Vascular neurocognitive disorders and the vascular risk factors

Dementias are clinical neurodegenerative diseases characterized by permanent and progressive transformation of cognitive functions such as memory, learning capacity, attention, thinking, language, passing judgments, calculation or orientation. Dementias represent a relatively frequent pathology, encountered at about 10% of the population of 65-year olds and 20% of the population of 80-year olds. This review presents the main etiological forms of dementia, which include Alzheimer form of dementia, vascular dementia, dementia associated with alpha-synucleionopathies, and mixed forms. Regarding vascular dementia, the risk factors are similar to those for an ischemic or hemorrhagic cerebrovascular accident: arterial hypertension, diabetes mellitus, dyslipidemia, smoking, obesity, age, alcohol consumption, cerebral atherosclerosis/ arteriosclerosis. Several studies show that efficient management of the vascular risk factors can prevent the expression and/ or progression of dementia. Thus, lifestyle changes such as stress reduction, regular physical exercise, decreasing dietary fat, multivitamin supplementation, adequate control of blood pressure and serum cholesterol, and social integration and mental stimulation in the elderly population are important factors in preventing or limiting the symptoms of dementia, a disease with significant individual, social, and economic implications

Vascular neurocognitive disorders and the vascular risk factors

Dementias are clinical neurodegenerative diseases characterized by permanent and progressive transformation of cognitive functions such as memory, learning capacity, attention, thinking, language, passing judgments, calculation or orientation. Dementias represent a relatively frequent pathology, encountered at about 10% of the population of 65-year olds and 20% of the population of 80-year olds. This review presents the main etiological forms of dementia, which include Alzheimer form of dementia, vascular dementia, dementia associated with alpha-synucleionopathies, and mixed forms. Regarding vascular dementia, the risk factors are similar to those for an ischemic or hemorrhagic cerebrovascular accident: arterial hypertension, diabetes mellitus, dyslipidemia, smoking, obesity, age, alcohol consumption, cerebral atherosclerosis/ arteriosclerosis. Several studies show that efficient management of the vascular risk factors can prevent the expression and/ or progression of dementia. Thus, lifestyle changes such as stress reduction, regular physical exercise, decreasing dietary fat, multivitamin supplementation, adequate control of blood pressure and serum cholesterol, and social integration and mental stimulation in the elderly population are important factors in preventing or limiting the symptoms of dementia, a disease with significant individual, social, and economic implications

Assessment of the total precipitable water from a sun photometer, microwave radiometer and radiosondes at a continental site in southeastern Europe

In this study, we discuss the differences in the total precipitable water (TPW), retrieved from a Cimel sun photometer operating at a continental site in southeast Europe, between version 3 (V3) and version 2 (V2) of the AErosol RObotic NETwork (AERONET) algorithms. In addition, we evaluate the performance of the two algorithms comparing their product with the TPW obtained from a collocated microwave radiometer and nearby radiosondes during the period 2007–2017. The TPW from all three instruments was highly correlated, showing the same annual cycle, with lower values during winter and higher values during summer. The sun photometer and the microwave radiometer depict the same daily cycle, with some discrepancies during early morning and late afternoon due to the effect of solar zenith angle on the measurements of the photometer. The TPW from V3 of the AERONET algorithm has small differences compared with V2, mostly related to the use of the new laboratory-based temperature coefficients used in V3. The microwave radiometer measurements are in good agreement with those obtained by the radiosonde, especially during night-time when the differences between the two instruments are almost negligible. The comparison of the sun photometer data with high-quality independent measurements from radiosondes and the radiometer shows that the absolute differences between V3 and the other two datasets are slightly higher compared with V2. However, V3 has a lower dependence from the TPW and the internal sensor temperature, indicating a better performance of the retrieving algorithm. The calculated one-sigma uncertainty for V3 as estimated, from the comparison with the radiosondes, is about 10&thinsp;%, which is in accordance with previous studies for the estimation of uncertainty for V2. This uncertainty is further reduced to about 6&thinsp;% when AERONET V3 is compared with the collocated microwave radiometer. To our knowledge, this is the first in-depth analysis of the V3 TPW, and although the findings presented here are for a specific site, we believe that they are representative of other mid-latitude continental stations.</p

Automatic pollen classification and segmentation using U-nets and synthetic Data.

