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"Liu, Liang"
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Barriers and enablers to implementing clinical practice guidelines in primary care: an overview of systematic reviews
ObjectivesTo identify the barriers and enablers to implementing clinical practice guidelines (CPGs) recommendations in primary care and to provide recommendations that could facilitate the uptake of CPGs recommendations.DesignAn overview of systematic reviews.Data sourcesNine electronic databases (PubMed, Cochrane Library, CINAHL, MEDLINE, PsycINFO, Web of Science, Journals @Ovid Full Text, EMBase, JBI) and three online data sources for guidelines (Turning Research Into Practice, the National Guideline Clearinghouse and the National Institute for Health and Care Excellence) were searched until May 2021.Eligibility criteriaSystematic reviews, meta-analyses or other types of systematic synthesis of quantitative, qualitative or mixed-methods studies on the topic of barriers and/or enablers for CPGs implementation in primary care were included.Data extraction and synthesisTwo authors independently screened the studies and extracted the data using a predesigned data extraction form. The methodological quality of the included studies was appraised by using the JBI Critical Appraisal Checklist for Systematic Reviews and Research Syntheses. Content analysis was used to synthesise the data.ResultsTwelve systematic reviews were included. The methodological quality of the included reviews was generally robust. Six categories of barriers and enablers were identified, which include (1) political, social and culture factors, (2) institutional environment and resources factors, (3) guideline itself related factors, (4) healthcare provider-related factors, (5) patient-related factors and (6) behavioural regulation-related factors. The most commonly reported barriers within the above-mentioned categories were suboptimal healthcare networks and interprofessional communication pathways, time constraints, poor applicability of CPGs in real-world practice, lack of knowledge and skills, poor motivations and adherence, and inadequate reinforcement (eg, remuneration). Presence of technical support (‘institutional environment and resources factors’), and timely education and training for both primary care providers (PCPs) (‘healthcare provider-related factors’) and patients (‘patient-related factors’) were the frequently reported enablers.ConclusionPolicy-driven strategies should be developed to motivate different levels of implementation activities, which include optimising resources allocations, promoting integrated care models, establishing well-coordinated multidisciplinary networks, increasing technical support, encouraging PCPs and patients’ engagement in guideline development, standardising the reporting of guidelines, increasing education and training, and stimulating PCPs and patients’ motivations. All the activities should be conducted by fully considering the social, cultural and community contexts to ensure the success and sustainability of CPGs implementation.
Journal Article
Aerobic exercise regulates FGF21 and NLRP3 inflammasome-mediated pyroptosis and inhibits atherosclerosis in mice
Fibroblast growth factor 21 (FGF21), a known risk factor for atherosclerosis, is readily regulated by exercise, and it can inhibit NOD-like receptor protein 3 (NLRP3)-mediated pyroptosis. However, it is not clear whether aerobic exercise inhibits atherosclerosis via these pathways. Eight-week-old apolipoprotein E-deficient ( ApoE -/- ) mice on a high-fat diet were randomly divided into 1-h post-exercise (EX-1h), 24-h post-exercise (EX-24h), and sedentary (SED) groups. C57BL/6J wild-type mice fed normal chow served as controls (WT group). Mice in the EX-1h and EX-24h groups were subjected to treadmill exercise training for 12 weeks. Aerobic exercise reduced body weight; blood glucose, lipid, and inflammation levels; and aortic plaque area proportion. Aerobic exercise increased the sensitivity of FGF21 by upregulating the expression of the downstream receptor adiponectin (ApN); the serum FGF21 level after exercise increased initially, and then decreased. Aerobic exercise downregulated the expression of NLRP3 inflammasome-mediated pyroptosis-related markers in the aorta, and FGF21 may participate in the above process. Meanwhile, the liver may be the tissue source of serum FGF21 during aerobic exercise. In conclusion, aerobic exercise may inhibit atherogenesis by regulating FGF21 and NLRP3 inflammasome-mediated pyroptosis. Our study provides new information on the atherosclerosis-preventing mechanism of aerobic exercise.
