Pub Date : 2024-04-09DOI: 10.2174/0122115366264794240327073739
Parkhomenko Daria, Belenichev Igor F, Kuchkovskyi Oleh M, Ryzhenko Victor
OBJECTIVES Periodontal diseases are a rather complex problem of modern dentistry and do not have only medical but also social significance. The objective of this study is to weigh the effect of a mixture of Thiotriazoline and L-arginine (1:4) on the parameters of the system of endogenous cytoprotection of blood and periodontal illness in rats with experimental chronic generalized periodontitis and substantiate further study of this blend. MATERIALS AND METHODS The study aimed to evaluate the impact of a combination of Thiotria-zoline and L-arginine (in a ratio of 1:4) on the parameters of the endogenous blood cytoprotection system and periodontium in rats with experimental chronic generalized periodontitis. A group of outbred rats weighing 190-220 g and sourced from the vivarium of the Institute of Pharmacology and Toxicology of the Academy of Medical Sciences of Ukraine were divided into four groups, each consisting of 10 animals. 1) Intact group, animals that were injected intragastrically with a solution of sodium chlo-ride to chloride 0.9% for 30 days; 2) control, animals with experimental CGP who intragastrically sodium chloride solution 0.9% for 30 days; 3) animals with experimental CGP were injected intramuscularly with Thiotriazoline + L-arginine (1:4) in a dosage of 200 mg/kg (30 days). 4) animals with experimental CGP, for which daily intragastric reference drug Mexidol, in dosage 250 mg/kg (30 days). In this study, we utilized two substances: Thiotriazoline and L-arginine hydrochloride. The com-bination of Thiotriazoline and L-arginine (in a ratio of 1:4) was prepared at the Department of Pharmaceutical Chemistry of ZSMU. At the conclusion of the experiment, the rats were carefully removed from the study while under thiopental-sodium anesthesia, and administered at a dosage of 40 mg/kg. RESULTS We have found that the administration of a combined preparation of Thiotriazoline with L-arginine to rats with CGP leads to a significant decrease in the blood concentration of pro-inflammatory cytokines IL-1b and TNF-a by 56.1% and 71%, respectively. CONCLUSION The administration of Mexidol at a dosage of 250 mg/kg, as well as the combination of Thiotriazoline and L-arginine in a ratio of 1:4 at a dosage of 200 mg/kg, resulted in a significant reduction in gingival pocket depth in animals with CGP. Specifically, the gingival pocket depth was reduced to 6 mm (p<0.05) with Mexidol and further reduced to 4 mm (p<0.05) with the combination of Thiotriazoline and L-arginine. Additionally, the animals exhibited minimal bleed-ing, swelling, and tooth mobility when treated with the combination of Thiotriazoline and L-arginine. The administration of a combination of Thiotriazoline and L-arginine (in a ratio of 1:4) at a dos-age of 200 mg/kg to animals with CGP resulted in a noteworthy reduction in the blood concen-tration of pro-inflammatory cytokines IL-1b and TNF-a. Specifically, there was a significant de-crease of 56.1% (p<0.05) in IL-1b and 71
{"title":"Characteristics of HIF-1Α and HSP70 MRNA Expression, Level, and Inter-leukins in Experimental Chronic Generalized Periodontitis.","authors":"Parkhomenko Daria, Belenichev Igor F, Kuchkovskyi Oleh M, Ryzhenko Victor","doi":"10.2174/0122115366264794240327073739","DOIUrl":"https://doi.org/10.2174/0122115366264794240327073739","url":null,"abstract":"OBJECTIVES\u0000Periodontal diseases are a rather complex problem of modern dentistry and do not have only medical but also social significance. The objective of this study is to weigh the effect of a mixture of Thiotriazoline and L-arginine (1:4) on the parameters of the system of endogenous cytoprotection of blood and periodontal illness in rats with experimental chronic generalized periodontitis and substantiate further study of this blend.