Selective USP7 inhibition elicits cancer cell killing through a p53-dependent mechanism

Ubiquitin specific peptidase 7 (USP7) is a deubiquitinating enzyme (DUB) that removes ubiquitin tags from specific protein substrates in order to alter their degradation rate and sub-cellular localization. USP7 has been proposed as a therapeutic target in several cancers because it has many reported substrates with a role in cancer progression, including FOXO4, MDM2, N-Myc, and PTEN. The multisubstrate nature of USP7, combined with the modest potency and selectivity of early generation USP7 inhibitors, has presented a challenge in defining predictors of response to USP7 and potential patient populations that would benefit most from USP7-targeted drugs. Here, we describe the structureguided development of XL177A, which irreversibly inhibits USP7 with sub-nM potency and selectivity across the human proteome. Evaluation of the cellular effects of XL177A reveals that selective USP7 inhibition suppresses cancer cell growth predominantly through a p53-dependent mechanism: XL177A specifically upregulates p53 transcriptional targets transcriptome-wide, hotspot mutations in TP53 but not any other genes predict response to XL177A across a panel of similar to 500 cancer cell lines, and TP53 knockout rescues XL177A-mediated growth suppression of TP53 wild-type (WT) cells. Together, these findings suggest TP53 mutational status as a biomarker for response to USP7 inhibition. We find that Ewing sarcoma and malignant rhabdoid tumor (MRT), two pediatric cancers that are sensitive to other p53-dependent cytotoxic drugs, also display increased sensitivity to XL177A

Prognostic significance of preoperative neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with glioma

The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been recognized as inflammatory markers and used as prognostic makers in various cancers. The present study sought to investigate the prognostic role of NLR and PLR in Chinese patients with glioma. Clinical data, including NLR, PLR and overall survival (OS), were collected from 112 patients who underwent surgery to treat primary glioma. Kaplan-Meier survival analysis as well as uni- and multivariate Cox regression were performed to examine potential associations of preoperative NLR and PLR with OS. Among all patients, mean NLR was 3.80±1.48 and mean PLR was 183.60 ±81.38. NLR increased with increasing WHO tumor grade (p 0.05). Patients with NLR ≥ 4 had significantly shorter mean OS (20.75±7.68 months) than patients with NLR < 4 (26.91±7.50 months; p < 0.001). Similarly, patients with PLR ≥ LR had significantly shorter OS than patients with PLR < 200 (p = 0.007). Univariate Cox analysis identified the following parameters as significantly associated with worse OS: NLR (≥ 4), PLR (> 200), tumor size (≥ 5 cm), WHO grade (III/IV), and Karnofsky Performance Status (< 70). Multivariate analysis identified only NLR > 4 as an independent predictor of OS (HR 1.932, 95 % CI 1.011 to 3.694, p = 0.046). Our results suggest that at least in Chinese patients, increased preoperative NLR and PLR are associated with worse OS, and NLR may be an independent risk factor to identify glioma patients with poor prognosis. These results should be validated and extended in larger clinical studies

Recommending 1000 ppm fluoride toothpaste for caries prevention in children

10.1177/2010105820963291Proceedings of Singapore Healthcare201010582096329-20101058209632

Deep Learning on Point Clouds and Its Application: A Survey

Point cloud is a widely used 3D data form, which can be produced by depth sensors, such as Light Detection and Ranging (LIDAR) and RGB-D cameras. Being unordered and irregular, many researchers focused on the feature engineering of the point cloud. Being able to learn complex hierarchical structures, deep learning has achieved great success with images from cameras. Recently, many researchers have adapted it into the applications of the point cloud. In this paper, the recent existing point cloud feature learning methods are classified as point-based and tree-based. The former directly takes the raw point cloud as the input for deep learning. The latter first employs a k-dimensional tree (Kd-tree) structure to represent the point cloud with a regular representation and then feeds these representations into deep learning models. Their advantages and disadvantages are analyzed. The applications related to point cloud feature learning, including 3D object classification, semantic segmentation, and 3D object detection, are introduced, and the datasets and evaluation metrics are also collected. Finally, the future research trend is predicted

Stimuli-Responsive Gold Nanocages for Cancer Diagnosis and Treatment

With advances in nanotechnology, various new drug delivery systems (DDSs) have emerged and played a key role in the diagnosis and treatment of cancers. Over the last two decades, gold nanocages (AuNCs) have been attracting considerable attention because of their outstanding properties. This review summarizes current advancements in endogenous, exogenous, and dual/multi-stimuli responsive AuNCs in drug delivery. This review focuses on the properties, clinical translation potential, and limitations of stimuli-responsive AuNCs for cancer diagnosis and treatment

Interaction Among Magmas from Various Sources and Crustal Melting Processes During Continental Collision: Insights from the Huayang Intrusive Complex of the South Qinling Belt, China

