DEVELOPMENT AND VALIDATION OF REVERSED PHASE HPLC-PDA METHOD FOR THE QUANTIFICATION OF CHRYSIN IN SOLID LIPID NANOPARTICLES

Objective: The main aim of the present study was to develop and validate a simple, precise and accurate Reversed-Phase HPLC-PDA method for the quantitative determination of Chrysin in solid lipid nanoparticles (SLNs). Methods: The RP-HPLC-PDA system equipped with a C-18 reversed-phase column (250 × 4.6 mm, particle size 5 μm) was employed in the present study. HPLC grade methanol and water in 85:15 (v/v) ratio was selected as the mobile phase at flow rate of 1 ml/min under an ambient column oven temperature. The detection wavelength was kept at 268 nm. Validation of developed method was performed according to the ICH guidelines. Results: The developed reversed-phase HPLC-PDA method was found to be linear in the concentration range of 0.2-10 µg/ml with a correlation coefficient of 0.999. The method was also observed to be precise with % relative standard deviation (RSD) below 2%. The limit of detection and limit of quantification of this method were found to be 0.05µg/ml and 0.14µg/ml, respectively. The percent recovery of the developed method was estimated to more than 99%. Conclusion: The developed HPLC method can be utilized for the determination of Chrysin with a high degree of accuracy, precision, robustness, specificity in solid lipid nanoparticles in the presence of excipients

Twitter Based Information Extraction

In the modern world of social media dominance, the microblogs like Twitter and Facebook are probably the best source of up-to-date information. The amount of information available on these platforms is huge, although most of it is unstructured and redundant which makes our task of extracting information from it much more challenging. This automatic extraction of information from noisy sources has opened up new opportunities for querying and analyzing data. This paper is a review of the research that has been done on extracting information like event dates [1] and classification of information from social networking platforms like Twitter. We present a brief study of the work which shows that extracting useful information from Twitter and other social media platforms is indeed feasible. We provide brief study about the extraction techniques applied by the applications based on this subject like the extraction tasks and the input exploited for extraction, the types of methods of extraction used and the type of output produced

Blockchain-enabled secured medical supply chain management

The medical supply chain management revolves around regulating medical goods and services from the producer to the ultimate user. The supply chain could be defined as a set of resources required to deliver products and services to the customer. Supply chain management is a complex and fragmented process in the medical industry. The medical supply chain enables the procurement of the required resources and delivery of the necessary equipment to the patient by ensuring that the healthcare facility has the required inventory. To complete the process, information and physical goods regarding medical services and products go through a personalised regress process based on the needs of manufacturers, hospitals, providers, insurance companies and regulatory agencies. However, promoting efficiency in the medical supply chain creates substantial opportunities for reducing costs across the organisation by hospitals and private practitioners. The medical supply chain involves the management of downstream and upstream relationships with customers and suppliers to deliver optimised customer value at less cost throughout the supply chain. The standards of the hospital are focused on making sure that the physicians are giving priority to the customers. Medical supply chain management revolves around distributing and procuring medical equipment from the inventory to the patient. The healthcare organisation needs to address the logistic issues, leading to increased supply costs which prevent them from meeting the quality standards within their budgets. This contributes to the complexity of medical supply chain management. However, medical supplies are not managed, which could lead to inadequate data reporting, poor standardisation of products, lack of automation in the process, and increasing requirements for regulation

Risk Factors Associated With Severe Hypoglycemia in Older Adults With Type 1 Diabetes

OBJECTIVE Severe hypoglycemia is common in older adults with long-standing type 1 diabetes, but little is known about factors associated with its occurrence

Risk of secondhand smoke exposure and severity of COVID-19 infection: multicenter case–control study

IntroductionExposure to secondhand smoke (SHS) is an established causal risk factor for cardiovascular disease (CVD) and chronic lung disease. Numerous studies have evaluated the role of tobacco in COVID-19 infection, severity, and mortality but missed the opportunity to assess the role of SHS. Therefore, this study was conducted to determine whether SHS is an independent risk factor for COVID-19 infection, severity, mortality, and other co-morbidities.MethodologyMulticentric case–control study was conducted across six states in India. Severe COVID-19 patients were chosen as our study cases, and mild and moderate COVID-19 as control were evaluated for exposure to SHS. The sample size was calculated using Epi-info version 7. A neighborhood-matching technique was utilized to address ecological variability and enhance comparability between cases and controls, considering age and sex as additional matching criteria. The binary logistic regression model was used to measure the association, and the results were presented using an adjusted odds ratio. The data were analyzed using SPSS version 24 (SPSS Inc., Chicago, IL, USA).ResultsA total of 672 cases of severe COVID-19 and 681 controls of mild and moderate COVID-19 were recruited in this study. The adjusted odds ratio (AOR) for SHS exposure at home was 3.03 (CI 95%: 2.29–4.02) compared to mild/moderate COVID-19, while SHS exposure at the workplace had odds of 2.19 (CI 95%: 1.43–3.35). Other factors significantly related to the severity of COVID-19 were a history of COVID-19 vaccination before illness, body mass index (BMI), and attached kitchen at home.DiscussionThe results of this study suggest that cumulative exposure to secondhand cigarette smoke is an independent risk factor for severe COVID-19 illness. More studies with the use of biomarkers and quantification of SHS exposure in the future are needed

Long- and short-range correlations and their event-scale dependence in high-multiplicity pp collisions at 1as = 13 TeV

Two-particle angular correlations are measured in high-multiplicity proton-proton collisions at s = 13 TeV by the ALICE Collaboration. The yields of particle pairs at short-( 06\u3b7 3c 0) and long-range (1.6 < | 06\u3b7| < 1.8) in pseudorapidity are extracted on the near-side ( 06\u3c6 3c 0). They are reported as a function of transverse momentum (pT) in the range 1 < pT< 4 GeV/c. Furthermore, the event-scale dependence is studied for the first time by requiring the presence of high-pT leading particles or jets for varying pT thresholds. The results demonstrate that the long-range \u201cridge\u201d yield, possibly related to the collective behavior of the system, is present in events with high-pT processes as well. The magnitudes of the short- and long-range yields are found to grow with the event scale. The results are compared to EPOS LHC and PYTHIA 8 calculations, with and without string-shoving interactions. It is found that while both models describe the qualitative trends in the data, calculations from EPOS LHC show a better quantitative agreement for the pT dependency, while overestimating the event-scale dependency. [Figure not available: see fulltext.

Neutral to charged kaon yield fluctuations in Pb – Pb collisions at sNN=2.76 TeV

We present the first measurement of event-by-event fluctuations in the kaon sector in Pb – Pb collisions at √sNN = 2.76 TeV with the ALICE detector at the LHC. The robust fluctuation correlator νdyn is used to evaluate the magnitude of fluctuations of the relative yields of neutral and charged kaons, as well as the relative yields of charged kaons, as a function of collision centrality and selected kinematic ranges. While the correlator νdyn[K+, K− ] exhibits a scaling approximately in inverse proportion of the charged particle multiplicity, νdyn[K0 S , K± ] features a significant deviation from such scaling. Within uncertainties, the value of νdyn[K0S , K± ] is independent of the selected transverse momentum interval, while it exhibits a pseudorapidity dependence. The results are compared with HIJING, AMPT and EPOS–LHC predictions, and are further discussed in the context of the possible production of disoriented chiral condensates in central Pb – Pb collisions