The Effects of Skin Lesion Segmentation on the Performance of Dermatoscopic Image Classification

Malignant melanoma (MM) is one of the deadliest types of skin cancer. Analysing dermatoscopic images plays an important role in the early detection of MM and other pigmented skin lesions. Among different computer-based methods, deep learning-based approaches and in particular convolutional neural networks have shown excellent classification and segmentation performances for dermatoscopic skin lesion images. These models can be trained end-to-end without requiring any hand-crafted features. However, the effect of using lesion segmentation information on classification performance has remained an open question. In this study, we explicitly investigated the impact of using skin lesion segmentation masks on the performance of dermatoscopic image classification. To do this, first, we developed a baseline classifier as the reference model without using any segmentation masks. Then, we used either manually or automatically created segmentation masks in both training and test phases in different scenarios and investigated the classification performances. Evaluated on the ISIC 2017 challenge dataset which contained two binary classification tasks (i.e. MM vs. all and seborrheic keratosis (SK) vs. all) and based on the derived area under the receiver operating characteristic curve scores, we observed four main outcomes. Our results show that 1) using segmentation masks did not significantly improve the MM classification performance in any scenario, 2) in one of the scenarios (using segmentation masks for dilated cropping), SK classification performance was significantly improved, 3) removing all background information by the segmentation masks significantly degraded the overall classification performance, and 4) in case of using the appropriate scenario (using segmentation for dilated cropping), there is no significant difference of using manually or automatically created segmentation masks.Comment: Accepted to the Computer Methods and Programs in Biomedicine journa

Mitophagy-associated genes PINK1 and PARK2 are independent prognostic markers of survival in papillary renal cell carcinoma and associated with aggressive tumor behavior

Abstract The aim of this study was to investigate the mitophagy-related genes PINK1 and PARK2 in papillary renal cell carcinoma and their association with prognosis. In silico data of PINK1 and PARK2 were analyzed in TCGA cohorts of papillary renal cell carcinoma comprising 290 tumors and 33 corresponding non-neoplastic renal tissues. Protein expression data from a cohort of 95 papillary renal cell carcinoma patients were analyzed and associated with clinical-pathological parameters including survival. PINK1 and PARK2 were significantly downregulated in papillary renal cell carcinoma at transcript and protein levels. Reduced transcript levels of PINK1 and PARK2 were negatively associated with overall survival (p < 0.05). At the protein level, PARK2 and PINK1 expression were positively correlated (correlation coefficient 0.286, p = 0.04) and reduced PINK1 protein expression was prognostic for shorter survival. Lower PINK1 protein levels were found in tumors with metastases at presentation and in tumors of higher pT-stages. The multivariate analysis revealed mRNA expression of PINK1 and PARK2 as well as PINK1 protein expression as independent prognostic factors for shorter overall survival. The downregulation of PINK1 is a strong predictor of poor survival in papillary renal cell carcinoma. Immunohistochemical PINK1 expression in resected pRCC should be considered as an additional prognostic marker for routine practice

Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations

Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of pharmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity

Irinotecan and temozolomide in combination with dasatinib and rapamycin versus irinotecan and temozolomide for patients with relapsed or refractory neuroblastoma (RIST-rNB-2011): a multicentre, open-label, randomised, controlled, phase 2 trial

Background Neuroblastoma is the most common extracranial solid tumour in children. Relapsed or refractory neuroblastoma is associated with a poor outcome. We assessed the combination of irinotecan–temozolomide and dasatinib–rapamycin (RIST) in patients with relapsed or refractory neuroblastoma. Methods The multicentre, open-label, randomised, controlled, phase 2, RIST-rNB-2011 trial recruited from 40 paediatric oncology centres in Germany and Austria. Patients aged 1–25 years with high-risk relapsed (defined as recurrence of all stage IV and MYCN amplification stages, after response to treatment) or refractory (progressive disease during primary treatment) neuroblastoma, with Lansky and Karnofsky performance status at least 50%, were assigned (1:1) to RIST (RIST group) or irinotecan–temozolomide (control group) by block randomisation, stratified by MYCN status. We compared RIST (oral rapamycin [loading 3 mg/m2 on day 1, maintenance 1 mg/m2 on days 2–4] and oral dasatinib [2 mg/kg per day] for 4 days with 3 days off, followed by intravenous irinotecan [50 mg/m2 per day] and oral temozolomide [150 mg/m2 per day] for 5 days with 2 days off; one course each of rapamycin–dasatinib and irinotecan–temozolomide for four cycles over 8 weeks, then two courses of rapamycin–dasatinib followed by one course of irinotecan–temozolomide for 12 weeks) with irinotecan–temozolomide alone (with identical dosing as experimental group). The primary endpoint of progression-free survival was analysed in all eligible patients who received at least one course of therapy. The safety population consisted of all patients who received at least one course of therapy and had at least one post-baseline safety assessment. This trial is registered at ClinicalTrials.gov, NCT01467986, and is closed to accrual. Findings Between Aug 26, 2013, and Sept 21, 2020, 129 patients were randomly assigned to the RIST group (n=63) or control group (n=66). Median age was 5·4 years (IQR 3·7–8·1). 124 patients (78 [63%] male and 46 [37%] female) were included in the efficacy analysis. At a median follow-up of 72 months (IQR 31–88), the median progression-free survival was 11 months (95% CI 7–17) in the RIST group and 5 months (2–8) in the control group (hazard ratio 0·62, one-sided 90% CI 0·81; p=0·019). Median progression-free survival in patients with amplified MYCN (n=48) was 6 months (95% CI 4–24) in the RIST group versus 2 months (2–5) in the control group (HR 0·45 [95% CI 0·24-0·84], p=0·012); median progression-free survival in patients without amplified MYCN (n=76) was 14 months (95% CI 9–7) in the RIST group versus 8 months (4–15) in the control group (HR 0·84 [95% CI 0·51–1·38], p=0·49). The most common grade 3 or worse adverse events were neutropenia (54 [81%] of 67 patients given RIST vs 49 [82%] of 60 patients given control), thrombocytopenia (45 [67%] vs 41 [68%]), and anaemia (39 [58%] vs 38 [63%]). Nine serious treatment-related adverse events were reported (five patients given control and four patients given RIST). There were no treatment-related deaths in the control group and one in the RIST group (multiorgan failure). Interpretation RIST-rNB-2011 demonstrated that targeting of MYCN-amplified relapsed or refractory neuroblastoma with a pathway-directed metronomic combination of a multkinase inhibitor and an mTOR inhibitor can improve progression-free survival and overall survival. This exclusive efficacy in MYCN-amplified, relapsed neuroblastoma warrants further investigation in the first-line setting. Funding Deutsche Krebshilfe