Pollen allergies have become one of the most wide-spread afflictions that impact quality of life. This has made the need for automatic pollen detection, classification and monitoring a very important topic. This paper introduces a new public annotated image data-set of pollen with almost 45 thousand samples obtained from an automatic instrument. In this work we apply some of the best performing convolutional neural networks architectures on the task of pollen classification as well as some fully convolutional networks optimized for image segmentation on complex microscope images. We obtain an F1 scores of 0.95 on the new data-set when the best trained model is used as a fully convolutional classifier and a class mean Intersection over Union (IoU) of 0.88 when used as an object detector

Incidental findings in CT imaging of coronary artery bypass grafts: results from a Canadian multicenter prospective cohort

Abstract Objective To assess the prevalence and clinical significance of incidental findings identified during computed tomography imaging of coronary artery bypass grafts. Results This prospective study includes 144 patients undergoing coronary graft patency assessment using computed tomography. Incidental findings were classified as significant if they were considered to need an immediate action or treatment, short-term work-up or follow-up, or minor. A total of 211 incidental findings were present in 109 (75.7%) patients. Seventy-one incidental findings (33.6%) were cardiac and 140 (66.4%) were extracardiac. Most common cardiac incidental findings were atrial dilatation [39 patients, 48 incidental findings (67.6%)] and aortic valve calcifications (7 patients, 9.9%). Among the 140 extracardiac incidental findings, the most common were lung nodules (51 patients, 54 nodules, 38.6%), and emphysema (21 patients, 15%). Thirty-six (25.7%) extracardiac incidental findings were significant and notably, 23 (63.9%) were lung nodules. Follow-up was recommended in 37 cases, among which all patients with significant lung nodules (23 patients, 62.2%). In conclusion, most common computed tomography incidental findings in patients with coronary grafts were lung nodules and emphysema

Assessment of the total precipitable water from a sun photometer, microwave radiometer and radiosondes at a continental site in southeastern Europe

In this study, we discuss the differences in the total precipitable water (TPW), retrieved from a Cimel sun photometer operating at a continental site in southeast Europe, between version 3 (V3) and version 2 (V2) of the AErosol RObotic NETwork (AERONET) algorithms. In addition, we evaluate the performance of the two algorithms comparing their product with the TPW obtained from a collocated microwave radiometer and nearby radiosondes during the period 2007-2017. The TPW from all three instruments was highly correlated, showing the same annual cycle, with lower values during winter and higher values during summer. The sun photometer and the microwave radiometer depict the same daily cycle, with some discrepancies during early morning and late afternoon due to the effect of solar zenith angle on the measurements of the photometer. The TPW from V3 of the AERONET algorithm has small differences compared with V2, mostly related to the use of the new laboratory-based temperature coefficients used in V3. The microwave radiometer measurements are in good agreement with those obtained by the radiosonde, especially during night-time when the differences between the two instruments are almost negligible. The comparison of the sun photometer data with high-quality independent measurements from radiosondes and the radiometer shows that the absolute differences between V3 and the other two datasets are slightly higher compared with V2. However, V3 has a lower dependence from the TPW and the internal sensor temperature, indicating a better performance of the retrieving algorithm. The calculated one-sigma uncertainty for V3 as estimated, from the comparison with the radiosondes, is about 10 %, which is in accordance with previous studies for the estimation of uncertainty for V2. This uncertainty is further reduced to about 6 % when AERONET V3 is compared with the collocated microwave radiometer. To our knowledge, this is the first in-depth analysis of the V3 TPW, and although the findings presented here are for a specific site, we believe that they are representative of other mid-latitude continental stations

<em>Alternaria</em> spore exposure in Bavaria, Germany, measured using artificial intelligence algorithms in a network of BAA500 automatic pollen monitors.

Although Alternaria spores are well-known allergenic fungal spores, automatic bioaerosol recognition systems have not been trained to recognize these particles until now. Here we report the development of a new algorithm able to classify Alternaria spores with BAA500 automatic bioaerosol monitors. The best validation score was obtained when the model was trained on both data from the original dataset and artificially generated images, with a validation unweighted mean Intersection over Union (IoU), also called Jaccard Index, of 0.95. Data augmentation techniques were applied to the training set. While some particles were not recognized (false negatives), false positives were few. The results correlated well with manual counts (mean of four Hirst-type traps), with R2 = 0.78. Counts from BAA500 were 1.92 times lower than with Hirst-type traps. The algorithm was then used to re-analyze the historical automatic pollen monitoring network (ePIN) dataset (2018–2022), which lacked Alternaria spore counts. Re-analysis of past data showed that Alternaria spore exposure in Bavaria was very variable, with the highest counts in the North (Marktheidenfeld, 154 m a.s.l.), and the lowest values close to the mountains in the South (Garmisch-Partenkirchen, 735 m a.s.l.). This approach shows that in our network future algorithms can be run on past datasets. Over time, the use of different algorithms could lead to misinterpretations as stemming from climate change or other phenological causes. Our approach enables consistent, homogeneous treatment of long-term series, thus preventing variability in particle counts owing to changes in the algorithms