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Enzymatic reactions are essential for most cellular reactions and ubiquitous in living organisms. In the present study, we explore the pivotal role of the reverse reaction in enzymatic reactions. It is a powerful noise-buffering motif. By SSA (stochastic simulation algorithm), a remarkable 32% reduction of product CV (coefficient of variation) was observed. To better understand the causes, we split the upstream noise. The product CV reduction is more than 35% for the noise inherited from the enzyme but merely 6%-21% for that from the substrate. It implies that the system applies different strategies to different upstream noises. We identified two leading causes responsible for noise attenuation. A cell is well designed to control its intracellular noise, and to acquire wisdom from nature is always enjoyable.

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In normal cold rolling, the elastic deformation of the strip is typically ignored because of the dominant plastic deformation. However, this neglect may introduce additional errors when the strip is very thin. The aim of this study is to investigate the characteristics of the deformation region and thickness reduction in the asymmetrical rolling of ultra-thin strips. Mathematical models were developed based on the slab method, with consideration of the elastic deformation of the strips, and employed in the simulation calculation. The percentage of the three zones and the thickness reduction were analyzed using the simulation results. An increase in the speed ratio results in an increase in the reduction ratio, which is influenced by parameters, such as front tension, back tension, friction coefficient, and entry thickness. The elastic deformation of the strip reduces the tension and the roll pressure and causes the reduction ratio to decrease. The findings and conclusions of this study may be helpful to the mill operating in the asymmetrical rolling process of ultra-thin strips.

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Mechanical parameters, time consumption and energy consumption are important considerations in the application of a certain rolling process. This study aims to investigate characteristics of the roll force, roll torque, roll power, rolling time and total work in multi-pass asymmetrical rolling of strip. Mathematic models were built using the slab method to calculate parameters in the asymmetrical rolling process, and the characteristics of these parameters were analyzed on the basis of simulation results. Mechanical parameters are affected by the change of deformation region type. When the speed ratio is less than the critical speed ratio, the roll force, absolute values of roll torque and roll power are found to increase with the increase in the speed ratio. After the speed ratio reaches the critical speed ratio, the roll force, roll torque and lower roll power keep constant, but the upper roll power continues increasing. The upper roll torque and upper roll power required by asymmetrical rolling are much greater than that by symmetrical rolling, which indicates that stronger drive shafts and more powerful drive motors are required by asymmetrical rolling. Compared with symmetrical rolling, asymmetrical rolling requires less roll force to obtain the same thickness reduction, especially for thin and hard strips. Rolling time can be saved at the cost of more energy consumption by using asymmetrical rolling with the same roll force to attain the same final thickness. The results and conclusions of this study can provide a reference for mill design and application of asymmetrical rolling in strip manufacturing.

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In the pharmacokinetic analysis of ethanol after oral administration, only single- or two-compartment models are used, but their precision in estimating pharmacokinetic parameters might be insufficient. In a recent study, pharmacokinetic analysis using a modified Norberg three-compartment model was performed after oral administration of differently sweetened alcoholic solutions and compared to pharmacokinetic analysis using the classic Widmark model. On three occasions, eight male volunteers consumed differently sweetened alcoholic solutions: non-sweetened, sweetened with sucrose, and sweetened with steviol glycoside. Blood ethanol concentration was determined from samples obtained at t = 15, 30, 60, 90, 120, 180 min after consumption. Pharmacokinetic analysis was performed model independently, using the classic Widmarks model and using the modified Norberg model. Results showed that estimated pharmacokinetic parameters depend on the type of model used. The classic Widmark model in particular overestimated the fraction of absorbed ethanol from the gastrointestinal system to systemic circulation. Furthermore, the type of sweetener also affected pharmacokinetic parameters, although the difference was not statistically significant. In conclusion, the novel pharmacokinetic model, while being more physiological, fits experimental data better and hence is more suitable for modelling real-life alcohol consumption. In addition, the effect of natural non-caloric sweetener steviol glycoside on ethanol pharmacokinetics, analysed for the first time in the current research, might be different when compared to the common-used sweetener sucrose.

