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BackgroundA reduction in mortality risk of COVID-19 throughout the first wave of the pandemic has been reported, but less is known about later waves. This study aimed to describe changes in hospitalizations and mortality of patients receiving inpatient geriatric care for COVID-19 or other causes during the pandemic.MethodsPatients 70 years and older hospitalized in geriatric hospitals in Stockholm for COVID-19 or other causes between March 2020-July 2021 were included. Data on the incidence of COVID-positive cases and 30-day mortality of the total ≥ 70-year-old population, in relation to weekly hospitalizations and mortality after hospital admissions were analyzed. Findings The total number of hospitalizations was 5,320 for COVID-19 and 32,243 for non-COVID-cases. In COVID-patients, the 30-day mortality rate was highest at the beginning of the first wave (29% in March-April 2020), reached 17% at the second wave peak (November-December) followed by 11-13% in the third wave (March-July 2021). The mortality in non-COVID geriatric patients showed a similar trend, but of lower magnitude (5-10%). During the incidence peaks, COVID-19 hospitalizations displaced non-COVID geriatric patients.InterpretationHospital admissions and 30-day mortality after hospitalizations for COVID-19 increased in periods of high community transmission, albeit with decreasing mortality rates from wave 1 to 3, with a probable vaccination effect in wave 3. Thus, the healthcare system could not compensate for the high community spread of COVID-19 during the pandemic peaks, which also led to displacing care for non-COVID geriatric patients.

BackgroundIn Stockholm (Sweden) a substantial number of persons who were infected with SARS-CoV-2 during spring 2020, and received intensive care followed by rehabilitation due to COVID-19, were of working age. For this group, return to work (RTW) is an important part of the rehabilitation, however this is an area that thus far has received little scholarly attention. The Aim of this study was two-fold. First, to descriptively look at self-reported work ability over time using the Work Abilty Index among working age adults who recovered from severe COVID-19, and secondly, to explore experiences and expectations concerning RTW among working age adults who recovered from severe COVID-19.MethodsFocus group interviews and qualitative thematic analyses were utilized. In addition, the study populations' self-reported work ability index was recorded over one year.FindingsQualitative analysis of data resulted in 5 themes: a) Initial experiences after discharge from in-patient rehabilitation, b) Disparate first contact with work, c) Uncertainties about own role in RTW process, d) Working situation for those who had started getting back to work, and e) A need to reprioritize expectations for work in the context of everyday life. There were no statistical differences in work ability index scores between 18 and 52 weeks after discharge from an in-patient rehabilitation unit.ConclusionRTW after COVID-19 can require systematic support for several months as well as be initiated earlier in the rehabilitation process. Further research in the area is needed.

BACKGROUND:To allow early identification of patients at risk of sepsis in the emergency department (ED), a variety of risk stratification scores and/or triage systems are used. The first aim of this study was to develop a risk stratification score for sepsis based upon vital signs and biomarkers using a statistical approach. Second, we aimed to validate the Rapid Emergency Triage and Treatment System (RETTS) for sepsis. RETTS combines vital signs with symptoms for risk stratification. METHODS:We retrospectively analysed data from two prospective, observational, multicentre cohorts of patients from studies of biomarkers in ED. A candidate risk stratification score called Sepsis Heparin-binding protein-based Early Warning Score (SHEWS) was constructed using the Least Absolute Shrinkage and Selector Operator (LASSO) method. SHEWS and RETTS were compared to National Early Warning Score 2 (NEWS2) for infection-related organ dysfunction, intensive care or death within the first 72h after admission (i.e. sepsis). RESULTS:506 patients with a diagnosed infection constituted cohort A, in which SHEWS was derived and RETTS was validated. 435 patients constituted cohort B of whom 184 had a diagnosed infection where both scores were validated. In both cohorts (A and B), AUC for infection-related organ dysfunction, intensive care or death was higher for NEWS2, 0.80 (95% CI 0.76-0.84) and 0.69 (95% CI 0.63-0.74), than RETTS, 0.74 (95% CI 0.70-0.79) and 0.55 (95% CI 0.49-0.60), p = 0.05 and p

