American Journal of Transplantation

Unplanned readmissions after liver transplantation occur in over 30% of recipients, yet no validated prediction models exist, and prior observational studies suffer from immortal time bias. The optimal readmission window for outcome prediction and the feasibility of early risk stratification remain undefined. This study is a retrospective analysis of 922 adult liver transplant recipients (August 2018-August 2025) at a single center. Time-varying Cox regression evaluated 14-, 30-, and 90-day readmission windows as predictors of 1-year mortality, correcting for immortal time bias. Gradient-boosted machine learning models leveraging 528,400 laboratory measurements (28 analytes) predicted 90-day readmission using either complete hospitalization data or data restricted to postoperative day 7. Feature importance was quantified by gain, and clinical utility was assessed through risk stratification. Among 902 hospital survivors, 342 (37.9%) experienced an unplanned readmission within 90 days of initial discharge. Only the 90-day readmission window predicted 1-year mortality in time-varying analysis (HR 1.73, 95% CI 1.17-2.57, p=0.006). The model for readmission using complete data achieved AUC 0.614 (95% CI 0.576-0.652); the postoperative day 7 restricted model achieved AUC 0.615 (95% CI 0.577-0.652), with no meaningful performance difference. The tacrolimus coefficient of variation x peak creatinine interaction was the dominant predictor in both the complete model (17.3% importance, rank 1) and the day 7 restricted model (20.4% importance, rank 2). This interaction stratified patients into high-risk (tacrolimus CV >0.3 and creatinine >2.0 mg/dL; 49.8% readmission) versus low-risk (24.8% readmission) groups (risk ratio 2.01, p<0.001). These results identify a modifiable biological determinant of readmission and establish a framework for targeted interventions to reduce unplanned readmission and improve post-transplant outcomes.

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.

Rodent models of kidney disease have been widely used to assess the efficacy, safety and mode of action of mesenchymal stromal cells (MSCs) as therapies. However, because kidney disease models, MSC type and the methods used to assess kidney injury tend to differ between research groups, it is difficult to obtain data that are sufficiently robust and reproducible to support clinical translation. We present here for the first time a side-by-side analysis of the performance of human MSCs derived from the most commonly used tissue sources, bone marrow (BM-), adipose- (A-) and umbilical cord (UC-), in a kidney ischaemia reperfusion injury (IRI) model in mice. For each animal, we performed a comprehensive assessment of kidney function and health by longitudinal transdermal measurements of sinistrin clearance, serum biomarker levels at the experimental endpoint, and histopathological scoring of sections from left and right kidneys. Furthermore, we tracked the MSCs by bioluminescence imaging in the injured mice to determine their viability over time and their capacity for homing to the damaged kidneys. Our results reveal that only modest if any beneficial effects of the MSC treatments were detectable on kidney function and histology, irrespective of cell type administered. Furthermore, all three MSC types were sequestered in the lungs without reaching the kidneys, and had completely disappeared within 7 days. Our data suggest that none of the MSC types has the capability to improve renal health following IRI to a meaningful extent, questioning their suitability as a clinical therapy. Significance StatementMSCs have been proposed as efficacious cell therapies in murine models of kidney disease, with potential for clinical translation. We compare efficacy of human MSCs of different tissue origins (adipose, bone marrow and umbilical cord) in a refined mouse model of renal IRI. Only modest if any beneficial effects on kidney function and histology were detectable for all three cell types, and cells did not reach the kidneys but sequestered in the lungs where they died.

BACKGROUND: Machine learning (ML) models have been used to evaluate one-year post-transplant mortality in donor-recipient pairs. Previous modeling utilizing noninterpretable ML methods (deep neural networks [DNN] and XGBoost) showed modest gains in area under the receiver operating curve (AUC) beyond logistic regression, but suffered a significant drop in predictive AUC applied to the subsequent years' data and lacked statistical significance in validating previously identified risk factors. METHODS: Using balanced SRTR datasets, we evaluated non-interpretable models against interpretable ML models (adaptive logistic regression with interaction terms [aLR], Classification and Regression tree [CART], and conditional inference tree [CIT]) for one-year mortality, including comprehensive clinician-supervised data curation and inclusion of variables describing pre- and post-2018 listing status changes. Models were trained/tested using rolling-window validation across years and further analyzed with repeated ten-fold crossvalidation. Interaction terms were obtained via Adaptive Best-Subset Selection (ABESS). RESULTS: Predictive validation before the listing policy change in 2018 showed similar AUCs between DNN (0.579), aLR (0.642), CART (0.579), and CIT (0.584), with XGBoost having a higher (0.763) AUC. However, in the post-2018 predictive analysis, aLR outperformed XGBoost (AUC 0.613 vs. 0.586). The interpretable ML models confirm the significance of previously reported risk factors (recipient bilirubin and creatinine) and identify risk factors not previously reported (donor pH, potential recipient distance, and recipient transfusion), as well as clinically relevant interaction terms. CONCLUSIONS: Carefully developed interpretable ML models of one-year transplant mortality have similar predictive performance to black-box models, while identifying novel risk factors, and showing improved performance after recent listing policy changes. With appropriate validation and additional data, interpretable ML modeling may allow real-time data-driven donor selection.

