Firing Patterns Research Articles

Balancing brain metabolic states during sickness and recovery sleep.

Sickness sleep and rebound following sleep deprivation share humoral signals including the rise of cytokines, in particular interleukins. Nevertheless, they represent unique physiological states with unique brain firing patterns and involvement of specific circuitry. Here, we performed untargeted metabolomics of mouse cortex and hippocampus to uncover changes with sickness and rebound sleep as compared with normal daily sleep. We found that the three settings are biochemically unique with larger differences in the cortex than in the hippocampus. Both sickness and rebound sleep shared an increase in tryptophan. Surprisingly, these two sleep conditions showed opposite modulation of the methionine-homocysteine cycle and differences in terms of the energetic signature, with sickness impinging on glycolysis intermediates whilst rebound increased the triphosphorylated form of nucleotides. These findings indicate that rebound following sleep deprivation stimulates an energy rich setting in the brain that is devoid during sickness sleep.

Using Paleoecological Methods to Study Long-Term Disturbance Patterns in High-Elevation Whitebark Pine Ecosystems

Pinus albicaulis (whitebark pine) is a keystone species, providing food and habitat to wildlife, in high-elevation ecological communities. In recent years, this important species has been negatively impacted by changes in fire regimes, increased Dendroctonus ponderosae (mountain pine beetle) outbreaks associated with human landscape and climate modification, and the continued impact of the non-native Cronartium ribicola (white pine blister rust). This research investigates changes in fire occurrence, the establishment of Pinus albicaulis, and fuel availability at a high-elevation site in the Sawtooth National Recreation Area, Idaho, USA. Charcoal and pollen analyses were used to reconstruct fire and vegetation patterns for Phyllis Lake, Idaho, USA, over the past ~8200 cal y BP. We found that significant fire episodes occurred when the pollen accumulation rates (PARs) indicated more arboreal fuel availability, and we identified that Pinus albicaulis became well established at the site ~7200 cal y BP. The high-elevation nature of Phyllis Lake (2800 m) makes this record unique, as there are not many paleorecords at this high elevation from the Northern Rocky Mountains, USA. Additional high-elevation sites in Pinus albicaulis habitats will provide critical insight into the long-term dynamics of this threatened species.

Low power tactile sensory neuron using nanoparticle-based strain sensor and memristor

Endowing strain sensors with neuromorphic computing capabilities could permit the efficient processing of tactile information on the edge. The realization of such functionalities from a simple circuit without software processing holds promise for attaining skin-based perception. Here, leveraging the intrinsic neuronal plasticity of memristive neurons, various firing patterns induced by the applied strain were demonstrated. More specifically, tonic, bursting, transition from tonic to bursting, adaptive, and nociceptive activities were captured. The implementation of these patterns permits the facile translation of the analog pressure signals into digital spikes, attaining accurate perception of various tactile characteristics. The tactile sensory neuron consisting of an RC circuit was composed of a SiO2-based conductive bridge memristor exhibiting leaky integrate-and-fire properties and a Pt nanoparticles (NPs)-based strain sensor with a gauge factor of ∼270. A dense layer of Pt NPs was also used as the bottom electrode for the memristive element, yielding the manifestation of a threshold switching mode with a switching voltage of only ∼350 mV and an exceptional switching ratio of 107. Our work provides valuable insights for developing low power neurons with tactile feedback for prosthetics and robotics applications.

VTA dopamine neurons are hyperexcitable in 3xTg-AD mice due to casein kinase 2-dependent SK channel dysfunction

Alzheimer’s disease (AD) patients exhibit neuropsychiatric symptoms that extend beyond classical cognitive deficits, suggesting involvement of subcortical areas. Here, we investigated the role of midbrain dopamine (DA) neurons in AD using the amyloid + tau-driven 3xTg-AD mouse model. We found deficits in reward-based operant learning in AD mice, suggesting possible VTA DA neuron dysregulation. Physiological assessment revealed hyperexcitability and disrupted firing in DA neurons caused by reduced activity of small-conductance calcium-activated potassium (SK) channels. RNA sequencing from contents of single patch-clamped DA neurons (Patch-seq) identified up-regulation of the SK channel modulator casein kinase 2 (CK2), which we corroborated by immunohistochemical protein analysis. Pharmacological inhibition of CK2 restored SK channel activity and normal firing patterns in 3xTg-AD mice. These findings identify a mechanism of ion channel dysregulation in VTA DA neurons that could contribute to behavioral abnormalities in AD, paving the way for novel treatment strategies.

