Outcome Prognostic Factors in MRI during Spica Cast Therapy Treating Developmental Hip Dysplasia with Midterm Follow-Up

Closed reduction followed by spica casting is a conservative treatment for developmental dysplasia of the hip (DDH). Magnetic resonance imaging (MRI) can verify proper closed reduction of the dysplastic hip. Our aim was to find prognostic factors in the first MRI to predict the possible outcome of the initial treatment success by means of ultrasound monitoring according to Graf and the further development of the hip dysplasia or risk of recurrence in the radiological follow-up examinations. A total of 48 patients (96 hips) with DDH on at least one side, and who were treated with closed reduction and spica cast were included in this retrospective cohort study. Treatment began at a mean age of 9.9 weeks. The children were followed for 47.4 months on average. We performed closed reduction and spica casting under general balanced anaesthesia. This was directly followed by MRI to control the position/reduction of the femoral head without anaesthesia. The following parameters were measured in the MRI: hip abduction angle, coronal, anterior and posterior bony axial acetabular angles and pelvic width. A Graf alpha angle of at least 60° was considered successful. In the radiological follow-up controls, we evaluated for residual dysplasia or recurrence. In our cohort, we only found the abduction angle to be an influencing factor for improvement of the DDH. No other prognostic factors in MRI measurements, such as gender, age at time of the first spica cast, or treatment involving overhead extension were found to be predictive of mid-term outcomes. This may, however, be due to the relatively small number of treatment failures

Brain volumes predict neurodevelopment in adolescents after surgery for congenital heart disease

Patients with complex congenital heart disease are at risk for neurodevelopmental impairments. Evidence suggests that brain maturation can be delayed and pre- and postoperative brain injury may occur, and there is limited information on the long-term effect of congenital heart disease on brain development and function in adolescent patients. At a mean age of 13.8 years, 39 adolescent survivors of childhood cardiopulmonary bypass surgery with no structural brain lesions evident through conventional cerebral magnetic resonance imaging and 32 healthy control subjects underwent extensive neurodevelopmental assessment and cerebral magnetic resonance imaging. Cerebral scans were analysed quantitatively using surface-based and voxel-based morphometry. Compared with control subjects, patients had lower total brain (P = 0.003), white matter (P = 0.004) and cortical grey matter (P = 0.005) volumes, whereas cerebrospinal fluid volumes were not different. Regional brain volume reduction ranged from 5.3% (cortical grey matter) to 11% (corpus callosum). Adolescents with cyanotic heart disease showed more brain volume loss than those with acyanotic heart disease, particularly in the white matter, thalami, hippocampi and corpus callosum (all P-values < 0.05). Brain volume reduction correlated significantly with cognitive, motor and executive functions (grey matter: P < 0.05, white matter: P < 0.01). Our findings suggest that there are long-lasting cerebral changes in adolescent survivors of cardiopulmonary bypass surgery for congenital heart disease and that these changes are associated with functional outcom

3D printing of functional assemblies with integrated polymer-bonded magnets demonstrated with a prototype of a rotary blood pump

Conventional magnet manufacturing is a significant bottleneck in the development processes of products that use magnets, because every design adaption requires production steps with long lead times. Additive manufacturing of magnetic components delivers the opportunity to shift to agile and test-driven development in early prototyping stages, as well as new possibilities for complex designs. In an effort to simplify integration of magnetic components, the current work presents a method to directly print polymer-bonded hard magnets of arbitrary shape into thermoplastic parts by fused deposition modeling. This method was applied to an early prototype design of a rotary blood pump with magnetic bearing and magnetic drive coupling. Thermoplastics were compounded with 56 vol.% isotropic NdFeB powder to manufacture printable filament. With a powder loading of 56 vol.%, remanences of 350 mT and adequate mechanical flexibility for robust processability were achieved. This compound allowed us to print a prototype of a turbodynamic pump with integrated magnets in the impeller and housing in one piece on a low-cost, end-user 3D printer. Then, the magnetic components in the printed pump were fully magnetized in a pulsed Bitter coil. The pump impeller is driven by magnetic coupling to non-printed permanent magnets rotated by a brushless DC motor, resulting in a flow rate of 3 L/min at 1000 rpm. For the first time, an application of combined multi-material and magnet printing by fused deposition modeling was shown. The presented process significantly simplifies the prototyping of products that use magnets, such as rotary blood pumps, and opens the door for more complex and innovative designs. It will also help postpone the shift to conventional manufacturing methods to later phases of the development process

Weakly Supervised Learning with Automated Labels from Radiology Reports for Glioma Change Detection

Gliomas are the most frequent primary brain tumors in adults. Glioma change detection aims at finding the relevant parts of the image that change over time. Although Deep Learning (DL) shows promising performances in similar change detection tasks, the creation of large annotated datasets represents a major bottleneck for supervised DL applications in radiology. To overcome this, we propose a combined use of weak labels (imprecise, but fast-to-create annotations) and Transfer Learning (TL). Specifically, we explore inductive TL, where source and target domains are identical, but tasks are different due to a label shift: our target labels are created manually by three radiologists, whereas our source weak labels are generated automatically from radiology reports via NLP. We frame knowledge transfer as hyperparameter optimization, thus avoiding heuristic choices that are frequent in related works. We investigate the relationship between model size and TL, comparing a low-capacity VGG with a higher-capacity ResNeXt model. We evaluate our models on 1693 T2-weighted magnetic resonance imaging difference maps created from 183 patients, by classifying them into stable or unstable according to tumor evolution. The weak labels extracted from radiology reports allowed us to increase dataset size more than 3-fold, and improve VGG classification results from 75% to 82% AUC. Mixed training from scratch led to higher performance than fine-tuning or feature extraction. To assess generalizability, we ran inference on an open dataset (BraTS-2015: 15 patients, 51 difference maps), reaching up to 76% AUC. Overall, results suggest that medical imaging problems may benefit from smaller models and different TL strategies with respect to computer vision datasets, and that report-generated weak labels are effective in improving model performances. Code, in-house dataset and BraTS labels are released.Comment: This work has been submitted as Original Paper to a Journa

