Sorting Mechanism Research Articles

Exosomal MicroRNAs and Organotropism in Breast Cancer Metastasis.

Breast cancer is the most frequent malignancy for women in which one in eight women will be diagnosed with the disease in their lifetime. Despite advances made in treating primary breast cancer, there is still no effective treatment for metastatic breast cancer. Consequently, metastatic breast cancer is responsible for 90% of breast cancer-related deaths while only accounting for approximately one third of all breast cancer cases. To help develop effective treatments for metastatic breast cancer, it is important to gain a deeper understanding of the mechanisms by which breast cancer metastasizes, particularly, those underlying organotropism towards brain, bone, and lungs. In this review, we will primarily focus on the roles that circulating exosomal microRNAs (miRNAs) play in organotropism of breast cancer metastasis. Exosomes are extracellular vesicles that play critical roles in intercellular communication. MicroRNAs can be encapsulated in exosomes; cargo-loaded exosomes can be secreted by tumor cells into the tumor microenvironment to facilitate tumor–stroma interactions or released to circulation to prime distant organs for subsequent metastasis. Here, we will summarize our current knowledge on the biogenesis of exosomes and miRNAs, mechanisms of cargo sorting into exosomes, the exosomal miRNAs implicated in breast cancer metastasis, and therapeutic exosomal miRNAs.

Mechanisms of procollagen and HSP47 sorting during ER-to-Golgi trafficking

Efficient quality control and export of procollagen from the cell is crucial for extracellular matrix homeostasis, yet it is still incompletely understood. One of the debated questions is the role of a collagen-specific ER chaperone HSP47 in these processes. Most ER chaperones preferentially bind to unfolded polypeptide chains, enabling selective export of natively folded proteins from the ER after chaperone release. In contrast, HSP47 preferentially binds to the natively folded procollagen and is believed to be released only in the ER-Golgi intermediate compartment (ERGIC) or cis-Golgi. HSP47 colocalization with procollagen in punctate structures observed by immunofluorescence imaging of fixed cells has thus been interpreted as evidence for HSP47 export from the ER together with procollagen in transport vesicles destined for ERGIC or Golgi. To understand the mechanism of this co-trafficking and its physiological significance, we imaged the dynamics of fluorescently tagged type I procollagen and HSP47 punctate structures in live MC3T3 murine osteoblasts with up to 120 nm spatial and 500 ms time resolution. Contrary to the prevailing model, we discovered that most bona fide carriers delivering procollagen from ER exit sites (ERESs) to Golgi contained no HSP47, unless the RDEL signal for ER retention in HSP47 was deleted or mutated. These transport intermediates exhibited characteristic rapid, directional motion along microtubules, while puncta with colocalized HSP47 and procollagen similar to the ones described before had only limited, stochastic motion. Live cell imaging and fluorescence recovery after photobleaching revealed that the latter puncta (including the ones induced by ARF1 inhibition) were dilated regions of ER lumen, ERESs, or autophagic structures surrounded by lysosomal membranes. Procollagen was colocalized with HSP47 and ERGIC53 at ERESs. It was colocalized with ERGIC53 but not HSP47 in Golgi-bound transport intermediates. Our results suggest that procollagen and HSP47 sorting occurs at ERES before procollagen is exported from the ER in Golgi-bound transport intermediates, providing new insights into mechanisms of procollagen trafficking.

Rapid contextualization of fragmented scene information in the human visual system

Real-world environments are extremely rich in visual information. At any given moment in time, only a fraction of this information is available to the eyes and the brain, rendering naturalistic vision a collection of incomplete snapshots. Previous research suggests that in order to successfully contextualize this fragmented information, the visual system sorts inputs according to spatial schemata, that is knowledge about the typical composition of the visual world. Here, we used a large set of 840 different natural scene fragments to investigate whether this sorting mechanism can operate across the diverse visual environments encountered during real-world vision. We recorded brain activity using electroencephalography (EEG) while participants viewed incomplete scene fragments at fixation. Using representational similarity analysis on the EEG data, we tracked the fragments’ cortical representations across time. We found that the fragments’ typical vertical location within the environment (top or bottom) predicted their cortical representations, indexing a sorting of information according to spatial schemata. The fragments’ cortical representations were most strongly organized by their vertical location at around 200 ​ms after image onset, suggesting rapid perceptual sorting of information according to spatial schemata. In control analyses, we show that this sorting is flexible with respect to visual features: it is neither explained by commonalities between visually similar indoor and outdoor scenes, nor by the feature organization emerging from a deep neural network trained on scene categorization. Demonstrating such a flexible sorting across a wide range of visually diverse scenes suggests a contextualization mechanism suitable for complex and variable real-world environments.

