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This study demonstrated the feasibility of using hyperpolarized 13C-MR spectroscopic imaging with [1-13C]-pyruvate to evaluate in vivo spinal cord metabolism. High pyruvate and relatively small lactate signal were observed in the cervical spinal cords of naive rats. Lactate and pyruvate measures were similar for spinal cord and supratentorial brain. The results from this study establish baseline measures for spinal cord hyperpolarized MRS imaging with 13C pyruvate. This technique holds promise as a valuable molecular imaging tool for monitoring biochemical processes in the normal and diseased spinal cord.

© 2015 Published by Elsevier Inc.Recent technological progress in the multiband echo planer imaging (MB EPI) technique enables accelerated MR diffusion weighted imaging (DWI) and allows whole brain, multi-b-value diffusion imaging to be acquired within a c

© 2014 The Author(s) To evaluate metrics that describe changes in apparent diffusion coefficient (ADC) and to examine their association with clinical outcome for patients with newly diagnosed GBM who were participating in a Phase II clinical trial of treat

Background and purposeIn vivo MR imaging and postmortem neuropathologic studies have demonstrated elevated iron concentration and atrophy within the striatum of patients with Huntington disease, implicating neuronal loss and iron accumulation in the pathogenesis of this neurodegenerative disorder. We used 7T MR imaging to determine whether quantitative phase, a measurement that reflects both iron content and tissue microstructure, is altered in subjects with premanifest Huntington disease.Materials and methodsLocal field shift, calculated from 7T MR phase images, was quantified in 13 subjects with premanifest Huntington disease and 13 age- and sex-matched controls. All participants underwent 3T and 7T MR imaging, including volumetric T1 and 7T gradient recalled-echo sequences. Local field shift maps were created from 7T phase data and registered to caudate ROIs automatically parcellated from the 3T T1 images. Huntington disease-specific disease burden and neurocognitive and motor evaluations were also performed and compared with local field shift.ResultsSubjects with premanifest Huntington disease had smaller caudate volume and higher local field shift than controls. A significant correlation between these measurements was not detected, and prediction accuracy for disease state improved with inclusion of both variables. A positive correlation between local field shift and genetic disease burden was also found, and there was a trend toward significant correlations between local field shift and neurocognitive tests of working memory and executive function.ConclusionsSubjects with premanifest Huntington disease exhibit differences in 7T MR imaging phase within the caudate nuclei that correlate with genetic disease burden and trend with neurocognitive assessments. Ultra-high-field MR imaging of quantitative phase may be a useful approach for monitoring neurodegeneration in premanifest Huntington disease.

Gliomas are routinely graded according to histopathological criteria established by the World Health Organization. Although this classification can be used to understand some of the variance in the clinical outcome of patients, there is still substantial h

Objective There is increasing evidence that altered glutamate (Glu) homeostasis is involved in the pathophysiology of multiple sclerosis (MS). The aim of this study was to evaluate the in vivo effects of excess brain Glu on neuroaxonal integrity measured by N-acetylaspartate (NAA), brain volume, and clinical outcomes in a large, prospectively followed cohort of MS subjects. Methods We used multivoxel spectroscopy at 3T to longitudinally estimate Glu and NAA concentrations from large areas of normal-appearing white and gray matter (NAWM and GM) in MS patients (n = 343) with a mean follow-up time of 5 years. Using linear mixed-effects models, Glu was examined as a predictor of NAA decline, annualized percentage brain volume change, and evolution of clinical outcomes (Multiple Sclerosis Functional Composite [MSFC], Paced Auditory Serial Addition Test-3 [PASAT], and Expanded Disability Status Scale). Glu/NAA ratio was tested as a predictor of brain volume loss and clinical outcomes. Results Baseline Glu[NAWM] was predictive of accelerated longitudinal decline in NAA[GM] (-0.06mM change in NAA[GM]/yr for each unit increase in Glu; p = 0.004). The sustained elevation of Glu[NAWM] was predictive of a loss of 0.28mM/yr in NAA[NAWM] (p < 0.001) and 0.15mM/yr in NAA[GM] (p = 0.056). Each 10% increase in Glu/NAA [NAWM] was associated with a loss of 0.33% brain volume/yr (p = 0.001), 0.009 standard deviations/yr in MSFC z-score (p < 0.001), and 0.17 points/yr on the PASAT (p < 0.001). Interpretation These results indicate that higher Glu concentrations increase the rate of NAA decline, and higher Glu/NAA[NAWM] ratio increases the rate of decline of brain volume, MSFC, and PASAT. This provides evidence of a relationship between brain Glu and markers of disease progression in MS. © 2014 American Neurological Association.

Background and purposeSuper-resolution track density imaging generates anatomic images with submillimeter voxel resolution by using high-angular-resolution diffusion imaging and fiber-tractography. TDI within the diseased human brain has not been previously described. The purpose of this study was to correlate TDI with histopathologic features of GBM.Materials and methodsA total of 43 tumor specimens (24 contrast-enhancing, 12 NE, and 7 centrally necrotic regions) were collected from 18 patients with treatment-naïve GBM by use of MR imaging-guided neurosurgical techniques. Immunohistochemical stains were used to evaluate the following histopathologic features: hypoxia, architectural disruption, microvascular hyperplasia, and cellular proliferation. We reconstructed track density maps at a 0.25-mm isotropic spatial resolution by using probabilistic streamline tractography combined with constrained spheric deconvolution (model order, 8; 0.1-mm step size; 1 million seed points). Track density values were obtained from each tissue site. A P value of .05 was considered significant and was adjusted for multiple comparisons by use of the false discovery rate method.ResultsTrack density was not significantly different between contrast-enhancing and NE regions but was more likely to be elevated within regions demonstrating aggressive histopathologic features (P < .05). Significant correlation between relative track density and hypoxia (odds ratio, 3.52; P = .01), architectural disruption (odds ratio, 3.49; P = .03), and cellular proliferation (odds ratio, 1.70; P = .05) was observed irrespective of the presence or absence of contrast enhancement.ConclusionsNumeric values of track density correlate with GBM biologic features and may be clinically useful for identification of regions of tumor infiltration within both enhancing and NE components of GBM.

