Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence-based consideration of dietary ‘alternatives’ to anticoccidial drugs to help control poultry coccidial infections

SUMMARY Coccidiosis remains a major disease and economic challenge for the global poultry industry. Coccidiosis in chickens is caused by seven Eimeria species that target specific regions of the gastrointestinal tract and cause malabsorptive or haemorrhagic disease. These Eimeria species infect segment-specific epithelial cells and thus need to navigate the host’s indigenous microbiome and intestinal defences to establish an infection and cause disease. Good husbandry practices, prophylactic use of anticoccidial drugs and/or live parasite vaccination have been the primary control measures employed but there are challenges with vaccination and growing constraints on anticoccidial drug use. This review, therefore, considers available information on the key steps of the infection process, notable microbiome- or host-related changes occurring, and the (potential) influence of dietary ‘alternatives’ to anticoccidial drugs. There is good available evidence to indicate that some phytogenics, prebiotics, probiotics, betaine, n-3 fatty acids, as well as carbohydrase enzymes and anti-IL-10 antibodies, can (beneficially) modulate at least some of these features in coccidiosis-specific challenge studies. As a minimum, these anticoccidial drug ‘alternatives’ could support the establishment of a desirable host microbiome and optimum immune system development. It is important to better understand the potential of these ‘alternatives’ in commercial production and how they can complement, or reduce, the use of anticoccidial drugs.
State Space Model Predictive Control for Advanced Process Operation: A Review of Recent Development, New Results, and Insight

Model predictive control (MPC) has acquired lots of developments and extensive applications in various industries during the past 40 years. For the early version of basic MPC strategies, there are challenges in both control performance and applications. On the basis of such backgrounds, state space models that contain more system information on the controlled system than conventional models and make the controller design straightforward under MIMO situations were introduced to the MPC framework, and many academic results have been put forward. One of the challenging missions for current MPC research is still focused on the optimal control of systems with improved (or robust) control performance. Therefore, it is of significance to investigate new developments of MPC. In order to improve the control performance of MPC, we introduced a new comprehensive state space model formulation strategy in which state variables and the output tracking errors are combined and can be regulated separately. On the basis of.
A complex feature-based representation of vocalizations emerges in the superficial layers of primary auditory cortex

Early in auditory processing, neural responses faithfully reflect acoustic input. At higher stages of auditory processing, however, neurons become selective for particular call types, eventually leading to specialized regions of cortex that preferentially process calls at the highest auditory processing stages. We previously proposed that an intermediate step in how non-selective responses are transformed into call-selective responses is the detection of informative call features. But how neural selectivity for informative call features emerges from non-selective inputs, whether feature selectivity gradually emerges over the processing hierarchy, and how stimulus information is represented in non-selective and feature-selective populations remain open questions. In this study, using unanesthetized guinea pigs, a highly vocal and social rodent, as an animal model, we characterized the neural representation of calls in three auditory processing stages – the thalamus (vMGB), and thalamorecipient (L4) and superficial layers (L2/3) of primary auditory cortex (A1). We found that neurons in vMGB and A1 L4 did not exhibit call-selective responses and responded throughout the call durations. However, A1 L2/3 neurons showed high call-selectivity with about a third of neurons responding to only one or two call types. These A1 L2/3 neurons only responded to restricted portions of calls suggesting that they were highly selective for call features. Receptive fields of these A1 L2/3 neurons showed complex spectrotemporal structures that could underlie their high call feature selectivity. Information theoretic analysis revealed that in A1 L4 stimulus information was distributed over the population and was spread out over the call durations. In contrast, in A1 L2/3, individual neurons showed brief bursts of high stimulus-specific information, and conveyed high levels of information per spike. These data demonstrate that a transformation in the neural representation of calls occurs between A1 L4 and A1 L2/3, leading to the emergence of a feature-based representation of calls in A1 L2/3. Our data thus suggest that observed cortical specializations for call processing emerge in A1, and set the stage for further mechanistic studies.
Genome-wide chromosomal association of Upf1 is linked to Pol II transcription in Schizosaccharomyces pombe

Although the RNA helicase Upf1 has hitherto been examined mostly in relation to its cytoplasmic role in nonsense mediated mRNA decay (NMD), here we report high-throughput ChIP data indicating genome-wide association of Upf1 with active genes in Schizosaccharomyces pombe. This association is RNase sensitive and it correlates with Pol II transcription and mRNA expression levels. While changes in Pol II occupancy were detected at only some genes in a Upf1-deficient (upf1Δ) strain, there is an increased Ser2 Pol II signal at all highly transcribed genes examined by ChIP-qPCR. Furthermore, upf1Δ cells are hypersensitive to the transcription elongation inhibitor 6-azauracil and display Pol II abnormalities suggestive of Pol II hyperphosphorylation. A significant proportion of the genes associated with Upf1 in wild-type conditions are also mis-regulated in upf1Δ. These data envisage that by operating on the nascent transcript Upf1 might influence Pol II phosphorylation and transcription.
Modeling the role of mortality-based response triggers on the effectiveness of African swine fever control strategies

African swine fever (ASF) is considered the most impactful transboundary swine disease. In the absence of effective vaccines, control strategies are heavily dependent on mass depopulation and movement restrictions. Here we developed a nested multiscale model for the transmission of ASF, combining spatially explicit network model of animal movements with a deterministic compartmental model for the dynamics of two ASF strains within-pixels of 3 km x 3 km, amongst the pig population in one Brazilian state. The model outcomes are epidemic duration, number of secondary infected farms and pigs, and distance of ASF spread. The model also shows the spatial distribution of ASF epidemics. We analyzed quarantine-based control interventions in the context of mortality trigger thresholds for the deployment of control strategies. The mean epidemic duration of a moderately virulent strain was 11.2 days assuming the first infection is detected (best-case scenario) and 15.9 days when detection is triggered at 10 % mortality. For a highly virulent strain, the epidemic duration was 6.5 days and 13.1 days, respectively. The distance from the source to infected locations and the spatial distribution was not dependent on strain virulence. Under the best-case scenario, we projected an average number of infected farms of 23.77 farms and 18.8 farms for the moderate and highly virulent strains, respectively. At 10% mortality-trigger, the predicted number of infected farms was on average 46.27 farms and 42.96 farms, respectively. We also demonstrated that the establishment of ring quarantine zones regardless of size (i.e., 5 km, 15 km) was outperformed by backward animal movement tracking. The proposed modeling framework provides an evaluation of ASF epidemic potential, providing a ranking of quarantine-based control strategies that could assist animal health authorities in planning the national preparedness and response plan.
Why most Principal Component Analyses (PCA) in population genetic studies are wrong

Principal Component Analysis (PCA) is a multivariate analysis that allows reduction of the complexity of datasets while preserving data covariance and visualizing the information on colorful scatterplots, ideally with only a minimal loss of information. PCA applications are extensively used as the foremost analyses in population genetics and related fields (e.g., animal and plant or medical genetics), implemented in well-cited packages like EIGENSOFT and PLINK. PCA outcomes are used to shape study design, identify, and characterize individuals and populations, and draw historical and ethnobiological conclusions on origins, evolution, dispersion, and relatedness. The replicability crisis in science has prompted us to evaluate whether PCA results are reliable, robust, and replicable. We employed an intuitive color-based model alongside human population data for eleven common test cases. We demonstrate that PCA results are artifacts of the data and that they can be easily manipulated to generate desired outcomes. PCA results may not be reliable, robust, or replicable as the field assumes. Our findings raise concerns about the validity of results reported in the literature of population genetics and related fields that place a disproportionate reliance upon PCA outcomes and the insights derived from them. We conclude that PCA may have a biasing role in genetic investigations. An alternative mixed-admixture population genetic model is discussed.
Nonnegative matrix factorization integrates single-cell multi-omic datasets with partially overlapping features

Single-cell genomic technologies provide an unprecedented opportunity to define molecular cell types in a data-driven fashion, but present unique data integration challenges. Integration analyses often involve datasets with partially overlapping features, including both shared features that occur in all datasets and features exclusive to a single experiment. Previous computational integration approaches require that the input matrices share the same number of either genes or cells, and thus can use only shared features. To address this limitation, we derive a novel nonnegative matrix factorization algorithm for integrating single-cell datasets containing both shared and unshared features. The key advance is incorporating an additional metagene matrix that allows unshared features to inform the factorization. We demonstrate that incorporating unshared features significantly improves integration of single-cell RNA-seq, spatial transcriptomic, SHARE-seq, and cross-species datasets. We have incorporated the UINMF algorithm into the open-source LIGER R package (https://github.com/welch-lab/liger).
Linearised loop kinematics to study pathways between conformations

Conformational changes are central to the function of many proteins. Characterization of these changes using molecular simulation requires methods to effectively sample pathways between protein conformational states. In this paper we present an iterative algorithm that samples conformational transitions in protein loops, referred to as the Jacobian-based Loop Transition (JaLT) algorithm. The method uses internal coordinates to minimise the sampling space, while Cartesian coordinates are used to maintain loop closure. Information from the two representations is combined to push sampling towards a desired target conformation. The innovation that enables the simultaneous use of Cartesian coordinates and internal coordinate is the linearisation of the inverse kinematics of a protein backbone. The algorithm uses the Rosetta all-atom energy function to steer sampling through low-energy regions and uses Rosetta’s side-chain energy minimiser to update side-chain conformations along the way. Because the JaLT algorithm combines a detailed energy function with a low-dimensional conformational space, it is positioned in between molecular dynamics (MD) and elastic network model (ENM) methods. As a proof of principle, we apply the JaLT algorithm to study the conformational transition between the open and occluded state in the MET20 loop of the Escherichia coli dihydrofolate reductase enzyme. Our results show that the algorithm generates semi-continuous pathways between the two states with realistic energy profiles. These pathways can be used to identify energy barriers along the transition. The effect of a single point mutation of the MET20 loop was also investigated and the predicted increase in energy barrier is consistent with the experimentally observed reduction in catalytic rate of the enzyme. Additionally, it is demonstrated how the JaLT algorithm can be used to identify dominant degrees of freedom during a transition. This can be valuable input for a more extensive characterization of the free energy pathway along a transition using molecular dynamics, which is often performed with a reduced set of degrees of freedom. This study has thereby provided the first examples of how linearisation of inverse kinematics can be applied to the analysis of proteins.
Parametric Deconvolution for Cancer Cells Viscoelasticity Measurements from Quantitative Phase Images

In this contribution, we focused on optimising a dynamic flow-based shear stress system to achieve a reliable platform for cell shear modulus (stiffness) and viscosity assessment using quantitative phase imaging. The estimation of cell viscoelastic properties is influenced by distortion of the shear stress waveform, which is caused by the properties of the flow system components (i.e., syringe, flow chamber and tubing). We observed that these components have a significant influence on the measured cell viscoelastic characteristics. To suppress this effect, we applied a correction method utilizing parametric deconvolution of the flow system’s optimized impulse response. Achieved results were compared with the direct fitting of the Kelvin-Voigt viscoelastic model and the basic steady-state model. The results showed that our novel parametric deconvolution approach is more robust and provides a more reliable estimation of viscosity with respect to changes in the syringe’s compliance compared to Kelvin-Voigt model.
Cypripedium wardii (Orchidaceae) employs pseudopollen with both reward and deception to attract both flis and bees as pollinators

Flowering plants always attract animals providing rewards or deceptive signals to gain reproductive success. However, there is no well-documented reporting about a pollination mechanism with both rewards and deceptive signals by a same object. We found Cypripedium wardii flowers seem to attract visitors by the white pseudopollenlike trichomes on labella in our preliminary field observation. To explore the pollination mechanism of Cypripedium wardii, especially, the ecological function of the pseudopollen-like trichomes, we conducted field observations, analyses of the traits of visitors and flowers, and breeding system experiments. The white trichomes composed by multicellular moniliform hairs on the floral labella played a crucial role to attract pollinators, causing a high natural fruit set ratio in C. wardii. We established the direct connection of the white trichomes and real pollen. We propose that flowers of C. wardii provide pseudopollen to attract suitable bees and hoverflies as pollinators. And our evidence indicate that the pseudopollen owns both deceptive and rewarding ecological functions. Our study provide a clear pollination mechanism with both rewards and deceptive signals by a same object in angiosperm for the first time. However, an inbreeding depression seem to be caused by this strategy. And we speculated that the pollen mimicry strategy with both rewarding and deceptive functions in C. wardii may be an adaptation to the habitat fragmentation of this species to gain a reproductive assurance.
Honeybee Queen mandibular pheromone induces starvation in Drosophila melanogaster, implying a role for nutrition signalling in the evolution of eusociality

Eusocial insect societies are defined by the reproductive division of labour, a social structure that is generally enforced by the reproductive dominant or ‘queen’. Reproductive dominance is maintained through behavioural dominance in some species as well as production of queen pheromones in others, or a mixture of both. Queen mandibular pheromone (QMP) is produced by honeybee (Apis mellifera) queens and has been characterised chemically. How QMP acts to repress worker reproduction, and how it has evolved this activity, remains less well understood. Surprisingly, QMP is capable of repressing reproduction in non-target arthropods which have not co-evolved with QMP, are never exposed to QMP in nature, and are up to 530 million years diverged from the honeybee. Here we show that, in Drosophila melanogaster, QMP treatment mimics nutrient limiting conditions, leading to disrupted reproduction. Exposure to QMP induces an increase in food consumption, consistent with that observed in D. melanogaster in response to starvation conditions. This response induces the activation of two checkpoints within the ovary that inhibit oogenesis. The first is the 2a/b ovarian checkpoint in the germarium, which reduces the flow of presumptive oocytes. A stage 9 ovarian checkpoint is also activated, causing degradation of oocytes. The magnitude of activation of both checkpoints is indistinguishable between QMP treated and starved individuals. As QMP seems to trigger a starvation response in an insect highly diverged from honeybees, we propose that QMP originally evolved by co-opting nutrition signalling pathways to regulate reproduction, a key step in the evolution of eusociality.
Insights into Promoted Adsorption Capability of Layered BiOCl Nanostructures Decorated with TiO2 Nanoparticles

Rational design of excellent adsorbents with remarkable adsorption capability and renewable properties is of significant importance to practical applications. Herein, an adsorbent of BiOCl nanoplates decorated with TiO2 nanoparticles was successfully prepared from porous BiOCl microspheres and tetrabutoxytitanium. Through TiO2 nanoparticle decoration, the tuned morphology, surface charge property, Brunauer–Emmett–Teller (BET) surface area, and hydrophilic property of the BiOCl microsphere were favorable for achieving optimization of adsorption capability toward Congo red removal with a maximum adsorption amount of 254.7 mg/g. A possible adsorption mechanism model involving the BET surface area, electrostatic interactions, and competitive adsorption between solvent and solute was proposed to account for the enhancement of adsorption capability of BiOCl-TiO2 nanocomposites compared to those of pure BiOCl and TiO2. Furthermore, the BiOCl-TiO2 nanocomposite adsorbent can be simply regenerated by a photocataly.
East-African savanna dynamics: from a knowledge-based model to the possible futures of a social-ecological system

Sub-Saharan savanna ecosystems are undergoing transitions such as bush encroachment, desertification or agricultural expansion. Such shifts and persistence of land cover are increasingly well understood, especially bush encroachment which is of major concern in pastoral systems. Although dominant factors can explain such transformations, they often result from intertwined causes in which human activities play a significant role. Therefore, in this latter case, these issues may require integrated solutions, involving many interacting components. Ecosystem modelling has proved appropriate to support decision-makers in such complex situations. However, ecosystem models often require lots of quantitative information for estimating parameters and the precise functional form of interactions is often unknown. Alternatively, in rangeland management, States-and-Transitions Models (STMs) have been developed to organize knowledge about system transitions and to help decision-makers. However, these conceptual diagrams often lack mathematical analyzing tools, which strongly constrains their complexity. In this paper, we introduce the Ecological Discrete-Event Network (EDEN) modelling approach for representing the qualitative dynamics of an East-African savanna as a set of discrete states and transitions generated from empirical rules. These rules are derived from local knowledge, field observations and scientific literature. In contrast with STMs, EDEN generates automatically every possible states and transitions, thus enabling the prediction of novel ecosystem structures. Our results show that the savanna is potentially resilient to the disturbances considered. Moreover, the model highlights all transitions between vegetation types and socio-economic profiles under various climatic scenarios. The model also suggests that wildlife diversity may increase socio-economic resistance to seasonal drought. Tree-grass coexistence and agropastoralism have the widest ranges of conditions of existence of all vegetation types and socio-economic profiles, respectively. As this is a preliminary use of EDEN for applied purpose, analysis tools should be improved to enable finer investigation of desirable trajectories. By translating local knowledge into ecosystem dynamics, the EDEN approach seems promising to build a new bridge between managers and modellers.
High-speed widefield handheld swept-source OCT angiography with a VCSEL light source

Optical coherence tomography (OCT) and OCT angiography (OCTA) enable noninvasive structural and angiographic imaging of the eye. Portable handheld OCT/OCTA systems are required for imaging patients in the supine position. Examples include infants in the neonatal intensive care unit (NICU) and operating room (OR). The speed of image acquisition plays a pivotal role in acquiring high quality OCT/OCTA images, particularly with the handheld system, since both the operator hand tremor and subject motion can cause significant motion artifacts. In addition, having a large field of view and the ability of real-time data visualization are critical elements in rapid disease screening, reducing imaging time, and detecting peripheral retinal pathologies. The arrangement of optical components is less flexible in the handheld system due to the limitation of size and weight. In this paper, we introduce a 400-kHz, 55-degree field of view handheld OCT/OCTA system that has overcome many technical challenges as a portable OCT system as well as a high-speed OCTA system. We demonstrate imaging premature infants with retinopathy of prematurity (ROP) in the NICU, and patients with incontinentia pigmenti (IP) in the OR using our handheld OCT system. Our design may have potential for improving the diagnosis of retinal diseases and help provide a practical guideline for designing a flexible and portable OCT system.
SorCS2 deletion leads to altered neuronal lysosome activity

Vps10p domain receptors are important for regulating intracellular protein sorting within the central nervous system and as such constitute risk factors for different brain pathologies. Here, we show that removal of SorCS2 leads to altered lysosomal activity in mouse primary neurons. SorCS2-/- neurons show elevated lysosomal markers such as LAMP1 and acidic hydrolases including cathepsin B and D. Despite increased levels, SorCS2-/- neurons fail to degrade cathepsin specific substrates in a live context. SorCS2-deficient mice present an increase in lysolipids, which may contribute to membrane permeabilization and increased susceptibility to lysosomal stress. Our findings highlight SorCS2 as an important factor for a balanced neuronal lysosome milieu.