Miracle-dz/UniFAR-FTUs huggingface dataset:
Exenatide once weekly over 2 years as a potential disease-modifying treatment for Parkinson’s disease: protocol for a multicentre, randomised, double blind, parallel group, placebo controlled, phase 3 trial: The ‘Exenatide-PD3’ study

Introduction Parkinson’s disease (PD) is a common neurodegenerative disorder with substantial morbidity. No disease-modifying treatments currently exist. The glucagon like peptide-1 receptor agonist exenatide has been associated in single-centre studies with reduced motor deterioration over 1 year. The aim of this multicentre UK trial is to confirm whether these previous positive results are maintained in a larger number of participants over 2 years and if effects accumulate with prolonged drug exposure. Methods and analysis This is a phase 3, multicentre, double-blind, randomised, placebo-controlled trial of exenatide at a dose of 2 mg weekly in 200 participants with mild to moderate PD. Treatment duration is 96 weeks. Randomisation is 1:1, drug to placebo. Assessments are performed at baseline, week 12, 24, 36, 48, 60, 72, 84 and 96 weeks. The primary outcome is the comparison of Movement Disorders Society Unified Parkinson’s Disease Rating Scale part 3 motor subscore in the practically defined OFF medication state at 96 weeks between participants according to treatment allocation. Secondary outcomes will compare the change between groups among other motor, non-motor and cognitive scores. The primary outcome will be reported using descriptive statistics and comparisons between treatment groups using a mixed model, adjusting for baseline scores. Secondary outcomes will be summarised between treatment groups using summary statistics and appropriate statistical tests to assess for significant differences. Ethics and dissemination This trial has been approved by the South Central-Berkshire Research Ethics Committee and the Health Research Authority. Results will be disseminated in peer-reviewed journals, presented at scientific meetings and to patients in lay-summary format. Trial registration numbers NCT04232969, ISRCTN14552789.
Syndromic neurodevelopmental disorder associated with de novo variants in DDX23

The DEAD/DEAH box RNA helicases are a superfamily of proteins involved in the processing and transportation of RNA within the cell. A growing literature supports this family of proteins as contributing to various types of human disorders from neurodevelopmental disorders to syndromes with multiple congenital anomalies. This article presents a cohort of nine unrelated individuals with de novo missense alterations in DDX23 (Dead‐Box Helicase 23). The gene is ubiquitously expressed and functions in RNA splicing, maintenance of genome stability, and the sensing of double‐stranded RNA. Our cohort of patients, gathered through GeneMatcher, exhibited features including tone abnormalities, global developmental delay, facial dysmorphism, autism spectrum disorder, and seizures. Additionally, there were a variety of other findings in the skeletal, renal, ocular, and cardiac systems. The missense alterations all occurred within a highly conserved RecA‐like domain of the protein, and are located within or proximal to the DEAD box sequence. The individuals presented in this article provide evidence of a syndrome related to alterations in DDX23 characterized predominantly by atypical neurodevelopment.
Psychosis proneness, loneliness, and hallucinations in nonclinical individuals

Hallucinations occur along a continuum of normal functioning. Investigating the factors related to this experience in nonclinical individuals may offer important information for understanding the etiology of hallucinations in psychiatric populations. In this study we test the relationship between psychosis proneness, loneliness, and auditory hallucinations in a nonclinical sample using the White Christmas paradigm. Seventy-six undergraduate students participated in this study. We found that slightly more than half of our participants endorsed a hallucinatory experience during the White Christmas paradigm. However, we did not observe a relationship between the number of hallucinatory experiences and schizotypy, propensity to hallucinate, or loneliness. Moreover, there were no differences on these measures between individuals who reported hearing a hallucination during the White Christmas paradigm relative to those who did not. Thus, there may be other contextual factors not investigated in this study that might clarify the mechanism by which auditory hallucinations are experienced in a nonclinical population.
Intra-species sialic acid polymorphism in humans: a common niche for influenza and coronavirus pandemics?

