Drug Susceptibility in Leishmania Isolates Following Miltefosine Treatment in Cases of Visceral Leishmaniasis and Post Kala-Azar Dermal Leishmaniasis

Resistance to antimonials has emerged as a major hurdle to the treatment and control of VL and led to the introduction of Miltefosine as first line treatment in the Indian subcontinent. MIL is an oral drug with a long half-life, and it is feared that resistance may emerge rapidly, threatening control efforts under the VL elimination program. There is an urgent need for monitoring treatment efficacy and emergence of drug resistance in the field. In a set of VL/PKDL cases recruited for MIL treatment, we observed comparable drug susceptibility in pre- and post-treatment isolates from cured VL patients while MIL susceptibility was significantly reduced in isolates from VL relapse and PKDL cases. The PKDL isolates showed higher tolerance to MIL as compared to VL isolates. Both VL and PKDL isolates were uniformly susceptible to PMM. MIL transporter genes LdMT/LdRos3 were previously reported as potential resistance markers in strains in which MIL resistance was experimentally induced. The point mutations and the down-regulated expression of these transporters observed in vitro could, however, not be verified in natural populations of parasites. LdMT/LdRos3 genes therefore, do not appear to be suitable markers so far for monitoring drug susceptibility in clinical leishmanial isolates

Utilising information foraging theory for user interaction with image query auto-completion

Query Auto-completion (QAC) is a prominently used feature in search engines, where user interaction with such explicit feature is facilitated by the possible automatic suggestion of queries based on a prefix typed by the user. Existing QAC models have pursued a little on user interaction and cannot capture a user’s information need (IN) context. In this work, we devise a new task of QAC applied on an image for estimating patch (one of the key components of Information Foraging Theory) probabilities for query suggestion. Our work supports query completion by extending a user query prefix (one or two characters) to a complete query utilising a foraging-based probabilistic patch selection model. We present iBERT, to fine-tune the BERT (Bidirectional Encoder Representations from Transformers) model, which leverages combined textual-image queries for a solution to image QAC by computing probabilities of a large set of image patches. The reflected patch probabilities are used for selection while being agnostic to changing information need or contextual mechanisms. Experimental results show that query auto-completion using both natural language queries and images is more effective than using only language-level queries. Also, our fine-tuned iBERT model allows to efficiently rank patches in the image

Augmented Reality: What Motivates Late Millennials towards Fashion Mobile Apps?

Generation Z is expected to be a dominant demographic and economic group. Cyber-waviness, constant reliance on smart devices that allows them to be always connected are among some of their intrinsic characteristics. The combination of this reality with the ever-changing technological environment is compelling retailers to reshape their business strategies, to meet this group desires and expectations and to foster their engagement. Augmented reality (AR) is emerging as a technological solution that pleases both consumers and retailers. This paper aims to answer two main questions: (1) How does generation Z evaluate an AR experience? (2) Which attributes/benefits do they value or not during an AR experience? Drawing on a qualitative methodology – content analysis of 34 interviewees – we discuss six main dimensions the potential customer value of the relationship between them and AR experiences under retailer context.info:eu-repo/semantics/publishedVersio

One moment, please: can the speed and quality of political contact affect democratic health

Contact between politicians and their constituents is the cornerstone of democracies globally but an area of scholarship that remains relatively underdeveloped. Political contact can help convey authority, provide legitimacy and facilitate governance. This article goes beyond the assumption that representatives need to communicate more with the public and suggests, instead, that the quality of contact matters. Focusing on four processes by which citizens can contact their representatives (face-to-face, by letter, email or social media), we employ an experimental vignette methodology to test whether the character and timeliness of politicians’ responses to citizen communication affects two indicators of democratic health: (a) the latter’s satisfaction with political contact and (b) their likelihood to re-contact representatives. Our findings provide evidence that personalised communication and to a smaller extent, speed of response, can influence citizen satisfaction and their likelihood of re-engagement. This suggests politicians can improve these indicators of democratic health by adjusting the style of political contact and communication

Modelling trust formation in health information contexts

This study explores trust formation in the context of health information. Trust as an interpersonal notion, when formed in a vulnerable state, is a response or belief about how the trusted will behave towards the trustor. This study focuses on the process of assessing the trustworthiness of information, in a dependency state of information need, through the identification of the many factors influencing this assessment. A set of propositions are developed to suggest the criteria by which trustworthiness is assessed as well as the factors that influence these judgements. The proposed model is tested in a large-scale survey using a trust inventory with factor analysis to explore the constructs of trust formation. Structural equation modelling is used to explore the relationship among the identified criteria and their influencing factors. The resulting framework contributes to the understanding of trust formation in digital information contexts on the criteria of usefulness and credibility and further research into the influencing factors is recommended

Options for Active Case Detection of Visceral Leishmaniasis in Endemic Districts of India, Nepal and Bangladesh, Comparing Yield, Feasibility and Costs

