Stent retriever thrombectomy is a pre-eminent treatment modality for large vessel ischaemic stroke. Simulation of thrombectomy could help understand stent and clot mechanics in failed cases and ...provide a digital testbed for the development of new, safer devices. Here, we present a novel,
thrombectomy method using a hybrid finite-element analysis (FEA) and smoothed particle hydrodynamics (SPH). Inspired by its biological structure and components, the blood clot was modelled with the hybrid FEA-SPH method. The Solitaire self-expanding stent was parametrically reconstructed from micro-CT imaging and was modelled as three-dimensional finite beam elements. Our simulation encompassed all steps of mechanical thrombectomy, including stent packaging, delivery and self-expansion into the clot, and clot extraction. To test the feasibility of our method, we simulated clot extraction in simple straight vessels. This was compared against
thrombectomies using the same stent, vessel geometry, and clot size and composition. Comparisons with benchtop tests indicated that our model was able to accurately simulate clot deflection and penetration of stent wires into the clot, the relative movement of the clot and stent during extraction, and clot fragmentation/embolus formation. In this study, we demonstrated that coupling FEA and SPH techniques could realistically model stent retriever thrombectomy.
•New mixing method improved the early compressive strength of concrete.•Longer immersion time of glass powder in water improved the compressive strength of concrete up to 145%.•Packing and pozzolanic ...reaction are responsible on the increase of the compressive strength at early age while the pozzoalnic reactivity is the responsible later.
The goal of this work is to investigate the effect of immersion time of glass powder (GP) in water before mixing it with the other concrete ingredients on the fresh and hardened properties of concrete. Six immersion times (0, 1, 2, 3, 6 and 12 h) were investigated with different amount of GP as cement replacement (0, 2.5, 5, 10 and 20%).
The dissolution of GP in water leads to form more Na ions than Ca ions, because Na ions have less mobility than Ca ions. The concentration of Na decreased as a function of immersion time as it bonds with the SiO2 on the surface of GP particles.
Immediately after putting the glass powder in the water, the workability of concrete decreased with the increase of GP content due to the sorption of water molecules on GP particles. As the immersion time increased the workability of concrete increased with the amount of glass powder due to the bleeding effect of the water from the GP.
The optimum compressive strength was obtained at 2.5 and 5% GP mixes and at 3 h and 6 h immersion time. At early age, the higher compressive strength is originated from the double effect of the development of pozzolanic reaction due to the increase of the free ions in the water before mixing with the concrete and the packing filling effect of glass powder. The densification of the transitional zone between the cement paste and the aggregate leads to higher compressive strength of concrete. Later, at long curing time, the increase of the compressive strength is correlated to the progress of the pozzolanic reaction of the GP.
Rationale
The Lipidyzer platform was recently updated on a SCIEX QTRAP 6500+ mass spectrometer and offers a targeted lipidomics assay including 1150 different lipids. We evaluated this targeted ...approach using human plasma samples and compared the results against a global untargeted lipidomics method using a high‐resolution Q Exactive HF Orbitrap mass spectrometer.
Methods
Lipids from human plasma samples (N = 5) were extracted using a modified Bligh–Dyer approach. A global untargeted analysis was performed using a Thermo Orbitrap Q Exactive HF mass spectrometer, followed by data analysis using Progenesis QI software. Multiple reaction monitoring (MRM)‐based targeted analysis was performed using a QTRAP 6500+ mass spectrometer, followed by data analysis using SCIEX OS software. The samples were injected on three separate days to assess reproducibility for both approaches.
Results
Overall, 465 lipids were identified from 11 lipid classes in both approaches, of which 159 were similar between the methods, 168 lipids were unique to the MRM approach, and 138 lipids were unique to the untargeted approach. Phosphatidylcholine and phosphatidylethanolamine species were the most commonly identified using the untargeted approach, while triacylglycerol species were the most commonly identified using the targeted MRM approach. The targeted MRM approach had more consistent relative abundances across the three days than the untargeted approach. Overall, the coefficient of variation for inter‐day comparisons across all lipid classes was ∼ 23% for the untargeted approach and ∼ 9% for the targeted MRM approach.
Conclusions
The targeted MRM approach identified similar numbers of lipids to a conventional untargeted approach, but had better representation of 11 lipid classes commonly identified by both approaches. Based on the separation methods employed, the conventional untargeted approach could better detect phosphatidylcholine and sphingomyelin lipid classes. The targeted MRM approach had lower inter‐day variability than the untargeted approach when tested using a small group of plasma samples. These studies highlight the advantages in using targeted MRM approaches for human plasma lipidomics analysis.
