Autologous Tissue Repair and Total Face Restoration.

Importance: Total face restoration remains a challenge in modern reconstructive surgery. After 17 years of experiments and preliminary clinical studies, a new concept of face prefabrication was developed for face restoration with autologous tissue. Objective: To evaluate the long-term results of face restoration with autologous tissue and report a finalized and standardized approach of face prefabrication. Design, Setting, and Participants: In this single-center long-term retrospective study, 32 patients who underwent total face restoration between 2005 and 2022 were reviewed. These patients underwent total facial reconstruction, which included flap prefabrication, 3-dimensional printing, tissue expansion, and flap transfer with aid of indocyanine green angiography (IGA). The flap first undergoes prefabrication by transferring vascularized fascia under the skin of the selected chest. A tissue expander is then placed under the fascia to create a large, thin, reliable skin flap after expansion. Once completed, the flap is transferred to the face during the second stage of the reconstruction. Intraoperative IGA is performed to guide the design of subsequent openings for facial fissures. Data were analyzed from July to September 2023. Main Outcomes and Measures: Flap healing, reconstructive outcome, and patient recovery were assessed during follow-up. Three questionnaires, including the 36-Item Short Form Health Survey (SF-36), Aesthetic and Functional Status Score of Facial Soft-Tissue Deformities/Defects, and the EuroQoL Health-Related Quality of Life (EQ-5D-5L), were used to evaluate the quality of life and satisfaction with facial aesthetic and functional status. Results: Of 24 included patients, 14 (58%) were male, and the mean (range) age was 32.9 (8-62) years. The mean (range) follow-up was 5.6 (2-12) years. All patients reported a significant improvement in quality of life (SF-36), especially in mean (SD) social functioning (preoperative score, 53.65 [34.51]; postoperative score, 80.73 [19.10]) and emotional stability (preoperative score, 56.67 [25.55]; postoperative score, 71.17 [18.51]). A total of 22 patients (92%) went back to work. Mean (SD) facial aesthetic status (preoperative score, 4.96 [3.26]; postoperative score, 11.52 [3.49]; P < .001) and functional status (preoperative score, 11.09 [3.51]; postoperative score, 15.78 [3.26]; P < .001) also improved. In addition, there was a significant increase in overall satisfaction and self-reported health status (preoperative score, 8.13 [1.52]; postoperative score, 3.58 [2.31]). Conclusions and Relevance: In this study, 5-year follow-up results suggested that this innovative approach to total face restoration offered a safe and valid option for indicated patients, with acceptable reconstructive and cosmetic outcomes.

Development of novel bisphenol derivatives with a membrane-targeting mechanism as potent gram-positive antibacterial agents.

Antibiotic resistance is becoming increasingly severe. The development of small molecular antimicrobial peptides is regarded as a promising design strategy for antibiotics. Here, a series of bisphenol derivatives with amphiphilic structures were designed and synthesized as antibacterial agents by imitating the design strategy of antimicrobial peptides. After a series of structural optimizations, lead compound 43 was identified, which exhibited excellent antibacterial activity against Gram-positive bacterial strains (MICs = 0.78-1.56 µg/mL), poor hemolytic activity (HC50 > 200 µg/mL), and low cytotoxicity (CC50 > 100 µg/mL). Further biological evaluation results indicated that 43 exerted antibacterial effects by directly destroying bacterial cell membranes and displayed rapid bactericidal properties (within 0.5-1 h), leading to a very low probability of drug resistance. Moreover, in a murine model of corneal infection, 43 exhibited a strong in vivo antibacterial efficacy. These findings indicate that 43 is a promising candidate compound for the treatment of bacterial infections.

Steroidal Saponins from Water Eggplant (Fruits of Solanum torvum) Exhibit Anti-Epileptic Activity against Pentylenetetrazole-Induced Seizure Model in Zebrafish.

