Modeling genetic epilepsies in a dish

Human pluripotent stem cells (hPSCs), including embryonic and induced pluripotent stem cells, provide a powerful platform for mechanistic studies of disorders of neurodevelopment and neural networks. hPSC models of autism, epilepsy, and other neurological disorders are also advancing the path toward designing and testing precision therapies. The field is evolving rapidly with the addition of genome‐editing approaches, expanding protocols for the two‐dimensional (2D) differentiation of different neuronal subtypes, and three‐dimensional (3D) human brain organoid cultures. However, the application of these techniques to study complex neurological disorders, including the epilepsies, remains a challenge. Here, we review previous work using both 2D and 3D hPSC models of genetic epilepsies, as well as recent advances in the field. We also describe new strategies for applying these technologies to disease modeling of genetic epilepsies, and discuss current challenges and future directions.Key FindingsZebrafish post‐embryonic intestinal development is slow during the first two weeks due to proliferation pattern.Transformation to the juvenile intestine is preceded by increased proliferation and changes in mitotic pattern.cells integrate between proliferating fold base epithelial cells and may regulate proliferation.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153080/1/dvdy79.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153080/2/dvdy79_am.pd

Layered double hydroxides in bioinspired nanotechnology

Layered Double Hydroxides (LDHs) are a relevant class of inorganic lamellar nanomaterials that have attracted significant interest in life science-related applications, due to their highly controllable synthesis and high biocompatibility. Under a general point of view, this class of materials might have played an important role for the origin of life on planet Earth, given their ability to adsorb and concentrate life-relevant molecules in sea environments. It has been speculated that the organic-mineral interactions could have permitted to organize the adsorbed molecules, leading to an increase in their local concentration and finally to the emergence of life. Inspired by nature, material scientists, engineers and chemists have started to leverage the ability of LDHs to absorb and concentrate molecules and biomolecules within life-like compartments, allowing to realize highly-efficient bioinspired platforms, usable for bioanalysis, therapeutics, sensors and bioremediation. This review aims at summarizing the latest evolution of LDHs in this research field under an unprecedented perspective, finally providing possible challenges and directions for future research

Strategies and Bottlenecks Towards Humanizing the Proteasome Core in Yeast

All organism are derived from a common ancestor and share several biological processes. The principle of evolutionary conservation of genes between species enables their investigation in simpler model organisms. These evolutionary conserved genes encode essential cellular machinery whose failures are linked to diseases in humans. Despite a billion years of evolutionary divergence, budding yeast share several thousand protein coding-genes with humans. Recent systematic studies have identified many human orthologs that can individually complement a lethal growth defect confered by the loss of the corresponding yeast gene. Computational analysis of many properties of orthologous gene pairs revealed functional ability is not well-explained by sequence similarity between the human and yeast genes. Instead, it is a property of specific protein complexes and pathways "genetic modularity", that broadly defines the human protein's ability to interact with yeast proteins such that some genetic modules are entirely non replaceable (e.g., DNA replication initiation complexes, splicing machinery), whereas some are entirely replaceable, including the proteasome complex, a highly conserved, multi-protein complex comprising ~33 proteins. The modularity paradigm allows if the entire yeast and human systems are, to a first approximation, interchangeable (atleast in yeast). My thesis aims to humanize the yeast proteasome core complex comprising 14 subunits. In Chapter 1, I present a review of concepts relevant to humanized yeast and our recent efforts to use humanized yeast models to study human biology, disease, and evolution. In Chapter 2, I describe efforts to humanize the entire alpha proteasome core in yeast. In the process, I describe a novel rapid, scalable, and combinatorial genome engineering strategy, by Markerless Enrichment and Recombination of Genetically Engineered loci (MERGE) in yeast. In Chapter 3, I demonstrate the humanization of the non-replaceable yeast beta core subunits revealing the role of species specific protein-protein interactions and genetic modularity in functional replaceability. Finally, in chapter 4, I discuss future efforts to humanize the proteasome core in its entirety in yeast, including the assembly chaperones required for optimal assembly of the multi-subunit core

