Deprotonation of formic, acetic acids and bicarbonate ion in slit silica nanopores at infinite dilution and in the presence of electrolytes.

Dielectric effects and the coupled electrostatics between the nanoconfined and the internal/external aqueous media contribute to the observed deviations of chemistry within the nanoconfined environment when compared with unconfined systems. A systematic understanding has remained elusive, especially with respect to background salt concentration and boundary condition effects like the nanopore surface chemistry and the reference state used to calculate free energies. We utilize molecular dynamics simulations along with thermodynamic integration to determine the free energy difference associated with acid-base chemistry in 2 nm and 4 nm slit pores open to a bulk-like reservoir. pKa increases are predicted when confining acetic acid, formic acid, and bicarbonate in the slits at infinite dilution conditions. We find that confinement weakens the acids, and the modulation of outer pore surface dipole magnitudes can tune the pKa shift values, suggesting that purely "intrinsic" electrostatic effect on confinement may not exist. At sufficiently high salt concentrations, the dielectric/electrostatic effects on pKa values diminish due to charge screening effects. These discoveries enable future modifications of nanopore chemistries to achieve desirable properties for industrial applications.

Hybrid Density Functional Theory Comparison of Oxygen Release and Solvent Decomposition Kinetics on LixNiO2 Surfaces.

High-nickel-content layered oxides are among the most promising electric vehicle battery cathode materials. However, their interfacial reactivity with electrolytes and tendency toward oxygen release (possibly yielding reactive 1O2) remain degradation concerns. Elucidating the most relevant (i.e., fastest) interfacial degradation mechanism will facilitate future mitigation strategies. We apply screened hybrid density functional (HSE06) calculations to compare the reaction kinetics of LixNiO2 surfaces with ethylene carbonate (EC) with those of O2 release. On both the (001) and (104) facets, EC oxidative decomposition exhibits lower activation energies than O2 release. Our calculations, coupled with previously computed liquid-phase reaction rates of 1O2 with EC, strongly question the role of "reactive 1O2" species in electrolyte oxidative degradation. The possible role of other oxygen species is discussed. To deal with the challenges of modeling LixNiO2 surface reactivity, we emphasize a "local structure" approach instead of pursuing the global energy minimum.

MFGE8 in exosomes derived from mesenchymal stem cells prevents esophageal stricture after endoscopic submucosal dissection in pigs.

BACKGROUND: Endoscopic submucosal dissection (ESD) is the current standard treatment for early-stage esophageal neoplasms. However, the postoperative esophageal stricture after extensive mucosal dissection remains a severe challenge with limited effective treatments available. In this study, we introduced a chitosan/gelatin (ChGel) sponge encapsulating the adipose mesenchymal stem cells (ADMSCs)-derived exosomes (ChGelMSC-Exo) for the prevention of esophageal stenosis after ESD in a porcine model. RESULTS: Pigs were randomly assigned into (1) ChGelMSC-Exo treatment group, (2) ChGelPBS group, and (3) the controls. Exosome treatments were applied immediately on the day after ESD as well as on day 7. Exosome components crucial for wound healing were investigated by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and small RNA sequencing. ChGelMSC-Exo treatment significantly reduced mucosal contraction on day 21, with less fiber accumulation and inflammatory infiltration, and enhanced angiogenesis when compared with the control and ChGelPBS groups. The anti-fibrotic effects following MSC-Exo treatment were further found to be associated with the anti-inflammatory M2 polarization of the resident macrophages, especially within the M2b subset characterized by the reduced TGFß1 secretion, which sufficiently inhibited inflammation and prevented the activation of myofibroblast with less collagen production at the early stage after ESD. Moreover, the abundant expression of exosomal MFGE8 was identified to be involved in the transition of the M2b-macrophage subset through the activation of MFGE8/STAT3/Arg1 axis. CONCLUSIONS: Our study demonstrates that exosomal MFGE8 significantly promotes the polarization of the M2b-macrophage subset, consequently reducing collagen deposition. These findings suggest a promising potential for MSC-Exo therapy in preventing the development of esophageal stricture after near-circumferential ESD.

Challenges in the discovery of tumor-specific alternative splicing-derived cell-surface antigens in glioma.

