Hair tourniquet syndrome: A retrospective study.

OBJECTIVE: Hair thread tourniquet syndrome (HTS) is a pediatric condition in which human hair or synthetic fiber encircles and strangulates a body appendage causing tissue necrosis. Few epidemiologic studies have been done. Our objective was to better define the demographics, clinical features, and predisposing factors for this condition. MATERIALS AND METHODS: Medical records of all infants up to 1 year old seen in the orthopedic emergency department of Galilee Medical Center were searched for the diagnosis of HTS or its ICD equivalent. RESULTS: Forty-one cases of hair tourniquet syndrome (HTS) were reviewed. Most cases (68%) occurred during the winter months (December to February). There were no reports between June to August (summer). The median age was 4 months and the male-to-female ratio was approximately 2:5. Toes were significantly more involved than fingers (97.5%) and the 3rd toe was the most affected (58%). Nine patients (21.9%) had more than one toe affected and only one case reported finger involvement. CONCLUSIONS: HTS in our population is a phenomenon that seems to occur mostly in winter. Infants between 3 and 5 months are at greater risk. Toes are more affected than fingers. The most involved toes are the 3rd and 4th.

Outbreak Size Distribution in Stochastic Epidemic Models.

Motivated by recent epidemic outbreaks, including those of COVID-19, we solve the canonical problem of calculating the dynamics and likelihood of extensive outbreaks in a population within a large class of stochastic epidemic models with demographic noise, including the susceptible-infected-recovered (SIR) model and its general extensions. In the limit of large populations, we compute the probability distribution for all extensive outbreaks, including those that entail unusually large or small (extreme) proportions of the population infected. Our approach reveals that, unlike other well-known examples of rare events occurring in discrete-state stochastic systems, the statistics of extreme outbreaks emanate from a full continuum of Hamiltonian paths, each satisfying unique boundary conditions with a conserved probability flux.

Phase Transition in a Non-Markovian Animal Exploration Model with Preferential Returns.

We study a non-Markovian and nonstationary model of animal mobility incorporating both exploration and memory in the form of preferential returns. Exact results for the probability of visiting a given number of sites are derived and a practical WKB approximation to treat the nonstationary problem is developed. A mean-field version of this model, first suggested by Song et al., [Modelling the scaling properties of human mobility, Nat. Phys. 6, 818 (2010)NPAHAX1745-247310.1038/nphys1760] was shown to well describe human movement data. We show that our generalized model adequately describes empirical movement data of Egyptian fruit bats (Rousettus aegyptiacus) when accounting for interindividual variation in the population. We also study the probability of visiting any site a given number of times and derive a mean-field equation. Our analysis yields a remarkable phase transition occurring at preferential returns which scale linearly with past visits. Following empirical evidence, we suggest that this phase transition reflects a trade-off between extensive and intensive foraging modes.

[HAIR TOURNIQUET SYNDROME - A DISCREPANCY BETWEEN INCIDENCE AND DOCUMENTATION AND A DISCREPANCY BETWEEN COMMON TERMINOLOGY AND THE ICD].

INTRODUCTION: Hair tourniquet syndrome, AKA hair thread tourniquet or hair strangulation occurs among infants. A human hair or a thread strangulates a body appendage, resulting in obstruction of blood and lymph flow. If not recognized early it may cause tissue necrosis and rarely, require amputation. AIMS: Revealing the discrepancy between incidence and documentation in practice. Understanding the challenges standing in the way of the clinician while admitting a patient. METHODS: A retrospective study. The hospital's archive was searched for the period between the years 2008 to 2018. According to the ICD9 system this phenomenon is termed "external constriction caused by hair". Upon questioning, doctors had admitted having trouble finding the right diagnosis while digitally documenting a patient. The archive was searched twice - firstly, by the correct ICD9 code. Secondly, a general search was performed reviewing all 0-1 year-old patients' files. RESULTS: By researching the ICD9 code, 7 files were found. On the second search, 41 files were found, among them only 5 files were documented properly according to the ICD9 system. CONCLUSIONS: The majority (87.8%) of patients suffered from hair strangulation syndrome were not documented properly. Lack of documentation is a result of the digital difficulty finding the right diagnosis. DISCUSSION: Hair strangulation syndrome is not as rare as may be concluded basing on existing data. Clinicians must include it in the differential diagnosis when admitting a patient with the relevant symptoms or an agitated infant with no clear cause. Adjusting the digital systems in Israeli hospitals should be considered.

