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The description and delineation of trematode species is a major ongoing task. Across the field there has been, and currently still is, great variation in the standard of this work and in the sophistication of the proposal of taxonomic hypotheses. Although most species are relatively unambiguously distinct from their congeners, many are either morphologically very similar, including the major and rapidly growing component of cryptic species, or are highly variable morphologically despite little to no molecular variation for standard DNA markers. Here we review challenges in species delineation in the context provided to us by the historical literature, and the use of morphological, geographical, host, and molecular data. We observe that there are potential challenges associated with all these information sources. As a result, we encourage careful proposal of taxonomic hypotheses with consideration for underlying species concepts and frank acknowledgement of weaknesses or conflict in the data. It seems clear that there is no single source of data that provides a wholly reliable answer to our taxonomic challenges but that nuanced consideration of information from multiple sources (the ‘integrated approach’) provides the best possibility of developing hypotheses that will stand the test of time.
Medical and surgical advancements have enabled a 95% survival rate for children with CHD. However, these survivors are disproportionately affected by neurodevelopmental disabilities. In particular, they have behavioural problems in toddlerhood. Because there is a known relationship between behavioural problems and early language delay, we hypothesise that children with critical CHD have early detectable language deficits. To test our hypothesis, we performed a retrospective study on a cohort of children with critical CHD to visualise their early language developmental trajectories.
Methods:
We identified a cohort of 27 children with two diagnoses: single ventricle physiology (19) and transposition of the great arteries (8). As part of their routine clinical care, all of these children had serial developmental evaluations with the language subsection of the Capute Scales. We visualised their developmental language trajectories as a function of chronologic age, and we used a univariate linear regression model to calculate diagnosis-specific expected developmental age equivalents.
Results:
In each group, language development is age-appropriate in infancy. Deviation from age-appropriate development is apparent by 18 months. This results in borderline-mild language delay by 30 months.
Discussion:
Using the Capute Scales, our team quantified early language development in infants and toddlers with critical CHD. Our identification of deceleration in skill acquisition reinforces the call for ongoing neurodevelopmental surveillance in these children. Understanding early language development will help clinicians provide informed anticipatory guidance to families of children with critical CHD.
Social Media Synopsis:
Children with single ventricle physiology and transposition of the great arteries have measurable early language delays.
To quantify the impact of patient- and unit-level risk adjustment on infant hospital-onset bacteremia (HOB) standardized infection ratio (SIR) ranking.
Design:
A retrospective, multicenter cohort study.
Setting and participants:
Infants admitted to 284 neonatal intensive care units (NICUs) in the United States between 2016 and 2021.
Methods:
Expected HOB rates and SIRs were calculated using four adjustment strategies: birthweight (model 1), birthweight and postnatal age (model 2), birthweight and NICU complexity (model 3), and birthweight, postnatal age, and NICU complexity (model 4). Sites were ranked according to the unadjusted HOB rate, and these rankings were compared to rankings based on the four adjusted SIR models.
Results:
Compared to unadjusted HOB rate ranking (smallest to largest), the number and proportion of NICUs that left the fourth quartile (worst-performing) following adjustments were as follows: adjusted for birthweight (16, 22.5%), birthweight and postnatal age (19, 26.8%), birthweight and NICU complexity (22, 31.0%), birthweight, postnatal age and NICU complexity (23, 32.4%). Comparing NICUs that moved into the better-performing quartiles after birthweight adjustment to those that remained in the better-performing quartiles regardless of adjustment, the median percentage of low birthweight infants was 17.1% (Interquartile Range (IQR): 15.8, 19.2) vs 8.7% (IQR: 4.8, 12.6); and the median percentage of infants who died was 2.2% (IQR: 1.8, 3.1) vs 0.5% (IQR: 0.01, 12.0), respectively.
Conclusion:
Adjusting for patient and unit-level complexity moved one-third of NICUs in the worst-performing quartile into a better-performing quartile. Risk adjustment may allow for a more accurate comparison across units with varying levels of patient acuity and complexity.
