Fabricating 3-dimensional human brown adipose microtissues for transplantation studies

Transplanting cell cultured brown adipocytes (BAs) represents a promising approach to prevent and treat obesity (OB) and its associated metabolic disorders, including type 2 diabetes mellitus (T2DM). However, transplanted BAs have a very low survival rate in vivo. The enzymatic dissociation during the harvest of fully differentiated BAs also loses significant cells. There is a critical need for novel methods that can avoid cell death during cell preparation, transplantation, and in vivo. Here, we reported that preparing BAs as injectable microtissues could overcome the problem. We found that 3D culture promoted BA differentiation and UCP-1 expression, and the optimal initial cell aggregate size was 100 μm. The microtissues could be produced at large scales via 3D suspension assisted with a PEG hydrogel and could be cryopreserved. Fabricated microtissues could survive in vivo for long term. They alleviated body weight and fat gain and improved glucose tolerance and insulin sensitivity in high-fat diet (HFD)-induced OB and T2DM mice. Transplanted microtissues impacted multiple organs, secreted protein factors, and influenced the secretion of endogenous adipokines. To our best knowledge, this is the first report on fabricating human BA microtissues and showing their safety and efficacy in T2DM mice. The proposal of transplanting fabricated BA microtissues, the microtissue fabrication method, and the demonstration of efficacy in T2DM mice are all new. Our results show that engineered 3D human BA microtissues have considerable advantages in product scalability, storage, purity, safety, dosage, survival, and efficacy

Research on the influence of the nature of the weathered bedrock zone on the roof water bursting and sand bursting: taking Zhaogu No. 1 Mine as an example

Based on Zhaogu No. 1 Mine’s characters that are the overlying thick alluvium, multi-aquifers (groups) and thin bedrock, the water pressure of the gravel aquifer under the alluvial layer reaches 4.0 MPa, defined a high-pressure aquifer. To determine the influence of bedrock properties on roof water inrush and sand bursting, and ensure the normal mining around the thin bedrock area under groups, there were tests, point loading, dry saturated water absorption rate and indoor disintegration, of bedrock samples taken from hydrological survey holes to determine those properties and influence on retaining sand-proof pillars by analyzing the variation curves of various indexes of them with depth. The experiments’ results showed that the weathering depth of bedrock exceeds 20 m; the dry saturated water absorption rate of mudstone in the vertical depth ranging of 0−6.5 m from the bottom interface of the alluvial layer is greater than 15%. The mudstone exposed to water features muddy disintegration, broken rock fragments and mud blocks, which means it is good water-proof performance of effective bridging mining cracks and a protective layer for waterproof coal pillars; as the strength of weathered mudstone below the alluvial layer 0 to 11.4 m is lower than it of the fine gravel aquifer in the lower that of 4.0 MPa, the sand control coal pillar’s protective layer that is greater more than 11.4 m is cannot be entirely composed of weathered mudstone; due to strong resistance to disintegration and lower dry saturated water absorption rate of sandstone, the protective layer cannot be entirely composed of weathered sandstone. The compressive strength of weathered sandstone, when it is higher than 4.0 MPa, can effectively resist the overlying water head pressure

Comparison of successful versus failed percutaneous coronary intervention in patients with chronic total occlusion: A systematic review and meta-analysis

Background: The optimal treatment strategy of chronic total occlusion (CTO) is currently debated. This meta-analysis aimed to evaluate the long-term clinical outcomes of successful percutaneous coronary intervention (PCI) of CTO. Methods: Electronic databases were searched for studies comparing long-term outcomes between successful PCI in patients with CTO using drug-eluting stents and failed procedures. Meta-analysis was conducted with major adverse cardiac events (MACE) and all-cause mortality during the longest follow-up as endpoints. The combined hazard ratios (HRs) were applied to assess the correlation between successful CTO PCI and MACE/all-cause mortality. Results: Eight studies consisting of 6,211 patients published between 2012 and 2020 met our inclusion criteria, and the CTO PCI success rate was 81.2%. Patients in the failed group were much older, and more likely to have morbidities (hypertension and prior myocardial infarction), reduced left ventricular ejection fraction, and severe lesion characteristics (multivessel disease and moderate/severe calcification). Pooled results indicated that successful CTO PCI was significantly associated with prognosis. Compared to failed recanalization, patients receiving successful procedures had an improved MACE (HR: 0.50, 95% CI: 0.40–0.61, p < 0.001). Subgroup analyses further revealed the prognostic value of successful CTO PCI. However, no difference was observed regarding all-cause mortality (HR: 0.79, 95% CI: 0.61–1.02, p = 0.074). Conclusions: The present study showed that CTO recanalization was associated with improved long-term outcomes. However, randomized trials are needed to confirm the results due to the mismatch of baseline characteristics

