A modular circuit coordinates the diversification of courtship strategies.

Mate recognition systems evolve rapidly to reinforce the reproductive boundaries between species, but the underlying neural mechanisms remain enigmatic. Here we leveraged the rapid coevolution of female pheromone production and male pheromone perception in Drosophila1,2 to gain insight into how the architecture of mate recognition circuits facilitates their diversification. While in some Drosophila species females produce unique pheromones that act to arouse their conspecific males, the pheromones of most species are sexually monomorphic such that females possess no distinguishing chemosensory signatures that males can use for mate recognition3. We show that Drosophila yakuba males evolved the ability to use a sexually monomorphic pheromone, 7-tricosene, as an excitatory cue to promote courtship. By comparing key nodes in the pheromone circuits across multiple Drosophila species, we reveal that this sensory innovation arises from coordinated peripheral and central circuit adaptations: a distinct subpopulation of sensory neurons has acquired sensitivity to 7-tricosene and, in turn, selectively signals to a distinct subset of P1 neurons in the central brain to trigger courtship. Such a modular circuit organization, in which different sensory inputs can independently couple to parallel courtship control nodes, may facilitate the evolution of mate recognition systems by allowing novel sensory modalities to become linked to male arousal. Together, our findings suggest how peripheral and central circuit adaptations can be flexibly coordinated to underlie the rapid evolution of mate recognition strategies across species.

DeepFGRN: inference of gene regulatory network with regulation type based on directed graph embedding.

The inference of gene regulatory networks (GRNs) from gene expression profiles has been a key issue in systems biology, prompting many researchers to develop diverse computational methods. However, most of these methods do not reconstruct directed GRNs with regulatory types because of the lack of benchmark datasets or defects in the computational methods. Here, we collect benchmark datasets and propose a deep learning-based model, DeepFGRN, for reconstructing fine gene regulatory networks (FGRNs) with both regulation types and directions. In addition, the GRNs of real species are always large graphs with direction and high sparsity, which impede the advancement of GRN inference. Therefore, DeepFGRN builds a node bidirectional representation module to capture the directed graph embedding representation of the GRN. Specifically, the source and target generators are designed to learn the low-dimensional dense embedding of the source and target neighbors of a gene, respectively. An adversarial learning strategy is applied to iteratively learn the real neighbors of each gene. In addition, because the expression profiles of genes with regulatory associations are correlative, a correlation analysis module is designed. Specifically, this module not only fully extracts gene expression features, but also captures the correlation between regulators and target genes. Experimental results show that DeepFGRN has a competitive capability for both GRN and FGRN inference. Potential biomarkers and therapeutic drugs for breast cancer, liver cancer, lung cancer and coronavirus disease 2019 are identified based on the candidate FGRNs, providing a possible opportunity to advance our knowledge of disease treatments.

FFMAVP: a new classifier based on feature fusion and multitask learning for identifying antiviral peptides and their subclasses.

Antiviral peptides (AVPs) are widely found in animals and plants, with high specificity and strong sensitivity to drug-resistant viruses. However, due to the great heterogeneity of different viruses, most of the AVPs have specific antiviral activities. Therefore, it is necessary to identify the specific activities of AVPs on virus types. Most existing studies only identify AVPs, with only a few studies identifying subclasses by training multiple binary classifiers. We develop a two-stage prediction tool named FFMAVP that can simultaneously predict AVPs and their subclasses. In the first stage, we identify whether a peptide is AVP or not. In the second stage, we predict the six virus families and eight species specifically targeted by AVPs based on two multiclass tasks. Specifically, the feature extraction module in the two-stage task of FFMAVP adopts the same neural network structure, in which one branch extracts features based on amino acid feature descriptors and the other branch extracts sequence features. Then, the two types of features are fused for the following task. Considering the correlation between the two tasks of the second stage, a multitask learning model is constructed to improve the effectiveness of the two multiclass tasks. In addition, to improve the effectiveness of the second stage, the network parameters trained through the first-stage data are used to initialize the network parameters in the second stage. As a demonstration, the cross-validation results, independent test results and visualization results show that FFMAVP achieves great advantages in both stages.

USP49 promotes adenocarcinoma of the esophagogastric junction malignant progression via activating SHCBP1-ß-catenin-GPX4 axis.

Adenocarcinoma of the esophagogastric junction (AEG) has received widespread attention because of its increasing incidence. However, the molecular mechanism underlying tumor progression remains unclear. Here, we report that the downregulation of Ubiquitin-specific peptidase 49 (USP49) promotes ferroptosis in OE33 and OE19 cells, thereby inhibiting cell proliferation in vitro and in vivo, whereas the overexpression of USP49 had the opposite effect. In addition, USP49 downregulation promoted AEG cell radiotherapy sensitivity. Moreover, overexpression of Glutathione PeroXidase 4 (GPX4) reversed the ferroptosis and proliferation inhibition induced by USP49 knockdown. Mechanistically, USP49 deubiquitinates and stabilizes Shc SH2-domain binding protein 1 (SHCBP1), subsequently facilitating the entry of ß-catenin into the nucleus to enhance GPX4 transcriptional expression. Finally, high USP49 expression was correlated with shorter overall survival in patients with AEG. In summary, our findings identify USP49 as a novel regulator of ferroptosis in AEG cells, indicating that USP49 may be a potential therapeutic target in AEG.

