Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinician engagement in the ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness) trial

Background: ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness) is a pragmatic clinical trial examining high-dose versus low-dose aspirin among patients with cardiovascular disease. ADAPTABLE is leveraging novel approaches for clinical trial conduct to expedite study completion and reduce costs. One pivotal aspect of the trial conduct is maximizing clinician engagement. Methods/Results: Clinician engagement can be diminished by barriers including time limitations, insufficient research infrastructure, lack of research training, inadequate compensation for research activities, and clinician beliefs. We used several key approaches to boost clinician engagement such as empowering clinician champions, including a variety of clinicians, nurses and advanced practice providers, periodic newsletters and coordinated team celebrations, and deploying novel technological solutions. Specifically, some centers generated electronic health records–based best practice advisories and research dashboards. Future large pragmatic trials will benefit from standardization of the various clinician engagement strategies especially studies leveraging electronic health records–based approaches like research dashboards. Financial or academic “credit” for clinician engagement in clinical research may boost participation rates in clinical studies. Conclusion: Maximizing clinician engagement is important for the success of clinical trials; the strategies employed in the ADAPTABLE trial may serve as a template for future pragmatic studies.
Efficacy of Popular Diets Applied by Endurance Athletes on Sports Performance: Beneficial or Detrimental? A Narrative Review

Endurance athletes need a regular and well-detailed nutrition program in order to fill their energy stores before training/racing, to provide nutritional support that will allow them to endure the harsh conditions during training/race, and to provide effective recovery after training/racing. Since exercise-related gastrointestinal symptoms can significantly affect performance, they also need to develop strategies to address these issues. All these factors force endurance athletes to constantly seek a better nutritional strategy. Therefore, several new dietary approaches have gained interest among endurance athletes in recent decades. This review provides a current perspective to five popular diet approaches: (a) vegetarian diets, (b) high-fat diets, (c) intermittent fasting diets, (d) gluten-free diet, and (e) low fermentable oligosaccharides, disaccharides, monosaccharides and polyols (FODMAP) diets. We reviewed scientific studies published from 1983 to January 2021 investigating the impact of these popular diets on the endurance performance and health aspects of endurance athletes. We also discuss all the beneficial and harmful aspects of these diets, and offer key suggestions for endurance athletes to consider when following these diets.
Sequence of clinical and neurodegeneration events in Parkinson’s disease progression

See Le Heron et al. (doi:10.1093/brain/awab060) for a scientific commentary on this article. Using event-based modelling, Oxtoby et al. reveal the fine-grained probabilistic sequence of changes in clinical, cognitive and neuroimaging measures during Parkinson’s disease progression. Performance on visual tasks is impaired early on, typically before neurodegeneration and retinal thinning can be detected.
Effects of periodontal management for patients with type 2 diabetes on healthcare expenditure, hospitalization, and worsening of diabetes: an observational study using medical, dental, and pharmacy claims data in Japan.

AIMS To investigate the effects of regular periodontal management for people with type 2 diabetes on total healthcare expenditure, hospitalization, and the introduction of insulin. MATERIALS AND METHODS We collected data of individuals who were prescribed diabetes medications during the fiscal year 2015 from the claims database of a prefecture in Japan. We fitted generalized linear models that had sex, age, comorbidities, and the status of periodontal management during the previous two years as predictors. RESULTS A total of 16,583 individuals were enrolled. The annual healthcare expenditure in the third year was 4% less (adjusted multiplier 0.96, 95% confidence interval [CI] 0.92-1.00) in the group receiving periodontal management every year. The adjusted odds ratio (aOR) for all-cause hospitalization was 0.90 (95% CI: 0.82-0.98). The aOR of introducing insulin in the third year for those who had not been prescribed insulin during the previous two years (n=13,222) was 0.77 (95% CI: 0.64-0.92) in the group receiving periodontal management every year. CONCLUSION Regular periodontal management for diabetic people was associated with reduced healthcare expenditure, all-cause hospitalization, and the introduction of insulin therapy.
Concurrent Prediction of Finger Forces Based on Source Separation and Classification of Neuron Discharge Information

