Miracle-dz/UniFAR-FTUs huggingface dataset:
The prevalence of professional burnout among dentists: a systematic review and meta-analysis

ABSTRACT Professional burnout refers to mental weariness caused by occupational stress. However, there is a lack of systematic studies on the prevalence of professional burnout among dentists. The purpose of this study was to investigate the prevalence of professional burnout among dentists. Databases including PubMed, PsycINFO, Embase, Cochrane, and Web of Science were systematically searched from inception to 28 October 2021. The random-effects model and forest plots were used to assess the pooled prevalence of professional burnout among dentists. A total of 15 studies with a total of 6038 study subjects were included in the meta-analysis, and the overall professional burnout among dentists was 13% (95%CI: 6–23). Subgroup analysis suggested a high prevalence of burnout in Europe, and the least in the Americas. The pooled burnout prevalence in cross-sectional surveys was significantly lower than that in longitudinal studies. In addition, the overall burnout prevalence in the last decade was significantly lower than that of a decade ago. This meta-analysis demonstrated that the prevalence of burnout was relatively low among dentists, and there was a downward trend. Therefore, it is important to continue to pay close attention to the mental health of dentists and effectively prevent and treat professional burnout to better maintain the provision of health care services. Summary The overall prevalence of professional burnout among dentists was 13%. Subgroup analysis revealed that the prevalence of burnout differed in geographical regions, with the highest in Europe, followed by Asia, and the lowest in America. The pooled burnout prevalence in cross-sectional surveys was significantly lower than that in longitudinal studies. In addition, the overall burnout prevalence in the last decade was significantly lower than that of a decade ago. More attention should be paid to professional burnout among dentists to improve the provision of health care services.
RNA granules: functional compartments or incidental condensates?

In this review, Putnam et al. tackle our current understanding of RNA granules, intracellular phase-separated sites of RNA metabolism that contain factors for RNA biogenesis and turnover and are often assumed to represent specialized compartments for RNA biochemistry. The authors discuss the possibility that some RNA granules are condensation by-products that form when subsoluble RNP complexes saturate the cytoplasm or nucleoplasm, and introduce the term “incidental condensates” to refer to condensates that are tolerated by cells but do not add functionality beyond that provided by the soluble pool of saturating RNP complexes. Finally, they consider best practices for distinguishing functional RNA granules from incidental condensates.
Obsessive‐compulsive disorder: Etiology, neuropathology, and cognitive dysfunction

This review provides an overview of obsessive‐compulsive disorder (OCD) symptoms, including the four partially distinct subtypes of the disorder, current diagnostic criteria, and common comorbidities. Critically, it focuses on the etiology of OCD, including its underlying neuropathology, and examines cognitive dysfunction in OCD.
Deep Domain Adaptation, Pseudo-Labeling, and Shallow Network for Accurate and Fast Gait Prediction of Unlabeled Datasets

Developing personalized gait phase prediction models is difficult because acquiring accurate gait phases requires expensive experiments. This problem can be addressed via semi-supervised domain adaptation (DA), which minimizes the discrepancy between the source and target subject features. However, classical DA models have a trade-off between accuracy and inference speed. Whereas deep DA models provide accurate prediction results with a slow inference speed, shallow DA models produce less accurate results with a fast inference speed. To achieve both high accuracy and fast inference, a dual-stage DA framework is proposed in this study. The first stage uses a deep network for precise DA. Then, a pseudo-gait-phase label of the target subject is obtained using the first-stage model. In the second stage, a shallow but fast network is trained using the pseudo-label. Because computation for DA is not conducted in the second stage, an accurate prediction can be accomplished even with the shallow network. Test results show that the proposed DA framework reduces the prediction error by 1.04% compared with a shallow DA model while maintaining its fast inference speed. The proposed DA framework can be used to provide fast personalized gait prediction models for real-time control systems such as wearable robots.
On the superstability of generalized d’Alembert harmonic functions

