Substance Misuse Education for Physicians: Why Older People are Important.

This perspective article focuses on the need for training and education for undergraduate medical students on substance-related disorders, and describes initiatives undertaken in the United Kingdom (UK), Netherlands, United States (US), and Norway to develop the skills, knowledge, and attitudes needed by future doctors to treat patients adequately. In addition, we stress that in postgraduate training, further steps should be taken to develop Addiction Medicine as a specialized and transverse medical domain. Alcohol use disorder is a growing public health problem in the geriatric population, and one that is likely to continue to increase as the baby boomer generation ages. Prescription drug misuse is a major concern, and nicotine misuse remains problematic in a substantial minority. Thus, Addiction Medicine training should address the problems for this specific population. In recent years, several countries have started an Addiction Medicine specialty. Although addiction psychiatry has been a subspecialty in the UK and US for more than 20 years, in most countries it has been a more recent development. Additional courses on addiction should be integrated into the curriculum at both undergraduate and postgraduate levels, as well as form part of the continuous training of other medical specialists. It is recommended that further research and mapping of what is currently taught in medical programs be undertaken, so as to enhance medical education in addiction and improve treatment services

Parents' points of view: an evaluation of the M'Lop Tapang special needs programme, Cambodia

M’Lop Tapang is a registered non-governmental organisation working in South West Cambodia and providing services to 5000 vulnerable children and 2500 families. This evaluation was commissioned to review M’Lop Tapang’s special needs programme. Interviews were conducted with 35 parents / carers of children who receive services from M’Lop Tapang’s special needs programme . Nearly all of these parents / carers reported that they had noticed improvements in their children’s behaviour or functional ability since attending the programme. Significantly, almost all also reported a dramatic reduction in stress as a result of their child attending the programmes. While the study revealed many positive aspects of M'Lop Tapang’s special needs programme it also highlighted areas for improvement, particularly in areas of parental learning and education

Approximation Algorithms for the Capacitated Domination Problem

We consider the {\em Capacitated Domination} problem, which models a service-requirement assignment scenario and is also a generalization of the well-known {\em Dominating Set} problem. In this problem, given a graph with three parameters defined on each vertex, namely cost, capacity, and demand, we want to find an assignment of demands to vertices of least cost such that the demand of each vertex is satisfied subject to the capacity constraint of each vertex providing the service. In terms of polynomial time approximations, we present logarithmic approximation algorithms with respect to different demand assignment models for this problem on general graphs, which also establishes the corresponding approximation results to the well-known approximations of the traditional {\em Dominating Set} problem. Together with our previous work, this closes the problem of generally approximating the optimal solution. On the other hand, from the perspective of parameterization, we prove that this problem is {\it W[1]}-hard when parameterized by a structure of the graph called treewidth. Based on this hardness result, we present exact fixed-parameter tractable algorithms when parameterized by treewidth and maximum capacity of the vertices. This algorithm is further extended to obtain pseudo-polynomial time approximation schemes for planar graphs

The social return on investment of a new approach to heart failure in the Spanish National Health System

AIMS: We aim to agree on a set of proposals to improve the current management of heart failure (HF) within the Spanish National Health System (SNHS) and apply the social return on investment (SROI) method to measure the social impact that these proposals would generate. METHODS AND RESULTS: A multidisciplinary working team of 16 experts was set up, with representation from the main stakeholders regarding HF: medical specialists (cardiologists, internal medicine physicians, general practitioners, and geriatric physicians), nursing professionals, health management professionals, patients, and informal caregivers. This team established a set of proposals to improve the management of HF according to the main areas of HF care: emergency and hospitalization, primary care, cardiology, and internal medicine. A forecast-type SROI method, with a 1-year time frame, was applied to measure the social impact resulting from the implementation of these proposals. The required investment and social return were estimated and summarized into a ratio indicating how much social return could be generated for each euro invested. Intangible returns were included and quantified through financial proxies. The approach to improve the management of HF consisted of 28 proposals, including the implementation of a case management nurse network, standardization of operational protocols, psychological support, availability of echocardiography machines at emergency departments, stationary units and primary care, early specialist visits after hospital discharge, and cardiac rehabilitation units, among others. These proposals would benefit not only patients and their informal caregivers but also the SNHS. Regarding patients, proposals would increase their autonomy in everyday activities, decrease anxiety, increase psychological and physical well-being, improve pharmacological adherence and self-care, enhance understanding of the disease, delay disease progression, expedite medical assessment, and prevent the decrease in work productivity associated with HF management. Regarding informal caregivers, proposals would increase their quality of life; improve their social, economic, and emotional well-being; and reduce their care burden. The SNHS would benefit from shorter stays of HF patients at intensive care units and reduction of hospitalizations and admissions to emergency departments. The investment needed to implement these proposals would amount to euro548m and yield a social return of euro1932m, that is, euro3.52 for each euro invested. CONCLUSIONS: The current management of HF could be improved by a set of proposals that resulted in an overall positive social return, varying between areas of analysis. This may guide the allocation of healthcare resources and improve the quality of life of patients with HF