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BACKGROUND: In cases of terrorism, disasters, or mass casualty incidents, far-reaching life-and-death decisions about prioritizing patients are currently made using triage algorithms that focus solely on the patient's current health status rather than their prognosis, thus leaving a fatal gap of patients who are under- or overtriaged. OBJECTIVE: The aim of this proof-of-concept study is to demonstrate a novel approach for triage that no longer classifies patients into triage categories but ranks their urgency according to the anticipated survival time without intervention. Using this approach, we aim to improve the prioritization of casualties by respecting individual injury patterns and vital signs, survival likelihoods, and the availability of rescue resources. METHODS: We designed a mathematical model that allows dynamic simulation of the time course of a patient's vital parameters, depending on individual baseline vital signs and injury severity. The 2 variables were integrated using the well-established Revised Trauma Score (RTS) and the New Injury Severity Score (NISS). An artificial patient database of unique patients with trauma (N=82,277) was then generated and used for analysis of the time course modeling and triage classification. Comparative performance analysis of different triage algorithms was performed. In addition, we applied a sophisticated, state-of-the-art clustering method using the Gower distance to visualize patient cohorts at risk for mistriage. RESULTS: The proposed triage algorithm realistically modeled the time course of a patient's life, depending on injury severity and current vital parameters. Different casualties were ranked by their anticipated time course, reflecting their priority for treatment. Regarding the identification of patients at risk for mistriage, the model outperformed the Simple Triage And Rapid Treatment's triage algorithm but also exclusive stratification by the RTS or the NISS. Multidimensional analysis separated patients with similar patterns of injuries and vital parameters into clusters with different triage classifications. In this large-scale analysis, our algorithm confirmed the previously mentioned conclusions during simulation and descriptive analysis and underlined the significance of this novel approach to triage. CONCLUSIONS: The findings of this study suggest the feasibility and relevance of our model, which is unique in terms of its ranking system, prognosis outline, and time course anticipation. The proposed triage-ranking algorithm could offer an innovative triage method with a wide range of applications in prehospital, disaster, and emergency medicine, as well as simulation and research.

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We examined gene expression with DNA switching between two states, active and inactive. Subpopulations emerge from mechanisms that do not arise from trivial transcriptional heterogeneity. Although the RNA demonstrates a unimodal distribution, dimerization intriguingly causes protein bimodality. No control loop or deterministic bistability are present. In such a situation, increasing the degradation rate of the protein does not lead to bimodality. The bimodality is achieved through the interplay between the protein monomer and the formation of protein dimer. We applied Stochastic Simulation Algorithm (SSA) and found that cells spontaneously change states at the protein level. While sweeping parameters, decreasing the rate constant of dimerization severely impairs the bimodality. We also examined the influence of DNA switching. To have bimodality, the system requires a proper ratio of DNA in the active state to the inactive state. In addition to bimodality of the monomer, tetramerization also causes the bimodality of the dimer.

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The new Acute Respiratory Syndrome, COVID-19, has affected the health and the economy worldwide. Therefore, scientists have been looking for ways to understand this disease. In this context, the main objective of this study was the spatialization of COVID-19, thinking in distinguishing areas with high transmissibility yet, verifying if these areas were associated with the elderly population occurrence. The work was delineated, supposing that spatialization could support the decision-making to combat the outbreak and that the same method could be used for spatialization and prevent other diseases. The study area was a municipality near Sao Paulo Metropolis, one of Brazil's main disease epicenters. Using official data and an empirical Bayesian model, we spatialized people infected by region, including older people, obtaining reasonable adjustment. The results showed a weak correlation between regions infected and older adults. Thus, we define a robust model that can support the definition of actions aiming to control the COVID-19 spread.

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In recent years, graphene has shown great application prospects in tunable microwave devices due to its tunable conductivity. However, the electromagnetic (EM) properties of graphene, especially the dynamic tunning characteristics, are largely dependent on experimental results, and thus are unable to be effectively predicted according to growth parameters, which causes great difficulties in the design of graphene-based tunable microwave devices. In this work, we systematically explored the impact of chemical vapor deposition (CVD) parameters on the dynamic tunning range of graphene. Firstly, through improving the existing waveguide method, the dynamic tunning range of graphene can be measured more accurately. Secondly, a direct mathematical model between growth parameters and the tunning range of graphene is established. Through this, one can easily obtain needed growth parameters for the desired tunning range of graphene. As a verification, a frequency tunable absorber prototype is designed and tested. The good agreement between simulation and experimental results shows the reliability of our mathematic model in the rapid design of graphene-based tunable microwave devices.