Abstract The aim of this paper is to study the superstability problem of the d’Alembert type functional equation f(x+y+z)+f(x+y+σ(z))+f(x+σ(y)+z)+f(σ(x)+y+z)=4f(x)f(y)f(z) $$f(x + y + z) + f(x + y + \sigma (z)) + f(x + \sigma (y) + z) + f(\sigma (x) + y + z) = 4f(x)f(y)f(z)$$ for all x, y, z ∈ G, where G is an abelian group and σ : G → G is an endomorphism such that σ(σ(x)) = x for an unknown function f from G into ℂ or into a commutative semisimple Banach algebra.
The miR‐126‐5p and miR‐212‐3p in the extracellular vesicles activate monocytes in the early stage of radiation‐induced vascular inflammation implicated in atherosclerosis

Abstract People exposed to radiation in cancer therapy and nuclear accidents are at increased risk of cardiovascular outcomes in long‐term survivors. Extracellular vesicles (EVs) are involved in radiation‐induced endothelial dysfunction, but their role in the early stage of vascular inflammation after radiation exposure remains to be fully understood. Herein, we demonstrate that endothelial cell‐derived EVs containing miRNAs initiate monocyte activation in radiation‐induced vascular inflammation. In vitro co‐culture and in vivo experimental data showed that endothelial EVs can be sensitively increased by radiation exposure in a dose‐dependent manner, and stimulate monocytes releasing monocytic EVs and adhesion to endothelial cells together with an increase in the expression of genes encoding specific ligands for cell‐cell interaction. Small RNA sequencing and transfection using mimics and inhibitors explained that miR‐126‐5p and miR‐212‐3p enriched in endothelial EVs initiate vascular inflammation by monocyte activation after radiation exposure. Moreover, miR‐126‐5p could be detected in the circulating endothelial EVs of radiation‐induced atherosclerosis model mice, which was found to be tightly correlated with the atherogenic index of plasma. In summary, our study showed that miR‐126‐5p and miR‐212‐3p present in the endothelial EVs mediate the inflammatory signals to activate monocytes in radiation‐induced vascular injury. A better understanding of the circulating endothelial EVs content can promote their use as diagnostic and prognostic biomarkers for atherosclerosis after radiation exposure.
A Consensus Approach to Distributed Convex Optimization in Multi-Agent Systems

In this thesis we address the problem of distributed unconstrained convex optimization under separability assumptions, i.e., the framework where a network of agents, each endowed with local private convex cost and subject to communication constraints, wants to collaborate to compute the minimizer of the sum of the local costs. We propose a design methodology that combines average consensus algorithms and separation of time-scales ideas. This strategy is proven, under suitable hypotheses, to be globally convergent to the true minimizer. Intuitively, the procedure lets the agents distributedly compute and sequentially update an approximated Newton-Raphson direction by means of suitable average consensus ratios. We consider both a scalar and a multidimensional scenario of the Synchronous Newton-Raphson Consensus, proposing some alternative strategies which trade-off communication and computational requirements with convergence speed. We provide analytical proofs of convergence and we show with numerical simulations that the speed of convergence of this strategy is comparable with alternative optimization strategies such as the Alternating Direction Method of Multipliers, the Distributed Subgradient Method and Distributed Control Method. Moreover, we consider the convergence rates of the Synchronous Newton-Raphson Consensus and the Gradient Descent Consensus under the simplificative assumption of quadratic local cost functions. We derive sufficient conditions which guarantee the convergence of the algorithms. From these conditions we then obtain closed form expressions that can be used to tune the parameters for maximizing the rate of convergence. Despite these formulas have been derived under quadratic local cost functions assumptions, they can be used as rules-of-thumb for tuning the parameters of the algorithms. Finally, we propose an asynchronous version of the Newton-Raphson Consensus. Beside having low computational complexity, low communication requirements and being interpretable as a distributed Newton-Raphson algorithm, the technique has also the beneficial properties of requiring very little coordination and naturally supporting time-varying topologies. Again, we analytically prove that under some assumptions it shows either local or global convergence properties. Through numerical simulations we corroborate these results and we compare the performance of the Asynchronous Newton-Raphson Consensus with other distributed optimization methods.
Investigating effect modification between childhood maltreatment and genetic risk for cardiovascular disease in the UK Biobank

