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Precision cancer medicine (PCM) to support the treatment of solid tumors requires minimally invasive diagnostics. Here, we describe the development of fine‐needle aspiration biopsy‐based (FNA) molecular cytology which will be increasingly important in diagnostics and adaptive treatment. We provide support for FNA‐based molecular cytology having a significant potential to replace core needle biopsy (CNB) as a patient‐friendly potent technique for tumor sampling for various tumor types. This is not only because CNB is a more traumatic procedure and may be associated with more complications compared to FNA‐based sampling, but also due to the recently developed molecular methods used with FNA. Recent studies show that image‐guided FNA in combination with ultrasensitive molecular methods also offers opportunities for characterization of the tumor microenvironment which can aid therapeutic decisions. Here we provide arguments for an increased implementation of molecular FNA‐based sampling as a patient‐friendly diagnostic method, which may, due to its repeatability, facilitate regular sampling that is needed during different treatment lines, to provide tumor information, supporting treatment decisions, shortening lead times in healthcare, and benefit healthcare economics.

Abstract Background and Aims Intrahepatic cholangiocarcinoma (iCC) is an aggressive tumor, usually detected at an advanced stage. Our aim was to investigate the potential of body composition analysis (BCA) derived from presurgical staging computed tomography (CT) in predicting perisurgical complications. Methods In this retrospective cohort study, we enrolled 86 patients who underwent CT imaging prior to liver surgery. Cox and logistic regression were performed to assess risk factors for prolonged hospital and intensive care unit (ICU) stays, as well as the occurrence of various complications. BCA parameters served as covariates besides conventional risk factors. Results Postoperative complications after resection of iCC significantly prolonged the overall length of hospitalization (p

Abstract Background Obesity is a known cardiovascular risk factor and associated with higher postoperative complication rates in patients undergoing cardiac surgery. In heart failure (HF), conflicting evidence in terms of survival has been reported, whereas sarcopenia is associated with poor prognosis. An increasing number of HF patients require left ventricular assist device (LVAD) implantations. The postoperative mortality has improved in recent years but is still relatively high. The impact of body composition on outcome in this population remains unclear. The aim of this investigation was to examine the preoperative computed tomography (CT) body composition as a predictor of the postoperative outcome in advanced HF patients, who receive LVAD implantations. Methods Preoperative CT scans of 137 patients who received LVADs between 2015 and 2020 were retrospectively analysed using an artificial intelligence (AI)‐powered automated software tool based on a convolutional neural network, U‐net, developed for image segmentation (Visage Version 7.1, Visage Imaging GmbH, Berlin, Germany). Assessment of body composition included visceral and subcutaneous adipose tissue areas (VAT and SAT), psoas and total abdominal muscle areas and sarcopenia (defined by lumbar skeletal muscle indexes). The body composition parameters were correlated with postoperative major complication rates, survival and postoperative 6‐min walk distance (6MWD) and quality of life (QoL). Results The mean age of patients was 58.21 ± 11.9 years; 122 (89.1%) were male. Most patients had severe HF requiring inotropes (Interagency Registry for Mechanically Assisted Circulatory Support [INTERMACS] profile I–III, 71.9%) secondary to coronary artery diseases or dilated cardiomyopathy (96.4%). Forty‐four (32.1%) patients were obese (body mass index ≥ 30 kg/m2), 96 (70.1%) were sarcopene and 19 (13.9%) were sarcopene obese. Adipose tissue was associated with a significantly higher risk of postoperative infections (VAT 172.23 cm2 [54.96, 288.32 cm2] vs. 124.04 cm2 [56.57, 186.25 cm2], P = 0.022) and in‐hospital mortality (VAT 168.11 cm2 [134.19, 285.27 cm2] vs. 135.42 cm2 [49.44, 227.91 cm2], P = 0.033; SAT 227.28 cm2 [139.38, 304.35 cm2] vs. 173.81 cm2 [97.65, 254.16 cm2], P = 0.009). Obese patients showed no improvement of 6MWD and QoL within 6 months postoperatively (obese: +0.94 ± 161.44 months, P = 0.982; non‐obese: +166.90 ± 139.00 months, P

Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest of cancers. Attempts to develop targeted therapies still need to be established. Some oncogenic mechanisms in PDAC carcinogenesis harness the EGFR/ERBB receptor family. To explore the effects on pancreatic lesions, we attempted simultaneous blockade of all ERBB ligands in a PDAC mouse model. To this end, we engineered a molecular decoy, TRAP‐FC, comprising the ligand‐binding domains of both EGFR and ERBB4 and able to trap all ERBB ligands. Next, we generated a transgenic mouse model (CBATRAP/0) expressing TRAP‐FC ubiquitously under the control of the chicken‐beta‐actin promoter and crossed these mice with KRASG12D/+ mice (Kras) to generate Trap/Kras mice. The resulting mice displayed decreased emergence of spontaneous pancreatic lesion areas and exhibited reduced RAS activity and decreased activities of ERBBs, with the exception of ERBB4, which showed increased activity. To identify the involved receptor(s), we employed CRISPR/Cas9 DNA editing to singly delete each ERBB receptor in the human pancreatic carcinoma cell line Panc‐1. Ablation of each ERBB family member, especially the loss of EGFR or ERBB2/HER2, altered signaling downstream of the other three ERBB receptors and decreased cell proliferation, migration, and tumor growth. We conclude that simultaneously blocking the entire ERBB receptor family is therapeutically more effective than individually inhibiting only one receptor or ligand in terms of reducing pancreatic tumor burden. In summary, trapping all ERBB ligands can reduce pancreatic lesion area and RAS activity in a murine model of pancreatic adenocarcinoma; hence, it might represent a promising approach to treat PDAC in patients.

Abstract Background Body composition alterations are frequent in patients with cancer or chronic liver disease, but their prognostic value remains unclear in many cancer entities. Objective We investigated the impact of disease aetiology and body composition after surgery for intrahepatic cholangiocarcinoma (iCCA), a rare and understudied cancer entity in European and North American cohorts. Methods Computer tomography‐based assessment of body composition at the level of the third lumbar vertebra was performed in 173 patients undergoing curative‐intent liver resection for iCCA at the Department of Surgery, Charité – Universitätsmedizin Berlin. Muscle mass and ‐composition as well as subcutaneous and visceral adipose tissue quantity were determined semi‐automatically. (Secondary) sarcopenia, sarcopenic obesity, myosteatosis, visceral and subcutaneous obesity were correlated to clinicopathological data. Results Sarcopenia was associated with post‐operative morbidity (intraoperative transfusions [p = 0.027], Clavien–Dindo ≥ IIIb complications [p = 0.030], post‐operative comprehensive complication index, CCI [p 65, fresh frozen plasma transfusions) as independently prognostic for overall survival. Conclusion This study evidenced a high prevalence of MAFLD in iCCA, suggesting its potential contribution to disease aetiology. Alterations of muscle mass and adipose tissue were more frequent in patients with MAFLD.

Abstract Citizen and community science datasets are typically collected using flexible protocols. These protocols enable large volumes of data to be collected globally every year; however, the consequence is that these protocols typically lack the structure necessary to maintain consistent sampling across years. This can result in complex and pronounced interannual changes in the observation process, which can complicate the estimation of population trends because population changes over time are confounded with changes in the observation process. Here we describe a novel modelling approach designed to estimate spatially explicit species population trends while controlling for the interannual confounding common in citizen science data. The approach is based on Double machine learning, a statistical framework that uses machine learning (ML) methods to estimate population change and the propensity scores used to adjust for confounding discovered in the data. ML makes it possible to use large sets of features to control for confounding and to model spatial heterogeneity in trends. Additionally, we present a simulation method to identify and adjust for residual confounding missed by the propensity scores. To illustrate the approach, we estimated species trends using data from the citizen science project eBird. We used a simulation study to assess the ability of the method to estimate spatially varying trends when faced with realistic confounding and temporal correlation. Results demonstrated the ability to distinguish between spatially constant and spatially varying trends. There were low error rates on the estimated direction of population change (increasing/decreasing) at each location and high correlations on the estimated magnitude of population change. The ability to estimate spatially explicit trends while accounting for confounding inherent in citizen science data has the potential to fill important information gaps, helping to estimate population trends for species and/or regions lacking rigorous monitoring data.

