To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak.
We retrospectively analyzed 9 hospital outbreaks that occurred during 2011–2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time.
Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively.
Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.
Externalizing disorders are known to be partly heritable, but the biological pathways linking genetic risk to the manifestation of these costly behaviors remain under investigation. This study sought to identify neural phenotypes associated with genomic vulnerability for externalizing disorders.
One-hundred fifty-five White, non-Hispanic veterans were genotyped using a genome-wide array and underwent resting-state functional magnetic resonance imaging. Genetic susceptibility was assessed using an independently developed polygenic score (PS) for externalizing, and functional neural networks were identified using graph theory based network analysis. Tasks of inhibitory control and psychiatric diagnosis (alcohol/substance use disorders) were used to measure externalizing phenotypes.
A polygenic externalizing disorder score (PS) predicted connectivity in a brain circuit (10 nodes, nine links) centered on left amygdala that included several cortical [bilateral inferior frontal gyrus (IFG) pars triangularis, left rostral anterior cingulate cortex (rACC)] and subcortical (bilateral amygdala, hippocampus, and striatum) regions. Directional analyses revealed that bilateral amygdala influenced left prefrontal cortex (IFG) in participants scoring higher on the externalizing PS, whereas the opposite direction of influence was observed for those scoring lower on the PS. Polygenic variation was also associated with higher Participation Coefficient for bilateral amygdala and left rACC, suggesting that genes related to externalizing modulated the extent to which these nodes functioned as communication hubs.
Findings suggest that externalizing polygenic risk is associated with disrupted connectivity in a neural network implicated in emotion regulation, impulse control, and reinforcement learning. Results provide evidence that this network represents a genetically associated neurobiological vulnerability for externalizing disorders.
Posttraumatic stress disorder (PTSD) and stress/trauma exposure are cross-sectionally associated with advanced DNA methylation age relative to chronological age. However, longitudinal inquiry and examination of associations between advanced DNA methylation age and a broader range of psychiatric disorders is lacking. The aim of this study was to examine if PTSD, depression, generalized anxiety, and alcohol-use disorders predicted acceleration of DNA methylation age over time (i.e. an increasing pace, or rate of advancement, of the epigenetic clock).
Genome-wide DNA methylation and a comprehensive set of psychiatric symptoms and diagnoses were assessed in 179 Iraq/Afghanistan war veterans who completed two assessments over the course of approximately 2 years. Two DNA methylation age indices (Horvath and Hannum), each a weighted index of an array of genome-wide DNA methylation probes, were quantified. The pace of the epigenetic clock was operationalized as change in DNA methylation age as a function of time between assessments.
Analyses revealed that alcohol-use disorders (p = 0.001) and PTSD avoidance and numbing symptoms (p = 0.02) at Time 1 were associated with an increasing pace of the epigenetic clock over time, per the Horvath (but not the Hannum) index of cellular aging.
This is the first study to suggest that posttraumatic psychopathology is longitudinally associated with a quickened pace of the epigenetic clock. Results raise the possibility that accelerated cellular aging is a common biological consequence of stress-related psychopathology, which carries implications for identifying mechanisms of stress-related cellular aging and developing interventions to slow its pace.
The History, Electrocardiogram (ECG), Age, Risk Factors, and Troponin (HEART) score is a decision aid designed to risk stratify emergency department (ED) patients with acute chest pain. It has been validated for ED use, but it has yet to be evaluated in a prehospital setting.
A prehospital modified HEART score can predict major adverse cardiac events (MACE) among undifferentiated chest pain patients transported to the ED.
A retrospective cohort study of patients with chest pain transported by two county-based Emergency Medical Service (EMS) agencies to a tertiary care center was conducted. Adults without ST-elevation myocardial infarction (STEMI) were included. Inter-facility transfers and those without a prehospital 12-lead ECG or an ED troponin measurement were excluded. Modified HEART scores were calculated by study investigators using a standardized data collection tool for each patient. All MACE (death, myocardial infarction [MI], or coronary revascularization) were determined by record review at 30 days. The sensitivity and negative predictive values (NPVs) for MACE at 30 days were calculated.
