12,684 research outputs found
Factors associated with oral specialist referral of patients with Sjögren’s syndrome in a rheumatology tertiary centre
An alternative synthetic approach for 1,3- benzoxazine derivatives
1,3-benzoxazine derivatives were synthesized in high yield using three-step synthetic technique by the condensation of 2-hydroxybenzaldehyde with aromatic amines, reducing the condensation products and replacing the usual formaldehyde with methylene bromide to achieve ring closure. The structures of the benzoxazines were confirmed by FTIR, 1H and 13C NMR spectra and Mass spectroscopy
Balancing Demand, Quality and Efficiency in Nigerian Health Care Delivery System
The health sector is crucial to growth and development of a nation. Despite sound policies and interventions to develop the Nigerian health sector, it has witnessed several challenges that continue to reduce the progress and achievement of universal access to health care. Some of the factors that affect the overall performance of the health system include; inadequate health facilities/structure, poor human resources and management, poor remuneration and motivation, lack of fair and sustainable health care financing, unequal economic and political relations, the neo-liberal economic policies of the Nigerian state, corruption, illiteracy, very low government spending on health, high out-of-pocket expenditure in health and absence of integrated system for disease prevention, surveillance and treatment, inadequate mechanisms for families to access health care, shortage of essential drugs and supplies and inadequate supervision of health care providers are among some of the persistent problems of the health system in Nigeria. This paper looks at the enormity of the problems and recommends policy options vital to addressing the problems in order to attain the equilibrium in demand, quality and efficiency in the health care delivery system in Nigeria. Keywords: Demand, Quality, efficiency, health care system, Nigeri
Target Population Environments and Pest Distribution Modelling: An Approach towards Pest Prioritization and Preparedness
The transboundary crop pest and disease (P&D) outbreaks over large geographical regions jeopardizes the food security and have broad economic, social and environmental impacts. The upsurge of new crop P&D, such as fall armyworm; cassava mosaic and brown streak virus; banana fusarium wilt tropical race 4 and wheat stem rust Ug99 are having serious repercussions on agriculture. Climate change is, in part, responsible for food chain catastrophes arising from these transboundary P&D. However, there is clear evidence that climate change impacts are altering the distribution of crop P&D. Such accelerated events require more attention on a greater scale to strengthen food security and protect the livelihoods of poor and most vulnerable countries of the world. A well-defined P&D ranking and distribution will focus on supporting policy-making, integrated P&D management as well as tangible pre-emptive breeding strategies at large scale. Here, we have used chickpea homogenous systems units (HSUs) defined by mechanistic models and geo-bio-physical parameters; over which the P&D distribution and rankings were over-layered. The chickpea P&D severity, distributions, social impact and key drivers responsible for spread on these locations were identified by using meta-analysis. Further, in order to understand the possible risks and consequences of P&D population growth and geographical expansion, the CLIMEX package was used. We aim to compare the pest distribution generic models and prioritization methodologies for emerging regional specific P&D. These findings would support policy intrusions associated with long term transformative adaptation strategies for climate change
Cloud-Based Data Analytics on Human Factor Measurement to Improve Safer Transport
Improving safer transport includes individual and collective behavioural aspects and their interaction. A system that can monitor and evaluate the human cognitive and physical capacities based on human factor measurement is often beneficial to improve safety in driving condition. However, analysis and evaluation of human factor measurement i.e. demographics, behaviour and physiology in real-time is challenging. This paper presents a methodology for cloud-based data analysis, categorization and metrics correlation in real-time through a H2020 project called SimuSafe. Initial implementation of this methodology shows a step-by-step approach which can handle huge amount of data with variation and verity in the cloud
Therapeutically targeting the unique disease landscape of pediatric high-grade gliomas
