Face Hurdles Research Articles

IoT-based framework for optimizing energy efficiency and reliability in acoustic sensor networks using mobile sinks

In today’s world, there is an increasing demand for environmental monitoring, surveillance, and oceanographic research, which poses challenges in improving energy efficiency and data transfer reliability in Acoustic Sensor Networks. Existing methods face hurdles due to limited energy resources and unreliable data transmission. We propose a Reliable and Energy-Efficient Framework with Sink Mobility (REEFSM) to address these issues. This framework optimizes energy consumption and enhances data reliability by incorporating advanced energy management strategies such as adaptive duty cycling and efficient data transmission mechanisms by minimizing forwarding nodes. Simulation results demonstrate that REEFSM reduces energy consumption by up to 43% and increases data reliability by 35% compared to protocols like EERBCR and DEADS. REEFSM ensures zero dead nodes, minimizes packet drops, and maintains high data accuracy throughout the simulation. This research outcome provides a sustainable and reliable solution for energy-efficient data collection in underwater environments. The future research directions, including integrating autonomous path planning, energy harvesting, and machine learning techniques, hold great potential for further advancements in the field.

Exploring novel antitubercular agents: Innovative design of 2,3-diaryl-quinoxalines targeting DprE1 for effective tuberculosis treatment

Abstract The rising instances of drug resistance in Mycobacterium tuberculosis strains pose a significant global health challenge. Conventional tuberculosis (TB) treatments, which typically involve multiple antibiotics, face hurdles like drug resistance, reduced effectiveness, and heightened toxicity. Consequently, there is a pressing need for innovative anti-TB agents with new modes of action. Decaprenyl-phosphoryl-β-d-ribose 2′-epimerase 1(DprE1), a crucial enzyme in Mycobacterium tuberculosis, plays a vital role in cell wall biosynthesis – a critical aspect for the bacterium’s survival. Building on the success of diarylquinolines like bedaquiline, targeting DprE1 presents a promising avenue for developing anti-TB drugs, especially against drug-resistant strains. Our research focused on discovering novel DprE1 inhibitors using a ligand-based drug design strategy, starting with the established non-covalent inhibitor Ty38c. We assembled a library of 16 molecules, modifying them based on factors like drug-like properties, chemical accessibility, and synthetic feasibility. Molecular docking analyses of this library identified three molecules with binding affinities comparable to Ty38c. Among these, KS_QD_05 and KS_QD_04 are promising candidates, which were further validated through molecular dynamics simulation studies where root-mean-square deviation (RMSD) values of all three complexes reached a plateau, measuring around 0.3 nm, indicating that the apoprotein and all complexes stabilized during the simulation. The ligands KS_QD_04 and KS_QD_05 displayed significantly stable deviation. KS_QD_05 reached about 0.1 nm equilibrium value. However, the ligand KS_QD_04 reached an RMSD value of 0.17 nm and showed distress at 70 nm. KS_QD_04 and KS_QD_05 showed an average value of 1-3 H-bond interaction and regarding the RMSF values, both the compounds showed fluctuations less than 0.5 nm in the case of Mtb. DprE1 enzyme. This indicates the potential of both compounds to become lead compounds in the pursuit of DprE1 inhibitors for TB treatment.

Advances in Intrathecal Nanoparticle Delivery: Targeting the Blood-Cerebrospinal Fluid Barrier for Enhanced CNS Drug Delivery.

The blood-cerebrospinal fluid barrier (BCSFB) tightly regulates molecular exchanges between the bloodstream and cerebrospinal fluid (CSF), creating challenges for effective central nervous system (CNS) drug delivery. This review assesses intrathecal (IT) nanoparticle (NP) delivery systems that aim to enhance drug delivery by circumventing the BCSFB, complementing approaches that target the blood-brain barrier (BBB). Active pharmaceutical ingredients (APIs) face hurdles like restricted CNS distribution and rapid clearance, which diminish the efficacy of IT therapies. NPs can be engineered to extend drug circulation times, improve CNS penetration, and facilitate sustained release. This review discusses key pharmacokinetic (PK) parameters essential for the effectiveness of these systems. NPs can quickly traverse the subarachnoid space and remain within the leptomeninges for extended periods, often exceeding three weeks. Some designs enable deeper brain parenchyma penetration. Approximately 80% of NPs in the CSF are cleared through the perivascular glymphatic pathway, with microglia-mediated transport significantly contributing to their paravascular clearance. This review synthesizes recent progress in IT-NP delivery across the BCSFB, highlighting critical findings, ongoing challenges, and the therapeutic potential of surface modifications and targeted delivery strategies.

