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A high-throughput assay is used to analyse 40,000 potential extracellular domain interactions of a large family of plant cell surface receptors (LRR-RKs) and provide a cell surface interaction network for these receptors. A network of cell surface interactions Cell surface receptors mediate communication between the interior of a cell and its external environment. Specifically, the extracellular domains (ECDs) of such receptors interact with external molecules. It is less clear how interactions between ECDs of different receptors help to form receptor complexes for signal transduction. Youssef Belkhadir and colleagues investigate systems-level organization of leucine-rich repeat receptor kinases (LRR-RKs)—a large family of plant cell surface receptors with roles in processes including plant defence and development. The authors use a high-throughput assay to study 40,000 potential ECD interactions. They develop a cell surface interaction network for these receptors and study its dynamics. The team demonstrate the power of this network for detecting biologically relevant interactions by predicting and validating the function of previously uncharacterized LRR-RKs in plant growth and immunity. The cells of multicellular organisms receive extracellular signals using surface receptors. The extracellular domains (ECDs) of cell surface receptors function as interaction platforms, and as regulatory modules of receptor activation 1 , 2 . Understanding how interactions between ECDs produce signal-competent receptor complexes is challenging because of their low biochemical tractability 3 , 4 . In plants, the discovery of ECD interactions is complicated by the massive expansion of receptor families, which creates tremendous potential for changeover in receptor interactions 5 . The largest of these families in Arabidopsis thaliana consists of 225 evolutionarily related leucine-rich repeat receptor kinases (LRR-RKs) 5 , which function in the sensing of microorganisms, cell expansion, stomata development and stem-cell maintenance 6 , 7 , 8 , 9 . Although the principles that govern LRR-RK signalling activation are emerging 1 , 10 , the systems-level organization of this family of proteins is unknown. Here, to address this, we investigated 40,000 potential ECD interactions using a sensitized high-throughput interaction assay 3 , and produced an LRR-based cell surface interaction network (CSI LRR ) that consists of 567 interactions. To demonstrate the power of CSI LRR for detecting biologically relevant interactions, we predicted and validated the functions of uncharacterized LRR-RKs in plant growth and immunity. In addition, we show that CSI LRR operates as a unified regulatory network in which the LRR-RKs most crucial for its overall structure are required to prevent the aberrant signalling of receptors that are several network-steps away. Thus, plants have evolved LRR-RK networks to process extracellular signals into carefully balanced responses.

Spatial organization of signalling events of the phytohormone auxin is fundamental for maintaining a dynamic transition from plant stem cells to differentiated descendants. The cambium, the stem cell niche mediating wood formation, fundamentally depends on auxin signalling but its exact role and spatial organization is obscure. Here we show that, while auxin signalling levels increase in differentiating cambium descendants, a moderate level of signalling in cambial stem cells is essential for cambium activity. We identify the auxin-dependent transcription factor ARF5/MONOPTEROS to cell-autonomously restrict the number of stem cells by directly attenuating the activity of the stem cell-promoting WOX4 gene. In contrast, ARF3 and ARF4 function as cambium activators in a redundant fashion from outside of WOX4 -expressing cells. Our results reveal an influence of auxin signalling on distinct cambium features by specific signalling components and allow the conceptual integration of plant stem cell systems with distinct anatomies. Auxin activity controls plant stem cell function. Here the authors show that in the cambium, moderate auxin activity restricts cambial stem cell number via ARF5-dependent repression of the stem‐cell‐promoting factor WOX4, while ARF3 and ARF4 promote cambial activity outside of the WOX4‐expression domain.

In this Letter, an incorrect version of the Supplementary Information file was inadvertently used, which contained several errors. The details of references 59–65 were missing from the end of the Supplementary Discussion section on page 4. In addition, the section ‘Text 3. Y2H on ICD interactions’ incorrectly referred to ‘Extended Data Fig. 4d’ instead of ‘Extended Data Fig. 3d’ on page 3. Finally, the section ‘Text 4. Interaction network analysis’ incorrectly referred to ‘Fig. 1b and Extended Data Fig. 6’ instead of ‘Fig. 2b and Extended Data Fig. 7’ on page 3. These errors have all been corrected in the Supplementary Information.

Plants use surface receptors to perceive information about many aspects of their local environment. These receptors physically interact to form both steady state and signalling competent complexes. The signalling events downstream of receptor activation impact both plant developmental and immune responses. Here, we present a comprehensive study of the physical interactions between the extracellular domains of leucine-rich repeat receptor kinases (LRR-RKs) in Arabidopsis. Using a sensitized assay, we tested reciprocal interactions among 200 of the 225 Arabidopsis LRR-RKs for a total search space of 40,000 interactions. Applying a stringent statistical cut-off and requiring that interactions performed well in both bait-prey and prey-bait orientations resulted in a high-confidence set of 567 bidirectional interactions. Additionally, we identified a total of 2,586 unidirectional interactions, which passed our stringent statistical cut-off in only one orientation. These datasets will guide further investigation into the regulatory roles of LRR-RKs in plant developmental and immune signalling decisions.

