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Abstract Trace elements are important for human health but may exert toxic or adverse effects. Mechanisms of uptake, distribution, metabolism, and excretion are partly under genetic control but have not yet been extensively mapped. Here we report a comprehensive multi-element genome-wide association study of 57 essential and non-essential trace elements. We perform genome-wide association meta-analyses of 14 trace elements in up to 6564 Scandinavian whole blood samples, and genome-wide association studies of 43 trace elements in up to 2819 samples measured only in the Trøndelag Health Study (HUNT). We identify 11 novel genetic loci associated with blood concentrations of arsenic, cadmium, manganese, selenium, and zinc in genome-wide association meta-analyses. In HUNT, several genome-wide significant loci are also indicated for other trace elements. Using two-sample Mendelian randomization, we find several indications of weak to moderate effects on health outcomes, the most precise being a weak harmful effect of increased zinc on prostate cancer. However, independent validation is needed. Our current understanding of trace element-associated genetic variants may help establish consequences of trace elements on human health.

Abstract More than 700,000 tons of food are wasted annually in Denmark where dairy products are among the 10 most wasted food products. Therefore, this study aims to analyze Danish consumers’ understanding of the best‐before‐date label and relational patterns for different knowledge‐attitude‐behavior factors influencing their willingness to buy (WTB) dairy products close to the best‐before‐date. Respondents (n = 436) from an online survey were segmented into four segments based on (i) their frequency of purchasing and (ii) their WTB dairy products close to the best‐before‐date: low/low (n = 53), medium/low (n149), medium/high (n = 190), and high/high (n = 44). All four segments had a relatively high understanding of the best‐before‐date label (total mean score = 2.43). For the medium/high and high/high segments, drivers for buying dairy products close to the best‐before‐date were avoidance of food waste, reduced price, and organic certification. However, the low/low and medium/low segments refrained from purchasing dairy products close to the best‐before‐date due to health concerns and low‐quality perception and found them unappetizing. Furthermore, there seems to be a tendency for an age‐dependent pattern. Older respondents (low/low and medium/low) had a higher risk perception than the younger respondents (medium/high and high/high). Consumers’ level of risk perception and food disgust sensitivity are the actual drivers or barriers for consumers’ WTB dairy products close to the best‐before‐date and not their level of knowledge. The results obtained from this study contribute valuable insights into consumer values and can be crucial for developing strategies to reduce food waste in an environment where consumers make their purchasing decisions.

Abstract Background Lung cancer is associated with the greatest cancer mortality as it typically presents with incurable distributed disease. Biomarkers relevant to risk assessment for the detection of lung cancer continue to be a challenge because they are often not detectable during the asymptomatic curable stage of the disease. A solution to population-scale testing for lung cancer will require a combination of performance, scalability, cost-effectiveness, and simplicity. Methods One solution is to measure the activity of serum available enzymes that contribute to the transformation process rather than counting biomarkers. Protease enzymes modify the environment during tumor growth and present an attractive target for detection. An activity based sensor platform sensitive to active protease enzymes is presented. A panel of 18 sensors was used to measure 750 sera samples from participants at increased risk for lung cancer with or without the disease. Results A machine learning approach is applied to generate algorithms that detect 90% of cancer patients overall with a specificity of 82% including 90% sensitivity in Stage I when disease intervention is most effective and detection more challenging. Conclusion This approach is promising as a scalable, clinically useful platform to help detect patients who have lung cancer using a simple blood sample. The performance and cost profile is being pursued in studies as a platform for population wide screening.

Current rock engineering design in drill and blast tunnelling primarily relies on engineers' observational assessments. Measure While Drilling (MWD) data, a high-resolution sensor dataset collected during tunnel excavation, is underutilised, mainly serving for geological visualisation. This study aims to automate the translation of MWD data into actionable metrics for rock engineering. It seeks to link data to specific engineering actions, thus providing critical decision support for geological challenges ahead of the tunnel face. Leveraging a large and geologically diverse dataset of ∼500,000 drillholes from 15 tunnels, the research introduces models for accurate rock mass quality classification in a real-world tunnelling context. Both conventional machine learning and image-based deep learning are explored to classify MWD data into Q-classes and Q-values—examples of metrics describing the stability of the rock mass—using both tabular- and image data. The results indicate that the K-nearest neighbours algorithm in an ensemble with tree-based models using tabular data effectively classifies rock mass quality. It achieves a cross-validated balanced accuracy of 0.86 in classifying rock mass into the Q-classes A, B, C, D, E1, E2, and 0.95 for a binary classification with E versus the rest. Classification using a CNN with MWD-images for each blasting round resulted in a balanced accuracy of 0.82 for binary classification. Regressing the Q-value from tabular MWD-data achieved cross-validated R2 and MSE scores of 0.80 and 0.18 for a similar ensemble model as in classification. High performance in regression and classification boosts confidence in automated rock mass assessment. Applying advanced modelling on a unique dataset demonstrates MWD data's value in improving rock mass classification accuracy and advancing data-driven rock engineering design, reducing manual intervention.

