Development of in vitro Chylomicron Assay Using Caco-2 Cells

Dietary fats are mainly transported by the intestine in lipoproteins: chylomicrons (CMs) and very low density lipoproteins (VLDLs). Unfortunately, studies of the intestinal absorption of dietary fat have been hampered by the lack of an adequate in vitro model system. As an in vitro model Caco-2 cells are able to secrete lipoproteins. We investigated the possible factors that may affect the secretion of CMs through the ultracentrifugation technique. The dose-dependent effects of oleic acid, mono-olein, egg lecithin, collagen matrix, and the effect of cell differentiation on CM secretion were then tested. We found that oleic acid, lecithin, and cell differentiation are critical for CM secretion by Caco-2 cells. To further confirm that our optimal condition is, in fact, favorable for efficient CM production, we compared it with control groups. We observed that our condition led to more efficient CM secretion as determined by the TGs, ApoB, and TEM analysis

Effects of Stirrups on Bond Behavior Between Concrete and Corroded Steel Bars

Steel corrosion leads to the deterioration of bond between concrete and steel bars. The serviceability and ultimate strength of concrete elements within RC structures are hence affected. Many researchers have studied the bond behavior of corroded steel bars. However, very few studies have investigated the effects of confinements on the degradation of bond strength. The present paper proposed a new kind of beam specimen based on which the effects of stirrups on degradation of bond were investigated. The test results proved that stirrups can effectively increase the bond strength between concrete and corroded steel bars

Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network

Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67\% accuracy and 96.02\% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.Comment: 9 pages, 4 figures, Accepted by Scientific Report

Studying dawn-dusk asymmetries of Mercury's magnetotail using MHD-EPIC simulations

MESSENGER has observed a lot of dawn-dusk asymmetries in Mercury's magnetotail, such as the asymmetries of the cross-tail current sheet thickness and the occurrence of flux ropes, dipolarization events and energetic electron injections. In order to obtain a global pictures of Mercury's magnetotail dynamics and the relationship between these asymmetries, we perform global simulations with the magnetohydrodynamics with embedded particle-in-cell (MHD-EPIC) model, where Mercury's magnetotail region is covered by a PIC code. Our simulations show that the dawnside current sheet is thicker, the plasma density is larger, and the electron pressure is higher than the duskside. Under a strong IMF driver, the simulated reconnection sites prefer the dawnside. We also found the dipolarization events and the planetward electron jets are moving dawnward while they are moving towards the planet, so that almost all dipolarization events and high-speed plasma flows concentrate in the dawn sector. The simulation results are consistent with MESSENGER observations

Electrical Behavior Association Mining for Household ShortTerm Energy Consumption Forecasting

Accurate household short-term energy consumption forecasting (STECF) is crucial for home energy management, but it is technically challenging, due to highly random behaviors of individual residential users. To improve the accuracy of STECF on a day-ahead scale, this paper proposes an novel STECF methodology that leverages association mining in electrical behaviors. First, a probabilistic association quantifying and discovering method is proposed to model the pairwise behaviors association and generate associated clusters. Then, a convolutional neural network-gated recurrent unit (CNN-GRU) based forecasting is provided to explore the temporal correlation and enhance accuracy. The testing results demonstrate that this methodology yields a significant enhancement in the STECF.Comment: 3 figures and 4 tables; This manuscript is submitted for possible publicatio

High Sensitivity Tunable Radio Frequency Sensors

Highly sensitive and tunable RF sensors that provide detection and analysis of single cells and particles are provided. The tunable RF sensors are configured as tunable interferometers, wherein cells or particles to be analyzed are passed through a channel, such as a microfluidic channel, across waveguides corresponding to reference and test branches of the interferometers. A network analyzer coupled to the interferometers can be configured to measure a plurality of scattering parameters, such as transmission scattering coefficients (S.sub.21) of the reference and test branches, to evaluate characteristics of cells passing through the channel. A plurality of tunable interferometers may be employed, each interferometer operating in different frequency bands such that information obtain from the plurality of interferometers may be combined to provide further information

Effects of Family Dignity Interventions Combined With Standard Palliative Care on Family Adaptability, Cohesion, and Anticipatory Grief in Adult Advanced Cancer Survivors and Their Family Caregivers: A Randomized Controlled Trial

