Effects of early-life amino acids supplementation on fish responses to a thermal challenge.

Nutritional programming is a promising concept for promoting metabolic adaptation of fish to challenging conditions, such as the increase in water temperature. The present work evaluates in ovo arginine or glutamine supplementation as enhancers of zebrafish metabolic or absorptive capacity, respectively, at optimum (28 ºC) and challenging temperatures (32 ºC) in the long-term. Growth performance, free amino acids profile, methylation index and the activity levels of digestive and intermediary metabolism enzymes were analysed to assess the metabolic plasticity induced by an early nutritional intervention. Temperature affected fish larvae growth performance. At the end of the experimental period 28 ºC-fish showed higher dry weight than 32 ºC-fish. The effects of the early supplementation were reflected in the larval free amino acids profile at the end of the experiment. Higher methylation potential was observed in the ARG-fish. In ovo amino acid supplementation modulated the metabolic response in zebrafish larvae, however, the magnitude of this effect differed according to the amino acid and the temperature. Overall, arginine supplementation enhanced carbohydrates metabolism at 32 ºC. In conclusion, the present work suggests that in ovo arginine supplementation may promote a better adaptive response to higher temperatures.

Adaptive Finite-Time-Based Neural Optimal Control of Time-Delayed Wheeled Mobile Robotics Systems.

For nonlinear systems with uncertain state time delays, an adaptive neural optimal tracking control method based on finite time is designed. With the help of the appropriate LKFs, the time-delay problem is handled. A novel nonquadratic Hamilton-Jacobi-Bellman (HJB) function is defined, where finite time is selected as the upper limit of integration. This function contains information on the state time delay, while also maintaining the basic information. To meet specific requirements, the integral reinforcement learning method is employed to solve the ideal HJB function. Then, a tracking controller is designed to ensure finite-time convergence and optimization of the controlled system. This involves the evaluation and execution of gradient descent updates of neural network weights based on a reinforcement learning architecture. The semi-global practical finite-time stability of the controlled system and the finite-time convergence of the tracking error are guaranteed.

Research on Trajectory Planning of Autonomous Vehicles in Constrained Spaces.

This paper addresses the challenge of trajectory planning for autonomous vehicles operating in complex, constrained environments. The proposed method enhances the hybrid A-star algorithm through back-end optimization. An adaptive node expansion strategy is introduced to handle varying environmental complexities. By integrating Dijkstra's shortest path search, the method improves direction selection and refines the estimated cost function. Utilizing the characteristics of hybrid A-star path planning, a quadratic programming approach with designed constraints smooths discrete path points. This results in a smoothed trajectory that supports speed planning using S-curve profiles. Both simulation and experimental results demonstrate that the improved hybrid A-star search significantly boosts efficiency. The trajectory shows continuous and smooth transitions in heading angle and speed, leading to notable improvements in trajectory planning efficiency and overall comfort for autonomous vehicles in challenging environments.

Point Cloud Densification Algorithm for Multiple Cameras and Lidars Data Fusion.

Fusing data from many sources helps to achieve improved analysis and results. In this work, we present a new algorithm to fuse data from multiple cameras with data from multiple lidars. This algorithm was developed to increase the sensitivity and specificity of autonomous vehicle perception systems, where the most accurate sensors measuring the vehicle's surroundings are cameras and lidar devices. Perception systems based on data from one type of sensor do not use complete information and have lower quality. The camera provides two-dimensional images; lidar produces three-dimensional point clouds. We developed a method for matching pixels on a pair of stereoscopic images using dynamic programming inspired by an algorithm to match sequences of amino acids used in bioinformatics. We improve the quality of the basic algorithm using additional data from edge detectors. Furthermore, we also improve the algorithm performance by reducing the size of matched pixels determined by available car speeds. We perform point cloud densification in the final step of our method, fusing lidar output data with stereo vision output. We implemented our algorithm in C++ with Python API, and we provided the open-source library named Stereo PCD. This library very efficiently fuses data from multiple cameras and multiple lidars. In the article, we present the results of our approach to benchmark databases in terms of quality and performance. We compare our algorithm with other popular methods.

Integrating Programming into Neuroscience Courses.

