Correction: Deep-Fuzz: A synergistic integration of deep learning and fuzzy water flows for fine-grained nuclei segmentation in digital pathology.

[This corrects the article DOI: 10.1371/journal.pone.0286862.].

Deep-Fuzz: A synergistic integration of deep learning and fuzzy water flows for fine-grained nuclei segmentation in digital pathology.

Robust semantic segmentation of tumour micro-environment is one of the major open challenges in machine learning enabled computational pathology. Though deep learning based systems have made significant progress, their task agnostic data driven approach often lacks the contextual grounding necessary in biomedical applications. We present a novel fuzzy water flow scheme that takes the coarse segmentation output of a base deep learning framework to then provide a more fine-grained and instance level robust segmentation output. Our two stage synergistic segmentation method, Deep-Fuzz, works especially well for overlapping objects, and achieves state-of-the-art performance in four public cell nuclei segmentation datasets. We also show through visual examples how our final output is better aligned with pathological insights, and thus more clinically interpretable.

Instrument-free single-step direct estimation of the plasma glucose level from one drop of blood using smartphone-interfaced analytics on a paper strip.

We demonstrated an instrument-free miniaturized adaptation of the laboratory gold standard methodology for the direct estimation of plasma glucose from a drop of whole blood using a low-cost single-user-step paper-strip sensor interfaced with a smartphone. Unlike a majority of the existing glucose meters that use whole blood-based indirect sensing technologies, our direct adaptation of the gold-standard laboratory benchmark could eliminate the possibilities of cross interference with other analytes present in the whole blood by facilitating an in situ plasma separation, capillary flow and colorimetric reaction occurring concomitantly, without incurring additional device complexity or embodiment. The test reagents were dispensed in lyophilized form, and the resulting paper strips were found to be stable over three months stored in a normal freezer, rendering easy adaptability commensurate with the constrained supply chains in extreme resource-poor settings. Quantitative results could be arrived at via a completely-automated mobile-app-based image analytics interface developed using dynamic machine learning, obviating manual interpretation. The tests were demonstrated to be of high efficacy, even when executed by minimally trained frontline personnel having no special skill of drawing precise volume of blood, on deployment at under-resourced community centres having no in-built or accessible healthcare infrastructure. Clinical validation using 220 numbers of human blood samples in a double-blinded manner evidenced sensitivity and specificity of 98.11% and 96.7%, respectively, as compared to the results obtained from a laboratory-benchmarked biochemistry analyser, establishing its efficacy for public health and community disease management in resource-limited settings without any quality compromise of the test outcome.

Smartphone-Enabled Paper-Based Hemoglobin Sensor for Extreme Point-of-Care Diagnostics.

We report a simple, affordable (∼0.02 US $/test), rapid (within 5 min), and quantitative paper-based sensor integrated with smartphone application for on-spot detection of hemoglobin (Hgb) concentration using approximately 10 µL of finger-pricked blood. Quantitative analytical colorimetry is achieved via an Android-based application (Sens-Hb), integrating key operational steps of image acquisition, real-time analysis, and result dissemination. Further, feedback from the machine learning algorithm for adaptation of calibration data offers consistent dynamic improvement for precise predictions of the test results. Our study reveals a successful deployment of the extreme point-of-care test in rural settings where no infrastructural facilities for diagnostics are available. The Hgb test device is validated both in the controlled laboratory environment (n = 200) and on the field experiments (n = 142) executed in four different Indian villages. Validation results are well correlated with the pathological gold standard results (r = 0.9583) with high sensitivity and specificity for the healthy (n = 136) (>11 g/dL) (specificity: 97.2%), mildly anemic (n = 55) (<11 g/dL) (sensitivity: 87.5%, specificity: 100%), and severely anemic (n = 9) (<7 g/dL) (sensitivity: 100%, specificity: 100%) samples. Results from field trials reveal that only below 5% cases of the results are interpreted erroneously by classifying mildly anemic patients as healthy ones. On-field deployment has unveiled the test kit to be extremely user friendly that can be handled by minimally trained frontline workers for catering the needs of the underserved communities.

Evaluation of oxidative stress and the microenvironment in oral submucous fibrosis.

BACKGROUND: Oral Submucous fibrosis (OSF) is a chronic inflammatory mucosal disease of unknown etiology. Statistics show cases of OSF which has a high rate of overall prevalence and increase the chance of malignant transformation. As we know malignant cells is situated in a very complex microenvironment with altered metabolic pathway including intermediates which participate in oxidative stress process which enhances metabolic rewiring and promotes tumor progression. This study aims to evaluate the tumor microenvironment and their role in metabolic reprogramming. METHODS: This study was conducted on the serum sample of OSF (n = 20) compared to the healthy group (n = 20) using ELISA. The serum levels of intermediate by-products of metabolic pathway and oxidative stress induced biomolecular damage products were determined. The sensitivity of results was analyzed by correlating it with markers of metabolic status (Glucose, Total cholesterol, Total protein). RESULTS: Metabolic pathway intermediates molecules like Fatty Acids (FAA), Ascorbic acid, Citrate, Oxaloacetate (OAA), levels were significantly high in the serum of OSF cases. This indicated that intermediates act as a metabolic switch that drives cells to adapt malignant transformation pathway. Markers related to oxidative DNA damage (8-hydroxy-2' -deoxyguanosine), Oxidative lipid peroxidation (8-epi-Prostaglandin F2α), and Protein carbonyl were significantly up-regulated. This significant increase in oxidative stress marker revealed the reprogramming of the metabolic pathway for fulfilling the nutritional requirement of cancer cells. A further significant correlation was observed with metabolic products confirmed altered metabolic status. CONCLUSION: Our findings could identify the differentiating intermediate pathway metabolites and oxidative damage to biomolecules that are leading to rewiring of metabolism in the OSF group. Findings described in the study can be helpful to explain further the molecular aspects that lead to the progression of OSF towards carcinogenesis.

Delineating metabolic dysfunction in cellular metabolism of oral submucous fibrosis using 1H nuclear magnetic resonance spectroscopy.

OBJECTIVE: To delineate the metabolism involved in oral submucous fibrosis progression towards carcinogenesis by 1H nuclear magnetic resonance spectroscopy. METHODS: The proposed study was designed using 1H-NMR by comparing the metabolites in the serum sample of oral submucous fibrosis (n = 20) compared to the normal group (n = 20) using 1H nuclear magnetic resonance spectroscopy. Various statistical analysis like multivariate statistical analysis, Principle component analysis, Partial least squares Discriminant Analysis, Hierarchical cluster analysis was applied to analyze potential serum metabolites. RESULTS: The results generated from the principle component analysis, partial least squares discriminant analysis and hierarchical cluster analysis are sufficient to distinguish between oral submucous fibrosis group and normal group. A total of 15 significant metabolites associated with main pathways were identified, which correlated with the progression of cancer. Up-regulation of glucose metabolism-related metabolites indicated the high energy demand due to enhanced cell division rate in the oral submucous fibrosis group. A significant increase in lipid metabolism-related metabolites revealed the reprogramming of the fatty acids metabolic pathway to fulfilling the need for cell membrane formation in cancer cells. On the other hand, metabolites related to choline phosphocholine, the metabolic pathway was also altered. CONCLUSION: Our findings could identify the differentiating metabolites in the oral submucous fibrosis group. Significant alteration in metabolites in the oral submucous fibrosis group exhibited deregulation in metabolic events. The findings reported in the study can be beneficial to further explain the molecular aspects that lead to the progression of oral submucous fibrosis towards carcinogenesis.

2dSpAn: semiautomated 2-d segmentation, classification and analysis of hippocampal dendritic spine plasticity.

MOTIVATION: Accurate and effective dendritic spine segmentation from the dendrites remains as a challenge for current neuroimaging research community. In this article, we present a new method (2dSpAn) for 2-d segmentation, classification and analysis of structural/plastic changes of hippocampal dendritic spines. A user interactive segmentation method with convolution kernels is designed to segment the spines from the dendrites. Formal morphological definitions are presented to describe key attributes related to the shape of segmented spines. Spines are automatically classified into one of four classes: Stubby, Filopodia, Mushroom and Spine-head Protrusions. RESULTS: The developed method is validated using confocal light microscopy images of dendritic spines from dissociated hippocampal cultures for: (i) quantitative analysis of spine morphological changes, (ii) reproducibility analysis for assessment of user-independence of the developed software and (iii) accuracy analysis with respect to the manually labeled ground truth images, and also with respect to the available state of the art. The developed method is monitored and used to precisely describe the morphology of individual spines in real-time experiments, i.e. consequent images of the same dendritic fragment. AVAILABILITY AND IMPLEMENTATION: The software and the source code are available at https://sites.google.com/site/2dspan/ under open-source license for non-commercial use. CONTACT: subhadip@cse.jdvu.ac.in or j.wlodarczyk@nencki.gov.pl SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CD-Based Microfluidics for Primary Care in Extreme Point-of-Care Settings.

We review the utility of centrifugal microfluidic technologies applied to point-of-care diagnosis in extremely under-resourced environments. The various challenges faced in these settings are showcased, using areas in India and Africa as examples. Measures for the ability of integrated devices to effectively address point-of-care challenges are highlighted, and centrifugal, often termed CD-based microfluidic technologies, technologies are presented as a promising platform to address these challenges. We describe the advantages of centrifugal liquid handling, as well as the ability of a standard CD player to perform a number of common laboratory tests, fulfilling the role of an integrated lab-on-a-CD. Innovative centrifugal approaches for point-of-care in extremely resource-poor settings are highlighted, including sensing and detection strategies, smart power sources and biomimetic inspiration for environmental control. The evolution of centrifugal microfluidics, along with examples of commercial and advanced prototype centrifugal microfluidic systems, is presented, illustrating the success of deployment at the point-of-care. A close fit of emerging centrifugal systems to address a critical panel of tests for under-resourced clinic settings, formulated by medical experts, is demonstrated. This emphasizes the potential of centrifugal microfluidic technologies to be applied effectively to extremely challenging point-of-care scenarios and in playing a role in improving primary care in resource-limited settings across the developing world.