BACKGROUND: Family involvement and comfort are equally important in palliative care. Dignity undertook a new meaning and novel challenges as a result of restrictions on visits and companionship during the pandemic. Family-centered family dignity interventions have been shown to be effective in increasing patients\u27 sense of dignity, increasing levels of hope, and reducing psychological distress; however, the effectiveness in enhancing family adaptability and intimacy in the survivor-caregiver binary and reducing expected grief have been inconclusive. OBJECTIVES: The primary objective of this study was to assess the efficacy of family dignity interventions on family adaptability and cohesion. The secondary objective was to explore the effects of the interventions on anticipatory grief and psychological distress, and the lasting effect 1 month after the intervention. DESIGN: A single-blinded, two-arm parallel group, randomized controlled trial was conducted in China. SETTINGS: and methods: Ninety-eight dyads who met the inclusion criteria were randomly assigned to the family dignity intervention (n = 51) or standard palliative care group (n = 47) between June and August 2022. Study outcomes were measured at baseline, immediately post-intervention, and at the 1-month follow-up post-intervention evaluation. Data were analyzed using the Kolmogorov-Smirnov test, chi-square test, Fisher\u27s exact test, independent sample RESULTS: In comparison to the control group, significant improvements in family adaptability and cohesion and anticipatory grief over post-intervention and 1-month follow-up were demonstrated among the patients in the intervention group. The intervention group of caregivers had significant improvement in anticipatory grief at post-intervention and 1-month follow-up. The level of psychological distress was significantly lower in the intervention group than the control group (p \u3c 0.05) at 1-month follow-up but the differences were not statistically significant at post-intervention. All outcomes showed clear differences from baseline after the intervention and at the 1-month follow-up evaluation but not between post-intervention and at the 1-month follow-up evaluation. CONCLUSION: This study further verifies the actual effect of family dignity intervention program through randomized controlled trials, and provides a reference for improving the family relationship between advanced cancer patients and their family caregivers, and improving their mental health. The addition of family dignity intervention to standard palliative care greatly increased the adaptability and cohesion between survivors and their families, lessened the anticipatory grief of the survivor-caregiver pair, and relieved caregivers\u27 anxiety and despair. We did not detect a statistically significant difference between post-intervention and the 1-month follow-up evaluation, suggesting that the intervention may have a durable impact at least 1 month

Flexible Differentially Private Vertical Federated Learning with Adaptive Feature Embeddings

The emergence of vertical federated learning (VFL) has stimulated concerns about the imperfection in privacy protection, as shared feature embeddings may reveal sensitive information under privacy attacks. This paper studies the delicate equilibrium between data privacy and task utility goals of VFL under differential privacy (DP). To address the generality issue of prior arts, this paper advocates a flexible and generic approach that decouples the two goals and addresses them successively. Specifically, we initially derive a rigorous privacy guarantee by applying norm clipping on shared feature embeddings, which is applicable across various datasets and models. Subsequently, we demonstrate that task utility can be optimized via adaptive adjustments on the scale and distribution of feature embeddings in an accuracy-appreciative way, without compromising established DP mechanisms. We concretize our observation into the proposed VFL-AFE framework, which exhibits effectiveness against privacy attacks and the capacity to retain favorable task utility, as substantiated by extensive experiments

2,5-Bis[(3-hy­droxy­prop­yl)amino]-1,4-benzoquinone monohydrate

The title compound, C12H18N2O4·H2O, was obtained as a product of the reaction of hydro­quinone with n-propanol amine. The compound crystallizes as a monohydrate, integrating water into its hydrogen-bonded network. Each diamino­quinone moiety forms two centrosymmetric 10-membered rings through C=O⋯H—N bonds. The resulting bands along [102] are inter­linked through hy­droxy groups and water mol­ecules into three-dimensional network. The chemically equivalent bond lengths in the diamino­quinone moiety exhibit a perceptible discrepancy [e.g. C=O bond lengths differ by 0.016 (2) Å], apparently as a result of asymmetric hydrogen bonding: one O atom serves as an acceptor of one hydrogen bond, whereas the other is an acceptor of two