A reliable neural-machine interface is essential for humans to intuitively interact with advanced robotic hands in an unconstrained environment. Existing neural decoding approaches utilize either discrete hand gesture-based pattern recognition or continuous force decoding with one finger at a time. We developed a neural decoding technique that allowed continuous and concurrent prediction of forces of different fingers based on spinal motoneuron firing information. High-density skin-surface electromyogram (HD-EMG) signals of finger extensor muscle were recorded, while human participants produced isometric flexion forces in a dexterous manner (i.e. produced varying forces using either a single finger or multiple fingers concurrently). Motoneuron firing information was extracted from the EMG signals using a blind source separation technique, and each identified neuron was further classified to be associated with a given finger. The forces of individual fingers were then predicted concurrently by utilizing the corresponding motoneuron pool firing frequency of individual fingers. Compared with conventional approaches, our technique led to better prediction performances, i.e. a higher correlation ([Formula: see text] versus [Formula: see text]), a lower prediction error ([Formula: see text]% MVC versus [Formula: see text]% MVC), and a higher accuracy in finger state (rest/active) prediction ([Formula: see text]% versus [Formula: see text]%). Our decoding method demonstrated the possibility of classifying motoneurons for different fingers, which significantly alleviated the cross-talk issue of EMG recordings from neighboring hand muscles, and allowed the decoding of finger forces individually and concurrently. The outcomes offered a robust neural-machine interface that could allow users to intuitively control robotic hands in a dexterous manner.
Maintenance cost in the processing of subject-verb dependencies.

Although research in sentence comprehension has suggested that processing long-distance dependencies involves maintenance between the elements that form the dependency, studies on maintenance of long-distance subject-verb (SV) dependencies are scarce. The few relevant studies have delivered mixed results using self-paced reading or phoneme-monitoring tasks. In the current study, we used eye tracking during reading to test whether maintaining a long-distance SV dependency results in a processing cost on an intervening adverbial clause. In Experiment 1, we studied this question in Spanish and found that both go-past reading times and regressions out of an adverbial clause to the previous regions were significantly increased when the clause interrupts a SV dependency compared to when the same clause doesn't interrupt this dependency. We then replicated these findings in English (Experiment 2), observing significantly increased go-past reading times on a clause interrupting a SV dependency. The current study provides the first eye-tracking data showing a maintenance cost in the processing of SV dependencies cross-linguistically. Sentence comprehension models should account for the maintenance cost generated by SV dependency processing, and future research should focus on the nature of the maintained representation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Resting cerebral oxygen metabolism exhibits archetypal network features

Standard magnetic resonance imaging approaches offer high‐resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low‐frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO2). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies. Seventeen participants underwent 20 min of resting imaging during dual‐echo, pseudocontinuous arterial spin labeling, and blood‐oxygen‐level dependent (BOLD) signal acquisition. Participants also underwent a 10 min normocapnic and hypercapnic procedure. Brain‐wide, CMRO2 low‐frequency fluctuations were subjected to graph‐based and voxel‐wise functional connectivity analyses. Results demonstrated that connections derived from resting CMRO2 fluctuations exhibited complex, small‐world topological properties (i.e., high integration and segregation, cost efficiency) consistent with those observed in previous studies using functional and anatomical connectivity approaches. Voxel‐wise CMRO2 connectivity also exhibited spatial patterns consistent with four targeted resting‐state subnetworks: two association (i.e., frontoparietal and default mode) and two perceptual (i.e., auditory and occipital‐visual). These are the first findings to support the use of calibration‐derived CMRO2 low‐frequency fluctuations for detecting brain‐wide organizational properties typical of healthy participants. We discuss interpretations, advantages, and challenges in using calibration‐derived oxygen metabolism signals for examining the intrinsic organization of the human brain.
Triggers and alleviating factors for fatigue in Parkinson’s disease

Background Fatigue is common in Parkinson’s Disease, but few effective treatments are available for it. Exploring triggers and alleviating factors, including effects of exercise, could inform development of management strategies for Parkinson’s Disease fatigue. Objectives To examine triggers and alleviating factors for fatigue reported by individuals with Parkinson’s Disease, including perceived effect of exercise. Methods A sample of individuals with self-reported Parkinson’s Disease participating in the study Fox Insight were administered an online survey. The survey included the Parkinson's Fatigue Scale, the Physical Activity Scale for the Elderly, and multiple-choice questions about triggers and alleviating factors for fatigue. Results Among the sample of 1,029 individuals with Parkinson’s disease, mean (standard deviation (SD)) age was 67.4 (9.3) years, 44.0% were female. Parkinson’s Fatigue Scale score ranged from 16–80, mean (SD) 48.8 (16.2). Poor sleep (62.1%) and physical exertion (45.1%) were frequently reported triggers for fatigue. Coping strategies including sitting quietly (58.1%), laying down with or without napping, and exercise (20%). Physical Activity Scale for the Elderly scores were higher in those who reported that exercise alleviated their fatigue (49.7%) compared to those who reported it worsened their fatigue (18.9%) (mean (SD) score 158.5 (88.8) vs 119.8 (66.6) respectively; p<0.001). Conclusions Several behavioral and environmental triggers and alleviating strategies for fatigue are reported by individuals with Parkinson’s disease. Many feel that exercise alleviates fatigue, though the relationship between exercise and fatigue in Parkinson’s Disease appears complex. This exploratory study may inform future development of treatments or coping strategies for Parkinson’s disease fatigue.
Measuring prompt gamma-ray emissions from elements found in tissue during passive-beam proton therapy

