Solvent-free synthesis of biostable segmented polyurethane shape memory polymers for biomedical applications.

Biostable shape memory polymers that remain stable in physiological conditions are beneficial for user-defined shape recovery in response to a specific stimulus. For potential commercialization and biocompatibility considerations, biomaterial synthesis must be simple and scalable. Hence, a library of biostable and cytocompatible shape memory polymers with tunable thermomechanical properties based on hard segment content was synthesized using a solvent-free method. Polymer surface chemistry, thermomechanical and shape memory properties, and biostability were assessed. We also investigated the effects of processing methods on thermomechanical and shape memory properties. All polymers showed high glass transition temperatures (>50 °C), which indicates that their temporary shape could be preserved after implantation. Polymers also demonstrate high shape fixity (73-80%) and shape recovery (93-95%). Minimal mass loss (<5%) was observed in accelerated oxidative (20% H2O2) and hydrolytic (0.1 M NaOH) media. Additionally, minimal shape recovery (∼0%) occurred in programmed samples with higher hard segment content that were stored in degradation media. After 40 days of storage in media, programmed samples recovered their primary shapes upon heating to temperatures above their transition temperature. Annealing to above the polymer melting point and solvent casting of polymers improved shape memory and thermal properties. To enable their potential use as biomaterial scaffolds, fiber formation of synthesized polyurethanes was compared with those of samples synthesized using a previously reported solvent-based method. The new method provided polymers that can form fibrous scaffolds with improved mechanical and shape memory properties, which is attributed to the higher molecular weight and crystalline content of polymers synthesized using the new, solvent-free approach. These biostable segmented polyurethanes could be coupled with a range of components that respond to specific stimuli, such as enzymes, magnetic field, pH, or light, to enable a specific shape change response, which could be coupled with drug and/or bioactive material delivery in future work.

Self-Defensive Antimicrobial Shape Memory Polyurethanes with Honey-Based Compounds.

Infection treatment plays a crucial role in aiding the body in wound healing. To that end, we developed a library of antimicrobial polymers based on segmented shape memory polyurethanes with nondrug-based antimicrobials (i.e., honey-based phenolic acids (PAs)) using both chemical and physical incorporation approaches. The antimicrobial shape memory polymers (SMPs) have high transition temperatures (>55 °C) to enable maintenance of temporary, programmed shapes in physiological conditions unless a specific external stimulus is present. Polymers showed tunable mechanical and shape memory properties by changing the ratio, chemistry, and incorporation method of PAs. Cytocompatible (∼100% cell viability) synthesized polymers inhibited growth rates of Staphylococcus aureus (∼100% with physically incorporated PAs and >80% with chemically incorporated PAs) and Escherichia coli (∼100% for samples with cinnamic acid (physical and chemical)). Crystal violet assays showed that all formulations inhibit biofilm formation in surrounding solutions, and chemically incorporated samples showed surface antibiofilm properties with S. aureus. Molecular dynamics simulations confirm that PAs have higher levels of interactions with S. aureus cell membranes than E. coli. Long-term antimicrobial properties were measured after storage of the sample in aqueous conditions; the polymers retained their antimicrobial properties against E. coli after up to 20 days. As a proof of concept, magnetic particles were incorporated into the polymer to trigger user-defined shape recovery by applying an external magnetic field. Shape recovery disrupted preformed S. aureus biofilms on polymer surfaces. This antimicrobial biomaterial platform could enable user- or environmentally controlled shape change and/or antimicrobial release to enhance infection treatment efforts.

The application of artificial intelligence in health policy: a scoping review.

