Nucleosomes in pancreatic cancer patients during radiochemotherapy

Nucleosomes appear spontaneously in elevated concentrations in the serum of patients with malignant diseases as well as during chemo- and radiotherapy. We analyzed whether their kinetics show typical characteristics during radiochemotherapy and enable an early estimation of therapy efficacy. We used the Cell Death Detection Elisaplus ( Roche Diagnostics) and investigated the course of nucleosomes in the serum of 32 patients with a local stage of pancreatic cancer who were treated with radiochemotherapy for several weeks. Ten of them received postsurgical therapy, 21 received primary therapy and 1 received therapy for local relapse. Blood was taken before the beginning of therapy, daily during the first week, once weekly during the following weeks and at the end of radiochemotherapy. The response to therapy was defined according to the kinetics of CA 19-9: a decrease of CA 19-9 650% after radiochemotherapy was considered as `remission'; an increase of >= 100% ( which was confirmed by two following values) was defined as `progression'. Patients with `stable disease' ranged intermediately. Most of the examined patients showed a decrease of the concentration of nucleosomes within 6 h after the first dose of radiation. Afterwards, nucleosome levels increased rapidly, reaching their maximum during the following days. Patients receiving postsurgery, primary or relapse therapies did not show significant differences in nucleosome values during the time of treatment. Single nucleosome values, measured at 6, 24 and 48 h after the application of therapy, could not discriminate significantly between patients with no progression and those with progression of disease. However, the area under the curve of the first 3 days, which integrated all variables of the initial therapeutic phase, showed a significant correlation with the progression-free interval ( p = 0.008). Our results indicate that the area under the curve of nucleosomes during the initial phase of radiochemotherapy could be valuable for the early prediction of the progression-free interval. Copyright (C) 2005 S. Karger AG, Basel

Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning

Background and purpose: The electrocardiogram (ECG) is frequently obtained in the work-up of COVID-19 patients. So far, no study has evaluated whether ECG-based machine learning models have added value to predict in-hospital mortality specifically in COVID-19 patients. / Methods: Using data from the CAPACITY-COVID registry, we studied 882 patients admitted with COVID-19 across seven hospitals in the Netherlands. Raw format 12-lead ECGs recorded within 72 h of admission were studied. With data from five hospitals (n = 634), three models were developed: (a) a logistic regression baseline model using age and sex, (b) a least absolute shrinkage and selection operator (LASSO) model using age, sex and human annotated ECG features, and (c) a pre-trained deep neural network (DNN) using age, sex and the raw ECG waveforms. Data from two hospitals (n = 248) was used for external validation. / Results: Performances for models a, b and c were comparable with an area under the receiver operating curve of 0.73 (95% confidence interval [CI] 0.65–0.79), 0.76 (95% CI 0.68–0.82) and 0.77 (95% CI 0.70–0.83) respectively. Predictors of mortality in the LASSO model were age, low QRS voltage, ST depression, premature atrial complexes, sex, increased ventricular rate, and right bundle branch block. / Conclusion: This study shows that the ECG-based prediction models could be helpful for the initial risk stratification of patients diagnosed with COVID-19, and that several ECG abnormalities are associated with in-hospital all-cause mortality of COVID-19 patients. Moreover, this proof-of-principle study shows that the use of pre-trained DNNs for ECG analysis does not underperform compared with time-consuming manual annotation of ECG features

Sex differences in cardiovascular complications and mortality in hospital patients with covid-19: registry based observational study

Objective To assess whether the risk of cardiovascular complications of covid-19 differ between the sexes and to determine whether any sex differences in risk are reduced in individuals with pre-existing cardiovascular disease. Design Registry based observational study. Setting 74 hospitals across 13 countries (eight European) participating in CAPACITY-COVID (Cardiac complicAtions in Patients With SARS Corona vIrus 2 regisTrY), from March 2020 to May 2021 Participants All adults (aged ≥18 years), predominantly European, admitted to hospital with highly suspected covid-19 disease or covid-19 disease confirmed by positive laboratory test results (n=11 167 patients). Main outcome measures Any cardiovascular complication during admission to hospital. Secondary outcomes were in-hospital mortality and individual cardiovascular complications with ≥20 events for each sex. Logistic regression was used to examine sex differences in the risk of cardiovascular outcomes, overall and grouped by pre-existing cardiovascular disease. Results Of 11 167 adults (median age 68 years, 40% female participants) included, 3423 (36% of whom were female participants) had pre-existing cardiovascular disease. In both sexes, the most common cardiovascular complications were supraventricular tachycardias (4% of female participants, 6% of male participants), pulmonary embolism (3% and 5%), and heart failure (decompensated or de novo) (2% in both sexes). After adjusting for age, ethnic group, pre-existing cardiovascular disease, and risk factors for cardiovascular disease, female individuals were less likely than male individuals to have a cardiovascular complication (odds ratio 0.72, 95% confidence interval 0.64 to 0.80) or die (0.65, 0.59 to 0.72). Differences between the sexes were not modified by pre-existing cardiovascular disease; for the primary outcome, the female-to-male ratio of the odds ratio in those without, compared with those with, pre-existing cardiovascular disease was 0.84 (0.67 to 1.07). Conclusions In patients admitted to hospital for covid-19, female participants were less likely than male participants to have a cardiovascular complication. The differences between the sexes could not be attributed to the lower prevalence of pre-existing cardiovascular disease in female individuals. The reasons for this advantage in female individuals requires further research

Extensive innate immune gene activation accompanies brain aging, increasing vulnerability to cognitive decline and neurodegeneration: a microarray study

BACKGROUND: This study undertakes a systematic and comprehensive analysis of brain gene expression profiles of immune/inflammation-related genes in aging and Alzheimer’s disease (AD). METHODS: In a well-powered microarray study of young (20 to 59 years), aged (60 to 99 years), and AD (74 to 95 years) cases, gene responses were assessed in the hippocampus, entorhinal cortex, superior frontal gyrus, and post-central gyrus. RESULTS: Several novel concepts emerge. First, immune/inflammation-related genes showed major changes in gene expression over the course of cognitively normal aging, with the extent of gene response far greater in aging than in AD. Of the 759 immune-related probesets interrogated on the microarray, approximately 40% were significantly altered in the SFG, PCG and HC with increasing age, with the majority upregulated (64 to 86%). In contrast, far fewer immune/inflammation genes were significantly changed in the transition to AD (approximately 6% of immune-related probesets), with gene responses primarily restricted to the SFG and HC. Second, relatively few significant changes in immune/inflammation genes were detected in the EC either in aging or AD, although many genes in the EC showed similar trends in responses as in the other brain regions. Third, immune/inflammation genes undergo gender-specific patterns of response in aging and AD, with the most pronounced differences emerging in aging. Finally, there was widespread upregulation of genes reflecting activation of microglia and perivascular macrophages in the aging brain, coupled with a downregulation of select factors (TOLLIP, fractalkine) that when present curtail microglial/macrophage activation. Notably, essentially all pathways of the innate immune system were upregulated in aging, including numerous complement components, genes involved in toll-like receptor signaling and inflammasome signaling, as well as genes coding for immunoglobulin (Fc) receptors and human leukocyte antigens I and II. CONCLUSIONS: Unexpectedly, the extent of innate immune gene upregulation in AD was modest relative to the robust response apparent in the aged brain, consistent with the emerging idea of a critical involvement of inflammation in the earliest stages, perhaps even in the preclinical stage, of AD. Ultimately, our data suggest that an important strategy to maintain cognitive health and resilience involves reducing chronic innate immune activation that should be initiated in late midlife

Paternal Allele of IGF2 Gene Haplotype CTG Is Associated With Fetal and Placental Growth in Japanese

http://journals.lww.com/pedresearch/pages/default.aspx This is a non-final version of an article published in final form in (Pediatric Research, 66(2), pp.135-139, 2009)IGF-II associates with feto-placental growth in rodent and human. determined three tag-single nucleotide polymorphisms (SNPs) to investigate haplotype frequency of IGF2 relative to size at birth in 134 healthy Japanese infants. In addition, a total of 276 healthy infants were investigated to determine whether common genetic variation of IGF2 might contribute to feto-placental growth Using haplotype analysis. Further, quantitative methylation analysis of the IGF2/HI9 wits performed using the MassARRAY Compact system. In the initial study,. the frequency of haplotype CTG front the paternal allele in small for date (SFD) infants was significantly higher than that in non-SFD infants (p = 0.03). In second Study, the CTG haplotype infants exhibited significantly lower birth length, weight. and placental weight Compared with non-CTG infants. Further, the number of infants less than - 1,5 SD (SD) birth weight in CTG haplotype was higher than those if non-CTG infants. There was no significant difference in the methylation status of HI9/IGF2 in the two haplotypes. In conclusion, inheriting the IGF2 CTG haplotype front I paternal allele results ill reduced feto-placental growth. but it is not associated with the methylation Status of IGF2/HI9. (Pediatr Res 66: 135-139, 2009

Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning

BACKGROUND AND PURPOSE: The electrocardiogram (ECG) is frequently obtained in the work-up of COVID-19 patients. So far, no study has evaluated whether ECG-based machine learning models have added value to predict in-hospital mortality specifically in COVID-19 patients. METHODS: Using data from the CAPACITY-COVID registry, we studied 882 patients admitted with COVID-19 across seven hospitals in the Netherlands. Raw format 12-lead ECGs recorded within 72 h of admission were studied. With data from five hospitals (n = 634), three models were developed: (a) a logistic regression baseline model using age and sex, (b) a least absolute shrinkage and selection operator (LASSO) model using age, sex and human annotated ECG features, and (c) a pre-trained deep neural network (DNN) using age, sex and the raw ECG waveforms. Data from two hospitals (n = 248) was used for external validation. RESULTS: Performances for models a, b and c were comparable with an area under the receiver operating curve of 0.73 (95% confidence interval [CI] 0.65–0.79), 0.76 (95% CI 0.68–0.82) and 0.77 (95% CI 0.70–0.83) respectively. Predictors of mortality in the LASSO model were age, low QRS voltage, ST depression, premature atrial complexes, sex, increased ventricular rate, and right bundle branch block. CONCLUSION: This study shows that the ECG-based prediction models could be helpful for the initial risk stratification of patients diagnosed with COVID-19, and that several ECG abnormalities are associated with in-hospital all-cause mortality of COVID-19 patients. Moreover, this proof-of-principle study shows that the use of pre-trained DNNs for ECG analysis does not underperform compared with time-consuming manual annotation of ECG features. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s12471-022-01670-2) contains supplementary material, which is available to authorized users