ObjectA novel method of estimating metabolite T1 relaxation times using MR spectroscopic imaging (MRSI) is proposed. As opposed to conventional single-voxel metabolite T1 estimation methods, this method investigates regional and gray matter (GM)/white matter (WM) differences in metabolite T1 by taking advantage of the spatial distribution information provided by MRSI.Material and methodsThe method, validated by Monte Carlo studies, involves a voxel averaging to preserve the GM/WM distribution, a non-linear least squares fit of the metabolite T1 and an estimation of its standard error by bootstrapping. It was applied in vivo to estimate the T1 of N-acetyl compounds (NAA), choline, creatine and myo-inositol in eight normal volunteers, at 1.5 T, using a short echo time 2D-MRSI slice located above the ventricles.ResultsWM-T 1,NAA was significantly (P < 0.05) longer in anterior regions compared to posterior regions of the brain. The anterior region showed a trend of a longer WM T1 compared to GM for NAA, creatine and myo-Inositol. Lastly, accounting for the bootstrapped standard error estimate in a group mean T1 calculation yielded a more accurate T1 estimation.ConclusionThe method successfully measured in vivo metabolite T1 using MRSI and can now be applied to diseased brain.

Human skin prepared with an optical clearing agent manifests reduced scattering as a result of de-hydration and refractive index matching. This has potentially large effects for laser therapies of several skin lesions such as port wine stain, hair removal and tattoo removal. With most topically applied clearing agents the clearing effect is limited because they penetrate poorly through the intact superficial skin layer (stratum corneum). Agent application modi other than topically are impractical and have limited the success of optical clearing in laser dermatology. In recent reports, however, a mixture of lipofylic and hydrofylic agents was shown to successfully penetrate through the intact stratum corneum layer which has raised new interest in this field. Immediately after application, the optical clearing effect is superficial and, as the agent diffuses through the skin, reduced scattering is manifested in deeper skin layers. For practical purposes as well as to maximize therapeutic success, it is important to quantify the reduced scattering as well as the trans-cutaneous transport dynamics of the agent. We determined the time and tissue depth resolved effects of optically cleared skin by inserting a microscopic reflector array in the skin. Depth dependent light intensity was measured by quantifying the signal of the reflector array with optical coherence tomography. A 1-dimensional mass diffusion model was used to estimate a trans-cutaneous transport diffusion constant for the clearing agent mixture. The results are used in Monte Carlo modeling to determine the optimal time of laser treatment after topical application of the optical clearing agent.

Purpose: To demonstrate the feasibility of using DNP hyperpolarized [1-(13)C]-pyruvate to measure early response to temozolomide (TMZ) therapy using an orthotopic human glioblastoma xenograft model.Materials and Methods: Twenty athymic rats with intracranial implantation of human glioblastoma cells were divided into two groups: one group received an oral administration of 100 mg/kg TMZ (n = 10) and the control group received vehicle only (n = 10). (13)C 3D magnetic resonance spectroscopic imaging (MRSI) data were acquired following injection of 2.5 mL (100 mM) hyperpolarized [1-(13)C]-pyruvate using a 3T scanner prior to treatment (day D0), at D1 (days from treatment) or D2.Results: Tumor metabolism as assessed by the ratio of lactate to pyruvate (Lac/Pyr) was significantly altered at D1 for the TMZ-treated group but tumor volume did not show a reduction until D5 to D7. The percent change in Lac/Pyr from baseline was statistically different between the two groups at D1 and D2 (P < 0.008), while percent tumor volume was not (P > 0.2).Conclusion: The results from this study suggest that metabolic imaging with hyperpolarized [1-(13)C]-pyruvate may provide a unique tool that clinical neuro-oncologists can use in the future to monitor tumor response to therapy for patients with brain tumors. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the signal-to-noise-ratio (SNR) and data quality of time-reduced three-dimensional (3D) proton magnetic resonance spectroscopic imaging ((1)H MRSI) techniques in the human brain at 3 Tesla.Materials and Methods: Techniques that were investigated included ellipsoidal k-space sampling, parallel imaging, and echo-planar spectroscopic imaging (EPSI). The SNR values for N-acetyl aspartate, choline, creatine, and lactate or lipid peaks were compared after correcting for effective spatial resolution and acquisition time in a phantom and in the brains of human volunteers. Other factors considered were linewidths, metabolite ratios, partial volume effects, and subcutaneous lipid contamination.Results: In volunteers, the median normalized SNR for parallel imaging data decreased by 34-42%, but could be significantly improved using regularization. The normalized signal to noise loss in flyback EPSI data was 11-18%. The effective spatial resolutions of the traditional, ellipsoidal, sensitivity encoding (SENSE) sampling scheme, and EPSI data were 1.02, 2.43, 1.03, and 1.01 cm(3), respectively. As expected, lipid contamination was variable between subjects but was highest for the SENSE data. Patient data obtained using the flyback EPSI method were of excellent quality.Conclusion: Data from all (1)H 3D-MRSI techniques were qualitatively acceptable, based upon SNR, linewidths, and metabolite ratios. The larger field of view obtained with the EPSI methods showed negligible lipid aliasing with acceptable SNR values in less than 9.5 min without compromising the point-spread function. [ABSTRACT FROM AUTHOR]

Purpose: To measure T(1) and T(2) relaxation times of metabolites in glioma patients at 3T and to investigate how these values influence the observed metabolite levels.Materials and Methods: A total of 23 patients with gliomas and 10 volunteers were studied with single-voxel two-dimensional (2D) J-resolved point-resolved spectral selection (PRESS) using a 3T MR scanner. Voxels were chosen in normal appearing white matter (WM) and in regions of tumor. The T(1) and T(2) of choline containing compounds (Cho), creatine (Cr), and N-acetyl aspartate (NAA) were estimated.Results: Metabolite T(1) relaxation values in gliomas were not significantly different from values in normal WM. The T(2) of Cho and Cr were statistically significantly longer for grade 4 gliomas than for normal WM but the T(2) of NAA was similar. These differences were large enough to impact the corrections of metabolite levels for relaxation times with tumor grade in terms of metabolite ratios (P < 0.001).Conclusion: The differential increase in T(2) for Cho and Cr relative to NAA means that the ratios of Cho/NAA and Cr/NAA are higher in tumor at longer echo times (TEs) relative to values in normal appearing brain. Having this information may be useful in defining the acquisition parameters for optimizing contrast between tumor and normal tissue in MR spectroscopic imaging (MRSI) data, in which limited time is available and only one TE can be used. [ABSTRACT FROM AUTHOR]

