Efficacy of cardiopulmonary rehabilitation nursing in enhancing pulmonary function, sleep quality, and living ability in COVID-19 patients.

OBJECTIVE: The purpose of this study was to elucidate the impact of cardiopulmonary rehabilitation nursing on the pulmonary function, sleep quality, and living ability of patients afflicted with Coronavirus Disease 2019 (COVID-19). METHODS: A total of 98 patients with COVID-19 treated at The People's Hospital of Guang'an between September 2021 and January 2023 were retrospectively collected as the research subjects. Among them, 48 patients who received standard nursing care from September 2021 to September 2022 were set as the control group, and 50 patients who underwent cardiopulmonary rehabilitation nursing from October 2022 to January 2023 were set as the research group. The pulmonary function indicators [including Forced Expiratory Volume in 1 second (FEV1) and Left Ventricular Ejection Fraction (LVEF)], sleep quality [evaluated using the Pittsburgh Sleep Quality Index (PSQI)], and living ability [assessed by the 36-Item Short Form Survey (SF-36) scale] pre- and post-intervention were compared between the two groups. RESULTS: Pre-intervention, FEV1, LVEF, PSQI scores, inflammatory factor levels [C-reactive protein (CRP), procalcitonin (PCT)], and SF-36 scores showed no significant differences between the two groups (P>0.05). Post-intervention, the research group exhibited notably enhanced FEV1 and LVEF, lower PSQI scores, lower CRP and PCT, and higher SF-36 scores compared with the control group, with statistical significance (P<0.05). Multifactorial logistic regression analysis showed that non-receipt of cardiopulmonary rehabilitation, age ≥60 years, concurrent respiratory failure, coexistent heart failure, and acid-base imbalance were independent risk factors of adverse outcomes in COVID-19 patients (P<0.05). CONCLUSION: Application of cardiopulmonary rehabilitation nursing in COVID-19 patients can significantly improve pulmonary function, sleep quality, and overall quality of life, and relieve the inflammatory state of the patients, thereby enhancing prognosis. This approach has certain value of popularization and application.

Phylogenomic data exploration with increased sampling provides new insights into the higher-level relationships of butterflies and moths (Lepidoptera).

A robust and stable phylogenetic framework is a fundamental goal of evolutionary biology. As the third largest insect order in the world following Coleoptera and Diptera, Lepidoptera (butterflies and moths) play a central role in almost every terrestrial ecosystem as indicators of environmental change and serve as important models for biologists exploring questions related to ecology and evolutionary biology. However, for such a charismatic insect group, the higher-level phylogenetic relationships among its superfamilies are still poorly resolved. Compared to earlier phylogenomic studies, we increased taxon sampling among Lepidoptera (37 superfamilies and 68 families containing 263 taxa) and acquired a series of large amino-acid datasets from 69,680 to 400,330 for phylogenomic reconstructions. Using these datasets, we explored the effect of different taxon sampling with significant increases in the number of included genes on tree topology by considering a series of systematic errors using maximum-likelihood (ML) and Bayesian inference (BI) methods. Moreover, we also tested the effectiveness in topology robustness among the three ML-based models. The results showed that taxon sampling is an important determinant in tree robustness of accurate lepidopteran phylogenetic estimation. Long-branch attraction (LBA) caused by site-wise heterogeneity is a significant source of bias giving rise to unstable positions of ditrysian groups in phylogenomic reconstruction. Phylogenetic inference showed the most comprehensive framework to reveal the relationships among lepidopteran superfamilies, and presented some newly relationships with strong supports (Papilionoidea was sister to Gelechioidea and Immoidea was sister to Galacticoidea, respectively), but limited by taxon sampling, the relationships within the species-rich and relatively rapid radiation Ditrysia and especially Apoditrysia remain poorly resolved, which need to increase taxon sampling for further phylogenomic reconstruction. The present study demonstrates that taxon sampling is an important determinant for an accurate lepidopteran tree of life and provides some essential insights for future lepidopteran phylogenomic studies.

Computer aided diagnosis of diabetic retinopathy based on multi-view joint learning.

