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Odours are a fundamental part of the sensory environment used by animals to guide behaviours such as foraging and navigation 1 , 2 . Primary olfactory (piriform) cortex is thought to be the main cortical region for encoding odour identity 3 – 8 . Here, using neural ensemble recordings in freely moving rats performing an odour-cued spatial choice task, we show that posterior piriform cortex neurons carry a robust spatial representation of the environment. Piriform spatial representations have features of a learned cognitive map, being most prominent near odour ports, stable across behavioural contexts and independent of olfactory drive or reward availability. The accuracy of spatial information carried by individual piriform neurons was predicted by the strength of their functional coupling to the hippocampal theta rhythm. Ensembles of piriform neurons concurrently represented odour identity as well as spatial locations of animals, forming an odour–place map. Our results reveal a function for piriform cortex in spatial cognition and suggest that it is well-suited to form odour–place associations and guide olfactory-cued spatial navigation. Studies using neural ensemble recordings in rats show that cells in the piriform cortex carry a spatial representation of the environment and link locations to olfactory sensory inputs.

Local field potentials (LFPs) reflect coordination among neural populations, yet their exact relationship to neural computation remains unknown. One exception is the theta rhythm of the rodent hippocampus, which organizes sequential firing among place cells, enabling spike timing to track the animal’s path through its environment. But when the animal stops, the theta rhythm becomes irregular, which is assumed to disrupt its ability to carry spatial information. Here we challenge this assumption by developing an artificial neural network that discovers position-tuned theta rhythms (pThetas) from LFPs even in the absence of strong theta oscillations. Using recordings from male rats, we provide evidence that pTheta is distinct from the dominant theta rhythm, while reflecting rhythmic coordination among place cell populations. Our work suggests that weak and intermittent oscillations, as seen in many brain regions and species, can convey information commensurate with population spike codes when decoded using information-based rather than variance-based principles. Whether weak brain rhythms carry information about ongoing behavior remains unclear. Here, the authors develop a neural network that finds subtle motifs in irregular brain rhythms arising from neural populations to read out where a rat is in its environment.

Although neuronal spikes can be readily detected from extracellular recordings, synaptic and subthreshold activity remains undifferentiated within the local field potential (LFP). In the hippocampus, neurons discharge selectively when the rat is at certain locations, while LFPs at single anatomical sites exhibit no such place-tuning. Nonetheless, because the representation of position is sparse and distributed, we hypothesized that spatial information can be recovered from multiple-site LFP recordings. Using high-density sampling of LFP and computational methods, we show that the spatiotemporal structure of the theta rhythm can encode position as robustly as neuronal spiking populations. Because our approach exploits the rhythmicity and sparse structure of neural activity, features found in many brain regions, it is useful as a general tool for discovering distributed LFP codes.

Atherosclerosis is a chronic vascular disease that underlies the pathogenesis of both peripheral arterial disease and coronary artery disease, two of the leading causes of morbidity and mortality worldwide. Characterized by the accumulation of lipids, chronic inflammation, and fibrotic remodeling within vasculature, atherosclerosis involves a complex interplay of endothelial dysfunction, immune dysregulation, vascular smooth muscle cell proliferation, and maladaptive neovascularization. Increasing evidence now suggests that atherosclerosis has notable overlap with cancer biology, including sustained proliferative signaling, evasion of immune surveillance, angiogenesis, and resistance to cell death. These shared molecular features have prompted growing interest in the potential repurposing of oncologic treatments in the modulation of atherosclerotic disease. While preclinical data are promising, successful translation and integration of oncologic therapeutics will require overcoming critical barriers, including drug toxicity, long-term safety, regulatory constraints, and cost-effectiveness. Future work should focus on biomarker-guided patient selection, dose optimization, and targeted delivery systems to minimize off-target effects while enhancing efficacy.

This review article delves into the strategic integration of renewable energy sources within smart cities, emphasizing the role of electric vehicles (EVs) in ensuring stability. Smart cities, at the forefront of sustainable urban development, prioritize energy systems that are both clean and renewable. The integration of various renewable energy resources, including solar, wind, geothermal, hydropower, ocean, and biofuels, into the energy systems of smart cities is explored, considering both technical and economic aspects. The rapid adoption of these technologies provides a foundation for a low-carbon economy, ensuring a cleaner and more sustainable urban environment. However, challenges persist, particularly in optimizing energy systems for renewable integration, stability, operational range, and cost-effectiveness. Additionally, the evolution of smart cities has brought forth advanced energy conservation systems, addressing energy management at both building and city levels. Innovative solutions, such as advanced infrastructure and energy trading strategies in distributed systems, are proposed. The role of EVs in the smart grid is also highlighted, addressing challenges posed by renewable energy’s intermittent output. The potential of EVs to counteract these fluctuations, especially under the vehicle-to-grid (V2G) framework, is discussed, offering insights into future research avenues for a harmonious and sustainable energy ecosystem in smart cities.

