Reviving Bistable Perception in Patients With Depression by Decreasing the Overestimation of Prior Precision.

Slower perceptual alternations, a notable perceptual effect observed in psychiatric disorders, can be alleviated by antidepressant therapies that affect serotonin levels in the brain. While these phenomena have been well documented, the underlying neurocognitive mechanisms remain to be elucidated. Our study bridges this gap by employing a computational cognitive approach within a Bayesian predictive coding framework to explore these mechanisms in depression. We fitted a prediction error (PE) model to behavioral data from a binocular rivalry task, uncovering that significantly higher initial prior precision and lower PE led to a slower switch rate in patients with depression. Furthermore, serotonin-targeting antidepressant treatments significantly decreased the prior precision and increased PE, both of which were predictive of improvements in the perceptual alternation rate of depression patients. These findings indicated that the substantially slower perception switch rate in patients with depression was caused by the greater reliance on top-down priors and that serotonin treatment's efficacy was in its recalibration of these priors and enhancement of PE. Our study not only elucidates the cognitive underpinnings of depression, but also suggests computational modeling as a potent tool for integrating cognitive science with clinical psychology, advancing our understanding and treatment of cognitive impairments in depression.

Transcriptome Responses to Different Environments in Intertidal Zones in the Peanut Worm Sipunculus nudus.

The peanut worm (Sipunculus nudus) is an important intertidal species worldwide. Species living in the same aquaculture area might suffer different environmental impacts. To increase knowledge of the molecular mechanisms underlying the response to environmental fluctuations, we performed a transcriptome analysis of S. nudus from different intertidal zones using a combination of the SMRT platform and the Illumina sequencing platform. (1) A total of 105,259 unigenes were assembled, and 23,063 unigenes were perfectly annotated. The results of the PacBio Iso-Seq and IIIumina RNA-Seq enriched the genetic database of S. nudus. (2) A total of 830 DEGs were detected in S. nudus from the different groups. In particular, 33 DEGs had differential expression in the top nine KEGG pathways related to pathogens, protein synthesis, and cellular immune response and signaling. The results indicate that S. nudus from different zones experience different environmental stresses. (3) Several DEGs (HSPA1, NFKBIA, eEF1A, etc.) in pathways related to pathogens (influenza A, legionellosis, measles, and toxoplasmosis) had higher expression in groups M and L. HSPA1 was clearly enriched in most of the pathways, followed by NFKBIA. The results show that the peanut worms from the M and L tidal flats might have suffered more severe environmental conditions. (4) Some DEGs (MKP, MRAS, and HSPB1) were upregulated in peanut worms from the H tidal flat, and these DEGs were mainly involved in the MAPK signaling pathway. These results indicate that the MAPK pathway may play a vital role in the immune response of the peanut worm to the effects of different intertidal flats. This study provides a valuable starting point for further studies to elucidate the molecular basis of the response to different environmental stresses in S. nudus.

Autoregressive optimal transport models.

Series of univariate distributions indexed by equally spaced time points are ubiquitous in applications and their analysis constitutes one of the challenges of the emerging field of distributional data analysis. To quantify such distributional time series, we propose a class of intrinsic autoregressive models that operate in the space of optimal transport maps. The autoregressive transport models that we introduce here are based on regressing optimal transport maps on each other, where predictors can be transport maps from an overall barycenter to a current distribution or transport maps between past consecutive distributions of the distributional time series. Autoregressive transport models and their associated distributional regression models specify the link between predictor and response transport maps by moving along geodesics in Wasserstein space. These models emerge as natural extensions of the classical autoregressive models in Euclidean space. Unique stationary solutions of autoregressive transport models are shown to exist under a geometric moment contraction condition of Wu & Shao [(2004) Limit theorems for iterated random functions. Journal of Applied Probability 41, 425-436)], using properties of iterated random functions. We also discuss an extension to a varying coefficient model for first-order autoregressive transport models. In addition to simulations, the proposed models are illustrated with distributional time series of house prices across U.S. counties and annual summer temperature distributions.

Testing homogeneity: the trouble with sparse functional data.

Testing the homogeneity between two samples of functional data is an important task. While this is feasible for intensely measured functional data, we explain why it is challenging for sparsely measured functional data and show what can be done for such data. In particular, we show that testing the marginal homogeneity based on point-wise distributions is feasible under some mild constraints and propose a new two-sample statistic that works well with both intensively and sparsely measured functional data. The proposed test statistic is formulated upon energy distance, and the convergence rate of the test statistic to its population version is derived along with the consistency of the associated permutation test. The aptness of our method is demonstrated on both synthetic and real data sets.

Trajectories of brain volumes in young children are associated with maternal education.

