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Abstract The genus Megalocytivirus, belonging to the family Iridoviridae, is one of the most detrimental virus groups to fish aquaculture. Megalocytivirus creates a virus-mock basement membrane (VMBM) on the surface of infected cells. This membrane provides attachment sites for lymphatic endothelial cells (LECs), disrupting fish's endothelial cell-extracellular matrix system. This disruption triggers injury to the vascular system and can result in death. Exploring the VMBM-cell interaction mechanism is crucial for uncovering the pathogenesis of Megalocytivirus and identifying therapeutic targets. Claudins, a class of tetra transmembrane proteins, play a key role in creating tight junctions between endothelial or epithelial cells. In this study, we demonstrated that the expression of Claudin2, a member of the Claudin family in fish, was significantly up-regulated by Megalocytivirus infection. Claudin2 was found in LECs attached to the surface of infected cells. It interacted with the VMBM viral components VP23R, VP08R, and VP33L at multiple binding sites through its two extracellular loops. However, it did not interact with the host basement membrane’s nidogen. Therefore, Claudin2 is involved in the interaction of LEC with VMBM and plays a role in the disturbed distribution of extracellular matrix and endothelial cells in Megalocytivirus-infected fish tissues. This study aims to uncover the molecular mechanisms by which Megalocytivirus infection leads to pathological changes in the vascular system.

Abstract Dysfunction of pancreatic δ cells contributes to the etiology of diabetes. Despite their important role, human δ cells are scarce, limiting physiological studies and drug discovery targeting δ cells. To date, no directed δ-cell differentiation method has been established. Here, we demonstrate that fibroblast growth factor (FGF) 7 promotes pancreatic endoderm/progenitor differentiation, whereas FGF2 biases cells towards the pancreatic δ-cell lineage via FGF receptor 1. We develop a differentiation method to generate δ cells from human stem cells by combining FGF2 with FGF7, which synergistically directs pancreatic lineage differentiation and modulates the expression of transcription factors and SST activators during endoderm/endocrine precursor induction. These δ cells display mature RNA profiles and fine secretory granules, secrete somatostatin in response to various stimuli, and suppress insulin secretion from in vitro co-cultured β cells and mouse β cells upon transplantation. The generation of human pancreatic δ cells from stem cells in vitro would provide an unprecedented cell source for drug discovery and cell transplantation studies in diabetes.

Abstract With the flourishing of spatial omics technologies, alignment and stitching of slices becomes indispensable to decipher a holistic view of 3D molecular profile. However, existing alignment and stitching methods are unpractical to process large-scale and image-based spatial omics dataset due to extreme time consumption and unsatisfactory accuracy. Here we propose SANTO, a coarse-to-fine method targeting alignment and stitching tasks for spatial omics. SANTO firstly rapidly supplies reasonable spatial positions of two slices and identifies the overlap region. Then, SANTO refines the positions of two slices by considering spatial and omics patterns. Comprehensive experiments demonstrate the superior performance of SANTO over existing methods. Specifically, SANTO stitches cross-platform slices for breast cancer samples, enabling integration of complementary features to synergistically explore tumor microenvironment. SANTO is then applied to 3D-to-3D spatiotemporal alignment to study development of mouse embryo. Furthermore, SANTO enables cross-modality alignment of spatial transcriptomic and epigenomic data to understand complementary interactions.

Abstract With the fast‐growing and evolving omics data, the demand for streamlined and adaptable tools to handle bioinformatics analysis continues to grow. In response to this need, Automated Bioinformatics Analysis (AutoBA) is introduced, an autonomous AI agent designed explicitly for fully automated multi‐omic analyses based on large language models (LLMs). AutoBA simplifies the analytical process by requiring minimal user input while delivering detailed step‐by‐step plans for various bioinformatics tasks. AutoBA's unique capacity to self‐design analysis processes based on input data variations further underscores its versatility. Compared with online bioinformatic services, AutoBA offers multiple LLM backends, with options for both online and local usage, prioritizing data security and user privacy. In comparison to ChatGPT and open‐source LLMs, an automated code repair (ACR) mechanism in AutoBA is designed to improve its stability in automated end‐to‐end bioinformatics analysis tasks. Moreover, different from the predefined pipeline, AutoBA has adaptability in sync with emerging bioinformatics tools. Overall, AutoBA represents an advanced and convenient tool, offering robustness and adaptability for conventional multi‐omic analyses.

