Morphological structures and drug release effect of multiple electrospun nanofibre membrane systems based on PLA, PCL, and PCL/Magnetic nanoparticle composites

Biopolymers are good carrier materials in relation to efficient release sustainability for encapsulated drugs. In particular, electrospun polymer/composite fibre membranes can offer greater benefits owing to their competitive release features as well as large specific surface areas. In this study, multiple electrospun nanofibre membrane systems were utilised including different material systems such as poly(lactic acid) (PLA), poly(ε-caprolactone) (PCL), and PCL/magnetic nanoparticle (MP) composites loaded with tetracycline hydrochloride (TCH) as a therapeutic compound for their potential use in drug delivery applications. Such electrospun nanofibres were investigated to understand how composite constituents could tailor surface morphology for drug release control and biodegradation effect of PCL electrospun nanofibers on a long term for different drug release systems. Fibre diameter appeared to be decreased considerably with the addition of TCH drug. It was also evident that average fibre diameter was reduced when embedding MPs owing to the enhancement of solution conductivity. The encapsulation of TCH drug was found to be effective, as evidenced by Fourier transform infrared (FTIR) spectra. Thermogravimetric analysis (TGA) data revealed no significant change in the thermal stability of PCL with the inclusion of TCH and MPs. However, the use of TCH to PLA delayed the thermal degradation. Glass transition temperature (TQ) and melting temperature (TM) of PCL were decreased with the inclusion of MPs and TCH. The degree of crystallinity (XC) for PCL diminished when incorporated with MPs. Additional TCH to PLA, PCL, and PCL/MP nanocomposites resulted in a moderate decrease in (XC). TCH might be dispersed in an amorphous state within nanofibre membranes. Over the short-term periods, it was clearly seen that TCH release from PCL nanofibre membranes was higher as opposed to PLC/MP and PLA counterparts. On the contrary, such a drug release from PLC membranes became relatively slow owing to its high (XC). Further, the mass loss results were consistent with those obtained from in vitro drug release. Overall, TCH release kinetics of PCL/TCH nanofibre membranes were better estimated by Zeng model as opposed to PLA/TCH counterparts

Human Activity Recognition Using Deep Models and Its Analysis from Domain Adaptation Perspective

© 2019, Springer Nature Switzerland AG. Human activity recognition (HAR) is a broad area of research which solves the problem of determining a user’s activity from a set of observations recorded on video or low-level sensors (accelerometer, gyroscope, etc.) HAR has important applications in medical care and entertainment. In this paper, we address sensor-based HAR, because it could be deployed on a smartphone and eliminates the need to use additional equipment. Using machine learning methods for HAR is common. However, such, methods are vulnerable to changes in the domain of training and test data. More specifically, a model trained on data collected by one user loses accuracy when utilised by another user, because of the domain gap (differences in devices and movement pattern results in differences in sensors’ readings.) Despite significant results achieved in HAR, it is not well-investigated from domain adaptation (DA) perspective. In this paper, we implement a CNN-LSTM based architecture along with several classical machine learning methods for HAR and conduct a series of cross-domain tests. The result of this work is a collection of statistics on the performance of our model under DA task. We believe that our findings will serve as a foundation for future research in solving DA problem for HAR

Synthesis optimization of carbon-supported ZrO2 nanoparticles from different organometallic precursors

We report here the synthesis of carbon-supported ZrO2 nanoparticles from zirconium oxyphthalocyanine (ZrOPc) and acetylacetonate [Zr(acac)4]. Using thermogravimetric analysis (TGA) coupled with mass spectrometry (MS), we could investigate the thermal decomposition behavior of the chosen precursors. According to those results, we chose the heat treatment temperatures (THT) using partial oxidizing (PO) and reducing (RED) atmosphere. By X-ray diffraction we detected structure and size of the nanoparticles; the size was further confirmed by transmission electron microscopy. ZrO2 formation happens at lower temperature with Zr(acac)4 than with ZrOPc, due to the lower thermal stability and a higher oxygen amount in Zr(acac)4. Using ZrOPc at THT C900 °C, PO conditions facilitate the crystallite growth and formation of distinct tetragonal ZrO2, while with Zr(acac)4 a distinct tetragonal ZrO2 phase is observed already at THT C750 °C in both RED and PO conditions. Tuning of ZrO2 nanocrystallite size from 5 to 9 nm by varying the precursor loading is also demonstrated. The chemical state of zirconium was analyzed by X-ray photoelectron spectroscopy, which confirms ZrO2 formation from different synthesis routes

Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

When COVID-19 spread in China in December 2019, thousands of studies have focused on this pandemic. Each presents a unique perspective that reflects the pandemic’s main scientific disciplines. For example, social scientists are concerned with reducing the psychological impact on the human mental state especially during lockdown periods. Computer scientists focus on establishing fast and accurate computerized tools to assist in diagnosing, preventing, and recovering from the disease. Medical scientists and doctors, or the frontliners, are the main heroes who received, treated, and worked with the millions of cases at the expense of their own health. Some of them have continued to work even at the expense of their lives. All these studies enforce the multidisciplinary work where scientists from different academic disciplines (social, environmental, technological, etc.) join forces to produce research for beneficial outcomes during the crisis. One of the many branches is computer science along with its various technologies, including artificial intelligence, Internet of Things, big data, decision support systems (DSS), and many more. Among the most notable DSS utilization is those related to multicriterion decision making (MCDM), which is applied in various applications and across many contexts, including business, social, technological and medical. Owing to its importance in developing proper decision regimens and prevention strategies with precise judgment, it is deemed a noteworthy topic of extensive exploration, especially in the context of COVID-19-related medical applications. The present study is a comprehensive review of COVID-19-related medical case studies with MCDM using a systematic review protocol. PRISMA methodology is utilized to obtain a final set of (n = 35) articles from four major scientific databases (ScienceDirect, IEEE Xplore, Scopus, and Web of Science). The final set of articles is categorized into taxonomy comprising five groups: (1) diagnosis (n = 6), (2) safety (n = 11), (3) hospital (n = 8), (4) treatment (n = 4), and (5) review (n = 3). A bibliographic analysis is also presented on the basis of annual scientific production, country scientific production, co- occurrence, and co-authorship. A comprehensive discussion is also presented to discuss the main challenges, motivations, and recommendations in using MCDM research in COVID-19-related medial case studies. Lastly, we identify critical research gaps with their corresponding solutions and detailed methodologies to serve as a guide for future directions. In conclusion, MCDM can be utilized in the medical field effectively to optimize the resources and make the best choices particularly during pandemics and natural disasters

Care planning interventions for care home residents: A scoping review

Context: Previous reviews of care planning (CP) interventions in care homes focus on higher quality research methodologies and exclusively consider advanced care planning (ACP), thereby excluding many intervention-based studies that could inform current practice. CP is concerned with residents’ current circumstances while ACP focuses on expressing preferences which relate to future care decisions. Objectives: To identify, map, and summarise studies reporting CP interventions for older people in care homes. Methods: Seven electronic databases were searched from 1 January 2012 until 1 January 2022. Studies of CP interventions, targeted at older people (>60 years) whose primary place of residence was a care home, were eligible for inclusion. Two reviewers independently screened the titles and abstracts of 3,778 articles. Following a full text review of 404 articles, data from 112 eligible articles were extracted using a predefined data extraction form. Findings: Studies were conducted in 25 countries and the majority of studies took place in the USA, Australia, and the UK. Most interventions occurred within nursing homes (61%, 68/112). More than 90% of interventions (93%, 104/112) targeted staff, and training was the most common focus (80%, 83/104), although only one included training for ancillary staff (such as cleaners and caterers). Only a third of studies (35%, 39/112) involved family and friends, and 62% (69/112) described interventions to improve CP practices through multiple means. Limitations: Only papers written in English were included and so potentially relevant studies may have been omitted. Implications: Two groups of people – ancillary workers and family and friends – who could play a valuable role in CP, were often not included in CP interventions. These oversights should be addressed in future research

