Intracellular ribonucleoprotein (RNP) granules are membrane‐less droplet organelles that are thought to regulate posttranscriptional gene expression. While liquid–liquid phase separation may drive ...RNP granule assembly, the mechanisms underlying their supramolecular dynamics and internal organization remain poorly understood. Herein, we demonstrate that RNA, a primary component of RNP granules, can modulate the phase behavior of RNPs by controlling both droplet assembly and dissolution in vitro. Monotonically increasing the RNA concentration initially leads to droplet assembly by complex coacervation and subsequently triggers an RNP charge inversion, which promotes disassembly. This RNA‐mediated reentrant phase transition can drive the formation of dynamic droplet substructures (vacuoles) with tunable lifetimes. We propose that active cellular processes that can create an influx of RNA into RNP granules, such as transcription, can spatiotemporally control the organization and dynamics of such liquid‐like organelles.
Vacuolated ribonucleoprotein droplets: RNA controls the reentrant phase transition of ribonucleoproteins (RNPs) to assemble and dissolve RNP droplets. During dissolution, controlled RNA flux into the RNP droplets generates dynamic vacuolated substructures with tunable lifetimes.
•Proposes Tri-Staged Feature Selection (TFS) for multi-class heterogeneous datasets.•Initial features are selected using Kruskal Wallis Test.•Refinement of obtained features using Memetic Algorithm ...with local beam search.•Final feature set refinement using Cuckoo search algorithm for better classification.•Experiments conducted on 12 real datasets for validation of proposed method.
Classification algorithms and their preprocessing operations usually performs on feature selection on homogeneous or heterogeneous attributes, binary or multi-class labels separately. Only very few methods attempt to perform feature selection on datasets with heterogeneous multi-class attributes. In order to bridge this gap with better classification performance, the paper proposes a Tri-staged Feature Selection (TFS) methodology which performs (i) Feature selection using Kruskal Wallis test (ii) Refinement of feature selection using a new Memetic Algorithm with local beam search and genetic algorithm operations and (iii) Further refinement of feature selection using Cuckoo Search algorithm. Proper tradeoff between both exploration and exploitation is maintained in the proposed method. The experimental results on 12 datasets show that the proposed method is better than that of state-of-the-art methods used for feature selection in terms of multi-class accuracy, hamming loss, ranking loss, normalized coverage and convergence rate for multi-class heterogeneous datasets.
Aluminum-doped lanthanum phosphate (LaPO
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:Al) nanoparticles were synthesized using a simple co-precipitation technique. The x-ray diffraction patterns show that all of the collected samples have a ...monoclinic structure with crystallite size (D) increasing from 13 to 17 nm as the Al-doping concentration increases, whereas the band gap values dropped from 5.46 eV to 3.93 eV with the increased Al-doping concentration. The effect of I–V electrical performance was methodically investigated in 10% Al-doped LaPO
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-based metal–insulator–semiconductor (MIS)-type Schottky barrier diodes (SBDs). The experimental results reveal that the changes in the barrier height of 0.772 eV and the lowest ideality factor of 2.95 were both attained under light irradiation. In the comparison of the values of the undoped Cu/LaPO
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/
n
-Si and Cu/Al-LaPO
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/
n
-Si Schottky barrier diodes, the Al-LaPO
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/
n
-Si Schottky barrier diode was found to possess a significantly better barrier height (
ϕ
B
) and ideality factor values (
n
) than the other. The reported results in this work are among the best to date for 10% Al-doped LaPO
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Schottky barrier diodes.
Graphical Abstract
Synthesis of undoped and Al doped LaPO
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NPs and fabrication of Cu/AL-LaPO
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/n-Si based metal-insulator-semiconductor (MIS) Schottky barrier diodes (SBDs).
Liquid-liquid phase separation (LLPS) of RNA-protein complexes plays a major role in the cellular function of membraneless organelles (MLOs). MLOs are sensitive to changes in cellular conditions, ...such as fluctuations in cytoplasmic ion concentrations. To investigate the effect of these changes on MLOs, we studied the influence of divalent cations on the physical and chemical properties of RNA coacervates. Using a model system comprised of an arginine-rich peptide and RNA, we predicted and observed that variations in signaling cations exert interaction-dependent effects on RNA LLPS. Changing the ionic environment has opposing effects on the propensity for heterotypic peptide-RNA and homotypic RNA LLPS, which results in a switch between coacervate types. Furthermore, divalent ion variations continuously tune the microenvironments and fluid properties of heterotypic and homotypic droplets. Our results may provide a general mechanism for modulating the biochemical environment of RNA coacervates in a cellular context.
