Salivary immunoglobulin A (IgA) is a key component of oral mucosal immunity, yet its relationships to systemic health are not well defined. We investigated whether salivary IgA relates to systemic immune responses, cardiometabolic risk, and oral microbial diversity and composition. In this cross-sectional study we analyzed adults from the Northern Finland Birth Cohort 1966 at age 46 years. Participants underwent standardized clinical and laboratory assessments and provided saliva and serum samples. The oral microbiome was characterized from salivary samples (n = 863) by 16S rRNA gene sequencing. Salivary IgA and circulating IgA/IgG/IgM were quantified by chemiluminescence immunoassay. Participants were categorized by salivary IgA levels, and immunological, anthropometric, metabolic, inflammatory, and microbiome measures were examined. Here we show that higher salivary IgA is associated with greater adiposity, including higher BMI (25.7 vs. 27.2 kg/m²; P = 0.001), percent body fat (27.3% vs. 29.6%; P = 0.031), body fat mass (20.7 vs. 24.0 kg; P = 0.00007), and visceral fat area (95.3 vs. 107.7 cm²; P = 0.002) across salivary IgA quartiles. Salivary IgA is associated with less favorable glycemic profiles: higher fasting glucose (P = 0.018), HbA1c (P = 0.014), and insulin (P = 0.006), and shows a positive association with serum IgA (P = 0.042) while serum IgG, IgM, and high-sensitivity C-reactive protein (hs-CRP) do not differ across salivary IgA quartiles (Kruskal–Wallis, Bonferroni post hoc). Oral microbial α-diversity is lower in the highest IgA quartile compared with the lowest, and specific shifts in the community structure and composition are observed. Oral microbiome α- or β-diversity is not associated with body fat mass. In this cross-sectional study, greater adiposity and higher glycemic indices are associated with higher salivary IgA, which in turn is associated with decreased oral microbiome diversity in the absence of overt oral inflammation. These findings are consistent with possible mucosal-metabolic crosstalk and motivate longitudinal and mechanistic studies to determine directionality and clinical implications.

AIM:The humoral immune system is implicated in the link between periodontitis and atherosclerosis. This study aims to explore how interactions between the oral microbiota and humoral immune responses may contribute to this association. MATERIALS AND METHODS:We analysed data from the Northern Finland Birth Cohort 1966, which included 1560 participants who underwent comprehensive health and oral examinations. Serum antibodies against phosphorylcholine (PCho) and malondialdehyde acetaldehyde (MAA) adducts were measured using chemiluminescence immunoassays. In a sub-cohort (n = 868), the oral microbiome from saliva samples was characterised using 16S rRNA gene sequencing. RESULTS:Higher serum levels of IgA and IgG to PCho, as well as IgA to MAA, were associated with an increased number of teeth with probing pocket depths (PPD) ≥ 4 mm. Several oral bacterial species, including Prevotella dentalis , Filifactor alocis and Treponema denticola , correlated with both PPD ≥ 4 mm and IgA/IgG responses to PCho. Mediation analysis, adjusted for periodontitis risk factors, identified F. alocis as a mediator linking elevated plasma IgG to PCho with the number of teeth with PPD ≥ 4 mm. Additionally, individuals harbouring F. alocis exhibited increased carotid intima-media thickness. CONCLUSIONS:Our findings suggest that F. alocis may serve as a microbial link between periodontitis and atherosclerosis. Future mechanistic studies should investigate how F. alocis induces systemic IgG responses and contributes to atherosclerosis.