Abstract Volatile solid additives have attracted increasing attention in optimizing the morphology and improving the performance of currently dominated non‐fullerene acceptor‐based organic solar cells (OSCs). However, the underlying principles governing the rational design of volatile solid additives remain elusive. Herein, a series of efficient volatile solid additives are successfully developed by the crossbreeding effect of chalcogenation and iodination for optimizing the morphology and improving the photovoltaic performances of OSCs. Five benzene derivatives of 1,4‐dimethoxybenzene (DOB), 1‐iodo‐4‐methoxybenzene (OIB), 1‐iodo‐4‐methylthiobenzene (SIB), 1,4‐dimethylthiobenzene (DSB) and 1,4‐diiodobenzene (DIB) are systematically studied, where the widely used DIB is used as the reference. The effect of chalcogenation and iodination on the overall property is comprehensively investigated, which indicates that the versatile functional groups provided various types of noncovalent interactions with the host materials for modulating the morphology. Among them, SIB with the combination of sulphuration and iodination enabled more appropriate interactions with the host blend, giving rise to a highly ordered molecular packing and more favorable morphology. As a result, the binary OSCs based on PM6:L8‐BO and PBTz‐F:L8‐BO as well as the ternary OSCs based on PBTz‐F:PM6:L8‐BO achieved impressive high PCEs of 18.87%, 18.81% and 19.68%, respectively, which are among the highest values for OSCs.

Antibody leads must fulfill multiple desirable properties to be clinical candidates. Primarily due to the low throughput in the experimental procedure, the need for such multi-property optimization causes the bottleneck in preclinical antibody discovery and development, because addressing one issue usually causes another. We developed a reinforcement learning (RL) method, named AB-Gen, for antibody library design using a generative pre-trained transformer (GPT) as the policy network of the RL agent. We showed that this model can learn the antibody space of heavy chain complementarity determining region 3 (CDRH3) and generate sequences with similar property distributions. Besides, when using human epidermal growth factor receptor-2 (HER2) as the target, the agent model of AB-Gen was able to generate novel CDRH3 sequences that fulfill multi-property constraints. Totally, 509 generated sequences were able to pass all property filters, and three highly conserved residues were identified. The importance of these residues was further demonstrated by molecular dynamics simulations, consolidating that the agent model was capable of grasping important information in this complex optimization task. Overall, the AB-Gen method is able to design novel antibody sequences with an improved success rate than the traditional propose-then-filter approach. It has the potential to be used in practical antibody design, thus empowering the antibody discovery and development process. The source code of AB-Gen is freely available at Zenodo (https://doi.org/10.5281/zenodo.7657016) and BioCode (https://ngdc.cncb.ac.cn/biocode/tools/BT007341).

Abstract Repetitive DNA sequences playing critical roles in driving evolution, inducing variation, and regulating gene expression. In this review, we summarized the definition, arrangement, and structural characteristics of repeats. Besides, we introduced diverse biological functions of repeats and reviewed existing methods for automatic repeat detection, classification, and masking. Finally, we analyzed the type, structure, and regulation of repeats in the human genome and their role in the induction of complex diseases. We believe that this review will facilitate a comprehensive understanding of repeats and provide guidance for repeat annotation and in-depth exploration of its association with human diseases.

Background The key challenge in drug discovery is to discover novel compounds with desirable properties. Among the properties, binding affinity to a target is one of the prerequisites and usually evaluated by molecular docking or quantitative structure activity relationship (QSAR) models. Methods In this study, we developed SGPT-RL, which uses a generative pre-trained transformer (GPT) as the policy network of the reinforcement learning (RL) agent to optimize the binding affinity to a target. SGPT-RL was evaluated on the Moses distribution learning benchmark and two goal-directed generation tasks, with Dopamine Receptor D2 (DRD2) and Angiotensin-Converting Enzyme 2 (ACE2) as the targets. Both QSAR model and molecular docking were implemented as the optimization goals in the tasks. The popular Reinvent method was used as the baseline for comparison. Results The results on the Moses benchmark showed that SGPT-RL learned good property distributions and generated molecules with high validity and novelty. On the two goal-directed generation tasks, both SGPT-RL and Reinvent were able to generate valid molecules with improved target scores. The SGPT-RL method achieved better results than Reinvent on the ACE2 task, where molecular docking was used as the optimization goal. Further analysis shows that SGPT-RL learned conserved scaffold patterns during exploration. Conclusions The superior performance of SGPT-RL in the ACE2 task indicates that it can be applied to the virtual screening process where molecular docking is widely used as the criteria. Besides, the scaffold patterns learned by SGPT-RL during the exploration process can assist chemists to better design and discover novel lead candidates.

Abstract Craniofacial microsomia (CFM; also known as Goldenhar syndrome), is a craniofacial developmental disorder of variable expressivity and severity with a recognizable set of abnormalities. These birth defects are associated with structures derived from the first and second pharyngeal arches, can occur unilaterally and include ear dysplasia, microtia, preauricular tags and pits, facial asymmetry and other malformations. The inheritance pattern is controversial, and the molecular etiology of this syndrome is largely unknown. A total of 670 patients belonging to unrelated pedigrees with European and Chinese ancestry with CFM, are investigated. We identify 18 likely pathogenic variants in 21 probands (3.1%) in FOXI3. Biochemical experiments on transcriptional activity and subcellular localization of the likely pathogenic FOXI3 variants, and knock-in mouse studies strongly support the involvement of FOXI3 in CFM. Our findings indicate autosomal dominant inheritance with reduced penetrance, and/or autosomal recessive inheritance. The phenotypic expression of the FOXI3 variants is variable. The penetrance of the likely pathogenic variants in the seemingly dominant form is reduced, since a considerable number of such variants in affected individuals were inherited from non-affected parents. Here we provide suggestive evidence that common variation in the FOXI3 allele in trans with the pathogenic variant could modify the phenotypic severity and accounts for the incomplete penetrance.

AbstractDoxorubicin (DOX) is a commonly studied chemotherapeutic agent for the treatment of solid tumors, but the severe side effects limit its clinical application. It is shown that DOX-metal chelate has lower in vitro cytotoxicity compared with DOX, as the anthracyclines of DOX can form coordinative interaction with transition metal ions. In addition, the transition metal ions could catalyze the production of hydroxyl radicals (·OH) via Fenton/Fenton-like reactions to achieve antitumor chemodynamic therapy (CDT). In this study, copper ions (Cu2+) were applied to obtain DOX/Cu(II) prodrug, and a liposomal formulation was used to avoid the rapid blood clearance and optimize the biodistribution of this prodrug. In vitro and in vivo antitumor results demonstrated that this pH sensitive Cu-chelating prodrug can reduce adverse effects of DOX but improve the antitumor efficiency due to the combination of chemotherapy and chemodynamic therapy. Our study provided a facile and effective approach of metal-chelating prodrug strategy for combination cancer therapy strategy.

Abstract Deep learning (DL) is currently revolutionizing peptide drug development due to both computational advances and the substantial recent expansion of digitized biological data. However, progress in oligopeptide drug development has been limited, likely due to the lack of suitable datasets and difficulty in identifying informative features to use as inputs for DL models. Here, we utilized an unsupervised deep learning model to learn a semantic pattern based on the intrinsically disordered regions of ~171 known osteogenic proteins. Subsequently, oligopeptides were generated from this semantic pattern based on Monte Carlo simulation, followed by in vivo functional characterization. A five amino acid oligopeptide (AIB5P) had strong bone-formation-promoting effects, as determined in multiple mouse models (e.g., osteoporosis, fracture, and osseointegration of implants). Mechanistically, we showed that AIB5P promotes osteogenesis by binding to the integrin α5 subunit and thereby activating FAK signaling. In summary, we successfully established an oligopeptide discovery strategy based on a DL model and demonstrated its utility from cytological screening to animal experimental verification.

