Jegatheesan Kalirajan

@tcarts.in

Associate Professor Department of Botany and Biotechnology
Thiagarajar College, Madurai

Jegatheesan Kalirajan


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https://researchid.co/jega1966

RESEARCH, TEACHING, or OTHER INTERESTS

Multidisciplinary, Plant Science, Ecology, Evolution, Behavior and Systematics, Biochemistry, Genetics and Molecular Biology
18

Scopus Publications

517

Scholar Citations

11

Scholar h-index

11

Scholar i10-index

Scopus Publications

  • Plant mediated Synthesis and Characterization of Silver nanoparticles and their Application in the Degradation of Methylene Blue dye
    T. Kasthuri, Dr. K. Jegatheesan
    International Journal of Drug Delivery Technology, 2026
    Green technology is the new approach for the synthesis of Silver nanoparticles, and this technique is cost-effective and eco-friendly. In this study, Portulaca grandiflora leaf extract was used for the green synthesis of Silver nanoparticles. This aqueous leaf extract acts as a reducing and stabilizing agent. Green synthesized Silver nanoparticles were characterized using UV-Visible spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), Energy Dispersive X-ray Spectroscopy (EDAX), and Scanning Electron Microscopy (SEM). Also, this method evaluates their efficacy in the degradation of methylene blue. The synthesized nanoparticles were visually confirmed by the formation of a brown-colored solution. An absorption peak at 434 nm confirmed the formation of Silver nanoparticles. This peak corresponds to a band gap of 2.86 eV. FTIR analysis revealed that phytochemicals like phenols and flavonoids present in the plant extract served as capping agents. The crystalline structure of the Silver nanoparticle was confirmed by XRD analysis. The average size of the particle was approximately 13.4 nm and had a face-centered cubic (fcc) crystalline structure. The elements present in the sample were examined by EDAX. The SEM analysis confirmed a spherical morphology, which confirms the presence of metallic Silver. Application studies indicated that the AgNPs effectively degraded the methylene blue dye at room temperature within 24 hours. GC-MS analysis was performed to confirm the degradation process. The result showed the degradation of complex aromatic structures and the formation of new compounds. The present study reveals that the biosynthesized Silver nanoparticles showed high photocatalytic efficiency in the degradation of methylene blue dye.
  • ARSENIC ELIMINATION FROM GROUNDWATER THROUGH PLANT-MEDIATED MAGNETITE NANOPARTICLES SYNTHESIS AND ITS CHARACTERIZATION
    Gopal Samy Balakrishnan, Jegatheesan Kalirajan, Karthik Rajendran
    Environmental Engineering and Management Journal, 2024
    Domestic drinking water arsenic infectivity has long been a source of concern.The current study concentrated on the production and classification of magnetite nanoparticles (MNps) from the collection of plants to evaluate their effectiveness in eliminating arsenic from groundwater.Using plant leaves Abelmoschus esculentus (AE) and Arachis hypogea (AH), magnetite nanoparticles (MNps-AE and MNps-AH) could be easily, economically, and eco-friendly synthesized to create novel inexpensive adsorbents to help remove arsenic as of earth water.The characterization of synthesized MNps was done by UV spectroscopy, SEM, X-ray diffraction, FT-IR, and a sample magnetometer with vibration.A very reliable technique for treating arsenic-contaminated groundwater, with MNps-AE and MNps-AH extracts creates adsorbents with an elevated ability for arsenic as well as magnetic properties.With the aid of kinetic, equilibrium experiments, also the corresponding statistical representations, the adsorption capacities of MNps-AE and MNps-AH, and the arsenic exclusion process of these special adsorbents, were evaluated.The Langmuir adsorption isotherm representation could be clarified by the adsorption isotherm for equally produced resources, more precisely than Freundlich's.The pseudo-second-order mannequin's narrative of the adsorption kinetics mutually with adsorbents revealed intraparticle dispersion was not a single stage for the adsorption practice that could control the rate.
