LC-MS Analysis, Computational Investigation, and Antimalarial Studies of Azadirachta indica Fruit

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Study Justification:
– Malaria is a deadly disease that poses a threat to children and maternal well-being.
– The study aims to identify the chemical constituents in the fruit extract of Azadirachta indica and investigate their potential as antimalarial agents.
– The study provides information about the phytochemicals and background pharmacological evidence of the antimalarial claim of A. indica fruit.
Highlights:
– Liquid chromatography-mass spectrometry (LC-MS) analysis was used to identify the chemical compounds in the fruit extract.
– Density functional theory (DFT) analysis was performed to elucidate the pharmacological potentials of the identified phytochemicals.
– Antimalarial assays were conducted using chemosuppression and curative models.
– The identified phytochemicals showed potential as antimalarial agents.
– The ethanolic extract of A. indica fruit exhibited significant suppression and clearance of parasitaemia.
Recommendations:
– Further studies should focus on isolating and elucidating the structures of the identified phytochemicals from the active extract.
– Extensive antimalarial studies should be conducted to discover new therapeutic agents.
Key Role Players:
– Researchers and scientists specializing in pharmacognosy, chemistry, and malaria research.
– Ethnobotanists and herbal medicine experts.
– Animal care personnel for conducting experiments on mice.
– Institutional ethics committees for approving the animal experimental methodology.
Cost Items for Planning Recommendations:
– Research materials and supplies for chemical analysis and antimalarial assays.
– Animal care and housing facilities.
– Laboratory equipment and instruments.
– Research personnel salaries and benefits.
– Publication and dissemination of research findings.
– Travel and conference expenses for presenting research results.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study design includes LC-MS analysis, computational investigation, and antimalarial studies, which provide a comprehensive approach. The identification of phytochemicals and their potential as antimalarial agents is supported by the density functional theory analysis. The antimalarial activity of the extract is also demonstrated through chemosuppression and curative models. However, the abstract lacks specific details about the methodology and results of the LC-MS analysis, computational investigation, and antimalarial studies. Providing more information on these aspects would strengthen the evidence. Additionally, the abstract could benefit from including the sample size and statistical analysis used in the antimalarial studies. Overall, the evidence is strong, but providing more specific details and statistical analysis would improve it further.

Malaria is a deadly disease that continues to pose a threat to children and maternal well-being. This study was designed to identify the chemical constituents in the ethanolic fruit extract of Azadirachta indica, elucidate the pharmacological potentials of identified phytochemicals through the density functional theory method and carry out the antimalarial activity of extract using chemosuppression and curative models. The liquid chromatography-mass spectrometry (LC-MS) analysis of the ethanolic extract was carried out, followed by the density functional theory studies of the identified phytochemicals using B3LYP and 6-31G (d, p) basis set. The antimalarial assays were performed using the chemosuppression (4 days) and curative models. The LC-MS fingerprint of the extract led to the identification of desacetylnimbinolide, nimbidiol, O-methylazadironolide, nimbidic acid, and desfurano-6α-hydroxyazadiradione. Also, the frontier molecular orbital properties, molecular electrostatic potential, and dipole moment studies revealed the identified phytochemicals as possible antimalarial agents. The ethanolic extract of A indica fruit gave 83% suppression at 800 mg/kg, while 84% parasitaemia clearance was obtained in the curative study. The study provided information about the phytochemicals and background pharmacological evidences of the antimalarial ethnomedicinal claim of A indica fruit. Thus, isolation and structure elucidation of the identified phytochemicals from the active ethanolic extract and extensive antimalarial studies towards the discovery of new therapeutic agents is recommended for further studies.

The fruit of A indica (Meliaceae) was collected within Obafemi Awolowo University (OAU) campus. The fruit was identified, authenticated, and deposited at the Faculty of Pharmacy Herbarium, Ife by Mr. I. I. Ogunlowo of the Pharmacognosy Department, OAU, Ile-Ife, with voucher specimen number FPI 2423. The fruits were air-dried, powdered, and 500 g of the dried powder was macerated in 1500 mL ethanol for 48 hours with intermittent shaking. The resultant extract (17 g) was filtered, evaporated in vacuo, freeze-dried, weighed, and stored. A linear trap quadrupole (LTQ) Orbitrap spectrometer (Thermo Scientific, USA) was used to carry out liquid chromatography-mass spectrometry (LC-MS) analysis. The instrument is equipped with an Agilent 1200 HPLC system (Santa Clara, CA, USA) and connected to a photodiode array (PDA) detector. Sample preparation was done by making the fruit extract into a final concentration of 2 mg/mL in methanol and was centrifuged for 5 min at 6600 r/min and loaded for analysis. A reverse phase Luna C18 column (60 × 3 mm, 3 μm) (Phenomenex, Torrance CA, USA), was used to carry out high-performance liquid chromatography (HPLC) analysis of the sample. The mobile phase consists of water (+0.1% formic acid) A and methanol (+0.1% formic acid) B at a flow rate of 360 μL/min. The gradient was configured to be a linear gradient from 96% A to 100% B over 14 minutes, followed by 100% B for 4 minutes, then a return to the initial concentration of 96% A in 0.6 minutes, and allowed to equilibrate for 4.6 minutes. The column oven condition was kept at 30°C, and the injection volume was 6 μL. Spectrometry analysis was carried out in positive mode with a nominal mass resolving power of 60 000 at 400 m/z, spray voltage of 6 kV, and a scan rate of 1 Hz. The spectrometer was run with a capillary temperature of (300°C), a tube lens of 100 V, collision gases were argon and nitrogen as sheath gas (66 arbitrary units) and auxiliary gas (8 arbitrary units), respectively.7,23 Xcalibur software 2.2.48 was used for data analysis. Compounds were proposed by comparison of acquired MS data with literature. Density functional theory analysis of phytochemicals identified from the ethanolic extract of A indica fruit was performed using the Spartan 14 programme containing functional B3LYP (Lee-Yang Parr exchange-correlation functional method). Also, a 6-31G basis set was chosen for the DFT study.24 During the calculations, the values of the frontier orbital energies were computed from the most established conformation of the compounds using the following formulas: Seven-week-old Swiss albino mice of either sex weighing between 18 and 24 g (male and female, not pregnant) were obtained from the Animal House, Faculty of Basic Medical Sciences, College of Health Sciences, OAU, Ile-Ife, Nigeria, where they were housed in aluminium cages with wood shavings used as beddings and allowed free access to water and food (Growers’ mash) under 12-hour day/night cycle. The animal experimental methodology was approved by the Health Research and Ethics Committee of the Institute of Public Health, OAU, Ile-Ife, Nigeria. They were also handled in accordance with the National Institutes of Health (NIH) Guide for the care and use of laboratory animals (NIH Publication, No. 83-123 (revised), 1985). They were acclimatized for at least 7 days before use and randomly divided into groups of 5 mice each for the experiments. Plasmodium berghei strain NK65 sensitive to chloroquine (CQ), obtained from Professor O G Ademowo of the Institute of Advanced Medical Research and Training (IMRAT), University College Hospital, Ibadan, was used to assess the in vivo chemo-suppressive and curative antimalarial activity. The parasite strain was preserved via serial passage of blood taken from an infected mouse into an uninfected mouse. The donor mouse was sacrificed, and blood was withdrawn through cardiac puncture into a heparinized bottle to prepare the inoculum. It was diluted with normal saline solution so that 0.2 mL of the inoculum will contain 1.0 × 107 parasitized red blood cells. The chemosuppressive and the curative activities were performed by oral administration of the extract (100, 200, 400, and 800 mg/kg), CQ (10 mg/kg), and normal saline to groups of 5 mice each, 2 hours after infection and thereafter daily for 3 days in the chemosuppressive model, while in the curative model, the administration was done daily for 5 days starting from the third day after infection.25,26 The temperature of each mouse was taken using a digital clinical thermometer inserted into the rectum before the administration of the extracts or drugs. The level of parasitaemia was determined for each mouse on Day 4 (D4) and daily after infection for the chemosuppressive and curative models, respectively, by cell counting of 5 fields in a view of the microscope of a thin blood smear, fixed with methanol and stained with Giemsa, obtained from the tail of each mouse.25,26 The average parasitaemia in each group was calculated to determine the percentage chemo-suppressive and curative activities of the extract using the following formula: where A and B are the mean parasitaemia in the negative control and the test groups, respectively.27 The extract’s antimalarial chemo-suppressive activity was determined by the percentage reduction of parasitaemia in treated groups compared with the untreated infected group. The animals were further observed for 28 days for mortality while survival times and percentage of survivors were estimated.25,28 The percentage of survival time was calculated for each group by using the following formula: Values were expressed as mean ± standard error of the mean (SEM) and analysed statistically using 1-way analysis of variance (ANOVA) followed by Student-Newmann-Keuls’ post hoc for comparison to determine the source of significant difference for all values. Values of P < .05 were of statistical significance.

Based on the provided information, here are some potential innovations that can be used to improve access to maternal health:

1. Telemedicine: Implementing telemedicine services can allow pregnant women in remote or underserved areas to access prenatal care and consultations with healthcare providers without the need for physical travel.

