Miracle-dz/UniFAR-FTUs huggingface dataset:
Lower Statistical Support with Larger Data Sets: Insights from the Ochrophyta Radiation

It is commonly assumed that increasing the number of characters has the potential to resolving radiations. We studied photosynthetic stramenopiles (Ochrophyta) using alignments of heterogeneous size and origin (6,762 sites for mitochondrion, 21,692 sites for plastid and 209,105 sites for nucleus). While statistical support for the relationships between the six major Ochrophyta lineages increases when comparing the mitochondrion and plastid trees, it decreases in the nuclear tree. Statistical support is not simply related to the dataset size but also to the quantity of phylogenetic signal available at each position and our ability to extract it. Here, we show that proper signal extraction is difficult to attain, as demonstrated by conflicting results obtained when varying taxon sampling. Even though the use of a better fitting model improved signal extraction and reduced the observed conflicts, the plastid dataset provided higher statistical support for the ochrophyte radiation than the larger nucleus dataset. We propose that the higher support observed in the plastid tree is due to an acceleration of the evolutionary rate in one short deep internal branch, implying that more phylogenetic signal per position is available to resolve the Ochrophyta radiation in the plastid than in the nuclear dataset. Our work therefore suggests that, in order to resolve radiations, beyond the obvious use of datasets with more positions, we need to continue developing models of sequence evolution that better extract the phylogenetic signal and design methods to search for genes/characters that contain more signal specifically for short internal branches.
Dopamine enhances model-free credit assignment through boosting of retrospective model-based inference

Dopamine is implicated in signalling model-free (MF) reward prediction errors and various aspects of model-based (MB) credit assignment and choice. Recently, we showed that cooperative interactions between MB and MF systems include guidance of MF credit assignment by MB inference. Here, we used a double-blind, placebo-controlled, within-subjects design to test the hypothesis that enhancing dopamine levels, using levodopa, boosts the guidance of MF credit assignment by MB inference. We found that levodopa enhanced retrospective guidance of MF credit assignment by MB inference, without impacting on MF and MB influences per se. This drug effect positively correlated with working memory, but only in a context where reward needed to be recalled for MF credit assignment. The dopaminergic enhancement in MB-MF interactions correlated negatively with a dopamine-dependent change in MB credit assignment, possibly reflecting a potential trade-off between these two components of behavioural control. Thus, our findings demonstrate that dopamine boosts MB inference during guidance of MF learning, supported in part by working memory, but trading-off with a dopaminergic enhancement of MB credit assignment. The findings highlight a novel role for a DA influence on MB-MF interactions.
A comprehensive score reflecting memory‐related fMRI activations and deactivations as potential biomarker for neurocognitive aging

Older adults and particularly those at risk for developing dementia typically show a decline in episodic memory performance, which has been associated with altered memory network activity detectable via functional magnetic resonance imaging (fMRI). To quantify the degree of these alterations, a score has been developed as a putative imaging biomarker for successful aging in memory for older adults (Functional Activity Deviations during Encoding, FADE; Düzel et al., 2011). Here, we introduce and validate a more comprehensive version of the FADE score, termed FADE-SAME (Similarity of Activations during Memory Encoding), which differs from the original FADE score by considering not only activations but also deactivations in fMRI contrasts of stimulus novelty and successful encoding, and by taking into account the variance of young adults’ activations. We computed both scores for novelty and subsequent memory contrasts in a cohort of 217 healthy adults, including 106 young and 111 older participants, as well as a replication cohort of 117 young subjects. We further tested the stability and generalizability of both scores by controlling for different MR scanners and gender, as well as by using different data sets of young adults as reference samples. Both scores showed robust age-group-related differences for the subsequent memory contrast, and the FADE-SAME score additionally exhibited age-group-related differences for the novelty contrast. Furthermore, both scores correlate with behavioral measures of cognitive aging, namely memory performance. Taken together, our results suggest that single-value scores of memory-related fMRI responses may constitute promising biomarkers for quantifying neurocognitive aging.
The total mRNA concentration buffering system in yeast is global rather than gene-specific

Gene expression in eukaryotes does not follow a linear process from transcription to translation and mRNA degradation. Instead it follows a circular process in which cytoplasmic mRNA decay crosstalks with nuclear transcription. In many instances this crosstalk contributes to buffer mRNA at a roughly constant concentration. Whether the mRNA buffering concept operates on the total mRNA concentration or at the gene-specific level, and if the mechanism to do so is a global or a specific one, remain unknown. Here we assessed changes in mRNA concentrations and their synthesis rates along the transcriptome of aneuploid strains of the yeast Saccharomyces cerevisiae. We also assessed mRNA concentrations and their synthesis rates in non sense-mediated decay (NMD) targets in euploid strains. We found that the altered synthesis rates in the genes from the aneuploid chromosome and the changes in their mRNA stabilities were not counterbalanced. In addition, the stability of NMD targets was not specifically compensated by the changes in synthesis rate. We conclude that there is no genetic compensation of NMD mRNA targets in yeast, and total mRNA buffering uses mostly a global system rather than a gene-specific one.
Sporulation is dispensable for the vegetable‐associated life cycle of the human pathogen Bacillus cereus

