Journal of Immunological Methods

Marmosets (MAR, Callithrix jacchus) are nonhuman primates extensively studied in a broad array of preclinical biomedical research areas. However, the limited number of available immunological reagents remains a critical shortcoming of these models. We successfully developed monoclonal antibodies (mAbs) pairs that can be used in immunoassays for the identification and quantification of the biomarkers of inflammation C-reactive protein (CRP), CXCL-10 (IP-10), interleukin (IL)-4, IL-6, and IL-10. Recombinant MAR protein variants were produced in mammalian cells, purified and used for mice immunization. Hybridoma clones were selected first for their capacity to bind the recombinant proteins. All possible pair combinations of these mAbs were then tested for their capacity to identify their targets in MAR-derived samples. These MAR samples consisted of supernatant of PBMCs exposed ex vivo to different stimulants, and plasma samples from animals stimulated in vivo with a low-dose intravenous LPS inoculation. The majority of the mAbs that recognized the recombinant proteins failed to bind to the MAR-derived homologs. However, we found MAR-derived reactive mAbs and selected pairs with optimal sensitivity and signal-to-noise ratio for immunoassays that included Luminex multiplexing assays, ELISA, and ELISpot assays. These immunoreagents and assays will improve the translational value of different MAR biomedical models.

Phage Display Immunoprecipitation sequencing (PhIP-Seq) is a high throughput method allowing to measure antibody binding against hundreds of thousands of potential antigens. Typically, blood samples of hundreds to thousands of individuals are measured in 96-well plates, necessitating distribution of samples on multiple plates and processing in batches. To correctly interpret PhIP-Seq results, it is crucial to understand its nature and technical limitations. Here, we analyzed 195 technical replicates of controls (anchor samples) from 49 plates measured in 13 immunoprecipitation runs to gauge technical variability and replicability. While there were few false-positive enriched peptides, we observed a substantial fraction of false negatives. The total number of enriched peptides can be affected by batch effects. Additionally, the type of biological material used (serum or plasma) influences enrichment profiles with an antigen library containing bacterial proteins due to the interaction of phages with plasma proteins. Finally, replicating measurements in different labs produces comparable enrichment profiles, but slight differences in a subset of peptides are noticeable. These results suggest best practices for PhIP-Seq experiments. Most importantly, due to batch effects, samples of cases and controls should be evenly distributed between 96-well plates to avoid confounding with biological effects. Also, for highly complex libraries, the total number of enriched peptides can be a technical artifact and potentially not a feature useful in comparisons.

Background: Noninvasive biomarkers capable of detecting kidney allograft injury and distinguishing rejection from infection remain an important clinical need. Torque teno virus (TTV) reflects host immune status, but its utility in urine has not been well established. We evaluated urinary TTV, total cell-free DNA (cfDNA), cfDNA fragmentation, and BK polyomavirus (BKV) as potential biomarkers of kidney transplant rejection and BK polyomavirus-associated nephropathy (BKPyVAN). Methods: Urine samples from 334 kidney transplant recipients were analyzed in association with kidney biopsies performed within 30 days of sample collection. TTV and cfDNA were measured by multiplex quantitative PCR (qPCR), with a subset analyzed by digital PCR (dPCR), and BKV was quantified by qPCR. Associations with biopsy results were evaluated using group comparisons and nominal logistic regression. Changes associated with outcomes of consecutive biopsies were assessed by matched pairs analysis. Results: Among 544 unique urine samples, the urinary TTV/cfDNA ratio was significantly lower in rejection than in non-rejection samples (P<0.0001). Logistic regression adjusted for demographic factors confirmed an inverse association between the qPCR-derived TTV/cfDNA metric and rejection (adjusted odds ratio per delta Cq, 0.91; 95% CI, 0.88-0.94; P<0.00001). Significant differences were observed for all types of rejection. Association was confirmed by dPCR: higher TTV was associated with lower rejection odds, whereas higher cfDNA was associated with greater rejection odds. A nominal logistic model incorporating dPCR measurements achieved an AUROC of 0.76 (95% CI, 0.69-0.82). Matched pairs analysis showed a significant decrease in TTV/cfDNA when rejection developed and an increase following recovery from rejection, with no significant changes when biopsy status remained unchanged. BKV levels were strongly associated with BKPyVAN. No correlation between TTV and BKV was observed. Nominal logistic regression integrating TTV, cfDNA, and BKV measurements yielded AUROCs of 0.75, 0.97, and 0.73 for rejection, BKPyVAN, and non-rejection, respectively. Conclusions: A reduced urinary TTV/cfDNA ratio is associated with biopsy-defined kidney transplant rejection, and changes in the ratio correlate with transitions in biopsy results. Combined TTV, cfDNA, and BKV measurements showed differential associations with rejection and BKPyVAN, supporting further evaluation as complementary urinary biomarkers.

