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Bipolar disorder (BD) is a highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. BD shows substantial clinical and genetic overlap with other psychiatric disorders, in particular schizophrenia (SCZ). The genes underlying this etiological overlap remain largely unknown. A recent SCZ genome wide association study (GWAS) by the Psychiatric Genomics Consortium identified 128 independent genome-wide significant single nucleotide polymorphisms (SNPs). The present study investigated whether these SCZ-associated SNPs also contribute to BD development through the performance of association testing in a large BD GWAS dataset (9747 patients, 14278 controls). After re-imputation and correction for sample overlap, 22 of 107 investigated SCZ SNPs showed nominal association with BD. The number of shared SCZ-BD SNPs was significantly higher than expected (p = 1.46x10-8). This provides further evidence that SCZ-associated loci contribute to the development of BD. Two SNPs remained significant after Bonferroni correction. The most strongly associated SNP was located near TRANK1, which is a reported genome-wide significant risk gene for BD. Pathway analyses for all shared SCZ-BD SNPs revealed 25 nominally enriched gene-sets, which showed partial overlap in terms of the underlying genes. The enriched gene-sets included calcium- and glutamate signaling, neuropathic pain signaling in dorsal horn neurons, and calmodulin binding. The present data provide further insights into shared risk loci and disease-associated pathways for BD and SCZ. This may suggest new research directions for the treatment and prevention of these two major psychiatric disorders.
The biological effects of energetic heavy ions are attracting increasing interest for their applications in cancer therapy and protection against space radiation. The cascade of events leading to cell death or late effects starts from stochastic energy deposition on the nanometer scale and the corresponding lesions in biological molecules, primarily DNA. We have developed experimental techniques to visualize DNA nanolesions induced by heavy ions. Nanolesions appear in cells as “streaks” which can be visualized by using different DNA repair markers. We have studied the kinetics of repair of these “streaks” also with respect to the chromatin conformation. Initial steps in the modeling of the energy deposition patterns at the micrometer and nanometer scale were made with MCHIT and TRAX models, respectively.
Background: Radiochemotherapy (RCT) has been shown to induce changes in immune cell homeostasis which might affect antitumor immune responses. In the present study, we aimed to compare the composition and kinetics of major lymphocyte subsets in the periphery of patients with non-locoregional recurrent (n = 23) and locoregional recurrent (n = 9) squamous cell carcinoma of the head and neck (SCCHN) upon primary RCT. Methods: EDTA-blood of non-locoregional recurrent SCCHN patients was collected before (t0), after application of 20–30 Gy (t1), in the follow-up period 3 (t2) and 6 months (t3) after RCT. In patients with locoregional recurrence blood samples were taken at t0, t1, t2 and at the time of recurrence (t5). EDTA-blood of age-related, healthy volunteers (n = 22) served as a control (Ctrl). Major lymphocyte subpopulations were phenotyped by multiparameter flow cytometry. Results: Patients with non-recurrent SCCHN had significantly lower proportions of CD19+ B cells compared to healthy individuals before start of any therapy (t0) that dropped further until 3 months after RCT (t2), but reached initial levels 6 months after RCT (t3). The proportion of CD3+ T and CD3+/CD4+ T helper cells continuously decreased between t0 and t3, whereas that of CD8+ cytotoxic T cells and CD3+/CD56+ NK-like T cells (NKT) gradually increased in the same period of time in non-recurrent patients. The percentage of CD4+/CD25+/FoxP3+ regulatory T cells (Tregs) decreased directly after RCT, but increased above initial levels in the follow-up period 3 (t2) and 6 (t3) months after RCT. Patients with locoregional recurrence showed similar trends with respect to B, T cells and Tregs between t0 and t5. CD4+ T helper cells remained stably low between t0 and t5 in patients with locoregional recurrence compared to Ctrl. NKT/NK cell subsets (CD56+/CD69+, CD3−/CD56+, CD3−/CD94+, CD3−/NKG2D+, CD3−/NKp30+, CD3−/NKp46+) increased continuously up to 6 months after RCT (t0-t3) in patients without locoregional recurrence, whereas in patients with locoregional recurrence, these subsets remained stably low until time of recurrence (t5). Conclusion: Monitoring the kinetics of lymphocyte subpopulations especially activatory NK cells before and after RCT might provide a clue with respect to the development of an early locoregional recurrence in patients with SCCHN. However, studies with larger patient cohorts are needed. Trial registration: Observational Study on Biomarkers in Head and Neck Cancer (HNprädBio), NCT02059668. Registered on 11 February 2014, https://clinicaltrials.gov/ct2/show/NCT02059668.
