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Purpose: Nursing turnover is a leading cause of inefficiency in health care delivery. Few studies have examined turnover among nurses who work in rural areas., Methods: We accessed human resources data that tracked hiring and terminations from a large health system operating in South Dakota, North Dakota, and Minnesota between January 2016 and December 2017. Our study sample included 7,634 registered nurses, 1,765 of whom worked in a rural community. Within the health system, there were 27 affiliated hospitals, 17 of which were designated critical access hospitals. We estimated nursing turnover rates overall and stratified turnover rates by available demographic and occupational characteristics, including whether the nurse worked in a community with an affiliated acute care hospital or critical access hospital., Findings: Overall, 19% of nurses left their position between January 2016 and December 2017. Turnover rates were associated with state, nurse gender and age, and occupational tenure, but were similar in urban and rural areas. Of note, turnover rates were significantly higher in communities without an affiliated acute care hospital or critical access hospital., Conclusion: Between 2016 and 2017, nearly 1 in 5 nurses working in this health system left their position. Turnover rates differed based on nurse demographics and selected occupational characteristics, including tenure. We also found higher turnover rates among nurses who worked in communities without an affiliated hospital, which points to a potential but unexplored benefit of hospitals in rural areas., (© 2022 National Rural Health Association.)

Background: Rare diseases (RD) are a diverse collection of more than 7-10,000 different disorders, most of which affect a small number of people per disease. Because of their rarity and fragmentation of patients across thousands of different disorders, the medical needs of RD patients are not well recognized or quantified in healthcare systems (HCS)., Methodology: We performed a pilot IDeaS study, where we attempted to quantify the number of RD patients and the direct medical costs of 14 representative RD within 4 different HCS databases and performed a preliminary analysis of the diagnostic journey for selected RD patients., Results: The overall findings were notable for: (1) RD patients are difficult to quantify in HCS using ICD coding search criteria, which likely results in under-counting and under-estimation of their true impact to HCS; (2) per patient direct medical costs of RD are high, estimated to be around three-fivefold higher than age-matched controls; and (3) preliminary evidence shows that diagnostic journeys are likely prolonged in many patients, and may result in progressive, irreversible, and costly complications of their disease CONCLUSIONS: The results of this small pilot suggest that RD have high medical burdens to patients and HCS, and collectively represent a major impact to the public health. Machine-learning strategies applied to HCS databases and medical records using sentinel disease and patient characteristics may hold promise for faster and more accurate diagnosis for many RD patients and should be explored to help address the high unmet medical needs of RD patients., (© 2021. The Author(s).)

Rasch modeling was used to examine the 25-item Connor-Davidson Resilience Scale within adults ( n  = 410) in a weight management program. Rasch analysis assessed model-data fit, item difficulty and person's resilience level, an item-person map to evaluate relative distribution items and persons, and rating scale function. Four misfit items were identified and removed. Item difficulty ranged from 1.25 to 1.19 logits (higher logit values indicate more difficult items). Persons' resilience level had wide distribution (resilience = 2.27 ± 1.56 logits). Item difficulty levels did not adequately assess higher resilience levels. An improved inventory that measures a wider range of resilient behaviors would improve measurement quality.

Background: Traditional research approaches do not promote timely implementation of evidence-based innovations (EBIs) to benefit patients. Embedding research within health systems can accelerate EBI implementation by blending rigorous methods with practical considerations in real-world settings. A state-of-the-art (SOTA) conference was convened in February 2019 with five workgroups that addressed five facets of embedded research and its potential to impact healthcare. This article reports on results from the workgroup focused on how embedded research programs can be implemented into heath systems for greatest impact., Methods: Based on a pre-conference survey, participants indicating interest in accelerating implementation were invited to participate in the SOTA workgroup. Workgroup participants (N = 26) developed recommendations using consensus-building methods. Ideas were grouped by thematic clusters and voted on to identify top recommendations. A summary was presented to the full SOTA membership. Following the conference, the workgroup facilitators (LJD, CDH, NR) summarized workgroup findings, member-checked with workgroup members, and were used to develop recommendations., Results: The workgroup developed 12 recommendations to optimize impact of embedded researchers within health systems. The group highlighted the tension between "ROI vs. R01" goals-where health systems focus on achieving return on their investments (ROI) while embedded researchers focus on obtaining research funding (R01). Recommendations are targeted to three key stakeholder groups: researchers, funders, and health systems. Consensus for an ideal foundation to support optimal embedded research is one that (1) maximizes learning; (2) aligns goals across all 3 stakeholders; and (3) implements EBIs in a consistent and timely fashion., Conclusions: Four cases illustrate a variety of ways that embedded research can be structured and conducted within systems, by demonstrating key embedded research values to enable collaborations with academic affiliates to generate actionable knowledge and meaningfully accelerate implementation of EBIs to benefit patients., Implications: Embedded research approaches have potential for transforming health systems and impacting patient health. Accelerating embedded research should be a focused priority for funding agencies to maximize a collective return on investment., (Published by Elsevier Inc.)

