Explore the vast range of titles available.

Background Ganglioneuroma (GN) and ganglioneuroblastoma intermixed (GNBI) are mature variants of neuroblastic tumors (NT). It is still discussed whether incomplete resection of GN/GNBI impairs the outcome of patients. Methods Clinical characteristics and outcome of localized GN/GNBI were retrospectively compared to localized neuroblastoma (NB) and ganglioneuroblastoma-nodular (GNBN) registered in the German neuroblastoma trials between 2000 and 2010. Results Of 808 consecutive localized NT, 162 (20 %) were classified as GN and 55 (7 %) as GNBI. GN/GNBI patients presented more often with stage 1 disease (68 % vs. 37 %, p < 0.001), less frequently with adrenal tumors (31 % vs. 43 %, p = 0.001) and positive mIBG-uptake (34 % vs. 90 %, p < 0.001), and had less often elevated urine catecholamine metabolites (homovanillic acid 39 % vs. 62 %, p < 0.001, vanillylmandelic acid 27 % vs. 64 %, p < 0.001). Median age at diagnosis increased with grade of differentiation (NB/GNBN: 9; GNBI: 61; GN-maturing: 71; GN-mature: 125 months, p < 0.001). Complete tumor resection was achieved at diagnosis in 70 % of 162 GN and 67 % of 55 GNBI, and after 4 to 32 months of observation in 4 GN (2 %) and 5 GNBI (9 %). Eleven patients received chemotherapy without substantial effect. Fifty-five residual tumors (42 GN, 13 GNBI) are currently under observation (median: 44 months). Five patients (3 GN, 2 GNBI) showed local progression; all had tumor residuals > 2 cm. No progression occurred after subtotal resection. Two patients died of treatment, none of tumor progression. Conclusions GN/GNBI account for one quarter of localized NT and differ from immature tumors in their clinical features. Chemotherapy is not effective. Subtotal resection appears to be a sufficient treatment. Trial registration ClinicalTrials.gov identifiers - NB97 (NCT00017225; registered June 6, 2001); NB2004 (NCT00410631; registered December 11, 2006)

In many areas of psychology, correlation-based network approaches (i.e., psychometric networks) have become a popular tool. In this paper, we propose an approach that recursively splits the sample based on covariates in order to detect significant differences in the structure of the covariance or correlation matrix. Psychometric networks or other correlation-based models (e.g., factor models) can be subsequently estimated from the resultant splits. We adapt model-based recursive partitioning and conditional inference tree approaches for finding covariate splits in a recursive manner. The empirical power of these approaches is studied in several simulation conditions. Examples are given using real-life data from personality and clinical research.

Background Although several studies have been conducted on the role of surgery in localized neuroblastoma, the impact of surgical timing and extent of primary tumor resection on outcome in high-risk patients remains controversial. Methods Patients from the German neuroblastoma trial NB97 with localized neuroblastoma INSS stage 1–3 age > 18 months were included for retrospective analysis. Imaging reports were reviewed by two independent physicians for Image Defined Risk Factors (IDRF). Operation notes and corresponding imaging reports were analyzed for surgical radicality. The extent of tumor resection was classified as complete resection (95–100%), gross total resection (90–95%), incomplete resection (50–90%), and biopsy (<50%) and correlated with local control rate and outcome. Patients were stratified according to the International Neuroblastoma Risk Group (INRG) staging system. Survival curves were estimated according to the method of Kaplan and Meier and compared by the log-rank test. Results A total of 179 patients were included in this study. 77 patients underwent more than one primary tumor operation. After best surgery, 68.7% of patients achieved complete resection of the primary tumor, 16.8% gross total resection, 14.0% incomplete surgery, and 0.5% biopsy only. The cumulative complication rate was 20.3% and the surgery associated mortality rate was 1.1%. Image defined risk factors (IDRF) predicted the extent of resection. Patients with complete resection had a better local-progression-free survival (LPFS), event-free survival (EFS) and OS (overall survival) than the other groups. Subgroup analyses showed better EFS, LPFS and OS for patients with complete resection in INRG high-risk patients. Multivariable analyses revealed resection (complete vs. other), and MYCN (non-amplified vs. amplified) as independent prognostic factors for EFS, LPFS and OS. Conclusions In patients with localized neuroblastoma age 18 months or older, especially in INRG high-risk patients harboring MYCN amplification, extended surgery of the primary tumor site improved local control rate and survival with an acceptable risk of complications.