A multi-agent curiosity reward model for task-oriented dialogue systems

In practical decision-making dialogues, reinforcement learning methods face hurdles due to delays and sparse reward feedback for agents, and in some cases, lack of rewards altogether. These issues can impede efficient learning of dialogue strategies and compromise the performance of the model. To address this challenge, this paper introduces the Multi-Agent Curiosity Reward Model (MACRM) for task-oriented dialog systems. Firstly, in terms of dialog reward mechanisms, a forward dynamics model generates curiosity rewards, which are integrated with extrinsic rewards from the dialog environment feedback to mitigate the problem of sparse rewards resulting from inadequate agent exploration. Secondly, regarding the dialogue strategy training mechanism, an exploration-exploitation approach inspired by organismic exploration is adopted. This approach involves fully exploring the dialogue environment in the early stages and optimally exploiting learned knowledge later, thereby balancing exploration and exploitation and enhancing dialogue strategy learning efficiency. To assess the proposed model's effectiveness, experiments are conducted using the MultiWOZ corpus across three reward environments: (1) extrinsic rewards only, (2) curiosity rewards only, and (3) a combination of both. The experimental results demonstrate that agents employing MACRM exhibit faster learning of dialogue strategies compared to those relying on a single exploratory reward method, effectively addressing reward sparsity and delay issues in practical decision-making scenarios.

Opportunities and Challenges of Sustainable Innovation for Climate Change Mitigation in Companies: A Systematic Literature Review

ABSTRACTThe escalating environmental degradation and tightening regulations worldwide since the 1990s have heightened environmental concerns among organizations, necessitating innovative and sustainable responses to climate change. This article aims to explore opportunities and challenges of sustainable innovations for mitigating climate change within companies. A systematic literature review was conducted, encompassing 42 articles from 2005 to 2022. Most studies originate from European countries, particularly from institutions like Sapienza University of Rome, Jinan University, and Amsterdam Business School. Notable authors include Rosa Maria Dangelico, Ans Kolk, and Jonatan Pinkse. The most cited journals include Business Strategy and the Environment, Journal of Cleaner Production, and Sustainability (MDPI). Identified opportunities for companies embracing climate change mitigation through innovation include enhanced image and competitiveness. Challenges comprise high implementation costs, ambiguous sustainable development guidelines, partnership scarcity, technological risk uncertainties, consumer acceptance concerns, deficient tools for low‐carbon product development, and the sociotechnical system's influence. Moreover, companies face hurdles like reliance on supply chain complementary capabilities and regulatory uncertainties. Future research should prioritize less costly sustainability practices and examine the sociotechnical factor's impact on sustainable innovation adoption. Prohibitive investment costs hinder companies from embracing these practices, highlighting the need for cost‐effective alternatives. Understanding the sociotechnical dynamic's role in driving or obstructing sustainable innovation adoption is crucial for comprehensive analysis and effective strategy development.

Endothelial cells-derived exosomes-based hydrogel improved tendinous repair via anti-inflammatory and tissue regeneration-promoting properties

Tendon injuries are common orthopedic ailments with a challenging healing trajectory, especially in cases like the Achilles tendon afflictions. The healing trajectory of tendon injuries is often suboptimal, leading to scar formation and functional impairment due to the inherent low metabolic activity and vascularization of tendon tissue. As pressing is needed for effective interventions, efforts are made to explore biomaterials to augment tendon healing. However, tissue engineering approaches face hurdles in optimizing tissue scaffolds and nanomedical strategies. To navigate these challenges, an injectable hydrogel amalgamated with human umbilical vein endothelial cells-derived exosomes (HUVECs-Exos) was prepared and named H-Exos-gel in this study, aiming to enhance tendon repair. In our research involving a model of Achilles tendon injuries in 60 rats, we investigated the efficacy of H-Exos-gel through histological assessments performed at 2 and 4 weeks and behavioral assessments conducted at the 4-week mark revealed its ability to enhance the Achilles tendon’s mechanical strength, regulate inflammation and facilitate tendon regeneration and functional recovery. Mechanically, the H-Exos-gel modulated the cellular behaviors of macrophages and tendon-derived stem cells (TDSCs) by inhibiting inflammation-related pathways and promoting proliferation-related pathways. Our findings delineate that the H-Exos-gel epitomizes a viable bioactive medium for tendon healing, heralding a promising avenue for the clinical amelioration of tendon injuries.