Diabetic retinopathy (DR) is a kind of ocular complication of diabetes, and its degree grade is an essential basis for early diagnosis of patients. Manual diagnosis is a long and expensive process with a specific risk of misdiagnosis. Computer-aided diagnosis can provide more accurate and practical treatment recommendations. In this paper, we propose a multi-view joint learning DR diagnostic model called RT2Net, which integrates the global features of fundus images and the local detailed features of vascular images to reduce the limitations of single fundus image learning. Firstly, the original image is preprocessed using operations such as contrast-limited adaptive histogram equalization, and the vascular structure of the extracted DR image is segmented. Then, the vascular image and fundus image are input into two branch networks of RT2Net for feature extraction, respectively, and the feature fusion module adaptively fuses the feature vectors' output from the branch networks. Finally, the optimized classification model is used to identify the five categories of DR. This paper conducts extensive experiments on the public datasets EyePACS and APTOS 2019 to demonstrate the method's effectiveness. The accuracy of RT2Net on the two datasets reaches 88.2% and 85.4%, and the area under the receiver operating characteristic curve (AUC) is 0.98 and 0.96, respectively. The excellent classification ability of RT2Net for DR can significantly help patients detect and treat lesions early and provide doctors with a more reliable diagnosis basis, which has significant clinical value for diagnosing DR.

Deepm6A-MT: A deep learning-based method for identifying RNA N6-methyladenosine sites in multiple tissues.

N6-methyladenosine (m6A) is the most prevalent, abundant, and conserved internal modification in the eukaryotic messenger RNA (mRNAs) and plays a crucial role in the cellular process. Although more than ten methods were developed for m6A detection over the past decades, there were rooms left to improve the predictive accuracy and the efficiency. In this paper, we proposed an improved method for predicting m6A modification sites, which was based on bi-directional gated recurrent unit (Bi-GRU) and convolutional neural networks (CNN), called Deepm6A-MT. The Deepm6A-MT has two input channels. One is to use an embedding layer followed by the Bi-GRU and then by the CNN, and another is to use one-hot encoding, dinucleotide one-hot encoding, and nucleotide chemical property codes. We trained and evaluated the Deepm6A-MT both by the 5-fold cross-validation and the independent test. The empirical tests showed that the Deepm6A-MT achieved the state of the art performance. In addition, we also conducted the cross-species and the cross-tissues tests to further verify the Deepm6A-MT for effectiveness and efficiency. Finally, for the convenience of academic research, we deployed the Deepm6A-MT to the web server, which is accessed at the URL http://www.biolscience.cn/Deepm6A-MT/.

Flexible changes to the Heliothis virescens ascovirus 3h (HvAV-3h) virion components affect pathogenicity against different host larvae species.

IMPORTANCE: Different pathogenic processes of a virus in different hosts are related to the host individual differences, which makes the virus undergoes different survival pressures. Here, we found that the virions of an insect virus, Heliothis virescens ascovirus 3h (HvAV-3h), had different protein composition when they were purified from different host larval species. These "adaptive changes" of the virions were analyzed in detail in this study, which mainly included the differences of the protein composition of virions and the differences in affinity between virions and different host proteins. The results of this study revealed the flexible changes of viruses to help themselves adapt to different hosts. Also, these interesting findings can provide new insights to improve our understanding of virus adaptability and virulence differentiation caused by the adaptation process.

6mA-StackingCV: an improved stacking ensemble model for predicting DNA N6-methyladenine site.

DNA N6-adenine methylation (N6-methyladenine, 6mA) plays a key regulating role in the cellular processes. Precisely recognizing 6mA sites is of importance to further explore its biological functions. Although there are many developed computational methods for 6mA site prediction over the past decades, there is a large root left to improve. We presented a cross validation-based stacking ensemble model for 6mA site prediction, called 6mA-StackingCV. The 6mA-StackingCV is a type of meta-learning algorithm, which uses output of cross validation as input to the final classifier. The 6mA-StackingCV reached the state of the art performances in the Rosaceae independent test. Extensive tests demonstrated the stability and the flexibility of the 6mA-StackingCV. We implemented the 6mA-StackingCV as a user-friendly web application, which allows one to restrictively choose representations or learning algorithms. This application is freely available at http://www.biolscience.cn/6mA-stackingCV/ . The source code and experimental data is available at https://github.com/Xiaohong-source/6mA-stackingCV .