Prompt gamma detection during proton radiotherapy for range verification purposes will need to operate in both active and passive treatment beam environments. This paper describes prompt gamma measurements using a high resolution 2″ × 2″ LaBr3 detector for a 200 MeV clinical passive-scatter proton beam. These measurements examine the most likely discrete prompt gamma rays emitted from tissue by detecting gammas produced in water, Perspex, carbon and liquid-nitrogen targets. Measurements were carried out at several positions around the depth corresponding to the location of the Bragg peak for water and Perspex targets in order to investigate prompt gamma emission as a function of depth along the beam path. This work also focused on validating the Geant4 Monte Carlo model of the passive-scatter proton beam line and LaBr3 detector by making a direct comparison between the simulated and experimental results. The initial prompt gamma measurements were overwhelmed by the high amount of scattered radiation when measuring at isocenter, shifting the target further downstream from the final collimator significantly reduced the background radiation. Prompt gamma peaks were then clearly identified for the water, Perspex and graphite targets. The developed Geant4 Monte Carlo model was able to replicate the measured prompt gamma ray energy spectra, including production for important photopeaks to within 10%, except for the 4.44 MeV peak from the water target, which had more than a 50% overestimation of the number of produced prompt gamma rays. The prompt gamma measurements at various depths correlated well with the proton dose deposition; the 4.44 and 6.13 MeV photopeak profiles peaked within 1 cm of the Bragg peak and the R50% value for the 3–7 MeV energy range predicted the proton range within 8 mm.
Prognostic impact of elevated fatty acid‐binding protein 1 in patients with heart failure

Few biomarkers to evaluate pathophysiological changes in extra‐cardiac tissues have been identified in patients with heart failure (HF). Fatty acid‐binding protein 1 (FABP), also known as liver FABP, is predominantly expressed in the liver. Circulating FABP1 has been proposed to be a sensitive biomarker for liver injury. However, little is known about the potential role of FABP1 as a biomarker for HF.
Comparison of serum and plasma SDMA measured with point-of-care and reference laboratory analysers: implications for interpretation of SDMA in cats

Objectives Symmetric dimethylarginine (SDMA) reflects the glomerular filtration rate (GFR) in people, dogs and cats. Initial assays used a liquid chromatography-mass spectroscopy (LC-MS) technique. A veterinary immunoassay has been developed for use in commercial laboratories and point-of-care (POC) laboratory equipment. This study sought to: determine POC and commercial laboratory (CL) SDMA assay imprecision; determine any bias of the POC assay compared with the CL assay; calculate observed total error of the POC assay and compare with analytical performance goals; and calculate dispersion and sigma metrics (σ) for POC and CL SDMA methods. Methods Two separate studies were performed that assessed: (1) imprecision, determined by evaluation of pooled feline plasma or serum; and (2) bias, assessed by comparing pooled plasma and serum results, as well as paired analyses of clinical samples from a single venepuncture measured using both analysers. Results were assessed in relation to performance goals. Dispersion and σ were calculated for both analysers. Results Bias between CL and POC analysers was consistent and high numbers of clinical results were outside performance goals across both studies. Imprecision was poor for both analysers for study 1 and improved to within quality goals for the CL analyser for study 2. Dispersion was at least 40%, meaning a measured result of 14 μg/dl represents a range of possible results from 8 μg/dl to 20 μg/dl. Conclusions and relevance Clinicians should be careful ascribing medical significance to small changes in SDMA concentration, as these may reflect analytical and biological variability. Analyser-specific reference intervals are likely required.
A-WEAR Bracelet for Detection of Hand Tremor and Bradykinesia in Parkinson’s Patients

Parkinson’s disease patients face numerous motor symptoms that eventually make their life different from those of normal healthy controls. Out of these motor symptoms, tremor and bradykinesia, are relatively prevalent in all stages of this disease. The assessment of these symptoms is usually performed by traditional methods where the accuracy of results is still an open question. This research proposed a solution for an objective assessment of tremor and bradykinesia in subjects with PD (10 older adults aged greater than 60 years with tremor and 10 older adults aged greater than 60 years with bradykinesia) and 20 healthy older adults aged greater than 60 years. Physical movements were recorded by means of an AWEAR bracelet developed using inertial sensors, i.e., 3D accelerometer and gyroscope. Participants performed upper extremities motor activities as adopted by neurologists during the clinical assessment based on Unified Parkinson’s Disease Rating Scale (UPDRS). For discriminating the patients from healthy controls, temporal and spectral features were extracted, out of which non-linear temporal and spectral features show greater difference. Both supervised and unsupervised machine learning classifiers provide good results. Out of 40 individuals, neural net clustering discriminated 34 individuals in correct classes, while the KNN approach discriminated 91.7% accurately. In a clinical environment, the doctor can use the device to comprehend the tremor and bradykinesia of patients quickly and with higher accuracy.
Antioxidant-Based Therapies in Male Infertility: Do We Have Sufficient Evidence Supporting Their Effectiveness?

Under physiological conditions, reactive oxygen species (ROS) play pivotal roles in various processes of human spermatozoa. Indeed, semen requires the intervention of ROS to accomplish different stages of its maturation. However, ROS overproduction is a well-documented phenomenon occurring in the semen of infertile males, potentially causing permanent oxidative damages to a vast number of biological molecules (proteins, nucleic acids, polyunsaturated fatty acids of biological membrane lipids), negatively affecting the functionality and vitality of spermatozoa. ROS overproduction may concomitantly occur to the excess generation of reactive nitrogen species (RNS), leading to oxidative/nitrosative stress and frequently encountered in various human pathologies. Under different conditions of male infertility, very frequently accompanied by morpho-functional anomalies in the sperm analysis, several studies have provided evidence for clear biochemical signs of damages to biomolecules caused by oxidative/nitrosative stress. In the last decades, various studies aimed to verify whether antioxidant-based therapies may be beneficial to treat male infertility have been carried out. This review analyzed the results of the studies published during the last ten years on the administration of low-molecular-weight antioxidants to treat male infertility in order to establish whether there is a sufficient number of data to justify antioxidant administration to infertile males. An analysis of the literature showed that only 30 clinical studies tested the effects of the administration of low-molecular-weight antioxidants (administered as a single antioxidant or as a combination of different antioxidants with the addition of vitamins and/or micronutrients) to infertile males. Of these studies, only 33.3% included pregnancy and/or live birth rates as an outcome measure to determine the effects of the therapy. Of these studies, only 4 were case–control studies, and only 2 of them found improvement of the pregnancy rate in the group of antioxidant-treated patients. Additionally, of the 30 studies considered in this review, only 43.3% were case–control studies, 66.7% enrolled a number of patients higher than 40, and 40% carried out the administration of a single antioxidant. Therefore, it appears that further studies are needed to clearly define the usefulness of antioxidant-based therapies to treat male infertility.
Robust Extrinsic Calibration of Multiple RGB-D Cameras with Body Tracking and Feature Matching

RGB-D cameras have been commercialized, and many applications using them have been proposed. In this paper, we propose a robust registration method of multiple RGB-D cameras. We use a human body tracking system provided by Azure Kinect SDK to estimate a coarse global registration between cameras. As this coarse global registration has some error, we refine it using feature matching. However, the matched feature pairs include mismatches, hindering good performance. Therefore, we propose a registration refinement procedure that removes these mismatches and uses the global registration. In an experiment, the ratio of inliers among the matched features is greater than 95% for all tested feature matchers. Thus, we experimentally confirm that mismatches can be eliminated via the proposed method even in difficult situations and that a more precise global registration of RGB-D cameras can be obtained.
Transcriptomic Analysis of the Anthocyanin Biosynthetic Pathway Reveals the Molecular Mechanism Associated with Purple Color Formation in Dendrobium Nestor

Dendrobium nestor is a famous orchid species in the Orchidaceae family. There is a diversity of flower colorations in the Dendrobium species, but knowledge of the genes involved and molecular mechanism underlying the flower color formation in D. nestor is less studied. Therefore, we performed transcriptome profiling using Illumina sequencing to facilitate thorough studies of the purple color formation in petal samples collected at three developmental stages, namely—flower bud stage (F), half bloom stage (H), and full bloom stage (B) in D. nestor. In addition, we identified key genes and their biosynthetic pathways as well as the transcription factors (TFs) associated with purple flower color formation. We found that the phenylpropanoid–flavonoid–anthocyanin biosynthesis genes such as phenylalanine ammonia lyase, chalcone synthase, anthocyanidin synthase, and UDP-flavonoid glucosyl transferase, were largely up-regulated in the H and B samples as compared to the F samples. This upregulation might partly account for the accumulation of anthocyanins, which confer the purple coloration in these samples. We further identified several differentially expressed genes related to phytohormones such as auxin, ethylene, cytokinins, salicylic acid, brassinosteroid, and abscisic acid, as well as TFs such as MYB and bHLH, which might play important roles in color formation in D. nestor flower. Sturdy upregulation of anthocyanin biosynthetic structural genes might be a potential regulatory mechanism in purple color formation in D. nestor flowers. Several TFs were predicted to regulate the anthocyanin genes through a K-mean clustering analysis. Our study provides valuable resource for future studies to expand our understanding of flower color development mechanisms in D. nestor.