The history of cocaine misuse includes a destructive epidemic during the 1980s. While recent surveys suggest cocaine use is stable or decreasing, we have observed increasing trends of cocaine-related death through analysis of medical examiner data collected by the Florida Department of Law Enforcement (FDLE). Florida's per capita cocaine-related death rates nearly doubled from 2001 to 2005. Electronic collection of data such as that collected by the FDLE nationally and in real-time would greatly advance understanding of drug-use patterns and consequences. For example, results from Florida suggest that high school and college students, and members of higher socioeconomic status, appear to be at increased risk of cocaine abuse. Public health interventions are necessary to prevent another full-fledged epidemic. [ABSTRACT FROM AUTHOR]

OBJECTIVE: The integration of SNOMED CT into the Unified Medical Language System (UMLS) involved the alignment of two views of synonymy that were different because the two vocabulary systems have different intended purposes and editing principles. The UMLS is organized according to one view of synonymy, but its structure also represents all the individual views of synonymy present in its source vocabularies. Despite progress in knowledge-based automation of development and maintenance of vocabularies, manual curation is still the main method of determining synonymy. The aim of this study was to investigate the quality of human judgment of synonymy. DESIGN: Sixty pairs of potentially controversial SNOMED CT synonyms were reviewed by 11 domain vocabulary experts (six UMLS editors and five noneditors), and scores were assigned according to the degree of synonymy. MEASUREMENTS: The synonymy scores of each subject were compared to the gold standard (the overall mean synonymy score of all subjects) to assess accuracy. Agreement between UMLS editors and noneditors was measured by comparing the mean synonymy scores of editors to noneditors. RESULTS: Average accuracy was 71% for UMLS editors and 75% for noneditors (difference not statistically significant). Mean scores of editors and noneditors showed significant positive correlation (Spearman's rank correlation coefficient 0.654, two-tailed p < 0.01) with a concurrence rate of 75% and an interrater agreement kappa of 0.43. CONCLUSION: The accuracy in the judgment of synonymy was comparable for UMLS editors and nonediting domain experts. There was reasonable agreement between the two groups. [ABSTRACT FROM AUTHOR]

Objective: International Classification of Diseases (ICD) codes recorded in electronic health records (EHRs) are frequently used to create patient cohorts or define phenotypes. Inconsistent assignment of codes may reduce the utility of such cohorts. We assessed the reliability across time and location of the assignment of ICD codes in a US health system at the time of the transition from ICD-9-CM (ICD, 9th Revision, Clinical Modification) to ICD-10-CM (ICD, 10th Revision, Clinical Modification)., Materials and Methods: Using clusters of equivalent codes derived from the US Centers for Disease Control and Prevention General Equivalence Mapping (GEM) tables, ICD assignments occurring during the ICD-9-CM to ICD-10-CM transition were investigated in EHR data from the US Veterans Administration Central Data Warehouse using deep learning and statistical models. These models were then used to detect abrupt changes across the transition; additionally, changes at each VA station were examined., Results: Many of the 687 most-used code clusters had ICD-10-CM assignments differing greatly from that predicted from the codes used in ICD-9-CM. Manual reviews of a random sample found that 66% of the clusters showed problematic changes, with 37% having no apparent explanations. Notably, the observed pattern of changes varied widely across care locations., Discussion and Conclusion: The observed coding variability across time and across location suggests that ICD codes in EHRs are insufficient to establish a semantically reliable cohort or phenotype. While some variations might be expected with a changing in coding structure, the inconsistency across locations suggests other difficulties. Researchers should consider carefully how cohorts and phenotypes of interest are selected and defined., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)

Warming associated with climate change will advance the onset of spring phenology for many forest plants across the Eastern United States. Understory forbs and spring ephemerals that fix a disproportionate amount of carbon during early spring may be negatively affected by earlier canopy closure; however, information on the spatial patterns of phenological change for these communities is still lacking. To assess the potential for changes in spring phenological windows, we synthesized observations from the Appalachian Mountain Club's (AMCs) Mountain Watch (MW) project, the National Phenology Network (NPN), and AMC's iNaturalist projects between 2004 and 2022 (n = 118,250) across the length of the Appalachian Trail (AT) Corridor (34° N-46° N latitude). We used hierarchical Bayesian modeling to examine the sensitivity of spring flowering and leaf-out for 11 understory species and 14 canopy tree species to mean spring temperature (April-June). We conducted analyses across the AT Corridor, partitioned by regions of 4° latitude (south, mid-Atlantic, and north). Spring phenologies for both understory plants and canopy trees advanced with warming (~6 and ~3 days/°C, respectively). However, the sensitivity of each group varied by latitude, with the phenology of trees and understory plants advancing to a greater degree in the mid-Atlantic region (~10 days/°C) than in the southern or northern regions (~5 days/°C). While we find evidence that phenological windows remain stable in the southern and mid-Atlantic portions of the AT, we observed an expansion of the spring phenological window in the north where there was greater understory forb temperature sensitivity compared with trees (~2.7 days/°C). Our analyses indicate the differential sensitivity of forest plant phenology to potential warming across a large latitudinal gradient in the Eastern United States. Further, evidence for a temperature-driven expansion of the spring phenological window suggests a potential beneficial effect for understory plants in the northern AT, although phenological mismatch with potential pollinators and increased vulnerability to late winter frosts are possible. Using extensive citizen-science datasets allows us to synthesize regional- and continental-scale data to explore spatial and temporal trends in spring phenology related to warming. Such data can help to standardize approaches in phenological research and its application to forest climate resiliency., (© 2024 The Ecological Society of America.)

