Emergent scale-free networks.

Many complex systems-from the Internet to social, biological, and communication networks-are thought to exhibit scale-free structure. However, prevailing explanations require that networks grow over time, an assumption that fails in some real-world settings. Here, we explain how scale-free structure can emerge without growth through network self-organization. Beginning with an arbitrary network, we allow connections to detach from random nodes and then reconnect under a mixture of preferential and random attachment. While the numbers of nodes and edges remain fixed, the degree distribution evolves toward a power-law with an exponent γ = 1 + 1 p that depends only on the proportion p of preferential (rather than random) attachment. Applying our model to several real networks, we infer p directly from data and predict the relationship between network size and degree heterogeneity. Together, these results establish how scale-free structure can arise in networks of constant size and density, with broad implications for the structure and function of complex systems.

Synchrotron-source micro-x-ray computed tomography for examining butterfly eyes.

Comparative anatomy is an important tool for investigating evolutionary relationships among species, but the lack of scalable imaging tools and stains for rapidly mapping the microscale anatomies of related species poses a major impediment to using comparative anatomy approaches for identifying evolutionary adaptations. We describe a method using synchrotron source micro-x-ray computed tomography (syn-µXCT) combined with machine learning algorithms for high-throughput imaging of Lepidoptera (i.e., butterfly and moth) eyes. Our pipeline allows for imaging at rates of ~15 min/mm3 at 600 nm3 resolution. Image contrast is generated using standard electron microscopy labeling approaches (e.g., osmium tetroxide) that unbiasedly labels all cellular membranes in a species-independent manner thus removing any barrier to imaging any species of interest. To demonstrate the power of the method, we analyzed the 3D morphologies of butterfly crystalline cones, a part of the visual system associated with acuity and sensitivity and found significant variation within six butterfly individuals. Despite this variation, a classic measure of optimization, the ratio of interommatidial angle to resolving power of ommatidia, largely agrees with early work on eye geometry across species. We show that this method can successfully be used to determine compound eye organization and crystalline cone morphology. Our novel pipeline provides for fast, scalable visualization and analysis of eye anatomies that can be applied to any arthropod species, enabling new questions about evolutionary adaptations of compound eyes and beyond.

Perceptual Resolution of Ambiguity: Can Tuned, Divisive Normalization Account for both Interocular Similarity Grouping and Difference Enhancement.

Our visual system usually provides a unique and functional representation of the external world. At times, however, the visual system has more than one compelling interpretation of the same retinal stimulus; in this case, neural populations compete for perceptual dominance to resolve ambiguity. Spatial and temporal context can guide perceptual experience. Recent evidence shows that ambiguous retinal stimuli are sometimes resolved by enhancing either similarity or differences among multiple percepts. Divisive normalization is a canonical neural computation that enables context-dependent sensory processing by attenuating a neuron's response by other neurons. Experiments here show that divisive normalization can account for perceptual representations of either similarity enhancement (so-called grouping) or difference enhancement, offering a unified framework for opposite perceptual outcomes.

High prevalence of trachomatous inflammation-follicular with no trachomatous trichiasis: can alternative indicators explain the epidemiology of trachoma in Côte d'Ivoire?

Baseline trachoma surveys in Côte d'Ivoire (2019) identified seven evaluation units (EUs) with a trachomatous inflammation-follicular (TF) prevalence ≥10%, but a trachomatous trichiasis (TT) prevalence in individuals ≥15 y of age below the elimination threshold (0.2%). Two of these EUs, Bondoukou 1 and Bangolo 2, were selected for a follow-up survey to understand the epidemiology of trachoma using additional indicators of Chlamydia trachomatis infection (DNA from conjunctival swabs) and exposure (anti-Pgp3 and Ct694 antibodies from dried blood spots [DBSs]). A two-stage cluster sampling methodology was used to select villages and households. All individuals 1-9 y of age from each selected household were recruited, graded for trachoma and had a conjunctival swab and DBS collected. Conjunctival swabs and DBSs were tested using Cepheid GeneXpert and a multiplex bead assay, respectively. The age-adjusted TF and infection prevalence in 1- to 9-year-olds was <1% and <0.3% in both EUs. Age-adjusted seroprevalence was 5.3% (95% confidence interval [CI] 1.5 to 15.6) in Bondoukou 1 and 8.2% (95% CI 4.3 to 13.7) in Bangolo 2. The seroconversion rate for Pgp3 was low, at 1.23 seroconversions/100 children/year (95% CI 0.78 to 1.75) in Bondoukou 1 and 1.91 (95% CI 1.58 to 2.24) in Bangolo 2. Similar results were seen for CT694. These infection, antibody and clinical data provide strong evidence that trachoma is not a public health problem in either EU.

