bluuebunny/crossref_metadata_2025 huggingface dataset:
Rainfall Assessment Using Weighted Interval Type-2 Fuzzy Inference System
Authors: Syed Aamir Adnan R. , Kumaravel R.
Published: March 2024

This study proposes an integrated model for assessing rainfall in Chennai using the Interval type-2 fuzzy reasoning technique and the Analytic Hierarchy Process (AHP). Interval Type-2 Fuzzy Inference System (IT2FIS) is employed to describe complex relationship between the rainfall variables and rainfall rate by considering individual weights of those variables through the aggregation of criteria weights using AHP. The suggested approach has an edge over its predecessors in terms of modeling the inter-personal and intra-personal uncertainty involved in rainfall rate classification. Finally, the developed rainfall model (RM) is applied on the historical dataset collected from Indian Meteorological Department (IMD). The actual data and the IT2FIS model’s performance are compared. Correlation coefficient ([Formula: see text]) and Bland–Altman Plot (BAP) have been used to evaluate the performance metrics of the proposed model. The outcome suggests that the AHP-IT2FIS model can accurately estimate rainfall over time, indicating its potential for long-term use.
Indoloquinoxaline-based organic material enabling multi-stimuli response
Authors: Mao Guanghao , Zhang Caihang , Hua Chijun , Deng Ping , Yu Yan
Published: March 2024

A new triphenylethylene-modified indolo[2,3-[Formula: see text]]quinoxaline TPE-IQ has been synthesized by a mild Suzuki-Miyaura coupling reaction. The thermal, electrochemical, photophysical, aggregation, and acidofluorochromic and mechanofluorochromic properties were investigated. TPE-IQ shows typical solvatochromism and aggregation-induced emission enhancement features. TPE-IQ also exhibits interesting reversible acid and mechanical force-responsive properties. This work highlights the development of multi-stimuli responsive organic material containing indolo[2,3-[Formula: see text]]quinoxaline moiety.
A Real-to-Sim-to-Real Approach for Vision-Based Autonomous MAV-Catching-MAV
Authors: Ning Zian , Zhang Yin , Lin Xiaofeng , Zhao Shiyu
Published: March 2024

This paper studies the task of vision-based MAV-catching-MAV, where a catcher MAV (micro aerial vehicle) can detect, localize, and pursue a target MAV autonomously. Since it is challenging to develop detectors that can effectively detect unseen MAVs in complex environments, the main novelty of this paper is to propose a real-to-sim-to-real approach to address this challenge. In this method, images of real-world environments are first collected. Then, these images are used to construct a high-fidelity simulation environment, based on which a deep-learning detector is trained. The merit of this approach is that it allows efficient automatic collection of large-scale and high-quality labeled datasets. More importantly, since the simulation environment is constructed from real-world images, this approach can effectively bridge the sim-to-real gap, enabling efficient deployment in real environments. Another contribution of this paper lies in the successful implementation of a fully autonomous vision-based MAV-catching-MAV system including proposed estimation and pursuit control algorithms. While the previous works mainly focused on certain aspects of this system, we developed a completely autonomous system that integrates detection, estimation, and control algorithms on real-world robotic platforms.
Inferring Transcriptional Bursting Kinetics Using Gene Expression Model with Memory and Crosstalk from scRNA-seq Data
Authors: Wang Mengyuan , Cao Wenjie , Guo Yanbing , Wang Guilin , Jiang Jian , Qiu Huahai , Zhang Ben-Gong
Published: March 2024

Genetically identical cell populations growing in the same environment show a large degree of heterogeneity in gene expression profiles, resulting in significant phenotypic consequences. One of the important sources of this heterogeneity is transcriptional bursting. In recent years, single cell transcriptome sequencing (scRNA-seq) data have been widely used to infer the kinetics of transcriptional bursting. Moreover, the increasing evidence showed that genes are jointly regulated by several competitive pathways when activated by external signals, and there is molecular memory in the process of gene state switching. Therefore, a gene expression model considering both gene activation pathway and molecular memory can better reflect the nature of transcriptional bursting. In this paper, we used an approximate Bayesian computation algorithm called ABC-PRC combined with a gene expression model that considered crosstalk and memory, to infer the kinetics of transcriptional bursting. We analyze the internal relationship between transcriptional bursting and gene expression using scRNA-seq data obtained from mouse embryonic stem cells and mouse embryonic fibroblasts. Both model analysis and data simulations demonstrate that the bimodal coefficient increases with the increase of burst size, and the noise intensity decreases with the increase of burst frequency. Additionally, we show that some previously proposed models can be simplified as special cases of the gene expression model and inference algorithm proposed here under certain circumstances.
Dynamic Placement in Refugee Resettlement
Authors: Ahani Narges , Gölz Paul , Procaccia Ariel D. , Teytelboym Alexander , Trapp Andrew C.
Published: March 2024

