Comparative genomic analyses reveal evidence for adaptive A-to-I RNA editing in insect Adar gene

Although A-to-I RNA editing leads to similar effects to A-to-G DNA mutation, nonsynonymous RNA editing (recoding) is believed to confer its adaptiveness by 'epigenetically' regulating proteomic diversity in a temporospatial manner, avoiding the pleiotropic effect of genomic mutations. Recent discoveries on the evolutionary trajectory of Ser>Gly auto-editing site in insect Adar gene demonstrated a selective advantage to having an editable codon compared to uneditable ones. However, apart from pure observations, quantitative approaches for justifying the adaptiveness of individual RNA editing sites are still lacking. We performed a comparative genomic analysis on 113 Diptera species, focusing on the Adar Ser>Gly auto-recoding site in Drosophila. We only found one species having a derived Gly at the corresponding site, and this occurrence was significantly lower than genome-wide random expectation. This suggests that the Adar Ser>Gly site is unlikely to be genomically replaced with G during evolution, and thus indicating the advantage of editable status over hardwired genomic alleles. Similar trends were observed for the conserved Ile>Met recoding in gene Syt1. In the light of evolution, we established a comparative genomic approach for quantitatively justifying the adaptiveness of individual editing sites. Priority should be given to such adaptive editing sites in future functional studies.

Early Predicting Osteogenic Differentiation of Mesenchymal Stem Cells Based on Deep Learning Within One Day

Osteogenic differentiation of mesenchymal stem cells (MSCs) is proposed to be critical for bone tissue engineering and regenerative medicine. However, the current approach for evaluating osteogenic differentiation mainly involves immunohistochemical staining of specific markers which often can be detected at day 5-7 of osteogenic inducing. Deep learning (DL) is a significant technology for realizing artificial intelligence (AI). Computer vision, a branch of AI, has been proved to achieve high-precision image recognition using convolutional neural networks (CNNs). Our goal was to train CNNs to quantitatively measure the osteogenic differentiation of MSCs. To this end, bright-field images of MSCs during early osteogenic differentiation (day 0, 1, 3, 5, and 7) were captured using a simple optical phase contrast microscope to train CNNs. The results showed that the CNNs could be trained to recognize undifferentiated cells and differentiating cells with an accuracy of 0.961 on the independent test set. In addition, we found that CNNs successfully distinguished differentiated cells at a very early stage (only 1 day). Further analysis showed that overall morphological features of MSCs were the main basis for the CNN classification. In conclusion, MSCs differentiation detection can be achieved early and accurately through simple bright-field images and DL networks, which may also provide a potential and novel method for the field of cell detection in the near future.

Lactylome analyses suggest systematic lysine-lactylated substrates in oral squamous cell carcinoma under normoxia and hypoxia

Cancer cells tend to live in hypoxic environment characterized by enhanced glycolysis and accumulation of lactate. Intracellular lactate is shown to drive a novel type of post-translational modification (PTM), lysine lactylation (Kla). Kla has been confirmed to affect the malignant progression of tumors such as hepatocellular carcinoma (HCC) and colon cancer, whereas the global lactylomic profiling of oral squamous cell carcinoma (OSCC) is unclear. Here, the integrative lactylome and proteome analyses by using liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified 1011 Kla sites within 532 proteins and 1197 Kla sites within 608 proteins in SCC25 cells under normoxic and hypoxic environments, respectively. Among these lactylated proteins, histones accounted for only a small fraction, suggesting the presence of Kla modification of OSCC in a large number of non-histone proteins. Notably, Kla preferred to enrich in spliceosome, ribosome and glycolysis/gluconeogenesis pathway in both normoxic and hypoxic cultures. Compared with normoxia, 589 differential proteins with 898 differentially lactylated sites were detected under hypoxia, which were mainly associated with the glycolysis/gluconeogenesis pathway by KEGG analysis. Importantly, we verified the presence of lactylation modification in the spliceosomal proteins hnRNPA1, SF3A1, hnRNPU and SLU7, as well as in glycolytic enzyme PFKP. In addition, the differential alternative splicing analysis described the divergence of pre-mRNA splicing patterns in the presence or absence of sodium lactate and at different oxygen concentrations. Finally, a negative correlation between tissue Kla levels and the prognosis of OSCC patients was revealed by immunohistochemistry. Our study is the first report to elucidate the lactylome and its biological function in OSCC, which deepens our understanding of the mechanisms underlying OSCC progression and provides a novel strategy for targeted therapy for OSCC.

Perfect cooperative pest control via nano-pesticide and natural predator: High predation selectivity and negligible toxicity toward predatory stinkbug

The improper use of synthetic pesticides has caused adverse effects on global ecosystems and human health. As a part of sustainable pest management strategy, natural predators, along with nano-pesticides, have made significant contributions to ecological agriculture. The cooperative application of both approaches may overcome their limitations, substantially reducing pesticide application while controlling insect pests efficiently. Herein, the current study introduced a cationic star polymer (SPc) to prepare two types of nano-pesticides, which were co-applied with predatory stinkbugs Picromerus lewisi to achieve perfect cooperative pest control. The SPc exhibited nearly no toxicity against predatory stinkbugs at the working concentration, but it led to the death of predatory stinkbugs at extremely high concentration with the lethal concentration 50 (LC50) value of 13.57 mg/mL through oral feeding method. RNA-seq analysis revealed that the oral feeding of SPc could induce obvious stress responses, leading to stronger phagocytosis, exocytosis, and energy synthesis to ultimately result in the death of predatory stinkbugs. Then, the broflanilide and chlorobenzuron were employed to prepare the self-assembled nano-pesticides via hydrogen bond and Van der Waals force, and the complexation with SPc broke the self-aggregated structures of pesticides and reduced their particle sizes down to nanoscale. The bioactivities of prepared nano-pesticides were significantly improved toward common cutworm Spodoptera litura with the corrected mortality increase by approximately 30%. Importantly, predatory stinkbugs exhibited a strong predation selectivity for alive common cutworms to reduce the exposure risk of nano-pesticides, and the nano-pesticides showed negligible toxicity against predators. Thus, the nano-pesticides and predatory stinkbugs could be applied simultaneously for efficient and sustainable pest management. The current study provides an excellent precedent for perfect cooperative pest control via nano-pesticide and natural predator.

Longitudinal profiling identifies co-occurring BRCA1/2 reversions, TP53BP1, RIF1 and PAXIP1 mutations in PARP inhibitor-resistant advanced breast cancer

BACKGROUND

Resistance to therapies that target homologous recombination deficiency (HRD) in breast cancer limits their overall effectiveness. Multiple, preclinically validated, mechanisms of resistance have been proposed, but their existence and relative frequency in clinical disease are unclear, as is how to target resistance.

PATIENTS AND METHODS

Longitudinal mutation and methylation profiling of circulating tumour (ct)DNA was carried out in 47 patients with metastatic BRCA1-, BRCA2- or PALB2-mutant breast cancer treated with HRD-targeted therapy who developed progressive disease-18 patients had primary resistance and 29 exhibited response followed by resistance. ctDNA isolated at multiple time points in the patient treatment course (before, on-treatment and at progression) was sequenced using a novel >750-gene intron/exon targeted sequencing panel. Where available, matched tumour biopsies were whole exome and RNA sequenced and also used to assess nuclear RAD51.

RESULTS

BRCA1/2 reversion mutations were present in 60% of patients and were the most prevalent form of resistance. In 10 cases, reversions were detected in ctDNA before clinical progression. Two new reversion-based mechanisms were identified: (i) intragenic BRCA1/2 deletions with intronic breakpoints; and (ii) intragenic BRCA1/2 secondary mutations that formed novel splice acceptor sites, the latter being confirmed by in vitro minigene reporter assays. When seen before commencing subsequent treatment, reversions were associated with significantly shorter time to progression. Tumours with reversions retained HRD mutational signatures but had functional homologous recombination based on RAD51 status. Although less frequent than reversions, nonreversion mechanisms [loss-of-function (LoF) mutations in TP53BP1, RIF1 or PAXIP1] were evident in patients with acquired resistance and occasionally coexisted with reversions, challenging the notion that singular resistance mechanisms emerge in each patient.

CONCLUSIONS

These observations map the prevalence of candidate drivers of resistance across time in a clinical setting, information with implications for clinical management and trial design in HRD breast cancers.

The first A-to-I RNA editome of hemipteran species Coridius chinensis reveals overrepresented recoding and prevalent intron editing in early-diverging insects

BACKGROUND

Metazoan adenosine-to-inosine (A-to-I) RNA editing resembles A-to-G mutation and increases proteomic diversity in a temporal-spatial manner, allowing organisms adapting to changeable environment. The RNA editomes in many major animal clades remain unexplored, hampering the understanding on the evolution and adaptation of this essential post-transcriptional modification.

METHODS

We assembled the chromosome-level genome of Coridius chinensis belonging to Hemiptera, the fifth largest insect order where RNA editing has not been studied yet. We generated ten head RNA-Seq libraries with DNA-Seq from the matched individuals.

