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Abstract A key aspect of nature conservation is knowledge of which aspects of nature to conserve or restore to favor the characteristic diversity of plants in a given area. Here, we used a large plant dataset with >40 000 plots combined with airborne laser scanning (lidar) data to reveal the local characteristics of habitats having a high plant dark diversity—that is, absence of suitable species—at national extent (>43 000 km2). Such habitats have potential for reaching high realized diversity levels and hence are important in a conservation context. We calculated 10 different lidar based metrics (both terrain and vegetation structure) and combined these with seven different field‐based measures (soil chemistry and species indicators). We then used Integrated Nested Laplace Approximation for modelling plant dark diversity across 33 North European habitat types (open landscapes and forests) selected by the European communities to be important. In open habitat types high‐dark‐diversity habitats had relatively low pH, high nitrogen content, tall homogenous vegetation, and overall relatively homogenous terrains (high terrain openness) although with a rather high degree of local microtopographical variations. High‐dark‐diversity habitats in forests had relatively tall vegetation, few natural‐forest indicators, low potential solar radiation input and a low cover of small woody plants. Our results highlight important vegetation, terrain‐ and soil‐related factors that managers and policymakers should be aware of in conservation and restoration projects to ensure a natural plant diversity, for example low nutrient loads, natural microtopography and possibly also open forests with old‐growth elements such as dead wood and rot attacks.

Abstract Electroencephalogram (EEG) datasets from epilepsy patients have been used to develop seizure detection and prediction algorithms using machine learning (ML) techniques with the aim of implementing the learned model in a device. However, the format and structure of publicly available datasets are different from each other, and there is a lack of guidelines on the use of these datasets. This impacts the generatability, generalizability, and reproducibility of the results and findings produced by the studies. In this narrative review, we compiled and compared the different characteristics of the publicly available EEG datasets that are commonly used to develop seizure detection and prediction algorithms. We investigated the advantages and limitations of the characteristics of the EEG datasets. Based on our study, we identified 17 characteristics that make the EEG datasets unique from each other. We also briefly looked into how certain characteristics of the publicly available datasets affect the performance and outcome of a study, as well as the influences it has on the choice of ML techniques and preprocessing steps required to develop seizure detection and prediction algorithms. In conclusion, this study provides a guideline on the choice of publicly available EEG datasets to both clinicians and scientists working to develop a reproducible, generalizable, and effective seizure detection and prediction algorithm.

Abstract Purpose Limited data exist to help surgeons decide between active surveillance (AS) versus treatment for men with favorable intermediate risk (FIR) prostate cancer. To estimate the theoretical excess risk of prostate cancer‐specific mortality (PCSM) with AS versus radical prostatectomy (RP), we determined the risk of PCSM in FIR men undergoing RP and modeled the PCSM risk for AS using a range of increased PSCM scenarios ranging from 1.25x to 2x higher relative to RP. Materials and Methods We retrospectively reviewed data from men undergoing RP from 1988 to 2017 at 8 Veterans Affairs hospitals within the SEARCH cohort. Men with FIR PC were identified using the NCCN risk criteria. Risk of PCSM at 5, 10, and 15 years after RP was estimated. Using these estimates, PCSM was then modeled for AS using a range of increased risk of PCSM relative to RP ranging from 1.25x to 2x higher. Results For the 920 FIR men identified, 5‐, 10‐, and 15‐year survival estimates for PCSM after RP were 99.9%, 99.0%, and 97.8%, respectively. If the risk of PCSM on AS were 1.25–2x greater than RP, there would be 0.54%–2.17% excess risk of PCSM at 15 years. Conclusions The risk of death for FIR after RP is very low. Assuming even modestly increased PCSM with AS versus RP, the excess risk of death for AS in FIR is low even up to 15 years. These data support the consideration of AS as a relatively safe alternative to RP in FIR men, though prospective randomized trials are needed to validate these findings.

Abstract Pharmacokinetics is the cornerstone of understanding drug absorption, distribution, metabolism, and elimination. It is also the key to describing variability in drug response caused by drug‐drug interactions (DDIs), pharmacogenetics, impaired kidney and liver function, etc. This tutorial aims to provide a guideline and step‐by‐step tutorial on essential considerations when designing clinical pharmacokinetic studies and reporting results. This includes a comprehensive guide on how to conduct the statistical analysis and a complete code for the statistical software R. As an example, we created a mock dataset simulating a clinical pharmacokinetic DDI study with 12 subjects who were administered 2 mg oral midazolam with and without an inducer of cytochrome P450 3A. We provide a step‐by‐step guide to the statistical analysis of this clinical pharmacokinetic study, including sample size/power calculation, descriptive statistics, noncompartmental analyses, and hypothesis testing. The different analyses and parameters are described in detail, and we provide a complete R code ready to use in supplementary files. Finally, we discuss important considerations when designing and reporting clinical pharmacokinetic studies. The scope of this tutorial is not limited to DDI studies, and with minor adjustments, it applies to all types of clinical pharmacokinetic studies. This work was done by early career researchers for early career researchers. We hope this tutorial may help early career researchers when getting started on their own pharmacokinetic studies. We encourage you to use this as an inspiration and starting point and continuously evolve your statistical skills.

