Search

Several dozen Mendelian mutants have been discovered in axolotl (Ambystoma mexicanum) populations, including several that affect pigmentation. Four recessive mutants have been described in the scientific literature and genes for three of these have been identified. Here we describe and genetically dissect copper, a mutant with an albino-like phenotype known only from the pet trade. We performed a cross segregating copper and wildtype color phenotypes and used bulked segregant RNA-Seq to identify a region on chromosome 6 that was enriched for single-nucleotide polymorphisms (SNPs) between the color phenotypes. This region included Tyrosinase-like Protein 1 (Tyrp1), a melanin synthesis protein that when mutated, is associated with lighter than black melanin coloration in animal models and oculocutaneous albinism in humans. Inspection of RNA-Seq reads identified a single nucleotide deletion that is predicted to change the coding frame, introduce a premature stop codon in exon 6 and yield a truncated Tyrp1 protein in copper individuals. Using CRISPR-Cas9 editing, we show that wildtype Tyrp1 crispants exhibit copper pigmentation, thus confirming Tyrp1 as the copper locus. Our results suggest that commercial and hobbyist axolotl populations may harbor useful mutants for biological research., (© 2024. The Author(s).)

Introduction: There is little consensus and high heterogeneity on the optimal set of relevant clinical outcomes in research studies regarding extubation in neurocritical care patients with brain injury undergoing mechanical ventilation. The aims of this study are to: (1) develop a core outcome set (COS) and (2) reach consensus on a hierarchical composite endpoint for such studies., Methods and Analysis: The study will include a broadly representative, international panel of stakeholders with research and clinical expertise in this field and will involve four stages: (1) a scoping review to generate an initial list of outcomes represented in the literature, (2) an investigator meeting to review the outcomes for inclusion in the Delphi surveys, (3) four rounds of online Delphi consensus-building surveys and (4) online consensus meetings to finalise the COS and hierarchical composite endpoint., Ethics and Dissemination: This study received ethical approval from the French Society of Anesthesia and Critical Care Medicine Institutional Review Board (SFAR CERAR-IRB 00010254-2023-029). The study results will be disseminated through communication to stakeholders, publication in a peer-reviewed journal, and presentations at conferences., Trial Registration Number: This study is registered with the Core Outcome Measures in Effectiveness Trials (COMET) Initiative., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Existing methods to characterise the evolving condition of traumatic brain injury (TBI) patients in the intensive care unit (ICU) do not capture the context necessary for individualising treatment. Here, we integrate all heterogenous data stored in medical records (1166 pre-ICU and ICU variables) to model the individualised contribution of clinical course to 6-month functional outcome on the Glasgow Outcome Scale -Extended (GOSE). On a prospective cohort (n = 1550, 65 centres) of TBI patients, we train recurrent neural network models to map a token-embedded time series representation of all variables (including missing values) to an ordinal GOSE prognosis every 2 h. The full range of variables explains up to 52% (95% CI: 50-54%) of the ordinal variance in functional outcome. Up to 91% (95% CI: 90-91%) of this explanation is derived from pre-ICU and admission information (i.e., static variables). Information collected in the ICU (i.e., dynamic variables) increases explanation (by up to 5% [95% CI: 4-6%]), though not enough to counter poorer overall performance in longer-stay (>5.75 days) patients. Highest-contributing variables include physician-based prognoses, CT features, and markers of neurological function. Whilst static information currently accounts for the majority of functional outcome explanation after TBI, data-driven analysis highlights investigative avenues to improve the dynamic characterisation of longer-stay patients. Moreover, our modelling strategy proves useful for converting large patient records into interpretable time series with missing data integration and minimal processing., (© 2023. Springer Nature Limited.)

Background: Increased burnout and decreased professional fulfillment among intensive care physicians is partly due to intensive care unit (ICU) workload. Although the SARS-CoV-2 (COVID-19) pandemic increased ICU workload, it also may have increased feelings of personal fulfillment due to positive public perceptions of physicians caring for COVID patients. We surveyed critical care anesthesiologists to identify the effect of provider demographics, ICU workload, and COVID-19-related workload, on professional fulfillment and burnout., Methods: We performed an exploratory survey of 606 members of the Society of Critical Care Anesthesiologists (SOCCA) in January and February 2022. We used the Stanford Professional Fulfillment Index (PFI) to grade levels of professional fulfillment and markers of burnout (ie, work exhaustion and disengagement). Univariable and multivariable models were used to identify associations between provider demographics and practice characteristics and professional fulfillment and work exhaustion., Results: One hundred and seventy-five intensivists (29%) responded. A total of 65% were male and 49% were between 36 and 45 years old. The overall median PFI score-0 (none) to 24 (most professional fulfillment)-was 17 (IQR, 1-24), with a wide distribution of responses. In multivariable analysis, factors associated with higher professional fulfillment included age >45 years ( P =.004), ≤15 weeks full-time ICU coverage in 2020 ( P =.02), role as medical director ( P =.01), and nighttime home call with supervision of in-house ICU fellows ( P =.01)., Conclusions: Professional fulfillment and work exhaustion in this cross-sectional survey were associated with several demographic and practice characteristics but not COVID-19-related workload, suggesting that COVID-19 workload may not have either positive or negative perceptions on professional fulfillment., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2023 International Anesthesia Research Society.)

Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to declare., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: There is insufficient evidence to guide ventilatory targets in acute brain injury (ABI). Recent studies have shown associations between mechanical power (MP) and mortality in critical care populations. We aimed to describe MP in ventilated patients with ABI, and evaluate associations between MP and clinical outcomes., Methods: In this preplanned, secondary analysis of a prospective, multi-center, observational cohort study (ENIO, NCT03400904), we included adult patients with ABI (Glasgow Coma Scale ≤ 12 before intubation) who required mechanical ventilation (MV) ≥ 24 h. Using multivariable log binomial regressions, we separately assessed associations between MP on hospital day (HD)1, HD3, HD7 and clinical outcomes: hospital mortality, need for reintubation, tracheostomy placement, and development of acute respiratory distress syndrome (ARDS)., Results: We included 1217 patients (mean age 51.2 years [SD 18.1], 66% male, mean body mass index [BMI] 26.3 [SD 5.18]) hospitalized at 62 intensive care units in 18 countries. Hospital mortality was 11% (n = 139), 44% (n = 536) were extubated by HD7 of which 20% (107/536) required reintubation, 28% (n = 340) underwent tracheostomy placement, and 9% (n = 114) developed ARDS. The median MP on HD1, HD3, and HD7 was 11.9 J/min [IQR 9.2-15.1], 13 J/min [IQR 10-17], and 14 J/min [IQR 11-20], respectively. MP was overall higher in patients with ARDS, especially those with higher ARDS severity. After controlling for same-day pressure of arterial oxygen/fraction of inspired oxygen (P/F ratio), BMI, and neurological severity, MP at HD1, HD3, and HD7 was independently associated with hospital mortality, reintubation and tracheostomy placement. The adjusted relative risk (aRR) was greater at higher MP, and strongest for: mortality on HD1 (compared to the HD1 median MP 11.9 J/min, aRR at 17 J/min was 1.22, 95% CI 1.14-1.30) and HD3 (1.38, 95% CI 1.23-1.53), reintubation on HD1 (1.64; 95% CI 1.57-1.72), and tracheostomy on HD7 (1.53; 95%CI 1.18-1.99). MP was associated with the development of moderate-severe ARDS on HD1 (2.07; 95% CI 1.56-2.78) and HD3 (1.76; 95% CI 1.41-2.22)., Conclusions: Exposure to high MP during the first week of MV is associated with poor clinical outcomes in ABI, independent of P/F ratio and neurological severity. Potential benefits of optimizing ventilator settings to limit MP warrant further investigation., (© 2023. The Author(s).)

Motor impairments are only one aspect of Parkinson's disease (PD), which also include cognitive and linguistic impairments. Speech-derived interpretable biomarkers may help clinicians diagnose PD at earlier stages and monitor the disorder's evolution over time. This study focuses on the multilingual evaluation of a composite array of biomarkers that facilitate PD evaluation from speech. Hypokinetic dysarthria, a motor speech disorder associated with PD, has been extensively analyzed in previously published studies on automatic PD evaluation, with a relative lack of inquiry into language and task variability. In this study, we explore certain acoustic, linguistic, and cognitive information encoded within the speech of several cohorts with PD. A total of 24 biomarkers were analyzed from American English, Italian, Castilian Spanish, Colombian Spanish, German, and Czech by conducting a statistical analysis to evaluate which biomarkers best differentiate people with PD from healthy participants. The study leverages conceptual robustness as a criterion in which a biomarker behaves the same, independent of the language. Hence, we propose a set of speech-based biomarkers that can effectively help evaluate PD while being language-independent. In short, the best acoustic and cognitive biomarkers permitting discrimination between experimental groups across languages were fundamental frequency standard deviation, pause time, pause percentage, silence duration, and speech rhythm standard deviation. Linguistic biomarkers representing the length of the narratives and the number of nouns and auxiliaries also provided discrimination between groups. Altogether, in addition to being significant, these biomarkers satisfied the robustness requirements., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Favaro, Moro-Velázquez, Butala, Motley, Cao, Stevens, Villalba and Dehak.)

Background: Delirium poses significant risks to patients, but countermeasures can be taken to mitigate negative outcomes. Accurately forecasting delirium in intensive care unit (ICU) patients could guide proactive intervention. Our primary objective was to predict ICU delirium by applying machine learning to clinical and physiologic data routinely collected in electronic health records., Methods: Two prediction models were trained and tested using a multicenter database (years of data collection 2014 to 2015), and externally validated on two single-center databases (2001 to 2012 and 2008 to 2019). The primary outcome variable was delirium defined as a positive Confusion Assessment Method for the ICU screen, or an Intensive Care Delirium Screening Checklist of 4 or greater. The first model, named "24-hour model," used data from the 24 h after ICU admission to predict delirium any time afterward. The second model designated "dynamic model," predicted the onset of delirium up to 12 h in advance. Model performance was compared with a widely cited reference model., Results: For the 24-h model, delirium was identified in 2,536 of 18,305 (13.9%), 768 of 5,299 (14.5%), and 5,955 of 36,194 (11.9%) of patient stays, respectively, in the development sample and two validation samples. For the 12-h lead time dynamic model, delirium was identified in 3,791 of 22,234 (17.0%), 994 of 6,166 (16.1%), and 5,955 of 28,440 (20.9%) patient stays, respectively. Mean area under the receiver operating characteristics curve (AUC) (95% CI) for the first 24-h model was 0.785 (0.769 to 0.801), significantly higher than the modified reference model with AUC of 0.730 (0.704 to 0.757). The dynamic model had a mean AUC of 0.845 (0.831 to 0.859) when predicting delirium 12 h in advance. Calibration was similar in both models (mean Brier Score [95% CI] 0.102 [0.097 to 0.108] and 0.111 [0.106 to 0.116]). Model discrimination and calibration were maintained when tested on the validation datasets., Conclusions: Machine learning models trained with routinely collected electronic health record data accurately predict ICU delirium, supporting dynamic time-sensitive forecasting., (Copyright © 2023, the American Society of Anesthesiologists. All Rights Reserved.)

Background: Despite the growing contributions of critical care anesthesiologists to clinical practice, research, and administrative leadership of intensive care units (ICUs), relatively little is known about the subspecialty-specific clinical practice environment. An understanding of contemporary clinical practice is essential to recognize the opportunities and challenges facing critical care anesthesia, optimize staffing patterns, assess sustainability and satisfaction, and strategically plan for future activity, scope, and training. This study surveyed intensivists who are members of the Society of Critical Care Anesthesiologists (SOCCA) to evaluate practice patterns of critical care anesthesiologists, including compensation, types of ICUs covered, models of overnight ICU coverage, and relationships between these factors. We hypothesized that variability in compensation and practice patterns would be observed between individuals., Methods: Board-certified critical care anesthesiologists practicing in the United States were identified using the SOCCA membership distribution list and invited to take a voluntary online survey between May and June 2021. Multiple-choice questions with both single- and multiple-select options were used for answers with categorical data, and adaptive questioning was used to clarify stem-based responses. Respondents were asked to describe practice patterns at their respective institutions and provide information about their demographics, salaries, effort in ICUs, as well as other activities., Results: A total of 490 participants were invited to take this survey, and 157 (response rate 32%) surveys were completed and analyzed. The majority of respondents were White (73%), male (69%), and younger than 50 years of age (82%). The cardiothoracic/cardiovascular ICU was the most common practice setting, with 69.5% of respondents reporting time working in this unit. Significant variability was observed in ICU practice patterns. Respondents reported spending an equal proportion of their time in clinical practice in the operating rooms and ICUs (median, 40%; interquartile range [IQR], 20%-50%), whereas a smaller proportion-primarily those who completed their training before 2009-reported administrative or research activities. Female respondents reported salaries that were $36,739 less than male respondents; however, this difference was not statistically different, and after adjusting for age and practice type, these differences were less pronounced (-$27,479.79; 95% confidence interval [CI], -$57,232.61 to $2273.03; P = .07)., Conclusions: These survey data provide a current snapshot of anesthesiology critical care clinical practice patterns in the United States. Our findings may inform decision-making around the initiation and expansion of critical care services and optimal staffing patterns, as well as provide a basis for further work that focuses on intensivist satisfaction and burnout., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 International Anesthesia Research Society.)

Species with low effective population sizes are at greater risk of extinction because of reduced genetic diversity. Such species are more vulnerable to chance events that decrease population sizes (e.g. demographic stochasticity). Dipodomys elator, (Texas kangaroo rat) is a kangaroo rat that is classified as threatened in Texas and field surveys from the past 50 years indicate that the distribution of this species has decreased. This suggests geographic range reductions that could have caused population fluctuations, potentially impacting effective population size. Conversely, the more common and widespread D. ordii (Ord's kangaroo rat) is thought to exhibit relative geographic and demographic stability. We assessed the genetic variation of D. elator and D. ordii samples using 3RAD, a modified restriction site associated sequencing approach. We hypothesized that D. elator would show lower levels of nucleotide diversity, observed heterozygosity, and effective population size when compared to D. ordii. We were also interested in identifying population structure within contemporary samples of D. elator and detecting genetic variation between temporal samples to understand demographic dynamics. We analyzed up to 61,000 single nucleotide polymorphisms. We found that genetic variability and effective population size in contemporary D. elator populations is lower than that of D. ordii. There is slight, if any, population structure within contemporary D. elator samples, and we found low genetic differentiation between spatial or temporal historical samples. This indicates little change in nuclear genetic diversity over 30 years. Results suggest that genetic diversity of D. elator has remained stable despite reduced population size and/or abundance, which may indicate a metapopulation-like system, whose fluctuations might counteract species extinction., Competing Interests: The authors have declared that no competing interests exist.

