R. Rakshanaa, Aashmi P.L. Jemima, Amin Sheikh Rahul, D. Vishnudas, Kingsley J. Danie
The use of natural substances in cancer treatment is the current need because alternative approaches are intensive and have numerous negative side effects. In this current study, the natural product Prunus dulcis (Almond) was screened for its ability to inhibit the proliferation of (PA-1) cancer cells. In the MTT assay, IC50 values obtained are 220 μg/ml. Reactive Oxygen Species (ROS), Mitochondrial Membrane Potential (MMP) and Apoptosis induction in cancer cells of the ovary are noticed and this assay shows the anti-cancerous activity of Prunus dulcis. Catechin has emerged as the major bioactive compound of Prunus dulcis. Anti-bacterial activity of Prunus dulcis at various concentrations of 50, 80, 90 and 100μl was tested. 90μl of Prunus dulcis extract showed a good antibacterial effect against Saccharomyces cerevisiae. This research shows that the almond bioactive molecules inhibit the proliferation of ovarian cancer cell lines. The identified promising active pharmaceutical ingredient catechin needs focused research.
{"title":"Anti-cancer effects of the bioactive compounds of Prunus dulcis against ovarian cancer cell lines (PA-1)","authors":"R. Rakshanaa, Aashmi P.L. Jemima, Amin Sheikh Rahul, D. Vishnudas, Kingsley J. Danie","doi":"10.25303/1810rjbt041047","DOIUrl":"https://doi.org/10.25303/1810rjbt041047","url":null,"abstract":"The use of natural substances in cancer treatment is the current need because alternative approaches are intensive and have numerous negative side effects. In this current study, the natural product Prunus dulcis (Almond) was screened for its ability to inhibit the proliferation of (PA-1) cancer cells. In the MTT assay, IC50 values obtained are 220 μg/ml. Reactive Oxygen Species (ROS), Mitochondrial Membrane Potential (MMP) and Apoptosis induction in cancer cells of the ovary are noticed and this assay shows the anti-cancerous activity of Prunus dulcis. Catechin has emerged as the major bioactive compound of Prunus dulcis. Anti-bacterial activity of Prunus dulcis at various concentrations of 50, 80, 90 and 100μl was tested. 90μl of Prunus dulcis extract showed a good antibacterial effect against Saccharomyces cerevisiae. This research shows that the almond bioactive molecules inhibit the proliferation of ovarian cancer cell lines. The identified promising active pharmaceutical ingredient catechin needs focused research.","PeriodicalId":21091,"journal":{"name":"Research Journal of Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.25303/1810rjbt1200126
Nancy Kwatra, Nehalika Ramchandani, Jayanthi Abraham
The use of glyphosate has raised a major concern among researchers around the world because of its adverse effects and toxic nature. In the present study, the enrichment technique was used to isolate the strain JAN3 Aspergillus tubingensis from agricultural soil. The ability of the isolate to utilize glyphosate as the sole carbon and energy source was evaluated using HPLC and FTIR. The results revealed that the strain JAN3 could mineralize 96% of glyphosate within 5 days of incubation. The infrared spectrum of standard glyphosate when compared to degradation by strain Aspergillus tubingensis showed the absence of peak for major functional groups which could be due to the breakdown of the compound into simpler structures. IR spectra of the degraded sample showed the presence of an aldehyde group and carboxylic acid which confirmed that glyphosate was mineralized by the strain JAN3. The degradation results were further fitted into different kinetic models and the results showed that the reaction followed pseudo first order kinetics. The extracellular enzymatic activity was analysed during glyphosate degradation. The results of the study highlight that the strain Aspergillus tubingensis may have the potential to mineralize high concentrations of the herbicide in the contaminated areas.