Assessment of dietary supplementation of green iron oxide nanoparticles: impact on growth performance, ammonia emissions, carcass criteria, tissue iron content, and meat quality in broiler chickens under hot climate conditions.

The potential significance and importance of green iron nanoparticles (Nano-Fe) in poultry production lie in their capability to effectively tackle iron deficiency in poultry. Iron, an indispensable mineral for numerous physiological functions in birds, such as oxygen transport, energy metabolism, and immune response, underscores the critical need for adequate iron levels. Nevertheless, conventional iron supplementation methods frequently face hurdles like limited bioavailability rates in poultry. To enhance performance, and promote sustainable broiler productivity, Nano-Fe showed promise as an efficient feed supplement for broiler chickens. The objective of this study was to assess the impact of green Nano-Fe inclusions in diets on growth, ammonia excretion, carcass criteria, and meat quality in broiler chickens. A total of 192 one-day-old male Ross 308 broiler chicks, were assigned to three treatment diets including Nano-Fe oxide at 0, 20, or 40 mg/kg, respectively, for 42 days. Each treatment comprised eight replicates, each with eight broiler chicks. Two phases comprised the 42-day study (0 to 21 days for the starter and 21 to 42 days for the finisher). In comparison to the control group, the Nano-Fe oxide groups 20 mg/kg and 40 mg/kg linearly improved (p < 0.05) body weight (R 2 = 0.574) and body weight gain (R 2 = 0.367) under hot climatic conditions at 42 days of age. Furthermore, Nano-Fe oxide to broiler diets, improved (linear, p < 0.05) feed conversion ratio (R 2 = 0.424) throughout whole periods. The feed intake did not show any significant difference (p > 0.05) among groups during the experimental periods under hot climatic conditions. The ammonia content of excreta (R 2 = 0.454) was linearly decreased (p < 0.05) with increasing Nano-Fe oxide levels in broiler diets compared to control at 21 and 42 days of age under hot climatic conditions. Nano-Fe oxide positively influences cook loss, water-holding capacity, and iron content in various tissues. Moreover, it contributes to a healthier carcass yield and reduced abdominal fat. In conclusion, broiler chickens fed diets containing Nano-Fe oxide at 20 mg/kg and 40 mg/kg demonstrated enhanced growth performance, improved meat quality, increased iron content in tissues, higher dressing percentage, and reduced abdominal fat deposition. Future research should explore the impact of green Nano-Fe oxide on additional factors such as the microbiome and gene expression related to immunity and heat stress.

Unraveling the Factors Influencing Healthcare Accessibility: An In-depth Investigation in Jhenaidah Sadar Upazila

Healthcare plays a significant role in Bangladesh. The key to wealth is health. In the absence of healthcare development, we would not be able to live a quality lifestyle. In order for a nation to develop economically and socially, its health must be in good condition. It is reported that health services in Bangladesh are well funded by the government, but some issues affect the sector. A considerable proportion of Bangladesh's population lacks or has little access to healthcare services. There are several dimensions to the problem of lack of health service participation. This study evaluates, through collecting information from primary data, public health facilities' scarceness and identifies factors that act as barriers to the functioning effectively of public health facilities. The authors conducted qualitative research in order to gain an in-depth understanding of the underlying insights of various components that affect Bangladesh's healthcare sector. A purposive sampling style is followed to specify the respondents. The findings scrutinize the healthcare system in the selected areas of Bangladesh. It has explored what factors affect access to health services in urban areas of Bangladesh. It has also revealed patients’ views towards healthcare services. The findings from the qualitative data have unveiled that there are many key dimensions, in terms of various dimensions, that indicate why people face hurdles when accessing health services. Finally, the paper concludes with a variety of recommendations.

Direct observation of atmospheric turbulence with a video-rate wide-field wavefront sensor

Turbulence is a complex and chaotic state of fluid motion. Atmospheric turbulence within the Earth’s atmosphere poses fundamental challenges for applications such as remote sensing, free-space optical communications and astronomical observation due to its rapid evolution across temporal and spatial scales. Conventional methods for studying atmospheric turbulence face hurdles in capturing the wide-field distribution of turbulence due to its transparency and anisoplanatism. Here we develop a light-field-based plug-and-play wide-field wavefront sensor (WWS), facilitating the direct observation of atmospheric turbulence over 1,100 arcsec at 30 Hz. The experimental measurements agreed with the von Kármán turbulence model, further verified using a differential image motion monitor. Attached to an 80 cm telescope, our WWS enables clear turbulence profiling of three layers below an altitude of 750 m and high-resolution aberration-corrected imaging without additional deformable mirrors. The WWS also enables prediction of the evolution of turbulence dynamics within 33 ms using a convolutional recurrent neural network with wide-field measurements, leading to more accurate pre-compensation of turbulence-induced errors during free-space optical communication. Wide-field sensing of dynamic turbulence wavefronts provides new opportunities for studying the evolution of turbulence in the broad field of atmospheric optics.

Analisis Persepsi Pengguna Aplikasi Lalamove Dengan Menggunakan Metode Technology Acceptance Model (TAM)

A number of on-demand platforms have arisen with the goal of making the delivery of products easier for all members of society, and Lalamove is one of them. Technological improvements have been a big driver in the growth of the logistics business. The study's overarching goal is to investigate users' impressions and thoughts about the Lalamove app via an exploratory lens. To have a better grasp of the topic at hand, this descriptive qualitative study used a content analysis strategy, which entails reducing the amount of data collected. This study's sample was chosen using a non-probability sampling approach, with a focus on user reviews of the Lalamove app located on the Google Play Store marketplace. Based on the TAM, which centres on the two primary components of perceived utility and perceived ease of use, this model attempts to explain why people adopt new technologies. Based on these findings, it seems that the app is still not as user-friendly as it might be. Despite the app's usefulness in enhancing delivery effectiveness, customers still face hurdles such as connecting couriers with users, registration issues, order cancellation, a tracking system that isn't up to par, and payment options that don't fulfil their expectations. Because of this, the Lalamove app's general usefulness and convenience are diminished due to persistent issues.

Modulating nanostructures with polyvinylpyrrolidone: Design and development of a porous, biocompatible, and pH-Stable core-shell magnetic microrobot for demonstrating drug absorption from wastewater

Increased antineoplastic drug concentrations in wastewater stem from ineffective treatment plants and increased usage. Although microrobots are promising for pollutant removal, they face hurdles in developing a superstructure with superior adsorption capabilities, biocompatibility, porosity, and pH stability. This study focused on adjusting the PVP concentration from 0.05 to 0.375 mM during synthesis to create a favorable CMOC structure for drug absorption. Lower PVP concentrations (0.05 mM) yielded a three-dimensional nanoflower structure of CaMoO4 and CuS nanostructures, whereas five-fold concentrations (0.25 mM) produced a porous structure with a dense CuS core encased in a transparent CaMoO4 shell. The magnetically movable and pH-stable COF@CMOC microrobot, achieved by attaching CMOC to cobalt ferrite (CoF) NPs, captured doxorubicin efficiently, with up to 57 % efficiency at 200 ng/mL concentration for 30 min, facilitated by electrostatic interaction, hydrogen bonding, and pore filling of DOX. The results demonstrated that DOX removal through magnetic motion showed superior performance, with an estimated improvement of 57% compared to stirring conditions (17 %). A prototype PDMS microchannel system was developed to study drug absorption and microrobot recovery. The CaMoO4 shell of the microrobots exhibited remarkable robustness, ensuring long-lasting functionality in harsh wastewater environments and improving biocompatibility while safeguarding the CuS core from degradation. Therefore, microrobots are a promising eco-friendly solution for drug extraction. These microrobots show promise for the selective removal of doxorubicin from contaminated wastewater.

