CRISPR/Cas9-mediated gene manipulation to create single-amino-acid-substituted and floxed mice with a cloning-free method.

Clustered regulatory interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) technology is a powerful tool to manipulate the genome with extraordinary simplicity and speed. To generate genetically modified animals, CRISPR/Cas9-mediated genome editing is typically accomplished by microinjection of a mixture of Cas9 DNA/mRNA and single-guide RNA (sgRNA) into zygotes. However, sgRNAs used for this approach require manipulation via molecular cloning as well as in vitro transcription. Beyond these complexities, most mutants obtained with this traditional approach are genetically mosaic, yielding several types of cells with different genetic mutations. Recently, a growing body of studies has utilized commercially available Cas9 protein together with sgRNA and a targeting construct to introduce desired mutations. Here, we report a cloning-free method to target the mouse genome by pronuclear injection of a commercial Cas9 protein:crRNA:tracrRNA:single-strand oligodeoxynucleotide (ssODN) complex into mouse zygotes. As illustration of this method, we report the successful generation of global gene-knockout, single-amino-acid-substituted, as well as floxed mice that can be used for conditional gene-targeting. These models were produced with high efficiency to generate non-mosaic mutant mice with a high germline transmission rate

A Three-Dimensional Frictional Stress Analysis of Double-Shear Bolted Wood Joints

The three-dimensional stresses in bolted wood connections are evaluated and the results compared with those from two-dimensional analyses. Elastic bolts, bolt/hole clearance, and geometric variations are accounted for, as are the effects of side members. While the two- and three-dimensional results agree reasonably well with each other for relatively short bolts (thin members), contact stresses become extremely large and highly three-dimensional for proportionally longer bolts (thick members) and/or with decreased friction. Under such conditions, plane-stress assumptions are inadequate. Ability to include friction is facilitated by using special contact elements that have a symmetrical stiffness matrix

Sufficiency Conditions For Constrained Optima

Sufficiency conditions for constrained optimization problems were derived by the use of constrained second total derivatives. The results are in a simpler form than the Schechter and Beveridge relation. The sufficiency conditions of Phipps were corrected. © 1971, American Chemical Society. All rights reserved

Inhibition of cAMP/PKA Pathway Protects Optic Nerve Head Astrocytes against Oxidative Stress by Akt/Bax Phosphorylation-Mediated Mfn1/2 Oligomerization.

Glaucoma is characterized by a progressive optic nerve degeneration and retinal ganglion cell loss, but the underlying biological basis for the accompanying neurodegeneration is not known. Accumulating evidence indicates that structural and functional abnormalities of astrocytes within the optic nerve head (ONH) have a role in glaucomatous neurodegeneration. Here, we investigate the impact of activation of cyclic adenosine 3',5'-monophosphate (cAMP)/protein kinase A (PKA) pathway on mitochondrial dynamics of ONH astrocytes exposed to oxidative stress. ONH astrocytes showed a significant loss of astrocytic processes in the glial lamina of glaucomatous DBA/2J mice, accompanied by basement membrane thickening and collagen deposition in blood vessels and axonal degeneration. Serial block-face scanning electron microscopy data analysis demonstrated that numbers of total and branched mitochondria were significantly increased in ONH astrocytes, while mitochondrial length and volume density were significantly decreased. We found that hydrogen peroxide- (H2O2-) induced oxidative stress compromised not only mitochondrial bioenergetics by reducing the basal and maximal respiration but also balance of mitochondrial dynamics by decreasing dynamin-related protein 1 (Drp1) protein expression in rat ONH astrocytes. In contrast, elevated cAMP by dibutyryl-cAMP (dbcAMP) or isobutylmethylxanthine treatment significantly increased Drp1 protein expression in ONH astrocytes. Elevated cAMP exacerbated the impairment of mitochondrial dynamics and reduction of cell viability to oxidative stress in ONH astrocytes by decreasing optic atrophy type 1 (OPA1), and mitofusin (Mfn)1/2 protein expression. Following combined treatment with H2O2 and dbcAMP, PKA inhibition restored mitochondrial dynamics by increasing mitochondrial length and decreasing mitochondrial number, and this promoted cell viability in ONH astrocytes. Also, PKA inhibition significantly promoted Akt/Bax phosphorylation and Mfn1/2 oligomerization in ONH astrocytes. These results suggest that modulation of the cAMP/PKA signaling pathway may have therapeutic potential by activating Akt/Bax phosphorylation and promoting Mfn1/2 oligomerization in glaucomatous ONH astrocytes

Reducing DNN labelling cost using surprise adequacy: An industrial case study for autonomous driving

Deep Neural Networks (DNNs) are rapidly being adopted by the automotive industry, due to their impressive performance in tasks that are essential for autonomous driving. Object segmentation is one such task: its aim is to precisely locate boundaries of objects and classify the identified objects, helping autonomous cars to recognise the road environment and the traffic situation. Not only is this task safety critical, but developing a DNN based object segmentation module presents a set of challenges that are significantly different from traditional development of safety critical software. The development process in use consists of multiple iterations of data collection, labelling, training, and evaluation. Among these stages, training and evaluation are computation intensive while data collection and labelling are manual labour intensive. This paper shows how development of DNN based object segmentation can be improved by exploiting the correlation between Surprise Adequacy (SA) and model performance. The correlation allows us to predict model performance for inputs without manually labelling them. This, in turn, enables understanding of model performance, more guided data collection, and informed decisions about further training. In our industrial case study the technique allows cost savings of up to 50% with negligible evaluation inaccuracy. Furthermore, engineers can trade off cost savings versus the tolerable level of inaccuracy depending on different development phases and scenarios

Reducing DNN Labelling Cost using Surprise Adequacy: An Industrial Case Study for Autonomous Driving

Deep Neural Networks (DNNs) are rapidly being adopted by the automotive industry, due to their impressive performance in tasks that are essential for autonomous driving. Object segmentation is one such task: its aim is to precisely locate boundaries of objects and classify the identified objects, helping autonomous cars to recognise the road environment and the traffic situation. Not only is this task safety critical, but developing a DNN based object segmentation module presents a set of challenges that are significantly different from traditional development of safety critical software. The development process in use consists of multiple iterations of data collection, labelling, training, and evaluation. Among these stages, training and evaluation are computation intensive while data collection and labelling are manual labour intensive. This paper shows how development of DNN based object segmentation can be improved by exploiting the correlation between Surprise Adequacy (SA) and model performance. The correlation allows us to predict model performance for inputs without manually labelling them. This, in turn, enables understanding of model performance, more guided data collection, and informed decisions about further training. In our industrial case study the technique allows cost savings of up to 50% with negligible evaluation inaccuracy. Furthermore, engineers can trade off cost savings versus the tolerable level of inaccuracy depending on different development phases and scenarios.Comment: to be published in Proceedings of the 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineerin

Oxytocin is an age-specific circulating hormone that is necessary for muscle maintenance and regeneration.

The regenerative capacity of skeletal muscle declines with age. Previous studies suggest that this process can be reversed by exposure to young circulation; however, systemic age-specific factors responsible for this phenomenon are largely unknown. Here we report that oxytocin--a hormone best known for its role in lactation, parturition and social behaviours--is required for proper muscle tissue regeneration and homeostasis, and that plasma levels of oxytocin decline with age. Inhibition of oxytocin signalling in young animals reduces muscle regeneration, whereas systemic administration of oxytocin rapidly improves muscle regeneration by enhancing aged muscle stem cell activation/proliferation through activation of the MAPK/ERK signalling pathway. We further show that the genetic lack of oxytocin does not cause a developmental defect in muscle but instead leads to premature sarcopenia. Considering that oxytocin is an FDA-approved drug, this work reveals a potential novel and safe way to combat or prevent skeletal muscle ageing

On-Line Selection of c

A sequence is a -alternating sequence if any odd term is less than or equal to the next even term and the any even term is greater than or equal to the next odd term , where is a nonnegative constant. In this paper, we present an optimal on-line procedure to select a -alternating subsequence from a symmetric distributed random sample. We also give the optimal selection rate when the sample size goes to infinity