Cardiovascular disease (CVD) is influenced by genetic and environmental factors. Childhood maltreatment is associated with CVD and may modify genetic susceptibility to cardiovascular risk factors. We used genetic and phenotypic data from 100,833 White British UK Biobank participants (57% female; mean age = 55.9 years). We regressed nine cardiovascular risk factors/diseases (alcohol consumption, body mass index [BMI], low-density lipoprotein cholesterol, lifetime smoking behaviour, systolic blood pressure, atrial fibrillation, coronary heart disease, type 2 diabetes, and stroke) on their respective polygenic scores (PGS) and self-reported exposure to childhood maltreatment. Effect modification was tested on the additive and multiplicative scales by including a product term (PGS*maltreatment) in regression models. On the additive scale, childhood maltreatment accentuated the effect of genetic susceptibility to higher BMI (Peffect modification: 0.003). Individuals not exposed to childhood maltreatment had an increase in BMI of 0.12 SD (95% CI: 0.11, 0.13) per SD increase in BMI PGS, compared to 0.17 SD (95% CI: 0.14, 0.19) in those exposed to all types of childhood maltreatment. On the multiplicative scale, similar results were obtained for BMI though these did not withstand to Bonferroni correction. There was little evidence of effect modification by childhood maltreatment in relation to other outcomes, or of sex-specific effect modification. Our study suggests the effects of genetic susceptibility to a higher BMI may be moderately accentuated in individuals exposed to childhood maltreatment. However, gene*environment interactions are likely not a major contributor to the excess CVD burden experienced by childhood maltreatment victims.
The Study Of Swimming Propulsion Using Computational Fluid Dynamics

Introduction The generation of propulsive forces in human swimming has been studied recently using numerical simulation techniques with computational fluid dynamics (CFD) models (Bixler and Riewald, 2002; Rouboa et al., 2006). However, some limitations still remain, regarding the geometrical representation of the human limbs. Therefore, the aim of this study was to determine the propulsive force in a 3-D hand/forearm model using CFD. Methods The CFD analysis consisted in the use of a mesh of cells that simulates the flow around the considered model. The whole domain was meshed with 400.000 trapezoidal elements of 4 nodes each. Numerical simulations for the whole computational steady domain were calculated in the three dimensions with the commercial code fluent. Models used in the simulations were created in CAD, based on realistic dimensions of a right adult human hand/forearm. The governing system of equations considered was the incompressible Reynolds averaged Navier-Stokes equations with the standard k-epsilon model (Moreira et al., 2006). Flow speeds were chosen to be within or near the range of typical hand speeds during freestyle swimming underwater path: from 0.50 m/s to 4.00 m/s. Angles of attack of hand/forearm model of 0o, 45o e 90o, with an angle of orientation of 0o (thumb as the leading edge) were used for the calculations. The measured forces on the hand/forearm model were decomposed into drag and lift components. The combined hand and forearm drag (CD) and lift (CL) coefficients were calculated. Results The magnitude of CD and CL remained constant throughout the flow speeds tested. Angles of attack of 0o, 45o and 90o produced, respectively, CD values of 0.35, 0.63 and 1.10 and CL values of 0.18, 0.32 and 0.05. Discussion CD was the main responsible for propulsion, with the maximum value of force production corresponding to an angle of attack of 90o, as expected. CL has a residual influence in the generation of propulsive force by the hand/forearm segment for angles of attack of 0o and 90o, but it is important with an angle of attack of 45o. These data confirm experimental studies reporting reduced contribution of lift component to the overall propulsive force generation by the hand/forearm in front crawl swimming, except for the insweep phase, when the angle of attack nears 45o (Berger et al., 1995; Sanders, 1999). References Berger M, de Groot G, Hollander A (1995). J Biomec, 28(2), 125-133. Bixler B, Riewald S (2002). J Biomec, 35, 713-717. Moreira A, Silva A, Rouboa A, Marinho D, Alves F, Reis V, Machado L, Vilas-Boas J (2006). Portuguese J Sports Sci, 6 (Supl. 1), 48-49. Rouboa A, Silva A, Leal L, Rocha J, Alves F (2006). J Biomec, 39(7), 1239-1248. Sanders R (1999). J Appl Biomec, 15, 3-26. Acknowledgments This work was supported by the Portuguese Government by a grant of the Science and Technology Foundation (SFRH/BD/25241/2005; POCTI/10/58872/2004).
Simulation of Commensurate Fractional Order Systems