DeepHLAPred: a deep learning-based method for non-classical HLA binder prediction.

Human leukocyte antigen (HLA) is closely involved in regulating the human immune system. Despite great advance in detecting classical HLA Class I binders, there are few methods or toolkits for recognizing non-classical HLA Class I binders. To fill in this gap, we have developed a deep learning-based tool called DeepHLAPred. The DeepHLAPred used electron-ion interaction pseudo potential, integer numerical mapping and accumulated amino acid frequency as initial representation of non-classical HLA binder sequence. The deep learning module was used to further refine high-level representations. The deep learning module comprised two parallel convolutional neural networks, each followed by maximum pooling layer, dropout layer, and bi-directional long short-term memory network. The experimental results showed that the DeepHLAPred reached the state-of-the-art performanceson the cross-validation test and the independent test. The extensive test demonstrated the rationality of the DeepHLAPred. We further analyzed sequence pattern of non-classical HLA class I binders by information entropy. The information entropy of non-classical HLA binder sequence implied sequence pattern to a certain extent. In addition, we have developed a user-friendly webserver for convenient use, which is available at http://www.biolscience.cn/DeepHLApred/ . The tool and the analysis is helpful to detect non-classical HLA Class I binder. The source code and data is available at https://github.com/tangxingyu0/DeepHLApred .

Research progress on iron absorption, transport, and molecular regulation strategy in plants.

Iron is a trace element essential for normal plant life activities and is involved in various metabolic pathways such as chlorophyll synthesis, photosynthesis, and respiration. Although iron is highly abundant in the earth's crust, the amount that can be absorbed and utilized by plants is very low. Therefore, plants have developed a series of systems for absorption, transport, and utilization in the course of long-term evolution. This review focuses on the findings of current studies of the Fe2+ absorption mechanism I, Fe3+ chelate absorption mechanism II and plant-microbial interaction iron absorption mechanism, particularly effective measures for artificially regulating plant iron absorption and transportation to promote plant growth and development. According to the available literature, the beneficial effects of using microbial fertilizers as iron fertilizers are promising but further evidence of the interaction mechanism between microorganisms and plants is required.

High Intensity Focused Ultrasound Ablation for Juvenile Cystic Adenomyosis: Two Case Reports and Literature Review.

Cystic adenomyosis is a rare type of uterine adenomyosis, mainly seen in young women, which is often characterized by severe dysmenorrhea. The quality of life and reproductive function of young women could be affected by misdiagnosis and delayed treatment. At present, there are no universal guidelines and consensus. We report two cases of patients with cystic adenomyosis in juveniles treated with high-intensity focused ultrasound (HIFU) ablation. In the first case, magnetic resonance imaging (MRI) indicated a cystic mass of 2.0 cm × 3.1 cm × 2.4 cm in the uterus. After she underwent HIFU treatment, her pelvic MRI showed a mass of 1.1 × 2.4 cm in size, and her dysmenorrhea symptoms gradually disappeared. In the second case, a pelvic MRI indicated a 5.1 cm × 3.3 cm × 4.7 cm cystic mass in the uterus. After she underwent HIFU and combined four consecutive cycles of GnRH-a treatment, the lesion shrunk 1.2 cm ×1.4 cm × 1.6 cm, without dysmenorrhea. Simultaneously, the report reviewed 14 cases of juvenile cystic adenomyosis over the last ten years. HIFU or HIFU-combined drugs were safe and effective in treating juvenile cystic adenomyosis, but multicenter and prospective studies may be necessary to validate this in the future.

A new record family Neopseustidae (Insecta: Lepidoptera) from Chongqing of China, with the first description of the Neopseustis archiphenax female adult.

In 2022, the insect inventories organized by Prof. Zhi-Sheng Zhang of Southwest University were constructed in Yintiaoling Nature Reserve, Chongqing Municipality, China. The neopseustid moth from Chongqing based on three specimens of Neopseustis archiphenax by light trapping were reported in this paper. The photos of the male and female adults, genitalia, and abdominal special structures are presented with the female described firstly. Also, the DNA barcoding sequence data is provided, and the key to the Neopseustis species is given.

