The effects of dietary fiber level on nutrient digestibility in growing pigs

The objective of this study was to investigate the effects of total dietary fiber level on nutrient digestibility and the relationship between apparent total tract digestibility of total dietary fiber, and soluble dietary fiber, insoluble dietary fiber and available energy. Sugar beet pulp was as the only fiber source. The experiment was designed as a 6 × 6 Latin square with an adaptation period of 7 d followed by a 5-d total collection of feces and urine. Feed intake tended to decrease (P =0.10) as total dietary fiber level increased. The apparent total tract digestibility of dry matter, crude protein and gross energy decreased (P <0.01) when total dietary fiber increased but the digestibility of soluble dietary fiber and insoluble dietary fiber increased (P <0.01). The digestible energy and metabolizable energy content of diets decreased (P <0.01) as the total dietary fiber increased

Carbon dots for specific “off-on” sensing of Co\u3csup\u3e2+\u3c/sup\u3e and EDTA for in vivo bioimaging

Fluorescent carbon dots (CDs) were hydrothermally synthesized from a mixture of frozen tofu, ethylenediamine and phosphoric acid in an efficient 64% yield. The resulting CDs exhibit good water solubility, low cytotoxicity, high stability, and excellent biocompatibility. The CDs selectively and sensitively detect Co2+ through fluorescent quenching with a detection limit of 58 nM. Fluorescence can be restored through the introduction of EDTA, and this phenomenon can be used to quantify EDTA in solution with a detection limit of 98 nM. As both analytes are detected by the same CD platform, this is an “off-on” fluorescence sensor for Co2+ and EDTA. The technique\u27s robustness for real-world samples was illustrated by quantifying cobalt in tap water and EDTA in contact lens solution. The CDs were also evaluated for in vivo imaging as they show low cytotoxicity and excellent cellular uptake. In a zebrafish model, the CDs are rapidly adsorbed from the intestine into the liver, and are essentially cleared from the body in 24 h with no appreciable bioaccumulation. Their simple and efficient synthesis, combined with excellent physical and chemical performance, renders these CDs attractive candidates for theranostic applications in targeted “smart” drug delivery and bioimaging

Markov probabilistic decision making of self-driving cars in highway with random traffic flow: a simulation study

Purpose - Decision-making is one of the key technologies for self-driving cars. The high dependency of previously existing methods on human driving data or rules makes it difficult to model policies for different driving situations. Design/methodology/approach - In this research, a probabilistic decision-making method based on the Markov decision process (MDP) is proposed to deduce the optimal maneuver automatically in a two-lane highway scenario without using any human data. The decision-making issues in a traffic environment are formulated as the MDP by defining basic elements including states, actions and basic models. Transition and reward models are defined by using a complete prediction model of the surrounding cars. An optimal policy was deduced using a dynamic programing method and evaluated under a two-dimensional simulation environment. Findings - Results show that, at the given scenario, the self-driving car maintained safety and efficiency with the proposed policy. Originality/value - This paper presents a framework used to derive a driving policy for self-driving cars without relying on any human driving data or rules modeled by hand

Policy Bifurcation in Safe Reinforcement Learning

Safe reinforcement learning (RL) offers advanced solutions to constrained optimal control problems. Existing studies in safe RL implicitly assume continuity in policy functions, where policies map states to actions in a smooth, uninterrupted manner; however, our research finds that in some scenarios, the feasible policy should be discontinuous or multi-valued, interpolating between discontinuous local optima can inevitably lead to constraint violations. We are the first to identify the generating mechanism of such a phenomenon, and employ topological analysis to rigorously prove the existence of policy bifurcation in safe RL, which corresponds to the contractibility of the reachable tuple. Our theorem reveals that in scenarios where the obstacle-free state space is non-simply connected, a feasible policy is required to be bifurcated, meaning its output action needs to change abruptly in response to the varying state. To train such a bifurcated policy, we propose a safe RL algorithm called multimodal policy optimization (MUPO), which utilizes a Gaussian mixture distribution as the policy output. The bifurcated behavior can be achieved by selecting the Gaussian component with the highest mixing coefficient. Besides, MUPO also integrates spectral normalization and forward KL divergence to enhance the policy's capability of exploring different modes. Experiments with vehicle control tasks show that our algorithm successfully learns the bifurcated policy and ensures satisfying safety, while a continuous policy suffers from inevitable constraint violations