The Qinling Orogenic Belt in central China, which resulted from continent-continent collision, is an excellent area for the study of collision-related magmatism. An integrated study including detailed field investigations, petrography, mineral and whole-rock geochemistry, zircon U-Pb-Hf-O isotopes, and geochemical modeling was carried out on the Huayang intrusive complex-a key magmatic intrusion in the South Qinling Belt-in order to understand the nature and melt source regions of magmatism associated with continental collisional orogenesis. The Huayang intrusive complex is composed of similar to 207-202 Ma medium to fine-grained granite, coarse to medium-grained granite of the same age, similar to 214-207 Ma tonalite and granodiorite, and rare similar to 218-213 Ma mafic xenoliths. The mafic xenoliths are characterized by enriched large ion lithophile elements, with zircon eHf(t) values of -6.8 to+4.1 and average zircon delta O-18 of 6.1 parts per thousand, which suggests that the xenoliths may represent melts derived from phlogopite-bearing lithospheric mantle. The tonalites and granodiorites exhibit high Sr/Y and La/Yb, but low Rb/Sr, with variable zircon eHf(t) values of - 6.7 to +1..9 and zircon delta O-18 values of 5.3 parts per thousand to 9.0 parts per thousand. We suggest that they were derived from partial melting of Neoproterozoic, low delta O-18 basaltic rocks with a minor input of mafic magma. These melts underwent fractional crystallization and assimilated high delta O-18 crustal materials during magma ascent and emplacement. The coarse to medium-grained granitic rocks have zircon epsilon Hf(t) values of -7.3 to +1.5, with low zircon delta O-18 values (average 5.7 parts per thousand). The medium to fine-grained granitic rocks have zircon eHf(t) values of -14.7 to +1.1, with high zircon delta O-18 values (average 8.4 parts per thousand). Both of these granitic rock types show similar whole-rock geochemistry, with metaluminous to strongly peraluminous compositions, and are characterized by intermediate to low Sr/Y values. We propose that the coarse to medium-grained granites originated from partial melting of low delta O-18 Neoproterozoic metabasaltic to metatonalitic rocks, and that the medium to fine-grained granites were derived from high delta O-18 Neoproterozoic metagreywackes. Both granitic magma types experienced plagioclase-dominated fractional crystallization during magma ascent and emplacement. The data suggest that three different source materials were involved in magmatism in the South Qinling Belt: 1) the lithospheric mantle; 2) low delta O-18 Neoproterozoic metabasaltic to tonalitic rocks, and 3) high delta O-18 Neoproterozoic metagreywackes. Slab break-off and/or dehydration of the subducted slab may have induced the melting of the sub-continental lithospheric mantle and caused subsequent crustal melting by heating the base of the crust. The results of this study suggest that magmatism in continental collisional orogens is not only generated by heating from radioactive element decay during crustal thickening.National Natural Science Foundation of China [41530207, 41772188]; Romanian Executive Agency for Higher Education, Research, Development and Innovation Funding project [PN-III-P4-ID-PCE-2016-0127]; China Geological Survey [1212011085534]; China Scholarship Council [201606010070]12 month embargo; published online: 03 May 2018This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

At what age do children have the motor development to adequately brush their teeth?

10.1111/ipd.12938INTERNATIONAL JOURNAL OF PAEDIATRIC DENTISTRY324598-60

Influence of load frequency and corrosive environments on fatigue behavior of as-extruded Mg–Zn–Zr–Nd alloy

Fatigue resistance is a key criterion for new material that would be applied as an implant. As a “smart” implant material with good biodegradability and high strength, Mg–2Zn–0.5Zr–0.5Nd alloy has been recognized as a promising candidate for bone implant. A series of tests on fatigue properties of extruded Mg–2Zn–0.5Zr–0.5Nd alloy are carried out in this study. Alternating cyclic dynamic loads at frequencies of 5 Hz and 10 Hz both in air and in 0.9 wt% NaCl solution were loaded on extruded Mg–2Zn–0.5Zr–0.5Nd alloy respectively. In air condition, the fatigue life variational trends of Mg–2Zn–0.5Zr–0.5Nd alloy at different frequencies are similar according to the stress-life (S–N) curves. However, under high fatigue cycles, the lower loading frequency prolongs the loading time of repetitive stresses and reduces the fatigue life of the samples. In 0.9 wt% NaCl solution, the S–N curves under different frequencies show different changing trends due to the synergistic effect of corrosion environment and loading frequency. It is also found that the fatigue resistance of the alloy in 0.9 wt% NaCl solution is poorer than that in air due to the significant promotion of the formation and growth of corrosion pits by the NaCl environment. In addition, according to the fatigue fracture morphology analysis, it can be found that the failed samples show different fracture patterns in air and 0.9 wt% NaCl solution