Invasion and interaction determine population composition in an open evolving ecological system

It is well-known that interactions between species determine the population composition in an ecosystem. Conventional studies have focused on fixed population structures to reveal how interactions shape population compositions. However, interaction structures are not fixed but change over time due to invasions. Thus, invasion and interaction play an important role in shaping communities. Despite its importance, however, the interplay between invasion and interaction has not been well explored. Here, we investigate how invasion affects the population composition with interactions in open evolving ecological systems considering generalized Lotka-Volterra-type dynamics. Our results show that the system has two distinct regimes. One is characterized by low diversity with abrupt changes of dominant species in time, appearing when the interaction between species is strong and invasion slowly occurs. On the other hand, frequent invasions can induce higher diversity with slow changes in abundances despite strong interactions. It is because invasion happens before the system reaches its equilibrium, which drags the system from its equilibrium all the time. All species have similar abundances in this regime, which implies that fast invasion induces regime shift. Therefore, whether invasion or interaction dominates determines the population composition.

Micropyramidal Flexible Ion Gel Sensor for Multianalyte Discrimination and Strain Compensation

A highly sensitive and flexible gas sensor that can detect a wide range of chemicals is crucial for wearable applications. However, conventional single resistance-based flexible sensors face challenges in maintaining chemical sensitivity under mechanical stress and can be affected by interfering gases. This study presents a versatile approach for fabricating a micropyramidal flexible ion gel sensor, which accomplishes sub-ppm sensitivity (<80 ppb) at room temperature and discrimination capability between various analytes, including toluene, isobutylene, ammonia, ethanol, and humidity. The discrimination accuracy of our flexible sensor is as high as 95.86%, enhanced by using machine learning-based algorithms. Moreover, its sensing capability remains stable with only a 2.09% change from the flat state to a 6.5 mm bending radius, further amplifying its universal usage for wearable chemical sensing. Therefore, we envision that a micropyramidal flexible ion gel sensor platform assisted by machine learning-based algorithms will provide a new strategy toward next-generation wearable sensing technology.

Degree distributions under general node removal: Power-law or Poisson?

Perturbations made to networked systems may result in partial structural loss, such as a blackout in a power-grid system. Investigating the resulting disturbance in network properties is quintessential to understand real networks in action. The removal of nodes is a representative disturbance, but previous studies are seemingly contrasting about its effect on arguably the most fundamental network statistic, the degree distribution. The key question is about the functional form of the degree distributions that can be altered during node removal or sampling. The functional form is decisive in the remaining subnetwork's static and dynamical properties. In this work, we clarify the situation by utilizing the relative entropies with respect to the reference distributions in the Poisson and power-law form, to quantify the distance between the subnetwork's degree distribution and either of the reference distributions. Introducing general sequential node removal processes with continuously different levels of hub protection to encompass a series of scenarios including uniform random removal and preferred or protective (i.e., biased random) removal of the hub, we classify the altered degree distributions starting from various power-law forms by comparing two relative entropy values. From the extensive investigation in various scenarios based on direct node-removal simulations and by solving the rate equation of degree distributions, we discover in the parameter space two distinct regimes, one where the degree distribution is closer to the power-law reference distribution and the other closer to the Poisson distribution.

Power-grid stability predictions using transferable machine learning

Complex network analyses have provided clues to improve power-grid stability with the help of numerical models. The high computational cost of numerical simulations, however, has inhibited the approach, especially when it deals with the dynamic properties of power grids such as frequency synchronization. In this study, we investigate machine learning techniques to estimate the stability of power-grid synchronization. We test three different machine learning algorithms-random forest, support vector machine, and artificial neural network-training them with two different types of synthetic power grids consisting of homogeneous and heterogeneous input-power distribution, respectively. We find that the three machine learning models better predict the synchronization stability of power-grid nodes when they are trained with the heterogeneous input-power distribution rather than the homogeneous one. With the real-world power grids of Great Britain, Spain, France, and Germany, we also demonstrate that the machine learning algorithms trained on synthetic power grids are transferable to the stability prediction of the real-world power grids, which implies the prospective applicability of machine learning techniques on power-grid studies.

Mask-induced dermatoses during the COVID-19 pandemic: a questionnaire-based study in 12 Korean hospitals

BACKGROUND

During the coronavirus disease 2019 (COVID-19) pandemic, various adverse skin reactions to long-term mask wearing have been reported.

