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The application of a biocompatible polymer nanocarrier can provide target delivery to tumor tissues, improved pharmacokinetics, controlled drug release, etc. Therefore, the proposed strategy was to use the water-soluble star-like copolymers with a Dextran core and Poly(N-isopropylacrylamide) grafts (D-g-PNIPAM) for conjugation with the widely used chemotherapy drugs in oncology–Cisplatin (Cis-Pt) and Doxorubicin (Dox). The molecular characteristics of the copolymer were received using size-exclusion chromatography. The physicochemical characterization of the D-g-PNIPAM-Cis-Pt (or Dox) nanosystem was conducted using dynamic light scattering and FTIR spectroscopy. Using traditional biochemical methods, a comparative analysis of the enhancement of the cytotoxic effect of free Cis-Pt and Dox in combination with D-g-PNIPAM copolymers was performed in cancer cells of the Lewis lung carcinoma line, which are both sensitive and resistant to Dox; in addition, the mechanism of their action in vitro was evaluated. [ABSTRACT FROM AUTHOR]

The human microbiome has become an area of intense research due to its potential impact on human health. However, the analysis and interpretation of this data have proven to be challenging due to its complexity and high dimensionality. Machine learning (ML) algorithms can process vast amounts of data to uncover informative patterns and relationships within the data, even with limited prior knowledge. Therefore, there has been a rapid growth in the development of software specifically designed for the analysis and interpretation of microbiome data using ML techniques. These software incorporate a wide range of ML algorithms for clustering, classification, regression, or feature selection, to identify microbial patterns and relationships within the data and generate predictive models. This rapid development with a constant need for new developments and integration of new features require efforts into compile, catalog and classify these tools to create infrastructures and services with easy, transparent, and trustable standards. Here we review the state-of-the-art for ML tools applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities. This scoping review focuses on ML based software and framework resources currently available for the analysis of microbiome data in humans. The aim is to support microbiologists and biomedical scientists to go deeper into specialized resources that integrate ML techniques and facilitate future benchmarking to create standards for the analysis of microbiome data. The software resources are organized based on the type of analysis they were developed for and the ML techniques they implement. A description of each software with examples of usage is provided including comments about pitfalls and lacks in the usage of software based on ML methods in relation to microbiome data that need to be considered by developers and users. This review represents an extensive compilation to date, offering valuable insights and guidance for researchers interested in leveraging ML approaches for microbiome analysis. [ABSTRACT FROM AUTHOR]

Cancer sonodynamic therapy (SDT) is the therapeutic strategy of a high-frequency ultrasound (US) combined with a special sonosensitizer that becomes cytotoxic upon US exposure. The growing number of newly discovered sonosensitizers and custom US in vitro treatment solutions push the SDT field into a need for systemic studies and reproducible in vitro experimental set-ups. In the current research, we aimed to compare two of the most used and suitable SDT in vitro set-ups—"sealed well" and "transducer in well"—in one systematic study. We assessed US pressure, intensity, and temperature distribution in wells under US irradiation. Treatment efficacy was evaluated for both set-ups towards cancer cell lines of different origins, treated with two promising sonosensitizer candidates—carbon nanoparticle C60 fullerene (C60) and herbal alkaloid berberine. C60 was found to exhibit higher sonotoxicity toward cancer cells than berberine. The higher efficacy of sonodynamic treatment with a "transducer in well" set-up than a "sealed well" set-up underlined its promising application for SDT in vitro studies. The "transducer in well" set-up is recommended for in vitro US treatment investigations based on its US-field homogeneity and pronounced cellular effects. Moreover, SDT with C60 and berberine could be exploited as a promising combinative approach for cancer treatment. [ABSTRACT FROM AUTHOR]

The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish "gold standard" protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory 'omics' features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices. [ABSTRACT FROM AUTHOR]

Microbiomic analysis of human gut samples is a beneficial tool to examine the general well-being and various health conditions. The balance of the intestinal flora is important to prevent chronic gut infections and adiposity, as well as pathological alterations connected to various diseases. The evaluation of microbiome data based on next-generation sequencing (NGS) is complex and their interpretation is often challenging and can be ambiguous. Therefore, we developed an innovative approach for the examination and classification of microbiomic data into healthy and diseased by visualizing the data as a radial heatmap in order to apply deep learning (DL) image classification. The differentiation between 674 healthy and 272 type 2 diabetes mellitus (T2D) samples was chosen as a proof of concept. The residual network with 50 layers (ResNet-50) image classification model was trained and optimized, providing discrimination with 96% accuracy. Samples from healthy persons were detected with a specificity of 97% and those from T2D individuals with a sensitivity of 92%. Image classification using DL of NGS microbiome data enables precise discrimination between healthy and diabetic individuals. In the future, this tool could enable classification of different diseases and imbalances of the gut microbiome and their causative genera. [ABSTRACT FROM AUTHOR]