Verhaltensökonomische Ansätze zugunsten der Verkehrssicherheit (Nudging)

Forschungsprojekt MFZ_20_00A_01 auf Antrag der Arbeitsgruppe Mensch und Fahrzeug (MFZ

Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence

Ampattu BJ, Hagmann L, Liang C, et al. Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence. BMC Genomics. 2017;18(1): 282.Background: Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain alpha 522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence. Results: Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p) ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region. Conclusions: Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis

Independent Evaluation of Green Climate Fund’s Investment Framework

This evaluation of the GCF Investment Framework assesses the overall relevance and effectiveness of the Investment Framework in the context of the GCF’s efforts towards climate change mitigation and adaptation. Overall, the evaluation examines how effective and fit-for-purpose the GCF Investment Framework is in fulfilling strategic goals and mandate. It assesses the coherence and complementarity of the GCF Investment Framework internally with other GCF internal policies, and externally with the country-level climate change strategies and action plans. It also assesses and analyse the efficiency, effectiveness, coherence and complementarity of the GCF Investment Framework with regard to funding proposals, projects and programmes. In addition, it reviews alignment with wider results and risk management frameworks

Mutual Projectile and Target Ionization in 1-MeV/amu N⁴⁺ and N₅⁺+ He Collisions

We have studied mutual projectile and target ionization in 1-MeV/amu N4+ and N5++He collisions in kinematically complete experiments by measuring the momenta of the recoil ion and both ejected electrons in coincidence with the charge-changed projectiles. By means of four-particle Dalitz plots, in which multiple differential cross sections are presented as a function of the momenta of all four particles, experimental spectra are compared with theoretical results from various models. The experimental data are qualitatively reproduced by higher-order calculations, where good agreement is achieved for N5++He collisions, while some discrepancies persist for N4++He collisions

Gravitational clustering of relic neutrinos and implications for their detection

We study the gravitational clustering of big bang relic neutrinos onto existing cold dark matter (CDM) and baryonic structures within the flat $\Lambda$CDM model, using both numerical simulations and a semi-analytical linear technique, with the aim of understanding the neutrinos' clustering properties for direct detection purposes. In a comparative analysis, we find that the linear technique systematically underestimates the amount of clustering for a wide range of CDM halo and neutrino masses. This invalidates earlier claims of the technique's applicability. We then compute the exact phase space distribution of relic neutrinos in our neighbourhood at Earth, and estimate the large scale neutrino density contrasts within the local Greisen--Zatsepin--Kuzmin zone. With these findings, we discuss the implications of gravitational neutrino clustering for scattering-based detection methods, ranging from flux detection via Cavendish-type torsion balances, to target detection using accelerator beams and cosmic rays. For emission spectroscopy via resonant annihilation of extremely energetic cosmic neutrinos on the relic neutrino background, we give new estimates for the expected enhancement in the event rates in the direction of the Virgo cluster.Comment: 38 pages, 8 embedded figures, iopart.cls; v2: references added, minor changes in text, to appear in JCA

Bayesian and frequentist analysis of an Austrian genome-wide association study of colorectal cancer and advanced adenomas

Most genome-wide association studies (GWAS) were analyzed using single marker tests in combination with stringent correction procedures for multiple testing. Thus, a substantial proportion of associated single nucleotide polymorphisms (SNPs) remained undetected and may account for missing heritability in complex traits. Model selection procedures present a powerful alternative to identify associated SNPs in high-dimensional settings. In this GWAS including 1060 colorectal cancer cases, 689 cases of advanced colorectal adenomas and 4367 controls we pursued a dual approach to investigate genome-wide associations with disease risk applying both, single marker analysis and model selection based on the modified Bayesian information criterion, mBIC2, implemented in the software package MOSGWA. For different case-control comparisons, we report models including between 1-14 candidate SNPs. A genome-wide significant association of rs17659990 (P=5.43x10(-9), DOCK3, chromosome 3p21.2) with colorectal cancer risk was observed. Furthermore, 56 SNPs known to influence susceptibility to colorectal cancer and advanced adenoma were tested in a hypothesis-driven approach and several of them were found to be relevant in our Austrian cohort. After correction for multiple testing (alpha=8.9x10(-4)), the most significant associations were observed for SNPs rs10505477 (P=6.08x10(-4)) and rs6983267 (P=7.35x10(-4)) of CASC8, rs3802842 (P=8.98x10(-5), COLCA1,2), and rs12953717 (P=4.64x10(-4), SMAD7). All previously unreported SNPs demand replication in additional samples. Reanalysis of existing GWAS datasets using model selection as tool to detect SNPs associated with a complex trait may present a promising resource to identify further genetic risk variants not only for colorectal cancer