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The Mangshan pit viper, Protobothrops mangshanensis, is a rare, highly endangered snake native to the mountainous regions of Hunan Province in China. Snakes possess abdominal scent glands, which have been chemically studied in several species. These glands can contain various lipids and peptides, but very often also complex mixtures of carboxylic acids. We report here the occurrence of novel methyl-branched unsaturated acids found in the secretions of six captive individuals living in a zoo. The structures of these compounds, 4.6-dimethylalk-5-enoates in a homologous series from C11–C16, were characterized by GC–MS and GC–IR analysis and various microderivatization reactions including hydrogenation and esterification leading to methyl and pyridylmethyl esters. In addition, dimethyloxazoline formation helped to localize the double bond. The synthesis of methyl 4,6-dimethyldodec-5-enoate allowed the correct assignment of structures and showed the (E)-configuration of the double bond for the major naturally occurring diastereomers. These acids occur in small amounts compared to the major glandular components, cholesterol, and 1-O-hexadecylglycerol, as well as other common long-chain alcohols and amides. Although a general defensive function has been proposed for snake abdominal scent glands, the specific chemistry and moderate amounts of acids reported here may suggest a function in chemical signaling for the Mangshan pit viper. In addition, proline-containing diketopiperazines were identified for the first time in snake scent glands, although an artificial formation from amino acids likely present in the secretion cannot be excluded.

Abstract Desensitisation of the mu-opioid receptor (MOR) is proposed to underlie the initiation of opioid analgesic tolerance and previous work has shown that agonist-induced phosphorylation of the MOR C-tail contributes to this desensitisation. Moreover, phosphorylation is important for β-arrestin recruitment to the receptor, and ligands of different efficacies induce distinct phosphorylation barcodes. The C-tail 370TREHPSTANT379 motif harbours Ser/Thr residues important for these regulatory functions. 375Ser is the primary phosphorylation site of a ligand-dependent, hierarchical, and sequential process, whereby flanking 370Thr, 376Thr and 379Thr get subsequently and rapidly phosphorylated. Here we used GRK KO cells, phosphosite specific antibodies and site-directed mutagenesis to evaluate the contribution of the different GRK subfamilies to ligand-induced phosphorylation barcodes and β-arrestin2 recruitment. We show that both GRK2/3 and GRK5/6 subfamilies promote phosphorylation of 370Thr and 375Ser. Importantly, only GRK2/3 induce phosphorylation of 376Thr and 379Thr, and we identify these residues as key sites to promote robust β-arrestin recruitment to the MOR. These data provide insight into the mechanisms of MOR regulation and suggest that the cellular complement of GRK subfamilies plays an important role in determining the tissue responses of opioid agonists.

Objective Clinical narratives provide comprehensive patient information. Achieving interoperability involves mapping relevant details to standardized medical vocabularies. Typically, natural language processing divides this task into named entity recognition (NER) and medical concept normalization (MCN). State-of-the-art results require supervised setups with abundant training data. However, the limited availability of annotated data due to sensitivity and time constraints poses challenges. This study addressed the need for unsupervised medical concept annotation (MCA) to overcome these limitations and support the creation of annotated datasets. Method We use an unsupervised SapBERT -based bi-encoder model to analyze n-grams from narrative text and measure their similarity to SNOMED CT concepts. At the end, we apply a syntactical re-ranker. For evaluation, we use the semantic tags of SNOMED CT candidates to assess the NER phase and their concept IDs to assess the MCN phase. The approach is evaluated with both English and German narratives. Result Without training data, our unsupervised approach achieves an F1 score of 0.765 in English and 0.557 in German for MCN. Evaluation at the semantic tag level reveals that “disorder” has the highest F1 scores, 0.871 and 0.648 on English and German datasets. Furthermore, the MCA approach on the semantic tag “disorder” shows F1 scores of 0.839 and 0.696 in English and 0.685 and 0.437 in German for NER and MCN, respectively. Conclusion This unsupervised approach demonstrates potential for initial annotation (pre-labeling) in manual annotation tasks. While promising for certain semantic tags, challenges remain, including false positives, contextual errors, and variability of clinical language, requiring further fine-tuning.

BackgroundClinical narratives are essential components of electronic health records. The adoption of electronic health records has increased documentation time for hospital staff, leading to the use of abbreviations and acronyms more frequently. This brevity can potentially hinder comprehension for both professionals and patients. ObjectiveThis review aims to provide an overview of the types of short forms found in clinical narratives, as well as the natural language processing (NLP) techniques used for their identification, expansion, and disambiguation. MethodsIn the databases Web of Science, Embase, MEDLINE, EBMR (Evidence-Based Medicine Reviews), and ACL Anthology, publications that met the inclusion criteria were searched according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for a systematic scoping review. Original, peer-reviewed publications focusing on short-form processing in human clinical narratives were included, covering the period from January 2018 to February 2023. Short-form types were extracted, and multidimensional research methodologies were assigned to each target objective (identification, expansion, and disambiguation). NLP study recommendations and study characteristics were systematically assigned occurrence rates for evaluation. ResultsOut of a total of 6639 records, only 19 articles were included in the final analysis. Rule-based approaches were predominantly used for identifying short forms, while string similarity and vector representations were applied for expansion. Embeddings and deep learning approaches were used for disambiguation. ConclusionsThe scope and types of what constitutes a clinical short form were often not explicitly defined by the authors. This lack of definition poses challenges for reproducibility and for determining whether specific methodologies are suitable for different types of short forms. Analysis of a subset of NLP recommendations for assessing quality and reproducibility revealed only partial adherence to these recommendations. Single-character abbreviations were underrepresented in studies on clinical narrative processing, as were investigations in languages other than English. Future research should focus on these 2 areas, and each paper should include descriptions of the types of content analyzed.

During Hedgehog (Hh) signal transduction in development and disease, the atypical G protein-coupled receptor (GPCR) SMOOTHENED (SMO) communicates with GLI transcription factors by binding the protein kinase A catalytic subunit (PKA-C) and physically blocking its enzymatic activity. Here, we show that GPCR kinase 2 (GRK2) orchestrates this process during endogenous mouse and zebrafish Hh pathway activation in the primary cilium. Upon SMO activation, GRK2 rapidly relocalizes from the ciliary base to the shaft, triggering SMO phosphorylation and PKA-C interaction. Reconstitution studies reveal that GRK2 phosphorylation enables active SMO to bind PKA-C directly. Lastly, the SMO-GRK2-PKA pathway underlies Hh signal transduction in a range of cellular and in vivo models. Thus, GRK2 phosphorylation of ciliary SMO and the ensuing PKA-C binding and inactivation are critical initiating events for the intracellular steps in Hh signaling. More broadly, our study suggests an expanded role for GRKs in enabling direct GPCR interactions with diverse intracellular effectors.

Most clinical information is only available as free text. Large language models (LLMs) are increasingly applied to clinical data to streamline communication, enhance the accuracy of clinical documentation, and ultimately improve healthcare delivery. This study focuses on a corpus of anonymized clinical narratives in German. On the one hand it evaluates the use of ChatGPT for text cleansing, i.e., the automatic rephrasing of raw text into a more readable and standardized form, and on the other hand for retrieval-augmented generation (RAG). In both tasks, the final goal was medical concept normalization (MCN), i.e., the annotation of text segments with codes from a controlled vocabulary using natural language processing. We found that ChatGPT (GPT-4) significantly improves precision and recall compared to simple dictionary matching. For all scenarios, the importance of the underlying terminological basis was also demonstrated. Maximum F1 scores of 0.607, 0.735 and 0.754 (i.e, for top 1, 5 and 10 matches) were achieved through a pipeline including document cleansing, bi-encoder-based term matching based on a large domain dictionary linked to SNOMED CT, and finally re-ranking using RAG.