Enhanced virulence of genetically engineered Autographa californica nucleopolyhedrovirus owing to accelerated viral DNA replication aided by inserted ascovirus genes.

Genetic engineering technology is an ideal method to improve insecticidal efficiency by combining the advantages of different pathogenic microorganisms. Thus, six ascovirus genes were introduced into the genomic DNA of Autographa californica nucleopolyhedrovirus (AcMNPV) to possibly transfer the intrinsically valuable insecticidal properties from ascovirus to baculovirus. The viral budded virus (BV) production and viral DNA replication ability of AcMNPV-111 and AcMNPV-165 were significantly stronger than that of AcMNPV-Egfp (used as the wild-type virus in this study), whereas AcMNPV-33 had reduced ones. AcMNPV-111 and AcMNPV-165 also exhibited excellent insecticidal efficiency in the in vivo bioassays: AcMNPV-111 showed a 24.1% decrease in the LT50 value and AcMNPV-165 exhibited a 56.3% decrease in the LD50 value compared with AcMNPV-Egfp against the 3rd instar of Spodoptera exigua larvae, respectively. Furthermore, the size of the occlusion bodies (OBs) of AcMNPV-33, AcMNPV-111, and AcMNPV-165 were significantly increased compared to that of AcMNPV-Egfp. AcMNPV-111 and AcMNPV-165 had stable virulence against the 2nd to 4th instars tested larvae and higher OB yield than AcMNPV-Egfp in the 3rd and 4th instar larvae. Correlation and regression analyses indicated that it is better to use 5 OBs/larva virus to infect the 2nd instar larvae to produce AcMNPV-111 and 50 OBs/larva virus to infect the 3rd instar larvae to produce AcMNPV-165. The results of this study obtained recombinant viruses with enhanced virulence and exhibited a diversity of ascovirus gene function based on the baculovirus platform, which provided a novel strategy for the improvement of baculovirus as a biological insecticide.

Comparison of high-intensity focused ultrasound and microwave ablation for the treatment of small liver metastatic tumors.

OBJECTIVE: To evaluate the feasibility, safety, and efficacy of high-intensity focused ultrasound (HIFU) and microwave ablation (MWA) for the treatment of small liver metastatic tumors. METHODS: Fifty-eight patients with small liver metastatic tumors who underwent HIFU (n = 28) or MWA (n = 30) at Suining Central Hospital between January 2016 and December 2021 were retrospectively evaluated. Demographic and clinical characteristics were compared between the two groups. RESULTS: Operation times were longer and hospitalization costs were lower in the HIFU group than in the MWA group. Postoperative hospitalization times, tumor ablation rates, and clinical response and control rates did not differ significantly between the two groups 1 month after surgery. Rates of postoperative complications such as fever, liver dysfunction, injury, pain, and biliary leakage did not differ between the two groups. The 1- and 3-year cumulative survival rates were 96.4% and 52.4%, respectively, after HIFU and 93.3% and 51.4%, respectively, after MWA, which did not represent significant differences. CONCLUSIONS: HIFU is a safe and feasible method of treating small liver metastatic tumors. Compared with MWA, HIFU was associated with lower hospitalization costs, reduced trauma, and fewer postoperative complications, making it a promising new local ablative treatment option for liver metastatic tumors.

DeepLBCEPred: A Bi-LSTM and multi-scale CNN-based deep learning method for predicting linear B-cell epitopes.

The epitope is the site where antigens and antibodies interact and is vital to understanding the immune system. Experimental identification of linear B-cell epitopes (BCEs) is expensive, is labor-consuming, and has a low throughput. Although a few computational methods have been proposed to address this challenge, there is still a long way to go for practical applications. We proposed a deep learning method called DeepLBCEPred for predicting linear BCEs, which consists of bi-directional long short-term memory (Bi-LSTM), feed-forward attention, and multi-scale convolutional neural networks (CNNs). We extensively tested the performance of DeepLBCEPred through cross-validation and independent tests on training and two testing datasets. The empirical results showed that the DeepLBCEPred obtained state-of-the-art performance. We also investigated the contribution of different deep learning elements to recognize linear BCEs. In addition, we have developed a user-friendly web application for linear BCEs prediction, which is freely available for all scientific researchers at: http://www.biolscience.cn/DeepLBCEPred/.

