On the effect of friction on tibiofemoral joint kinematics

The effect of friction on nonlinear dynamics and vibration of total knee arthroplasties is yet to be investigated and understood. This research work aims at studying the influence of friction on nonlinear dynamics, friction-induced vibration, and damage of tibiofemoral joints. For this purpose, a spatial dynamic knee model is developed using an asymmetric nonlinear elastic model accounting for knee joint ligaments and a penalty contact model to compute normal contact stresses in the joint while contact detection is treated such that the associated computational time is reduced. Several friction models are considered and embedded in the dynamic model to estimate tangential friction forces in the knee joint. External loads and moments, due to the presence of all soft tissues, e.g., muscles and hip-joint reaction forces, applied to the femoral bone are determined using a musculoskeletal approach. In the post-processing stage, damage, i.e., wear and creep, are estimated using three wear models and an empirical creep formulation, respectively. In addition, a FFT analysis is performed to evaluate likely friction-induced vibration of tibiofemoral joints. Mesh density analysis is performed and the methodology is assessed against outcomes available in the literature. It can be concluded that friction influences not only the tribology, but also dynamics of the knee joint, and friction-induced vibration is likely to take place when the friction coefficient increases

Low vitamin D serum level is associated with HDL-C dyslipidemia and increased serum thrombomodulin levels of insulin-resistant individuals

Background: Insulin-resistant individuals are known to have dyslipidemia and are predicted to be at high risk of cardiovascular events. Vitamin D deficiency was shown to be associated with dyslipidemia; however, the type of dyslipidemia associated with vitamin D deficiency in insulin-resistant individuals is not determined. Furthermore, there is evidence linking insulin resistance with low-grade inflammation suggesting levels of pro-inflammatory cytokines to be increased in insulin-resistant states. Objective: This study was performed to evaluate the impact of vitamin D deficiency, defined as serum level of 25(OH)D below 20 ng/mL, on lipid profile and inflammatory markers such as interleukin (IL-6) and IL-8, as well as soluble thrombomodulin (TM) in the serum of insulin-resistant individuals. Methods: A total of 4114 individuals had simultaneous serum 25(OH)D, insulin, and lipid panel testing during 2013 as part of the United Arab Emirates National Diabetes and Lifestyle (UAEDIAB) study. Multivariate logistic regression analysis was used to assess the association between serum level of 25(OH)D and lipid profile in insulin-sensitive versus-resistan t individuals. The lipid panel was stratified into high total cholesterol (TC: >6.2 mmol/L), high low-density lipoprotein-cholesterol (LDL-C: >2.59 mmol/L), high triglycerides (TG: >2.3 mmol/L), and low high-density lipoprotein-cholesterol (HDL-C: <1.55 mmol/L) dysli-pidemia. Furthermore, the immunomodulatory and vasculoprotective effects of 25(OH)D were assessed by measuring the levels of IL-6, IL-8, and soluble TM in serum using ELISA. Results: More than half of the 4114 individuals were insulin resistant (n=2760, 67%) and around one-fifth of them were vitamin D-deficient (n=796, 19%). After adjusting for age, gender, body mass index, smoking, ethnicity, and educational level, the only dyslipidemia associated with vitamin D-deficient-insulin-resistant individuals (OR 2.09 [95]; P=0.009) was lower HDL-C. Furthermore, deficient 25(OH)D individuals with low HDL-C levels had higher circulatory IL-6 and IL-8 levels, and higher serum soluble TM compared to individuals with sufficient 25(OH)D and normal lipid profiles (median, IL-6 pg/mL 0.82 vs 1.71, P=0.001; median, IL-8 pg/mL 51.31 vs 145.6, P=0.003; and median, soluble TM ng/mL 5.19 vs 7.38, P<0.0001; in sufficient vs deficient groups, respectively). Conclusion: The results of our study showed that in insulin-resistant individuals, vitamin Ddeficiency status is associated with HDL-C dyslipidemia and higher serum inflammatory and endothelial damage markers

How Islamic are Islamic Countries?

