Assessing Environmental Risks during the Drug Development Process for Parasitic Vector-Borne Diseases: A Critical Reflection

Parasitic vector-borne diseases (VBDs) represent nearly 20% of the global burden of infectious diseases. Moreover, the spread of VBDs is enhanced by global travel, urbanization, and climate change. Treatment of VBDs faces challenges due to limitations of existing drugs, as the potential for side effects in nontarget species raises significant environmental concerns. Consequently, considering environmental risks early in drug development processes is critically important. Here, we examine the environmental risk assessment process for veterinary medicinal products in the European Union and identify major gaps in the ecotoxicity data of these drugs. By highlighting the scarcity of ecotoxicological data for commonly used antiparasitic drugs, we stress the urgent need for considering the One Health concept. We advocate for employing predictive tools and nonanimal methodologies such as New Approach Methodologies at early stages of antiparasitic drug research and development. Furthermore, adopting progressive approaches to mitigate ecological risks requires the integration of nonstandard tests that account for real-world complexities and use environmentally relevant exposure scenarios. Such a strategy is vital for a sustainable drug development process as it adheres to the principles of One Health, ultimately contributing to a healthier and more sustainable world

Nucleoside analogues for the treatment of animal trypanosomiasis

Animal trypanosomiasis (AT) is a parasitic disease with high socio-economic impact. Given the limited therapeutic options and problems of toxicity and drug resistance, this study assessed redirecting our previously identified antitrypanosomal nucleosides for the treatment of AT. Promising hits were identified with excellent in vitro activity across all important animal trypanosome species. Compound 7, an inosine analogue, and our previously described lead compound, 3′-deoxytubercidin (8), showed broad spectrum anti-AT activity, metabolic stability in the target host species and absence of toxicity, but with variable efficacy ranging from limited activity to full cure in mouse models of Trypanosoma congolense and T. vivax infection. Several compounds show promise against T. evansi (surra) and T. equiperdum (dourine). Given the preferred target product profile for a broad-spectrum compound against AT, this study emphasizes the need to include T. vivax in the screening cascade given its divergent susceptibility profile and provides a basis for lead optimization toward such broad spectrum anti-AT compound

The effect of balance training and pilates on static and functional balance of elderly men

Background: Physiological changes related to aging and muscular disorders can increase the risk of falling, as a major problem of elderly group which in cases may even cause death. The purpose of this study was to compare the effects of a 6-week pilates and balance training program on static and functional balance among the elderly. Materials and Methods: In this quasi-experimental study, 30 elderly people selected from Kashmar (Khorasan province, Iran) were randomly divided into three groups: the balance training, pilates and control groups. The body-mass index and the static balance stork test were used in all three groups. The static and functional balance assessments were performed using the stork and timed up and go tests, respectively. All tests were repeated for the groups after six weeks of training (three sessions per week) in the same condition.Results: The mean values for the static and functional balance time were 5.51±0.55 and 10.71±6.72 before 4.42±0.90 and 28.42±8.88 after the balance training, respectively which showed a significant improvement (P=0.001vs P=0.023). However, the pilates training significantly improved only the static balance (P=0.027). Conclusion: It can be concluded that six weeks of balance training can improve both static and functional balance in the elderly men, while the pilates exercise can only improve the static balance of the elderly

Using Internet-based marketplaces to conduct surveys: an application to airline itinerary choice models

Within the transportation community, there has been increasing interest in using online outsourcing platforms such as Amazon Mechanical Turk (AMT) to conduct surveys. To date, transportation researchers’ use of AMT has been justified based on findings from studies in other fields. That is, to the best of our knowledge, there has been no study that has evaluated how the distribution of responses associated with each question and behavioral model estimated from AMT survey data compares to survey data collected from a traditional platform for a travel behavior application. This paper fills an important gap in the literature by examining (1) whether the distributions of responses from AMT and Qualtrics (a traditional market research firm) respondents are statistically equivalent, and (2) whether itinerary choice models estimated from these two surveys are statistically equivalent? Results show that AMT and Qualtrics respondents reported similar air trip characteristics and were drawn from a similar geographic distribution, but they exhibited distinct sociodemographic characteristics. After controlling for different age distributions in the two datasets, we found that airline itinerary choice models estimated from the AMT and Qualtrics survey data produced similar results, with the key difference related to price sensitivities. Our study provides preliminary evidence on the viability of using AMT and similar online outsourcing platforms for air travel behavior studies

