Developmental stress elicits preference for methamphetamine in the spontaneously hypertensive rat model of attention-deficit/hyperactivity disorder

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Study Justification:
The study aimed to investigate the effects of developmental stress on the preference for methamphetamine in an animal model of attention-deficit/hyperactivity disorder (ADHD). This is important because developmental stress has been hypothesized to interact with genetic predisposition to increase the risk of developing substance use disorders. Understanding the relationship between stress and substance use disorders in individuals with ADHD can provide valuable insights for prevention and treatment strategies.
Highlights:
– The study used a conditioned place preference paradigm to assess the preference for methamphetamine in different rat strains.
– Maternal separation-induced developmental stress was found to increase the preference for the methamphetamine-associated compartment in spontaneously hypertensive rats, a genetic rat model of ADHD.
– The study also found that maternal separation increased behavioral sensitization to the locomotor-stimulatory effects of methamphetamine in spontaneously hypertensive and Sprague-Dawley strains, but not in Wistar Kyoto rats.
– These findings suggest that developmental stress in individuals with ADHD may increase vulnerability to the development of substance use disorders.
Recommendations:
Based on the study findings, the following recommendations can be made:
1. Further research should be conducted to explore the underlying mechanisms through which developmental stress interacts with genetic predisposition to increase the risk of substance use disorders in individuals with ADHD.
2. Prevention and intervention strategies should be developed to target individuals with ADHD who have experienced developmental stress, in order to reduce the risk of substance use disorders.
3. Healthcare professionals should be aware of the increased vulnerability to substance use disorders in individuals with ADHD who have experienced developmental stress, and provide appropriate support and treatment.
Key Role Players:
1. Researchers and scientists specializing in ADHD, substance use disorders, and developmental stress.
2. Healthcare professionals, including psychiatrists, psychologists, and addiction specialists.
3. Policy makers and government officials responsible for developing and implementing prevention and treatment programs for substance use disorders.
4. Animal care and research facility staff responsible for maintaining and providing the necessary resources for the animal models used in the study.
Cost Items for Planning Recommendations:
1. Research funding for further studies investigating the mechanisms underlying the interaction between developmental stress and genetic predisposition to substance use disorders in individuals with ADHD.
2. Funding for the development and implementation of prevention and intervention programs targeting individuals with ADHD who have experienced developmental stress.
3. Resources for training healthcare professionals in identifying and providing appropriate support and treatment for individuals with ADHD and substance use disorders.
4. Budget for maintaining and operating animal care and research facilities to support ongoing studies in this field.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides specific details about the study design, methodology, and results. However, it lacks information about sample size and statistical analysis. To improve the evidence, the authors could include the sample size for each group and provide more details about the statistical tests used, including the p-values and effect sizes.

Background: Developmental stress has been hypothesised to interact with genetic predisposition to increase the risk of developing substance use disorders. Here we have investigated the effects of maternal separation-induced developmental stress using a behavioural proxy of methamphetamine preference in an animal model of attention-deficit/hyperactivity disorder, the spontaneously hypertensive rat, versus Wistar Kyoto and Sprague-Dawley comparator strains. Results: Analysis of results obtained using a conditioned place preference paradigm revealed a significant strain × stress interaction with maternal separation inducing preference for the methamphetamine-associated compartment in spontaneously hypertensive rats. Maternal separation increased behavioural sensitization to the locomotor-stimulatory effects of methamphetamine in both spontaneously hypertensive and Sprague-Dawley strains but not in Wistar Kyoto rats. Conclusions: Our findings indicate that developmental stress in a genetic rat model of attention-deficit/hyperactivity disorder may foster a vulnerability to the development of substance use disorders.

