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Objective: Gestational diabetes mellitus (GDM) is associated with substantial morbidity for mothers and their offspring. While clinical and basic research activities on this important disease grow constantly, there is no concise analysis of global architecture of GDM research. Hence, it was the objective of this study to assess the global scientific performance chronologically, geographically and in relation to existing research networks and gender distribution of publishing authors.
Study design: On the basis of the New Quality and Quantity Indices in Science (NewQIS) platform, scientometric methods were combined with modern visualizing techniques such as density equalizing mapping, and the Web of Science database was used to assess GDM-related entries from 1900 to 2012.
Results: Twelve thousand five hundred four GDM-related publications were identified and analyzed. The USA (4295 publications) and the UK (1354 publications) dominated the field concerning research activity, overall citations and country-specific Hirsch-Index, which quantified the impact of a country’s published research on the scientific community. Semi-qualitative indices such as country-specific citation rates ranked New Zealand and the UK at top positions. Annual collaborative publications increased steeply between the years 1990 and 2012 (71 to 1157 respectively). Subject category analysis pointed to a minor interest of public health issues in GDM research. Gender analysis in terms of publication authorship revealed a clear dominance of the male gender until 2005; then a trend towards gender equity started and the activity of female scientists grew visibly in many countries. The country-specific gender analysis revealed large differences, i.e. female scientists dominated the scientific output in the USA, whereas the majority of research was published by male authors in countries such as Japan.
Conclusion: This study provides the first global sketch of GDM research architecture. While North-American and Western-European countries were dominating the GDM-related scientific landscape, a disparity exists in terms of research output between developed and low-resource countries. Since GDM is linked to considerable mortality and morbidity of mothers and their offspring and constitutes a tremendous burden for the healthcare systems in underserved countries, our findings emphasize the need to address disparities by fostering research endeavors, public health programs and collaborative efforts in these nations.
Introduction: Reliable predictive and prognostic markers for routine diagnostic purposes are needed for breast cancer patients treated with neoadjuvant chemotherapy. We evaluated protein biomarkers in a cohort of 116 participants of the GeparDuo study on anthracycline/taxane-based neoadjuvant chemotherapy for operable breast cancer to test for associations with pathological complete response (pCR) and disease-free survival (DFS). Particularly, we evaluated if interactions between hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression might lead to a different clinical behavior of HR+/HER2+ coexpressing and HR+/HER2- tumors and whether subgroups of triple negative tumors might be identified by the help of Ki67 labeling index, cytokeratin 5/6 (CK5/6), as well as cyclooxygenase-2 (COX-2), and Y-box binding protein 1 (YB-1) expression. Methods: Expression analysis was performed using immunohistochemistry and silver-enhanced in situ hybridization on tissue microarrays (TMAs) of pretherapeutic core biopsies. Results: pCR rates were significantly different between the biology-based tumor types (P = 0.044) with HR+/HER2+ and HR-/HER2- tumors having higher pCR rates than HR+/HER2-tumors. Ki67 labeling index, confirmed as significant predictor of pCR in the whole cohort (P = 0.001), identified HR-/HER- (triple negative) carcinomas with a higher chance for a pCR (P = 0.006). Biology-based tumor type (P = 0.046 for HR+/HER2+vs. HR+/HER2-), Ki67 labeling index (P = 0.028), and treatment arm (P = 0.036) were independent predictors of pCR in a multivariate model. DFS was different in the biology-based tumor types (P < 0.0001) with HR+/HER2- and HR+/HER2+ tumors having the best prognosis and HR-/HER2+ tumors showing the worst outcome. Biology-based tumor type was an independent prognostic factor for DFS in multivariate analysis (P < 0.001). Conclusions: Our data demonstrate that a biology-based breast cancer classification using estrogen receptor (ER), progesterone receptor (PgR), and HER2 bears independent predictive and prognostic potential. The HR+/HER2+ coexpressing carcinomas emerged as a group of tumors with a good response rate to neoadjuvant chemotherapy and a favorable prognosis. HR+/HER2- tumors had a good prognosis irrespective of a pCR, whereas patients with HR-/HER- and HR-/HER+ tumors, especially if they had not achieved a pCR, had an unfavorable prognosis and are in need of additional treatment options. Trial registration ClinicalTrials.gov identifier: NCT00793377
The ongoing pandemic caused by the Betacoronavirus SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) demonstrates the urgent need of coordinated and rapid research towards inhibitors of the COVID-19 lung disease. The covid19-nmr consortium seeks to support drug development by providing publicly accessible NMR data on the viral RNA elements and proteins. The SARS-CoV-2 genome encodes for approximately 30 proteins, among them are the 16 so-called non-structural proteins (Nsps) of the replication/transcription complex. The 217-kDa large Nsp3 spans one polypeptide chain, but comprises multiple independent, yet functionally related domains including the viral papain-like protease. The Nsp3e sub-moiety contains a putative nucleic acid-binding domain (NAB) with so far unknown function and consensus target sequences, which are conceived to be both viral and host RNAs and DNAs, as well as protein-protein interactions. Its NMR-suitable size renders it an attractive object to study, both for understanding the SARS-CoV-2 architecture and drugability besides the classical virus’ proteases. We here report the near-complete NMR backbone chemical shifts of the putative Nsp3e NAB that reveal the secondary structure and compactness of the domain, and provide a basis for NMR-based investigations towards understanding and interfering with RNA- and small-molecule-binding by Nsp3e.
