Giant axonal neuropathy: clinical and genetic study in six cases.

BACKGROUND: Giant axonal neuropathy (GAN) is a severe recessive disorder characterised by variable combination of progressive sensory motor neuropathy, central nervous system (CNS) involvement, and "frizzly" hair. The disease is caused by GAN gene mutations on chromosome 16q24.1. AIMS: To search for GAN gene mutations in Turkish patients with GAN and characterise the phenotype associated with them. METHODS: Linkage and mutation analyses were performed in six affected patients from three consanguineous families. These patients were also investigated by cranial magnetic resonance imaging (MRI) and electroencephalography (EEG). Electromyography (EMG) was performed in heterozygous carriers from family 1 and family 3. RESULTS: Linkage to 16q24.1 was confirmed by haplotype analysis. GAN mutations were identified in all families. Family 1 had the R293X mutation, previously reported in another Turkish family. Families 2 and 3, originating from close geographical areas, shared a novel mutation, 1502+1G>T, at the donor splice site of exon 9. All patients displayed a common phenotype, including peripheral neuropathy, cerebellar ataxia, and frizzly hair. Cranial MRI showed diffuse white matter abnormalities in two patients from family 1 and the patient from family 3, and minimal white matter involvement in the patient from family 2. EMG of a heterozygous R293X mutation carrier showed signs of mild axonal neuropathy, whereas a 1502+1G>T mutation carrier had normal EMG. EEG abnormalities were found in three patients. CONCLUSION: These findings highlight the association of CNS involvement, in particular white matter abnormalities, with peripheral neuropathy in GAN. The phenotypical consequences of both mutations (when homozygous) were similar.

Vasculogenesis in early human placental villi: an ultrastructural study.

In this study we examined the chorionic villi of 5 normal human placentas at 12-14 weeks of gestation ultrastructurally with regard to differentiation of the vascular components. The aim of the present report is to discuss the factors influencing vasculogenesis (in situ formation of blood vessels) at the ultrastructural level. Our observations have led us to think that the cytotrophoblast influences vasculogenesis in human chorionic villi. Mesenchymal-preendothelial cell groups were always found in very close association with the cytotrophoblast at the periphery of the villi, forming blood vessels. The cytotrophoblast probably attracts mesenchymal cells towards the margin of the villi by secreting vascular endothelial growth factor (VEGF). Once cells attach to the trophoblastic basement membrane they begin to differentiate into endothelial cells. This close structural relation between two cell types (cytotrophoblast and mesenchymal cells) may not be the only mechanism controlling vasculogenesis, but it seems to be one of the factors influencing the differentiation of mesenchymal cells into the endothelial cells of blood vessels in early human chorionic villi.

Endoglin (CD 105) expression in human lymphoid organs and placenta.

Endoglin (CD 105) is a cell surface antigen widely expressed on vascular endothelium, syncytiotrophoblast, some tissue macrophages, certain culture cells (including early leukemic B-lineage) and some endothelial cell lines. Though its relation to the transforming growth factor-beta (TGF-beta) receptor system is well documented, its function and detailed pattern of expression still remain to be clarified. We examined the differential tissue distribution of endoglin in human lymphoid organs and placenta with several anti-CD 105 monoclonal antibodies (mAbs) using an indirect immunoperoxidase technique, and performed semi-quantitative measurements using an image-analyzing system for comparison. Arterial, venous and capillary endothelia in these organs were reactive with anti-CD 105 mAbs at varying intensities. Interestingly, a distinctly stronger staining pattern was observed in the high endothelial venules (HEVs) which may indicate a special role for endoglin in lymphocyte trafficking. Syncytiotrophoblast expressed endoglin strongly on their apical cell membrane. Extravillous trophoblasts at certain locations selectively expressed endoglin on their cell membranes, suggesting a special role for this surface antigen during trophoblast differentiation.

An artificial intelligent diagnostic system on differential recognition of hematopoietic cells from microscopic images.

