The Genetics of Aging: A Vertebrate Perspective.

Aging negatively impacts vitality and health. Many genetic pathways that regulate aging were discovered in invertebrates. However, the genetics of aging is more complex in vertebrates because of their specialized systems. This Review discusses advances in the genetic regulation of aging in vertebrates from work in mice, humans, and organisms with exceptional lifespans. We highlight challenges for the future, including sex-dependent differences in lifespan and the interplay between genes and environment. We also discuss how the identification of reliable biomarkers of age and development of new vertebrate models can be leveraged for personalized interventions to counter aging and age-related diseases.

Network modeling of dynamic brain interactions predicts emergence of neural information that supports human cognitive behavior.

How cognitive task behavior is generated by brain network interactions is a central question in neuroscience. Answering this question calls for the development of novel analysis tools that can firstly capture neural signatures of task information with high spatial and temporal precision (the "where and when") and then allow for empirical testing of alternative network models of brain function that link information to behavior (the "how"). We outline a novel network modeling approach suited to this purpose that is applied to noninvasive functional neuroimaging data in humans. We first dynamically decoded the spatiotemporal signatures of task information in the human brain by combining MRI-individualized source electroencephalography (EEG) with multivariate pattern analysis (MVPA). A newly developed network modeling approach-dynamic activity flow modeling-then simulated the flow of task-evoked activity over more causally interpretable (relative to standard functional connectivity [FC] approaches) resting-state functional connections (dynamic, lagged, direct, and directional). We demonstrate the utility of this modeling approach by applying it to elucidate network processes underlying sensory-motor information flow in the brain, revealing accurate predictions of empirical response information dynamics underlying behavior. Extending the model toward simulating network lesions suggested a role for the cognitive control networks (CCNs) as primary drivers of response information flow, transitioning from early dorsal attention network-dominated sensory-to-response transformation to later collaborative CCN engagement during response selection. These results demonstrate the utility of the dynamic activity flow modeling approach in identifying the generative network processes underlying neurocognitive phenomena.

Acute psychosocial stress modulates neural and behavioral substrates of cognitive control.

Acute psychosocial stress affects learning, memory, and attention, but the evidence for the influence of stress on the neural processes supporting cognitive control remains mixed. We investigated how acute psychosocial stress influences performance and neural processing during the Go/NoGo task-an established cognitive control task. The experimental group underwent the Trier Social Stress Test (TSST) acute stress induction, whereas the control group completed personality questionnaires. Then, participants completed a functional magnetic resonance imaging (fMRI) Go/NoGo task, with self-report, blood pressure and salivary cortisol measurements of induced stress taken intermittently throughout the experimental session. The TSST was successful in eliciting a stress response, as indicated by significant Stress > Control between-group differences in subjective stress ratings and systolic blood pressure. We did not identify significant differences in cortisol levels, however. The stress induction also impacted subsequent Go/NoGo task performance, with participants who underwent the TSST making fewer commission errors on trials requiring the most inhibitory control (NoGo Green) relative to the control group, suggesting increased vigilance. Univariate analysis of fMRI task-evoked brain activity revealed no differences between stress and control groups for any region. However, using multivariate pattern analysis, stress and control groups were reliably differentiated by activation patterns contrasting the most demanding NoGo trials (i.e., NoGo Green trials) versus baseline in the medial intraparietal area (mIPA, affiliated with the dorsal attention network) and subregions of the cerebellum (affiliated with the default mode network). These results align with prior reports linking the mIPA and the cerebellum to visuomotor coordination, a function central to cognitive control processes underlying goal-directed behavior. This suggests that stressor-induced hypervigilance may produce a facilitative effect on response inhibition which is represented neurally by the activation patterns of cognitive control regions.

Causally informed activity flow models provide mechanistic insight into network-generated cognitive activations.

