Mitochondrial fusion and altered beta-oxidation drive muscle wasting in a Drosophila cachexia model.

Cancer cachexia is a tumour-induced wasting syndrome, characterised by extreme loss of skeletal muscle. Defective mitochondria can contribute to muscle wasting; however, the underlying mechanisms remain unclear. Using a Drosophila larval model of cancer cachexia, we observed enlarged and dysfunctional muscle mitochondria. Morphological changes were accompanied by upregulation of beta-oxidation proteins and depletion of muscle glycogen and lipid stores. Muscle lipid stores were also decreased in Colon-26 adenocarcinoma mouse muscle samples, and expression of the beta-oxidation gene CPT1A was negatively associated with muscle quality in cachectic patients. Mechanistically, mitochondrial defects result from reduced muscle insulin signalling, downstream of tumour-secreted insulin growth factor binding protein (IGFBP) homologue ImpL2. Strikingly, muscle-specific inhibition of Forkhead box O (FOXO), mitochondrial fusion, or beta-oxidation in tumour-bearing animals preserved muscle integrity. Finally, dietary supplementation with nicotinamide or lipids, improved muscle health in tumour-bearing animals. Overall, our work demonstrates that muscle FOXO, mitochondria dynamics/beta-oxidation and lipid utilisation are key regulators of muscle wasting in cancer cachexia.

A computational model to uncover the biophysical underpinnings of neural firing heterogeneity in dissociated hippocampal cultures.

Calcium (Ca2+ ) imaging reveals a variety of correlated firing in cultures of dissociated hippocampal neurons, pinpointing the non-synaptic paracrine release of glutamate as a possible mediator for such firing patterns, although the biophysical underpinnings remain unknown. An intriguing possibility is that extracellular glutamate could bind metabotropic receptors linked with inositol trisphosphate (IP3 ) mediated release of Ca2+ from the endoplasmic reticulum of individual neurons, thereby modulating neural activity in combination with sarco/endoplasmic reticulum Ca2+ transport ATPase (SERCA) and voltage-gated Ca2+ channels (VGCC). However, the possibility that such release may occur in different neuronal compartments and can be inherently stochastic poses challenges in the characterization of such interplay between various Ca2+ channels. Here we deploy biophysical modeling in association with Monte Carlo parameter sampling to characterize such interplay and successfully predict experimentally observed Ca2+ patterns. The results show that the neurotransmitter level at the plasma membrane is the extrinsic source of heterogeneity in somatic Ca2+ transients. Our analysis, in particular, identifies the origin of such heterogeneity to an intrinsic differentiation of hippocampal neurons in terms of multiple cellular properties pertaining to intracellular Ca2+ signaling, such as VGCC, IP3 receptor, and SERCA expression. In the future, the biophysical model and parameter estimation approach used in this study can be upgraded to predict the response of a system of interconnected neurons.

Three-dimensional imaging and quantification of real-time cytosolic calcium oscillations in microglial cells cultured on electrospun matrices using laser scanning confocal microscopy.

The development of a minimally invasive, robust, and inexpensive technique that permits real-time monitoring of cell responses on biomaterial scaffolds can improve the eventual outcomes of scaffold-based tissue engineering strategies. Towards establishing correlations between in situ biological activity and cell fate, we have developed a comprehensive workflow for real-time volumetric imaging of spatiotemporally varying cytosolic calcium oscillations in pure microglial cells cultured on electrospun meshes. Live HMC3 cells on randomly oriented electrospun fibers were stained with a fluorescent dye and imaged using a laser scanning confocal microscope. Resonance scanning provided high-resolution in obtaining the time-course of intracellular calcium levels without compromising spatial and temporal resolution. Three-dimensional reconstruction and depth-coding enabled the visualization of cell location and intracellular calcium levels as a function of sample thickness. Importantly, changes in cell morphology and in situ calcium spiking were quantified in response to a soluble biochemical cue and varying matrix architectures (i.e., randomly oriented and aligned fibers). Importantly, raster plots generated from spiking data revealed calcium signatures specific to culture conditions. In the future, our approach can be used to elucidate correlations between calcium signatures and cell phenotype/activation, and facilitate the rational design of scaffolds for biomedical applications.