ObjectiveSurvival in epithelial ovarian cancer (EOC) remains poor. Most patients are diagnosed in late stages. Early diagnosis increases the chance of survival. We used the proximity extension assay from Olink Proteomics to search for new protein biomarkers with the potential to improve the diagnostic performance of CA125 and HE4 in patients with ovarian tumors.Material and methodsPlasma samples were obtained from 180 women with ovarian tumors; 30 cases of benign tumor, 28 cases with borderline tumors, 25 early EOC cases (FIGO stage I) and 97 advanced EOC cases (FIGO stages II-IV). Proteins were measured using the Olink® Oncology II and Inflammation panels. For statistical analyses, patients were categorized into benign tumors versus cancer and benign tumors versus borderline + cancer, respectively.ResultsWe analyzed 177 biomarkers. Thirty-four proteins had ROC AUC > 0.7 for discrimination between benign tumors and cancer. Fifteen proteins had ROC AUC > 0.7 for discrimination between benign tumors and borderline tumors + cancer. HE4 ranked highest for both comparisons. A reference model with HE4, CA125 and age (AUC 0.838 for benign tumors vs. cancer and AUC 0.770 for benign tumors vs. borderline tumors + cancer) was compared to the reference model with the addition of each of the remaining proteins with AUC > 0.7. ITGAV was the only individual biomarker found to improve diagnostic performance of the reference model, to AUC 0.874 for benign tumors vs. cancer and AUC 0.818 for benign tumors vs. borderline tumors + cancer (p < 0.05). Cross-validation and LASSO regression was combined to select multiple biomarker combinations. The best performing model for discrimination between benign tumors and borderline tumors + cancer was a 6-biomarker combination (HE4, CA125, ITGAV, CXCL1, CEACAM1, IL-10RB) and age (AUC 0.868, sensitivity 0.86 and specificity 0.82, p = 0.016 for comparison with the reference model).ConclusionHE4 was the best performing individual biomarker for discrimination between benign ovarian tumors and EOC including borderline tumors. The addition of other carcinogenesis-related biomarkers in a multiplex biomarker panel can improve the diagnostic performance of the established biomarkers HE4 and CA125.

We present the first study to examine the year-round distribution, activity patterns, and habitat use of one of New Zealand's most common seabirds, the fluttering shearwater (Puffinus gavia). Seven adults from Burgess Island, in the Hauraki Gulf, and one individual from Long Island, in the Marlborough Sounds, were successfully tracked with combined light-saltwater immersion loggers for one to three years. Our tracking data confirms that fluttering shearwaters employ different overwintering dispersal strategies, where three out of eight individuals, for at least one of the three years when they were being tracked, crossed the Tasman Sea to forage over coastal waters along eastern Tasmania and southeastern Australia. Resident birds stayed confined to waters of northern and central New Zealand year-round. Although birds frequently foraged over pelagic shelf waters, the majority of tracking locations were found over shallow waters close to the coast. All birds foraged predominantly in daylight and frequently visited the colony at night throughout the year. We found no significant inter-seasonal differences in the activity patterns, or between migratory and resident individuals. Although further studies of inter-colony variation in different age groups will be necessary, this study presents novel insights into year-round distribution, activity patterns and habitat use of the fluttering shearwater, which provide valuable baseline information for conservation as well as for further ecological studies.

Rapeseed meal (RSM) is an alternative feed ingredient to soybean meal (SBM) in pig diets. However, knowledge on the effect of RSM on gut health, especially in relation to changes in gut microbiota is still limited. In our study, Norwegian Landrace weaner pigs were fed with either a control diet (CON) based on wheat, barley and SBM, or a high-fiber experimental diet where SBM was replaced by RSM (RSF). We found no large differences in the gut microbiota of pigs fed the two diets, suggesting that RSF does not disturb the gut microbiota and the normal gut function. The relative abundance of SCFA-producing phylotypes and colon-health related phylotypes increased in the large intestine of RSF-fed pigs. Among them, Lachnospira and Coprococcus were negatively associated with the presence of neutrophils in the colon wall. The higher abundance of these bacteria in colon of RSF pigs may suggest an anti-inflammatory stimulus effect of the RSF diet. The gut microbiota of RSF-fed pigs was relatively unaltered following episodes of diarrhea suggesting that the RSF diet may promote robustness in weaner pigs and reduce the risk of dysbiosis.

A Swedish pedigree with an autosomal dominant inheritance of idiopathic scoliosis was initially studied by genetic linkage analysis, prioritising genomic regions for further analysis. This revealed a locus on chromosome 1 with a putative risk haplotype shared by all affected individuals. Two affected individuals were subsequently exome-sequenced, identifying a rare, non-synonymous variant in the CELSR2 gene. This variant is rs141489111, a c.G6859A change in exon 21 (NM_001408), leading to a predicted p.V2287I (NP_001399.1) change. This variant was found in all affected members of the pedigree, but showed reduced penetrance. Analysis of tagging variants in CELSR1-3 in a set of 1739 Swedish-Danish scoliosis cases and 1812 controls revealed significant association (p = 0.0001) to rs2281894, a common synonymous variant in CELSR2. This association was not replicated in case-control cohorts from Japan and the US. No association was found to variants in CELSR1 or CELSR3. Our findings suggest a rare variant in CELSR2 as causative for idiopathic scoliosis in a family with dominant segregation and further highlight common variation in CELSR2 in general susceptibility to idiopathic scoliosis in the Swedish-Danish population. Both variants are located in the highly conserved GAIN protein domain, which is necessary for the auto-proteolysis of CELSR2, suggesting its functional importance.

