Extension Of Domain Research Articles

Research on lateral stability control strategy for distributed drive electric vehicles considering driving style

To improve the handling stability of distributed drive electric vehicle (DDEV), a lateral stability control strategy considering driving style is proposed. Firstly, a driving style recognition model based on support vector machines (SVM) was constructed to identify driving styles in different lateral motion scenarios. Then, a layered architecture is used to design a driver/Active Front Steering (AFS)/Direct Yaw Control (DYC) stability coordination control strategy. The upper layer is based on the phase plane of the sideslip angle and extension control theory, dividing the vehicle operating range into classical, extension, and non domains. In the middle level, three control strategies are designed for different work domains. In the classical domain, a driver/AFS coordinated control strategy based on non-cooperative Nash games is constructed, and the weight coefficients in the AFS system cost function are modified based on driving characteristics; Construct a coordinated control strategy for AFS/DYC systems based on cooperative Pareto games in the extension domain; In non-domain, construct a direct yaw torque control strategy based on twin-delayed deep deterministic policy gradient (TD3) reinforcement learning. The lower layer aims to minimize tire utilization and optimizes the allocation of additional yaw moment. Finally, by establishing Hardware in the Loop (HIL) experiment platform, the effectiveness of the proposed control strategy is verified in lane changing scenarios of different styles of drivers. Compared to DYC stability control based solely on TD3, the maximum yaw rate and standard deviation of the lateral stability control strategy considering driving style reduce by 2.4 % and 10.82 %, respectively, and the maximum and standard deviation of the sideslip angle reduce by 29.29 % and 39.24 %, respectively, thereby improving the vehicle's handling stability.

Neumann eigenvalues of elliptic operators in Sobolev extension domains

We obtain estimates of Neumann eigenvalues of the divergence form elliptic operators in Sobolev extension domains. The suggested approach is based on connections between divergence form elliptic operators and quasiconformal mappings. The connection between Neumann eigenvalues of elliptic operators and the smallest-circle problem (initially suggested by J. J. Sylvester in 1857) is given.

Image Robust Watermarking Method Based on DWT-SVD Transform and Chaotic Map

The existing watermarking algorithms make it difficult to balance the invisibility and robustness of the watermark. This paper proposes a robust image watermarking method based on discrete wavelet transform (DWT), singular value decomposition (SVD), and chaotic maps. This method is a semiblind watermarking method. First, a chaotic logistic-tent map is introduced, employing an extensive chaotic parameter domain. This map is amalgamated with Arnold’s transformation to encrypt the watermark image, thereby bolstering the security of the watermark information. Subsequently, the frequency domain is obtained by applying DWT to the carrier image. Embedding watermarks in the frequency domain ensures the invisibility of the watermark, with a preference for a high-frequency subband after the DWT of the carrier image for enhanced watermark robustness. SVD is then applied to both the high-frequency subband of the carrier image after DWT and the encrypted watermark image. The final step involves embedding the singular values of the encrypted watermark image into the carrier image’s singular values, thereby completing the watermark information embedding process. In simulation experiments, an invisibility test was conducted on various carrier images, yielding peak signal-to-noise ratio (PSNR) values consistently exceeding 43, and structural similarity (SSIM) close to 1. Robustness testing against various types of attacks resulted in normalized correlation (NC) values consistently surpassing 0.9, with bit error rate (BER) values approaching 0. In conclusion, the proposed algorithm satisfies imperceptibility requirements while demonstrating formidable robustness.

Assessing Viscosity in Sustainable Deep Eutectic Solvents and Cosolvent Mixtures: An Artificial Neural Network-Based Molecular Approach.

