Combined Set Research Articles

Designing Multi-axis Compliant Mechanisms With Lockable Decoupled Inputs: A Tip–Tilt Case Study

Abstract This research is about designing multi-degree-of-freedom (multi-DOF) compliant mechanisms with decoupled inputs that can be independently locked/unlocked using bistable switches to achieve different combinations of DOFs. A case study mechanism achieving two decoupled rotational DOFs (tip and tilt) is designed, fabricated, and characterized. It can be triggered using two pairs of bistable switches, achieving drastically different states of torsional stiffness for each DOF in four sets of DOF combinations—no DOFs, a tip DOF, a tilt DOF, and both tip and tilt DOFs. Bistability and stiffness cancelation principles are exploited to achieve the desired changes in stiffness. Two flexure elements can be identified—the switch providing a negative stiffness and the cross-axis-flexural-pivot (CAFP) producing a positive stiffness. The mechanism is tuned to achieve static balancing, reaching a near-zero stiffness over much of its range. The pseudo-rigid body model and two-dimensional (2D) finite element model (FEM) are combined defining a fast method to dimension the system. The 3D FEM is simulated to validate the obtained results. For each DOF, the system is tested in two configurations (stiff and compliant) for three cycles over a ±10 deg rotation, achieving a stiffness reduction of around 99%. Comparable stiffness values were measured after triggering the switches more than once, repetitively reaching the required two states of stiffness, confirming the system's usability in practical applications. The positive stiffness provided by the CAFP is measured and compared to the device's overall stiffness, highlighting the stiffness cancelation concept.

Rapid Assessment Method of Buckling Stability of Bridge Pier–Cap–Pile System Under Scour Effect

A novel analytical method for evaluating the buckling stability of the pier–cap–pile system under scour effect is proposed, and furthermore, the concept of rapid assessment of bridge buckling stability based on natural frequency is innovatively introduced in this paper. First, the total potential energy function of the bridge pier–cap–pile system is established, and the closed-form solution of structural system critical buckling load under scouring is solved according to the principle of stationary potential energy. Second, the sensitivity analyses of pier height, pier width, bending stiffness reduction in pier, pile slenderness ratio, pile bending stiffness reduction, m-value of soil and structural gravity to the buckling load are carried out. On this basis, 60 sets of sensitive parameter sample combinations are extracted by the Latin Hypercube Sampling algorithm, and a proxy model relating the critical buckling load to scour depth and the sensitive parameters are then developed using the McQuarter global optimization algorithm. Finally, the regression relationship model between the critical buckling load and the natural frequency is formed by combining the proxy model and the existing relationship between the scour depth and the first-order natural frequency. The feasibility of the proposed assessment method is demonstrated by the finite element method using a bridge case study, which provides an insight and a new means of quantitatively evaluating the safety of bridges under scour effect.

Improvement of the functional layouts of multifunctional soil-cultivating sowing units

BACKGROUND: With the technology evolution, the use of combined machines and units has become more in demand. From the numerous studies that were carried out during the operation of machines of this type, it can be seen that the cost of raw materials and financial costs have been significantly reduced, and the number of other advantages has been identified as well. AIM: Improvement of the functional layouts of multifunctional tillage sowing units for a more optimal combination of structural layouts and parameters of its use. METHODS: Engineers use the method of changing working bodies designed as layouts aiming to turn the machines into the modules capable of performing various types of operations based on working conditions. Thanks to this method, sets of individual working bodies and combinations are prepared for any kind of conditions (soil, climate, etc.). In addition to the advantages, this system has a number of disadvantages. One of these is that at the factory-built modules that are part of the original basis of the unit cannot be fully adapted to environmental conditions and economic factors of production. In this regard, combination of structural layouts and selection of the necessary parameters become problem causing. It is difficult to choose necessary parameters that are capable of ensuring minimal losses and adjusting the unit to the necessary operating mode. The objects of study are the devices and production processes, the main task of which is performing tillage and sowing operations. The practical value of this study presented in the form of: building the algorithm capable of structuring the analysis and synthesis of the structural layout of the tillage-sowing unit to find the working links for various types of unit functions; finding the methods and improved combinations of working bodies, comparison of similar mechanical analogues with the original properties of systems. RESULTS: When studying the studies of Wilde, who gave a description of the combined units, as well as the studies of Runchev, who determined the generalization of the combined machines, the relevant typology of agricultural machinery was developed. In this typology, one of the most important characteristics is multifunctionality, which has developed from the need for the versatility of units and the compilation of combinations of several units. The developed technology contains a number of characteristics that are fundamental for the choice of agricultural machinery. CONCLUSION: As a result of the study, it was determined at which velocity of the unit the system is balanced.