The fruits of Solanum torvum Swartz, a wild relative of eggplant, are consumed as a wild vegetable in tropical regions of Africa, Asia, and South America. In traditional Chinese medicine, it is believed to have anti-inflammatory and sedative effects. In the Philippines, water decoction is used to treat hyperactivity disorder. Twenty-two steroidal saponins were isolated and purified from the fruits grown in Yunnan, China, including six new compounds: torvosides U-Z (1-6). During drying and cooking, the saponins may undergo transformation, resulting in small amounts of sapogenins. These transformations can include dehydration of hydroxyl groups at position C22, formation of double bonds at position 20, 22 or 22, 23, and even formation of peroxide products. Saponin compounds torvoside X (4), torvoside Y (5), torvoside A (7), and (25S)-3-oxo-5α-spirostan-6α-yl-O-ß-d-xylopyranoside (20), which are glycosylated at C-6, showed certain anti-epileptic activity in a pentylenetetrazole-induced zebrafish seizure model. No antiproliferative activity was detected when tested on the cancer cell line HepG2, and no hepatotoxic effect was noted on normal liver cell line LO2.

Efficient spiking neural network design via neural architecture search.

Spiking neural networks (SNNs) are brain-inspired models that utilize discrete and sparse spikes to transmit information, thus having the property of energy efficiency. Recent advances in learning algorithms have greatly improved SNN performance due to the automation of feature engineering. While the choice of neural architecture plays a significant role in deep learning, the current SNN architectures are mainly designed manually, which is a time-consuming and error-prone process. In this paper, we propose a spiking neural architecture search (NAS) method that can automatically find efficient SNNs. To tackle the challenge of long search time faced by SNNs when utilizing NAS, the proposed NAS encodes candidate architectures in a branchless spiking supernet which significantly reduces the computation requirements in the search process. Considering that real-world tasks prefer efficient networks with optimal accuracy under a limited computational budget, we propose a Synaptic Operation (SynOps)-aware optimization to automatically find the computationally efficient subspace of the supernet. Experimental results show that, in less search time, our proposed NAS can find SNNs with higher accuracy and lower computational cost than state-of-the-art SNNs. We also conduct experiments to validate the search process and the trade-off between accuracy and computational cost.

Development of cannabidiol derivatives as potent broad-spectrum antibacterial agents with membrane-disruptive mechanism.

The emergence of antibiotic resistance has brought a significant burden to public health. Here, we designed and synthesized a series of cannabidiol derivatives by biomimicking the structure and function of cationic antibacterial peptides. This is the first report on the design of cannabidiol derivatives as broad-spectrum antibacterial agents. Through the structure-activity relationship (SAR) study, we found a lead compound 23 that killed both Gram-negative and Gram-positive bacteria via a membrane-targeting mechanism of action with low resistance frequencies. Compound 23 also exhibited very weak hemolytic activity, low toxicity toward mammalian cells, and rapid bactericidal properties. To further validate the membrane action mechanism of compound 23, we performed transcriptomic analysis using RNA-seq, which revealed that treatment with compound 23 altered many cell wall/membrane/envelope biogenesis-related genes in Gram-positive and Gram-negative bacteria. More importantly, compound 23 showed potent in vivo antibacterial efficacy in murine corneal infection models caused by Staphylococcus aureus or Pseudomonas aeruginosa. These findings would provide a new design idea for the discovery of novel broad-spectrum antibacterial agents to overcome the antibiotic resistance crisis.

Brain Topology Modeling With EEG-Graphs for Auditory Spatial Attention Detection.

OBJECTIVE: Despite recent advances, the decoding of auditory attention from brain signals remains a challenge. A key solution is the extraction of discriminative features from high-dimensional data, such as multi-channel electroencephalography (EEG). However, to our knowledge, topological relationships between individual channels have not yet been considered in any study. In this work, we introduced a novel architecture that exploits the topology of the human brain to perform auditory spatial attention detection (ASAD) from EEG signals. METHODS: We propose EEG-Graph Net, an EEG-graph convolutional network, which employs a neural attention mechanism. This mechanism models the topology of the human brain in terms of the spatial pattern of EEG signals as a graph. In the EEG-Graph, each EEG channel is represented by a node, while the relationship between two EEG channels is represented by an edge between the respective nodes. The convolutional network takes the multi-channel EEG signals as a time series of EEG-graphs and learns the node and edge weights from the contribution of the EEG signals to the ASAD task. The proposed architecture supports the interpretation of the experimental results by data visualization. RESULTS: We conducted experiments on two publicly available databases. The experimental results showed that EEG-Graph Net significantly outperforms the state-of-the-art methods in terms of decoding performance. In addition, the analysis of the learned weight patterns provides insights into the processing of continuous speech in the brain and confirms findings from neuroscientific studies. CONCLUSION: We showed that modeling brain topology with EEG-graphs yields highly competitive results for auditory spatial attention detection. SIGNIFICANCE: The proposed EEG-Graph Net is more lightweight and accurate than competing baselines and provides explanations for the results. Also, the architecture can be easily transferred to other brain-computer interface (BCI) tasks.

A Hybrid Neural Coding Approach for Pattern Recognition With Spiking Neural Networks.

Recently, brain-inspired spiking neural networks (SNNs) have demonstrated promising capabilities in solving pattern recognition tasks. However, these SNNs are grounded on homogeneous neurons that utilize a uniform neural coding for information representation. Given that each neural coding scheme possesses its own merits and drawbacks, these SNNs encounter challenges in achieving optimal performance such as accuracy, response time, efficiency, and robustness, all of which are crucial for practical applications. In this study, we argue that SNN architectures should be holistically designed to incorporate heterogeneous coding schemes. As an initial exploration in this direction, we propose a hybrid neural coding and learning framework, which encompasses a neural coding zoo with diverse neural coding schemes discovered in neuroscience. Additionally, it incorporates a flexible neural coding assignment strategy to accommodate task-specific requirements, along with novel layer-wise learning methods to effectively implement hybrid coding SNNs. We demonstrate the superiority of the proposed framework on image classification and sound localization tasks. Specifically, the proposed hybrid coding SNNs achieve comparable accuracy to state-of-the-art SNNs, while exhibiting significantly reduced inference latency and energy consumption, as well as high noise robustness. This study yields valuable insights into hybrid neural coding designs, paving the way for developing high-performance neuromorphic systems.

Sesquiterpenoids from aged Artemisia argyi and their 3D-QSAR for anti-HBV activity.

Artemisia argyi Levl. Et Vant, commonly known as "Chinese Mugwort," has been utilized in traditional Chinese medicine and cuisine for centuries. Aged Chinese Mugwort has been uncovered to possess superior quality and safety, and its ethyl acetate extract has been found to exhibit anti-hepatitis B virus (HBV) activity. In this study, twenty-five sesquiterpenoids were isolated and characterized from three-year-aged A. argyi. Among them, 14 previously undescribed sesquiterpenoids (1-14), featuring double bond oxidation or ring opening. It is hypothesized that during the aging process, sesquiterpenes undergo oxidative transformation of their double bonds to form alcohols due to external factors and inherent properties. The anti-HBV activity and cytotoxicity of all compounds were assessed in vitro using HepG 2.2.15 cells, and their structure-activity relationships were analyzed through three-dimensional quantitative structure-activity relationship (3D-QASR) techniques. The α-methylene-γ-lactone sesquiterpenoid derivatives were discovered to have potent inhibitory activity against HBV. This research may broaden the potential applications of Chinese Mugwort and offer further guidance for its development and utilization as functional food or traditional Chinese medicine.

RGCnet: An Efficient Recursive Gated Convolutional Network for EEG-based Auditory Attention Detection.

Humans are able to listen to one speaker and disregard others in a speaking crowd, referred to as the "cocktail party effect". EEG-based auditory attention detection (AAD) seeks to identify whom a listener is listening to by decoding one's EEG signals. Recent research has demonstrated that the self-attention mechanism is effective for AAD. In this paper, we present the Recursive Gated Convolutional network (RGCnet) for AAD, which implements long-range and high-order interactions as a self-attention mechanism, while maintaining a low computational cost. The RGCnet expands the 2nd order feature interactions to a higher order to model the complex interactions between EEG features. We evaluate RGCnet on two public datasets and compare it with other AAD models. Our results demonstrate that RGCnet outperforms other comparative models under various conditions, thus potentially improving the control of neuro-steered hearing devices.

Tunnel Prescribed Control of Nonlinear Systems With Unknown Control Directions.

This article solves the entry capture problem (ECP) such that for any initial tracking error, it can be regulated into the prescribed performance constraints within a user-given time. The challenge lies in how to remove the initial condition limitation and to handle the ECP for nonlinear systems under unknown control directions and asymmetric performance constraints. For better tracking performance, we propose a unified tunnel prescribed performance (TPP) providing strict and tight allowable set. With the aid of a scaling function, error self-tuning functions (ESFs) are then developed to make the control scheme suitable to any initial condition (including the initial constraint violation), where the initial values of ESFs always satisfy performance constraints. In lieu of the Nussbaum technique, an orientation function is introduced to deal with unknown control directions while such way is capable of reducing the control peaking problem. Using ESFs, together with TPP and an orientation function, the resulted tunnel prescribed control (TPC) leads to a solution for the underlying ECP, which also exhibits a low complexity level since no command filters or dynamic surface control is required. Finally, simulation results are provided to further demonstrate these theoretical findings.

