Experimental demonstration of flexible information rate PON beyond 100 Gb/s with rate-compatible LDPC codes.

The applications of rate-compatible low-density parity-check (RC-LDPC) codes are investigated for a 16 quadrature amplitude modulation (16QAM) signal and coherent detection system. With rate-compatible signals, we can provide the flexible net data rate between 135.5 Gb/s and 169.7 Gb/s in a passive optical network (PON) link. Based on the LDPC codes defined in the IEEE 802.3ca standard, we construct two sets of RC-LDPC codes with a fixed and variable information bit length. Since the puncturing operation may degrade the performance of LDPC codes, we apply the protograph-based extrinsic information transfer (PEXIT) technique to optimize the puncturing positions to mitigate the degradation. Additionally, we explore four low-complexity LDPC decoding algorithms (min sum, offset min sum, variable weight min sum, and relaxed min sum with 2nd min emulation) to investigate the relationship between the computational complexity and decoding performance. Simulation results indicate that the constructed codewords exhibit good performance in the waterfall region across a range of code rates. Finally, we conduct an experimental setup in a dual-polarization 25 GBaud 16QAM coherent PON to verify the effectiveness of the constructed LDPC codes with four decoding algorithms. The experimental results show maximal 4.8 dB receiver sensitivity differences, which demonstrate the feasibility of the method for constructing RC-LDPC codes in future high-speed flexible coherent PON.

Underwater laser positioning of targets outside the field of view based on a binocular vision.

An underwater laser positioning scheme based on a binocular camera is introduced. In spite of the scattering, the underwater laser light path can be clearly captured by a camera within an appropriate range depending on the water turbidity. For an emitting laser with a fixed position, the three-dimensional information of the laser source can be calculated from the beam images captured by a binocular camera, even if the laser is out of the camera's field of view (FOV). This method can break through the FOV limitation of traditional camera positioning and perform a 3D spatial positioning for the target even outside the FOV of the camera. We simulate and analyze the scattering light imaging and find that the laser propagation direction can be recognized from the scattering image. The experimental results show that the proposed underwater positioning scheme achieves an average 3D positioning error of 5.53 cm within a range of 5 m when the underwater attenuation is 0.325m -1.

ACSL4-Mediated Ferroptosis and Its Potential Role in Central Nervous System Diseases and Injuries.

As an iron-dependent regulated form of cell death, ferroptosis is characterized by iron-dependent lipid peroxidation and has been implicated in the occurrence and development of various diseases, including nervous system diseases and injuries. Ferroptosis has become a potential target for intervention in these diseases or injuries in relevant preclinical models. As a member of the Acyl-CoA synthetase long-chain family (ACSLs) that can convert saturated and unsaturated fatty acids, Acyl-CoA synthetase long-chain familymember4 (ACSL4) is involved in the regulation of arachidonic acid and eicosapentaenoic acid, thus leading to ferroptosis. The underlying molecular mechanisms of ACSL4-mediated ferroptosis will promote additional treatment strategies for these diseases or injury conditions. Our review article provides a current view of ACSL4-mediated ferroptosis, mainly including the structure and function of ACSL4, as well as the role of ACSL4 in ferroptosis. We also summarize the latest research progress of ACSL4-mediated ferroptosis in central nervous system injuries and diseases, further proving that ACSL4-medicated ferroptosis is an important target for intervention in these diseases or injuries.

Assembly of model postsynaptic densities involves interactions auxiliary to stoichiometric binding.