Bacillus cereus is a common food-borne pathogen that is responsible for important outbreaks of food poisoning in humans. Diseases caused by B. cereus usually exhibit two major symptoms, emetic or diarrheic, depending on the toxins produced. It is assumed that after the ingestion of contaminated vegetables or processed food, spores of enterotoxigenic B. cereus reach the intestine, where they germinate and produce the enterotoxins that are responsible for food poisoning. In our study, we observed that sporulation is required for the survival of B. cereus in leaves but is dispensable in ready-to-eat vegetables, such as endives. We demonstrate that vegetative cells of B. cereus that are originally impaired in sporulation but not biofilm formation are able to reach the intestine and cause severe disorders in a murine model. We propose that loss of part of the sporulation programme and reinforcement of structural factors related to adhesion, biofilm formation and pathogenic interaction with the host are adaptive traits of B. cereus with a life cycle primarily related to human hosts. Furthermore, our findings emphasise that the number of food poisoning cases associated with B. cereus is underestimated and suggest the need to revise the detection protocols, which are based primarily on spores and toxins.
Glacial connectivity and current population fragmentation in sky-islands explain the contemporary distribution of genomic variation in two narrow-endemic montane grasshoppers from a biodiversity hotspot

Aim Cold-adapted biotas from mid-latitudes often show small population sizes, harbor low levels of local genetic diversity, and are highly vulnerable to extinction due to ongoing climate warming and the progressive shrink of montane and alpine ecosystems. In this study, we use a suite of analytical approaches to infer the demographic processes that have shaped contemporary patterns of genomic variation in Omocestus bolivari and O. femoralis, two narrow-endemic and red-listed Iberian grasshoppers forming highly fragmented populations in the sky island archipelago of the Baetic System. Location Southeastern Iberia. Methods We quantified genomic variation in the two focal taxa and coupled ecological niche models and a spatiotemporally explicit simulation approach based on coalescent theory to determine the relative statistical support of a suite of competing demographic scenarios representing contemporary population isolation (i.e., a predominant role of genetic drift) vs. historical connectivity and post-glacial colonization of sky islands (i.e., pulses of gene flow and genetic drift linked to Pleistocene glacial cycles). Results Inference of spatial patterns of genetic structure, environmental niche modelling, and statistical evaluation of alternative species-specific demographic models within an Approximate Bayesian Computation framework collectively supported genetic admixture during glacial periods and postglacial colonization of sky islands, rather than long-term population isolation, as the scenario best explaining the current distribution of genomic variation in the two focal taxa. Moreover, our analyses revealed that isolation in sky islands have also led to extraordinary genetic fragmentation and contributed to reduce local levels of genetic diversity. Main conclusions This study exemplifies the potential of integrating genomic and environmental niche modelling data across biological and spatial replicates to determine whether organisms with similar habitat requirements have experienced concerted/idiosyncratic responses to Quaternary climatic oscillations, which can ultimately help to reach more general conclusions about the vulnerability of mountain biodiversity hotspots to ongoing climate warming.
Genetic nurture effects on education: a systematic review and meta-analysis

Child educational development is associated with major psychological, social, economic and health milestones throughout the life course. Understanding the early origins of educational inequalities and their reproduction across generations is therefore crucial. Recent genomic studies provide novel insights in this regard, uncovering “genetic nurture” effects, whereby parental genotypes influence offspring’s educational development via environmental pathways rather than genetic transmission. These findings have yet to be systematically appraised. We conducted the first systematic review and meta-analysis to quantify genetic nurture effects on educational outcomes and investigate key moderators. Twelve studies comprising 38,654 distinct parent(s)-offspring pairs or trios from eight cohorts were included, from which we derived 22 estimates of genetic nurture effects. Multilevel random effects models showed that the effect of genetic nurture on offspring’s educational outcomes (βgenetic nurture = 0.08, 95% CI [0.07, 0.09]) was about half the size of direct genetic effects (βdirect genetic = 0.17, 95% CI [0.13, 0.20]). Maternal and paternal genetic nurture effects were similar in magnitude, suggesting comparable roles of mothers and fathers in determining their children’s educational outcomes. Genetic nurture effects were largely explained by parental educational level and family socioeconomic status, suggesting that genetically influenced environments play an important role in shaping child educational outcomes. Even after accounting for genetic transmission, we provide evidence that environmentally mediated parental genetic influences contribute to the intergenerational transmission of educational outcomes. Further exploring these downstream environmental pathways may inform educational policies aiming to break the intergenerational cycle of educational underachievement and foster social mobility. Public Significance Statement This meta-analysis demonstrates that parents’ genetics influence their children’s educational outcomes through the rearing environments that parents provide. This “genetic nurture” effect is largely explained by family socioeconomic status and parental education level, is similar for mothers and fathers (suggesting that both parents equally shape their children’s educational outcomes) and is about half the size of direct genetic effects on children’s educational outcomes. Interventions targeting such environmental pathways could help to break the intergenerational cycle of educational underachievement and foster social mobility.
Dissociable mechanisms of reward learning co-mature during human adolescence as predicted by macaque lesion models

