Firing Frequency Research Articles

Rocky outcrops form islands of high and unique tree biodiversity within an ocean of grass in Serengeti National Park

AbstractAfrican savannahs are characterised by a high plant diversity, partly resulting from a high turnover in community compositions across space. However, it is poorly understood what is driving this spatial turnover in plant communities. Here, we investigate to which extent the presence of rocky outcrops (also called kopjes) explains the community composition of trees in an African savannah, and how we can understand the responses of tree species to rocky outcrops by their functional traits. Along a precipitation gradient, we visited 24 sites in Serengeti National Park (Tanzania). At each site, we characterised tree communities, as well as their functional traits, in both a kopje and an adjacent open savannah plot (matrix plot). We found that kopjes harboured elevated tree abundances and species richness. Their dominant trees were more often evergreen, had a higher specific leaf area, a lower leaf nitrogen content and a lower spine density, than dominant trees in the savannah matrix. Differences in tree communities between kopjes and savannah matrix plots were generally the largest at sites with low precipitation. Our results indicate that kopjes are strong drivers of tree biodiversity, possibly due to locally increased soil moisture and low fire frequencies. The uniqueness of kopje tree communities may have important implications for higher trophic levels and ecosystem functioning.

Spatial heterogeneity of fire and flooding patterns can support higher diversity of floral functional traits in an indigenous‐managed landscape

AbstractIn tropical wetlands, in addition to flooding, fire also contributes to the structure of biodiversity across environmental gradients. In fire‐prone ecosystems, flower‐rich fire refuges can be maintained by a seasonal patch‐burning mosaic. Here, we evaluate how a set of floral traits that influence and are related to the pollination systems of tree and non‐tree species varies in response to spatial patterns of fire frequency in a landscape with floodable and flood‐free areas. We classified the sampled species according to flower size, color, shape, symmetry, floral resource, type of pollination units, flowering duration, and anthesis time and compared them between floodable and flood‐free areas with high, moderate, or low fire frequency. We analyzed the functional richness in response to landscape metrics related to spatial patterns of fire frequency. The composition of floral traits of non‐tree species was stable, while tree species differed among fire frequency classes, especially in floodable areas. Many floral traits of tree species are ecological indicators, especially in floodable areas with high fire frequency. In contrast, among non‐tree species, only floral tissues as resources for pollinator were related to flood‐free areas with moderate/high fire frequency. The floral functional richness of the tree species positively linked with the modified Simpson diversity index, and for both trees and non‐trees, it negatively associated with the homogenization of the fire frequency (e.g., connectance based on probability that two adjacent sites belong to the same fire frequency class was negatively related to the functional richness of floral traits). These results demonstrate that homogenization of fire frequency in the landscape decreases the functional richness. Patches with different combinations of fire frequency and flood regime can support a shared set of floral traits besides those specifically related to a particular regime. The spatial heterogeneity of fire and flood patterns in wetlands needs to be preserved to support a higher diversity of pollination systems mediated by functional complementarity between the flowers of the tree and non‐tree species.

Impacts of Fire Frequency on Net CO2 Emissions in the Cerrado Savanna Vegetation

Impacts of Fire Frequency on Net CO2 Emissions in the Cerrado Savanna Vegetation

Effects of Wildfires on Soil Organic Carbon in Boreal Permafrost Regions: A Review

ABSTRACTWildfire strongly influences permafrost environment and soil organic carbon (SOC) pool. In this study, we reviewed the effects of fire severity, time after a fire, and frequency on SOC in boreal permafrost regions. This review highlighted several key points: the effect of wildfires on SOC increased with an increase of fire severity, and the amount of vegetation returned and surface organic matter replenished was less in a short term, which resulted in a significantly lower SOC content compared to that of before the fire. Within a short period after fire, the SOC in near‐surface permafrost and the active layer decreased significantly due to the loss of above ground biomass, permafrost thaw, and increased microbial decomposition; as the years pass after a fire, the SOC gradually accumulates due to the contributions of litter layer accumulation and rooting systems from different stages of succession. The increase in fire frequency accelerated permafrost thawing and the formation of thermokarst, resulting in the rapid release of a large amount of soil carbon and reduced SOC storage. Therefore, the study on the effects of wildfires on SOC in the boreal permafrost region is of great significance to understanding and quantifying the carbon balance of the ecosystem.