The assembly of functional biomolecular condensates often involves liquid-liquid phase separation (LLPS) of proteins with multiple modular domains, which can be folded or conformationally disordered to various degrees. To understand the LLPS-driving domain-domain interactions, a fundamental question is how readily the interactions in the condensed phase can be inferred from interdomain interactions in dilute solutions. In particular, are the interactions leading to LLPS exclusively those underlying the formation of discrete interdomain complexes in homogeneous solutions? We address this question by developing a mean-field LLPS theory of two stoichiometrically constrained solute species. The theory is applied to the neuronal proteins SynGAP and PSD-95, whose complex coacervate serves as a rudimentary model for neuronal postsynaptic densities (PSDs). The predicted phase behaviors are compared with experiments. Previously, a three SynGAP/two PSD-95 ratio was determined for SynGAP/PSD-95 complexes in dilute solutions. However, when this 3:2 stoichiometry is uniformly imposed in our theory encompassing both dilute and condensed phases, the tie-line pattern of the predicted SynGAP/PSD-95 phase diagram differs drastically from that obtained experimentally. In contrast, theories embodying alternate scenarios postulating auxiliary SynGAP-PSD-95 as well as SynGAP-SynGAP and PSD-95-PSD-95 interactions, in addition to those responsible for stoichiometric SynGAP/PSD-95 complexes, produce tie-line patterns consistent with experiment. Hence, our combined theoretical-experimental analysis indicates that weaker interactions or higher-order complexes beyond the 3:2 stoichiometry, but not yet documented, are involved in the formation of SynGAP/PSD-95 condensates, imploring future efforts to ascertain the nature of these auxiliary interactions in PSD-like LLPS and underscoring a likely general synergy between stoichiometric, structurally specific binding and stochastic, multivalent "fuzzy" interactions in the assembly of functional biomolecular condensates.

Joint design of ordered QR precoding and SIC detection for MIMO VLC systems.

Ordered successive interference cancellation (OSIC) detection has been investigated to mitigate the high spatial correlation for multiple-input multiple-output (MIMO) visible light communication (VLC) systems. However, existing OSIC schemes have to perform reordering and matrix inversion for each detected symbol, which may lead to high complexity when a large number of symbols are transmitted. In this work, a joint design of ordered QR decomposition precoding and SIC detection (OQR-SIC) is proposed for MIMO VLC systems. This work jointly investigates OQR precoding and SIC detection to reduce the detection complexity while alleviating spatial correlation issue for MIMO VLC systems. In OQR-SIC, with the upper triangular matrix obtained by QR decomposition, the SIC detector can detect the symbol sequentially without reordering and matrix inversion calculations. To improve the system data rate, we further optimize the ordering of the columns of the channel matrix before QR decomposition and the power allocation of transmitted signals under the constraints of dimming control, total electrical power and reliable SIC detection. Simulation results demonstrate that the proposed OQR-SIC achieves 2 dB and 9.8 dB signal-to-noise ratio gains compared to conventional QR-SIC in 4 × 4 and 9 × 9 MIMO VLC systems, respectively, when the bit error rate is 10-3.

Partially pruned DNN coupled with parallel Monte-Carlo algorithm for path loss prediction in underwater wireless optical channels.

In this paper, we propose a new approach to solve the radiative transfer equation (RTE) and determine the path loss for line-of-sight (LOS) propagation with laser diode sources in underwater wireless optical channels, which severely suffers from attenuation due to inevitable absorption and scattering. The scheme is based on an effective combination of Monte-Carlo (MC) simulation employed for dataset generation and a partially pruned deep neural network (PPDNN) utilized to predict the received optical power. First, a parallel MC algorithm is newly introduced and applied to speed up the dataset-generation process. Compared with the conventional single-step MC, the dataset-generation time of the parallel MC can be reduced by at least 95%. Meanwhile, a deep neural network (DNN) is partially pruned to acquire a compact structure and adopted to predict the path loss in three typical water types. The simulation results yield that the mean square errors (MSEs) between the predictive and the reference ones are all lower than 0.2, while the sparsity of the original DNN's weights can be appropriately increased to 0.9, 0.7, and 0.5 for clear water, coastal water, and harbor water, respectively. Finally, the occupied storage space of the original DNN can be dramatically compressed by at least 40% with a small performance penalty. In view of this, the received optical power under certain parameters could be instantly obtained by employing the proposed PPDNN, which can effectively help design underwater wireless optical communication systems in future work.

Demonstration of a 2 × 2 MIMO-UWOC system with large spot against air bubbles.