  • Microbial synthesis of magnetite nanoparticles for arsenic removal
    Gopal Samy Balakrishnan, Karthik Rajendran, Jegatheesan Kalirajan
    Journal of Applied Biology and Biotechnology, 2020
    Apart from their vast applications, the magnetic property of magnetite nanoparticles make it as opt candidate for the removal of arsenic from drinking water and other polluted water streams. Magnetite nanoparticles were produced by microbial synthesis from Fusarium oxysporum with Ferric Chloride and magnetite ore as substrates. The structure and morphology of magnetite nanoparticles were characterized by Fourier Transform Infrared (FTIR) Spectroscopy, UV-Vis spectroscopy, X-ray Diffraction (XRD), Scanning Electron Microscope (SEM), and their magnetic properties were characterized Vibrating Sample Magnetometer. The presence of magnetite nanoparticles was indicated by the XRD spectral pattern and their SEM micrograph showed in the nano ranged particles with an average diameter of 26.78 nm. Magnetic characteristic of magnetite nanoparticles was indicated super paramagnetic properties with a saturation magnetic value of 90.01 emug -1 . These magnetite nanoparticles were used to remove the arsenic in the water by simple magnetic adsorption process and the removal efficiency was found to be 96%.
  • Text mining and natural language processing on social media data giving insights for pharmacovigilance: A case study with fentanyl
    R Paulose, B Gopal Samy, K Jegatheesan
    Indian Journal of Pharmaceutical Sciences, 2018
    In the present Investigation, the contribution of data mining and natural language processing in pharmacovigilance of fentanyl, a synthetic opioid pain medication was evaluated as a case study. The tweets containing fentanyl as keyword were retrieved from Twitter social media. The tweets were preprocessed in order to make them ready for the analysis. The sentiment analysis algorithm labeled 1927 tweets (41.85 %) as negative, 2067 tweets (44.9 %) as neutral and 610 (13.25 %) tweets as positive. Crisis, dead, death, die, dose, drug, heroin, kill, lethal, opioid, overdose and police were some of the words frequently associated with fentanyl. The high correlation and association of fentanyl with these terms identified by association rule algorithms demonstrated fentanyl abuse and aftermaths in the real world. This study could further be extended to study the region- and population-wise fentanyl misuse and side effects by adding location and user demographic information, which possibly could help in developing drug abuse prevention programs.
  • A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction
    Renjith Paulose, Kalirajan Jegatheesan, GopalSamy Balakrishnan
    Indian Journal of Pharmacology, 2018