A dynamic scale-mixture model of motion in natural scenes.

Some of the most important tasks of visual and motor systems involve estimating the motion of objects and tracking them over time. Such systems evolved to meet the behavioral needs of the organism in its natural environment, and may therefore be adapted to the statistics of motion it is likely to encounter. By tracking the movement of individual points in videos of natural scenes, we begin to identify common properties of natural motion across scenes. As expected, objects in natural scenes move in a persistent fashion, with velocity correlations lasting hundreds of milliseconds. More subtly, we find that the observed velocity distributions are heavy-tailed and can be modeled as a Gaussian scale-mixture. Extending this model to the time domain leads to a dynamic scale-mixture model, consisting of a Gaussian process multiplied by a positive scalar quantity with its own independent dynamics. Dynamic scaling of velocity arises naturally as a consequence of changes in object distance from the observer, and may approximate the effects of changes in other parameters governing the motion in a given scene. This modeling and estimation framework has implications for the neurobiology of sensory and motor systems, which need to cope with these fluctuations in scale in order to represent motion efficiently and drive fast and accurate tracking behavior.

Exactly solvable statistical physics models for large neuronal populations.

Maximum entropy methods provide a principled path connecting measurements of neural activity directly to statistical physics models, and this approach has been successful for populations of N~100 neurons. As N increases in new experiments, we enter an undersampled regime where we have to choose which observables should be constrained in the maximum entropy construction. The best choice is the one that provides the greatest reduction in entropy, defining a "minimax entropy" principle. This principle becomes tractable if we restrict attention to correlations among pairs of neurons that link together into a tree; we can find the best tree efficiently, and the underlying statistical physics models are exactly solved. We use this approach to analyze experiments on N~1500 neurons in the mouse hippocampus, and show that the resulting model captures the distribution of synchronous activity in the network.

The double-drift illusion biases the marmoset oculomotor system.

The double-drift illusion has two unique characteristics: The error between the perceived and physical position of the stimulus grows over time, and saccades to the moving target land much closer to the physical than the perceived location. These results suggest that the perceptual and saccade targeting systems integrate visual information over different time scales. Functional imaging studies in humans have revealed several potential cortical areas of interest, including the prefrontal cortex. However, we currently lack an animal model to study the neural mechanisms of location perception that underlie the double-drift illusion. To fill this gap, we trained two marmoset monkeys to fixate and then saccade to the double-drift stimulus. In line with human observers for radial double-drift trajectories with fast internal motion, we find that saccade endpoints show a significant bias that is, nevertheless, smaller than the bias seen in human perceptual reports. This bias is modulated by changes in the external and internal speeds of the stimulus. These results demonstrate that the saccade targeting system of the marmoset monkey is influenced by the double-drift illusion.

Stimulus invariant aspects of the retinal code drive discriminability of natural scenes.

Everything that the brain sees must first be encoded by the retina, which maintains a reliable representation of the visual world in many different, complex natural scenes while also adapting to stimulus changes. Decomposing the population code into independent and cell-cell interactions reveals how broad scene structure is encoded in the adapted retinal output. By recording from the same retina while presenting many different natural movies, we see that the population structure, characterized by strong interactions, is consistent across both natural and synthetic stimuli. We show that these interactions contribute to encoding scene identity. We also demonstrate that this structure likely arises in part from shared bipolar cell input as well as from gap junctions between retinal ganglion cells and amacrine cells.

Sex Differences in Perceived Motor Competence After the Children's Health Activity Motor Program Intervention.

This study examined the effects of a motor-skill intervention on children's perceived motor competence (PMC; object control, locomotor, and combined [total]) and explored if effects differed between the sexes. Preschoolers (N = 274; 47.96 months) completed either a motor-skill intervention (the Children's Health Activity Motor Program [CHAMP]) or recess. PMC was measured with the Digital Scale of PMC before and after each condition. Controlling for pretest scores, recess girls had lower posttest object-control PMC scores than CHAMP boys, CHAMP girls, and recess boys (all p < .05). CHAMP children had significantly higher posttest locomotor and total PMC (all p < .001) compared with children who engaged in recess. CHAMP partially eliminates sex differences in PMC, particularly for object-control skills. Girls who participated in recess did not increase PMC like children in CHAMP and boys who engaged in outdoor recess.

