Compact polymer components for an integrated add-drop multiplexer

A phasar and a digital thermo optic switch have been designed and processed in a high index contrast polymer technology. Both devices are small enough to fabricate two integrated add-drop multiplexers on one 4 inch wafe

Selenoprotein dio2 is a regulator of mitochondrial function, morphology and uprmt in human cardiomyocytes

Members of the fetal-gene-program may act as regulatory components to impede deleterious events occurring with cardiac remodeling, and constitute potential novel therapeutic heart failure (HF) targets. Mitochondrial energy derangements occur both during early fetal development and in patients with HF. Here we aim to elucidate the role of DIO2, a member of the fetal-gene-program, in pluripotent stem cell (PSC)-derived human cardiomyocytes and on mitochondrial dynamics and energetics, specifically. RNA sequencing and pathway enrichment analysis was performed on mouse cardiac tissue at different time points during development, adult age, and ischemia-induced HF. To determine the function of DIO2 in cardiomyocytes, a stable human hPSC-line with a DIO2 knockdown was made using a short harpin sequence. Firstly, we showed the selenoprotein, type II deiodinase (DIO2): the enzyme responsible for the tissue-specific conversion of inactive (T4) into active thyroid hormone (T3), to be a member of the fetal-gene-program. Secondly, silencing DIO2 resulted in an increased reactive oxygen species, impaired activation of the mitochondrial unfolded protein response, severely impaired mitochondrial respiration and reduced cellular viability. Microscopical 3D reconstruction of the mitochondrial network displayed substantial mitochondrial fragmentation. Summarizing, we identified DIO2 to be a member of the fetal-gene-program and as a key regulator of mitochondrial performance in human cardiomyocytes. Our results suggest a key position of human DIO2 as a regulator of mitochondrial function in human cardiomyocytes

No effect of topical digoxin and furosemide for patients with actinic keratosis

Drug Delivery Technolog

⁸⁹Zr-Trastuzumab PET/CT Imaging of HER2-Positive Breast Cancer for Predicting Pathological Complete Response after Neoadjuvant Systemic Therapy:A Feasibility Study

Background: Approximately 20% of invasive ductal breast malignancies are human epidermal growth factor receptor 2 (HER2)-positive. These patients receive neoadjuvant systemic therapy (NAT) including HER2-targeting therapies. Up to 65% of patients achieve a pathological complete response (pCR). These patients might not have needed surgery. However, accurate preoperative identification of a pCR remains challenging. A radiologic complete response (rCR) on MRI corresponds to a pCR in only 73% of patients. The current feasibility study investigates if HER2-targeted PET/CT-imaging using Zirconium-89 (89Zr)-radiolabeled trastuzumab can be used for more accurate NAT response evaluation. Methods: HER2-positive breast cancer patients scheduled to undergo NAT and subsequent surgery received a 89Zr-trastuzumab PET/CT both before (PET/CT-1) and after (PET/CT-2) NAT. Qualitative and quantitative response evaluation was performed. Results: Six patients were enrolled. All primary tumors could be identified on PET/CT-1. Four patients had a pCR and two a pathological partial response (pPR) in the primary tumor. Qualitative assessment of PET/CT resulted in an accuracy of 66.7%, compared to 83.3% of the standard-of-care MRI. Quantitative assessment showed a difference between the SUVR on PET/CT-1 and PET/CT-2 (ΔSUVR) in patients with a pPR and pCR of −48% and −90% (p = 0.133), respectively. The difference in tumor-to-blood ratio on PET/CT-1 and PET/CT-2 (ΔTBR) in patients with pPR and pCR was −79% and −94% (p = 0.133), respectively. Three patients had metastatic lymph nodes at diagnosis that were all identified on PET/CT-1. All three patients achieved a nodal pCR. Qualitative assessment of the lymph nodes with PET/CT resulted in an accuracy of 66.7%, compared to 50% of the MRI. Conclusions: NAT response evaluation using 89Zr-trastuzumab PET/CT is feasible. In the current study, qualitative assessment of the PET/CT images is not superior to standard-of-care MRI. Our results suggest that quantitative assessment of 89Zr-trastuzumab PET/CT has potential for a more accurate response evaluation of the primary tumor after NAT in HER2-positive breast cancer.</p

