Miracle-dz/UniFAR-FTUs huggingface dataset:
3D spheroid culturing of Astyanax mexicanus liver-derived cell lines recapitulates distinct transcriptomic and metabolic states of in vivo tissue environment

In vitro assays are crucial tools for gaining detailed insights into various biological processes, including metabolism. Cave morphs of the river-dwelling fish species, Astyanax mexicanus, have adapted their metabolism allowing them to thrive in the biodiversity-deprived and nutrient-limited environment of caves. Liver-derived cells from the cave and river morphs of Astyanax mexicanus have proven to be excellent in vitro resources to better understand the unique metabolism of these fish. However, the current 2D cultures have not fully captured the complex metabolic profile of the Astyanax liver. It is known that 3D culturing can modulate the transcriptomic state of cells when compared to its 2D monolayer culture. Therefore, in order to broaden the possibilities of the in vitro system by modeling a wider gamut of metabolic pathways, we cultured the liver-derived Astyanax cells of both surface and cavefish into 3D spheroids. We successfully established 3D cultures at various cell seeding densities for several weeks and characterized the resultant transcriptomic and metabolic variations. We found that the 3D cultured Astyanax cells represent a wider range of metabolic pathways, including cell cycle changes and antioxidant activities, associated with liver functioning as compared to its monolayer culture. Additionally, the spheroids also exhibited surface and cave-specific metabolic signatures, making it a suitable system for evolutionary studies associated with cave adaptation. Taken together, the liver-derived spheroids prove to be a promising in vitro model for widening our understanding of metabolism in Astyanax mexicanus and of vertebrates in general.
Flexibility of learning in complex worlds

Learning to adjust to changing environments is an important aspect of behavioral flexibility. Here we investigate the possible advantages of flexible learning rates in volatile environments, using learning simulations. We compare two established learning mechanisms, one with fixed learning rates and one with flexible rates that adjust to volatility. We study three types of ecological and experimental volatility: transitions from a simpler to a more complex foraging environment, reversal learning, and learning set formation. For transitions to a complex world, we use developing cleaner fish as an example, having more types of client fish to choose between as they become adult. There are other similar transitions in nature, such as migrating to a new and different habitat. Performance in reversal learning and in learning set formation are commonly used experimental measures of behavioral flexibility. Concerning transitions to a complex world, we show that both fixed and flexible learning rates perform well, losing only a small proportion of available rewards in the period after a transition, but flexible rates perform better than fixed. For reversal learning, flexible rates improve the performance with each successive reversal, because of increasing learning rates, but this does not happen for fixed rates. For learning set formation, we find no improvement in performance with successive shifts to new stimuli to discriminate for either flexible or fixed learning rates. Flexible learning rates might thus explain increasing performance in reversal learning, but not in learning set formation. We discuss our results in relation to current ideas about behavioral flexibility.
Functional diversity reduces the risk of hydraulic failure in tree mixtures through hydraulic disconnection

Forest ecosystems are increasingly threatened by anthropogenic pressures, especially by the increase in drought frequency and intensity. Tree species mixtures could improve resilience to diverse global anthropogenic pressures. However, there is still little consensus on how tree diversity affects water stress. Although some studies suggest that mixing species with different drought response strategies could be beneficial, the underlying mechanisms have seldom been identified. By combining a greenhouse experiment and a soil-plant-atmosphere hydraulic model, we explored whether mixing a drought avoidant (Pinus halepensis) and a drought tolerant (Quercus ilex) tree species could reduce plant water stress (defined as the risk of hydraulic failure) during extreme drought, compared to their respective monocultures. Our experiment showed that mixing species with divergent drought response strategies had a neutral effect on the drought-avoidant species and a positive effect on the drought-tolerant species. The model simulations further suggested that the beneficial effect of mixture on plant water stress during extreme drought was related to changes in the hydraulic connection of the plant from both the soil and the atmosphere. The ability of the drought-avoidant species to disconnect from the soil and the atmosphere limits its exposure to water stress, whereas the ability of the drought-tolerant species to increase its hydraulic connection to the soil lowers its hydraulic risk. This study brings a new insight on the mechanisms and traits combinations improving drought resistance in diversified forests and plantations, with important implications for forest management under climate change.
Ketogenic diet as a metabolic vehicle for enhancing the therapeutic efficacy of mebendazole and devimistat in preclinical pediatric glioma