Background Donation after circulatory death (DCD) is an increasingly accepted strategy to expand the adult heart donor pool, but its use in children remains limited and incompletely characterized. We compared national characteristics and post-transplant outcomes of pediatric DCD versus donation after brain death (DBD) heart transplantation. Methods We performed a retrospective cohort study of the Organ Procurement and Transplantation Network (OPTN) registry, including patients younger than 18 years who underwent primary isolated heart transplantation between January 1993 and March 2025. Recipients were stratified by donor type (DCD vs DBD). Continuous variables were compared with the Mann Whitney U test and categorical variables with the Fisher exact test. Survival was estimated by the Kaplan Meier method and compared using the log-rank test and Cox proportional hazards regression. Results Of 10,671 pediatric heart transplant recipients, 33 (approximately 0.3%) received DCD allografts. The first DCD transplant was recorded in 2004, with a marked increase in 2023 to 2024. Compared with DBD recipients, DCD recipients were more frequently infants (<1 year, 51.5% vs 28.4%) and more often had congenital heart disease (69.7% vs 47.6%; P=0.033); DCD donors were younger (median 0 vs 6 years; P=0.038) and more frequently died of anoxia (72.7% vs 37.0%; P<0.001). Donor and recipient left ventricular mass were lower in the DCD group (P<0.05), but predicted left ventricular mass matching was similar. DCD recipients had longer hospital stays (median 31.5 vs 19 days; P=0.023); rates of treated rejection, dialysis, stroke, and pacemaker implantation were comparable. Early survival did not differ (30-day, 90-day, and 1-year), and Kaplan Meier survival through 5 years was not significantly different (hazard ratio 1.17; 95% CI 0.49 to 2.81; log-rank P=0.73). More than 90% of DCD transplants were performed in four UNOS regions (11, 4, 5, and 8). Conclusions In this national analysis, pediatric DCD heart transplantation was uncommon but expanding rapidly, concentrated in a few regions, and used preferentially in infants and children with congenital heart disease. Early post-transplant outcomes were not significantly different from DBD, supporting cautious expansion of DCD as a means of enlarging the pediatric donor pool. The small number of DCD recipients and limited followup warrant confirmation in larger, longer-term studies. Keywords: pediatric heart transplantation; donation after circulatory death; donor pool; congenital heart disease; OPTN registry; organ allocation.

Antibody-mediated rejection (AMR) is a major cause of kidney allograft failure, with donor HLA-specific antibodies (DSA) recognized as primary drivers of AMR pathology. However, a significant proportion of AMR diagnoses lack detectable DSA, thus implicating DSA-independent mechanisms. In support, we previously reported on the accumulation of autoreactive B cells in rejecting renal biopsies, which raised the possibility that autoreactive IgG produced within the allograft contributes to graft pathology. In this study, we used mouse models to show that rejecting kidney allografts preferentially promoted a breach in autoreactive B cell tolerance, leading to the local production of autoreactive antibodies. Notably, autoreactive IgG responses were uncoupled from DSA production, indicative of distinct regulation. Organoid cultures confirmed that autoantibody production was observed in the rejecting kidney, whereas DSAs were produced in both the lymph node and graft. Intrarenal B cells expressing Nur77 were enriched for autoreactivity, consistent with in situ antigen recognition. Finally, autoreactive antibodies are pathogenic, since inhibiting autoantibody production with transient anti-IL-15 and CTLA-4Ig led to preserved kidney allografts. These unique features of in situ autoantibody responses may be relevant to diverse diseases with chronic tissue inflammation beyond transplantation.

