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In “A Model for Estimating Biological Age From Physiological Biomarkers of Healthy Aging: Cross-sectional Study” (JMIR Aging 2022;5(2):e35696) the authors noted one error. In the originally published article, Figure 4 inadvertently appeared with the same image as that of Figure 3. In the corrected version of the article, Figure 4 was updated with the following image: (Figure Presented) The correction will appear in the online version of the paper on the JMIR Publications website on June 28, 2022, together with the publication of this correction notice. Because this was made after submission to PubMed, PubMed Central, and other full-text repositories, the corrected article has also been resubmitted to those repositories.

Background: Individual differences in the rate of aging and susceptibility to disease are not accounted for by chronological age alone. These individual differences are better explained by biological age, which may be estimated by biomarker prediction models. In the light of the aging demographics of the global population and the increase in lifestyle-related morbidities, it is interesting to invent a new biological age model to be used for health promotion. Objective: This study aims to develop a model that estimates biological age based on physiological biomarkers of healthy aging. Methods: Carefully selected physiological variables from a healthy study population of 100 women and men were used as biomarkers to establish an estimate of biological age. Principal component analysis was applied to the biomarkers and the first principal component was used to define the algorithm estimating biological age. Results: The first principal component accounted for 31% in women and 25% in men of the total variance in the biological age model combining mean arterial pressure, glycated hemoglobin, waist circumference, forced expiratory volume in 1 second, maximal oxygen consumption, adiponectin, high-density lipoprotein, total cholesterol, and soluble urokinase-type plasminogen activator receptor. The correlation between the corrected biological age and chronological age was r=0.86 (P<.001) and r=0.81 (P<.001) for women and men, respectively, and the agreement was high and unbiased. No difference was found between mean chronological age and mean biological age, and the slope of the regression line was near 1 for both sexes. Conclusions: Estimating biological age from these 9 biomarkers of aging can be used to assess general health compared with the healthy aging trajectory. This may be useful to evaluate health interventions and as an aid to enhance awareness of individual health risks and behavior when deviating from this trajectory.

BACKGROUND: Actions to improve healthy aging and delay morbidity are crucial, given the global aging population. We believe that biological age estimation can help promote the health of the general population. Biological age reflects the heterogeneity in functional status and vulnerability to disease that chronological age cannot. Thus, biological age assessment is a tool that provides an intuitively meaningful outcome for the general population, and as such, facilitates our understanding of the extent to which lifestyle can increase health span.OBJECTIVE: This interdisciplinary study intends to develop a biological age model and explore its usefulness.METHODS: The model development comprised three consecutive phases: (1) conducting a cross-sectional study to gather candidate biomarkers from 100 individuals representing normal healthy aging people (the derivation cohort); (2) estimating the biological age using principal component analysis; and (3) testing the clinical use of the model in a validation cohort of overweight adults attending a lifestyle intervention course.RESULTS: We completed the data collection and analysis of the cross-sectional study, and the initial results of the principal component analysis are ready. Interpretation and refinement of the model is ongoing. Recruitment to the validation cohort is forthcoming. We expect the results to be published by December 2021.CONCLUSIONS: We expect the biological age model to be a useful indicator of disease risk and metabolic risk, and further research should focus on validating the model on a larger scale.

Pseudomonas aeruginosa PAO1 (MIC 0.064µg/ml) was used to perform agar diffusion tests employing tobramycin containing tablets. The growth of the bacteria and the formation of inhibition zones were studied by stereomicroscopy and by blotting with microscope slides and staining with Methylene blue, Alcian blue and a fluorescent lectin for the P. aeruginosa PSL which was studied by confocal laser scanning microscopy. The diffusion of tobramycin from the deposit was modelled by using a 3D geometric version of Fick's 2nd law of diffusion. The time-dependent gradual increase of Minimal Biofilm Eradication Concentration (MBEC) was studied by the Calgary Biofilm Devise. The early inhibition zone was visible after 5 h incubation. The corresponding calculated tobramycin concentration at the border was 1.9µg/ml and increased to 3.2µg/ml and 6.3µg/ml after 7 and 24 h incubation. The inhibition zone increased to the stable, final zone after 7 h incubation. Bacterial growth and small aggregate formation (young biofilms) took place inside the inhibition zone until the small aggregates contained ≤≈64 cells and production of polysaccharide matrix including PSL had begun, thereafter the small bacterial aggregates were killed by tobramycin. The bacteria at the border of the stable inhibition zone and beyond continued to grow to a mature biofilm and produced large amount of polysaccharide containing matrix. The formation of the inhibition zone during the agar diffusion antibiotic susceptibility test is due to a switch from the planktonic to the biofilm mode of growth and gives clinical important information about the increased antibiotic tolerance of biofilms.