AIM

To assess the clinical features of mask-induced dermatoses and to recommend prevention and treatment options.

METHODS

From April to August 2020, questionnaires including topics such as demographic information, pre-existing skin disorders, reported mask-related symptoms, daily mask-wearing duration and frequency, types of masks used and whether the participant was a healthcare worker, were distributed to patients in 12 hospitals. Dermatologists assessed skin lesions, confirmed diagnosis and recorded treatments.

RESULTS

Itchiness was the most frequent symptom, mostly affecting the cheeks. The most common skin disease was new-onset contact dermatitis (33.94%), followed by new-onset acne (16.97%) and worsening of pre-existing acne (16.97%). Daily wearing of masks was significantly (P = 0.02) associated with new-onset contact dermatitis. More than half of patients with pre-existing skin problems experienced disease worsening while wearing masks. Longer duration of wearing (> 6 h/day, P = 0.04) and use of cotton masks (P < 0.001) significantly increased acne flare-up. Healthcare workers had a higher incidence of skin disease. Skin lesions were generally mild and well tolerated with topical treatment. The study had some limitations: the effect of seasonal characteristics and other risk factors were not assessed, and the patients were visiting dermatological clinics and had interest in their skin status, thus, there may have been selection bias.

CONCLUSION

Mask-induced/-triggered dermatoses contribute to increase the dermatological burden during the pandemic.

Deep learning for bias correction of MJO prediction

Producing accurate weather prediction beyond two weeks is an urgent challenge due to its ever-increasing socioeconomic value. The Madden-Julian Oscillation (MJO), a planetary-scale tropical convective system, serves as a primary source of global subseasonal (i.e., targeting three to four weeks) predictability. During the past decades, operational forecasting systems have improved substantially, while the MJO prediction skill has not yet reached its potential predictability, partly due to the systematic errors caused by imperfect numerical models. Here, to improve the MJO prediction skill, we blend the state-of-the-art dynamical forecasts and observations with a Deep Learning bias correction method. With Deep Learning bias correction, multi-model forecast errors in MJO amplitude and phase averaged over four weeks are significantly reduced by about 90% and 77%, respectively. Most models show the greatest improvement for MJO events starting from the Indian Ocean and crossing the Maritime Continent.

Synchronization of active rotators interacting with environment

Multiple organs in a living system respond to environmental changes, and the signals from the organs regulate the physiological environment. Inspired by this biological feedback, we propose a simple autonomous system of active rotators to explain how multiple units are synchronized under a fluctuating environment. We find that the feedback via an environment can entrain rotators to have synchronous phases for specific conditions. This mechanism is markedly different from the simple entrainment by a common oscillatory external stimulus that is not interacting with systems. We theoretically examine how the phase synchronization depends on the interaction strength between rotators and environment. Furthermore, we successfully demonstrate the proposed model by realizing an analog electric circuit with microelectronic devices. This bioinspired platform can be used as a sensor for monitoring varying environments and as a controller for amplifying signals by their feedback-induced synchronization.

On structural and dynamical factors determining the integrated basin instability of power-grid nodes

In electric power systems delivering alternating current, it is essential to maintain its synchrony of the phase with the rated frequency. The synchronization stability that quantifies how well the power-grid system recovers its synchrony against perturbation depends on various factors. As an intrinsic factor that we can design and control, the transmission capacity of the power grid affects the synchronization stability. Therefore, the transition pattern of the synchronization stability with the different levels of transmission capacity against external perturbation provides the stereoscopic perspective to understand the synchronization behavior of power grids. In this study, we extensively investigate the factors affecting the synchronization stability transition by using the concept of basin stability as a function of the transmission capacity. For a systematic approach, we introduce the integrated basin instability, which literally adds up the instability values as the transmission capacity increases. We first take simple 5-node motifs as a case study of building blocks of power grids, and a more realistic IEEE 24-bus model to highlight the complexity of decisive factors. We find that both structural properties such as gate keepers in network topology and dynamical properties such as large power input/output at nodes cause synchronization instability. The results suggest that evenly distributed power generation and avoidance of bottlenecks can improve the overall synchronization stability of power-grid systems.

