Bio-Algorithms and Med-Systems最新文献

{"title":"Transcriptomic data analysis of melanocytes and melanoma cell lines of LAT transporter genes for precise medicine","authors":"M. Szczepanek, D. Panek, M. Przybyło, P. Moskal, E. Stępień","doi":"10.2478/bioal-2022-0086","DOIUrl":"https://doi.org/10.2478/bioal-2022-0086","url":null,"abstract":"\u0000 Background: Boron Neutron Capture Therapy (BNCT) is a two-step treatment that can be used in some types of cancers. It involves administering a compound containing boron atoms to the patient and irradiating the affected area of the body with a neutron beam. The success of the therapy depends mainly on the delivery of the boron isotope (10B) to the tumor using an appropriate boron carrier. One of the boron carriers used is boronophenylalanine (BPA). Therefore, in research on the use of boron carriers, it is also important to know the mechanisms of its uptake by cells. Aim: To study the expression of LAT family genes in two melanoma (high melanotic WM115 and low melanotic WM266-4) cell lines and melanocytes (HEMa-Lp) which are responsible for the transport the BPA into cells. Methods: To normalize data from the transcriptomic analysis, the ratio of the median method was used. This allowed the samples to be compared with each other. Comparison metrics included log-fold change (LFC) values. The heatmap of LFC values and the cluster map were created. These graphs show the similarities and differences between the samples. Results: Transcriptomic data show that in melanocytes, LFC for SLC7A5 (LAT1) and SLC3A2 (4Fhc) was higher than in melanoma cell lines, which corresponded with their melanin content. Conclusion: Our results indicate overexpression of BPA transporter genes in normal cells (melanocytes), which may suggest the highest level of these proteins in melanocytes compared to less melanotic melanoma. Therefore, for BNCT, the use of BPA as the 10B carrier will require additional qualifying tests of amino acid transporter expression for patients and specific tumors to develop a personalized BNCT.","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41691769","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}

{"title":"Welcome to Bio-Algorithms and Med-Systems (BAMS)","authors":"E. Stępień","doi":"10.2478/bioal-2022-0092","DOIUrl":"https://doi.org/10.2478/bioal-2022-0092","url":null,"abstract":"\"Times are changing and we are changing with them.\" This hexameter has appeared since the 16th century and accompanies us in many paraphrases and translations, such as „Tempora mutantur et nos mutamur in ipsis” (Time is changing and we are in time, by Andreas Bardonius) [1]. Over time, our research problems, methodology and ways of disseminating scientific information also change. The first issue of the journal was published in 2005 as a result of the May conference in the series \"Cybernetic modeling of biological systems\", and the issue was entirely edited by prof. Irena RotermanKonieczna, founder and longtime editor of the journal [2]. In the final discussion summarizing this conference, Prof. Roterman-Konieczna described the idea of establishing an interdisciplinary forum, enabling mutual contacts between representatives of various fields of science, including working contacts, the journal BioAlgorithms and Med-Systems (BAMS). BAMS has been successfully such a \"forum\" for over 17 years. From today’s perspective, the scale of this forum seemed small, if only because of the Polish editorial house, but it was a nationwide journal, read and edited by a scientific team of international reputation. In the first issue of the journal we meet the names of scientists and professors, such as Leszek Konieczny, Andrzej Szczeklik, Piotr Thor, Jan Trąbka, Antoni Grzanka, Piotr Franaszczuk, Kalina Kawecka-Jaszcz, Jerzy Włodarski, Zbigniew Mikrut, but also young scientists such as Piotr Augustyniak, Mariusz Duplaga, Aleksandra Jung, Andrzej Kononowicz and many others.","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48527484","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}

{"title":"Proteomic profiling of exosomes derived from pancreatic beta-cells cultured under hyperglycemia","authors":"Carina Rząca, U. Jankowska, E. Stępień","doi":"10.2478/bioal-2022-0085","DOIUrl":"https://doi.org/10.2478/bioal-2022-0085","url":null,"abstract":"\u0000 Introduction\u0000 Cargo carried by extracellular vesicles (EVs) is considered a promising diagnostic marker, especially proteins. EVs can be divided according to their size and way of biogenesis into exosomes (diameter < 200 nm) and ectosomes (diameter > 200 nm). Exosomes are considered to be of endocytic origin, and ectosomes are produced by budding and shedding from the plasma membrane [1].\u0000 Methods\u0000 The first step of this study was a characterization of the exosome sample. Using Tunable Resistive Pulse Sensing (qNano) size distribution and concentration were measured. The mean size of exosomes was 120±9.17 nm. In the present study, a nano liquid chromatography coupled with tandem mass spectrometry (nanoLCMS/MS) was used to compare protein profiles of exosomes secreted by pancreatic beta cells (1.1B4) grown under normal glucose (NG, 5 mM D-glucose) and high glucose (HG, 25 mM D-glucose) conditions. The EV samples were lysed, and proteins were denatured, digested, and analyzed using a Q-Exactive mass spectrometer coupled with the UltiMate 3000 RSLC nano system. The nanoLC-MS/MS data were searched against the SwissProt Homo sapiens database using MaxQuant software and protein quantitation was done by the MaxLFQ algorithm. Statistical analysis was carried out with Perseus software. Further bioinformatic analysis was performed using the FunRich 3.1.4 software with the UniProt protein database and String [2].\u0000 Results\u0000 As a result of the nanoLC-MS/MS analysis more than 1,000 proteins were identified and quantified in each sample. The average number of identified proteins in exosomes was 1,397. Label-free quantitative analysis showed that exosome composition differed significantly between those isolated under NG and HG conditions. Many pathways were down-regulated in HG, particularly the ubiquitin-proteasome pathway. In addition, a significant up-regulation of the Ras-proteins pathway was observed in HG.\u0000 Conclusion\u0000 Our description of exosomes protein content and its related functions provides the first insight into the EV interactome and its role in glucose intolerance development and diabetic complications. The results also indicate the applicability of EV proteins for further investigation regarding their potential as circulating in vivo biomarkers.","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49267307","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}

