Albuminuria-lowering effect of dapagliflozin, exenatide, and their combination in patients with type 2 diabetes: A randomized cross-over clinical study.

AIM: To evaluate the albuminuria-lowering effect of dapagliflozin, exenatide, and the combination of dapagliflozin and exenatide in patients with type 2 diabetes and microalbuminuria or macroalbuminuria. METHODS: Participants with type 2 diabetes, an estimated glomerular filtration rate (eGFR) of more than 30 ml/min/1.73m2 and an urinary albumin: creatinine ratio (UACR) of more than 3.5 mg/mmol and 100 mg/mmol or less completed three 6-week treatment periods, during which dapagliflozin 10 mg/d, exenatide 2 mg/wk and both drugs combined were given in random order. The primary outcome was the percentage change in UACR. Secondary outcomes included blood pressure, HbA1c, body weight, extracellular volume, fractional lithium excretion and renal haemodynamic variables as determined by magnetic resonance imaging. RESULTS: We enrolled 20 patients, who completed 53 treatment periods in total. Mean percentage change in UACR from baseline was -21.9% (95% CI: -34.8% to -6.4%) during dapagliflozin versus -7.7% (95% CI: -23.5% to 11.2%) during exenatide and -26.0% (95% CI: -38.4% to -11.0%) during dapagliflozin-exenatide treatment. No correlation was observed in albuminuria responses between the different treatments. Numerically greater reductions in systolic blood pressure, body weight and eGFR were observed during dapagliflozin-exenatide treatment compared with dapagliflozin or exenatide alone. Renal blood flow and effective renal plasma flow (ERPF) did not significantly change with either treatment regimen. However, all but four and two patients in the dapagliflozin and dapagliflozin-exenatide groups, respectively, showed reductions in ERPF. The filtration fraction did not change during treatment with dapagliflozin or exenatide, and decreased during dapagliflozin-exenatide treatment (-1.6% [95% CI: -3.2% to -0.01%]; P = .048). CONCLUSIONS: In participants with type 2 diabetes and albuminuria, treatment with dapagliflozin, exenatide and dapagliflozin-exenatide reduced albuminuria, with a numerically larger reduction in the combined dapagliflozin-exenatide treatment group.

Multimodal AI Combining Clinical and Imaging Inputs Improves Prostate Cancer Detection.

OBJECTIVES: Deep learning (DL) studies for the detection of clinically significant prostate cancer (csPCa) on magnetic resonance imaging (MRI) often overlook potentially relevant clinical parameters such as prostate-specific antigen, prostate volume, and age. This study explored the integration of clinical parameters and MRI-based DL to enhance diagnostic accuracy for csPCa on MRI. MATERIALS AND METHODS: We retrospectively analyzed 932 biparametric prostate MRI examinations performed for suspected csPCa (ISUP ≥2) at 2 institutions. Each MRI scan was automatically analyzed by a previously developed DL model to detect and segment csPCa lesions. Three sets of features were extracted: DL lesion suspicion levels, clinical parameters (prostate-specific antigen, prostate volume, age), and MRI-based lesion volumes for all DL-detected lesions. Six multimodal artificial intelligence (AI) classifiers were trained for each combination of feature sets, employing both early (feature-level) and late (decision-level) information fusion methods. The diagnostic performance of each model was tested internally on 20% of center 1 data and externally on center 2 data (n = 529). Receiver operating characteristic comparisons determined the optimal feature combination and information fusion method and assessed the benefit of multimodal versus unimodal analysis. The optimal model performance was compared with a radiologist using PI-RADS. RESULTS: Internally, the multimodal AI integrating DL suspicion levels with clinical features via early fusion achieved the highest performance. Externally, it surpassed baselines using clinical parameters (0.77 vs 0.67 area under the curve [AUC], P < 0.001) and DL suspicion levels alone (AUC: 0.77 vs 0.70, P = 0.006). Early fusion outperformed late fusion in external data (0.77 vs 0.73 AUC, P = 0.005). No significant performance gaps were observed between multimodal AI and radiologist assessments (internal: 0.87 vs 0.88 AUC; external: 0.77 vs 0.75 AUC, both P > 0.05). CONCLUSIONS: Multimodal AI (combining DL suspicion levels and clinical parameters) outperforms clinical and MRI-only AI for csPCa detection. Early information fusion enhanced AI robustness in our multicenter setting. Incorporating lesion volumes did not enhance diagnostic efficacy.

The neutrophil: the unnoticed threat in xenotransplantation?

BACKGROUND: Xenotransplantation offers one way to circumvent the widening gap between the demand for and supply of human organs for transplantation, and the pig is widely regarded as the donor animal most likely to prove appropriate. Most attention has focused on the adaptive immune response to xenogeneic tissue. However, there is optimism that it may soon be possible to overcome that hurdle. In this paper, we consider the possibility of the direct recognition of xenogeneic tissue by neutrophils. METHODS: We studied in vitro the interaction of human neutrophils with cultured porcine endothelial cells in assays of adhesion (both static and flow), activation on the basis of chemiluminescence, and diapedesis and chemotaxis using split-well chambers. RESULTS: Human neutrophils showed increased adhesiveness to porcine endothelium in both static and flow adhesion systems. While this did not activate the neutrophils at rest, in the presence of suboptimal concentrations of a parallel stimulus, phorbol myristate acetate, the interaction of human neutrophils with porcine endothelium caused a much greater respiratory burst than their interaction with controls. In addition, they showed greater diapedesis through porcine endothelium. Of greatest interest is the observation that porcine endothelium secretes a molecule that is chemotactic for human neutrophils. CONCLUSIONS: On the basis of these observations, we should consider the potential for neutrophil-mediated low-grade damage to xenografts emerging as a significant problem when others have been circumvented.