Elimination of Specular reflection and Identification of ROI: The First Step in Automated Detection of Cervical Cancer using Digital Colposcopy

Cervical Cancer is one of the most common forms of cancer in women worldwide. Most cases of cervical cancer can be prevented through screening programs aimed at detecting precancerous lesions. During Digital Colposcopy, Specular Reflections (SR) appear as bright spots heavily saturated with white light. These occur due to the presence of moisture on the uneven cervix surface, which act like mirrors reflecting light from the illumination source. Apart from camouflaging the actual features, the SR also affects subsequent segmentation routines and hence must be removed. Our novel technique eliminates the SR and makes the colposcopic images (cervigram) ready for segmentation algorithms. The cervix region occupies about half of the cervigram image. Other parts of the image contain irrelevant information, such as equipment, frames, text and non-cervix tissues. This irrelevant information can confuse automatic identification of the tissues within the cervix. The first step is, therefore, focusing on the cervical borders, so that we have a geometric boundary on the relevant image area. We have proposed a type of modified kmeans clustering algorithm to evaluate the region of interest.Comment: IEEE Imaging Systems and Techniques, 2011, Print ISBN: 978-1-61284-894-5, pages 237 - 24

Evaluation of efficacy of BIORAD D10TM testing system in detection of beta thalassaemia carrier

Background: Hemoglobinopathies especially thalassaemia and its interaction with HbE and HbS are significant cause of morbidity and mortality in our country. With no feasible treatment, prevention of cases by carrier detection is the only option for successful reduction of the disease burden. VARIANT hemoglobin testing system BIORAD using principle of cation exchange chromatography has been in use and considered as gold standard for carrier detection. The purpose of this study is to compare the efficacy of a different, cheaper instrument; D10 by the same manufacturer BIORAD for carrier detection in beta thalassaemia.Methods: Patients diagnosed as beta thalassaemia carrier by VARIANT hemoglobin testing system (HbA2 value between 4.0-9.0) were retested using D10 instrument and checked for agreement.Results: There was good correlation between VARIANT and D-10 methods with Intraclass correlation coefficient 0.832 (95% Confidence Interval 0.756-0.884). Bland-Altman analysis showed mean bias of +0.3526 (95% CI -0.3958 to +1.101).Conclusions: Although further study is needed with larger sample size for assessment of sensitivity and specificity of D10 instrument, it is evident from this study that this instrument can be an effective and cheaper alternative of VARIANT hemoglobin testing system

Association of cannabis with glutamatergic levels in patients with early psychosis: Evidence for altered volume striatal glutamate relationships in patients with a history of cannabis use in early psychosis

The associative striatum, an established substrate in psychosis, receives widespread glutamatergic projections. We sought to see if glutamatergic indices are altered between early psychosis patients with and without a history of cannabis use and characterise the relationship to grey matter. 92 participants were scanned: Early Psychosis with a history of cannabis use (EPC\u2009=\u200929); Early Psychosis with minimal cannabis use (EPMC\u2009=\u200925); Controls with a history of cannabis use (HCC\u2009=\u200916) and Controls with minimal use (HCMC\u2009=\u200922). Whole brain T1 weighted MR images and localised proton MR spectra were acquired from head of caudate, anterior cingulate and hippocampus. We examined relationships in regions with known high cannabinoid 1 receptor (CB1R) expression (grey matter, cortex, hippocampus, amygdala) and low expression (white matter, ventricles, brainstem) to caudate Glutamine+Glutamate (Glx). Patients were well matched in symptoms, function and medication. There was no significant group difference in Glx in any region. In EPC grey matter volume explained 31.9% of the variance of caudate Glx (p\u2009=\u20090.003) and amygdala volume explained 36.9% (p\u2009=\u20090.001) of caudate Glx. There was no significant relationship in EPMC. The EPC vs EPMC interaction was significant (p\u2009=\u20090.042). There was no such relationship in control regions. These results are the first to demonstrate association of grey matter volume and striatal glutamate in the EPC group. This may suggest a history of cannabis use leads to a conformational change in distal CB1 rich grey matter regions to influence striatal glutamatergic levels or that such connectivity predisposes to heavy cannabis use

Cannabis use in patients with early psychosis is associated with alterations in putamen and thalamic shape

Around half of patients with early psychosis have a history of cannabis use. We aimed to determine if there are neurobiological differences in these the subgroups of persons with psychosis with and without a history of cannabis use. We expected to see regional deflations in hippocampus as a neurotoxic effect and regional inflations in striatal regions implicated in addictive processes. Volumetric, T1w MRIs were acquired from people with a diagnosis psychosis with (PwP + C = 28) or without (PwP − C = 26) a history of cannabis use; and Controls with (C + C = 16) or without (C − C = 22) cannabis use. We undertook vertex‐based shape analysis of the brainstem, amygdala, hippocampus, globus pallidus, nucleus accumbens, caudate, putamen, thalamus using FSL FIRST. Clusters were defined through Threshold Free Cluster Enhancement and Family Wise Error was set at p < .05. We adjusted analyses for age, sex, tobacco and alcohol use. The putamen (bilaterally) and the right thalamus showed regional enlargement in PwP + C versus PwP − C. There were no areas of regional deflation. There were no significant differences between C + C and C − C. Cannabis use in participants with psychosis is associated with morphological alterations in subcortical structures. Putamen and thalamic enlargement may be related to compulsivity in patients with a history of cannabis use

