Selection Mechanism Research Articles

In Vitro Evaluation of the Safety and Efficacy of Cibisatamab Using Adult Stem Cell-Derived Organoids and Colorectal Cancer Spheroids.

Objectives: Developing ex vivo models that replicate immune-tumor interactions with high fidelity is essential for advancing immunotherapy research, as traditional two-dimensional in vitro systems often lack the complexity required to fully represent these interactions. Methods: In this study, we establish a comprehensive 3D redirect lysis (3D-RDL) assay using colorectal cancer spheroids and adult stem cell-derived, healthy human organoids to evaluate the efficacy and safety profile of Cibisatamab, a bispecific antibody targeting carcinoembryonic antigens (CEAs) on cancer cells and CD3 on T cells. This model allows us to assess cytotoxic activity and immune responses, capturing variations in therapeutic response not observable in simpler systems. Our model integrates live imaging and cytotoxicity analyses to enable precise, real-time tracking of antibody effects on CEA-expressing tumor cells compared to healthy cells. Additionally, by standardizing effector-to-target cell ratios in each co-culture, we establish a reproducible workflow that enhances data accuracy and comparability across assays. Flow cytometry and Granzyme B release profiling further allow us to characterize immune cell activation, revealing distinct T cell activation markers and Granzyme B release patterns tied to Cibisatamab treatment. Results: Our results show that Cibisatamab effectively induces cell death in cancer spheroids with high CEA expression while being dose-dependent on target, off-tumor binding and killing on non-cancerous cells of healthy organoids with intermediate CEA levels. This highlights our model's potential to predict clinical immunotherapy outcomes, capturing complex responses like immune activation, therapeutic selectivity, and potential resistance mechanisms. Conclusions: These findings underscore the utility of our model as a reliable, physiologically relevant tool for screening new immunotherapies and advancing our understanding of tumor-immune dynamics.

Spatial sorting and selection within urban agglomerations: a tripartite evolutionary game model approach

Urban agglomerations play a pivotal role in regional economic growth by fostering industrial clustering and attracting firms, thereby enhancing urban productivity and efficiency. However, existing research on spatial sorting and selection in urban settings-primarily based on quantitative spatial models-often overlooks the dynamic strategic adaptations of firms with varying skill levels. This gap leads to an incomplete understanding of how firms interact and adjust their spatial positioning over time in response to evolving urban economic conditions. To address this, we develop a tripartite evolutionary game model to investigate the spatial sorting and selection mechanisms among high-, medium-, and low-skill firms in urban settings. The model simulates firms’ strategic choices-whether to enter or avoid central cities-under varying initial conditions, such as participation willingness, skill disparities, and urban costs. Extensive simulations reveal that although these factors influence the process and equilibrium rates, they do not change the ultimate strategic outcome: high-skill firms consistently gravitate toward central cities, whereas low-skill firms tend to remain in peripheral areas, especially when urban costs are high. These findings provide significant insights for urban policy. The concentration of high-skill firms in large cities poses challenges for smaller cities attempting to attract these industries, potentially exacerbating regional disparities. Policymakers are thus encouraged to prioritize firm quality over quantity to drive sustained economic growth across regions. Additionally, reforming restrictive household registration policies could reduce entry barriers for high-skill labor, improve urban resource allocation, and facilitate more balanced development. The ongoing interaction between spatial sorting and selection fosters agglomeration economies in urban centers, underscoring the need for policy frameworks that accommodate firms’ diverse needs and skill levels across the urban landscape.

Different fates between extracellular and intracellular antimicrobial resistome in full-scale activated sludge and membrane bioreactor processes.