Deep eutectic solvents (DESs) are gaining recognition as environmentally friendly solvent alternatives for diverse chemical processes. Yet, designing DESs tailored to specific applications is a resource-intensive task, which requires an accurate estimation of their physicochemical properties. Among them, viscosity is crucial, as it often dictates a DES's suitability as a solvent. In this study, an artificial neural network (ANN) is introduced to accurately describe the viscosity of DESs and their mixtures with cosolvents. The ANN utilizes molecular parameters derived from σ-profiles, computed using the conductor-like screening model for the real solvent segment activity coefficient (COSMO-SAC). The data set comprises 1891 experimental viscosity measurements for 48 DESs based on choline chloride, encompassing 279 different compositions, along with 1618 data points of DES mixtures with cosolvents as water, methanol, isopropanol, and dimethyl sulfoxide, covering a wide range of viscosity measurements from 0.3862 to 4722 mPa s. The optimal ANN structure for describing the logarithmic viscosity of DESs is configured as 9-19-16-1, achieving an overall average absolute relative deviation of 1.6031%. More importantly, the ANN shows a remarkable extrapolation capacity, as it is capable of predicting the viscosity of systems including solvents (ethanol) and hydrogen bond donors (2,3-butanediol) not considered in the training. The ANN model also demonstrates an extensive applicability domain, covering 94.17% of the entire database. These achievements represent a significant step forward in developing robust, open source, and highly accurate models for DESs using molecular descriptors.

Automated Vibroacoustic Monitoring of Trees for Borer Infestation.

In previous research, we presented an apparatus designed for comprehensive and systematic surveillance of trees against borers. This apparatus entailed the insertion of an uncoated waveguide into the tree trunk, enabling the transmission of micro-vibrations generated by moving or digging larvae to a piezoelectric probe. Subsequent recordings were then transmitted at predetermined intervals to a server, where analysis was conducted manually to assess the infestation status of the tree. However, this method is hampered by significant limitations when scaling to monitor thousands of trees across extensive spatial domains. In this study, we address this challenge by integrating signal processing techniques capable of distinguishing vibrations attributable to borers from those originating externally to the tree. Our primary innovation involves quantifying the impulses resulting from the fracturing of wood fibers due to borer activity. The device employs criteria such as impulse duration and a strategy of waiting for periods of relative quietness before commencing the counting of impulses. Additionally, we provide an annotated large-scale database comprising laboratory and field vibrational recordings, which will facilitate further advancements in this research domain.

Spatiotemporal characteristics and earthquake statistics of the 2020 and 2022 adjacent earthquake sequences in North Aegean Sea (Greece)

The two moderate earthquakes that occurred close and to the north of the North Aegean Trough (NAT) on 26 September 2020 (Mw5.3) and 16 January 2022 (Mw5.4), both followed by aftershock activity, are examined. Seismic activity along the NAT and its parallel branches is continuous and remarkable, with numerous strong instrumental (M≥6.0) earthquakes. Yet, the frequency of moderate (5.0≤M<6.0) earthquakes outside these major fault branches is rather rare and therefore their investigation provides the optimal means to decipher the seismotectonic properties of the broader area. The temporal and spatial proximity of the two seismic excitations from late September of 2020 through early 2022, intrigues for exhaustive investigation of seismic activity with the employment of earthquake relocation techniques, moment tensor solutions and statistical analysis. Our research revealed that this seismic activity purely falls inside the Mainshock – Aftershock type, with fast aftershock decay rates and moderate productivity. According to our findings, the two seismic sequences, despite their close proximity, exhibit distinctive features as a result of the intricate stress field generated at the western termination of the NAF system in an extensional domain.

Inflow stabilization for hemodynamic simulations using Stokesian regions

Blood flow simulations in three-dimensional space pose the challenge of isolating the vascular domain of interest, which introduces artificial interfaces, both upstream and downstream, where boundary conditions must be prescribed. Vessel curvature, tortuosity, and blood flow pulsatility contribute to the complexity of performing these simulations. A common practice in defining boundary conditions is to prescribe Neumann-like boundary conditions over these boundaries. A typical numerical problem in such a setting is associated with the unbounded nature of the kinetic energy that enters into the system, either through antegrade upstream flow or through downstream retrograde flow. Lack of energy control in the continuum problem may become a source of numerical instability, resulting in corrupted simulations. In this work, we propose a novel approach to avoid these instabilities by considering a bulk fluid with specific properties in a small portion of the domain in the vicinity of such boundaries. More precisely, the convective term from the governing equations is nullified in these domain extensions, resulting in Stokesian regions. In contrast to the classical approach based on the inclusion of straight long extensions to allow flow development, the proposed approach involves dealing with small regions whose length is smaller than the vessel diameter, to control the kinetic energy with near zero added computational cost. This stabilization strategy is investigated within the context of the Transversally Enriched Pipe Element Method, which makes the implementation straightforward. Academic examples and patient-specific vascular geometries are employed to illustrate the performance of the proposed stabilization strategy.

