Impact of heat treatment on size, structure, and bioactivity of elemental selenium nanoparticles

Jinsong Zhang1, Ethan W Taylor2, Xiaochun Wan1, Dungeng Peng31School of Tea and Food Science, Anhui Agricultural University, Anhui, People's Republic of China; 2Department of Nanoscience, Joint School of Nanoscience and Nanoengineering, University of North Carolina at Greensboro, Greensboro, NC, 3Department of Biochemistry, Vanderbilt University, Nashville, TN, USABackground: Elemental selenium nanoparticles have emerged as a novel selenium source with the advantage of reduced risk of selenium toxicity. The present work investigated whether heat treatment affects the size, structure, and bioactivity of selenium nanoparticles.Methods and results: After a one-hour incubation of solution containing 80 nm selenium particles in a 90°C water bath, the nanoparticles aggregated into larger 110 nm particles and nanorods (290 nm × 70 nm), leading to significantly reduced bioavailability and phase II enzyme induction in selenium-deficient mice. When a solution containing 40 nm selenium nanoparticles was treated under the same conditions, the nanoparticles aggregated into larger 72 nm particles but did not transform into nanorods, demonstrating that the thermostability of selenium nanoparticles is size-dependent, smaller selenium nanoparticles being more resistant than larger selenium nanoparticles to transformation into nanorods during heat treatment.Conclusion: The present results suggest that temperature and duration of the heat process, as well as the original nanoparticle size, should be carefully selected when a solution containing selenium nanoparticles is added to functional foods.Keywords: nanoparticle, selenium, bioactivity, heat treatmen

Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding

Large language models have demonstrated impressive universal capabilities across a wide range of open-ended tasks and have extended their utility to encompass multimodal conversations. However, existing methods encounter challenges in effectively handling both image and video understanding, particularly with limited visual tokens. In this work, we introduce Chat-UniVi, a unified vision-language model capable of comprehending and engaging in conversations involving images and videos through a unified visual representation. Specifically, we employ a set of dynamic visual tokens to uniformly represent images and videos. This representation framework empowers the model to efficiently utilize a limited number of visual tokens to simultaneously capture the spatial details necessary for images and the comprehensive temporal relationship required for videos. Moreover, we leverage a multi-scale representation, enabling the model to perceive both high-level semantic concepts and low-level visual details. Notably, Chat-UniVi is trained on a mixed dataset containing both images and videos, allowing direct application to tasks involving both mediums without requiring any modifications. Extensive experimental results demonstrate that Chat-UniVi, as a unified model, consistently outperforms even existing methods exclusively designed for either images or videos.Comment: 26 page

Effect of Ag nanopowders on microstructure, hardness and elastic modulus of Sn-Bi solders

This paper presents the microstructure, hardness and elastic modulus of Sn58Bi, Sn57Bi1Ag and Ag nanopowders reinforced Sn58Bi composite solders. Microstructural observations reveal that the Ag nanopowders reinforced Sn58Bi composite solders have smaller grains of Ag3Sn and a more uniform Ag3Sn distribution in comparison with those of Sn57Bi1Ag solder. Nanoindentation test results show that the addition of Ag nanopowders has greatly enhanced the mechanical properties of Sn58Bi solder, i.e., it exhibits 13-30% increase in hardness and 10-22% increase in modulus of the composite solder. Besides, hardness and elastic modulus of solder are dependent on the size, distribution and the quantity of the second-phase

Undrained shear strength of soft clay reinforce with single 16mm diameter encapsulated bottom ash column

Soft clay soil can be categorized as problematic soil. It consists of low shear strength, low permeability and high compressibility characteristics affect the stability and settlement of the structures constructed on this type of soil. A careful design analysis could be taken for any structure built on it. However, those characteristics could be improved through many methods and the easiest method that is being used in the construction field was stone column. On the other hand, coal is one of the world’s most important sources of energy. Disposal of bottom ash become environmental issues if it is not effectively reused or recycled for other application. This study is to present suitability in term of shear strength by using bottom ash to replace sand or granular material in column for ground improvement technique using laboratory scale model. Since sand is one of non-renewable material so by using by-product or waste material such bottom ash we can reduce the cost of construction as well as keep the non-renewable natural material in balance. Several experimental procedures are carried out to know the physical and mechanical properties of bottom ash and kaolin clay sample. Kaolin is being used as soil sample and bottom ash as the reinforced columns. The shear strength of the encapsulated bottom ash column measured by Unconfined Compression Test. A total 4 batches of kaolin sample had been tested and each batch consist of 5 specimens represent sample without bottom ash, partially penetration and fully penetration for singular bottom ash column. The specimen used were 50mm in diameter and 100mm in height. The diameter of bottom ash is 16mm and the height of the column are 60mm, 80mm and 100mm. The encapsulated bottom ash was installed at the centre of the specimen. The encapsulated bottom ash column with 10.24% area replacement ratio are 58.21%, 58.66% and 42.58% at sample penetration ratio, Hc/Hs of 0.6, 0.8 and 1.0 respectively. It can be concluded that the shear strength of soft clay could be improved by installation of encapsulated bottom ash column. However the value of shear strength of soft clay inserted with partially penetration column increased more significant compared to the fully penetration column

Silencing of rhomboid domain containing 1 to inhibit the metastasis of human breast cancer cells in vitro

Objective(s): A growing body of evidence indicates that rhomboid domain containing 1 (RHBDD1) plays an important role in a variety of physiological and pathological processes, including tumorigenesis. We aimed to determine the function of RHBDD1 in breast cancer cells. Materials and Methods: In this study, we used the Oncomine™ database to determine the expression patterns of RHBDD1 in normal and breast cancer tissues. We performed lentiviral transfection of RHBDD1-specific small interfering RNA into the breast cancer cell lines ZR-75-30 and MDA-MB-231 in order to investigate the effects of RHBDD1 deficiency on breast cancer metastasis. Results: We found that knockdown of RHBDD1 inhibited breast cancer cell migration and invasion in vitro. Moreover, knockdown of RHBDD1 promoted epithelial–mesenchymal transition (EMT) by suppressing the expression of MPP2, MPP9, fibronectin 1, vimentin, SRY-box 2, zinc finger E-box binding homeobox 1, and snail family transcriptional repressor 1, and promoting the expression of cadherin 1. Additionally, knockdown of RHBDD1 inhibited the protein expression and phosphorylation of Akt.Conclusion: Our data indicate that RHBDD1 overexpression may promote breast cancer metastasis via the regulation of EMT, suggesting that RHBDD1 may be an important regulator of breast cancer metastasis

Does Serum Vitamin D Level Affect COVID-19 Infection and Its Severity?-A Case-Control Study

Background: As effective medication to treat COVID-19 is currently unavailable, preventive remedies may be particularly important. Objective: To examine the relationship between serum 25-hydroxy vitamin D (25(OH)D) level and COVID-19 infection, its severity, and its clinical case characteristics. Methods: This case-control study compared serum 25(OH)D levels and rates of vitamin D deficiency (VDD) between 80 healthy controls and 62 patients diagnosed with COVID-19 and admitted to Guangxi People’s Hospital, China, 2/16/2020–3/16/2020. Cases were categorized into asymptomatic, mild/moderate, and severe/critical disease. Logistic regression analysis was conducted to examine the associations between 25(OH)D level, or VDD, and case status/severity of COVID-19 while controlling for demographics and comorbidities. A threshold level of vitamin D for conveying COVID-19 risk was estimated. Results: Severe/critical COVID-19 cases were significantly older and had higher percentages of comorbidity (renal failure) compared to mild cases. The serum 25(OH)D concentration in COVID-19 patient was much lower than that in healthy control. And 25(OH)D level was the lowest in severe/ critical cases, compared with mild cases. In further, significantly higher rates of VDD were found in COVID-19 cases (41.9%) compared to healthy controls (11.1%). And VDD was the greatest in severe/critical cases (80%), compared with mild cases (36%). These statistically significant associations remained even after controlling for demographics and comorbidities. A potential threshold of 25(OH)D (41.19nmol/L) to protect against COVID-19 was identified. Conclusion: Elderly and people with comorbidities were susceptible to severe COVID-19 infection. VDD was a risk factor for COVID-19, especially for severe/critical cases. While further confirmation is needed, vitamin D supplementation may have prevention or treatment potential for COVID- 19 disease

A live-cell image-based machine learning strategy for reducing variability in PSC differentiation systems

The differentiation of pluripotent stem cells (PSCs) into diverse functional cell types provides a promising solution to support drug discovery, disease modeling, and regenerative medicine. However, functional cell differentiation is currently limited by the substantial line-to-line and batch-to-batch variabilities, which severely impede the progress of scientific research and the manufacturing of cell products. For instance, PSC-to-cardiomyocyte (CM) differentiation is vulnerable to inappropriate doses of CHIR99021 (CHIR) that are applied in the initial stage of mesoderm differentiation. Here, by harnessing live-cell bright-field imaging and machine learning (ML), we realize real-time cell recognition in the entire differentiation process, e.g., CMs, cardiac progenitor cells (CPCs), PSC clones, and even misdifferentiated cells. This enables non-invasive prediction of differentiation efficiency, purification of ML-recognized CMs and CPCs for reducing cell contamination, early assessment of the CHIR dose for correcting the misdifferentiation trajectory, and evaluation of initial PSC colonies for controlling the start point of differentiation, all of which provide a more invulnerable differentiation method with resistance to variability. Moreover, with the established ML models as a readout for the chemical screen, we identify a CDK8 inhibitor that can further improve the cell resistance to the overdose of CHIR. Together, this study indicates that artificial intelligence is able to guide and iteratively optimize PSC differentiation to achieve consistently high efficiency across cell lines and batches, providing a better understanding and rational modulation of the differentiation process for functional cell manufacturing in biomedical applications