The pleiotropic protein hepatocyte growth factor (HGF) is the only known ligand of the tyrosine kinase mesenchymal–epithelial transition (cMET) receptor. The HGF/cMET pathway mediates invasion and migration of ovarian cancer cells, and upregulation of HGF/cMET pathway components has been associated with poor prognosis. This study investigated the clinical relevance of circulating HGF in serum of patients with ovarian cancer. Serum HGF (sHGF) was determined by enzyme‐linked immunosorbent assay in a total of 471 serum samples from 82 healthy controls and 113 patients with ovarian cancer (88.5% with ≥ FIGO III). Patient samples were collected at primary diagnosis and at four follow‐up time points throughout treatment and at disease recurrence. Patients with ovarian cancer showed elevated median sHGF levels at primary diagnosis, and sHGF levels transiently increased after surgery and normalized in the course of chemotherapy, even dropping below initial baseline. Higher levels of sHGF were an independent predictor for shorter overall survival (OS) (a) at primary diagnosis (HR = 0.41, 95% CI: 0.22–0.78, P = 0.006), (b) at longitudinal follow‐up time points (after surgery and before/during/after chemotherapy), (c) along the patients’ individual dynamics (HR = 0.21, 95% CI: 0.07–0.63, P = 0.005), and (d) among a subgroup analysis of patients with BRCA1/2 wild‐type ovarian cancer. This is the first study proposing sHGF as an independent prognostic biomarker for ovarian cancer at primary diagnosis and in the course of platinum‐based chemotherapy, irrespective of the postoperative residual disease after surgical debulking. sHGF could be implemented into clinical diagnostics as a CA125 auxiliary tumor marker for individualized prognosis stratification and sHGF‐guided therapy monitoring.

Abstract The aim of the study was to investigate if there is a clinically relevant drug interaction between metformin and codeine. Volunteers were randomized to receive on four separate occasions: (A) orally administered metformin (1 g), (B) intravenously administered metformin (0.5 g), (C) five doses of tablet codeine 25 mg; the last dose was administered together with oral metformin (1 g), and (D) five doses of tablet codeine 25 mg; the last dose was administered together with metformin (0.5 g) intravenously. Blood samples were drawn for 24 h after administration of metformin, and for 6 h after administration of codeine and analyzed using liquid chromatography and tandem mass spectrometry. Healthy volunteers genotyped as CYP2D6 normal metabolizers (*1/*1) without known reduced function variants in the OCT1 gene (rs12208357, rs34130495, rs34059508, and rs72552763) were invited. The median absorption fraction of metformin was 0.31 and was not influenced by codeine intake. The median time to maximum concentration (Tmax) after oral intake of metformin was 2 h without, and 3 h with codeine (p = 0.06). The geometric mean ratios of the areas under the plasma concentration time‐curve (AUCs) for morphine and its metabolites M3G and M6G for oral intake of metformin‐to‐no metformin were 1.21, 1.31, and 1.27, respectively, and for i.v. metformin‐to‐no metformin 1.28, 1.34, and 1.30, respectively. Concomitant oral and i.v. metformin increased the plasma levels of morphine, M3G and M6G. These small pharmacokinetic changes may well contribute to an increased risk of early discontinuation of metformin. Hence, a clinically relevant drug‐drug interaction between metformin and codeine seems plausible.

