Cortical axons contain a diverse range of voltage-activated ion channels, including Ca²⁺currents. Interestingly, Ca²⁺channels are not only located at presynaptic terminals, but also in the axon initial segment (AIS), suggesting a potentially important role in the regulation of action potential generation and neuronal excitability. Here, using two-photon microscopy and whole-cell patch-clamp recording, we examined the properties and role of calcium channels located in the AIS and presynaptic terminals of ferret layer 5 prefrontal cortical pyramidal cellsin vitro. Subthreshold depolarization of the soma resulted in an increase in baseline and spike-triggered calcium concentration in both the AIS and nearby synaptic terminals. The increase in baseline calcium concentration rose with depolarization and fell with hyperpolarization with a time constant of approximately 1 s and was blocked by removal of Ca²⁺from the bathing medium. The increases in calcium concentration at the AIS evoked by subthreshold or suprathreshold depolarization of the soma were blocked by the P/Q-channel antagonist ω-agatoxin IVA or the N-channel antagonist ω-conotoxin GVIA or both. The presence of these channels in the AIS pyramidal cells was confirmed with immunochemistry. Block of these channels slowed axonal action potential repolarization, apparently from reduction of the activation of a Ca²⁺-activated K⁺current, and increased neuronal excitability. These results demonstrate novel mechanisms by which calcium currents may control the electrophysiological properties of axonal spike generation and neurotransmitter release in the neocortex.

The Architecture, Engineering, and Construction (AEC) Industry is one of the most important productive sectors, hence also produce a high impact on the economic balances, societal stability, and global challenges in climate change. Regarding its adoption of technologies, applications and processes is also recognized by its status-quo, its slow innovation pace, and the conservative approaches. However, a new technological era - Industry 4.0 fueled by AI- is driving productive sectors in a highly pressurized global technological competition and sociopolitical landscape. In this paper, we develop an adaptive approach to mining text content in the literature research corpus related to the AEC and AI (AEC-AI) industries, in particular on its relation to technological processes and applications. We present a first stage approach to an adaptive assessment of AI algorithms, to form an integrative AI platform in the AEC industry, the AEC-AI industry 4.0. At this stage, a macroscopic adaptive method is deployed to characterize “Optimization,” a key term in AEC-AI industry, using a mixed methodology incorporating machine learning and classical evaluation process. Our results show that effective use of metadata, constrained search queries, and domain knowledge allows getting a macroscopic assessment of the target concept. This allows the extraction of a high-level mapping and conceptual structure characterization of the literature corpus. The results are comparable, at this level, to classical methodologies for the literature review. In addition, our method is designed for an adaptive assessment to incorporate further stages.