Mismatch Model Research Articles

Optimal spatial arrangement of modules for large‐scale photovoltaic farms in complex topography

AbstractThe existing methods for determining the module arrangement in photovoltaic (PV) farms are considered insufficient as they are generally limited to the environment of flat ground without considering both physical and electrical factors. The orientations of PV modules may be very diverse when installed in places with complex topography, e.g. mountains and abandoned mine sites. Thus, the received irradiance by the modules is inconsistent directly results in current differences and hence leads to significant mismatch loss in the PV arrays. This paper proposes a solution to determine the most appropriate combination of tilts and orientations of PV modules as well as the arrangement of PV arrays. The complex topographies are fully considered to minimize the mismatch loss phenomenon, and hence the power generation degradation. The solution adopts a set of models, i.e. the irradiation model for the calculation of optimal module tilts and orientations, the shadow model for shadow effect analysis, and the mismatch model for mismatch condition analysis. A two‐layer multi‐objective optimization is implemented for the optimal arrangement. The proposed solution is assessed through the case study of a 30 MW PV farm. The result confirms the effectiveness of the proposed solution for the optimal spatial module placement.

Large vessel occlusion mediated fluid attenuated inversion recovery signal intensity ratio is associated with stroke within 4.5 h.

The primary objective was to investigate the value of the fluid attenuated inversion recovery (FLAIR) signal intensity ratio (SIR) in identifying stroke within 4.5 h. The secondary objective was to ascertain whether large vessel occlusion (LVO) mediated the relationship between the SIR and stroke within 4.5 h. We analyzed 633 acute stroke patients within 24 h of clear symptom onset. The SIR and DWI-FLAIR mismatch were evaluated. First, we determined whether demographic variables, vascular risk factors and LVO were related to stroke within 4.5 h with multivariate logistic regression analyses and stratified regression analysis. Next, we used mediation analysis to determine whether LVO explained the association between SIR and stroke within 4.5 h. Finally, we used receiver operating characteristic (ROC) analysis to assess the value of SIR, independent variable, and multiparameter models in identifying stroke within 4.5 h and compared with DWI-FLAIR mismatch. Hyperlipemia, LVO and SIR were associated with stroke within 4.5 h. Mediation analysis revealed that LVO partially mediated the relationship between SIR and stroke within 4.5 h (p < 0.001). The multiparameter model (hyperlipemia, LVO and SIR) showed significantly improved performance (AUC 0.869) in identifying stroke within 4.5 h over DWI-FLAIR mismatch (0.684), hyperlipemia (0.632), LVO (0.667) and SIR (0.773) models. SIR is associated with stroke within 4.5 h, and LVO partially mediates this relationship. A multiparameter model combining hyperlipemia, LVO and SIR can more accurately identify stroke within 4.5 h than individual parameter models.

Experimental study of thermal transport across metal/h-BN interfaces: Comparison with metal/graphite interfaces

The continuing miniaturization of layered material electronics highlights the increasingly significant role of interfacial thermal conductance (G) in the efficient nanoscale heat dissipation in these electronics. Despite its importance, the mechanisms of thermal transport across the interfaces of layered materials and the underlying substrate remain unclear. In this work, we comprehensively investigate the interfacial thermal and phonon transport across layered-material interfaces through our ultrafast pump-probe measurements and detailed calculations on G for the interfaces of hexagonal boron nitride (h-BN), one of the most promising layered materials. We first experimentally measure Gc for interfaces between four different metals (Al, Pd, Au and Ti) and h-BN along c-axis using time-domain thermoreflectance (TDTR) from 80 to 300 K. We successfully achieve high accuracy of our measurements with uncertainty <10 % through using the carefully chosen high modulation frequency (15.6 MHz) and relatively large laser spot size (22.5 μm). We find that the measured Gc for interfaces between metals (except Al) and (100) plane of h-BN is lower than that of metal/graphite interfaces, while Gc of Al/h-BN is comparable to that of Al/graphite interfaces. Furthermore, together with our proposed anisotropic model and the diffuse mismatch model (DMM), we determine the transmission probability for the various metal/h-BN interfaces and find that the strong bonding strength enhances the phonon transmission across Ti/h-BN or Ti/graphite interfaces. Finally, we predict the orientation-dependent thermal conductance (i.e., the different interfacial thermal transport along c-axis (Gc) and in-plane (Gab) crystallographic orientations) for both metal/h-BN and metal/graphite. We find Gab between metals and (001) plane is up to 2–3 times higher than Gc. This can be attributed to the highly anisotropic elastic properties in the h-BN and graphite. This work provides important insight into the phonon transmission mechanisms across metal/h-BN interfaces, and thus contributes significantly to the thermal management of layered material electronics.

