ABSTRACT
BACKGROUND: Improved COVID-19 prevention is needed for immunocompromised individuals. METHODS: Prospective study of healthcare workers (HCW) and immunocompromised participants with baseline serology following 2 mRNA vaccines and who were retested after dose 3 (D3); multivariable regression was used to identify predictors of serological responses. IFNγ/TNFα T-cell responses were assessed in a subset. RESULTS: 536 participants were included: 492 immunocompromised [(206 solid organ transplant (SOT), 128 autoimmune, 80 hematologic malignancy (HM), 48 solid tumor, 25 HIV], 44 HCW. D3 significantly increased Spike IgG levels among all, but SOT and HM participants had the lowest median antibody levels post-D3 (increase from 0.09 to 0.83 and 0.27 to 1.92, respectively), versus HCW and persons with HIV, autoimmune conditions, and solid tumors (increases from 4.44 to 19.79, 2.9 to 15.75, 3.82 to 16.32, and 4.1 to 25.54, respectively). Seropositivity post-D3 was lowest for SOT (49.0%) and HM (57.8%), versus others (>90% seropositive). Neutralization post-D3 was lowest among SOT and HM. Predictors of lower antibody levels included low baseline levels and shorter intervals between vaccines. T-cell responses against Spike increased significantly among HCW and non-significantly among immunocompromised individuals. CONCLUSIONS: D3 significantly improves serological but not T-cell responses among immunocompromised individuals. SOT and HM patients have suboptimal responses to D3.
ABSTRACT
Essential genes tend to be highly conserved across eukaryotes, but, in some cases, their critical roles can be bypassed through genetic rewiring. From a systematic analysis of 728 different essential yeast genes, we discovered that 124 (17%) were dispensable essential genes. Through whole-genome sequencing and detailed genetic analysis, we investigated the genetic interactions and genome alterations underlying bypass suppression. Dispensable essential genes often had paralogs, were enriched for genes encoding membrane-associated proteins, and were depleted for members of protein complexes. Functionally related genes frequently drove the bypass suppression interactions. These gene properties were predictive of essential gene dispensability and of specific suppressors among hundreds of genes on aneuploid chromosomes. Our findings identify yeast's core essential gene set and reveal that the properties of dispensable essential genes are conserved from yeast to human cells, correlating with human genes that display cell line-specific essentiality in the Cancer Dependency Map (DepMap) project.
Subject(s)
Genes, Essential , Genes, Fungal , Saccharomyces cerevisiae/genetics , Suppression, Genetic , Aneuploidy , Evolution, Molecular , Gene Deletion , Gene Duplication , Gene Regulatory Networks , Genes, Suppressor , Multiprotein Complexes/metabolismABSTRACT
BACKGROUND: Publicly available speech corpora facilitate reproducible research by providing open-access data for participants who have consented/assented to data sharing among different research teams. Such corpora can also support clinical education, including perceptual training and training in the use of speech analysis tools. PURPOSE: In this research note, we introduce the PERCEPT (Perceptual Error Rating for the Clinical Evaluation of Phonetic Targets) corpora, PERCEPT-R (Rhotics) and PERCEPT-GFTA (Goldman-Fristoe Test of Articulation), which together contain over 36 hr of speech audio (> 125,000 syllable, word, and phrase utterances) from children, adolescents, and young adults aged 6-24 years with speech sound disorder (primarily residual speech sound disorders impacting /ɹ/) and age-matched peers. We highlight PhonBank as the repository for the corpora and demonstrate use of the associated speech analysis software, Phon, to query PERCEPT-R. A worked example of research with PERCEPT-R, suitable for clinical education and research training, is included as an appendix. Support for end users and information/descriptive statistics for future releases of the PERCEPT corpora can be found in a dedicated Slack channel. Finally, we discuss the potential for PERCEPT corpora to support the training of artificial intelligence clinical speech technology appropriate for use with children with speech sound disorders, the development of which has historically been constrained by the limited representation of either children or individuals with speech impairments in publicly available training corpora. CONCLUSIONS: We demonstrate the use of PERCEPT corpora, PhonBank, and Phon for clinical training and research questions appropriate to child citation speech. Increased use of these tools has the potential to enhance reproducibility in the study of speech development and disorders.
