The relationship between cellular adhesion and surface roughness for polyurethane modified by microwave plasma radiation

Surface modification of medical polymers is carried out to improve biocompatibility. In this study, conventional polyurethane was exposed to microwave plasma treatment with oxygen and argon gases for 30 seconds and 60 seconds. Attenuated total reflection Fourier transform infrared spectra investigations of irradiated samples indicated the presence of functional groups. Atomic force microscope images of samples irradiated with inert and active gases indicated the nanometric topography of the sample surfaces. Samples irradiated by oxygen plasma indicated high roughness compared with those irradiated by inert plasma for the different lengths of time. In addition, surface roughness increased with time, which can be due to a reduction of contact angle of samples irradiated by oxygen plasma. Contact angle analysis indicated a reduction in samples irradiated with both types of plasma. However, samples irradiated with oxygen plasma indicated lower contact angle compared with those irradiated by argon plasma. Cellular investigations with unrestricted somatic stem cells showed better adhesion, cell growth, and proliferation among samples radiated by oxygen plasma for longer than for normal samples

Liver Disease Recognition: A Discrete Hidden Markov Model Approach

The liver alongside the heart and the brain is the largest and the most vital organ within the human body whose absence leads to certain death. In addition, diagnosis of liver diseases takes a long time and requires sufficient expertise of physicians. To this end, statistical methods as automatic prediction systems can help specialists to diagnose liver diseases quickly and accurately. The Discrete Hidden Markov Model (DHMM) is an intelligent and a strong statistical model used to predict the types of liver diseases in patients in this study. The data in this crosssectional study included information elicited from the records of 1143 patients with 5 different types of liver diseases including cirrhosis of the liver, liver cancer, acute hepatitis, chronic hepatitis, and fatty liver disease admitted to Afzalipour Hospital in the city of Kerman in the time period of 2006-2013. At first, the type of diseases for each patient was identified; however, it was assumed that the type of diseases is unknown and there were attempts to diagnose the type of the disease through the DHMM to examine its accuracy. Therefore, the DHMM was fitted to the data and its performance was evaluated by using the parameters of accuracy, sensitivity, and specificity. Such parameters of the model were separately calculated for the diagnosis of liver diseases. The highest levels of accuracy, sensitivity, and specificity were associated with the diagnosis of cirrhosis of the liver and equal to 0.77, 0.82, 0.96, respectively; and the lowest levels were related to the diagnosis of fatty liver disease with an accuracy level of 0.65 and a sensitivity level of 0.69. As well, the specificity level in the diagnosis of fatty liver disease was 0.94. The results of this study indicated the potential ability of the DHMM; thus, the use of this model in terms of diagnosing liver diseases was strongly recommended

Nanotoxicology and nanoparticle safety in biomedical designs

Nanotechnology has wide applications in many fields, especially in the biological sciences and medicine. Nanomaterials are applied as coating materials or in treatment and diagnosis. Nanoparticles such as titania, zirconia, silver, diamonds, iron oxides, carbon nanotubes, and biodegradable polymers have been studied in diagnosis and treatment. Many of these nanoparticles may have toxic effects on cells. Many factors such as size, inherent properties, and surface chemistry may cause nanoparticle toxicity. There are methods for improving the performance and reducing toxicity of nanoparticles in medical design, such as biocompatible coating materials or biodegradable/biocompatible nanoparticles. Most metal oxide nanoparticles show toxic effects, but no toxic effects have been observed with biocompatible coatings. Biodegradable nanoparticles are also used in the efficient design of medical materials, which will be reviewed in this article

Translation and validation study of the Persian version of the Arthritis Impact Measurement Scales 2 (AIMS2) in patients with osteoarthritis of the knee

