Lung epithelial apoptosis in influenza virus pneumonia: the role of macrophage-expressed TNF-related apoptosis-inducing ligand

Mononuclear phagocytes have been attributed a crucial role in the host defense toward influenza virus (IV), but their contribution to influenza-induced lung failure is incompletely understood. We demonstrate for the first time that lung-recruited “exudate” macrophages significantly contribute to alveolar epithelial cell (AEC) apoptosis by the release of tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) in a murine model of influenza-induced pneumonia. Using CC-chemokine receptor 2–deficient (CCR2−/−) mice characterized by defective inflammatory macrophage recruitment, and blocking anti-CCR2 antibodies, we show that exudate macrophage accumulation in the lungs of influenza-infected mice is associated with pronounced AEC apoptosis and increased lung leakage and mortality. Among several proapoptotic mediators analyzed, TRAIL messenger RNA was found to be markedly up-regulated in alveolar exudate macrophages as compared with peripheral blood monocytes. Moreover, among the different alveolar-recruited leukocyte subsets, TRAIL protein was predominantly expressed on macrophages. Finally, abrogation of TRAIL signaling in exudate macrophages resulted in significantly reduced AEC apoptosis, attenuated lung leakage, and increased survival upon IV infection. Collectively, these findings demonstrate a key role for exudate macrophages in the induction of alveolar leakage and mortality in IV pneumonia. Epithelial cell apoptosis induced by TRAIL-expressing macrophages is identified as a major underlying mechanism

Eine negative Geburtserfahrung: Einfluss auf Stresshormone und depressive Symptome?

Hintergrund: Eine negative Geburtserfahrung erhöht das Risiko, eine postpartale Depression (PPD) zu entwickeln. Veränderungen der Hypothalamus-Hypophysen-Nebennieren-Achse (HHNA) werden als ein zugrundeliegender Mechanismus diskutiert. Bisher gibt es nur wenig Forschung zu dem Zusammenhang zwischen negativen Geburtserfahrungen und langfristig integrierten Glukokortikoiden. Ziel der vorliegenden Arbeit war zu untersuchen, ob objektive und subjektive Geburtserfahrungen mütterliche Glukokortikoide, gemessen anhand der Haarsegmentanalyse, vor-hersagen können. Methoden: Acht Wochen nach der Geburt wurden Haarproben von 257 Müttern entnommen, die in der prospektiven Kohortenstudie DREAMHAIR teilnahmen. Die Haar-Glukokortikoide wurden in den kopfhautnahen 2cm Haarsegmenten mittels der Flüssigchromatographie-Massenspektrometrie quantifiziert. Die analysierten Haarsträhnen spiegeln die Stresshormonkonzentrationen von der Geburt bis zu zwei Monaten nach der Entbindung wider. Die objektive und subjektive Geburtserfahrung sowie die PPD-Symptome wurden mittels etablierter Fragebögen gemessen. Ergebnisse: Die Geburtserfahrung war kein signifikanter Prädiktor für Cortisol oder Cortisone und Letztere sagten PPD-Symptome nicht signifikant vorher. Allerdings sagte eine negative objektive und subjektive Geburtserfahrung eine signifikant höhere Cortisol/Cortisone Ratio voraus und die Cortisol/Cortisone Ratio wiederum war ein signifikanter Prädiktor von PPD-Symptomen. Der Zusammenhang zwischen einer subjektiven negativen Geburtserfahrung und PPD-Symptomen wurde teilweise durch die Cortisol/Cortisone Ratio erklärt. Schlussfolgerungen: Die Ergebnisse legen nahe, dass eine negative Geburtserfahrung mit einer höheren mütterlichen Cortisol/Cortisone Ratio assoziiert ist. Insbesondere die subjektive Geburtserfahrung ist ein wesentlicher Risikofaktor für Veränderungen des Glukokortikoid-Stoffwechsels, welche wiederum PPD-Symptome vorhersagen. Unsere Studie deutet darauf hin, dass die Cortisol/Cortisone Ratio ein vielversprechender Biomarker sein könnte, um Frauen mit einem erhöhten Risiko für die Entwicklung einer PPD zu identifizieren.:Theoretischer Hintergrund Methoden Diskussio