{"title":"Comparison of Lugol’s solution and Fe3O4 nanoparticles as contrast agents for tumor spheroid imaging using microcomputed tomography","authors":"D. Panek, M. Szczepanek, B. Leszczyński, P. Moskal, E. Stępień","doi":"10.2478/bioal-2022-0084","DOIUrl":"https://doi.org/10.2478/bioal-2022-0084","url":null,"abstract":"\u0000 Background Lugol’s solution is well known for its unique contrasting properties to biological samples in in microcomputed tomography imaging. On the other hand, iron oxide nanoparticles (IONPs), which have much lower attenuation capabilities to X-ray radiation show decent cell penetration and accumulation properties, are increasingly being used as quantitative contrast agents in biology and medicine. In our research, they were used to stain 3D cell structures called spheroids. Aim In this study, the micro computed tomography (µCT) technique was used to visualize and compare the uptake and accumulation of two contrast agents, Lugol’s solution and iron (II, III ) oxid e nanoparticles (IONPs) in the in vitro human spheroid tumour model. Methods The metastatic human melanoma cell line WM266-4 was cultured, first under standard 2D conditions, and after reaching 90% confluence cells was seeded in a low adhesive plate, which allows spheroid formation. On the 7th day of growth, the spheroids were transferred to the tubes and stained with IONPs or Lugol’s solution and subjected to µCT imaging. Results Our research allows visualization of the regions of absorption at the level of single cells, with relatively short incubation times - 24h - for Lugol’s solution. IONPs proved to be useful only in high concentrations (1 mg/ml) and long incubation times (96h). Conclusions When comparing the reconstructed visualizations of the distribution of these stating agents, it is worth noting that Lugol’s solution spreads evenly throughout the spheroids, whereas IONPs (regardless of their size 5 and 30 nm) accumulate only in the outer layer of the spheroid structure.","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47272543","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}

{"title":"Towards high sensitivity and high-resolution PET scanners: imaging-guided proton therapy and total body imaging","authors":"K. Lang","doi":"10.2478/bioal-2022-0079","DOIUrl":"https://doi.org/10.2478/bioal-2022-0079","url":null,"abstract":"\u0000 Quantitative imaging (i.e., providing not just an image but also the related data) guidance in proton radiation therapy to achieve and monitor the precision of planned radiation energy deposition field in-vivo (a.k.a. proton range verification) is one of the most under-invested aspects of radiation cancer treatment despite that it may dramatically enhance the treatment accuracy and lower the exposure related toxicity improving the entire outcome of cancer therapy. In this article, we briefly describe the effort of the TPPT Consortium (a collaborative effort of groups from the University of Texas and Portugal) on building a time-of-flight positron-emission-tomography (PET) scanner to be used in pre-clinical studies for proton therapy at MD Anderson Proton Center in Houston. We also discuss some related ideas towards improving and expanding the use of PET detectors, including the total body imaging.","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45922434","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}

{"title":"Electrical frequency discrimination by fungi Pleurotus ostreatus","authors":"Dawid Przyczyna, K. Szaciłowski, A. Chiolerio, A. Adamatzky","doi":"10.48550/arXiv.2210.01775","DOIUrl":"https://doi.org/10.48550/arXiv.2210.01775","url":null,"abstract":"We stimulate mycelian networks of oyster fungi Pleurotus ostreatus with low frequency sinusoidal electrical signals. We demonstrate that the fungal networks can discriminate between frequencies in a fuzzy or threshold based manner. Details about the mixing of frequencies by the mycelium networks are provided. The results advance the novel field of fungal electronics and pave ground for the design of living, fully recyclable, electronic devices.","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86809605","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}