The epidemiology of coma is unknown because case ascertainment with traditional methods is difficult. Here, we used crowdsourcing methodology to estimate the incidence and prevalence of coma in the UK and the USA. We recruited UK and US laypeople (aged ≥18 years) who were nationally representative (i.e. matched for age, gender and ethnicity according to census data) of the UK and the USA, respectively, utilizing a crowdsourcing platform. We provided a description of coma and asked survey participants if they-'right now' or 'within the last year'-had a family member in coma. These participants (UK n  = 994, USA n  = 977) provided data on 30 387 family members (UK n  = 14 124, USA n  = 16 263). We found more coma cases in the USA ( n  = 47) than in the UK ( n  = 20; P  = 0.009). We identified one coma case in the UK (0.007%, 95% confidence interval 0.00-0.04%) on the day of the survey and 19 new coma cases (0.13%, 95% confidence interval 0.08-0.21%) within the preceding year, resulting in an annual incidence of 135/100 000 (95% confidence interval 81-210) and a point prevalence of 7 cases per 100 000 population (95% confidence interval 0.18-39.44) in the UK. We identified five cases in the USA (0.031%, 95% confidence interval 0.01-0.07%) on the day of the survey and 42 new cases (0.26%, 95% confidence interval 0.19-0.35%) within the preceding year, resulting in an annual incidence of 258/100 000 (95% confidence interval 186-349) and a point prevalence of 31 cases per 100 000 population (95% confidence interval 9.98-71.73) in the USA. The five most common causes were stroke, medically induced coma, COVID-19, traumatic brain injury and cardiac arrest. To summarize, for the first time, we report incidence and prevalence estimates for coma across diagnosis types and settings in the UK and the USA using crowdsourcing methods. Coma may be more prevalent in the USA than in the UK, which requires further investigation. These data are urgently needed to expand the public health perspective on coma and disorders of consciousness., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Identifying biological processes that structure natural communities has long interested ecologists. Community structure may be determined by various processes, including differential responses of species to environmental characteristics, regional-level spatial influences such as dispersal, or stochasticity generated from ecological drift. Few studies have used the metacommunity paradigm (interacting communities linked by dispersal) to investigate avian community composition along an urban gradient, yet such a theoretical construct may provide insights into species turnover even in unnatural settings such as rural to urban gradients. We measured the influence of spatial and environmental characteristics on two aspects of avian community structure across a gradient of urbanization: 1) taxonomic composition and 2) functional richness based on diet, foraging strategies, nesting locations and morphology. We also measured the relationship between species traits and environmental variables with an RLQ-fourth corner analysis. Together, environmental and spatial processes were significantly related to taxonomic structure and functional richness, but spatial variables accounted for more variation than environmental variables. Fine spatial scales were positively correlated with insectivorous birds and negatively correlated with body and wing size. Urbanization was positively correlated with birds that forage at the canopy level, while emergent wetlands were negatively correlated with birds that nested in cliffs and frugivorous birds. Functional richness and urbanization were significantly related to fine spatial variables. Spatial and environmental factors played an important role in taxonomic and functional structure in avian metacommunity structure. This study highlights the importance of studying multiple aspects of biodiversity, such as taxonomic and functional dimensions, especially when examining effects of complementary spatial and environmental processes., Competing Interests: The authors have declared that no competing interests exist.

When a patient is admitted to the intensive care unit (ICU) after a traumatic brain injury (TBI), an early prognosis is essential for baseline risk adjustment and shared decision making. TBI outcomes are commonly categorised by the Glasgow Outcome Scale-Extended (GOSE) into eight, ordered levels of functional recovery at 6 months after injury. Existing ICU prognostic models predict binary outcomes at a certain threshold of GOSE (e.g., prediction of survival [GOSE > 1]). We aimed to develop ordinal prediction models that concurrently predict probabilities of each GOSE score. From a prospective cohort (n = 1,550, 65 centres) in the ICU stratum of the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) patient dataset, we extracted all clinical information within 24 hours of ICU admission (1,151 predictors) and 6-month GOSE scores. We analysed the effect of two design elements on ordinal model performance: (1) the baseline predictor set, ranging from a concise set of ten validated predictors to a token-embedded representation of all possible predictors, and (2) the modelling strategy, from ordinal logistic regression to multinomial deep learning. With repeated k-fold cross-validation, we found that expanding the baseline predictor set significantly improved ordinal prediction performance while increasing analytical complexity did not. Half of these gains could be achieved with the addition of eight high-impact predictors to the concise set. At best, ordinal models achieved 0.76 (95% CI: 0.74-0.77) ordinal discrimination ability (ordinal c-index) and 57% (95% CI: 54%- 60%) explanation of ordinal variation in 6-month GOSE (Somers' Dxy). Model performance and the effect of expanding the predictor set decreased at higher GOSE thresholds, indicating the difficulty of predicting better functional outcomes shortly after ICU admission. Our results motivate the search for informative predictors that improve confidence in prognosis of higher GOSE and the development of ordinal dynamic prediction models., Competing Interests: The authors have declared that no competing interests exist.

Purpose: External ventricular drains (EVD) are commonly used in aneurysmal subarachnoid hemorrhage (aSAH) patients and can be life-saving by diverting cerebrospinal fluid. However, the overall relationship between EVD use and outcome is poorly understood., Methods: In an exploratory analysis of an aSAH patient cohort, we examined EVD use in relation to modified Rankin Scale (mRS) at hospital discharge and at 6 months (unfavorable outcome = mRS > 2) using univariable and multivariable analyses., Results: EVDs were placed in 31 of 56 (55.4%) patients and more often in women than men (66.7% vs 35.0%, p = 0.022) despite similar rates of hydrocephalus. Women had greater ICU [18 (13.5-25) vs 11.5 (6.5-18.5) days, p = 0.014] and hospital lengths of stay (LOS) [20.5 (16.5-34) vs 13.5 (10.5-27) days, p = 0.015] than men and greater mRS at discharge [4 (3-5) vs 3 (2-3.5), p = 0.011] although mRS at 6 months was similar. Patients with EVDs had longer ICU and hospital LOS and greater mRS at discharge [5 (3-6) vs 2 (2-3), p < 0.001] and at 6 months [4 (2-6) vs 1 (0-2), p = 0.001] than those without an EVD. In multivariable models, EVD use was associated with unfavorable 6-month outcome accounting for age, sex, and admission modified Fisher scale, but not in models adjusting for Hunt and Hess scale and World Federation of Neurological Surgeons scale., Conclusion: In an aSAH cohort, the use of EVDs was associated with female sex and longer LOS, and may be linked to functional outcomes at discharge and at 6 months, although these associations warrant further investigation., (© 2022. The Author(s).)

