A latent class linear mixed model for monotonic continuous processes measured with error

Motivated by measurement errors in radiographic diagnosis of osteoarthritis, we propose a Bayesian approach to identify latent classes in a model with continuous response subject to a monotonic, that is, non-decreasing or non-increasing, process with measurement error. A latent class linear mixed model has been introduced to consider measurement error while the monotonic process is accounted for via truncated normal distributions. The main purpose is to classify the response trajectories through the latent classes to better describe the disease progression within homogeneous subpopulations.

Analysis of Adverse Drug Reactions in Pediatric Patients with Epilepsy: An Intensive Pharmacovigilance Study

Epilepsy is a chronic neurological disease characterized by the presence of spontaneous seizures, with a higher incidence in the pediatric population. Anti-seizure medication (ASM) may produce adverse drug reactions (ADRs) with an elevated frequency and a high severity. Thus, the objective of the present study was to analyze, through intensive pharmacovigilance over 112 months, the ADRs produced by valproic acid (VPA), oxcarbazepine (OXC), phenytoin (PHT), and levetiracetam (LEV), among others, administered to monotherapy or polytherapy for Mexican hospitalized pediatric epilepsy patients. A total of 1034 patients were interviewed; 315 met the inclusion criteria, 211 patients presented ADRs, and 104 did not. A total of 548 ASM-ADRs were identified, and VPA, LEV, and PHT were the main culprit drugs. The most frequent ADRs were drowsiness, irritability, and thrombocytopenia, and the main systems affected were hematologic, nervous, and dermatologic. LEV and OXC caused more nonsevere ADRs, and PHT caused more severe ADRs. The risk analysis showed an association between belonging to the younger groups and polytherapy with ADR presence and between polytherapy and malnutrition with severe ADRs. In addition, most of the severe ADRs were preventable, and most of the nonsevere ADRs were nonpreventable.

Incomplete Antiretroviral Therapy Adherence Is Associated with Lower CD4-CD8 Ratio in Virally Suppressed Patients with HIV Infection in Mexico

Suboptimal adherence to antiretroviral therapy (ART) in people with HIV, even during sustained viral suppression, is associated with persistent inflammation, immune activation, and coagulopathy. Persistently low CD4-CD8 Ratio has been also associated with residual inflammation, is a good predictor of increased risk of death and more widely available than inflammatory biomarkers. We tested the hypothesis that the CD4-CD8 Ratio is associated with ART adherence during periods of complete viral suppression. We used the Medication Possession Ratio based in pharmacy registries as measure of adherence and time-varying, routine care CD4 and CD8 measurements as outcome. We used a linear mixed model for longitudinal data, including fixed effects for sex, age, education, date of ART initiation, AIDS-related conditions, and baseline CD4 to model the outcome. In 988 adults with a median follow-up of 4.13 years, higher ART adherence was independently associated with a modest increase in CD4-CD8. For each increasing percentage point in adherence, the CD4-CD8 Ratio increased 0.000857 (95% confidence interval [CI] -0.000494 to 0.002209, p = .213731) in the first year after achieving viral suppression; 0.001057 (95% CI 0.000262-0.001853, p = .009160) in years 1 to 3; 0.000323 (95% CI -0.000448 to 0.001095, p = .411441) in years 3 to 5; and 0.000850 (95% CI 0.000272-0.001429, p = .003946) 5-10 years after achieving viral suppression. The magnitude of the effect of adherence over CD4-CD8 Ratios varied over time and by baseline CD4 count, with increasing adherence having a larger effect early after ART initiation in people with higher baseline CD4 (>500 cells/μL) and in later years in people with lower baseline CD4 count (≥200 cells/μL). Our findings expand on previous evidence suggesting that the benefits of optimal adherence to modern ART regimens goes beyond maintaining viral suppression. These results highlight the importance of including objective measurements of adherence as part of routine care, even in patients with complete HIV suppression over long-term follow-up.