Abstract Background For the topical treatment of plaque psoriasis, vitamin D analogues and corticosteroids are used as a fixed combination, which is available in different galenic preparations. Objectives The aim of this study was to investigate the effectiveness and tolerability of calcipotriol/betamethasone (Cal/BD) cutaneous foam in a real‐world setting. Methods Overall, 107 adult patients with at least mild plaque psoriasis as measured by the Investigator Global Assessment (IGA) were included and treated for 4 weeks. Affected body surface area (BSA), plaque locations, and Psoriasis Area and Severity Index (PASI) were documented at baseline, after 4 weeks and at the end of the study. Pruritus, overall patient satisfaction, tolerability and convenience of use, as well as quality of life (DLQI) were also evaluated. Results In total, 96% of the patients suffered from mild to moderate psoriasis vulgaris. Of all patients included, 76% had previously received topical therapy. Under treatment with Cal/BD aerosol foam, the mean IGA score was reduced from 2.49 to 1.28 points (p

Abstract In situ data are an essential need in the analyses of past and current climate change. All over the world, different data rescue activities try to extend existing time series and to retrieve data in spatial and temporal data sparse regions. Also in Europe, part of the historic data is still only available in paper archives, without any digital access to these sources. The EUMETNET Data Rescue activity was started in order to investigate the potential for additional long‐term stations, to monitor the progress of data rescue in European countries and to support participants with know‐how exchange and international connections to facilitate data exchange. The activity raised the awareness of the need for data rescue and ongoing activities. This paper will provide information on the data rescue activities of 4 EUMETNET countries focusing on different aspects and in different states of the data rescue process. While Austria, Croatia and Slovenia are connected by a partly common history which is also displayed in the history of their meteorological network, Catalonia has a different historical background. Nevertheless, the problems data rescue is confronted with are similar for all activities. Therefore, the selected countries will provide a good overview of the problems and solutions discussed during the EUMETNET meetings. This paper wants to offer insight into different strategies for data rescue as well as into ongoing activities. Moreover, the importance of cooperation in regard to data rescue is underlined and examples of possible partnerships are provided.

Abstract Background Epididymal sperm can be collected post‐castration or post‐mortem. This method has already been described for alpaca (Vicugna pacos), but little data are available on success rate and the influence of diluent on it. Objective The aim was to investigate the effectiveness of epididymis incision as an extraction method. Method Post‐castration epididymides (n = 78) were incised and semen was collected from cut surfaces. Further sperm were flushed with two semen extenders. For the left epididymis, a diluent without animal proteins and for the right, a diluent with egg yolk was utilised. Collected sperms were immediately spermatologically examined. Results Due to incorrect measurements, the samples of seven epididymides were not analysed. An evaluation was possible in 58 samples. Average density was 108.80 ± 83.28 million/mL and motility was 53.30 ± 18.17%. On average, 76.70 ± 11.60% of the sperm were vital in eosin‐stained specimens. In the hypoosmotic swelling test, an average of 69.50 ± 10.48% of the sperm had an intact plasma membrane. Semen extender had no effect on spermatological parameters (p > 0.05). Overall success rate of sperm recovery was 83%. Extraction of epididymal sperm was possible in 68.80% of the 2‐year‐old males. The 13 epididymides from which no sperm recovery was possible were histologically examined and for 10, there was no histological evidence of sperm. The corrected success rate was 95.60%. Conclusion Testicular volume (p = 0.0453), but not age (p = 0.62), had an effect on the probability of obtaining sperm.

