Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of proteins in the biosynthesis and functioning of metallic nanoparticles

Abstract Proteins are known to play important roles in the biosynthesis of metallic nanoparticles (NPs), which are biological substitutes for conventionally used chemical capping and stabilizing agents. When a pristine nanoparticle comes in contact with a biological media or system, a bimolecular layer is formed on the surface of the nanoparticle and is primarily composed of proteins. The role of proteins in the biosynthesis and further uptake, translocation, and bio-recognition of nanoparticles is documented in the literature. But, a complete understanding has not been achieved concerning the mechanism for protein-mediated nanoparticle biosynthesis and the role proteins play in the interaction and recognition of nanoparticles, aiding its uptake and assimilation into the biological system. This review critically evaluates the knowledge and gaps in the protein-mediated biosynthesis of nanoparticles. In particular, we review the role of proteins in multiple facets of metallic nanoparticle biosynthesis, the interaction of proteins with metallic nanoparticles for recognition and interaction with cells, and the toxic potential of protein-nanoparticle complexes when presented to the cell. Graphical Abstract
Click linker: efficient and high yielding synthesis of a new family of kojic acid congeners as cytotoxic agents

Abstract Highly efficient methodology was developed for the construction of functionalized Kojic acid involving Click linker via 1,3-dipolar cycloaddition and their cytotoxicity against MCF-7, MIAPaCa-2 and DU145 mammalian cell lines were evaluated. Preliminary studies on structure-activity-relationship (SAR) revealed that substitution at C-2 of kojic acid as well as C-5 of 1,2,3-triazole motif played a major role in the activity profile. Kojic acid 1,2,3-triazole analogue 3 b containing an alkyl chain (n = 6) exhibited two fold potent activity than the parent compound, kojic acid against MCF-7 and MIA PaCa-2 cell lines. It induced apoptosis in these cell lines via ID1/PARP1 mediated pathway. The structures of the new analogues of kojic acid 1,2,3-triazole were confirmed by the detailed spectroscopic data analysis. Graphical Abstract
Genistein suppresses ox‐LDL‐elicited oxidative stress and senescence in HUVECs through the SIRT1‐p66shc‐Foxo3a pathways

The anti‐senescence function of genistein is related to inhibiting oxidative stress, however, the mechanism has not been clarified. The present study aimed to explore the effects of genistein on oxidized low‐density lipoprotein (ox‐LDL)‐induced endothelial senescence and the role of the sirtuin‐1 (SIRT1)—66‐kDa Src homology 2 domain‐containing protein (p66Shc)–forkhead box protein O3 (Foxo3a) pathways in the process. In this paper, human umbilical vein endothelial cells were pretreated with 1000 nM genistein for 30 min and then incubated with 50 mg/L ox‐LDL for another 12 h; meanwhile, the functions of adenovirus‐mediated overexpression of p66shc and small interfering RNA‐mediated silencing of SIRT1 were investigated. Results showed that genistein pretreatment alleviated ox‐LDL‐induced mitochondrial reactive oxygen species, the levels of oxidatively modified DNA (8‐OHdG) and pai‐1, and the activity of SA‐β‐gal, which was associated with mitigating p66shc. Further studies indicated the inhibitory effect of genistein on p66shc was correlated with suppressing the acetylation and phosphorylation of p66shc, and ameliorating its mitochondrial translocation by activating SIRT1. Moreover, the inactivated p66shc could enhance the activity of Foxo3a via restraining the phosphorylation and triggering nucleus accumulation. The study demonstrates genistein could prevent ox‐LDL‐induced mitochondrial oxidative stress and senescence through the SIRT1–p66shc–Foxo3a pathways.
Therapeutic role of Azadirachta indica leaves ethanolic extract against diabetic nephropathy in rats neonatally induced by streptozotocin

ABSTRACT Diabetic nephropathy (DN) is manifested by chronic loss of renal function due to damage of glomeruli and renal tubules. Therefore, this study is mainly designed to evaluate the therapeutic role of Azadiracta indica (neem) leaves extract as a novel approach for treatment of DN in rats neonatally induced by streptozotocin (STZ). For this study, 40 offspring were selected after parturition and categorized into four groups (n = 10). Group1: control group, group 2: neem leaves extract supplemented group, group 3: diabetic group that injected with a single dose of STZ and group 4: diabetic group treated with neem extract. The results revealed deleterious histological and ultrstructural changes in the renal tissues of diabetic rats. Such changes included atrophied glomeruli, dilated renal cortical tubules and scattered hemorrhage spots, thickening of glomerular basement membrane, expansion of mesangial matrix and pyknotic podocyte. Additionally, the proximal convoluted tubule and distal tubule showed cytoplasmic vacuolation, vacuolated mitochondria, scattered lipid droplets, lost microvilli and disrupted basal lamina and basal infoldings. Moreover, significant decreased levels of serum antioxidants (SOD&CAT) and significant increased levels of serum MDA, urea and creatinine were noticed in diabetic rats. Neem leaves extract successfully alleviated the histological and ultrastructural as well as biochemical changes induced by diabetes.
Quantitative analysis of the intra-beam respiratory motion with baseline drift for respiratory-gating lung stereotactic body radiation therapy

Abstract This study aimed to quantitatively clarify the baseline drift for each respiratory cycle in two respiratory-gating methods using the intra-beam respiratory motion data of lung cancer patients. The residual motion and dose distribution were calculated based on intra-beam respiratory motion data with the baseline drift. To quantify the baseline drift \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\Delta$\end{document} during irradiation, it was defined as the inclination between the detected expiration point and the expiration point in the next cycle in the anterior–posterior (AP), cranial–caudal (CC) and left–right (LR) directions obtained using an in-house programme. The baseline drift value reached up to 0.74 mm/s in the CC direction as per the respiratory motion data of 10 patients. The homogeneity index (HI) of the phase-gating method tended to increase because the target was irradiated even when the amplitude position of the target differed from period to period. In contrast, the amplitude-gating method enabled irradiation considering the amplitude position of the target because the gating window was set considering the amplitude position of the respiratory motion. The respiratory-gating methods and respiratory phase in respiratory-gating lung stereotactic body radiation therapy (SBRT) must be determined based on the respiratory motion of the patients.
Efficient induction and sustenance of pluripotent stem cells from bovine somatic cells

ABSTRACT Although derivation of naïve bovine embryonic stem cells is unachieved, the possibility for generation of bovine induced pluripotent stem cells (biPSCs) has been generally reported. However, attempts to sustain biPSCs by promoting self-renewal have not been successful. Methods established for maintaining murine and human induced pluripotent stem cells (iPSCs) do not support self-renewal of iPSCs for any bovid species. In this study, we examined methods to enhance complete reprogramming and concurrently investigated signaling relevant to pluripotency of the bovine blastocyst inner cell mass (ICM). First, we identified that forced expression of SV40 large T antigen together with the reprogramming genes (OCT4, SOX2, KLF4 and MYC) substantially enhanced the reprogramming efficacy of bovine fibroblasts to biPSCs. Second, we uncovered that TGFβ signaling is actively perturbed in the ICM. Inhibition of ALK4/5/7 to block TGFβ/activin/nodal signaling together with GSK3β and MEK1/2 supported robust in vitro self-renewal of naïve biPSCs with unvarying colony morphology, steady expansion, expected pluripotency gene expression and committed differentiation plasticity. Core similarities between biPSCs and stem cells of the 16-cell-stage bovine embryo indicated a stable ground state of pluripotency; this allowed us to reliably gain predictive understanding of signaling in bovine pluripotency using systems biology approaches. Beyond defining a high-fidelity platform for advancing biPSC-based biotechnologies that have not been previously practicable, these findings also represent a significant step towards understanding corollaries and divergent aspects of bovine pluripotency. This article has an associated First Person interview with the joint first authors of the paper.
Application of LoRa and NB-IoT in Ubiquitous Power Internet of Things: A Case Study of Fault Indicator in Electricity Distribution Network

Traditional communication technologies based on 2G and 4G cannot meet the requirements of low-power wide-area data transmission in electricity distribution network. Ubiquitous power Internet of things (UPIoT) has thus been proposed by the State Grid of China and it can be used to transmit energy information requested from any location. Narrowband Internet of things (NB-IoT) and LoRa are two promising low-power wide-area communication technologies, which are capable of providing good performance to transmit data collected from the devices installed in the distribution network. In this paper, taking the fault indicator as an example, we combine LoRa and NB-IoT to construct a wireless network to transmit the operation status of fault indicator, which can improve the transmission distance and reduce the operating cost of the system. It adopts a communication mode including a master node and a plurality of child nodes to meet the needs of large-scale information monitoring. Among them, the design of the master node uses NB-IoT and LoRa communication technologies. The design of the child node uses LoRa communication technology and sensor technology. The control chip STM32F103C8T6 is used for data transmission, and the data is finally managed by a centralized means through upper computer software.
'Just keep taking them, keep hoping they'll work': A qualitative study of adhering to medications for multimorbidity.

OBJECTIVE Compared to single diseases, health psychology reflects many areas of medical research by affording relatively less attention to the experiences of people self-managing multiple co-occurring conditions and, in particular, the experience of managing the associated complex medication regimens. This study aimed to explore the experience of self-managing multimorbidity among older adults, with a focus on medication adherence. DESIGN A qualitative approach was taken, using individual semi-structured interviews. METHODS Sixteen people with complex multimorbidity aged 65 years or older were recruited through general practice to take part in semi-structured interviews. Data were analysed following guidelines for reflexive thematic analysis. RESULTS Two themes were generated, with each theme comprising three subthemes. Theme one represents the amplified burden arising from multimorbidity that leads to unique challenges for self-management, such as integrating multiple medications into daily life, accumulating new symptoms and treatments, and managing evolving medication regimens. Theme two represents pathways towards relief that reduce this burden and promote medication adherence, such as prioritising certain conditions and treatments, resigning to the need for multiple medications, and identifying and utilising adherence supports. CONCLUSIONS We identified factors relevant to medication adherence for older adults with multimorbidity that go beyond single-disease influences and account for the amplified experience of chronic disease that multimorbidity can produce for some people. While evidence of single-disease influences remains fundamental to tailoring behavioural interventions to individuals, the impact of multimorbidity on medication adherence should be accounted for in research and practice.
The MHC-characterized Miniature Swine: Lessons Learned From a 40-Year Experience in Transplantation

Over the last 40 y, a specialized herd of miniature swine has been intentionally bred to develop lines of animals homozygous for the swine major histocompatibility complex (MHC), which have facilitated transplantation studies across reproducible MHC and minor antigen mismatch barriers. These MHC-characterized miniature swine (Mc-MS) have been used for the study of novel surgical techniques, various approaches to tolerance induction of solid organ and vascularized composite allografts, as well as studies of the immunobiology of allografts and xenografts. Mc-MS possess characteristics that are highly advantageous to these studies, and their continued use will likely continue to play an important role in bridging “bench-to-cage-to bedside” therapies in the field of transplantation. In this review, we highlight the seminal contributions of the Mc-MS model to the field and analyze their role in the broader context of large animal models in transplantation research.
fMBN-E: Efficient Unsupervised Network Structure Ensemble and Selection for Clustering

It is known that unsupervised nonlinear dimensionality reduction and clustering is sensitive to the selection of hyperparameters, particularly for deep learning based methods, which hinders its practical use. How to select a proper network structure that may be dramatically different in different applications is a hard issue for deep models, given little prior knowledge of data. In this paper, we aim to automatically determine the optimal network structure of a deep model, named multilayer bootstrap networks (MBN), via simple ensemble learning and selection techniques. Specifically, we first propose an MBN ensemble (MBN-E) algorithm which concatenates the sparse outputs of a set of MBN base models with different network structures into a new representation. Then, we take the new representation produced by MBN-E as a reference for selecting the optimal MBN base models. Moreover, we propose a fast version of MBN-E (fMBN-E), which is not only theoretically even faster than a single standard MBN but also does not increase the estimation error of MBN-E. Importantly, MBN-E and its ensemble selection techniques maintain the simple formulation of MBN that is based on one-nearest-neighbor learning. Empirically, comparing to a number of advanced deep clustering methods and as many as 20 representative unsupervised ensemble learning and selection methods, the proposed methods reach the state-of-the-art performance without manual hyperparameter tuning. fMBN-E is empirically even hundreds of times faster than MBN-E without suffering performance degradation. The applications to image segmentation and graph data mining further demonstrate the advantage of the proposed methods.
Error analysis of received signal strength-based visible-light positioning using dilution of precision

Abstract. An analytical method to investigate the characteristics of the visible-light positioning using received signal strength (RSS) is proposed, and the formation mechanism of the positioning error is explored. The positioning error is studied in terms of two contributing factors being the original measurement noise of RSS and the dilution of precision (DOP), which transforms the measurement error to the positioning error. It is found that the DOP is related to light-emitting diode (LED) parameters, receiver parameters, and the geometric deployment of the LED beacons. In particular, the LED beacon geometric deployment in the form of triangle, square, and hexagon cell geometries are characterized and optimized. Numerical results show that the mean positioning error of the triangle deployment is smaller than the other two geometries under the same condition, and the side length of the cell should reduce as the half power angle of the LED decreases. The results of this paper provide a guideline to design the RSS-based visible-light positioning (VLP) systems.
The shape of view: an alert system for video viewership anomalies

Internet video providers rely on alerting workflows to identify and remedy incidents that can impact users (e.g., outages or buggy players). There is growing evidence for the need for viewership-based analytics---detecting and diagnosing incidents that manifest through changes in viewership patterns but not in other (e.g., QoE) metrics. However, both detection and diagnosis of viewership anomalies is challenging due to the contextual nature of anomalies, non-stationarity of viewership, and complex dependencies between the structure of events and how they impact different subpopulations of viewers. We present Proteas, an alerting framework for video viewership anomalies that tackles these challenges. Proteas builds on key spatiotemporal structural insights. First, across different sub-populations of viewers and days of the week, we find that the shape of the viewership curve remains invariant over multiple weeks, thus enabling anomaly detection. Second, we use the hierarchy of viewership groups to produce compact alerts. Finally, we find that common anomalies manifest with spatiotemporal signatures, which enables us to classify anomalies to produce actionable alerts. We evaluate Proteas using 3 months of real viewership data (including the onset of the COVID-19 pandemic) and show that Proteas is accurate with over 80% True Positive Rate, average precision of over 86% (i.e., few false positives) and doesn't miss any major events. In addition, we find that approximately half of Proteas's alerts refer to events not caught by other alerting workflows, thus adding value to operators' existing toolkit.
HLISA: towards a more reliable measurement tool

Automated browsers (web bots) are an invaluable tool for studying the web. However, research has shown that web bots can be distinguished from regular browsers and that they may be served different content as a consequence. This undermines their utility as a measurement tool. So far, three methods have been used to detect web bots: browser fingerprint, order of site traversal, and aspects of page interaction. While site traversal depends on the study being executed, the other two aspects can be controlled in a generic fashion. Whereas identifiability of web bot fingerprints has been studied in the past, how to alter the fingerprint has received less attention. In this paper, we study which method to alter the fingerprint incurs the least side effects. Secondly, we provide an initial investigation of how the interaction API of Selenium differs from human interaction. We incorporate the latter results into HLISA, an API that simulates interaction like humans. Finally, we discuss the conceptual arms race between simulators and detectors and find that conceptually, detecting HLISA requires modelling human interaction.
Measuring the network performance of Google cloud platform

Public cloud platforms are vital in supporting online applications for remote learning and telecommuting during the COVID-19 pandemic. The network performance between cloud regions and access networks directly impacts application performance and users' quality of experience (QoE). However, the location and network connectivity of vantage points often limits the visibility of edge-based measurement platforms (e.g., RIPE Atlas). We designed and implemented the CLoud-based Applications Speed Platform (CLASP) to measure performance to various networks from virtual machines in cloud regions with speed test servers that have been widely deployed on the Internet. In our five-month longitudinal measurements in Google Cloud Platform (GCP), we found that 30-70% of ISPs we measured showed severe throughput degradation from the peak throughput of the day.
Simulation and analysis of heat dissipation performance of power battery based on phase change material enhanced heat transfer variable fin structure

Abstract The further development of battery thermal management phase change material (PCM) cooling technology is limited by the low thermal conductivity of a single PCM. In order to enhance the performance of thermal conductivity of phase change materials and improve the heat dissipation capacity of power battery, the fin with high thermal conductivity is used as a style of enhance heat transfer to phase change materials. The computational fluid dynamics (CFD) method is used to study the effect of parameters, such as shape, number and material of high thermal conductivity fins added in PCM as well as the air convection coefficient of shell on the heat dissipation performance of lithium ion power battery. The results show that the maximum temperature of the battery decreases the most, which is 5.57 K, when the oblique-oblique fins are added, compared with the fin without enhanced heat transfer in PCM. In the limited available space, the decrease rate of the maximum temperature of the battery does not increase with the increase of the number of oblique-oblique fins. When four oblique-oblique fins are added, the rate of decrease in the maximum temperature of the battery is the maximum, which is 0.47%. According to the thermal physical properties of each fin material and the simulation results, aluminum is the best choice for fin material. As for the convection coefficient of the air, the greater the value, the better the heat dissipation effect of the battery is.
Building destination resilience to multiple crises to secure tourism’s future

ABSTRACT The devastating impacts of recent Australian bushfires and the COVID-19 pandemic have highlighted the immediacy of climate change impacts and accelerated social, economic and environmental change which will shape the future of tourism. Moving away from single foci approaches to tourism risk management, this paper examines the vulnerability and resilience factors of tourism destinations to multiple crises. Using a whole system destination vulnerability/resilience assessment, two case studies inform priorities for building future resilience to multiple crises at organisational and destination levels. Based on critical reflection, a simplified, multi-level destination resilience framework for interdisciplinary tourism researchers and managers is proposed.
Silicon dioxide dispersion

Stable, aqueous dispersion containing silicon dioxide powder having a hydroxyl group density of 2.5 to 4.7 OH/nm² which is obtained from a silicon dioxide powder produced by a flame hydrolysis process under acid conditions. The dispersion is produced by incorporating the silicon dioxide powder into an aqueous solution by means of a dispersing device. The dispersion can be used to produce glass articles.