Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation activities of Aeolus wind products on the southeastern Iberian Peninsula

Abstract. In 2018, the European Space Agency launched the first Doppler wind lidar system into space, providing wind observation profiles from the lower stratosphere down to the surface in two different channels based on the scene classification: cloudy or clear. A statistical validation campaign of Aeolus wind products has been performed with a ground-based Doppler lidar system and radiosondes at the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS)–Andalusian Global ObseRvatory of the Atmosphere (AGORA) facility in Granada (Spain). The validation activities with the automatic ground-based lidar system lasted from July 2019 to the orbit shift of June 2021. Aeolus data from two different processing baselines (10 and 11) were validated with 30 min averages of coincident ground-based lidar measurements, using a 100 km horizontal spatial collocation criterion. This resulted in 109 collocations and a mean observation distance from the ground-based lidar system of ∼50 km. The comparison did not raise any significant over- or underestimation of Aeolus horizontal line-of-sight wind speed during that period for the Rayleigh-clear and Mie-cloudy configurations. However, the ground-based lidar measurements were limited to the lower 3.5 km of the atmosphere and, consequently, the obtained results. Multiple analyses were performed varying the criteria of maximum distance and the average period for the ground-based lidar measurements in order to confirm the reliability of the criteria considered. A separate study was performed with Aeolus products after the orbit shift (baseline 12) with different collocation criteria (mean observation distance of ∼75 km, to the station), from July 2021 to May 2022. A set of seven radiosondes were launched with the aim of increasing their coincidence in space and time with the satellite overpass (∼30 min before). The radiosondes could provide full vertical coverage of Aeolus profiles (from the surface up to ∼20 km above sea level), and the comparison did not yield any significant over- or underestimation of the Rayleigh-clear wind speed, while the Mie-cloudy wind speed was significantly overestimated. Multiple analyses were performed in order to test how the spatiotemporal collocation of the radiosonde affected the results. Radiosondes not ideally collocated were proven to still be useful for comparison with the Rayleigh-clear observations but not with the Mie-cloudy observations.
A HUMANIZED FCRN TRANSGENIC MOUSE FOR PRECLINICAL PHARMACOKINETICS STUDIES

Monoclonal antibodies (mAbs) are one of the fastest-growing classes of drugs and have been approved to treat several diseases, including cancers and autoimmune disorders. Preclinical pharmacokinetics studies are performed to determine the therapeutically meaningful dosages and efficacy of candidate drugs. These studies are typically performed in non-human primates; however, using primates is costly and raises ethical considerations. As a result, rodent models that better mimic human-like pharmacokinetics have been generated and remain an area of active investigation. Pharmacokinetic characteristics of a candidate drug, such as half-life, are partly controlled by antibody binding to the human neonatal receptor hFCRN. Due to the abnormally high binding of human antibodies to mouse FCRN, traditional laboratory rodents do not accurately model the pharmacokinetics of human mAbs. In response, humanized rodents expressing hFCRN have been generated. However, these models generally use large inserts randomly integrated into the mouse genome. Here, we report the production and characterization of a CRISPR/Cas9-mediated hFCRN transgenic mouse termed SYNB-hFCRN. Using CRISPR/Cas9-assisted gene targeting, we prepared a strain with a simultaneous knockout of mFcrn and insertion of a hFCRN mini-gene under the control of the endogenous mouse promoter. These mice are healthy and express hFCRN in the appropriate tissues and immune cell subtypes. Pharmacokinetic evaluation of human IgG and adalimumab (Humira®) demonstrate hFCRN- mediated protection. These newly generated SYNB-hFCRN mice provide another valuable animal model for use in preclinical pharmacokinetics studies during early drug development. Materials availability Cryopreserved germline cells from the strains are available from the MMRRC. Dr. Jarnagin will provide sequencing and other evidence supporting strain identity and the plasmids used for constructions.
High level and molecular nature of transcriptional noise in yeast cells

“Biological noise” is defined as functionally insignificant events that occur in living cells due to imperfect fidelity of biological processes. Distinguishing between biological function and biological noise is often difficult, and experiments to measure biological noise have not been performed. Here, we measure biological noise in yeast cells by analyzing chromatin structure and transcription of an 18 kb region of DNA whose sequence was randomly generated and hence lacks biological function. Nucleosome occupancy on random-sequence DNA is comparable to that on yeast genomic DNA. However, nucleosome-depleted regions are much less frequent, and there are fewer well-positioned nucleosomes and shorter nucleosome arrays. Steady-state levels of RNAs expressed from random-sequence DNA are comparable to those of typical yeast mRNAs, although transcription and mRNA decay rates are higher. Transcriptional initiation (5’ ends) from random-sequence DNA occurs at numerous sites at low levels, indicating very low intrinsic specificity of the Pol II machinery. In contrast, poly(A) profiles (relative levels and clustering of 3’ isoforms) of random-sequence RNAs are roughly comparable to those within 3’ untranslated regions of yeast mRNAs, suggesting limited evolutionary constraints on poly(A) site choice. RNAs expressed from random-sequence DNA show higher cell-to-cell variability than RNAs expressed from yeast genomic DNA, suggesting that functional elements limit the variability among individual cells within a population. These observations indicate that transcriptional noise occurs at high levels in yeast, and they provide insight into how chromatin and transcription patterns arise from the evolved yeast genome.
Predicting species distributions with environmental time series data and deep learning

