SummaryBackgroundPrune Belly Syndrome (PBS) is a rare entity, usually found in male neonates. It comprises complex urinary tract anomalies, bilateral undescended testis and absence of anterior abdominal wall muscles. Patients with unilateral abdominal wall deficiency, unilateral undescended testis and female neonates with abdominal wall laxity are classified as Pseudo Prune Belly syndrome (PPBS). Reports on PPBS do not highlight the radiological and imaging characteristics of this syndrome and the current literature on the role of newer imaging modalities, such as Magnetic Resonance Imaging (MRI), remains relatively sparse. We describe a new case of PPBS and emphasize the role of imaging, especially ultrasound and MRI in the process of diagnosis and briefly review the subject.Case ReportA male infant of four months of age was referred for evaluation of left-sided cryptorchidism. Clinical examination revealed laxity of the left abdominal wall. Ultrasound examination of the abdomen, pelvis and scrotum was performed together with routine laboratory tests. Ultrasound examination was followed by intravenous urography, voiding cysto-urethrography and MRI of the abdomen.On ultrasound, the left testis was located in the inguinal canal, the right kidney was slightly enlarged and the left kidney could not be localized. Ultrasound appearances suggested chronic obstruction in the urinary bladder. Intravenous urography, voiding cysto-urethrography and MRI confirmed the ultrasound diagnosis and also revealed a left dysplastic kidney with a dilated, tortuous ureter. Clinical and imaging features were consistent with pseudo prune belly syndrome (PPBS).ConclusionsWe report a new occurrence of PPBS, a rare entity. The imaging approach for a comprehensive evaluation of the renal system in PPBS, especially with MRI, is emphasized.

Objective. To determine the incidence of feed intolerance in vigorous babies with meconium stained liquor (MSL) who received prophylactic gastric lavage as compared to those who were not subjected to this procedure. Design. Randomized controlled trial. Setting. Tertiary care teaching hospital. Participants/Intervention. 330 vigorous babies delivered with MSL and satisfying the predefined inclusion criteria were randomized either to receive gastric lavage (group A, n = 165) or to not receive gastric lavage (group B, n = 153). Clinical monitoring was subsequently performed and recorded in prestructured proforma. Results. There was no significant statistical difference (P > 0.05) in incidence of feed intolerance in “lavage” and “no lavage” groups. Secondary Outcome. There was no evidence of secondary respiratory distress in either group. None of the patients in the lavage group exhibited adverse effects owing to the procedure. Conclusions. There is no role of prophylactic gastric lavage in neonates born with MSL.

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Learning from different modalities is a challenging task. In this paper, we look at the challenging problem of cross modal face verification and recognition between caricature and visual image modalities. Caricature have exaggerations of facial features of a person. Due to the significant variations in the caricatures, building vision models for recognizing and verifying data from this modality is an extremely challenging task. Visual images with significantly lesser amount of distortions can act as a bridge for the analysis of caricature modality. We introduce a publicly available large Caricature-VIsual dataset [CaVI] with images from both the modalities that captures the rich variations in the caricature of an identity. This paper presents the first cross modal architecture that handles extreme distortions of caricatures using a deep learning network that learns similar representations across the modalities. We use two convolutional networks along with transformations that are subjected to orthogonality constraints to capture the shared and modality specific representations. In contrast to prior research, our approach neither depends on manually extracted facial landmarks for learning the representations, nor on the identities of the person for performing verification. The learned shared representation achieves 91% accuracy for verifying unseen images and 75% accuracy on unseen identities. Further, recognizing the identity in the image by knowledge transfer using a combination of shared and modality specific representations, resulted in an unprecedented performance of 85% rank-1 accuracy for caricatures and 95% rank-1 accuracy for visual images. * Authors with equal contribution