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Register a new userNew Universal Theory of Injury Prediction and Prevention
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Vladimir G. Ivancevic
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The prediction and prevention of traumatic brain injury, spinal injury and general musculo-skeletal injury is a very important aspect of preventive medical science. Recently, in a series of papers, I have proposed a new coupled loading-rate hypothesis as a unique cause of all above injuries. This new hypothesis states that the main cause of all mechanical injuries is a Euclidean Jolt, which is an impulsive loading that strikes any part of the human body (head, spine or any bone/joint) - in several coupled degrees-of-freedom simultaneously. It never goes in a single direction only. Also, it is never a static force. It is always an impulsive translational and/or rotational force, coupled to some human mass eccentricity. Keywords: traumatic brain injury, spinal injury, musculo-skeletal injury, coupled loading-rate hypothesis, Euclidean jolt
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The prediction and prevention of spinal injury is an important aspect of preventive health science. The spine, or vertebral column, represents a chain of 26 movable vertebral bodies, joint together by transversal viscoelastic intervertebral discs and longitudinal elastic tendons. This paper proposes a new locally-coupled loading-rate hypothesis}, which states that the main cause of both soft- and hard-tissue spinal injury is a localized Euclidean jolt, or SE(3)-jolt, an impulsive loading that strikes a localized spine in several coupled degrees-of-freedom simultaneously. To show this, based on the previously defined covariant force law, we formulate the coupled Newton-Euler dynamics of the local spinal motions and derive from it the corresponding coupled SE(3)-jolt dynamics. The SE(3)-jolt is the main cause of two basic forms of spinal injury: (i) hard-tissue injury of local translational dislocations; and (ii) soft-tissue injury of local rotational disclinations. Both the spinal dislocations and disclinations, as caused by the SE(3)-jolt, are described using the Cosserat multipolar viscoelastic continuum model. Keywords: localized spinal injury, coupled loading-rate hypothesis, coupled Newton-Euler dynamics, Euclidean jolt dynamics, spinal dislocations and disclinations
Prediction and prevention of musculo-skeletal injuries is an important aspect of preventive health science. Using as an example a human knee joint, this paper proposes a new coupled-loading-rate hypothesis, which states that a generic cause of any musculo-skeletal injury is a Euclidean jolt, or SE(3)-jolt, an impulsive loading that hits a joint in several coupled degrees-of-freedom simultaneously. Informally, it is a rate-of-change of joint acceleration in all 6-degrees-of-freedom simultaneously, times the corresponding portion of the body mass. In the case of a human knee, this happens when most of the body mass is on one leg with a semi-flexed knee -- and then, caused by some external shock, the knee suddenly `jerks; this can happen in running, skiing, sports games (e.g., soccer, rugby) and various crashes/impacts. To show this formally, based on the previously defined covariant force law and its application to traumatic brain injury (Ivancevic, 2008), we formulate the coupled Newton--Euler dynamics of human joint motions and derive from it the corresponding coupled SE(3)-jolt dynamics of the joint in case. The SE(3)-jolt is the main cause of two forms of discontinuous joint injury: (i) mild rotational disclinations and (ii) severe translational dislocations. Both the joint disclinations and dislocations, as caused by the SE(3)-jolt, are described using the Cosserat multipolar viscoelastic continuum joint model. Keywords: musculo-skeletal injury, coupled-loading--rate hypothesis, coupled Newton-Euler dynamics, Euclidean jolt dynamics, joint dislocations and disclinations
The prediction and prevention of traumatic brain injury is a very important aspect of preventive medical science. This paper proposes a new coupled loading-rate hypothesis for the traumatic brain injury (TBI), which states that the main cause of the TBI is an external Euclidean jolt, or SE(3)-jolt, an impulsive loading that strikes the head in several coupled degrees-of-freedom simultaneously. To show this, based on the previously defined covariant force law, we formulate the coupled Newton-Euler dynamics of brains micro-motions within the cerebrospinal fluid and derive from it the coupled SE(3)-jolt dynamics. The SE(3)-jolt is a cause of the TBI in two forms of brains rapid discontinuous deformations: translational dislocations and rotational disclinations. Brains dislocations and disclinations, caused by the SE(3)-jolt, are described using the Cosserat multipolar viscoelastic continuum brain model. Keywords: Traumatic brain injuries, coupled loading-rate hypothesis, Euclidean jolt, coupled Newton-Euler dynamics, brains dislocations and disclinations
Coronavirus disease (COVID-19) is an infectious disease discovered in 2019 and currently in outbreak across the world. Lung injury with severe respiratory failure is the leading cause of death in COVID-19, brought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there still lacks efficient treatment for COVID-19 induced lung injury and acute respiratory failure. Inhibition of Angiotensin-converting enzyme 2 (ACE2) caused by spike protein of SARS-CoV-2 is the most plausible mechanism of lung injury in COVID-19. We propose two candidate drugs, COL-3 (a chemically modified tetracycline) and CGP-60474 (a cyclin-dependent kinase inhibitor), for treating lung injuries in COVID-19, based on their abilities to reverse the gene expression patterns in HCC515 cells treated with ACE2 inhibitor and in human COVID-19 patient lung tissues. Further bioinformatics analysis shows that twelve significantly enriched pathways (P-value <0.05) overlap between HCC515 cells treated with ACE2 inhibitor and human COVID-19 patient lung tissues, including signaling pathways known to be associated with lung injury such as TNF signaling, MAPK signaling and Chemokine signaling pathways. All these twelve pathways are targeted in COL-3 treated HCC515 cells, in which genes such as RHOA, RAC2, FAS, CDC42 have reduced expression. CGP-60474 shares eleven of twelve pathways with COL-3 with common target genes such as RHOA. It also uniquely targets genes related to lung injury, such as CALR and MMP14. In summary, this study shows that ACE2 inhibition is likely part of the mechanisms leading to lung injury in COVID-19, and that compounds such as COL-3 and CGP-60474 have the potential as repurposed drugs for its treatment.
Acute kidney injury (AKI) in critically ill patients is associated with significant morbidity and mortality. Development of novel methods to identify patients with AKI earlier will allow for testing of novel strategies to prevent or reduce the complications of AKI. We developed data-driven prediction models to estimate the risk of new AKI onset. We generated models from clinical notes within the first 24 hours following intensive care unit (ICU) admission extracted from Medical Information Mart for Intensive Care III (MIMIC-III). From the clinical notes, we generated clinically meaningful word and concept representations and embeddings, respectively. Five supervised learning classifiers and knowledge-guided deep learning architecture were used to construct prediction models. The best configuration yielded a competitive AUC of 0.779. Our work suggests that natural language processing of clinical notes can be applied to assist clinicians in identifying the risk of incident AKI onset in critically ill patients upon admission to the ICU.
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