Contrast response function estimation with nonparametric Bayesian active learning

Multidimensional psychometric functions can typically be estimated nonparametrically for greater accuracy or parametrically for greater efficiency. By recasting the estimation problem from regression to classification, however, powerful machine learning tools can be leveraged to provide an adjustable balance between accuracy and efficiency. Contrast sensitivity functions (CSFs) are behaviorally estimated curves that provide insight into both peripheral and central visual function. Because estimation can be impractically long, current clinical workflows must make compromises such as limited sampling across spatial frequency or strong assumptions on CSF shape. This article describes the development of the machine learning contrast response function (MLCRF) estimator, which quantifies the expected probability of success in performing a contrast detection or discrimination task. A machine learning CSF can then be derived from the MLCRF. Using simulated eyes created from canonical CSF curves and actual human contrast response data, the accuracy and efficiency of the machine learning contrast sensitivity function (MLCSF) was evaluated to determine its potential utility for research and clinical applications. With stimuli selected randomly, the MLCSF estimator converged slowly toward ground truth. With optimal stimulus selection via Bayesian active learning, convergence was nearly an order of magnitude faster, requiring only tens of stimuli to achieve reasonable estimates. Inclusion of an informative prior provided no consistent advantage to the estimator as configured. MLCSF achieved efficiencies on par with quickCSF, a conventional parametric estimator, but with systematically higher accuracy. Because MLCSF design allows accuracy to be traded off against efficiency, it should be explored further to uncover its full potential

PHYTOCHEMICAL SCREENING AND ANALYSIS POLYPHENOLIC ANTIOXIDANT ACTIVITY OF METHANOLIC EXTRACT OF WHITE DRAGON FRUIT (Hylocereus undatus)

White dragon fruit is a well known and widely used herbal medicine, especially in Asia, which contains several interesting bioactive constituents and possesses health promoting properties. The aim of this study was to analyze for the bioactive compounds, evaluate total phenolic contents and antioxidant capacities of methanolic extract of white dragon fruit. The antioxidant activity was determined by the 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging activity assay. Total phenolic content were determined by Folin-Ciocalteu method. Phytochemical screening of the white dragon fruit showed the presence of triterpenoid, alkaloid, flavonoid and saponin. The extract exhibited strong antioxidant activity with IC50 of 193 μg/mL, and total phenolic content of 246 μg/mL in 1 Kg dry extract

Inhibition of Cholinergic Signaling Causes Apoptosis in Human Bronchioalveolar Carcinoma

Recent case-controlled clinical studies show that bronchioalveolar carcinomas (BAC) are correlated with smoking. Nicotine, the addictive component of cigarettes, accelerates cell proliferation through nicotinic acetylcholine receptors (nAChR). In this study, we show that human BACs produce acetylcholine (ACh) and contain several cholinergic factors including acetylcholinesterase (AChE), choline acetyltransferase (ChAT), choline transporter 1 (CHT1, SLC5A7), vesicular acetylcholine transporter (VAChT, SLC18A3), and nACh receptors (AChRs, CHRNAs). Nicotine increased the production of ACh in human BACs, and ACh acts as a growth factor for these cells. Nicotine-induced ACh production was mediated by α7-, α3β2-, and β3-nAChRs, ChAT and VAChT pathways. We observed that nicotine upregulated ChAT and VAChT. Therefore, we conjectured that VAChT antagonists, such as vesamicol, may suppress the growth of human BACs. Vesamicol induced potent apoptosis of human BACs in cell culture and nude mice models. Vesamicol did not have any effect on EGF or insulin-like growth factor-II–induced growth of human BACs. siRNA-mediated attenuation of VAChT reversed the apoptotic activity of vesamicol. We also observed that vesamicol inhibited Akt phosphorylation during cell death and that overexpression of constitutively active Akt reversed the apoptotic activity of vesamicol. Taken together, our results suggested that disruption of nicotine-induced cholinergic signaling by agents such as vesamicol may have applications in BAC therapy