Despite advancements in cancer immunotherapy, solid tumors remain formidable challenges. In glioma, profound inter- and intra-tumoral heterogeneity of antigen landscape hampers therapeutic development. Therefore, it is critical to consider alternative sources to expand the repertoire of targetable (neo-)antigens and improve therapeutic outcomes. Accumulating evidence suggests that tumor-specific alternative splicing (AS) could be an untapped reservoir of antigens. In this study, we investigated tumor-specific AS events in glioma, focusing on those predicted to generate major histocompatibility complex (MHC)-presentation-independent, cell-surface antigens that could be targeted by antibodies and chimeric antigen receptor-T cells. We systematically analyzed bulk RNA-sequencing datasets comparing 429 tumor samples (from The Cancer Genome Atlas) and 9166 normal tissue samples (from the Genotype-Tissue Expression project), and identified 13 AS events in 7 genes predicted to be expressed in more than 10% of the patients, including PTPRZ1 and BCAN, which were corroborated by an external RNA-sequencing dataset. Subsequently, we validated our predictions and elucidated the complexity of the isoforms using full-length transcript amplicon sequencing on patient-derived glioblastoma cells. However, analyses of the RNA-sequencing datasets of spatially mapped and longitudinally collected clinical tumor samples unveiled remarkable spatiotemporal heterogeneity of the candidate AS events. Furthermore, proteomics analysis did not reveal any peptide spectra matching the putative antigens. Our investigation illustrated the diverse characteristics of the tumor-specific AS events and the challenges of antigen exploration due to their notable spatiotemporal heterogeneity and elusive nature at the protein levels. Redirecting future efforts toward intracellular, MHC-presented antigens could offer a more viable avenue.

Antibody discovery identifies regulatory mechanisms of protein arginine deiminase 4.

Unlocking the potential of protein arginine deiminase 4 (PAD4) as a drug target for rheumatoid arthritis requires a deeper understanding of its regulation. In this study, we use unbiased antibody selections to identify functional antibodies capable of either activating or inhibiting PAD4 activity. Through cryogenic-electron microscopy, we characterized the structures of these antibodies in complex with PAD4 and revealed insights into their mechanisms of action. Rather than steric occlusion of the substrate-binding catalytic pocket, the antibodies modulate PAD4 activity through interactions with allosteric binding sites adjacent to the catalytic pocket. These binding events lead to either alteration of the active site conformation or the enzyme oligomeric state, resulting in modulation of PAD4 activity. Our study uses antibody engineering to reveal new mechanisms for enzyme regulation and highlights the potential of using PAD4 agonist and antagonist antibodies for studying PAD4-dependency in disease models and future therapeutic development.

Deep Semisupervised Transfer Learning for Fully Automated Whole-Body Tumor Quantification and Prognosis of Cancer on PET/CT.

Automatic detection and characterization of cancer are important clinical needs to optimize early treatment. We developed a deep, semisupervised transfer learning approach for fully automated, whole-body tumor segmentation and prognosis on PET/CT. Methods: This retrospective study consisted of 611 18F-FDG PET/CT scans of patients with lung cancer, melanoma, lymphoma, head and neck cancer, and breast cancer and 408 prostate-specific membrane antigen (PSMA) PET/CT scans of patients with prostate cancer. The approach had a nnU-net backbone and learned the segmentation task on 18F-FDG and PSMA PET/CT images using limited annotations and radiomics analysis. True-positive rate and Dice similarity coefficient were assessed to evaluate segmentation performance. Prognostic models were developed using imaging measures extracted from predicted segmentations to perform risk stratification of prostate cancer based on follow-up prostate-specific antigen levels, survival estimation of head and neck cancer by the Kaplan-Meier method and Cox regression analysis, and pathologic complete response prediction of breast cancer after neoadjuvant chemotherapy. Overall accuracy and area under the receiver-operating-characteristic (AUC) curve were assessed. Results: Our approach yielded median true-positive rates of 0.75, 0.85, 0.87, and 0.75 and median Dice similarity coefficients of 0.81, 0.76, 0.83, and 0.73 for patients with lung cancer, melanoma, lymphoma, and prostate cancer, respectively, on the tumor segmentation task. The risk model for prostate cancer yielded an overall accuracy of 0.83 and an AUC of 0.86. Patients classified as low- to intermediate- and high-risk had mean follow-up prostate-specific antigen levels of 18.61 and 727.46 ng/mL, respectively (P < 0.05). The risk score for head and neck cancer was significantly associated with overall survival by univariable and multivariable Cox regression analyses (P < 0.05). Predictive models for breast cancer predicted pathologic complete response using only pretherapy imaging measures and both pre- and posttherapy measures with accuracies of 0.72 and 0.84 and AUCs of 0.72 and 0.76, respectively. Conclusion: The proposed approach demonstrated accurate tumor segmentation and prognosis in patients across 6 cancer types on 18F-FDG and PSMA PET/CT scans.

