Goal Choices Modify Frontotemporal Memory Representations.

Adapting flexibly to changing circumstances is guided by memory of past choices, their outcomes in similar circumstances, and a method for choosing among potential actions. The hippocampus (HPC) is needed to remember episodes, and the prefrontal cortex (PFC) helps guide memory retrieval. Single-unit activity in the HPC and PFC correlates with such cognitive functions. Previous work recorded CA1 and mPFC activity as male rats performed a spatial reversal task in a plus maze that requires both structures, found that PFC activity helps reactivate HPC representations of pending goal choices but did not describe frontotemporal interactions after choices. We describe these interactions after choices here. CA1 activity tracked both current goal location and the past starting location of single trials; PFC activity tracked current goal location better than past start location. CA1 and PFC reciprocally modulated representations of each other both before and after goal choices. After choices, CA1 activity predicted changes in PFC activity in subsequent trials, and the magnitude of this prediction correlated with faster learning. In contrast, PFC start arm activity more strongly modulated CA1 activity after choices correlated with slower learning. Together, the results suggest post-choice HPC activity conveys retrospective signals to the PFC, which combines different paths to common goals into rules. In subsequent trials, prechoice mPFC activity modulates prospective CA1 signals informing goal selection.SIGNIFICANCE STATEMENT HPC and PFC activity supports cognitive flexibility in changing circumstances. HPC signals represent behavioral episodes that link the start, choice, and goal of paths. PFC signals represent rules that guide goal-directed actions. Although prior studies described HPC-PFC interactions preceding decisions in the plus maze, post-decision interactions were not investigated. Here, we show post-choice HPC and PFC activity distinguished the start and goal of paths, and CA1 signaled the past start of each trial more accurately than mPFC. Postchoice CA1 activity modulated subsequent PFC activity, so rewarded actions were more likely to occur. Together, the results show that in changing circumstances, HPC retrospective codes modulate subsequent PFC coding, which in turn modulates HPC prospective codes that predict choices.

An insulin-regulated arrestin domain protein controls hepatic glucagon action.

Glucagon signaling is essential for maintaining normoglycemia in mammals. The arrestin fold superfamily of proteins controls the trafficking, turnover, and signaling of transmembrane receptors as well as other intracellular signaling functions. Further investigation is needed to understand the in vivo functions of the arrestin domain-containing 4 (ARRDC4) protein family member and whether it is involved in mammalian glucose metabolism. Here, we show that mice with a global deletion of the ARRDC4 protein have impaired glucagon responses and gluconeogenesis at a systemic and molecular level. Mice lacking ARRDC4 exhibited lower glucose levels after fasting and could not suppress gluconeogenesis at the refed state. We also show that ARRDC4 coimmunoprecipitates with the glucagon receptor, and ARRDC4 expression is suppressed by insulin. These results define ARRDC4 as a critical regulator of glucagon signaling and glucose homeostasis and reveal a novel intersection of insulin and glucagon pathways in the liver.

Hippocampal and Medial Prefrontal Cortex Fractal Spiking Patterns Encode Episodes and Rules.

A central question in neuroscience is how the brain represents and processes information to guide behavior. The principles that organize brain computations are not fully known, and could include scale-free, or fractal patterns of neuronal activity. Scale-free brain activity may be a natural consequence of the relatively small subsets of neuronal populations that respond to task features, i.e., sparse coding. The size of the active subsets constrains the possible sequences of inter-spike intervals (ISI), and selecting from this limited set may produce firing patterns across wide-ranging timescales that form fractal spiking patterns. To investigate the extent to which fractal spiking patterns corresponded with task features, we analyzed ISIs in simultaneously recorded populations of CA1 and medial prefrontal cortical (mPFC) neurons in rats performing a spatial memory task that required both structures. CA1 and mPFC ISI sequences formed fractal patterns that predicted memory performance. CA1 pattern duration, but not length or content, varied with learning speed and memory performance whereas mPFC patterns did not. The most common CA1 and mPFC patterns corresponded with each region's cognitive function: CA1 patterns encoded behavioral episodes which linked the start, choice, and goal of paths through the maze whereas mPFC patterns encoded behavioral "rules" which guided goal selection. mPFC patterns predicted changing CA1 spike patterns only as animals learned new rules. Together, the results suggest that CA1 and mPFC population activity may predict choice outcomes by using fractal ISI patterns to compute task features.

A Single Center 8 Year Experience of Segmental Arterial Mediolysis Management.

