Verification of Piecewise Deep Neural Networks: A Star Set Approach with Zonotope Pre-filter

Verification has emerged as a means to provide formal guarantees on learning-based systems incorporating neural network before using them in safety-critical applications. This paper proposes a new verification approach for deep neural networks (DNNs) with piecewise linear activation functions using reachability analysis. The core of our approach is a collection of reachability algorithms using star sets (or shortly, stars), an effective symbolic representation of high-dimensional polytopes. The star-based reachability algorithms compute the output reachable sets of a network with a given input set before using them for verification. For a neural network with piecewise linear activation functions, our approach can construct both exact and over-approximate reachable sets of the neural network. To enhance the scalability of our approach, a star set is equipped with an outer-zonotope (a zonotope over-approximation of the star set) to quickly estimate the lower and upper bounds of an input set at a specific neuron to determine if splitting occurs at that neuron. This zonotope pre-filtering step reduces significantly the number of linear programming optimization problems that must be solved in the analysis, and leads to a reduction in computation time, which enhances the scalability of the star set approach. Our reachability algorithms are implemented in a software prototype called the neural network verification tool, and can be applied to problems analyzing the robustness of machine learning methods, such as safety and robustness verification of DNNs. Our experiments show that our approach can achieve runtimes twenty to 1400 times faster than Reluplex, a satisfiability modulo theory-based approach. Our star set approach is also less conservative than other recent zonotope and abstract domain approaches

Dose- and Ion-Dependent Effects in the Oxidative Stress Response to Space-Like Radiation Exposure in the Skeletal System

Exposure to space radiation may pose a risk to skeletal health during subsequent aging. Irradiation acutely stimulates bone remodeling in mice, although the long-term influence of space radiation on bone-forming potential (osteoblastogenesis) and possible adaptive mechanisms are not well understood. We hypothesized exposure to ionizing radiation impairs osteoblastogenesis in an ion-type specific manner, with low doses capable of modulating expression of redox-related genes. 16-week old, male, C57BL6/J mice were exposed to low linear-energy-transfer (LET) protons (150 mega electron volts per nucleon) or high-LET (sup 56) Fe ions (600 mega electron volts per nucleon) using either low (5 or 10 centigrays) or high (50 or 200 centigrays) doses at NASAs Space Radiation Lab at Brookhaven National Lab (NSRL/BNL). Tissues were harvested 5 weeks or 1 year after irradiation and bones were analyzed by microcomputed tomography for cancellous microarchitecture and cortical geometry. Marrow-derived, adherent cells were grown under osteoblastogenic culture conditions. Cell lysates were analyzed for select groups by RT-PCR (Reverse Transcription-Polymerase Chain Reaction) during the proliferative phase or the mineralizing phase, and differentiation was analyzed by imaging mineralized nodules (percentage surface area). Representative genes were selected for expression analyses, including cell proliferation (PCNA, Cdk2, p21, p53), differentiation (Runx2, Alpl, Bglap), oxidative metabolism (Catalase, GPX, MnSOD, CuZnSOD, iNos, Foxo1), DNA-damage repair (Gadd45), or apoptosis (Caspase 3). As expected, a high dose (200 centigrays), but not low doses, of either (sup 56) Fe or protons caused a loss of cancellous bone volume per total volume. Marrow cells produced mineralized nodules ex vivo regardless of radiation type or dose; (sup 56) Fe (200 centigrays) inhibited median nodule area by more than 90 percent at 5 weeks and 1 year post-irradiation, compared to controls. At 5 weeks post exposure, irradiation with protons or (sup 56) Fe caused few changes in gene expression levels during osteoblastogenesis, although a high dose of (sup 56) Fe (200 centigrays) increased levels of Catalase and Gadd45. In addition, supplementing cell culture media with SOD protected marrow-derived osteoprogenitors from the damaging effects of exposure to low-LET ((sup 137) Cs gamma) if irradiated in vitro, but had limited protective effects on high-LET (sup 56) Fe-exposed cells. In sum, exposure of mice to either protons or (sup 56) Fe at a relatively high dose (200 cGy) caused persistent bone loss, whereas only high-LET (sup 56) Fe increased expression of redox-related genes and inhibited osteoblastogenesis, albeit to a limited extent. We conclude that high-LET irradiation impaired osteoblastogenesis and regulated steady-state gene expression of select redox-related genes during osteoblastogenesis, which may contribute to persistent bone loss

Biallelic mutations in valyl-tRNA synthetase gene VARS are associated with a progressive neurodevelopmental epileptic encephalopathy.

