對社會養老模式的思考與探索

摘要 根据我国社会老龄化进程加快，社会养老服务需求迅速增长的趋势，提出构建社会养老模式，类比以人为中心的社会养老服务支援系统；结合养老服务的实践，探索社会养老服务支援系统的作用，方法和路子，为高龄病残老人提供优质服务，对提高老年人幸福指数，推动积极老龄化，健康老龄化进程，加快老龄事业科学发展，实现有中国特色的积极老龄化战略思想，具有重要现实意义

Intrathoracic Endotracheal Metastasis from Nasopharyngeal Carcinoma: A First Case Report and Review of the Literature

Intrathoracic endotracheal metastasis from a very distant site is extremely rare. We report the first case of such a disease in a 68-year-old man with nasopharyngeal carcinoma who presented with a cough and hemoptysis 34 months after finishing radiotherapy. Prior to tracheal metastasis, he developed a solitary metastasis in the lung and underwent chemotherapy followed by radiotherapy. Computed tomography showed the presence of an enlarged lymph node in the para-aortic arch. Fiberoptic bronchoscopy revealed an endotracheal tumor 1 cm above the carina. Histological and immunohistochemical analyses confirmed its nasopharyngeal origin. He was treated with conventional radiotherapy and three-dimensional conformal radiotherapy; complete tumor remission was achieved. He died of nonmalignant disease with no signs of tumor recurrence 2 years after treatment completion. Radiotherapy may be an appropriate management approach to achieve long-term tumor control for this disease

Dynamic placement of the linker histone H1 associated with nucleosome arrangement and gene transcription in early Drosophila embryonic development

The linker histone H1 is critical to maintenance of higher-order chromatin structures and to gene expression regulation. However, H1 dynamics and its functions in embryonic development remain unresolved. Here, we profiled gene expression, nucleosome positions, and H1 locations in early Drosophila embryos. The results show that H1 binding is positively correlated with the stability of beads-on-a-string nucleosome organization likely through stabilizing nucleosome positioning and maintaining nucleosome spacing. Strikingly, nucleosomes with H1 placement deviating to the left or the right relative to the dyad shift to the left or the right, respectively, during early Drosophila embryonic development. H1 occupancy on genic nucleosomes is inversely correlated with nucleosome distance to the transcription start sites. This inverse correlation reduces as gene transcription levels decrease. Additionally, H1 occupancy is lower at the 5\u27 border of genic nucleosomes than that at the 3\u27 border. This asymmetrical pattern of H1 occupancy on genic nucleosomes diminishes as gene transcription levels decrease. These findings shed new lights into how H1 placement dynamics correlates with nucleosome positioning and gene transcription during early Drosophila embryonic development

Differential analysis of chromatin accessibility and histone modifications for predicting mouse developmental enhancers

Enhancers are distal cis-regulatory elements that modulate gene expression. They are depleted of nucleosomes and enriched in specific histone modifications; thus, calling DNase-seq and histone mark ChIP-seq peaks can predict enhancers. We evaluated nine peak-calling algorithms for predicting enhancers validated by transgenic mouse assays. DNase and H3K27ac peaks were consistently more predictive than H3K4me1/2/3 and H3K9ac peaks. DFilter and Hotspot2 were the best DNase peak callers, while HOMER, MUSIC, MACS2, DFilter and F-seq were the best H3K27ac peak callers. We observed that the differential DNase or H3K27ac signals between two distant tissues increased the area under the precision-recall curve (PR-AUC) of DNase peaks by 17.5-166.7% and that of H3K27ac peaks by 7.1-22.2%. We further improved this differential signal method using multiple contrast tissues. Evaluated using a blind test, the differential H3K27ac signal method substantially improved PR-AUC from 0.48 to 0.75 for predicting heart enhancers. We further validated our approach using postnatal retina and cerebral cortex enhancers identified by massively parallel reporter assays, and observed improvements for both tissues. In summary, we compared nine peak callers and devised a superior method for predicting tissue-specific mouse developmental enhancers by reranking the called peaks