High-accuracy 2D DOA estimation with three parallel sparse nested array

To improve the performance for two-dimensional (2D) direction of arrival (DOA) estimation in the presence of limited antennas in practice, we propose a novel three parallel sparse nested array with extended aperture and reduced mutual coupling. The proposed array consists of three subarrays where locations of antennas have closed-form expressions, to efficiently achieve increased degrees of freedom in difference coarray domain. The unit inter-antenna spacings and the displacements among subarrays are all expanded by D1, D2 or D3 fold for aperture extension and mutual coupling reduction in physical array domain. By exploiting the configuration, the two methods, i.e., BOMP-based and CMT-BCS-based methods, are further explored for high-precision but ambiguous angle estimation, and then the coprime-ness between the displacements is utilized to solve the angle ambiguities. Simulation results demonstrate the superiority of the proposed array and methods for 2D DOA estimation over the existing technologies.

Development of conditionally active IL-10 INDUKINE TM molecules for the treatment of inflammatory bowel disease

Abstract Inflammatory bowel disease (IBD) encompasses two chronic inflammatory diseases of the gastrointestinal tract, Ulcerative Colitis (UC) and Crohn’s disease. Although great strides have been made in the treatment of IBD, subsets of patients do not respond or lose responsiveness to therapy, underlining a need for new treatments. Interleukin 10 (IL-10) is a immunoregulatory cytokine, known to suppress and inhibit inflammatory responses of a variety of immune cells including monocytes, macrophages, and T cells. Polymorphisms associated with reduced expression of IL-10 and IL-10R have been linked with IBD. Clinical trials using recombinant IL-10 in IBD have been unsuccessful, highlighting a need for further engineering to utilize IL-10 as a therapeutic agent. We have developed IL-10 INDUKINE molecules that are designed as prodrugs containing human IL-10, an inactivation domain and a half-life extension domain tethered together by protease-sensitive linkers. IL-10 INDUKINE molecules are peripherally inactive but due to dysregulation of the protease milieu in the inflamed colon, the linkers are cleaved, and IL-10 is released locally. We have identified proprietary linkers which are cleaved by UC and Crohn’s human colon samples. In a mouse model of colitis, IL-10 INDUKINE molecules prevent weight loss, intestinal damage and inhibit inflammatory cytokine production within the colon. Together these data support the potential of an IL-10 INDUKINE molecule for the treatment of IBD.

CityGML Grotto ADE for modelling niches in 3D with semantic information

The regions of East Asia, as well as South Asia and the Middle East are rich in cultural heritage of grottoes where a large number of Buddhist niches exist. Three-dimensional (3D) semantic modelling enriches 3D geometric models with an understanding of the historical and cultural value of cultural heritage, facilitating interoperability and analysis beyond mere visualization. 3D models with semantic information act as essential digital infrastructure for heritage management, knowledge dissemination and simulation analysis in cultural heritage. However, due to the lack of standardized data model for the grotto domain, it is difficult to exchange information, share knowledge and the advancement of spatial analysis and simulation. In order to fill the above-mentioned gap, this study develops a data model for niches as a CityGML Application Domain Extension (ADE) based on the CityGML 3.0 standard. In this ADE, niche components and their attributes are defined on two semantic levels, i.e., niche structural component and niche component member. A famous niche in China belonging to the World Heritage was selected as a case study to demonstrate the integration of geometries, semantics and attributes, illustrating that the extended ADE module complies with the CityGML 3.0 standard. This study provides novel insights into the 3D semantic modelling of niches as well as expands the applications scope of CityGML standard within the cultural heritage sector.