In order to reduce turbulence-induced scintillation and deal with alignment problems, a 2×2 multiple-input multiple-output (MIMO) underwater wireless optical communication (UWOC) system is proposed and experimentally demonstrated. With help of the large divergence angle of light beams and large field of view (FOV) of the detectors, the effect of high-density air bubbles is greatly eliminated. Simulation and experimental results confirm that, in most intensity-modulation/direct-detection (IM/DD) MIMO-UWOC systems, the repetition coding (RC) scheme performs better than the space-time block coding (STBC) scheme. In a 50 m swimming pool, the maximum horizontal offset can reach 97.9 cm, which is 421% and 192% higher than that of STBC multiple-input single-output (MISO) and RC-MISO/STBC-MIMO schemes, respectively. With a data rate of 233 Mbps and a transmission distance of 50 m, the large detection range can meet a variety of underwater wireless communication requirements. The experiment indicates that, when the difference in the transmission distance between the two optical signals is higher than 1 m, the bit error rate (BER) of the RC scheme increases sharply, while the BER of the STBC scheme is stable. The MIMO coding scheme needs to be selected according to the actual application environment.

Liquid-Liquid Phase Separation in Biology: Specific Stoichiometric Molecular Interactions vs Promiscuous Interactions Mediated by Disordered Sequences.

Extensive studies in the past few years have shown that nonmembrane bound organelles are likely assembled via liquid-liquid phase separation (LLPS), a process that is driven by multivalent protein-protein and/or protein-nucleic acid interactions. Both stoichiometric molecular interactions and intrinsically disordered region (IDR)-driven interactions can promote the assembly of membraneless organelles, and the field is currently dominated by IDR-driven biological condensate formation. Here we discuss recent studies that demonstrate the importance of specific biomolecular interactions for functions of diverse physiological condensates. We suggest that phase separation based on combinations of specific interactions and promiscuous IDR-driven interactions is likely a general feature of biological condensation under physiological conditions.

Glucose starvation induces mitochondrial fragmentation depending on the dynamin GTPase Dnm1/Drp1 in fission yeast.

Mitochondria undergo morphological and dynamic changes in response to environmental stresses. Few studies have focused on addressing mitochondrial remodeling under stress. Using the fission yeast Schizosaccharomyces pombe as a model organism, here we investigated mitochondrial remodeling under glucose starvation. We employed live-cell microscopy to monitor mitochondrial morphology and dynamics of cells in profusion chambers under glucose starvation. Our results revealed that mitochondria fragment within minutes after glucose starvation and that the dynamin GTPase Dnm1 is required for promoting mitochondrial fragmentation. Moreover, we found that glucose starvation enhances Dnm1 localization to mitochondria and increases the frequency of mitochondrial fission but decreases PKA activity. We further demonstrate that low PKA activity enhances glucose starvation-induced mitochondrial fragmentation, whereas high PKA activity confers resistance to glucose starvation-induced mitochondrial fragmentation. Moreover, we observed that AMP-activated protein kinase is not involved in regulating mitochondrial fragmentation under glucose starvation. Of note, glucose starvation-induced mitochondrial fragmentation was associated with enhanced reactive oxygen species production. Our work provides detailed mechanistic insights into mitochondrial remodeling in response to glucose starvation.

Frequency Feature Learning from Vibration Information of GIS for Mechanical Fault Detection.

The reliability of gas insulated switchgear (GIS) is very important for the safe operation of power systems. However, the research on potential faults of GIS is mainly focused on partial discharge, and the research on the intelligent detection technology of the mechanical state of GIS is very scarce. Based on the abnormal vibration signals generated by a GIS fault, a fault diagnosis method consisting of a frequency feature extraction method based on coherent function (CF) and a multi-layer classifier was developed in this paper. First, the Fourier transform was used to analyze the differences and consistency in the frequency spectrum of signals. Secondly, the frequency domain commonalities of the vibration signals were extracted by using CF, and the vibration characteristics were screened twice by using the correlation threshold and frequency threshold to further select the vibration features for diagnosis. Then, a multi-layer classifier composed of two one-class support vector machines (OCSVMs) and one support vector machine (SVM) was designed to classify the faults of GIS. Finally, the feasibility of the feature extraction method was verified by experiments, and compared with other classification methods, the stability and reliability of the proposed classifier were verified, which indicates that the fault diagnosis method promotes the development of an intelligent detection technology of the mechanical state in GIS.

Intelligent Fault Diagnosis of HVCB with Feature Space Optimization-Based Random Forest.