Importance: Heart failure (HF) is a leading cause of death in the US. The current evidence on the burdens of HF in Asian American populations, especially Asian American subgroups, is limited and inconsistent., Objective: To assess and compare the incidence and prevalence of HF in Asian American subgroups., Design, Setting, and Participants: This retrospective cohort study used electronic health record data from patients 40 years or older with health care encounters from January 1, 2015, to December 31, 2019, recorded in the Oracle Electronic Health Record Real-World Data database, which has more than 100 health care systems across the US contributing to the database as of February 2024. For prevalence analysis, the study samples were those who had at least 1 encounter in the study calendar year. For incidence analysis, participants were additionally limited to those without HF before the study year who also had encounter(s) the year before the study year. Data analysis was performed from August 1, 2023, to July 31, 2024., Exposure: Race and ethnicity were determined using patient self-reported data, which were categorized as Black, East Asian, South Asian, Southeast Asian, other Asian (without specified ethnicity), and White., Main Outcomes and Measures: Outcomes were incidence and prevalence of HF, identified using recorded International Classification of Diseases, Ninth Revision, Clinical Modification and International Statistical Classification of Diseases, Tenth Revision, Clinical Modification codes. Age- and sex-standardized incidence and prevalence were used to calculate the risk ratio of each racial and ethnic group compared with White patients., Results: Incidence and prevalence analyses were performed for 6 845 791 patients (mean [SD] age, 62.1 [12.5] years; 59.9% female; 2.8% Asian, 6.7% Black, and 90.5% White) and for 13 440 234 patients (mean [SD] age, 61.7 [12.7] years; 57.0% female; 2.9% Asian, 7.1% Black, and 90.0% White), respectively. Using the 2015 population as the standard, age- and sex-standardized HF incidence was 2.26% (95% CI, 2.07%-2.45%) for Southeast Asian patients, 1.56% (95% CI, 1.31%-1.82%) for South Asian patients, and 1.22% (95% CI, 1.06%-1.38%) for East Asian patients compared with 1.58% (95% CI, 1.57%-1.59%) for White patients and 2.39% (95% CI, 2.36%-2.42%) for Black patients. Similarly, heterogeneous rates in Asian American subgroups were also observed in the prevalence analysis., Conclusions and Relevance: In this study of HF outcomes, the disparities between Southeast and East Asian patients were larger than those between Black and White patients, with the estimates in Southeast Asian patients being similar to those of Black patients. These findings reinforce that individual Asian ethnicities and cardiovascular risk factors should be considered in the assessment of HF risks.

Background: To improve the site selection process for clinical trials, we expanded a site survey to include standardized assessments of site commitment time, team experience, feasibility of tight timelines, and local medical community equipoise as factors that might better predict performance. We also collected contact information about institutional research services ahead of site onboarding., Aim: As a first step, we wanted to confirm that an expanded survey could be feasible and generalizable-that asking site teams for more details upfront was acceptable and that the survey could be completed in a reasonable amount of time, despite the assessment length., Methods: A standardized, two-part Site Assessment Survey Instrument (SASI), examining qualitative components and with multiple contact list sections, was developed using a publicly accessible dashboard and later transferred to a REDCap platform. After multiple rounds of internal testing, the SASI was deployed 11 times for multicenter trials. Follow-up questionnaires were sent to site teams to confirm that an expanded survey instrument is acceptable to the research community and could be completed during a brief work shift., Results: Respondents thought the SASI collected useful and relevant information about their sites (100%). Sites were "comfortable" (90%) supplying detailed information early in the site selection process and 57% completed the SASI in one to two hours., Conclusions: Coordinating centers and sites found the SASI tool to be acceptable and helpful when collecting data in consideration of multicenter trial site selection., Competing Interests: Declaration of competing interest Bradley Barney's relationship with Johns Hopkins University includes: consulting or advisory and receives financial support. Salina Waddy and Ken Wiley work for the National Institutes of Health., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Atmospheric mercury (Hg) emissions and subsequent transport and deposition are major concerns within protected lands, including national parks, where Hg can bioaccumulate to levels detrimental to human and wildlife health. Despite this risk to biological resources, there is limited understanding of the relative importance of different Hg sources and delivery pathways within the protected regions. Here, we used Hg stable isotope measurements within a single aquatic bioindicator, dragonfly larvae, to determine if these tracers can resolve spatial patterns in Hg sources, delivery mechanisms, and aquatic cycling at a national scale. Mercury isotope values in dragonfly tissues varied among habitat types (e.g., lentic, lotic, and wetland) and geographic location. Photochemical-derived isotope fractionation was habitat-dependent and influenced by factors that impact light penetration directly or indirectly, including dissolved organic matter, canopy cover, and total phosphorus. Strong patterns for Δ 200 Hg emerged in the western United States, highlighting the relative importance of wet deposition sources in arid regions in contrast to dry deposition delivery in forested regions. This work demonstrates the efficacy of dragonfly larvae as biosentinels for Hg isotope studies due to their ubiquity across freshwater ecosystems and ability to track variation in Hg sources and processing attributed to small-scale habitat and large-scale regional patterns.

