763 research outputs found

    Intervenção com atividades educativas sobre diabetes mellitus na Estratégia Saúde da faamília no município de Patrocínio do Muriaé

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    O diabetes mellitus (DM) é um grupo de doenças metabólicas que se caracteriza por hiperglicemia e está relacionado a múltiplas complicações, disfunções e insuficiência de vários órgãos, principalmente olhos, rins, nervos, cérebro, coração e vasos sanguíneos. A natureza crônica do DM, a gravidade das complicações e os meios necessários para controlá-la, tornam esta doença muito onerosa, não apenas para os indivíduos afetados e suas famílias, mas também para o sistema de saúde. Pesquisadores esclarecem a relação da incidência da doença com a baixa escolaridade. Este trabalho se justifica pela alta prevalência de diabetes na população de Patrocínio do Muriaé, assim como de pacientes com complicações da doença, que muitas vezes por falta de conhecimento, recebem o diagnóstico tardiamente ou não seguem o tratamento adequadamente. O objetivo do projeto é aumentar o conhecimento da população a respeito do diabetes mellitus e consequentemente aumentar a adesão ao tratamento e diminuir as complicações tardias do diabetes, assim como aumentar o diagnóstico oportuno com aumento da cobertura de consultas e exames diagnósticos na população assistida pela equipe da Estratégia Saúde da Família do Posto de Saúde da Família (PSF) Maria Aparecida de Lima Campos, no Município de Patrocínio do Muriaé-MG. A metodologia selecionada foi a utilização do planejamento estratégico situacional para a análise situacional em saúde com definição do diabetes como doença prevalente. Houve a proposta de confecção e distribuição de panfletos informativos, ações educativas e a aplicação de entrevista a população alvo para avaliar o aprendizado a respeito do tema

    The contribution of female community health volunteers (FCHVs) to maternity care in Nepal: a qualitative study.

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    BACKGROUND: In resource-poor settings, the provision of basic maternity care within health centres is often a challenge. Despite the difficulties, Nepal reduced its maternal mortality ratio by 80% from 850 to an estimated 170 per 100,000 live births between 1991 and 2011 to achieve Millennium Development Goal Five. One group that has been credited for this is community health workers, known as Female Community Health Volunteers (FCHVs), who form an integral part of the government healthcare system. This qualitative study explores the role of FCHVs in maternal healthcare provision in two regions: the Hill and Terai. METHODS: Between May 2014 and September 2014, 20 FCHVs, 11 health workers and 26 service users were purposefully selected and interviewed using semi-structured topic guides. In addition, four focus group discussions were held with 19 FCHVs. Data were analysed using thematic analysis. RESULTS: All study participants acknowledged the contribution of FCHVs in maternity care. All FCHVs reported that they shared key health messages through regularly held mothers' group meetings and referred women for health checks. The main difference between the two study regions was the support available to FCHVs from the local health centres. With regular training and access to medical supplies, FCHVs in the hill villages reported activities such as assisting with childbirth, distributing medicines and administering pregnancy tests. They also reported use of innovative approaches to educate mothers. Such activities were not reported in Terai. In both regions, a lack of monetary incentives was reported as a major challenge for already overburdened volunteers followed by a lack of education for FCHVs. CONCLUSIONS: Our findings suggest that the role of FCHVs varies according to the context in which they work. FCHVs, supported by government health centres with emphasis on the use of local approaches, have the potential to deliver basic maternity care and promote health-seeking behaviour so that serious delays in receiving healthcare can be minimised. However, FCHVs need to be reimbursed and provided with educational training to ensure that they can work effectively. The study underlines the relevance of community health workers in resource-poor settings

    THz-PCR Based on Resonant Coupling between Middle Infrared and DNA Carbonyl Vibrations

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    The carbonyl groups of deoxyribonucleotide can resonantly couple with 53 THz middle infrared, which can highly transmit water without ionization-based damage to DNA molecules. Herein, we predict that vibrational coupling with THz irradiation could lower down the hybridization landscape of nucleic acids and thus affect DNA replication. Using polymerase chain reaction (PCR) as a measure, we found that THz shining can reduce the denature temperature of DNA duplexes by about 3 °C, which allows one to conduct PCR at lower temperature, facilitating long-time amplification reaction without losing enzymatic fidelity, i.e., normal PCR should be carried out at denaturing temperature ∼4 °C higher than the melting temperature (Tm), but THz-PCR only requires temperature ∼1 °C higher than Tm due to the nonthermal effect of THz shining. Moreover, the melting time can also be shortened to 1/5 due to the enhanced vibration coupling with 53 THz irradiation. We proposed THz-PCR as an innovated DNA amplification technique with ultrahigh specificity and sensitivity and also successfully demonstrated its advantages in forensic detections

