| Volume 26, Issue 2 | |
| Identification of Metabolite Compounds and Biological Activity of Diplazium esculentum | 131-140 |
| Fathul Zannah, Mohamad Amin, Hadi Suwono, Betty Lukiati | |
| doi: 10.7546/ijba.2022.26.2.000740 | |
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| Fathul Zannah, Mohamad Amin, Hadi Suwono, Betty Lukiati (2022) Identification of Metabolite Compounds and Biological Activity of Diplazium esculentum, Int J Bioautomation, 26 (2), 131-140, doi: 10.7546/ijba.2022.26.2.000740 | |
| Abstract: Diplazium esculentum is one of the medicinal plants used by Dayak tribes in Central Kalimantan to cure acne. The potential of D. esculentum can be proved through information on the active compounds of the extract obtained in decoction and infusa methods. Thus, a liquid chromatography-mass spectrophotometry (LC-MS)-based method is developed to identify the active compounds of D. esculentum extract in either decoction method or infusa method. The chemical compound potential of D. esculentum extract was then analysed using bioinformatics approach based upon the database of PASS online server. Results showed that the D. esculentum extract contained 81 chemical compounds in decoction method and 68 compounds in infusa method, in which the dominant compound was flavonoid. Moreover, PASS online web server analysis found 7 flavonoid compound groups potential as anti-acne containing antisebor, AR expression inhibitor and CYP1A1 inhibitor. This information could be very useful for designing a clinical test on plant natural compound potential for traditional drug development.
Keywords: Medicinal plant, Fern, Anti-acne, Decoction and Infusa methods | |
| Validation of a Light Source for Phototoxicity in in vitro Conditions | 141-152 |
| Ivan Iliev, Inna Sulikovska, Elena Ivanova, Mashenka Dimitrova, Biliana Nikolova, Christina Andreeva | |
| doi: 10.7546/ijba.2022.26.2.000837 | |
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| Ivan Iliev, Inna Sulikovska, Elena Ivanova, Mashenka Dimitrova, Biliana Nikolova, Christina Andreeva (2022) Validation of a Light Source for Phototoxicity in in vitro Conditions, Int J Bioautomation, 26 (2), 141-152, doi: 10.7546/ijba.2022.26.2.000837 | |
| Abstract: Phototoxicity is a chemically induced skin irritation in the presence of sunlight. Phototoxic substances after irradiation with sunlight absorb and convert light energy into chemical energy, leading to the formation of highly reactive oxygen species with toxic effects. Recently LED technologies made possible their application for novel effective solar simulators, to be used in biology and medicine. We study the possibilities of application of LED sunlight simulator (Helios-iO, model LE-9ND55-H – 5500K) for in vitro testing of synthetic and natural products for phototoxicity. Cytotoxicity/phototoxicity was assessed by validated BALB/3T3 clone A31 Neutral Red Uptake Assay. The morphological alterations in BALB/3T3 cells induced by the Radachlorin® and irradiated with dose 2.4 J, were analyzed by fluorescent microscopy. The physical characteristics of the lamp were determined and the intensity distribution of the LED light over a model of a 96-well plate at a distance of 25 cm from the lamp diode matrix center was estimated. The obtained results show that the light emitted by the solar simulator used is similar to the natural sun light. The biological testing results reveal the high efficiency of the solar simulator in an in vitro experimental system for phototoxicity testing.
Keywords: LED Solar Simulator, Phototoxicity, in vitro | |
| Evaluation of the Level of Alertness with Variations in Reaction Time in Bulgarian Sport Students | 153-160 |
| Mariya Zaharinova | |
| doi: 10.7546/ijba.2022.26.2.000859 | |
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| Mariya Zaharinova (2022) Evaluation of the Level of Alertness with Variations in Reaction Time in Bulgarian Sport Students, Int J Bioautomation, 26 (2), 153-160, doi: 10.7546/ijba.2022.26.2.000859 | |
| Abstract: The aim of this study is to evaluate the level of alertness with reaction time test in Bulgarian sport students. Materials and methods: Our sample includes 25 sports student, mean age 19.92, recruited from different disciplines from National Sports Academy “Vassil Levski”, Sofia, Bulgaria. Reaction time has been assessed twice a day (once in the morning and once in the afternoon) to check if reaction time has a relationship with the level of alertness based on chronotype according to Morningness-eveningness Questionnaire (MEQ). Outcome measures include Vienna Test System (test form S7) and MEQ. Results: The moderate morning type had a faster reaction time both, in the morning and in the afternoon as compared to the intermediate and moderate evening type (reaction time with and without cue). Intermediate type had the worst reaction time and moderate evening type were in the middle. Conclusions: The main objective of this study is to find out if the reaction time depends on the level of alertness. It has been found that the participants, which are moderate morning type, indicating high alertness in the morning, have faster reaction time in the morning and in the evening (with or without cue).