Surface plasmon resonance (SPR) and biolayer interferometry (BLI) are well-established label-free analytical technologies used to determine biomolecular interaction rates (ka, kd) and equilibrium constants (KD). While assays historically rely on multi-cycle kinetics (MCK), this approach requires intermediate surface regeneration, risking sensor degradation and increasing reagent consumption. Single-cycle kinetics (SCK) avoids regeneration by sequentially injecting increasing analyte concentrations. However, implementing SCK workflows on biosensor platforms like the OctetRR8 BLI instrument (Sartorius) remains a challenge due to the lack of built-in or online data analysis tools. To address this, we introduce SCKAnalyzer, a free, user-friendly web application designed for processing and fitting SCK datasets. SCKAnalyzer accepts column-based text files and native raw BLI data (.frd format) from Sartorius instruments, performing data pre-processing and non-linear fitting to a 1:1 interaction model. Additionally, it offers advanced simulation capabilities that allow variable association and dissociation durations across sequential injection steps, a feature absent in existing platforms such as BiacoreTMSimul8. The performance of SCKAnalyzer was experimentally validated using a 3-step SCK method (SCK3) for DNA/RNA duplex formation on a Biacore T200, as well as 4-step (SCK4) and 5-step (SCK5) methods for DNA/DNA duplex formation on an OctetRR8 BLI instrument. Binding parameters (ka, kd, KD) derived from SCKAnalyzer showed excellent agreement with values from established proprietary softwares such as Biacore T200 Evaluation Software v3.2.1 and BIAevaluation v4.1.1. SCKAnalyzer provides a practical alternative to MCK, reducing probe consumption and extending SCK utility across biosensor platforms. SCKAnalyzer is available at sck.iecb.u-bordeaux.fr (source code: github.com/synthaze/sckanalyzer).

Glycosylphosphatidylinositol (GPI) anchors are involved in the organization of membrane microdomains that support T cell receptor (TCR) signaling. However, their role in regulating expression of TCR-related proteins and downstream functional output remains unclear. This study aimed to characterize the effects of GPI-deficiency on TCR, cluster of differentiation 3 (CD3), and CD28 expression as well as interleukin-2 (IL-2) production using a GPI-deficient Jurkat T cell line (S12). Flow cytometry confirmed the complete loss of GPI anchors and GPI-anchored proteins (GPI-APs) in the S12 cell line. Compared to GPI-producing parental Jurkat, S12 had significantly higher expression of CD3 and TCR{beta} while CD28 had similar expression. IL-2 production by S12 was assessed following stimulation with anti-CD3/anti-CD28 beads and following stimulation with phorbol 12-myristate 13-acetate (PMA) and ionomycin. Neither S12 nor parental Jurkat produced detectable IL-2 in response to anti-CD3/anti-CD28 bead-mediated stimulation. Both parental Jurkat and S12 produced IL-2 following PMA/ionomycin-mediated stimulation. No significant difference in IL-2 production was observed between S12 and parental Jurkat following PMA/ionomycin-mediated stimulation. These findings demonstrate that GPI-deficiency influences surface receptor expression but does not significantly impair downstream IL-2 production under PMA/ionomycin stimulation. This finding suggests that GPI anchors and GPI-APs contribute to proximal signaling organization but are not required for cytokine production when downstream pathways are directly activated.

