All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation

In this work, we propose a new transformer-based regularization to better localize objects for Weakly supervised semantic segmentation (WSSS). In image-level WSSS, Class Activation Map (CAM) is adopted to generate object localization as pseudo segmentation labels. To address the partial activation issue of the CAMs, consistency regularization is employed to maintain activation intensity invariance across various image augmentations. However, such methods ignore pair-wise relations among regions within each CAM, which capture context and should also be invariant across image views. To this end, we propose a new all-pairs consistency regularization (ACR). Given a pair of augmented views, our approach regularizes the activation intensities between a pair of augmented views, while also ensuring that the affinity across regions within each view remains consistent. We adopt vision transformers as the self-attention mechanism naturally embeds pair-wise affinity. This enables us to simply regularize the distance between the attention matrices of augmented image pairs. Additionally, we introduce a novel class-wise localization method that leverages the gradients of the class token. Our method can be seamlessly integrated into existing WSSS methods using transformers without modifying the architectures. We evaluate our method on PASCAL VOC and MS COCO datasets. Our method produces noticeably better class localization maps (67.3% mIoU on PASCAL VOC train), resulting in superior WSSS performances.Comment: ICCV 2023 worksho

Applications of 2D-layered palladium diselenide and its van der Waals heterostructures in electronics and optoelectronics

The rapid development of two-dimensional (2D) transition-metal dichalcogenides has been possible owing to their special structures and remarkable properties. In particular, palladium diselenide (PdSe2) with a novel pentagonal structure and unique physical characteristics have recently attracted extensive research interest. Consequently, tremendous research progress has been achieved regarding the physics, chemistry, and electronics of PdSe2. Accordingly, in this review, we recapitulate and summarize the most recent research on PdSe2, including its structure, properties, synthesis, and applications. First, a mechanical exfoliation method to obtain PdSe2 nanosheets is introduced, and large-area synthesis strategies are explained with respect to chemical vapor deposition and metal selenization. Next, the electronic and optoelectronic properties of PdSe2 and related heterostructures, such as field-effect transistors, photodetectors, sensors, and thermoelectric devices, are discussed. Subsequently, the integration of systems into infrared image sensors on the basis of PdSe2 van der Waals heterostructures is explored. Finally, future opportunities are highlighted to serve as a general guide for physicists, chemists, materials scientists, and engineers. Therefore, this comprehensive review may shed light on the research conducted by the 2D material community.Web of Science131art. no. 14

Integrated rocksalt–polyanion cathodes with excess lithium and stabilized cycling

Co- and Ni-free disordered rocksalt cathodes utilize oxygen redox to increase the energy density of lithium-ion batteries, but it is challenging to achieve good cycle life at high voltages >4.5 V (versus Li/Li+). Here we report a family of Li-excess Mn-rich cathodes that integrates rocksalt- and polyanion-type structures. Following design rules for cation filling and ordering, we demonstrate the bulk incorporation of polyanion groups into the rocksalt lattice. This integration bridges the two primary families of lithium-ion battery cathodes—layered/spinel and phosphate oxides—dramatically enhancing the cycling stability of disordered rocksalt cathodes with 4.8 V upper cut-off voltage. The cathode exhibits high gravimetric energy densities above 1,100 Wh kg−1 and >70% retention over 100 cycles. This study opens up a broad compositional space for developing battery cathodes using earth-abundant elements such as Mn and Fe

SIRT3-SOD2-ROS pathway is involved in Linalool-induced glioma cell apoptotic death

Glioma is the most prevalent type of adult primary brain tumor and chemotherapy of glioma was limited by drug-resistance. Linalool is an acyclic monoterpene alcohol possessing various pharmacological activities. The present study was conducted to evaluate the effect of linalool on glioma cell growth. The effect of linalool on cell viability in U87-MG cells was investigated and the results showed that linalool significantly reduced cell viability in a concentration- and time-dependent manner. In addition, exposure of the cells to linalool resulted in a concentration-dependent increase of TUNEL-stained cells, indicating the occurrence of apoptotic cell death. Linalool decreased mitochondrial oxygen consumption rate, increased the expression of Bax and Bak, reduced the expression of Bcl-2 and Bcl-xl, and increased the activities of caspase 3 and caspase 9, leading to increase of apoptosis. Linalool resulted in a concentration-dependent decrease of SOD activity but had no significant effect on mRNA and protein expression of SOD2. Moreover, linalool resulted in a significant increase of the expression of acetylated SOD2. The mRNA and protein expression of SIRT3 was significantly inhibited by linalool. Immunoblot analysis showed that there was an evident protein/protein interaction between SOD2 and SIRT3 under normal condition. Linalool treatment significantly decreased the interaction between SOD2 and SIRT3. Overexpression of SIRT3 significantly inhibited linalool-induced increase of mitochondrial ROS production and apoptotic cell death, and decrease of cell viability. In summary, the data demonstrated that linalool exhibited inhibitory effect on glioma cells through regulation of SIRT3-SOD2-ROS signaling

SIRT3-SOD2-ROS pathway is involved in linalool-induced glioma cell apoptotic death

Glioma is the most prevalent type of adult primary brain tumor and chemotherapy of glioma was limited by drug-resistance. Linalool is an acyclic monoterpene alcohol possessing various pharmacological activities. The present study was conducted to evaluate the effect of linalool on glioma cell growth. The effect of linalool on cell viability in U87-MG cells was investigated and the results showed that linalool significantly reduced cell viability in a concentration- and time-dependent manner. In addition, exposure of the cells to linalool resulted in a concentration-dependent increase of TUNEL-stained cells, indicating the occurrence of apoptotic cell death. Linalool decreased mitochondrial oxygen consumption rate, increased the expression of Bax and Bak, reduced the expression of Bcl-2 and Bcl-xl, and increased the activities of caspase 3 and caspase 9, leading to increase of apoptosis. Linalool resulted in a concentration-dependent decrease of SOD activity but had no significant effect on mRNA and protein expression of SOD2. Moreover, linalool resulted in a significant increase of the expression of acetylated SOD2. The mRNA and protein expression of SIRT3 was significantly inhibited by linalool. Immunoblot analysis showed that there was an evident protein/protein interaction between SOD2 and SIRT3 under normal condition. Linalool treatment significantly decreased the interaction between SOD2 and SIRT3. Overexpression of SIRT3 significantly inhibited linalool-induced increase of mitochondrial ROS production and apoptotic cell death, and decrease of cell viability. In summary, the data demonstrated that linalool exhibited inhibitory effect on glioma cells through regulation of SIRT3-SOD2-ROS signaling

G-protein Coupled Receptor 34 Promotes Gliomagenesis by Inducing Proliferation and Malignant Phenotype via TGF-Beta/Smad Signaling Pathway

Background: G-protein coupled receptor 34 (GPR34) is involved in cell motility, differentiation, and mitosis. GPR34 was reported to be highly expressed and play an oncogenic role in several solid tumors. Here, we investigated the mechanisms underlying how GPR34 promotes glioma progression. Methods: Bioinformatic analysis was performed on RNA-seq and clinical data from the gene expression omnibus (GEO), cancer genome atlas (TCGA), and Genotype-Tissue Expression (GTEx) databases. TIMER database and single-sample GSEA (ssGAEA) method were used to investigate the association between the GPR34 expression and immune infiltration level in glioma. Cox regression analysis was employed to ascertain whether the risk signature was an independent prognostic indicator for glioma. The viability and migratory/invasive potential of glioma cells were assessed using Cell Counting Kit-8, colony formation, wound healing, and Transwell assays. Results: We found that GPR34 expression was positively correlated with immune infiltration level and that high GPR34 level may be associated with poor prognosis in glioma. We further found that GPR34 may serve as an independent prognostic marker and prediction factor for the clinicopathological features of glioma. We showed that knocking down GPR34 attenuated the viability and migratory/invasive capacity of glioma cells (U251 and LN229), while GPR34 overexpression exerted the opposite effects. Additionally, core enrichment in the GSEA analysis indicated that GPR34-mediated gliomagenesis was associated with the cell cycle arrest, epithelial–mesenchymal transition (EMT), and activation of the TGF-β/Smad pathway; furthermore, inhibiting TGF-β/Smad signaling using LY2157299, a TGF-β inhibitor, reversed the oncogenic effects and malignant phenotype associated with GPR34 overexpression. Conclusion: GPR34 enhances the malignancy and carcinogenesis of glioma by promoting an EMT-like process, G1/S phase cell cycle transition, and TGF-β/Smad signaling. Accordingly, GPR34 likely functions as an oncogene in glioma and may represent a potential therapeutic target for this cancer. </jats:p