Abstract Extracellular vesicles (EVs) released by a variety of cell types have been shown to act as a natural delivery system for bioactive molecules such as RNAs and proteins. EV therapy holds great promise as a safe and cell‐free therapy for many immunological and degenerative diseases. However, translation to clinical application is limited by several factors, including insufficient large‐scale manufacturing technologies and low yield. We have developed a novel drug delivery platform technology, BioDrone™, based on cell‐derived vesicles (CDVs) produced from diverse cell sources by using a proprietary extrusion process. This extrusion technology generates nanosized vesicles in far greater numbers than naturally obtained EVs. We demonstrate that the CDVs are surrounded by a lipid bilayer membrane with a correct membrane topology. Physical, biochemical and functional characterisation results demonstrate the potential of CDVs to act as effective therapeutics. Umbilical cord mesenchymal stem cell (UCMSC)‐derived CDVs exhibit a biological activity that is similar to UCMSCs or UCMSC‐derived EVs. Lastly, we present the establishment of a GMP‐compliant process to allow the production of a large number of UCMSC‐CDVs in a reproducible manner. GMP‐compliant manufacturing of CDVs will facilitate the preclinical and clinical evaluation of these emerging therapeutics in anti‐inflammatory or regenerative medicine. This study also represents a crucial step in the development of this novel drug delivery platform based on CDVs.

Abstract Artificial light at night (ALAN) is adversely affecting natural systems worldwide, including the disorienting influence of ALAN on nocturnally migrating birds. Understanding how ALAN trends are developing across species' seasonal distributions will inform mitigation efforts, such as Lights Out programs. Here, we intersect ALAN annual trend estimates (1992–2013) with weekly estimates of relative abundance for 42 nocturnally migrating passerine bird species that breed in North America using observations from the eBird community science database for the combined period 2005–2020. We use a cluster analysis to identify species with similar weekly associations with ALAN trends. Our results identified three prominent clusters. Two contained species that occurred in northeastern and western North America during the breeding season. These species were associated with moderate ALAN levels and weak negative ALAN trends during the breeding season, and low ALAN levels and strong positive ALAN trends during the nonbreeding season. The difference between the breeding and nonbreeding seasons was lower for species that occurred in northern South America and greater for species that occurred in Central America during the nonbreeding season. For species that occurred in South America during the nonbreeding season, positive ALAN trends increased in strength as species migrated through Central America, especially in the spring. The third cluster contained species whose associations with positive ALAN trends remained high across the annual cycle, peaking during migration, especially in the spring. These species occurred in southeastern North America during the breeding season where they were associated with high ALAN levels, and in northern South America during the nonbreeding season where they were associated with low ALAN levels. Our findings suggest reversing ALAN trends in Central America during migration, especially in the spring, would benefit the most individuals of the greatest number of species. Reversing ALAN trends in southeastern North America during the breeding season and Central America during the nonbreeding season would generate the greatest benefits outside of migration.

Abstract Background The protein proAKAP4 is crucial for sperm motility and has been suggested as an indicator of male fertility. We determined the relationship between proAKAP4 concentration and sperm motility parameters in mice, and investigated the effects of cryopreservation on these variables. Methods Computer‐assisted sperm analysis and ELISA were applied to determine sperm motility and proAKAP4 concentration in fresh and frozen‐thawed epididymal sperm of SWISS, B6D2F1, C57BL/6N, and BALB/c mice. Results ProAKAP4 levels ranged between 12 and 89 ng/ml and did not differ between fresh and frozen‐thawed samples, or between strains. We found a negative relationship between proAKAP4 levels and some sperm motility parameters. Sperm traits differed between strains, and cryopreservation negatively affected sperm velocity but not sperm direction parameters. Conclusion ProAKAP4 levels in epididymal mouse spermatozoa were unaffected by cryopreservation, highlighting the robustness of this parameter as a potentially time‐independent marker for sperm motility and fertility. The high individual variation in proAKAP4 levels supports the potential role of proAKAP4 as a marker for sperm quality, though we found no positive, and even negative relationships between proAKAP4 levels and some sperm motility parameters. Future studies have to investigate the significance of proAKAP4 as an indicator for fertility in mice.