Techniques for partitioning objects into optimally homogeneous groups on the basis of empirical measures of similarity among those objects have received increasing attention in several different fields. This paper develops a useful correspondence between any hierarchical system of such clusters, and a particular type of distance measure. The correspondence gives rise to two methods of clustering that are computationally rapid and invariant under monotonic transformations of the data. In an explicitly defined sense, one method forms clusters that are optimally “connected,” while the other forms clusters that are optimally “compact.”
The conventional method of measuring ability, which is based on items with assumed true parameter values obtained from a pretest, is compared to a Bayesian method that deals with the uncertainties of such items. Computational expressions are presented for approximating the posterior mean and variance of ability under the three-parameter logistic (3PL) model. A 1987 American College Testing Program (ACT) math test is used to demonstrate that the standard practice of using maximum likelihood or empirical Bayes techniques may seriously underestimate the uncertainty in estimated ability when the pretest sample is only moderately large.
The theoretical basis for the Johnson-Neyman Technique is here presented for the first time in an American journal. In addition, a simplified working procedure is outlined, step-by-step, for an actual problem. The determination of significance is arrived at early in the analysis; and where no significant difference is found, the problem is complete at this point. The plotting of the region of significance where a significant difference does exist has also been simplified by using the procedure of rotation and translation of axes.
The global population and status of Snowy Owls Bubo scandiacus are particularly challenging to assess because individuals are irruptive and nomadic, and the breeding range is restricted to the remote circumpolar Arctic tundra. The International Union for Conservation of Nature (IUCN) uplisted the Snowy Owl to “Vulnerable” in 2017 because the suggested population estimates appeared considerably lower than historical estimates, and it recommended actions to clarify the population size, structure, and trends. Here we present a broad review and status assessment, an effort led by the International Snowy Owl Working Group (ISOWG) and researchers from around the world, to estimate population trends and the current global status of the Snowy Owl. We use long-term breeding data, genetic studies, satellite-GPS tracking, and survival estimates to assess current population trends at several monitoring sites in the Arctic and we review the ecology and threats throughout the Snowy Owl range. An assessment of the available data suggests that current estimates of a worldwide population of 14,000–28,000 breeding adults are plausible. Our assessment of population trends at five long-term monitoring sites suggests that breeding populations of Snowy Owls in the Arctic have decreased by more than 30% over the past three generations and the species should continue to be categorised as Vulnerable under the IUCN Red List Criterion A2. We offer research recommendations to improve our understanding of Snowy Owl biology and future population assessments in a changing world.
To understand healthcare workers’ (HCWs) beliefs and practices toward blood culture (BCx) use.
Design:
Cross-sectional electronic survey and semi-structured interviews.
Setting:
Academic hospitals in the United States.
Participants:
HCWs involved in BCx ordering and collection in adult intensive care units (ICU) and wards.
Methods:
We administered an anonymous electronic survey to HCWs and conducted semi-structured interviews with unit staff and quality improvement (QI) leaders in these institutions to understand their perspectives regarding BCx stewardship between February and November 2023.
Results:
Of 314 HCWs who responded to the survey, most (67.4%) were physicians and were involved in BCx ordering (82.3%). Most survey respondents reported that clinicians had a low threshold to culture patients for fever (84.4%) and agreed they could safely reduce the number of BCx obtained in their units (65%). However, only half of them believed BCx was overused. Although most made BCx decisions as a team (74.1%), a minority reported these team discussions occurred daily (42.4%). A third of respondents reported not usually collecting the correct volume per BCx bottle, half were unaware of the improved sensitivity of 2 BCx sets, and most were unsure of the nationally recommended BCx contamination threshold (87.5%). Knowledge regarding the utility of BCx for common infections was limited.
Conclusions:
HCWs’ understanding of best collection practices and yield of BCx was limited.
The association between cannabis and psychosis is established, but the role of underlying genetics is unclear. We used data from the EU-GEI case-control study and UK Biobank to examine the independent and combined effect of heavy cannabis use and schizophrenia polygenic risk score (PRS) on risk for psychosis.
Methods
Genome-wide association study summary statistics from the Psychiatric Genomics Consortium and the Genomic Psychiatry Cohort were used to calculate schizophrenia and cannabis use disorder (CUD) PRS for 1098 participants from the EU-GEI study and 143600 from the UK Biobank. Both datasets had information on cannabis use.
Results
In both samples, schizophrenia PRS and cannabis use independently increased risk of psychosis. Schizophrenia PRS was not associated with patterns of cannabis use in the EU-GEI cases or controls or UK Biobank cases. It was associated with lifetime and daily cannabis use among UK Biobank participants without psychosis, but the effect was substantially reduced when CUD PRS was included in the model. In the EU-GEI sample, regular users of high-potency cannabis had the highest odds of being a case independently of schizophrenia PRS (OR daily use high-potency cannabis adjusted for PRS = 5.09, 95% CI 3.08–8.43, p = 3.21 × 10−10). We found no evidence of interaction between schizophrenia PRS and patterns of cannabis use.
Conclusions
Regular use of high-potency cannabis remains a strong predictor of psychotic disorder independently of schizophrenia PRS, which does not seem to be associated with heavy cannabis use. These are important findings at a time of increasing use and potency of cannabis worldwide.
Past studies indicate daily increases in estrogen across the menstrual cycle protect against binge-eating (BE) phenotypes (e.g. emotional eating), whereas increases in progesterone enhance risk. Two previous studies from our laboratory suggest these associations could be due to differential genomic effects of estrogen and progesterone. However, these prior studies were unable to directly model effects of daily changes in hormones on etiologic risk, instead relying on menstrual cycle phase or mean hormone levels. The current study used newly modified twin models to examine, for the first time, the effects of daily changes in estradiol and progesterone on genetic/environmental influences on emotional eating in our archival twin sample assessed across 45 consecutive days.
Methods
Participants included 468 female twins from the Michigan State University Twin Registry. Daily emotional eating was assessed with the Dutch Eating Behavior Questionnaire, and daily saliva samples were assayed for ovarian hormone levels. Modified genotype × environment interaction models examined daily changes in genetic/environmental effects across hormone levels.
Results
Findings revealed differential effects of daily changes in hormones on etiologic risk, with increasing genetic influences across progesterone levels, and increasing shared environmental influences at the highest estradiol levels. Results were consistent across primary analyses examining all study days and sensitivity analyses within menstrual cycle phases.
Conclusions
Findings are significant in being the first to identify changes in etiologic risk for BE symptoms across daily hormone levels and highlighting novel mechanisms (e.g. hormone threshold effects, regulation of conserved genes) that may contribute to the etiology of BE.
The gut microbiome is impacted by certain types of dietary fibre. However, the type, duration and dose needed to elicit gut microbial changes and whether these changes also influence microbial metabolites remain unclear. This study investigated the effects of supplementing healthy participants with two types of non-digestible carbohydrates (resistant starch (RS) and polydextrose (PD)) on the stool microbiota and microbial metabolite concentrations in plasma, stool and urine, as secondary outcomes in the Dietary Intervention Stem Cells and Colorectal Cancer (DISC) Study. The DISC study was a double-blind, randomised controlled trial that supplemented healthy participants with RS and/or PD or placebo for 50 d in a 2 × 2 factorial design. DNA was extracted from stool samples collected pre- and post-intervention, and V4 16S rRNA gene sequencing was used to profile the gut microbiota. Metabolite concentrations were measured in stool, plasma and urine by high-performance liquid chromatography. A total of fifty-eight participants with paired samples available were included. After 50 d, no effects of RS or PD were detected on composition of the gut microbiota diversity (alpha- and beta-diversity), on genus relative abundance or on metabolite concentrations. However, Drichlet’s multinomial mixture clustering-based approach suggests that some participants changed microbial enterotype post-intervention. The gut microbiota and fecal, plasma and urinary microbial metabolites were stable in response to a 50-d fibre intervention in middle-aged adults. Larger and longer studies, including those which explore the effects of specific fibre sub-types, may be required to determine the relationships between fibre intake, the gut microbiome and host health.