Abstract Background Oxygen saturation, a key indicator of COVID-19 severity, poses challenges, especially in cases of silent hypoxemia. Electronic health records (EHRs) often contain supplemental oxygen information within clinical narratives. Streamlining patient identification based on oxygen levels is crucial for COVID-19 research, underscoring the need for automated classifiers in discharge summaries to ease the manual review burden on physicians. Method We analysed text lines extracted from anonymised COVID-19 patient discharge summaries in German to perform a binary classification task, differentiating patients who received oxygen supplementation and those who did not. Various machine learning (ML) algorithms, including classical ML to deep learning (DL) models, were compared. Classifier decisions were explained using Local Interpretable Model-agnostic Explanations (LIME), which visualize the model decisions. Result Classical ML to DL models achieved comparable performance in classification, with an F-measure varying between 0.942 and 0.955, whereas the classical ML approaches were faster. Visualisation of embedding representation of input data reveals notable variations in the encoding patterns between classic and DL encoders. Furthermore, LIME explanations provide insights into the most relevant features at token level that contribute to these observed differences. Conclusion Despite a general tendency towards deep learning, these use cases show that classical approaches yield comparable results at lower computational cost. Model prediction explanations using LIME in textual and visual layouts provided a qualitative explanation for the model performance.

Abstract The salinilactones, volatile marine natural products secreted from Salinispora arenicola, feature a unique [3.1.0]‐lactone ring system and cytotoxic activities through a hitherto unknown mechanism. To find their molecular target, an activity‐based protein profiling with a salinilactone‐derived probe is applied that disclosed the protein disulfide‐isomerases (PDIs) as the dominant mammalian targets of salinilactones, and thioredoxin (TRX1) as secondary target. The inhibition of protein disulfide‐isomerase A1 (PDIA1) and TRX1 is confirmed by biochemical assays with recombinant proteins, showing that (1S,5R)‐salinilactone B is more potent than its (1R,5S)‐configured enantiomer. The salinilactones bound covalently to C53 and C397, the catalytically active cysteines of the isoform PDIA1 according to tandem mass spectrometry. Reactions with a model substrate demonstrated that the cyclopropyl group is opened by an attack of the thiol at C6. Fluorophore labeling experiments showed the cell permeability of a salinilactone‐BODIPY (dipyrrometheneboron difluoride) conjugate and its co‐localization with PDIs in the endoplasmic reticulum. The study is one of the first to pinpoint a molecular target for a volatile microbial natural product, and it demonstrates that salinilactones can achieve high selectivity despite their small size and intrinsic reactivity.

The emerging European Health Data Space (EHDS) Regulation opens new prospects for large-scale sharing and re-use of health data. Yet, the proposed regulation suffers from two important limitations: it is designed to benefit the whole population with limited consideration for individuals, and the generation of secondary datasets from heterogeneous, unlinked patient data will remain burdensome. AIDAVA, a Horizon Europe project that started in September 2022, proposes to address both shortcomings by providing patients with an AI-based virtual assistant that maximises automation in the integration and transformation of their health data into an interoperable, longitudinal health record. This personal record can then be used to inform patient-related decisions at the point of care, whether this is the usual point of care or a possible cross-border point of care. The personal record can also be used to generate population datasets for research and policymaking. The proposed solution will enable a much-needed paradigm shift in health data management, implementing a ‘curate once at patient level, use many times’ approach, primarily for the benefit of patients and their care providers, but also for more efficient generation of high-quality secondary datasets. After 15 months, the project shows promising preliminary results in achieving automation in the integration and transformation of heterogeneous data of each individual patient, once the content of the data sources managed by the data holders has been formally described. Additionally, the conceptualization phase of the project identified a set of recommendations for the development of a patient-centric EHDS, significantly facilitating the generation of data for secondary use.

Abstract Little is known about the expression of the orphan G protein-coupled receptor GPR19 at the protein level. Therefore, we developed a rabbit antibody, targeting human GPR19. After verification of the antibody specificity using GPR19-expressing cell lines and a GPR19-specific siRNA, the antibody was used for immunohistochemical staining of a variety of formalin-fixed, paraffin-embedded normal and neoplastic human tissue samples. In normal tissues, GPR19 expression was detected in a distinct cell population within the cortex, in single cells of the pancreatic islets, in intestinal ganglia, gastric chief cells, and in endocrine cells of the bronchial tract, the gastrointestinal tract, and the prostate. Among the 30 different tumour entities investigated, strong GPR19 expression was found in adenocarcinomas, typical and atypical carcinoids of the lung, and small cell lung cancer. To a lesser extent, the receptor was also present in large cell neuroendocrine carcinomas of the lung, medullary thyroid carcinomas, parathyroid adenomas, pheochromocytomas, and a subpopulation of pancreatic neuroendocrine neoplasms. In lung tumours, a negative correlation with the expression of the proliferation marker Ki-67 and a positive interrelationship with patient survival was observed. Overall, our results indicate that in adenocarcinomas and neuroendocrine tumours of the lung GPR19 may serve as a suitable diagnostic or therapeutic target.

Abstract Somatostatin receptors are clinically validated GPCR biomarkers for diagnosis and treatment of various neuroendocrine tumors (NET). Among the five somatostatin receptors, SST2 and SST3 are associated with apoptosis and cell cycle arrest, making these receptor subtypes better differentiated targets in precision oncology. In this study we performed immunohistochemistry of paired tissue microarrays containing 1125 cores, representing 43 tumor types, each stained for SST2 and SST3. A 12-point immunoreactive scoring (IRS) range was used for interpretation of the staining results. We analyzed the results twice, using the conventional positivity IRS cutoffs ≥ 3 and more stringent ≥ 6. Evaluation of receptors expression dynamics was performed for tumor-nodes-metastases (TNM) defined subgroups (ovarian and hepatocellular adenocarcinomas) as a function of their tumor stage. Our results indicate that two-thirds of tested cores exhibit clinically significant expression of at least SST2 or SST3 (IRS ≥ 6). The expression prevalence of both receptors tends to decline with tumor progression. However, an unexpected upregulation of both SST2 and SST3 reemerged in metastases suggesting conserved receptors genetic potential during tumor life cycle. We suggest that SST2 and SST3 should be further explored as potential biomarkers and therapeutic tools for maximizing the efficiency of somatostatin-based precision oncology of solid tumors beyond NET.

The translational research community, in general, and the Clinical and Translational Science Awards (CTSA) community, in particular, share the vision of repurposing EHRs for research that will improve the quality of clinical practice. Many members of these communities are also aware that electronic health records (EHRs) suffer limitations of data becoming poorly structured, biased, and unusable out of original context. This creates obstacles to the continuity of care, utility, quality improvement, and translational research. Analogous limitations to sharing objective data in other areas of the natural sciences have been successfully overcome by developing and using common ontologies. This White Paper presents the authors’ rationale for the use of ontologies with computable semantics for the improvement of clinical data quality and EHR usability formulated for researchers with a stake in clinical and translational science and who are advocates for the use of information technology in medicine but at the same time are concerned by current major shortfalls. This White Paper outlines pitfalls, opportunities, and solutions and recommends increased investment in research and development of ontologies with computable semantics for a new generation of EHRs.

