Background: Within the able majority of ELBW survivors, there is a lack of identified predictors of which children will require extra support despite having escaped significant disability.
Aims: Investigate the predictive validity of early motor scores, compared to that of perinatal descriptors or early growth, on long-term motor impairment in non-disabled ELBW (<1000g) children.
Study Design: Prospective longitudinal study.
Outcome Measures: 48 non-disabled ELBW children (27 male) completed the Neurosensory Motor Developmental Assessment (NSMDA) at 8 months, 2 years and 4 years post term and The Motor Assessment Battery for Children (MABC) at 11-13 years of age. Other possible predictors of long-term outcomes (gestational age, birthweight, multiple birth, head circumference measures and gender) were retrieved from the records.
Results: Early motor assessment (NSMDA score) independently predicted the MABC total score at 11-13 years of age with a positive predictive value of 87% by 4 years post term. There was increased risk of long-term motor impairment associated with male gender but the degree of prematurity, multiple birth status or early growth measures did not predict motor outcome. Postural control and sensory motor scores at 4 years post term, rather than neurological score, were associated with long-term motor outcomes for the ELBW children at 11-13 years of age.
Conclusions: Early motor scores are valid markers of long-term motor outcomes for "apparently normal" ELBW children. Early postural competence and sensory motor function are discriminating in regards to long-term motor function in neurologically normal ELBW children.
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http://dx.doi.org/10.1016/j.earlhumdev.2012.01.010 | DOI Listing |
Orthop Surg
January 2025
Department of Orthopedics, Tianjin Medical University General Hospital, International Science and Technology Cooperation Base of Spinal Cord Injury, Tianjin Key Laboratory of Spine and Spinal Cord, Tianjin, China.
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January 2025
Department of Molecular and Translational Oncology, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland.
Gonadotroph neuroendocrine pituitary tumors are among the most common intracranial neoplasms. A notable proportion of these tumors is characterized by invasive growth which hampers the treatment results and worsens prognoses of patients. Increased hsa-miR-184 expression was observed in invasive as compared to non-invasive gonadotroph tumors.
View Article and Find Full Text PDFQ J Exp Psychol (Hove)
January 2025
Faculdade de Letras, Universidade Federal de Minas Gerais.
The link between the cognitive effort of word processing and the eye movement patterns elicited by that word is well established in psycholinguistic research using eye tracking. Yet less evidence or consensus exists regarding whether the same link exists between complexity linguistic complexity measures of a sentence or passage, and eye movements registered at the sentence or passage level. This paper focuses on "global" measures of syntactic and lexical complexity, i.
View Article and Find Full Text PDFJ Cosmet Dermatol
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State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Background: Scalp itch without evident cause is an uncomfortable symptom that annoys many people in life but lacks adequate attention in academic.
Aims: To investigate the relationship between scalp itching and microorganisms, and identify the key microbes and predicted functions associated with scalp itching, furtherly to provide useful targets for scalp itch solution.
Methods: We performed microbial comparison between 44 normal subjects and 89 subjects having scalp itching problem with un-identified origin based on 16S rRNA gene sequencing and ddPCR (digital droplet PCR), and identified itch relevant microbes and predicted functions.
Bioinform Adv
November 2024
Institute of Biochemistry and Molecular Medicine, University of Bern, Bern 3012, Switzerland.
Summary: Protein structure prediction aims to infer a protein's three-dimensional (3D) structure from its amino acid sequence. Protein structure is pivotal for elucidating protein functions, interactions, and driving biotechnological innovation. The deep learning model AlphaFold2, has revolutionized this field by leveraging phylogenetic information from multiple sequence alignments (MSAs) to achieve remarkable accuracy in protein structure prediction.
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