Educational attainment (EduA) is correlated with life outcomes, and EduA itself is influenced by both cognitive and non-cognitive factors. A recent study performed a ‘genome-wide association study (GWAS) by subtraction,’ subtracting genetic effects for cognitive performance from an educational attainment GWAS to create orthogonal ‘cognitive’ and ‘non-cognitive’ factors. These cognitive and non-cognitive factors showed associations with behavioral health outcomes in adults; however, whether these correlations are present during childhood is unclear.
Methods
Using data from up to 5517 youth (ages 9–11) of European ancestry from the ongoing Adolescent Brain Cognitive DevelopmentSM Study, we examined associations between polygenic scores (PGS) for cognitive and non-cognitive factors and cognition, risk tolerance, decision-making & personality, substance initiation, psychopathology, and brain structure (e.g. volume, fractional anisotropy [FA]). Within-sibling analyses estimated whether observed genetic associations may be consistent with direct genetic effects.
Results
Both PGSs were associated with greater cognition and lower impulsivity, drive, and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk tolerance, increased odds of choosing delayed reward, and decreased likelihood of ADHD and bipolar disorder; the non-cognitive PGS was associated with lack of perseverance and reward responsiveness. Cognitive PGS were more strongly associated with larger regional cortical volumes; non-cognitive PGS were more strongly associated with higher FA. All associations were characterized by small effects.
Conclusions
While the small sizes of these associations suggest that they are not effective for prediction within individuals, cognitive and non-cognitive PGS show unique associations with phenotypes in childhood at the population level.
The retrieval of sea ice thickness using L-band passive remote sensing requires robust models for emission from sea ice. In this work, measurements obtained from surface-based radiometers during the MOSAiC expedition are assessed with the Burke, Wilheit and SMRT radiative transfer models. These models encompass distinct methodologies: radiative transfer with/without wave coherence effects, and with/without scattering. Before running these emission models, the sea ice growth is simulated using the Cumulative Freezing Degree Days (CFDD) model to further compute the evolution of the ice structure during each period. Ice coring profiles done near the instruments are used to obtain the initial state of the computation, along with Digital Thermistor Chain (DTC) data to derive the sea ice temperature during the analyzed periods. The results suggest that the coherent approach used in the Wilheit model results in a better agreement with the horizontal polarization of the in situ measured brightness temperature. The Burke and SMRT incoherent models offer a more robust fit for the vertical component. These models are almost equivalent since the scattering considered in SMRT can be safely neglected at this low frequency, but the Burke model misses an important contribution from the snow layer above sea ice. The results also suggest that a more realistic permittivity falls between the spheres and random needles formulations, with potential for refinement, particularly for L-band applications, through future field measurements.
Metabolite supplementation during in vitro embryo development improves blastocyst quality, however, our understanding of the incorporation of metabolites during in vitro maturation (IVM) is limited. Two important metabolites, follistatin and choline, have beneficial impacts during in vitro culture; however, effects of supplementation during IVM are unknown. The objective of this study was to investigate combining choline and follistatin during IVM on bovine oocytes and subsequent early embryonic development. We hypothesized that supplementation of choline with follistatin would synergistically improve oocyte quality and subsequent early embryonic development. Small follicles were aspirated from slaughterhouse ovaries to obtain cumulus oocyte complexes for IVM with choline (0, 1.3 or 1.8 mM) and follistatin (0 or 10 ng/mL) supplementation in a 3 × 2 design. A subset of oocytes underwent transcriptomic analysis, the remaining oocytes were used for IVF and in vitro culture (IVC). Transcript abundance of CEPT1 tended to be reduced in oocytes supplemented with 1.8 mM choline and follistatin compared to control oocytes (P = 0.07). Combination of follistatin with 1.8 mM choline supplementation during maturation, tended (P = 0.08) to reduce CPEB4 in oocytes. In the blastocysts, HDCA8, NANOG, SAV1 and SOX2 were increased with choline 1.8 mM supplementation without follistatin (P < 0.05), while HDCA8 and SOX2 were increased when follistatin was incorporated (P < 0.05). The combination of choline and follistatin during oocyte maturation may provide a beneficial impact on early embryonic development. Further research is warranted to investigate the interaction between these two metabolites during early embryonic development and long-term influence on fetal development.
