(1) Background: The need to elucidate the microbial patterns in preservation fluid and explore their relationship with early infection-related events post kidney transplant and investigate antimicrobial resistance and the effects of preemptive antibiotic therapy. (2) Methods: This retrospective study analyzed the clinical data of 514 kidney transplant donors and 808 recipients from April 2015 to October 2020. Clinical data of donor and recipient characteristics, preservation fluid microbes, early infections (≤30 days), probable donor-derived infections (P-DDIs), antimicrobial resistance and preemptive antibiotic therapy was collected. (3) Results: The incidence of bloodstream (10.3% versus 5.2%, p = 0.006) and graft-site infections (9.7% versus 4.6%, p = 0.004) was significantly higher in recipients with culture-positive preservation fluid. In addition, recipients with ESKAPE pathogens or Candida species had a notably higher rate of bloodstream infections (14.1% versus 6.9%, p = 0.033) and graft-site infections (16.7% versus 3.5%, p < 0.01) than those with other positive pathogens. Preemptive antibiotic therapy decreased the bloodstream infection rate (11.8% versus 35.7%, p = 0.047) when preservation fluid was positive for ESKAPE pathogens. (4) Conclusions: Culture-positive preservation fluid has potential implications for kidney transplant recipients. ESKAPE pathogens or Candida species in preservation fluid as well as their antimicrobial resistance properties and non-preemptive antibiotic therapy could pose a risk of early infection-related events.

Spatial transcriptomics and proteomics have enabled profound insights into tissue organization, yet these technologies remain largely disparate, and emerging same-slide multiomics approaches are limited in plex, spatial resolution, signal retention, and integrative analytics. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined, resource-efficient, commercially compatible workflow using single-cell spatial proteomics-derived imaging to guide transcriptomic capture on the same slide without RNA signal loss. To integrate modalities beyond niche-level mapping, we developed Spectral Graph Cross-Correlation (SGCC), a proteomic–transcriptomic framework resolving spatially coordinated functional state changes across interacting cell populations. Applied to diffuse large B-cell lymphoma (DLBCL), IN-DEPTH and SGCC enabled stepwise discovery from Epstein–Barr virus (EBV)–positive and EBV-negative tumor comparisons with single-cell resolution, revealing coordinated tumor–macrophage–CD4 T-cell remodeling, immunosuppressive C1Q macrophage enrichment, CD4 T-cell dysfunction, and a candidate IL27–STAT3 signaling axis. Collectively, IN-DEPTH enables scalable spatial multiomics to uncover clinically relevant microenvironmental mechanisms and toward robust spatial multimodal AI models. Significance: IN-DEPTH enables same-slide spatial multiomics across commercial platforms via a protein-first strategy preserving protein epitopes, RNA quality, and tissue integrity. Coupled with SGCC, it resolves coordinated spatial immune remodeling, revealing EBV/LMP1-driven C1Q macrophage polarization and CD4 T-cell dysfunction in DLBCL, with broad applicability to other diseases.

Glycans regulate multiple physiological processes, including immune recognition and cancer progression. In disease, altered glycan landscapes are interpreted by human lectins. Functional glycan-lectin interactions are difficult to profile because glycans are not genome-encoded and their changes are poorly captured by existing multimodal methods. We present two platforms, single-cell outlining and transcriptome sequencing (scGOAT-seq) and GlycoScope, which use human lectins to enable functional glycan accessibility into single-cell and spatial multiomic measurements. ScGOAT-seq quantifies lectin-accessible glycan states with gene expression, while GlycoScope enables multiplexed in situ co-detection of glycans and proteins in tissues. Applying these approaches to immune cells, we identify stimulus-specific glycan remodeling and show that distinct Siglec-ligand-defined programs stratify immune activation states not captured by traditional methods; in follicular lymphoma, GlycoScope, resolves spatial glycan programs associated with malignant B cells and localized immune microenvironments. The presented methods provide a general framework for integrating functional glycan accessibility into single-cell and spatial multiomics.

(1) Calculated panel-reactive antibody (CPRA) is a measure of sensitization based on unacceptable antigens (UAs). Determination of UAs based on single-antigen bead assays at allele or antigen levels may be inappropriate. We aimed to introduce eplets for better assessment of sensitization; (2) 900 recipients and 1427 donors were enrolled for candidate or donor pools, respectively. Eplets were from the HLA Epitope Registry. UAs were determined by anti-HLA antibodies identified using LIFECODES Single Antigen (LSA) kits. CPRA values were calculated using a simplified method of donor filtering; (3) HLA antigens containing all eplets of an HLA antigen in LSA kits (LSA antigen) were defined as eplet-predicted (EP) antigens, the reactivity of which could be predicted by that LSA antigen. High reactivity concordance was found between LSA and EP antigens. More HLA antigens were covered by EP antigens in the population than LSA antigens. CPRA values at the EP level were higher than at the allele level and lower than at the antigen level. The EP antigens facilitated UA determination for non-LSA antigens and avoided acute rejection; (4) UA determination using EP antigens can lead to more accurate assessment of sensitization, enabling a high probability of compatible organs and a low risk of adverse outcomes.

Parameters used in SIFT alignment.