The SARS-CoV-2 genome encodes for approximately 30 proteins. Within the international project COVID19-NMR, we distribute the spectroscopic analysis of the viral proteins and RNA. Here, we report NMR chemical shift assignments for the protein Nsp3b, a domain of Nsp3. The 217-kDa large Nsp3 protein contains multiple structurally independent, yet functionally related domains including the viral papain-like protease and Nsp3b, a macrodomain (MD). In general, the MDs of SARS-CoV and MERS-CoV were suggested to play a key role in viral replication by modulating the immune response of the host. The MDs are structurally conserved. They most likely remove ADP-ribose, a common posttranslational modification, from protein side chains. This de-ADP ribosylating function has potentially evolved to protect the virus from the anti-viral ADP-ribosylation catalyzed by poly-ADP-ribose polymerases (PARPs), which in turn are triggered by pathogen-associated sensing of the host immune system. This renders the SARS-CoV-2 Nsp3b a highly relevant drug target in the viral replication process. We here report the near-complete NMR backbone resonance assignment (1H, 13C, 15N) of the putative Nsp3b MD in its apo form and in complex with ADP-ribose. Furthermore, we derive the secondary structure of Nsp3b in solution. In addition, 15N-relaxation data suggest an ordered, rigid core of the MD structure. These data will provide a basis for NMR investigations targeted at obtaining small-molecule inhibitors interfering with the catalytic activity of Nsp3b.
CXCL12-CXCR4 signaling controls multiple physiological processes and its dysregulation is associated with cancers and inflammatory diseases. To discover as-yet-unknown endogenous ligands of CXCR4, we screened a blood-derived peptide library for inhibitors of CXCR4-tropic HIV-1 strains. This approach identified a 16 amino acid fragment of serum albumin as an effective and highly specific CXCR4 antagonist. The endogenous peptide, termed EPI-X4, is evolutionarily conserved and generated from the highly abundant albumin precursor by pH-regulated proteases. EPI-X4 forms an unusual lasso-like structure and antagonizes CXCL12-induced tumor cell migration, mobilizes stem cells, and suppresses inflammatory responses in mice. Furthermore, the peptide is abundant in the urine of patients with inflammatory kidney diseases and may serve as a biomarker. Our results identify EPI-X4 as a key regulator of CXCR4 signaling and introduce proteolysis of an abundant precursor protein as an alternative concept for chemokine receptor regulation.
New experimental data for dissociation of relativistic 17Ne projectiles incident on targets of lead, carbon, and polyethylene targets at GSI are presented. Special attention is paid to the excitation and decay of narrow resonant states in 17Ne. Distributions of internal energy in the three-body system have been determined together with angular and partial-energy correlations between the decay products in different energy regions. The analysis was done using existing experimental data on 17Ne and its mirror nucleus 17N. The isobaric multiplet mass equation is used for assignment of observed resonances and their spins and parities. A combination of data from the heavy and light targets yielded cross sections and transition probabilities for the Coulomb excitations of the narrow resonant states. The resulting transition probabilities provide information relevant for a better understanding of the 17Ne structure.
Experimental study of the ¹⁵O(2p,γ)¹⁷Ne cross section by Coulomb dissociation for the rp process
(2016)
The time-reversed reaction 15O(2p, γ)17Ne has been studied by the Coulomb dissociation technique. Secondary 17Ne ion beams at 500 AMeV have been produced by fragmentation reactions of 20Ne in a beryllium production target and dissociated on a secondary Pb target. The incoming beam and the reaction products have been identified with the kinematically complete LAND-R3B experimental setup at GSI. The excitation energy prior to decay has been reconstructed by using the invariant-mass method. The preliminary differential and integral Coulomb Dissociation cross sections (σCoul) have been calculated, which provide a photoabsorption (σphoto) and a radiative capture cross section (σcap). Additionally, important information about the nuclear structure of the 17Ne nucleus will be obtained. The analysis is in progress.
We have studied one-proton-removal reactions of about 500MeV/u 17Ne beams on a carbon target at the R3B/LAND setup at GSI by detecting beam-like 15O-p and determining their relative-energy distribution. We exclusively selected the removal of a 17Ne halo proton, and the Glauber-model analysis of the 16F momentum distribution resulted in an s2 contribution in the 17Ne ground state of about 40%.
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.