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951.
经皮射频消融髓核成形术治疗椎间盘源性腰痛 总被引:7,自引:2,他引:5
目的探讨经皮射频消融髓核成形术治疗椎间盘源性腰痛的疗效、优缺点及其并发症的防治。方法对47例椎间盘源性腰痛患者采用ArthroCare2000行射频消融髓核成形术。结果随访4~36个月,平均19个月。依据VAS评分系统评定,有效率为97%,VAS降低53%(P<0.05),无严重的并发症发生。结论经皮射频消融髓核成形术治疗椎间盘源性腰痛方法简单,有效率高,并发症少。 相似文献
952.
目的 探讨虚拟现实(virtual reality,VR)情景互动训练应用在养老院阿尔茨海默病(Alzheimer's disease,AD)患者康复治疗中的效果.方法 将56例养老院AD患者随机分为观察组和对照组,各28例.对照组给予养老院常规养老护理服务和健康宣教,观察组在对照组的基础上给予VR情景互动训练进行干预... 相似文献
953.
Background:To explore the effects of type 2 diabetes mellitus (T2DM) on osteoarthritis (OA), 12 bone tissue samples were obtained surgically from the human total knee arthroplasty patients and analyzed by quantitative proteomics.Methods:Based on patient clinical histories, patient samples were assigned to diabetes mellitus osteoarthritis (DMOA) and OA groups. A data-independent acquisition method for data collection was used with proteomic data analysis to assess intergroup proteomic differences. Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis were used to further find the correlation between T2DM and OA.Results:GO functional analysis found 153 differentially expressed proteins between DMOA and OA groups, of which 92 differentially expressed proteins were significantly up-regulated and 61 were significantly down-regulated. Kyoto Encyclopedia of Genes and Genome pathway analysis found 180 pathways, including 9 pathways significantly enriched. Further data analysis revealed that 6 signaling pathways were closely associated with T2DM and OA.Conclusion:OA and DMOA onset and progression were closely related to synthesis and metabolism of extracellular matrix components (e.g., fibronectin, decorin, etc.). The effects of T2DM on OA occur though 2 major ways of oxidative stress and low-grade chronic inflammation, involving in 2 inhibited signaling pathways and 4 activated signaling pathways. 相似文献
954.
Tara Dahn Patrick T.Fok Hana Wiemer Daniel J.Dutton Valancy Cole David Lewis Tong Liu Keith R. Brunt Robert Hanlon Jacqueline Fraser Chris Vaillancourt Paul Atkinson 《世界急诊医学杂志(英文)》2023,14(1):62-64
<正>Multiple studies have reported decreased emergency department(ED) patient volumes during the coronavirus disease(COVID-19) pandemic,[1-6] including areas most affected by the virus.[7]Most existing studies have investigated general trends in ED presentations and have not examined the impact of COVID-19 on different types of EDs, specific ED patient groups, or illness presentations. 相似文献
955.
956.
Yingqiang Liu Mengzhen Lai Shan Li Yanan Wang Fang Feng Tao Zhang Linjiang Tong Mengge Zhang Hao Chen Yi Chen Peiran Song Yan Li Gang Bai Yi Ning Haotian Tang Yan Fang Yi Chen Xiaoyun Lu Meiyu Geng Ke Ding Ker Yu Hua Xie Jian Ding 《Cancer science》2022,113(2):709
With the wide clinical use of the third‐generation epidermal growth factor receptor (EGFR) inhibitor osimertinib for the treatment of EGFR‐mutated non–small cell lung cancer (NSCLC), acquired resistance caused by EGFR C797S tertiary mutation has become a concern. Therefore, fourth‐generation EGFR inhibitors that could overcome this mutation have gained increasing attention in recent years. Here, we identified LS‐106 as a novel EGFR inhibitor against C797S mutation and evaluated its antitumor activity both in vitro and in vivo. In cell‐free assay, LS‐106 potently inhibited the kinase activities of EGFR19del/T790M/C797S and EGFRL858R/T790M/C797S with IC50 values of 2.4 nmol/L and 3.1 nmol/L, respectively, which was more potent than osimertinib. Meanwhile, LS‐106 exhibited comparable kinase inhibitory effect to osimertinib on EGFRL858R/T790M and wild‐type EGFR. Results from cellular experiments demonstrated that LS‐106 potently blocked the phosphorylation of EGFR C797S triple mutations in the constructed BaF3 cells that highly expressed EGFR19del/T790M/C797S or EGFRL858R/T790M/C797S, and thus inhibited the proliferation of these cells. We also constructed tumor cells harboring EGFR19del/T790M/C797S (named PC‐9‐OR cells) using the CRISPR/Cas9 system and found that LS‐106 markedly suppressed the activation of EGFR19del/T790M/C797S and the proliferation of PC‐9‐OR cells. Moreover, cells harboring EGFR19del/T790M/C797S underwent remarkable apoptosis upon LS‐106 treatment. In vivo experiments further demonstrated that oral administration of LS‐106 caused significant tumor regression in a PC‐9‐OR xenograft model, with a tumor growth inhibition rate (TGI) of 83.5% and 136.6% at doses of 30 and 60 mg/kg, respectively. Taken together, we identified LS‐106 as a novel fourth‐generation EGFR inhibitor against C797S mutation and confirmed its preclinical antitumor effects in C797S–triple‐mutant tumor models. 相似文献
957.