Impact of personal protective equipment on the clarity of vision among trachoma survey graders and trichiasis surgeons in the context of COVID-19.

BACKGROUND/AIMS: The COVID-19 pandemic necessitated the use of personal protective equipment for those involved in trachoma survey grading and trichiasis surgery. We sought to determine which configuration of a face shield would be less likely to impact grading accuracy and ability to conduct trichiasis surgery. The research also included assessment of comfort, ease of cleaning and robustness. METHODS: There were three research phases. In phase 1, assessment of four potential face shield configurations was undertaken with principal trachoma graders and trichiasis surgeon trainers to decide which two options should undergo further testing. In phase 2, clarity of vision and comfort (in a classroom environment) of the two configurations were assessed compared with no face shield (control), while grading trachomatous inflammation-follicular (TF). The second phase also included the assessment of impact of the configurations while performing trichiasis surgery using a training model. In phase 3, face shield ease of use was evaluated during routine surgical programmes. RESULTS: In phase 2, 124 trachoma graders and 28 trichiasis surgeons evaluated the 2 face shield configurations selected in phase 1. TF agreement was high (kappa=0.83 and 0.82) for both configurations compared with not wearing a face shield. Comfort was reported as good by 51% and 32% of graders using the two configurations. Trichiasis skill scores were similar for both configurations. CONCLUSION: The face shield configuration that includes a cut-out for mounting the 2.5× magnifying loupes does not appear to impact the ability or comfort of trachoma graders or trichiasis surgeons to carry out their work.

Predictive saccades and decision making in the beetle-predating saffron robber fly.

Internal predictions about the sensory consequences of self-motion, encoded by corollary discharge, are ubiquitous in the animal kingdom, including for fruit flies, dragonflies, and humans. In contrast, predicting the future location of an independently moving external target requires an internal model. With the use of internal models for predictive gaze control, vertebrate predatory species compensate for their sluggish visual systems and long sensorimotor latencies. This ability is crucial for the timely and accurate decisions that underpin a successful attack. Here, we directly demonstrate that the robber fly Laphria saffrana, a specialized beetle predator, also uses predictive gaze control when head tracking potential prey. Laphria uses this predictive ability to perform the difficult categorization and perceptual decision task of differentiating a beetle from other flying insects with a low spatial resolution retina. Specifically, we show that (1) this predictive behavior is part of a saccade-and-fixate strategy, (2) the relative target angular position and velocity, acquired during fixation, inform the subsequent predictive saccade, and (3) the predictive saccade provides Laphria with additional fixation time to sample the frequency of the prey's specular wing reflections. We also demonstrate that Laphria uses such wing reflections as a proxy for the wingbeat frequency of the potential prey and that consecutively flashing LEDs to produce apparent motion elicits attacks when the LED flicker frequency matches that of the beetle's wingbeat cycle.

Evaluating the availability and quality of services for lymphatic filariasis morbidity in Ghana.

BACKGROUND AND METHODOLOGY: In districts where lymphatic filariasis (LF) is endemic, the goal is to provide 100% geographical coverage of the essential package of care. Additionally, countries seeking elimination status must document the availability of services for lymphoedema and hydrocele in all endemic areas. To do this, the WHO recommends conducting assessments of the readiness and quality of services provided to identify service delivery and quality gaps. This study used the recommended WHO Direct Inspection Protocol (DIP), which consists of 14 core indicators related to LF case management, medicine and commodities, staff knowledge and patient tracking. The survey was administered in 156 health facilities across Ghana designated and trained to provide LF morbidity management services. Patient and health provider interviews were also conducted to assess challenges and feedback. PRINCIPAL FINDINGS: The highest performing indicators across the 156 surveyed facilities were related to staff knowledge; 96.6% of health workers correctly identified two or more signs and symptoms. The lowest scoring indicators concerned medication availability, with the two lowest scoring indicators in the survey being availability of antifungals (26.28%) and antiseptics (31.41%). Hospitals performed best with an overall score of 79.9%, followed by health centers (73%), clinics (67.1%) and CHPS compounds (66.8%). The most commonly reported challenge from health worker interviews was lack of medications and supplies, followed by a lack of training or poor motivation. CONCLUSIONS AND SIGNIFICANCE: The findings from this study can help the Ghana NTD Program identify areas of improvement as they seek to achieve LF elimination targets and continue to improve access to care for those with LF-related morbidity as part of overall health systems strengthening. Key recommendations include prioritizing refresher and MMDP training for health workers, ensuring reliable patient tracking systems, and integrating lymphatic filariasis morbidity management into the routine healthcare system to ensure medicine and commodity availably.

