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Page kidney is a rare but potentially curable cause of secondary hypertension. While the pancreatic pseudocyst is a completely different and unrelated entity. Here, we report a case of a 45-year-old female, diagnosed with idiopathic acute pancreatitis with multiple pseudocysts. After successful ultrasound -guided drainage of her left subcapsular renal pseudocyst, she became normotensive again, confirming the diagnosis of page kidney. This case highlights dual reasons that prompted us to report the case. The first being such remotely located subcapsular renal pseudocyst as itself a rare entity and the second, its unusual presentation as page kidney. The case emphasizes on the early management of such patients so as to salvage renal function.

The Covid-19 also known as the Coronavirus is a viral disease from the SARS-CoV-2 family of virus, as at December 2019 the first case of this virus infection was identified at Wuhan, China, this seemingly isolated case soon became a global pandemic, whose effect was felt globally which also had colossal effects on both health, economic and politics . As at the time of this research about 4.5 million people have died of the Coronavirus and over 215 million people already infected by it. This pandemic stood out not just for its scale but for how social media was a major contribution to its spread as well as to curbing it. The power of social media was used to spread misinformation as well as to spread awareness on the subject, with both having massive impact on the people. In this paper we will be running a sentimental analysis on twitter under the keyword “Covid-19 and Coronavirus”, twitter is a powerful social media tool that is known for its ability to keep trends in the form of tweets, we will be drawing correlations between the peaks of tweet with the peak of infection. We will also be analyzing to know what the impact of these tweets are having on the rate of the infection and vice versa. We will also be analyzing what people are tweeting most about, what are the talking points, comparing both real time and past tweets with real time infection and death rates using deep different learning methods to access what information can be derived from it.

SummaryMarfan syndrome is multisystem connective tissue disorder that primarily involves the skeletal, cardiovascular, and ocular systems. The gastrointestinal complications in Marfan syndrome are rare, with only a few case reports described in the literature. We present a 25-year-old woman who presented with acute abdominal pain for 1 day. The imaging features revealed complex diaphragmatic hiatus hernia with organoaxial gastric volvulus. This is a unique case report about an adult patient with Marfan syndrome who presented with symptomatic paraesophageal hernia and organoaxial gastric volvulus.

The present work proposes a classification framework for the prediction of breast density using an ensemble of neural network classifiers. Expert radiologists, visualize the textural characteristics of center region of a breast to distinguish between different breast density classes. Accordingly, ROIs of fixed size are cropped from the center location of the breast tissue and GLCM mean features are computed for each ROI by varying inter-pixel distance ‘d’ from 1 to 15. The proposed classification framework consists of two stages, (a) first stage: this stage consists of a single 4-class neural network classifier NN0 (B-I/B-II/B-III/B-IV) which yields the output probability vector [PB-I PB-II PB-III PB-IV] indicating the probability values with which a test ROI belongs to a particular breast density class. (b) second stage: this stage consists of an ensemble of six binary neural network classifiers NN1 (B-I/B-II), NN2 (B-I/B-III), NN3 (B-I/B-IV), NN4 (B-II/B-III), NN5 (B-II/B-IV) and NN6 (B-III/B-IV). The output of the first stage of the classification framework, i.e. output on NN0 is used to obtain the two most probable classes for a test ROI. In the second stage this test ROI is passed through one of the binary neural networks, i.e. NN1 to NN6 corresponding to the two most probable classes predicted by NN0. After passing the entire test ROIs through the second stage, the overall accuracy increases from 79.5% to 90.8%. The promising results achieved by the proposed classification framework indicate that it can be used in clinical environment for differentiation between breast density patterns.

Breast cancer ranks second as the major cause of death due to cancer among women. The disease's mortality rate has decreased over the last few years, and this is believed to be due to early detection, greater awareness, and better treatments. This paper deals with the classification of breast mammograms and the effect of different enhancement techniques on classification accuracy. The algorithm proposed in this study to classify mammograms on the basis of normal and abnormal comprises the following five steps: image database, preprocessing using image enhancement techniques, ROI extraction, texture feature extraction using the Gabor filter, and finally, classification using the SVM classifier. The effect of 14 enhancement methods, namely, alpha trimmed mean filter, contrast adjustment, contrast limited adaptive histogram equalization, contra-harmonic mean filter, hybrid median filter, histogram equalization, morphological enhancement, mean filter, median filter, recursive mean separated histogram equalization, unsharp masking, wavelet based subband filter, morphological enhancement followed by contrast adjustment, and a combination of unsharp masking and contrast adjustment is demonstrated in this study. The work is performed on the MIAS database consisting of 322 mammogram images. ROIs of size 32 × 32 pixels are cropped from the enhanced images and a set of Gabor filters with three different scales and seven orientations is applied to extract features from the cropped ROIs. These features are used to classify abnormal ROIs from normal using SVM. A combination of morphological enhancement and contrast stretching results in the best overall classification accuracy of 92.16%, with individual class accuracy (abnormal) at 90.2% and individual class accuracy (normal) at 94.12%. The feature set derived from these images is further subjected to a GA-SVM feature selection procedure. It is observed that only 21 selected features are significant to classify the screen film mammographic images enhanced by morphological enhancement and contrast stretching.

