Virulence Traits and Azole Resistance in Korean Candida auris Isolates.

We analyzed the virulence traits and azole resistance mechanisms of 104 Candida auris isolates collected from 13 Korean hospitals from 1996 to 2022. Of these 104 isolates, 96 (5 blood and 91 ear isolates) belonged to clade II, and 8 (6 blood and 2 other isolates) belonged to clade I. Fluconazole resistance (minimum inhibitory concentration ≥32 mg/L) was observed in 68.8% of clade II and 25.0% of clade I isolates. All 104 isolates were susceptible to amphotericin B and three echinocandins. In 2022, six clade I isolates indicated the first nosocomial C. auris cluster in Korea. Clade II C. auris isolates exhibited reduced thermotolerance at 42 °C, with diminished in vitro competitive growth and lower virulence in the Galleria mellonella model compared to non-clade II isolates. Of the 66 fluconazole-resistant clade II isolates, several amino acid substitutions were identified: Erg11p in 14 (21.2%), Tac1Ap in 2 (3.0%), Tac1Bp in 62 (93.9%), and Tac1Bp F214S in 33 (50.0%). Although there were a limited number of non-clade II isolates studied, our results suggest that clade II C. auris isolates from Korean hospitals might display lower virulence traits than non-clade II isolates, and their primary fluconazole resistance mechanism is linked to Tac1Bp mutations.

Revealing invisible cell phenotypes with conditional generative modeling.

Biological sciences, drug discovery and medicine rely heavily on cell phenotype perturbation and microscope observation. However, most cellular phenotypic changes are subtle and thus hidden from us by natural cell variability: two cells in the same condition already look different. In this study, we show that conditional generative models can be used to transform an image of cells from any one condition to another, thus canceling cell variability. We visually and quantitatively validate that the principle of synthetic cell perturbation works on discernible cases. We then illustrate its effectiveness in displaying otherwise invisible cell phenotypes triggered by blood cells under parasite infection, or by the presence of a disease-causing pathological mutation in differentiated neurons derived from iPSCs, or by low concentration drug treatments. The proposed approach, easy to use and robust, opens the door to more accessible discovery of biological and disease biomarkers.

Molecular and Clinical Features of Fluconazole Non-susceptible Candida albicans Bloodstream Isolates Recovered in Korean Multicenter Surveillance Studies.

Acquired fluconazole resistance (FR) in bloodstream infection (BSI) isolates of Candida albicans is rare. We investigated the FR mechanisms and clinical features of 14 fluconazole non-susceptible (FNS; FR and fluconazole-susceptible dose-dependent) BSI isolates of C. albicans recovered from Korean multicenter surveillance studies during 2006-2021. Mutations causing amino acid substitutions (AASs) in the drug-target gene ERG11 and the FR-associated transcription factor genes TAC1, MRR1, and UPC2 of the 14 FNS isolates were compared with those of 12 fluconazole-susceptible isolates. Of the 14 FNS isolates, eight and seven had Erg11p (K143R, F145L, or G464S) and Tac1p (T225A, R673L, A736T, or A736V) AASs, respectively, which were previously described in FR isolates. Novel Erg11p, Tac1p, and Mrr1p AASs were observed in two, four, and one FNS isolates, respectively. Combined Erg11p and Tac1p AASs were observed in seven FNS isolates. None of the FR-associated Upc2p AASs were detected. Of the 14 patients, only one had previous azole exposure, and the 30-day mortality rate was 57.1% (8/14). Our data show that Erg11p and Tac1p AASs are likely to contribute to FR in C. albicans BSI isolates in Korea and that most FNS C. albicans BSIs develop without azole exposure.

Observation of Hidden Polar Phases and Flux Closure Domain Topology in Bi2WO6 Thin Films.