Purpose: To compare the effective lens position (ELP), anterior chamber depth (ACD) changes, and visual outcomes in patients with and without pseudoexfoliation syndrome (PEX) after cataract surgery.
Design: Prospective, randomized, fellow-eye controlled clinical case series.
Methods: This prospective comparative case series enrolled 56 eyes of 56 consecutive patients with (n = 28) or without PEX (n = 28) and clinically significant cataract who underwent standard phacoemulsification and were implanted with single-piece acrylic posterior chamber intraocular lenses (IOLs). The primary outcome parameters were the ACD referring to the distance between the corneal anterior surface and the lens anterior surface, which is an indicator of the postoperative axial position of the IOL (the so-called ELP) and distance corrected visual acuity (DCVA).
Results: Before surgery, the ACD was 2.54 ± 0.42 mm in the PEX group and 2.53 ± 0.38 mm in the control group (p = 0.941). Postoperatively, the ACD was 4.29 ± 0.71 mm in the PEX group and 4.33 ± 0.72 mm in the normal group, respectively (p = 0.533). There was no significant difference in ACD changes between groups (PEX group: 1.75 ± 0.74 mm, control group: 1.81 ± 0.61 mm, p = 0.806) and DCVA pre- (p = 0.469) and postoperatively (PEX group: 0.11 ± 0.13 logMAR, control group: 0.09 ± 0.17 logMAR, p = 0.245) between groups.
Conclusion: Preoperative and postoperative ACD, as an indicator of ELP, between PEX eyes and healthy eyes after cataract surgery showed no significant difference. Phacoemulsification induced similar changes in eyes with PEX compared to healthy eyes.
This paper introduces a new methodology for the fabrication of strain-sensor elements for MEMS and NEMS applications based on the tunneling effect in nano-granular metals. The strain-sensor elements are prepared by the maskless lithography technique of focused electron-beam-induced deposition (FEBID) employing the precursor trimethylmethylcyclopentadienyl platinum [MeCpPt(Me)3]. We use a cantilever-based deflection technique to determine the sensitivity (gauge factor) of the sensor element. We find that its sensitivity depends on the electrical conductivity and can be continuously tuned, either by the thickness of the deposit or by electron-beam irradiation leading to a distinct maximum in the sensitivity. This maximum finds a theoretical rationale in recent advances in the understanding of electronic charge transport in nano-granular metals.
Highlights:
• Assessment of body composition parameters in a large cohort of patients with HCC undergoing TACE.
• Fully automated artificial intelligence-based quantitative 3D volumetry of abdominal cavity tissue composition.
• Skeletal muscle volume and related parameters were independent prognostic factors in patients with HCC undergoing TACE.
Background & Aims: Body composition assessment (BCA) parameters have recently been identified as relevant prognostic factors for patients with hepatocellular carcinoma (HCC). Herein, we aimed to investigate the role of BCA parameters for prognosis prediction in patients with HCC undergoing transarterial chemoembolization (TACE).
Methods: This retrospective multicenter study included a total of 754 treatment-naïve patients with HCC who underwent TACE at six tertiary care centers between 2010–2020. Fully automated artificial intelligence-based quantitative 3D volumetry of abdominal cavity tissue composition was performed to assess skeletal muscle volume (SM), total adipose tissue (TAT), intra- and intermuscular adipose tissue, visceral adipose tissue, and subcutaneous adipose tissue (SAT) on pre-intervention computed tomography scans. BCA parameters were normalized to the slice number of the abdominal cavity. We assessed the influence of BCA parameters on median overall survival and performed multivariate analysis including established estimates of survival.
Results: Univariate survival analysis revealed that impaired median overall survival was predicted by low SM (p <0.001), high TAT volume (p = 0.013), and high SAT volume (p = 0.006). In multivariate survival analysis, SM remained an independent prognostic factor (p = 0.039), while TAT and SAT volumes no longer showed predictive ability. This predictive role of SM was confirmed in a subgroup analysis of patients with BCLC stage B.
Conclusions: SM is an independent prognostic factor for survival prediction. Thus, the integration of SM into novel scoring systems could potentially improve survival prediction and clinical decision-making. Fully automated approaches are needed to foster the implementation of this imaging biomarker into daily routine.
Impact and implications: Body composition assessment parameters, especially skeletal muscle volume, have been identified as relevant prognostic factors for many diseases and treatments. In this study, skeletal muscle volume has been identified as an independent prognostic factor for patients with hepatocellular carcinoma undergoing transarterial chemoembolization. Therefore, skeletal muscle volume as a metaparameter could play a role as an opportunistic biomarker in holistic patient assessment and be integrated into decision support systems. Workflow integration with artificial intelligence is essential for automated, quantitative body composition assessment, enabling broad availability in multidisciplinary case discussions.
Human behaviour is inextricably linked to the interaction of emotion and cognition. For decades, emotion and cognition were perceived as separable processes, yet with mutual interactions. Recently, this differen-tiation has been challenged by more integrative approaches, but without addressing the exact neurophysiological basis of their interaction. Here, we aimed to uncover neurophysiological mechanisms of emotion-cognition interaction. We used an emotional Flanker task paired with EEG/FEM beamforming in a large cohort (N=121) of healthy human participants, obtaining high temporal and fMRI-equivalent spatial resolution. Spatially, emotion and cognition processing overlapped in the right inferior frontal gyrus (rIFG), specifically in pars triangularis. Temporally, emotion and cognition processing overlapped during the transition from emotional to cognitive processing, with a stronger interaction in β-band power leading to worse behavioral performance. Despite functionally segregated subdivisions in rIFG, frequency-specific information flowed extensively within IFG and top-down to visual areas (V2, Precuneus) – explaining the behavioral interference effect. Thus, for the first time we here show the neural mechanisms of emotion-cognition interaction in space, time, frequency and information transfer with high temporal and spatial resolution, revealing a central role for β-band activity in rIFG. Our results support the idea that rIFG plays a broad role in both inhibitory control and emotional interference inhibition as it is a site of convergence in both processes. Furthermore, our results have potential clinical implications for understanding dysfunctional emotion-cognition interaction and emotional interference inhibition in psychiatric disor-ders, e.g. major depression and substance use disorder, in which patients have difficulties in regulating emotions and executing inhibitory control.
The Kinase Chemogenomic Set (KCGS): An open science resource for kinase vulnerability identification
(2019)
We describe the assembly and annotation of a chemogenomic set of protein kinase inhibitors as an open science resource for studying kinase biology. The set only includes inhibitors that show potent kinase inhibition and a narrow spectrum of activity when screened across a large panel of kinase biochemical assays. Currently, the set contains 187 inhibitors that cover 215 human kinases. The kinase chemogenomic set (KCGS) is the most highly annotated set of selective kinase inhibitors available to researchers for use in cell-based screens.
Comprehensive analysis of tumour sub-volumes for radiomic risk modelling in locally advanced HNSCC
(2020)
Simple Summary: Radiomic risk models are usually based on imaging features, which are extracted from the entire gross tumour volume (GTV entire ). This approach does not explicitly consider the complex biological structure of the tumours. Therefore, in this retrospective study, we investigated the prognostic value of radiomic analyses based on different tumour sub-volumes using computed tomography imaging of patients with locally advanced head and neck squamous cell carcinoma who were treated with primary radio-chemotherapy. The GTV entire was cropped by different margins to define the rim and corresponding core sub-volumes of the tumour. Furthermore, the best performing tumour rim sub-volume was extended into surrounding tissue with different margins. As a result, the models based on the 5 mm tumour rim and on the 3 mm extended rim sub-volume showed an improved performance compared to models based on the corresponding tumour core. This indicates that the consideration of tumour sub-volumes may help to improve radiomic risk models.