Using toxin receptor-mediated cell ablation, a diabetes mouse model was generated that supports engraftment of human hematopoietic stem/progenitor cells (HSPCs) without the need for irradiation. The NBSGW immunodeficient strain was crossed with the NSG RIP-DTR which carries the diphtheria toxin receptor (hDTR) under the control of the rat insulin promoter to generate the NBSGW RIP-DTR mouse. This model enables controlled {beta}-cell ablation, robust human immune system reconstitution without myeloablative conditioning, and evaluation of human immune-mediated graft rejection within a single platform. NBSGW RIP-DTR mice exhibited reproducible and titratable diabetes induction, supported durable human islet engraftment and glycemic correction, and retained efficient human hematopoietic reconstitution comparable to the parental NBSGW strain. In humanized mice, diphtheria toxin-mediated diabetes induction was well tolerated and enabled assessment of human immune responses to allogeneic islet grafts. Collectively, these findings establish the NBSGW RIP-DTR mouse as an integrated and clinically relevant platform for studying {beta}-cell replacement therapies and human immune-mediated graft rejection. Article HighlightsO_LICurrent preclinical models do not simultaneously support controlled diabetes induction, human islet transplantation, and durable human immune reconstitution without irradiation. C_LIO_LIThis study asked whether the NBSGW RIP-DTR mouse could integrate diphtheria toxin-mediated {beta}-cell ablation with irradiation-free humanization in a single platform. C_LIO_LINBSGW RIP-DTR mice demonstrated reproducible diabetes induction, supported functional human islet engraftment, and retained robust human hematopoietic reconstitution comparable to parental strains. C_LIO_LIThese findings establish the NBSGW RIP-DTR model as a clinically relevant platform for studying {beta}-cell replacement and human immune response to islet allografts, xenografts and stem cell-derived islets. C_LI

The emergence of donor-specific antibodies (DSA) against HLA-DQ reduces graft survival and limits future transplant options. Current practice predicts DSA development from HLA antigen mismatches or unique eplet counts (HLAMatchmaker), but predictive accuracy remains limited. Improving the prediction accuracy is crucial for solid organ transplants. We analysed a retrospective cohort of 240 kidney transplants (480 donor-DQ samples) in which the donor DQ allele targeted by each post-transplant DSA was identified. We compared the predictive accuracy of unique eplets (HLAMatchmaker), total eplets, amino acid mismatches, PAM genetic distance, and electrostatic mismatch score (EMS), individually and in combination. DSA emerge through the response of two donor and two patient DQ heterodimers. We evaluate the appropriate combination method of patient and donor alleles. Total eplet or amino acid mismatch counts outperformed unique eplets as used in HLAMatchmaker (AUC 0.79 vs. 0.73). Combining eplets with PAM and EMS distances in an XGBoost classifier achieved AUC 0.84, with a hazard ratio above 7. The most informative features were PAM distance and a subset of eplets distributed across the HLA-DQ alpha and beta chains. When extending prediction from a single donor DQ allele to the donor as a whole, the maximum of the two per-allele scores outperformed a probabilistic combination. The unique-eplet approach is suboptimal for predicting anti-DQ DSA in this cohort; combining total eplets with genetic and biochemical distance metrics yields substantially better prediction, essential for the reduction of DSA emergence. External validation in independent cohorts is the necessary next step.

BACKGROUND: Increased left ventricular mass (LVM) at a single time point after heart transplantation (HT) predicts future adverse outcomes. However, dynamic changes in LVM could have better biological relevance and reflect adverse graft remodeling (AGR). The prognostic significance of such serial changes has not been studied. METHODS: Using an automated, electronic health record-based institutional data infrastructure, we studied 439 HT recipients with 5,563 LVM measurements. Separate Bayesian joint models estimated the simultaneous associations of current LVM and its instantaneous rate of change with graft dysfunction (GD) and mortality. A joint-model-derived remodeling score combining patient-specific deviations in LVM and slope was dichotomized to define AGR and non-AGR groups. A mixed-effects analysis of all clinical variables was performed to assess associations with LVM both between and within patients. An independent cohort of 35 patients with 79 surveillance-biopsy RNA-sequencing samples was used to examine early stress-responsive pathways associated with the remodeling score. RESULTS: LVM declined by approximately 7 g/year after transplantation, with regression attenuating over time. Sixty patients (13.7%) had GD, and 75 (17.1%) died. Higher LVM was associated with subsequent GD (hazard ratio [HR] per 10 g, 1.14; 95% credible interval [CrI], 1.02-1.28) and mortality (HR, 1.10; 95% CrI, 1.02-1.19). A more positive LVM slope was associated with GD (HR per 1 g/year, 1.21; 95% CrI, 1.06-1.42) and with cardiac allograft vasculopathy (CAV) grade 2 or 3 (HR, 1.39; 95% Crl, 1.02-1.96). LVM regressed more slowly in the AGR group (-5.8 vs -8.4 g/year), with higher GD (21.0% vs 6.4%) and mortality (24.2% vs 10.0%). Time-updated GD was associated with subsequent death (HR, 8.12; 95% Confidence Interval [CI], 4.67-14.14). Transcriptomic analysis showed enrichment of interferon-mediated signaling and vascular endothelial activation with higher remodeling scores, whereas lower scores were associated with mitochondrial and metabolic processes, ribosome biogenesis, and pathways related to tissue repair and stress responses. CONCLUSIONS: AGR is an easily accessible imaging biomarker that reflects the changes in the allograft in response to various stressors and predicts future adverse outcomes. Discovery of molecular mechanisms of AGR could lead to novel therapies to protect the allograft from chronic rejection.