Population Dynamics in a Changing Environment: Random versus Periodic Switching.

Environmental changes greatly influence the evolution of populations. Here, we study the dynamics of a population of two strains, one growing slightly faster than the other, competing for resources in a time-varying binary environment modeled by a carrying capacity switching either randomly or periodically between states of abundance and scarcity. The population dynamics is characterized by demographic noise (birth and death events) coupled to a varying environment. We elucidate the similarities and differences of the evolution subject to a stochastically and periodically varying environment. Importantly, the population size distribution is generally found to be broader under intermediate and fast random switching than under periodic variations, which results in markedly different asymptotic behaviors between the fixation probability of random and periodic switching. We also determine the detailed conditions under which the fixation probability of the slow strain is maximal.

Degree Dispersion Increases the Rate of Rare Events in Population Networks.

There is great interest in predicting rare and extreme events in complex systems, and in particular, understanding the role of network topology in facilitating such events. In this Letter, we show that degree dispersion-the fact that the number of local connections in networks varies broadly-increases the probability of large, rare fluctuations in population networks generically. We perform explicit calculations for two canonical and distinct classes of rare events: network extinction and switching. When the distance to threshold is held constant, and hence stochastic effects are fairly compared among networks, we show that there is a universal, exponential increase in the rate of rare events proportional to the variance of a network's degree distribution over its mean squared.

Stochastic Model of Breakdown Nucleation under Intense Electric Fields.

A plastic response due to dislocation activity under intense electric fields is proposed as a source of breakdown. A model is formulated based on stochastic multiplication and arrest under the stress generated by the field. A critical transition in the dislocation population is suggested as the cause of protrusion formation leading to subsequent arcing. The model is studied using Monte Carlo simulations and theoretical analysis, yielding a simplified dependence of the breakdown rates on the electric field. These agree with experimental observations of field and temperature breakdown dependencies.

A new minimally invasive surgical technique for medial retinaculum repair following traumatic patellar dislocation.

A new surgical method is introduced offering a less invasive approach to reattach the medial retinaculum following acute patellar dislocation. This retrospective analysis comprised 12 cases of medial retinacular repair in 10 patients. The surgical technique achieved reinforced reattachment of the torn region of the medial retinaculum for improved patellar support and stabilization. During follow-up, no recurrent patellar dislocations occurred, except where one patient reported a subjective feeling of patellar dislocation. The average Kujala score for our sample group after 2 years was 89.2. A plethora of methods are described in the literature to repair a tear to the medial patellofemoral ligament, which attaches at the superomedial patella. However, it is our contention that traumatic patellar dislocation invariably results in osteochondral avulsion at the inferomedial patella, refuting medial patellofemoral ligament involvement, and, rather, implicating the inferior aspect of the deep layer of medial retinaculum. Our surgical technique enables stable fixation of the region, decreasing the rate of recurrent dislocations. No grafts are used, permitting tendinous and ligamentous anatomy to remain intact. We further postulate that performing a CT examination preoperatively may reduce time between diagnosis and surgery, in addition to locating fracture sites more precisely.

Genetic Toggle Switch in the Absence of Cooperative Binding: Exact Results.

