Strong electron-phonon coupling and multigap superconductivity in 2H/1T Janus MoSLi monolayer.

Two-dimensional (2D) Janus transition metal dichalcogenides MXY manifest novel physical properties owing to the breaking of out-of-plane mirror symmetry. Recently, the 2H phase of MoSH has been demonstrated to possess intrinsic superconductivity, whereas the 1T phase exhibits a charge density waves state. In this paper, we have systematically studied the stability and electron-phonon interaction characteristics of MoSLi. Our results have shown that both the 2H and 1T phases of MoSLi are stable, as indicated by the phonon spectrum and the ab initio molecular dynamics. However, the 1T phase exhibits an electron-phonon coupling constant that is twice as large as that of the 2H phase. In contrast to MoSH, the 1T phase of MoSLi exhibits intrinsic superconductivity. By employing the ab initio anisotropic Migdal-Eliashberg formalism, we have revealed the two-gap superconducting nature of 1T-MoSLi, with a transition temperature (Tc) of 14.8 K. The detailed analysis indicates that the superconductivity in 1T-MoSLi primarily originates from the interplay between the vibration of the phonon modes in the low-frequency region and the dz2 orbital. These findings provide a fresh perspective on superconductivity within Janus structures.

Confined and spontaneously transformed oxidation structures due to the intrinsic heterogeneous surface morphology of C3N monolayer.

Identifying the oxidation structure of two-dimensional interfaces is crucial to improve surface chemistry and electronic properties. Beyond graphene with only phenyl rings, a novel carbon-nitrogen material, C3N, presents an intrinsic heterogeneous surface morphology where each phenyl ring is encircled by six nitrogen atoms, yet its atomistic oxidation structure remains unclear. Here, combining a series of density functional theory calculations and ab initio molecular dynamics simulations, we demonstrate that thermodynamically favorable oxidation loci are confined to the phenyl ring, and kinetic transformations of oxidation structures are feasible along the phenyl ring, whereas those toward nitrogen atoms are proven to be extremely difficult. These results are attributed to the lower barrier of oxygen atom migration along the phenyl ring, while the significantly high barriers toward nitrogen atoms are due to the heterogeneous potential energy surface for oxygen-C3N interaction. This work highlights the significance of surface morphology on the characteristics of oxidation structure, offering insights into tunable electronic properties via confined interfacial oxidation.

Exceptional metal-semiconductor-metal transition of lead apatites via oxygen defect tuning.

Lead apatites, distinguished and compelling bulk materials with the stoichiometric arrangement as Pb10(POx)6Oy, are renowned for their structural complexity. Recently, the discovery of possible room-temperature superconductivity under ambient pressure in copper-substituted lead apatites has engendered considerable interest within both the physics community and beyond. Nevertheless, exploration of pristine Pb10(POx)6Oy parent structures has hitherto remained elusive. In this study, we employ density functional theory (DFT) calculations to investigate the effects of oxygen defects on the electronic structures of Pb10(POx)6Oy and Pb9Cu(POx)6Oy. We scrutinize two distinct categories of defects: oxygen atoms enmeshed within POx groups (Ox) and solitary oxygen atoms (Oy). Our investigation uncovers a profound influence of these defects on the band structure. Specifically, the introduction of Oy defects prompts a remarkable transition in Pb10(PO4)6Oy from a metal to semiconductor to metal state, accompanied by pivotal shifts in the principal electronic contributors from p orbitals of Oy to those of Pb atoms. Furthermore, the introduction of Ox defects in Pb10(POx)6O1 engenders metamorphosis in the band structure, transmuting it from a semiconductor to a metallic state. Significantly, our findings pinpoint the suitable range of x in the Pb10(POx)6O1 configuration as lying between 2 and 4. Additionally, our study also demonstrates that the oxygen defects (Ox/Oy) do not affect the metallic properties of copper-substituted lead apatites. This study elucidates the significant role of oxygen defects in modulating the electronic properties of apatite materials, offering insights into potential interdisciplinary applications. This establishes a crucial link between material composition and electronic behavior, revealing key mechanisms for engineering functionality in lead apatites and other advanced materials.

Rational Design of Full-Color Fluorescent C3N Quantum Dots.