    CONTEXT: Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details create massive data which are becoming difficult to manage. Identifying the desired featured chemical with the desired biological activity from millions of chemicals is a challenging task. AIMS: In this study, we investigate and explore big data technologies and machine learning approaches to do an efficient chemical data mining for endocrine receptor disruption prediction and virtual compound screening. The power of artificial neural network (ANN) in predicting chemicals' activity toward androgen receptor (AR) and estrogen receptor (ER) and thereby classifying into human endocrine disruptor or nondisruptor is investigated. SUBJECTS AND METHODS: Molecules are collected along with their Inhibitory Concentration (IC50) values toward AR and ER. Training and test datasets are created with active and inactive classes of molecules. Molecular fingerprints of Electro Topological State (E-State) are generated for describing every compound. ANN machine learning model is created using Apache Spark and implemented in Hadoop big data environment. Test chemical's structural similarity toward active class of training compounds is estimated and combined with ANN model for improving prediction accuracy. RESULTS: AR and ER predictive models applied on corresponding test datasets gave 86.31% and 89.57% accuracies, respectively, in correctly classifying molecules as disruptor or nondisruptor. Molecular fragments and functional groups are ranked based on their importance in forming ANN model and influence toward the AR and ER disruption behavior. Training molecules that are specific to the test molecules' endocrine disruption prediction are retrieved based on the structural similarity values. CONCLUSIONS: The current study demonstrates a new approach of chemical endocrine receptor disruption prediction combining ANN machine learning method and molecular similarity in a big data environment. This method of predictive modeling can be further tested with more receptors and hormones and predictive power can be examined.
  • Isolation of microbes for remediation of textile dye industry effluent
    Ecology Environment and Conservation, 2017
  • Identification of tyrosinase from Dioscorea alata tuber extract by homology driven proteomics approach
    Gopal Samy Balakrishnan, Jegatheesan Kalirajan
    Current Proteomics, 2016
  • Machine learning classifier algorithms to predict endocrine toxicity of chemicals
    International Journal of Toxicological and Pharmacological Research, 2015
  • Potential expression of cDNA of BHK21 cells-derived recombinant human erythropoietin in E.Coli cells
    International Journal of Pharmtech Research, 2015
  • Evaluation of antidiabetic, antihyperlipidemic and histopathologic effect of dry fruit powders of Phyllanthus emblica Linn (Euphorbiaceae) in alloxan induced diabetic albino rats
    International Journal of Pharmaceutical Sciences Review and Research, 2015
  • Characterization of tyrosinase enzyme from the tubers of amorphophallus paeoniifolius (Dennst.) Nicolson, (Araceae)
    International Journal of Pharmacognosy and Phytochemical Research, 2015
  • Antifungal activity of biogenic selenium nanoparticles synthesized from electronic waste
    International Journal of Pharmtech Research, 2015
  • Synthesis of magnetite nanoparticles for arsenic removal from ground water pond
    International Journal of Pharmtech Research, 2015
  • Hepatoprotective effect of Embilica Officinalis and its silver nanoparticles against CCL4 induced hepatotoxicity in wistar albino rats
    Digest Journal of Nanomaterials and Biostructures, 2014
  • Prophylactic effect of andrographis paniculata extracts against fungal species
    Rajalakshmi
    Journal of Applied Pharmaceutical Science, 2012
  • Use of silica-gold core shell structured nanoparticles for targeted drug delivery system
    Thangaraja Amirthalingam, Jegatheesan Kalirajan
    Journal of Nanomedicine and Nanotechnology, 2011
  • Immunomodulatory activity of Eclipta prostrata in SRBC immunized mice
    Journal of Pharmacognosy and Phytotherapy, 2011
  • Isolation of potential antibacterial and antioxidant compounds from Acalypha indica and Ocimum basilicum
    Journal of Medicinal Plants Research, 2009

