Application of Digital Cognitive Biomarkers for Alzheimer's Disease: Identifying Cognitive Process Changes and Impending Cognitive Decline.

BACKGROUND: Recent Alzheimer's disease (AD) trials have faced significant challenges to enroll pre-symptomatic or early stage AD subjects with biomarker positivity, minimal or no cognitive impairment, and likelihood to decline cognitively during a short trial period. Our previous study showed that digital cognitive biomarkers (DCB), generated by a hierarchical Bayesian cognitive process (HBCP) model, were able to distinguish groups of cognitively normal individuals with impending cognitive decline from those without. We generated DCBs using only baseline Auditory Verbal Learning Test's wordlist memory (WLM) item response data from the Mayo Clinic Alzheimer's Disease Patient Registry. OBJECTIVES: To replicate our previous findings, using baseline ADAS-Cog WLM item response data from the Alzheimer's Disease Neuroimaging Initiative, and compare DCBs to traditional approaches for scoring word-list memory tests. DESIGN: Classified decliner subjects (n = 61) as those who developed amnestic MCI or AD dementia within 3 years of normal baseline assessment and non-decliner (n = 442) as those who did not. MEASURES: Evaluated the relative value of DCBs compared to traditional measures, using three analytic approaches to group differences: 1) logistic regression of summary scores per ADAS-Cog WLM task; 2) Bayesian modeling of summary scores; and 3) HBCP modeling to generate DCBs from item-level responses. RESULTS: The HBCP model produced posterior distributions of group differences, of which Bayes factor assessment identified three DCBs with notable group differences: Immediate Retrieval from Durable Storage, (BFds = 11.8, strong evidence); One-Shot Learning, (BFds = 4.5, moderate evidence); and Partial Learning (BFds = 2.9, weak evidence). In contrast, logistic regression of summary scores did not significantly discriminate between groups, and the Bayes factor assessment of modeled summary scores provided moderate evidence that the groups were equivalent (BFsd = 3.4, 3.1, 2.9, and 1.4, respectively). CONCLUSIONS: This study demonstrated DCBs' ability to distinguish , at baseline, between impending cognitive decline and non-decline groups where individuals in both groups were classified as cognitively normal. This validated findings from our previous study, demonstrating DCBs' advantages over traditional approaches. This study warrants further refinement of the HBCP DCBs to predict impending cognitive decline in individuals and other factors associated with AD, such as physical biomarker load.

Novel Therapy of Hyperhomocysteinemia in Mild Cognitive Impairment, Alzheimer's Disease, and Other Dementing Disorders.

OBJECTIVES: Studies have produced conflicting results assessing hyperhomocysteinemia (HYH) treatment with B vitamins in patients with normal cognition, Alzheimer's disease and related disorders (ADRD). This study examined the effect of HYH management with L-methylfolate (LMF), methylcobalamin (MeCbl; B12), and N-acetyl-cysteine (CFLN: Cerefolin®/Cerefolin-NAC®) on cognitive decline. DESIGN: Prospective, case-control study of subjects followed longitudinally. SETTING: Outpatient clinic for cognitive disorders. PARTICIPANTS: 116 ADRD patients (34 with HYH, 82 with No-HYH) met inclusion and exclusion criteria to participate. No study participant took B vitamins. INTERVENTION: HYH patients received CFLN, and No-HYH patients did not. MEASUREMENTS: Cognitive outcome measures included MCI Screen (memory), CERAD Drawings (constructional praxis), Ishihara Number Naming (object recognition), Trails A and B (executive function), and F-A-S test (verbal fluency). Dependent or predictor measures included demographics, functional severity, CFLN and no CFLN treatment duration, ADRD diagnosis, memantine and cholinesterase inhibitor treatment. Linear mixed effects models with covariate adjustment were used to evaluate rate of change on cognitive outcomes. RESULTS: The duration of CFLN treatment, compared to an equivalent duration without CFLN treatment, significantly slowed decline in learning and memory, constructional praxis, and visual-spatial executive function (Trails B). CFLN treatment slowed cognitive decline significantly more for patients with milder baseline severity. CFLN treatment effect increased as baseline functional severity decreased. The analytical model showed that treatment duration must exceed some minimum period of at least one year to slow the rate of cognitive decline. CONCLUSION: After covariate adjustment, HYH+CFLN significantly slowed cognitive decline compared to No-HYH+No-CFLN. Longer CFLN treatment duration, milder baseline severity, and magnitude of homocysteine reduction from baseline were all significant predictors. There are a number of factors that could account for disagreement with other clinical trials of B vitamin treatment of HYH. Moreover, CFLN is chemically distinct from commonly used B vitamins as both LMF and MeCbl are the fully reduced and bioactive functional forms; CLFN also contains the glutathione precursor, N-acetyl-cysteine. The findings of other B vitamin trials of HYH can, therefore, only partly account for treatment effects of CFLN. These findings warrant further evaluation with a randomized, placebo-controlled trial.