Factors impacting target-enriched long-read sequencing of resistomes and mobilomes.

We investigated the efficiency of target-enriched long-read sequencing (TELSeq) for detecting antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) within complex matrices. We aimed to overcome limitations associated with traditional antimicrobial resistance (AMR) detection methods, including short-read shotgun metagenomics, which can lack sensitivity, specificity, and the ability to provide detailed genomic context. By combining biotinylated probe-based enrichment with long-read sequencing, we facilitated the amplification and sequencing of ARGs, eliminating the need for bioinformatic reconstruction. Our experimental design included replicates of human fecal microbiota transplant material, bovine feces, pristine prairie soil, and a mock human gut microbial community, allowing us to examine variables including genomic DNA input and probe set composition. Our findings demonstrated that TELSeq markedly improves the detection rates of ARGs and MGEs compared to traditional sequencing methods, underlining its potential for accurate AMR monitoring. A key insight from our research is the importance of incorporating mobilome profiles to better predict the transferability of ARGs within microbial communities, prompting a recommendation for the use of combined ARG-MGE probe sets for future studies. We also reveal limitations for ARG detection from low-input workflows, and describe the next steps for ongoing protocol refinement to minimize technical variability and expand utility in clinical and public health settings. This effort is part of our broader commitment to advancing methodologies that address the global challenge of AMR.

СТРАТЕГІЧНІ АЛЬТЕРНАТИВИ ВІДНОВЛЕННЯ КОНКУРЕНТОСПРОМОЖНОСТІ СФЕРИ ГОСТИННОСТІ УКРАЇНИ

Introduction. The field of hospitality is the basis for the development of the economies of many countries of the world. Ukraine is no exception. Although the full-scale invasion of the territory of Ukraine left its mark on this sector of the economy, causing great damage to it, the global situation has not changed and its development remains one of the priorities, especially in the context of Ukraine's vector for European integration. However, in today's conditions, appropriate strategies and tools for their implementation are necessary to preserve and restore the competitiveness of the hospitality industry. The purpose of the article: to justify strategic alternatives for restoring the competitiveness of the hospitality sector of Ukraine Results. The article substantiates that since the field of hospitality is a complex socio-ecological-economic system, which is characterized by significant regional differences, it is advisable to apply combined strategic sets formed on the basis of a hierarchical approach. The application of three levels of strategic alternatives is substantiated: Level I as a market positioning strategy (globalization, deep market penetration, adaptation, anticipatory development); Level II as strategic directions for ensuring competitive advantages (creating new competitive advantages, increasing competitive advantages, maintaining a competitive position, restoring lost competitive advantages); Level III as typical competitive strategies (diversification, differentiation, focus, specialization, cost leadership). The results of the study were used to justify the correlation of the specified strategies with the identified trends in the development of the hospitality industry in the world and in Ukraine. The sets of alternative strategies will be identified in the coordinates "Level of competitive advantages" / "Level of competitiveness", according to which the regions of Ukraine will be grouped and the specifics of the implementation of each of the sets will be determined. In the conditions of the current situation, the proposals are characterized by a high level of speculation, but they can serve as a reference point for the development of the hospitality industry in the regions of Ukraine, the basis of regional programs and strategies, which is a perspective for further research. Conclusions. A strategic approach to restoring the competitiveness of the hospitality sector of Ukraine ensures the prediction and achievement of expected results, obtaining competitive advantages for the long-term perspective, is the basis for the development of regional strategies and programs, which is of practical importance.