Topological textures of ferroelectric polarizations have promise as alternative devices for future information technology. A polarization rotation inevitably deviates from the stable orientation in axial ferroelectrics, but local energy losses compromise the global symmetry, resulting in a distorted shape of the topological vortex or inhibiting the vortex. Easy planar isotropy helps to promote rotating structures and, accordingly, to facilitate access to nontrivial textures. Here, we investigate the domain structure of an epitaxial thin film of bismuth tungsten oxide (Bi2WO6) grown on a (001) SrTiO3 substrate. By using angle-resolved piezoresponse force microscopy and scanning transmission electron microscopy, we find the existence of a hidden phase with ⟨100⟩-oriented ferroelectric polarizations in the middle of the four variant ⟨110⟩-oriented polarization domains, which assists in the formation of flux closure domains. The results suggest that this material is one step closer to becoming an isotropic two-dimensional polar material.

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma.

BACKGROUND: Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. METHODS: We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. RESULTS: In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e-4 for progression-free survival (PFS) and 3.63e-4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fisher's exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e-4 for PFS and 3.66e-4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient using in vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage ( http://www.wang-lab-hkust.com:3838/TMZEP ). CONCLUSIONS: We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs.

High-content phenotyping of Parkinson's disease patient stem cell-derived midbrain dopaminergic neurons using machine learning classification.

Combining multiple Parkinson's disease (PD) relevant cellular phenotypes might increase the accuracy of midbrain dopaminergic neuron (mDAN) in vitro models. We differentiated patient-derived induced pluripotent stem cells (iPSCs) with a LRRK2 G2019S mutation, isogenic control, and genetically unrelated iPSCs into mDANs. Using automated fluorescence microscopy in 384-well-plate format, we identified elevated levels of α-synuclein (αSyn) and serine 129 phosphorylation, reduced dendritic complexity, and mitochondrial dysfunction. Next, we measured additional image-based phenotypes and used machine learning (ML) to accurately classify mDANs according to their genotype. Additionally, we show that chemical compound treatments, targeting LRRK2 kinase activity or αSyn levels, are detectable when using ML classification based on multiple image-based phenotypes. We validated our approach using a second isogenic patient-derived SNCA gene triplication mDAN model which overexpresses αSyn. This phenotyping and classification strategy improves the practical exploitability of mDANs for disease modeling and the identification of novel LRRK2-associated drug targets.

Patient-Derived Tumor Organoids for Guidance of Personalized Drug Therapies in Recurrent Glioblastoma.

An obstacle to effective uniform treatment of glioblastoma, especially at recurrence, is genetic and cellular intertumoral heterogeneity. Hence, personalized strategies are necessary, as are means to stratify potential targeted therapies in a clinically relevant timeframe. Functional profiling of drug candidates against patient-derived glioblastoma organoids (PD-GBO) holds promise as an empirical method to preclinically discover potentially effective treatments of individual tumors. Here, we describe our establishment of a PD-GBO-based functional profiling platform and the results of its application to four patient tumors. We show that our PD-GBO model system preserves key features of individual patient glioblastomas in vivo. As proof of concept, we tested a panel of 41 FDA-approved drugs and were able to identify potential treatment options for three out of four patients; the turnaround from tumor resection to discovery of treatment option was 13, 14, and 15 days, respectively. These results demonstrate that this approach is a complement and, potentially, an alternative to current molecular profiling efforts in the pursuit of effective personalized treatment discovery in a clinically relevant time period. Furthermore, these results warrant the use of PD-GBO platforms for preclinical identification of new drugs against defined morphological glioblastoma features.

Personalized functional profiling using ex-vivo patient-derived spheroids points out the potential of an antiangiogenic treatment in a patient with a metastatic lung atypical carcinoid.

Lung carcinoids are neuroendocrine tumors representing 1 to 2% of lung cancers. This study outlines the case of a patient with a metastatic lung atypical carcinoid who presented with a pleural effusion and progression of liver metastases after developing resistance to conventional treatments. Personalized functional profiling (PFP), i.e. drug screening, was performed in ex-vivo spheroids obtained from the patient's liver metastasis to identify potential therapeutic options. The drug screening results revealed cediranib, an antiangiogenic drug, as a hit drug for this patient, from a library of 66 Food and Drug Administration (FDA)-approved and investigational drugs. Based on the PFP results and the reported evidence of clinical efficacy of bevacizumab and capecitabine combination in gastro-intestinal neuroendocrine tumors, this combination was given to the patient. Four months later, the pleural effusion and pleura carcinosis regressed and the liver metastasis did not progress. The patient experienced 2 years of a stable disease under the PFP-guided personalized treatment.