Species distribution models (SDMs) are widely used to gain ecological understanding and guide conservation decisions. These models are developed with a wide variety of algorithms - from statistic-based approaches to more recent machine learning algorithms - but one property they all have in common is the use of predictors that strongly simplify the temporal variability of driving factors. On the other hand, recent architectures of deep learning neural networks allow dealing with fully explicit spatiotemporal dynamics and thus fitting SDMs without the need to simplify the temporal and spatial dimension of predictor data. We present a deep learning-based SDM approach that uses time series of spatial data as predictors, and compare it with conventional modelling approaches, using five well known invasive species. Deep learning approaches provided consistently high performing models while also avoiding the use of pre-processed predictor sets, that can obscure relevant aspects of environmental variation.
Spike-phase coupling patterns reveal laminar identity in primate cortex

The cortical column is one of the fundamental computational circuits in the brain. In order to understand the role neurons in different layers of this circuit play in cortical function it is necessary to identify the boundaries that separate the laminar compartments. While histological approaches can reveal ground truth they are not a practical means of identifying cortical layers in vivo. The gold standard for identifying laminar compartments in electrophysiological recordings is current-source density (CSD) analysis. However, laminar CSD analysis requires averaging across reliably evoked responses that target the input layer in cortex, which may be difficult to generate in less well studied cortical regions. Further the analysis can be susceptible to noise on individual channels resulting in errors in assigning laminar boundaries. Here, we have analyzed linear array recordings in multiple cortical areas in both the common marmoset and the rhesus macaque. We describe a pattern of laminar spike-field phase relationships that reliably identifies the transition between input and deep layers in cortical recordings from multiple cortical areas in two different non-human primate species. This measure corresponds well to estimates of the location of the input layer using CSDs, but does not require averaging or specific evoked activity. Laminar identity can be estimated rapidly with as little as a minute of ongoing data and is invariant to many experimental parameters. This method may serve to validate CSD measurements that might otherwise be unreliable or to estimate laminar boundaries when other methods are not practical.
Metabolic Modeling of Hermetia illucens Larvae Resource Allocation for High-Value Fatty Acid Production

All plant and animal kingdom organisms use highly connected biochemical networks to facilitate sustaining, proliferation and growth functions. While biochemical network details are well known, the understanding of intense regulation principles is still limited. We chose to investigate Hermetia illucens fly at the larval stage as it is crucial for successful resource accumulation and allocation for the consequential organism’s developmental stages. We combined the iterative wet lab experiments and innovative metabolic modeling design approaches, to simulate and explain the H. illucens larval stage resource allocation processes and biotechnology potential. We performed time-based growth and high-value chemical compound accumulation wet lab chemical analysis experiments in larvae and Gainesville diet composition. To predict diet-based alterations on fatty acid allocation potential, we built and validated the first H. illucens medium-size stoichiometric metabolic model. Using optimization methods like Flux balance and Flux variability analysis on the novel insect metabolic model, it predicted that doubled essential amino acid consumption increased the growth rate by 32%, but pure glucose consumption had no positive impact on growth. In the case of doubled pure valine consumption, the model predicted a 2% higher growth rate. In this study, we describe a new framework to research the impact of dietary alterations on the metabolism of multi-cellular organisms at different developmental stages for improved, sustainable and directed high-value chemicals. Significance Statement Metabolic modeling serves as a platform for researchers to investigate and study in depth the possible states of the system based on the existing knowledgebase (e.g. metabolic reactions, substrates, products and their stoichiometry). These models can be applied for different industrial applications, to simulate resource allocation potential and growth conditions. Moreover, these models predict the required diet for living organisms and insects to improve survival and growth rates and accumulate higher-value products, like fatty acids.
Low Temperature and High Hydrostatic Pressure Have Compounding Negative Effects on Marine Microbial Motility