Evolutionary arms-races between plants and insect herbivores have long been proposed to generate key innovations such as plant toxins and detoxification mechanisms that can drive diversification of the interacting species. A novel front-line of plant defence is the killing of herbivorous insect eggs. We test whether an egg-killing plant trait has an evolutionary basis in such a plant-insect arms-race. Within the crucifer family (Brassicaceae), some species express a hypersensitive response (HR)-like necrosis underneath butterfly eggs (Pieridae) that leads to eggs desiccating or falling off the plant. We studied the phylogenetic distribution of this trait, its egg-killing effect on and elicitation by butterflies, by screening 31 Brassicales species, and nine Pieridae species. We show a clade-specific induction of strong, egg-killing HR-like necrosis mainly in species of the Brassiceae tribe including Brassica crops and close relatives. The necrosis is strongly elicited by pierid butterflies that are specialists of crucifers. Furthermore, HR-like necrosis is linked to PR1 defence gene expression, accumulation of reactive oxygen species and cell death, eventually leading to egg-killing. Our findings suggest that the plants' egg-killing trait is a new front on the evolutionary arms-race between Brassicaceae and pierid butterflies beyond the well-studied plant toxins that have evolved against their caterpillars., (© 2020 The Authors. New Phytologist © 2020 New Phytologist Foundation.)

Background: Diabetes is a medical and economic burden in the United States. In this study, a machine learning predictive model was developed to predict unplanned medical visits among patients with diabetes, and findings were used to design a clinical intervention in the sponsoring healthcare organization. This study presents a case study of how predictive analytics can inform clinical actions, and describes practical factors that must be incorporated in order to translate research into clinical practice., Methods: Data were drawn from electronic medical records (EMRs) from a large healthcare organization in the Northern Plains region of the US, from adult (≥ 18 years old) patients with type 1 or type 2 diabetes who received care at least once during the 3-year period. A variety of machine-learning classification models were run using standard EMR variables as predictors (age, body mass index (BMI), systolic blood pressure (BP), diastolic BP, low-density lipoprotein, high-density lipoprotein (HDL), glycohemoglobin (A1C), smoking status, number of diagnoses and number of prescriptions). The best-performing model after cross-validation testing was analyzed to identify strongest predictors., Results: The best-performing model was a linear-basis support vector machine, which achieved a balanced accuracy (average of sensitivity and specificity) of 65.7%. This model outperformed a conventional logistic regression by 0.4 percentage points. A sensitivity analysis identified BP and HDL as the strongest predictors, such that disrupting these variables with random noise decreased the model's overall balanced accuracy by 1.3 and 1.4 percentage points, respectively. These recommendations, along with stakeholder engagement, behavioral economics strategies, and implementation science principles helped to inform the design of a clinical intervention targeting behavioral changes., Conclusion: Our machine-learning predictive model more accurately predicted unplanned medical visits among patients with diabetes, relative to conventional models. Post-hoc analysis of the model was used for hypothesis generation, namely that HDL and BP are the strongest contributors to unplanned medical visits among patients with diabetes. These findings were translated into a clinical intervention now being piloted at the sponsoring healthcare organization. In this way, this predictive model can be used in moving from prediction to implementation and improved diabetes care management in clinical settings.

The study objective was to (1) develop a statistical model that creates a novel patient engagement score (PES) from electronic medical records (EMR) and health claim data, and (2) validate this developed score using health-related outcomes and charges of patients with multiple chronic conditions (MCCs). This study used 2014-16 EMR and health claim data of patients with MCCs from Sanford Health. Patient engagement score was created based on selected patients' engagement behaviors using Gaussian finite mixture model. The PES was validated using multiple logistic and linear regression analyses to examine the associations between the PES and health-related outcomes, and hospital charges, respectively. Patient engagement score was generated from 5095 patient records and included low, medium, and high levels of patient engagement. The PES was a significant predictor for low-density lipoprotein, emergency department visit, hemoglobin A 1c , estimated glomerular filtration rate, hospitalization, and hospital charge. The PES derived from patient behaviors recorded in EMR and health claim data can potentially serve as a patient engagement measure. Further study is needed to refine and validate the newly developed score., Competing Interests: Declaration of Conflicting Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Emily Griese and Ariella Selya received funding from the National Institutes of General Medical Sciences (NIGMS) of the NIH, grant number 1P20GM121341., (© The Author(s) 2021.)

