Search

Molecular dynamics (MD) simulations have emerged to be a vital tool for the analysis of nanoscale materials like graphene. However, the reliability of the results derived from MD simulations depends on the adopted inter-atomic potential (IP), which is mathematically fitted to the data obtained from first principles approaches or experiments. There exists a significant scope of uncertainty associated with the IP parameters. Such internal uncertainties, together with the effect of stochastic external parameters like temperature and strain rate can trigger an augmented random deviation in the output mechanical responses. With the aim of developing an inclusive analysis and design paradigm, we have systematically quantified the effect of the uncertainties associated with the internal parameters (Tersoff IP parameters) and external parameters (temperature and strain rate) individually, and their compound effect on the mechanical properties of graphene. In establishing the complete probabilistic descriptions of the response quantities corresponding to different levels of source uncertainties, we show that a coupled machine learning-based Monte Carlo simulation approach could lead to significant computational efficiency without compromising the accuracy of the results. The study reveals that, in general, the internal parameters are more sensitive than the external parameters. Among the inter-atomic parameters, λ1 and λ2 are found to be the most sensitive, while the temperature is found to be more sensitive than the strain rate among the external parameters. The cohesive energy is noted to be dependent only on the inter-atomic potential parameters, while the fracture strength depends on both the internal and external input parameters. The numerically quantifiable outcomes of this study will improve and bring new perspectives in the inclusive analysis and design of various graphene-based devices and systems, including the effect of inherent uncertainties and their relative sensitivity.

A biomarker can be measured, used to diagnose or classify disease, and measure progress as well as the therapeutic response of the disease. Early diagnosis and selection of appropriate treatment can be critical for the successful treatment of diseases. Identification and characterization of potent diagnostic biomarkers, and therapeutic targets rely heavily on traditional in vitro screens which require extensive resources and time. Integration of in silico screens prior to experimental validation can improve the efficiency and potency of biomarkers as well as reduce the cost and time of biomarker discovery. Considering the need, present work was undertaken to identify biomarkers for different classes of leukemia. Differential Gene Expression (DGE) analysis and co-regulated expression analysis were used for in silico identification and characterise a potent biomarker for leukemia. On the basis of in silico screening, the present study proposed seven protein-coding (CD38, TSC22D3, TNFRSF25, AGL, LARGE1, ARHGAP32, and PARM1) genes for the diagnosis of leukemia. The study also proposed a novel three-step lineage-specific model for the diagnosis of leukemia. In the three-step diagnosis model, the first group of biomarkers with an association of clinical and hematological parameters diagnose leukemia. The second group of biomarkers diagnoses acute and chronic form of leukemia. The third group of biomarkers identifies whether it belongs to myeloid lineage or lymphoid lineage.

Introduction Acute pancreatitis (AP) is an inflammatory process of pancreas with varying degree of involvement of regional tissues. The aim of this study was to investigate the potential use of serum cystatin C (Cys-C) for the early and accurate diagnosis of acute kidney injury (AKI) in patients of AP. Materials and methods This was a prospective study conducted in 1 year. Total of 215 cases of AP fulfilling the inclusion criteria were enrolled in this study. Patients suffering from chronic pancreatitis, neoplasm, chronic liver disease, and chronic kidney disease were excluded from the study. Diagnosis of AP was based on the Atlanta classification 2012. All patients were classified into a non-AKI group (n = 152) and an AKI group (n = 38) according to the dynamic changes in serum creatinine levels. Serum Cys-C was measured by particle-enhanced immune nephelometric assay. Results By univariate logistic regression analysis, body mass index (BMI) (OR = 1.44, 95% CI: 1.23–1.68; p < 0.001), blood urea (OR = 1.15, 95% CI: 1.06–1.23; p < 0.001), Cys-C (OR = 1.04, 95% CI: 1.01–1.07; p < 0.05), serum calcium (OR = 0.59, 95% CI: 0.41–0.86; p < 0.05), and serum lactate dehydrogenase (LDH) (OR = 1.001, 95% CI: 1.0–1.001; p < 0.05) were the significant indicators for AKI in patients with AP. Using multivariate logistic regression analysis, urinary albumin and Cys-C were independent and significant indicators of AKI in patients with AP (OR = 1.026, 95% CI: 1.01–1.07; p < 0.01). Receiver operating characteristic (ROC) curve of serum Cys-C, for AKI in patient with AP could be identified with a sensitivity of 92.06% at specificity of 96.0% [area under the curve (AUC) = 0.96, 95% CI: 0.92–0.98] by baseline serum Cys-C (cutoff value = >32.32 mg/L). Conclusion Increase of baseline serum Cys-C was associated with AKI in patients with AP. How to cite this article Patel ML, Shyam R, Bharti H, Sachan R, Gupta KK, Parihar A. Evaluation of Serum Cystatin C as an Early Biomarker of Acute Kidney Injury in Patients with Acute Pancreatitis. Indian J Crit Care Med 2020;24(9):777–782.