Carbon-based quantum dots (QDs) exhibit unique photoluminescence due to size-dependent quantum confinement, giving rise to fascinating full-color emission properties. Accurate emission calculations using time-dependent density functional theory are a time-costing and expensive process. Herein, we employed an artificial neural network (ANN) combined with statistical learning to establish the relationship between geometrical/electronic structures of ground states and emission wavelength for C3N QDs. The emission energy of these QDs can be doubly modulated by size and edge effects, which are governed by the number of C4N2 rings and the CH group, respectively. Moreover, these two structural characteristics also determine the phonon vibration mode of C3N QDs to harmonize the emission intensity and lifetime of hot electrons in the electron-hole recombination process, as indicated by nonadiabatic molecular dynamics simulation. These computational results provide a general approach to atomically precise design the full-color fluorescent carbon-based QDs with targeted functions and high performance.

The effect of exposure to COVID-19 on life satisfaction: The mediating role of hyperarousal and moderating/mediating role of affective forecasting.

BACKGROUND: As a global trauma event, the Coronavirus disease (COVID-19) hugely impacts people's mental health and well-being. The purpose of our study is threefold: first, investigate the relationship between exposure to COVID-19 and life satisfaction among a large sample in China; second, test the mediating role of hyperarousal in the association between exposure to COVID-19 and life satisfaction; third, explore the moderating/mediating role of affective forecasting in the association between hyperarousal and life satisfaction. METHOD: The current study recruited 5546 participants to complete a set of self-report questionnaires online from April 22, 2020 to April 24, 2020. The moderated mediation and chain mediation model analyses were conducted using the SPSS software and PROCESS macro program. RESULTS: Exposure to COVID-19 negatively predicted life satisfaction (Effect = -0.058, p < 0.001). This relationship was partially mediated by the hyperarousal level (Effect = -0.018, CI = [-0.024, -0.013]). The moderating role of forecasted positive affect (PA)/forecasted negative affect (NA) between hyperarousal and life satisfaction was significant (ß = 0.058, CI = [0.035, 0.081]; ß = 0.037, CI = [0.014, 0.06]). The chain mediating effect of hyperarousal and forecasted PA/forecasted NA on the relationship between exposure to COVID-19 and life satisfaction was also significant (Effect = -0.003, CI = [-0.004, -0.002]; Effect = -0.006, CI = [-0.008, -0.004]). LIMITATIONS: The cross-sectional design precludes causal inference. CONCLUSION: Greater exposure to COVID-19 was associated with more severe hyperarousal symptoms, decreased life satisfaction. Forecasted PA and forecasted NA could moderate and mediate the negative impact of hyperarousal on life satisfaction. The moderating/mediating role of forecasted PA/NA implied that future interventions targeting at improving affective forecasting and reducing hyperarousal might be helpful to improve life satisfaction during the post-COVID-19 era.

The single-atom catalytic activity of the hydrogen evolution reaction of the experimentally synthesized boridene 2D material: a density functional theory study.

CONTEXT: Previous theoretical studies have suggested that two-dimensional (2D) MBene materials might display adequate monatomic catalytic activity for the hydrogen evolution reaction (HER). Recently, a study reported the experimental synthesis of a 2D MBene (Mo4/3B2), re-defined as boridene, albeit no effort has been devoted to explore the single-atom catalytic activity for HER of this experimentally synthesized 2D material. Therefore, we herein investigate the single-atom HER performance of the boridene. Interestingly, with Mo defects mixed with single Au and Zn atoms shows excellent hydrogen evolution performance, and the change in the Gibbs free energy ([Formula: see text]) value is close to 0 eV, which can even match the performance of Pt-based materials. Through analysis of the charge density difference and density of states, the mechanism affecting the HER performance is explained at the electronic level. This work provides a new direction for the use of the Mo4/3B2 monolayer two-dimensional materials in the field of single-atom catalysis for HER. METHODS: This study used the DFT calculations in Vienna ab initio simulation package. The GGA-Perdew-Burke-Ernzerhof functional with DFT-D2 correction is used to describe the exchange-correlation interactions. The projection augmented wave is used with the plane wave cutoff of 500 eV. The convergences of energy and force are 10-5 eV and 0.01 eV/Å, respectively. A vacuum layer with a height of 20 Å is set in the Z direction. For geometry optimization, self-consistent, and DOS calculations, the k-point grids sampled in Brillouin zones are 3 × 3 × 1, 9 × 9 × 1, and 9 × 9 × 1, respectively. The AIMD simulation is performed in the canonical ensemble (NVT), and the temperature was maintained at 300 K by Nosé-Hoover thermostats with a time step of 2.0 fs.

