Miracle-dz/UniFAR-FTUs huggingface dataset:
Tumor Necrosis Factor-Mediated Survival of CD169+ Cells Promotes Immune Activation during Vesicular Stomatitis Virus Infection

ABSTRACT Innate immune activation is essential to mount an effective antiviral response and to prime adaptive immunity. Although a crucial role of CD169+ cells during vesicular stomatitis virus (VSV) infections is increasingly recognized, factors regulating CD169+ cells during viral infections remain unclear. Here, we show that tumor necrosis factor is produced by CD11b+ Ly6C+ Ly6G+ cells following infection with VSV. The absence of TNF or TNF receptor 1 (TNFR1) resulted in reduced numbers of CD169+ cells and in reduced type I interferon (IFN-I) production during VSV infection, with a severe disease outcome. Specifically, TNF triggered RelA translocation into the nuclei of CD169+ cells; this translocation was inhibited when the paracaspase MALT-1 was absent. Consequently, MALT1 deficiency resulted in reduced VSV replication, defective innate immune activation, and development of severe disease. These findings indicate that TNF mediates the maintenance of CD169+ cells and innate and adaptive immune activation during VSV infection. IMPORTANCE Over the last decade, strategically placed CD169+ metallophilic macrophages in the marginal zone of the murine spleen and lymph nodes (LN) have been shown to play a very important role in host defense against viral pathogens. CD169+ macrophages have been shown to activate innate and adaptive immunity via “enforced virus replication,” a controlled amplification of virus particles. However, the factors regulating the CD169+ macrophages remain to be studied. In this paper, we show that after vesicular stomatitis virus infection, phagocytes produce tumor necrosis factor (TNF), which signals via TNFR1, and promote enforced virus replication in CD169+ macrophages. Consequently, lack of TNF or TNFR1 resulted in defective immune activation and VSV clearance.
Effects of TiO2 and Co3O4 Nanoparticles on Cell Cycle of a Pulmonary Cell Line (A549)

1Department of Medicine and Surgery, University of Parma, via Gramsci 14 43126 Parma, Italy 2Italian Workers' Compensation Authority (INAIL) Research Center at the University of Parma, via Gramsci 14 43126 Parma, Italy 3 Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 17/A 43124 Parma, Italy 4Italian Workers’ Compensation Authority (INAIL), Research Area, Department of Occupational Hygiene, via Fontana Candida, 1, 00040 Monte Porzio Catone Roma Italy
Differential Experimental Effects of a Short Bout of Walking, Meditation, or Combination of Walking and Meditation on State Anxiety Among Young Adults

Introduction: Single bouts of aerobic exercise and meditation have been shown to improve anxiety states. Yet to be evaluated in the literature, we sought to examine the effects of a single, short bout of aerobic exercise or meditation, as well as exercise and meditation combined on state anxiety among young adults. Design: Randomized controlled trial. Setting: University. Subjects: Participants (N = 110, mean age = 21.4 years) were randomly assigned to walk, meditate, walk then meditate, meditate then walk, or to sit (inactive control). Measures: All walking and meditation bouts were 10 minutes in duration. Participants’ state anxiety was monitored before and after the intervention using the State Trait Anxiety Inventory questionnaire. Results: Significant group × time interaction effects were observed (P = .01). Post hoc paired t tests revealed that state anxiety significantly decreased from baseline to postintervention in the meditation (P = .002), meditation then walk (P = .002), and walk then meditation (P = .03) groups but not the walk (P = .75) or control (P = .45) groups. Conclusion: Meditation (vs a brisk walk) may be a preferred method of attenuating anxiety symptomology. Individuals desiring the health benefits associated with aerobic exercise may achieve additional anxiolytic benefits if they employ a brief meditation session before or after exercising.
Pre-simulation preparation and briefing practices for healthcare professionals and students: a systematic review protocol.