Existence and stability criteria for global synchrony and for synchrony in two alternating clusters of pulse-coupled oscillators updated to include conduction delays

Phase Response Curves (PRCs) have been useful in determining and analyzing various phase-locking modes in networks of oscillators under pulse-coupling assumptions, as reviewed in Mathematical Biosciences, 226:77–96, 2010. Here, we update that review to include progress since 2010 on pulse coupled oscillators with conduction delays. We then present original results that extend the derivation of the criteria for stability of global synchrony in networks of pulse-coupled oscillators to include conduction delays. We also incorporate conduction delays to extend previous studies that showed how an alternating firing pattern between two synchronized clusters could enforce within-cluster synchrony, even for clusters unable to synchronize themselves in isolation. To obtain these results, we used self-connected neurons to represent clusters. These results greatly extend the applicability of the stability analyses to networks of pulse-coupled oscillators since conduction delays are ubiquitous and strongly impact the stability of synchrony. Although these analyses only strictly apply to identical oscillators with identical connections to other oscillators, the principles are general and suggest how to promote or impede synchrony in physiological networks of neurons, for example. Heterogeneity can be interpreted as a form of frozen noise, and approximate synchrony can be sustained despite heterogeneity. The pulse-coupled oscillator model can not only be used to describe biological neuronal networks but also cardiac pacemakers, lasers, fireflies, artificial neural networks, social self-organization, and wireless sensor networks.

The retrosplenial cortical role in delayed spatial alternation

The retrosplenial cortex (RSC) plays an important role in spatial cognition. RSC neurons exhibit a variety of spatial firing patterns and lesion studies have found that the RSC is necessary for spatial working memory tasks. However, little is known about how RSC neurons might encode spatial memory during a delay period. In the present study, we trained control rats and rats with excitotoxic lesions of the RSC on spatial alternation task with varying delay durations and in a separate group of rats, we recorded RSC neuronal activity as the rats performed the alternation task. We found that RSC lesions significantly impaired alternation performance, particularly at the longest delay duration. We also found that RSC neurons exhibited reliably different firing patterns throughout the delay periods preceding left and right trials, consistent with a working memory signal. These differential firing patterns were absent during the delay periods preceding errors. We also found that many RSC neurons exhibit a large spike in firing rate leading up to the start of the trial. Many of these trial start responses also differentiated left and right trials, suggesting that they could play a role in priming the ‘go left’ or ‘go right’ behavioral responses. Our results suggest that these firing patterns represent critical memory information that underlies the RSC role in spatial working memory.

Multimodal spatiotemporal drug assessment platform based on a microelectrode neural network chip in Alzheimer’s disease

The pathogenesis of Alzheimer’s disease (AD) remains elusive. The development of new drugs is protracted, costly, and fraught with failure, largely due to the lack of convenient methods for dynamically studying the pathogenesis of AD and evaluating drug efficacy in vitro. There is a dearth of in vitro multi-site assay platforms capable of observing the therapeutic effects of AD drugs at the level of cellular and network. Consequently, an in vitro multimodal spatiotemporal drug assessment platform has been developed based on a neuronal network chip. It has a symmetric distribution of electrode points with two different sizes (10 μm and 30 μm), which are more suitable for the detection of neuronal connections. The multifaceted neurophysiological properties, including single neuron firing pattern, intercellular connection, transmission speed, and neural network communication, were detected in real time. The results demonstrated that the differences between experimental groups in electrophysiological properties, could significantly distinguish the effects of AD representative drug treatment after different levels of neurological injury. The administration of the drug at the initial stage of β-amyloid oligomers (AβOs) toxicity was found to effectively retard the deterioration of neurons and network (early stage: firing rate increased by 8 %; middle stage: cross-correlation coefficient decreased by 27 %; late stage: similarity index remained positive and relative transmission speed decreased by 11 %). The neurophysiological mechanism of drug interaction was further elucidated, which may provide the guidance for the optimal timing of drug administration. Following the further extension of biosensor longevity and the expansion of synchronous multidimensional parameter detection, including impedance and electrochemistry, it is anticipated that this will become a novel platform for the preclinical evaluation and screening of AD drugs.