A Pipeline for Dynamic Analysis of Mitochondrial Content in Developing T Cells: Bridging the Gap Between High-Throughput Flow Cytometry and Single-Cell Microscopy Analysis.

Analyzing the dynamics of mitochondrial content in developing T cells is crucial for understanding the metabolic state during T cell development. However, monitoring mitochondrial content in real-time needs a balance of cell viability and image resolution. In this chapter, we present experimental protocols for measuring mitochondrial content in developing T cells using three modalities: bulk analysis via flow cytometry, volumetric imaging in laser scanning confocal microscopy, and dynamic live-cell monitoring in spinning disc confocal microscopy. Next, we provide an image segmentation and centroid tracking-based analysis pipeline for automated quantification of a large number of microscopy images. These protocols together offer comprehensive approaches to investigate mitochondrial dynamics in developing T cells, enabling a deeper understanding of their metabolic processes.

In vitro laser scanning confocal microscopy and unsupervised segmentation: Quantification of cytosolic calcium and RNA distribution in hypoxic neurons.

The mimicry of neurodegenerative diseases in vitro can be observed through the induction of chronic hypoxia, and the impact of this stress is monitored using multiplexed imaging techniques. While laser scanning confocal microscopy (LSCM) is a valuable tool for observing single neurons under degenerative conditions, accurately quantifying RNA distribution and cell size by deep learning tools remains challenging due to the lack of annotated training datasets. To address this, we propose a framework that combines 3D tracking of RNA distribution and cell size identification using unsupervised image segmentation. Additionally, we quantified the calcium level in neurons using fluorescent microscopy using unsupervised image segmentation. First, we performed imaging of neuronal morphology using differential interference contrast (DIC) optics and RNA/calcium level imaging using fluorescent microscopy. Next, we performed k-means clustering-based cell segmentation. The results show that our framework can distinguish between distinct neuronal states under control and chronic hypoxic conditions. The analysis reveals that hypoxia induces a significant increase in cytosolic calcium level, reduction in neuron diameter, and alterations in RNA distribution.Clinical Relevance- The proposed framework is crucial to study the neurodegeneration process and evaluating the efficacy of neuroprotective drugs through image analysis.

Non-prophylactic resveratrol-mediated protection of neurite integrity under chronic hypoxia is associated with reduction of Cav1.2 channel expression and calcium overloading.

Cellular hypoxia is a major cause of oxidative stress, culminating in neuronal damage in neurodegenerative diseases. Numerous ex vivo studies have implicated that hypoxia episodes leading to disruption of Ca2+ homeostasis and redox status contribute to the progression of various neuropathologies and cell death. Isolation and maintenance of primary cell culture being cost-intensive, the details of the time course relationship between Ca2+ overload, L-type Ca2+ channel function, and neurite retraction under chronic and long-term hypoxia remain undefined. In order to explore the effect of oxidative stress and Ca2+ overload on neurite length, first, we developed a 5-day-long neurite outgrowth model using N2a cell line. Second, we propose a chronic hypoxia model to investigate the modulation of the L-type Ca2+ channel (Cav1.2) and oxidative resistance gene (OXR1) expression level during the process of neurite retraction and neuronal damage over 32 h. Thirdly, we developed a framework for quantitative analysis of cytosolic Ca2+, superoxide formation, neurite length, and constriction formation in individual cells using live imaging that provides an understanding of molecular targets. Our findings suggest that an increase in cytosolic Ca2+ is a feature of an early phase of hypoxic stress. Further, we demonstrate that augmentation in the L-type channel leads to amplification in Ca2+ overload, ROS accumulation, and a reduction in neurite length during the late phase of hypoxic stress. Next, we demonstrated that non-prophylactic treatment of resveratrol leads to the reduction of calcium overloading under chronic hypoxia via lowering of L-type channel expression. Finally, we demonstrate that resveratrol-mediated reduction of Cav1.2 channel and STAT3 expression are associated with retention of neurite integrity. The proposed in vitro model assumes significance in the context of drug designing and testing that demands monitoring of neurite length and constriction formations by imaging before animal testing.

Three-Dimensional Tracking of Intracellular Calcium and Redox State during Real-Time Control in a Hypoxic Gradient in Microglia Culture: Comparison of the Channel Blocker and Reoxygenation under Ischemic Shock.