REVIEW QUESTION/OBJECTIVE The objective of this review is to systematically examine the use and effectiveness of pre-simulation preparation and briefing practices for healthcare professionals and students. More specifically, the objectives are to identify characteristics/activities of pre-simulation preparation and briefing and their effects on knowledge, attitudes, self-confidence, self-efficacy, anxiety and skill performance in healthcare professionals and students.The review question is: What are the characteristics/activities of effective pre-simulation preparation and briefing?
The NAIMS cooperative pilot project: Design, implementation and future directions

The North American Imaging in Multiple Sclerosis (NAIMS) Cooperative represents a network of 27 academic centers focused on accelerating the pace of magnetic resonance imaging (MRI) research in multiple sclerosis (MS) through idea exchange and collaboration. Recently, NAIMS completed its first project evaluating the feasibility of implementation and reproducibility of quantitative MRI measures derived from scanning a single MS patient using a high-resolution 3T protocol at seven sites. The results showed the feasibility of utilizing advanced quantitative MRI measures in multicenter studies and demonstrated the importance of careful standardization of scanning protocols, central image processing, and strategies to account for inter-site variability.
Ego involvement increases doping likelihood

ABSTRACT Achievement goal theory provides a framework to help understand how individuals behave in achievement contexts, such as sport. Evidence concerning the role of motivation in the decision to use banned performance enhancing substances (i.e., doping) is equivocal on this issue. The extant literature shows that dispositional goal orientation has been weakly and inconsistently associated with doping intention and use. It is possible that goal involvement, which describes the situational motivational state, is a stronger determinant of doping intention. Accordingly, the current study used an experimental design to examine the effects of goal involvement, manipulated using direct instructions and reflective writing, on doping likelihood in hypothetical situations in college athletes. The ego-involving goal increased doping likelihood compared to no goal and a task-involving goal. The present findings provide the first evidence that ego involvement can sway the decision to use doping to improve athletic performance.
Physiotherapy Post Lumbar Discectomy: Prospective Feasibility and Pilot Randomised Controlled Trial

Objectives To evaluate: acceptability and feasibility of trial procedures; distribution of scores on the Roland Morris Disability Questionnaire (RMDQ, planned primary outcome); and efficient working of trial components. Design and Setting A feasibility and external pilot randomised controlled trial (ISRCTN33808269, assigned 10/12/2012) was conducted across 2 UK secondary care outpatient physiotherapy departments associated with regional spinal surgery centres. Participants Consecutive consenting patients aged >18 years; post primary, single level, lumbar discectomy. Interventions Participants were randomised to either 1:1 physiotherapy outpatient management including patient leaflet, or patient leaflet alone. Main Outcome Measures Blinded assessments were made at 4 weeks post surgery (baseline) and 12 weeks post baseline (proposed primary end point). Secondary outcomes included: Global Perceived Effect, back/leg pain, straight leg raise, return to work/function, quality of life, fear avoidance, range of movement, medication, re-operation. Results At discharge, 110 (44%) eligible patients gave consent to be contacted. 59 (54%) patients were recruited. Loss to follow up was 39% at 12 weeks, with one site contributing 83% losses. Mean (SD) RMDQ was 10.07 (5.58) leaflet and 10.52 (5.94) physiotherapy/leaflet at baseline; and 5.37 (4.91) leaflet and 5.53 (4.49) physiotherapy/leaflet at 12 weeks. 5.1% zero scores at 12 weeks illustrated no floor effect. Sensitivity to change was assessed at 12 weeks with mean (SD) change -4.53 (6.41), 95%CI -7.61 to -1.44 for leaflet; and -6.18 (5.59), 95%CI -9.01 to -3.30 for physiotherapy/leaflet. RMDQ mean difference (95%CI) between change from baseline to twelve weeks was 1.65(-2.46 to 5.75). Mean difference (95%CI) between groups at 12 weeks was -0.16 (-3.36 to 3.04). Participant adherence with treatment was good. No adverse events were reported. Conclusions Both interventions were acceptable, and it is promising that they both demonstrated a trend in reducing disability in this population. A randomised controlled trial, using a different trial design, is needed to ascertain the effectiveness of combining the interventions into a stepped care intervention and comparing to a no intervention arm. Findings will guide design changes for an adequately powered randomised controlled trial, using RMDQ as the primary outcome. Trial Registration ISRCTN registry 33808269
Persistent effects of early infant diet and associated microbiota on the juvenile immune system