Spatial organization of signaling events of the phytohormone auxin is fundamental for maintaining a dynamic transition from plant stem cells to differentiated descendants. The cambium, the stem cell niche mediating wood formation, fundamentally depends on auxin signaling but its exact role and spatial organization is obscure. Here, we show that, while auxin signaling levels increase in differentiating cambium descendants, a moderate level of signaling in cambial stem cells is essential for cambium activity. We identify the auxin-dependent transcription factor ARF5/MONOPTEROS to cell-autonomously restrict the number of stem cells by attenuating the activity of the stem cell promoting WOX4 gene. In contrast, ARF3 and ARF4 function as cambium activators in a redundant fashion from outside of WOX4-expressing cells. Our results reveal an influence of auxin signaling on distinct cambium features by specific signaling components and allow the conceptual integration of plant stem cell systems with distinct anatomies.

Background Developing predictive models for precision psychiatry is challenging because of unavailability of the necessary data: extracting useful information from existing electronic health record (EHR) data is not straightforward, and available clinical trial datasets are often not representative for heterogeneous patient groups. The aim of this study was constructing a natural language processing (NLP) pipeline that extracts variables for building predictive models from EHRs. We specifically tailor the pipeline for extracting information on outcomes of psychiatry treatment trajectories, applicable throughout the entire spectrum of mental health disorders (“transdiagnostic”). Methods A qualitative study into beliefs of clinical staff on measuring treatment outcomes was conducted to construct a candidate list of variables to extract from the EHR. To investigate if the proposed variables are suitable for measuring treatment effects, resulting themes were compared to transdiagnostic outcome measures currently used in psychiatry research and compared to the HDRS (as a gold standard) through systematic review, resulting in an ideal set of variables. To extract these from EHR data, a semi-rule based NLP pipeline was constructed and tailored to the candidate variables using Prodigy. Classification accuracy and F1-scores were calculated and pipeline output was compared to HDRS scores using clinical notes from patients admitted in 2019 and 2020. Results Analysis of 34 questionnaires answered by clinical staff resulted in four themes defining treatment outcomes: symptom reduction, general well-being, social functioning and personalization. Systematic review revealed 242 different transdiagnostic outcome measures, with the 36-item Short-Form Survey for quality of life (SF36) being used most consistently, showing substantial overlap with the themes from the qualitative study. Comparing SF36 to HDRS scores in 26 studies revealed moderate to good correlations (0.62—0.79) and good positive predictive values (0.75—0.88). The NLP pipeline developed with notes from 22,170 patients reached an accuracy of 95 to 99 percent (F1 scores: 0.38 – 0.86) on detecting these themes, evaluated on data from 361 patients. Conclusions The NLP pipeline developed in this study extracts outcome measures from the EHR that cater specifically to the needs of clinical staff and align with outcome measures used to detect treatment effects in clinical trials.

ObjectivesThe choice of drug treatment in advanced soft tissue sarcoma (STS) continues to be a challenge regarding efficacy, quality of life (QoL) and toxicity. Unlike other cancer types, where integrating patient-reported outcomes (PRO) has proven to be beneficial for QoL, there is no such evidence in patients with STS as of now. The YonLife trial aimed to explore the effect of a tailored multistep intervention on QoL, symptoms and survival in patients with advanced STS undergoing treatment with trabectedin as well as identifying predictors of QoL.DesignYonLife is a cluster-randomised, open-label, proof-of-concept study. The intervention incorporates electronic PRO assessment, a case vignette and expert-consented treatment recommendations.ParticipantsSix hospitals were randomised to the control arm (CA) or interventional arm (IA). Seventy-nine patients were included of whom 40 were analysed as per-protocol analysis set.Primary and secondary outcome measuresThe primary end point was the change of Functional Assessment for Cancer Therapy (FACT-G) total score after 9 weeks. Secondary outcomes included QoL (FACT-G subscales), anorexia and cachexia (Functional Assessment of Anorexia/Cachexia Therapy (FAACT)), symptoms (MD Anderson Symptom Inventory (MDASI)), anxiety and depression (HADS), pain intensity and interference (Brief Pain Inventory (BPI)) and survival assessment.ResultsAfter 9 weeks of treatment, QoL declined less in the IA (ΔFACT-G total score: −2.4, 95% CI: −9.2 to 4.5) as compared with CA (ΔFACT-G total score: −3.9; 95% CI:−11.3 to 3.5; p=0.765). In almost all FACT-G subscales, average declines were lower in IA, but without reaching statistical significance. Smaller adverse trends between arms were observed for MDASI, FAACT, HADS and BPI scales. These trends failed to reach statistical significance. Overall mean survival was longer in IA (648 days) than in CA (389 days, p=0.110). QoL was predicted by symptom severity, symptom interference, depression and anxiety.ConclusionOur data suggest a potentially favourable effect of an electronic patient-reported outcomes based intervention on QoL that needs to be reappraised in confirmatory studies.Trial registration numberClinicalTrials.gov Identifier (NCT02204111).