BACKGROUND:Although there have been significant advancements in reducing the burden of cardiovascular disease (CVD) by modifying traditional CVD risk factors, substantial risks persist, particularly among male subjects who exhibit heightened susceptibility to atherosclerosis. In this context, we aim to study the link between oral microbiome and carotid intima media thickness (cIMT). METHODS:The Northern Finland Birth Cohort of 1966 (mean age 46 years, n = 869) underwent an extensive health examination, including the measurement of cIMT. The oral microbiome was also investigated using high-throughput 16S rRNA gene sequencing. RESULTS:Here we show that oral microbiome diversity links with atherosclerosis risk factors, namely smoking, glycemic balance, low-grade inflammation, and periodontitis. After excluding CVD-influencing factors (n = 339), oral microbiome genera (p = 0.030), Shannon index (p = 0.001), β-diversity Bray-Curtis (p < 0.001), and Jaccard (p < 0.001) are associated with cIMT in males, but not in the female sub-cohort. Furthermore, in the male sub-cohort (n = 131), the genera Prevotella, Megasphaera, and Veillonella associate positively with cIMT, while Absconditabacteria, Capnocytophaga, Gemella, Fusobacterium, Neisseria, Aggregatibacter, Tannerella, Treponema, Cardiobacterium, and Bacteroidales associate inversely with cIMT. We examine the involvement of serum total immunoglobulins and antibodies to phosphorylcholine (PCho) and malondialdehyde-acetaldehyde LDL (MAA-LDL) with cIMT. Subjects with high cIMT have lower levels of serum total IgA (p = 0.009), IgA to PCho (p = 0.017), and IgG to PCho (p = 0.008). The relative abundance of cIMT-associated genera correlates with serum IgA antibodies. CONCLUSIONS:This middle-aged birth cohort study shows that male oral microbiome diversity links to cIMT, suggesting a potential sex-specific interaction between the oral microbiome and atherosclerosis.

Abstract In crude oil process vessels, precise control of oil and water levels is vital. In oil refining, high-voltage electrostatic coalescers create strong electric fields for desalting and dehydration, which may disrupt electrical level measurements. Stilling wells improve measurement conditions and shield devices from external electrical interference. This paper proposes enclosing electric tomography- based level measurement technology within a perforated stilling well to counteract high-voltage grid effects. Electrical Tomography (ET) enables comprehensive real-time monitoring of material distributions in various environments, such as pipes, tanks, and vessels. The ET probe sensor provides information on liquid levels within separators, identifying water-emulsion, emulsion-oil and oil-gas interfaces. The probe sensor is confined by a rather narrow stilling well to investigate its effects on measurement accuracy. The stilling well, with an inner diameter of 91.3 mm, accommodated a probe with a diameter of 59.0 mm. The system was tested with 11 different configurations of stratified liquids so that its level measurement capabilities were assessed with water, emulsion, oil and gas. In general, ET measurements within stilling wells are very localized since the proximity of the metal wall of the stilling well affects the electric interactions between the electrodes. The test results showed that the measured information still contains a sufficient amount of information so that the conductivity profile and subsequent interface levels can be estimated with good accuracy. The Root Mean Square Error (RMSE) across all interface levels in the entire series of test cases was 20.6 mm. This equates to approximately 1% of the length of the measurement area. This is of the same order of magnitude as in standard test measurements in identical conditions but without the stilling well. Electrical Tomography is well-suited for real-time measurement of various interface levels in challenging operating conditions where good repeatability and time-resolution are needed. This study demonstrated that Electrical Tomography based level measurements are successful even when installed in narrow stilling wells, without significant impact on measurement accuracy.