BACKGROUND: Policymakers require precise and in-time information to make informed decisions in complex environments such as health systems. Artificial intelligence (AI) is a novel approach that makes collecting and analyzing data in complex systems more accessible. This study highlights recent research on AI's application and capabilities in health policymaking. METHODS: We searched PubMed, Scopus, and the Web of Science databases to find relevant studies from 2000 to 2023, using the keywords "artificial intelligence" and "policymaking." We used Walt and Gilson's policy triangle framework for charting the data. RESULTS: The results revealed that using AI in health policy paved the way for novel analyses and innovative solutions for intelligent decision-making and data collection, potentially enhancing policymaking capacities, particularly in the evaluation phase. It can also be employed to create innovative agendas with fewer political constraints and greater rationality, resulting in evidence-based policies. By creating new platforms and toolkits, AI also offers the chance to make judgments based on solid facts. The majority of the proposed AI solutions for health policy aim to improve decision-making rather than replace experts. CONCLUSION: Numerous approaches exist for AI to influence the health policymaking process. Health systems can benefit from AI's potential to foster the meaningful use of evidence-based policymaking.

Social stigma during COVID-19: A systematic review.

Objectives: Stigmatization was reported throughout the COVID pandemic for COVID-19 patients and close contacts. The aim of this systematic review was to comprehensively examine the prevalence and impact of stigmatization during COVID-19 pandemic. Methods: English articles were searched using online databases that included PubMed, Scopus, Embase, and Web of Science up to 24 August 2022. A two-step screening and selection process was followed utilizing an inclusion and exclusion criteria and then data was extracted from eligible articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was followed, and the risk of bias was assessed using the Newcastle-Ottawa Scale. Results: Seventy-six studies were eligible for inclusion. Twenty-two studies reported the prevalence of social stigma due to COVID-19 infection with social isolation being the most commonly reported stigma. There were 20 studies that reported the majority of participants experienced stigma due to COVID-19 infection, which was as high as 100% of participants in two studies. Participants in 16 studies reported blaming from others as the second most common type of stigma, with various other types reported such as psychological pressure, verbal violence, avoidance, and labeling. The most common effect of the stigma was anxiety followed by depression, and then reduction of socialization. Conclusion: Findings from the present review have identified that COVID-19-related stigma studies have generally focused on its prevalence, type, and outcome. Greater awareness of this topic may assist with improving public education during pandemics such as COVID-19 as well as access to support services for individuals impacted by stigmatization.

The application of artificial intelligence in health financing: a scoping review.

INTRODUCTION: Artificial Intelligence (AI) represents a significant advancement in technology, and it is crucial for policymakers to incorporate AI thinking into policies and to fully explore, analyze and utilize massive data and conduct AI-related policies. AI has the potential to optimize healthcare financing systems. This study provides an overview of the AI application domains in healthcare financing. METHOD: We conducted a scoping review in six steps: formulating research questions, identifying relevant studies by conducting a comprehensive literature search using appropriate keywords, screening titles and abstracts for relevance, reviewing full texts of relevant articles, charting extracted data, and compiling and summarizing findings. Specifically, the research question sought to identify the applications of artificial intelligence in health financing supported by the published literature and explore potential future applications. PubMed, Scopus, and Web of Science databases were searched between 2000 and 2023. RESULTS: We discovered that AI has a significant impact on various aspects of health financing, such as governance, revenue raising, pooling, and strategic purchasing. We provide evidence-based recommendations for establishing and improving the health financing system based on AI. CONCLUSIONS: To ensure that vulnerable groups face minimum challenges and benefit from improved health financing, we urge national and international institutions worldwide to use and adopt AI tools and applications.

Research agenda for using artificial intelligence in health governance: interpretive scoping review and framework.

BACKGROUND: The governance of health systems is complex in nature due to several intertwined and multi-dimensional factors contributing to it. Recent challenges of health systems reflect the need for innovative approaches that can minimize adverse consequences of policies. Hence, there is compelling evidence of a distinct outlook on the health ecosystem using artificial intelligence (AI). Therefore, this study aimed to investigate the roles of AI and its applications in health system governance through an interpretive scoping review of current evidence. METHOD: This study intended to offer a research agenda and framework for the applications of AI in health systems governance. To include shreds of evidence with a greater focus on the application of AI in health governance from different perspectives, we searched the published literature from 2000 to 2023 through PubMed, Scopus, and Web of Science Databases. RESULTS: Our findings showed that integrating AI capabilities into health systems governance has the potential to influence three cardinal dimensions of health. These include social determinants of health, elements of governance, and health system tasks and goals. AI paves the way for strengthening the health system's governance through various aspects, i.e., intelligence innovations, flexible boundaries, multidimensional analysis, new insights, and cognition modifications to the health ecosystem area. CONCLUSION: AI is expected to be seen as a tool with new applications and capabilities, with the potential to change each component of governance in the health ecosystem, which can eventually help achieve health-related goals.