Changes in motor unit firing pattern are associated with post-exercise blood pressure response in older untreated but not treated hypertensive adults.

This study aimed to determine the difference in motor unit (MU) firing pattern between hypertensive and normotensive individuals, and the relationship between MU firing pattern and post-exercise blood pressure (BP) response in older individuals. Fourteen older untreated (systolic/diastolic BP (SBP/DBP)≥130/80mmHg, 76 (5) years), 11 treated hypertensive (78 (4) years) and 14 normotensive (SBP/DBP<130/80mmHg, 71 (4) years) individuals were studied. Participants performed ramp-up exercises until 50% of maximal voluntary contraction (MVC) of knee extension and five MVCs. During the ramp-up exercise, high-density surface electromyography signals were recorded and each MU firing rate (FR) and recruitment threshold was assessed. The slope of the linear regression between MUFRs and recruitment thresholds was calculated to assess the MU firing pattern. Pre- and post-exercise blood pressure was measured. Change in (∆)SBP from pre- to post-exercise was greater in treated hypertensive than untreated hypertensive individuals (P=0.026). MUFR was lower in treated hypertensive than untreated hypertensive and normotensive individuals (P<0.001). Although the slope was not significantly different between groups (P=0.294), FRs of larger MUs were lower than those of smaller MUs in treated hypertensive and normotensive individuals (P<0.05) but sustained in untreated hypertensive individuals. The FRs of larger MUs and slope were positively correlated with the ∆SBP only in hypertensive individuals (r=0.768 and 0.715; P=0.044 and 0.020). MUFR was lower in treated hypertensive than untreated hypertensive and normotensive individuals. Furthermore, MU firing patterns were associated with the ∆SBP after exercise in older untreated hypertensive individuals, but this relationship was not observed in treated hypertensive and normotensive individuals.

Study on the Driving Factors of the Spatiotemporal Pattern in Forest Lightning Fires and 3D Fire Simulation Based on Cellular Automata

Lightning-induced forest fires frequently inflict substantial damage on forest ecosystems, with the Daxing’anling region in northern China recognized as a high-incidence region for such phenomena. To elucidate the occurrence patterns of forest fires caused by lightning and to prevent such fires, this study employs a multifaceted approach, including statistical analysis, kernel density estimation, and spatial autocorrelation analysis, to conduct a comprehensive examination of the spatiotemporal distribution patterns of lightning-induced forest fires in the Greater Khingan Mountains region from 2016–2020. Additionally, the geographical detector method is utilized to assess the explanatory power of three main factors: climate, topography, and fuel characteristics associated with these fires, encompassing both univariate and interaction detections. Furthermore, a mixed-methods approach is adopted, integrating the Zhengfei Wang model with a three-dimensional cellular automaton to simulate the spread of lightning-induced forest fire events, which is further validated through rigorous quantitative verification. The principal findings are as follows: (1) Spatiotemporal Distribution of Lightning-Induced Forest Fires: Interannual variability reveals pronounced fluctuations in the incidence of lightning-induced forest fires. The monthly concentration of incidents is most significant in May, July, and August, demonstrating an upward trajectory. In terms of temporal distribution, fire occurrences are predominantly concentrated between 1:00 PM and 5:00 PM, conforming to a normal distribution pattern. Spatially, higher incidences of fires are observed in the western and northwestern regions, while the eastern and southeastern areas exhibit reduced rates. At the township level, significant spatial autocorrelation indicates that Xing’an Town represents a prominent hotspot (p = 0.001), whereas Oupu Town is identified as a significant cold spot (p = 0.05). (2) Determinants of the Spatiotemporal Distribution of Lightning-Induced Forest Fires: The spatiotemporal distribution of lightning-induced forest fires is influenced by a multitude of factors. Univariate analysis reveals that the explanatory power of these factors varies significantly, with climatic factors exerting the most substantial influence, followed by topographic and fuel characteristics. Interaction factor analysis indicates that the interactive effects of climatic variables are notably more pronounced than those of fuel and topographical factors. (3) Three-Dimensional Cellular Automaton Fire Simulation Based on the Zhengfei Wang Model: This investigation integrates the fire spread principles from the Zhengfei Wang model into a three-dimensional cellular automaton framework to simulate the dynamic behavior of lightning-induced forest fires. Through quantitative validation against empirical fire events, the model demonstrates an accuracy rate of 83.54% in forecasting the affected fire zones.

