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Iron deficiency is common in pregnant and lactating women and is associated with reduced cognitive development of the offspring. Since iron affects lipid metabolism, the availability of fatty acids, particularly the polyunsaturated fatty acids required for early neural development, was investigated in the offspring of female rats fed iron-deficient diets during gestation and lactation. Subsequent to the dams giving birth, one group of iron-deficient dams was recuperated by feeding an iron-replete diet. Dams and neonates were killed on postnatal days 1, 3 and 10, and the fatty acid composition of brain and stomach contents was assessed by gas chromatography. Changes in the fatty acid profile on day 3 became more pronounced on day 10 with a decrease in the proportion of saturated fatty acids and a compensatory increase in monounsaturated fatty acids. Long-chain polyunsaturated fatty acids in the n-6 family were reduced, but there was no change in the n-3 family. The fatty acid profiles of neonatal brain and stomach contents were similar, suggesting that the change in milk composition may be related to the changes in the neonatal brain. When the dams were fed an iron-sufficient diet at birth, the effects of iron deficiency on the fatty acid composition of lipids in both dam’s milk and neonates’ brains were reduced. This study showed an interaction between maternal iron status and fatty acid composition of the offspring’s brain and suggests that these effects can be reduced by iron repletion of the dam’s diet at birth.
The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural–geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.
This literature review provides an overview of the research using magnetic resonance imaging (MRI) in pediatric migraine and compares findings with the adult migraine literature. A literature search using PubMed was conducted using all relevant sources up to February 2019. Using MRI methods to categorize and explain pediatric migraine in comparison with adult migraine is important, in order to recognize and appreciate the differences between the two entities, both clinically and physiologically. We aim to demonstrate the differences and similarities between pediatric and adult migraine using data from white matter and gray matter structural studies, cerebral perfusion, metabolites, and functional MRI (fMRI) studies, including task-based and resting-state blood oxygen level-dependent studies. By doing this we identify areas that need further research, as well as possible areas where intervention could alter outcomes.
Englerophytum and Synsepalum are two closely related genera of trees and shrubs from the African tropics. Previous molecular studies have shown that these genera collectively form a clade within the subfamily Chrysophylloideae (Sapotaceae). However, little is known about the inter-relationships of the taxa within the Englerophytum–Synsepalum clade. In this study, nuclear ribosomal DNA and plastid trnH–psbA sequences were used to estimate the phylogeny within the clade. Results indicate that the clade consists of six major lineages, two composed solely of taxa from the genus Englerophytum and four composed of taxa from the genus Synsepalum. Each lineage can be distinguished by suites of vegetative and floral characters. Leaf venation patterns, calyx fusion, style length and staminodal structure were among the most useful characters for distinguishing clades. Some of the subclades within the Englerophytum–Synsepalum clade were also found to closely fit descriptions of former genera, most of which were described by Aubréville, that have since been placed in synonymy with Englerophytum and Synsepalum. The clade with the type species of Englerophytum also contains the type species of the genera Wildemaniodoxa and Zeyherella, which are confirmed as synonyms.
Timely identification of multidrug-resistant gram-negative infections remains an epidemiological challenge. Statistical models for predicting drug resistance can offer utility where rapid diagnostics are unavailable or resource-impractical. Logistic regression–derived risk scores are common in the healthcare epidemiology literature. Machine learning–derived decision trees are an alternative approach for developing decision support tools. Our group previously reported on a decision tree for predicting ESBL bloodstream infections. Our objective in the current study was to develop a risk score from the same ESBL dataset to compare these 2 methods and to offer general guiding principles for using each approach.
Using a dataset of 1,288 patients with Escherichia coli or Klebsiella spp bacteremia, we generated a risk score to predict the likelihood that a bacteremic patient was infected with an ESBL-producer. We evaluated discrimination (original and cross-validated models) using receiver operating characteristic curves and C statistics. We compared risk score and decision tree performance, and we reviewed their practical and methodological attributes.
In total, 194 patients (15%) were infected with ESBL-producing bacteremia. The clinical risk score included 14 variables, compared to the 5 decision-tree variables. The positive and negative predictive values of the risk score and decision tree were similar (>90%), but the C statistic of the risk score (0.87) was 10% higher.
A decision tree and risk score performed similarly for predicting ESBL infection. The decision tree was more user-friendly, with fewer variables for the end user, whereas the risk score offered higher discrimination and greater flexibility for adjusting sensitivity and specificity.