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Background: Dysregulated interleukin (IL)-6 production can be characterised by the levels present, the kinetics of its rise and its inappropriate location. Rapid, excessive IL-6 production can exacerbate tissue damage in vital organs. In this situation, therapy with an anti-IL-6 or anti-IL-6 receptor (IL-6R) monoclonal antibody, if inappropriately dosed, may be insufficient to fully block IL-6 signalling and normalise the immune response. Methods: We analysed inhibition of C-reactive protein (CRP) - a biomarker for IL-6 activity - in patients with COVID-19 or idiopathic multicentric Castleman disease (iMCD) treated with tocilizumab (anti-IL-6R) or siltuximab (anti-IL-6), respectively. We used mathematical modelling to analyse how to optimise anti-IL-6 or anti-IL-6R blockade for the high levels of IL-6 observed in these diseases. Results: IL-6 signalling was insufficiently inhibited in patients with COVID-19 or iMCD treated with standard doses of anti-IL-6 therapy. Patients whose disease worsened throughout therapy had only partial inhibition of CRP production. Our model demonstrated that, in a scenario representative of iMCD with persistent high IL-6 production not controlled by a single dose of anti-IL-6 therapy, repeated administration more effectively inhibited IL-6 activity. In a situation with rapid, high, dysregulated IL-6 production, such as severe COVID-19 or a cytokine storm, repeated daily administration of an anti-IL-6/anti-IL-6R agent, or alternating daily doses of anti-IL-6 and anti-IL-6R therapies, could neutralise IL-6 activity. Conclusion: In clinical practice, IL-6 inhibition should be individualised based on pathophysiology to achieve full blockade of CRP production. Funding: EUSA Pharma funded medical writing assistance and provided access to the phase II clinical data of siltuximab for analysis.

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The current fertilizer recommendations for melon plantation have many limitations and exhibit deficiencies regarding future development. Therefore, in this study, the optimal quantities of fertilizer, in terms of the effects of single factors and interaction effects, are studied. There were significant interaction effects between N and P, N and K, P and K; the contents of soluble protein, vitamin C (Vc), and soluble sugar in melon could be improved using the optimal fertilization ratios. The optimal ratio of N:P:K was 2.33:1:3.85, with the amounts of N, P2O5, and K2O, respectively, being 157.5, 67.58, and 260.38 kg/hm2, yielding 8.73 g/kg of soluble protein in melon. The optimal ratio of N:P:K was 2.03:1:3.36, with amounts of N, P2O5, and K2O being 157.50, 77.40, and 260.38 kg/hm2, respectively, yielding 25.32 g/kg Vc content in melon. Finally, the optimal ratio of N:P:K was 1.53:1:3.36, with the amounts of N, P2O5, and K2O being 118.07, 77.40, respectively, and 260.38 kg/hm2, yielding 13.34% soluble sugar content in melon.

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Despite the high coverage of pertussis vaccines in high-income countries, pertussis resurgence has been reported in recent years, and has stimulated interest in the effects of vaccines and vaccination strategies. Immunoglobulin G (IgG) antibodies against pertussis toxoid (PT), filamentous hemagglutinin (FHA), and pertactin (PRN) after immunization with four doses of co-purified or component vaccines were determined by enzyme-linked immunosorbent assay (ELISA). Serological data of PT-IgG geometric mean concentrations (GMCs) over time since vaccination were used to fit the mathematical models. A total of 953 children were included in this study; 590 participants received four doses of the component acellular vaccine and 363 participants received four doses of the co-purified acellular vaccine. The GMCs and the seropositivity rate of pertussis IgG were significantly influenced by the production methods, and the immunogenicity of the component acellular vaccine was superior to that of the co-purified acellular vaccine. The fitted mathematical models for the component acellular vaccine and the co-purified acellular vaccine were Y=91.20e-0.039x and Y=37.71x-0.493, respectively. The initial GMCs of the component acellular vaccine was higher than that of the co-purified acellular vaccine, but both were similar at 72 months after immunization. Pertussis IgG levels waned over time after four doses of acellular pertussis vaccine, regardless of whether component or co-purified vaccine was used. The development and promotion of component acellular pertussis vaccines should be accelerated in China, and booster doses of pertussis vaccine in adolescents, adults, and pregnant women should be employed.