What causes social class disparities in education? The role of the mismatches between academic contexts and working-class socialization contexts and how the effects of these mismatches are explained.

Within psychology, the underachievement of students from working-class backgrounds has often been explained as a product of individual characteristics such as a lack of intelligence or motivation. Here, we propose an integrated model illustrating how educational contexts contribute to social class disparities in education over and beyond individual characteristics. According to this new Social Class-Academic Contexts Mismatch model, social class disparities in education are due to several mismatches between the experiences that students from working-class backgrounds bring with them to the classroom and those valued in academic contexts-specifically, mismatches between (a) academic contexts' culture of independence and the working-class orientation to interdependence, (b) academic contexts' culture of competition and the working-class orientation toward cooperation, (c) the knowledge valued in academic contexts and the knowledge developed through working-class socialization, and (d) the social identities valued in academic contexts and the negatively stereotyped social identities of students from working-class backgrounds. Because of these mismatches, students from working-class backgrounds are likely to experience discomfort and difficulty in the classroom. We further propose that, when attempting to make sense of these first-order effects, students and teachers rely on inherent characteristics (e.g., ability, motivation) more often than warranted; conversely, they overlook extrinsic, contextual factors. In turn, this explanatory bias toward inherent features leads (a) students from working-class backgrounds to experience self-threat and (b) their teachers to treat them unfairly. These second-order effects magnify social class disparities in education. This integrated model has the potential to reshape research and discourse on social class and education. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Microstructure and performance of carbon fiber reinforced aluminum matrix composites with molybdenum carbide coating on carbon fibers

In this work, a molybdenum carbide coating on the surface of short carbon fibers prepared using molten salt method was proposed to ameliorate the interfacial bonding and improve the performance of carbon fiber/Al composites. The carbon fiber/Al composites were produced using vacuum hot pressing. The characteristics of molybdenum carbide coating were analyzed. Besides, the microstructures, bending strength and thermal properties of the carbon fiber/Al composites were explored. Furthermore, the interfacial thermal resistance of the composites was investigated in relation to theoretical evaluations derived from the combined Maxwell-Garnett effective medium approach and acoustic mismatch model schemes. The results indicated that a homogeneous Mo2C coating with a thickness of 0.5 μm was obtained by proper molar ratio of carbon fibers, MoO3 and chloride salts mixture and heated at 1000 °C for 60 min. The Mo2C coating greatly enhanced the bond between the aluminum matrix and carbon fiber, leading to improvements in the densification behavior and bending strength of the coated composites. The enhanced thermal properties including improved thermal conductivity and reduced coefficient of thermal expansion (CTE) were also achieved by the Mo2C coating. The in-plane thermal conductivity of 60 vol.% Mo2C-coated carbon fiber/Al composite was 221 W·m−1·K−1 enhanced by 92% compared to that of uncoated composite and the CTE was 6.0 × 10–6 K−1 which was suitable for electronic packaging materials.

Spatiotemporal Analysis of Food Production-Demand Mismatch in China and Implications for Agricultural Structural Adjustment.