Treated effluent of wastewater treatment plants (WWTPs) are major sources of extracellular antimicrobial resistance genes (eARGs) into aquatic environments. This study aimed to clarify the fate and origins of eARGs from influent to treated effluent at a full-scale WWTP. The compositions of eARG and intracellular ARG (iARG) were acquired via shotgun metagenomic sequencing in influent wastewater, activated sludge, and treated effluent of the target WWTP, where identical wastewater was treated by conventional activated sludge (CAS) and membrane bioreactor (MBR) processes. The proportion of eARGs to iARGs increased from influent to effluent in both processes, reaching almost half of the total ARG. Most eARGs in influent were associated with clinically important antimicrobials, whereas eARGs in sludge and effluent were dominated by aminoglycoside resistance genes of aadA and APH variants. Although the eARGs composition in influent wastewater mirrored that of iARGs, a substantial shift occurred in activated sludge and effluent, highlighting the presence of distinct dissemination and reduction mechanisms between eARGs and iARGs. Notably, the origin of eARGs in treated effluent was mainly iARGs in the effluent rather than the carryover of eARG from activated sludge, which were substantially reduced in MBR, compared to CAS. Consequently, these differences in selective mechanisms led to different fates between eARG and iARG during wastewater treatment.

A bi-subpopulation coevolutionary immune algorithm for multi-objective combinatorial optimization in multi-UAV task allocation

With the development of Unmanned Aerial Vehicle (UAV) technology towards multi-UAV and UAV swarm, multi-UAV cooperative task allocation has more and more influence on the success or failure of UAV missions. From the operational research point of view, such problems belong to high-dimensional combinatorial optimization problems, which makes the solving process face many challenges. One is that the discrete and high-dimensional decision variables make the quality of the solution obtained with acceptable time not guaranteed. Second, the desired solution of real missions often needs to satisfy multiple objective functions, or a set of solutions for decision-making. Therefore, this paper constructs a Multi-objective Combinatorial Optimization in Multi-UAV Task Allocation Problem (MCOTAP) model, and proposes a Bi-subpopulation Coevolutionary Immune Algorithm (BCIA). The two coevolutionary mechanisms improve the lower limit of population diversity, and the evolutionary strategy pool integrating multiple strategies and the adaptive strategy selection mechanism enhance the local search ability in the late evolution. In the experiments, BCIA competes fairly with the mainstream multi-objective evolutionary algorithms (MOEAs), multi-objective immune algorithms (MOIAs) and the recently proposed multi-UAV mission planning algorithms. The experimental results on different test problems (including several multi-objective combinatorial optimization benchmark problems and the proposed MCOTAP model) show that BCIA has superior performance in solving multi-objective combinatorial optimization problems (MCOPs). At the same time, the effectiveness of each design component of BCIA has been comprehensively verified in the ablation study.

Equilibrium distance from long-range dune interactions

Abstract. Flow perturbations induced by dune topography affect sediment transport locally but can also be felt over long distances, altering the dynamics of isolated neighbouring dunes downstream. In order to work under optimal conditions that eliminate transverse flow components, collisions, and mass exchange between dunes, we study here these long-range interactions using a 2D numerical model where two equal-sized dunes lying on a non-erodible bed are exposed to a symmetric reversing flow. Depending on the initial spacing, dunes either attract or repel each other to eventually converge towards a steady-state spacing. This equilibrium distance decreases with flow strength and increases with the period of flow reorientation and dune size. It is mainly controlled by the reversing dune shape and the structure of the turbulent wake it generates, which continuously modulates the mean shear stress on the downstream dune. Under multi-directional wind regimes, these long-range flow perturbations offer an alternative mechanism for wavelength selection in linear dune fields with non-erodible interdune areas. Within these dune fields, estimates of mean shear stress could be used to assess the relative migration rate and the state of attraction or repulsion between neighbouring dunes.

The stereoselective bioactivity and mechanism of indoxacarb against Spodoptera frugiperda.

Indoxacarb, a type of chiral pesticide, is used to control Lepidoptera insects. Most studies had focused on the environmental behavior and selective toxicity of indoxacarb enantiomers, and the mechanism behind its selective biological activity against target organisms is not well understood. Spodoptera frugiperda was selected as the target insect. The lethal concentrations (96 h) of indoxacarb enantiomers on S. frugiperda were 2.61 mg/kg (S-indoxacarb) and 463.52 mg/kg (R-indoxacarb). S-Indoxacarb resulted in stronger oxidative damage to S. frugiperda than R-indoxacarb, and catalase and malondialdehyde were upregulated by 40.46% and 68.64% respectively after treatment with S-indoxacarb. Furthermore, cytochrome P450 and carboxylesterase were activated by S-indoxacarb, increasing by 39.62% and 63.68% respectively. Decarbomethoxyllated JW062 (DCJW), a metabolite of indoxacarb, has insecticidal activity. The concentration of DCJW in the S-indoxacarb treatment group was 2.73 times that in the R-indoxacarb treatment group. Molecular docking results demonstrated that S-indoxacarb could spontaneously bind to metabolic enzymes and be metabolized. Enantiomeric bioactivity of indoxacarb enantiomers against on S. frugiperda was observed. S-Indoxacarb demonstrated remarkable insecticidal efficacy. Upon ingestion by S. frugiperda, it induced oxidative damage. Furthermore, S-indoxacarb was metabolized to DCJW, which has a significant role in its insecticidal properties. The selective bioactivity of indoxacarb enantiomers in S. frugiperda might be attributed to the enantiomeric metabolites. These findings offer a new perspective on the selective mechanisms of chiral pesticides. © 2025 Society of Chemical Industry.

