Impact of CNG on emissions of PAHs and PCDDs/Fs from the road transport in Delhi

AbstractIn this paper we present the first estimates and inventory of polycyclic aromatic hydrocarbon (PAH) emissions from mobile sources in megacity Delhi, India for the period 1999–2006. The “COPERT 4” model was used to estimate 23–species of PAHs and 5–congeners of polychlorinated dibenzo–p–dioxins (PCDDs) and dibenzo–furans (PCDFs) from the gasoline, diesel, and CNG (compressed natural gas) fuelled vehicles.Our study shows that the total annual emissions of ∑23–PAHs from road transport has increased ~4 times and emissions of Napthalene (Nap) emerged as the most prominent (8 times), whereas a two-fold increase was seen for the carcinogen benzo[a]pyrene (BaP) and benzo[a]pyrene equivalence (BaPeq) emissions between 1999 and 2006 from the road transport alone. Further increase in total PCDDs and PCDFs by ~3 times can made air quality even worse. Estimated emission share of low molecular weight PAHs (2–ring) has increased (from 43%–85%), whereas vice-versa for ones with high molecular weights. Switch–over to CNG especially for public transport resulted into an offset of 21% emissions of ∑23–PAHs, 14% in BaP, and 15% in BaPeq for the year 2006. It is also observed that the PAH emissions from CNG fuelled vehicles have decreased, but overall increase in the share of private vehicles (1.5 times) has outweighed this benefit

Juvenile granulosa cell tumour: a rare clinical entity

Ovarian cancer is the third most common neoplasm of the female genital tract. Based on the cell type of origin, primary ovarian malignancies are classified into surface epithelium, germ cell, and sex cord tumors. Sex cord tumors account for 1% to 2% of ovarian malignancies. They may contain granulosa cells, theca cells, sertoli cells, or fibroblasts of gonadal stromal origin. Granulosa Cell Tumours (GCTs) account for approximately 2-5% of all ovarian tumors and can be divided into adult (95%) and juvenile (5%) types based on histologic findings. GCTs secrete estrogen thus resulting in menstrual irregularities in the affected individual. More serious estrogen effects can occur in various end organs such as uterus resulting in endometrial hyperplasia, endometrial adenocarcinomas and increased risk of breast cancers. Androgen production is also reported but rare and produces virilization in the affected women. Juvenile Granulosa Cell Tumours (JGCTs) are clinically & histopathologically distinct from the GCTs. They are rarely encountered but mostly in youngsters. Surgery is the primary modality of treatment with chemotherapy being reserved for advanced or recurrent disease states. We herewith report an interesting case of JGCT in a young teenage girl.

Comparison of transvaginal sonography and saline infusion sonohysterography for the diagnosis of causes of abnormal uterine bleeding: a diagnostic accuracy study

Background: Abnormal uterine bleeding (AUB) is one of the frequently observed gynecological problems in outpatient settings. Diagnosis of the cause of AUB is important and hysteroscopy with biopsy is considered is best method for diagnosis of the same. Recent studies suggest the role of transvaginal sonography (TVS) and saline infusion sonohysterography (SIS) for the diagnosis of AUB though data about accuracy and comparison of these techniques with gold standard is not available. The study was designed with the aim of comparison of TVS and SIS for the diagnosis of abnormal uterine bleeding in reference to microscopical examination after hysterectomy.Methods: 100 consecutive patients of AUB were included in the study on the basis of inclusion and exclusion criteria. TVS and SIS were performed on each patient before the surgery for hysterectomy. The findings of TVS and SIS were compared with microscopical examination of the specimen after the hysterectomy. Sensitivity, specificity, positive predictive and negative predictive values were measured.Results: For sub mucosal myoma sensitivity , specificity, positive predictive value, negative predictive value and kappa statistics of SIS were 100%, 100%, 100%, 100%, 1 respectively while for TVS It were 18.1%, 98.8%, 66.6%, 90.7% and 0.25 respectively.Conclusions: SIS has superior diagnostic accuracy and compared to TVS. These findings need to be confirmed by randomized studies with more sample size

Ultrasound guided fine needle aspiration cytology in deep seated lesions: an effective diagnostic tool