Employment outcomes of resettled refugees depend strongly on where they are placed inside the host country. While the U.S. sets refugee capacities for communities on an annual basis, refugees arrive and must be placed over the course of the year. We introduce a dynamic allocation system based on potentials derived from dual prices of a linear programming (LP) relaxation to improve employment outcomes. Our algorithm achieves over 98% of the hindsight- optimal employment compared to under 90% of current greedy-like approaches. This dramatic improvement persists even when we incorporate a vast array of practical features of the refugee resettlement process including indivisible families, batching, and uncertainty with respect to the number of future arrivals. Our algorithm is now part of the
Annie
™
Moore optimization software used by a leading American refugee resettlement agency.
A Survey on the Densest Subgraph Problem and its Variants
Authors: Lanciano Tommaso , Miyauchi Atsushi , Fazzone Adriano , Bonchi Francesco
Published: March 2024

The Densest Subgraph Problem requires us to find, in a given graph, a subset of vertices whose induced subgraph maximizes a measure of density. The problem has received a great deal of attention in the algorithmic literature since the early 1970s, with many variants proposed and many applications built on top of this basic definition. Recent years have witnessed a revival of research interest in this problem with several important contributions, including some groundbreaking results, published in 2022 and 2023. This survey provides a deep overview of the fundamental results and an exhaustive coverage of the many variants proposed in the literature, with a special attention to the most recent results. The survey also presents a comprehensive overview of applications and discusses some interesting open problems for this evergreen research topic.
Characterizing the Effect of Mind Wandering on Braking Dynamics in Partially Autonomous Vehicles
Authors: Sridhar Harini , Huang Gaojian , Thorpe Adam , Oishi Meeko , Pitts Brandon J.
Published: March 2024

Partially autonomous driving systems may require the human driver to take control at any moment, yet by their design, they often cause difficulty with attention management. In this preliminary study, we propose a data- and dynamics-driven approach to characterize driving performance in a partially autonomous vehicle during a manual braking event, under attentive or mind wandering states. A 10-participant experiment was completed in an advanced driving simulator. We employ a non-parametric learning technique, conditional distribution embeddings, to the driving simulator data, to evaluate likelihood of successfully completing the braking maneuver, under both attentive and mind wandering states. Our approach shows a statistically significant difference in braking profiles during mind wandering and non-mind wandering episodes for each participant. Our results reveal that heterogeneity in driving performance may have important implications for the design of autonomy that is responsive to attentional states. Data-driven tools, such as the one proposed here, may be useful in designing participant-specific alerts and warnings for control handovers and other safety-critical maneuvers, because of their potential to accommodate heterogeneous response.
Xylem: An Energy-efficient, Globally Redistributive, Financial Infrastructure Using Proof-by-Location
Authors: Patterson Donald Jay , Tomlinson Bill
Published: March 2024

The Proof-of-Work algorithm that underlies Bitcoin, Ethereum
w
,

1

and many other cryptocurrencies is well known for its energy-intensive requirements. The Proof-of-Stake algorithm that underlies Ethereum and various other cryptocurrencies is less impactful environmentally, but it has a second, looming issue: the problem of wealth inequality. We have developed an alternative to Proof-of-Work and Proof-of-Stake, called Proof-by-Location, that has the potential to address both of these issues. This article describes Proof-by-Location and a financial platform called Xylem that is based on it. This platform seeks to distribute transaction fees to billions of cryptocurrency “Notaries” around the world (essentially, anyone with a smartphone), who work together to establish a distributed consensus about financial transactions. In this article, we demonstrate that this platform can scale to more than 3.9 trillion transactions per year (more than triple the number of digital payments per year currently occurring). We show a reduction of electricity usage per transaction of 99.9999914% compared to Bitcoin, 99.999905% compared to Ethereum
w
, 99.83% compared to Ethereum, and 95.9% compared to the Visa financial services company. We demonstrate that this platform would have a redistributive rather than consolidatory effect on wealth compared to any of these platforms, leading to a source of income for more than 1 billion people around the world, including more than 110 million in the bottom 10th to 20th percentile by income, with income for that group equivalent to 8.8 million full-time jobs. Finally, this currency provides a positive, non-compulsory mechanism for shaping human habitation patterns in ways that can slow global biodiversity loss and enable ecological restoration. Using Xylem as a global financial infrastructure could lead to significantly better social and environmental outcomes than existing financial platforms.

2
Listwise Generative Retrieval Models via a Sequential Learning Process
Authors: Tang Yubao , Zhang Ruqing , Guo Jiafeng , de Rijke Maarten , Chen Wei , Cheng Xueqi
Published: March 2024

Recently, a novel generative retrieval (GR) paradigm has been proposed, where a single sequence-to-sequence model is learned to directly generate a list of relevant document identifiers (docids) given a query. Existing GR models commonly employ maximum likelihood estimation (MLE) for optimization: This involves maximizing the likelihood of a single relevant docid given an input query, with the assumption that the likelihood for each docid is independent of the other docids in the list. We refer to these models as the pointwise approach in this article. While the pointwise approach has been shown to be effective in the context of GR, it is considered sub-optimal due to its disregard for the fundamental principle that ranking involves making predictions about lists. In this article, we address this limitation by introducing an alternative listwise approach, which empowers the GR model to optimize the relevance at the docid list level. Specifically, we view the generation of a ranked docid list as a sequence learning process: At each step, we learn a subset of parameters that maximizes the corresponding generation likelihood of theith docid given the (preceding) topi-1 docids. To formalize the sequence learning process, we design a positional conditional probability for GR. To alleviate the potential impact of beam search on the generation quality during inference, we perform relevance calibration on the generation likelihood of model-generated docids according to relevance grades. We conduct extensive experiments on representative binary and multi-graded relevance datasets. Our empirical results demonstrate that our method outperforms state-of-the-art GR baselines in terms of retrieval performance.
Morphological Properties and Electrochemical Performance for Compressed Carbon-fiber Electrodes in Redox Flow Batteries
Authors: Liu Baichen , Simonsen Søren Bredmose , Hjelm Johan
Published: March 2024

