Monoclonal gammopathies are a group of blood diseases characterized by presence of abnormal immunoglobulins in peripheral blood and/or urine of patients. Multiple myeloma and plasma cell leukemia are monoclonal gammopathies with unclear etiology, caused by malignant transformation of bone marrow plasma cells. Mass spectrometry with matrix-assisted laser desorption/ionization and time-of-flight detection is commonly used for investigation of the peptidome and small proteome of blood plasma with high accuracy, robustness, and cost-effectivity. In addition, mass spectrometry coupled with advanced statistics can be used for molecular profiling, classification, and diagnosis of liquid biopsies and tissue specimens in various malignancies. Despite the fact there have been fully optimized protocols for mass spectrometry of normal blood plasma available for decades, in monoclonal gammopathy patients, the massive alterations of biophysical and biochemical parameters of peripheral blood plasma often limit the mass spectrometry measurements. In this paper, we present a new two-step extraction protocol and demonstrated the enhanced resolution and intensity (>50×) of mass spectra obtained from extracts of peripheral blood plasma from monoclonal gammopathy patients. When coupled with advanced statistics and machine learning, the mass spectra profiles enabled the direct identification, classification, and discrimination of multiple myeloma and plasma cell leukemia patients with high accuracy and precision. A model based on PLS-DA achieved the best performance with 71.5% accuracy (95% confidence interval, CI = 57.1-83.3%) when the 10× repeated 5-fold CV was performed. In summary, the two-step extraction protocol improved the analysis of monoclonal gammopathy peripheral blood plasma samples by mass spectrometry and provided a tool for addressing the complex molecular etiology of monoclonal gammopathies.
The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of compression algorithms. This study evaluates whether the pathologies present in ECG signals affect the efficiency and quality of compression. Single-cycle fractal-based compression algorithm and compression algorithm based on combination of wavelet transform and set partitioning in hierarchical trees are used to compress 125 15-leads ECG signals from CSE database. Rhythm and morphology of these signals are newly annotated as physiological or pathological. The compression performance results are statistically evaluated. Using both compression algorithms, physiological signals are compressed with better quality than pathological signals according to 8 and 9 out of 12 quality metrics, respectively. Moreover, it was statistically proven that pathological signals were compressed with lower efficiency than physiological signals. Signals with physiological rhythm and physiological morphology were compressed with the best quality. The worst results reported the group of signals with pathological rhythm and pathological morphology. This study is the first one which deals with effects of ECG pathologies on the performance of compression algorithms. Signal-by-signal rhythm and morphology annotations (physiological/pathological) for the CSE database are newly published.
- MeSH
- algoritmy MeSH
- databáze faktografické MeSH
- elektrokardiografie metody MeSH
- fraktály MeSH
- komprese dat metody MeSH
- lidé MeSH
- vlnková analýza MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Multidrug resistance (MDR) is a common problem when fighting cancer with chemotherapy. P-glycoprotein (P-gp, or MDR1) is an active pump responsible for the efflux of xenobiotics out of the cell, including anti-cancer drugs. It is a validated target against MDR. No crystal structure of the human P-gp is available to date, and only recently several cryo-EM structures have been solved. In this paper, we present a comprehensive computational approach that includes constructing the full-length three-dimensional structure of the human P-gp and its refinement using molecular dynamics. We assessed its flexibility and conformational diversity, compiling a dynamical ensemble that was used to dock a set of lignan compounds, previously reported as active P-gp inhibitors, and disclose their binding modes. Based on the statistical analysis of the docking results, we selected a system for performing the structure-based virtual screening of new potential P-gp inhibitors. We tested the method on a library of 87 natural flavonoids described in the literature, and 10 of those were experimentally assayed. The results reproduced the theoretical predictions only partially due to various possible factors. However, at least two of the predicted natural flavonoids were demonstrated to be effective P-gp inhibitors. They were able to increase the accumulation of doxorubicin inside the human promyelocytic leukemia HL60/MDR cells overexpressing P-gp and potentiate the antiproliferative activity of this anti-cancer drug.
