A novel seasonal index-based machine learning approach for air pollution forecasting.

Novel machine learning models (MLMs) using the seasonal indexing approach that captures the variation in air quality caused due to meteorological changes have been used to provide short-term, real-time forecasts of PM2.5 concentration for one of the most polluted air quality control regions (AQCR) in the capital city of Delhi. Two MLMs-multi-linear regression and random forest-have been developed for using time series data for 1-h and 24-h average PM2.5 concentration. Short-term, real-time forecasts have been made using the developed models. Various model performance evaluation indices indicate satisfactory model performance. R2 values for the hourly and daily models varied between 0.95 and 0.72 and between 0.76 and 0.68 for the 1st to 5th h/day, respectively. The lagged values of PM2.5 concentration (persistence) and the hourly and daily indices are the most influential variables for the forecasts for immediate time steps. In contrast, seasonal indices become more important with the forecasting time horizon. The developed models can be used for making short-term, real-time air quality forecasts and issuing a warning when the pollution levels go beyond acceptable limits.

Individual transducer impulse response characterization method to improve image quality of array-based handheld optoacoustic tomography.

The physical properties of each transducer element play a vital role in the quality of images generated in optoacoustic (photoacoustic) tomography using transducer arrays. Thorough experimental characterization of such systems is often laborious and impractical. A shortcoming of the existing impulse response correction methods, however, is the assumption that all transducers in the array are identical and therefore share one electrical impulse response (EIR). In practice, the EIRs of the transducer elements in the array vary, and the effect of this element-to-element variability on image quality has not been investigated so far, to the best of our knowledge. We hereby propose a robust EIR derivation for individual transducer elements in an array using sparse measurements of the total impulse response (TIR) and by solving the linear system for temporal convolution. Thereafter, we combine a simulated spatial impulse response with the derived individual EIRs to obtain a full characterization of the TIR, which we call individual synthetic TIR. Correcting for individual transducer responses, we demonstrate significant improvement in isotropic resolution, which further enhances the clinical potential of array-based handheld transducers.

Simvastatin and MBCD Inhibit Breast Cancer-Induced Osteoclast Activity by Targeting Osteoclastogenic Factors.

Previous reports have documented that cholesterol-lowering simvastatin prevented osteolytic metastasis of breast cancer in animal model in which cancer cells were placed into blood circulation. Thus, simvastatin treatment might have a preventive effect in inhibiting osteoclast activity of metastatic bone microenvironment. This study documented that both simvastatin and MBCD (cholesterol depleting drug) blocked the breast cancer-induced TRAP and MMP activity, and expressions of various osteoclastogenic genes (TRAP, Cathepsin K, and NFATc1) in pre-osteoclast RAW264.7 cells, and osteoclastogenic CSF-1 and RANKL expressions in breast cancer MCF-7 cells. Thus, these findings unravel a molecular mechanism of simvastatin-/MBCD-mediated inhibition of breast cancer-driven osteoclast activity.

Comparative single-cell profiling reveals distinct cardiac resident macrophages essential for zebrafish heart regeneration.

Zebrafish exhibit a robust ability to regenerate their hearts following injury, and the immune system plays a key role in this process. We previously showed that delaying macrophage recruitment by clodronate liposome (-1d_CL, macrophage-delayed model) impairs neutrophil resolution and heart regeneration, even when the infiltrating macrophage number was restored within the first week post injury (Lai et al., 2017). It is thus intriguing to learn the regenerative macrophage property by comparing these late macrophages vs. control macrophages during cardiac repair. Here, we further investigate the mechanistic insights of heart regeneration by comparing the non-regenerative macrophage-delayed model with regenerative controls. Temporal RNAseq analyses revealed that -1d_CL treatment led to disrupted inflammatory resolution, reactive oxygen species homeostasis, and energy metabolism during cardiac repair. Comparative single-cell RNAseq profiling of inflammatory cells from regenerative vs. non-regenerative hearts further identified heterogeneous macrophages and neutrophils, showing alternative activation and cellular crosstalk leading to neutrophil retention and chronic inflammation. Among macrophages, two residential subpopulations (hbaa+ Mac and timp4.3+ Mac 3) were enriched only in regenerative hearts and barely recovered after +1d_CL treatment. To deplete the resident macrophage without delaying the circulating macrophage recruitment, we established the resident macrophage-deficient model by administrating CL earlier at 8 d (-8d_CL) before cryoinjury. Strikingly, resident macrophage-deficient zebrafish still exhibited defects in revascularization, cardiomyocyte survival, debris clearance, and extracellular matrix remodeling/scar resolution without functional compensation from the circulating/monocyte-derived macrophages. Our results characterized the diverse function and interaction between inflammatory cells and identified unique resident macrophages prerequisite for zebrafish heart regeneration.