A Comprehensive Survey on Deep Graph Representation Learning

Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been widely studied in a range of fields, including machine learning and data mining. Classic graph embedding methods follow the basic idea that the embedding vectors of interconnected nodes in the graph can still maintain a relatively close distance, thereby preserving the structural information between the nodes in the graph. However, this is sub-optimal due to: (i) traditional methods have limited model capacity which limits the learning performance; (ii) existing techniques typically rely on unsupervised learning strategies and fail to couple with the latest learning paradigms; (iii) representation learning and downstream tasks are dependent on each other which should be jointly enhanced. With the remarkable success of deep learning, deep graph representation learning has shown great potential and advantages over shallow (traditional) methods, there exist a large number of deep graph representation learning techniques have been proposed in the past decade, especially graph neural networks. In this survey, we conduct a comprehensive survey on current deep graph representation learning algorithms by proposing a new taxonomy of existing state-of-the-art literature. Specifically, we systematically summarize the essential components of graph representation learning and categorize existing approaches by the ways of graph neural network architectures and the most recent advanced learning paradigms. Moreover, this survey also provides the practical and promising applications of deep graph representation learning. Last but not least, we state new perspectives and suggest challenging directions which deserve further investigations in the future

A Systematic Investigation of Structure/Function Requirements for The Apolipoprotein A-I/Lecithin Cholesterol Acyltransferase Interaction Loop of High-density Lipoprotein

The interaction of lecithin-cholesterol acyltransferase (LCAT) with apolipoprotein A-I (apoA-I) plays a critical role in high-density lipoprotein (HDL) maturation. We previously identified a highly solvent-exposed apoA-I loop domain (Leu159–Leu170) in nascent HDL, the so-called “solar flare” (SF) region, and proposed that it serves as an LCAT docking site (Wu, Z., Wagner, M. A., Zheng, L., Parks, J. S., Shy, J. M., 3rd, Smith, J. D., Gogonea, V., and Hazen, S. L. (2007) Nat. Struct. Mol. Biol. 14, 861–868). The stability and role of the SF domain of apoA-I in supporting HDL binding and activation of LCAT are debated. Here we show by site-directed mutagenesis that multiple residues within the SF region (Pro165, Tyr166, Ser167, and Asp168) of apoA-I are critical for both LCAT binding to HDL and LCAT catalytic efficiency. The critical role for possible hydrogen bond interaction at apoA-I Tyr166 was further supported using reconstituted HDL generated from apoA-I mutants (Tyr166 → Glu or Asn), which showed preservation in both LCAT binding affinity and catalytic efficiency. Moreover, the in vivo functional significance of NO2-Tyr166-apoA-I, a specific post-translational modification on apoA-I that is abundant within human atherosclerotic plaque, was further investigated by using the recombinant protein generated from E. coli containing a mutated orthogonal tRNA synthetase/tRNACUA pair enabling site-specific insertion of the unnatural amino acid into apoA-I. NO2-Tyr166-apoA-I, after subcutaneous injection into hLCATTg/Tg, apoA-I−/− mice, showed impaired LCAT activation in vivo, with significant reduction in HDL cholesteryl ester formation. The present results thus identify multiple structural features within the solvent-exposed SF region of apoA-I of nascent HDL essential for optimal LCAT binding and catalytic efficiency

Prognostic and therapeutic significance of microbial cell-free DNA in plasma of people with acutely decompensated cirrhosis

