Comparing Patients' Perceptions of Dry Eye Disease Between Spanish- and English-Speaking Patients in the United States.

PURPOSE: It is well-known that patients' perceptions of their disease can impact management strategies and disease outcomes. Limited knowledge exists on such perceptions in dry eye disease (DED) and the role of language in these perceptions. Herein, we compared the perceptions about DED between Spanish- and English-speaking patients. METHODS: This cross-sectional study included 146 patients with DED who underwent ophthalmic evaluation and completed questionnaires assessing their perceptions of DED on a 10-point scale during their routine appointments. Perceptions included opinions on the level of satisfaction with understanding of DED, ease of following doctor's advice, effectiveness of treatment, satisfaction with DED care, and outlook on DED. Perceptions were categorized as low (scores 0-2), moderate (scores 3-7), and high (scores 8-10). The percentage of patients with high perception scores were then compared between Spanish- and English-speaking patients. RESULTS: There were 48 Spanish speakers and 98 English speakers. Overall, high scores of DED perceptions were identified in 47.9% for satisfaction with the level of understanding of DED, 72.6% for ease of following doctor's advice, 52.1% for helpfulness of DED treatment, 64.4% for satisfaction with DED care, and 52.1% for optimistic outlook on DED. High scores for satisfaction with the level of understanding of DED were significantly lower in Spanish speakers (27.1%) than English speakers (58.2%, p < .001). No significant differences were observed in other perceptions between Spanish- and English-speaking participants. CONCLUSIONS: Spanish-speaking subjects reported lower satisfaction with their understanding of DED than English speakers. Clinicians should provide health services and educational materials in the patient's preferred language to minimize barriers to understanding their disease.

Modeling epithelial homeostasis and perturbation in three-dimensional human esophageal organoids.

Background: Esophageal organoids from a variety of pathologies including cancer are grown in Advanced Dulbecco's Modified Eagle Medium-Nutrient Mixture F12 (hereafter ADF). However, the currently available ADF-based formulations are suboptimal for normal human esophageal organoids, limiting the ability to compare normal esophageal organoids with those representing a given disease state. Methods: We have utilized immortalized normal human esophageal epithelial cell (keratinocyte) lines EPC1 and EPC2 and endoscopic normal esophageal biopsies to generate three-dimensional (3D) organoids. To optimize ADF-based medium, we evaluated the requirement of exogenous epidermal growth factor (EGF) and inhibition of transforming growth factor-(TGF)-ß receptor-mediated signaling, both key regulators of proliferation of human esophageal keratinocytes. We have modeled human esophageal epithelial pathology by stimulating esophageal 3D organoids with interleukin (IL)-13, an inflammatory cytokine, or UAB30, a novel pharmacological activator of retinoic acid signaling. Results: The formation of normal human esophageal 3D organoids was limited by excessive EGF and intrinsic TGFß receptor-mediated signaling. In optimized HOME0, normal human esophageal organoid formation was improved, whereas IL-13 and UAB30 induced epithelial changes reminiscent of basal cell hyperplasia, a common histopathologic feature in broad esophageal disease conditions including eosinophilic esophagitis. Conclusions: HOME0 allows modeling of the homeostatic differentiation gradient and perturbation of the human esophageal epithelium while permitting a comparison of organoids from mice and other organs grown in ADF-based media.

An LSTM-based adversarial variational autoencoder framework for self-supervised neural decoding of behavioral choices.

Objective.This paper presents data-driven solutions to address two challenges in the problem of linking neural data and behavior: (1) unsupervised analysis of behavioral data and automatic label generation from behavioral observations, and (2) extraction of subject-invariant features for the development of generalized neural decoding models.Approach. For behavioral analysis and label generation, an unsupervised method, which employs an autoencoder to transform behavioral data into a cluster-friendly feature space is presented. The model iteratively refines the assigned clusters with soft clustering assignment loss, and gradually improves the learned feature representations. To address subject variability in decoding neural activity, adversarial learning in combination with a long short-term memory-based adversarial variational autoencoder (LSTM-AVAE) model is employed. By using an adversary network to constrain the latent representations, the model captures shared information among subjects' neural activity, making it proper for cross-subject transfer learning.Main results. The proposed approach is evaluated using cortical recordings of Thy1-GCaMP6s transgenic mice obtained via widefield calcium imaging during a motivational licking behavioral experiment. The results show that the proposed model achieves an accuracy of 89.7% in cross-subject neural decoding, outperforming other well-known autoencoder-based feature learning models. These findings suggest that incorporating an adversary network eliminates subject dependency in representations, leading to improved cross-subject transfer learning performance, while also demonstrating the effectiveness of LSTM-based models in capturing the temporal dependencies within neural data.Significance. Results demonstrate the feasibility of the proposed framework in unsupervised clustering and label generation of behavioral data, as well as achieving high accuracy in cross-subject neural decoding, indicating its potentials for relating neural activity to behavior.

Cell-Type Specific Connectivity of Whisker-Related Sensory and Motor Cortical Input to Dorsal Striatum.

The anterior dorsolateral striatum (DLS) is heavily innervated by convergent excitatory projections from the primary motor (M1) and sensory cortex (S1) and considered an important site of sensorimotor integration. M1 and S1 corticostriatal synapses have functional differences in their connection strength with striatal spiny projection neurons (SPNs) and fast-spiking interneurons (FSIs) in the DLS and, as a result, exert distinct influences on sensory-guided behaviors. In the present study, we tested whether M1 and S1 inputs exhibit differences in the subcellular anatomical distribution of striatal neurons. We injected adeno-associated viral vectors encoding spaghetti monster fluorescent proteins (sm.FPs) into M1 and S1 in male and female mice and used confocal microscopy to generate 3D reconstructions of corticostriatal inputs to single identified SPNs and FSIs obtained through ex vivo patch clamp electrophysiology. We found that M1 and S1 dually innervate SPNs and FSIs; however, there is a consistent bias towards the M1 input in SPNs that is not found in FSIs. In addition, M1 and S1 inputs were distributed similarly across the proximal, medial, and distal regions of SPN and FSI dendrites. Notably, closely localized M1 and S1 clusters of inputs were more prevalent in SPNs than FSIs, suggesting that cortical inputs are integrated through cell-type specific mechanisms. Our results suggest that the stronger functional connectivity from M1 to SPNs compared to S1, as previously observed, is due to a higher quantity of synaptic inputs. Our results have implications for how sensorimotor integration is performed in the striatum through cell-specific differences in corticostriatal connections.

Patient diversity and author representation in clinical studies supporting the Surviving Sepsis Campaign guidelines for management of sepsis and septic shock 2021: a systematic review of citations.

BACKGROUND: The generalizability of the Surviving Sepsis Campaign (SSC) guidelines to various patient populations and hospital settings has been debated. A quantitative assessment of the diversity and representation in the clinical evidence supporting the guidelines would help evaluate the generalizability of the recommendations and identify strategic research goals and priorities. In this study, we evaluated the diversity of patients in the original studies, in terms of sex, race/ethnicity, and geographical location. We also assessed diversity in sex and geographical representation among study first and last authors. METHODS: All clinical studies cited in support of the 2021 SSC adult guideline recommendations were identified. Original clinical studies were included, while editorials, reviews, non-clinical studies, and meta-analyses were excluded. For eligible studies, we recorded the proportion of male patients, percentage of each represented racial/ethnic subgroup (when available), and countries in which they were conducted. We also recorded the sex and location of the first and last authors. The World Bank classification was used to categorize countries. RESULTS: The SSC guidelines included six sections, with 85 recommendations based on 351 clinical studies. The proportion of male patients ranged from 47 to 62%. Most studies did not report the racial/ ethnic distribution of the included patients; when they did so, most were White patients (68-77%). Most studies were conducted in high-income countries (77-99%), which included Europe/Central Asia (33-66%) and North America (36-55%). Moreover, most first/last authors were males (55-93%) and from high-income countries (77-99%). CONCLUSIONS: To enhance the generalizability of the SCC guidelines, stakeholders should define strategies to enhance the diversity and representation in clinical studies. Though there was reasonable representation in sex among patients included in clinical studies, the evidence did not reflect diversity in the race/ethnicity and geographical locations. There was also lack of diversity among the first and last authors contributing to the evidence.