Programming is a useful skill for students, both in neuroscience research and in the broader economy. Many instructors, however, may wonder how and when they should integrate it into their coursework, especially if they themselves have limited computational training. The suggestions offered here aim to help a wide range of educators - even those who have minimal coding experience - who wish to expose their students to the intersection of neuroscience and programming. Throughout, I provide examples of how I have weaved coding into various elements of neuroscience courses, even those without a computational focus. I also discuss the rich landscape of low-cost, accessible programming tools as well as how generative AI can (and should) impact the way that we are teaching programming. Ultimately, the goal is not to insist that all our students learn how to code, but rather to lower barriers and provide exposure and opportunity to any student who wishes to integrate programming into their research or careers.

Mixed-integer disciplined convex programming approach applied to the optimal energy supply of near-zero energy buildings.

Energy needs in the buildings sector accounts for 40 % of global energy demand. Therefore, the implementation of several renewable energy sources is necessary to reduce this demand. The design stage of a decentralized generation project requires quantifying the power to be installed and the energy forecast for each source throughout the useful life of the building. This study develops a novel optimization algorithm for a long-term economic function based on mixed-integer disciplined convex programming (MIDCP) which guarantees the sustainability of the building and its energy systems. The robust algorithm integrates risk management of intermittent sources, technical and economic parameters of selected technologies, and life cycle analysis (LCA) of different energy systems, including storage. Furthermore, the penetration of green hydrogen into the distributed generation mix is evaluated as an important contribution. Meteorological and energy demand variables of two antagonistic scenarios were also used as inputs to the algorithm. As a result, the optimal energy supply sizing for tertiary buildings in the two defined locations was obtained. The results of the simulations have achieved an optimal convergence of 100 % in the proposed scenarios, with a resolution time of 14 s and using a memory of about 183 MB. The simulations suggest a higher penetration of green hydrogen in scenarios where supply and investment costs decrease to gray hydrogen supply levels, reaching up to 81 % coverage of the thermal demand of the building. Hybrid energy systems under favorable conditions show a penetration of about 92 % within the distributed generation mix. The developed tool could enable decision-makers to optimally plan distributed generation projects in buildings based on economic, policy, and geographic conditions.

Predicting compressive strength of hollow concrete prisms using machine learning techniques and explainable artificial intelligence (XAI).

The design of masonry structures requires accurate estimation of compressive strength (CS) of hollow concrete masonry prisms. Generally, the CS of masonry prisms is determined by destructive laboratory testing which results in time and resource wastage. Thus, this study aims to provide machine learning-based predictive models for CS of hollow concrete masonry blocks using different algorithms including Multi Expression Programming (MEP), Random Forest Regression (RFR), and Extreme Gradient Boosting (XGB) etc. A dataset of 159 experimental results was collected from published literature for this purpose. The collected dataset consisted of four input parameters including strength of masonry units ( f b ), height-to-thickness ratio (h/t), strength of mortar ( f m ), and ratio of f m / f b and only one output parameter i.e., CS. Out of all the algorithms employed in current study, only MEP and GEP expressed their output in the form of an empirical equation. The accuracy of developed models was assessed using root mean squared error (RMSE), objective function (OF), and R 2 etc. Among all algorithms assessed, XGB turned out to be the most accurate having R 2  = 0.99 and least OF value of 0.0063 followed by AdaBoost, RFR, and other algorithms. The developed XGB model was also used to conduct different explainable artificial intelligence (XAI) analysis including sensitivity and shapley analysis and the results showed that strength of masonry unit ( f b ) is the most significant variable in predicting CS. Thus, the ML-based predictive models presented in this study can be utilized practically for determining CS of hollow concrete masonry prisms without requiring expensive and time-consuming laboratory testing.

The Association Between Maternal Psychological Health and Human Milk Oligosaccharide Composition.