Improving reactor performance of redox flow batteries is critical to reduce capital cost, and one of the main contributions to the internal resistance is generated by the electrodes, which also impact the pressure drop of the stack. Porous electrodes with optimized microstructure and physiochemical properties play a key role in enhancing electrochemical and fluid dynamic performance. Electrode compression significantly impacts morphology and battery behavior, but the relationship between microstructure and performance remains unclear. In the present study, three representative, commercially available, carbon-fiber electrodes (i.e., paper, felt, and cloth) with distinct microstructures were investigated, and a comprehensive study was conducted to compare morphology, hydraulic permeability, mechanical behavior, electrochemical performance in a lab-scale vanadium redox flow battery at compression ratios of 0%–50%. The 3D electrode morphology was characterized through X-ray computed tomography and the extracted microstructure parameters (e.g., surface area and tortuosity) were compared with corresponding electrochemically determined parameters. The optimal trade-off between fluid dynamics and electrochemical performance occurred at the compression ratios of 30%, 20%, and 20% for the felt, paper, and cloth, respectively. Owing to the bi-modal porosity of the woven microstructure, the cloth showed a better trade-off between the electrochemical performance and pressure drop than the other electrodes.
Exceptional Performance of Li-ion Battery Cells with Liquid Electrolyte at 100 °C
Authors: Tuul Kenneth , Maher Sasha Martin , Floras Claire , Black William , Taskovic Tina , Chisholm Sam , Clarke Alison , Lust Enn , Dahn J. R.
Published: March 2024

Single crystal NMC640/artificial graphite cells balanced for low voltage operation (≤4.1 V) and using electrolyte salts rich in lithium bis(fluorosulfonyl)imide are demonstrated to have exceptional lifetime during continuous operation at 100 °C. Cells tested to an upper cutoff voltage of 4.0 V retained >80% of their original capacity for 600 cycles and 4300 h at 100 °C and 1200 cycles and 1 year cycling to 3.9 V at 85 °C. The cells exhibited minimal gassing, no transition metal dissolution from the positive electrode, and no detectable corrosion of the aluminum current collector. Ultra-high precision coulometry measurements from 20 to 100 °C suggest an Arrhenius-type relationship for the coulombic inefficiency and capacity fade of these cells. The possibility of exploiting this relationship to project ambient temperature lifetime from high-temperature measurements is suggested. However, cell performance at the highest temperatures is most likely reduced by the permeation of electrolyte through the seals of the pouch cell.
Research on Vehicle Vibration Fatigue Damage Potential under Non‐Gaussian Road Profile Excitation
Authors: Xu Fei , Chen Zhifeng , Ahlin Kjell
Published: March 2024

The amplitude modulation method was used to generate a non‐Gaussian road profile with prescribed power spectral density (PSD) and kurtosis. The vehicle vibration fatigue damage potential has been proven to be closely related to the amplitude modulation signal (AMS) and kurtosis of vehicle response. In this paper, the iterative method of AMS modelling based on absolute standard Gaussian distribution is first reviewed. To address the long iteration time problem, a closed‐form formulation is presented to construct the AMS directly. Furthermore, by proving that the vehicle response under a slowly varying non‐Gaussian road profile excitation can be regarded as the product of the same AMS and vehicle response under a Gaussian road profile excitation with the same PSD, the theoretical relationship between fatigue damage spectrum (FDS) of vehicle response under non‐Gaussian and corresponding Gaussian road profiles is formulated based on the AMS. A case study is used to verify the proposed approach. The results show that a wide range of specified kurtosis of road profile can be achieved and the kurtosis of vehicle response is the same as for the road profile. Given kurtosis and fatigue exponent, the extra fatigue damage caused by non‐Gaussian road profile can be derived easily from the corresponding Gaussian road profile without calculating the vehicle response, which lays the foundation for a significantly simplified and more accurate fatigue test of vehicle vibration under non‐Gaussian road profile.
A Mathematical Model for the Dynamics of Income Distribution in the Presence of Production
Authors: Bertotti Maria Letizia
Published: March 2024

In this paper, a mathematical model is formulated, suitable to explain the evolution of income distribution over a population in the presence of production. The model is conceived from the perspective of complexity. Indeed, the income distribution emerges as the result of a myriad of economic exchanges taking place between individuals. In fact, the aim of the paper is to provide a framework and mathematical tools for the construction and the investigation of models having an exploratory character. The framework is expressed in the form of a system of nonlinear ordinary differential equations, as many as the income classes are, involving transition probabilities. Numerical solutions of these systems are constructed under different assumptions on the law of production and in the presence of different fiscal systems, which provides an example of the versatility of the method.
Meningitis and Bacteremia by Unusual Serotype of Salmonella enterica Strain: A Whole Genome Analysis
Authors: Brek Thamer , Gohal Gassem A. , Yasir Muhammad , Azhar Esam I. , Al-Zahrani Ibrahim A.
Published: March 2024