RESULTS

We identified thousands of high-confidence RNA editing sites in C. chinensis. Overrepresentation of nonsynonymous editing was observed, but conserved recoding across different orders was very rare. Under cold stress, the global editing efficiency was down-regulated and the general transcriptional processes were shut down. Nevertheless, we found an interesting site with "conserved editing but non-conserved recoding" in potassium channel Shab which was significantly up-regulated in cold, serving as a candidate functional site in response to temperature stress.

CONCLUSIONS

RNA editing in C. chinensis largely recodes the proteome. The first RNA editome in Hemiptera indicates independent origin of beneficial recoding during insect evolution, which advances our understanding on the evolution, conservation, and adaptation of RNA editing.

Treatment of auricular pseudocysts using enhanced negative drainage: a prospective study of 21 cases

OBJECTIVE

Auricular pseudocysts are rare, painless, benign intracartilaginous cysts of the auricle that are not lined by epithelium and have no known aetiology.

METHOD

This was a prospective study conducted in an ENT department from January 2020 to June 2022. In 21 patients, complete aspiration of the pseudocyst with enhanced negative drainage was performed. They were followed for a minimum of six months.

RESULTS

All patients completely responded to the negative drainage treatment. No cases of recurrence or obvious deformities were observed.

CONCLUSION

Aspiration with intensified negative drainage was associated with a positive response in patients with auricular pseudocysts. Complete resolution of the swelling can be achieved without any serious complications. Thus, it appears to be a simple and effective method for managing the condition.

Stem chewing lice on Cretaceous feathers preserved in amber

Phthirapteran lice (true lice or parasitic lice) are a major group of ectoparasitic insects living on their bird or mammal hosts during their entire life cycle.1 Due to their highly specialized lifestyles, they are extremely poorly represented in fossil records.2 Molecular clock estimations have speculated extensively about the origin time of parasitic lice,3,4 yet none have been confirmed unequivocally. Herein, we report a new family of stem chewing lice, based on two adult insects associated with several semiplume feathers preserved within a piece of Kachin amber from the mid-Cretaceous. They display some defining characteristics of the Amblycera, an early-diverging lineage of the crown lice group. These features include a wingless body, chewing mouthparts, narrow and small thorax, and short tarsus with elongated euplantulae. Our phylogenetic analysis places the new taxa in the Amblycera, and the discovery thus pushes back the lice fossil records by at least 55 million years. Furthermore, the new specimens show primitive characters such as compressed and club-shaped terminal segments of antennae, maxillary and labial palps, and unmodified femora of hind legs, providing key information for the evolutionary relationship between free-living booklice and parasitic lice. This suggests that some ectoparasitic characters defining the crown lice group might have evolved among amblyceran and non-amblyceran lice in parallel. These newly described fossil specimens imply at least a Cretaceous age of Phthiraptera.

Natural selection and genetic diversity maintenance in a parasitic wasp during continuous biological control application

Aphidius gifuensis is a parasitoid wasp and primary endoparasitoid enemy of the peach potato aphid, Myzus persicae. Artificially reared, captive wasps of this species have been extensively and effectively used to control populations of aphids and limit crop loss. However, the consequences of large-scale releasing of captive A. gifuensis, such as genetic erosion and reduced fitness in wild populations of this species, remains unclear. Here, we sequence the genomes of 542 A. gifuensis individuals collected across China, including 265 wild and 277 human-intervened samples. Population genetic analyses on wild individuals recovered Yunnan populations as the ancestral group with the most complex genetic structure. We also find genetic signature of environmental adaptation during the dispersal of wild populations from Yunnan to other regions. While comparative genomic analyses of captive wasps revealed a decrease in genetic diversity during long-term rearing, population genomic analyses revealed signatures of natural selection by several biotic (host plants) or abiotic (climate) factors, which support maintenance of the gene pool of wild populations in spite of the introduction of captive wasps. Therefore, the impact of large-scale release is reduced. Our study suggests that A. gifuensis is a good system for exploring the genetic and evolutionary effects of mass rearing and release on species commonly used as biocontrol agents.

Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening

Age-related macular degeneration (AMD) is the leading cause of central vision impairment among the elderly. Effective and accurate AMD screening tools are urgently needed. Indocyanine green angiography (ICGA) is a well-established technique for detecting chorioretinal diseases, but its invasive nature and potential risks impede its routine clinical application. Here, we innovatively developed a deep-learning model capable of generating realistic ICGA images from color fundus photography (CF) using generative adversarial networks (GANs) and evaluated its performance in AMD classification. The model was developed with 99,002 CF-ICGA pairs from a tertiary center. The quality of the generated ICGA images underwent objective evaluation using mean absolute error (MAE), peak signal-to-noise ratio (PSNR), structural similarity measures (SSIM), etc., and subjective evaluation by two experienced ophthalmologists. The model generated realistic early, mid and late-phase ICGA images, with SSIM spanned from 0.57 to 0.65. The subjective quality scores ranged from 1.46 to 2.74 on the five-point scale (1 refers to the real ICGA image quality, Kappa 0.79-0.84). Moreover, we assessed the application of translated ICGA images in AMD screening on an external dataset (n = 13887) by calculating area under the ROC curve (AUC) in classifying AMD. Combining generated ICGA with real CF images improved the accuracy of AMD classification with AUC increased from 0.93 to 0.97 (P < 0.001). These results suggested that CF-to-ICGA translation can serve as a cross-modal data augmentation method to address the data hunger often encountered in deep-learning research, and as a promising add-on for population-based AMD screening. Real-world validation is warranted before clinical usage.

The complete mitochondrial genome of Aphidius colemani (Hymenoptera: Braconidae: Aphidiinae)

The genome-level features are crucial genetic resources for species identification and phylogenetic analysis. Here, the complete mitochondrial genome of Aphidius colemani Viereck 1912 (Hymenoptera: Braconidae: Aphidiinae) was sequenced, determined and analyzed. The circular genome is 16,372 bp in length with an overall base composition of 38.9% for A, 46.2% for T, 6.7% for C, and 8.2% for G. The mitochondrial genome of A. colemani contained 13 protein-coding genes that initiated by the ATN codon, 22 transfer RNA genes, two ribosomal RNA genes (rRNAs), and a control region (CR). It shared the same gene arrangement patterns that occurred in two tRNA clusters of trnI-trnQ-trnM and trnW-trnC-trnY with Aphidius gifuensis. Phylogenetic analyses using Bayesian inference and Maximum-likelihood methods supported that the two species of Aphidiinae formed a clade and sister to other subfamilies of Braconidae.

SI-ViT: Shuffle instance-based Vision Transformer for pancreatic cancer ROSE image classification

BACKGROUND AND OBJECTIVE

The rapid on-site evaluation (ROSE) technique improves pancreatic cancer diagnosis by enabling immediate analysis of fast-stained cytopathological images. Automating ROSE classification could not only reduce the burden on pathologists but also broaden the application of this increasingly popular technique. However, this approach faces substantial challenges due to complex perturbations in color distribution, brightness, and contrast, which are influenced by various staining environments and devices. Additionally, the pronounced variability in cancerous patterns across samples further complicates classification, underscoring the difficulty in precisely identifying local cells and establishing their global relationships.

METHODS

To address these challenges, we propose an instance-aware approach that enhances the Vision Transformer with a novel shuffle instance strategy (SI-ViT). Our approach presents a shuffle step to generate bags of shuffled instances and corresponding bag-level soft-labels, allowing the model to understand relationships and distributions beyond the limited original distributions. Simultaneously, combined with an un-shuffle step, the traditional ViT can model the relationships corresponding to the sample labels. This dual-step approach helps the model to focus on inner-sample and cross-sample instance relationships, making it potent in extracting diverse image patterns and reducing complicated perturbations.

RESULTS

Compared to state-of-the-art methods, significant improvements in ROSE classification have been achieved. Aiming for interpretability, equipped with instance shuffling, SI-ViT yields precise attention regions that identifying cancer and normal cells in various scenarios. Additionally, the approach shows excellent potential in pathological image analysis through generalization validation on other datasets.

CONCLUSIONS

By proposing instance relationship modeling through shuffling, we introduce a new insight in pathological image analysis. The significant improvements in ROSE classification leads to protential AI-on-site applications in pancreatic cancer diagnosis. The code and results are publicly available at https://github.com/sagizty/MIL-SI.

A new ant species of the genus Carebara Westwood, 1840 (Hymenoptera, Formicidae, Myrmicinae) with a key to Chinese species

A new Chinese ant species Carebaralaevicepssp. nov. is described based on the major and minor workers. This species is most similar to C.lusciosa (Wheeler, 1928) due to a spineless propodeum, the absence of horns, and a smooth head capsule. It is distinguished by the following features: (1) antenna 10-segmented; (2) katepisternum rugose-reticulate; (3) in major workers, lateral sides of head in full-face view parallel; (4) metanotal groove distinct, anterodorsal corner forming an acute tooth behind metanotal groove. Moreover, an updated key to Chinese Carebara species is presented based on major workers, with a checklist comprising a total of 36 Chinese Carebara species and subspecies. Morphological structures and scanning electron micrographs of the newly discovered species' minor and major workers are provided.

