Many functional network properties of the human brain have been identified during rest and task states, yet it remains unclear how the two relate. We identified a whole-brain network architecture ...present across dozens of task states that was highly similar to the resting-state network architecture. The most frequent functional connectivity strengths across tasks closely matched the strengths observed at rest, suggesting this is an “intrinsic,” standard architecture of functional brain organization. Furthermore, a set of small but consistent changes common across tasks suggests the existence of a task-general network architecture distinguishing task states from rest. These results indicate the brain’s functional network architecture during task performance is shaped primarily by an intrinsic network architecture that is also present during rest, and secondarily by evoked task-general and task-specific network changes. This establishes a strong relationship between resting-state functional connectivity and task-evoked functional connectivity—areas of neuroscientific inquiry typically considered separately.
•There is an “intrinsic” functional network architecture present across many tasks•The intrinsic architecture is highly similar to the resting-state architecture•Tasks modify the intrinsic architecture to produce “evoked” network architectures•Task-evoked changes common across tasks form a task-general network architecture
Cole et al. identify a whole-brain functional network architecture in humans that is intrinsic, as it is present across rest and dozens of tasks. Only small network modifications were observed, but many were consistent, composing a task-general evoked network architecture.
Administration of intravenous crystalloid solutions is a fundamental therapy for sepsis, but the effect of crystalloid composition on patient outcomes remains unknown.
To compare the effect of ...balanced crystalloids versus saline on 30-day in-hospital mortality among critically ill adults with sepsis.
Secondary analysis of patients from SMART (Isotonic Solutions and Major Adverse Renal Events Trial) admitted to the medical ICU with an
code for sepsis, using multivariable regression to control for potential confounders.
Of 15,802 patients enrolled in SMART, 1,641 patients were admitted to the medical ICU with a diagnosis of sepsis. A total of 217 patients (26.3%) in the balanced crystalloids group experienced 30-day in-hospital morality compared with 255 patients (31.2%) in the saline group (adjusted odds ratio aOR, 0.74; 95% confidence interval CI, 0.59-0.93;
= 0.01). Patients in the balanced group experienced a lower incidence of major adverse kidney events within 30 days (35.4% vs. 40.1%; aOR, 0.78; 95% CI, 0.63-0.97) and a greater number of vasopressor-free days (20 ± 12 vs. 19 ± 13; aOR, 1.25; 95% CI, 1.02-1.54) and renal replacement therapy-free days (20 ± 12 vs. 19 ± 13; aOR, 1.35; 95% CI, 1.08-1.69) compared with the saline group.
Among patients with sepsis in a large randomized trial, use of balanced crystalloids was associated with a lower 30-day in-hospital mortality compared with use of saline.Clinical trial registered with www.clinicaltrials.gov (NCT02444988).
Summary Background The Foundation for the National Institutes of Health Sarcopenia Project validated cutpoints for appendicular lean mass (ALM) to identify individuals at risk for functional ...impairment. Recognizing possible underlying mechanisms between adipose tissue and muscle, we sought to apply the recent definitions and determine the relationship with markers of glucose homeostasis and inflammation in individuals with sarcopenia and sarcopenic obesity. Methods The National Health and Nutrition Examination Surveys 1999-2004 were used to identify 4,984 adults aged ≥60 years with DEXA measures. Sarcopenia was defined using ALM (men<19.75 kg, women<15.02 kg) and ALM adjusted for body mass index (BMI; men<0.789 kg/m2 , women<0.512 kg/m2 ). Sarcopenic obesity was defined as subjects fulfilling the criteria for sarcopenia and obesity by body fat (men ≥25%, women ≥35%). We assessed the association between ALM and ALM:BMI with inflammatory and markers of glucose homestasis, both as continuous variables but also classifying as having sarcopenic obesity or not after adjusting for confounding variables including pro-inflammatory chronic diseases such as diabetes and cancer. Results Mean age was 71.1 years (56.5%) females. Prevalence of sarcopenia and sarcopenic obesity were (ALM definition: 29.9 and 24.4%; ALM:BMI definition: 23.0 and 22.7%). There were significant associations with ALM and ln C-reactive protein (β=0.0287;p=0.001), fibrinogen (β=0.519;p<0.001), and HOMA-IR (β=0.359;p<0.001). Using ALM:BMI, significant associations were observed with ln CRP (β=-2.58;p=0.001), fibrinogen (β=-124.2;p<0.001), and HOMA-IR (β=-6.63;p<0.001). Sarcopenic obesity using the ALM:BMI definition demonstrated significant associations with CRP (β=0.422;p<0.001), fibrinogen (β=22.5;p<0.001), but not HOMA-IR (β=1.19;p=0.13). Strong associations with seen with increased levels of fibrinogen and CRP with sarcopenic obesity (ALM:BMI definition) that persisted after adjusting for diabetes and cancer. Conclusions Biologically plausible associations exist between ALM:BMI and inflammation and HOMA-IR that were not observed when using ALM alone. Future study should validate each of these definitions to prevent disparate results from being determined.