Antibacterial and Cytocompatible pH-Responsive Peptide Hydrogel.

A short peptide, FHHF-11, was designed to change stiffness as a function of pH due to changing degree of protonation of histidines. As pH changes in the physiologically relevant range, G' was measured at 0 Pa (pH 6) and 50,000 Pa (pH 8). This peptide-based hydrogel is antimicrobial and cytocompatible with skin cells (fibroblasts). It was demonstrated that the incorporation of unnatural AzAla tryptophan analog residue improves the antimicrobial properties of the hydrogel. The material developed can have a practical application and be a paradigm shift in the approach to wound treatment, and it will improve healing outcomes for millions of patients each year.

Developing an organizational capacity assessment tool and capacity-building package for the National Center for Prevention and Control of Noncommunicable Diseases in Iran.

Non-communicable diseases represent 71% of all deaths worldwide. In 2015, Sustainable Development Goals, including target 3.4 of SDGs, were seated on the world agenda; "By 2030, reduce premature mortality from NCDs by one-third. More than half of the world's countries are not on track to reach SDG 3.4, and the COVID-19 crisis has hampered the delivery of essential NCD services globally, which means the premature death of millions of people and indicates the need for capacity building for health systems. We designed a tool to measure the capacity of the National Center for Non-Communicable Disease and then presented the proposed policy package to enhance the national center's organizational capacity. The data for this explanatory sequential mixed method study was collected using quantitative and qualitative approaches between February 2020 and December 2021. The tool for assessing organizational capacity for NCDs was developed, and its validity and reliability were measured. The developed tool assessed the organizational capacity by evaluating NCNCD's managers and experts. Following the quantitative phase, a qualitative phase focused on the low-capacity points revealed by the tool. The causes of low capacity were investigated, as well as potential interventions to improve capacity. The developed tool comprises six main domains and eighteen subdomains, including (Governance, Organizational Management, Human Resources Management, Financial Management, Program Management, and Relations Management) which verified validity and reliability. In seven separate National Center for Non-Communicable Disease units, the organizational capacity was measured using the designed tool. (Cardiovascular disease and hypertension; diabetes; chronic respiratory disease; obesity and physical activity; tobacco and alcohol; nutrition; and cancers). The organizational management dimensions and the sub-dimensions of the organizational structure of the Ministry of Health and Medical Education and units affiliated with the national center, in all cases, were almost one of the main challenges that affected the country's capacity to fight against NCDs. However, all units had a relatively good situation in terms of governance (mission statement, vision, and written strategic plan). The content analysis of experts' opinions on the low-capacity subdomains highlighted challenges and recommended capacity-building interventions. Transparency in methods and processes is necessary to allocate funding among various health programs and evaluate their effects through cost-effectiveness indicators. This study identified weak points or areas where capacity building is required. The root causes of low capacity and interventions to build capacity are listed in each dimension of the tool. Some of the proposed interventions, such as strengthening organizational structures, have the potential to impact other domains. Improving organizational capacity for NCDs can assist countries to achieve national and global goals with greater efficiency.

Antimicrobial PVA Hydrogels with Tunable Mechanical Properties and Antimicrobial Release Profiles.

