Inhibition of USP7 activity selectively eliminates senescent cells in part via restoration of p53 activity.

The accumulation of senescent cells (SnCs) is a causal factor of various age-related diseases as well as some of the side effects of chemotherapy. Pharmacological elimination of SnCs (senolysis) has the potential to be developed into novel therapeutic strategies to treat these diseases and pathological conditions. Here we show that ubiquitin-specific peptidase 7 (USP7) is a novel target for senolysis because inhibition of USP7 with an inhibitor or genetic depletion of USP7 by RNA interference induces apoptosis selectively in SnCs. The senolytic activity of USP7 inhibitors is likely attributable in part to the promotion of the human homolog of mouse double minute 2 (MDM2) ubiquitination and degradation by the ubiquitin-proteasome system. This degradation increases the levels of p53, which in turn induces the pro-apoptotic proteins PUMA, NOXA, and FAS and inhibits the interaction of BCL-XL and BAK to selectively induce apoptosis in SnCs. Further, we show that treatment with a USP7 inhibitor can effectively eliminate SnCs and suppress the senescence-associated secretory phenotype (SASP) induced by doxorubicin in mice. These findings suggest that small molecule USP7 inhibitors are novel senolytics that can be exploited to reduce chemotherapy-induced toxicities and treat age-related diseases

Recognition Technology for Four Arithmetic Operations

Numeral recognition is an important research direction in field of pattern recognition, and it has broad application prospects. Aiming at four arithmetic operations of general printed formats, this article adopts a multiple hybrid recognition method and is applied to automatically calculating. This method mainly uses BP neural network and template matching method to distinguish the numerals and operators, in order to increase the operation speed and recognition accuracy. Sample images of four arithmetic operations are extracted from printed books, and they are used for testing the performance of proposed recognition method. The experiments show that the method provides correct recognition rate of 96% and correct calculation rate of 89%

Transcriptome Comparative Profiling of Barley eibi1 Mutant Reveals Pleiotropic Effects of HvABCG31 Gene on Cuticle Biogenesis and Stress Responsive Pathways

Wild barley eibi1 mutant with HvABCG31 gene mutation has low capacity to retain leaf water, a phenotype associated with reduced cutin deposition and a thin cuticle. To better understand how such a mutant plant survives, we performed a genome-wide gene expression analysis. The leaf transcriptomes between the near-isogenic lines eibi1 and the wild type were compared using the 22-k Barley1 Affymetrix microarray. We found that the pleiotropic effect of the single gene HvABCG31 mutation was linked to the co-regulation of metabolic processes and stress-related system. The cuticle development involved cytochrome P450 family members and fatty acid metabolism pathways were significantly up-regulated by the HvABCG31 mutation, which might be anticipated to reduce the levels of cutin monomers or wax and display conspicuous cuticle defects. The candidate genes for responses to stress were induced by eibi1 mutant through activating the jasmonate pathway. The down-regulation of co-expressed enzyme genes responsible for DNA methylation and histone deacetylation also suggested that HvABCG31 mutation may affect the epigenetic regulation for barley development. Comparison of transcriptomic profiling of barley under biotic and abiotic stresses revealed that the functions of HvABCG31 gene to high-water loss rate might be different from other osmotic stresses of gene mutations in barley. The transcriptional profiling of the HvABCG31 mutation provided candidate genes for further investigation of the physiological and developmental changes caused by the mutant

Quantitative evaluation and models of hydrocarbon accumulation controlled by faults in the Pearl River Mouth Basin