Decreased levels of C1q in cerebrospinal fluid of living Alzheimer patients correlate with disease state.

Recent reports that complement proteins comprising the classical pathway are associated with senile plaques suggest that activation of the classical complement cascade in Alzheimer's disease tissue results in bystander cell lysis and may contribute to AD neuropathology. Analysis of cerebrospinal fluid may prove to be a useful means of detecting changes in immunological activity in the brain. We use an enzyme-linked immunosorbent assay to measure levels of C1q, a subunit of the classical complement cascade, in the CSF of patients clinically diagnosed with possible or probable AD. Significantly lower levels of C1q were detected in the CSF of the Alzheimer group as compared to control CSF [AD: mu = 268 ng/ml, SD = 84; non-AD: mu = 340 ng/ml, SD = 76; F(1, 44) = 5.84, p = 0.02]. Diminished performance on global measures of mental status such as the Mini-Mental State Exam (R = 0.45; p = 0.0072) and Blessed's Information, Memory, and Concentration test (R = 0.42; p = 0.0138) showed high correlations with decreased C1q levels. More specific measures of cognitive function, such as word recall (R = 0.42; p = 0.012), word recognition (R = 0.52; p = 0.0017) and delayed recall (R = 0.45; p = 0.0062) memory tasks also correlated strongly with decreased C1q levels.

Cortical CSF volume fluctuations by MRI in brain aging, dementia and hydrocephalus.

Dynamic MR imaging has revealed dramatic fluctuations in the appearance of CSF in the cortical sulci and cortical subarachnoid spaces in aging individuals and patients with hydrocephalus, dementia and Down syndrome in contrast to young healthy volunteers. The changes have been interpreted as volume fluctuations that represent undamped CSF hydrodynamics and have implications with respect to the origin of CSF in the cortical regions and with respect to the similarity between aging and dementia and edematous states of the brain.

Ishihara test performance and dementia.

Ishihara trail-tracing (TT) and number-naming (NN) tests were administered to a clinical sample of 378 demented patients. Error counts on TT and NN tests were best fit by a negative binomial (overdispersed Poisson) distribution. TT, NN, and combined (TT + NN) error counts were regressed on patient characteristics (sex, age, and education), severity of cognitive impairment (Mini-Mental State Exam: MMSE), dementia stage (Clinical Dementia Rating: CDR), etiology, onset age, and symptom duration in a negative binomial generalized linear model. Patient characteristics, onset age, and symptom duration had no significant effects on any error count. The effects of MMSE, CDR, and etiology, on the other hand, were highly significant and appear to help discriminate vascular dementia from Alzheimer's disease. MMSE (which taps cognitive skills) correlated with both TT and NN errors. CDR (which taps both cognitive and functional skills) correlated only with TT errors and dementia etiology correlated only with NN errors. These distinct correlational patterns reflect differences between the TT and NN tasks (i.e., trail-tracing vs. number-naming) related to specific brain loci and associated functions. This aspect of the phenomenon suggests that Ishihara tests have useful clinical applications in dementia.