Background and Objective: Human milk oligosaccharides (HMOs) are carbohydrates abundant in human breast milk. Their composition varies widely among women, and prior research has identified numerous factors contributing to this variation. However, the relationship between maternal psychological health and HMO levels is currently unknown. Thus, our objective was to identify whether maternal stress, anxiety, or depressive symptoms are associated with HMOs. Methods: Data originated from 926 lactating individuals from the UC San Diego Human Milk Biorepository. Nineteen prevalent HMOs were assayed using high-performance liquid chromatography. Participants self-reported measures of the Edinburgh Postnatal Depression Scale (n = 495), State-Trait Anxiety Inventory S-Scale (n = 486), and/or Perceived Stress Scale (n = 493) within 60 days of their milk collection; their results were categorized using standard screening cutoffs. HMOs were assessed individually and grouped by principal component analysis (PCA), and associations with maternal psychological symptoms were analyzed using multivariable linear regression adjusted for covariates. Results: After Bonferroni correction (p < 0.002), the following HMOs significantly varied with maternal psychological distress in multivariate analysis: lacto-N-fucopentaose III (LNFP III) and lacto-N-hexaose (LNH) among Secretors with depressive symptoms and difucosyllactose (DFLac), LNFP III, and disialyl-LNH (DSLNH) among Secretors with stress. In PCA, depressive symptoms and stress were associated with one principal component among Secretors. No HMOs varied with anxiety symptoms. Conclusions: Several HMOs varied with maternal depressive symptoms and stress, suggesting a relationship between maternal psychological health and breast milk composition. Additional studies are needed to determine the impact of this variation on infant health.

Food-based dietary guidelines for optimizing calcium intakes for reproductive-aged women in Ethiopia using local foods.

Increasing dietary calcium intakes of Ethiopian women of reproductive age (WRA) is a public health priority for reducing pre-eclampsia in pregnancy. Using linear programming, we determined whether locally available foods consumed by WRA in nine regions (urban and rural) and two administrative cities of Ethiopia could provide 1000 mg/day of dietary calcium, and we identified food-based recommendations (FBRs) to improve dietary calcium adequacy in each region. Results showed that diets providing 1000 mg/day of calcium were feasible in eight regions (40%) of the target populations examined. It would, however, require marked changes for most populations (90%), increasing the number of servings per week of several food groups to levels close to those of high consumers in each population. The selected calcium-specific FBRs integrate well into the 2022 Ethiopian Dietary Guidelines, requiring additional messages to consume green leafy vegetables, milk, root crops, or teff (Eragrostis tef) or to consume a higher number of servings of vegetables than currently recommended, depending on the population. In conclusion, these analyses show that a food-based approach can be used to achieve dietary calcium adequacy among WRA in 40% of the populations examined. For the other populations, food-based interventions alone may be inadequate and other interventions are likely needed.

Presaccadic preview shapes postsaccadic processing more where perception is poor.

The presaccadic preview of a peripheral target enhances the efficiency of its postsaccadic processing, termed the extrafoveal preview effect. Peripheral visual performance-and thus the quality of the preview-varies around the visual field, even at isoeccentric locations: It is better along the horizontal than vertical meridian and along the lower than upper vertical meridian. To investigate whether these polar angle asymmetries influence the preview effect, we asked human participants to preview four tilted gratings at the cardinals, until a central cue indicated which one to saccade to. During the saccade, the target orientation either remained or slightly changed (valid/invalid preview). After saccade landing, participants discriminated the orientation of the (briefly presented) second grating. Stimulus contrast was titrated with adaptive staircases to assess visual performance. Expectedly, valid previews increased participants' postsaccadic contrast sensitivity. This preview benefit, however, was inversely related to polar angle perceptual asymmetries; largest at the upper, and smallest at the horizontal meridian. This finding reveals that the visual system compensates for peripheral asymmetries when integrating information across saccades, by selectively assigning higher weights to the less-well perceived preview information. Our study supports the recent line of evidence showing that perceptual dynamics around saccades vary with eye movement direction.

Influence of Infill Patterns on the Shape Memory Effect of Cold-Programmed Additively Manufactured PLA.

In four-dimensional additive manufacturing (4DAM), specific external stimuli are applied in conjunction with additive manufacturing technologies. This combination allows the development of tailored stimuli-responsive properties in various materials, structures, or components. For shape-changing functionalities, the programming step plays a crucial role in recovery after exposure to a stimulus. Furthermore, precise tuning of the 4DAM process parameters is essential to achieve shape-change specifications. Within this context, this study investigated how the structural arrangement of infill patterns (criss-cross and concentric) affects the shape memory effect (SME) of compression cold-programmed PLA under a thermal stimulus. The stress-strain curves reveal a higher yield stress for the criss-cross infill pattern. Interestingly, the shape recovery ratio shows a similar trend across both patterns at different displacements with shallower slopes compared to a higher shape fixity ratio. This suggests that the infill pattern primarily affects the mechanical strength (yield stress) and not the recovery. Finally, the recovery force increases proportionally with displacement. These findings suggest a consistent SME under the explored interval (15-45% compression) despite the infill pattern; however, the variations in the mechanical properties shown by the stress-strain curves appear more pronounced, particularly the yield stress.

Hispanic Thrifty Food Plan (H-TFP): Healthy, Affordable, and Culturally Relevant.

The USDA Thrifty Food Plan (TFP) is a federal estimate of a healthy diet at lowest cost for US population groups defined by gender and age. The present goal was to develop a version of the TFP that was more tailored to the observed dietary patterns of self-identified Hispanic participants in NHANES 2013-16. Analyses used the same national food prices and nutrient composition data as the TFP 2021. Diet quality was measured using the Healthy Eating Index 2015. The new Hispanic TFP (H-TFP) was cost-neutral with respect to TFP 2021 and fixed at $186/week for a family of four. Two H-TFP models were created using a quadratic programming (QP) algorithm. Fresh pork was modeled separately from other red meats. Hispanic NHANES participants were younger, had lower education and incomes, but had similar or higher HEI 2015 scores than non-Hispanics. Their diet included more pulses, beans, fruit, 100% juice, grain-based dishes, and soups, but less pizza, coffee, candy, and desserts. The H-TFP market basket featured more pork, whole grains, 100% fruit juice, and cheese. The second TFP model showed that pork could replace both poultry and red meat, while satisfying all nutrient needs. A vegetarian H-TFP proved infeasible for most age-gender groups. Healthy, affordable, and culturally relevant food plans can be developed for US population subgroups.

Rapid Growth between 0 and 2 Years Old in Healthy Infants Born at Term and Its Relationship with Later Obesity: A Systematic Review and Meta-Analysis of Evidence.

INTRODUCTION: Rapid growth in early childhood has been identified as a possible risk factor for long-term adiposity. However, there is a lack of studies quantifying this phenomenon only in healthy, full-term infants with appropriate birth weight for gestational age. This systematic review and meta-analysis aimed to investigate the association of rapid growth in full-term children up to 2 years of age with adiposity up to 18 years of age. METHODOLOGY: A systematic review of the literature was conducted in PubMed, EMBASE, and Web of Science. RESULTS: 14 studies were included. We were unable to find strong evidence that rapid growth in early childhood is a risk factor for long-term adiposity. Rapid growth in early childhood was associated with taller heights (standardized mean difference: 0.51 (CI: 0.25-0.77)) and higher body mass index (standardized mean difference: 0.50 (CI: 0.25-0.76)) and a higher risk of overweight under 18 years. CONCLUSION: Rapid growth in early childhood in term infants with appropriate birth weight is associated with higher growth, body mass index, and risk of being overweight up to age 18, but further work is needed to identify the associations between early rapid growth and obesity later in adulthood.

Maternal glucose homeostasis during pregnancy in women with overweight or obesity and offspring metabolic health.

Gestational diabetes mellitus (GDM) adversely affects offspring glucose homeostasis and risk of developing obesity. Here, we examined the association between glycemia in pregnant women with overweight or obesity without GDM and offspring metabolic health. Maternal fasting glucose concentrations and glucose 2-h after an oral glucose tolerance test (OGTT) were measured in 208 women with a pre-pregnancy body mass index (BMI) of 28-45 kg/m2 without GDM. Offspring outcomes were collected at birth, 3, and 5 years of age. Linear mixed models with time as fixed factor and subject ID as random effects were used for analysis. No associations were found between maternal fasting or 2-h glucose concentrations with offspring glucose and insulin concentrations from birth to 5 years of age. However, maternal fasting glucose in GW 28 and 36, and 2-h OGTT glucose in GW 28 were positively associated with C-peptide concentration at birth. Maternal fasting glucose concentrations in GW 28 and 36 were positively associated with weight-for-length, and maternal fasting glucose in GW 36 was associated with BMI z-score at birth. In summary, blood glucose in pregnant women with overweight or obesity is positively associated with offspring C-peptide concentration, weight-for-length, and BMI z-score at birth, even in the absence of GDM.

Neighborhood environments underpin screen time intervention success in children: Evidence from a study of greenspace and community programming across 130 US communities.