Approximately three fourths of all pelagic marine prokaryotes live in the deep-sea, an environment characterized by low temperature and high hydrostatic pressure. Within deep-sea environments labile organic matter is often scarce and motility can serve as a competitive advantage for microorganisms. Experimental work with a handful of species suggests motility is one of the most temperature- and pressure-sensitive cellular processes, however the combined effects of temperature and pressure together have yet to be investigated in detail. Here we employed growth-dependent motility agar assays and growth-independent microscopy assays to assess how changes in these two physical factors impact motility both individually and in combination, using ecologically relevant model organisms from the cosmopolitan genera Halomonas, Alcanivorax, and Marinobacter. At pressures equivalent to bathyal and abyssal depths, changes in temperature from 30°C to 4°C (motility assays) or 23°C to 7°C (microscopy assays) had a greater influence on motility than pressure. In addition, low-temperature and high-pressure impacts were additive. Exposure to high pressure had varying degrees of effect on flagellar function, depending on the strain and the magnitude of the pressure. These ranged from short-term impacts that were quickly reversible to long-term impacts that were detrimental to the function of the flagellum, leading to complete loss of motility. These findings highlight the sensitivity of deep-sea bacterial motility systems to combined temperature/pressure conditions, phenotypes that will contribute to the modulation of diverse microbial activities at depth. IMPORTANCE Microorganisms perform critical functions in biogeochemical cycles at depth, as well as likely modulating the carbon sequestration potential of the deep ocean. However, their activities under in situ conditions are poorly constrained. One aspect of microbial activity is motility, generally mediated by the energy-consuming rotation of one or more flagellar filaments that enables swimming behavior. This provides a competitive advantage for microbes in the environment, such as by enhancing nutrient acquisition. Here we report on culture-based and microscopy-based analyses of pressure-temperature (P-T) effects on the motility of three ecologically relevant marine microbes. The results in all cases indicate that high pressure and low temperature exert compounding inhibitory effects. This argues for the need for further investigations into P-T effects on deep-sea microbial processes.
Disrupting peroxisomes alters lipid metabolism in melanoma and uncovers a novel therapeutic vulnerability in combination with MAPK-targeted therapies

Melanomas reprogram their metabolism to rapidly adapt to therapy-induced stress conditions, allowing them to persist and ultimately develop resistance. We report that a subpopulation of melanoma cells tolerate MAPK pathway inhibitors (MAPKi) through a concerted metabolic reprogramming mediated by peroxisomes and UDP-glucose ceramide glycosyltransferase (UGCG). Compromising peroxisome biogenesis, by repressing PEX3 expression, potentiates the pro-apoptotic effects of MAPKi via an induction of ceramides, an effect limited by UGCG-mediated ceramide metabolism. Co-targeting PEX3 and UGCG selectively eliminates a subset of metabolically active, drug-tolerant CD36+ melanoma persister cells, thereby sensitizing melanoma to MAPKi and delaying resistance. Increased levels of peroxisomal genes and UGCG are found in patient-derived MAPKi-relapsed melanomas, and simultaneously inhibiting PEX3 and UGCG restores MAPKi sensitivity in multiple models of therapy resistance. Finally, triple therapy comprised of a newly identified inhibitor of the PEX3-PEX19 interaction, a UGCG inhibitor and a MAPKi demonstrates potent anti-tumor activity in pre-clinical melanoma models, thus representing a promising approach for melanoma treatment. Highlights Inhibiting peroxisome biogenesis uncovers a metabolic vulnerability in melanoma CD36+ persister melanoma cells tolerate MAPK-targeted therapy through peroxisome/UGCG mediated metabolic rewiring Dual blockade of PEX3 and UGCG potentiates melanoma response to MAPK-targeted therapies and restores therapeutic sensitivity in MAPKi-resistant tumors NNC 55-0396 is a PEX3-PEX19 binding inhibitor with potent anti-tumor activity in melanoma
Convergent escape behavior from distinct visual processing of impending collision in fish and grasshoppers