We aimed to study levels of natural antibodies in plasma, and their associations to clinical and fecal biomarkers, before and 6 months after Roux‐en‐Y gastric bypass (RYGB) surgery. Thirty individuals with obesity [16 type 2 diabetic, 14 non‐diabetic (ND)] had RYGB surgery. Total plasma IgA, IgG and IgM antibody levels and specific antibodies to oxidized low‐density lipoprotein (oxLDL), malondialdehyde‐acetaldehyde adducts, Porphyromonas gingivalis gingipain A hemagglutinin domain (Rgp44), and phosphocholine were measured using chemiluminescence immunoassay. Associations between plasma and fecal antibodies as well as clinical markers were analyzed. RYGB surgery reduced blood pressure, and the glycemic state was improved. A higher level of diastolic blood pressure was associated with lower plasma antibodies to oxLDL after surgery. Also, lower level of glucose markers associated with lower level of plasma antibodies to bacterial virulence factors. Antibodies to oxLDL decreased after surgery, and positive association between active serum lipopolysaccharide and specific oxLDL antibodies was detected. Total IgG levels decreased after surgery, but only in ND individuals. Reduced level of total plasma IgG, improved state of hypertension and hyperglycemia and their associations with decreased levels of specific antibodies in plasma, suggest an improved state of systemic inflammation after RYGB surgery.

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.

OBJECTIVEOxidized epitopes such as malondialdehyde-acetaldehyde (MAA) play a crucial role in the progression of atherosclerosis through activation of the humoral immune response. The exact mechanism of the association between atherosclerosis and periodontal diseases is not fully understood. The aim of the current study is to evaluate the association of oral humoral immune response to oxidized epitopes with parameters of periodontal disease.MATERIALS AND METHODSThe Parogene cohort consist of patients who have undergone coronary angiography due to cardiac symptoms. In this study, 423 patients were randomly selected for an extensive oral examination. Salivary Immunoglobulin A to oxidized epitopes and bacterial antigens was determined by chemiluminescence immunoassay.RESULTSIn a binary logistic regression model adjusted with periodontal disease confounders, periodontal pocket depth (PPD) 4-5 mm associated with salivary IgA antibodies to MAA-LDL (p = 0.034), heat shock protein 60 of Aggregatibacter actinomycetemcomitans (p = 0.045), Porphyromonas gingivalis (p = 0.045), A. actinomycetemcomitans (p = 0.005), P. intermedia (p = 0.020), and total IgA (p = 0.003).CONCLUSIONSThe current study shows the association of salivary IgA to MAA-LDL with PPD 4-5 mm in a cohort of patients with chronic coronary artery disease. Humoral immune cross-reactivation to oxidized epitopes such MAA-LDL could partly explain the link of periodontitis with systemic diseases.

Measurement of sand build-up in the production separators has been a challenge for field personnel due to the limitations of current technologies. Nucleonic-type level profiler has been previously implemented in a few offshore locations but limited due to special handling and permit/license requirements of radioactive material involved. Therefore, this paper aims to present the acceleration of new non-nucleonic tomographic technology testing and qualification to measure accumulating sand in separators as well as multi-disciplinary approvals for fast-track field application. The general idea in tomography is to expose the target of interest to electrical signals and measure the response of the target. With the aid of mathematical models, it is possible to infer the distribution of different materials within the target from the responses. Results of tomographic measurements are displayed on a computer as a vertical profile. The tested tomographic solution was based on a tomographic technology called Electrical Tomography. The key idea in Electrical Tomographic image construction is to find a permittivity and conductivity distribution for which the observations predicted by the model are in good agreement with actual ET measurement data and hence profiling is to be created. The test was performed at the laboratory with a full tomographic profiler setup including a test probe sensor for profiling, electronics, and a computer unit. In addition to the tomographic instrumentation, a transparent plastic vessel was used for visual observations of the accumulated sand layers. Visual observations were made simultaneously with tomographic imaging. In the test setup, we had sand, water, emulsion, and oil. The samples were placed into a transparent vessel. It was visually observed that the probe sensor was able to distinguish "wet sand-water" interface and "water-oil interface" in all the tested conditions. At the end of the test, the sand layer was flattened and packed more tightly and the change in the layer thickness was seen in the tomographic image. We concluded that the resolution of the detection of the sand layer was in the range of 1-2 cm. The technology is novel as it is a non-nucleonic profiler and a field-safe technology to be used. The profiler is intrinsically safe and certified to the most demanding IECEx class to be used in Zone 0 hazardous atmospheres. Detailed engineering of the technology to be installed at one of the production separators has proceeded. Finite Element Analysis has shown that the system can withstand turbulent conditions within the multi-phase production separator.