Gene-corrected p.A30P SNCA patient-derived isogenic neurons rescue neuronal branching and function.

Parkinson's disease (PD) is characterised by the degeneration of A9 dopaminergic neurons and the pathological accumulation of alpha-synuclein. The p.A30P SNCA mutation generates the pathogenic form of the alpha-synuclein protein causing an autosomal-dominant form of PD. There are limited studies assessing pathogenic SNCA mutations in patient-derived isogenic cell models. Here we provide a functional assessment of dopaminergic neurons derived from a patient harbouring the p.A30P SNCA mutation. Using two clonal gene-corrected isogenic cell lines we identified image-based phenotypes showing impaired neuritic processes. The pathological neurons displayed impaired neuronal activity, reduced mitochondrial respiration, an energy deficit, vulnerability to rotenone, and transcriptional alterations in lipid metabolism. Our data describes for the first time the mutation-only effect of the p.A30P SNCA mutation on neuronal function, supporting the use of isogenic cell lines in identifying image-based pathological phenotypes that can serve as an entry point for future disease-modifying compound screenings and drug discovery strategies.

Dynamics and Predictors of Mortality Due to Candidemia Caused by Different Candida Species: Comparison of Intensive Care Unit-Associated Candidemia (ICUAC) and Non-ICUAC.

We investigated mortality and predictors of mortality due to intensive care unit-associated candidemia (ICUAC) versus non-ICUAC by Candida species. This study included all candidemia cases in 11 hospitals from 2017 to 2018 in South Korea. The all-cause mortality rates in all 370 patients with ICUAC were approximately twofold higher than those in all 437 patients with non-ICUAC at 7 days (2.3-fold, 31.1%/13.3%), 30 days (1.9-fold, 49.5%/25.4%), and 90 days (1.9-fold, 57.8%/30.9%). Significant species-specific associations with 7- and 30-day ICUAC-associated mortality were not observed. Multivariate analysis revealed that ICU admission was an independent predictor of Candida glabrata (OR, 2.07-2.48) and Candida parapsilosis-associated mortality (OR, 6.06-11.54). Fluconazole resistance was a predictor of C. glabrata-associated mortality (OR, 2.80-5.14). Lack (less than 3 days) of antifungal therapy was the strongest predictor of 7-day mortality due to ICUAC caused by Candida albicans (OR, 18.33), Candida tropicalis (OR, 10.52), and C. glabrata (OR, 21.30) compared with 30- and 90-day mortality (OR, 2.72-6.90). C. glabrata ICUAC had a stronger association with lack of antifungal therapy (55.2%) than ICUAC caused by other species (30.6-36.7%, all p < 0.05). Most predictors of mortality associated with ICUAC were distinct from those associated with non-ICUAC and were mediated by Candida species.

CXCL10 Is an Agonist of the CC Family Chemokine Scavenger Receptor ACKR2/D6.

Atypical chemokine receptors (ACKRs) are important regulators of chemokine functions. Among them, the atypical chemokine receptor ACKR2 (also known as D6) has long been considered as a scavenger of inflammatory chemokines exclusively from the CC family. In this study, by using highly sensitive ß-arrestin recruitment assays based on NanoBiT and NanoBRET technologies, we identified the inflammatory CXC chemokine CXCL10 as a new strong agonist ligand for ACKR2. CXCL10 is known to play an important role in the infiltration of immune cells into the tumour bed and was previously reported to bind to CXCR3 only. We demonstrated that ACKR2 is able to internalize and reduce the availability of CXCL10 in the extracellular space. Moreover, we found that, in contrast to CC chemokines, CXCL10 activity towards ACKR2 was drastically reduced by the dipeptidyl peptidase 4 (DPP4 or CD26) N-terminal processing, pointing to a different receptor binding pocket occupancy by CC and CXC chemokines. Overall, our study sheds new light on the complexity of the chemokine network and the potential role of CXCL10 regulation by ACKR2 in many physiological and pathological processes, including tumour immunology. Our data also testify that systematic reassessment of chemokine-receptor pairing is critically needed as important interactions may remain unexplored.