Free fatty acid receptor 2 (FFAR2) is activated by short-chain fatty acids and expressed widely, including in white adipocytes and various immune and enteroendocrine cells. Using both wild-type human FFAR2 and a designer receptor exclusively activated by designer drug (DREADD) variant we explored the activation and phosphorylation profile of the receptor, both in heterologous cell lines and in tissues from transgenic knock-in mouse lines expressing either human FFAR2 or the FFAR2-DREADD. FFAR2 phospho-site-specific antisera targeting either pSer296/pSer297 or pThr306/pThr310 provided sensitive biomarkers of both constitutive and agonist-mediated phosphorylation as well as an effective means to visualise agonist-activated receptors in situ. In white adipose tissue, phosphorylation of residues Ser296/Ser297 was enhanced upon agonist activation whilst Thr306/Thr310 did not become phosphorylated. By contrast, in immune cells from Peyer’s patches Thr306/Thr310 become phosphorylated in a strictly agonist-dependent fashion whilst in enteroendocrine cells of the colon both Ser296/Ser297 and Thr306/Thr310 were poorly phosphorylated. The concept of phosphorylation bar-coding has centred to date on the potential for different agonists to promote distinct receptor phosphorylation patterns. Here, we demonstrate that this occurs for the same agonist-receptor pairing in different patho-physiologically relevant target tissues. This may underpin why a single G protein-coupled receptor can generate different functional outcomes in a tissue-specific manner.

Abstract G protein-coupled receptors (GPCRs) are important signal transducers that are phosphorylated upon activation at intracellular serine and threonine residues. Although antibodies that specifically recognize the phosphorylation state of GPCRs have been available for many years, efficient immunolocalization of phosphorylated receptors in their tissues of origin has not been possible. Here, we show that phosphorylation of receptors is highly unstable during routine immunohistochemical procedures, requiring the use of appropriate phosphatase inhibitors particular during tissue perfusion, post-fixation, and cryoprotection but not during immunostaining of tissue sections. We provide proof of concept using phosphorylation state-specific μ-opioid receptor (MOP) and cannabinoid receptor 1 (CB1) antibodies. Indeed, three of four well-characterized phosphosite-specific MOP antibodies, including pS375-MOP, pT376-MOP, and pT379-MOP, showed robust neuronal immunostaining in brain and spinal cord sections of opioid-treated mice only after inclusion of phosphatase inhibitors. We then extended this approach to the CB1 receptor and demonstrated that one of three newly-generated phosphosite-specific CB1 antibodies, namely pS425-CB1, showed striking staining of fibers and varicosities in brain slices from cannabinoid-treated mice. Although subsequent experiments showed that phospho-CB1 immunostaining was less sensitive to phosphatases, we conclude that the use of phosphatase inhibitors should always be considered in the development of immunohistochemical procedures for new phosphosite-specific GPCR antibodies. In summary, we anticipate that this improved protocol will facilitate the widespread use of phosphorylation state-specific antibodies to monitor the activation of endogenous GPCRs under physiological and pharmacological conditions. Our approach may also prove useful to confirm target engagement of GPCR drug candidates in native tissues.

Boron (B) containing III-nitride materials, such as wurtzite (wz) (B, Ga)N alloys, have recently attracted significant interest due to their ability to tailor the electronic and optical properties of optoelectronic devices operating in the visible and ultraviolet spectral range. However, the growth of high quality samples is challenging and B atom clustering is often observed in (B, Ga)N alloys. To date, a fundamental understanding of the impact of such clustering on the electronic and optical properties of these alloys is sparse. In this work, we employ density functional theory (DFT) in the framework of the meta-generalized gradient approximation [modified Becke Johnson (mBJ) functional] to provide insight into this question. We use mBJ DFT calculations, benchmarked against state-of-the-art hybrid functional DFT, on (B, Ga)N alloys in the experimentally relevant B content range of up to 7.4%. Our results reveal that B atom clustering can lead to a strong reduction in the bandgap of such an alloy, in contrast to alloy configurations where B atoms are not forming clusters, thus not sharing nitrogen (N) atoms. We find that the reduction in bandgap is linked mainly to carrier localization effects in the valence band, which stem from local strain and polarization field effects. However, our study also reveals that the alloy microstructure of a B atom cluster plays an important role: B atom chains along the wz c axis impact the electronic structure far less strongly when compared to a chain formed within the c-plane. This effect is again linked to local polarization field effects and the orbital character of the involved valence states in wz BN and GaN. Overall, our calculations show that controlling the alloy microstructure of (B, Ga)N alloys is of central importance when it comes to utilizing these systems in future optoelectronic devices with improved efficiencies.

Hyperolid reed frogs are one of the few families of Anurans known to possess glands that emit volatile compounds used in chemical communication. Hyperolius cinnamomeoventris, a model species, possesses a gular gland on its vocal sac that emits chemicals, and sends visual and auditory signals during calling. Previous investigations have shown that the glandular compounds are typically macrocyclic lactones. However, in this work, we show that another major constituent of the male specific gland is (10R,1S,6R,7R,10R)-amorph-4-ene-10β-ol [(1R,4R,4aR,8aS)-4-isopropyl-1,6-dimethyl-1,2,3,4,4a,7,8,8a-octahydronaphthalen-1-ol]. This compound was synthesized for the first time and has the opposite configuration to amorph-4-ene-10β-ol known from plants. A short synthesis using an organocatalytic approach through a tandem Mannich/intramolecular Diels–Alder reaction led to a mixture of cadinols, which was used for the assignment of the natural cadinol structures and their stereoisomers.

Controlling multi-joint prostheses intuitively and effortlessly has been a research topic since the appearance of the first electric elbow prostheses. Researchers mainly focused on single handed tasks, however in daily life these are mostly executed with the healthy hand and the prosthetic arms only become relevant for two-handed manipulations. Thus, a new approach is presented in this paper addressing bilateral tasks. A taxonomy for bilateral tasks is elaborated in order to categorize and prioritize bilateral manipulations involving a prosthetic arm. Five different key figures for rating bilateral movements are introduced and used to form two quality criteria, which allow evaluation and comparison of different control strategies. Based on the proposed taxonomy and quality criteria, a generalized benchmark test environment is developed with five different evaluation scenarios and realized in virtual reality in an exemplary manner. Furthermore, a new controller-agent strategy, greatly facilitating the usage of prosthetic arms, is presented. The effectiveness of the criteria for evaluation of different control strategies is demonstrated with healthy subjects. With this evaluation concept, we provide the community a means to explore and compare controlling methods and inputs, facilitating the progress and development of new strategies.

Abstract Carvedilol is among the most effective β-blockers for improving survival after myocardial infarction. Yet the mechanisms by which carvedilol achieves this superior clinical profile are still unclear. Beyond blockade of β1-adrenoceptors, arrestin-biased signalling via β2-adrenoceptors is a molecular mechanism proposed to explain the survival benefits. Here, we offer an alternative mechanism to rationalize carvedilol’s cellular signalling. Using primary and immortalized cells genome-edited by CRISPR/Cas9 to lack either G proteins or arrestins; and combining biological, biochemical, and signalling assays with molecular dynamics simulations, we demonstrate that G proteins drive all detectable carvedilol signalling through β2ARs. Because a clear understanding of how drugs act is imperative to data interpretation in basic and clinical research, to the stratification of clinical trials or to the monitoring of drug effects on the target pathway, the mechanistic insight gained here provides a foundation for the rational development of signalling prototypes that target the β-adrenoceptor system.

A G protein-coupled receptors (GPCRs) phosphorylation assay for cell culture plates can be used for ligand profiling and inhibitor screening, as evidenced by the identification of two GRK inhibitor compounds.