Unsupervised representation learning of Kohn–Sham states and consequences for downstream predictions of many-body effects

Representation learning for the electronic structure problem is a major challenge of machine learning in computational condensed matter and materials physics. Within quantum mechanical first principles approaches, density functional theory (DFT) is the preeminent tool for understanding electronic structure, and the high-dimensional DFT wavefunctions serve as building blocks for downstream calculations of correlated many-body excitations and related physical observables. Here, we use variational autoencoders (VAE) for the unsupervised learning of DFT wavefunctions and show that these wavefunctions lie in a low-dimensional manifold within latent space. Our model autonomously determines the optimal representation of the electronic structure, avoiding limitations due to manual feature engineering. To demonstrate the utility of the latent space representation of the DFT wavefunction, we use it for the supervised training of neural networks (NN) for downstream prediction of quasiparticle bandstructures within the GW formalism. The GW prediction achieves a low error of 0.11 eV for a combined test set of two-dimensional metals and semiconductors, suggesting that the latent space representation captures key physical information from the original data. Finally, we explore the generative ability and interpretability of the VAE representation.

Model-driven development for functional correctness of avionics systems: a verification framework for SysML specifications

AbstractCurrently, the most widespread software quality assurance methods in the avionics domain are semi-automated reviews and testing. However, their effort grows disproportionately to the size of the system under development. Also, these methods cannot achieve exhaustive coverage due to the complexity of today’s avionics systems and their potentially infinite set of combinations of possible inputs and system states. Furthermore, the later software issues are detected in the development process, the more expensive it is to fix them. To overcome these issues, a model-driven verification approach for modeling and analyzing avionics systems in early phases of the development is presented. To this end, semantics is given to SysML v2 models by a mapping to a theorem prover encoding. The development of a dedicated SysML v2 profile supporting event-driven data flow specifications, the encoding of corresponding structures in the theorem prover Isabelle, and a generator creating theorems from SysML v2 models are presented. The approach is evaluated by formally proving a representative liveness property of a hierarchical system model from the avionics domain. Since liveness properties can be negated only by infinite data sequences and thus cannot be covered exhaustively by testing, this case study demonstrates the added value for meeting typical safety requirements in the avionics domain. The results can be transferred from avionics to other domains, as well.

Targeting the Sirtuin–1/PPAR–Gamma Axis, RAGE/HMGB1/NF-κB Signaling, and the Mitochondrial Functions by Canagliflozin Augments the Protective Effects of Levodopa/Carbidopa in Rotenone-Induced Parkinson’s Disease

Background and Objectives: Parkinson’s disease (PD) is a pathological state characterized by a combined set of abnormal movements including slow motion, resting tremors, profound stiffness of skeletal muscles, or obvious abnormalities in posture and gait, together with significant behavioral changes. Until now, no single therapeutic modality was able to provide a complete cure for PD. This work was a trial to assess the immunomodulatory effects of canagliflozin with or without levodopa/carbidopa on rotenone-induced parkinsonism in Balb/c mice. Materials and Methods: In a mouse model of PD, the effect of canagliflozin with or without levodopa/carbidopa was assessed at the behavioral, biochemical, and histopathological levels. Results: The combination of levodopa/carbidopa and canagliflozin significantly mitigated the changes induced by rotenone administration regarding the behavioral tests, striatal dopamine, antioxidant status, Nrf2 content, SIRT–1/PPAR–gamma axis, RAGE/HMGB1/NF-κB signaling, and mitochondrial dysfunction; abrogated the neuroinflammatory responses, and alleviated the histomorphologic changes induced by rotenone administration relative to the groups that received either levodopa/carbidopa or canagliflozin alone. Conclusions: Canagliflozin may represent a new adjuvant therapeutic agent that may add value to the combatting effects of levodopa/carbidopa against the pathological effects of PD.

Comparative Mitogenomics Analysis Revealed Evolutionary Divergence among Purpureocillium Species and Gene Arrangement and Intron Dynamics of Ophiocordycipitaceae.

