Miracle-dz/UniFAR-FTUs huggingface dataset:
Regulation of C-C chemokine receptor 5 (CCR5) stability by Lys197 and by transmembrane protein aptamers that target it for lysosomal degradation

C-C motif chemokine receptor 5 (CCR5) is a cell surface–associated, immune-regulatory G protein–coupled receptor (GCPR) with seven transmembrane helices. We previously reported the isolation and initial characterization of short artificial transmembrane protein aptamers, named “traptamers,” that specifically down-regulate CCR5 expression and inhibit infection of human T cells by HIV strains that use CCR5 as a co-receptor. Here, we investigated the mechanism of traptamer-mediated CCR5 down-regulation and show that most of the traptamers (designated class 1 traptamers) form a stable complex with CCR5 and target it for lysosome-mediated degradation. The ability of these traptamers to down-regulate CCR5 depended on Lys197 in the fifth transmembrane helix of CCR5. In the absence of traptamers, substitution of Lys197 to an uncharged amino acid increased CCR5 stability, and introduction of a lysine at the homologous position in CCR2b, a related chemokine receptor, decreased CCR2b levels. The prototypic class 2 traptamer BY6M4 also formed a complex with CCR5, but CCR5 down-regulation caused by class 2 traptamers did not depend on the lysosome or on Lys197. These results demonstrate that traptamers use diverse mechanisms to down-regulate CCR5 and identify a specific amino acid that plays a central role in controlling chemokine receptor stability. Further studies of these traptamers are likely to provide new insights into CCR5 metabolism and biology and may suggest new therapeutic approaches to modulate the levels of CCR5 and other GPCRs.
Personalised Patient Embeddings - Towards a Whole Data Health Profile

True personalised medicine relies on being able to create a learned representation, or embedding, of a patient’s health data. While efforts have been made to incorporate some of the data available, there is a distinct lack of imaging modalities used to develop this representation. Due to the complexity of extracting useful features across data types from imaging to text, including overcoming data sparsity, accurately embedding multi-modal data, and ensuring interpretability, design decisions for machine learning models need to take this into account. This article covers the rationale driving the development of personalised patient embeddings, the current approaches used with healthcare data and in the wider realm of multi-modal deep learning as well as shortfalls and challenges. Finally, drawing on current best practices and extensions to single mode learning metrics as well as the shifting focus towards utilising a patient’s imaging data for determining relevant clinical factors, a model architecture is proposed and discussed.
Analysis and design of an energy regenerative snubber for magnetically coupled impedance source converters

Magnetically coupled impedance source (MCIS) converters are prone to high voltage spikes across the inverter bridge (or dc-link) due to the presence of leakage and stray inductances in the high frequency loop. The problem manifolds because of a shoot-through state in impedance source converters, which avoids application of a decoupling dc-link capacitor. This makes the impedance source converter less attractive for industry applications despite of its merits over the conventional voltage-fed and current-fed inverters. Only few attempts have been made in the literature to solve this problem, but the solutions are not generic (i.e. structure-oriented) and they are quite lossy with intuitive modification in the circuit itself, resulting in significant changes in the performance of the power converter (e.g. increase in components stresses). To address this concern, a general passive regenerative inductor-capacitor-diode (L-C-D) snubber is presented in this paper for all MCIS converters without any modification in the original circuit. The proposed circuit rechannel the leakage energy of the coupled magnetics and feedback it to input or network itself, which does not only avoid extreme voltage spikes across the inverter bridge but also improves the efficiency of the system. In this paper, the analysis of the proposed snubber is introduced with simulation results and experimental implementation of the proposed snubber in a 500 W three-phase quasi-Y-source inverter (qYSI) to verify the efficacy of the proposed solution.
Irinotecan or oxaliplatin combined with leucovorin and 5-fluorouracil as first-line treatment in advanced colorectal cancer: a multicenter, randomized, phase II study.

BACKGROUND Irinotecan (IRI) and oxaliplatin (OXA) are effective in the treatment of colorectal cancer. Previously untreated patients with advanced colorectal carcinoma (CRC) were randomly assigned to receive IRI plus leucovorin (LV)/5-fluorouracil (5-FU), or OXA plus LV/5-FU in order to compare the response rates, time-to-tumor progression, overall survival rates, and toxicity profiles of these two agents. MATERIALS AND METHODS From January 1999 to February 2002, 295 patients were randomized to receive either IRI/LV/5-FU or OXA/LV/5-FU. The treatment schedules consisted of weekly IRI 70 mg/m(2) or OXA 45 mg/m(2) plus LV 200 mg/m(2) followed immediately by intravenous bolus 5-FU 450 mg/m(2) for 6 weeks, followed by a 2-week rest period. Treatment was continued for up to four cycles or until disease progression, unacceptable toxicity or patient refusal. RESULTS There were no significant differences between the study arms in the overall response rate (33% with IRI/LV/5-FU versus 32% with OXA/LV/5-FU based on responses demonstrated on a single evaluation; 23% with IRI/LV/5-FU versus 22.3% with OXA/LV/5-FU based on responses confirmed according to WHO criteria) median time to progression (8.9 versus 7.6 months), and median overall survival (17.6 versus 17.4 months). Toxicity profiles (grades 3 and 4) were similar in the IRI and OXA arms (diarrhea 12.3% and 9.8%, neutropenia 8.2% and 4.9%, and febrile neutropenia 1.4% and 1.4%, respectively), with the exception of grade 3 sensory neuropathy, which almost exclusively occurred in the OXA arm (0% versus 5.6%; P=0.003, Fisher's exact test). CONCLUSION The IRI/LV/5-FU and OXA/LV/5-FU regimens demonstrated equally substantial efficacies and manageable toxicity profiles in the first-line treatment of patients with advanced CRC. However, IRI/LV/5-FU may be the preferable regimen to avoid significant neurotoxicity associated with OXA-LV/5-FU.
Stability Analysis of SSR in Multiple Wind Farms Connected to Series-Compensated Systems Using Impedance Network Model

Recently, an emerging subsynchronous resonance (SSR) issue was observed in series-compensated systems comprising multiple wind farms. However, only simplified single-machine-infinite-bus system models were adopted to investigate the characteristics of this issue in the previous work. As a result, it is unable to reflect the impact on SSR from some critical factors, such as the network topology, the spatial distribution of wind farms, the diversity of wind turbine generators, and the distributed wind speed. To fill in this gap, this paper proposes an impedance network model (INM) based SSR stability analysis method. The impedance models of each wind farm and transmission line are established, and then interconnected according to system topology to form the whole INM. Such INM is further aggregated into lumped impedance. By analyzing the impedance-frequency features of the latter, a new stability criterion is developed to quantify the stability of SSR. The application of the criterion is demonstrated on a practical power system containing multiple wind farms. Both field measurements and time-domain simulations have been presented to validate its effectiveness and accuracy. The proposed method is of great potential in analyzing the SSR issue for very large-scale wind power systems.
Exploring Hypersonic, Unstructured-Grid Issues through Structured Grids

Pure-tetrahedral unstructured grids have been shown to produce asymmetric heat transfer rates for symmetric problems. Meanwhile, two-dimensional structured grids produce symmetric solutions and as documented here, introducing a spanwise degree of freedom to these structured grids also yields symmetric solutions. The effects of grid skewness and other perturbations of structured-grids are investigated to uncover possible mechanisms behind the unstructured-grid solution asymmetries. By using controlled experiments around a known, good solution, the effects of particular grid pathologies are uncovered. These structured-grid experiments reveal that similar solution degradation occurs as for unstructured grids, especially for heat transfer rates. Non-smooth grids within the boundary layer is also shown to produce large local errors in heat flux but do not affect surface pressures.
An Intrusion Detection System using KNN-ACO Algorithm

With the remarkable enlargement of the usage of computers through the network and expansion in application running on several platform captures the consideration toward network security. This hypothesis exploits security susceptibilities on the entire computer systems that are technically challenging and expensive to resolve. Therefore, intrusion is employs as a key to conciliate reliability, availability and privacy/confidentiality of a computer resource. An Intrusion Detection System (IDS) participates a noteworthy responsibility in detecting anomalies and attacks over’s network. In this research work, data mining conception is integrated with IDS to sort assured the relevant, concealed information of interest for the user efficiently and with fewer implementation times. Four concerns likely Classification of Data, Lack of Labeled Data, Extreme Level of Human Interaction and Effectiveness of D-DOS are being resolved by using the projected algorithms like EDADT algorithm, Semi-Supervised Approach, Hybrid IDS model and transforming HOPERAA Algorithm respectively. In this paper, proposes a SVM and KNN-ACO method for the intrusion detection and the analysis of this is perform using KDD1999 Cup dataset. This proposed algorithm shows improved precision and concentrated false alarm
A haplotype of three SNPs in FTO had a strong association with body composition and BMI in Iranian male adolescents

Background Single-nucleotide polymorphisms (SNPs), which are located in the first intron of the FTO gene, are reported to be associated with body weight and the body mass index (BMI). However, their effects on anthropometric measurements in adolescents are poorly understood. Objective This study aimed to investigate the association of three adjacent polymorphisms (rs9930506, rs9930501, & rs9932754) in the FTO gene with anthropometric indices in Iranian adolescent males. Design The participants comprised a total of 237 adolescent males who were recruited randomly from two high schools in Tehran, Iran. The DNA samples were genotyped for the FTO gene polymorphisms by DNA sequencing. BMI, body fat percentage (BF%), and body muscle percentage (BM%) were determined using a validated bioelectrical impedance analysis scale. The association of the FTO polymorphisms with weight, height, BMI, BF%, and BM% was investigated. Results A haplotype of rs9930506, rs9930501, and rs9932754 (GGT) in the first intron of the FTO with complete linkage disequilibrium (LD) was found to be significantly associated with higher weight (OR = 1.32), BMI (OR = 5.36) and BF% (OR = 1.46), and lower BM% (OR = 3.59) (all P<0.001). None of the students with GGC genotypes were underweight, while all of the students with AAT genotypes had high muscle mass. Conclusions A haplotype in the first intron of the FTO gene had a strong association with obesity indices in Iranian adolescent males. The FTO gene polymorphisms might have greater effects on anthropometric indices than what was previously imagined. Moreover, we suggested that the FTO gene exerted their effects on anthropometric measurements through haplotypes (and not single SNPs).
Adaptive Boundary Iterative Learning Control for an Euler–Bernoulli Beam System With Input Constraint

This paper addresses the vibration control and the input constraint for an Euler–Bernoulli beam system under aperiodic distributed disturbance and aperiodic boundary disturbance. Hyperbolic tangent functions and saturation functions are adopted to tackle the input constraint. A restrained adaptive boundary iterative learning control (ABILC) law is proposed based on a time-weighted Lyapunov–Krasovskii-like composite energy function. In order to deal with the uncertainty of a system parameter and reject the external disturbances, three adaptive laws are designed and learned in the iteration domain. All the system states of the closed-loop system are proved to be bounded in each iteration. Along the iteration axis, the displacements asymptotically converge toward zero. Simulation results are provided to illustrate the effectiveness of the proposed ABILC scheme.
Biocompatibility of nanostructured boron doped diamond for the attachment and proliferation of human neural stem cells

Objective. We quantitatively investigate the biocompatibility of chemical vapour deposited (CVD) nanocrystalline diamond (NCD) after the inclusion of boron, with and without nanostructuring. The nanostructuring method involves a novel approach of growing NCD over carbon nanotubes (CNTs) that act as a 3D scaffold. This nanostructuring of BNCD leads to a material with increased capacitance, and this along with wide electrochemical window makes BNCD an ideal material for neural interface applications, and thus it is essential that their biocompatibility is investigated. Approach. Biocompatibility was assessed by observing the interaction of human neural stem cells (hNSCs) with a variety of NCD substrates including un-doped ones, and NCD doped with boron, which are both planar, and nanostructured. hNSCs were chosen due to their sensitivity, and various methods including cell population and confluency were used to quantify biocompatibility. Main results. Boron inclusion into NCD film was shown to have no observable effect on hNSC attachment, proliferation and viability. Furthermore, the biocompatibility of nanostructured boron-doped NCD is increased upon nanostructuring, potentially due to the increased surface area. Significance. Diamond is an attractive material for supporting the attachment and development of cells as it can show exceptional biocompatibility. When boron is used as a dopant within diamond it becomes a p-type semiconductor, and at high concentrations the diamond becomes quasi-metallic, offering the prospect of a direct electrical device-cell interfacing system.
GritNet: Student Performance Prediction with Deep Learning

Student performance prediction - where a machine forecasts the future performance of students as they interact with online coursework - is a challenging problem. Reliable early-stage predictions of a student's future performance could be critical to facilitate timely educational interventions during a course. However, very few prior studies have explored this problem from a deep learning perspective. In this paper, we recast the student performance prediction problem as a sequential event prediction problem and propose a new deep learning based algorithm, termed GritNet, which builds upon the bidirectional long short term memory (BLSTM). Our results, from real Udacity students' graduation predictions, show that the GritNet not only consistently outperforms the standard logistic-regression based method, but that improvements are substantially pronounced in the first few weeks when accurate predictions are most challenging.
Willis Hippocampus and Entorhinal Complex , Functional Imaging

The hippocampus is comprised of the dentate gyrus and the CA1, CA2 and CA3 pyramidal cell fields. The hippocampal formation consists of the hippocampus and the subiculum. The adjacent entorhinal, perirhinal, and parahippocampal cortices comprise the parahippocampal region (Fig. 1). These limbic subregions differ in their cellular organization and connectivity, but are commonly implicated in memory and emotion processing.
3S – Systematic, Systemic, and Systems Biology and Toxicology

Summary A biological system is more than the sum of its parts – it accomplishes many functions via synergy. Deconstructing the system down to the molecular mechanism level necessitates the complement of reconstructing functions on all levels, i.e., in our conceptualization of biology and its perturbations, our experimental models and computer modelling. Toxicology contains the somewhat arbitrary subclass “systemic toxicities”; however, there is no relevant toxic insult or general disease that is not systemic. At least inflammation and repair are involved that require coordinated signaling mechanisms across the organism. However, the more body components involved, the greater the challenge to recapitulate such toxicities using non-animal models. Here, the shortcomings of current systemic testing and the development of alternative approaches are summarized. We argue that we need a systematic approach to integrating existing knowledge as exemplified by systematic reviews and other evidence-based approaches. Such knowledge can guide us in modelling these systems using bioengineering and virtual computer models, i.e., via systems biology or systems toxicology approaches. Experimental multi-organon-chip and microphysiological systems (MPS) provide a more physiological view of the organism, facilitating more comprehensive coverage of systemic toxicities, i.e., the perturbation on organism level, without using substitute organisms (animals). The next challenge is to establish disease models, i.e., micropathophysiological systems (MPPS), to expand their utility to encompass biomedicine. Combining computational and experimental systems approaches and the challenges of validating them are discussed. The suggested 3S approach promises to leverage 21st century technology and systematic thinking to achieve a paradigm change in studying systemic effects.
Propolin C Inhibited Migration and Invasion via Suppression of EGFR-Mediated Epithelial-to-Mesenchymal Transition in Human Lung Cancer Cells

Controlling lung cancer cell migration and invasion via epithelial-to-mesenchymal transition (EMT) through the regulation of epidermal growth factor receptor (EGFR) signaling pathway has been demonstrated. Searching biological active phytochemicals to repress EGFR-regulated EMT might prevent lung cancer progression. Propolis has been used as folk medicine in many countries and possesses anti-inflammatory, antioxidant, and anticancer activities. In this study, the antimigration and anti-invasion activities of propolin C, a c-prenylflavanone from Taiwanese propolis, were investigated on EGFR-regulated EMT signaling pathway. Cell migration and invasion activities were dose-dependently suppressed by noncytotoxic concentration of propolin C. Downregulations of vimentin and snail as well as upregulation of E-cadherin expressions were through the inhibition of EGFR-mediated phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) and extracellular signal-regulated kinase (ERK) signaling pathway in propolin C-treated cells. In addition, EGF-induced migration and invasion were suppressed by propolin C-treated A549 lung cancer cells. No significant differences in E-cadherin expression were observed in EGF-stimulated cells. Interestingly, EGF-induced expressions of vimentin, snail, and slug were suppressed through the inhibition of PI3K/Akt and ERK signaling pathway in propolin C-treated cells. Inhibition of cell migration and invasion by propolin C was through the inhibition of EGF/EGFR-mediated signaling pathway, followed by EMT suppression in lung cancer.
MAEER: Mobility aware energy efficient routing protocol for Internet of Things

In many IoT applications, Point-to-Point communication (P2P communication) and mobility are fundamental requirements. For such applications, routing protocols must support mobility and discover optimum P2P routes along with the energy-efficiency. The nodes in IoT have limited energy. Fast energy depletion of nodes leads to the creation of energy holes in the network, which hinders the intended services to IoT application. Hence, energy-efficiency is also one of the fundamental objectives of routing protocols. In the literature, many researchers have proposed energy-efficient routing protocols that provide optimum P2P routes. But most of them do not support mobility of nodes in the network. In this paper, Mobility Aware Energy Efficient Routing Protocol (MAEER) for Internet of Things is proposed that supports mobility and discovers nearly optimum routes with reduced energy consumption. The proposed protocol reduces the number of participating nodes in P2P route discovery to decrease the energy consumption. In addition to that, it also offers an efficient approach to provide mobility support with increased packet delivery ratio. The performance of our routing protocol is analyzed with benchmark protocols i.e. RPL, P2P-RPL, along with ME-RPL. The results show that the proposed protocol provides 24% less energy consumption in comparison to P2P-RPL which is best among RPL, P2P-RPL, and ME-RPL, and 15% better packet delivery ratio than ME-RPL which provides best packet delivery ratio among the three.
C:N:P Stoichiometry and Leaf Traits of Halophytes in an Arid Saline Environment, Northwest China

Salinization is an important and increasingly prevalent issue which has broad and profound effects on plant survival and distribution pattern. To understand the patterns and potential drivers of leaf traits in saline environments, we determined the soil properties, leaf morphological traits (specific leaf area, SLA, and leaf dry matter content, LDMC), leaf chemical traits (leaf carbon, C, nitrogen, N, and phosphorus, P, stoichiometry) based on 142 observations collected from 23 sites in an arid saline environment, which is a vulnerable ecosystem in northwest China. We also explored the relationships among leaf traits, the responses of leaf traits, and plant functional groups (herb, woody, and succulent woody) to various saline environments. The arid desert halophytes were characterized by lower leaf C and SLA levels, higher N, but stable P and N:P. The leaf morphological traits were correlated significantly with the C, N, and P contents across all observations, but they differed within each functional group. Succulent woody plants had the lowest leaf C and highest leaf N levels among the three functional groups. The growth of halophytes might be more limited by N rather than P in the study area. GLM analysis demonstrated that the soil available nutrients and plant functional groups, but not salinity, were potential drivers of leaf C:N:P stoichiometry in halophytes, whereas species differences accounted for the largest contributions to leaf morphological variations. Our study provides baseline information to facilitate the management and restoration of arid saline desert ecosystem.