Mixed kernel SVR addressing Parkinson's progression from voice features

Parkinson’s Disease (PD) is a progressive neurodegenerative disease with multiple motor and non-motor characteristics. PD patients commonly face vocal impairments during the early stages of the disease. In this article, the aim is to explain the Unified Parkinson’s Disease Rating Scale (UPDRS) as a measure of the progression of Parkinson’s disease using a set of covariates obtained from voice signals. In particular, a Support Vector Regression (SVR) model based on a combination of kernel functions is introduced. Theoretically, this proposal, that relies on a mixed kernel (global and local) produces an admissible kernel function. The optimal fitting was obtained for the combination given by the product of radial and polynomial basis. Important results are the non-linear relationships inferred from the features to the response, as well as a considerable improvement in prediction performance metrics, when compared to other learning approaches. Furthermore, with knowledge on factors such as age and gender, it is possible to describe the dynamics of patients’ UPDRS from the data collected during their monitoring. In summary, these advances could expand learning processes and intelligent systems to assist in monitoring the evolution of Parkinson’s disease.

A spatio-temporal study of state-wide case-fatality risks during the first wave of the COVID-19 pandemic in Mexico

spatio-temporal analysis of the first wave of the coronavirus (COVID-19) pandemic in Mexico (April to September 2020) was performed by state. Descriptive analyses through diagrams, mapping, animations and time series representations were carried out. Greater risks were observed at certain times in specific regions. Various trends and clusters were observed and analysed by fitting linear mixed models and time series clustering. The association of co-morbidities and other variables were studied by fitting a spatial panel data linear model (SPLM). On average, the greatest risks were observed in Baja California Norte, Chiapas and Sonora, while some other densely populated states, e.g., Mexico City, had lower values. The trends varied by state and a four-order polynomial, including fixed and random effects, was necessary to model them. The most common risk development was observed in states belonging to two clusters and consisted of an initial increase followed by a decrease. Some states presented cluster configurations with a retarded risk increase before the decrease, while the risk increased throughout the time of study in others. A cyclic behaviour with a second increasing trend was also observed in some states. The SPLM approach revealed a positive significant association with respect to case fatality risk between certain groups, such as males and individuals aged 50 years and more, and the prevalence of chronic kidney disease, cardiovascular disease, asthma and hypertension. The analysis may provide valuable insight into COVID-19 dynamics applicable in future outbreaks, as well as identify determinants signifying certain trends at the state level. The combination of spatial and temporal information may provide a better understanding of the fatalities due to COVID-19.

Replication-based regularization approaches to diagnose Reinke's edema by using voice recordings

Reinke's edema is one of the most prevalent laryngeal pathologies. Its detection can be addressed by using computer-aided diagnosis systems based on features extracted from speech recordings. When extracting acoustic features from different voice recordings of a particular subject at a concrete moment, imperfections in technology and the very biological variability result in values that are close, but they are not identical. This suggests that the within-subject variability must be properly addressed in the statistical methodology. Regularization-based regression approaches can be used to reduce the classification errors by favoring the best predictors and penalizing the worst ones. Three replication-based regularization approaches for variable selection and classification have been specifically designed and implemented to take into account the underlying within-subject variability. In order to illustrate the applicability of these approaches, an experiment has been specifically conducted to discriminate Reinke's edema patients (30 subjects) from healthy people (30 subjects) in a hospital environment. The features have been extracted from four phonations of the sustained vowel /a/ recorded for each subject, leading to a database that has fed the proposed machine learning approaches. The proposed replication-based approaches have been proved to be reliable in terms of selected features and predictive ability, leading to a stable accuracy rate of 0.89 under a cross-validation framework. Also, a comparison with traditional independence-based regularization methods reports a great variability of the latter in terms of selected features and accuracy metrics. Therefore, the proposed approaches contribute to fill a gap in the scientific literature on statistical approaches considering within-subject variability and can be used to build a robust expert system.

Random intercept and linear mixed models including heteroscedasticity in a logarithmic scale: Correction terms and prediction in the original scale

Random intercept models are linear mixed models (LMM) including error and intercept random effects. Sometimes heteroscedasticity is included and the response variable is transformed into a logarithmic scale, while inference is required in the original scale; thus, the response variable has a log-normal distribution. Hence, correction terms should be included to predict the response in the original scale. These terms multiply the exponentiated predicted response variable, which subestimates the real values. We derive the correction terms, simulations and real data about the income of elderly are presented to show the importance of using them to obtain more accurate predictions. Generalizations for any LMM are also presented.

A mixed hidden Markov model for multivariate monotone disease processes in the presence of measurement errors

Motivated by a longitudinal oral health study, the Signal-Tandmobiel® study, an inhomogeneous mixed hidden Markov model with continuous state-space is proposed to explain the caries disease process in children between 6 and 12 years of age. The binary caries experience outcomes are subject to misclassification. We modelled this misclassification process via a longitudinal latent continuous response subject to a measurement error process and showing a monotone behaviour. The baseline distributions of the unobservable continuous processes are defined as a function of the covariates through the specification of conditional distributions making use of the Markov property. In addition, random effects are considered to model the relationships among the multivariate responses. Our approach is in contrast with a previous approach working on the binary outcome scale. This method requires conditional independence of the possibly corrupted binary outcomes on the true binary outcomes. We assumed conditional independence on the latent scale, which is a weaker assumption than conditional independence on the binary scale. The aim of this article is therefore to show the properties of a model for a progressive longitudinal response with misclassification on the manifest scale but modelled on the latent scale. The model parameters are estimated in a Bayesian way using an efficient Markov chain Monte Carlo method. The model performance is shown through a simulation-based example, and the analysis of the motivating dataset is presented.

A hidden Markov model addressing measurement errors in the response and replicated covariates for continuous nondecreasing processes

Motivated by a study tracking the progression of Parkinson’s disease (PD) based on features extracted from voice recordings, an inhomogeneous hidden Markov model with continuous state-space is proposed. The approach addresses the measurement error in the response, the within-subject variability of the replicated covariates and presumed nondecreasing response. A Bayesian framework is described and an efficient Markov chain Monte Carlo method is developed. The model performance is evaluated through a simulation-based example and the analysis of a PD tracking progression dataset is presented. Although the approach was motivated by a PD tracking progression problem, it can be applied to any monotonic nondecreasing process whose continuous response variable is subject to measurement errors and where replicated covariates play a key role.

A two-stage variable selection and classification approach for Parkinson's disease detection by using voice recording replications

BACKGROUND AND OBJECTIVE

In the scientific literature, there is a lack of variable selection and classification methods considering replicated data. The problem motivating this work consists in the discrimination of people suffering Parkinson's disease from healthy subjects based on acoustic features automatically extracted from replicated voice recordings.

METHODS

A two-stage variable selection and classification approach has been developed to properly match the replication-based experimental design. The way the statistical approach has been specified allows that the computational problems are solved by using an easy-to-implement Gibbs sampling algorithm.

RESULTS

The proposed approach produces an acceptable predictive capacity for PD discrimination with the considered database, despite the fact that the sample size is relatively small. Specifically, the accuracy rate, sensitivity and specificity are 86.2%, 82.5%, and 90.0%, respectively. However, the most important fact is that there is an improvement in the interpretability of the results at the same time that it is shown a better chain mixing and a lower computation time with respect to the only-classification approaches presented in the scientific literature.

CONCLUSIONS

To the best of the authors' knowledge, this is the first approach developed to properly consider intra-subject variability for variable selection and classification. Although the proposed approach has been applied for PD discrimination, it can be applied in other contexts with similar replication-based experimental designs.