Type 1 diabetes is associated with abberations of fat metabolism before and after the clinical onset of disease. It has been hypothesized that the absence of the effect of insulin in the liver contributes to reduced hepatic fat synthesis. We measured hepatic gene expression and serum metabolites before and after the onset of hyperglycemia in a BioBreeding rat model of type 1 diabetes. Functional pathway annotation identified that lipid metabolism was differentially expressed in hyperglycemic rats and that these pathways significantly overlapped with genes regulated by insulin. 17 serum metabolites significantly changed in concentration. All but 2 of the identified metabolites had previously been reported in type 1 diabetes, and carbohydrates were overall the most upregulated class of metabolites. We conclude that lack of insulin in the liver contributes to the changes in fat metabolism observed in type 1 diabetes. Further studies are needed to understand the clinical consequences of a lack of insulin in the liver in patients with type 1 diabetes.

The development of high-throughput biomolecular technologies has resulted in generation of vast omics data at an unprecedented rate. This is transforming biomedical research into a big data discipline, where the main challenges relate to the analysis and interpretation of data into new biological knowledge. The aim of this study was to develop a framework for biomedical big data analytics, and apply it for analyzing transcriptomics time series data from early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. To this end, transcriptome profiling by microarray was performed on differentiating human pluripotent stem cells sampled at eleven consecutive days. The gene expression data was analyzed using the five-stage analysis framework proposed in this study, including data preparation, exploratory data analysis, confirmatory analysis, biological knowledge discovery, and visualization of the results. Clustering analysis revealed several distinct expression profiles during differentiation. Genes with an early transient response were strongly related to embryonic- and mesendoderm development, for example CER1 and NODAL. Pluripotency genes, such as NANOG and SOX2, exhibited substantial downregulation shortly after onset of differentiation. Rapid induction of genes related to metal ion response, cardiac tissue development, and muscle contraction were observed around day five and six. Several transcription factors were identified as potential regulators of these processes, e.g. POU1F1, TCF4 and TBP for muscle contraction genes. Pathway analysis revealed temporal activity of several signaling pathways, for example the inhibition of WNT signaling on day 2 and its reactivation on day 4. This study provides a comprehensive characterization of biological events and key regulators of the early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. The proposed analysis framework can be used to structure data analysis in future research, both in stem cell differentiation, and more generally, in biomedical big data analytics.

Dietary choices are central to our understanding of ecology and evolution. Still, many aspects of food choice have been hampered by time consuming procedures and methodological problems. Faster and cheaper methods, such as DNA metabarcoding, have therefore been widely adopted. However, there is still very little empirical support that this new method is better and more accurate compared to the classic methods. Here, we compare DNA metabarcoding to macroscopic identifications of rumen contents in two species of wild free-ranging ungulates: roe deer and fallow deer. We found that the methods were comparable, but they did not completely overlap. Sometimes the DNA method failed to identify food items that were found macroscopically, and the opposite was also true. However, the total number of taxa identified increased using DNA compared to the macroscopic analysis. Moreover, the taxonomic precision of metabarcoding was substantially higher, with on average 90% of DNA-sequences being identified to genus or species level compared to 75% of plant fragments using macroscopy. In niche overlap analyses, presence/absence data showed that both methods came to very similar conclusions. When using the sequence count data and macroscopic weight, niche overlap was lower than when using presence-absence data yet tended to increase when using DNA compared to macroscopy. Nevertheless, the significant positive correlation between macroscopic quantity and number of DNA sequences counted from the same plant group give support for the use of metabarcoding to quantify plants in the rumen. This study thus shows that there is much to be gained by using metabarcoding to quantitatively assess diet composition compared to macroscopic analysis, including higher taxonomic precision, sensitivity and cost efficiency.

The white spotting locus (S) in dogs is colocalized with the MITF (microphtalmia-associated transcription factor) gene. The phenotypic effects of the four S alleles range from solid colour (S) to extreme white spotting (sw). We have investigated four candidate mutations associated with the sw allele, a SINE insertion, a SNP at a conserved site and a simple repeat polymorphism all associated with the MITF-M promoter as well as a 12 base pair deletion in exon 1B. The variants associated with white spotting at all four loci were also found among wolves and we conclude that none of these could be a sole causal mutation, at least not for extreme white spotting. We propose that the three canine white spotting alleles are not caused by three independent mutations but represent haplotype effects due to different combinations of causal polymorphisms. The simple repeat polymorphism showed extensive diversity both in dogs and wolves, and allele-sharing was common between wolves and white spotted dogs but was non-existent between solid and spotted dogs as well as between wolves and solid dogs. This finding was unexpected as Solid is assumed to be the wild-type allele. The data indicate that the simple repeat polymorphism has been a target for selection during dog domestication and breed formation. We also evaluated the significance of the three MITF-M associated polymorphisms with a Luciferase assay, and found conclusive evidence that the simple repeat polymorphism affects promoter activity. Three alleles associated with white spotting gave consistently lower promoter activity compared with the allele associated with solid colour. We propose that the simple repeat polymorphism affects cooperativity between transcription factors binding on either flanking sides of the repeat. Thus, both genetic and functional evidence show that the simple repeat polymorphism is a key regulator of white spotting in dogs. [ABSTRACT FROM AUTHOR]