In-depth data on the network structure and hourly activity of the Central Chilean power grid

Network science enables us to improve the performance of complex systems such as traffic, communication, and power grids. To do so, it is necessary to use a well-constructed flawless network dataset associated with the system of interest. In this study, we present the dataset of the Chilean power grid. We harmonized data from three diverse sources to generate a unified dataset. Through an intensive review on the raw data, we filter out inconsistent errors and unrealistic faults, making the data more trustworthy. In contrast to other network dataset for power grids, we especially focus on preserving the physical structure of nodes' connection incorporating the 'tap' structure. As a result, we provide three different versions of the dataset: 'with-tap', 'without-tap', and 'reduced versions'. Along with structure, we incorporate various attributes of the nodes and edges such as the geo-coordinates, voltage of transmission lines, and the time series data of generation or consumption. These data are useful for network scientists to analyze the performance and dynamic stability of power grids.

Silver nanoparticles induce Egr-1-dependent psoriasin expression via the ERK and p38 pathways

BACKGROUND

Silver nanoparticles (Ag-NPs) can prevent bacterial infection and improve cutaneous wound healing owing to their antimicrobial activity. However, the mechanism of their antimicrobial activity is poorly understood.

AIM

To determine the mechanistic relationship between Ag-NP treatment and expression of psoriasin.

METHODS

Human epidermal keratinocytes, neonatal (HEKn) were used. Psoriasin mRNA expression was measured by reverse transcription PCR and real-time PCR. Western blotting was performed to verify expression of early growth response-1 (Egr-1) and psoriasin, and phosphorylation of mitogen-activated protein kinase (MAPK). Psoriasin promoter activity by Egr-1 was detected by a luciferase assay.

RESULTS

Treatment of HEKn with Ag-NPs induced psoriasin mRNA and protein expression. Upregulation of psoriasin promoter activity was also observed in the luciferase assay. Ag-NPs increased Egr-1 expression, promoter activity and nuclear translocation in HEKn. Psoriasin luciferase activity was increased in HEKn transfected with Egr-1 pcDNA 3.1. Ag-NPs activated MAPK pathways including the extracellular signal-regulated kinase (ERK), p38, and c-Jun-N-terminal kinase (JNK) pathways. The upregulation of Egr-1 expression by Ag-NP stimulation was inhibited by ERK and p38 inhibitors, but not by a JNK inhibitor. Psoriasin expression was reduced in Egr-1 small interfering RNA-transfected HEKn.

CONCLUSIONS

Ag-NP treatment induces upregulation of psoriasin expression through Egr-1 expression. We suggest that the ERK and p38 pathways are involved in Egr-1-dependent psoriasin expression.

Effect of Dietary sugar beet pulp supplementation on growth performance, nutrient digestibility, fecal Microflora, blood profiles and Diarrhea incidence in weaning pigs

Background

In 2006, the European Union (EU) has decided to forbid use of antibiotics as growth promoters. Although many researches had been conducted about fiber source as alternatives of antibiotics, there are still lack of reports in the literature about the optimum level of sugar beet pulp supplementation, affecting growth performance and nutrient digestibility in weaning pigs. Therefore, different level of sugar beet pulp was added to diets to determine the effects of sugar beet pulp supplementation on growth performance, nutrient digestibility, fecal microflora, blood profile and incidence of diarrhea in weaning pigs.

Methods

A total of 200 weaning pigs [(Yorkshire × Landrace) × Duroc], averaging 9.01 ± 1.389 kg of initial body weight were, allotted to 5 treatments in a randomized complete block (RCB) design. Each treatment was composed of 4 replicates with 10 pigs per pen. The treatments were control treatment: Corn-SBM basal diet + ZnO (phase 1: 0.05%; phase 2; 0.03%) and four different levels of sugar beet pulp were supplemented in Corn-SBM basal diet (3, 6, 9 or 12%). Two phase feeding programs (phase 1: 1–2 weeks; phase 2: 3–5 weeks) were used for 5 week of growth trial.

Results

In feeding trial, there were no significant differences in growth performance and incidence of diarrhea among treatments. The E.coli counts were not significantly different among dietary treatments but linear response was observed in Lactobacillus counts as sugar beet pulp supplementation increased (P < 0.05). In addition, IGF-1, IgA and IgG were not affected by dietary treatments. However, the BUN concentration was decreased when pigs were fed the treatments of diets with SBP compared to that of control treatment (P < 0.05). In nutrient digestibility, crude fiber and NDF digestibilities were improved as the sugar beet pulp increased (P < 0.05). However, digestibilities of crude ash, crude fat, crude fiber and nitrogen retention were not affected by dietary sugar beet pulp levels.