The majority of patients with neuroblastoma due to MYCN oncogene amplification and consequent N-Myc oncoprotein over-expression die of the disease. Here our analyses of RNA sequencing data identify the long noncoding RNA lncNB1 as one of the transcripts most over-expressed in MYCN -amplified, compared with MYCN -non-amplified, human neuroblastoma cells and also the most over-expressed in neuroblastoma compared with all other cancers. lncNB1 binds to the ribosomal protein RPL35 to enhance E2F1 protein synthesis, leading to DEPDC1B gene transcription. The GTPase-activating protein DEPDC1B induces ERK protein phosphorylation and N-Myc protein stabilization. Importantly, lncNB1 knockdown abolishes neuroblastoma cell clonogenic capacity in vitro and leads to neuroblastoma tumor regression in mice, while high levels of lncNB1 and RPL35 in human neuroblastoma tissues predict poor patient prognosis. This study therefore identifies lncNB1 and its binding protein RPL35 as key factors for promoting E2F1 protein synthesis, N-Myc protein stability and N-Myc-driven oncogenesis, and as therapeutic targets. MYCN amplification is common in neuroblastomas. Here, the authors identify a long noncoding RNA, lncNB1 in these cancers and show that it promotes tumorigenesis by binding to ribosomal protein, RPL35 to enhance E2F1 and DEPDC1B protein synthesis, which phosphorylates ERK to stabilise N-Myc.

Physical numerical weather prediction models have biases and miscalibrations that can depend on the weather situation, which makes it difficult to post-process them effectively using the traditional model output statistics (MOS) framework based on parametric regression models. Consequently, much recent work has focused on using flexible machine learning methods that are able to take additional weather-related predictors into account during post-processing beyond the forecast of the variable of interest only. Some of these methods have achieved impressive results, but they typically require significantly more training data than traditional MOS and are less straightforward to implement and interpret. We propose MOS random forests, a new post-processing method that avoids these problems by fusing traditional MOS with a powerful machine learning method called random forests to estimate weather-adapted MOS coefficients from a set of predictors. Since the assumed parametric base model contains valuable prior knowledge, much smaller training data sizes are required to obtain skillful forecasts, and model results are easy to interpret. MOS random forests are straightforward to implement and typically work well, even with no or very little hyperparameter tuning. For the difficult task of post-processing daily precipitation sums in complex terrain, they outperform reference machine learning methods at most of the stations considered. Additionally, the method is highly robust in relation to changes in data size and works well even when less than 100 observations are available for training.

Background Long‐term childhood cancer survivors (CCS) may develop anthracycline‐induced cardiomyopathy. Our cross‐sectional study focused on the question of whether a central echocardiographic reference assessment is associated with a higher detection rate of cardiac dysfunction in a population‐based cohort of affected children with neuroblastoma or nephroblastoma. We also examined the prevalence of anthracycline‐induced cardiomyopathy and its risk factors. Methods and Patients The cohort of this subproject comprises 370 nephroblastoma or neuroblastoma survivors diagnosed with cancer between 1990 and 2012. At study entry, participants were younger than 18 years old, had been treated with anthracyclines, and had no documented previous cardiac disease. Data were collected via patient questionnaires, cardiologic examinations in the network of adults with congenital heart defects (Erwachsene mit angeborenem Herzfehler [EMAH]) and a reference assessment of the recorded echocardiography. Results The prevalence of cardiomyopathy in the study cohort (mean age: 12 years) was 6.3% at a median of 9.1 years after initial cancer diagnosis. Risk factors were an age under 5 years at tumor diagnosis and concomitant treatment with cyclophosphamide or radiation. As a central and novel finding, the detection rates by the EMAH cardiologists and the reference center are similarly high but discrepant. Discussion Limitations were mainly due to the low responder rate and incomplete data. This study established a nationwide competence network linking pediatric oncology and cardiology centers across six university hospitals in Germany, enabling data collection on pediatric CCS. Despite lower case numbers compared to adult CCS cohorts, meaningful data were gathered and analyzed. Conclusion Cardiac late effects after anthracycline‐based therapy in childhood affect a relevant proportion of long‐term CCS at pediatric age. In order to enable timely diagnosis and treatment, preventive examinations are essential and might benefit from additional central reference assessments. Discrepancy in detection of cardiomyopathy by reference and EMAH cardiologists requires further investigation.