Background: Smoking exacerbates the complications of diabetes, but little is known about whether patients with diabetes who smoke have more unplanned medical visits than those who do not smoke. This study examines the association between smoking status and unplanned medical visits among patients with diabetes., Methods: Data were drawn from electronic medical records (EMR's) from a large healthcare provider in the Northern Plains region of the US, from adult (≥18 years old) patients with type 1 or type 2 diabetes who received care at least once during 2014-16 (N = 62,149). The association between smoking status (current, former, or never smoker) and having ≥1 unplanned visit (comprised of emergency department visits, hospitalizations, hospital observations, and urgent care) was examined after adjusting for age, race/ethnicity, and body mass index (BMI). The top ten most common diagnoses for unplanned visits were examined by smoking status., Results: Both current and former smoking were associated with an approximately 1.2-fold increase in the odds of having at least one unplanned medical visit in the 3-year period (OR = 1.22, 95% CI = 1.16-129; OR = 1.23, 95% CI = 1.19-1.28, respectively), relative to never-smokers. Most common diagnoses for all patients were pain-related. However, diagnoses related to musculoskeletal system and connective tissue disorders were more common among smokers. Smoking is associated with a higher rate of unplanned medical visits among patients with diabetes in this regional healthcare system., Conclusions: Results from this study reveal higher rates of unplanned visits among smokers and former smokers, as well as increased frequencies of unplanned medical visits among current smokers.

The preference-performance hypothesis (PPH) states that herbivorous female insects prefer to oviposit on those host plants that are best for their offspring. Yet, past attempts to show the adaptiveness of host selection decisions by herbivores often failed. Here, we tested the PPH by including often neglected oviposition-induced plant responses, and how they may affect both egg survival and larval weight. We used seven Brassicaceae species of which most are common hosts of two cabbage white butterfly species, the solitary Pieris rapae and gregarious P. brassicae. Brassicaceous species can respond to Pieris eggs with leaf necrosis, which can lower egg survival. Moreover, plant-mediated responses to eggs can affect larval performance. We show a positive correlation between P. brassicae preference and performance only when including the egg phase: 7-day-old caterpillars gained higher weight on those plant species which had received most eggs. Pieris eggs frequently induced necrosis in the tested plant species. Survival of clustered P. brassicae eggs was unaffected by the necrosis in most tested species and no relationship between P. brassicae egg survival and oviposition preference was found. Pieris rapae preferred to oviposit on plant species most frequently expressing necrosis although egg survival was lower on those plants. In contrast to the lower egg survival on plants expressing necrosis, larval biomass on these plants was higher than on plants without a necrosis. We conclude that egg survival is not a crucial factor for oviposition choices but rather egg-mediated responses affecting larval performance explained the preference-performance relationship of the two butterfly species.

Compared to demographic data from other healthcare professions, genetic counselors (GCs) are more likely to be Caucasian females. Many current underrepresented in genetic counseling (URGC) professionals in the field found genetic counseling later in their careers due in part to their lack of awareness. A pilot study consisting of equal numbers of male and female sixth grade science club students was conducted to explore the impact that direct teaching might have on students' awareness of and interest in genetic counseling. The analysis used the non-parametric Wilcoxon signed rank test due to the ordinal, Likert-scale data. Results derived from a pre- and post-survey of lesson participants indicated a statistically significant increase in students' perceptions of having a role model in a science career. Efforts to reach local middle school students to highlight genetic counseling as a potential career choice, especially by role models, may add to the continued work being done to increase the diversity of future genetic counseling applicant pools.

Plants employ various defences killing the insect attacker in an early stage. Oviposition by cabbage white butterflies (Pieris spp.) on brassicaceous plants, including Brassica nigra, induces a hypersensitive response (HR) - like leaf necrosis promoting desiccation of eggs. To gain a deeper insight into the arms race between butterflies and plants, we conducted field and greenhouse experiments using different B. nigra genotypes. We investigated variation in HR and consequent survival of P. brassicae egg clusters. Impact of egg density, distribution type and humidity on HR formation and egg survival was tested. HR differed among plant genotypes as well as plant individuals. Egg density per plant did not affect HR formation. Remarkably, egg survival did not depend on the formation of HR, unless butterflies were forced to lay single eggs. Larval hatching success from single eggs was lower on plants expressing HR. This may be due to increased vulnerability of single eggs to low humidity conditions at necrotic leaf sites. We conclude that effectiveness of HR-like necrosis in B. nigra varies with plant genotype, plant individual and the type of egg laying behaviour (singly or clustered). By clustering eggs, cabbage white butterflies can escape the egg-killing, direct plant defence trait.