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Compound-specific isotope analysis has been demonstrated to be a powerful tool for the assessment of in situ pollutant degradation. Enrichment factor, an essential and prerequisite parameter, could be determined under simulated control laboratory in advance. However, different microbial community composition and substrate availability may significantly affect the accuracy of simulated enrichment factor. Here, a modified mathematic method of two dimensional is proposed to quantify the extent of pollutant degradation involving the break of carbon and hydrogen bond. In this new model, the laboratory cultures used to determine carbon or hydrogen enrichment factors in advance could be canceled and the key point to assess the extent of biodegradation is only determining the value of Λri (dual C-H isotope slope calculated with a self-modified model) in the field investigation. As a new and convenient method, this math model greatly facilitates the investigation of pollutant degradation extent under field conditions. Two approaches are applied to evaluate the proposed model. With our model, the estimated results based on C isotope are consistent with those measured values, while those based on H isotope are unsatisfactory. This can be attributed to the differences in accuracy of C-H isotope determinations. Overall, enrichment factors and biodegradation rates calculated with the proposed model are comparable with those measured figures.

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Lithium-sulfur (Li-S) batteries have been regarded as a promising next-generation energy storage technology for their ultrahigh theoretical energy density compared with those of the traditional lithium-ion batteries. However, the practical applications of Li-S batteries are still blocked by notorious problems such as the shuttle effect and the uncontrollable growth of lithium dendrites. Recently, the rapid development of electrospinning technology provides reliable methods in preparing flexible nanofibers materials and is widely applied to Li-S batteries serving as hosts, interlayers, and separators, which are considered as a promising strategy to achieve high energy density flexible Li-S batteries. In this review, a fundamental introduction of electrospinning technology and multifarious electrospinning-based nanofibers used in flexible Li-S batteries are presented. More importantly, crucial parameters of specific capacity, electrolyte/sulfur (E/S) ratio, sulfur loading, and cathode tap density are emphasized based on the proposed mathematic model, in which the electrospinning-based nanofibers are used as important components in Li-S batteries to achieve high gravimetric (WG ) and volume (WV ) energy density of 500 Wh kg-1 and 700 Wh L-1 , respectively. These systematic summaries not only provide the principles in nanofiber-based electrode design but also propose enlightening directions for the commercialized Li-S batteries with high WG and WV .

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Polysaccharide foulant is known to play a crucial role in membrane fouling, however the detailed influential mechanisms and the pertinence to specific structure of polysaccharides, as well as intermolecular interactions among them with and without divalent cation are still indistinct. In this study, seven polysaccharides including agarose, sodium alginate, carrageenan, pectin, starch, sodium carboxymethylcellulose (CMC) and xanthan gum, with different chain and molecular structures, were used as model foulants to investigate the role of structural and functional features of polysaccharides in membrane fouling. Two Hermia's models (classical and mass-transfer models) as well as the resistance-in-series model were used to analyze the fouling mechanism. Results show that the spatial configuration of foulant molecule is significant in membrane fouling which actually controls the resistance of gel layer formed on membrane. Polysaccharides with different properties show distinct fouling mechanisms which are in accordance with the four models described by Hermia respectively. Cations may change the interaction of polysaccharide foulant which further leads to the structural change of the gel layer. It turns out that mass-transfer model is more suitable for interpreting of crossflow filtration data. So far, little has been known about the effects of molecule structure of polysaccharides on membrane fouling. In this paper, we provide a basic database for polysaccharide fouling which will work as a theoretical basis for finding more effective measures to prevent and control membrane fouling.

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Folate receptors (FRs) are a class of valuable therapeutic target which is highly expressed on a variety of cancers. The accurate detection of the expression of FRs in different cells is conducive to improve the accuracy of FR targeted tumor therapy. Herein, a method based on nonimmobilized cell capillary electrophoresis (NICCE) combined with a mathematic model to quantify FRs on each single tumor cell was developed. At first, we studied the interactions between FA and A549, HT-29, HepG2, and U87MG cells by NICCE respectively, and calculated the kinetic parameters (Ka, k', ka, and kd). Next, we established a mathematic model to accurately determine the number of moles of FRs on per A549, HT-29, HepG2, and U87MG cell for the first time, that were (10.44 ± 0.53) × 10-19 mol, (34.32 ± 1.33) × 10-19 mol, (337.14 ± 10.11) × 10-19 mol, and (37.31 ± 2.13) × 10-19 mol. Then, these re-sults were proved to be consistent with the results of enzyme-linked immunosorbent assay (ELISA). Therefore, this method is simple, rapid, sensitive, and without protein separation or purification, which is expected to achieve clinical detection of cell membrane receptor expression level of cell membrane receptors on a single cell, which may be greatly beneficial to further clinical diagnosis and therapy.