In this cluster-randomized, multiple-crossover trial conducted in 5 ICUs, intravenous administration of balanced crystalloids resulted in a lower rate of the composite outcome — death from any cause, ...new renal-replacement therapy, or persistent renal dysfunction — than saline.
•A publicly available deep learning tool to segment the hypothalamus and its subunits.•Our tool outperforms inter-rater accuracy and approaches intra-rater precision level.•It can robustly generalise ...to unseen heterogeneous datasets.•It yields a rejection rate of less than 1% in a QC analysis performed on 675 scans.•It detects subtle subunit-specific hypothalamic atrophy in Alzheimer’s Disease.
Despite the crucial role of the hypothalamus in the regulation of the human body, neuroimaging studies of this structure and its nuclei are scarce. Such scarcity partially stems from the lack of automated segmentation tools, since manual delineation suffers from scalability and reproducibility issues. Due to the small size of the hypothalamus and the lack of image contrast in its vicinity, automated segmentation is difficult and has been long neglected by widespread neuroimaging packages like FreeSurfer or FSL. Nonetheless, recent advances in deep machine learning are enabling us to tackle difficult segmentation problems with high accuracy. In this paper we present a fully automated tool based on a deep convolutional neural network, for the segmentation of the whole hypothalamus and its subregions from T1-weighted MRI scans. We use aggressive data augmentation in order to make the model robust to T1-weighted MR scans from a wide array of different sources, without any need for preprocessing. We rigorously assess the performance of the presented tool through extensive analyses, including: inter- and intra-rater variability experiments between human observers; comparison of our tool with manual segmentation; comparison with an automated method based on multi-atlas segmentation; assessment of robustness by quality control analysis of a larger, heterogeneous dataset (ADNI); and indirect evaluation with a volumetric study performed on ADNI. The presented model outperforms multi-atlas segmentation scores as well as inter-rater accuracy level, and approaches intra-rater precision. Our method does not require any preprocessing and runs in less than a second on a GPU, and approximately 10 seconds on a CPU. The source code as well as the trained model are publicly available at https://github.com/BBillot/hypothalamus_seg, and will also be distributed with FreeSurfer.
Extensive evidence suggests that the human ability to adaptively implement a wide variety of tasks is preferentially a result of the operation of a fronto-parietal brain network (FPN). We ...hypothesized that this network's adaptability is made possible by flexible hubs: brain regions that rapidly update their pattern of global functional connectivity according to task demands. Using recent advances in characterizing brain network organization and dynamics, we identified mechanisms consistent with the flexible hub theory. We found that the FPN's brain-wide functional connectivity pattern shifted more than those of other networks across a variety of task states and that these connectivity patterns could be used to identify the current task. Furthermore, these patterns were consistent across practiced and novel tasks, suggesting that reuse of flexible hub connectivity patterns facilitates adaptive (novel) task performance. Together, these findings support a central role for fronto-parietal flexible hubs in cognitive control and adaptive implementation of task demands.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Multivariate pattern analysis (MVPA) is a relatively recent innovation in functional magnetic resonance imaging (fMRI) methods. MVPA is increasingly widely used, as it is apparently more effective ...than classical general linear model analysis (GLMA) for detecting response patterns or representations that are distributed at a fine spatial scale. However, we demonstrate that widely used approaches to MVPA can systematically admit certain confounds that are appropriately eliminated by GLMA. Thus confounds rather than distributed representations may explain some cases in which MVPA produced positive results but GLMA did not. The issue is that it is common practice in MVPA to conduct group tests on single-subject summary statistics that discard the sign or direction of underlying effects, whereas GLMA group tests are conducted directly on single-subject effects themselves. We describe how this common MVPA practice undermines standard experiment design logic that is intended to control at the group level for certain types of confounds, such as time on task and individual differences. Furthermore, we note that a simple application of linear regression can restore experimental control when using MVPA in many situations. Finally, we present a case study with novel fMRI data in the domain of rule representations, or flexible stimulus–response mappings, which has seen several recent MVPA publications. In our new dataset, as with recent reports, standard MVPA appears to reveal rule representations in prefrontal cortex regions, whereas GLMA produces null results. However, controlling for a variable that is confounded with rule at the individual-subject level but not the group level (reaction time differences across rules) eliminates the MVPA results. This raises the question of whether recently reported results truly reflect rule representations, or rather the effects of confounds such as reaction time, difficulty, or other variables of no interest.