Composition and Size Dependent Sorting in Preplanetary Growth: Seeding the Formation of Mercury-like Planets

Abstract In an earlier work, we found that large metallic iron fractions in dust aggregates and strong magnetic fields boost preplanetary growth. This sets an initial bias for the formation of Mercury-like planets in the inner part of protoplanetary disks. We extended these experiments here by adding pure quartz aggregates to the iron-rich aggregates. Magnetic boost still leads to the formation of larger clusters of aggregates. These clusters now include silicate aggregates, which can also be connecting bridges between chains. However, at least a certain fraction of iron-rich aggregates are needed to trigger magnetic boost. Without a magnetic field, the sticking properties of the aggregates and their constituents determine the composition of clusters of a given size. This introduces a new fractionation and sorting mechanism by cluster formation at the bouncing barrier.

Accounting for Teacher Labor Markets and Student Segregation in Analyses of Teacher Quality Gaps

Studies show that historically underserved students are disproportionately assigned to less qualified and effective teachers, leading to a “teacher quality gap.” Past analyses decompose this gap to determine whether inequitable access is driven by teacher and student sorting across and within schools. These sorting mechanisms have divergent policy implications related to school finance, student desegregation, teacher recruitment, and classroom assignment. I argue that analyses of the teacher quality gap that consider how teachers and students are sorted across labor markets offer additional policy guidance. Using statewide data from Texas, I show that teacher quality gaps are driven by sorting across school districts within the same labor market, but this finding differs depending on how “teacher quality” is defined.

Sarcoma Treatment Efficacy Portal (STEP): A novel informatics portal providing real-time, real-world outcomes to clinicians.

e23538 Background: There are currently no informatics tools that are capable of providing complex clinical decision support using real-world outcomes (RWO) for patients with sarcoma. Although existing nomograms can provide prognostic scores based on clinical or genomics features, they typically are static and lack the ability to compare outcomes for patients managed with alternative treatment strategies. To address this need, we present STEP, a Sarcoma Treatment Efficacy Portal, a web-based tool designed for real-time exploration and visualization of patient data with the potential to be integrated into clinical decision workflows during outpatient visits. Methods: At The Ohio State University, clinical histories and omics data for sarcoma patients are captured in our prospective Sarcoma Registry (NCT0267796). STEP is an interactive web-based tool built in R/Shiny and supported by a pipeline written Python that processes, transforms, and caches clinical data extracted from the Sarcoma Registry in near real-time. Protected health information (PHI) is stored on a secure HIPAA compliant server behind the hospital firewall and migrated to a secure, deidentified staging database. Results: The STEP system is powered by detailed treatment specific data elements that are continuously abstracted for over 400 patients with bone and soft tissue sarcoma. This consists of manually annotated clinical histories in addition to nearly 10 million discrete data points are pulled from the EHR (labs, ICD-9/10 codes, medications, omics data). Importantly, STEP includes a cohort builder which allows users to define a treatment group of interest though any number of variables including tumor histology, chemotherapy, and omic features of interest. For any predefined cohort, STEP can provide information on overall survival and response to a variety of treatments. It also provides sorting mechanisms for identifying candidate treatments. A secure web interface allows a simple integration into a busy clinic flow. Conclusions: STEP provides a first in class, convenient, clinician friendly platform for delivering access to real-time, real-world treatment outcomes (RWO) in patients with a diagnosis of bone or soft tissue sarcoma. Additional usability testing is forthcoming.