Design of phenothiazine-based cationic amphiphilic derivatives incorporating arginine residues: Potential membrane-active broad-spectrum antimicrobials combating pathogenic bacteria in vitro and in vivo.

Multidrug-resistant bacteria infections pose an increasingly serious threat to human health, and the development of antimicrobials is far from meeting the clinical demand. It is urgent to discover and develop novel antibiotics to combat bacterial resistance. Currently, the development of membrane active antimicrobial agents is an attractive strategy to cope with antimicrobial resistance issues. In this study, the synthesis and biological evaluation of cationic amphiphilic phenothiazine-based derivatives were reported. Among them, the most promising compound 30 bearing a n-heptyl group and two arginine residues displayed potent bactericidal activity against both Gram-positive (MICs = 1.56 µg/mL) and Gram-negative bacteria (MICs = 3.125-6.25 µg/mL). Compound 30 showed low hemolysis activity (HC50 = 281.4 ± 1.6 µg/mL) and low cytotoxicity (CC50 ＞ 50 µg/mL) toward mammalian cells, as well as excellent salt resistance. Compound 30 rapidly killed bacteria by acting on the bacterial cell membrane and appeared less prone to resistance. Importantly, compound 30 showed potent in vivo efficacy in a murine model of bacterial keratitis. Hence, the results suggested compound 30 has a promising prospect as a broad-spectrum antibacterial agent for the treatment of drug-resistant bacterial infections.

A Bio-Inspired Spiking Attentional Neural Network for Attentional Selection in the Listening Brain.

Humans show a remarkable ability in solving the cocktail party problem. Decoding auditory attention from the brain signals is a major step toward the development of bionic ears emulating human capabilities. Electroencephalography (EEG)-based auditory attention detection (AAD) has attracted considerable interest recently. Despite much progress, the performance of traditional AAD decoders remains to be improved, especially in low-latency settings. State-of-the-art AAD decoders based on deep neural networks generally lack the intrinsic temporal coding ability in biological networks. In this study, we first propose a bio-inspired spiking attentional neural network, denoted as BSAnet, for decoding auditory attention. BSAnet is capable of exploiting the temporal dynamics of EEG signals using biologically plausible neurons and an attentional mechanism. Experiments on two publicly available datasets confirm the superior performance of BSAnet over other state-of-the-art systems across various evaluation conditions. Moreover, BSAnet imitates realistic brain-like information processing, through which we show the advantage of brain-inspired computational models.

Stochastic and Deterministic Assembly Processes in Seamount Microbial Communities.

Seamounts are ubiquitous in the ocean. However, little is known about how seamount habitat features influence the local microbial community. In this study, the microbial populations of sediment cores from sampling depths of 0.1 to 35 cm from 10 seamount summit sites with a water depth of 1,850 to 3,827 m across the South China Sea (SCS) Basin were analyzed. Compared with nonseamount ecosystems, isolated seamounts function as oases for microbiomes, with average moderate to high levels of microbial abundance, richness, and diversity, and they harbor distinct microbial communities. The distinct characteristics of different seamounts provide a high level of habitat heterogeneity, resulting in the wide range of microbial community diversity observed across all seamounts. Using dormant thermospores as tracers to study the effect of dispersal by ocean currents, the observed distance-decay biogeography across different seamounts shaped simultaneously by the seamounts' naturally occurring heterogeneous habitat and the limitation of ocean current dispersal was found. We also established a framework that links initial community assembly with successional dynamics in seamounts. Seamounts provide resource-rich and dynamic environments, which leads to a dominance of stochasticity during initial community establishment in surface sediments. However, a progressive increase in deterministic environmental selection, correlated with resource depletion in subsurface sediments, leads to the selective growth of rare species of surface sediment communities in shaping the subsurface community. Overall, the study indicates that seamounts are a previously ignored oasis in the deep sea. This study also provides a case study for understanding the microbial ecology in globally widespread seamounts. IMPORTANCE Although there are approximately 25 million seamounts in the ocean, surprisingly little is known about seamount microbial ecology. We provide evidence that seamounts are island-like habitats harboring microbial communities distinct from those of nonseamount habitats, and they exhibit a distance-decay pattern. Environmental selection and dispersal limitation simultaneously shape the observed biogeography. Coupling empirical data with a null mode revealed a shift in the type and strength, which controls microbial community assembly and succession from the seamount surface to the subsurface sediments as follows: (i) community assembly is initially primarily driven by stochastic processes such as dispersal limitation, and (ii) changes in the subsurface environment progressively increase the importance of environmental selection. This case study contributes to the mechanistic understanding essential for a predictive microbial ecology of seamounts.

Intraoperative Indocyanine Green Angiography Facilitates Flap Fenestration and Facial Organ Fabrication in Total Facial Restoration.

BACKGROUND: As effective measures to visualize flap vasculature and perfusion were unavailable, flap fenestration and facial organ fabrication could not be performed safely, preventing the transition from 2-D coverage to the restoration of the 3-D structure of facial organs. This study aims to evaluate the efficacy of indocyanine green angiography (ICGA) in guiding flap fenestration and facial organ fabrication in total facial restoration. METHODS: Ten patients with total facial scarring following burn injury were enrolled in the study. They were treated with pre-expanded, prefabricated monoblock flaps for total face restoration. The opening of nostrils, oral and palpebral orifices, together with organ fabrication, were conducted under the guidance of intraoperative ICGA via hemodynamic evaluation of flap perfusion. Postoperative follow-up parameters include vascular crisis, infection, flap necrosis and patients' aesthetic and functional recovery. RESULTS: The opening of facial organ orifices was performed at the stage of flap transfer in nine patients. To avoid damaging the major nourishing vessels, the left palpebral orifice was opened eight days after the flap transfer in one patient, as observed by ICGA. Based on ICGA evaluation, the decision to perform additional vascular anastomosis before flap fenestration was made in six patients. Hemodynamic analysis of flap perfusion following fenestration revealed no significant change. Follow-up showed satisfactory aesthetic recovery and well-restored 3-D structures of facial organs. CONCLUSION: This pilot study demonstrates how intraoperative ICGA can enhance the safety of flap fenestration, thereby transforming full facial restoration from the 2-D to the 3-D realm by facilitating facial organ fabrication.

Midface Prelamination by using a Three-dimensional Cervicothoracic Prefabricated Flap.

SUMMARY: The midface is an important area in aesthetics and function and a complex area to manage after burn injuries, trauma, and tumor resection. Traditional treatment to reconstruct midface defects involving the nose, lips and cheeks requires multiple sequential flap surgeries but results in a patch-like appearance, which remains a major challenge for head and neck reconstructive surgeons. This article describes how the authors perform prelamination using the prefabricated cervicothoracic flap on the anterior chest for midface reconstruction. The key point of the authors' procedure is to three-dimensionalize the cervicothoracic prefabricated flap with flap folding, flap rotation, and cartilage grafts for coverage, lining, and support of the nose and lips. This technique may be indicated for extensive midface defects involving total nose and lip loss. It provides a uniform matched facial appearance and significant functional improvement. Donor-site morbidity and the need for multiple flap procedures could be reduced.

Study on Chemical Constituents of Panax notoginseng Leaves.

Panax notoginseng (Burk.) F. H. is a genuine medicinal material in Yunnan Province. As accessories, P. notoginseng leaves mainly contain protopanaxadiol saponins. The preliminary findings have indicated that P. notoginseng leaves contribute to its significant pharmacological effects and have been administrated to tranquilize and treat cancer and nerve injury. Saponins from P. notoginseng leaves were isolated and purified by different chromatographic methods, and the structures of 1-22 were elucidated mainly through comprehensive analyses of spectroscopic data. Moreover, the SH-SY5Y cells protection bioactivities of all isolated compounds were tested by establishing L-glutamate models for nerve cell injury. As a result, twenty-two saponins, including eight dammarane saponins, namely notoginsenosides SL1-SL8 (1-8), were identified as new compounds, together with fourteen known compounds, namely notoginsenoside NL-A3 (9), ginsenoside Rc (10), gypenoside IX (11), gypenoside XVII (12), notoginsenoside Fc (13), quinquenoside L3 (14), notoginsenoside NL-B1 (15), notoginsenoside NL-C2 (16), notoginsenoside NL-H2 (17), notoginsenoside NL-H1 (18), vina-ginsenoside R13 (19), ginsenoside II (20), majoroside F4 (21), and notoginsenoside LK4 (22). Among them, notoginsenoside SL1 (1), notoginsenoside SL3 (3), notoginsenoside NL-A3 (9), and ginsenoside Rc (10) showed slight protective effects against L-glutamate-induced nerve cell injury (30 µM).

