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The aim was to implement uncertainty calculation for detecting the negative effects of smoking on the bone density of the paranasal sinus. Materials and Methods: A total of 100 male participants aged 20 to 44 were included in the study and divided into two groups. The first group comprised individuals with minimal harmful habits, while the second group consisted of individuals who had been smoking for at least 10 years, consuming 1 to 2 packs of cigarettes per day. Results Bone density has a negative impact on the bone tissue of the upper wall of the maxillary sinus. The findings suggest that individuals with a pronounced decrease in minimum density, as well as those with a marked difference between minimum and maximum density values, may require heightened medical attention due to potential associations with undiagnosed diseases or specific structural characteristics in the skull. Conclusions. The uncertainty calculation was implemented for the detection of negative effect of smoking on the bone density of paranasal sinuses. The calculated difference between maximum and minimum density during the research suggests significant medical implications, especially considering the heterogeneity of the trabecular bone structure in the skull. Individuals with a marked difference may require heightened medical attention, potentially associated with undiagnosed diseases or specific structural characteristics in the skull.
Evaluation of medical images is of key importance in the work of medical staff today. Especially this problem pays important role in otolaryngology.
The aim of our work was to develop an automatic complex method for assessing the state of the human paranasal sinuses.
Our research included 10 people of different sex and age, who were divided into groups, taking into account the recommendations of the WHO for 2019-2021. The structure of the mucous membrane of the maxillary sinus were calculated and compared.
In the course of our research, an algorithm was developed for the automatic assessment of the state of the mucous membrane of the maxillary sinus and its bone walls according to the data of the spiral computed tomography. The difference between obtained data in the manual and automatic mode is minimal.
Solutions to the 3D Model Problem of Pressure Measurement in the Area of Maxillary Sinus Anastomosis
(2020)
The ostiomeatal complex (OMC) is a key area that determines the occurrence of inflammatory processes in the paranasal sinuses (PNSs). The aim of our work was to develop a procedure for studying the OMC components in the preoperative period that allows for identification the impact of anatomical peculiarities on change of physiological pressure in the maxillary sinus. Materials and methods: The study was carried out on the basis of the otorhinolaryngological department of Kharkiv Regional Clinical Hospital in 2019-2020. It involved 100 patients of both sexes aged 20-59 years with chronic non-polyposis maxillary sinusitis. Results: The sizes of the uncinate process, the middle turbinate and the natural anastomosis were determined using the calculation of uncertainty. Basing on the data obtained, all the patients were divided into three groups. Conclusions: Changes in the size of the natural anastomosis (both an increase and its narrowing) lead to changes in pressure in the area of the anastomosis, and a decrease in ventilation in the paranasal sinuses. SCT study with subsequent 3D modeling is an informative, accurate and effective method for assessment of OMC and PNSs condition. It allows surgeons to presume the method and volume of surgery as early as at the preoperative stage, without resorting to invasive research methods.
Processing biological materials with 3-dimensional (3D) printers has attracted increasing interest in several research areas. At the same time, off-the-shelf solutions are increasingly available in a wider variety to meet the current market demand. However, most of the available bioprinters are closed source, thus, modifications are quite challenging or require an avoidable consultation process with the manufacturer. Furthermore, the entry prices for basic machines amount to several thousands of euros. Whereas, high-end 3D bio printers with a vast array of features are available for several hundred thousand euros. Due to the immense potential of this tool in the field of biotechnology it is important to extend the availability of this technology for research purposes in terms of adaptability and price. This ongoing work focuses on open-source 3D printer heads with the ability to extrude biological materials. The print heads include several techniques to process low as well as high viscose biomaterials such as agar and gelatin. Additionally, obstacles such as continuous substrate tempering or integration into existing 3D printers are addressed. The work presented is open source and thus freely adaptable to any user’s specific needs. Our goal is to process a diverse range of biomaterials with different print techniques.
The sample preparation for biological and chemical probes involves following a strict workflow to eliminate any contamination to the sample beforehand. Furthermore, it is time consuming and must be carried out by trained personnel such as a nurse or other supervisors, making it therefore expensive. The development of novel sample preparation techniques paired with modern sample analysis systems is focused on improving the operability while keeping a constant quality of results. This is important to analyse samples, which cannot be determined with current screening conditions. The analysis of analytes is required to receive a more detailed picture of the patient and to fully understand its complexity. Possible samples for in-depth analysis of chemical origin can be cholesterol or glucose. More complex samples, such as blood or saliva, require a sophisticated system, which analyses the samples for their individual compounds.
The aim of our study was to investigate the impact of insulin resistance on the bone density of the upper wall of the maxillary sinus. Materials and Methods: The study included 100 female participants aged 18 to 44 years, divided into two groups. The first group consisted of individuals with insulin resistance, while the control group comprised individuals without signs of insulin resistance. In each group, we conducted an investigation of the radiological density of the upper wall of the maxillary sinus using uncertainty calculations. Results of the study suggest a potential influence of insulin resistance on the density of bone tissue around the nasal sinuses, specifically the upper wall of the maxillary sinus in our case. This parameter was found to be minimal in the group of individuals with insulin resistance. It is particularly noteworthy that both minimum and maximum bone density decreased in this group. Conclusions. The research focused on how insulin resistance affects the density of the upper wall of the maxillary sinus. By employing uncertainty calculations, the study revealed that insulin resistance is associated with a decrease in the minimum density of the upper wall of the maxillary sinus. This tendency may act as a catalyst for the emergence of significant inflammatory alterations in the nasal sinuses, serving as a foundation for the initiation of complications.
Hintergrund: Etablierte Protein- und Nukleinsäure-basierte Methoden für den spezifischen Pathogennachweis sind nur unter standardisierten Laborbedingungen von geschultem Personal durchführbar und daher mit einem hohen Zeit- und Kostenaufwand verbunden. In der Nukleinsäure-basierten Diagnostik kann durch die Einführung der isothermalen Amplifikation eine schnelle und kostengünstige Alternative zur Polymerase-Kettenreaktion (PCR) verwendet werden. Die Loop-mediated isothermal amplification (LAMP) bietet aufgrund der hohen Amplifikationseffizienz vielfältige Detektionsmöglichkeiten, die sowohl für Schnelltest- als auch für Monitoring-Anwendungen geeignet sind.