Real-time three-dimensional (3-D) imaging is crucial for quantifying correlations among various molecules under acute ischemic stroke. Insights into such correlations may be decisive in selecting molecules capable of providing a protective effect within a shorter period. The major bottleneck is maintaining the cultures under severely hypoxic conditions while simultaneously 3-D imaging intracellular organelles with a microscope. Moreover, comparing the protective effect of drugs and reoxygenation remains challenging. To address this, we propose a novel workflow for the induction of gas-environment-based hypoxia in the HMC-3 cells along with 3-D imaging using laser-scanning-confocal microscopy. The imaging framework is complemented with a pipeline for quantifying time-lapse videos and cell-state classification. First, we show an imaging-based assessment of the in vitro model for hypoxia using a steep gradient in O2 with time. Second, we demonstrate the correlation between mitochondrial superoxide production and cytosolic calcium under acute hypoxia. We then test the efficacy of an L-type calcium channel blocker, compare the results with reoxygenation, and show that the blocker alleviates hypoxic conditions in terms of cytosolic calcium and viability within an acute window of one hour. Furthermore, we show that the drug reduces the expression of oxidative stress markers (HIF1A and OXR1) within the same time window. In the future, this model can also be used to investigate drug toxicity and efficacy under ischemic conditions.

Mapping of structural arrangement of cells and collective calcium transients: an integrated framework combining live cell imaging using confocal microscopy and UMAP-assisted HDBSCAN-based approach.

Live cell calcium (Ca2+) imaging is one of the important tools to record cellular activity during in vitro and in vivo preclinical studies. Specially, high-resolution microscopy can provide valuable dynamic information at the single cell level. One of the major challenges in the implementation of such imaging schemes is to extract quantitative information in the presence of significant heterogeneity in Ca2+ responses attained due to variation in structural arrangement and drug distribution. To fill this gap, we propose time-lapse imaging using spinning disk confocal microscopy and machine learning-enabled framework for automated grouping of Ca2+ spiking patterns. Time series analysis is performed to correlate the drug induced cellular responses to self-assembly pattern present in multicellular systems. The framework is designed to reduce the large-scale dynamic responses using uniform manifold approximation and projection (UMAP). In particular, we propose the suitability of hierarchical DBSCAN (HDBSCAN) in view of reduced number of hyperparameters. We find UMAP-assisted HDBSCAN outperforms existing approaches in terms of clustering accuracy in segregation of Ca2+ spiking patterns. One of the novelties includes the application of non-linear dimension reduction in segregation of the Ca2+ transients with statistical similarity. The proposed pipeline for automation was also proved to be a reproducible and fast method with minimal user input. The algorithm was used to quantify the effect of cellular arrangement and stimulus level on collective Ca2+ responses induced by GPCR targeting drug. The analysis revealed a significant increase in subpopulation containing sustained oscillation corresponding to higher packing density. In contrast to traditional measurement of rise time and decay ratio from Ca2+ transients, the proposed pipeline was used to classify the complex patterns with longer duration and cluster-wise model fitting. The two-step process has a potential implication in deciphering biophysical mechanisms underlying the Ca2+ oscillations in context of structural arrangement between cells.

Quantitative Confocal Microscopy for Grouping of Dose-Response Data: Deciphering Calcium Sequestration and Subsequent Cell Death in the Presence of Excess Norepinephrine.

Fluorescent calcium (Ca2+) imaging is one of the preferred methods to record cellular activity during in vitro preclinical studies, high-content drug screening, and toxicity analysis. Visualization and analysis for dose-response data obtained using high-resolution imaging remain challenging, due to the inherent heterogeneity present in the Ca2+ spiking. To address this challenge, we propose measurement of cytosolic Ca2+ ions using spinning-disk confocal microscopy and machine learning-based analytics that is scalable. First, we implemented uniform manifold approximation and projection (UMAP) for visualizing the multivariate time-series dataset in the two-dimensional (2D) plane using Python. The dataset was obtained through live imaging experiments with norepinephrine-induced Ca2+ oscillation in HeLa cells for a large range of doses. Second, we demonstrate that the proposed framework can be used to depict the grouping of the spiking pattern for lower and higher drug doses. To the best of our knowledge, this is the first attempt at UMAP visualization of the time-series dose response and identification of the Ca2+ signature during lytic death. Such quantitative microscopy can be used as a component of a high-throughput data analysis workflow for toxicity analysis.

