Pulmonary embolism and 3-month outcomes in 4036 patients with venous thromboembolism and chronic obstructive pulmonary disease: data from the RIETE registry

Background

Patients with chronic obstructive pulmonary disease (COPD) have a modified clinical presentation of venous thromboembolism (VTE) but also a worse prognosis than non-COPD patients with VTE. As it may induce therapeutic modifications, we evaluated the influence of the initial VTE presentation on the 3-month outcomes in COPD patients.

Methods

COPD patients included in the on-going world-wide RIETE Registry were studied. The rate of pulmonary embolism (PE), major bleeding and death during the first 3 months in COPD patients were compared according to their initial clinical presentation (acute PE or deep vein thrombosis (DVT)).

Results

Of the 4036 COPD patients included, 2452 (61%; 95% CI: 59.2-62.3) initially presented with PE. PE as the first VTE recurrence occurred in 116 patients, major bleeding in 101 patients and mortality in 443 patients (Fatal PE: first cause of death). Multivariate analysis confirmed that presenting with PE was associated with higher risk of VTE recurrence as PE (OR, 2.04; 95% CI: 1.11-3.72) and higher risk of fatal PE (OR, 7.77; 95% CI: 2.92-15.7).

Conclusions

COPD patients presenting with PE have an increased risk for PE recurrences and fatal PE compared with those presenting with DVT alone. More efficient therapy is needed in this subtype of patients.     

Theoretical Study On The Reaction Mechanism Of Gecl3ch2ch2cooh+h2o→gecl2ohch2ch2cooh+hcl

The mechanism and dynamical properties for the title reaction have been investigated theoretically. Three reaction pathways have been found. Geometries, vibrational frequencies, infra-red (IR) intensities and relative energies for various stationary points in the three reaction channels have been determined respectively. The corresponding rate constants at the B3LYP/6-31++G(2d,2p) level have been deduced over a wide temperature range of 200–2000 K by using canonical variational transition state theory with small curvature tunnelling effect. Solvent effects are taken into account via the Onsager model of self-constant reaction field at the same level of theory. This preliminary study shows that the complex formation is favoured by the use of water solvent.     

Influence of segmental and extra-segmental conditioning stimuli on cortical potentials evoked by painful electrical stimulation

This study evaluated the effects of two different types of segmental/extra-segmental conditioning stimuli (tonic muscle pain and non-painful vibration) on the subjective experience (perceived pain intensity) and on the cortical evoked potentials to standardized test stimuli (cutaneous electrical stimuli). Twelve subjects participated in two separate sessions to investigate the effects of tonic muscle pain or cutaneous vibration on experimental test stimuli. The experimental protocol contained a baseline registration (test stimuli only), a registration with the test stimuli in combination with the conditioning stimuli, followed by a registration with the test stimuli only. In addition, the effects of the conditioning stimuli were examined at two anatomically separated locations (segmental and extra-segmental). Compared with the test stimulus alone, the perceived pain intensity and peak-to-peak amplitudes of the evoked potentials were unchanged in the presence of non-painful conditioning stimuli at either location. In contrast, a significant decrease of the perceived pain intensity and peak-to-peak amplitudes was found in the presence of painful conditioning stimuli at the extra-segmental sites. Moreover, the topographic maps of the 32-channel recordings suggested that the distribution of the scalp evoked potentials was almost symmetrical around the vertex Cz in the baseline registration. The evoked potentials were generally decreased during hypertonic saline infusion at the extra-segmental sites, but the distribution of the topographic maps did not appear to change. Vibration has previously been shown to inhibit pain, but in the present study the perceived intensity of phasic painful electrical stimuli was unchanged. The reduced perceived pain intensity and the smaller peak-to-peak amplitude of the evoked potential in the presence of extra-segmental conditioning pain are in accordance with the concept of diffuse noxious inhibitory control.     

From robustness to resilience: A network Price identity approach

We model a closed-loop network of agents distributed among subnetworks and study the sustainability of network structures in presence of random perturbations. The model outcomes show that the stability of compartmentalized networks built on uniform operators depends on perturbations on between-subnetwork coupling, while the stability of networks built on mutation operators depends on their assimilation capacity. Through the study of eigenvalues of the Laplacian, we succeed in measuring the degree of network robustness and resilience. Our results also permit to situate the Price theorem, both in its standard and expanded forms, in the context of network evolutionary variational identity.     