OBJECTIVE: Segmental Arterial Mediolysis (SAM) is a rare, poorly understood vasculopathy that involves vacuolization of the arterial wall, most commonly of the visceral arteries. There are no established therapeutic or monitoring guidelines for SAM, and intervention typically depends on patient presentation. The purpose of this study is to review the management and outcomes of patients with this rare vascular disease METHODS: Single center retrospective review of patients diagnosed with SAM between 2011 and 2019. Included were patients with radiological diagnosis of SAM. Demographic factors, past medical history, presenting symptoms, affected vessels, management, and lesion characteristics over time were collected. Demographic and periprocedural factors, and medical management strategies were compared for those who required operative intervention versus those managed non-operatively. RESULTS: Thirty patients were included, 21 (70%) were male, mean age was 53.5 years (range: 35.7-72.2). Twenty-seven patients were managed non-operatively, 3 patients required surgical intervention. Patients who underwent operative intervention were more likely to present with pain >30 days (P < 0.05), and hemorrhage (P < 0.01). Abdominal pain was the most common presenting symptom (n = 24, 80%). Arterial dissection was the most common radiological finding at time of presentation (n = 20, 67%). The celiac artery and its branches were most often involved (n=22, 73%) followed by the superior mesenteric artery and its branches (n = 15, 50%). Non-operative management most often consisted of anti-hypertensive therapy (n = 13, 43%), antiplatelet agents (n = 17, 57%%), and lipid-lowering agents (n = 13, 43%), with 7 patients receiving all three. Six patients demonstrated confirmed resolution of lesions during surveillance imaging, with average time to resolution of 325.5 days. CONCLUSIONS: Patients who underwent intervention for SAM presented with either mesenteric ischemia or pseudoaneurysm rupture. In patients that present without those conditions, medical management consisting of anti-hypertensives, antiplatelet agents, and lipid-lowering therapy was effective. Non operative management resulted in symptom resolution in all patients and surveillance imaging showed resolution of radiographic abnormalities in 6 patients out of 27 at less than one year.

PyTrack: An end-to-end analysis toolkit for eye tracking.

Eye tracking is a widely used tool for behavioral research in the field of psychology. With technological advancement, we now have specialized eye-tracking devices that offer high sampling rates, up to 2000 Hz, and allow for measuring eye movements with high accuracy. They also offer high spatial resolution, which enables the recording of very small movements, like drifts and microsaccades. Features and parameters of interest that characterize eye movements need to be algorithmically extracted from raw data as most eye trackers identify only basic parameters, such as blinks, fixations, and saccades. Eye-tracking experiments may investigate eye movement behavior in different groups of participants and in varying stimuli conditions. Hence, the analysis stage of such experiments typically involves two phases, (i) extraction of parameters of interest and (ii) statistical analysis between different participants or stimuli conditions using these parameters. Furthermore, the datasets collected in these experiments are usually very large in size, owing to the high temporal resolution of the eye trackers, and hence would benefit from an automated analysis toolkit. In this work, we present PyTrack, an end-to-end open-source solution for the analysis and visualization of eye-tracking data. It can be used to extract parameters of interest, generate and visualize a variety of gaze plots from raw eye-tracking data, and conduct statistical analysis between stimuli conditions and subject groups.

Identifying Intermolecular Interactions in Single-Molecule Localization Microscopy.

Intermolecular interactions underlie all cellular functions, yet visualizing these interactions at the single-molecule level remains challenging. Single-molecule localization microscopy (SMLM) offers a potential solution. Given a nanoscale map of two putative interaction partners, it should be possible to assign molecules either to the class of coupled pairs or to the class of non-coupled bystanders. Here, we developed a probabilistic algorithm that allows accurate determination of both the absolute number and the proportion of molecules that form coupled pairs. The algorithm calculates interaction probabilities for all possible pairs of localized molecules, selects the most likely interaction set, and corrects for any spurious colocalizations. Benchmarking this approach across a set of simulated molecular localization maps with varying densities (up to ∼ 50 molecules µm - 2 ) and localization precisions (5 to 50 nm) showed typical errors in the identification of correct pairs of only a few percent. At molecular densities of ∼ 5-10 molecules µm - 2 and localization precisions of 20-30 nm, which are typical parameters for SMLM imaging, the recall was ∼ 90%. The algorithm was effective at differentiating between non-interacting and coupled molecules both in simulations and experiments. Finally, it correctly inferred the number of coupled pairs over time in a simulated reaction-diffusion system, enabling determination of the underlying rate constants. The proposed approach promises to enable direct visualization and quantification of intermolecular interactions using SMLM.

Hippocampal and medial prefrontal ensemble spiking represents episodes and rules in similar task spaces.

Episodic memory requires the hippocampus and prefrontal cortex to guide decisions by representing events in spatial, temporal, and personal contexts. Both brain regions have been described by cognitive theories that represent events in context as locations in maps or memory spaces. We query whether ensemble spiking in these regions described spatial structures as rats performed memory tasks. From each ensemble, we construct a state-space with each point defined by the coordinated spiking of single and pairs of units in 125-ms bins and investigate how state-space locations discriminate task features. Trajectories through state-spaces correspond with behavioral episodes framed by spatial, temporal, and internal contexts. Both hippocampal and prefrontal ensembles distinguish maze locations, task intervals, and goals by distances between state-space locations, consistent with cognitive mapping and relational memory space theories of episodic memory. Prefrontal modulation of hippocampal activity may guide choices by directing memory representations toward appropriate state-space goal locations.

Precarious employment and associated health and social consequences; a systematic review.

OBJECTIVE: This systematic review aims to identify, evaluate, and summarise the consequences of precarious employment. METHODS: We included studies published within the last ten years (Jan 2011-July 2021) that employed at least two of three key dimensions of precarious employment: employment insecurity, income inadequacy, and lack of rights and protection. RESULTS: Of the 4,947 initially identified studies, only five studies met our eligibility criteria. These five studies were of moderate quality as assessed by the Newcastle-Ottawa Scale. Our review found that the current literature predominantly defines precarity based on the single criterion of employment insecurity. Our review identified evidence for the negative consequences of precarious employment, including poorer workplace wellbeing, general health, mental health, and emotional wellbeing. The findings indicated an increase in the magnitude of these adverse outcomes with a higher degree of job precariousness. CONCLUSIONS: The rise of employment precariousness will likely continue to be a major issue in the coming years. More research is needed to inform effective policies and practices using a consensus definition of precarious employment. IMPLICATIONS FOR PUBLIC HEALTH: The presence of adverse effects of precarious employment suggests workplace initiatives are essential to mitigate the negative consequences of precarity.

Interventions to increase sleep duration in young people: A systematic review.

This systematic review explored the outcomes of current interventions to increase sleep duration in healthy young people (14-25 years). Nine databases were systematically searched, and 26 studies were included in this review. Quality assessment of the included studies was evaluated using two tools: the Newcastle-Ottawa scale, and Cochrane Risk of Bias. The interventions incorporated a range of strategies including behavioral (46.2%), educational (26.9%), a combination of behavioral and educational (15.4%), and other strategies such as physical therapy (11.5%). The findings indicate that behavioral and combination interventions were consistently effective in increasing sleep duration in healthy young people. Educational interventions alone were less effective at increasing young people's sleep duration. Of all the included studies, only one randomized control trial but none of the non-randomized trials were rated as good quality. Our findings suggest a combination of strategies with an emphasis on personalization of intervention could possibly maximize the chances of success at improving sleep duration in healthy young people. More high-quality studies with long-term assessments (≥ 6 months) should be conducted to test the efficacy and durability of interventions to increase sleep duration in young people, as well as the clinical implications to mental and physical health.

An in silico model for determining the influence of neuronal co-activity on rodent spatial behavior.

BACKGROUND: Neuropsychological and neurophysiological analyses focus on understanding how neuronal activity and co-activity predict behavior. Experimental techniques allow for modulation of neuronal activity, but do not control neuronal ensemble spatiotemporal firing patterns, and there are few, if any, sophisticated in silico techniques which accurately reconstruct physiological neural spike trains and behavior using unit co-activity as an input parameter. NEW METHOD: Our approach to simulation of neuronal spike trains is based on using state space modeling to estimate a weighted graph of interaction strengths between pairs of neurons along with separate estimations of spiking threshold voltage and neuronal membrane leakage. These parameters allow us to tune a biophysical model which is then employed to accurately reconstruct spike trains from freely behaving animals and then use these spike trains to estimate an animal's spatial behavior. The reconstructed spatial behavior allows us to confirm the same information is present in both the recorded and simulated spike trains. RESULTS: Our method reconstructs spike trains (98 ± 0.0013% like original spike trains, mean ± SEM) and animal position (9.468 ± 0.240 cm, mean ± SEM) with high fidelity. COMPARISON WITH EXISTING METHOD(S): To our knowledge, this is the first method that uses empirically derived network connectivity to constrain biophysical parameters and predict spatial behavior. Together, these methods allow in silico quantification of the contribution of specific unit activity and co-activity to animal spatial behavior. CONCLUSIONS: Our novel approach provides a flexible, robust in silico technique for determining the contribution of specific neuronal activity and co-activity to spatial behavior.

Venous insufficiency, lymphocutaneous fistula, and use of autologous blood.

Lymphocutaneous fistulas are an uncommon occurrence that can present after surgical intervention in lymphatic-rich areas. A spontaneous lymphatic leak can occur in conjunction with lymphedema or in the vicinity of venous stasis ulcers. However, spontaneous lymphocutaneous fistulas are extremely rare. Traditional treatments have included surgical ligation, negative pressure therapy, and embolization. We present the case of a lymphocutaneous fistula secondary to chronic venous stasis, which was treated via injection of autologous blood and subsequent thrombosis. In the present case report, we have demonstrated successful embolization of a lymphatic vessel via autologous blood injection, a nontraditional technique that, nonetheless, yielded positive and lasting results.

A unique case of bilateral lower extremity post-endovascular aneurysm repair claudication.

The majority of abdominal aortic aneurysms have been treated by endovascular aneurysm repair in the past decade. Common perioperative complications after this procedure are mostly related to vascular access and improper stent-graft placement. We present the first case of bilateral lower extremity claudication due to severe angulation of the graft-aorta interface, which may have been prevented by a more critical consideration of the patient's anatomy. Treatment required open explantation and repair of the abdominal aortic aneurysms which led to complete resolution of claudication. The results of this case highlight the importance of adherence to instructions for use guidelines.

AutoSholl allows for automation of Sholl analysis independent of user tracing.

BACKGROUND: Sholl analysis has been used to analyze neuronal morphometry and dendritic branching and complexity for many years. While the process has become semi-automated in recent years, existing software packages are still dependent on user tracing and hence are subject to observer bias, variability, and increased user times for analyses. Commercial software packages have the same issues as they also rely on user tracing. In addition, these packages are also expensive and require extensive user training. NEW METHOD: To address these issues, we have developed a broadly applicable, no-cost ImageJ plugin, we call AutoSholl, to perform Sholl analysis on pre-processed and 'thresholded' images. This algorithm extends the already existing plugin in Fiji ImageJ for Sholl analysis by allowing for secondary analysis techniques, such as determining number and length of root, intermediate, and terminal dendrites; functions not currently supported in the existing Sholl Analysis plugin in Fiji ImageJ. RESULTS: The algorithm allows for rapid Sholl analysis in both 2-dimensional and 3-dimensional data sets independent of user tracing. COMPARISON WITH EXISTING METHODS: We validated the performance of AutoSholl against pre-existing software packages using trained human observers and images of neurons. We found that our algorithm outputs similar results as available software (i.e., Bonfire), but allows for faster analysis times and unbiased quantification. CONCLUSIONS: As such, AutoSholl allows inexperienced observers to output results like more trained observers efficiently, thereby increasing the consistency, speed, and reliability of Sholl analyses.

Bioinspired, Spine-Like, Flexible, Rechargeable Lithium-Ion Batteries with High Energy Density.

The rapid development of flexible and wearable electronics proposes the persistent requirements of high-performance flexible batteries. Much progress has been achieved recently, but how to obtain remarkable flexibility and high energy density simultaneously remains a great challenge. Here, a facile and scalable approach to fabricate spine-like flexible lithium-ion batteries is reported. A thick, rigid segment to store energy through winding the electrodes corresponds to the vertebra of animals, while a thin, unwound, and flexible part acts as marrow to interconnect all vertebra-like stacks together, providing excellent flexibility for the whole battery. As the volume of the rigid electrode part is significantly larger than the flexible interconnection, the energy density of such a flexible battery can be over 85% of that in conventional packing. A nonoptimized flexible cell with an energy density of 242 Wh L-1 is demonstrated with packaging considered, which is 86.1% of a standard prismatic cell using the same components. The cell also successfully survives a harsh dynamic mechanical load test due to this rational bioinspired design. Mechanical simulation results uncover the underlying mechanism: the maximum strain in the reported design (≈0.08%) is markedly smaller than traditional stacked cells (≈1.1%). This new approach offers great promise for applications in flexible devices.