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Introduction: COVID-19 is an infectious disease caused by the SARS-CoV-2 virus that commonly involved the respiratory system. However, the virus can affect any organ in the body including the liver. Hepatic involvement in COVID-19 could be related to the direct cytopathic effect of the virus, an uncontrolled immune reaction, sepsis, or drug-induced liver injury. Background: The current study aims to evaluate the relevance of liver enzyme derangement in COVID-19. Methods: The sample size of 165 patients, tested positive for covid 19 and underwent liver enzyme testing. These patients were categorized into mild, severe, and critical diseases based on clinical evaluation, radiological findings, and biochemical parameters. Results: Of 165 patients selected 103 (62.4%) have mild disease, 40(24.2%) have severe and 12(7.2%) suffered from the critical disease. 48(29.1%) patients show deranged liver function. 83.3% of critical patients and 45% of severe patients show deranged liver function.9.09%of patients died due to severe COVID-19 infections showing moderately to severe liver function derangement. Conclusions: This study concludes that the severity of COVID-19 disease may increase due to chronic liver disease, particularly fatty liver. Atypical ALT and AST levels during hospitalization were indicative of liver injury and correlated with the severity of patients.
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The word Taxonomy is the way of Classification. It is the science of naming and classifying all the living organisms as well as extinct organisms of the world. Swedish Botanist Carlous Linnaeus was the father of taxonomy;Out of 17000 plant species present in India, more than 7600 plants are medicinal plants. Indigenous Indian medicines are formulations of traditional knowledge and medicinal plant extracts. The traditional knowledge is transferred from one generation to other generations which is used as drug for various diseases, instead of relying on what is the ingredients and proportions these drugs are based on traditional knowledge. These drugs involve the use of plant extract. The World Health Organization (WHO), leading agency in health care found that 80 % population in low economic output countries depend on traditional medicine for their essential health care[1]. In the current era of pandemic medicinal plant species like citrus spp, allium sativum, allium cepa found effective in management of COVID 19. As per WHO guidelines, In the field of medicinal research where clinical trials are used for new drug discovery, there is need of continuous supply of authenticated products which are correctly identified, classified, and verified [1]. Traditional identification and classification methods are not quick, efficient and reliable. Automated Classification of medicinal Plants help to conserve knowledge of medicinal plant species, share it from one generation to next generation and help the whole society to improve the knowledge about medicinal plants. The paper presents traditional and recent trends using Computer vision and machine learning for classifying medicinal plant species. The main focus is on Leaf image as input. It presents the challenges as well as opportunities in identifying and classifying medicinal plant species by performing comprehensive review of traditional methodologies. © 2023 Author(s).
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Since the start of the covid 19 pandemic, a wide range of medications have been produced and are currently being utilized to treat the disease. Tulsi, in addition to all of the chemical-based medications, is an herbal therapy that is particularly effective in the treatment of this ailment. Tulsi has been used to heal ailments and infections for millennia, particularly in India. Because we use tulsi for medicinal purposes, it's vital to monitor its health in order to reap the full benefits of its herbal properties. Plant diseases harm the health and growth of the plant. Disease detection in plants is crucial so that it can be treated before it spreads throughout the plant. To detect illnesses in tulsi leaves, we propose employing a model based on convolution neural networks. Image processing and CNN are widely employed. The prepared model extracts the image's key features and categorizes it into different disorders. The model has a 75 percent accuracy rate. © 2022 IEEE.