A vision-inertial interaction-based autonomous UAV positioning algorithm

Abstract In wartime scenarios where global navigation satellite system (GNSS) may be compromised, the cumulative errors associated with inertial navigation systems (INSs) can lead to significant positional deviations during long-distance navigation of drones. To address this issue, this study proposes an innovative vision-inertial interactive autonomous positioning algorithm that integrates visual positioning with inertial measurement unit-based methods, aiming to achieve enhanced system robustness and optimal positioning accuracy. The algorithm first implements an adaptive tile map level selection mechanism based on prior positional information from INS and onboard barometric pressure data, thereby mitigating the impact of inconsistent image scales. Subsequently, the proposed feature point extraction algorithm (Super Point V) effectively filters out invalid and interfering feature points from aerial images and tile maps. Finally, a novel matching mechanism for map expansion based on direction weights is employed to facilitate image matching and positioning, ensuring real-time accuracy and precision. Experimental results across various terrain conditions demonstrate that this approach not only enables accurate real-time computation of latitude and longitude but also effectively corrects the accumulated positioning errors of INS, achieving an average positioning accuracy error of only 4.94 m, comparable to that of conventional civilian GNSS, while maintaining excellent robustness.

Artificial Visual System for Stereo-Orientation Recognition Based on Hubel-Wiesel Model.

Stereo-orientation selectivity is a fundamental neural mechanism in the brain that plays a crucial role in perception. However, due to the recognition process of high-dimensional spatial information commonly occurring in high-order cortex, we still know little about the mechanisms underlying stereo-orientation selectivity and lack a modeling strategy. A classical explanation for the mechanism of two-dimensional orientation selectivity within the primary visual cortex is based on the Hubel-Wiesel model, a cascading neural connection structure. The local-to-global information aggregation thought within the Hubel-Wiesel model not only contributed to neurophysiology but also inspired the development of computer vision fields. In this paper, we provide a clear and efficient conceptual understanding of stereo-orientation selectivity and propose a quantitative explanation for its generation based on the thought of local-to-global information aggregation within the Hubel-Wiesel model and develop an artificial visual system (AVS) for stereo-orientation recognition. Our approach involves modeling depth selective cells to receive depth information, simple stereo-orientation selective cells for combining distinct depth information inputs to generate various local stereo-orientation selectivity, and complex stereo-orientation selective cells responsible for integrating the same local information to generate global stereo-orientation selectivity. Simulation results demonstrate that our AVS is effective in stereo-orientation recognition and robust against spatial noise jitters. AVS achieved an overall over 90% accuracy on noise data in orientation recognition tasks, significantly outperforming deep models. In addition, the AVS contributes to enhancing deep models' performance, robustness, and stability in 3D object recognition tasks. Notably, AVS enhanced the TransNeXt model in improving its overall performance from 73.1% to 97.2% on the 3D-MNIST dataset and from 56.1% to 86.4% on the 3D-Fashion-MNIST dataset. Our explanation for the generation of stereo-orientation selectivity offers a reliable, explainable, and robust approach for extracting spatial features and provides a straightforward modeling method for neural computation research.

Electrospinning for Biomedical Applications: An Overview of Material Fabrication Techniques

This review examines recent methodologies for fabricating nonwoven polymer materials through electrospinning, focusing on the underlying physical principles, including the effects of external parameters, experimental conditions, material selection, and primary operational mechanisms. Potential applications of electrospun polymer matrices in tissue engineering are analyzed, with particular emphasis on their utility in biomedical contexts. Key challenges in incorporating new materials into biomedical devices are discussed, along with recent advances in electrospinning techniques driving innovation in this field.