Enhancing Surgical Robotics: A Dynamic Model and Optimized Control Strategy for Cable-Driven Continuum Robots

Abstract This paper tackles the challenges encountered in surgical continuum robotics by introducing a dynamic model tailored for a cable-driven continuum robot. The intricacies of dynamic modeling and control frequently lead to suboptimal outcomes. Prior studies have often lacked comprehensive descriptions of individual robot component movements, thereby impeding control processes, especially in the presence of external disturbances. Although machine learning-based models show promise across different domains, they face hurdles in continuum robotics due to the complexity of the systems involved. Traditional mathematical models, in contrast, offer explicit equations, providing better interpretability, unlike machine learning models that may struggle with generalization, especially in highly nonlinear systems like continuum robots. The developed model adeptly captures the kinematic and dynamic constraints of various robot segments, serving as the foundation for a robust optimized control strategy. This strategy, which integrates computed torque control and particle swarm optimization (PSO-CTC), enables real-time computation of joint torques based on feedback, ensuring precise and stable task execution even amidst external perturbations. Comparative analysis with an optimized proportional integral derivative (OPID) controller unequivocally demonstrates the superiority of the optimized computed torque controller (OCTC) in settling time, overshoot, and robustness against disturbances. This advancement represents a noteworthy contribution to robotics, with the potential to significantly enhance continuum robot performance in surgical and inspection applications, thereby fostering innovative advancements across various fields.

Between war and peace: Exploring the role of refugee law in the context of Sudan political conflict

AbstractThe ongoing political turmoil gripping Sudan is fraught with violence between two opposing factions within its military government. This unsettling state of affairs has led to devastating consequences, including large‐scale displacement of people and severe human rights violations, causing dire humanitarian consequences. Against this tumultuous backdrop, we explore how existing refugee law, one facet of international law governing refugees, can help bring relief amidst a volatile conflict zone. Examining complex legal questions ranging from determining who qualifies for asylum status through various geographic considerations to what role states play in securing basic protections for refugees fleeing persecution or war at home will be analysed herein. Further difficulties involving how these complex provisions protect refugees face hurdles due to practical factors like lack of resources or security concerns will be considered thoroughly. While recognizing that instituting legal reforms alone is not enough to address these complex crises due to various challenges of reasons ranging from political to practical, this paper concludes by putting forth strategic recommendations for improvement aimed towards bolstering resources and support mechanisms required for refugees across the region to ensure they can seize‐hold of eventual solutions.

Decoding Innocence: Advancing Forensic Facial Discrimination through Comparative Analysis of Conventional CNN and Advanced Architectures

The field of Digital Image Forensics (DIF) faces a critical issue in accurately identifying children in digital images, notably in cases involving the proliferation of child sexual abuse content. Existing techniques face hurdles due to model architecture limitations, dataset suitability concerns, and classification imbalance, impeding their ability to recognize children to deter pornographic images. Addressing this challenge, this study introduces Implicit Feature Extraction (IFE), a specialized approach for distinguishing child and adult images in object detection. Leveraging Convolutional Neural Networks (CNNs), the IFE method automates the extraction of discriminative facial features, surpassing the constraints of Explicit Feature Extraction (EFE) methods, which achieve an accuracy of around 70%. The research focuses on three core objectives introducing IFE for detailed face feature detection in DIF's child and adult image identification, implementing IFE with CNNs to enhance image classification, and conducting a thorough evaluation of the proposed technique's performance using key metrics like accuracy and balanced classification results and comparing the result with a basic CNN model’s performance. This research's significance lies in its notable contributions to digital image forensics, particularly in combatting child exploitation. The fusion of IFE with CNNs showcases 92% accuracy in distinguishing child and adult images, promising advancements with practical implications in child protection and forensic investigations. The comprehensive evaluation using the UTKFace dataset underscores the proposed technique's efficacy, marking a substantial improvement in child image identification within digital image forensics.

Integrated operational model to analyse policies and socio-demography leading to selection of electric vehicle - A case study on Bihar

In the push for sustainability in the power sector, Electric Vehicles show substantial promise. However, they still face hurdles in replacing traditional combustion engine cars, which have dominated the market for decades. Consumer awareness, especially regarding new technologies like Electric Vehicles, remains a significant barrier to adoption. This study aims to bridge the gap between technical aspects and consumer knowledge and a case study is done on the Indian state of Bihar. Using a hybrid Multi-Criteria Decision-Making approach with Triangular Fuzzy Numbers, a customized model is presented to help residents choose the right Electric Vehicle based on their needs and resources. Results are analyzed from customers’ perspective using Quality Function Deployment and conduct Sensitivity Analysis to explore cost trends. This survey examines seven Electric Vehicle models available in India, with MG ZS Electric Vehicle emerging as a potential standout. It's important to note that this research work does not endorse any specific Electric Vehicle model; rather, a mathematical framework is build to guide customers in selecting an Electric Vehicle that suits their requirements.

