Relevant Region Research Articles

Spectral Narrowing in a Subwavelength Solid-State Laser

The association of metallic nanostructures and solid-state gain media has recently led to the emergence of functional platforms for nanolasing with relevant features such as chemical and thermal stability and the absence of photobleaching. In this work, we demonstrate that the incorporation of plasmonic nanoparticle chains on a Nd3+-doped solid-state laser platform enables nanoscale laser emission at the technologically relevant spectral region of telecom (λe = 1385 nm), outside the spectral response of the plasmonic resonance of the nanoparticle chains. In addition, we experimentally show that the plasmonic chains improve the monochromaticity of the solid-state laser, thus, attaining spectral narrowing of the laser line by up to 38% depending on the pump wavelength. The effect of the plasmon driven absorption enhancement in the vicinities of the Ag nanoparticle chains is analyzed by tuning the optical pump in a broad spectral range (580–890 nm) at different Nd3+ transitions that overlap the spectral resp...

Near-Infrared Imaging of Serotonin Release from Cells with Fluorescent Nanosensors.

Serotonin is an important neurotransmitter involved in various functions of the nervous, blood, and immune system. In general, detection of small biomolecules such as serotonin in real time with high spatial and temporal resolution remains challenging with conventional sensors and methods. In this work, we designed a near-infrared (nIR) fluorescent nanosensor (NIRSer) based on fluorescent single-walled carbon nanotubes (SWCNTs) to image the release of serotonin from human blood platelets in real time. The nanosensor consists of a nonbleaching SWCNT backbone, which is fluorescent in the beneficial nIR tissue transparency window (800-1700 nm) and a serotonin binding DNA aptamer. The fluorescence of the NIRSer sensor (995 nm emission wavelength for (6,5)-SWCNTs) increases in response to serotonin by a factor up to 1.8. It detects serotonin reversibly with a dissociation constant of 301 nM ± 138 nM and a dynamic linear range in the physiologically relevant region from 100 nM to 1 μM. As a proof of principle, we detected serotonin release patterns from activated platelets on the single-cell level. Imaging of the nanosensors around and under the platelets enabled us to locate hot spots of serotonin release and quantify the time delay (≈ 21-30 s) between stimulation and release in a population of platelets, highlighting the spatiotemporal resolution of this nanosensor approach. In summary, we report a nIR fluorescent nanosensor for the neurotransmitter serotonin and show its potential for imaging of chemical communication between cells.

On Complex Network Construction of Rain Gauge Stations Considering Nonlinearity of Observed Daily Rainfall Data

Rainfall data is frequently used as input and analysis data in the field of hydrology. To obtain adequate rainfall data, there should be a rain gauge network that can cover the relevant region. Therefore, it is necessary to analyze and evaluate the adequacy of rain gauge networks. Currently, a complex network analysis is frequently used in network analysis and in the hydrology field, Pearson correlation is used as strength of link in constructing networks. However, Pearson correlation is used for analyzing the linear relationship of data. Therefore, it is now suitable for nonlinear hydrological data (such as rainfall and runoff). Thus, a possible solution to this problem is to apply mutual information that can consider nonlinearity of data. The present study used a method of statistical analysis known as the Brock–Dechert–Scheinkman (BDS) statistics to test the nonlinearity of rainfall data from 55 Automated Synoptic Observing System (ASOS) rain gauge stations in South Korea. Analysis results indicated that all rain gauge stations showed nonlinearity in the data. Complex networks of these rain gauge stations were constructed by applying Pearson correlation and mutual information. Then, they were compared by computing their centrality values. Comparing the centrality rankings according to different thresholds for correlation showed that the network based on mutual information yielded consistent results in the rankings, whereas the network, which based on Pearson correlation exhibited much variability in the results. Thus, it was found that using mutual information is appropriate when constructing a complex network utilizing rainfall data with nonlinear characteristics.

A Novel and Translational Rat Model of Concussion Combining Force and Rotation with In Vivo Cerebral Microdialysis.

