Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and characterization of sorafenib-loaded lipid nanocapsules for the treatment of glioblastoma

Abstract Anticancer agents that target both tumor cells and angiogenesis are of potential interest for glioblastoma (GB) therapy. One such agent is sorafenib (SFN), a tyrosine kinase inhibitor. However, poor aqueous solubility and undesirable side effects limit its clinical application, including local treatment. We encapsulated SFN in lipid nanocapsules (LNCs) to overcome these drawbacks. LNCs are nanocarriers formulated according to a solvent-free process, using only components that have received regulatory approval. SFN-LNCs had a diameter of 54 ± 1 nm, high encapsulation efficiency (>90%), and a drug payload of 2.11 ± 0.03 mg/g of LNC dispersion. They inhibited in vitro angiogenesis and decreased human U87MG GB cell viability similarly to free SFN. In vivo studies showed that the intratumoral administration of SFN-LNCs or free SFN in nude mice bearing an orthotopic U87MG human GB xenograft decreased the proportion of proliferating cells in the tumor relative to control groups. SFN-LNCs were more effective than free SFN for inducing early tumor vascular normalization, characterized by increases in tumor blood flow and decreases in tumor vessel area. These results highlight the potential of LNCs as delivery systems for SFN. The vascular normalization induced by SFN-LNCs could be used to improve the efficacy of chemotherapy or radiotherapy for treating GB.
Relationships between muscle size, strength, and physical activity in adults with muscular dystrophy

Muscular dystrophy (MD) is characterized by progressive muscle wasting and weakness, yet few comparisons to non‐MD controls (CTRL) of muscle strength and size in this adult population exist. Physical activity (PA) is promoted to maintain health and muscle strength within MD; however, PA reporting in adults with MD is limited to recall data, and its impact on muscle strength is seldom explored.
Tunable Intermodulation Generator for Passive Intermodulation Tester Calibration

As a key step to guarantee passive intermodulation (PIM) test accuracy, PIM calibration for PIM tester draws great attention these days. This paper provides three solutions to realize tunable PIM calibration standard sources for PIM tester calibration. Two types of nonlinearity sources are applied while three circuit or cavity structures are developed to control these sources. By using different strategies, the proposed PIM sources can generate controllable PIM references with different ranges that cover most PIM test ranges. In the experiments, the PIM signal stability is evaluated as well as PIM dynamic range. They show the minimal PIM fluctuation as less as 1dB, while the maximal dynamic range can reach 50dB. As these solutions have various sizes and function, they can be utilized according to different test requirements and easily integrated with PIM tester. These solutions can help develop new generation of PIM testers.
Environmental exposure to triclosan and polycystic ovary syndrome: a cross-sectional study in China

Objectives Polycystic ovary syndrome (PCOS) is the most common endocrinopathy of women at reproductive age. Although the aetiology of PCOS remains unclear, potential effects of environmental endocrine-disrupting compounds on the development of PCOS have drawn increasing attention. The aim of the current study was to examine the association between triclosan (TCS) and PCOS, and explore possible mechanisms on how TCS may contribute to the development of clinical manifestations of PCOS. Design Cross-sectional study. Setting This study was conducted in one tertiary-level hospital located in Zhejiang, China. Participants A total of 674 infertile women at 18–45 years of age were recruited in 2014–2015. Participants with (n=84) and without (n=212) PCOS with urinary TCS concentration available were included in the analyses. Methods Urinary TCS concentration was measured using a high-performance liquid chromatography–electrospray ionisation tandem mass spectrometry. Logistic regression model was used to examine the association between TCS and PCOS. Fractional polynomial regression models were built to fit the potential non-linear relationship between TCS concentrations and luteinising hormone (LH) and LH/follicle stimulate hormone (FSH). Results The PCOS group had significantly higher level of TCS concentration than the non-PCOS group (the median of TCS (IQR), μg/g creatinine: 1.49 (0.68–3.80) vs 1.06 (0.52–3.02), p=0.0407). Compared with the lowest tertile, the highest tertile of TCS concentration was associated with an increased odd of PCOS (OR 2.12, 95% CI 1.12 to 3.99). After adjusting for potential confounders, the significant association remained (OR 1.99, 95% CI 1.05 to 3.79). Positive relationships were found between TCS levels and LH and LH/FSH ratio in non-PCOS participants. Conclusions TCS exposure at a relatively low level is associated with PCOS in Chinese women. Further epidemiological studies are needed to confirm our finding, which may have important public health implications.
Interleukin-22, a potent target for treatment of non-autoimmune diseases

