ATGL promotes the proliferation of hepatocellular carcinoma cells via the p‐AKT signaling pathway

Abnormal metabolism, including abnormal lipid metabolism, is a hallmark of cancer cells. Some studies have demonstrated that the lipogenic pathway might promote the development of hepatocellular carcinoma (HCC). However, the role of adipose triglyceride lipase (ATGL) in hepatocellular carcinoma cells has not been elucidated. We evaluated the function of ATGL in hepatocellular carcinoma using methyl azazolyl blue and migration assay through overexpression of ATGL in HepG2 cells. Quantitative reverse‐transcription polymerase chain reaction and Western blot analyses were used to assess the mechanisms of ATGL in hepatocellular carcinoma. In the current study, we first constructed and transiently transfected ATGL into hepatocellular carcinoma cells. Secondly, we found that ATGL promoted the proliferation of hepatoma cell lines via upregulating the phosphorylation of AKT, but did not affect the metastatic ability of HCC cells. Moreover, the p‐AKT inhibitor significantly eliminated the effect of ATGL on the proliferation of hepatoma carcinoma cells. Taken together, our results indicated that ATGL promotes hepatocellular carcinoma cells proliferation through upregulation of the AKT signaling pathway

Higher radiation doses after partial laryngectomy may raise the incidence of pneumonia: A retrospective cohort study

BackgroundCurrently, studies have shown that a high dose of radiotherapy to the throat have various harmful and adverse effects on the patients’ laryngeal function, resulting in the development of pneumonia. This study aimed to explore how radiotherapy dose affected the probability of pneumonia following laryngeal cancer surgery.Materials and methodsA retrospective analysis was done on patients diagnosed with laryngeal cancer between 2010 and 2020 and were treated surgically and with postoperative radiotherapy in the same institution. This study included 108 patients in total, 51 of who were in the low-dose group and 57 of whom were in the high-dose group. Age, gender, the location of laryngeal cancer, the presence or absence of lymph node metastasis, and other demographic and clinical characteristics were collected, and the prevalence of postoperative pneumonia was compared between the two groups.ResultsThe total prevalence of postoperative pneumonia was 59.3%, but there was a significant difference between the two groups(high-dose group 71.9% VS low-dose group 45.1%; p=0.005). A total of 9.3% (10/108) of the patients had readmission due to severe pneumonia, and the rate of readmission due to pneumonia was significantly different between the two groups (high-dose group 15.8% VS low-dose group 2.0%, p=0.032). Additionally, the high-dose group’s prevalence of Dysphagia was significantly higher than the low-dose group’s. According to multivariate logistic modeling, high-dose radiation was a risk factor for pneumonia (OR=4.224, 95%CI =1.603-11.131, p=0.004).ConclusionPneumonia risk could increase with radiotherapy doses > 50 Gy in the treatment of laryngeal cancer. Therefore, we recommend that when the radiation dose surpasses 50Gy, doctors should pay particular attention to the lung health of patients with laryngeal cancer

First outcomes from the PHEBUS FPT1 uncertainty application done in the EU MUSA project

The Management and Uncertainties of Severe Accidents (MUSA) project, founded in HORIZON 2020 and coordinated by CIEMAT (Spain), aims to consolidate a harmonized approach for the analysis of uncertainties and sensitivities associated with Severe Accidents (SAs) by focusing on Source Term (ST) Figure of Merits (FOM). In this framework, among the 7 MUSA WPs the Application of Uncertainty Quantification (UQ) Methods against Integral Experiments (AUQMIE – Work Package 4 (WP4)), led by ENEA (Italy), looked at applying and testing UQ methodologies, against the internationally recognized PHEBUS FPT1 test. Considering that FPT1 is a simplified but representative SA scenario, the main target of the WP4 is to train project partners to perform UQ for SA analyses. WP4 is also a collaborative platform for highlighting and discussing results and issues arising from the application of UQ methodologies, already used for design basis accidents, and in MUSA for SA analyses. As a consequence, WP4 application creates the technical background useful for the full plant and spent fuel pool applications planned along the MUSA project, and it also gives a first contribution for MUSA best practices and lessons learned. 16 partners from different world regions are involved in the WP4 activities. The purpose of this paper is to describe the MUSA PHEBUS FPT1 uncertainty application exercise, the methodologies used by the partners to perform the UQ exercise, and the first insights coming out from the calculation phase

Utilizing Machine Learning Techniques for Classifying Translated and Non-Translated Corporate Annual Reports

Globalization has led to the widespread adoption of translated corporate annual reports in international markets. Nonetheless, it remains largely unexplored whether these translated documents fulfill the same function and communicate as effectively to international investors as their non-translated counterparts. Considering their significance to stakeholders, differentiating between these two types of reports is essential, yet research in this area is insufficient. This study seeks to bridge this gap by leveraging machine learning algorithms to classify corporate annual reports based on their translation status. By constructing corpora of comparable texts and employing thirteen syntactic complexity indices as features, we analyzed the reports using eight different algorithms: Naïve Bayes, Logistic Regression, Support Vector Machine, k-Nearest Neighbors, Neural Network, Random Forest, Gradient Boosting and Deep Learning. Additionally, ensemble models were created by combining the three most effective algorithms. The best-performing model in our study achieved an Area Under the Curve (AUC) of 99.3%. This innovative approach demonstrates the effectiveness of syntactic complexity indices in machine learning for classifying translational language in corporate reporting, contributing valuable insights to text classification and translational language research. Our findings offer critical implications for stakeholders in multilingual contexts, highlighting the need for further research in this field.</p