Cetuximab Plus Carboplatin and Paclitaxel With or Without Bevacizumab Versus Carboplatin and Paclitaxel With or Without Bevacizumab in Advanced NSCLC (SWOG S0819): A Randomised, Phase 3 Study

Background EGFR antibodies have shown promise in patients with advanced non-small-cell lung cancer (NSCLC), particularly with squamous cell histology. We hypothesised that EGFR copy number by fluorescence in-situ hybridisation (FISH) can identify patients most likely to benefit from these drugs combined with chemotherapy and we aimed to explore the activity of cetuximab with chemotherapy in patients with advanced NSCLC who are EGFR FISH-positive. Methods We did this open-label, phase 3 study (SWOG S0819) at 277 sites in the USA and Mexico. We randomly assigned (1:1) eligible patients with treatment-naive stage IV NSCLC to receive paclitaxel (200 mg/m 2; every 21 days) plus carboplatin (area under the curve of 6 by modified Calvert formula; every 21 days) or carboplatin plus paclitaxel and bevacizumab (15 mg/kg; every 21 days), either with cetuximab (250 mg/m 2 weekly after loading dose; cetuximab group) or without (control group), stratified by bevacizumab treatment, smoking status, and M-substage using a dynamic-balancing algorithm. Co-primary endpoints were progression-free survival in patients with EGFR FISH-positive cancer and overall survival in the entire study population. We analysed clinical outcomes with the intention-to-treat principle and analysis of safety outcomes included patients who received at least one dose of study drug. This study is registered with ClinicalTrials.gov (number NCT00946712). Findings Between Aug 13, 2009, and May 30, 2014, we randomly assigned 1313 patients to the control group (n=657; 277 with bevacizumab and 380 without bevacizumab in the intention-to-treat population) or the cetuximab group (n=656; 283 with bevacizumab and 373 without bevacizumab in the intention-to-treat population). EGFR FISH was assessable in 976 patients and 400 patients (41%) were EGFR FISH-positive. The median follow-up for patients last known to be alive was 35·2 months (IQR 22·9–39·9). After 194 progression-free survival events in the cetuximab group and 198 in the control group in the EGFR FISH-positive subpopulation, progression-free survival did not differ between treatment groups (hazard ratio [HR] 0·92, 95% CI 0·75–1·12; p=0·40; median 5·4 months [95% CI 4·5–5·7] vs 4·8 months [3·9–5·5]). After 570 deaths in the cetuximab group and 593 in the control group, overall survival did not differ between the treatment groups in the entire study population (HR 0·93, 95% CI 0·83–1·04; p=0·22; median 10·9 months [95% CI 9·5–12·0] vs 9·2 months [8·7–10·3]). In the prespecified analysis of EGFR FISH-positive subpopulation with squamous cell histology, overall survival was significantly longer in the cetuximab group than in the control group (HR 0·58, 95% CI 0·36–0·86; p=0·0071), although progression-free survival did not differ between treatment groups in this subgroup (0·68, 0·46–1·01; p=0·055). Overall survival and progression-free survival did not differ among patients who were EGFR FISH non-positive with squamous cell histology (HR 1·04, 95% CI 0·78–1·40; p=0·77; and 1·02, 0·77–1·36; p=0·88 respectively) or patients with non-squamous histology regardless of EGFR FISH status (for EGFR FISH-positive 0·88, 0·68–1·14; p=0·34; and 0·99, 0·78–1·27; p=0·96; respectively; and for EGFR FISH non-positive 1·00, 0·85–1·17; p=0·97; and 1·03, 0·88–1·20; p=0·69; respectively). The most common grade 3–4 adverse events were decreased neutrophil count (210 [37%] in the cetuximab group vs 158 [25%] in the control group), decreased leucocyte count (103 [16%] vs 74 [20%]), fatigue (81 [13%] vs 74 [20%]), and acne or rash (52 [8%] vs one [\u3c 1%]). 59 (9%) patients in the cetuximab group and 31 (5%) patients in the control group had severe adverse events. Deaths related to treatment occurred in 32 (6%) patients in the cetuximab group and 13 (2%) patients in the control group. Interpretation Although this study did not meet its primary endpoints, prespecified subgroup analyses of patients with EGFR FISH-positive squamous-cell carcinoma cancers are encouraging and support continued evaluation of anti-EGFR antibodies in this subpopulation