IgA is the most abundant Ab in the human body. However, most patients with selective IgA deficiency (SIgAD) are asymptomatic. IgM, and to lesser extent IgG Abs, are generally presumed to compensate for the lack of IgA in SIgAD by multiplying and adopting functions of IgA. We used data from the Northern Finland Birth Cohort 1966 to investigate whether SIgAD patients have differences in levels of natural Abs to oxidized epitopes compared with 20 randomly selected healthy controls. First, we screened the saliva and serum samples from the Northern Finland Birth Cohort 1966 cohort (n = 1610) for IgA concentration. We detected five IgA-deficient subjects, yielding a prevalence of 0.3%, which is consistent with the general prevalence of 0.25% in the Finnish population. To detect natural Abs, we used malondialdehyde acetaldehyde-low-density lipoprotein (MAA-LDL), an Ag known to bind natural Abs. In this study, we show that natural secretory IgM and IgG Abs to MAA-DL were significantly increased in subjects with SIgAD. Given that secretory IgA is an important part of mucosal immune defense and that, in the gut microbiota, dysbiosis with SIgAD patients has been observed, we characterized the oral bacterial microbiota of the subjects with and without SIgAD using high-throughput 16S rRNA gene sequencing. We found no significant alterations in diversity and composition of the oral microbiota in subjects with SIgAD. Our data suggest that increased levels of secretory natural Abs in patients with SIgAD could be a compensatory mechanism, providing alternative first-line defense against infections and adjusting mucosal milieu to maintain a healthy oral microbiota.

Deposition formation inside pipelines is a major and growing problem in the oil and gas industry. The optimal use of prevention and remediation tools such as chemical inhibitors and cleaning processes could lead to major savings due to minimized production problems and optimized pipe cleaning costs. This requires characterization and quantification of the actual deposits inside pipelines and downholes. Recently, a novel deposition inline inspection sensor moving inside the pipeline has been proposed based on "inside-out" electrical tomography. In this sensor, the distribution of electrical properties between the sensor and the pipe wall are estimated based on measurements carried out using electrodes around the sensor. In this study, the next generation sensor moving inside the pipeline is described and a deep neural network based approach to deposit estimation is introduced. Test results from a 70 m long semi-industrial scale flow loop containing paraffin wax and calcium carbonate deposits of different thicknesses are shown. Challenges include the changing position and orientation of the sensor during the low. The results show that the sensor is able to measure both deposit thickness and type with good accuracy which indicates that the sensor is suitable for industrial use. Accurate knowledge about deposits allows future blockage prevention, detecting build-up locations in the early phase, increasing accuracy of multi-phase flow and deposition models, optimization of chemical use and validation of deposit cleaning tools before integrity campaigns leading to overall reduced pipeline operation costs.