The human T cell repertoire is generated through recombination of a multitude of T cell receptor gene segments, yielding a complex array of T cell clones. T cell receptor beta (TRB) V gene segment defined, T cell clonal frequency when organized in correspondence with the respective V gene segment positions on the TRB genomic locus yields a periodic, undulating curve in the spatial domain. Using the genomic distance from the TRB-D1 segment to the TRB-V1-29 segments, spectral analysis was performed utilizing Lomb-Scargle periodogram (modified Fourier analysis) to obtain spectral power curves quantifying the TRB V clonal frequencies from 12 allogeneic stem cell transplant donors (baseline) and recipients (<100 days or b/w 100-365) using a variety of analytic software. Patients either underwent HLA matched related bone marrow or HLA matched unrelated blood stem cell transplantation, using PT-CY for the former and ATG for the latter. Spectral Power curves revealed dominant spectral peaks at wavelengths ranging from 113-335 millicycles/kb in the 12 donors, with consistent frequency domain spectral patterns, supporting similar use of V segments across healthy individuals. PT-CY recipients had power spectra closely corresponding to the respective donors, however the ATG recipients had relatively dispersed spectra, with spectral centroid shifted towards higher frequencies compared to donors and a reciprocal decline in the low frequency indices. Spectral power was concentrated in the <3 kb and 3-12 kb wavelengths in both groups, consistent with the periodicity observed in the relative V gene segment usage across the repertoire. The analyses reported here demonstrate that the healthy SCT donors have a spectral signature occupying short to intermediate wavelegnths in the frequency domain, PT CY recipients recover with donor-like spectra on the average, however ATG recipients tend to shift towards higher frequencies. These findings are consistent with a normal organized distribution of TRB V segment usage in healthy individuals, with PT-CY preserving this organization more consistently than ATG. Spectral (Fourier) analysis of TRB sequencing data provides a repertoire wide summary of T cell clonal distribution.

Schistosoma mansoni is a vector-borne intestinal parasite, endemic in [~]70 tropical countries. Most of the World Health Organization interventions are based on mass drug administration (MDA) and sanitation. Since the parasite does not induce permanent immunity, reinfection rate is high, inducing scheduling of several MDA campaigns. To follow up after treatment and avoid blind MDA, providing a new rapid and cheap diagnostic test is needed, since the most used method is fifty years-old, lacks sensitivity and efficiency. Venom Allergen-Like proteins (SmVALs) have been previously identified as secreted/excreted proteins and potential biomarkers. Here we present the biophysical characterization of SmVAL11 and SmVAL13, their recognition by both specific antibodies and molecularly imprinted polymers (nanoMIPs), an easy-to-standardize alternative. The specific antibodies showed no cross-reactivity, while initial characterization of the nanoMIPs indicates a promising level of selectivity, establishing them as a reliable, cost-effective alternative. Therefore, our results are promising for the future development of a new cheap diagnostic test of intestinal schistosomiasis.