The share of chronic odontogenic rhinosinusitis is 40% among all chronic rhinosinusitis. Using automated information systems for differential diagnosis will improve the efficiency of decision-making by doctors in diagnosing chronic odontogenic rhinosinusitis. Therefore, this study aimed to develop an intelligent decision support system for the differential diagnosis of chronic odontogenic rhinosinusitis based on computer vision methods. A dataset was collected and processed, including 162 MSCT images. A deep learning model for image segmentation was developed. A 23 convolutional layer U-Net network architecture has been used for the segmentation of multi-spiral computed tomography (MSCT) data with odontogenic maxillary sinusitis. The proposed model is implemented in such a way that each pair of repeated 3 × 3 convolutions layers is followed by an Exponential Linear Unit instead of a Rectified Linear Unit as an activation function. The model showed an accuracy of 90.09%. To develop a decision support system, an intelligent chatbot allows the user to conduct an automated patient survey and collect patient examination data from several doctors of various profiles. The intelligent information system proposed in this study made it possible to combine an image processing model with a patient interview and examination data, improving physician decision-making efficiency in the differential diagnosis of Chronic Odontogenic Rhinosinusitis. The proposed solution is the first comprehensive solution in this area. [ABSTRACT FROM AUTHOR]

The acoustic pressure waves of ultrasound (US) not only penetrate biological tissues deeper than light, but they also generate light emission, termed sonoluminescence. This promoted the idea of its use as an alternative energy source for photosensitizer excitation. Pristine C60 fullerene (C60), an excellent photosensitizer, was explored in the frame of cancer sonodynamic therapy (SDT). For that purpose, we analyzed C60 effects on human cervix carcinoma HeLa cells in combination with a low-intensity US treatment. The time-dependent accumulation of C60 in HeLa cells reached its maximum at 24 h (800 ± 66 ng/106 cells). Half of extranuclear C60 is localized within mitochondria. The efficiency of the C60 nanostructure's sonoexcitation with 1 MHz US was tested with cell-based assays. A significant proapoptotic sonotoxic effect of C60 was found for HeLa cells. C60′s ability to induce apoptosis of carcinoma cells after sonoexcitation with US provides a promising novel approach for cancer treatment. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the probiotic strain Lacticaseibacillus (L.) paracasei subsp. paracasei F19 (F19) with the yeast Saccharomyces cerevisiae US-05 (US-05), using Spondias mombin L. ('taperebá' or 'cajá') juice and by-product, in four sour-type beer formulations: control, with bagasse, juice, and juice and bagasse. The viability of F19 was evaluated by pour-plating and PMA-qPCR. Fermentability, in addition to physicochemical and sensory parameters, and aroma and flavor, were evaluated during brewery by using Headspace Solid-Phase Microextraction (HS-SPME) coupled with gas chromatography–mass spectrometry (GC–MS). F19 was successful in fermenting bagasse in a MRS medium (9.28 log CFU/mL in 24 h) but had a low viability in hopped wort, growing better in formulations without bagasse or juice. No difference between formulations was observed regarding sensory acceptability, and the HS-SPME/GC-MS revealed different flavors and aroma compounds. In conclusion, the production of a potential probiotic sour beer with F19 and US-05 is feasible regarding probiotic viability. However, S. mombin, as juice or bagasse, threatened probiotic survival. Different flavors and aroma compounds were detected, whereas no difference between formulations was found regarding sensory acceptability. The moderate alcohol content achieved is important for bacterial survival and for the development of a probiotic beer with health claims. [ABSTRACT FROM AUTHOR]