Aminoacyl-tRNA synthetases (ARSs) function to transfer amino acids to cognate tRNA molecules, which are required for protein translation. To date, biallelic mutations in 31 ARS genes are known to cause recessive, early-onset severe multi-organ diseases. VARS encodes the only known valine cytoplasmic-localized aminoacyl-tRNA synthetase. Here, we report seven patients from five unrelated families with five different biallelic missense variants in VARS. Subjects present with a range of global developmental delay, epileptic encephalopathy and primary or progressive microcephaly. Longitudinal assessment demonstrates progressive cortical atrophy and white matter volume loss. Variants map to the VARS tRNA binding domain and adjacent to the anticodon domain, and disrupt highly conserved residues. Patient primary cells show intact VARS protein but reduced enzymatic activity, suggesting partial loss of function. The implication of VARS in pediatric neurodegeneration broadens the spectrum of human diseases due to mutations in tRNA synthetase genes

Solving inherited white matter disorder etiologies in the neurology clinic: Challenges and lessons learned using next-generation sequencing

IntroductionRare neurodevelopmental disorders, including inherited white matter disorders or leukodystrophies, often present a diagnostic challenge on a genetic level given the large number of causal genes associated with a range of disease subtypes. This study aims to demonstrate the challenges and lessons learned in the genetic investigations of leukodystrophies through presentation of a series of cases solved using exome or genome sequencing.MethodsEach of the six patients had a leukodystrophy associated with hypomyelination or delayed myelination on MRI, and inconclusive clinical diagnostic genetic testing results. We performed next generation sequencing (case-based exome or genome sequencing) to further investigate the genetic cause of disease.ResultsFollowing different lines of investigation, molecular diagnoses were obtained for each case, with patients harboring pathogenic variants in a range of genes including TMEM106B, GJA1, AGA, POLR3A, and TUBB4A. We describe the lessons learned in reaching the genetic diagnosis, including the importance of (a) utilizing proper multi-gene panels in clinical testing, (b) assessing the reliability of biochemical assays in supporting diagnoses, and (c) understanding the limitations of exome sequencing methods in regard to CNV detection and region coverage in GC-rich areas.DiscussionThis study illustrates the importance of applying a collaborative diagnostic approach by combining detailed phenotyping data and metabolic results from the clinical environment with advanced next generation sequencing analysis techniques from the research environment to increase the diagnostic yield in patients with genetically unresolved leukodystrophies

Central Role of Pyrophosphate in Acellular Cementum Formation

Background: Inorganic pyrophosphate (PPi) is a physiologic inhibitor of hydroxyapatite mineral precipitation involved in regulating mineralized tissue development and pathologic calcification. Local levels of PPi are controlled by antagonistic functions of factors that decrease PPi and promote mineralization (tissue-nonspecific alkaline phosphatase, Alpl/TNAP), and those that increase local PPi and restrict mineralization (progressive ankylosis protein, ANK; ectonucleotide pyrophosphatase phosphodiesterase-1, NPP1). The cementum enveloping the tooth root is essential for tooth function by providing attachment to the surrounding bone via the nonmineralized periodontal ligament. At present, the developmental regulation of cementum remains poorly understood, hampering efforts for regeneration. To elucidate the role of PPi in cementum formation, we analyzed root development in knock-out ((-/-)) mice featuring PPi dysregulation. Results: Excess PPi in the Alpl(-/-) mouse inhibited cementum formation, causing root detachment consistent with premature tooth loss in the human condition hypophosphatasia, though cementoblast phenotype was unperturbed. Deficient PPi in both Ank and Enpp1(-/-) mice significantly increased cementum apposition and overall thickness more than 12-fold vs. controls, while dentin and cellular cementum were unaltered. Though PPi regulators are widely expressed, cementoblasts selectively expressed greater ANK and NPP1 along the root surface, and dramatically increased ANK or NPP1 in models of reduced PPi output, in compensatory fashion. In vitro mechanistic studies confirmed that under low PPi mineralizing conditions, cementoblasts increased Ank (5-fold) and Enpp1 (20-fold), while increasing PPi inhibited mineralization and associated increases in Ank and Enpp1 mRNA. Conclusions: Results from these studies demonstrate a novel developmental regulation of acellular cementum, wherein cementoblasts tune cementogenesis by modulating local levels of PPi, directing and regulating mineral apposition. These findings underscore developmental differences in acellular versus cellular cementum, and suggest new approaches for cementum regeneration

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care