{"title":"Bacterial species metabolic interaction network for deciphering the lignocellulolytic system in fungal cultivating termite gut microbiota","authors":"Pritam Kundu, Suman Mondal, Amit Ghosh","doi":"10.2139/ssrn.4043589","DOIUrl":"https://doi.org/10.2139/ssrn.4043589","url":null,"abstract":"Fungus-cultivating termite Odontotermes badius developed a mutualistic association with Termitomyces fungi for the plant material decomposition and providing a food source for the host survival. The mutualistic relationship sifted the microbiome composition of the termite gut and Termitomyces fungal comb. Symbiotic bacterial communities in the O. badius gut and fungal comb have been studied extensively to identify abundant bacteria and their lignocellulose degradation capabilities. Despite several metagenomic studies, the species-wide metabolic interaction pattern of bacterial communities in termite gut and fungal comb remains unclear. The bacterial species metabolic interaction network (BSMIN) has been constructed with 230 bacteria identified from the O. badius gut and fungal comb microbiota. The network portrayed the metabolic map of the entire microbiota and highlighted several inter-species biochemical interactions like cross-feeding, metabolic interdependency, and competition. Further, the reconstruction and analysis of the bacterial influence network (BIN) quantified the positive and negative pairwise influences in the termite gut and fungal comb microbial communities. Several key macromolecule degraders and fermentative microbial entities have been identified by analyzing the BIN. The mechanistic interplay between these influential microbial groups and the crucial glycoside hydrolases (GH) enzymes produced by the macromolecule degraders execute the community-wide functionality of lignocellulose degradation and subsequent fermentation. The metabolic interaction pattern between the nine influential microbial species has been determined by considering them growing in a synthetic microbial community. Competition (30%), parasitism (47%), and mutualism (17%) were predicted to be the major mode of metabolic interaction in this synthetic microbial community. Further, the antagonistic metabolic effect was found to be very high in the metabolic-deprived condition, which may disrupt the community functionality. Thus, metabolic interactions of the crucial bacterial species and their GH enzyme cocktail identified from the O. badius gut and fungal comb microbiota may provide essential knowledge for developing a synthetic microcosm with efficient lignocellulolytic machinery.","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90979492","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}

{"title":"Dive into Machine Learning Algorithms for Influenza Virus Host Prediction with Hemagglutinin Sequences","authors":"Yanhua Xu, D. Wojtczak","doi":"10.48550/arXiv.2207.13842","DOIUrl":"https://doi.org/10.48550/arXiv.2207.13842","url":null,"abstract":"Influenza viruses mutate rapidly and can pose a threat to public health, especially to those in vulnerable groups. Throughout history, influenza A viruses have caused pandemics between different species. It is important to identify the origin of a virus in order to prevent the spread of an outbreak. Recently, there has been increasing interest in using machine learning algorithms to provide fast and accurate predictions for viral sequences. In this study, real testing data sets and a variety of evaluation metrics were used to evaluate machine learning algorithms at different taxonomic levels. As hemagglutinin is the major protein in the immune response, only hemagglutinin sequences were used and represented by position-specific scoring matrix and word embedding. The results suggest that the 5-grams-transformer neural network is the most effective algorithm for predicting viral sequence origins, with approximately 99.54% AUCPR, 98.01% F1 score and 96.60% MCC at a higher classification level, and approximately 94.74% AUCPR, 87.41% F1 score and 80.79% MCC at a lower classification level.","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74357317","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}

{"title":"The Hiatus Between Organism and Machine Evolution: Contrasting Mixed Microbial Communities with Robots","authors":"A. Roli, S. Kauffman","doi":"10.48550/arXiv.2206.14916","DOIUrl":"https://doi.org/10.48550/arXiv.2206.14916","url":null,"abstract":"Mixed microbial communities, usually composed of various bacterial and fungal species, are fundamental in a plethora of environments, from soil to human gut and skin. Their evolution is a paradigmatic example of intertwined dynamics, where not just the relations among species plays a role, but also the opportunities-and possible harms-that each species presents to the others. These opportunities are in fact affordances, which can be seized by heritable variations and selection. In this paper, starting from a systemic viewpoint of mixed microbial communities, we focus on the pivotal role of affordances in evolution and we contrast it to the artificial evolution of programs and robots. We maintain that the two realms are neatly separated, in that natural evolution proceeds by extending the space of its possibilities in a completely open way, while the latter is inherently limited by the algorithmic framework in which it is defined. This discrepancy characterises also an envisioned setting in which robots evolve in the physical world. We present arguments supporting our claim and we propose an experimental setting for assessing our statements. Rather than just discussing the limitations of the artificial evolution of machines, the aim of this contribution is to emphasize the tremendous potential of the evolution of the biosphere, beautifully represented by the evolution of communities of microbes.","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83029371","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}

{"title":"Editorial: 2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2020)","authors":"G. A. Ruz, D. Ashlock, R. Allmendinger, G. Fogel","doi":"10.1016/j.biosystems.2022.104698","DOIUrl":"https://doi.org/10.1016/j.biosystems.2022.104698","url":null,"abstract":"","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76785555","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}