Notes

Prescribed Prescription antibiotic Use One of many Us all population 1999-2018: National Nutrition and health Exam Surveys.
gested a new approach to improve the selectivity and anticancer activity of ZnO NPs. learn more Studies on antitumor activity of SnO
-ZnO/rGO NCs in animal models are further warranted.
SnO2-ZnO/rGO NCs showed enhanced anticancer activity and better biocompatibility than SnO2-ZnO NPs and pure ZnO NPs. This work suggested a new approach to improve the selectivity and anticancer activity of ZnO NPs. Studies on antitumor activity of SnO2-ZnO/rGO NCs in animal models are further warranted.
Current treatment options for muscle-invasive bladder cancer (MIBC) are associated with substantial morbidity. Local release of doxorubicin (DOX) from phosphatidyldiglycerol-based thermosensitive liposomes (DPPG
-TSL-DOX) potentiated by hyperthermia (HT) in the bladder wall may result in bladder sparing without toxicity of systemic chemotherapy. We investigated whether this approach, compared to conventional DOX application, increases DOX concentrations in the bladder wall while limiting DOX in essential organs.

Twenty-one pigs were anaesthetized, and a urinary catheter equipped with a radiofrequency-emitting antenna for HT (60 minutes) was placed. Experimental groups consisted of iv low or full dose (20 or 60 mg/m
) DPPG
-TSL-DOX with/without HT, iv low dose (20 mg/m
) free DOX with HT, and full dose (50 mg/50 mL) intravesical DOX with/without HT. After the procedure, animals were immediately sacrificed. HPLC was used to measure DOX levels in the bladder, essential organs and serum, and fluorescence atment for MIBC.
Iv DPPG2-TSL-DOX combined with HT achieved higher DOX concentrations in the bladder wall including the detrusor, compared to conventional iv and intravesical DOX application. In combination with lower DOX accumulation in heart and kidneys, compared to iv free chemotherapy, DPPG2-TSL-DOX with HT has great potential to attain a role as a bladder-sparing treatment for MIBC.
The present study investigates the phytosynthesis of silver nanoparticles (AgNPs) using
leaf extract, which acts as a reducing agent for the conversion of silver ions (Ag+) into AgNPs.
leaf synthesized AgNPs (PF@AgNPs) were evaluated for biomedical properties including antibacterial, antioxidant and anticancer activities.

PF@AgNPs were synthesized using
leaf extract and silver nitrate solution. The morphology and physical properties of PF@AgNPs were studied by spectroscopic techniques including, UV-Vis, FTIR, TEM, XRD, DLS, and TGA. Antibacterial activity of PF@AgNPs was evaluated by disk diffusion assay. Antioxidant activity of PF@AgNPs was checked by 2.2-diphenyl-1-picrylhydrazyl (DPPH), and 2.2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical scavenging assays. Anticancer activity of PF@AgNPs was checked by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay. Cytotoxic effects of PF@AgNPs on most susceptible cancer cell lines were observed by phase contrauccessful synthesis of PF@AgNPs using
leaf extract. The synthesized PF@AgNPs are FCC crystals, monodispersed, long-term stable, and non-agglomerated. The observed antibacterial, antioxidant, and anticancer activities demonstrate the potential biomedical applications of PF@AgNPs.
The present study reports the successful synthesis of PF@AgNPs using P. frutescens leaf extract. The synthesized PF@AgNPs are FCC crystals, monodispersed, long-term stable, and non-agglomerated. The observed antibacterial, antioxidant, and anticancer activities demonstrate the potential biomedical applications of PF@AgNPs.
This manuscript analyzes the exacerbations recorded by the Prevexair application through the daily analysis of symptoms in high-risk patients with COPD and explores its usefulness in assessing clinical stability with respect to that reported in visits.

This study is a multi-centre cohort of COPD patients with the exacerbator phenotype who were monitored over 6 months. The Prevexair application was installed on the patients' smartphones. Patients used the app to record symptom changes, use of medication and use of healthcare resources. It is not established a recommended action plan when worsening of symptoms. At their clinical visit during the follow-up period, patients were asked about exacerbations suffered during these 6 months of monitoring. The investigators who conducted the visit were blinded about the Prevexair app records.

The patients experienced a total of 185 exacerbations according to daily records in the app whereas only 64 exacerbations were recalled during medical visits. Perception becatients do not always remember the exacerbations suffered during their medical visit. The prevexair application is useful in monitoring COPD patients at high risk, in order to a better assessment of exacerbations of COPD during medical visits. Further research must be carried out to evaluate this strategy in clinical practice.
The presence of cardiovascular (CV) risk factors and CV disease in patients with chronic obstructive pulmonary disease (COPD) leads to worse outcomes. A number of tools are currently available to stratify the risk of adverse outcomes in these patients with COPD. This post hoc analysis evaluated the Summit Lab Score for validation as a predictor of the first episode of moderate-to-severe acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and other outcomes, in patients with COPD and high arterial pulse wave velocity (aPWV).