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Aims and objectives: The aim of this study was to compare the immediate adverse effects of the coronavirus disease 2019 (COVID-19) vaccine (COVAXIN) in a pregnant woman with that of a nonpregnant woman. Material(s) and Method(s): It is a prospective observational study done at Vanivilas Hospital, Bangalore Medical College & Research Institute (BMCRI) for 2 months. The sample size was 100 pregnant and 100 nonpregnant women. Telephonically, patients were followed-up, and details of the side/adverse effects were collected in a proforma after 2 and 14 days. Data collected from both groups were analyzed using the Chi-square test or Fisher's exact test. Result(s): The majority of women were in the age group of <=25 years (64.0% and 36.0%, respectively) with a mean age of 25.01 +/- 3.71 years among the pregnant and 28.52 +/- 6.00 years among nonpregnant women. About 25.0% of pregnant women and 38.0% of nonpregnant women reported side effects. About 15.0% and 22.0% had taken treatment for side effects among pregnant women and nonpregnant women, respectively. Among the pregnant women, the common side effects reported were injection site pain (17) followed by fever (5), fatigue (4), and myalgia (03). Whereas among the nonpregnant women, the common side effects reported were injection site pain (28) followed by fever (6), myalgia (3), headache (2), and fatigue (1). Conclusion(s): Side effects reported following the administration of Covaxin in pregnant and nonpregnant women are fever, fatigue, injection site pain, myalgia, and headache. The proportion of side effects was not significantly different in the pregnant and nonpregnant women following Covaxin administration. Clinical significance: Covaxin is an inactivated killed vaccine against COVID-19 by Bharat Biotech. The vaccine has been recommended for pregnant women by the Government of India during corona pandemic. Studies are lacking regarding the difference in adverse events in pregnant versus nonpregnant women, after vaccine administration.Copyright © The Author(s).
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The XXIV annual state conference of the Medicolegal Association of Maharashtra: Forensicon 2021 organized by the department of Forensic and Toxicology, Lokmanya Tilak Municipal Medical College and Hospital, Mumbai. Previous conference "Forensicon 2020” was held at TNMC & BYL Nair Ch. Hospital, Mumbai in the month of April 2021 as COVID pandemic prevented the continuity of the conference in the year 2020. Responsibility of organizing XXIV annual State conference was allotted to Department of Forensic Medicine and Toxicology, Lokmanya Tilak Municipal Medical College and General Hospital, Sion, Mumbai on 22nd November 2021. The organizing committee have magnificently conducted the annual state conference in the very short duration of 24 days on 17th and 18th December 2021 at main auditorium, Lokmanya Tilak Municipal Medical College and hospital, Mumbai. Dr Rajesh Dere, professor and head, Forensic Medicine Dept, LTMMC & hospital and Dean BKC Jumbo COVID 19 facility, Mumbai through his valiant efforts as team leader overcoming all the obstacles brought this conference to epitome of success. © 2022, Medicolegal Association of Maharashtra. All rights reserved.
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Introduction: Rise of major Healthcare associated infections (HAIs) can be mitigated by inculcating good infection control practices which can only be possible by proper and timely educational training of healthcare workers. Aim: To reinforce infection prevention and control knowledge and practices of nursing staff through proper training program- To conduct the training in multiple sessions, to assess the immediate outcome of training program by conducting Pre and Post test (in written format only) Materials and Methods: This study was done in a tertiary care hospital in Davangere, Karnataka over a period of 2 years. Healthcare workers including 144 nurses and 12 doctors underwent training in four sessions where knowledge on how to identify, audit and conduct surveillance of major healthcare associated infections, management of needlestick injuries were imparted through interactive lectures and video demonstrations followed by hands on hand hygiene, proper use and disposal of personal protective equipments. Pre and Post test were given to know their basal knowledge and effect of our training intervention. Data was collected, analyzed and tabulated. Results: Out of four sessions covering a total of 144 nurses, 84 were trained before the onset of COVID-19 and remaining 60 were trained in the latter half of 2021, when the lockdown was relaxed in our region. The mean total Knowledge score in pre test and post test was 5.93 +or- 1.336 and 7.95 +or- 1.040. The mean difference was -2.021 and it was statistically significant by paired test. (p - 0.001). The mean total practice pretest and post test score was 3.57 +or- 1.48 and 4.56 +or- 1.114. Paired t test showed significant mean difference between the pretest and post test score. (p - 0.001). Conclusion: Our training intervention was effective in increasing their awareness on proper infection prevention and control practices. Repeated training and retraining of healthcare care workers have to be carried out to prevent and control healthcare associated infections.
