10,718 research outputs found
A domino reaction of tetrahalo- 7,7-dimethoxybicyclo[2.2.1]heptenyl alcohols leading to indenones and a de novo synthesis of ninhydrin derivatives
An efficient acid induced rearrangement of a tetrahalo-7,7-dimethoxybicyclo[2.2.1]heptenyl system leading to substituted indenones is reported. This domino reaction involves dehydration, olefin isomerization, ketal hydrolysis, [3,3]-sigmatropic rearrangement and dehydrohalogenation. The resultant vicinal dihalo olefin moiety in the efficiently generated indenone derivatives was utilized to transform into ninhydrin derivatives by employing Ru(III)-catalyzed oxidation
Refeeding Syndrome: A Literature Review
Refeeding syndrome (RFS) describes the biochemical changes, clinical manifestations, and complications that can occur as a consequence of feeding a malnourished catabolic individual. RFS has been recognised in the literature for over fifty years and can result in serious harm and death. Crude estimates of incidence, morbidity, and mortality are available for specific populations. RFS can occur in any individual but more commonly occurs in at-risk populations. Increased awareness amongst healthcare professionals is likely to reduce morbidity and mortality. This review examines the physiology of RFS and describes the clinical manifestations. A management strategy is described. The importance of a multidisciplinary approach is emphasized
A convex selective segmentation model based on a piece-wise constant metric guided edge detector function
The challenge of segmentation for noisy images, especially those that have light in their backgrounds, is still exists in many advanced state-of-the-art segmentation models. Furthermore, it is significantly difficult to segment such images. In this article, we provide a novel variational model for the simultaneous restoration and segmentation of noisy images that have intensity inhomogeneity and high contrast background illumination and light. The suggested concept combines the multi-phase segmentation technology with the statistical approach in terms of local region knowledge and details of circular regions that are, in fact, centered at every pixel to enable in-homogeneous image restoration. The suggested model is expressed as a fuzzy set and is resolved using the multiplier alternating direction minimization approach. Through several tests and numerical simulations with plausible assumptions, we have evaluated the accuracy and resilience of the proposed approach over various kinds of real and synthesized images in the existence of intensity inhomogeneity and light in the background. Additionally, the findings are contrasted with those from cutting-edge two-phase and multi-phase methods, proving the superiority of our proposed approach for images with noise, background light, and inhomogeneity
Enhanced hypertension care through private clinics in Pakistan: a cluster randomised trial
Background Hypertension in Pakistan affects 33% of people aged ≥45 years, and in urban areas around 70% of basic health care occurs in private facilities.
Aim To assess whether enhanced care at urban private clinics resulted in better control of hypertension, cardiovascular disease (CVD) risk factors, and treatment adherence.
Design & setting A two-arm cluster randomised controlled trial was conducted at 26 private clinics (in three districts of Punjab) between January 2015–September 2016. Both arms had enhanced screening and diagnosis of hypertension and related conditions, and patient recording processes. Intervention facilities also had a clinical care guide, additional drugs for hypertension, a patient lifestyle education flipchart, associated training, and mobile phone follow-up.
Method Clinics were randomised in a 1:1 ratio (sealed envelope lottery method). A total of 574 intervention and 564 control patients in 13 clusters in each arm were recruited (male and female, aged ≥25 years, systolic blood pressure [SBP] >140 mmHg, and/or diastolic blood pressure [DBP] >90 mmHg). The primary outcome was change in SBP from baseline to 9-month follow-up.
Staff and patients were not blinded, but outcome assessors were blinded.
Results Nine-month primary outcomes were available for 522/574 (90.9%) intervention and 484/564 (85.8%) control participants (all clusters). The unadjusted cluster-level analysis results were as follows: mean intervention outcome was -25.2 mmHg (95% confidence intervals [CI] = -29.9 to
-20.6); mean control outcome was -9.4 mmHg (95% CI = 21.2 to 2.2); and mean control–intervention difference was 15.8 (95% CI = 3.6 to 28.0; P = 0.01).
Conclusion The findings and separate process evaluation support the scaling of an integrated CVD–hypertension care intervention in urban private clinics in areas lacking public primary care in Pakistan
Identification of genomic markers correlated with sensitivity in solid tumors to Dasatinib using sparse principal components
Background: Differential analysis techniques are commonly used to offer scientists a dimension reduction procedure and an interpretable gateway to variable selection, especially when confronting high-dimensional genomic data. Huang et al. used a gene expression profile of breast cancer cell lines to identify genomic markers which are highly correlated with in vitro sensitivity of a drug Dasatinib. They considered three statistical methods to identify differentially expressed genes and finally used the results from the intersection. But the statistical methods that are used in the paper are not sufficient to select the genomic markers.
Methods: In this paper we used three alternative statistical methods to select a combined list of genomic markers and compared the genes that were proposed by Huang et al. We then proposed to use sparse principal component analysis (PCA) to identify a final list of genomic markers. The sparse PCA incorporates correlation into account among the genes and helps to draw a successful genomic markers discovery.
Results: We present a new and a small set of genomic markers to separate out the groups of patients effectively who are sensitive to the drug Dasatinib. The analysis procedure will also encourage scientists in identifying genomic markers that can help to separate out two groups
An adaptive distributed Intrusion detection system architecture using multi agents
Intrusion detection systems are used for monitoring the network data, analyze them and find the intrusions if any. The major issues with these systems are the time taken for analysis, transfer of bulk data from one part of the network to another, high false positives and adaptability to the future threats. These issues are addressed here by devising a framework for intrusion detection. Here, various types of co-operating agents are distributed in the network for monitoring, analyzing, detecting and reporting. Analysis and detection agents are the mobile agents which are the primary detection modules for detecting intrusions. Their mobility eliminates the transfer of bulk data for processing. An algorithm named territory is proposed to avoid interference of one analysis agent with another one. A communication layout of the analysis and detection module with other modules is depicted. The inter-agent communication reduces the false positives significantly. It also facilitates the identification of distributed types of attacks. The co-ordinator agents log various events and summarize the activities in its network. It also communicates with co-ordinator agents of other networks. The system is highly scalable by increasing the number of various agents if needed. Centralized processing is avoided here to evade single point of failure. We created a prototype and the experiments done gave very promising results showing the effectiveness of the system
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