Background The treatment of high-risk neuroblastoma patients consists of multimodal induction therapy to achieve remission followed by consolidation therapy to prevent relapses. However, the type of consolidation therapy is still discussed controversial. We applied metronomic chemotherapy in the prospective NB90 trial and monoclonal anti-GD2-antibody (MAB) ch14.18 in the NB97 trial. Here, we present the long term outcome data of the patient cohort. Methods A total of 334 stage 4 neuroblastoma patients one year or older were included. All patients successfully completed the induction therapy. In the NB90 trial, 99 patients received at least one cycle of the oral maintenance chemotherapy (NB90 MT, 12 alternating cycles of oral melphalan/etoposide and vincristine/cyclophosphamide). In the NB97 trial, 166 patients commenced the MAB ch14.18 consolidation therapy (six cycles over 12 months). Patients who received no maintenance therapy according to the NB90 protocol or by refusal in NB97 (n = 69) served as controls. Results The median observation time was 11.11 years. The nine-year event-free survival rates were 41 ± 4%, 31 ± 5%, and 32 ± 6% for MAB ch14.18, NB90 MT, and no consolidation, respectively (p = 0.098). In contrast to earlier reports, MAB ch14.18 treatment improved the long-term outcome compared to no additional therapy (p = 0.038). The overall survival was better in the MAB ch14.18-treated group (9-y-OS 46 ± 4%) compared to NB90 MT (34 ± 5%, p = 0.026) and to no consolidation (35 ± 6%, p = 0.019). Multivariable Cox regression analysis revealed ch14.18 consolidation to improve outcome compared to no consolidation, however, no difference between NB90 MT and MAB ch14.18-treated patients was found. Conclusions Follow-up analysis of the patient cohort indicated that immunotherapy with MAB ch14.18 may prevent late relapses. Finally, metronomic oral maintenance chemotherapy also appeared effective.

Background Telomere maintenance mechanisms (TMM) are a hallmark of high-risk neuroblastoma, and are conferred by activation of telomerase or alternative lengthening of telomeres (ALT). However, detection of TMM is not yet part of the clinical routine, and consensus on TMM detection, especially on ALT assessment, remains to be achieved. Methods Whole genome sequencing (WGS) data of 68 primary neuroblastoma samples were analyzed. Telomere length was calculated from WGS data or by telomere restriction fragment analysis (n = 39). ALT was assessed by C-circle assay (CCA, n = 67) and detection of ALT-associated PML nuclear bodies (APB) by combined fluorescence in situ hybridization and immunofluorescence staining (n = 68). RNA sequencing was performed (n = 64) to determine expression of TERT and telomeric long non-coding RNA (TERRA). Telomerase activity was examined by telomerase repeat amplification protocol (TRAP, n = 15). Results Tumors were considered as telomerase-positive if they harbored a TERT rearrangement, MYCN amplification or high TERT expression (45.6%, 31/68), and ALT-positive if they were positive for APB and CCA (19.1%, 13/68). If all these markers were absent, tumors were considered TMM-negative (25.0%, 17/68). According to these criteria, the majority of samples were classified unambiguously (89.7%, 61/68). Assessment of additional ALT-associated parameters clarified the TMM status of the remaining seven cases with high likelihood: ALT-positive tumors had higher TERRA expression, longer telomeres, more telomere insertions, a characteristic pattern of telomere variant repeats, and were associated with ATRX mutations. Conclusions We here propose a workflow to reliably detect TMM in neuroblastoma. We show that unambiguous classification is feasible following a stepwise approach that determines both, activation of telomerase and ALT. The workflow proposed in this study can be used in clinical routine and provides a framework to systematically and reliably determine telomere maintenance mechanisms for risk stratification and treatment allocation of neuroblastoma patients.