Land Surface Temperature (LST) is an important resource for a variety of tasks. The data are mostly free of charge and combine high spatial and temporal resolution with reliable data collection over a historical timeframe. When remote sensing is used to provide LST data, such as the MODA11 product using information from the MODIS sensors attached to NASA satellites, data acquisition can be hindered by clouds or cloud shadows, occluding the sensors’ view on different areas of the world. This makes it difficult to take full advantage of the high resolution of the data. A common solution to interpolating LST data is statistical interpolation methods, such as fitting polynomials or thin plate spine interpolation. These methods have difficulties in incorporating additional knowledge about the research area and learning local dependencies that can help with the interpolation process. We propose a novel approach to interpolating remote sensing LST data in a fixed research area considering local ground-site air temperature measurements. The two-step approach consists of learning the LST from air temperature measurements, where the ground-site weather stations are located, and interpolating the remaining missing values with partial convolutions within a U-Net deep learning architecture. Our approach improves the interpolation of LST for our research area by 44% in terms of RMSE, when compared to state-of-the-art statistical methods. Due to the use of air temperature, we can provide coverage of 100%, even when no valid LST measurements were available. The resulting gapless coverage of high resolution LST data will help unlock the full potential of remote sensing LST data.

Abstract Somatostatin receptors SST1, SST2, and SST5 are overexpressed in neuroendocrine neoplasms (NENs), but little is known about SST4 expression in NENs because of a lack of specific monoclonal antibodies. We recently developed and thoroughly characterised a rabbit monoclonal anti-human SST4 antibody, 7H49L61, and showed that it is well suited for identifying SST4 expression in routine pathology samples. The present study aimed to re-evaluate SST4 expression in a large set of NEN samples using this antibody. For this purpose, we assessed SST4 expression in 722 formalin-fixed, paraffin-embedded NEN samples from 274 patients by immunohistochemistry using the novel antibody 7H49L61. The immunostaining was semiquantitatively evaluated using the 12-point immunoreactivity score (IRS), and the results were correlated with clinicopathological data. SST4 was detected in 39.3% of all NENs, but with a median IRS of 2.0, its expression intensity was negligible overall. In all cases, both cytoplasmic and membraneous staining was observed. SST4 expression was somewhat higher in bronchopulmonary NEN (BP-NEN) than in gastroenteropancreatic NEN (GEP-NEN) but still very low. SST4 expression positively correlated with favourable patient outcomes in BP-NEN but had a positive association with Ki-67 index or tumour grading and a negative interrelationship with overall survival in GEP-NEN. In conclusion, unlike that of other SST subtypes, SST4 expression in both BP-NEN and GEP-NEN is negligible and of no diagnostic or therapeutic relevance.

Abstract Background Papillary and follicular thyroid carcinomas can be treated surgically and with radioiodine therapy, whereas therapeutic options for advanced stage IV medullary and for anaplastic tumours are limited. Recently, somatostatin receptors (SSTs) and the chemokine receptor CXCR4 have been evaluated for the treatment of thyroid carcinomas, however, with contradictory results. Methods The expression of the five SSTs and of CXCR4 was assessed in 90 samples from 56 patients with follicular, papillary, medullary, or anaplastic thyroid carcinoma by means of immunohistochemistry using well-characterised monoclonal antibodies. The stainings were evaluated using the Immunoreactivity Score (IRS) and correlated to clinical data. In order to further substantiate the immunohistochemistry results, in serial sections of a subset of the samples receptor expression was additionally examined at the mRNA level using qRT-PCR. Results Overall, SST and CXCR4 protein expression was low in all four entities. In single cases, however, very high IRS values for SST2 and CXCR4 were observed. SST2 was the most frequently expressed receptor, found in 38% of cases, followed by SST5 and SST4, found in 14 and 9% of tumours, respectively. SST1 and SST3 could not be detected to any significant extent. CXCR4 was present in 12.5% of medullary and 25% of anaplastic carcinomas. Expression SST3, SST4, SST5 and CXCR4 was positively correlated with expression of the proliferation marker Ki-67. Additionally, a negative interrelationship between SST4 or SST5 expression and patient survival and a positive association between SST3 expression and tumour diameter were observed. qRT-PCR revealed a similar receptor expression pattern to that seen at the protein level. However, probably due to the low overall expression, no correlation was found for the SSTs or the CXCR4 between the IRS and the mRNA values. Conclusions SST- or CXCR4-based diagnostics or therapy in thyroid carcinomas should not be considered in general but may be feasible in single cases with high levels of expression of these receptors.

N-(3-fluoro-1-phenethylpiperidine-4-yl)-N-phenyl propionamide is a newly-designed pain killer selectively activating G-protein-coupled mu-opioid receptors (MOR) in acidic injured tissues, and therefore devoid of central side effects which are typically elicited at normal pH values in healthy tissues. However, the neuronal mechanisms underlying NFEPP’s antinociceptive effects were not examined in detail so far. Voltage-dependent Ca2+ channels (VDCCs) in nociceptive neurons play a major role in the generation and inhibition of pain. In this study, we focused on the effects of NFEPP on calcium currents in rat dorsal root ganglion (DRG) neurons. The inhibitory role of the G-protein subunits Gi/o and Gβγ on VDCCs was investigated using the blockers pertussis toxin and gallein, respectively. GTPγS binding, calcium signals and MOR phosphorylation were also investigated. All experiments were performed at acidic and normal pH values using NFEPP in comparison to the conventional opioid agonist fentanyl. At low pH, NFEPP produced more efficient G-protein activation in transfected HEK293 cells and significantly reduced VDCCs in depolarized DRG neurons. The latter effect was mediated by Gβγ subunits, and NFEPP-mediated MOR phosphorylation was pH-dependent. Fentanyl’s responses were not affected by pH changes. Our data indicate that NFEPP-induced MOR signaling is more effective at low pH and that the inhibition of calcium channels in DRG neurons underlies NFEPP’s antinociceptive actions.

Outer Membrane Vesicles (OMVs) of the Gram-negative marine bacterium Dinoroseobacter shibae, a member of the Roseobacteraceae, were investigated for the presence of volatile organic compounds (VOCs). Extracts of vesicles were analyzed by gas chromatography/mass spectrometry (GC/MS). In these analyses the short fatty acid (Z)-5-dodecenoic acid (1) and the related, more volatile aldehyde (Z)-5-dodecenal (8) were identified as VOCs of the OMVs. The aldehyde 8 has not yet been reported before from bacteria. Due to their possible function as signaling molecules, both compounds were tested for Quorum Sensing (QS) inhibition in a bioassay against the QS sensor strain Pseudomonas putida F117 (pKRC12) responsive to long-chain N-acylhomoserine lactones, the effectors of the sensor. Both compounds showed QS inhibitory activity. The potential function of VOCs in OMVs which has not been observed previously is discussed.

This paper provides an overview of current linguistic and ontological challenges which have to be met in order to provide full support to the transformation of health ecosystems in order to meet precision medicine (5 PM) standards. It highlights both standardization and interoperability aspects regarding formal, controlled representations of clinical and research data, requirements for smart support to produce and encode content in a way that humans and machines can understand and process it. Starting from the current text-centered communication practices in healthcare and biomedical research, it addresses the state of the art in information extraction using natural language processing (NLP). An important aspect of the language-centered perspective of managing health data is the integration of heterogeneous data sources, employing different natural languages and different terminologies. This is where biomedical ontologies, in the sense of formal, interchangeable representations of types of domain entities come into play. The paper discusses the state of the art of biomedical ontologies, addresses their importance for standardization and interoperability and sheds light to current misconceptions and shortcomings. Finally, the paper points out next steps and possible synergies of both the field of NLP and the area of Applied Ontology and Semantic Web to foster data interoperability for 5 PM.

