Small RNAs called PIWI-interacting RNAs (piRNAs) act as an immune system to suppress transposable elements in the animal gonads. A poorly understood adaptive pathway links cytoplasmic slicing of ...target RNA by the PIWI protein MILI to loading of target-derived piRNAs into nuclear MIWI2. Here we demonstrate that MILI slicing generates a 16-nt by-product that is discarded and a pre-piRNA intermediate that is used for phased piRNA production. The ATPase activity of Mouse Vasa Homolog (MVH) is essential for processing the intermediate into piRNAs, ensuring transposon silencing and male fertility. The ATPase activity controls dissociation of an MVH complex containing PIWI proteins, piRNAs, and slicer products, allowing safe handover of the intermediate. In contrast, ATPase activity of TDRD9 is dispensable for piRNA biogenesis but is essential for transposon silencing and male fertility. Our work implicates distinct RNA helicases in specific steps along the nuclear piRNA pathway.
Display omitted
•MILI slicing of an RNA creates a pre-piRNA intermediate and a 16-nt by-product•ATPase activity of helicase MVH is required for the pre-piRNA to mature as a piRNA•ATPase mutant MVH traps biogenesis factors, piRNAs, and slicer products•Helicase TDRD9 is essential for transposon silencing, but not piRNA biogenesis
PIWI-interacting RNAs (piRNAs) are gonad-specific small RNAs targeting transposon and cellular mRNAs and are essential to male mouse fertility. Wenda et al. uncover sequential roles for RNA helicases in piRNA biogenesis and function: MVH is essential for maturation of PIWI slicer products to piRNAs, whereas TDRD9 is essential for transposon silencing.
•Severely affected youth with comorbid social phobia (SP) and major depressive disorder (MDD) show reduced reward anticipation and processing compared to typically developing controls.•In the ...clinical group higher reward anticipation correlates with high SP symptoms and lower anticipation with high MDD symptoms.•Results are in line with the theory of heightened vigilance in anxiety and blunted reward processing due to anhedonia in MDD.
Impaired reward processing has been found in individuals with anxiety, but also major depressive disorder (MDD). Here, we studied neural correlates of reward anticipation and processing in a sample of youth with severe social phobia and comorbid depression (SP/MDD) and investigated the specific contribution of SP and MDD symptoms.
15 affected, unmedicated and 25 typically developing (TD) youth completed a monetary gambling task, which included a positive, negative and ambiguous reward condition. Event-related potentials representing cue processing (cue P300), reward anticipation (stimulus preceding negativity, SPN), reward sensitivity (feedback related negativity, FRN) and reward processing (reward P300) were analysed.
Reduced amplitudes of the right hemispheric (r)SPN and reward P300 were observed in SP/MDD compared to TD. Within the SP/MDD group SP symptoms correlated with larger rSPN, and FRN amplitudes. MDD symptoms correlated with smaller rSPN and smaller FRN positive–negative difference wave.
Reward anticipation and feedback processing are reduced in SP/MDD. Higher SP symptoms are associated with stronger neural activation during reward anticipation and reward sensitivity. Depressive symptoms are associated with decreased reward anticipation and sensitivity. Findings are in line with the theory of heightened vigilance in anxiety and blunted reward processing due to anhedonia in MDD.
The study results can inform behavioural interventions for SP and MDD.
In this study, the authors propose a new loss function for denoising convolutional neural network (DnCNN) for salt-and-pepper noise (SPN). Based on the motivation of utilising the mask of SPN, ...firstly from the usual SPN-denoising restoration equation, the authors establish a perfect restoration condition; the restored image is precisely the clean image if this condition holds. Then they design a mask-involved loss function to encourage the network to satisfy this condition in training progress. Experimental results demonstrate that compared with general DnCNN and other state-of-the-art SPN denoising methods, DnCNN equipped with the proposed loss function involving mask (MaskDnCNN) is more effective, robust and efficient.
Neurophysiological studies have shown a strong activation in visual areas in response to symmetry. Electrophysiological (EEG) studies, in particular, have confirmed that amplitude at posterior ...electrodes is more negative for symmetrical compared to asymmetrical patterns. This response is present even when observers perform tasks that do not require processing of symmetry. In this sense the activation is automatic. In this study we test this automaticity more directly by presenting stimuli that contain both symmetry and asymmetry, as overlapping patterns of dots of different colour (black and white). Observers were asked to respond to symmetry in only one of the two colours. If feature-based attention has no role the response should depend on properties of the image. If attention fully filters only the relevant colour the response should depend on properties of the relevant colour only. Neither of these models fully explained the data. We conclude that selective attention does modulate the neural response to symmetry, however we also found a significant contribution from the irrelevant pattern.
•A stochastic Petri net modeling is proposed for reliability assessment in distribution system.•Fuzzy Petri net modeling is employed to incorporate uncertainty in operating time of protective ...equipment.•For reliability assessment, stochastic Petri net is compared to fault tree analysis.•Loss of probability of situational awareness is analyzed using event tree analysis.
The sprawl of power system network paved a challenge to achieve quality and uninterrupted power to the consumers. Lack of situational awareness (SA) is a key concern, because it adversely affects the reliability of the system. This paper concerns about the co-ordination of protective equipment in distribution side of the power system network when there is a fault on any section of the network. Petri net (PN) based approach has been proposed for modeling the co-ordination between protective equipment for different fault scenarios to assess the operational reliability. The PN model encapsulates the dynamic behavior of the protective equipment together with their co-ordination. This assists in predicting the future disturbances and helps to take precautionary measures for the pre-warning situation and prevent cascaded failures, leading to enhanced SA. To analyze the effect of uncertainties in the operating time of protective equipment, fuzzy Petri net (FPN) approach has been explored. In addition, this research also incorporates a comparison between PN and fault tree, to analyze the impact of protection co-ordination modeling on power system reliability. Furthermore, event tree analysis (ETA) is used to evaluate the loss of probability of SA. The studies have been carried out on a part of distribution system and 14 bus ABB distribution system for implementation and validation of the proposed method.