SHR (Charles River Laboratories, Wilmington, MA, USA), WKY (Harlan Laboratories, Bicester, UK) and SD (Charles River Laboratories, Wilmington, MA, USA) rats were obtained from strains maintained at the University of Cape Town Research Animal Facility. The decision to source WKY from Harlan, UK, rather than Charles River Laboratories, was based on research suggesting that they are the most appropriate behavioural and genetic control [24]. Rats had ad libitum access to water and standard rat chow and were housed in clear Perspex cages with wood chip bedding in a facility maintained at 21–23 °C with a 12/12 h light/dark cycle (lights on at 06h00). All experiments were authorised by the University of Cape Town Faculty of Health Sciences Animal Ethics Committee under application 011/047 and conformed to local and international standards set out for the care and use of animals for scientific purposes [28, 29]. The MS paradigm was performed as previously described [30]. Briefly, male and female rats were pair bred in the University of Cape Town Human Biology satellite animal facility and the day of birth of the resulting litters was designated as postnatal day 0 (P0). On P2, the dam was removed from the cage and the number and sex of the pups was determined. In order to maintain uniformity of care, litters were culled to 8 pups with males preferentially selected for. However, a minimum of 2 female pups were retained in each litter to control for possible altered maternal behaviour and subsequent anxiety in offspring due to varying litter gender composition [31, 32]. Dams of non-separated (nMS) litters were subsequently returned to the home cage and remained with the litter in the animal facility until weaning. Conversely, on P2 MS litters were removed from the dam to a separate room maintained at 31–33 °C with infrared heating lamps. Three hours later the litters were returned to the animal facility and the dam returned to the home cage. This separation paradigm occurred between 09h00 and 13h00 over 13 days from P2 to P14. Cleaning of cages and the initial handling of pups on P2 was consistent across MS and nMS groups to ensure that potential differences would be due to the effect of the separation paradigm. On P21 litters were weaned and male rats we co-housed (2–4 rats/cage) for the remainder of the project. No more than 2 rats from any one litter were assigned to an experimental group so as to avoid potential confounding litter effects. The CPP paradigm was performed over the course of 7 days (P54–P60) in male adolescent rats, thereby corresponding with the most common age of onset for SUDs in humans [33]. This compressed protocol consisted of 3 preconditioning, 3 conditioning and 1 probe trial day. Briefly, a square black Perspex box (43 cm length × 50 cm height) was equally divided by a central partition to produce one chamber with a grid floor and thin vertical white stripes on the walls and a second chamber with unadorned walls and a smooth floor. Rats were allowed to freely explore the apparatus for 30 min during preconditioning, which was performed over the course of 3 days to compensate for the increased exploratory drive and preference for novelty in SHR as well as potential anxiety in WKY [34]. The compartment in which rats spent the most time on the 3rd day of testing was designated as the preferred compartment. The conditioning period was composed of 2 × 1-h trials per day with a vehicle (0.9 % saline administered via intraperitoneal injection at 1 ml/kg volume) injection paired with the preferred compartment, and a methamphetamine (Sigma-Aldrich, St Louis, MO, USA) injection (1.5 mg/kg in 0.9 % saline administered via intraperitoneal injection at 1 ml/kg) paired with the non-preferred compartment. These 2 trials were separated by at least 3 h to allow sufficient time for memory formation with the non-drug pairing conducted first to prevent the association of potential withdrawal effects with the subsequent trial [27]. The selected dose of methamphetamine (1.5 mg/kg calculated as a free base) was based on 3 factors: successful CPP in SHR following conditioning with a 1.25 mg/kg dose; the failure to find an effect of MS on place preference in SD rats administered a 1.0 mg/kg dose; and the need to avoid potential neurotoxic side effects associated with a higher dose, which might reduce locomotor activity due to depressive effects [35–38]. As caudate putamen methamphetamine concentrations peak between 30 and 60 min post intraperitoneal injection, rats were injected 10 min prior to the onset of conditioning trials to ensure that peak cerebral concentrations of methamphetamine were reached within the 1 h conditioning trial [39]. On the final day of testing, P60, rats were exposed to a 30 min probe trial during which they were allowed to freely explore the apparatus. Behaviour was recorded using a Soni Handicam DCR-SX 83E and time spent in each compartment as well as locomotor activity were analysed using Noldus Ethovision XT 7.0 (Noldus Information Technology, Wageningen, Netherlands). This experimental design produced 6 final groups: nMS SHR (n = 13), MS SHR (n = 11), nMS WKY (n = 10), MS WKY (n = 13), nMS SD (n = 13) and MS SD (n = 10). All data were tested for normal distribution using a Shapiro–Wilk W test. Baseline activity data over the course of the 3 preconditioning days was analysed to check for strain and stress effects. The time spent highly mobile (defined as the period of time during which the area detected as the animal changes by at least 60 % per second) was non-parametrically distributed and therefore tested for potential strain × stress effects using a Kruskal–Wallis test with multiple comparisons of mean ranks with Bonferroni adjustment as a post hoc test. To check for differences in the initial strength of compartment preference, the duration spent in the non-preferred compartment on the third day of preconditioning was subjected to a factorial ANOVA with strain and stress as categorical predictors. Significant differences were further investigated using a Tukey post hoc test. Methamphetamine preference scores were calculated by subtracting the time spent in the non-preferred compartment on the third day of preconditioning from the time spent in the same compartment during the probe trial. Therefore a positive value, i.e. increased time spent in the non-preferred compartment following methamphetamine conditioning, was taken as an indication of increased preference for the drug-paired compartment. Preference scores were normally distributed and thus analysed using a factorial ANOVA with strain and stress as categorical factors. Significant differences between groups were probed using a Tukey post hoc test. To determine which groups displayed behavioural sensitisation to methamphetamine, the total distance covered and the time spent highly mobile on the first and third days of conditioning were compared. As these data were non-parametrically distributed, they were analysed with a Wilcoxon Matched Pairs Test. To check for strain × stress effects on sensitisation, we subjected the mobility data to an aligned rank transform for nonparametric factorial analyses [40]. This preprocessing allows common ANOVA procedures to be used to investigate interaction effects in repeated measures non-parametrically distributed data. All statistical analyses were performed using Statistica 13 (Statsoft, Dell Software, Tulsa, OK, USA) and an α value of 0.05 was used to determine significance. Graphs were generated using GraphPad Prism 6.0 (GraphPad, La Jolla, CA, USA).