The species of Purpureocillium are cosmopolitan and multitrophic fungi that can infect a wide range of invertebrate hosts. This study reports the mitogenome of P. atypicola, a specialized spider pathogenic fungus. The 112,465 bp mitogenome encoded genes typically found in fungal mitogenomes, and a total of 52 introns inserted into seven genes. A comparison with three other Purpureocillium species revealed significant differences in length and intron number, primarily due to intron variation; however, there was no dynamic variation in the introns of the cox1 gene within the same species of the Purpureocillium genus. Different mitochondrial protein-coding genes showed variable degrees of genetic differentiation among these species, but they were all under purifying selection. Additionally, frequent intron loss or gain events were detected to have occurred during the evolution of the Ophiocordycipitaceae mitogenomes, yet the gene arrangement remains conserved. A phylogenetic analysis of the combined mitochondrial gene set gave identical and well-supported tree topologies. The estimated age of the crown of Ophiocordycipitaceae and Purpureocillium were around the Early Cretaceous period (127 Mya) and Late Cretaceous period (83 Mya), respectively. The results of this study advance our understanding of the genomics, evolution, and taxonomy of this important fungal group.

Path-filtering in path-integral simulations of open quantum systems using GFlowNets.

An important class of methods for modeling dynamics in open quantum systems is based on the well-known influence functional (IF) approach to solving path-integral equations of motion. Within this paradigm, path-filtering schemes based on the removal of IF elements that fall below a certain threshold aim to reduce the effort needed to calculate and store the influence functional, making very challenging simulations possible. A filtering protocol of this type is considered acceptable as long as the simulation remains mathematically stable. This, however, does not guarantee that the approximated dynamics preserve the physics of the simulated process. In this paper, we explore the possibility of training Generative Flow Networks (GFlowNets) to produce filtering protocols while optimizing for mathematical stability and for physical accuracy. Trained using the trajectory balance objective, the model produces sets of paths to be added to a truncated initial set; it is rewarded if the combined set of paths gives rise to solutions in which the trace of the density matrix is conserved, the populations remain real, and the dynamics approach the exact reference. Using a simple two-level system coupled to a dissipative reservoir, we perform proof-of-concept simulations and demonstrate the elegant and surprising filtering solutions proposed by the GFlowNet.

PM2.5 prediction based on modified whale optimization algorithm and support vector regression

In order to obtain the pattern of variation of PM2.5concentrations in the atmosphere in Nanchang City, we build a Support Vector Regression(SVR) with modified Whale Optimization Algorithm(WOA) hybrid model (namely mWOA-SVR model) that can predict the PM2.5concentration. Firstly, according to the Pearson correlation coefficient (PCC) method to examine the dynamic relationship between air pollutants and meteorological factors together with them, PM10, SO2and CO were selected as air pollutant concentration characteristics, while daily maximum and minimum temperatures, and wind power levels were selected as meteorological characteristics; then, using modified WOA algorithm for parameter selection of SVR model, four sets of better parameter combinations were found; finally, the mWOA-SVR model was built by the four sets parameters to predict PM2.5concentration. The results show that the prediction accuracy of mixed mWOA-SVR model with pollutant concentration plus weather factors as the feature was higher than single pollutant concentration.

An Antiferroelectric‐Coated Metal Foam Infiltrated with Liquid Metal as a Dielectric Capacitor

Nickel metal foams serve as both a substrate and bottom electrode for a dielectric capacitor using atomic‐layer deposition (ALD) and a eutectic gallium–indium (EGaIn) liquid metal (LQM) counter electrode. The conformal dielectric has a composition of 6.25% Al–HfO2 in the antiferroelectric phase, confirmed with polarization versus electric field measurements. Liquid EGaIn is pressure‐infiltrated within the coated foams to form the dielectric capacitor. Capacitances up to 4 μF are realized. Calorimetry of the infiltrated capacitor shows a 60 J g−1 latent heat upon melting a frozen EGaIn electrode, suggesting that the phase change can alleviate thermal deviations from pulsed power capacitor operation. Infiltrated capacitors are also shown to survive bending and freeze–thaw cycles. The metal foam–ALD dielectric–LQM capacitor shows a combined set of thermal and electrical properties not available in other classes of capacitors.

Oncology Combination Drug Development Strategies for Project Optimus.