The number of people suffering from Alzheimer's disease (AD) is increasing rapidly every year. One aspect of AD that is often overlooked is the disproportionate incidence of AD among African ...American/Black populations. With the recent development of novel assays for lipidomics analysis in recent times, there has been a drastic increase in the number of studies focusing on changes of lipids in AD. However, very few of these studies have focused on or even included samples from African American/Black individuals samples. In this study, we aimed to determine if the lipidome in AD is universal across non-Hispanic White and African American/Black individuals. To accomplish this, a targeted mass spectrometry lipidomics analysis was performed on plasma samples (
= 113) obtained from cognitively normal (CN,
= 54) and AD (
= 59) individuals from African American/Black (
= 56) and non-Hispanic White (
= 57) backgrounds. Five lipids (PS 18:0_18:0, PS 18:0_20:0, PC 16:0_22:6, PC 18:0_22:6, and PS 18:1_22:6) were altered between AD and CN sample groups (
value < 0.05). Upon racial stratification, there were notable differences in lipids that were unique to African American/Black or non-Hispanic White individuals. PS 20:0_20:1 was reduced in AD in samples from non-Hispanic White but not African American/Black adults. We also tested whether race/ethnicity significantly modified the association between lipids and AD status by including a race × diagnosis interaction term in a linear regression model. PS 20:0_20:1 showed a significant interaction (
= 0.004). The discovery of lipid changes in AD in this study suggests that identifying relevant lipid biomarkers for diagnosis will require diversity in sample cohorts.
African American/Black adults have a disproportionate incidence of Alzheimer's disease (AD) and are underrepresented in biomarker discovery efforts.
This study aimed to identify potential diagnostic ...biomarkers for AD using a combination of proteomics and machine learning approaches in a cohort that included African American/Black adults.
We conducted a discovery-based plasma proteomics study on plasma samples (N = 113) obtained from clinically diagnosed AD and cognitively normal adults that were self-reported African American/Black or non-Hispanic White. Sets of differentially-expressed proteins were then classified using a support vector machine (SVM) to identify biomarker candidates.
In total, 740 proteins were identified of which, 25 differentially-expressed proteins in AD came from comparisons within a single racial and ethnic background group. Six proteins were differentially-expressed in AD regardless of racial and ethnic background. Supervised classification by SVM yielded an area under the curve (AUC) of 0.91 and accuracy of 86%for differentiating AD in samples from non-Hispanic White adults when trained with differentially-expressed proteins unique to that group. However, the same model yielded an AUC of 0.49 and accuracy of 47%for differentiating AD in samples from African American/Black adults. Other covariates such as age, APOE4 status, sex, and years of education were found to improve the model mostly in the samples from non-Hispanic White adults for classifying AD.
These results demonstrate the importance of study designs in AD biomarker discovery, which must include diverse racial and ethnic groups such as African American/Black adults to develop effective biomarkers.
It has been over three decades since the term “sustainable development” was coined in Brundtland’s report in 1987, and 28 years have passed since the world’s first sustainability assessment method ...for buildings was founded by the Building Research Establishment in UK in 1990. During these three decades, many sustainability standards, codes, and rating systems were created and used to help in designing, constructing, maintaining, rating, and labeling buildings with attaining the principles of sustainability. Yet by looking at the Arab world at the beginning of 2019, one can argue that, although the Arab countries have dedicated the effort and budget to save energy, water, and natural resources, the region as a whole is still struggling to shift the paradigm of the building industry from conventional to sustainable. This struggle raises some questions; are there any challenges that Arab countries must overcome to leap forward to a prosperous sustainable building design and construction practices? Why are existing green building rating systems such as Estidama in United Arab Emirates, global sustainability assessment system (GSAS) in Qatar, and ARZ in Lebanon lagging behind the trends of green building rating systems in the developed countries? What are the coordinated steps needed to expedite this movement across the region? The current study explores the limits and potentials of the green building industry in the Arab world through analysis of the green building initiatives, academic scholarship activities in architecture and engineering sectors, and feedback from green building professionals across the Arab world. This article introduces a theoretical framework to expedite the green building movement in the Arab region; the framework is shaped by the environmental, social, and economic factors that are crucial to the transformation of the building industry from conventional to sustainable. The study seeks to support a line of research that could help governments in the Arab world catch up with the global green building trends.