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Based on the provided information, it seems that the text is a scientific research article discussing the effects of developmental stress on methamphetamine preference in an animal model of attention-deficit/hyperactivity disorder. It includes details about the experimental design, methods, and statistical analyses used in the study.

However, it does not provide any specific innovations or recommendations for improving access to maternal health. If you have any specific questions or need assistance with a different topic related to maternal health, please let me know and I’ll be happy to help.
AI Innovations Description
The provided description does not directly relate to improving access to maternal health. However, based on the information provided, it appears to be a research study investigating the effects of developmental stress on methamphetamine preference in an animal model of attention-deficit/hyperactivity disorder. The study involved using different rat strains, maternal separation, and a conditioned place preference paradigm.

To improve access to maternal health, it is important to focus on interventions and innovations that directly address the barriers and challenges faced by pregnant women and new mothers. Some recommendations to improve access to maternal health include:

1. Strengthening healthcare systems: This involves improving the availability and quality of maternal health services, ensuring an adequate number of skilled healthcare providers, and enhancing the infrastructure and resources of healthcare facilities.

2. Increasing awareness and education: Implementing comprehensive public health campaigns to raise awareness about the importance of maternal health, promoting prenatal and postnatal care, and providing education on healthy pregnancy and childbirth practices.

3. Addressing socio-economic factors: Identifying and addressing socio-economic factors that hinder access to maternal health, such as poverty, lack of transportation, and limited access to nutritious food. This may involve providing financial support, transportation services, and nutritional assistance to pregnant women and new mothers.

4. Empowering women: Promoting women’s rights and empowerment, ensuring their active participation in decision-making processes related to their own health, and providing access to information and resources that enable them to make informed choices about their maternal health.

5. Utilizing technology and innovation: Exploring the use of technology and innovative solutions to improve access to maternal health, such as telemedicine for remote consultations, mobile health applications for prenatal care monitoring, and community-based interventions using digital platforms.

It is important to note that these recommendations are general and may need to be tailored to specific contexts and populations. Additionally, further research and evaluation are necessary to determine the effectiveness and feasibility of these recommendations in improving access to maternal health.
AI Innovations Methodology
I’m sorry, but I’m unable to provide recommendations for innovations to improve access to maternal health based on the information you provided. The description you provided seems to be unrelated to maternal health and focuses on a study involving developmental stress and substance use disorders in rats.

To improve access to maternal health, some potential recommendations could include:

1. Telemedicine: Implementing telemedicine services to provide remote access to prenatal care, postnatal care, and consultations with healthcare providers. This can be particularly beneficial for women in rural or remote areas who may have limited access to healthcare facilities.

2. Mobile clinics: Setting up mobile clinics that can travel to underserved areas to provide maternal health services, including prenatal care, vaccinations, and health education. This can help reach women who may face transportation barriers or live far from healthcare facilities.

3. Community health workers: Training and deploying community health workers who can provide basic maternal health services, education, and support in local communities. These workers can help bridge the gap between healthcare facilities and the community, improving access to care.

4. Financial incentives: Implementing financial incentives, such as subsidies or cash transfers, to encourage women to seek and utilize maternal health services. This can help address financial barriers that may prevent women from accessing care.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include:

1. Data collection: Gather data on the current state of maternal health access, including the number of women accessing care, distance to healthcare facilities, and any existing barriers.

2. Modeling: Use mathematical modeling techniques to simulate the potential impact of the recommendations on improving access to maternal health. This can involve creating a simulation model that takes into account factors such as population demographics, geographic distribution, and healthcare infrastructure.

3. Scenario analysis: Run different scenarios in the simulation model to assess the potential impact of each recommendation. This can involve adjusting variables such as the number of telemedicine consultations, the frequency of mobile clinic visits, or the number of community health workers deployed.

4. Outcome evaluation: Evaluate the outcomes of each scenario, such as the increase in the number of women accessing maternal health services, the reduction in travel distance to healthcare facilities, or the improvement in health outcomes for mothers and infants.

5. Sensitivity analysis: Conduct sensitivity analysis to assess the robustness of the results and identify key factors that may influence the impact of the recommendations.

6. Policy recommendations: Based on the simulation results, provide policy recommendations on the most effective strategies to improve access to maternal health. This can help inform decision-making and resource allocation for implementing the recommendations.

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