Hydrogels are broadly employed in wound healing applications due to their high water content and tissue-mimicking mechanical properties. Healing is hindered by infection in many types of wound, including Crohn's fistulas, tunneling wounds that form between different portions of the digestive system in Crohn's disease patients. Owing to the rise of drug-resistant infections, alternate approaches are required to treat wound infections beyond traditional antibiotics. To address this clinical need, we designed a water-responsive shape memory polymer (SMP) hydrogel, with natural antimicrobials in the form of phenolic acids (PAs), for potential use in wound filling and healing. The shape memory properties could allow for implantation in a low-profile shape, followed by expansion and would filling, while the PAs provide localized delivery of antimicrobials. Here, we developed a urethane-crosslinked poly(vinyl alcohol) hydrogel with cinnamic (CA), p-coumaric (PCA), and caffeic (Ca-A) acid chemically or physically incorporated at varied concentrations. We examined the effects of incorporated PAs on antimicrobial, mechanical, and shape memory properties, and on cell viability. Materials with physically incorporated PAs showed improved antibacterial properties with lower biofilm formation on hydrogel surfaces. Both modulus and elongation at break could be increased simultaneously in hydrogels after both forms of PA incorporation. Cellular response in terms of initial viability and growth over time varied based on PA structure and concentration. Shape memory properties were not negatively affected by PA incorporation. These PA-containing hydrogels with antimicrobial properties could provide a new option for wound filling, infection control, and healing. Furthermore, PA content and structure provide novel tools for tuning material properties independently of network chemistry, which could be harnessed in a range of materials systems and biomedical applications.

Bacterial protease-responsive shape memory polymers for infection surveillance and biofilm inhibition in chronic wounds.

Chronic wound healing is often negatively impacted by infection. Efficient infection assessment is crucial for effective treatment, and biofilm inhibition could improve treatment efficacy. To that end, we developed a bacterial protease-responsive shape memory polymer based on a segmented polyurethane with incorporated poly(glutamic acid) peptide (PU-Pep). Poly(glutamic acid) degrades in response to bacterial proteases to trigger shape recovery of PU-Pep films that are programmed into a secondary shape. These materials have transition temperatures well above body temperature (~60°C), which enables stable storage in temporary shapes after implantation. Synthesized polymers have high shape fixity (~74%-88%), shape recovery (~93%-95%), and cytocompatibility (~100%). Strained PU-Pep samples underwent shape recovery within ≤24 h in response to the V8 enzyme from Staphylococcus aureus (S. aureus, ~50% recovery) and multiple bacteria strains (S. aureus [~40%], Staphylococcus epidermidis [~30%], and Escherichia coli [~25%]), and they had minimal shape change in response to media controls and mammalian cells. Shape recovery of strained PU-Pep samples prevented biofilm formation on the sample surfaces, and resulting attached planktonic bacteria were vulnerable to applied treatments. PU-Pep with physically incorporated antimicrobials simultaneously prevented biofilm formation and killed isolated bacteria. PU-Pep dressings displayed visible shape change and resistance to biofilm formation in in vitro and ex vivo models. In the in vitro model, PU-Pep shape change also disrupted pre-formed biofilm structures. This novel bacterial protease-responsive biomaterial could serve as a wound dressing that changes shape specifically during bacterial colonization to alert clinicians to infection and make biofilm-associated infections easier to treat.

In vitro and in vivo degradation correlations for polyurethane foams with tunable degradation rates.

Polyurethane foams present a tunable biomaterial platform with potential for use in a range of regenerative medicine applications. Achieving a balance between scaffold degradation rates and tissue ingrowth is vital for successful wound healing, and significant in vivo testing is required to understand these processes. Vigorous in vitro testing can minimize the number of animals that are required to gather reliable data; however, it is difficult to accurately select in vitro degradation conditions that can effectively mimic in vivo results. To that end, we performed a comprehensive in vitro assessment of the degradation of porous shape memory polyurethane foams with tunable degradation rates using varying concentrations of hydrogen peroxide to identify the medium that closely mimics measured in vivo degradation rates. Material degradation was studied over 12 weeks in vitro in 1%, 2%, or 3% hydrogen peroxide and in vivo in subcutaneous pockets in Sprague Dawley rats. We found that the in vitro degradation conditions that best predicted in vivo degradation rates varied based on the number of mechanisms by which the polymer degraded and the polymer hydrophilicity. Namely, more hydrophilic materials that degrade by both hydrolysis and oxidation require lower concentrations of hydrogen peroxide (1%) to mimic in vivo rates, while more hydrophobic scaffolds that degrade by oxidation alone require higher concentrations of hydrogen peroxide (3%) to model in vivo degradation. This information can be used to rationally select in vitro degradation conditions that accurately identify in vivo degradation rates prior to characterization in an animal model.

Antimicrobial Shape Memory Polymer Hydrogels for Chronic Wound Dressings.

Chronic wounds can remain open for several months and have high risks of amputation due to infection. Dressing materials to treat chronic wounds should be conformable for irregular wound geometries, maintain a moist wound bed, and reduce infection risks. To that end, we developed cytocompatible shape memory polyurethane-based poly(ethylene glycol) (PEG) hydrogels that allow facile delivery to the wound site. Plant-based phenolic acids were physically incorporated onto the hydrogel scaffolds to provide antimicrobial properties. These materials were tested to confirm their shape memory properties, cytocompatibility, and antibacterial properties. The incorporation of phenolic acids provides a new mechanism for tuning intermolecular bonding in the hydrogels and corollary mechanical and shape memory properties. Phenolic acid-containing hydrogels demonstrated an increased shape recovery ratio (1.35× higher than the control formulation), and materials with cytocompatibility >90% were identified. Antimicrobial properties were retained over 20 days in hydrogels with higher phenolic acid content. Phenolic acid retention and antimicrobial efficacy were dependent upon phenolic acid structures and interactions with the polymer backbone. This novel hydrogel system provides a platform for future development as a chronic wound dressing material that is easy to implant and reduces infection risks.

Magnetically Actuated Shape Memory Polymers for On-Demand Drug Delivery.

Repeated use of intravenous infusions to deliver drugs can cause nerve damage, pain, and infection. There is an unmet need for a drug delivery method that administers drugs on demand for prolonged use. Here, we developed magnetically responsive shape memory polymers (SMPs) to enhance control over drug release. Iron oxide magnetic nanoparticles (mnps) were synthesized and incorporated into previously developed SMPs to enable magnetically induced shape memory effects that can be activated remotely via the application of an alternating magnetic field. These materials were tested for their shape memory properties (dynamic mechanical analysis), cytocompatibility (3T3 fibroblast viability), and tunable drug delivery rates (UV−VIS to evaluate the release of incorporated doxorubicin, 6-mercaptopurine, and/or rhodamine). All polymer composites had >75% cytocompatibility over 72 h. Altering the polymer chemistry and mnp content provided methods to tune drug release. Namely, linear polymers with higher mnp content had faster drug release. Highly cross-linked polymer networks with lower mnp content slowed drug release. Shape memory properties and polymer/drug interactions provided additional variables to tune drug delivery rates. Polymers that were fixed in a strained secondary shape had a slower release rate compared with unstrained polymers, and hydrophobic drugs were released more slowly than hydrophilic drugs. Using these design principles, a single material with gradient chemistry and dual drug loading was synthesized, which provided a unique mechanism to deliver two drugs from a single scaffold with distinct delivery profiles. This system could be employed in future work to provide controlled release of selected drug combinations with enhanced control over release as compared with previous approaches.

COVID-19 mortality in patients with immunodeficiency and its predictors: a systematic review.

INTRODUCTION: Patients with immunodeficiency are usually more prone to worse outcomes of infectious diseases. However, there are some disagreements in the context of COVID-19, for example, in patients with human immunodeficiency virus (HIV). Herein, we aimed to systematically review the risk and predictors of COVID-19 mortality in people with primary or secondary immunodeficiency. METHODS: PubMed, Scopus, Web of Science, and Science Direct were searched. We followed a two-step screening process to identify eligible results. We first reviewed the title and abstract of the records and the unqualified studies were removed. Then, their full texts were evaluated based on their coherence with the purpose and inclusion/exclusion criteria, and those eligible for qualitative synthesis were included. RESULTS: Twenty-two articles were included, which investigated a total of 109,326 with primary or secondary immunodeficiencies. Three studies investigated the pediatric and infant population, while other studies were conducted on the adult population. Overall, studies on both primary and secondary immunodeficiency conflicted as some reported higher and some mentioned lower mortality rates in patients with immunodeficiency. CONCLUSIONS: Overall, there were two points of view in both types of immunodeficiencies. The first is the classical viewpoint that all immunodeficient patients are at a higher risk of infection leading to a higher mortality rate. The second types of studies found that immunodeficiency might play a less important or even an inverse role in mortality rates by lowering the severity of the inflammatory response. However, it is important to take note to comorbidities, such as DM, HTN, CAD, ESRD, history of lower respiratory infection, etc., and demographic factors, such as obesity and age > 70 years, as they appear to influence the mortality rate, especially in patients with secondary immunodeficiency.

COVID-19 mortality and its predictors in the elderly: A systematic review.

Background and Aims: Older people have higher rates of comorbidities and may experience more severe inflammatory responses; therefore, are at higher risk of death. Herein, we aimed to systematically review the mortality in coronavirus disease 2019 (COVID-19) patients and its predictors in this age group. Methods: We searched PubMed, Web of Science, and Science Direct using relevant keywords. Retrieved records underwent a two-step screening process consisting of title/abstract and full-text screenings to identify the eligible studies. Results: Summarizing findings of 35 studies demonstrated that older patients have higher mortality rates compared to the younger population. A review of articles revealed that increasing age, body mass index, a male gender, dementia, impairment or dependency in daily activities, presence of consolidations on chest X-ray, hypoxemic respiratory failure, and lower oxygen saturation at admission were risk factors for death. High d-dimer levels, 25-hydroxy vitamin D serum deficiencies, high C-reactive protein (≥5 mg/L) levels plus any other abnormalities of lymphocyte, higher blood urea nitrogen or lactate dehydrogenase, and higher platelet count were predictors of poor prognosis and mortality in the elderly. Studies have also shown that previous treatment with renin-angiotensin-aldosterone system inhibitors, pharmacological treatments of respiratory disorders, antibiotics, corticosteroids, vitamin K antagonist, antihistamines, azithromycin, Itolizumab (an anti-CD6 monoclonal antibody) in combination with other antivirals reduces COVID-19 worsening and mortality. Vaccination against seasonal influenza might also reduce COVID-19 mortality. Conclusion: Overall, a critical consideration is necessary for the care and management of COVID-19 in the aged population considering the drastic contrasts in manifestation and prognosis compared to other age groups. Mortality from COVID-19 is independently associated with the patient's age. Elderly patients with COVID-19 are more vulnerable to poor outcomes. Thus, strict preventive measures, timely diagnosis, and aggressive therapeutic/nontherapeutic care are of great importance to reduce acute respiratory distress syndrome and severe complications in older people.

Effects of auditory processing training on speech perception and brainstem plastisity in adolescents with autism spectrum disorders.

OBJECTIVE: Autism spectrum disorder (ASD) is a neurodevelopmental disorder. A major problem of ASD is speech perception impairment in the presence of background noise. Additionally, researchers have reported temporal auditory processing impairment in patients with ASD. In the present study, we evaluated the effects of a temporal-based training program on improvement of speech perception in the presence of noise using the speech auditory brainstem response (sABR). MATERIALS & METHODS: Twenty-eight adolescents with high functional ASD with the mean age of 14.35±1.86 years were randomly selected and divided into an ASD group (11 males and three females) and a control group (13 males and one female). All the subjects had a normal hearing and intelligence threshold and had no history of neurological disorder.A speech perception test was performed in signal-to-noise ratios of 0 and +10. The intervention group received a temporal processingbased auditory training program, and the control group received a conventional training program. A P-value of <0.05 was considered significant. RESULTS: After training, speech perception in the presence of noise was significantly higher (P <0.001) and the latency of all sABR waves was lower in the intervention group compared to the control group. CONCLUSION: Improvement of speech perception in noisy environments and the reduced latency of sABR waves following a temporal processingbased training program highlight the role of brainstem neural plasticity in speech processing.

Auditory brainstem response to speech in children with high functional autism spectrum disorder.

