Tunable Visible Emission of Ag-Doped CdZnS Alloy Quantum Dots

Highly luminescent Ag-ion-doped Cd1−xZnxS (0 ≤ x ≤ 1) alloy nanocrystals were successfully synthesized by a novel wet chemical precipitation method. Influence of dopant concentration and the Zn/Cd stoichiometric variations in doped alloy nanocrystals have been investigated. The samples were characterized by X-ray diffraction (XRD) and high resolution transmission electron microscope (HRTEM) to investigate the size and structure of the as prepared nanocrystals. A shift in LO phonon modes from micro-Raman investigations and the elemental analysis from the energy dispersive X-ray analysis (EDAX) confirms the stoichiometry of the final product. The average crystallite size was found increasing from 1.0 to 1.4 nm with gradual increase in Ag doping. It was observed that photoluminescence (PL) intensity corresponding to Ag impurity (570 nm), relative to the other two bands 480 and 520 nm that originates due to native defects, enhanced and showed slight red shift with increasing silver doping. In addition, decrease in the band gap energy of the doped nanocrystals indicates that the introduction of dopant ion in the host material influence the particle size of the nanocrystals. The composition dependent bandgap engineering in CdZnS:Ag was achieved to attain the deliberate color tunability and demonstrated successfully, which are potentially important for white light generation

Clinical efficacy of clonidine versus nalbuphine as intrathecal adjuvants to 0.5% hyperbaric bupivacaine for subarachnoid block during gynaecological procedures: a double blind study

Background: Regional anesthesia techniques for gynaecological procedures are on increasing trends due to their advantage of postoperative analgesia owing to intrathecal adjuvants. The present study was aimed to comparatively evaluate the clinical efficacy of clonidine with nalbuphine when co-administered intrathecally with 0.5% hyperbaric bupivacaine for gynaecological procedures.Methods: Regional anesthesia techniques for gynaecological procedures are on increasing trends due to their advantage of postoperative analgesia owing to intrathecal adjuvants. The present study was aimed to comparatively evaluate the clinical efficacy of clonidine with nalbuphine when co-administered intrathecally with 0.5% hyperbaric bupivacaine for gynaecological procedures.Results: The onset of sensory block was earlier in patients of Group BN (3.91±2.25 min vs 4.30±0.87 min, p=0.039). The onset of motor block was also earlier in patients of Group BN (p=0.042). The time to first rescue analgesia in patients receiving intrathecal clonidine was significantly delayed (283±14.18 min vs 231.50±26.18 min, p=0.001). Intraoperative hemodynamic changes were comparable and none of the patient suffered from respiratory depression, shivering, nausea or vomiting.Conclusions: Intrathecal clonidine as adjuvant to bupivacaine provided was clinically more effective than nalbuphine for prolonging the duration of analgesia for gynaecological procedures

Prescription pattern in ischemic heart disease inpatients at B. P. Koirala Institute of Health Sciences: a cross sectional study

Background: Drug utilization pattern studies seek to screen, evaluate and suggest appropriate modifications in prescription practices. It would help to make patient care rational and cost effective. Objective was to analyze the drug prescribing pattern for treatment of ischemic heart disease (IHD). Methods: A prospective cross-sectional observational study was conducted in patients of IHD admitted in intensive coronary care unit and medicine ward for the period of six months. Data were collected in preformed case record form. The data were analyzed for drug use indicators, demographic parameters, morbidities, pattern of drug use using Microsoft excel 2010. Results: A total of 145 patients were enrolled out of that 89 (61.38%) were males. The mean age was 60.01±12.71 years and majority (26.89%) belonged to age group of 61-70 years. A total of 1208 drugs were prescribed in 145 patients. Most frequently prescribed drugs were antiplatelet group of drugs 100% encounters, followed by hypo-lipidemics (98.62%). Average number of drugs per encounter was 8.33 and percentage of drugs prescribed by generic name was 5.04%.  Conclusions: IHD was more common in males than females. The most commonly prescribed drug classes were anti-platelet drugs followed by hypolipidemic agents

Microarray-based approach identifies microRNAs and their target functional patterns in polycystic kidney disease

Background: MicroRNAs (miRNAs) play key roles in mammalian gene expression and several cellular processes, including differentiation, development, apoptosis and cancer pathomechanisms. Recently the biological importance of primary cilia has been recognized in a number of human genetic diseases. Numerous disorders are related to cilia dysfunction, including polycystic kidney disease (PKD). Although involvement of certain genes and transcriptional networks in PKD development has been shown, not much is known how they are regulated molecularly. Results: Given the emerging role of miRNAs in gene expression, we explored the possibilities of miRNA-based regulations in PKD. Here, we analyzed the simultaneous expression changes of miRNAs and mRNAs by microarrays. 935 genes, classified into 24 functional categories, were differentially regulated between PKD and control animals. In parallel, 30 miRNAs were differentially regulated in PKD rats: our results suggest that several miRNAs might be involved in regulating genetic switches in PKD. Furthermore, we describe some newly detected miRNAs, miR-31 and miR-217, in the kidney which have not been reported previously. We determine functionally related gene sets, or pathways to reveal the functional correlation between differentially expressed mRNAs and miRNAs. Conclusion: We find that the functional patterns of predicted miRNA targets and differentially expressed mRNAs are similar. Our results suggest an important role of miRNAs in specific pathways underlying PKD

