Drosophila Activin signaling promotes muscle growth through InR/TORC1-dependent and -independent processes.

The Myostatin/Activin branch of the TGF-ß superfamily acts as a negative regulator of vertebrate skeletal muscle size, in part, through downregulation of insulin/insulin-like growth factor 1 (IGF-1) signaling. Surprisingly, recent studies in Drosophila indicate that motoneuron-derived Activin signaling acts as a positive regulator of muscle size. Here we demonstrate that Drosophila Activin signaling promotes the growth of muscle cells along all three axes: width, thickness and length. Activin signaling positively regulates the insulin receptor (InR)/TORC1 pathway and the level of Myosin heavy chain (Mhc), an essential sarcomeric protein, via increased Pdk1 and Akt1 expression. Enhancing InR/TORC1 signaling in the muscle of Activin pathway mutants restores Mhc levels close to those of the wild type, but only increases muscle width. In contrast, hyperactivation of the Activin pathway in muscles increases overall larval body and muscle fiber length, even when Mhc levels are lowered by suppression of TORC1. Together, these results indicate that the Drosophila Activin pathway regulates larval muscle geometry and body size via promoting InR/TORC1-dependent Mhc production and the differential assembly of sarcomeric components into either pre-existing or new sarcomeric units depending on the balance of InR/TORC1 and Activin signals.

Unmanned Surface Vehicle Thruster Fault Diagnosis via Vibration Signal Wavelet Transform and Vision Transformer under Varying Rotational Speed Conditions.

Among unmanned surface vehicle (USV) components, underwater thrusters are pivotal in their mission execution integrity. Yet, these thrusters directly interact with marine environments, making them perpetually susceptible to malfunctions. To diagnose thruster faults, a non-invasive and cost-effective vibration-based methodology that does not require altering existing systems is employed. However, the vibration data collected within the hull is influenced by propeller-fluid interactions, hull damping, and structural resonant frequencies, resulting in noise and unpredictability. Furthermore, to differentiate faults not only at fixed rotational speeds but also over the entire range of a thruster's rotational speeds, traditional frequency analysis based on the Fourier transform cannot be utilized. Hence, Continuous Wavelet Transform (CWT), known for attributions encapsulating physical characteristics in both time-frequency domain nuances, was applied to address these complications and transform vibration data into a scalogram. CWT results are diagnosed using a Vision Transformer (ViT) classifier known for its global context awareness in image processing. The effectiveness of this diagnosis approach was verified through experiments using a USV designed for field experiments. Seven cases with different fault types and severity were diagnosed and yielded average accuracy of 0.9855 and 0.9908 at different vibration points, respectively.

Forsythia velutina Nakai extract: A promising therapeutic option for atopic dermatitis through multiple cell type modulation.

BACKGROUND: Atopic dermatitis (AD) is a complex condition characterized by impaired epithelial barriers and dysregulated immune cells. In this study, we demonstrated Forsythia velutina Nakai extract (FVE) simultaneously inhibits basophils, macrophages, keratinocytes, and T cells that are closely interrelated in AD development. METHODS: We analyzed the effect of FVE on nitric oxide and reactive oxygen species (ROS) production in macrophages, basophil degranulation, T cell activation, and tight junctions in damaged keratinocytes. Expression of cell-type-specific inflammatory mediators was analyzed, and the underlying signaling pathways for anti-inflammatory effects of FVE were investigated. The anti-inflammatory effects of FVE were validated using a DNCB-induced mouse model of AD. Anti-inflammatory activity of compounds isolated from FVE was validated in each immune cell type. RESULTS: FVE downregulated the expression of inflammatory mediators and ROS production in macrophages through TLR4 and NRF2 pathways modulation. It significantly reduced basophil degranulation and expression of type 2 (T2) and pro-inflammatory cytokines by perturbing FcεRI signaling. Forsythia velutina Nakai extract also robustly inhibited the expression of T2 cytokines in activated T cells. Furthermore, FVE upregulated the expression of tight junction molecules in damaged keratinocytes and downregulated leukocyte attractants, as well as IL-33, an inducer of T2 inflammation. In the AD mouse model, FVE showed superior improvement in inflammatory cell infiltration and skin structure integrity compared to dexamethasone. Dimatairesinol, a lignan dimer, was identified as the most potent anti-inflammatory FVE compound. CONCLUSION: Forsythia velutina Nakai extract and its constituent compounds demonstrate promising efficacy as a therapeutic option for prolonged AD treatment by independently inhibiting various cell types associated with AD and disrupting the deleterious link between them.