The Pearl River Mouth Basin is the largest petroliferous basin in the northern South China Sea, where hydrocarbon accumulation is strongly controlled by fault activities. This study performed the quantitative evaluation of the effects of faults on hydrocarbon migration and accumulation in the basin. The results indicate that the critical values of vertical migration of middle-shallow hydrocarbon, including the active strength of faults and the ratio of fault throw to shale caprock thickness, were up to 10 m/Ma and 5, respectively. The lateral hydrocarbon migration efficiency of the unbreached relay zone was higher than that of the barely breached and strongly breached types. The lower critical value of shale gouge ratio for the clay sealing efficiency was 0.32. Additionally, the zones with the EW-trending transtensional faults were found to have unique dual functions of migration and stress sealing, suggesting that the linking fault positions play important roles in the lateral migration of hydrocarbons. Finally, seven hydrocarbon accumulation models controlled by faults in different tectonic settings were constructed to clarify the effects of faults on the vertical and lateral migrations of hydrocarbon. These models suggested that fine hydrocarbon exploration should be undertaken in the northeastern Baiyun Sag, and that middle-deep hydrocarbon exploration should be enhanced in the Enping, Huizhou, and southwestern Baiyun Sags.Cited as: Peng, G., Wu, Z., Dai, Y., Zhang, L., Yu, S., Wang, W., Pang, H. Quantitative evaluation and models of hydrocarbon accumulation controlled by faults in the Pearl River Mouth Basin. Advances in Geo-Energy Research, 2023, 8(2): 89-99. https://doi.org/10.46690/ager.2023.05.0

Investigation of lipid metabolism dysregulation and the effects on immune microenvironments in pan-cancer using multiple omics data.

BACKGROUND: Lipid metabolism reprogramming is a hallmark for tumor which contributes to tumorigenesis and progression, but the commonality and difference of lipid metabolism among pan-cancer is not fully investigated. Increasing evidences suggest that the alterations in tumor metabolism, including metabolite abundance and accumulation of metabolic products, lead to local immunosuppression in the tumor microenvironment. An integrated analysis of lipid metabolism in cancers from different tissues using multiple omics data may provide novel insight into the understanding of tumorigenesis and progression. RESULTS: Through systematic analysis of the multiple omics data from TCGA, we found that the most-widely altered lipid metabolism pathways in pan-cancer are fatty acid metabolism, arachidonic acid metabolism, cholesterol metabolism and PPAR signaling. Gene expression profiles of fatty acid metabolism show commonalities across pan-cancer, while the alteration in cholesterol metabolism and arachidonic acid metabolism differ with tissue origin, suggesting tissue specific lipid metabolism features in different tumor types. An integrated analysis of gene expression, DNA methylation and mutations revealed factors that regulate gene expression, including the differentially methylated sites and mutations of the lipid genes, as well as mutation and differential expression of the up-stream transcription factors for the lipid metabolism pathways. Correlation analysis of the proportion of immune cells in the tumor microenvironment and the expression of lipid metabolism genes revealed immune-related differentially expressed lipid metabolic genes, indicating the potential crosstalk between lipid metabolism and immune response. Genes related to lipid metabolism and immune response that are associated with poor prognosis were discovered including HMGCS2, GPX2 and CD36, which may provide clues for tumor biomarkers or therapeutic targets. CONCLUSIONS: Our study provides an integrated analysis of lipid metabolism in pan-cancer, highlights the perturbation of key metabolism processes in tumorigenesis and clarificates the regulation mechanism of abnormal lipid metabolism and effects of lipid metabolism on tumor immune microenvironment. This study also provides new clues for biomarkers or therapeutic targets of lipid metabolism in tumors

Event-stream representation for human gaits identification using deep neural networks

Dynamic vision sensors (event cameras) are recently introduced to solve a number of different vision tasks such as object recognition, activities recognition, tracking, etc.Compared with the traditional RGB sensors, the event cameras have many unique advantages such as ultra low resources consumption, high temporal resolution and much larger dynamic range. However, those cameras only produce noisy and asynchronous events of intensity changes, i.e., event-streams rather than frames, where conventional computer vision algorithms can't be directly applied. We hold the opinion that the key challenge of improving the performance of event cameras in vision tasks is finding the appropriate representations of the event-streams so that cutting-edge learning approaches can be applied to fully uncover the spatial-temporal information contained in the event-streams. In this paper, we focus on the event-based human gait identification task and investigate the possible representations of the event-streams when deep neural networks are applied as the classifier. We propose new event-based gait Recognition approaches basing on two different representations of the event-stream, i.e., graph and image-like representations, and use Graph-based Convolutional Network (GCN) and Convolutional Neural Networks (CNN) respectively to recognize gait from the event-streams

Re-ID done right: towards good practices for person re-identification

Training a deep architecture using a ranking loss has become standard for the person re-identification task. Increasingly, these deep architectures include additional components that leverage part detections, attribute predictions, pose estimators and other auxiliary information, in order to more effectively localize and align discriminative image regions. In this paper we adopt a different approach and carefully design each component of a simple deep architecture and, critically, the strategy for training it effectively for person re-identification. We extensively evaluate each design choice, leading to a list of good practices for person re-identification. By following these practices, our approach outperforms the state of the art, including more complex methods with auxiliary components, by large margins on four benchmark datasets. We also provide a qualitative analysis of our trained representation which indicates that, while compact, it is able to capture information from localized and discriminative regions, in a manner akin to an implicit attention mechanism

Ions-induced Epitaxial Growth of Perovskite Nanocomposites for Highly Efficient Light-Emitting Diodes with EQE Exceeding 30%

Cesium lead bromide (CsPbBr3) is a widely used emitter for perovskite light-emitting diodes (PeLEDs), benefiting from its large carrier mobility, high color purity and good thermal stability. However, the three-dimensional CsPbBr3 films encounter challenges due to their massive intrinsic defects and weak exciton binding effect, which limited their electroluminescence efficiency. To address this issue, the prevailing approach is to confine carriers by reducing dimensionality or size. Nonetheless, this method results in an increase in surface trap states due to the larger surface-to-volume ratio and presents difficulties in carrier injection and transport after reducing lattice splitting to smaller sizes. Here, we successfully achieved proper control over film crystallization by introducing sodium ions, which facilitate the epitaxial growth of zero-dimensional Cs4PbBr6 on the surface of CsPbBr3, forming large grain matrixes where CsPbBr3 is encapsulated by Cs4PbBr6. Notably, the ions-induced epitaxial growth enables the CsPbBr3 emitter with significantly reduced trap states, and generates coarsened nanocomposites of CsPbBr3&Cs4PbBr6 with grain size that surpass the average thickness of the thin perovskite film, resulting in a wavy surface conducive to light out-coupling. Additionally, another additive of formamidinium chloride was incorporated to assist the growth of nanocomposites with larger size and lower defects as well as better carrier injection and transportation. As a result, our demonstrated PeLEDs based on the coarsened nanocomposites exhibit low nonradiative recombination, enhanced light extraction and well-balanced carrier transportation, leading to high-performance devices. The champion device achieved an external quantum efficiency of 31.0% at the emission peak of 521 nm with a narrow full width at half-maximum (FWHM) of 18 nm

Revealing missing human protein isoforms based on Ab initio prediction, RNA-seq and proteomics

Biological and biomedical research relies on comprehensive understanding of protein-coding transcripts. However, the total number of human proteins is still unknown due to the prevalence of alternative splicing. In this paper, we detected 31,566 novel transcripts with coding potential by filtering our ab initio predictions with 50 RNA-seq datasets from diverse tissues/cell lines. PCR followed by MiSeq sequencing showed that at least 84.1% of these predicted novel splice sites could be validated. In contrast to known transcripts, the expression of these novel transcripts were highly tissue-specific. Based on these novel transcripts, at least 36 novel proteins were detected from shotgun proteomics data of 41 breast samples. We also showed L1 retrotransposons have a more significant impact on the origin of new transcripts/genes than previously thought. Furthermore, we found that alternative splicing is extraordinarily widespread for genes involved in specific biological functions like protein binding, nucleoside binding, neuron projection, membrane organization and cell adhesion. In the end, the total number of human transcripts with protein-coding potential was estimated to be at least 204,950.publishedVersio