Rama Sundari Akondy

Teaching immunology to undergraduates presents unique challenges due to the subject's complexity and abstract nature. To address this, we implemented a flexible assignment model, allowing students to design personalized assignments aligned with course objectives. This constructivist approach aimed to support engagement by promoting autonomy, creativity, and critical thinking. Assignments included diverse formats, such as posters, models, and creative works, supported by a mid-semester checkpoint for feedback and academic rigor. Anonymous surveys indicated that students found the format engaging, though some requested clearer guidelines. Generative AI tools were introduced as scaffolds, enhancing problem-solving and active learning while addressing ethical considerations. Challenges like grading subjectivity, scalability, and resource disparities were mitigated with transparent rubrics, milestones, and low-cost project designs. This model reflects an effort to introduce variety into assessment formats and sustain student interest over the course of the semester, and illustrates the potential of flexible assignments to foster deeper engagement with complex topics such as immunology.

Understanding how immunological memory lasts a lifetime requires quantifying changes in the number of memory cells as well as how their division and death rates change over time. We address these questions by using a statistically powerful mixed-effects differential equations framework to analyze data from two human studies that follow CD8 T cell responses to the yellow fever vaccine (YFV-17D). Models were first fit to the frequency of YFV-specific memory CD8 T cells and deuterium enrichment in those cells 42 days to 1 year post-vaccination. A different dataset, on the loss of YFV-specific CD8 T cells over three decades, was used to assess out of sample predictions of our models. The commonly used exponential and bi-exponential decline models performed relatively poorly. Models with the cell loss following a power law (exactly or approximately) were most predictive. Notably, using only the first year of data, these models accurately predicted T cell frequencies up to 30 years post-vaccination. Our analyses suggest that division rates of these cells drop and plateau at a low level (0.1% per day, ∼ double the estimated values for naive T cells) within one year following vaccination, whereas death rates continue to decline for much longer. Our results show that power laws can be predictive for T cell memory, a finding that may be useful for vaccine evaluation and epidemiological modeling. Moreover, since power laws asymptotically decline more slowly than any exponential decline, our results help explain the longevity of immune memory phenomenologically. Immunological memory, generated in response to infection or vaccination, may provide complete or partial protection from antigenically similar infections for the lifetime. Memory CD8 T cells are important players in protection from secondary viral infections but quantitative understanding of their dynamics in humans is limited. We analyze data from two studies where immunization with the yellow fever virus vaccine (YFV-17D) generates a mild acute infection and long-term memory. We find that: (i) the division rate of YFV-17D-specific CD8 T cells drops and stabilizes at ∼ 0.1% per day during the first year following vaccination whereas the death rate declines more gradually, and (ii) the number of these cells declines approximately in accordance with a power law (∝ time^−0.75) for at least several decades following vaccination.

Understanding how immunological memory lasts a lifetime requires quantifying changes in the number of memory cells as well as how their division and death rates change over time. We address these questions by using a statistically powerful mixed-effects differential equations framework to analyze data from two human studies that follow CD8 T cell responses to the yellow fever vaccine (YFV-17D). Models were first fit to the frequency and division rates of YFV-specific memory CD8 T cells 42 days to 1 year post-vaccination. A different dataset, on the loss of YFV-specific CD8 T cells over three decades, was used to assess out of sample predictions of our models. The commonly used exponential and bi-exponential decline models performed relatively poorly. Models with the cell loss following a power law (exactly or approximately) were most predictive. Notably, using only the first year of data, these models accurately predicted T cell frequencies up to 30 years post-vaccination. Our analyses suggest that division rates of these cells drop and plateau at a low level (0.001 per day, ~double estimates for naive T cells) within one year following vaccination, whereas death rates continue to decline for much longer. Our results show that power laws can be predictive for T cell memory, a finding that may be useful for vaccine evaluation and epidemiological modeling. Moreover, since power laws asymptotically decline more slowly than any exponential decline, our results help explain the longevity of immune memory phenomenologically. Author summary: Immunological memory, generated in response to infection or vaccination, may provide complete or partial protection from antigenically similar infections for the lifetime. Memory CD8 T cells are important players in protection from secondary viral infections but quantitative understanding of their dynamics in humans is limited. We analyze data from two studies where immunization with the yellow fever virus vaccine (YFV-17D) generates a mild acute infection and long-term memory. We find that: (i) the division rate of YFV-17D-specific CD8 T cells drops and stabilizes at ~ 0.1% per day during the first year following vaccination whereas the death rate declines more gradually, and (ii) the number of these cells declines approximately in accordance with a power law (∝time ^−0.82 ) for at least several decades following vaccination.

Does target cell depletion, innate immunity, or adaptive immunity play the dominant role in controlling primary acute viral infections? Why do some individuals have higher peak virus titers than others? Answering these questions is a basic problem in immunology and can be particularly difficult in humans due to limited data, heterogeneity in responses in different individuals, and limited ability for experimental manipulation. We address these questions for infections following vaccination with the live attenuated yellow fever virus (YFV-17D) by analyzing viral load data from 80 volunteers. Using a mixed effects modeling approach, we find that target cell depletion models do not fit the data as well as innate or adaptive immunity models. Examination of the fits of the innate and adaptive immunity models to the data allows us to select a minimal model that gives improved fits by widely used model selection criteria (AICc and BIC) and explains why it is hard to distinguish between the innate and adaptive immunity models. We then ask why some individuals have over 1000-fold higher virus titers than others and find that most of the variation arises from differences in the initial/maximum growth rate of the virus in different individuals.

