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.

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.

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.

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.