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result(s) for
"Bhattacharya, Sabyasachi"
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A noble extended stochastic logistic model for cell proliferation with density-dependent parameters
Cell proliferation often experiences a density-dependent intrinsic proliferation rate (IPR) and negative feedback from growth-inhibiting molecules in culture media. The lack of flexible models with explanatory parameters fails to capture such a proliferation mechanism. We propose an extended logistic growth law with the density-dependent IPR and additional negative feedback. The extended parameters of the proposed model can be interpreted as density-dependent cell-cell cooperation and negative feedback on cell proliferation. Moreover, we incorporate further density regulation for flexibility in the model through environmental resistance on cells. The proposed growth law has similarities with the strong Allee model and harvesting phenomenon. We also develop the stochastic analog of the deterministic model by representing possible heterogeneity in growth-inhibiting molecules and environmental perturbation of the culture setup as correlated multiplicative and additive noises. The model provides a conditional maximum sustainable stable cell density (MSSCD) and a new fitness measure for proliferative cells. The proposed model shows superiority to the logistic law after fitting to real cell culture datasets. We illustrate both conditional MSSCD and the new cell fitness for a range of parameters. The cell density distributions reveal the chance of overproliferation, underproliferation, or decay for different parameter sets under the deterministic and stochastic setups.
Journal Article
Tumor-immune profiling of murine syngeneic tumor models as a framework to guide mechanistic studies and predict therapy response in distinct tumor microenvironments
Mouse syngeneic tumor models are widely used tools to demonstrate activity of novel anti-cancer immunotherapies. Despite their widespread use, a comprehensive view of their tumor-immune compositions and their relevance to human tumors has only begun to emerge. We propose each model possesses a unique tumor-immune infiltrate profile that can be probed with immunotherapies to inform on anti-tumor mechanisms and treatment strategies in human tumors with similar profiles. In support of this endeavor, we characterized the tumor microenvironment of four commonly used models and demonstrate they encompass a range of immunogenicities, from highly immune infiltrated RENCA tumors to poorly infiltrated B16F10 tumors. Tumor cell lines for each model exhibit different intrinsic factors in vitro that likely influence immune infiltration upon subcutaneous implantation. Similarly, solid tumors in vivo for each model are unique, each enriched in distinct features ranging from pathogen response elements to antigen presentation machinery. As RENCA tumors progress in size, all major T cell populations diminish while myeloid-derived suppressor cells become more enriched, possibly driving immune suppression and tumor progression. In CT26 tumors, CD8 T cells paradoxically increase in density yet are restrained as tumor volume increases. Finally, immunotherapy treatment across these different tumor-immune landscapes segregate into responders and non-responders based on features partially dependent on pre-existing immune infiltrates. Overall, these studies provide an important resource to enhance our translation of syngeneic models to human tumors. Future mechanistic studies paired with this resource will help identify responsive patient populations and improve strategies where immunotherapies are predicted to be ineffective.
Journal Article
Microbiome and ecology of a hot spring-microbialite system on the Trans-Himalayan Plateau
Little is known about life in the boron-rich hot springs of Trans-Himalayas. Here, we explore the geomicrobiology of a 4438-m-high spring which emanates ~70
°
C-water from a boratic microbialite called
Shivlinga
. Due to low atmospheric pressure, the vent-water is close to boiling point so can entropically destabilize biomacromolecular systems. Starting from the vent,
Shivlinga
’s geomicrobiology was revealed along the thermal gradients of an outflow-channel and a progressively-drying mineral matrix that has no running water; ecosystem constraints were then considered in relation to those of entropically comparable environments. The spring-water chemistry and sinter mineralogy were dominated by borates, sodium, thiosulfate, sulfate, sulfite, sulfide, bicarbonate, and other macromolecule-stabilizing (kosmotropic) substances. Microbial diversity was high along both of the hydrothermal gradients. Bacteria, Eukarya and Archaea constituted >98%, ~1% and <1% of
Shivlinga
’s microbiome, respectively. Temperature constrained the biodiversity at ~50 °C and ~60 °C, but not below 46 °C. Along each thermal gradient, in the vent-to-apron trajectory, communities were dominated by
Aquificae
/
Deinococcus
-
Thermus
, then
Chlorobi
/
Chloroflexi
/Cyanobacteria, and finally
Bacteroidetes
/
Proteobacteria
/
Firmicutes
. Interestingly, sites of >45 °C were inhabited by phylogenetic relatives of taxa for which laboratory growth is not known at >45 °C.
Shivlinga
’s geomicrobiology highlights the possibility that the system’s kosmotrope-dominated chemistry mitigates against the biomacromolecule-disordering effects of its thermal water.
Journal Article
Spatial characterization and quantification of CD40 expression across cancer types
Background
CD40, a TNF receptor family member, is expressed by a variety of immune cells and is involved in the activation of both adaptive and innate immune responses. Here, we used quantitative immunofluorescence (QIF) to evaluate CD40 expression on the tumor epithelium of solid tumors in large patient cohorts of lung, ovarian, and pancreatic cancers.
Methods
Tissue samples from nine different solid tumors (bladder, breast, colon, gastric, head and neck, non-small cell lung cancer (NSCLC), ovarian, pancreatic and renal cell carcinoma), constructed in tissue microarray format, were initially assessed for CD40 expression by QIF. CD40 expression was then evaluated on the large available patient cohorts for three of the tumor types demonstrating high CD40 positivity rate; NSCLC, ovarian and pancreatic cancer. The prognostic impact of CD40 expression on tumor cells was also investigated.