In animal species ranging from invertebrate to mammals, visually guided escape behaviors have been studied using looming stimuli, the two-dimensional expanding projection on a screen of an object approaching on a collision course at constant speed. The peak firing rate or membrane potential of neurons responding to looming stimuli often tracks a fixed threshold angular size of the approaching stimulus that contributes to the triggering of escape behaviors. To study whether this result holds more generally, we designed stimuli that simulate acceleration or deceleration over the course of object approach on a collision course. Under these conditions, we found that collision detecting neurons in grasshoppers were sensitive to acceleration whereas the triggering of escape behaviors was less so. In contrast, neurons in goldfish identified indirectly through the characteristic features of the escape behaviors they trigger, showed little sensitivity to acceleration. This closely mirrored a broader lack of sensitivity to acceleration of the goldfish escape behavior. Thus, although the sensory coding of simulated colliding stimuli with non-zero acceleration likely differs in grasshoppers and goldfish, the triggering of escape behaviors converges towards similar characteristics. Approaching stimuli with non-zero acceleration may help refine our understanding of neural computations underlying escape behaviors in a broad range of animal species. Key points A companion manuscript showed that two mathematical models of collision-detecting neurons in grasshoppers and goldfish make distinct predictions for their responses to simulated objects approaching on a collision course with non-zero acceleration. Testing these experimental predictions showed that grasshopper neurons are sensitive to acceleration while goldfish neurons are not, in agreement with the distinct models proposed previously in these species using constant velocity approaches. Both the escape behaviors of grasshopper and goldfish were insensitive to acceleration suggesting a further transformation downstream in grasshopper motor circuits that matches the computation observed in the goldfish Mauthner cell. Thus, in spite of different sensory processing in the two species, escape behaviors converge towards similar solutions. The use of object acceleration during approach on a collision course may help better understand the neural computations implemented for collision avoidance in a broad range of species.
Resting-state EEG dynamics help explain differences in response control in ADHD: Insight into electrophysiological mechanisms and sex differences

Reductions in response control (greater reaction time variability and commission error rate) are consistently observed in those diagnosed with attention-deficit/hyperactivity disorder (ADHD). Previous research suggests these reductions arise from a dysregulation of large-scale cortical networks. Here, we extended our understanding of this cortical-network/response-control pathway important to the neurobiology of ADHD. First, we assessed how dynamic changes in three resting-state EEG network properties thought to be relevant to ADHD (phase-synchronization, modularity, oscillatory power) covaried with response control during a simple perceptual decision-making task in 112 children/adolescents (aged 8-16) with and without formal ADHD diagnoses. Second, we tested whether these associations differed in males and females who were matched in age, ADHD-status and ADHD-subtype. We found that changes in oscillatory power (as opposed to phase-synchrony and modularity) are most related with response control, and that this relationship is stronger in ADHD compared to controls. Specifically, a tendency to dwell in an electrophysiological state characterized by high alpha/beta power (8-12/13-30Hz) and low delta/theta power (1-3/4-7Hz) supported response control, particularly in those with ADHD. Time in this state might reflect an increased initiation of alpha-suppression mechanisms, recruited by those with ADHD to suppress processing unfavourable to response control. We also found marginally significant evidence that this relationship is stronger in males compared to females, suggesting a distinct etiology for response control in the female presentation of ADHD. Highlights - Hidden Markov modeling of EEG functional network properties in ADHD and controls. - EEG power dynamics, not phase-synchrony or modularity, covary with response control. - Association between EEG dynamics and response control is more pronounced in ADHD. - ADHD cortical-network/response-control pathway is more prominent in males vs. females.
Benchmarking water-limited yield potential and yield gaps of Shiraz in the Barossa and Eden Valleys

Background and Aims Vineyard performance is impacted by water availability including the amount and seasonality of rainfall and evapotranspiration and irrigation volume. We benchmarked water-limited yield potential (Yw), calculated yield gaps as the difference between Yw and actual yield, and explored the underlying environmental and management causes of these gaps. Methods and Results The yield and its components in two sections of 24 Shiraz vineyards was monitored during three vintages in the Barossa zone (GI). The frequency distribution of yield was L-shaped, with half the vineyards below 5.2 t ha-1, and an extended tail of the distribution that reached 24.9 t ha-1. The seasonal ratio of actual crop evapotranspiration and reference evapotranspiration was below 0.48 in 85% of cases, with a maximum of 0.65, highlighting a substantial water deficit in these vineyards. A boundary function relating actual yield and seasonal rainfall was fitted to quantify Yw. Yield gaps increased with increasing vine water deficit, quantified by the carbon isotope composition in the fruit. The yield gap was smaller with higher rainfall before budburst, putatively favouring early-season vegetative growth and allocation to reproduction, and with higher rainfall between flowering and veraison, putatively favouring fruit set and berry growth. The gap was larger with higher rainfall and lower radiation between budburst and flowering. The yield gap increased linearly with vine age between 6 and 33 yr at a rate of 0.3 t ha-1 yr-1. The correlation between yield gap and yield components ranked bunch weight ≈ berries per bunch > bunch number > berry weight; the minimum to close the yield gap was 185,000 bunches ha-1, 105 g bunch-1, 108 berries bunch-1 and 1.1 g berry-1. Conclusions Water deficit and vine age were major causes of yield gaps. Winter irrigation provides an opportunity to improve productivity. The cost of dealing with older, less productive vines needs to be weighed against the rate of increase in yield gap with vine age. Significance of the Study A boundary function to estimate water-limited yield potential returned viticulturally meaningful yield gaps and highlighted potential targets to improve vineyard productivity.