A Computational and Spectroscopic Analysis of Solvate Ionic Liquids Containing Anions with Long and Short Perfluorinated Alkyl Chains.

Anion-driven, nanoscale polar-apolar structural organization is investigated in a solvate ionic liquid (SIL) setting by comparing sulfonate-based anions with long and short perfluorinated alkyl chains. Representative SILs are created from 1,2-bis(2-methoxyethoxy)ethane ("triglyme" or "G3"), lithium nonafluoro-1-butanesulfonate, and lithium trifluoromethanesulfonate. Molecular dynamics simulations, density functional theory computations, and vibrational spectroscopy provide insight into the overall liquid structure, cation-solvent interactions, and cation-anion association. Significant competition between G3 and anions for cation-binding sites characterizes the G3-LiC4F9SO3 mixtures. Only 50% of coordinating G3 molecules form tetradentate complexes with Li+ in [(G3)1Li][C4F9SO3]. Moreover, the SIL is characterized by extensive amounts of ion pairing. Based on these observations, [(G3)1Li][C4F9SO3] is classified as a "poor" SIL, similar to the analogous [(G3)1Li][CF3SO3] system. Even though the comparable basicity of the CF3SO3- and C4F9SO3- anions leads to similar SIL classifications, the hydrophobic fluorobutyl groups support extensive apolar domain formation. These apolar moieties permeate throughout [(G3)1Li][C4F9SO3] and persist even at relatively low dilution ratios of [(G3)10Li][C4F9SO3]. By way of comparison, the CF3 group is far too short to sustain polar-apolar segregation. This demonstrates how chemically modifying the anions to include hydrophobic groups can impart unique nanoscale organization to a SIL. Moreover, tuning these nano-segregated fluorinated domains could, in principle, control the presence of dimensionally ordered states in these mixtures without changing the coordination of the lithium ions.

BTR: a bioinformatics tool recommendation system.

The rapid expansion of Bioinformatics research has led to a proliferation of computational tools for scientific analysis pipelines. However, constructing these pipelines is a demanding task, requiring extensive domain knowledge and careful consideration. As the Bioinformatics landscape evolves, researchers, both novice and expert, may feel overwhelmed in unfamiliar fields, potentially leading to the selection of unsuitable tools during workflow development. In this article, we introduce the Bioinformatics Tool Recommendation system (BTR), a deep learning model designed to recommend suitable tools for a given workflow-in-progress. BTR leverages recent advances in graph neural network technology, representing the workflow as a graph to capture essential context. Natural language processing techniques enhance tool recommendations by analyzing associated tool descriptions. Experiments demonstrate that BTR outperforms the existing Galaxy tool recommendation system, showcasing its potential to streamline scientific workflow construction. The Python source code is available at https://github.com/ryangreenj/bioinformatics_tool_recommendation.

Intel TDX Demystified: A Top-Down Approach

Intel Trust Domain Extensions (TDX) is an architectural extension in the 4th Generation Intel Xeon Scalable Processor that supports confidential computing. TDX allows the deployment of virtual machines in the Secure-Arbitration Mode (SEAM) with encrypted CPU state and memory, integrity protection, and remote attestation. TDX aims at enforcing hardware-assisted isolation for virtual machines and minimize the attack surface exposed to host platforms, which are considered to be untrustworthy or adversarial in the confidential computing’s new threat model. TDX can be leveraged by regulated industries or sensitive data holders to outsource their computations and data with end-to-end protection in public cloud infrastructures. This article aims at providing a comprehensive understanding of TDX to potential adopters, domain experts, and security researchers looking to leverage the technology for their own purposes. We adopt a top-down approach, starting with high-level security principles and moving to low-level technical details of TDX. Our analysis is based on publicly available documentation and source code, offering insights from security researchers outside of Intel.