Abstract Objectives/Scope Mature fields operations, which are almost 70% of today's production have a high water cut content. For each barrel of oil produced there can be 3 or more barrels of water. This means that operational conditions are challenging and might not be ideal for the facilities. In crude oil tanks, one of the most crucial operation parameter is the settling time of oil and water. Especially with heavy oils and high water cut, the operational conditions can be challenging with the existence of emulsion/rag layers in the tank. Most common level detection instrumentation struggle with detecting the proper interface levels leading to faulty control that can cause costly remediation and loss of revenue. This paper presents a novel solution by applying electric tomography pipe and probe sensors. Methods, Procedures, Process In electrical tomography, multiple electrodes are attached on the surface of the sensor and excitations are applied to some electrodes and responses are measured from other electrodes. Assuming a fast separation in the following crude oil tank, the operator expects the flow being stratified already in incoming trunk line. In real life this is not often the case: The incoming flow is turbulent meaning that there is no clear water/oil interface. To overcome this a pipe sensor is needed to monitor the flow regime and hence there is a possibility to control the a) chemical feed and b) flow speed to get the flow stratified. As soon as the flow is stratified in a trunk line it will be guided to a crude oil settling tank for an additional separation. In this tank there is a possibility to apply a probe sensor to monitor reliably the emulsion layer between water and oil. This allows settling time, process parameters and chemicals to be optimized to get a clear separation and hence improving the oil and water quality for a further processing. Results, Observations, Conclusions Results from pipe sensor operation in crude oil pipelines will be shared. The results will show an accurate water cut profile across the pipe cross section even under stratified flow conditions. Additionally, probe sensor results in a crude oil tank operation will be shared and hence confirming the reliability and robustness of the probe sensor operation in tanks. One of the key features of the pipe and probe sensors is the full functionality even under severe contamination with deposits on the sensor surfaces. The operational principle of this method will be shared and verified by experimental results. Novel/Additive Information The sensor technology for the tank inspection and piping uses novel electrical tomography with compact electronic and fast-acting computation with high resolution. This type of technology for settling tank application is new.

Objectives/ScopeDeposition inspection sensor based on electrical tomography has been proposed recently. In this work, a next generation electrical tomography sensor is introduced and a novel mathematical approach for the estimation of the deposit thickness is described. It is essential for the pipeline operators to keep the lines open for smooth flow and high flow efficiency. Deposit thickness, deposit type and location of deposit is required for optimal pipeline cleaning. The usage of chemicals as well as number of cleaning pig runs can be optimized based on the information that intelligent pig is giving.Methods, Procedures, ProcessIn electrical tomography, electrodes are attached on the surface of the sensor and excitations are applied to some electrodes and responses are measured from other electrodes. The electrical properties of the medium are estimated based on these measurements. In pigging applications, the distribution of electrical properties between the PIG surface and metal pipe is estimated. The thickness and type of deposit (wax/scale) can be identified from the estimated electrical properties. In the proposed approach the estimation of the parameters is done by using a novel deep neural network based approach. In practice, number of measurements that are analyzed after each PIG run can be hundreds of thousands. The neural network based approach was chosen in order to achieve reasonable computational efficiency (computation time) in real applications with large amounts of data.Results, Observations, ConclusionsThe introduced sensor is for 12-inch lines and designed to be used when the oil line is filled with water. This sensor was tested in a laboratory test line with artificial deposit samples. After these tests and calibration, the sensor is deployed to be used in real pipe line inspections. The major challenges in pipe line runs include the movement of the sensor during measurements, electrical noise and changing excitations. In the neural network model, the position of the PIG is estimated simultaneously with the electrical properties and the effect of all these aforementioned uncertainties are also modelled. Based on the results conclusions can be drawn on the efficiency and performance using neural networks and the high suitability of electrical tomography for deposit mapping.Novel/Additive InformationIn this study, it is shown that intelligent pig based on the electrical tomography can be used reliable for deposit inspection. Furthermore, the computation approach based on the deep neural network is computationally efficient and it is tolerable for measurement noise and other uncertainties in real measurements.

Natural Abs are produced by B lymphocytes in the absence of external Ag stimulation. They recognise self, altered self and foreign Ags, comprising an important first-line defence against invading pathogens and serving as innate recognition receptors for tissue homeostasis. Natural IgG Abs have been found in newborns and uninfected individuals. Yet, their physiological role remains unclear. Previously, no natural IgG Abs to oxidation-specific epitopes have been reported. Here, we show the cloning and characterisation of mouse IgG mAbs against malondialdehyde acetaldehyde (MAA)-modified low-density lipoprotein. Sequence analysis reveals high homology with germline genes, suggesting that they are natural. Further investigation shows that the MAA-specific natural IgG Abs cross-react with the major periodontal pathogen Porphyromonas gingivalis and recognise its principle virulence factors gingipain Kgp and long fimbriae. The study provides evidence that natural IgGs may play an important role in innate immune defence and in regulation of tissue homeostasis by recognising and removing invading pathogens and/or modified self-Ags, thus being involved in the development of periodontitis and atherosclerosis.

