Perilipin regulates the thermogenic actions of norepinephrine in brown adipose tissue

In response to cold, norepinephrine (NE)-induced triacylglycerol hydrolysis (lipolysis) in adipocytes of brown adipose tissue (BAT) provides fatty acid substrates to mitochondria for heat generation (adaptive thermogenesis). NE-induced lipolysis is mediated by protein kinase A (PKA)-dependent phosphorylation of perilipin, a lipid droplet-associated protein that is the major regulator of lipolysis. We investigated the role of perilipin PKA phosphorylation in BAT NE-stimulated thermogenesis using a novel mouse model in which a mutant form of perilipin, lacking all six PKA phosphorylation sites, is expressed in adipocytes of perilipin knockout (Peri KO) mice. Here, we show that despite a normal mitochondrial respiratory capacity, NE-induced lipolysis is abrogated in the interscapular brown adipose tissue (IBAT) of these mice. This lipolytic constraint is accompanied by a dramatic blunting (∼70%) of the in vivo thermal response to NE. Thus, in the presence of perilipin, PKA-mediated perilipin phosphorylation is essential for NE-dependent lipolysis and full adaptive thermogenesis in BAT. In IBAT of Peri KO mice, increased basal lipolysis attributable to the absence of perilipin is sufficient to support a rapid NE-stimulated temperature increase (∼3.0°C) comparable to that in wild-type mice. This observation suggests that one or more NE-dependent mechanism downstream of perilipin phosphorylation is required to initiate and/or sustain the IBAT thermal response

Разработка алгоритма кластеризации кардиокомплексов с посткоррекцией для задач длительного мониторирования электрокардиосигнала

Introduction. The most common method for diagnosing cardiovascular diseases is the method of ECG monitoring. In order to facilitate the analysis of the obtained monitorograms, special software solutions for automated ECG processing are required. One possible approach is the use of algorithms for automated ECG processing. Such algorithms perform  clustering of cardiac signals by dividing the ECG into complexes of similar cardiac signals. The most representative complexes obtained by statistical averaging are subject to further analysis.Aim. Development of an algorithm for automated ECG processing,  which performs clustering of cardiac signals by dividing the ECG into complexes of similar cardiac signals.Materials and methods. Experimental testing of the developed software was carried out using patient records provided by the Pavlov First State Medical University of St  Petersburg. The software module was implemented in the MatLab environment.Results. An algorithm for clustering cardiac signals with post-correction for the tasks of long-term ECG monitoring and a software module on its basis were proposed.Conclusion.  The presence of a small number of reference cardiac signal complexes, obtained through ECG processing using the proposed algorithm, allows physicians to optimize the process of ECG analysis. The as- obtained information serves as a basis for assessing dynamic changes in the shape and other parameters of cardiac signals for both a particular patient and groups of patients. The paper considers the effect of synchronization errors of clustered cardiac signals on the shape of the averaged cardiac complex. The classical solution to the deconvolution problem leads to significant errors in finding an estimate of the true form of a cardiac signal complex. On the basis of analytical calculations, expressions were obtained for the correction of clustered cardiac signals. Such correction was shown to reduce clusterization errors associated with desynchronization, which creates a basis for investigating the fine structure of ECG signals.Введение.  Наиболее распространенным методом диагностики сердечно- сосудистых заболеваний является длительное  мониторирование  электрокардиосигнала  (ЭКС) .  Для  облегчения  анализа  полученных  мониторограмм врачам- кардиологам необходимы специальные алгоритмы и программные средства автоматизированной обработки  ЭКС. Одним из  таких средств  является алгоритм автоматизированной обработки  ЭКС, выполня ющий  кластеризацию кардиокомплексов  (КК) , разделяя  ЭКС  на группы максимально близких по форме  КК. Дальнейшему анализу подвергаются только эталонные КК, полученные статистическим  усреднением  КК  в каждой группе.Цель  работы.  Разработка  алгоритма  автоматизированной  кластеризации  КК  ЭКС,  разделяющего  электрокардиосигнал на группы максимально близких по форме КК.Материалы и методы.  Экспериментальная апробация  алгоритма и  программного  модуля  проводилась на  базе обезличенных суточных записей ЭКС пациентов Первого Санкт- Петербургского государственного медицинского университета им.   акад.   И. П. Павлова Минздрава России.  Программный модуль был реализован в среде MatLab.Результаты.  Разработан  алгоритм  сортировки  КК  с  посткоррекцией  для  длительного  мониторирования  ЭКС; представлен программный модуль, реализованный на базе  разработанного алгоритма. Рассмотрено  влияние ошибок синхронизации  КК  при их накоплении  на форму усредняемого КК. Классическое решение задачи деконволюции приводит к значительным ошибкам при нахождении оценки "истинной" формы КК. На основании аналитических расчетов получены выражения для коррекции накапливаемого КК.  Показано, что в результате коррекции можно  нивелировать ошибки накопления, связанные с рассинхронизацией.Заключение.  Наличие  небольшого  количества  эталонных  КК,  полученных  в  результате  обработки  ЭКС с помощью  предложенного  алгоритма,  позволяет  врачу-исследователю  значительно  сократить  время, затрачиваемое  на  анализ  ЭКС,  и  является  основой  исследования  динамических  изменений  формы  и иных параметров КК  как для конкретного пациента, так и для их группы. Полученные результаты  позволяют создать основу для решения задач, направленных на исследование "тонкой" структуры ЭКС