A comprehensive study of parallel gap resistance welding joint between Ag foil and front electrode of GaAs solar cell

When space solar cell array is subjected to harsh temperature cycle, such as planet orbit, thermal fatigue cracks in bonding area are easily induced. With the aim of improving bonding quality and elucidating failure mechanism of parallel gap resistance welding (PGRW) joints in temperature cycling environment, the present research investigates the effect of current density on bonding quality and thermal fatigue behavior of PGRW joint between Ag interconnector and front electrode of GaAs solar cell. When current density is set at 417 A/mm2, a solid diffusion bonding is achieved at the Ag/Au interface, which also possesses adequate joint strength as ensured by both pressure and input energy of PGRW. Crack initiation by thermal fatigue is found at joint edge, which subsequently propagates along the interface as the environment temperature cycling continues. Further investigation reveals that the conducted temperature cycling generates serious tensile and compressive stress in the multi-layered joint structure. Since such reciprocating forces directly induce micro-plastic deformation and strain accumulation at joint interface, failure by crack is finally generated at the joining interface

Detection of In Vivo-like Cells by a Biosensor Chip Based on Metamaterials in Terahertz Regime

Early diagnosis of diseases, especially cancer, is critical for effective treatment. The unique properties of terahertz technology have attracted attention in this field. However, current terahertz bio-detection methods face challenges due to differences between the test environment and the actual in vivo conditions. In this study, a novel method is proposed for detecting in vivo-like cells using a biosensor chip composed of metamaterials and a cavity. The cavity has a thickness of ~50 μm. The structure can protect cells from damage and provides a liquid environment like an in vivo state. Through simulation analysis, the metamaterials sensor exhibits a theoretical sensitivity of 0.287 THz/RIU (Refractive Index Unit) with a 50 μm thick analyte. The detection method is experimentally validated using the apoptosis of glioma cells and various cell types. The biosensor investigates the apoptosis of glioma cells under the impact of temozolomide, and the trend of the results was consistent with the Cell Counting Kit-8 method. Furthermore, at a concentration of ~5200 cells/cm2, the experimental results demonstrate that the sensor can distinguish between neurons and glioma cells with a resonance frequency difference of approximately 30 GHz. This research has significant potential for detecting glioma cells and offers an alternative approach to in vivo-like cell detection

Limosilactobacillus reuteri and caffeoylquinic acid synergistically promote adipose browning and ameliorate obesity-associated disorders

Abstract Objective High intake of caffeoylquinic acid (CQA)-rich dietary supplements, such as green coffee bean extracts, offers health-promoting effects on maintaining metabolic homeostasis. Similar to many active herbal ingredients with high pharmacological activities but low bioavailability, CQA has been reported as a promising thermogenic agent with anti-obesity properties, which contrasts with its poor oral absorption. Intestinal tract is the first site of CQA exposure and gut microbes might react quickly to CQA. Thus, it is of interest to explore the role of gut microbiome and microbial metabolites in the beneficial effects of CQA on obesity-related disorders. Results Oral CQA supplementation effectively enhanced energy expenditure by activating browning of adipose and thus ameliorated obesity-related metabolic dysfunctions in high fat diet-induced obese (DIO) mice. Here, 16S rRNA gene amplicon sequencing revealed that CQA treatment remodeled the gut microbiota to promote its anti-obesity actions, as confirmed by antibiotic treatment and fecal microbiota transplantation. CQA enriched the gut commensal species Limosilactobacillus reuteri (L. reuteri) and stimulated the production of short-chain fatty acids, especially propionate. Mono-colonization of L. reuteri or low-dose CQA treatment did not reduce adiposity in DIO mice, while their combination elicited an enhanced thermogenic response, indicating the synergistic effects of CQA and L. reuteri on obesity. Exogenous propionate supplementation mimicked the anti-obesity effects of CQA alone or when combined with L. reuteri, which was ablated by the monocarboxylate transporter (MCT) inhibitor 7ACC1 or MCT1 disruption in inguinal white adipose tissues to block propionate transport. Conclusions Our data demonstrate a functional axis among L. reuteri, propionate, and beige fat tissue in the anti-obesity action of CQA through the regulation of thermogenesis. These findings provide mechanistic insights into the therapeutic use of herbal ingredients with poor bioavailability via their interaction with the gut microbiota. Video Abstrac

Nanohybrid of Carbon Quantum Dots/Molybdenum Phosphide Nanoparticle for Efficient Electrochemical Hydrogen Evolution in Alkaline Medium

The exploration of highly efficient non-noble metal electrocatalysts for hydrogen evolution reaction (HER) under alkaline conditions is highly imperative but still remains a great challenge. In this work, the nanohybrid of carbon quantum dots and molybdenum phosphide nanoparticle (CQDs/MoP) has been firstly demonstrated as an efficient alkaline HER electrocatalyst. The CQDs/MoP nanohybrid is readily prepared through a charge-directed self-assembly of CQDs with phosphomolybdic acid (H₃PMo₁₂O₄₀) at the molecular level, followed by facile phosphatizing at 700 °C. The introduction of CQDs greatly helps to alleviate the agglomeration and surface oxidation of MoP nanoparticles and ensures each MoP nanoparticle to be electronically addressed, thus significantly enhancing the intrinsic catalytic activity of MoP. The optimized CQDs/MoP exhibits high-efficiency synergistic catalysis toward HER in 1 M KOH electrolyte with a low onset potential of −0.08 V and a small Tafel slope of 56 mV dec^–1 as well as high durability with negligible current loss for at least 24 h