Background Liquid biopsies offer less burdensome sensitive disease monitoring. Bone marrow (BM) metastases, common in various cancers including neuroblastoma, is associated with poor outcomes. In pediatric high-risk neuroblastoma most patients initially respond to treatment, but in the majority the disease recurs with only 40% long-term survivors, stressing the need for more sensitive detection of disseminated disease during therapy. Methods To validate sensitive neuroblastoma mRNA RT-qPCR BM testing, we prospectively assessed serial BM samples from 345 international high‐risk neuroblastoma patients, treated in trials NB2004 (GPOH) or NBL2009 (DCOG), using PHOX2B , TH , DDC , CHRNA3 , and GAP43 RT-qPCR mRNA markers and BM GD2-immunocytology. Association between BM-infiltration levels and event-free survival (EFS) and overall survival (OS) was estimated by using Cox regression models and Kaplan-Meier’s methodology. Results BM infiltration >10% by RT-qPCR at diagnosis was prognostic for survival (adjusted hazard ratio (HR) 1.82 [95%CI 1.25‐2.63] and 2.04 [1.33‐3.14] for EFS and OS, respectively). Any post-induction RT-qPCR positivity correlated with poor EFS and OS, with a HR of 2.10 [1.27-3.49] and 1.76 [1.01-3.08] and 5-years EFS of 26.6% [standard error 5.2%] versus 60.4% [6.7] and OS of 43.8% [5.9] versus 65.7% [6.6] for RT-qPCR-positive patients versus RT-qPCR-negative patients. In contrast, post-induction immunocytology positivity was not associated with EFS or OS (HR 1.22 [0.68-2.19] and 1.26 [0.54-2.42]). Conclusion This study validates the association of not clearing of BM metastases by sensitive RT-qPCR detection with very poor outcome. We therefore propose implementation of RT-qPCR for minimal residual disease testing in neuroblastoma to guide therapy.

This study investigates lightning at tall objects and evaluates the risk of upward lightning (UL) over the eastern Alps and its surrounding areas. While uncommon, UL poses a threat, especially to wind turbines, as the long‐duration current of UL can cause significant damage. Current risk assessment methods overlook the impact of meteorological conditions, potentially underestimating UL risks. Therefore, this study employs random forests, a machine learning technique, to analyze the relationship between UL measured at Gaisberg Tower (Austria) and 35 larger‐scale meteorological variables. Of these, the larger‐scale upward velocity, wind speed and direction at 10 m and cloud physics variables contribute most information. The random forests predict the risk of UL across the study area at a 1 km2${\\text{km}}^{2}$resolution. Strong near‐surface winds combined with upward deflection by elevated terrain increase UL risk. The diurnal cycle of the UL risk as well as high‐risk areas shift seasonally. They are concentrated north/northeast of the Alps in winter due to prevailing northerly winds, and expanding southward, impacting northern Italy in the transitional and summer months. The model performs best in winter, with the highest predicted UL risk coinciding with observed peaks in measured lightning at tall objects. The highest concentration is north of the Alps, where most wind turbines are located, leading to an increase in overall lightning activity. Comprehensive meteorological information is essential for UL risk assessment, as lightning densities are a poor indicator of lightning at tall objects. Plain Language Summary This study investigates the risk of upward lightning (UL) in the eastern Alps and surrounding regions, which is critical for tall objects such as wind turbines. Current risk assessments often overlook meteorological conditions, potentially underestimating the hazard. Using random forests, a machine learning method, the study analyzes UL at the Gaisberg Tower in Austria, taking into account 35 meteorological factors. Key contributors include wind speed, wind direction, and cloud physics. The model predicts UL risk at a resolution of 1 km2${\\text{km}}^{2}$ , highlighting higher‐risk areas influenced by near‐surface winds and terrain. Risk varies daily and seasonally, peaking in winter north of the Alps and shifting southward in warmer months. Winter predictions are consistent with observed lightning at tall objects, particularly concentrated north of the Alps where wind turbines are prevalent. This study highlights the importance of detailed meteorological data for accurate UL risk assessment and demonstrates that general lightning densities are inadequate indicators of the safety of tall objects. Key Points Strong winds near the surface and upward deflection by obstructing terrain increase the risk of upward lightning at tall objects Lightning at tall wind turbines can account for up to 20% of total lightning activity north of the Alps High‐risk areas are north and east of the Alps in winter and shift southward in the transition seasons and summer