Abstract Background We aimed to investigate whether alpha‐galactosylceramide (α‐GalCer)‐producing Bacteroides fragilis could induce natural killer T (NKT) cells in nonobese diabetic (NOD) mice and reduce their diabetes incidence. Methods Five‐week‐old female NOD mice were treated orally with B. fragilis, and islet pathology and diabetes onset were monitored. Immune responses were analyzed by flow cytometry and multiplex technology. Effects of ultraviolet (UV)‐killed α‐GalCer‐producing B. fragilis and their culture medium on invariant NKT (iNKT) cells were tested ex vivo on murine splenocytes, and the immunosuppressive capacity of splenocytes from B. fragilis‐treated NOD mice were tested by adoptive transfer to nonobese diabetic/severe combined immunodeficiency (NOD/SCID) mice. Results B. fragilis reduced the diabetes incidence from 69% to 33% and the percent of islets with insulitis from 40% to 7%, which doubled the serum insulin level compared with the vehicle‐treated control mice. Furthermore, the early treatment reduced proinflammatory mediators in the serum, whereas the proportion of CD4+ NKT cell population was increased by 33%. B. fragilis growth media stimulated iNKT cells and anti‐inflammatory M2 macrophages ex vivo in contrast to UV‐killed bacteria, which had no effect, strongly indicating an α‐GalCer‐mediated effect. Adoptive transfer of splenocytes from B. fragilis‐treated NOD mice induced a similar diabetes incidence as splenocytes from untreated NOD mice. Conclusions B. fragilis induced iNKT cells and M2 macrophages and reduced type 1 diabetes in NOD mice. The protective effect seemed to be more centered on gut–pancreas interactions rather than a systemic immunosuppression. B. fragilis should be considered for probiotic use in individuals at risk of developing type 1 diabetes.

Background: Robust optimization has been suggested as an approach to reduce the irradiated volume in lung Stereotactic Body Radiation Therapy (SBRT). We performed a retrospective planning study to investigate the potential benefits over Planning Target Volume (PTV)-based planning. Material and methods: Thirty-nine patients had additional plans using robust optimization with 5-mm isocenter shifts of the Gross Tumor Volume (GTV) created in addition to the PTV-based plan used for treatment. The optimization included the mid-position phase and the extreme breathing phases of the 4D-CT planning scan. The plans were compared for tumor coverage, isodose volumes, and doses to Organs At Risk (OAR). Additionally, we evaluated both plans with respect to observed tumor motion using the peak tumor motion seen on the planning scan and cone-beam CTs. Results: Statistically significant reductions in irradiated isodose volumes and doses to OAR were achieved with robust optimization, while preserving tumor dose. The reductions were largest for the low-dose volumes and reductions up to 188 ccm was observed. The robust evaluation based on observed peak tumor motion showed comparable target doses between the two planning methods. Accumulated mean GTV-dose was increased by a median of 4.46 Gy and a non-significant increase of 100 Monitor Units (MU) was seen in the robust optimized plans. Interpretation: The robust plans required more time to prepare, and while it might not be a feasible planning strategy for all lung SBRT patients, we suggest it might be useful for selected patients.

Abstract The atmospheric large‐scale environment determines the occurrence of local extreme precipitation, and it is unclear how climate change affects this relationship. Here we investigate the present‐day relationship between large‐scale circulation types (CTs) and daily precipitation extremes over Scandinavia and its future change. A 50‐member EC‐Earth3 large ensemble is used to assess future changes against internal variability. We show that CTs are related to extreme precipitation over the entire domain. The intensity of extreme daily precipitation increases in all seasons in the future climate, generally following the strength of warming in the six different future scenarios considered. However, no significant future change is found in the relationship between extreme precipitation and the CTs in any season or scenario. The results have important implications for applications that rely on the stability of this relationship, such as statistical and event‐based dynamical downscaling of future weather and climate predictions and long‐term climate projections.

BackgroundMigraine has an increased prevalence in several immune disorders, but genetic cause-effect relationships remain unclear. Mendelian randomization (MR) was used in this study to explore whether immune diseases are causally associated with migraine and its subtypes.MethodsWe conducted a two-sample bidirectional multivariate Mendelian randomization study. Single-nucleotide polymorphisms (SNP) for six immune diseases, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes mellitus (T1D), allergic rhinitis (AR), asthma and psoriasis, were used as genetic instrumental variables. Summary statistics for migraine were obtained from 3 databases: the International Headache Genetics Consortium (IHGC), UK Biobank, and FinnGen study. MR analyses were performed per outcome database for each exposure and subsequently meta-analyzed. Reverse MR analysis was performed to determine whether migraine were risk factors for immune diseases. In addition, we conducted a genetic correlation to identify shared genetic variants for these two associations.ResultsNo significant causal relationship was found between immune diseases and migraine and its subtypes. These results were robust with a series of sensitivity analyses. Using the linkage disequilibrium score regression method (LDSC), we detected no genetic correlation between migraine and immune diseases.ConclusionThe evidence from our study does not support a causal relationship between immune diseases and migraine. The mechanisms underlying the frequent comorbidity of migraine and several immune diseases need to be further elucidated.

Abstract Metastatic castration resistant prostate cancer (mCRPC) is still the lethal stage for the whole spectrum of prostate cancer disease. Even though different treatment options have been introduced in the last decade with a significant survival improvement for this population, a lack of more reliable prognostic and predictive markers is still one of the main clinical challenges in management of mCRPC. The aim of this study was to investigate the correlation between Natural Killer cell activity (NKA) and both treatment effect and outcomes in patients with mCRPC treated with enzalutamide. A total of 87 patients with mCRPC treated with enzalutamide as the first line treatment were enrolled. NKA was estimated at baseline and prior to each treatment cycle. Endpoints included both treatment effect with biochemical response (BR), biochemical progression (BP) and radiological progression (RP), as well as outcome data with overall survival (OS), radiologic progression free survival (rPFS), and time to next treatment (TTT). At the time of BR, interferon-gamma (IFNγ) decreased significantly compared to levels detected at baseline (z-score = 2.33, p = 0.019). Regarding outcome data, the whole cohort was divided into four groups according to the change of IFNγ level during the first 3 cycles of enzalutamide treatment. In group 1 (n = 42) the IFNγ level remained within a normal range (≥ 250 pg/mL),while in group 2 (n = 7) it increased from an abnormal (