Subject(s)
Speech Sound Disorder , Speech , Child , Adolescent , Humans , Artificial Intelligence , Reproducibility of Results , Speech Disorders , PhoneticsABSTRACT
Purpose: Recent research suggests that visual-acoustic biofeedback can be an effective treatment for residual speech errors, but adoption remains limited due to barriers including high cost and lack of familiarity with the technology. This case study reports results from the first participant to complete a course of visual-acoustic biofeedback using a not-for-profit iOS app, Speech Therapist's App for /r/ Treatment. Method: App-based biofeedback treatment for rhotic misarticulation was provided in weekly 30-min sessions for 20 weeks. Within-treatment progress was documented using clinician perceptual ratings and acoustic measures. Generalization gains were assessed using acoustic measures of word probes elicited during baseline, treatment, and maintenance sessions. Results: Both clinician ratings and acoustic measures indicated that the participant significantly improved her rhotic production accuracy in trials elicited during treatment sessions. However, these gains did not transfer to generalization probes. Conclusions: This study provides a proof-of-concept demonstration that app-based biofeedback is a viable alternative to costlier dedicated systems. Generalization of gains to contexts without biofeedback remains a challenge that requires further study. App-delivered biofeedback could enable clinician-research partnerships that would strengthen the evidence base while providing enhanced treatment for children with residual rhotic errors. Supplemental Material: https://doi.org/10.23641/asha.5116318.
Subject(s)
Articulation Disorders/therapy , Biofeedback, Psychology , Mobile Applications , Speech Therapy , Therapy, Computer-Assisted , Adolescent , Biofeedback, Psychology/methods , Female , Generalization, Psychological , Humans , Phonetics , Proof of Concept Study , Speech Acoustics , Speech Therapy/methods , Treatment OutcomeABSTRACT
Kinases and transcription factors (TFs) are key modulators of important signaling pathways and their activities underlie the proper function of many basic cellular processes such as cell division, differentiation, and development. Changes in kinase and TF dosage are often associated with disease, yet a systematic assessment of the cellular phenotypes caused by the combined perturbation of kinases and TFs has not been undertaken. We used a reverse-genetics approach to study the phenotypic consequences of kinase and TF overexpression (OE) in the budding yeast, Saccharomyces cerevisiae We constructed a collection of strains expressing stably integrated inducible alleles of kinases and TFs and used a variety of assays to characterize the phenotypes caused by TF and kinase OE. We used the Synthetic Genetic Array (SGA) method to examine dosage-dependent genetic interactions (GIs) between 239 gain-of-function (OE) alleles of TFs and six loss-of-function (LOF) and seven OE kinase alleles, the former identifying Synthetic Dosage Lethal (SDL) interactions and the latter testing a GI we call Double Dosage Lethality (DDL). We identified and confirmed 94 GIs between 65 OE alleles of TFs and 9 kinase alleles. Follow-up experiments validated regulatory relationships between genetically interacting pairs (Cdc28-Stb1 and Pho85-Pdr1), suggesting that GI studies involving OE alleles of regulatory proteins will be a rich source of new functional information.
Subject(s)
Gene Library , Protein Kinases/metabolism , Saccharomyces cerevisiae Proteins/metabolism , Saccharomyces cerevisiae/enzymology , Saccharomyces cerevisiae/genetics , Transcription Factors/metabolism , Alleles , Gene Dosage , Gene Expression Regulation, Fungal , Green Fluorescent Proteins/metabolism , Mutation/genetics , Protein Processing, Post-Translational/genetics , Saccharomyces cerevisiae/metabolismABSTRACT
Genetic suppression occurs when the phenotypic defects caused by a mutation in a particular gene are rescued by a mutation in a second gene. To explore the principles of genetic suppression, we examined both literature-curated and unbiased experimental data, involving systematic genetic mapping and whole-genome sequencing, to generate a large-scale suppression network among yeast genes. Most suppression pairs identified novel relationships among functionally related genes, providing new insights into the functional wiring diagram of the cell. In addition to suppressor mutations, we identified frequent secondary mutations,in a subset of genes, that likely cause a delay in the onset of stationary phase, which appears to promote their enrichment within a propagating population. These findings allow us to formulate and quantify general mechanisms of genetic suppression.
Subject(s)
Gene Regulatory Networks , Genes, Fungal , Genes, Suppressor , Saccharomyces cerevisiae Proteins/genetics , Saccharomyces cerevisiae/genetics , Suppression, Genetic , Cell Physiological Phenomena/genetics , Chromosome MappingABSTRACT
A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for approximately 75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.