This paper presents a novel method for the automatic segmentation of coronary arteries in X-ray angiograms, based on multiscale analysis and neural networks. The multiscale analysis is performed by using Gaussian filters in the spatial domain and Gabor filters in the frequency domain, which are used as inputs by a multilayer perceptron (MLP) for the enhancement of vessel-like structures. The optimal design of the MLP is selected following a statistical comparative analysis, using a training set of 100 angiograms, and the area under the ROC curve ( $A_z$ ) for assessment of the detection performance. The detection results of the proposed method are compared with eleven state-of-the-art blood vessel enhancement methods, obtaining the highest performance of $A_z=0.9775$ , with a test set of 30 angiograms. The database of 130 X-ray coronary angiograms has been outlined by a specialist and approved by a medical ethics committee. On the other hand, the vessel extraction technique was selected from fourteen binary classification algorithms applied to the multiscale filter response. Finally, the proposed segmentation method is compared with twelve state-of-the-art vessel segmentation methods in terms of six binary evaluation metrics, where the proposed method provided the most accurate coronary arteries segmentation with a classification rate of $0.9698$ and Dice coefficient of $0.6857$ , using the test set of angiograms. In addition to the experimental results, the performance in the detection and segmentation steps of the proposed method have also shown that it can be highly suitable for systems that perform computer-aided diagnosis in X-ray imaging.

Objective: This study aimed to evaluate the psychological impacts of COVID-19 prevention measures, such as social isolation, on a Mexican sample. Methods: We conducted an online sociodemographic and Impact of Event Scale-Revised (IES-R) survey during the second phase of the COVID-19 outbreak in Mexico to evaluate the presence of psychological distress, signs of post-traumatic stress, and to identify the groups at highest risk in the sample. Results: Prevalence of psychological distress at moderate or severe levels in the sample were as follows: 943 (22%) intrusive thoughts, 933 (22.3%) avoidance, and 515 (12.2%) hyperarousal. Furthermore, we found the symptoms of clinically significant post-traumatic stress in 1160 (27.7%) of the participants. The variables positively correlated with higher psychological distress were as follows: age (younger), sex (female), employment (employed), relationship status (single), in social isolation, number of days in isolation, the number of people in the household (3– 5), and a perception of a high risk of contracting COVID-19, change in routine, engaging in less activity, and loss of income. Conclusion: During phase 2 of the COVID-19 outbreak in Mexico, we observed the presence of psychological distress and post-traumatic stress symptoms in over a quarter of the population. This investigation may guide mental health interventions and policies towards the groups that are most vulnerable to the impacts of the social and lifestyle changes taking place in Mexico due to COVID-19.

Background: Increased telomere shortening has been demonstrated in several diseases including type 2 diabetes. However, it is not known whether telomere length changes during the course of type 2 diabetes. Objective: To determine telomere length at different stages of type 2 diabetes, including early and late stages. Methods: A total of 93 males with type 2 diabetes and 10 years or more since original diagnosis; 96 males with less than one year of diagnosis; 98 age matched healthy males. Telomere length was estimated by means of real-time polymerase chain reaction. Fasting venous blood samples were obtained for measurement of lipid peroxidation and inflammation markers.Results: We found a greater telomere shortening in group (A) with type 2 diabetes of 10 years or more since original diagnosis, compared with the control group (C) of healthy males (5.4 vs 9.6 Kb) (p = 0.04) and with group B (5.4 vs 8.7kb) (p = 0.05). With regard to inflammatory markers TNF-α, malondialdehyde peroxidation and adiponectin we found significant differences. Conclusion: Telomere shortening increases with the duration of diabetes. The time of exhibition suggests in parallel that the progressive increase of inflammation and/or oxidative stress plays a direct role in telomere shortening.

COVID‐19 related social isolation measures and school closures have likely increased students' stress levels. In our study, we assess the level of psychological distress and psychosocial factors among students in Mexico at the beginning of the pandemic. We conducted a cross‐sectional exploratory study with 848 participants, the majority undergraduate or postgraduate (79.7%). Participants completed the Impact of Event Scale‐Revised to measure emotions, and a COVID‐19 questionnaire. We conducted a logistic regression analysis to find variables associated with stress: 36% (n = 309) had elevated stress, 31.4% (n = 266) anxiety, and 18.2% (n = 154) sadness often or all the time. Those who identified as women and reported a reduction in their incomes also reported a higher stress level. Stress was positively correlated with anxiety, anger, sadness, days in isolation, and hours watching TV daily; and negatively correlated with relaxation and happiness. The variable most strongly correlated with stress was a high perception of infection risk. Our findings will inform mental health strategies for students who are at higher risk of stress due to the COVID‐19 pandemic response.