Efficacy of Kegel exercises combined with electrical stimulation on the restoration of postpartum pelvic floor muscle function.

OBJECTIVE: To investigate the efficacy of Kegel exercises combined with electrical stimulation on the restoration of postpartum pelvic floor muscle (PFM) function. METHODS: Data of 120 parturients with full-term singleton pregnancy who delivered vaginally in the Guang'an People's Hospital were retrospectively analyzed, and the study subjects were grouped into a Kegel exercise group (n=40, receiving Kegel exercise alone), an electrical stimulation group (n=40, receiving electrical stimulation alone) and a combined group (n=40, receiving Kegel exercises combined with electrical stimulation) according to the treatments received. All three groups received intervention for 3 months. The overall response rates (ORRs) at 3 months, changes in PFM strength and vaginal pressure during treatment, the scores of International Consultation on Incontinence Questionnaire-Urinary Incontinence Short Form (ICIQ-UI SF), the incontinence quality of life questionnaire (I-QOL), and the incidence rates of pelvic floor dysfunction (PFD) were evaluated in the three groups. RESULTS: ORR in the combined group (100.00%) was higher than that of the Kegel exercises group (87.50%) and the electrical stimulation group (85.00%) (P < 0.05). At 1, 3, and 6 months after intervention, the combined group was superior to the Kegel exercises and the electrical stimulation groups in systolic blood pressure (SBP) of pelvic floor, and the continuous SBP of type I and II muscle fibers (P < 0.05). After 6 months of follow-up, the scores of ICIQ-UI SF and I-QOL in the combined group were higher than those in the Kegel exercises and electrical stimulation groups (P < 0.05). The score of satisfaction in the combined group was higher than in Kegel exercises and electrical stimulation groups (P < 0.05). CONCLUSION: Kegel exercises combined with electrical stimulation have a good therapeutic effect on postpartum pelvic floor dysfunction, which can markedly improve PFM strength and vaginal pressure.

Apoptosis or Antiapoptosis? Interrupted Regulated Cell Death of Host Cells by Ascovirus Infection In Vitro.

Ascoviruses are insect-specific viruses thought to utilize the cellular apoptotic processes of host larvae to produce numerous virion-containing vesicles. In this study, we first determined the biochemical characteristics of ascovirus-infected, in vitro-cultured insect cells and the possible antiapoptotic capacity of ascovirus-infected insect cells. The results indicated that the ascovirus infection in the first 24 h was different from the infection from 48 h to the later infection stages. In the early infection stage, the Spodoptera exigua host cells had high membrane permeability and cleaved gasdermin D (GSDMD) but uncleaved Casp-6 (SeCasp-6). In contrast, the later infection stage had no such increased membrane permeability and had cleaved SeCasp-6. Four different chemicals were used to induce apoptosis at different stages of ascovirus infection: hydrogen peroxide (H2O2) and actinomycin D (ActD) had similar effects on the ascovirus-infected cells, whereas cMYC inhibitors and tumor necrosis factor alpha (TNF-α) plus SM-164 apoptosis inducers (T/S) had similar effects on infected cells. The former two inducers inhibited viral DNA replication in most situations, while the latter two inducers inhibited viral DNA replication in the early stage of infection but promoted viral DNA replication in the later infection stage. Furthermore, immunoblotting assays verified that T/S treatment could increase the expression levels of viral major capsid protein (MCP) and the host inhibitor of apoptosis protein (SeIAP). Coimmunoprecipitation assays revealed interaction between SeIAP and SeCasps, but this interaction was disturbed in ascovirus-infected cells. This study details the in vitro infection process of ascovirus, indicating the utilization of pyroptosis for antiapoptosis cytopathology. IMPORTANCE Clarifying the relationship between different types of viral infections and host regulation of cell death (RCD) can provide insights into the interaction between viruses and host cells. Ascoviruses are insect-specific viruses with apoptosis-utilizing-like infection cytopathology. However, RCD does not only include apoptosis, and while in our previous transmission electron microscopic observations, ascovirus-infected cells did not show typical apoptotic characteristics (unpublished data), in this study, they did show increased membrane permeability. These results indicate that the cytopathology of ascovirus infection is a complex process in which the virus manipulates host RCD. The RCD of insect cells is quite different from that of mammals, and studies on the former are many fewer than those on the latter, especially in the case of RCD in lepidopteran insects. Our results will lay a foundation for understanding the RCD of lepidopteran insects and its function in the process of insect virus infection.