GPCR mediated control of calcium dynamics: A systems perspective.

G-protein coupled receptor (GPCR) mediated calcium (Ca2+)-signaling transduction remains crucial in designing drugs for various complex diseases including neurodegeneration, chronic heart failure as well as respiratory diseases. Although there are several reviews detailing various aspects of Ca2+-signaling such as the role of IP3 receptors and Ca2+-induced-Ca2+-release, none of them provide an integrated view of the mathematical descriptions of GPCR signal transduction and investigations on dose-response curves. This article is the first study in reviewing the network structures underlying GPCR signal transduction that control downstream [Cac2+]-oscillations. The central theme of this paper is to present the biochemical pathways, as well as molecular mechanisms underlying the GPCR-mediated Ca2+-dynamics in order to facilitate a better understanding of how agonist concentration is encoded in Ca2+-signals for Gαq, Gαs, and Gαi/o signaling pathways. Moreover, we present the GPCR targeting drugs that are relevant for treating cardiac, respiratory, and neuro-diseases. The current paper presents the ODE formulation for various models along with the detailed schematics of signaling networks. To provide a systems perspective, we present the network motifs that can provide readers an insight into the complex and intriguing science of agonist-mediated Ca2+-dynamics. One of the features of this review is to pinpoint the interplay between positive and negative feedback loops that are involved in controlling intracellular [Cac2+]-oscillations. Furthermore, we review several examples of dose-response curves obtained from [Cac2+]-spiking for various GPCR pathways. This paper is expected to be useful for pharmacologists and computational biologists for designing clinical applications of GPCR targeting drugs through modulation of Ca2+-dynamics.

Cell-to-Cell Variability in Protein Expression during Viral Infection: Monte-Carlo Simulation and Validation based on Confocal Imaging.

One of the major challenges is to identify the statistical model underlying the heterogeneity in viral protein expression in single cells. In this endeavor, we propose a computational tool to address the cell-to-cell variability in protein expression by random variate generation following probability distributions. Here, we show that statistical modeling using the probability density function of various distribution offers considerable potential for providing stochastic inputs to Monte Carlo simulation. Specifically, we present the ranking between three distribution families including gamma, normal and Weibull distribution using a comparison of cumulative frequency obtained from experiment and simulation. The major contribution of the proposed simulation method is to identify the underlying statistical model in kinetic parameters that capture the variability in protein expression in single cells obtained through imaging using confocal microscopy.

Effect of topology and time window on probability distribution underlying baclofen induced Ca2+ response in hippocampal neurons.

Cytosolic Ca2+ oscillation in neurons regulate a wide range of cellular functions starting from cell division to apoptosis. The major challenge in analyzing the large-scale heterogeneous calcium data obtained from hippocampal neurons is that there is no specific tool available for probability density function (pdf) fitting and model ranking. First, we focus on the ranking of various pdf and selection of a particular pdf using maximum log-likelihood. Five pdfs were analyzed in this study, exponential, gamma, log-normal, Rayleigh, and Weibull. Next, we used the statistical models to find the effect of two factors, the network topology and time window for the calcium response. The robustness of the best pdf was validated using multiple datasets obtained through random sampling of neurons from a neuron pool. GPCR targeting drug, baclofen was chosen as the model drug to inhibit Ca2+ response. Strongly-connected neurons show a significant change in Ca2+ oscillations after the addition of drug in comparison to weakly-connected neurons. The proposed technique can be used to study the dose-response from a large number of calcium imaging videos having heterogeneous responses.

Production of phenolic compounds using waste coir pith: Estimation of kinetic and thermodynamic parameters.

The present study illustrates the production of phenolic compounds via slow pyrolysis of coir pith biomass in a bench-scale reactor. The primary objective of the study is to optimize the pyrolysis conditions to maximize the yield of bio-oil and phenolic compounds. Up to 88.14% phenolic compounds were obtained in the organic fraction of the bio-oil obtained at 350 °C. The phenolic compounds thus extracted can be used for the production of phenol-formaldehyde resins, which reduces the dependence on petroleum-based phenols for the manufacturing of resin. An independent kinetic analysis of the apparent pyrolysis reaction was also performed using thermogravimetry and isoconversional methodology. The calculated values of activation energy showed a variation from 28.41 to 200.09 kJ/mol, with the mean value being 140 kJ/mol. The thermodynamic parameters (ΔS, ΔH, and ΔG) were subsequently evaluated at different conversions using the activation energy values obtained from the kinetic analysis.