Based on the food equivalent unit (FEU), this article analyzed Chinese food consumption patterns, spatial mismatch, and production potential to explore agricultural reform strategies. Assessing production-demand mismatch involved the spatial mismatch model, drawing data from statistical yearbooks. Calculations of food production potential utilized the CASA model and the Thornthwaite Memorial model, with net primary productivity (NPP) derived from remote sensing data as indicators. The results showed that livestock product consumption is on the rise, and the spatial mismatch index for herbivorous livestock products was the largest, ranging from 22.81 to 98.12 in 2019. The mismatched degree distribution of rations and food-consuming livestock products showed a trend of increasing on both sides, with the Hu Huanyong line as the center line. Production factors played a predominant role in food production-to-demand mismatch. Climatic productivity and actual productivity decreased from the southeast to northwest in space in 2019, and human activities significantly impacted productivity. When grassland agriculture is pursued as the adjustment orientation, the production potential can reach up to 4540.76 × 107 kg·FEU. Moreover, a grassland agriculture plan was devised, prioritizing its development in the developed southern regions.

Investigating thermal transport across the AlN/diamond interface via the machine learning potential

Aluminum nitride (AlN) is an ultrawide-bandgap semiconductor with excellent potential for high-power applications. However, the heat dissipation issue remains a huge challenge for the use of AlN in high-power devices. A promising solution for this problem is to integrate AlN with the diamond heat sink. Therefore, interfacial thermal transport has become a significant bottleneck in thermal management. In this work, one neuroevolution potential is developed based on neural networks, which significantly improves the accuracy of predicting thermal properties compared to traditional potentials and address the issue of inaccurate thermal performance prediction of AlN/diamond heterostructures using traditional potentials. Molecular dynamics simulations based on NEP is adopted to investigate the crystal-orientation-dependent and interfacial-atom-dependent thermal boundary resistance of the AlN/diamond heterostructures after the interfacial bonding. Compared to bonding with Al and C atoms, the TBR decreases by approximately 50 % after bonding with N and C atoms at the interface. Especially for the AlN (0001)-N-diamond (100) heterostructure, the TBR is 0.95 m2·K·GW−1, very close to the theoretical limit of 0.8 m2·K·GW−1 through the diffuse mismatch model (DMM) theory. Finally, the insightful optimization strategies are proposed in this work which could pave the way for better thermal design and management of AlN/diamond heterostructures.

Role of elastic phonon couplings in dictating the thermal transport across atomically sharp SiC/Si interfaces

The interfaces between SiC and the corresponding substrate largely affect the performance of SiC-based electronics. Understanding and designing the interfacial thermal transport across the SiC/substrate interfaces is critical for the thermal management design of these SiC-based power electronics. In this work, we systematically investigate the heat transfer across the 3C-SiC/Si, 4H-SiC/Si, and 6H-SiC/Si interfaces using non-equilibrium molecular dynamics simulations and diffuse mismatch model. We find that the room temperature ITC for 3C-SiC/Si, 4H-SiC/Si, and 6H-SiC/Si interfaces is 932 MW/m2K, 759 MW/m2K, and 697 MW/m2K, respectively, which is among the highest values for all interfaces made up of semiconductors (Yue et al., 2011; Cheng et al., 2020; Wilson et al., 2015; Ziade et al., 2015) [1–4]. The ultrahigh ITC of SiC/Si heterointerfaces at room temperature and high temperatures results from the dictating elastic scatterings at interfaces. We further find the ITC contributed by the elastic scattering decreases with the temperature but remains at a high ratio of 67%-78% even at an ultrahigh temperature of 1000 K. The reason for such a high elastic ITC is the large overlap between the vibrational density of states of Si and SiC at low and middle frequencies (<∼18 THz), which is also demonstrated by the diffuse mismatch model.

Model-based interpretation of bottomhole pressure records during matrix treatments in layered formations

During injection treatments, bottomhole pressure measurements may significantly mismatch modeling results. We devise a computationally effective technique for interpretation of fluid injection in a wellbore interval with multiple geological layers based on the bottomhole pressure measurements. The permeability, porosity and compressibility in each layer are initially setup, while the skin factor and partitioning of injected fluids among the zones during the injection are found as a solution of the problem. The problem takes into account Darcy flow and chemical interactions between the injected acids, diverter fluids and reservoir rock typical in modern matrix acidizing treatments. Using the synchronously recorded injection rate and bottomhole pressure, we evaluate skin factor changes in each layer and actual fluid placement into the reservoir during different pumping jobs: matrix acidizing, water control, sand control, scale squeezes and water flooding. The model is validated by comparison with a simulator used in industry. It gives opportunity to estimate efficiency of a matrix treatment job, role of every injection stage, and control fluid delivery to each layer in real time. The presented interpretation technique significantly improves accuracy of matrix treatments analysis by coupling the hydrodynamic model with records of pressure and injection rate during the treatment.

Electronic interfacial thermal conductance between metal nano-films in sub-picosecond non-equilibrium transport process

Interfaces play a critical role in nanoscale thermal transport, and understanding thermal transport mechanisms across metal/metal interfaces at the non-equilibrium states is urgently needed for highly integrated electronic structures or devices. In this work, the electronic interfacial thermal conductance hee of two metal interfaces, Au/Pt and Au/Al, was measured by time domain thermoreflectance (TDTR) at the non-equilibrium states and an extended two-temperature model was applied to well describe the interactions of electrons between the metal films. For the Au/Pt structure, the measured hee is 4.4 ± 1.8 GWm−2K−1, which is consistent with the predicted value by the electronic diffuse mismatch model (DMM). While for the Au/Al structure, the measured hee (0.13±0.05 GWm−2K−1) is an order of magnitude smaller than that of Au/Pt and the predicted value of the electronic DMM. The results indicate that even the extremely thin oxide layer at the Au/Al interface can significantly hinder the electron thermal transport across the metal interface. Overall, our findings contribute to revealing the non-equilibrium interfacial thermal transport mechanisms and pave the way for designing the highly integrated electronic devices.

Nonlinear acoustic response in nanoparticle-dielectric systems and nondestructive assessment of particle agglomeration

Nanoparticle agglomeration reduces the modification effect of nanocomposites, and there is a need to investigate a technique for evaluating the overall particle dispersion within the material, which in turn ensures the modification effect of the material. In this paper, a non-destructive testing technique for nanoparticle dispersion based on nonlinear ultrasonic (NLUS) is proposed to rapidly assess the overall nanoparticle dispersion within a material. An interfacial mismatch model describing different degrees of nanoparticle agglomeration was firstly developed, and then the nonlinear acoustic response of the nanoparticle-dielectric system was quantitatively solved, and the theoretical model was validated in conjunction with NLUS tests. The experimental results show that agglomerated interfaces are the source of the nonlinear response of nanodielectrics and that the microscopically generated nonlinear effects can be equivalently accumulated to the mesoscopic domain, with the error in the theoretically calculated values of the two being less than 5%; The NLUS technique eliminates the need for cumbersome steps such as particle size counting, and its small number of rapid detection results are close to the statistical convergence of the particle size of the 250 particles accumulated in the imaging image of the scanning electron microscope, with an error of between 3% ∼ and 13%. With a single inspection area of 339 mm3, the NLUS technology significantly reduces evaluation time and cost while expanding the inspection area, offering the combined advantages of speed, wide field of view, and non-destructiveness.