ABSTRACT White spot syndrome virus (WSSV) is a serious threat to shrimp aquaculture, especially Pacific white shrimp, Penaeus vannamei, the most farmed shrimp in the world. Activation of the Hippo-Yki signaling pathway, characterized by the intracellular Hippo-Wts kinase cascade reactions and the phosphorylation and cytoplasmic retention of Yki, is widely involved in various life activities. The current work established the fundamental structure and signal transduction profile of the Hippo-Yki pathway in P. vannamei and further investigated its role in viral infection. We demonstrated that WSSV promoted the dephosphorylation and nuclear translocation of Yki, suggesting that Hippo signaling is impaired and Yki is activated after WSSV infection in shrimp. In vivo, Yki gene silencing suppressed WSSV infection, while Hippo and Wts silencing promoted it, indicating a positive role of Hippo signaling in antiviral response. Further analyses showed that Yki suppressed Dorsal pathway activation and inhibited hemocyte apoptosis in WSSV-infected shrimp, while Hippo and Wts showed opposite effects, which contributed to the role of Hippo signaling in WSSV infection. Therefore, the current study suggests that WSSV annexes Yki to favor its infection in shrimp by inhibiting Hippo signaling. IMPORTANCE White spot syndrome virus (WSSV) is one of the most harmful viral pathogens to shrimp. The pathological mechanism of WSSV infection remains unclear to date. The Hippo-Yki signaling pathway is important for various biological processes and is extensively involved in mammalian immunity, but little is known about its role in infectious diseases in invertebrates. Based on revealing the fundamental structure of the shrimp Hippo pathway, this study investigated its implication in the pathogenesis of WSSV disease. We demonstrated that WSSV enhanced Yki activation by inhibiting Hippo signaling in shrimp. The activated Yki promoted WSSV infection by inhibiting hemocyte apoptosis and suppressing the activation of Dorsal, an NF-κB family member in shrimp that is critical for regulating antiviral response. Therefore, this study suggests that WSSV can hijack the Hippo-Yki signaling pathway to favor its infection in shrimp.

The occurrence and distribution of 10 brominated flame retardants (BFRs) and 10 organophosphate flame retardants (OPFRs) were investigated in indoor dust, total suspended particles (TSP), and vapour phase from offices (n = 10), homes (n = 9), and day-care centres (n = 10) in Beijing, China. Three types of samples were collected biweekly from one office and one home over a year to examine temporal trends. BFRs in dust significantly correlated with those in TSP, while OPFRs significantly correlated among all three matrices. In addition, BFRs in dust (ng/g) and TSP (pg/m3) exhibited similar temporal trends with higher levels in the cold season, whereas OPFRs in TSP and vapour phase (pg/m3) showed similar temporal trends with higher levels in the warm season. The geometric mean concentrations of BFRs and OPFRs in the three matrices from the above mentioned three types of indoor microenvironments were used for exposure and health risk estimation, and ∑7OPFRs showed much higher hazard index (HI) values than ∑10BFRs for all subpopulations, and inhalation of OPFRs was a major risk source. With the volatility of flame retardants (FRs) decreasing, the contribution of dust ingestion and dermal absorption showed an increasing trend, and the contribution of inhalation exhibited a gradual decreasing trend, which implied the dominant exposure pathway to FRs is strongly related to the vapour pressure (25 °C, Pa) of these substances. Using a single type of microenvironment or the collection of samples at a single point in time can lead to overestimation or underestimation of overall exposure and risk for people to some extent. The correlations of FRs in dust, TSP, and vapour phase from indoor microenvironments, as well as their temporal trends were first reported in this study, which will provide a basis for more accurate FR exposure assessments in the future.

Chemodynamic therapy (CDT), a newly developed approach for cancer treatment, can convert hydrogen peroxide (H2O2) into toxic hydroxyl radicals (•OH) by using Fenton/Fenton-like reaction to kill tumor cells. However, due to the complexity of the intracellular environment of tumor cells, the therapeutic efficacy of CDT was severely restricted. Recently, combination therapy strategies have become popular approaches for tumor treatment, and there are numerous studies have demonstrated that the CDT-based combination strategies can significantly improve the anti-tumor efficiency of CDT. In this review, we outline some of the recent progress in cancer chemodynamic therapy from 2020, and discuss the progress in the design of nanosystems for CDT synergistic combination therapies.

Abstract Despite remarkable breakthrough made by virtue of “polymerized small‐molecule acceptor (PSMA)” strategy recently, the limited selection pool of high‐performance polymer acceptors and long‐standing challenge in morphology control impede their further developments. Herein, three PSMAs of PYDT‐2F, PYDT‐3F, and PYDT‐4F are developed by introducing different fluorine atoms on the end groups and/or bithiophene spacers to fine‐tune their optoelectronic properties for high‐performance PSMAs. The PSMAs exhibit narrow bandgap and energy levels that match well with PM6 donor. The fluorination promotes the crystallization of the polymer chain for enhanced electron mobility, which is further improved by following n‐doping with benzyl viologen additive. Moreover, the miscibility is also improved by introducing more fluorine atoms, which promotes the intermixing with PM6 donor. Among them, PYDT‐3F exhibits well‐balanced high crystallinity and miscibility with PM6 donor; thus, the layer‐by‐layer processed PM6/PYDT‐3F film obtains an optimal nanofibril morphology with submicron length and ≈23 nm width of fibrils, facilitating the charge separation and transport. The resulting PM6/PYDT‐3F devices realizes a record high power conversion efficiency (PCE) of 17.41% and fill factor of 77.01%, higher than the PM6/PYDT‐2F (PCE = 16.25%) and PM6/PYDT‐4F (PCE = 16.77%) devices.