Progressive telomere shortening occurs in somatic cells, and with increasing donor age a significant decline in telomere length has been shown in various postnatal tissues. In contrast, little is known about changes in telomere length during human fetal development. Therefore, we measured telomere length in the leukocyte fraction of umbilical cord blood samples from 15 preterm (<37 wk of gestation) and 11 full-term (>37 wk of gestation) neonates using the telomere restriction fragment assay. Whereas no differences in mean (+/- SD) telomere restriction fragment between the groups of preterm neonates (8512 +/- 523 bp) and full-term newborns (8323 +/- 503 bp) could be found, significantly longer telomeres (p = 0.002) were found in very low birth weight preterm neonates when compared with low birth weight preterm neonates. In addition, a rapid and significant decline in mean telomere restriction fragment was observed between 27 and 32 wk of gestation (p = 0.02, r = 0.79) followed by a period of no significant loss of telomere repeats between 33 and 42 wk of gestation. These results are consistent with the known almost maximal proliferation rate of hematopoietic progenitor cells before 32 wk of gestation. The initial decrease in telomere restriction fragment could be caused by ontogeny-related functional alterations of hematopoietic cells or differences in stem cell turnover or the rate of telomere loss per cell division.

The polymorphisms of the important xenobiotic metabolizing enzymes CYP2D6, CYP2C19 and CYP2E1 have been studied extensively in a large number of populations and show significant heterogeneity in the frequency of different alleles/genotypes and in the prevalence of the extensive and poor metabolizer phenotypes. Understanding of inter-ethnic differences in genotypes is important in prediction of either beneficial or adverse effects from therapeutic agents and other xenobiotics. Since no data were available for Australian Aborigines, we investigated the frequencies of alleles and genotypes for CYP2D6, CYP2C19 and CYP2E1 in a population living in the far north of Western Australia. Because of its geographical isolation, this population can serve as a model to study the impact of evolutionary forces on the distribution of different alleles for xenobiotic metabolizing enzymes. Twelve CYP2D6 alleles were analysed. The wild-type allele *1 was the most frequent (85.81%) and the non-functional alleles (*4, * 5, * 16) had an overall frequency of less than 10%. Only one subject (0.4%) was a poor metabolizer for CYP2D6 because of the genotype *5/*5. For CYP2C19, the frequencies of the *1 (wild-type) and the non-functional (*2 and *3) alleles were 50.2%, 35.5% and 14.3%, respectively. The combined CYP2C19 genotypes (*2/*2, *2/*3 or *3/*3) correspond to a predicted frequency of 25.6% for the CYP2C19 poor metabolizer phenotype. For CYP2EI, only one subject had the rare c2 allele giving an overall allele frequency of 0.2%. For CYP2D6 and CYP2C19, allele frequencies and predicted phenotypes differed significantly from those for Caucasians but were similar to those for Orientals indicating a close relationship to East Asian populations. Differences between Aborigines and Orientals in allele frequencies for CYP2D6* 10 and CYP2E1 c2 may have arisen through natural selection, or genetic drift, respectively.

A subgroup of 10-15% of Caucasians are termed phenotypical 'intermediate metabolizers' of drug substrates of CYP2D6 because they have severely impaired yet residual in-vivo function of this cytochrome P450. Genotyping based on the currently known CYP2D6 alleles does not predict this phenotype satisfactorily. A systematic sequencing strategy through 1.6 kb of the CYP2D6 5'-flanking sequence revealed six mutations of which three were exclusively associated with the functional CYP2D6*2 allele (-1496 C to G; -652 C to T; and -590 G to A), two were associated with the nonfunctional *4 and with the functional *10-alleles (-1338 C to T and -912 G to A) and one (-1147 A to G) was seen in all *2, *4 and *10-alleles investigated. The -1496 C to G mutation was found to be polymorphic within CYP2D6*2 alleles. In a family study, the wild-type CYP2D6 *2[-1496 C] and the novel variant [-1496 G] allele co-segregated with lower and higher CYP2D6 in-vivo function, respectively, as shown by phenotyping using sparteine as probe drug. In a representative population sample selected for genotypes comprising one CYP2D6*2 and one non-functional allele, the median urinary metabolic ratio (MRs) for sparteine oxidation was 4.4-fold reduced in individuals with the variant allele (*2[-1496 G], MRs = 0.53, n = 27) compared with individuals lacking the mutation (*2[-1496 C], MRs = 2.33, n = 12; P < 0.0001). The mutation -1496 C to G has an estimated frequency of approximately 20% in the general population and allows establishment of a genotype for the identification of over 60% of intermediate metabolizers in Caucasian populations.