Conclusion

This experiment demonstrated that sugar beet pulp can be supplemented in weaning pigs’ diet instead of ZnO to prevent postweaning diarrhea without any detrimental effect on growth performance.

Various levels of copra meal supplementation with β-Mannanase on growth performance, blood profile, nutrient digestibility, pork quality and economical analysis in growing-finishing pigs

BACKGROUND

To reduce use of main feed ingredient like corn, soy bean meal (SBM) and wheat, alternative ingredients has been studied like copra meal (CM). Production amount of CM which has been high makes CM to be an alternative feed stuff. However, low digestibility on AA and low energy content by high fiber content can be an obstacle for using CM. This experiment was conducted to evaluate the effects of CM supplementation with β-mannanase on growth performance, blood profile, nutrient digestibility, pork quality and economic analysis in growing-finishing pigs.

METHODS

A total of 100 growing pigs ([Yorkshire × Landrace] × Duroc) averaging 31.22 ± 2.04 kg body weight were allotted to 5 different treatments by weight and sex in a randomized complete block (RCB) design in 5 replicate with 4 pigs per pen. Treatments were 1) Control (corn-SBM based diet + 0.1% of β-mannanase (800 IU)), 2) CM10 (10% copra meal + 0.1% β-mannanase (800 IU)), 3) CM15 (15% copra meal + 0.1% β-mannanase (800 IU)), 4) CM20 (20% copra meal + 0.1% β-mannanase (800 IU)) and 5) CM25 (25% copra meal + 0.1% β-mannanase (800 IU)). Four phase feeding program was used: growing I (week 1-3), growing II (week 4-6), finishing I (week 7-9) and finishing II (week 10-12).

RESULTS

In growth performance, there was no significant difference among treatments during whole experimental period. In growingI phase, G:F ratio tended to increase when CM was increased (P = 0.05), but ADG and ADFI tended to decrease in finishingII phase (linear, P = 0.08). Also, increasing CM reduced ADG (linear, P = 0.02) and feed efficiency (linear, P = 0.08) during the whole finishing period. In blood profiles, BUN was linearly increased as CM increased (linear, P = 0.02) at growingII period. In digestibility trial, there was no significant difference in dry matter, crude fat, crude ash and nitrogen digestibility. However, crude protein digestibility was decreased linearly (linear, P = 0.02). In economic analysis, feed cost per weight gain and total feed cost per pig were reduced in overall period when CM was provided by 25% (linear, P = 0.02).

CONCLUSION

CM with 0.1% of β-mannanase (800 IU) could be supplemented instead of corn and SBM up to 25% without detrimental effects on growth performance and pork quality of growing-finishing pigs.

Laser Writing Block Copolymer Self-Assembly on Graphene Light-Absorbing Layer

Recent advance of high-power laser processing allows for rapid, continuous, area-selective material fabrication, typically represented by laser crystallization of silicon or oxides for display applications. Two-dimensional materials such as graphene exhibit remarkable physical properties and are under intensive development for the manufacture of flexible devices. Here we demonstrate an area-selective ultrafast nanofabrication method using low intensity infrared or visible laser irradiation to direct the self-assembly of block copolymer films into highly ordered manufacturing-relevant architectures at the scale below 12 nm. The fundamental principles underlying this light-induced nanofabrication mechanism include the self-assembly of block copolymers to proceed across the disorder-order transition under large thermal gradients, and the use of chemically modified graphene films as a flexible and conformal light-absorbing layers for transparent, nonplanar, and mechanically flexible surfaces.

Nash equilibrium and evolutionary dynamics in semifinalists' dilemma

We consider a tournament among four equally strong semifinalists. The players have to decide how much stamina to use in the semifinals, provided that the rest is available in the final and the third-place playoff. We investigate optimal strategies for allocating stamina to the successive matches when players' prizes (payoffs) are given according to the tournament results. From the basic assumption that the probability to win a match follows a nondecreasing function of stamina difference, we present symmetric Nash equilibria for general payoff structures. We find three different phases of the Nash equilibria in the payoff space. First, when the champion wins a much bigger payoff than the others, any pure strategy can constitute a Nash equilibrium as long as all four players adopt it in common. Second, when the first two places are much more valuable than the other two, the only Nash equilibrium is such that everyone uses a pure strategy investing all stamina in the semifinal. Third, when the payoff for last place is much smaller than the others, a Nash equilibrium is formed when every player adopts a mixed strategy of using all or none of its stamina in the semifinals. In a limiting case that only last place pays the penalty, this mixed-strategy profile can be proved to be a unique symmetric Nash equilibrium, at least when the winning probability follows a Heaviside step function. Moreover, by using this Heaviside step function, we study the tournament by using evolutionary replicator dynamics to obtain analytic solutions, which reproduces the corresponding Nash equilibria on the population level and gives information on dynamic aspects.