Abstract Multi-receptor targeting has been proposed as a promising strategy for the development of opioid analgesics with fewer side effects. Cebranopadol and AT-121 are prototypical bifunctional ligands targeting the nociceptin/orphanin FQ peptide receptor (NOP) and µ-opioid receptor (MOP) that elicit potent analgesia in humans and nonhuman primates, respectively. Cebranopadol was reported to produce typical MOP-related side effects such as respiratory depression and reward, whereas AT-121 appeared to be devoid of these liabilities. However, the molecular basis underlying different side effect profiles in opioid analgesics remains unknown. Here, we examine agonist-induced receptor phosphorylation and G protein signaling profiles of a series of chemically diverse mixed MOP/NOP agonists, including cebranopadol and AT-121. We found that these compounds produce strikingly different MOP phosphorylation profiles. Cebranopadol, AT-034 and AT-324 stimulated extensive MOP phosphorylation, whereas AT-201 induced selective phosphorylation at S375 only. AT-121, on the other hand, did not promote any detectable MOP phosphorylation. Conversely, none of these compounds was able to elicit strong NOP phosphorylation and low NOP receptor phosphorylation correlated with partial agonism in a GIRK-channel assay. Our results suggest a close correlation between MOP receptor phosphorylation and side effect profile. Thus, bifunctional MOP/NOP opioid ligands combining low efficacy G protein signaling at both NOP and MOP with no detectable receptor phosphorylation appear to be devoid of side-effects such as respiratory depression, abuse liability or tolerance development, as with AT-121.

Fritzwanker et al. develop a knock-in transgenic mouse line in which the hemagglutinin epitope tag sequence is fused with the amino-terminus of the µ-opioid receptor. Their model enables more efficient immunodetection of G protein-coupled receptors.

Many plant species are pollinated by butterflies. These insects are primarily attracted by visual flower cues, however, butterflies are also known to respond to flower scents and some butterfly-pollinated plants are strongly scented. One of such plants is the butterfly bush, Buddleja davidii, which is a magnet for butterflies. It is widespread in its native region in Asia and famous for its success in invasive spreading in regions throughout the world. Due to its attractiveness to butterflies and its beautiful and conspicuous inflorescences, it also is an important ornamental, found in many gardens. Here, we elucidated the signaling between the butterfly bush and one of its abundant visitors, the peacock butterfly (Aglais io), using chemical and behavioral approaches. We found that olfactory cues are more attractive than visual cues, and that feeding behavior is only elicited by olfactory cues, most effectively by 4-oxoisophorone and oxoisophorone epoxide. The latter compound was not known to elicit behavioral responses in pollinators before this study. The relative importance of olfactory cues was higher in our study than previously observed in any butterfly pollination system. The identified attractants might contribute to the widespread occurrence of the butterfly bush in its native region in Asia and its success in invasive spreading in regions throughout the world.

Clostridioides difficile (previously Clostridium difficile) causes life-threatening gut infections. The central metabolism of the bacterium is strongly influencing toxin production and consequently the infection progress. In this context, the composition and potential origin of the volatile metabolome was investigated, showing a large number of sulfur-containing volatile metabolites. Gas chromatography/mass spectrometry (GC/MS)-based headspace analyses of growing C. difficile 630Δerm cultures identified 105 mainly sulfur-containing compounds responsible of the typical C. difficile odor. Major components were identified to be 2-methyl-1-propanol, 2-methyl-1-propanethiol, 2-methyl-1-butanethiol, 4-methyl-1-pentanethiol, and as well as their disulfides. Structurally identified were 64 sulfur containing volatiles. In order to determine their biosynthetic origin, the concentrations of the sulfur-containing amino acids methionine and cysteine were varied in the growth medium. The changes observed in the volatile metabolome profile indicated that cysteine plays an essential role in the formation of the sulfur-containing volatiles. We propose that disulfides are derived from cysteine via formation of cystathionine analogs, which lead to corresponding thiols. These thiols may then be oxidized to disulfides. Moreover, methionine may contribute to the formation of short-chain disulfides through integration of methanethiol into the disulfide biosynthesis. In summary, the causative agents of the typical C. difficile odor were identified and first hypotheses for their biosynthesis were proposed.

Abstract Background Controlled vocabularies are fundamental resources for information extraction from clinical texts using natural language processing (NLP). Standard language resources available in the healthcare domain such as the UMLS metathesaurus or SNOMED CT are widely used for this purpose, but with limitations such as lexical ambiguity of clinical terms. However, most of them are unambiguous within text limited to a given clinical specialty. This is one rationale besides others to classify clinical text by the clinical specialty to which they belong. Results This paper addresses this limitation by proposing and applying a method that automatically extracts Spanish medical terms classified and weighted per sub-domain, using Spanish MEDLINE titles and abstracts as input. The hypothesis is biomedical NLP tasks benefit from collections of domain terms that are specific to clinical subdomains. We use PubMed queries that generate sub-domain specific corpora from Spanish titles and abstracts, from which token n-grams are collected and metrics of relevance, discriminatory power, and broadness per sub-domain are computed. The generated term set, called Spanish core vocabulary about clinical specialties (SCOVACLIS), was made available to the scientific community and used in a text classification problem obtaining improvements of 6 percentage points in the F-measure compared to the baseline using Multilayer Perceptron, thus demonstrating the hypothesis that a specialized term set improves NLP tasks. Conclusion The creation and validation of SCOVACLIS support the hypothesis that specific term sets reduce the level of ambiguity when compared to a specialty-independent and broad-scope vocabulary.

Abstract The dopamine D2 receptor (D2R) is the target of drugs used to treat the symptoms of Parkinson’s disease and schizophrenia. The D2R is regulated through its interaction with and phosphorylation by G protein receptor kinases (GRKs) and interaction with arrestins. More recently, D2R arrestin-mediated signaling has been shown to have distinct physiological functions to those of G protein signalling. Relatively little is known regarding the patterns of D2R phosphorylation that might control these processes. We aimed to generate antibodies specific for intracellular D2R phosphorylation sites to facilitate the investigation of these mechanisms. We synthesised double phosphorylated peptides corresponding to regions within intracellular loop 3 of the hD2R and used them to raise phosphosite-specific antibodies to capture a broad screen of GRK-mediated phosphorylation. We identify an antibody specific to a GRK2/3 phosphorylation site in intracellular loop 3 of the D2R. We compared measurements of D2R phosphorylation with other measurements of D2R signalling to profile selected D2R agonists including previously described biased agonists. These studies demonstrate the utility of novel phosphosite-specific antibodies to investigate D2R regulation and signalling.

Abstract The degree to which loci promoting reproductive isolation cluster in the genome—that is, the genetic architecture of reproductive isolation—can influence the tempo and mode of speciation. Tight linkage between these loci can facilitate speciation in the face of gene flow. Pheromones play a role in reproductive isolation in many Lepidoptera species, and the role of endogenously produced compounds as secondary metabolites decreases the likelihood of pleiotropy associated with many barrier loci. Heliconius butterflies use male sex pheromones to both court females (aphrodisiac wing pheromones) and ward off male courtship (male‐transferred antiaphrodisiac genital pheromones), and it is likely that these compounds play a role in reproductive isolation between Heliconius species. Using a set of backcross hybrids between H. melpomene and H. cydno, we investigated the genetic architecture of putative male pheromone compound production. We found a set of 40 significant quantitative trait loci (QTL) representing 33 potential pheromone compounds. QTL clustered significantly on two chromosomes, chromosome 8 for genital compounds and chromosome 20 for wing compounds, and chromosome 20 was enriched for potential pheromone biosynthesis genes. There was minimal overlap between pheromone QTL and known QTL for mate choice and color pattern. Nonetheless, we did detect linkage between a QTL for wing androconial area and optix, a color pattern locus known to play a role in reproductive isolation in these species. This tight clustering of putative pheromone loci might contribute to coincident reproductive isolating barriers, facilitating speciation despite ongoing gene flow.