Abstract: Imaging features for radiomic analyses are commonly calculated from the entire gross tumour volume (GTVentire). However, tumours are biologically complex and the consideration of different tumour regions in radiomic models may lead to an improved outcome prediction. Therefore, we investigated the prognostic value of radiomic analyses based on different tumour sub-volumes using computed tomography imaging of patients with locally advanced head and neck squamous cell carcinoma. The GTVentire was cropped by different margins to define the rim and the corresponding core sub-volumes of the tumour. Subsequently, the best performing tumour rim sub-volume was extended into surrounding tissue with different margins. Radiomic risk models were developed and validated using a retrospective cohort consisting of 291 patients in one of the six Partner Sites of the German Cancer Consortium Radiation Oncology Group treated between 2005 and 2013. The validation concordance index (C-index) averaged over all applied learning algorithms and feature selection methods using the GTVentire achieved a moderate prognostic performance for loco-regional tumour control (C-index: 0.61 ± 0.04 (mean ± std)). The models based on the 5 mm tumour rim and on the 3 mm extended rim sub-volume showed higher median performances (C-index: 0.65 ± 0.02 and 0.64 ± 0.05, respectively), while models based on the corresponding tumour core volumes performed less (C-index: 0.59 ± 0.01). The difference in C-index between the 5 mm tumour rim and the corresponding core volume showed a statistical trend (p = 0.10). After additional prospective validation, the consideration of tumour sub-volumes may be a promising way to improve prognostic radiomic risk models.
Purpose: To develop and validate a CT-based radiomics signature for the prognosis of loco-regional tumour control (LRC) in patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated by primary radiochemotherapy (RCTx) based on retrospective data from 6 partner sites of the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG).
Material and methods: Pre-treatment CT images of 318 patients with locally advanced HNSCC were collected. Four-hundred forty-six features were extracted from each primary tumour volume and then filtered through stability analysis and clustering. First, a baseline signature was developed from demographic and tumour-associated clinical parameters. This signature was then supplemented by CT imaging features. A final signature was derived using repeated 3-fold cross-validation on the discovery cohort. Performance in external validation was assessed by the concordance index (C-Index). Furthermore, calibration and patient stratification in groups with low and high risk for loco-regional recurrence were analysed.
Results: For the clinical baseline signature, only the primary tumour volume was selected. The final signature combined the tumour volume with two independent radiomics features. It achieved moderately good discriminatory performance (C-Index [95% confidence interval]: 0.66 [0.55–0.75]) on the validation cohort along with significant patient stratification (p = 0.005) and good calibration.
Conclusion: We identified and validated a clinical-radiomics signature for LRC of locally advanced HNSCC using a multi-centric retrospective dataset. Prospective validation will be performed on the primary cohort of the HNprädBio trial of the DKTK-ROG once follow-up is completed.
(1) Background: Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) who are biologically at high risk for the development of loco–regional recurrences after postoperative radiotherapy (PORT) but at intermediate risk according to clinical risk factors may benefit from additional concurrent chemotherapy. In this matched-pair study, we aimed to identify a corresponding predictive gene signature. (2) Methods: Gene expression analysis was performed on a multicenter retrospective cohort of 221 patients that were treated with postoperative radiochemotherapy (PORT-C) and 283 patients who were treated with PORT alone. Propensity score analysis was used to identify matched patient pairs from both cohorts. From differential gene expression analysis and Cox regression, a predictive gene signature was identified. (3) Results: 108 matched patient pairs were selected. We identified a 2-metagene signature that stratified patients into risk groups in both cohorts. The comparison of the high-risk patients between the two types of treatment showed higher loco–regional control (LRC) after treatment with PORT-C (p < 0.001), which was confirmed by a significant interaction term in Cox regression (p = 0.027), i.e., the 2-metagene signature was indicative for the type of treatment. (4) Conclusion: We have identified a novel gene signature that may be helpful to identify patients with high-risk HNSCC amongst those at intermediate clinical risk treated with PORT, who may benefit from additional concurrent chemotherapy.