- Publikační typ
- časopisecké články MeSH
Alzheimer's disease (AD) is a chronic neurodegenerative disease associated with the overproduction and accumulation of amyloid-β peptide and hyperphosphorylation of tau proteins in the brain. Despite extensive research on the amyloid-based mechanism of AD pathogenesis, the underlying cause of AD is not fully understood. No disease-modifying therapies currently exist, and numerous clinical trials have failed to demonstrate any benefits. The recent discovery that the amyloid-β peptide has antimicrobial activities supports the possibility of an infectious aetiology of AD and suggests that amyloid-β plaque formation might be induced by infection. AD patients have a weakened blood-brain barrier and immune system and are thus at elevated risk of microbial infections. Such infections can cause chronic neuroinflammation, production of the antimicrobial amyloid-β peptide, and neurodegeneration. Various pathogens, including viruses, bacteria, fungi, and parasites have been associated with AD. Most research in this area has focused on individual pathogens, with herpesviruses and periodontal bacteria being most frequently implicated. The purpose of this review is to highlight the potential role of multi-pathogen infections in AD. Recognition of the potential coexistence of multiple pathogens and biofilms in AD's aetiology may stimulate the development of novel approaches to its diagnosis and treatment. Multiple diagnostic tests could be applied simultaneously to detect major pathogens, followed by anti-microbial treatment using antiviral, antibacterial, antifungal, and anti-biofilm agents.
Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.
Human pluripotent stem cells have the potential to change the way in which human diseases are cured. Clinical-grade human embryonic stem cells and human induced pluripotent stem cells have to be created according to current good manufacturing practices and regulations. Quality and safety must be of the highest importance when humans' lives are at stake. With the rising number of clinical trials, there is a need for a consensus on hPSCs characterization. Here, we summarize mandatory and 'for information only' characterization methods with release criteria for the establishment of clinical-grade hPSC lines.
Ultrasound imaging of the thyroid gland is considered to be the best diagnostic choice for evaluating thyroid nodules in early stages, since it has been marked as cost-effective, non-invasive and risk-free. Computer aided diagnosis (CAD) systems can offer a second opinion to radiologists, thereby increasing the overall diagnostic accuracy of ultrasound imaging. Although current CAD systems exhibit promising results, their use in clinical practice is limited. Some of the main limitations are that the majority use direction dependent features so, they are only compatible with static images in just one plane (axial or longitudinal), requiring precise segmentation of a nodule. Our intention has been to design a CAD system which will use only direction independent features i.e., not dependent upon the orientation or inclination angle of the ultrasound probe when acquiring the image. In this study, 60 thyroid nodules (20 malignant, 40 benign) were divided into small patches of 17 × 17 pixels, which were then used to extract several direction independent features by employing Two-Threshold Binary Decomposition, a method that decomposes an image into the set of binary images. The features were then used in Random Forests (RF) and Support Vector Machine (SVM) classifiers to categorize nodules into malignant and benign classes. Classification was evaluated using group 10-fold cross-validation method. Performance on individual patches was then averaged to classify whole nodules with the following results: overall accuracy, sensitivity, specificity and area under receiver operating characteristics (ROC) curve: 95%, 95%, 95%, 0.971 for RF and; 91.6%, 95%, 90%, 0.965 for SVM respectively. The patch-based CAD system we present can provide support to radiologists in their current diagnosis of thyroid nodules, whereby it can increase the overall accuracy of ultrasound imaging.
- MeSH
- diagnóza počítačová metody MeSH
- diferenciální diagnóza MeSH
- interpretace obrazu počítačem metody MeSH
- lidé středního věku MeSH
- lidé MeSH
- senzitivita a specificita MeSH
- support vector machine * MeSH
- ultrasonografie metody MeSH
- uzle štítné žlázy diagnostické zobrazování patologie MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Enzymes are efficient and specific catalysts for many essential reactions in biotechnological and pharmaceutical industries. Many times, the natural enzymes do not display the catalytic efficiency, stability or specificity required for these industrial processes. The current enzyme engineering methods offer solutions to this problem, but they mainly target the buried active site where the chemical reaction takes place. Despite being many times ignored, the tunnels and channels connecting the environment with the active site are equally important for the catalytic properties of enzymes. Changes in the enzymatic tunnels and channels affect enzyme activity, specificity, promiscuity, enantioselectivity and stability. This review provides an overview of the emerging field of enzyme access tunnel engineering with case studies describing design of all the aforementioned properties. The software tools for the analysis of geometry and function of the enzymatic tunnels and channels and for the rational design of tunnel modifications will also be discussed. The combination of new software tools and enzyme engineering strategies will provide enzymes with access tunnels and channels specifically tailored for individual industrial processes.
BACKGROUND: Sarcomas are rare tumors but represent the third most common malignancy in children. The cancer stem cell (CSC) paradigm is well established, and CSCs have been intensively studied in sarcomas in the past decade. SCOPE OF REVIEW: This review summarizes current knowledge on CSCs in sarcomas and provides new perspectives on the role of a deregulated stemness program in sarcomagenesis. MAJOR CONCLUSIONS: Cell surface markers have so far failed to specifically target sarcoma CSCs. Sarcomas likely arise from immature cells that undergo pathological reprogramming. Transcription factor Sox2, which is frequently upregulated in sarcomas, is directly involved in this process, and its crucial role in the acquisition and maintenance of the CSC phenotype has been demonstrated in various sarcomas. GENERAL SIGNIFICANCE: Sox2 is a core functional regulator of the stem-like state and is an outstanding marker of sarcoma CSCs. Fluorescence protein-based reporters of Sox2 expression might provide useful tools for subsequent studies of sarcoma CSCs.
- MeSH
- lidé MeSH
- nádorová transformace buněk metabolismus patologie MeSH
- nádorové kmenové buňky metabolismus patologie MeSH
- sarkom metabolismus patologie MeSH
- transkripční faktory SOXB1 metabolismus MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- přehledy MeSH
We present comprehensive testing of solvent representation in quantum mechanics (QM)-based scoring of protein-ligand affinities. To this aim, we prepared 21 new inhibitors of cyclin-dependent kinase 2 (CDK2) with the pyrazolo[1,5-a]pyrimidine core, whose activities spanned three orders of magnitude. The crystal structure of a potent inhibitor bound to the active CDK2/cyclin A complex revealed that the biphenyl substituent at position 5 of the pyrazolo[1,5-a]pyrimidine scaffold was located in a previously unexplored pocket and that six water molecules resided in the active site. Using molecular dynamics, protein-ligand interactions and active-site water H-bond networks as well as thermodynamics were probed. Thereafter, all the inhibitors were scored by the QM approach utilizing the COSMO implicit solvent model. Such a standard treatment failed to produce a correlation with the experiment (R(2) = 0.49). However, the addition of the active-site waters resulted in significant improvement (R(2) = 0.68). The activities of the compounds could thus be interpreted by taking into account their specific noncovalent interactions with CDK2 and the active-site waters. In summary, using a combination of several experimental and theoretical approaches we demonstrate that the inclusion of explicit solvent effects enhance QM/COSMO scoring to produce a reliable structure-activity relationship with physical insights. More generally, this approach is envisioned to contribute to increased accuracy of the computational design of novel inhibitors.
- MeSH
- cyklin A metabolismus MeSH
- cyklin-dependentní kinasa 2 antagonisté a inhibitory chemie metabolismus MeSH
- inhibitory proteinkinas chemie metabolismus farmakologie MeSH
- katalytická doména * MeSH
- kvantová teorie * MeSH
- lidé MeSH
- pyrimidiny chemie metabolismus farmakologie MeSH
- racionální návrh léčiv MeSH
- rozpouštědla chemie MeSH
- simulace molekulární dynamiky MeSH
- voda chemie MeSH
- vztahy mezi strukturou a aktivitou MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