We present an analytical treatment of a genetic switch model consisting of two mutually inhibiting genes operating without cooperative binding of the corresponding transcription factors. Previous studies have numerically shown that these systems can exhibit bimodal dynamics without possessing two stable fixed points at the deterministic level. We analytically show that bimodality is induced by the noise and find the critical repression strength that controls a transition between the bimodal and nonbimodal regimes. We also identify characteristic polynomial scaling laws of the mean switching time between bimodal states. These results, independent of the model under study, reveal essential differences between these systems and systems with cooperative binding, where there is no critical threshold for bimodality and the mean switching time scales exponentially with the system size.

Cytokine levels (IL-4, IL-6, IL-8 and TGFß) as potential biomarkers of systemic inflammatory response in trauma patients.

PURPOSE: Much research is now being conducted in order to understand the role of cytokines in the development of the inflammatory response following trauma. The purpose of this study was to evaluate whether serum levels of certain cytokines, measured immediately after initial injury, can be used as potential biomarkers for predicting the development and the degree of severity of the systemic inflammatory response (SIRS) in patients with moderate and severe trauma. METHODS: We conducted a prospective study with 71 individuals of whom 13 (18.3 %) were healthy controls and 58 (81.7 %) were traumatized orthopaedic patients who were categorized into two groups: 31 (43.6 %) with moderate injuries and 27 (38.1 %) patients with severe orthopaedic trauma. Thirty cc of heparinized blood were drawn from each individual within a few hours after the injury. Serum levels of pro-inflammatory, regulatory and anti-inflammatory cytokines were measured in each individual participant. RESULTS: High levels of pro-inflammatory cytokines IL-1ß,-6,-8,-12, tumour necrosis factor alpha and interferon gamma were found in all injured patients compared to healthy controls. Only IL-6 and IL-8 were significantly higher in the injured patients. Levels of the regulatory cytokines, transformed growth factor beta (TGF-ß) and IL-10 were higher in the injured patients, but significant only for TGF-ß. Levels of IL-4 were significantly lower in the injured groups as compared to the controls. CONCLUSIONS: Secretion of large amounts of pro-inflammatory cytokines and decreased level of anti-inflammatory cytokines during the acute phase of trauma may lead to the development of systemic inflammatory response syndrome (SIRS) in unstable polytraumatized patients. SIRS may result in life threatening conditions as acute respiratory distress syndrome (ARDS) and multiple organ failure (MOF). High levels of IL-6, IL-8, TGFß and low levels of IL-4 were found to be reliable markers for the existence of immune reactivity in trauma patients. More research is needed to study pattern of cytokine levels along the acute period of injury, after surgical interventions and during recovery.

Population dynamics in a time-varying environment with fat-tailed correlations.

Temporal environmental noise (EN) is a prevalent natural phenomenon that controls population and community dynamics, shaping the destiny of biological species and genetic types. Conventional theoretical models often depict EN as a Markovian process with an exponential distribution of correlation times, resulting in two distinct qualitative dynamical categories: quenched (long environmental timescales) and annealed (short environmental timescales). However, numerous empirical studies demonstrate a fat-tailed decay of correlation times. Here we study the consequences of power-law correlated EN on the dynamics of isolated and competing populations. We analyze the intermediate region that lies between the quenched and annealed regimes and show that it can widen indefinitely. Within this region, dynamics is primarily driven by rare, yet not exceedingly rare, long periods of almost-steady environmental conditions. For an isolated population, the time to extinction in this region exhibits a power-law scaling with the logarithm of the abundance and also a nonmonotonic dependence on the spectral exponent.

DNA looping increases the range of bistability in a stochastic model of the lac genetic switch.

Conditions and parameters affecting the range of bistability of the lac genetic switch in Escherichia coli are examined for a model which includes DNA looping interactions with the lac repressor and a lactose analogue. This stochastic gene-mRNA-protein model of the lac switch describes DNA looping using a third transcriptional state. We exploit the fast bursting dynamics of mRNA by combining a novel geometric burst extension with the finite state projection method. This limits the number of protein/mRNA states, allowing for an accelerated search of the model's parameter space. We evaluate how the addition of the third state changes the bistability properties of the model and find a critical region of parameter space where the phenotypic switching occurs in a range seen in single molecule fluorescence studies. Stochastic simulations show induction in the looping model is preceded by a rare complete dissociation of the loop followed by an immediate burst of mRNA rather than a slower build up of mRNA as in the two-state model. The overall effect of the looped state is to allow for faster switching times while at the same time further differentiating the uninduced and induced phenotypes. Furthermore, the kinetic parameters are consistent with free energies derived from thermodynamic studies suggesting that this minimal model of DNA looping could have a broader range of application.

Cooperation dilemma in finite populations under fluctuating environments.

We present a novel approach allowing the study of rare events like fixation under fluctuating environments, modeled as extrinsic noise, in evolutionary processes characterized by the dominance of one species. Our treatment consists of mapping the system onto an auxiliary model, exhibiting metastable species coexistence, that can be analyzed semiclassically. This approach enables us to study the interplay between extrinsic and demographic noise on the statistics of interest. We illustrate our theory by considering the paradigmatic prisoner's dilemma game, whose evolution is described by the probability that cooperators fixate the population and replace all defectors. We analytically and numerically demonstrate that extrinsic noise may drastically enhance the cooperation fixation probability and even change its functional dependence on the population size. These results, which generalize earlier works in population genetics, indicate that extrinsic noise may help sustain and promote a much higher level of cooperation than static settings.

Extrinsic noise driven phenotype switching in a self-regulating gene.

Analysis of complex gene regulation networks gives rise to a landscape of metastable phenotypic states for cells. Heterogeneity within a population arises due to infrequent noise-driven transitions of individual cells between nearby metastable states. While most previous works have focused on the role of intrinsic fluctuations in driving such transitions, in this Letter we investigate the role of extrinsic fluctuations. First, we develop an analytical framework to study the combined effect of intrinsic and extrinsic noise on a toy model of a Boolean regulated genetic switch. We then extend these ideas to a more biologically relevant model with a Hill-like regulatory function. Employing our theory and Monte Carlo simulations, we show that extrinsic noise can significantly alter the lifetimes of the phenotypic states and may fundamentally change the escape mechanism. Finally, our theory can be readily generalized to more complex decision making networks in biology.

Estimating emergency department crowding with stochastic population models.

Environments such as shopping malls, airports, or hospital emergency-departments often experience crowding, with many people simultaneously requesting service. Crowding highly fluctuates, with sudden overcrowding "spikes". Past research has either focused on average behavior, used context-specific models with a large number of parameters, or machine-learning models that are hard to interpret. Here we show that a stochastic population model, previously applied to a broad range of natural phenomena, can aptly describe hospital emergency-department crowding. We test the model using data from five-year minute-by-minute emergency-department records. The model provides reliable forecasting of the crowding distribution. Overcrowding is highly sensitive to the patient arrival-flux and length-of-stay: a 10% increase in arrivals triples the probability of overcrowding events. Expediting patient exit-rate to shorten the typical length-of-stay by just 20 minutes (8.5%) cuts the probability of severe overcrowding events by 50%. Such forecasting is critical in prevention and mitigation of breakdown events. Our results demonstrate that despite its high volatility, crowding follows a dynamic behavior common to many systems in nature.

Metastability and anomalous fixation in evolutionary games on scale-free networks.

We study the influence of complex graphs on the metastability and fixation properties of a set of evolutionary processes. In the framework of evolutionary game theory, where the fitness and selection are frequency dependent and vary with the population composition, we analyze the dynamics of snowdrift games (characterized by a metastable coexistence state) on scale-free networks. Using an effective diffusion theory in the weak selection limit, we demonstrate how the scale-free structure affects the system's metastable state and leads to anomalous fixation. In particular, we analytically and numerically show that the probability and mean time of fixation are characterized by stretched-exponential behaviors with exponents depending on the network's degree distribution.

Effect of weak rotation on large-scale circulation cessations in turbulent convection.