Background. Although meningitis caused by Salmonella species is relatively rare and accounts for <1% of the confirmed cases in neonates, it is associated with case complications and fatality rates up to 50–70% when compared to other forms of Gram-negative bacilli meningitis. Objectives. We conducted an investigation into the first reported case of neonatal meningitis caused by nontyphoidal S. enterica in Jazan, a region in the southwestern part of Saudi Arabia. Methods. CSF and blood culture were collected from a female neonate patient to confirm the presence of bacterial meningitis. WGS was conducted to find out the comprehensive genomic characterization of S. enterica isolate. Results. A 3-week-old infant was admitted to a local hospital with fever, poor feeding, and hypoactivity. She was diagnosed with Salmonella meningitis and bacteremia caused by S. enterica, which was sensitive to all antimicrobials tested. WGS revealed the specific strain to be S. enterica serotype Johannesburg JZ01, belonging to ST515 and cgMLST 304742. Conclusions. We presented a genomic report of rare case of NTS meningitis in an infant who is living in a rural town in Jazan region, Saudi Arabia. Further research is required to understand the impact of host genetic factors on invasive nontyphoidal Salmonella infection.
TLR3 Agonist Amplifies the Anti‐Inflammatory Potency of ADSCs via IL‐10‐Mediated Macrophage Polarization in Acute Pancreatitis
Authors: Liu Jianxing , Yan Wenjing , Chen Shanshan , Sun Yingjie , Zhang Fangfang , Yang Yue , Jin Liang
Published: March 2024

The immunoregulatory role of mesenchymal stem cells (MSCs) in inflammation is heterogeneous and can exhibit anti‐inflammatory or proinflammatory properties depending on the microenvironment. We herein observed that the activation of Toll‐like receptor 3 (TLR3) by polyinosinic : polycytidylic acid (poly(I : C)) stimulation facilitated the transformation of adipose‐derived stem cells (ADSCs) into an anti‐inflammatory phenotype. The enhanced anti‐inflammatory properties were assessed in a taurocholate‐induced pancreatitis model. The results demonstrated that poly(I : C) pretreated ADSCs exhibited enhanced anti‐inflammatory properties than untreated ADSCs in taurocholate‐induced pancreatitis. Mechanistically, poly(I : C)‐treated ADSCs showed increased production and secretion of interleukin‐10 (IL‐10), which demonstrates a potent ability to alleviate inflammatory signaling cascades in acinar cells. Simultaneously, the heightened anti‐inflammatory effects of poly(I : C)‐treated ADSCs in pancreatitis were associated with the regulation of macrophage classical/alternative transformation, thereby mitigating inflammatory factor‐mediated damage to the pancreatic acinar cell. We propose that TLR3 activation by poly(I : C) is an effective strategy to enhance the anti‐inflammatory properties of MSCs, which offers a valuable consideration for improving the therapeutic efficacy of MSCs in inflammatory diseases.
Bifurcation Analysis of the Dynamics in COVID‐19 Transmission through Living and Nonliving Media
Authors: Wiraya Ario , Fitriana Laila , Triyanto  , Adi Yudi Ari , Kusumadewi Yuvita Andriani , Khoirunnisa Sarah
Published: March 2024

Transmission of COVID‐19 occurs either through living media, such as interaction with a sufferer, or nonliving objects contaminated with the virus. Recovering sufferers and disinfectant spraying prevent interaction between people and virus become the treatment to overcome it. In this research, we formulate a new mathematical model as a three‐dimensional ordinary differential equation system representing an interaction between viruses attached in nonliving media, susceptible, and infected subpopulations, including the treatment to investigate its effect. Disease‐free, sterile‐media endemic, and two nonsterile media endemic equilibriums exist in the model. The nonexistence of sterile‐media equilibria interpreting the nonendemic condition is achieved by crossing the branch point bifurcation of the equilibria point as the infected subpopulation recovery rate increases. Continuation of the limit cycle generated at a Hopf bifurcation point as susceptible‐coronavirus interaction prevention rate and period increase trigger two saddle‐node bifurcations and a branch point bifurcation of cycle. Stable symmetric cycles with decreasing amplitude that make the dynamic of subpopulation easier to control start to be gained at the branch point bifurcation of cycle between the two saddle‐node bifurcation points as the prevention rate increases. Some chaotic attractors which describe a complex and unpredictable pattern of the dynamic in the population are also found at inclination flip bifurcation by a continuation of a homoclinic orbit generated near the Bogdanov‐Takens bifurcation point as the prevention rate increases while the recovery rate decreases. Increasing the recovery and prevention rate along with avoiding an increase of the prevention rate while the recovery rate decreases becomes the treatment to optimize the effort in overcoming COVID‐19 transmission.
Abstract 1045: A freely expandable 20-plex immuno-oncology antibody core panel for spatial biology experiments on human FFPE cancer sections: REAplex IO Core for MICS technology
Authors: Femel Julia , DiBasio Eric C. , Schönborn Katrin , Büttner Maximilian , Düking Tim , Habich Markus , Wantenaar Tanya , Eulitz Stefan , Bosio Andreas
Published: March 2024

