The phosphatase and tensin homolog deleted on chromosome 10 (PTEN) tumor suppressor is a phosphatase that antagonizes the phosphoinositol-3-kinase/AKT signaling pathway and suppresses cell survival ...as well as cell proliferation. PTEN is the second most frequently mutated gene in human cancer after p53. Germline mutations of PTEN have been found in cancer susceptibility syndromes, such as Cowden syndrome, in which over 80% of patients have mutations of PTEN. Homozygous deletion of Pten causes embryonic lethality, suggesting that PTEN is essential for embryonic development. Mice heterozygous for Pten develop spontaneous tumors in a variety of organs comparable with the spectrum of its mutations in human cancer. The mechanisms of PTEN functions in tumor suppression are currently under intense investigation. Recent studies demonstrate that PTEN plays an essential role in the maintenance of chromosomal stability and that loss of PTEN leads to massive alterations of chromosomes. The tumor suppressor p53 is known as a guardian of the genome that mediates the cellular response to environmental stress, leading to cell cycle arrest or cell death. Through completely different mechanisms, PTEN also protects the genome from instability. Thus, we propose that PTEN is a new guardian of the genome. In this review, we will discuss new discoveries on the role of PTEN in tumor suppression and explore mechanisms by which PTEN maintains genomic stability.
Summary The survival rate of dental implants is markedly influenced by the quality of the bone into which they are placed. The purpose of this study was to determine the trabecular bone density at ...potential dental implant sites in different regions of the Chinese jawbone using computed tomography (CT) images. One hundred and fifty‐four potential implant sites (15 in the anterior mandible, 47 in the anterior maxilla, 55 in the posterior mandible, and 37 in the posterior maxilla) were selected from the jawbones of 62 humans. The data were subjected to statistical analysis to determine any correlation between bone density (in Hounsfield units, HU) and jawbone region using the Kruskal–Wallis test. The bone densities in the four regions decreased in the following order: anterior mandible (530 ± 161 HU, mean ± s.d.) ≅ anterior maxilla (516 ± 132 HU) > posterior mandible (359 ± 150 HU) ≅ posterior maxilla (332 ± 136 HU). The CT data demonstrate that trabecular bone density varies markedly with potential implant site in the anterior and posterior regions of the maxilla and mandible. These findings may provide the clinician with guidelines for dental implant surgical procedures (i.e., to determine whether a one‐stage or a two‐stage protocol is required).
The recent breakthroughs in assembling long error-prone reads were based on the overlap-layout-consensus (OLC) approach and did not utilize the strengths of the alternative de Bruijn graph approach ...to genome assembly. Moreover, these studies often assume that applications of the de Bruijn graph approach are limited to short and accurate reads and that the OLC approach is the only practical paradigm for assembling long error-prone reads. We show how to generalize de Bruijn graphs for assembling long error-prone reads and describe the ABruijn assembler, which combines the de Bruijn graph and the OLC approaches and results in accurate genome reconstructions.
Following Cas9 cleavage, DNA repair without a donor template is generally considered stochastic, heterogeneous and impractical beyond gene disruption. Here, we show that template-free Cas9 editing is ...predictable and capable of precise repair to a predicted genotype, enabling correction of disease-associated mutations in humans. We constructed a library of 2,000 Cas9 guide RNAs paired with DNA target sites and trained inDelphi, a machine learning model that predicts genotypes and frequencies of 1- to 60-base-pair deletions and 1-base-pair insertions with high accuracy (r = 0.87) in five human and mouse cell lines. inDelphi predicts that 5-11% of Cas9 guide RNAs targeting the human genome are 'precise-50', yielding a single genotype comprising greater than or equal to 50% of all major editing products. We experimentally confirmed precise-50 insertions and deletions in 195 human disease-relevant alleles, including correction in primary patient-derived fibroblasts of pathogenic alleles to wild-type genotype for Hermansky-Pudlak syndrome and Menkes disease. This study establishes an approach for precise, template-free genome editing.