Neural Signatures of Competition between Voluntary and Involuntary Influences over the Focus of Attention in Visual Working Memory.

Adaptive behavior relies on the selection and prioritization of relevant sensory inputs from the external environment as well as from among internal sensory representations held in working memory. Recent behavioral evidence suggests that the classic distinction between voluntary (goal-driven) and involuntary (stimulus-driven) influences over attentional allocation also applies to the selection of internal representations held in working memory. In the current EEG study, we set out to investigate the neural dynamics associated with the competition between voluntary and involuntary control over the focus of attention in visual working memory. We show that when voluntary and involuntary factors compete for the internal focus of attention, prioritization of the appropriate item is delayed-as reflected both in delayed gaze biases that track internal selection and in delayed neural beta (15-25 Hz) dynamics that track the planning for the upcoming memory-guided manual action. We further show how this competition is paralleled-possibly resolved-by an increase in frontal midline theta (4-8 Hz) activity that, moreover, predicts the speed of ensuing memory-guided behavior. Finally, because theta increased following retrocues that effectively reduced working-memory load, our data unveil how frontal theta activity during internal attentional focusing tracks demands on cognitive control over and above working-memory load. Together, these data yield new insight into the neural dynamics that govern the focus of attention in visual working memory, and disentangle the contributions of frontal midline theta activity to the processes of control versus retention in working memory.

Robust Double Emulsions for Multicolor Fluorescence-Activated Cell Sorting.

Cell-cell interactions are essential for the proper functioning of multicellular organisms. For example, T cells interact with antigen-presenting cells (APCs) through specific T-cell receptor (TCR)-antigen interactions during an immune response. Fluorescence-activated droplet sorting (FADS) is a high-throughput technique for efficiently screening cellular interaction events. Unfortunately, current droplet sorting instruments have significant limitations, most notably related to analytical throughput and complex operation. In contrast, commercial fluorescence-activated cell sorters offer superior speed, sensitivity, and multiplexing capabilities, although their use as droplet sorters is poorly defined and underutilized. Herein, we present a universally applicable and simple-to-implement workflow for generating double emulsions and performing multicolor cell sorting using a commercial FACS instrument. This workflow achieves a double emulsion detection rate exceeding 90%, enabling multicellular encapsulation and high-throughput immune cell activation sorting for the first time. We anticipate that the presented droplet sorting strategy will benefit cell biology laboratories by providing access to an advanced microfluidic toolbox with minimal effort and cost investment.

A Molecular Cage Accessed by Threefold Click Reaction of a C3v-Symmetric Triazido-Functionalized Tribenzotriquinacene.

The hitherto unknown hexakis(halomethyl)-functionalized tribenzotriquinacenes (TBTQs) 9 and 10 were synthesized from the key 4b,8b,12b-tribromo-TBTQ derivative 6 by an improved route in 67% overall yield. Extension of the bowl-shaped framework of 9 or 10 by threefold condensation with propargylamine or 2-azidoethylamine afforded the corresponding TBTQ-trialkyne 11 and TBTQ-triazide 12, respectively. While attempts to construct bis-TBTQ cages, including homodimerization of 11 and heterocoupling of 11 with 12, were unsuccessful, triazide 12 was found to undergo threefold [3 + 2]-cycloaddition with 3-ethynylaniline and phloroglucinol tripropargyl ether under click chemistry conditions. The latter reaction enabled facile capping of the TBTQ bowl to give the novel cage compound 5 in 22% yield.

Persistent Mesodermal Differentiation Capability of Bone Marrow MSCs Isolated from Aging Patients with Low-Energy Traumatic Hip Fracture and Osteoporosis: A Clinical Evidence.

