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Success in long-term weight management depends partly on psychological and behavioral aspects. Understanding the links between psychological factors and eating behavior tendencies is needed to develop more effective weight management methods. This population-based cross-sectional study examined whether eating self-efficacy (ESE) is associated with cognitive restraint (CR), uncontrolled eating (UE), emotional eating (EE), and binge eating (BE). The hypothesis was that individuals with low ESE have more unfavorable eating behavior tendencies than individuals with high ESE. Participants were classified as low ESE and high ESE by the Weight-Related Self-Efficacy questionnaire (WEL) median cut-off point. Eating behavior tendencies were assessed with Three Factor Eating Questionnaire R-18 and Binge Eating Scale, and additionally, by the number of difficulties in weight management. The difficulties were low CR, high UE, high EE, and moderate or severe BE. Five hundred and thirty-two volunteers with overweight and obesity were included in the study. Participants with low ESE had lower CR (p < 0.03) and higher UE, EE, and BE (p < 0.001) than participants with high ESE. Thirty-nine percent of men with low ESE had at least two difficulties in successful weight control while this percentage was only 8% in men with high ESE. In women, the corresponding figures were 56% and 10%. The risk of low ESE was increased by high UE [OR 5.37 (95% CI 1.99–14.51)], high EE [OR 6.05 (95% CI 2.07–17.66)], or moderate or severe BE [OR 12.31 (95% CI 1.52–99.84)] in men, and by low CR [OR 5.19 (95% CI 2.22–12.18)], high UE [OR 7.20 (95% CI 2.41–19.22)], or high EE [OR 23.66 (95% CI 4.79–116.77)] in women. Low ESE was associated with unfavorable eating behavior tendencies and multiple concomitant difficulties in successful weight loss promotion. These eating behavior tendencies should be considered when counseling patients with overweight and obesity.

Generating electricity from solar energy is a way for households to participate in the ongoing transition to decarbonized and more decentralized energy systems. A large empirical literature has examined the drivers and barriers associated with household solar PV adoption. An emerging strand of this literature investigates what distinguishes earlier adopters from later adopters and non-adopters. However, there is yet limited understanding of the differences between earlier and later adopters, as few papers have applied formal statistical models to compare different customer segments. The present study addresses this gap. We examine how the factors that influence household solar PV choices differ between earlier adopters, potential adopters — households that have considered installing solar PV but have not yet done so — and non-adopters. We analyze these choices using rich data from a household-level survey conducted in Finland. The findings show that the adoption of solar PV is linked to a multitude of socio-demographic and financial factors and personal motivations. There are clear differences in the motives and perceptions of adopters, potential adopters, and non-adopters. Accounting for such differences between customer segments will help to better design and target public policy instruments and marketing campaigns that aim to incentivize and nudge households toward solar PV investments.

In this paper, we identify hybrid heating systems on a single residential customer’s premises using smart meter data. A comprehensive methodology is developed at a generic level for residential sector buildings to identify the type of primary and support heating systems. The methodology includes the use of unsupervised and supervised learning algorithms both separately and combined. It is applied to two datasets that vary in size, quality of data, and availability and reliability of background information. The datasets contain hourly electricity consumption profiles of residential customers together with the outdoor temperature. The validation metrics for the developed algorithms are elaborated to provide a probabilistic evaluation of the model. The results show that it is possible to identify the types of both primary and support heating systems in the form of probability of having electric- or non-electric type of heating. The results obtained help estimate the flexibility domain of the residential building sector and thereby generate a high value for the energy system as a whole.

Many mHealth interventions for health behavior change are considered effective for improving health outcomes. However, there is a limited understanding of the role of the components in an intervention on its effectiveness. Insights into intervention components such as content and software features are needed to design efficient and effective interventions. In this study, we conducted an exploratory analysis of objective data from the usage of a weight management app to understand the role of intervention components in weight loss. We identified a positive correlation between weight loss and the use of the intervention. We also found differences in the app feature use among those who lost weight. To lose weight, users needed to comply with the intervention by completing a combination of tasks. They needed to complete 70% of some tasks and up to a maximum of 30% of other tasks. In the future, we hope to use other types of collected data (logged and survey data) to gain more nuanced insights into how interventions are used. With the help of data analytics, we may find optimal paths of use and determine a satisfactory level of compliance to achieve desired goals. This can deepen our understanding of what works in an intervention.

