Czech Technical University in Prague

Background Cell cycle progression and leukemia development are tightly regulated processes in which even a small imbalance in the expression of cell cycle regulatory molecules and microRNAs (miRNAs) can lead to an increased risk of cancer/leukemia development. Here, we focus on the study of a ubiquitous, multifunctional, and oncogenic miRNA-hsa-miR-155–5p (miR-155, MIR155HG), which is overexpressed in malignancies including chronic lymphocytic leukemia (CLL). Nonetheless, the precise mechanism of how miR-155 regulates the cell cycle in leukemic cells remains the subject of extensive research. Methods We edited the CLL cell line MEC-1 by CRISPR/Cas9 to introduce a short deletion within the MIR155HG gene. To describe changes at the transcriptome and miRNome level in miR-155-deficient cells, we performed mRNA-seq/miRNA-seq and validated changes by qRT-PCR. Flow cytometry was used to measure cell cycle kinetics. A WST-1 assay, hemocytometer, and Annexin V/PI staining assessed cell viability and proliferation. Results The limited but phenotypically robust miR-155 modification impaired cell proliferation, cell cycle, and cell ploidy. This was accompanied by overexpression of the negative cell cycle regulator p21/CDKN1A and Cyclin D1 (CCND1). We confirmed the overexpression of canonical miR-155 targets such as PU.1, FOS, SHIP-1, TP53INP1 and revealed new potential targets (FCRL5, ISG15, and MX1). Conclusions We demonstrate that miR-155 deficiency impairs cell proliferation, cell cycle, transcriptome, and miRNome via deregulation of the MIR155HG/TP53INP1/CDKN1A/CCND1 axis. Our CLL model is valuable for further studies to manipulate miRNA levels to revert highly aggressive leukemic cells to nearly benign or non-leukemic types.

This study focuses on laser metal deposition of wire (LMD-w) using a pulsed laser for titanium, addressing the influence of technological parameters on geometry and porosity. This paper investigates the impact of process parameters, such as wire feed rate, machine feed rate, pulse frequency, and pulse length, on the geometry and porosity of titanium wire deposited using the LMD-w process. The parameters were systematically altered, and the geometry and porosity were evaluated using visual inspection, 3D scanning, and X-ray computed tomography. The results indicate that the technological parameters affect the geometry of the weld bead and impact the amount of porosity. Increasing the wire feed rate results in a higher bead, but also greater porosity and not acceptable geometry of bead by visual inspection. Pulse energy has great influence on weld bead width. With greater pulse energy the weld bead is wider, but the porosity is also higher. With increasing feed rate, the height of the bead decreases and porosity also increases. This investigation provides valuable insights into the LMD-w process, laying the groundwork for further optimization of additive manufacturing processes.

Non-healing wounds are a serious complication in diabetic patients. One of the detrimental factors contributing to limited wound healing is the accumulation of metalloproteinase-9 (MMP‑9) in the wound. Selective inhibition...

Understanding the mechanics of the respiratory system is crucial for optimizing ventilator settings and ensuring patient safety. While simple models of the respiratory system typically consider only flow resistance and lung compliance, lung tissue resistance is usually neglected. This study investigated the effect of lung tissue viscoelasticity on delivered mechanical power in a physical model of the respiratory system and the possibility of distinguishing tissue resistance from airway resistance using proximal pressure measured at the airway opening. Three different configurations of a passive physical model of the respiratory system representing different mechanical properties (Tissue resistance model, Airway resistance model, and No-resistance model) were tested. The same volume-controlled ventilation and parameters were set for each configuration, with only the inspiratory flow rates being adjusted. Pressure and flow were measured with a Datex-Ohmeda S/5 vital signs monitor (Datex-Ohmeda, Madison, WI, USA). Tissue resistance was intentionally tuned so that peak pressures and delivered mechanical energy measured at airway opening were similar in Tissue and Airway Resistance models. However, measurements inside the artificial lung revealed significant differences, with Tissue resistance model yielding up to 20% higher values for delivered mechanical energy. The results indicate the need to revise current methods of calculating mechanical power delivery, which do not distinguish between tissue resistance and airway flow resistance, making it difficult to evaluate and interpret the significance of mechanical power delivery in terms of lung ventilation protectivity.

