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We study a large-scale Brazilian loan subsidy program to expand long-term credit. The government subsidizes banks' funding costs for lenders, who then allocate credit to firms at regulated interest rates below a maximum ceiling. We propose and test a mechanism allowing banks to circumvent the rate caps and capture part of the subsidy. We show that when issuing a subsidized loan, lenders with market power use a cross-product pricing strategy, whereby they increase the price of other products to the same client. Our results have important policy implications for the design and effectiveness of government interventions in credit markets. (JEL G21, H81, E43) [ABSTRACT FROM AUTHOR]

Tumor hypoxia is a negative prognostic factor in many tumors and is predictive of metastatic spread and poor responsiveness to both chemotherapy and radiotherapy. Purpose: To assess the feasibility of using 18F-Fluoroazomycin arabinoside (FAZA) PET/MR to image tumor hypoxia in patients with locally advanced rectal cancer (LARC) prior to and following neoadjuvant chemoradiotherapy (nCRT). The secondary objective was to compare different reference tissues and thresholds for tumor hypoxia quantification. Patients and Methods: Eight patients with histologically proven LARC were included. All patients underwent 18F-FAZA PET/MR prior to initiation of nCRT, four of whom also had a second scan following completion of nCRT and prior to surgery. Tumors were segmented using T2-weighted MR. Each voxel within the segmented tumor was defined as hypoxic or oxic using thresholds derived from various references: ×1.0 or ×1.2 SUVmean of blood pool [BP] or left ventricle [LV] and SUVmean +3SD for gluteus maximus. Correlation coefficient (CoC) between HF and tumor SUVmax/reference SUVmean TRR for the various thresholds was calculated. Hypoxic fraction (HF), defined as the % hypoxic voxels within the tumor volume was calculated for each reference/threshold. Results: For all cases, baseline and follow-up, the CoCs for gluteus maximus and for BP and LV (×1.0) were 0.241, 0.344, and 0.499, respectively, and HFs were (median; range) 16.6% (2.4–33.8), 36.8% (0.3–72.9), and 30.7% (0.8–55.5), respectively. For a threshold of ×1.2, the CoCs for BP and LV as references were 0.611 and 0.838, respectively, and HFs were (median; range) 10.4% (0–47.6), and 4.3% (0–20.1%), respectively. The change in HF following nCRT ranged from (−18.9%) to (+54%). Conclusions: Imaging of hypoxia in LARC with 18F-FAZA PET/MR is feasible. Blood pool as measured in the LV appears to be the most reliable reference for calculating the HF. There is a wide range of HF and variable change in HF before and after nCRT. [ABSTRACT FROM AUTHOR]

We aimed to determine if clinical parameters and radiomics combined with sarcopenia status derived from baseline 18F-FDG-PET/CT could predict developing metastatic disease and overall survival (OS) in gastroesophageal cancer (GEC). Patients referred for primary staging who underwent 18F-FDG-PET/CT from 2008 to 2019 were evaluated retrospectively. Overall, 243 GEC patients (mean age = 64) were enrolled. Clinical, histopathology, and sarcopenia data were obtained, and primary tumor radiomics features were extracted. For classification (early-stage vs. advanced disease), the association of the studied parameters was evaluated. Various clinical and radiomics models were developed and assessed. Accuracy and area under the curve (AUC) were calculated. For OS prediction, univariable and multivariable Cox analyses were performed. The best model included PET/CT radiomics features, clinical data, and sarcopenia score (accuracy = 80%; AUC = 88%). For OS prediction, various clinical, CT, and PET features entered the multivariable analysis. Three clinical factors (advanced disease, age ≥ 70 and ECOG ≥ 2), along with one CT-derived and one PET-derived radiomics feature, retained their significance. Overall, 18F-FDG PET/CT radiomics seems to have a potential added value in identifying GEC patients with advanced disease and may enhance the performance of baseline clinical parameters. These features may also have a prognostic value for OS, improving the decision-making for GEC patients. [ABSTRACT FROM AUTHOR]

Simple Summary: There is a lack of ample knowledge about the origin of anatomical disease- and histology-specific radiomic variations across different malignancies. Thus, the aim of our proof-of-principle study was to investigate whether radiomics features have the ability to discriminate between histological subtypes and to predict the anatomical disease origin of different tumour entities. Also, we tried to synchronously predict histology and anatomical disease origin using baseline [18F]F-FDG PET/CT. Based on our findings, our proof-of-principle study may demonstrate a potentially high degree of diagnostic accuracy to predict histology and disease origin across different tumour entities, using the standard of care combined [18F]F-FDG PET/CT-derived radiomics features. This may help with the development of a new paradigm regarding the potential of also thinking about tumours from their molecular basis, and not only on the basis of their anatomical origin perse. We aimed to investigate whether [18F]F-FDG-PET/CT-derived radiomics can classify histologic subtypes and determine the anatomical origin of various malignancies. In this IRB-approved retrospective study, 391 patients (age = 66.7 ± 11.2) with pulmonary (n = 142), gastroesophageal (n = 128) and head and neck (n = 121) malignancies were included. Image segmentation and feature extraction were performed semi-automatically. Two models (all possible subset regression [APS] and recursive partitioning) were employed to predict histology (squamous cell carcinoma [SCC; n = 219] vs. adenocarcinoma [AC; n = 172]), the anatomical origin, and histology plus anatomical origin. The recursive partitioning algorithm outperformed APS to determine histology (sensitivity 0.90 vs. 0.73; specificity 0.77 vs. 0.65). The recursive partitioning algorithm also revealed good predictive ability regarding anatomical origin. Particularly, pulmonary malignancies were identified with high accuracy (sensitivity 0.93; specificity 0.98). Finally, a model for the synchronous prediction of histology and anatomical disease origin resulted in high accuracy in determining gastroesophageal AC (sensitivity 0.88; specificity 0.92), pulmonary AC (sensitivity 0.89; specificity 0.88) and head and neck SCC (sensitivity 0.91; specificity 0.92). Adding PET-features was associated with marginal incremental value for both the prediction of histology and origin in the APS model. Overall, our study demonstrated a good predictive ability to determine patients' histology and anatomical origin using [18F]F-FDG-PET/CT-derived radiomics features, mainly from CT. [ABSTRACT FROM AUTHOR]

This study aims to determine the variability of the components of fitness along the menstrual cycle (MC) of physically active eumenorrheic women. Fifteen subjects were monitored along two consecutive MCs through the calendar-based counting method in combination with a urine luteinizing hormone surge kit. Subjects were tested at the early follicular phase (EFP), pre-ovulatory or late follicular phase (LFP), and post-ovulatory or mid-luteal phase (MLP). In each session, the back squat one-repetition maximum (1-RM), maximum fat oxidation (MFO), maximum oxygen uptake (VO2max) and acute recovery capacity were determined. The results revealed a wide variability among components of fitness and a low to high variability among subjects (acute recovery: 3.6% [range 1.5 to 9.5%]; back squat 1-RM: 6.1% [range 2.2 to 11%]; VO2max : 6.6% [range 1.1 to 15%]; MFO: 23% [range 4.6 to 35%]). Despite the individual nature, considering the number and magnitude of the responses in each MC phase, VO2max and acute recovery capacity tended to be enhanced at the LFP, the MFO at the MLP, and the back squat 1-RM remained stable along the MC. Thus, practitioners are aware of which components are susceptible to change along the MC phase, but an individual monitoring is recommended. [ABSTRACT FROM AUTHOR]