BackgroundTraditional immunohistochemistry (IHC) with chromogen detection has limited multiplex capacity, detecting at most 4 protein markers per tissue section simultaneously, thereby restricting comprehensive spatial analysis of valuable human biopsies. We developed and validated a robust serial IHC (sIHC) staining method to detect multiple antigens on a single kidney biopsy slide, maximizing data yield for diagnosing and studying complex kidney diseases. MethodsFormalin-fixed, paraffin-embedded kidney biopsy sections were subjected to repeated IHC/imaging cycles with antibody removal using an optimized sodium dodecyl sulfate-glycerol buffer stripping protocol. Images were then co-registered, and analysis was performed using a variety of methodologies, including color deconvolution, cell segmentation, and spatial clustering. ResultsThis optimized sIHC method successfully detected up to 20 antigens on a single slide. Combining image analysis and artificial intelligence software, for example with HALO (Indica Labs), the assay assembles high-dimensional images and enables quantitative histology and single-cell spatial analysis. Using this advanced method, we were able to identify rare cell populations, such as double-negative T cells, that are challenging to detect conventionally. ConclusionWe have developed a validated, high-capacity sIHC protocol that uses standard IHC procedures with commercially available, clinically validated off-the-shelf antibodies. This method is a valuable, cost-effective tool for obtaining extensive, high-dimensional single-cell-resolved spatial data from limited pathology samples, such as a human kidney biopsy.

Background: Acute kidney injury (AKI) is a common complication after liver transplantation (LT). Alactic base excess (ABE) reflects the metabolic component of acid base disturbances not attributable to lactate and has been associated with kidney dysfunction in other clinical settings. We evaluated the association between intraoperative ABE and postoperative AKI after LT. Methods: We conducted a retrospective cohort study of adult patients undergoing LT. ABE was calculated from standard base excess and lactate obtained from the last intraoperative arterial blood gas analysis. The primary outcome was creatinine based AKI occurring within the first 7 postoperative days according to Kidney Disease: Improving Global Outcomes criteria. The association between ABE and AKI was estimated using modified Poisson regression with robust variance, adjusted for age, sex, body mass index, MELD score, cold ischemia time, and anhepatic phase duration. A post hoc exploratory analysis evaluated severe AKI, defined as KDIGO stages 2,3. Results: Seventy patients were included, of whom 32 (45.7%) developed AKI. ABE values were lower among patients who developed AKI than among those who did not (median, -1.15 vs 0.75 mmol/L; Hodges Lehmann location shift, -1.60 mmol/L; 95%CI, -2.80 to -0.20). After multivariable adjustment, ABE was not independently associated with AKI (aRR, 0.91; 95%CI, 0.82-1.01; p=0.07). Severe AKI occurred in 14 patients (20.0%), and ABE was not independently associated with severe AKI (aRR, 0.98; 95%CI, 0.78-1.23; p=0.87). Sensitivity analyses yielded consistent findings. Conclusions: A single intraoperative ABE measurement was not independently associated with postoperative AKI or severe AKI after LT. Serial measurements across different phases of transplantation may better characterize the potential relationship between ABE dynamics and postoperative kidney injury.

Background: Point-of-care manufacturing of CAR-T cells could reduce cost and improve patient access, but few closed, automated systems support both flexible process development and GMP production. Methods and results: We describe LimCORE, a single-use consumable for cell incubation and processing, implemented in LimGROW (manual system) and LimONE (closed and automated system). In LimGROW, T cells expanded 246 +/-18 fold over 10 days at optimized seeding density, versus 89 +/-9 fold in a G-Rex control, with similar viability (>90%) and phenotype. Process parameters directly transferred to LimONE, where automated, closed buoyancy-based CD3+ selection achieved 90.3 +/-3.5% purity and 59.2 +/-17.0% recovery in under two hours. Using this workflow, we manufactured CD19 CAR-T cells in a fully closed, automated 7-day LimONE process requiring 155 minutes of operator intervention. LimONE manufactured CAR-T cells reached 42.6 +/-2.4 fold expansion (532 +/-29x10e6; cells at harvest), with 43.6 +/-6.0% transduction efficiency and viability similar to G-Rex controls. CD4+/CD8+ ratios, CD8+ differentiation subsets, and cytotoxicity were comparable between platforms, while LimONE-manufactured cells showed increased spare respiratory capacity and oxygen consumption. Across four manufacturing runs on the LimONE, no hardware or software failures occurred, and automated liquid transfers and volume concentration stayed within +/-5% accuracy. Conclusions: These data show that LimCORE supports T cell expansion, selection, and complete CD19 CAR-T manufacturing with performance similar to existing platforms while reducing operator time, across R&D and GMP scale closed-system formats.