To enhance enrollment into randomized clinical trials (RCTs), we proposed electronic health record-based clinical decision support for patient–clinician shared decision-making about care and RCT enrollment, based on “mathematical equipoise.”
As an example, we created the Knee Osteoarthritis Mathematical Equipoise Tool (KOMET) to determine the presence of patient-specific equipoise between treatments for the choice between total knee replacement (TKR) and nonsurgical treatment of advanced knee osteoarthritis.
With input from patients and clinicians about important pain and physical function treatment outcomes, we created a database from non-RCT sources of knee osteoarthritis outcomes. We then developed multivariable linear regression models that predict 1-year individual-patient knee pain and physical function outcomes for TKR and for nonsurgical treatment. These predictions allowed detecting mathematical equipoise between these two options for patients eligible for TKR. Decision support software was developed to graphically illustrate, for a given patient, the degree of overlap of pain and functional outcomes between the treatments and was pilot tested for usability, responsiveness, and as support for shared decision-making.
The KOMET predictive regression model for knee pain had four patient-specific variables, and an r2 value of 0.32, and the model for physical functioning included six patient-specific variables, and an r2 of 0.34. These models were incorporated into prototype KOMET decision support software and pilot tested in clinics, and were generally well received.
Use of predictive models and mathematical equipoise may help discern patient-specific equipoise to support shared decision-making for selecting between alternative treatments and considering enrollment into an RCT.
To establish the prevalence of hypocalcaemia following laryngectomy and demonstrate that total thyroidectomy is a risk factor.
A retrospective cohort study was conducted that included all patients who underwent total laryngectomy from 1st January 2006 to 1st August 2017. Exclusion criteria were: pre-operative calcium derangement, previous thyroid or parathyroid surgery, concurrent glossectomy, pharyngectomy, or oesophagectomy.
Ninety patients were included. Sixteen patients had early hypocalcaemia (18 per cent), seven had protracted hypocalcaemia (8 per cent) and six had permanent hypocalcaemia (10 per cent). Exact logistic regression values for hypocalcaemia following total thyroidectomy compared to other patients were: early hypocalcaemia, odds ratio = 15.5 (95 per cent confidence interval = 2.2–181.9; model p = 0.002); protracted hypocalcaemia, odds ratio = 13.3 (95 per cent confidence interval = 1.5–117.1; model p = 0.01); and permanent hypocalcaemia, odds ratio = 22.7 (95 per cent confidence interval = 1.9–376.5; model p = 0.005).
This is the largest study to investigate the prevalence of hypocalcaemia following laryngectomy and the first to include follow up of longer than three months. Total thyroidectomy significantly increased the risk of hypocalcaemia at all time frames and independent of other variables.
The pressure transducer technique of Theodorou et al. (1984) is becoming of increasing importance in food evaluation. The main advantage over end-point procedures is the collection of kinetic data on a food. Previously such data were only obtained by sequential sacrifice or in situ techniques. Earlier work (Harris, 1996) showed that kinetics in the early stages of the incubation may not accurately simulate the processes occurring in vivo and this led to the use of a priming technique when the microbial innocula is acclimatized for 24 h to a priming food similar to the basal diet of the donor animal. This work investigates the effect of the length of priming on fermentation characteristics of two foods.
Samples of barley grain and straw were ground through a 1-mm screen and a priming food of grass silage and concentrates prepared according to the method of Harris (1996). Gas production was determined from the barley grain and straw using bovine rumen liquor after exposing the microbial population to the priming food for 0 (unprimed), 6, 12, or 24 h. Gas volumes were recorded manually and the blank corrected volumes fitted to the equation of France et al. (1993).
The Middle East respiratory syndrome coronavirus (MERS-CoV) is caused by a novel coronavirus discovered in 2012. Since then, 1806 cases, including 564 deaths, have been reported by the Kingdom of Saudi Arabia (KSA) and affected countries as of 1 June 2016. Previous literature attributed increases in MERS-CoV transmission to camel breeding season as camels are likely the reservoir for the virus. However, this literature review and subsequent analysis indicate a lack of seasonality. A retrospective, epidemiological cluster analysis was conducted to investigate increases in MERS-CoV transmission and reports of household and nosocomial clusters. Cases were verified and associations between cases were substantiated through an extensive literature review and the Armed Forces Health Surveillance Branch's Tiered Source Classification System. A total of 51 clusters were identified, primarily nosocomial (80·4%) and most occurred in KSA (45·1%). Clusters corresponded temporally with the majority of periods of greatest incidence, suggesting a strong correlation between nosocomial transmission and notable increases in cases.