Brain growth in early childhood is reflected in the evolution of proportional cerebrospinal fluid volumes (pCSF), grey matter (pGM), and white matter (pWM). We study brain development as reflected in the relative fractions of these three tissues for a cohort of 388 children that were longitudinally followed between the ages of 18 and 96 months. We introduce statistical methodology (Riemannian Principal Analysis through Conditional Expectation, RPACE) that addresses major challenges that are of general interest for the analysis of longitudinal neuroimaging data, including the sparsity of the longitudinal observations over time and the compositional structure of the relative brain volumes. Applying the RPACE methodology, we find that longitudinal growth as reflected by tissue composition differs significantly for children of mothers with higher and lower maternal education levels.

Network evolution of regional brain volumes in young children reflects neurocognitive scores and mother's education.

The maturation of regional brain volumes from birth to preadolescence is a critical developmental process that underlies emerging brain structural connectivity and function. Regulated by genes and environment, the coordinated growth of different brain regions plays an important role in cognitive development. Current knowledge about structural network evolution is limited, partly due to the sparse and irregular nature of most longitudinal neuroimaging data. In particular, it is unknown how factors such as mother's education or sex of the child impact the structural network evolution. To address this issue, we propose a method to construct evolving structural networks and study how the evolving connections among brain regions as reflected at the network level are related to maternal education and biological sex of the child and also how they are associated with cognitive development. Our methodology is based on applying local Fréchet regression to longitudinal neuroimaging data acquired from the RESONANCE cohort, a cohort of healthy children (245 females and 309 males) ranging in age from 9 weeks to 10 years. Our findings reveal that sustained highly coordinated volume growth across brain regions is associated with lower maternal education and lower cognitive development. This suggests that higher neurocognitive performance levels in children are associated with increased variability of regional growth patterns as children age.

Bioextractive Removal of Nitrogen by Oysters in Great Bay Piscataqua River Estuary, New Hampshire, USA.

Eutrophication is a challenge to coastal waters around the globe. In many places, nutrient reductions from land-based sources have not been sufficient to achieve desired water quality improvements. Bivalve shellfish have shown promise as an in-water strategy to complement land-based nutrient management. A local-scale production model was used to estimate oyster (Crassostrea virginica) harvest and bioextraction of nitrogen (N) in Great Bay Piscataqua River Estuary (GBP), New Hampshire, USA, because a system-scale ecological model was not available. Farm-scale N removal results (0.072 metric tons acre-1 year-1) were up-scaled to provide a system-wide removal estimate for current (0.61 metric tons year-1), and potential removal (2.35 metric tons year-1) at maximum possible expansion of licensed aquaculture areas. Restored reef N removal was included to provide a more complete picture. Nitrogen removal through reef sequestration was ~ 3 times that of aquaculture. Estimated reef-associated denitrification, based on previously reported rates, removed 0.19 metric tons N year-1. When all oyster processes (aquaculture and reefs) were included, N removal was 0.33% and 0.54% of incoming N for current and expanded acres, respectively. An avoided cost approach, with wastewater treatment as the alternative management measure, was used to estimate the value of the N removed. The maximum economic value for aquaculture-based removal was $105,000 and $405,000 for current and expanded oyster areas, respectively. Combined aquaculture and reef restoration is suggested to maximize N reduction capacity while limiting use conflicts. Comparison of removal based on per oyster N content suggests much lower removal rates than model results, but model harvest estimates are similar to reported harvest. Though results are specific to GBP, the approach is transferable to estuaries that support bivalve aquaculture but do not have complex system-scale hydrodynamic or ecological models.

Impact of different running conditions on performance of biofilters treating secondary effluent during start-up.

In this study, the impact of different aeration sequences, hydraulic retention time (HRT), aeration time ratios and external carbon types on performance of biofilters treating secondary effluent during start-up was explored. For an intermittently aerated nitrifying filter, the adjustment of aeration sequence with prior nitrification or denitrification had no significant impact on overall performance. Extending HRT promoted sedimentation and denitrification. However, extending HRT to enhance performance is inadvisable due to incompleted denitrification. Similarly, the impact of different aeration time ratios on performance was not as apparent as that of start-up time. External carbon addition to denitrifying filter could enhance performance with glucose more favorable for denitrification and sodium acetate better for P sequestration. When the synthetic over-standard secondary effluent treated by the nitrifying and denitrifying filters in order with the latter added with glucose, all the monitored indices could reach the A standard (GB 18918-2002, China).

Bioturbation of peanut worms Sipunculus nudus on the composition of prokaryotic communities in a tidal flat as revealed by 16S rRNA gene sequences.