Gut microbiota differences induced by Toxoplasma gondii seropositivity in stray cats in South Korea.

T. gondii is a highly prevalent parasite worldwide, with cats serving as its final host. However, few studies have investigated the impact of T. gondii infection on cat gut microbiota. Therefore, this study examined the influence of T. gondii infection on the gut microbiota of stray cats and identified potential pathogens in their feces. This study examined T. gondii infection through blood of stray cats and the influence of microbiota in their feces using 16S rRNA gene amplicon sequencing. The results revealed significant differences in gut microbiota composition and diversity between the T. gondii seropositive and seronegative groups. Seropositive samples displayed a lower number of operational taxonomic units and reduced Shannon index than the seronegative samples. The seropositive and seronegative groups exhibited enrichment of taxa, including Escherichia and Enterobacteriaceae and Collinsella, Bifidobacterium, and Roseburia, respectively. Furthermore, potential pathogen species, including Campylobacter, Escherichia, and Streptococcus, were identified in the fecal samples. These findings suggest that T. gondii infection significantly impacts gut microbiota composition and diversity in stray cats. Additionally, an increased potential pathogen load, represented by Escherichia spp., was observed. These results underscore the importance of monitoring the prevalence of zoonotic pathogens in stray cats, as they can serve as reservoirs for zoonotic diseases.

Dementia key gene identification with multi-layered SNP-gene-disease network.

MOTIVATION: Recently, various approaches for diagnosing and treating dementia have received significant attention, especially in identifying key genes that are crucial for dementia. If the mutations of such key genes could be tracked, it would be possible to predict the time of onset of dementia and significantly aid in developing drugs to treat dementia. However, gene finding involves tremendous cost, time and effort. To alleviate these problems, research on utilizing computational biology to decrease the search space of candidate genes is actively conducted.In this study, we propose a framework in which diseases, genes and single-nucleotide polymorphisms are represented by a layered network, and key genes are predicted by a machine learning algorithm. The algorithm utilizes a network-based semi-supervised learning model that can be applied to layered data structures. RESULTS: The proposed method was applied to a dataset extracted from public databases related to diseases and genes with data collected from 186 patients. A portion of key genes obtained using the proposed method was verified in silico through PubMed literature, and the remaining genes were left as possible candidate genes. AVAILABILITY AND IMPLEMENTATION: The code for the framework will be available at http://www.alphaminers.net/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Microbiome of Haemaphysalis longicornis Tick in Korea.

Ticks can transmit pathogenic bacteria, protozoa, and viruses to humans and animals. In this study, we investigated the microbiomes of Haemaphysalis longicornis according to sex and life stages. The Shannon index was significantly higher for nymphs than adult ticks. Principal coordinates analysis showed that the microbiome composition of female adult and male adult ticks were different. Notably, Coxiella-like bacterium (AB001519), known as a tick symbiont, was found in all nymphs and female adult ticks, but only one out of 4 male adult ticks had Coxiella-like bacterium (AB001519). In addition, Rickettsia rickettsii, Coxiella burnetii, and Anaplasma bovis were detected in this study.

Drug repurposing with network reinforcement.

BACKGROUND: Drug repurposing has been motivated to ameliorate low probability of success in drug discovery. For the recent decade, many in silico attempts have received primary attention as a first step to alleviate the high cost and longevity. Such study has taken benefits of abundance, variety, and easy accessibility of pharmaceutical and biomedical data. Utilizing the research friendly environment, in this study, we propose a network-based machine learning algorithm for drug repurposing. Particularly, we show a framework on how to construct a drug network, and how to strengthen the network by employing multiple/heterogeneous types of data. RESULTS: The proposed method consists of three steps. First, we construct a drug network from drug-target protein information. Then, the drug network is reinforced by utilizing drug-drug interaction knowledge on bioactivity and/or medication from literature databases. Through the enhancement, the number of connected nodes and the number of edges between them become more abundant and informative, which can lead to a higher probability of success of in silico drug repurposing. The enhanced network recommends candidate drugs for repurposing through drug scoring. The scoring process utilizes graph-based semi-supervised learning to determine the priority of recommendations. CONCLUSIONS: The drug network is reinforced in terms of the coverage and connections of drugs: the drug coverage increases from 4738 to 5442, and the drug-drug associations as well from 808,752 to 982,361. Along with the network enhancement, drug recommendation becomes more reliable: AUC of 0.89 was achieved lifted from 0.79. For typical cases, 11 recommended drugs were shown for vascular dementia: amantadine, conotoxin GV, tenocyclidine, cycloeucine, etc.

Titanium-oxide based nanoscale and embeddable subzero temperature sensor using MIT deformation characteristics.

In this research, we propose a nanoscale and embeddable subzero temperature sensor that is made with a temperature-dependent titanium-oxide based metal-insulator-transition (MIT) device. For a nanoscale two-terminal structured MIT device, the MIT device's characteristics are noticeably changed from abrupt to gradual MIT under zero temperature, which is called MIT deformation. On the basis of the MIT deformation characteristics, subzero temperatures can be detected by reading current levels as temperature changes. Furthermore, this sensor has desirable sensing properties such as high-linearity and proper sensitivity. The obtained results strongly show that titanium-oxides with CMOS process compatibility, cost-effectiveness, nontoxicity, etc, can be applied at the nanoscale and embeddable on subzero temperature sensors on a chip.

Microstructural engineering in interface-type synapse device for enhancing linear and symmetric conductance changes.

The origins of the nonlinear and asymmetric synaptic characteristics of TiO x -based synapse devices were investigated. Based on the origins, a microstructural electrode was utilized to improve the synaptic characteristics. Under an identical pulse bias, a TiO x -based synapse device exhibited saturated conductance changes, which led to nonlinear and asymmetric synaptic characteristics. The formation of an interfacial layer between the electrode and TiO x layer, which can limit consecutive oxygen migration and chemical reactions, was considered as the main origin of the conductance saturation behavior. To achieve consecutive oxygen migration and chemical reactions, structural engineering was utilized. The resultant microstructural electrode noticeably improved the synaptic characteristics, including the unsaturated, linear, and symmetric conductance changes. These synaptic characteristics resulted in the recognition accuracy significantly increasing from 38% to 90% in a neural network-based pattern recognition simulation.

An inference method from multi-layered structure of biomedical data.

BACKGROUND: Biological system is a multi-layered structure of omics with genome, epigenome, transcriptome, metabolome, proteome, etc., and can be further stretched to clinical/medical layers such as diseasome, drugs, and symptoms. One advantage of omics is that we can figure out an unknown component or its trait by inferring from known omics components. The component can be inferred by the ones in the same level of omics or the ones in different levels. METHODS: To implement the inference process, an algorithm that can be applied to the multi-layered complex system is required. In this study, we develop a semi-supervised learning algorithm that can be applied to the multi-layered complex system. In order to verify the validity of the inference, it was applied to the prediction problem of disease co-occurrence with a two-layered network composed of symptom-layer and disease-layer. RESULTS: The symptom-disease layered network obtained a fairly high value of AUC, 0.74, which is regarded as noticeable improvement when comparing 0.59 AUC of single-layered disease network. If further stretched to whole layered structure of omics, the proposed method is expected to produce more promising results. CONCLUSION: This research has novelty in that it is a new integrative algorithm that incorporates the vertical structure of omics data, on contrary to other existing methods that integrate the data in parallel fashion. The results can provide enhanced guideline for disease co-occurrence prediction, thereby serve as a valuable tool for inference process of multi-layered biological system.