Photoproximity Labeling from Single Catalyst Sites Allows Calibration and Increased Resolution for Carbene Labeling of Protein Partners In Vitro and on Cells.

The cell surface proteome (surfaceome) plays a pivotal role in virtually all extracellular biology, and yet we are only beginning to understand the protein complexes formed in this crowded environment. Recently, a high-resolution approach (µMap) was described that utilizes multiple iridium-photocatalysts attached to a secondary antibody, directed to a primary antibody of a protein of interest, to identify proximal neighbors by light-activated conversion of a biotin-diazirine to a highly reactive carbene followed by LC/MS (Geri, J. B.; Oakley, J. V.; Reyes-Robles, T.; Wang, T.; McCarver, S. J.; White, C. H.; Rodriguez-Rivera, F. P.; Parker, D. L.; Hett, E. C.; Fadeyi, O. O.; Oslund, R. C.; MacMillan, D. W. C. Science2020, 367, 1091-1097). Here we calibrated the spatial resolution for carbene labeling using site-specific conjugation of a single photocatalyst to a primary antibody drug, trastuzumab (Traz), in complex with its structurally well-characterized oncogene target, HER2. We observed relatively uniform carbene labeling across all amino acids, and a maximum distance of ∼110 Å from the fixed photocatalyst. When targeting HER2 overexpression cells, we identified 20 highly enriched HER2 neighbors, compared to a nonspecific membrane tethered catalyst. These studies identify new HER2 interactors and calibrate the radius of carbene photoprobe labeling for the surfaceome.

Challenges in the discovery of tumor-specific alternative splicing-derived cell-surface antigens in glioma.

Background: Despite advancements in cancer immunotherapy, solid tumors remain formidable challenges. In glioma, profound inter-and intra-tumoral heterogeneity of antigen landscape hampers therapeutic development. Therefore, it is critical to consider alternative sources to expand the repertoire of targetable (neo-)antigens and improve therapeutic outcomes. Accumulating evidence suggests that tumor-specific alternative splicing (AS) could be an untapped reservoir of neoantigens. Results: In this study, we investigated tumor-specific AS events in glioma, focusing on those predicted to generate major histocompatibility complex (MHC)-presentation-independent, cell-surface neoantigens that could be targeted by antibodies and chimeric antigen receptor (CAR)-T cells. We systematically analyzed bulk RNA-sequencing datasets comparing 429 tumor samples (from The Cancer Genome Atlas [TCGA]) and 9,166 normal tissue samples (from the Genotype-Tissue Expression project [GTEx]), and identified 13 AS events in 7 genes predicted to be expressed in more than 10% of the patients, including PTPRZ1 and BCAN , which were corroborated by an external RNA-sequencing dataset. Subsequently, we validated our predictions and elucidated the complexity of the isoforms using full-length transcript amplicon sequencing on patient-derived glioblastoma cells. However, analyses of the RNA-sequencing datasets of spatially mapped and longitudinally collected clinical tumor samples unveiled remarkable spatiotemporal heterogeneity of the candidate AS events. Furthermore, proteomics analysis did not reveal any peptide spectra matching the putative neoantigens. Conclusions: Our investigation illustrated the diverse characteristics of the tumor-specific AS events and the challenges of antigen exploration due to their notable spatiotemporal heterogeneity and elusive nature at the protein levels. Redirecting future efforts toward intracellular, MHC-presented antigens could offer a more viable avenue.

Formic and acetic acid pKa values increase under nanoconfinement.