Chromosome-level genome of the poultry shaft louse Menopon gallinae provides insight into the host-switching and adaptive evolution of parasitic lice

BACKGROUND

Lice (Psocodea: Phthiraptera) are one important group of parasites that infects birds and mammals. It is believed that the ancestor of parasitic lice originated on the ancient avian host, and ancient mammals acquired these parasites via host-switching from birds. Here we present the first chromosome-level genome of Menopon gallinae in Amblycera (earliest diverging lineage of parasitic lice). We explore the transition of louse host-switching from birds to mammals at the genomic level by identifying numerous idiosyncratic genomic variations.

RESULTS

The assembled genome is 155 Mb in length, with a contig N50 of 27.42 Mb. Hi-C scaffolding assigned 97% of the bases to 5 chromosomes. The genome of M. gallinae retains a basal insect repertoire of 11,950 protein-coding genes. By comparing the genomes of lice to those of multiple representative insects in other orders, we discovered that gene families of digestion, detoxification, and immunity-related are generally conserved between bird lice and mammal lice, while mammal lice have undergone a significant reduction in genes related to chemosensory systems and temperature. This suggests that mammal lice have lost some of these genes through the adaption to environment and temperatures after host-switching. Furthermore, 7 genes related to hematophagy were positively selected in mammal lice, suggesting their involvement in the hematophagous behavior.

CONCLUSIONS

Our high-quality genome of M. gallinae provides a valuable resource for comparative genomic research in Phthiraptera and facilitates further studies on adaptive evolution of host-switching within parasitic lice.

Relaxed purifying selection pressure drives accelerated and dynamic gene rearrangements in thrips (Insecta: Thysanoptera) mitochondrial genomes

Insect mitochondrial genomes (mitogenome) generally present a typical gene order, which is considered as the ancestral arrangement. All sequenced mitogenomes in the Thysanoptera display high levels of gene rearrangement. Due to limited number of thrips mitogenomes sequenced, how gene rearrangement may be shaped by evolution remain unclear. Here, we analyzed 33 thrips mitogenomes, including 14 newly sequenced. These mitogenomes were diverse in organization, nucleotides substitution and gene arrangements. We found 28 highly rearranged gene orders with the breakpoints of gene rearrangements from 25 to 33. Reconstruction of the ancestors mitochondrial gene arrangements states indicated that Tubulifera have more complex pathways than Terebrantia in the gene order evolution. Molecular calibration estimated that divergence of two suborders occurred in the middle Triassic while the radiation of thrips was associated with the arose and flourish of angiosperm. Our evolutionary hypothesis testing suggests that relaxation of selection pressure enabled the early phase of Thysanoptera evolution, followed by a stronger selective pressure fixed diversification. Our analyses found gene inversion increases the nonsynonymous substitution rates and provide an evolutionary hypothesis driving the diverse gene orders.

Identification and Interpretation of A-to-I RNA Editing Events in Insect Transcriptomes

Adenosine-to-inosine (A-to-I) RNA editing is the most prevalent RNA modification in the nervous systems of metazoans. To study the biological significance of RNA editing, we first have to accurately identify these editing events from the transcriptome. The genome-wide identification of RNA editing sites remains a challenging task. In this review, we will first introduce the occurrence, regulation, and importance of A-to-I RNA editing and then describe the established bioinformatic procedures and difficulties in the accurate identification of these sit esespecially in small sized non-model insects. In brief, (1) to obtain an accurate profile of RNA editing sites, a transcriptome coupled with the DNA resequencing of a matched sample is favorable; (2) the single-cell sequencing technique is ready to be applied to RNA editing studies, but there are a few limitations to overcome; (3) during mapping and variant calling steps, various issues, like mapping and base quality, soft-clipping, and the positions of mismatches on reads, should be carefully considered; (4) Sanger sequencing of both RNA and the matched DNA is the best verification of RNA editing sites, but other auxiliary evidence, like the nonsynonymous-to-synonymous ratio or the linkage information, is also helpful for judging the reliability of editing sites. We have systematically reviewed the understanding of the biological significance of RNA editing and summarized the methodology for identifying such editing events. We also raised several promising aspects and challenges in this field. With insightful perspectives on both scientific and technical issues, our review will benefit the researchers in the broader RNA editing community.

Comparative and phylogenetic analyses of mitochondrial genomes in Elateridae (Coleoptera: Elateroidea)

The click-beetles (Elateridae) are a species-rich beetle family that is easily recognizable. They are distributed in all zoogeographical regions with over 11,000 species. Comparative studies of the structural characteristics of mitochondrial genomes (mitogenomes), as well as phylogenetic relationships of click-beetles, can improve our understanding of mitogenomic evolution. In this study, we determined four mitogenomes from Elateridae by next-generation sequencing. The four mitogenomes were 16,005 to 16,930 bp in length with 37 typical genes and a control region (A + T-rich region). Combined with previously reported elaterid mitogenomes, all PCGs initiate with either the standard start codon of ATN or TTG. According to the nonsynonymous/synonymous mutation ratio (Ka/Ks) of all PCGs, the highest and the lowest evolutionary rates were found for atp8 and cox1, respectively. Among the control regions of the four mitogenomes, several different patterns and numbers of tandem repeats were identified, which was the primary cause of the length variation in control regions. Phylogenetic analyses were conducted based on 13 protein-coding genes and two ribosomal RNA genes from 33 species of Elateridae and two outgroups. The Bayesian inference and maximum likelihood trees had an identical topological structure. The monophyly of Cardiophorinae, Agrypninae and Elaterinae was recovered with high support in all topologies, and the Tetralobinae was placed as the earliest branch in the Elateridae. Expanding the availability of mitogenomic and genomic data from a broader range of click-beetles could provide more clarity on the disputed relationships among subfamilies within Elateridae.

Translation of Color Fundus Photography into Fluorescein Angiography Using Deep Learning for Enhanced Diabetic Retinopathy Screening

Purpose

To develop and validate a deep learning model that can transform color fundus (CF) photography into corresponding venous and late-phase fundus fluorescein angiography (FFA) images.

Design

Cross-sectional study.

Participants

We included 51 370 CF-venous FFA pairs and 14 644 CF-late FFA pairs from 4438 patients for model development. External testing involved 50 eyes with CF-FFA pairs and 2 public datasets for diabetic retinopathy (DR) classification, with 86 952 CF from EyePACs, and 1744 CF from MESSIDOR2.

Methods

We trained a deep-learning model to transform CF into corresponding venous and late-phase FFA images. The translated FFA images' quality was evaluated quantitatively on the internal test set and subjectively on 100 eyes with CF-FFA paired images (50 from external), based on the realisticity of the global image, anatomical landmarks (macula, optic disc, and vessels), and lesions. Moreover, we validated the clinical utility of the translated FFA for classifying 5-class DR and diabetic macular edema (DME) in the EyePACs and MESSIDOR2 datasets.

Main Outcome Measures

Image generation was quantitatively assessed by structural similarity measures (SSIM), and subjectively by 2 clinical experts on a 5-point scale (1 refers real FFA); intragrader agreement was assessed by kappa. The DR classification accuracy was assessed by area under the receiver operating characteristic curve.

Results

The SSIM of the translated FFA images were > 0.6, and the subjective quality scores ranged from 1.37 to 2.60. Both experts reported similar quality scores with substantial agreement (all kappas > 0.8). Adding the generated FFA on top of CF improved DR classification in the EyePACs and MESSIDOR2 datasets, with the area under the receiver operating characteristic curve increased from 0.912 to 0.939 on the EyePACs dataset and from 0.952 to 0.972 on the MESSIDOR2 dataset. The DME area under the receiver operating characteristic curve also increased from 0.927 to 0.974 in the MESSIDOR2 dataset.