Individuals use Vehicular Ad Hoc Networks (VANETs) to secure, reliable communication networks as a viable route of transmission. Platooning uses Inter-Vehicular Communication to supervise a group of ...vehicles (IVC). The information communicated, especially acceleration, location, and speed, can then be used to respond by longitudinal control legislation. Platoons require help between those vehicles to improve fuel efficiency, security, and various crises associated with driver errors. Despite these advances, the communication network must govern vehicles unprotected from adequate threat vectors, which malicious attacks might exploit. Considering that connected cars between trusts could increase security, whereas all active automobiles can develop and spread legitimate, accurate, and recognized information within the network. So, considering badmouth, this work proposes a unique node centric weight-based trust management algorithm (NC-WTM). By quickly recognising and deleting fraudulent vehicles and their generated messages, the NC-WTM (node-centric weighted trust management) technique improves aggregate platoon security. The NC-WTM beats the robust and privacy-preserving reputation management scheme (RPRep) and the attack resistant trust management scheme (ART) trust designs regarding accuracy, recall, and F-score. Metrics, such as precision results of 78%, recall of 69.3%, F-score of 60.4%, and accuracy of 89%, are achieved and optimised in this trust model.
Abbreviations: VANETs: vehicular ad hoc networks; IVC: inter-vehicular communication; NC-WTM: node-centric weight-based trust management algorithm; WTM: weight-based trust management algorithm; RPRep: robust and privacy-preserving reputation management scheme; ART: attack-resistant trust management scheme; MANET: mobile ad hoc network; DSRC: dedicated short-range communication; WAVE: wireless access in vehicular environment; IVC: inter-vehicular communication; I2V: infrastructure-to-vehicle; V2I: vehicle-to-infrastructure; V2V: vehicle-to-vehicle; TA: trust authority; RSU: road side unit; OBU: on-board unit; GPS: global positioning system; WSN: wireless sensor network; VASNETs: vehicular sensor networks; CCW: cooperative collision warning; BMA: bad mouth attack; TDMA: time division multiple access; GDVAN: greedy detection for VANETs; SMTS: spider monkey time synchronization; SVM: support vector machine; DST: Dempster-Shafer theory of evidence; TA: trust authority; PCA: puzzle-based co-authentication; VLC: visible light communication; NE: Nash equilibrium; RTB: request-to-broadcast; CTB: clear-to-broadcast; RREQ: route request message; RREP: route reply; DDR: data disseminate ratio; Dir: direct trust; IDir: indirect trust; TCE: trust computation error; PDR: packet delivery ratio
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The therapeutic resistance of pancreatic ductal adenocarcinoma (PDAC) is partly ascribed to ineffective delivery of chemotherapy to cancer cells. We hypothesized that physical properties at vascular, ...extracellular, and cellular scales influence delivery of and response to gemcitabine-based therapy.
We developed a method to measure mass transport properties during routine contrast-enhanced CT scans of individual human PDAC tumors. Additionally, we evaluated gemcitabine infusion during PDAC resection in 12 patients, measuring gemcitabine incorporation into tumor DNA and correlating its uptake with human equilibrative nucleoside transporter (hENT1) levels, stromal reaction, and CT-derived mass transport properties. We also studied associations between CT-derived transport properties and clinical outcomes in patients who received preoperative gemcitabine-based chemoradiotherapy for resectable PDAC.
Transport modeling of 176 CT scans illustrated striking differences in transport properties between normal pancreas and tumor, with a wide array of enhancement profiles. Reflecting the interpatient differences in contrast enhancement, resected tumors exhibited dramatic differences in gemcitabine DNA incorporation, despite similar intravascular pharmacokinetics. Gemcitabine incorporation into tumor DNA was inversely related to CT-derived transport parameters and PDAC stromal score, after accounting for hENT1 levels. Moreover, stromal score directly correlated with CT-derived parameters. Among 110 patients who received preoperative gemcitabine-based chemoradiotherapy, CT-derived parameters correlated with pathological response and survival.
Gemcitabine incorporation into tumor DNA is highly variable and correlates with multiscale transport properties that can be derived from routine CT scans. Furthermore, pretherapy CT-derived properties correlate with clinically relevant endpoints.
Clinicaltrials.gov NCT01276613.
Lustgarten Foundation (989161), Department of Defense (W81XWH-09-1-0212), NIH (U54CA151668, KCA088084).
Turmeric is affected by various diseases during its growth process. Not finding its diseases at early stages may lead to a loss in production and even crop failure. The most important thing is to ...accurately identify diseases of the turmeric plant. Instead of using multiple steps such as image pre-processing, feature extraction, and feature classification in the conventional method, the single-phase detection model is adopted to simplify recognizing turmeric plant leaf diseases. To enhance the detection accuracy of turmeric diseases, a deep learning-based technique called the Improved YOLOV3-Tiny model is proposed. To improve detection accuracy than YOLOV3-tiny, this method uses residual network structure based on the convolutional neural network in particular layers. The results show that the detection accuracy is improved in the proposed model compared to the YOLOV3-Tiny model. It enables anyone to perform fast and accurate turmeric leaf diseases detection. In this paper, major turmeric diseases like leaf spot, leaf blotch, and rhizome rot are identified using the Improved YOLOV3-Tiny algorithm. Training and testing images are captured during both day and night and compared with various YOLO methods and Faster R-CNN with the VGG16 model. Moreover, the experimental results show that the Cycle-GAN augmentation process on turmeric leaf dataset supports much for improving detection accuracy for smaller datasets and the proposed model has an advantage of high detection accuracy and fast recognition speed compared with existing traditional models.
In the recent scenario of global warming and climate change, numerous biotic and abiotic stresses inhibit crop growth and development and finally lead to reduced crop productivity. When it comes to ...overcoming biotic and abiotic constraints for sustainable agriculture, nanotechnology is gradually gaining its position over other approaches. Silicon (Si), one of nature's most beneficial metalloids, provides ameliorative effects against issues related to the environment. Due to their remarkable chemical and optoelectronic properties, silicon/silica nanoparticles (Si/SiO2 NPs) have drawn particular attention. Researchers have found it to be particularly appealing due to its mesoporous structure, ease of nutrient availability, and low biological toxicity. Plants can be supplied with SiNPs through foliar, soil, or seed priming after being synthesized using chemical, physical, or biological techniques. Subsequently, the application and delivery of SiNPs to their target cells exhibit optimal growth, development, and tolerance to environmental stresses, pest attack, and pathogen infection. Compared to synthetic pesticides, SiNPs prevent environmental pollution and risk to non-target organisms. The use of SiNPs in agriculture provides an ecologically and inexpensive solution for sustainability, as they facilitate the uptake of nutrients by plants, helping them to overcome biotic and abiotic stress, and primarily improving plant resistance. This review aims to provide an overview of the effects of SiNPs on plants, their application in different crops, translocation, enhanced crop productivity, interaction with rhizospheric microbiome, and management of insect pests and disease.
•Global warming and climate changes pose biotic and abiotic stresses on crops, reducing productivity.•Silicon nanoparticles offer mesoporous structure, low toxicity, and easy nutrient availability for improved plant growth.•Silicon nanoparticles can be applied through foliar, soil, or seed priming, enhancing growth, stress tolerance, and pest resistance.•Silicon nanoparticles are an eco-friendly alternative to synthetic pesticides, promoting sustainability and preventing environmental pollution.
In this review, the EMI shielding properties of the various carbonaceous fillers are thoroughly reviewed. Electromagnetic interference (EMI) had been a cause of major concern in the live ...broadcasting, entertainment, aviation and defense industries since vital radio signals could create more interference, which could lead to poor performance. To reduce the effect of EMI, the organic polymeric composites along with the carbonaceous fillers are mostly used since they are flexible, low denser, high mechanical strength, high thermo‐stability, high electrical and thermal conductivity, excellent fracture toughness, and high friction/wear resistance. There are lot of carbon based materials are being used as EMI shielding material in mono and compound form. This review gives a broad understanding of the utilization of carbonaceous fillers in polymer matrixes. Thus, the overall coverage on this carbon based materials and their effectiveness could help the researchers to find right carbon material for suitable application. According to this review, the absorption mechanism is vital to achieve high EMI shielding effect. The fillers such as graphene and CNTs are most preferable EMI shielding filler, according to the vast coverage of previous articles. However, there are more magnetoelectric materials also evolved recently, having combined properties of both conductive and magnetic, yielding high SE at elevated frequencies.
The incomplete datasets with missing values are unsuitable for making strategic decisions since they lead to biased results. This problem is even worse when the dataset is large and collected from ...many heterogeneous sources. The paper deals with missing scenarios which were not dealt together earlier. The proposed Dual Repopulated Bayesian Ant Colony Optimization (DPBACO) handles both ignorable and non-ignorable missing values in heterogeneous attributes of large datasets The DPBACO integrates Bayesian principles with Ant Colony Optimization technique since both are simple and efficient to implement. After pheromone updation, repopulation of the solution pool is done by dividing the population into two based on their fitness values and generating new offsprings by performing crossover operation. The DPBACO algorithm is implemented on six large mixed-attribute datasets for imputing both kinds of missing values. The empirical and statistical results show that DPBACO performs better than other existing methods at variable missing rates ranging from 5% to 50%.
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