In order to obtain results from simulations that are close to reality, it is necessary to correctly set the parameters of the welding process. One of them is the efficiency of the welding process. Currently, new modifications of MIG/MAG methods are being created, which are characterized by lower heat introduced into the material (smaller efficiency coefficient). The efficiency coefficient determined by the European standard EN 1011–1 is no longer accurate enough for simulations. Therefore, it is necessary to accurately determine the efficiency coefficient of the method even for the mentioned modified welding processes. An experiment of calorimetric measurement of the efficiency of the CMT process (cold metal transfer—modification of the MIG/MAG method) was proposed. The specific heat capacity of the base material was accurately measured. Furthermore, a calorimetric measurement of the efficiency of the welding process was carried out on a flat sample (bead-on-plate method) and on a sample with a V-groove to simulate the treatment of welding surfaces. Accurate method efficiency values were determined for different welding current settings and different V-groove depths. The geometric characteristics of the fusion faces in butt welds have a greater influence on the efficiency coefficient than the size of the welding current.

The main goal of this study was to describe the Czech population of patients with MG in terms of demographics, disease characteristics, management approaches, and treatment trends. We selected all patients, both incident and prevalent, who were enrolled in the Czech MyReg registry between August 24, 2015 and November 19, 2021. For the descriptive analysis, all patients enrolled in the registry, regardless of their date of diagnosis or date of enrolment, were included. We analyzed the following disease-related endpoints: myasthenia gravis composite (MGC) score, forced vital capacity (FVC), and Myasthenia Gravis Foundation of America (MGFA) clinical classification. The incidence showed a consistent increasing trend from 0.62 to 3.13. The mean MGC score was 5.0 (median 4.0, 95% CI 4.7, 5.3) representing mild form of MG. The difference in FVC from the predicted value in patients during and without myasthenic crisis was 58.93% (95% CI 37.27, 80.59) and 75.93% (95% CI 74.87, 77.00), respectively. We identified 70 patients (5.0%) with refractory MG, of whom 58.6% were female. The MGFA classifications in those with refractory vs. non-refractory disease was as follows: IIa 21.8% vs 23.2%, IIb 45.3% vs 33.6%, and IIIb 14.1% vs 4.6%, respectively. Our analysis shows that the incidence of MG is increasing in the Czech Republic and that patients with refractory disease, of whom up to 58% are female, have a higher burden of disease than non-refractory patients.

This paper explores the potential of movable tensegrities and nonlinear cable-driven structures for designing lightweight robots. These mechanisms exhibit both drive and degrees of freedom redundancy, allowing additional conditions on pure end-effector motion control. The study focuses on using the redundancy in tensegrity mechanisms to maximize manipulability within a workspace. The methodology is demonstrated using a planar two-stage cable-driven tensegrity robot as a benchmark. The study begins with a description of self-stress analysis. Actuation planning is adapted for workspace exploration and position interpolation in trajectory planning. The control strategy for the manipulator involves trajectory planning, motion control, and implementing computed torque control. Actuator redundancy is addressed using singular value decomposition and the least squares method. Controller gains are optimized based on different test trajectories. A key contribution of this study is the development of a manipulability optimization methodology based on nonlinear dynamics. After meeting the end-effector motion requirements, the objective function, created by combining extreme singular values and the condition number of the Jacobian matrix, is optimized. Simulation experiments demonstrate the robustness of the algorithm, showing a significant improvement in the objective function.