The goal of this study was to understand how neighborhood greenspace access may support or hinder the effectiveness of community programs and policies (CPPs) aimed at reducing racial and ethnic inequities in screen time among 4598 US children. We found higher CPP intensity was significantly associated with fewer screen time behaviors in high greenspace neighborhoods, but not neighborhoods with low or moderate greenspace. Moreover, there were significant differences in greenspace access by neighborhood-level race and ethnicity. Implementing CPPs without regard for racial and ethnic greenspace inequities may be an underlying cause in the perpetuation of inequities in childhood screen time.

Adaptive dynamic programming for containment control with robustness analysis to iterative error: A global Nash equilibrium solution.

Global Nash equilibrium is an optimal solution for each player in a graphical game. This paper proposes an iterative adaptive dynamic programming-based algorithm to solve the global Nash equilibrium solution for optimal containment control problem with robustness analysis to the iterative error. The containment control problem is transferred into the graphical game formulation. Sufficient conditions are given to decouple the Hamilton-Jacobi equations, which guarantee the solvability of the global Nash equilibrium solution. The iterative algorithm is designed to obtain the solution without any knowledge of system dynamics. Conditions of iterative error for global stability are given with rigorous proof. Compared with existing works, the design procedures of control gain and coupling strength are separated, which avoids trivial cases in the design procedure. The robustness analysis exactly quantifies the effect of the iterative error caused by various sources in engineering practice. The theoretical results are validated by two numerical examples with marginally stable and unstable dynamics of the leader.

A hybrid, nonlinear programming approach for optimizing passive shimming in MRI.

BACKGROUND: In magnetic resonance imaging (MRI), maintaining a highly uniform main magnetic field (B0) is essential for producing detailed images of human anatomy. Passive shimming (PS) is a technique used to enhance B0 uniformity by strategically arranging shimming iron pieces inside the magnet bore. Traditionally, PS optimization has been implemented using linear programming (LP), posing challenges in balancing field quality with the quantity of iron used for shimming. PURPOSE: In this work, we aimed to improve the efficacy of passive shimming that has the advantages of balancing field quality, iron usage, and harmonics in an optimal manner and leads to a smoother field profile. METHODS: This study introduces a hybrid algorithm that combines particle swarm optimization with sequential quadratic programming (PSO-SQP) to enhance shimming performance. Additionally, a regularization method is employed to reduce the iron pieces' weight effectively. RESULTS: The simulation study demonstrated that the magnetic field was improved from 462  to 3.6 ppm, utilizing merely 1.2 kg of iron in a 40 cm diameter spherical volume (DSV) of a 7T MRI magnet. Compared to traditional optimization techniques, this method notably enhanced magnetic field uniformity by 96.7% and reduced the iron weight requirement by 81.8%. CONCLUSION: The results indicated that the proposed method is expected to be effective for passive shimming.

Feeding parenteral nutrition in the neonatal period programs dyslipidemia in adulthood in Yucatan miniature pigs.

BACKGROUND: Early nutritional challenges can lead to permanent metabolic changes, increasing risk for developing chronic diseases later in life. Total parenteral nutrition (TPN) is a life-saving nutrition regimen, used especially in intrauterine growth-restricted (IUGR) neonates. Early TPN feeding alters metabolism, but whether these alterations are permanent is unclear. Programmed metabolism is likely caused by epigenetic changes due to imbalances of methyl nutrients. OBJECTIVES: We sought to determine whether feeding TPN in early life would increase the risk of developing dyslipidemia in adulthood and whether supplementing the methyl nutrients betaine and creatine to TPN would prevent this development. We also sought to determine whether IUGR exacerbates the effects of neonatal TPN on lipid metabolism in adulthood. METHODS: Female piglets (n=32, 7 d old) were used in four treatments: 24 normal weight piglets were randomized to sow-fed (SowFed), standard TPN (TPN-control), and TPN with betaine and creatine (TPN-B+C); 8 IUGR piglets were fed control TPN (TPN-IUGR) as a fourth group. After 2 weeks of treatment, all pigs were then fed a standard solid diet. At 8 mo old, central venous catheters were implanted to conduct postprandial fat tolerance tests. RESULTS: Feeding TPN in the neonatal period led to dyslipidemia in adulthood, as indicated by higher postprandial triglyceride (TG) levels in TPN-control (P<0.05), compared to SowFed. IUGR piglets were particularly sensitive to neonatal TPN feeding, as TPN-IUGR piglets developed obesity and dyslipidemia in adulthood, as indicated by greater backfat thickness (P<0.05), higher liver TG (P<0.05), slower postprandial TG clearance (P<0.05), and elevated fasting plasma non-high density lipoprotein (HDL)-cholesterol (P<0.01), and non-esterified fatty acids (NEFA) (P<0.001), compared to TPN-control. CONCLUSIONS: Feeding TPN in early life increases the risk of developing dyslipidemia in adulthood, especially in IUGR neonates; however, methyl nutrient supplementation to TPN did not prevent TPN-induced changes in lipid metabolism.