Although base editors are widely used to install targeted point mutations, the factors that determine base editing outcomes are not well understood. We characterized sequence-activity relationships ...of 11 cytosine and adenine base editors (CBEs and ABEs) on 38,538 genomically integrated targets in mammalian cells and used the resulting outcomes to train BE-Hive, a machine learning model that accurately predicts base editing genotypic outcomes (R ≈ 0.9) and efficiency (R ≈ 0.7). We corrected 3,388 disease-associated SNVs with ≥90% precision, including 675 alleles with bystander nucleotides that BE-Hive correctly predicted would not be edited. We discovered determinants of previously unpredictable C-to-G, or C-to-A editing and used these discoveries to correct coding sequences of 174 pathogenic transversion SNVs with ≥90% precision. Finally, we used insights from BE-Hive to engineer novel CBE variants that modulate editing outcomes. These discoveries illuminate base editing, enable editing at previously intractable targets, and provide new base editors with improved editing capabilities.
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•Base editing outcome precision and efficiency are frequently unintuitive•Machine learning model (BE-Hive) accurately predicts base editing efficiency and editing patterns•Base editor engineering can increase and reduce aberrant transversion editing•We precisely correct 3,388 pathogenic SNVs, many previously considered intractable
A comprehensive look at CRISPR base editing efficiencies and outcomes across target sequences, cell lines, and base editing effectors yields machine learning models and a web-based tool for users to predict the editing efficiency, bystander edits, and the best base editor to use for a sequence of interest.
Size optimization of solar array and battery in a standalone photovoltaic (SPV) system is investigated. Based on the energy efficiency model, the loss of power supply probability (LPSP) of the SPV ...system is calculated for different size combinations of solar array and battery. For the desired LPSP at the given load demand, the optimal size combination is obtained at the minimum system cost. One case study is given to show the application of the method in Malaysian weather conditions.
Programmable C•G-to-G•C base editors (CGBEs) have broad scientific and therapeutic potential, but their editing outcomes have proved difficult to predict and their editing efficiency and product ...purity are often low. We describe a suite of engineered CGBEs paired with machine learning models to enable efficient, high-purity C•G-to-G•C base editing. We performed a CRISPR interference (CRISPRi) screen targeting DNA repair genes to identify factors that affect C•G-to-G•C editing outcomes and used these insights to develop CGBEs with diverse editing profiles. We characterized ten promising CGBEs on a library of 10,638 genomically integrated target sites in mammalian cells and trained machine learning models that accurately predict the purity and yield of editing outcomes (R = 0.90) using these data. These CGBEs enable correction to the wild-type coding sequence of 546 disease-related transversion single-nucleotide variants (SNVs) with >90% precision (mean 96%) and up to 70% efficiency (mean 14%). Computational prediction of optimal CGBE-single-guide RNA pairs enables high-purity transversion base editing at over fourfold more target sites than achieved using any single CGBE variant.
Because the surface-to-volume ratio of quasi-two-dimensional materials is extremely high, understanding their surface characteristics is crucial for practically controlling their intrinsic properties ...and fabricating p-type and n-type layered semiconductors. Van der Waals crystals are expected to have an inert surface because of the absence of dangling bonds. However, here we show that the surface of high-quality synthesized molybdenum disulfide (MoS2) is a major n-doping source. The surface electron concentration of MoS2 is nearly four orders of magnitude higher than that of its inner bulk. Substantial thickness-dependent conductivity in MoS2 nanoflakes was observed. The transfer length method suggested the current transport in MoS2 following a two-dimensional behavior rather than the conventional three-dimensional mode. Scanning tunneling microscopy and angle-resolved photoemission spectroscopy measurements confirmed the presence of surface electron accumulation in this layered material. Notably, the in situ-cleaved surface exhibited a nearly intrinsic state without electron accumulation.
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