Organic acids are prevalent in the environment and their acidity and the corresponding dissociation constants can change under varying environmental conditions. The impact of nanoconfinement (when acids are confined within nanometer-scale domains) on physicochemical properties of chemical species is poorly understood and is an emerging field of study. By combining infrared and Raman spectroscopies with molecular dynamics (MD) simulations, we quantified the effect of nanoconfinement in silica nanopores on one of the fundamental chemical reactions-the dissociation of organic acids. The pKa of formic and acetic acids confined within cylindrical silica nanopores with 4 nm diameters were measured. MD models were constructed to calculate the shifts in the pKa values of acetic acid nanoconfined within 1, 2, 3, and 4 nm silica slit pores. Both experiments and MD models indicate a decrease in the apparent acid dissociation constants (i.e., increase in the pKa values) when organic acids are nanoconfined. Therefore, nanoconfinement stabilizes the protonated species. We attribute this observation to (1) a decrease in the average dielectric response of nanoconfined aqueous solutions where charge screening may be decreased; or (2) an increase in proton concentration inside nanopores, which would shift the equilibrium towards the protonated form. Overall, the results of this study provide the first quantification of the pKa values for nanoconfined formic and acetic acids and pave the way for a unifying theory predicting the impact of nanoconfinement on acid-base chemistry.

Finding Infinities in Nanoconfined Geothermal Electrolyte Static Dielectric Properties and Implications on Ion Adsorption/Pairing.

Infinities should naturally occur in the dielectric responses of ionic solutions relevant to many geochemical, energy storage, and electrochemical applications at a strictly zero frequency. Using molecular dynamics simulations cross-referenced with coarse-grained Monte Carlo models, using nanoslit pore models at hydrothermal conditions, and treating confined mobile charges as polarization, we demonstrate the far reaching consequences. The dielectric permittivity profile perpendicular to the slit (ϵ⊥(z)) increases, not decreases, with ionic concentration, unlike in the more widely studied megahertz-to-gigahertz frequency range. In confined electrolytes, the divergences in ϵ⊥(z) correctly describe crossovers between bulk- and surface-dominated dielectric behavior. Nanoconfinement at low ionic concentrations changes monovalent ion energetics by 1-2 kJ/mol, but no dielectric property studied so far is universally correlated to ion adsorption or ion-ion interactions. We caution that infinities signal violation of the "electrical insulator" dielectric assumption.

Site-specific proximity labeling at single residue resolution for identification of protein partners in vitro and on cells.

The cell surface proteome, or surfaceome, is encoded by more than 4000 genes, but we are only beginning to understand the complexes they form. Rapid proximity labeling around specific membrane targets allows for capturing weak and transient interactions expected in the crowded and dynamic environment of the surfaceome. Recently, a high-resolution approach called µMap has been described (Geri, J. B., Oakley, J. V., Reyes-Robles, T., Wang, T., McCarver, S. J., White, C. H., Rodriguez-Rivera, F. P., Parker, D. L., Hett, E. C., Fadeyi, O. O., Oslund, R. C., and MacMillan, D. W. C. (2020) Science 367 , 1091-1097) in which an iridium (Ir)-based photocatalyst is attached to a specific antibody to target labeling of neighbors utilizing light-activated generation of carbenes from diazirine compounds via Dexter Energy Transfer (DET). Here we studied and optimized the spatial resolution for the method using an oncoprotein complex between the antibody drug, trastuzumab (Traz), and its target HER2. A set of eight single site-specific Ir-catalytic centers were engineered into Traz to study intra- and inter-molecular labeling in vitro and on cells by mass spectrometry. From this structurally well-characterized complex we observed a maximum distance of ∼110 Å for labeling. Labeling occurred almost uniformly over the full range of amino acids, unlike the residue specific labeling of other techniques. To examine on cell labeling that is specific to HER2 as opposed to simply being on the membrane, we compared the labeling patterns for the eight Traz-catalyst species to random labeling of membrane proteins using a metabolically integrated fatty acid catalyst. Our results identified 20 high confidence HER2 neighbors, many novel, that were more than 6-fold enriched compared to the non-specific membrane tethered catalyst. These studies define distance labeling parameters from single-site catalysts placed directly on the membrane target of interest, and more accurately compare to non-specific labeling to identify membrane complexes with higher confidence.

Examining the Molecular Origins of Anomalously High H2O Generation at Oxide-Passivated Metal Surfaces for Plasma Applications.