Gaussian Information Bottleneck and the Non-Perturbative Renormalization Group.

The renormalization group (RG) is a class of theoretical techniques used to explain the collective physics of interacting, many-body systems. It has been suggested that the RG formalism may be useful in finding and interpreting emergent low-dimensional structure in complex systems outside of the traditional physics context, such as in biology or computer science. In such contexts, one common dimensionality-reduction framework already in use is information bottleneck (IB), in which the goal is to compress an "input" signal X while maximizing its mutual information with some stochastic "relevance" variable Y. IB has been applied in the vertebrate and invertebrate processing systems to characterize optimal encoding of the future motion of the external world. Other recent work has shown that the RG scheme for the dimer model could be "discovered" by a neural network attempting to solve an IB-like problem. This manuscript explores whether IB and any existing formulation of RG are formally equivalent. A class of soft-cutoff non-perturbative RG techniques are defined by families of non-deterministic coarsening maps, and hence can be formally mapped onto IB, and vice versa. For concreteness, this discussion is limited entirely to Gaussian statistics (GIB), for which IB has exact, closed-form solutions. Under this constraint, GIB has a semigroup structure, in which successive transformations remain IB-optimal. Further, the RG cutoff scheme associated with GIB can be identified. Our results suggest that IB can be used to impose a notion of "large scale" structure, such as biological function, on an RG procedure.

Motor skills predict adaptive behavior in autistic children and adolescents.

It is well-documented that intelligence quotient (IQ) is a poor predictor of adaptive behavior scores in autism, with autistic children having lower adaptive behavior scores than would be predicted based on their IQ scores. Differences in motor skills may explain the variability in their adaptive behavior scores. The current study examined how motor skills might explain autistic individuals' low adaptive behavior scores and which individual components of IQ (i.e., verbal comprehension and perceptual reasoning) and motor skills (i.e., manual dexterity, aiming and catching, and balance) may drive this effect. We examined the associations between IQ, motor skills, calibrated severity, and adaptive behavior scores in 45 autistic children and adolescents. Using a t-test, we found a significant difference (p <0.001) between full-scale IQ and adaptive behavior scores, indicating that our participants' adaptive behavior scores were lower than would be expected given their full-scale IQ. Using a linear regression, we investigated whether motor skills predicted adaptive behavior in autistic children and adolescents and found that motor skills scores were associated with adaptive behavior scores (p = 0.022). To further investigate these associations, we used another linear regression to examine how individual components of IQ and motor skills predicted adaptive behavior scores in autistic children and adolescents. Our results indicated that manual dexterity scores were associated with adaptive behavior scores (p = 0.036). These findings clearly illustrate the need for further understanding of autistic individuals' difficulties with adaptive behavior and the potential role of motor skill difficulties that may underlie these difficulties. LAY SUMMARY: Autistic children have lower adaptive behavior scores (e.g., daily living skills, social skills, communication) than intelligence scores (e.g., verbal and perceptual skills) along with difficulties with motor skills. Motor skills may explain the gap between adaptive behavior and intelligence. We found motor skills were associated with adaptive behavior in autistic children and adolescents. In particular, hand coordination was associated with adaptive behavior. We need to better understand how autistic individuals' motor skills impact their adaptive behavior to provide effective supports.

Learning low-dimensional generalizable natural features from retina using a U-net.

Much of sensory neuroscience focuses on presenting stimuli that are chosen by the experimenter because they are parametric and easy to sample and are thought to be behaviorally relevant to the organism. However, it is not generally known what these relevant features are in complex, natural scenes. This work focuses on using the retinal encoding of natural movies to determine the presumably behaviorally-relevant features that the brain represents. It is prohibitive to parameterize a natural movie and its respective retinal encoding fully. We use time within a natural movie as a proxy for the whole suite of features evolving across the scene. We then use a task-agnostic deep architecture, an encoder-decoder, to model the retinal encoding process and characterize its representation of "time in the natural scene" in a compressed latent space. In our end-to-end training, an encoder learns a compressed latent representation from a large population of salamander retinal ganglion cells responding to natural movies, while a decoder samples from this compressed latent space to generate the appropriate future movie frame. By comparing latent representations of retinal activity from three movies, we find that the retina has a generalizable encoding for time in the natural scene: the precise, low-dimensional representation of time learned from one movie can be used to represent time in a different movie, with up to 17 ms resolution. We then show that static textures and velocity features of a natural movie are synergistic. The retina simultaneously encodes both to establishes a generalizable, low-dimensional representation of time in the natural scene.