    Binding Strength of Nucleobases and Nucleosides on Silver Nanoparticles Probed by a Colorimetric Method

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    Because of their unique and tunable properties, oligonucleotide-functionalized noble metal nanoparticles have provided a versatile platform for various engineering and biomedical applications. The vast majority of such applications were demonstrated with gold nanoparticles (AuNPs) while only a few were demonstrated with sliver nanoparticles (AgNPs). This is largely due to the lack of robust protocols to functionalize AgNPs with thiol-modified oligonucleotides. Previous studies have revealed strong interactions between nucleobases and AgNPs. This could enable an alternative way to functionalize AgNPs with non-thiolated oligonucleotides. However, there is no quantitative study on the interaction strengths between AgNPs and oligonucleotides. Several methods have been used for quantitative evaluation of the interaction strengths between AuNPs and oligonucleotides. These methods often require specialized equipment that might not be widely accessible or rely on labor-intensive procedures to obtain the adsorption isotherms. Herein, we developed a colorimetric method, as a simple and high-throughput alternative of existing methods, to quantify the binding strength between AgNPs and nucleobases/nucleosides. In this colorimetric method, concentration-dependent destabilizing effects of nucleobase/nucleoside adsorption on AgNPs are utilized to indirectly quantify the amount of nucleobases/nucleosides adsorbed on AgNPs, thus deriving the binding strength between AgNPs and nucleobases/nucleosides. First, the concentration-dependent AgNP aggregation kinetics in the presence of nucleobases/nucleosides were systematically investigated. Then, this colorimetric method was used to determine the binding strengths between AgNPs and various DNA/RNA nucleobases/nucleosides. It was found that the ranking of interaction strengths between AgNPs and DNA/RNA nucleosides (dC < dT < dA, rC < rU < rA) is generally agreed with that between AgNPs and corresponding nucleobases (C < T < U < A). This suggests that DNA/RNA nucleosides interact with AgNPs mainly via the constituent nucleobases. It was also revealed that interactions of AgNPs with DNA/RNA nucleosides are significantly weaker than that with corresponding nucleobases. This implies that deoxyribose/ribose might sterically inhibit the interactions between nucleobases and AuNPs

    Spline Multiscale Smoothing to Control FDR for Exploring Features of Regression Curves

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    <p>SiZer (significant zero crossing of the derivatives) is a multiscale smoothing method for exploring trends, maxima, and minima in data. In this article, a regression spline version of SiZer is proposed in a nonparametric regression setting by the fiducial method. The number of knots for spline interpolation is used as the scale parameter of the new SiZer, which controls the smoothness of estimate. In the construction of the new SiZer, multiple testing adjustment is made to control the row-wise false discovery rate (FDR) of SiZer. This adjustment is appealing for exploratory data analysis and has potential to increase the power. A special map is also produced on a continuous scale using <i>p</i>-values to assess the significance of features. Simulations and a real data application are carried out to investigate the performance of the proposed SiZer, in which several comparisons with other existing SiZers are presented. Supplementary materials for this article are available online.</p

    Nanoscale Infrared, Thermal, and Mechanical Characterization of Telaprevir–Polymer Miscibility in Amorphous Solid Dispersions Prepared by Solvent Evaporation

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    Miscibility is of great interest for pharmaceutical systems, in particular, for amorphous solid dispersions, as phase separation can lead to a higher tendency to crystallize, resulting in a loss in solubility, decreased dissolution rate, and compromised bioavailability. The purpose of this study was to investigate the miscibility behavior of a model poorly water-soluble drug, telaprevir (TPV), with three different polymers using atomic force microscopy-based infrared, thermal, and mechanical analysis. Standard atomic force microscopy (AFM) imaging together with nanoscale infrared spectroscopy (AFM-IR), nanoscale thermal analysis (nanoTA), and Lorentz contact resonance (LCR) measurements were used to evaluate the miscibility behavior of TPV with three polymers, hydroxypropyl methylcellulose (HPMC), HPMC acetate succinate (HPMCAS), and poly­(vinylpyrrolidone-<i>co</i>-vinyl acetate) (PVPVA), at different drug to polymer ratios. Phase separation was observed with HPMC and PVPVA at drug loadings above 10%. For HPMCAS, a smaller miscibility gap was observed, with phase separation being observed at drug loadings higher than ∼30–40%. The domain size of phase-separated regions varied from below 50 nm to a few hundred nanometers. Localized infrared spectra, nano-TA measurements, images from AFM-based IR, and LCR measurements showed clear contrast between the continuous and discrete domains for these phase-separated systems, whereby the discrete domains were drug-rich. Fluorescence microscopy provided additional evidence for phase separation. These methods appear to be promising to evaluate miscibility in drug–polymer systems with similar <i>T</i><sub>g</sub>s and submicron domain sizes. Furthermore, such findings are of obvious importance in the context of contributing to a mechanistic understanding of amorphous solid dispersion phase behavior

