Manipulating Trapped Nanobubbles Moving and Coalescing with Surface Nanobubbles.

Trapped nanobubbles are observed nucleating at nanopits on a pitted substrate, while surface nanobubbles are usually formed on the smooth solid surface in water. In this work, trapped nanobubbles and surface nanobubbles were captured by a tapping-mode atomic force microscope (AFM) on a nanopitted substrate based on the temperature difference method. A single trapped nanobubble was manipulated to change into a surface nanobubble, then to change into the trapped nanobubble again. At the same time, surface nanobubbles can be moved to merge into a trapped nanobubble. Our results show that the scan load and the size of the scan area were the main factors that significantly affect the mobility of surface/trapped nanobubbles. The coalescence and mutual transformation of the two kinds of nanobubbles indicate that trapped nanobubbles and surface nanobubbles have the same chemical nature, which also provides vital experimental proof of the existence of nanobubbles in the course of contact line depinning. Our results are of great significance for understanding nanobubble stability and providing guidelines in some industrial applications.

Immunomodulatory effects of Trichinella spiralis excretory-secretory antigens on macrophages.

Helminths and their products can suppress the host immune response and other immunopathologies which may benefit parasite survival. Parasitic nematode Trichinella spiralis (T. spiralis) exert immunomodulatory effect on the host immune response through excretory-secretory (ES) products. However, the immunomodulatory mechanism is not yet completely understood or defined. Macrophages play a key role in modulating the host immune response to helminth parasite infection. Here, we focus on the effect of T. spiralis ES antigens on the immune response by studying the effect of ES antigens on RAW264.7 macrophages in vitro. RAW264.7 macrophages were incubated with ES antigens either alone or in combination with LPS. The cytokine production (TNF-α, IL-10 and IL-12 p70) and the expression of TLR were measured. Moreover, the nuclear translocation of MyD88 and NF-кB was assessed by Western blot analysis. Results indicate that ES products had impacts on reducing the expression of TLRs in LPS-induced macrophages. In addition, ES products inhibited the cytokine production of IL-12 p70 and TNF-α and alone boosted the expression of cytokine IL-10 in RAW264.7 macrophages. In conclusion, our results implied that T. spiralis ES antigens may regulate host immune response at the macrophages level in vitro.

The effect of Se-deficient diet on gene expression of inflammatory cytokines in chicken brain.

Selenium (Se) plays an important role in the brain development, function, and degeneration, nutritional encephalomalacia is closely related with dietary Se in avian. However, there is little evidence on the relationship between inflammation and encephalomalacia in avian and the mechanism which Se regulates the inflammatory response in brain tissues remains to be unclear. The present paper describes the effects of Se-deficient granulated diet on one transcription factor-nuclear factor kappaB and four pro-inflammatory cytokines-tumor necrosis factor, cyclooxygenase2, inducible nitric oxide synthase and Prostaglandin E synthase mRNA expression in the chicken brain tissues associated encephalomalacia. One hundred male chickens (1 day old; Weiwei Co. Ltd., Harbin, China) were divided into two groups (50 chickens per group). The expression levels in the brain tissues (cerebral gray matter, cerebral white matter, marrowbrain, cerebellum, thalamus and brain stem) were determined by real-time PCR on days 15, 25, 35, 45, and 55, respectively. The results showed the productions of pro-inflammatory mediators were increased following Se-deficiency. These data indicate the correlations between nutritional encephalomalacia and inflammatory response and the activity of inflammatory response in chicken brain may be induced by Se-deficiency.

Artificial intelligence generated content (AIGC) in medicine: A narrative review.

Recently, artificial intelligence generated content (AIGC) has been receiving increased attention and is growing exponentially. AIGC is generated based on the intentional information extracted from human-provided instructions by generative artificial intelligence (AI) models. AIGC quickly and automatically generates large amounts of high-quality content. Currently, there is a shortage of medical resources and complex medical procedures in medicine. Due to its characteristics, AIGC can help alleviate these problems. As a result, the application of AIGC in medicine has gained increased attention in recent years. Therefore, this paper provides a comprehensive review on the recent state of studies involving AIGC in medicine. First, we present an overview of AIGC. Furthermore, based on recent studies, the application of AIGC in medicine is reviewed from two aspects: medical image processing and medical text generation. The basic generative AI models, tasks, target organs, datasets and contribution of studies are considered and summarized. Finally, we also discuss the limitations and challenges faced by AIGC and propose possible solutions with relevant studies. We hope this review can help readers understand the potential of AIGC in medicine and obtain some innovative ideas in this field.

[Dynamic VRML for training in medicine].

Experimenting in medicine can be accomplished by virtual reality system. VRML is a tool to build virtual object and scenes which can realize static and animated applications in medicine. However, to creat a real environment, the demanded level of interactivity and dynamics is difficult to achieve. In this paper we describe some approaches and techniques which can realize dynamic 3D. Our demonstration is based on the implementation of a virtual baby model, whose character can be accomplished by external JAVA applications.

Skull defect reconstruction based on a new hybrid level set.

Skull defect reconstruction is an important aspect of surgical repair. Historically, a skull defect prosthesis was created by the mirroring technique, surface fitting, or formed templates. These methods are not based on the anatomy of the individual patient's skull, and therefore, the prosthesis cannot precisely correct the defect. This study presented a new hybrid level set model, taking into account both the global optimization region information and the local accuracy edge information, while avoiding re-initialization during the evolution of the level set function. Based on the new method, a skull defect was reconstructed, and the skull prosthesis was produced by rapid prototyping technology. This resulted in a skull defect prosthesis that well matched the skull defect with excellent individual adaptation.