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Mitra Basu

Publications and source records attributed to Mitra Basu.

4 recordsLinked to original sources
PubMed2005

Analysis of avian bone response to mechanical loading. Part two: Development of a computational connected cellular network to study bone intercellular communication.

Mechanical loading-induced signals are hypothesized to be transmitted and integrated by connected bone cells before reaching the bone surfaces where adaptation occurs. A computational connected cellular network (CCCN) model is developed to explore how bone cells perceive and transmit the signals through intercellular communication. This is part two of a two-part study in which a CCCN is developed to study the intercellular communication within a grid of bone cells. The excitation signal was computed as the loading-induced bone fluid shear stress in part one. Experimentally determined bone adaptation responses (Gross et al. in J Bone Miner Res 12:982-988, 1997 and Judex et al. in J Bone Miner Res 12:1737-1745, 1997) are correlated with the fluid shear stress by the CCCN, which adjusts cell sensitivities (loading and signal thresholds) and connection weights. Intercellular communication patterns extracted by the CCCN indicate the cell population responsible for perceiving the loading-induced signal, and loading threshold is shown to play an important role in regulating the bone response.

Algorithms↗
PubMed2005

Analysis of avian bone response to mechanical loading-Part one: Distribution of bone fluid shear stress induced by bending and axial loading.

Mechanical loading-induced signals are hypothesized to be transmitted and integrated by a bone-connected cellular network (CCN) before reaching the bone surfaces where adaptation occurs. Our objective is to establish a computational model to explore how bone cells transmit the signals through intercellular communication. In this first part of the study the bone fluid shear stress acting on every bone cell in a CCN is acquired as the excitation signal for the computational model. Bending and axial loading-induced fluid shear stress is computed in transverse sections of avian long bones for two adaptation experiments (Gross et al. in J Bone Miner Res 12:982-988, 1997 and Judex et al. in J Bone Miner Res 12:1737-1745, 1997). The computed fluid shear stress is found to be correlated with the radial strain gradient but not with bone formation. These results suggest that the radial strain gradient is the driving force for bone fluid flow in the radially distributed lacunar-canalicular system and that bone formation is not linearly related to the loading-induced local stimulus.

Animals↗
PubMed1998

The fractional correction rule: a new perspective.

In this paper we discover and explore a useful property of the fractional correction rule, a variation of the perceptron learning rule, for a single neural unit. We rename this rule the projection learning rule (PrLR), which seems more appropriate because of the technique that we use to prove convergence. We state and prove a more powerful convergence theorem and establish the link with S. Agmon's work (1954) on linear inequalities. The hallmark of this rule is that if the problem is not linearly separable then the proposed rule will always converge to the origin of the weight-space. This points out that appropriate nonlinear methods (e.g., multilayer neural network, nonlinear transformation on input-space etc.) should be used to address this problem. On the other hand, if the patterns are linearly separable, the performance of this rule is equivalent to that of the perceptron rule. A theoretical investigation of this rule leads to interesting observations. We present experimental results with linearly separable as well as linearly non-separable data using the PrLR and compare its performance with that of the perceptron rule.

Journal Article↗