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BACKGROUND: Survival after burn injury has steadily improved in recent decades. The models for assessing the severity of burn injury and predicting burn-associated mortality have been used for over 20 years. The predictive accuracy of these models should be reconsidered now. METHOD: In this retrospective study on all burn patients (n = 9625) admitted to the Burn Department, Southwest Hospital between 2008 and 2017, we compared the predictive performance of the four burn-severity models (Abbreviated Burn Severity Index, Ryan score, revised Baux score and Belgian Outcome of Burn Injury) by area under the receiver operating curve (AUC) and Hosmer-Lemeshow test. We developed a new model with the data from 2008 to 2012 (5006 patients) by logistic regression, data from 2013 to 2017 (4619 patients) were used for validation. RESULT: The overall mortality rate of the burn patients was 1.14%. The four previously validated burn models showed good discrimination power of death risk (AUC > 0.890) but poor fitness to the observed mortality rate (p < 0.001). Risk factors associated with mortality included sex, age, total burn area, full thickness burn area, and inhalation injury. The new logistic model was devised with high sensitivity and specificity (0.913 and 0.806, respectively) and an AUC of 0.940. The new model also had good fitness to the observed mortality of burn patients (p = 0.588). CONCLUSION: The four widely used burn models have poor accuracy in predicting burn-associated mortality, and an accurate new model was developed based on simple and objective clinical characteristics of burn patients at admission.

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BACKGROUND: Nowadays, to research and formulate an efficiency extraction system for Chinese herbal medicine, scientists have always been facing a great challenge for quality management, so that the transitivity of Q-markers in quantitative analysis of TCM was proposed by Prof. Liu recently. In order to improve the quality of extraction from raw medicinal materials for clinical preparations, a series of integrated mathematic models for transitivity of Q-markers in quantitative analysis of TCM were established. Buyanghuanwu decoction (BYHWD) was a commonly TCMs prescription, which was used to prevent and treat the ischemic heart and brain diseases. In this paper, we selected BYHWD as an extraction experimental subject to study the quantitative transitivity of TCM. STUDY DESIGN: Based on theory of Fick's Rule and Noyes-Whitney equation, novel kinetic models were established for extraction of active components. Meanwhile, fitting out kinetic equations of extracted models and then calculating the inherent parameters in material piece and Q-marker quantitative transfer coefficients, which were considered as indexes to evaluate transitivity of Q-markers in quantitative analysis of the extraction process of BYHWD. METHODS: HPLC was applied to screen and analyze the potential Q-markers in the extraction process. Fick's Rule and Noyes-Whitney equation were adopted for mathematically modeling extraction process. Kinetic parameters were fitted and calculated by the Statistical Program for Social Sciences 20.0 software. The transferable efficiency was described and evaluated by potential Q-markers transfer trajectory via transitivity availability AUC, extraction ratio P, and decomposition ratio D respectively. The Q-marker was identified with AUC, P, D. RESULTS: Astragaloside IV, laetrile, paeoniflorin, and ferulic acid were studied as potential Q-markers from BYHWD. The relative technologic parameters were presented by mathematic models, which could adequately illustrate the inherent properties of raw materials preparation and affection of Q-markers transitivity in equilibrium processing. AUC, P, D for potential Q-markers of AST-IV, laetrile, paeoniflorin, and FA were obtained, with the results of 289.9 mAu s, 46.24%, 22.35%; 1730 mAu s, 84.48%, 1.963%; 5600 mAu s, 70.22%, 0.4752%; 7810 mAu s, 24.29%, 4.235%, respectively. CONCLUSION: The results showed that the suitable Q-markers were laetrile and paeoniflorin in our study, which exhibited acceptable traceability and transitivity in the extraction process of TCMs. Therefore, these novel mathematic models might be developed as a new standard to control TCMs quality process from raw medicinal materials to product manufacturing.

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Objective To evaluate the therapeutic effect of chemotherapeutic drugs on pancreatic carcinoma based on patient-derived xenograft(PDX)models,and to screen an individualized treatment strategy. Methods Fresh human pancreatic carcinoma tissues were subcutaneously transplanted into nude mice to establish PDX models which could be stab-ly passaged. The traceability of PDX models was determined by STR analysis. The PDX models were treated with three dif-ferent clinical chemotherapeutic drugs oxaliplatin, gemcitabine and irinotecan, respectively, and the tumor volumes were measured at different times. The therapeutic effect of those drugs was assessed by TGD mathematical model and plasma CA19-9 test. Results The traceability of patient-derived xenograft samples was up to 99.99%. Compared with the con-trol group,the treatment with irinotecan and gemcitabine inhibited tumor growth significantly(P=0.001), and gemcit-abine had even better result. The minimum toxic effect in the mice was induced by irinotecan treatment,followed by gem-citabine treatment. Conclusions Pancreatic carcinoma PDX models are successfully established and can be stably pas-saged. Gemcitabine shows the most inhibitory effect on tumor growth based on TGD mathematical model assessment, and deserves to be recommended as the preferred drug for individual treatment of pancreatic carcinoma.