Objective. The importance of early microbial dysbiosis in later development of obesity and metabolic disorders has been a subject of debate. Here we tested cause and effect in mice. Methods. Germ-free male Swiss Webster mice were colonized in a specific-pathogen-free (SPF) facility at 1 week (1W) and 3 weeks (3W) of age. They were challenged with a high-fat diet and their responses were compared with SPF mice. Gut microbiota was analyzed by 16S rRNA gene sequencing. Moreover, RNA sequencing of the liver was performed on additional 3W and SPF mice on a regular chow diet. Results. There were no significant differences in weight, food consumption, epididymal fat weight, HbA1c levels, and serum insulin and leptin, whereas the early germ-free period resulted in mice with impaired glucose tolerance. Both the 1W and 3W group peaked 56% (p

Abstract Objectives Allele counts of sequence variants obtained by whole genome sequencing (WGS) often play a central role in interpreting the results of genetic and genomic research. However, such variant counts are not readily available for individuals in the Danish population. Here, we present a dataset with allele counts for sequence variants (single nucleotide variants (SNVs) and indels) identified from WGS of 8,671 (5,418 females) individuals from the Danish population. The data resource is based on WGS data from three independent research projects aimed at assessing genetic risk factors for cardiovascular, psychiatric, and headache disorders. To enable the sharing of information on sequence variation in Danish individuals, we created summarized statistics on allele counts from anonymized data and made them available through the European Genome-phenome Archive (EGA, https://identifiers.org/ega.dataset:EGAD00001009756 ) and in a dedicated browser, DanMAC5 (available at www.danmac5.dk ). The summary level data and the DanMAC5 browser provide insight into the allelic spectrum of sequence variants segregating in the Danish population, which is important in variant interpretation. Data description Three WGS datasets with an average coverage of 30x were processed independently using the same quality control pipeline. Subsequently, we summarized, filtered, and merged allele counts to create a high-quality summary level dataset of sequence variants.

Abstract Pnictogens and chalcogens are both viable anions for promoting Fe-based superconductivity, and intense research activity in the related families has established a systematic correlation between the Fe-anion height and the superconducting critical temperature T c, with an optimum Fe-anion height of ~1.38 Å. Here, we report the discovery of superconductivity in the compound LaFeSiO1−δ that incorporates a crystallogen element, Si, and challenges the above picture: considering the strongly squeezed Fe–Si height of 0.94 Å, the superconducting transition at T c = 10 K is unusually high. In the normal state, the resistivity displays non-Fermi-liquid behavior while NMR experiments evidence weak antiferromagnetic fluctuations. According to first-principles calculations, the Fermi surface of this material is dominated by hole pockets without nesting properties, which explains the strongly suppressed tendency toward magnetic order and suggests that the emergence of superconductivity materializes in a distinct set-up, as compared to the standard s ±- and d-wave electron-pocket-based situations. These properties and its simple-to-implement synthesis make LaFeSiO1−δ a particularly promising platform to study the interplay between structure, electron correlations, and superconductivity.

Objectives To examine the level of loneliness experienced during the COVID-19 pandemic in Denmark and to identify associated behavioural patterns and demographic factors.Design Cross-sectional cohort study.Setting Includes Danish active and former blood donors.Participants A questionnaire was sent to 124 307 active and former blood donors, of these a total of 50 968 participants completed the study questionnaire (response rate=41%).Primary and secondary outcome measures Subjective experience of loneliness was measured using the 3-item University of California, Los Angeles Loneliness Scale (UCLA-3). Besides the UCLA-3, the respondents answered items on sociodemographic and economic characteristics, items on precautionary measures taken to avoid COVID-19 infection as well as on COVID-19 anxiety.Results The participants indicated their experienced level of loneliness both before and during the pandemic. Comparing the two reports yielded a mean increase in loneliness scores of 14.1% (p

Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.

As our societies and natural systems are becoming ever more interconnected, it is critical that sustainable management can adapt to new knowledge from both the ecological and the social domains, and act on it in a timely and effective manner. This need is amplifying in the Anthropocene as we are approaching the limit for humanity's safe operating space, leading to irreversible change to ecosystem function. This urgently requires increased attention and concern regarding the information feedbacks between the silos of science, policy and society. A web of policies is in place to protect the health of people and the planet, but to ensure that they are effective we need frameworks to make sense of real-world complexities and interlinkages between multiple factors. The Drivers-Pressures-State-Impacts-Response (DPSIR) framework was created for this purpose, however, its' implicit focus on 1) analytical and 2) procedural aspects must be made explicit, to enable coordination across silos and studies. Continued creation of new DPSIR derivatives may limit its impact, while more explicit coordination between these two aspects can improve the effectiveness of DPSIR while retaining its flexibility. We thus propose five elements to support sustainable policy development and implementation using DPSIR: 1) iteration; 2) risk, uncertainty and analytical bias; 3) flexible integration; 4) use of quantitative methods, and; 5) clear and standard definitions for DPSIR. We illustrate these elements in four cases: Three highlight missing feedbacks when DPSIR elements are not made explicit and a fourth case – on per-and-polyfluorinated alkyl substances (PFAS) – showing a potential roadmap to successful policy implementation using DPSIR.

Although the concepts of nonuniform sampling (NUS​​​​​​​) and non-Fourier spectral reconstruction in multidimensional NMR began to emerge 4 decades ago (Bodenhausen and Ernst, 1981; Barna and Laue, 1987), it is only relatively recently that NUS has become more commonplace. Advantages of NUS include the ability to tailor experiments to reduce data collection time and to improve spectral quality, whether through detection of closely spaced peaks (i.e., “resolution”) or peaks of weak intensity (i.e., “sensitivity”). Wider adoption of these methods is the result of improvements in computational performance, a growing abundance and flexibility of software, support from NMR spectrometer vendors, and the increased data sampling demands imposed by higher magnetic fields. However, the identification of best practices still remains a significant and unmet challenge. Unlike the discrete Fourier transform, non-Fourier methods used to reconstruct spectra from NUS data are nonlinear, depend on the complexity and nature of the signals, and lack quantitative or formal theory describing their performance. Seemingly subtle algorithmic differences may lead to significant variabilities in spectral qualities and artifacts. A community-based critical assessment of NUS challenge problems has been initiated, called the “Nonuniform Sampling Contest” (NUScon), with the objective of determining best practices for processing and analyzing NUS experiments. We address this objective by constructing challenges from NMR experiments that we inject with synthetic signals, and we process these challenges using workflows submitted by the community. In the initial rounds of NUScon our aim is to establish objective criteria for evaluating the quality of spectral reconstructions. We present here a software package for performing the quantitative analyses, and we present the results from the first two rounds of NUScon. We discuss the challenges that remain and present a roadmap for continued community-driven development with the ultimate aim of providing best practices in this rapidly evolving field. The NUScon software package and all data from evaluating the challenge problems are hosted on the NMRbox platform.

Abstract Migraine attacks are delimited, allowing investigation of changes during and outside attack. Gene expression fluctuates according to environmental and endogenous events and therefore, we hypothesized that changes in RNA expression during and outside a spontaneous migraine attack exist which are specific to migraine. Twenty-seven migraine patients were assessed during a spontaneous migraine attack, including headache characteristics and treatment effect. Blood samples were taken during attack, two hours after treatment, on a headache-free day and after a cold pressor test. RNA-Sequencing, genotyping, and steroid profiling were performed. RNA-Sequences were analyzed at gene level (differential expression analysis) and at network level, and genomic and transcriptomic data were integrated. We found 29 differentially expressed genes between ‘attack’ and ‘after treatment’, after subtracting non-migraine specific genes, that were functioning in fatty acid oxidation, signaling pathways and immune-related pathways. Network analysis revealed mechanisms affected by changes in gene interactions, e.g. ‘ion transmembrane transport’. Integration of genomic and transcriptomic data revealed pathways related to sumatriptan treatment, i.e. ‘5HT1 type receptor mediated signaling pathway’. In conclusion, we uniquely investigated intra-individual changes in gene expression during a migraine attack. We revealed both genes and pathways potentially involved in the pathophysiology of migraine and/or migraine treatment.

Endothelial dysfunction result from inflammation and excessive production of reactive oxygen species as part of the surgical stress response. Remote ischemic preconditioning (RIPC) potentially exerts anti-oxidative and anti-inflammatory properties, which might stabilise the endothelial function after non-cardiac surgery. This was a single centre randomised clinical trial including 60 patients undergoing sub-acute laparoscopic cholecystectomy due to acute cholecystitis. Patients were randomised to RIPC or control. The RIPC procedure consisted of four cycles of five minutes of ischaemia and reperfusion of one upper extremity. Endothelial function was assessed as the reactive hyperaemia index (RHI) and circulating biomarkers of nitric oxide (NO) bioavailability (L-arginine, asymmetric dimethylarginine (ADMA), L-arginine/ADMA ratio, tetra- and dihydrobiopterin (BH4 and BH2), and total plasma biopterin) preoperative, 2–4 h after surgery and 24 h after surgery. RHI did not differ between the groups (p = 0.07). Neither did levels of circulating biomarkers of NO bioavailability change in response to RIPC. L-arginine and L-arginine/ADMA ratio was suppressed preoperatively and increased 24 h after surgery (p < 0.001). The BH4/BH2-ratio had a high preoperative level, decreased 2–4 h after surgery and remained low 24 h after surgery (p = 0.01). RIPC did not influence endothelial function or markers of NO bioavailability until 24 h after sub-acute laparoscopic cholecystectomy. In response to surgery, markers of NO bioavailability increased, and oxidative stress decreased. These findings support that a minimally invasive removal of the inflamed gallbladder countereffects reduced markers of NO bioavailability and increased oxidative stress caused by acute cholecystitis.

Abstract Background Antibiotic (AB) consumption in production animals has a high awareness among politicians and consumers due to the risk of selection for AB resistance among potentially zoonotic bacteria. However, AB treatment of animals is at times necessary to treat diseases and ensure the wellbeing of the animals we take into our care. Raised without antibiotics (RWA) is a concept where pigs are individually ear-tagged for tracking, and if pigs are AB treated, they lose their RWA status. At slaughter, the farmer receives an additional price for non-AB treated pigs. The objective of this study was to identify risk factors for AB treatment and to investigate growth performance of pigs in two Danish RWA herds. Results A total of 518 pigs in herd A and 436 pigs in herd B, were individually ear-tagged and subjected to weekly investigations of AB treatment status from birth to 12 weeks of age. Bodyweight was recorded at birth, 2, 4 and 12 weeks of age. The results showed, that at 12 weeks of age, 82 of 518 liveborn pigs were AB treated in herd A and 31 of 436 liveborn pigs were AB treated in herd B. Individual pigs that required AB treatment had a reduced average daily gain from day 0 to 28 in both herds (herd A, P

Bell et al. report 46 new loci associated with biomarkers of iron homeostasis, including ferritin levels, iron binding capacity, and iron saturation, in the Icelandic, Danish and UK populations. The associated loci point to new iron-regulating proteins and important genetic differences between men and women.

The role of ciliary/centriolar components in the postnatal brain is unclear. Here, the authors show via ablation of Pcm1 in mice that degenerative ciliary/centriolar phenotypes induce neuroanatomical and behavioral changes. Sequencing of PCM1 in human cohorts and zebrafish in vivo complementation suggests PCM1 mutations can contribute to schizophrenia.

