Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach

Deep learning techniques have recently made considerable advances in the field of artificial intelligence. These methodologies can assist psychologists in early diagnosis of mental disorders and preventing severe trauma. Major Depression Disorder (MDD) is a common and serious medical condition whose exact manifestations are not fully understood. So, early discovery of MDD patients helps to cure or limit the adverse effects. Electroencephalogram (EEG) is prominently used to study brain diseases such as MDD due to having high temporal resolution information, and being a noninvasive, inexpensive and portable method. This paper has proposed an EEG-based deep learning framework that automatically discriminates MDD patients from healthy controls. First, the relationships among EEG channels in the form of effective brain connectivity analysis are extracted by Generalized Partial Directed Coherence (GPDC) and Direct directed transfer function (dDTF) methods. A novel combination of sixteen connectivity methods (GPDC and dDTF in eight frequency bands) was used to construct an image for each individual. Finally, the constructed images of EEG signals are applied to the five different deep learning architectures. The first and second algorithms were based on one and two-dimensional convolutional neural network (1DCNN–2DCNN). The third method is based on long short-term memory (LSTM) model, while the fourth and fifth algorithms utilized a combination of CNN with LSTM model namely, 1DCNN-LSTM and 2DCNN-LSTM. The proposed deep learning architectures automatically learn patterns in the constructed image of the EEG signals. The efficiency of the proposed algorithms is evaluated on resting state EEG data obtained from 30 healthy subjects and 34 MDD patients. The experiments show that the 1DCNN-LSTM applied on constructed image of effective connectivity achieves best results with accuracy of 99.24% due to specific architecture which captures the presence of spatial and temporal relations in the brain connectivity. The proposed method as a diagnostic tool is able to help clinicians for diagnosing the MDD patients for early diagnosis and treatment.     

乡村景观生物多样性研究进展

乡村景观是一种人文和自然共生的复合生态系统, 为生物多样性的维持提供了支持。目前, 中国传统乡村地区生物多样性的维持正面临着农业集约化、人工林树种单一化、非农业用地急剧扩张及生态传承机制解体等复杂多样的威胁, 亟待展开深入研究。本文在总结乡村景观生物多样性相关概念及特征的基础上, 通过文献分析概括了国际乡村景观生物多样性的热点研究方向, 包括农业集约化下的生物多样性管理、区域尺度乡村景观与生物多样性的协同关系、局地尺度不同乡村景观类型的物种多样性及乡村景观中的生物文化多样性, 进一步梳理了国内在相关研究方向上的主要进展并指出研究不足。在此基础上提出未来研究展望, 包括突出生物文化多样性特征、加强多时空尺度分析、深化动态维持机制研究、推进生物多样性研究在乡村生态景观规划中的全过程应用等建议。     

Cross-scale quality assessment of a mechanistic cation exchange chromatography model

Cation exchange chromatography (CEX) is an essential part of most monoclonal antibody (mAb) purification platforms. Process characterization and root cause investigation of chromatographic unit operations are performed using scale down models (SDM). SDM chromatography columns typically have the identical bed height as the respective manufacturing-scale, but a significantly reduced inner diameter. While SDMs enable process development demanding less material and time, their comparability to manufacturing-scale can be affected by variability in feed composition, mobile phase and resin properties, or dispersion effects depending on the chromatography system at hand. Mechanistic models can help to close gaps between scales and reduce experimental efforts compared to experimental SDM applications. In this study, a multicomponent steric mass-action (SMA) adsorption model was applied to the scale-up of a CEX polishing step. Based on chromatograms and elution pool data ranging from laboratory- to manufacturing-scale, the proposed modeling workflow enabled early identification of differences between scales, for example, system dispersion effects or ionic capacity variability. A multistage model qualification approach was introduced to measure the model quality and to understand the model's limitations across scales. The experimental SDM and the in silico model were qualified against large-scale data using the identical state of the art equivalence testing procedure. The mechanistic chromatography model avoided limitations of the SDM by capturing effects of bed height, loading density, feed composition, and mobile phase properties. The results demonstrate the applicability of mechanistic chromatography models as a possible alternative to conventional SDM approaches.     