Cortical atrophy in Alzheimer's disease unmasks electrically silent sulci and lowers EEG dipolarity.

Alzheimer's disease (AD) patients show lower dipolarity (goodness-of-fit) for dipole localizations of alpha or other dominant electroencephalography (EEG) frequency components in the occipital cortex. In the present study, we performed computer simulations to discover which of distributions of dipole activity lower dipolarity in a manner similar to that seen in severe AD. Dipolarity was estimated from simulations of various electric dipole generator configurations within the occipital cortex under conditions of widened cortical sulci (a severely demented AD case) or no sulcal widening (a normal subject). The cortical and scalp surfaces, derived from the subjects' MRI's, were assumed to be uniformly electrically conducting. Randomly placed, nonoverlapping lesions ranging from 1 to 4 mm2 per lesion were used in both the normal and AD models to simulate the electrical effect of neuropathological AD lesions. In both models, dipolarity decreased as total lesion size increased. However, the AD model showed lower dipolarity than the normal model for both individual lesion sizes and for larger total lesion sizes. The larger decline in dipolarity in the AD model appears to be due to sulcal widening which unmasks the effect of lesions buried within sulci. These simulations identify a possible mechanism explaining why sulcally-located neuropathological changes plus progressive cortical atrophy in AD brains (and presumably other cortical disorders producing atrophy) alter EEG patterns and dipolarity differently from normal cortex damaged by similar lesions.

Approximating dipoles from human EEG activity: the effect of dipole source configuration on dipolarity using single dipole models.

Dipolarity is the goodness-of-fit of the observed potential distribution with one calculated using specific assumptions about the source of the electrical potential distribution. We used computer simulations to examine the effect of different distributions of sources on their resulting dipolarity values. Electric dipoles were placed in a head-shaped model with uniform conductivity using four different dipole configurations (randomly oriented dipoles, a uniform dipole disk layer, a dipole disk layer with uniformly distributed holes, or one with randomly oriented dipoles). The best-fitting single dipole for each configuration was calculated and the dipolarity was computed as the mean squared error of the electrical potential distributions generated by the actual dipole configuration and by the best-fitting single dipole. The simulations show that: 1) a smooth dipole layer with or without holes gives dipolarities above 99.5% even when extended over areas as large as 1256 mm2; 2) randomly oriented dipoles under a smooth dipole layer also give dipolarities above 99.5%; and 3) randomly oriented and distributed dipoles, even if contained in a small portion of the total area, give dipolarities below 93.0%. These simulations show that inhomogeneity (holes) within a dipole disk layer per se do not lower dipolarity; rather, it is the random orientation and distribution of these dipoles which lowers dipolarity. Furthermore, dipolarity is not lowered by such randomly oriented and distributed dipoles when they are beneath a dipole disk layer.

Cardiomyopathy in childhood and adult life, with emphasis on hypertrophic cardiomyopathy.

Over 60 entries in the genetic catalog have cardiomyopathy features--32 autosomal dominant, 35 autosomal recessive and X-linked. Over 40 present in, or can have survival into, adult life. Major clinicopathologic categories of these cardiomyopathic disorders included: sudden death (13 entities); cardiac conduction disturbance important feature; associated myopathy or motor dysfunction; storage diseases with cardiac involvement; cardiac amyloidoses; and, other categories. Genes, abnormality of which can cause hypertrophic cardiomyopathy (HCM), have been identified on chromosomes 1, 14 and 15, the locus on chromosome 14 involving the B-myosin heavy chain gene, but at least one unidentified locus is known to exist and there is a suggestive locus on chromosome 16, so that HCM is not a single disease but a group of disorders with clinicopatholopic similarities. To investigate these aspects of HCM in some detail, sixty-six patients with "sharply demarcated" differential myocardial fiber bundle hypertrophy (DMBH), considered to be of significant degree, from a pediatric autopsy data base of approximately 8,000 cases, were reviewed. Twenty-three of the patients died suddenly, without antecedent significant cardiac dysfunction, seven had clinical congestive heart failure of varying duration, three were stillborn, six showed evidence of aspiration of amniotic sac content (three had history of fetal distress), five had ischemic bowel disease, three (two with clinical cerebral palsy and one with Ondine's curse syndrome) had cerebral atrophy and sclerosis and one had extensive more acute encephalomalacia, and a variety of other major "causes of death" were present. Whether all infants and children with DMBH meeting the criteria used, who do not have congenital heart disease, have dominant hypertrophic cardiomyopathy (HCM) cannot be established by studies of this type, but the "concentration" of a gene or genes for HCM in pediatric autopsy series because the strong effect of HCM on life expectancy is relevant to this possibility. The data raise the question that stillbirth, fetal distress with aspiration of amniotic sac content, ischemic bowel disease and cerebral atrophy and sclerosis may be hitherto underappreciated features of HCM in childhood, and that patients with HCM may be peculiarly liable to die with certain types of septic shock, such as acute meningococcemia. In the material of this study, sudden death was statistically more frequent in females than in males in childhood (p < .029).

Two-Stage Machine Learning model for guideline development.

We present a Two-Stage Machine Learning (ML) model as a data mining method to develop practice guidelines and apply it to the problem of dementia staging. Dementia staging in clinical settings is at present complex and highly subjective because of the ambiguities and the complicated nature of existing guidelines. Our model abstracts the two-stage process used by physicians to arrive at the global Clinical Dementia Rating Scale (CDRS) score. The model incorporates learning intermediate concepts (CDRS category scores) in the first stage that then become the feature space for the second stage (global CDRS score). The sample consisted of 678 patients evaluated in the Alzheimer's Disease Research Center at the University of California, Irvine. The demographic variables, functional and cognitive test results used by physicians for the task of dementia severity staging were used as input to the machine learning algorithms. Decision tree learners and rule inducers (C4.5, Cart, C4.5 rules) were selected for our study as they give expressive models, and Naive Bayes was used as a baseline algorithm for comparison purposes. We first learned the six CDRS category scores (memory, orientation, judgement and problem solving, personal care, home and hobbies, and community affairs). These learned CDRS category scores were then used to learn the global CDRS scores. The Two-Stage ML model classified as well as or better than the published inter-rater agreements for both the category and global CDRS scoring by dementia experts. Furthermore, for the most critical distinction, normal versus very mildly impaired, the Two-Stage ML model was 28.1 and 6.6% more accurate than published performances by domain experts. Our study of the CDRS examined one of the largest, most diverse samples in the literature, suggesting that our findings are robust. The Two-Stage ML model also identified a CDRS category, Judgment and Problem Solving, which has low classification accuracy similar to published reports. Since this CDRS category appears to be mainly responsible for misclassification of the global CDRS score when it occurs, further attribute and algorithm research on the Judgment and Problem Solving CDRS score could improve its accuracy as well as that of the global CDRS score.

A multinomial modeling analysis of memory deficits in Alzheimer's disease and vascular dementia.

Data from the immediate recall task of the Consortium to Establish a Registry for Alzheimer's Disease neuropsychological test battery were disaggregated into nine subject groups and analyzed with traditional statistics as well as with a general processing tree (GPT) model of free recall. The groups represented four levels of severity of Alzheimer's and vascular dementia, as well as a ninth group of healthy elderly controls. It was demonstrated that the patterns of success and failure of recall to individual items across successive trials contained much more information than the marginal trial-to-trial performance scores traditionally used in scoring the test. The GPT model analyzed recall performance in terms of three levels of item storage: unstored, intermediate, and long-term. Associated with the intermediate and long-term storage levels were respective retrieval parameters. Statistical methods enable one to estimate the parameters for each group, and the analyses revealed group differences in long-term storage that were not evident in a statistical analysis of the marginal trial-to-trial performance scores.

Acceptance of rules generated by machine learning among medical experts.

OBJECTIVES: The aim was to evaluate the potential for monotonicity constraints to bias machine learning systems to learn rules that were both accurate and meaningful. METHODS: Two data sets, taken from problems as diverse as screening for dementia and assessing the risk of mental retardation, were collected and a rule learning system, with and without monotonicity constraints, was run on each. The rules were shown to experts, who were asked how willing they would be to use such rules in practice. The accuracy of the rules was also evaluated. RESULTS: Rules learned with monotonicity constraints were at least as accurate as rules learned without such constraints. Experts were, on average, more willing to use the rules learned with the monotonicity constraints. CONCLUSIONS: The analysis of medical databases has the potential of improving patient outcomes and/or lowering the cost of health care delivery. Various techniques, from statistics, pattern recognition, machine learning, and neural networks, have been proposed to "mine" this data by uncovering patterns that may be used to guide decision making. This study suggests cognitive factors make learned models coherent and, therefore, credible to experts. One factor that influences the acceptance of learned models is consistency with existing medical knowledge.

Simple models for estimating dementia severity using machine learning.

Estimating dementia severity using the Clinical Dementia Rating (CDR) Scale is a two-stage process that currently is costly and impractical in community settings, and at best has an interrater reliability of 80%. Because staging of dementia severity is economically and clinically important, we used Machine Learning (ML) algorithms with an Electronic Medical Record (EMR) to identify simpler models for estimating total CDR scores. Compared to a gold standard, which required 34 attributes to derive total CDR scores, ML algorithms identified models with as few as seven attributes. The classification accuracy varied with the algorithm used with naïve Bayes giving the highest. (76%) The mildly demented severity class was the only one with significantly reduced accuracy (59%). If one groups the severity classes into normal, very mild-to-mildly demented, and moderate-to-severely demented, then classification accuracies are clinically acceptable (85%). These simple models can be used in community settings where it is currently not possible to estimate dementia severity due to time and cost constraints.

Splenic growth rates in cirrhotic and other splenomegalic diseases of childhood.

The weights of the spleens of series of patients with various disorders of children dating from birth or early infancy and causing splenomegaly, with or without cirrhosis of the liver, were analyzed. The linear regression equation for spleen weight versus age in months for each disease was derived, and the rate constants from these equations were adjusted for the age range of the patients in each group. The original data of Coppoletta and Wolbach were used for normal values. The rates of splenic growth of appropriate entities for which the regression equation could be computed fell into three groups, with adjusted rate constants (growth of spleen in grams per month) of 6.53-6.95 (biliary atresia, thalassemia, and cirrhosis following neonatal hepatitis), 2.30-2.62 (cirrhosis of alpha-1-antitrypsin deficiency, infantile polycystic disease, and spherocytosis), and 1.06-1.11 (cystic fibrosis and idiopathic thrombocytopenic purpura). These classes of splenic growth rates are approximately 10, 3.7, and 1.6 times the normal growth rate (0.67 g/mo). Rate constants could not be computed for the categories cirrhosis following viral hepatitis and hemolytic anemia other than spherocytosis and sickle cell anemia, and the numbers of patients with splenic vein obstruction, cirrhosis with the cholestatic syndrome of parenteral alimentation, hypoplastic anemia with hemosiderosis, tyrosinemia, Byler's disease, congenital hepatic fibrosis, and Wilson's disease were too few for analysis. The significance of the finding of classes or "quantum groups" of splenic growth rates in disorders of children, dating from birth or early infancy and causing splenomegaly, is uncertain. Comparable data on adequate series of patients with other appropriate disorders will be necessary.

Reduced inferior olivary neuron number in early Down syndrome.

Counts of total neuron number per section and of neurons per microscopic field of inferior olivary principal nuclei were made on sections from 10 patients with Down syndrome (DS) aged 0.36 to 28 months and seven control (C) patients aged 1 to 29 months. After stereologic and appropriate shrinkage corrections of the count data, the ratios of values for DS/C were calculated. For mean principal olivary nucleus neuron number, DS/C = 0.64; for mean number of neurons per field, DS/C = 0.84; for mean volume of olivary neuronal band per section, DS/C = 0.79; and for mean volume of neuronal band per neuron, DS/C = 1.27. The data are in accord with other data suggesting that (1) numbers of cells in various cell populations, including various areas of the cerebrum, in DS approximate two-thirds normal (DS/C approximately 0.67); (2) for the volumes of such cell populations, DS/C = 0.82 normal; and (3) for volumes of individual cells, DS/C = 1.22 normal. The data of the present study suggest that the inferior olivary nuclei in DS are affected in the same way and to a similar degree as other brain areas, with the age distribution and histologic features of the specimens studied suggesting that the reduced olivary principal nucleus number in early Down syndrome results from reduced initial neuron production rather than postnatal neuron loss.

Low-dose propranolol reduces aggression and agitation resembling that associated with orbitofrontal dysfunction in elderly demented patients.

Although several reports suggest that intermediate to high doses of propranolol (80-160 and 200-600 mg/day) can effectively treat aggressive behavior in dementia, significant side effects can occur at these doses. To minimize these side effects, we treated and followed-up a series of 12 demented patients, whose caregivers sought medical help for their disruptive, aggressive behavior, with low-dose propranolol monotherapy (10-80 mg/day). Assessment measures obtained at baseline and during treatment by caregiver interview included ordinal ratings of aggression severity, the Cohen-Mansfield Agitation Inventory (CMAI), and the California Behavior Questionnaire (CBQ). The aggression ratings showed that low-dose propranolol effectively reduced aggression in eight of 12 patients (67%) within 2 weeks of treatment and remained effective for the duration of follow-up (1 to 14 months). Subscales of the CMAI showed responders to have significant reductions in physical and verbal aggression/agitation and in pacing/wandering. These results suggest that low-dose propranolol should be further studied for treating aggression or agitation in demented patients.

Myopathic skeletal muscle fiber abnormalities in cardiomyopathies of childhood.

Skeletal muscle fibers isolated from 50 muscle specimens from 10 children with cardiomyopathy of unknown cause are compared to those from 18 specimens from 5 patients with skeletal muscle myopathies, 45 specimens from 18 patients with congenital heart disease, and 15 specimens from 7 patients with no genetic, chromosomal, or cardiac disease. Muscle fibers from the myopathy specimens show increased nuclei/mm of fiber and increased nuclei/mm/micron of diameter (R value), as well as reduced surface area and volume of cytoplasm per nucleus, compared to control values. The values for cardiomyopathy deviate from normal in the same way as, but to a lesser degree than, those for myopathy--namely, in this material, diseases with cardiomyopathy tend also to produce mild myopathy. Since cardiac and skeletal muscle pathologic findings have not been adequately studied for the majority of the approximately 50 genetic disorders causing cardiomyopathy or otherwise affecting cardiac function described to date, the data indicate primarily that skeletal muscle biopsy will undoubtedly be more useful in cardiomyopathic disorders when the appropriate correlative studies of cardiac and skeletal muscle in such diseases have been done. Because larger biopsy specimens can be obtained, skeletal muscle merits further exploitation in biochemical research on basic mechanisms of disorders causing cardiomyopathy.

Normal organ weights of infants and children: graphs of values by age, with confidence intervals.

This study subjects the Coppoletta-Wolbach data of normal organ weights of children from birth to 12 years of age to statistical analysis, producing a set of curves that show the linear regression of organ weight versus age for each set of weights plus, for each organ, the 75%, 80%, 90%, 95%, and 99% confidence bands for single new values.

Comparisons of eccrine sweat gland anatomy in genetic, chromosomal, and other diseases, and a suggested procedure for use of sweat gland measurements in differential diagnosis.

