Inequality persists in a large citizen science programme despite increased participation through ICT innovations.

Biological recording is a prominent and widely practised form of citizen science, but few studies explore long-term demographic trends in participation and knowledge production. We studied long-term demographic trends of age and gender of participants reporting to a large online citizen science multi-taxon biodiversity platform ( www.artportalen.se ). Adoption by user communities and continually developing Information and Communications Technologies (ICTs) greatly increased the number of participants reporting data, but profound long-term imbalances in gender contribution across species groups persisted over time. Reporters identifying as male dominated in numbers, spent more days in the field reporting and reported more species on each field day. Moreover, an age imbalance towards older participants amplified over time. As the first long-term study of citizen participation by age and gender, our results show that it is important for citizen science project developers to account for cultural and social developments that might exclude participants, and to engage with underrepresented and younger participants. This could facilitate the breadth of engagement and learning across a larger societal landscape, ensure project longevity and biodiversity data representation (e.g. mitigate gender bias influence on the number of reports of different species groups).

Thermoregulatory costs of the innate immune response are modulated by winter food availability in a small passerine.

In winter, a challenge to the immune system could pose a major energetic trade-off for small endotherms, whereby increasing body temperature (Tb ; i.e. eliciting fever) may be beneficial to fight off invading pathogens yet incur a cost for vital energy-saving mechanisms. Having previously shown that the availability and acquisition of energy, through manipulation of food predictability, influences the depth of rest-phase hypothermia in a wild bird in winter, we expected that the nocturnal thermoregulatory component of the acute-phase immune response would also be modulated by food availability. By manipulating winter food availability in the wild for great tits Parus major, we created an area offering a "predictable" and constant supply of food at feeding stations, while an unmanipulated area was subject to naturally "unpredictable" food. Birds were subject to an immune challenge shortly after dusk, and the thermoregulatory response was quantified via continuous recording of nocturnal Tb , using subcutaneous thermo-sensitive transponders. In response to immune challenge, all birds increased Tb above the level maintained prior to immune challenge (i.e. baseline). However, birds experiencing a naturally unpredictable food supply elevated Tb more than birds subject to predictable food resources, during the period of expected peak response and for the duration of the night. Furthermore, "unpredictable-food" females took longer to return to their baseline Tb . Assuming baseline nocturnal Tb reflects an individual's optimum, based on their available energy budget, the metabolic cost of eliciting an acute-phase response for "unpredictable-food" birds was more than double that of "predictable-food" birds. The absence of differences in absolute Tb during the peak response could support the idea of an optimal Tb for immune system activation. Alternatively, "predictable-food" birds could have acquired tolerance to endotoxin as a result of using feeding stations, thus affording them reduced costs associated with a smaller Tb increase. These findings shed new light on the trade-offs associated with food acquisition, thermoregulation and immune function in small-bodied endotherms. This knowledge is of increasing importance, given the predicted elevated pathogen risks associated with changes in climate and anthropogenic activities.

The Gothenburg H70 Birth cohort study 2014-16: design, methods and study population.

To improve health care for older persons, we need to learn more about ageing, e.g. identify protective factors and early markers for diseases. The Gothenburg H70 Birth Cohort Studies (the H70 studies) are multidisciplinary epidemiological studies examining representative birth cohorts of older populations in Gothenburg, Sweden. So far, six birth cohorts of 70-year-olds have been examined over time, and examinations have been virtually identical between studies. This paper describes the study procedures for the baseline examination of the Birth cohort 1944, conducted in 2014-16. In this study, all men and women born 1944 on specific dates, and registered as residents in Gothenburg, were eligible for participation (n = 1839). A total of 1203 (response rate 72.2%; 559 men and 644 women; mean age 70.5 years) agreed to participate in the study. The study comprised sampling of blood and cerebrospinal fluid, psychiatric, cognitive, and physical health examinations, examinations of genetics and family history, use of medications, social factors, functional ability and disability, physical fitness and activity, body composition, lung function, audiological and ophthalmological examinations, diet, brain imaging, as well as a close informant interview, and qualitative studies. As in previous examinations, data collection serves as a basis for future longitudinal follow-up examinations. The research gained from the H70 studies has clinical relevance in relation to prevention, early diagnosis, clinical course, experience of illness, understanding pathogenesis and prognosis. Results will increase our understanding of ageing and inform service development, which may lead to enhanced quality of care for older persons.

Acute pancreatitis--costs for healthcare and loss of production.