Metabolomic analysis of rumen-protected branched-chain amino acids in primiparous dairy cows

IntroductionPeripartal cows are susceptible to a negative energy balance due to inadequate nutrient intake and high energy requirements for lactation. Improving the energy metabolism of perinatal dairy cows is crucial in increasing production in dairy cows.MethodsIn this study, we investigated the impact of rumen-protected branched-chain amino acid (RPBCAA) on the production performance, energy and lipid metabolism, oxidative stress, and immune function of primiparous dairy cows using metabolomics through a single-factor experiment. Twenty healthy primiparous Holstein cows were selected based on body condition scores and expected calving date, and were randomly divided into RPBCAA (n = 10) and control (n = 10) groups. The control group received a basal diet from calving until 21 d in milk, and the RPBCAA group received the basal diet and 44.6 g/d RPLeu, 25.14 g/d RPIle, and 25.43 g/d RPVal.ResultsIn comparison to the control group, the supplementation of RPBCAA had no significant effect on milk yield and milk composition of the dairy cows. Supplementation with RPBCAA significantly increased the concentrations of insulin, insulin growth factor 1, glucagon, and growth hormones, which are indicators of energy metabolism in postpartum cows. The very low density lipoprotein, fatty acid synthase, acetyl coenzyme A carboxylase, and hormone-sensitive lipase contents of the RPBCAA group were significantly greater than that of the control group; these metrics are related to lipid metabolism. In addition, RPBCAA supplementation significantly increased serum glutathione peroxidase and immunoglobulin G concentrations and decreased malondialdehyde concentrations. Liquid chromatography–mass spectrometry (LC-MS) analysis revealed 414 serum and 430 milk metabolic features. Supplementation with RPBCAA primarily increased concentrations of amino acid and lipid metabolism pathways and upregulated the abundance of serotonin, glutamine, and phosphatidylcholines.DiscussionIn summary, adding RPBCAA to the daily ration can influence endocrine function and improve energy metabolism, regulate amino acid and lipid metabolism, mitigate oxidative stress and maintain immune function on primiparous cows in early lactation

Familial cluster of COVID-19 infection from an asymptomatic

Since December 2019, the first case of a novel coronavirus (COVID-19) infection pneumonia was detected in Wuhan, and the outbreak has been spreading rapidly in the world. As of February 18, 2020, a total of 73,332 cases of confirmed COVID-19 infection have been detected in the world as reported by the WHO [1, 2]. Given that the asymptomatic persons are potential sources of COVID-19 infection [3], we report a familial cluster case of five patients infected with COVID-19 from an asymptomatic confirmed case in Beijing. We obtained the data of patients, which included demographic, epidemiological, and clinical features; chest radiography; laboratory test; and outcomes. Laboratory confirmation of COVID-19 was detected in the first hospital admission and verified by the Beijing Center for Disease Control and Prevention (CDC). An asymptomatic case was defined as a laboratory-confirmed COVID-19 infection case who was afebrile and well. We enrolled the family that had five patients in total with COVID-19 infection who were transferred by the Beijing Emergency Medical Service (EMS) from January 24 to 27, 2020, to the designated hospitals for special treatment. Clinical outcomes were followed up to February 29, 2020