{"title":"Biodegradation of Glyphosate in Aqueous Medium by Strain JAN3 Aspergillus tubingensis isolated from Agricultural Soil","authors":"Nancy Kwatra, Nehalika Ramchandani, Jayanthi Abraham","doi":"10.25303/1810rjbt1200126","DOIUrl":"https://doi.org/10.25303/1810rjbt1200126","url":null,"abstract":"The use of glyphosate has raised a major concern among researchers around the world because of its adverse effects and toxic nature. In the present study, the enrichment technique was used to isolate the strain JAN3 Aspergillus tubingensis from agricultural soil. The ability of the isolate to utilize glyphosate as the sole carbon and energy source was evaluated using HPLC and FTIR. The results revealed that the strain JAN3 could mineralize 96% of glyphosate within 5 days of incubation. The infrared spectrum of standard glyphosate when compared to degradation by strain Aspergillus tubingensis showed the absence of peak for major functional groups which could be due to the breakdown of the compound into simpler structures. IR spectra of the degraded sample showed the presence of an aldehyde group and carboxylic acid which confirmed that glyphosate was mineralized by the strain JAN3. The degradation results were further fitted into different kinetic models and the results showed that the reaction followed pseudo first order kinetics. The extracellular enzymatic activity was analysed during glyphosate degradation. The results of the study highlight that the strain Aspergillus tubingensis may have the potential to mineralize high concentrations of the herbicide in the contaminated areas.","PeriodicalId":21091,"journal":{"name":"Research Journal of Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An important factor that leads to the progression of Alzheimer’s disease is the amyloid-β peptide. Improper degradation of such molecules accompanied by reduced synaptic signaling contributes to the disease. Thus, a critical understanding of proteins interacting in peptide degradation, synaptic transmission and cognition is important to understand the disease progression. In this study, a dataset from public databases was taken and differential gene expression analysis was implemented along with network construction and gene ontology. This gives us more insights into the various biological parameters that are affected and their genetic basis to understand the disease. With a cut-off in adj P-value and log 2-fold change, differentially expressed (DEG) were identified using R. The enrichment analysis resulted in three hub genes which are SST, GFAP and GABRD. These genes have been found to dysregulate crucial processes in Alzheimer’s disease etiology. These three genes are the main drivers of disease and targeting them could essentially reduce disease progression. These could also be used as markers to identify the disease and can be used in diagnostics.
{"title":"Identification of differentially expressed hub genes in Alzheimer’s disease using microarray dataset","authors":"Sampath Kumar Vijayasarathy, Shanthi Veerappapillai","doi":"10.25303/1810rjbt077086","DOIUrl":"https://doi.org/10.25303/1810rjbt077086","url":null,"abstract":"An important factor that leads to the progression of Alzheimer’s disease is the amyloid-β peptide. Improper degradation of such molecules accompanied by reduced synaptic signaling contributes to the disease. Thus, a critical understanding of proteins interacting in peptide degradation, synaptic transmission and cognition is important to understand the disease progression. In this study, a dataset from public databases was taken and differential gene expression analysis was implemented along with network construction and gene ontology. This gives us more insights into the various biological parameters that are affected and their genetic basis to understand the disease. With a cut-off in adj P-value and log 2-fold change, differentially expressed (DEG) were identified using R. The enrichment analysis resulted in three hub genes which are SST, GFAP and GABRD. These genes have been found to dysregulate crucial processes in Alzheimer’s disease etiology. These three genes are the main drivers of disease and targeting them could essentially reduce disease progression. These could also be used as markers to identify the disease and can be used in diagnostics.","PeriodicalId":21091,"journal":{"name":"Research Journal of Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surgical treatment is one of the best approaches to provide a better cure for lung cancer patients. Despite the technological advancements, the increase in lung cancer recurrence rate urges the development of an early-stage predictive model. Therefore, we carried out machine learning algorithms to predict post-operative recurrence in lung cancer patients. It is to note that 80% of patient data was used for the model development and 20% of patient data was used for validation of the model. Besides, the important parameters were found using the extra tree classifier and correlation analysis. Notably, OS, DFS time and tumor size were ensured higher importance during the feature selection process. Random forest achieved the highest accuracy score of 96% than the other algorithms investigated in this study. Indeed, prior consideration of the important features together with the random forest algorithm will help surgeons to make effective treatment progress in lung cancer patients.