Automatic Identification of Mixed Retinal Cells in Time-Lapse Fluorescent Microscopy Images using High-Dimensional DBSCAN.

Despite providing high spatial resolution, functional imaging remains largely unsuitable for high-throughput experiments because current practices require cells to be manually identified in a time-consuming procedure. Against this backdrop, we seek to integrate such high-resolution technique in high-throughput workflow by automating the process of cell identification. As a step forward, we attempt to identify mixed retinal cells in time-lapse fluorescent microscopy images. Unfortunately, usual 2D image segmentation as well as other existing methods do not adequately distinguish between time courses of different spatial locations. Here, the task gets further complicated due to the inherent heterogeneity of cell morphology. To overcome such challenge, we propose to use a high-dimensional (HiD) version of DBSCAN (density based spatial clustering of applications with noise) algorithm, where difference in such time courses are appropriately accounted. Significantly, outcome of the proposed method matches manually identified cells with over 80% accuracy, marking more than 50% improvement compared to a reference 2D method.

Co-pyrolysis of phumdi and para grass biomass from Loktak Lake.

In the present work, the pyrolysis of para grass (PG) and phumdi (PH) biomass samples was conducted in the temperature range of 300-500 °C to obtain the optimum temperature for obtaining the maximum yield of bio-oil. Further, co-pyrolysis experiments of PH and PG were also conducted at the same optimized temperature and varied compositions to investigate the synergistic effect. It was observed during the co-pyrolysis, that the maximum bio-oil yield of 37.80 wt% was obtained at the mass ratio of 1:1. The GC-MS, FT-IR and 1H NMR analysis revealed that the bio-oils produced from all the processes were rich in functionalities. Phenolic compounds such as 2-methoxy-4-vinyl phenol, phenol, 2-methoxy, phenol 4-ethyl constituted a significant portion of bio-oils. The biochars obtained at the optimum pyrolytic conditions were analyzed by FT-IR and TOC analyzer.

Effect of composting on the thermal decomposition behavior and kinetic parameters of pig manure-derived solid waste.

In this work, the influence of composting on the thermal decomposition behavior and decomposition kinetics of pig manure-derived solid wastes was analyzed using thermogravimetry. Wheat straw, biochar, zeolite, and wood vinegar were added to pig manure during composting. The composting was done in the 130 L PVC reactors with 100 L effective volume for 50 days. The activation energy of pyrolysis of samples before and after composting was calculated using Friedman's method, while the pre-exponential factor was calculated using Kissinger's equation. It was observed that composting decreased the volatile content of all the samples. The additives when added together in pig manure lead to a reduction in the activation energy of decomposition, advocating the presence of simpler compounds in the compost material in comparison with the complex feedstock.

Thermal decomposition kinetics of sorghum straw via thermogravimetric analysis.

The thermal decomposition of sorghum straw was investigated by non-isothermal thermogravimetric analysis, where the determination of kinetic triplet (activation energy, pre-exponential factor, and reaction model), was the key objective. The activation energy was determined using different isoconversional methods: Friedman, Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), Starink, Iterative method of Chai & Chen, Vyazovkin AIC method, and Li & Tang equation. The pre-exponential factor was calculated using Kissinger's equation; while the reaction model was predicted by comparison of z-master plot obtained from experimental values with the theoretical plots. The values of activation energy obtained from isoconversional methods were further used for evaluation of thermodynamic parameters, enthalpy, entropy and Gibbs free energy. Results showed three zones of pyrolysis having average activation energy values of 151.21kJ/mol, 116.15kJ/mol, and 136.65kJ/mol respectively. The data was well fitting with two-dimension 'Valensi' model for conversion values from 0 to 0.4 with a coefficient of determination (R2) value of 0.988, and with third order reaction model for values from 0.4 to 0.9 with an R2 value of 0.843.