T−n (n: 2.4∼2.56) temperature dependence of thermal resistance at single-walled carbon nanotubes/SiO2 interface at

The burgeoning significance of energy coupling at interfaces of nm dimension aligns seamlessly with the rapid strides made in micro/nanoelectronics. The nm-scale interface thermal resistance (ITR) is strongly affected by temperature but is poorly understood to date due to extreme challenges in nm-scale characterization. This work reports a pioneering and high-level study on how temperature affects the ITR of single-walled carbon nanotube (SWCNT)-SiO2 interface with a < 8 nm lateral dimension. From 297 to 77 K, the ITR is observed to increase from 530 to 725 to (1.56–1.74)×104 K·m·W−1. The reported ITRs at room temperature are in line with reported data for SWCNT/SiO2 interface. The ITR variation with temperature is compared with the prediction based on the phonon diffuse mismatch model (DMM). A great qualitative agreement is observed while the DMM under the Debye approximation of linear dispersion underestimates the ITR. Our ITR dependency on temperature takes the form of T−n where n is found to be 2.4 and 2.56 for two different locations of the sample. Such observation resembles the dependency of specific heat on temperature far below the Debye temperature. We introduce a concept termed as the effective interface energy transmission velocity (vi,eff) in an attempt to rule out the role of specific heat in ITR-temperature dependence to uncover the intrinsic effect of temperature on interface energy coupling. Very interestingly, vi,eff shows little variation over a wide temperature range for various reported interfaces. Further exploration and refinement of this concept is expected in forthcoming research endeavors.

Data‐driven plant‐model mismatch quantification in closed‐loop system based on output predictions

AbstractThe assessment and diagnosis of controller performance for model‐based closed‐loop control systems has received considerable attention in recent years. A recognized factor dilapidating the controller performance is mismatching the true dynamical model of the plant and the mathematic model employed in the controller. In order to reduce the heavy effort to re‐identify the entire model, a large amount of recent works have been focusing on locating the mismatch. To further improve the mathematic model as well as controller performance, in this article, we provide a novel prediction‐based plant‐model mismatch quantification approach, which belongs to the class of moment match methodology. In particular, two cases of output prediction are considered: one‐step ahead prediction and multistep ahead prediction. Compared with existing efforts along the same line of mismatch quantification, when using the one‐step ahead prediction, our method shows an advantage of light computational complexity. On the other hand, when utilizing multistep predictions, it shows better convergence and robustness than the former, especially in the case of structural mismatches, and the long‐term prediction capability of the model is employed. With both predictions and consideration of the existence of unknown noise models in practice, we show that the plant‐model mismatch and unknown parameters of noise models can be quantified as the solution of a minimization issue that penalizes the discrepancy between the sample of plant outputs and the predictions calculated by considering the plant‐model mismatch and noise model parameters. Several examples are provided to demonstrate the effectiveness of the proposed methods, respectively.

Modification of the Acoustic Mismatch Model and Diffuse Mismatch Model for Accurate Prediction of Interface Thermal Conductance At Low Temperatures

Abstract Houston&amp;amp;amp;amp;#39;s method for summing phonon modes in the Brillouin zone is applied to exclude specular transmission of phonon modes of specific symmetries, thus, modifying the Acoustic Mismatch Model when phonon heat flux is incident from a heavier to a lighter medium. The Houston method is also used to impose conservation of the number of phonons in each direction of high symmetry, thus modifying the detailed balance theorem and the Diffuse Mismatch Model. Based on the assumption that phonons are in equilibrium at the interface and are transmitted specularly or diffusely by two-phonon elastic processes, interpolation between the modified Acoustic Mismatch Model and the modified Diffuse Mismatch Model has led to a general analytical formalism for low-temperature interface thermal conductance. The Debye temperature, the only parameter in the derived formalism, is expressed as a function of temperature by assimilating numerically obtained specific heat values to the Debye expression for specific heat. Previous measurements of the thermal conductance of smooth and rough interfaces between dissimilar materials could be reproduced numerically without adjustment of model parameters, demonstrating the importance of modifications to the Acoustic Mismatch Model and the Diffuse Mismatch Model, and supporting the hypothesis that anharmonic processes play a minimal role in heat transport across interfaces below ambient temperature. The formalism developed is used to study the thermal conductance of the interface between silicon and germanium because of the potential of silicon-germanium nanocomposites for thermoelectric applications.