Statins are a class of drug widely prescribed for the prevention of cardiovascular disease, with pleiotropic cellular effects. Statins inhibit HMG-CoA reductase (HMGCR), which converts the metabolite HMG-CoA into mevalonate. Recent discoveries have shown HMG-CoA is a reactive metabolite that can non-enzymatically modify proteins and impact their activity. Therefore, we predicted that inhibition of HMGCR by statins might increase HMG-CoA levels and protein modifications. Upon statin treatment, we observe a strong increase in HMG-CoA levels and modification of only a single protein. Mass spectrometry identifies this protein as fatty acid synthase (FAS), which is modified on active site residues and, importantly, on non-lysine side-chains. The dynamic modifications occur only on a sub-pool of FAS that is located near HMGCR and alters cellular signaling around the ER and Golgi. These results uncover communication between cholesterol and lipid biosynthesis by the substrate of one pathway inhibiting another in a rapid and reversible manner., (© 2022. The Author(s).)

Data papers and open databases have revolutionized contemporary science, as they provide the long-needed incentive to collaborate in large international teams and make natural history information widely available. Nevertheless, most data papers have focused on species occurrence or abundance, whereas interactions have received much less attention. To help fill this gap, we have compiled a georeferenced data set of interactions between 93 bat species of the family Phyllostomidae (Chiroptera) and 501 plant species of 68 families. Data came from 169 studies published between 1957 and 2007 covering the entire Neotropical Region, with most records from Brazil (34.5% of all study sites), Costa Rica (16%), and Mexico (14%). Our data set includes 2571 records of frugivory (75.1% of all records) and nectarivory (24.9%). The best represented bat genera are Artibeus (28% of all records), Carollia (24%), Sturnira (10.1%), and Glossophaga (8.8%). Carollia perspicillata (187), Artibeus lituratus (125), Artibeus jamaicensis (94), Glossophaga soricina (86), and Artibeus planirostris (74) were the bat species with the broadest diets recorded based on the number of plant species. Among the plants, the best represented families were Moraceae (17%), Piperaceae (15.4%), Urticaceae (9.2%), and Solanaceae (9%). Plants of the genera Cecropia (46), Ficus (42), Piper (40), Solanum (31), and Vismia (27) exhibited the largest number of interactions. These data are stored as arrays (records, sites, and studies) organized by logical keys and rich metadata, which helped to compile the information on different ecological and geographic scales, according to how they should be used. Our data set on bat-plant interactions is by far the most extensive, both in geographic and taxonomic terms, and includes abiotic information of study sites, as well as ecological information of plants and bats. It has already facilitated several studies and we hope it will stimulate novel analyses and syntheses, in addition to pointing out important gaps in knowledge. Data are provided under the Creative Commons Attribution 4.0 International License. Please cite this paper when the data are used in any kind of publication related to research, outreach, and teaching activities., (© 2022 The Authors. Ecology © 2022 The Ecological Society of America.)

Using presence/absence data from over 10,000 Ves SINE insertions, we reconstructed a phylogeny for 11 Myotis species. With nearly one-third of individual Ves gene trees discordant with the overall species tree, phylogenetic conflict appears to be rampant in this genus. From the observed conflict, we infer that ILS is likely a major contributor to the discordance. Much of the discordance can be attributed to the hypothesized split between the Old World and New World Myotis clades and with the first radiation of Myotis within the New World. Quartet asymmetry tests reveal signs of introgression between Old and New World taxa that may have persisted until approximately 8 MYA. Our introgression tests also revealed evidence of both historic and more recent, perhaps even contemporary, gene flow among Myotis species of the New World. Our findings suggest that hybridization likely played an important role in the evolutionary history of Myotis and may still be happening in areas of sympatry. Despite limitations arising from extreme discordance, our SINE-based phylogeny better resolved deeper relationships (particularly the positioning of M. brandtii ) and was able to identify potential introgression pathways among the Myotis species sampled.

Our goal is to explore quantitative motor features in critically ill patients with severe brain injury (SBI). We hypothesized that computational decoding of these features would yield information on underlying neurological states and outcomes. Using wearable microsensors placed on all extremities, we recorded a median 24.1 (IQR: 22.8-25.1) hours of high-frequency accelerometry data per patient from a prospective cohort (n = 69) admitted to the ICU with SBI. Models were trained using time-, frequency-, and wavelet-domain features and levels of responsiveness and outcome as labels. The two primary tasks were detection of levels of responsiveness, assessed by motor sub-score of the Glasgow Coma Scale (GCSm), and prediction of functional outcome at discharge, measured with the Glasgow Outcome Scale-Extended (GOSE). Detection models achieved significant (AUC: 0.70 [95% CI: 0.53-0.85]) and consistent (observation windows: 12 min-9 h) discrimination of SBI patients capable of purposeful movement (GCSm > 4). Prediction models accurately discriminated patients of upper moderate disability or better (GOSE > 5) with 2-6 h of observation (AUC: 0.82 [95% CI: 0.75-0.90]). Results suggest that time series analysis of motor activity yields clinically relevant insights on underlying functional states and short-term outcomes in patients with SBI., (© 2021. The Author(s).)

Traumatic brain injury (TBI) is a leading neurological cause of death and disability across the world. Early characterization of TBI severity could provide a window for therapeutic intervention and contribute to improved outcome. We hypothesized that granular electronic health record data available in the first 24 h following admission to the intensive care unit (ICU) can be used to differentiate outcomes at discharge. Working from two ICU datasets we focused on patients with a primary admission diagnosis of TBI whose length of stay in ICU was ≥ 24 h (N = 1689 and 127). Features derived from clinical, laboratory, medication, and physiological time series data in the first 24 h after ICU admission were used to train elastic-net regularized Generalized Linear Models for the prediction of mortality and neurological function at ICU discharge. Model discrimination, determined by area under the receiver operating characteristic curve (AUC) analysis, was 0.903 and 0.874 for mortality and neurological function, respectively. Model performance was successfully validated in an external dataset (AUC 0.958 and 0.878 for mortality and neurological function, respectively). These results demonstrate that computational analysis of data routinely collected in the first 24 h after admission accurately and reliably predict discharge outcomes in ICU stratum TBI patients., (© 2021. The Author(s).)