Persistent cognitive and motor symptoms are known consequences of concussions/mild traumatic brain injury (mTBIs) that can be partly attributable to altered neurotransmission. Indeed, cerebral microdialysis studies in rodents have demonstrated an excessive extracellular glutamate release in the hippocampus within the first 10 min following trauma. Microdialysis offers the clear advantage of in vivo neurotransmitter continuous sampling while not having to sacrifice the animal. In addition to the aforementioned technique, a closed head injury model that exerts rapid acceleration and deceleration of the head and torso is needed, as such a factor is not available in many other animal models. The Wayne State weight-drop model mimics this essential component of human craniocerebral trauma, allowing the induction of an impact on the head of an unrestrained rodent with a falling weight. Our novel and translational rat model combines cerebral microdialysis with the Wayne State weight-drop model to study, in lightly anesthetized and unrestrained adult rats, the acute changes in extracellular neurotransmitter levels following concussion. In this protocol, the microdialysis probe was inserted inside the hippocampus as region of interest, and was left inserted in the brain at impact. There is a high density of terminals and receptors in the hippocampus, making it a relevant region to document altered neurotransmission following concussion. When applied to adult Sprague-Dawley rats, our combined model induced increases in hippocampal extracellular glutamate concentrations within the first 10 min, consistent with the previously reported post-concussion symptomology. This combined weight-drop model provides a reliable tool for researchers to study early therapeutic responses to concussions in addition to repetitive brain injury, since this protocol induces a closed-head mild trauma.

Controlled-advancement rigid-body optimization of nanosystems.

In this study, we propose a novel optimization algorithm, with application to the refinement of molecular complexes. Particularly, we consider optimization problem as the calculation of quasi-static trajectories of rigid bodies influenced by the inverse-inertia-weighted energy gradient and introduce the concept of advancement region that guarantees displacement of a molecule strictly within a relevant region of conformational space. The advancement region helps to avoid typical energy minimization pitfalls, thus, the algorithm is suitable to work with arbitrary energy functions and arbitrary types of molecular complexes without necessary tuning of its hyper-parameters. Our method, called controlled-advancement rigid-body optimization of nanosystems (Carbon), is particularly useful for the large-scale molecular refinement, as for example, the putative binding candidates obtained with protein-protein docking pipelines. Implementation of Carbon with user-friendly interface is available in the SAMSON platform for molecular modeling at https://www.samson-connect.net. © 2019 Wiley Periodicals, Inc.

Comparative evaluation of region query strategies for DBSCAN clustering

Clustering is a technique that allows data to be organized into groups of similar objects. DBSCAN (Density-Based Spatial Clustering of Applications with Noise) constitutes a popular clustering algorithm that relies on a density-based notion of cluster and is designed to discover clusters of arbitrary shape. The computational complexity of DBSCAN is dominated by the calculation of the ϵ-neighborhood for every object in the dataset. Thus, the efficiency of DBSCAN can be improved in two different ways: (1) by reducing the overall number of ϵ-neighborhood queries (also known as region queries), or (2) by reducing the complexity of the nearest neighbor search conducted for each region query. This paper deals with the first issue by considering the most relevant region query strategies for DBSCAN, all of them characterized by inspecting the neighborhoods of only a subset of the objects in the dataset. We comparatively evaluate these region query strategies (or DBSCAN variants) in terms of clustering effectiveness and efficiency; additionally, a novel region query strategy is introduced in this work. The results show that some DBSCAN variants are only slightly inferior to DBSCAN in terms of effectiveness, while greatly improving its efficiency. Among these variants, the novel one outperforms the rest.