The level of nitric oxide regulates lipocalin-2 expression under inflammatory condition in RINm5F beta-cells.

We previously reported that proinflammatory cytokines (interleukin-1ß and interferon-γ) induced the expression of lipocalin-2 (LCN-2) together with inducible nitric oxide synthase (iNOS) in RINm5F beta-cells. Therefore, we examined the effect of nitric oxide (NO) on LCN-2 expression in cytokines-treated RINm5F beta-cells. Additionally, we observed the effect of LCN-2 on cell viability. First, we found the existence of LCN-2 receptor and the internalization of exogenous recombinant LCN-2 peptide in RINm5F and INS-1 beta-cells. Next, the effects of NO on LCN-2 expression were evaluated. Aminoguanidine, an iNOS inhibitor and iNOS gene silencing significantly inhibited cytokines-induced LCN-2 expression while sodium nitroprusside (SNP), an NO donor potentiated it. Luciferase reporter assay showed that transcription factor NF-κB was not involved in LCN-2 expression. Both LCN-2 mRNA and protein stability assays were conducted. SNP did not affect LCN-2 mRNA stability, however, it significantly reduced LCN-2 protein degradation. The LCN-2 protein degradation was significantly attenuated by MG132, a proteasome inhibitor. Finally, the effect of LCN-2 on cell viability was evaluated. LCN-2 peptide treatment and LCN-2 overexpression significantly reduced cell viability. FACS analysis showed that LCN-2 induced the apoptosis of the cells. Collectively, NO level affects LCN-2 expression via regulation of LCN-2 protein stability under inflammatory condition and LCN-2 may reduce beta-cell viability by promoting apoptosis.

CLASH: Complementary Linkage with Anchoring and Scoring for Heterogeneous biomolecular and clinical data.

BACKGROUND: The study on disease-disease association has been increasingly viewed and analyzed as a network, in which the connections between diseases are configured using the source information on interactome maps of biomolecules such as genes, proteins, metabolites, etc. Although abundance in source information leads to tighter connections between diseases in the network, for a certain group of diseases, such as metabolic diseases, the connections do not occur much due to insufficient source information; a large proportion of their associated genes are still unknown. One way to circumvent the difficulties in the lack of source information is to integrate available external information by using one of up-to-date integration or fusion methods. However, if one wants a disease network placing huge emphasis on the original source of data but still utilizing external sources only to complement it, integration may not be pertinent. Interpretation on the integrated network would be ambiguous: meanings conferred on edges would be vague due to fused information. METHODS: In this study, we propose a network based algorithm that complements the original network by utilizing external information while preserving the network's originality. The proposed algorithm links the disconnected node to the disease network by using complementary information from external data source through four steps: anchoring, connecting, scoring, and stopping. RESULTS: When applied to the network of metabolic diseases that is sourced from protein-protein interaction data, the proposed algorithm recovered connections by 97%, and improved the AUC performance up to 0.71 (lifted from 0.55) by using the external information outsourced from text mining results on PubMed comorbidity literatures. Experimental results also show that the proposed algorithm is robust to noisy external information. CONCLUSION: This research has novelty in which the proposed algorithm preserves the network's originality, but at the same time, complements it by utilizing external information. Furthermore it can be utilized for original association recovery and novel association discovery for disease network.

GluN2B-containing N-methyl-D-aspartate receptors compensate for the inhibitory control of synaptic plasticity during the early critical period in the rat visual cortex.

