Cytoarchitectonics of the Superior Parietal Cortex of an Outstanding Russian Scientist-Physiologist

The aim of the study is to identify possible cytoarchitectonic features of the structure of the cortex in the superior parietal region of an outstanding and talented scientist-physiologist.Material and methods. The cortex (area 7) of the superior parietal region of a scientist-physiologist and men of the senile age in the control group (8 hemispheres) was studied on the series of frontal brain slices, 20 μ thick, stained with cresyl purple according to Nissl method. The cortex area thickness, the thickness of the cytoarchitectonics layer III, the area of profile field of pyramidal neurons in layers III and V, the density of neurons surrounded by satellite glia and satellite glia density in layers III and V were measured in the cortex (area 7) of the superior parietal region in the left and right hemispheres of the brain.Results. We have identified several features of the cytoarchitectonics structure of the cortex (area 7) in the brain of the scientist-physiologist that may correlate with his outstanding scientific abilities. The cortex of a scientist-physiologist is characterized by a large thickness of the studied cortex and its cytoarchitectonic layers III and V, and a greater value of the area of the profile field of neurons if compared with the cortex in men of the senile age from the control group. A higher value of the neuron density and satellite glia in the cortex of the superior parietal region of the scientist-physiologist was revealed. There was also a lower severity of age-related changes in the cortex of the scientist-physiologist compared with the control group of men.Conclusion. The structure of the cortex (area 7) of the superior parietal region of the scientistphysiologist is characterized by a greater parameter of the cortical thickness and the thickness of the associative layer III, the size of neurons and the density of satellite glia if compared with those in men of the senile age of the control group. These features distinguish the structure of his cortex from the similar cortex of the control group of men and may be related to the features of the cognitive activity of the outstanding scientist-physiologist.

AGE-RELATED CHANGES OF THE PROFILE FIELD OF NEURONS OF THE AREA 7 OF THE BRAIN OF MEN AND WOMEN IN THE PROCESS OF THE AGING

The aim of the work is to study changes in the profile field of pyramidal neurons in the cortex of field 7 of the brain of men and women in the aging process. A cytoarchitectonic study of the cortex of field 7 of the upper parietal region of the brain of men and women was carried out on a series of frontal paraffin sections stained by the Nissl method. The brain preparations of men and women of three age groups were studied: the groups of mature age (from 20 to 60 years), the elderly group (from 60 to 75 years) and the group of senile age (from 75 years and older). In each age group, 5 preparations of the male brain and 5 preparations of the female brain were studied. Age-related changes in the cytoarchitectonics of the profile field of pyramidal neurons in the cytoarchitectonic layers of the third and fifth cortex fields 7 of the brain of men and women were studied. As a result of the study, it was revealed that in the process of aging of the brain of men and women, changes in similar morphometric indicators of field 7 cortex occur at different age periods, the dynamics of age-related changes in functionally different cytoarchitectonic layers III and V of the cerebral cortex of men and women are also different.

Health Informatics via Machine Learning for the Clinical Management of Patients

Summary Objectives: To review how health informatics systems based on machine learning methods have impacted the clinical management of patients, by affecting clinical practice. Methods: We reviewed literature from 2010-2015 from databases such as Pubmed, IEEE xplore, and INSPEC, in which methods based on machine learning are likely to be reported. We bring together a broad body of literature, aiming to identify those leading examples of health informatics that have advanced the methodology of machine learning. While individual methods may have further examples that might be added, we have chosen some of the most representative, informative exemplars in each case. Results: Our survey highlights that, while much research is taking place in this high-profile field, examples of those that affect the clinical management of patients are seldom found. We show that substantial progress is being made in terms of methodology, often by data scientists working in close collaboration with clinical groups. Conclusions: Health informatics systems based on machine learning are in their infancy and the translation of such systems into clinical management has yet to be performed at scale.

Introduction: From Affect to Exegesis

This article introduces a thematic issue of Biblical Interpretation on the high-profile field of affect theory as it relates to biblical studies. Affect theory analyzes emotions and still more elemental forces that are rooted in bodies and pass between them. In addition to previewing the six articles in the issue – three of which grapple with Hebrew Bible texts and three with early Christian texts – this introduction provides a brief history of affect theory and maps its main variants. The article also reflects on the challenges of turning a body of theory largely uninterested in literary interpretation into a set of strategies for reading biblical texts.