BayesianSpikeFusion: accelerating spiking neural network inference via Bayesian fusion of early prediction.

Spiking neural networks (SNNs) have garnered significant attention due to their notable energy efficiency. However, conventional SNNs rely on spike firing frequency to encode information, necessitating a fixed sampling time and leaving room for further optimization. This study presents a novel approach to reduce sampling time and conserve energy by extracting early prediction results from the intermediate layer of the network and integrating them with the final layer's predictions in a Bayesian fashion. Experimental evaluations conducted on image classification tasks using MNIST, CIFAR-10, and CIFAR-100 datasets demonstrate the efficacy of our proposed method when applied to VGGNets and ResNets models. Results indicate a substantial energy reduction of 38.8% in VGGNets and 48.0% in ResNets, illustrating the potential for achieving significant efficiency gains in spiking neural networks. These findings contribute to the ongoing research in enhancing the performance of SNNs, facilitating their deployment in resource-constrained environments. Our code is available on GitHub: https://github.com/hanebarla/BayesianSpikeFusion.

Parvalbumin expression does not account for discrete electrophysiological profiles of glutamatergic ventral pallidal subpopulations

The ventral pallidum (VP) has emerged as a critical node in the mesolimbic reward system. Modulating the VP can impact the subjective valuation of rewards, reward motivation, and reward seeking under conflict, making it an attractive target for clinical neuromodulation therapies that manage substance use disorders. To understand how to rationally modulate the VP, we need a better understanding of the electrophysiological properties of VP neurons and the molecular and biophysical determinants of these properties. Here, we used patch-clamp electrophysiology to characterize the intrinsic properties of glutamatergic VP (VPGlu) neurons and observed two distinct electrophysiological profiles: VPGlu neurons that undergo depolarization block in response to progressively increasing current injection amplitudes and those that were resistant to depolarization block. To explore the mechanisms that could contribute to these distinct profiles, we used targeted ribosome affinity purification to identify ion channel subunits and regulatory proteins by isolating actively transcribed mRNA selectively from VPGlu neurons. We then used this transcriptomic information to implement a Markov Chain Monte Carlo method to parameterize a large population of biophysically distinct multicompartment models of VPGlu neurons conforming to either subpopulation. Based on prior literature suggesting parvalbumin (PV) is expressed in a subset of VPGlu neurons, and that PV expression governs the firing properties of those neurons, we tested the hypothesis that PV expression accounted for differences in subgroups, by increasing the maximal firing frequency and conferring resistance to depolarization block. In contrast, our model determined that PV expression at physiological levels had no effect on maximum firing rate. However, supraphysiological expression levels of PV appeared to induce a depolarization block in previously depolarization block-resistant neuron models, suggesting that other intracellular calcium-binding proteins could play a role in determining the firing phenotype of VPGlu neurons. We corroborated this result with single-cell patch-clamp RT-PCR, which confirmed that PV expression did not distinguish the two electrophysiologically distinct subpopulations. Together, these findings establish that VPGlu neurons are composed of biophysically distinct subpopulations that have not been appreciated in prior studies interrogating the function of this population. With the advent of novel tools for cell-type specific pharmacology and targeted neurostimulation, this understanding will be critical for developing strategies to rationally modulate VPGlu cells to treat disorders characterized by maladaptive reward seeking.

Heterozygous expression of a Kcnt1 gain-of-function variant has differential effects on SST- and PV-expressing cortical GABAergic neurons.