A novel energy sequence optimization algorithm for efficient spot-scanning proton arc (SPArc) treatment delivery

Background Spot-scanning proton arc therapy (SPArc) has been proposed to improve dosimetric outcome and to simplify treatment workflow. To efficiently deliver a SPArc plan, it’s crucial to minimize the number of energy layer switches (ELS) a sending because of the magnetic hysteresis effect. In this study, we introduced a new SPArc energy sequence optimization algorithm (SPArc_seq) to reduce ascended ELS and to investigate its impact on the beam delivery time (BDT). Method and materials An iterative energy layer sorting and re-distribution mechanism following the direction of the gantry rotation was implemented in the original SPArc algorithm (SPArc_orig). Five disease sites, including prostate, lung, brain, head neck cancer (HNC) and breast cancer were selected to evaluate this new algorithm. Dose-volume histogram (DVH) and plan robustness were used to assess the plan quality for both SPArc_seq and SPArc_orig plans. The BDT evaluations were analyzed through two methods: 1. fixed gantry angle delivery (BDTfixed) and 2. An in-house dynamic arc scanning controller simulation which considered of gantry rotation speed, acceleration and deceleration (BDTarc). Results With a similar total number of energy layers, SPArc_seq plans provided a similar nominal plan quality and plan robustness compared to SPArc_orig plans. SPArc_seq significantly reduced the number of ascended ELS by 83% (19 vs.115), 70% (16 vs. 64), 82% (19 vs. 104), 80% (19 vs. 94) and 70% (9 vs. 30), which effectively shortened the BDTfixed by 65% (386 vs. 1091 s), 61% (235 vs. 609 s), 64% (336 vs. 928 s), 48% (787 vs.1521 s) and 25% (384 vs. 511 s) and shortened BDTarc by 54% (522 vs.1128 s), 52% (310 vs.645 s), 53% (443 vs. 951 s), 49% (803 vs.1583 s) and 26% (398 vs. 534 s) in prostate, lung, brain, HNC and breast cancer, respectively. Conclusions The SPArc_seq optimization algorithm could effectively reduce the BDT compared to the original SPArc algorithm. The improved efficiency of the SPArc_seq algorithm has the potential to increase patient throughput, thereby reducing the operation cost of proton therapy.

The Development of Budgeting Module on Android based on Backpacker BackInd Applications: Sorting and Filtering Features

Decision making problems often occur in tourists to determine the activity within the tourist destinations or location. For tourists, information about attractions also is needed to allow their planning to be precise and meaningful. The BackInd (Backpacker Management System) have been developed as an application to help and support tourists by providing comprehensive information about tourist attractions through filtering and sorting mechanism. In addition to provide those type of information, tourists also allowed to buy tickets directly without much more burden to wait physically in that attractions counter. The development of this application is expected to help tourists get recommendations based on their preferences that are in accordance with the budget of the travellers. Thus, this study uses the Rapid Application Development (RAD) method, which the results focused on the featured added to the application in term of sorting, filtering and budgeting features so the homestay that tourist want will match accordingly with their plan.

RPE Cells Engulf Microvesicles Secreted by Degenerating Rod Photoreceptors.

Rhodopsin is mislocalized to the inner segment plasma membrane (IS PM) in various blinding disorders including autosomal-dominant retinitis pigmentosa caused by class I rhodopsin mutations. In these disorders, rhodopsin-laden microvesicles are secreted into the extracellular milieu by afflicted photoreceptor cells. Using a Xenopus laevis model expressing class I mutant rhodopsin or Na+/K+-ATPase (NKA) fused to Dendra2, we fluorescently labeled the microvesicles and found retinal pigment epithelial (RPE) cells are capable of engulfing microvesicles containing rhodopsin. A unique sorting mechanism allows class I mutant rhodopsin, but not NKA, to be packaged into the microvesicles. Under normal physiological conditions, NKA is not shed as microvesicles to the extracellular space, but is degraded intracellularly. Those studies provide novel insights into protein homeostasis in the photoreceptor IS PM.

Integrating fuzzy Kano model and fuzzy importance–performance analysis to analyse the attractive factors of new products

The sorting mechanism underlying the traditional evaluation grid method with attractive factors mainly represents the time or the paired comparison method. However, the current approach employed to identify abstract factors of attractiveness may not be comprehensive. The objective of this article is to propose a hybrid method with an integrated fuzzy Kano model and fuzzy importance–performance analysis to evaluate attractive factors. Fuzzy importance–performance analysis is a more accurate quantitative–qualitative method for two-dimensional analysis, and integrated fuzzy Kano model compensates for the low-resolution problem of the traditional Kano model. A combination of both models arrives at a more comprehensive and reliable evaluation grid method evaluation mechanism. The results indicate that the attractive factors sorted through integrated fuzzy Kano model–fuzzy importance–performance analysis have deconstructed abstract factors and feature factors of the customer service robot. Moreover, the key factors of the products sorted by through integrated fuzzy Kano model–fuzzy importance–performance analysis provide a better understanding of customer expectations associated with the products, which consequently enables developers and designers to accurately understand the design style and conceive new ideas.