Modulation of intracellular pH in human ovarian cancer

To sustain tumor growth, the cancer cells need to adapt to low levels of oxygen (i.e., hypoxia) in the tumor tissue and to the tumor-associated acidic microenvironment. In this phenomenon, the activation of the sodium/proton exchanger 1 (NHE1) at the plasma membrane and the hypoxia-inducible factor (HIF) are critical for the control of the intracellular pH (pHi) and for hypoxia adaptation, respectively. Interestingly, both of these mechanisms end in sustaining cancer cell proliferation. However, regulatory mechanisms of pHi in human ovary tissue and in malignant ascites are unknown. Additionally, a potential role of NHE1 in the modulation of H(+) efflux in human ovarian cancer cells is unknown. In this review, we discussed the characteristics of tumor microenvironment of primary human ovarian tumors and tumor ascites, in terms of pHi regulatory mechanisms and oxygen level. The findings described in the literature suggest that NHE1 may likely play a role in pHi regulation and cell proliferation in human ovarian cancer, potentially involving HIF2α activation. Since ovarian cancer is the fifth cause of prevalence of women cancer in Chile and is usually of late diagnosis, i.e., when the disease jeopardizes peritoneal cavity and other organs, resulting in reduced patient survival, new efforts are required to improve patient-life span and for a better understanding of the pathophysiology of the disease. The potential advantage of the use of amiloride and amiloride-derivatives for cancer treatment in terms of NHE1 expression and activity is also discussed as a therapeutic approach in human ovarian cancer.

Deep sequencing in library selection projects: what insight does it bring?

High throughput sequencing is poised to change all aspects of the way antibodies and other binders are discovered and engineered. Millions of available sequence reads provide an unprecedented sampling depth able to guide the design and construction of effective, high quality naïve libraries containing tens of billions of unique molecules. Furthermore, during selections, high throughput sequencing enables quantitative tracing of enriched clones and position-specific guidance to amino acid variation under positive selection during antibody engineering. Successful application of the technologies relies on specific PCR reagent design, correct sequencing platform selection, and effective use of computational tools and statistical measures to remove error, identify antibodies, estimate diversity, and extract signatures of selection from the clone down to individual structural positions. Here we review these considerations and discuss some of the remaining challenges to the widespread adoption of the technology.

Lysine is catabolized to 2-aminoadipic acid in Penicillium chrysogenum by an omega-aminotransferase and to saccharopine by a lysine 2-ketoglutarate reductase. Characterization of the omega-aminotransferase

The biosynthesis and catabolism of lysine in Penicillium chrysogenum is of great interest because these pathways provide 2-aminoadipic acid, a precursor of the tripeptide delta-L-2-aminoadipyl-L-cysteinyl-D-valine that is an intermediate in penicillin biosynthesis. In vivo conversion of labelled L-lysine into two different intermediates was demonstrated by HPLC analysis of the intracellular amino acid pool. L-lysine is catabolized to 2-aminoadipic acid by an omega-aminotransferase and to saccharopine by a lysine-2-ketoglutarate reductase. In lysine-containing medium both activities were expressed at high levels, but the omega-aminotransferase activity, in particular, decreased sharply when ammonium was used as the nitrogen source. The omega-aminotransferase was partially purified, and found to accept L-lysine, L-ornithine and, to a lesser extent, N-acetyl-L-lysine as amino-group donors. 2-Ketoglutarate, 2-ketoadipate and, to a lesser extent, pyruvate served as amino group acceptors. This pattern suggests that this enzyme, previously designated as a lysine-6-aminotransferase, is actually an omega-aminotransferase. When 2-ketoadipate is used as substrate, the reaction product is 2-aminoadipic acid, which contributes to the pool of this intermediate available for penicillin biosynthesis. The N-terminal end of the purified 45-kDa omega-aminotransferase was sequenced and was found to be similar to the corresponding segment of the OAT1 protein of Emericella (Aspergillus) nidulans. This information was used to clone the gene encoding this enzyme.

Expression of cefD2 and the conversion of isopenicillin N into penicillin N by the two-component epimerase system are rate-limiting steps in cephalosporin biosynthesis

The conversion of isopenicillin N into penicillin N in Acremonium chrysogenum is catalyzed by an epimerization system that involves an isopenicillin N-CoA synthethase and isopenicillin N-CoA epimerase, encoded by the genes cefD1 and cefD2. Several transformants containing two to seven additional copies of both genes were obtained. Four of these transformants (TMCD26, TMCD53, TMCD242 and TMCD474) showed two-fold higher IPN epimerase activity than the untransformed A. chrysogenum C10, and produced 80 to 100% more cephalosporin C and deacetylcephalosporin C than the parental strain. A second class of transformants, including TMCD2, TMCD32 and TMCD39, in contrast, showed a drastic reduction in cephalosporin biosynthesis relative to the untransformed control. These transformants had no detectable IPN epimerase activity and did not produce cephalosporin C or deacetylcephalosporin C. They also expressed both endogenous and exogenous cefD2 genes only after long periods (72-96 h) of incubation, as shown by Northern analysis, and were impaired in mycelial branching in liquid cultures. The negative effect of amplification of the cefD1 - cefD2 gene cluster in this second class of transformants is not correlated with high gene dosage, but appears to be due to exogenous DNA integration into a specific locus, which results in a pleiotropic effect on growth and cefD2 expression.

Conversion of pipecolic acid into lysine in Penicillium chrysogenum requires pipecolate oxidase and saccharopine reductase: characterization of the lys7 gene encoding saccharopine reductase

Pipecolic acid is a component of several secondary metabolites in plants and fungi. This compound is useful as a precursor of nonribosomal peptides with novel pharmacological activities. In Penicillium chrysogenum pipecolic acid is converted into lysine and complements the lysine requirement of three different lysine auxotrophs with mutations in the lys1, lys2, or lys3 genes allowing a slow growth of these auxotrophs. We have isolated two P. chrysogenum mutants, named 7.2 and 10.25, that are unable to convert pipecolic acid into lysine. These mutants lacked, respectively, the pipecolate oxidase that converts pipecolic acid into piperideine-6-carboxylic acid and the saccharopine reductase that catalyzes the transformation of piperideine-6-carboxylic acid into saccharopine. The 10.25 mutant was unable to grow in Czapek medium supplemented with alpha-aminoadipic acid. A DNA fragment complementing the 10.25 mutation has been cloned; sequence analysis of the cloned gene (named lys7) revealed that it encoded a protein with high similarity to the saccharopine reductase from Neurospora crassa, Magnaporthe grisea, Saccharomyces cerevisiae, and Schizosaccharomyces pombe. Complementation of the 10.25 mutant with the cloned gene restored saccharopine reductase activity, confirming that lys7 encodes a functional saccharopine reductase. Our data suggest that in P. chrysogenum the conversion of pipecolic acid into lysine proceeds through the transformation of pipecolic acid into piperideine-6-carboxylic acid, saccharopine, and lysine by the consecutive action of pipecolate oxidase, saccharopine reductase, and saccharopine dehydrogenase.

Radionuclides in pinon pine (Pinus edulis) nuts from Los Alamos National Laboratory lands and the dose from consumption

One of the dominant tree species growing within and around the eastern portion of Los Alamos National Laboratory (LANL), Los Alamos, NM, lands is the pinon pine (Pinus edulis). Pinon pine is used for firewood, fence posts, and building materials and is a source of nuts for food--the seeds are consumed by a wide variety of animals and are also gathered by people in the area and eaten raw or roasted. This study investigated the (1) concentration of 3H, 137Cs, 90Sr, totU, 238Pu, 239,240Pu, and 241Am in soils (0- to 12-in. [31 cm] depth underneath the tree), pinon pine shoots (PPS), and pinon pine nuts (PPN) collected from LANL lands and regional background (BG) locations, (2) committed effective dose equivalent (CEDE) from the ingestion of nuts, and (3) soil to PPS to PPN concentration ratios (CRs). Most radionuclides, with the exception of 3H in soils, were not significantly higher (p < 0.10) in soils, PPS, and PPN collected from LANL as compared to BG locations, and concentrations of most radionuclides in PPN fromLANL have decreased over time. The maximum net CEDE (the CEDE plus two sigma minus BG) at the most conservative ingestion rate (10 lb [4.5 kg]) was 0.0018 mrem (0.018 microSv); this is far below the International Commission on Radiological Protection (all pathway) permissible dose limit of 100 mrem (1000 microSv). Soil-to-nut CRs for most radionuclides were within the range of default values in the literature for common fruits and vegetables.