Impact of renal impairment on atrial fibrillation: ESC-EHRA EORP-AF Long-Term General Registry

Background: Atrial fibrillation (AF) and renal impairment share a bidirectional relationship with important pathophysiological interactions. We evaluated the impact of renal impairment in a contemporary cohort of patients with AF. Methods: We utilised the ESC-EHRA EORP-AF Long-Term General Registry. Outcomes were analysed according to renal function by CKD-EPI equation. The primary endpoint was a composite of thromboembolism, major bleeding, acute coronary syndrome and all-cause death. Secondary endpoints were each of these separately including ischaemic stroke, haemorrhagic event, intracranial haemorrhage, cardiovascular death and hospital admission. Results: A total of 9306 patients were included. The distribution of patients with no, mild, moderate and severe renal impairment at baseline were 16.9%, 49.3%, 30% and 3.8%, respectively. AF patients with impaired renal function were older, more likely to be females, had worse cardiac imaging parameters and multiple comorbidities. Among patients with an indication for anticoagulation, prescription of these agents was reduced in those with severe renal impairment, p <.001. Over 24 months, impaired renal function was associated with significantly greater incidence of the primary composite outcome and all secondary outcomes. Multivariable Cox regression analysis demonstrated an inverse relationship between eGFR and the primary outcome (HR 1.07 [95% CI, 1.01–1.14] per 10 ml/min/1.73 m2 decrease), that was most notable in patients with eGFR <30 ml/min/1.73 m2 (HR 2.21 [95% CI, 1.23–3.99] compared to eGFR ≥90 ml/min/1.73 m2). Conclusion: A significant proportion of patients with AF suffer from concomitant renal impairment which impacts their overall management. Furthermore, renal impairment is an independent predictor of major adverse events including thromboembolism, major bleeding, acute coronary syndrome and all-cause death in patients with AF

Clinical complexity and impact of the ABC (Atrial fibrillation Better Care) pathway in patients with atrial fibrillation: a report from the ESC-EHRA EURObservational Research Programme in AF General Long-Term Registry

Background: Clinical complexity is increasingly prevalent among patients with atrial fibrillation (AF). The ‘Atrial fibrillation Better Care’ (ABC) pathway approach has been proposed to streamline a more holistic and integrated approach to AF care; however, there are limited data on its usefulness among clinically complex patients. We aim to determine the impact of ABC pathway in a contemporary cohort of clinically complex AF patients. Methods: From the ESC-EHRA EORP-AF General Long-Term Registry, we analysed clinically complex AF patients, defined as the presence of frailty, multimorbidity and/or polypharmacy. A K-medoids cluster analysis was performed to identify different groups of clinical complexity. The impact of an ABC-adherent approach on major outcomes was analysed through Cox-regression analyses and delay of event (DoE) analyses. Results: Among 9966 AF patients included, 8289 (83.1%) were clinically complex. Adherence to the ABC pathway in the clinically complex group reduced the risk of all-cause death (adjusted HR [aHR]: 0.72, 95%CI 0.58–0.91), major adverse cardiovascular events (MACEs; aHR: 0.68, 95%CI 0.52–0.87) and composite outcome (aHR: 0.70, 95%CI: 0.58–0.85). Adherence to the ABC pathway was associated with a significant reduction in the risk of death (aHR: 0.74, 95%CI 0.56–0.98) and composite outcome (aHR: 0.76, 95%CI 0.60–0.96) also in the high-complexity cluster; similar trends were observed for MACEs. In DoE analyses, an ABC-adherent approach resulted in significant gains in event-free survival for all the outcomes investigated in clinically complex patients. Based on absolute risk reduction at 1 year of follow-up, the number needed to treat for ABC pathway adherence was 24 for all-cause death, 31 for MACEs and 20 for the composite outcome. Conclusions: An ABC-adherent approach reduces the risk of major outcomes in clinically complex AF patients. Ensuring adherence to the ABC pathway is essential to improve clinical outcomes among clinically complex AF patients

Impact of clinical phenotypes on management and outcomes in European atrial fibrillation patients: a report from the ESC-EHRA EURObservational Research Programme in AF (EORP-AF) General Long-Term Registry

Background: Epidemiological studies in atrial fibrillation (AF) illustrate that clinical complexity increase the risk of major adverse outcomes. We aimed to describe European AF patients\u2019 clinical phenotypes and analyse the differential clinical course. Methods: We performed a hierarchical cluster analysis based on Ward\u2019s Method and Squared Euclidean Distance using 22 clinical binary variables, identifying the optimal number of clusters. We investigated differences in clinical management, use of healthcare resources and outcomes in a cohort of European AF patients from a Europe-wide observational registry. Results: A total of 9363 were available for this analysis. We identified three clusters: Cluster 1 (n = 3634; 38.8%) characterized by older patients and prevalent non-cardiac comorbidities; Cluster 2 (n = 2774; 29.6%) characterized by younger patients with low prevalence of comorbidities; Cluster 3 (n = 2955;31.6%) characterized by patients\u2019 prevalent cardiovascular risk factors/comorbidities. Over a mean follow-up of 22.5 months, Cluster 3 had the highest rate of cardiovascular events, all-cause death, and the composite outcome (combining the previous two) compared to Cluster 1 and Cluster 2 (all P <.001). An adjusted Cox regression showed that compared to Cluster 2, Cluster 3 (hazard ratio (HR) 2.87, 95% confidence interval (CI) 2.27\u20133.62; HR 3.42, 95%CI 2.72\u20134.31; HR 2.79, 95%CI 2.32\u20133.35), and Cluster 1 (HR 1.88, 95%CI 1.48\u20132.38; HR 2.50, 95%CI 1.98\u20133.15; HR 2.09, 95%CI 1.74\u20132.51) reported a higher risk for the three outcomes respectively. Conclusions: In European AF patients, three main clusters were identified, differentiated by differential presence of comorbidities. Both non-cardiac and cardiac comorbidities clusters were found to be associated with an increased risk of major adverse outcomes

Бактериальные инфекции у пациентов детского и подросткового возраста после трансплантации аллогенных гемопоэтических стволовых клеток: этиология, структура, факторы риска

155 children and adolescents who had been diagnosed oncohematological diseases and had undergone allogeneic hemapoetic stem cell transplantation were examined. In post-transplant period 80% of patients developed different bacterial complications. Main risk factors of bacterial infections were acute leukemia (73%), acute «graft versus host disease» (61%), severe infectious complications before HSCT (30%), cytomegaloviral reactivation (51%). Main causative agents were Kl. pneumoniae (15%), Escherichia coli (8%), Enterobacter sp. (7%), Pseudomonas sp. (6,5%), Enterococcus sp. (16,5%), S.еpidermidis (13,5%). Most frequent involved sites are urinary tract (30,6%), lungs (22,5%) and bacteriemia (38,7%). Rise in ciprofloxacin resistans among Entorobactri, aerobic and Gram-positive cocci. General survival rate of patients with bacterial complications was 36,3% (p<0,001). Number of infectious episodes and their severity were statistically significant (both p<0,001) deteriorating factor for general surviral rate.Обследовано 155 пациентов детского и подросткового возраста со злокачественными заболеваниями системы крови после трансплантации аллогенных гемопоэтических стволовых клеток (алло-ТГСК). У 80% больных на разных этапах после алло-ТГСК развились бактериальные осложнения различной степени тяжести. Основными факторами риска бактериальных инфекций были диагноз острого лейкоза (73%), развитие острой «реакции трансплантат против хозяина» (61%), тяжелые инфекционные осложнения в анамнезе до трансплантации (30%), реактивация цитомегаловирусной инфекции (51%). Основные возбудители: Kl. pneumoniae (15%), Escherichia coli (8%), Enterobacter sp. (7%), Pseudomonas sp. (6,5%), Enterococcus sp. (16,5%), S. еpidermidis (13,5%). Наиболее часто возникает поражение мочевыводящих путей (30,6%), легких (22,5%) и бактериемия (38,7%). Отмечен рост резистентности к ципрофлоксацину среди энтеробактерий, аэробной и грам-положительной кокковой флоры. Общая выживаемость больных с развившимися бактериальными осложнениями составила 36,3% (p<0,001). Статистически значимо ухудшает показатели общей выживаемости больных с бактериальными инфекциями количество инфекционных эпизодов (p<0,001) и их тяжесть (p<0,001)

Transsphenoidal endoscopic appro ach in the treat ment of spontaneous cerebrospinal fluid (CSF) leak

Introduction. Spontaneous nasal liquorrhea is a pathological condition associated with defect between nasal cavity and intracranial structures that lead to the expiration of the CSF from the nasal cavity.The objective is to evaluate the effectiveness of endoscopic endonasal approach in the CSF leak treatment.Material and methods. For the period from 2008 to 2018, 38 patients with spontaneous nasal liquorrhea were examined and treated in Pavlov First Saint Petersburg State Medical University, the clinic of neurosurgery of Kirov Medical Institute and Almazov National Medical Research Centre. All patients underwent plastic surgery of the CSF fistula by endoscopic endonasal aproach.Results. Only in 4 cases, there was a large defect, the failure of the closure of which required repeated surgical intervention in 1–2 weeks after the initial operation.Conclusion. The use of autologous tissues (muscle or fat autograft) is the method of choice for repeated surgical plastics of the cerebrospinal fluid fistula or in a large size defect (more than 5 mm)