{"title":"Development of machine learning models for post-operative recurrence prediction in lung cancer patients","authors":"Dhayanitha Ranganathan Dhakshinamoorthy, Muthu Kumar Thirunavukkarasu, Shanthi Veerappapillai, Ramanathan Karuppasamy","doi":"10.25303/1810rjbt2270234","DOIUrl":"https://doi.org/10.25303/1810rjbt2270234","url":null,"abstract":"Surgical treatment is one of the best approaches to provide a better cure for lung cancer patients. Despite the technological advancements, the increase in lung cancer recurrence rate urges the development of an early-stage predictive model. Therefore, we carried out machine learning algorithms to predict post-operative recurrence in lung cancer patients. It is to note that 80% of patient data was used for the model development and 20% of patient data was used for validation of the model. Besides, the important parameters were found using the extra tree classifier and correlation analysis. Notably, OS, DFS time and tumor size were ensured higher importance during the feature selection process. Random forest achieved the highest accuracy score of 96% than the other algorithms investigated in this study. Indeed, prior consideration of the important features together with the random forest algorithm will help surgeons to make effective treatment progress in lung cancer patients.","PeriodicalId":21091,"journal":{"name":"Research Journal of Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Aphurvika, M. Hemalatha, V. Mohanasrinivasan, Devi C. Subathra
Probiotic drink from fermented beet juice (Beta vulgaris) using Lactobacillus acidophilus and Lactobacillus plantarum was studied for its bioactive properties. The samples were assessed after 24h and 48h of fermentation for their physico-chemical changes and cell viability. Fermented juice showed a significant antibacterial activity against Listeria monocytogenes. Fermented beet juice exhibited a prominent anti-oxidant activity. When compared to fresh beet juice, more amount of total polyphenol content was detected in the fermented beet juice. The probiotic drink also exhibited anti-inflammatory and anti-hemolytic activity which exposed the potential usage of this probiotic drink in the pharmaceutical industry. The antibacterial activity observed against Listeria monocytogenes demonstrated that the fermented beet juice can be used to treat Listeriosis. The FTIR analysis and GC-MS results confirmed the presence of bioactive compounds in the fermented beet juice.
{"title":"Metabolite Profiling and Bioactivity Assessment of Beet Juice fermented by Lactobacillus spp.","authors":"M. Aphurvika, M. Hemalatha, V. Mohanasrinivasan, Devi C. Subathra","doi":"10.25303/1810rjbt069076","DOIUrl":"https://doi.org/10.25303/1810rjbt069076","url":null,"abstract":"Probiotic drink from fermented beet juice (Beta vulgaris) using Lactobacillus acidophilus and Lactobacillus plantarum was studied for its bioactive properties. The samples were assessed after 24h and 48h of fermentation for their physico-chemical changes and cell viability. Fermented juice showed a significant antibacterial activity against Listeria monocytogenes. Fermented beet juice exhibited a prominent anti-oxidant activity. When compared to fresh beet juice, more amount of total polyphenol content was detected in the fermented beet juice. The probiotic drink also exhibited anti-inflammatory and anti-hemolytic activity which exposed the potential usage of this probiotic drink in the pharmaceutical industry. The antibacterial activity observed against Listeria monocytogenes demonstrated that the fermented beet juice can be used to treat Listeriosis. The FTIR analysis and GC-MS results confirmed the presence of bioactive compounds in the fermented beet juice.","PeriodicalId":21091,"journal":{"name":"Research Journal of Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.25303/1810rjbt1270138
K. Sakthishabarish, T. Karthika, S.N. Sandhya, A. Yazhini, Krishnan Kannabiran
Water and soil pollution caused by industrial effluent has become an alarming threat to environmental safety. This is mainly because of the direct discharge of textile effluents into the water bodies, without any pre-treatments. To resolve this, microbial bioremediation is used for the effective removal of the dyes and toxic compounds present in textile effluents. The textile dye-degrading isolates (3A, 4A, 5B and 6B) were isolated from the soil samples collected at the dye contaminated sites. Synthetic textile dyes, Brill Red 3BN and Blue SE2R obtained from the textile dyeing units were used as positive control for this study. The genus of the dye degrading isolates was identified by morphological and biochemical characterization. Based on the results, the isolates were belonged to the genus Pseudomonas. All four strains are producing both pyomelanin (brown) and pyoverdine (green) pigments during their growth. Maximum tolerance concentration (MTC) test, growth kinetics, decolorization and degradation studies were performed to analyze the dye degrading potential of isolates. Strain 3A and 6B showed more than 80% of decolorization up to 2500 ppm dye mix within 5 days of incubation. Isolates used textile dye as their sole carbon source for their growth and development. The biodegraded dye was analysed by GC-MS to measure the dye degrading ability of isolates.
