A Multispecialty Approach to the Identification and Diagnosis of Nonaccidental Trauma in Children.

Child abuse is a preventable phenomenon of considerable concern resulting in significant child mortality and morbidity. We analyze various abuse lesions such as radiological (visceral and skeletal lesions and those associated with head trauma) and cutaneous (burns, bruises, bites, etc.) to enhance streamlined identification of injuries in cases of physical child abuse. For effective results, it is essential to remain mindful of all background factors, such as the caregiver setting and the prevalence of child maltreatment in the concerned community while acknowledging the possibility of natural causes (genetic diseases such as osteogenesis imperfecta and hemophilia, or acquired abnormalities) that can mimic NAT and cause confusion in diagnosis and treatment. The margin of error in cases of abuse is negligible, therefore, making its diagnosis a momentous as well as challenging clinical task. An ineffective diagnosis can have detrimental emotional consequences for the family and may even expose the child to future potentially fatal episodes of abuse. Hence, there is a need to direct special focus on the importance of accurate history taking and immediate, responsible reporting to authorities, as well as to child protective services. Therefore, considering the multifactorial approach this subject requires, this review aims to delve into prevalence statistics, various risk factors, and their effect on psychological health to offer a near-complete regulation to ensure an effective understanding of NAT on part of doctors, social workers, and other relevant authorities.

T resident helper cells promote humoral responses in the lung.

Influenza is a deadly and costly infectious disease, even during flu seasons when an effective vaccine has been developed. To improve vaccines against respiratory viruses, a better understanding of the immune response at the site of infection is crucial. After influenza infection, clonally expanded T cells take up permanent residence in the lung, poised to rapidly respond to subsequent infection. Here, we characterized the dynamics and transcriptional regulation of lung-resident CD4+ T cells during influenza infection and identified a long-lived, Bcl6-dependent population that we have termed T resident helper (TRH) cells. TRH cells arise in the lung independently of lymph node T follicular helper cells but are dependent on B cells, with which they tightly colocalize in inducible bronchus-associated lymphoid tissue (iBALT). Deletion of Bcl6 in CD4+ T cells before heterotypic challenge infection resulted in redistribution of CD4+ T cells outside of iBALT areas and impaired local antibody production. These results highlight iBALT as a homeostatic niche for TRH cells and advocate for vaccination strategies that induce TRH cells in the lung.

Segmentation of endothelial cell boundaries of rabbit aortic images using a machine learning approach.

This paper presents an automatic detection method for thin boundaries of silver-stained endothelial cells (ECs) imaged using light microscopy of endothelium mono-layers from rabbit aortas. To achieve this, a segmentation technique was developed, which relies on a rich feature space to describe the spatial neighbourhood of each pixel and employs a Support Vector Machine (SVM) as a classifier. This segmentation approach is compared, using hand-labelled data, to a number of standard segmentation/thresholding methods commonly applied in microscopy. The importance of different features is also assessed using the method of minimum Redundancy, Maximum Relevance (mRMR), and the effect of different SVM kernels is also considered. The results show that the approach suggested in this paper attains much greater accuracy than standard techniques; in our comparisons with manually labelled data, our proposed technique is able to identify boundary pixels to an accuracy of 93%. More significantly, out of a set of 56 regions of image data, 43 regions were binarised to a useful level of accuracy. The results obtained from the image segmentation technique developed here may be used for the study of shape and alignment of ECs, and hence patterns of blood flow, around arterial branches.

Morphological evidence for a change in the pattern of aortic wall shear stress with age.

OBJECTIVE: The distribution of atherosclerosis around branch sites changes with age in human and rabbit aortas. We tested whether that reflects a change in the pattern of wall shear stress by examining shear-dependent morphological features of endothelial cells. METHODS AND RESULTS: Endothelial cells and their nuclei align and elongate with applied shear. These parameters were examined in the descending thoracic aorta of immature and mature rabbits. The use of Häutchen preparations, fluorescent stains, and automated image analysis allowed nuclear morphology to be mapped reliably at high resolution over large areas. Cells and their nuclei were most elongated downstream of branch ostia in immature aortas but upstream of them in mature aortas. Elongation was generally greater in mature animals, and nuclei aligned toward the ostia more in these animals, consistent with a greater flow into the branch. Morphology away from branches was indicative of helical flow in the aorta, with greatest shear on the dorsal wall, at both ages. CONCLUSIONS: The data are consistent with age-related changes in the pattern of shear around aortic branches. Maps of nuclear elongation closely resembled maps of lesion frequency. The association was positive, implying that lesions occur at sites of high shear stress at both ages.