RECENT SCHOLAR PUBLICATIONS

  • Plant Mediated Synthesis ans Characterization of Silver nanoparticles and their application on the degradation of Methylene Blue dye
    TKK Jegatheesan
    International Journal of Drug Delivery Technology Volume 16, Issue 10s, 2026 … , 2026
    2026
  • Plant-Mediated Synthesis (Portulaca grandiflora) and Characterization of Zinc Oxide Nanoparticles and their effect on Degradation pof Methylene Blue Dye and Textile Dye Effluent
    KT Jegatheesan K
    JOURNAL OF APPLIED BIOANALYSIS, 11 (16), 565-576 , 2025
    2025
  • ARSENIC ELIMINATION FROM GROUNDWATER THROUGH PLANT-MEDIATED MAGNETITE NANOPARTICLES SYNTHESIS AND ITS CHARACTERIZATION.
    GS Balakrishnan, J Kalirajan, K Rajendran
    Environmental Engineering & Management Journal (EEMJ) 23 (1) , 2024
    2024
    Citations: 1
  • NANOPARTICLES – A REVIEW ON THEIR PROPERTIES AND APPLICATIONS IN TARGETED DRUG DELIVERY
    AAJ Kalirajan
    European Chemical Bulletin 12 (10), 8451-8480 , 2023
    2023
  • Comparative analysis of Physico Chemical parameter and Chromium Level of Untreated and Treated Effluents of Tannery Industries of Dindigul, Tamilnadu, India
    AA Jegatheesan K
    Applie Ecology and Environmental Sciences 10 (8), 557-564 , 2022
    2022
    Citations: 2
  • SYNTHESIS AND CHARACTERIZATION OF CHROMIUM NANOPARTICLES FROM TANNERY INDUSTRIES USING PLANT EXTRACTS
    JK Anusha A
    International Journal of Modern Research and Reviews 8 (11), 16-24 , 2020
    2020
  • Microbial synthesis of magnetite nanoparticles for arsenic removal
    KRJK Gopal Samy Balakrishnan
    Journal of Applied Biology & Biotechnology 8 (3), 70-75 , 2020
    2020
    Citations: 23
  • A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction
    R Paulose, K Jegatheesan, GS Balakrishnan
    Indian Journal of Pharmacology 50 (4), 169-176 , 2018
    2018
    Citations: 8
  • Text mining and Natural Language Processing on Social Media Data giving Insights for Pharmacovigilance: A Case Study with Fentanyl
    GSBKJ PAULOSE, R.
    Indian J Pharm Sci 80 (4), 762-766 , 2018
    2018
    Citations: 9
  • Isolation of microbes for remediation of textile dye industry effluent
    KJBGS Shiny Guruce A.*†, S. Rajanarayanan†
    Eco. Env. & Cons. 23 (1), 433-440 , 2017
    2017
  • In-Vitro Propagation of Dioscorea alata for Tyrosinase Production
    CIF B. Gopal Samy, K. Jegatheesan
    Journal of Applied Biology & Biotechnology Vol. 5 (02), pp. 085-088 5 (2), 85-88 , 2017
    2017
    Citations: 4
  • Identification of tyrosinase from Dioscorea alata tuber extract by homology driven proteomics approach
    G Samy Balakrishnan, J Kalirajan
    Current Proteomics 13 (1), 1-8 , 2016
    2016
    Citations: 2
  • Decision Tree Learning and Regression Models to Predict Endocrine Disruptor Chemicals-A Big Data Analytics Approach with Hadoop and Apache Spark
    P Renjith
    International Journal of Machine Intelligence, ISSN, 0975-2927 , 2016
    2016
    Citations: 2
  • Synthesis of magnetite nanoparticles for arsenic removal from ground water pond.
    KR Karthik Rajendran, GS Balakrishnan, JK Jegatheesan Kalirajan
    2015
  • Synthesis of magnetite nanoparticles for arsenic removal from ground water pond
    K Rajendran, GS Balakrishnan, J Kalirajan
    Int. J. PharmTech Res 8, 670-677 , 2015
    2015
    Citations: 15
  • Antifungal Activity of Biogenic Selenium Nanoparticles Synthesized from Electronic Waste
    B Eswarapriya, KS Jegatheesan
    Int J PharmTech Res 8 (3), 383-6 , 2015
    2015
    Citations: 27
  • Isolation of Streptomyces Species from Soil and Its Medium Optimization for Microbial Transglutaminase Production by Box-Behnken Design
    GB Samy, S Sujitha, R Thyagarajan, K Jegatheesan
    Journal of Ecosystem and Ecography 6 (1) , 2015
    2015
    Citations: 1
  • Potential Expression of cDNA of BHK21 cells -Derived Recombinant Human Erythropoietin in E.coli cells
    JK Anitha G
    International Journal of Pharm Tech Research 8 (6), 19-25 , 2015
    2015
  • Machine Learning Classifier Algorithms to Predict Endocrine Toxicity of Chemicals
    JK Renjith P
    International Journal of Toxicological and Pharmacological Research 7 (6) , 2015
    2015
    Citations: 2
  • Characterization of Tyrosinase enzyme from the tubers of Amorphophallus paeoniifolius (Dennst.) Nicolson, (Araceae)
    BGSK Jegatheesan
    International Journal of Pharmacognosy and Phytochemical Research 7 (3), 585-589 , 2015
    2015
    Citations: 9