目的观察水莲风亏方对盆腔炎性疾病后遗症患者的临床疗效。方法将70例盆腔炎性疾病后遗症患者随机分为试验组和对照组,各35例。试验组给予水莲风亏方加减治疗,对照组给予妇科千金片治疗,疗程均为8周。结果治疗后,试验组组症状评分有效率为94.29%(33/35),明显高于对照组71.43%(25/35),差异有统计学意义(P<0.05)。试验组VAS疼痛评分、临床症状的变化情况、实验室指标(ESR、HCT)等均优于对照组(P<0.05);试验组不良反应例数低于对照组,但结果无统计学意义(P>0.05)。结论水莲风亏方能有效缓解盆腔炎患者疼痛,减少炎症反应,下调红细胞沉降率(ESR)、红细胞压积(HCT)等血液流变学指标,效果显著。 相似文献
958.
Colorectal cancer is one of the common malignant tumors in China.It poses a serious threat to the national health of China.For advanced colorectal cancer, the main goal of treatment is to prolong survival and improve quality of life.It complements other advantages, showing good therapeutic results.However, how to grasp the timing of integrated Chinese and Western Medicine for the treatment of advanced colorectal cancer and use the integrated Chinese and Western Medicine treatment methods flexibly contains profound therapeutic art.Prof.YANG Yu-fei is an authoritative expert in the field of integrated Chinese and Western medicine for colorectal cancer.She is good at accurately grasping the timing of treatment of integrated Chinese and Western Medicine, and flexibly adjusts the treatment strategy according to the specific conditions.In this paper, we shared Professor YANG Yu-fei's strategy for treating advanced colorectal cancer with emphasis on integrated Chinese and Western Medicine and attached a typical case, with a view to provide reference for the treatment of advanced colorectal cancer with integrated Chinese and Western Medicine. 相似文献
959.
960.
Leonardo Fernandino Jia-Qing Tong Lisa L. Conant Colin J. Humphries Jeffrey R. Binder 《Proceedings of the National Academy of Sciences of the United States of America》2022,119(6)
The nature of the representational code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. We assessed the extent to which different representational systems contribute to the instantiation of lexical concepts in high-level, heteromodal cortical areas previously associated with semantic cognition. We found that lexical semantic information can be reliably decoded from a wide range of heteromodal cortical areas in the frontal, parietal, and temporal cortex. In most of these areas, we found a striking advantage for experience-based representational structures (i.e., encoding information about sensory-motor, affective, and other features of phenomenal experience), with little evidence for independent taxonomic or distributional organization. These results were found independently for object and event concepts. Our findings indicate that concept representations in the heteromodal cortex are based, at least in part, on experiential information. They also reveal that, in most heteromodal areas, event concepts have more heterogeneous representations (i.e., they are more easily decodable) than object concepts and that other areas beyond the traditional “semantic hubs” contribute to semantic cognition, particularly the posterior cingulate gyrus and the precuneus.The capacity for conceptual knowledge is arguably one of the most defining properties of human cognition, and yet it is still unclear how concepts are represented in the brain. Recent developments in functional neuroimaging and computational linguistics have sparked renewed interest in elucidating the information structures and neural circuits underlying concept representation (1–5). Attempts to characterize the representational code for concepts typically involve information structures based on three qualitatively distinct types of information, namely, taxonomic, experiential, and distributional information. As the term implies, a taxonomic information system relies on category membership and intercategory relations. Our tendency to organize objects, events, and experiences into discrete categories has led most authors—dating back at least to Plato (6)—to take taxonomic structure as the central property of conceptual knowledge (7). The taxonomy for concepts is traditionally seen as a hierarchically structured network, with basic-level categories (e.g., “apple,” “orange”) grouped into superordinate categories (e.g., “fruit,” “food”) and subdivided into subordinate categories (e.g., “Gala apple,” “tangerine”) (8). A prominent account in cognitive science maintains that such categories are represented in the mind/brain as purely symbolic entities, whose semantic content and usefulness derive primarily from how they relate to each other (9, 10). Such representations are seen as qualitatively distinct from the sensory-motor processes through which we interact with the world, much like the distinction between software and hardware in digital computers.An experiential representational system, on the other hand, encodes information about the experiences that led to the formation of particular concepts. It is motivated by a view, often referred to as embodied, grounded, or situated semantics, in