Kidney transplant recipients experience a higher burden of several malignancies, yet the factors associated with prostate cancer presentation after transplantation remain poorly understood. Unlike malignancies strongly associated with impaired immune surveillance, prostate cancer has not consistently demonstrated an increased incidence after transplantation, suggesting that different mechanisms may underlie disease presentation. This study evaluated recipient, donor, transplant, immunologic, and immunosuppressive factors associated with prostate cancer phenotype after kidney transplantation. A retrospective cohort study was conducted using national transplant registry data from adult kidney transplant recipients diagnosed with post-transplant prostate cancer between 2015 and 2024. Cases were classified as de novo (no pre-transplant history of prostate cancer) or recurrent (documented pre-transplant history). Multivariable Firth penalized logistic regression was used to evaluate factors associated with recurrent phenotype. Prespecified sensitivity analyses included deceased donor restricted models, incorporation of donor organ quality variables, and adjustment for time from transplantation to cancer diagnosis. Exploratory machine learning analyses included elastic net logistic regression, random forest, and extreme gradient boosting. The cohort included 660 recipients, of whom 623 (94.4%) had de novo disease and 37 (5.6%) had recurrent disease. Recipient age was the only variable consistently associated with recurrent phenotype across primary and sensitivity analyses (adjusted odds ratio per year 1.11, 95% CI 1.05-1.17; p<0.001). Immunosuppressive regimen, donor characteristics, immunologic variables, and time from transplantation to cancer diagnosis were not independently associated with phenotype in the primary cohort. In deceased donor restricted analyses, alemtuzumab induction showed an exploratory association with recurrent phenotype, although estimates were imprecise. Machine learning models demonstrated modest discrimination and calibration and did not outperform penalized regression approaches. These findings suggest that, among kidney transplant recipients with prostate cancer, differences between recurrent and de novo presentation are more closely associated with recipient age and underlying disease characteristics than with transplant exposures or specific immunosuppressive regimens.

Background: Histopathological diagnoses in kidney transplant biopsies, as described by the Banff classification, suffer from substantial inter-observer variability and misinterpretation, making them prone to diagnostic errors. Continuous indices based on BanffNET automated lesion scores are proposed to quantify the continuous phenotypic spectrum of kidney transplant biopsies, complementary to pathologist assessment of biopsies. Methods: The BanffNET model was used to obtain continuous lesion scoring for a training cohort of 2544 biopsies, a large validation cohort of 3863 biopsies, and a multi-reader cohort of 36 biopsies scored by 67 pathologists. A penalized regression approach was used to condense 17 automated lesion scores into four indices, representing the most important dimensions of graft injury: a TCMR/TI Index, an AMR/MVI Index, an Activity Index and a Chronicity Index. The BanffNET Indices were evaluated against Banff diagnoses and histological indices in the training cohort and validation cohort. Since pathologist-assigned Banff lesions and diagnoses suffer from inter-observer variability, associations were also assessed with diagnoses in a multi-reader study, with time to kidney graft failure in the training and validation cohort and with biopsy-based molecular signatures in the validation cohort. Results: The BanffNET TCMR/TI Index, AMR/MVI Index and Activity Index showed excellent discrimination of Banff TCMR, Banff MVI and Banff Any Diagnosis respectively, with validation AUCs ranging from 0.80 to 0.92. In addition, the BanffNET Indices explained large amounts of variability in multi-observer reference standards, time to graft failure and molecular biopsy-based diagnostics. In the large majority of cases, variability explained by BanffNET Indices matched or exceeded the variability explained by pathologist-assigned diagnoses and histological indices. Conclusions: BanffNET Indices are reproducible descriptors of whole slide images that could complement and augment kidney transplant biopsy evaluation by pathologists. Associations of BanffNET Indices with multi-observer diagnoses and related outcomes suggest that they capture additional information on tissue injury type and severity on top of pathologist-assigned Banff diagnoses and histological indices.