Inferring couplings in networks across order-disorder phase transitions.

Statistical inference is central to many scientific endeavors, yet how it works remains unresolved. Answering this requires a quantitative understanding of the intrinsic interplay between statistical models, inference methods, and the structure in the data. To this end, we characterize the efficacy of direct coupling analysis (DCA) - a highly successful method for analyzing amino acid sequence data-in inferring pairwise interactions from samples of ferromagnetic Ising models on random graphs. Our approach allows for physically motivated exploration of qualitatively distinct data regimes separated by phase transitions. We show that inference quality depends strongly on the nature of data-generating distributions: optimal accuracy occurs at an intermediate temperature where the detrimental effects from macroscopic order and thermal noise are minimal. Importantly our results indicate that DCA does not always outperform its local-statistics-based predecessors; while DCA excels at low temperatures, it becomes inferior to simple correlation thresholding at virtually all temperatures when data are limited. Our findings offer insights into the regime in which DCA operates so successfully, and more broadly, how inference interacts with the structure in the data.

A Pandemic Instrument Can Start Turning Collective Problems into Collective Solutions by Governing the Common-Pool Resource of Antimicrobial Effectiveness.

To address the complex challenge of global antimicrobial resistance (AMR), a pandemic treaty should include mechanisms that 1) equitably address the access gap for antimicrobials, diagnostic technologies, and alternative therapies; 2) equitably conserve antimicrobials to sustain effectiveness and access across time and space; 3) equitably finance the investment, discovery, development, and distribution of new technologies; and 4) equitably finance and establish greater upstream and midstream infection prevention measures globally. Biodiversity, climate, and nuclear governance offer lessons for addressing these challenges.

Restarting Neglected Tropical Diseases Programs in West Africa during the COVID-19 Pandemic: Lessons Learned and Best Practices.

Countries across West Africa began reporting COVID-19 cases in February 2020. By March, the pandemic began disrupting activities to control and eliminate neglected tropical diseases (NTDs) as health ministries ramped up COVID-19-related policies and prevention measures. This was followed by interim guidance from the WHO in April 2020 to temporarily pause mass drug administration (MDA) and community-based surveys for NTDs. While the pandemic was quickly evolving worldwide, in most of West Africa, governments and health ministries took quick action to implement mitigation measures to slow the spread. The U.S. Agency for International Development's (USAID) Act to End NTDs | West program (Act | West) began liaising with national NTD programs in April 2020 to pave a path toward the eventual resumption of activities. This process consisted of first collecting and analyzing COVID-19 epidemiological data, policies, and standard operating procedures across the program's 11 countries. The program then developed an NTD activity restart matrix that compiled essential considerations to restart activities. By December 2020, all 11 countries in Act | West safely restarted MDA and certain surveys to monitor NTD prevalence or intervention impact. Preliminary results show satisfactory MDA program coverage, meaning that enough people are taking the medicine to keep countries on track toward achieving their NTD disease control and elimination goals, and community perceptions have remained positive. The purpose of this article is to share the lessons and best practices that have emerged from the adoption of strategies to limit the spread of the novel coronavirus during MDA and other program activities.

Rational Design of an Antimicrobial Peptide Based on Structural Insight into the Interaction of Pseudomonas aeruginosa Initiation Factor 1 with Its Cognate 30S Ribosomal Subunit.

Bacterial infections continue to represent a major worldwide health hazard following the emergence of drug-resistant pathogenic strains. Pseudomonas aeruginosa is an opportunistic pathogen causing nosocomial infections with increased morbidity and mortality. The increasing antibiotic resistance in P. aeruginosa has led to an unmet need for discovery of new antibiotic candidates. Bacterial protein synthesis is an essential metabolic process and a validated target for antibiotic development; however, the precise structural mechanism in P. aeruginosa remains unknown. In this work, the interaction of P. aeruginosa initiation factor 1 (IF1) with the 30S ribosomal subunit was studied by NMR, which enabled us to construct a structure of IF1-bound 30S complex. A short α-helix in IF1 was found to be critical for IF1 ribosomal binding and function. A peptide derived from this α-helix was tested and displayed a high ability to inhibit bacterial growth. These results provide a clue for rational design of new antimicrobials.