Radionuclides and trace elements in fish collected upstream and downstream of Los Alamos National Laboratory and the doses to humans from the consumption of muscle and bone

The purpose of this study was to determine radionuclide and trace element concentrations in bottom-feeding fish (catfish, carp, and suckers) collected from the confluences of some of the major canyons that cross Los Alamos National Laboratory (LANL) lands with the Rio Grande (RG) and the potential radiological doses from the ingestion of these fish. Samples of muscle and bone (and viscera in some cases) were analyzed for 3H, 90Sr, 137Cs, totU, 238Pu, 239,240Pu, and 241Am and Ag, As, Ba, Be, Cr, Cd, Cu, Hg, Ni, Pb, Sb, Se, and Tl. Most radionuclides, with the exception of 90Sr, in the muscle plus bone portions of fish collected from LANL canyons/RG were not significantly (p < 0.05) higher from fish collected upstream (San Ildefonso/background) of LANL. Strontium-90 in fish muscle plus bone tissue significantly (p < 0.05) increases in concentration starting from Los Alamos Canyon, the most upstream confluence (fish contained 3.4E-02 pCi g-1 [126E-02 Bq kg-1]), to Frijoles Canyon, the most downstream confluence (fish contained 14E-02 pCi g-1 [518E-02 Bq kg-1]). The differences in 90Sr concentrations in fish collected downstream and upstream (background) of LANL, however, were very small. Based on the average concentrations (+/- 2SD) of radionuclides in fish tissue from the four LANL confluences, the committed effective dose equivalent from the ingestion of 46 lb (21 kg) (maximum ingestion rate per person per year) of fish muscle plus bone, after the subtraction of background, was 0.1 +/- 0.1 mrem y-1 (1.0 +/- 1.0 microSv y-1), and was far below the International Commission on Radiological Protection (all pathway) permissible dose limit of 100 mrem y-1 (1000 microSv y-1). Of the trace elements that were found above the limits of detection (Ba, Cu, and Hg) in fish muscle collected from the confluences of canyons that cross LANL and the RG, none were in significantly higher (p < 0.05) concentrations than in muscle of fish collected from background locations.

Antioxidant effects of 1,4-dihydropyridine and nitroso aryl derivatives on the Fe+3/ascorbate-stimulated lipid peroxidation in rat brain slices

1. Lipid peroxidation in rat brain slices was induced by Fe+3/ascorbate. 2. Brain lipid peroxidation, as measured by malondialdehyde formation, was inhibited by all the tested nitro aryl 1,4-dihydropyridine derivatives over a wide range of concentrations. The time-course antioxidant effects of the most representative agents were assessed. On the basis of both time-course and IC50 experiments the tentative order of antioxidant activity on rat brain slices could be: nicardipine>nisoldipine> (R,S/S,R)-furnidipine > (R,R/S,S)-furnidipine>nitrendipine>nimodipine> nifedipine. 3. 1,4-Dihydropyridine derivatives that lack of a nitro group in the molecule (isradipine, amlodipine) also inhibited lipid peroxidation in rat brain slices but at higher concentrations than that of nitro-substituted derivatives. 4. All the tested nitroso aryl derivatives [2,6-dimethyl-4-(2-nitrosophenyl)-3,5-pyridinedicar. boxylic acid dimethyl ester (NTP), nitrosotoluene, nitrosobenzene] were more potent inhibitors of lipid peroxidation than were the parent nitro compounds. In conclusion, on the basis of the IC50 values determined, the rank order of antioxidant potency for these derivatives can be established as: ortho-nitrosotoluene>NTP>nitrosobenzene.

Electrochemical study of nisoldipine: analytical application in pharmaceutical forms and photodegradation