which concepts arise primarily from generalization over particular experiences, as information originating from the various modality-specific systems (e.g., visual, auditory, tactile, motor, affective) is combined and re-encoded into progressively more schematic representations that are stored in memory. Since, in this view, there is a degree of continuity between conceptual and modality-specific systems, concept representations are thought to reflect the structure of the perceptual, affective, and motor processes involved in those experiences (11–14).Finally, distributional information pertains to statistical patterns of co-occurrence between lexical concepts (i.e., concepts that are widely shared within a population and denoted by a single word) in natural language usage. As is now widely appreciated, these co-occurrence patterns encode a substantial amount of information about word meaning (15–17). Although word co-occurrence patterns primarily encode contextual associations, such as those connecting the words “cow,” “barn,” and “farmer,” semantic similarity information is indirectly encoded since words with similar meanings tend to appear in similar contexts (e.g., “cow” and “horse,” “pencil” and “pen”). This has led some authors to propose that concepts may be represented in the brain, at least in part, in terms of distributional information (15, 18).Whether, and to what extent, each of these types of information plays a role in the neural representation of conceptual knowledge is a topic of intense research and debate. A large body of evidence has emerged from behavioral studies, functional neuroimaging experiments, and neuropsychological assessments of patients with semantic deficits, with results typically interpreted in terms of taxonomic (19–24), experiential (13, 25–34), or distributional (2, 3, 5, 35, 36) accounts. However, the extent to which each of these representational systems plays a role in the neural representation of conceptual knowledge remains controversial (23, 37, 38), in part, because their representations of common lexical concepts are strongly intercorrelated. Patterns of word co-occurrence in natural language are driven in part by taxonomic and experiential similarities between the concepts to which they refer, and the taxonomy of natural categories is systematically related to the experiential attributes of the exemplars (39–41). Consequently, the empirical evidence currently available is unable to discriminate between these representational systems.Several computational models of concept representation have been proposed based on these structures. While earlier models relied heavily on hierarchical taxonomic structure (42, 43), more recent proposals have emphasized the role of experiential and/or distributional information (34, 44–46). The model by Chen and colleagues (45), for example, showed that graded taxonomic structure can emerge from the statistical coherent covariation found across experiences and exemplars without explicitly coding such taxonomic information per se. Other models propose that concepts may be formed through the combination of experiential and distributional information (44, 46), suggesting a dual representational code akin to Paivio’s dual coding theory (47).We investigated the relative contribution of each representational system by deriving quantitative predictions from each system for the similarity structure of a large set of concepts and then using representational similarity analysis (RSA) with high-resolution functional MRI (fMRI) to evaluate those predictions. Unlike the more typical cognitive subtraction technique, RSA focuses on the information structure of the pattern of neural responses to a set of stimuli (48). For a given stimulus set (e.g., words), RSA assesses how well the representational similarity structure predicted by a model matches the neural similarity structure observed from fMRI activation patterns (Fig. 1). This allowed us to directly compare, in quantitative terms, predictions derived from the three representational systems.Open in a separate windowFig. 1.Representational similarity analysis. (A) An fMRI activation map was generated for each concept presented in the study, and the activation across voxels was reshaped as a vector. (B) The neural RDM for the stimulus set was generated by computing the dissimilarity between these vectors (1 − correlation) for every pair of concepts. (C) A model-based RDM was computed from each model, and the similarity between each model’s RDM and the neural RDM was evaluated via Spearman correlation. (D) Anatomically defined ROIs. The dashed line indicates the boundary where temporal lobe ROIs were split into anterior and posterior portions (see main text for acronyms). (E) Cortical areas included in the functionally defined semantic network ROI (49). 相似文献