42 research outputs found
Method for finding metabolic properties based on the general growth law. Liver examples. A General framework for biological modeling
We propose a method for finding metabolic parameters of cells, organs and
whole organisms, which is based on the earlier discovered general growth law.
Based on the obtained results and analysis of available biological models, we
propose a general framework for modeling biological phenomena and discuss how
it can be used in Virtual Liver Network project. The foundational idea of the
study is that growth of cells, organs, systems and whole organisms, besides
biomolecular machinery, is influenced by biophysical mechanisms acting at
different scale levels. In particular, the general growth law uniquely defines
distribution of nutritional resources between maintenance needs and biomass
synthesis at each phase of growth and at each scale level. We exemplify the
approach considering metabolic properties of growing human and dog livers and
liver transplants. A procedure for verification of obtained results has been
introduced too. We found that two examined dogs have high metabolic rates
consuming about 0.62 and 1 gram of nutrients per cubic centimeter of liver per
day, and verified this using the proposed verification procedure. We also
evaluated consumption rate of nutrients in human livers, determining it to be
about 0.088 gram of nutrients per cubic centimeter of liver per day for males,
and about 0.098 for females. This noticeable difference can be explained by
evolutionary development, which required females to have greater liver
processing capacity to support pregnancy. We also found how much nutrients go
to biomass synthesis and maintenance at each phase of liver and liver
transplant growth. Obtained results demonstrate that the proposed approach can
be used for finding metabolic characteristics of cells, organs, and whole
organisms, which can further serve as important inputs for many applications in
biology (protein expression), biotechnology (synthesis of substances), and
medicine.Comment: 20 pages, 6 figures, 4 table
Physical paradigm of Life as a generalization of biochemical conception. A Physical law governing life origin and development
The present view of biological phenomena is based on a biomolecular paradigm
that development of living organisms is entirely defined by information stored
in a molecular form as some genetic code. However, new facts and discoveries
indicate that biological phenomena cannot be reduced to a biomolecular realm
alone, but are also governed by mechanisms of other nature. These mechanisms,
acting in tight cooperation with biochemical mechanisms, define life cycles of
individual organisms, and, through this, the origin and evolution of the living
world. Here, we present such a physical mechanism (General growth law), which
represents a new physical law of nature acting at cellular, organ, system and
whole organism levels, directing growth and reproduction together with
biomolecular mechanisms. It imposes uniquely defined constraints on
distribution of nutrients between biomass production and maintenance, thus
defining the composition of biochemical reactions, their change and
irreversibility during the organismal life cycle. Mathematically, this law is
represented by the growth equation. Using this equation, we introduce growth
models and explain division mechanisms for unicellular organisms. High adequacy
of obtained results to experiments proves validity of the General growth law
and of the new physical paradigm of Life based on this law.Comment: 38 pages, 8 figures, 1 table. Analysis of general principles of Life
organization was added, as well as new material and two figures. In
particular, analysis of views of E. Schrodinger, whose famous lectures
contributed to origin of a biochemical paradigm, exposes what assumptions led
him to make inaccurate conclusions. A new, more general physical paradigm of
Life was propose
A Method for Modeling Growth of Organs and Transplants Based on the General Growth Law: Application to the Liver in Dogs and Humans
Understanding biological phenomena requires a systemic approach that
incorporates different mechanisms acting on different spatial and temporal
scales, since in organisms the workings of all components, such as organelles,
cells, and organs interrelate. This inherent interdependency between diverse
biological mechanisms, both on the same and on different scales, provides the
functioning of an organism capable of maintaining homeostasis and physiological
stability through numerous feedback loops. Thus, developing models of organisms
and their constituents should be done within the overall systemic context of
the studied phenomena. We introduce such a method for modeling growth and
regeneration of livers at the organ scale, considering it a part of the overall
multi-scale biochemical and biophysical processes of an organism. Our method is
based on the earlier discovered general growth law, postulating that any
biological growth process comprises a uniquely defined distribution of
nutritional resources between maintenance needs and biomass production. Based
on this law, we introduce a liver growth model that allows to accurately
predicting the growth of liver transplants in dogs and liver grafts in humans.
Using this model, we find quantitative growth characteristics, such as the time
point when the transition period after surgery is over and the liver resumes
normal growth, rates at which hepatocytes are involved in proliferation, etc.
We then use the model to determine and quantify otherwise unobservable
metabolic properties of livers.Comment: 13 pages, 6 figure
Sequencing identifies a distinct signature of circulating microRNAs in early radiographic knee osteoarthritis
OBJECTIVE: MicroRNAs act locally and systemically to impact osteoarthritis (OA) pathophysiology, but comprehensive profiling of the circulating miRNome in early vs late stages of OA has yet to be conducted. Sequencing has emerged as the preferred method for microRNA profiling since it offers high sensitivity and specificity. Our objective is to sequence the miRNome in plasma from 91 patients with early [Kellgren-Lawrence (KL) grade 0 or 1 (n = 41)] or late [KL grade 3 or 4 (n = 50)] symptomatic radiographic knee OA to identify unique microRNA signatures in each disease state.
DESIGN: MicroRNA libraries were prepared using the QIAseq miRNA Library Kit and sequenced on the Illumina NextSeq 550.Counts were produced for microRNAs captured in miRBase and for novel microRNAs. Statistical, bioinformatics, and computational biology approaches were used to refine and interpret the final list of microRNAs.
RESULTS: From 215 differentially expressed microRNAs (FDR \u3c 0.01), 97 microRNAs showed an increase or decrease in expression in ≥85% of samples in the early OA group as compared to the median expression in the late OA group. Increasing this threshold to ≥95%, seven microRNAs were identified: hsa-miR-335-3p, hsa-miR-199a-5p, hsa-miR-671-3p, hsa-miR-1260b, hsa-miR-191-3p, hsa-miR-335-5p, and hsa-miR-543. Four novel microRNAs were present in ≥50% of early OA samples and had 27 predicted gene targets in common with the prioritized set of predicted gene targets from the 97 microRNAs, suggesting common underlying mechanisms.
CONCLUSION: Applying sequencing to well-characterized patient cohorts produced unbiased profiling of the circulating miRNome and identified a unique panel of 11 microRNAs in early radiographic knee OA