Rituximab and Cytokine Release Syndrome

Rituximab is a biologic agent that is usually well tolerated. With its increasing use for a myriad of rheumatologic and immunologic conditions, post-marketing surveillance has revealed more side effects. Systemic inflammatory response syndrome associated with cytokine release syndrome (CRS) is a very rare entity associated with the use of rituximab and carries a very high morbidity and case fatality rate. Cases of CRS reported within the literature are of patients with a very high tumor burden leading to a catastrophic cascade of events. We report the case of a patient having post-transplant lymphoproliferative disorder who died of fatal lactic acidosis and CRS within 24 h of receiving rituximab. Understanding the pathophysiology of such cases and identifying patients at risk may help to possibly avert this life-threatening complication

VANT-GAN: adversarial learning for discrepancy-based visual attribution in medical imaging

Visual attribution (VA) in relation to medical images is an essential aspect of modern automation-assisted diagnosis. Since it is generally not straightforward to obtain pixel-level ground-truth labelling of medical images, classification-based interpretation approaches have become the de facto standard for automated diagnosis, in which the ability of classifiers to make categorical predictions based on class-salient regions is harnessed within the learning algorithm. Such regions, however, typically constitute only a small subset of the full range of features of potential medical interest. They may hence not be useful for VA of medical images where capturing all of the disease evidence is a critical requirement. This hence motivates the proposal of a novel strategy for visual attribution that is not reliant on image classification. We instead obtain normal counterparts of abnormal images and find discrepancy maps between the two. To perform the abnormal-to-normal mapping in unsupervised way, we employ a Cycle-Consistency Generative Adversarial Network, thereby formulating visual attribution in terms of a discrepancy map that, when subtracted from the abnormal image, makes it indistinguishable from the counterpart normal image. Experiments are performed on three datasets including a synthetic, Alzheimer’s disease Neuro imaging Initiative and, BraTS dataset. We outperform baseline and related methods in both experiments

EFFECT OF DIFFERENT SOLVENTS ON THE CHEMICAL COMPOSITION AND ANTI-DIABETIC ACTIVITY OF ACACIA ARABICA AND ZIZYPHUS MAURITIANA

The current study was designed to investigate the effect of solvents on chemical composition and antidiabetic activity of Zizyphus mauritiana and Acacia Arabica extracts. Total five solvents were used for this purpose (100% methanol, 50% aqueous methanol, 100% ethanol, 50% aqueous ethanol and aqueous). The data obtained from the investigation was subjected to the statistical analysis by using analysis of variance technique. The present study revealed that maximum antioxidant activity was attributed to Acacia arabica (96.53 ± 0.46%) followed by Zizyphus mauritiana (94.33 ± 0.52% by 50% aqueous ethanol extracts). Maximum total phenolic content of both Zizyphus mauritiana and Acacia arabica (670.83 ± 1.46 mg GAE/100g and 934.34 ± 0.89 mg GAE/100g) were shown by 50% aqueous ethanol extracts while maximum total flavonoid content (146.36 ± 0.81 mg QE/100 g, 172.52 ± 0.99 mg QE/100 g) was exhibited by 50% aqueous ethanol extract. The maximum (IC 50= 49.63 ± 0.12 µg/mL) antidiabetic activity was found in aqueous extract of Acacia arabica while in Zizyphus mauritiana the aqueous extract indicated excellent (IC 50= 46.90 ± 0.23 µg/mL) antidiabetic activity

Probing Study on Facilities of Competitive Sports in District Jail, Lucknow (India)

The purpose of this study was to evaluate organizational structure, administrative frame-work andfacilities of Sports in District Jail of Lucknow in Uttar Pradesh, India. The sample of the present study wasdrawn randomly from the jail administrators, prisoners and physical educator(s) of District Jail of Lucknow.The size of the sample was 55 comprising 50 prisoners and 5 administrators. No physical educator(s) wasfound in the jail. Questionnaire taken for the study was developed by the researchers in a pilot study. Itincludes five sub-scales (a) Organizational Structure, (b) Administrative Frame-work, (c) Facilities ofSports, (d) Preference of Sports, and (e) Achievements in Sports. The percentile method was used in theanalysis of the results. The data indicates that some of the inmate information's intended to continue theirsports involvement following their release whereas some of the administrators recorded their responses to prescribe the Government of India for the proper sports facilities in their jail. Many of the inmates wouldrather watch sports events on television rather than participate in one themselves.Keywords: Organization; Facilities; Prisoners; Administrators; District Jail, Lucknow