Abstract Background Chondroclasts and osteoclasts have been previously identified as the cells capable of resorbing mineralized cartilage and bone matrices, respectively. While both cell types appear morphologically similar, contain comparable ultrastructural features, and express tartrate-resistant acid phosphatase (TRAP), however, no information is available about the genomic similarities and differences between osteoclasts and chondroclasts. Methods To address this question, we laser captured homogeneous populations of TRAP-positive cells that interact with bone (osteoclasts) and TRAP-positive cells that interact with mineralized cartilage (chondroclasts) on the same plane from murine femoral fracture callus sections. We then performed a global transcriptome profiling of chondroclasts and osteoclasts by utilizing a mouse genome Agilent GE 4X44K V2 microarray platform. Multiple computational approaches and interaction networks were used to analyze the transcriptomic landscape of osteoclasts and chondroclasts. Results Our systematic and comprehensive analyses using hierarchical clustering and principal component analysis (PCA) demonstrate that chondroclasts and osteoclasts are transcriptionally distinct cell populations and exhibit discrete transcriptomic signatures as revealed by multivariate analysis involving scatter plot, volcano plot, and heatmap analysis. TaqMan qPCR was used to validate the microarray results. Intriguingly, the functional enrichment and integrated network analyses revealed distinct Gene Ontology terms and molecular pathways specific to chondroclasts and osteoclasts and further suggest that subsets of metabolic genes were specific to chondroclasts. Protein-protein interaction (PPI) network analysis showed an abundance of structured networks of metabolic pathways, ATP synthesis, and proteasome pathways in chondroclasts. The regulatory network analysis using transcription factor-target gene network predicted a pool of genes including ETV6, SIRT1, and ATF1 as chondroclast-specific gene signature. Conclusions Our study provides an important genetic resource for further exploration of chondroclast function in vivo. To our knowledge, this is the first demonstration of genetic landscape of osteoclasts from chondroclasts identifying unique molecular signatures, functional clustering, and interaction network.

Machine vision has demonstrated its usefulness in the livestock industry in terms of improving welfare in such areas as lameness detection and body condition scoring in dairy cattle. In this article, we present some promising results of applying state of the art object detection and classification techniques to insects, specifically Black Soldier Fly (BSF) and the domestic cricket, with the view of enabling automated processing for insect farming. We also present the low-cost “Insecto” Internet of Things (IoT) device, which provides environmental condition monitoring for temperature, humidity, CO2, air pressure, and volatile organic compound levels together with high resolution image capture. We show that we are able to accurately count and measure size of BSF larvae and also classify the sex of domestic crickets by detecting the presence of the ovipositor. These early results point to future work for enabling automation in the selection of desirable phenotypes for subsequent generations and for providing early alerts should environmental conditions deviate from desired values.

Endometrioid endometrial carcinomas (EECs) are the most common histological subtype of uterine cancer. Late-stage disease is an adverse prognosticator for EEC. The purpose of this study was to analyze EEC exome mutation data to identify late-stage-specific statistically significantly mutated genes (SMGs), which represent candidate driver genes potentially associated with disease progression. We exome sequenced 15 late-stage (stage III or IV) non-ultramutated EECs and paired non-tumor DNAs; somatic variants were called using Strelka, Shimmer, SomaticSniper and MuTect. Additionally, somatic mutation calls were extracted from The Cancer Genome Atlas (TCGA) data for 66 late-stage and 270 early-stage (stage I or II) non-ultramutated EECs. MutSigCV (v1.4) was used to annotate SMGs in the two late-stage cohorts and to derive p-values for all mutated genes in the early-stage cohort. To test whether late-stage SMGs are statistically significantly mutated in early-stage tumors, q-values for late-stage SMGs were re-calculated from the MutSigCV (v1.4) early-stage p-values, adjusting for the number of late-stage SMGs tested. We identified 14 SMGs in the combined late-stage EEC cohorts. When the 14 late-stage SMGs were examined in the TCGA early-stage data, only Krüppel-like factor 3 (KLF3) and Paired box 6 (PAX6) failed to reach significance as early-stage SMGs, despite the inclusion of enough early-stage cases to ensure adequate statistical power. Within TCGA, nonsynonymous mutations in KLF3 and PAX6 were, respectively, exclusive or nearly exclusive to the microsatellite instability (MSI)-hypermutated molecular subgroup and were dominated by insertions-deletions at homopolymer tracts. In conclusion, our findings are hypothesis-generating and suggest that KLF3 and PAX6, which encode transcription factors, are MSI target genes and late-stage-specific SMGs in EEC.

Abstract Background Patients suffering from high risk stage II colon cancer (CC) may benefit from adjuvant onco-therapy, but additional prognostic markers are needed for better treatment stratification. We investigated the prognostic value of Programmed Death Ligand-1 (PD-L1) in a true population-based cohort of patients with stage II CC. Methods PD-L1 expression on tumour cells was evaluated by immunohistochemistry in 572 colon cancers. Whole sections from tumour blocks representing the deepest invasive front of the primary tumour were used for analysis. A cut-off of 5% positivity was used for dichotomizing the data. The prognostic value was investigated in Cox proportional hazard models for recurrence-free survival (RFS) and overall survival (OS). Results Overall, 6% of the tumours were classified as high PD-L1. High PD-L1 was related to female gender (p = 0.028), high malignancy grade (

The risk factors and disease implications of hyper­hidrosis are unknown. The objectives of this retrospective cohort study were to estimate the prevalence of hyperhidrosis and to compare demographic, life­style, and socioeconomic parameters in blood donors with and without self-reported or hospital-diagnosed hyperhidrosis. The study included blood donors from the Danish Blood Donor Study for the period 2010–2019. Registry data were collected from Statistics Denmark. Overall, 2,794 of 30,808 blood donors (9.07%; 95% confidence interval (95% CI) 8.75–9.40) had self- reported hyperhidrosis and 284 of 122,225 (0.23%; 95% CI 0.21–0.26) had hospital-diagnosed hyperhidrosis. Self-reported hyperhidrosis was associated with smoking (odds ratio (OR) 1.17; 95% CI 1.05–1.31), overweight (OR 1.72; 95% CI 1.58–1.87), “unemployed” (OR 1.60; 95% CI 1.24–2.08), “short education” (OR 0.76; 95% CI 0.64–0.90), and lower income (beta-coefficient –26,121; 95% CI –37,931, –14,311). Hospital-diagnosed hyperhidrosis did not differ from controls. Thus, self-reported hyperhidrosis was associated with potential hyperhidrosis risk factors (smoking, overweight) and disease implications (unemployment, low education level and income).

