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Obesity-induced inflammation causes metabolic dysfunction, but the mechanisms remain elusive. Here we show that the innate immune transcription factor interferon regulatory factor (IRF3) adversely affects glucose homeostasis through induction of the endogenous FAHFA hydrolase androgen induced gene 1 (AIG1) in adipocytes. Adipocyte-specific knockout of IRF3 protects male mice against high-fat diet-induced insulin resistance, whereas overexpression of IRF3 or AIG1 in adipocytes promotes insulin resistance on a high-fat diet. Furthermore, pharmacological inhibition of AIG1 reversed obesity-induced insulin resistance and restored glucose homeostasis in the setting of adipocyte IRF3 overexpression. We, therefore, identify the adipocyte IRF3/AIG1 axis as a crucial link between obesity-induced inflammation and insulin resistance and suggest an approach for limiting the metabolic dysfunction accompanying obesity., (© 2024. The Author(s).)

Most research on mental lexical representations (lemmas) assumes they are discrete and correspond in number to a word's number of distinct meanings. Thus, homophones ( bat ), whose meanings are unrelated, have separate lemmas for each meaning (one for baseball bat , another for flying bat ), whereas polysemes ( paper ), whose senses are related, have shared lemmas (the same lemma for printer paper and term paper ). However, most aspects of cognition are thought to be graded, not discrete; could lemmas be graded too? We conducted a preregistered picture-word interference study with pictures of words whose meanings ranged from unrelated (homophones) to very related (regular polysemes). Whereas semantic competitors to picture names slow picture naming, semantic competitors to non-depicted meanings of homophones facilitate naming, suggesting distinct lemmas for homophones' meanings. We predicted that competitors to non-depicted senses of polysemes would slow naming, as polysemes' depicted and non-depicted senses presumably share a lemma. Crucially, we aimed to examine the transition from facilitation to inhibition: two groupings (where competitors to non-depicted senses led to facilitation for words with two lemmas but inhibition for words with one lemma) would imply that lemmas are indeed discrete. But a transition that varies continuously by sense relatedness would imply that lemmas are graded. Unexpectedly, competitors to non-depicted senses of both homophones and polysemes facilitated naming. Although these results do not indicate whether lemmas are graded or discrete, they do inform a long-standing question on the nature of polysemes, supporting a multiple-lemma (vs. core-lemma) account., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The "dorsal pons", or "dorsal pontine tegmentum" (dPnTg), is part of the brainstem. It is a complex, densely packed region whose nuclei are involved in regulating many vital functions. Notable among them are the parabrachial nucleus, the Kölliker Fuse, the Barrington nucleus, the locus coeruleus, and the dorsal, laterodorsal, and ventral tegmental nuclei. In this study, we applied single-nucleus RNA-seq (snRNA-seq) to resolve neuronal subtypes based on their unique transcriptional profiles and then used multiplexed error robust fluorescence in situ hybridization (MERFISH) to map them spatially. We sampled ~1 million cells across the dPnTg and defined the spatial distribution of over 120 neuronal subtypes. Our analysis identified an unpredicted high transcriptional diversity in this region and pinpointed the unique marker genes of many neuronal subtypes. We also demonstrated that many neuronal subtypes are transcriptionally similar between humans and mice, enhancing this study's translational value. Finally, we developed a freely accessible, GPU and CPU-powered dashboard ( http://harvard.heavy.ai:6273/ ) that combines interactive visual analytics and hardware-accelerated SQL into a data science framework to allow the scientific community to query and gain insights into the data., (© 2024. The Author(s).)