Cell-Type Specific Connectivity of Whisker-Related Sensory and Motor Cortical Input to Dorsal Striatum.

The anterior dorsolateral striatum (DLS) is heavily innervated by convergent excitatory projections from the primary motor (M1) and sensory cortex (S1) and is considered an important site of sensorimotor integration. M1 and S1 corticostriatal synapses have functional differences in the strength of their connections with striatal spiny projection neurons (SPNs) and fast-spiking interneurons (FSIs) in the DLS, and as a result exert an opposing influence on sensory-guided behaviors. In the present study, we tested whether M1 and S1 inputs exhibit differences in the subcellular anatomical distribution onto striatal neurons. We injected adeno-associated viral vectors encoding spaghetti monster fluorescent proteins (sm.FPs) into M1 and S1, and used confocal microscopy to generate 3D reconstructions of corticostriatal inputs to single identified SPNs and FSIs obtained through ex-vivo patch-clamp electrophysiology. We found that SPNs are less innervated by S1 compared to M1, but FSIs receive a similar number of inputs from both M1 and S1. In addition, M1 and S1 inputs were distributed similarly across the proximal, medial, and distal regions of SPNs and FSIs. Notably, clusters of inputs were prevalent in SPNs but not FSIs. Our results suggest that SPNs have stronger functional connectivity to M1 compared to S1 due to a higher density of synaptic inputs. The clustering of M1 and S1 inputs onto SPNs but not FSIs suggest that cortical inputs are integrated through cell-type specific mechanisms and more generally have implications for how sensorimotor integration is performed in the striatum. Significance Statement: The dorsolateral striatum (DLS) is a key brain area involved in sensorimotor integration due to its dense innervation by the primary motor (M1) and sensory cortex (S1). However, the quantity and anatomical distribution of these inputs to the striatal cell population has not been well characterized. In this study we demonstrate that corticostriatal projections from M1 and S1 differentially innervate spiny projection neurons (SPNs) and fast-spiking interneurons (FSIs) in the DLS. S1 inputs innervate SPNs less than M1 and are likely to form synaptic clusters in SPNs but not in FSIs. These findings suggest that sensorimotor integration is partly achieved by differences in the synaptic organization of corticostriatal inputs to local striatal microcircuits.

Developing and validating clinical features-based machine learning algorithms to predict influenza infection in influenza-like illness patients.

BACKGROUND: Seasonal influenza poses a significant risk, and patients can benefit from early diagnosis and treatment. However, underdiagnosis and undertreatment remain widespread. We developed and compared clinical feature-based machine learning (ML) algorithms that can accurately predict influenza infection in emergency departments (EDs) among patients with influenza-like illness (ILI). MATERIAL AND METHODS: We conducted a prospective cohort study in five EDs in the US and Taiwan from 2015 to 2020. Adult patients visiting the EDs with symptoms of ILI were recruited and tested by real-time RT-PCR for influenza. We evaluated seven ML algorithms and compared their results with previously developed clinical prediction models. RESULTS: Out of the 2189 enrolled patients, 1104 tested positive for influenza. The eXtreme Gradient Boosting achieved superior performance with an area under the receiver operating characteristic curve of 0.82 (95% confidence interval [CI] = 0.79-0.85), with a sensitivity of 0.92 (95% CI = 0.88-0.95), specificity of 0.89 (95% CI = 0.86-0.92), and accuracy of 0.72 (95% CI = 0.69-0.76) in the testing set over cut-offs of 0.4, 0.6 and 0.5, respectively. These results were superior to those of previously proposed clinical prediction models. The model interpretation revealed that body temperature, cough, rhinorrhea, and exposure history were positively associated with and the days of illness and influenza vaccine were negatively associated with influenza infection. We also found the week of the influenza season, pulse rate, and oxygen saturation to be associated with influenza infection. CONCLUSIONS: The clinical feature-based ML model outperformed conventional models for predicting influenza infection.