OUTLINE: In chronic lung infections by Pseudomonas aeruginosa (PA) the bacteria thrive in biofilm structures protected from the immune system of the host and from antibiotic treatment. Increasing evidence suggests that the susceptibility of the bacteria to antibiotic treatment can be significantly enhanced by hyperbaric oxygen treatment. The aim of this study is to simulate the effect of ciprofloxacin treatment in a PAO1 biofilm model with aggregates in agarose when combined with hyperbaric oxygen treatment. This is achieved in a reaction-diffusion model that describes the combined effect of ciprofloxacin diffusion, oxygen diffusion and depletion, bacterial growth and killing, and adaptation of the bacteria to ciprofloxacin. In the model, the oxygen diffusion and depletion use a set of parameters derived from experimental results presented in this work. The part of the model describing ciprofloxacin killing uses parameter values from the literature in combination with our estimates (Jacobs, et al., 2016; Grillon, et al., 2016). Micro-respirometry experiments were conducted to determine the oxygen consumption in the P. aeruginosa strain PAO1. The parameters were validated against existing data from an HBOT experiment by Kolpen et al. (2017). The complete oxygen model comprises a reaction-diffusion equation describing the oxygen consumption by using a Michaelis-Menten reaction term. The oxygen model performed well in predicting oxygen concentrations in both time and depth into the biofilm. At 2.8 bar pure oxygen pressure, HBOT increases the penetration depth of oxygen into the biofilm almost by a of factor 4 in agreement with the scaling that follows from the stationary balance between the consumption term and diffusion term. CONCLUSION: In the full reaction-diffusion model we see that hyperbaric oxygen treatment significantly increases the killing by ciprofloxacin in a PAO1 biofilm in alignment with the experimental results from Kolpen et al. (Kolpen, et al., 2017

In chronic Pseudomonas aeruginosa (PA) biofilm lung infections the bacteria are protected from the immune system of the host and from antibiotic treatment. It has been demonstrated that the susceptibility of the bacteria to antibiotic treatment can be enhanced by hyperbaric oxygen treatment. Here we present a reaction-diffusion model that describes the combined effect of ciprofloxacin diffusion, oxygen diffusion and depletion, bacterial growth and killing, and adaptation of the bacteria to ciprofloxacin. In the model, the oxygen diffusion and depletion use a set of parameters derived from experiments. The description of ciprofloxacin killing uses parameter values from the literature in combination with our estimates. The complete oxygen model comprises a reaction-diffusion equation describing the oxygen consumption by using a Michaelis-Menten reaction term. The oxygen model performed well in predicting oxygen concentrations in both time and depth into the biofilm. At 2.8 bar pure oxygen pressure, HBOT increases the penetration depth of oxygen into the biofilm by a of factor 4 and we see that hyperbaric oxygen treatment significantly increases the killing by ciprofloxacin in a PAO1 biofilm in alignment with the experimental results

The abdominal aorta (AA) is predisposed to development of abdominal aneurysms (AAA), a focal dilatation of the artery with fatal consequences if left untreated. The blood flow patterns in the AA is thought to play an important role in the development of AAA. The purpose of this work is to investigate the blood flow pat- terns within a group of healthy volunteers (4 females, 7 males) aged 23 to 76 years to identify changes and differences related to age and gender. The healthy volunteers were categorized by gender (male/female) and age (below/above 35 years). Subject-specific flow and geometry data were acquired using the research interface on a medical ultrasound scanner and segmentation of 3D magnetic resonance angiography respectively. The largest average diameter was among the elderly males (19.7 (± 1.33) mm) and smallest among the young females (12.4 (± 0.605) mm). The highest peak systolic velocity was in the young female group (1.02 (± 0.336) m/s) and lowest in the elderly male group (0.836 (± 0.127) m/s). A geometrical change with age was observed as the AA becomes more bended with age. This also affects the blood flow velocity patterns, which are markedly different from young to elderly. Thus, changes in blood flow patterns in the AA related to age and gender is observed. Further investigations are needed to determine the relation between changes in blood flow patterns and AAA development.

This contribution describes and evaluates an experimental combination of a spiral and discipline-oriented curriculum implemented in the bachelor’s and master’s program in Medicine and Technology. The implementation in the master’s program is in the form of a study line in Medical Imaging and Radiation Physics containing three disciplines: Imaging modalities, Radiation therapy and Image processing. The two imaging courses in the bachelor’s program and the first imaging course in the master’s program follow a spiral curriculum in which most disciplines are encountered in all courses, but in a gradually more advanced manner. The remaining courses in the master’s program follow a discipline-oriented curriculum. From a practical point of view, the spiral course portfolio works well in an undergraduate environment, where the courses involved are to be taken by all students and in the order planned. However, in the master’s program, such a tight schedule is impractical since students are likely to seek specialization. From a pedagogical point of view, the spiral curriculum is advantageous to use in the initial semesters where the teaching can be conducted so that the students can build on their intuitive understanding of the subject. The program was evaluated in terms of the progression in scientific demands in exam from course to course and in terms of the pattern of course selection by the students. The analysis was based on 96 students. The pattern of course selection was found to follow the intentions of the program, thus demonstrating high fulfillment of the learning outcomes.