This work proposes a 4-class breast tissue pattern classification using principal component analysis (PCA) and weighted score fusion of neural network classifiers. The fixed size ROIs are extorted from the middle of the breast around the glandular ducts for 480 mammographic images acquired from Digital Database for Screening Mammography. The GLCMmean feature descriptors are figured out for every input sample, i.e., ROI for {d ϵ [1, 2, …,15]} where d is known as interpixel distance. The proposed breast density classification system consisting of 2-stages, (i) stage one: It consists of single 4-class PCA-NN1,2,3,4, which yields the probability score vector that indicates the probability score to test the belongings of an ROI to a specific class; (ii) stage two: this stage consists of six binary PCA-NN classifiers for classification between individual BIRADS classes. After passing all testing instances through stage two, the obtained accuracy is 92.1% with ICA values of 96.6%, 91.6%, 80.0%, and 100% for B1, B2, B3, and B4 classes respectively. It can be observed that after passing all testing instances through stage two, the accuracy boost is from 79.6% to 92.1%.

We investigate the prospect of constraining scalar field dark energy models using HI 21-cm intensity mapping surveys. We consider a wide class of coupled scalar field dark energy models whose predictions about the background cosmological evolution are different from the $\Lambda$CDM predictions by a few percent. We find that these models can be statistically distinguished from $\Lambda$CDM through their imprint on the 21-cm angular power spectrum. At the fiducial $z= 1.5$, corresponding to a radio interferometric observation of the post-reionization HI 21 cm observation at frequency $568 \rm MHz$, these models can infact be distinguished from the $\Lambda$CDM model at $ {\rm SNR }> 3 \sigma$ level using a 10,000 hr radio observation distributed over 40 pointings of a SKA1-mid like radio-telescope. We also show that tracker models are more likely to be ruled out in comparison with $\Lambda$CDM than the thawer models. Future radio observations can be instrumental in obtaining tighter constraints on the parameter space of dark energy models and supplement the bounds obtained from background studies., Comment: 10 pages, mnras style, 11 eps figures. Spelling mistake in author name is corrected

In the present work, three-class breast tissue density classification has been carried out using SVM-based hierarchical classifier. The performance of Laws’ texture descriptors of various resolutions have been investigated for differentiating between fatty and dense tissues as well as for differentiation between fatty-glandular and dense-glandular tissues. The overall classification accuracy of 88.2% has been achieved using the proposed SVM-based hierarchical classifier.

Display Omitted Identification of bacteriocin secretors lactic acid bacteria and biosynthetic gene with bioinformatic tools.Phylogenetic tree of LAB with 16S rRNA, rpoB and gyrB (housekeeping genes) by MEGA6 tool.Physiochemical and secondary structure analysis of putative strains by computational methodology. Bacteriocins are antimicrobial peptides which are ribosomally synthesized by mainly all bacterial species. LABs (lactic acid bacteria) are a diverse group of bacteria that include around 20 genera of various species. Though LABs have a tremendous potential for production of anti-microbial peptides, this group of bacteria is still underexplored for bacteriocins. To study the diversity among bacteriocin encoding clusters and the putative bacteriocin precursors, genome mining was performed on 20 different species of LAB not reported to be bacteriocin producers. The phylogenetic tree of gyrB, rpoB, and 16S rRNA were constructed using MEGA6 software to analyze the diversity among strains. Putative bacteriocins operons identified were found to be diverse and were further characterized on the basis of physiochemical properties and the secondary structure. The presence of at least two cysteine residues in most of the observed putative bacteriocins leads to disulphide bond formation and provide stability. Our data suggests that LABs are prolific source of low molecular weight non modified peptides.

Puerperal uterine inversion is a rare and potentially life-threatening complication of a mismanaged third stage of labour. Early diagnosis is mandatory for proper management of the patient. Complete uterine inversion is a clinical diagnosis. However, incomplete uterine inversion is difficult to identify and warrants further workup. Sonographic evaluation, although a bedside procedure, may be confusing. The conspicuity of findings is much greater on MR examination than on ultrasound. Only a few diagnostic imaging findings in uterine inversion have been described in previous reports. We present the case of a 26-year-old woman who had a full-term vaginal delivery and presented after 20 days with acute urinary retention and mild vaginal bleeding. She was diagnosed as a case of neglected subacute incomplete uterine inversion. Both greyscale and Doppler sonographic and MR features of the case are described with an emphasis on better delineation of uterine and adnexal anatomy on MR imaging.

