High-Frequency Ultrasound Imaging to Evaluate Liver Fibrosis Progression in Rats and Yi Guan Jian Herbal Therapeutic Effects

The animals used in liver fibrosis studies must usually be sacrificed. Ultrasound has been demonstrated to have the ability to diagnose hepatic fibrosis and cirrhosis in experimental small-animal models. However, few studies have used high-frequency ultrasound (HFU, 40 MHz) to monitor changes in the rat liver and other hollow organs longitudinally. In this study, liver fibrosis was induced by administering dimethylnitrosamine (DMN) in SD rats, aged 8 weeks, for three consecutive days per week for up to 4 weeks. A Chinese herbal medicine Yi Guan Jian (YGJ) was orally administered (1.8 g/kg daily) to DMN-induced liver fibrosis rats for 2 weeks. Compared with the normal control rats, rats treated with DMN for either 2 weeks or 4 weeks had significantly lower body weights, liver indexes and elevation of hydroxyproline, GOT, and GPT contents. YGJ herbal treatment remarkably prevented rats from DMN-induced liver fibrosis. The HFU scoring results among the normal controls, 2-week DMN-treated rats, 4-week DMN-treated rats, and combined 2-week YGJ therapy with 4-week DMN-treated rats also reached statistical significance. Thus, HFU is an accurate tool for the longitudinal analysis of liver fibrosis progression in small-animal models, and the YGJ may be useful in reversing the development of hepatic fibrosis

Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties

General physical scene understanding requires more than simply localizing and recognizing objects -- it requires knowledge that objects can have different latent properties (e.g., mass or elasticity), and that those properties affect the outcome of physical events. While there has been great progress in physical and video prediction models in recent years, benchmarks to test their performance typically do not require an understanding that objects have individual physical properties, or at best test only those properties that are directly observable (e.g., size or color). This work proposes a novel dataset and benchmark, termed Physion++, that rigorously evaluates visual physical prediction in artificial systems under circumstances where those predictions rely on accurate estimates of the latent physical properties of objects in the scene. Specifically, we test scenarios where accurate prediction relies on estimates of properties such as mass, friction, elasticity, and deformability, and where the values of those properties can only be inferred by observing how objects move and interact with other objects or fluids. We evaluate the performance of a number of state-of-the-art prediction models that span a variety of levels of learning vs. built-in knowledge, and compare that performance to a set of human predictions. We find that models that have been trained using standard regimes and datasets do not spontaneously learn to make inferences about latent properties, but also that models that encode objectness and physical states tend to make better predictions. However, there is still a huge gap between all models and human performance, and all models' predictions correlate poorly with those made by humans, suggesting that no state-of-the-art model is learning to make physical predictions in a human-like way. Project page: https://dingmyu.github.io/physion_v2

Gene Regulation, Modulation, and Their Applications in Gene Expression Data Analysis

Common microarray and next-generation sequencing data analysis concentrate on tumor subtype classification, marker detection, and transcriptional regulation discovery during biological processes by exploring the correlated gene expression patterns and their shared functions. Genetic regulatory network (GRN) based approaches have been employed in many large studies in order to scrutinize for dysregulation and potential treatment controls. In addition to gene regulation and network construction, the concept of the network modulator that has significant systemic impact has been proposed, and detection algorithms have been developed in past years. Here we provide a unified mathematic description of these methods, followed with a brief survey of these modulator identification algorithms. As an early attempt to extend the concept to new RNA regulation mechanism, competitive endogenous RNA (ceRNA), into a modulator framework, we provide two applications to illustrate the network construction, modulation effect, and the preliminary finding from these networks. Those methods we surveyed and developed are used to dissect the regulated network under different modulators. Not limit to these, the concept of "modulation" can adapt to various biological mechanisms to discover the novel gene regulation mechanisms

Study of the Behavior of Titanium Alloys as the Cathode for Photovoltaic Hydrogen Production

CP-Ti and Ti-153 were adopted in this study to observe their electrochemical behavior in serving as the cathode for photovoltaic hydrogen production. The designed cyclic hydrogenation-solution heat treating processes were performed to increase the hydrogen uptake for both alloys. The results are as follows. (1) Both arsenic trioxide and thiourea showed hydrogenation promotive effect on CP-Ti, while thiourea was an inhibitor for Ti-153 under the applied conditions. (2) Arsenic trioxide showed hydrogenation promotive effect on both Ti-153 and CP-Ti in this study. (3) Ti-153 demonstrated superiority to CP-Ti when serves as the cathode for photovoltaic hydrogen production. The hydrogen mass payload for Ti-153 is 68 times larger than that for CP-Ti

Impact of ovarian preservation in women with endometrial cancer

AbstractBackgroundBilateral salpingo-oophorectomy (BSO) is standardly performed in the treatment of endometrial cancer. The purpose of this study was to evaluate the impact of ovarian preservation on the outcome of patients with endometrial cancer.MethodsA retrospective cohort study was performed using the 2000–2010 database of endometrial cancer patients who were treated at Taipei Veterans General Hospital. Information regarding patient age, pathologic reports, and follow-up results was abstracted from medical records.ResultsFive hundred and twenty-nine patients were reviewed in this study. Mean age and follow-up duration were 55.7 ± 11.4 years and 37.5 ± 30.1 months, respectively. The median disease-free survival was 31.2 months (range 0.2–126.9 months). There were no significant differences in disease-free survival between stage I patients with ovarian preservation versus those with oophorectomy (p = 0.473). In a multivariate Cox model, ovarian preservation had no effect on disease-free survival [hazard ratio (HR) = 2.72; 95% confidence interval (CI), 0.48–15.59]; however, it was not significantly related to stage and para-aortic lymph node involvement.ConclusionOvarian preservation may be considered in premenopausal women with early-stage low-risk endometrial cancer

Pembuatan Niosom Berbasis Maltodekstrin De 5-10 Dari Pati Singkong (Manihot Utilissima)

Niosomes are non ionic surfactant vesicles that have potential application in the delivery of hydrophobic or amphilic drugs. We developed proniosomes, a dry formulation using a maltodextrin as a carrier coated with non ionic surfactant, which can be used to produce niosomes within a minutes by addition of hot water followed by agitation. A novel method is reported here for rapid preparation of proniosomes with wide range of surfactant loading. Maltodextrin DE 5-10 was hidrolyzed from tapioca starch using Thermamyl L 120 da Novo at 85o C. The result from SEM analyses shown that proniosomes appear very similar to the maltodextrin, but the surface was more smooth. Niosome suspensions which was observed under the optical microscopy and particle size analyzer were evaluated as drug carrier using ibuprofen as a model. The result provide an indication of maltodextrin DE 5-10 from tapioca starch are potentialy carrier in the proniosome preparation which can be used for producing niosomes