关节置换术后抗凝药物预防深静脉血栓及相关并发症的临床研究进展

抗凝药物有助于预防全髋关节置换术和全膝关节置换术后深静脉血栓形成,临床上最常使用的传统抗凝药物如低分子肝素、华法林等可以起到很好的预防效果。目前有一类新的口服抗凝药物已经用于临床,为关节置换术后患者带来了一种更方便、安全和有效预防血栓的治疗选择。本篇综述主要针对传统抗凝药物低分子肝素及维生素K拮抗剂,直接凝血酶抑制剂达比加群,以及选择性Xa因子抑制剂利伐沙班和阿哌沙班,对迄今为止传统抗凝药物在全髋关节置换术和全膝关节置换术患者中的临床使用经验、优缺点、以及新型口服抗凝药物最新临床用药进展进行综述,为关节置换术后患者预防深静脉血栓提供用药参考。     

血栓弹力图预测下肢骨折围手术期深静脉血栓的应用研究

目的:探讨血栓弹力图(TEG)预测下肢骨折围手术期深静脉血栓的临床价值。方法:选择在我院进行体检的健康志愿献血者作为对照组(Ⅰ),同时选择82例在我院进行骨科手术的下肢骨折患者作为实验组(Ⅱ)。分别在骨折后第2天、手术当天、术后第3天、术后第7天和术后第10天进行血栓弹力图检测,比较实验组(Ⅱ)与对照组(Ⅰ)TEG各参数差异,并对所有数据进行相关性分析。结果:实验组(Ⅱ)82例研究对象中有63例(76.83%)于术后一周内出现高凝状态。与对照组(Ⅰ)比较,实验组(Ⅱ)骨折第2天、手术当天、术后第3天、术后第7天和术后第10天R、K缩短,Angle角、MA、CI值均延长。与手术当日比较,实验组(Ⅱ)术后第3天、术后第7天R和K明显缩短,Angle角、MA、CI值均明显延长(P0.05),与术后第3天、术后第7天比较,术后第10天R、K延长,Angle角、MA、CI值有缩短趋势。结论:血栓弹力图能及时准确监测下肢骨折患者凝血状态变化情况,及时预测下肢深静脉血栓(LDVT)发生风险,为抗凝药物的合理使用提供参考依据。     

A Hybrid Deep Learning Model for Predicting Molecular Subtypes of Human Breast Cancer Using Multimodal Data

BackgroundThe prediction of breast cancer subtypes plays a key role in the diagnosis and prognosis of breast cancer. In recent years, deep learning (DL) has shown good performance in the intelligent prediction of breast cancer subtypes. However, most of the traditional DL models use single modality data, which can just extract a few features, so it cannot establish a stable relationship between patient characteristics and breast cancer subtypes.DatasetWe used the TCGA-BRCA dataset as a sample set for molecular subtype prediction of breast cancer. It is a public dataset that can be obtained through the following link: https://portal.gdc.cancer.gov/projects/TCGA-BRCAMethodsIn this paper, a Hybrid DL model based on the multimodal data is proposed. We combine the patient's gene modality data with image modality data to construct a multimodal fusion framework. According to the different forms and states, we set up feature extraction networks respectively, and then we fuse the output of the two feature networks based on the idea of weighted linear aggregation. Finally, the fused features are used to predict breast cancer subtypes. In particular, we use the principal component analysis to reduce the dimensionality of high-dimensional data of gene modality and filter the data of image modality. Besides, we also improve the traditional feature extraction network to make it show better performance.ResultsThe results show that compared with the traditional DL model, the Hybrid DL model proposed in this paper is more accurate and efficient in predicting breast cancer subtypes. Our model achieved a prediction accuracy of 88.07% in 10 times of 10-fold cross-validation. We did a separate AUC test for each subtype, and the average AUC value obtained was 0.9427. In terms of subtype prediction accuracy, our model is about 7.45% higher than the previous average.     

Phylogeny and physiology of candidate phylum BRC1 inferred from the first complete metagenome-assembled genome obtained from deep subsurface aquifer

Candidate bacterial phylum BRC1 has been identified in a broad range of mostly organic-rich oxic and anoxic environments through molecular analysis of microbial communities. None of the members of BRC1 have been cultivated and only a few draft genome sequences have been obtained from metagenomes or as a result of single-cell sequencing. We have reconstructed complete genome of BRC1 bacterium, BY40, from metagenome of the microbial community of a deep subsurface thermal aquifer in the Tomsk Region of the Western Siberia, Russia, and used it for metabolic reconstruction and comparison with existing genomic data. Analysis of 3.3 Mb genome of BY40 bacterium revealed numerous glycoside hydrolases that could enable utilization of carbohydrates, including enzymes of chitin-degradation pathway. The bacterium lacks flagellar machinery but the twitching motility is encoded. The reconstructed central metabolism revealed pathways enabling the fermentation of organic substrates, as well as their complete oxidation through aerobic and anaerobic respiration. Phylogenetic analysis using BY40 genome supported the phylum level classification of BRC1 lineage. Based on phylogenetic and genomic analyses, the novel bacterium is proposed to be classified as Candidatus Sumerlaea chitinivorans, within a candidate phylum Sumerlaeota.     

Long-term Changes in Macrozoobenthos of the Gdańsk Deep

The paper presents an analysis of the bottom fauna occurrence in the central part of the Gdańsk Deep in the past four decades. In 53% of the samples there were not any bottom invertebrates at all and they periodically disappeared in every decade. At the beginning of the study period, Priapuloidea, Bivalvia, Crustacea and Polychaeta were present in the bottom fauna communities, while only the two latter groups occurred towards the end of the period and the hemipelagic polychaete Harmothoe sarsi was often noted as the only species of the macrozoobenthos.