Hybrid speciation driven by multilocus introgression of ecological traits.

Hybridization allows adaptations to be shared among lineages and may trigger the evolution of new species1,2. However, convincing examples of homoploid hybrid speciation remain rare because it is challenging to demonstrate that hybridization was crucial in generating reproductive isolation3. Here we combine population genomic analysis with quantitative trait locus mapping of species-specific traits to examine a case of hybrid speciation in Heliconius butterflies. We show that Heliconius elevatus is a hybrid species that is sympatric with both parents and has persisted as an independently evolving lineage for at least 180,000 years. This is despite pervasive and ongoing gene flow with one parent, Heliconius pardalinus, which homogenizes 99% of their genomes. The remaining 1% introgressed from the other parent, Heliconius melpomene, and is scattered widely across the H. elevatus genome in islands of divergence from H. pardalinus. These islands contain multiple traits that are under disruptive selection, including colour pattern, wing shape, host plant preference, sex pheromones and mate choice. Collectively, these traits place H. elevatus on its own adaptive peak and permit coexistence with both parents. Our results show that speciation was driven by introgression of ecological traits, and that speciation with gene flow is possible with a multilocus genetic architecture.

Chemical species recognition in an adaptive radiation of Hawaiian Tetragnatha spiders (Araneae: Tetragnathidae).

Studies of adaptive radiations have played a central role in our understanding of reproductive isolation. Yet the focus has been on human-biased visual and auditory signals, leaving gaps in our knowledge of other modalities. To date, studies on chemical signals in adaptive radiations have focused on systems with multimodal signalling, making it difficult to isolate the role chemicals play in reproductive isolation. In this study we examine the use of chemical signals in the species recognition and adaptive radiation of Hawaiian Tetragnatha spiders by focusing on entire communities of co-occurring species, and conducting behavioural assays in conjunction with chemical analysis of their silks using gas chromatography-mass spectrometry. Male spiders significantly preferred the silk extracts of conspecific mates over those of sympatric heterospecifics. The compounds found in the silk extracts, long chain alkyl methyl ethers, were remarkably species-specific in the combination and quantity. The differences in the profile were greatest between co-occurring species and between closely related sibling species. Lastly, there were significant differences in the chemical profile between two populations of a particular species. These findings provide key insights into the role chemical signals play in the attainment and maintenance of reproductive barriers between closely related co-occurring species.

Rapid elucidation of agonist-driven regulation of the neurokinin 1 receptor using a GPCR phosphorylation immunoassay.

Agonist-induced phosphorylation is a crucial step in the activation/deactivation cycle of G protein-coupled receptors (GPCRs), but direct determination of individual phosphorylation events has remained a major challenge. We have recently developed a bead-based immunoassay for the quantitative assessment of agonist-induced GPCR phosphorylation that can be performed entirely in 96-well plates, thus eliminating the need for western blot analysis. In the present study, we adapted this assay to three novel phosphosite-specific antibodies directed against the neurokinin 1 (NK1) receptor, namely pS338/pT339-NK1, pT344/pS347-NK1, and pT356/pT357-NK1. We found that substance P (SP) stimulated concentration-dependent phosphorylation of all three sites, which could be completely blocked in the presence of the NK1 receptor antagonist aprepitant. The other two endogenous ligands of the tachykinin family, neurokinin A (NKA) and neurokinin B (NKB), were also able to induce NK1 receptor phosphorylation, but to a much lesser extent than substance P. Interestingly, substance P promoted phosphorylation of the two distal sites more efficiently than that of the proximal site. The proximal site was identified as a substrate for phosphorylation by protein kinase C. Analysis of GPCR kinase (GRK)-knockout cells revealed that phosphorylation was mediated by all four GRK isoforms to similar extents at the T344/S347 and the T356/T357 cluster. Knockout of all GRKs resulted in abolition of all phosphorylation signals highlighting the importance of these kinases in agonist-mediated receptor phosphorylation. Thus, the 7TM phosphorylation assay technology allows for rapid and detailed analyses of GPCR phosphorylation.

Activity-Based Protein Profiling Identifies Protein Disulfide-Isomerases as Target Proteins of the Volatile Salinilactones.