To understand the impacts of peanut worms Sipunculus nudus on the prokaryotic community composition in a tidal flat, an onsite investigation was conducted in Suixi in the Beibu Gulf (109.82E, 21.35N) in the burrow sediments, non-burrow sediments and the sediments without peanut worm disturbance (control). The16S rRNA gene Illumina MiSeq sequencing was used to investigate the microbial communities and their response to bioturbation by S. nudus in a sandy tidal flat. A total of 18 bacteria phyla were detected, and Proteobacteria and Cyanobacteria constituted the majority of the prokaryotic community in the samples. The distribution of the relative abundances of genera showed that approximately 6.99%-17% of the reads in the samples were classified into 25 known genera. Sulfate-reducing bacteria (Desulfococcus and Desulfosarcina) were the most abundant taxa, followed by Thermodesulfovibrionaceae LCP-6, indicating that sulfate reduction is the main process in the sandy tidal flat. The abundances of Desulfococcus, LCP-6 and Cyanobacterium in the non-burrow sediment were greater than in the burrow sediment, suggesting that the anoxic condition is more suitable for Desulfococcus and LCP-6 when the activity of S. nudus is absent. The biomass of Cyanobacterium was decreased by the feeding bioturbation of S. nudus. Meanwhile, the relative abundance of the Bacteroidetes Luteimonas in the burrow sediments was significantly greater than in the non-burrow sediment, and there was a strong relationship between S. nudus bioturbation and increased in oxygen contents and oxidation-reduction potentials in the burrow sediment. The abundances of Desulfococcus and LCP-6 were greater in the middle layer (20-30 cm) than in the top layer in the non-burrow sediment. However, the middle and bottom layers (20-30, 30-40 cm) had higher abundances of these genera than did the upper layers (0-10, 10-20 cm) in the burrow sediments. The abundances of the Fusobacteria Propionigenium and the Spirochaetes Spirochaeta were greater in the middle and bottom layers (20-30 cm, 30-40 cm) than in the top layers (0-10, 10-20 cm) in the burrow sediment, but this phenomenon was not found in the non-burrow sediment. This study demonstrates that bioturbation by S. nudus plays an important role in reshaping the bacterial community composition in intertidal regions.

Role of Shellfish Aquaculture in the Reduction of Eutrophication in an Urban Estuary.

Land-based management has reduced nutrient discharges; however, many coastal waterbodies remain impaired. Oyster "bioextraction" of nutrients and how oyster aquaculture might complement existing management measures in urban estuaries was examined in Long Island Sound, Connecticut. Eutrophication status, nutrient removal, and ecosystem service values were estimated using eutrophication, circulation, local- and ecosystem-scale models, and an avoided-costs valuation. System-scale modeling estimated that 1.31% and 2.68% of incoming nutrients could be removed by current and expanded production, respectively. Up-scaled local-scale results were similar to system-scale results, suggesting that this up-scaling method could be useful in bodies of water without circulation models. The value of removed nitrogen was estimated using alternative management costs (e.g., wastewater treatment) as representative, showing ecosystem service values of $8.5 and $470 million per year for current and maximum expanded production, respectively. These estimates are conservative; removal by clams in Connecticut, oysters and clams in New York, and denitrification are not included. Optimistically, the calculation of oyster-associated removal from all leases in both states (5% of bottom area) plus denitrification losses showed increases to 10%-30% of annual inputs, which would be higher if clams were included. Results are specific to Long Island Sound, but the approach is transferable to other urban estuaries.

Overview of integrative tools and methods in assessing ecological integrity in estuarine and coastal systems worldwide.

In recent years, several sets of legislation worldwide (Oceans Act in USA, Australia or Canada; Water Framework Directive or Marine Strategy in Europe, National Water Act in South Africa, etc.) have been developed in order to address ecological quality or integrity, within estuarine and coastal systems. Most such legislation seeks to define quality in an integrative way, by using several biological elements, together with physico-chemical and pollution elements. Such an approach allows assessment of ecological status at the ecosystem level ('ecosystem approach' or 'holistic approach' methodologies), rather than at species level (e.g. mussel biomonitoring or Mussel Watch) or just at chemical level (i.e. quality objectives) alone. Increasing attention has been paid to the development of tools for different physico-chemical or biological (phytoplankton, zooplankton, benthos, algae, phanerogams, fishes) elements of the ecosystems. However, few methodologies integrate all the elements into a single evaluation of a water body. The need for such integrative tools to assess ecosystem quality is very important, both from a scientific and stakeholder point of view. Politicians and managers need information from simple and pragmatic, but scientifically sound methodologies, in order to show to society the evolution of a zone (estuary, coastal area, etc.), taking into account human pressures or recovery processes. These approaches include: (i) multidisciplinarity, inherent in the teams involved in their implementation; (ii) integration of biotic and abiotic factors; (iii) accurate and validated methods in determining ecological integrity; and (iv) adequate indicators to follow the evolution of the monitored ecosystems. While some countries increasingly use the establishment of marine parks to conserve marine biodiversity and ecological integrity, there is awareness (e.g. in Australia) that conservation and management of marine ecosystems cannot be restricted to Marine Protected Areas but must include areas outside such reserves. This contribution reviews the current situation of integrative ecological assessment worldwide, by presenting several examples from each of the continents: Africa, Asia, Australia, Europe and North America.