Epidemiological studies have long reported that perturbations of the childhood microbiome increase the risk of developing allergies, but a causal relationship with atopic dermatitis remains unclear. Here we colonized germ-free mice at birth or at one or eight week-of-age to investigate the role of prenatal and early postnatal microbial exposure on development of oxozolone-induced dermatitis later in life. We demonstrate that only one week delayed microbial colonization increased IgE levels and the total histological score of the inflamed ear compared to mice colonized throughout life. In parallel, several pro-inflammatory cytokines and chemokines were upregulated in the ear tissue demonstrating an enhanced immunological response following delayed postnatal colonization of the gut. In contrast, sensitivity to oxazolone-induced dermatitis was unaffected by the presence of a maternal microbiota during gestation. Mice colonized at eight week-of-age failed to colonize Rikenellaceae, a group of bacteria previously associated with a high-responding phenotype, and did not develop an immunological response to the same extent as the early colonized mice despite pronounced histopathological manifestations. The study provides proof-of-principle that the first intestinal colonizers of mice pups are crucial for the development of oxazolone-induced dermatitis later in life, and that the status of the maternal microbiota during pregnancy has no influence on the offspring’s allergic immune response. This highlights an important window of opportunity following birth for microbiota-mediated interventions to prevent atopic responses later in life. How long such a window is open may vary between mice and humans considering species differences in the ontogeny of the immune system.

Weaning comprises a challenging period for pigs, but dietary tools can be implemented to avoid excess antibiotics usage. Therefore, we tested the effect of a 17.6% crude protein (CP) diet on growth and diarrhoea and investigated the effect of a 15.5% CP diet post-weaning on transcriptomic responses, growth, and diarrhoea-related antibiotic treatments. At weaning, pigs were divided into five dietary treatment groups in a three-phase diet from weaning to 30 kg bodyweight. The diets included a positive control group (PC) with medicinal zinc oxide, a negative control group (NC), a 17.6% CP diet based on soy protein concentrate (SP), a 17.6% CP diet based on soybean meal (SB), and a 15.5% CP diet with additional amino acids (XLA). Growth performance and the occurrence of diarrhoea were similar between the SP and SB groups. The XLA pigs had a reduced weight gain and fewer antibiotics treatments caused by diarrhoea, as well as a reduced level of blood proteins. Intestinal tissue samples from the XLA pigs displayed decreased expression of genes involved in nutrient metabolism and immune responses relative to the PC group. In conclusion, a very low CP diet reduces antibiotics treatments, but also adapts gut nutrient metabolism and reduces growth performance.

Enhancing treatment uptake for hepatitis C to achieve the elimination goals set by the World Health Organization could be achieved by reducing the treatment duration. The aim of this study was to compare the sustained virological response at week 12 (SVR12) after four weeks of glecaprevir/pibrentasvir (GLE/PIB) + ribavirin compared to eight weeks of GLE/PIB and to estimate predictors for SVR12 with four weeks of treatment through a multicenter open label randomized controlled trial. Patients were randomized 2:1 (4 weeks:8 weeks) and stratified by genotype 3 and were treatment naïve of all genotypes and without significant liver fibrosis. A total of 27 patients were analyzed for predictors for SVR12, including 15 from the first pilot phase of the study. In the ‘modified intention to treat’ group, 100% (7/7) achieved cure after eight weeks and for patients treated for four weeks the SVR12 was 58.3% (7/12). However, patients with a baseline viral load

Circulating inflammatory markers are essential to human health and disease, and they are often dysregulated or malfunctioning in cancers as well as in cardiovascular, metabolic, immunologic and neuropsychiatric disorders. However, the genetic contribution to the physiological variation of levels of circulating inflammatory markers is largely unknown. Here we report the results of a genome-wide genetic study of blood concentration of ten cytokines, including the hitherto unexplored calcium-binding protein (S100B). The study leverages a unique sample of neonatal blood spots from 9,459 Danish subjects from the iPSYCH initiative. We estimate the SNP-heritability of marker levels as ranging from essentially zero for Erythropoietin (EPO) up to 73% for S100B. We identify and replicate 16 associated genomic regions (p < 5 x 10-9), of which four are novel. We show that the associated variants map to enhancer elements, suggesting a possible transcriptional effect of genomic variants on the cytokine levels. The identification of the genetic architecture underlying the basic levels of cytokines is likely to prompt studies investigating the relationship between cytokines and complex disease. Our results also suggest that the genetic architecture of cytokines is stable from neonatal to adult life.