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.

Deep Interpolation of Remote Sensing Land Surface Temperature Data with Partial Convolutions.

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.

Complexity of Chemical Emissions Increases Concurrently with Sexual Maturity in Heliconius Butterflies.

Pheromone communication is widespread among animals. Since it is often involved in mate choice, pheromone production is often tightly controlled. Although male sex pheromones (MSPs) and anti-aphrodisiacs have been studied in some Heliconius butterfly species, little is known about the factors affecting their production and release in these long-lived butterflies. Here, we investigate the effect of post-eclosion age on chemical blends from pheromone-emitting tissues in Heliconius atthis and Heliconius charithonia, exhibiting respectively free-mating and pupal-mating strategies that are hypothesised to differently affect the timing of their pheromone emissions. We focus on two different tissues: the wing androconia, responsible for MSPs used in courtship, and the genital tip, the production site for anti-aphrodisiac pheromones that affect post-mating behaviour. Gas chromatography-mass spectrometric analysis of tissue extracts from virgin males and females of both species from day 0 to 8 post-eclosion demonstrates the following. Some ubiquitous fatty acid precursors are already detectable at day 0. The complexity of the chemical blends increases with age regardless of tissue or sex. No obvious difference in the time course of blend production was evident between the two species, but female tissues in H. charithonia were more affected by age than in H. atthis. We suggest that compounds unique to male androconia and genitals and whose amount increases with age are potential candidates for future investigation into their roles as pheromones. While this analysis revealed some of the complexity in Heliconius chemical ecology, the effects of other factors, such as the time of day, remain unknown.

Socialane, a Nonaprenyl Terpene Hydrocarbon Surface Lipid from the Collembola Hypogastrura socialis.

Springtails use unique compounds for their outermost epicuticular wax layer, often of terpenoid origin. We report here the structure and synthesis of socialane, the major cuticular constituent of the Collembola Hypogastrura socialis. Socialane is also the first regular nonaprenyl terpene with a cyclic head group. The saturated side chain has seven stereogenic centers, making the determination of the configuration difficult. We describe here the identification of socialane and a synthetic approach using the building blocks farnesol and phytol, enantioselective hydrogenation, and α-alkylation of sulfones for the synthesis of various stereoisomers. NMR experiments showed the presence of an anti-configuration of the methyl groups closest to the benzene ring and that the other methyl groups of the polyprenyl side-chain are not uniformly configured. Furthermore, socialane is structurally different from [6+2]-terpene viaticene of the closely related H. viatica, showing species specificity of the epicuticular lipids of this genus and hinting at a possible role of surface lipids in the communication of these gregarious arthropods.

O2 supplementation disambiguation in clinical narratives to support retrospective COVID-19 studies.

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.

Cyclopropane Hydrocarbons from the Springtail Vertagopus sarekensis─A New Class of Cuticular Lipids from Arthropods.

The epicuticle of insects is usually coated with a complex mixture of hydrocarbons, primarily straight-chain and methyl-branched alkanes and alkenes. We were interested in whether springtails (Collembola), a sister class of the insects, also use such compounds. We focused here on Vertagopus sarekensis, an abundant Isotomidae species in European high alpine regions, exhibiting coordinated group behavior and migration. This coordination, suggesting chemical communication, made the species interesting for our study on epicuticular hydrocarbons in springtails with different degrees of group behavior. We isolated a single hydrocarbon from its surface, which is the major epicuticular lipid. The structure was deduced by NMR analysis and GC/MS including derivatization. Total synthesis confirmed the structure as cis,cis-3,4,13,14-bismethylene-24-methyldotriacontane (4, sarekensane). The GC/MS analyses of some other cyclopropane hydrocarbons also synthesized showed the close similarity of both mass spectra and gas chromatographic retention indices of alkenes and cyclopropanes. Therefore, analyses of cuticular alkenes must be performed with appropriate derivatization to distinguish these two types of cuticular hydrocarbons. Sarekensane (4) is the first nonterpenoid cuticular hydrocarbon from Collembola that is biosynthesized via the fatty acid pathway, as are insect hydrocarbons, and contains unprecedented cyclopropane rings in the chain, not previously reported from arthropods.