Determination of bioavailable arsenic threshold and validation of modelled permissible total arsenic in paddy soil using machine learning

Minimizing arsenic intake from food consumption is a key aspect of the public health response in As-contaminated regions. In many of these regions, rice is the predominant staple food. Here we present a validated maximum allowable concentration of total As in paddy soil and provide the first derivation of a maximum allowable soil concentration for bioavailable As. We have previously used meta-analysis to predict the maximum allowable total As in soil based on decision tree (DT) and logistic regression (LR) models. The models were defined using the maximum tolerable concentration (MTC) of As in rice grains as per the codex recommendation. In the present study, we validated these models using three test data sets derived from purposely collected field data. The DT model performed better than the LR in terms of accuracy and Matthews correlation coefficient (MCC). Therefore, the DT estimated maximum allowable total As in paddy soil of 14 mg kg−1 could confidently be used as appropriate guideline value. We further used the purposely collected field data to predict the concentration of bioavailable As in the paddy soil with the help of random forest (RF), gradient boosting machine (GBM) and LR models. The category of grain As (MTC) was considered as the dependent variable; bioavailable As (BAs), total As (TAs), pH, organic carbon (OC), available phosphorus (AvP) and available iron (AvFe) were the predictor variables. LR performed better than RF and GBM in terms of accuracy, sensitivity, specificity, kappa, precision, log loss, F1score and MCC. From the better performing LR model, bioavailable As (BAs), TAs, AvFe and OC were significant variables for grain As. From the partial dependence plots (PDP) and individual conditional expectation (ICE) of the LR model, 5.70 mg kg−1 was estimated to be the limit for BAs in soil

Association of cannabis with glutamatergic levels in patients with early psychosis: Evidence for altered volume striatal glutamate relationships in patients with a history of cannabis use in early psychosis

he associative striatum, an established substrate in psychosis, receives widespread glutamatergic projections. We sought to see if glutamatergic indices are altered between early psychosis patients with and without a history of cannabis use and characterise the relationship to grey matter. 92 participants were scanned: Early Psychosis with a history of cannabis use (EPC = 29); Early Psychosis with minimal cannabis use (EPMC = 25); Controls with a history of cannabis use (HCC = 16) and Controls with minimal use (HCMC = 22). Whole brain T1 weighted MR images and localised proton MR spectra were acquired from head of caudate, anterior cingulate and hippocampus. We examined relationships in regions with known high cannabinoid 1 receptor (CB1R) expression (grey matter, cortex, hippocampus, amygdala) and low expression (white matter, ventricles, brainstem) to caudate Glutamine+Glutamate (Glx). Patients were well matched in symptoms, function and medication. There was no significant group difference in Glx in any region. In EPC grey matter volume explained 31.9% of the variance of caudate Glx (p = 0.003) and amygdala volume explained 36.9% (p = 0.001) of caudate Glx. There was no significant relationship in EPMC. The EPC vs EPMC interaction was significant (p = 0.042). There was no such relationship in control regions. These results are the first to demonstrate association of grey matter volume and striatal glutamate in the EPC group. This may suggest a history of cannabis use leads to a conformational change in distal CB1 rich grey matter regions to influence striatal glutamatergic levels or that such connectivity predisposes to heavy cannabis use

Transcriptomic and metabolomic shifts in rice roots in response to Cr (VI) stress

<p>Abstract</p> <p>Background</p> <p>Widespread use of chromium (Cr) contaminated fields due to careless and inappropriate management practices of effluent discharge, mostly from industries related to metallurgy, electroplating, production of paints and pigments, tanning, and wood preservation elevates its concentration in surface soil and eventually into rice plants and grains. In spite of many previous studies having been conducted on the effects of chromium stress, the precise molecular mechanisms related to both the effects of chromium phytotoxicity, the defense reactions of plants against chromium exposure as well as translocation and accumulation in rice remain poorly understood.</p> <p>Results</p> <p>Detailed analysis of genome-wide transcriptome profiling in rice root is reported here, following Cr-plant interaction. Such studies are important for the identification of genes responsible for tolerance, accumulation and defense response in plants with respect to Cr stress. Rice root metabolome analysis was also carried out to relate differential transcriptome data to biological processes affected by Cr (VI) stress in rice. To check whether the Cr-specific motifs were indeed significantly over represented in the promoter regions of Cr-responsive genes, occurrence of these motifs in whole genome sequence was carried out. In the background of whole genome, the lift value for these 14 and 13 motifs was significantly high in the test dataset. Though no functional role has been assigned to any of the motifs, but all of these are present as promoter motifs in the Database of orthologus promoters.</p> <p>Conclusion</p> <p>These findings clearly suggest that a complex network of regulatory pathways modulates Cr-response of rice. The integrated matrix of both transcriptome and metabolome data after suitable normalization and initial calculations provided us a visual picture of the correlations between components. Predominance of different motifs in the subsets of genes suggests the involvement of motif-specific transcription modulating proteins in Cr stress response of rice.</p