Abstract Preliminary studies show that clavicle fractures (CF) are known as an indicator in the severely injured for overall injury severity that are associated with relevant concomitant injuries in the thorax and upper extremity. In this regard, little data is available for the rarer injuries of the sternoclavicular and acromioclavicular joints (SCJ and ACJ, respectively). Our study will answer whether clavicular joint injuries (CJI), by analogy, have a similar relevance for the severely injured. We performed an analysis from the TraumaRegister DGU (TR-DGU). The inclusion criterion was an Injury Severity Score (ISS) of at least 16. In the TR-DGU, the CJI were registered as one entity. The CJI group was compared with the CF and control groups (those without any clavicular injuries). Concomitant injuries were distinguished using the Abbreviated Injury Scale according to their severity. The inclusion criteria were met by n = 114,595 patients. In the case of CJI, n = 1228 patients (1.1%) were found to be less severely injured than the controls in terms of overall injury severity. Compared to the CF group (n = 12,030; 10.5%) with higher ISS than the controls, CJI cannot be assumed as an indicator for a more severe trauma; however, CF can. Concomitant injuries were more common for severe thoracic and moderate upper extremity injuries than other body parts for CJI. This finding confirms our hypothesis that CJI could be an indicator of further specific severe concomitant injuries. Despite the rather lower relevance of the CJI in the cohort of severely injured with regard to the overall injury severity, these injuries have their importance in relation to the indicator effect for thoracic concomitant injuries and concomitant injuries of the upper extremity. A limitation is the collective registration of SCJ and ACJ injuries as one entity in the TR-DGU. A distorted picture of the CJI in favor of ACJ injuries could arise from the significantly higher incidence of the ACJ dislocation compared to the SCJ. Therefore, these two injury entities should be recorded separately in the future, and prospective studies should be carried out in order to derive a standardized treatment strategy for the care of severely injured with the respective CJI.

Male ithomiine butterflies (Nymphalidae: Danainae) have hairpencils on the forewings (i.e., androconia) that disseminate semiochemicals during courtship. While most ithomiines are known to contain derivatives of pyrrolizidine alkaloids, dihydropyrrolizines, or γ-lactones in these androconia, here we report on a new class of fatty acid esters identified in two subspecies, Ithomia salapia aquinia and I. s. derasa. The major components were identified as isoprenyl (3-methyl-3-butenyl) (Z)-3-acetoxy-11-octadecenoate, isoprenyl (Z)-3-acetoxy-13-octadecenoate (12) and isoprenyl 3-acetoxyoctadecanoate (11) by GC/MS and GC/IR analyses, microderivatizations, and synthesis of representative compounds. The absolute configuration of 12 was determined to be R. The two subspecies differed not only in the composition of the ester bouquet, but also in the composition of more volatile androconial constituents. While some individuals of I. s. aquinia contained ithomiolide A (3), a pyrrolizidine alkaloid derived γ-lactone, I. s. derasa carried the sesquiterpene α-elemol (8) in the androconia. These differences might be important for the reproductive isolation of the two subspecies, in line with previously reported low gene exchange between the two species in regions where they co-occur. Furthermore, the occurrence of positional isomers of unsaturated fatty acid derivatives indicates activity of two different desaturases within these butterflies, Δ9 and Δ11, which has not been reported before in male Lepidoptera.

Abstract In many animals, mate choice is important for the maintenance of reproductive isolation between species. Traits important for mate choice and behavioral isolation are predicted to be under strong stabilizing selection within species; however, such traits can also exhibit variation at the population level driven by neutral and adaptive evolutionary processes. Here, we describe patterns of divergence among androconial and genital chemical profiles at inter‐ and intraspecific levels in mimetic Heliconius butterflies. Most variation in chemical bouquets was found between species, but there were also quantitative differences at the population level. We found a strong correlation between interspecific chemical and genetic divergence, but this correlation varied in intraspecific comparisons. We identified “indicator” compounds characteristic of particular species that included compounds already known to elicit a behavioral response, suggesting an approach for identification of candidate compounds for future behavioral studies in novel systems. Overall, the strong signal of species identity suggests a role for these compounds in species recognition, but with additional potentially neutral variation at the population level.

Abstract The δ-opioid receptor (DOP) is an attractive pharmacological target due to its potent analgesic, anxiolytic and anti-depressant activity in chronic pain models. However, some but not all selective DOP agonists also produce severe adverse effects such as seizures. Thus, the development of novel agonists requires a profound understanding of their effects on DOP phosphorylation, post-activation signaling and dephosphorylation. Here we show that agonist-induced DOP phosphorylation at threonine 361 (T361) and serine 363 (S363) proceeds with a temporal hierarchy, with S363 as primary site of phosphorylation. This phosphorylation is mediated by G protein-coupled receptor kinases 2 and 3 (GRK2/3) followed by DOP endocytosis and desensitization. DOP dephosphorylation occurs within minutes and is predominantly mediated by protein phosphatases (PP) 1α and 1β. A comparison of structurally diverse DOP agonists and clinically used opioids demonstrated high correlation between G protein-dependent signaling efficacies and receptor internalization. In vivo, DOP agonists induce receptor phosphorylation in a dose-dependent and agonist-selective manner that could be blocked by naltrexone in DOP-eGFP mice. Together, our studies provide novel tools and insights for ligand-activated DOP signaling in vitro and in vivo and suggest that DOP agonist efficacies may determine receptor post-activation signaling.

Little information is available concerning protein expression of the calcitonin receptor-like receptor (CALCRL) at the protein level. Here, we developed a rabbit monoclonal antibody, 8H9L8, which is directed against human CALCRL but cross-reacts with the rat and mouse forms of the receptor. We confirmed antibody specificity via Western blot analyses and immunocytochemistry using the CALCRL-expressing neuroendocrine tumour cell line BON-1 and a CALCRL-specific small interfering RNA (siRNA). We then used the antibody for immunohistochemical analyses of various formalin-fixed, paraffin-embedded specimens of normal and neoplastic tissues. In nearly all tissue specimens examined, CALCRL expression was detected in the capillary endothelium, smooth muscles of the arterioles and arteries, and immune cells. Analyses of normal human, rat, and mouse tissues revealed that CALCRL was primarily present in distinct cell populations in the cerebral cortex; pituitary; dorsal root ganglia; epithelia, muscles, and glands of the larger bronchi; intestinal mucosa (particularly in enteroendocrine cells); intestinal ganglia; exocrine and endocrine pancreas; arteries, capillaries, and glomerular capillary loops in the kidneys; the adrenals; Leydig cells in the testicles; and syncytiotrophoblasts in the placenta. In the neoplastic tissues, CALCRL was predominantly expressed in thyroid carcinomas, parathyroid adenomas, small-cell lung cancers, large-cell neuroendocrine carcinomas of the lung, pancreatic neuroendocrine neoplasms, renal clear-cell carcinomas, pheochromocytomas, lymphomas, and melanomas. In these tumours with strong expression of CALCRL, the receptor may represent a useful target structure for future therapies.

BackgroundClear-cell renal cell carcinoma (ccRCC) is common and associated with substantial mortality. TNM stage and histopathological grading have been the sole determinants of a patient’s prognosis for decades and there are few prognostic biomarkers used in clinical routine. Management of ccRCC involves multiple disciplines such as urology, radiology, oncology, and pathology and each of these specialties generates highly complex medical data. Here, artificial intelligence (AI) could prove extremely powerful to extract meaningful information to benefit patients.ObjectiveIn the study, we developed and evaluated a multimodal deep learning model (MMDLM) for prognosis prediction in ccRCC.Design, Setting, and ParticipantsTwo mixed cohorts of non-metastatic and metastatic ccRCC patients were used: (1) The Cancer Genome Atlas cohort including 230 patients and (2) the Mainz cohort including 18 patients with ccRCC. For each of these patients, we trained the MMDLM on multiscale histopathological images, CT/MRI scans, and genomic data from whole exome sequencing.Outcome Measurements and Statistical AnalysisOutcome measurements included Harrell’s concordance index (C-index) and also various performance parameters for predicting the 5-year survival status (5YSS). Different visualization techniques were used to make our model more transparent.ResultsThe MMDLM showed great performance in predicting the prognosis of ccRCC patients with a mean C-index of 0.7791 and a mean accuracy of 83.43%. Training on a combination of data from different sources yielded significantly better results compared to when only one source was used. Furthermore, the MMDLM’s prediction was an independent prognostic factor outperforming other clinical parameters.InterpretationMultimodal deep learning can contribute to prognosis prediction in ccRCC and potentially help to improve the clinical management of this disease.Patient SummaryAn AI-based computer program can analyze various medical data (microscopic images, CT/MRI scans, and genomic data) simultaneously and thereby predict the survival time of patients with renal cancer.

