Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Effects of Drinking Water Quality on Phagocyte Responses of Broiler Chickens Against Fungal and Bacterial Challenges

Combinatorial effects of xenobiotics in water on health may occur even at levels within current acceptable guidelines for individual chemicals. Herein, we took advantage of the sensitivity of the immune system and an avian animal model to examine the impact of xenobiotic mixtures on animal health. Water was derived from an underground well in Alberta, Canada and met guidelines for consumption, but contained a number of contaminants. Changes to chicken immunity were evaluated following acute (7d) exposure to contaminated water under basal and immune challenged conditions. An increase in resident macrophages and a decrease in CD8+ lymphocytes were identified in the abdominal cavity, which served as a relevant site where immune leukocytes could be examined. Subsequent intra-abdominal immune stimulation detected differential in vivo acute inflammatory responses to fungal and bacterial challenges. Leukocyte recruitment into the challenge site and activation of phagocyte antimicrobial responses were affected. These functional responses paralleled molecular changes in the expression for pro-inflammatory and regulatory genes. In all, this study primarily highlights dysregulation of phagocyte responses following acute (7d) exposure of poultry to contaminated water. Given that production food animals hold a unique position at the interface of animal, environmental and human health, this emphasizes the need to consider the impact of xenobiotic mixtures in our assessments of water quality.
Frequency-Aware Summarization of Resting-State fMRI Data

Many brain imaging modalities reveal interpretable patterns after the data dimensionality is reduced and summarized via data-driven approaches. In functional magnetic resonance imaging (fMRI) studies, such summarization is often achieved through independent component analysis (ICA). ICA transforms the original data into a relatively small number of interpretable bases in voxel space (referred to as ICA spatial components, or spatial maps) and corresponding bases in the time domain (referred to as time-courses of corresponding spatial maps) In this work, we use the word “basis” to broadly refer to either of the two factors resulting from the transformation. A precise summarization for fMRI requires accurately detecting co-activation of voxels by measuring temporal dependence. Accurate measurement of dependence requires a proper understanding of the underlying temporal characteristics of the data. One way to understand such characteristics is to study the frequency spectrum of fMRI data. Researchers have argued that information regarding the underlying neuronal activity might be spread over a range of frequencies as a result of the heterogeneous temporal nature of the neuronal activity, which is reflected in its frequency spectrum. Many studies have accounted for heterogeneous characteristics of the frequency of the signal by either directly inspecting the contents of frequency domain-transformed data or augmenting their analyses with such information. For example, studies on fMRI data have investigated brain functional connectivity by leveraging frequency-adjusted measures of dependence (e.g., when a correlation is measured as a function of frequency, as with “coherence”). Although these studies measure dependence as a function of frequency, the formulation does not capture all characteristics of the frequency-based dependence. Incorporating frequency information into a summarization approach would enable the retention of important frequency-related information that exists in the original space but might be lost after performing a frequency-independent summarization. We propose a novel data-driven approach built upon ICA, which is based on measuring dependence as a generalized function of frequency. Applying this approach to fMRI data provides evidence of existing cross-frequency functional connectivity between different areas of the brain.
Computational Oncology in the Multi-Omics Era: State of the Art

Cancer is the quintessential complex disease. As technologies evolve faster each day, we are able to quantify the different layers of biological elements that contribute to the emergence and development of malignancies. In this multi-omics context, the use of integrative approaches is mandatory in order to gain further insights on oncological phenomena, and to move forward toward the precision medicine paradigm. In this review, we will focus on computational oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. We will discuss the current roles of computation in oncology in the context of multi-omic technologies, which include: data acquisition and processing; data management in the clinical and research settings; classification, diagnosis, and prognosis; and the development of models in the research setting, including their use for therapeutic target identification. We will discuss the machine learning and network approaches as two of the most promising emerging paradigms, in computational oncology. These approaches provide a foundation on how to integrate different layers of biological description into coherent frameworks that allow advances both in the basic and clinical settings.
The Private Governance of Identity on the Silk Road

Long before the creation of blockchain platforms, the rise of personal computing, and Internet connectivity brought with it a digital, online dimension of the material world, leading to the socio-technical construct known as “digital identity. ” After the online discussion boards and emailing lists of the early 1990s, individuals started socializing via the Internet more predominantly using social networks. One specific type of platform links this online socializing and transacting to blockchain-based spaces: dark web marketplaces. Identified as second-generation cryptocommunities, dark web marketplaces deployed cryptography for the use of pseudonymous identity, for communication, but also currency. This paper explores two questions in this fascinating space: what was the role of identity on the Silk Road, and what governance lessons can be drawn from this illustration for the purpose of applying them to more recent cybercommunities such as Ethereum? The paper is structured as follows. The first part describes the Silk Road and sketches its essential characteristics. The second part looks at how individuals could become platform users on the Silk Road, by analyzing the contractual relationship between the Silk Road and an individual user based on the rights and obligations enshrined in the Silk Road terms of service (ToS). The third part critically reflects on arbitrariness as the main pitfall arising out of the private regulatory framework created by the Silk Road, and contributes to existing narratives surrounding the regulatory nature of code by proposing a code-as-procedure perspective for analyzing this regulatory framework. Part four concludes.
Habitat Features and Their Influence on the Restoration Potential of Marine Habitats in Europe

To understand the restoration potential of degraded habitats, it is important to know the key processes and habitat features that allow for recovery after disturbance. As part of the EU (Horizon 2020) funded MERCES project, a group of European experts compiled and assessed current knowledge, from both past and ongoing restoration efforts, within the Mediterranean Sea, the Baltic Sea, and the North-East Atlantic Ocean. The aim was to provide an expert judgment of how different habitat features could impact restoration success and enhance the recovery of marine habitats. A set of biological and ecological features (i.e., life-history traits, population connectivity, spatial distribution, structural complexity, and the potential for regime shifts) were identified and scored according to their contribution to the successful accomplishment of habitat restoration for five habitats: seagrass meadows, kelp forests, Cystoseira macroalgal beds, coralligenous assemblages and cold-water coral habitats. The expert group concluded that most of the kelp forests features facilitate successful restoration, while the features for the coralligenous assemblages and the cold-water coral habitat did not promote successful restoration. For the other habitats the conclusions were much more variable. The lack of knowledge on the relationship between acting pressures and resulting changes in the ecological state of habitats is a major challenge for implementing restoration actions. This paper provides an overview of essential features that can affect restoration success in marine habitats of key importance for valuable ecosystem services.
Events and Causal Mappings Modeled in Conceptual Spaces

The aim of the article is to present a model of causal relations that is based on what is known about human causal reasoning and that forms guidelines for implementations in robots. I argue for two theses concerning human cognition. The first is that human causal cognition, in contrast to that of other animals, is based on the understanding of the forces that are involved. The second thesis is that humans think about causality in terms of events. I present a two-vector model of events, developed by Gärdenfors and Warglien, which states that an event is represented in terms of two main components – the force of an action that drives the event, and the result of its application. Apart from the causal mapping, the event model contains representations of a patient, an agent, and possibly some other roles. Agents and patients are objects (animate or inanimate) that have different properties. Following my theory of conceptual spaces, they can be described as vectors of property values. At least two spaces are needed to describe an event, an action space and a result space. The result of an event is modeled as a vector representing the change of properties of the patient before and after the event. In robotics the focus has been on describing results. The proposed model also includes the causal part of events, typically described as an action. A central part of an event category is the mapping from actions to results. This mapping contains the central information about causal relations. In applications of the two-vector model, the central problem is how the event mapping can be learned in a way that is amenable to implementations in robots. Three processes are central for event cognition: causal thinking, control of action and learning by generalization. Although it is not yet clear which is the best way to model how the mappings can be learned, they should be constrained by three corresponding mathematical properties: monotonicity (related to qualitative causal thinking); continuity (plays a key role in activities of action control); and convexity (facilitates generalization and the categorization of events). I argue that Bayesian models are not suitable for these purposes, but some more geometrically oriented approach to event mappings should be used.
In situ Measuring Film-Depth-Dependent Light Absorption Spectra for Organic Photovoltaics

Organic donor–acceptor bulk heterojunction are attracting wide interests for solar cell applications due to solution processability, mechanical flexibility, and low cost. The photovoltaic performance of such thin film is strongly dependent on vertical phase separation of each component. Although film-depth-dependent light absorption spectra measured by non-in situ methods have been used to investigate the film-depth profiling of organic semiconducting thin films, the in situ measurement is still not well-resolved. In this work, we propose an in situ measurement method in combination with a self-developed in situ instrument, which integrates a capacitive coupled plasma generator, a light source, and a spectrometer. This in situ method and instrument are easily accessible and easily equipped in laboratories of the organic electronics, which could be used to conveniently investigate the film-depth-dependent optical and electronic properties.
Associations Between Factors Across Life and One-Legged Balance Performance in Mid and Later Life: Evidence From a British Birth Cohort Study

Introduction: Despite its associations with falls, disability, and mortality, balance is an under-recognized and frequently overlooked aspect of aging. Studies investigating associations between factors across life and balance are limited. Understanding the factors related to balance performance could help identify protective factors and appropriate interventions across the life course. This study aimed to: (i) identify socioeconomic, anthropometric, behavioral, health, and cognitive factors that are associated with one-legged balance performance; and (ii) explore how these associations change with age. Methods: Data came from 3,111 members of the MRC National Survey of Health and Development, a British birth cohort study. Multilevel models examined how one-legged standing balance times (assessed at ages 53, 60–64, and 69) were associated with 15 factors across life: sex, maternal education (4 years), paternal occupation (4 years), own education (26 years), own occupation (53 years), and contemporaneous measures (53, 60–64, 69 years) of height, BMI, physical activity, smoking, diabetes, respiratory symptoms, cardiovascular events, knee pain, depression and verbal memory. Age and sex interactions with each variable were assessed. Results: Men had 18.8% (95%CI: 13.6, 23.9) longer balance times than women at age 53, although this difference decreased with age (11.8% at age 60–64 and 7.6% at age 69). Disadvantaged socioeconomic position in childhood and adulthood, low educational attainment, less healthy behaviors, poor health status, lower cognition, higher body mass index (BMI), and shorter height were associated with poorer balance at all three ages. For example, at age 53, those from the lowest paternal occupational classes had 29.6% (22.2, 38.8) worse balance than those from the highest classes. Associations of balance with socioeconomic indicators, cognition and physical activity became smaller with age, while associations with knee pain and depression became larger. There were no sex differences in these associations. In a combined model, the majority of factors remained associated with balance. Discussion: This study identified numerous risk factors across life that are associated with one-legged balance performance and highlighted diverse patterns of association with age, suggesting that there are opportunities to intervene in early, mid and later life. A multifactorial approach to intervention, at both societal and individual levels, may have more benefit than focusing on a single risk factor.
Silicon Quantum Dots: Synthesis, Encapsulation, and Application in Light-Emitting Diodes

Silicon quantum dots (SiQDs) are semiconductor Si nanoparticles ranging from 1 to 10 nm that hold great applicative potential as optoelectronic devices and fluorescent bio-marking agents due to their ability to fluoresce blue and red light. Their biocompatibility compared to conventional toxic Group II-VI and III-V metal-based quantum dots makes their practical utilization even more attractive to prevent environmental pollution and harm to living organisms. This work focuses on their possible use for light-emitting diode (LED) manufacturing. Summarizing the main achievements over the past few years concerning different Si quantum dot synthetic methods, LED formation and characteristics, and strategies for their stabilization by microencapsulation and modification of their surface by specific ligands, this work aims to provide guidance en route to the development of the first stable Si-based light-emitting diodes.
Abnormal Cerebellar Development Is Involved in Dystonia-Like Behaviors and Motor Dysfunction of Autistic BTBR Mice

Motor control and learning impairments are common complications in individuals with autism spectrum disorder (ASD). Abnormal cerebellar development during critical phases may disrupt these motor functions and lead to autistic motor dysfunction. However, the underlying mechanisms behind these impairments are not clear. Here, we utilized BTBR T+ Itprtf/J (BTBR) mice, an animal model of autism, to investigate the involvement of abnormal cerebellar development in motor performance. We found BTBR mice exhibited severe dystonia-like behavior and motor coordination or motor learning impairments. The onset of these abnormal movements coincided with the increased proliferation of granule neurons and enhanced foliation, and Purkinje cells displayed morphological hypotrophy with increased dendritic spine formation but suppressed maturation. The migration of granule neurons seemed unaffected. Transcriptional analyses confirmed the differential expression of genes involved in abnormal neurogenesis and revealed TRPC as a critical regulator in proliferation and synaptic formation. Taken together, these findings indicate that abnormal cerebellar development is closely related to dystonia-like behavior and motor dysfunction of BTBR mice and that TRPC may be a novel risk gene for ASD that may participate in the pathological process of autistic movement disorders.
An Efficient Stochastic Linearisation Procedure for the Seismic Optimal Design of Passive Control Devices

The seismic response of structures is often enhanced by introducing passive control devices that can operate through the dissipation of the input energy or by modifying the dynamic characteristics of the main structure. The inherent non-linearities in the constitutive laws of some of them lead to computation difficulties and have limited the large-scale use and design of these devices. In this study, a procedure for the optimal design of multi passive control devices is proposed. The general case of linear Multi-Degree-Of-Freedom (MDOF) not-classically-damped structural systems controlled by Fluid Viscous Dampers (FVD) are investigated in a stochastic framework. The procedure consists of evaluation of the device optimal pattern by minimizing an objective function related to the dampers cost and subjected to a constraint on the structural behavior. For each configuration, the complete probabilistic characterization of the response is achieved by employing random vibration theory, Stochastic Linearisation (SL) techniques and a novel analytic model which provides closed-form PSD functions of earthquakes accelerations coherent to response spectra suggested by seismic codes. Exploiting this model, a procedure to speed up the Stochastic Linearisation technique by avoiding any numerical integration is proposed. Applications on MDOF building structures have been carried out to validate the proposed approach in terms of accuracy and reduction of the computational effort and to obtain optimal pattern of the passive control device coherently with the provisions of seismic building codes.
Unified Behavioral Scoring for Preclinical Models

Preclinical mental health research relies upon animal models, and whilst many encouraging advances are being made, reproducibility and translational relevance may be limited by sub-optimal testing or model choices. Animal behaviors are complex and test batteries should be designed to include their multifaceted nature. However, multiple behavioral testing is often avoided due to cost, availability or statistical rigor. Additionally, despite the disparity in the incidence of mental health problems between the sexes, a move toward reducing animal numbers could be a deterrent to including both male and female animals. The current study introduces a unified scoring system for specific behavioral traits with the aim of maximizing the use of all data generated whilst reducing the incidence of statistical errors. Female and male mice from two common background strains were tested on behavior batteries designed to probe multiple aspects of anxiety-related and social behavioral traits. Results for every outcome measure were normalized to generate scores for each test and combined to give each mouse a single unified score for each behavioral trait. The unified behavioral scores revealed clear differences in the anxiety and stress-related, and sociability traits of mice. Principle component analysis of data demonstrated significant clustering of animals into their experimental groups. In contrast, individual tests returned an ambiguous mixture of non-significant trends and significant effects for various outcome measures. Utilizing a range of behavioral measures and combining all outcome measure data to produce unified scores provides a useful tool for detecting subtle behavioral traits in preclinical models.
Efficacy of an Integrative Treatment for Tinnitus Combining Music and Cognitive-Behavioral Therapy—Assessed With Behavioral and EEG Data

Chronic tinnitus is a prevalent condition that could cause severe negative impact on an individual’s life. However, there has not been an established treatment due to a limited understanding of the pathophysiology of this multifarious disorder. In this study, we tested the efficacy of an integrative treatment, combining music therapy with cognitive-behavioral therapy (CBT). We collected three groups of patients receiving three different treatments: Music-CBT, music therapy and CBT. We used both subjective (i.e., questionnaires) and objective (i.e., resting-state EEG data) measurements to assess the behavioral and neural changes brought upon by the treatments. Analyses of the subjective measurements found a significant improvement of scale scores in Music-CBT and CBT, but not in the Music group. Analysis of the EEG data further showed increased powers in alpha and theta band after the Music-CBT treatment, and increased gamma power after CBT, whereas no significant difference was found for the music therapy. Further source localization analysis of alpha and theta changes in the Music-CBT group found that primary sources of the changes were located at auditory processing regions such as superior temporal gyrus, and higher emotional and cognitive processing regions such as ventromedial prefrontal cortex (vMPFC), lateral prefrontal cortex and parahippocampus. These results indicated that Music-CBT was effective in improving tinnitus symptoms on both a behavioral and neural level, which is more robust than the music therapy or CBT alone.
Expansion of frozen hybrids in the guppy ectoparasite, Gyrodactylus turnbulli

Hybridization is one of the major factors contributing to the emergence of highly successful parasites. Hybrid vigor can play an important role in this process, but subsequent rounds of recombination in the hybrid population may dilute its effects. Increased fitness of hybrids can, however, be frozen by asexual reproduction. Here, we identify invasion of a “frozen hybrid” genotype in natural populations of Gyrodactylus turnbulli, a facultatively sexual ectoparasitic flatworm that causes significant damage to its fish host. We re-sequenced genomes of these parasites infecting guppies from six Trinidad and Tobago populations, and found surprisingly high discrepancy in genome-wide nucleotide diversity between islands. The elevated heterozygosity on Tobago is maintained by predominantly clonal reproduction of hybrids formed from two diverged genomes. Hybridization has been followed by spread of the hybrids across the island, implying a selective advantage compared to native genotypes. Our results thus highlight that a single outcrossing event may be independently sufficient to cause pathogen expansion.