Viral infections remain a cause of substantial morbidity and mortality in allogeneic hematopoietic cell transplant (aHCT) recipients. While antiviral prophylaxis has dramatically reduced the risk of herpes simplex virus (HSV) disease, the relationship between HSV serostatus and major post-transplant complications in the context of HSV prophylaxis is unknown. We evaluated the association between HSV serostatus and survival among adults who received a first aHCT at the Fred Hutchinson Cancer Center between 2002 and 2022. Patients were screened for HSV-1 and HSV-2 by Western blot (WB) prior to transplant. We fit Cox proportional hazards models for mortality up to one year post-transplant, comparing HSV seropositive to seronegative patients. Models were adjusted for age, sex, cytomegalovirus (CMV) serostatus, conditioning regimen, disease risk, graft type and HLA matching, year of transplant and acute graft-versus host disease. A total of 4,016 aHCT recipients were included in this analysis. The cumulative all-cause 1-year mortality was 29.8%. For HSV-1, the adjusted hazard ratio (aHR) for all-cause mortality comparing seropositive to seronegative individuals was 1.20 (95% CI: 1.06-1.36). The aHRs for relapse, non-relapse mortality (NRM) and relapse-related mortality (RRM) were 1.46 (1.24-1.71), 1.04 (0.89-1.21), and 1.75 (1.40-2.19), respectively. For HSV-2, the aHRs for all-cause mortality, relapse, NRM, and RRM were 1.03 (0.93-1.14), 1.16 (1.03-1.31), 0.99 (0.87-1.13), and 1.13 (0.97-1.33), respectively. Despite universal antiviral prophylaxis, HSV-1 seropositivity was associated with higher mortality in the year after transplant, driven by RRM. Further studies are needed to confirm the association and understand the potential mechanisms underlying this relationship.

BackgroundLupus nephritis remains a major cause of chronic kidney disease and kidney failure in systemic lupus erythematosus. Glucocorticoids are central to treatment but are limited by systemic toxicity. We evaluated whether a previously characterized collagen IV 3-targeted liposomal nanoparticle formulation carrying low-dose prednisolone could attenuate established lupus nephritis in MRL/lpr mice. MethodsFemale MRL/lpr mice with disease present at treatment initiation and C57BL/6J control mice received saline or collagen IV 3-targeted prednisolone-loaded nanoparticles (Col4-3-Pred-NPs). Renal outcomes were assessed by longitudinal proteinuria, glomerular filtration rate (GFR), survival, kidney histopathology, renal IgG and C3d deposition, dUTP/TUNEL-associated injury staining, and renal cytokine/chemokine profiling. Body weight, food and water intake, and blood glucose were monitored as measures of general condition and preliminary tolerability. ResultsCol4-3-Pred-NPs improved survival in MRL/lpr mice, reduced cumulative proteinuria burden, and attenuated terminal GFR decline compared with saline-treated MRL/lpr controls. Treatment reduced glomerular and tubulointerstitial injury, lowered composite EGTI histopathology scores, decreased terminal kidney enlargement, reduced glomerular IgG deposition and renal dUTP-positive injury signals, and reduced renal signals for IL-28A/B, IL-7, PD-ECGF, IL-11, CCL6/C10, and IL-15. C3d deposition was not significantly altered. Nanoparticle treatment was not associated with sustained treatment-related increases in blood glucose or body-weight loss during the measured study period. ConclusionsCollagen IV 3-targeted liposomal delivery of low-dose prednisolone attenuated established lupus nephritis in MRL/lpr mice and improved renal structural, functional, inflammatory, and survival outcomes. These findings support further evaluation of glomerulus-targeted nanotherapy as a potential strategy to improve the precision and therapeutic index of glucocorticoid treatment in lupus nephritis.