The tyrosine kinase mesenchymal–epithelial transition (cMET) is typically overexpressed in up to 75% of patients with ovarian cancer, and cMET overexpression has been associated with poor prognosis. The proteolytic release of the soluble cMET (sMET) ectodomain by metalloproteases, a process called ectodomain shedding, reflects the malignant potential of tumour cells. sMET can be detected in the human circulation and has been proposed as biomarker in several cancers. However, the clinical relevance of sMET in ovarian cancer as blood‐based biomarker is unknown and was therefore investigated in this study. sMET levels were determined by enzyme‐linked immunosorbent assay in a set of 432 serum samples from 85 healthy controls and 86 patients with ovarian cancer (87% FIGO III/IV). Samples were collected at primary diagnosis, at four longitudinal follow‐up time points during the course of treatment and at disease recurrence. Although there was no significant difference between median sMET levels at primary diagnosis of ovarian cancer vs. healthy controls, increased sMET levels at primary diagnosis were an independent predictor of shorter PFS (HR = 0.354, 95% CI: 0.130–0.968, P = 0.043) and shorter OS (HR = 0.217, 95% CI: 0.064–0.734, P = 0.014). In the follow‐up samples, sMET levels were prognostically most informative after the first three cycles of chemotherapy, with high sMET levels being an independent predictor of shorter PFS (HR = 0.245, 95% CI: 0.100–0.602, P = 0.002). This is the first study to suggest that sMET levels in the blood can be used as an independent prognostic biomarker for ovarian cancer. Patients at high risk of recurrence and with poor prognosis, as identified based on sMET levels in the blood, could potentially benefit from cMET‐directed therapies or other targeted regimes, such as PARP inhibitors or immunotherapy.

Platinum‐based compounds remain a well‐established chemotherapy for cancer treatment despite their adverse effects which substantially restrict the therapeutic windows of the drugs. Both the cell type‐specific toxicity and the clinical responsiveness of tumors have been associated with mechanisms that alter drug entry and export. We sought to identify pharmacological agents that promote cisplatin (CP) efficacy by augmenting the levels of drug‐induced DNA lesions in malignant cells and simultaneously protecting normal tissues from accumulating such damage and from functional loss. Formation and persistence of platination products in the DNA of individual nuclei were measured in drug‐exposed cell lines, in primary human tumor cells and in tissue sections using an immunocytochemical method. Using a mouse model of CP‐induced toxicity, the antihistaminic drug diphenhydramine (DIPH) and two methylated derivatives decreased DNA platination in normal tissues and also ameliorated nephrotoxicity, ototoxicity, and neurotoxicity. In addition, DIPH sensitized multiple cancer cell types, particularly ovarian cancer cells, to CP by increasing intracellular uptake, DNA platination, and/or apoptosis in cell lines and in patient‐derived primary tumor cells. Mechanistically, DIPH diminished transport capacity of CP efflux pumps MRP2, MRP3, and MRP5 particularly in its C2+C6 bimethylated form. Overall, we demonstrate that DIPH reduces side effects of platinum‐based chemotherapy and simultaneously inhibits key mechanisms of platinum resistance. We propose that measuring DNA platination after ex vivo exposure may predict the responsiveness of individual tumors to DIPH‐like modulators.

Abstract Increasing goose population sizes gives rise to conflicts with human socioeconomic interests and in some circumstances conservation interests. Grazing by high abundances of geese in grasslands is postulated to lead to a very short and homogeneous sward height negatively affecting cover for breeding meadow birds and impacting survival of nests and chicks. We studied the effects of spring grazing barnacle geese Branta leucopsis and brent geese Branta bernicla on occupancy of extensively farmed freshwater grasslands by nesting and brood‐rearing waders on the island Mandø in the Danish Wadden Sea. We hypothesized that goose grazing would lead to a shorter grass sward, negatively affecting the field occupancy by territorial/nesting and chick‐rearing waders, particularly species preferring taller vegetation. Goose grazing led to a short grass sward (

Metastasis‐associated in colon cancer 1 (MACC1) and S100 calcium‐binding protein A4 (S100A4) are prominent inducers of tumor progression and metastasis. For the first time, we systematically tracked circulating serum levels of MACC1 and S100A4 transcripts in the course of surgery and chemotherapy and analyzed their clinical relevance for ovarian cancer. MACC1 and S100A4 transcripts were quantified in a total of 318 serum samples from 79 ovarian cancer patients by RT‐qPCR and digital droplet PCR, respectively. MACC1 and S100A4 transcripts were significantly elevated in serum of ovarian cancer patients, compared to healthy controls (P = 0.024; P

Background Careful identification of nerves during head and neck surgery is essential to prevent nerve damage. Currently, nerves are identified based on anatomy and appearance, optionally combined with electromyography (EMG). In challenging cases, nerve damage is reported in up to 50%. Recently, optical techniques, like diffuse reflectance spectroscopy (DRS) and fluorescence spectroscopy (FS) show potential to improve nerve identification. Methods 212 intra‐operative DRS/FS measurements were performed. Small nerve branches (1–3 mm), on near‐nerve adipose tissue, muscle and subcutaneous fat were measured during 11 surgical procedures. Tissue identification was based on quantified concentrations of optical absorbers and scattering parameters. Results Clinically comprehensive parameters showed significant differences (