3D pore-interconnected calcium phosphate bone blocks for bone tissue engineering

Pore size and connectivity of artificial bone scaffolds play key role in regulating cell ingrowth and vascularization during healing. The objective of this study was to develop a novel process for preparing 3D pore-interconnected open-cell bone substitutes with varying pore sizes. This was achieved by thermal-induced expansion, drying, then sintering the mixture of biphasic calcium phosphate (BCP) and a thermal responsive porogen comprising chitosan (CS) and hydroxypropyl methyl cellulose (HPMC). The interpolymer complexes (IPCs) of CS/HPMC were prepared and investigated by FT-IR. The mixtures of IPCs/BCP were heated up to 100 °C for analyzing their thermal expansion properties. This resulted in ~13% and ~42% volume increment for IPC-1/BCP and IPC-2/BCP, respectively, while ~230% volume increased in the case of IPC-3/BCP (therefore chosen for sintering bone blocks). Heating rate-dependent (0.20–0.25 °C/min range) sintering profiles for IPC-3/BCP were utilized to produce BCP bone blocks. Gasification of IPC during sintering resulted in the formation of interconnected porous structures, and the morphology was investigated by SEM, revealing varying sizes ranging from 106 ± 13 μm to 1123 ± 75 μm. The pore size range of bone blocks from 235 ± 46 μm to 459 ± 76 μm portrayed significantly high MC3T3-E1 cell viability with prominent filopodial extensions, and elongated cells, depicting efficient biocompatibility. Therefore, the process for preparing porous interconnected 3D bone blocks were feasible, thereby serving as an alternative for potential bone tissue engineering applications.     

ANN inverse analysis based on stochastic small-sample training set simulation

A new approach of inverse analysis is proposed to obtain parameters of a computational model in order to achieve the best agreement with experimental data. The inverse analysis is based on the coupling of a stochastic simulation and an artificial neural network (ANN). The identification parameters play the role of basic random variables with a scatter reflecting the physical range of potential values. A novelty of the approach is the utilization of the efficient small-sample simulation method Latin Hypercube Sampling (LHS) used for the stochastic preparation of the training set utilized in training the artificial neural network. Once the network has been trained, it represents an approximation consequently utilized to solve the key task: To provide the best possible set of model parameters for the given experimental data. The efficiency of the approach is shown using numerical examples from civil engineering computational mechanics.     

Chronic fluoride exposure does not cause detrimental, extraskeletal effects in nutritionally deficient rats

On the basis of observations that endemic fluorosis occurs more often in malnourished populations, a series of studies tested the hypothesis that deficient dietary intake of calcium, protein or energy affects fluoride metabolism so that the margin of safe fluoride exposure may be reduced. The objective of the investigation was to determine whether changes in fluoride metabolism in nutritionally deficient rats resulted in manifestation of any extraskeletal toxic fluoride effects not observed in healthy animals. This investigation included two studies, one that monitored the effect of calcium deficiency on the effects of chronic fluoride exposure, and a second study that observed fluoride effects in rats that were deficient either in protein or in energy and total nutrient intake. Control and experimental rats received drinking water containing 0, 0.26 (5), 0.79 (15) or 2.63 (50) mmol fluoride/L (mg/L) for 16 or 48 wk. Control rats were fed optimal diets and experimental rats were fed diets deficient in calcium (Study 1) or protein (Study 2). An additional group of experimental rats (Study 2) was provided with a restricted amount of diet; thus these rats were deficient in energy and total nutrient intake. The intake, excretion and retention of fluoride were monitored; after the rats were killed, tissue fluoride levels and biochemical markers of tissue function were analyzed. Bone marrow cells were harvested from some of the rats, after 48 wk of treatment, for determining the frequency of sister chromatid exchange, a marker of genetic damage. Although there were significant differences among fluoride treatment groups in fluoride excretion and retention that resulted in significantly greater fluoride levels in tissues of the experimental rats, we were unable to detect any harmful, extraskeletal biochemical, physiologic or genetic effects of fluoride in the nutritionally deficient rats.     

Genetic programming of conventional features to detect seizure precursors

This paper presents an application of genetic programming (GP) to optimally select and fuse conventional features (C-features) for the detection of epileptic waveforms within intracranial electroencephalogram (IEEG) recordings that precede seizures, known as seizure precursors. Evidence suggests that seizure precursors may localize regions important to seizure generation on the IEEG and epilepsy treatment. However, current methods to detect epileptic precursors lack a sound approach to automatically select and combine C-features that best distinguish epileptic events from background, relying on visual review predominantly. This work suggests GP as an optimal alternative to create a single feature after evaluating the performance of a binary detector that uses: (1) genetically programmed features; (2) features selected via GP; (3) forward sequentially selected features; and (4) visually selected features. Results demonstrate that a detector with a genetically programmed feature outperforms the other three approaches, achieving over 78.5% positive predictive value, 83.5% sensitivity, and 93% specificity at the 95% level of confidence.     