Anomalous rapid defect annihilation in self-assembled nanopatterns by defect melting

Molecular self-assembly commonly suffers from dense structural defect formation. Spontaneous defect annihilation in block copolymer (BCP) self-assembly is particularly retarded due to significant energy barrier for polymer chain diffusion and structural reorganization. Here we present localized defect melting induced by blending short neutral random copolymer chain as an unusual method to promote the defect annihilation in BCP self-assembled nanopatterns. Chemically neutral short random copolymer chains blended with BCPs are specifically localized and induce local disordered states at structural defect sites in the self-assembled nanopatterns. Such localized "defect melting" relieves the energy penalty for polymer diffusion and morphology reorganization such that spontaneous defect annihilation by mutual coupling is anomalously accelerated upon thermal annealing. Interestingly, neutral random copolymer chain blending also causes morphology-healing self-assembly behavior that can generate large-area highly ordered 10 nm scale nanopattern even upon poorly defined defective prepatterns. Underlying mechanisms of the unusual experimental findings are thoroughly investigated by three-dimensional self-consistent field theory calculation.

Large-scale quantitative analysis of painting arts

Scientists have made efforts to understand the beauty of painting art in their own languages. As digital image acquisition of painting arts has made rapid progress, researchers have come to a point where it is possible to perform statistical analysis of a large-scale database of artistic paints to make a bridge between art and science. Using digital image processing techniques, we investigate three quantitative measures of images - the usage of individual colors, the variety of colors, and the roughness of the brightness. We found a difference in color usage between classical paintings and photographs, and a significantly low color variety of the medieval period. Interestingly, moreover, the increment of roughness exponent as painting techniques such as chiaroscuro and sfumato have advanced is consistent with historical circumstances.

Wrinkle-directed self-assembly of block copolymers for aligning of nanowire arrays

Highly aligned metal nanowire arrays with feature sizes approaching 10 nm are fabricated. This is made possible by the self-assembly of block copolymers (BCPs) on graphene-wrinkle arrays. Thickness-modulated BCP films confined on the wrinkled reduced graphene oxide (rGO) surface promote the strict alignment of the self-assembled BCP lamellae in the direction of the film thickness gradient.

Costly bilingualism model in a population with one zealot

We consider a costly bilingualism model in which one can take two strategies in parallel. We investigate how a single zealot triggers the cascading behavior and how the compatibility of the two strategies affects when interacting patterns change. First, the role of the interaction range in the cascading is studied by increasing the range from local to global. We find that people sometimes do not favor taking the superior strategy even though its payoff is higher than that of the inferior one. This is found to be caused by the local interactions rather than the global ones. Applying this model to social networks, we find that the location of the zealot is also important for larger cascading in heterogeneous networks.

Gender-specific association of androgenetic alopecia with metabolic syndrome in a middle-aged Korean population

BACKGROUND

Although several previous studies have investigated the association between metabolic syndrome (MetS) and androgenetic alopecia (AGA), the study results have been inconsistent.

OBJECTIVES

The aim of this study was to investigate the relationship between the presence of MetS and AGA according to gender in a middle-aged Korean population.

METHODS

A population-based cross-sectional study was conducted on a sample from the Korean Genome Epidemiology Study. In total, 3408 subjects (1707 men and 1701 women) were enrolled between January 2008 and February 2010. The Norwood classification for men and Ludwig classification for women were used for assessment of the degree of hair loss. Information on components of MetS together with other possible risk factors was collected.

RESULTS

In men, the risk of having Norwood type IV or greater was not increased for subjects with MetS compared with those without MetS. In women, the risk of having Ludwig type I or greater was significantly increased for subjects with MetS compared with those without MetS after controlling for age and smoking status (OR 1.68, 95% CI 1.14-2.48; P=0.01). Similar results were also observed for the number of fulfilled components of MetS [odds ratio (OR) 1.38, 95% confidence interval (CI) 1.00-1.91; P<0.05]. When each component of MetS was considered individually, associations between AGA and all five components of MetS (waist circumference, triglycerides, high-density lipoprotein-C, blood glucose, and blood pressure) were not statistically significant. When multiple regression was used to adjust for age, family history and smoking, there was no significant association between the prevalence of MetS and moderate to severe AGA in the male group. On the contrary, a statistically significant positive association was noted between the prevalence of MetS and AGA in the female group.