Bibliometric Analysis of the Top-Cited Publications and Research Trends for Stereotactic Body Radiotherapy

ObjectiveThis study aims to analyze the 100 most cited papers and research trends on stereotactic body radiotherapy (SBRT).MethodsWe used Web of Science to identify the 100 most frequently cited papers on SBRT on September 29, 2021 and extracted the following data: publication year, source title, country/region, organization, total citations, and average number of citations per year. The research type and research domain were classified independently by the authors. Then we carried out a bibliometric analysis to determine the trends in research on SBRT.ResultsThese 100 papers were cited a total of 26,540 times, and the median number of citations was 190 (range, 138-1688). “Stereotactic body radiation therapy for inoperable early stage lung cancer” by Timmerman et al. had the highest number of total citations (1688 times). International Journal of Radiation Oncology, Biology, Physics published the largest number of papers (37 papers), followed by Journal of Clinical Oncology (13 papers). The USA contributed the most papers (67 papers), followed by Canada (18 papers). Primary lung cancer (33 papers, 10,683 citations) and oligometastases (30 papers, 7,147 citations) were the most cited research areas.ConclusionsTo the best of our knowledge, this is the first bibliometric analysis of the most frequently cited papers on SBRT. Our results provide insight into the historical development of SBRT and important advances in its application to cancer treatment. Early-stage non–small-cell lung cancer and oligometastases were the most cited research areas in the top 100 publications on SBRT, and SBRT combined with immunotherapy was a hot topic in the past few years. This study is helpful for researchers to identify the most influential papers and current research hotspots on SBRT.</jats:sec

Evaluation of Seismicity Induced by Geothermal Development Based on Artificial Neural Network

The process of geothermal energy development may cause induced seismic activities, posing a potential threat to the sustainable utilization and safety of geothermal energy. To effectively evaluate the danger of induced seismic activities, this paper establishes an artificial neural network model and selects nine influencing factors as the input parameters of the neurons. Based on the results of induced seismic activity under different parameter conditions, a sensitivity analysis is conducted for each parameter, and the influence degree of each parameter on the magnitude of induced seismic activity is ranked from largest to smallest as follows: in situ stress state, fault presence or absence, depth, degree of fracture aggregation, maximum in situ stress, distance to fault, injection volume, fracture dip angle, angle between fracture, and fault. Then, the weights of each parameter in the model are modified to improve the accuracy of the model. Finally, through data collection and the literature review, the Pohang EGS project in South Korea is analyzed, and the induced seismic activity influencing factors of the Pohang EGS site are analyzed and evaluated using the induced seismic activity evaluation model. The results show that the induced seismicity are all located below 3.7 km (drilling depth). As the depth increases, the seismicity magnitude also shows a gradually increasing trend. An increase in injection volume and a shortening of the distance from faults will also lead to an increase in the seismicity magnitude. When the injection volume approaches 10,000 cubic meters, the intensity of the seismic activity sharply increases, and the maximum magnitude reaches 5.34, which is consistent with the actual situation. This model can be used for the induced seismic evaluation of future EGS projects and provide a reference for project site selection and induced seismic risk warning