Brain activity flow models estimate the movement of task-evoked activity over brain connections to help explain network-generated task functionality. Activity flow models have been shown to accurately generate task-evoked brain activations across a wide variety of brain regions and task conditions. However, these models have had limited explanatory power, given known issues with causal interpretations of the standard functional connectivity measures used to parameterize activity flow models. We show here that functional/effective connectivity (FC) measures grounded in causal principles facilitate mechanistic interpretation of activity flow models. We progress from simple to complex FC measures, with each adding algorithmic details reflecting causal principles. This reflects many neuroscientists' preference for reduced FC measure complexity (to minimize assumptions, minimize compute time, and fully comprehend and easily communicate methodological details), which potentially trades off with causal validity. We start with Pearson correlation (the current field standard) to remain maximally relevant to the field, estimating causal validity across a range of FC measures using simulations and empirical fMRI data. Finally, we apply causal-FC-based activity flow modeling to a dorsolateral prefrontal cortex region (DLPFC), demonstrating distributed causal network mechanisms contributing to its strong activation during a working memory task. Notably, this fully distributed model is able to account for DLPFC working memory effects traditionally thought to rely primarily on within-region (i.e., not distributed) recurrent processes. Together, these results reveal the promise of parameterizing activity flow models using causal FC methods to identify network mechanisms underlying cognitive computations in the human brain.

Dorsal attention network activity during perceptual organization is distinct in schizophrenia and predictive of cognitive disorganization.

Visual shape completion is a canonical perceptual organization process that integrates spatially distributed edge information into unified representations of objects. People with schizophrenia show difficulty in discriminating completed shapes, but the brain networks and functional connections underlying this perceptual difference remain poorly understood. Also unclear is whether brain network differences in schizophrenia occur in related illnesses or vary with illness features transdiagnostically. To address these topics, we scanned (functional magnetic resonance imaging, fMRI) people with schizophrenia, bipolar disorder, or no psychiatric illness during rest and during a task in which they discriminated configurations that formed or failed to form completed shapes (illusory and fragmented condition, respectively). Multivariate pattern differences were identified on the cortical surface using 360 predefined parcels and 12 functional networks composed of such parcels. Brain activity flow mapping was used to evaluate the likely involvement of resting-state connections for shape completion. Illusory/fragmented task activation differences ('modulations') in the dorsal attention network (DAN) could distinguish people with schizophrenia from the other groups (AUCs > .85) and could transdiagnostically predict cognitive disorganization severity. Activity flow over functional connections from the DAN could predict secondary visual network modulations in each group, except in schizophrenia. The secondary visual network was strongly and similarly modulated in each group. Task modulations were dispersed over more networks in patients compared to controls. In summary, DAN activity during visual perceptual organization is distinct in schizophrenia, symptomatically relevant, and potentially related to improper attention-related feedback into secondary visual areas.

Correction: The solution structures and relative stability constants of lanthanide-EDTA complexes predicted from computation.

Correction for 'The solution structures and relative stability constants of lanthanide-EDTA complexes predicted from computation' by Ravi D. O'Brien et al., Phys. Chem. Chem. Phys., 2022, 24, 10263-10271, https://doi.org/10.1039/D2CP01081J.

The solution structures and relative stability constants of lanthanide-EDTA complexes predicted from computation.

Ligand selectivity to specific lanthanide (Ln) ions is key to the separation of rare earth elements from each other. Ligand selectivity can be quantified with relative stability constants (measured experimentally) or relative binding energies (calculated computationally). The relative stability constants of EDTA (ethylenediaminetetraacetic acid) with La3+, Eu3+, Gd3+, and Lu3+ were predicted from relative binding energies, which were quantified using electronic structure calculations with relativistic effects and based on the molecular structures of Ln-EDTA complexes in solution from density functional theory molecular dynamics simulations. The protonation state of an EDTA amine group was varied to study pH ∼7 and ∼11 conditions. Further, simulations at 25 °C and 90 °C were performed to elucidate how structures of Ln-EDTA complexes varying with temperature are related to complex stabilities at different pH conditions. Relative stability trends are predicted from computation for varying Ln3+ ions (La, Eu, Gd, Lu) with a single ligand (EDTA at pH ∼11), as well as for a single Ln3+ ion (La) with varying ligands (EDTA at pH ∼7 and ∼11). Changing the protonation state of an EDTA amine site significantly changes the solution structure of the Ln-EDTA complex resulting in a reduction of the complex stability. Increased Ln-ligand complex stability is correlated to reduced structural variations in solution upon an increase in temperature.

Brain network mechanisms of visual shape completion.

Visual shape completion recovers object shape, size, and number from spatially segregated edges. Despite being extensively investigated, the process's underlying brain regions, networks, and functional connections are still not well understood. To shed light on the topic, we scanned (fMRI) healthy adults during rest and during a task in which they discriminated pac-man configurations that formed or failed to form completed shapes (illusory and fragmented condition, respectively). Task activation differences (illusory-fragmented), resting-state functional connectivity, and multivariate patterns were identified on the cortical surface using 360 predefined parcels and 12 functional networks composed of such parcels. Brain activity flow mapping (ActFlow) was used to evaluate the likely involvement of resting-state connections for shape completion. We identified 36 differentially-active parcels including a posterior temporal region, PH, whose activity was consistent across 95% of observers. Significant task regions primarily occupied the secondary visual network but also incorporated the frontoparietal, dorsal attention, default mode, and cingulo-opercular networks. Each parcel's task activation difference could be modeled via its resting-state connections with the remaining parcels (r=.62, p<10-9), suggesting that such connections undergird shape completion. Functional connections from the dorsal attention network were key in modelling task activation differences in the secondary visual network. Dorsal attention and frontoparietal connections could also model activations in the remaining networks. Taken together, these results suggest that shape completion relies upon a sparsely distributed but densely interconnected network coalition that is centered in the secondary visual network, coordinated by the dorsal attention network, and inclusive of at least three other networks.

Task-evoked activity quenches neural correlations and variability across cortical areas.

Many large-scale functional connectivity studies have emphasized the importance of communication through increased inter-region correlations during task states. In contrast, local circuit studies have demonstrated that task states primarily reduce correlations among pairs of neurons, likely enhancing their information coding by suppressing shared spontaneous activity. Here we sought to adjudicate between these conflicting perspectives, assessing whether co-active brain regions during task states tend to increase or decrease their correlations. We found that variability and correlations primarily decrease across a variety of cortical regions in two highly distinct data sets: non-human primate spiking data and human functional magnetic resonance imaging data. Moreover, this observed variability and correlation reduction was accompanied by an overall increase in dimensionality (reflecting less information redundancy) during task states, suggesting that decreased correlations increased information coding capacity. We further found in both spiking and neural mass computational models that task-evoked activity increased the stability around a stable attractor, globally quenching neural variability and correlations. Together, our results provide an integrative mechanistic account that encompasses measures of large-scale neural activity, variability, and correlations during resting and task states.

Predicting dysfunctional age-related task activations from resting-state network alterations.

Alzheimer's disease (AD) is linked to changes in fMRI task activations and fMRI resting-state functional connectivity (restFC), which can emerge early in the illness timecourse. These fMRI correlates of unhealthy aging have been studied in largely separate subfields. Taking inspiration from neural network simulations, we propose a unifying mechanism wherein restFC alterations associated with AD disrupt the flow of activations between brain regions, leading to aberrant task activations. We apply this activity flow model in a large sample of clinically normal older adults, which was segregated into healthy (low-risk) and at-risk subgroups based on established imaging (positron emission tomography amyloid) and genetic (apolipoprotein) AD risk factors. Modeling the flow of healthy activations over at-risk AD connectivity effectively transformed the healthy aged activations into unhealthy (at-risk) aged activations. This enabled reliable prediction of at-risk AD task activations, and these predicted activations were related to individual differences in task behavior. These results support activity flow over altered intrinsic functional connections as a mechanism underlying Alzheimer's-related dysfunction, even in very early stages of the illness. Beyond these mechanistic insights, this approach raises clinical potential by enabling prediction of task activations and associated cognitive dysfunction in individuals without requiring them to perform in-scanner cognitive tasks.