Age-related changes in relative expression stability of commonly used housekeeping genes in selected porcine tissues

<p>Abstract</p> <p>Background</p> <p>Gene expression analysis using real-time RT-PCR (qRT-PCR) is increasingly important in biological research due to the high-throughput and accuracy of qRT-PCR. For accurate and reliable gene expression analysis, normalization of gene expression data against housekeeping genes or internal control genes is required. The stability of reference genes has a tremendous effect on the results of relative quantification of gene expression by qRT-PCR. The expression stability of reference genes could vary according to tissues, age of individuals and experimental conditions. In the pig however, very little information is available on the expression stability of reference genes. The aim of this research was therefore to develop a new set of reference genes which can be used for normalization of mRNA expression data of genes expressed in varieties of porcine tissues at different ages.</p> <p>Results</p> <p>The mRNA expression stability of nine commonly used reference genes (<it>B2M, BLM, GAPDH, HPRT1, PPIA, RPL4, SDHA, TBP </it>and <it>YWHAZ</it>) was determined in varieties of tissues collected from newborn, young and adult pigs. geNorm, NormFinder and BestKeeper software were used to rank the genes according to their stability. geNorm software revealed that <it>RPL4, PPIA </it>and <it>YWHAZ </it>showed high stability in newborn and adult pigs, while <it>B2M, YWHAZ </it>and <it>SDHA </it>showed high stability in young pigs. In all cases, <it>GAPDH </it>showed the least stability in geNorm. NormFinder revealed that <it>TBP </it>was the most stable gene in newborn and young pigs, while <it>PPIA </it>was most stable in adult pigs. Moreover, geNorm software suggested that the geometric mean of three most stable gene would be the suitable combination for accurate normalization of gene expression study.</p> <p>Conclusions</p> <p>Although, there was discrepancy in the ranking order of reference genes obtained by different analysing software methods, the geometric mean of the <it>RPL4, PPIA </it>and <it>YWHAZ </it>seems to be the most appropriate combination of housekeeping genes for accurate normalization of gene expression data in different porcine tissues at different ages.</p

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all &gt;0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council

Reproductive health and access to healthcare facilities: risk factors for depression and anxiety in women with an earthquake experience

<p>Abstract</p> <p>Background</p> <p>The reproductive and mental health of women contributes significantly to their overall well-being. Three of the eight Millennium Development Goals are directly related to reproductive and sexual health while mental disorders make up three of the ten leading causes of disease burden in low and middle-income countries. Among mental disorders, depression and anxiety are two of the most prevalent. In the context of slower progress in achieving Millennium Development Goals in developing countries and the ever-increasing man-made and natural disasters in these areas, it is important to understand the association between reproductive health and mental health among women with post-disaster experiences.</p> <p>Methods</p> <p>This was a cross-sectional study with a sample of 387 women of reproductive age (15-49 years) randomly selected from the October 2005 earthquake affected areas of Pakistan. Data on reproductive health was collected using the Centers for Disease Control reproductive health assessment toolkit. Depression and anxiety were measured using the Hopkins Symptom Checklist-25, while earthquake experiences were captured using the Harvard Trauma Questionnaire. The association of either depression or anxiety with socio-demographic variables, earthquake experiences, reproductive health and access to health facilities was estimated using multivariate logistic regression.</p> <p>Results</p> <p>Post-earthquake reproductive health events together with economic deprivation, lower family support and poorer access to health care facilities explained a significant proportion of differences in the experiencing of clinical levels of depression and anxiety. For instance, women losing resources for subsistence, separation from family and experiencing reproductive health events such as having a stillbirth, having had an abortion, having had abnormal vaginal discharge or having had genital ulcers, were at significant risk of depression and anxiety.</p> <p>Conclusion</p> <p>The relationship between women's post-earthquake mental health and reproductive health, socio-economic status, and health care access is complex and explained largely by the socio-cultural role of women. It is suggested that interventions that consider gender differences and that are culturally appropriate are likely to reduce the incidence.</p

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children &lt;18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p&lt;0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p&lt;0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p&lt;0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer