Prenatal diagnosis of binders phenotype: a cross road to decision making

Binder’s syndrome is an uncommon congenital condition which develops in the first trimester of pregnancy and has characteristic effects on the facial features. Those effects are: arhinoid face, intermaxillary hypoplasia (associated with malocclusion), abnormal position of the nasal bones, nasal mucosa atrophy, anterior nasal spine agenesis and (in most cases) a lack of frontal sinuses. Other deformities, as well as mental retardation, are also possible. Due to the rarity of the disease, there are no treatment trials for these patients. Treatments reported in the medical literature are part of single case reports or small case series of patients. Here is a case report of a 23-year-old who presented to OPD at 26 weeks with features of binders’ phenotype. This woman delivered an infant of 2.7 kg without other abnormalities and no respiratory distress postnatally. Sonographic evaluation during pregnancy depicts proper differential diagnosis and therapeutic strategy. Multidisciplinary approach is mandatory in order to establish meticulous treatment. Further studies must be conducted, achieving this ultimate scope. Even so, the parents should be counselled that Binder syndrome is a tentative diagnosis prenatally, and that not all genetic syndromes can be prenatally excluded

M1/M2 Macrophage Polarity in Normal and Complicated Pregnancy

Tissue macrophages play an important role in all stages of pregnancy, including uterine stromal remodeling (decidualization) before embryo implantation, parturition, and postpartum uterine involution. The activation state and function of utero-placental macrophages are largely dependent on the local tissue microenvironment. Thus, macrophages are involved in a variety of activities such as regulation of immune cell activities, placental cell invasion, angiogenesis, and tissue remodeling. Disruption of the uterine microenvironment, particularly during the early stages of pregnancy (decidualization, implantation, and placentation) can have profound effects on macrophage activity and subsequently impact pregnancy outcome. In this review, we will provide an overview of the temporal and spatial regulation of utero-placental macrophage activation during normal pregnancy in humans and rodents with a focus on more recent findings. We will also discuss the role of M1/M2 dysregulation within the intrauterine environment during adverse pregnancy outcomes

A Systematic Search for High Surface Brightness Giant Arcs in a Sloan Digital Sky Survey Cluster Sample

We present the results of a search for gravitationally-lensed giant arcs conducted on a sample of 825 SDSS galaxy clusters. Both a visual inspection of the images and an automated search were performed and no arcs were found. This result is used to set an upper limit on the arc probability per cluster. We present selection functions for our survey, in the form of arc detection efficiency curves plotted as functions of arc parameters, both for the visual inspection and the automated search. The selection function is such that we are sensitive only to long, high surface brightness arcs with g-band surface brightness mu_g 10. Our upper limits on the arc probability are compatible with previous arc searches. Lastly, we report on a serendipitous discovery of a giant arc in the SDSS data, known inside the SDSS Collaboration as Hall's arc.Comment: 34 pages,8 Fig. Accepted ApJ:Jan-200

Epidemiological and pathological screening of suspected cases of contagious bovine pleuropneumonia in Yola Modern Abattoir, Adamawa State Nigeria

Contagious bovine pleuropneumonia is an important infectious disease of cattle caused by Mycoplasma mycoides subsp. mycoides and a major constraint to cattle production in sub-Saharan Africa. This study was aimed to identify pathological and histopathological lesions identified in cattle tentatively diagnosed with CBPP at Yola Modern Abattoir, Adamawa State. A total of 9,750 cattle were examined at post-mortem for a period of six months, 110 (1.13%) had lesions suggestive of CBPP out of which seventeen (17) were randomly selected and processed for histopathology based on standard laboratory protocols. Based on sex, CBPP lesion was observed more in female 63 (1.06%) than in the male 47 (1.24%). Whereas, CBPP lesions was observed highest in White Fulani breed 68 (1.14%) followed by Cross breeds 23 (91.16%) and Sokoto Gudali 19 (1.74%) and lowest in Red Bororo 10 (1.36%). There was insignificant statistical association (P>0.05) between CBPP lesions and sex and breed of cattle sampled. Age distribution of CBPP lesion was observed higher in cattle between ages of 4-7 years 79 (1.16%), followed by cattle of 1-3 years 28 (1.15%) and least in cattle less than 1 year 3 (0.60%) with significant statistical difference (P<0.05) between the age groups. Histopathology lesions observed include severe congestion of pulmonary blood vessel in all the lung tissues and fibrin exudation into inter-alveolar spaces with almost all the alveoli collapsed. The bronchiolar epithelium was observed to be thickened, hyperplastic and folded, with a considerable quantity of edematous fluid and numerous inflammatory cells seen in the lumen. In conclusion, this study had demonstrated the presence of CBPP lesions in cattle in the study area. Therefore, serological screening of all cattle, stamping out policies and aggressive annual vaccination campaigns are thus recommended in the study area

Vessel segmentation for automatic registration of untracked laparoscopic ultrasound to CT of the liver

PURPOSE: Registration of Laparoscopic Ultrasound (LUS) to a pre-operative scan such as Computed Tomography (CT) using blood vessel information has been proposed as a method to enable image-guidance for laparoscopic liver resection. Currently, there are solutions for this problem that can potentially enable clinical translation by bypassing the need for a manual initialisation and tracking information. However, no reliable framework for the segmentation of vessels in 2D untracked LUS images has been presented. METHODS: We propose the use of 2D UNet for the segmentation of liver vessels in 2D LUS images. We integrate these results in a previously developed registration method, and show the feasibility of a fully automatic initialisation to the LUS to CT registration problem without a tracking device. RESULTS: We validate our segmentation using LUS data from 6 patients. We test multiple models by placing patient datasets into different combinations of training, testing and hold-out, and obtain mean Dice scores ranging from 0.543 to 0.706. Using these segmentations, we obtain registration accuracies between 6.3 and 16.6 mm in 50% of cases. CONCLUSIONS: We demonstrate the first instance of deep learning (DL) for the segmentation of liver vessels in LUS. Our results show the feasibility of UNet in detecting multiple vessel instances in 2D LUS images, and potentially automating a LUS to CT registration pipeline