Here we present a plasma proteomics dataset that was generated to understand the importance of self-reported race for biomarker discovery in Alzheimer's disease. This dataset is related to the ...article “Why inclusion matters for Alzheimer's disease biomarker discovery in plasma” 1. Plasma samples were obtained from clinically diagnosed Alzheimer's disease and cognitively normal adults of African American/Black and non-Hispanic White racial and ethnic backgrounds. Plasma was immunodepleted, digested, and isobarically tagged with commercial reagents. Tagged peptides were fractionated using high pH fractionation and resulting fractions analysed by liquid chromatography – mass spectrometry (LC-MS/MS & MS3) analysis on an Orbitrap Fusion Lumos mass spectrometer. The resulting data was processed using Proteome Discoverer to produce a list of identified proteins with corresponding tandem mass tag (TMT) intensity information.
To identify the frequency and reasons of operations cancellation in 25 Makkah region hospitals in Saudi Arabia.
Retrospective evaluation of the rate of surgery cancellation in 25 hospitals of Makkah ...region was performed in this study. The data of scheduled surgeries from 15 different surgical specialties was collected from January to December 2013. Frequency and reasons of cancellation of elective surgical cases in different specialty were studied with a view to recommend suggestions for improvement. Data was analyzed on SPSS -16.
There are 120 operating rooms (OR) in 25 Makkah region hospitals and during the year 2013, a total of 16,211 surgery cases were listed, and 1,238 (7.6%) cases were canceled. Contribution to total cancellation was highest in orthopedic 33.8% followed by general surgery 27.5%, obstetrics 7.7% and ENT 5.2%. According to category, 42.81% rate of cancellation was patient related, 20.03% facility related, 9.45% due to improper work-up, 1.45% associated with anesthesia, 7.19% related to surgeons, and 18.90% other/and not recorded reasons.
Present study found 7.6% cancelation rate in Makkah region hospitals and three most common causes for cancellations were patients related, facility related and improper work-up.
To evaluate the diseases pattern among pilgrims attending the 2 Holy Mosque (Haram) Health Care Centers during the Hajj season 2013 (Hijra 1434).
In this cross-sectional study, data was collected ...from 2 medical centers located in the Holy Mosque in Makkah city, Saudi Arabia, from the first of Dhul-Hijjah to sixteenth Dhul-Hijjah 1434. The present study was completed in 16 days (6th October to 21st October 2013).
Over 16 days, 1008 patients attended the medical centers during Hajj 1434, (2013), out of which 554 (55%) were males and 454 (45%) were females. Most of the patients were Egyptians (n=242, 24%), followed by Saudis (n=116, 11.5%), Pakistani (n=114, 11.3%), Turkish (n=50, 5%), and other nationalities (n=404). According to age distribution, mostly were in the 51-60 years age group (n=237, 23.5%), followed by other age groups. Out of 1008 patients, 842 (83.5%) patients were treated and subsequently discharged, while 166 patients (16.5%) were referred to the tertiary centers. According to the diseases pattern, most of the patients were suffering from respiratory problems (n=177, 17.6%) followed by skin diseases (n=158, 15.7%), gastrointestinal tract (GIT) diseases (n=133, 13.2%), and others.
Most of the patients were suffering from respiratory problems followed by skin and GIT diseases, and less than 25% of patients were referred to tertiary care centers.
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•First systematic review of text summarization in the biomedical domain.•The study found a predominance of methods producing extractive summaries.•Multiple documents were used as the ...source for summarization.•Natural language processing, and hybrid techniques were prominently used.•Research is needed on the application of text summarization in real settings.
The amount of information for clinicians and clinical researchers is growing exponentially. Text summarization reduces information as an attempt to enable users to find and understand relevant source texts more quickly and effortlessly. In recent years, substantial research has been conducted to develop and evaluate various summarization techniques in the biomedical domain. The goal of this study was to systematically review recent published research on summarization of textual documents in the biomedical domain.
MEDLINE (2000 to October 2013), IEEE Digital Library, and the ACM digital library were searched. Investigators independently screened and abstracted studies that examined text summarization techniques in the biomedical domain. Information is derived from selected articles on five dimensions: input, purpose, output, method and evaluation.
Of 10,786 studies retrieved, 34 (0.3%) met the inclusion criteria. Natural language processing (17; 50%) and a hybrid technique comprising of statistical, Natural language processing and machine learning (15; 44%) were the most common summarization approaches. Most studies (28; 82%) conducted an intrinsic evaluation.
This is the first systematic review of text summarization in the biomedical domain. The study identified research gaps and provides recommendations for guiding future research on biomedical text summarization.
Recent research has focused on a hybrid technique comprising statistical, language processing and machine learning techniques. Further research is needed on the application and evaluation of text summarization in real research or patient care settings.
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