Elucidating the mechanisms responsible for sub-microsecond desorption of water and other impurities from electrode surfaces at high heating rates is crucial for understanding pulsed-power behavior and optimizing its efficiency. Ionization of desorbed impurities in the vacuum regions may create parallel loads and current loss. Devising methods to limit desorption during the short time duration of pulsed-power will signficantly improve the power output. This problem also presents an exciting challenge to and paradigm for molecular length-scale modeling and theories. Previous molecular modeling studies have strongly suggested that, under high vacuum conditions, the amount of water impurity adsorbed on oxide surfaces on metal electrodes is at a sub-monolayer level, which appears insufficient to explain the observed pulsed-power losses at high current densities. Based on Density Functional Theory (DFT) calculations, we propose that hydrogen trapped inside iron metal can diffuse into iron (III) oxide on the metal surface in sub-microsecond time scales, explaining the extra desorbed inventory. These hydrogen atoms react with the oxide to form Fe(II) and desorbed H2O at elevated temperatures. Cr2O3 is found to react more slowly to form Cr(II). H2 evolution is also predicted to require higher activation energies, so H2 may be evolved at later times than H2O. A one-dimensional diffusion model, based on DFT results, is devised to estimate the water outgassing rate under different conditions. This model explains outgassing above 1 ML for surface temperatures of 1 eV often assumed in pulsed-power systems. Finally, we apply a suite of characterization techniques to demonstrate that when iron metal is heated to 650 Celsius, the dominant surface oxide component becomes alpha-Fe2O3. We propose such specially-prepared samples will lead to convergence between atomic modeling and measurements like temperature-programmed desorption. .

Engaging a Non-catalytic Cysteine Residue Drives Potent and Selective Inhibition of Caspase-6.

Caspases are a family of cysteine-dependent proteases with important cellular functions in inflammation and apoptosis, while also implicated in human diseases. Classical chemical tools to study caspase functions lack selectivity for specific caspase family members due to highly conserved active sites and catalytic machinery. To overcome this limitation, we targeted a non-catalytic cysteine residue (C264) unique to caspase-6 (C6), an enigmatic and understudied caspase isoform. Starting from disulfide ligands identified in a cysteine trapping screen, we used a structure-informed covalent ligand design to produce potent, irreversible inhibitors (3a) and chemoproteomic probes (13-t) of C6 that exhibit unprecedented selectivity over other caspase family members and high proteome selectivity. This approach and the new tools described will enable rigorous interrogation of the role of caspase-6 in developmental biology and in inflammatory and neurodegenerative diseases.

Prediction of total knee replacement using deep learning analysis of knee MRI.

Current methods for assessing knee osteoarthritis (OA) do not provide comprehensive information to make robust and accurate outcome predictions. Deep learning (DL) risk assessment models were developed to predict the progression of knee OA to total knee replacement (TKR) over a 108-month follow-up period using baseline knee MRI. Participants of our retrospective study consisted of 353 case-control pairs of subjects from the Osteoarthritis Initiative with and without TKR over a 108-month follow-up period matched according to age, sex, ethnicity, and body mass index. A traditional risk assessment model was created to predict TKR using baseline clinical risk factors. DL models were created to predict TKR using baseline knee radiographs and MRI. All DL models had significantly higher (p < 0.001) AUCs than the traditional model. The MRI and radiograph ensemble model and MRI ensemble model (where TKR risk predicted by several contrast-specific DL models were averaged to get the ensemble TKR risk prediction) had the highest AUCs of 0.90 (80% sensitivity and 85% specificity) and 0.89 (79% sensitivity and 86% specificity), respectively, which were significantly higher (p < 0.05) than the AUCs of the radiograph and multiple MRI models (where the DL models were trained to predict TKR risk using single contrast or 2 contrasts together as input). DL models using baseline MRI had a higher diagnostic performance for predicting TKR than a traditional model using baseline clinical risk factors and a DL model using baseline knee radiographs.

Wirelessly powered deformable electronic stent for noninvasive electrical stimulation of lower esophageal sphincter.

Electrical stimulation is a promising method to modulate gastrointestinal disorders. However, conventional stimulators need invasive implantation and removal surgeries associated with risks of infection and secondary injuries. Here, we report a battery-free and deformable electronic esophageal stent for wireless stimulation of the lower esophageal sphincter in a noninvasive fashion. The stent consists of an elastic receiver antenna infilled with liquid metal (eutectic gallium-indium), a superelastic nitinol stent skeleton, and a stretchable pulse generator that jointly enables 150% axial elongation and 50% radial compression for transoral delivery through the narrow esophagus. The compliant stent adaptive to the dynamic environment of the esophagus can wirelessly harvest energy through deep tissue. Continuous electrical stimulations delivered by the stent in vivo using pig models significantly increase the pressure of the lower esophageal sphincter. The electronic stent provides a noninvasive platform for bioelectronic therapies in the gastrointestinal tract without the need for open surgery.

Adsorption at Nanoconfined Solid-Water Interfaces.

Reactions at solid-water interfaces play a foundational role in water treatment systems, catalysis, and chemical separations, and in predicting chemical fate and transport in the environment. Over the last century, experimental measurements and computational models have made tremendous progress in capturing reactions at solid surfaces. The interfacial reactivity of a solid surface, however, can change dramatically and unexpectedly when it is confined to the nanoscale. Nanoconfinement can arise in different geometries such as pores/cages (3D confinement), channels (2D confinement), and slits (1D confinement). Therefore, measurements on unconfined surfaces, and molecular models parameterized based on these measurements, fail to capture chemical behaviors under nanoconfinement. This review evaluates recent experimental and theoretical advances, with a focus on adsorption at solid-water interfaces. We review how nanoconfinement alters the physico-chemical properties of water, and how the structure and dynamics of nanoconfined water dictate energetics, pathways, and products of adsorption in nanopores. Finally, the implications of these findings and future research directions are discussed.

Computational pipeline provides mechanistic understanding of Omicron variant of concern neutralizing engineered ACE2 receptor traps.

The SARS-CoV-2 Omicron variant, with 15 mutations in Spike receptor-binding domain (Spike-RBD), renders virtually all clinical monoclonal antibodies against WT SARS-CoV-2 ineffective. We recently engineered the SARS-CoV-2 host entry receptor, ACE2, to tightly bind WT-RBD and prevent viral entry into host cells ("receptor traps"). Here we determine cryo-EM structures of our receptor traps in complex with stabilized Spike ectodomain. We develop a multi-model pipeline combining Rosetta protein modeling software and cryo-EM to allow interface energy calculations even at limited resolution and identify interface side chains that allow for high-affinity interactions between our ACE2 receptor traps and Spike-RBD. Our structural analysis provides a mechanistic rationale for the high-affinity (0.53-4.2 nM) binding of our ACE2 receptor traps to Omicron-RBD confirmed with biolayer interferometry measurements. Finally, we show that ACE2 receptor traps potently neutralize Omicron and Delta pseudotyped viruses, providing alternative therapeutic routes to combat this evolving virus.

Theranostic Targeting of CUB Domain-Containing Protein 1 (CDCP1) in Multiple Subtypes of Bladder Cancer.

PURPOSE: Despite recent approvals for checkpoint inhibitors and antibody-drug conjugates targeting NECTIN4 or TROP2, metastatic bladder cancer remains incurable and new treatment strategies are urgently needed. CUB domain-containing protein 1 (CDCP1) is a cell surface protein and promising drug target for many cancers. This study aimed to determine whether CDCP1 is expressed in bladder cancer and whether CDCP1 can be targeted for treatment with radiolabeled antibodies. EXPERIMENTAL DESIGN: CDCP1 expression was evaluated in four bladder cancer datasets (n = 1,047 biopsies). A tissue microarray of primary bladder cancer biopsies was probed for CDCP1 by IHC. CDCP1 expression was evaluated in patient-derived xenografts and cell lysates by immunoblot, flow cytometry, and saturation binding assays. Tumor detection in mouse bladder cancer models was tested using 89Zr-labeled 4A06, a monoclonal antibody targeting the ectodomain of CDCP1. 177Lu-4A06 was applied to mice bearing UMUC3 or HT-1376 xenografts to evaluate antitumor effects (CDCP1 expression in UMUC3 is 10-fold higher than HT-1376). RESULTS: CDCP1 was highest in the basal/squamous subtype, and CDCP1 was expressed in 53% of primary biopsies. CDCP1 was not correlated with pathologic or tumor stage, metastatic site, or NECTIN4 and TROP2 at the mRNA or protein level. CDCP1 ranged from 105 to 106 receptors per cell. Mechanism studies showed that RAS signaling induced CDCP1 expression. 89Zr-4A06 PET detected five human bladder cancer xenografts. 177Lu-4A06 inhibited the growth of UMUC3 and HT-1376 xenografts, models with high and moderate CDCP1 expression, respectively. CONCLUSIONS: These data establish that CDCP1 is expressed in bladder cancer, including TROP2 and NECTIN4-null disease, and suggest that bladder cancer can be treated with CDCP1-targeted radiotherapy.