Susceptibility to weld solidification cracking in transformation-induced plasticity steel sheets was studied using a modified standard hot cracking test used in the automotive industry. To vary the amount of self-restraint, bead-on-plate laser welding was carried out on a single-sided clamped specimen at increasing distances from the free edge. Solidification cracking was observed when welding was carried out close to the free edge. With increasing amount of restraint, the crack length showed a decreasing trend, and at a certain distance, no cracking was observed. With the aid of a finite element-based model, dynamic thermal and mechanical conditions that prevail along the transverse direction of the mushy zone are used to explain the cracking susceptibility obtained experimentally. The results indicate that the transverse strain close to the fusion boundary can be used as a criterion to predict the cracking behavior. The outcome of the study shows that optimum processing parameters can be used to weld steels closer to the free edge without solidification cracking.

At the Drosophila melanogaster larval neuromuscular junction (NMJ), a motor neuron releases glutamate from 30–100 boutons onto the muscle it innervates. How transmission strength is distributed among the boutons of the NMJ is unknown. To address this, we created synapcam, a version of the Ca 2+ reporter Cameleon. Synapcam localizes to the postsynaptic terminal and selectively reports Ca 2+ influx through glutamate receptors (GluRs) with single-impulse and single-bouton resolution. GluR-based Ca 2+ signals were uniform within a given connection (that is, a given bouton/postsynaptic terminal pair) but differed considerably among connections of an NMJ. A steep gradient of transmission strength was observed along axonal branches, from weak proximal connections to strong distal ones. Presynaptic imaging showed a matching axonal gradient, with higher Ca 2+ influx and exocytosis at distal boutons. The results suggest that transmission strength is mainly determined presynaptically at the level of individual boutons, possibly by one or more factors existing in a gradient. *Note: In the version of this article initially published online, the second author’s name was misspelled. The correct spelling should be Dierk F Reiff. The error has been corrected in the HTML version of the article. This correction has been appended to the PDF and print versions.

Surface properties of bearing steel and other small automotive parts are generally modified in an effort to enhance its hardness and wear characteristics. In the current study, tantalum and graphite powders are added to surface of steel during tungsten inert gas (TIG) arcing to create in situ tantalum carbide to improve reinforcement to the modified surface in addition to the hard martensite matrix. Numerical simulation using COMSOL software was performed to estimate the thermal profile and validated by the experimental observation. The microstructural characteristics of the matrix were examined using optical, scanning and transmission electron microscope (OM, SEM and TEM). High resolution transmission electron microscope (HRTEM) along with electron energy loss spectrum (EELS) mode was employed to understand the type of carbide particles formed. It was found that the top modified surface contains TaC particles which enhances the hardness. The extent upto which different zones like fusion and heat affected zone, base metal, etc formed after the arcing was established both by microscopic examination and micro-hardness mapping. Modified surfaces show a notable increase in hardness from 100 to 150 percent relative to the base material. The weight loss during wear testing for different modified surfaces was significantly reduced by two to four times when compared to the substrate, indicating the presence of an effective wear resistance mechanism in the modified surfaces.

In response to vascular injury, vascular smooth muscle cells (VSMCs) may switch from a contractile to a proliferative phenotype thereby contributing to neointima formation. Previous studies showed that the long noncoding RNA (lncRNA) NEAT1 is critical for paraspeckle formation and tumorigenesis by promoting cell proliferation and migration. However, the role of NEAT1 in VSMC phenotypic modulation is unknown. Herein we showed that NEAT1 expression was induced in VSMCs during phenotypic switching in vivo and in vitro. Silencing NEAT1 in VSMCs resulted in enhanced expression of SM-specific genes while attenuating VSMC proliferation and migration. Conversely, overexpression of NEAT1 in VSMCs had opposite effects. These in vitro findings were further supported by in vivo studies in which NEAT1 knockout mice exhibited significantly decreased neointima formation following vascular injury, due to attenuated VSMC proliferation. Mechanistic studies demonstrated that NEAT1 sequesters the key chromatin modifier WDR5 (WD Repeat Domain 5) from SM-specific gene loci, thereby initiating an epigenetic “off” state, resulting in down-regulation of SM-specific gene expression. Taken together, we demonstrated an unexpected role of the lncRNA NEAT1 in regulating phenotypic switching by repressing SM-contractile gene expression through an epigenetic regulatory mechanism. Our data suggest that NEAT1 is a therapeutic target for treating occlusive vascular diseases.