OBJECTIVE. Severity of acute pancreatitis (AP) can vary from a mild to a fulminant disease with high morbidity and mortality. Cost analysis has, however, hitherto been sparse. The aim of this study was to calculate the cost of acute pancreatitis, both including hospital costs and costs due to loss of production. MATERIAL AND METHODS. All adult patients treated at Skane University Hospital, Lund, during 2009-2010, were included. A severity grading was conducted and cost analysis was performed on an individual basis. RESULTS. Two hundred and fifty-two patients with altogether 307 admissions were identified. Mean age was 60 ± 19 years, and 121 patients (48%) were men. Severe AP (SAP) was diagnosed in 38 patients (12%). Thirteen patients (5%) died. Acute biliary pancreatitis was more costly than alcohol induced AP (p < 0.001). Total costs for treating mild AP (MAP) in patients ≤65 years old was lower (p = 0.001) and costs for SAP was higher (p = 0.024), as compared to older patients. The overall hospital cost and cost for loss of production was per person in mean €5,100 ± 2,400 for MAP and €28,200 ± 38,100 for SAP (p < 0.001). The costs for treating AP during the two-year-long study period were in mean €9,762 ± 19,778 per patient. Extrapolated to a national perspective, the annual financial burden for AP in Sweden would be €38,500,000; corresponding to €4,100,000 per million inhabitants. CONCLUSIONS. The costs of treating AP are high, especially in severe cases with a long ICU stay. These results highlight the need to optimize care and continue the identification and focus on SAP, in order to try to limit organ failure and infectious complications.

The 2011 outcome from the Swedish Health Care Registry on Heart Disease (SWEDEHEART).

OBJECTIVES: The Swedish Web-system for Enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies (SWEDEHEART) collects data to support the improvement of care for heart disease. DESIGN: SWEDEHEART collects on-line data from consecutive patients treated at any coronary care unit n = (74), followed for secondary prevention, undergoing any coronary angiography, percutaneous coronary intervention, percutaneous valve or cardiac surgery. The registry is governed by an independent steering committee, the software is developed by Uppsala Clinical Research Center and it is funded by The Swedish national health care provider independent of industry support. Approximately 80,000 patients per year enter the database which consists of more than 3 million patients. RESULTS: Base-line, procedural, complications and discharge data consists of several hundred variables. The data quality is secured by monitoring. Outcomes are validated by linkage to other registries such as the National Cause of Death Register, the National Patient Registry, and the National Registry of Drug prescriptions. Thanks to the unique social security number provided to all citizens follow-up is complete. The 2011 outcomes with special emphasis on patients more than 80 years of age are presented. CONCLUSION: SWEDEHEART is a unique complete national registry for heart disease.

CODUSA--customize optimal donor using simulated annealing in heart transplantation.

In heart transplantation, selection of an optimal recipient-donor match has been constrained by the lack of individualized prediction models. Here we developed a customized donor-matching model (CODUSA) for patients requiring heart transplantations, by combining simulated annealing and artificial neural networks. Using this approach, by analyzing 59,698 adult heart transplant patients, we found that donor age matching was the variable most strongly associated with long-term survival. Female hearts were given to 21% of the women and 0% of the men, and recipients with blood group B received identical matched blood group in only 18% of best-case match compared with 73% for the original match. By optimizing the donor profile, the survival could be improved with 33 months. These findings strongly suggest that the CODUSA model can improve the ability to select optimal match and avoid worst-case match in the clinical setting. This is an important step towards personalized medicine.

Validation of a modified EuroSCORE risk stratification model for cardiac surgery: the Swedish experience.

OBJECTIVE: The European System for Cardiac Operative Risk Evaluation (EuroSCORE) is used to identify patients at high risk for aortic valve replacement (AVR) in whom alternative procedures, such as trans-catheter aortic valve implantation (TAVI), may be appropriate. The aim of the present study was to calibrate and validate the EuroSCORE for different cardiac surgery procedures to improve patient selection for valve surgery. METHODS: The study included 46516 patients undergoing open cardiac surgery during 2001-2007. A fivefold cross-validation technique was used to calibrate four different models. Model discrimination was determined by the area under the receiver operating characteristic (ROC) curve and model calibration by the Hosmer-Lemeshow (H-L) test. RESULTS: The actual and predicted 30-day mortality was 3.2%. The discrimination (ROC area) of the calibrated 30-day mortality prediction models was 0.79 for coronary bypass surgery, 0.77 for mitral valve surgery (MVS), and 0.75 for miscellaneous procedures, compared with 0.78 (p = 0.199), 0.74 (p = 0.077), and 0.72 (p = 0.001), respectively, for the original EuroSCORE. The discrimination for AVR was the same for the calibrated and the original EuroSCORE model (0.70). The H-L test gave a p-value of 0.104 for the calibrated and <0.001 for the original EuroSCORE model. CONCLUSIONS: A calibration of EuroSCORE resulted in an acceptable predictive capacity for 30-day mortality, and improved discrimination and calibration for MVS and miscellaneous procedures. However, the poor discriminatory for the AVR procedure suggests that the EuroSCORE may not be satisfying for assessing risk prior to TAVI and that more optimized risk stratification models may be needed.