China’s South Asia Policy in the ‘New Era’

In recent years, there has been a rise in China’s profile in South Asia. It is no surprise that Chinese experts have used terms, such as ‘new springtime’ in China–South Asia relations, ‘rediscovery of the strategic status of South Asia’ and ‘most relevant region with regard to the rise of China’. The objective of this article is to examine the nature and drivers of China’s South Asia policy, especially under the leadership of Xi Jinping vis-à-vis China’s policy towards the region in the past. It is not sufficient to only examine international factors or foreign and security policy in the context of the neighbouring region, such as South Asia. China’s ‘domestic periphery’ presents a significant threat to its national security. These areas are linked to neighbouring countries of South Asia and Central Asia.The announcement by Chinese President Xi Jinping of a ‘New Era’ or ‘third era’ in the history of Communist Party of China (CPC) represents a China which is known for its dictum ‘striving for achievement’ ( fenfa youwei). This is different from the second era’s policy of ‘keeping a low profile and biding the time’ proposed by Deng Xiaoping. Of course, the name of Mao Zedong is synonymous with the first era beginning from 1949.

Iodine Maps from Subtraction CT or Dual-Energy CT to Detect Pulmonary Emboli with CT Angiography: A Multiple-Observer Study.

Background Dual-energy CT iodine maps are used to detect pulmonary embolism (PE) with CT angiography but require dedicated hardware. Subtraction CT, a software-only solution, results in iodine maps with high contrast-to-noise ratios. Purpose To compare the use of subtraction CT versus dual-energy CT iodine maps to CT angiography for PE detection. Materials and Methods In this prospective study ( https://clinicaltrials.gov , NCT02890706), 274 participants suspected of having PE underwent precontrast CT followed by contrast material-enhanced dual-energy CT angiography between July 2016 and April 2017. Iodine maps from dual-energy CT were derived. Subtraction maps (contrast-enhanced CT minus precontrast CT) were calculated after motion correction. Truth was established by expert consensus. A total of 75 randomly selected participants with and without PE (1:1 ratio) were evaluated by three radiologists and six radiology residents (blinded to final diagnosis) for the presence of PE using three types of CT: CT angiography alone, dual-energy CT, and subtraction CT. The partial area under the receiver operating characteristic curve (AUC) for the clinically relevant specificity region (maximum partial AUC, 0.11) was compared by using multireader multicase variance. A P value less than or equal to .025 was considered indicative of a significant difference due to multiple comparisons. Results There were 35 men and 40 women in the reader study (mean age, 63 years ± 12 [standard deviation]). The pooled sensitivities were not different (P ≥ .31 among techniques) (95% confidence intervals [CIs]: 67%, 89% for CT angiography; 72%, 91% for dual-energy CT; 70%, 91% for subtraction CT). However, pooled specificity was higher for subtraction CT (95% CI: 100%, 100%) than for CT angiography (95% CI: 89%, 97%) or dual-energy CT (95% CI: 89%, 98%) (P < .001). Partial AUCs for the average observer improved equally when adding iodine maps (subtraction CT [0.093] vs CT angiography [0.088], P = .03; dual-energy CT [0.094] vs CT angiography, P = .01; dual-energy CT vs subtraction CT, P = .68). Average reading times were equivalent (range, 97-101 seconds; P ≥ .41) among techniques. Conclusion Subtraction CT iodine maps had greater specificity than CT angiography alone in pulmonary embolism detection. Subtraction CT had comparable diagnostic performance to that of dual-energy CT, without the need for dedicated hardware. © RSNA, 2019 Online supplemental material is available for this article.

Receptor subtype discrimination using extensive shape complementary designed interfaces.

Discriminating between closely related members of a protein family which differ at a limited number of spatially distant positions is a challenge for drug discovery. We describe an approach for computationally designing binders targeting functional sites with large, shape complementary interfaces to ‘read out’ subtle sequence differences for sub-type specific antagonism. Repeat proteins are computationally docked against a functionally relevant region of the target protein surface that varies in the different subtypes, and the interface sequences are optimized for affinity and specificity first computationally and then experimentally. We used this approach to generate a series of human Frizzled (Fz) subtype-selective antagonists with extensive shape complementary interaction surfaces considerably larger than those of repeat proteins selected from random libraries. In vivo administration revealed that Wnt-dependent pericentral liver gene expression involves multiple Fz subtypes, while maintenance of the intestinal crypt stem cell compartment involves only a limited subset.