Phase-Dependent Phonon Heat Transport in Nanoscale Gallium Oxide Thin Films.

Different phases of Ga2O3 have been regarded as superior platforms for making new-generation high-performance electronic devices. However, understanding of thermal transport in different phases of nanoscale Ga2O3 thin-films remains challenging, owing to the lack of phonon transport models and systematic experimental investigations. Here, thermal conductivity (TC) and thermal boundary conductance (TBC) of the α-, β-, and (001) κ-Ga2O3 thin films on sapphire are investigated. At ≈80nm, the measured TC of α (8.8W m-1 K-1) is ≈1.8 times and ≈3.0 times larger than that of β and κ, respectively, consistent with model based on density functional theory (DFT), whereas the model reveals a similar TC for the bulk α- and β-Ga2O3. The observed phase- and size-dependence of TC is discussed thoroughly with phonon transport properties such as phonon mean free path and group velocity. The measured TBC at Ga2O3/sapphire interface is analyzed with diffuse mismatch model using DFT-derived full phonon dispersion relation. Phonon spectral distribution of density of states, transmission coefficients, and group velocity are studied to understand the phase-dependence of TBC. This study provides insight into the fundamental phonon transport mechanism in Ga2O3 thin films and paves the way for improved thermal management of high-power Ga2O3-based devices.

Two-time scale dynamic closed-loop scheduling for gas supply network with multiple air separation units

The gas supply network with multiple air separation units (ASUs) in steel enterprises provides the essential gas products for iron- and steel-making processes. Steel enterprises must make scheduling decisions for their gas supply networks to meet the fast-changing downstream demands. Therefore, the dynamic characteristics of the process must be considered during short-interval production scheduling to ensure more reasonable scheduling decisions. A two-scale dynamic scheduling method is first developed in this paper to consider the process dynamics. In this method, scheduling decisions are made in the slow time scale, and the nonlinear dynamic characteristics are described using a varied time constant dynamic model in the fast time scale. Then, an autoregressive moving average (ARMA) model is established to address the unavoidable model mismatch, which explicitly predicts and integrates future mismatches into the scheduling model. Moreover, a moving horizon closed-loop framework is designed to integrate the state feedback, mismatch modeling, and scheduling decision modification so that scheduling decisions can be modified in real time to avoid potential safety hazards. The results of the industrial application indicate that the proposed method can provide better scheduling decisions in case studies of model mismatch and unknown leakage compared with existing methods.

Evolution Pattern and Spatial Mismatch of Urban Greenspace and Its Impact Mechanism: Evidence from Parkland of Hunan Province

Planners need to fully understand the quantity of land supply and its matching relationship with population demand, as these are prerequisites for urban greenspace planning. Most papers have focused on single cities and parks, with little attention paid to comparative analysis between multiple cities on a macro scale, ignoring the influence of spatial effects and leading to a lack of basis for regional green infrastructure planning. This paper selected 102 cities in Hunan province as case studies to comprehensively conduct empirical research using the spatial mismatch model and the geographically weighted regression method. The urban parkland in Hunan province are characterized by significant spatial heterogeneity and correlation, and the mismatch between land supply and population demand should not be ignored, with oversupply and undersupply co-existing. The urban parkland and its mismatch with population are influenced by a number of factors, and each factor has a stronger influence on the latter than the former. Different factors vary widely in the nature and intensity of their effects, and the dynamics are more complex. Economic development, financial capacity, and air quality are key factors, with the former having a negative impact and the latter having opposite (positive) effects. We suggest that when the government allocates land resources and targets for urban parks, it should formulate a differentiated allocation plan based on the supply and demand conditions of each city; besides, it should also place emphasis on regional integration and coordination and support mutual cooperation.

