Variants in the SCN1A gene are associated with a wide range of disorders including genetic epilepsy with febrile seizures plus (GEFS+), familial hemiplegic migraine (FHM), and the severe childhood epilepsy Dravet syndrome (DS). Predicting disease outcomes based on variant type remains challenging. Despite thousands of SCN1A variants being reported, only a minority has been functionally assessed.We review the functional SCN1A work performed to date, critically appraise electrophysiological measurements, compare this to in silico predictions, and relate our findings to the clinical phenotype.Our results show, regardless of the underlying phenotype, that conventional in silico software correctly predicted benign from pathogenic variants in nearly 90%, however was unable to differentiate within the disease spectrum (DS vs. GEFS+ vs. FHM). In contrast, patch-clamp data from mammalian expression systems revealed functional differences among missense variants allowing discrimination between disease severities. Those presenting with milder phenotypes retained a degree of channel function measured as residual whole-cell current, whereas those without any wholecell current were often associated with DS (p = .024).These findings demonstrate that electrophysiological data from mammalian expression systems can serve as useful disease biomarker when evaluating SCN1A variants, particularly in view of new and emerging treatment options in DS. K E Y W O R D SDravet syndrome, electrophysiology, familial hemiplegic migraine, functional testing, GEFS+, patch-clamp, SCN1A *Andreas Brunklaus and Stephanie Schorge contributed equally to this study.

We have screened sporadic early-onset Alzheimer’s disease (sEOAD, n = 408) samples using the NeuroX array for known causative and predicted pathogenic variants in 16 genes linked to familial forms of neurodegeneration. We found 2 sEOAD individuals harboring a known causative variant in PARK2 known to cause early-onset Parkinson’s disease; p.T240M (n = 1) and p.Q34fs delAG (n = 1). In addition, we identified 3 sEOAD individuals harboring a predicted pathogenic variant in MAPT (p.A469T), which has previously been associated with AD. It is currently unknown if these variants affect susceptibility to sEOAD, further studies would be needed to establish this. This work highlights the need to screen sEOAD individuals for variants that are more classically attributed to other forms of neurodegeneration.

Background: Eliciting doses (EDs) (eg, ED 01 or ED 05 values, which are the amounts of allergen expected to cause objective symptoms in 1% and 5% of the population with an allergy, respectively) are increasingly being used to inform allergen labeling and clinical management. These values are generated from food challenge, but the frequency of anaphylaxis in From a the

Opioids account for 69,000 overdose deaths per annum worldwide and cause serious side effects. Safer analgesics are urgently needed. The endogenous opioid peptide Leu-Enkephalin (Leu-ENK) is ineffective when introduced peripherally due to poor stability and limited membrane permeability. We developed a focused library of Leu-ENK analogs containing small hydrophobic modifications. N-pivaloyl analog KK-103 showed the highest binding affinity to the delta opioid receptor (68% relative to Leu-ENK) and an extended plasma half-life of 37 h. In the murine hot-plate model, subcutaneous KK-103 showed 10-fold improved anticonception (142%MPE·h) compared to Leu-ENK (14%MPE·h). In the formalin model, KK-103 reduced the licking and biting time to ~50% relative to the vehicle group. KK-103 was shown to act through the opioid receptors in the central nervous system. In contrast to morphine, KK-103 was longer-lasting and did not induce breathing depression, physical dependence, and tolerance, showing potential as a safe and effective analgesic.

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