Oxandrolone in constitutional delay of growth: Analisys of the growth patterns up to final stature

1993 ◽  
Vol 16 (2) ◽  
pp. 133-137 ◽  
Author(s):  
Francesca Bassi ◽  
A. S. Neri ◽  
R. G. Gheri ◽  
D. Cheli ◽  
M. Serio
Author(s):  
Gerald Fine ◽  
Azorides R. Morales

For years the separation of carcinoma and sarcoma and the subclassification of sarcomas has been based on the appearance of the tumor cells and their microscopic growth pattern and information derived from certain histochemical and special stains. Although this method of study has produced good agreement among pathologists in the separation of carcinoma from sarcoma, it has given less uniform results in the subclassification of sarcomas. There remain examples of neoplasms of different histogenesis, the classification of which is questionable because of similar cytologic and growth patterns at the light microscopic level; i.e. amelanotic melanoma versus carcinoma and occasionally sarcoma, sarcomas with an epithelial pattern of growth simulating carcinoma, histologically similar mesenchymal tumors of different histogenesis (histiocytoma versus rhabdomyosarcoma, lytic osteogenic sarcoma versus rhabdomyosarcoma), and myxomatous mesenchymal tumors of diverse histogenesis (myxoid rhabdo and liposarcomas, cardiac myxoma, myxoid neurofibroma, etc.)


1993 ◽  
Vol 89 (1) ◽  
pp. 33-39 ◽  
Author(s):  
Jeff S. Kuehny ◽  
Mary C. Halbrooks

Larval growth and settlement rates are important larval behaviors for larval protections. The variability of larval growthsettlement rates and physical conditions for 2006-2012 and in the future with potential climate changes was studied using the coupling ROMS-IMBs, and new temperature and current indexes. Forty-four experimental cases were conducted for larval growth patterns and release mechanisms, showing the spatial, seasonal, annual, and climatic variations of larval growthsettlement rates and physical conditions, demonstrating that the slight different larval temperature-adaption and larval release strategies made difference in larval growth-settlement rates, and displaying that larval growth and settlement rates highly depended upon physical conditions and were vulnerable to climate changes.


2013 ◽  
Author(s):  
Raffaella Radin ◽  
Mirella Moro ◽  
Massimo Scacchi ◽  
Francesco Cavagnini ◽  
Leila Danesi ◽  
...  

2011 ◽  
Vol 32 (5) ◽  
pp. 129-144
Author(s):  
Karl Schmetzer ◽  
Heinz-Jürgen Bernhardt ◽  
Thomas Hainschwang
Keyword(s):  

2020 ◽  
Vol 26 (5) ◽  
pp. 517-524
Author(s):  
Noah S. Cutler ◽  
Sudharsan Srinivasan ◽  
Bryan L. Aaron ◽  
Sharath Kumar Anand ◽  
Michael S. Kang ◽  
...  

OBJECTIVENormal percentile growth charts for head circumference, length, and weight are well-established tools for clinicians to detect abnormal growth patterns. Currently, no standard exists for evaluating normal size or growth of cerebral ventricular volume. The current standard practice relies on clinical experience for a subjective assessment of cerebral ventricular size to determine whether a patient is outside the normal volume range. An improved definition of normal ventricular volumes would facilitate a more data-driven diagnostic process. The authors sought to develop a growth curve of cerebral ventricular volumes using a large number of normal pediatric brain MR images.METHODSThe authors performed a retrospective analysis of patients aged 0 to 18 years, who were evaluated at their institution between 2009 and 2016 with brain MRI performed for headaches, convulsions, or head injury. Patients were excluded for diagnoses of hydrocephalus, congenital brain malformations, intracranial hemorrhage, meningitis, or intracranial mass lesions established at any time during a 3- to 10-year follow-up. The volume of the cerebral ventricles for each T2-weighted MRI sequence was calculated with a custom semiautomated segmentation program written in MATLAB. Normal percentile curves were calculated using the lambda-mu-sigma smoothing method.RESULTSVentricular volume was calculated for 687 normal brain MR images obtained in 617 different patients. A chart with standardized growth curves was developed from this set of normal ventricular volumes representing the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles. The charted data were binned by age at scan date by 3-month intervals for ages 0–1 year, 6-month intervals for ages 1–3 years, and 12-month intervals for ages 3–18 years. Additional percentile values were calculated for boys only and girls only.CONCLUSIONSThe authors developed centile estimation growth charts of normal 3D ventricular volumes measured on brain MRI for pediatric patients. These charts may serve as a quantitative clinical reference to help discern normal variance from pathologic ventriculomegaly.


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