62 research outputs found

    An Improved Similarity Matching based Clustering Framework for Short and Sentence Level Text

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    Text clustering plays a key role in navigation and browsing process. For an efficient text clustering, the large amount of information is grouped into meaningful clusters. Multiple text clustering techniques do not address the issues such as, high time and space complexity, inability to understand the relational and contextual attributes of the word, less robustness, risks related to privacy exposure, etc. To address these issues, an efficient text based clustering framework is proposed. The Reuters dataset is chosen as the input dataset. Once the input dataset is preprocessed, the similarity between the words are computed using the cosine similarity. The similarities between the components are compared and the vector data is created. From the vector data the clustering particle is computed. To optimize the clustering results, mutation is applied to the vector data. The performance the proposed text based clustering framework is analyzed using the metrics such as Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR) and Processing time. From the experimental results, it is found that, the proposed text based clustering framework produced optimal MSE, PSNR and processing time when compared to the existing Fuzzy C-Means (FCM) and Pairwise Random Swap (PRS) methods

    AWAKENING CHARACTERISTICS AND RECOVERY OF COGNITIVE FUNCTION IN PATIENTS UNDERGOING SHORT SURGICAL PROCEDURES: COMPARISON BETWEEN DESFLURANE AND PROPOFOL

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    Objectives: Early awakening and recovery of the cognitive function improves post-operative outcome and early discharge of the patients. Desflurane and Propofol offer rapid emergence from anesthesia. We compared the awakening and recovery of cognitive function between these two agents. Methods: A total of 50 patients aged 30–60 years belonging to ASA 1 and 2 were studied. In both the groups baseline, Mini Mental State Examination (MMSE) score was recorded and were induced with Target controlled infusion (TCI) of Propofol to achieve plasma site concentration (Cp) of 6 mcg/ml. Group P continued with TCI Propofol Cp 3 mcg ml-1 and in group D, TCI was stopped and started Desflurane 6% end tidal concentration followed by Desflurane 3%. Hemodynamic variables were noted and after stopping the agent, time to eye open, squeeze hands, removal of laryngeal mask airway, state name, and modified Aldrete score were noted. MMSE score was recorded 1, 6, and 24 h postoperatively. Results: Awakening time was significantly shorter in duration in Desflurane group compared to Propofol. The mean time to eye open in the Propofol group was 10.41±2:31 min and Desflurane group was 06.21±01.42 min (***p=0.000). There was an increase in the mean MMSE score postoperatively at 6 h and 24 h interval when compared to the baseline within the groups. However, there was no difference in recovery of cognitive function between the two groups. Conclusion: The use of inhalational agent Desflurane provided shorter awakening time than intravenous Propofol in short surgical procedures but the recovery of cognitive function was comparable. There were no significant side effects

    Advancements in Natural Language Processing for Text Understanding

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    Natural language processing (NLP) developments have made it possible for robots to read and analyze human language with astounding precision, revolutionizing the field of text understanding. An overview of current advancements in NLP approaches and their effects on text comprehension are provided in this abstract. It examines significant developments in fields including named entity identification, sentiment analysis, semantic analysis, and question answering, highlighting the difficulties encountered and creative solutions put forth. To sum up, recent developments in natural language processing have raised the bar for text comprehension. Deep learning models and extensive pre-training have changed methods including semantic analysis, sentiment analysis, named entity identification, and question answering. These developments have produced text comprehension systems that are increasingly precise and complex. However, issues with prejudice, coreference resolution, and contextual comprehension still need to be resolved. The future of NLP for text understanding has considerable potential with continuing study and innovation, opening the door for increasingly sophisticated applications in numerous sectors

    Privacy-Preserving Data Mining and Analytics in Big Data

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    Privacy concerns have gotten more attention as Big Data has spread. The difficulties of striking a balance between the value of data and individual privacy have led to the emergence of privacy-preserving data mining and analytics approaches as a crucial area of research. An overview of the major ideas, methods, and developments in privacy-preserving data mining and analytics in the context of Big Data is given in this abstract. Data mining that protects privacy tries to glean useful insights from huge databases while shielding the private data of individuals. Commonly used in traditional data mining methods, sharing or pooling data might have serious privacy implications. On the other hand, privacy-preserving data mining strategies concentrate on creating procedures and algorithms that enable analysis without jeopardizing personal information. Finally, privacy-preserving data mining and analytics in the Big Data age bring important difficulties and opportunities. An overview of the main ideas, methods, and developments in privacy-preserving data mining and analytics are given in this abstract. It underscores the value of privacy in the era of data-driven decision-making and the requirement for effective privacy-preserving solutions to safeguard sensitive personal data while facilitating insightful analysis of huge datasets

    Medication adherence among diabetic and hypertensive patients in Al-Qassim region of Saudi Arabia

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    Non-adherence to medication is often an unrecognized risk factor that contributes to failure of the therapeutic plan. The purpose of the study was to identify factors related to high, medium and low medication adherence among adult Saudi patients with hypertension and diabetes mellitus. This study is designed as a descriptive cross sectional survey and was conducted in three tertiary care hospitals of Al-Qassim province of Saudi Arabia. The data was collected using the 8-item Morisky Medication Adherence Scale (MMAS-8) and analyzed by SPSS. Three levels of adherence were considered based on the following scores: 0 to <6 (low); 6 to <8 (medium); 8 (high). Of the 396 patients interviewed, 52% reported low adherence to prescribed medication. Multinomial logistic regression analysis was conducted. Gender, age, literacy level, duration of illness and type of chronic disease were negatively associated with medication adherence. The study shows very high proportion of low and medium adherence on long term medication, which may be responsible for the failure of achieving therapeutic outcome. Further investigation is required to evaluate the applicability of MMAS-8 as a tool of measuring medication adherence among Saudi patients with chronic diseases. Adherence enhancing strategies should also be evaluated in separate patients group

    Genetic effects on gene expression across human tissues

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    Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

    Redox cycling metals: Pedaling their roles in metabolism and their use in the development of novel therapeutics

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    Essential metals, such as iron and copper, play a critical role in a plethora of cellular processes including cell growth and proliferation. However, concomitantly, excess of these metal ions in the body can have deleterious effects due to their ability to generate cytotoxic reactive oxygen species (ROS). Thus, the human body has evolved a very well-orchestrated metabolic system that keeps tight control on the levels of these metal ions. Considering their very high proliferation rate, cancer cells require a high abundance of these metals compared to their normal counterparts. Interestingly, new anti-cancer agents that take advantage of the sensitivity of cancer cells to metal sequestration and their susceptibility to ROS have been developed. These ligands can avidly bind metal ions to form redox active metal complexes, which lead to generation of cytotoxic ROS. Furthermore, these agents also act as potent metastasis suppressors due to their ability to up-regulate the metastasis suppressor gene, N-myc downstream regulated gene 1. This review discusses the importance of iron and copper in the metabolism and progression of cancer, how they can be exploited to target tumors and the clinical translation of novel anti-cancer chemotherapeutics

    Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

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    Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

    Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

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    Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

    A reference map of the human binary protein interactome.

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    Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships(1,2). Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome(3), transcriptome(4) and proteome(5) data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes
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