Firing patterns transitions and resonance effects of the extended Hindmarsh-Rose neural model with Gaussian noise and transcranial magneto-acousto-electrical stimulation

Considering the fact that the typical three-variable Hindmarsh-Rose(HR) neural model has limitations in describing the complex non-linear features and precise behavior patterns of neuron, the influences of transcranial magneto-acousto-electrical stimulation(TMAES) on firing patterns and resonance effects are analyzed based on an extended HR neural model in this paper. Obtained results show that TMAES can induce transitions in the firing patterns of extended HR neuron, such as spiking and multi-periodic bursting state, etc If appropriate parameters are selected, the multimodal discharge modes can also be observed. Coefficient of variation is calculated to further investigate the effect of TMAES and Gaussian white noise on the firing rhythm of extended HR neuron, and relevant results indicate that TMAES can induce coherent resonance phenomena in HR neuronal systems similar to the effects of Gaussian white noise, which reveals a new mechanism of coherent resonance induced by TMAES. Further more, TMAES can also regulate coefficient of variation to exhibit anti-coherent resonance and multiple anti-coherent resonance structures, exhibiting richer regulatory functions than Gaussian white noise in regulating neuronal firing rhythm. This study seeks to enhance the understanding of the processes that influence the firing patterns and coherence degree of neuron under TMAES in neuroses or psychoses.

Severity of a megafire reduced by interactions of wildland fire suppression operations and previous burns

Abstract Burned area and proportion of high severity fire have been increasing in the western USA, and reducing wildfire severity with fuel treatments or other means is key for maintaining fire-prone dry forests and avoiding fire-catalyzed forest loss. Despite the unprecedented scope of firefighting operations in recent years, their contribution to patterns of wildfire severity is rarely quantified. Here we investigate how wildland fire suppression operations and past fire severity interacted to affect severity patterns of the northern third of the 374 000 ha Dixie Fire, the largest single fire in California history. We developed a map of the intensity and type of suppression operations and a statistical model of the Composite Burn Index (CBI) including weather, fuels, and terrain variables during the fire to quantify the importance of operations and prior fires on wildfire severity. Wildfire severity was estimated without operations and previous fires and then compared with modeled severity under observed conditions. Previous low and moderate-severity fire without operations decreased CBI by 38% and 19% respectively. Heavy operations and offensive firing in the footprint of past fires lowered fire severity even more compared to prior fire alone. Medium operations and defensive firing reduced but did not eliminate the moderating effects of past fires. This analysis demonstrates important interactions between suppression operations and previous burns that drive patterns of fire severity and vegetation dynamics in post-fire landscapes. Given the need to reduce wildfire severity to maintain forest resilience, particularly with a warming climate, increased attention to using operations and severity patterns of previous fires known to reduce wildfire severity in megafires are likely to increase forest resilience and improve ecological outcomes.

Dynamical effects of low-frequency and high-frequency current stimuli in a memristive Morris–Lecar neuron model

This paper deduces that the potassium and calcium ion currents in the two-dimensional (2D) Morris–Lecar neuron model can be respectively characterized by a passive memristor and a locally active memristor. Then a memristive Morris–Lecar neuron model with an equivalent circuit scheme is first constructed. The equilibrium trajectory and its stability are analyzed, which displays fold and Hopf bifurcations with proper model parameters. Bursting behavior and mixed-mode oscillations with after-depolarizing potential for low-frequency current stimulus are numerically disclosed. Besides, the bifurcation mechanisms for bursting behavior and mixed-mode oscillations are theoretically deduced. Furthermore, the firing patterns and antimonotonicity phenomenon for high-frequency current stimulus are numerically discovered. This study provides a new concept for building memristive bionic circuits from neuron models with well-defined ion channel currents.