SH2-domain-containing protein tyrosine phosphatases (PTPs), belonging to the class I PTP superfamily, are responsible for the dephosphorylation on the phosphorylated tyrosine residues in some proteins that are involved in multiple biological processes in eukaryotes. The Janus kinase/signal transducers and activators of transcription (JAK/STAT) pathway transduce signaling responding to interferons and initiate cellular antiviral responses. The activity of the JAK/STAT pathway is generally orchestrated by the de-/phosphorylation of the tyrosine and serine residues of JAKs and STATs, in which the dephosphorylation processes are mainly controlled by PTPs. In the present study, an SH2-domian-contianing PTP, temporally named as LvPTPN6, was identified in Litopenaeus vannamei. LvPTPN6 shares high similarity with PTPN6s from other organisms and was phylogenetically categorized into the clade of arthropods that differs from those of fishes and mammals. LvPTPN6 was constitutively expressed in all detected tissues, located mainly in the cytoplasm, and differentially induced in hemocyte and gill after the challenge of stimulants, indicating its complicated regulatory roles in shrimp immune responses. Intriguingly, the expression of LvPTPN6 was regulated by interferon regulatory factor (IRF), which could directly bind to the LvPTPN6 promoter. Surprisingly, unlike other PTPN6s, LvPTPN6 could promote the dimerization of STAT and facilitate its nuclear localization, which further elevated the expression of STAT-targeting immune effector genes and enhanced the antiviral immunity of shrimp. Therefore, this study suggests a PTPN6-mediated regulatory approach from IRF to the JAK/STAT signaling pathway in shrimp, which provides new insights into the regulatory roles of PTPs in the JAK/STAT signaling pathway and contributes to the further understanding of the mechanisms of antiviral immunity in invertebrates.

The inverse design method based on a generative adversarial network (GAN) combined with a simulation neural network (sim-NN) and the self-attention mechanism is proposed in order to improve the efficiency of GAN for designing nanophotonic devices. The sim-NN can guide the model to produce more accurate device designs via the spectrum comparison, whereas the self-attention mechanism can help to extract detailed features of the spectrum by exploring their global interconnections. The nanopatterned power splitter with a 2 μm × 2 μm interference region is designed as an example to obtain the average high transmission (>94%) and low back-reflection (

Toll-like receptors (TLRs) are canonical cell membrane receptors functioning to recognize pathogens and transduce signals to activate immune responses. It has been known that Toll3 in Pacific white shrimp Litopenaeus vannamei (LvToll3) plays a critical role in antiviral immunity by inducing the transcription of interferon regulatory factor (IRF), which mediates a signaling axis that is similar to the interferon system of vertebrates. However, the regulatory mechanism of the Toll3-IRF signaling is still unclear. In this study, a novel microRNA (miRNA) of miR-10 family, temporarily named as miR-10c, was identified from L. vannamei. miR-10c may play a nonnegligible regulatory role in shrimp immune responses since it was constitutively expressed in all detected tissues and transcriptionally induced by immune stimulation. Functional analysis validated that miR-10c could target LvToll3 to inhibit its expression, through which miR-10c blocked the nuclear translocation of IRF and facilitated white spot syndrome virus (WSSV) infection. To our knowledge, the present study revealed the first report of a Toll targeted by miRNA in crustaceans and provided a solid evidence base for supporting the role of LvToll3 in antiviral defense by activating IRF signaling in L. vannamei. Identification of the miR-10c/Toll3/IRF regulatory axis in shrimp provides new insights into the participation of miRNA in the regulation of immune responses and contributes to in-depth understanding of the mechanisms of Toll-induced immune responses in L. vannamei.