Pediatric high-grade gliomas (pHGG) are a rare yet devastating malignancy of the central nervous system’s glial support cells, affecting children, adolescents, and young adults. Tumors of the central nervous system account for the leading cause of pediatric mortality of which high-grade gliomas present a significantly grim prognosis. While the past few decades have seen many pediatric cancers experiencing significant improvements in overall survival, the prospect of survival for patients diagnosed with pHGGs has conversely remained unchanged. This can be attributed in part to tumor heterogeneity and the existence of the blood-brain barrier. Advances in discovery research have substantiated the existence of unique subgroups of pHGGs displaying alternate responses to different therapeutics and varying degrees of overall survival. This highlights a necessity to approach discovery research and clinical management of the disease in an alternative subtype-dependent manner. This review covers traditional approaches to the therapeutic management of pHGGs, limitations of such methods and emerging alternatives. Novel mutations which predominate the pHGG landscape are highlighted and the therapeutic potential of targeting them in a subtype specific manner discussed. Collectively, this provides an insight into issues in need of transformative progress which arise during the management of pHGGs
Phenomenological Aspects of Gauge Mediation with Sequestered Supersymmetry Breaking in light of Dark Matter Detection
In a recent work, a model of gauge mediation with sequestered supersymmetry
(SUSY) breaking was proposed. In this model, the mass of the gravitino is
O(100) GeV without causing the flavor-changing neutral-current problem. In
contrast to traditional gauge mediation, the gravitino is not the lightest SUSY
particle and the neutralino is the candidate of the dark matter. In this paper,
we investigate phenomenological aspects of this model and discuss the
possibility of the direct detection of the dark matter. In particular, we focus
on the light neutralino case and find that the light-Higgsino scenario such as
the focus point is interesting, taking account of the recent CDMS result.Comment: 17 pages, 8 figures; v2:references added, some corrections;
v3:version accepted for publication in JHE
Loop-induced photon spectral lines from neutralino annihilation in the NMSSM
We have computed the loop-induced processes of neutralino annihilation into
two photons and, for the first time, into a photon and a Z boson in the
framework of the NMSSM. The photons produced from these radiative modes are
monochromatic and possess a clear "smoking gun" experimental signature. This
numerical analysis has been done with the help of the SloopS code, initially
developed for automatic one-loop calculation in the MSSM. We have computed the
rates for different benchmark points coming from SUGRA and GMSB soft SUSY
breaking scenarios and compared them with the MSSM. We comment on how this
signal can be enhanced, with respect to the MSSM, especially in the low mass
region of the neutralino. We also discuss the possibility of this observable to
constrain the NMSSM parameter space, taking into account the latest limits from
the FERMI collaboration on these two modes.Comment: 18 pages, 3 figures. Minor clarifications added in the text. Typing
mistakes and references corrected. Matches published versio
Validation of the OAKS prognostic model for acute kidney injury after gastrointestinal surgery
Background Postoperative acute kidney injury (AKI) is a common complication of major gastrointestinal surgery with an impact on short- and long-term survival. No validated system for risk stratification exists for this patient group. This study aimed to validate externally a prognostic model for AKI after major gastrointestinal surgery in two multicentre cohort studies.Methods The Outcomes After Kidney injury in Surgery (OAKS) prognostic model was developed to predict risk of AKI in the 7 days after surgery using six routine datapoints (age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker). Validation was performed within two independent cohorts: a prospective multicentre, international study ('IMAGINE') of patients undergoing elective colorectal surgery (2018); and a retrospective regional cohort study ('Tayside') in major abdominal surgery (2011-2015). Multivariable logistic regression was used to predict risk of AKI, with multiple imputation used to account for data missing at random. Prognostic accuracy was assessed for patients at high risk (greater than 20 per cent) of postoperative AKI.Results In the validation cohorts, 12.9 per cent of patients (661 of 5106) in IMAGINE and 14.7 per cent (106 of 719 patients) in Tayside developed 7-day postoperative AKI. Using the OAKS model, 558 patients (9.6 per cent) were classified as high risk. Less than 10 per cent of patients classified as low-risk developed AKI in either cohort (negative predictive value greater than 0.9). Upon external validation, the OAKS model retained an area under the receiver operating characteristic (AUC) curve of range 0.655-0.681 (Tayside 95 per cent c.i. 0.596 to 0.714; IMAGINE 95 per cent c.i. 0.659 to 0.703), sensitivity values range 0.323-0.352 (IMAGINE 95 per cent c.i. 0.281 to 0.368; Tayside 95 per cent c.i. 0.253 to 0.461), and specificity range 0.881-0.890 (Tayside 95 per cent c.i. 0.853 to 0.905; IMAGINE 95 per cent c.i. 0.881 to 0.899).Conclusion The OAKS prognostic model can identify patients who are not at high risk of postoperative AKI after gastrointestinal surgery with high specificity.Presented to Association of Surgeons in Training (ASiT) International Conference 2018 (Edinburgh, UK), European Society of Coloproctology (ESCP) International Conference 2018 (Nice, France), SARS (Society of Academic and Research Surgery) 2020 (Virtual, UK)
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