TURBOMOLE: Today and Tomorrow

TURBOMOLE is a highly optimized software suite for large-scale quantum-chemical and materials science simulations of molecules, clusters, extended systems, and periodic solids. TURBOMOLE uses Gaussian basis sets and has been designed with robust and fast quantum-chemical applications in mind, ranging from homogeneous and heterogeneous catalysis to inorganic and organic chemistry and various types of spectroscopy, light–matter interactions, and biochemistry. This Perspective briefly surveys TURBOMOLE’s functionality and highlights recent developments that have taken place between 2020 and 2023, comprising new electronic structure methods for molecules and solids, previously unavailable molecular properties, embedding, and molecular dynamics approaches. Select features under development are reviewed to illustrate the continuous growth of the program suite, including nuclear electronic orbital methods, Hartree–Fock-based adiabatic connection models, simplified time-dependent density functional theory, relativistic effects and magnetic properties, and multiscale modeling of optical properties

Therapeutic targeting of ependymoma as informed by oncogenic enhancer profiling

Genomic sequencing has driven precision-based oncology therapy; however, the genetic drivers of many malignancies remain unknown or non-targetable, so alternative approaches to the identification of therapeutic leads are necessary. Ependymomas are chemotherapy-resistant brain tumours, which, despite genomic sequencing, lack effective molecular targets. Intracranial ependymomas are segregated on the basis of anatomical location (supratentorial region or posterior fossa) and further divided into distinct molecular subgroups that reflect differences in the age of onset, gender predominance and response to therapy1,2,3. The most common and aggressive subgroup, posterior fossa ependymoma group A (PF-EPN-A), occurs in young children and appears to lack recurrent somatic mutations2. Conversely, posterior fossa ependymoma group B (PF-EPN-B) tumours display frequent large-scale copy number gains and losses but have favourable clinical outcomes1,3. More than 70% of supratentorial ependymomas are defined by highly recurrent gene fusions in the NF-κB subunit gene RELA (ST-EPN-RELA), and a smaller number involve fusion of the gene encoding the transcriptional activator YAP1 (ST-EPN-YAP1)1,3,4. Subependymomas, a distinct histologic variant, can also be found within the supratetorial and posterior fossa compartments, and account for the majority of tumours in the molecular subgroups ST-EPN-SE and PF-EPN-SE. Here we describe mapping of active chromatin landscapes in 42 primary ependymomas in two non-overlapping primary ependymoma cohorts, with the goal of identifying essential super-enhancer-associated genes on which tumour cells depend. Enhancer regions revealed putative oncogenes, molecular targets and pathways; inhibition of these targets with small molecule inhibitors or short hairpin RNA diminished the proliferation of patient-derived neurospheres and increased survival in mouse models of ependymomas. Through profiling of transcriptional enhancers, our study provides a framework for target and drug discovery in other cancers that lack known genetic drivers and are therefore difficult to treat.This work was supported by an Alex's Lemonade Stand Young Investigator Award (S.C.M.), The CIHR Banting Fellowship (S.C.M.), The Cancer Prevention Research Institute of Texas (S.C.M., RR170023), Sibylle Assmus Award for Neurooncology (K.W.P.), the DKFZ-MOST (Ministry of Science, Technology & Space, Israel) program in cancer research (H.W.), James S. McDonnell Foundation (J.N.R.) and NIH grants: CA154130 (J.N.R.), R01 CA169117 (J.N.R.), R01 CA171652 (J.N.R.), R01 NS087913 (J.N.R.) and R01 NS089272 (J.N.R.). R.C.G. is supported by NIH grants T32GM00725 and F30CA217065. M.D.T. is supported by The Garron Family Chair in Childhood Cancer Research, and grants from the Pediatric Brain Tumour Foundation, Grand Challenge Award from CureSearch for Children’s Cancer, the National Institutes of Health (R01CA148699, R01CA159859), The Terry Fox Research Institute and Brainchild. M.D.T. is also supported by a Stand Up To Cancer St. Baldrick’s Pediatric Dream Team Translational Research Grant (SU2C-AACR-DT1113)

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives