Scoring PD-L1 Expression in Urothelial Carcinoma: An International Multi-Institutional Study on Comparison of Manual and Artificial Intelligence Measurement Model (AIM-PD-L1) Pathology Assessments.

Assessing programmed death ligand 1 (PD-L1) expression on tumor cells (TCs) using Food and Drug Administration-approved, validated immunoassays can guide the use of immune checkpoint inhibitor (ICI) therapy in cancer treatment. However, substantial interobserver variability has been reported using these immunoassays. Artificial intelligence (AI) has the potential to accurately measure biomarker expression in tissue samples, but its reliability and comparability to standard manual scoring remain to be evaluated. This multinational study sought to compare the %TC scoring of PD-L1 expression in advanced urothelial carcinoma, assessed by either an AI Measurement Model (AIM-PD-L1) or expert pathologists. The concordance among pathologists and between pathologists and AIM-PD-L1 was determined. The positivity rate of ≥ 1%TC PD-L1 was between 20-30% for 8/10 pathologists, and the degree of agreement and scoring distribution for among pathologists and between pathologists and AIM-PD-L1 was similar both scored as a continuous variable or using the pre-defined cutoff. Numerically higher score variation was observed with the 22C3 assay than with the 28-8 assay. A 2-h training module on the 28-8 assay did not significantly impact manual assessment. Cases exhibiting significantly higher variability in the assessment of PD-L1 expression (mean absolute deviation > 10) were found to have patterns of PD-L1 staining that were more challenging to interpret. An improved understanding of sources of manual scoring variability can be applied to PD-L1 expression analysis in the clinical setting. In the future, the application of AI algorithms could serve as a valuable reference guide for pathologists while scoring PD-L1.

Lesion-induced sprouting promotes neurophysiological integration of septal and entorhinal inputs to granule cells in the dentate gyrus of rats.

Axonal sprouting of dentate gyrus (DG) afferents after entorhinal cortex (EC) lesion is a model preparation to assess lesion-induced functional reorganization in a denervated target structure. Following a unilateral EC lesion, the surviving contralateral entorhinal projection, termed the crossed temporodentate pathway (CTD), and the heterotypic septal input to the DG, the septodentate pathway (SD), undergo extensive axonal sprouting. We explored whether EC lesion alters the capacity of the SD pathway to influence CTD-evoked granule cell excitability in the DG. We recorded extracellular field excitatory postsynaptic potentials (fEPSPs) after CTD stimulation alone and paired SD-CTD stimulation. Male rats were given unilateral EC lesions or sham operations; evoked fEPSPs in the DG were recorded at 4-, 15-, and 90-days post-entorhinal lesion to assess functional reorganization of the CTD and SD pathways. We found significantly increased fEPSP amplitudes in cases with unilateral lesions compared to sham-operates at 15- and 90-days post lesion. Within each time point, paired SD-CTD stimulation resulted in significantly depressed fEPSP amplitudes compared to amplitudes evoked after CTD stimulation alone and this effect was solely seen in cases with EC lesion. In cases where granule cell discharge was observed, SD stimulation increased discharge amplitude elicited by the CTD stimulation at 90-days postlesion. These findings demonstrate that synaptic remodeling following unilateral cortical lesion results in a synergistic interaction between two established hippocampal afferents that is not seen in uninjured brains. This work may be important for models of neurodegenerative disease and neural injury that target these structures and associated hippocampal circuitry.

A large majority of awake hippocampal sharp-wave ripples feature spatial trajectories with momentum.

During periods of rest, hippocampal place cells feature bursts of activity called sharp-wave ripples (SWRs). Heuristic approaches have revealed that a small fraction of SWRs appear to "simulate" trajectories through the environment, called awake hippocampal replay. However, the functional role of a majority of these SWRs remains unclear. We find, using Bayesian model comparison of state-space models to characterize the spatiotemporal dynamics embedded in SWRs, that almost all SWRs of foraging rodents simulate such trajectories. Furthermore, these trajectories feature momentum, or inertia in their velocities, that mirrors the animals' natural movement, in contrast to replay events during sleep, which lack such momentum. Last, we show that past analyses of replayed trajectories for navigational planning were biased by the heuristic SWR sub-selection. Our findings thus identify the dominant function of awake SWRs as simulating trajectories with momentum and provide a principled foundation for future work on their computational function.