Human placental lactogen enhancer: Tissue specificity and binding with specific proteins

Human placental lactogen (hPL) is a 22,000 dalton protein hormone produced in the placenta. The physiological actions of hPL are not well understood but its major activity is to regulate both maternal and fetal metabolism. hPL stimulates maternal lipolysis increasing free fatty acids in the maternal blood, allowing their use as an energy source by the mother, and sparing glucose for the fetus. It may also act as a growth promoting hormone for the fetus. hPL is produced in increasing amounts as pregnancy progresses. At term, hPL accounts for 10% of protein and 5% of total RNA in the placenta. This high level of hPL production is tissue-specific, as hPL is only produced in the placenta by syncytiotrophoblast cells.^ The objective of this work was to understand the mechanism by which such high levels of hPL are produced in a tissue-specific manner. A transcriptional enhancer found 2.2 kb 3$\sp\prime$ to one of the hPL genes (hPL$\sb3$) may explain the regulation of hPL expression. Transient transfection experiments using the hPL-producing human choriocarcinoma cell line JEG-3 localized the hPL enhancer to a 138 bp core element. This 138 bp sequence was found to be tissue specific in its actions as it did not promote transcription in heterologous cell lines. Gel mobility shift assays showed the hPL enhancer interacts specifically with nuclear proteins unique to hPL-producing cells. Within the 138 bp enhancer a 22 bp region was shown to be protected from DNase I digestion due to binding of proteins derived from placental nuclear extracts. Proteins binding this region of the enhancer may be instrumental in the tissue specific activity of the hPL enhancer. ^

XYLITOL METABOLISM IN RAT LIVER AND HEPATOCELLULAR CARCINOMAS

The significance of nutritional factors in cancer research has been strongly emphasized. Such research is concerned not only with epidemiological effects relative to dietary factors on the causation of cancer, but with nutritional effects as an energy source on the prevention of cancer. Many studies speculate that the energy flow between tumor and host can be regulated by dietary intake. However, little knowledge on the comparison of the specific nutritional and energy requirements of different cells and tissues is available. Most popular and essential energy sources for the body are the carbohydrates. Among them, xylitol is known as efficient an energy source as glucose. In carbohydrate metabolism, glycolysis is one of the major energy producing pathways. However, recently the existence of an alternate catabolic pathway in mammals for carbohydrate besides glycolysis, i.e. bypass through triosephosphates to lactate via methylglyoxal has been suggested. This bypass was implicated to regulate glycolysis and also be responsible for the fluctuation in the levels of a regulator of cell growth. Methylglyoxal itself is known as a cancerostatic agent. The alterations of biochemical parameters in xylitol metabolism in animals indicated that xylitol may be metabolized through a methylglyoxal pathway.^ To elucidate the biological effect of xylitol as an energy source and the biological effect of its metabolites as a cancerostatis agent, the mode and extent of metabolism must be understood in tumor-bearing animals. Differential utilization of xylitol and glucose, if any, between tumor and host in such animals may exert tissue selective effects on both in terms of methylglyoxal formation and energy provision. The aim of this work was to assess the extent to which the differential utilization of xylitol might be used to generate different metabolic pathways in tumor and host, and to consider a role of nutrition in cancer.^ The results disclose that the existence of a pathway for biological methylglyoxal formation in normal rat liver has been confirmed in single cell suspension; the metabolic significance of the methylglyoxal pathway in the metabolism of glucose and xylitol has been evaluated quantitatively in normal rat liver and the differential metabolism of glucose and xylitol through overall catabolic pathways of carbohydrates has been studied in normal hepatic cells, AS-30D hepatoma and other several hepatoma lines. ^

DUAL ENERGY COMPUTED TOMOGRAPHY FOR PROTON THERAPY TREATMENT PLANNING

Proton radiation therapy is gaining popularity because of the unique characteristics of its dose distribution, e.g., high dose-gradient at the distal end of the percentage-depth-dose curve (known as the Bragg peak). The high dose-gradient offers the possibility of delivering high dose to the target while still sparing critical organs distal to the target. However, the high dose-gradient is a double-edged sword: a small shift of the highly conformal high-dose area can cause the target to be substantially under-dosed or the critical organs to be substantially over-dosed. Because of that, large margins are required in treatment planning to ensure adequate dose coverage of the target, which prevents us from realizing the full potential of proton beams. Therefore, it is critical to reduce uncertainties in the proton radiation therapy. One major uncertainty in a proton treatment is the range uncertainty related to the estimation of proton stopping power ratio (SPR) distribution inside a patient. The SPR distribution inside a patient is required to account for tissue heterogeneities when calculating dose distribution inside the patient. In current clinical practice, the SPR distribution inside a patient is estimated from the patient’s treatment planning computed tomography (CT) images based on the CT number-to-SPR calibration curve. The SPR derived from a single CT number carries large uncertainties in the presence of human tissue composition variations, which is the major drawback of the current SPR estimation method. We propose to solve this problem by using dual energy CT (DECT) and hypothesize that the range uncertainty can be reduced by a factor of two from currently used value of 3.5%. A MATLAB program was developed to calculate the electron density ratio (EDR) and effective atomic number (EAN) from two CT measurements of the same object. An empirical relationship was discovered between mean excitation energies and EANs existing in human body tissues. With the MATLAB program and the empirical relationship, a DECT-based method was successfully developed to derive SPRs for human body tissues (the DECT method). The DECT method is more robust against the uncertainties in human tissues compositions than the current single-CT-based method, because the DECT method incorporated both density and elemental composition information in the SPR estimation. Furthermore, we studied practical limitations of the DECT method. We found that the accuracy of the DECT method using conventional kV-kV x-ray pair is susceptible to CT number variations, which compromises the theoretical advantage of the DECT method. Our solution to this problem is to use a different x-ray pair for the DECT. The accuracy of the DECT method using different combinations of x-ray energies, i.e., the kV-kV, kV-MV and MV-MV pair, was compared using the measured imaging uncertainties for each case. The kV-MV DECT was found to be the most robust against CT number variations. In addition, we studied how uncertainties propagate through the DECT calculation, and found general principles of selecting x-ray pairs for the DECT method to minimize its sensitivity to CT number variations. The uncertainties in SPRs estimated using the kV-MV DECT were analyzed further and compared to those using the stoichiometric method. The uncertainties in SPR estimation can be divided into five categories according to their origins: the inherent uncertainty, the DECT modeling uncertainty, the CT imaging uncertainty, the uncertainty in the mean excitation energy, and SPR variation with proton energy. Additionally, human body tissues were divided into three tissue groups – low density (lung) tissues, soft tissues and bone tissues. The uncertainties were estimated separately because their uncertainties were different under each condition. An estimate of the composite range uncertainty (2s) was determined for three tumor sites – prostate, lung, and head-and-neck, by combining the uncertainty estimates of all three tissue groups, weighted by their proportions along typical beam path for each treatment site. In conclusion, the DECT method holds theoretical advantages in estimating SPRs for human tissues over the current single-CT-based method. Using existing imaging techniques, the kV-MV DECT approach was capable of reducing the range uncertainty from the currently used value of 3.5% to 1.9%-2.3%, but it is short to reach our original goal of reducing the range uncertainty by a factor of two. The dominant source of uncertainties in the kV-MV DECT was the uncertainties in CT imaging, especially in MV CT imaging. Further reduction in beam hardening effect, the impact of scatter, out-of-field object etc. would reduce the Hounsfeld Unit variations in CT imaging. The kV-MV DECT still has the potential to reduce the range uncertainty further.

A convolution model for energy transport in a therapeutic fast neutron beam

A three-dimensional model has been proposed that uses Monte Carlo and fast Fourier transform convolution techniques to calculate the dose distribution from a fast neutron beam. This method transports scattered neutrons and photons in the forward, lateral, and backward directions and protons, electrons, and positrons in the forward and lateral directions by convolving energy spread kernels with initial interaction available energy distributions. The primary neutron and photon spectrums have been derived from narrow beam attenuation measurements. The positions and strengths of the effective primary neutron, scattered neutron, and photon sources have been derived from dual ion chamber measurements. The size of the effective primary neutron source has been measured using a copper activation technique. Heterogeneous tissue calculations require a weighted sum of two convolutions for each component since the kernels must be invariant for FFT convolution. Comparisons between calculations and measurements were performed for several water and heterogeneous phantom geometries. ^

A QUANTITATIVE INVESTIGATION OF SOURCE AND ELEMENTAL COMPOSITION OF INDOOR AND OUTDOOR FINE PARTICULATE AIR POLLUTION IN HOUSTON (TEXAS)

An investigation was undertaken to determine the chemical characterization of inhalable particulate matter in the Houston area, with special emphasis on source identification and apportionment of outdoor and indoor atmospheric aerosols using multivariate statistical analyses.^ Fine (<2.5 (mu)m) particle aerosol samples were collected by means of dichotomous samplers at two fixed site (Clear Lake and Sunnyside) ambient monitoring stations and one mobile monitoring van in the Houston area during June-October 1981 as part of the Houston Asthma Study. The mobile van allowed particulate sampling to take place both inside and outside of twelve homes.^ The samples collected for 12-h sampling on a 7 AM-7 PM and 7 PM-7 AM (CDT) schedule were analyzed for mass, trace elements, and two anions. Mass was determined gravimetrically. An energy-dispersive X-ray fluorescence (XRF) spectrometer was used for determination of elemental composition. Ion chromatography (IC) was used to determine sulfate and nitrate.^ Average chemical compositions of fine aerosol at each site were presented. Sulfate was found to be the largest single component in the fine fraction mass, comprising approximately 30% of the fine mass outdoors and 12% indoors, respectively.^ Principal components analysis (PCA) was applied to identify sources of aerosols and to assess the role of meteorological factors on the variation in particulate samples. The results suggested that meteorological parameters were not associated with sources of aerosol samples collected at these Houston sites.^ Source factor contributions to fine mass were calculated using a combination of PCA and stepwise multivariate regression analysis. It was found that much of the total fine mass was apparently contributed by sulfate-related aerosols. The average contributions to the fine mass coming from the sulfate-related aerosols were 56% of the Houston outdoor ambient fine particulate matter and 26% of the indoor fine particulate matter.^ Characterization of indoor aerosol in residential environments was compared with the results for outdoor aerosols. It was suggested that much of the indoor aerosol may be due to outdoor sources, but there may be important contributions from common indoor sources in the home environment such as smoking and gas cooking. ^