Life Insurance Corporation

Abstract Background: Adoptive transfer of selected tumor infiltrating lymphocytes (SEL-TIL)+ pembrolizumab has yielded clinical responses of 23.5% in a phases 2 trial.1 Following expansion in IL-2, TIL cultures are selected for treatment based on in vitro reactivity assays in which TIL are co-cultured with candidate autologous tumor targets, (peptides, tandem minigenes (TMGs), and autologous tumor organoid). Detection of neoantigen reactivity currently relies on 4-1BB, OX40, and interferon-γ (IFN-γ) upregulation.2 Clinical administration of more neoantigen reactive CD4+ TIL is associated with improved responses.1 However, there may be additional reactivity markers that would allow for detection of neoantigen relevant fragments and more diverse final treatment products in both CD4+ and CD8+ T-cells. Methods: Initial screening and selection of neoantigen reactive TIL completed using standard screening via upregulation of 4-1BB, and OX40 by flowcytometry and IFN-γ by ELISpot. These samples with known reactivity were then selected for transcriptomics. scRNA sequencing was performed using 10x Genomics Chromium platform on known tumor-reactive fragments to organoid and negative controls. Conditions were tracked with barcode hashing of TCRs. CITE-Seq, and TCR-seq were also used. Clustering and analysis completed using Seurat. Results: Upregulation of TNFRSF9 (4-1BB) and IFNG (IFN-γ) were found in a single cluster. An additional larger cluster was found expressing additional genes including TNFRSF18 (GITR). This activation of GITR, and other markers was not seen in negative control conditions. In additional validation samples, GITR was successfully observed by flow cytometry equal to or greater than 4-1BB when tested as a cell surface marker of activation for CD8 T-cells against autologous organoid. Conclusions: The methodology of using scRNA transcriptomic analysis is a successful and viable method for identifying new markers of upregulation. GITR is a potential marker of CD8+ T-cell tumor reactivity, however, it requires further validation in additional samples and evaluation of antitumor effects. Citation Format: Abraham A. Hakim, Lisa Kenney, Nivedita Mohan Ratnam, Jared J. Gartner, Ian S. Goldlust, Aarushi Bhasin, Brian Bui, Nicholas D. Klemen, Steven A. Rosenberg, Frank J. Lowery. Identifying new cell surface markers of T-cell reactivity through single cell transcriptomic analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6718.

El interés central del presente escrito radica en comenzar a pensar ciertas características particulares de las sociedades actuales -cambios técnicos y tecnológicos- que se presentan ante la mirada de los actores participantes de los procesos como marcas relevantes de las crecientes transformaciones socio-económicas y políticas. En este sentido, se ponen en tensión conceptos claves para la conformación de una mirada unificada de los fenómenos tecnológicos comunicacionales a los que asistimos desde hace ya más de tres décadas. Algunas preguntas que orientarán el presente trabajo son: ¿Podemos afirmar el surgimiento de un nuevo paradigma? ¿Cuáles son sus características principales? ¿Las miradas de la ciencia ortodoxa dan crédito a estos trabajos? ¿Si son visiones compartidas por grupos de investigadores de diferentes disciplinas de las ciencias sociales puede ser que estemos asistiendo a una nueva revolución científica de la ciencia normal? Por ello, se realiza la reflexión centrada sobre el cambio hacia un nuevo paradigma tecnológico y para llevar adelante las premisas planteadas se abordan las visiones un tanto disímiles de Tomas Kuhn en su libro “La Estructura de las Revoluciones Científicas”; así como de Manuel Castells “La era de la Información, Vol 1, La sociedad Red”.

AbstractBackgroundCachexia is a wasting syndrome associated with systemic inflammation and metabolic disruption. Detection of the early signs of the disease may contribute to the effective attenuation of associated symptoms. Despite playing a central role in the control of metabolism and inflammation, the liver has received little attention in cachexia. We previously described relevant disruption of metabolic pathways in the organ in an animal model of cachexia, and herein, we adopt the same model to investigate temporal onset of inflammation in the liver. The aim was thus to study inflammation in rodent liver in the well‐characterized cachexia model of Walker 256 carcinosarcoma and, in addition, to describe inflammatory alterations in the liver of one cachectic colon cancer patient, as compared to one control and one weight‐stable cancer patient.MethodsColon cancer patients (one weight stable [WSC] and one cachectic [CC]) and one patient undergoing surgery for cholelithiasis (control, n = 1) were enrolled in the study, after obtainment of fully informed consent. Eight‐week‐old male rats were subcutaneously inoculated with a Walker 256 carcinosarcoma cell suspension (2 × 107 cells in 1.0 mL; tumour‐bearing [T]; or phosphate‐buffered saline—controls [C]). The liver was excised on Days 0 (n = 5), 7 (n = 5) and 14 (n = 5) after tumour cell injection.ResultsIn rodent cachexia, we found progressively higher numbers of CD68+ myeloid cells in the liver along cancer‐cachexia development. Similar findings are described for CC, whose liver showed infiltration of the same cell type, compared with both WSC and control patient organs. In advanced rodent cachexia, hepatic phosphorylated c‐Jun N‐terminal kinase protein content and the inflammasome pathway protein expression were increased in relation to baseline (P < 0.05). These changes were accompanied by augmented expression of the active interleukin‐1β (IL‐1β) form (P < 0.05 for both circulating and hepatic content).ConclusionsThe results show that cancer cachexia is associated with an increase in the number of myeloid cells in rodent and human liver and with modulation of hepatic inflammasome pathway. The latter contributes to the aggravation of systemic inflammation, through increased release of IL‐1β.

This paper investigated the role of information related, social and customer characteristics in public information adoption tendencies of online customers to result in herding in e-commerce. E-commerce platforms contains numerous online reviews about products which have the potential to influence customers. We applied structural equation modeling and a 2 × 2 scenario experiment to empirically verify the effect of a few factors in creating online herding. Two levels of cognitive complexity (simple, complex) and risk aversion (risk averse, risk taker) formed the 2 × 2 factorial design. The study's primary finding was that a person with simple cognitive structure and risk avoidance tendency may exhibit higher intention to adopt public information and engage in herding. Information specific attributes contributed maximum towards information adoption and herding. Among sociological variables, only reputation concern significantly predicted both information adoption and herding. Theoretically, the study offered a framework to explore herding intentions online and augmented the observations from the information adoption model. The quality of concise information from credible sources significantly instigates adoption of public information contained in online reviews. From the perspective of marketers, having a better understanding of herding behaviors and its mechanisms can enable the e-commerce platform to reduce herding’s erosion on the wisdom of the crowd by optimizing its information structures (i.e., public information, private information, etc.).

John W. Tukey (1975) defined statistical data depth as a function that determines centrality of an arbitrary point with respect to a data cloud or to a probability measure. During the last decades, this seminal idea of data depth evolved into a powerful tool proving to be useful in various fields of science. Recently, extending the notion of data depth to the functional setting attracted a lot of attention among theoretical and applied statisticians. We go further and suggest a notion of data depth suitable for data represented as curves, or trajectories, which is independent of the parametrization. We show that our curve depth satisfies theoretical requirements of general depth functions that are meaningful for trajectories. We apply our methodology to diffusion tensor brain images and also to pattern recognition of hand written digits and letters. Supplementary Materials are available online.