Journal Article
Damage to dopaminergic neurons by oxidative stress in Parkinson's disease (Review)
Oxidative stress is increasingly recognized as a central event contributing to the degeneration of dopaminergic neurons in the pathogenesis of Parkinson's disease (PD). Although reactive oxygen species (ROS) production is implicated as a causative factor in PD, the cellular and molecular mechanisms linking oxidative stress with dopaminergic neuron death are complex and not well characterized. The primary insults cause the greatest production of ROS, which contributes to oxidative damage by attacking all macromolecules, including lipids, proteins and nucleic acids, leading to defects in their physiological function. Consequently, the defects in these macromolecules result in mitochondrial dysfunction and neuroinflammation, which subsequently enhance the production of ROS and ultimately neuronal damage. The interaction between these various mechanisms forms a positive feedback loop that drives the progressive loss of dopaminergic neurons in PD, and oxidative stress-mediated neuron damage appears to serve a central role in the neurodegenerative process. Thus, understanding the cellular and molecular mechanisms by which oxidative stress contributes to the loss of dopaminergic neurons may provide a promising therapeutic approach in PD treatment.
Journal Article
FastEmbed: Predicting vulnerability exploitation possibility based on ensemble machine learning algorithm
In recent years, the number of vulnerabilities discovered and publicly disclosed has shown a sharp upward trend. However, the value of exploitation of vulnerabilities varies for attackers, considering that only a small fraction of vulnerabilities are exploited. Therefore, the realization of quick exclusion of the non-exploitable vulnerabilities and optimal patch prioritization on limited resources has become imperative for organizations. Recent works using machine learning techniques predict exploited vulnerabilities by extracting features from open-source intelligence (OSINT). However, in the face of explosive growth of vulnerability information, there is room for improvement in the application of past methods to multiple threat intelligence. A more general method is needed to deal with various threat intelligence sources. Moreover, in previous methods, traditional text processing methods were used to deal with vulnerability related descriptions, which only grasped the static statistical characteristics but ignored the context and the meaning of the words of the text. To address these challenges, we propose an exploit prediction model, which is based on a combination of fastText and LightGBM algorithm and called fastEmbed. We replicate key portions of the state-of-the-art work of exploit prediction and use them as benchmark models. Our model outperforms the baseline model whether in terms of the generalization ability or the prediction ability without temporal intermixing with an average overall improvement of 6.283% by learning the embedding of vulnerability-related text on extremely imbalanced data sets. Besides, in terms of predicting the exploits in the wild, our model also outperforms the baseline model with an F1 measure of 0.586 on the minority class (33.577% improvement over the work using features from darkweb/deepweb). The results demonstrate that the model can improve the ability to describe the exploitability of vulnerabilities and predict exploits in the wild effectively.
Journal Article
Hypoxia-induced LncRNA-BX111 promotes metastasis and progression of pancreatic cancer through regulating ZEB1 transcription
The contribution of long noncoding RNAs (lncRNAs) to pancreatic cancer progression and the regulatory mechanisms of their expression are attractive areas. In the present study, the overexpression of lncRNA-BX111887 (BX111) in pancreatic cancer tissues was detected by microarray and further validated in a cohort of pancreatic cancer tissues. We further demonstrated that knockdown or overexpression of BX111 dramatically repressed or enhanced proliferation and invasion of pancreatic cancer cells. Mechanically, BX111 activated transcription of ZEB1, a key regulator for epithelia-mesenchymal transition (EMT), via recruiting transcriptional factor Y-box protein (YB1) to its promoter region. Moreover, we revealed that BX111 transcription was induced by hypoxia-inducible factor (HIF-1α) in response to hypoxia. In addition, BX111 contributed to the hypoxia-induced EMT of pancreatic cells by regulating expression of ZEB1 and its downstream proteins E-cadherin and MMP2. Coincidence with in vitro results, BX111 depletion effectively inhibited growth and metastasis of xenograft tumor in vivo. The clinical samples of pancreatic cancer further confirmed a positive association between BX111 and ZEB1. Moreover, high BX111 expression was correlated with late TNM stage, lymphatic invasion and distant metastasis, as well as short overall survival time in patients. Taken together, our findings implicate a hypoxia-induced lncRNA contributes to metastasis and progression of pancreatic cancer, and suggest BX111 might be applied as a potential biomarker and therapeutic target for pancreatic cancer.
Journal Article