Evaluating the WOLF® Cell Sorter impact on neutrophil viability and activation

Abstract Neutrophils have been associated with antimicrobial functions in acute infections and also play critical roles in chronic inflammation. The half-life of circulating neutrophils is estimated at between 13–19 hours and, if activated, they may be cleared even faster. The shear forces and pressure of traditional FACS can be harsh on such sensitive cells and as a result, the use of magnetic beads and centrifugation gradients to isolate neutrophils is sometimes preferred. However, these methods lack the ability to select for viability or multiple markers needed for specific subset gating. NanoCellect’s WOLF Cell Sorter allows for multi-parameter detection and sorting like traditional FACS. However, the WOLF’s microfluidic sorting mechanism uses far lower pressure (<2 psi vs 10–70 psi) that results in gentler sorting and a higher quality of cells post-sort. Here, the ability of this novel instrument to sort neutrophils with minimal cell death or activation was investigated. Live CD16+ neutrophils were sorted from whole blood and evaluated for purity, viability, and expression levels of CD11b, and CD62L. Results demonstrate that the WOLF Cell Sorter can enrich for neutrophils with high purity, viability, and a limited effect on activation, making it an effective method for neutrophil separation. This indicates that this novel microfluidic cell sorting technology can be used to study emerging neutrophil functions, mechanisms of action, and novel cell-based therapeutic approaches.

Multi-scale channel importance sorting and spatial attention mechanism for retinal vessels segmentation

Retinal Vessels segmentation is an important procedure for detecting and diagnosing a variety of pathological diseases. However, the inherent complex properties around the disc make it challenging to improve the segmenting accuracy of capillaries and the retinal blood vessels at the ends. In this paper, we proposed a multi-scale channel importance sorting and important spatial information positioning (MSCS) encoder–decoder for segmentation in Retinal Vessels. Firstly, the fully convolutional encoder–decoder is formed to implement a series of linear and non-linear transformation and achieve end-to-end segmentation tasks. Then, the channel importance sorting module is employed to suppress useless feature responses during the process of encoding and to identify effective channels, whose information is utilized to recognize capillaries and the retinal vessels at the ends. Finally, in the decoding stage, the spatial attention mechanism module is designed to extract the positioning information of multi-scale feature maps. The spatial information of retinal vessels is collected to better locate the position of the vessels. In addition, aiming at taking fully advantage of the network, the multi-scale asymmetric cascade convolution module is proposed to reduce the parameters of the model and increase the operation rate. Experimental results on DRIVE, STARE datasets indicate that the proposed method outperforms other state-of-the-art strategies. This system, as demonstrated, can greatly decrease false positive rate of the blood vessels at the ends and enhance the sharpness of retinal vessels.

Exosomal circular RNA sorting mechanisms and their function in promoting or inhibiting cancer.

Exosomes are nanoscale phospholipid bilayer vesicles that can be artificially engineered into vectors for the treatment of cancer. Circular RNA (circRNA), a type of non-coding RNA, has crucial regulatory functions in various aspects of cancer, such as tumorigenesis, apoptosis, proliferation, invasion, metastasis and chemo- and radiotherapeutic resistance, as well as in cancer prognosis. Notably, the exosomal transfer of circRNAs may function to both promote and inhibit cancer. Numerous studies have addressed the importance of circRNAs in cancer and non-coding RNAs (such as microRNAs and long non-coding RNAs) in exosomes. However, little research has focussed on a class of RNAs called exosomal circRNAs. The present review discusses current studies regarding exosomal circRNAs, including their biogenesis and biological functions, their abundance in exosomes and possible sorting mechanisms and their potential roles in both promoting and inhibiting cancer. It is predicted that in the next five years there will be increasing research exploring the functional mechanisms of exosomal circRNA in various diseases, in particular their roles in cancer genesis and progression.