We paired mercury (Hg) concentrations in dragonfly larvae with water chemistry in 29 U.S. national parks to highlight how ecological and biogeochemical context (habitat, dissolved organic carbon [DOC]) influence drivers of Hg bioaccumulation. Although prior studies have defined influences of biogeochemical variables on Hg production and bioaccumulation, it has been challenging to determine their influence across diverse habitats, regions, or biogeochemical conditions within a single study. We compared global (i.e., all sites), habitat-specific, and DOC-class models to illuminate how these controls on biotic Hg vary. Although the suite of important biogeochemical factors across all sites (e.g., aqueous Hg, DOC, sulfate [SO 4 2- ], and pH) was consistent with general findings in the literature, contrasting the restricted models revealed more nuanced controls on biosentinel Hg. Comparing habitats, aqueous (filtered) total mercury (THg) and SO 4 2- were important in lentic systems whereas aqueous (filtered) methylmercury (MeHg), DOC, pH, and SO 4 2- were important in lotic and wetland systems. The ability to identify important variables varied among habitats, with less certainty in lentic (model weight (W) = 0.05) than lotic (W = 0.11) or wetland habitats (W = 0.23), suggesting that biogeochemical drivers of bioaccumulation are more variable, or obscured by other aspects of Hg cycling, in these habitats. Results revealed a contrast in the importance of aqueous MeHg versus aqueous THg between DOC-classes: in low-DOC sites (<8.5 mg/L), availability of upstream inputs of MeHg appeared more important for bioaccumulation; in high-DOC sites (>8.5 mg/L) THg was more important, suggesting a link to in-situ controls on bioavailability of Hg for MeHg production. Mercury bioaccumulation (indicated by bioaccumulation factor) was more efficient in low DOC-class sites, likely due to reduced partitioning of aqueous MeHg to DOC. Together, findings highlight substantial variation in the drivers of Hg bioaccumulation and suggest consideration of these factors in natural resource management and decision-making., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Mycobacterium tuberculosis is exposed to a variety of stresses during a chronic infection, as the immune system simultaneously produces bactericidal compounds and starves the pathogen of essential nutrients. The intramembrane protease, Rip1, plays an important role in the adaptation to these stresses, at least partially by the cleavage of membrane-bound transcriptional regulators. Although Rip1 is known to be critical for surviving copper intoxication and nitric oxide exposure, these stresses do not fully account for the regulatory protein's essentiality during infection. In this work, we demonstrate that Rip1 is also necessary for growth in low-iron and low-zinc conditions, similar to those imposed by the immune system. Using a newly generated library of sigma factor mutants, we show that the known regulatory target of Rip1, SigL, shares this defect. Transcriptional profiling under iron-limiting conditions supported the coordinated activity of Rip1 and SigL and demonstrated that the loss of these proteins produces an exaggerated iron starvation response. These observations demonstrate that Rip1 coordinates several aspects of metal homeostasis and suggest that a Rip1- and SigL-dependent pathway is necessary to thrive in the iron-deficient environments encountered during infection. IMPORTANCE Metal homeostasis represents a critical point of interaction between the mammalian immune system and potential pathogens. While the host attempts to intoxicate microbes with high concentrations of copper or starve the invader of iron and zinc, successful pathogens have acquired mechanisms to overcome these defenses. Our work identifies a regulatory pathway consisting of the Rip1 intramembrane protease and the sigma factor, SigL, that is essential for the important human pathogen, Mycobacterium tuberculosis, to grow in low-iron or low-zinc conditions such as those encountered during infection. In conjunction with Rip1's known role in resisting copper toxicity, our work implicates this protein as a critical integration point that coordinates the multiple metal homeostatic systems required for this pathogen to survive in host tissue., Competing Interests: The authors declare no conflict of interest.

Transformer is the latest deep neural network (DNN) architecture for sequence data learning, which has revolutionized the field of natural language processing. This success has motivated researchers to explore its application in the healthcare domain. Despite the similarities between longitudinal clinical data and natural language data, clinical data presents unique complexities that make adapting Transformer to this domain challenging. To address this issue, we have designed a new Transformer-based DNN architecture, referred to as Hybrid Value-Aware Transformer (HVAT), which can jointly learn from longitudinal and non-longitudinal clinical data. HVAT is unique in the ability to learn from the numerical values associated with clinical codes/concepts such as labs, and in the use of a flexible longitudinal data representation called clinical tokens. We have also trained a prototype HVAT model on a case-control dataset, achieving high performance in predicting Alzheimer's disease and related dementias as the patient outcome. The results demonstrate the potential of HVAT for broader clinical data-learning tasks.

Introduction: Postpartum hemorrhage (PPH) was the second leading cause of maternal death, accounting for approximately 14% of all pregnancy-related deaths between 2017 and 2019 in the United States. Several large multi-center studies have demonstrated decreased PPH rates with the use of tranexamic acid (TXA). Little data exists regarding the prevalence of TXA use in obstetric patients., Methods: We identified over 1.2 million US pregnancies between January 1, 2015 and June 30, 2021, with and without PPH by International Statistical Classification of Disease and Related Health Problems, Tenth Revision codes using Cerner Real-World Database™. TXA use and patient characteristics were abstracted from the electronic medical record., Results: During delivery, TXA was used approximately 1% of the time (12,394 / 1,262,574). Pregnant patients who did and did not receive TXA during delivery had similar demographic characteristics. Pregnant patients who underwent cesarean delivery (4,356 / 12,394), had a term delivery (10,199 / 12,394), and had comorbid conditions were more likely to receive TXA during hospitalization for delivery. The majority of TXA was use was concentrated in Arizona, Colorado, Idaho, New Mexico, Nevada, Utah, and Wyoming. During the study period the use of TXA increased in both patients with PPH and those without., Conclusion: The data illustrate a rapid increase in the use of TXA after 2017 while the total number of pregnancies remained relatively constant. The observed increase in TXA use may reflect changing practicing patterns as the support for use of TXA in the setting of PPH prophylaxis increases., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Mercury (Hg) exposure to fish, wildlife, and humans is widespread and of global concern, thus stimulating efforts to reduce emissions. Because the relationships between rates of inorganic Hg loading, methylmercury (MeHg) production, and bioaccumulation are extremely complex and challenging to predict, there is a need for reliable biosentinels to understand the distribution of Hg in the environment and monitor the effectiveness of reduction efforts. However, it is important to assess how temporal and spatial variation at multiple scales influences the efficacy of specific biosentinels. Seasonal and interannual variation in total Hg (THg) concentrations of dragonfly larvae were examined in relation to spatial variability among 21 sites in two U.S. national parks with contrasting ecologies and Hg deposition patterns. Dragonfly THg differed among sampling events at 17 of the 21 sites, but by an average of only 20.4 % across events, compared to an average difference of 52.7 % among sites. Further, THg concentrations did not follow consistent seasonal patterns across sites or years, suggesting that the observed temporal variation was unlikely to bias monitoring efforts. Importantly, for a specific site, there was no difference in % MeHg in dragonflies among sampling events. Finally, there was significant temporal variability in the biogeochemical factors (aqueous inorganic Hg, aqueous MeHg, DOC, SO 4 , and pH) influencing dragonfly THg, with the importance of individual factors varying by 2.4 to 4.3-fold across sampling events. Despite these results, it is noteworthy that the observed temporal variation in dragonfly THg concentrations was neither large nor consistent enough to bias spatial assessments. Thus, although this temporal variation may provide insights into the processes influencing biological Hg concentrations, it is unlikely to impair the use of dragonflies as biosentinels for monitoring spatial or temporal patterns at scales relevant to most mitigation efforts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The US Geological Survey, Elsevier B.V. Published by Elsevier B.V. All rights reserved.)

