Notes

RSV infection-elicited large MMP-12-producing macrophages worsen sensitized air passage swelling using neutrophil infiltration.
The dose of administered chemotherapy drugs is crucial to determine due to the potential for efficient or adverse outcomes for cancer patients. To date, no user-friendly and low-cost method of doxorubicin (DOX) detection using nontoxic and biodegradable materials has been reported. For this reason, in this work, we have developed for the first time a nanofiber-based sensing platform for sensitive and on-site DOX assay in just 10 min. This is obtained thanks to printable, porosity and embeddability features of electrospun nanofibrous films (ENFFs) combined with nitrogen and sulfur co-doped carbon dots (NS-CDs) as sensing probes. The assay was done by just pipetting analyte on the hydrophilic spots of the fabricated photoluminescence water-stable ENFFs where the color intensity was being darkened. DOX quenched NS-CDs fluorescence onto ENFFs through inner filter effect. The developed sensor was either coupled with smartphone technology to provide miniaturized, portable and easy-to-use device or an ordinary spectrofluorimeter for solid-state sensing applications (detection limit of 5.4 nM). Moreover, applicability of the designed sensor was evaluated in human serum with satisfactory recoveries. It is more interesting that the fabricated NS-CDs/ENF scaffolds have a high potential to detect the intracellular DOX to enhance cell proliferation leading to be considered as a multimodal tool in biomedical research and clinical diagnostics.
This study aimed to examine the reliability and validity of a newly developed Asthma Numeracy Test (ANT) and to make it available in Arabic.

Patients with asthma who were ≥18 years were seen in 3 outpatient primary care or respiratory medicine clinics in the United Arab Emirates. They completed the ANT of 10 questions assessing participant arithmetic computation, meaning of percentages, estimation, and problem solving. Each question was worth 1 point, giving a total score of 10. The ANT was forward and back translated to Arabic and English, respectively, by independent legal translators and piloted on 15 participants. Convergent validity was tested by comparing the ANT with the Asthma Knowledge Test (AKT) scores, knowledge of inhaled medications, and practical inhaler technique using Pearson's correlation coefficients.

The average ANT score achieved by 150 participants was 6.47 ± 2.09; 25% and 45% scored ≤4.0 and 6.0, respectively. Correlation between ANT and AKT and knowledge of inhaled medications were positive, r= .22 and r= .16, P < .05, respectively. No correlation with participants' practical inhaler technique was noted. Prostaglandin E2 ic50 ANT was positively associated with participant educational attainment and negatively with emergency room visits.

A new short and easy-to-administer test of asthma numeracy has been developed and found to be valid and reliable. It may be used to assess numeracy levels of patients with asthma and consequently develop and evaluate targeted interventions designed to improve patient care outcomes. The test is available in English and Arabic.
A new short and easy-to-administer test of asthma numeracy has been developed and found to be valid and reliable. It may be used to assess numeracy levels of patients with asthma and consequently develop and evaluate targeted interventions designed to improve patient care outcomes. The test is available in English and Arabic.An automated equine fecal egg count test, known as the Parasight System, was modified for use with small ruminants. Modifications included the introduction of a short centrifugation step in a floatation medium, an adjustment in pre-test sample filtering, and training of an image analysis-based egg counting algorithm to recognize and enumerate trichostrongylid eggs. In preliminary assessments, the modified method produced trichostrongylid egg counts comparable to manual McMaster analyses of the same samples from both ovine and caprine sources. The coefficient of determination (R2) for the linear correlation between McMaster and automated counts from these samples was 0.958, and there were no significant differences when comparing counts using feces from either sheep or goats. More extensive comparison utilized ovine samples split into three groups based on trichostrongylid egg content Low (201-500 EPG), Medium (501-1000 EPG) and High (1001 or greater EPG). Each group contained 5 samples, each of which was used to produce individual slurries that were counted 8 times each using both McMaster and the automated method. This, again, showed no difference in accuracy between the techniques, but revealed significantly higher precision, as assessed by coefficients of variation (CoV), for the automated method for determining egg counts in the Low and Medium groups. The CoV of the McMaster method was 2.2, 2.5 and 1.3 times greater than the automated in the Low, Medium and High groups, respectively. Overall, the automated egg counting system showed good linear agreement with trichostrongylid egg counts determined with the McMaster method, and demonstrated significantly better precision. This technology reduces operator error and the results presented here illustrate its utility for determination of small ruminant trichostrongylid fecal egg counts.
The incidence of non-alcoholic fatty liver disease (NAFLD) and its progressive form, non-alcoholic steatohepatitis (NASH), has been increasing for decades. Since the mainstay is lifestyle modification in this mainly asymptomatic condition, there is a need for accurate diagnostic methods.