Supercomputer framework for reverse engineering firing patterns of neuron populations to identify their synaptic inputs

In this study, we develop new reverse engineering (RE) techniques to identify the organization of the synaptic inputs generating firing patterns of populations of neurons. We tested these techniques in silico to allow rigorous evaluation of their effectiveness, using remarkably extensive parameter searches enabled by massively-parallel computation on supercomputers. We chose spinal motoneurons as our target neural system, since motoneurons process all motor commands and have well-established input-output properties. One set of simulated motoneurons was driven by 300,000+ simulated combinations of excitatory, inhibitory, and neuromodulatory inputs. Our goal was to determine if these firing patterns had sufficient information to allow RE identification of the input combinations. Like other neural systems, the motoneuron input-output system is likely non-unique. This non-uniqueness could potentially limit this RE approach, as many input combinations can produce similar outputs. However, our simulations revealed that firing patterns contained sufficient information to sharply restrict the solution space. Thus, our RE approach successfully generated estimates of the actual simulated patterns of excitation, inhibition, and neuromodulation, with variances accounted for ranging from 75–90%. It was striking that nonlinearities induced in firing patterns by the neuromodulation inputs did not impede RE, but instead generated distinctive features in firing patterns that aided RE. These simulations demonstrate the potential of this form of RE analysis. It is likely that the ever-increasing capacity of supercomputers will allow increasingly accurate RE of neuron inputs from their firing patterns from many neural systems.

Supercomputer framework for reverse engineering firing patterns of neuron populations to identify their synaptic inputs.

In this study, we develop new reverse engineering (RE) techniques to identify the organization of the synaptic inputs generating firing patterns of populations of neurons. We tested these techniques in silico to allow rigorous evaluation of their effectiveness, using remarkably extensive parameter searches enabled by massively-parallel computation on supercomputers. We chose spinal motoneurons as our target neural system, since motoneurons process all motor commands and have well-established input-output properties. One set of simulated motoneurons was driven by 300,000+ simulated combinations of excitatory, inhibitory, and neuromodulatory inputs. Our goal was to determine if these firing patterns had sufficient information to allow RE identification of the input combinations. Like other neural systems, the motoneuron input-output system is likely non-unique. This non-uniqueness could potentially limit this RE approach, as many input combinations can produce similar outputs. However, our simulations revealed that firing patterns contained sufficient information to sharply restrict the solution space. Thus, our RE approach successfully generated estimates of the actual simulated patterns of excitation, inhibition, and neuromodulation, with variances accounted for ranging from 75-90%. It was striking that nonlinearities induced in firing patterns by the neuromodulation inputs did not impede RE, but instead generated distinctive features in firing patterns that aided RE. These simulations demonstrate the potential of this form of RE analysis. It is likely that the ever-increasing capacity of supercomputers will allow increasingly accurate RE of neuron inputs from their firing patterns from many neural systems.

Disrupted Hippocampal-Prefrontal Networks in a Rat Model of Fragile X Syndrome: A Study Linking Neural Dynamics to Autism-Like Behavioral Impairments.

FMR-KO and control rats underwent a battery of behavioral tests assessing sociability, memory, and anxiety. Single-unit electrophysiology recordings were then conducted to measure patterns of neural activity in H-PFC circuit. Advanced mathematical models were used to characterize the patterns that were then compared between groups using generalized linear mixed models. FMR-KO rats demonstrated significant behavioral deficits in sociability, spatial learning, and anxiety, aligning with symptoms of ASD. At the neural level, these rats exhibited abnormal firing patterns in the H-PFC circuit that is critical for learning, memory, and social behavior. The neural networks in FMR-KO rats were also less densely connected and more fragmented, particularly in hippocampal-PFC correlated firing. These findings suggest that disruptions in neural network dynamics underlie the observed behavioral impairments in FMR-KO rats. FMR-KO significantly disrupts several characteristics of action potential firing in the H-PFC network, leading to deficits in social behavior, memory, and anxiety, as seen in FXS. This disruption is characterized by less organized and less resilient hippocampal-PFC networks. These findings suggest that therapeutic strategies aimed at normalizing neural dynamics, such as with brain stimulation, could potentially improve behavior and cognitive functions in autistic individuals. Fragile X Syndrome is associated with autism, cognitive challenges and anxietyThe loss of Fmr1 protein disrupts processes involved in building neural networksThe consequence is abnormal neural dynamics in hippocampal-prefrontal cortex networksNormalization of dynamics could improve outcomes in FXS and ASD.

Diversity of ancestral brainstem noradrenergic neurons across species and multiple biological factors.

The brainstem region, locus coeruleus (LC), has been remarkably conserved across vertebrates. Evolution has woven the LC into wide-ranging neural circuits that influence functions as broad as autonomic systems, the stress response, nociception, sleep, and high-level cognition among others. Given this conservation, there is a strong possibility that LC activity is inherently similar across species, and furthermore that age, sex, and brain state influence LC activity similarly across species. The degree to which LC activity is homogenous across these factors, however, has never been assessed due to the small sample size of individual studies. Here, we pool data from 20 laboratories (1,855 neurons) and show diversity across both intrinsic and extrinsic factors such as species, age, sex and brain state. We use a negative binomial regression model to compare activity from male monkeys, and rats and mice of both sexes that were recorded across brain states from brain slices ex vivo or under different anesthetics or during wakefulness in vivo . LC activity differed due to complex interactions of species, sex, and brain state. The LC became more active during aging, independent of sex. Finally, in contrast to the foundational principle that all species express two distinct LC firing modes ("tonic" or "phasic"), we discovered great diversity within spontaneous LC firing patterns. Different factors were associated with higher incidence of some firing modes. We conclude that the activity of the evolutionarily-ancient LC is not conserved. Inherent differences due to age and species-sex-brain state interactions have implications for understanding the role of LC in species-specific naturalistic behavior, as well as in psychiatric disorders, cardiovascular disease, immunology, and metabolic disorders.

Thermosensitive double-membrane neurons and their network dynamics

Abstract Cell membrane of biological neurons has distinct geometric structure, and involvement of diffusive term is suitable to estimate the spatial effect of cell membrane on neural activities. The gradient field diversity between two sides of the cell membrane can be approached by using a double-layer membrane model for the neuron. Therefore, two capacitive variables and diffusive terms are used to investigate the neural activities of cell membrane, and the local kinetics is described by a functional circuit composed of two capacitors. The voltages for the two parallel capacitors describe the inner and outer membrane potentials, and the diffusive effect of ions is considered on the membrane surface. The results reveal that neural activities are relative to the capacitance ratio between the inside and outside of the membrane and diffusive coefficient. High-energy periodic external stimulation induces the target waves to spread uniformly, while low-energy chaotic stimulation results in wave fragmentation. Furthermore, when the capacitance ratio exhibits exponential growth under an adaptive control law, the resulting energy gradient within the network induces stable target waves. That is, energy distribution affects the wave propagation and pattern formation in the neuron. The result indicates that the spatial diffusive effect and capacitance diversity between outer and inner cell membranes are important for selection of firing patterns and signal processing during neural activities. This model is more suitable to estimate neural activities than using generic oscillator-like or map neurons without considering the spatial diffusive effect.

Neuropathologic Findings and Electrolyte Abnormalities in a Case of Lennox-Gastaut Syndrome (SCN2a- related) Encountered at Autopsy

Abstract Introduction/Objective Lennox-Gastaut syndrome is a severe form of childhood epilepsy which may be due to several conditions, including sodium channelopathies which alter neuronal firing patterns. We present a case of a 6-year-old female with Lennox-Gastaut syndrome (SCN2A-related) complicated by developmental delay, spastic quadriplegia, and gastrojejunostomy tube dependence who was referred for medicolegal autopsy due to death subsequent to becoming unresponsive during a supervised bath. Methods/Case Report A complete autopsy was performed, including gross and microscopic examination of all primary organ systems, formal neuropathologic examination, and postmortem microbiology, toxicology, and vitreous electrolyte studies. The decedent showed evidence of developmental delay and flexion contractures of the extremities. No significant traumatic injuries were identified. A postmortem nasopharyngeal swab was positive for Rhinovirus/Enterovirus and Influenza A H3. A postmortem vitreous electrolyte panel demonstrated a dehydration pattern, including markedly elevated sodium and chloride and elevated urea nitrogen. Gross examination of the brain showed a thin corpus callosum, small hippocampi, as well as abnormal cerebellar dentate and inferior olivary nuclei. Microscopic examination of the brain tissue supported the gross findings, including dentato-olivary dysplasia. The cause of death was certified as dehydration complicating Lennox-Gastaut syndrome (SCN2a-related). Rhinovirus/Enterovirus and Influenza A H3 infections were considered contributory to death. The manner of death remained undetermined, since it was unknown if the decedent’s natural diseases, issues following a scheduled gastrojejunostomy feeding regimen, neglect, or some combination thereof caused the dehydration. Results (if a Case Study enter NA) NA Conclusion This case highlights unique and rarely documented neuropathologic findings and electrolyte abnormalities that may be seen in Lennox-Gastaut syndrome associated with an SCN2A mutation in addition to demonstrating the challenges of cause and manner death certification in cases of severe developmental disorders of childhood related to sodium channelopathies.