Construction of Bi2WO6/g-C3N4/Cu foam as 3D Z-scheme photocatalyst for photocatalytic CO2 reduction

Photocatalytic CO2 reduction to hydrocarbon fuels represents a promising solution to CO2 emission challenges. However, photocatalytic CO2 reduction systems face hurdles in practical utilization for the low efficiency of photocatalysts and challenge in catalyst immobilization. Therefore, a novel monolithic three-dimensional Z-scheme photocatalyst was synthesized by fabricating Bi2WO6/g-C3N4 heterojunction on Cu foam substrate (Bi2WO6/g-C3N4/Cu foam) via thermal polymerization and electrophoresis deposition. A series of characterization results, including X-ray diffraction, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, scanning electron microscopy and N2 adsorption–desorption, illustrate the crystalline properties, pore structure, and morphology of the composite photocatalyst. Consequently, Bi2WO6/g-C3N4/Cu foam achieved CO production yield of 33.84 μmol/g cat under visible light illumination for 6 h and retained 96.2 % of initial photocatalytic activity after 30 h of reaction. UV–Vis diffuse reflection spectra, photoluminescence spectra and photoelectrochemical analysis was involved to reveal the mechanism of the photocatalytic activity of composite photocatalyst.The synergistic effect of the Z-scheme mechanism and the hierarchical macroporous structure improves the light absorption, light-induced electron-hole pair separation, and charge transmission. This catalyst construction strategy provides a viable approach for facilitating practical photocatalytic CO2 reduction.

“PERCEPTIONS AND CHALLENGES ENCOUNTERED BY TEACHERS WHO ARE CURRENTLY STRUGGLING TO IMPLEMENT ENGLISH AS A MEDIUM OF INSTRUCTION AT DENAU INSTITUTE OF ENTREPRENEURSHIP AND PEDAGOGY”

This study investigates the perceptions and challenges encountered by teachers tasked with implementing English as a medium of instruction at the field of Entrepreneurship and Management in Denau Institute of Entrepreneurship and Pedagogy. Amidst the global push for English language proficiency, many educational institutions, particularly in non-native English-speaking contexts, face hurdles in adopting English as the primary medium of instruction. Through qualitative research methods, including interviews and surveys, this study explores the perspectives of teachers navigating this transition. Findings reveal a range of challenges, including linguistic barriers, pedagogical adjustments, and cultural considerations. Moreover, the study sheds light on teachers' perceptions regarding the effectiveness and feasibility of English-medium instruction, providing valuable insights for educational policymakers and administrators.

Implementing digital innovations: Overcoming organizational challenges

While real estate owners play a significant role in advancing digitalization and sustainability within the sector, there's limited understanding of their innovation processes. This article aims to increase understanding on the innovation processes and dynamic capabilities in real estate owner organizations. The article examines a longitudinal case study within a prominent Swedish real estate owner known for significant investments in smart building technologies. Despite these investments, practical benefits face hurdles, reflecting broader challenges in real estate sector digitalization projects. These obstacles include top-down innovation focus, limited cross-functional and user-centric innovation, innovation process discontinuities, ambiguous innovator roles, hierarchical communication, resource constraints, and uncertainties in technology implementation. The study emphasizes the inclusion of diverse perspectives in innovation processes and suggests further research on organizational and user-centric aspects. It contributes to real estate and facility management literature by proposing potential solutions to innovation processes, offering valuable insights for industry practitioners and researchers alike.

