Organ weights in healthy and apparently healthy Danish infants

Kock, Kirsten; Lammert, O; Thobo-Carlsen, B.; Garby, Lars

doi:10.1002/(sici)1520-6300(1997)9:1<35::aid-ajhb6>3.0.co;2-p

Cited by 5 publications

(1 citation statement)

References 4 publications

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“…The validity of OM assessments is difficult to prove in vivo as we do not have a gold‐standard or algorithms based on appropriate autopsy reference data (see refs 21–25). Based on a Scandinavian autopsy database, a number of algorithms have been proposed for estimations of brain, heart, liver and kidney mass [22].…”

Section: Computer Tomography (Ct) and Magnetic Resonance Imaging (Mrimentioning

confidence: 99%

Metabolically active components of fat‐free mass and resting energy expenditure in humans: recent lessons from imaging technologies

Bosy‐Westphal²,

et al. 2002

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Imaging technologies, i.e. magnetic resonance imaging (MRI), computer tomography (CT) and dual-energy X-ray absorptiometry (DEXA), are precise and accurate techniques used to study lean body mass and adipose tissue distribution. CT and MRI can also be used to assess metabolically active components of fat-free mass (FFM). (Throughout this article, metabolic activity is defined with respect to oxidative metabolism.) To date a total of 116 in vivo measurements of organ masses (OM), in combination with the measurement of resting energy expenditure (REE), have been reported. These data suggest that MRI- or CT-derived OM explains part (approximately 5-10%) of the interindividual variance in REE. The data also suggest that REE can be reconstructed from detailed body composition analysis. Calculating REE from the sum of individual OM multiplied by a constant organ tissue-respiration rate showed a high correlation between calculated and measured REE, with only small and non-significant differences of 83-96 kJ d-1. In addition to CT- and MRI-derived OM, data are available of 244 obese and non-obese subjects regarding the association between regional components of lean body mass (LBM, assessed by DEXA) and REE. These results suggest that measurement of LBM distribution also provides the opportunity to adjust for the non-linearity of REE on body mass. Assessment of metabolically active components of FFM or LBM may also add to our understanding of malnutrition-, obesity- and disease states-related variance in REE. There is need for (1) standardization of imaging technology in body composition research; (2) reference data on detailed body composition, also including more recent autopsy data; (3) reducing the number of assumptions in model-based predictions; and (4) a combination of imaging technologies with in vivo measurements of individual OM respiration.

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Section: Computer Tomography (Ct) and Magnetic Resonance Imaging (Mrimentioning

confidence: 99%

Metabolically active components of fat‐free mass and resting energy expenditure in humans: recent lessons from imaging technologies

Bosy‐Westphal²,

et al. 2002

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Increased thymus weight in sudden infant death syndrome compared to controls: The role of sub‐clinical infections

Goldwater

Kelmanson

Little

2020

American J Hum Biol

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Objective: The goal of the present investigation is to analyze thymus, brain, heart, liver, and kidney weights in SIDS victims compared to controls. Background: Epidemiologic risk factors for SIDS (eg, male gender, genetic, obstetric, environmental, smoke exposure, nonbreastfeeding, etc.) are consistent with an infectious process underlying many of these deaths. Methods: Data from autopsy reports on 585 SIDS victims and comparison deaths (n = 294 control, n = 291 SIDS) were analyzed. Cases were obtained from Australia (n = 184 controls, n = 98 SIDS) and Russia (n = 122 controls, n = 181 SIDS). Log 10 transform of thymus and other organ weights was computed because variables were skewed. Multivariate analysis of variance (MANOVA) of standardized log values were age-adjusted by multivariate analysis of covariance (MANCOVA). The standardized log 10 thymus residual adjusted for age, brain and liver weights was computed for the final analysis.Results: After controlling for age by MANCOVA, thymus, body, brain and liver weights were significantly higher among SIDS compared to non-SIDS victims. The largest difference as between covariate-adjusted log 10 non-SIDS thymus weight differed (mean = 1.423, 95% CI: 1.393-1.452) and log 10 non-SIDS thymus weight (mean = 1.269, 95% CI: 1.243-1.294) were significantly different (P < .0001). Heart weight was significantly lower in SIDS victims. Discussion: When adjusted for confounders (age, body, and organ weights), SIDS victims have a significantly heavier thymus and brain compared to non-SIDS controls who died of trauma. This finding supports previously published studies that link infection to SIDS deaths.

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Overgrowth of a Mouse Model of the Simpson–Golabi–Behmel Syndrome Is Independent of IGF Signaling

Chiao

Fisher

Crisponi

et al. 2002

Developmental Biology

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The type 1 Simpson-Golabi-Behmel overgrowth syndrome (SGBS1) is caused by loss-of-function mutations of the X-linked GPC3 gene encoding glypican-3, a cell-surface heparan sulfate proteoglycan that apparently plays a negative role in growth control by an unknown mechanism. Mice carrying a Gpc3 gene knockout exhibited several phenotypic features that resemble clinical hallmarks of SGBS1, including somatic overgrowth, renal dysplasia, accessory spleens, polydactyly, and placentomegaly. In Gpc3/DeltaH19 double mutants (lacking GPC3 and also carrying a deletion around the H19 gene region that causes bialellic expression of the closely linked Igf2 gene by imprint relaxation), the Gpc3-null phenotype was exacerbated, while additional SGBS1 features (omphalocele and skeletal defects) were manifested. However, results from a detailed comparative analysis of growth patterns in double mutants lacking GPC3 and also IGF2, IGF1, or the type 1 IGF receptor (IGF1R) provided conclusive genetic evidence inconsistent with the hypothesis that GPC3 acts as a growth suppressor by sequestering or downregulating an IGF ligand. Nevertheless, our data are compatible with a model positing that there is downstream convergence of the independent signaling pathways in which either IGFs or (indirectly) GPC3 participate.

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Organ weights in healthy and apparently healthy Danish infants

Cited by 5 publications

References 4 publications

Metabolically active components of fat‐free mass and resting energy expenditure in humans: recent lessons from imaging technologies

Metabolically active components of fat‐free mass and resting energy expenditure in humans: recent lessons from imaging technologies

Increased thymus weight in sudden infant death syndrome compared to controls: The role of sub‐clinical infections

Overgrowth of a Mouse Model of the Simpson–Golabi–Behmel Syndrome Is Independent of IGF Signaling

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