Colorectal cancer incidence has continually fallen among those 50 years old and over. However, the incidence has increased in those under 50. Even with the recent screening guidelines recommending that screening begins at age 45, nearly half of all early-onset colorectal cancer will be missed. Methods are needed to identify high-risk individuals in this age group for targeted screening. Colorectal cancer studies, as with other clinical studies, have required labor intensive chart review for the identification of those affected and risk factors. Natural language processing and machine learning can be used to automate the process and enable the screening of large numbers of patients. This study developed and compared four machine learning and statistical models: logistic regression, support vector machine, random forest, and deep neural network, in their performance in classifying colorectal cancer patients. Excellent classification performance is achieved with AUCs over 97%.

Participant recruitment for research is a persistent bottleneck that can be improved by leveraging electronic health records (EHRs). Despite emerging evidence for various EHR-driven approaches, guidance for those attempting to select and use such approaches is limited. The national Recruitment Innovation Center established the EHR Recruitment Consult Resource (ERCR) service line to support multisite studies through implementation of EHR-driven recruitment strategies. As the ERCR, we evolved a guide through 17 consultations over 3 years with multisite studies recruiting in diverse biomedical research domains. We assessed literature and engaged domain experts to identify five key EHR-driven recruitment strategies: direct to patient messages, candidate lists for mailings/calls, direct to research alerts, point of care alerts, and participant registries. Differentiating factors were grouped into factors of study population, study protocol and recruitment workflows, and recruitment site capabilities. The decision matrix indicates acceptable or preferred strategies based on the differentiating factors. Across the ERCR consultations, candidate lists for mailing or calls were most common, participant registries were least frequently recommended, and for some studies no EHR-driven recruitment was recommended. Comparative effectiveness research is needed to refine further evidence for these and potentially new strategies to come., (© The Author(s) 2022.)

Background: The impact of coronavirus disease 2019 (COVID-19) on adverse perinatal outcomes remains unclear., Objective: This study aimed to investigate whether COVID-19 is associated with adverse perinatal outcomes in a large national dataset and to examine the rates of adverse outcomes during the pandemic compared with the rates of adverse outcomes during the prepandemic period., Study Design: This observational cohort study included 683,905 patients, between the ages of 12 and 50, hospitalized for childbirth and abortion between January 1, 2019, and May 31, 2021. During the prepandemic period, 271,444 women were hospitalized for childbirth. During the pandemic, 308,532 women were hospitalized for childbirth, and 2708 women had COVID-19. The associations between COVID-19 and inhospital adverse perinatal outcomes were examined using propensity score-adjusted logistic regression., Results: Women with COVID-19 were more likely to experience both early and late preterm birth (adjusted odds ratios, 1.38 [95% confidence interval, 1.1-1.7] and 1.62 [95% confidence interval, 1.3-1.7], respectively), preeclampsia (adjusted odds ratio, 1.2 [95% confidence interval, 1.0-1.4]), disseminated intravascular coagulopathy (adjusted odds ratio, 1.57 [95% confidence interval, 1.1-2.2]), pulmonary edema (adjusted odds ratio, 2.7 [95% confidence interval, 1.1-6.3]), and need for mechanical ventilation (adjusted odds ratio, 8.1 [95% confidence interval, 3.8-17.3]) than women without COVID-19. There was no significant difference in the prevalence of stillbirth among women with COVID-19 (16/2708) and women without COVID-19 (174/39,562) (P=.257). There was no difference in adverse outcomes among women who delivered during the pandemic vs prepandemic period. Combined inhospital mortality was significantly higher for women with COVID-19 (147 [95% confidence interval, 3.0-292.0] vs 2.5 [95% confidence interval, 0.0-7.5] deaths per 100,000 women). Women diagnosed with COVID-19 within 30 days before hospitalization were more likely to experience early preterm birth, placental abruption, and mechanical ventilation than women diagnosed with COVID-19 >30 days before hospitalization for childbirth (4.0% vs 2.4% for early preterm birth [adjusted odds ratio, 1.7; 95% confidence interval, 1.1-2.7]; 2.2% vs 1.2% for placental abruption [adjusted odds ratio, 1.86; 95% confidence interval, 1.0-3.4]; and 0.9% vs 0.1% for mechanical ventilation [adjusted odds ratio, 13.7; 95% confidence interval, 1.8-107.2])., Conclusion: Women with COVID-19 had a higher prevalence of adverse perinatal outcomes and increased in-hospital mortality, with the highest risk occurring when the diagnosis was within 30 days of hospitalization, raising the possibility of a high-risk period., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Objective: The Recruitment Innovation Center (RIC), partnering with the Trial Innovation Network and institutions in the National Institutes of Health-sponsored Clinical and Translational Science Awards (CTSA) Program, aimed to develop a service line to retrieve study population estimates from electronic health record (EHR) systems for use in selecting enrollment sites for multicenter clinical trials. Our goal was to create and field-test a low burden, low tech, and high-yield method., Materials and Methods: In building this service line, the RIC strove to complement, rather than replace, CTSA hubs' existing cohort assessment tools. For each new EHR cohort request, we work with the investigator to develop a computable phenotype algorithm that targets the desired population. CTSA hubs run the phenotype query and return results using a standardized survey. We provide a comprehensive report to the investigator to assist in study site selection., Results: From 2017 to 2020, the RIC developed and socialized 36 phenotype-dependent cohort requests on behalf of investigators. The average response rate to these requests was 73%., Discussion: Achieving enrollment goals in a multicenter clinical trial requires that researchers identify study sites that will provide sufficient enrollment. The fast and flexible method the RIC has developed, with CTSA feedback, allows hubs to query their EHR using a generalizable, vetted phenotype algorithm to produce reliable counts of potentially eligible study participants., Conclusion: The RIC's EHR cohort assessment process for evaluating sites for multicenter trials has been shown to be efficient and helpful. The model may be replicated for use by other programs., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Mental health is an increasing concern in adolescents. Mental health disorders can affect academic performance, affect the cultivation of healthy relationships, and even lead to suicide. Healthy lifestyle can improve mental health, though there are gaps in the research, partly resulted from the lack of detailed longitudinal datasets on lifestyle and mental health. To inform and engage students in the research on adolescent lifestyle and mood, the George Washington University and the T.C. Williams High School in Alexandria, Virginia teamed up in a citizen science project. Students generated questions, collected data on themselves, analyzed the data, and produced research reports relating to their mental health and lifestyle. Student feedbacks suggest that the students find the project to be generally interesting and some students (46%) reported that the participation in the project may influence their college and career plans. The anonymized dataset resulted from the project provides another contribution to science., (©2021 AMIA - All rights reserved.)