CONCLUSIONS

Our analysis of AGA and the prevalence of MetS in a large population-based cohort demonstrated quite different findings compared with previous reports. The different results according to gender suggest that there may be different mechanisms that are yet to be defined between male and female AGA.

Phase-shift inversion in oscillator systems with periodically switching couplings

A system's response to external periodic changes can provide crucial information about its dynamical properties. We investigate the synchronization transition, an archetypical example of a dynamic phase transition, in the framework of such a temporal response. The Kuramoto model under periodically switching interactions has the same type of phase transition as the original mean-field model. Furthermore, we see that the signature of the synchronization transition appears in the relative delay of the order parameter with respect to the phase of oscillating interactions as well. Specifically, the phase shift becomes significantly larger as the system gets closer to the phase transition, so that the order parameter at the minimum interaction density can even be larger than that at the maximum interaction density, counterintuitively. We argue that this phase-shift inversion is caused by the diverging relaxation time, in a similar way to the resonance near the critical point in the kinetic Ising model. Our result, based on exhaustive simulations on globally coupled systems as well as scale-free networks, shows that an oscillator system's phase transition can be manifested in the temporal response to the topological dynamics of the underlying connection structure.

Percolation transitions are not always sharpened by making networks interdependent

We study a model for coupled networks introduced recently by Buldyrev et al., [Nature (London) 464, 1025 (2010)], where each node has to be connected to others via two types of links to be viable. Removing a critical fraction of nodes leads to a percolation transition that has been claimed to be more abrupt than that for uncoupled networks. Indeed, it was found to be discontinuous in all cases studied. Using an efficient new algorithm we verify that the transition is discontinuous for coupled Erdös-Rényi networks, but find it to be continuous for fully interdependent diluted lattices. In 2 and 3 dimensions, the order parameter exponent β is larger than in ordinary percolation, showing that the transition is less sharp, i.e., further from discontinuity, than for isolated networks. Possible consequences for spatially embedded networks are discussed.

Exact solutions for mass-dependent irreversible aggregations

We consider the mass-dependent aggregation process (k+1)X→X, given a fixed number of unit mass particles in the initial state. One cluster is chosen proportional to its mass and is merged into one, either with k neighbors in one dimension, or--in the well-mixed case--with k other clusters picked randomly. We find the same combinatorial exact solutions for the probability to find any given configuration of particles on a ring or line, and in the well-mixed case. The mass distribution of a single cluster exhibits scaling laws and the finite-size scaling form is given. The relation to the classical sum kernel of irreversible aggregation is discussed.

Explosive percolation is continuous, but with unusual finite size behavior

We study four Achlioptas-type processes with "explosive" percolation transitions. All transitions are clearly continuous, but their finite size scaling functions are not entirely holomorphic. The distributions of the order parameter, i.e., the relative size s(max)/N of the largest cluster, are double humped. But-in contrast to first-order phase transitions-the distance between the two peaks decreases with system size N as N(-η) with η>0. We find different positive values of β (defined via (s(max)/N)∼(p-p(c))β for infinite systems) for each model, showing that they are all in different universality classes. In contrast, the exponent Θ (defined such that observables are homogeneous functions of (p-p(c))N(Θ)) is close to-or even equal to-1/2 for all models.

Enhancing synchronization by directionality in complex networks

We propose a method called the residual edge-betweenness gradient (REBG) to enhance the synchronizability of networks by assigning the link direction while keeping the topology and link weights unchanged. Direction assignment has been shown to improve the synchronizability of undirected networks in general, but we find that in some cases incommunicable components emerge and networks fail to synchronize. We show that the REBG method improves the residual degree gradient (RDG) method by effectively avoiding the synchronization failure. Further experiments show that the REBG method enhances the synchronizability in networks with a community structure compared with the RDG method.