Doping in pristine 2D materials brings about the advantage of modulating wide range of mechanical properties simultaneously. However, intrinsic defects (such as Stone-Wales and nanopore) in such hybrid materials are inevitable due to complex manufacturing and synthesis processes. Besides that, defects and irregularities can be intentionally induced in a pristine nanostructure for multi-synchronous modulation of various multi-functional properties. Whatever the case may be, in order to realistically analyse a doped graphene sheet, it is of utmost importance to investigate the compound effect of doping and defects in such 2D monolayers. Here we present a molecular dynamics based investigation for probing mechanical properties (such as Young’s modulus, post-elastic behaviour, failure strength and strain) of doped graphene (C14 and Si) coupling the effect of inevitable defects. Spatial sensitivity of defect and doping are systematically analyzed considering different rational instances. The study reveals the effects of individual defects and doping along with their possible compounded influences on the failure stress, failure strain, Young’s modulus and constitutive relations beyond the elastic regime. Such detailed mechanical characterization under the practically relevant compound effects would allow us to access the viability of adopting doped graphene in various multifunctional nanoelectromechanical devices and systems in a realistic situation.

Biogenic zinc oxide nanoparticles (BZnONPs) as a nano medicine attain high importance in the treatment of Peri Implantitis (PI). Present study was aimed to biosynthesize, optimize, characterize and evaluate the response of BZnONPs against PI triggering non periodontal pathogen. The BZnONPs synthesis, characterization, optimization and stability were based on UV-Visible, FTIR, XRD, FESEM, and EDX data. The BZnONPs were tested against S. aureus. Treatment of zinc acetate with Dimocarpus longan leaves extract resulted in formation of BZnONPs, which exhibited the absorbance signal between 350- 359 nm. Optimization study established 0.05 M zinc acetate, 6 ml of DLL aqueous extract, pH 12, and 2 h stirring time as parametric requirements for BZnONPs synthesis. Stability study of BZnONPs exhibited absorbance at 340 nm. The BZnONPs were characterized based on broad and shifted FT-IR bands, XRD signals (at 2θ values of 31.70◦ , 34.33◦ , 36.19◦ , 47.45◦ , 56.52◦ , 62.78◦ , 67.88◦ and 72.45◦ ), size range from 42.07-61.33 nm in FESEM, and elemental zinc 74.22 % in EDX spectrum. The BZnONPs exhibited high inhibitory response towards S. aureus. Present study establish that BZnONPs synthesis using Dimocarpus longan leaves aqueous extract is a facile method and reports that BZnONPs could be potential remedy for PI.

Aim and objective The aim of this study was to evaluate and compare the antifungal efficacy of MTA Fillapex, Metapex, zinc oxide eugenol cement, Endomethasone, and Endoflas against Candida albicans. Materials and methods Root canal exudates of 30 patients were tested against MTA Fillapex (Angelus), Metapex (BioMed), zinc oxide eugenol (Deepak Enterprise), Endomethasone (Septodont), Endoflas FS (Sanlor Laboratories), MTA (Angelus) (positive control), and glycerine (negative control). Children with failed endodontic cases were included in the study. Tube dilution and agar diffusion methods were used to check the antifungal efficacy of the root canal sealers. In tube dilution method, 24-well culture plates containing freshly mixed material along with Candida albicans were used. Wells containing MTA (Angelus) along with Sabouraud dextrose agar and Candida albicans served as positive control while glycerine along with Sabouraud dextrose agar and Candida albicans served as negative control. All plates were incubated at 37°C for 24 hours. Growth of the fungi was monitored after 24 hours by the presence of the turbidity. The samples were recultured to test the experimental material using agar well diffusion method, and the Petri plates were incubated for 24 hours and 72 hours. Zone of inhibition was measured after respective time period. Paired t test was used for the data analysis. Results It was seen in tube dilution method Endomethasone showed least turbidity while maximum was shown by Metapex; similar results were seen in case of agar well diffusion method in which largest zone of inhibition was shown by Endomethasone while smallest was by Metapex. Conclusion It was concluded that Endomethasone showed maximum efficacy against Candida albicans as compared to Metapex. How to cite this article Singh S, Srivastava B, Gupta K, et al. Comparative Evaluation of Antifungal Efficacy of Five Root Canal Sealers against Clinical Isolates of Candida albicans: A Microbiological Study. Int J Clin Pediatr Dent 2020;13(2):119-123.

BACKGROUND Since its discovery, treatment of hepatitis C virus (HCV) has undergone extensive changes. Antiviral treatments and sustained virological responses (SVR) have also improved from the early interferon monotherapy to the current all-oral regimens using direct acting antiviral (DAAs). We aimed to analyse our experience for last 4 years in treatment of hepatitis C with the currently available antivirals in terms of SVR at various time-points, new onset decompensation, hepatocellular carcinoma (HCC), mortality and side effects. METHODS Data of all patients with anti-HCV were collected prospectively and analysed. This included history taking, examination findings, routine blood investigations, viral markers, HCV RNA before initiating antivirals and at the end of giving antivirals and every 3 months thereafter among all HCV positive patients, HCV genotype, and ultrasonography of whole abdomen, upper gastrointestinal endoscopy and alpha fetoprotein (AFP). RESULTS A total of 520 patients was found positive for anti HCV, from 2014 to 2018, of which 276 (53%) were male and 244 (47%) were female patients. Among all 520 patients, 353 (68%) had detectable HCV RNA, of which 43 (12%) patients had cirrhosis and 310 (88%) had chronic infection. 29 (8%) received Sofosbuvir plus Ledipasvir, 73 (20%) Sofosbuvir plus Ribavirin, 115 (33%) Sofosbuvir plus Daclatasvir, and 70 (20%) received Sofosbuvir plus Velpatasvir. All except one achieved SVR. No any new onset HCC was detected while 7 (2%) patients developed new onset decompensation. Total 3 (7%) cirrhotic patients expired. One patient developed self-limiting erythematous rash. CONCLUSIONS Directly acting antivirals (DAAs) are highly effective and safer drugs for the treatment of chronic hepatitis C infection even in real life scenario as evident from our study most of the patients receiving antivirals survived.

AIM Assessing the accuracy of surgical guides generated with the help of a simple chair side ridge mapping technique by comparing the planned implant position with the achieved implant position on post-op computerized tomography scans. MATERIALS AND METHODS In this study, 20 implant sites in patients were selected. Ridge mapping was done through a vacuum press template at three buccal (B1, B2, B3), three lingual (L1, L2, L3), and one crestal (C) points for each implant site. Readings were transferred onto the cast, and surgical guides were fabricated for implant placement. Postoperative cone beam computerized tomography (CBCT) was done to assess planned and achieved implant position. Comparison was done between soft tissue depths and implant distance from the crest of alveolar bone determined by the ridge mapping technique with measurements done on CBCT. The points used for ridge mapping were used as the reference for measurements. The data were analyzed using paired t test. p < 0.05 was considered to be statistically significant. RESULTS On comparing the mean values of soft tissue depths from the ridge mapping and CBCT data, insignificant differences were found at B1, B2, L1, L2, L3, and C, but significant differences were found at B3. On comparing the implant distances from alveolar bone from both the data, insignificant differences were found at B, B2, B3, L1, L2, and L3 and significant difference was found at the crest in the mean values. CONCLUSION Under the limitations of the above study, it can be concluded that a simple chairside procedure like ridge mapping can be used as an effective way for guided implant placement in sufficient available alveolar bone.