Major depressive disorder (MDD) is a tremendous global disease burden and the leading cause of disability worldwide. Unfortunately, individuals diagnosed with MDD typically experience a delayed response to traditional antidepressants and many do not adequately respond to pharmacotherapy, even after multiple trials. The critical need for novel antidepressant treatments has led to a recent resurgence in the clinical application of psychedelics, and intravenous ketamine, which has been investigated as a rapid-acting treatment for treatment resistant depression (TRD) as well acute suicidal ideation and behavior. However, variations in the type and quality of experimental design as well as a range of treatment outcomes in clinical trials of ketamine make interpretation of this large body of literature challenging.
Objectives
This umbrella review aims to advance our understanding of the effectiveness of intravenous ketamine as a pharmacotherapy for TRD by providing a systematic, quantitative, large-scale synthesis of the empirical literature.
Methods
We performed a comprehensive PubMed search for peer-reviewed meta-analyses of primary studies of intravenous ketamine used in the treatment of TRD. Meta-analysis and primary studies were then screened by two independent coding teams according to pre-established inclusion criteria as well as PRISMA and METRICS guidelines. We then employed metaumbrella, a statistical package developed in R, to perform effect size calculations and conversions as well as statistical tests.
Results
In a large-scale analysis of 1,182 participants across 51 primary studies, repeated-dose administration of intravenous ketamine demonstrated statistically significant effects (p<0.05) compared to placebo-controlled as well as other experimental conditions in patients with TRD, as measured by standardized clinician-administered and self-report depression symptom severity scales.
Conclusions
This study provides large-scale, quantitative support for the effectiveness of intravenous, repeated-dose ketamine as a therapy for TRD and a report of the relative effectiveness of several treatment parameters across a large and rapidly growing literature. Future investigations should use similar analytic tools to examine evidence-stratified conditions and the comparative effectiveness of other routes of administration and treatment schedules as well as the moderating influence of other clinical and demographic variables on the effectiveness of ketamine on TRD and suicidal ideation and behavior.
There has been rapidly growing interest in understanding the pharmaceutical and clinical properties of psychedelic and dissociative drugs, with a particular focus on ketamine. This compound, long known for its anesthetic and dissociative properties, has garnered attention due to its potential to rapidly alleviate symptoms of depression, especially in individuals with treatment-resistant depression (TRD) or acute suicidal ideation or behavior. However, while ketamine’s psychopharmacological effects are increasingly well-documented, the specific patterns of its neural impact remain a subject of exploration and basic questions remain about its effects on functional activation in both clinical and healthy populations.
Objectives
This meta-analysis seeks to contribute to the evolving landscape of neuroscience research on dissociative drugs such as ketamine by comprehensively examining the effects of acute ketamine administration on neural activation, as measured by functional magnetic resonance imaging (fMRI), in healthy participants.
Methods
We conducted a meta-analysis of existing fMRI activation studies of ketamine using multilevel kernel density analysis (MKDA). Following a comprehensive PubMed search, we quantitatively synthesized all published primary fMRI whole-brain activation studies of the effects of ketamine in healthy subjects with no overlapping samples (N=18). This approach also incorporated ensemble thresholding (α=0.05-0.0001) to minimize cluster-size detection bias and Monte Carlo simulations to correct for multiple comparisons.
Results
Our meta-analysis revealed statistically significant (p<0.05-0.0001; FWE-corrected) alterations in neural activation in multiple cortical and subcortical regions following the administration of ketamine to healthy participants (N=306).