Blunt high-energy chest trauma is often associated with thoracic and abdominal organ injuries. Literature for a hyperextension-distraction mechanism resulting in a costal arch fracture combined with a thoracic spine fracture is sparse. A 65-year-old male suffered a fall from a height of six meters. Initial X-ray of the chest shows left-sided high-riding diaphragm and CT scan proves anterior cartilage fracture, posterolateral serial rib fractures, traumatic intercostal pulmonary hernia, avulsion of the diaphragm, and 7th thoracic vertebral fracture. An exploratory thoracotomy was performed and the rupture of the diaphragm, creating a two-cavity injury, had been re-fixed, the pulmonary hernia was closed, and locking plate osteosyntheses of the fractured ribs including the costal arch were performed. We generally recommend surgical therapy of the thorax to restore stability in this severe injury entity. The spine was fixed dorsally using a screw-rod system. In conclusion, this thoracovertebral injury entity is associated with high overall injury severity and life-threatening thoracoabdominal injuries. Since two-cavity traumata and particularly diaphragmatic injuries are often diagnosed delayed, injuries to the costal arch can act as an indicator of severe trauma. They should be detected through clinical examination and assessment of the trauma CT in the soft tissue window.

Secondary metabolites are key components in microbial ecology by mediating interactions between bacteria and their environment, neighboring species or host organisms. Bioactivities can be beneficial for both interaction partners or provide a competitive advantage only for the producer. Colonizers of confined habitats such as biofilms are known as prolific producers of a great number of bioactive secondary metabolites and are a potential source for novel compounds. We investigated the strain Paracoccus marcusii CP157, which originates from the biofilm on the carapace of a shell disease-affected Cancer pagurus specimen, for its potential to produce bioactive secondary metabolites. Its closed genome contains 22 extrachromosomal elements and several gene clusters potentially involved in biosynthesis of bioactive polyketides, bacteriocins, and non-ribosomal peptides. Culture extracts of CP157 showed antagonistic activities against bacteria from different phyla, but also against microalgae and crustacean larvae. Different HPLC-fractions of CP157 culture extracts had antibacterial properties, indicating that several bioactive compounds are produced by CP157. The bioactive extract contains several small, antibacterial compounds that partially withstand elevated temperatures, extreme pH values and exposure to proteolytic enzymes, providing high stability toward environmental conditions in the natural habitat of CP157. Further, screening of 17 Paracoccus spp. revealed that antimicrobial activity, hemolysis and production of N-acyl homoserine lactones are common features within the genus. Taking into account the large habitat diversity and phylogenetic distance of the tested strains, we hypothesize that bioactive secondary metabolites play a central role in the ecology of Paracoccus spp. in their natural environments.

Abstract Background The identification of sections in narrative content of Electronic Health Records (EHR) has demonstrated to improve the performance of clinical extraction tasks; however, there is not yet a shared understanding of the concept and its existing methods. The objective is to report the results of a systematic review concerning approaches aimed at identifying sections in narrative content of EHR, using both automatic or semi-automatic methods. Methods This review includes articles from the databases: SCOPUS, Web of Science and PubMed (from January 1994 to September 2018). The selection of studies was done using predefined eligibility criteria and applying the PRISMA recommendations. Search criteria were elaborated by using an iterative and collaborative keyword enrichment. Results Following the eligibility criteria, 39 studies were selected for analysis. The section identification approaches proposed by these studies vary greatly depending on the kind of narrative, the type of section, and the application. We observed that 57% of them proposed formal methods for identifying sections and 43% adapted a previously created method. Seventy-eight percent were intended for English texts and 41% for discharge summaries. Studies that are able to identify explicit (with headings) and implicit sections correspond to 46%. Regarding the level of granularity, 54% of the studies are able to identify sections, but not subsections. From the technical point of view, the methods can be classified into rule-based methods (59%), machine learning methods (22%) and a combination of both (19%). Hybrid methods showed better results than those relying on pure machine learning approaches, but lower than rule-based methods; however, their scope was more ambitious than the latter ones. Despite all the promising performance results, very few studies reported tests under a formal setup. Almost all the studies relied on custom dictionaries; however, they used them in conjunction with a controlled terminology, most commonly the UMLSⓇ metathesaurus. Conclusions Identification of sections in EHR narratives is gaining popularity for improving clinical extraction projects. This study enabled the community working on clinical NLP to gain a formal analysis of this task, including the most successful ways to perform it.

Following up on a recent debate, we examined advice taking in dyads compared to individuals in a set of three studies (total N = 303 dyads and 194 individuals). Our first aim was to test the replicability of an important previous finding, namely that dyads heed advice less than individuals because they feel more confident in the accuracy of their initial judgments. Second, we aimed to explain dyads’ behavior based on three premises: first, that dyads understand that the added value of an outside opinion diminishes when the initial pre-advice judgment is made by two judges rather than one judge (given that the dyad members’ opinions are independent of each other); second, that they fail to recognize when the assumption of independence of opinions does not hold; and third, that the resistance to advice commonly observed in individuals persists in groups but is neither aggravated nor ameliorated by the group context. The results of our studies show consistently that previous findings on advice taking in dyads are replicable. They also support our hypothesis that groups exhibit a general tendency to heed advice less than individuals, irrespective of whether the accuracy of their initial judgments warrants this behavior. Finally, based on the three assumptions mentioned above, we were able to make accurate predictions about advice taking in dyads, prompting us to postulate a general model of advice taking in groups of arbitrary size.

Abstract Background The amount of patient-related information within clinical information systems accumulates over time, especially in cases where patients suffer from chronic diseases with many hospitalizations and consultations. The diagnosis or problem list is an important feature of the electronic health record, which provides a dynamic account of a patient’s current illness and past history. In the case of an Austrian hospital network, problem list entries are limited to fifty characters and are potentially linked to ICD-10. The requirement of producing ICD codes at each hospital stay, together with the length limitation of list items leads to highly redundant problem lists, which conflicts with the physicians’ need of getting a good overview of a patient in short time. This paper investigates a method, by which problem list items can be semantically grouped, in order to allow for fast navigation through patient-related topic spaces. Methods We applied a minimal language-dependent preprocessing strategy and mapped problem list entries as tf-idf weighted character 3-grams into a numerical vector space. Based on this representation we used the unweighted pair group method with arithmetic mean (UPGMA) clustering algorithm with cosine distances and inferred an optimal boundary in order to form semantically consistent topic spaces, taking into consideration different levels of dimensionality reduction via latent semantic analysis (LSA). Results With the proposed clustering approach, evaluated via an intra- and inter-patient scenario in combination with a natural language pipeline, we achieved an average compression rate of 80% of the initial list items forming consistent semantic topic spaces with an F-measure greater than 0.80 in both cases. The average number of identified topics in the intra-patient case (μ Intra = 78.4) was slightly lower than in the inter-patient case (μ Inter = 83.4). LSA-based feature space reduction had no significant positive performance impact in our investigations. Conclusions The investigation presented here is centered on a data-driven solution to the known problem of information overload, which causes ineffective human-computer interactions at clinicians’ work places. This problem is addressed by navigable disease topic spaces where related items are grouped and the topics can be more easily accessed.