As an answer to the need to reduce greenhouse gas emissions, organizations are increasingly making efforts to account for their carbon footprint. While general guidelines for carbon footprint calculation exist, they usually do not consider special characteristics of organisations such as institutions of higher education. Case studies can act then as learning tools, and comparisons between applied methodologies can be used to develop best practices. However, a lack of case studies published in peerreviewed journals limits access to the calculation results. This work provides a case study for a Northern European institution to extend the pool of available calculation methodologies tested under real-life conditions. The carbon footprint calculation of the University of Oulu utilises a hybrid model, combining approaches of Environmentally Extended Input-Output Analysis and Life-Cycle Assessment. The focus of the work was to consider included scopes and categories of emissions that represent indirect and non-energy-related greenhouse gas emissions, such as commuting or procurement of research and laboratory equipment. In 2019, the institution’s emission inventory sums up to 19,072 t CO2e, with the highest share due to the use of district heat on campus. Another goal of conducting this research was to show the limitations researchers might encounter when analysing caused emissions on an organisational level, and how the calculated carbon footprint can help to identify the best mitigation measures and possibilities for universities to reach carbon neutrality. It was found that the availability of information and missing strategies for data collection are prominent limiting factors. Favourable mitigation measures include the implementation of energysaving policies and improved policies for procurements.

Obesity is associated with low-grade inflammation and increased systemic oxidative stress. Roux-en-Y gastric bypass (RYGB) surgery is known to ameliorate the obesity-induced metabolic dysfunctions. We aimed to study the levels of natural antibodies in feces, before and 6 months after RYGB surgery in obese individuals with and without type 2 diabetes (T2D). Sixteen individuals with T2D and 14 non-diabetic (ND) individuals were operated. Total IgA, IgG and IgM antibody levels and specific antibodies to oxidized low-density lipoprotein (oxLDL), malondialdehyde-acetaldehyde adducts (MAA adducts), Porphyromonas gingivalis gingipain A hemagglutinin domain (Rgp44) and phosphocholine (PCho) were measured using chemiluminescence immunoassay. Total fecal IgA was elevated, while total IgM and IgG were not affected by the surgery. Fecal natural IgM specific to oxLDL decreased significantly in both T2D and ND individuals, while fecal IgM to Rgp44 and PCho decreased significantly in T2D individuals. A decrease in IgG to MAA-LDL, Rgp44 and PCho was detected. RYGB surgery increases the levels of total fecal IgA and decreases fecal natural IgG and IgM antibodies specific to oxLDL. Natural antibodies and IgA are important in maintaining the normal gut homeostasis and first-line defense against microbes, and their production is markedly altered with RYGB surgery.

The EU has several directives aiming toward carbon neutrality and is attempting to promote and encourage individual electricity consumers to participate in this endeavor. The key idea behind consumer awakening and activation is to push consumers to become aware of their electricity consumption behavior. The purpose of this paper was to examine the current consumption behavior of Finnish electricity consumers and their intention to support the goals of carbon neutrality through energy efficient consumption. The aim was to reveal how far the consumption behavior of people was from the intention to tackle climate change. To reach this goal, a qualitative research method was applied to evaluate the consumer awareness and intentions. A consumer survey was conducted to enable standardized and consistent data collection. The research utilized a key performance indicator (KPI) approach to evaluate the results: the social KPIs connected with qualitative values provide a comprehensive approach. According to the results, the awareness of consumers of their consumption behavior was not very high, and some data needs can be identified. In addition, clear intentions can be detected among the residents to support the environment and to save energy. However, the consumers did not seem to be aware of the available data and existing services that could help them to improve their energy efficiency. Therefore, more motivation and communication is still required to affect the electricity consumption behavior.