Purpose: Coronavirus disease 2019 (COVID-19) is associated with hypercoagulability and increased thrombotic risk. The impact of prehospital antiplatelet therapy on in-hospital mortality is uncertain., Methods: This was an observational cohort study of 34 675 patients ≥50 years old from 90 health systems in the United States. Patients were hospitalized with laboratory-confirmed COVID-19 between February 2020 and September 2020. For all patients, the propensity to receive prehospital antiplatelet therapy was calculated using demographics and comorbidities. Patients were matched based on propensity scores, and in-hospital mortality was compared between the antiplatelet and non-antiplatelet groups., Results: The propensity score-matched cohort of 17 347 patients comprised of 6781 and 10 566 patients in the antiplatelet and non-antiplatelet therapy groups, respectively. In-hospital mortality was significantly lower in patients receiving prehospital antiplatelet therapy (18.9% vs. 21.5%, p < .001), resulting in a 2.6% absolute reduction in mortality (HR: 0.81, 95% CI: 0.76-0.87, p < .005). On average, 39 patients needed to be treated to prevent one in-hospital death. In the antiplatelet therapy group, there was a significantly lower rate of pulmonary embolism (2.2% vs. 3.0%, p = .002) and higher rate of epistaxis (0.9% vs. 0.4%, p < .001). There was no difference in the rate of other hemorrhagic or thrombotic complications., Conclusions: In the largest observational study to date of prehospital antiplatelet therapy in patients with COVID-19, there was an association with significantly lower in-hospital mortality. Randomized controlled trials in diverse patient populations with high rates of baseline comorbidities are needed to determine the ultimate utility of antiplatelet therapy in COVID-19., (© 2021 International Society on Thrombosis and Haemostasis.)

Objective: Understanding the risk factors for developing heart failure among patients with type 2 diabetes can contribute to preventing deterioration of quality of life for those persons. Electronic health records (EHR) provide an opportunity to use sophisticated machine learning models to understand and compare the effect of different risk factors for developing HF. As the complexity of the model increases, however, the transparency of the model often decreases. To interpret the results, we aimed to develop a model-agnostic approach to shed light on complex models and interpret the effect of features on developing heart failure. Using the HealthFacts EHR database of the Cerner EHR, we extracted the records of 723 patients with at least 6 yeas of follow up of type 2 diabetes, of whom 134 developed heart failure. Using age and comorbidities as features and heart failure as the outcome, we trained logistic regression, random forest, XGBoost, neural network, and then applied our proposed approach to rank the effect of each factor on developing heart failure., Results: Compared to the "importance score" built-in function of XGBoost, our proposed approach was more accurate in ranking the effect of the different risk factors on developing heart failure.

Magnetic resonance spectroscopic imaging (MRSI) offers considerable promise for monitoring metabolic alterations associated with disease or injury; however, to date, these methods have not had a significant impact on clinical care, and their use remains largely confined to the research community and a limited number of clinical sites. The MRSI methods currently implemented on clinical MRI instruments have remained essentially unchanged for two decades, with only incremental improvements in sequence implementation. During this time, a number of technological developments have taken place that have already greatly benefited the quality of MRSI measurements within the research community and which promise to bring advanced MRSI studies to the point where the technique becomes a true imaging modality, while making the traditional review of individual spectra a secondary requirement. Furthermore, the increasing use of biomedical MR spectroscopy studies has indicated clinical areas where advanced MRSI methods can provide valuable information for clinical care. In light of this rapidly changing technological environment and growing understanding of the value of MRSI studies for biomedical studies, this article presents a consensus from a group of experts in the field that reviews the state-of-the-art for clinical proton MRSI studies of the human brain, recommends minimal standards for further development of vendor-provided MRSI implementations, and identifies areas which need further technical development., (© 2020 John Wiley & Sons, Ltd.)

Background: Incomplete suicidality coding in administrative claims data is a known obstacle for observational studies. With most of the negative outcomes missing from the data, it is challenging to assess the evidence on treatment strategies for the prevention of self-harm in bipolar disorder (BD), including pharmacotherapy and psychotherapy. There are conflicting data from studies on the drug-dependent risk of self-harm, and there is major uncertainty regarding the preventive effect of monotherapy and drug combinations., Objective: The aim of this study was to compare all commonly used BD pharmacotherapies, as well as psychotherapy for the risk of self-harm, in a large population of commercially insured individuals, using self-harm imputation to overcome the known limitations of this outcome being underrecorded within US electronic health care records., Methods: The IBM MarketScan administrative claims database was used to compare self-harm risk in patients with BD following 65 drug regimens and drug-free periods. Probable but uncoded self-harm events were imputed via machine learning, with different probability thresholds examined in a sensitivity analysis. Comparators included lithium, mood-stabilizing anticonvulsants (MSAs), second-generation antipsychotics (SGAs), first-generation antipsychotics (FGAs), and five classes of antidepressants. Cox regression models with time-varying covariates were built for individual treatment regimens and for any pharmacotherapy with or without psychosocial interventions ("psychotherapy")., Results: Among 529,359 patients, 1.66% (n=8813 events) had imputed and/or coded self-harm following the exposure of interest. A higher self-harm risk was observed during adolescence. After multiple testing adjustment (P≤.012), the following six regimens had higher risk of self-harm than lithium: tri/tetracyclic antidepressants + SGA, FGA + MSA, FGA, serotonin-norepinephrine reuptake inhibitor (SNRI) + SGA, lithium + MSA, and lithium + SGA (hazard ratios [HRs] 1.44-2.29), and the following nine had lower risk: lamotrigine, valproate, risperidone, aripiprazole, SNRI, selective serotonin reuptake inhibitor (SSRI), "no drug," bupropion, and bupropion + SSRI (HRs 0.28-0.74). Psychotherapy alone (without medication) had a lower self-harm risk than no treatment (HR 0.56, 95% CI 0.52-0.60; P=8.76×10 -58 ). The sensitivity analysis showed that the direction of drug-outcome associations did not change as a function of the self-harm probability threshold., Conclusions: Our data support evidence on the effectiveness of antidepressants, MSAs, and psychotherapy for self-harm prevention in BD., Trial Registration: ClinicalTrials.gov NCT02893371; https://clinicaltrials.gov/ct2/show/NCT02893371., (©Anastasiya Nestsiarovich, Praveen Kumar, Nicolas Raymond Lauve, Nathaniel G Hurwitz, Aurélien J Mazurie, Daniel C Cannon, Yiliang Zhu, Stuart James Nelson, Annette S Crisanti, Berit Kerner, Mauricio Tohen, Douglas J Perkins, Christophe Gerard Lambert. Originally published in JMIR Mental Health (https://mental.jmir.org), 21.04.2021.)