A low-energy hit, such as a slight fall from a bed, results in a bone fracture, especially in the hip, which is a life-threatening risk for the older adult and a heavy burden for the social economy. Patients with low-energy traumatic bone fractures usually suffer a higher level of bony catabolism accompanied by osteoporosis. Bone marrow-derived stem cells (BMSCs) are critical in osteogenesis, leading to metabolic homeostasis in the healthy bony microenvironment. However, whether the BMSCs derived from the patients who suffered osteoporosis and low-energy traumatic hip fractures preserve a sustained mesodermal differentiation capability, especially in osteogenesis, is yet to be explored in a clinical setting. Therefore, we aimed to collect BMSCs from clinical hip fracture patients with osteoporosis, followed by osteogenic differentiation comparison with BMSCs from healthy young donors. The CD markers identification, cytokines examination, and adipogenic differentiation were also evaluated. The data reveal that BMSCs collected from elderly osteoporotic patients secreted approximately 122.8 pg/mL interleukin 6 (IL-6) and 180.6 pg/mL vascular endothelial growth factor (VEGF), but no PDGF-BB, IL-1b, TGF-b1, IGF-1, or TNF-α secretion. The CD markers and osteogenic and adipogenic differentiation capability in BMSCs from these elderly osteoporotic patients and healthy young donors are equivalent and compliant with the standards defined by the International Society of Cell Therapy (ISCT). Collectively, our data suggest that the elderly osteoporotic patients-derived BMSCs hold equivalent differentiation and proliferation capability and intact surface markers identical to BMSCs collected from healthy youth and are available for clinical cell therapy.

Improved Anti-Oxidant and Anti-Bacterial Capacities of Skim Milk Fermented by Lactobacillus plantarum.

Milk, on account of its abundant protein content, is recognized as a vital source of bioactive substances. In this study, the bioactive ingredients in milk were obtained by a combination of protease hydrolysis and fermentation with Lactobacillus plantarum. The compositions of protease hydrolysate (PM) and fermentation supernatant (FM) were determined, and their anti-oxidant and anti-bacterial activities were evaluated. Using LC-MS/MS, the molecular weights and sequences of the peptides were characterized, among which a total of 25 bioactive peptides were identified. The DPPH radical scavenging results demonstrated that FM exhibited an enhanced anti-oxidant capacity compared to PM. The bacterial survival rate results revealed that FM had a remarkable anti-bacterial ability compared to PM. Additionally, the anti-bacterial component and potential anti-bacterial mechanisms were determined. The results of cytoplasmic membrane depolarization, cell membrane permeability, and morphological observation indicated that FM could interact with bacterial membranes to achieve its anti-bacterial effect. These findings suggested that FM, as a bioactive substance of natural origin, holds potential applications in the functional food, pharmaceutical, and cosmetic industries.

Integrated Omnidirectional Design of Non-volatile Solid Additive Enables Binary Organic Solar Cells with Efficiency Exceeding 19.5.

Solid additives have drawn great attention due to their numerous appealing benefits in enhancing the power conversion efficiencies (PCEs) of organic solar cells (OSCs). To date, various strategies have been reported for the selection or design of non-volatile solid additives. However, the lack of a general design/evaluation principles for developing non-volatile solid additives often results in individual solid additives offering only one or two efficiency-boosting attributes. In this work, we propose an integrated omnidirectional strategy for designing non-volatile solid additives. By validating the method on the 4,5,9,10-pyrene diimide (PyDI) system, a novel non-volatile solid additive named PyMC5 was designed. PyMC5 is capable of enhancing device performance by establishing synergistic dual charge transfer channels, forming appropriate interactions with active layer materials, reducing non-radiative voltage loss and optimizing film morphology. Notably, the binary device (PM6:L8-BO) treated by PyMC5 achieved a PCE over 19.5%, ranking among the highest reported to date. In addition, the integration of PyMC5 mitigated the degradation process of the devices under photo- and thermal-stress conditions. This work demonstrates an efficient integrated omnidirectional approach for designing non-volatile solid additives, offering a promising avenue for further advancements in OSC development.

Smartphone Imaging Flow Cytometry for High-Throughput Single-Cell Analysis.

We present a portable imaging flow cytometer comprising a smartphone, a small-footprint optical framework, and a PDMS-based microfluidic device. Flow cytometric analysis is performed in a sheathless manner via elasto-inertial focusing with a custom-written Android program, integrating a graphical user interface (GUI) that provides a high degree of user control over image acquisition. The proposed system offers two different operational modes. First, "post-processing" mode enables particle/cell sizing at throughputs of up to 67 000 particles/s. Alternatively, "real-time" mode allows for integrated cell/particle classification with machine learning at throughputs of 100 particles/s. To showcase the efficacy of our platform, polystyrene particles are accurately enumerated within heterogeneous populations using the post-processing mode. In real-time mode, an open-source machine learning algorithm is deployed within a custom-developed Android application to classify samples containing cells of similar size but with different morphologies. The flow cytometer can extract high-resolution bright-field images with a spatial resolution <700 nm using the developed machine learning-based algorithm, achieving classification accuracies of 97% and 93% for Jurkat and EL4 cells, respectively. Our results confirm that the smartphone imaging flow cytometer (sIFC) is capable of both enumerating single particles in flow and identifying morphological features with high resolution and minimal hardware.

Synthesis of a DNA-Encoded Macrocyclic Library Utilizing Intramolecular Benzimidazole Formation.