Auditory brainstem response (ABR) provides useful information about the auditory brainstem pathway. However, there is little known about the subcortical speech processing in individuals with autism spectrum disorder (ASD). The aim of the present study was to investigate the subcortical speech processing in children with high functioning ASD. Twenty-eight children with ASD, with a mean age of 14.36 ± 1.86, and 28 typically developing (TD) children, with a mean age of 14.99 ± 1.92, were selected from Rofeydeh Rehabilitation Hospital (Tehran, Iran), and speech ABR (sABR) with a 40 ms synthetic /da/ syllable stimulus was recorded. There was no significant difference between the two groups in terms of age and IQ. Latencies of all waves in sABR and duration of V-A complex were significantly longer in children with ASD than in TD children. It was concluded that patients with ASD have deficits in the temporal neural encoding of speech at the brainstem level. Further studies are needed to generalize this result.

Finite element simulation of fracture in a restored premolar tooth using high aspect ratio elements

Abstract Introduction The term cracked tooth syndrome refers to an incomplete fracture of a vital posterior tooth that involves the dentin and occasionally extends into the pulp. There is a very limited number of publications trying to model dentin crack growth using numerical techniques. Therefore, it is essential to numerically model this phenomenon in order to improve the clinical procedures. Methods A 2D finite element model is proposed to simulate crack initiation and propagation in a restored premolar tooth. The geometric model was based on computed tomography data. A special finite element technique, named mesh fragmentation technique, is used to model and analyze the behavior of the tooth. This technique was used to model cracks in quasi-brittle materials based on the use of interface solid finite elements with high aspects ratio. A tension damage constitutive relation between stresses and strains consistent with the continuous strong discontinuity approach is used to describe crack formation and propagation. Results The main aspects of modeling technique and procedures are explained in detail as well as the whole results, including both elastic and fracture analyses of the restored tooth. Conclusion The results of the current fracture analysis show that, under various loading conditions, there is no crack initiation in the restored tooth under typical loading magnitude. However, in the case of tooth with a pre-existing crack, which can be aroused during the restoration process, a crack propagation was observed, while they did not reach a critical fracture state.

Preconcentration and determination of lead ions in fish and mollusk tissues by nanocomposite of Fe3O4@graphene oxide@polyimide as a solid phase extraction sorbent.

The separation and pre-concentration of pb2+ ions from mollusk and fish samples were performed by nanocomposite of magnetic graphene oxide-polyimide, as an efficient solid-phase extraction sorbent. The nanocomposite was characterized by field emission scanning electron microscopy, Fourier transform infrared spectroscopy and energy-dispersive X-ray spectroscopy. The parameters affecting the extraction processes including: amount of adsorbent, adsorption and desorption times, type and volume of the eluent solvent and interfering ions of the sample were investigated and optimized. The calibration curve was linear in the concentration ranges of 0.8-400µgL-1 (R2=0.998). The limit of detection and quantification were obtained as 0.25µgL-1 and 0.80µgL-1, respectively. The relative standard deviation was 7.3% and the pre-concentration factor was 141. A gastropod, Trochus erithreus, and a muscle tissue of fish, Otolithes ruber, were analyzed as real samples and good relative spiked recoveries (95-106%) were obtained.

Can physiologic menstrual cycle change serum lamotrigine concentration?

PURPOSE: The present study aimed to compare the serum LTG levels during the early-/mid-follicular (low estradiol) and mid-luteal (high estradiol) phases of the physiologic menstrual cycle. METHOD: In a cross-sectional study, 20 women with epilepsy were recruited. Participants had been on monotherapy with LTG for at least two months. All the subjects had normal menstrual cycles. Blood samples for each patient were taken whilst fasting during the early-/mid-follicular (Days 3-5) and mid-luteal phases (Days 20-24). All samples were analyzed in batched assays. A comparison of the serum LTG levels was carried out using the Mann-Whitney U test Data were analyzed with the SPSS program, version 16 (SPSS Inc., Chicago, IL), p-values below 0.05 were considered significant. RESULTS: The mean serum LTG levels for the early-/mid-follicular and mid-luteal phases were 4.28±2.76 mg/ml (SD) and 3.86±2.06 mg/ml (SD), respectively. There was no statistically significant difference in serum LTG level between the (low estradiol) early-/mid-follicular and (high estradiol) mid-luteal phases in our patients (p-value=0.23). CONCLUSION: The serum level of LTG does not alter significantly during the menstrual cycle.