Unexpectedly spontaneous water dissociation on graphene oxide supported by copper substrate.

Water dissociation is of fundamental importance in scientific fields and has drawn considerable interest in diverse technological applications. However, the high activation barrier of breaking the OH bond within the water molecule has been identified as the bottleneck, even for the water adsorbed on the graphene oxide (GO). Herein, using the density functional theory calculations, we demonstrate that the water molecule can be spontaneously dissociated on GO supported by the (111) surface of the copper substrate (Copper-GO). This process involves a proton transferring from water to the interfacial oxygen group, and a hydroxide covalently bonding to GO. Compared to that on GO, the water dissociation barrier on Copper-GO is significantly decreased to be less than or comparable to thermal fluctuations. This is ascribed to the orbital-hybridizing interaction between copper substrate and GO, which enhances the reaction activity of interfacial oxygen groups along the basal plane of GO for water dissociation. Our work provides a novel strategy to access water dissociation via the substrate-enhanced reaction activity of interfacial oxygen groups on GO and indicates that the substrate can serve as an essential key to tuning the catalytic performance of various two-dimensional material devices.

Directional Bloch surface wave coupling enabled by magnetic spin-momentum locking of light.

We study the magnetic spin-locking of optical surface waves. Through an angular spectrum approach and numerical simulations, we predict that a spinning magnetic dipole develops a directional coupling of light to transverse electric (TE) polarized Bloch surface waves (BSWs). A high-index nanoparticle as a magnetic dipole and nano-coupler is placed on top of a one-dimensional photonic crystal to couple light into BSWs. Upon circularly polarized illumination, it mimics the spinning magnetic dipole. We find that the helicity of the light impinging on the nano-coupler controls the directionality of emerging BSWs. Furthermore, identical silicon strip waveguides are configured on the two sides of the nano-coupler to confine and guide the BSWs. We achieve a directional nano-routing of BSWs with circularly polarized illumination. Such a directional coupling phenomenon is proved to be solely mediated by the optical magnetic field. This offers opportunities for directional switching and polarization sorting by controlling optical flows in ultra-compact architectures and enables the investigation of the magnetic polarization properties of light.

microRNA-93 packaged in extracellular vesicles from mesenchymal stem cells reduce neonatal hypoxic-ischemic brain injury.

OBJECTIVE: Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have been proposed as a promising strategy for treating ischemia-related diseases. Herein, we probed into the role of miR-93 delivered by BMSC-EVs in hypoxic-ischemic brain injury (HIBD). METHODS: Neonatal HIBD mouse models and hippocampal neuron models of oxygen glucose deprivation (OGD) were constructed. EVs were isolated from the culture medium of bone marrow MSCs (BMSCs). After co-culture of BMSC-EVs with OGD-exposed hippocampal neurons, the effect of microRNA-93 (miR-93) delivered by BMSC-EVs on OGD-induced hippocampal neurons as well as on HIBD in vivo under transfection of miR-93 mimic or inhibitor was explored. The interaction among miR-93, JMJD3, and p53/KLF2 axis was assessed. RESULTS: BMSC-EVs prevented OGD-induced hippocampal neuron apoptosis and inflammation, which was associated with their transfer of miR-93 into the hippocampal neurons. miR-93 targeted JMJD3 and downregulated its expression, thus inhibiting the OGD-induced hippocampal neuron apoptosis. By regulating the JMJD3/p53/KLF2 axis, miR-93 in BMSC-EVs reduced the OGD-induced hippocampal neuron apoptosis in vitro as well as alleviating HIBD in vivo. CONCLUSIONS: The current study highlighted that miR-93 delivered by BMSC-EVs alleviated HIBD in neonatal mice through the JMJD3-dependent p53/KLF2 axis.

Construction and Research on Chinese Semantic Mapping Based on Linguistic Features and Sparse Self-Learning Neural Networks.