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Foot-and-mouth disease (FMD) and Coronavirus Disease 2019 (COVID-19) are transboundary diseases caused by single-stranded positive-sense RNA viruses with similarities in genome replication and viral protein synthesis. In FMD, asymptomatic infection leads to carrier status and persistently infected animals that threaten the animals vaccinated with a trivalent inactivated whole virus vaccine. Similar information on COVID-19 is not yet available. As COVID-19 vaccination is introduced in January 2021 (since 16 January 2021 in India), its outcome can be assessed by the year-end;and while doing so, the experiences gained in the control of FMD in livestock worldwide can be applied, including monitoring of vaccination response, duration of immunity, level of herd immunity developed, and antigenic matching of the vaccine virus. Antigenic divergence of the virus is a major issue in FMD, and different geographical regions in the world use different virus strains in vaccine preparations to antigenically match circulating virus strains in respective regions for control of the disease. Non-synonymous mutations in the critical antigenic determinants of SARS-CoV-2 have been observed, and there is likely the existence/development of antigenic variants. Therefore, during the post-COVID-19 vaccination regime, it will be essential to monitor the suitability of the in-use vaccine strain region-wise from time to time, as there could be an eruption of isolated outbreaks in a country arising due to antigenic variation and variants. In the context of the present scenario of COVID-19 around the Globe and multiple ongoing efforts to develop suitable vaccine(s) to control the disease, it is a must to develop NSP-antibody (that differentiate infected from vaccinated) assays to differentiate infected from vaccinated individuals(DIVI;DIVA in veterinary epidemiology). The techniques used and experiences gained in ongoing FMD control programs in the endemic countries can be applied to COVID-19 control in a country;and finally, the Globe. After achieving the control of COVID-19, the aim would be to eradicate the virus, which will be tough even with vaccination, as the disease/infection may become endemic during the time to come. To achieve this, applying the principles of Progressive Control Pathway for Foot-and-Mouth Disease (PCP-FMD;FAO/OIE) to COVID-19 control will be beneficial in its control. The present review discusses the issue of control of COVID-19. © 2021 by the authors.
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Introduction: Robust data of LDH (Lactate dehydrogenase) is available in bacterial infection, and it can be utilized in this COVID-19 Pneumonia pandemic for initial assessment, planning of treatment in indoor setting in association with HRCT severity. Method(s): Prospective, observational, 12 weeks follow up study, included 2000 COVID-19cases confirmed with RT PCR. All cases were assessed with lung involvement documented and categorized on HRCT thorax, oxygen saturation, LDH at entry point and follow up.Age, gender, comorbidity and BIPAP/NIV use and outcome as with or without lung fibrosis as per CT severity. Statistical analysis is done by Chi square test. Result(s): HRCT severity score at entry point has significant correlation with LDH titer [p<0.00001] LDH titer has significant association with duration of illness (Doi) [p<0.00001] Comorbidities has significant association with LDH titer. [p<0.00001] LDH titer has significant association with oxygen saturation [p<0.00001] BIPAP/NIV requirement during hospitalization has significant association with LDH titer. [p<0.00001] Timing of BIPAP/NIV requirement has significant association with LDH titer. [p<0.00001] Follow-up LDH titer during hospitalization as compared to entry point (initial) normal and abnormal LDH has significant association in post-covid lung fibrosis [p<0.00001] Conclusion(s): LDH is easily available, and universally acceptable inflammatory marker in COVID-19 pandemic and documented very crucial role in covid-19 pneumonia in predicting severity of illness, assessing response to treatment and analyzing outcome during hospitalization.Copyright © 2023 Patil S.
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The pandemic is changing the clinical needs and potential for AI-driven computer-assisted diagnoses (CDS). Since the beginning, rapid identification of COVID-19 patients has been a significant difficulty, especially in areas with limited diagnostic testing capacity. Intelligent Information System (IIS) represents the knowledge progression of available data. It has been directed by recent technological integration, data processing, and distribution in multiple computational environments. Intelligent Information Systems are aimed to work like an advanced human brain, where, as per the requirement of changing circumstances, the optimal decision can be evolved. IIS tools are expected to be adaptive, which may vary according to their processing data. As a result, the goal of this study was to provide a complete analysis of various technologies for combating COVID-19, with a focus on their features, problems, and domiciliation nation. Our findings demonstrate the performance of developing technologies. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The management of Covid-19 affected patients is a very difficult task. The current healthcare system of India is not able to cope with the enormous flow of patients and is in a dire need for improvement. This implementation paper provides a system which will manage all the affected patients right from the time they are Covid-19 positive till the time they are treated and discharged. This paper includes all the technical details of a fully implemented healthcare management system which is a significant improvement in the current system. The proposed system is a cross platform multi user web app which can be used by multiple stakeholders to carry out smooth management of the patients. It consists of a lot of key features like dynamic location-wise patient status, an accurate tracking system of ambulances, a statistical trend analysis of patients and categorical report generation of patients. This system aims to help the medical Front-liners in efficient management of Covid-19 patients, and it is a common site for all the different health workers like field workers and medical officers to work togetherand fight against this deadly disease affecting our country. © 2022 IEEE.
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Recently COVID-19 has become the most discussed topic in different social media platforms like Twitter, Facebook, Instagram etc. As time moves on, lot of messages and videos are posted in social media. As expected, most of the public followed these messages and becomes panic because of lack of information, misinformation about COVID-19 and its impact. This research study proposes a Twitter sentiment analysisbased on the most popular vaccines Covaxin, Covishield, and Pfizer. Most of the people expressed their feelings about vaccines in the twitter. Twitter API authentication is used here to extract the tweets. These extracted tweets are difficult to analyze, hence pre-processing has been done i.e., unstructured data is converted into structured format. After completion of preprocessing, the data is further classified by using Naïve Bayes algorithm. This algorithm performs data classification and divides it into three major classes as positive, negative, and neutral. The result shows that the covaxin yields 48.36% positive, 35.6% negative, and 16.04% neutral, Covishield yields 44.25% positive, 39.67% negative, and 16.08% neutral, Pfizer yields 42.95% positive, 39.45% negative, and 17.6% neutral sentiment. © 2022 IEEE.
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Methods: multicentric observational study, included 6000 COVID-19 RT PCR Positive cases with lung involvement on HRCT thorax at entry point & categorised as Radiological presentation phenotypes as severity assessmentmild, moderate, severe as per lung segment involvement (mild<7, moderate 8-15 and severe 16-25), Evolving and Evolved phenotype- with or without GGOs, consolidations, and crazy paving with or without spreading edges, Anatomical phenotype-Unilateral or bilateral as per lung lobe segment or lobe involvement, Clinicalradiological-pathological phenotypes-five types as classical GGOs, consolidations, Bronchopneumonia, Necrotizing pneumonia and cavitating. Response to treatment phenotypes-easy to treat and difficult to treat as per interventions required & response to treatment. Radiological outcome phenotypes as Resolving, Persistent and Progressive as per lung reticular and fibrosing lesions as with or without honeycombing and or tractional bronchiectasis. Statistical analysis by Chi test and students t test and ANOVA. Observations and analysis:In 6000 radiological assessment of covid-19 pneumonia, significant association was documented in Evolving and Evolved pneumonia phenotypes (p<0.000026), Unilateral and Bilateral pneumonia anatomical phenotypes (p<0.00001), Clinical-radiological-pathological phenotypes (p<0.00001), Easy to treat and Difficult to treat pneumonia phenotypes (p<0.00001), Radiological final outcome phenotypes-Persistent, Progressive & Resolving phenotype (p<0.00001) conclusion: Radiological phenotypes will guide in assessing severity, predicting response to therapy and final outcome in covid-19 pneumonia.
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Methods: observational study, included 6000 COVID-19 indoor cases confirmed with RT-PCR. Retrospective analysis with treatment records, laboratory markers as IL-6, D-dimer, Ferritin, LDH, BSL, HBA1C. All cases undergone thorough interview in 'post covid care' outdoor setting regarding symptomatology, documnted vital signs abnormality, & workup as HBA1C, BSL, TFT, KFT, ECG, chest x-ray, HRCT thorax, BMD, Echocardiography, MRI brain whichever is necessary. Statistical analysis by using Chi square test and ANOVA. Observations: Long covid manifestations were documented in 36.06% (2517/6000) post COVID cases as- Fatigue 41.95%, dyspnea 35.98%, cough 31.96%, chest discomfort 26.95%, anosmia 8.76%, joint pain & headache 11.96% , dizziness, vertigo&insomnia 22.95% &alopecia 4.18% cases, Lung fibrosis in 16.66%, minimal lung abnormality 23.65%, pulmonary embolism 7.18% cases, palpitations 25.56%, chest pain 11.3%, arrythmias 5.53%, cardiac dysfunction 24.31%, PTSD 28%, Impaired memory with or without poor concentration (brain fog) 24.03%, Anxiety and or depression 6.33%, Reduction in quality of life 33%, Diabetes mellitus-new onset26%, transient34%, uncontrolled27%, Osteoporosis38.08%, thyroid dysfunction12.1%. CT severity score, Intensive care treatment with or without oxygen and or ventilator use & Laboratory parameters (D-dimer, IL6, LDH, Ferritin) during hospitalization has significant association with long covid manifestations (p<0.00001) Conclusion(s): Long covid in underestimated, improperly evaluated and halfheartedly treated during follow-up. All treated cases needs prompt evaluation, more awareness regrding its manifestations and its impact on quality of life is must.