The structural integrity of the abdominal aorta is maintained by elastin, collagen, and vascular smooth muscle cells. Changes with age in the structure can lead to develop-ment of aneurysms. This paper presents initial work to capture these changes in a finite element model (FEM) of a structural-ly-motivated anisotropic constitutive relation for the “four fiber family” arterial model. First a 2D implementation is used for benchmarking the FEM implementation to fitted biaxial stress-strain data obtained experimentally from four different groups of persons; 19-29 years, 30-60 years, 61-79 years and abdominal aortic aneurysm (AAA) patients. Next the constitu-tive model is implemented in an anisotropic 3D FEM formula-tion for future simulation of intact aortic geometries. The 2D simulations of the biaxial test experiment show good agree-ment with experimental data with a standard deviation below 0.5% in all cases. The maximum axial and hoop stress in the group of AAA patients was 94.9 kPa (±0.283 kPa) and 94.3 kPa (±0.224 kPa) at maximum stretch ratios of 1.043 and 1.037, respectively. In the 3D simulations, the maximum stress is also found to occur in the AAA patient group, with the highest stress in the circumferential direction (275 kPa). Comparison with an already published isotropic model indicates that the latter underestimates the peak stress significantly. Based on these results it is concluded that the four fiber family model has been successfully implemented into a 3D anisotropic finite element model and that this model can provide more accurate insight into the stress conditions in aortic aneurysms.

Cigarette smoking is the leading self-inflicted risk factor for cardiovascular diseases; it causes arterial stiffening with serious sequelea including atherosclerosis and abdominal aortic aneurysms. This work presents a new interpretation of arterial stiffening caused by smoking based on data published for rat pulmonary arteries. A structurally motivated ‘‘four fiber family’’ constitutive relation was used to fit the available biaxial data and associated best-fit values of material parameters were estimated using multivariate nonlinear regression. Results suggested that arterial stiffening caused by smoking was reflected by consistent increase in an elastin-associated parameter and moreover by marked increase in the collagen-associated parameters. That is, we suggest that arterial stiffening due to cigarette smoking appears to be isotropic, which may allow simpler phenomenological models to capture these effects using a single stiffening parameter similar to the approach in isotropic continuum damage mechanics. There is a pressing need, however, for more detailed histological information coupled with more complete biaxial mechanical data for a broader range of systemic arteries.

Cigarette smoking constitutes a major risk factor for diverse cardiovascular diseases (CVD). Many physiological and pathophysiological parameters affect arterial stiffness. While underlying mechanisms remain unclear, smoking increases arterial stiffness, which contributes to many disease processes. The goal of this work was to use a structurally motivated nonlinear constitutive relation to quantify increased arterial stiffness based on available data. Specifically, we used a “four-fiber family model” that includes dominant effects of axial, circumferential, and symmetric-diagonal families of collagen fibers embedded within an isotropic, elastin-dominated matrix. Published data, i.e. biaxial responses during pressure-diameter and axial force-length tests on pulmonary arteries from rats subjected to 2 or 3 months of smoking, were used to determine the associated best-fit values of the material parameters. The primary finding was that cigarette smoking induces significant increases in the material parameters describing the micromechanical properties of all four families of collagen fibers with increased duration of smoking. Additionally, there was a moderate increase in the material parameter describing the behaviour of the elastic fibers. These findings suggest that arterial stiffening in response to smoking is isotropic due to the changes in the material parameters seen in all fiber directions. Although changes are manifested in both elastic and collagen fibers, the predominant stiffening appeared to be due mainly to changes in collagen fiber structure (e.g., cross-linking).

This work presents new fluid-structure interaction (FSI) models in both 2D and 3D of the effect of using vascular stents as treatment of cerebral berry aneurysms. The stent is positioned inside the cerebral artery covering the neck of the aneurysm. The stent is expected to alter the blood flow into the aneurysm such that the blood coagulates due to low blood velocity, and rupture of the aneurysm is prevented. A 3D FSI model consisting of three domains (blood, arterial, and aneurismal) is used to investigate the effect of the aneurysm on blood flow. Aspects of stent design such as pore size and shape and strut size, shape, and position are modeled in 2D and 3D FSI models. The models show that pore size and strut shape both have significant influence on stent efficiency.