超声技术在抑郁症诊疗中的作用研究及应用进展

超声波作为一种机械振动波,兼具波动效应、力学效应和热效应.这3种效应在临床中均有较大应用价值,可用于疾病的成像诊断、辅助给药、调控以及热消融治疗等.超声技术所具有的非侵入性、穿透力强、空间分辨率高等特性,使其在神经系统疾病的诊断和治疗中具有广泛的应用前景.而抑郁症作为一种常见的精神疾病,其诊断和治疗都面临很大的困难.因此,大量学者将超声技术应用于抑郁症诊疗.本文主要从超声成像、超声定点给药、超声调控、超声诱导抑郁几个方面总结近十年来超声技术在抑郁症中的应用,以期为研究抑郁症发病机制及诊疗提供一定的参考和帮助.     

Genomic Consequences of Long-Term Population Decline in Brown Eared Pheasant

Population genetic theory and empirical evidence indicate that deleterious alleles can be purged in small populations. However, this viewpoint remains controversial. It is unclear whether natural selection is powerful enough to purge deleterious mutations when wild populations continue to decline. Pheasants are terrestrial birds facing a long-term risk of extinction as a result of anthropogenic perturbations and exploitation. Nevertheless, there are scant genomics resources available for conservation management and planning. Here, we analyzed comparative population genomic data for the three extant isolated populations of Brown eared pheasant (Crossoptilon mantchuricum) in China. We showed that C. mantchuricum has low genome-wide diversity and a contracting effective population size because of persistent declines over the past 100,000 years. We compared genome-wide variation in C. mantchuricum with that of its closely related sister species, the Blue eared pheasant (C. auritum) for which the conservation concern is low. There were detrimental genetic consequences across all C. mantchuricum genomes including extended runs of homozygous sequences, slow rates of linkage disequilibrium decay, excessive loss-of-function mutations, and loss of adaptive genetic diversity at the major histocompatibility complex region. To the best of our knowledge, this study is the first to perform a comprehensive conservation genomic analysis on this threatened pheasant species. Moreover, we demonstrated that natural selection may not suffice to purge deleterious mutations in wild populations undergoing long-term decline. The findings of this study could facilitate conservation planning for threatened species and help recover their population size.     

小胶质细胞极化与抑郁症关系的研究进展

小胶质细胞控制着中枢神经系统主要的免疫功能,在各种精神疾病中发挥重要作用. 某些信号通路的激活引发的神经炎症与抑郁症的发生有着密切的关系. 小胶质细胞是神经炎症的主要介导者,不同的刺激促进小胶质细胞极化,不同极化类型的小胶质细胞能分泌多种炎性细胞因子,在神经炎症调节中具有重要的作用. 临床研究和体内外实验研究表明,抑郁症与小胶质细胞极化介导的神经炎症有关. 小胶质细胞极化参与抑郁症发生发展的可能机制包括NF-κB信号通路激活、呼吸爆发、补体受体3信号通路、NLRP3炎症激活、cannibalism受体1、Notch-1信号通路和过氧化物酶体增殖物激活受体γ的激活. 本文就小胶质细胞极化与抑郁关系的研究进展作一综述.     

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.     

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.