Introduction Timely diagnosis of kidney allograft rejection is critical for post-transplant management, yet treatment decisions may need to be made empirically while awaiting the final pathology report. We previously demonstrated that biopsy transport medium (BTM) contains molecular signals reflective of allograft rejection. Building on these findings, we developed a rapid BTM qPCR workflow using a targeted gene panel for early molecular assessment of rejection. Methods Kidney transplant biopsies assessed at Leiden University Medical Center from April 2023 to November 2024 were eligible. A predefined gene panel was quantified in BTM by qPCR, while matched formalin-fixed paraffin-embedded tissues were profiled using Tempo-Seq. Elastic Net, Random Forest, and support vector machine models were developed to classify rejection and predict continuous histological indices directly from the BTM. Results A total of 134 paired BTM samples and biopsy tissues were analyzed. The best-performing BTM gene-panel models demonstrated good discrimination for rejection, with a median AUC of 0.80, and good calibration (median slope, 0.92; median intercept, 0.08). For continuous histological indices, the best-performing BTM gene-panel models achieved R square values of 0.33 for Activity, 0.31 for TCMR/TI, and 0.27 for AMR/MVI. Corresponding biopsy gene-panel models showed similar patterns across diagnostic outcomes. Conclusions The BTM qPCR workflow captures molecular features of kidney allograft rejection and enables prediction of rejection status along the spectrum of continuous activity indices. By providing same-day molecular information while definitive biopsy interpretation is pending, this rapid approach has the potential to complement conventional histopathological diagnostics and support early clinical decision-making.

This 28-color panel was developed to identify classical and non-classical T lymphocytes in decidual leukocytes and peripheral blood mononuclear cells (PBMC) of pregnant rhesus macaques. By profiling these T lymphocytes, we can investigate how maternal immunity balances tolerance to fetal antigens with protection against vertically transmitted pathogens. The selected markers define memory populations and characterize tissue residency, activation, proliferation, cytotoxicity, trafficking, and exhaustion status. This panel also delineates B lymphocytes and NK cells to confirm expected frequencies. The utility of this panel is aimed at evaluating cellular immune correlates of protection against congenital infections at the maternal-fetal interface and PBMC in rhesus macaques.

Preformed and de novo antibodies against donor human leukocyte antigen (HLA) antigens remain a major cause of antibody-mediated rejection and graft loss after organ transplantation. Although solid-phase assays and virtual crossmatching have reshaped pre-transplant risk assessment, physical crossmatching, which assesses whether recipient antibodies react with donor cells, remains widely used as the final compatibility assessment before transplantation. These workflows include both complement-dependent cytotoxicity (CDC) and flow cytometry crossmatch (FCXM) assays, but their interpretation remains partly manual, operator-dependent, and, for microscopic CDC readout, semi-quantitative. Here, we present AlloViewer, a web-based software platform for automated and traceable interpretation of image-based and flow-cytometry-based HLA antibody diagnostics. For CDC microscopy, AlloViewer employs a simulation-trained deep learning (UNet) workflow that combines automated lymphocyte segmentation with experiment-specific fluorescence classification and well-level cytotoxicity scoring. To deliberately capture the technical variability encountered in routine diagnostics, we generated simulated CDC-like training images spanning differences in image resolution, acquisition conditions, staining quality, cell density, cell distribution, clustering, and background fluorescence, among others. The resulting simulation-trained model enabled robust lymphocyte detection across heterogeneous imaging conditions and outperformed a conventional rule-based image analysis pipeline under variable acquisition conditions. Automated CDC scoring achieved performance within the range of human inter-annotator variability and approached the practical reproducibility limit defined by human disagreement. To cover all modalities of pre-transplant physical crossmatching, AlloViewer further supports automated FCXM interpretation through cell population identification and population-specific immunoglobulin G (IgG) readouts. The platform integrates these workflows in an assay-specific web interface and provides application programming interface (API) access for programmatic submission of assay data and retrieval of processed results. Together, AlloViewer establishes an integrated computational framework for standardized and traceable interpretation of CDC crossmatch assays, CDC-based HLA antibody identification testing using commercial test-cell panels, and FCXM workflows. More broadly, this work demonstrates how simulation-trained artificial intelligence (AI) can facilitate robust computational analysis across technically heterogeneous laboratory environments, providing a framework for standardizing traditionally operator-dependent diagnostic workflows.

