Advances in neurobiology最新文献

Amyotrophic lateral sclerosis (ALS) is a complex disease impacting motor neurons of the brain, brainstem, and spinal cord. Disease etiology is quite heterogeneous with over 40 genes causing the disease and a vast ~90% of patients having no prior family history. Astrocytes are major contributors to ALS, particularly through involvement in accelerating disease progression. Through study of genetic forms of disease including SOD1, TDP43, FUS, C9orf72, VCP, TBK1, and more recently patient-derived cells from sporadic individuals, many biological mechanisms have been identified to cause intrinsic or glial-mediated neurotoxicity to motor neurons. Overall, many of the normally supportive and beneficial roles that astrocytes contribute to neuronal health and survival instead switch to become deleterious and neurotoxic. While the exact pathways may differ based on disease-origin, altered astrocyte-neuron communication is a common feature of ALS. Within this chapter, distinct genetic forms are examined in detail, along with what is known from sporadic patient-derived cells. Overall, this chapter highlights the interplay between astrocytes and neurons in this complex disease and describes the key features underlying: astrocyte-mediated motor neuron toxicity, excitotoxicity, oxidative/nitrosative stress, protein dyshomeostasis, metabolic imbalance, inflammation, trophic factor withdrawal, blood-brain/blood-spinal cord barrier involvement, disease spreading, and the extracellular matrix/cell adhesion/TGF-β signaling pathways.

In the intricate landscape of neurophysiology, astrocytes have been traditionally cast as homeostatic cells; however, their mechanistic involvement in allostasis-particularly how they modulate the adaptive response to stress and its accumulative impact that disrupts cognitive functions and precipitates psychiatric disorders-is now starting to be unraveled. Here, we address the gap by positing astrocytes as crucial allostatic players whose molecular adaptations underlie cognitive flexibility in stress-related neuropsychiatric conditions. We review how astrocytes, responding to stress mediators such as glucocorticoid and epinephrine/norepinephrine, undergo morphological and functional transformations that parallel the maladaptive changes. Our synthesis of recent findings reveals that these glial changes, especially in the metabolically demanding prefrontal cortex, may underlie some of the neuropsychiatric mechanisms characterized by the disruption of energy metabolism and astrocytic networks, compromised glutamate clearance, and diminished synaptic support. We argue that astrocytes extend beyond their homeostatic role, actively participating in the brain's allostatic response, especially by modulating energy substrates critical for cognitive functions.

Microglial cells are unique tissue-resident macrophages located in the parenchyma of the central nervous system (CNS). A recent comparative transcriptional study on microglia across more than 20 species from leach across chicken and many more up to humans revealed multiple conserved features. The results indicate the imperative role of microglia over the last 500 million years (Geirsdottir et al. Cell 181:746, 2020). Improved understanding of microglial evolution provides essential insights into conserved and divergent microglial pathways and will have implications for future development of microglia-based therapies to treat CNS disorders. Not only therapeutic approaches may be rethought, but also the understanding of sex specificity of the immune system within the CNS needs to be renewed. Besides revealing the highly detailed characteristics of microglia, the former paradigm of microglia being the only CNS-resident immune cells was outdated by the identification of CNS-associated macrophages (CAMs) as CNS interface residents, who, most likely, accompanied microglia in evolution over the past million years.

From the morphological point of view, the nervous system exhibits a fractal, self-similar geometry at various levels of observations, from single cells up to cell networks. From the functional point of view, it is characterized by a hierarchical organization in which self-similar structures (networks) of different miniaturizations are nested within each other. In particular, neuronal networks, interconnected to form neuronal systems, are formed by neurons, which operate thanks to their molecular networks, mainly having proteins as components that via protein-protein interactions can be assembled in multimeric complexes working as micro-devices. On this basis, the term "self-similarity logic" was introduced to describe a nested organization where, at the various levels, almost the same rules (logic) to perform operations are used. Self-similarity and self-similarity logic both appear to be intimately linked to the biophysical evidence for the nervous system being a pattern-forming system that can flexibly switch from one coherent state to another. Thus, they can represent the key concepts to describe its complexity and its concerted, holistic behavior.

Fractal analysis has emerged as a powerful tool for characterizing irregular and complex patterns found in the nervous system. This characterization is typically applied by estimating the fractal dimension (FD), a scalar index that describes the topological complexity of the irregular components of the nervous system, both at the macroscopic and microscopic levels, that may be viewed as geometric fractals. Moreover, temporal properties of neurophysiological signals can also be interpreted as dynamic fractals. Given its sensitivity for detecting changes in brain morphology, FD has been explored as a clinically relevant marker of brain damage in several neuropsychiatric conditions as well as in normal and pathological cerebral aging. In this sense, evidence is accumulating for decreases in FD in Alzheimer's disease, frontotemporal dementia, Parkinson's disease, multiple sclerosis, and many other neurological disorders. In addition, it is becoming increasingly clear that fractal analysis in the field of clinical neurology opens the possibility of detecting structural alterations in the early stages of the disease, which highlights FD as a potential diagnostic and prognostic tool in clinical practice.

Over the past 40 years, from its classical application in the characterization of geometrical objects, fractal analysis has been progressively applied to study time series in several different disciplines. In neuroscience, starting from identifying the fractal properties of neuronal and brain architecture, attention has shifted to evaluating brain signals in the time domain. Classical linear methods applied to analyzing neurophysiological signals can lead to classifying irregular components as noise, with a potential loss of information. Thus, characterizing fractal properties, namely, self-similarity, scale invariance, and fractal dimension (FD), can provide relevant information on these signals in physiological and pathological conditions. Several methods have been proposed to estimate the fractal properties of these neurophysiological signals. However, the effects of signal characteristics (e.g., its stationarity) and other signal parameters, such as sampling frequency, amplitude, and noise level, have partially been tested. In this chapter, we first outline the main properties of fractals in the domain of space (fractal geometry) and time (fractal time series). Then, after providing an overview of the available methods to estimate the FD, we test them on synthetic time series (STS) with different sampling frequencies, signal amplitudes, and noise levels. Finally, we describe and discuss the performances of each method and the effect of signal parameters on the accuracy of FD estimation.

Arteriovenous malformations (AVMs) are cerebrovascular lesions consisting of a pathologic tangle of the vessels characterized by a core termed the nidus, which is the "nest" where the fistulous connections occur. AVMs can cause headache, stroke, and/or seizures. Their treatment can be challenging requiring surgery, endovascular embolization, and/or radiosurgery as well. AVMs' morphology varies greatly among patients, and there is still a lack of standardization of angioarchitectural parameters, which can be used as morphometric parameters as well as potential clinical biomarkers (e.g., related to prognosis).In search of new diagnostic and prognostic neuroimaging biomarkers of AVMs, computational fractal-based models have been proposed for describing and quantifying the angioarchitecture of the nidus. In fact, the fractal dimension (FD) can be used to quantify AVMs' branching pattern. Higher FD values are related to AVMs characterized by an increased number and tortuosity of the intranidal vessels or to an increasing angioarchitectural complexity as a whole. Moreover, FD has been investigated in relation to the outcome after Gamma Knife radiosurgery, and an inverse relationship between FD and AVM obliteration was found.Taken altogether, FD is able to quantify in a single and objective value what neuroradiologists describe in qualitative and/or semiquantitative way, thus confirming FD as a reliable morphometric neuroimaging biomarker of AVMs and as a potential surrogate imaging biomarker. Moreover, computational fractal-based techniques are under investigation for the automatic segmentation and extraction of the edges of the nidus in neuroimaging, which can be relevant for surgery and/or radiosurgery planning.

The dynamics of tumor growth is a very complex process, generally accompanied by numerous chromosomal aberrations that determine its genetic and dynamical heterogeneity. Consequently, the tumor interface exhibits a non-regular and heterogeneous behavior often described by a single fractal dimension. A more suitable approach is to consider the tumor interface as a multifractal object that can be described by a set of generalized fractal dimensions. In the present work, detrended fluctuation and multifractal analysis are used to characterize the complexity of glioblastoma.

Temporomandibular joint disorders include a variety of clinical syndromes that are difficult to manage if associated with debilitating severe jaw pain. Thus, seeking additional experimental therapies for temporomandibular joint pain reduction is warranted. Targeted enkephalin gene therapy approaches provide clear promise for pain control. The studies detailed here indicate significant analgesia and protection of joint tissue are provided after injection of an overexpression viral vector gene therapy near the joint. The viral vector gene therapy described provides overexpression of naturally occurring opioid peptides after its uptake by trigeminal nerve endings. The viral vectors act as independent "minipump" sources for the opioid peptide synthesis in the neuronal cytoplasm producing the intended biological function, reduction of pain, and tissue repair. The antinociceptive effects provided with this delivery method of opioid expression persist for over 4 weeks. This is coincident with the expected time frame for the duration of the transgene overproduction of the endogenous opioid peptide before its diminution due to dormancy of the virus. These experimental studies establish a basis for the use of replication-defective herpes simplex type 1-based gene therapy for severe chronic inflammatory temporomandibular joint destruction and pain. As innovative means of significantly reducing joint inflammation and preserving tissue architecture, gene therapies may extend their clinical usefulness for patients with temporomandibular joint disorders.

The opioid system involves opioid receptors (OPRs) and endogenous opioid peptides.This chapter will focus on the distribution of OPRs in the cardiovascular system, the expression pattern in the heart, the activation by opioid peptides, and the effects of OPRs activation with potential relevance in cardiovascular performance. In the heart, OPRs are co-expressed with beta adrenergic receptors (β-ARs) in the G-protein-coupled receptor (GPCR) superfamily, functionally cross-talk with β-Ars and modify catecholamine-induced effects. They are involved in cardiac contractility, energy metabolism, myocyte survival or death, vascular resistance. The effects of the opioid system in the regulation of systemic circulation at both the central and peripheral level are presented. The pathways are discussed under physiological (i.e., aging) and pathological conditions (atherosclerosis, heart failure, essential hypertension, ischemic stress). Stimulation of OPRs not only inhibits cardiac excitation-contraction coupling, but also protects the heart against hypoxic and ischemic injury. An enhanced sensitivity to opioids of endocrine organs and neuronal systems is operative in hypertensive patients. The opioid system can be pharmacologically engaged to selectively mimic these responses via cardiac and nervous signaling. The clinical opportunities for the use of cardioprotective effects of opioids require future investigations to provide more specific details of the impact on cardiac performance and electrophysiological properties.