Introduction A variable proportion of non‐responders to cardiac resynchronization therapy (CRT) warrants the search for new approaches to optimize the position of the left ventricular (LV) lead and the CRT device programming. CineECG is a novel ECG modality proposed for the spatial visualization and quantification of myocardial depolarization and repolarization sequences. Objective The present study aimed to evaluate CineECG‐derived parameters in different pacing modes and to test their associations with acute hemodynamic responses in CRT patients. Methods and Results CineECG was used to construct the average electrical path within the cardiac anatomy from the 12‐lead ECG. CineECG and LV dP/dt max were tested in 15 patients with nonischemic dilated cardiomyopathy and left bundle branch block (QRS: 170 ± 17 ms; LVEF: 26 ± 5.5%) under pacing protocols with different LV lead localizations. The CineECG‐derived path directions were computed for the QRS and ST‐T intervals for the anteroposterior (X h ), interventricular (Y h ), and apicobasal (Z h ) axes. In a multivariate linear regression analysis with adjustment for the pacing protocol type, the ST‐T path direction Y h was independently associated with the increase in dP/dt max during CRT, [regression coefficient 639.4 (95% confidence interval: 187.9–1090.9), p = 0.006]. In ROC curve analysis, the ST‐T path direction Y h was associated with the achievement of a 10% increase in dP/dt max (AUC: 0.779, p = 0.002) with the optimal cut‐off > 0.084 (left‐to‐right direction) with sensitivity 0.67 and specificity 0.92. Conclusion The acute hemodynamic response in CRT patients was associated with specific CineECG repolarization sequence parameters, warranting their further testing as potential predictors of clinical outcomes.

UHPC has been developed in the Czech republic for about 15 years. The paper shows some of the new footbridges with the deck made of UHPC and then focuses on repair and strengthening of existing structures. Extensive experimental work was carried out as a basis for applications. Different loading situations were examined so that the structural performance in serviceability and in ultimate limit states was investigated. Experience from the construction of structures made of UHPC, from extensive experimental campaign, and from literature resulted in development of the Technical conditions for production of UHPC, design and execution and for reconstruction of structures with UHPC, which were approved by the Ministry of Transport in 2024. The document provides a possibility to apply UHPC also in structures of the transport infrastructure. Finally, example of application of UHPC in repair of a heavily loaded road bridge is introduced. Now, the fourth stage of the repair is under construction. Experience from earlier stages led to minor modifications of the original technology.

Time Difference of Arrival (TDoA) based Visible Light Positioning (VLP) and Optical Wireless Positioning (OWP) offer considerable potential over conventional Received Signal Strength (RSS) methods. The current state of the art in TDoA OWP is however limited concerning experimental assessments, mainly focusing on simulations. This work presents experimental TDoA measurements in a proof-of-concept setup. The measurement results demonstrate a 95th percentile accuracy of 5.3 cm in a 50×50 cm area, in the absence of reflections. The susceptibility to reflections is examined experimentally, demonstrating that the performance deterioration can easily be minimized by performing a recalibration.

The available telecommunication services nowadays make connecting users easier. In return, vast streams of data are generated every day. However, mining useful information in data requires relevant techniques and procedures. In this article, a novel study is proposed consisting of a multi-algorithm approach to understand, detect and predict anomalies in cellular networks. The study holds 37 million Call Detail Records data from a cellular network with deployment of the latest network generations including 5G. The research is divided into two phases. In the first phase, we outline the voice traffic profile, where utilizing certain algorithms are meant to target specific attributes and scenarios in the data to understand the typical voice traffic patterns. Gaussian Mixture model is used to define the regular groups of call duration and Mean Shift clustering algorithm is employed to detect the peak hours on a daily basis. In the second phase, we deseasonalize the data for higher accuracy followed by the distribution function to comprehend the patterns in the data. We introduce three algorithms to detect and predict anomalies in the cellular network. The performance evaluation shows that DBSCAN and Isolation Forest algorithms provide the highest accuracy with 98% compared to the Z-score algorithm.