Ein wesentliches Ziel dieser Arbeit war die Verbesserung der Anwendbarkeit der LAMP und die Entwicklung einer neuen Methode für den einfachen, schnellen und günstigen Nachweis von Pathogenen mittels alternativer DNA- oder Pyrophosphat-abhängiger Detektionsverfahren. Hier wurden zunächst direkte und indirekte Detektionsmethoden untersucht und darauf aufbauend ein Verfahren entwickelt, mit dem neue Metallionen-abhängige Fluoreszenzfarbstoffe für die selektive Detektion von Pyrophosphat in der LAMP und anderen enzymatischen Reaktionen identifiziert werden können. Als Alternative für die DNA-basierte Detektion in der digitalen LAMP sollten die zuvor etablierten Farbstoffe für den Pyrophosphatnachweis in einer Emulsion getestet werden. Abschließend wurde ein neuer Reaktionsmechanismus für die effiziente Generierung hochmolekularer DNA unter isothermalen Bedingungen als Alternative zur LAMP entwickelt.
Ergebnisse: Für den Nachweis RNA- und DNA-basierter Phythopathogene konnte die Echtzeit- und Endpunktdetektion mit verschiedenen Farbstoffen in einem geschlossenen System etabliert werden. Hier wurde Berberin als DNA-interkalierender Fluoreszenzfarbstoff mit vergleichbarer Sensitivität zu SYBR Green und EvaGreen erfolgreich in der LAMP mit Echtzeitdetektion eingesetzt. Ein Vorteil von Berberin gegenüber den anderen Farbstoffen ist die Toleranz der DNA-Polymerase auch bei hohen Farbstoffkonzentrationen. Berberin kann daher auch in der geschlossenen LAMP-Reaktion ohne zusätzliche Anpassung der Reaktionsbedingungen für die Endpunktdetektion verwendet werden. Darüber hinaus konnte Hydroxynaphtholblau (HNB), das für den kolorimetrischen Endpunktnachweis bekannt ist, erstmals auch für die fluorimetrische Detektion der LAMP in Echtzeit eingesetzt werden. Zusätzlich konnten in der Arbeit weitere Metallionen-abhängige Farbstoffe zur indirekten Detektion der LAMP über das Pyrophosphat identifiziert werden. Dafür wurde eine iterative Methode entwickelt, mit der potenzielle Farbstoffe hinsichtlich ihrer Enzymkompatibilität und ihrer spektralen Eigenschaften bei An- oder Abwesenheit von Manganionen selektiert werden können. Mithilfe eines kombinatorischen Screenings im Mikrotiterplattenformat konnte die komplexe Konzentrationsabhängigkeit zwischen den einzelnen Komponenten für einen fluorimetrischen Verdrängungsnachweis untersucht werden. Durch die Visualisierung des Signal-Rausch-Verhältnis’ als Intensitätsmatrix (heatmap) konnten zunächst Alizarinrot S und Tetrazyklin unter simulierten Reaktionsbedingungen selektiert werden. In der anschließenden enzymatischen LAMP-Reaktion konnte insbesondere Alizarinrot S als günstiger, nicht-toxischer und robuster Fluoreszenzfarbstoff identifiziert werden und zeigte eine Pyrophosphat-abhängige Zunahme der Fluoreszenzintensität. Die zuvor etablierten Farbstoffe (HNB, Calcein und Alizarinrot S) konnten anschließend erfolgreich für die indirekte, fluorimetrische Detektion von Pyrophosphat in einer LAMP-optimierten Emulsion eingesetzt werden. Die Stabilität und Homogenität der generierten Emulsion wurde durch den Zusatz des Emulgators Poloxamer 188 verbessert. Durch die fluoreszenzmikroskopische Analyse der Emulsion war eine eindeutige Diskriminierung der positiven und negativen Tröpfchen vor allem bei Einsatz von Calcein und Alizarinrot S möglich. Aufgrund des komplexen Primer-Designs und der hohen Wahrscheinlichkeit unspezifischer Amplifikation in der LAMP wurde eine neue Bst DNA-Polymerase-abhängige isothermale Amplifikationsreaktion entwickelt. Durch die Integration einer spezifischen Linkerstruktur (abasische Stelle oder Hexaethylenglykol) zwischen zwei Primersequenzen konnte ein bifunktioneller Primer die effiziente Regenerierung der Primerbindungsstellen gewährleisten. Der neue Primer induziert nach der spezifischen Hybridisierung auf dem Templat die Rückfaltung zu einer Haarnadelstruktur und blockiert gleichzeitig die Polymeraseaktivität am Gegenstrang, wodurch eine autozyklische Amplifikation trotz konstanter Reaktionstemperatur möglich ist. Die Effizienz der „Hinge-initiated Primer dependent Amplification“ (HIP) konnte abschließend durch die Verkürzung der Distanz zwischen einem modifizierten Hinge-Primer und einem PCR-ähnlichen Primer verbessert werden.
Schlussfolgerung: Die LAMP hat sich aufgrund der hohen Robustheit und Effizienz zu einer leistungsfähigen Alternative für die klassische PCR in der molekularbiologischen Diagnostik entwickelt. Unterschiedliche Detektionsverfahren verbessern die Leistungsfähigkeit der qualitativen und quantitativen LAMP für die Feldanwendungen und für die Diagnostik, da die neuen DNA- und Pyrophosphat-abhängigen Nachweismethoden in einer geschlossenen Reaktion eingesetzt werden können und so eine einfache Pathogendiagnostik ermöglichen. Die gezeigten Methoden können darüber hinaus zu einer Kostensenkung und Zeitersparnis gegenüber den herkömmlichen Methoden beitragen. Ein attraktives Ziel stellt die Weiterentwicklung der HIP für den Pathogennachweis als Alternative zur LAMP dar. Hierbei können die neuen LAMP-Detektionsverfahren ebenfalls Anwendung finden. Die Verwendung von Bst DNA-Polymerase-abhängigen Reaktionen ermöglicht darüber hinaus die Integration einer robusten isothermalen Amplifikation in mikrofluidische Systeme. Durch die Kombination der Probenvorbereitung, Amplifikation und Detektion sind zukünftige Anwendungen mit kurzer Analysezeit und geringem apparativen Aufwand insbesondere in der Pathogendiagnostik möglich.