Statistical analysis of the dimensions of microdissected eccrine sweat glands (duct length, coil volume, ratio of coil volume to duct length, and axis ratio of coil) was performed for several diseases (cystic fibrosis of the pancreas, Werdnig-Hoffmann disease, tetralogy of Fallot, chronic renal disease, and trisomies 13, 18, and 21) using both individual and grouped age-matched control patients. Duct length, coil volume, and the ratio of the two all rise with age. Eccrine gland duct length was found to be significantly large in tetralogy of Fallot and Werdnig-Hoffmann disease and small in chronic renal disease (less so in males than in females, trisomy 13 and trisomy 18). Secretory coil volume was significantly smaller than normal in trisomy 21 (Down syndrome) and in chronic renal disease, and the ratio of coil volume to duct length was low in trisomy 21 and chronic renal disease. The shape of the secretory coil (axis ratio) was possibly abnormal in trisomy 13. Gland dimensions were normal for cystic fibrosis. Using the multivariate procedure of discriminant analysis, it was found that sweat gland measures significantly contributed to the differentiation of diseases, after adjustments were made for variations in age-at-death. This suggested the possibility that criteria for distinction of clinically similar genetic, metabolic, or chromosomal diseases by study of the anatomic properties of eccrine glands obtained by skin biopsy could be developed. A procedure of analysis comparing the "percentage of normal" of gland dimensions for each disease to control values, and thereby differentiating disease categories on the basis of the "percentage of normal" values, is presented.

Syndromal associations of common origin of the carotid arteries.

The term "common origin of the carotid arteries" (COCA) has been proposed to replace the older terms "origin of the left carotid artery from the innominate stem" and "bicarotid trunk with anomalous right or left subclavian artery." These anatomic patterns are usually reported to occur in about 11% of whites and 20-25% of blacks and have been reported to have increased frequency in patients with esophageal atresia-tracheoesophageal fistula, DiGeorge anomaly, and anomalous origin of the left coronary artery from the pulmonary artery. COCA is a significant, if not invariant, feature of the great arteries in the condition usually called in the more recent literature "anomalous origin of the innominate artery," the most frequent cause of symptomatic tracheal compression by anomalous systemic arteries. Analysis of associations of COCA with various other congenital cardiovascular lesions showed, in addition, significant association with congenital polyvalvular disease, truncus arteriosus, aorticopulmonary window, trisomy 13, 18, and 21 syndromes, acrocephalosyndactyly (especially Apert syndrome), tetralogy of Fallot not associated with DiGeorge anomaly, and clinical Noonan phenotype. Pentalogy of Cantrell was associated with no increase in incidence of COCA.

Constructing the human cerebral cortex during infancy and childhood: types and numbers of cortical columns and numbers of neurons in such columns at different age-points.

This study examines JL Conel's data on neuron numbers in 35 human cortical areas for eight age points from 0 (birth) to 72 months, to analyze cortical columns, the presumed functional units of the cortex. For each cortical area at each age point, cortical surface divided by the square root of the area's neuron number gives cross-sectional areas with radii ranging from 180 microns at birth to 250 microns at 72 months. For the prefrontal cortex at birth and 48 months, these radii are approximately 2.10 and 1.19 times the longest radial basal dendrites, suggesting similar dimensions between these two measures of column radius. The logarithm of neuron number per cortical area and age point was examined in relation to the Weber-Fechner law governing the relationship between stimulus intensity and perception. A mechanism for this law consistent with the cortical model of Douglas et al. illustrates the importance of local circuit neurons. The cross-sectional areas of hexagonal columns for prefrontal cortex, using as radius, the longest radial extent of layer 5 pyramidal neuron basal dendrites, ranging from 0.013 mm2 at birth to 0.064 mm2 at 48 months, suggests that functional cortical columns increase cross-sectional area during development. These cross-sectional areas are 55-100-fold larger at birth, and 229-277-fold larger at 48 months, than those computed from somal width in prefrontal, layer 5 pyramidal neurons. Comparison of radial extent of pyramidal basal dendrites to their soma-to-soma distances shows that layer 3 pyramidal basal dendrites reach 1.5 and 4.0 other pyramidal neurons at 15 and 60 months, respectively, while layer 5, extra-large pyramidal basal dendrites reach 1.14 and 1.72 other such neurons at birth and 48 months, respectively. If such a relationship holds for other cortical areas, then the Conel data can be used to estimate basal dendrite extent, for which there currently is a paucity of data.