    Table_12_Ovarian cancer subtypes based on the regulatory genes of RNA modifications: Novel prediction model of prognosis.xlsx

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    BackgroundOvarian cancer (OC) is a female reproductive system tumor. RNA modifications play key roles in gene expression regulation. The growing evidence demonstrates that RNA methylation is critical for various biological functions, and that its dysregulation is related to the progression of cancer in human.MethodOC samples were classified into different subtypes (Clusters 1 and 2) based on various RNA-modification regulatory genes (RRGs) in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) by nonnegative matrix factorization method (NMF). Based on differently expressed RRGs (DERRGs) between clusters, a pathologically specific RNA-modification regulatory gene signature was constructed with Lasso regression. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves were used to evaluate the prognostic ability of the identified model. The correlations of clinicopathological features, immune subtypes, immune scores, immune cells, and tumor mutation burden (TMB) were also estimated between different NMF clusters and riskscore groups.ResultsIn this study, 59 RRGs in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) were obtained from TCGA database. These RRGs were interactional, and sample clusters based on these regulators were significantly correlated with survival rate, clinical characteristics (involving survival status and pathologic stage), drug sensibility, and immune microenvironment. Furthermore, Lasso regression based on these 21 DERRGs between clusters 1 and 2 constructed a four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1). Based on this signature, 307 OC patients were classified into high- and low-risk groups based on median value of riskscores from lasso regression. This identified signature was significantly associated with overall survival, radiation therapy, age, clinical stage, cancer status, and immune cells (involving CD4+ memory resting T cells, plasma cells, and Macrophages M1) of ovarian cancer patients. Further, GSEA revealed that multiple biological behaviors were significantly enriched in different groups.ConclusionsOC patients were classified into two subtypes per these RRGs. This study identified four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1) in OC, which was an independent prognostic model for patient stratification, prognostic evaluation, and prediction of response to immunotherapy in ovarian cancer by classifying OC patients into high- and low-risk groups.</p

    Table_9_Ovarian cancer subtypes based on the regulatory genes of RNA modifications: Novel prediction model of prognosis.xlsx

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    BackgroundOvarian cancer (OC) is a female reproductive system tumor. RNA modifications play key roles in gene expression regulation. The growing evidence demonstrates that RNA methylation is critical for various biological functions, and that its dysregulation is related to the progression of cancer in human.MethodOC samples were classified into different subtypes (Clusters 1 and 2) based on various RNA-modification regulatory genes (RRGs) in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) by nonnegative matrix factorization method (NMF). Based on differently expressed RRGs (DERRGs) between clusters, a pathologically specific RNA-modification regulatory gene signature was constructed with Lasso regression. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves were used to evaluate the prognostic ability of the identified model. The correlations of clinicopathological features, immune subtypes, immune scores, immune cells, and tumor mutation burden (TMB) were also estimated between different NMF clusters and riskscore groups.ResultsIn this study, 59 RRGs in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) were obtained from TCGA database. These RRGs were interactional, and sample clusters based on these regulators were significantly correlated with survival rate, clinical characteristics (involving survival status and pathologic stage), drug sensibility, and immune microenvironment. Furthermore, Lasso regression based on these 21 DERRGs between clusters 1 and 2 constructed a four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1). Based on this signature, 307 OC patients were classified into high- and low-risk groups based on median value of riskscores from lasso regression. This identified signature was significantly associated with overall survival, radiation therapy, age, clinical stage, cancer status, and immune cells (involving CD4+ memory resting T cells, plasma cells, and Macrophages M1) of ovarian cancer patients. Further, GSEA revealed that multiple biological behaviors were significantly enriched in different groups.ConclusionsOC patients were classified into two subtypes per these RRGs. This study identified four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1) in OC, which was an independent prognostic model for patient stratification, prognostic evaluation, and prediction of response to immunotherapy in ovarian cancer by classifying OC patients into high- and low-risk groups.</p