工业废水对水和土壤的污染已成为环境安全的严重威胁。这主要是因为纺织废水直接排放到水体中，没有任何预处理。为了解决这个问题，微生物生物修复技术被用于有效去除纺织品废水中存在的染料和有毒化合物。从染染点土壤样品中分离到降解纺织染料的分离菌株3A、4A、5B和6B。以纺织染色单元获得的合成纺织染料Brill Red 30和Blue SE2R为阳性对照。通过形态和生化鉴定鉴定了该染料降解菌株属。结果表明，分离物属于假单胞菌属。所有四种菌株在生长过程中都产生pyomelanin(棕色)和pyoverdine(绿色)色素。通过最大耐受浓度(MTC)试验、生长动力学、脱色和降解研究，分析了菌株对染料的降解潜力。菌株3A和6B在培养5天内，在2500 ppm的染料混合物中脱色率超过80%。分离菌以纺织染料作为其生长发育的唯一碳源。采用气相色谱-质谱分析分离菌株对染料的降解能力。
{"title":"Bacterial bioremediation of textile effluent dyes contaminated sites","authors":"K. Sakthishabarish, T. Karthika, S.N. Sandhya, A. Yazhini, Krishnan Kannabiran","doi":"10.25303/1810rjbt1270138","DOIUrl":"https://doi.org/10.25303/1810rjbt1270138","url":null,"abstract":"Water and soil pollution caused by industrial effluent has become an alarming threat to environmental safety. This is mainly because of the direct discharge of textile effluents into the water bodies, without any pre-treatments. To resolve this, microbial bioremediation is used for the effective removal of the dyes and toxic compounds present in textile effluents. The textile dye-degrading isolates (3A, 4A, 5B and 6B) were isolated from the soil samples collected at the dye contaminated sites. Synthetic textile dyes, Brill Red 3BN and Blue SE2R obtained from the textile dyeing units were used as positive control for this study. The genus of the dye degrading isolates was identified by morphological and biochemical characterization. Based on the results, the isolates were belonged to the genus Pseudomonas. All four strains are producing both pyomelanin (brown) and pyoverdine (green) pigments during their growth. Maximum tolerance concentration (MTC) test, growth kinetics, decolorization and degradation studies were performed to analyze the dye degrading potential of isolates. Strain 3A and 6B showed more than 80% of decolorization up to 2500 ppm dye mix within 5 days of incubation. Isolates used textile dye as their sole carbon source for their growth and development. The biodegraded dye was analysed by GC-MS to measure the dye degrading ability of isolates.","PeriodicalId":21091,"journal":{"name":"Research Journal of Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.25303/1810rjbt1830190
Sekaran Karthik, R. Gnanasambandan, Iyyadurai Ramya, G. Karthik, Priya Doss C. George
Early diagnosis of the lethal SARS-CoV-2 virus determines a patient’s survival rate. Highly transmissible novel coronavirus prevention is possible with effective, rapid diagnostic strategies. The reverse transcription polymerase chain reaction (RT-PCR), a globally adopted SARS-CoV-2 detection technique, provides better diagnosis results. The output of the RT-PCR test produces the amplified gene scores of ORF1a/b, S, N, E and RdRp. This study intends to evaluate the performance of the RT-PCR-based COVID-19 diagnosis using machine learning models. The confirmatory genes ORF1b, E and RdRp and their cycle threshold (Ct) values are the main parameters used to build the machine learning model for SARS-CoV-2 screening. The real-time dataset collected from the Indian Council of Medical Research (ICMR) database containing missing, redundant information is processed and eliminated. Statistical interpretations are performed with demographic information to understand the dynamics of the disease prevalence in India. Binary classification models delivered promising results in discriminating the samples of two classes. The models were examined further to scrutinize their performance via evaluation metrics such as balanced accuracy, f1-score, ROC curve, precision and recall. This algorithmic assessment exhibits a better outcome on the RT-PCR-based SARS-CoV-2 disease diagnosis.