Direct capture cross section of Be9(n,γ)Be10

The cross section of the $^{9}$Be(n,$\gamma$)$^{10}$Be reaction was calculated in the direct capture model. All parameters of the calculations were adjusted to properties of the $^{9}$Be + n system at thermal energies. The calculated cross section at thermonuclear energies shows the expected $1/v$ behavior of $s$-wave capture at low energies, but increases towards higher energies as typical $p$-wave capture. Excellent agreement between new experimental data in the astrophysically relevant energy region and the present calculation is found.

In vivo fate of bone marrow mesenchymal stem cells implanted into rat pulpotomized molars

In our previous work, we established an in vivo coronal pulp regeneration model in which biodegradable hydrogel-made scaffolds carrying rat bone marrow mesenchymal stem cells (BM-MSCs) were implanted in the coronal pulp chamber of pulpotomized rat maxillary first molars. In this study, we investigated the in vivo fate of LacZ-labeled BM-MSCs in our coronal pulp regeneration model. BM-MSCs were nucleofected with pVectOZ-LacZ plasmid encoding β-galactosidase 1 day before implantation, and the LacZ-transfected BM-MSCs were implanted into the pulpotomized pulp chamber with biodegradable preformed scaffold-hydrogel constructs. Empty vector was used as a control. After 3 and 14 days, the molars were retrieved and subjected to β-galactosidase staining. At 3 days, β-galactosidase-expressing cells with a round profile were located mainly around the scaffold. At 14 days, when the pulp-like tissue had been generated, the majority of β-galactosidase-expressing cells were detected under the newly formed dentin bridge-like structure, where nestin-expressing odontoblast-like cells were arranged. Immunoreactivity for dentin sialoprotein, a marker of mature odontoblasts, was strongly detected under the original dentin. No β-galactosidase staining was observed in the control group. Thus, we demonstrated that BM-MSCs survived for 2 weeks after implantation and colonized within the site of potential cytodifferentiation. Our findings indicated that BM-MSCs could differentiate into cells involved in mineralized tissue formation in the functionally relevant region.

Ag cluster beam deposition for TCO/Ag/TCO multilayer

Environment friendly, thin and flexible devices require the synthesis of Indium-free new transparent conducting materials (TCM) with improved structural, thermal, electrical and optical properties. To overcome the critical issues raised by thinning the TCM, we propose a multilayer structure in which nanogranular Ag film obtained by supersonic cluster beam deposition is sandwiched in between Alluminum doped Zinc Oxide (AZO) thin layers. The introduction of the nanogranular Ag film, when compared to the standard sputtered one, yields higher optical transmittance in the technologically relevant VIS-NIR region and superior mechanical reliability while preserving low electrical resistance. The present results open new perspectives to exploit the nanogranular nature of conductive films, synthesized via Supersonic Cluster Beam Deposition, to engineer transparent conducting materials.

Industrial-era decline in subarctic Atlantic productivity.

Marine phytoplankton have a crucial role in the modulation of marine-based food webs1, fishery yields2 and the global drawdown of atmospheric carbon dioxide3. However, owing to sparse measurements before satellite monitoring in the twenty-first century, the long-term response of planktonic stocks to climate forcing is unknown. Here, using a continuous, multi-century record of subarctic Atlantic marine productivity, we show that a marked 10±7% decline in net primary productivity has occurred across this highly productive ocean basin over the past two centuries. We support this conclusion by the application of a marine-productivity proxy, established using the signal of the planktonic-derived aerosol methanesulfonic acid, which is commonly identified across an array of Greenlandic ice cores. Using contemporaneous satellite-era observations, we demonstrate the use of this signal as a robust and high-resolution proxy for pastvariations in spatially integrated marine productivity. We show that the initiation of declining subarctic Atlantic productivity broadly coincides with the onset of Arctic surface warming4, and that productivity strongly covaries with regional sea-surface temperatures and basin-wide gyre circulation strength over recent decades. Taken together, our results suggest that the decline in industrial-era productivity may be evidence of the predicted5 collapse of northern Atlantic planktonic stocks in response to a weakened Atlantic Meridional Overturning Circulation6-8. Continued weakening of this Atlantic Meridional Overturning Circulation, as projected for the twenty-first century9,10, may therefore result in further productivity declines across this globally relevant region.