ObjectiveThe emergence of multi-drug resistance (MDR) in esophageal carcinoma has severely affected the effect of chemotherapy and shortened the survival of patients. To this end, we intend to develop a biomimetic nano-targeting drug modified by cancer cell membrane, and investigate its therapeutic effect.MethodsThe degradable poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) co-loaded with doxorubicin (DOX) and curcumin (Cur) were prepared by solvent evaporation method. TE10 cell membrane and Distearoyl phosphatidylethanolamine-polyethylene glycol (DSPE-PEG) were then coated on the PLGA NPs by membrane extrusion to prepare the PEG-TE10@PLGA@DOX-Cur NPs (PMPNs). Size and zeta potential of the PMPNs were analyzed by lazer particle analyzer, and the morphology of PMPNs was observed by transmission electron microscope. The TE10 cell membrane protein on PMPNs was analyzed by gel electrophoresis. The DOX-resistant esophageal cancer cell model TE10/DOX was established through high-dose induction. The In vitro homologous targeting ability of PMPNs was evaluated by cell uptake assay, and the in vitro anti-tumor effect of PMPNs was assessed through CCK-8, clone formation and flow cytometry. A Balb/c mouse model of TE10/DOX xenograft was constructed to evaluate the anti-tumor effect in vivo and the bio-safety of PMPNs.ResultsThe prepared cell membrane coated PMPNs had a regular spherical structure with an average diameter of 177 nm. PMPNs could directly target TE10 and TE10/DOX cells or TE10/DOX xenografted tumor and effectively inhibit the growth of DOX-resistant esophageal carcinoma. Besides, the PMPNs was confirmed to have high biosafety.ConclusionIn this study, a targeted biomimetic nano-drug delivery system PMPNs was successfully prepared, which overcome the MDR of esophageal carcinoma by co-delivering DOX and sensitizer curcumin.

Summary: Two wide band-gap copolymers poly[4,8-bis(5-(2-butylhexylthio)thiophen-2-yl)benzo[1,2-b:4,5-b′]dithiophene-2,6-diyl-alt-TZNT] (PBDTS-TZNT) and poly[4,8-bis(4-fluoro-5-(2-butylhexylthio)thiophen-2-yl)benzo[1,2-b:4,5-b′]dithiophene-2,6-diyl-alt-TZNT] (PBDTSF-TZNT) based on naphtho[1,2-c:5,6-c]bis(2-octyl-[1,2,3]triazole) (TZNT) and benzo[1,2-b:4,5-b']dithiophene (BDT) with different conjugated side chains have been developed for efficient nonfullerene polymer solar cells (NF-PSCs). The rigid planar backbone of BDT and TZNT units imparted high crystallinity and good molecular stacking property to these copolymers. Using 3,9-bis(2-methylene-(3-(1,1-dicyanomethylene)-indanone)-5,5,11,11-tetrakis(4-hexylphenyl)-dithieno[2,3-d:2′,3′-d′]-s-indaceno[1,2-b:5,6-b′]-dithiophene (ITIC) as the acceptor, PBDTSF-TZNT devices showed a high Voc of 0.98 V with an Eloss of 0.61 eV. On selecting 3,9-bis(2-methylene-(5,6-difluoro-(3-(1,1-dicyanomethylene)-indanone)-5,5,11,11-tetrakis(4-hexylphenyl)-dithieno[2,3-d:2′,3′-d′]-s-indaceno[1,2-b:5,6-b’]-dithiophene (IT-4F) instead of ITIC, the devices maintained the high Voc of 0.93 V with an even lower Eloss of 0.59 eV. The combination of the above-mentioned low Eloss, broadened absorption, better matched energy level, improved crystallinity, and fine-tuned morphology promoted the power conversion efficiency (PCE) of PBDTSF-TZNT:IT-4F devices from 12.16% to 13.25%. Homo-tandem devices based on PBDTSF-TZNT:IT-4F subcells further enhanced the light-harvesting ability and boosted the PCE of 14.52%, which is the best value for homo-tandem NF-PSCs at present. : Chemical Synthesis; Energy Materials; Devices Subject Areas: Chemical Synthesis, Energy Materials, Devices

The forkhead box protein P (FoxP) family members have been known to be important for regulation of immune responses in vertebrates, but their roles in invertebrate immunity remain unclear. In this study, a novel FoxP gene (LvFoxP) was identified from Pacific white shrimp Litopenaeus vannamei and functionally studied in the context of immune response. Possessing a conserved FoxP coiled-coil domain and a forkhead domain, LvFoxP shared homology to vertebrate FoxP family members, in particular FoxP1. Expression of LvFoxP was detectable in all the examined tissues and could be up-regulated by immune challenge in gill and hemocytes. The LvFoxP protein was present in both the cytoplasm and nucleus of hemocytes and could be nuclear-translocated upon immune stimulation. Silencing of LvFoxP increased the susceptibility of shrimp to infections by Vibrio parahaemolyticus and white spot syndrome virus (WSSV) and down-regulated the expression of multiple components of NF-κB and JAK-STAT pathways and almost all the examined immune effector genes. Moreover, the phagocytic activity of hemocytes from LvFoxP-silenced shrimp against V. parahaemolyticus was decreased. These suggested that LvFoxP could play a positive role in immune response. The current study may provide novel insights into the immunity of invertebrates and the functional evolution of the FoxP family.

