Evidence for CO2-rich fluids in rocks from the type charnockite area near Pallavaram, Tamil Nadu

Fluid inclusion and mineral chemistry data was presented for samples from the type charnockite area near Pallavaram (Tamil Nadu, India). The results indicate the presence of a dense CO2 fluid phase, but the data cannot distinguish between influx of this fluid from elsewhere or localized migration of CO2-rich fluids associated with dehydration melting

The Role of Orexin-A in Anxiety and the Emission of Ultrasonic Vocalizations in Rats

Central administration of orexin-A has been shown to activate autonomic arousal in rats, reliably inducing anxiety-like behaviours in the open field. To date, there has yet to be a study investigating the role of orexin-A in the communication of such negative affective state. In the current study, forty-six adult male rats were chronically cannulated and administered orexin-A into the medial preoptic area/anterior hypothalamic area to determine the effect of this neuropeptide on anxiety-like behaviour and the production of 22 kHz aversive ultrasonic vocalizations. It was found that intracerebral administration of orexin-A increased autonomic arousal as measured by a significant increase in fecal boli output, however orexin-A did not significantly affect locomotor activity or induce 22 kHz calling. These data suggest that orexin-A is involved in the regulation of the autonomic aspect of anxiety-like behaviour but not in the vocal communication of such negative affec

Defeating the Credit Card Scams Through Machine Learning Algorithms

Credit card fraud is a significant problem that is not going to go away. It is a growing problem and surged during the Covid-19 pandemic since more transactions are done without cash in hand now. Credit card frauds are complicated to distinguish as the characteristics of legitimate and fraudulent transactions are very similar. The performance evaluation of various Machine Learning (ML)-based credit card fraud recognition schemes are significantly pretentious due to data processing, including collecting variables and corresponding ML mechanism being used. One possible way to counter this problem is to apply ML algorithms such as Support Vector Machine (SVM), K nearest neighbor (KNN), Naive Bayes, and logistic regression. This research work aims to compare the ML as mentioned earlier models and its impact on credit card scam detection, especially in situations with imbalanced datasets. Moreover, we have proposed state of the art data balancing algorithm to solve data unbalancing problems in such situations. Our experiments show that the logistic regression has an accuracy of 99.91%, and naive bays have an accuracy of 97.65%. K nearest neighbor has an accuracy is 99.92%, support vector machine has an accuracy of 99.95%. The precision and accuracy comparison of our proposed approach shows that our model is state of the art

Cost-effectiveness of a model consultation to support self-management in patients with osteoarthritis

Objectives: The aim of this study was to estimate the cost-effectiveness of a model OA consultation for OA to support self-management compared with usual care. Methods: An incremental cost-utility analysis using patient responses to the three-level EuroQoL-5D (EQ-5D) questionnaire was undertaken from a UK National Health Service perspective alongside a two-arm cluster-randomized controlled trial. Uncertainty was explored through the use of cost-effectiveness acceptability curves. Results: Differences in health outcomes between the model OA consultation and usual care arms were not statistically significant. On average, visits to the orthopaedic surgeon were lower in the model OA consultation arm by -0.28 (95% CI: -0.55, -0.06). The cost-utility analysis indicated that the model OA consultation was associated with a non-significant incremental cost of £-13.11 (95% CI: -81.09 to 54.85) and an incremental quality adjusted life year (QALY) of -0.003 (95% CI: -0.03 to 0.02), with a 44% chance of being cost-effective at a threshold of £20 000 per QALY gained. The percentage of participants who took time off and the associated productivity cost were lower in the model OA consultation arm. Conclusion: Implementing National Institute for Health and Care Excellence guidelines using a model OA consultation in primary care does not appear to lead to increased costs, but health outcomes remain very similar to usual care. Even though the intervention seems to reduce the demand for orthopaedic surgery, overall it is unlikely to be cost-effective

Impact of socioeconomic deprivation on rate and cause of death in severe mental illness