Phase II Study of Everolimus in Metastatic Malignant Melanoma (NCCTG-N0377, Alliance).

LESSONS LEARNED: Everolimus does not have sufficient activity to justify its use as single agent in metastatic melanoma.Patients treated with 10 mg per day dose were most likely to require dose reductions.Everolimus appeared to reduce the numbers of regulatory T cells in approximately half of the treated patients; unfortunately, these effects were not correlated with clinical outcomes. BACKGROUND: Everolimus (RAD-001) is an orally active rapamycin analogue shown in preclinical data to produce cytostatic cell inhibition, which may be potentially beneficial in treating melanoma. We conducted a phase II study to evaluate the efficacy and safety of everolimus in patients with unresectable metastatic melanoma (MM). METHODS: This study included two cohorts; cohort 1 received 30 mg of everolimus by mouth (PO) weekly, and cohort 2 was dosed with 10 mg of everolimus PO daily. The endpoints of the study were safety, 16-week progression-free survival (PFS), overall survival (OS), and measures of immunomodulatory/antiangiogenic properties with therapy. Tumor samples before therapy and at week 8 of treatment were analyzed. Peripheral blood plasma or mononuclear cell isolates collected prior to therapy and at weeks 8 and 16 and at time of tumor progression were analyzed for vascular endothelial growth factor and regulatory T-cell (Treg) measurements. RESULTS: A total of 53 patients were enrolled in cohort 1 (n = 24) and cohort 2 (n = 29). Only 2 patients of the first 20 patients enrolled in cohort 2 had treatment responses (25%; 95% confidence interval, 8.6%-49.1%); this result did not allow full accrual to cohort 2, as the study was terminated for futility. Median OS was 12.2 months for cohort 1 versus 8.1 months in cohort 2; no PFS advantage was seen in either group (2.1 months vs. 1.8 months). Dose-limiting toxicities included grade 4 myocardial ischemia (3.4%); grade 3 fatigue, mucositis, and hyperglycemia (10.3%); and anorexia and anemia (6.9%). Everolimus significantly reduced the number of Tregs in approximately half of the treated patients; however, these effects were not correlated with clinical outcomes. CONCLUSION: Everolimus does not have sufficient single-agent activity in MM; however, we have identified evidence of biological activity to provide a potential rationale for future combination studies.

RImmPort: an R/Bioconductor package that enables ready-for-analysis immunology research data.

Summary: : Open access to raw clinical and molecular data related to immunological studies has created a tremendous opportunity for data-driven science. We have developed RImmPort that prepares NIAID-funded research study datasets in ImmPort (immport.org) for analysis in R. RImmPort comprises of three main components: (i) a specification of R classes that encapsulate study data, (ii) foundational methods to load data of a specific study and (iii) generic methods to slice and dice data across different dimensions in one or more studies. Furthermore, RImmPort supports open formalisms, such as CDISC standards on the open source bioinformatics platform Bioconductor, to ensure that ImmPort curated study datasets are seamlessly accessible and ready for analysis, thus enabling innovative bioinformatics research in immunology. Availability and Implementation: RImmPort is available as part of Bioconductor (bioconductor.org/packages/RImmPort). Contact: rshankar@stanford.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

From connectome to cognition: The search for mechanism in human functional brain networks.

Recent developments in functional connectivity research have expanded the scope of human neuroimaging, from identifying changes in regional activation amplitudes to detailed mapping of large-scale brain networks. However, linking network processes to a clear role in cognition demands advances in the theoretical frameworks, algorithms, and experimental approaches applied. This would help evolve the field from a descriptive to an explanatory state, by targeting network interactions that can mechanistically account for cognitive effects. In the present review, we provide an explicit framework to aid this search for "network mechanisms", which anchors recent methodological advances in functional connectivity estimation to a renewed emphasis on careful experimental design. We emphasize how this framework can address specific questions in network neuroscience. These span ambiguity over the cognitive relevance of resting-state networks, how to characterize task-evoked and spontaneous network dynamics, how to identify directed or "effective" connections, and how to apply multivariate pattern analysis at the network level. In parallel, we apply the framework to highlight the mechanistic interaction of network components that remain "stable" across task domains and more "flexible" components associated with on-task reconfiguration. By emphasizing the need to structure the use of diverse analytic approaches with sound experimentation, our framework promotes an explanatory mapping between the workings of the cognitive mind and the large-scale network mechanisms of the human brain.