Evaluating the Perception and Awareness of Patients Regarding Ovarian Cysts in Peshawar, Pakistan

Purpose: To evaluate patients’ perception regarding ovarian cyst as well as their awareness of the symptoms and health management of the disease.Methods: A quantitative research approach was used to conduct this study. Patients were selected from the Gynecology wards, Hayatabad Medical Complex, Peshawar and a questionnaire was designed to evaluate the patients’ knowledge and awareness.Results: When women were asked if they had prior knowledge about the ovarian cyst, 37 (58.7 %) responded that they were first told by the  physician during their visit to the clinic or hospital while the patients  responded, “Still don’t know” are 22 (34.9 %). With respect to educational level of the patients, they seemed to be less aware of the disease. Their perception regarding the disease is that they had a “water filled” balloon or tumor.Conclusion: Prior to discharge of an ovarian cyst patient from the hospital, she should be counseled on the disease and successful treatment outcomes. Counseling of the patients may result in compliance with therapy, good quality of life and lower economic burden.Keywords: Ovarian cyst, Menstrual cycle, Awareness, Perception, Treatment outcome

Enhanced solar light photocatalytic performance of Fe-ZnO in the presence of H2O2, S2O82−, and HSO5− for degradation of chlorpyrifos from agricultural wastes: Toxicities investigation

This study reported Fe doped zinc oxide (Fe-ZnO) synthesis to degrade chlorpyrifos (CPY), a highly toxic organophosphate pesticide and important sources of agricultural wastes. Fourier transform infrared, X-ray diffraction, scanning electron microscope, and energy-dispersive X-ray spectroscopic analyses showed successful formation of the Fe-ZnO with highly crystalline and amorphous nature. Water collected from agricultural wastes were treated with Fe-ZnO and the results showed 67% degradation of CPY by Fe-ZnO versus 39% by ZnO at 140 min treatment time. Detail mechanism involving reactive oxygen species production from solar light activated Fe-ZnO and their role in degradation of CPY was assessed. Use of H2O2, peroxydisulfate (S2O82−) and peroxymonosulfate (HSO5−) with Fe-ZnO under solar irradiation promoted removal of CPY. The peroxides yielded hydroxyl ([rad]OH) and sulfate radical ([Formula presented]) under solar irradiation mediated by Fe-ZnO. Effects of several parameters including concentration of pollutant and oxidants, pH, co-existing ions, and presence of natural organic matter on CPY degradation were studied. Among peroxides, HSO5− revealed to provide better performance. The prepared Fe-ZnO showed high reusability and greater mineralization of CPY. The GC-MS analysis showed degradation of CPY resulted into several transformation products (TPs). Toxicity analysis of CPY as well as its TPs was performed and the formation of non-toxic acetate imply greater capability of the treatment technology

Bag of Deep Features for Instructor Activity Recognition in Lecture Room

This paper has been presented at : 25th International Conference on MultiMedia Modeling (MMM2019)This research aims to explore contextual visual information in the lecture room, to assist an instructor to articulate the effectiveness of the delivered lecture. The objective is to enable a self-evaluation mechanism for the instructor to improve lecture productivity by understanding their activities. Teacher’s effectiveness has a remarkable impact on uplifting students performance to make them succeed academically and professionally. Therefore, the process of lecture evaluation can significantly contribute to improve academic quality and governance. In this paper, we propose a vision-based framework to recognize the activities of the instructor for self-evaluation of the delivered lectures. The proposed approach uses motion templates of instructor activities and describes them through a Bag-of-Deep features (BoDF) representation. Deep spatio-temporal features extracted from motion templates are utilized to compile a visual vocabulary. The visual vocabulary for instructor activity recognition is quantized to optimize the learning model. A Support Vector Machine classifier is used to generate the model and predict the instructor activities. We evaluated the proposed scheme on a self-captured lecture room dataset, IAVID-1. Eight instructor activities: pointing towards the student, pointing towards board or screen, idle, interacting, sitting, walking, using a mobile phone and using a laptop, are recognized with an 85.41% accuracy. As a result, the proposed framework enables instructor activity recognition without human intervention.Sergio A Velastin has received funding from the Universidad Carlos III de Madrid, the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 600371, el Ministerio de Economía, Industria y Competitividad (COFUND2014-51509) el Ministerio de Educación, Cultura y Deporte (CEI-15-17) and Banco Santander