Reward-guided learning and decision-making is a fundamental adaptive ability and depends on a number of component processes. We investigate how such component processes mature during human adolescence. Our approach was guided by analyses of the effects of lateral orbitofrontal lesions in macaque monkeys, as this part of the brain shows clear developmental maturation in humans during adolescence. Using matched tasks and analyses in humans (n=388, 11-35yrs), we observe developmental changes in two key learning mechanisms as predicted from the monkey data. First, choice-reward credit assignment – the ability to link a specific outcome to a specific choice – is reduced in adolescents. Second, the effects of the global reward state – how good the environment is overall recently − exerts a distinctive pattern of influence on learning in humans compared to other primates and across adolescence this pattern becomes more pronounced. Both mechanisms were correlated across participants suggesting that associative learning of correct reward assignments and GRS based learning constitute two complementary mechanisms of reward-learning that co-mature during adolescence.
noisyR: Enhancing biological signal in sequencing datasets by characterising random technical noise

High-throughput sequencing enables an unprecedented resolution in transcript quantification, at the cost of magnifying the impact of technical noise. The consistent reduction of random background noise to capture functionally meaningful biological signals is still challenging. Intrinsic sequencing variability introducing low-level expression variations can obscure patterns in downstream analyses. We introduce noisyR, a comprehensive noise filter to assess the variation in signal distribution and achieve an optimal information-consistency across replicates and samples; this selection also facilitates meaningful pattern recognition outside the background-noise range. noisyR is applicable to count matrices and sequencing data; it outputs sample-specific signal/noise thresholds and filtered expression matrices. We exemplify the effects of minimising technical noise on several datasets, across various sequencing assays: coding, non-coding RNAs and interactions, at bulk and single-cell level. An immediate consequence of filtering out noise is the convergence of predictions (differential-expression calls, enrichment analyses and inference of gene regulatory networks) across different approaches. Teaser Noise removal from sequencing quantification improves the convergence of downstream tools and robustness of conclusions.
Reducing phenotypic instabilities of a microbial population during continuous cultivation based on cell switching dynamics

Predicting the fate of individual cells among a microbial population (i.e., growth and gene expression) remains a challenge, especially when this population is exposed to very dynamic environmental conditions, such as those encountered during continuous cultivation. Indeed, the dynamic nature of a continuous cultivation process implies the potential diversification of the microbial population resulting in genotypic and phenotypic heterogeneity. The present work focused on the induction of the arabinose operon in Escherichia coli as a model system to study this diversification process in continuous cultivations. As a preliminary step, the green fluorescent protein (GFP) level triggered by an arabinose‐inducible ParaBAD promoter was tracked by flow cytometry in chemostat cultivations with glucose‐arabinose co‐feeding. For a wide range of glucose‐arabinose co‐feeding concentrations in the chemostats, the simultaneous occurrence of GFP positive and negative subpopulation was observed. In the second set of experiments, continuous cultivation was performed by adding glucose continuously and arabinose based on the capability of individual cells to switch from low GFP to high GFP expression states, performed with a technology setup called segregostat. In the segregostat cultivation mode, on‐line flow cytometry analysis was used for adjusting the arabinose/glucose transitions based on the phenotypic switching profiles of the microbial population. This strategy allowed finding an appropriate arabinose pulsing frequency, leading to prolonged maintenance of the induction level with a limited increase in the phenotypic diversity for more than 60 generations. The results suggest that the steady forcing of individual cells into a given phenotypic trajectory may not be the best strategy for controlling cell populations. Instead, allowing individual cells to switch periodically around a predefined threshold seems to be a more robust strategy leading to oscillations, but within a predictable cell population behavior range.
Collective action or individual choice: Spontaneity and individuality contribute to decision-making in Drosophila