More than twenty recurrent missense gain-of-function (GOF) mutations have been identified in the sodium-activated potassium (KNa) channel gene KCNT1 in patients with severe developmental and epileptic encephalopathies (DEEs), most of which are resistant to current therapies. Defining the neuron types most vulnerable to KCNT1 GOF will advance our understanding of disease mechanisms and provide refined targets for precision therapy efforts. Here, we assessed the effects of heterozygous expression of a Kcnt1 GOF variant (Y777H) on KNa currents and neuronal physiology among cortical glutamatergic and GABAergic neurons in mice, including those expressing vasoactive intestinal polypeptide (VIP), somatostatin (SST), and parvalbumin (PV), to identify and model the pathogenic mechanisms of autosomal dominant KCNT1 GOF variants in DEEs. Although the Kcnt1-Y777H variant had no effects on glutamatergic or VIP neuron function, it increased subthreshold KNa currents in both SST and PV neurons but with opposite effects on neuronal output; SST neurons became hypoexcitable with a higher rheobase current and lower action potential (AP) firing frequency, whereas PV neurons became hyperexcitable with a lower rheobase current and higher AP firing frequency. Further neurophysiological and computational modeling experiments showed that the differential effects of the Y777H variant on SST and PV neurons are not likely due to inherent differences in these neuron types, but to an increased persistent sodium current in PV, but not SST, neurons. The Y777H variant also increased excitatory input onto, and chemical and electrical synaptic connectivity between, SST neurons. Together, these data suggest differential pathogenic mechanisms, both direct and compensatory, contribute to disease phenotypes, and provide a salient example of how a pathogenic ion channel variant can cause opposite functional effects in closely related neuron subtypes due to interactions with other ionic conductances.

Fire is associated with forest degradation and economic land concessions, but not land conversion in the rapidly transforming Cambodian landscape

Abstract Cambodia is beset by high deforestation rates and fire frequencies. From 2001–2020, forest cover declined by 34%, and cropland and rubber expanded by 31,401 km2 and 4,530 km2, respectively; meanwhile nearly 8.7 million fires burned 41.6% of the land. Fires may be associated with deliberate land change, stable land management systems, and unplanned forest degradation. We integrated annual land cover and monthly burned area data from 2001–2020 to test three hypotheses. First, if fire is used during land conversion, there would be a detectable pulse in fire activity in the year immediately prior to, and the year of land cover change. Our temporal analysis found statistically elevated burn rates in five of 16 transition tests, however, they were typically <1% outside the predicted range, indicating no practical significance in the association of fire with land cover change. Second, fire prevalence would be lower in land managed for conservation or agricultural production than unclassified or unmanaged land. persistent forest and shrubland burned at significantly higher rates than expected, cropland burned significantly less, burning was almost absent from rubber plantations, and forests in protected areas (PAs) exhibited lower total burn percentages than unclassified land or industrial economic land concessions (ELCs), thus supporting the fire-land management hypothesis. However, total burned area in ELCs was greater than unclassified land for several persistent land cover classes, suggesting that local landowners may prevent fire in commercially valuable private agricultural land, but there may be no such prevention measures in industrial ELCs. Anti-fire policy enforcement in ELCs should be enhanced. Third, forests that converted into (degraded) shrublands would experience increasing fire frequency in the years leading up to transition, a hypothesis we found strong support for through our temporal analysis. Cambodia’s 2013 Law on Fire Prevention and Fire Fighting deputizes the public to enforce its provision, however given that the vast majority of fires occur in persistent forest in state-owned land, collective action problems are likely to hinder its effective implementation.

Will fire-smart landscape management buffer the effects of climate and land-use changes on fire regimes?

BackgroundLong-term farmland abandonment has increased fuel build-up in many Euro-Mediterranean mountainous regions. The high fuel hazard in these landscapes, combined with ongoing climate change, is increasing the frequency of extreme wildfires, thus altering contemporary fire regimes. Mitigating the loss of the landscape’s capacity to regulate large and intense fires is crucial to prevent future harmful effects of fires. As such, effective strategies to manage these fire-prone landscapes are needed. Yet, further understanding of their performance under global change scenarios is required. This study assessed the effects of fire-smart management strategies on future landscape dynamics, fire regulation capacity (FRC), and fire regime in a Mediterranean fire-prone mountainous landscape in Portugal (30,650 ha) undergoing long-term land abandonment and climate change scenarios. For that, we applied the LANDIS-II model under climate change scenarios (RCP 4.5 and 8.5) and long-term farmland abandonment (2020–2050) according to three fire-smart management strategies focused on fire prevention compared with a business-as-usual (BAU) strategy based on fire suppression.ResultsFuture fire activity and land dynamics resulted in changes that fostered landscape heterogeneity and fragmentation and favoured fire-adapted forests and agroforestry systems while decreasing the dominance of shrublands and croplands. FRC decreased over time, particularly under RCP 8.5 and the BAU strategy. In turn, fire-smart strategies better prevented large and intense fires than the BAU strategy, but their effectiveness decreased under RCP 8.5. The loss of FRC resulted in increased burned area and fire frequency, which predicts a shift from contemporary fire regimes but more markedly under RCP 8.5 and in the BAU strategy.ConclusionsFire-smart strategies outperformed BAU in averting current fire regime intensification. Merging forest- and silvopasture-based management is the most promising approach in taming the effects of climate and farmland abandonment on future fire activity. Our study underlines that planning and management policies in fire-prone Mediterranean mountain landscapes must integrate fire-smart strategies to decrease landscape fuel hazard and buffer the impact of global change on future fire regimes.