Computational Fluid Dynamics Methodology to Estimate the Drag Coefficient of Balls in Rolling Element Bearings

The emergence of electric vehicles has brought new issues such as the problem of rolling element bearings (REBs) operating at high speeds. Losses due to these components in mechanical transmissions are a key issue and must therefore be taken into account right from the design stage of these systems. Among these losses, the one induced by the motion of rolling elements, known as drag loss, becomes predominant in high-speed REBs. Although an experimental approach is still possible, it is difficult to isolate this loss in order to study it properly. A numerical approach based on CFD is therefore a possible way forward, even if other issues arise. The aim of this article is to study the ability of such an approach to correctly estimate the drag coefficient associated with the motion of rolling elements. The influence of the numerical domain extension, the mesh refinement, the simplification of the ring shape, and the presence of the cage on the values of the drag coefficient is presented. While it seems possible to compromise on the calculation domain and mesh size, it appears that the other parameters must be taken into account as much as possible to obtain realistic results.

Modelling multidecadal variability in flood frequency using the Two-Component Extreme Value distribution

The Two-Component Extreme Value (TCEV) distribution is traditionally known as the exact distribution of extremes arising from Poissonian occurrence of a mixture of two exponential exceedances. In some regions, flood frequency is affected by low-frequency (decadal) climate fluctuations resulting in wet and dry epochs. We extend the exact distribution of extremes approach to such regions to show that the TCEV arises as the distribution of annual maximum floods for Poissonian occurrences and (at least two) exponential exceedances. A case study using coastal basins in Queensland and New South Wales (Australia) affected by low-frequency climate variability, shows that the TCEV produces good fits to the marginal distribution over the entire range of observed values without the explicit need to resort to climate covariates and removal of potentially influential low values. Moreover, the TCEV reproduces the observed dog-leg, a key signature of different flood generation processes. A literature review shows that the assumptions underpinning the TCEV are conceptually consistent with available evidence on climate and flood mechanisms in these basins. We provide an extended domain of the TCEV distribution in the L-moment ratio diagram to account for the wider range of parameter values encountered in the case study and show that for all basins, L-skew and L-kurtosis fall within the extended domain of the TCEV.

Mapping the CityGML Energy ADE to CityGML 3.0 Using a Model-Driven Approach

With the increasing adoption of semantic 3D city models, the relevance of applications in the field of Urban Building Energy Modelling (UBEM) has rapidly grown, as the building sector accounts for a large part of the total energy consumption. UBEM allows us to better understand the energy performance of the building stock and can contribute to defining refurbishment strategies. However, UBEM applications require lots of heterogeneous data, eventually advocating for standards for data interoperability. The Energy Application Domain Extension has been created to cope with UBEM data requirements and offers a standardised data model that builds upon the CityGML standard. The Energy ADE 1.0, released in 2018, creates new classes and adds new properties to existing classes of the CityGML 2.0 Core and Building modules. CityGML 3.0, released in 2021, has introduced several changes to the data model and its ADE mechanism. These changes render the Energy ADE incompatible with CityGML 3.0. This article presents how the Energy ADE has been ported to CityGML 3.0 to allow, on the one hand, for a lossless data conversion and, on the other hand, to exploit the new characteristics of CityGML 3.0 while keeping a logical symmetry between the ADE classes of both CityGML versions. The article describes the chosen methodology, the mapping strategies, the implementation steps, as well as the data conversion tests to check the validity of the “new” Energy ADE for CityGML 3.0.

Serious Games in Medical Education: What it Adds? How to Go about It?

ABSTRACT Medical educators have adopted a number of teaching–learning methodologies to make their sessions interactive considering the need for active engagement of students to strengthen the process of learning. One among them is the use of serious games, wherein digital applications are used to enable the attainment of the intended learning objectives. A wide range of serious games can be designed to target different areas in healthcare training, which cumulatively provide a holistic and engaging approach for students to acquire knowledge and develop skills. Owing to the extensive areas and domains in medical education wherein we can use serious games, the benefits attributed to them are immense. The successful introduction of serious games into the medical curriculum depends on several factors and we must adopt a systematic approach to optimize the benefits. In conclusion, the introduction of serious games into medical education can benefit medical students by helping them master multiple skills required for successful clinical practice. Acknowledging the changing landscapes in medical education, there is an immense need that teachers and administrators to explore the possibility of integrating these games into medical schools.

Matrix deformation of marls in a foreland fold-and-thrust belt: The example of the eastern Jaca basin, southern Pyrenees

In this study, we used the Anisotropy of Magnetic Susceptibility (AMS) to investigate the matrix strain record of two calcareous shale formations, the Eocene Larrès and Pamplona Marls, along the eastern Jaca foreland fold-and-thrust belt (Southern Pyrenees). More than 1000 unoriented fragments, collected from 62 sites along 4 sub-parallel sections in the footwall of the regional Oturia thrust and through local Yebra anticline, were measured. The analysis of the degree of anisotropy (P’) and shape parameter (T) allowed to identify four types of magnetic fabrics. Type II fabrics associated with poorly deformed rocks are characterized by a relatively high anisotropy and an oblate shape. In contrast, type III fabrics, associated with strongly fractured rocks are characterized by the lowest anisotropy and a triaxial shape. Type IV and type V fabrics are characterized by increasing anisotropy and shape parameters, and are associated with the development of a weak to a slaty cleavage in rocks. The distribution of the magnetic fabric is roughly similar along the four studied sections. In the footwall of the Oturia thrust, magnetic fabrics evolve from the type V to type II over a 1000 m-long interval. By contrast, the distribution of magnetic fabric is roughly symmetric across the Yebra anticline, evolving from a dominating type II fabric in both limbs to mixed type III-type V fabrics within the 1 km-large hinge zone. The succession of the magnetic fabrics is interpreted as recording various degrees of matrix strain in response to thrusting and folding. The correlation of magnetic fabrics between the four sections highlights some along-strike variations in the extension of fabric domains that are interpreted as reflecting the local influence of 2nd-order factors, such as the syn-tectonic sedimentation. Results are integrated within the tectono-sedimentary framework of the studied area to propose a model of matrix strain related to the tectonic and sedimentary evolution of a foreland fold and thrust belt.

Abstract 4074: Discovery of WTX-518, an IL-18 pro-drug that is conditionally activated within the tumor microenvironment and induces regressions in mouse tumor models

Abstract Systemic administration of proinflammatory cytokines is a promising approach to treat cancer. IL-18 has been shown to promote activation of both innate and adaptive anti-tumor responses in pre-clinical models. Specifically, IL-18 has been shown to impact macrophage suppressive function as well as drive CD4+ T cells towards a TH1 phenotype. However, IL-18 therapies have been hampered by a lack of efficacy due to the suppressive activity of IL-18 binding protein (IL-18BP), which binds to IL-18 and prevents its interaction with its receptor. Several groups have taken the approach of modifying IL-18 to render it resistant to IL-18BP as a potential strategy to enhance anti-tumor activity. To explore the therapeutic benefit of delivering a conditionally-activated IL-18 to the tumor microenvironment, we have developed inducible polypeptides (INDUKINE™ molecules) consisting of mouse IL-18 or IL-18BP resistant IL-18 (BPR IL-18) tethered via protease-sensitive linkers to a high affinity antibody blockade domain, and a half-life extension (HLE) domain which improves exposure in the tumor. IL-18 INDUKINE™ molecules are inactive until reaching the tumor microenvironment, where the linkers are cleaved by intra-tumoral proteases, releasing active IL-18. Intraperitoneal (i.p.) administration of an IL-18BP resistant IL-18 (BPR IL-18) INDUKINE™ molecule led to complete tumor regression in the MC38 tumor model. In contrast, equimolar doses of wild-type IL-18 INDUKINE™ protein were not as efficacious. Moreover, BPR IL-18 INDUKINE treatment led to increased activation and frequencies of NK cells and tumor specific CD8 T cells in MC38 tumors. WTX-518 is a novel INDUKINE™ molecule that is designed to selectively deliver active human BPR IL-18 to the tumor microenvironment. WTX-518 is inducible in vitro, either when tested using a reporter assay or primary immune cells. Importantly, the active BPR IL-18 payload is resistant to IL-18BP in reporter or primary immune cell assays. WTX-518 is also selectively inducible, as incubation ex vivo with various primary human tumors led to the release of active BPR IL-18, while WTX-518 was stable in human serum and after exposure to primary cells from healthy tissues. Pharmacological and efficacy data support continued preclinical development of this innovative and differentiated engineered IL-18 therapy. Citation Format: Kristin R. Morris, Heather Brodkin, Kyriakos Economides, Daniel J. Hicklin, Julie LePrevost, Celesztina Nagy-Domonkos, Christopher Nirschl, Andres Salmeron, Cynthia Seidel-Dugan, Cierra Spencer, Zoe Steuert, William M. Winston. Discovery of WTX-518, an IL-18 pro-drug that is conditionally activated within the tumor microenvironment and induces regressions in mouse tumor models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4074.