Perylene diimide (PDI) is a widely explored chromophore for constructing non-fullerene acceptors (NFAs) for polymer solar cells (PSCs). The advantage of using PDI derivatives lies in the readily availability of PDI unit which largely reduces the synthesis cost and improves material stability. Indeed, the recent development of high performance NFAs shed light on the feasibility of the commercialization, but the complex synthesis and poor stability of the top performing NFAs cast a shadow on this bright future. Our previous work has demonstrated a propeller-like structure with three PDIs lined to a benzene center core with a C-C bond which prevented the PDIs to aggregate into undesired large crystals. In this work, we designed and synthesized three new propeller-like PDI derivatives with extra chalcogen linkages between the PDIs and the center core to form all-fused rigid structures. These molecules showed more suitable absorption range than that of their unfused counterparts when blend with donor polymer PTB7-Th. Comparing between the molecules with extra oxygen, sulfur or selenium linkages, the sulfur-based BTT-PDI outperformed the others due to its higher photon absorption and charge transport abilities. This work demonstrated the great potential of PDI derivatives for PSC applications and explored the influences of linkage type on the fused PDI derivatives, which provided a useful tuning knob for molecular design of PDI-based NFAs in the future.

Cereal crops' grain yield and quality are traits that are usually considered to be negatively correlated. Here, the authors show that interaction of G-protein βγ subunits with an alternatively spliced MADS1lgy3 protein can increase rice grain yield and quality simultaneously in field conditions.

Polydatin and resveratrol, as major active components in Polygonum cuspidatum, have anti-inflammatory, antioxidant and antitumor functions. However, the effect and mechanism of polydatin and resveratrol on enterovirus 71 (EV71) have not been reported. In this study, resveratrol revealed strong antiviral activity on EV71, while polydatin had weak effect. Neither polydatin nor resveratrol exhibited influence on viral attachment. Resveratrol could effectively inhibit the synthesis of EV71/VP1 and the phosphorylation of IKKα, IKKβ, IKKγ, IKBα, NF-κB p50 and NF-κB p65, respectively. Meanwhile, the remarkably increased secretion of IL-6 and TNF-α in EV71-infected rhabdosarcoma (RD) cells could be blocked by resveratrol. These results demonstrated that resveratrol inhibited EV71 replication and cytokine secretion in EV71-infected RD cells through blocking IKKs/NF-κB signaling pathway. Thus, resveratrol may have potent antiviral effect on EV71 infection.

The nuclear factor-kappa B (NF-κB) pathways play important roles in innate immune responses. IκB is the main cytoplasmic inhibitor of NF-κB. In this study, we identified the LvCactus gene from Litopenaeus vannamei, which is the first cloned IκB homologue in subphylum Crustacea. LvCactus contains six predicted ankyrin repeats, which show similarities to those of Cactus proteins from insects. LvCactus localizes in cytoplasm and interacts with LvDorsal, an L. vannamei homologue to Drosophila melanogaster Dorsal belonging to class II NF-κB family, to prevent its nuclear translocation. Contrary to that of LvDorsal, over-expression of LvCactus down-regulates the activities of shrimp antimicrobial peptides promoters, suggesting LvCactus is an inhibitor of LvDorsal. The promoter of LvCactus was predicted to contain five putative NF-κB binding motifs, among which four were proved to be bound by LvDorsal by chromatin immunoprecipitation assays. Dual-luciferase reporter assays also showed that transcription of LvCactus was promoted by LvDorsal but inhibited by LvCactus itself, indicating a feedback regulatory pathway between LvCactus and LvDorsal. Expression of LvCactus was up-regulated after Lipopolysaccharides, poly (I:C), Vibrio parahaemolyticus, and Staphylococcus aureus injections, suggesting an activation response of LvCactus to bacterial and immune stimulant challenges. Differently, the LvCactus expression levels obviously decreased during white spot syndrome virus (WSSV) infection, indicating the feedback regulatory pathway of LvCactus/LvDorsal could be modified by WSSV.