2. Mobile health (mHealth) applications: Developing mobile applications that provide educational resources, appointment reminders, and personalized health information can empower pregnant women to take an active role in their own healthcare and improve their access to maternal health services.

3. Community health workers: Training and deploying community health workers who can provide basic prenatal care, education, and support to pregnant women in their communities can help bridge the gap in access to maternal health services, especially in areas with limited healthcare infrastructure.

4. Transportation solutions: Developing transportation solutions, such as mobile clinics or ambulances, specifically designed to transport pregnant women to healthcare facilities can ensure timely access to prenatal care, emergency obstetric services, and delivery facilities.

5. Public-private partnerships: Collaborating with private sector organizations, such as pharmaceutical companies or technology companies, can help leverage their resources and expertise to improve access to maternal health services, including the availability of affordable medications and medical technologies.

It is important to note that these are general recommendations based on the topic of maternal health. Further research and analysis would be needed to determine the specific context and feasibility of implementing these innovations in a particular setting.
AI Innovations Description
The recommendation provided in the description is to further study the isolation and structure elucidation of the identified phytochemicals from the active ethanolic extract of Azadirachta indica fruit. This would involve conducting extensive antimalarial studies to discover new therapeutic agents. The study suggests that the identified phytochemicals have potential antimalarial properties based on their molecular properties and the observed antimalarial activity of the extract in chemosuppression and curative models. The study also emphasizes the need for further research to validate the ethnomedicinal claim of Azadirachta indica fruit as an antimalarial agent.
AI Innovations Methodology
Based on the provided description, it seems that the methodology described is focused on the analysis and evaluation of the antimalarial potential of the ethanolic fruit extract of Azadirachta indica (A. indica). While this study is important for understanding the potential pharmacological properties of A. indica in relation to malaria treatment, it does not directly address the improvement of access to maternal health.

To improve access to maternal health, it is important to consider innovations that specifically target the barriers and challenges faced by pregnant women in accessing healthcare services. Here are a few potential recommendations for innovations to improve access to maternal health:

1. Telemedicine and mobile health (mHealth) solutions: Develop and implement telemedicine and mHealth platforms that allow pregnant women to access prenatal care, consultations, and health information remotely. This can help overcome geographical barriers and provide timely and convenient access to healthcare services.

2. Community-based healthcare models: Establish community-based healthcare models that bring maternal health services closer to pregnant women, especially in rural and underserved areas. This can involve setting up mobile clinics, community health workers, and outreach programs to provide antenatal care, education, and support.

3. Transportation and logistics solutions: Address transportation challenges by developing innovative transportation and logistics solutions specifically designed for pregnant women. This can include providing affordable transportation options, improving road infrastructure, and coordinating transportation services for prenatal visits and emergencies.

4. Health information systems: Implement robust health information systems that enable efficient and accurate collection, analysis, and sharing of maternal health data. This can help identify gaps in access, monitor progress, and inform evidence-based decision-making for improving maternal health services.

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

1. Define the target population: Identify the specific population or region where the innovation will be implemented and assess the current state of maternal health access in that area.

2. Collect baseline data: Gather data on key indicators related to maternal health access, such as the number of prenatal visits, distance to healthcare facilities, transportation availability, and maternal health outcomes.

3. Develop a simulation model: Create a simulation model that incorporates the proposed innovations and their potential impact on maternal health access. This model should consider factors such as population size, geographical distribution, healthcare infrastructure, and resource availability.

4. Input data and parameters: Input the baseline data and relevant parameters into the simulation model. This may include data on the target population, healthcare facilities, transportation networks, and the expected effects of the innovations.

5. Run simulations: Run multiple simulations using different scenarios and assumptions to assess the potential impact of the innovations on maternal health access. This can involve varying factors such as the coverage and effectiveness of the innovations, population growth, and resource allocation.

6. Analyze results: Analyze the simulation results to evaluate the potential impact of the innovations on maternal health access. This may include assessing changes in key indicators, such as increased prenatal visits, reduced travel time, and improved health outcomes.

7. Refine and optimize: Use the simulation results to refine and optimize the proposed innovations. Identify areas of improvement, potential challenges, and strategies to maximize the impact on maternal health access.

8. Implement and monitor: Implement the recommended innovations and closely monitor their implementation and impact. Continuously collect data and evaluate the actual outcomes to validate the simulation results and make necessary adjustments.

By following this methodology, policymakers and healthcare providers can gain insights into the potential impact of innovations on improving access to maternal health and make informed decisions on their implementation.

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