BackgroundMinichromosomal maintenance (MCM) complex components 2, 4, 5 and 6 have been linked to human disease with phenotypes including microcephaly and intellectual disability. The MCM complex has DNA helicase activity and is thereby important for the initiation and elongation of the replication fork and highly expressed in proliferating neural stem cells.MethodsWhole-exome sequencing was applied to identify the genetic cause underlying the neurodevelopmental disease of the index family. The expression pattern of Mcm7 was characterised by performing quantitative real-time PCR, in situ hybridisation and immunostaining. To prove the disease-causative nature of identified MCM7, a proof-of-principle experiment was performed.ResultsWe reported that the homozygous missense variant c.793G>A/p.A265T (g.7:99695841C>T, NM_005916.4) in MCM7 was associated with autosomal recessive primary microcephaly (MCPH), severe intellectual disability and behavioural abnormalities in a consanguineous pedigree with three affected individuals. We found concordance between the spatiotemporal expression pattern of Mcm7 in mice and a proliferative state: Mcm7 expression was higher in early mouse developmental stages and in proliferative zones of the brain. Accordingly, Mcm7/MCM7 levels were detectable particularly in undifferentiated mouse embryonal stem cells and human induced pluripotent stem cells compared with differentiated neurons. We further demonstrate that the downregulation of Mcm7 in mouse neuroblastoma cells reduces cell viability and proliferation, and, as a proof-of-concept, that this is counterbalanced by the overexpression of wild-type but not mutant MCM7.ConclusionWe report mutations of MCM7 as a novel cause of autosomal recessive MCPH and intellectual disability and highlight the crucial function of MCM7 in nervous system development.
Mostly used material is concrete which has versatile quality for construction works. Fibrous concrete have significant factor that improve the scale and value to concrete for humid environments with significant role. Day by day abundant demand and use of concrete is increasing. It is considered as a 2nd largest building material due to the major productivity. By the use of fibrous concrete, some bonding and environmental issues have been addressed. Keeping in this view, an experimental based study is conducted to evaluate the strength of fiber reinforced concrete at different percentages 0%, 0.5%, 1.0%, 1.5% and 2.0%. All percentages are added by the weight of concrete with all fibers. In this connection, one hundred and fifty-three cylinders of five mixes are prepared. Workability checked of fresh concrete during the pouring of concrete cylinders. Poured cylinders’ samples are left for different curing ages at 7 and 28 days. One hundred and two cylinders for compression at 7 and 28days but fifty-one cylinders for split tensile test at 28days with all fibers i.e. glass fiber, steel fiber, coconut fiber and polypropylene fiber. After curing, compression and split tensile tests are performed to check the strength of hardened concrete. Workability of five mixes lies between 40-90mm.Fibrous concrete is suitable for humid environment where high strength and voids less concrete are required. Addition of fibers in concrete may improves the strength parameters as well as to increase the bonding and tensile properties of concrete. It reduces the quantity of water to be used in concrete. Also the use of different types of fibers has been proved to be economical and is considered as environmental friendly construction material.
This paper proposes a novel approach for solving the problem of collision avoidance for autonomous vehicles starting from data provided by LiDAR sensors. Rather than attempting the actual recognition of pedestrians or other moving or static objects – as in the solutions based on machine learning - we define “safety bubbles” around the vehicle and all the other moving entities identified within the on-vehicle LiDAR sensing area, and issue a signal for the upper control layers when the boundary of the vehicle’s safety bubble intersects with other objects’ bubbles. The shape and size of these safety bubbles are dynamically adjusted depending on the speed of the objects. This solution is an extension/adaptation of an idea successfully applied in one of our previous works in the context of the problem of obstacle avoidance for mobile robots. The proposed algorithm was tested using CARLA simulator with promising results, as it reduces the required computational load, so that it can be used in real time, with commercially available LiDAR sensors.
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