Accreting supermassive black holes (SMBHs), also known as active galactic nuclei (AGN), are generally surrounded by large amounts of gas and dust. This surrounding material reprocesses the primary X-ray emission produced close to the SMBH and gives rise to several components in the broadband X-ray spectra of AGN, including a power-law possibly associated with Thomson-scattered radiation. In this work, we study the properties of this scattered component for a sample of 386 hard-X-ray-selected, nearby ($z \sim 0.03$) obscured AGN from the 70-month Swift/BAT catalog. We investigate how the fraction of Thomson-scattered radiation correlates with different physical properties of AGN, such as line-of-sight column density, X-ray luminosity, black hole mass, and Eddington ratio. We find a significant negative correlation between the scattering fraction and the column density. Based on a large number of spectral simulations, we exclude the possibility that this anti-correlation is due to degeneracies between the parameters. The negative correlation also persists when considering different ranges of luminosity, black hole mass, and Eddington ratio. We discuss how this correlation might be either due to the angle dependence of the Thomson cross-section or to more obscured sources having a higher covering factor of the torus. We also find a positive correlation between the scattering fraction and the ratio of [OIII] $\lambda$5007 to X-ray luminosity. This result is consistent with previous studies and suggests that the Thomson-scattered component is associated with the narrow-line region., Comment: Accepted for publication in MNRAS, 18 pages, 9 figures, 2 tables, 1 equation

A machine learning assisted efficient, yet comprehensive characterization of the dynamics of coronaviruses, in conjunction with finite element (FE) approach, is presented. Without affecting the accuracy of prediction in low-frequency vibration analysis, an equivalent model for the FE analysis is proposed, based on which the natural frequencies corresponding to first three non-rigid modes are analyzed. To quantify the inherent system-uncertainty efficiently, Monte Carlo simulation is proposed in conjunction with the machine learning based FE computational framework for obtaining complete probabilistic descriptions considering both individual and compound effect of stochasticity. A variance based sensitivity analysis is carried out to enumerate the relative significance of different material parameters corresponding to various constituting parts of the coronavirus structure. Using the modal characteristics like natural frequencies and mode shapes of the virus structure including their stochastic bounds, it is possible to readily identify coronaviruses by comparing the experimentally measured dynamic responses in terms of the peaks of frequency response function. Results from this first of its kind study on coronaviruses along with the proposed generic machine learning based approach will accelerate the detection of viruses and create efficient pathways toward future inventions leading to cure and containment in the field of virology.

In present research work, cotton fabric was dyed with reactive dye using primary colors like red, green, blue after evaluate the fastness properties of the dyed sample via, fastness to washing, fastness to water, fastness to rubbing were evaluated by standard method. Using the non-formaldehyde based fixing agent in reactive dyes. It is also pointed out that the non-formaldehyde based fixing agent is eco-friendly and meets the environmental norms and all fastness result are good. In continuation after dyeing applying the various concentration of silicone softener and polyethylene softener which increases in tearing and tensile strength.

This venture depicts the improvement of water body mapping (WBM), utilizing a computerized calculation to process Landsat pictures from the United States Geological Survey (USGS) database. We utilized Landsat 2, 3, 5, 8 band pictures so as to depict a precise water body map, with no normal unsettling influence. Perpetual water bodies were recognized from fleeting water-shrouded regions by computing the recurrence of water body presence from covering, multi-transient, Landsat scenes. By examining the recurrence of water body presence, the WBM isolates stream channels and floodplains more obviously than past examinations. This recommends the utilization of multi-transient pictures is as significant as examination at higher goals for worldwide water body mapping. We screen the Chennai and adjacent surface water region changes from 1977 to 2016. Three scenes from the Multispectral Scanner System (MSS), three scenes from the Thematic Mapper (TM), and three scenes from the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) remote detecting information of Landsat satellites, the standardized distinctive water file (NDWI), standardized diverse vegetation record (NDVI), and NIR technique were utilized to quantitatively gauge the Chennai buffer surface water territory during the 1970s, 1980s, 2000s, and 2010s, separately. The examination closed the estimation of human exercises sway on surface water spatiotemporal dissemination. The point was to decide the exactness of utilizing basic computerized picture handling strategies to delineate water bodies with Landsat 2(MSS), Landsat 3(MSS), Landsat 5(MSS/TM), and Landsat 8(OLI/TIRS) information.