Clarithromycin and amikacin vs. clarithromycin and moxifloxacin for the treatment of post-acupuncture cutaneous infections due to Mycobacterium abscessus: a prospective observational study

An outbreak of post-acupuncture cutaneous infections due to Mycobacterium abscessus occurred in Ansan, Korea, from November 2007 through to May 2008. During this time a prospective, observational, non-randomized study was conducted involving 52 patients that were diagnosed with cutaneous M. abscessus infection. We compared the clinical response between patients treated with clarithromycin plus amikacin regimen and those treated with clarithromycin plus moxifloxacin regimens with regard to time to resolution of the cutaneous lesions. Among the 52 study patients, 33 were treated with clarithromycin plus amikacin, and 19 were treated with clarithromycin plus moxifloxacin. The baseline characteristics for the treatment groups were not significantly different, except for initial surgical excision (n = 27 vs. 6, respectively, p = 0.001). The median time (weeks) to resolution of the lesions in the clarithromycin plus moxifloxacin-treated subjects was significantly shorter than that in the clarithromycin plus amikacin-treated subjects (17 ± 1.1 vs. 20 ± 0.9, respectively, p = 0.017). With adjustments for age, location of lesions, prior incision and drainage, and excision during medical therapy, clarithromycin plus moxifloxacin-treated subjects were more likely to have resolved lesions (hazard ratio, 0.387; 95% confidence interval, 0.165-0.907; p = 0.029). The frequency of drug-related adverse events in the two treatment groups was not significantly different (n = 18 vs. 14, respectively; p = 0.240). The most common adverse event was gastrointestinal discomfort. The results of our study showed that the combination regimen of clarithromycin and moxifloxacin resulted in a better clinical response than a regimen of clarithromycin plus amikacin when used for treatment of cutaneous M. abscessus infection.

Thermal fluctuation effects on finite-size scaling of synchronization

We consider globally coupled random frequency oscillators under thermal noise, and explore the synchronization transition with its critical behavior near the transition. In particular, we focus on the finite-size scaling behavior of the synchronization, and investigate how the thermal noise affects the correlation size exponent ν of the synchronized oscillators. Extensive numerical simulations as well as mean-field analysis have been performed. We find that the correlation size exponent changes from ν=5/2 without thermal noise to ν=2 with strong thermal noise, where the value ν=2 is the same as that for the usual equilibrium systems described by the Ginzburg-Landau mean-field theory. In order to see the effects of thermal fluctuation further, we remove the frequency-disorder fluctuations originating from the different realizations of natural frequencies of the oscillators, and examine the finite-size scaling behavior for the case only with the thermal fluctuation. It is found that ν becomes 2 at much weak thermal noise strength, which implies that even very weak thermal fluctuations may lead to ν=2 when frequency-disorder fluctuations are absent.

Finding communities in directed networks

To identify communities in directed networks, we propose a generalized form of modularity in directed networks by presenting the quantity LinkRank, which can be considered as the PageRank of links. This generalization is consistent with the original modularity in undirected networks and the modularity optimization methods developed for undirected networks can be directly applied to directed networks by optimizing our modified modularity. Also, a model network, which can be used as a benchmark network in further community studies, is proposed to verify our method. Our method is supposed to find communities effectively in citation- or reference-based directed networks.

Dynamics and directionality in complex networks

We investigate how we can improve the synchronizability of complex networks simply by changing the link direction while conserving the local link weights and topology. Performing the linear stability analysis of synchronization and numerical simulation of the Kuramoto model in the directed networks, we find that while a random assignment of link directions generally weakens the degree of synchronization, a properly organized directionality can systematically enhance the network synchronization. In this respect, we suggest a simple method of changing the link direction according to the larger residual degree starting from small residual degree nodes. This result provides plausible applications to control the synchronizability of systems in various fields.

Upregulation of Fas and downregulation of CD94/NKG2A inhibitory receptors on circulating natural killer cells in patients with new-onset psoriasis

BACKGROUND

Psoriasis has been considered as a T-helper 1 cell-mediated autoimmune disease driven by collaboration with multiple components of innate and acquired immune cells. Natural killer (NK) cells have been shown to bridge innate and acquired immunity, and thus could potentially contribute to the pathophysiology of psoriasis.

OBJECTIVES

To investigate the phenotypic changes of circulating NK cells in patients with new-onset psoriasis.

METHODS

Fifteen patients with plaque psoriasis (eight women and seven men) who visited our clinic after their first episode of psoriasis and did not have a history of previous systemic therapy or phototherapy participated in this study. Peripheral blood mononuclear cells were isolated and stained with a panel of antibodies against cell surface receptors expressed on T and/or NK cells and analysed by flow cytometry.

