In this work we show that modifying the thermal history of the Universe by including an early period of matter domination can lead to the formation of astronomical objects. However, the survival of these objects can only be possible if the dominating matter decays to a daughter particle which is not only almost degenerate with the parent particle but also has an open annihilation channel. This requirement translates in an upper bound for the coupling of such a channel and makes the early structure formation viable.

Variation in cognitive ability arises from subtle differences in underlying neural architecture. Understanding and predicting individual variability in cognition from the differences in brain networks requires harnessing the unique variance captured by different neuroimaging modalities. Here we adopted a multi-level machine learning approach that combines diffusion, functional, and structural MRI data from the Human Connectome Project (N = 1050) to provide unitary prediction models of various cognitive abilities: global cognitive function, fluid intelligence, crystallized intelligence, impulsivity, spatial orientation, verbal episodic memory and sustained attention. Out-of-sample predictions of each cognitive score were first generated using a sparsity-constrained principal component regression on individual neuroimaging modalities. These individual predictions were then aggregated and submitted to a LASSO estimator that removed redundant variability across channels. This stacked prediction led to a significant improvement in accuracy, relative to the best single modality predictions (approximately 1% to more than 3% boost in variance explained), across a majority of the cognitive abilities tested. Further analysis found that diffusion and brain surface properties contribute the most to the predictive power. Our findings establish a lower bound to predict individual differences in cognition using multiple neuroimaging measures of brain architecture, both structural and functional, quantify the relative predictive power of the different imaging modalities, and reveal how each modality provides unique and complementary information about individual differences in cognitive function.

Genetic mutations of the Methyl-CpG-binding protein-2 (MECP2) gene underlie Rett syndrome (RTT). Developmental processes are often considered to be irrelevant in RTT pathogenesis but neuronal activity at birth has not been recorded. We report that the GABA developmental shift at birth is abolished in CA3 pyramidal neurons of Mecp2^−/ymice and the glutamatergic/GABAergic postsynaptic currents (PSCs) ratio is increased. Two weeks later, GABA exerts strong excitatory actions, the glutamatergic/GABAergic PSCs ratio is enhanced, hyper-synchronized activity is present and metabotropic long-term depression (LTD) is impacted. One day before delivery, maternal administration of the NKCC1 chloride importer antagonist bumetanide restored these parameters but not respiratory or weight deficits, nor the onset of mortality. Results suggest that birth is a critical period in RTT with important alterations that can be attenuated by bumetanide raising the possibility of early treatment of the disorder.

History, chance, and selection are the fundamental factors that drive and constrain evolution. We designed evolution experiments to disentangle and quantify effects of these forces on the evolution of antibiotic resistance. Previously, we showed that selection of the pathogen Acinetobacter baumannii in both structured and unstructured environments containing the antibiotic ciprofloxacin produced distinct genotypes and phenotypes, with lower resistance in biofilms as well as collateral sensitivity to β-lactam drugs (Santos-Lopez et al., 2019). Here we study how this prior history influences subsequent evolution in new β-lactam antibiotics. Selection was imposed by increasing concentrations of ceftazidime and imipenem and chance differences arose as random mutations among replicate populations. The effects of history were reduced by increasingly strong selection in new drugs, but not erased, at times revealing important contingencies. A history of selection in structured environments constrained resistance to new drugs and led to frequent loss of resistance to the initial drug by genetic reversions and not compensatory mutations. This research demonstrates that despite strong selective pressures of antibiotics leading to genetic parallelism, history can etch potential vulnerabilities to orthogonal drugs.

While cosmological inflation can erase primordial inhomogeneities, it is possible that inflation may not begin in a significantly inhomogeneous universe. This issue is particularly pressing in multifield scenarios, where even the homogeneous dynamics may depend sensitively on the initial configuration. This paper presents an initial survey of the onset of inflation in multifield models, via qualitative lattice-based simulations that do not include local gravitational backreaction. Using hybrid inflation as a test model, our results suggest that small subhorizon inhomogeneities do play a key role in determining whether inflation begins in multifield scenarios. Interestingly, some configurations which do not inflate in the homogeneous limit ``succeed'' after inhomogeneity is included, while other initial configurations which inflate in the homogeneous limit ``fail'' when inhomogeneity is added.

There is little consensus and controversial evidence on anatomical alterations in the brain of patients with autism spectrum disorder (ASD), due in part to the large heterogeneity present in ASD, which in turn is a major drawback for developing therapies. One strategy to characterize this heterogeneity in ASD is to cluster large-scale functional brain connectivity profiles. A subtyping approach based on consensus clustering of functional brain connectivity patterns was applied to a population of N=657 autistic patients with quality-assured neuroimaging data. We then used high-resolution gene transcriptomic data to characterize the molecular mechanism behind each subtype by performing enrichment analysis of the set of genes showing a high spatial similarity with the profiles of functional connectivity alterations between each subtype and the group of typically developing controls (TDC). Two major stable subtypes were found: Subtype 1 exhibited hypo-connectivity (less average connectivity than TDC) and subtype 2, hyper-connectivity. The two subtypes did not differ in structural imaging metrics in any of the analyzed regions (64 cortical and 14 subcortical), nor in any of the behavioral scores (including Intelligence Quotient, ADI and ADOS). Finally, only subtype 2, comprising about 42% of all patients, led to significant enrichments after multiple testing corrections. Notably, the dominant enrichment corresponded to excitation-inhibition (E/I) imbalance, a leading well-known primary mechanism in the pathophysiology of ASD. Our results support a link between E/I imbalance and functional connectivity alterations, but only in one ASD subtype, overall characterized by brain hyper-connectivity and major alterations in somatomotor and default mode networks.