Intergenerational effects of inbreeding in Nicrophorus vespilloides: offspring suffer fitness costs when either they or their parents are inbred

Inbreeding depression is the reduction in fitness caused by mating between related individuals. Inbreeding is expected to cause a reduction in offspring fitness when the offspring themselves are inbred, but outbred individuals may also suffer a reduction in fitness when they depend on care from inbred parents. At present, little is known about the significance of such intergenerational effects of inbreeding. Here, we report two experiments on the burying beetle Nicrophorus vespilloides, an insect with elaborate parental care, in which we investigated inbreeding depression in offspring when either the offspring themselves or their parents were inbred. We found substantial inbreeding depression when offspring were inbred, including reductions in hatching success of inbred eggs and survival of inbred offspring. We also found substantial inbreeding depression when parents were inbred, including reductions in hatching success of eggs produced by inbred parents and survival of outbred offspring that received care from inbred parents. Our results suggest that intergenerational effects of inbreeding can have substantial fitness costs to offspring, and that future studies need to incorporate such costs to obtain accurate estimates of inbreeding depression.     

On the genetic parameter determining the efficiency of purging: an estimate for Drosophila egg‐to‐pupae viability

The consequences of inbreeding on fitness can be crucial in evolutionary and conservation grounds and depend upon the efficiency of purging against deleterious recessive alleles. Recently, analytical expressions have been derived to predict the evolution of mean fitness, taking into account both inbreeding and purging, which depend on an ‘effective purging coefficient (d_e)’. Here, we explore the validity of that predictive approach and assay the strength of purging by estimating d_e for egg‐to‐pupae viability (EPV) after a drastic reduction in population size in a recently captured base population of Drosophila melanogaster. For this purpose, we first obtained estimates of the inbreeding depression rate (δ) for EPV in the base population, and we found that about 40% was due to segregating recessive lethals. Then, two sets of lines were founded from this base population and were maintained with different effective size throughout the rest of the experiment (N = 6; N = 12), their mean EPV being assayed at different generations. Due to purging, the reductions in mean EPV experienced by these lines were considerably smaller than the corresponding neutral predictions. For the 60% of δ attributable to nonlethal deleterious alleles, our results suggest an effective purging coefficient d_e > 0.02. Similarly, we obtain that d_e > 0.09 is required to roughly account for purging against the pooled inbreeding depression from lethal and nonlethal deleterious alleles. This implies that purging should be efficient for population sizes of the order of a few tens and larger, but might be inefficient against nonlethal deleterious alleles in smaller populations.     

Temperature stress and survival ability of Mediterranean sclerophyllous plants

ABSTRACT

The Mediterranean climate with hot and dry summer periods, and low winter temperatures and episodic frosts in northern, altitudinal and continental districts, demands from evergreen broadleaved woody plants an adequate and flexible acclimation to the climatic constraints.

In this brief survey on some responses of Mediterranean sclerophylls to temperature stress, the following is presented and discussed: criteria for cold and heat limits of photosynthetic function; winter depression and summer photoinactivation of photosynthesis; peculiar patterns of tissue freezing of scleromorphous leaves and limits of frost resistance of various plant parts and ontogenetic stages; heat impairment of chloroplasts and thermotolerance of sclerophyllous species; survival capacity and recovery after damage. Risks of damage to plants in relation to stressful temperatures in Mediterranean regions are estimated. Cold stress and drought stress indices, according to Mitrakos (1980), have been applied to characterise different localities in Italy. Additionally, a heat stress index for the Mediterranean region is proposed. Future research topics are suggested.     

Local temperatures inferred from plant communities suggest strong spatial buffering of climate warming across Northern Europe

Recent studies from mountainous areas of small spatial extent (<2500 km²) suggest that fine‐grained thermal variability over tens or hundreds of metres exceeds much of the climate warming expected for the coming decades. Such variability in temperature provides buffering to mitigate climate‐change impacts. Is this local spatial buffering restricted to topographically complex terrains? To answer this, we here study fine‐grained thermal variability across a 2500‐km wide latitudinal gradient in Northern Europe encompassing a large array of topographic complexities. We first combined plant community data, Ellenberg temperature indicator values, locally measured temperatures (LmT) and globally interpolated temperatures (GiT) in a modelling framework to infer biologically relevant temperature conditions from plant assemblages within <1000‐m² units (community‐inferred temperatures: CiT). We then assessed: (1) CiT range (thermal variability) within 1‐km² units; (2) the relationship between CiT range and topographically and geographically derived predictors at 1‐km resolution; and (3) whether spatial turnover in CiT is greater than spatial turnover in GiT within 100‐km² units. Ellenberg temperature indicator values in combination with plant assemblages explained 46–72% of variation in LmT and 92–96% of variation in GiT during the growing season (June, July, August). Growing‐season CiT range within 1‐km² units peaked at 60–65°N and increased with terrain roughness, averaging 1.97 °C (SD = 0.84 °C) and 2.68 °C (SD = 1.26 °C) within the flattest and roughest units respectively. Complex interactions between topography‐related variables and latitude explained 35% of variation in growing‐season CiT range when accounting for sampling effort and residual spatial autocorrelation. Spatial turnover in growing‐season CiT within 100‐km² units was, on average, 1.8 times greater (0.32 °C km^?1) than spatial turnover in growing‐season GiT (0.18 °C km^?1). We conclude that thermal variability within 1‐km² units strongly increases local spatial buffering of future climate warming across Northern Europe, even in the flattest terrains.     

Environmental gradients shift the direction of the relationship between native and alien plant species richness

Aim

To assess how environmental, biotic and anthropogenic factors shape native–alien plant species richness relationships across a heterogeneous landscape.

Location

Banks Peninsula, New Zealand.

Methods

We integrated a comprehensive floristic survey of over 1200 systematically located 6 × 6 m plots, with corresponding climate, environmental and anthropogenic data. General linear models examined variation in native and alien plant species richness across the entire landscape, between native‐ and alien‐dominated plots, and within separate elevational bands.

Results

Across all plots, there was a significant negative correlation between native and alien species richness, but this relationship differed within subsets of the data: the correlation was positive in alien‐dominated plots but negative in native‐dominated plots. Within separate elevational bands, native and alien species richness were positively correlated at lower elevations, but negatively correlated at higher elevations. Alien species richness tended to be high across the elevation gradient but peaked in warmer, mid‐ to low‐elevation sites, while native species richness increased linearly with elevation. The negative relationship between native and alien species richness in native‐dominated communities reflected a land‐use gradient with low native and high alien richness in more heavily modified native‐dominated vegetation. In contrast, native and alien richness were positively correlated in very heavily modified alien‐dominated plots, most likely due to covariation along a gradient of management intensity.

Main conclusions

Both positive and negative native–alien richness relationships can occur across the same landscape, depending on the plant community and the underlying human and environmental gradients examined. Human habitat modification, which is often confounded with environmental variation, can result in high alien and low native species richness in areas still dominated by native species. In the most heavily human modified areas, dominated by alien species, both native and alien species may be responding to similar underlying gradients.

     

Integrating frugivory and animal movement: a review of the evidence and implications for scaling seed dispersal

General principles about the consequences of seed dispersal by animals for the structure and dynamics of plant populations and communities remain elusive. This is in part because seed deposition patterns emerge from interactions between frugivore behaviour and the distribution of food resources, both of which can vary over space and time. Here we advocate a frugivore‐centred, process‐based, synthetic approach to seed dispersal research that integrates seed dispersal ecology and animal movement across multiple spatio‐temporal scales. To guide this synthesis, we survey existing literature using paradigms from seed dispersal and animal movement. Specifically, studies are discussed with respect to five criteria: selection of focal organisms (animal or plant); measurement of animal movement; characterization of seed shadow; animal, plant and environmental factors included in the study; and scales of the study. Most studies focused on either frugivores or plants and characterized seed shadows directly by combining gut retention time with animal movement data or indirectly by conducting maternity analysis of seeds. Although organismal traits and environmental factors were often measured, they were seldom used to characterize seed shadows. Multi‐scale analyses were rare, with seed shadows mostly characterized at fine spatial scales, over single fruiting seasons, and for individual dispersers. Novel animal‐ and seed‐tracking technologies, remote environmental monitoring tools, and advances in analytical methods can enable effective implementation of a hierarchical mechanistic approach to the study of seed dispersal. This kind of mechanistic approach will provide novel insights regarding the complex interplay between the factors that modulate animal behaviour and subsequently influence seed dispersal patterns across spatial and temporal scales.