Background: Adult congenital heart disease (ACHD) patients are prone to HLA-antibody formation from multiple surgeries, transfusions, and prosthetic surgical material. Females with ACHD may accrue additional, non-surgical alloantigen exposure. Whether sex modifies the impact of allosensitization on heart transplant (HT) access and outcomes in ACHD remains unknown. Methods: We retrospectively analyzed the OPTN/UNOS registry of adults with ACHD listed for first-time HT (2018-2025). Sensitization was defined by calculated panel reactive antibodies (cPRA) at listing. We tested the sex x sensitization (highly sensitized, cPRA >50%) interaction on transplant access using Fine-Gray competing-risks regression, treating transplantation as the event of interest and death or removal from the waitlist as competing events, and on post-transplant survival using multivariable Cox proportional-hazards regression, both adjusted for age at listing, mechanical support at listing, and the number of distinct prior cardiac surgery categories. Results: Among 856 candidates (38% female), females were more often highly sensitized than males (23% vs 14%; age-adjusted OR 1.81, 95% CI 1.26-2.61), even after adjusting for surgical burden. Sensitization reduced transplant access in females (84% to 71%; median wait 60 to 110 days, p < 0.001) but not males (79% vs 79%, median wait 88 vs 98 days). In adjusted Fine-Gray models, the subdistribution hazard for transplant was reduced in sensitized females (sHR 0.54, 95% CI 0.41-0.72) with no effect in males (sHR 0.96, 95% CI 0.73-1.26), and the sex x sensitization interaction was significant (interaction sHR 0.64, 95% CI 0.44-0.94, p = 0.02). Post-transplant mortality was numerically higher in sensitized than non-sensitized candidates in both sexes and the sex x sensitization interaction on 1-year mortality was not significant. The sex-asymmetric effect persisted and was more pronounced in the multiorgan candidates. Conclusions: Allosensitization is not a sex-neutral barrier to transplant in HT candidates with ACHD. Females are more sensitized and have reduced transplant access without differences in 1-year mortality. The female excess in sensitization is not accounted for by surgical burden, and the exposures responsible remain to be defined. These findings warrant a sex-aware listing strategy and further studies.

Background: The efficacy and safety of avacopan in ANCA-associated vasculitis (AAV) has been established in randomized trials of of avacopan as a glucocorticoid (GC) sparing therapy. However, real world evidence (RWE) has an important role in confirming effectiveness and evaluating safety in more generalizable settings. This study aimed to synthesize RWE on the effectiveness and safety of avacopan in adults with AAV. Methods: A systematic literature review and meta analysis of non interventional real world studies was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) guidelines. Eligible studies included adults with AAV treated with avacopan in routine clinical practice. Pooled estimates of effectiveness and safety outcomes were calculated using random effects meta-analyses. Primary outcomes included remission at 6 and 12 months and sustained remission at 12 months. Secondary outcomes included relapse, GC use and dosing, hepatotoxicity, infections, and treatment discontinuation. Exploratory outcomes included changes in estimated glomerular filtration rate (eGFR) and dialysis related endpoints. Results: A total of 71 studies were included and contributed to quantitative analyses. Pooled remission for patients on avacopan was 87% (95% CI: 75%-94%) at 6 months and 93% (95% CI: 86%-97%) at 12 months, and sustained remission was 86% (95% CI: 74%-93%) at 12 months. Relapse at 12 months was low (7%; 95% CI: 4%-11%). GC use was 36% at both 6 and 12 months. Improvements in eGFR were observed at 6 months (18 mL/min/1.73 m2) and 12 months (18 mL/min/1.73 m2), and dialysis liberation was 66% in a limited subset. Among avacopan patients, 11% experienced any hepatotoxicity, including 7% with serious (defined as directly reported or requiring hospitalization) hepatotoxicity, while 7% experienced serious (defined as directly reported or requiring hospitalization) infection. Conclusions: In real world clinical practice, avacopan is associated with high remission rates, low relapse rates, and a consistent GC sparing effect, with effectiveness comparable to standard of care regimens. Findings support its clinical use with appropriate safety monitoring; however, the observed heterogeneity in hepatotoxicity and the limited comparative effectiveness evidence highlight areas requiring further investigation.