This study proposes a method with a computer-aided diagnosis (CAD) system to predict NAFLD Activity score (NAS scores-steatosis, lobular inflammation, and ballooning) and fibrosis stage from histopathology slides.

A total of 87 pathology slides pairs (H&E and Trichrome-stained) were used for the study. Ground-truth NAS scores and fibrosis stages were previously identified by a pathologist. Each slide was split into 224×224 patches and fed into a feature extraction network to generate local features. These local features were processed and aggregated to obtain a global feature to predict the slide's scores. The effects of different training strategies, as well as training data with different staining and magnificatioThe algorithms are an aid in having an accurate and systematic diagnosis in a condition that affects hundreds of millions of patients globally.
These results were robust. The method proposed proved to be effective in predicting NAFLD Activity score and fibrosis stage from histopathology slides. The algorithms are an aid in having an accurate and systematic diagnosis in a condition that affects hundreds of millions of patients globally.
The Baby-Friendly Hospital Initiative (BFHI) is an international strategy aimed at improving breastfeeding practices in health care services. Regular monitoring of indicators is key for BFHI implementation and maintenance. Currently, routine data collected from electronic health records (EHR) is an excellent source for infant feeding monitoring, however data quality (DQ) assessment should be undertaken. The aim of this research is to enable robust estimations of infant feeding indicators through DQ assessment of routine EHR data.

We use the longitudinal series of healthcare contacts belonging to 6427 children born from 2009 to 2018 in the Health Area V of Murcia (Spain). Longitudinal data came from EHR at hospital discharge and community infant health reviews up to 18 months. The data of each healthcare contact contained a 24-h recall of infant feeding. We perform a DQ process in three phases (1) an assessment of each-single-contact and the definition of their infant feeding status; (2) a longitudinal DQ eviously published. The methodology provided with this study allows a continuous and reliable population monitoring of infant feeding indicators of BFHI from routine EHR data.
Despite the DQ deficiencies found in raw data, the DQ assurance approach by indicators proposed in this work, allowed us to obtain a robust estimation of indicators with a significant percentage of subjects with valid information for ABF and FBF monitoring. The estimations were consistent with results previously published. The methodology provided with this study allows a continuous and reliable population monitoring of infant feeding indicators of BFHI from routine EHR data.
The massive increase, in the Internet of Things applications, has greatly evolved technological aspects of human life. The drastic development of IoT based smart healthcare services have layout the smart process models to facilitate all stakeholders (e.g. patients, doctors, hospitals etc.) and made it an important social-economic concern. There are variety of smart healthcare services like remote patient monitoring, diagnostic, disease specific remote treatments and telemedicine. Many trending Internet of Health Things research and development are done in a very disjoint and independent fashion providing solutions and guidelines for variant diseases, medical resources and remote services management. These expositions work over many shared resources such as health facilities for patient and human in healthcare system.

This research discusses the ontology for merging methods to form an integrated platform with shared knowledge of smart healthcare services. The proposed process model creates an ontological fand merging techniques. The model efficiency enhancement and query optimization methods are listed in future tasks of the research.
The development of biomechanical models of the torso and the spine opens the door to computational solutions for the design of braces for adolescent idiopathic scoliosis. However, the design of such biomechanical models faces several unknowns, such as the correct identification of relevant mechanical elements, or the required accuracy of model parameters. The objective of this study was to design a methodology for the identification of the aforementioned elements, with the purpose of creating personalized models suited for patient-specific brace design and the definition of parameter estimation criteria.

We have developed a comprehensive model of the torso, including spine, ribcage and soft tissue, and we have developed computational tools for the analysis of the model parameters. With these tools, we perform an analysis of the model under typical loading conditions of scoliosis braces.

We present a complete sensitivity analysis of the models mechanical parameters and a comparison between a reference het the axial rotation of the spine also requires careful modeling.
The size, shape, and position of the pancreas are affected by the patient characteristics such as age, sex, adiposity. Owing to more complex anatomical structures (size, shape, and position) of the pancreas, specialists have some difficulties in the analysis of pancreatic diseases (diabetes, pancreatic cancer, pancreatitis). Therefore, the treatment of the disease requires enormous time and depends on the experience of specialists. In order to decrease the rate of pancreatic disease deaths and to assist the specialist in the analysis of pancreatic diseases, automatic pancreas segmentation techniques have been actively developed in the research article for many years.

Although the rapid growth of deep learning and proving satisfactory performance in many medical image processing and computer vision applications, the maximum Dice Similarity Coefficients (DSC) value of these techniques related to automatic pancreas segmentation is only around 85% due to complex structure of the pancreas and other factors. Contrary to previous techniques which are required significantly higher computational power and memory, this paper suggests a novel two-phase approach for high-accuracy automatic pancreas segmentation in computed tomography (CT) imaging.
Homepage: https://www.selleckchem.com/products/prostaglandin-e2-cervidil.html