The Project Optimus initiative from the FDA introduced a new dose optimization and selection paradigm in oncology drug development. The FDA has outlined approaches to dose optimization for single agents, but multiple oncology drugs are being developed for use in combination with other therapies. Dose optimization in the context of combination drug development is complex and requires a case-by-case approach. It necessitates commitment to the totality of available evidence, leveraging all relevant data on mechanism of action, nonclinical and clinical pharmacology, safety, and principles of model-informed drug development. In this article, we outline key considerations for sponsors and investigators pursuing dose optimization with combinatorial regimens. We illustrate important strategies for dose optimization in the combination setting using a range of hypothetical case examples that represent typical drug development scenarios. Close discussions and collaboration with regulators regarding the optimal approaches to these scenarios will continue to be critical.

Study on the Properties of Sinusoidal Micro-Textured Ball End Milling Cutter for Milling Titanium Alloy

To improve the cutting performance when cutting hard alloys and achieve reasonable optimization of micro-texture parameters, this paper proposes a sinusoidal micro-textured tool, with four parameters set as micro-textured spacing, period, width, and amplitude. Establish three-dimensional models of non-micro-textured and micro-textured milling tools and simulate the milling process using finite element simulation. Study the effects of milling force and milling temperature on tool performance. Prepare micro-textured milling tools for orthogonal experiments, analyse the effects of milling force and the surface roughness of a titanium alloy workpiece, and study the impact of different micro-textured parameters on milling tool performance. Obtain the parameters that have the greatest impact on milling tool performance, and then use genetic algorithm to optimize three sets of parameter combinations. Use the optimized parameters to prepare milling tools for comparative experiments, and then determine the optimal parameter combination. The research results indicate that micro-textured tools can effectively improve the milling performance of the tool, and the spacing between sinusoidal micro-textures has the greatest effect on improving the milling performance of the tool. When the period of sinusoidal micro-texture is 2.87 and the amplitude is 25.13 μm, width is 79.89 μm, and spacing is 134.54 μm, the milling performance of the tool is optimal.

Multi-site DNA methylation alterations of peripheral blood mononuclear cells serve as novel biomarkers for the diagnosis of AIS/stage I lung adenocarcinoma: A multi-center cohort study.

Early diagnosis remains an obstacle for improving the outcome of lung adenocarcinoma (LUAD). DNA methylation changes in peripheral blood mononuclear cells (PBMCs) could reflect immune response to tumorigenesis, providing the theoretical basis for early cancer diagnosis based on immune cell profiling. This multi-center study evaluated the DNA methylation patterns based on PBMCs samples from 1115 individuals at nine medical centers. Genome-wide DNA methylation profiling of PBMCs in a discovery cohort (35 LUAD patients and 50 healthy controls) was performed using Illumina 850K microarray. Candidate differentially methylated CpG positions (DMPs) were selected and validated in a two-step DMPs screening cohort (65 LUAD patients and 80 healthy controls) by pyrosequencing and multiple target region methylation enrichment sequencing (MTRMES). Then, an early LUAD Diagnostic Panel (LDP score) based on multi-site methylation-specific chip-based digital PCR was constructed in a training set and then confirmed in a validation set from the LDP score development cohort (389 AIS/stage I LUAD patients and 293 healthy controls). Besides, we included 157 other cancer patients, including 52 gastric cancer (GC) patients, 50 breast cancer (BC) patients, and 55 colorectal cancer (CRC) patients to assess the specificity of LDP score. In addition, we also evaluated the early warning ability of LDP score for LUAD in a prospective cohort (46 people who were at high-risk of developing LC). A total of 1415 LUAD-specific DMPs were identified. Then, six DMPs were selected for validation and three DMPs were finally verified. The LDP score was constructed by combining the three DMPs, age, and gender, and showed an AUC of 0.916, sensitivity of 88.17%, and specificity of 80.20% in combined set, outperforming traditional methods, such as CEA and CT (detection rate: 87.79% vs. 4.69%; 87.79% vs. 35.21%). This diagnostic performance was confirmed in sub-types of LUAD with clinical challenges, such as 6-20mm LUAD (AUC: 0.914, 95%CI: 0.889-0.934) and ground-glass nodules (AUC: 0.916, 95%CI: 0.889-0.938). Importantly, our LDP score had significant improvement in terms of selecting high-risk individuals who should receive low-dose computed tomography (87.80% vs. 9.28%). Remarkably, LDP score could predict LUAD around two years before clinical diagnosis in our prospective cohort. The novel developed LDP score represented a convenient and effective assay for the detection of AIS/stage I LUAD with high sensitivity and specificity, and had demonstrated unique advantages over traditional detection methods.