The clinicopathological factors associated with disease progression in Luminal a breast cancer and characteristics of metastasis: A retrospective study from a single center in China

Background/Aim: This study investigated the clinicopathological factors associated with outcomes in patients with Luminal A breast cancer. Patients and Methods: Retrospective analysis of the association of clinicopathological factors and breast cancer outcome in 421 patients with newly diagnosed Luminal-A breast cancer that were enrolled from January 2008 to December 2014. Clinicopathological data were analyzed to validate the relationship with disease free survival (DFS) and overall survival (OS). Kaplan-Meier curves and log-rank tests were used to analyze the value of clinicopathological factors (tumor size, node status and lymphovascular invasion), and subsequent Cox regression analysis revealed significant prognostic factors. Results: With a median of 61 months follow up, the 5-year DFS and 5-year OS rate were 98.3% and 99.3%. Cox multivariate regression analysis showed that clinical anatomic stage, tumor size, status of lymph nodes, lymphovascular invasion and systemic treatment are strong prognostic factors for clinical outcome in patients with Luminal-A breast cancer. Of all 413 patients with stage I-III breast cancer, 14 presented with metastasis (3.4%) during the follow up. Bone (6/14, 42.9%) was the most common site of metastasis followed by liver (5/14, 35.7%) and lung (4/14, 28.6%). The median survival time after metastasis was 20.4 months. Of all the sites of distant metastasis, liver metastasis was the only factor that affected survival time after metastasis (χ2=6.263, p=0.012). Conclusion: Patients with Luminal A breast cancer have excellent outcomes. Liver metastasis is an important factor compressing the survival time after distant metastasis presents

The Hepatitis B Surface Antigen Binding Protein: An Immunoglobulin G Constant Region-Like Protein That Interacts With HBV Envelop Proteins and Mediates HBV Entry

Hepatitis B virus (HBV) infection is a leading cause of liver cirrhosis, liver cancer, and liver failure, affecting 350 million people worldwide. Currently available anti-HBV drugs include (PEGylated-) interferon-α and nucleos(t)ide analogs, which can cause significant side effects and drug-resistance in many cases of long-term treatment. The lack of a reliable and robust in vitro infection system is a major barrier for understanding the HBV life cycle and discovering novel therapeutic targets. In the present study, we demonstrate that overexpression of the hepatitis B surface antigen binding protein (SBP) in HepG2 cells (HepG2-SBP) resulted in their susceptibility to HBV infection. HepG2-SBP cells supported the uptake of the viral surface protein (HBsAg-preS), HBV-pseudotyped virus, and live HBV in patient sera. Moreover, SBP-mediated HBsAg-preS uptake, and HBV pseudotyped virus infections were efficiently blocked by preS1- and SBP-specific antibodies. These observations suggest that SBP is involved in HBV entry and that HepG2-SBP cells can serve as a cellular model to study the post-binding steps of HBV infection

Substantial transition to clean household energy mix in rural China

The household energy mix has significant impacts on human health and climate, as it contributes greatly to many health- and climate-relevant air pollutants. Compared to the well-established urban energy statistical system, the rural household energy statistical system is incomplete and is often associated with high biases. Via a nationwide investigation, this study revealed high contributions to energy supply from coal and biomass fuels in the rural household energy sector, while electricity comprised ∼20%. Stacking (the use of multiple sources of energy) is significant, and the average number of energy types was 2.8 per household. Compared to 2012, the consumption of biomass and coals in 2017 decreased by 45% and 12%, respectively, while the gas consumption amount increased by 204%. Increased gas and decreased coal consumptions were mainly in cooking, while decreased biomass was in both cooking (41%) and heating (59%). The time-sharing fraction of electricity and gases (E&G) for daily cooking grew, reaching 69% in 2017, but for space heating, traditional solid fuels were still dominant, with the national average shared fraction of E&G being only 20%. The non-uniform spatial distribution and the non-linear increase in the fraction of E&G indicated challenges to achieving universal access to modern cooking energy by 2030, particularly in less-developed rural and mountainous areas. In some non-typical heating zones, the increased share of E&G for heating was significant and largely driven by income growth, but in typical heating zones, the time-sharing fraction was <5% and was not significantly increased, except in areas with policy intervention. The intervention policy not only led to dramatic increases in the clean energy fraction for heating but also accelerated the clean cooking transition. Higher income, higher education, younger age, less energy/stove stacking and smaller family size positively impacted the clean energy transition