Moonlighting genes harbor antisense ORFs that encode potential membrane proteins.

Moonlighting genes encode for single polypeptide molecules that perform multiple and often unrelated functions. These genes occur across all domains of life. Their ubiquity and functional diversity raise many questions as to their origins, evolution, and role in the cell cycle. In this study, we present a simple bioinformatics probe that allows us to rank genes by antisense translation potential, and we show that this probe enriches, reliably, for moonlighting genes across a variety of organisms. We find that moonlighting genes harbor putative antisense open reading frames (ORFs) rich in codons for non-polar amino acids. We also find that moonlighting genes tend to co-locate with genes involved in cell wall, cell membrane, or cell envelope production. On the basis of this and other findings, we offer a model in which we propose that moonlighting gene products are likely to escape the cell through gaps in the cell wall and membrane, at wall/membrane construction sites; and we propose that antisense ORFs produce "membrane-sticky" protein products, effectively binding moonlighting-gene DNA to the cell membrane in porous areas where intensive cell-wall/cell-membrane construction is underway. This leads to high potential for escape of moonlighting proteins to the cell surface. Evolutionary and other implications of these findings are discussed.

Spectral forecast: A general purpose prediction model as an alternative to classical neural networks.

Here, we describe a general-purpose prediction model. Our approach requires three matrices of equal size and uses two equations to determine the behavior against two possible outcomes. We use an example based on photon-pixel coupling data to show that in humans, this solution can indicate the predisposition to disease. An implementation of this model is made available in the supplementary material.

Photon-pixel coupling: A method for parallel acquisition of electrical signals in scientific investigations.

Here we describe a novel prototype method for parallel sampling of electrical signals from 200 sensors. The amplified signal from each sensor was remotely converted into a luminous signal on a LED matrix. A digital camera supported by a duralumin skeleton, was installed at 15 cm above an LED matrix inside an opaque box. Images were sampled at discrete time intervals of 5 s. A total of 25,920 images of the LED matrix have been recorded. Thus, 5.2 million measurements have been recorded as light intensities from the LED matrix. Light intensities of individual LEDs from the images were converted into 1 pixel value/LED. Each pixel value was then converted into percentages for evaluation. We used this methodology to measure the temporal variation of the electrical current on the skin of the torso on human volunteers, to assess the presence of a correlation between the electrical activity and diabetes (Ionescu-Tirgoviste et al., 2018). This method also allowed us to compile the first high resolution map of the electrical activity generated by the human skin (Ionescu-Tirgoviste et al., 2018). •A novel method for a parallel acquisition of electrical signals which can be applied in any related field.•It provides the ability to retrieve a large number of electrical channels simultaneously.•It provides for an inexpensive and reliable way to digitize hundreds to thousands of channels at video rate frequencies.

Maps of electrical activity in diabetic patients and normal individuals.

Here, data related to the electrical activity of the human skin are presented in detail. The 3D electrical activity maps in normal and diabetic individuals are shown and described using raw data obtained with Photon-Pixel coupling. Average electrical activity matrices are shown by subject, gender and group. Distributions of the electrical activity data are shown in connection with the ventral and dorsal side of the human torso. For a better understanding of the electrical activity data, critical parameters of the individuals that participated in the study are also presented.

The electrical activity map of the human skin indicates strong differences between normal and diabetic individuals: A gateway to onset prevention.

The human skin is not only the largest organ, but also the most important candidate for novel non-invasive methods of investigation. Here we describe a large-scale prototype for determining the real-time distribution of the electrical activity from the surface of the human skin. A collection of 200 sensors have been placed across the entire trunk surface. The output of each sensor was remotely inserted into a 20 × 10 LED matrix for a parallel capture of the signals. Continuous observations of the electrical activity pattern were made above the LED matrix by a digital camera in an obscure environment. A total of 5.2 million measurements (25,920 maps) have been recorded as light intensities from the LED matrix and converted into percentages for evaluation. A total of 36 individuals were divided equally into two groups and subjected to a short glucose tolerance test for 1 h; one group with established Type 2 Diabetes (T2D) and the other group without diabetes. The electrical activity pattern and the average signal intensity of normal individuals (37% ±â€¯8.1) and diabetic individuals (58% ±â€¯7.8), showed a significant difference of 21%. The average signal intensity on the ventral side (VS) and dorsal side (DS) of the torso exhibited different behaviors in diabetics and non-diabetics. On average, diabetic individuals have shown an electrical activity of higher intensity on DS (DS = 60%, VS = 55%), while the normal group has shown a higher intensity on VS (DS = 36%, VS = 39%).

A 3D map of the islet routes throughout the healthy human pancreas.

Islets of Langerhans are fundamental in understanding diabetes. A healthy human pancreas from a donor has been used to asses various islet parameters and their three-dimensional distribution. Here we show that islets are spread gradually from the head up to the tail section of the pancreas in the form of contracted or dilated islet routes. We also report a particular anatomical structure, namely the cluster of islets. Our observations revealed a total of 11 islet clusters which comprise of small islets that surround large blood vessels. Additional observations in the peripancreatic adipose tissue have shown lymphoid-like nodes and blood vessels captured in a local inflammatory process. Our observations are based on regional slice maps of the pancreas, comprising of 5,423 islets. We also devised an index of sphericity which briefly indicates various islet shapes that are dominant throughout the pancreas.