Characterization of regulated cancer cell death pathways induced by the different modalities of non-thermal plasma treatment

Non-thermal plasma (NTP) has shown promising anti-cancer effects, but there is still limited knowledge about the underlying cell death mechanisms induced by NTP and inherent differences between NTP treatment modalities. This study aimed to investigate four major regulated cell death (RCD) pathways, namely apoptosis, pyroptosis, necroptosis, and ferroptosis, in melanoma cancer cells following NTP treatment, and to provide an overview of molecular mechanistic differences between direct and indirect NTP treatment modalities. To discriminate which cell death pathways were triggered after treatment, specific inhibitors of apoptosis, pyroptosis, necroptosis, and ferroptosis were evaluated. RCD-specific molecular pathways were further investigated to validate the findings with inhibitors. Both direct and indirect NTP treatment increased caspase 3/7 and annexin V expression, indicative of apoptosis, as well as lipid peroxidation, characteristic of ferroptosis. Pyroptosis, on the other hand, was only induced by direct NTP treatment, evidenced by increased caspase 1 activity, whereas necroptosis was stimulated in a cell line-dependent manner. These findings highlight the molecular differences and implications of direct and indirect NTP treatment for cancer therapy. Altogether, activation of multiple cell death pathways offers advantages in minimizing treatment resistance and enhancing therapeutic efficacy, particularly in a combination setting. Understanding the mechanisms underlying NTP-induced RCD will enable the development of strategic combination therapies targeting multiple pathways to achieve cancer lethality.

Semantics and Micro-Parametric Variation: The Simple Future in Ibero-Romance

Cross-linguistic variation in future-tense sentences has been extensively documented in the literature. Despite this diversity, there is a prevailing sense that a common core meaning exists and that the various interpretations in each language are connected. To account for both the similarities and the differences, Escandell-Vidal proposes that the meaning encoded by verbal tenses can be analysed into two components: i) core meaning; and ii) semantic micro-parameters (additional fine-grained constraints on specific categories of the core meaning that account for subtle differences between related languages or dialects). The purpose of this paper is twofold. On the descriptive side, it aims to refine the approach in terms of microparametric distinctions by suggesting some modifications. On the theoretical side, it seeks to offer a simpler and more powerful tool to account for interlinguistic variation by restricting its range to a limited set of predictable combinations.

Проблемы поиска и преследования беспилотных летательных аппаратов с использованием теоретико-игрового подхода

Currently, the application of mathematical modeling theory is widely used in various fields and, among other things, can be used to prevent illegal actions. This study examines scenarios involving a single pursuer tracking a single evader, as well as situations involving multiple pursuers pursuing multiple evaders. The authors formulate this problem as a search and pursuit problem for four-rotor unmanned aerial vehicles (UAVs) or quadcopters. The solution to the problem is based on game theory, as it provides a mathematical framework for modeling and studying strategic interactions involving multiple decision makers. The authors consider a game where the set of strategies of the runner is the set of possible combinations of speeds and directions of his movement, and the set of strategies of the pursuer is the set of all possible permutations of the elements of his speeds. The matrix of the resulting game consists of elements that are the time of capture. A mathematical problem on the optimal assignments of searching and pursuing unmanned aerial vehicles is formulated and solved. Purpose: optimizing the effectiveness of strategies for detecting and capturing four-rotor unmanned aerial vehicles (quadcopters). Methods: methods of mathematical modeling, game theory apparatus, Hungarian method of solving the problem of assignments, decision theory, the principle of dynamic programming, the Maple package for solving examples were used. Results: In order to fulfill the conditions for solving the problem of optimal assignments, it is necessary and sufficient that it is balanced. This assignment problem can be balanced by entering the required number of fictitious boats or escaping boats. After that, it is possible to formulate and solve the dual problem of optimal appointments. The resulting game can be solved by any method of solving matrix games. In this way, it is possible to determine the policy of harassment and search between drones. Practical importance: All escaped quadcopter UAVs can be chased and successfully intercepted using the developed models. Examples of the study of mathematical models using the Maple software package are given.