Legal forms of ensuring personnel security in the personnel management system of public agencies

Relevance. The relevance lies in the need for a comprehensive study of the legal forms of ensuring security in the administrative and public sphere: a competence-based approach to personnel and career modeling, ethics of official behavior, reasonable state and public control over certain types of permitted activities of Russian officials, support for the social status of an employee.Purpose. The purpose is a legal analysis of existing areas of personnel policy to prevent occupational risks within the framework of security, including the identification of positive examples of the functioning of similar foreign institutions.Objective. The objectives are to summarize scientific positions on the methodology of ensuring safety in the personnel management system; consideration of legislative innovations in the regulation of the sphere of labor; identification of risks of illegal and unethical behavior of officials at various stages of professional activity, identification of legal ways to eliminate them; assessment of foreign experience in the field of personnel security.Methodology. The use of formal-dogmatic, comparative-legal and other scientific methods made it possible to identify a system of measures taken by administrative and public structures in order to overcome threats to the high-quality and objective performance of official duties by employees of public agencies.Results. The results are in the importance of transforming the personnel selection mechanism (the preliminary stage of the process of filling a public position), eliminating the shortcomings of the existing practice of competitive procedures, preventing illegal, unethical behavior of employees. Elements of novelty are present in the proposal to develop measures to regulate the initial stage of personnel work in civil institutions, which is currently limited by formal requirements for candidates and regulated by various departmental acts.Conclusion. It is concluded that it is necessary to improve the procedures for the admission and distribution of personnel to public agencies in the Russian Federation, including improving a number of competitive procedures based on anonymity by analogy with foreign experience.

Toward secure industrial internet of behaviours: a federated learning-based lightweight human behaviour recognition method with selective state space models

Human behaviour recognition is one of the most fundamental tasks in Industrial Internet of Behaviour (IIoB) and is crucial for the safe and reliable IIoB. Existing methods lacks adaptability and transferability. In addition, there is a data isolation problem among different users. Therefore, there is an urgent requirement to construct a secure and adaptive human behaviour recognition model in IIoB without violating the privacy of users. Mamba, a structured state space model that integrates a selection mechanism and a scan module, is used for time series modelling tasks. To tackle the aforementioned problems, an Federated Learning-based lightweight human behaviour recognition model with selective state space models is proposed. First, we design a human behaviour recognition model integrating Mamba and residual structure to achieve lightweight and secure human behaviour modelling. In addition, considering data privacy and training efficiency, a decentralised dynamic FL framework is designed to achieve lightweight and secure model collaborative training, including: initial selection of source users, model aggregation strategy based on dynamic weighting, and fine-tuning module based on small-sample data, to improve the training efficiency of the model and the accuracy of human behaviour recognition. Extensive experiments are conducted to prove the superior performance of the proposed method.

Effective removal of strontium from wastewater using Co-doped layered sodium vanadosilicate.

The effective removal of strontium (Sr) from radioactive wastewater is essential for human health and ecological sustainability. However, due to the existence of a large number of coexisting ions, the selective removal of Sr2+ from it remains a significant challenge. Herein, three novel metal-doped sodium vanadosilicates were developed by structural regulation. It was found that Co-doping can not only significantly reduce the dissolution loss of vanadosilicate (NaVOSi) from the adsorbent in extreme environments by adjusting the orbital energy distribution, energy band structure, bond length, and bond energy of sodium vanadosilicate crystals, but also further enhance the adsorption performance by reducing its zeta potentials and agglomeration phenomenon. The maximum adsorption capacity of the developed adsorbent (Co-NaVOSi) was up to 319.10 mg·g-1 within 5 min. When applied to Sr2+ removal from simulated wastewater, the distribution coefficients of Sr2+ reached 2943.15 mL·g-1, and the separation coefficients between Sr2+ and coexisting ions were above 64. DFT calculations further revealed the highly selective removal mechanism of Sr2+ from wastewater. In addition, NaNO3 was proved to be an efficient eluent. The excellent properties above make NaVOSi an excellent candidate for effectively removing Sr2+ from wastewater.