Empirical validation of directed functional connectivity.

Mapping directions of influence in the human brain connectome represents the next phase in understanding its functional architecture. However, a host of methodological uncertainties have impeded the application of directed connectivity methods, which have primarily been validated via "ground truth" connectivity patterns embedded in simulated functional MRI (fMRI) and magneto-/electro-encephalography (MEG/EEG) datasets. Such simulations rely on many generative assumptions, and we hence utilized a different strategy involving empirical data in which a ground truth directed connectivity pattern could be anticipated with confidence. Specifically, we exploited the established "sensory reactivation" effect in episodic memory, in which retrieval of sensory information reactivates regions involved in perceiving that sensory modality. Subjects performed a paired associate task in separate fMRI and MEG sessions, in which a ground truth reversal in directed connectivity between auditory and visual sensory regions was instantiated across task conditions. This directed connectivity reversal was successfully recovered across different algorithms, including Granger causality and Bayes network (IMAGES) approaches, and across fMRI ("raw" and deconvolved) and source-modeled MEG. These results extend simulation studies of directed connectivity, and offer practical guidelines for the use of such methods in clarifying causal mechanisms of neural processing.

Anoxybacillus sp. Strain UARK-01, a New Thermophilic Soil Bacterium with Hyperthermostable Alkaline Laccase Activity.

We describe the isolation and characteristics of a novel thermophilic bacterium from soil. The organism is a member of the Anoxybacillus genus based on phylogenetic analysis of the 16S rRNA gene. The 16S rRNA of the organism shares >99% sequence identity with those of two species, Anoxybacillus rupiensis and A. geothermalis. We named this isolate as Anoxybacillus sp. strain UARK-01. UARK-01 grows optimally in the presence of oxygen at 55 °C and pH 8. It grew excellently in the presence of lignin as the sole carbon source. Culture supernatant from UARK-01 grown on lignin was rich in laccase activity. The laccase activity was optimal at 90 °C and pH 9, and there was comparable activity at 80 and 100 °C. The crude laccase decolorized approximately 75% of Congo Red in 7 h under optimal conditions. A single laccase gene was identified from the draft genome sequence of Anoxybacillus sp. UARK-01. The UARK-01 laccase (Anox_Lacc) was cloned and overexpressed in Escherichia coli and was partially purified. The partially purified Anox_Lacc decolorized approximately 1.64+/0.21 nanomoles of Congo Red per microgram protein in 30 min at 90 °C and pH 9. Anox_Lacc is a member of the multicopper polyphenol oxidoreductase laccase family (pfam02578 Cu-oxidase_4) and has novel characteristics. Multiple sequence analysis of Anox_Lacc with six homologs from the family revealed four conserved copper ligands and several new residues that are fully conserved. Anox_Lacc is enriched in leucine, glutamine, and lysine, and it contains fewer alanine, arginine, glycine, and serine residues. Skewed amino acid composition of Anox_Lacc likely contributes to the exceptional thermochemical properties of the laccase activity from UARK-01. Both lignin utilization and production of hyperthermostable alkaline laccase are new findings in the Anoxybacillus genus.

Comparison of luminescence property of gamma-ray irradiated Tb3+ -doped and Ce3+ co-doped potassium halide single crystals.

Single crystals of KCl and KBr singly and doubly doped with Tb3+ and Ce3+ , respectively, were successfully grown using the Bridgeman technique. This work reports the comparative luminescence behavior and optical absorption characterization of non-irradiated and γ-ray-irradiated single crystals of these materials. The existing defect and the defect created by γ-ray irradiation were monitored by optical absorption spectra. The excitation and emission spectra of these materials were measured at room temperature with a spectrofluorometer and the pertaining results were compared. The F-band comparison was made when bleached with F-light for 2 mins. The trap-level changes in KCl and KBr when it is singly and doubly doped enabled us to draw conclusions on the nature of the defect and on the recombination processes involved.