Assessing Cross-Contamination in Spike-Sorted Electrophysiology Data.

Recent advances in extracellular electrophysiology now facilitate the recording of spikes from hundreds or thousands of neurons simultaneously. This has necessitated both the development of new computational methods for spike sorting and better methods to determine spike-sorting accuracy. One long-standing method of assessing the false discovery rate (FDR) of spike sorting-the rate at which spikes are assigned to the wrong cluster-has been the rate of interspike interval (ISI) violations. Despite their near ubiquitous usage in spike sorting, our understanding of how exactly ISI violations relate to FDR, as well as best practices for using ISI violations as a quality metric, remains limited. Here, we describe an analytical solution that can be used to predict FDR from the ISI violation rate (ISIv). We test this model in silico through Monte Carlo simulation and apply it to publicly available spike-sorted electrophysiology datasets. We find that the relationship between ISIv and FDR is highly nonlinear, with additional dependencies on firing frequency, the correlation in activity between neurons, and contaminant neuron count. Predicted median FDRs in public datasets recorded in mice were found to range from 3.1 to 50.0%. We found that stochasticity in the occurrence of ISI violations as well as uncertainty in cluster-specific parameters make it difficult to predict FDR for single clusters with high confidence but that FDR can be estimated accurately across a population of clusters. Our findings will help the growing community of researchers using extracellular electrophysiology assess spike-sorting accuracy in a principled manner.

Semantic segmentation and thermal imaging for forest fires detection and monitoring by drones

Forest ecosystems play a crucial role in providing a wide range of ecological, social, and economic benefits. However, the increasing frequency and severity of forest fires pose a significant threat to the sustainability of forests and their functions, highlighting the need for early detection and swift action to mitigate damage. The combination of drones and artificial intelligence, particularly deep learning, proves to be a cost-effective solution for accurately and efficiently detecting forest fires in real-time. Deep learning-based image segmentation models can not only be employed for forest fire detection but also play a vital role in damage assessment and support reforestation efforts. Furthermore, the integration of thermal cameras on drones can significantly enhance the sensitivity in forest fire detection. This study undertakes an in-depth analysis of recent advancements in deep learning-based semantic segmentation, with a particular focus on model’s mask region convolutional neural network (Mask R-CNN) and you only look once (YOLO) v5, v7, and v8 variants. Emphasis is placed on their suitability for forest fire monitoring using drones equipped with RGB and/or thermal cameras. The conducted experiments have yielded encouraging outcomes across various metrics, underscoring its significance as an invaluable asset for both fire detection and continuous monitoring endeavors.

Autonomic modulation by SGLT2i or DPP4i in patients with diabetes favors cardiovascular outcomes as revealed by skin sympathetic nerve activity.