Mechanical faults of high-voltage circuit breakers (HVCBs) always happen over long-term operation, so extracting the fault features and identifying the fault type have become a key issue for ensuring the security and reliability of power supply. Based on wavelet packet decomposition technology and random forest algorithm, an effective identification system was developed in this paper. First, compared with the incomplete description of Shannon entropy, the wavelet packet time-frequency energy rate (WTFER) was adopted as the input vector for the classifier model in the feature selection procedure. Then, a random forest classifier was used to diagnose the HVCB fault, assess the importance of the feature variable and optimize the feature space. Finally, the approach was verified based on actual HVCB vibration signals by considering six typical fault classes. The comparative experiment results show that the classification accuracy of the proposed method with the origin feature space reached 93.33% and reached up to 95.56% with optimized input feature vector of classifier. This indicates that feature optimization procedure is successful, and the proposed diagnosis algorithm has higher efficiency and robustness than traditional methods.

The Interplay between Ferroptosis and Neuroinflammation in Central Neurological Disorders.

Central neurological disorders are significant contributors to morbidity, mortality, and long-term disability globally in modern society. These encompass neurodegenerative diseases, ischemic brain diseases, traumatic brain injury, epilepsy, depression, and more. The involved pathogenesis is notably intricate and diverse. Ferroptosis and neuroinflammation play pivotal roles in elucidating the causes of cognitive impairment stemming from these diseases. Given the concurrent occurrence of ferroptosis and neuroinflammation due to metabolic shifts such as iron and ROS, as well as their critical roles in central nervous disorders, the investigation into the co-regulatory mechanism of ferroptosis and neuroinflammation has emerged as a prominent area of research. This paper delves into the mechanisms of ferroptosis and neuroinflammation in central nervous disorders, along with their interrelationship. It specifically emphasizes the core molecules within the shared pathways governing ferroptosis and neuroinflammation, including SIRT1, Nrf2, NF-κB, Cox-2, iNOS/NO·, and how different immune cells and structures contribute to cognitive dysfunction through these mechanisms. Researchers' findings suggest that ferroptosis and neuroinflammation mutually promote each other and may represent key factors in the progression of central neurological disorders. A deeper comprehension of the common pathway between cellular ferroptosis and neuroinflammation holds promise for improving symptoms and prognosis related to central neurological disorders.

Demixing is a default process for biological condensates formed via phase separation.

Excitatory and inhibitory synapses do not overlap even when formed on one submicron-sized dendritic protrusion. How excitatory and inhibitory postsynaptic cytomatrices or densities (e/iPSDs) are segregated is not understood. Broadly, why membraneless organelles are naturally segregated in cellular subcompartments is unclear. Using biochemical reconstitutions in vitro and in cells, we demonstrate that ePSDs and iPSDs spontaneously segregate into distinct condensed molecular assemblies through phase separation. Tagging iPSD scaffold gephyrin with a PSD-95 intrabody (dissociation constant ~4 nM) leads to mistargeting of gephyrin to ePSD condensates. Unexpectedly, formation of iPSD condensates forces the intrabody-tagged gephyrin out of ePSD condensates. Thus, instead of diffusion-governed spontaneous mixing, demixing is a default process for biomolecules in condensates. Phase separation can generate biomolecular compartmentalization specificities that cannot occur in dilute solutions.

Enhanced Tunability of Dual-Band Chiral Metasurface in the Mid-Infrared Range via Slotted Nanocircuit Design.

Multi-band circular dichroism (CD) response and tunability on the chiral metasurface are crucial for this device's applications in sensing and detection. This work proposes a dual-band CD Au-CaF2-Au dimer elliptical metasurface absorber, where chiroptical sensing is realized by breaking the geometric symmetry between two ellipses. The proposed metasurface can achieve high CD values of 0.8 and -0.74 for the dual-band within the 3-5 µm region, and the CD values can be manipulated by independently adjusting the geometric parameters of the metasurface. Furthermore, a slotted nanocircuit is introduced onto the metasurface to enhance its tunability by manipulating the geometry parameter in the design process, and the related mechanism is explained using an equivalent circuit model. The simulation of the sensing model revealed that the slotted nanocircuit enhances the sensor's tunability and significantly improves its bandwidth and sensitivity, achieving peak enhancements at approximately 753 nm and 1311 nm/RIU, respectively. Due to the strong dual-band positive (and negative) responses of the CD values, flexible wavelength tunability, and nonlinear sensitivity enhancement, this design provides a new approach for the development and application of mid-infrared chiroptical devices.