Over the study period, 794 patients met inclusion criteria. A MACE at 30 days was present in 10.7% (85/794) of patients with 12 deaths (1.5%), 66 MIs (8.3%), and 12 coronary revascularizations without MI (1.5%). The modified HEART score identified 33.2% (264/794) of patients as low risk. Among low-risk patients, 1.9% (5/264) had MACE (two MIs and three revascularizations without MI). The sensitivity and NPV for 30-day MACE was 94.1% (95% CI, 86.8-98.1) and 98.1% (95% CI, 95.6-99.4), respectively.
Prehospital modified HEART scores have a high NPV for MACE at 30 days. A study in which prehospital providers prospectively apply this decision aid is warranted.
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.
We present first attempts to compare the Birmingham Solar-Oscillations Network (BiSON) high precision solar mean magnetic field (SMMF) data of four years with the occurrence of CMEs (coronal mass ejections) as recorded by LASCO on board SOHO. The BiSON magnetic measurement technique is given in Chaplin et al. (2003). Particularly interesting results of recent SMMF high-cadence observations have come from studies of correlation between the SMMF determined by MDI and the occurrence of CMEs (Boberg and Lundstedt 2000 and Boberg et al 2002). Two frequency ranges, centered on 13 and 90 minutes, have been identified as possibly correlating with CME occurrence.
We have used BiSON SMMF data from two sites to investigate CME related SMMF signals to try to confirm the MDI results. To search methodically through our data set we have developed two correlation techniques suited to short (up to 32 minutes) and long (up to 3 hours) period wavelets, respectively. For short periods we analyzed SMMF data in the vicinity of CMEs, and for long periods we compared SMMF results for days with and without recorded CMEs. In neither period range have we yet clearly identified correlations between SMMF power excesses and CME onsets. For the details of the techniques and the results see Chaplin et al. (2004).
Field experiments were conducted in 2006, 2007, and 2008 at the Louisiana State University Agricultural Center's Northeast Research Station near St. Joseph, LA, to evaluate imazosulfuron programs involving rate, application timings, and tank mixes for PRE and POST broadleaf weed control in drill-seeded rice. Imazosulfuron showed residual activity against both Texasweed and hemp sesbania. PRE-applied imazosulfuron at 168 g ai ha−1 and higher rates provided 83 to 93% Texasweed control at 4 WAP. At 12 WAP, Texasweed control with 168 g ha−1 and higher rates was 92%. Hemp sesbania control with 168 g ha−1 and higher rates was 86 to 89% at 4 WAP and 65 to 86% at 12 WAP. Imazosulfuron at 224 g ha−1 applied EPOST provided 84 to 93% Texasweed control and 82 to 87% hemp sesbania control, and it was as effective as its tank mixture with bispyribac-sodium. When applied LPOST, four- to five-leaf Texasweed, imazosulfuron alone at 224 g ha−1 was not effective against Texasweed and hemp sesbania, but did improve weed control when mixed with bispyribac-sodium at 17.6 g ai ha−1.
Ostracodes have a wide geographical distribution in the Ordovician of Scotland. They are known from the Southern Uplands, the Girvan district, the Highland Border region and the Inner Hebrides. Overall, more than forty species are recorded. They occur in clastic and carbonate rocks indicative of a range of shallow to deeper marine-shelf environments. Though many of the faunas are allochthonous, broad patterns of ostracode palaeoenvironmental distribution can be elucidated, and elements of the shallow marine Leperditella and open marineshelf Anisocyamus associations (previously recorded from N America) are present. Indigenous faunas are absent from the deep marine sediments of the Southern Uplands Northern Belt. Ostracodes are known from the Arenig, Llanvirn, Caradoc and Ashgill series in Scotland; those of the latter two series have widest biostratigraphical value. In the Girvan district the Caradoc species ‘Ctenobolbina’ ventrospinosa, Krausella variata, Balticella deckeri and Monoceratella teres have correlative value with N America, whilst the Ashgill species Kinnekullea comma appears to be a locum for the anceps graptolite Biozone in Britain, Ireland and possibly the eastern Baltic. The ostracodes are of typical Laurentian affinity, but show progressive generic links with the Baltic region during the late Llanvirn–Caradoc interval, and by Ashgill times display species-level links with southern Britain and Ireland. These distributional patterns suggest approaching geographical proximity for the early Palaeozoic continents of Laurentia, Baltica and Avalonia, and the ability of some Ordovician ostracodes to cross the Iapetus Ocean.