Abstract 4078: WTX-712, a conditionally active IL-21 INDUKINETM molecule, induces a strong anti-tumor phenotype through a differentiated mechanism

Abstract Despite great strides seen recently in the development of immunotherapies such as immune checkpoint inhibitors (ICI), many patients do not respond or acquire resistance, highlighting a need for alternative immunotherapies. As potent immunomodulators, cytokines have been explored as treatments for cancer, but their use has been limited due to toxicity and poor pharmacokinetics (PK). One of these key cytokines, interleukin 21 (IL-21), is a pluripotent cytokine that activates anti-tumor T cell responses, induces B cell activation, and promotes generation and maintenance of germinal centers and tertiary lymphoid structures. IL-21 acts on a broader range of cells and does not induce vascular leak syndrome compared to IL-2, another common-gamma chain family member. Half-life extended IL-21 (IL-21-HLE) drives robust anti-tumor activity in several syngeneic tumor mouse models. Of particular interest, IL-21-HLE showed superior anti-tumor activity compared to IL-2-HLE in the EMT-6 and Renca models, both of which are highly resistant to anti-PD-1/PD-L1 treatment. Although IL-21-HLE and IL-2-HLE induced a similar frequency of tumor infiltrating CD8+ T cells, IL-21-HLE treatment led to higher polyfunctionality in CD8+ T cells than IL-2-HLE treatment. Of note, IL-21-HLE induced greater amounts of effector cytokines, Granzyme B and perforin, than IL-2-HLE. Transcriptomic analysis revealed that IL-21 drives upregulation of a type I IFN signature in the tumor promoting an anti-tumorigenic microenvironment. Clinical activity of IL-21 has been hampered by poor PK and adverse events at dose levels associated with signs of efficacy. To overcome these limitations Werewolf Therapeutics has developed WTX-712, an IL-21 INDUKINETM molecule, which contains wild-type human IL-21, an inactivation domain, and a half-life extension domain tethered together by protease sensitive linkers. In preclinical studies with mouse syngeneic tumor models, WTX-712 is inactive in the periphery, and wild-type IL-21 is selectively released within the tumor, resulting in anti-tumor efficacy with an expanded therapeutic window compared to IL-21-HLE. Anti-tumor efficacy was linked to expansion and activation of tumor infiltrating CD8 T cells with increased polyfunctionality. We will show additional mechanistic data evaluating the effect of WTX-712 dosing on immune populations, including tumor spatial profiling using different models. Citation Format: Jenna M. Sullivan, Pamela A. Aderhold, Heather R. Brodkin, Celesztina Nagy-Domonkos, Kyriakos Economides, Daniel J. Hicklin, Nesreen Ismail, Yuka Lewis, Cynthia Seidel-Dugan, William M. Winston, Andres Salmeron. WTX-712, a conditionally active IL-21 INDUKINETM molecule, induces a strong anti-tumor phenotype through a differentiated mechanism [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4078.