Background: The early identification of treatment effect is wanted in several settings, including the management of metastatic colorectal cancer (mCRC). A potential universal marker is circulating tumor DNA (ctDNA). Our prospective study explored the association between progression-free survival (PFS) and overall survival (OS), and early change of ctDNA after one cycle of chemotherapy in patients with mCRC. Methods: The study included mCRC patients receiving standard first line combination chemotherapy with 5-Fluorouracil (FU), oxaliplatin, and bevacizumab. Hypermethylated neuropeptide Y (NPY) ctDNA (meth-ctDNA) served as a marker analyzed by droplet digital polymerase chain reaction (PCR). The meth-ctDNA level was analyzed in plasma before treatment start and again before cycle two. The patients were divided into two groups according to the dynamics of meth-ctDNA. Low ctDNA (LctDNA) included patients with zero or values of meth-ctDNA decreasing to a level including zero in the 95% confidence interval. High ctDNA (HctDNA) included all other patients (stable, increasing, or slightly decreasing values). The two groups were compared as to PFS and OS. Results: The study included 123 patients. The PFS in the two groups differed significantly with a median of 9.2 and 6.7 months in LctDNA and HctDNA, respectively ( p = 0.0005). This translated into a 12-month difference in OS with a median of 25.4 and 13.5 months, respectively ( p = 0.0001). Conclusions: Early therapeutic reconsideration is of utmost importance. A low level of meth-ctDNA after one cycle of chemotherapy in the first line setting is a potential marker for excellent clinical outcomes. The clinical utility should be confirmed in randomized clinical trials.

Hypertension occurs at a higher rate in African Americans than in European Americans. Based on the assumption that causal variants are more frequently found on DNA segments inherited from the ancestral population with higher disease risk, we employed admixture mapping to identify genetic loci with excess local African ancestry associated with blood pressure. Chromosomal regions 1q21.2-21.3, 4p15.1, 19q12 and 20p13 were significantly associated with diastolic blood pressure (β = 5.28, -7.94, -6.82 and 5.89, P-value = 6.39E-04, 2.07E-04, 6.56E-05 and 5.04E-04, respectively); 1q21.2-21.3 and 19q12 were also significantly associated with mean arterial pressure (β = 5.86 and -6.40, P-value = 5.32E-04 and 6.37E-04, respectively). We further selected SNPs that had large allele frequency differences within these regions and tested their association with blood pressure. SNP rs4815428 was significantly associated with diastolic blood pressure after Bonferroni correction (β = -2.42, P-value = 9.57E-04), and it partially explained the admixture mapping signal at 20p13. SNPs rs771205 (β = -1.99, P-value = 3.37E-03), rs3126067, rs2184953 and rs58001094 (the latter three exhibit strong linkage disequilibrium, β = -2.3, P-value = 1.4E-03) were identified to be significantly associated with mean arterial pressure, and together they fully explained the admixture signal at 1q21.2-21.3. Although no SNP at 4p15.1 showed large ancestral allele frequency differences in our dataset, we detected association at low-frequency African-specific variants that mapped predominantly to the gene PCDH7, which is most highly expressed in aorta. Our results suggest that these regions may harbor genetic variants that contribute to the different prevalence of hypertension.

Understanding how genomic variation causes differences in observable phenotypes remains a major challenge in biology. It is difficult to trace the sequence of events originating from genomic variants to changes in transcriptional responses or protein modifications. Ideally, one would conduct experiments with individuals that are at either extreme of the trait of interest, but such resources are often not available. Further, advances in genome editing will enable testing of candidate polymorphisms individually and in combination. Here we have created a resource for the study of sleep with 39 inbred lines of Drosophila—the Sleep Inbred Panel (SIP). SIP lines have stable long- and short-sleeping phenotypes developed from naturally occurring polymorphisms. These lines are fully sequenced, enabling more accurate targeting for genome editing and transgenic constructs. This panel facilitates the study of intermediate transcriptional and proteomic correlates of sleep, and supports genome editing studies to verify polymorphisms associated with sleep duration.

BACKGROUND: Additional prognostic markers are needed for better treatment stratification of stage II colon cancer (CC). We investigated the prognostic value of tumor-infiltrating lymphocytes (TILs) in a true population-based cohort of patients with stage II CC. MATERIAL AND METHODS: A total of 573 patients were included. Tumor blocks representing the deepest invasive part of the primary tumor were used for analysis. CD3+ and CD8+ TILs at the invasive front were evaluated by immunohistochemistry on whole tumor sections. The invasive area was manually outlined, and Visiopharm Integrator System software was used for quantification. Data were dichotomized for comparison with clinical data. The prognostic value was investigated in Cox proportional-hazard models for recurrence-free survival (RFS) and overall survival (OS). RESULTS: Low CD3+ or CD8+ TILs were significantly associated with poor RFS and OS (P = .0021 and P ≤ .0009, respectively, log-rank test). In multiple Cox regression analysis, low CD3+ and CD8+ TILs were associated with reduced RFS with hazard ratio (HR) = 1.386 (95% CI 1.039-1.850), P = .026, and HR = 1.394 (95% CI 1.029-1.890), P = .032, respectively, independent of age, T-stage, localization, perforation, and microsatellite instability (MSI). In the subgroups of patients with low CD3+ or CD8+ TILs, there was no difference in survival between patients with MSI and microsatellite-stable tumors, (P = .821 and P = .907, respectively). CONCLUSION: Low CD3+ and CD8+ TILs in the invasive area are both related to inferior prognosis of stage II CC, and we recommend either of these parameters to be considered as additional high-risk factor.