Despite their advantages, none of the automated white blood cell differentiated counters have replaced the conventional microscopic evaluations of blood and bone marrow slides by hematologists. We have analyzed the smears of 39 patients and 8 control subjects to develop an artificial expert system that recognizes 16 different types of nucleated hematopoietic cells during the stages of differentiation. A charge coupled television camera and a special frame grabber were used for data acquisition, and 247 nucleated cell images were transferred from a microscope to an IBM 386 computer to be processed. One hundred sixty-five and 82 of these images were used for training and testing, respectively. Our system is composed of image processing and analysis (enhancement, thresholding/smoothing, edge detection), pattern recognition (feature extraction and classification with supervised artificial neural network), and expert system development. Image processing and analysis were used to obtain 13 cellular features to be used as the input parameters (neurons) of the artificial neural network. A supervised artificial neural network (back-propagation learning algorithm) was used in the classification of 16 different cells (output neurons of the neural network), which is the second step of pattern recognition. A confusion matrix has been developed to compare the similarities and dissimilarities between the differential recognitions of the hematologist and the expert system. The discriminatory power of the procedure is statistically significant: Q = (N - n.K)2/N.(K - 1) = 28.2. The sensitivity and the specificity of the expert system were 71.4% and 90.9%, respectively.

An expert diagnostic system based on neural networks and image analysis techniques in the field of automated cytogenetics.

In this study, we introduce an expert system for intelligent chromosome recognition and classification based on artificial neural networks (ANN) and features obtained by automated image analysis techniques. A microscope equipped with a CCTV camera, integrated with an IBM-PC compatible computer environment including a frame grabber, is used for image data acquisition. Features of the chromosomes are obtained directly from the digital chromosome images. Two new algorithms for automated object detection and object skeletonizing constitute the basis of the feature extraction phase which constructs the components of the input vector to the ANN part of the system. This first version of our intelligent diagnostic system uses a trained unsupervised neural network structure and an original rule-based classification algorithm to find a karyotyped form of randomly distributed chromosomes over a complete metaphase. We investigate the effects of network parameters on the classification performance and discuss the adaptability and flexibility of the neural system in order to reach a structure giving an output including information about both structural and numerical abnormalities. Moreover, the classification performances of neural and rule-based system are compared for each class of chromosome.

An artificial intelligent diagnostic system with neural networks to determine genetical disorders and fetal health by using maternal serum markers.

OBJECTIVE: To develop an artificial intelligent diagnostic system with neural networks to determine genetical disorders and fetal health problems by using maternal serum markers ('Triple Test') and maternal age. STUDY DESIGN: A total of 112 pregnant women were referred to Fetal Medicine Unit of Hacettepe University Hospital for fetal ultrasonography and chromosome analysis with different indications. All patients underwent genetic amniocentesis or fetal blood sampling under ultrasound guidance. Gross malformations and hydrops fetalis were detected in 15 and 5 fetuses, respectively. We have found chromosomal abnormality in 7 cases. 'Triple Test' is offered to all patients and serum levels of alpha-fetoprotein, human chorionic gonadotropin and unconjugated estriol were analyzed by radioimmunoassay. In this study, we have used supervised artificial neural network structure to develop a diagnostic system. Our system's input parameters are maternal age, gestational age and 'Triple Test' results. Our system consists of two different artificial neural network modules whose decision-making logics are different. One of them is designed to search genetical disorders while the other one is for the assessment of fetal well-being. Confusion matrix is used for statistical evaluation. RESULTS: The discriminatory power of the artificial neural network to search genetical disorders and fetal well-being is found to be highly significant (z = 10.583 and z = 10.424, respectively). CONCLUSION: This system brings objectively to the evaluation of 'Triple Test' results and can be used both for the detection of genetical disorders and fetal well-being. Nevertheless, the analysis program's performance is limited to input information and knowledge and medical expert expert can not get more than he or she has donated the system.

Development of the human renal inner medullary interstitial cells.

Two cell types were identified in the inner medulla and papilla of four fetal kidneys of 16 1/7-, 17 3/7-, 21 1/7- and 25 5/7-week-old (menstrual): undifferentiated mesenchymal cells and some highly differentiated cells which contained some lipid granules, lysosomes, smooth and rough endoplasmic reticulum. The structure of these cells resembled the two cell types which were observed in the adult tissue.

The endocrinological evaluation of bilateral and unilateral oophorectomy in premenopausal women.

The sequence of changes in serum follicle stimulating hormone (FSH), luteinizing hormone (LH), prolactin (PRL), estradiol (E2), testosterone (T), and progesterone (P) levels immediately following unilateral and bilateral oophorectomy with hysterectomy and hysterectomy alone has been measured in 65 premenopausal women by radioimmunoassay (RIA). In addition, relationship of vasomotor symptoms and serum hormone levels were studied and no correlation was found. We show mathematically the change of the relationship of the pituitary and gonadal hormones after castration. We believe that castration causes change in the activity of the hypothalamo-pituitary and gonadal axis. In view of our results, we recommend leaving at least one ovary to prevent postcastration symptoms and to maintain a good physiological condition.