BACKGROUND: Pacific white shrimp (Litopenaeus vannamei), the major species of farmed shrimps in the world, has been attracting extensive studies, which require more and more genome background knowledge. The now available transcriptome data of L. vannamei are insufficient for research requirements, and have not been adequately assembled and annotated. METHODOLOGY/PRINCIPAL FINDINGS: This is the first study that used a next-generation high-throughput DNA sequencing technique, the Solexa/Illumina GA II method, to analyze the transcriptome from whole bodies of L. vannamei larvae. More than 2.4 Gb of raw data were generated, and 109,169 unigenes with a mean length of 396 bp were assembled using the SOAP denovo software. 73,505 unigenes (>200 bp) with good quality sequences were selected and subjected to annotation analysis, among which 37.80% can be matched in NCBI Nr database, 37.3% matched in Swissprot, and 44.1% matched in TrEMBL. Using BLAST and BLAST2Go softwares, 11,153 unigenes were classified into 25 Clusters of Orthologous Groups of proteins (COG) categories, 8171 unigenes were assigned into 51 Gene ontology (GO) functional groups, and 18,154 unigenes were divided into 220 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. To primarily verify part of the results of assembly and annotations, 12 assembled unigenes that are homologous to many embryo development-related genes were chosen and subjected to RT-PCR for electrophoresis and Sanger sequencing analyses, and to real-time PCR for expression profile analyses during embryo development. CONCLUSIONS/SIGNIFICANCE: The L. vannamei transcriptome analyzed using the next-generation sequencing technique enriches the information of L. vannamei genes, which will facilitate our understanding of the genome background of crustaceans, and promote the studies on L. vannamei.

Background The key challenge in drug discovery is to discover novel compounds with desirable properties. Among the properties, binding affinity to a target is one of the prerequisites and usually evaluated by molecular docking or quantitative structure activity relationship (QSAR) models. Methods In this study, we developed SGPT-RL, which uses a generative pre-trained transformer (GPT) as the policy network of the reinforcement learning (RL) agent to optimize the binding affinity to a target. SGPT-RL was evaluated on the Moses distribution learning benchmark and two goal-directed generation tasks, with Dopamine Receptor D2 (DRD2) and Angiotensin-Converting Enzyme 2 (ACE2) as the targets. Both QSAR model and molecular docking were implemented as the optimization goals in the tasks. The popular Reinvent method was used as the baseline for comparison. Results The results on the Moses benchmark showed that SGPT-RL learned good property distributions and generated molecules with high validity and novelty. On the two goal-directed generation tasks, both SGPT-RL and Reinvent were able to generate valid molecules with improved target scores. The SGPT-RL method achieved better results than Reinvent on the ACE2 task, where molecular docking was used as the optimization goal. Further analysis shows that SGPT-RL learned conserved scaffold patterns during exploration. Conclusions The superior performance of SGPT-RL in the ACE2 task indicates that it can be applied to the virtual screening process where molecular docking is widely used as the criteria. Besides, the scaffold patterns learned by SGPT-RL during the exploration process can assist chemists to better design and discover novel lead candidates.

Background: The key challenge in drug discovery is to discover novel compounds with desirable properties. Among the properties, binding affinity to a target is one of the prerequisites and usually evaluated by molecular docking or quantitative structure activity relationship (QSAR) models. Methods: In this study, we developed Simplified molecular input line entry system Generative Pre-trained Transformer with Reinforcement Learning (SGPT-RL), which uses a transformer decoder as the policy network of the reinforcement learning agent to optimize the binding affinity to a target. SGPT-RL was evaluated on the Moses distribution learning benchmark and two goal-directed generation tasks, with Dopamine Receptor D2 (DRD2) and Angiotensin-Converting Enzyme 2 (ACE2) as the targets. Both QSAR model and molecular docking were implemented as the optimization goals in the tasks. The popular Reinvent method was used as the baseline for comparison. Results: The results on Moses benchmark showed that SGPT-RL learned good property distributions and generated molecules with high validity and novelty. On the two goal-directed generation tasks, both SGPT-RL and Reinvent were able to generate valid molecules with improved target scores. The SGPT-RL method achieved better results than Reinvent on the ACE2 task, where molecular docking was used as the optimization goal. Further analysis shows that SGPT-RL learned conserved scaffold patterns during exploration. Conclusions: The superior performance of SGPT-RL in the ACE2 task indicates that it can be applied to the virtual screening process where molecular docking is widely used as the criteria. Besides, the scaffold patterns learned by SGPT-RL during the exploration process can assist chemists to better design and discover novel lead candidates.