•MVPA admits confounds that are controlled by classical GLM analysis.•MVPA-specific confounds can be controlled post hoc using linear regression.•Confound and control are demonstrated with theoretical simulations.•Confound and control are demonstrated with a “rule representation” case study.•Implications are discussed for existing MVPA results.
The ability to act on the world with the goal of gaining information is core to human adaptability and intelligence. Perhaps the most successful and influential account of such abilities is the ...Optimal Experiment Design (OED) hypothesis, which argues that humans intuitively perform experiments on the world similar to the way an effective scientist plans an experiment. The widespread application of this theory within many areas of psychology calls for a critical evaluation of the theory’s core claims. Despite many successes, we argue that the OED hypothesis remains lacking as a theory of human inquiry and that research in the area often fails to confront some of the most interesting and important questions. In this critical review, we raise and discuss nine open questions about the psychology of human inquiry.
Correct daily phasing of transcription confers an adaptive advantage to almost all organisms, including higher plants. In this study, we describe a hypothesis-driven network discovery pipeline that ...identifies biologically relevant patterns in genome-scale data. To demonstrate its utility, we analyzed a comprehensive matrix of time courses interrogating the nuclear transcriptome of Arabidopsis thaliana plants grown under different thermocycles, photocycles, and circadian conditions. We show that 89% of Arabidopsis transcripts cycle in at least one condition and that most genes have peak expression at a particular time of day, which shifts depending on the environment. Thermocycles alone can drive at least half of all transcripts critical for synchronizing internal processes such as cell cycle and protein synthesis. We identified at least three distinct transcription modules controlling phase-specific expression, including a new midnight specific module, PBX/TBX/SBX. We validated the network discovery pipeline, as well as the midnight specific module, by demonstrating that the PBX element was sufficient to drive diurnal and circadian condition-dependent expression. Moreover, we show that the three transcription modules are conserved across Arabidopsis, poplar, and rice. These results confirm the complex interplay between thermocycles, photocycles, and the circadian clock on the daily transcription program, and provide a comprehensive view of the conserved genomic targets for a transcriptional network key to successful adaptation.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Tirzepatide (LY3298176) is a dual GIP and GLP-1 receptor agonist under development for the treatment of type 2 diabetes mellitus (T2DM), obesity, and nonalcoholic steatohepatitis. Early phase trials ...in T2DM indicate that tirzepatide improves clinical outcomes beyond those achieved by a selective GLP-1 receptor agonist. Therefore, we hypothesized that the integrated potency and signaling properties of tirzepatide provide a unique pharmacological profile tailored for improving broad metabolic control. Here, we establish methodology for calculating occupancy of each receptor for clinically efficacious doses of the drug. This analysis reveals a greater degree of engagement of tirzepatide for the GIP receptor than the GLP-1 receptor, corroborating an imbalanced mechanism of action. Pharmacologically, signaling studies demonstrate that tirzepatide mimics the actions of native GIP at the GIP receptor but shows bias at the GLP-1 receptor to favor cAMP generation over β-arrestin recruitment, coincident with a weaker ability to drive GLP-1 receptor internalization compared with GLP-1. Experiments in primary islets reveal β-arrestin1 limits the insulin response to GLP-1, but not GIP or tirzepatide, suggesting that the biased agonism of tirzepatide enhances insulin secretion. Imbalance toward GIP receptor, combined with distinct signaling properties at the GLP-1 receptor, together may account for the promising efficacy of this investigational agent.
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