Spatial biology is integral to understanding the dynamics of immune cells, tumor microenvironment (TME), and therapeutic responses in cancer research. Ultra-high-plex immunofluorescence has transformed deep phenotyping and cell neighborhood analysis, providing unprecedented insight into complex and heterogeneous samples such as the TME. Many spatial biology platforms reduce operator hands-on time by automating image acquisition. However, determining the most appropriate markers to distinguish key cell types, finding application-compatible antibody clones and optimizing their dilution remains a tedious manual process. To streamline the panel-building process, we have developed a series of pre-defined, commercially available antibody panels for the MACSima™ Imaging Cyclic Staining (MICS) technology. So far, these have covered the spectrum from ultra-high-plex screening panels with up to 205 antibodies (REAscreen™ MAX) to the more focused REAscreen Immuno Oncology antibody panel with 61 cancer and immune-related antibodies for the comprehensive analysis of various different human FFPE samples. Here, we introduce a new, 20-plex, pre-defined antibody panel. Organized along essential marker groups, it can function as a stand-alone panel that allows the identification of the major tumor-infiltrating leukocyte populations with a focus on T-cells, and providing insight into TME architecture, tumor neovascularization, and cellular activity. Because it can be combined and expanded with any number of antibodies or even entire panel modules, it can be used as a standardized basis for highly multiplexed custom panels optimized for the research question at hand. We demonstrate its performance and broad applicability across several cancer types analyzed with the MICS technology. Finally, preset template examples for panel-specific data processing with MACS iQ View analysis software demonstrate the simplicity yet power of an integrated end-to-end workflow.

Citation Format: Julia Femel, Eric C. DiBasio, Katrin Schönborn, Maximilian Büttner, Tim Düking, Markus Habich, Tanya Wantenaar, Stefan Eulitz, Andreas Bosio. A freely expandable 20-plex immuno-oncology antibody core panel for spatial biology experiments on human FFPE cancer sections: REAplex IO Core for MICS technology [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 1045.
Abstract 1060: Circulating early myeloid derived suppressor cells as biomarkers for early detection of lung cancer
Authors: Fortunato Orazio , Bassani Barbara , Lecchi Mara , Verderio Paolo , Pastorino Ugo , Sozzi Gabriella , Colombo Mario Paolo , Sangaletti Sabina
Published: March 2024

Background. Lung cancer (LC) patients, despite innovative cancer treatments such as target and immune-therapies, still have the poorest five-year survival rate. In this context the possibility of an early detection can anticipate therapeutic intervention, avoiding aggressive therapies thus prolonging disease-free and overall survival. Therefore, the identification of new circulating early biomarkers still represents a relevant clinical need.

Methods. Lung cancer (LC) patients (n=63) and heavy smokers (HS) cancer free-subjects (n=52) were evaluated for the enrichment of specific subtypes of myeloid cells. Circulating early myeloid derived suppressor cells (eMDSCs) and low-density neutrophils (LDNs) were assessed by flow cytometry on peripheral blood mononuclear cells (PMBCs). Early MDSCs were defined as CD11b+CD33+CD15-CD14- cells among Lineage negative (Lin-) HLA-DR- PBMCs, whereas LDNs were defined as CD66b+CD15+ cells within the gate of CD11b+ PBMCs. Mature and immature subtypes were discriminated according to the expression of CD10.

Results. Performing a sex- and smoking -matched case-control analysis in 39 LC and 39 HS subjects we were able to compare the capacity of specific myeloid population to discriminate lung cancer patients from heavy smokers. The analysis showed significantly higher values of eMDSC (OR=1.12; 95% Confidence Interval (CI) 1.03-1.21), total LDN (CD66b+CD15+; OR=1.23; 95%CI 1.04-1.45) and of mature CD10+ LDN (OR=1.30; 95%CI 1.05-1.61). Moreover, within the overall cohort of 63 LC patients, we analyzed the distributions of the different myeloid populations according to stage (I-II vs III-IV). In this comparison, total LDN (CD66b+CD15+; Kruskal-Wallis (KW) Test p-value=0.014), and mature CD10+ LDN (KW test p-value=0.006) showed significant different distributions according to tumor stage, observing higher values in patients with advanced stage. On the contrary, no difference among stages was observed for the eMDSC population.

Conclusions. These findings point to eMDSCs as an early marker for lung cancer detection whereas LDN could be as well associated with disease progression.