Invasion of high-grade glioma (HGG) cells through the brain and spinal cord is a leading cause of cancer death in children. Despite advances in treatment, survivors often suffer from life-long adverse effects of the toxic therapies. This study investigated the influence of nutritional ketosis on the therapeutic action of mebendazole (MBZ) and devimistat (CPI-613) against the highly invasive VM-M3 glioblastoma cells in juvenile syngeneic p20-p25 mice; a preclinical model of pediatric HGG. Cerebral implantation of the VM-M3 glioblastoma cells invaded throughout the brain and the spinal column similar to that seen commonly in children with malignant glioma. The maximum therapeutic benefit of MBZ and CPI-613 on tumour invasion and mouse survival occurred only when the drugs were administered together with a ketogenic diet (KD). MBZ reduced VM-M3 tumour cell growth and invasion when evaluated under in-vitro and in-vivo conditions through inhibition of both the glutaminolysis and the glycolysis pathways. Moreover, administration of the drugs with the KD allowed a low dosing for the juvenile mice, which minimized toxicity while improving overall survival. This preclinical study in juvenile mice highlights the potential importance of a diet/drug therapeutic strategy for managing childhood brain cancer.
eIF4E1b is a non-canonical eIF4E required for maternal mRNA dormancy

Maternal mRNAs are essential for protein synthesis during oogenesis and early embryogenesis. To adapt translation to specific needs during development, maternal mRNAs are translationally repressed by shortening the polyA tails. While mRNA deadenylation is associated with decapping and degradation in somatic cells, maternal mRNAs with short polyA tails are stable. Here we report an essential role for the germline-specific paralog of the mRNA cap-binding factor eIF4E, known as eIF4E1b, in the storage and repression of maternal mRNAs with short polyA tails. eIF4E1b binds to the mRNA cap and is targeted to ribonucleoprotein complexes through its direct interaction with eIF4ENIF1/4E-T. In early embryos, eIF4E1b binds to a specific set of translationally repressed mRNAs with short or no polyA tails, such as histone mRNAs, which are translated later on during embryogenesis. Consistent with an important role in maternal mRNA dormancy, mutation of eIF4E1b in zebrafish impairs female germline development. Understanding the mechanism and function of eIF4E1B provides new insights into fundamental post-transcriptional regulatory principles governing early vertebrate development.
Gene family evolution in brassicaceous-feeding insects: Implications for adaptation and host plant range

Herbivores have a defined range of hostplants that they can feed on, which is mediated by underlying detoxification and sensory repertoires. Insects that feed on Brassicaceae represent one of the striking examples of co-evolutionary arms race. Insects specialized on Brassicaceae have evolved specific mechanisms to detoxify mustard oils (glucosinolates), while generalist species use detoxification enzymes that act on a variety of substrates. Understanding the gene evolution of detoxification and sensory repertoire in specialist and generalist Brassicaceae feeders will shed light on the processes involved in mediating hostplant ranges in herbivores. We use a comparative phylogenomic approach in 12 lepidopterans that feed on Brassicaceae, ranging from specialist to pests in their host range to examine the gene family expansion of detoxification and sensory gene families. We found that gene family expansions and contractions were larger in generalist herbivores compared to specialist herbivores. Gene evolutionary rate of detoxification genes reflected hostplant range where generalists had a higher evolutionary rate of detoxification genes that act on wide substrates while specialists had a higher evolutionary rate in genes that conjugate toxic compounds to hydrophilic byproducts. Our analysis on the nitrile specifier gene, a key innovation for feeding on Brassicaceae, indicated pervasive purifying selection with lineage specific differences in selection. Our results add to the growing body of work addressing gene family evolution and its role in hostplant range and specialization in insects.
Gauge equivariant convolutional neural networks for diffusion mri

Diffusion MRI (dMRI) is an imaging technique widely used in neuroimaging research, where the signal carries directional information of underlying neuronal fibres, based on the diffusivity of water molecules. One of the shortcomings of dMRI is that numerous images, sampled at gradient directions on a sphere, must be acquired to achieve a reliable angular resolution for model-fitting, which translates to longer scan times, higher costs, and barriers to clinical adoption. In this work we introduce gauge equivariant convolutional neural network (gCNN) layers that overcome the challenges associated with the dMRI signal being acquired on a sphere with antipodal points identified, by making it equivalent to the real projective plane, RP 2, which is a non-euclidean and a non-orientable manifold. This is in stark contrast to a rectangular grid which typical convolutional neural networks (CNNs) are designed for. We apply our method to upsample angular resolution for predicting diffusion tensor imaging (DTI) parameters from just six diffusion gradient directions. The symmetries introduced allow gCNNs the ability to train with fewer subjects and are general enough to be applied to many dMRI related problems.
In Vitro Culture Alters Cell Lineage Composition and Cellular Metabolism of Bovine Blastocyst

Profiling transcriptome at single cell level of bovine blastocysts derived in vivo (IVV), in vitro from conventional culture medium (IVC), and reduced nutrient culture medium (IVR) has enabled us to reveal cell lineage segregation, during which forming inner cell mass (ICM), trophectoderm (TE), and an undefined population of transitional cells. Only IVV embryos had well-defined ICM, indicating in vitro culture may delay the first cell fate commitment to ICM. Differences between IVV, IVC and IVR embryos were mainly contributed by ICM and transitional cells. Pathway analysis by using the differentially expressed genes of these non-TE cells between groups pointed to highly active metabolic and biosynthetic processes, with reduced cellular signaling and membrane transport in IVC embryos, which may lead to reduced developmental potential. IVR embryos had lower activities in metabolic and biosynthetic processes, but increased cellular signaling and membrane transport, suggesting these cellular mechanisms may contribute to the improved blastocyst development compared to IVC embryos. However, the IVR embryos had compromised development when compared to IVV embryos with notably over-active membrane transport activities that led to impaired ion homeostasis. Summary Statement Single-cell transcriptomic analysis of bovine blastocysts produced in vivo, and in vitro in conventional and reduced nutrient conditions reveals the effect of culture environments on embryo developmental potential.
PTV profiling of particles motion from the top and side of a swirling fluidized bed

A swirling fluidized bed (SFB) operation heavily depends on geometry of the solid particles and gas distributor. This study was aimed at investigating the hydrodynamics of the solid particles in a SFB, set into fluidization using an annular blade distributor. MATLAB supported particle tracking velocimetry (PTV) was engaged to generate the velocity vector profiles of the top surface and side of the swirling bed. The pressure drop curve suggested that the uniform bed swirling happens at the superficial air velocities between 2 m/s and 2.6 m/s. The average particle velocity, both at the top and side of the bed, exhibited a monotonically increasing trend over the superficial air velocity. However, an inverse relationship was predicted between particle velocity and the bed height. At lower superficial air velocities, a Gaussian distribution of the velocity vectors was predicted along the radius of the bed. Particles in the vicinity of the bed walls moved relatively slower than those marching in the middle of the bed. However, the average particle velocity was decreased with an increase in the blade fin angle and inclination angle. Overall, the particle velocity at the top surface of the bed remained slightly lower than along the side of the bed.
Humans Valuing Nature: Synthesising Insights from Philosophy, Psychology and Economics

A rational process for assessment of environmental policy options should be based on an appreciation of how humans value nature. Increased understanding of values will also contribute to the development of appropriate ways for us to relate to and manage natural areas. Over the past two decades, environmental philosophers have examined the notion that there is an intrinsic value in nature. Economists have attempted to define and measure the market and nonmarket economic values associated with decisions concerning natural areas. Psychologists have tried to assess the extent to which people believe in an intrinsic value in nature, and have also begun to work with economists to improve nonmarket valuation techniques. I briefly review the contributions made to our understanding of natural area value by environmental philosophy, psychology and economics, and develop a model that integrates insights from these disciplines. Components in the model include cognitions, held values, assigned values and various modes of value expression. I make recommendations for future validation, development and use of the model.
Improving Anaerobic Fitness in Young Basketball Players: Plyometric vs. Specific Sprint Training

Improving Anaerobic Fitness in Young Basketball Players: Plyometric vs. Specific Sprint Training Basketball is a game that is typically performed in an intermittent manner, and includes numerous bursts of explosive activity. Thus, implementation of training methods that best develop anaerobic fitness is of significant importance to basketball coaches and players. The aim of the present study was to compare the effect of plyometric and specific sprint training, matched for total volume, on the anaerobic fitness of young basketball players. Nineteen young (16.3 ± 0.5 years) male basketball players were randomly assigned to either a plyometric training group or a specific sprint training group, and completed two similar fitness tests prior to and following six weeks of training. The two training programs consisted of plyometric jump training (4 sets of 4-6 series with 6 jumps each) and specific sprint training (4 sets of 4-6 × 20 m repetitions). Prior to training there were no baseline differences between the groups in 20 m sprint time (speed test), bounding distance and vertical jump height (power tests), 2×5 m run time (agility test) or suicide run time (basketball-specific anaerobic endurance test). Plyometric training led to a significant improvement only in the suicide test time (1.6 ± 1.6%, p<0.05). Specific sprint training led to a significant improvement in the 20 m sprint time (2.6 ± 1.7%), bounding distance (3.9 ± 3.8%), and suicide test time (1.2 ± 1.1%, p<0.05 for all). However, there was no significant between-group differences in the training effects on any of the anaerobic variables measured. Neither training program had a significant effect on jump height or the 2×5 m run. The study showed that plyometric training and specific sprint training do not differ statistically in enhancing anaerobic fitness of young basketball players. Thus, coaches may have the possibility of alternating between these methods during the busy basketball season.
Interpretation of Statistical Preference in Terms of Location Parameters

Abstract Stochastic orders are methods that allow the comparison of random quantities. One of the most used stochastic orders is stochastic dominance. This method is based on the direct comparison of the cumulative distribution functions of the random variables, and it is characterized by comparing the expectations of the adequate transformation of the variables. Statistical preference is another alternative based on a probabilistic relation that provides preference degrees between the variables. This paper proves that statistical preference is connected to another location parameter different from the expectation: the median. Then, both stochastic orders have different interpretations, in the same way as mean and median are two different location parameters for describing random samples. Nevertheless, we prove that stochastic dominance and statistical preference are connected when the random variables are independent.
Black-box LTI modelling of flapping-wing micro aerial vehicle dynamics

This paper presents the development of black-box linear state-space models for the flight dynamics of a flapping-wing micro aerial vehicle (FWMAV), the DelFly. The models were obtained by means of system identification techniques applied to flight data recorded in a motion tracking chamber and describe the time-averaged dynamics of the vehicle in the proximity of specific stationary points in forward flight. Ordinary least squares and maximum likelihood-based estimation approaches were applied in the time domain, and decoupled models were identified for the longitudinal and the lateral dynamics. The availability of several different datasets additionally allowed for validation and for the estimation and comparison among each other of several separate models. Adequate models were obtained for both the longitudinal and the lateral dynamics. These reproduce the estimation data well and are also capable of predicting the response to validation inputs with a reasonable degree of accuracy, thus allowing for a simulation of the DelFly near the stationary points considered. The identified dynamics are stable and thus in agreement with the observed behaviour of the DelFly in the considered flight regime.
Biased Wage Expectations and Female Labor Supply Working paper

We quantify the effects of biased wage expectations on female labor market outcomes. A wide sample of full-time and part-time employees report counterfactual predictions about their own wage trajectories in future full-time and part-time employment, revealing severe misperceptions. Actual wage growth occurs almost exclusively in full-time work whereas it is close to zero in part-time work, as we show with reduced-form regressions and in a structural life-cycle model. Subjective expectations, however, predict a mild difference in the opposite direction, with strong over-optimism about part time. We leverage the structural model to quantify how the employees’ beliefs influence their labor supply and wages over the life cycle. The bias increases part-time employment strongly, induces flatter long-run wage profiles, and substantially affects two widely discussed policy reforms. The largest impact of the bias appears for college-educated women, consistent with the large difference between expected and realized wages observed for this group.
zkSaaS: Zero-Knowledge SNARKs as a Service

A decade of active research has led to practical constructions of zero-knowledge succinct noninteractive arguments of knowledge (zk-SNARKs) that are now being used in a wide variety of applications. Despite this astonishing progress, overheads in proof generation time remain significant. In this work, we envision a world where consumers with low computational resources can outsource the task of proof generation to a group of untrusted servers in a privacy-preserving manner. The main requirement is that these servers should be able to collectively generate proofs at a faster speed (than the consumer). Towards this goal, we introduce a framework called zk-SNARKs-as-aservice (zkSaaS) for faster computation of zk-SNARKs. Our framework allows for distributing proof computation across multiple servers such that each server is expected to run for a shorter duration than a single prover. Moreover, the privacy of the prover’s witness is ensured against any minority of colluding servers. We design custom protocols in this framework that can be used to obtain faster runtimes for widely used zk-SNARKs, such as Groth16 [EUROCRYPT 2016], Marlin [EUROCRYPT 2020] and Plonk [EPRINT 2019]. We implement proof of concept zkSaaS for the Groth16 and Plonk provers. In comparison to generating these proofs on commodity hardware, we show that not only can we generate proofs for a larger number of constraints (without memory exhaustion), but can also get ≈ 22× speed-up when run with 128 parties for 2 constraints with Groth16 and 2 gates with Plonk.
The Role of Stimuli-Driven and Goal-Driven Attention in Shopping Decision-Making Behaviors—An EEG and VR Study

The human attention system, similar to other networks in the brain, is of a complex nature. At any moment, our attention can shift between external and internal stimuli. In this study, we aimed to assess three EEG-based measures of attention (Power Spectral Density, Connectivity, and Spectral Entropy) in decision-making situations involving goal-directed and stimulus-driven attention using a Virtual Reality supermarket. We collected the EEG data of 29 participants in 2 shopping phases, planned and unplanned purchases. The three mentioned features were extracted and a statistical analysis was conducted. We evaluated the discriminatory power of these features using an SVM classifier. The results showed a significant (p-value < 0.001) increase in theta power over frontal, central, and temporal lobes for the planned purchase phase. There was also a significant decrease in alpha power over frontal and parietal lobes in the unplanned purchase phase. A significant increase in the frontoparietal connectivity during the planned purchase was observed. Additionally, an increase in spectral entropy was observed in the frontoparietal region for the unplanned purchase phase. The classification results showed that spectral entropy has the highest discriminatory power. This study can provide further insights into the attentional behaviors of consumers and how their type of attentional control can affect their decision-making processes.