Ziel dieser Arbeit war die Erhöhung der Temperaturtoleranz des Cyanobakteriums Synechocystis sp. PCC 6803 mittels ungerichteter Mutagenese und adaptiver Evolution. Trotz des erneuten Interesses an Cyanobakterien und Mikroalgen in den letzten Jahren, gibt es nur relativ wenige aktuelle Studien zum Einsatz dieser Methoden an Cyanobakterien. Zur Analyse eines mittels Mutagenese erzeugten Gemischs an Stämmen, ist es von großem Vorteil Hochdurchsatz-Methoden zur Kultivierung und zum Screening einsetzen zu können. Auf Basis eines Pipettierroboters wurde solch eine Plattform für phototrophe Mikroorganismen neu entwickelt und folgend stetig verbessert. Die Kultivierung erfolgt in 2,2ml Deepwell-Mikrotiterplatten innerhalb einer speziell angefertigten Kultivierungskammer. Schüttelbedingungen, Beleuchtung, Temperatur und CO2-Atmosphäre sind hierbei vollständig einstellbar.Die Plattform erlaubt semi-kontinuierliche Kultivierungen mit automatisierten Verdünnungen von hunderten Kulturen gleichzeitig. Automatisierte Messungen des Wachstums, des Absorptionsspektrums, der Chlorophyllkonzentration, MALDI-TOF-MS sowie eines neu entwickelten Vitalitätsassays wurden etabliert. Für die Mutagenese wurden die Letalität- und die nicht-letale Punktmutationsrate von ultravioletter Strahlung und Methylmethansulfonat für Synechocystis charakterisiert. Synechocystis wurde mit den so ermittelten optimalen Dosen mehrfach behandelt und anschließend einer in vivo Selektion unterzogen. Somit wurde dessen Temperaturtoleranz um bis zu 3°C erhöht. Über die Screeningplattform wurden die thermotolerantesten monoklonalen Stämme identifiziert. Nach einer Validierung wurde das vollständige Genom der Stämme sequenziert. Hierdurch wurden erstmals Mutationen in verschiedenen Genen mit der Langzeittemperaturtoleranz von Synechocystis in Verbindung gebracht. Bei einigen dieser Gene ist es sehr unwahrscheinlich, dass sie mittels anderer Verfahren hätten identifiziert werden können.
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.
Patients with congenital heart defects and cardiovascular diseases are required new approaches to surgical intervention. The use of biological cardiac implants, which are made from the extracellular matrix, is a promising trend in modern regenerative medicine. These bioimplants can completely replace defective tissue or organs, and when manufactured with strict protocols and quality control measures, can be safe and effective for therapeutic applications. The process of manufacturing bioimplants involves various risks that need to be assessed and mitigated with ongoing monitoring and evaluation necessary to ensure the highest standards of quality. Overall, this study was successfully evaluated the requirements for introducing a new medical device into practice and created a technical file that meets all necessary documentation for certification.
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.
Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action
(2023)
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.
Background
Diabetes mellitus type 2 is a common disease that poses a challenge to the healthcare system. The disease is very often diagnosed late. A better understanding of the relationship between the gut microbiome and type 2 diabetes can support early detection and form an approach for therapies. Microbiome analysis offers a potential opportunity to find markers for this disease. Next-generation sequencing methods can be used to identify the bacteria present in the stool sample and to generate a microbiome profile through an analysis pipeline. Statistical analysis, e.g., using Student’s t-test, allows the identification of significant differences. The investigations are not only focused on single bacteria, but on the determination of a comprehensive profile. Also, the consideration of the functional microbiome is included in the analyses. The dataset is not from a clinical survey, but very extensive.
Results
By examining 946 microbiome profiles of diabetes mellitus type 2 sufferers (272) and healthy control persons (674), a large number of significant genera (25) are revealed. It is possible to identify a large profile for type 2 diabetes disease. Furthermore, it is shown that the diversity of bacteria per taxonomic level in the group of persons with diabetes mellitus type 2 is significantly reduced compared to a healthy control group. In addition, six pathways are determined to be significant for type 2 diabetes describing the fermentation to butyrate. These parameters tend to have high potential for disease detection.
Conclusions
With this investigation of the gut microbiome of persons with diabetes type 2 disease, we present significant bacteria and pathways characteristic of this disease.
The identification of biomarkers is crucial for cancer diagnosis, understanding the underlying biological mechanisms, and developing targeted therapies. In this study, we propose a machine learning approach to predict ovarian cancer patients’ outcomes and platinum resistance status using publicly available gene expression data. Six classical machine-learning algorithms are compared on their predictive performance. Those with the highest score are analyzed by their feature importance using the SHAP algorithm. We were able to select multiple genes that correlated with the outcome and platinum resistance status of the patients and validated those using Kaplan–Meier plots. In comparison to similar approaches, the performance of the models was higher, and different genes using feature importance analysis were identified. The most promising identified genes that could be used as biomarkers are TMEFF2, ACSM3, SLC4A1, and ALDH4A1.
Background
Type 2 diabetes mellitus is a prevalent disease that contributes to the development of various health issues, including kidney failure and strokes. As a result, it poses a significant challenge to the worldwide healthcare system. Research into the gut microbiome has enabled the identification and description of various diseases, with bacterial pathways playing a critical role in this context. These pathways link individual bacteria based on their biological functions. This study deals with the classification of microbiome pathway profiles of type 2 diabetes mellitus patients.
Methods
Pathway profiles were determined by next-generation sequencing of 16S rDNA from stool samples, which were subsequently assigned to bacteria. Then, the involved pathways were assigned by the identified gene families. The classification of type 2 diabetes mellitus is enabled by a constructed neural network. Furthermore, a feature importance analysis was performed via a game theoretic approach (SHapley Additive exPlanations). The study not only focuses on the classification using neural networks, but also on identifying crucial bacterial pathways.
Results
It could be shown that a neural network classification of type 2 diabetes mellitus and a healthy comparison group is possible with an excellent prediction accuracy. It was possible to create a ranking to identify the pathways that have a high impact on the model prediction accuracy. In this way, new associations between the alteration of, e.g. a biosynthetic pathway and the presence of diabetes mellitus type 2 disease can also be discovered. The basis is formed by 946 microbiome pathway profiles from diabetes mellitus type 2 patients (272) and healthy comparison persons (674).
Conclusion
With this study of the gut microbiome, we present an approach using a neural network to obtain a classification of healthy and type 2 diabetes mellitus and to identify the critical features. Intestinal bacteria pathway profiles form the basis.
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.