Conclusions

Our CF-to-FFA framework produced realistic FFA images. Moreover, adding the translated FFA images on top of CF improved the accuracy of DR screening. These results suggest that CF-to-FFA translation could be used as a surrogate method when FFA examination is not feasible and as a simple add-on to improve DR screening.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Genetic Modification of a Hox Locus Drives Mimetic Color Pattern Variation in a Highly Polymorphic Bumble Bee

Müllerian mimicry provides natural replicates ideal for exploring mechanisms underlying adaptive phenotypic divergence and convergence, yet the genetic mechanisms underlying mimetic variation remain largely unknown. The current study investigates the genetic basis of mimetic color pattern variation in a highly polymorphic bumble bee, Bombus breviceps (Hymenoptera, Apidae). In South Asia, this species and multiple comimetic species converge onto local Müllerian mimicry patterns by shifting the abdominal setal color from orange to black. Genetic crossing between the orange and black phenotypes suggested the color dimorphism being controlled by a single Mendelian locus, with the orange allele being dominant over black. Genome-wide association suggests that a locus at the intergenic region between 2 abdominal fate-determining Hox genes, abd-A and Abd-B, is associated with the color change. This locus is therefore in the same intergenic region but not the same exact locus as found to drive red black midabdominal variation in a distantly related bumble bee species, Bombus melanopygus. Gene expression analysis and RNA interferences suggest that differential expression of an intergenic long noncoding RNA between abd-A and Abd-B at the onset setal color differentiation may drive the orange black color variation by causing a homeotic shift late in development. Analysis of this same color locus in comimetic species reveals no sequence association with the same color shift, suggesting that mimetic convergence is achieved through distinct genetic routes. Our study establishes Hox regions as genomic hotspots for color pattern evolution in bumble bees and demonstrates how pleiotropic developmental loci can drive adaptive radiations in nature.

FTO Sensitizes Oral Squamous Cell Carcinoma to Ferroptosis via Suppressing ACSL3 and GPX4

Ferroptosis is a newly established form of regulated cell death characterized by intracellular lipid peroxidation and iron accumulation that may be a promising cancer treatment strategy. However, the function and therapeutic value of ferroptosis in oral squamous cell carcinoma (OSCC) remain inadequately understood. In the present study, we investigated the biological role of the fat mass and obesity-associated gene (FTO) in ferroptosis in the context of OSCC. We found that OSCC had greater potential for ferroptosis, and FTO is associated with ferroptosis. Furthermore, higher FTO expression sensitized OSCC cells to ferroptosis in vitro and in vivo. Mechanistically, FTO suppressed the expression of anti-ferroptotic factors, acyl-CoA synthetase long-chain family member 3 (ACSL3) and glutathione peroxidase 4 (GPX4), by demethylating the m6A modification on the mRNA of ACSL3 and GPX4 and decreasing their stability. Taken together, our findings revealed that FTO promotes ferroptosis through ACSL3 and GPX4 regulation. Thus, ferroptosis activation in OSCC with high FTO levels may serve as a potential therapeutic target.

A deep learning model for generating fundus autofluorescence images from color fundus photography

Background

Fundus Autofluorescence (FAF) is a valuable imaging technique used to assess metabolic alterations in the retinal pigment epithelium (RPE) associated with various age-related and disease-related changes. The practical uses of FAF are ever-growing. This study aimed to evaluate the effectiveness of a generative deep learning (DL) model in translating color fundus (CF) images into synthetic FAF images and explore its potential for enhancing screening of age-related macular degeneration (AMD).

Methods

A generative adversarial network (GAN) model was trained on pairs of CF and FAF images to generate synthetic FAF images. The quality of synthesized FAF images was assessed objectively by common generation metrics. Additionally, the clinical effectiveness of the generated FAF images in AMD classification was evaluated by measuring the area under the curve (AUC), using the LabelMe dataset.

Results

A total of 8410 FAF images from 2586 patients were analyzed. The synthesized FAF images exhibited an impressive objectively assessed quality, achieving a multi-scale structural similarity index (MS-SSIM) of 0.67. When evaluated on the LabelMe dataset, the combination of generated FAF images and CF images resulted in a noteworthy improvement in AMD classification accuracy, with the AUC increasing from 0.931 to 0.968.

Conclusions

This study presents the first attempt to use a generative deep learning model to create authentic and high-quality FAF images from CF images. The incorporation of the translated FAF images on top of CF images improved the accuracy of AMD classification. Overall, this study presents a promising approach to enhance large-scale AMD screening.

Canonical transient receptor potential channel 1 aggravates myocardial ischemia-and-reperfusion injury by upregulating reactive oxygen species

The canonical transient receptor potential channel (TRPC) proteins form Ca2+-permeable cation channels that are involved in various heart diseases. However, the roles of specific TRPC proteins in myocardial ischemia/reperfusion (I/R) injury remain poorly understood. We observed that TRPC1 and TRPC6 were highly expressed in the area at risk (AAR) in a coronary artery ligation induced I/R model. Trpc1-/- mice exhibited improved cardiac function, lower serum Troponin T and serum creatine kinase level, smaller infarct volume, less fibrotic scars, and fewer apoptotic cells after myocardial-I/R than wild-type or Trpc6-/- mice. Cardiomyocyte-specific knockdown of Trpc1 using adeno-associated virus 9 mitigated myocardial I/R injury. Furthermore, Trpc1 deficiency protected adult mouse ventricular myocytes (AMVMs) and HL-1 cells from death during hypoxia/reoxygenation (H/R) injury. RNA-sequencing-based transcriptome analysis revealed differential expression of genes related to reactive oxygen species (ROS) generation in Trpc1-/- cardiomyocytes. Among these genes, oxoglutarate dehydrogenase-like (Ogdhl) was markedly downregulated. Moreover, Trpc1 deficiency impaired the calcineurin (CaN)/nuclear factor-kappa B (NF-κB) signaling pathway in AMVMs. Suppression of this pathway inhibited Ogdhl upregulation and ROS generation in HL-1 cells under H/R conditions. Chromatin immunoprecipitation assays confirmed NF-κB binding to the Ogdhl promoter. The cardioprotective effect of Trpc1 deficiency was canceled out by overexpression of NF-κB and Ogdhl in cardiomyocytes. In conclusion, our findings reveal that TRPC1 is upregulated in the AAR following myocardial I/R, leading to increased Ca2+ influx into associated cardiomyocytes. Subsequently, this upregulates Ogdhl expression through the CaN/NF-κB signaling pathway, ultimately exacerbating ROS production and aggravating myocardial I/R injury.

PPG-based Continuous BP Waveform Estimation Using Polarized Attention-guided Conditional Adversarial Learning Model

The blood pressure (BP) waveform is a vital source of physiological and pathological information concerning the cardiovascular system. This study proposes a novel attention-guided conditional generative adversarial network (cGAN), named PPG2BP-cGAN, to estimate BP waveforms based on photoplethysmography (PPG) signals. The proposed model comprises a generator and a discriminator. Specifically, the UNet3+-based generator integrates a full-scale skip connection structure with a modified polarized self-attention module based on a spatial-temporal attention mechanism. Additionally, its discriminator comprises PatchGAN, which augments the discriminative power of the generated BP waveform by increasing the perceptual field through fully convolutional layers. We demonstrate the superior BP waveform prediction performance of our proposed method compared to state-of-the-art (SOTA) techniques on two independent datasets. Our approach first pre-trained on a dataset containing 683 subjects and then tested on a public dataset. Experimental results from the Multi-parameter Intelligent Monitoring in Intensive Care dataset show that the proposed method achieves a root mean square error of 3.54, mean absolute error of 2.86, and Pearson coefficient of 0.99 for BP waveform estimation. Furthermore, the estimation errors (mean error ± standard deviation error) for systolic BP and diastolic BP are 0.72 ± 4.34 mmHg and 0.41 ± 2.48 mmHg, respectively, meeting the American Association for the Advancement of Medical Instrumentation standard. Our approach exhibits significant superiority over SOTA techniques on independent datasets, thus highlighting its potential for future applications in continuous cuffless BP waveform measurement.

Independent wing reductions and losses among stick and leaf insects (Phasmatodea), supported by new Cretaceous fossils in amber

BACKGROUND

Phasmatodea (stick and leaf insects) play a central role on the debate regarding wing reduction and loss, and its wings are putative reacquisition from secondarily wingless ancestors based solely on extant species. A pivotal taxon in this respect is the species-poor Timematodea, consisting of approximately 21 wingless extant species, which form the sister group of all remaining winged or wingless stick and leaf insects, the Euphasmatodea.

RESULTS

Herein, the new fossils of Timematodea from mid-Cretaceous Kachin amber are reported, with winged and wingless species co-occurring. The palaeogeographic distributions of all fossils of Holophasmatodea are summarized, showing their wide paleo-distributions. The phylogenetic analysis based on morphological characters confirms the earliest-diverging lineage of winged Breviala cretacea gen. et sp. nov. in Timematodea, and the possible relationships among all families of Holophasmatodea. These are critical for the reconstruction of patterns of wing evolution in early Phasmatodea.

CONCLUSIONS

The new fossils suggest that Timematodea once had wings, at least during the mid-Cretaceous. The palaeogeographic occurrences imply that Timematodea probably have been widely distributed since at least the Jurassic. The phylogenetic analysis with the ancestral-state reconstruction of wings indicates that the common ancestors of Holophasmatodea were winged, the reductions and losses of wings among Timematodea and Euphasmatodea have occurred independently since at least the Cretaceous, and the reduction or loss of the forewing earlier than the hind wings.