Exhausted T cells in chronic infections and cancer have sustained expression of the inhibitory receptor programmed cell death 1 (PD-1). Therapies that block the PD-1 pathway have shown promising clinical results in a significant number of advanced-stage cancer patients. Nonetheless, a better understanding of the immunological responses induced by PD-1 blockade in cancer patients is lacking. Identification of predictive biomarkers is a priority in the field, but whether peripheral blood analysis can provide biomarkers to monitor or predict patients’ responses to treatment remains to be resolved. In this study, we analyzed longitudinal blood samples from advanced stage non–small cell lung cancer (NSCLC) patients (n = 29) receiving PD-1–targeted therapies. We detected an increase in Ki-67+ PD-1+ CD8 T cells following therapy in ∼70% of patients, and most responses were induced after the first or second treatment cycle. This T-cell activation was not indiscriminate because we observed only minimal effects on EBV-specific CD8 T cells, suggesting that responding cells may be tumor specific. These proliferating CD8 T cells had an effector-like phenotype (HLA-DR⁺, CD38⁺, Bcl-2^lo), expressed costimulatory molecules (CD28, CD27, ICOS), and had high levels of PD-1 and coexpression of CTLA-4. We found that 70% of patients with disease progression had either a delayed or absent PD-1+ CD8 T-cell response, whereas 80% of patients with clinical benefit exhibited PD-1+ CD8 T-cell responses within 4 wk of treatment initiation. Our results suggest that peripheral blood analysis may provide valuable insights into NSCLC patients’ responses to PD-1–targeted therapies.

Introduction The increased availability of immunotherapeutic agents for the treatment of a wide array of cancer in the general oncology practice setting will reveal rare and unique toxicities. Materials and methods The mechanism of cardiac allograft rejection in the context of PD-1 antibody therapy was explored in a patient with cutaneous squamous cell cancer complicating long-standing cardiac allograft. Immune cell infiltrate in the myocardium and peripheral blood lymphocyte repertoire were assessed using myocardial biopsy and temporal analysis of peripheral blood samples. The efficacy of high-intensity immunosuppression to reverse graft rejection was explored. Results Endomyocardial biopsy showed acute moderate diffuse cellular rejection with a predominant population of CD3+, CD8+ and CD4+ infiltrating lymphocytes; peripheral blood circulating lymphocytes showed a high frequency of proliferating and activated CD8+ T cells expressing PD-1 compared to a normal control. There was no difference in the activation and proliferation of CD4+ T cells compared to a normal control. Cardiac function improved following high-intensity immunosuppression and patient survived for up to 7 months after discontinuation of nivolumab. Conclusions Immune checkpoint inhibitors should be avoided in allograft recipients but high-intensity immunosuppression is effective to salvage allograft rejection induced by these agents.

Significantly higher levels of plasma CXCL13 [chemokine (C-X-C motif) ligand 13] were associated with the generation of broadly neutralizing antibodies (bnAbs) against HIV in a large longitudinal cohort of HIV-infected individuals. Germinal centers (GCs) perform the remarkable task of optimizing B-cell Ab responses. GCs are required for almost all B-cell receptor affinity maturation and will be a critical parameter to monitor if HIV bnAbs are to be induced by vaccination. However, lymphoid tissue is rarely available from immunized humans, making the monitoring of GC activity by direct assessment of GC B cells and germinal center CD4⁺ T follicular helper (GC Tfh) cells problematic. The CXCL13–CXCR5 [chemokine (C-X-C motif) receptor 5] chemokine axis plays a central role in organizing both B-cell follicles and GCs. Because GC Tfh cells can produce CXCL13, we explored the potential use of CXCL13 as a blood biomarker to indicate GC activity. In a series of studies, we found that plasma CXCL13 levels correlated with GC activity in draining lymph nodes of immunized mice, immunized macaques, and HIV-infected humans. Furthermore, plasma CXCL13 levels in immunized humans correlated with the magnitude of Ab responses and the frequency of ICOS⁺ (inducible T-cell costimulator) Tfh-like cells in blood. Together, these findings support the potential use of CXCL13 as a plasma biomarker of GC activity in human vaccine trials and other clinical settings.

Significance: In 2014, Ebola virus became a household term. The ongoing outbreak in West Africa is the largest Ebola virus outbreak ever recorded, with over 20,000 cases and over 8,000 deaths to date. Very little is known about the human cellular immune response to Ebola virus infection, and this lack of knowledge has hindered development of effective therapies and vaccines. In this study, we characterize the human immune response to Ebola virus infection in four patients. We define the kinetics of T- and B-cell activation, and determine which viral proteins are targets of the Ebola virus-specific T-cell response in humans.