Background: Cell transplantation-based treatments for neurological disease are promising, yet graft rejection remains a major barrier to successful regenerative therapies. Our group and others have shown that long-lasting tolerance of transplanted stem cells can be achieved in the brain with systemic application of monoclonal antibodies blocking co-stimulation signaling. However, it is unknown if subsequent injury and the blood-brain barrier breach could expose the transplanted cells to systemic immune system spurring fulminant rejection and fatal encephalitis. Therefore, we investigated whether delayed traumatic brain injury (TBI) could trigger graft rejection., Methods: Glial-restricted precursor cells (GRPs) were intracerebroventricularly transplanted in immunocompetent neonatal mice and co-stimulation blockade (CoB) was applied 0, 2, 4, and 6 days post-grafting. Bioluminescence imaging (BLI) was performed to monitor the grafted cell survival. Mice were subjected to TBI 12 weeks post-transplantation. MRI and open-field test were performed to assess the brain damage and behavioral change, respectively. The animals were decapitated at week 16 post-transplantation, and the brains were harvested. The survival and distribution of grafted cells were verified from brain sections. Hematoxylin and eosin staining (HE) was performed to observe TBI-induced brain legion, and neuroinflammation was evaluated immunohistochemically., Results: BLI showed that grafted GRPs were rejected within 4 weeks after transplantation without CoB, while CoB administration resulted in long-term survival of allografts. BLI signal had a steep rise following TBI and subsequently declined but remained higher than the preinjury level. Open-field test showed TBI-induced anxiety for all animals but neither CoB nor GRP transplantation intensified the symptom. HE and MRI demonstrated a reduction in TBI-induced lesion volume in GRP-transplanted mice compared with non-transplanted mice. Brain sections further validated the survival of grafted GRPs and showed more GRPs surrounding the injured tissue. Furthermore, the brains of post-TBI shiverer mice had increased activation of microglia and astrocytes compared to post-TBI wildtype mice, but infiltration of CD45+ leukocytes remained low., Conclusions: CoB induces sustained immunological tolerance towards allografted cerebral GRPs which is not disrupted following TBI, and unexpectedly TBI may enhance GRPs engraftment and contribute to post-injury brain tissue repair.

Coronavirus SARS-COV-2 infections continue to spread across the world, yet effective large-scale disease detection and prediction remain limited. COVID Control: A Johns Hopkins University Study, is a novel syndromic surveillance approach, which collects body temperature and COVID-like illness (CLI) symptoms across the US using a smartphone app and applies spatio-temporal clustering techniques and cross-correlation analysis to create maps of abnormal symptomatology incidence that are made publicly available. The results of the cross-correlation analysis identify optimal temporal lags between symptoms and a range of COVID-19 outcomes, with new taste/smell loss showing the highest correlations. We also identified temporal clusters of change in taste/smell entries and confirmed COVID-19 incidence in Baltimore City and County. Further, we utilized an extended simulated dataset to showcase our analytics in Maryland. The resulting clusters can serve as indicators of emerging COVID-19 outbreaks, and support syndromic surveillance as an early warning system for disease prevention and control.

Glycine levels are inversely associated with branched-chain amino acids (BCAAs) and cardiometabolic disease phenotypes, but biochemical mechanisms that explain these relationships remain uncharted. Metabolites and genes related to BCAA metabolism and nitrogen handling were strongly associated with glycine in correlation analyses. Stable isotope labeling in Zucker fatty rats (ZFRs) shows that glycine acts as a carbon donor for the pyruvate-alanine cycle in a BCAA-regulated manner. Inhibition of the BCAA transaminase (BCAT) enzymes depletes plasma pools of alanine and raises glycine levels. In high-fat-fed ZFRs, dietary glycine supplementation raises urinary acyl-glycine content and lowers circulating triglycerides but also results in accumulation of long-chain acyl-coenzyme As (acyl-CoAs), lower 5' adenosine monophosphate-activated protein kinase (AMPK) phosphorylation in muscle, and no improvement in glucose tolerance. Collectively, these studies frame a mechanism for explaining obesity-related glycine depletion and also provide insight into the impact of glycine supplementation on systemic glucose, lipid, and amino acid metabolism., Competing Interests: Declaration of Interests C.B.N. is a member of the Eli Lilly Global Diabetes Advisory Board. He was also the lead investigator of now-completed sponsored research agreements with Pfizer and Lilly that supported a portion of the studies described herein., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Prolonged invasive ventilation is common in patients with severe brain injury. Information on optimal management of extubation and on the use of tracheostomy in these patients is scarce. International guidelines regarding the ventilator liberation and tracheostomy are currently lacking., Methods: The aim of 'Extubation strategies in Neuro-Intensive care unit patients and associations with Outcomes' (ENIO) study is to describe current management of weaning from invasive ventilation, focusing on decisions on timing of tracheal extubation and tracheostomy in intensive care unit (ICU) patients with brain injury. We conducted a prospective, international, multi-centre observational study enrolling patients with various types of brain injury, including trauma, stroke, and subarachnoid haemorrhage, with an initial Glasgow Coma Score equal or less than 12, and a duration of invasive ventilation longer than 24 hours from ICU admission. ENIO is expected to include at least 1,500 patients worldwide. The primary endpoint of the ENIO study is extubation success in the 48 hours following endotracheal tube removal. The primary objective is to validate a score predictive of extubation success. To accomplish this, the study population will be randomly divided to a development cohort (2/3 of the included patients) and a validation cohort (the remaining 1/3). Secondary objectives are: to determine the incidence of extubation success rate according to various time-frames (within 96 hours, >96 hours after extubation); to validate (existing) prediction scores for successful extubation according to various time-frames and definitions (i.e., tracheostomy as extubation failure); and to describe the current practices of extubation and tracheostomy, and their associations., Discussion: ENIO will be the largest prospective observational study of ventilator liberation and tracheostomy practices in patients with severe brain injury undergoing invasive mechanical ventilation, providing a validated predictive score of successful extubation., Trial Registration: The ENIO study is registered in the Clinical Trials database: NCT03400904., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/atm.2020.03.160). Pr Karim Asehnoune received fees from Baxter, Edwards, LFB, Fisher and Payckel, out of the scope of the present work. The other authors have no conflicts of interest to declare., (2020 Annals of Translational Medicine. All rights reserved.)

Crocodilians are an economically, culturally, and biologically important group. To improve researchers' ability to study genome structure, evolution, and gene regulation in the clade, we generated a high-quality de novo genome assembly of the saltwater crocodile, Crocodylus porosus, from Illumina short read data from genomic libraries and in vitro proximity-ligation libraries. The assembled genome is 2,123.5 Mb, with N50 scaffold size of 17.7 Mb and N90 scaffold size of 3.8 Mb. We then annotated this new assembly, increasing the number of annotated genes by 74%. In total, 96% of 23,242 annotated genes were associated with a functional protein domain. Furthermore, multiple noncoding functional regions and mappable genetic markers were identified. Upon analysis and overlapping the results of branch length estimation and site selection tests for detecting potential selection, we found 16 putative genes under positive selection in crocodilians, 10 in C. porosus and 6 in Alligator mississippiensis. The annotated C. porosus genome will serve as an important platform for osmoregulatory, physiological, and sex determination studies, as well as an important reference in investigating the phylogenetic relationships of crocodilians, birds, and other tetrapods., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Context: Newborn adiposity is associated with childhood obesity. Cord blood metabolomics is one approach that can be used to understand early-life contributors to adiposity and insulin resistance., Objective: To determine the association of cord blood metabolites with newborn adiposity and hyperinsulinemia in a multiethnic cohort of newborns., Design: Cross-sectional, observational study., Setting: Hyperglycemia and Adverse Pregnancy Outcome study., Participants: One thousand six hundred multiethnic mother-newborn pairs., Main Outcome Measure: Cord blood C-peptide, birthweight, and newborn sum of skinfolds., Results: Meta-analyses across four ancestry groups (Afro-Caribbean, Northern European, Thai, and Mexican American) demonstrated significant associations of cord blood metabolites with cord blood C-peptide, birthweight, and newborn sum of skinfolds. Several metabolites, including branched-chain amino acids (BCAAs), medium- and long-chain acylcarnitines, nonesterified fatty acids, and triglycerides were negatively associated with cord C-peptide but positively associated with birthweight and/or sum of skinfolds. 1,5-Anhydroglucitol, an inverse marker of recent maternal glycemia, was significantly inversely associated with birthweight and sum of skinfolds. Network analyses revealed groups of interrelated amino acid, acylcarnitine, and fatty acid metabolites associated with all three newborn outcomes., Conclusions: Cord blood metabolites are associated with newborn size and cord blood C-peptide levels after adjustment for maternal body mass index and glucose during pregnancy. Negative associations of metabolites with C-peptide at birth were observed. 1,5-Anhydroglucitol appears to be a marker of adiposity in newborns. BCAAs were individually associated with birthweight and demonstrated possible associations with newborn adiposity in network analyses., (Copyright © 2019 Endocrine Society.)