The use of explosives has led to a widespread distribution of 2,4,6-trinitrotoluene (TNT) and its by- and degradation products in the soil on former production and testing sites. The investigation of those large contaminated sites is so far based on a few selected soil samples, due to high costs of conventional HPLC and GC analysis, although huge differences in concentrations can already be found in small areas and different collection depths. We introduce a novel high-throughput screening system for those areas, which combines a smartphone-based collection of GPS data and soil characteristics with a fast MALDI-TOF MS quantification of explosives in soil sample extracts and finally a heatmap visualization of the explosives’ spread in soil and an analysis of correlation between concentrations and soil characteristics. The analysis of a 400 m2 area presented an extensive contamination with TNT and lower concentrations of the degradation and by-products aminodinitrotoluenes (ADNT) and dinitrotoluenes (DNT) next to a former production facility for TNT. The contamination decreased in deeper soil levels and depended on the soil type. Pure humus samples showed significantly lower contaminations compared to sand and humus/sand mixtures, which is likely to be caused by an increased binding potential of the humic material. No correlation was found between the vegetation and the concentration of explosives. Since the results were obtained and visualized within several hours, the MALDI-TOF MS based comprehensive screening and heatmap analysis might be valuable for a fast and high-throughput characterization of contaminated areas.
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.
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.
The development of precision cancer medicine relies on novel formulation strategies for targeted drug delivery to increase the therapeutic outcome. Biocompatible polymer nanoparticles, namely dextran-graft-polyacrylamide (D-g-PAA) copolymers, represent one of the innovative non-invasive approaches for drug delivery applications in cancer therapy. In this study, the star-like D-g-PAA copolymer in anionic form (D-g-PAAan) was developed for pH-triggered targeted drug delivery of the common chemotherapeutic drugs – doxorubicin (Dox) and cisplatin (Cis). The initial D-g-PAA copolymer was synthesized by the radical graft polymerization method, and then alkaline-hydrolyzed to get this polymer in anionic form for further use for drug encapsulation. The acidification of the buffer promoted the release of loaded drugs. D-g-PAAan nanoparticles increased the toxic potential of the drugs against human and mouse lung carcinoma cells (A549 and LLC), but not against normal human lung cells (HEL299). The drug-loaded D-g-PAAan-nanoparticles promoted further oxidative stress and apoptosis induction in LLC cells. D-g-PAAan-nanoparticles improved Dox accumulation and drugs’ toxicity in a 3D LLC multi-cellular spheroid model. The data obtained indicate that the strategy of chemotherapeutic drug encapsulation within the branched D-g-PAAan nanoparticle allows not only to realize pH-triggered drug release but also to potentiate its cytotoxic, prooxidant and proapoptotic effects against lung carcinoma cells.
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.
Background
Cutaneous leishmaniasis (CL) is a vector-borne parasitic diseases of public health importance that is prevalent in the West Bank but not in the Gaza Strip. The disease caused by parasitic protozoans from the genus Leishmania and it is transmitted by infected phlebotomine sand flies. The aim of our study is to investigate the eco-epidemiological parameters and spatiotemporal projections of CL in Palestine over a 30-years period from 1990 through 2020 and to explore future projections until 2060.
Methodology/Principal findings
This long-term descriptive epidemiological study includes investigation of demographic characteristics of reported patients by the Palestinian Ministry of Health (PMoH). Moreover, we explored spatiotemporal distribution of CL including future projection based on climate change scenarios. The number of CL patients reported during this period was 5855 cases, and the average annual incidence rate (AAIR) was 18.5 cases/105 population. The male to female ratio was 1.25:1. Patients-age ranged from 2 months to 89 years (mean = 22.5, std 18.67, and the median was 18 years). More than 65% of the cases came from three governates in the West Bank; Jenin 29% (1617 cases), Jericho 25% (1403), and Tubas 12% (658) with no cases reported in the Gaza Strip. Seasonal occurrence of CL starts to increase in December and peaked during March and April of the following year. Current distribution of CL indicate that Jericho, Tubas, Jenin and Nablus have the most suitable climatic settings for the sandfly vectors. Future projections until 2060 suggest an increasing incidence from northwest of Jenin down to the southwest of Ramallah, disappearance of the foci in Jericho and Tubas throughout the Jordan Vally, and possible emergence of new foci in Gaza Strip.
Conclusions/Significance
The future projection of CL in Palestine until 2060 show a tendency of increasing incidence in the north western parts of the West Bank, disappearance from Jericho and Tubas throughout the Jordan Vally, and emergence of new CL endemic foci in the Gaza Strip. These results should be considered to implement effective control and surveillance systems to counteract spatial expansion of CL vectors.
The isoquinoline quaternary alkaloid Berberine possesses a variety of pharmacological properties that suggests its promising application for an anticancer delivery system design utilizing its ability to intercalate DNA. In the current work, we have investigated the effects of Berberine on the human T cell leukemia cell line in vitro. Fluorescent microscopy of leukemic cells revealed Berberine nuclear localization. The results showed that Berberine inhibited leukemic cell growth in a time- and dose-dependent manner, that was associated with reactive oxygen species production intensification and caspase 3/7 activity increase with followed apoptosis induction. Berberine was used as a toxic and phototoxic agent for triple system synthesis along with DNA as a carrier and nanosilver as a plasmonic accelerator of Berberine electronic transitions and high energy emission absorbent centers. The proposed method allows to obtain the complex of DNA with Berberine molecules and silver nanoparticles. The optical properties of free components as well as their various combinations, including the final triple system DNA-Nanosilver-Berberine, were investigated. Obtained results support the possibility to use the triple system DNA-Nanosilver-Berberine as an alternative therapeutic agent for cancer treatment.
Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.
Microscopic examination of human blood samples is an excellent opportunity to assess general health status and diagnose diseases. Conventional blood tests are performed in medical laboratories by specialized professionals and are time and labor intensive. The development of a point-of-care system based on a mobile microscope and powerful algorithms would be beneficial for providing care directly at the patient's bedside. For this purpose human blood samples were visualized using a low-cost mobile microscope, an ocular camera and a smartphone. Training and optimisation of different deep learning methods for instance segmentation are used to detect and count the different blood cells. The accuracy of the results is assessed using quantitative and qualitative evaluation standards.
In this work, the fabrication and characterization of a simple, inexpensive, and effective microfluidic paper analytic device (µPAD) for monitoring DNA samples is reported. The glass microfiber-based chip has been fabricated by a new wax-based transfer-printing technique and an electrode printing process. It is capable of moving DNA effectively in a time-dependent fashion. The nucleic acid sample is not damaged by this process and is accumulated in front of the anode, but not directly on the electrode. Thus, further DNA processing is feasible. The system allows the DNA to be purified by separating it from other components in sample mixtures such as proteins. Furthermore, it is demonstrated that DNA can be moved through several layers of the glass fiber material. This proof of concept will provide the basis for the development of rapid test systems, e.g., for the detection of pathogens in water samples.
Besides invasive mosquito species also several native species are proven or suspected vectors of arboviruses as West Nile or Usutu virus in Western Europe. Habitat models of these native vectors can be a helpful tool for assessing the risk of autochthonous occurrence, outbreaks and spread of diseases caused by such arboviruses. Modelling native mosquitoes is complicated because of the perfect adaptation to the climatic and landscape conditions and their high abundance in contrast to invasive species. Here we present a new approach for such a habitat model for native mosquito species in Germany, which are considered as vectors of West Nile virus (WNV). Epizootic emergence of WNV was registered in Germany since 2018. The models are based on surveillance data of mosquitoes from the German citizen science project “Mückenatlas” complemented by data from systematic trap monitoring in Germany, and on data freely available from the Deutscher Wetterdienst (DWD) and OpenStreetMap (OSM). While climatic factors still play an important role, we could show that habitat suitability is predictable only by the combination of the climate model with a regional model. Both models were based on a machine-learning approach using XGBoost. Evaluation of the accuracy of the models was done by statistical analysis, determining among others feature importances using the SHAP-Library. Final output of the combined climatic and regional models are maps showing the superposed habitat suitability which are generated through a number of steps described in detail. These maps also include the registered cases of WNV infections in the selected region of Germany.
Nile tilapia (Oreochromis niloticus) is a species of worldwide importance for aquaculture. A crossbred lineage was developed through introgressive backcross breeding techniques and combines the high growth performance of the Chitralada (CHIT) lwith attractive reddish color of the Red Stirling (REDS) strains. Since the crossbreed has an unknown genetically improved background, the objective of this work was to characterize expression signatures that portray the advantageous phenotype of the crossbreeds. We characterized the microRNA transcriptome by high throughput sequencing (RNA-seq) and the proteome through mass spectrometry (ESI-Q-TOF-MS) and applied bioinformatics for the comparative analysis of such molecular data on the three strains. Crossbreed expressed a distinct set of miRNAs and proteins compared to the parents. They comprised several microRNAs regulate traits of economic interest. Proteomic profiles revealed differences between parental and crossbreed in expression of proteins associated with glycolisis. Distinctive miRNA and protein signatures contribute to the phenotype of crossbreed.
AbstractThe 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.
In the present study we report on the ability of gold nanoparticles (AuNP) to enhance the antimicrobial activity of the photosensitizer Rose Bengal (RB), a very effective singlet oxygen generator. Our experiments were conducted using a suspension of Escherichia Coli in the presence of either RB or a combination of RB and AuNP. Nanoparticles were synthesized by laser ablation in water, which allows high purity, biologically friendly AuNP production, as compared to traditional chemical methods. Several relative concentrations of bacteria, photosensitizes and AuNP were studied. Bacterial survival rates were determined before and after LED light illumination. The phototoxicity of RB with and without AuNP was checked following illumination for 10 and 20 minutes. As a control, the dark toxicity of RB was verified. The results show that the survival rate of bacteria decreases significantly with the increase of RB concentration and illumination time, which is in accordance with previous works. Interestingly, our results also indicate a significant increase in the lethal photosensitization of RB in the presence of AuNP. We propose this effect is due to plasmonic light enhancement, considering the superposition of RB and AuNP absorption spectra, which favors electric field enhancement effects in the presence of AuNP. Similar experiments using the photosensitizer Methylene Blue (MB) allowed us to test our hypothesis for MB did not show any difference in its phototoxicity in the presence of AuNP. We propose this observed synergistic effect could be an effective way for improving photodynamic inactivation of microorganisms.
Glycolysis is one of the primordial pathways of metabolism, playing a pivotal role in energy metabolism and biosynthesis. Glycolytic enzymes are known to form transient multi-enzyme assemblies. Here we examine the wider protein-protein interactions of plant glycolytic enzymes and reveal a moonlighting role for specific glycolytic enzymes in mediating the co-localization of mitochondria and chloroplasts. Knockout mutation of phosphoglycerate mutase or enolase resulted in a significantly reduced association of the two organelles. We provide evidence that phosphoglycerate mutase and enolase form a substrate-channelling metabolon which is part of a larger complex of proteins including pyruvate kinase. These results alongside a range of genetic complementation experiments are discussed in the context of our current understanding of chloroplast-mitochondrial interactions within photosynthetic eukaryotes.
Protein interaction and protein imaging strongly benefit from the advancements in time-resolved and superresolution fluorescence microscopic techniques. However, the techniques were typically applied separately and ex vivo because of technical challenges and the absence of suitable fluorescent protein pairs. Here, we show correlative in vivo fluorescence lifetime imaging microscopy Förster resonance energy transfer (FLIM-FRET) and stimulated emission depletion (STED) microscopy to unravel protein mechanics and structure in living cells. We use magnetotactic bacteria as a model system where two proteins, MamJ and MamK, are used to assemble magnetic particles called magnetosomes. The filament polymerizes out of MamK and the magnetosomes are connected via the linker MamJ. Our system reveals that bacterial filamentous structures are more fragile than the connection of biomineralized particles to this filament. More importantly, we anticipate the technique to find wide applicability for the study and quantification of biological processes in living cells and at high resolution.
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.
Synergistic Chemo- and Photodynamic Treatment of Cancer Cells with C60 Fullerene Nanocomplexes
(2021)
Recent progress in nanotechnology has attracted interest to a biomedical application of the carbon nanoparticle C60 fullerene (C60) due to its unique structure and versatile biological activity. In the current study the dual functionality of C60 as a photosensitizer and a drug nanocarrier was exploited to improve the efficiency of chemotherapeutic drugs towards human leukemic cells.
Pristine C60 demonstrated time-dependent accumulation with predominant mitochondrial localization in leukemic cells. C60’s effects on leukemic cells irradiated with high power single chip LEDs of different wavelengths were assessed to find out the most effective photoexcitation conditions. A C60-based noncovalent nanosized system as a carrier for an optimized drug delivery to the cells was evaluated in accordance to its physicochemical properties and toxic effects. Finally, nanomolar amounts of C60-drug nanocomplexes in 1:1 and 2:1 molar ratios were explored to improve the efficiency of cell treatment, complementing it with photodynamic approach.