Integrated, automated maintenance, expansion and differentiation of 2D and 3D patient-derived cellular models for high throughput drug screening.

Patient-derived cellular models become an increasingly powerful tool to model human diseases for precision medicine approaches. The identification of robust cellular disease phenotypes in these models paved the way towards high throughput screenings (HTS) including the implementation of laboratory advanced automation. However, maintenance and expansion of cells for HTS remains largely manual work. Here, we describe an integrated, complex automated platform for HTS in a translational research setting also designed for maintenance and expansion of different cell types. The comprehensive design allows automation of all cultivation steps and is flexible for development of methods for variable cell types. We demonstrate protocols for controlled cell seeding, splitting and expansion of human fibroblasts, induced pluripotent stem cells (iPSC), and neural progenitor cells (NPC) that allow for subsequent differentiation into different cell types and image-based multiparametric screening. Furthermore, we provide automated protocols for neuronal differentiation of NPC in 2D culture and 3D midbrain organoids for HTS. The flexibility of this multitask platform makes it an ideal solution for translational research settings involving experiments on different patient-derived cellular models for precision medicine.

Evaluation of a Fully Automated Antinuclear Antibody Indirect Immunofluorescence Assay in Routine Use.

Indirect immunofluorescence assay (IFA) using HEp-2 cells as a substrate is the gold standard for detecting antinuclear antibodies (ANA) in patient serum. However, the ANA IFA has labor-intensive nature of the procedure and lacks adequate standardization. To overcome these drawbacks, the automation has been developed and implemented to the clinical laboratory. The purposes of this study were to evaluate the analytical performance of a fully automated Helios ANA IFA analyzer in a real-life laboratory setting, and to compare the time and the cost of ANA IFA testing before and after adopting the Helios system. A total of 3,276 consecutive serum samples were analyzed for ANA using the Helios system from May to August 2019. The positive/negative results, staining patterns, and endpoint titers were compared between Helios and visual readings. Furthermore, the turnaround time and the number of wells used were compared before and after the introduction of Helios system. Of the 3,276 samples tested, 748 were positive and 2,528 were negative based on visual readings. Using visual reading as the reference standard, the overall relative sensitivity, relative specificity, and concordance of Helios reading were 73.3, 99.4, and 93.4% (κ = 0.80), respectively. For pattern recognition, the overall agreement was 70.1% (298/425) for single patterns, and 72.4% (89/123) for mixed patterns. For titration, there was an agreement of 75.9% (211/278) between automated and classical endpoint titers by regarding within ± one titer difference as acceptable. Helios significantly shortened the median turnaround time from 100.6 to 55.7 h (P < 0.0001). Furthermore, routine use of the system reduced the average number of wells used per test from 4 to 1.5. Helios shows good agreement in distinguishing between positive and negative results. However, it still has limitations in positive/negative discrimination, pattern recognition, and endpoint titer prediction, requiring additional validation of results by human observers. Helios provides significant advantages in routine laboratory ANA IFA work in terms of labor, time, and cost savings. We hope that upgrading and developing softwares with more reliable capabilities will allow automated ANA IFA analyzers to be fully integrated into the routine operations of the clinical laboratory.

Patient-derived organoids and orthotopic xenografts of primary and recurrent gliomas represent relevant patient avatars for precision oncology.