Transposable elements (TEs) play major roles in the evolution of genome structure and function. However, because of their repetitive nature, they are difficult to annotate and discovering the specific roles they may play in a lineage can be a daunting task. Heliconiine butterflies are models for the study of multiple evolutionary processes including phenotype evolution and hybridization. We attempted to determine how TEs may play a role in the diversification of genomes within this clade by performing a detailed examination of TE content and accumulation in 19 species whose genomes were recently sequenced. We found that TE content has diverged substantially and rapidly in the time since several subclades shared a common ancestor with each lineage harboring a unique TE repertoire. Several novel SINE lineages have been established that are restricted to a subset of species. Furthermore, the previously described SINE, Metulj, appears to have gone extinct in two subclades while expanding to significant numbers in others. This diversity in TE content and activity has the potential to impact how heliconiine butterflies continue to evolve and diverge., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Growth failure during infancy is a major global problem that has adverse effects on long-term health and neurodevelopment. Preterm infants are disproportionately affected by growth failure and its effects. Herein we found that extremely preterm infants with postnatal growth failure have disrupted maturation of the intestinal microbiota, characterized by persistently low diversity, dominance of pathogenic bacteria within the Enterobacteriaceae family, and a paucity of strictly anaerobic taxa including Veillonella relative to infants with appropriate postnatal growth. Metabolomic profiling of infants with growth failure demonstrated elevated serum acylcarnitines, fatty acids, and other byproducts of lipolysis and fatty acid oxidation. Machine learning algorithms for normal maturation of the microbiota and metabolome among infants with appropriate growth revealed a pattern of delayed maturation of the microbiota and metabolome among infants with growth failure. Collectively, we identified novel microbial and metabolic features of growth failure in preterm infants and potentially modifiable targets for intervention.

Aims/hypothesis: We aimed to determine the association of maternal metabolites with newborn adiposity and hyperinsulinaemia in a multi-ethnic cohort of mother-newborn dyads., Methods: Targeted and non-targeted metabolomics assays were performed on fasting and 1 h serum samples from a total of 1600 mothers in four ancestry groups (Northern European, Afro-Caribbean, Mexican American and Thai) who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, underwent an OGTT at ~28 weeks gestation and whose newborns had anthropometric measurements at birth., Results: In this observational study, meta-analyses demonstrated significant associations of maternal fasting and 1 h metabolites with birthweight, cord C-peptide and/or sum of skinfolds across ancestry groups. In particular, maternal fasting triacylglycerols were associated with newborn sum of skinfolds. At 1 h, several amino acids, fatty acids and lipid metabolites were associated with one or more newborn outcomes. Network analyses revealed clusters of fasting acylcarnitines, amino acids, lipids and fatty acid metabolites associated with cord C-peptide and sum of skinfolds, with the addition of branched-chain and aromatic amino acids at 1 h., Conclusions/interpretation: The maternal metabolome during pregnancy is associated with newborn outcomes. Maternal levels of amino acids, acylcarnitines, lipids and fatty acids and their metabolites during pregnancy relate to fetal growth, adiposity and cord C-peptide, independent of maternal BMI and blood glucose levels.

Acyl CoA metabolites derived from the catabolism of carbon fuels can react with lysine residues of mitochondrial proteins, giving rise to a large family of post-translational modifications (PTMs). Mass spectrometry-based detection of thousands of acyl-PTMs scattered throughout the proteome has established a strong link between mitochondrial hyperacylation and cardiometabolic diseases; however, the functional consequences of these modifications remain uncertain. Here, we use a comprehensive respiratory diagnostics platform to evaluate three disparate models of mitochondrial hyperacylation in the mouse heart caused by genetic deletion of malonyl CoA decarboxylase (MCD), SIRT5 demalonylase and desuccinylase, or SIRT3 deacetylase. In each case, elevated acylation is accompanied by marginal respiratory phenotypes. Of the >60 mitochondrial energy fluxes evaluated, the only outcome consistently observed across models is a ∼15% decrease in ATP synthase activity. In sum, the findings suggest that the vast majority of mitochondrial acyl PTMs occur as stochastic events that minimally affect mitochondrial bioenergetics., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Effects of species diversity on population and community stability (or more precisely, the effects of species richness on temporal variability) have been studied for several decades, but there have been no large-scale tests in natural communities of predictions from theory. We used 91 data sets including plants, fish, small mammals, zooplankton, birds, and insects, to examine the relationship between species richness and temporal variability in populations and communities. Seventy-eight of 91 data sets showed a negative relationship between species richness and population variability; 46 of these relationships were statistically significant. Only five of the 13 positive richness-population variability relationships were statistically significant. Similarly, 51 of 91 data sets showed a negative relationship between species richness and community variability; of these, 26 were statistically significant. Seven of the 40 positive richness-community-variability relationships were statistically significant. We were able to test transferability (i.e., the predictive ability of models for sites that are spatially distinct from sites that were used to build the models) for 69 of 91 data sets; 35 and 31 data sets were transferable at the population and community levels, respectively. Only four were positive at the population level, and two at the community level. We conclude that there is compelling evidence of a negative relationship between species richness and temporal variability for about one-half of the ecological communities we examined. However, species richness explained relatively little of the variability in population or community abundances and resulted in small improvements in predictive ability., (© 2018 by the Ecological Society of America.)