Keywords: Morningness-eveningness questionnaire, Reaction time, Chronotype | |
| Experimental Testing of a Prototype of an Active Elbow Orthosis Based on in vivo Investigation of Elbow Flexion/Extension of Healthy Subjects | 161-174 |
| Silvija Angelova, Emil Petrov, Plamen Raykov, Rositsa Raikova | |
| doi: 10.7546/ijba.2022.26.2.000865 | |
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| Silvija Angelova, Emil Petrov, Plamen Raykov, Rositsa Raikova (2022) Experimental Testing of a Prototype of an Active Elbow Orthosis Based on in vivo Investigation of Elbow Flexion/Extension of Healthy Subjects, Int J Bioautomation, 26 (2), 161-174, doi: 10.7546/ijba.2022.26.2.000865 | |
| Abstract: Many people have problems with elbow joint driving because of different diseases, sport trauma, road traffic injuries, etc. A good way for restoring elbow motions is a self-rehabilitation using an active orthosis. It has to be light, convenient for daily use, active, easy to control by patients, and safe. The paper presents a prototype of an active elbow orthosis. The plastic details were designed using a CAD system and were 3D printed. The joint was driven by a Dynamixel actuator. To increase the joint moment, a reduction gear-belt drive was constructed and applied. Experiments with six healthy subjects were performed using a Noraxon measuring system, aiming to investigate elbow joint angles in natural movements with four different velocities of elbow flexion and extension without and with a load of 0.5 kg in the hand. The four velocities (from very slow to very fast) were controlled by a specialized PC application. In order to achieve similar motions of the orthosis, the angle profiles were approximated so that the motion was between 10° and 120° because of electro/mechanical and software safety stoppers. Experiments were performed with the orthosis following the given angle profile without load and with a load of 0.5 kg. The results show that the orthosis’ forearm performs the given angle and angular speed profiles with enough precision.
Keywords: Elbow, Active orthosis, Rehabilitation, Flexion/extension, Human experiments | |
| A Clustering Algorithm for Tumor Gene Data Based on Improved DPC Algorithm | 175-192 |
| Wei Wang, Bo Gao | |
| doi: 10.7546/ijba.2022.26.2.000872 | |
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| Wei Wang, Bo Gao (2022) A Clustering Algorithm for Tumor Gene Data Based on Improved DPC Algorithm, Int J Bioautomation, 26 (2), 175-192, doi: 10.7546/ijba.2022.26.2.000872 | |
| Abstract: Cluster analysis is a principal approach to discover unknown tumor subtypes. Innovative and effective cluster analysis methods are of great significance for tumor diagnosis and malignant tumor treatment. Existing studies on the cluster analysis of tumor gene data generally have defects in aspects such as unsatisfactory performance in clustering high-dimensional and high-noise data, and insufficient accuracy in selecting cluster centers. To overcome these defects, this paper performed cluster analysis on tumor gene data based on an improved Density peaks clustering (DPC) algorithm. At first, this paper elaborated on the composition and storage format of tumor tissue samples used in the experiment, gave the tumor gene expression profile data in the matrix format, and introduced the preprocessing process of gene expression profile data. Then, this paper carried out feature selection of tumor gene expression profile data. At last, this paper innovatively divided the target gene density into two parts of K-nearest neighbor local density and neighborhood density, thereby completing the improvement of conventional DPC algorithm and expanding its application scenarios. Combining with experiment, the clustering results of the algorithm before and after introducing the idea of Approximate Nearest Neighbor (ANN) were given, which had verified the effectiveness of the algorithm proposed in this paper.
Keywords: Cluster analysis, Tumor genes, DPC algorithm, Feature selection, Gene density | |
| A Key Protein Recognition Algorithm Based on High-order Complex Protein Network | 193-208 |
| Xiaojing Wang | |
| doi: 10.7546/ijba.2022.26.2.000873 | |
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| Xiaojing Wang (2022) A Key Protein Recognition Algorithm Based on High-order Complex Protein Network, Int J Bioautomation, 26 (2), 193-208, doi: 10.7546/ijba.2022.26.2.000873 | |
| Abstract: Although the existing protein recognition methods have improved the recognition accuracy of key proteins to a certain extent, they have ignored the biological features of the proteins. In view of this shortcoming, this paper constructed a high-order dynamic complex protein network for key protein recognition. At first, this paper presented a method for feature selection and candidate set evaluation of complex protein network; a weighted network was constructed based on the obtained topological features of the complex protein network and the semantic similarity of protein gene ontology annotations. Then, this paper proposed an algorithm for recognizing key proteins in high-order dynamic protein network based on a Fruit fly optimization algorithm. At last, the effectiveness of the proposed model was verified by experimental results.
Keywords: Complex protein network, Dynamic network, Key protein recognition, Fruit fly optimization algorithm (FOA) |
Sponsored by National Science Fund of Bulgaria, Grant No KP-06-NP3-37, 2022
© 2022, BAS, Institute of Biophysics and Biomedical Engineering