ABSTRACT The ongoing COVID-19 pandemic has led to more than 159 million confirmed cases with over 3.3 million deaths worldwide, but it remains mystery why most infected individuals (∼98%) were asymptomatic or only experienced mild illness. The same mystery applies to the deadly 1918 H1N1 influenza pandemic, which has puzzled the field for a century. Here we discuss dual potential properties of the 1918 H1N1 pandemic viruses that led to the high fatality rate in the small portion of severe cases, while about 98% infected persons in the United States were self-limited with mild symptoms, or even asymptomatic. These variations now have been postulated to be impacted by polymorphisms of the sialic acid receptors in the general population. Since coronaviruses (CoVs) also recognize sialic acid receptors and cause severe acute respiratory syndrome epidemics and pandemics, similar principles of influenza virus evolution and pandemicity may also apply to CoVs. A potential common principle of pathogen/host co-evolution of influenza and CoVs under selection of host sialic acids in parallel with different epidemic and pandemic influenza and coronaviruses is discussed.
Canine Leishmaniasis Prevalence in the Slovenian Dog Population

Abstract Introduction Leishmaniasis is a life-threatening zoonosis of which dogs are the major reservoir and sandflies are the vectors. Until now, the prevalence of canine leishmaniasis (CanL) in the Slovenian dog population was unknown. Material and Methods Epidemiological data, eye swabs and blood samples were taken from 465 dogs born in Slovenia and older than one year. Commercial ELISA kits and real-time PCR were used. For ELISA-positive samples, an immunofluorescence antibody test (IFAT) was performed. Descriptive statistics were used to characterise the samples. The one-sample nonparametric chi-square test was used to test whether the categories of a variable were equally distributed. Results A 59.9% proportion of the recruited dogs had travelled to endemic regions and 62.1% of them had not been protected by insect repellents. Skin symptoms that might be CanL-related were described in 109 of the dogs’ histories (23.4%), inappetence and/or weight loss in 25 (5.4%), and anaemia, intermittent fever, and/or lymphadenopathy in 19 (4.1%). At the time of recruitment, all dogs were asymptomatic. All samples were PCR negative, nine (1.9%) were ELISA positive, but none were IFAT positive. Five of the nine ELISA-positive dogs were non-travellers. Conclusion We conclude that the seroprevalence of canine leishmaniasis of 1.9 % in the autochthonous Slovenian dog population may pose a risk of endemic spread of the disease.
Thermal and Rheological Characteristics of Biobased Carbon Fiber Precursor Derived from Low Molecular Weight Organosolv Lignin

In the present work, electrospinnability as well as thermal, rheological, and morphological characteristics of low molecular weight hardwood organosolv lignin, as a potential precursor for carbon fiber, was investigated. Submicromter biobased fibers were electrospun from a wide range of polymer solutions with different ratios of organosolv lignin to polyacrylonitrile (PAN). Rheological studies were conducted by measuring viscosity, surface tension, and electrical conductivity of hybrid polymer solutions, and used to correlate electrospinning behavior of solutions with the morphology of the resultant electrospun composite fibers. Using scanning electron microscopy (SEM) images, the solutions that led to the formation of bead-free uniform fibers were found. Differential scanning calorimetry (DSC) analysis revealed that lignin-based fibers enjoy higher decomposition temperatures than that of pure PAN. Thermal stability of the lignin-based fibers was investigated by thermogravimetric analysis (TGA) indicating.
HLA–B*08 Identified as the Most Prominently Associated Major Histocompatibility Complex Locus for Anti–Carbamylated Protein Antibody–Positive/Anti–Cyclic Citrullinated Peptide–Negative Rheumatoid Arthritis

Previously, only the HLA–DRB1 alleles have been assessed in rheumatoid arthritis (RA). The aim of the present study was to identify the key major histocompatibility complex (MHC) susceptibility factors showing a significant association with anti–carbamylated protein antibody–positive (anti‐CarP+) RA.
Introduction to The Special Section on Bias and Fairness in AI

Fairness in Artificial Intelligence rightfully receives a lot of attention these days. Many life-impacting decisions are being partially automated, including health-care resource planning decisions, insurance and credit risk predictions, recidivism predictions, etc. Much of work appearing on this topic within the Data Mining, Machine Learning and Artificial Intelligence community is focused on technological aspects. Nevertheless, fairness is much wider than this as it lies at the intersection of philosophy, ethics, legislation, and practical perspectives. Therefore, to fill this gap and bring together scholars of these disciplines working on fairness, the first workshop on Bias and Fairness in AI was held online on September 18, 2020 at the ECML-PKDD 2020 conference. This special section includes six articles presenting different perspectives on bias and fairness from different angles.
Automatic Evaluation of Difficult-to-Recognize Characters for Efficient Transcription of Japanese Cursive Characters

In this study, we approached Japanese cursive character (kuzushiji) recognition using machine learning to improve the efficiency of their transcription process. In particular, we discussed methods that automatically distinguish difficult-to-recognize characters or characters that were not included in the training, and put them on hold as unknown characters. We analyzed two methods that deferred recognition of characters: In the first method, characters with low confidence values obtained from the recognition model were put on hold as unknown characters. In the second method, we trained a “miscellaneous class” that combined multiple character classes and deferred the recognition of characters if they were recognized as belonging to the “miscellaneous class. ” Experiments showed that by narrowing down the characters to be recognized, a recognition rate of more than 90% was achieved for over 1,500 character classes, confirming the usefulness of temporarily deferring recognition during the transcription process.
Horse Breed Classification Based on Transfer Learning

Expert identification of horse breeds is an age-old task that can now be identified using genetic techniques. However, neither approach is cheap nor efficient. The automatic classification of horse breeds by computer vision is an effective solution. In this paper, we solve this task by proposing a novel method using transfer learning of pre-trained deep convolution neural networks architectures. The pre-trained convolutional neural networks include MobilenetV2, Mobilenet, Xception, VGG16, and VGG19. We use the keras deep learning framework, and train these deep convolution neural networks for transfer learning, which overcomes the problem of small amount of data in the early stage. An extensive experimental study on various horse breeds datasets shows that our method obtains an average accuracy rate of automatic classification of horse breeds to 89.34%, which has obvious advantage over other deep convolutional neural network models such as xception, vgg16, vgg19 and self-made convolutional neural network.
Dynamic Task Allocation based on Individual Abilities - Experiences from Developing and Operating an Inclusive Assembly Line for Workers With and Without Disabilities

Digital assistive systems, enable workers with disabilities to perform complex industrial work. However, the previously presented systems considered only a single workplace and a single user. This paper presents an assembly line that enables a joint processing of complex tasks by multiple workers with and without disabilities. The aim was to investigate the use of interaction technologies such as in-situ projections and hand-tracking to enable the processing of complex assembly tasks by work teams with highly heterogeneous abilities. The developed assembly line assists users and coordinates the joint work by distributing single assembly steps to workers based on the individual workers' abilities. Besides presenting the concept and implementation of the assembly line, we report our findings after six months of operation. Our results indicate that using the assistive assembly line has positive impacts, such as increased satisfaction and independence of the workers combined with a higher productivity.
TPJF: Machine Learning Based Intelligent Prediction of Preference for Japanese Food

With the development of the catering industry in China in recent years, foreign cuisine, such as Japanese cuisine, has become a significant part of some people's daily lives. However, for Japanese restaurants, there has not been a widespread and reliable way to target at advertising to those interested in Japanese food, or for consumers to determine whether they are interested in Japanese food. This paper proposes an intelligent and novel prediction method, called TPJF – Targeting Preference for Japanese Food, to determine people's attitude towards Japanese food. Our method is proposed based on the dataset obtained by real world questionnaires, which are about participant fillers’ basic dietary habits and personal information. We apply data mining techniques on the dataset. During the evaluation experiments, machine learning models such as DT, KNN, GBM, RF, ANN, SVM and NB are investigated to achieve such a multi-class classification. The experimental results show that RF offers the best accuracy of 76.26% and the best F1-score of 77.67%. RF also provides the optimal effective accuracy of 74.29% for advertising, which is defined by this paper.
Engineering Model-Based Software Testing of WIMP Interactive Applications

The goal of software testing is to detect defects with the objective of removing them at a later stage in the development process. Interactive software development follows the User Centered Design approach that promotes continuous involvement of users both at design and evaluation phases. This process is meant to produce usable interactive software by gathering functional and non-functional requirements related to both user needs and context of use. However, taking into account these potentially very-complex-to-implement requirements increases the complexity of the software that is likely, without appropriate methods and tools, to encompass a large number of defects. One of the limitations of UCD approaches is that it provides no guidance on the engineering of the interactive application, which thus usually embeds numerous defects resulting in failures at the origin of user frustrations and performance drops. Even though a classification of interactive application defects has been proposed, interactive application testers remain only superficially supported in detecting them. This paper defines a model-based approach to engineer the testing activity for interactive applications. It proposes a process that bridges the gap between UCD artefacts and interactive software implementation by the production of a dedicated formal model exploited for testing purposes only. The application of the process is demonstrated on an interactive cockpit WIMP application. Finally, threats to validity (capability of the approach to detect defects and to ensure an acceptable coverage testing of the interactive application) are addressed by a longitudinal study on 61 variants of a simple application developed by 61 different developers.
Unleashing a novel function of Endonuclease G in mitochondrial genome instability

Having its own genome makes mitochondria a unique and semiautonomous organelle within cells. Mammalian mitochondrial DNA (mtDNA) is double-stranded closed circular molecule of about 16 kb coding 37 genes. Mutations, including deletions in the mitochondrial genome can culminate in different human diseases. Mapping of the deletion junctions suggests that the breakpoints are generally seen at hotspots. ‘9-bp deletion’ (8271-8281), seen in the intergenic region of cytochrome c oxidase II/tRNALys, is the most common mitochondrial deletion. While it is associated with several diseases like myopathy, dystonia, and hepatocellular carcinoma, it has also been used as an evolutionary marker. However, the mechanism responsible for its fragility is unclear. In the current study, we show that Endonuclease G, a mitochondrial nuclease responsible for nonspecific cleavage of nuclear DNA during apoptosis, can induce breaks at sequences associated with ‘9-bp deletion’, when it is present on a plasmid or in the mitochondrial genome. Through a series of in vitro and intracellular studies, we show that Endonuclease G binds to G-quadruplex structures formed at the hotspot and induces DNA breaks. Besides, we reconstitute the whole process of ‘9-bp deletion’ using purified Endonuclease G to induce breaks in mtDNA, followed by mitochondrial extract-mediated DSB repair and establish that microhomology-mediated end joining is responsible for the generation of mtDNA deletion. Finally, we show that the whole process is regulated by different stress conditions, which may modulate release of Endonuclease G to the mitochondrial matrix. Therefore, we uncover a new role for Endonuclease G in generating deletions, which is dependent on the formation of G4 DNA within the mitochondrial genome. Thus, in this study we identify a novel property of Endonuclease G, besides its role in apoptosis, and the recently described ‘elimination of paternal mitochondria during fertilization.
Expansion and contraction of resource allocation in sensory bottlenecks

Topographic sensory representations often do not scale proportionally to the size of their input regions, with some expanded and others contracted. In vision, the foveal representation is magnified cortically, as are the fingertips in touch. What principles drive this allocation, and how should receptor density, e.g. the high innervation of the fovea or the fingertips, and stimulus statistics, e.g. the higher contact frequencies on the fingertips, contribute? Building on work in efficient coding, we address this problem using linear models that maximize information transmission through decorrelation. We introduce a sensory bottleneck to impose constraints on resource allocation and derive the optimal neural allocation. We find that bottleneck width is a crucial factor in resource allocation, inducing either expansion or contraction. Both receptor density and stimulus statistics affect allocation and jointly determine convergence for wider bottlenecks. Furthermore, we show a close match between the predicted and empirical cortical allocations in a well-studied model system, the star-nosed mole. Overall, our results suggest that the strength of cortical magnification depends on resource limits.
Human HELB is a processive motor protein that catalyzes RPA clearance from single-stranded DNA

Human HELB is a poorly-characterised helicase suggested to play both positive and negative regulatory roles in DNA replication and recombination. In this work, we used bulk and single molecule approaches to characterise the biochemical activities of HELB protein with a particular focus on its interactions with RPA and RPA-ssDNA filaments. HELB is a monomeric protein which binds tightly to ssDNA with a site size of ∼20 nucleotides. It couples ATP hydrolysis to translocation along ssDNA in the 5′-to-3′ direction accompanied by the formation of DNA loops and with an efficiency of 1 ATP per base. HELB also displays classical helicase activity but this is very weak in the absence of an assisting force. HELB binds specifically to human RPA which enhances its ATPase and ssDNA translocase activities but inhibits DNA unwinding. Direct observation of HELB on RPA nucleoprotein filaments shows that translocating HELB concomitantly clears RPA from single-stranded DNA.
Growth hormone transgenesis affects thermal tolerance in zebrafish (Danio rerio)

In fish, growth hormone (GH)-transgenesis may modify physiological mechanisms of adaptation when challenged by biotic and abiotic stressors. Thus, we evaluated whether GH overexpression can alter the thermal tolerance of adult and juvenile GH-transgenic zebrafish (Danio rerio). This study compared the thermal tolerance in non-transgenic (NT) and GH-transgenic (T) zebrafish exposed to 13 °C, 39 °C, or 28 °C (control) for 96 h. Mortality rate was checked every 12 h in juvenile (8 week-old) and adult males (6 month-old). Exposure to different temperatures revealed that GH overexpression increases the tolerance of transgenic juveniles exposed to 13 °C and diminishes the tolerance of juveniles and adults, when exposed to 39 °C. Additionally, we have analyzed transcriptional expression from the heat shock proteins (HSPs), which are mainly involved in the thermal tolerance mechanism. The mRNA level analysis results revealed that, under controlled conditions (28 °C), GH-transgenesis upregulates the expression of hsp47, hsp70, hsp90a and heat shock transcription factor (hsf1a) in transgenic juveniles, although the same result was not observed in transgenic adults. Exposure to low temperature did not alter the expression of any analyzed gene, both in adults and in juveniles. Exposure to 39 °C decreased the expression of all genes analyzed, in GH-transgenic adults. Furthermore, the HSP expression pattern was analyzed via hierarchical clustering. This analysis revealed two major clusters illustrating the dependency of gene changes related to age. These results indicate that the GH overexpression can alter thermal tolerance of fish, depending of age and temperature. Highlights - GH-transgenesis increased the survival rate of juveniles at low temperature; - High temperature is more lethal for juvenile ande adult GH-transgenic zebrafish; - GH-transgenesis increased expression of hsf1a, hsp47, and hsp70 genes in juvenile zebrafish; - hsf1a, hsp47, hsp70, hsp90a, and hsp90b genes expression is diminished in adult zebrafish GH-transgenesis exposure at high temperature.
Model Polyelectrolyte Gels Synthesized by End-Linking of Tetra-Arm Polymers with Click Chemistry: Synthesis and Mechanical Properties

A series of poly(sodium acrylate) gels was synthesized via end-linking reaction between tetra-arm poly(tert-butyl acrylate)s by copper-catalyzed azide–alkyne cycloaddition followed by deprotection of tert-butyl group and neutralization. Characterization of the gels using gravimetry, IR measurement, and stretching test revealed that they have only small amounts of sol fractions, dangling chains, and trapped entanglements. The relationship between polymer weight fraction (ϕe) and shear modulus (G′) at equilibrium swelling in saline was expressed as G′ ∝ ϕe 2.5. The power index (2.5) was comparable with the theoretical value for nonionic gels swollen in good solvents (2.3). The relationship between G′ and ϕe was superior to that of poly(sodium acrylate) gels synthesized by conventional radical copolymerization. The difference may be partly attributed to the difference in the ratio of chemical cross-links to trapped entanglements.