We previously reported how the loss of CHIP expression (Carboxyl terminus of Hsc70-Interacting Protein) during pressure overload resulted in robust cardiac dysfunction, which was accompanied by a failure to maintain ATP levels in the face of increased energy demand. In this study, we analyzed the cardiac metabolome after seven days of pressure overload and found an increase in long-chain and medium-chain fatty acid metabolites in wild-type hearts. This response was attenuated in mice that lack expression of CHIP ( CHIP -/- ). These findings suggest that CHIP may play an essential role in regulating oxidative metabolism pathways that are regulated, in part, by the nuclear receptor PPARα (Peroxisome Proliferator-Activated Receptor alpha). Next, we challenged CHIP -/- mice with the PPARα agonist called fenofibrate. We found that treating CHIP -/- mice with fenofibrate for five weeks under non-pressure overload conditions resulted in decreased skeletal muscle mass, compared to wild-type mice, and a marked increase in cardiac fibrosis accompanied by a decrease in cardiac function. Fenofibrate resulted in decreased mitochondrial cristae density in CHIP -/- hearts as well as decreased expression of genes involved in the initiation of autophagy and mitophagy, which suggests that a metabolic challenge, in the absence of CHIP expression, impacts pathways that contribute to mitochondrial quality control. In conclusion, in the absence of functional CHIP expression, fenofibrate results in unexpected skeletal muscle and cardiac pathologies. These findings are particularly relevant to patients harboring loss-of-function mutations in CHIP and are consistent with a prominent role for CHIP in regulating cardiac metabolism.

Background: There is uncertainty regarding the effect of anemia and red blood cell transfusion on functional outcome following acute ischemic stroke. We studied the relationship of hemoglobin parameters and red cell transfusion with post stroke functional outcome after adjustment for neurological severity and medical comorbidities., Methods: Retrospective cohort study of 536 patients discharged with a diagnosis of ischemic stroke from a tertiary care hospital between January 2012 and April 2015. Hemoglobin level at hospital admission, lowest recorded value during hospitalization (nadir), delta hemoglobin (admission minus nadir), red cell transfusion during hospitalization were noted. Charlson Comorbidity Index (CCI) was computed as a summary measure of medical comorbidities. A multivariable logistic regression model was used to determine risk-adjusted odds of unfavorable outcome, defined as a modified Rankin Score of > 2., Results: Anemia was present on hospital admission in 31% of patients. Forty five percent of patients had unfavorable outcome. In the univariable analysis increasing age, admission National Institutes of Health Stroke Scale (NIHSS), CCI, nadir hemoglobin, delta hemoglobin and blood transfusion were associated with unfavorable outcome. In the multivariable model, only increasing age, CCI and NIHSS remained associated with unfavorable outcome. No quadratic association was found on repeating the model to identify a possible U-shaped relationship of hemoglobin with outcome., Conclusions: Our findings contradict prior observational studies and highlight an area of clinical equipoise regarding the optimal management of anemia in patients hospitalized for ischemic stroke. This uncertainty could be addressed with appropriately designed clinical trials.

Current obesity interventions suffer from lack of durable effects and undesirable complications. Fumagillin, an inhibitor of methionine aminopeptidase-2, causes weight loss by reducing food intake, but with effects on weight that are superior to pair-feeding. Here, we show that feeding of rats on a high-fat diet supplemented with fumagillin (HF/FG) suppresses the aggressive feeding observed in pair-fed controls (HF/PF) and alters expression of circadian genes relative to the HF/PF group. Multiple indices of reduced energy expenditure are observed in HF/FG but not HF/PF rats. HF/FG rats also exhibit changes in gut hormones linked to food intake, increased energy harvest by gut microbiota, and caloric spilling in the urine. Studies in gnotobiotic mice reveal that effects of fumagillin on energy expenditure but not feeding behavior may be mediated by the gut microbiota. In sum, fumagillin engages weight loss-inducing behavioral and physiologic circuits distinct from those activated by simple caloric restriction.

At present, accurate and reliable biomarkers to ascertain the presence, severity, or prognosis of blast traumatic brain injury (bTBI) are lacking. There is an urgent need to establish accurate and reliable biomarkers capable of mbTBI detection. Currently, there are no studies that identify changes in miRNA and lipids at varied severities of bTBI. Various biological components such as lipids, circulating mRNA, and miRNA, could potentially be detected using advanced techniques such as next-generation sequencing and mass spectroscopy. Therefore, plasma analysis is an attractive approach with which to diagnose and treat brain injuries. Subacute changes in plasma microRNA (miRNA) and lipid composition for sphingolipids were evaluated in a murine model of mild-to-moderate bTBI using next-generation sequencing and mass spectroscopy respectively. Animals were exposed at 17, 17 × 3, and 20 psi blast intensities using a calibrated blast simulator. Plasma lipid profiling demonstrated decreased C18 fatty acid chains of sphingomyelins and increased ceramide levels when compared with controls. Plasma levels of brain-enriched miRNA, miR-127 were increased in all groups while let-7a, b, and g were reduced in the 17 × 3 and 20 psi groups, but let 7d was increased in the 17 psi group. The majority of the miRs and lipids are highly conserved across different species, making them attractive to explore and potentially employ as diagnostic markers. It is tempting to speculate that sphingolipids, miR-128, and the let-7 family could predict mTBI, while a combination of miR-484, miR-122, miR-148a, miR-130a, and miR-223 could be used to predict the overall status of injury following blast injury.

Bats are the second most diverse mammal order and they provide vital ecosystem functions (e.g., pollination, seed dispersal, and nutrient flux in caves) and services (e.g., crop pest suppression). Bats are also important vectors of infectious diseases, harboring more than 100 different virus types. In the present study, we compiled information on bat communities from the Atlantic Forests of South America, a species-rich biome that is highly threatened by habitat loss and fragmentation. The ATLANTIC BATS data set comprises 135 quantitative studies carried out in 205 sites, which cover most vegetation types of the tropical and subtropical Atlantic Forest: dense ombrophilous forest, mixed ombrophilous forest, semideciduous forest, deciduous forest, savanna, steppe, and open ombrophilous forest. The data set includes information on more than 90,000 captures of 98 bat species of eight families. Species richness averaged 12.1 per site, with a median value of 10 species (ranging from 1 to 53 species). Six species occurred in more than 50% of the communities: Artibeus lituratus, Carollia perspicillata, Sturnira lilium, Artibeus fimbriatus, Glossophaga soricina, and Platyrrhinus lineatus. The number of captures divided by sampling effort, a proxy for abundance, varied from 0.000001 to 0.77 individuals·h -1 ·m -2 (0.04 ± 0.007 individuals·h -1 ·m -2 ). Our data set reveals a hyper-dominance of eight species that together that comprise 80% of all captures: Platyrrhinus lineatus (2.3%), Molossus molossus (2.8%), Artibeus obscurus (3.4%), Artibeus planirostris (5.2%), Artibeus fimbriatus (7%), Sturnira lilium (14.5%), Carollia perspicillata (15.6%), and Artibeus lituratus (29.2%)., (© 2017 by the Ecological Society of America.)

Objective: We used targeted metabolomics to determine associations of maternal BMI and glucose levels with cord blood metabolites and associations of cord blood metabolites with newborn birth weight and adiposity in mother-offspring dyads., Research Design and Methods: Targeted metabolomic assays were performed on cord blood serum samples from European ancestry, Afro-Caribbean, Thai, and Mexican American newborns (400 from each ancestry group) whose mothers participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and who had anthropometric measurements at birth., Results: Meta-analysis across the four cohorts demonstrated significant correlation of all cord blood metabolites analyzed with maternal fasting levels of the same metabolites at ∼28 weeks' gestation except for triglycerides, asparagine/aspartate, arginine, and the acylcarnitine C14-OH/C12-DC. Meta-analyses also demonstrated that maternal BMI with or without adjustment for maternal glucose was associated with cord blood metabolites including the branched-chain amino acids and their metabolites as well as phenylalanine. One-hour but not fasting glucose was associated with cord blood 3-hydroxybutyrate and its carnitine ester, a medium-chain acylcarnitine, and glycerol. A number of cord blood metabolites were associated with newborn birth weight and sum of skinfolds, including a negative association of triglycerides and positive association of 3-hydroxybutyrate, its carnitine ester, and serine with both newborn outcomes., Conclusions: Maternal BMI and glycemia are associated with different components of the newborn metabolome, consistent with their independent effects on newborn size at birth. Maternal BMI is associated with a newborn metabolic signature characteristic of insulin resistance and risk of type 2 diabetes in adults., (© 2017 by the American Diabetes Association.)