In the post 9/11 era, there is growing interest in the complex relationship between religion,\ud economics, finance, politics, law, and social behavior. This has brought with it a disagreement\ud on how to investigate the impact of religiosity, whether religion affects the economic, political,\ud and social outlook of countries or whether these factors affect religiosity? In other words, should\ud religion be viewed as a dependent or an independent variable? In this paper we ask what we\ud believe to be the precursor question to such linkages, namely, do self-declared Islamic countries,\ud as attested by membership in the OIC (Organization of Islamic Conference), embrace policies\ud that are founded on Islamic teachings? We believe that only once this question is addressed can\ud one begin to estimate how Islam adherence to Islam may affect economic, political and social\ud behavior. In the first part of the paper we present what we believe should be the characteristics and\ud scaffolding of an “Islamic” country. We base our depiction on the Quran, and the life, practices\ud and sayings of the Prophet Mohammad – the two principal channels that provide Muslims with\ud the road map. In the second part, we develop an index to measure the “Islamicity” of Islamic and\ud non-Islamic countries. This IslamicityIndex (or I2\ud ) measures 208 countries adherence to Islamic\ud principles using four sub-indices related to economics, legal and governance, human and political\ud rights, and international relations.\ud KEYWORDS: Islam, economic development, index, religion, economics, finance, politics, law,\ud socia

Dihydrofolate Reductase Gene Variations in Susceptibility to Disease and Treatment Outcomes

Dihydrofolate reductase (DHFR) catalyzes the reduction of dihydrofolate to tetrahydrofolate (THF). THF is needed for the action of folate-dependent enzymes and is thus essential for DNA synthesis and methylation. The importance of this reaction is demonstrated by the effectiveness of antifolate medications used to treat cancer by inhibiting DHFR, thereby depleting THF and slowing DNA synthesis and cell proliferation. Due to the pivotal role that DHFR plays in folate metabolism and cancer treatment, changes in the level of DHFR expression can affect susceptibility to a variety of diseases dependent on folate status such as spina bifida and cancer. Likewise, variability in DHFR expression can affect sensitivity to anti-cancer drugs such as the folate antagonist methotrexate. Alterations in DHFR expression can be due to polymorphisms in the DHFR gene. Several variations have recently been described in DHFR, including promoter polymorphisms, the 19-bp deletion allele and variations in 3’UTR. These polymorphisms seem to be functional, affecting mRNA levels through various interesting mechanisms, including regulation through RNA interference. Several groups have assessed the association of these polymorphisms with folate levels, risk of cancer and spina bifida as well as the outcome of diseases treated with MTX. The latter may lead to different treatment schedules, improving treatment efficacy and/or allowing for a reduction in drug side effects. This review will summarize present knowledge regarding the predictive potential of DHFR polymorphisms in disease and treatment

A Test Collection of Synthetic Documents for Training Rankers:ChatGPT vs. Human Experts

We investigate the usefulness of generative large language models (LLMs) in generating training data for cross-encoder re-rankers in a novel direction: generating synthetic documents instead of synthetic queries. We introduce a new dataset, ChatGPT-RetrievalQA, and compare the effectiveness of strong models fine-tuned on both LLM-generated and human-generated data. We build ChatGPT-RetrievalQA based on an existing dataset, the human ChatGPT comparison corpus (HC3), consisting of multiple public question collections featuring both human- and ChatGPT-generated responses. We fine-tune a range of cross-encoder re-rankers on either human-generated or ChatGPT-generated data. Our evaluation on MS MARCO DEV, TREC DL'19, and TREC DL'20 demonstrates that cross-encoder re-ranking models trained on LLM-generated responses are significantly more effective for out-of-domain re-ranking than those trained on human responses. For in-domain re-ranking, however, the human-trained re-rankers outperform the LLM-trained re-rankers. Our novel findings suggest that generative LLMs have high potential in generating training data for neural retrieval models and can be used to augment training data, especially in domains with less labeled data. ChatGPT-RetrievalQA presents various opportunities for analyzing and improving rankers with both human- and LLM-generated data. Our data, code, and model checkpoints are publicly available.</p

Shear deformation theories for elastic buckling of fluid-infiltrated porous plates: An analytical approach