Using Internet-based marketplaces to conduct surveys:an application to airline itinerary choice models

\u3cp\u3eWithin the transportation community, there has been increasing interest in using online outsourcing platforms such as Amazon Mechanical Turk (AMT) to conduct surveys. To date, transportation researchers’ use of AMT has been justified based on findings from studies in other fields. That is, to the best of our knowledge, there has been no study that has evaluated how the distribution of responses associated with each question and behavioral model estimated from AMT survey data compares to survey data collected from a traditional platform for a travel behavior application. This paper fills an important gap in the literature by examining (1) whether the distributions of responses from AMT and Qualtrics (a traditional market research firm) respondents are statistically equivalent, and (2) whether itinerary choice models estimated from these two surveys are statistically equivalent? Results show that AMT and Qualtrics respondents reported similar air trip characteristics and were drawn from a similar geographic distribution, but they exhibited distinct sociodemographic characteristics. After controlling for different age distributions in the two datasets, we found that airline itinerary choice models estimated from the AMT and Qualtrics survey data produced similar results, with the key difference related to price sensitivities. Our study provides preliminary evidence on the viability of using AMT and similar online outsourcing platforms for air travel behavior studies.\u3c/p\u3

A new twist on the gig economy: conducting surveys on Amazon Mechanical Turk

There is growing interest in using online outsourcing platforms that are part of the “gig economy” to conduct surveys for academic research. This interest has been driven in part by the belief that compared to traditional survey data collection methods, internet-based marketplaces such as Amazon Mechanical Turk (MTurk) enable one to collect survey data cheaper and faster from a larger, more diverse participant pool. However, many have questioned whether models based on survey data from these online marketplaces are similar to models based on survey data from more traditional platforms. To investigate this research question, we used MTurk and Qualtrics (a traditional market research firm) to survey air travelers. Our results showed that MTurk and Qualtrics respondents had distinct socio-demographic characteristics, but we found no statistical evidence for different air trip characteristics. In our data, proportionately more MTurk respondents were in the younger, single, male, and lower-income categories than for Qualtrics respondents. We found that airline itinerary choice models estimated from the MTurk and Qualtrics survey data were similar, with the key difference related to price sensitivities. Although our results provide evidence that MTurk can be used for travel demand modeling applications, we offer words of caution for others planning to conduct surveys in online marketplaces, particularly for those seeking to recruit more than 1000 participants or for those targeting specific geographic areas

A new twist on the gig economy: conducting surveys on Amazon Mechanical Turk

There is growing interest in using online outsourcing platforms that are part of the “gig economy” to conduct surveys for academic research. This interest has been driven in part by the belief that compared to traditional survey data collection methods, internet-based marketplaces such as Amazon Mechanical Turk (MTurk) enable one to collect survey data cheaper and faster from a larger, more diverse participant pool. However, many have questioned whether models based on survey data from these online marketplaces are similar to models based on survey data from more traditional platforms. To investigate this research question, we used MTurk and Qualtrics (a traditional market research firm) to survey air travelers. Our results showed that MTurk and Qualtrics respondents had distinct socio-demographic characteristics, but we found no statistical evidence for different air trip characteristics. In our data, proportionately more MTurk respondents were in the younger, single, male, and lower-income categories than for Qualtrics respondents. We found that airline itinerary choice models estimated from the MTurk and Qualtrics survey data were similar, with the key difference related to price sensitivities. Although our results provide evidence that MTurk can be used for travel demand modeling applications, we offer words of caution for others planning to conduct surveys in online marketplaces, particularly for those seeking to recruit more than 1000 participants or for those targeting specific geographic areas