NSGA-II with ENLU inspired clustering for wireless sensor networks

Wireless sensor networks (WSNs) have a large number of existing applications and is continuously increasing. Thus it is envisioned that WSN will become an integral part of our life in the near future. Direct propagation, chain formation, cluster creation are various techniques by which data is communicated by sensor nodes to the sink. It has been proved that Clustering is an efficient and scalable method to utilize the energy of sensor nodes efficiently. Optimal election of cluster heads is an NP (non deterministic polynomial time)-Hard problem. In our proposed work, a multi-objective optimization algorithm, non dominated sorting genetic algorithm-II based clustering in wireless sensor networks has been proposed. Energy conservation, network lifetime, coverage and load balancing are the four conflicting objective functions used. Our proposed algorithm handles all of these multiple objectives simultaneously. To reduce the computational complexity of the algorithm, efficient non-dominated level update mechanism for sorting has been used, which eliminates the need of applying non dominated sorting from scratch every time. The algorithm returns a solution set consisting of multiple non dominated solutions, wherein every solution is a best solution according to some objective function, in a single run, from which any solution can be chosen based on user preferences. According to our simulation carried on MATLAB, the proposed approach outperforms the established clustering algorithms in terms of network characteristics such as network lifetime, energy consumption and number of packets received.

Optimal power flow by means of improved adaptive differential evolution

Optimal power flow (OPF) problem is a large-scale, non-convex, multi-modal, and non-linear constrained optimization problem, which has been widely used in power system operation. Because of these features, solving the OPF problem is a very popular and challenging task in power system optimization. In recent years, many advanced optimization methods are employed to deal with the OPF problem. However, most of these methods are unconstrained. In this paper, an enhanced adaptive differential evolution (JADE) with self-adaptive penalty constraint handling technique, referred to as EJADE-SP, is proposed to obtain the optimal solution of the OPF problem. The EJADE-SP is an enhanced version of JADE, where four improvements are proposed to enhance the performance of JADE when solving the OPF problem: i) crossover rate (CR) sorting mechanism is introduced to allow individuals to inherit more good genes; ii) re-randomizing parameters (CR and scale factor F) to maintain the search efficiency and diversity; iii) dynamic population reduction strategy is used to accelerate convergence; and iv) self-adaptive penalty constraint handling technique is integrated to deal with the constraints. To verify the effectiveness of the proposed method, it is applied to the OPF problem on a modified IEEE 30-bus test system, which combines stochastic wind energy and solar energy with conventional thermal power generators. The simulation results demonstrate that the proposed approach can be an effective alternative for the OPF problem.

Oil Palm Sorting System of Fresh Fruit Bunch (FFB) Using Forward Chaining Algorithm

Oil palm is the producer of oil and fuel. To get a good quality, it is necessary to sort the fresh oil palm fruit based on the characteristics and criteria of the type of fresh fruit bunches (FFB). This paper aims to carry out the process of sorting the oil palm fruits using the Forward Chaining algorithm to obtain superior quality oil palm fruit based on the characteristics and criteria of fresh oil palm fruit bunches. The sorting phase purpose is to shorten industrial process phase and reduce cost. This sorting mechanism will be developed as a system that can educate oil palm farmers to do sorting before the oil palm goes through the industrial process. The research method uses a forward chaining algorithm by determining 5 criteria and 39 characteristics of fresh oil palm fruit bunches with percentage value determined by using the classical probability calculation. The accuracy of this research is 100%.

Liquid-Liquid Phase Transition Drives Intra-chloroplast Cargo Sorting

In eukaryotic cells, organelle biogenesis is pivotal for cellular function and cell survival. Chloroplasts are unique organelles with a complex internal membrane network. The mechanisms of the migration of imported nuclear-encoded chloroplast proteins across the crowded stroma to thylakoid membranes are less understood. Here, we identified two Arabidopsis ankyrin-repeat proteins, STT1 and STT2, that specifically mediate sorting of chloroplast twin arginine translocation (cpTat) pathway proteins to thylakoid membranes. STT1 and STT2 form a unique hetero-dimer through interaction of their C-terminal ankyrin domains. Binding of cpTat substrate by N-terminal intrinsically disordered regions of STT complex induces liquid-liquid phase separation. The multivalent nature of STT oligomer is critical for phase separation. STT-Hcf106 interactions reverse phase separation and facilitate cargo targeting and translocation across thylakoid membranes. Thus, the formation of phase-separated droplets emerges as a novel mechanism of intra-chloroplast cargo sorting. Our findings highlight a conserved mechanism of phase separation in regulating organelle biogenesis.