A proposed treatment strategy was developed for C60 nanocomplexes with the common chemotherapeutic drug Doxorubicin, whose intracellular accumulation and localization, cytotoxicity and mechanism of action were investigated. The developed strategy was revealed to be transferable to an alternative potent anticancer drug – the herbal alkaloid Berberine.
Hereafter, a strong synergy of treatments arising from the combination of C60-mediated drug delivery and C60 photoexcitation was revealed. Presented data indicate that a combination of chemo- and photodynamic treatments with C60-drug nanoformulations could provide a promising synergetic approach for cancer treatment.
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.
Today, academic researchers benefit from the changes driven by digital technologies and the enormous growth of knowledge and data, on globalisation, enlargement of the scientific community, and the linkage between different scientific communities and the society. To fully benefit from this development, however, information needs to be shared openly and transparently. Digitalisation plays a major role here because it permeates all areas of business, science and society and is one of the key drivers for innovation and international cooperation. To address the resulting opportunities, the EU promotes the development and use of collaborative ways to produce and share knowledge and data as early as possible in the research process, but also to appropriately secure results with the European strategy for Open Science (OS). It is now widely recognised that making research results more accessible to all societal actors contributes to more effective and efficient science; it also serves as a boost for innovation in the public and private sectors. However for research data to be findable, accessible, interoperable and reusable the use of standards is essential. At the metadata level, considerable efforts in standardisation have already been made (e.g. Data Management Plan and FAIR Principle etc.), whereas in context with the raw data these fundamental efforts are still fragmented and in some cases completely missing. The CHARME consortium, funded by the European Cooperation in Science and Technology (COST) Agency, has identified needs and gaps in the field of standardisation in the life sciences and also discussed potential hurdles for implementation of standards in current practice. Here, the authors suggest four measures in response to current challenges to ensure a high quality of life science research data and their re-usability for research and innovation.
The ElonginB/C-Cullin5-SOCS-Box-Complex Is a Potential Biomarker for Growth Hormone Disorders
(2021)
Insulin-like growth factor 1 (IGF-1) is the standard biochemical marker for the diagnosis and treatment control of acromegaly and growth hormone deficiency (GHD). However, its limitations necessitate the screening for new specific and sensitive biomarkers. The elonginB/C-cullin5-SOCS-box-complex (ECS-complex) (an intracellular five-protein complex) is stimulated by circulating growth hormone (GH) and regulates GH receptor levels through a negative feedback loop. It mediates the cells’ sensitivity for GH and therefore, represents a potent new biomarker for those diseases. In this study, individual ECS-complex proteins were measured in whole blood samples of patients with acromegaly (n = 32) or GHD (n = 12) via ELISA and compared to controls. Hierarchical clustering of the results revealed that by combining the three ECS-complex proteins suppressor of cytokine signaling 2 (SOCS2), cullin-5 and ring-box protein 2 (Rbx-2), 93% of patient samples could be separated from controls, despite many patients having a normal IGF-1 or not receiving medical treatment. SOCS2 showed the best individual diagnostic performance with an overall accuracy of 0.93, while the combination of the three proteins correctly identified all patients and controls. This resulted in perfect sensitivity and specificity for all patient groups, which demonstrates potential benefits of the ECS-complex proteins as clinical biomarkers for the diagnostics of GH-related diseases and substantiates their important role in GH metabolism.
This review presents the 100-year history of the Martsinovsky Institute of Medical Parasitology and Tropical Medicine in Moscow, Russia, starting with its foundation and early activities, and also describes the impact of its leading scientists, some of whom became internationally known. The institute headed a network of nine tropical institutes in the various Soviet republics from the 1920s to 1990. The extensive body of literature on the history and research accomplishments of this institute has mainly been published in Russian; our goal here is to introduce these achievements and this expertise to the international scientific and medical community, focusing on malaria and leishmaniasis and the development of measures to control and monitor these diseases in the USSR.
Pepper bacterial spot is one of the most severe plant diseases in terms of infection persistence and economic losses when it comes to fresh pepper fruits used in nutrition and industrial processing. In this study, Bacillus velezensis IP22 isolated from fresh cheese was used as a biocontrol agent of pepper bacterial spot, whose main causal agent is the cosmopolitan pathogen Xanthomonas euvesicatoria. After optimization of the cultivation medium composition aimed at maximizing of the antimicrobial activity against X. euvesicatoria and validation of the optimized medium at the scale of a laboratory bioreactor, in planta tests were performed. The results have showed significant suppression of bacterial spot symptoms in pepper plants by the produced biocontrol agent, as well as reduction of disease spreading on the healthy (uninoculated) pepper leaves. Furthermore, HPLC-MS (high pressure liquid chromatography–mass spectrometry) analysis was employed to examine antimicrobial metabolites produced by B. velezensis IP22, where lipopeptides were found with similar m/z values compared to lipopeptides from fengycin and locillomycin families. The bioprocess solution developed at the laboratory scale investigated in this study represents a promising strategy for production of pepper bacterial spot biocontrol agent based on B. velezensis IP22, a food isolate with a great perspective for application in plant protection.
Trimeric photosystem I from the cyanobacterium Thermosynechococcus elongatus (TePSI) is an intrinsic membrane protein, which converts solar energy into electrical energy by oxidizing the soluble redox mediator cytochrome c6 (Cyt c6) and reducing ferredoxin. Here, we use cryo-electron microscopy and small angle neutron scattering (SANS) to characterize the transient binding of Cyt c6 to TePSI. The structure of TePSI cross-linked to Cyt c6 was solved at a resolution of 2.9 Å and shows additional cofactors as well as side chain density for 84% of the peptide chain of subunit PsaK, revealing a hydrophobic, membrane intrinsic loop that enables binding of associated proteins. Due to the poor binding specificity, Cyt c6 could not be localized with certainty in our cryo-EM analysis. SANS measurements confirm that Cyt c6 does not bind to TePSI at protein concentrations comparable to those for cross-linking. However, SANS data indicate a complex formation between TePSI and the non-native mitochondrial cytochrome from horse heart (Cyt cHH). Our study pinpoints the difficulty of identifying very small binding partners (less than 5% of the overall size) in EM structures when binding affinities are poor. We relate our results to well resolved co-structures with known binding affinities and recommend confirmatory methods for complexes with KM values higher than 20 μM.