Our own unique character traits make our behavior consistent and define our individuality. Yet, this consistency does not entail that we behave repetitively like machines. Like humans, animals also combine personality traits with spontaneity to produce adaptive behavior: consistent, but not fully predictable. Here, we study an iconically rigid behavioral trait – insect phototaxis – that that nevertheless also contains both components of individuality and spontaneity. In a light/dark T-maze, approximately 70% of a group of Drosophila fruit flies choose the bright arm of the T-Maze, while the remaining 30% walk into the dark. Taking the photopositive and the photonegative subgroups and re-testing them reveals the spontaneous component: a similar 70-30 distribution emerges in each of the two subgroups. Increasing the number of choices to ten choices, reveals the individuality component: flies with extremely negative first choices were more likely to show photonegative behavior in subsequent choices and vice versa. General behavioral traits, independent of light/dark preference, contributed to the development of this individuality. The interaction of individuality and spontaneity together explains why group averages, even for such seemingly stereotypical behaviors, are poor predictors of individual choices.
Selection for feed efficiency elicits different postprandial plasma metabolite profiles in response to poor hygiene of housing conditions in growing pigs

Selection for residual feed intake (RFI), a measure of feed efficiency, may affect the ability of pigs to adapt their metabolism in response to poor environmental conditions. This study was conducted to compare postprandial plasma concentrations of insulin, energy related metabolites, and amino acids measured after a 6-week challenge consisting of exposure to good or poor hygiene of housing conditions of 24 growing pigs divergently selected for low-RFI (LRFI) and high-RFI (HRFI). Blood indicators of immune responses were assessed from samples collected before (week 0 or W0), and 3 (W3) and 6 weeks (W6) after pigs transfer to their respective housing hygiene conditions. Plasma haptoglobin concentrations and blood neutrophil granulocyte numbers were greater in poor than in good conditions at W3. Plasma concentrations of total immunoglobulin G were greater (p = 0.04) in poor than in good hygiene conditions at W6. At W6, pigs were fitted with an intravenous catheter for serial blood samplings. Low-RFI pigs had greater insulin (p < 0.001) and lower triglyceride (p = 0.04) average plasma concentrations than HRFI pigs in both conditions. In poor hygiene conditions, the peaks of insulin and glucose occured earlier and that of insulin was greater in LRFI than in HRFI pigs. Irrespective of genetic line, average plasma concentrations of histidine, isoleucine, leucine, methionine, threonine, valine, and alanine were greater in poor compared with good conditions. Only HRFI pigs had greater lysine, asparagine, proline, and tyrosine plasma concentrations in poor than in good hygiene conditions. Conversely, arginine, tryptophan, proline, and tyrosine plasma concentrations were lower only for LRFI pigs housed in poor hygiene conditions. The impact of poor hygiene of housing conditions on insulin, triglycerides, and AA profiles differed between RFI lines. More specifically, our results suggest that, contrary to HRFI, LRFI pigs increased or maintained their utilization of Trp, Arg, and Lys when housed in poor hygiene conditions. This difference may contribute to the better capacity of LRFI to cope with the poor hygiene of housing conditions.
Validation and Comparison of Six Risk Scores for Infection in Patients With ST-Segment Elevation Myocardial Infarction Undergoing Percutaneous Coronary Intervention

Aims: Very few of the risk scores to predict infection in ST-segment elevation myocardial infarction (STEMI) patients undergoing percutaneous coronary intervention (PCI) have been validated, and reports on their differences. We aimed to validate and compare the discriminatory value of different risk scores for infection. Methods: A total of 2,260 eligible patients with STEMI undergoing PCI from January 2010 to May 2018 were enrolled. Six risk scores were investigated: age, serum creatinine, or glomerular filtration rate, and ejection fraction (ACEF or AGEF) score; Canada Acute Coronary Syndrome (CACS) risk score; CHADS2 score; Global Registry for Acute Coronary Events (GRACE) score; and Mehran score conceived for contrast induced nephropathy. The primary endpoint was infection during hospitalization. Results: Except CHADS2 score (AUC, 0.682; 95%CI, 0.652–0.712), the other risk scores showed good discrimination for predicting infection. All risk scores but CACS risk score (calibration slope, 0.77; 95%CI, 0.18–1.35) showed best calibration for infection. The risks scores also showed good discrimination for in-hospital major adverse clinical events (MACE) (AUC range, 0.700–0.786), except for CHADS2 score. All six risk scores showed best calibration for in-hospital MACE. Subgroup analysis demonstrated similar results. Conclusions: The ACEF, AGEF, CACS, GRACE, and Mehran scores showed a good discrimination and calibration for predicting infection and MACE.