Aims: The pharmacokinetics of dihydrocodeine (DHC) and its active metabolite dihydromorphine (DHM) were assessed after a single oral dose of DHC and after increasing doses of DHC at steady-state. Methods Twelve healthy male volunteers (18-45 years, CYP2D6 extensive metabolizers (EMs), MR<1 took a single oral dose (s.d.) of DHC 60 mg after breakfast. After 60 h DHC 60 mg was administered twice daily for 3 days, the dose was increased to 90 mg twice daily for 3 days, the final dose of 120 mg was administered twice daily for 3 days (multiple dose: m.d.). Blood sampling and urine collection: during 60 h after s.d. and during 12 h after m.d. Results No significant differences in the area under the curve (AUC) of both, DHC and DHM could be detected after a single oral dose of 60 mg DHC (AUC (0,infinity)) and during steady-state doses of 60 mg DHC (AUC(0,12 h)). During increasing steady-state doses of DHC, the data showed a dose linearity of AUC, maximal serum concentration (Cmax ) and minimal steady-state serum levels (Cssmin) of both, DHC and DHM (P<0.0001), point estimates of DHC dose corrected AUCs were well within the bioequivalence range (60 mg: 0.989; 90%CI 0.951-1. 028, 90 mg: 0.997; 90%CI 0.959-1.036, 120 mg: 0.977; 90%CI 0.940-1. 016). O-demethylation from DHC to DHM remained constant within the increasing steady-state doses of DHC in the 12 extensive metabolizers of CYP2D6., Conclusions: In the studied dose range (60-120 mg) the pharmacokinetics of DHC and its active metabolite DHM are linear in EMs of CYP2D6.

The development of CYP2D6 has been attributed to the need of earth-dwelling animals to detoxify toxic xenobiotics (phytoalexins) present in plants. This hypothesis has been extrapolated to humans, but is yet unconfirmed. Therefore, we studied two Amerindian populations as the best available model to test the effect of selection through diet on human CYP2D6 evolution. The frequency of sparteine poor metabolizers in Ngawbe was 4.4% (n = 344), while the frequency in Embera was 2.2% (n = 153). Among Ngawbe and Embera, CYP2D6*4 (allelic frequencies for each tribe, respectively: 0.171; 0.14), CYP2D6*6 (0.005; 0.011) and CYP2D6*10 (0.175; 0.069) were detected, while CYP2D6*3, CYP2D6*5, CYP2D6*9 and CYP2D6*16 were absent. All poor metabolizers possessed either CYP2D6*4 or CYP2D6*6 and there were no disagreements between genotypic and phenotypic data. The total frequency of mutant alleles showed no difference among Amerindians or when compared to Caucasians. It was higher than in Chinese, since the frequency of CYP2D6*4 was higher in Amerindians. XbaI restriction fragment length polymorphisms haplotypes were very homogeneous in Amerindians, because the only fragment that hybridized with the CYP2D6 cDNA probe was the 29 kb (not 42/44 kb or 11.5/13 kb). This indicated no gene cluster recombinations that generate insertions or deletions. We propose that in earlier hominids and humans, CYP2D6 had increasingly become a vestigial characteristic unconstrained by dietary stressors, as a result of cultural survival strategies. Human CYP2D6 evolution was preferentially affected by random genetic drift, and not by adaptive or purifying selection.

Modafinil is a psychostimulant compound that is just now becoming available in many countries for treatment of narcoleptic and hypersomnic patients. Whereas sleep attacks and drowsiness can be effectively improved, the drug does not sufficiently reduce cataplectic seizures. It therefore is often used in combination with tricyclic antidepressant medication, although little is known about the possible interactions. This case report describes a narcoleptic patient chronically treated with clomipramine who started receiving modafinil. The blood concentrations of clomipramine and its metabolite showed a significant dose-dependent and reversible increase under modafinil. Since the patient was genotypically and phenotypically a cytochrome P450 2D6 poor metabolizer, the authors attribute the relevant pharmacokinetic interaction to another clomipramine-metabolizing enzyme.