Citation Format: Orazio Fortunato, Barbara Bassani, Mara Lecchi, Paolo Verderio, Ugo Pastorino, Gabriella Sozzi, Mario Paolo Colombo, Sabina Sangaletti. Circulating early myeloid derived suppressor cells as biomarkers for early detection of lung cancer [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 1060.
Abstract 1115: Enhancing lung cancer sensitivity to chemotherapy, radiation, and chemo-radiation through inhibition of a mitotic checkpoint kinase BUB1
Authors: Thoidingjam Shivani , Sriramulu Sushmitha , Brown Stephen L. , Siddiqui Farzan , Movsas Benjamin , Gadgeel Shirish , Nyati Shyam
Published: March 2024

Non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) represent two major subtypes of lung cancer, marked by challenging treatment resistance. Our study explores the inhibition of BUB1, a critical mitotic checkpoint kinase, in conjunction with radiotherapy and chemotherapy. This approach has the potential to overcome resistance, thus enhancing the efficacy of treatment and improving treatment outcomes for lung cancer patients. We analyzed BUB1 expression in lung cancer using TCGA datasets and patient tissue microarrays (TMAs). In vitro experiments used four NSCLC and two SCLC cell lines with BUB1 inhibitor (BAY1816032), Paclitaxel, Cisplatin and Olaparib. Cells were irradiated (2, 4, or 6 Gy), and assays measured proliferation, long-term effects, DNA damage, and repair. Bioinformatic analysis in NSCLC subtype, lung adenocarcinoma (LUAD) demonstrated marked overexpression of BUB1, correlated with cancer stage, tumor grade and survival. Lung cancer TMAs revealed elevated expression of BUB1 protein in SCLC that correlated with poorer survival. BUB1 inhibition (BUB1i) induced cytotoxicity in LUAD cell lines at micromolar concentrations, while nanomolar concentrations enhanced cell death significantly when combined with radiation. Furthermore, BUB1i sensitized LUAD cells to different classes of chemotherapy (Paclitaxel, Cisplatin), and PARP inhibitor (Olaparib) alone (chemo-sensitization) or with radiation therapy (chemo-radiosensitization). H2030 and H1975 demonstrated higher chemo-radiosensitization efficacy compared to A549, likely due to genetic differences, potentially including a p53 mutation that improves sensitivity by affecting DNA repair and cell cycle regulation. Preliminary investigations revealed DNA double-strand breaks, indicated by prolonged γH2AX foci, and the inhibition of the NHEJ DNA damage repair pathway after BUB1 ablation. Among SCLC cell lines, NCI-H1876 demonstrated higher radiosensitivity upon BUB1 ablation compared to NCI-H2198, potentially due to genetic differences/mutations affecting radiation response. The study highlights the potential of BUB1i in enhancing the sensitivity of NSCLC and SCLC cells to radiotherapy and chemotherapy and provide rationale to explore BUB1i as a novel approach to enhance lung cancer therapy in clinical trials.

Citation Format: Shivani Thoidingjam, Sushmitha Sriramulu, Stephen L. Brown, Farzan Siddiqui, Benjamin Movsas, Shirish Gadgeel, Shyam Nyati. Enhancing lung cancer sensitivity to chemotherapy, radiation, and chemo-radiation through inhibition of a mitotic checkpoint kinase BUB1 [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 1115.
Abstract 1177: The chronology of immune-related adverse events (irAEs)-mechanistic implications
Authors: Mazahreh Farah , Safar Haya , Mazahreh Liyan , Safar A. Mazin
Published: March 2024

Immune Oncology (IO) is a novel component of the oncology armamentarium given its distinct mechanism of action, and by extension, unique mechanisms of toxicity (Tx). To recognize these unusual Txs, the term irAEs was popularized in clinical trials. Most organs have been involved by irAEs and autoimmunity has been implicated commonly by practicing oncologists. The onset of irAEs has not been studied well, however. We reasoned that autoimmune phenomena would be expected early after IO, since this is the timeframe within which T-cells expand to exert their effects on tumor and other ‘self’ tissues. It follows that if autoimmunity is the sole mechanism of irAEs, such toxicities should be reported early. Mechanism(s) of irARs may prove important for IO duration discussions. In some cases, tumor antigenic epitopes may mimic self-tissues, and in such cases irAEs develop early after initiation of IO. We hypothesized that irAEs have distinct chronology: earlier events representing autoimmunity (unavoidable); later events reflecting an intercurrent exposure to an antigen (e.g., virus) and therefore are avoidable by limiting duration of IO. Methods: We reviewed published IO monotherapy trials if individual patient data (swimmers’ plot) were reported. We derived the timing and frequency of Tx. We used therapy discontinuation without progressive disease as a surrogate for Tx if reported before the planned 24 months IO therapy.Results: Table depicts the data on included clinical trialsConclusion: The emergence of irAEs after IO extends over a protracted periods with 86% of events occurring beyond 4 months of IO. Though responses occasionally develop late after IO, for Tx consideration, T-cell expansion starts within days of IO initiation, and if autoimmunity is the mediator of Tx, irAEs would emerge only early. Our results suggest dual mechanisms and provide one more impetus to consider shortening IO duration.