Data from a multicenter, randomized, placebo-controlled, double-blind study were retrospectively analyzed to evaluate treatment effects of once-daily fluticasone furoate/vilanterol 100/25 μg in patients with COPD and an elevated CV risk (aPWV≥11m/s) over 24 weeks. The previously derived Summit Lab Score and, secondarily, the Intermountain Risk Score (IMRS) were computed for each patient, with patients then stratified into tertiles for each score. Risk of moderate-to-setowards differences in the risk of AECOPD, which was not statistically significant.
There have been calls for more knowledge of activities of daily living (ADL) performance in order to address interventions in pulmonary rehabilitation effectively. Everyday technology (ET) has become an integrated dimension of ADL, impacting the ways in which ADL is performed. To improve everyday functioning and quality of life, the use of ADL and ET use needs to be evaluated and addressed effectively in interventions. Therefore, the aim of this study was twofold 1) to explore the quality of ADL performance, and 2) to investigate the relationship between observation and self-reported ADL performance and ability to use everyday technologies in people living with COPD.

This cross-sectional study involved 84 participants aged 46-87 years. Participants were recruited through healthcare centres in the Northern Region of Denmark using a convenience sampling procedure. Data were collected using standardized assessments that investigated different ADL perspectives self-reported ADL tasks and ET use, observed mototant to evaluate and target pulmonary rehabilitation.
Overall, the knowledge from the present study is valuable for focusing interventions that address challenging ADL performance and ET use through relevant and realistic activities. The ability to use ET is important to evaluate and target pulmonary rehabilitation.
Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is often underdiagnosed.

To develop machine learning methods to predict COPD using chest radiographs and a convolutional neural network (CNN) trained with near-concurrent pulmonary function test (PFT) data. Comparison is made to natural language processing (NLP) of the associated radiologist text reports.

This IRB-approved single-institution retrospective study uses 6749 two-view chest radiograph exams (2012-2017, 4436 unique subjects, 54% female, 46% male), same-day associated radiologist text reports, and PFT exams acquired within 180 days. The Image Model (Resnet18 pre-trained with ImageNet CNN) is trained using frontal and lateral radiographs and PFTs with 10% of the subjects for validation and 19% for testing. The NLP Model is trained using radiologist text reports and PFTs. The primary metric of model comparison is the area under the receiver operating characteristic curve (AUC).

The Image Model achieves an AUC of 0.814 for prediction of obstructive lung disease (FEV1/FVC <0.7) from chest radiographs and performs better than the NLP Model (AUC 0.704, p<0.001) from radiologist text reports where FEV1 = forced expiratory volume in 1 second and FVC = forced vital capacity. The Image Model performs better for prediction of severe or very severe COPD (FEV1 <0.5) with an AUC of 0.837 versus the NLP model AUC of 0.770 (p<0.001).

A CNN Image Model trained on physiologic lung function data (PFTs) can be applied to chest radiographs for quantitative prediction of obstructive lung disease with good accuracy.
A CNN Image Model trained on physiologic lung function data (PFTs) can be applied to chest radiographs for quantitative prediction of obstructive lung disease with good accuracy.
Socioeconomic status (SES) is a strong determinant in the development of various diseases. We evaluated the relationship between SES and the incidence of chronic obstructive pulmonary disease (COPD) by using a community-based cohort data.

Four-year follow-up data of 6341 adults (aged ≥ 40 years), who underwent serial pulmonary function test were analyzed. Incidence of COPD in the participants was defined as the absence of airflow obstruction compatible with COPD (pre-bronchodilator forced expiratory volume in 1 second/forced vital capacity ratio of <0.7) at baseline but documentation of airflow obstruction in serial testing. SES of patients was divided into quartiles according to household income and educational level. Multivariate logistic regression analyses were performed to estimate the association between SES and COPD incidence.

A total of 280 (4.4%) patients developed COPD during the follow-up. The proportion of subjects with lowest education (elementary school) and lowest household income levels (1st quartile) was significantly higher in the COPD group than in the non-COPD group (37.9% vs 29.5%, p<0.011 and 48.4% vs 30.8%, p<0.001, respectively). Logistic regression analysis revealed that education level of elementary school was independently associated with COPD incidence after adjustment for sex, age, body mass index, white blood cell count, residence area, and occupation (odds ratio 1.879, 95% confidence interval 1.124-3.141, p=0.016).

In the general population, educational level of elementary school was an independent risk factor for COPD among the components comprising SES. Our results indicate that the implementation of preventive strategies for COPD in those with low educational status could be beneficial.
In the general population, educational level of elementary school was an independent risk factor for COPD among the components comprising SES. Our results indicate that the implementation of preventive strategies for COPD in those with low educational status could be beneficial.
To describe the characteristics and prognosis of patients with COPD admitted to the hospital due to SARS-CoV-2 infection.

The SEMI-COVID registry is an ongoing retrospective cohort comprising consecutive COVID-19 patients hospitalized in Spain since the beginning of the pandemic in March 2020. Data on demographics, clinical characteristics, comorbidities, laboratory tests, radiology, treatment, and progress are collected. Patients with COPD were selected and compared to patients without COPD. Factors associated with a poor prognosis were analyzed.

Of the 10,420 patients included in the SEMI-COVID registry as of May 21, 2020, 746 (7.16%) had a diagnosis of COPD. Patients with COPD are older than those without COPD (77 years vs 68 years) and more frequently male. They have more comorbidities (hypertension, hyperlipidemia, diabetes mellitus, atrial fibrillation, heart failure, ischemic heart disease, peripheral vascular disease, kidney failure) and a higher Charlson Comorbidity Index (2 vs 1, p<0.001). The mortality rate in COPD patients was 38.
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