Commensurate fractional order systems is a special kind of fractional order systems.The basic item of commensurate fractional order systems can be looked upon as the whole.The commensurate fractional order systems can be converted to the integer order systems through approximation method.The complexity the commensurate fractional order systems can be depressed greatly through much less approximation procession.The validity and succinctness of the method was demonstrated by some simulation examples.The proposed method is used for solution of the commensurate fractional order systems.
Research on arithmetic of the number theory transformation(NTT) applied in the image compression

A new image compression arithmetic is put forward, i e. the Number Theoretic Transformation (NTT). It proves that the NTT on the integral ring Z p module p is linear transformation and the NTT on Z p has the convolution characteristic, and a quick arithmetic with FFT is designed. The arithmetic may be realized by shift and its velocity is superior to the DCT(Discrete Cosine Transformation). Finally by contrast of instances, it indicates that this method represents such advantages as fast velocity, high precision, and good effect of compression, etc. The study on NTT arithmetic exploits a new method for the image compression technique.
DYNAMICS OF FINITE-SIZED LIGHT SPHERES IN TURBULENCE

We report experimental results on the Lagrangian dynamics of finite-size light particles in turbulence. Using an orthogonal camera setup and 3D particle tracking, we study the velocity and acceleration statistics of rigid light spheres in a water tunnel with nearly homogeneous and isotropic turbulence. The Reynolds number (Re ) is varied from 180 to 300, and the study covers a range of size ratios (4 < < 16) for marginally light spheres. We find that the normalized acceleration PDF decreases in intermittency with increasing size ratio - in qualitative agreement with the predictions of the Faxen corrected model (1). We also present preliminary results on the rotational dynamics of large light spheres in turbulence. INTRODUCTION, MOTIVATION AND EXPERIMENTS Particles dispersions in turbulent flows exist in many natural situations - typical examples include pollutants dispersed in the atmosphere, droplet suspensions in clouds, and air bubbles and plankton in the oceans. Particle suspensions occur in industrial settings as well, for example, sprays in the combustion chambers of engines, and air-bubbles in bubble column reacters. An accurate representation of the behavior of these particles requires a fundamental understanding of the physics of the problem. Major research efforts are directed to this end, particularly on the statistical properties (mainly the velocity and acceleration) of such particle suspensions in turbulent flows. Figure 1. The Twente Water Tunnel facility: A vertical water tunnel with turbulence generated by an active-grid. Light rigid spheres (4 < < 16) are dispersed in the tunnel, with the flow in the downward direction.
Biopsy prostate cancer perineural invasion and tumour load are associated with positive posterolateral margins at radical prostatectomy: implications for planning of nerve‐sparing surgery

Radical prostatectomy (RP) for prostate cancer is frequently complicated by erectile dysfunction and urinary incontinence. However, sparing of the nerve bundles adjacent to the posterolateral sides of the prostate reduces the number of complications at the risk of positive surgical margins. Preoperative selection of men eligible for safe, nerve‐sparing surgery is therefore needed. Our aim was to identify pathological factors associated with positive posterolateral surgical margins in men undergoing bilateral nerve‐sparing RP.
Cyclin-Dependent Kinase Inhibitor 2A is a Key Regulator of Cell Cycle Arrest and Senescence in Endothelial Colony-Forming Cells in Moyamoya Disease