In this paper, Reddy's higher-order and Mindlin's first-order plate theories are used for buckling analysis of porous rectangular plates subjected to various types of mechanical loading. The condition of the internal pores is considered to be either free of or saturated by fluid. Biot's theory of poroelasticity is thereby employed to model the behaviour of fluid. Distribution of pores is assumed to vary through the thickness according to an asymmetric distribution. For each displacement field considered, five highly coupled partial differential equations are derived by means of variational principle. These systems of equations are first decoupled through an efficient method, and then solved analytically for Levy-type boundary conditions. Accuracy of the approach is examined by comparing the obtained results with those available in literature. Eventually, comprehensive parametric studies are provided to investigate the effects of geometrical parameters, boundary conditions, loading conditions, porosity coefficient and pore fluid compressibility on the buckling response of the system. The results suggest that a structure with higher equivalent rigidity is met, when its corresponding internal pores are saturated by fluid. The results of the current work can be considered as a benchmark for future studies

Enhanced Expression of Autoantigens During SARS-CoV-2 Viral Infection

Immune homeostasis is disturbed during severe viral infections, which can lead to loss of tolerance to self-peptides and result in short- or long-term autoimmunity. Using publicly available transcriptomic datasets, we conducted an in-silico analyses to evaluate the expression levels of 52 autoantigens, known to be associated with 24 autoimmune diseases, during SAR-CoV-2 infection. Seven autoantigens (MPO, PRTN3, PADI4, IFIH1, TRIM21, PTPRN2, and TSHR) were upregulated in whole blood samples. MPO and TSHR were overexpressed in both lung autopsies and whole blood tissue and were associated with more severe COVID-19. Neutrophil activation derived autoantigens (MPO, PRTN3, and PADI4) were prominently increased in blood of both SARS-CoV-1 and SARS-CoV-2 viral infections, while TSHR and PTPRN2 autoantigens were specifically increased in SARS-CoV-2. Using single-cell dataset from peripheral blood mononuclear cells (PBMCs), we observed an upregulation of MPO, PRTN3, and PADI4 autoantigens within the low-density neutrophil subset. To validate our in-silico analysis, we measured plasma protein levels of two autoantigens, MPO and PRTN3, in severe and asymptomatic COVID-19. The protein levels of these two autoantigens were significantly upregulated in more severe COVID-19 infections. In conclusion, the immunopathology and severity of COVID-19 could result in transient autoimmune activation. Longitudinal follow-up studies of confirmed cases of COVID-19 could determine the enduring effects of viral infection including development of autoimmune disease

Prediabetes and diabetes prevalence and risk factors comparison between ethnic groups in the United Arab Emirates

The economic growth has paralleled the rise of diabetes and its complications in multiethnic population of United Arab Emirates (UAE). Previous studies have shown that characteristics of diabetes is variable across different ethnicities. The objective of this study was to compare diabetes prevalence and risk factors between UAE nationals and different expatriate's ethnic groups in UAE using data from UAE National Diabetes and Lifestyle Study (UAEDIAB). The UAE nationals made one-fourth (n = 797, 25%) of total cohort and the remaining 75% belonged to immigrants. Across different ethnicities, adjusted prevalence of prediabetes ranged from 8% to 17%, while adjusted prevalence of newly diagnosed diabetes ranged from 3% to 13%. UAE nationals, Arabs non-nationals and Asians had the highest number of pre-diabetic as well as newly diagnosed diabetic patients. Adjusted prevalence of diabetes was highest in UAE nationals (male 21% and female 23%) as well as Asian non-Arabs (male 23% and female 20%), where 40% of both groups fell under the range of either prediabetes or diabetes conditions. Multivariate factors of diabetes versus non-diabetes included older age, ethnicities of Asian non-Arabs and local UAE nationals, family history of diabetes, obesity, snoring, decreased level of high density lipoprotein, elevated levels of triglycerides and blood pressure. In conclusion, diabetes prevalence and risk factors vary across the different ethnic groups in UAE, and hence interventions towards identification and prevention of diabetes should not treat all patients alike