Sand flies (Diptera: Psychodidae: Phlebotominae) are blood-feeding insects that transmit the protozoan parasites Leishmania spp. and various arthropod-borne (arbo) viruses. While in Mediterranean parts of Europe the sand fly fauna is diverse, in Central European countries including Austria mainly Phlebotomus mascittii is found, an assumed but unproven vector of Leishmania infantum. To update the currently understudied sand fly distribution in Austria, a sand fly survey was performed and other entomological catches were screened for sand flies. Seven new trapping locations of Ph. mascittii are reported including the first record in Vienna, representing also one of the first findings of this species in a city. Morphological identification, supported by fluorescence microscopy, was confirmed by two molecular approaches, including sequencing and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) protein profiling. Sand fly occurrence and activity were evaluated based on surveyed locations, habitat requirements and climatic parameters. Moreover, a first comparison of European Ph. mascittii populations was made by two marker genes, cytochrome c oxidase subunit 1 (COI), and cytochrome b (cytb), as well as MALDI-TOF mass spectra. Our study provides new important records of Ph. mascittii in Austria and valuable data for prospective entomological surveys. MALDI-TOF MS protein profiling was shown to be a reliable tool for differentiation between sand fly species. Rising temperatures and globalization demand for regular entomological surveys to monitor changes in species distribution and composition. This is also important with respect to the possible vector competence of Ph. mascittii.
Research publications and data nowadays should be publicly available on the internet and, theoretically, usable for everyone to develop further research, products, or services. The long-term accessibility of research data is, therefore, fundamental in the economy of the research production process. However, the availability of data is not sufficient by itself, but also their quality must be verifiable. Measures to ensure reuse and reproducibility need to include the entire research life cycle, from the experimental design to the generation of data, quality control, statistical analysis, interpretation, and validation of the results. Hence, high-quality records, particularly for providing a string of documents for the verifiable origin of data, are essential elements that can act as a certificate for potential users (customers). These records also improve the traceability and transparency of data and processes, therefore, improving the reliability of results. Standards for data acquisition, analysis, and documentation have been fostered in the last decade driven by grassroot initiatives of researchers and organizations such as the Research Data Alliance (RDA). Nevertheless, what is still largely missing in the life science academic research are agreed procedures for complex routine research workflows. Here, well-crafted documentation like standard operating procedures (SOPs) offer clear direction and instructions specifically designed to avoid deviations as an absolute necessity for reproducibility.
Therefore, this paper provides a standardized workflow that explains step by step how to write an SOP to be used as a starting point for appropriate research documentation.
Pituitary neuroendocrine tumors (PitNET) do not only belong to the most common intracranial neoplasms but seem to be generally more common than has been thought. Minimally invasive liquid biopsies have the potential to improve their early screening efficiency as well as monitor prognosis by facilitating the diagnostic procedures. This review aims to assess the potential of using liquid biopsies of different kinds of biomarker species that have only been obtained from solid pituitary tissues so far. Numerous molecules have been associated with the development of a PitNET, suggesting that it often develops from the cumulative effects of many smaller genetic or epigenetic changes. These minor changes eventually pile up to switch critical molecules into tumor-promoting states, which may be the key regulatory nodes representing the most potent marker substances for a diagnostic test. Drugs targeting these nodes may be superior for the therapeutic outcome and therefore the identification of such pituitary-specific cellular key nodes will help to accelerate their application in medicine. The ongoing genetic degeneration in pituitary adenomas suggests that repeated tumor profiling via liquid biopsies will be necessary for personalized and effective treatment solutions.
A nanosized drug complex was explored to improve the efficiency of cancer chemotherapy, complementing it with nanodelivery and photodynamic therapy. For this, nanomolar amounts of a non-covalent nanocomplex of Doxorubicin (Dox) with carbon nanoparticle C60 fullerene (C60) were applied in 1:1 and 2:1 molar ratio, exploiting C60 both as a drug-carrier and as a photosensitizer. The fluorescence microscopy analysis of human leukemic CCRF-CEM cells, in vitro cancer model, treated with nanocomplexes showed Dox’s nuclear and C60’s extranuclear localization. It gave an opportunity to realize a double hit strategy against cancer cells based on Dox’s antiproliferative activity and C60’s photoinduced pro-oxidant activity. When cells were treated with 2:1 C60-Dox and irradiated at 405 nm the high cytotoxicity of photo-irradiated C60-Dox enabled a nanomolar concentration of Dox and C60 to efficiently kill cancer cells in vitro. The high pro-oxidant and pro-apoptotic efficiency decreased IC50 16, 9 and 7 × 103-fold, if compared with the action of Dox, non-irradiated nanocomplex, and C60’s photodynamic effect, correspondingly. Hereafter, a strong synergy of therapy arising from the combination of C60-mediated Dox delivery and C60 photoexcitation was revealed. Our data indicate that a combination of chemo- and photodynamic therapies with C60-Dox nanoformulation provides a promising synergetic approach for cancer treatment.
C60 Fullerene as an Effective Nanoplatform of Alkaloid Berberine Delivery into Leukemic Cells
(2019)
A herbal alkaloid Berberine (Ber), used for centuries in Ayurvedic, Chinese, Middle-Eastern, and native American folk medicines, is nowadays proved to function as a safe anticancer agent. Yet, its poor water solubility, stability, and bioavailability hinder clinical application. In this study, we have explored a nanosized carbon nanoparticle—C60 fullerene (C60)—for optimized Ber delivery into leukemic cells. Water dispersions of noncovalent C60-Ber nanocomplexes in the 1:2, 1:1, and 2:1 molar ratios were prepared. UV–Vis spectroscopy, dynamic light scattering (DLS), and atomic force microscopy (AFM) evidenced a complexation of the Ber cation with the negatively charged C60 molecule. The computer simulation showed that π-stacking dominates in Ber and C60 binding in an aqueous solution. Complexation with C60 was found to promote Ber intracellular uptake. By increasing C60 concentration, the C60-Ber nanocomplexes exhibited higher antiproliferative potential towards CCRF-CEM cells, in accordance with the following order: free Ber < 1:2 < 1:1 < 2:1 (the most toxic). The activation of caspase 3/7 and accumulation in the sub-G1 phase of CCRF-CEM cells treated with C60-Ber nanocomplexes evidenced apoptosis induction. Thus, this study indicates that the fast and easy noncovalent complexation of alkaloid Ber with C60 improved its in vitro efficiency against cancer cells.