The polymorphic cytochrome P450 CYP2D6 catalyses the biotransformation of at least 40 drugs. The CYP2D6 genetic polymorphism is responsible for pronounced interindividual differences in plasma concentrations and, hence, in drug action and side-effects after administration of the same dose. Provided there is a close relationship between CYP2D6 genotypes and catalytic function, genotyping could be used in the clinical setting for individualization of drug dose. In the present study, we evaluated the relationship between the in-vivo enzyme activity and 35 different genotypes in order to determine whether genotyping can be used to predict a person's metabolic capacity for CYP2D6-catalysed drug oxidation using sparteine as a probe drug. One hundred and ninety-five Caucasian individuals were genotyped for seven nonfunctional (CYP2D6 x 3, x 4, x 5, x 6, x 7, x 8, x 16) and eight functional alleles (CYP2D6 x 1, x 2, x 2 x 2, x 2B, x 2B x 2, x 9, x 10, x 17). The metabolic ratio distribution for sparteine showed trimodality, with 15 poor metabolizers, 21 intermediate metabolizers, and 1.59 extensive and ultrarapid metabolizers. All poor metabolizers were unambiguously identified as carriers of two nonfunctional alleles. In contrast, the most frequent functional genotypes extensively overlapped and, with few exceptions, genotype was not a useful predictor of function. Gene dose effects among homozygotes and heterozygotes of the major functional alleles were not significant and could not explain the wide variations. Only a minor fraction of phenotypical ultrarapid metabolizers, arbitrarily defined as individuals with a metabolic ratio < 0.2, could be identified as carriers of three functional gene copies, including duplicated CYP2D6 x 2 x 2 alleles. Similarly, only a minor fraction of the intermediate metabolizers had predictive genotypes involving alleles coding for enzyme with impaired function. Thus, genotyping correctly identifies poor metabolizers, but quantitative prediction of drug metabolism capacity among extensive metabolizers is not possible.

We have studied whether CYP2D6 is expressed in human lung tissue, using a specific and sensitive reverse transcriptase-polymerase chain reaction method and immunohistochemistry. Seven out of the eight patients were extensive metabolizers as shown by genotyping for the CYP2D6 (debrisoquine-sparteine) polymorphism. To investigate whether expression of CYP2D6 in lung tumours is different from that in normal lung tissue, tumour tissue samples were also obtained from the same eight patients. Correctly spliced CYP2D6 mRNA was detected by RT-PCR analysis in human liver and duodenum but not in any of the lung samples. In accordance with these negative results, immunoreactivity for CYP2D6 protein, using specific monoclonal and polyclonal antibodies, was very low or absent. No specific cell type of lung tissue showed strong immunoreactivity for CYP2D6, although expression of CYP3A could be clearly demonstrated in the same tissue samples. Moreover, a Western blot analysis revealed no signal in lung microsomes from two additional extensive metabolizers. Taken together, these results indicate that expression of CYP2D6 in human lung is absent or very low. These findings thus argue against a significant local metabolic activation of procarcinogenic agents by CYP2D6 in the lung.

The CYP2D6 gene on human chromosome 22 encodes a cytochrome P450 responsible for oxidative metabolism of over 30 clinically used drugs. The CYP2D6 gene is highly polymorphic with more than 20 alleles described to date. Some of these harbour loss-of-function mutations which lead to the poor metabolizer phenotype in 5-10% of Caucasians. These individuals are at increased risk of suffering from adverse side effects or to experience therapeutic failure following drug treatment. Phenotype determination requires ingestion of a probe drug and has other inherent problems. Due to the increasing number of alleles known, comprehensive CYP2D6 genotyping using the conventional assays has become cumbersome and time consuming. We have therefore developed a streamlined and more rapid CYP2D6 genotyping procedure. Use of long distance PCR allowed the amplification of a 4666 bp fragment which contains the entire CYP2D6 gene. The 4.7 kb fragment serves as a template for a multiplex allele-specific PCR assay to simultaneously identify the five PM-associated alleles, CYP2D6*3 (A), *4 (B), *6 (T), *7 (E), and *8 (G). Together with the CYP2D6 deletion allele CYP2D6*5 (D), which can be detected in a separate PCR assay, these alleles are responsible for the PM phenotype in approximately 99% of Caucasian individuals. We tested the reliability of the procedure by analysing DNA from more than 80 individuals with known CYP2D6 genotypes. Twelve different genotypes were present among these samples and all of them were correctly identified.

The essential role of cytochrome P450 3A4 (CYP3A4) in human small intestine is well established, and CYP3A5 seems also to be present in most subjects. However, the role of CYP3A7 in the small intestine remains poorly characterized. We have therefore studied the expression of these CYP3A enzymes in the duodenal tissue from 19 patients, using a specific RT-PCR (reverse transcriptase-polymerase chain reaction) method. CYP3A4 and CYP3A5 were present at the mRNA level in the duodenum of 18 and 19 of the 19 patients studied, respectively. In contrast, mRNA for CYP3A7 was not found in the duodenum in any of the patients. These findings strongly suggest that, unlike CYP3A4 and CYP3A5, CYP3A7 is not expressed in human duodenum.