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BACKGROUND AND OBJECTIVE: The pullout strength of a screw is an indicator of how secure bone fragments are being held in place. Such bone-purchasing ability is sensitive to bone quality, thread design, and the pilot hole, and is often evaluated by experimental and numerical methods. Historically, there are some mathematical formulae to simulate the screw withdrawal from the synthetic bone. There are great variations in screw specifications. However, extensive investigation of the correlation between experimental and analytical results has not been reported in literature. METHODS: Referring to the literature formulae, this study aims to evaluate the differences in the calculated pullout strengths. The pullout tests of the surgical screws are measured and the sawbone is used as the testing block. The absolute errors and correlation coefficients of the experimental and analytical results are calculated as the comparison baselines of the formulae. RESULTS: The absolute error of the dental, traumatic, and spinal groups are 21.7%, 95.5%, and 37.0%, respectively. For the screws with a conical profile and/or tiny threads, the calculated and measured results are not well correlated. The formulae are not accurate indicators of the pullout strengths of the screws where the design parameters are slightly varied. However, the experimental and numerical results are highly correlated for the cylindrical screws. The pullout strength of a conical screw is higher than that of its counterpart, but all formulae consistently predict the opposite results. In general, the bony purchase of the buttress threads is securer than that of the symmetric thread. CONCLUSIONS: An absolute error of up to 51.4% indicates the theoretical results cannot predict the actual value of the pullout strength. Only thread diameter, pitch, and depth are considered in the investigated formulae. The thread profile and shape should be formulated to modify the slippage mechanism at the bone-screw interfaces and simulate the strength change in the squeezed bones, especially for the conical screw.

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INTRODUCTION: The intercellular network of cell-cell communication among osteocytes is mediated by gap junctions. Gap junctional intercellular communication (GJIC) is thought to play an important role in the integration and synchronization of bone remodeling. To further understand the mechanism of bone development it is important to quantify the difference in the GJIC capacity of young and developmentally mature osteocytes. MATERIALS AND METHODS: We first established an embryonic chick calvaria growth model to show the growth of the calvaria in embryos at 13 to 21days of age. We then applied a fluorescence recovery after photobleaching (FRAP) technique to compare the difference in the GJIC capacity of young osteocytes with that of developmentally mature osteocytes. Finally, we quantified the dye (Calcein) diffusion from the FRAP data using a mathematic model of simple diffusion which was also used to identify simple diffusion GJIC pattern cells (fitted model) and accelerated diffusion GJIC pattern cells (non-fitted model). RESULTS: The relationship between the longest medial-lateral length of the calvaria (frontal bone) and the embryonic age fit a logarithmic growth model: length=5.144×ln(day)-11.340. The morphometric data during osteocyte differentiation showed that the cellular body becomes more spindle-shaped and that the cell body volume decreased by approximately 22% with an increase in the length of the processes between the cells. However, there were no significant differences in the cellular body surface area or in the distance between the mass centres of the cells. The dye-displacement rate in young osteocytes was significantly higher than that in developmentally mature osteocytes: dye displacement only occurred in 26.88% of the developmentally mature osteocytes, while it occurred in 64.38% of the young osteocytes. Additionally, in all recovered osteocytes, 36% of the developmentally mature osteocytes comprised non-fitted model cells while 53.19% of the young osteocytes were the non-fitted model, which indicates the active transduction of dye molecules. However, there were no statistically significant differences between the young and developmentally mature osteocytes with regard to the diffusion coefficient, permeability coefficient, or permeance of the osteocyte processes, which were 3.93±3.77 (×10(-8)cm(2)/s), 5.12±4.56 (×10(-5)cm(2)/s) and 2.99±2.47 (×10(-13)cm(2)/s) (mean±SD), respectively. CONCLUSIONS: These experiments comprehensively quantified the GJIC capacity in the embryonic chick calvaria and indicated that the cell-cell communication capacity of the osteocytes in the embryonic chick calvaria was related to their development.

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