{"title":"SARS-CoV-2 Screening on the Multiplex Real-Time RT-PCR Gene Cycle Threshold - A Machine Learning Approach","authors":"Sekaran Karthik, R. Gnanasambandan, Iyyadurai Ramya, G. Karthik, Priya Doss C. George","doi":"10.25303/1810rjbt1830190","DOIUrl":"https://doi.org/10.25303/1810rjbt1830190","url":null,"abstract":"Early diagnosis of the lethal SARS-CoV-2 virus determines a patient’s survival rate. Highly transmissible novel coronavirus prevention is possible with effective, rapid diagnostic strategies. The reverse transcription polymerase chain reaction (RT-PCR), a globally adopted SARS-CoV-2 detection technique, provides better diagnosis results. The output of the RT-PCR test produces the amplified gene scores of ORF1a/b, S, N, E and RdRp. This study intends to evaluate the performance of the RT-PCR-based COVID-19 diagnosis using machine learning models. The confirmatory genes ORF1b, E and RdRp and their cycle threshold (Ct) values are the main parameters used to build the machine learning model for SARS-CoV-2 screening. The real-time dataset collected from the Indian Council of Medical Research (ICMR) database containing missing, redundant information is processed and eliminated. Statistical interpretations are performed with demographic information to understand the dynamics of the disease prevalence in India. Binary classification models delivered promising results in discriminating the samples of two classes. The models were examined further to scrutinize their performance via evaluation metrics such as balanced accuracy, f1-score, ROC curve, precision and recall. This algorithmic assessment exhibits a better outcome on the RT-PCR-based SARS-CoV-2 disease diagnosis.","PeriodicalId":21091,"journal":{"name":"Research Journal of Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.25303/1810rjbt2350240
Nancy Kwatra, Soumya Nair, Jayanthi Abraham
Antibiotic resistance by microorganisms is a growing global concern in the medical field. Due to the rampant of medicines, bacterial strains are evolving with new resistance mechanisms the threaten the ability to treat common infectious diseases. The majority of human infections are caused due to the quorum sensing activity of the clinical pathogens, thereby, reducing the effects of antibiotics to combat the prevailing problem. In healthcare, the development of effective strategies to counter antibiotic resistance and microbial biofilm is an urgent priority. The use of specific or potent antimicrobial systems can help to combat, eradicate, or mitigate infections. The polymers are effectively and extensively used in this field due to their inherent properties. The aim of the present study was to analyze the antimicrobial and antibiofilm effects of four natural polymers (chitin, cellulose, chitosan and polyvinylpyrrolidone) against clinical pathogens. The minimum inhibitory concentration of the test polymers was elucidated. Based on the results obtained, it can be concluded that the natural polymers were effective against the clinical strains at varying concentrations. Furthermore, the results highlight the advantage of using natural polymers as a strategy to combat antibiotic resistance and antibiofilm activity in various medical and biotechnological applications.
{"title":"Bioactivity of Natural Polymers against Clinical Pathogens","authors":"Nancy Kwatra, Soumya Nair, Jayanthi Abraham","doi":"10.25303/1810rjbt2350240","DOIUrl":"https://doi.org/10.25303/1810rjbt2350240","url":null,"abstract":"Antibiotic resistance by microorganisms is a growing global concern in the medical field. Due to the rampant of medicines, bacterial strains are evolving with new resistance mechanisms the threaten the ability to treat common infectious diseases. The majority of human infections are caused due to the quorum sensing activity of the clinical pathogens, thereby, reducing the effects of antibiotics to combat the prevailing problem. In healthcare, the development of effective strategies to counter antibiotic resistance and microbial biofilm is an urgent priority. The use of specific or potent antimicrobial systems can help to combat, eradicate, or mitigate infections. The polymers are effectively and extensively used in this field due to their inherent properties. The aim of the present study was to analyze the antimicrobial and antibiofilm effects of four natural polymers (chitin, cellulose, chitosan and polyvinylpyrrolidone) against clinical pathogens. The minimum inhibitory concentration of the test polymers was elucidated. Based on the results obtained, it can be concluded that the natural polymers were effective against the clinical strains at varying concentrations. Furthermore, the results highlight the advantage of using natural polymers as a strategy to combat antibiotic resistance and antibiofilm activity in various medical and biotechnological applications.","PeriodicalId":21091,"journal":{"name":"Research Journal of Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aanchal Pandey, Sakshi Digraskar, Saakshi Lakhwani, Asha Devi S.