Modulation of VEGFA Signaling During Heart Regeneration in Zebrafish.

Over the last decades, myocardial infarction and heart failure have accounted every year for millions of deaths worldwide. After a coronary occlusion, the lack of blood supply to downstream muscle leads to cell death and scarring. To date, several pro-angiogenic factors have been tested to stimulate reperfusion of the affected myocardium, VEGFA being one of the most extensively studied. Given the unsuccessful outcomes of clinical trials, understanding how cardiac revascularization takes place in models with endogenous regenerative capacity holds the key to devising more efficient therapies. Here, we summarize the main findings on VEGFA's role during cardiac repair and regeneration, with a particular focus on zebrafish as a regenerative model. Moreover, we provide a comprehensive overview of available tools to modulate Vegfa expression and action in zebrafish regeneration studies. Understanding the role of Vegfa during zebrafish heart regeneration may help devise efficient therapies and circumvent current limitations in using VEGFA for therapeutic angiogenesis approaches.

Deep-Learning-Based Electrical Noise Removal Enables High Spectral Optoacoustic Contrast in Deep Tissue.

Image contrast in multispectral optoacoustic tomography (MSOT) can be severely reduced by electrical noise and interference in the acquired optoacoustic signals. Previously employed signal processing techniques have proven insufficient to remove the effects of electrical noise because they typically rely on simplified models and fail to capture complex characteristics of signal and noise. Moreover, they often involve time-consuming processing steps that are unsuited for real-time imaging applications. In this work, we develop and demonstrate a discriminative deep learning approach to separate electrical noise from optoacoustic signals prior to image reconstruction. The proposed deep learning algorithm is based on two key features. First, it learns spatiotemporal correlations in both noise and signal by using the entire optoacoustic sinogram as input. Second, it employs training on a large dataset of experimentally acquired pure noise and synthetic optoacoustic signals. We validated the ability of the trained model to accurately remove electrical noise on synthetic data and on optoacoustic images of a phantom and the human breast. We demonstrate significant enhancements of morphological and spectral optoacoustic images reaching 19% higher blood vessel contrast and localized spectral contrast at depths of more than 2 cm for images acquired in vivo. We discuss how the proposed denoising framework is applicable to clinical multispectral optoacoustic tomography and suitable for real-time operation.

A Synthetic Total Impulse Response Characterization Method for Correction of Hand-Held Optoacoustic Images.

The impulse response of optoacoustic (photoacoustic) tomographic imaging system depends on several system components, the characteristics of which can influence the quality of reconstructed images. The effect of these system components on reconstruction quality have not been considered in detail so far. Here we combine sparse measurements of the total impulse response (TIR) with a geometric acoustic model to obtain a full characterization of the TIR of a handheld optoacoustic tomography system with concave limited-view acquisition geometry. We then use this synthetic TIR to reconstruct data from phantoms and healthy human volunteers, demonstrating improvements in image resolution and fidelity. The higher accuracy of optoacoustic tomographic reconstruction with TIR correction further improves the diagnostic capability of handheld optoacoustic tomographic systems.

Portable System for Neuro-Optical Diagnostics Using Virtual Reality Display.

A new product prototype system for diagnosing vision and neurological disorders, called NeuroDotVR, is described herein: this system utilizes a novel wireless NeuroDot brain sensor [Versek C et al. J Neural Eng. 2018 Aug; 15(4):046027] that quantitatively measures visual evoked potentials and fields resulting from custom visual stimuli displayed on a smartphone housed in a virtual reality headset. The NeuroDot brain sensor is unique in that it can be operated both in regular electroencephalography mode, as well as a new electric field encephalography mode, which yields improvements in signal sensitivity and provides new diagnostic information. Steady state and transient visual evoked potentials and fields using reversing checkerboard stimuli are presented with case studies in amblyopia, glaucoma, and dark adaptation. These preliminary data sets highlight potential clinical applications that may be pursued in further product development and scientific studies.

Metformin exhibited anticancer activity by lowering cellular cholesterol content in breast cancer cells.

Metformin, a widely prescribed anti-diabetic drug, shows anticancer activity in various cancer types. Few studies documented that there was a decreased level of LDL and total cholesterol in blood serum of metformin users. Based on these views, this study aimed to determine if metformin exhibits anticancer activity by alleviating cholesterol level in cancer cells. The present study found that treatment of breast cancer MDA-MB-231 cells with metformin significantly decreased cholesterol content with concomitant inhibition of various cholesterol regulatory genes (e.g., HMGCoR, LDLR and SREBP1). Metformin decreased cell viability, migration and stemness in metastatic MDA-MB-231 cells. Similarly, metformin treatment suppressed expressions of anti-apoptotic genes BCL2 and Bcl-xL, and mesenchymal genes vimentin, N-cadherin, Zeb1 and Zeb2 with simultaneous enhancement of apoptotic caspase 3 and Bax, and epithelial genes E-cadherin and keratin 19 expressions, confirming an inhibitory effect of metformin in tumorigenesis. Similar to metformin, depletion of cholesterol by methyl beta cyclodextrin (MBCD) diminished cell viability, migration, EMT and stemness in breast cancer cells. Moreover, metformin-inhibited cell viability, migration, colony and sphere formations were reversed back by cholesterol treatment. Similarly, cholesterol treatment inverted metformin-reduced several gene expressions (e.g., Bcl-xL, BCL2, Zeb1, vimentin, and BMI-1). Additionally, zymography data demonstrated that cholesterol upregulated metformin-suppressed MMP activity. These findings suggested that metformin revealed anticancer activity by lowering of cholesterol content in breast cancer cells. Thus, this study, for the first time, unravelled this additional mechanism of metformin-mediated anticancer activity.

Presence of a consensus DNA motif at nearby DNA sequence of the mutation susceptible CG nucleotides.

Complexity in tissues affected by cancer arises from somatic mutations and epigenetic modifications in the genome. The mutation susceptible hotspots present within the genome indicate a non-random nature and/or a position specific selection of mutation. An association exists between the occurrence of mutations and epigenetic DNA methylation. This study is primarily aimed at determining mutation status, and identifying a signature for predicting mutation prone zones of tumor suppressor (TS) genes. Nearby sequences from the top five positions having a higher mutation frequency in each gene of 42 TS genes were selected from a cosmic database and were considered as mutation prone zones. The conserved motifs present in the mutation prone DNA fragments were identified. Molecular docking studies were done to determine putative interactions between the identified conserved motifs and enzyme methyltransferase DNMT1. Collective analysis of 42 TS genes found GC as the most commonly replaced and AT as the most commonly formed residues after mutation. Analysis of the top 5 mutated positions of each gene (210 DNA segments for 42 TS genes) identified that CG nucleotides of the amino acid codons (e.g., Arginine) are most susceptible to mutation, and found a consensus DNA "T/AGC/GAGGA/TG" sequence present in these mutation prone DNA segments. Similar to TS genes, analysis of 54 oncogenes not only found CG nucleotides of the amino acid Arg as the most susceptible to mutation, but also identified the presence of similar consensus DNA motifs in the mutation prone DNA fragments (270 DNA segments for 54 oncogenes) of oncogenes. Docking studies depicted that, upon binding of DNMT1 methylates to this consensus DNA motif (C residues of CpG islands), mutation was likely to occur. Thus, this study proposes that DNMT1 mediated methylation in chromosomal DNA may decrease if a foreign DNA segment containing this consensus sequence along with CG nucleotides is exogenously introduced to dividing cancer cells.

Colocynth Extracts Prevent Epithelial to Mesenchymal Transition and Stemness of Breast Cancer Cells.