Preparation of ion imprinted EDTA modified chitosan-magnetic graphene oxide for selective recovery and adsorption mechanism of Ce(III).

Selective recovery of rare earth elements (REEs) from environmental waste is strategically significant. Herein, Ce(III) imprinted EDTA modified chitosan-magnetic graphene oxide (IIP-EDTA-CS-MGO) was prepared for selective recovery of Ce(III). Furthermore, adsorption mechanism was clarified based on versatile adsorption fittings and spectroscopic tests. Result presents, adsorption reaches its peak at pH=7 in 25min with maximum adsorption capacity 353.28mg·g-1. Functional groups C(=O)NH, CN and C-O-C in IIP-EDTA-CS-MGO provide heterogeneous affinity for Ce(III) to induce chemical adsorption. Thermodynamic calculation suggests spontaneous, endothermic and entropy increasing adsorption. Owing to Ce(III) imprinting, IIP-EDTA-CS-MGO demonstrates selectivity coefficients 3.09, 3.19, 14.10, 12.65 towards Ce(III) for binary solutions Ce/Eu, Ce/Dy, Ce/Cu, Ce/Cr, respectively. By virtue of its paramagnetic property, IIP-EDTA-CS-MGO can be readily recovered via magnetic separation for cyclic adsorption, thereby retaining adsorption quantity 116.58mg·g-1 for Ce(III) in five consecutive cycles. This work provides a new approach for fabricating magnetic bio-adsorbent towards selective recovery of Ce(III).

Density functional theory study on the selective adsorption mechanism of thiourea on gold and hydroxylated hematite surfaces

Density functional theory study on the selective adsorption mechanism of thiourea on gold and hydroxylated hematite surfaces

Selective leaching mechanisms of zinc from industrial waste using hybrid acids: Sustainable synthesis of Nano-ZnO

Zinc-containing dust (ZCD) has received extensive attention because it is a hazardous waste rich in various metals. This study innovatively proposed a hybrid acid leaching agent based on malic acid (MA) and sulfuric acid to selectively extract Zn from ZCD and successfully prepare nano-ZnO materials. The leaching experiments show that among the combinations of various organic acids and sulfuric acid, MA and sulfuric acid are superior in the selective leaching of Zn. Under optimal conditions, the leaching ratios of Zn, Pb, and Fe are 97.70%, 0.88%, and 2.95%, respectively. In addition, the use of hybrid acids can reduce sulfuric acid consumption by more than 46%. The Molecular dynamics simulation indicate that the interaction between the hybrid acid with ZnO and PbO was stronger (PbO > ZnO > Fe2O3). The radial distribution function (RDF) reveals that Zn and Pb ions form strong coordination structures with some oxygen atoms in MA, thereby confirming that MA plays a crucial role in preventing the dissolution of Fe. Finally, spherical nano-ZnO with a purity of 98.14% and an average particle size of 68.60 nm is obtained from the leaching solutions by precipitation method. This study provides a green and sustainable alternative for the selective recovery of Zn from ZCD.

Deactivation of Copper Electrocatalysts During CO2 Reduction Occurs via Dissolution and Selective Redeposition Mechanism

As electrochemical CO2 reduction (ECR) nears industrialisation levels, addressing the uncontrolled stability, restructuring, and deactivation of copper (Cu) catalysts during operation becomes as crucial as achieving high activity and selectivity...

Chaperone-mediated insertion of mitochondrial import receptor TOM70 protects against diet-induced obesity.

Outer mitochondrial membrane (OMM) proteins communicate with the cytosol and other organelles, including the endoplasmic reticulum. This communication is important in thermogenic adipocytes to increase the energy expenditure that controls body temperature and weight. However, the regulatory mechanisms of OMM protein insertion are poorly understood. Here the stress-induced cytosolic chaperone PPID (peptidyl-prolyl isomerase D/cyclophilin 40/Cyp40) drives OMM insertion of the mitochondrial import receptor TOM70 that regulates body temperature and weight in obese mice, and respiratory/thermogenic function in brown adipocytes. PPID PPIase activity and C-terminal tetratricopeptide repeats, which show specificity towards TOM70 core and C-tail domains, facilitate OMM insertion. Our results provide an unprecedented role for endoplasmic-reticulum-stress-activated chaperones in controlling energy metabolism through a selective OMM protein insertion mechanism with implications in adaptation to cold temperatures and high-calorie diets.