Objective: We used targeted metabolomics in pregnant mothers to compare maternal metabolite associations with maternal BMI, glycemia, and insulin sensitivity., Research Design and Methods: Targeted metabolomic assays of clinical metabolites, amino acids, and acylcarnitines were performed on fasting and 1-h postglucose serum samples from European ancestry, Afro-Caribbean, Thai, and Mexican American mothers (400 from each ancestry group) who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and underwent an oral glucose tolerance test at ∼28 weeks gestation., Results: K-means clustering, which identified patterns of metabolite levels across ancestry groups, demonstrated that, at both fasting and 1-h, levels of the majority of metabolites were similar across ancestry groups. Meta-analyses demonstrated association of a broad array of fasting and 1-h metabolites, including lipids and amino acids and their metabolites, with maternal BMI, glucose levels, and insulin sensitivity before and after adjustment for the different phenotypes. At fasting and 1 h, a mix of metabolites was identified that were common across phenotypes or associated with only one or two phenotypes. Partial correlation estimates, which allowed comparison of the strength of association of different metabolites with maternal phenotypes, demonstrated that metabolites most strongly associated with different phenotypes included some that were common across as well as unique to each phenotype., Conclusions: Maternal BMI and glycemia have metabolic signatures that are both shared and unique to each phenotype. These signatures largely remain consistent across different ancestry groups and may contribute to the common and independent effects of these two phenotypes on adverse pregnancy outcomes., (© 2017 by the American Diabetes Association.)

Sirtuins are NAD + -dependent protein deacylases that regulate several aspects of metabolism and aging. In contrast to the other mammalian sirtuins, the primary enzymatic activity of mitochondrial sirtuin 4 (SIRT4) and its overall role in metabolic control have remained enigmatic. Using a combination of phylogenetics, structural biology, and enzymology, we show that SIRT4 removes three acyl moieties from lysine residues: methylglutaryl (MG)-, hydroxymethylglutaryl (HMG)-, and 3-methylglutaconyl (MGc)-lysine. The metabolites leading to these post-translational modifications are intermediates in leucine oxidation, and we show a primary role for SIRT4 in controlling this pathway in mice. Furthermore, we find that dysregulated leucine metabolism in SIRT4KO mice leads to elevated basal and stimulated insulin secretion, which progressively develops into glucose intolerance and insulin resistance. These findings identify a robust enzymatic activity for SIRT4, uncover a mechanism controlling branched-chain amino acid flux, and position SIRT4 as a crucial player maintaining insulin secretion and glucose homeostasis during aging., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The mechanisms underlying the formation of acyl protein modifications remain poorly understood. By investigating the reactivity of endogenous acyl-CoA metabolites, we found a class of acyl-CoAs that undergo intramolecular catalysis to form reactive intermediates that non-enzymatically modify proteins. Based on this mechanism, we predicted, validated, and characterized a protein modification: 3-hydroxy-3-methylglutaryl(HMG)-lysine. In a model of altered HMG-CoA metabolism, we found evidence of two additional protein modifications: 3-methylglutaconyl(MGc)-lysine and 3-methylglutaryl(MG)-lysine. Using quantitative proteomics, we compared the "acylomes" of two reactive acyl-CoA species, namely HMG-CoA and glutaryl-CoA, which are generated in different pathways. We found proteins that are uniquely modified by each reactive metabolite, as well as common proteins and pathways. We identified the tricarboxylic acid cycle as a pathway commonly regulated by acylation and validated malate dehydrogenase as a key target. These data uncover a fundamental relationship between reactive acyl-CoA species and proteins and define a new regulatory paradigm in metabolism., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Aims/hypothesis: Maternal obesity increases the risk for large-for-gestational-age birth and excess newborn adiposity, which are associated with adverse long-term metabolic outcomes in offspring, probably due to effects mediated through the intrauterine environment. We aimed to characterise the maternal metabolic milieu associated with maternal BMI and its relationship to newborn birthweight and adiposity., Methods: Fasting and 1 h serum samples were collected from 400 European-ancestry mothers in the Hyperglycaemia and Adverse Pregnancy Outcome Study who underwent an OGTT at ∼28 weeks gestation and whose offspring had anthropometric measurements at birth. Metabolomics assays were performed using biochemical analyses of conventional clinical metabolites, targeted MS-based measurement of amino acids and acylcarnitines and non-targeted GC/MS., Results: Per-metabolite analyses demonstrated broad associations with maternal BMI at fasting and 1 h for lipids, amino acids and their metabolites together with carbohydrates and organic acids. Similar metabolite classes were associated with insulin resistance with unique associations including branched-chain amino acids. Pathway analyses indicated overlapping and unique associations with maternal BMI and insulin resistance. Network analyses demonstrated collective associations of maternal metabolite subnetworks with maternal BMI and newborn size and adiposity, including communities of acylcarnitines, lipids and related metabolites, and carbohydrates and organic acids. Random forest analyses demonstrated contribution of lipids and lipid-related metabolites to the association of maternal BMI with newborn outcomes., Conclusions/interpretation: Higher maternal BMI and insulin resistance are associated with broad-based changes in maternal metabolites, with lipids and lipid-related metabolites accounting, in part, for the association of maternal BMI with newborn size at birth.

Background: Metabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based or large-scale clinical studies demands large numbers of subjects and therefore sample batching for gas-chromatography/mass spectrometry (GC/MS) non-targeted assays. When run over weeks or months, technical noise due to batch and run-order threatens data interpretability. Application of existing normalization methods to metabolomics is challenged by unsatisfied modeling assumptions and, notably, failure to address batch-specific truncation of low abundance compounds., Results: To curtail technical noise and make GC/MS metabolomics data amenable to analyses describing biologically relevant variability, we propose mixture model normalization (mixnorm) that accommodates truncated data and estimates per-metabolite batch and run-order effects using quality control samples. Mixnorm outperforms other approaches across many metrics, including improved correlation of non-targeted and targeted measurements and superior performance when metabolite detectability varies according to batch. For some metrics, particularly when truncation is less frequent for a metabolite, mean centering and median scaling demonstrate comparable performance to mixnorm., Conclusions: When quality control samples are systematically included in batches, mixnorm is uniquely suited to normalizing non-targeted GC/MS metabolomics data due to explicit accommodation of batch effects, run order and varying thresholds of detectability. Especially in large-scale studies, normalization is crucial for drawing accurate conclusions from non-targeted GC/MS metabolomics data.