Objective Endothelial colony-forming cells (ECFCs) have been reported to play an important role in the pathogenesis of moyamoya disease (MMD). We have previously observed stagnant growth in MMD ECFCs with functional impairment of tubule formation. We aimed to verify the key regulators and related signaling pathways involved in the functional defects of MMD ECFCs. Methods ECFCs were cultured from peripheral blood mononuclear cells of healthy volunteers (normal) and MMD patients. Low-density lipoproteins uptake, flow cytometry, high content screening, senescence-associated β-galactosidase, immunofluorescence, cell cycle, tubule formation, microarray, real-time quantitative polymerase chain reaction, small interfering RNA transfection, and western blot analyses were performed. Results The acquisition of cells that can be cultured for a long time with the characteristics of late ECFCs was significantly lower in the MMD patients than the normal. Importantly, the MMD ECFCs showed decreased cellular proliferation with G1 cell cycle arrest and cellular senescence compared to the normal ECFCs. A pathway enrichment analysis demonstrated that the cell cycle pathway was the major enriched pathway, which is consistent with the results of the functional analysis of ECFCs. Among the genes associated with the cell cycle, cyclin-dependent kinase inhibitor 2A (CDKN2A) showed the highest expression in MMD ECFCs. Knockdown of CDKN2A in MMD ECFCs enhanced proliferation by reducing G1 cell cycle arrest and inhibiting senescence through the regulation of CDK4 and phospho retinoblastoma protein. Conclusion Our study suggests that CDKN2A plays an important role in the growth retardation of MMD ECFCs by inducing cell cycle arrest and senescence.
Exploration at the network pharmacology level of possible targeting mechanisms of Smilacis Glabrae Rhixoma for the treatment of osteoporosis.

OBJECTIVE The aim of this study was to evaluate the therapeutic effect of Smilacis Glabrae Rhixoma (SGR) on osteoporosis at the level of network pharmacology, and to find new targets and mechanisms of SGR in the treatment of osteoporosis, to better find new drugs and their clinical applications. MATERIALS AND METHODS In the original network pharmacology mode, we used an improved mode, such as screening the ingredients and targets of SGR through tools such as GEO database, Autodock Vina, and GROMACS. Through molecular docking, we conducted further screening for the targets acting on the effective ingredients of SGR, and finally we performed molecular dynamics simulation and consulted a large amount of related literature for the validation of the results. RESULTS By screening and validating the data, we finally confirmed that there were mainly 10 active ingredients in SGR, which were isoeruboside b, smilagenin, diosgenin, stigmasterol, beta-sitosterol, sodium taurocholate, sitogluside, 4,7-dihydroxy-5-methoxy-6-methyl-8-formyl-flavan, simiglaside B, and simiglaside E, and mainly acted on eleven targets. These targets mainly exert therapeutic effects on osteoporosis by regulating 20 signaling pathways including Th17 cell differentiation, HIF-1 signaling pathway, apoptosis, inflammatory bowel disease, and osteoclast differentiation. CONCLUSIONS Our study successfully explains the effective mechanism by which SGR ameliorates osteoporosis while predicting the potential targets NFKB1 and CTSK of SGR for the treatment of osteoporosis, which provides a novel basis for investigating the mechanism of action of new Traditional Chinese medicines (TCMs) at the network pharmacology level and a great support for subsequent studies on osteoporosis.
Predictors of insulin pump initiation among people with type 2 diabetes from a US claims database using machine learning

Abstract Objective Insulin pump use is increasing among people with type 2 diabetes (T2D), albeit at a slower rate compared to people with type 1 diabetes (T1D). Factors associated with insulin pump initiation among people with T2D in the real-world are understudied. Methods This retrospective, nested case-control study aimed to identify predictors of insulin pump initiation among people with T2D in the United States (US). Adults with T2D who were new to bolus insulin use were identified from the IBM MarketScan Commercial database (2015–2020). Candidate variables of pump initiation were entered into conditional logistic regression (CLR) and penalized CLR models. Results Of the 32,104 eligible adults with T2D, 726 insulin pump initiators were identified and matched to 2,904 non-pump initiators using incidence density sampling. Consistent predictors of insulin pump initiation across the base case, sensitivity, and post hoc analyses included continuous glucose monitor (CGM) use, visiting an endocrinologist, acute metabolic complications, higher count of HbA1c tests, lower age, and fewer diabetes-related medication classes. Conclusions Many of these predictors could represent a clinical indication for treatment intensification, greater patient engagement in diabetes management, or proactive management by healthcare providers. Improved understanding of predictors for pump initiation may lead to more targeted efforts to improve access and acceptance of insulin pumps among persons with T2D.