Most biochemical reactions depend on the pH value of the aqueous environment and some are strongly favoured to occur in an acidic environment. A non-invasive control of pH to tightly regulate such reactions with defined start and end points is a highly desirable feature in certain applications, but has proven difficult to achieve so far. We report a novel optical approach to reversibly control a typical biochemical reaction by changing the pH and using acid phosphatase as a model enzyme. The reversible photoacid G-acid functions as a proton donor, changing the pH rapidly and reversibly by using high power UV LEDs as an illumination source in our experimental setup. The reaction can be tightly controlled by simply switching the light on and off and should be applicable to a wide range of other enzymatic reactions, thus enabling miniaturization and parallelization through non-invasive optical means.
Quantification of nitroaromatic explosives in contaminated soil using MALDI-TOF mass spectrometry
(2019)
Contamination from various sources is a global environmental and health threat, with mining and military activities in particular having spread nitroaromatic compounds, such as 2,4,6-trinitrotoluene and its degradation products and by-products, to the soil. The investigation and monitoring of large contaminated areas requires new detection methods since the established ones are expensive and time-consuming. Hence, we established a matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI--TOF MS) method using 1,5-diaminonaphthalene as the matrix substance and an internal standard for quantification. Analyzing standard substances, we found specific signals for radical and fragment ions of different nitrotoluenes and nitrobenzenes with good reproducibility and detection limits down to 0.25 ng/μL. The analysis of soil sample extracts from a former production site showed clear signals for 2,4,6-trinitrotoluene and the primary degradation products aminodinitrotoluenes. Furthermore, quantification gave results comparable to those obtained by conventional liquid chromatography--tandem mass spectrometry analysis. The MALDI-TOF MS method has a comparatively lower reproducibility, with relative standard deviations of 6% to 20% for multiple measurements of standard solutions and soil sample extracts. Nevertheless, a comparison of both methods revealed the advantages of MALDI-TOF MS analysis of explosive-contaminated areas with regard to costs, time, and handling. Finally, our MALDI-TOF MS method fulfills all the needs for high sample throughput and can therefore be a valuable screening tool for explosive-contaminated areas.
Quantum dots increasingly gain popularity for in vivo applications. However, their delivery and accumulation into cells can be challenging and there is still lack of detailed information. Thereby, the application of advanced fluorescence techniques can expand the portfolio of useful parameters for a more comprehensive evaluation. Here, we encapsulated hydrophilic quantum dots into liposomes for studying cellular uptake of these so-called lipodots into living cells. First, we investigated photophysical properties of free quantum dots and lipodots observing changes in the fluorescence decay time and translational diffusion behaviour. In comparison to empty liposomes, lipodots exhibited an altered zeta potential, whereas their hydrodynamic size did not change. Fluorescence lifetime imaging microscopy (FLIM) and fluorescence correlation spectroscopy (FCS), both combined with two-photon excitation (2P), were used to investigate the interaction behaviour of lipodots with an insect epithelial tissue. In contrast to the application of free quantum dots, their successful delivery into the cytosol of salivary gland duct cells could be observed when applying lipodots. Lipodots with different lipid compositions and surface charges did not result in considerable differences in the intracellular labelling pattern, luminescence decay time and diffusion behaviour. However, quantum dot degradation after intracellular accumulation could be assumed from reduced luminescence decay times and blue-shifted luminescence signals. In addition to single diffusing quantum dots, possible intracellular clustering of quantum dots could be assumed from increased diffusion times. Thus, by using a simple and manageable liposome carrier system, 2P-FLIM and 2P-FCS recording protocols could be tested, which are promising for investigating the fate of quantum dots during cellular interaction.
The importance of software validation increases since the need for high usability and suitability of software applications grows. In order to reduce costs and manage risk factors, more and more recommendations and rules have been established. In the field of pharmacy the vendors of so-called chromatography data systems (CDSs) had to implement the guidelines of the Code of Federal Regulations Title 21 (CFR 21) during the last few years in order to fulfill the increasing requirements. The CFR 21 part 11 deals with electronic records and signatures. This part is binding for each company in the regulated environment that wishes to create, edit and sign electronic information instead of printing them on paper. Subsection CFR 21 part 11.10(h) explains how to perform an input check for manual user entries as well as for data that will be collected from an external device. In this article we present an approach performing the double entry method on data provided by the hardware instrument in order to investigate possible influences on the raw data by the handling CDS.
A software tool has been written which allows us to communicate with a high-performance liquid chromatography (HPLC) detector and acquire data from it. The communication is completely independent of a CDS which is started separately and connected to the same system. Using this configuration we made a parallel data acquisition of two instances at the same time possible. Two CDSs have been tested and for at least one of them it has been shown that a comparison of the acquired data can be done as with the double entry method for the data verification. For the second CDS we checked whether it would be applicable after a few modifications. The given approach could be either used for a live data verification of produced raw data or as a single test during a software operational qualification to verify the data acquisition functionality of the software.
BIOMEX (BIOlogy and Mars EXperiment) is an ESA/Roscosmos space exposure experiment housed within the exposure facility EXPOSE-R2 outside the Zvezda module on the International Space Station (ISS). The design of the multiuser facility supports—among others—the BIOMEX investigations into the stability and level of degradation of space-exposed biosignatures such as pigments, secondary metabolites, and cell surfaces in contact with a terrestrial and Mars analog mineral environment. In parallel, analysis on the viability of the investigated organisms has provided relevant data for evaluation of the habitability of Mars, for the limits of life, and for the likelihood of an interplanetary transfer of life (theory of lithopanspermia). In this project, lichens, archaea, bacteria, cyanobacteria, snow/permafrost algae, meristematic black fungi, and bryophytes from alpine and polar habitats were embedded, grown, and cultured on a mixture of martian and lunar regolith analogs or other terrestrial minerals. The organisms and regolith analogs and terrestrial mineral mixtures were then exposed to space and to simulated Mars-like conditions by way of the EXPOSE-R2 facility. In this special issue, we present the first set of data obtained in reference to our investigation into the habitability of Mars and limits of life. This project was initiated and implemented by the BIOMEX group, an international and interdisciplinary consortium of 30 institutes in 12 countries on 3 continents. Preflight tests for sample selection, results from ground-based simulation experiments, and the space experiments themselves are presented and include a complete overview of the scientific processes required for this space experiment and postflight analysis. The presented BIOMEX concept could be scaled up to future exposure experiments on the Moon and will serve as a pretest in low Earth orbit.