Atherosclerosis is a chronic inflammatory disease and major cause of mortality worldwide. One of the crucial steps for atherosclerotic plaque development is oxidation of low-density lipoprotein (LDL). Through the oxidation, highly immunogenic epitopes are created and the immune system is activated. Association between atherosclerosis and periodontal diseases is well documented, and one of the main oral pathogens common in periodontitis is Aggregatibacter actinomycetemcomitans (Aa). Heat shock protein 60 (HSP60) is an important virulence factor for Aa bacteria and a strong activator of the immune system. Cross-reactivity of HSP60 and oxidized LDL (OxLDL) antibodies could be a potential mechanism in the progression of atherosclerosis and one possible link between atherosclerosis and periodontitis. Human plasma samples from neonates and mothers were analyzed to determine if antibody titer to Aa-HSP60 protein is already present in newborns. Further objectives were to characterize antibody response in Aa-HSP60 immunized mice and to determine possible antibody cross-reaction with oxidized LDL. We demonstrated that newborns already have IgM antibody levels to Aa-HSP60. We also showed that in mice, Aa-HSP60 immunization provoked IgG and IgM antibody response not only to Aa-HSP60 but also to malondialdehyde acetaldehyde-modified LDL (MAA-LDL). Competition assay revealed that the antibodies were specific to Aa-HSP60 and cross-reacted with MAA-LDL. Our results suggest a possibility of molecular mimicry between Aa-HSP60 and MAA-LDL, making it intriguing to speculate on the role of HSP60 protein in atherosclerosis that manifests at young age.

A large body of literature has established the link between periodontal disease and cardiovascular disease. Oxidized low-density lipoproteins (OxLDLs) have a crucial role in atherosclerosis progression through initiation of immunological response. Monoclonal IgM antibodies to malondialdehyde-modified low-density lipoprotein (MDA-LDL) and to malondialdehyde acetaldehyde-modified low-density lipoprotein (MAA-LDL) have been shown to cross-react with the key virulence factors of periodontal pathogens Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans. We have previously shown that salivary IgA antibodies to MAA-LDL cross-react with P. gingivalis in healthy humans. In this study, we aim to assess whether oral mucosal immune response represented by salivary IgA to MAA-LDL and oral pathogens is associated with coronary artery disease (CAD). Also, the molecular mimicry through antibody cross-reaction between salivary IgA to MAA-LDL and oral pathogens was evaluated. The study subjects consisted of 451 patients who underwent a coronary angiography with no CAD ( n = 133), stable CAD ( n = 169), and acute coronary syndrome (ACS, n = 149). Elevated salivary IgA antibody levels to MAA-LDL, Rgp44 (gingipain A hemagglutinin domain of P. gingivalis), and Aa-HSP60 (heat shock protein 60 of A. actinomycetemcomitans) were discovered in stable-CAD and ACS patients when compared to no-CAD patients. In a multinomial regression model adjusted for known cardiovascular risk factors, stable CAD and ACS were associated with IgA to MAA-LDL ( P = 0.016, P = 0.043), Rgp44 ( P = 0.012, P = 0.004), Aa-HSP60 ( P = 0.032, P = 0.030), Tannerella forsythia ( P = 0.002, P = 0.004), Porphyromonas endodontalis ( P = 0.016, P = 0.020), Prevotella intermedia ( P = 0.038, P = 0.005), and with total IgA antibody concentration ( P = 0.002, P = 0.016). Salivary IgA to MAA-LDL showed cross-reactivity with the oral pathogens tested in the study patients. The study highlights an association between salivary IgA to MAA-LDL and atherosclerosis. However, whether salivary IgA to MAA-LDL and the related oral humoral responses play a causal role in the development in the CAD should be elucidated in the future.

