the geometric tread arrangement, and/or intended-end-use for the shoe. In summary, this research characterized the variation that can be expected when test impressions are created using different methods and when a foot/shoe size match or mismatch is present using the walking method. Based on the findings presented in this paper, best practice dictates that footwear analysts creating test impressions using the walking method should avoid wearing a manufacturer’s reported shoe size that is two or more sizes smaller than their foot size

Projecting ocean acidification impacts for the Gulf of Maine to 2050: new tools and expectations

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Siedlecki, S. A., Salisbury, J., Gledhill, D. K., Bastidas, C., Meseck, S., McGarry, K., Hunt, C. W., Alexander, M., Lavoie, D., Wang, Z. A., Scott, J., Brady, D. C., Mlsna, I., Azetsu-Scott, K., Liberti, C. M., Melrose, D. C., White, M. M., Pershing, A., Vandemark, D., Townsend, D. W., Chen, C,. Mook, W., Morrison, R. Projecting ocean acidification impacts for the Gulf of Maine to 2050: new tools and expectations. Elementa: Science of the Anthropocene, 9(1), (2021): 00062, https://doi.org/10.1525/elementa.2020.00062.Ocean acidification (OA) is increasing predictably in the global ocean as rising levels of atmospheric carbon dioxide lead to higher oceanic concentrations of inorganic carbon. The Gulf of Maine (GOM) is a seasonally varying region of confluence for many processes that further affect the carbonate system including freshwater influences and high productivity, particularly near the coast where local processes impart a strong influence. Two main regions within the GOM currently experience carbonate conditions that are suboptimal for many organisms—the nearshore and subsurface deep shelf. OA trends over the past 15 years have been masked in the GOM by recent warming and changes to the regional circulation that locally supply more Gulf Stream waters. The region is home to many commercially important shellfish that are vulnerable to OA conditions, as well as to the human populations whose dependence on shellfish species in the fishery has continued to increase over the past decade. Through a review of the sensitivity of the regional marine ecosystem inhabitants, we identified a critical threshold of 1.5 for the aragonite saturation state (Ωa). A combination of regional high-resolution simulations that include coastal processes were used to project OA conditions for the GOM into 2050. By 2050, the Ωa declines everywhere in the GOM with most pronounced impacts near the coast, in subsurface waters, and associated with freshening. Under the RCP 8.5 projected climate scenario, the entire GOM will experience conditions below the critical Ωa threshold of 1.5 for most of the year by 2050. Despite these declines, the projected warming in the GOM imparts a partial compensatory effect to Ωa by elevating saturation states considerably above what would result from acidification alone and preserving some important fisheries locations, including much of Georges Bank, above the critical threshold.This research was financially supported by the Major Special Projects of the Ministry of Science and Technology of China (2016YFC020600), the Young Scholars Science Foundation of Lanzhou Jiaotong University (2018033), and the Talent Innovation and Entrepreneurship Projects of Lanzhou (2018-RC-84)

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Quantifying sources of variability in infancy research using the infant-directed-speech preference

Psychological scientists have become increasingly concerned with issues related to methodology and replicability, and infancy researchers in particular face specific challenges related to replicability: For example, high-powered studies are difficult to conduct, testing conditions vary across labs, and different labs have access to different infant populations. Addressing these concerns, we report on a large-scale, multisite study aimed at (a) assessing the overall replicability of a single theoretically important phenomenon and (b) examining methodological, cultural, and developmental moderators. We focus on infants’ preference for infant-directed speech (IDS) over adult-directed speech (ADS). Stimuli of mothers speaking to their infants and to an adult in North American English were created using seminaturalistic laboratory-based audio recordings. Infants’ relative preference for IDS and ADS was assessed across 67 laboratories in North America, Europe, Australia, and Asia using the three common methods for measuring infants’ discrimination (head-turn preference, central fixation, and eye tracking). The overall meta-analytic effect size (Cohen’s d) was 0.35, 95% confidence interval = [0.29, 0.42], which was reliably above zero but smaller than the meta-analytic mean computed from previous literature (0.67). The IDS preference was significantly stronger in older children, in those children for whom the stimuli matched their native language and dialect, and in data from labs using the head-turn preference procedure. Together, these findings replicate the IDS preference but suggest that its magnitude is modulated by development, native-language experience, and testing procedure. (This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 798658.

Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18 : a modelling study

Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2 ·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676· 5 (513· 6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique, had the highest estimated HIV incidence (4661·7 [2544·8–8120·3]) cases per 100000 people in 2018 and Inhassunge District, Zambezia Province, Mozambique, had the highest estimated HIV mortality rate (1163·0 [679·0–1866·8]) deaths per 100 000 people. Further, the rate of reduction in HIV incidence and mortality from 2000 to 2018, as well as the ratio of new infections to the number of people living with HIV was highly variable. Although most second-level administrative units had declines in the number of new cases (3316 [81· 1%] of 4087 units) and number of deaths (3325 [81·4%]), nearly all appeared well short of the targeted 75% reduction in new cases and deaths between 2010 and 2020. Interpretation: Our estimates suggest that most second-level administrative units in sub-Saharan Africa are falling short of the targeted 75% reduction in new cases and deaths by 2020, which is further compounded by substantial within-country variability. These estimates will help decision makers and programme implementers expand access to ART and better target health resources to higher burden subnational areas

Comprehensive Rare Variant Analysis via Whole-Genome Sequencing to Determine the Molecular Pathology of Inherited Retinal Disease

Inherited retinal disease is a common cause of visual impairment and represents a highly heterogeneous group of conditions. Here, we present findings from a cohort of 722 individuals with inherited retinal disease, who have had whole-genome sequencing (n = 605), whole-exome sequencing (n = 72), or both (n = 45) performed, as part of the NIHR-BioResource Rare Diseases research study. We identified pathogenic variants (single-nucleotide variants, indels, or structural variants) for 404/722 (56%) individuals. Whole-genome sequencing gives unprecedented power to detect three categories of pathogenic variants in particular: structural variants, variants in GC-rich regions, which have significantly improved coverage compared to whole-exome sequencing, and variants in non-coding regulatory regions. In addition to previously reported pathogenic regulatory variants, we have identified a previously unreported pathogenic intronic variant in $\textit{CHM}$ in two males with choroideremia. We have also identified 19 genes not previously known to be associated with inherited retinal disease, which harbor biallelic predicted protein-truncating variants in unsolved cases. Whole-genome sequencing is an increasingly important comprehensive method with which to investigate the genetic causes of inherited retinal disease.This work was supported by The National Institute for Health Research England (NIHR) for the NIHR BioResource – Rare Diseases project (grant number RG65966). The Moorfields Eye Hospital cohort of patients and clinical and imaging data were ascertained and collected with the support of grants from the National Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital, National Health Service Foundation Trust, and UCL Institute of Ophthalmology, Moorfields Eye Hospital Special Trustees, Moorfields Eye Charity, the Foundation Fighting Blindness (USA), and Retinitis Pigmentosa Fighting Blindness. M.M. is a recipient of an FFB Career Development Award. E.M. is supported by UCLH/UCL NIHR Biomedical Research Centre. F.L.R. and D.G. are supported by Cambridge NIHR Biomedical Research Centre

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery