Miracle-dz/UniFAR-FTUs huggingface dataset:
Rapid growth of onion-like carbon nanospheres in a microwave oven

Onion-like carbon spheres (OLCSs) were synthesized by heating a mixture of naphthalene and graphite powder inside a kitchen microwave oven for ∼1 min under atmospheric conditions. Naphthalene, a hydrocarbon, provides carbon for growth, while graphite plays the crucial role of microwave absorber. The size of the OLCS particles was distributed over a wide range from a few 10s of nm up to a few μm. The OLCS particles self-assembled in a long range chain-like structure. The duration of microwave heating and the ratio of the precursor components were found to be important factors affecting the size and density of the particles. Alternative hydrocarbon sources and microwave absorbers were also examined for OLCS growth. Addition of ferrocene as a catalyst to the precursor mixture of naphthalene and graphite resulted in the formation of highly crystalline carbon-encapsulated iron (in the form of oxide/carbide) nanoparticles with a core–shell structure. The as-synthesized OLCS mixture containing graphite as the precursor was mixed with poly-alpha olefin oil (PAO4) as an additive. A significantly lower friction coefficient and wear rate were obtained with this mixture as compared to the neat PAO4 and PAO4+graphite mixture. Microwave heating was also employed to coat thin films of OLCSs on alumina/glass substrates. The conductivity of these films was measured using the four probe method. The microwave-assisted method used to produce OLCSs has several advantages like cost and energy efficiency, minimal preprocessing, etc. This technique can be of industrial importance for bulk productions of OLCSs and graphitic shell-encapsulated metal nanoparticles.
[The roles of two HIV self-testing models in promoting HIV-testing among men who have sex with men].

Objective: To evaluate the roles between two different HIV self-testing models in promoting HIV-testing among men who have sex with men (MSM). Methods: This paper focuses on two HIV self-testing service models. The first; is the online self-testing model (HIV self-testing conventional model) with the sexual health promotion network platform. The other one is an innovative HIV self-testing model (secondary distribution model), based on the previous program. The two different self-testing models, including the number of indexes and alters, the positive rate, and the demographics of indexes and alters, are compared. The influence of volunteers with or without leadership on the number of HIV self-test kits distributed or self-use is analyzed through the leadership survey scale. Results: The return rates of HIV self-testing results in the two models are 94.7%(323/341) and 99.2%(1 141/1 150), respectively, within 30 days. The proportion of alters in the secondary distribution is significantly higher (45.9%,281/612) than the conventional HIV self-testing (6.3%,20/318). In the secondary distribution model, the difference between the number of indexes and alters indicators including age, marital status, residence, sex orientation, anal sex with men in the past six months, and HIV test are statistically significant (χ2 test, all P<0.05). The opinion leader of MSM has significantly impacted the promotion of HIV self-testing (P<0.05). Conclusions: Both models can promote HIV self-testing, result return, and HIV positive detection among MSM. In terms of expanding the testing and detection of HIV positive, the secondary distribution mode shows more obvious advantages, which significantly promotes a large number of MSM who have never been tested for HIV to undergo HIV testing. Influential indexes have a significant effect on increasing the HIV testing rate and promoting HIV testing among MSM.
Single-Cell Transcriptomic Atlas of Different Human Cardiac Arteries Identifies Cell Types Associated With Vascular Physiology

Supplemental Digital Content is available in the text. Objective: Although cellular heterogeneity within arterial walls has been explored in mice and nonhuman primates, the cellular composition of human arterial walls remains unclear. Approach and Results: The cellular composition of nondiseased cardiac arteries (3 aortas, 2 pulmonary arteries and 9 coronary arteries) from 3 heart transplantation patients were investigated by single-cell sequencing of >105 cells. Clustering analysis identified 25 subpopulations representing the 10 main arterial cell types: vascular smooth muscle cell (4 clusters), fibroblast (4 clusters), macrophage (Mφ, 4 clusters), T cell (4 clusters), endothelial cell (4 clusters), NK cell (2 clusters), mast cell (1 cluster), myofibroblast (1 cluster), oligodendrocyte (1 cluster), and B/plasma cells (1 cluster). Vascular smooth muscle cell was the largest cell population in cardiac arteries, followed by fibroblast, Mφ, T cell, endothelial cell, NK cell, and so on. We compared cellular composition among different arteries and found some artery-specific vascular smooth muscle cell and fibroblast subpopulations. The communication between vascular smooth muscle cell and fibroblast was predominant in nondiseased condition. Atherosclerosis-associated genes were particularly enriched in endothelial cell and Mφ, and intercellular communication between endothelial cell and immune cells was predicted to increase in atherosclerosis. The interaction between ICAM1/VCAM1 (EC1) and ITGB2 (immune cells, especially inflammatory Mφ) was speculated to be essential for the pathogenesis of atherosclerosis. Conclusions: We created a cell atlas of human nondiseased cardiac arteries, and characterized the cellular compositions in different cardiac arteries. Our results could be used as a reference to identify vascular disease-associated cell populations and help investigate new therapeutic strategies for vascular diseases.
Synthesis of Thermoresponsive Shell Cross-Linked Micelles via Living Cationic Polymerization and UV Irradiation

A series of well-defined thermoresponsive poly(2-ethoxyethyl vinyl ether)-block-poly(2-hydroxyethyl vinyl ether) (PEOVE-b-PHOVE) block copolymers have been synthesized via sequential living cationic polymerization, containing methacryloyl groups derived from 2-(vinyloxy)ethyl methacrylate (VEM) in the PHOVE segment, PEOVE-b-P(HOVE/VEM). The ratio of EOVE/HOVE in the block copolymers was fixed at 1:2. The obtained PEOVE-b-P(HOVE/VEM) dissolved molecularly in aqueous solution, when below the lower critical solution temperature (LCST) of PEOVE. Upon heating above LCST of PEOVE, spherical micellization occurred, comprising of PEOVE cores and PHOVE shells. This was confirmed by dynamic light scattering (DLS) and 1H NMR spectroscopy at various temperatures. The methacryloyl groups in the block copolymer are located around the surface of the PHOVE shells as a random copolymer of HOVE and VEM. The micelles were cross-linked by UV (254 nm) irradiation in water to obtain shell cross-linked (SCL) micelles. The SCL m.
Measurement and comparison of potentiometric selectivity coefficients of urea biosensors based on ammonium ion-selective electrodes

This study analyzes the selectivity of a potentiometric urea biosensor prepared by immobilizing of urease directly onto the surface of an ammonium ion-selective electrode. In this investigation, using the entrapment method, the urease enzyme was immobilized onto the carboxylated polyvinylchloride (PVC-COOH) membrane surface of an ion-selective electrode containing nonactin as an ionophore and a tin oxide (SnO/sub 2/) thin film. To describe the characteristics of the selectivity of urea biosensors based on ammonium ion-selective electrodes, the determinations of potentiometric selectivity coefficients (K/sup pot//sub i,j/) of the urea biosensor in different univalent interfering ions were presented in a sample solution of pH 7.5. Using the separate solution method and fixed interference method (FIM) for determining selectivity coefficients, this investigation considers and discusses the influence of the urea biosensors preference on the primary ions relative to interfering ions of the same charge number. The observation results indicate that FIM is the proper method for calculating the selectivity coefficients of the ammonium ISE-based urea biosensors.
Multi-Modal Retinal Image Classification With Modality-Specific Attention Network

Recently, automatic diagnostic approaches have been widely used to classify ocular diseases. Most of these approaches are based on a single imaging modality (e.g., fundus photography or optical coherence tomography (OCT)), which usually only reflect the oculopathy to a certain extent, and neglect the modality-specific information among different imaging modalities. This paper proposes a novel modality-specific attention network (MSAN) for multi-modal retinal image classification, which can effectively utilize the modality-specific diagnostic features from fundus and OCT images. The MSAN comprises two attention modules to extract the modality-specific features from fundus and OCT images, respectively. Specifically, for the fundus image, ophthalmologists need to observe local and global pathologies at multiple scales (e.g., from microaneurysms at the micrometer level, optic disc at millimeter level to blood vessels through the whole eye). Therefore, we propose a multi-scale attention module to extract both the local and global features from fundus images. Moreover, large background regions exist in the OCT image, which is meaningless for diagnosis. Thus, a region-guided attention module is proposed to encode the retinal layer-related features and ignore the background in OCT images. Finally, we fuse the modality-specific features to form a multi-modal feature and train the multi-modal retinal image classification network. The fusion of modality-specific features allows the model to combine the advantages of fundus and OCT modality for a more accurate diagnosis. Experimental results on a clinically acquired multi-modal retinal image (fundus and OCT) dataset demonstrate that our MSAN outperforms other well-known single-modal and multi-modal retinal image classification methods.
Maladaptive brain organization at 1 month into abstinence as an indicator for future relapse in patients with alcohol use disorder

Abstinence is a lifelong endeavor, and the risk of a relapse is always present for patients with Alcohol Use Disorder (AUD). The aim of the study was to better understand specific characteristics of the intrinsic whole‐brain‐network architecture of 34 AUD patients that may support abstinence or relapse. We used Graph Theory Analysis (GTA) of resting‐state fMRI data from treatment seekers at 1 month of abstinence and their follow‐up data as abstainers or relapsers 3 months later, together with data from 30 light/non‐drinking controls scanned at the same interval. We determined the group‐specific intrinsic community configurations at both timepoints as well as the corresponding modularity Q, a GTA measure that quantifies how well individual network communities are separated from each other. Both AUD groups at both timepoints had community configurations significantly different from those of controls, but the three groups did not significantly differ in their Q values. However, relapsers showed a maladaptive community configuration at baseline, which became more similar to the controls’ community organization after the relapsers had started consuming alcohol again during the study interval. Additionally, successful recovery from AUD was not associated with re‐gaining the intrinsic brain organization found in light/non‐drinkers, but with a re‐configuration resulting in a new brain organization distinctly different from that of healthy controls. Resting‐state fMRI provides useful measures reflecting neuroplastic adaptations related to AUD treatment outcome.
Recovering is about living my life, as it evolves: perspectives of stroke survivors in remote northwest Queensland

Abstract Purpose Recovering from stroke in remote Australia has rarely been considered, even though rehabilitation services are generally scarce. The primary purpose of this study was to explore stroke recovery, from the perspective of stroke survivors in remote northwest Queensland (NWQ), to explicate the lens through which they view recovering. The secondary purpose was to explore the role of technology to support stroke survivors in remote locations along their recovery journey. Methods A qualitative study was undertaken using elements of constructivist grounded theory for data collection and analysis. Semi-structured interviews were conducted with fifteen stroke survivors and two partners living, working or travelling in remote NWQ. Results From the participants’ perspective, recovering in a remote area after stroke is about living my life, as it evolves by endeavouring to recover my way and navigating my recovery in my world. Technology was only considered helpful when it supported participants to recover their way in their world. Conclusion Recovering from stroke from the perspective of stroke survivors in remote NWQ is about living their life, as they want it to be, and as it unfolds within their own context. Technology only has a place when it can support them to recover their way in their world. These findings reinforce the importance of health professionals listening, learning about, and enabling stroke survivors along their recovery journey, within their remote context and support network. Implications for Rehabilitation Recovering from the perspective of stroke survivors is about living their life as it evolves. To support stroke survivors from remote areas, health professionals need to listen to and learn from each stroke survivor about what matters to them, what works for them, and about their world; including the challenges (e.g., switching between services) and enablers (e.g., community support) as the stroke survivor perceives them. Finding ways to utilise the strengths within and around them, may improve the recovery process for the stroke survivor in a remote area, ensuring they can access care that meets their needs in their world. Working together with stroke survivors, health professionals need to consider how technology could help them to live their life, while recovering their way and in their world.
A Study of Hygiene in Swedish Schools and Pre-Schools-Sources of Air Pollution

Poor indoor air quality is a large problem in Swedish schools, since the health of occupants may be affected. The building itself is often in focus and other building-related problems may be neglected. The hypothesis of this study is that factors other than the building itself have decisive influence on indoor environment. An assessment of these nonspecific building-related reasons for bad indoor environment has been made in the present work using surveys combined with particle measurements and comfort measurements (air humidity and air temperature). People are experiencing poor indoor air quality, the air is too dry and the temperature is uneven and uncomfortable indoors in the winter. It is important to highlight the problem of indoor environments with high particulate emissions especially in the range from 5.0 microns and larger since they are conveyers of allergens and bacteria, combined with dry air. An interesting observation regarding the ventilation system is that mechanical systems are tending to generate drier indoor air than the natural ventilation system. Results show that it is possible to decrease emissions through eliminating activity-related sources of airborne contaminants and better the comfort indoors with relatively simple measures.
Extrapolating Parametric Survival Models in Health Technology Assessment Using Model Averaging: A Simulation Study

Previous work examined the suitability of relying on routine methods of model selection when extrapolating survival data in a health technology appraisal setting. Here we explore solutions to improve reliability of restricted mean survival time (RMST) estimates from trial data by assessing model plausibility and implementing model averaging. We compare our previous methods of selecting a model for extrapolation using the Akaike information criterion (AIC) and Bayesian information criterion (BIC). Our methods of model averaging include using equal weighting across models falling within established threshold ranges for AIC and BIC and using BIC-based weighted averages. We apply our plausibility assessment and implement model averaging to the output of our previous simulations, where 10,000 runs of 12 trial-based scenarios were examined. We demonstrate that removing implausible models from consideration reduces the mean squared error associated with the restricted mean survival time (RMST) estimate from each selection method and increases the percentage of RMST estimates that were within 10% of the RMST from the parameters of the sampling distribution. The methods of averaging were superior to selecting a single optimal extrapolation, aside from some of the exponential scenarios where BIC already selected the exponential model. The averaging methods with wide criterion-based thresholds outperformed BIC-weighted averaging in the majority of scenarios. We conclude that model averaging approaches should feature more widely in the appraisal of health technologies where extrapolation is influential and considerable uncertainty is present. Where data demonstrate complicated underlying hazard rates, funders should account for the additional uncertainty associated with these extrapolations in their decision making. Extended follow-up from trials should be encouraged and used to review prices of therapies to ensure a fair price is paid.
Molecular and Structural Insights into the Life Cycle of Rubella Virus

Rubella virus (RUBV), a rubivirus, is an airborne human pathogen that generally causes mild measles-like symptoms in children or adults. However, RUBV infection of pregnant women can result in miscarriage or congenital rubella syndrome (CRS), a collection of long-term birth defects, including incomplete organ development and mental retardation. ABSTRACT Rubella virus (RUBV), a rubivirus, is an airborne human pathogen that generally causes mild measles-like symptoms in children or adults. However, RUBV infection of pregnant women can result in miscarriage or congenital rubella syndrome (CRS), a collection of long-term birth defects, including incomplete organ development and mental retardation. Worldwide vaccination campaigns have significantly reduced the number of RUBV infections, but RUBV continues to be a problem in countries with low vaccination coverage. Furthermore, the recent discovery of pathogenic rubiviruses in other mammals emphasizes the spillover potential of rubella-related viruses to humans. In the last decade, our understanding of RUBV has been significantly increased by virological, biochemical, and structural studies, providing a platform to begin understanding the life cycle of RUBV at the molecular level. This review concentrates on recent work on RUBV, focusing on the virion; its structural components; and its entry, fusion, and assembly mechanisms. Important features of RUBV are compared with those of viruses from other families. We also use comparative genomics, manual curation, and protein homology modeling to highlight distinct features of RUBV that are evolutionarily conserved in the nonhuman rubiviruses. Since rubella-like viruses may potentially have higher pathogenicity and transmissibility to humans, we also propose a framework for utilizing RUBV as a model to study its more pathogenic cousins.
RIPK3 Activates MLKL-Mediated Necroptosis and Inflammasome Signaling during Streptococcus Infection.

Community-acquired pneumonia is the most common type of pneumonia and remains a leading cause of morbidity and mortality worldwide. Although many different pathogens can contribute to pneumonia, Streptococcus pneumoniae (S. pneumoniae) is one of the common bacterial pathogens that underlie community-acquired pneumonia [1]. Receptor-interacting protein kinase 3 (RIPK3) is widely recognized as a key modulator of inflammation and cell death. To elucidate a potential role of RIPK3 in pneumonia, we examined plasma from healthy controls and patients positive with streptococcal pneumonia. In human studies, RIPK3 protein levels were significantly elevated and were identified as a potential plasma marker of pneumococcal pneumonia. To expand these findings, we used an in vivo murine model of pneumococcal pneumonia to demonstrate that RIPK3 deficiency leads to reduced bacterial clearance, severe pathological damage and high mortality. Our results illustrated that RIPK3 forms a complex with RIPK1, MLKL and MCU to induce mitochondrial calcium uptake and mitochondrial ROS (mROS) production during S. pneumoniae infection. In macrophages, RIPK3 initiated necroptosis via mROS-mediated mitochondrial permeability transition pore (mPTP) opening and NLRP3 inflammasome activation via mROS-AKT pathway to protect against S. pneumoniae. In conclusion, our study demonstrated a mechanism by which RIPK3 initiated necroptosis is essential for host defense against S. pneumoniae.
Population genetics and genome‐wide association studies provide insights into the influence of selective breeding on genetic variation in lettuce

Genetic diversity is an important resource in crop breeding to improve cultivars with desirable traits. Selective breeding can lead to a reduction of genetic diversity. However, our understanding on this subject remains limited in lettuce (Lactuca sativa L.). Genotyping‐by‐sequencing (GBS) can provide a reduced version of the genome as a cost‐effective method to identify genetic variants across the genome. We genotyped a diverse set of 441 lettuce accessions using the GBS method. Phylogenetic and population genetic analyses indicated substantial genetic divergence among four horticultural types of lettuce: butterhead, crisphead, leaf, and romaine. Genetic‐diversity estimates between and within the four types indicated that the crisphead type was the most differentiated from other types, whereas its population was the most homogenous with the slowest linkage disequilibrium (LD) decay among the four types. These results suggested that crisphead lettuces had relatively less genetic variation across the genome as well as low gene flow from other types. We identified putative selective sweep regions that showed low genetic variation in the crisphead type. Genome‐wide association study (GWAS) and quantitative trait loci (QTL) analyses provided evidence that these genomic regions were, in part, associated with delayed bolting, implicating the positive selection of delayed bolting in reducing variation. Our findings enhance the current understanding of genetic diversity and the impacts of selective breeding on patterning genetic variation in lettuce.