An Efficient Feature Selection Algorithm for Gene Families Using NMF and ReliefF.

Gene families, which are parts of a genome's information storage hierarchy, play a significant role in the development and diversity of multicellular organisms. Several studies have focused on the characteristics of gene families, such as function, homology, or phenotype. However, statistical and correlation analyses on the distribution of gene family members in the genome have yet to be conducted. Here, a novel framework incorporating gene family analysis and genome selection based on NMF-ReliefF is reported. Specifically, the proposed method starts by obtaining gene families from the TreeFam database and determining the number of gene families within the feature matrix. Then, NMF-ReliefF is used to select features from the gene feature matrix, which is a new feature selection algorithm that overcomes the inefficiencies of traditional methods. Finally, a support vector machine is utilized to classify the acquired features. The results show that the framework achieved an accuracy of 89.1% and an AUC of 0.919 on the insect genome test set. We also employed four microarray gene data sets to evaluate the performance of the NMF-ReliefF algorithm. The outcomes show that the proposed method may strike a delicate balance between robustness and discrimination. Additionally, the proposed method's categorization is superior to state-of-the-art feature selection approaches.

MultiScale-CNN-4mCPred: a multi-scale CNN and adaptive embedding-based method for mouse genome DNA N4-methylcytosine prediction.

N4-methylcytosine (4mC) is an important epigenetic mechanism, which regulates many cellular processes such as cell differentiation and gene expression. The knowledge about the 4mC sites is a key foundation to exploring its roles. Due to the limitation of techniques, precise detection of 4mC is still a challenging task. In this paper, we presented a multi-scale convolution neural network (CNN) and adaptive embedding-based computational method for predicting 4mC sites in mouse genome, which was referred to as MultiScale-CNN-4mCPred. The MultiScale-CNN-4mCPred used adaptive embedding to encode nucleotides, and then utilized multi-scale CNNs as well as long short-term memory to extract more in-depth local properties and contextual semantics in the sequences. The MultiScale-CNN-4mCPred is an end-to-end learning method, which requires no sophisticated feature design. The MultiScale-CNN-4mCPred reached an accuracy of 81.66% in the 10-fold cross-validation, and an accuracy of 84.69% in the independent test, outperforming state-of-the-art methods. We implemented the proposed method into a user-friendly web application which is freely available at: http://www.biolscience.cn/MultiScale-CNN-4mCPred/ .

LangMoDHS: A deep learning language model for predicting DNase I hypersensitive sites in mouse genome.

DNase I hypersensitive sites (DHSs) are a specific genomic region, which is critical to detect or understand cis-regulatory elements. Although there are many methods developed to detect DHSs, there is a big gap in practice. We presented a deep learning-based language model for predicting DHSs, named LangMoDHS. The LangMoDHS mainly comprised the convolutional neural network (CNN), the bi-directional long short-term memory (Bi-LSTM) and the feed-forward attention. The CNN and the Bi-LSTM were stacked in a parallel manner, which was helpful to accumulate multiple-view representations from primary DNA sequences. We conducted 5-fold cross-validations and independent tests over 14 tissues and 4 developmental stages. The empirical experiments showed that the LangMoDHS is competitive with or slightly better than the iDHS-Deep, which is the latest method for predicting DHSs. The empirical experiments also implied substantial contribution of the CNN, Bi-LSTM, and attention to DHSs prediction. We implemented the LangMoDHS as a user-friendly web server which is accessible at http:/www.biolscience.cn/LangMoDHS/. We used indices related to information entropy to explore the sequence motif of DHSs. The analysis provided a certain insight into the DHSs.