\u0000\u0000\u0000MATERIALS AND METHODS\u0000The study aimed to evaluate the impact of a combination of Thiotria-zoline and L-arginine (in a ratio of 1:4) on the parameters of the endogenous blood cytoprotection system and periodontium in rats with experimental chronic generalized periodontitis. A group of outbred rats weighing 190-220 g and sourced from the vivarium of the Institute of Pharmacology and Toxicology of the Academy of Medical Sciences of Ukraine were divided into four groups, each consisting of 10 animals. 1) Intact group, animals that were injected intragastrically with a solution of sodium chlo-ride to chloride 0.9% for 30 days; 2) control, animals with experimental CGP who intragastrically sodium chloride solution 0.9% for 30 days; 3) animals with experimental CGP were injected intramuscularly with Thiotriazoline + L-arginine (1:4) in a dosage of 200 mg/kg (30 days). 4) animals with experimental CGP, for which daily intragastric reference drug Mexidol, in dosage 250 mg/kg (30 days). In this study, we utilized two substances: Thiotriazoline and L-arginine hydrochloride. The com-bination of Thiotriazoline and L-arginine (in a ratio of 1:4) was prepared at the Department of Pharmaceutical Chemistry of ZSMU. At the conclusion of the experiment, the rats were carefully removed from the study while under thiopental-sodium anesthesia, and administered at a dosage of 40 mg/kg.\u0000\u0000\u0000RESULTS\u0000We have found that the administration of a combined preparation of Thiotriazoline with L-arginine to rats with CGP leads to a significant decrease in the blood concentration of pro-inflammatory cytokines IL-1b and TNF-a by 56.1% and 71%, respectively.\u0000\u0000\u0000CONCLUSION\u0000The administration of Mexidol at a dosage of 250 mg/kg, as well as the combination of Thiotriazoline and L-arginine in a ratio of 1:4 at a dosage of 200 mg/kg, resulted in a significant reduction in gingival pocket depth in animals with CGP. Specifically, the gingival pocket depth was reduced to 6 mm (p<0.05) with Mexidol and further reduced to 4 mm (p<0.05) with the combination of Thiotriazoline and L-arginine. Additionally, the animals exhibited minimal bleed-ing, swelling, and tooth mobility when treated with the combination of Thiotriazoline and L-arginine. The administration of a combination of Thiotriazoline and L-arginine (in a ratio of 1:4) at a dos-age of 200 mg/kg to animals with CGP resulted in a noteworthy reduction in the blood concen-tration of pro-inflammatory cytokines IL-1b and TNF-a. Specifically, there was a significant de-crease of 56.1% (p<0.05) in IL-1b and 71","PeriodicalId":18583,"journal":{"name":"MicroRNA","volume":"30 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140720960","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 : 2024-04-08DOI: 10.2174/0122115366288068240322064431
Huiwen Jiang, Song Kai
BACKGROUND Long non-coding RNA (lncRNA) plays a crucial role in various biolog-ical processes, and mutations or imbalances of lncRNAs can lead to several diseases, including cancer, Prader-Willi syndrome, autism, Alzheimer's disease, cartilage-hair hypoplasia, and hear-ing loss. Understanding lncRNA-protein interactions (LPIs) is vital for elucidating basic cellular processes, human diseases, viral replication, transcription, and plant pathogen resistance. Despite the development of several LPI calculation methods, predicting LPI remains challenging, with the selection of variables and deep learning structure being the focus of LPI research. METHODS We propose a deep learning framework called AR-LPI, which extracts sequence and secondary structure features of proteins and lncRNAs. The framework utilizes an auto-encoder for feature extraction and employs SE-ResNet for prediction. Additionally, we apply transfer learning to the deep neural network SE-ResNet for predicting small-sample datasets. RESULTS Through comprehensive experimental comparison, we demonstrate that the AR-LPI ar-chitecture performs better in LPI prediction. Specifically, the accuracy of AR-LPI increases by 2.86% to 94.52%, while the F-value of AR-LPI increases by 2.71% to 94.73%. CONCLUSION Our experimental results show that the overall performance of AR-LPI is better than that of other LPI prediction tools.