    Table_2_Ovarian cancer subtypes based on the regulatory genes of RNA modifications: Novel prediction model of prognosis.xlsx

    No full text
    BackgroundOvarian cancer (OC) is a female reproductive system tumor. RNA modifications play key roles in gene expression regulation. The growing evidence demonstrates that RNA methylation is critical for various biological functions, and that its dysregulation is related to the progression of cancer in human.MethodOC samples were classified into different subtypes (Clusters 1 and 2) based on various RNA-modification regulatory genes (RRGs) in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) by nonnegative matrix factorization method (NMF). Based on differently expressed RRGs (DERRGs) between clusters, a pathologically specific RNA-modification regulatory gene signature was constructed with Lasso regression. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves were used to evaluate the prognostic ability of the identified model. The correlations of clinicopathological features, immune subtypes, immune scores, immune cells, and tumor mutation burden (TMB) were also estimated between different NMF clusters and riskscore groups.ResultsIn this study, 59 RRGs in the process of RNA modifications (m1A, m6A, m6Am, m5C, m7G, ac4C, m3C, and Ψ) were obtained from TCGA database. These RRGs were interactional, and sample clusters based on these regulators were significantly correlated with survival rate, clinical characteristics (involving survival status and pathologic stage), drug sensibility, and immune microenvironment. Furthermore, Lasso regression based on these 21 DERRGs between clusters 1 and 2 constructed a four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1). Based on this signature, 307 OC patients were classified into high- and low-risk groups based on median value of riskscores from lasso regression. This identified signature was significantly associated with overall survival, radiation therapy, age, clinical stage, cancer status, and immune cells (involving CD4+ memory resting T cells, plasma cells, and Macrophages M1) of ovarian cancer patients. Further, GSEA revealed that multiple biological behaviors were significantly enriched in different groups.ConclusionsOC patients were classified into two subtypes per these RRGs. This study identified four-DERRG signature (ALYREF, ZC3H13, WTAP, and METTL1) in OC, which was an independent prognostic model for patient stratification, prognostic evaluation, and prediction of response to immunotherapy in ovarian cancer by classifying OC patients into high- and low-risk groups.</p

    Effect of pathological heterogeneity on shear wave elasticity imaging in the staging of deep venous thrombosis

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    <div><p>Background</p><p>We aimed to observe the relationship between the pathological components of a deep venous thrombus (DVT), which was divided into three parts, and the findings on quantitative ultrasonic shear wave elastography (SWE) to increase the accuracy of thrombus staging in a rabbit model.</p><p>Methods</p><p>A flow stenosis-induced vein thrombosis model was used, and the thrombus was divided into three parts (head, body and tail), which were associated with corresponding observation points. Elasticity was quantified in vivo using SWE over a 2-week period. A quantitative pathologic image analysis (QPIA) was performed to obtain the relative percentages of the components of the main clots.</p><p>Results</p><p>DVT maturity occurred at 2 weeks, and the elasticity of the whole thrombus and the three parts (head, body and tail) showed an increasing trend, with the Young's modulus values varying from 2.36 ± 0.41 kPa to 13.24 ± 1.71 kPa; 2.01 ± 0.28 kPa to 13.29 ± 1.48 kPa; 3.27 ± 0.57 kPa to 15.91 ± 2.05 kPa; and 1.79 ± 0.36 kPa to 10.51 ± 1.61 kPa, respectively. Significant increases occurred on different days for the different parts: the head showed significant increases on days 4 and 6; the body showed significant increases on days 4 and 7; and the tail showed significant increases on days 3 and 6. The QPIA showed that the thrombus composition changed dynamically as the thrombus matured, with the fibrin and calcium salt deposition gradually increasing and the red blood cells (RBCs) and platelet trabecula gradually decreasing. Significant changes were observed on days 4 and 7, which may represent the transition points for acute, sub-acute and chronic thrombi. Significant heterogeneity was observed between and within the thrombi.</p><p>Conclusions</p><p>Variations in the thrombus components were generally consistent between the SWE and QPIA. Days 4 and 7 after thrombus induction may represent the transition points for acute, sub-acute and chronic thrombi in rabbit models. A dynamic examination of the same part of the thrombus may be helpful for improving the sensitivity and reproducibility of SWE for DVT diagnosis and staging.</p></div
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