Autorecoding A-to-I RNA editing sites in the Adar gene underwent compensatory gains and losses in major insect clades

As one of the most prevalent RNA modifications in animals, adenosine-to-inosine (A-to-I) RNA editing facilitates the environmental adaptation of organisms by diversifying the proteome in a temporal-spatial manner. In flies and bees, the editing enzyme Adar has independently gained two different autorecoding sites that form an autofeedback loop, stabilizing the overall editing efficiency. This ensures cellular homeostasis by keeping the normal function of target genes. However, in a broader range of insects, the evolutionary dynamics and significance of this Adar autoregulatory mechanism are unclear. We retrieved the genomes of 377 arthropod species covering the five major insect orders (Hemiptera, Hymenoptera, Coleoptera, Diptera, and Lepidoptera) and aligned the Adar autorecoding sites across all genomes. We found that the two autorecoding sites underwent compensatory gains and losses during the evolution of two orders with the most sequenced species (Diptera and Hymenoptera), and that the two editing sites were mutually exclusive among them: One editable site is significantly linked to another uneditable site. This autorecoding mechanism of Adar could flexibly diversify the proteome and stabilize global editing activity. Many insects independently selected different autorecoding sites to achieve a feedback loop and regulate the global RNA editome, revealing an interesting phenomenon during evolution. Our study reveals the evolutionary force acting on accurate regulation of RNA editing activity in insects and thus deepens our understanding of the functional importance of RNA editing in environmental adaptation and evolution.

Identification of CKS2 as a novel prognostic biomarker and potential therapeutic target for oral squamous cell carcinoma

Background

The cyclin-dependent kinase subunit 2 (CKS2) is recognized to have a substantial impact on the pathogenesis and advancement of several malignant neoplasms. Nevertheless, its biological function and prognostic significance in oral squamous cell carcinoma (OSCC) have yet to be thoroughly investigated. Our primary objective was to clarify the contribution of CKS2 in the progression and prognosis of OSCC.

Methods

We first conducted a thorough examination of online databases to investigate the expression of CKS2, and subsequently corroborated our discoveries by analyzing clinical specimens that we collected. According to the clinicopathological data, we then explored the prognostic significance of CKS2. Furthermore, we predicted the role of CKS2 in OSCC progression by employing weighted gene co-expression network analysis (WGCNA) in conjunction with functional enrichment analysis. We conducted functional experiments in vitro to confirm our speculations. Additionally, we explored other potential functions of CKS2 in immune infiltration, tumor mutation burden (TMB), and drug sensitivity. Finally, we established and validated a nomogram that effectively integrated CKS2-related genes and other relevant clinical factors.

Results

Our findings indicated a significant upregulation of CKS2 expression in OSCC tissues compared to normal groups, which was positively associated with poor clinical outcomes. We also predicted and validated the role of CKS2 in promoting proliferation by regulating the cell cycle. Additionally, its upregulation was significantly correlated to enhanced immune cell infiltration, high TMB, and increased sensitivity of anti-tumor agents. Following verification, the nomogram was conducted to quantify an individual's survival probability.

Conclusions

In general, our study indicates that CKS2 is a novel prognostic biomarker and potential therapeutic target in OSCC.

METTL14 inhibits malignant progression of oral squamous cell carcinoma by targeting the autophagy-related gene RB1CC1 in an m6A-IGF2BP2-dependent manner

N6-methyladenosine (m6A) plays crucial roles in tumorigenesis and autophagy. However, the underlying mechanisms mediated by m6A and autophagy in the malignant progression of oral squamous cell carcinoma (OSCC) remain unclear. In the present study, we revealed that down-regulated expression of METTL14 was correlated with advanced clinicopathological characteristics and poor prognosis in OSCC. METTL14 knockdown significantly inhibited autophagy and facilitated malignant progression in vitro, and promoted tumor growth and metastasis in vivo. A cell model of rapamycin-induced autophagy was established to identify RB1CC1 as a potential target gene involved in m6A-regulated autophagy in OSCC, through RNA sequencing and methylated RNA immunoprecipitation sequencing (meRIP-seq) analysis. Mechanistically, we confirmed that METTL14 posttranscriptionally enhanced RB1CC1 expression in an m6A-IGF2BP2-dependent manner, thereby affecting autophagy and progression in OSCC, through methylated RNA immunoprecipitation qRT-PCR (meRIP-qPCR), RNA stability assays, mutagenesis assays and dual-luciferase reporter. Collectively, our findings demonstrated that METTL14 serves as an OSCC suppressor by regulating the autophagy-related gene RB1CC1 through m6A modification, which may provide a new insight for the diagnosis and therapy of OSCC.

Differential adaptive RNA editing signals between insects and plants revealed by a new measurement termed haplotype diversity

BACKGROUND

C-to-U RNA editing in plants is believed to confer its evolutionary adaptiveness by reversing unfavorable DNA mutations. This "restorative hypothesis" has not yet been tested genome-wide. In contrast, A-to-I RNA editing in insects like Drosophila and honeybee is already known to benefit the host by increasing proteomic diversity in a spatial-temporal manner (namely "diversifying hypothesis").

METHODS

We profiled the RNA editomes of multiple tissues of Arabidopsis thaliana, Drosophila melanogaster, and Apis melifera. We unprecedentedly defined the haplotype diversity (HD) of RNA molecules based on nonsynonymous editing events (recoding sites).

RESULTS

Signals of adaptation is confirmed in Arabidopsis by observing higher frequencies and levels at nonsynonymous editing sites over synonymous sites. Compared to A-to-I recoding sites in Drosophila, the C-to-U recoding sites in Arabidopsis show significantly lower HD, presumably due to the stronger linkage between C-to-U events.

CONCLUSIONS

C-to-U RNA editing in Arabidopsis is adaptive but it is not designed for diversifying the proteome like A-to-I editing in Drosophila. Instead, C-to-U recoding sites resemble DNA mutations. Our observation supports the restorative hypothesis of plant C-to-U editing which claims that editing is used for fixing unfavorable genomic sequences.

A Novel Feature Engineering Method Based on Latent Representation Learning for Radiomics: Application in NSCLC Subtype Classification

Radiomics refers to the high-throughput extraction of quantitative features from medical images, and is widely used to construct machine learning models for the prediction of clinical outcomes, while feature engineering is the most important work in radiomics. However, current feature engineering methods fail to fully and effectively utilize the heterogeneity of features when dealing with different kinds of radiomics features. In this work, latent representation learning is first presented as a novel feature engineering approach to reconstruct a set of latent space features from original shape, intensity and texture features. This proposed method projects features into a subspace called latent space, in which the latent space features are obtained by minimizing a unique hybrid loss function including a clustering-like loss and a reconstruction loss. The former one ensures the separability among each class while the latter one narrows the gap between the original features and latent space features. Experiments were performed on a multi-center non-small cell lung cancer (NSCLC) subtype classification dataset from 8 international open databases. Results showed that compared with four traditional feature engineering methods (baseline, PCA, Lasso and L2,1-norm minimization), latent representation learning could significantly improve the classification performance of various machine learning classifiers on the independent test set (all p<0.001). Further on two additional test sets, latent representation learning also showed a significant improvement in generalization performance. Our research shows that latent representation learning is a more effective feature engineering method, which has the potential to be used as a general technology in a wide range of radiomics researches.

Exploring the Mitogenomes of Mantodea: New Insights from Structural Diversity and Higher-Level Phylogenomic Analyses

The recently reorganized classification of Mantodea has made significant progress in resolving past homoplasy problems, although some relationships among higher taxa remain uncertain. In the present study, we utilized newly sequenced mitogenomes and nuclear gene sequences of 23 mantid species, along with published data of 53 mantises, to perform familial-sampling structural comparisons of mantodean mitogenomes and phylogenomic studies. Our rstructural analysis revealed generally conserved mitogenome organizations, with a few cases of tRNA gene rearrangements, including the detection of trnL₂ duplication for the first time. In our phylogenetic analysis, we found a high degree of compositional heterogeneity and lineage-specific evolutionary rates among mantodean mitogenomes, which frequently corresponded to several unexpected groupings in the topologies under site-homogeneous models. In contrast, the topologies obtained using the site-heterogeneous mixture model fit the currently accepted phylogeny of Mantodea better. Topology tests and four-cluster likelihood mapping analyses further determined the preferred topologies. Our phylogenetic results confirm the monophyly of superfamilial groups Schizomantodea, Amerimantodea, Heteromantodea, Promantidea, and Mantidea and recover the early-branching relationships as (Mantoidoidea + (Amerimantodea + (Metallyticoidea + Cernomantodea))). Additionally, the results suggest that the long-unresolved phylogenetic position of Majangidae should be placed within Mantidea, close to Mantoidea, rather than within Epaphroditoidea. Our findings contribute to understanding the compositional and structural diversity in mantodean mitogenomes, underscore the importance of evolutionary model selection in phylogenomic studies, and provide new insights into the high-level phylogeny of Mantodea.

Novel Genetic Subtypes of Urothelial Carcinoma With Differential Outcomes on Immune Checkpoint Blockade

PURPOSE

Immune checkpoint blockade (ICB) therapy has significantly improved clinical outcomes in bladder cancer. Identification of correlates of benefit is critical to select appropriate therapy for individual patients.