Subtype-specific neurons from patient iPSCs display distinct neuropathological features of Alzheimer’s disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by massive neuronal loss in the brain. Both cortical glutamatergic neurons and basal forebrain cholinergic neurons (BFCNs) in the AD brain are selectively vulnerable. The degeneration and dysfunction of these two subtypes of neurons are closely associated with the cognitive decline of AD patients. The determination of cellular and molecular mechanisms involved in AD pathogenesis, especially in the early stage, will largely facilitate the understanding of this disease and the development of proper intervention strategies. However, due to the inaccessibility of living neurons in the brains of patients, it remains unclear how cortical glutamatergic neurons and BFCNs respond to pathological stress in the early stage of AD. In this study, we established in vitro differentiation systems that can efficiently differentiate patient-derived iPSCs into BFCNs. We found that AD-BFCNs secreted less Aβ peptide than cortical glutamatergic neurons did, even though the Aβ42/Aβ40 ratio was comparable to that of cortical glutamatergic neurons. To further mimic the neurotoxic niche in AD brain, we treated iPSC-derived neurons with Aβ42 oligomer (AβO). BFCNs are less sensitive to AβO induced tau phosphorylation and expression than cortical glutamatergic neurons. However, AβO could trigger apoptosis in both AD-cortical glutamatergic neurons and AD-BFCNs. In addition, AD iPSC-derived BFCNs and cortical glutamatergic neurons exhibited distinct electrophysiological firing patterns and elicited different responses to AβO treatment. These observations revealed that subtype-specific neurons display distinct neuropathological changes during the progression of AD, which might help to understand AD pathogenesis at the cellular level.

Impacts of a short-interval severe fire on forest structure and regeneration in a temperate Andean Araucaria-Nothofagus forest

BackgroundWarmer climate conditions are altering fire regimes globally, eroding the capacity of forest ecosystems to resist and recover from natural disturbances like wildfire. Severe and rapidly repeated wildfires are promoting tree regeneration failure of obligate-seeders and/or fire-sensitive species in temperate forests of the Southern Hemisphere. We collected post-fire field data to evaluate whether forest structure and tree regeneration responses varied between two Andean forest study areas dominated by the threatened Gondwanan conifer Araucaria araucana and Nothofagus species (southern beeches) — one area burned once, the other reburned after 13 years.ResultsTree mortality was high across species after a single high severity and/or repeated wildfire, although some A. araucana trees were able to survive both events. Post-fire seedling regeneration of A. araucana and Nothofagus spp. was poor in areas affected by severe wildfires, and the latter was absent from reburned plots. A key driver of this regeneration failure was increasing distance to live seed source trees, which was negatively correlated with these species’ post-fire seedling abundances. In contrast, species with the capacity to regenerate via resprouting (A. araucana, N. alpina, N. obliqua) did so after a single high severity fire; however, only a single Nothofagus species (N. alpina) resprouted abundantly after a reburn.ConclusionsOur findings suggest that high severity and short-interval fires can drastically change the structure of and limit post-fire tree regeneration in Araucaria-Nothofagus forests, promoting alternative post-fire forest ecosystem trajectories. Resprouting species of the Nothofagus genus, especially N. alpina, exhibit the greatest resilience to these emerging fire patterns. These forests are currently facing an unprecedented climatic shift toward greater fire activity, where resprouting is the favored regeneration strategy. If the occurrence of severe and short-interval fires increases in the coming decades, as predicted, we expect Araucaria-Nothofagus forests to shift toward a drier, more flammable shrubland ecosystem state.