Deletion of the KH1 Domain of Fmr1 Leads to Transcriptional Alterations and Attentional Deficits in Rats.

Fragile X syndrome (FXS) is a neurodevelopmental disorder caused by mutations in the FMR1 gene. It is a leading monogenic cause of autism spectrum disorder and inherited intellectual disability and is often comorbid with attention deficits. Most FXS cases are due to an expansion of CGG repeats leading to suppressed expression of fragile X mental retardation protein (FMRP), an RNA-binding protein involved in mRNA metabolism. We found that the previously published Fmr1 knockout rat model of FXS expresses an Fmr1 transcript with an in-frame deletion of exon 8, which encodes for the K-homology (KH) RNA-binding domain, KH1. Notably, 3 pathogenic missense mutations associated with FXS lie in the KH domains. We observed that the deletion of exon 8 in rats leads to attention deficits and to alterations in transcriptional profiles within the medial prefrontal cortex (mPFC), which map to 2 weighted gene coexpression network modules. These modules are conserved in human frontal cortex and enriched for known FMRP targets. Hub genes in these modules represent potential therapeutic targets for FXS. Taken together, these findings indicate that attentional testing might be a reliable cross-species tool for investigating FXS and identify dysregulated conserved gene networks in a relevant brain region.

EMAS position statement: Predictors of premature and early natural menopause

IntroductionWhile the associations of genetic, reproductive and environmental factors with the timing of natural menopause have been extensively investigated, few epidemiological studies have specifically examined their association with premature (<40 years) or early natural menopause (40–45 years). AimThe aim of this position statement is to provide evidence on the predictors of premature and early natural menopause, as well as recommendations for the management of premature and early menopause and future research. Materials and methodsLiterature review and consensus of expert opinion. Results and conclusionsStrong genetic predictors of premature and early menopause include a family history of premature or early menopause, being a child of a multiple pregnancy and some specific genetic variants. Women with early menarche and nulliparity or low parity are also at a higher risk of experiencing premature or early menopause. Cigarette smoking (with a strong dose–response effect) and being underweight have been consistently associated with premature and early menopause. Current guidelines for the management of premature and early menopause mainly focus on early initiation of hormone therapy (HT) and continued treatment until the woman reaches the average age at menopause (50–52 years). We suggest that clinicians and health professionals consider the age at menopause of the relevant region or ethnic group as part of the assessment for the timing of HT cessation. In addition, there should be early monitoring of women with a family history of early menopause, who are a child of a multiple pregnancy, or who have had early menarche (especially those who have had no children). As part of preventive health strategies, women should be encouraged to quit smoking (preferably before the age of 30 years) and maintain optimal weight in order to reduce their risk of premature or early menopause.

Computational geometry for modeling neural populations: From visualization to simulation.

The importance of a mesoscopic description level of the brain has now been well established. Rate based models are widely used, but have limitations. Recently, several extremely efficient population-level methods have been proposed that go beyond the characterization of a population in terms of a single variable. Here, we present a method for simulating neural populations based on two dimensional (2D) point spiking neuron models that defines the state of the population in terms of a density function over the neural state space. Our method differs in that we do not make the diffusion approximation, nor do we reduce the state space to a single dimension (1D). We do not hard code the neural model, but read in a grid describing its state space in the relevant simulation region. Novel models can be studied without even recompiling the code. The method is highly modular: variations of the deterministic neural dynamics and the stochastic process can be investigated independently. Currently, there is a trend to reduce complex high dimensional neuron models to 2D ones as they offer a rich dynamical repertoire that is not available in 1D, such as limit cycles. We will demonstrate that our method is ideally suited to investigate noise in such systems, replicating results obtained in the diffusion limit and generalizing them to a regime of large jumps. The joint probability density function is much more informative than 1D marginals, and we will argue that the study of 2D systems subject to noise is important complementary to 1D systems.

Deep Attention Network for Egocentric Action Recognition.

Recognizing a camera wearer's actions from videos captured by an egocentric camera is a challenging task. In this paper, we employ a two-stream deep neural network composed of an appearance-based stream and a motion-based stream to recognize egocentric actions. Based on the insight that human action and gaze behavior are highly coordinated in object manipulation tasks, we propose a spatial attention network to predict human gaze in the form of attention map. The attention map helps each of the two streams to focus on the most relevant spatial region of the video frames to predict actions. To better model the temporal structure of the videos, a temporal network is proposed. The temporal network incorporates bi-directional long short-term memory to model the long-range dependencies to recognize egocentric actions. The experimental results demonstrate that our method is able to predict attention maps that are consistent with human attention and achieve competitive action recognition performance with the state-of-the-art methods on the GTEA Gaze and GTEA Gaze+ datasets.

Using Colour Images for Online Yeast Growth Estimation.

Automatisation and digitalisation of laboratory processes require adequate online measurement techniques. In this paper, we present affordable and simple means for non-invasive measurement of biomass concentrations during cultivation in shake flasks. Specifically, we investigate the following research questions. Can images of shake flasks and their content acquired with smartphone cameras be used to estimate biomass concentrations? Can machine vision be used to robustly determine the region of interest in the images such that the process can be automated? To answer these questions, 18 experiments were performed and more than 340 measurements taken. The relevant region in the images was selected automatically using K-means clustering. Statistical analysis shows high fidelity of the resulting model predictions of optical density values that were based on the information embedded in colour changes of the automatically selected region in the images.

Morphological Assessment of Maxillary Sinus Septa Variations with Cone-Beam Computed Tomography in a Turkish Population

Objective The purpose of this study was to measure and classify sinus septa variables (prevalence, numbers, heights, locations, orientations, and morphology) and to determine the effects of age, gender, and dental status on the presence of septa and also to evaluate the effects of septa on pathological mucosal thickening. Materials and Methods A total of 2,000 patients were analyzed through conebeam computed tomography (CBCT). The total of 500 maxillary sinuses were included in this study. The number of maxillary sinus septa was determined on axial sections of CBCT images. Their locations, orientations, and morphologies were determined on both the axial and sagittal sections, and their heights were determined only on the sagittal sections. The influence of age, gender, dental status, and pathological mucosal thickening on the presence of septa was statistically analyzed. Mann–Whitney U-test and descriptive statistics were used for statistical analysis. Results The average height of the determined 287 septa was measured as 7.36 mm. The highest rates of septa location, morphology, and orientation were found, respectively, in the middle region septa (57.49%), completed septa (75.95%), and transverse septa (93.37%). The effect of dental status, age, and gender on the presence of septa was not statistically significant ( p > 0.05). Conclusion These high rates of findings support the importance of CBCT in the diagnosis of the variations of the maxillary sinus septa. Therefore, it is important to evaluate CBCT images of the relevant region to increase the success of surgical interventions in the maxillary posterior region and to eliminate possible complications.

Выявление факторов неравенства в России с использованием регрессионной декомпозиции

The purpose of this study was to identify the factors of income inequality in Russia using RLMSdata (2009–2016). In this paper inequality refers to differentiation in equivalent household income, adjusted for the cost of the consumer basket in the regions of Russia. To solve the problem, we used regression decomposition of the inequality index. According to the results, such factors as “the share of children in households”, “the size of households” and “the share of non-working adults” had the largest positive contribution to the inequality index. The “region of residence” factor, which is usually considered as the key factor of inequality in Russia, had an equalizing effect. This is due to the fact that we analyzed differentiation in the standard of living. Indeed, we calculated the dependent variable of income, adjusted for the cost of the consumer basket in the relevant region. Thus, the level of inequality was not affected by the regional attribute, but rather by the differentiation of other significant factors of the regions. The obtained results can be used for a deeper study of the causes of changes in inequality.