ABSTRACT Interleukin −22 (IL-22) is a member of interleukin-10 (IL-10) family cytokines that is produced by different types of lymphocytes included in both innate and adaptive immune systems. These lymphocytes include activated T cells, most notably Th17 and Th22 cells, as well as NK cells, γδ T cells, etc. IL-22 mediate its effects via the IL-22-IL-22R complex and subsequent Janus Kinase-signal transduces and activators transcription (JAK-STAT) signaling pathway. According to recent evidence, IL-22 played a critical role in the pathogenesis of many non-autoimmune diseases. In this review, we mainly discussed the recent findings and advancements of the role of IL-22 in several non-autoimmune diseases, such as acute lung injury, atherosclerosis and some bacterial infections, suggesting that IL-22 may have therapeutic potential for treating non-autoimmune diseases.
Programmed DNA destruction by miniature CRISPR-Cas14 enzymes

A programmable type of CRISPR system CRISPR-Cas9 systems have been causing a revolution in biology. Harrington et al. describe the discovery and technological implementation of an additional type of CRISPR system based on an extracompact effector protein, Cas14. Metagenomics data, particularly from uncultivated samples, uncovered the CRISPR-Cas14 systems containing all the components necessary for adaptive immunity in prokaryotes. At half the size of class 2 CRISPR effectors, Cas14 appears to target single-stranded DNA without class 2 sequence restrictions. By leveraging this activity, a fast and high-fidelity nucleic acid detection system enabled detection of single-nucleotide polymorphisms. Science, this issue p. 839 Identification, characterization, and technological implementation of additional archaea-derived CRISPR-Cas14 systems are described. CRISPR-Cas systems provide microbes with adaptive immunity to infectious nucleic acids and are widely employed as genome editing tools. These tools use RNA-guided Cas proteins whose large size (950 to 1400 amino acids) has been considered essential to their specific DNA- or RNA-targeting activities. Here we present a set of CRISPR-Cas systems from uncultivated archaea that contain Cas14, a family of exceptionally compact RNA-guided nucleases (400 to 700 amino acids). Despite their small size, Cas14 proteins are capable of targeted single-stranded DNA (ssDNA) cleavage without restrictive sequence requirements. Moreover, target recognition by Cas14 triggers nonspecific cutting of ssDNA molecules, an activity that enables high-fidelity single-nucleotide polymorphism genotyping (Cas14-DETECTR). Metagenomic data show that multiple CRISPR-Cas14 systems evolved independently and suggest a potential evolutionary origin of single-effector CRISPR-based adaptive immunity.
Technology-Based Physical Activity Self-Monitoring Among College Students

Understanding the relationship between college students’ physical activity (PA) self-monitoring and PA levels has the potential to inform initiatives to promote PA. This study’s purpose was to examine the prevalence of technology-based self-monitoring among college students the potential relationship between device usage, goal setting behaviors, PA enjoyment, and PA levels. An online survey assessed students’ demographics, current PA level, technology-based PA self-monitoring, and psychosocial outcomes. Independent t-tests examined differences in PA level and psychosocial outcomes by device use. 55.5% of the final sample (N=1,154) reported technology-based self-monitoring. Mobile phone app-based PA tracking was the most commonly reported (29.9%), followed by heart rate monitors (23.1%). Device use was significantly related to vigorous PA and psychosocial outcomes. Findings have the potential to inform development of technology-based interventions that promote student PA.
Radiated Wideband IEMI: Coupling Model and Worst-Case Analysis for Smart Grid Wiring Harness

The fast transition from the conventional electrical-energy infrastructures to the Smart Grid demands for an in-depth analysis of risks associated to Intentional Electromagnetic Interference (IEMI). In line with this aim, this work presents an approach for the prediction of the effects of wideband radiated IEMI in wire harness, based on a worst-case criterion. For a specified bandwidth and energy density, the waveform of the electromagnetic (EM) field is optimized so to maximize the peak value of the common-mode voltage induced at cable terminals. This solution depends on the unknown direction of incidence and polarization angle of the EM field. The worst-case rationale is therefore extended to the search for the extreme value of the induced peak voltage, which is reached in specific, unfavorable conditions of incidence and polarization, here investigated. Moreover, the impact of the main geometrical/electrical parameters of the wiring structure (length, height, impedances) is assessed.
Hybrid Analytical Modeling of Saturated Linear and Rotary Electrical Machines: Integration of Fourier Modeling and Magnetic Equivalent Circuits

This paper presents a 2-D hybrid analytical modeling method for the analysis of the magnetostatic field distribution with the capability of including nonlinear materials. The model combines Fourier modeling, which is accurate and fast, with meshed magnetic equivalent circuits that have unique permeability in mesh elements and, therefore, can model local saturation. To present the diverse applicability of the proposed method, it is applied to a linear machine with permanent magnet excitation and a rotary machine with current excitation. Magnetic field calculations are compared with finite-element analysis (FEA) with good agreement.
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey

This paper presents a comprehensive literature review on applications of deep reinforcement learning (DRL) in communications and networking. Modern networks, e.g., Internet of Things (IoT) and unmanned aerial vehicle (UAV) networks, become more decentralized and autonomous. In such networks, network entities need to make decisions locally to maximize the network performance under uncertainty of network environment. Reinforcement learning has been efficiently used to enable the network entities to obtain the optimal policy including, e.g., decisions or actions, given their states when the state and action spaces are small. However, in complex and large-scale networks, the state and action spaces are usually large, and the reinforcement learning may not be able to find the optimal policy in reasonable time. Therefore, DRL, a combination of reinforcement learning with deep learning, has been developed to overcome the shortcomings. In this survey, we first give a tutorial of DRL from fundamental concepts to advanced models. Then, we review DRL approaches proposed to address emerging issues in communications and networking. The issues include dynamic network access, data rate control, wireless caching, data offloading, network security, and connectivity preservation which are all important to next generation networks, such as 5G and beyond. Furthermore, we present applications of DRL for traffic routing, resource sharing, and data collection. Finally, we highlight important challenges, open issues, and future research directions of applying DRL.
Metabolic syndrome in polycystic ovary syndrome: a systematic review, meta‐analysis and meta‐regression

Women with polycystic ovary syndrome (PCOS) have increased risk of metabolic syndrome. The relative contribution of clinical, demographic or biochemical factors to metabolic syndrome in PCOS is not known. A literature search was conducted in MEDLINE, CINAHL, EMBASE and clinical trial registries. Of 4530 studies reviewed, 59 were included in the systematic review and 27 in the meta‐analysis and meta‐regression. In good and fair quality studies, women with PCOS had an overall increased prevalence of metabolic syndrome (odds ratio, OR 3.35, 95% confidence interval, CI 2.44, 4.59). Increased prevalence of metabolic syndrome occurred in overweight or obese women with PCOS (OR 1.88, 95% 1.16, 3.04) but not in lean women (OR 1.45, 95% CI 0.35, 6.12). In meta‐regression analyses, the markers of metabolic syndrome diagnostic criteria (waist circumference, high‐density lipoprotein cholesterol, triglyceride, blood pressure), BMI, glucose tolerance (2‐hr oral glucose tolerance test) and surrogate markers of insulin resistance (HOMA‐IR) but not markers of reproductive dysfunction (sex hormone binding globulin, testosterone, PCOS phenotypes) contributed significantly to the heterogeneity in the prevalence of metabolic syndrome. Women with PCOS have increased risk of metabolic syndrome which was associated with obesity and metabolic features but not with indices of hyperandrogenism.
DC-Arcing Detection by Noise Measurement With Magnetic Sensing by TMR Sensors

An arc fault establishes a current path in the air which may cause malfunction of direct current (dc) system and even a fire hazard. Arc fault detection is essential to improving the reliability, efficiency, and safety of the dc system. However, the randomness of dc arc faults makes it difficult to define their characteristics. In this paper, a magnetic-sensing-based technique is proposed to detect dc arc. This paper developed a promising dc-arcing detection technique based on the analysis of frequency-domain features of the magnetic field measured by a magnetic sensor. The effects of the supply voltage, load current, and electrode diameter on the frequency domain of the arc current were investigated. The experimental results show that the proposed detection technique could reliably discriminate the normal operation and arc fault. This technique is cost-effective because it can be implemented with low-cost magnetoresistive sensors and does not require an expensive current transformer.
Eigen-Analysis of Large Delayed Cyber-Physical Power System by Time Integration-Based Solution Operator Discretization Methods

In this paper, solution operator discretization methods with linear multistep and implicit Runge–Kutta (SOD-LMS/IRK) are presented for efficient eigen-analysis of large delayed cyber-physical power system (DCPPS). First, the time integration-based discretization generates highly structured approximate matrices to the solution operator. Exploitation of the structure ensures low computational burden and high efficiency in solving the matrix-inversion-vector product involved in eigenvalue computation. Second, the implicitly restarted Arnoldi algorithm is employed to compute critical eigenvalue from the solution operator's discretized matrices. SOD-LMS/IRK are endowed with scalability in analyzing very large DCPPS by fully utilizing the inherent sparsity in the augmented system state matrices. The main contribution of the presented SOD-LMS/IRK is the improved efficiency and scalability of existing SOD-PS (pseudo-spectral collocation) and SOD-LMS/IRK. Numerical results on the 16-generator 68-bus test system, a 516-bus, and a 33028-bus real-life large transmission systems validate the effectiveness of the proposed SOD-LMS/IRK.
Patterned Deposition of Xylan and Lignin is Independent from that of the Secondary Wall Cellulose of Arabidopsis Xylem Vessels[OPEN]

A novel cesa7 mutant revealed that patterned deposition of non-cellulosic secondary wall polymers, xylan and lignin, is not dependent on cellulose patterning during xylem vessel differentiation. The secondary cell wall (SCW) of xylem vessel cells provides rigidity and strength that enables efficient water conduction throughout the plant. To gain insight into SCW deposition, we mutagenized Arabidopsis thaliana VASCULAR-RELATED NAC-DOMAIN7-inducible plant lines, in which ectopic protoxylem vessel cell differentiation is synchronously induced. The baculites mutant was isolated based on the absence of helical SCW patterns in ectopically-induced protoxylem vessel cells, and mature baculites plants exhibited an irregular xylem (irx) mutant phenotype in mature plants. A single nucleic acid substitution in the CELLULOSE SYNTHASE SUBUNIT 7 (CESA7) gene in baculites was identified: while the mutation was predicted to produce a C-terminal truncated protein, immunoblot analysis revealed that cesa7bac mutation results in loss of production of CESA7 proteins, indicating that baculites is a novel cesa7 loss-of-function mutant. In cesa7bac, despite a lack of patterned cellulose deposition, the helically-patterned deposition of other SCW components, such as the hemicellulose xylan and the phenolic polymer lignin, was not affected. Similar phenotypes were found in another point mutation mutant cesa7mur10-2, and an established knock-out mutant, cesa7irx3-4. Taken together, we propose that the spatio-temporal deposition of different SCW components, such as xylan and lignin, is not dependent on cellulose patterning.
Preference Aggregation with Incomplete CP-Nets

Generalized CP-nets (gCP-nets) extend standard CP-nets by allowing conditional preference tables to be incomplete. Such generality is desirable, as in practice users may want to express preferences over the values of a variable that depend only on partial assignments for other variables. In this paper we study aggregation of gCP-nets, under the name of multiple gCP-nets (mgCP-nets). Inspired by existing research on mCP-nets, we define different semantics for mgCP-nets and study the complexity of prominent reasoning tasks such as dominance, consistency and various notions of optimality.
Design and Characterization of a Soft Dielectric Elastomer Peristaltic Pump Driven by Electromechanical Load

Pumps are widely used in nature and engineering to transport fluids, particles, and mixtures. Compared to those in engineering, most natural pumps are soft, highly efficient, and reliable. In this paper, we design a soft dielectric elastomer peristaltic pump (DEPP) inspired by the human heart. The DEPP is composed of two pump modules and each module consists of four layers of dielectric elastomer membrane and three layers of carbon grease as electrodes. The two pump modules are driven by two complementary signals with different waveforms including square, sine, sawtooth, and triangular waves. We build a measuring system including pressure and flow rate sensors to characterize the DEPP's performance. The experimental results reveal that the square wave voltage provides the highest flow rate and pressure difference compared to the other three waveforms. The mechanical resonance of DEPP is observed and the optimal frequency with square wave voltage is about 1.5 Hz, which falls in the range of the human heart rate. The optimal frequency decreases with the increase of electromechanical loads. In the experiment, compared with the existing dielectric elastomer pump, we obtain the highest average flow rate and the highest instant flow rate as 2.5 L/min and 3.2 L/min, respectively. The maximum pump volume per cycle for the DEPP is 0.09 L. It takes about 1 s for the DEPP to reach a new equilibrium state when the working frequency of the voltage is switched from 1 to 1.5 Hz. It is hoped that this study will guide the development of new artificial hearts and other soft industrial pumps.
Beyond Google Play: A Large-Scale Comparative Study of Chinese Android App Markets

China is one of the largest Android markets in the world. As Chinese users cannot access Google Play to buy and install Android apps, a number of independent app stores have emerged and compete in the Chinese app market. Some of the Chinese app stores are pre-installed vendor-specific app markets (e.g., Huawei, Xiaomi and OPPO), whereas others are maintained by large tech companies (e.g., Baidu, Qihoo 360 and Tencent). The nature of these app stores and the content available through them vary greatly, including their trustworthiness and security guarantees. As of today, the research community has not studied the Chinese Android ecosystem in depth. To fill this gap, we present the first large-scale comparative study that covers more than 6 million Android apps downloaded from 16 Chinese app markets and Google Play. We focus our study on catalog similarity across app stores, their features, publishing dynamics, and the prevalence of various forms of misbehavior (including the presence of fake, cloned and malicious apps). Our findings also suggest heterogeneous developer behavior across app stores, in terms of code maintenance, use of third-party services, and so forth. Overall, Chinese app markets perform substantially worse when taking active measures to protect mobile users and legit developers from deceptive and abusive actors, showing a significantly higher prevalence of malware, fake, and cloned apps than Google Play.
Natural history of mineral metabolism, bone turnover and bone mineral density in de novo renal transplant recipients treated with a steroid minimization immunosuppressive protocol.

The skeletal effects of renal transplantation are not completely understood, especially in patients managed with a steroid minimization immunosuppressive protocol and long term. We enrolled 69 adult transplant recipients (39 males; ages 51.1 ± 12.2 years), free of antiresorptive therapy and managed with a steroid minimization immunosuppressive protocol, into a 5-year prospective observational study to evaluate changes in areal bone mineral density (aBMD), mineral metabolism and bone remodelling. Dual energy X-ray absorptiometry, laboratory parameters of mineral metabolism (including parathyroid hormone, sclerostin and fibroblast growth factor 23) and non-renal cleared bone turnover markers (BTMs) (bone-specific alkaline phosphatase, trimeric N-terminal propeptide and tartrate-resistant acid phosphatase 5b) were assessed at baseline and 1 and 5 years post-transplantation. The mean cumulative methylprednisolone exposure at 1 and 5 years amounted to 2.5 ± 0.8 and 5.8 ± 3.3 g, respectively. Overall, bone remodelling activity decreased after transplantation. Post-transplant aBMD changes were minimal and were significant only in the ultradistal radius during the first post-operative year {median -2.2% [interquartile range (IQR) -5.9-1.2] decline, P = 0.01} and in the lumbar spine between Years 1 and 5 [median 1.6% (IQR -3.2-7.0) increase, P = 0.009]. BTMs, as opposed to mineral metabolism parameters and cumulative corticosteroid exposure, associated with aBMD changes, both in the early and late post-transplant period. Most notably, aBMD changes inversely associated with bone remodelling changes. In summary, in de novo renal transplant recipients treated with a steroid minimization immunosuppressive protocol, BMD changes are limited, highly variable and related to remodelling activity rather than corticosteroid exposure.