Stephen Ryan

We have shown that osteogenic protein-1 (OP-1) (bone morphogenetic protein-7) is responsible for the induction of nephrogenic mesenchyme during embryonic kidney development. Gene knock-out studies showed that OP-1 null mutant mice die of renal failure within the first day of postnatal life. In the present study, we evaluated the effect of recombinant human OP-1 for the treatment of acute renal failure after 60 min bilateral renal artery occlusion in rats. Bioavailability studies in normal rats indicate that approximately 1.4 microg OP-1/ml is available in the circulation 1 min after intravenous administration of 250 microg/kg, which then declines steadily with a half life of 30 min. About 0.5% of the administered OP-1 dose/g tissue is targeted for OP-1 receptors in the kidney. We show that OP-1 preserves kidney function, as determined by reduced blood urea nitrogen and serum creatinine, and increased survival rate when administered 10 min before or 1 or 16 h after ischemia, and then at 24-h intervals up to 72 h after reperfusion. Histochemical and molecular analyses demonstrate that OP-1: (a) minimizes infarction and cell necrosis, and decreases the number of plugged tubules; (b) suppresses inflammation by downregulating the expression of intercellular adhesive molecule, and prevents the accumulation and activity of neutrophils; (c) maintains the expression of the vascular smooth muscle cell phenotype in pericellular capillaries; and (d) reduces programmed cell death during the recovery. Collectively, these data suggest that OP-1 prevents the loss of kidney function associated with ischemic injury and may provide a basis for the treatment of acute renal failure.

Cancer diagnosis and classification are pivotal for effective patient management and treatment planning. In this study, a comprehensive approach is presented utilizing ensemble deep learning techniques to analyze breast cancer histopathology images. Our datasets were based on two widely employed datasets from different centers for two different tasks: BACH and BreakHis. Within the BACH dataset, a proposed ensemble strategy was employed, incorporating VGG16 and ResNet50 architectures to achieve precise classification of breast cancer histopathology images. Introducing a novel image patching technique to preprocess a high-resolution image facilitated a focused analysis of localized regions of interest. The annotated BACH dataset encompassed 400 WSIs across four distinct classes: Normal, Benign, In Situ Carcinoma, and Invasive Carcinoma. In addition, the proposed ensemble was used on the BreakHis dataset, utilizing VGG16, ResNet34, and ResNet50 models to classify microscopic images into eight distinct categories (four benign and four malignant). For both datasets, a five-fold cross-validation approach was employed for rigorous training and testing. Preliminary experimental results indicated a patch classification accuracy of 95.31% (for the BACH dataset) and WSI image classification accuracy of 98.43% (BreakHis). This research significantly contributes to ongoing endeavors in harnessing artificial intelligence to advance breast cancer diagnosis, potentially fostering improved patient outcomes and alleviating healthcare burdens.

Importance: 5α-Reductase inhibitors (5-ARIs), commonly used to treat benign prostatic hyperplasia, reduce serum prostate-specific antigen (PSA) concentrations by 50%. The association of 5-ARIs with detection of prostate cancer in a PSA-screened population remains unclear. Objective: To test the hypothesis that prediagnostic 5-ARI use is associated with a delayed diagnosis, more advanced disease at diagnosis, and higher risk of prostate cancer-specific mortality and all-cause mortality than use of other or no PSA-decreasing drugs. Design, Setting, and Participants: This population-based cohort study linked the Veterans Affairs Informatics and Computing Infrastructure with the National Death Index to obtain patient records for 80 875 men with American Joint Committee on Cancer stage I-IV prostate cancer diagnosed from January 1, 2001, to December 31, 2015. Patients were followed up until death or December 31, 2017. Data analysis was performed from March 2018 to May 2018. Exposures: Prediagnostic 5-ARI use. Main Outcomes and Measures: The primary outcome was prostate cancer-specific mortality (PCSM). Secondary outcomes included time from first elevated PSA (defined as PSA≥4 ng/mL) to diagnostic prostate biopsy, cancer grade and stage at time of diagnosis, and all-cause mortality (ACM). Prostate-specific antigen levels for 5-ARI users were adjusted by doubling the value, consistent with previous clinical trials. Results: Median (interquartile range [IQR]) age at diagnosis was 66 (61-72) years; median [IQR] follow-up was 5.90 (3.50-8.80) years. Median time from first adjusted elevated PSA to diagnosis was significantly greater for 5-ARI users than 5-ARI nonusers (3.60 [95% CI, 1.79-6.09] years vs 1.40 [95% CI, 0.38-3.27] years; P < .001) among patients with known prostate biopsy date. Median adjusted PSA at time of biopsy was significantly higher for 5-ARI users than 5-ARI non-users (13.5 ng/mL vs 6.4 ng/mL; P < .001). Patients treated with 5-ARI were more likely to have Gleason grade 8 or higher (25.2% vs 17.0%; P < .001), clinical stage T3 or higher (4.7% vs 2.9%; P < .001), node-positive (3.0% vs 1.7%; P < .001), and metastatic (6.7% vs 2.9%; P < .001) disease than 5-ARI nonusers. In a multivariable regression, patients who took 5-ARI had higher prostate cancer-specific (subdistribution hazard ratio [SHR], 1.39; 95% CI, 1.27-1.52; P < .001) and all-cause (HR, 1.10; 95% CI, 1.05-1.15; P < .001) mortality. Conclusions and Relevance: Results of this study demonstrate that prediagnostic use of 5-ARIs was associated with delayed diagnosis and worse cancer-specific outcomes in men with prostate cancer. These data highlight a continued need to raise awareness of 5-ARI-induced PSA suppression, establish clear guidelines for early prostate cancer detection, and motivate systems-based practices to facilitate optimal care for men who use 5-ARIs.