Non-contact acoustic cell trapping in disposable glass capillaries.

Non-contact trapping using acoustic standing waves has shown promising results in cell-based research lately. However, the devices demonstrated are normally fabricated using microfabrication or precision machining methods leading to a high unit cost. In e.g. clinical or forensic applications avoiding cross-contamination, carryover or infection is of outmost importance. In these applications disposable devices are key elements, thus making the cost per unit a critical factor. A solution is presented here where low-cost off-the-shelf glass capillaries are used as resonators for standing wave trapping. Single-mode as well as multi-node trapping is demonstrated with an excellent agreement between simulated and experimentally found operation frequencies. Single particle trapping is verified at 7.53 MHz with a trapping force on a 10 microm particle of up to 1.27 nN. The non-contact trapping is proved using confocal microscopy. Finally, an application is presented where the capillary is used as a pipette for aspirating, trapping and dispensing red blood cells.

Gastrointestinal complications after cardiac surgery - improved risk stratification using a new scoring model.

Gastrointestinal (GI) complications are serious consequences of cardiac surgery. The aim of this study was to develop, evaluate and validate a new risk score model for GI complications after cardiac surgery. The risk score model, named gastrointestinal complication score (GICS), was developed using prospectively collected data from 5593 patients who underwent 5636 cardiac surgical procedures between 1996 and 2001. The model was validated on 1031 cardiac surgery patients between 2005 and 2006. The scoring system's ability to predict GI complications was estimated by receiver operating characteristic (ROC)-curves and Hosmer-Lemeshow test. Fifty GI complications were identified in 47 patients (0.8%) in the developmental data set and eight (0.8%) in the validation data set. The ROC area in the developmental data set was 0.81 with a good calibration estimated by Hosmer-Lemeshow test (P=0.89). In the validation data set, the area under the curve was 0.83. The estimated probability for the patient to develop a GI complication after cardiac surgery at a GICS >or=15 is >20% and at a GICS

Implementation of a protein profiling platform developed as an academic-pharmaceutical industry collaborative effort.

As much attention has devoted to the proteome research during the last few years, biomarker discovery has become an increasingly hot area, potentially enabling the development of new assays for diagnosis and prognosis of severe diseases. This is the field of research interest where efforts originating from both academic and industrial groups should jointly work on solutions. In this paper, we would like to demonstrate the fruitful combination of both research domains where the scientific crossroads sprout fresh ideas from the basic research domain and how these are refined and tethered to industrial standards. We will present an approach that is based on novel microfluidic devices, utilizing their benefits in processing small-volume samples. Our biomarker discovery strategy, built around this platform, involves optimized samples processing (based on SPE and sample enrichment) and fast MALDI-MS readout. The identification of novel biomarkers at low-abundance level has been achieved by the utilization of a miniaturized sample handling platform, which offers clean-up and enrichment of proteins in one step. Complete automation has been realized in the form of a unique robotic instrumentation that is able to extract and transfer 96 samples onto standard MALDI target plates with high throughput. The developed platform was operated with a 60 sample turnaround per hour allowing sensitivities in femtomol regions of medium- and low-abundant target proteins from clinical studies on samples of multiple sclerosis and gastroesophageal reflux disease. Several proteins have been identified as new biomarkers from cerebrospinal fluid and esophagus epithelial cells.

The cost of vacuum-assisted closure therapy in treatment of deep sternal wound infection.

OBJECTIVES: Surgical sites infections are very expensive and the total costs for coronary artery bypass grafting (CABG) surgery followed by deep sternal wound infection (DSWI) with conventional therapy are estimated to be 2.8 times that for normal, CABG surgery. Promising results have been reported with vacuum-assisted closure (VAC) therapy in patients with DSWI. This study presents the cost of VAC therapy in patients with DSWI after CABG surgery. DESIGN: Thirty-eight CABG patients with DSWI, between 2001 and 2005, were treated with VAC therapy. The cost of surgery, intensive care, ward care, laboratory tests and other costs were analyzed. RESULTS: No three-month mortality or recurrent infection was observed. The average cost of CABG procedure and treatment of DSWI was 2.5 times higher than the mean cost of CABG alone. No significant correlations were found between the preoperative EuroSCORE and the cost of DSWI therapy. CONCLUSIONS: VAC therapy for patients who underwent CABG surgery followed by DSWI seems to be cost effective, and has low mortality rate.

