Clinical and angiographic profile in patients of western Rajasthan undergoing percutaneous coronary interventions: a single centre experience

Background: This study was aimed to evaluate clinical and angiographic profile of patients undergoing percutaneous coronary intervention at the Department of Cardiology, Mathura Das Mathur (MDM) Hospital attached to Dr. Sampurnanand Medical College, Jodhpur.Methods: This study was hospital based prospective observational study conducted in the department of cardiology at MDM hospital. This study included 1166 patients who underwent percutaneous coronary intervention at cardiac cathlab of MDM hospital from January 2016 to April 2017. Procedural details noted included vascular access route, lesion characteristics, number of lesions intervened, stents used and periprocedural pharmacotherapy administered.Results: A total of 1166 patients (mean age- 56.3±10.4 years) with 76.5% male and 23.5% female were included in the study. Smoking and hypertension were the most common risk factors, present in 64% and 56% patients respectively. Diabetes mellitus and obesity were observed in 24.5% , 18.0% patients respectively. Anterior wall MI was the most common mode of presentation (36.2%). Single Vessel Disease (SVD) was the most common angiographic pattern observed in 62% patients; left anterior descending artery (LAD) was the most frequently involved vessel (65.9%); and type B lesions were most prevalent (48%). Most of the procedures were elective (61.4%) and femoral route was used in the majority (76%). Radial access was obtained in 24% of patients. Primary PCI was done in 6% of cases while pharmaco-invasive approach was adopted in 32.6% of patients. Drug eluting stents were deployed in 100% of the cases. The overall procedural success rate was 95.4%. Procedural mortality was nil and periprocedural complications occurred in 16.0% patients.Conclusions: This first PCI study from western Rajasthan provides an overview into the salient features of CAD among regional population and focus on the characteristics of PCIs performed with their outcomes

Study of P. falciparum-infected erythrocytes and induced anisotropies under optical and fluid forces

Background & objectives: The effect of P. falciparum on erythrocytes has been studied for a long time at the population level but actual studies at the single cell level remain largely unexplored. The aim of this study was to address the host-parasite relationship at the single cell level under two different kinds of forces, an optical force and a fluid force. The questions addressed were about the basic host-parasite interactions, but our findings have larger implications in diverse fields of parasite biology. Methods: Erythrocytes were monitored under optical forces (using optical tweezers) and fluid forces (using microfluidic chambers) and dynamical images were captured in real-time video clips. These videos were then split into their respective frames so as to yield temporal information and various parameters pertaining to membrane structure, ionic imbalance and interaction with different forces were studied. Results: The results of this study mainly bring to fore the inherent differences between infected and normal cell populations at the single cell level under various external forces. We probed three different criteria folding times, rotation speeds and rolling frequency to show inherent difference in various cell populations and also the dependence of the above to the cycle of the parasite. Interpretation & conclusion: This study portrays the importance of single cell observations pertaining to the host-parasite relationship. It shows the effect the malarial parasite has on erythrocytes and how the intrinsic property of the infected and its neighbouring uninfected cells change as compared to normal erythrocytes. There are thus implications in the fields of cytoadherence, parasite invasions and host immune evasion

Machine learning for intrusion detection in industrial control systems : challenges and lessons from experimental evaluation

Abstract: Gradual increase in the number of successful attacks against Industrial Control Systems (ICS) has led to an urgent need to create defense mechanisms for accurate and timely detection of the resulting process anomalies. Towards this end, a class of anomaly detectors, created using data-centric approaches, are gaining attention. Using machine learning algorithms such approaches can automatically learn the process dynamics and control strategies deployed in an ICS. The use of these approaches leads to relatively easier and faster creation of anomaly detectors compared to the use of design-centric approaches that are based on plant physics and design. Despite the advantages, there exist significant challenges and implementation issues in the creation and deployment of detectors generated using machine learning for city-scale plants. In this work, we enumerate and discuss such challenges. Also presented is a series of lessons learned in our attempt to meet these challenges in an operational plant

Human Rad52 binding renders ssDNA unfolded: image and contour length analyses by Atomic Force Microscopy

Atomic force microscopy imaging has been used to study the changes associated with human Rad52 (HsRad52) protein in solution, in dried state as well as following ssDNA (linear and circular) binding. In the dried state, the free protein exists predominantly as a characteristic panoply of novel trifoliate forms. However, in solution, the level of trifoliates diminishes significantly. Height analyses of either form reveal two categories: smaller (~ 3-5 nm) and larger ((~ 10-12 nm) particles, perhaps related to sub-heptameric and heptameric forms respectively. Interestingly, binding of the protein to linear ssDNA smoothly extends and unfolds the naked DNA. Contour length measurements performed on several individual circular ssDNA/nucleoprotein complexes reveal marked (about threefold) extension of naked ssDNA, following HsRad52 binding. We speculate that the alignment of HsRad52 on ssDNA into a smoothly extended and unfolded strand from that of highly compact morphology of naked ssDNA, may have bearing on the recombination function of HsRad52 protein

Truth Will Out: Departure-Based Process-Level Detection of Stealthy Attacks on Control Systems

Recent incidents have shown that Industrial Control Systems (ICS) are becoming increasingly susceptible to sophisticated and targeted attacks initiated by adversaries with high motivation, domain knowledge, and resources. Although traditional security mechanisms can be implemented at the IT-infrastructure level of such cyber-physical systems, the community has acknowledged that it is imperative to also monitor the process-level activity, as attacks on ICS may very well influence the physical process. In this paper, we present PASAD, a novel stealthy-attack detection mechanism that monitors time series of sensor measurements in real time for structural changes in the process behavior. We demonstrate the effectiveness of our approach through simulations and experiments on data from real systems. Experimental results show that PASAD is capable of detecting not only significant deviations in the process behavior, but also subtle attack-indicating changes, significantly raising the bar for strategic adversaries who may attempt to maintain their malicious manipulation within the noise level