A Prospective Comparative Study of Color Doppler Ultrasound with Twinkling and Noncontrast Computerized Tomography for the Evaluation of Acute Renal Colic.

PURPOSE: We performed a prospective comparison of the use of twinkling color Doppler ultrasound and noncontrast computerized tomography in the diagnosis of renal colic in emergency room patients. MATERIALS AND METHODS: A total of 815 consecutive adult patients with suspected renal colic presented to the emergency room and were evaluated immediately with color Doppler ultrasound and noncontrast computerized tomography. The site, side and maximum transverse diameter of the stones were assessed. The patients were followed for 4 to 8 weeks. RESULTS: Of 815 patients 723 (88.72%) had ureteral stones, 60 (7.36%) had kidney stones and 32 (3.93%) had pain from extra-urinary causes. Mean patient age was 37.17±11 years. Of the 723 patients with ureteral stones 619 (85.6%) were male and 104 (14.4%) were female. The stones were located on the right side in 340 (47%) patients and on the left side in 383 (53%). Color Doppler ultrasound successfully identified the stones in 702 (97.1%) patients and failed in 21 (2.9%). Noncontrast computerized tomography confirmed stones in 720 (99.6%) patients and was negative in 3 (0.4%). The diagnosis was 166 (23%) upper ureter stones, 63 (8.7%) in the middle and 494 (68.3%) in the lower ureter. The color Doppler ultrasound results were significantly affected by the stone site and maximum transverse diameter (p = 0.03 and 0.007, respectively). CONCLUSIONS: The initial use of color Doppler ultrasound in the emergency room has led to the diagnosis and characterization of ureteral stones in the majority of patients. Color Doppler ultrasound results were comparable to those of the concomitant use of noncontrast computerized tomography. Therefore, color Doppler ultrasound can replace noncontrast computerized tomography in the emergency room.

Peer-assisted learning: filling the gaps in basic science education for preclinical medical students.

In contrast to peer-assisted learning (PAL) in clinical training, there is scant literature on the efficacy of PAL during basic medical sciences teaching for preclinical students. A group of senior medical students aimed to design and deliver clinically oriented small-group tutorials after every module in the preclinical curriculum at a United Kingdom medical school. Twenty tutorials were delivered by senior students throughout the year to first- and second-year students. A baseline questionnaire was delivered to inform the development of the program followed by an end-point questionnaire the next year (n = 122). Quizzes were administered before and after five separate tutorials to assess changes in mean student scores. Additionally, each tutorial was evaluated via a questionnaire for participants (n = 949). All five posttutorial quizzes showed a significant improvement in mean student score (P < 0.05). Questionnaires showed students found the program to be relevant and useful for revision purposes and appreciated how tutorials contextualized basic science to clinical medicine. Students appreciated the interactive nature of the sessions and found receiving personalized feedback about their learning and consolidating information with someone familiar with the material to be useful. With the inclusion of the program, students felt there were now an adequate number of tutorials during the year. In conclusion, this study shows that senior medical students can design and deliver a program that adds value to the mostly lecture-based formal preclinical curriculum. We hope that our study can prompt further work to explore the effect of PAL on the teaching of basic sciences during preclinical studies.

Interventional Procedures for Chronic Pain in Children and Adolescents: A Review of the Current Evidence.

This review discusses the role of interventional procedures in the treatment of chronic pain in children and adolescents. Due to lack of scientific evidence, significant controversy surrounds the utility of invasive techniques for managing pediatric chronic pain states. Interventional procedures are a widely accepted modality for pain management in adults. The use of such techniques in children is supported only by case reports, case series, and very few randomized controlled studies. In addition, the potential for severe complications leaves open a debate on the safety of these invasive procedures, which must be confirmed by more extensive and accurate prospective studies.