Real-world products and physics-based simulations are becoming interconnected. In particular, real-time capable dynamic simulation has made it possible for simulation models to run in parallel and simultaneously with operating machinery. This capability combined with state observer techniques such as Kalman filtering have enabled the synchronization between simulation and the real world. State estimator techniques can be applied to estimate unmeasured quantities, also referred as virtual sensing, or to enhance the quality of measured signals. Although synchronized models could be used in a number of ways, value creation and business model development are currently defining the most practical and beneficial use cases from a business perspective. The research reported here reveals the communication and collaboration methods that lead to economically relevant technology solutions. Two case examples are given that demonstrate the proposed methodology. The work benefited from the broad perspective of researchers from different backgrounds and the joint effort to drive the technology development towards business relevant cases.

Background: Roux-en-Y gastric bypass (RYGB) surgery is an effective treatment for obesity, which improves cardiovascular health and reduces the risk of premature mortality. However, some reports have suggested that RYGB may predispose patients to adverse health outcomes, such as inflammatory bowel disease (IBD) and colorectal cancer. Objectives: The present prospective study aimed to evaluate the impact of RYGB surgery on cardiovascular risk factors and gastrointestinal inflammation in individuals with and without type 2 diabetes (T2D). Setting: University hospital setting in Finland. Methods: Blood and fecal samples were collected at baseline and 6 months after surgery from 30 individuals, of which 16 had T2D and 14 were nondiabetics. There were also single study visits for 6 healthy reference patients. Changes in cardiovascular risk factors, serum cholesterol, and triglycerides were investigated before and after surgery. Fecal samples were analyzed for calprotectin, anti-Saccharomyces cerevisiae immunoglobulin A antibodies (ASCA), active lipopolysaccharide (LPS) concentration, short-chain fatty acids (SCFAs), intestinal alkaline phosphatase activity, and methylglyoxal-hydro-imidazolone (MG-H1) protein adducts formation. Results: After RYGB, weight decreased on average −21.6% (−27.2 ± 7.8 kg), excess weight loss averaged 51%, and there were improvements in cardiovascular risk factors. Fecal calprotectin levels (P < 0.001), active LPS concentration (P < 0.002), ASCA (P < 0.02), and MG-H1 (P < 0.02) values increased significantly, whereas fecal SCFAs, especially acetate (P < 0.002) and butyrate (P < 0.03) levels, were significantly lowered. Conclusion: The intestinal homeostasis is altered after RYGB, with several fecal markers suggesting increased inflammation; however, clinical significance of the detected changes is currently uncertain. As chronic inflammation may predispose patients to adverse health effects, our findings may have relev

Background and purpose: Many drugs and environmental contaminants induce hypercholesterolemia and promote the risk of atherosclerotic cardiovascular disease. We tested the hypothesis that pregnane X receptor (PXR), a xenobiotic-sensing nuclear receptor, regulates the level of circulating atherogenic lipids in humans and utilized mouse experiments to identify the mechanisms involved. Experimental approach: We performed serum NMR metabolomics in healthy volunteers administered rifampicin, a prototypical human PXR ligand or placebo in a crossover setting. We used high-fat diet fed wild-type and PXR knockout mice to investigate the mechanisms mediating the PXR-induced alterations in cholesterol homeostasis. Key results: Activation of PXR induced cholesterogenesis both in pre-clinical and clinical settings. In human volunteers, rifampicin increased intermediate-density lipoprotein (IDL), low-density lipoprotein (LDL) and total cholesterol and lathosterol–cholesterol ratio, a marker of cholesterol synthesis, suggesting increased cholesterol synthesis. Experiments in mice indicated that PXR activation causes widespread induction of the cholesterol synthesis genes including the rate-limiting Hmgcr and upregulates the intermediates in the Kandutsch–Russell cholesterol synthesis pathway in the liver. Additionally, PXR activation induced plasma proprotein convertase subtilisin/kexin type 9 (PCSK9), a negative regulator of hepatic LDL uptake, in both mice and humans. We propose that these effects were mediated through increased proteolytic activation of sterol regulatory element-binding protein 2 (SREBP2) in response to PXR activation. Conclusions and implications: PXR activation induces cholesterol synthesis, elevating LDL and total cholesterol in humans. The PXR–SREBP2 pathway is a novel regulator of the cholesterol and PCSK9 synthesis and a molecular mechanism for drug- and chemical-induced hypercholesterolemia.