Early infant diet has significant impacts on the gut microbiota and developing immune system. We previously showed that breast-fed and formula-fed rhesus macaques develop significantly different gut microbial communities, which in turn are associated with different immune systems in infancy. Breast-fed animals manifested greater T cell activation and proliferation and harbored robust pools of T helper 17 (TH17) cells. These differences were sustained throughout the first year of life. Here we examine groups of juvenile macaques (approximately 3 to 5 y old), which were breast-fed or formula-fed in infancy. We demonstrate that juveniles breast-fed in infancy maintain immunologic differences into the fifth year of life, principally in CD8+ memory T cell activation. Additionally, long-term correlation networks show that breast-fed animals maintain persistent relationships between immune subsets that are not seen in formula-fed animals. These findings demonstrate that infant feeding practices have continued influence on immunity for up to 3 to 5 y after birth and also reveal mechanisms for microbial modulation of the immune system.
Possible role of nuclear β‐catenin in resistance to preoperative chemoradiotherapy in locally advanced rectal cancer

β‐Catenin signalling participates in the regulation of epithelial–mesenchymal transition (EMT)/cancer stem cell (CSC) properties. The aim of this study was to investigate the role of β‐catenin in resistance to neoadjuvant chemoradiotherapy in patients with rectal cancer, especially pertaining to its association with EMT/CSC features.
Theoretical and Experimental Studies on Fracture Mechanics of Spices as Model Food Material

The particle size of industrially manufactured food is an important quality criterion in which both the taste (sensory) as well as functionality is influenced. Due to the tough, plastic or elastic characteristics and often fibrous structure, food is difficult to grind conventionally. The present thesis examines the fracture mechanism, crack growth as well as shape formation during low temperature grinding under controlled conditions. The experiments are validated bz modelling of grinding by Finite Element Method. Turmeric (Curcuma Longa) was used as model material for experiments and modelling.
Drilling of micro-holes on titanium alloy using pulsed Nd:YAG laser: Parametric appraisal and prediction of performance characteristics

Laser drilling is a preferable method in drilling micro and slender holes because of its non-physical contact between the tool and the workpiece leading to elimination of the problems like chatter and vibration. In this article, an experimental investigation of the laser drilling process is carried out on thin sheet (0.5 mm) of titanium alloy (Ti6Al4V) using pulsed Nd:YAG laser. The study investigates the effect of laser parameters such as laser energy, pulse repetition rate, pulse width and gas pressure on hole quality characteristics, namely, circularity at entry and exit, taper and spatter area. Taguchi’s L27 orthogonal array is adopted for conducting the experiments to establish significance of control parameters on the performance measures with less number of experimental run. Analysis of variance shows that laser energy and pulse width significantly influence on circularity, taper and spatter area. Optimal parameter setting for all the performance measures is suggested. Statistically valid empirical models relating hole quality characteristics with laser parameters have been developed based on least square regression analysis. Backpropagation artificial neural network is used predict the output responses considering laser process parameters as inputs. A mean square error within 5% for both the training and testing data suggests the adequacy and robustness of the proposed artificial neural network model. Variation of performance measures with respect to process parameters is predicted through the well-trained artificial neural network model. The pattern of variation exhibits good agreement with the main effect plots obtained through Taguchi method. Artificial neural network model produces mean relative error of 0.001, 0.001, 0.0437 and 0.0234 for circularity at entry, circularity at exit, taper and spatter area, respectively, when compared with experimental values. Since small values of mean relative error are obtained, the proposed artificial neural network model can be satisfactorily used for prediction of quality characteristics of laser micro-drilled holes.
A Survey on Modeling Energy Consumption of Cloud Applications: Deconstruction, State of the Art, and Trade-Off Debates