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
The interannual variations in atmospheric transport patterns to Summit, Greenland, are studied using twice-daily, three-dimensional, 10 day backward trajectory data corresponding to the summers (1 June–31 August) of 1989–98. While previous trajectory climatology studies have been prepared for Summit, the present work considers both the horizontal and vertical components of transport. A three-dimensional residence-time methodology is employed to account for both horizontal and vertical components of transport. the vertical transport component is quantified by passing all trajectories through a three-dimensional grid and tracking the time spent (i.e. the residence time) in each gridcell. This method also allows inspection of trajectory altitude distributions corresponding to transport from upwind regions of interest. the three-dimensional residence-time methodology is shown to be a valuable tool for diagnosing the details of long-range atmospheric transport to remote locations. for Summit, we find that the frequent transport from North America tends to occur at low altitudes, whereas transport from Europe is highly variable. Mean summertime flow patterns are described, as are anomalous patterns during 1990,1996 and 1998.
We summarize B,V imagery results from the CTIO 4-m telescope and two electronic detectors: (1) The SIT vidicon at the R-C focus yielded pixels in the 0.82 or 1.1 arcmin2 frames (Harris, Hesser and Atwood 1983). (2) KPNO's P-F CCD (used by McClure and Hesser) gave 0.6 pixels in 3×5′ fields. (The latter data are being analyzed in cooperation with Stryker and Nemec, who observed some of the same objects.) Zero points for the CCD data are set by observations of E region standards and of giants in Galactic star clusters.
We have obtained CMR photometry for a roughly 1° square region centered on NGC 5128. Preliminary results indicate that the limiting magnitude of the images is ≳ 1 magnitude fainter than the peak of the globular cluster luminosity function (GCLF) at R ⋍ 21.
Risk adjustment is needed to fairly compare central-line–associated bloodstream infection (CLABSI) rates between hospitals. Until 2017, the Centers for Disease Control and Prevention (CDC) methodology adjusted CLABSI rates only by type of intensive care unit (ICU). The 2017 CDC models also adjust for hospital size and medical school affiliation. We hypothesized that risk adjustment would be improved by including patient demographics and comorbidities from electronically available hospital discharge codes.
Using a cohort design across 22 hospitals, we analyzed data from ICU patients admitted between January 2012 and December 2013. Demographics and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) discharge codes were obtained for each patient, and CLABSIs were identified by trained infection preventionists. Models adjusting only for ICU type and for ICU type plus patient case mix were built and compared using discrimination and standardized infection ratio (SIR). Hospitals were ranked by SIR for each model to examine and compare the changes in rank.
Overall, 85,849 ICU patients were analyzed and 162 (0.2%) developed CLABSI. The significant variables added to the ICU model were coagulopathy, paralysis, renal failure, malnutrition, and age. The C statistics were 0.55 (95% CI, 0.51–0.59) for the ICU-type model and 0.64 (95% CI, 0.60–0.69) for the ICU-type plus patient case-mix model. When the hospitals were ranked by adjusted SIRs, 10 hospitals (45%) changed rank when comorbidity was added to the ICU-type model.
Our risk-adjustment model for CLABSI using electronically available comorbidities demonstrated better discrimination than did the CDC model. The CDC should strongly consider comorbidity-based risk adjustment to more accurately compare CLABSI rates across hospitals.
Cognitive deficits are a core feature of schizophrenia, and impairments in most domains are thought to be stable over the course of the illness. However, cross-sectional evidence indicates that some areas of cognition, such as visuospatial associative memory, may be preserved in the early stages of psychosis, but become impaired in later established illness stages. This longitudinal study investigated change in visuospatial and verbal associative memory following psychosis onset.
In total 95 first-episode psychosis (FEP) patients and 63 healthy controls (HC) were assessed on neuropsychological tests at baseline, with 38 FEP and 22 HCs returning for follow-up assessment at 5–11 years. Visuospatial associative memory was assessed using the Cambridge Neuropsychological Test Automated Battery Visuospatial Paired-Associate Learning task, and verbal associative memory was assessed using Verbal Paired Associates subtest of the Wechsler Memory Scale - Revised.
Visuospatial and verbal associative memory at baseline did not differ significantly between FEP patients and HCs. However, over follow-up, visuospatial associative memory deteriorated significantly for the FEP group, relative to healthy individuals. Conversely, verbal associative memory improved to a similar degree observed in HCs. In the FEP cohort, visuospatial (but not verbal) associative memory ability at baseline was associated with functional outcome at follow-up.