Comparative effectiveness of S-adenosylmethionine and etoricoxib in newly diagnosed patients of knee osteoarthritis

Background: Knee osteoarthritis is an important cause for morbidity in elderly people. Therapy is largely symptomatic with nonsteroidal anti-inflammatory drugs which pose risk in the elderly. Methionine is natural body constituent with novel property of blunting S-adenosylmethionine (SAMe) inflammatory process and cartilage degradation. The aim of this study was to compare effectiveness of SAMe, with standard etoricoxib therapy in newly diagnosed knee osteoarthritis cases.Methods: 127 newly diagnosed knee osteoarthritis patients were randomized into two groups. 55 participants received treatment  of etoricoxib 600 mg extended release once daily for 90 days (group 1) and 72 received  etoricoxib 600 mg extended release once daily and SAMe 400 mg twice daily  for initial 15 days followed by SAMe once daily 400 mg as maintenance dose for next 75 days  (group 2). The outcomes were measured by knee injury and osteoarthritis outcome score (KOOS). Pre and post treatment KOOS scores of all cases were separately pooled to define the median for whole as well as components of KOOS parameters. Relative frequencies of cases with values around respective medians were compared by MOODS median test. Patient characteristics, disease characteristics were also examined for bearing on outcomes besides the treatment.Results: SAMe treatment was associated with significantly greater improvement in symptoms, activities of daily life, spontaneous recreational activities and the quality of life compared to etoricoxib therapy. The therapy was well-tolerated.Conclusions: The study confirms SAMe as superior therapeutic option in osteoarthritis. SAMe indeed has been reported to have specific anti-arthritic effects and promotive to general well-being

Plasticity of rosette size in response to nitrogen availability is controlled by an RCC1-family protein

Nitrogen (N) is fundamental to plant growth, development and yield. Genes underlying N utilization and assimilation are well-characterized, but mechanisms underpinning plasticity of different phenotypes in response to N remain elusive. Here, using Arabidopsis thaliana accessions, we dissected the genetic architecture of plasticity in early and late rosette diameter, flowering time and yield, in response to three levels of N in the soil. Furthermore, we found that the plasticity in levels of primary metabolites were related with the plasticities of the studied traits. Genome-wide association analysis identified three significant associations for phenotypic plasticity, one for early rosette diameter and two for flowering time. We confirmed that the gene At1g19880, hereafter named as PLASTICITY OF ROSETTE TO NITROGEN 1 (PROTON1), encoding for a regulator of chromatin condensation 1 (RCC1) family protein, conferred plasticity of rosette diameter in response to N. Treatment of PROTON1 T-DNA line with salt implied that the reduced plasticity of early rosette diameter was not a general growth response to stress. We further showed that plasticities of growth and flowering-related traits differed between environmental cues, indicating decoupled genetic programs regulating these traits. Our findings provide a prospective to identify genes that stabilize performance under fluctuating environments.Peer reviewe

DEEP LEARNING-BASED INTRUSION DETECTION AND PREVENTION IN WIRELESS COMMUNICATION

Wireless sensor networks (WSNs) are made up of a large number of sensor nodes which collect data and send it to a centralized location. Nevertheless, the WSN has several security difficulties because of resource-constrained nodes, deployment methodologies, and communication channels. So, it is very necessary to identify illegal access in order to strengthen the safety measures of WSN. The use of network intrusion detection systems (IDS) to safeguard the network is now standard procedure for any communication system. While deep learning (DL) methods are often utilized in IDS, their efficacy falls short when faced with imbalanced attacks. An IDS based on a novel transfer deep multicolumn convolution neural network (TDMCNN) technique was presented in this study to address this problem and boost performance. The most significant features of the dataset are chosen using a cross-correlation procedure and then included into the suggested methods for detecting intrusions. The accuracy, precision, sensitivity, and specificity are used to conduct the analysis and comparison. The experimental findings verified the effectiveness of the suggested method over the status quo of deep learning models for attack detection

Innovation of System Biological Approach in Computational Drug Discovery

Computational methods like classification and network-based algorithms can be used to understand the mode of action and the efficacy of a given compound and to help elucidating the patho-physiology of a disease. In the pharmacological industry there has already been a shift from symptomatic oriented drugs that can relieve the symptoms but not the cause of the disease to pathology-based drugs whose targets are the genes and proteins involved in the etiology of the disease. Drugs targeting the affected pathway have thus the potential to become therapeutic. A network approach to drug design would examine the effect of drugs in the context of a network of relevant protein regulatory metabolic interactions resulting in the development of a drug that would hit multiple targets selected in such a way as to decrease network integrity and so completely disrupt the functioning of the network. The screening of a compound to quickly identify the proteins it interacts with gives us all the necessary tools to identify and repair the deregulated biological pathway causing the disease

Highlighting the Compound Risk of COVID-19 and Environmental Pollutants Using Geospatial Technology

The new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections.The authors acknowledge financial support from the Spanish Government, Grant RTI2018-354 094336-B-I00 (MCIU/AEI/FEDER, UE), the Spanish Carlos III Health Institute, COV 20/01213, and the Basque Government, Grant IT1207-19