Miracle-dz/UniFAR-FTUs huggingface dataset:
Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in mice

Deciphering the genetic bases of behavioural traits is essential to understanding how they evolve and contribute to adaptation and biological diversification, but it remains a substantial challenge, especially for behavioural traits with polygenic architectures. In this study, we developed a population genomics approach coupled with functional predictions to address the evolution and genetic basis of olfactory-based assortative mate preferences in the house mouse, suspected to have evolved as a response to selection against hybridisation. We used whole genome resequencing data and the C2 statistic of the program BayPass, which contrasts allele frequencies corrected for population structure, to characterize genetic differentiation between sets of populations with strong contrast in behaviour (expressing or not assortative mate preferences) and we identified some regions of the genome showing the expected significant and consistent association with behavioural divergence. A series of Olfactory and Vomeronasal Receptor genes, among the most differentiated genomic regions and in line with functional predictions, stand out as the prime candidates underlying this olfactory-based behavioural divergence. These genes form large gene clusters in the genome, with two main candidate clusters extending up to 1.8 Mb. Variant analyses indicate a potential dual role of regulatory and protein-coding changes in the evolution of choosiness. This study shows that combining expectations on the genomic patterns of divergence with functional expectations represents a promising route to unravelling the genetic architecture of complex trait variation and provides novel insights into the role of olfactory and vomeronasal receptors in mammal adaptation and speciation.
Oral oxycodone self-administration leads to features of opioid addiction in male and female mice

Use of prescription opioids, particularly oxycodone is an initiating factor driving the current opioid epidemic. There are several challenges with modeling oxycodone abuse. First, prescription opioids including oxycodone are orally self-administered and have different pharmacokinetics and dynamics than morphine or fentanyl which have been more commonly used in rodent research. This oral route of administration determines the pharmacokinetic profile, which then influences the establishment of drug-reinforcement associations in animals. Moreover, the pattern of intake and the environment in which addictive drugs are self-administered are critical determinants of the levels of drug intake, of behavioral sensitization, and of propensity to relapse behavior. These are all important considerations when modeling prescription opioid use, which is characterized by continuous drug access in familiar environments. Thus, to model features of prescription opioid use and the transition to abuse, we designed an oral, homecage-based oxycodone self-administration paradigm. Mice voluntarily self-administer oxycodone in this paradigm without any taste modification such as sweeteners, and the majority exhibit preference for oxycodone, escalation of intake, physical signs of dependence, and reinstatement of seeking after withdrawal. In addition, a subset of animals demonstrate drug taking that is resistant to aversive consequences. This model is therefore translationally relevant and useful for studying the neurobiological substrates of prescription opioid abuse.
Epigenetic age acceleration is associated with oligodendrocyte proportions in MSA and control brain tissue

Aims Epigenetic clocks are widely applied as surrogates for biological age in different tissues and/or diseases, including several neurodegenerative diseases. Despite white matter (WM) changes often being observed in neurodegenerative diseases, no study has investigated epigenetic ageing in white matter. Methods We analysed the performances of two DNA methylation-based clocks, DNAmClockMulti and DNAmClockCortical, in post-mortem WM tissue from multiple subcortical regions and the cerebellum, and in oligodendrocyte-enriched nuclei. We also examined epigenetic ageing in control and multiple system atrophy (MSA) (WM and mixed WM and grey matter), as MSA is a neurodegenerative disease comprising pronounced WM changes and α-synuclein aggregates in oligodendrocytes. Results Estimated DNA methylation (DNAm) ages showed strong correlations with chronological ages, even in WM (e.g., DNAmClockCortical, r = [0.80-0.97], p<0.05). However, performances and DNAm age estimates differed between clocks and brain regions. DNAmClockMulti significantly underestimated ages in all cohorts except in the MSA prefrontal cortex mixed tissue, whereas DNAmClockCortica tended towards age overestimations. Pronounced age overestimations in the oligodendrocyte-enriched cohorts (e.g., oligodendrocyte-enriched nuclei, p=6.1×10-5) suggested that this cell-type ages faster. Indeed, significant positive correlations were observed between estimated oligodendrocyte proportions and DNAm age acceleration estimated by DNAmClockCortica (r>0.31, p<0.05), and similar trends with DNAmClockMulti. Although increased age acceleration was observed in MSA compared to controls, no significant differences were observed upon adjustment for possible confounders (e.g., cell-type proportions). Conclusions Our findings show that oligodendrocyte proportions positively influence epigenetic age acceleration across brain regions and highlight the need to further investigate this in ageing and neurodegeneration.
A spherical harmonics-based framework for representing steady-state shifts in neuron models induced by weak electric fields

Objective: We provide a systematic framework for the quantification of the effect of externally applied weak electric fields on realistic neuron compartment models as captured by physiologically relevant quantities such as the membrane potential or transmembrane current as a function of the orientation of the field. Approach: We define a response function as the steady-state change of the membrane potential induced by a canonical external field of 1 V/m as a function of its orientation. We estimate the function values through simulations employing reconstructions of the rat somatosensory cortex from the Blue Brain Project. The response of different cell types is simulated using the NEURON simulation environment. We represent and analyze the angular response as an expansion in spherical harmonics. Main results: We report membrane perturbation values comparable to those in the literature, extend them to different cell types, and provide their profiles as spherical harmonic coefficients. We show that in resting condition, responses are dominated by their dipole terms (l = 1), in agreement with experimental findings and compartment theory. Indeed, we show analytically that for a passive cell only the dipole term is nonzero. However, for states other than resting, other terms, while small, appear relevant. In particular, we show how l = 0 and l = 2 terms can modify the function to induce asymmetries in the response. Significance: This work provides a practical framework for the realistic representation of the effects of weak electric fields on different neuron types and their main regions—an important milestone for the development of microand mesoscale models and the optimization of brain stimulation solutions.
The influence of the importance of event factors on meeting planner satisfaction: A case study of a theme park event business

This paper presents data from a research project aimed at identifying how important the different event factors are to the visiting meeting planners and how this might influence guest satisfaction. The focus for the researchers was to get an overall picture of the meeting planners’ satisfaction and to identify the areas which needed more focus, in order to improve future business. This was done by sending an online survey to 25 regularly visiting meeting planners. This survey asked the meeting planners to rate event factors on their importance, and the satisfaction level regarding a certain planned event on service and physical factors. The event factors were derived from both the academic literature and the experience of the company. The survey was split into two parts. First, the factors needed to be rated in terms of importance, and second on satisfaction. Seven meeting planners filled out the survey. Nevertheless the findings showed that friendliness and politeness scored highest on importance of all factors. Also empathy, reliability, responsiveness, tangibles, and food quality scored high on importance. Improvement areas concerning satisfaction are “consultation” and “reachability” during the planning process, and “cleanliness of meeting rooms”. Further investigation is needed for the factors of “lighting, climate and soundproofing of meeting rooms”, “size and number of facilities”, “presentation, variety and quantity of food”. and why customers actually choose a theme park for their event.
Metabolic reprogramming in Rheumatoid Arthritis Synovial Fibroblasts: A hybrid modeling approach

Rheumatoid Arthritis (RA) is an autoimmune disease characterized by a highly invasive pannus formation consisting mainly of synovial fibroblasts (RASFs). This pannus leads to cartilage, bone and soft tissue destruction in the affected joint. RASFs’ activation is associated with metabolic alterations resulting from dysregulation of extracellular signals transduction and gene regulation machinery. Deciphering the intricate mechanisms at the origin of this metabolic reprogramming may provide significant insight into RASFs’ involvement in RA’s pathogenesis and offer new therapeutic strategies. Qualitative and quantitative dynamic modeling can address some of these features, but hybrid models represent a real asset in their ability to span multiple layers of biological machinery. This work presents the first hybrid RASF model: the combination of a cell-specific qualitative regulatory network with a global metabolic network. The automated framework for hybrid modeling exploits the regulatory network’s trap-spaces as additional constraints on the metabolic networks. Subsequent flux balance analysis allows assessment of RASFs’ regulatory outcomes’ impact on their metabolic flux distribution. The hybrid RASF model simulates the experimentally observed metabolic reprogramming induced by signaling and gene regulation in RASFs. Simulations also enable further hypotheses on the potential reverse Warburg effect in RA. RASFs may undergo metabolic reprogramming to turn into “metabolic factories”, producing high levels of energy-rich fuels and nutrients for neighboring demanding cells through the crucial role of HIF1. Author Summary We successfully built the first large-scale hybrid dynamical model for human Rheumatoid Arthritis Synovial Fibroblasts (RASFs) including signaling, gene regulation and metabolism. We used a state-of-the-art molecular map for upstream signaling and gene regulation, the tool CaSQ to infer a large-scale Boolean model, and a genome-scale metabolic model. Trap-spaces of the Boolean asynchronous model were used to infer additional metabolic constraints on the metabolic network for subsequent flux balance analysis. This method allowed us to study the impact of various regulatory initial conditions on RASFs’ metabolic fluxes distribution. Our model successfully reproduces the metabolic reprogramming of RASFs which shift their ATP production from oxidative pathways to glycolysis, highlighting the key role of HIF1 in this process. Our findings allow us to hypothesize a reverse Warburg relationship occurring between RASFs and other RA joint cells. Similarly to tumor microenvironment’s fibroblasts, RASFs would undergo a metabolic switch and reprogram their metabolism to adapt to their hypoxic environment and provide crucial metabolic intermediates to neighboring cells to sustain their inflammatory activity.
Ornamental Algebras, Algebraic Ornaments

This paper re-examines the presentation of datatypes in dependently typed languages, addressing in particular the issue of what it means for one datatype to be in various ways more informative than another. Informal human observations like ‘lists are natural numbers with extra decoration’ and ‘vectors are lists indexed by length’ are expressed in a first class language of ornaments — presentations of fancy new types based on plain old ones — encompassing both decoration and, in the sense of Tim Freeman and Frank Pfenning (1991), refinement. Each ornament adds information, so it comes with a forgetful function from fancy data back to plain, expressible as the fold of its ornamental algebra: lists built from numbers acquire the ‘length’ algebra. Conversely, each algebra for a datatype induces a way to index it — an algebraic ornament. The length algebra for lists induces the construction of the paradigmatic dependent vector types. Dependent types thus provide not only a new ‘axis of diversity’ — indexing — for data structures, but also new abstractions to manage and exploit that diversity. In the spirit of ‘the new programming’ (McBride & McKinna, 2004), the engineering of coincidence is replaced by the propagation of consequence.
Inseminação artificial transcervical em ovinos

The growth of sheep flocks in the Brazilian Northeast in the last years has conducted technicians and sheep owners to improvement, adaptation and utilization of the techniques that allow substantial rise in productivity. This procedure is justified by the relatively fast return of invested capital, moreover, the good price of its subproducts, as an incentive of this agribusiness development. Reproductive biotechniques, especially artificial insemination (AI), allows the rapid dissemination of superior genetic patrimony, when correctly worked out. However, anatomic characteristics of the ovine cervix, associated lo the high sensibility of the ovine semen to the freezing process makes the utilization of the transcervical artificial insemination technique difficult, when compared lo laparoscopy, associated lo theoccurrenceoflowfertility.Dilferencesrelaledlolhelechniquesandlhe moment of artificial insemination, the quality of the used semen, the semen deposition place, age and breed of the females substantially influence the results. The overcoming of these factors, which negatively permeable the dissemination of the technique, can represent a substantial advance in the quality of commercialized ovine products.
Construction of Efficient Mixed-Level Fractional Factorial Designs

Mixed-level factorial experimental designs involve factors with different numbers of levels. Full factorial designs require runs at all possible combinations of the factor levels. As the number of factors and/or factor levels increases, the total number of experiments increases dramatically. As a result, interest has focused on developing orthogonal or near-orthogonal mixed-level fractional factorial designs. Currently existing mixed-level designs are all balanced. However, relaxing the requirement of balance may result in a reduced number of experimental runs in practice. The objective of this paper is to develop mixed-level fractional factorial designs with economical run sizes that are as nearly balanced and orthogonal as possible. A new criterion is developed to assess the degree of near-balance for comparing and constructing designs. A modified J2-optimality criterion is used for evaluating design near orthogonality. These criteria are combined and used to assess different design alternatives. Three algorithms are then compared and used to build designs with desirable combinations of near balance and near orthogonality.
Variation in Thermal Tolerance of the Giant Kelp’s Gametophytes: Suitability of Habitat, Population Quality or Local Adaptation?

The giant kelp Macrocystis pyrifera is a cosmopolitan species of cold-temperate coasts. Its South-American distribution ranges from Peru to Cape Horn and Argentina, encompassing a considerable temperature gradient, from 3 to 20°C. Temperature is known to strongly affect survival, growth and reproduction of many kelp species, and ongoing global warming is already eroding their range distribution. Their response to thermal variability was shown to vary among genetically differentiated regions and populations, suggesting a possible adaptive divergence in thermal tolerance traits. This study aimed at testing the existence of local adaptation in the giant kelp, in regions separated by up to 4000km and strong thermal divergence. Two complementary experiments mimicked reciprocal transplants through a common garden approach, each habitat being represented by a given temperature corresponding to the regional average of the sampled populations. Several proxies of fitness were measured in the haploid stage of the kelp, and sympatric versus allopatric conditions (i.e. individuals at the temperature of their region of origin versus in a different temperature and versus individuals from other regions in that temperature) were compared. Additionally, a heat wave at 24°C was applied to measure the tolerance limits of these gametophytes. A significant interaction between experimental temperature and region of origin revealed that temperature tolerance varied among regions. However, depending on the fitness parameter measured, high latitude populations from the sub-Antarctic region were not always less heat resilient than populations from the warmer region of Peru. Even at 24°C, a temperature that is exceptionally reached in the southernmost part of the kelp’s natural habitat, all the gametophytes survived, although with strong differences in other traits among regions and populations within regions. This large range of temperature tolerance supports the idea of kelp gametophytes being a resistant stage. Finally, local adaptation sensu stricto was not detected. Fertility was more influenced by the geographic origin than by temperature, with possible effects of marginal conditions at the extremes of the distribution range. The latter results also suggest that stochastic dynamics such as genetic drift restricts adaptive processes in some populations of M. pyrifera.
Microplastics in commercial clams from the intertidal zone of the South Yellow Sea, China

Clams are commercially important species and are a vital component of the offshore ecosystem. Investigations on microplastics (MPs) in clams have attracted public attention recently, for its ecological and food safety risks. However, knowledge gaps still exist regarding MPs in commercial clams from the intertidal zone of the South Yellow Sea (SYS), China, an important clam habitat. In this study, to investigate the distribution of MPs in clams of the SYS, four species of clams were collected from nine sites in different tide zones (high, middle, and low tides) in three coastal areas (Nantong, Yancheng and Lianyungang). The abundance and characteristics of MPs, including size, shape, color and composition, were determined using microscope and micro-Fourier transform infrared (FTIR) spectroscopy. Furthermore, to evaluate the MPs purification ability of clams, the abundance of MPs in various tissues was examined by microscopic observation after being purified in filtered seawater for 72 h. The results showed that there were significant differences in the abundance of MPs in clams from different regions, with the most serious pollution in the high-tide zone. Moreover, the lowest MPs abundance was found in Yancheng (5.07 ± 2.73 items/individual, 1.16 ± 0.78 items/g), while Lianyungang was found with the most abundant MPs (7.52 ± 2.68 items/individual, 3.94 ± 3.00 items/g). The size of MPs in Ruditapes philippinarum (1,329.99 μm) was significantly higher than in other species. The MPs in clams were characterized by fiber in shape, black-grey, blue-green and white-transparent in color and rayon in composition. Moreover, it was found that the MPs originally present in various tissues tended to migrate and accumulate into the mantle of the clam during depuration, and after 72 h of depuration, removing the mantle could reduce nearly half amount of microplastics in clams. Overall, our study revealed the microplastic distribution in commercial clams from the intertidal zone of the SYS and provided suggestions for the safety of aquatic production.
Machine learning-based clustering in cervical spondylotic myelopathy patients to identify heterogeneous clinical characteristics

Background Anterior cervical decompression and fusion can effectively treat cervical spondylotic myelopathy (CSM). Accurately classifying patients with CSM who have undergone anterior cervical decompression and fusion is the premise of precision medicine. In this study, we used machine learning algorithms to classify patients and compare the postoperative efficacy of each classification. Methods A total of 616 patients with cervical spondylotic myelopathy who underwent anterior cervical decompression and fusion were enrolled. Unsupervised machine learning algorithms (UMLAs) were used to cluster subjects according to similar clinical characteristics. Then, the results of clustering were visualized. The surgical outcomes were used to verify the accuracy of machine learning clustering. Results We identified two clusters in these patients who had significantly different baseline clinical characteristics, preoperative complications, the severity of neurological symptoms, and the range of decompression required for surgery. UMLA divided the CSM patients into two clusters according to the severity of their illness. The repose to surgical treatment between the clusters was significantly different. Conclusions Our results showed that UMLA could be used to rationally classify a heterogeneous cohort of CSM patients effectively, and thus, it might be used as the basis for a data-driven platform for identifying the cluster of patients who can respond to a particular treatment method.