Effect of heat and hypoxia stress on mitochondrion and energy metabolism in the gill of hard clam.

Aquatic animals suffer from heat and hypoxia stress more frequently due to global climate change and other anthropogenic activities. Heat and hypoxia stress can significantly affect mitochondrial function and energy metabolism. Here, the response and adaptation characteristics of mitochondria and energy metabolism in the gill of the hard clam Mercenaria mercenaria under heat (35 °C), hypoxia (0.2 mg/L), and heat plus hypoxia stress (35 °C, 0.2 mg/L) after 48 h exposure were investigated. Mitochondrial membrane potentials were depolarized under environmental stress. Mitochondrial fusion, fission and mitophagy played a key role in maintain mitochondrion function. The AMPK subunits showed different expression under environmental stress. Acceleration of enzyme activities (phosphofructokinase, pyruvate kinase and lactic dehydrogenase) and accumulation of anaerobic metabolites in glycolysis and TCA cycle implied that the anaerobic metabolism might play a key role in providing energy. Accumulation of amino acids might help to increase tolerance under heat and heat combined hypoxia stress. In addition, urea cycle played a key role in amino acid metabolism to prevent ammonia/nitrogen toxicity. This study improved our understanding of the mitochondrial and energy metabolism responses of marine bivalves exposed to environmental stress.

A Tandem Learning Rule for Effective Training and Rapid Inference of Deep Spiking Neural Networks.

Spiking neural networks (SNNs) represent the most prominent biologically inspired computing model for neuromorphic computing (NC) architectures. However, due to the nondifferentiable nature of spiking neuronal functions, the standard error backpropagation algorithm is not directly applicable to SNNs. In this work, we propose a tandem learning framework that consists of an SNN and an artificial neural network (ANN) coupled through weight sharing. The ANN is an auxiliary structure that facilitates the error backpropagation for the training of the SNN at the spike-train level. To this end, we consider the spike count as the discrete neural representation in the SNN and design an ANN neuronal activation function that can effectively approximate the spike count of the coupled SNN. The proposed tandem learning rule demonstrates competitive pattern recognition and regression capabilities on both the conventional frame- and event-based vision datasets, with at least an order of magnitude reduced inference time and total synaptic operations over other state-of-the-art SNN implementations. Therefore, the proposed tandem learning rule offers a novel solution to training efficient, low latency, and high-accuracy deep SNNs with low computing resources.

Molecular response and developmental speculations in metamorphosis of the veined rapa whelk, Rapana venosa.

Metamorphosis is the short developmental stage characterized by dramatic ontogenetic changes that occurs in most animals. However, this important process remains largely unclear in marine invertebrates. In this study, we performed the sequential RNA sequencing of a representative mollusk, the rapa whelk (Rapana venosa), that is undergoing metamorphosis and conducted differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to investigate the overall and dynamic transcriptome responses. The results revealed that the expression of cytochrome P450 2A and 3A were upregulated during metamorphosis, while the expression of H/ACA ribonucleoproteins increased 4 h after metamorphosis induction (M4 stage), indicating that R. venosa mainly responded to the pelagobenthic changes. At the M24 stage, the enrichment of V-type proton ATPase and insulin indicated the complete development of secretory organs and initiation of hormone secretion. Furthermore, at the M48 stage, the enrichment of zinc metalloproteinase and conotoxin indicated a well-developed predation system that requires exogenous nutrition. Finally, during the PL stage, the genes associated with growth control were highly enriched, implying that R. venosa had completed metamorphosis and has entered the period of rapid growth. Therefore, our study provides useful transcriptomic resources for R. venosa and contributes new insights that may assist in elucidating the mechanisms underlying metamorphosis in marine invertebrates.