Abstract Interest in mesenchymal stem cell derived extracellular vesicles (MSC‐EVs) as therapeutic agents has dramatically increased over the last decade. Current approaches to the characterization and quality control of EV‐based therapeutics include particle tracking techniques, Western blotting, and advanced cytometry, but standardized methods are lacking. In this study, we established and verified quartz crystal microbalance (QCM) as highly sensitive label‐free immunosensing technique for characterizing clinically approved umbilical cord MSC‐EVs enriched by tangential flow filtration and ultracentrifugation. Using QCM in conjunction with common characterization methods, we were able to specifically detect EVs via EV (CD9, CD63, CD81) and MSC (CD44, CD49e, CD73) markers. Furthermore, analysis of QCM dissipation versus frequency allowed us to quantitatively determine the ratio of marker‐specific EVs versus non‐vesicular particles (NVPs) – a parameter that cannot be obtained by any other technique so far. Additionally, we characterized the topography and elasticity of these EVs by atomic force microscopy (AFM), enabling us to distinguish between EVs and NVPs in our EV preparations. This measurement modality makes it possible to identify EV sub‐fractions, discriminate between EVs and NVPs, and to characterize EV surface proteins, all with minimal sample preparation and using label‐free measurement devices with low barriers of entry for labs looking to widen their spectrum of characterization techniques. Our combination of QCM with impedance measurement (QCM‐I) and AFM measurements provides a robust multi‐marker approach to the characterization of clinically approved EV therapeutics and opens the door to improved quality control.

Abstract Background Isolated myelosarcoma of infancy is a rare presentation of acute myelogenous leukaemia (AML). Because of its rarity and early onset in infancy underlying genetic predisposition is potentially relevant in disease initiation. Methods and Results We report an oncologic emergency in an infant with thoracic and intraspinal aleukaemic myeloid sarcoma causing acute myelon compression and lower leg palsy. Whole‐exome sequencing of the patient's germline DNA identified a rare PALB2 (OMIM 610355) variant (p.A1079S), which is located in a domain critical for the gene's proper function within the homology‐directed repair pathway. In line with potential DNA damage repair defects mediated by the PALB2 deregulation, the patient's fibroblasts showed increased sensitivity towards radiation and DNA intercalating agents. Conclusion Therefore, we suggest PALB2 p.A1079S as a pathogenic variant potentially contributing to the here observed patient phenotype.

There are increasing demands for informative cancer biomarkers, accessible via minimally invasive procedures, both for initial diagnostics and for follow‐up of personalized cancer therapy, including immunotherapy. Fine‐needle aspiration (FNA) biopsy provides ready access to relevant tissue samples; however, the minute amounts of sample require sensitive multiplex molecular analysis to be of clinical biomarker utility. We have applied proximity extension assays (PEA) to analyze 167 proteins in FNA samples from patients with breast cancer (BC; n = 25) and benign lesions (n = 32). We demonstrate that the FNA BC samples could be divided into two main clusters, characterized by differences in expression levels of the estrogen receptor (ER) and the proliferation marker Ki67. This clustering corresponded to some extent to established BC subtypes. Our analysis also revealed several proteins whose expression levels differed between BC and benign lesions (e.g., CA9, GZMB, IL‐6, VEGFA, CXCL11, PDL1, and PCD1), as well as several chemokines correlating with ER and Ki67 status (e.g., CCL4, CCL8, CCL20, CXCL8, CXCL9, and CXCL17). Finally, we also identified three signatures that could predict Ki67 status, ER status, and tumor grade, respectively, based on a small subset of proteins, which was dominated by chemokines. To our knowledge, expression profiles of CCL13 in benign lesions and BC have not previously been described but were shown herein to correlate with proliferation (P = 0.00095), suggesting a role in advanced BC. Given the broad functional range of the proteins analyzed, immune‐related proteins were overrepresented among the observed alterations. Our pilot study supports the emerging role of chemokines in BC progression. Due to the minimally traumatic sampling and clinically important molecular information for therapeutic decisions, this methodology is promising for future immunoscoring and monitoring of treatment efficacy in BC.