In the visual cortex, synaptic plasticity is very high during the early developmental stage known as the critical period and declines with development after the critical period. Changes in the properties of N-methyl-D-aspartate receptor (NMDAR) and γ-aminobutyric acid type A receptor (GABAA R) have been suggested to underlie the changes in the characteristics of plasticity. However, it is largely unknown how the changes in the two receptors interact to regulate synaptic plasticity. The present study investigates the changes in the properties of NMDAR and GABAA R from 3 to 5 weeks of age in layer 2/3 pyramidal neurons of the rat visual cortex. The impact of these changes on the characteristics of long-term potentiation (LTP) is also investigated. The amplitude and decay time constant of GABAA R-mediated currents increased during this period. However, the decay time constant of NMDAR-mediated currents decreased as a result of the decrease in the proportion of the GluN2B subunit-mediated component. Induction of NMDAR-dependent LTP at 3 weeks depended on the GluN2B subunit, but LTP at 5 weeks did not. Enhancement of GABAA R-mediated inhibition suppressed the induction of LTP only at 5 weeks. However, partial inhibition of the GluN2B subunit with a low concentration of ifenprodil allowed the GABAA R-mediated suppression of LTP at 3 weeks. These results suggest that changes in the properties of NMDAR- and GABAA R-mediated synaptic transmission interact to determine the characteristics of synaptic plasticity during the critical period in the visual cortex.

Spatial charge separation in asymmetric structure of Au nanoparticle on TiO2 nanotube by light-induced surface potential imaging.

Both enhancing the excitons' lifetime and ingeniously controlling the spatial charge transfer are the key to the realization of efficiently photocatalytic and artificially photosynthetic devices. Nanostructured metal/metal-oxide interfaces often exhibit improved energy conversion efficiency. Understanding the surface potential changes of nano-objects under light illumination is crucial in photoelectrochemical cells. Under ultraviolet (UV) illumination, here, we directly observed the charge separation phenomena at the Au-nanoparticle/TiO2-nanotube interfaces by using Kelvin probe force microscopy. The surface potential maps of TiO2 nanotubes with and without Au nanoparticles were compared on the effect of different substrates. We observed that in a steady state, approximately 0.3 electron per Au particle of about 4 nm in diameter is effectively charged and consequently screens the surface potential of the underlying TiO2 nanotubes. Our observations should help design improved photoelectrochemical devices for energy conversion applications.

Chronic Alcohol Consumption Results in Greater Damage to the Pancreas Than to the Liver in the Rats.

Alcohol consumption increases the risk of type 2 diabetes. However, its effects on prediabetes or early diabetes have not been studied. We investigated endoplasmic reticulum (ER) stress in the pancreas and liver resulting from chronic alcohol consumption in the prediabetes and early stages of diabetes. We separated Otsuka Long-Evans Tokushima Fatty (OLETF) rats, a type-2 diabetic animal model, into two groups based on diabetic stage: prediabetes and early diabetes were defined as occurrence between the ages of 11 to 16 weeks and 17 to 22 weeks, respectively. The experimental group received an ethanol-containing liquid diet for 6 weeks. An intraperitoneal glucose tolerance test was conducted after 16 and 22 weeks for the prediabetic and early diabetes groups, respectively. There were no significant differences in body weight between the control and ethanol groups. Fasting and 120-min glucose levels were lower and higher, respectively, in the ethanol group than in the control group. In prediabetes rats, alcohol induced significant expression of ER stress markers in the pancreas; however, alcohol did not affect the liver. In early diabetes rats, alcohol significantly increased most ER stress-marker levels in both the pancreas and liver. These results indicate that chronic alcohol consumption increased the risk of diabetes in prediabetic and early diabetic OLETF rats; the pancreas was more susceptible to damage than was the liver in the early diabetic stages, and the adaptive and proapoptotic pathway of ER stress may play key roles in the development and progression of diabetes affected by chronic alcohol ingestion.

Effect of thorax correction exercises on flexed posture and chest function in older women with age-related hyperkyphosis.

[Purpose] The purpose of this study was to determine the effects of thorax correction exercises on flexed posture and chest function in older women with age-related hyperkyphosis. [Subjects and Methods] The study participants included 41 elderly women who were divided into a thorax correction exercise group (n = 20) and a control group (n = 21). Participants in the exercise group completed a specific exercise program that included breathing correction, thorax mobility, thorax stability, and thorax alignment training performed twice per week, 1 hour each session, for 8 weeks. Outcome measures included the flexed posture (thoracic kyphosis angle, forward head posture) and chest function (vital capacity, forced expiratory volume in a second, and chest expansion length). [Results] Participants in the thorax correction exercise group demonstrated significantly greater improvements in thoracic kyphosis angle, forward head, and chest expansion than those in the control group. [Conclusion] This study provides a promising exercise intervention that may improve flexed posture and chest function in older women with age-related hyperkyphosis.

ROS-mediated activation of Drosophila larval nociceptor neurons by UVC irradiation.

BACKGROUND: The complex Drosophila larval peripheral nervous system, capable of monitoring sensory input from the external environment, includes a family of multiple dendritic (md) neurons with extensive dendritic arbors tiling the inner surface of the larval body wall. The class IV multiple dendritic (mdIV) neurons are the most complex with dendritic nerve endings forming direct intimate contacts with epithelial cells of the larval body wall. Functioning as polymodal mechanonociceptors with the ability to respond to both noxious mechanical stimulation and noxious heat, the mdIV neurons are also activated by nanomolar levels of the endogenous reactive oxygen species (ROS), H2O2. Although often associated with tissue damage related to oxidative stress, endogenous ROS have also been shown to function as signaling molecules at lower concentrations. The overall role of ROS in sensory signaling is poorly understood but the acutely sensitive response of mdIV neurons to ROS-mediated activation is consistent with a routine role in the regulation of mdIV neuronal activity. Larvae respond to short wavelength ultraviolet (UVC) light with an immediate and visual system-independent writhing and twisting of the body previously described as a nociceptive response. Molecular and cellular mechanisms mediating this response and potential relationships with ROS generation are not well understood. We have used the UVC-induced writhing response as a model for investigation of the proposed link between endogenous ROS production and mdIV neuron function in the larval body wall. RESULTS: Transgenic inactivation of mdIV neurons caused a strong suppression of UVC-induced writhing behavior consistent with a key role for the mdIV neurons as mediators of the behavioral response. Direct imaging of ROS-activated fluorescence showed that UVC irradiation caused a significant increase in endogenous ROS levels in the larval body wall and transgenic overexpression of antioxidant enzymes strongly suppressed the UVC-induced writhing response. Direct electrophysiological recordings demonstrated that UVC irradiation also increased neuronal activity of the mdIV neurons. CONCLUSIONS: Results obtained using UVC irradiation to induce ROS generation provide evidence that UVC-induced writhing behavior is mediated by endogenous production of ROS capable of activating mdIV mechanonociceptors in the larval body wall.

Multiple isoforms of the Activin-like receptor baboon differentially regulate proliferation and conversion behaviors of neuroblasts and neuroepithelial cells in the Drosophila larval brain.

In Drosophila coordinated proliferation of two neural stem cells, neuroblasts (NB) and neuroepithelial (NE) cells, is pivotal for proper larval brain growth that ultimately determines the final size and performance of an adult brain. The larval brain growth displays two phases based on behaviors of NB and NEs: the first one in early larval stages, influenced by nutritional status and the second one in the last larval stage, promoted by ecdysone signaling after critical weight checkpoint. Mutations of the baboon (babo) gene that produces three isoforms (BaboA-C), all acting as type-I receptors of Activin-type transforming growth factor ß (TGF-ß) signaling, cause a small brain phenotype due to severely reduced proliferation of the neural stem cells. In this study we show that loss of babo function severely affects proliferation of NBs and NEs as well as conversion of NEs from both phases. By analyzing babo-null and newly generated isoform-specific mutants by CRISPR mutagenesis as well as isoform-specific RNAi knockdowns in a cell- and stage-specific manner, our data support differential contributions of the isoforms for these cellular events with BaboA playing the major role. Stage-specific expression of EcR-B1 in the brain is also regulated primarily by BaboA along with function of the other isoforms. Blocking EcR function in both neural stem cells results in a small brain phenotype that is more severe than baboA-knockdown alone. In summary, our study proposes that the Babo-mediated signaling promotes proper behaviors of the neural stem cells in both phases and achieves this by acting upstream of EcR-B1 expression in the second phase.

