Model-based whole-brain effective connectivity to study distributed cognition in health and disease

Neuroimaging techniques are now widely used to study human cognition. The functional associations between brain areas have become a standard proxy to describe how cognitive processes are distributed across the brain network. Among the many analysis tools available, dynamic models of brain activity have been developed to overcome the limitations of original connectivity measures such as functional connectivity. This goes in line with the many efforts devoted to the assessment of directional interactions between brain areas from the observed neuroimaging activity. This opinion article provides an overview of our model-based whole-brain effective connectivity to analyze fMRI data, while discussing the pros and cons of our approach with respect to other established approaches. Our framework relies on the multivariate Ornstein-Uhlenbeck (MOU) process and is thus referred to as MOU-EC. Once tuned, the model provides a directed connectivity estimate that reflects the dynamical state of BOLD activity, which can be used to explore cognition. We illustrate this approach using two applications on task-evoked fMRI data. First, as a connectivity measure, MOU-EC can be used to extract biomarkers for task-specific brain coordination, understood as the patterns of areas exchanging information. The multivariate nature of connectivity measures raises several challenges for whole-brain analysis, for which machine-learning tools present some advantages over statistical testing. Second, we show how to interpret changes in MOU-EC connections in a collective and model-based manner, bridging with network analysis. Our framework provides a comprehensive set of tools that open exciting perspectives to study distributed cognition, as well as neuropathologies.

Concurrent processes set E. coli cell division

A cell can divide only upon completion of chromosome segregation; otherwise, its daughters would lose genetic material. However, we do not know whether the partitioning of chromosomes is the key event for the decision to divide. We show how key trends in single-cell data reject the classic idea of replication-segregation as the rate-limiting process for cell division. Instead, the data agree with a model where two concurrent processes (setting replication initiation and interdivision time) set cell division on competing time scales. During each cell cycle, division is set by the slowest process (an "AND" gate). The concept of transitions between cell cycle stages as decisional processes integrating multiple inputs instead of cascading from orchestrated steps can affect the way we think of the cell cycle in general.

The Complete Plastome Sequences of Eleven Capsicum Genotypes: Insights into DNA Variation and Molecular Evolution

Members of the genus Capsicum are of great economic importance, including both wild forms and cultivars of peppers and chilies. The high number of potentially informative characteristics that can be identified through next-generation sequencing technologies gave a huge boost to evolutionary and comparative genomic research in higher plants. Here, we determined the complete nucleotide sequences of the plastomes of eight Capsicum species (eleven genotypes), representing the three main taxonomic groups in the genus and estimated molecular diversity. Comparative analyses highlighted a wide spectrum of variation, ranging from point mutations to small/medium size insertions/deletions (InDels), with accD, ndhB, rpl20, ycf1, and ycf2 being the most variable genes. The global pattern of sequence variation is consistent with the phylogenetic signal. Maximum-likelihood tree estimation revealed that Capsicum chacoense is sister to the baccatum complex. Divergence and positive selection analyses unveiled that protein-coding genes were generally well conserved, but we identified 25 positive signatures distributed in six genes involved in different essential plastid functions, suggesting positive selection during evolution of Capsicum plastomes. Finally, the identified sequence variation allowed us to develop simple PCR-based markers useful in future work to discriminate species belonging to different Capsicum complexes.

Effects of an individualized home-based unsupervised aerobic training on body composition and physiological parameters in obese adults are independent of gender

PURPOSE

Evaluation of the effects of an individualized home-based unsupervised aerobic training on body composition, physical and physiological parameters in female and male obese adults.

METHODS

Two hundred and twenty obese adults (age 47.9 ± 12.4 years; BMI 38.0 ± 7.2 kg/m²) entered the 4-month training program. Body composition, physiological and functional capacities were assessed pre- and post-intervention. All subjects were requested to perform unsupervised aerobic training with the intensity based on heart rate, walking speed and OMNI-RPE score corresponding to the individual ventilatory threshold for at least 5 days/week.

RESULTS

After 4-month study period, 40% of patients completed the protocol, 24% had high compliance (HC) (exercise ≥ 3 days/week), while 16% had low compliance (LC) to exercise prescription (exercise < than 3 days/week). In HC group, a significant improvement of body composition variables after training was performed. Moreover, oxygen uptake and metabolic equivalent at peak significantly increased after training. Six-minute walking test (6MWT) distance significantly increased while heart rate during 6MWT was significantly lower after training. No significant differences were found in LC group between pre- and post-intervention in all variables. Interestingly, gender does not influence the effects of training.

CONCLUSIONS

Our results indicate that subjects, independent of gender, with high compliance to the aerobic training based on a new individualized method can achieve a significant reduction in weight loss and also an improvement in physical and physiological parameters. This innovative personalized prescription could be a valuable tool for exercise physiologist, endocrinologists, and nutritionists to approach and correct life style of obese subjects.

Chloroplast proteome response to drought stress and recovery in tomato (Solanum lycopersicum L.)

BACKGROUND

Drought is a major constraint for plant growth and crop productivity that is receiving an increased attention due to global climate changes. Chloroplasts act as environmental sensors, however, only partial information is available on stress-induced mechanisms within plastids. Here, we investigated the chloroplast response to a severe drought treatment and a subsequent recovery cycle in tomato through physiological, metabolite and proteomic analyses.

RESULTS

Under stress conditions, tomato plants showed stunted growth, and elevated levels of proline, abscisic acid (ABA) and late embryogenesis abundant gene transcript. Proteomics revealed that water deficit deeply affects chloroplast protein repertoire (31 differentially represented components), mainly involving energy-related functional species. Following the rewatering cycle, physiological parameters and metabolite levels indicated a recovery of tomato plant functions, while proteomics revealed a still ongoing adjustment of the chloroplast protein repertoire, which was even wider than during the drought phase (54 components differentially represented). Changes in gene expression of candidate genes and accumulation of ABA suggested the activation under stress of a specific chloroplast-to-nucleus (retrograde) signaling pathway and interconnection with the ABA-dependent network.

CONCLUSIONS

Our results give an original overview on the role of chloroplast as enviromental sensor by both coordinating the expression of nuclear-encoded plastid-localised proteins and mediating plant stress response. Although our data suggest the activation of a specific retrograde signaling pathway and interconnection with ABA signaling network in tomato, the involvement and fine regulation of such pathway need to be further investigated through the development and characterization of ad hoc designed plant mutants.