Abstract 243: Organoid co-cultures with allogenic T cells to assess toxicity and efficacy of bispecific antibodies

Abstract Recent advances in cancer immunotherapy positively impacted the life expectancy of patients for an extensive range of clinical indications. With new treatment strategies, druggable targets and biomarkers being identified at an increasing pace, the number of patients eligible for cancer immunotherapy is expected to expand steadily. For example, the emerging Bispecific T cell Engagers (BiTEs) designed to simultaneously target CD3 and tumor-specific antigens and promote T cell cytotoxicity have seen recent clinical success. While BiTEs have been approved for the treatment of hematologic malignancies, promising therapeutic developments for solid tumors face hurdles in translating preclinical findings into therapy since conventional two-dimensional cancer models fail to recapitulate the immune cell interactions in the tumor microenvironment and therefore hold low clinical predictive value. We developed an innovative alternative, building on the discovery that adult stem cells proliferate and organize into three-dimensional organotypic structures that maintain complex characteristics of the original parental tissue, including molecular heterogeneity and morphological and functional traits. Here, we show the development of a patient-relevant preclinical platform for immunotherapy development in which colorectal (CRC) and non-small cell lung cancer (NSCLC) organoids are co-cultured with allogenic or autologous T cells to evaluate the activity and assess the cytotoxic potential of a BiTEs. The expression of tumor-specific BiTE target antigens is determined in patient-derived organoids (PDOs) by flow cytometry. Following this assessment, T cell-induced organoid death is quantified and characterized in real-time by image-based analysis of fluorescent live/dead dyes. Additionally, we measure cytokine secretion as a read-out of T cell activation and function. In our co-cultures, T cell-induced PDO death was increased upon BiTEs treatment. Similarly, IFNγ secretion correlated with expression levels of the targeted tumor antigen. In addition, PDO apoptosis and IFNγ secretion increased in a dose-dependent fashion in the presence of the TA-targeting TCB. In summary, our organoids and T cell co-cultures offer a powerful platform for developing and validating immunotherapies such as T cell-bispecific antibodies and will significantly contribute to our understanding of the critical factors determining successful immunotherapies. Citation Format: Cesar Oyarce, Virginia Bruno, Lorenzo Spagnuolo, Claudia Beaurivage, Javier Frias Aldeguer, Farzin Pourfarzad, Robert G. Vries, Sylvia F. Boj. Organoid co-cultures with allogenic T cells to assess toxicity and efficacy of bispecific antibodies [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 243.

Abstract 4256: Autologous organoids and T cell co-cultures as a powerful personalized platform for immunotherapy development

Abstract Recent advances in cancer immunotherapy have had a positive impact on the life expectancy of patients for an extensive range of clinical indications. With new treatment strategies and druggable targets being identified at an increasing pace, the number of patients eligible for cancer immunotherapy is expected to expand steadily. However, promising therapeutic developments face hurdles in translating preclinical findings into therapy since conventional 2D cancer models hold low clinical predictive value. We developed an innovative alternative, building on the discovery that adult stem cells proliferate and organize into three-dimensional organotypic structures when they are embedded into extracellular matrix. Patient-derived organoids are generated from normal and malignant tissues and stored as high-quality biobanks that yield highly reproducible results. HUB Organoids® recapitulate complex characteristics of the parental tissue, including molecular heterogeneity, as well as morphological and functional traits. Since cancer progression and response to immunotherapy are governed by immune cell interactions in the tumor microenvironment, we developed an assay in which colorectal (CRC) and non-small cell lung cancer (NSCLC) tumor organoids are co-cultured with paired tumor infiltrating lymphocytes (TIL) that are simultaneously expanded as a source of tumor reactive cells. Paired resources allow for the screening of immune-modulatory therapies under physiologic conditions, not depending on peptide-pulsing and alloreactivity. We quantify tumor organoid killing and TILs reactivity by combining imaging-based analysis of apoptotic cells with flow cytometry to measure cytokine release by cytotoxic TILs. Here, we show that our system is robust and reproducible with an establishment rate of 75%, allowing for expansion of TILs that preserve T cell receptor repertoires. First line expansion of both PDO and TIL components can be used to effectively build coculture models and probe the tumor and immune components, respectively. Our system offers a powerful tool for the development and validation of cancer immunotherapy and can help to stratify cancer patients for susceptibility to various types of immunotherapies. We certify that the research use of each of the HBS marked above was conducted according to the expectations of each institution. Citation Format: Claudia Beaurivage, BanuPriya Sridharan, Sumeyra Mucuk, Kimberly Nadwodny, Derek Poore, Anna Schepers, Farzin Pourfarzad, Sylvia F. Boj. Autologous organoids and T cell co-cultures as a powerful personalized platform for immunotherapy development [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 4256.