Catalyst-free synthesis of unsymmetrical ureas from COS and amines: a strategy for selectivity regulation

A novel and mild method has been developed for the highly selective synthesis of unsymmetrical ureas from amines and COS, which features a wide substrate scope. Additionally, the regulation mechanism of selectivity has been explored in detail.

Phase selection mechanism and eutectic growth kinetics of refractory Nb<sub>81.7</sub>Si<sub>17.3</sub>Hf alloy under electrostatic levitation condition

The phase selection mechanism and eutectic growth kinetics of Nb<sub>81.7</sub>Si<sub>17.3</sub>Hf alloy are investigated by electrostatic levitation technique. The maximum undercooling of this alloy reaches 404 K(0.19<i>T</i><sub>L</sub>). By analyzing the cooling curves, its hypercooling limit is obtained to be 527 K (0.24 <i>T</i><sub>L</sub>). A critical undercooling of 194 K is determined for the transition of solidification path. Below this undercooling threshold, (Nb) phase firstly nucleates and grows into primary dendrites, resulting in the enrichment of Si and Hf in the residual melt, which is conducive to the formation of the (Nb)+<i>α</i>Nb<sub>5</sub>Si<sub>3</sub> eutectics. Therefore, (Nb)+<i>α</i>Nb<sub>5</sub>Si<sub>3</sub> lamellar eutectics form in interdendritic space. With the increase of undercooling, the growth velocity of primary (Nb) dendritic follows a power function, while the eutectic growth velocity increases slowly. The maximum values of (Nb) dendritic reaches 89.4 mm/s. A modified LKT/BCT model is used to calculate the growth velocity of (Nb) dendrites. The results are in good agreement with the experimental values, indicating that after the LKT model is modified slightly, it can be used to describe the rapid dendrite growth behavior of the (Nb) phase in the Nb<sub>81.7</sub>Si<sub>17.3</sub>Hf alloy melt. Meanwhile, the lamellar spacing of (Nb)+<i>α</i>Nb<sub>5</sub>Si<sub>3</sub> eutectics notably decreases to 360 nm at 194 K undercooling. Above the critical threshold, the primary (Nb) dendrites disappear, whereas (Nb) phase and Nb<sub>3</sub>Si phase nucleate independently in the undercooled liquid and grow into anomalous eutectics. The growth velocity of anomalous eutectic exhibits a power function relationship with the increase of undercooling, with a maximum value of 115.9 mm/s. The interphase spacing of (Nb)+Nb<sub>3</sub>Si anomalous eutectics is larger than that of (Nb)+<i>α</i>Nb<sub>5</sub>Si<sub>3</sub> lamellar eutectics. Owing to the formation of nanosized eutectics and the increase of volume fraction of (Nb) phase, the alloy fracture toughness at 194 K reaches 21.9 MPa·m<sup>1/2</sup>, which is 3.4 times as large as that under small undercooling condition.

A Cross-Layer Game-Theoretic Approach to Resilient Control of Networked Switched Systems Against DoS Attacks.

This article investigates the resilient control strategies of networked switched systems (NSSs) against denial-of-service (DoS) attacks and external disturbance. In the network layer, both the defender and the attacker allocate energy over multiple channels. Considering the impact of switching characteristic in the physical layer on the network layer, a dynamic regulating factor is proposed to adjust the total energy of the defender. To optimize the signal-to-interference-noise ratio and energy consumption simultaneously at each player's side, a multiobjective game problem is formulated. Furthermore, a nondominated sorting genetic algorithm framework is employed, incorporating the knee point selection mechanism to attain the Pareto-Nash equilibrium, based on which the optimal defense strategy can be derived to achieve resilience against DoS attacks. In the physical-layer, taking the dynamic packet loss caused by DoS attacks and external disturbance into account, an H∞ minimax controller containing control inputs and the switching signal is designed to guarantee the optimal performance for NSSs through the dynamic game-theoretic approach. Finally, the networked continuous stirred tank reactor system is provided to verify the effectiveness of the proposed method.