MOST CITED SCHOLAR PUBLICATIONS

  • Screening of Antibacterial and Antioxidant activities of Leaves of Eclipta prostrata (L).
    VKJK Karthi kumar S
    Scientific Research and Essay 2 (4), 101-104 , 2007
    2007
    Citations: 191
  • Isolation of potential antibacterial and antioxidant compounds from Acalypha indica and Ocimum basilicum.
    KR Durga, S Karthikumar, K Jegatheesan
    Journal of Medicinal Plants Research 3 (10), 703-706 , 2009
    2009
    Citations: 59
  • Use of silica-gold core shell structured nanoparticles for targeted drug delivery system
    T Amirthalingam, J Kalirajan, A Chockalingam
    J. Nanomed. Nanotechnol 2 (6) , 2011
    2011
    Citations: 38
  • Preparation and characterization of polyethylene glycol coated silica nanoparticles for drug delivery application
    A Thangaraja, V Savitha, K Jegatheesan
    Int. J. Nanotechnology. Appl. 4, 31-38 , 2010
    2010
    Citations: 36
  • HEPATOPROTECTIVE EFFECT OF EMBILICA OFFICINALIS AND ITS SILVER NANOPARTICLES AGAINST CCl4 INDUCED HEPATOTOXICITY IN WISTAR ALBINO RATS.
    R Bhuvaneswari, N Chidambaranathan, K Jegatheesan
    Digest Journal of Nanomaterials & Biostructures (DJNB) 9 (1) , 2014
    2014
    Citations: 28
  • Antifungal Activity of Biogenic Selenium Nanoparticles Synthesized from Electronic Waste
    B Eswarapriya, KS Jegatheesan
    Int J PharmTech Res 8 (3), 383-6 , 2015
    2015
    Citations: 27
  • Microbial synthesis of magnetite nanoparticles for arsenic removal
    KRJK Gopal Samy Balakrishnan
    Journal of Applied Biology & Biotechnology 8 (3), 70-75 , 2020
    2020
    Citations: 23
  • Hepatoprotective Activity of Andrographis paniculata on Paracetamol Induced Liver Damage in Rats
    K G. Rajalakshmi, G., Arul Jothi, K., Venkatesan, R
    Journal of Pharmacy Research 5 (6), 2983-2986 , 2012
    2012
    Citations: 21
  • Synthesis of magnetite nanoparticles for arsenic removal from ground water pond
    K Rajendran, GS Balakrishnan, J Kalirajan
    Int. J. PharmTech Res 8, 670-677 , 2015
    2015
    Citations: 15
  • Prophylactic effect of Andrographis paniculata extracts against fungal species
    G Rajalakshmi, D Aruna, B Bhuvaneswari, RS Venkatesan, A Natarajan, ...
    Journal of Applied Pharmaceutical Science 2 (9), 058-060 , 2012
    2012
    Citations: 13
  • Immunomodulatory activity of Eclipta prostrata in
    S Karthikumar, K Jegatheesan, A Thangaraja, K Banupriya, T Dhivya, ...
    Journal of Pharmacognosy and Phytotherapy 3 (4), 52-55 , 2011
    2011
    Citations: 13
  • Text mining and Natural Language Processing on Social Media Data giving Insights for Pharmacovigilance: A Case Study with Fentanyl
    GSBKJ PAULOSE, R.
    Indian J Pharm Sci 80 (4), 762-766 , 2018
    2018
    Citations: 9
  • Characterization of Tyrosinase enzyme from the tubers of Amorphophallus paeoniifolius (Dennst.) Nicolson, (Araceae)
    BGSK Jegatheesan
    International Journal of Pharmacognosy and Phytochemical Research 7 (3), 585-589 , 2015
    2015
    Citations: 9
  • A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction
    R Paulose, K Jegatheesan, GS Balakrishnan
    Indian Journal of Pharmacology 50 (4), 169-176 , 2018
    2018
    Citations: 8
  • HYPOGLYCEMIC EFFECT OF 2-HYDROXYCHALCONE ON HIGH FRUCTOSE FED DIABETIC RAT
    RVUK M. Jayanthi, K. Jegatheesan
    International Journal of Pharmaceutical Sciences and Research 3 (2), 600-604 , 2012
    2012
    Citations: 6
  • In-Vitro Propagation of Dioscorea alata for Tyrosinase Production
    CIF B. Gopal Samy, K. Jegatheesan
    Journal of Applied Biology & Biotechnology Vol. 5 (02), pp. 085-088 5 (2), 85-88 , 2017
    2017
    Citations: 4
  • Evaluation of Antidiabetic, Antihyperlipidemic and Histopathologic Effect of Dry Fruit Powders of Phyllanthus emblica Linn (Euphorbiaceae) in Alloxan Induced Diabetic Albino Rats
    JK Menaga. G
    Int. J. Pharm. Sci. Rev. Res., 32 (2), 180-186 , 2015
    2015
    Citations: 3
  • Isolation of Streptomyces sp. from soil and its medium optimization for microbial transglutaminase production by box-behnken design
    TRJK Gopal Samy B, Sujitha S
    3rd world Congress. Journal of Biotechnology and Biomaterials 2 , 2012
    2012
    Citations: 3
  • Comparative analysis of Physico Chemical parameter and Chromium Level of Untreated and Treated Effluents of Tannery Industries of Dindigul, Tamilnadu, India
    AA Jegatheesan K
    Applie Ecology and Environmental Sciences 10 (8), 557-564 , 2022
    2022
    Citations: 2
  • Identification of tyrosinase from Dioscorea alata tuber extract by homology driven proteomics approach
    G Samy Balakrishnan, J Kalirajan
    Current Proteomics 13 (1), 1-8 , 2016
    2016
    Citations: 2