The problem of kinodynamic multi-goal motion planning is to find a trajectory over multiple target locations with an apriori unknown sequence of visits. The objective is to minimize the cost of the trajectory planned in a cluttered environment for a robot with a kinodynamic motion model. This problem has yet to be efficiently solved as it combines two NP-hard problems, the Traveling Salesman Problem (TSP) and the kinodynamic motion planning problem. We propose a novel approximate method called Kinodynamic Rapidly-exploring Random Forest (KRRF) to find a collision-free multi-goal trajectory that satisfies the motion constraints of the robot. KRRF simultaneously grows kinodynamic trees from all targets towards all other targets while using the other trees as a heuristic to boost the growth. Once the target-to-target trajectories are planned, their cost is used to solve the TSP to find the sequence of targets. The final multi-goal trajectory satisfying kinodynamic constraints is planned by guiding the RRT-based planner along the target-totarget trajectories in the TSP sequence. Compared with existing approaches, KRRF provides shorter target-to-target trajectories and final multi-goal trajectories with 1:1–2 times lower costs while being computationally faster in most test cases. The method will be published as an open-source library.

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.

Artificial intelligence invades our lives and professions at an ever-increasing pace and intensity. Architecture, engineering, construction, and operation of the real estate have been joining the trend only timidly and belatedly. The paper overviews the basic concepts, methods, general background, and results of artificial intelligence in architecture to date, discusses the achievements and prospects, and concludes the perspectives on the deployment of machine learning in the field. The record of some of the most recent “famous achievements” in the field is set straight and challenged, the flawed idea of a (truly) creative potential of the technology is debunked. Its roots equidistributed both in a farsighted vision of the next workflow of both productive and creative architectural and engineering designing, and construction and real estate management on the one hand and state-of-the-art machine learning on the other, an ambitious though realistic blueprint for R&D of AI-fostered architectural creativity, building design, planning, and operation is tabled for discussion. The attention turns to open-source patterns platforms, generative patterns processing, generative pre-design, parametric evaluation and optimization, latest achievements in machine learning building on reinforcement learning, imitation-based learning, learning a behavior policy from demonstration, and self-learning paradigms zooming in on the design-development processes instead of only on their results. Leveraging the objectivity of assessments and streamlining workflows, artificial intelligence promises to unleash true architectural creativity and leverage the productivity and efficiency of the design, planning, and operation processes.

This contribution is concerned with the well‐posedness and homogenization of an ordinary differential equation (ODE) of Arrhenius‐type coupled with a doubly nonlinear parabolic partial differential equation (PDE) with rapidly oscillating coefficients and taking into account disparate diffusion‐reaction time scales, including regularly as well as singularly perturbed problems. The ODE‐PDE system is spatially dependent and is subjected to Robin‐type boundary conditions. Such problems are used to model a variety of processes and phenomena such as combustion and exothermal chemical reactions. We will have a special look at the questions of the existence, uniqueness, boundedness, and the asymptotic limit of the microscale problem by applying the two‐scale convergence and unfolding method. A numerical example illustrates both the expected behavior of the approximated solutions as well as the capability of the proposed upscaled models.

As a therapeutic approach for cancer, hyperthermia involves selectively increasing the temperature of affected tissues while preserving adjacent healthy tissues. This study explores the efficacy of pristine and coated silver, copper, and gold nanostructures such as nanorods, nanospheres, and nanoellipsoids for hyperthermia. This study performed finite element analysis to assess the relative performance of pristine nanostructures and those covered with different coating thicknesses. The metallic nanostructures were enclosed within the spherical zone of malignant tissue of 500 nm size, and the ambient temperature of these nanostructures was increased to 42–46 °C. Thermal equilibrium was reached after 0.1 μs of heating in the treatment region. Compared to other geometries, the nanorods quickly attained the required temperature in the treatment region. The nanorods with 1 nm coating thickness showed a fast heating response compared to 2 and 3 nm coatings. Silver, gold, and copper nanorods reached a temperature of 44.2, 43.6, and 43.5 °C, respectively, after 0.1 μs of heating. Gold-coated silver nanorods were discovered to be most efficient at achieving the highest temperature of 44.2 °C.