Background: Fine needle aspiration cytology (FNAC) is a diagnostic method used to assess various masses in the body with minimal invasion. FNAC alone has a lower yield as compared to biopsy for diagnosing deep-seated lesions. Radiological guidance improves the yield of FNAC. The aim of the study was to evaluate the diagnostic efficacy of Ultrasound (USG) guided FNAC in various deep-seated lesions in the body. We conducted a cross-sectional analytical study at the cytology section of pathology department of our hospital for indoor patients.Methods: It was a retrospective study done over a period of five years, which included 334 aspirates suspected to be of inflammatory or neoplastic origin obtained from deep-seated lesions. After a thorough clinical and radiological evaluation, USG guided FNACs were performed. Experienced pathologists processed the smears, prepared thereby, for cytological evaluation and diagnosis.Results: A total of 334 samples were collected using USG-guided FNAC. The most common site was lungs (36.5%) followed by liver (13.77%). The most common type were malignant lesions (57.19%) which were either primary malignancies or metastatic carcinomas. 29 samples were found to be acellular or had inadequate material, thus a diagnosis couldn’t be made. Out of the various lung masses, non-small cell carcinoma was the most common (66.39%). The most common liver mass was metastatic carcinoma (54.35%).Conclusions: USG guided FNAC is a relatively simple, safe, fast, minimally invasive and cost effective procedure, which provides quite a high rate of adequacy and diagnostic efficacy. It is useful for making a pre-operative diagnosis and guiding the choice of treatment.

Probabilistic Segmentation of Brain Tumors Based on Multi-Modality Magnetic Resonance Images

In this paper, multi-modal Magnetic Resonance (MR) images are integrated into a tissue profile that aims at differentiating tumor components, edema and normal tissue. This is achieved by a tissue classification technique that learns the appearance models of different tissue types based on training samples identified by an expert and assigns tissue labels to each voxel. These tissue classifiers produce probabilistic tissue maps reflecting imaging characteristics of tumors and surrounding tissues that may be employed to aid in diagnosis, tumor boundary delineation, surgery and treatment planning. The main contributions of this work are: 1) conventional structural MR modalities are combined with diffusion tensor imaging data to create an integrated multimodality profile for brain tumors, and 2) in addition to the tumor components of enhancing and non-enhancing tumor types, edema is also characterized as a separate class in our framework. Classification performance is tested on 22 diverse tumor cases using cross-validation

Cascaded Segmentation of Brain Tumors Using Multi-Modality MR Profiles

The accurate identification of the brain tumor boundary and its components is crucial for their effective treatment, but is rendered challenging due to the large variations in tumor size, shape and location, and the inherent inhomogeneity, presence of edema, and infiltration into surrounding tissue. Most of the existing tumor segmentation methods use supervised or unsupervised tissue classification based on the conventional T1 and/or T2 enhanced images and show promising results in differentiating tumor and normal tissues [1-3]. However, perhaps due to the lack of enough MR modalities that could provide a more distinctive appearance signature of each tissue type, these methods have difficulty in differentiating tumor components (enhancing or non-enhancing) and edema. These issues are alleviated by the framework proposed in this paper, that incorporates multi-modal MR images, including the conventional structural MR images and the diffusion tensor imaging (DTI) related maps to create tumor tissue profiles that provide better differentiation between tumor components, edema, and normal tissue types. Tissue profiles are created using pattern classification techniques that learn the multimodal appearance signature of each tissue type by training on expert identified training samples from several patients. The novel use of DTI in the multi-modality framework, helps incorporate the information that tumors grow along white matter tracts [4]. In addition to distinguishing between enhancing and non-enhancing tumors, our framework is also able to identify edema as a separate class, contributing to the solution of tumor boundary detection problem. Tumor segmentation and probabilistic tissue maps generated as a result of applying the classifiers on a new patient reflect the subtle characterizations of tumors and surrounding tissues, and thus could be used to aid tumor diagnosis, tumor boundary identification and tumor surgery planning

ELEMENTS OF MODERN ALGEBRA

ABSTRACT Modern algebra is the study of algebraic structures and also about their properties. Modern algebra is the set of several advanced topics of algebra which deals with the algebraic structures other than the number systems. The important structures of the modern algebraic structures are fields, groups and rings. This study discusses about all the basic elements of the modern algebra such as groups, abelian group, rings and lattices