Uniform, reproducible blood smears are critical for reliable hematological evaluation. Manual smear preparation, however, is user-dependent and introduces variability that limits quantitative microscopy. Here we developed BUsmear, a low-cost, 3D-printed, motorized blood smear device that prepares two smears simultaneously from a printed stage and a micro-motor drive with tunable linear velocity, controlled through a joystick-operated driver module. By spreading two slides in parallel with fully repeatable slide-to-slide motion, the device doubles throughput while eliminating operator-dependent motion artifacts, and can be fabricated on any benchtop 3D printer in under one day. To validate smear quality, we analyzed blood films from three donors together with a manual smear prepared by an expert from the blood of one of the same donors, giving a matched device-versus-manual pair. Automated Cellpose segmentation of 14,046 red blood cells across 12 bright-field fields showed that cell diameter was preserved and closely matched the expert smear (6.7-7.8 um across groups, within the 6.2-8.2 um human reference range; 6.7 vs 6.9 um in the matched pair), and that all films formed non-aggregated monolayers (Clark-Evans index of aggregation 1.04-1.24). Critically, red blood cells in the device films were markedly more circular than in the expert manual smear (mean eccentricity 0.405 vs 0.502; 0.443 vs 0.502 in the matched pair), with complete separation between the two methods at the level of whole fields of view. Because eccentricity reports smear-induced cell distortion, this indicates that a constant, mechanically controlled spreading velocity preserves red blood cell morphology better than skilled manual technique. BUsmear offers an accessible route to standardized smear geometry for quantitative analysis, including AI-based morphometry, and its low cost may be particularly advantageous in low-income countries with a high prevalence of malaria.

CD8 T cells play a central role in immune responses to infection and cancer. However, the diversity of T cell receptor (TCR) specificities makes it challenging to study the mechanisms that regulate T cell activation, differentiation, and effector function. Beyond TCR transgenic mouse models, various complex genome-editing approaches have been employed to overcome this challenge. However, these strategies are often technically demanding, time-intensive, and difficult to adapt. Investigators who are interested in testing de novo TCRs under their chosen experimental conditions would benefit from a standardized and accessible method. Here, we describe a protocol that combines ribonucleoprotein (RNP)-based CRISPR-Cas9 editing with retroviral transduction to enable efficient genetic manipulation of murine CD8 T cells. We show that T cells engineered via this protocol can be generated at sufficient scale for downstream in vitro assays and in vivo adoptive transfer experiments. We expect this method will be useful for investigators who require a standardized and accessible way to study how TCR specificity impacts CD8 T cell responses.