BACKGROUND AND AIMS: Although the effect of bacterial infection on cirrhosis has been well-described, the effect of non-hepatotropic virus (NHV) infection is unknown. This study evaluated the genome fragments of circulating microorganisms using metagenomic next-generation sequencing (mNGS) in cirrhosis patients with acute decompensation (AD), focusing on NHVs and related the findings to clinical outcomes. METHODS: Plasma mNGS was performed in 129 cirrhosis patients with AD in study cohort. Ten healthy volunteers and 20, 39, and 81 patients with stable cirrhosis, severe sepsis and hematological malignancies, respectively, were enrolled as controls. Validation assays for human cytomegalovirus (CMV) reactivation in a validation cohort (n = 58) were performed and exploratory treatment instituted. RESULTS: In study cohort, 188 microorganisms were detected in 74.4% (96/129) patients, including viruses (58.0%), bacteria (34.1%), fungi (7.4%) and chlamydia (0.5%). Patients with AD had an NHV signature, and CMV was the most frequent NHV, which correlated with the clinical effect of empirical antibiotic treatment, progression to acute-on-chronic liver failure (ACLF), and 90-day mortality. The NHV signature in ACLF patients was similar to patients with sepsis and hematological malignancies. The treatable NHV, CMV was detected in 24.1% (14/58) patients in the validation cohort. Of the 14 cases with detectable CMV by mNGS, 9 were further validated by DNA RT-PCR or pp65 antigenemia testing. Three patients with CMV reactivation received ganciclovir therapy in exploratory manner with clinical resolutions. CONCLUSIONS: The results of this study suggests that NHVs may have a pathogenic role in complicating the course of AD. Further validation is needed to define whether this should be incorporated in the routine management of AD patients. IMPACT AND IMPLICATIONS: ●Cirrhosis patients with acute decompensation have a non-hepatotropic virus (NHV) signature, which is similar to that in sepsis and hematological malignancies patients. ●The detected viral signature had clinical correlates, including clinical efficacy of empirical antibiotic treatment, progression to acute-on-chronic liver failure and short-term mortality. ●The treatable NHV, CMV reactivation may be involved in the clinical outcomes of decompensated cirrhosis. ●Routine screening for NHVs, especially CMV, may be useful for the management of patients with acutely decompensated cirrhosis

A novel hybrid machine learning model for auxiliary diagnosing myocardial ischemia

IntroductionAccurate identification of the myocardial texture features of fat around the coronary artery on coronary computed tomography angiography (CCTA) images are crucial to improve clinical diagnostic efficiency of myocardial ischemia (MI). However, current coronary CT examination is difficult to recognize and segment the MI characteristics accurately during earlier period of inflammation.Materials and methodsWe proposed a random forest model to automatically segment myocardium and extract peripheral fat features. This hybrid machine learning (HML) model is integrated by CCTA images and clinical data. A total of 1,316 radiomics features were extracted from CCTA images. To further obtain the features that contribute the most to the diagnostic model, dimensionality reduction was applied to filter features to three: LNS, GFE, and WLGM. Moreover, statistical hypothesis tests were applied to improve the ability of discriminating and screening clinical features between the ischemic and non-ischemic groups.ResultsBy comparing the accuracy, recall, specificity and AUC of the three models, it can be found that HML had the best performance, with the value of 0.848, 0.762, 0.704 and 0.729.ConclusionIn sum, this study demonstrates that ML-based radiomics model showed good predictive value in MI, and offer an enhanced tool for predicting prognosis with greater accuracy

An atlas of DNA methylomes in porcine adipose and muscle tissues

It is evident that epigenetic factors, especially DNA methylation, have essential roles in obesity development. Here, using pig as a model, we investigate the systematic association between DNA methylation and obesity. We sample eight variant adipose and two distinct skeletal muscle tissues from three pig breeds living within comparable environments but displaying distinct fat level. We generate 1,381 Gb of sequence data from 180 methylated DNA immunoprecipitation libraries, and provide a genome-wide DNA methylation map as well as a gene expression map for adipose and muscle studies. The analysis shows global similarity and difference among breeds, sexes and anatomic locations, and identifies the differentially methylated regions. The differentially methylated regions in promoters are highly associated with obesity development via expression repression of both known obesity-related genes and novel genes. This comprehensive map provides a solid basis for exploring epigenetic mechanisms of adipose deposition and muscle growth