We have previously demonstrated expression of cytochrome P 450 3A (CYP3A) protein in pulmonary carcinomas and surrounding normal tissue, using immunohistochemistry. These results suggested that different CYP3A enzymes may be expressed in normal and tumour tissue. Therefore, the aim of the present study was to identify specific CYP3A enzymes expressed in normal human lung and lung tumours. Both normal lung tissue and tumour tissue from eight patients was analyzed for CYP3A4, CYP3A5 and CYP3A7 mRNA using a specific RT-PCR (reverse transcriptase-polymerase chain reaction) method. Identical samples were subjected to immunohistochemical analysis of CYP3A protein. CYP3A5 was the major enzyme of the CYP3A subfamily present at the mRNA level in both normal human lung and lung tumours. CYP3A5 mRNA was detected in normal lung tissue in all eight cases and in tumour tissue in four cases. CYP3A7 mRNA was detected in five cases in normal tissue and in one tumour. Notably, no CYP3A4 mRNA was found in any of the samples. Immunohistochemical staining for CYP3A protein was found in normal lung tissue in each case. Interestingly, all pulmonary carcinomas showed immunostaining for CYP3A, while mRNA for CYP3A enzymes was found in only four cases. In summary, our study indicates a specific expression pattern of the members of the CYP3A subfamily in normal human lung and lung tumours. These findings have potential clinical significance, since it has been recently shown that CYP3A5 catalyzes the activation of the anticancer pro-drugs cyclophosphamide and ifosfamide. Thus, local activation of these agents may take place in pulmonary carcinomas and surrounding normal tissues.

Background: The opioid dihydrocodeine (DHC) is frequently used as an analgesic and antitussive agent. However, until now there have been no detailed data on dihydrocodeine metabolism in humans. We therefore investigated pathways that contribute to elimination of dihydrocodeine, and we tested the hypothesis that dihydrocodeine O-demethylation to dihydromorphine (DHM) is catalyzed by the polymorphic CYP2D6., Methods: A single oral dose of dihydrocodeine was administered to six extensive (metabolic ratio [MR] < or = 1), two intermediate (1 < MR < 20) and six poor metabolizers (MR > or = 20) of sparteine/debrisoquin. Serum concentrations of dihydrocodeine and dihydromorphine were measured up to 25 hours, and urinary excretion of conjugated and unconjugated dihydrocodeine, dihydromorphine, and nordihydrocodeine were determined., Results: There were no differences in the pharmacokinetics of dihydrocodeine between extensive and poor metabolizers. However, the area under the serum concentration-time curve (AUC), partial metabolic clearance, and total urinary recovery of dihydromorphine were significantly lower in poor metabolizers (10.3 +/- 6.1 nmol.hr/L; 7.0 +/- 4.1 ml/min; 1.3% +/- 0.9% of dose) compared with extensive metabolizers (75.5 +/- 42.9 nmol.hr/L; 49.7 +/- 29.9 ml/min; 8.9% +/- 6.2%; p < 0.01). There was a strong correlation between the AUCDHC/AUCDHM ratio and the urinary metabolic ratio of sparteine (rS = 0.89, p = 0.001). No significant differences between extensive and poor metabolizers were detected in urine for conjugated dihydrocodeine (extensive metabolizers, 27.7% of dose; poor metabolizers, 31.5%), unconjugated dihydrocodeine (extensive metabolizers, 31.1%; poor metabolizers, 31.1%), conjugated nordihydrocodeine (extensive metabolizers, 6.3%; poor metabolizers, 5.4%), or unconjugated nordihydrocodeine (extensive metabolizers, 15.8%; poor metabolizers, 19.5%)., Conclusions: Dihydrocodeine O-demethylation to dihydromorphine is impaired in poor metabolizers of sparteine. The main urinary metabolites after administration of dihydrocodeine are the parent compound and its conjugates in extensive and poor metabolizers.