In this paper, we adopt the algorithms of linguistic feature Rong and sparse self-learning neural network to conduct an in-depth study and analysis of Chinese semantic mapping, which complements the emotion semantic representation ability of traditional word embedding and fully explores the emotion semantic information contained in the text in the task preprocessing stage. We incorporate various semantic features such as lexical information and location information to make the model have richer emotion semantic expression, and the model also uses an attention mechanism to allow various features to interact and abstract deeper contextual internal semantic associations to improve the model's sentiment classification performance. Finally, experiments are conducted on two publicly available English sentiment classification corpora, and the results prove that the model outperforms other comparison models and effectively improves the sentiment classification performance. The model uses deep memory networks and capsule networks to construct a transfer learning framework and effectively leverages the transfer learning properties of capsule networks to transfer knowledge embedded in large-scale labeled data from similar domains to the target domain, improving the classification performance on small data sets. The use of multidimensional combined features compensates for the lack of a one-dimensional feature attention mechanism, while multiple domain category-based attention computation layers are superimposed to obtain deeper domain-specific sentiment feature information. Based on the segmented convolutional neural network, the model first introduces the dependent subtree of relational attributes to obtain the position weights of each word in the sentence, then introduces domain ontology knowledge in the output layer to constrain the extraction results, and conducts experimental comparison through the data set to verify the validity of the model, which ensures the accuracy of the network term entity and relational attribute recognition extraction and makes the knowledge map constructed in this paper. It ensures the accuracy of the extraction rate of the web term entities and relationship attributes and makes the knowledge map constructed in this paper more factual.

Comprehensive Analyses of Mutation-Derived Long-Chain Noncoding RNA Signatures of Genome Instability in Kidney Renal Papillary Cell Carcinoma.

Background: The role of long-chain noncoding RNA (lncRNA) in genomic instability has been demonstrated to be increasingly importance. Therefore, in this study, lncRNAs associated with genomic instability were identified and kidney renal papillary cell carcinoma (KIRP)-associated predictive features were analysed to classify high-risk patients and improve individualised treatment. Methods: The training (n = 142) and test (n = 144) sets were created using raw RNA-seq and patient's clinical data of KIRP obtained from The Cancer Genome Atlas (TCGA).There are 27 long-chain noncoding RNAs (lncRNAs) that are connected with genomic instability, these lncRNAs were identified using the 'limma' R package based on the numbers of somatic mutations and lncRNA expression profiles acquired from KIRP TCGA cohort. Furthermore, Cox regression analysis was carried out to develop a genome instability-derived lncRNA-based gene signature (GILncSig), whose prognostic value was confirmed in the test cohort as well as across the entire KIRP TCGA dataset. Results: A GILncSig derived from three lncRNAs (BOLA3-AS1, AC004870, and LINC00839), which were related with poor KIRP survival, was identified, which was split up into high- and low-risk groups. Additionally, the GILncSig was found to be an independent prognostic predictive index in KIRP using univariate and multivariate Cox analysis. Furthermore, the prognostic significance and characteristics of GilncSig were confirmed in the training test and TCGA sets. GilncSig also showed better predictive performance than other prognostic lncRNA features. Conclusion: The function of lncRNAs in genomic instability and the genetic diversity of KIRP were elucidated in this work. Moreover, three lncRNAs were screened for prediction of the outcome of KIRP survival and novel insights into identifying cancer biomarkers related to genomic instability were discussed.

Interaction between working memory load and the ability to resist interference from negative distractors in dysphoria.

Although the relationship between emotional working memory (WM) and depressive symptoms has been well established in clinical samples, research in the subclinical population has produced mixed results. The present study tested the effect of WM load on control of interference from emotional (positive, negative, neutral) distractors in dysphoria. Dysphoric (n = 32) and non-dysphoric (n = 35) university students were administered the emotional 2-back (lower WM load) and 3-back (higher WM load) tasks. Results showed that resisting negative distractors was more difficult for the dysphoric group than the non-dysphoric group, but only in the 3-back task. The results demonstrate that dysphoria is associated with greater interference from negative distractors under high WM load. We conclude that both WM load and emotional valence have an effect on WM performance in dysphoria, and the poor ability to resist interference from negative distractors in WM might be a key cognitive vulnerability factor for depression.

Unexpected spontaneous dynamic oxygen migration on carbon nanotubes.

Combining density functional theory (DFT) calculations and ab initio molecular dynamics (AIMD) simulations, we show that oxygen functional groups exhibit unexpected spontaneous dynamic behaviors on the interior surface of single-walled carbon nanotubes (SWCNTs). The hydroxyl and epoxy migrations are achieved by the C-O bond breaking/reforming reactions or the proton transfer reaction between the neighboring epoxy and hydroxyl groups. It is demonstrated that the spontaneous dynamic characteristic is attributed to the sharply reduced energy barrier less than or comparable to thermal fluctuations. We also observe a stable intermediate state with a dangling C-O bond, which permits the successive migration of the oxygen functional groups. However, on the exterior surface of SWCNTs, it is difficult for the oxygen groups to migrate spontaneously because there are relatively high energy barriers, and the dangling C-O bond prefers to transform into the more stable epoxy configuration. The spontaneous oxygen migration is further confirmed by the oxygen migration process using DFT calculations and AIMD simulations at room temperature. Our work provides a new understanding of the behavior of oxygen functional groups at interfaces and gives a potential route to design new carbon-based dynamic materials.