Background: The Arthritis Impact Measurement Scales 2 (AIMS2) has not been translated and validated for Persian-speaking patients with osteoarthritis of the knee. This was to provide a validated instrument to measure functional disability and health-related quality of life in patients with osteoarthritis of the knee in Iran. The aim of this study was to culturally adapt and validate the AIMS2 for Persian-speaking patients with osteoarthritis of the knee in Iran. Methods: A consecutive sample of patients with knee osteoarthritis were asked to complete the AIMS2, the Short Form Health Survey (SF-36) and four visual analog scales for pain, joint stiffness, patient's and physician's global assessment. Internal consistency and convergent validity were applied to examine psychometric properties of the AIMS2. In addition, 30 randomly selected patients were asked to complete the questionnaire two days later for the second time for test-retest reliability. Finally factor structure of the Persian AIMS2 was performed using the principal component factor analysis. Results: In all 230 patients were entered into the study. The mean (SD) age of the participants was 56.9 (8.7) years and the mean (SD) duration of disease was 7.2 (3.5) years. Cronbach's alpha coefficient and intraclass correlation coefficient (ICC) for the Persian AIMS2 scales ranged from 0.74 to 0.92 and 0.85 to 0.96, respectively. The correlation between most of the Persian AIMS2 scales and the physical and mental summary scores of the SF-36 and the visual analogue scales for pain, joint stiffness, patient's and physician's global assessment were statistically significant indicating a good convergent validity (p < 0.05). The results obtained from factor analysis indicated three latent factors that jointly accounted for 67.5% of the total variance. Conclusion: The results showed that the Persian AIMS2 had reasonably good internal consistency, test-retest reliability, and convergent validity in patients with osteoarthritis of the knee. It is simple and easy to use and now can be applied in the future studies in Iran. However, its sensitivity to change needs still to be studied.We wish to express our gratitude to physicians who co-operated in the selection of the patients and patients who gave their time to complete the questionnaires. This research was supported by Sport Medicine Research Center (SMRC), Tehran University of Medical Sciences; grant No 85-01-53-3579

Prospective Acid Reflux Study of Iran (PARSI): Methodology and study design

<p>Abstract</p> <p>Background</p> <p>Gastroesophageal reflux disease is a common and chronic disorder but long term, prospective studies of the fate of patients seeking medical advice are scarce. This is especially prominent when looking at non-erosive reflux disease (NERD) patients.</p> <p>Methods</p> <p>We designed a prospective cohort to assess the long term outcome of GERD patients referring to gastroenterologists. Consecutive consenting patients, 15 years of age and older, presenting with symptoms suggestive of GERD referring to our outpatient clinics undergo a 30 minute interview. Upper gastrointestinal endoscopy is performed for them with protocol biopsies and blood samples are drawn. Patients are then treated according to a set protocol and followed regularly either in person or by telephone for at least 10 years.</p> <p>Discussion</p> <p>Our data show that such a study is feasible and follow-ups, which are the main concern, can be done in a fairly reliable way to collect data. The results of this study will help to clarify the course of various subgroups of GERD patients after coming to medical attention and their response to treatment considering different variables. In addition, the basic symptoms and biological database will fuel further molecular epidemiologic studies.</p

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Liver Disease Recognition: A Discrete Hidden Markov Model Approach

The liver alongside the heart and the brain is the largest and the most vital organ within the human body whose absence leads to certain death. In addition, diagnosis of liver diseases takes a long time and requires sufficient expertise of physicians. To this end, statistical methods as automatic prediction systems can help specialists to diagnose liver diseases quickly and accurately. The discrete Hidden Markov Model (HMM) is an intelligent and a strong statistical model used to predict the types of liver diseases in patients in this study. The data in this cross-sectional study included information elicited from the records of ۱۱۴۳ patients with ۵ different types of liver diseases including cirrhosis of the liver, liver cancer, acute hepatitis, chronic hepatitis, and fatty liver disease admitted to Afzalipour Hospital in the city of ۲۰۱۳. At first, the type of diseases for each patient - Kerman in the time period of ۲۰۰۶ was identified; however, it was assumed that the type of diseases is unknown and there were attempts to diagnose the type of the disease through the HMM to examine its accuracy. Therefore, the HMM was fitted to the data and its performance was evaluated by using the parameters of accuracy, sensitivity, and specificity. Such parameters of the model were separately calculated for the diagnosis of liver diseases. The highest levels of accuracy, sensitivity, and specificity were associated with the diagnosis of cirrhosis of the liver and equal to ۰.۹۶, respectively; and the lowest levels were related to the diagnosis of , ۰.۸۲ , ۰.۷۷ fatty liver disease with an accuracy level of ۰.۶۵ and a sensitivity level of ۰.۶۹. As well, the specificity level in the diagnosis of fatty liver disease was ۰.۹۴.The results of this study indicated the potential ability of the HMM; thus, the use of this model in terms of diagnosing liver diseases was strongly recommended