Abstract The lack of approved anti‐inflammatory and neuroprotective therapies in otology has been acknowledged in the last decades and recent approaches are heralding a new era in the field. Extracellular vesicles (EVs) derived from human multipotent (mesenchymal) stromal cells (MSC) can be enriched in vesicular secretome fractions, which have been shown to exert effects (eg, neuroprotection and immunomodulation) of their parental cells. Hence, MSC‐derived EVs may serve as novel drug candidates for several inner ear diseases. Here, we provide first evidence of a strong neuroprotective potential of human stromal cell‐derived EVs on inner ear physiology. In vitro, MSC‐EV preparations exerted immunomodulatory activity on T cells and microglial cells. Moreover, local application of MSC‐EVs to the inner ear significantly attenuated hearing loss and protected auditory hair cells from noise‐induced trauma in vivo. Thus, EVs derived from the vesicular secretome of human MSC may represent a next‐generation biological drug that can exert protective therapeutic effects in a complex and nonregenerating organ like the inner ear.

Abstract Knowledge Graphs have been fast emerging as the de facto standard to model and explore knowledge in weakly structured data. Large corpora of documents constitute a source of weakly structured data of particular interest for both the academic and business world. Key examples include scientific publications, technical reports, manuals, patents, regulations, etc. Such corpora embed many facts that are elementary to critical decision making or enabling new discoveries. In this paper, we present a scalable cloud platform to create and serve Knowledge Graphs, which we named corpus processing service (CPS). Its purpose is to process large document corpora, extract the content and embedded facts, and ultimately represent these in a consistent knowledge graph that can be intuitively queried. To accomplish this, we use state‐of‐the‐art natural language understanding models to extract entities and relationships from documents converted with our previously presented corpus conversion service platform. This pipeline is complemented with a newly developed graph engine which ensures extremely performant graph queries and provides powerful graph analytics capabilities. Both components are tightly integrated and can be easily consumed through REST APIs. Additionally, we provide user interfaces to control the data ingestion flow and formulate queries using a visual programming approach. The CPS platform is designed as a modular microservice system operating on Kubernetes clusters. Finally, we validate the quality of queries on our end‐to‐end knowledge pipeline in a real‐world application in the oil and gas industry.

There are increasing demands for informative cancer biomarkers, accessible via minimally invasive procedures, both for initial diagnostics and to follow‐up personalized cancer therapy. Fine‐needle aspiration (FNA) biopsy provides ready access to relevant tissues; however, the minute sample amounts require sensitive multiplex molecular analysis to achieve clinical utility. We have applied proximity extension assays (PEA) and NanoString (NS) technology for analyses of proteins and of RNA, respectively, in FNA samples. Using samples from patients with breast cancer (BC, n = 25) or benign lesions (n = 33), we demonstrate that these FNA‐based molecular analyses (a) can offer high sensitivity and reproducibility, (b) may provide correct diagnosis in shorter time and at a lower cost than current practice, (c) correlate with results from routine analysis (i.e., benchmarking against immunohistochemistry tests for ER, PR, HER2, and Ki67), and (d) may also help identify new markers related to immunotherapy. A specific 11‐protein signature, including FGF binding protein 1, decorin, and furin, distinguished all cancer patient samples from all benign lesions in our main cohort and in smaller replication cohort. Due to the minimally traumatic sampling and rich molecular information, this combined proteomics and transcriptomic methodology is promising for diagnostics and evaluation of treatment efficacy in BC.