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Phytocytokines are signaling peptides that alert plant cells of danger. However, the downstream responses triggered by phytocytokines and their effect on plant survival are still largely unknown. Here, we have identified three biologically active maize orthologues of phytocytokines previously described in other plants. The maize phytocytokines show common features with microbe-associated molecular patterns (MAMPs), including the induction of immune-related genes and activation of papain-like cysteine proteases. In contrast to MAMPs, phytocytokines do not promote cell death in the presence of wounding. In infection assays with two fungal pathogens, we found that phytocytokines affect the development of disease symptoms, likely due to the activation of phytohormonal pathways. Collectively, our results show that phytocytokines and MAMPs trigger unique and antagonistic features of immunity. We propose a model in which phytocytokines activate immune responses partially similar to MAMPs but, in contrast to microbial signals, they act as danger and survival molecules to the surrounding cells. Future studies will focus on the components determining the divergence of signaling outputs upon phytocytokine activation. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Particle accelerators play a crucial role in scientific research, enabling the study of fundamental physics and materials science, as well as having important medical applications. This study proposes a novel graph learning approach to classify operational beamline configurations as good or bad. By considering the relationships among beamline elements, we transform data from components into a heterogeneous graph. We propose to learn from historical, unlabeled data via our self-supervised training strategy along with fine-tuning on a smaller, labeled dataset. Additionally, we extract a low-dimensional representation from each configuration that can be visualized in two dimensions. Leveraging our ability for classification, we map out regions of the low-dimensional latent space characterized by good and bad configurations, which in turn can provide valuable feedback to operators. This research demonstrates a paradigm shift in how complex, many-dimensional data from beamlines can be analyzed and leveraged for accelerator operations.

Cyanobacteria are a promising platform for the production of the triterpene squalene (C30), a precursor for all plant and animal sterols, and a highly attractive intermediate towards triterpenoids, a large group of secondary plant metabolites. Synechocystis sp. PCC 6803 natively produces squalene from CO2 through the MEP pathway. Based on the predictions of a constraint-based metabolic model, we took a systematic overexpression approach to quantify native Synechocystis gene’s impact on squalene production in a squalene-hopene cyclase gene knock-out strain (Δshc). Our in silico analysis revealed an increased flux through the Calvin-Benson-Bassham cycle in the Δshc mutant compared to the wildtype, including the pentose phosphate pathway, as well as lower glycolysis, while the tricarboxylic acid cycle predicted to be downregulated. Further, all enzymes of the MEP pathway and terpenoid synthesis, as well as enzymes from the central carbon metabolism, Gap2, Tpi and PyrK, were predicted to positively contribute to squalene production upon their overexpression. Each identified target gene was integrated into the genome of Synechocystis Δshc under the control of the rhamnose-inducible promoter Prha. Squalene production was increased in an inducer concentration dependent manner through the overexpression of most predicted genes, which are genes of the MEP pathway, ispH, ispE, and idi, leading to the greatest improvements. Moreover, we were able to overexpress the native squalene synthase gene (sqs) in Synechocystis Δshc, which reached the highest production titer of 13.72 mg l-1 reported for squalene in Synechocystis sp. PCC 6803 so far, thereby providing a promising and sustainable platform for triterpene production.

Context: Active surveillance (AS) of biopsy-proven renal oncocytomas may reduce overtreatment. However, on biopsy, the risk of misdiagnosis owing principally to entities with peculiar hybrids and overlap morphology, and phenotypes argues for early intervention. Objective: To assess the benefit and harm of AS in biopsy-proven renal oncocytoma. Evidence acquisition: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). We systematically searched PubMed, Scopus, and Web of Science databases from September 26 up to October 2021, for studies that analyzed the outcomes of AS in patients with biopsy-proven renal oncocytoma. Evidence synthesis: A total of ten studies with 633 patients met our inclusion criteria and were included for analysis. After a median follow-up of 34.5 mo (95% confidence interval [CI] 30.6–38.4), the overall definitive treatment rate from AS to definitive treatment was 17.3% (n = 75/433, six studies). The pooled pathological agreement between the initial renal mass biopsy and the surgical pathology report was 91.1%. The main indications for surgery during follow-up were rapid tumor growth and patient request. The pooled median growth rate was 1.55 mm/yr (95% CI 0.9–2.2). No metastasis or death related to renal oncocytoma was reported. Conclusions: Annual tumor growth of biopsy-proven renal oncocytoma is low. AS is oncologically safe, with favorable compliance of patients. Crossover to definitive treatment revealed a strong concordance between biopsy and final pathology. Further studies on the long-term outcomes of AS are needed. Patient summary: In this study, we examined the benefit and harm of active surveillance (AS) in biopsy-proven oncocytoma. Based on the available data, AS appears oncologically safe and may represent a promising alternative to immediate treatment. Patients should be included in AS decision discussions.