Studying heavy-flavor production in high-energy heavy-ion collisions (HIC) can enhance our comprehension of parton interactions with the quark-gluon plasma (QGP) created in these collisions. Due to their significant mass, heavy quarks (charm and bottom) are mainly generated during the initial phase of HIC when hard scatterings are prevalent, and experience the entire evolution of the QGP. One way to study heavy quarks is through the measurement of electrons from heavy-flavor hadron decay, heavy-flavor electrons (HFE). In this contribution, we present the analysis of HFE at low transverse momentum (pT) in Au+Au collisions at sNN=54.4GeV using data taken in 2017 by the STAR experiment. The strong HFE suppression was already observed in the central Au+Au collisions at s NN=200GeV. Measuring heavy-flavor quark nuclear modification factors below the RHIC top energy offers new insights on the in-medium energy loss, especially the collisional energy loss which is dominant at low pT.

In this research, microcrystalline cellulose was extracted from Terminalia catappa plant leaves (TCLC) through various chemical methods such as neutralization, alkalization, slow pyrolysis, acid hydrolysis, and bleaching. Thermal analysis, scanning electron microscopy, X-ray diffraction analysis, and Fourier transform spectroscopy were employed to get more data pertaining to the isolated cellulose. The crystalline size of the isolated cellulose powder was measured to be 12.69 nm, and it exhibited a notable crystallinity index of 51.09%. Upon scanning with a scanning electron microscope, a smooth and spherical surface is observed. The differential thermogram curve demonstrates that the maximum temperature of degradation occurs at 319.33 °C. The micro-sized particles, with a predominant diameter ranging from 100 to 120 µm, are recognized utilizing ImageJ. The density of extracted cellulose is 1.426 g/cm³. Cellulose-reinforced poly-L-lactic acid biofilms were also prepared. The tensile strength (23.05 MPa) of the 2% TCLC-filled poly-L-lactic acid biofilms was higher than that of films without filler material (20.65 MPa). All the above outcomes conclude that TCLC-filled poly-L-lactic acid biofilms can be used in food packaging applications.

Metal–organic framework nanosheets (MONs) have proved themselves to be useful additives for enhancing the performance of a variety of thin film solar cell devices. However, to date only isolated examples have been reported. In this work we take advantage of the modular structure of MONs in order to resolve the effect of their different structural and optoelectronic features on the performance of organic photovoltaic (OPV) devices. Three different MONs were synthesized using different combinations of two porphyrin-based ligands meso-tetracarboxyphenyl porphyrin (TCPP) or tetrapyridyl-porphyrin (TPyP) with either zinc and/or copper ions and the effect of their addition to polythiophene-fullerene (P3HT-PC71BM) OPV devices was investigated. The power conversion efficiency (PCE) of devices was found to approximately double with the addition of MONs of Zn2(ZnTCPP) -4.7% PCE, 10.45 mA/cm² short-circuit current density (JSC), 0.69 open-circuit voltage (VOC), 64.20% fill-factor (FF), but was unchanged with the addition of Cu2(ZnTPyP) (2.6% PCE, 3.68 mA/cm²JSC, 0.59 VOC, 46.27% FF) and halved upon the addition of Cu2(CuTCPP) (1.24% PCE, 6.72 mA/cm²JSC, 0.59 VOC, 56.24% FF) compared to devices without nanosheets (2.6% PCE, 6.61 mA/cm²JSC, 0.58 VOC, 56.64% FF). Our analysis indicates that there are three different mechanisms by which MONs can influence the photoactive layer – light absorption, energy level alignment, and morphological changes. Analysis of external quantum efficiency, UV–vis and photoelectron spectroscopy data found that MONs have similar effects on light absorption and energy level alignment. However, atomic force and Raman microscopy studies revealed that the nanosheet thickness and lateral size are crucial parameters in enabling the MONs to act as beneficial additives resulting in an improvement of the OPV device performance. We anticipate this study will aid in the design of MONs and other 2D materials for future use in other light harvesting and emitting devices.