Późna zatorowość płucna u pacjenta z łagodnym przebiegiem COVID-19. Związek z reinfekcją i prowadzonym leczeniem

W tekście opisano przypadek 49-letniego pacjenta bez czynników ryzyka żylnej choroby zakrzepowo-zatorowej hospitalizowanego z zatorowością płucną po przebytej chorobie koronawirusowej 2019 (COVID-19) leczonej przez krótki okres amantadyną. Skuteczne leczenie zachowawcze z regresją zmian zakrzepowych nastąpiło po trzech miesiącach. W pracy zawarto rozważania na temat potencjalnych przyczyn wystąpienia zatorowości i ewentualnych zaleceń dotyczących profilaktyki

Late pulmonary embolism in a patient with mild COVID-19. An association with reinfection and the instituted treatment

A case is presented of a 49-year-old patient without risk factors for venous thromboembolism hospitalized with pulmonary embolism after COVID-19 infection, previously treated with amantadine for a short period. The patient underwent successful medical treatment with resolution of embolic material at 3 months. The authors discuss potential causes of embolism and possible recommendations for prevention.A case of a 49-year-old patient without risk factors for venous thromboembolism hospitalized with pulmonary embolism after Covid-19 infection, treated with amantadine for a short period. Successful conservative treatment with regression of thrombosis after three months. Consideration of potential causes of embolism and possible recommendations for prevention

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Obrzęk płuc jako pierwszy objaw kardiomiopatii połogowej. Diagnostyka za pomocą rezonansu magnetycznego

We present a case of a 23 year-old pregnant woman, who underwent a cesarian section due to the risk of eclampsia. The patient developed pulmonary oedema due to severe left ventricular impairement. After the standard treatment and a short period of bromocriptine, the symptoms of the oedema subsided. In order to differentiate between the primary dilated cardiomyopathy and postpartum cardiomyopathy (PPC), the magnetic resonance imaging (MRI) examination was carried out twice at a 3-month interval, and confirmed the diagnosis of PPC. This case report underlines the role of MRI in detection of PPC. Kardiol Pol 2011; 69, 9: 942–94

Deep Convolutional Symmetric Encoder—Decoder Neural Networks to Predict Students’ Visual Attention

Prediction of visual attention is a new and challenging subject, and to the best of our knowledge, there are not many pieces of research devoted to the anticipation of students’ cognition when solving tests. The aim of this paper is to propose, implement, and evaluate a machine learning method that is capable of predicting saliency maps of students who participate in a learning task in the form of quizzes based on quiz questionnaire images. Our proposal utilizes several deep encoder–decoder symmetric schemas which are trained on a large set of saliency maps generated with eye tracking technology. Eye tracking data were acquired from students, who solved various tasks in the sciences and natural sciences (computer science, mathematics, physics, and biology). The proposed deep convolutional encoder–decoder network is capable of producing accurate predictions of students’ visual attention when solving quizzes. Our evaluation showed that predictions are moderately positively correlated with actual data with a coefficient of 0.547 ± 0.109. It achieved better results in terms of correlation with real saliency maps than state-of-the-art methods. Visual analyses of the saliency maps obtained also correspond with our experience and expectations in this field. Both source codes and data from our research can be downloaded in order to reproduce our results

Deep Convolutional Symmetric Encoder—Decoder Neural Networks to Predict Students’ Visual Attention

Prediction of visual attention is a new and challenging subject, and to the best of our knowledge, there are not many pieces of research devoted to the anticipation of students’ cognition when solving tests. The aim of this paper is to propose, implement, and evaluate a machine learning method that is capable of predicting saliency maps of students who participate in a learning task in the form of quizzes based on quiz questionnaire images. Our proposal utilizes several deep encoder–decoder symmetric schemas which are trained on a large set of saliency maps generated with eye tracking technology. Eye tracking data were acquired from students, who solved various tasks in the sciences and natural sciences (computer science, mathematics, physics, and biology). The proposed deep convolutional encoder–decoder network is capable of producing accurate predictions of students’ visual attention when solving quizzes. Our evaluation showed that predictions are moderately positively correlated with actual data with a coefficient of 0.547 ± 0.109. It achieved better results in terms of correlation with real saliency maps than state-of-the-art methods. Visual analyses of the saliency maps obtained also correspond with our experience and expectations in this field. Both source codes and data from our research can be downloaded in order to reproduce our results

Low-Level Light Therapy Protects Red Blood Cells Against Oxidative Stress and Hemolysis During Extracorporeal Circulation

Aim: An activation of non-specific inflammatory response, coagulation disorder, and blood morphotic elements damage are the main side effects of the extracorporeal circulation (ECC). Red-to-near-infrared radiation (R/NIR) is thought to be capable of stabilizing red blood cell (RBC) membrane through increasing its resistance to destructive factors. We focused on the development of a method using low-level light therapy (LLLT) in the spectral range of R/NIR which could reduce blood trauma caused by the heart-lung machine during surgery.Methods: R/NIR emitter was adjusted in terms of geometry and optics to ECC circuit. The method of extracorporeal blood photobiomodulation was tested during in vivo experiments in an animal, porcine model (1 h of ECC plus 23 h of animal observation). A total of 24 sows weighing 90–100 kg were divided into two equal groups: control one and LLLT. Blood samples were taken during the experiment to determine changes in blood morphology [RBC and white blood cell (WBC) counts, hemoglobin (Hgb)], indicators of hemolysis [plasma-free hemoglobin (PFHgb), serum bilirubin concentration, serum lactate dehydrogenase (LDH) activity], and oxidative stress markers [thiobarbituric acid reactive substances (TBARS) concentration, total antioxidant capacity (TAC)].Results: In the control group, a rapid systemic decrease in WBC count during ECC was accompanied by a significant increase in RBC membrane lipids peroxidation, while in the LLLT group the number of WBC and TBARS concentration both remained relatively constant, indicating limitation of the inflammatory process. These results were consistent with the change in the hemolysis markers like PFHgb, LDH, and serum bilirubin concentration, which were significantly reduced in LLLT group. No differences in TAC, RBC count, and Hgb concentration were detected.Conclusion: We presented the applicability of the LLLT with R/NIR radiation to blood trauma reduction during ECC

Application of FTIR-ATR Spectroscopy to Determine the Extent of Lipid Peroxidation in Plasma during Haemodialysis

During a haemodialysis (HD), because of the contact of blood with the surface of the dialyser, the immune system becomes activated and reactive oxygen species (ROS) are released into plasma. Particularly exposed to the ROS are lipids and proteins contained in plasma, which undergo peroxidation. The main breakdown product of oxidized lipids is the malondialdehyde (MDA). A common method for measuring the concentration of MDA is a thiobarbituric acid reactive substances (TBARS) method. Despite the formation of MDA in plasma during HD, its concentration decreases because it is removed from the blood in the dialyser. Therefore, this research proposes the Fourier Transform Infrared Attenuated Total Reflectance (FTIR-ATR) spectroscopy, which enables determination of primary peroxidation products. We examined the influence of the amount of hydrogen peroxide added to lipid suspension that was earlier extracted from plasma specimen on lipid peroxidation with use of TBARS and FTIR-ATR methods. Linear correlation between these methods was shown. The proposed method was effective during the evaluation of changes in the extent of lipid peroxidation in plasma during a haemodialysis in sheep. A measurement using the FTIR-ATR showed an increase in plasma lipid peroxidation after 15 and 240 minutes of treatment, while the TBARS concentration was respectively lower