Outcomes of Operative Treatment of Forearm Deformity in Children with Osteogenesis Imperfecta: 18 Cases

Osteogenesis imperfecta (OI) often results in recurrent fractures and/or progressive bowing of the long bones, including the arms. Upper extremity deformity has been shown to negatively impact function. The objective of this retrospective case series is to assess the ability to correct deformity, improve function and evaluate the complications and revision rates in our patients with OI who have undergone forearm deformity correction. A retrospective study, approved by The University of Nebraska Medical Center Institutional Review Board, was conducted with OI patients who underwent forearm osteotomy and fixation of one or both forearm bones between December 2011 and August 2018. There were no exclusion criteria. The electronic medical records were reviewed for patient demographics, surgical details, revisions and complications. A total of 48 procedures on 27 forearms in 18 patients were performed during the study. Surgery was performed in children with forearm deformity and recurrent fractures that were interfering with function. Half of the patients had surgery on one forearm and half had surgery on both forearms. The majority of the patients have Type III OI. There were multiple complications, the most common being wire migration which required either replacement or advancement of the wire. In conclusion, forearm deformity in OI is possible, with good healing of osteotomies and fractures, although many patients may require multiple surgical interventions.

What You Need to Know When Estimating Impact Functions with Panel Data for Demographic Research

The estimation of impact functions – that is the time-varying causal effect of a dichotomous treatment (e.g., marriage, divorce, parenthood) on outcomes (e.g., earnings, well-being, health) – has become a standard procedure in demographic applications. The basic methodology of estimating impact functions with panel data and fixed-effects regressions is now widely known. However, many researchers may not be fully aware of the methodological subtleties of the approach, which may lead to biased estimates of the impact function. In this paper, we highlight potential pitfalls and provide guidance on how to avoid these in practice. We demonstrate these issues with exemplary analyses, using data from the German Family Panel (pairfam) study and estimating the effect of motherhood on life satisfaction. * This article belongs to a special issue on “Identification of causal mechanisms in demographic research: The contribution of panel data”.

Whole Exome Sequencing in dense families suggests genetic pleiotropy amongst Mendelian and complex neuropsychiatric syndromes

Introduction: Whole Exome Sequencing (WES) studies have provided important insights into the genetic architecture of neuropsychiatric syndromes identifying rare and novel variants in the protein-coding sequence of the genome that impact function. Variants and genes that are central to the shared biology of these clinical syndromes may be identified by WES in families with multiple affected individuals with serious mental illnesses (F-SMI). Methods: We performed WES in 250 individuals (affected = 186, family-control = 64) from 100 families, each with 2 or more members with SMI, and 60 unrelated population-controls. Within pedigree prioritization employed criteria of 1. rarity (Minor Allele Frequency <0.1%, GnomAD South-Asian sample, 15308 exomes); 2. functional consequence (Loss of Function or missense deleterious in 4/5 in silico predictions). 3. sharing by 3 or more affected members within a family. Across the sample, gene-set-wide case-control association analysis was performed with Sequence Kernel Association Test, accounting for kinship. Results: In 17 families with 3 or more exome samples, we identified 79 rare predicted deleterious variants in 79 unique genes shared by 3 or more affected members and absent in 60 unrelated controls. Twenty (25.32%) genes were implicated in monogenic neurodevelopmental syndromes in Online Mendelian Inheritance in Man representing a statistically significant overrepresentation (Fishers Exact test OR = 2.47, p = 0.001). In gene-set wise SKAT, statistically significant association was noted for genes related to synaptic function (SKAT-p = 0.017). Discussion: In F-SMI based WES study, we identify private, rare, protein altering variants in genes previously implicated in monogenic Mendelian neuropsychiatric syndromes; suggesting pleotropic influences in neurodevelopment between complex and monogenic syndromes.

GT-Bidding: Group Trust Model of P2P Network Based on Bidding

Due to the lack of trusted third parties as guarantees in peer-to-peer (P2P) networks, how to ensure trusted transactions between peers has become a research hotspot. However, the open and distributed characteristics of P2P networks have brought challenges to network security, and there are problems such as node fraud and unavailability of services in the network. To solve the problem of how to select trusted transaction peers in P2P groups, a new trust model, GT-Bidding, is proposed in this paper. This model follows the bidding process of human society. First, each service peer applies for a group of guarantee peers and carries out credit mortgages for this service. Second, based on the entropy and TOPSIS method (Technology for Order Preference by Similarity to an Ideal Solution) approaching the ideal solution, a set of ideal trading sequences is selected. Then, the transaction impact function is used to assign weights to the selected guarantee peers and service nodes, respectively; thus, the comprehensive trust of each service node can be calculated. Finally, the service peer is verified using feedback based on the specific confidence level, which encourages the reputation of the service and its guarantee peers to update. Experiments show that GT-Bidding improves the successful transaction rate and resists complex attacks.

Statistical modelling and climate variability of compound surge and precipitation events in a managed water system: a case study in the Netherlands