Objectives: The study sought to learn if it were possible to develop an ontology that would allow the Food and Drug Administration approved indications to be expressed in a manner computable and comparable to what is expressed in an electronic health record., Materials and Methods: A random sample of 1177 of the 3000+ extant, distinct medical products (identified by unique new drug application numbers) was selected for investigation. Close manual examination of the indication portion of the labels for these drugs led to the development of a formal model of indications., Results: The model represents each narrative indication as a disjunct of conjuncts of assertions about an individual. A desirable attribute is that each assertion about an individual should be testable without reference to other contextual information about the situation. The logical primitives are chosen from 2 categories (context and conditions) and are linked to an enumeration of uses, such as prevention. We found that more than 99% of approved label indications for treatment or prevention could be so represented., Discussion: While some indications are straightforward to represent, difficulties stem from the need to represent temporal or sequential references. In addition, there is a mismatch of terminologies between what is present in an electronic health record and in the label narrative., Conclusions: A workable model for formalizing drug indications is possible. Remaining challenges include designing workflow to model narrative label indications for all approved drug products and incorporation of standard vocabularies., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: The data quality of electronic health records (EHR) has been a topic of increasing interest to clinical and health services researchers. One indicator of possible errors in data is a large change in the frequency of observations in chronic illnesses. In this study, we built and demonstrated the utility of a stacked multivariate LSTM model to predict an acceptable range for the frequency of observations., Methods: We applied the LSTM approach to a large EHR dataset with over 400 million total encounters. We computed sensitivity and specificity for predicting if the frequency of an observation in a given week is an aberrant signal., Results: Compared with the simple frequency monitoring approach, our proposed multivariate LSTM approach increased the sensitivity of finding aberrant signals in 6 randomly selected diagnostic codes from 75 to 88% and the specificity from 68 to 91%. We also experimented with two different LSTM algorithms, namely, direct multi-step and recursive multi-step. Both models were able to detect the aberrant signals while the recursive multi-step algorithm performed better., Conclusions: Simply monitoring the frequency trend, as is the common practice in systems that do monitor the data quality, would not be able to distinguish between the fluctuations caused by seasonal disease changes, seasonal patient visits, or a change in data sources. Our study demonstrated the ability of stacked multivariate LSTM models to recognize true data quality issues rather than fluctuations that are caused by different reasons, including seasonal changes and outbreaks., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Selenium is a vital micronutrient in many organisms. While traces are required for microbial utilization, excess amounts are toxic; thus, selenium can be regarded as a biological double-edged sword. Selenium is chemically similar to the essential element sulfur, but curiously, evolution has selected the former over the latter for a subset of oxidoreductases. Enzymes involved in sulfur metabolism are less discriminate in terms of preventing selenium incorporation; however, its specific incorporation into selenoproteins reveals a highly discriminate process that is not completely understood. We have identified SclA, a NifS-like protein in the nosocomial pathogen, Enterococcus faecalis, and characterized its enzymatic activity and specificity for l-selenocysteine over l-cysteine. It is known that Asp-146 is required for selenocysteine specificity in the human selenocysteine lyase. Thus, using computational biology, we compared the bacterial and mammalian enzymes and identified His-100, an Asp-146 ortholog in SclA, and generated site-directed mutants in order to study the residue's potential role in the l-selenocysteine discrimination mechanism. The proteins were overexpressed, purified, and characterized for their biochemical properties. All mutants exhibited varying Michaelis-Menten behavior towards l-selenocysteine, but His-100 was not found to be essential for this activity. Additionally, l-cysteine acted as a competitive inhibitor of all enzymes with higher affinity than l-selenocysteine. Finally, we discovered that SclA exhibited low activity with l-cysteine as a poor substrate regardless of mutations. We conclude that His-100 is not required for l-selenocysteine specificity, underscoring the inherent differences in discriminatory mechanisms between bacterial NifS-like proteins and mammalian selenocysteine lyases., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest associated with this manuscript., (Copyright © 2021 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.)

The knee meniscus is a soft fibrous tissue with a high incidence of injury in older populations. The objective of this study was to determine the effect of age on the failure behavior of human knee meniscus when applying uniaxial tensile loads parallel or perpendicular to the primary circumferential fiber orientation. Two age groups were tested: under 40 and over 65 years old. We paired high-speed video with digital image correlation to quantify for the first time the planar strains occurring in the tear region at precise time points, including at ultimate tensile stress, when the tissue begins losing load-bearing capacity. On average, older meniscus specimens loaded parallel to the fiber axis had approximately one-third less ultimate tensile strain and absorbed 60% less energy to failure within the tear region than younger specimens (p < 0.05). Older specimens also had significantly reduced strength and material toughness when loaded perpendicular to the fibers (p < 0.05). These age-related changes indicate a loss of collagen fiber extensibility and weakening of the non-fibrous matrix with age. In addition, we found that when loaded perpendicular to the circumferential fibers, tears propagated near the planes of maximum tensile stress and strain. Whereas when loaded parallel to the circumferential fibers, tears propagated oblique to the loading axis, closer to the planes of maximum shear stress and strain. Our experimental results can assist the selection of valid failure criteria for meniscus, and provide insight into the effect of age on the failure mechanisms of soft fibrous tissue., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)