HDL particles can be structurally modified in atherosclerotic disorders associated with low HDL cholesterol level (HDL-C). We studied whether the lipidome of the main phosphatidylcholine (PC), lysophosphatidylcholine (LPC) and sphingomyelin (SM) species of HDL2 and HDL3 subfractions is associated with premature coronary heart disease (CHD) or metabolic syndrome (MetS) in families where common low HDL-C predisposes to premature CHD. The lipidome was analyzed by LC-MS. Lysophosphatidylcholines were depleted of linoleic acid relative to more saturated and shorter-chained acids containing species in MetS compared with non-affected subjects: the ratio of palmitic to linoleic acid was elevated by more than 30%. A minor PC (16:0/16:1) was elevated (28–40%) in MetS. The contents of oleic acid containing PCs were elevated relative to linoleic acid containing PCs in MetS; the ratio of PC (16:0/18:1) to PC (16:0/18:2) was elevated by 11–16%. Certain PC and SM ratios, e.g., PC (18:0/20:3) to PC (16:0/18:2) and a minor SM 36:2 to an abundant SM 34:1, were higher (11–36%) in MetS and CHD. The fatty acid composition of certain LPCs and PCs displayed a characteristic pattern in MetS, enriched with palmitic, palmitoleic or oleic acids relative to linoleic acid. Certain PC and SM ratios related consistently to CHD and MetS.

Background: Gaucher disease (GD) is a rare inherited multiorgan disorder, yet a diagnosis can be significantly delayed due to a broad spectrum of symptoms and lack of disease awareness. Recently, the prototype of a GD point-scoring system (PSS) was established by the Gaucher Earlier Diagnosis Consensus (GED-C) initiative, and more recently, validated in Gaucher patients in UK. In our study, the original GED-C PSS was tested in Finnish GD patients. Furthermore, the feasibility of point scoring large electronic health record (EHR) data set by data mining to identify potential undiagnosed GD cases was evaluated. Methods: This biobank study was conducted in collaboration with two Finnish biobanks. Five previously diagnosed Finnish GD patients and ~ 170,000 adult biobank subjects were included in the study. The original PSS was locally adjusted due to data availability issues and applied to the Finnish EHR data representing special health care recordings. Results: All GD patients had high levels of the biomarker lyso-Gb1 and deleterious GBA mutations. One patient was a compound heterozygote with a novel variant, potentially pathogenic mutation. Finnish EHR data allowed the retrospective assessment of 27–30 of the 32 original GED-C signs/co-variables. Total point scores of GD patients were high but variable, 6–18.5 points per patient (based on the available data on 28–29 signs/co-variables per patient). All GD patients had been recorded with anaemia while only three patients had a record of splenomegaly. 0.72% of biobank subjects were assigned at least 6 points but none of these potential “GD suspects” had a point score as high as 18.5. Splenomegaly had been recorded for 0.25% of biobank subjects and was associated with variable point score distribution and co-occurring ICD-10 diagnoses. Discussion: This study provides an indicative GED-C PSS score range for confirmed GD patients, also representing potential mild cases, and demonstrates the feasibility of scoring