From last two decades, mobile ad-hoc network has significantly contributed to the research. Mobile ad-hoc network basically filed of wireless ad-hoc network in which all the connected components shares their data and make communication with each other without any dedicated links/path or without wired communication. There are various protocols available for the secured communication and safely transfer the files and data. However, the attacker will always be in action to destroy the communication or link between the sender and receiver. In the following paper, we present the survey on various types of attack in the field of wireless ad-hoc network including internal and external attack.

The present study uses the molecular dynamics approach to study the various defects available in graphene sheet and also to record its effect on the strength and stiffness of graphene. The graphene sheet is uniaxially deformed in its armchair and zigzag direction. In order to examine the fracture behaviour of defective graphene, molecular dynamics (MD) simulations based on AIREBO interatomic potential field and Nose-Hoover thermostat and barostat techniques are implemented. The present study shows that with the introduction of the defects, the fracture/yield strength of graphene reduces up to some extent in both of its direction. However, the presence of crack reduces the strength of graphene significantly more. Further, the study also concludes that the graphene withholds much higher stress when loaded in its zigzag direction in comparison with loading it in armchair direction.

Introduction : The Global Initiative for Chronic Obstructive Lung Disease (GOLD) recently defined COPD as “Chronic Obstructive Pulmonary Disease (COPD) as a common, preventable and treatable disease that is characterized by persistent respiratory symptoms and airflow limitation that is due to airway and/or alveolar abnormalities usually caused by significant exposure to noxious particles or gases”. Hyperglycemia has been associated with increased morbidity, increased mortality, and longer lengths of stay, and more hospital costs in patients with both medical and surgical conditions. Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is associated with hyperglycemia due to the stress related hormonal response to acute illness and possibly some of the medications routinely used in the treatment of AECOPD. Aim: To study the effect of hyperglycemia on outcome of acute exacerbation of COPD and to compare the mean duration of hospital stay in acute exacerbation of COPD patients divided in to groups according to severity of hyperglycemia and HbA1C levels. Materials and Methods : This was a Prospective study done in KGMU, Lucknow. The study group comprised of COPD patients and admitted as acute exacerbation of COPD and severity was determined according to GOLD classification criteria, and their hospital stay was correlated with RBS and HbA1c. Results: A total of 107 patients of COPD were enrolled in the study of which 6 patients died. 101 patients underwent the follow up study. Duration of hospital stay among patients having RBS> 200 mg/dl was (9.63±2.04 days) and was found to be statistically significant to patients whose RBS was 6 and < 6. Conclusion: Strict control of blood sugar, in the pre hospitalization period as well as during hospital stay results in better outcomes and also shortened hospital stay; thus influencing both mortality and morbidity.

Despite the tremendous capabilities of Molecular dynamics (MD) simulations, they suffer from the limitation of computationally intensive and time-consuming nature. This hinders the seamless discovery of nanomaterials with adequate computational insights. Over the last decade, graphene has received widespread attention from the scientific community due to its extra-ordinary multi-physical properties, primarily focusing on the fundamental physics and chemistry along with the notion of scalable synthesis. However, the recent advances in machine learning have opened new frontiers in the research of such exceptional two-dimensional materials where the boundaries of different multi-physical properties could be pushed further efficiently with the assistance of deep computational intelligence. Here we propose a coupled machine learning (ML) based approach to investigate the critical mechanical responses of graphene by capturing the underlying physics of the system through an (D-)optimally minimum number of MD simulations. We have investigated five different internal and external controlling input features like temperature, strain rate, nanostructural defects, doping, and chirality, which influence the critical mechanical properties of graphene such as the constitutive behavior including fracture strength, failure strain and Young's modulus. Even though the aspect of computational intensiveness in molecular dynamics simulations is addressed through the coupled ML based approach, in a data-driven comprehensive analysis, it is often difficult to get complete information about the concerning input parameters including their statistical distributions and occurrence bounds. Thus, it becomes difficult to carry out computational investigations based on powerful techniques like Monte Carlo simulation. To mitigate this lacuna, here we have exploited the ML-assisted approach for developing a level-based fuzzy framework at nano-scale under sparse input descriptions. In this article, we first demonstrate the computational efficiency achieved through the proposed ML based framework without compromising quality of the analysis, followed by data-intensive correlation analysis, sensitivity and uncertainty quantification considering various levels of the influencing system parameters, revealing detailed computational insights on mechanical properties of graphene including the coupled interactive influence of intrinsic defects and doping.