Background & Aims: Liver transplantation improves outcomes in hepatocellular carcinoma (HCC), yet treatment options for patients with tumor recurrence remain limited to tyrosine kinase inhibitors. Glypican-3 (GPC3)-targeted CAR T cells offer a tumor-directed immune-based therapeutic strategy, but their efficacy may be limited by post-transplant immunosuppression. We developed a CAR T cell platform combining CRISPR/Cas9-mediated FKBP1A disruption to confer resistance to FKBP12-dependent immunosuppressive agents, including tacrolimus, everolimus, and sirolimus, with TRAC knockout to eliminate endogenous T cell receptor expression and reduce alloreactivity. Methods: Human T cells were edited using Cas9 ribonucleoprotein complexes targeting FKBP1A and TRAC, expanded, and transduced with an anti-GPC3 CAR construct. Cytokine production and cytotoxicity were assessed in vitro. Antitumor activity under tacrolimus treatment was evaluated in a Hep G2 xenograft model, and xenoreactivity was assessed in a graft-versus-host disease model. FKBP1A/TRAC double-knockout T cells were enriched using mTOR inhibitor selection combined with CD3-based MACS depletion. PBMCs from liver transplant recipients were used to evaluate feasibility for clinical translation during the early post-transplant period. Results: Tacrolimus suppressed wild-type CAR T cell function but not FKBP1A/TRAC double-knockout CAR T cells, which retained cytokine production, cytotoxicity, and in vivo antitumor activity. Cyclosporine A remained suppressive, enabling its potential use as a pharmacologic control strategy. TRAC disruption reduced xenoreactivity. CD3-based MACS depletion and mTOR inhibition achieved functional double-knockout efficiencies greater than 98%, without compromising cell viability. Functional FKBP1A/TRAC knockout CAR T cells were generated from patient PBMC samples 30 days post-transplant. Conclusions: Dual-edited GPC3 CAR T cells resist tacrolimus-based immunosuppression while limiting alloreactivity, supporting their use for recurrent HCC after liver transplantation. Sequential, high-viability selection in a modular cellular engineering framework enables adaptation to alternative tumor targets and next-generation CAR T cell designs.

Background. Cardiovascular-kidney-metabolic (CKM) syndrome affects nearly 90% of US adults, yet most individuals at early, modifiable stages remain unidentified outside clinical care. Blood donation centers offer a scalable, non-clinical venue for CKM screening, but the potential benefit of screening in this context remains unclear. We projected the population-level impact of effective digital return of results (ROR) to inform the design of a pragmatic trial. Methods. We developed a Monte Carlo simulation (100,000 iterations) of the incident major adverse cardiovascular events (MACE), end-stage renal disease (ESRD), and type 2 diabetes (T2DM) preventable by ROR-prompted, guideline-concordant follow-up among donors in CKM Stages 1-2. The estimand counts only events averted by donors who act because of ROR; the intervention effect was modeled directly on strictly positive support, and action was translated into prevented events through a hazard-based cumulative-incidence difference that counts each donor at most once. We evaluated 18 design cells (donor volumes 300,000, 1 million, and 8 million/year; 5- and 10-year horizons; action-rate gains of +10, +20, and +30 percentage points [pp]) and, in a complementary two-arm simulation, the assurance (expected power) of detecting the effect in a single deployment. Results. Under the primary +20 pp scenario, ROR at a single large blood center (300,000 donors/year) is projected to prevent a median of 2,201 events (95% uncertainty interval [UI], 1,099-4,364) over 10 years, scaling to 58,526 (29,154-116,769) at the national donor pool. All 18 design cells had strictly positive 95% lower bounds. The number needed to screen was 136 and the screening cost $2,045 per event prevented (at $15/donor), both invariant to donor volume. Impact scaled linearly with volume and effect size but sub-linearly with the horizon. Detection of the effect was effectively certain at gains of +20 pp or larger (assurance [&ge;]99.6% in every cell and >99.9% in all but the smallest 5-year cell). Conclusions. Even under the conservative scenario, digital CKM ROR at blood donation centers is projected to prevent hundreds to tens of thousands of incident cardiometabolic events at a screening cost per event well within accepted prevention benchmarks, providing prospective, quantitative justification for a pragmatic, randomized evaluation of digital ROR in non-clinical screening settings.