The co-occurrence of (not necessarily extreme) precipitation and surge can lead to extreme inland water levels in coastal areas. In a previous work the positive dependence between the two meteorological drivers was demonstrated in a managed water system in the Netherlands by empirically investigating an 800-year time series of water levels, which were simulated via a physical-based hydrological model driven by a regional climate model large ensemble. In this study, we present an impact-focused multivariate statistical framework to model the dependence between these flooding drivers and the resulting return periods of inland water levels. This framework is applied to the same managed water system using the aforementioned large ensemble. Composite analysis is used to guide the selection of suitable predictors and to obtain an impact function that optimally describes the relationship between high inland water levels (the impact) and the explanatory predictors. This is complex due to the high degree of human management affecting the dynamics of the water level. Training the impact function with subsets of data uniformly distributed along the range of water levels plays a major role in obtaining an unbiased performance. The dependence structure between the defined predictors is modelled using two- and three-dimensional copulas. These are used to generate paired synthetic precipitation and surge events, transformed into inland water levels via the impact function. The compounding effects of surge and precipitation and the return water level estimates fairly well reproduce the earlier results from the empirical analysis of the same regional climate model ensemble. Regarding the return levels, this is quantified by a root-mean-square deviation of 0.02 m. The proposed framework is able to produce robust estimates of compound extreme water levels for a highly managed hydrological system. Even though the framework has only been applied and validated in one study area, it shows great potential to be transferred to other areas. In addition, we present a unique assessment of the uncertainty when using only 50 years of data (what is typically available from observations). Training the impact function with short records leads to a general underestimation of the return levels as water level extremes are not well sampled. Also, the marginal distributions of the 50-year time series of the surge show high variability. Moreover, compounding effects tend to be underestimated when using 50-year slices to estimate the dependence pattern between predictors. Overall, the internal variability of the climate system is identified as a major source of uncertainty in the multivariate statistical model.

Evolutionary, proteomic, and experimental investigations suggest the extracellular matrix of cumulus cells mediates fertilization outcomes

Studies of fertilization biology often focus on sperm and egg interactions. However, before gametes interact, mammalian sperm must pass through the cumulus layer; in mice, this consists of several thousand cells tightly glued together with hyaluronic acid and other proteins. To better understand the role of cumulus cells and their surrounding matrix, we perform proteomic experiments on cumulus oophorus complexes (COCs) in house mice (Mus musculus), producing over 24,000 mass spectra to identify 711 proteins. Seven proteins known to stabilize hyaluronic acid and the extracellular matrix were especially abundant (using spectral counts as an indirect proxy for abundance). Through comparative evolutionary analyses, we show that three of these evolve rapidly, a classic signature of genes that influence fertilization rate. Some of the selected sites overlap regions of the protein known to impact function. In a follow-up experiment, we compared COCs from females raised in two different social environments. Female mice raised in the presence of multiple males produced COCs that were smaller and more resistant to sperm-derived hyaluronidase compared to females raised in the presence of a single male, consistent with a previous study that demonstrated such females produced COCs that were more resistant to fertilization. Although cumulus cells are often thought of as enhancers of fertilization, our evolutionary, proteomic, and experimental investigations implicate their extracellular matrix as a potential mediator of fertilization outcomes.

Optimal Execution considering Trading Signal and Execution Risk Simultaneously

In this paper, we study the optimal execution problem by considering the trading signal and the transaction risk simultaneously. We propose an optimal execution problem by taking into account the trading signal and the execution risk with the associated decay kernel function and the transient price impact function being of generalized forms. In particular, we solve the stochastic optimal control problems under the assumptions that the decay kernel function is the Dirac function and the transient price function is a linear function. We give the optimal executing strategies in state-feedback form and the Hamilton‐Jacobi‐Bellman equations that the corresponding value functions satisfy in the cases of a constant execution risk and a linear execution risk. We also demonstrate that our results can recover previous results when the process of the trading signal degenerates.

Uncertainty and sensitivity analysis for natural risk and adaptation appraisal modeling with CLIMADA

&lt;p&gt;Modelling societal, ecological, and economic costs of natural hazards in the context of climate change is subject to both strong aleatoric and ethical uncertainty. Dealing with these is challenging on several levels &amp;#8211; from the identification and the quantification of the sources of uncertainty to their proper inclusion in the modelling, and the communication of these in a tangible way to both experts and non-experts. One particularly useful approach is global uncertainty and sensitivity analysis, which can help to quantify the confidence in the output values and identify the main drivers of the uncertainty while considering potential correlations in the model. Here we present applications of global uncertainty analysis, robustness quantification, and sensitivity analysis in natural hazard modelling using the new uncertainty module of the CLIMADA (CLIMate ADAptation) platform.&lt;/p&gt;&lt;p&gt;CLIMADA is a fully open-source Python program that implements a probabilistic multi-hazard global natural catastrophe damage model, which also calculates averted damage (benefit) thanks to adaptation measures of any kind (from grey to green infrastructure, behavioral, etc.). With the new uncertainty module, one can directly and comprehensively inspect the uncertainty and sensitivity to input variables of various output metrics, such as the spatial distribution of risk exceedance probabilities, or the benefit-cost ratios of different adaptation measures. This global approach does reveal interesting parameter interplays and might provide valuable input for decision-makers. For instance, a study of the geospatial distribution of sensitivity indices for tropical cyclones damage indicated that the main driver of uncertainty in dense regions (e.g. cities) is the impact function (vulnerability), whereas in sparse regions it is the exposure (asset) layer.&amp;#160;&lt;/p&gt;&lt;p&gt;CLIMADA: https://github.com/CLIMADA-project/climada_python&amp;#160;&lt;/p&gt;&lt;p&gt;(1) Aznar-Siguan, G. et al., GEOSCI MODEL DEV. 12, 7 (2019) 3085&amp;#8211;97&lt;br&gt;(2) Bresch, D. N. and Aznar-Siguan., G., &amp;#160;GEOSCI MODEL DEV. (2020), 1&amp;#8211;20.&lt;/p&gt;

periodicDNA: an R/Bioconductor package to investigate k-mer periodicity in DNA

Periodic occurrences of oligonucleotide sequences can impact the physical properties of DNA. For example, DNA bendability is modulated by 10-bp periodic occurrences of WW (W = A/T) dinucleotides. We present periodicDNA, an R package to identify k-mer periodicity and generate continuous tracks of k-mer periodicity over genomic loci of interest, such as regulatory elements. periodicDNA will facilitate investigation and improve understanding of how periodic DNA sequence features impact function.