Pertinence of Predictive Models as Regards the Behavior of Observed Biological and Artificial Phenomena

2021 ◽  
Vol 8 (3) ◽  
pp. 189-200
Author(s):  
Adel Razek

In this assessment, we have made an effort of synthesis on the role of theoretical and observational investigations in the analysis of the concepts and functioning of different natural biological and artificial phenomena. In this context, we pursued the objective of examining published works relating to the behavioral prediction of phenomena associated with its observation. We have examined examples from the literature concerning phenomena with known behaviors that associated to knowledge uncertainty as well as cases concerning phenomena with unknown and changing random behaviors linked to random uncertainty. The concerned cases are relative to brain functioning in neuroscience, modern smart industrial devices, and health care predictive endemic protocols. As predictive modeling is very concerned by the problematics relative to uncertainties that depend on the degree of matching in the link prediction-observation, we investigated first how to improve the model to match better the observation. Thus, we considered the case when the observed behavior and its model are contrasting, that implies the development of revised or amended models. Then we studied the case concerning the practice of modeling for the prediction of future behaviors of a phenomenon that is well known, and owning identified behavior. For such case, we illustrated the situation of prediction matched to observation operated in two cases. These are the Bayesian Brain theory in neuroscience and the Digital Twins industrial concept. The last investigated circumstance concerns the use of modeling for the prediction of future behaviors of a phenomenon that is not well known, or owning behavior varying arbitrary. For this situation, we studied contagion infections with an unknown mutant virus where the prediction task is very complicated and would be constrained only to adjust the principal clinical observation protocol. Keywords: prediction, observation, Bayesian, neuroscience, brain functioning, mutant virus

2020 ◽  
Vol 8 (1) ◽  
pp. 23-36
Author(s):  
Adel Razek

Recent developments in several theoretical and industrial concepts are closely associated to the relation of operational observation to mathematical modeling. The present work investigates first the interdependence of these two evaluation notions. An assessment of these notions is performed involving different analyses based on philosophical aspects as phenomenology and structural research. These analyses are also supported by illustrations from physics and quantum science. These analyses examine the autonomy limits of each of both concepts and their interdependence. The associate resulting from such interdependence is therefore studied. This involves different aspects characterizing such associate (couple) as its managing in time and its rulings. The immersion of the couple "observation-theory" is subsequently considered through the exploration of different representing cases showing the nature of the interdependence in this couple. The corroborating interdependence is illuminated in the case of coupled amended models. The matching interdependence is illustrated in the cases of the industrial digital twins concept and Bayesian brain theory in neuroscience. Finally, the imitating interdependence is pointed out in quantum and neuromorphic computing technologies. The conclusion of the paper underlines that mathematical modeling needs operational observation simply to be credible and that the second needs the first for deeper research. Additionally, the interdependence of this associate is valuable to the ideas of several research and industrial innovative concepts. Keywords: observation-modeling associate, phenomenology, structural research, Bayesian concepts, quantum science, matching, imitating, corroborating.


2021 ◽  
Vol 22 (14) ◽  
pp. 7494
Author(s):  
Przemyslaw Wielgat ◽  
Katarzyna Niemirowicz-Laskowska ◽  
Agnieszka Z. Wilczewska ◽  
Halina Car

The cell surface is covered by a dense and complex network of glycans attached to the membrane proteins and lipids. In gliomas, the aberrant sialylation, as the final stage of glycosylation, is an important regulatory mechanism of malignant cell behavior and correlates with worse prognosis. Better understanding of the role of sialylation in cellular and molecular processes opens a new way in the development of therapeutic tools for human brain tumors. According to the recent clinical observation, the cellular heterogeneity, activity of brain cancer stem cells (BCSCs), immune evasion, and function of the blood–brain barrier (BBB) are attractive targets for new therapeutic strategies. In this review, we summarize the importance of sialic acid-modified nanoparticles in brain tumor progression.


2020 ◽  
Vol 53 (2) ◽  
pp. 10556-10561
Author(s):  
Chiara Cimino ◽  
Gianni Ferretti ◽  
Alberto Leva
Keyword(s):  

2020 ◽  
Vol 53 (2) ◽  
pp. 10574-10578
Author(s):  
Cosimo Piancastelli ◽  
Mario Tucci
Keyword(s):  

1999 ◽  
Vol 77 (12) ◽  
pp. 1874-1890 ◽  
Author(s):  
C D Rollo ◽  
C V Ko ◽  
JG A Tyerman ◽  
L J Kajiura

Sleep is required for the consolidation of memory for complex tasks, and elements of the growth-hormone (GH) axis may regulate sleep. The GH axis also up-regulates protein synthesis, which is required for memory consolidation. Transgenic rat GH mice (TRGHM) express plasma GH at levels 100-300 times normal and sleep 3.4 h longer (30%) than their normal siblings. Consequently, we hypothesized that they might show superior ability to learn a complex task (8-choice radial maze); 47% of the TRGHM learned the task before any normal mice. All 17 TRGHM learned the task, but 33% of the 18 normal mice learned little. TRGHM learned the task significantly faster than normal mice (p < 0.05) and made half as many errors in doing so, even when the normal nonlearners were excluded from the analysis. Whereas normal mice expressed a linear learning curve, TRGHM showed exponentially declining error rates. The contribution of the GH axis to cognition is conspicuously sparse in literature syntheses of knowledge concerning neuroendocrine mechanisms of learning and memory. This paper synthesizes the crucial role of major components of the GH axis in brain functioning into a holistic framework, integrating learning, sleep, free radicals, aging, and neurodegenerative diseases. TRGHM show both enhanced learning in youth and accelerated aging. Thus, they may provide a powerful new probe for use in gaining an understanding of aspects of central nervous system functioning, which is highly relevant to human health.


2017 ◽  
pp. 120-125 ◽  
Author(s):  
N. V. Nudnov ◽  
U. Stanoevich ◽  
E. N. Grebenkin ◽  
E. V. Sidorova

Coloncancer is one of the first places in the structure of oncological diseases. According to statistics, edited by A.D. Kaprin, V.V. Starinskii, G.V. Petrova ofRussiafor 2015 was initially 36494 case of colorectal cancer, while 2% of cases are not diagnosed. Recurrence of colon cancer can occur at any stage regardless of the time elapsed after the radical treatment. Locoregionally originally is the presence of a tumor in the area of primary operation, which is represented by the primary tumor bed, the anastomosis, mesentery of the colon with lymphatic system, peritoneum and adjacent organs. Often after a diagnosis of “recurrence of the tumor in the colon” to the patient it is possible to provide only palliative care (colostomy, chemotherapy). The article cited clinical observation, confirming the important role of radiation techniques in determination of tactics of treatment of locoregional recurrence of the cecum cancer. 


2013 ◽  
pp. 71-72
Author(s):  
Fulvio Camerini ◽  
Luisa Mestroni ◽  
Gianfranco Sinagra ◽  
Michele Moretti

2013 ◽  
pp. 43-49
Author(s):  
Fulvio Camerini ◽  
Gianfranco Sinagra ◽  
Stefano Bardari

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