Association of symptoms of depression with diagnostic test charges among older adults

BACKGROUND: Previous studies have documented greater use of health services by depressed persons and have postulated that health care costs could be reduced overall through better recognition and treatment of depression. OBJECTIVE: To determine whether a greater burden of medical illness contributes to excess charges for diagnostic tests among older adults with symptoms of depression. DESIGN: Prospective cohort study. SETTING: A primary care group practice at an academic institution. PATIENTS: 3767 patients 60 years of age and older who completed testing on the Centers for Epidemiologic Studies Depression Scale (CES-D) during routine office visits. MEASUREMENTS: Charges for all inpatient and ambulatory diagnostic testing for 2 years, including clinical pathology, diagnostic imaging, and special procedures; number of visits to the ambulatory care center or emergency department; and number of hospitalizations. The Ambulatory Care Group case-mix approach, which is based on ambulatory diagnoses, was used as a measure of health status and expected resource consumption. RESULTS: Patients with symptoms of depression (CES-D scores > or = 16) were significantly younger (66.6 compared with 68.1 years; P < 0.001), more likely to be white (50.5% compared with 33.9%; P = 0.001), and more likely to be female (75.8% compared with 67.6%; P = 0.001) than were those without these symptoms (CES-D scores < 16). They also had more nonpsychiatric comorbid conditions, had more visits to the ambulatory care center (9.2 compared with 7.8; P < 0.001), were more likely to use the emergency department (52.3% compared with 40%; P = 0.001), were more likely to be hospitalized (22.4% compared with 17%; P = 0.002), and had greater median total diagnostic test charges for a period of 1 year ($583 compared with $387; P < 0.001). The difference in charges, most of which were clinical pathology charges (54.2%), persisted into the second year. Ambulatory Care Group assignment was independently associated with diagnostic test charges. The CES-D summary score was not independently associated with diagnostic test charges when controlling for Ambulatory Care Group assignment. CONCLUSIONS: Patients with symptoms of depression accrue greater average diagnostic test charges. However, these data suggest that such patients also have a greater burden of comorbid nonpsychiatric illness. Efforts to improve outcome and decrease cost for patients who have late-life depression must target interventions to improve the care of psychiatric and medical illness concurrently.     

Friction-transfer test for the assessment of in situ strength and adhesion of cementitious materials

Since in concrete industry, the quality control is generally accomplished by the testing of separately prepared samples, the accurate estimate of the in situ strength of concrete has become a necessity. The main discrepancies between the measured cube strength and the actual in situ strength of concrete, relates to their different conditions associated with the development of strength. In addition, due to chemical deterioration or damage, accurate estimate of in situ concrete strength provides valuable information about the present situation of the structure, when making decisions about the required repair and/or strengthening systems. The Friction-Transfer method, which is described in this paper, can be used to estimate the in situ strength of concrete and other materials. In this method a specially devised apparatus fits on to the top of the partial core and is clamped to it. To measure the concrete compressive strength, a torque is applied using an ordinary torque-meter and the maximum shear stress at failure is used to estimate the cube compressive strength by means of a calibration graph. In order to measure the adhesion between different layers of cementitious and/or resinous materials, their torsional shear strengths are calculated along the failed inter-facial surfaces of the layers. Laboratory and in situ tests, to evaluate the performance of the method are described. Also in view of the accurate and reliable results attainable, some specific applications are proposed.     

Analysis of truss structures using distributed object-oriented methods

Objected-oriented analysis methods are developed for distributed finite element analysis of truss structures. The method is based on distributed solution of finite element equations using the substructuring method. Objects for static analysis of truss structures are identified and presented in a pseudocode form. The developed techniques are implemented in a network of workstations. A software tool called the IDL-C++ (RPC) compiler has been developed to aid the programmer in constructing distributed object applications. The speedup/performance for moderate size problems is presented to illustrate the present approach for truss analysis using distributed object-oriented methods.     

Interactive Genetic Algorithm with Mixed Initiative Interaction for multi-criteria ground water monitoring design

Design of optimal plans for environmental planning and management applications should ideally consider the multiple quantitative and qualitative criteria relevant to the problem. For example, in ground water monitoring design problems, qualitative criteria such as acceptable spatial extent and shape of the contaminant plume predicted from the monitored locations can be equally important as the typical quantitative criteria such as economic costs and contaminant prediction accuracy. Incorporation of qualitative criteria in the problem-solving process is typically done in one of two ways: (a) quantifying approximate representations of the qualitative criteria, which are then used as additional criteria during the optimization process, or (b) post-optimization analysis of designs by experts to evaluate the overall performance of the optimized designs with respect to the qualitative criteria. These approaches, however, may not adequately represent all of the relevant qualitative information that affect a human expert involved in design (e.g. engineers, stakeholders, regulators, etc.), and do not necessarily incorporate the effect of the expert's own learning process on the suitability of the final design. The Interactive Genetic Algorithm with Mixed Initiative Interaction (IGAMII) is a novel approach that addresses these limitations by using a collaborative human-computer search strategy to assist users in designing optimized solutions to their applications, while also learning about their problem. The algorithm adaptively learns from the expert's feedback, and explores multiple designs that meet her/his criteria using both the human expert and a simulated model of the expert's responses in a collaborative fashion. The algorithm provides an introspection-based learning framework for the human expert and uses the human's subjective confidence measures to adjust the optimization search process to the transient learning process of the user. This paper presents the design and testing of this computational framework, and the benefits of using this approach for solving groundwater monitoring design problems.