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Background: Robust data of IL-6 is available in bacterial infection, and now it can be utilized in currently ongoing COVID-19 (corona virus disease-19) pneumonia pandemic to guide treatment strategy as marker of inflammation. Methods: Prospective, observational study included 1,000 COVID-19 cases confirmed with RT PCR (reverse transcription polymerase chain reaction). All cases were undergone categorized after clinical details, HRCT (high resolution computerized tomography) thorax, oxygen saturation, IL-6 (interleukin 6) at entry point and follow up. Age, gender, comorbidity and use BIPAP/NIV (bilevel positive airway pressure/non-invasive ventilation), and outcome as with or without lung fibrosis as per HRCT severity were key observations. Statistical analysis is done by using Chi-square test. Results: In study of 1,000 COVID-19 pneumonia cases, age (<50 and >50 years) and gender has significant association with IL-6. HRCT severity score at entry point has significant correlation with IL-6 level (p < 0.00001). IL-6 level has significant association with duration of illness (p < 0.00001). Comorbidities has significant association with IL-6 level (p < 0.00001). IL-6 level has significant association with oxygen saturation (p < 0.00001). BIPAP/NIV requirement has significant association with IL-6 level (p < 0.00001). Timing of BIPAP/NIV requirement during course of hospitalization has significant association with IL-6 level (p < 0.00001). Follow-up IL-6 titer during hospitalization as compared to entry point normal and abnormal IL-6 has significant association with post-COVID-19 lung fibrosis, respectively (p < 0.00001). Conclusion: IL-6 has very crucialrole in COVID-19 pneumonia in predicting severity of illness, progression of illness including 'cytokine storm' and assessing response to treatment during hospitalization and follow-up titers in analyzing post-COVID-19 lung fibrosis.
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LBPH (Local Binary Pattern Histogram) is a Facial recognition algorithm used to monitor a COVID infected person using a non-contact method of isolation check. The algorithm is programmed using Python software and the results are analysed using visual studio code. The program extracts feature from an input test image and compares it with the system database. The major goal would be to send the message if the person has violated the isolation norms. This algorithm captures the image of an isolated COVID patient when he/she breaks the isolation norms by opening the door and trying to escape from isolation. © 2022 IEEE.
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Reports of COVID-19 associated mucormycosis has exponentially increased in recent times, especially in patients with uncontrolled diabetes. It is reported to be associated with high mortality and morbidity rates and hence has emerged as a public health crisis. Covid-19 associated mucormycosis poses a diagnostic challenge for the Dentists as the clinical and radiological featuresare largely non-specific. The most common variant of mucormycosis in general is rhino-orbital and involvement of mandible is a rather uncommon presentation. Here we document a rare case of mucormycosis affecting the mandible with the concomitant presence of COVID19 infection in a diabetic patient.
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In the Covid 19 pandemic, education shifted from offline to online, impacting a lot of technical education. The online theory courses were conducted effectively, but there were a lot of problems the faculty faced in conducting laboratory courses. This problem includes an ineffective demonstration of lab experiments, difficulty in time management, monitoring, and assessment, inability to tackle the issues of various students' learning styles, and unavailability of a common platform for online lab conduction. In technical education, the lab course plays a vital role. We found that a virtual laboratory is the best solution to address these issues. Many virtual labs are available for programming courses but need a customized Virtual lab for core courses. In this paper, we have carried out 16 surveys through Google forms to get inputs/feedback from faculties and students to get difficulties in online lab conduction and how we can make the best use of virtual labs online to conduct the lab experiment online mode. We designed and created the virtual laboratory for the Computer Networks Lab course with various learning materials, including theory, simulation videos, pre-test & post-test, and the procedure to conduct the lab experiment, which benefited the students. The implemented virtual lab found more effective. We found the significant impact on the result of CN Lab after using the customized virtual lab for CN Lab course. © 2022, Rajarambapu Institute Of Technology. All rights reserved.