METHODS

To reveal genetic variables associated with benefit from ICB, we performed whole-exome sequencing on tumor specimens from 88 patients with advanced bladder cancer treated with ICB.

RESULTS

We identified several genetic factors that correlated with progression-free and overall survival after ICB therapy including ARID1A mutation, tumor mutational burden, intratumoral heterogeneity, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome (immune dN/dS), and tumor cell purity. In addition, we noted that neutrophil-to-lymphocyte ratio and smoking history were negatively associated with overall survival. These genetic characteristics define four molecular subtypes demonstrating differential sensitivity to ICB. We validated the association of these four subtypes with clinical benefit from ICB in an independent cohort (IMvigor210). Finally, we showed that these molecular subtypes also correlate with outcome, although with distinct relationships, among patients not treated with ICB using The Cancer Genome Atlas (TCGA) bladder cancer cohort. Using parallel RNA sequencing data, the subtypes were also shown to correlate with immune infiltration and inflammation, respectively, in the IMvigor210 and TCGA cohorts.

CONCLUSION

Together, our study defines molecular subgroups of bladder cancer that influence benefit from ICB.

Full-length transcriptome profiling of Aphidius gifuensis mitochondrial genome with gene rearrangement and control region duplication

Although mitochondrial gene rearrangement has been observed in many insect lineages, little is known about how it affects mitochondrial gene transcription. To address this question, we first constructed a quantitative transcription map for Aphidius gifuensis, a species of parasitoid wasp known to have a highly rearranged mitochondrial genome (mitogenome) and two potential control regions (CRs). Based on this transcription map, we assessed the models of the mitochondrial transcription and post-transcription cleavage. We found that the J and N strand of this mitogenome differ significantly in transcriptional regulation. On the J strand, we found two transcription initiation sites (TISs), five transcription termination sites (TTSs), and six polycistronic primary transcripts whereas only one TIS, one TTS and one polycistronic primary transcript can be found on the N strand. Most of the non-coding regions of both strands were transcribed into primary transcripts and cleaved after transcription. The proposed mode of transcription of A. gifuensis was similar to that of Drosophila, a model organism with no gene rearrangement. And two rearranged gene clusters (trnI-CR1-trnM-CR2-trnQ and trnW-trnY-trnC) seemed to have little effects on the mode of transcription. In addition, our results revealed the presence of TISs in CR1 and CR2, implying that both CRs maybe required for transcriptional regulation. Analysis of the post-transcriptional cleavage process showed that there were both "forward cleavage" and "reverse cleavage" models in A. gifuensis, and more than one way of cleavages were found in three regions. The incomplete transcripts suggested that the direction of mitochondrial RNA degradation was from 5' to 3' end and supported the view of polyadenylation-dependent RNA degradation. Our study provides insights into the transcriptional and post-transcriptional regulation processes of highly rearranged insect mitogenomes.

Chromosome-level genome assembly of bean flower thrips Megalurothrips usitatus (Thysanoptera: Thripidae)

Bean flower thrips Megalurothrips usitatus is a staple pest of cowpea and other legumes and causes dramatic economic losses. Its small size allows for easy concealment, and large reproductive capacity easily leads to infestations. Despite the importance of a genome in developing novel management strategies, genetic studies on M. usitatus remain limited. Thus, we generated a chromosome-level M. usitatus genome using a combination of PacBio long read and Hi-C technologies. The assembled genome was 238.14 Mb with a scaffold N50 of 13.85 Mb. The final genome was anchored into 16 pseudo-chromosomes containing 14,000 genes, of which 91.74% were functionally annotated. Comparative genomic analyses revealed that expanded gene families were enriched in fatty acid metabolism and detoxification metabolism (ABC transporters), and contracted gene families were strongly associated with chitin-based cuticle development and sensory perception of taste. In conclusion, this high-quality genome provides an invaluable resource for us to understand the thrips' ecology and genetics, contributing to pest management.

Cacopsylla fuscicella Sp. Nov. (Hemiptera, Psyllidae), a New Loquat Pest in China

Psylloidea, commonly known as jumping plant-lice, have a phloem-sucking habit and strong specificity to their host plants. Within the Psyllidae family, the genus Cacopsylla Ossiannilsson, 1970 stands out as being the most diverse, with three species feeding on the genus Eriobotrya Lindl. In this study, a new psyllid species, Cacopsylla fuscicella sp. nov., was described from China. It is a pest of Eriobotrya japonica (Thunb.) Lindl. and has been cultivated as a commercial fruit tree for years. Illustrations of habitus, morphological structures, and its damage to loquat were also provided. The complete mitochondrial genome of C. fuscicella sp. nov. was sequenced and annotated. The phylogenetic tree inferred from the maximum likelihood analyses confirmed C. fuscicella sp. nov. as a member of the genus Cacopsylla. Genetic distances were generated to assess comparative genetic distances within Psyllinae.

Climatic oscillation promoted diversification of spinous assassin bugs during Pleistocene glaciation

Insect speciation is among the most fascinating topics in evolutionary biology; however, its underlying mechanisms remain unclear. Allopatric speciation represents one of the major types of speciation and is believed to have frequently occurred during glaciation periods, when climatic oscillation may have caused suitable habitats to be fragmented repeatedly, creating geographical isolation among populations. However, supporting evidence for allopatric speciation of insects in East Asia during the Pleistocene glaciation remains lacking. We aim to investigate the effect of climatic oscillation during the Pleistocene glaciation on the diversification pattern and evolutionary history of hemipteran insects and to test the hypothesis of Pleistocene species stability using spinous assassin bugs Sclomina (Hemiptera: Reduviidae), a small genus widely distributed in southern China but was later found to have cryptic species diversity. Here, using the whole mitochondrial genome (mitogenome) and nuclear ribosomal RNA genes, we investigated both interspecific and intraspecific diversification patterns of spinous assassin bugs. Approximate Bayesian computation, ecological niche modeling, and demographic history analyses were also applied to understand the diversification process and driven factors. Our data suggest that the five species of Sclomina are highly diverged, despite three of them currently being cryptic. Speciation occurred during the Pleistocene when suitable distribution areas were possibly fragmented. Six phylogeographic groups in the type species S. erinacea were identified, among which two groups underwent expansion during the early Last Glacial Period and after Last Glacier Maximum. Our analyses suggest that this genus may have experienced climate-driven habitat fragmentation and postglacial expansion in the Pleistocene, promoting allopatric speciation and intraspecific diversification. Our results reveal underestimated species diversity in a small insect group and illustrate a remarkable example of allopatric speciation of insects in East Asia promoted by Pleistocene climatic oscillations. These findings provide important insights into the speciation processes and aid the conservation of insect species diversity.

[The role of CD4+ CD25+ Treg in the mechanism of autoimmune auditory neuropathy in SD rats]

Objective: To investigate the role of CD4⁺CD25⁺regulatory cell (CD4⁺CD25⁺Treg) in auditory neuropathy (AN) using a rat model of autoimmune auditory neuropathy. Methods: The SD rats were immunized with P0 protein emulsified in complete Freunds adjuvant for 8 weeks. The number of CD4⁺CD25⁺Treg in peripheral blood and cochlea and the expression of Foxp3 gene in cochlea were detected respectively 2, 4, 6 and 8 weeks after the immunization with P0 protein in rats. Then CD4⁺CD25⁺Treg were transferred intravenously to the AN rats at 2, 4, 6 and 8 weeks of the immunization, respectively. The change of auditory brainstem response (ABR) and distortion product otoacoustic emission (DPOAE) were detected, and the morphological changes in the inner ear were investigated. Results: The number of CD4⁺CD25⁺Treg in the peripheral blood of AN rats decreased gradually after 2, 4, 6 and 8 weeks of P0 protein immunization. The number of CD4⁺CD25⁺Treg in cochlea gradually increased with the prolongation of immunization time, but the expression of Foxp3 gene in cochlea gradually decreased over time. After intravenous transplantation of CD4⁺CD25⁺Treg in AN rats, the threshold of ABR response decreased, and DPOAE had no significant change. The number of spiral ganglion neurons in cochlea increased, and hair cells had no significant change under electron microscope. Conclusions: The decrease in the number and function of CD4⁺CD25⁺Treg reduces its inhibitory effect on autoimmune response and promotes the occurrence of autoimmune auditory neuropathy in AN rats. Adoptive transfer of CD4⁺CD25⁺Treg can reduce the autoimmune response and promote the recovery of autoimmune auditory neuropathy.