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) and dipeptidyl peptidase-4 inhibitors (DPP4i) are important second-line treatments for patients with type 2 diabetes mellitus (T2DM). Patients taking SGLT2i have favorable cardiovascular outcomes via various mechanisms, including autonomic nervous system (ANS) modulation. This study aimed to use neuro-electrocardiography (neuECG) to test the effects of SGLT2i or DPP4i on the ANS. Patients with T2DM, who did not reach target hemoglobin (Hb)A1C levels despite metformin treatment, were enrolled. SGLT2i or DPP4i were prescribed randomly unless a compelling indication was present. NeuECG and heart rate were recorded for 10min before and after a 3-month treatment. The patients were treated according to standard practice and the obtained data for skin sympathetic nerve activity (SKNA) and ANS entropy were analyzed offline. We enrolled 96 patients, of which 49 received SGLT2i and 47 received DPP4i. The baseline parameters were similar between the groups. No adverse event was seen during the study period. In the burst analysis of SKNA at baseline, all parameters were similar. After the 3-month treatment, the firing frequency was higher in SGLT2i group (0.104 ± 0.045 vs 0.083 ± 0.033 burst/min, p < 0.05), with increased long firing duration (7.34 ± 3.66 vs 5.906 ± 2.921, p < 0.05) in 3-s aSKNA scale; the other parameters did not show any significant change. By symbolic entropy, the most complex patterns (Rank 3) were found to be significantly higher in SGLT2i-treated patients than in DDP4i-treated group (0.084 ± 0.028 vs 0.07 ± 0.024, p = 0.01) and the direction of change in Rank 3, after SGLT2i treatment, was opposite to that observed in the DDP4i group (0.012 ± 0.036 vs. -0.005 ± 0.037, p = 0.024). Our findings demonstrated the favorable autonomic modulation by SGLTi and the detrimental effects of DPP4i on ANS. We demonstrated the autonomic modulation by SGLTi and DPP4i using SKNA in patients with DM, which might provide insights into the favorable outcomes of SGLT2i. Furthermore, we refined the analytical methods of neuECG, which uses SKNA to evaluate autonomic function.

Phosphorus controls symbiotic nitrogen fixation in fire‐dependent longleaf pine savannas

Abstract Symbiotic nitrogen (N) fixation has the potential to replenish fire‐induced N losses in frequently burned ecosystems. A strong relationship between fire and fixation may exist because fire volatilizes N and mineralizes phosphorus (P), creating N‐poor, P‐rich soils that favour plants capable of N‐fixation. However, human activities have enriched ecosystems with N, which may complicate the interplay among fire, fixation and soil P. We evaluated how N and P modulate the relationship between fire and symbiotic N fixation in longleaf pine savannas, where it was previously documented that N fixation fails to replenish N losses from fire. Across gradients of stand age and fire frequency, we investigated how N and P availability influence fixation, and we established a nutrient addition experiment to evaluate the effects of N and P on legume growth, fixation and mycorrhizal investment. We uncovered a clear signal of P limitation of herbaceous legumes. Legume growth and fixation were linked to the availability of soil mineral P and were further stimulated by P additions. In contrast, neither soil N availability nor N additions affected legume growth or fixation. Synthesis. Our findings suggest that symbiotic N fixation in sandhill longleaf pine savannas is controlled by soil P availability, which varies according to soil age and parent material. Therefore, fixation may only counterbalance N losses from fire if there is enough P in the soil to support this process. Nonetheless, recent N enrichment in contemporary longleaf pine ecosystems may have reduced the importance of N fixation as a post‐fire recovery mechanism.

Environmentally persistent free radicals and other paramagnetic species in wildland-urban interface fire ashes

Wildland-urban interface (WUI) fires consume fuels, such as vegetation and structural materials, leaving behind ash composed primarily of pyrogenic carbon and metal oxides. However, there is currently limited understanding of the role of WUI fire ash from different sources as a source of paramagnetic species such as environmentally persistent free radicals (EPFRs) and transition metals in the environment. Electron paramagnetic resonance (EPR) was used to detect and quantify paramagnetic species, including organic persistent free radicals and transition metal spins, in fifty-three fire ash and soil samples collected following the North Complex Fire and the Sonoma-Lake-Napa Unit (LNU) Lightning Complex Fire, California, 2020. High concentrations of organic EPFRs (e.g., 1.4 × 1014 to 1.9 × 1017 spins g−1) were detected in the studied WUI fire ash along with other paramagnetic species such as iron and manganese oxides, as well as Fe3+ and Mn2+ ions. The mean concentrations of EPFRs in various ash types decreased following the order: vegetation ash (1.1 × 1017 ± 1.1 × 1017 spins g−1) > structural ash (1.6 × 1016 ± 3.7 × 1016 spins g−1) > vehicle ash (6.4 × 1015 ± 8.6 × 1015 spins g−1) > soil (3.2 × 1015 ± 3.7 × 1015 spins g−1). The mean concentrations of EPFRs decreased with increased combustion completeness indicated by ash color; black (1.1 × 1017 ± 1.1 × 1017 spins g−1) > white (2.5 × 1016 ± 4.4 × 1016 spins g−1) > gray (1.8 × 1016 ± 2.4 × 1016 spins g−1). In contrast, the relative amounts of reduced Mn2+ ions increased with increased combustion completeness. Thus, WUI fire ash is an important global source of EPFRs and reduced metal species (e.g., Mn2+). Further research is needed to underpin the formation, transformation, and environmental and human health impacts of these paramagnetic species in light of the projected increased frequency, size, and severity of WUI fires.