Expression levels and stoichiometry of Hnf1β, Emx2, Pax8 and Hnf4 influence direct reprogramming of induced renal tubular epithelial cells

Generation of induced renal epithelial cells (iRECs) from fibroblasts offers great opportunities for renal disease modeling and kidney regeneration. However, the low reprogramming efficiency of the current approach to generate iRECs has hindered potential therapeutic application and regenerative approach. This could be in part attributed to heterogeneous and unbalanced expression of reprogramming factors (RFs) Hnf1β (H1), Emx2 (E), Pax8 (P), and Hnf4α (H4) in transduced fibroblasts. Here, we establish an advanced retroviral vector system that expresses H1, E, P, and H4 in high levels and distinct ratios from bicistronic transcripts separated by P2A. Mouse embryonic fibroblasts (MEFs) harboring Cdh16-Cre; mT/mG allele are utilized to conduct iREC reprogramming via directly monitoring single cell fate conversion. Three sets of bicistronic RF combinations including H1E/H4P, H1H4/EP, and H1P/H4E have been generated to induce iREC reprogramming. Each of the RF combinations gives rise to distinct H1, E, P, and H4 expression levels and different reprogramming efficiencies. The desired H1E/H4P combination that results in high expression levels of RFs with balanced stoichiometry. substantially enhances the efficiency and quality of iRECs compared with transduction of separate H1, E, P, and H4 lentiviruses. We find that H1E/H4P-induced iRECs exhibit the superior features of renal tubular epithelial cells, as evidenced by expressing renal tubular-specific genes, possessing endocytotic arrogation activity and assembling into tubules along decellularized kidney scaffolds. This study establishes H1E/H4P cassette as a valuable platform for future iREC studies and regenerative medicine.

Detection of Thymoma Disease Using mRMR Feature Selection and Transformer Models

Background: Thymoma is a tumor that originates in the thymus gland, a part of the human body located behind the breastbone. It is a malignant disease that is rare in children but more common in adults and usually does not spread outside the thymus. The exact cause of thymic disease is not known, but it is thought to be more common in people infected with the EBV virus at an early age. Various surgical methods are used in clinical settings to treat thymoma. Expert opinion is very important in the diagnosis of the disease. Recently, next-generation technologies have become increasingly important in disease detection. Today’s early detection systems already use transformer models that are open to technological advances. Methods: What makes this study different is the use of transformer models instead of traditional deep learning models. The data used in this study were obtained from patients undergoing treatment at Fırat University, Department of Thoracic Surgery. The dataset consisted of two types of classes: thymoma disease images and non-thymoma disease images. The proposed approach consists of preprocessing, model training, feature extraction, feature set fusion between models, efficient feature selection, and classification. In the preprocessing step, unnecessary regions of the images were cropped, and the region of interest (ROI) technique was applied. Four types of transformer models (Deit3, Maxvit, Swin, and ViT) were used for model training. As a result of the training of the models, the feature sets obtained from the best three models were merged between the models (Deit3 and Swin, Deit3 and ViT, Deit3 and ViT, Swin and ViT, and Deit3 and Swin and ViT). The combined feature set of the model (Deit3 and ViT) that gave the best performance with fewer features was analyzed using the mRMR feature selection method. The SVM method was used in the classification process. Results: With the mRMR feature selection method, 100% overall accuracy was achieved with feature sets containing fewer features. The cross-validation technique was used to verify the overall accuracy of the proposed approach and 99.22% overall accuracy was achieved in the analysis with this technique. Conclusions: These findings emphasize the added value of the proposed approach in the detection of thymoma.