Deep learning and radiomics framework for PSMA-RADS classification of prostate cancer on PSMA PET.

BACKGROUND: Accurate classification of sites of interest on prostate-specific membrane antigen (PSMA) positron emission tomography (PET) images is an important diagnostic requirement for the differentiation of prostate cancer (PCa) from foci of physiologic uptake. We developed a deep learning and radiomics framework to perform lesion-level and patient-level classification on PSMA PET images of patients with PCa. METHODS: This was an IRB-approved, HIPAA-compliant, retrospective study. Lesions on [18F]DCFPyL PET/CT scans were assigned to PSMA reporting and data system (PSMA-RADS) categories and randomly partitioned into training, validation, and test sets. The framework extracted image features, radiomic features, and tissue type information from a cropped PET image slice containing a lesion and performed PSMA-RADS and PCa classification. Performance was evaluated by assessing the area under the receiver operating characteristic curve (AUROC). A t-distributed stochastic neighbor embedding (t-SNE) analysis was performed. Confidence and probability scores were measured. Statistical significance was determined using a two-tailed t test. RESULTS: PSMA PET scans from 267 men with PCa had 3794 lesions assigned to PSMA-RADS categories. The framework yielded AUROC values of 0.87 and 0.90 for lesion-level and patient-level PSMA-RADS classification, respectively, on the test set. The framework yielded AUROC values of 0.92 and 0.85 for lesion-level and patient-level PCa classification, respectively, on the test set. A t-SNE analysis revealed learned relationships between the PSMA-RADS categories and disease findings. Mean confidence scores reflected the expected accuracy and were significantly higher for correct predictions than for incorrect predictions (P < 0.05). Measured probability scores reflected the likelihood of PCa consistent with the PSMA-RADS framework. CONCLUSION: The framework provided lesion-level and patient-level PSMA-RADS and PCa classification on PSMA PET images. The framework was interpretable and provided confidence and probability scores that may assist physicians in making more informed clinical decisions.

Using Split Luminescent Biosensors for SARS-CoV-2 Antibody Detection in Serum, Plasma, and Blood Samples.

Antibody detection assays are essential for evaluating immunity of individuals against a given virus, and this has been particularly relevant during the COVID-19 pandemic. Current serology assays either require a laboratory setting and take >1 hr (i.e., enzyme-linked immunosorbent assay [ELISA]) or are rapid but only qualitative in nature and cannot accurately track antibody levels over time (i.e., lateral flow assay [LFA]). Therefore, there is a need for development of a rapid and simple but also quantitative assay that can evaluate antibody levels in patients accurately over time. We have developed an assay that uses a split nanoluciferase fused to the spike or nucleocapsid proteins of the SARS-CoV-2 virus to enable luminescent-based detection of spike- or nucleocapsid-binding antibodies in serum, plasma, and whole blood samples. The resulting approach is simple, rapid, and quantitative and is highly amenable to low-/medium-throughput scale using plate-based assays, high-throughput scale using robotics, and point-of-care applications. In this article, we describe how to perform the assay in a laboratory setting using a plate reader or liquid-handling robotics and in a point-of-care setting using a handheld, battery-powered luminometer. Together, these assays allow antibody detection to be easily performed in multiple settings by simplifying and reducing assay time in a laboratory or clinical environment and by allowing for antibody detection in point-of-care, nonlaboratory settings. © 2022 Wiley Periodicals LLC. Basic Protocol: SARS-CoV-2 antibody detection using the split-luciferase assay on a medium-throughput scale with a laboratory luminometer Alternate Protocol 1: High-throughput-based protocol for SARS-CoV-2 antibody detection using a robotic platform Alternate Protocol 2: Point-of-care-based protocol for SARS-CoV-2 antibody detection using a handheld luminometer Support Protocol: Determining positive/negative cutoffs for test samples and standardizing the assay between days.