Phase separation-mediated actin bundling by the postsynaptic density condensates.

The volume and the electric strength of an excitatory synapse is near linearly correlated with the area of its postsynaptic density (PSD). Extensive research in the past has revealed that the PSD assembly directly communicates with actin cytoskeleton in the spine to coordinate activity-induced spine volume enlargement as well as long-term stable spine structure maintenance. However, the molecular mechanism underlying the communication between the PSD assembly and spine actin cytoskeleton is poorly understood. In this study, we discover that in vitro reconstituted PSD condensates can promote actin polymerization and F-actin bundling without help of any actin regulatory proteins. The Homer scaffold protein within the PSD condensates and a positively charged actin-binding surface of the Homer EVH1 domain are essential for the PSD condensate-induced actin bundle formation in vitro and for spine growth in neurons. Homer-induced actin bundling can only occur when Homer forms condensate with other PSD scaffold proteins such as Shank and SAPAP. The PSD-induced actin bundle formation is sensitively regulated by CaMKII or by the product of the immediate early gene Homer1a. Thus, the communication between PSD and spine cytoskeleton may be modulated by targeting the phase separation of the PSD condensates.

Multi-functional nanocellulose based nanocomposites for biodegradable food packaging: Hybridization, fabrication, key properties and application.

Nowadays, non-degradable plastic packaging materials have caused serious environmental pollution, posing a threat to human health and development. Renewable eco-friendly nanocellulose hybrid (NCs-hybrid) composites as an ideal alternative to petroleum-based plastic food packaging have been extensively reported in recent years. NCs-hybrids include metal, metal oxides, organic frameworks (MOFs), plants, and active compounds. However, no review systematically summarizes the preparation, processing, and multi-functional applications of NCs-hybrid composites. In this review, the design and hybridization of various NCs-hybrids, the processing of multi-scale nanocomposites, and their key properties in food packaging applications were systematically explored for the first time. Moreover, the synergistic effects of various NCs-hybrids on several properties of composites, including mechanical, thermal, UV shielding, waterproofing, barrier, antimicrobial, antioxidant, biodegradation and sensing were reviewed in detailed. Then, the problems and advances in research on renewable NCs-hybrid composites are suggested for biodegradable food packaging applications. Finally, a future packaging material is proposed by using NCs-hybrids as nanofillers and endowing them with various properties, which are denoted as "PACKAGE" and characterized by "Property, Application, Cellulose, Keen, Antipollution, Green, Easy."

Biological condensates form percolated networks with molecular motion properties distinctly different from dilute solutions.

Formation of membraneless organelles or biological condensates via phase separation and related processes hugely expands the cellular organelle repertoire. Biological condensates are dense and viscoelastic soft matters instead of canonical dilute solutions. To date, numerous different biological condensates have been discovered, but mechanistic understanding of biological condensates remains scarce. In this study, we developed an adaptive single-molecule imaging method that allows simultaneous tracking of individual molecules and their motion trajectories in both condensed and dilute phases of various biological condensates. The method enables quantitative measurements of concentrations, phase boundary, motion behavior, and speed of molecules in both condensed and dilute phases, as well as the scale and speed of molecular exchanges between the two phases. Notably, molecules in the condensed phase do not undergo uniform Brownian motion, but instead constantly switch between a (class of) confined state(s) and a random diffusion-like motion state. Transient confinement is consistent with strong interactions associated with large molecular networks (i.e., percolation) in the condensed phase. In this way, molecules in biological condensates behave distinctly different from those in dilute solutions. The methods and findings described herein should be generally applicable for deciphering the molecular mechanisms underlying the assembly, dynamics, and consequently functional implications of biological condensates.

TrkB agonist N-acetyl serotonin promotes functional recovery after traumatic brain injury by suppressing ferroptosis via the PI3K/Akt/Nrf2/Ferritin H pathway.

Ferroptosis is a form of regulated cell death that is mainly triggered by iron-dependent lipid peroxidation. A growing body of evidence suggests that ferroptosis is involved in the pathophysiology of traumatic brain injury (TBI), and tropomyosin-related kinase B (TrkB) deficiency would mediate TBI pathologies. As an agonist of TrkB and an immediate precursor of melatonin, N-acetyl serotonin (NAS) exerts several beneficial effects on TBI, but there is no information regarding the role of NAS in ferroptosis after TBI. Here, we examined the effect of NAS treatment on TBI-induced functional outcomes and ferroptosis. Remarkably, the administration of NAS alleviated TBI-induced neurobehavioral deficits, lesion volume, and neurodegeneration. NAS also rescued TBI-induced mitochondrial shrinkage, the changes in ferroptosis-related molecule expression, and iron accumulation in the ipsilateral cortex. Similar results were obtained with a well-established ferroptosis inhibitor, liproxstatin-1. Furthermore, NAS activated the TrkB/PI3K/Akt/Nrf2 pathway in the mouse model of TBI, while inhibition of PI3K and Nrf2 weakened the protection of NAS against ferroptosis both in vitro and in vivo, suggesting that a possible pathway linking NAS to the action of anti-ferroptosis was TrkB/PI3K/Akt/Nrf2. Given that ferritin H (Fth) is a known transcription target of Nrf2, we then investigated the effects of NAS on neuron-specific Fth knockout (Fth-KO) mice. Strikingly, Fth deletion almost abolished the protective effects of NAS against TBI-induced ferroptosis and synaptic damage, although Fth deletion-induced susceptibility toward ferroptosis after TBI was reversed by an iron chelator, deferoxamine. Taken together, these data indicate that the TrkB agonist NAS treatment appears to improve brain function after TBI by suppressing ferroptosis, at least in part, through activation of the PI3K/Akt/Nrf2/Fth pathway, providing evidence that NAS is likely to be a promising anti-ferroptosis agent for further treatment for TBI.

Arc weakens synapses by dispersing AMPA receptors from postsynaptic density via modulating PSD phase separation.

In response to stimuli, the immediate early gene product Arc can acutely down-regulate synaptic strength by removing AMPA receptors (AMPARs) from synapses and thus regulate synaptic plasticity. How Arc, a scaffold protein, can specifically facilitate synaptic removal of AMPARs is unknown. We found that Arc directly antagonizes with PSD-95 in binding to TARPs, which are the auxiliary subunits of AMPARs. Arc, in a highly concentration-sensitive manner, acutely disperses TARPs from the postsynaptic density (PSD) condensate formed via phase separation. TARPs with the Ser residue in the "P-S-Y"-motif of its tail phosphorylated are completely refractory from being dispersed by Arc, suggesting that Arc cannot displace AMPARs from PSDs in active synapses. Conversely, strengthening the interaction between Arc and TARPs enhances Arc's capacity in weakening synapses. Thus, Arc can specifically and effectively modulate synaptic AMPAR clustering via modulating PSD phase separation. Our study further suggests that activity-dependent, bi-directional modulation of PSD condensate formation/dispersion represents a general regulatory mechanism for synaptic plasticity.

Targeting Molecular Mediators of Ferroptosis and Oxidative Stress for Neurological Disorders.

With the acceleration of population aging, nervous system diseases including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), anxiety, depression, stroke, and traumatic brain injury (TBI) have become a huge burden on families and society. The mechanism of neurological disorders is complex, which also lacks effective treatment, so relevant research is required to solve these problems urgently. Given that oxidative stress-induced lipid peroxidation eventually leads to ferroptosis, both oxidative stress and ferroptosis are important mechanisms causing neurological disorders, targeting mediators of oxidative stress and ferroptosis have become a hot research direction at present. Our review provides a current view of the mechanisms underlying ferroptosis and oxidative stress participate in neurological disorders, the potential application of molecular mediators targeting ferroptosis and oxidative stress in neurological disorders. The target of molecular mediators or agents of oxidative stress and ferroptosis associated with neurological disorders, such as reactive oxygen species (ROS), nuclear factor erythroid 2-related factor-antioxidant response element (Nrf2-ARE), n-acetylcysteine (NAC), Fe2+, NADPH, and its oxidases NOX, has been described in this article. Given that oxidative stress-induced ferroptosis plays a pivotal role in neurological disorders, further research on the mechanisms of ferroptosis caused by oxidative stress will help provide new targets for the treatment of neurological disorders.