Perioperative Efficiency of Sugammadex Following Laparoscopic Cholecystectomy in Clinical Practice.

Background: Studies have proposed that the routine use of the modified gamma-cyclodextrin, sugammadex, could provide perioperative time savings. However, these investigations have been limited to small group analyses. The purpose of this study was to test the effectiveness of sugammadex on perioperative times when compared to neostigmine under general clinical practice conditions following rocuronium-induced neuromuscular blockade for laparoscopic cholecystectomy. Methods: Following institutional review board approval, data from 1,611 consecutive surgical records for laparoscopic cholecystectomy were reviewed. Patient characteristics, type of primary neuromuscular blocking reversal agent, operating room (OR) discharge times, and postanesthesia care unit (PACU) recovery times were the measures of interest. Equivalence testing was used to determine the between-group differences of the reversal agents in the two perioperative time periods of interest. Results: OR discharge times averaged 10.9 (95% CI, 10-11.8) minutes for patients administered sugammadex and 8.9 (95% CI, 8.2-9.7) minutes for patients administered neostigmine. PACU recovery times averaged 77.6 (95% CI, 74.1-81.1) minutes for sugammadex and 68.6 (95% CI, 65.9-71.3) minutes for neostigmine. Equivalence testing demonstrated no improvement in the two perioperative times with sugammadex. Conclusion: These results suggest no perioperative time savings with sugammadex when compared to neostigmine following laparoscopic cholecystectomy under general clinical practice conditions.

Brain serotonergic fibers suggest anomalous diffusion-based dropout in artificial neural networks.

Random dropout has become a standard regularization technique in artificial neural networks (ANNs), but it is currently unknown whether an analogous mechanism exists in biological neural networks (BioNNs). If it does, its structure is likely to be optimized by hundreds of millions of years of evolution, which may suggest novel dropout strategies in large-scale ANNs. We propose that the brain serotonergic fibers (axons) meet some of the expected criteria because of their ubiquitous presence, stochastic structure, and ability to grow throughout the individual's lifespan. Since the trajectories of serotonergic fibers can be modeled as paths of anomalous diffusion processes, in this proof-of-concept study we investigated a dropout algorithm based on the superdiffusive fractional Brownian motion (FBM). The results demonstrate that serotonergic fibers can potentially implement a dropout-like mechanism in brain tissue, supporting neuroplasticity. They also suggest that mathematical theories of the structure and dynamics of serotonergic fibers can contribute to the design of dropout algorithms in ANNs.

Comparison of HPMC Inhalation-Grade Capsules and Their Effect on Aerosol Performance Using Budesonide and Rifampicin DPI Formulations.

Despite the fact that capsules play an important role in many dry powder inhalation (DPI) systems, few studies have been conducted to investigate the capsules' interactions with respirable powders. The effect of four commercially available hydroxypropyl methylcellulose (HPMC)inhalation-grade capsule types on the aerosol performance of two model DPI formulations (lactose carrier and a carrier-free formulation) at two different pressure drops was investigated in this study. There were no statistically significant differences in performance between capsules by using the carrier-based formulation. However, there were some differences between the capsules used for the carrier-free rifampicin formulation. At 2-kPa pressure drop conditions, Embocaps® VG capsules had a higher mean emitted fraction (EF) (89.86%) and a lower mean mass median aerodynamic diameter (MMAD) (4.19 µm) than Vcaps® (Capsugel) (85.54%, 5.10 µm) and Quali-V® I (Qualicaps) (85.01%, 5.09 µm), but no significant performance differences between Embocaps® and ACGcaps™ HI. Moreover, Embocaps® VG capsules exhibited a higher mean respirable fraction (RF)/fine particle fraction (FPF) with a 3-µm-sized cutoff (RF/FPF< 3 µm) (33.05%/35.36%) against Quali-V® I (28.16%/31.75%) (P < 0.05), and a higher RF/FPF with a 5-µm-sized cutoff (RF/FPF< 5 µm) (49.15%/52.57%) versus ACGcaps™ HI (38.88%/41.99%) (P < 0.01) at 4-kPa pressure drop condition. Aerosol performance variability, pierced-flap detachment, as well as capsule hardness and stiffness, may all influence capsule type selection in a carrier-based formulation. The capsule type influenced EF, RF, FPF, and MMAD in the carrier-free formulation.

Antitarget Selectivity and Tolerability of Novel Pyrrolo[2,3-d]pyrimidine RET Inhibitors.

The selective inhibition of RET kinase as a treatment for relevant cancer types including lung adenocarcinoma has garnered considerable interest in recent years and prompted a variety of efforts toward the discovery of small-molecule therapeutics. Hits uncovered via the analysis of archival kinase data ultimately led to the identification of a promising pyrrolo[2,3-d]pyrimidine scaffold. The optimization of this pyrrolo[2,3-d]pyrimidine core resulted in compound 1, which demonstrated potent in vitro RET kinase inhibition and robust in vivo efficacy in RET-driven tumor xenografts upon multiday dosing in mice. The administration of 1 was well-tolerated at established efficacious doses (10 and 30 mg/kg, po, qd), and plasma exposure levels indicated a minimal risk of KDR or hERG inhibition in vivo, as evaluated by Miles assay and free plasma concentrations, respectively.

Pan-cancer analysis of non-coding transcripts reveals the prognostic onco-lncRNA HOXA10-AS in gliomas.

Long non-coding RNAs (lncRNAs) are increasingly recognized as functional units in cancer and powerful biomarkers; however, most remain uncharacterized. Here, we analyze 5,592 prognostic lncRNAs in 9,446 cancers of 30 types using machine learning. We identify 166 lncRNAs whose expression correlates with survival and improves the accuracy of common clinical variables, molecular features, and cancer subtypes. Prognostic lncRNAs are often characterized by switch-like expression patterns. In low-grade gliomas, HOXA10-AS activation is a robust marker of poor prognosis that complements IDH1/2 mutations, as validated in another retrospective cohort, and correlates with developmental pathways in tumor transcriptomes. Loss- and gain-of-function studies in patient-derived glioma cells, organoids, and xenograft models identify HOXA10-AS as a potent onco-lncRNA that regulates cell proliferation, contact inhibition, invasion, Hippo signaling, and mitotic and neuro-developmental pathways. Our study underscores the pan-cancer potential of the non-coding transcriptome for identifying biomarkers and regulators of cancer progression.

Single allele loss-of-function mutations select and sculpt conditional cooperative networks in breast cancer.

The most common events in breast cancer (BC) involve chromosome arm losses and gains. Here we describe identification of 1089 gene-centric common insertion sites (gCIS) from transposon-based screens in 8 mouse models of BC. Some gCIS are driver-specific, others driver non-specific, and still others associated with tumor histology. Processes affected by driver-specific and histology-specific mutations include well-known cancer pathways. Driver non-specific gCIS target the Mediator complex, Ca++ signaling, Cyclin D turnover, RNA-metabolism among other processes. Most gCIS show single allele disruption and many map to genomic regions showing high-frequency hemizygous loss in human BC. Two gCIS, Nf1 and Trps1, show synthetic haploinsufficient tumor suppressor activity. Many gCIS act on the same pathway responsible for tumor initiation, thereby selecting and sculpting just enough and just right signaling. These data highlight ~1000 genes with predicted conditional haploinsufficient tumor suppressor function and the potential to promote chromosome arm loss in BC.

Functional and genetic determinants of mutation rate variability in regulatory elements of cancer genomes.

BACKGROUND: Cancer genomes are shaped by mutational processes with complex spatial variation at multiple scales. Entire classes of regulatory elements are affected by local variations in mutation frequency. However, the underlying mechanisms with functional and genetic determinants remain poorly understood. RESULTS: We characterise the mutational landscape of 1.3 million gene-regulatory and chromatin architectural elements in 2419 whole cancer genomes with transcriptional and pathway activity, functional conservation and recurrent driver events. We develop RM2, a statistical model that quantifies mutational enrichment or depletion in classes of genomic elements through genetic, trinucleotide and megabase-scale effects. We report a map of localised mutational processes affecting CTCF binding sites, transcription start sites (TSS) and tissue-specific open-chromatin regions. Increased mutation frequency in TSSs associates with mRNA abundance in most cancer types, while open-chromatin regions are generally enriched in mutations. We identify ~ 10,000 CTCF binding sites with core DNA motifs and constitutive binding in 66 cell types that represent focal points of mutagenesis. We detect site-specific mutational signature enrichments, such as SBS40 in open-chromatin regions in prostate cancer and SBS17b in CTCF binding sites in gastrointestinal cancers. Candidate drivers of localised mutagenesis are also apparent: BRAF mutations associate with mutational enrichments at CTCF binding sites in melanoma, and ARID1A mutations with TSS-specific mutagenesis in pancreatic cancer. CONCLUSIONS: Our method and catalogue of localised mutational processes provide novel perspectives to cancer genome evolution, mutagenesis, DNA repair and driver gene discovery. The functional and genetic correlates of mutational processes suggest mechanistic hypotheses for future studies.

Structure-Based Design of Selective LONP1 Inhibitors for Probing In Vitro Biology.

LONP1 is an AAA+ protease that maintains mitochondrial homeostasis by removing damaged or misfolded proteins. Elevated activity and expression of LONP1 promotes cancer cell proliferation and resistance to apoptosis-inducing reagents. Despite the importance of LONP1 in human biology and disease, very few LONP1 inhibitors have been described in the literature. Herein, we report the development of selective boronic acid-based LONP1 inhibitors using structure-based drug design as well as the first structures of human LONP1 bound to various inhibitors. Our efforts led to several nanomolar LONP1 inhibitors with little to no activity against the 20S proteasome that serve as tool compounds to investigate LONP1 biology.

Activity-dependent somatodendritic dopamine release in the substantia nigra autoinhibits the releasing neuron.

Somatodendritic dopamine (DA) release from midbrain DA neurons activates D2 autoreceptors on these cells to regulate their activity. However, the source of autoregulatory DA remains controversial. Here, we test the hypothesis that D2 autoreceptors on a given DA neuron in the substantia nigra pars compacta (SNc) are activated primarily by DA released from that same cell, rather than from its neighbors. Voltage-clamp recording allows monitoring of evoked D2-receptor-mediated inhibitory currents (D2ICs) in SNc DA neurons as an index of DA release. Single-cell application of antibodies to Na+ channels via the recording pipette decreases spontaneous activity of recorded neurons and attenuates evoked D2ICs; antibodies to SNAP-25, a soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) protein, also decrease D2IC amplitude. Evoked D2ICs are nearly abolished by the light chain of botulinum neurotoxin A, which cleaves SNAP-25, whereas synaptically activated GABAB-receptor-mediated currents are unaffected. Thus, somatodendritic DA release in the SNc autoinhibits the neuron that releases it.

Efficacy and Tolerability of Pyrazolo[1,5-a]pyrimidine RET Kinase Inhibitors for the Treatment of Lung Adenocarcinoma.

RET (REarranged during Transfection) kinase gain-of-function aberrancies have been identified as potential oncogenic drivers in lung adenocarcinoma, along with several other cancer types, prompting the discovery and assessment of selective inhibitors. Internal mining and analysis of relevant kinase data informed the decision to investigate a pyrazolo[1,5-a]pyrimidine scaffold, where subsequent optimization led to the identification of compound WF-47-JS03 (1), a potent RET kinase inhibitor with >500-fold selectivity against KDR (Kinase insert Domain Receptor) in cellular assays. In subsequent mouse in vivo studies, compound 1 demonstrated effective brain penetration and was found to induce strong regression of RET-driven tumor xenografts at a well-tolerated dose (10 mg/kg, po, qd). Higher doses of 1, however, were poorly tolerated in mice, similar to other pyrazolo[1,5-a]pyrimidine compounds at or near the efficacious dose, and indicative of the narrow therapeutic windows seen with this scaffold.

Investigating learning-related neural circuitry with chronic in vivo optical imaging.

Fundamental aspects of brain function, including development, plasticity, learning, and memory, can take place over time scales of days to years. Chronic in vivo imaging of neural activity with cellular resolution is a powerful method for tracking the long-term activity of neural circuits. We review recent advances in our understanding of neural circuit function from diverse brain regions that have been enabled by chronic in vivo cellular imaging. Insight into the neural basis of learning and decision-making, in particular, benefit from the ability to acquire longitudinal data from genetically identified neuronal populations, deep brain areas, and subcellular structures. We propose that combining chronic imaging with further experimental and computational innovations will advance our understanding of the neural circuit mechanisms of brain function.

Opposing Influence of Sensory and Motor Cortical Input on Striatal Circuitry and Choice Behavior.

The striatum is the main input nucleus of the basal ganglia and is a key site of sensorimotor integration. While the striatum receives extensive excitatory afferents from the cerebral cortex, the influence of different cortical areas on striatal circuitry and behavior is unknown. Here, we find that corticostriatal inputs from whisker-related primary somatosensory (S1) and motor (M1) cortex differentially innervate projection neurons and interneurons in the dorsal striatum and exert opposing effects on sensory-guided behavior. Optogenetic stimulation of S1-corticostriatal afferents in ex vivo recordings produced larger postsynaptic potentials in striatal parvalbumin (PV)-expressing interneurons than D1- or D2-expressing spiny projection neurons (SPNs), an effect not observed for M1-corticostriatal afferents. Critically, in vivo optogenetic stimulation of S1-corticostriatal afferents produced task-specific behavioral inhibition, which was bidirectionally modulated by striatal PV interneurons. Optogenetic stimulation of M1 afferents produced the opposite behavioral effect. Thus, our results suggest opposing roles for sensory and motor cortex in behavioral choice via distinct influences on striatal circuitry.

Optogenetic and transcriptomic interrogation of enhanced muscle function in the paralyzed mouse whisker pad.

The functional state of denervated muscle is a critical factor in the ability to restore movement after injury- or disease-related paralysis. Here we used peripheral optogenetic stimulation and transcriptome profiling in the mouse whisker system to investigate the time course of changes in neuromuscular function following complete unilateral facial nerve transection. While most skeletal muscles rapidly lose functionality after lower motor neuron denervation, optogenetic muscle stimulation of the paralyzed whisker pad revealed sustained increases in the sensitivity, velocity, and amplitude of whisker movements, and reduced fatigability, starting 48 h after denervation. RNA-seq analysis showed distinct regulation of multiple gene families in denervated whisker pad muscles compared with the atrophy-prone soleus, including prominent changes in ion channels and contractile fibers. Together, our results define the unique functional and transcriptomic landscape of denervated facial muscles and have general implications for restoring movement after neuromuscular injury or disease. NEW & NOTEWORTHY Optogenetic activation of muscle can be used to noninvasively induce movements and probe muscle function. We used this technique in mice to investigate changes in whisker movements following facial nerve transection. We found unexpectedly enhanced functional properties of whisker pad muscle following denervation, accompanied by unique transcriptomic changes. Our findings highlight the utility of the mouse whisker pad for investigating the restoration of movement after paralysis.