For the elimination of any infectious disease (i.e., reduction of the burden of a serious public health problem to a minor problem which can be managed by the general health services) the right mix of public health tools has to be identified for the early detection and successful treatment of new cases as well as effective vector control (in the case of vector borne diseases) at affordable costs. The paper provides a powerful example of evidence building for cost-effective early case detection in the visceral leishmaniasis elimination initiative of Bangladesh, India and Nepal. It compares the camp approach (mobile teams testing in chronic fever camps for spleen enlargement and rapid diagnostic tests) with the index case approach (screening for new cases in the neighbourhood of reported visceral leishmaniasis patients) and the incentive based approach (where basic health workers receive an allowance for detecting a new case) using subsequent house-to-house screening for the identification of the real number of un-detected cases. By applying a mix of different study methods and an itinerate research process to identify the most effective, feasible and affordable case detection method, under different environmental conditions, recommendations could be developed which help governments in shaping their visceral leishmaniasis elimination strategy

Here Comes the Bad News: Doctor Robot Taking Over

To test in how far the Media Equation and Computers Are Social Actors (CASA) validly explain user responses to social robots, we manipulated how a bad health message was framed and the language that was used. In the wake of Experiment 2 of Burgers et al. (Patient Educ Couns 89(2):267–273, 2012. https://doi.org/10.1016/j.pec.2012.08.008), a human versus robot doctor delivered health messages framed positively or negatively, using affirmations or negations. In using frequentist (robots are different from humans) and Bayesian (robots are the same) analyses, we found that participants liked the robot doctor and the robot’s message better than the human’s. The robot also compelled more compliance to the medical treatment. For the level of expected quality of life, the human and robot doctor tied. The robot was not seen as affectively distant but rather involving, ethical, skilled, and people wanted to consult her again. Note that doctor robot was not a seriously looking physician but a little girl with the voice of a young woman. We conclude that both Media Equation and CASA need to be altered when it comes to robot communication. We argue that if certain negative qualities are filtered out (e.g., strong emotion expression), credibility will increase, which lowers affective distance to the messenger. Robots sometimes outperform humans on emotional tasks, which may relieve physicians from a most demanding duty of disclosing unfavorable information to a patient

Prevalence of prehypertension and associated cardiovascular risk profiles among prediabetic Omani adults

<p>Abstract</p> <p>Background</p> <p>The importance of prediabetes and prehypertension has been demonstrated in several studies especially for primary prevention of CVD. A recent community based cross-sectional study revealed that 40.9 percent Omani adults are prediabetics. This study was undertaken to estimate the prevalence of prehypertension and associated cardiovascular risk profiles in prediabetics. To best of our knowledge, this is the first report on this subject.</p> <p>Methods</p> <p>The study included 327 confirmed pre-diabetic Omani adults, who were analysed for their demographic, metabolic and behavioral characteristics. These characteristics were compared between the three different blood pressure groups to determine the CVD risk factors. Univariate and step-wise multiple logistic regression methods were used to carry out the analysis of the data.</p> <p>Results</p> <p>In this study, the prevalence of prehypertension was 54.1 percent. Males were at higher risk of developing prehypertension as compared to females (OR = 2.30, 95% CI: 1.21, 4.38; P < 0.01). The individuals with higher BMI have two fold more risk of developing prehypertension (OR = 2.25, 95% CI: 1.26, 4.02; P < 0.01). The increased level of OGT enhanced the risk of developing prehypertension (OR = 1.26, 95% CI: 1.06, 1.50; P < 0.01).</p> <p>Conclusion</p> <p>A high prevalence of prehypertension (54.1%) exists in this study population. The major determinants of prehypertension in these prediabetic subjects were male gender, increasing dysglycemia and BMI. Appropriate intervention strategies have been suggested.</p

Quantifying Age-Related Differences in Information Processing Behaviors When Viewing Prescription Drug Labels

Adverse drug events (ADEs) are a significant problem in health care. While effective warnings have the potential to reduce the prevalence of ADEs, little is known about how patients access and use prescription labeling. We investigated the effectiveness of prescription warning labels (PWLs, small, colorful stickers applied at the pharmacy) in conveying warning information to two groups of patients (young adults and those 50+). We evaluated the early stages of information processing by tracking eye movements while participants interacted with prescription vials that had PWLs affixed to them. We later tested participants’ recognition memory for the PWLs. During viewing, participants often failed to attend to the PWLs; this effect was more pronounced for older than younger participants. Older participants also performed worse on the subsequent memory test. However, when memory performance was conditionalized on whether or not the participant had fixated the PWL, these age-related differences in memory were no longer significant, suggesting that the difference in memory performance between groups was attributable to differences in attention rather than differences in memory encoding or recall. This is important because older adults are recognized to be at greater risk for ADEs. These data provide a compelling case that understanding consumers’ attentive behavior is crucial to developing an effective labeling standard for prescription drugs