The anodic and cathodic behavior of nisoldipine, 3-isobutyl-5-methyl-1,4-dihydro-2,6-dimethyl-4-(2-nitrophenyl)pyridine-3 ,5-dicarboxylate, are reported. This drug belongs to the nitroaryl-1,4-dihydropyridine family, known as calcium channel antagonist and employed in therapeuticalls as peripheral and cerebral vasodilators, in the treatment of the arterial hypertension. The cathodic response corresponds to the reduction of the nitroaromatic group to generate the hydroxylamine derivative. The study by dc and d.p.p. reveals the appearance of four signals depending on pH: Signal I (pH 1-11.5) R - NO2 + 4H+ + 4e- --> R - NHOH + H2O; Signal II (pH 1-5) R - N+H2OH + 2H+ + 2e- --> RN+H3 + H2O; Signal III (pH > 11.5) R - NO2 + e- <--> R - NO2.-; Signal IV (pH > 11.5) R - NO2.- + 3e- + 4H+ --> R - NHOH. In contrast, the anodic response corresponds to the oxidation of the 1,4-dihydropyridine ring to generate the corresponding pyridine derivative. Both, cathodic (d.p.p.) and anodic signals (d.p.v.) were employed to develop analytical methodology for the determination of the drug. The repeatability of the measurements for both methods was adequate with R.S.D. of 1.4% (n = 10) and 2.1% (n = 10) for d.p.p. and d.p.v., respectively. Also recovery studies, 103.8% (R.S.D. 2.65%) by d.p.p. and 98.7% (R.S.D. 2.1%) by d.p.v. show that the accuracy and precision of the developed methods were adequate. The analytical methods were successfully applied to the determination of nisoldipine in both tablets and capsules. In addition, a preliminary study of the photostability of nisoldipine (using both UV and artificial day light) was completed. The identity of the main electroactive photodegradation products by GC with spectrometry detection is provided.

The uptake of radionuclides by beans, squash, and corn growing in contaminated alluvial soils at Los Alamos National Laboratory

Pinto beans (Phaselous vulgaris), sweet corn (Zea mays), and zucchini squash (Cucurbita pepo) were grown in a field pot study using alluvial floodplain soils contaminated with various radionuclides within Los Alamos Canyon (LAC) at Los Alamos National Laboratory, New Mexico. Soils as well as washed edible (fruit) and nonedible (stems and leaves) crop tissues were analyzed for tritium (3H), cesium (137Cs), strontium (90Sr), plutonium (238Pu and 239,240Pu), americium (241Am), and total uranium (totU). Most radionuclides, with the exception of 3H and totU, in soil and crop tissues from LAC were detected in significantly higher concentrations (p < 0.05) than in soil or crop tissues collected from regional background locations. Significant differences in radionuclide concentrations among crop species (squash were generally higher than beans or corn) and plant parts (nonedible tissue were generally higher than edible tissue) were observed. Most soil-to-plant concentration ratios for radionuclides in edible and nonedible crop tissues grown in soils from LAC were within default values in the literature commonly used in dose and risk assessment models. Overall, the maximum net positive committed effective dose equivalent (CEDE)--the CEDE plus two sigma for each radioisotope minus background and then all positive doses summed--to a hypothetical 50-year resident that ingested 352 lb ([160 kg]; the maxiumum ingestion rate per person per year) of beans, corn, and squash in equal proportions was 74 mrem y-1 (740 microS y-1). This upper bound dose was below the International Commission on Radiological Protection permissible dose limit of 100 mrem y-1 (1000 microS y-1) from all pathways and corresponds to a risk of an excess cancer fatality of 3.7 x 10(-5) (37 in a million), which is also below the U.S. Environmental Protection Agency's guideline of 10(-4).

Glycohemoglobins in normal and diabetic pregnancy

Glycosylated hemoglobin (HbA1) concentration was measured in 155 pre- and 30 postpartum patients to study its correlation with glucose metabolism and perinatal outcome in patients suspected of carbohydrate intolerance during pregnancy. Though the mean HbA1 values were significantly higher in gestational diabetics compared to normal pregnant controls, the large overlap between HbA1 levels of diabetic patients and levels in the of normal range, make HbA1 an unreliable screening device for diabetes. However, if the HbA1 level was elevated in patients suspected of carbohydrate intolerance, but who had a normal glucose tolerance test, the perinatal outcome in terms of macrosomia and neonatal metabolic abnormalities was similar to that of the group with gestational diabetes. HbA1 measurements should be obtained in these women, and, if elevated, maternal and fetal surveillance is recommended. HbA1 level is not a useful predictor of birthweight, though may be of value as a postpartum screen for unrecognized diabetes and may help discriminate between a constitutionally large but otherwise normal newborn and a large infant of a diabetic mother.