{"title":"Prediction of LncRNA-protein Interactions Using Auto-Encoder, SE-ResNet Models and Transfer Learning.","authors":"Huiwen Jiang, Song Kai","doi":"10.2174/0122115366288068240322064431","DOIUrl":"https://doi.org/10.2174/0122115366288068240322064431","url":null,"abstract":"BACKGROUND\u0000Long non-coding RNA (lncRNA) plays a crucial role in various biolog-ical processes, and mutations or imbalances of lncRNAs can lead to several diseases, including cancer, Prader-Willi syndrome, autism, Alzheimer's disease, cartilage-hair hypoplasia, and hear-ing loss. Understanding lncRNA-protein interactions (LPIs) is vital for elucidating basic cellular processes, human diseases, viral replication, transcription, and plant pathogen resistance. Despite the development of several LPI calculation methods, predicting LPI remains challenging, with the selection of variables and deep learning structure being the focus of LPI research.\u0000\u0000\u0000METHODS\u0000We propose a deep learning framework called AR-LPI, which extracts sequence and secondary structure features of proteins and lncRNAs. The framework utilizes an auto-encoder for feature extraction and employs SE-ResNet for prediction. Additionally, we apply transfer learning to the deep neural network SE-ResNet for predicting small-sample datasets.\u0000\u0000\u0000RESULTS\u0000Through comprehensive experimental comparison, we demonstrate that the AR-LPI ar-chitecture performs better in LPI prediction. Specifically, the accuracy of AR-LPI increases by 2.86% to 94.52%, while the F-value of AR-LPI increases by 2.71% to 94.73%.\u0000\u0000\u0000CONCLUSION\u0000Our experimental results show that the overall performance of AR-LPI is better than that of other LPI prediction tools.","PeriodicalId":18583,"journal":{"name":"MicroRNA","volume":"201 S598","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140730851","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}
Non-coding RNAs that are small in size, called microRNAs (miRNAs), exert a conse-quence in neutralizing gene activity after transcription. The nervous system is a massively ex-pressed organ, and an expanding body of research reveals the vital functions that miRNAs play in the brain's growth and neural activity. The significant benefit of miRNAs on the development of the central nervous system is currently shown through new scientific methods that concentrate on targeting and eradicating vital miRNA biogenesis pathways the elements involving Dicer and DGCR8. Modulation of miRNA has been associated with numerous essential cellular processes on neural progenitors, like differentiation, proliferation, and destiny determination. Current re-search discoveries that emphasize the significance of miRNAs in the complex process of brain development are included in this book. The miRNA pathway plays a major role in brain devel-opment, its operational dynamics, and even diseases. Recent studies on miRNA-mediated gene regulation within neural discrepancy, the circadian period and synaptic remodeling are signs of this. We also discussed how these discoveries may affect our comprehension of the fundamental processes behind brain diseases, highlighting the novel therapeutic opportunities miRNAs pro-vide for treating various human illnesses.
{"title":"Role of miRNAs in Brain Development.","authors":"Himanshu Sharma, Monika Kaushik, Priyanka Goswami, Sanakattula Sreevani, Ananya Chakraborty, Sumel Ashique, Radheshyam Pal","doi":"10.2174/0122115366287127240322054519","DOIUrl":"https://doi.org/10.2174/0122115366287127240322054519","url":null,"abstract":"Non-coding RNAs that are small in size, called microRNAs (miRNAs), exert a conse-quence in neutralizing gene activity after transcription. The nervous system is a massively ex-pressed organ, and an expanding body of research reveals the vital functions that miRNAs play in the brain's growth and neural activity. The significant benefit of miRNAs on the development of the central nervous system is currently shown through new scientific methods that concentrate on targeting and eradicating vital miRNA biogenesis pathways the elements involving Dicer and DGCR8. Modulation of miRNA has been associated with numerous essential cellular processes on neural progenitors, like differentiation, proliferation, and destiny determination. Current re-search discoveries that emphasize the significance of miRNAs in the complex process of brain development are included in this book. The miRNA pathway plays a major role in brain devel-opment, its operational dynamics, and even diseases. Recent studies on miRNA-mediated gene regulation within neural discrepancy, the circadian period and synaptic remodeling are signs of this. We also discussed how these discoveries may affect our comprehension of the fundamental processes behind brain diseases, highlighting the novel therapeutic opportunities miRNAs pro-vide for treating various human illnesses.","PeriodicalId":18583,"journal":{"name":"MicroRNA","volume":"96 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140751807","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 : 2024-03-01DOI: 10.2174/221153661301240226102741
I. A
{"title":"MicroRNA and Cancer: A Path to Discovery","authors":"I. A","doi":"10.2174/221153661301240226102741","DOIUrl":"https://doi.org/10.2174/221153661301240226102741","url":null,"abstract":"","PeriodicalId":18583,"journal":{"name":"MicroRNA","volume":"7 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140085040","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 : 2023-11-01DOI: 10.2174/221153661203231025164834
{"title":"Acknowledgements to Reviewers","authors":"","doi":"10.2174/221153661203231025164834","DOIUrl":"https://doi.org/10.2174/221153661203231025164834","url":null,"abstract":"","PeriodicalId":18583,"journal":{"name":"MicroRNA","volume":"10 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135370344","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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