The sparteine/debrisoquine polymorphism is a clinically important genetic deficiency of cytochrome P4502D6-catalyzed oxidative drug metabolism. 5-10% of Caucasians designated as poor metabolizers have a severely impaired capacity to metabolize more than 30 therapeutically used drugs. Genotyping of a random Caucasian population for the known cytochrome P4502D6 mutations A, B and D which are associated with the poor metabolizer phenotype has revealed a substantial number of misclassified poor metabolizers indicating the existence of one or more unknown mutations which cannot be identified with the currently available genotyping assays. Therefore we have cloned and sequenced one nonfunctional cytochrome P4502D6 allele of a misclassified poor metabolizer and could identify a single missense mutation designated E mutation at position 3023(A-C) in exon 6. Direct sequencing analysis, FokI restriction analysis and a newly developed allele-specific polymerase chain reaction assay were applied to analyze for this mutation in a population study. Three out of 97 randomly selected Caucasians were carriers of this mutation and thus the E allele has a frequency of 1.5% (confidence interval95% = 0.33 - 4.54%). Since only 2 out of 4 misclassified poor metabolizers carried the E mutation, additional unknown mutant alleles must exist. Computer modelling suggests that the E mutation, which results in a histidine to proline exchange in position 324 of the protein, may cause an alteration of the 3D structure of CYP2D6 in close vicinity to the active site thereby leading to total loss of enzyme function.

The impact of gender, use of oral contraceptive steroids (OCS), coffee consumption and of smoking on the metabolism of sparteine, caffeine, and paracetamol was studied in 194 randomly selected subjects (98 male and 95 female). Thirty-eight of the male volunteers were cigarette smokers, 40 of the female subjects were smokers and/or users of OCS. The metabolic ratio of sparteine oxidation (MRs) showed a trimodal distribution. 7.7% of the subjects had a MRs > 20 and thus were poor metabolizers (PMs). Within the extensive metabolizer (EM) subjects, a distinct subgroup accounting for 11% was observed with 20 > MRs > 1.2. Six of the 15 phenotypical PMs were heterozygous EMs by genotyping. This indicates the existence of one or several CYP2D6 mutations which cannot be identified by the currently employed genotyping methods. In each subgroup, i.e. smokers/OCS and non-smokers/non-OCS, the cumulative frequency distribution of the heterozygous (wt/B) phenotype caused a shift to higher MRs compared with the wild-type homozygotes (wt/wt). Thus, for the in vivo activity of CYP2D6, genetic determinants prevail over environmental factors. Smoking, use of oral contraceptive steroids, caffeine consumption, or gender had no influence on sparteine metabolism. The distribution of the paracetamol glucuronide/paracetamol metabolic ratio appeared to be unimodal although skewed. Glucuronidation capacity was clearly affected by gender, OCS use and smoking. It was higher in male than in female subjects. Male smokers had the highest, and female non-smokers/non-OCS users the lowest metabolic ratio. CYP1A2 activity, as determined by a caffeine metabolic ratio ((AFMU + 1X + 1U)/1, 7U), was multimodally distributed and was clearly increased in smokers. It was significantly correlated to paracetamol glucoronidation in male heavy smokers (r=0.85), suggesting an element of co-regulation of CYP1A2 and of paracetamol conjugating UDP-glucuronosyltransferase isozymes, including UGTI.6.

Tumor cell resistance to cytotoxic drugs is considered one of the major obstacles to successful chemotherapy. Multidrug resistance (MDR) describes the simultaneous expression of cellular resistance to a wide range of structurally and functionally unrelated drugs. The development of the multidrug resistance phenotype is accompanied by multiple morphological and biochemical changes: (a) increased glutathione levels in the cytoplasm, (b) modified levels of enzymes in the nucleus, particularly topoisomerase II, (c) increased DNA repair capacity and (d) overexpression of the (human) MDR1 gene encoding a transmembrane efflux pump (P-glycoprotein, gp-170), which leads to decreased intracellular accumulation and therefore to resistance to a variety of cytotoxic drugs. In this report we describe a competitive polymerase chain reaction (PCR) assay for the absolute quantification of MDR1 mRNA. This assay uses a transcript generated in vitro as an internal standard which is later coamplified together with the MDR1 cDNA. Both cDNAs exhibit the same MDR1 primer sites but differ in the length of the amplicon. For a second round of amplification we applied nested MDR1 primers and were successful in improving the sensitivity of this competitive PCR system. This test for characterizing the MDR1 expression offers high sensitivity and specificity and is therefore of great clinical relevance. It should be useful in improving monitoring and design of chemotherapy.

alpha-Thalassaemia is a disturbance of the alpha-chain synthesis of the haemoglobin, which occurs mostly in the Far East. On account of the total absence of alpha-chains, the homozygous form is considered to be fatal. However, beta and lambda chains exist abundantly. Abortion, intrauterine or perinatal death are the results of the extreme anaemia (Hb-Bart's syndrome), despite modern intensive medical care. The prenatal diagnosis is possible by: 1. DNA analysis of material obtained by chorion villi sampling or culture of fibroblasts, when a risk of re-occurrence is known to the physician. 2. Hb-electrophoresis from foetal blood in cases of hydrops of uncertain origin. When the diagnosis of this fatal disease is established, there is no foetal indication for delivery by Caesarian section.