Flamingos are highly mobile waterbirds that can be found in tropical and subtropical regions worldwide. The large distribution range of flamingos, the inaccessibility of most of their breeding sites and the lack of species-specific molecular markers, such as microsatellites, have hampered population genetics studies of these majestic birds. Here, we developed a library of microsatellite loci primers using high-throughput sequencing technology that could be used for further genetic studies on Phoenicopteriformes. Microsatellite and mitochondrial markers were employed for the genetic characterization of individuals of all flamingo species and their hybrids, and to conduct a population genetics study of the Caribbean flamingo. The phylogeny of Phoenicopteriformes was confirmed with six species grouped in two major clades that diverged approximately 13 Mya. This suggests the existence of two genera of flamingos, not three, as is currently accepted. The analysis of the genetic structure of the Caribbean flamingo shows that all Cuban demes constitute a single population isolated from the Bonairean colony. This supports suggestions of the existence of limited connectivity between northern and southern Caribbean colonies. The small Galápagos colony was confirmed as an isolated population with low genetic diversity; thus, it should be considered as threatened. [ABSTRACT FROM AUTHOR]

Diagnosis of cardiovascular diseases is an urgent task because they are the main cause of death for 32% of the world's population. Particularly relevant are automated diagnostics using machine learning methods in the digitalization of healthcare and introduction of personalized medicine in healthcare institutions, including at the individual level when designing smart houses. Therefore, this study aims to analyze short 10-s electrocardiogram measurements taken from 12 leads. In addition, the task is to classify patients with suspected myocardial infarction using machine learning methods. We have developed four models based on the k-nearest neighbor classifier, radial basis function, decision tree, and random forest to do this. An analysis of time parameters showed that the most significant parameters for diagnosing myocardial infraction are SDNN, BPM, and IBI. An experimental investigation was conducted on the data of the open PTB-XL dataset for patients with suspected myocardial infarction. The results showed that, according to the parameters of the short ECG, it is possible to classify patients with a suspected myocardial infraction as sick and healthy with high accuracy. The optimized Random Forest model showed the best performance with an accuracy of 99.63%, and a root mean absolute error is less than 0.004. The proposed novel approach can be used for patients who do not have other indicators of heart attacks. [ABSTRACT FROM AUTHOR]

The introduction of nucleic acid amplification techniques has revolutionized the field of medical diagnostics in the last decade. The advent of PCR catalyzed the increasing application of DNA, not just for molecular cloning but also for molecular based diagnostics. Since the introduction of PCR, a deeper understanding of molecular mechanisms and enzymes involved in DNA/RNA replication has spurred the development of novel methods devoid of temperature cycling. Isothermal amplification methods have since been introduced utilizing different mechanisms, enzymes, and conditions. The ease with which isothermal amplification methods have allowed nucleic acid amplification to be carried out has had a profound impact on the way molecular diagnostics are being designed after the turn of the millennium. With all the advantages isothermal amplification brings, the issues or complications surrounding each method are heterogeneous making it difficult to identify the best approach for an end-user. This review pays special attention to the various isothermal amplification methods by classifying them based on the mechanistic characteristics which include reaction formats, amplification information, promoter, strand break, and refolding mechanisms. We would also compare the efficiencies and usefulness of each method while highlighting the potential applications and detection methods involved. This review will serve as an overall outlook on the journey and development of isothermal amplification methods as a whole. [ABSTRACT FROM AUTHOR]

Background: Berberine (Ber) is a herbal alkaloid with pharmacological activity in general and a high anticancer potency in particular. However, due to its low bioavailability, the difficulty in reaching a target and choosing the right dose, there is a need to improve approaches of Ber use in anticancer therapy. In this study, Ber, noncovalently bound to a carbon nanostructure C60 fullerene (C60) at various molar ratios of the components, was explored against Lewis lung carcinoma (LLC). Methods: C60–Ber noncovalent nanocomplexes were synthesized in 1:2, 1:1 and 2:1 molar ratios. Ber release from the nanocomplexes was studied after prolonged incubation at different pH with the liquid chromatography–mass spectrometry analysis of free Ber content. Biological effects of the free and C60-complaxated Ber were studied in vitro towards LLC cells with phase-contrast and fluorescence microscopy, flow cytometry, MTT reduction, caspase activity and wound closure assays. The treatment with C60–Ber nanocomplex was evaluated in vivo with the LLC-tumored C57Bl mice. The mice body weight, tumor size, tumor weight and tumor weight index were assessed for four groups, treated with saline, 15 mg C60/kg, 7.5 mg Ber/kg or 2:1 C60-Ber nanocomplex (15 mg C60/kg, 7.5 mg Ber/kg). Results: Ber release from C60–Ber nanocomplexes was promoted with medium acidification. LLC cells treatment with C60–Ber nanocomplexes was followed by enhanced Ber intracellular uptake as compared to free Ber. The cytotoxicity of the studied agents followed the order: free Ber < 1:2 < 1:1 < 2:1 C60–Ber nanocomplex. The potency of cytotoxic effect of 2:1 C60–Ber nanocomplex was confirmed by 21.3-fold decrease of IC50 value (0.8 ± 0.3 µM) compared to IC50 for free Ber (17 ± 2 µM). C60–Ber nanocomplexes induced caspase 3/7 activation and suppressed the migration activity of LLC cells. The therapeutic potency of 2:1 C60–Ber nanocomplex was confirmed in a mouse model of LLC. The tumor growth in the group treated with 2:1 C60–Ber nanocomplex is suppressed by approximately 50% at the end of experiment, while in the tumor-bearing group treated with free Ber no therapeutic effect was detected. Conclusions: This study indicates that complexation of natural alkaloid Ber with C60 may be a novel therapeutic strategy against lung carcinoma. [ABSTRACT FROM AUTHOR]