Sum–product networks (SPNs) in deep probabilistic models have made great progress in computer vision, robotics, neuro-symbolic artificial intelligence, natural language processing, probabilistic ...programming languages, and other fields. Compared with probabilistic graphical models and deep probabilistic models, SPNs can balance the tractability and expressive efficiency. In addition, SPNs remain more interpretable than deep neural models. The expressiveness and complexity of SPNs depend on their own structure. Thus, how to design an effective SPN structure learning algorithm that can balance expressiveness and complexity has become a hot research topic in recent years. In this paper, we review SPN structure learning comprehensively, including the motivation of SPN structure learning, a systematic review of related theories, the proper categorization of different SPN structure learning algorithms, several evaluation approaches and some helpful online resources. Moreover, we discuss some open issues and research directions for SPN structure learning. To our knowledge, this is the first survey to focus specifically on SPN structure learning, and we hope to provide useful references for researchers in related fields.
•SPNs are deep probabilistic graphical models with complete probabilistic semantics•SPNs are more tractable than PGMs•A reasonable structure of an SPN can balance expressiveness and complexity•Analyze SPN structure learning methods and forecast future research trends.
Thoracoscopic wedge resection of small pulmonary nodules (SPNs) is a common surgical procedure. Adequate surgical margin distance is challenging and key to successful resection for malignant nodules. ...The aim of this study was to evaluate the feasibility of a novel localization needle in wedge resection for SPNs with adequate margin distance.
A retrospective review of needle localization cases from November 2021 to August 2022 was performed, in which 58 patients who underwent modified computed tomography (CT)-guided needle localization following thoracoscopic wedge resection were enrolled. Nodules were localized by placing a novel device characterized by a 4-hook anchor and a tricolored suture with a scale. The clinical characteristics were collected to evaluate the feasibility of the procedure in obtaining a sufficient margin distance.
A total of 68 SPNs were collected, and the median size of SPNs was 10.0 mm with a median depth of 18.9 mm. Needle localization was successful in 65 nodules (95.6%), and all nodules were completely removed. The median resection margin distance was 14 mm (range, 8-26 mm). There were 62 (91.2%) SPNs with a margin distance to tumor size ratio ≥1, 38 (92.7%) SPNs with a depth <20 mm, and 24 (88.9%) SPNs with a depth ≥20 mm, respectively. Regardless of the nodule depth, the median resection margin distances were both 14 mm.
This study indicated that modified preoperative CT-guided 4-hook needle with scaled suture localization is a safe, efficient strategy for the wedge resection of SPNs via thoracoscopic surgery. Furthermore, it was considerably advantageous for obtaining adequate margins distance, especially for deep nodules.
With the recent increase in the risks and attacks facing our daily lives and digital environment around us,the trend towards securing data has become inevitable. Block ciphers play a crucial role in ...modern crypto-applicationssuch as secure network storage and signatures and are used to safeguard sensitive information. The present paperdevelops a new variant of the symmetric model called SUMER family ciphers with three equivalent modes: lightweight,conventional (traditional), and extended ciphers. SUMER name belongs to one of the oldest civilizations inMesopotamia and stands for Secure Universal Model of Encryption Robust Cipher. The SUMER cipher is based on asimple and robust symmetric structure and involves solid algebraic theories that completely depend on the Galois FieldGF(28). SUMER cipher is designed to work with two involutional structures of the Substitution-Permutation Network(SPN) and Feistel structure. These two involutional structures mean that the same algorithm is used for the encryptionand decryption process, and only the algorithm of the ciphering key is used in reverse order in both structures. TheSUMER lightweight structure is an elegant mode that does not need building an S-Box that requires a large amount ofmemory and a number of electronic logical gates as S-Box construction has been canceled and replaced by the on-flycomputation clue, which does not need a reserved memory for building S-Box. SUMER family ciphers also can work ina traditional mode or as an extended mode with high margin security. This family of ciphers is applicable with multimodes of various utilizations. The proposed ciphers are designed to be byte-oriented, showing good evaluation andresults under several measurement tests for speed, time implementation, and efficiency.
The principal neurons of the striatum, the spiny projection neurons (SPNs), make inhibitory synaptic connections with each other via collaterals of their main axon, forming a local lateral inhibition ...network. Serotonin, acting via the 5-HT1B receptor, modulates neurotransmitter release from SPN terminals in striatal output nuclei, but the role of 5-HT1B receptors in lateral inhibition among SPNs in the striatum is unknown. Here, we report the effects of 5-HT1B receptor activation on lateral inhibition in the mouse striatum. Whole-cell recordings were made from SPNs in acute brain slices of either sex, while optogenetically activating presynaptic SPNs or fast-spiking interneurons (FSIs). Activation of 5-HT1B receptors significantly reduced the amplitude of IPSCs evoked by optical stimulation of both direct and indirect pathway SPNs. This reduction was blocked by application of a 5-HT1B receptor antagonist. Activation of 5-HT1B receptors did not reduce the amplitude of IPSCs evoked from FSIs. These results suggest a new role for serotonin as a modulator of lateral inhibition among striatal SPNs. The 5-HT1B receptor may, therefore, be a suitable target for future behavioral experiments investigating the currently unknown role of lateral inhibition in the function of the striatum.
PDF