Tumor Author Discontinued IO (n) Months of IO Discontinuation 0-2 3-4 5-6 7-8 9-10 11-12 13-14 15-16 17-18 19-20 21-22 NSCLC Topalian 12 1 1 4 1 1 3 1 Dart 11 3 4 3 1 Warburton 56 2 2 7 8 7 22 1 3 1 2 1 Melanoma Topalian 13 4 1 2 1 2 2 1 Weber 2 1 1 Demetriou 66 8 4 6 5 6 10 6 10 6 5 RCC Topalian 3 1 2 Total 163 14 10 15 25 14 38 9 15 10 11 2 8% 6% 9% 15% 8% 23% 5% 9% 6% 7% 1%

Citation Format: Farah Mazahreh, Haya Safar, Liyan Mazahreh, A. Mazin Safar. The chronology of immune-related adverse events (irAEs)-mechanistic implications [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 1177.
Abstract 1203: Mushroom: a tool for identification of 3D cellular neighborhoods in multi-modal spatial datasets
Authors: Storrs Erik , Chen Siqi , Mo Chia-Kuei , Houston Andrew , Shinkle Andrew , Southard-Smith Austin , Simin Faria , Targino Andre , Li Xiang , Abedin Ateih , Jayasinghe Reyka , Karpova Alla , Liu Jingxian , Herndon John , Fenyo David , Chen Feng , Fields Ryan , Ju Tao , Raphael Ben , Ding Li
Published: March 2024

A comprehensive understanding of the spatial localization of cellular processes is necessary to fully describe tissue biology. Numerous techniques exist to identify cellular neighborhoods in spatial datasets, however, these techniques are limited in that they either only capture two-dimensional phenomena - and can't describe the full, 3-dimensional tumor volume, or they are restricted to one spatial technology (i.e. IF, 10X Visium, Xenium, MERFISH, etc.). To address this, we developed Mushroom, a tool for identification of three-dimensional cellular neighborhoods in serial-sectioned multi-modal datasets. Mushroom’s methodology consists of two main steps: 1) registration of multi-modal technologies taken in serial sections (such as multiplex imaging, H&E, or spatial transcriptomics), and 2) identification of 3-dimensional cellular neighborhoods comprising the tissue volume that has been serially sectioned. Keypoint registration is performed with BigWarp, after which the resulting dense displacement field (DDF) is used to register neighboring serial sections - including those from different data modalities. We then implement a neural network to identify three dimensional cellular neighborhoods. The network is a variational autoencoder (VAE) with a vision transformer (VIT) backbone that has been adapted to work with multiple spatial data modalities. Features extracted from the VIT backbone are then clustered to identify cellular neighborhoods unique to each input data type. With 3D neighborhoods in hand, biological questions not answerable in traditional 2D approaches can be investigated, such as z-dimensional changes in morphology and cellular interactions. Further, seamless characterization of cellular neighborhoods by simultaneous technologies at multiple levels of spatial and genomic resolution becomes possible.

Citation Format: Erik Storrs, Siqi Chen, Chia-Kuei Mo, Andrew Houston, Andrew Shinkle, Austin Southard-Smith, Faria Simin, Andre Targino, Xiang Li, Ateih Abedin, Reyka Jayasinghe, Alla Karpova, Jingxian Liu, John Herndon, David Fenyo, Feng Chen, Ryan Fields, Tao Ju, Ben Raphael, Li Ding. Mushroom: a tool for identification of 3D cellular neighborhoods in multi-modal spatial datasets [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 1203.
Abstract 1229: BDTX-1535: A MasterKey EGFR inhibitor targeting classical and non-classical oncogenic driver mutations and the C797S acquired resistance mutation to address the evolving molecular landscape of EGFR mutant NSCLC
Authors: Dardenne Etienne , O'Connor Matthew , Nilsson Monique , He Junqin , Yu Xiaoxing , Heymach John V. , Le Xiuning , Buck Elizabeth
Published: March 2024

The molecular landscape of EGFR mutated NSCLC has evolved over time in response to changing treatment practices with EGFR inhibitors and through the expanding use of NGS. With the replacement of first-generation reversible EGFR tyrosine kinase inhibitors (TKIs) by the third generation covalent TKI osimertinib as front-line therapy for patients with NSCLC expressing classical EGFR mutations, acquired resistance mutations have shifted with the near disappearance of EGFR-T790M and the emergence and growing incidence of EGFR-C797S. Our understanding of the EGFR mutation landscape has also continued to mature with comprehensive sequencing across all EGFR exons and with the vast majority of patients now undergoing sequencing. We now see how classical oncogenic drivers represent only a subset of oncogenic EGFR driver mutations and where other non-classical driver mutations are numerous and represent a major unmet medical need. Furthermore, there is a growing appreciation of the differences between the classical EGFR-L858R and EGFR-Ex19 deletion (Ex19del) mutations. For patients expressing L858R, many co-express non-classical drivers and this may explain the weaker relative activity for osimertinib in patients expressing L858R versus Ex19del. For patients expressing Ex19del, the co-expression of non-classical mutations is less common. In contrast, patients with Ex19del more often gain C797S as an acquired resistance mutation. Using the Foundation Medicine’s FoundationInsights™ web-based platform, we present real world evidence (RWE) to define the molecular landscape of classical, non-classical, and acquired resistance mutations from a survey of >80,000 sequenced cases of NSCLC, including >12000 EGFR altered cases. We further present the profile for BDTX-1535 as a MasterKey EGFR inhibitor designed to address this evolved EGFR mutational landscape and tested against over >50 EGFR mutations. We also show how BDTX-1535 can address classical EGFR mutations in addition to on target mechanisms of resistance post osimertinib with potency against C797S as well as non-classical mutations affecting both the intracellular and extracellular domains, including L718X, E709X, S784F, V834L and A289V.