Conclusions
These results offer valuable insights into the functional neuroanatomical effects caused by acute ketamine administration. These findings may also inform development of therapeutic applications of ketamine for various psychiatric and neurological conditions. Future studies should investigate the neural effects of ketamine administration, including both short-term and long-term effects, in clinical populations and their relation to clinical and functional improvements.
Bipolar I disorder (BD-I) is a chronic and recurrent mood disorder characterized by alternating episodes of depression and mania; it is also associated with substantial morbidity and mortality and with clinically significant functional impairments. While previous studies have used functional magnetic resonance imaging (fMRI) to examine neural abnormalities associated with BD-I, they have yielded mixed findings, perhaps due to differences in sampling and experimental design, including highly variable mood states at the time of scan.
Objectives
The purpose of this study is to advance our understanding of the neural basis of BD-I and mania, as measured by fMRI activation studies, and to inform the development of more effective brain-based diagnostic systems and clinical treatments.
Methods
We conducted a large-scale meta-analysis of whole-brain fMRI activation studies that compared participants with BD-I, assessed during a manic episode, to age-matched healthy controls. Following PRISMA guidelines, we conducted a comprehensive PubMed literature search using two independent coding teams to evaluate primary studies according to pre-established inclusion criteria. We then used multilevel kernel density analysis (MKDA), a well-established, voxel-wise, whole-brain, meta-analytic approach, to quantitatively synthesize all qualifying primary fMRI activation studies of mania. We used ensemble thresholding (p<0.05-0.0001) to minimize cluster size detection bias, and 10,000 Monte Carlo simulations to correct for multiple comparisons.
Results
We found that participants with BD-I (N=2,042), during an active episode of mania and relative to age-matched healthy controls (N=1,764), exhibit a pattern of significantly (p<0.05-0.0001; FWE-corrected) different activation in multiple brain regions of the cerebral cortex and basal ganglia across a variety of experimental tasks.
Conclusions
This study supports the formulation of a robust neural basis for BD-I during manic episodes and advances our understanding of the pattern of abnormal activation in this disorder. These results may inform the development of novel brain-based clinical tools for bipolar disorder such as diagnostic biomarkers, non-invasive brain stimulation, and treatment-matching protocols. Future studies should compare the neural signatures of BD-I to other related disorders to facilitate the development of protocols for differential diagnosis and improve treatment outcomes in patients with BD-I.
Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent psychiatric condition that frequently originates in early development and is associated with a variety of functional impairments. Despite a large functional neuroimaging literature on ADHD, our understanding of the neural basis of this disorder remains limited, and existing primary studies on the topic include somewhat divergent results.
Objectives
The present meta-analysis aims to advance our understanding of the neural basis of ADHD by identifying the most statistically robust patterns of abnormal neural activation throughout the whole-brain in individuals diagnosed with ADHD compared to age-matched healthy controls.
Methods
We conducted a meta-analysis of task-based functional magnetic resonance imaging (fMRI) activation studies of ADHD. This included, according to PRISMA guidelines, a comprehensive PubMed search and predetermined inclusion criteria as well as two independent coding teams who evaluated studies and included all task-based, whole-brain, fMRI activation studies that compared participants diagnosed with ADHD to age-matched healthy controls. We then performed multilevel kernel density analysis (MKDA) a well-established, whole-brain, voxelwise approach that quantitatively combines existing primary fMRI studies, with ensemble thresholding (p<0.05-0.0001) and multiple comparisons correction.
Results
Participants diagnosed with ADHD (N=1,550), relative to age-matched healthy controls (N=1,340), exhibited statistically significant (p<0.05-0.0001; FWE-corrected) patterns of abnormal activation in multiple brains of the cerebral cortex and basal ganglia across a variety of cognitive control tasks.
Conclusions
This study advances our understanding of the neural basis of ADHD and may aid in the development of new brain-based clinical interventions as well as diagnostic tools and treatment matching protocols for patients with ADHD. Future studies should also investigate the similarities and differences in neural signatures between ADHD and other highly comorbid psychiatric disorders.