RESULTS

As compared with normal healthy volunteers, patients with new-onset psoriasis showed no significant changes in numbers of peripheral NK, NK-T or T cells. NK activating receptors 2B4, CD48, NKG2D, CD16 and CD56 were found to be unchanged in new-onset psoriasis. However, the expression of Fas (activation-induced death receptor) was upregulated, whereas the expression of the NK inhibitory receptors CD94 and NKG2A was dramatically reduced on NK cells of new-onset psoriasis. These changes occurred at the level of mean fluorescent intensity, but minimally affected percentages of cells expressing Fas, CD94 and NKG2A.

CONCLUSIONS

Our findings demonstrate that changes in the expression of Fas and CD94/NKG2A receptors on NK cells may occur during new-onset psoriasis, and are likely to contribute to the pathogenesis of psoriasis.

Relaxation of synchronization on complex networks

We study collective synchronization in a large number of coupled oscillators on various complex networks. In particular, we focus on the relaxation dynamics of the synchronization, which is important from the viewpoint of information transfer or the dynamics of system recovery from a perturbation. We measure the relaxation time tau that is required to establish global synchronization by varying the structural properties of the networks. It is found that the relaxation time in a strong-coupling regime (K>Kc) logarithmically increases with network size N , which is attributed to the initial random phase fluctuation given by O(N-1/2) . After elimination of the initial-phase fluctuation, the relaxation time is found to be independent of the system size; this implies that the local interaction that depends on the structural connectivity is irrelevant in the relaxation dynamics of the synchronization in the strong-coupling regime. The relaxation dynamics is analytically derived in a form independent of the system size, and it exhibits good consistency with numerical simulations. As an application, we also explore the recovery dynamics of the oscillators when perturbations enter the system.

A protein interaction network associated with asthma

Identifying candidate genes related to complex diseases or traits and mapping their relationships require a system-level analysis at a cellular scale. The objective of the present study is to systematically analyze the complex effects of interrelated genes and provide a framework for revealing their relationships in association with a specific disease (asthma in this case). We observed that protein-protein interaction (PPI) networks associated with asthma have a power-law connectivity distribution as many other biological networks have. The hub nodes and skeleton substructure of the result network are consistent with the prior knowledge about asthma pathways, and also suggest unknown candidate target genes associated with asthma, including GNB2L1, BRCA1, CBL, and VAV1. In particular, GNB2L1 appears to play a very important role in the asthma network through frequent interactions with key proteins in cellular signaling. This network-based approach represents an alternative method for analyzing the complex effects of candidate genes associated with complex diseases and suggesting a list of gene drug targets. The full list of genes and the analysis details are available in the following online supplementary materials: http://biosoft.kaist.ac.kr:8080/resources/asthma_ppi.

Some fungal endophytes from vegetable crops and their anti-oomycete activities against tomato late blight

AIMS

To isolate endophytic fungi from vegetable plants and examine their in vivo anti-oomycete activity against Phytophthora infestans in tomato plants.

METHODS AND RESULTS

Endophytic fungi were isolated from surface-sterilized plant tissues and anti-oomycete activity was measured by in vivo assay using tomato seedlings. Endophytic fungi showing potent anti-oomycete activity were identified by morphological characteristics and nuclear ribosomal ITS1-5.8S-ITS2 sequence analysis. A total of 152 isolates were obtained from 66 healthy tissue samples of cucumber, red pepper, tomato, pumpkin and Chinese cabbage and the fermentation broths of 23 isolates showed potent in vivo anti-oomycete activity against tomato late blight with control values over 90%. The Fusarium oxysporum strain EF119, which was isolated from roots of red pepper, showed the most potent disease control efficacy against tomato late blight. In dual-culture tests, it inhibited the growth of Pythium ultimum, P. infestans and Phytophthora capsici.

CONCLUSIONS

Among endophytic fungi isolated from healthy tissues of vegetable plants, F. oxysporum EF119 showed the most potent in vivo anti-oomycete activity against tomato late blight and in vitro anti-oomycete activity against several oomycete pathogens.

SIGNIFICANCE AND IMPACT OF THE STUDY

Endophytic fungi showing anti-oomycete activity in vitro and in vivo may be used as biocontrol agents particularly of tomato late blight.

Tailgut cyst in a neonate

Tailgut cyst is a rare lesion of developmental origin located in the retrorectal space, which usually presents as a multilocular cystic mass. It is usually found in adults, and neonatal cases are extremely rare. The authors report a tailgut cyst in a neonate that was found by prenatal ultrasonogram, which was like a teratoma in gross appearance.