Chronic Morphine Induces Adaptations in Opioid Receptor Signaling in a Thalamostriatal Circuit That Are Location Dependent, Sex Specific, and Regulated by µ-Opioid Receptor Phosphorylation.

Chronic opioid exposure induces tolerance to the pain-relieving effects of opioids but sensitization to some other effects. While the occurrence of these adaptations is well understood, the underlying cellular mechanisms are less clear. This study aimed to determine how chronic treatment with morphine, a prototypical opioid agonist, induced adaptations to subsequent morphine signaling in different subcellular contexts. Opioids acutely inhibit glutamatergic transmission from medial thalamic (MThal) inputs to the dorsomedial striatum (DMS) via activity at µ-opioid receptors (MORs). MORs are present in somatic and presynaptic compartments of MThal neurons terminating in the DMS. We investigated the effects of chronic morphine treatment on subsequent morphine signaling at MThal-DMS synapses and MThal cell bodies in male and female mice. Surprisingly, chronic morphine treatment increased subsequent morphine inhibition of MThal-DMS synaptic transmission (morphine facilitation) in male, but not female, mice. At MThal cell bodies, chronic morphine treatment decreased subsequent morphine activation of potassium conductance (morphine tolerance) in both male and female mice. In knock-in mice expressing phosphorylation-deficient MORs, chronic morphine treatment resulted in tolerance to, rather than facilitation of, subsequent morphine signaling at MThal-DMS terminals, suggesting phosphorylation deficiency unmasks adaptations that counter the facilitation observed at presynaptic terminals in wild-type mice. The results of this study suggest that the effects of chronic morphine exposure are not ubiquitous; rather adaptations in MOR function may be determined by multiple factors such as subcellular receptor distribution, influence of local circuitry, and sex.

Impact of dental prosthetic treatment and patients' expectations on the seven domains and four-dimensional scale of the Oral Health Impact Profile.

BACKGROUND: Recently, recommendations were given for a new scoring of the Oral Health Impact Profile (OHIP). The original seven domain structure should be replaced by a four-dimensional scale. OBJECTIVES: To investigate the effect of dental prosthetic treatment on the seven domains and the four-dimensional scale of the OHIP-G49/53 questionnaire. METHODS: Seventy four patients were grouped according their pre- and post-treatment situation and the type of treatment they received. Patients completed the OHIP-G49/53 questionnaire before prosthetic treatment (T0), and at 1 week (T1), 3 months (T2) and 6 months (T3) after treatment. Treatment effects on the seven domains and the four dimensions of the OHIP scale were analysed, and the oral health-related quality of life (OHRQoL) was measured. Patients' expectations of their prosthetic treatment were also evaluated. Data were analysed using two-way Mixed ANOVA, regression analysis, and Cronbach's alpha test with a level of significance of α ≤ .017. RESULTS: OHRQoL significantly improved following prosthetic treatment compared with baseline. The largest improvement was found between T0 and T1 evaluations (all p ≤ .001). Unlike the seven-domain scale, the four OHIP dimensions demonstrated further significant improvements across the T1/T2/T3 evaluations (all p ≤ .017). Different pre-treatment findings had different treatment effects on the four OHIP dimensions and seven OHIP domains. Patients' expectations were mainly fulfilled. CONCLUSION: Compared with the seven-domain scale, the four dimensions showed significant follow-up changes, suggesting the four dimensions are suitable for evaluating treatment effects up to 6 months. Clinically meaningful effects of dental prosthetic treatment can be sensitively measured using the four-dimensional OHIP scale.

Phosphorylation bar-coding of free fatty acid receptor 2 is generated in a tissue-specific manner.

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.

[Multistain deep learning as a prognostic and predictive biomarker in colorectal cancer]. / Multistain Deep Learning zur Vorhersage von Prognose und Therapieansprechen im kolorektalen Karzinom.

The tumor immune microenvironment (TIME) plays a crucial prognostic and predictive role in solid malignancies such as colorectal cancer (CRC). Nevertheless, scoring systems based on TIME such as the Immunoscore (IS) are rarely used in clinical practice. Among other reasons, this might be due to the additional time required for manual quantification of tumor-associated immune cells or costs associated with proprietary/commercial solutions. To address these issues, we developed a multistain deep learning model (MSDLM) and trained, validated, and tested it on immunohistochemical image data of different immune cell subtypes from over 1000 patients with CRC. Our model showed high prognostic accuracy and outperformed other clinical, molecular, and immune cell-based parameters. It might also be used for therapy response prediction in rectal cancer patients undergoing neoadjuvant therapy. Leveraging artificial intelligence interpretability/explainability methods, we ascertained that the MSDLM's predictions align with recognized antitumor immune response patterns. Consequently, the AImmunoscore (AIS) could emerge as a potential TIME-based decision-making tool for clinicians.

Expression prevalence and dynamics of GPCR somatostatin receptors 2 and 3 as cancer biomarkers beyond NET: a paired immunohistochemistry approach.

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.

Expression of G protein-coupled receptor GPR19 in normal and neoplastic human tissues.

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.

Improving the Quality and Utility of Electronic Health Record Data through Ontologies.

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.

Clinical Acronym Disambiguation via ChatGPT and BING.

Clinical texts are written with acronyms, abbreviations and medical jargon expressions to save time. This hinders full comprehension not just for medical experts but also laypeople. This paper attempts to disambiguate acronyms with their given context by comparing a web mining approach via the search engine BING and a conversational agent approach using ChatGPT with the aim to see, if these methods can supply a viable resolution for the input acronym. Both approaches are automated via application programming interfaces. Possible term candidates are extracted using natural language processing-oriented functionality. The conversational agent approach surpasses the baseline for web mining without plausibility thresholds in precision, recall and F1-measure, while scoring similarly only in precision for high threshold values.

Low temperature atomic layer deposition of cobalt using dicobalt hexacarbonyl-1-heptyne as precursor.

In this work, we present the development of an atomic layer deposition (ALD) process for metallic cobalt. The process operates at low temperatures using dicobalt hexacarbonyl-1-heptyne [Co2(CO)6HC≡CC5H11] and hydrogen plasma. For this precursor an ALD window in the temperature range between 50 and 110 °C was determined with a constant deposition rate of approximately 0.1 Å/cycle. The upper limit of the ALD window is defined by the onset of the decomposition of the precursor. In our case, decomposition occurs at temperatures of 125 °C and above, resulting in a film growth in chemical vapour deposition mode. The lower limit of the ALD window is around 35 °C, where the reduction of the precursor is incomplete. The saturation behaviour of the process was investigated. X-ray photoelectron spectroscopy measurements could show that the deposited cobalt is in the metallic state. The finally established process in ALD mode shows a homogeneous coating at the wafer level.

Comprehensive Geriatric Assessment and Quality of Life Aspects in Patients with Recurrent/Metastatic Head and Neck Squamous Cell Carcinoma (HNSCC).

To define frailty in older cancer patients, the aim of this study was to assess the geriatric status and quality of life (QoL) aspects in patients suffering from recurrent/metastatic head and neck squamous cell carcinoma (r/m HNSCC) under palliative treatment. A comprehensive geriatric assessment (CGA) was performed on 21 r/m HNSCC patients at two defined assessments, and the QoL aspects and the impact of descriptive data were evaluated. The Kolmogorov-Smirnov test, Spearman's rho correlation, and two-way mixed ANOVA were used for statistical analysis. All patients were found to be "frail". Pain, fatigue, and the burden of illness were the highest-rated symptoms. Oral function and orofacial appearance were highly impaired. A significant impact of descriptive data on the CGA and QoL results was found (all p ≤ 0.05). Thus, the CGA results revealed high frailty, severe comorbidities, and high impairments in QoL aspects. The CGA and QoL results were negatively affected by the primary HNSCC treatment approach, the need for prosthetic treatment, and worse oral functional capacity. Therefore, frailty in r/m HNSCC patients seems to be multidimensional. The evaluation of the CGA and QoL aspects in r/m HNSCC patients can be recommended to detect special needs, organize aftercare, and improve the support for frail and vulnerable cancer patients to create a multidisciplinary treatment approach.