Citation Format: Etienne Dardenne, Matthew O'Connor, Monique Nilsson, Junqin He, Xiaoxing Yu, John V. Heymach, Xiuning Le, Elizabeth Buck. BDTX-1535: A MasterKey EGFR inhibitor targeting classical and non-classical oncogenic driver mutations and the C797S acquired resistance mutation to address the evolving molecular landscape of EGFR mutant NSCLC [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 1229.
Abstract 125: Development of humanized VEGFA models to assess preclinical efficacy of novel therapeutics in vivo
Authors: Zhang Shujin , Liu Chonghui , Guo Jin , Shen Zhiyuan , Jin James , Huwatibieke Bahetiyaer , Shen Yang
Published: March 2024

VEGFA is an essential growth factor required for angiogenesis in the context of normal wound healing as well as malignant tissue growth, ultimately facilitating the delivery of oxygen and nutrients to fuel cellular survival, expansion, and repair. VEGFA signaling has also been reported to exert effects on cancer cells and immune cells directly, with evidence suggesting that the pathway can both support tumor growth and inhibit immune surveillance. Thus, targeting VEGFA has been intensely explored as a therapeutic strategy for several cancer indications. Here, we generated a novel humanized VEGFA model (B-hVEGFA mice) to explore the ability of novel VEGFA-targeting therapeutics to curb cancer cell growth and angiogenesis in vivo. This was achieved by replacing the murine Vegfa gene with the corresponding human VEGFA coding region. We confirmed exclusive expression of human VEGF in lung homogenates of the humanized model at levels comparable to murine VEGF quantified in wild-type C57BL/6 mice. Immunohistochemical analysis at 8 weeks of age demonstrates no significant difference in the CD31+ area in several organs of the humanized mice when compared to wild-type C57BL/6 mice, including kidney, heart, liver, and eye. To assess the functional utility of this model in evaluating VEGFA modulators, tumor studies were conducted: murine colon cancer MC38 cells that were also engineered to express VEGFA in a similar manner (B-hVEGFA MC38 cells) were subcutaneously implanted into homozygous B-hVEGFA mice. Treatment with bevacizumab analog essentially abolished tumor growth in the humanized mice, while control tumors continued to expand over the 3 week study. To further evaluate the role of novel combination therapies or bispecific antibodies targeting VEGFA and PD-1, we also generated a triple humanized model expressing human VEGF, PD-1, and PD-L1 (B-hPD-1/hPD-L1/hVEGFA mice) by crossing B-hVEGFA mice with our B-hPD-1/hPD-L1 mice model, which expresses the extracellular domains of human PD-1 and PD-L1. Flow cytometric analysis of this model is currently underway to validate the model for further efficacy testing. Together, these humanized VEGF models provide robust in vivo platforms to evaluate novel VEGFA therapeutic candidates.

Citation Format: Shujin Zhang, Chonghui Liu, Jin Guo, Zhiyuan Shen, James Jin, Bahetiyaer Huwatibieke, Yang Shen. Development of humanized VEGFA models to assess preclinical efficacy of novel therapeutics in vivo [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 125.
Abstract 1298: Assessing the impact of Medicaid expansion on colorectal cancer preventative services utilization
Authors: Omeaku Paulette
Published: March 2024

Introduction: Colorectal cancer (CRC) is the second leading cause of cancer mortality. CRC screening rates have steadily risen and incidence rates around the nation have declined. To date, forty-one states have expanded Medicaid across the United States, with 9 states remaining that have not expanded. Although, access through insurance has increased, colorectal disparities in screening and mortality persist. Other studies have shown that screening guideline concordance can be inconsistent based on insurance type. Data suggests Medicaid enrollees are more likely to present advanced-stage cancers than those privately enrolled. The screening differences throughout the United States emphasize how complex colorectal cancer disparities are and how insurance may play a role.

Aims: Our study aims to investigate the impact of Medicaid expansion on timely CRC screenings, specifically examining whether these effects differ by African Americans, Hispanics, and White Americans.

Methods: Data was utilized from the Behavioral Risk Factor Surveillance System (BRFSS) to analyze timely CRC screening data of adults below 138% of the federal poverty level (FPL) of states with different Medicaid expansion statuses. Most recently available data was used in our analysis spanning the years 2014-2022 in all 50 states. States were stratified by dummy variables for Medicaid expansion and non-expansion status. Timely CRC screenings were determined by eligible respondent responses. Difference-in-difference analyses were used to study the effect of Medicaid expansion on timely CRC screenings in states with different Medicaid expansion statuses.

Results: Our sample included 60.52% White Americans, 12.22% African Americans, and 16.41% Hispanics in both Medicaid expanded and non-expanded states. Sex and race had significant associations to Medicaid expansion status and timely CRC screenings, particularly when analyzing race for Hispanics and White Americans. Between 2014 and 2022, timely CRC screening for low-income adults in Medicaid expansion states was at 33.15% compared to 23.17% from non-expansion status states. Notably, adults aged 45-64 demonstrated the highest differences in timely CRC screenings for Medicaid-expanded states (12.26% and 18.98%) compared to non-expanded states (9.27% and 13.96%, respectively).

Citation Format: Paulette Omeaku. Assessing the impact of Medicaid expansion on colorectal cancer preventative services utilization [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 1298.