Climate change projections are commonly based on multi-model ensembles of climate simulations. In this paper we consider the choice of bias models in Bayesian multimodel predictions. Buser et al. (Clim Res 44(2–3):227–241, 2010a) introduced a hybrid bias model which combines commonly used constant bias and constant relation bias assumptions. The hybrid model includes a weighting parameter which balances these bias models. In this study, we use a cross-validation approach to study which bias model or bias parameter leads to, in a specific sense, optimal climate change projections. The analysis is carried out for summer and winter season means of 2 m-temperatures spatially averaged over the IPCC SREX regions, using 19 model runs from the CMIP5 data set. The cross-validation approach is applied to calculate optimal bias parameters (in the specific sense) for projecting the temperature change from the control period (1961–2005) to the scenario period (2046–2090). The results are compared to the results of the Buser et al. (Clim Res 44(2–3):227–241, 2010a) method which includes the bias parameter as one of the unknown parameters to be estimated from the data.

Aims. This study investigated the association of autoantibodies binding to oxidized low-density lipoproteins (oxLDL) in diabetic retinopathy (DR). Methods. Plasma from 229 types 1 and 2 patients with DR including diabetic macular edema (DME) and proliferative diabetic retinopathy (PDR) was analysed with ELISA-based assay to determine IgA, IgG, and IgM autoantibody levels binding to oxLDL. The controls were 106 diabetic patients without retinopathy (NoDR) and 139 nondiabetic controls (C). Results. PDR group had significantly higher IgA autoantibody levels than DME or NoDR: mean 94.9 (SD 54.7) for PDR, 75.5 (41.8) for DME (p=0.001), and 76.1 (48.2) for NoDR (p=0.008). There were no differences in IgG, IgM, or IgA that would be specific for DR or for DME. Type 2 diabetic patients had higher levels of IgA autoantibodies than type 1 diabetic patients (86.0 and 65.5, resp., p=0.004) and the highest levels in IgA were found in type 2 diabetic patients with PDR (119.1, p>0.001). Conclusions. IgA autoantibodies were increased in PDR, especially in type 2 diabetes. The high levels of IgA in PDR, and especially in type 2 PDR patients, reflect the inflammatory process and enlighten the role of oxLDL and its autoantibodies in PDR.

The main objective of this study is to determine the drying kinetics of a fixed bed composed of porous particles using the electrical capacitance tomography (ECT) technique. This technique is an imaging modality in which the permittivity distribution inside an object is computed using capacitive measurements from the boundary of the object and mathematical algorithms. An experimental convective drying device equipped with an electrical tomography system is built. An existing relationship between the average moisture content and the dielectric permittivity of the product is determined experimentally from a calibration of the moisture content during the drying process. The tomograms of normalized permittivity distribution are presented. As a result, the distribution of the moisture content of the packed bed is then determined. The drying kinetics of the silica gel is drawn, and the various stages of the drying process are identified. The thermal behavior during the drying process at different levels of the granular bed has been established. The results show the efficiency of electrical tomography technique. This technique can be used to find other parameters such as the evolution of the porosity of the medium during drying as well as other parameters.

We consider electrical impedance tomography (EIT) imaging of the brain. The brain is surrounded by the poorly conducting skull which has low conductivity compared to the brain. The skull layer causes a partial shielding effect which leads to weak sensitivity for the imaging of the brain tissue. In this paper we propose an approach based on the Bayesian approximation error approach, to enhance the contrast in brain imaging. With this approach, both the (uninteresting) geometry and the conductivity of the skull are embedded in the approximation error statistics, which leads to a computationally efficient algorithm that is able to detect features such as internal haemorrhage with significantly increased sensitivity and specificity. We evaluate the approach with simulations and phantom data.