Activation of pregnane X receptor (PXR) elevates circulating 4β-hydroxycholesterol (4βHC), an agonist of liver X receptor (LXR). PXR may also regulate 25-hydroxycholesterol and 27-hydroxycholesterol. Our aim was to elucidate the roles of PXR and oxysterols in the regulation of cholesterol transporters. We measured oxysterols in serum of volunteers dosed with PXR agonist rifampicin 600 mg/day versus placebo for a week and analyzed the expression of cholesterol transporters in mononuclear cells. The effect of 4βHC on the transport of cholesterol and the expression of cholesterol transporters was studied in human primary monocyte-derived macrophages and foam cells in vitro. The expression of cholesterol transporters was measured also in rat tissues after dosing with a PXR agonist. The levels of 4βHC were elevated, while 25-hydroxycholesterol and 27-hydroxycholesterol remained unchanged in volunteers dosed with rifampicin. The expression of ATP binding cassette transporter A1 (ABCA1) was induced in human mononuclear cells in vivo. The influx of cholesterol was repressed by 4βHC, as was the expression of influx transporter lectin-like oxidized LDL receptor-1 in vitro. The cholesterol efflux and the expression of efflux transporters ABCA1 and ABCG1 were induced. The expression of inducible degrader of the LDL receptor was induced. In rats, PXR agonist increased circulating 4βHC and expression of LXR targets in peripheral tissues, especially ABCA1 and ABCG1 in heart. In conclusion, PXR activation-elevated 4βHC is a signaling molecule that represses cholesterol influx and induces efflux. The PXR-4βHC-LXR pathway could link the hepatic xenobiotic exposure and the regulation of cholesterol transport in peripheral tissues.

Objectives: The aim was to investigate whether lifestyle changes produced by persuasive Information and Communication Technology (ICT) counselling can lower the prevalence of metabolic syndrome (MetS). Methods: A total of 532 participants (20–60 years, body mass index 27–35 kg/m²) were randomly assigned to six arms according to counselling type (no, short-term, or intensive) with or without ICT intervention. In this report the prevalence of MetS and its components were compared between no-ICT group and ICT group. Moreover, the frequency of the web information system usage was analysed for the number of logins, responses to weekly messages, and other record variables. Results: The ICT group had significantly lower proportion of MetS (33.7% vs. 45.3%, p = .022) than the no-ICT group at 2-year follow-up. In mixed model, the ICT group had lower prevalence of MetS than no-ICT group (OR 0.50, 95%CI 0.27–0.90) after intervention. The tertile with the highest utilization had 71% lower prevalence of MetS compared with the lowest utilization tertile or the no-ICT group. Conclusions: Web-based ICT is able to reduce the prevalence of MetS. In addition, higher utilization of the web information system is associated with a greater decrease in the prevalence of MetS., Key messages Our internet health behaviour change support system based on persuasive design and cognitive behaviour therapy markedly reduces metabolic syndrome in overweight/obese subjects. As a stand-alone tool it may save healthcare personnel resources as it is suitable at a low cost for both obese/overweight patients and the public at large.

Mapping geological outcrops is a crucial part of mineral exploration, mine planning and ore extraction. With the advent of unmanned aerial systems (UAS) for rapid spatial and spectral mapping, opportunities arise in fields where traditional ground-based approaches are established and trusted, but fail to cover sufficient area or compromise personal safety. Multi-sensor UAS are a technology that change geoscientific research, but they are still not routinely used for geological mapping in exploration and mining due to lack of trust in their added value, missing expertise and guidance in the selection and combination of drones and sensors. To address these limitations and highlight the potential of using UAS in exploration settings, we present a UAS multi-sensor mapping approach based on the integration of drone-borne photography, multi- and hyperspectral imaging, and magnetics. Data are processed with conventional methods as well as innovative machine-learning algorithms and validated by geological field mapping, yielding a comprehensive and geologically interpretable product. As a case study, we chose the northern extension of the Siilinjärvi apatite mine in Finland, in a brownfield exploration setting with plenty of ground truth data available and a survey area that is only partly covered by vegetation. We conducted rapid UAS surveys from which we created a multi-layered dataset to investigate properties of the ore-bearing carbonatite-glimmerite body. Our resulting geologic map discriminates between the principal lithologic units and distinguishes ore-bearing from waste rocks. Structural orientations and lithological units are deduced based on high-resolution, hyperspectral image-enhanced point clouds. UAS-based magnetic data allow an insight into their subsurface geometry through modelling based on magnetic interpretation. We validate our results via ground survey including rock specimen sampling, geochemical and mineralogical analysis and spectroscopic point meas