Effect of Interfacial Coatings on Thermal Conductivity of Diamond/Al Composites

In this paper, the acoustic mismatch model and the differential effective medium scheme were applied to predict the influence of different interfacial coatings (Si and SiC) on the interfacial thermal conductivity and thermal conductivity of the Diamond/Al composites, respectively. With the increase of the thickness of interfacial coatings, the interfacial thermal conductivity and of the thermal conductivity of Diamond/Al composites decreased. In order to obtain ideal thermal conductivity of Diamond/Al composites, the thickness of the coating should be controlled below 1 μm. When the volume fraction of diamond was 60% and the average particle size was 100 μm, the interfacial thermal conductivity of Si and SiC coated Diamond/Al composites were in the range of 1.77×107∼1.1×108 W/(m2 · K) and 2.44×107∼1.29×108 W/(m2 · K), respectively; the thermal conductivity of Si and SiC coated Diamond/Al composites were in the range of 541.58∼764.15 W/(m· K) and 594.45∼777.3 W/(m· K), respectively. The thermal conductivity of Si and SiC coated Diamond/Al composites increased with the volume fraction and average particle size of Diamond, and the thermal conductivity of SiC coated Diamond/Al composites was higher than that of Si coated composites. SiC interface coating was proposed to be the most promising candidates to improve the thermal performance of Diamond/Al composites.

Adaptive controller based on the affine equivalent model with disturbance rejection for discrete-time switched systems

Switched systems often have hard-to-determine models, and the switching time is often unknown. Mismatched model dynamics and/or switching time may lead to performance degradation. Hence, the present work develops an adaptive controller for single-input single-output nonlinear discrete-time switched systems when the mathematical model, switching time and input–output disturbances are unknown. An affine equivalent model-based on Multi-input Fuzzy Rules Emulated Network characterises the unknown system. The control law is derived according to the tracking error, a proposed sliding surface and the affine equivalent model. The controller parameters were set according to the stability analyses (Uniformly Ultimate Bounded-Lyapunov method). Several experiments, including non-switched and switched systems with input and output disturbances, showed a mean perceptual error of less or equal to 1% for all cases, with recovery in the switch cases. This successfully proves the closed-loop performance of the proposed controller on a discrete-time switched and disturbed system.

Anti-CD20 Antibody and Calcineurin Inhibitor Combination Therapy Effectively Suppresses Antibody-Mediated Rejection in Murine Orthotopic Lung Transplantation.

Antibody-mediated rejection (AMR) is a risk factor for chronic lung allograft dysfunction, which impedes long-term survival after lung transplantation. There are no reports evaluating the efficacy of the single use of anti-CD20 antibodies (aCD20s) in addition to calcineurin inhibitors in preventing AMR. Thus, this study aimed to evaluate the efficacy of aCD20 treatment in a murine orthotopic lung transplantation model. Murine left lung transplantation was performed using a major alloantigen strain mismatch model (BALBc (H-2d) → C57BL/6 (BL/6) (H-2b)). There were four groups: isograft (BL/6→BL/6) (Iso control), no-medication (Allo control), cyclosporine A (CyA) treated, and CyA plus murine aCD20 (CyA+aCD20) treated groups. Severe neutrophil capillaritis, arteritis, and positive lung C4d staining were observed in the allograft model and CyA-only-treated groups. These findings were significantly improved in the CyA+aCD20 group compared with those in the Allo control and CyA groups. The B cell population in the spleen, lymph node, and graft lung as well as the levels of serum donor-specific IgM and interferon γ were significantly lower in the CyA+aCD20 group than in the CyA group. Calcineurin inhibitor-mediated immunosuppression combined with aCD20 therapy effectively suppressed AMR in lung transplantation by reducing donor-specific antibodies and complement activation.