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Background: Emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has given rise to COVID-19 pandemic, which has become a wreaking havoc worldwide. Therefore, there is an urgent need to find out novel drugs to combat SARS-CoV-2 in-fection. In this backdrop, the present study aimed to assess potent bioactive compounds from different fungi as potential inhibitors of SARS-CoV-2 main protease (Mpro) using an in-silico analysis. Method(s): High-Resolution Liquid Chromatography Mass Spectrometry analysis (HR-LCMS) was used for the bioactive profiling of ethanolic crude extract of Dictyophora indusiata, Geastrum tri-plex and Cyathus stercoreus. Of which, only bergenin (D. indusiata), quercitrin (G. triplex) and di-hydroartemisinin (C. stercoreus) were selected based on their medicinal uses, binding score and the active site covered. The 6LU7, a protein crystallographic structure of SARS-CoV-2 Mpro, was docked with bergenin, quercitrin and dihydroartemisinin using Autodock 4.2. Result(s): A total of 118 bioactive compounds were analyzed from the crude extract of used fungi and identified using HR LC/MS analysis. The binding energies obtained were-7.86,-10.29 and-7.20 kcal/mol, respectively, after docking analysis. Bergenin, quercitrin and dihydroartemisinin formed hydrogen bond, electrostatic interactions and hydrophobic interactions with foremost active site amino acids THR190, GLU166, GLN189, GLY143, HIS163, HIS164, CYS145 and PHE140. Conclusion(s): Present investigation suggests that these three compounds may be used as alternative inhibitors against SARS-CoV-2 Mpro. However, further research is necessary to assess in vitro potential of these compounds. To the best of our knowledge, the present investigation reported these three bioactive compounds of fungal origin for the first time.Copyright © 2021 Bentham Science Publishers.
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Background: Health-care providers, particularly pediatric dentists, highly depend on electronic media. This survey attempts to assess how they have taken to e-media to keep themselves abreast of the current situation and use it efficiently. Objectives: To determine attitudes, awareness, and practices of e-media usage among pediatric dental professionals and postgraduate students in pediatric dentistry during the COVID-19. Materials and Methods: A convenience sample of 958 pediatric dental practitioners and postgraduate students in pediatric dentistry from throughout India participated in a descriptive cross-sectional survey. An investigator-designed questionnaire comprising 23 close-ended questions related to the usage and various aspects of e-media before and during the COVID-19 pandemic. Results: Younger generations of pediatric dentistry are more active in the use of e-media. Dentists between the ages of 30 and 50 years are more likely to utilize social media in their profession than dentists above the age of 50 years. For academic purposes and patient communication, e-media was the most popular choice. Conclusion: The Indian pediatric dentistry profession has grown significantly with the use of e-media. © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
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Incidences and mortality from cardiovascular illnesses have grown during the last few decades. In patients with pre-existing cardiac disease, the COVID-19 pandemic has exacerbated cardiovascular problems. Researchers observed that rates of many conditions, comprising coronary heart failure and stroke, had been drastically higher in those who had recovered from COVID-19 as compared to those who did not have the disease. Herbal medicine is becoming more and more popular due to its relatively high safety and low toxicity. Shilajit has several beneficial properties because it primarily comprises fulvic acid and more than 84 minerals. It demonstrates antioxidant activity, which is a key factor in cardioprotection. Shilajit is appropriately referred to as "Rasayana/ Rasayanam";it translates as "rejuvenator" in Ayurvedic and Siddha scriptures since it prevents illnesses and improves the quality of life. The current study involved the collection, authentication, purification, and use of several extractive solvents to achieve high yield, then the extract was enriched by using organic solvents. UV-Vis spectroscopy was performed on each of the enriched samples, and the results showed that the enriched samples had increased fulvic acid concentrations. Fulvic acid was used as a standard in thin-layer chromatography. The extract's in-vitro antioxidant activity was assessed using the DPPH assay, and the results indicated good antioxidant activity. phytosomes were formulated by rapid injection methods for extract and enriched extract, and they were characterized using several spectroscopic techniques. According to the study's findings, combining novel formulation with conventional drug may improve its therapeutic potential and bioavailability.