Aldol reactions belong to the most important methods for carbon–carbon bond formation and are also involved in one of the most astonishing biosynthetic processes: the biosynthesis of polyketides governed by an extraordinarily sophisticated enzymatic machinery. In contrast to the typical linear or convergent strategies followed in chemical synthesis, this late-stage catalysis concept allows Nature to assemble intermediates that are diversified into a broad range of scaffolds, which assume various crucial biological functions. To transfer this concept to small-molecule catalysis to access products beyond the natural systems, a stepwise approach to differentiate increasingly complex substrates was followed by investigating arene-forming polyketide cyclizations. An outline of our efforts to develop and apply these concepts are presented herein.

RESUMO Introdução A terminologia para disfunção neurogênica do trato urinário inferior em adultos (DNTUIA) deve ser definida e organizada com base clínica em um relatório de consenso. Métodos Este relatório foi criado por um Grupo de Trabalho sob o endosso e diretrizes do Standardization Steering Committee (SSC) da International Continence Society (ICS), auxiliado em intervalos por julgadores externos. Todas as definições relevantes para DNTUIA foram atualizadas com base em pesquisas nos últimos 14 anos. Um extenso processo de 18 rodadas de revisão interna e externa foi realizado para examinar exaustivamente cada definição, com tomada de decisão pela opinião coletiva (consenso). Resultados O Relatório de Terminologia para a DNTUIA, englobando 97 definições (42 novas e oito modificadas), foi desenvolvido. Este relatório é clinicamente baseado nos diagnósticos definidos mais comuns. Clareza e facilidade de uso têm sido os principais objetivos para torná-lo interpretável por profissionais e pessoas em treinamento em todos os diferentes grupos envolvidos não só na disfunção do trato urinário inferior, mas também em muitas outras especialidades médicas. Conclusão Baseado no consenso, o Relatório de Terminologia para a DNTUIA foi produzido para auxiliar na pesquisa e na prática clínica.

We present the initial results of a proof-of-concept ‘smart alarm’ for the Continuous Electron Beam Accelerator Facility injector beamline at Jefferson Lab. To minimize machine downtime and improve operational efficiency, an autonomous alarm system able to identify and diagnose unusual machine states is needed. Our approach leverages a trained neural network capable of alerting operators (a) when an anomalous condition exists in the beamline and (b) identifying the element setting that is the root cause. The tool is based on an inverse model that maps beamline readings (diagnostic readbacks) to settings (beamline attributes operators can modify). The model takes as input readings from the machine and computes machine settings which are compared to control setpoints. Instances where predictions differ from setpoints by a user-defined threshold are flagged as anomalous. Given data corresponding to 354 anomalous injector configurations, the model can narrow the root cause of an anomalous condition to three potential candidates with 94.6% accuracy. Furthermore, compared to the current method of identifying anomalous conditions which raises an alarm when machine parameters drift outside their normal tolerances, the data-driven model can identify 83% more anomalous conditions.

BACKGROUND: Burnout syndrome is a result of chronic stress, characterized by emotional exhaustion, depersonalization, and a sense of low professional accomplishment. It affects workers under extreme responsibility or those who care for individuals at risk, including anesthesiologists who distanced themselves from the work, patients and colleagues because they feel safer in maintaining indifference. OBJECTIVE: To evaluate the prevalence of burnout syndrome and the intensity of its components and identify the characteristics of those with the syndrome among anesthesiologists in the Federal District. METHOD: A cross-sectional study was carried out with 241 anesthesiologists enrolled in the Society of Anesthesiology of the Federal District. A self-administered questionnaire was used, which included the Maslach Burnout Inventory, demographic, professional, and leisure data. RESULTS: Of the 134 completed questionnaires (55.8%), there was a predominance of male (65.6%), aged 30-50 years (67.9%). Significant lower levels of job satisfaction (47.7%), depersonalization (28.3%), and emotional exhaustion (23.1%) were found. Burnout syndrome showed a prevalence of 10.4%, occurring mainly in men (64.2%), aged 30-50 years (64.2%), with over 10 years of experience (64.2%), working in night shifts (71.4%), sedentary (57.1%), and not taking courses unrelated to medicine (78.5%). Of the participants, 50.7% had at least one of the three criteria to develop the syndrome and only 8.2% have a low risk to manifest it. CONCLUSION: The prevalence of burnout is relevant among anesthesiologists in the Federal District. It is advisable to seek strategies for labor restructuring to reduce stress factors and loss of motivation and increase job satisfaction.