Cross-cohort generalizability of deep and conventional machine learning for MRI-based diagnosis and prediction of Alzheimer's disease

This work validates the generalizability of MRI-based classification of Alzheimer’s disease (AD) patients and controls (CN) to an external data set and to the task of prediction of conversion to AD in individuals with mild cognitive impairment (MCI).We used a conventional support vector machine (SVM) and a deep convolutional neural network (CNN) approach based on structural MRI scans that underwent either minimal pre-processing or more extensive pre-processing into modulated gray matter (GM) maps. Classifiers were optimized and evaluated using cross-validation in the Alzheimer’s Disease Neuroimaging Initiative (ADNI; 334 AD, 520 CN). Trained classifiers were subsequently applied to predict conversion to AD in ADNI MCI patients (231 converters, 628 non-converters) and in the independent Health-RI Parelsnoer Neurodegenerative Diseases Biobank data set. From this multi-center study representing a tertiary memory clinic population, we included 199 AD patients, 139 participants with subjective cognitive decline, 48 MCI patients converting to dementia, and 91 MCI patients who did not convert to dementia.AD-CN classification based on modulated GM maps resulted in a similar area-under-the-curve (AUC) for SVM (0.940; 95%CI: 0.924–0.955) and CNN (0.933; 95%CI: 0.918–0.948). Application to conversion prediction in MCI yielded significantly higher performance for SVM (AUC = 0.756; 95%CI: 0.720-0.788) than for CNN (AUC = 0.742; 95%CI: 0.709-0.776) (p<0.01 for McNemar’s test). In external validation, performance was slightly decreased. For AD-CN, it again gave similar AUCs for SVM (0.896; 95%CI: 0.855–0.932) and CNN (0.876; 95%CI: 0.836–0.913). For prediction in MCI, performances decreased for both SVM (AUC = 0.665; 95%CI: 0.576-0.760) and CNN (AUC = 0.702; 95%CI: 0.624-0.786). Both with SVM and CNN, classification based on modulated GM maps significantly outperformed classification based on minimally processed images (p=0.01).Deep and conventional classifiers performed equally well for AD classification and their performance decreased only slightly when applied to the external cohort. We expect that this work on external validation contributes towards translation of machine learning to clinical practice

CEA, EpCAM, alpha v beta 6 and uPAR expression in rectal cancer patients with a pathological complete response after neoadjuvant therapy

Rectal cancer patients with a complete response after neoadjuvant therapy can be monitored with a watch-and-wait strategy. However, regrowth rates indicate that identification of patients with a pathological complete response (pCR) remains challenging. Targeted near-infrared fluorescence endoscopy is a potential tool to improve response evaluation. Promising tumor targets include carcinoembryonic antigen (CEA), epithelial cell adhesion molecule (EpCAM), integrin alpha v beta 6, and urokinase-type plasminogen activator receptor (uPAR). To investigate the applicability of these targets, we analyzed protein expression by immunohistochemistry and quantified these by a total immunostaining score (TIS) in tissue of rectal cancer patients with a pCR. CEA, EpCAM, alpha v beta 6, and uPAR expression in the diagnostic biopsy was high (TIS > 6) in, respectively, 100%, 100%, 33%, and 46% of cases. CEA and EpCAM expressions were significantly higher in the diagnostic biopsy compared with the corresponding tumor bed (p < 0.01). CEA, EpCAM, alpha v beta 6, and uPAR expressions were low (TIS < 6) in the tumor bed in, respectively, 93%, 95%, 85%, and 62.5% of cases. Immunohistochemical evaluation shows that CEA and EpCAM could be suitable targets for response evaluation after neoadjuvant treatment, since expression of these targets in the primary tumor bed is low compared with the diagnostic biopsy and adjacent pre-existent rectal mucosa in more than 90% of patients with a pCR.Surgical oncolog