Low-carbon diets across diverse dietary patterns: Addressing population heterogeneity under constrained optimization.

Mathematical optimization is a useful tool for modeling diets that fulfill requirements for health and environmental sustainability, however, population-based optimization approaches fail to account for underlying dietary diversity in populations. This study proposes a methodological approach to consider diverse dietary intake patterns in mathematical optimization of nutritionally adequate low-carbon diets and investigates the differences between different population groups, along with trade-offs between greenhouse gas emission (GHGE) reduction and the inconvenience of dietary changes required to achieve optimized diets. A k-means clustering analysis was applied to individual dietary intake data from Denmark, which resulted in four clusters with different dietary patterns. This was followed by quadratic programming, wherein the total dietary changes required from the observed diet within each cluster were used as a proxy for consumer inconvenience (i.e., "inconvenience index") and were minimized while fulfilling nutrient constraints and incrementally tightened GHGE constraints. Across clusters, a steep increase of the inconvenience index was observed at GHGE levels below approximately 3 kg CO2e/10 MJ, corresponding to GHGE reductions of 24-36 % in different clusters. In all clusters, the optimized diets with nutritional and GHGE constraints showed common traits of increased content of cereals and starches, eggs, and fish and decreased amounts of beef and lamb, cheese, animal-based fats, and alcoholic beverages, but differences across clusters were also observed, maintaining characteristics of the clusters' baselines. When additional health-based targets for food amounts were applied as constraints, the optimized diets converged towards the same type of diet. The total inconvenience of dietary changes required to fulfill constraints differed between clusters, indicating that specific sub-populations may be more effective targets for dietary transition. The method has potential for future integration of more sustainability aspects and different consumer preferences.

Maternal preconception glucose intolerance and fatty acid intake from conception to weaning: impact on offspring energy homeostasis in both male and female.

Environmental factors in the early life stages can lead the descendant to adaptations in gene expression, permanently impacting several structures and organs. The amount and quality of fatty acids in the maternal diet in pregnancy and lactation were found to impact offspring metabolism. So, maternal diet and insulin resistance can affect the male and female descendants through distinct pathways and at different time points. We hypothesized that maternal high-fat diet (HFD) intake before conception and an adequate amount of different fatty acids intake during pregnancy and lactation could influence the energy homeostasis system of 21-day-old offspring. Female rats received control diet (C) or HFD (HF) for 8 weeks before pregnancy. During pregnancy and lactation C group remained with same diet (C-C), HF group were distributed into 4 groups and received C diet (HF-C), normolipidic diet based on saturated fatty acids (HF-S) or based on polyunsaturated fatty acids n-3 (HF-P) or remained in same diet (HF-HF). Maternal HFD in preconception, pregnancy, and lactation (HF-HF) led to lower glucagon-like peptide-1 levels in male (HF-HF21) compared to other groups (C-C21, HF-C21, and HF-P21) and compared to HF-HF21 females. Neuropeptide YY levels were higher in the HF-HF21, HF-C21, and HF-S21 male offspring compared to HF-P21. HF-P21 was similar to C-C21. Positive correlations were found among the energy homeostasis markers genes expressed in the offspring hypothalamus. Maternal diet changes to adequate quantities of fatty acids during pregnancy and lactation showed less impaired results but was not entirely avoided. A maternal diet based on PUFA n-3 during pregnancy and lactation seems to reverse the damage of an HFD in preconception. These results of homeostasis energy system disturbance in the offspring at weaning give us clues about changes that precede the onset of the disease in adult life - adding notes to the knowledge for future investigations of prevention and treatment of chronic diseases.