Abstract Background Tumour budding (TB) and Tumour Stroma Ratio (TSR) may be rewarding in the treatment stratification of patients with stage II colon cancer. However, lack of standardization may exclude these parameters from being used in a clinical setting. The purpose of this methodologic study was to compare stereology with semi-quantitative estimations of TSR, to investigate the intra-tumoural heterogeneity of TB and TSR, and to assess the intra- and inter-observer agreement. Methods Three paraffin embedded tumour blocks, one of them representing the deepest invasive front, were selected from each of 43 patients treated for stage II colon cancer. TSR was estimated in H&E sections semi-quantitatively using conventional microscopy, and stereologically on scanned slides, using the newCAST stereology platform. TB was scored across 10 high power fields at the invasive front in cytokeratin AE1/AE3 stained sections. Results Subjective, semi-quantitative estimates of TSR significantly correlated to the stereological estimates, with the best correlation found for sections with the deepest invasive tumour penetration (σ = 0.621, p

Abstract Background Precision medicine calls for an early indicator of treatment efficiency. Circulating tumor DNA (ctDNA) is a promising marker in this setting. Our prospective study explored the association between disease development and change of ctDNA during first line chemotherapy in patients with RAS/RAF mutated metastatic colorectal cancer (mCRC). Methods The study included 138 patients with mCRC receiving standard first line treatment. In patients with RAS/RAF mutated tumor DNA the same mutation was quantified in the plasma using droplet digital PCR. The fractional abundance of ctDNA was assessed in plasma before treatment start and at every treatment cycle until radiologically defined progressive disease. Results RAS/RAF mutations were detected in the plasma from 77 patients. Twenty patients progressed on treatment and 57 stopped treatment without progression. The presence of mutated DNA in plasma was correlated with poor overall survival. A low level of ctDNA after the first cycle of chemotherapy was associated with a low risk of progression. On the other hand, a significant increase of ctDNA at any time during the treatment course was associated with a high risk of progression on continuous treatment. The first increase in ctDNA level occurred at a median of 51 days before radiologically confirmed progression. Conclusions The results indicate that the ctDNA level holds potential as a clinically valuable marker in first line treatment of mCRC. A rapid decrease was associated with a prolonged progression free interval, whereas a significant increase gave notice of early progression with a relevant lead time.

Animal welfare is not only an ethically important consideration in good animal husbandry but can also have a significant effect on an animal’s productivity. The aim of this paper was to show that a reduction in animal welfare, in the form of increased stress, can be identified in pigs from frontal images of the animals. We trained a convolutional neural network (CNN) using a leave-one-out design and showed that it is able to discriminate between stressed and unstressed pigs with an accuracy of >90% in unseen animals. Grad-CAM was used to identify the animal regions used, and these supported those used in manual assessments such as the Pig Grimace Scale. This innovative work paves the way for further work examining both positive and negative welfare states with the aim of developing an automated system that can be used in precision livestock farming to improve animal welfare.

Genome graphs are emerging as an important novel approach to the analysis of high-throughput human sequencing data. By explicitly representing genetic variants and alternative haplotypes in a mappable data structure, they can enable the improved analysis of structurally variable and hyperpolymorphic regions of the genome. In most existing approaches, graphs are constructed from variant call sets derived from short-read sequencing. As long-read sequencing becomes more cost-effective and enables de novo assembly for increasing numbers of whole genomes, a method for the direct construction of a genome graph from sets of assembled human genomes would be desirable. Such assembly-based genome graphs would encompass the wide spectrum of genetic variation accessible to long-read-based de novo assembly, including large structural variants and divergent haplotypes. Here we present NovoGraph, a method for the construction of a human genome graph directly from a set of de novo assemblies. NovoGraph constructs a genome-wide multiple sequence alignment of all input contigs and creates a graph by merging the input sequences at positions that are both homologous and sequence-identical. NovoGraph outputs resulting graphs in VCF format that can be loaded into third-party genome graph toolkits. To demonstrate NovoGraph, we construct a genome graph with 23,478,835 variant sites and 30,582,795 variant alleles from de novo assemblies of seven ethnically diverse human genomes (AK1, CHM1, CHM13, HG003, HG004, HX1, NA19240). Initial evaluations show that mapping against the constructed graph reduces the average mismatch rate of reads from sample NA12878 by approximately 0.2%, albeit at a slightly increased rate of reads that remain unmapped.

Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.

Important oligonucleotides in anti-sense research have been investigated in silico and experimentally. This involves quantum mechanical (QM) calculations and chromatography experiments on locked nucleic acid (LNA) phosphorothioate (PS) oligonucleotides. iso-potential electrostatic surfaces are essential in this study and have been calculated from the wave functions derived from the QM calculations that provide binding information and other properties of these molecules. The QM calculations give details of the electronic structures in terms of e.g., energy and bonding, which make them distinguish or differentiate between the individual PS diastereoisomers determined by the position of sulfur atoms. Rules are derived from the electronic calculations of these molecules and include the effects of the phosphorothioate chirality and formation of electrostatic potential surfaces. Physical and electrochemical descriptors of the PS oligonucleotides are compared to the experiments in which chiral states on these molecules can be distinguished. The calculations demonstrate that electronic structure, electrostatic potential, and topology are highly sensitive to single PS configuration changes and can give a lead to understanding the activity of the molecules. Keywords: LNA phosphorothioate, DNA/LNA oligonucleotide, diastereoisomers, Hartree-Fock calculations, iso-potential surface, anion chromatograms

Abstract Background Precise prognostic and predictive variables allowing improved post-operative treatment stratification are missing in patients treated for stage II colon cancer (CC). Investigation of tumor infiltrating lymphocytes (TILs) may be rewarding, but the lack of a standardized analytic technique is a major concern. Manual stereological counting is considered the gold standard, but digital pathology with image analysis is preferred due to time efficiency. The purpose of this study was to compare manual stereological estimates of TILs with automatic counts obtained by image analysis, and at the same time investigate the heterogeneity of TILs. Methods From 43 patients treated for stage II CC in 2002 three paraffin embedded, tumor containing tissue blocks were selected one of them representing the deepest invasive tumor front. Serial sections from each of the 129 blocks were immunohistochemically stained for CD3 and CD8, and the slides were scanned. Stereological estimates of the numerical density and area fraction of TILs were obtained using the computer-assisted newCAST stereology system. For the image analysis approach an app-based algorithm was developed using Visiopharm Integrator System software. For both methods the tumor areas of interest (invasive front and central area) were manually delineated by the observer. Results Based on all sections, the Spearman’s correlation coefficients for density estimates varied from 0.9457 to 0.9638 (p