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Objectives: Research on typically developing (TD) children and those with neurodevelopmental disorders and genetic syndromes was targeted. Specifically, studies on autism spectrum disorder, Down syndrome, Rett syndrome, fragile X syndrome, cerebral palsy, Angelman syndrome, tuberous sclerosis complex, Williams-Beuren syndrome, Cri-du-chat syndrome, Prader-Willi syndrome, and West syndrome were searched. The objectives are to review observational and computational studies on the emergence of (pre-)babbling vocalisations and outline findings on acoustic characteristics of early verbal functions.
Methods: A comprehensive review of the literature was performed including observational and computational studies focusing on spontaneous infant vocalisations at the pre-babbling age of TD children, individuals with genetic or neurodevelopmental disorders.
Results: While there is substantial knowledge about early vocal development in TD infants, the pre-babbling phase in infants with neurodevelopmental and genetic syndromes is scarcely scrutinised. Related approaches, paradigms, and definitions vary substantially and insights into the onset and characteristics of early verbal functions in most above-mentioned disorders are missing. Most studies focused on acoustic low-level descriptors (e.g. fundamental frequency) which bore limited clinical relevance. This calls for computational approaches to analyse features of infant typical and atypical verbal development.
Conclusions: Pre-babbling vocalisations as precursor for future speech-language functions may reveal valuable signs for identifying infants at risk for atypical development. Observational studies should be complemented by computational approaches to enable in-depth understanding of the developing speech-language functions. By disentangling features of typical and atypical early verbal development, computational approaches may support clinical screening and evaluation.
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http://dx.doi.org/10.1007/s41252-022-00300-7 | DOI Listing |
BMC Oral Health
September 2025
Oral and Maxillofacial Radiology Department, Cairo university, Cairo, Egypt.
Aim: The purpose of this study was to assess the accuracy of a customized deep learning model based on CNN and U-Net for detecting and segmenting the second mesiobuccal canal (MB2) of maxillary first molar teeth on cone beam computed tomography (CBCT) scans.
Methodology: CBCT scans of 37 patients were imported into 3D slicer software to crop and segment the canals of the mesiobuccal (MB) root of the maxillary first molar. The annotated data were divided into two groups: 80% for training and validation and 20% for testing.
Genome Biol
September 2025
Department of Biology, Plant-Microbe Interactions, Science for Life, Utrecht University, Utrecht, 3584CH, The Netherlands.
Background: Plant roots release root exudates to attract microbes that form root communities, which in turn promote plant health and growth. Root community assembly arises from millions of interactions between microbes and the plant, leading to robust and stable microbial networks. To manage the complexity of natural root microbiomes for research purposes, scientists have developed reductionist approaches using synthetic microbial inocula (SynComs).
View Article and Find Full Text PDFMetabolomics
September 2025
Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, Toulouse, France.
Introduction: Initially developed for transcriptomics data, pathway analysis (PA) methods can introduce biases when applied to metabolomics data, especially if input parameters are not chosen with care. This is particularly true for exometabolomics data, where there can be many metabolic steps between the measured exported metabolites in the profile and internal disruptions in the organism. However, evaluating PA methods experimentally is practically impossible when the sample's "true" metabolic disruption is unknown.
View Article and Find Full Text PDFAnn Biomed Eng
September 2025
Department of Mechanical Engineering, Koc University, Rumeli Feneri Campus, Sarıyer, 34450, Istanbul, Turkey.
Purpose: The design and development of ventricular assist devices have heavily relied on computational tools, particularly computational fluid dynamics (CFD), since the early 2000s. However, traditional CFD-based optimization requires costly trial-and-error approaches involving multiple design cycles. This study aims to propose a more efficient VAD design and optimization framework that overcomes these limitations.
View Article and Find Full Text PDFNPJ Biofilms Microbiomes
September 2025
Research Group Medical Systems Biology, University Hospital Schleswig-Holstein Campus Kiel, 24105 Kiel University, Kiel, Schleswig-Holstein, Germany.
Urinary tract infections (UTIs) are among the most common bacterial infections and are increasingly complicated by multidrug resistance (MDR). While Escherichia coli is frequently implicated, the contribution of broader microbial communities remains less understood. Here, we integrate metatranscriptomic sequencing with genome-scale metabolic modeling to characterize active metabolic functions of patient-specific urinary microbiomes during acute UTI.
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