A new design approach for nearly linear phase stable IIR filter using fractional derivative

In this paper, a new design method for digital infinite impulse response &#x0028 IIR &#x0029 filters with nearly linear-phase response is presented using fractional derivative constraints &#x0028 FDCs &#x0029 . In the proposed method, design problem of an IIR filter is constructed as the minimization of phase error between the desired and designed phase response of an allpass filter &#x0028 APF &#x0029 such that the designed lowpass filter &#x0028 LPF &#x0029 or highpass filter &#x0028 HPF &#x0029 yields less passband &#x0028 ep &#x0029 , and stopband errors &#x0028 es &#x0029 with optimal stopband attenuation &#x0028 As &#x0029 . In order to have accurate passband &#x0028 pb &#x0029 response, FDCs are imposed on appropriate reference frequency, where the optimality of these FDCs are ensured by using a new greedy based sorting mechanism. The simulated results reflect the efficiency of the proposed method in term of improved passband response along with better transition width. However, small reduction in As is observed within the allowable limit, when compared to non-fractional design approach, but the designed filter remains immune to wordlength &#x0028 WL &#x0029 effect.

Triplex Inertia-Magneto-Elastic (TIME) sorting of microparticles in non-Newtonian fluids

Detection of harmful biological substances in food at the Point of Use (PoU) is very important to the prevention of foodborne diseases. Sample and reagent preparation at the PoU, as a necessary step before detection, is urgently needed. Portable and field-deployable sample preparation microfluidic devices for manipulating particles and biological substances in Newtonian fluids like water have been developed. However, understanding the mechanism of particle focusing and multiplex sorting of particles with various properties in prominent non-Newtonian fluids such as milk, blood, and DNA solutions have lagged behind. Accordingly, we developed a microfluidic device to investigate the effect of inertial, magnetic and elastic forces on the focusing of magnetic (9 and 15 µm) and non-magnetic (15 µm) particles in synthetic viscoelastic fluids with various viscosities. We also demonstrated the application of our studies in Triplex Inertia-Magneto-Elastic (TIME) sorting of these particles with purity and efficiency of more than 92%. The device included a square microchannel with a side permanent magnet, expanding symmetrically downstream to a wider channel to drop the particles velocity for on-chip imaging. We investigated the effect of multiple parameters on the focusing of each particle experimentally and analytically, in order to obtain understanding of particle dynamics and the best recipe in which triplex particle separation could be achieved with high efficiency. The studied parameters included the microchannel dimension, flow rate, fluid viscoelasticity, and magnetic field strength and exposure time. This study provides the foundation for development of devices for separation of bio-substances in viscoelastic fluids, immunologically attached to microparticles. Our device has the potential to be used for on-site sample preparation along with a variety of biosensors to render biodetection possible at the PoU.

A Two-Layered Targeting Mechanism Underlies Nuclear RNA Sorting by the Human Exosome

Degradation of transcripts in human nuclei is primarily facilitated by the RNA exosome. To obtain substrate specificity, the exosome is aided by adaptors; in the nucleoplasm, those adaptors are the nuclearexosome-targeting (NEXT) complex and the poly(A) (pA) exosome-targeting (PAXT) connection. How these adaptors guide exosome targeting remains enigmatic. Employing high-resolution 3' end sequencing, we demonstrate that NEXT substrates arise from heterogenous and predominantly pA- 3' ends often covering kilobase-wide genomic regions. In contrast, PAXT targets harbor well-defined pA+ 3' ends defined by canonical pA site use. Irrespective of this clear division, NEXT and PAXT act redundantly in two ways: (1) regional redundancy, where the majority of exosome-targeted transcription units produce NEXT- and PAXT-sensitive RNA isoforms, and (2) isoform redundancy, where the PAXT connection ensures fail-safe decay of post-transcriptionally polyadenylated NEXT targets. In conjunction, this provides a two-layered targeting mechanism for efficient nuclear sorting of the human transcriptome.