The jamun fruit, Syzygium cumini, is known for its significant antioxidant and antigenotoxic characteristics in addition to its antidiabetic effects. Although numerous plant parts are utilized in herbal preparations, the chemical makeup of the fruit and seed is little understood. The high phenolic content of the seed was recently reported. In this study, zinc oxide nanoparticles (ZnO NPs) from Syzygium cumini are synthesized, characterized and evaluated for their antioxidant characteristics (SC). SC seed extract was used to make ZnO NPs which were then studied using X-ray diffraction (XRD), Transmission electron microscopy (TEM), Fourier transform infrared (FTIR) spectroscopy and Ultraviolet-visible spectroscopy. Several doses of nanoparticles were used in antioxidant assays such as the reducing power assay, the 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay and the hydrogen peroxide assay. It was discovered that the antioxidant activity increased along with the NP content.
{"title":"Antioxidant properties of zinc oxide nanoparticles synthesised from Syzygium cumini seed extract","authors":"Aanchal Pandey, Sakshi Digraskar, Saakshi Lakhwani, Asha Devi S.","doi":"10.25303/1810rjbt087091","DOIUrl":"https://doi.org/10.25303/1810rjbt087091","url":null,"abstract":"The jamun fruit, Syzygium cumini, is known for its significant antioxidant and antigenotoxic characteristics in addition to its antidiabetic effects. Although numerous plant parts are utilized in herbal preparations, the chemical makeup of the fruit and seed is little understood. The high phenolic content of the seed was recently reported. In this study, zinc oxide nanoparticles (ZnO NPs) from Syzygium cumini are synthesized, characterized and evaluated for their antioxidant characteristics (SC). SC seed extract was used to make ZnO NPs which were then studied using X-ray diffraction (XRD), Transmission electron microscopy (TEM), Fourier transform infrared (FTIR) spectroscopy and Ultraviolet-visible spectroscopy. Several doses of nanoparticles were used in antioxidant assays such as the reducing power assay, the 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay and the hydrogen peroxide assay. It was discovered that the antioxidant activity increased along with the NP content.","PeriodicalId":21091,"journal":{"name":"Research Journal of Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.25303/1810rjbt2160226
Adrija Aich, Ashish Kumar, Kavitha Thirumurugan
Genes related to human senescence were explored to find their interaction with Circadian rhythm using Cytoscape. Upregulated genes were analyzed for functional enrichment. In Cytohubba, top 10 ranking genes were scored for attributes like MCC, degree etc. TP53 was identified as a top-ranking gene in these attributes. The cancer network was retrieved in Network analyzer of Cytohubba and merged with TP53 network. The merged network was queried for ‘cisplatin’ using STICH in Cytoscape. Enrichment analysis of cisplatin bound TP53 network showed GO process cellular response to abiotic stimulus, negative regulation of telomere capping, replicative senescence, regulation of reactive oxygen species and cellular senescence.
{"title":"Altered Circadian Rhythm of genes involved in Human Senescence: An Interactome Analysis","authors":"Adrija Aich, Ashish Kumar, Kavitha Thirumurugan","doi":"10.25303/1810rjbt2160226","DOIUrl":"https://doi.org/10.25303/1810rjbt2160226","url":null,"abstract":"Genes related to human senescence were explored to find their interaction with Circadian rhythm using Cytoscape. Upregulated genes were analyzed for functional enrichment. In Cytohubba, top 10 ranking genes were scored for attributes like MCC, degree etc. TP53 was identified as a top-ranking gene in these attributes. The cancer network was retrieved in Network analyzer of Cytohubba and merged with TP53 network. The merged network was queried for ‘cisplatin’ using STICH in Cytoscape. Enrichment analysis of cisplatin bound TP53 network showed GO process cellular response to abiotic stimulus, negative regulation of telomere capping, replicative senescence, regulation of reactive oxygen species and cellular senescence.","PeriodicalId":21091,"journal":{"name":"Research Journal of Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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