Areas of cognition that develop prior to psychosis onset, such as visuospatial and verbal associative memory, may be preserved early in the illness. Later deterioration in visuospatial memory ability may relate to progressive structural and functional brain abnormalities that occurs following psychosis onset.
Antibiotic resistance is a major threat to public health. Resistance is largely driven by antibiotic usage, which in many cases is unnecessary and can be improved. The impact of decreasing overall antibiotic usage on resistance is unknown and difficult to assess using standard study designs. The objective of this study was to explore the potential impact of reducing antibiotic usage on the transmission of multidrug-resistant organisms (MDROs).
We used agent-based modeling to simulate interactions between patients and healthcare workers (HCWs) using model inputs informed by the literature. We modeled the effect of antibiotic usage as (1) a microbiome effect, for which antibiotic usage decreases competing bacteria and increases the MDRO transmission probability between patients and HCWs and (2) a mutation effect that designates a proportion of patients who receive antibiotics to subsequently develop a MDRO via genetic mutation.
Intensive care unit
Absolute reduction in overall antibiotic usage by experimental values of 10% and 25%
Reducing antibiotic usage absolutely by 10% (from 75% to 65%) and 25% (from 75% to 50%) reduced acquisition rates of high-prevalence MDROs by 11.2% (P<.001) and 28.3% (P<.001), respectively. We observed similar effect sizes for low-prevalence MDROs.
In a critical care setting, where up to 50% of antibiotic courses may be inappropriate, even a moderate reduction in antibiotic usage can reduce MDRO transmission.
To determine which comorbid conditions are considered causally related to central-line associated bloodstream infection (CLABSI) and surgical-site infection (SSI) based on expert consensus.
Using the Delphi method, we administered an iterative, 2-round survey to 9 infectious disease and infection control experts from the United States.
Based on our selection of components from the Charlson and Elixhauser comorbidity indices, 35 different comorbid conditions were rated from 1 (not at all related) to 5 (strongly related) by each expert separately for CLABSI and SSI, based on perceived relatedness to the outcome. To assign expert consensus on causal relatedness for each comorbid condition, all 3 of the following criteria had to be met at the end of the second round: (1) a majority (>50%) of experts rating the condition at 3 (somewhat related) or higher, (2) interquartile range (IQR)≤1, and (3) standard deviation (SD)≤1.
From round 1 to round 2, the IQR and SD, respectively, decreased for ratings of 21 of 35 (60%) and 33 of 35 (94%) comorbid conditions for CLABSI, and for 17 of 35 (49%) and 32 of 35 (91%) comorbid conditions for SSI, suggesting improvement in consensus among this group of experts. At the end of round 2, 13 of 35 (37%) and 17 of 35 (49%) comorbid conditions were perceived as causally related to CLABSI and SSI, respectively.
Our results have produced a list of comorbid conditions that should be analyzed as risk factors for and further explored for risk adjustment of CLABSI and SSI.
Approximately half of the variation in wellbeing measures overlaps with variation in personality traits. Studies of non-human primate pedigrees and human twins suggest that this is due to common genetic influences. We tested whether personality polygenic scores for the NEO Five-Factor Inventory (NEO-FFI) domains and for item response theory (IRT) derived extraversion and neuroticism scores predict variance in wellbeing measures. Polygenic scores were based on published genome-wide association (GWA) results in over 17,000 individuals for the NEO-FFI and in over 63,000 for the IRT extraversion and neuroticism traits. The NEO-FFI polygenic scores were used to predict life satisfaction in 7 cohorts, positive affect in 12 cohorts, and general wellbeing in 1 cohort (maximal N = 46,508). Meta-analysis of these results showed no significant association between NEO-FFI personality polygenic scores and the wellbeing measures. IRT extraversion and neuroticism polygenic scores were used to predict life satisfaction and positive affect in almost 37,000 individuals from UK Biobank. Significant positive associations (effect sizes <0.05%) were observed between the extraversion polygenic score and wellbeing measures, and a negative association was observed between the polygenic neuroticism score and life satisfaction. Furthermore, using GWA data, genetic correlations of -0.49 and -0.55 were estimated between neuroticism with life satisfaction and positive affect, respectively. The moderate genetic correlation between neuroticism and wellbeing is in line with twin research showing that genetic influences on wellbeing are also shared with other independent personality domains.