Accurate, reproducible interpretation of kidney allograft biopsies is critical for diagnosis of graft injury to guide prognosis and management. The international Banff classification is a consensus diagnostic system based on semiquantitative histological lesion scoring on either extent or severity of kidney transplant biopsies. However, pathologist scoring is limited by substantial interobserver variability, constrained scalability, and the inherent nature of the scoring system itself. Here we present BanffNET, a weakly supervised, probabilistic deep learning framework that combines self-supervised feature extraction with a novel Bayesian multiple-instance learning framework to predict (continuously) the full spectrum of Banff lesion scores directly from whole-slide images (WSIs). Using lesion-specific aggregation functions tailored to localized (modeling lesion severity) and diffuse pathologies (modeling lesion extent), BanffNET generates interpretable, patch-level probability maps and calibrated slide-level scores. BanffNET's performance was assessed relative to consensus, biological correlates of rejection and clinical outcome, demonstrating superior consistency, transportability and generalization. Trained on 7,249 WSIs from three cohorts, BanffNET demonstrates consistent performance on 11,028 WSIs across five external test sets, performing on par or exceeding expert consensus across lesions. BanffNET scores align more closely than pathologist Banff scores with molecular profiles of rejection, offering a transparent, biologically grounded framework for computational pathology with relevance beyond transplantation.

Abstract Objective: To synthesize the available evidence on the association between SARS-CoV-2-related microvascular thrombosis and acute kidney injury (AKI), with emphasis on renal outcomes, mortality, and renal replacement therapy requirements. Methods: This systematic review followed the PRISMA 2020 statement and was prospectively registered in PROSPERO (CRD420251132701). PubMed/MEDLINE, Scopus, and Embase were searched for systematic reviews, including meta-analyses, and umbrella reviews investigating the association between SARS-CoV-2-related microvascular thrombosis and acute kidney injury. Two reviewers independently performed study selection, data extraction, and methodological quality assessment using AMSTAR-2 and ROBIS. Evidence was synthesized through a structured narrative synthesis supported by quantitative data extracted from the included reviews. Results: Six evidence syntheses evaluating kidney involvement, thrombotic events, and microvascular mechanisms in COVID-19 were included. AKI incidence was 9.2% (95%CI 4.6-13.9) among hospitalized patients and 32.6% (95%CI 8.5-56.6) among critically ill patients. In children with multisystem inflammatory syndrome associated with SARS-CoV-2, AKI incidence was 20% (95%CI 14-28). Microvascular or thrombotic events were associated with adverse renal outcomes (OR 2.14; 95%CI 1.32-3.48). AKI was associated with increased mortality (OR 4.68; 95%CI 1.06-20.70) and greater likelihood of renal replacement therapy requirement (OR 2.87; 95%CI 1.45-5.68). The certainty of evidence ranged from moderate to high for the principal outcomes. Conclusion: Current evidence supports an important association between microvascular thrombotic injury and COVID-19-associated AKI. These findings reinforce the relevance of endothelial dysfunction and thromboinflammatory pathways in kidney involvement during COVID-19 and highlight the need for early renal monitoring, risk stratification, and kidney-protective strategies in high-risk patients. Keywords: COVID-19; Acute Kidney Injury; Microvascular Thrombosis; SARS-CoV-2; Renal Replacement Therapy; Systematic Review

Background Graft versus host disease (GVHD) remains a major determinant of morbidity and mortality following allogeneic hematopoietic stem cell transplantation (allo HSCT). Existing GVHD prediction models demonstrate modest discrimination and limited generalizability, and calibration drift across external populations is rarely characterized despite its essential role in the clinical interpretability of predicted probabilities. Objectives To develop and externally validate an explainable machine learning framework for predicting acute and chronic GVHD and associated overall survival in patients with acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), and myelodysplastic syndromes (MDS) undergoing allo HSCT, and to systematically characterize calibration across heterogeneous external validation cohorts to inform deployment requirements. Study Design The model was developed on three publicly available registry-derived datasets (N = 2,509) and externally validated across six independent cohorts (N = 14,788) comprising adult and pediatric allo HSCT recipients, including a regional Middle Eastern cohort (UAE and Jordan). A standardized preprocessing pipeline harmonized heterogeneous datasets. Gradient boosting models (CatBoost) were used for binary GVHD prediction; exploratory overall survival analysis used a Cox proportional hazards model with predicted acute GVHD risk as a covariate. Discrimination (AUROC with bootstrap 95% CI), calibration (logistic recalibration intercept and slope with analytical 95% CI), and feature importance (SHapley Additive exPlanations, SHAP) were assessed in training out-of-fold and all external cohorts. Results In internal validation, AUROC was 0.63 (95% CI 0.61-0.65) for acute GVHD and 0.72 (95% CI 0.70-0.74) for chronic GVHD. External validation demonstrated AUROC ranges of 0.51-0.57 (acute) and 0.54-0.64 (chronic), with consistent performance across disease subgroups despite substantial heterogeneity in transplant practices and feature availability. In exploratory survival analysis, the acute-GVHD-informed Cox model achieved a training-cohort C-index of 0.679 (95% CI 0.658-0.697); external C-indices ranged from 0.47-0.53. Calibration analysis identified systematic external risk overestimation (negative calibration intercept in 10 of 11 evaluable external cohort-target combinations) with heterogeneous slope drift requiring cohort-specific recalibration. Key predictors included recipient age, graft source, conditioning intensity, GVHD prophylaxis, and HLA match ratio. Conclusions An explainable, externally validated GVHD prediction framework was developed using heterogeneous registry-derived datasets, with systematic characterization of calibration drift across multiple external cohorts, an analysis rarely reported in prior GVHD prediction literature. Predictive performance was modest for acute GVHD and moderate for chronic GVHD, constrained by missing immunobiological variables and incomplete HLA characterization. Per-cohort recalibration is required before clinical deployment, with prospective validation and benchmarking against established GVHD risk scores identified as priority next steps.

