A numerical model for Hodgkin-Huxley neural stimulus reconstruction

The information about a neural activity is encoded in a neural response and usually the underlying stimulus that triggers the activity is unknown. This paper presents a numerical solution to reconstruct stimuli from Hodgkin-Huxley neural responses while retrieving the neural dynamics. The stimulus is reconstructed by first retrieving the maximal conductances of the ion channels and then solving the Hodgkin-Huxley equations for the stimulus. The results show that the reconstructed stimulus is a good approximation of the original stimulus, while the retrieved the neural dynamics, which represent the voltage-dependent changes in the ion channels, help to understand the changes in neural biochemistry. As high non-linearity of neural dynamics renders analytical inversion of a neuron an arduous task, a numerical approach provides a local solution to the problem of stimulus reconstruction and neural dynamics retrieval

LRR-protein RNH1 dampens the inflammasome activation and is associated with COVID-19 severity.

Inflammasomes are cytosolic innate immune sensors of pathogen infection and cellular damage that induce caspase-1-mediated inflammation upon activation. Although inflammation is protective, uncontrolled excessive inflammation can cause inflammatory diseases and can be detrimental, such as in coronavirus disease (COVID-19). However, the underlying mechanisms that control inflammasome activation are incompletely understood. Here we report that the leucine-rich repeat (LRR) protein ribonuclease inhibitor (RNH1), which shares homology with LRRs of NLRP (nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain containing) proteins, attenuates inflammasome activation. Deletion of RNH1 in macrophages increases interleukin (IL)-1β production and caspase-1 activation in response to inflammasome stimulation. Mechanistically, RNH1 decreases pro-IL-1β expression and induces proteasome-mediated caspase-1 degradation. Corroborating this, mouse models of monosodium urate (MSU)-induced peritonitis and lipopolysaccharide (LPS)-induced endotoxemia, which are dependent on caspase-1, respectively, show increased neutrophil infiltration and lethality in Rnh1 <sup>-/-</sup> mice compared with wild-type mice. Furthermore, RNH1 protein levels were negatively related with disease severity and inflammation in hospitalized COVID-19 patients. We propose that RNH1 is a new inflammasome regulator with relevance to COVID-19 severity

Spiking Neurons and Synaptic Stimuli: Determining the Fidelity of Coincidence-Factor in Neural Response Comparison

Abstract — Similarity between two spike trains is generally estimated using a ‘coincidence factor’. This factor relies on counting coincidences of firing-times for spikes in a given time window. However, in cases where there are significant fluctuations in membrane voltages, this uni-dimensional view is not sufficient. Results in this paper show that a two-dimensional approach taking both firing-time and the magnitude of spikes is necessary to determine similarity between spike trains. It is observed that the difference between the lower-bound limit of faithful behaviour and the reference inter-spike interval (ISI) reduces with the increase in the ISI of the input spike train. This indicates that spike trains generated by two highly-varying currents have a high coincidence factor thus indicating higher similarity – a limitation imposed due to a one-dimensional comparison approach. These results are analysed based on the responses of a Hodgkin-Huxley neuron, where the synaptic input induces fluctuations in the output membrane voltage. The requirement for a two-dimensional analysis is further supported by a clustering algorithm which differentiates between two visually-distinct responses as opposed to coincidence-factor. Index Terms—coincidence-factor, fluctuations, comparison, synaptic stimuli, membrane voltage

Stimulus reconstruction from a Hodgkin-Huxley neural response: A numerical solution

Neural responses are the fundamental expressions of any neural activity. Information carried by a neural response is determined by the nature of a neural activity. In majority of cases the underlying stimulus that triggers it remains largely unknown. Previous studies to reconstruct the stimulus from a neural response show that the high non-linearity of neural dynamics renders inversion of a neuron a challenging task. This paper presents a numerical solution rather than an analytical one to reconstruct stimuli from Hodgkin-Huxley neural responses. The stimulus is reconstructed by first retrieving the maximal conductances of the ionic channels and then solving the Hodgkin-Huxley equations for the stimulus. The results show that the reconstructed stimulus matches the original stimulus to a high degree of accuracy. In addition, this reconstruction approach also retrieves the neural dynamics for which an analytical solution does not currently exist. Constant-current and periodic stimuli are shown to be accurately reconstructed using this approach

Spiking neurons: Is coincidence-factor enough for comparing responses with fluctuating membrane voltage?

Similarity between two spike trains is generally estimated using a ‘coincidence factor’. This factor relies on counting coincidences of firing-times for spikes in a given time window. However, in cases where there are significant fluctuations in membrane voltages, this uni-dimensional view is not sufficient. Results in this paper show that a two-dimensional approach taking both firing-time and the magnitude of spikes is necessary to determine similarity between spike trains. It is observed that the difference between the lower-bound limit of faithful behaviour and the reference inter-spike interval (ISI) reduces with the increase in the ISI of the input spike train. This indicates that spike trains generated by two highly-varying currents have a high coincidence factor thus indicating higher similarity – a limitation imposed due to a one-dimensional comparison approach. These results are analysed based on the responses of a Hodgkin-Huxley neuron, where the synaptic input induces fluctuations in the output membrane voltage. The requirement for a two-dimensional analysis is further supported by a clustering algorithm which differentiates between two visually-distinct responses as opposed to coincidence-factor. Index Terms—coincidenc

Pharmacovigilance assessment of the association between Fournier's gangrene and other severe genital adverse events with SGLT-2 inhibitors

Objective: Sodium glucose cotransporter-2 inhibitors (SGLT2i) exert cardiorenal protection in people with diabetes. By inducing glycosuria, SGLT2i predispose to genital infections. In addition, rare occurrence of Fournier's gangrene (FG) has been reported. We aimed to investigate such association through the U.S. Food and Drug Administration (FDA) adverse event (AE) reporting system (FAERS). Research design and methods: We mined the FAERS up to 2018q3 (before FDA warning about SGLT2i-associated FG) to retrieve reports including FG as an AE and SGLT2i as suspect or concomitant drugs, and calculated proportional reporting ratios (PRR). Results: We retrieved 47 cases of FG and 17 cases of other severe AEs of the genital area associated with SGLT2i. Patients with FG were 3c10 years older than those with other severe genital AEs. Overall, 77% occurred in men. Three patients were concomitantly treated with systemic immunosuppressive drugs. Increased reporting frequency emerged for SGLT2i compared with other drugs, with a PRR ranging from 5 to 10. The disproportional reporting of FG with SGLT2i remained robust and consistently significant when restricting to the period when SGLT2i were available, to reports filed for glucose-lowering medications or for drugs with the diabetes indication, and after refining the definition of FG. FG was disproportionally associated with psoriasis and with the combination of immunosuppressants and SGLT2i. Conclusions: Although causality cannot be demonstrated, SGLT2i may predispose to FG and other severe genital AEs. Since the use of SGLT2i is expected to increase significantly, clinicians should be aware of these severe, although rare, AEs and their predisposing factors