Early Prediction of Refractory Epilepsy in Children Under Artificial Intelligence Neural Network.

In order to realize the early prediction of refractory epilepsy in children, data preprocessing technology was used to improve the data quality, and the detection model of refractory epilepsy in children based on convolutional neural network (CNN) was established. Then, the data in the epilepsy electroencephalography (EEG) signal public data set was used for model training and the diagnosis of refractory epilepsy in children. Moreover, back propagation neural network (BPNN), support vector machine (SVM), XGBoost, gradient boosting decision tree (GBDT), AdaBoost algorithm were introduced for comparison. The results showed that the early prediction accuracy of BP, SVM, XGBoost, GBDT, AdaBoost, and the algorithm in this study for refractory epilepsy in children were 0.745, 0.778, 0.885, 0.846, 0.874, and 0.941, respectively. The sensitivities were 0.81, 0.826, 0.822, 0.84, 0.859, and 0.918, respectively. The specificities were 0.683, 0.696, 0.743, 0.792, 0.84, and 0.905, respectively. The accuracy was 0.707, 0.732, 0.765, 0.802, 0.839, and 0.881, respectively. The recall rates were 0.69, 0.716, 0.753, 0.784, 0.813, and 0.877, respectively. F1 scores were 0.698, 0.724, 0.759, 0.793, 0.826, and 0.879, respectively. Through the comparisons of the above six indicators, the algorithm proposed in this study was significantly higher than other algorithms, suggesting that the proposed algorithm was more accurate in early prediction of refractory epilepsy in children. Analysis of the EEG characteristics and magnetic resonance imaging (MRI) images of refractory epilepsy in children suggested that the MRI images of patients' brains under this algorithm had obvious characteristics. The reason for the prediction error of the algorithm was that the duration of epilepsy was too short or the EEG of the patient didn't change notably during the epileptic seizure. In summary, the prediction method of refractory epilepsy in children based on CNN was accurate, which had broad adoption prospects in assisting clinicians in the examination and diagnosis of refractory epilepsy in children.

Exosomes containing miR-122-5p secreted by LPS-induced neutrophils regulate the apoptosis and permeability of brain microvascular endothelial cells by targeting OCLN.

OBJECTIVE: To explore the effect of exosomes containing miR-122-5p secreted by lipopolysaccharide (LPS)-induced neutrophils on the apoptosis and permeability of brain microvascular endothelial cells (BMECs). METHODS: Neutrophils in blood were isolated, purified and identified. LPS-induced neutrophils were co-cultured with BMECs. Untreated or LPS-induced neutrophil exosomes were isolated and identified with a transmission electron microscope. miR-122-5p expressions in the exosomes were detected by real-time quantitative polymerase chain reaction, and then the exosomes were co-cultured with BMECs. Bioinformatics analysis was performed to predict the downstream target gene of miR-122-5p, and OCLN was selected as the subject. Dual luciferase reporter assay was carried out to verify the interactive relationship between OCLN and miR-122-5p. LPS and miR-122-5p were used to treat neutrophils, and then exosomes were collected. Exosome or OCLN was embedded in BMECs. The proliferation, colony forming ability and apoptosis of BMECs were detected by cholecystokinin octopeptide, clone formation assay and flow cytometry, respectively. Corresponding kits were used to detect the activities of reactive oxygen species, superoxide dismutase, malondialdehyde and catalase. Vascular endothelial growth factor and tight junction proteins (ZO-1 and Claudin-5) expressions were measured by Western blot for cell permeability evaluation. RESULTS: miR-122-5p had an increased expression in LPS-induced neutrophil exosomes and could promote oxidative stress, apoptosis and permeability increase of BMECs and the inhibition of BMECs proliferation and colony formation (P<0.05). miR-122-5p targeted the binding with OCLN and down-regulated OCLN expression. OCLN overexpression partly decreased the malignant effect of miR-122-5p on BMECs (P<0.05). CONCLUSION: LPS can induce neutrophils to secrete exosomes containing miR-122-5p. The down-regulation of OLCN expression can aggravate BMECs injury.

MicroRNA miR-126 attenuates brain injury in septic rats via NF-κB signaling pathway.

The purpose of this study was to investigate the impact and mechanism of microRNA miR-126 on brain injury induced by blood-brain barrier (BBB) damage in septic rats. We used cecal ligation and perforation (CLP) to create a rat model of sepsis. The experimental rats were randomly divided into Control group, CLP group, CLP + miR-NC group, CLP + miR-126 group and CLP + miR-126 + NF-κB pathway agonist (PMA) group. MiR-126 expressed in the brain tissue of CLP rats was down-regulated by qRT-PCR. Upregulation of miR-126 in CLP rats could improve brain injury and BBB marker protein level, reduce brain water content, Evans blue extravasation, inflammation, and excessive oxidative stress. This could also result in an inhibition of NF-κB signaling pathway activity. In conclusion, miR-126 overexpression can prevent brain injury caused by BBB damage via the inhibition of NF-κB signaling pathway activity.

WITHDRAWN: Analysis of Risk Factors for Prognosis and Infection of Child with Refractory Epilepsy Via Artificial Intelligence Neural Network Image Information.

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Diminished Anticipatory and Consummatory Pleasure in Dysphoria: Evidence From an Experience Sampling Study.

Anhedonia, the experience of diminished pleasure, is a core feature of major depressive disorder and is often present long before the diagnosis of depression. Most previous studies have investigated anhedonia with self-report measures of trait anhedonia or with behavioral paradigms using laboratory stimuli, and the real-time characteristics of hedonic processing in subclinical depression remain under-investigated. We used the experience sampling method to evaluate momentary experience of hedonic feelings in the context of daily life. Dysphoric (n = 49) and non-dysphoric (n = 51) college students completed assessments of their current positive affect (PA), as well as state anticipatory and consummatory pleasure, 3 or 4 times a day every day for 2 weeks. The results showed that dysphoric individuals reported less state anticipatory and consummatory pleasure compared with non-dysphoric individuals. Moreover, significant time-lagged associations between anticipatory pleasure and follow-up consummatory pleasure were found in the whole sample, after adjustment for current PA. The current findings thus hold considerable promise in advancing our understanding of anhedonia as well as the important role of state anticipatory pleasure in relation to depression.

Insect antiviral innate immunity: pathways, effectors, and connections.

Insects are infected by a wide array of viruses some of which are insect restricted and pathogenic, and some of which are transmitted by biting insects to vertebrates. The medical and economic importance of these viruses heightens the need to understand the interaction between the infecting pathogen and the insect immune system in order to develop transmission interventions. The interaction of the virus with the insect host innate immune system plays a critical role in the outcome of infection. The major mechanism of antiviral defense is the small, interfering RNA pathway that responds through the detection of virus-derived double-stranded RNA to suppress virus replication. However, other innate antimicrobial pathways such as Imd, Toll, and Jak-STAT and the autophagy pathway have also been shown to play important roles in antiviral immunity. In this review, we provide an overview of the current understanding of the main insect antiviral pathways and examine recent findings that further our understanding of the roles of these pathways in facilitating a systemic and specific response to infecting viruses.

An antiviral role for antimicrobial peptides during the arthropod response to alphavirus replication.

Alphaviruses establish a persistent infection in arthropod vectors which is essential for the effective transmission of the virus to vertebrate hosts. The development of persistence in insects is not well understood, although it is thought to involve the innate immune response. Using a transgenic fly system expressing a self-replicating viral RNA genome analog, we have previously demonstrated antiviral roles of the Drosophila Imd (immune deficiency) and Jak-STAT innate immunity pathways in response to alphavirus replication. In the present study, comparative microarray analysis of flies harboring an alphavirus replicon and control green fluorescent protein flies identified 95 SINrep-sensitive genes. Furthermore, a subset of these genes is regulated by Rel or STAT transcription factors of the Imd and Jak-STAT pathways, respectively. We identified two antimicrobial peptide genes, attC and dptB, which are SINrep sensitive and regulated by STAT and Rel, respectively. SINrep flies heterozygous for attC had an increased viral RNA level, while knocking down dptB in SINrep flies resulted in impaired development. When injected with whole virus, the double-stranded RNA knockdowns of either attC or dptB showed a significant increase in virus titers. Our data demonstrate an antiviral response involving the Imd and Jak-STAT mediated expression of dptB and attC.