Background: Visceral leishmaniasis (VL) is re-emerging in Armenia since 1999 with 167 cases recorded until 2019. The objectives of this study were (i) to determine for the first time the genetic diversity and population structure of the causative agent of VL in Armenia; (ii) to compare these genotypes with those from most endemic regions worldwide; (iii) to monitor the diversity of vectors in Armenia; (iv) to predict the distribution of the vectors and VL in time and space by ecological niche modeling. Methodology/Principal findings: Human samples from different parts of Armenia previously identified by ITS-1-RFLP as L. infantum were studied by Multilocus Microsatellite Typing (MLMT). These data were combined with previously typed L. infantum strains from the main global endemic regions for population structure analysis. Within the 23 Armenian L. infantum strains 22 different genotypes were identified. The combined analysis revealed that all strains belong to the worldwide predominating MON1-population, however most closely related to a subpopulation from Southeastern Europe, Maghreb, Middle East and Central Asia. The three observed Armenian clusters grouped within this subpopulation with strains from Greece/Turkey, and from Central Asia, respectively. Ecological niche modeling based on VL cases and collected proven vectors (P. balcanicus, P. kandelakii) identified Yerevan and districts Lori, Tavush, Syunik, Armavir, Ararat bordering Georgia, Turkey, Iran and Azerbaijan as most suitable for the vectors and with the highest risk for VL transmission. Due to climate change the suitable habitat for VL transmission will expand in future all over Armenia. Conclusions: Genetic diversity and population structure of the causative agent of VL in Armenia were addressed for the first time. Further genotyping studies should be performed with samples from infected humans, animals and sand flies from all active foci including the neighboring countries to understand transmission cycles, re-emergence, spread, and epidemiology of VL in Armenia and the entire Transcaucasus enabling epidemiological monitoring. Author summary: Leishmaniasis is a vector-borne disease caused by protozoan parasites of the genus Leishmania. In Armenia visceral leishmaniasis (VL) is re-emerging since 1999 after a long break of 30 years, with 167 cases recorded until 2019. Molecular diagnosis of VL was implemented only in 2016, and the causative agent was identified as L. infantum. In the present study we expanded the investigation of the causative agent to a characterization at strain level and the identification of its phylogenetic position among the L. infantum genotypes circulating worldwide. This is the first study addressing genetic diversity and population structure of L. infantum in Armenia and in Transcaucasia. Armenia is an extremely interesting region due to its bio-geographic specificities e.g. the high number of different climates in this small mountainous country and the observed high diversity of sand fly species, part of which occurring in very high altitudes. Ecological niche modeling based on registered VL cases and sand fly vectors collected in active VL foci revealed that the risk of further spread of VL is very high due to climate change. Studies of this region should be expanded to enable targeted control measures. [ABSTRACT FROM AUTHOR]

Abstract Background Currently established methods to identify viable and non-viable cells of cyanobacteria are either time-consuming (eg. plating) or preparation-intensive (eg. fluorescent staining). In this paper we present a new and fast viability assay for unicellular cyanobacteria, which uses red chlorophyll fluorescence and an unspecific green autofluorescence for the differentiation of viable and non-viable cells without the need of sample preparation. Results The viability assay for unicellular cyanobacteria using red and green autofluorescence was established and validated for the model organism Synechocystis sp. PCC 6803. Both autofluorescence signals could be observed simultaneously allowing a direct classification of viable and non-viable cells. The results were confirmed by plating/colony count, absorption spectra and chlorophyll measurements. The use of an automated fluorescence microscope and a novel ImageJ based image analysis plugin allow a semi-automated analysis. Conclusions The new method simplifies the process of viability analysis and allows a quick and accurate analysis. Furthermore results indicate that a combination of the new assay with absorption spectra or chlorophyll concentration measurements allows the estimation of the vitality of cells.