Features and evolution of control regions in leafroller moths (Lepidoptera: Tortricidae) inferred from mitochondrial genomes and phylogeny

The control region (CR) of the mitochondrial genome (mitogenome) represents a major noncoding fragment with several special structural features that are thought to be responsible for the initiation of mitogenome transcription and replication. However, few studies have revealed the evolutionary patterns of CR in the phylogenetic context. Here, we explain the characteristics and evolution of CR in Tortricidae, inferred from a mitogenome-based phylogeny. The first complete mitogenomes of the genera Meiligma and Matsumuraeses were sequenced. Both mitogenomes are double-stranded circular DNA molecules with lengths of 15,675 bp and 15,330 bp, respectively. Phylogenetic analyses derived from 13 protein-coding genes and two ribosomal RNAs showed that most tribes, including subfamilies Olethreutinae and Tortricinae, were recovered as monophyletic clades, similar to previous studies based on morphological or nuclear data. Moreover, comprehensive comparative analyses of the structural organization and role of tandem replications on the length variation and high AT content of CR sequences were conducted. The results reveal a significant positive correlation between the total length and AT content of tandem repeats and whole CR sequences in Tortricidae. The structural organization in CR sequences is diverse, even between closely related tribes, which demonstrates the plasticity of the mitochondrial DNA molecule in Tortricidae.

The mitochondrial genome of Binodoxys acalephae (Hymenoptera: Braconidae) with unique gene rearrangement and phylogenetic implications

BACKGROUND

Species in the subfamily Aphidiinae from the Braconidae of Hymenoptera are endoparasitic wasps that exclusively utilize aphids as hosts. Some Aphidiinae species are widely used as biological agents. However, there were only one species with determined complete mitochondrial genome from this subfamily.

METHODS AND RESULTS

In this study, we sequenced and annotated the mitochondrial genome (mitogenome) of Binodoxys acalephae, which was 15,116 bp in size and contained 37 genes. The start codon of 13 protein-coding genes was ATN, and the complete stop codon TAA and TAG was widely assigned to 11 protein-coding genes. The lrRNA contains 43 stem-loop structures, and srRNA contains 25 stem-loop structures. Translocation and inversion of tRNA genes was found to be dominant in B. acalephae. In contrast to Aphidius gifuensis from the same subfamily Aphidiinae, inverted tRNA^Leu1 was translocated to the gene cluster between tRNA^Leu2 and COX2, and the control region between tRNA^Ile and tRNA^Met was deleted in the mitogenome of B. acalephae. Within Braconidae, gene clusters tRNA^Trp-tRNA^Cys-tRNA^Tyr and CR-tRNA^Ile-tRNA^Gln-tRNA^Met were hotspots for gene rearrangement. Phylogenetic analysis showed that both Bayesian and maximum-likelihood methods recovered the monophyly of Aphidiinae and suggested that Aphidiinae formed sister clades with the remaining subfamilies. The phylogenetic analyses of nine subfamilies supported the monophyly of Cyclostomes and Noncyclostomes in Braconidae.

CONCLUSION

The arrangement of mitochondrial genes and the phylogenetic relationships among nine Braconidae subfamilies were constructed better to understand the diversity and evolution of Aphidiinae mitogenomes.

Robust reconstruction of fluorescence molecular tomography based on adaptive adversarial learning strategy

Objective.Fluorescence molecular tomography (FMT) is a promising molecular imaging modality for quantifying the three-dimensional (3D) distribution of tumor probes in small animals. However, traditional deep learning reconstruction methods that aim to minimize the mean squared error (MSE) and iterative regularization algorithms that rely on optimal parameters are typically influenced by strong noise, resulting in poor FMT reconstruction robustness.Approach.In this letter, we propose an adaptive adversarial learning strategy (3D-UR-WGAN) to achieve robust FMT reconstructions. Unlike the pixel-based MSE criterion in traditional CNNs or the regularization strategy in iterative solving schemes, the reconstruction strategy can greatly facilitate the performance of the network models through alternating loop training of the generator and the discriminator. Second, the reconstruction strategy combines the adversarial loss in GANs with the L1 loss to significantly enhance the robustness and preserve image details and textual information.Main results.Both numerical simulations and physical phantom experiments demonstrate that the 3D-UR-WGAN method can adaptively eliminate the effects of different noise levels on the reconstruction results, resulting in robust reconstructed images with reduced artifacts and enhanced image contrast. Compared with the state-of-the-art methods, the proposed method achieves better reconstruction performance in terms of target shape recovery and localization accuracy.Significance.This adaptive adversarial learning reconstruction strategy can provide a possible paradigm for robust reconstruction in complex environments, and also has great potential to provide an alternative solution for solving the problem of poor robustness encountered in other optical imaging modalities such as diffuse optical tomography, bioluminescence imaging, and Cherenkov luminescence imaging.

D2-RecST: Dual-domain joint reconstruction strategy for fluorescence molecular tomography based on image domain and perception domain

BACKGROUND AND OBJECTIVE

Fluorescence molecular tomography (FMT) is a promising molecular imaging modality for quantifying the three-dimensional (3D) distribution of fluorescent probes in small animals. Over the past few years, learning-based FMT reconstruction methods have achieved promising results. However, these methods typically attempt to minimize the mean-squared error (MSE) between the reconstructed image and the ground truth. Although signal-to-noise ratios (SNRs) are improved, they are susceptible to non-uniform artifacts and loss of structural detail, making it extremely challenging to obtain accurate and robust FMT reconstructions under noisy measurements.

METHODS

We propose a novel dual-domain joint strategy based on the image domain and perception domain for accurate and robust FMT reconstruction. First, we formulate an explicit adversarial learning strategy in the image domain, which greatly facilitates training and optimization through two enhanced networks to improve anti-noise ability. Besides, we introduce a novel transfer learning strategy in the perceptual domain to optimize edge details by providing perceptual priors for fluorescent targets. Collectively, the proposed dual-domain joint reconstruction strategy can significantly eliminate the non-uniform artifacts and effectively preserve the structural edge details.

RESULTS

Both numerical simulations and in vivo mouse experiments demonstrate that the proposed method markedly outperforms traditional and cutting-edge methods in terms of positioning accuracy, image contrast, robustness, and target morphological recovery.

CONCLUSIONS

The proposed method achieves the best reconstruction performance and has great potential to facilitate precise localization and 3D visualization of tumors in in vivo animal experiments.

Radiomics feature analysis and model research for predicting histopathological subtypes of non-small cell lung cancer on CT images: A multi-dataset study

PURPOSE

Classifying the subtypes of non-small cell lung cancer (NSCLC) is essential for clinically adopting optimal treatment strategies and improving clinical outcomes, but the histological subtypes are confirmed by invasive biopsy or post-operative examination at present. Based on multi-center data, this study aimed to analyze the importance of extracted CT radiomics features and develop the model with good generalization performance for precisely distinguishing major NSCLC subtypes: adenocarcinoma (ADC) and squamous cell carcinoma (SCC).

METHODS

We collected a multi-center CT dataset with 868 patients from eight international databases on the cancer imaging archive (TCIA). Among them, patients from five databases were mixed and split to training and test sets (560:140). The remaining three databases were used as independent test sets: TCGA set (n = 97) and lung3 set (n = 71). A total of 1409 features containing shape, intensity, and texture information were extracted from tumor volume of interest (VOI), then the ℓ_2,1 -norm minimization was used for feature selection and the importance of selected features was analyzed. Next, the prediction and generalization performance of 130 radiomics models (10 common algorithms and 120 heterogeneous ensemble combinations) were compared by the average AUC value on three test sets. Finally, predictive results of the optimal model were shown.

RESULTS

After feature selection, 401 features were obtained. Features of intensity, texture GLCM, GLRLM, and GLSZM had higher classification weight coefficients than other features (shape, texture GLDM, and NGTDM), and the filtered image features exhibited significant importance than original image features (p-value = 0.0210). Moreover, five ensemble learning algorithms (Bagging, AdaBoost, RF, XGBoost, GBDT) had better generalization performance (p-value = 0.00418) than other non-ensemble algorithms (MLP, LR, GNB, SVM, KNN). The Bagging-AdaBoost-SVM model had the highest AUC value (0.815 ± 0.010) on three test sets. It obtained AUC values of 0.819, 0.823, and 0.804 on test set, TCGA set and lung3 set, respectively.

CONCLUSION

Our multi-dataset study showed that intensity features, texture features (GLCM, GLRLM, and GLSZM) and filtered image features were more important for distinguishing ADCs from SCCs. The method of ensemble learning can improve the prediction and generalization performance on the complicated multi-center data. The Bagging-AdaBoost-SVM model had the strongest generalization performance, and it showed promising clinical value for non-invasively predicting the histopathological subtypes of NSCLC.

Full-Length Transcriptome Profiling of Coridius chinensis Mitochondrial Genome Reveals the Transcription of Genes with Ancestral Arrangement in Insects

Coridius chinensis (Hemiptera: Dinidoridae) is a medicinal insect. Its mitochondrial gene arrangement is consistent with that of Drosophila melanogaster and Erthesina fullo, the two insects with well-studied mitochondrial transcription. To investigate whether the structural consistency of mitochondrial genes leads to similarities in transcription and post-transcriptional processing, we improved the gene annotation and constructed a quantitative transcription map for the C. chinensis mitochondrial genome (mitogenome) using full-length transcriptome sequencing. The size of this mitogenome was 16,214 bp and the proposed model of mitochondrial transcription was similar to that of Drosophila. Both strands were nearly entirely transcribed except for the antisense genes downstream of trnS2 on N strand. The expression of cytochrome c subunit genes is higher than that of NADH-dehydrogenase subunit genes. The post-transcriptional cleavage process followed the "tRNA punctuation" model, and both the "reverse cleavage" model in Drosophila and "forward cleavage" model in E. fullo were found in C. chinensis. In addition, we found that long non-coding RNAs from the control region contained tandem repeats. Polyadenylation was performed after CCA triplet at the 3' end of tRNA. The isoform diversity of lrRNA was identified. Our study sheds light on the transcriptional regulation and RNA processing of insect mitogenomes with the putative ancestral gene arrangement.

Intercellular Receptor-ligand Binding: Effect of Protein-membrane Interaction

Gaining insights into the intercellular receptor-ligand binding is of great importance for understanding numerous physiological and pathological processes, and stimulating new strategies in drug design and discovery. In contrast to the in vitro protein interaction in solution, the anchored receptor and ligand molecules interact with membrane in situ, which affects the intercellular receptor-ligand binding. Here, we review theoretical, simulation and experimental works regarding the regulatory effects of protein-membrane interactions on intercellular receptor-ligand binding mainly from the following aspects: membrane fluctuations, membrane curvature, glycocalyx, and lipid raft. In addition, we discuss biomedical significances and possible research directions to advance the field and highlight the importance of understanding of coupling effects of these factors in pharmaceutical development.

MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer

Pancreatic cancer is one of the most malignant cancers with high mortality. The rapid on-site evaluation (ROSE) technique can significantly accelerate the diagnostic workflow of pancreatic cancer by immediately analyzing the fast-stained cytopathological images with on-site pathologists. However, the broader expansion of ROSE diagnosis has been hindered by the shortage of experienced pathologists. Deep learning has great potential for the automatic classification of ROSE images in diagnosis. But it is challenging to model the complicated local and global image features. The traditional convolutional neural network (CNN) structure can effectively extract spatial features, while it tends to ignore global features when the prominent local features are misleading. In contrast, the Transformer structure has excellent advantages in capturing global features and long-range relations, while it has limited ability in utilizing local features. We propose a multi-stage hybrid Transformer (MSHT) to combine the strengths of both, where a CNN backbone robustly extracts multi-stage local features at different scales as the attention guidance, and a Transformer encodes them for sophisticated global modeling. Going beyond the strength of each single method, the MSHT can simultaneously enhance the Transformer global modeling ability with the local guidance from CNN features. To evaluate the method in this unexplored field, a dataset of 4240 ROSE images is collected where MSHT achieves 95.68% in classification accuracy with more accurate attention regions. The distinctively superior results compared to the state-of-the-art models make MSHT extremely promising for cytopathological image analysis. The codes and records are available at: https://github.com/sagizty/ Multi-Stage-Hybrid-Transformer.

A full repertoire of Hemiptera genomes reveals a multi-step evolutionary trajectory of auto-RNA editing site in insect Adar gene

Adenosine-to-inosine (A-to-I) RNA editing, mediated by metazoan ADAR enzymes, is a prevalent post-transcriptional modification that diversifies the proteome and promotes adaptive evolution of organisms. The Drosophila Adar gene has an auto-recoding site (termed S>G site) that forms a negative-feedback loop and stabilizes the global editing activity. However, the evolutionary trajectory of Adar S>G site in many other insects remains largely unknown, preventing us from a deeper understanding on the significance of this auto-editing mechanism. In this study, we retrieved the well-annotated genomes of 375 arthropod species including the five major insect orders (Lepidoptera, Diptera, Coleoptera, Hymenoptera and Hemiptera) and several outgroup species. We performed comparative genomic analysis on the Adar auto-recoding S>G site. We found that the ancestral state of insect S>G site was an uneditable serine codon (unSer) and that this state was largely maintained in Hymenoptera. The editable serine codon (edSer) appeared in the common ancestor of Lepidoptera, Diptera and Coleoptera and was almost fixed in the three orders. Interestingly, Hemiptera species possessed comparable numbers of unSer and edSer codons, and a few 'intermediate codons', demonstrating a multi-step evolutionary trace from unSer-to-edSer with non-synchronized mutations at three codon positions. We argue that the evolution of Adar S>G site is the best genomic evidence supporting the 'proteomic diversifying hypothesis' of RNA editing. Our work deepens our understanding on the evolutionary significance of Adar auto-recoding site which stabilizes the global editing activity and controls transcriptomic diversity.

Image restoration for blurry optical images caused by photon diffusion with deep learning

Optical macroscopic imaging techniques have shown great significance in the investigations of biomedical issues by revealing structural or functional information of living bodies through the detection of visible or near-infrared light derived from different mechanisms. However, optical macroscopic imaging techniques suffer from poor spatial resolution due to photon diffusion in biological tissues. This dramatically restricts the application of optical imaging techniques in numerous situations. In this paper, an image restoration method based on deep learning is proposed to eliminate the blur caused by photon diffusion in optical macroscopic imaging. Two blurry images captured at orthogonal angles are used as the additional information to ensure the uniqueness of the solution and restore the small targets at deep locations. Then a fully convolutional neural network is proposed to accomplish the image restoration, which consists of three sectors: V-shaped network for central view, V-shaped network for side views, and synthetical path. The two V-shaped networks are concatenated to the synthetical path with skip connections to generate the output image. Simulations as well as phantom and mouse experiments are implemented. Results indicate the effectiveness of the proposed method.

The association between dietary selenium intake and Hashimoto's thyroiditis among US adults: National Health and Nutrition Examination Survey (NHANES), 2007-2012

BACKGROUND

Selenium has been shown to influence the pathological processes and physiological functions of thyroid. Although growing evidence has shown that selenium can improve the treatment of Hashimoto's thyroiditis (HT), there is a need to evaluate the association between dietary selenium intake and HT in a large cross-sectional study. This study explored the association between dietary selenium intake and HT based on the National Health reand Nutrition Examination Survey (NHANES) database (2007-2012).

METHODS

A total of 8756 of 30,442 participants were included in the study. Dietary selenium intake was the independent variable, while HT was the dependent variable. In addition, the relative importance of the selected variables was determined using the XGBoost model. A smooth curve was constructed based on the fully adjusted model to investigate the potential linear relationship between dietary selenium intake and HT. Smooth curves were also constructed to explore the linear/non-linear relationship between dietary selenium intake and thyroid peroxidase antibody (TPOAb)/ thyroglobulin antibody (TgAb).

RESULTS

The mean age of the enrolled participants was 44.35 years (± 20.92). The risk of HT was significantly reduced by a 35% per-unit increase in dietary selenium intake after fully adjusting for covariates according to the model (log2-transformed data; OR 0.65; 95% CI 0.51, 0.83). The XGBoost model revealed that dietary selenium intake was the most important variable associated with Hashimoto's thyroiditis. Dietary selenium intake (Log2-transformed) was negatively correlated with TPOAb levels [- 16.42 (- 22.18, - 10.65), P < 0.0001], while a non-linear relationship was observed between dietary selenium intake and TgAb with an inflection point of 6.58 (95.67 μg, Log2-transformed).

CONCLUSION

Dietary selenium intake is independently and inversely associated with HT risk. Moreover, dietary selenium intake is negatively correlated with TPOAb levels and non-linearly correlated with TGAb levels. Therefore, dietary selenium intake may be a safe and low-cost alternative for the prevention and treatment of HT.

Prior Attention Network for Multi-Lesion Segmentation in Medical Images

The accurate segmentation of multiple types of lesions from adjacent tissues in medical images is significant in clinical practice. Convolutional neural networks (CNNs) based on the coarse-to-fine strategy have been widely used in this field. However, multi-lesion segmentation remains to be challenging due to the uncertainty in size, contrast, and high interclass similarity of tissues. In addition, the commonly adopted cascaded strategy is rather demanding in terms of hardware, which limits the potential of clinical deployment. To address the problems above, we propose a novel Prior Attention Network (PANet) that follows the coarse-to-fine strategy to perform multi-lesion segmentation in medical images. The proposed network achieves the two steps of segmentation in a single network by inserting a lesion-related spatial attention mechanism in the network. Further, we also propose the intermediate supervision strategy for generating lesion-related attention to acquire the regions of interest (ROIs), which accelerates the convergence and obviously improves the segmentation performance. We have investigated the proposed segmentation framework in two applications: 2D segmentation of multiple lung infections in lung CT slices and 3D segmentation of multiple lesions in brain MRIs. Experimental results show that in both 2D and 3D segmentation tasks our proposed network achieves better performance with less computational cost compared with cascaded networks. The proposed network can be regarded as a universal solution to multi-lesion segmentation in both 2D and 3D tasks. The source code is available at https://github.com/hsiangyuzhao/PANet.