Microbiome of lovebug (Plecia longiforceps) in Seoul, South Korea.

Lovebugs appeared in large numbers across a wide area in Seoul, South Korea, in June 2023. The sudden appearance of exotic insects not only discomforts people but also fosters anxiety, as their potential for pathogen transmission would be unknown. In this study, targeted next-generation sequencing (NGS) of the 16S rRNA gene V4 region was performed using iSeq 100 to screen for bacteria in lovebugs. Forty-one lovebugs (20 females and 21 males) collected in Seoul, Korea, were identified as Plecia longiforceps based on mitochondrial cytochrome oxidase subunit 1 sequencing data using PCR. We analyzed the microbiome of the lovebugs and detected 453 species of bacteria. Among all bacteria screened based on NGS, Rickettsia was detected in all samples with an average relative abundance of 80.40%, followed by Pandoraea and Ewingella. Diversity (alpha and beta) between females and males did not differ; however, only Tumebacillus showed a higher relative abundance in females. Sequencing analysis of Rickettsia using a gltA gene-specific primer by PCR showed that it had higher sequence similarity to the Rickettsia symbiont of arthropods than to the spotted fever group rickettsiae. Eleven samples in which Pandoraea was detected by iSeq 100 were confirmed by PCR and exhibited 100% sequence identity to Pandoraea oxalativorans strain DSM 23570. Consequently, the likelihood of pathogen transmission to humans is low. The applied method may play a crucial role in swiftly identifying bacterial species in the event of future outbreaks of exotic insects that may be harmful to humans.IMPORTANCELovebugs have recently emerged in large numbers in Seoul, causing major concern regarding potential health risks. By performing the next-generation sequencing of the 16S rRNA gene V4 region, we comprehensively examined the microbiome of these insects. We identified the presence of numerous bacteria, including Rickettsia and Pandoraea. Reassuringly, subsequent tests confirmed that these detected bacteria were not pathogenic. The present study addresses health concerns related to lovebugs and shows the accuracy and efficiency of our detection technique. Such methods prove invaluable for rapidly identifying bacterial species during potential outbreaks of unfamiliar insects, thereby ensuring public safety.

Metabarcoding of pathogenic parasites based on copro-DNA analysis of wild animals in South Korea.

Four species of dominant wild animals, namely, Prionailurus bengalensis euptilurus, Nyctereutes procyonoides koreensis, Hydropotes inermis argyropus, and Sus scrofa coreanus, are hosts of potential infectious agents, including helminths and protozoa. Therefore, it is necessary to analyze the infectious agents present in these wild animals to monitor and control the spread of pathogens. In the present study, fecal samples from 51 wild animals were collected from the mountains of Yangpyeong, Hoengseong, and Cheongyang in South Korea and metabarcoding of the V9 region of the 18S rRNA gene was performed to identify various parasite species that infect these wild animals. Genes from nematodes, such as Metastrongylus sp., Strongyloides spp., Ancylostoma sp., and Toxocara sp., were detected in the fecal samples from wild animals. In addition, platyhelminthes, including Spirometra sp., Echinostomatidae gen. sp., Alaria sp., Neodiplostomum sp., and Clonorchis sp., and protozoa, including Entamoeba sp., Blastocystis sp., Isospora sp., Tritrichomonas sp., Pentatrichomonas sp., and Cryptosporidium sp., were detected. In the present study, various parasites infecting wild animals were successfully identified using metabarcoding. Our technique may play a crucial role in monitoring parasites within wild animals, especially those causing zoonoses.