Background Sepsis is one of the most common triggering factors for acute kidney injury (AKI). The aim of the study is to evaluate the outcome in sepsis with AKI and determine the prognostic value of urinary neutrophil gelatinase-associated lipocalin (NGAL) in septicemic AKI. Materials and methods This prospective follow-up study was carried out over a period of 1 year after ethical clearance from the Institutional Ethics committee, a total 165 cases of septicemia were recruited, of which 15 patients were dropped out, 150 patients were identified suffering from septicemia defined as per the organ dysfunction criteria (according to third international consensus 2016) and patients of AKI defined as per the Kidney Disease Improving Global Outcomes 2012 criteria). Results Out of 150 patients of septicemia enrolled in the study, only 38 (25.33%) suffering from AKI were classified as Group I and rest 112 (74.67%) patients of septicemia not suffering from AKI were classified as Group II. In total, 60.0% (90) patients were discharged from the hospital, rest of the patients (40%) expired. Mean duration of survival was higher in Group II (21.29 ± 1.89 days) as compared to Group I (13.67 ± 1.06 days). Cases with ≥121.90 urine NGAL, rate of mortality (41.7%), were higher as compared to alive patients discharged (34.4%). Conclusion Sequential organ failure assessment score, hospital stay, and mortality were high in septicemic patients with AKI as compared to sepsis without AKI. Survival of patients also not good with septic AKI, those patients who had high NGAL value had poor prognosis.

Background: Chronic kidney disease (CKD) predisposes to accelerated atherosclerosis that is measured by carotid artery intima media thickness (CIMT) and brachial artery flow-mediated dilation (FMD). The aim of this study was to assess the noninvasive risk markers of subclinical atherosclerosis and endothelial dysfunction and their correlation with disease severity. Methods and Results: This was a cross-sectional study conducted in 62 patients with CKD: 38 predialysis and 24 on hemodialysis and 50 age- and gender-matched controls. In both the patients and controls, high-sensitivity C-reactive protein (CRP) levels, %FMD, and CIMT were measured. Patients with CKD had increased CRP levels {[5.8 (1.0–6.0)] mg/L vs [1.0 (0.5–2.20)] mg/L; P < 0.001}; %FMD was significantly lower in patients on hemodialysis (5.51%) compared with stage IV (7.62%) and stage III (15.02%) and 17.95% in control subjects (P < 0.001); and CIMT values in hemodialysis patients (0.88 ± 0.06 mm) were significantly higher compared with stage IV (0.67 ± 0.10) and stage III (0.61 ± 0.12) (P < 0.001). Increased CIMT values were seen in patients with CKD (0.82 ± 0.21 mm) than in the healthy controls (0.55 ± 0.16 mm). In patients with CKD, a significant negative correlation was found between CRP levels and FMD responses (r = −0.315; P < 0.001), while a significant positive correlation was found between CRP and CIMT values (r = 0.327; P < 0.001). Compared with predialysis, hemodialysis subjects had significantly lower FMD and higher CRP and IMT values. Conclusion: CKD confers a higher inflammatory status when compared with apparently healthy general population. Abnormal FMD responses and CIMT values are more commonly found in dialysis patients. Our findings suggest that CIMT and FMD can be used as noninvasive markers for early risk assessment and stratification in various stages of CKD.