Nonlinear woody vegetation effects on Holocene fire activity across the world's highlands

The accelerated warming in the world's highlands has prompted significant ecological adjustments and an increase in the frequency of forest fires. Nevertheless, the correlation between woody biomass and increased fire activity in the past has received limited attention. A total of 138 charcoal and 145 pollen records were analyzed to investigate the relationship between fire and woody biomass (arboreal pollen, AP) in the world's highlands during the Holocene. The findings indicate biomass burning in the Rockies, Alps and Andes stepped increased in the early to middle Holocene but decreased in the late Holocene. The positive AP-fuel feedback was recorded in the early-middle Holocene, whereas the negative AP-fuel feedback emerged in the late Holocene, the latter were attributed to denser forests in the Rockies and intensified human activities in the Alps and Andes. Conversely, Holocene biomass burning in the Tianshan-Altai Mountains, Africa and Tibetan Plateaus exhibited overall decreasing trends with sudden decreases in the Tianshan-Altai Mountains and Tibetan Plateau and a notable increase in the African Plateau over the past millennium. The variability observed in fire regime changes in the past millennium is likely influenced by human activities. Results illustrate that fire responses to woody vegetation are nonlinear, such that the same direction of change in vegetation can elicit different fire responses depending on their components at a site. Our study offers crucial insights into the influence of woody biomass on fire dynamics in the world's highlands, providing important contextual information about how these montane systems may respond to future climate change and anthropogenic activity.

Electroacupuncture alleviates myocardial ischemia-reperfusion injury by inhibiting hypothalamic paraventricular nucleus neurons projecting to the rostral ventrolateral medulla.

Accumulating evidence suggests that electroacupuncture (EA) has obvious therapeutic effects and unique advantages in alleviating myocardial ischemia-reperfusion injury (MIRI), while the underlying neuromolecular mechanisms of EA intervention for MIRI have not been fully elucidated. The aim of the study is to investigate the role of the neural pathway of hypothalamic paraventricular nucleus (PVN) neurons projecting to the rostral ventrolateral medulla (RVLM) in the alleviation of MIRI rats by EA preconditioning. MIRI models were established by ligating the left anterior descending coronary artery for 30 min followed by reperfusion for 2h. Electrocardiogram recording, chemogenetics, enzyme-linked immunosorbent assay, multichannel physiology recording and haematoxylin-eosin and immunofluorescence staining methods were conducted to demonstrate that the firing frequencies of neurons in the PVN and the expression of c-Fos decreased by EA pretreatment. Meanwhile, EA preconditioning significantly reduced the levels of creatine kinase isoenzymes (CK-MB), cardiac troponin I (cTnI) and lactic dehydrogenase (LDH). Virus tracing showed a projection connection between PVN and RVLM. The inhibition of the PVN-RVLM neural pathway could replicate the protective effect of EA pretreatment on MIRI rats. However, the activation of the pathway weakened the effect of EA preconditioning. EA pretreatment alleviated MIRI by regulating PVN neurons projecting to RVLM. This work provides novel evidence of EA pretreatment for alleviating MIRI.

Urban Fire Risk Dynamics and Mitigation Strategies in Shanghai: Integrating Spatial Analysis and Game Theory

In recent decades, the increasing frequency of urban fires, driven by urban functional enhancements and climate change, has posed a growing threat to metropolitan sustainability. This study investigates the temporal and spatial characteristics of fire incidents in Shanghai from 2019 to 2023. Using satellite fire point data and official government records, kernel density analysis and wavelet analysis were employed to analyze the time series and spatial distribution of fire data. Subsequently, eleven primary factors influencing urban fire occurrence were identified, encompassing probability, regional characteristics, and hazard sources. A combined methodology of subjective and objective weights with game theory was used to generate a fire risk assessment at a 1 × 1 km2 grid scale. Furthermore, the spatial distribution characteristics of the assessments were analyzed. The results reveal that the downtown area exhibits the highest intensity of urban fires in terms of spatial domain, with a decreasing intensity towards the suburbs. Temporally, fire frequency demonstrates significant periodicity at an 18a time scale, while clear seasonal fluctuations and periodicity are observed at a 16-22a time scale, with higher occurrences in spring and winter. The study identifies typical aggregation patterns of urban fires, with high-risk centers in downtown Shanghai. Considering the impact of climate change and human activities, high-risk areas may gradually expand to adjacent urban suburbs, presenting a concerning future scenario. By examining the dual attributes of “combustibles and fireproof space” within urban greening systems, this research offers recommendations for the future strategies of disaster prevention and mitigation of green systems in Shanghai.

Cholinergic stimulation stabilizes TRPM4 in the plasma membrane of cortical pyramidal neurons.

TRPM4 is a calcium activated non-selective cation channel, impermeable to Ca2+, in neurons it has been implicated in the regulation of the excitability and in the persistent firing. Cholinergic stimulation is also implicated in changes in excitability that leads neurons to an increased firing frequency, however it is not clear whether TRPM4 is involved in the cholinergic-induced increase in firing frequency. Here using a combination of patch clamp electrophysiology, Ca2+ imaging, immunofluorescence, fluorescence recovery after photobleaching (FRAP) and pharmacological approach, we demonstrate that carbachol (Cch) increases firing frequency, intracellular Ca2+ and that TRPM4 inhibition using 9-Ph and CBA reduces firing frequency and decreases the peak in intracellular Ca2+ induced by Cch in cortical pyramidal neurons in culture. Moreover, we determined that cholinergic stimulation reduces TRPM4 recycling and stabilizes TRPM4 in the plasma membrane. Together our results indicate that cholinergic stimulation increases firing in a TRPM4 dependent manner, and also increases the TRPM4 stability in the membrane, suggesting that TRPM4 is locked in microdomains in the membrane, possibly signaling or cytoskeleton proteins complexes.

Dopaminergic amacrine cells express HCN channels in the developing and adult mouse retina.

To determine the molecular and functional expression of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in developing and mature dopaminergic amacrine cells (DACs), the sole source of ocular dopamine that plays a vital role in visual function and eye development. HCN channels are encoded by isoforms 1-4. HCN1, HCN2, and HCN4 were immunostained in retinal slices obtained from mice at postnatal day 4 (P4), P8, and P12 as well as in adults. Each HCN channel isoform was also immunostained with tyrosine hydroxylase, a marker for DACs, at P12 and adult retinas. Genetically-marked DACs were recorded in flat-mount retina preparation using a whole-cell current-clamp technique. HCN1 was expressed in rods/cones, amacrine cells, and retinal ganglion cells (RGCs) at P4, along with bipolar cells by P12. Different from HCN1, HCN2 and HCN4 were each expressed in amacrine cells and RGCs at P4, along with bipolar cells by P8, and in rods/cones by P12. Double immunostaining shows that each of the three isoforms was expressed in approximately half of DACs at P12 but in almost all DACs in adults. Electrophysiology results demonstrate that HCN channel isoforms form functional HCN channels, and the pharmacological blockade of HCN channels reduced the spontaneous firing frequency in most DACs. Each class of retinal neurons may use different isoforms of HCN channels to function during development. HCN1, HCN2, and HCN4 form functional HCN channels in DACs, which appears to modulate their spontaneous firing activity.

Firing rate adaptation affords place cell theta sweeps, phase precession, and procession

Hippocampal place cells in freely moving rodents display both theta phase precession and procession, which is thought to play important roles in cognition, but the neural mechanism for producing theta phase shift remains largely unknown. Here, we show that firing rate adaptation within a continuous attractor neural network causes the neural activity bump to oscillate around the external input, resembling theta sweeps of decoded position during locomotion. These forward and backward sweeps naturally account for theta phase precession and procession of individual neurons, respectively. By tuning the adaptation strength, our model explains the difference between ‘bimodal cells’ showing interleaved phase precession and procession, and ‘unimodal cells’ in which phase precession predominates. Our model also explains the constant cycling of theta sweeps along different arms in a T-maze environment, the speed modulation of place cells’ firing frequency, and the continued phase shift after transient silencing of the hippocampus. We hope that this study will aid an understanding of the neural mechanism supporting theta phase coding in the brain.