Bacteria of the Roseobacter group (Rhodobacteraceae) are important members of many marine ecosystems. Similar to other Gram-negative bacteria many roseobacters produce N-acylhomoserine lactones (AHLs) for communication by quorum sensing systems. AHLs regulate different traits like cell differentiation or antibiotic production. Related N-acylalanine methyl esters (NAMEs) have been reported as well, but so far only from Roseovarius tolerans EL-164. While screening various roseobacters isolated from macroalgae we encountered four strains, Roseovarius sp. D12_1.68, Loktanella sp. F13, F14 and D3 that produced new derivatives and analogs of NAMEs, namely N-acyl-2-aminobutyric acid methyl esters (NABME), N-acylglycine methyl esters (NAGME), N-acylvaline methyl esters (NAVME), as well as for the first time a methyl-branched NAME, N-(13-methyltetradecanoyl)alanine methyl ester. These compounds were detected by GC–MS analysis, and structural proposals were derived from the mass spectra and by derivatization. Verification of compound structures was performed by synthesis. NABMEs, NAVMEs and NAGMEs are produced in low amounts only, making mass spectrometry the method of choice for their detection. The analysis of both EI and ESI mass spectra revealed fragmentation patterns helpful for the detection of similar compounds derived from other amino acids. Some of these compounds showed antimicrobial activity. The structural similarity of N-acylated amino acid methyl esters and similar lipophilicity to AHLs might indicate a yet unknown function as signalling compounds in the ecology of these bacteria, although their singular occurrence is in strong contrast to the common occurrence of AHLs. Obviously the structural motif is not restricted to Roseovarius spp. and occurs also in other genera.

Biallelic mutations in DONSON, an essential gene encoding for a replication fork protection factor, were linked to skeletal abnormalities and microcephaly. To better understand DONSON function in corticogenesis, we characterized Donson expression and consequences of conditional Donson deletion in the mouse telencephalon. Donson was widely expressed in the proliferation and differentiation zones of the embryonic dorsal and ventral telencephalon, which was followed by a postnatal expression decrease. Emx1-Cre-mediated Donson deletion in progenitors of cortical glutamatergic neurons caused extensive apoptosis in the early dorsomedial neuroepithelium, thus preventing formation of the neocortex and hippocampus. At the place of the missing lateral neocortex, these mutants exhibited a dorsal extension of an early-generated paleocortex. Targeting cortical neurons at the intermediate progenitor stage using Tbr2-Cre evoked no apparent malformations, whereas Nkx2.1-Cre-mediated Donson deletion in subpallial progenitors ablated 75% of Nkx2.1-derived cortical GABAergic neurons. Thus, the early telencephalic neuroepithelium depends critically on Donson function. Our findings help explain why the neocortex is most severely affected in individuals with DONSON mutations and suggest that DONSON-dependent microcephaly might be associated with so far unrecognized defects in cortical GABAergic neurons. Targeting Donson using an appropriate recombinase is proposed as a feasible strategy to ablate proliferating and nascent cells in experimental research.

Plants and insects often use the same compounds for chemical communication, but not much is known about the genetics of convergent evolution of chemical signals. The terpene (E)-β-ocimene is a common component of floral scent and is also used by the butterfly Heliconius melpomene as an anti-aphrodisiac pheromone. While the biosynthesis of terpenes has been described in plants and microorganisms, few terpene synthases (TPSs) have been identified in insects. Here, we study the recent divergence of 2 species, H. melpomene and Heliconius cydno, which differ in the presence of (E)-β-ocimene; combining linkage mapping, gene expression, and functional analyses, we identify 2 novel TPSs. Furthermore, we demonstrate that one, HmelOS, is able to synthesise (E)-β-ocimene in vitro. We find no evidence for TPS activity in HcydOS (HmelOS ortholog of H. cydno), suggesting that the loss of (E)-β-ocimene in this species is the result of coding, not regulatory, differences. The TPS enzymes we discovered are unrelated to previously described plant and insect TPSs, demonstrating that chemical convergence has independent evolutionary origins.

The complement component C5a and its receptor C5aR1 are involved in the development of numerous inflammatory diseases. In addition to immune cells, C5aR1 is expressed in neoplastic cells of multiple tumour entities, where C5aR1 is associated with a higher proliferation rate, advanced tumour stage, and poor patient outcomes. The aim of the present study was to obtain a broad expression profile of C5aR1 in human non-neoplastic and neoplastic tissues, especially in tumour entities not investigated in this respect so far. For this purpose, we generated a novel polyclonal rabbit antibody, {5227}, against the carboxy-terminal tail of C5aR1. The antibody was initially characterised in Western blot analyses and immunocytochemistry using transfected human embryonic kidney (HEK) 293 cells. It was then applied to a large series of formalin-fixed, paraffin-embedded non-neoplastic and neoplastic human tissue samples. C5aR1 was strongly expressed by different types of immune cells in the majority of tissue samples investigated. C5aR1 was also present in alveolar macrophages, bronchial, gut, and bile duct epithelia, Kupffer cells, occasionally in hepatocytes, proximal renal tubule cells, placental syncytiotrophoblasts, and distinct stem cell populations of bone marrow. C5aR1 was also highly expressed in the vast majority of the 32 tumour entities investigated, where a hitherto unappreciated high prevalence of the receptor was detected in thyroid carcinomas, small-cell lung cancer, gastrointestinal stromal tumours, and endometrial carcinomas. In addition to confirming published findings, we found noticeable C5aR1 expression in many tumour entities for the first time. Here, it may serve as an interesting target for future therapies.

In addition to the classical oestrogen receptors, ERα and ERβ, a G protein-coupled oestrogen receptor (GPER) has been identified that primarily mediates the rapid, non-genomic signalling of oestrogens. Data on GPER expression at the protein level are contradictory; therefore, the present study was conducted to re-evaluate GPER expression by immunohistochemistry to obtain broad GPER expression profiles in human non-neoplastic and neoplastic tissues, especially those not investigated in this respect so far. We developed and thoroughly characterised a novel rabbit monoclonal anti-human GPER antibody, 20H15L21, using Western blot analyses and immunocytochemistry. The antibody was then applied to a large series of formalin-fixed, paraffin-embedded human tissue samples. In normal tissue, GPER was identified in distinct cell populations of the cortex and the anterior pituitary; islets and pancreatic ducts; fundic glands of the stomach; the epithelium of the duodenum and gallbladder; hepatocytes; proximal tubules of the kidney; the adrenal medulla; and syncytiotrophoblasts and decidua cells of the placenta. GPER was also expressed in hepatocellular, pancreatic, renal, and endometrial cancers, pancreatic neuroendocrine tumours, and pheochromocytomas. The novel antibody 20H15L21 will serve as a valuable tool for basic research and the identification of GPER-expressing tumours during histopathological examinations.

The dinoflagellate Prorocentrum cordatum, often called P. minimum, is a potentially toxic alga found in algal blooms. Volatile compounds released by the alga might carry important information, e.g., on its physiological state, and may act as chemical messengers. We report here the identification of volatile organic compounds emitted by two strains, xenic P. cordatum CCMP 1529 and axenic P. cordatum CCMP 1329. The volatiles released during culture were identified despite their low production rates, using sensitive methods such as open-system-stripping analysis (OSSA) on Tenax TA desorption tubes, thermodesorption, cryofocusing and GC/MS-analysis. The analyses revealed 16 compounds released from the xenic strain and 52 compounds from the axenic strain. The majority of compounds were apocarotenoids, aromatic compounds and small oxylipins, but new natural products such as 3,7-dimethyl-4-octanolide were also identified and synthesized. The large difference of compound composition between xenic and axenic algae will be discussed.