Recent Progress on Semiconductor-Interface Facing Clinical Biosensing

From MDPI via Jisc Publications RouterHistory: accepted 2021-04-06, pub-electronic 2021-05-16Publication status: PublishedFunder: Army Research Office; Grant(s): W911NF-18-1-0458Funder: National Science Foundation; Grant(s): CHE-1832167, HRD-1700429Semiconductor (SC)-based field-effect transistors (FETs) have been demonstrated as amazing enhancer gadgets due to their delicate interface towards surface adsorption. This leads to their application as sensors and biosensors. Additionally, the semiconductor material has enormous recognizable fixation extends, high affectability, high consistency for solid detecting, and the ability to coordinate with other microfluidic gatherings. This review focused on current progress on the semiconductor-interfaced FET biosensor through the fundamental interface structure of sensor design, including inorganic semiconductor/aqueous interface, photoelectrochemical interface, nano-optical interface, and metal-assisted interface. The works that also point to a further advancement for the trademark properties mentioned have been reviewed here. The emergence of research on the organic semiconductor interface, integrated biosensors with Complementary metal–oxide–semiconductor (CMOS)-compatible, metal-organic frameworks, has accelerated the practical application of biosensors. Through a solid request for research along with sensor application, it will have the option to move forward the innovative sensor with the extraordinary semiconductor interface structure

Advanced photonic and electronic systems WILGA 2018

WILGA annual symposium on advanced photonic and electronic systems has been organized by young scientist for young scientists since two decades. It traditionally gathers around 400 young researchers and their tutors. Ph.D students and graduates present their recent achievements during well attended oral sessions. Wilga is a very good digest of Ph.D. works carried out at technical universities in electronics and photonics, as well as information sciences throughout Poland and some neighboring countries. Publishing patronage over Wilga keep Elektronika technical journal by SEP, IJET and Proceedings of SPIE. The latter world editorial series publishes annually more than 200 papers from Wilga. Wilga 2018 was the XLII edition of this meeting. The following topical tracks were distinguished: photonics, electronics, information technologies and system research. The article is a digest of some chosen works presented during Wilga 2018 symposium. WILGA 2017 works were published in Proc. SPIE vol.10445. WILGA 2018 works were published in Proc. SPIE vol.10808

Utilising marine collagen as a niche structure for enhanced osteoarthritic repair

Collagen is an abundant structural protein in the extracellular matrix and plays a role in both structural integrity and support that guides tissue formation and homeostasis. Collagen or matrix disruption, leading to altered cell-matrix interactions, is implicated in disease pathophysiology. Collagen has in turn become an attractive biomaterial in regenerative medicine, proving valuable in various long-term, robust repair strategies. Osteoarthritis (OA) is a multifactorial disease leading to the degeneration of articular cartilage, affecting approximately 8.5 million in the UK population. Current repair procedures require surgical interventions, with varying degrees of success, easing pain and recovery time. Future repair strategies are now being focused around the formation of new tissue for implantation, incorporating collagen scaffolds, donor cell populations and functional differentiation. This thesis presents a thorough characterization of a novel jellyfish (R.pulmo) source of collagen, benchmarked against mammalian collagen like material compatible with human and bovine chondroprogenitor cell invasion, proliferation, and differentiation. Significantly, no increased immune response was observed compared to research and clinical grade mammalian collagen sources during in vitro examination. Excitingly, jellyfish collagen (JCol) also demonstrated hallmarks of chondro-mimicry, enabling bovine chondroprogenitor cell invasion, proliferation and differentiation. Using a sponge scaffold design JCol provides adequate structural cell-matrix support appropriate for enhanced chondrogenesis in the presence of TGFβ1. The robust body of evidence presented supports the development of JCol, a seemingly inert collagen source, for tissue engineering and/or regenerative medicine applications. Analogous to native articular cartilage, this supports further development of jellyfish collagen as a biomaterial for matrix assisted chondrocyte implantation (MACI) approaches in OA repair. Jellagen, industrial sponsor for the project, have adopted central observations from this thesis and are now progressing with wider commercial and development activities to support market and clinical research expansion

Algorithmic Techniques in Gene Expression Processing. From Imputation to Visualization

The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.Siirretty Doriast