Results
CD40 expression on tumor cells was found to be common, with 80% of the NSCLC population, 40% of the ovarian cancer population, and 68% of the pancreatic adenocarcinoma population displaying some degree of CD40 expression on cancer cells. All of three of these cancer types displayed considerable intra-tumoral heterogeneity of CD40 expression, as well as partial correlation between expression of CD40 on tumor cells and on surrounding stromal cells. CD40 was not found to be prognostic for overall survival in NSCLC, ovarian cancer, or pancreatic adenocarcinoma.
Conclusions
The high percentage of tumor cells expressing CD40 in each of these solid tumors should be considered in the development of therapeutic agents designed to target CD40.
Journal Article
Role Reversals in a Tri-Trophic Prey–Predator Interaction System: A Model-Based Study Using Deterministic and Stochastic Approaches
It is frequently observed that adult members of prey species sometimes use their predation mechanism on juvenile members of predator species. Ecological literature describes this phenomenon as prey–predator role reversal dynamics.Numerous authors have observed and described the biological development behind this feeding behaviour. However, the dynamics of this role reversal have hardly been illustrated in the literature in a precise way. In this regard, we formulated an ecological model using the standard prey–predator interactions, allowing for a reverse feeding mechanism. The mathematical model consisted of a three-species food-web structure comprising the common prey, intermediate predator, and top predator. Note that a role-reversal mechanism was observed between the intermediate and top predators based on the scarcity of the prey population. However, we observed the most critical parameters had a significant effect on this reverse feeding behaviour. The bifurcation analysis is the primary criterion for this identification. The proposed deterministic model is then extended to its stochastic analogue by allowing for environmental influences on the tri-trophic food web structure. The conditional moment approach is applied to obtain the equilibrium distribution of populations and their conditional moments in the system. The stochastic setup analysis also supports the stability of this food chain structure, with some restricted conditions. Finally, to facilitate the interpretation of our mathematical results, we investigated it using numerical simulations.
Journal Article
Enhanced carbon-sulfur cycling in the sediments of Arabian Sea oxygen minimum zone center
Biogeochemistry of oxygen minimum zone (OMZ) sediments, which are characterized by high input of labile organic matter, have crucial bearings on the benthic biota, gas and metal fluxes across the sediment-water interface, and carbon-sulfur cycling. Here we couple pore-fluid chemistry and comprehensive microbial diversity data to reveal the sedimentary carbon-sulfur cycle across a water-depth transect covering the entire thickness of eastern Arabian Sea OMZ, off the west coast of India. Geochemical data show remarkable increase in average total organic carbon content and aerial sulfate reduction rate (J
SO4
2−
) in the sediments of the OMZ center coupled with shallowing of sulfate methane transition zone and hydrogen sulfide and ammonium build–up. Total bacterial diversity, including those of complex organic matter degraders, fermentative and exoelectrogenic bacteria, and sulfate-reducers (that utilize only simple carbon compounds) were also found to be highest in the same region. The above findings indicate that higher organic carbon sequestration from the water-columns (apparently due to lower benthic consumption, biodegradation and biotransformation) and greater bioavailability of simple organic carbon compounds (apparently produced by fermetative microflora of the sediments) are instrumental in intensifying the carbon-sulfur cycle in the sediments of the OMZ center.
Journal Article
Investigation and control strategy for canine distemper disease on endangered wild dog species: a model-based approach
The canine distemper virus (CDV) is a major threat to the already endangered wild dogs. We propose an evidence-based mathematical model of canine distemper in the wild to predict the rate and possibility of disease spread in wild dogs under a different scenario. We find the endemic and disease-free equilibrium points and the condition for their stability from the model. The bifurcation analysis of the model shows how the endemic equilibrium can be transformed into the disease-free equilibrium through parameters that represent fundamental ecological properties. The sensitivity of these parameters to the secondary disease spread points out the specific interaction rates and a birth rate that should be targeted to reduce the CDV outbreak. We suggest target parameters for controlling the disease outbreak considering the plausibility of manipulating them in terms of implications besides the sensitivity of the parameters. Finally, this article proposes two specific control strategies based on this modeling framework: isolation and birth-control-reintroduction. Since the isolation strategy may be cost-intensive, we modify our model to quantify the isolation rate necessary to reduce the disease outbreak. We suggest that the birth-control-reintroduction strategy based on the proposed model is cost-effective for a small contaminated area. Overall, the models in this study is applied in the field of conservation biology.
Article highlights
Natural regulation of Canine Distemper through mathematical study.
Assessment under the wild dog social structure of Canine Distemper.
A framework for policymaking in wild dog conservation.
Journal Article
Simultaneous identification of growth law and estimation of its rate parameter for biological growth data: a new approach
Scientific formalizations of the notion of growth and measurement of the rate of growth in living organisms are age-old problems. The most frequently used metric, “Average Relative Growth Rate” is invariant under the choice of the underlying growth model. Theoretically, the estimated rate parameter and relative growth rate remain constant for all mutually exclusive and exhaustive time intervals if the underlying law is exponential but not for other common growth laws (e.g., logistic, Gompertz, power, general logistic). We propose a new growth metric specific to a particular growth law and show that it is capable of identifying the underlying growth model. The metric remains constant over different time intervals if the underlying law is true, while the extent of its variation reflects the departure of the assumed model from the true one. We propose a new estimator of the relative growth rate, which is more sensitive to the true underlying model than the existing one. The advantage of using this is that it can detect crucial intervals where the growth process is erratic and unusual. It may help experimental scientists to study more closely the effect of the parameters responsible for the growth of the organism/population under study.
Journal Article