We investigate the effect of weak rotation on the large-scale circulation (LSC) of turbulent Rayleigh-Bénard convection, using the theory for cessations in a low-dimensional stochastic model of the flow previously studied. We determine the cessation frequency of the LSC as a function of rotation, and calculate the statistics of the amplitude and azimuthal velocity fluctuations of the LSC as a function of the rotation rate for different Rayleigh numbers. Furthermore, we show that the tails of the reorientation PDF remain unchanged for rotating systems, while the distribution of the LSC amplitude and correspondingly the cessation frequency are strongly affected by rotation. Our results are in close agreement with experimental observations.

Susceptible-infected-susceptible model of disease extinction on heterogeneous directed population networks.

Understanding the spread of diseases through complex networks is of great interest where realistic, heterogeneous contact patterns play a crucial role in the spread. Most works have focused on mean-field behavior-quantifying how contact patterns affect the emergence and stability of (meta)stable endemic states in networks. On the other hand, much less is known about longer time scale dynamics, such as disease extinction, whereby inherent process stochasticity and contact heterogeneity interact to produce large fluctuations that result in the spontaneous clearance of infection. Here we show that heterogeneity in both susceptibility and infectiousness (incoming and outgoing degree, respectively) has a nontrivial effect on extinction in directed contact networks, both speeding up and slowing down extinction rates depending on the relative proportion of such edges in a network, and on whether the heterogeneities in the incoming and outgoing degrees are correlated or anticorrelated. In particular, we show that weak anticorrelated heterogeneity can increase the disease stability, whereas strong heterogeneity gives rise to markedly different results for correlated and anticorrelated heterogeneous networks. All analytical results are corroborated through various numerical schemes including network Monte Carlo simulations.

Fluctuations and first-passage properties of systems of Brownian particles with reset.

We study, analytically and numerically, stationary fluctuations in two models involving N Brownian particles undergoing stochastic resetting in one dimension. We start with the well-known reset model where the particles reset to the origin independently (model A). Then we introduce nonlocal interparticle correlations by postulating that only the particle farthest from the origin can be reset to the origin (model B). At long times, models A and B approach nonequilibrium steady states. In the limit of N→∞, the steady-state particle density in model A has an infinite support, whereas in model B, it has a compact support, like the recently studied Brownian bees model. A finite system radius, which scales at large N as lnN, appears in model A when N is finite. In both models, we study stationary fluctuations of the center of mass of the system and of the radius of the system due to the random character of the Brownian motion and of the resetting events. In model A, we determine exact distributions of these two quantities. The variance of the center of mass for both models scales as 1/N. The variance of the radius is independent of N in model A and exhibits an unusual scaling (lnN)/N in model B. The latter scaling is intimately related to the 1/f noise in the radius autocorrelation. Finally, we evaluate the mean first-passage time (MFPT) to a distant target in model A, model B, and the Brownian bees model. For model A, we obtain an exact asymptotic expression for the MFPT which scales as 1/N. For model B and the Brownian bees model, we propose a sharp upper bound for the MFPT. The bound assumes an evaporation scenario, where the first passage requires multiple attempts of a single particle, which breaks away from the rest of the particles, to reach the target. The resulting MFPT for model B and the Brownian bees model scales exponentially with sqrt[N]. We verify this bound by performing highly efficient weighted-ensemble simulations of the first passage in model B.

Big-data approaches lead to an increased understanding of the ecology of animal movement.

Understanding animal movement is essential to elucidate how animals interact, survive, and thrive in a changing world. Recent technological advances in data collection and management have transformed our understanding of animal "movement ecology" (the integrated study of organismal movement), creating a big-data discipline that benefits from rapid, cost-effective generation of large amounts of data on movements of animals in the wild. These high-throughput wildlife tracking systems now allow more thorough investigation of variation among individuals and species across space and time, the nature of biological interactions, and behavioral responses to the environment. Movement ecology is rapidly expanding scientific frontiers through large interdisciplinary and collaborative frameworks, providing improved opportunities for conservation and insights into the movements of wild animals, and their causes and consequences.