OPTIMIZATION DESIGN OF TOWER DOOR STRUCTURE BASED ON ISIGHT

In the multidisciplinary optimization ISIGHT software environment,the comprehensive application of PRO / E parametric-modeling function and ABAQUS FEA function establish a framework of CAD / CAE integrated optimization design for tower door. Firstly,the parametric geometric model of door is built,Secondly,the FEA model is established and submitted. The interaction effects and the correlation factor between the geometric parameters and stress are analyzed by the DOE method of optimal LHD algorithm. Static strength optimization design of door is done by the ASA global optimization algorithm. The whole tower weight is as objection,the can strength the optimal design solutions of the door is gotten. The paper provides a scientific design method for strength optimization design of the tower door

An Agile Super-Resolution Network via Intelligent Path Selection

In edge computing environments, limited storage and computational resources pose significant challenges to complex super-resolution network models. To address these challenges, we propose an agile super-resolution network via intelligent path selection (ASRN) that utilizes a policy network for dynamic path selection, thereby optimizing the inference process of super-resolution network models. Its primary objective is to substantially reduce the computational burden while maximally maintaining the super-resolution quality. To achieve this goal, a unique reward function is proposed to guide the policy network towards identifying optimal policies. The proposed ASRN not only streamlines the inference process but also significantly boosts inference speed on edge devices without compromising the quality of super-resolution images. Extensive experiments across multiple datasets confirm ASRN’s remarkable ability to accelerate inference speeds while maintaining minimal performance degradation. Additionally, we explore the broad applicability and practical value of ASRN in various edge computing scenarios, indicating its widespread potential in this rapidly evolving domain

ScatterFormer: Locally-Invariant Scattering Transformer for Patient-Independent Multispectral Detection of Epileptiform Discharges

Patient-independent detection of epileptic activities based on visual spectral representation of continuous EEG (cEEG) has been widely used for diagnosing epilepsy. However, precise detection remains a considerable challenge due to subtle variabilities across subjects, channels and time points. Thus, capturing fine-grained, discriminative features of EEG patterns, which is associated with high-frequency textural information, is yet to be resolved. In this work, we propose Scattering Transformer (ScatterFormer), an invariant scattering transform-based hierarchical Transformer that specifically pays attention to subtle features. In particular, the disentangled frequency-aware attention (FAA) enables the Transformer to capture clinically informative high-frequency components, offering a novel clinical explainability based on visual encoding of multichannel EEG signals. Evaluations on two distinct tasks of epileptiform detection demonstrate the effectiveness our method. Our proposed model achieves median AUCROC and accuracy of 98.14%, 96.39% in patients with Rolandic epilepsy. On a neonatal seizure detection benchmark, it outperforms the state-of-the-art by 9% in terms of average AUCROC

The effect of urban 2D and 3D morphology on air temperature in residential neighborhoods

Context: Both urban two-dimensional (2D) and three-dimensional (3D) morphology can affect air and land surface temperature. While many studies have looked at the impact of horizontal morphology, few have explored the relationship between vertical morphology and temperature, especially at the neighborhood scale. Objectives: This study aims to answer two questions: (1) Does air temperature vary in neighborhoods with different morphology? (2) If so, how does the 2D (horizontal) and 3D (vertical) morphology affect air temperature? Methods: We examined the relationship between morphology and air temperature for 24 residential neighborhoods in Beijing, using correlation analysis, regression analysis, and structural equation modeling. Morphological indicators were derived from remotely sensed land cover and light detecting and ranging (LiDAR) point cloud data. Air temperature was continuously measured using HOBO data loggers during the summer of 2014. ResultsNighttime air temperature was higher in neighborhoods dominated by high-rise structures compared to neighborhoods dominated by low-rise structures suggesting that 3D morphology is more important than 2D morphology in predicting air temperature. The ratio of vegetation volume to building volume negatively correlated with average air temperature and daytime temperature, while the mean distance among adjacent buildings had a positive effect. Building height was the most important predictor of nighttime air temperature. The major determinants of air temperature in high-rise and low-rise neighborhoods were different. Conclusions: Both 2D and 3D morphology can affect air temperature in residential neighborhoods. Increasing vegetation volume relative to building volume and decreasing the distance among buildings can reduce daytime air temperatures