Modern treatment strategies provide better overall survival in cancer patients, primarily by controlling tumor growth. However, off-target and systemic toxicity, tumor recurrence, and resistance to therapy are still inadvertent hurdles in current treatment regimens. Similarly, metastasis is another deadly threat to patients suffering from cancer. This has created an urgent demand to come up with new drugs having anti-metastatic potential and minimum side effects. Thus, this study was aimed at exploring the anti-proliferative and anti-metastatic potential of colocynth medicinal plant. Results from MTT assay, morphological visualization of cells and scratch assay indicated a role of ethanol and acetone extracts of fruit pulp of the colocynth plant in inhibiting cell viability, enhancing cell cytotoxicity and preventing cell migration in various cancer cell types, including breast cancer cell lines MCF-7 and MDA-MB-231, and cervical cancer cell line SiHa, subsequently having a low cytotoxic effect on mononuclear PBMC and macrophage J774A cells. Our study in metastatic MDA-MB-231 cells showed that both ethanol and acetone pulp extracts decreased transcript levels of the anti-apoptotic genes BCL2 and BCLXL, and a reverse effect was observed for the pro-apoptotic genes BAX and caspase 3. Additionally, enhanced caspase 3 activity and downregulated BCL2 protein were seen, indicating a role of these extracts in inducing apoptotic activity. Moreover, MDA-MB-231 cells treated with both these extracts demonstrated up-regulation of the epithelial gene keratin 19 and down-regulation of the mesenchymal genes, vimentin, N-cadherin, Zeb1 and Zeb2 compared to control, suggesting a suppressive impact of these extracts in epithelial to mesenchymal transition (EMT). In addition, these extracts inhibited colony and sphere formation with simultaneous reduction in the transcript level of the stemness associated genes, BMI-1 and CD44. It was also found that both the plant extracts exhibited synergistic potential with the chemotherapeutic drug doxorubicin to inhibit cancer viability. Furthermore, GC-MS/MS analysis revealed the presence of certain novel compounds in both the extracts that are responsible for the anti-cancer role of the extracts. Overall, the results of this report suggest, for the first time, that colocynth fruit pulp extracts may block the proliferative as well as metastatic activity of breast cancer cells.

ImQuant - An image based fluorescence reader for quantitative lateral flow immunoassays.

Fluorescence immunoassays (FIA) have strong potential in enabling rapid quantitative immunological testing at point of care. Existing state of the art instruments employ laser scanning of FIA test kits, which require the use of electromechanical systems, making the instrument bulky, heavy and less reliable in the long term. There is a growing need for an extremely compact and reliable, motion-free, automated reader for accurate quantification of immunoassays. Here, we present ImQuant, an image based FIA reader with integrated monochromatic excitation source, optical filtering and real time image capture, assisted with an intuitive graphical user interface. A 12bit dynamic range RAW ouput CMOS camera with 1/3" sensor format and a sharp cut off wideband filter were utilized to ensure improved accuracy. A laboratory prototype was constructed and tested using a set of stable reference cartridges that provided repeatable fluorescent lines. The ImQuant could capture the lines and measure area ratios with coefficient of variation (CV) less than 2%. Further, tests with blood samples on Quanti® HbA1C test kits also demonstrated good repeatability with CV<;2%. The ImQuant is a novel platform of motion-free fluorescent scanning of FIA immunoassays and is being used for developing a variety of test kits and instruments.

Multi-Path Model and Sensitivity Analysis for Galvanic Coupled Intra-Body Communication Through Layered Tissue.

New medical procedures promise continuous patient monitoring and drug delivery through implanted sensors and actuators. When over the air wireless radio frequency (OTA-RF) links are used for intra-body implant communication, the network incurs heavy energy costs owing to absorption within the human tissue. With this motivation, we explore an alternate form of intra-body communication that relies on weak electrical signals, instead of OTA-RF. To demonstrate the feasibility of this new paradigm for enabling communication between sensors and actuators embedded within the tissue, or placed on the surface of the skin, we develop a rigorous analytical model based on galvanic coupling of low energy signals. The main contributions in this paper are: (i) developing a suite of analytical expressions for modeling the resulting communication channel for weak electrical signals in a three dimensional multi-layered tissue structure, (ii) validating and verifying the model through extensive finite element simulations, published measurements in existing literature, and experiments conducted with porcine tissue, (iii) designing the communication framework with safety considerations, and analyzing the influence of different network and hardware parameters such as transmission frequency and electrode placements. Our results reveal a close agreement between theory, simulation, literature and experimental findings, pointing to the suitability of the model for quick and accurate channel characterization and parameter estimation for networked and implanted sensors.

Image based quantitative reader for Lateral flow immunofluorescence assay.

Fluorescence Lateral flow immunoassays (LFIA) have wide range of applications in point-of-care testing (POCT). An integrated, motion-free, accurate, reliable reader that performs automated quantitative analysis of LFIA is essential for POCT diagnosis. We demonstrate an image based quantitative method to read the lateral flow immunofluorescence test strips. The developed reader uses line laser diode module to illuminate the LFIA test strip having fluorescent dye. Fluorescence light coming from the region of interest (ROI) of the LFIA test strip was filtered using an emission filter and imaged using a camera following which images were processed in computer. A dedicated control program was developed that automated the entire process including illumination of the test strip using laser diode, capturing the ROI of the test strip, processing and analyzing the images and displaying of results. Reproducibility of the reader has been evaluated using few reference cartridges and HbA1c (Glycated haemoglobin) test cartridges. The proposed system can be upgraded to a compact reader for widespread testing of LFIA test strips.