Patient-based cancer models are essential tools for studying tumor biology and for the assessment of drug responses in a translational context. We report the establishment a large cohort of unique organoids and patient-derived orthotopic xenografts (PDOX) of various glioma subtypes, including gliomas with mutations in IDH1, and paired longitudinal PDOX from primary and recurrent tumors of the same patient. We show that glioma PDOXs enable long-term propagation of patient tumors and represent clinically relevant patient avatars that retain histopathological, genetic, epigenetic, and transcriptomic features of parental tumors. We find no evidence of mouse-specific clonal evolution in glioma PDOXs. Our cohort captures individual molecular genotypes for precision medicine including mutations in IDH1, ATRX, TP53, MDM2/4, amplification of EGFR, PDGFRA, MET, CDK4/6, MDM2/4, and deletion of CDKN2A/B, PTCH, and PTEN. Matched longitudinal PDOX recapitulate the limited genetic evolution of gliomas observed in patients following treatment. At the histological level, we observe increased vascularization in the rat host as compared to mice. PDOX-derived standardized glioma organoids are amenable to high-throughput drug screens that can be validated in mice. We show clinically relevant responses to temozolomide (TMZ) and to targeted treatments, such as EGFR and CDK4/6 inhibitors in (epi)genetically defined subgroups, according to MGMT promoter and EGFR/CDK status, respectively. Dianhydrogalactitol (VAL-083), a promising bifunctional alkylating agent in the current clinical trial, displayed high therapeutic efficacy, and was able to overcome TMZ resistance in glioblastoma. Our work underscores the clinical relevance of glioma organoids and PDOX models for translational research and personalized treatment studies and represents a unique publicly available resource for precision oncology.

RNAi Screening-based Identification of USP10 as a Novel Regulator of Paraptosis.

Accumulating reports demonstrate that apoptosis does not explain all the effects of cancer therapy due to the innate and acquired apoptotic resistance of malignant cancer cells. Recently, paraptosis, a type of programmed cell death accompanied by dilation of mitochondria and/or the endoplasmic reticulum (ER), has garnered interest in cancer research as an alternative way to kill apoptosis-resistant cancers. We describe here the adaptation and validation of a high-content cell-based assay to screen and identify novel paraptotic regulators employing the malignant breast cancer cells undergoing curcumin-induced paraptosis. We used YFP-Mito cells, which express fluorescence selectively in mitochondria, to select paraptosis-related genes whose corresponding siRNAs appeared to modulate mitochondrial dilation, a morphological feature of paraptosis. From the selected 38 candidate genes, we chose ubiquitin specific peptidase 10 (USP10), a ubiquitin specific protease, as a strongly active candidate that warranted further evaluation of its involvement in paraptosis. We found that both siRNA-mediated knockdown of USP10 and treatment with the USP10 inhibitor, spautin-1, effectively attenuated curcumin-induced paraptosis. This systematic assay, in which a siRNA library is screened for the ability to ameliorate paraptotic changes in mitochondria, may enable researchers to identify potent regulators of paraptosis and new candidate genes/drugs to combat malignant breast cancer.

Candida auris Clinical Isolates from South Korea: Identification, Antifungal Susceptibility, and Genotyping.

Candida auris is an emerging worldwide fungal pathogen. Over the past 20 years, 61 patient isolates of C. auris (4 blood and 57 ear) have been obtained from 13 hospitals in Korea. Here, we reanalyzed those molecularly identified isolates using two matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) systems, including Biotyper and Vitek MS, followed by antifungal susceptibility testing, sequencing of the ERG11 gene, and genotyping. With a research-use-only (RUO) library, 83.6% and 93.4% of the isolates were correctly identified by Biotyper and Vitek MS, respectively. Using an in vitro diagnostic (IVD) library of Vitek MS, 96.7% of the isolates were correctly identified. Fluconazole-resistant isolates made up 62.3% of the isolates, while echinocandin- or multidrug-resistant isolates were not found. Excellent essential (within two dilutions, 96.7%) and categorical agreements (93.4%) between the Clinical and Laboratory Standards Institute (CLSI) and Vitek 2 (AST-YS07 card) methods were observed for fluconazole. Sequencing ERG11 for all 61 isolates revealed that only 3 fluconazole-resistant isolates showed the Erg11p amino acid substitution K143R. All 61 isolates showed identical multilocus sequence typing (MLST). Pulsed-field gel electrophoresis (PFGE) analyses revealed that both blood and ear isolates had the same or similar patterns. These results show that MALDI-TOF MS and Vitek 2 antifungal susceptibility systems can be reliable diagnostic tools for testing C. auris isolates from Korean hospitals. The Erg11p mutation was seldom found among Korean isolates of C. auris, and multidrug resistance was not found. Both MLST and PFGE analyses suggest that these isolates are genetically similar.