Exposure to copper, one of the prevalent contaminants in aquatic environments, has wide-ranging adverse immunological effects. However, it is unclear if copper induced immune changes are due to alterations in lymphoid tissues or the result of direct immune cell toxicity. Therefore, to understand the mechanistic action of copper immunomodulation, we utilized an emerging immunotoxicologic model, threespine stickleback fish (Gasterosteus aculeatus). We exposed stickleback fish to dietary copper for a period of 14 days and examined its effect on the spleen, including histopathologic changes in splenic architecture and resident melanomacrophage centers (MMC) populations. We found that dietary copper exposure decreases splenic MMC coverage, suggesting copper is suppressing this phagocyte population. We found no histopathological differences between control and copper groups. Quantification of splenic compartments demonstrated that there is no significant difference in red or white pulp between the control and copper groups, suggesting that reduced MMC coverage is not due to the expansion of other splenic regions. Overall, results from this study suggest that copper toxicity leads to melanomacrophage suppression without damaging or altering the splenic secondary immune tissue structure. Future studies should examine the effect of copper on melanomacrophage viability, development, and function to better understand the mechanism behind MMC reduction. Impact statementThis study demonstrates that dietary copper reduces splenic MMCs but does not cause histopathological damage or alter other compartments of spleen, including the red and white pulp, suggesting that copper-induced immune modulation is the result of direct melanomacrophage toxicity and not due to secondary immune tissue damage. MMC assays could be a useful tool for monitoring heavy metal and other contaminant exposures in aquatic organisms.

The primary question in this work is whether a turbidity trace contains more than one resolved kinetic event before any rate or aggregate-mass information is supplied. A blind, three-gate hierarchical Gompertz procedure applied to human interleukin-1 receptor antagonist (IL-1ra) at 53 {degrees}C in phosphate retained one phase at 1 and 2 mg/mL, but selected two phases at 5 and 10 mg/mL. Thus the first resolved multiphase behavior appears at the low protein concentration of 5 mg/mL. Source optical-rate markers were withheld until after selection. Those observed optical rates were then compared with blind-fit phase rates, and the same comparison was expressed on a conditional mass-equivalent scale using the published 5.3-fold Type-I/Type-II turbidity response ratio. A separate 50 {degrees}C citrate series (4, 6, 8, 10, and 14 mg/mL) also selected two phases in every retained trace; its printed Vmax values were used only as post-selection comparators. Finally, two challenging 40 {degrees}C high-concentration traces (180 and 200 mg/mL) were digitized from the instrument-output plot and each retained two phases. All three conditions are analyzed independently. Blind recognition is therefore the central result; the mass-equivalent conversion is a secondary, post-selection interpretation of optical phase rates. The absolute {micro}M/min scale remains conditional on an endpoint aggregate fraction measured elsewhere.

Platelet-leukocyte aggregates (PLAs) are a proposed interface between coagulation and immune regulation, but their distribution across leukocyte subsets beyond monocytes and neutrophils, and their behavior in acute disorders of immune regulation, such as sepsis and severe trauma, remain largely undefined. The study of thromboimmune mechanisms in these acute conditions has relied heavily on murine sepsis models, whose species differences in platelet and leukocyte biology limit translation to human disease. Direct measurement in human whole blood is needed yet reported PLA frequencies vary widely because quantification is highly sensitive to sample handling. Here we present a robust, minimally manipulative 27-color spectral flow cytometry protocol that allows simultaneous deep immunophenotyping and classification of PLAs across >40 leukocyte subpopulations. In healthy donors, PLA frequency ranged from 1.7% on memory CD4 T cells to over 50% on monocyte subsets, with monocytes contributing 25% of all PLAs. We also found novel platelet-binding leukocyte populations, including Th9 and Th22 CD4+ T cells. Optimization identified anticoagulant choice, centrifugation conditions, dilution, and sample processing time as key determinants of reproducible measurement; PLA quantification was validated by imaging flow cytometry. In a small validation cohort of sepsis and trauma patients, the assay recapitulated established immunophenotypic features of critical illness, including neutrophilia and myeloid-derived suppressor cells (MDSC) expansion, and quantified PLAs within each subset. This protocol provides a reference framework for studying thromboinflammation and other dysregulated immune response diseases directly in human blood, and a foundation for further studies, defining the mechanisms and clinical relevance of platelet-leukocyte interactions in disease.