Costly steroids: egg testosterone modulates nestling metabolic rate in the zebra finch.

The transfer of non-genetic resources from mother to the offspring often has considerable consequences for offspring performance. In birds, maternally derived hormones are known to influence a variety of morphological, physiological and behavioural traits in the chick. So far, the range of these hormonal effects involves benefits in terms of enhanced growth and competitive ability as well as costs in terms of immunosuppression. However, since yolk hormones can enhance growth and begging activity, high levels of these hormones may also involve energetic costs. Here, we show experimentally that elevated levels of prenatal testosterone increase resting metabolic rate in nestling zebra finches (Taeniopygia guttata). Surprisingly, however, elevation of prenatal testosterone did not result in higher growth rates and, thus, differences in resting metabolism do not seem to be linked to nestling growth. We conclude that apart from immunosuppressive effects, high levels of egg steroids may also entail costs in terms of increased energy expenditure.

Risk factor identification and mortality prediction in cardiac surgery using artificial neural networks.

OBJECTIVE: The artificial neural network model is a nonlinear technology useful for complex pattern recognition problems. This study aimed to develop a method to select risk variables and predict mortality after cardiac surgery by using artificial neural networks. METHODS: Prospectively collected data from 18,362 patients undergoing cardiac surgery at 128 European institutions in 1995 (the European System for Cardiac Operative Risk Evaluation database) were used. Models to predict the operative mortality were constructed using artificial neural networks. For calibration a sixfold cross-validation technique was used, and for testing a fourfold cross-testing was performed. Risk variables were ranked and minimized in number by calibrated artificial neural networks. Mortality prediction with 95% confidence limits for each patient was obtained by the bootstrap technique. The area under the receiver operating characteristics curve was used as a quantitative measure of the ability to distinguish between survivors and nonsurvivors. Subgroup analysis of surgical operation categories was performed. The results were compared with those from logistic European System for Cardiac Operative Risk Evaluation analysis. RESULTS: The operative mortality was 4.9%. Artificial neural networks selected 34 of the total 72 risk variables as relevant for mortality prediction. The receiver operating characteristics area for artificial neural networks (0.81) was larger than the logistic European System for Cardiac Operative Risk Evaluation model (0.79; P = .0001). For different surgical operation categories, there were no differences in the discriminatory power for the artificial neural networks (P = .15) but significant differences were found for the logistic European System for Cardiac Operative Risk Evaluation (P = .0072). CONCLUSIONS: Risk factors in a ranked order contributing to the mortality prediction were identified. A minimal set of risk variables achieving a superior mortality prediction was defined. The artificial neural network model is applicable independent of the cardiac surgical procedure.

EuroSCORE predicts intensive care unit stay and costs of open heart surgery.

BACKGROUND: This study aimed to determine whether the preoperative risk stratification model EuroSCORE predicts the different components of resource utilization in open heart surgery. METHODS: Data for all adult patients undergoing heart surgery at the University Hospital of Lund, Sweden, between 1999 and 2002 were prospectively collected. Costs were calculated for the surgery and intensive care and ward stay for each patient (excluding transplant cases and patients who died intraoperatively). Regression analysis was applied to evaluate the correlation between EuroSCORE and costs. The predictive accuracy for prolonged postoperative intensive care unit (ICU) stay was assessed by the Hosmer-Lemeshow goodness-of-fit test. The discriminatory power was evaluated by calculating the areas under receiver operating characteristics curves. RESULTS: The study included 3,404 patients. The mean cost for the surgery was 7,300 dollars, in the ICU 3,746 dollars, and in the ward 3,500 dollars. Total cost was significantly correlated with EuroSCORE, with a correlation coefficient of 0.47 (p < 0.0001); the correlation coefficient was 0.31 for the surgery cost, 0.46 for the ICU cost, and 0.11 for the ward cost. The Hosmer-Lemeshow p value for EuroSCORE prediction of more than 2 days' stay in the ICU was 0.40, indicating good accuracy. The area under the receiver operating characteristics curve was 0.78. The probability of an ICU stay exceeding 2 days was more than 50% at a EuroSCORE of 14 or more. CONCLUSIONS: In this single-institution study, the additive EuroSCORE algorithm could be used to predict ICU cost and also an ICU stay of more than 2 days after open heart surgery.