Background Diagnostic interpretation of kidney allograft biopsies using the Banff classification remains variable, but the determinants of this variability are not fully defined. We performed a global, fully digital multi-reader study to identify the principal drivers of disagreement in Banff-based assessment. Methods Thirty six kidney transplant biopsies were independently scored by 67 renal pathologists on a standardized digital platform. Readers assessed Banff lesions on hematoxylin and eosin, periodic acid Schiff, and Jones' silver stains; final diagnostic categories were assigned using prespecified Banff-based decision rules. Interobserver agreement was quantified with Gwet's agreement coefficient (AC) statistics. Determinants of diagnostic agreement were evaluated) using pairwise mixed-effects logistic regression, and reader similarity was examined by principal component analysis (PCA) with post hoc molecular annotation. Results Agreement for final diagnostic categories was moderate (Gwet's AC1, 0.55; 95% CI, 0.47 - 0.63). Lesion-level agreement varied substantially, with lowest agreement for selected threshold-dependent inflammatory or semi-quantitative lesions, including interstitial inflammation in areas of IFTA, peritubular capillaritis and arteriolar hyalinosis. Diagnostic concordance differed markedly across biopsies, indicating strong case-level heterogeneity. In pairwise models, differences in active inflammatory and vascular lesion scoring were the strongest correlates of diagnostic disagreement; reader experience and geography contributed minimally. Principal component analysis showed reader variation was organized along two dominant axes: a rejection-calling threshold axis linked mainly to tubulointerstitial inflammatory injury, and a T cell-mediated (TCMR/TI) and antibody-mediated/microvascular (AMR/MVI) inflammation-oriented phenotypic classification axis. Conclusion Interobserver variation in Banff-based kidney transplant biopsy assessment is structured rather than random and driven mainly by how readers threshold and integrate key inflammatory lesion compartments rather than experience or geographic location.

Introduction: Plasma metagenomic next-generation sequencing (mNGS) may detect pathogens in solid organ transplant (SOT) recipients, but optimal patient selection and result interpretation remain uncertain. Methods: Physicians reviewed SOT recipients with first-instance clinical plasma mNGS testing (Karius, Inc.) and determined consensus microbiological diagnoses, clinical impact of results, diagnostic yield, and clinical outcome. mNGS results were compared to microbiological diagnoses. A HIPAA-compliant large language model (GPT-4) was used to analyze electronic medical record (EMR) data and predict risk of infection with atypical bacteria, invasive fungi, mycobacteria, or parasites (collectively: pre-specified organisms of presumed significance, POPS) and identify patients who had positive-impact mNGS testing. Results: Of 145 SOT recipients, 119 (82.1%) had positive tests, 42 (29.0%) had [&ge;] 1 POPS organism, and 27 (19.1%) had [&ge;] 1 organism causing positive clinical impact. Positive impact was highly correlated with POPS status, with 24 (88.9%) of 27 positive-impact organisms categorized as POPS (P<0.001). GPT-4 scores accurately identified patients with POPS diagnoses (AUC 0.86), and assigned higher scores to patients with positive test impact (P=0.001). mNGS testing had highest sensitivity for atypical bacteria (82.4% sensitivity) and lower sensitivity for Aspergillus spp (53.3% sensitivity). Detection of greater numbers of organisms by mNGS was associated with increased mortality risk (odds ratio 1.32 per organism detected). Discussion: Plasma mNGS is a valuable clinical tool in SOT recipients. Positive clinical impact is associated with detection of atypical bacteria, fungi, mycobacteria, or parasites. GPT-4 analysis of EMR data identifies patients at risk of infection from these organisms and most likely to benefit from mNGS testing.