#JNeurosci: Adkins et al. explored how binge alcohol exposure and protracted abstinence impact the S1-insular circuit in mice, revealing how alcohol can reshape sensory processing to drive alcohol use disorder-related behavior. doi.org/10.1523/JNEUROSCI.15…

I don’t know how this claim has gone so viral. This was actually completely intentional by Novo. Novo Nordisk does not operate in an “oops. lawyer forgot the $250 CAD fee” manner. This is, with all due respect, a shallow read of Novo’s actual corporate strategy. (1/)

1. That is not a 'single nuc' dataset ... What’s being shown here is from the 2006 Allen Mouse Atlas using chromogenic DIG riboprobe ISH(single probe, single section, enzyme-amplified signal) ... That’s fundamentally different from modern datasets (snRNA-seq, MERFISH, Xenium), which sample 10⁵–10⁶ cells across animals with cell-type classification. That legacy ISH pipeline has known limitations for genes like GPCRs: - single probe per gene (isoform / region sensitivity) - nonlinear enzymatic amplification (BCIP/NBT) - limited dynamic range and no cell-type annotation - section-level variability (one slice ≠ population estimate) So a single probe image from 20 years ago is not a rigorous argument nor a quantitative or cell-type–resolved readout 2. Re: “can snRNA-seq detect GPCRs/neuropeptides?” Yes—with caveats. Nuclear RNA has lower abundance, but - detection improves with depth and aggregation across cells - multiple platforms (snRNA-seq, MERFISH, Xenium) now converge on similar cell-type assignments - MERFISH/Xenium bypass dropout via targeted probe amplification and spatial counting So the question isn’t one dataset—it’s convergence across modalities. 3. For Oprm1, we see consistent enrichment in glutamatergic populations across - snRNA-seq (mouse + human) - spatial transcriptomics (MERFISH / Xenium) - IHC - genetic access (multiple Oprm1-Cre lines) - viral promoter strategies - in vivo calcium imaging (morphine modulation of mMORp+ pyramidal activity) That’s orthogonal convergence, which is not cited ever in your papers/review artciles 4. Electrophysiology is powerful, but it’s also sampling-limited - biased toward visually accessible neurons (often L2/3 but not layers 5-6, as written in your Methods) - low N relative to transcriptomic datasets (10s vs 100k-millions of cells) - cell identity often inferred post hoc So slice ephys can overrepresentspecific populations depending on targeting strategy MOR signaling in cortex is largely dendritic and presynaptic, not confined to somatic excitability. Acute slices sever long-range afferents and axonal projections, limiting access to these compartments. Patch-clamp readouts (spiking, IPSCs) capture only a subset of GPCR function, missing modulation of dendritic integration, Ca²⁺ dynamics, and release probability, thus requiring orthogonal readouts to make claims like where MORs are expressed .. luckily that data exists! and it shows OPRM1/MORs are in gluatmatergic neurons and to a lesser extent some interneurons populations

Across single-nuc seq, FISH, IHC, four cell-type mouse lines, and a viral promoter, OPRM1/MOR is consistently enriched in glutamatergic PFC neurons While some slice electrophysiology studies emphasize GABAergic localization—biased, low throughput methodological differences?