Design and Performance of the mDOM Mainboard for the IceCube Upgrade

About 400 mDOMs (multi-PMT Digital Optical Modules) will be deployed as part of the IceCube Upgrade Project. The mDOM’s high pressure-resistant glass sphere houses 24 PMTs, 3 cameras, 10 flasher LEDs and various sensors. The mDOM mainboard design was challenging due to the limited available volume and demanding engineering requirements, like the maximum overall power consumption, a minimum trigger threshold of 0.2 photoelectrons (PE), the dynamic range and the linearity requirements. Another challenge was the FPGA firmware design, dealing with about 35 Gbit/s of continuous ADC data from the digitization of the 24 PMT channels, the control of a high speed dynamic buffer and the discriminator output sampling rate of about 1GSPS. High-speed sampling of each of the discriminator outputs at ~1 GSPS improves the leading-edge time resolution for the PMT waveforms. An MCU (microcontroller unit) coordinates the data taking, the data exchange with the surface and the sensor readout. Both the FPGA firmware and MCU software can be updated remotely. After discussing the main hardware blocks and the analog frontend (AFE) design, test results will be shown, covering especially the AFE performance. Additionally, the functionality of various sensors and modules will be evaluated

Searching for IceCube sub-TeV neutrino counterparts to sub-threshold Gravitational Wave events

Since the release of the Gravitational Wave Transient Catalogue GWTC-2.1 by the LIGO-Virgo collaboration, sub-threshold gravitational wave (GW) candidates are publicly available. They are expected to be released in real-time as well, in the upcoming O4 run. Using these GW candidates for multi-messenger studies complement the ongoing efforts to identify neutrino counterparts to GW events. This in turn, allows us to schedule electromagnetic follow-up searches more efficiently. However, the definition and criteria for sub-threshold candidates are pretty flexible. Finding a multi-messenger counterpart via archival studies for these candidates will help to set up strong bounds on the GW parameters which are useful for defining a GW signal as sub-threshold, thereby increasing their significance for scheduling follow-up searches. Here, we present the current status of this ongoing work with the IceCube Neutrino Observatory. We perform a selection of the sub-threshold GW candidates from GWTC-2.1 and conduct an archival search for sub-TeV neutrino counterparts detected by the dense infill array of the IceCube Neutrino Observatory, known as "DeepCore". For this, an Unbinned Maximum Likelihood (UML) method is used. We report the 90% C.L. sensitivities of this sub-TeV neutrino dataset for each selected sub-threshold GW candidate, considering the spatial and temporal correlation between the GW and neutrino events within a 1000 s time window

Estimating the coincidence rate between the optical and radio array of IceCube-Gen2

The IceCube-Gen2 Neutrino Observatory is proposed to extend the all-flavour energy range of IceCube beyond PeV energies. It will comprise two key components: I) An enlarged 8km3 in-ice optical Cherenkov array to measure the continuation of the IceCube astrophysical neutrino flux and improve IceCube\u27s point source sensitivity above ∼100TeV; and II) A very large in-ice radio array with a surface area of about 500km2. Radio waves propagate through ice with a kilometer-long attenuation length, hence a sparse radio array allows us to instrument a huge volume of ice to achieve a sufficient sensitivity to detect neutrinos with energies above tens of PeV. The different signal topologies for neutrino-induced events measured by the optical and in-ice radio detector - the radio detector is mostly sensitive to the cascades produced in the neutrino interaction, while the optical detector can detect long-ranging muon and tau leptons with high accuracy - yield highly complementary information. When detected in coincidence, these signals will allow us to reconstruct the neutrino energy and arrival direction with high fidelity. Furthermore, if events are detected in coincidence with a sufficient rate, they resemble the unique opportunity to study systematic uncertainties and to cross-calibrate both detector components