PurposeThe treatment landscape in metastatic renal cell carcinoma (mRCC) has evolved dramatically in recent years. Within the German guideline committee for RCC we evaluated current medical treatments and gave recommendations.MethodsA systematic review of published evidence for medical treatment of mRCC was performed (July 2016–August 2019) to cover the duration from last guideline update in 2016. Evidence was graded according to SIGN (http://www.sign.ac.uk/pdf/sign50.pdf). Recommendations were made on the basis of a nominal group work with consensus approach and included patient advocates and shareholder of the German RCC treatment landscape. Each recommendation was graded according to its strength as strong recommendation (A) or recommendation (B). Expert statements were given, where appropriate. ResultsStrong first-line recommendations (IA) exist for axitinib + pembrolizumab (all risk categories) and ipilimumab + nivolumab (intermediate or poor risk only). Axitinib + avelumab is a recommended first-line treatment across patients with any risk category (IB). In patients who are not candidates for immune check point inhibitor (ICI) combinations, targeted agents should be offered as an alternative treatment. Subsequent treatment after ICI-based combinations remain ill-defined and no standard of care can be formulated.ConclusionICI-based combinations are the first-line standard of care and should be considered accordingly. There is an unmet medical need for pivotal studies that define novel standards in patients with failure of ICI-based combinations.

Only 2–5% of patients who have a stroke receive thrombolytic treatment, mainly because of delay in reaching the hospital. We aimed to assess the efficacy of a new approach of diagnosis and treatment starting at the emergency site, rather than after hospital arrival, in reducing delay in stroke therapy. We did a randomised single-centre controlled trial to compare the time from alarm (emergency call) to therapy decision between mobile stroke unit (MSU) and hospital intervention. For inclusion in our study patients needed to be aged 18–80 years and have one or more stroke symptoms that started within the previous 2·5 h. In accordance with our week-wise randomisation plan, patients received either prehospital stroke treatment in a specialised ambulance (equipped with a CT scanner, point-of-care laboratory, and telemedicine connection) or optimised conventional hospital-based stroke treatment (control group) with a 7 day follow-up. Allocation was not masked from patients and investigators. Our primary endpoint was time from alarm to therapy decision, which was analysed with the Mann-Whitney U test. Our secondary endpoints included times from alarm to end of CT and to end of laboratory analysis, number of patients receiving intravenous thrombolysis, time from alarm to intravenous thrombolysis, and neurological outcome. We also assessed safety endpoints. This study is registered with ClinicalTrials.gov, number NCT00153036. We stopped the trial after our planned interim analysis at 100 of 200 planned patients (53 in the prehospital stroke treatment group, 47 in the control group), because we had met our prespecified criteria for study termination. Prehospital stroke treatment reduced the median time from alarm to therapy decision substantially: 35 min (IQR 31–39) versus 76 min (63–94), p<0·0001; median difference 41 min (95% CI 36–48 min). We also detected similar gains regarding times from alarm to end of CT, and alarm to end of laboratory analysis, and to intravenous thrombolysis for eligible ischaemic stroke patients, although there was no substantial difference in number of patients who received intravenous thrombolysis or in neurological outcome. Safety endpoints seemed similar across the groups. For patients with suspected stroke, treatment by the MSU substantially reduced median time from alarm to therapy decision. The MSU strategy offers a potential solution to the medical problem of the arrival of most stroke patients at the hospital too late for treatment. Ministry of Health of the Saarland, Germany, the Werner-Jackstädt Foundation, the Else-Kröner-Fresenius Foundation, and the Rettungsstiftung Saar.

Treatment concepts in oncology are becoming increasingly personalized and diverse. Successively, changes in standards of care mandate continuous monitoring of patient pathways and clinical outcomes based on large, representative real-world data. The German Cancer Consortium’s (DKTK) Clinical Communication Platform (CCP) provides such opportunity. Connecting fourteen university hospital-based cancer centers, the CCP relies on a federated IT-infrastructure sourcing data from facility-based cancer registry units and biobanks. Federated analyses resulted in a cohort of 600,915 patients, out of which 232,991 were incident since 2013 and for which a comprehensive documentation is available. Next to demographic data (i.e., age at diagnosis: 2.0% 0–20 years, 8.3% 21–40 years, 30.9% 41–60 years, 50.1% 61–80 years, 8.8% 81+ years; and gender: 45.2% female, 54.7% male, 0.1% other) and diagnoses (five most frequent tumor origins: 22,523 prostate, 18,409 breast, 15,575 lung, 13,964 skin/malignant melanoma, 9005 brain), the cohort dataset contains information about therapeutic interventions and response assessments and is connected to 287,883 liquid and tissue biosamples. Focusing on diagnoses and therapy-sequences, showcase analyses of diagnosis-specific sub-cohorts (pancreas, larynx, kidney, thyroid gland) demonstrate the analytical opportunities offered by the cohort’s data. Due to its data granularity and size, the cohort is a potential catalyst for translational cancer research. It provides rapid access to comprehensive patient groups and may improve the understanding of the clinical course of various (even rare) malignancies. Therefore, the cohort may serve as a decisions-making tool for clinical trial design and contributes to the evaluation of scientific findings under real-world conditions.