Drug Efficacy Comparison of 3D Forming and Preforming Sphere Models with a Micropillar and Microwell Chip Platform.

Hepatocellular carcinoma (HCC), a major histological subtype of liver cancer, is the third most common cause of cancer-related death worldwide. Currently, many curative standard treatments using target-specific chemotherapeutic agents are being developed. However, drug efficacy tests based on the 2D monolayer cell culture model do not effectively screen the best drug candidates because they do not accurately reflect in vivo tumor microenvironments. Thus, to select the best drug candidates or repositioning drugs, we developed new 3D in vitro hepatic tumor models, including 3D forming and preformed sphere models. A micropillar and microwell chip platform was used for the 3D in vitro liver cell-based model for high-throughput screening. We measured the efficacy of 60 drugs and sorted the most efficacious drugs by comparing the drug response of the 2D monolayer model with the 3D forming and preformed sphere models. Among the 60 drugs, 17 drugs (28.3%) showed a significant high efficacy in the 3D preformed sphere model, while 45 drugs (75%) showed an efficacy in the 2D model. We also calculated the IC50 values of the 17 drugs and found that 7 drugs exhibited a high sensitivity in HCC, which was in agreement with previous studies.

Pharmacogenomic landscape of patient-derived tumor cells informs precision oncology therapy.

Outcomes of anticancer therapy vary dramatically among patients due to diverse genetic and molecular backgrounds, highlighting extensive intertumoral heterogeneity. The fundamental tenet of precision oncology defines molecular characterization of tumors to guide optimal patient-tailored therapy. Towards this goal, we have established a compilation of pharmacological landscapes of 462 patient-derived tumor cells (PDCs) across 14 cancer types, together with genomic and transcriptomic profiling in 385 of these tumors. Compared with the traditional long-term cultured cancer cell line models, PDCs recapitulate the molecular properties and biology of the diseases more precisely. Here, we provide insights into dynamic pharmacogenomic associations, including molecular determinants that elicit therapeutic resistance to EGFR inhibitors, and the potential repurposing of ibrutinib (currently used in hematological malignancies) for EGFR-specific therapy in gliomas. Lastly, we present a potential implementation of PDC-derived drug sensitivities for the prediction of clinical response to targeted therapeutics using retrospective clinical studies.

Familiarity with a vocal category biases the compartmental expression of Arc/Arg3.1 in core auditory cortex.

Learning to recognize a stimulus category requires experience with its many natural variations. However, the mechanisms that allow a category's sensorineural representation to be updated after experiencing new exemplars are not well understood, particularly at the molecular level. Here we investigate how a natural vocal category induces expression in the auditory system of a key synaptic plasticity effector immediate early gene, Arc/Arg3.1, which is required for memory consolidation. We use the ultrasonic communication system between mouse pups and adult females to study whether prior familiarity with pup vocalizations alters how Arc is engaged in the core auditory cortex after playback of novel exemplars from the pup vocal category. A computerized, 3D surface-assisted cellular compartmental analysis, validated against manual cell counts, demonstrates significant changes in the recruitment of neurons expressing Arc in pup-experienced animals (mothers and virgin females "cocaring" for pups) compared with pup-inexperienced animals (pup-naïve virgins), especially when listening to more familiar, natural calls compared to less familiar but similarly recognized tonal model calls. Our data support the hypothesis that the kinetics of Arc induction to refine cortical representations of sensory categories is sensitive to the familiarity of the sensory experience.