Given the complexity and heterogeneity in Cloud computing scenarios, the modeling approach has widely been employed to investigate and analyze the energy consumption of Cloud applications, by abstracting real-world objects and processes that are difficult to observe or understand directly. It is clear that the abstraction sacrifices, and usually does not need, the complete reflection of the reality to be modeled. Consequently, current energy consumption models vary in terms of purposes, assumptions, application characteristics and environmental conditions, with possible overlaps between different research works. Therefore, it would be necessary and valuable to reveal the state-of-the-art of the existing modeling efforts, so as to weave different models together to facilitate comprehending and further investigating application energy consumption in the Cloud domain. By systematically selecting, assessing, and synthesizing 76 relevant studies, we rationalized and organized over 30 energy consumption models with unified notations. To help investigate the existing models and facilitate future modeling work, we deconstructed the runtime execution and deployment environment of Cloud applications, and identified 18 environmental factors and 12 workload factors that would be influential on the energy consumption. In particular, there are complicated trade-offs and even debates when dealing with the combinational impacts of multiple factors.
Modelling personal preferences for Top-N movie recommendations

Modelling the temporal dynamics of personal preferences is still under-developed despite the rapid development of personalization. In this paper, we observe that the user preference styles tend to change regularly following certain patterns in the context of movie recommendation systems. Therefore, we propose a Preference Pattern model to capture the user preference styles and their temporal dynamics, and apply this model to improve the accuracy of the Top-N movie recommendations. Precisely, a preference pattern is defined as a set of user preference styles sorted in a time order. The basic idea is to model user preference styles and their temporal dynamics by constructing a representative subspace with an Expectation-Maximization (EM)-like algorithm, which works in an iterative fashion by refining the global and the personal preference styles simultaneously. Then, the degree which the recommendations match the active user's preference styles, can be estimated by measuring its reconstruction error from its projection on the representative subspace. The experiment results indicate that the proposed model is robust to the data sparsity problem, and can significantly outperform the state-of-the-art algorithms on the Top-N movie recommendations in terms of accuracy.
III-V Nanowire Solar Cells: Growth and Characterization

To mitigate dangerous climate change, a transition to a new and sustainable energy system is needed. In this system, solar energy will need to be a key player. Prices of electricity made from solar cells have declined rapidly over the recent decades, making solar energy competitive in more markets. However, further price reductions and new innovations are needed for solar cell technology to fulfil its potential.In this thesis, we look at a class of materials that have gained increasing interest in the recent decade; III-V semiconductor nanowires. For solar cells, the III V semiconductors hold excellent optical and electrical properties, but high material and manufacturing costs have so far prevented competitiveness with the dominating Si based technology. However, III-V material in the nanowire geometry has a number of interesting advantages when it comes to reducing cost, as well as for adding III-Vs to conventional Si in tandem solar cell architectures. This has motivated substantial research efforts during recent years, both at universities and private companies. In this thesis, we have mainly studied InP and InxGa1-xP nanowire arrays as a solar cell material. The nanowires were grown by metal organic vapor phase epitaxy (MOVPE) via gold seeded vapor-liquid-solid growth. The gold seed particles were placed in a pattern on the growth substrate by help of nanoimprint lithography. Developing strategies to preserve this pattern through the stages of nanowire growth was an important foundation for the thesis work. These strategies allowed us to reproducibly grow dense and ordered arrays of nanowires, optimized for sunlight absorption. Controllably changing the electrical properties of the semiconductor through impurity doping is important to make a good solar cell. Doping nanowires is challenging since the growth mechanism is different from established layer growth by MOVPE, and nanowire characterization is demanding. We have studied doping in our nanowires in various ways. Most importantly, we have performed some of the first systematic doping studies in ternary III-V materials, with bandgaps needed to create tandem nanowire solar cells. Knowledge from these studies allowed us to realize and study the first nanowire tunnel junction connecting two materials of appropriate bandgap to match the solar spectrum.Finally, we have developed a characterization procedure to optimize nanowire solar cell characteristics. This helped us create a better understanding of performance limiting factors in our InP nanowire solar cells. As a result, we achieved more than a sevenfold performance improvement in these cells, with the best device having a certified power conversion efficiency of 15.0%. This is the highest reported efficiency value for a bottom-up synthesized InP nanowire solar cell.
Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting

A lensless blood cell counting system integrating microfluidic channel and a complementary metal oxide semiconductor (CMOS) image sensor is a promising technique to miniaturize the conventional optical lens based imaging system for point-of-care testing (POCT). However, such a system has limited resolution, making it imperative to improve resolution from the system-level using super-resolution (SR) processing. Yet, how to improve resolution towards better cell detection and recognition with low cost of processing resources and without degrading system throughput is still a challenge. In this article, two machine learning based single-frame SR processing types are proposed and compared for lensless blood cell counting, namely the Extreme Learning Machine based SR (ELMSR) and Convolutional Neural Network based SR (CNNSR). Moreover, lensless blood cell counting prototypes using commercial CMOS image sensors and custom designed backside-illuminated CMOS image sensors are demonstrated with ELMSR and CNNSR. When one captured low-resolution lensless cell image is input, an improved high-resolution cell image will be output. The experimental results show that the cell resolution is improved by 4×, and CNNSR has 9.5% improvement over the ELMSR on resolution enhancing performance. The cell counting results also match well with a commercial flow cytometer. Such ELMSR and CNNSR therefore have the potential for efficient resolution improvement in lensless blood cell counting systems towards POCT applications.
Protracted Development of the Proprioceptive Brain Network During and Beyond Adolescence

Abstract Proprioceptive processing is important for appropriate motor control, providing error‐feedback and internal representation of movement for adjusting the motor command. Although proprioceptive functioning improves during childhood and adolescence, we still have few clues about how the proprioceptive brain network develops. Here, we investigated developmental changes in the functional organization of this network in early adolescents (n = 18, 12 ± 1 years), late adolescents (n = 18, 15 ± 1), and young adults (n = 18, 32 ± 4), by examining task‐evoked univariate activity and patterns of functional connectivity (FC) associated with seeds placed in cortical (supramarginal gyrus) and subcortical (dorsal rostral putamen) regions. We found that although the network is already well established in early adolescence both in terms of topology and functioning principles (e.g., long‐distance communication and economy in wiring cost), it is still undergoing refinement during adolescence, including a shift from diffuse to focal FC and a decreased FC strength. This developmental effect was particularly pronounced for fronto‐striatal connections. Furthermore, changes in FC features continued beyond adolescence, although to a much lower extent. Altogether, these findings point to a protracted developmental time course for the proprioceptive network, which breaks with the relatively early functional maturation often associated with sensorimotor networks.
Performance Analysis of Device-to-Device Communications with Dynamic Interference Using Stochastic Petri Nets

In this paper, we study the performance of Device-to-Device (D2D) communications with dynamic interference. In specific, we analyze the performance of frequency reuse among D2D links with dynamic data arrival setting. We first consider the arrival and departure processes of packets in a non-saturated buffer, which result in varying interference on a link based on the change of its backlogged state. The packet-level system behavior is then represented by a coupled processor queuing model, where the service rate varies with time due to both the fast fading and the dynamic interference effects. In order to analyze the queuing model, we formulate it as a Discrete Time Markov Chain (DTMC) and compute its steady-state distribution. Since the state space of the DTMC grows exponentially with the number of D2D links, we use the model decomposition and some iteration techniques in Stochastic Petri Nets (SPNs) to derive its approximate steady state solution, which is used to obtain the approximate performance metrics of the D2D communications in terms of average queue length, mean throughput, average packet delay and packet dropping probability of each link. Simulations are performed to verify the analytical results under different traffic loads and interference conditions.