Caroli’s disease is autosomal recessive, non-obstructive dilatation of intrahepatic biliary ducts. The exact etiology is unclear. Two variants of Caroli’s disease are well known-simple; in which bile ducts are dilated without hepatic fibrosis and the second type which is associated with congenital hepatic fibrosis along with its sequelae, also known as Caroli’s syndrome. Simple Caroli’s disease without hepatic fibrosis is quite rare. The importance of recognizing this disease as a cause of biliary stasis is its frequent association with lithiasis, recurrent cholangitis, liver abscesses, cirrhosis and cholangiocarcinoma.

Aim The purpose of the study was to describe the enhancement patterns of focal liver lesions (FLLs) on contrast enhanced sonography (CEUS), assessing the potential of this technique for characterizing the lesions and to compare its diagnostic accuracy with conventional baseline sonography including color Doppler. Materials and methods Between August 2009 and July 2010, 50 patients with FLLs underwent gray scale sonography, color Doppler and CEUS. The enhancement patterns of these FLL’s were analyzed throughout the arterial phase, the portal venous phase and the extended portal venous phase (the late parenchymal phase). The final diagnosis was established on the basis of histopathologic examination or CT/MRI imaging. Results Out of these 50 FLLs, 33 were malignant (4 hepatocellular carcinoma and 29 metastasis) and 17 were benign (5 hemangioma, 5 abscess, 2 cyst and 1 each of FNH, focal fat sparing area, focal fatty infiltration, adenoma and benign/granulomatous lesion). The enhancement patterns after injecting microbubble contrast agent allowed characterization of FLLs. The malignant lesions showed intratumoral and/or peritumoral vascularity during the arterial phase and perfusion defect during the late parenchymal phase. Contrast enhanced sonography improved sensitivity in detecting malignancy (CEUS vs. baseline sonography, 100% vs. 81.8%). Conclusion CEUS improves detection and characterization of FLLs. It should be used as problem solving tool in cases where conventional gray scale and color Doppler sonography are non-diagnostic.

The morphogenesis of the pancreas is a complex process having a very low frequency of anatomic variation. The congenital anomalies are rare. Complete pancreatic and ventral pancreatic agenesis are incompatible with life. Dorsal pancreatic agenesis is exceedingly rare with less than 100 cases reported in the world literature. Patients with this anomaly may be asymptomatic or may present with abdominal pain, hyperglycemia, diabetes mellitus, and acute or chronic pancreatitis. Such anomalies are rarely reported; therefore, clinical awareness of agenesis of the dorsal pancreas as a cause of these symptoms can expand the differential diagnosis and improve patient management.

Encephalocraniocutaneous lipomatosis (ECCL), also known as Haberland syndrome, is a rare syndrome with unknown etiology. The syndrome is characterized by a triad of unique cutaneous, ocular, and central nervous system (CNS) manifestations. The cutaneous hallmark, nevus psiloliparus (NP), along with overlying alopecia is a constant feature. Choristoma of the eyelid is the most common ocular manifestation, while intracranial lipoma is the predominant CNS finding. Genetic counseling is required to emphasize that the disorder, although congenital, is not inheritable. We present a 21-year-old female with cutaneous, ocular, and CNS features satisfying the diagnostic criteria for ECCL. To our knowledge, this is the first case of ECCL having a large temporal exostosis. The objective of this article is to better understand the phenotypic spectrum of this syndrome whose molecular basis is still unknown.

Colorectal pathology in the present era is a major cause of morbidity and mortality. Optical Colonoscopy has been the Gold Standard investigation for the diagnosis of colorectal diseases however a better investigation is required to attain high diagnostic yield along with minimal invasiveness and good patient acceptance. Virtual Colonoscopy offers another modality for assessment of colorectal pathology and promises to play an important role in the future in this regard. Method Forty-two patients suspected of having colorectal lesions were included in the present study over one year period. Patients were assessed by Optical Colonsocopy (OC) and Virtual Colonoscopy (VC) and the efficacy of VC was compared statistically with OC. Results 38 patients demonstrated lesions in a study population of 42 on OC. VC was able to detect lesions in 37 patients. The sensitivity and specificity of VC was 97.4% and 100% respectively. The results obtained by VC were comparable to OC (p > 0.05). Conclusion Virtual Colonoscopy is a new 3D diagnostic modality. Its efficacy in lesion detection, less time requirement for performance, good patient compliance, and detection of extracolonic lesions in addition to colonic findings make it a favourable choice for assessing colonic lesions.

Hirayama disease is a benign, nonprogressive motor neuron disease affecting the upper limbs. It is secondary to an abnormal anterior displacement of the posterior dura with secondary compression of the lower cervical spinal cord. It should be suspected in young male patients with a chronic history of weakness and atrophy involving the upper extremities followed by clinical stability in few years. The involvement is usually unilateral but may be bilateral. MR imaging is the best way to make the diagnosis but it necessitates the use of both extension/flexion and post contrast studies.

A 29-year-old man presented with a penetrating injury in the posterior aspect of his neck. His vital signs were stable. On plain CT head and neck, pneumorrhachis along with air in subcutaneous plane was seen (figures 1 and 2).

It has been strongly advocated that increase in density of breast tissue is strongly correlated with the risk of developing breast cancer. Accordingly change in breast tissue density pattern is taken seriously by radiologists. In typical cases, the breast tissue density patterns can be easily classified into fatty, fatty-glandular and dense glandular classes, but the differential diagnosis between atypical breast tissue density patterns from mammographic images is a daunting challenge even for the experienced radiologists due to overlap of the appearances of the density patterns. Therefore a CAD system for the classification of the different breast tissue density patterns from mammographic images is highly desirable. Accordingly in the present work, exhaustive experiments have been carried out to evaluate the performance of statistical features using PCA-kNN, PCA-PNN, PCA-SVM and PCA-SSVM based CAD system designs for two-class and three-class breast tissue density classification using mammographic images. It is observed that for two-class breast tissue density classification, the highest classification accuracy of 94.4 % is achieved using only the first 10 principal components (PCs) derived from statistical features with the SSVM classifier. For three-class breast tissue density classification, the highest classification accuracy of 86.3 % is achieved using only the first 4 PCs with SVM classifier.

Gastric outlet obstruction caused by duodenal impaction of a large gallstone migrated through a cholecystoduodenal fistula has been referred to as Bouveret’s syndrome. We present a case of gallstone-induced duodenal obstruction in an elderly female patient, diagnosed on a 64-slice MDCT scanner. One-stage surgery, that is, stone removal and cholecystectomy, was performed resulting in relief of obstruction and complete cure. Clinical features, multidetector computed tomography (MDCT) findings, and surgical management are discussed.

Craniosynostosis means premature closure of calvarial sutures. It may be primary or secondary. The patient presents with unexplained neuropsychological impairment and radiological imaging clinches the diagnosis. We present a case of 31-year-old female having primary isolated craniosynostosis who survived into adulthood without any surgical intervention. The imaging findings of such a case are rarely described in the literature.

Increase in oxidative stress (OS) has been found to be linked with various disease conditions, including diabetes and post-diabetic complications. If there is any imbalance between the reactive oxygen species (ROS) and antioxidant species inside cells, ROS damage cellular functions directly or indirectly. Besides oxidizing the major biomolecules inside the cells, they also alter the cell signaling mechanism, cell permeability, basic genetic mechanism, etc. In case of diabetes, different types of stresses (emotional, physical, chemical, or infectious) can lead to damage to the pancreatic cells and may result in decreased production/secretion (by β-cells) or utilization (by adipocytes, skeletal muscles, hepatocytes, etc.) of insulin and so, can result into hyperglycemic conditions. For the cells, which are not insulin dependent for their glucose uptake and metabolism (retinal cells, nephrons, nerve cells, etc.), their intracellular glucose concentration rises, and as a result, an increase in oxidative stress occurs by various mechanisms. This further triggers the onset of post-diabetic complications. This chapter describes the causes and mechanisms for the onset of diabetes and post-diabetic complications.

CASE REPORT A 28­year­old male patient presented with progressive weakness of both forearms and hands along with clawing of hands for past eight years. Right side was affected more than the left. There was no history of similar illness in the family. There was no past history of any prolonged illness in childhood. There was no history of sensory, pyramidal or bladder dysfunction. There was evidence of atrophy of muscles of both forearms and hands. Muscle power was normal in both upper limbs. Nerve conduction studies showed reduced amplitude in bilateral median and ulnar nerves. Tendon reflexes were normal. Magnetic resonance imaging (MRI) examination was performed in non­flexion and flexed position. Subsequently, diffusion tensor imaging (DTI) was performed in non­flexion, which very clearly showed the cord atrophy at C7 – T1 level (Figure 1). This cord atrophy was not appreciated on routine flexion and non­flexion studies. The diagnosis of Hirayama Disease (HD) was thus established on DTI. CLINICAL IMAGES OPEN ACCESS