Abstract Background The phenomenon of desiccation tolerance, also called anhydrobiosis, involves the ability of an organism to survive the loss of almost all cellular water without sustaining irreversible damage. Although there are several physiological, morphological and ecological studies on tardigrades, only limited DNA sequence information is available. Therefore, we explored the transcriptome in the active and anhydrobiotic state of the tardigrade Milnesium tardigradum which has extraordinary tolerance to desiccation and freezing. In this study, we present the first overview of the transcriptome of M. tardigradum and its response to desiccation and discuss potential parallels to stress responses in other organisms. Results We sequenced a total of 9984 expressed sequence tags (ESTs) from two cDNA libraries from the eutardigrade M. tardigradum in its active and inactive, anhydrobiotic (tun) stage. Assembly of these ESTs resulted in 3283 putative unique transcripts, whereof ~50% showed significant sequence similarity to known genes. The resulting unigenes were functionally annotated using the Gene Ontology (GO) vocabulary. A GO term enrichment analysis revealed several GOs that were significantly underrepresented in the inactive stage. Furthermore we compared the putative unigenes of M. tardigradum with ESTs from two other eutardigrade species that are available from public sequence databases, namely Richtersius coronifer and Hypsibius dujardini. The processed sequences of the three tardigrade species revealed similar functional content and the M. tardigradum dataset contained additional sequences from tardigrades not present in the other two. Conclusions This study describes novel sequence data from the tardigrade M. tardigradum, which significantly contributes to the available tardigrade sequence data and will help to establish this extraordinary tardigrade as a model for studying anhydrobiosis. Functional comparison of active and anhydrobiotic tardigrades revealed a differential distribution of Gene Ontology terms associated with chromatin structure and the translation machinery, which are underrepresented in the inactive animals. These findings imply a widespread metabolic response of the animals on dehydration. The collective tardigrade transcriptome data will serve as a reference for further studies and support the identification and characterization of genes involved in the anhydrobiotic response.

Abstract Background Tardigrades represent an animal phylum with extraordinary resistance to environmental stress. Results To gain insights into their stress-specific adaptation potential, major clusters of related and similar proteins are identified, as well as specific functional clusters delineated comparing all tardigrades and individual species (Milnesium tardigradum, Hypsibius dujardini, Echiniscus testudo, Tulinus stephaniae, Richtersius coronifer) and functional elements in tardigrade mRNAs are analysed. We find that 39.3% of the total sequences clustered in 58 clusters of more than 20 proteins. Among these are ten tardigrade specific as well as a number of stress-specific protein clusters. Tardigrade-specific functional adaptations include strong protein, DNA- and redox protection, maintenance and protein recycling. Specific regulatory elements regulate tardigrade mRNA stability such as lox P DICE elements whereas 14 other RNA elements of higher eukaryotes are not found. Further features of tardigrade specific adaption are rapidly identified by sequence and/or pattern search on the web-tool tardigrade analyzer http://waterbear.bioapps.biozentrum.uni-wuerzburg.de. The work-bench offers nucleotide pattern analysis for promotor and regulatory element detection (tardigrade specific; nrdb) as well as rapid COG search for function assignments including species-specific repositories of all analysed data. Conclusion Different protein clusters and regulatory elements implicated in tardigrade stress adaptations are analysed including unpublished tardigrade sequences.

Abstract Background Up to now, microarray data are mostly assessed in context with only one or few parameters characterizing the experimental conditions under study. More explicit experiment annotations, however, are highly useful for interpreting microarray data, when available in a statistically accessible format. Results We provide means to preprocess these additional data, and to extract relevant traits corresponding to the transcription patterns under study. We found correspondence analysis particularly well-suited for mapping such extracted traits. It visualizes associations both among and between the traits, the hereby annotated experiments, and the genes, revealing how they are all interrelated. Here, we apply our methods to the systematic interpretation of radioactive (single channel) and two-channel data, stemming from model organisms such as yeast and drosophila up to complex human cancer samples. Inclusion of technical parameters allows for identification of artifacts and flaws in experimental design. Conclusion Biological and clinical traits can act as landmarks in transcription space, systematically mapping the variance of large datasets from the predominant changes down toward intricate details.