Background: Socioeconomic status has important associations with disease-specific mortality in the general population. Although individuals with Severe Mental Illnesses (SMI) experience significant premature mortality, the relationship between socioeconomic status and mortality in this group remains under investigated.<p></p> Aims: To assess the impact of socioeconomic status on rate and cause of death in individuals with SMI (schizophrenia and bipolar disorder) relative to the local (Glasgow) and wider (Scottish) populations.<p></p> Methods: Cause and age of death during 2006-2010 inclusive for individuals with schizophrenia or bipolar disorder registered on the Glasgow Psychosis Clinical Information System (PsyCIS) were obtained by linkage to the Scottish General Register Office (GRO). Rate and cause of death by socioeconomic status, measured by Scottish Index of Multiple Deprivation (SIMD), were compared to the Glasgow and Scottish populations.<p></p> Results: Death rates were higher in people with SMI across all socioeconomic quintiles compared to the Glasgow and Scottish populations, and persisted when suicide was excluded. Differences were largest in the most deprived quintile (794.6 per 10,000 population vs. 274.7 and 252.4 for Glasgow and Scotland respectively). Cause of death varied by socioeconomic status. For those living in the most deprived quintile, higher drug-related deaths occurred in those with SMI compared to local Glasgow and wider Scottish population rates (12.3% vs. 5.9%, p = <0.001 and 5.1% p = 0.002 respectively). A lower proportion of deaths due to cancer in those with SMI living in the most deprived quintile were also observed, relative to the local Glasgow and wider Scottish populations (12.3% vs. 25.1% p = 0.013 and 26.3% p = <0.001). The proportion of suicides was significantly higher in those with SMI living in the more affluent quintiles relative to Glasgow and Scotland (54.6% vs. 5.8%, p = <0.001 and 5.5%, p = <0.001). Discussion and conclusions: Excess mortality in those with SMI occurred across all socioeconomic quintiles compared to the Glasgow and Scottish populations but was most marked in the most deprived quintiles when suicide was excluded as a cause of death. Further work assessing the impact of socioeconomic status on specific causes of premature mortality in SMI is needed

Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves

<p>Abstract</p> <p>Background</p> <p>The results of Randomized Controlled Trials (RCTs) on time-to-event outcomes that are usually reported are median time to events and Cox Hazard Ratio. These do not constitute the sufficient statistics required for meta-analysis or cost-effectiveness analysis, and their use in secondary analyses requires strong assumptions that may not have been adequately tested. In order to enhance the quality of secondary data analyses, we propose a method which derives from the published Kaplan Meier survival curves a close approximation to the original individual patient time-to-event data from which they were generated.</p> <p>Methods</p> <p>We develop an algorithm that maps from digitised curves back to KM data by finding numerical solutions to the inverted KM equations, using where available information on number of events and numbers at risk. The reproducibility and accuracy of survival probabilities, median survival times and hazard ratios based on reconstructed KM data was assessed by comparing published statistics (survival probabilities, medians and hazard ratios) with statistics based on repeated reconstructions by multiple observers.</p> <p>Results</p> <p>The validation exercise established there was no material systematic error and that there was a high degree of reproducibility for all statistics. Accuracy was excellent for survival probabilities and medians, for hazard ratios reasonable accuracy can only be obtained if at least numbers at risk or total number of events are reported.</p> <p>Conclusion</p> <p>The algorithm is a reliable tool for meta-analysis and cost-effectiveness analyses of RCTs reporting time-to-event data. It is recommended that all RCTs should report information on numbers at risk and total number of events alongside KM curves.</p

Earliest rock fabric formed in the Solar System preserved in a chondrule rim

Rock fabrics – the preferred orientation of grains – provide a window into the history of rock formation, deformation and compaction. Chondritic meteorites are among the oldest materials in the Solar System1 and their fabrics should record a range of processes occurring in the nebula and in asteroids, but due to abundant fine-grained material these samples have largely resisted traditional in situ fabric analysis. Here we use high resolution electron backscatter diffraction to map the orientation of sub-micrometre grains in the Allende CV carbonaceous chondrite: the matrix material that is interstitial to the mm-sized spherical chondrules that give chondrites their name, and fine-grained rims which surround those chondrules. Although Allende matrix exhibits a bulk uniaxial fabric relating to a significant compressive event in the parent asteroid, we find that fine-grained rims preserve a spherically symmetric fabric centred on the chondrule. We define a method that quantitatively relates fabric intensity to net compression, and reconstruct an initial porosity for the rims of 70-80% - a value very close to model estimates for the earliest uncompacted aggregates2,3. We conclude that the chondrule rim textures formed in a nebula setting and may therefore be the first rock fabric to have formed in the Solar System

Acute kidney disease and renal recovery : consensus report of the Acute Disease Quality Initiative (ADQI) 16 Workgroup

Consensus definitions have been reached for both acute kidney injury (AKI) and chronic kidney disease (CKD) and these definitions are now routinely used in research and clinical practice. The KDIGO guideline defines AKI as an abrupt decrease in kidney function occurring over 7 days or less, whereas CKD is defined by the persistence of kidney disease for a period of > 90 days. AKI and CKD are increasingly recognized as related entities and in some instances probably represent a continuum of the disease process. For patients in whom pathophysiologic processes are ongoing, the term acute kidney disease (AKD) has been proposed to define the course of disease after AKI; however, definitions of AKD and strategies for the management of patients with AKD are not currently available. In this consensus statement, the Acute Disease Quality Initiative (ADQI) proposes definitions, staging criteria for AKD, and strategies for the management of affected patients. We also make recommendations for areas of future research, which aim to improve understanding of the underlying processes and improve outcomes for patients with AKD