An Ascovirus Utilizes Different Types of Host Larval Regulated Cell Death Mechanisms To Produce and Release Vesicles.

Ascoviruses are insect-specific viruses that are thought to utilize the cellular apoptotic processes of host larvae to produce numerous virion-containing vesicles. In this study, we monitored the in vivo infection processes of Heliothis virescens ascovirus 3h (HvAV-3h) to illustrate the regulated cell death (RCD) of host cells. Transmission electron microscopic observations did not reveal any morphological markers of apoptosis in the fat bodies or hemocytes of HvAV-3h-infected Helicoverpa armigera or Spodoptera exigua larvae. However, several hemocytes showed the morphological criteria for necrosis and/or pyroptosis. Further in vitro biochemical tests were performed to confirm the RCD type of host cells after infection with HvAV-3h. Different morphological characteristics were found between the early (prior to 24 hours post-infection, [hpi]) and later (48 to 120 hpi) stages in both HvAV-3h infected larval fat bodies and hemocytes. In the early stages, the virions could only be found in several adipohemocytes, and the fat bodies were cleaving their contained lipid inclusions into small lipid dots. In the later stage, both fat bodies and hemocytes were filled with numerous virions. According to the morphological characteristics of HvAV-3h infected larval fat bodies or hemocytes, the pathogenic characteristics and infection patterns of HvAV-3h in the host larvae were described, and the systematic pathogenic mode of ascovirus infection was refined in this study. This study details the complete infection process of ascoviruses, which provides insights into the relationship between a pathogenesis of an insect virus and the RCD of different host tissues at different stages of infection. IMPORTANCE Viruses and other pathogens can interrupt host cellular apoptosis to gain benefits, such as sufficient resources and a stable environment that enables them to complete their replication and assembly. It is unusual for viruses to code proteins with homology to caspases, which are commonly recognized as apoptosis regulators. Ascoviruses are insect viruses with special cytopathology, and they have been hypothesized to induce apoptosis in their host larvae via coding a caspase-like protein. This enables them to utilize the process of cellular apoptosis to facilitate vesicle formation and replication. However, our previous studies revealed different trends. The fat bodies and hemocytes of Heliothis virescens ascovirus 3h (HvAV-3h)-infected larvae did not show any morphological markers of apoptosis but did display necrosis and/or pyroptosis morphological characteristics. The pathogenic characteristics and infection patterns of HvAV-3h in the host larvae were described, which can help us understand the relationship between the pathogenesis of an insect virus and host RCD.

Insight into the regulation of the Nrf2 pathway in response to ascovirus infection in Spodoptera exigua.

BACKGROUND: Ascoviruses are a type of entomopathogenic microorganism with high biological pest control potential and are expected to contribute to the natural control of lepidopteran pests. However, knowledge of the molecular mechanism underlying the biocidal activity of ascovirus on its host insects remains limited. RESULTS: In this study, the relative enzyme activity of superoxide dismutase and peroxidase, as well as the expression level of Spodoptera exigua peroxidase (SePOD), were found to be significantly increased at 6 h post infection with Heliothis virescens ascovirus 3h (HvAV-3h). H2 O2 accumulation and enhanced expression of NADPH Oxidase (SeNOX) were also observed. In addition, Nuclear Factor erythroid 2-Related Factor 2 (SeNrf2) and muscle aponeurosis fibromatosis (SeMaf) were overexpressed following infection with HvAV-3h. Silencing of SeNrf2 decreased the expression of SePOD, whereas the mortality of SeNrf2-silenced larvae and viral genome copy number also increased. Further RNA interference of SeNOX significantly decreased expression of SeNrf2 and SePOD and therefore increased the mortality and viral genome copy number of the ascovirus-infected host. CONCLUSION: The HvAV-3h activated Nrf2/ARE pathway of S. exigua and reactive oxygen species were found to respond to ascovirus infection by regulating alterations in antioxidant enzyme genes mediated by the host Nrf2/ARE pathway. These findings enhance our knowledge of ascovirus-host interactions and lay the foundation for the application of ascoviruses in biological pest control. © 2022 Society of Chemical Industry.