Prediction of the Values of CRP, eGFR, and Hemoglobin in the Follow-Up of Renal Cell Carcinoma Patients after (Cryo)Surgery Using Machine Learning Algorithms.

BACKGROUND: Artificial intelligence can support clinical decisions by predictive modeling. Using patient-specific characteristics, models may predict the course of clinical parameters, thus guiding monitoring approaches for the individual patient. Here, we present prediction models for inflammation and for the course of renal function and hemoglobin (Hb) in renal cell carcinoma patients after (cryo)surgery. METHODS: Using random forest machine learning in a longitudinal value-based healthcare data set (n = 86) of renal cell carcinoma patients, prediction models were established and optimized using random and grid searches. Data were split into a training and test set in a 70:30 ratio. Inflammation was predicted for a single timepoint, whereas for renal function estimated glomerular filtration rate (eGFR) and Hb time course prediction was performed. RESULTS: Whereas the last Hb and eGFR values before (cryo)surgery were the main basis for the course of Hb and renal function, age and several time frame features also contributed significantly. For eGFR, the type of (cryo)surgery was also a main predicting feature, and for Hb, tumor location, and body mass index were important predictors. With regard to prediction of inflammation no feature was markedly prominent. Inflammation prediction was based on a combination of patient characteristics, physiological parameters, and time frame features. CONCLUSIONS: This study provided interesting insights into factors influencing complications and recovery in individual renal cell carcinoma patients. The established prediction models provide the basis for development of clinical decision support tools for selection and timing of laboratory analyses after (cryo)surgery, thus contributing to quality and efficiency of care.

Classical risk factors for primary coronary artery disease from an aging perspective through Mendelian Randomization.

The significance of classical risk factors in coronary artery disease (CAD) remains unclear in older age due to possible changes in underlying disease pathologies. Therefore, we conducted Mendelian Randomization approaches to investigate the causal relationship between classical risk factors and primary CAD in different age groups. A Mendelian Randomization study was conducted in European-ethnicity individuals from the UK Biobank population. Analyses were performed using data of 22,313 CAD cases (71.6% men) and 407,920 controls (44.5% men). Using logistic regression analyses, we investigated the associations between standardized genetic risk score and primary CAD stratified by age of diagnosis. In addition, feature importance and model accuracy were assessed in different age groups to evaluate predictive power of the genetic risk scores with increasing age. We found age-dependent associations for all classical CAD risk factors. Notably, body mass index (OR 1.22 diagnosis < 50 years; OR 1.02 diagnosis > 70 years), blood pressure (OR 1.12 < 50 years; OR 1.04 > 70 years), LDL cholesterol (OR 1.16 < 50 years; OR 1.02 > 70 years), and triglyceride levels (OR 1.11 < 50 years; 1.04 > 70 years). In line with the Mendelian Randomization analyses, model accuracy and feature importance of the classical risk factors decreased with increasing age of diagnosis. Causal determinants for primary CAD are age dependent with classical CAD risk factors attenuating in relation with primary CAD with increasing age. These results question the need for (some) currently applied cardiovascular disease risk reducing interventions at older age.

Real-time observation of tetrapyrrole binding to an engineered bacterial phytochrome.

Near-infrared fluorescent proteins (NIR FPs) engineered from bacterial phytochromes are widely used for structural and functional deep-tissue imaging in vivo. To fluoresce, NIR FPs covalently bind a chromophore, such as biliverdin IXa tetrapyrrole. The efficiency of biliverdin binding directly affects the fluorescence properties, rendering understanding of its molecular mechanism of major importance. miRFP proteins constitute a family of bright monomeric NIR FPs that comprise a Per-ARNT-Sim (PAS) and cGMP-specific phosphodiesterases - Adenylyl cyclases - FhlA (GAF) domain. Here, we structurally analyze biliverdin binding to miRFPs in real time using time-resolved stimulated Raman spectroscopy and quantum mechanics/molecular mechanics (QM/MM) calculations. Biliverdin undergoes isomerization, localization to its binding pocket, and pyrrolenine nitrogen protonation in <1 min, followed by hydrogen bond rearrangement in ~2 min. The covalent attachment to a cysteine in the GAF domain was detected in 4.3 min and 19 min in miRFP670 and its C20A mutant, respectively. In miRFP670, a second C-S covalent bond formation to a cysteine in the PAS domain occurred in 14 min, providing a rigid tetrapyrrole structure with high brightness. Our findings provide insights for the rational design of NIR FPs and a novel method to assess cofactor binding to light-sensitive proteins.

Real-time observation of tetrapyrrole binding to an engineered bacterial phytochrome.

Near-infrared fluorescent proteins (NIR FPs) engineered from bacterial phytochromes are widely used for structural and functional deep-tissue imaging in vivo. To fluoresce, NIR FPs covalently bind a chromophore, such as biliverdin IXa tetrapyrrole. The efficiency of biliverdin binding directly affects the fluorescence properties, rendering understanding of its molecular mechanism of major importance. miRFP proteins constitute a family of bright monomeric NIR FPs that comprise a Per-ARNT-Sim (PAS) and cGMP-specific phosphodiesterases - Adenylyl cyclases - FhlA (GAF) domain. Here, we structurally analyze biliverdin binding to miRFPs in real time using time-resolved stimulated Raman spectroscopy and quantum mechanics/molecular mechanics (QM/MM) calculations. Biliverdin undergoes isomerization, localization to its binding pocket, and pyrrolenine nitrogen protonation in <1 min, followed by hydrogen bond rearrangement in ~2 min. The covalent attachment to a cysteine in the GAF domain was detected in 4.3 min and 19 min in miRFP670 and its C20A mutant, respectively. In miRFP670, a second C-S covalent bond formation to a cysteine in the PAS domain occurred in 14 min, providing a rigid tetrapyrrole structure with high brightness. Our findings provide insights for the rational design of NIR FPs and a novel method to assess cofactor binding to light-sensitive proteins.