Macrocycles occupy chemical space "beyond the rule of five". They bridge traditional bioactive small molecule drugs and macromolecules and have the potential to modulate challenging targets such as PPI or proteases. Here we report an on-DNA macrocyclization reaction utilizing intramolecular benzimidazole formation. A 129-million-member macrocyclic library composed of a privileged benzimidazole core, a dipeptide sequence (natural or non-natural), and linkers of varying length and flexibility was designed and synthesized.

Modular Click Assembly DNA-Encoded Glycoconjugate Libraries with on-DNA Functional Group Transformations.

Carbohydrates are an important class of naturally active products and play vital roles in regulating various physiological activities. To meet the demand for carbohydrate-based libraries used for the identification of potential drug candidates for pharmaceutical-related targets, we developed a set of on-DNA protocols to construct the DNA-encoded glycoconjugates, including Seyferth-Gilbert homologation, anomeric azidation, and CuAAC cyclization. These on-DNA chemistries enable the generation and modification of DNA-linked glycosyl compounds with good conversions and broad substrate scope. Finally, three DNA-linked glycoconjugate libraries were successfully generated to demonstrate their applicability and feasibility in library preparation.

Analysis of mRNA-miRNA interaction network reveals the role of CAFs-derived exosomes in the immune regulation of oral squamous cell carcinoma.

BACKGROUND: Cancer-associated fibroblasts (CAFs) have significant tumor regulatory functions, and CAFs-derived exosomes (CAFs-Exo) released from CAFs play an important role in the progression of oral squamous cell carcinoma (OSCC). However, a lack of comprehensive molecular biological analysis leaves the regulatory mechanisms of CAFs-Exo in OSCC unclear. METHODS: We used platelet derived growth factor-BB (PDGF-BB) to induce the transformation of human oral mucosa fibroblast (hOMF) into CAFs, and extracted exosomes from the supernatant of CAFs and hOMF. We validated the effect of CAFs-Exo on tumor progression by exosomes co-culture with Cal-27 and tumor-forming in nude mice. The cellular and exosomal transcriptomes were sequenced, and immune regulatory genes were screened and validated using mRNA-miRNA interaction network analysis in combination with publicly available databases. RESULTS: The results showed that CAFs-Exo had a stronger ability to promote OSCC proliferation and was associated with immunosuppression. We discovered that the presence of immune-related genes in CAFs-Exo may regulate the expression of PIGR, CD81, UACA, and PTTG1IP in Cal-27 by analyzing CAFs-Exo sequencing data and publicly available TCGA data. This may account for the ability of CAFs-Exo to exert immunomodulation and promote OSCC proliferation. CONCLUSIONS: CAFs-Exo was found to be involved in tumor immune regulation through hsa-miR-139-5p, ACTR2 and EIF6, while PIGR, CD81, UACA and PTTG1IP may be potentially effective targets for the treatment of OSCC in the future.

Altered expression of the L-arginine/nitric oxide pathway in ovarian cancer: metabolic biomarkers and biological implications.

MOTIVATION: Ovarian cancer (OC) is a highly lethal gynecological malignancy. Extensive research has shown that OC cells undergo significant metabolic alterations during tumorigenesis. In this study, we aim to leverage these metabolic changes as potential biomarkers for assessing ovarian cancer. METHODS: A functional module-based approach was utilized to identify key gene expression pathways that distinguish different stages of ovarian cancer (OC) within a tissue biopsy cohort. This cohort consisted of control samples (n = 79), stage I/II samples (n = 280), and stage III/IV samples (n = 1016). To further explore these altered molecular pathways, minimal spanning tree (MST) analysis was applied, leading to the formulation of metabolic biomarker hypotheses for OC liquid biopsy. To validate, a multiple reaction monitoring (MRM) based quantitative LCMS/MS method was developed. This method allowed for the precise quantification of targeted metabolite biomarkers using an OC blood cohort comprising control samples (n = 464), benign samples (n = 3), and OC samples (n = 13). RESULTS: Eleven functional modules were identified as significant differentiators (false discovery rate, FDR < 0.05) between normal and early-stage, or early-stage and late-stage ovarian cancer (OC) tumor tissues. MST analysis revealed that the metabolic L-arginine/nitric oxide (L-ARG/NO) pathway was reprogrammed, and the modules related to "DNA replication" and "DNA repair and recombination" served as anchor modules connecting the other nine modules. Based on this analysis, symmetric dimethylarginine (SDMA) and arginine were proposed as potential liquid biopsy biomarkers for OC assessment. Our quantitative LCMS/MS analysis on our OC blood cohort provided direct evidence supporting the use of the SDMA-to-arginine ratio as a liquid biopsy panel to distinguish between normal and OC samples, with an area under the ROC curve (AUC) of 98.3%. CONCLUSION: Our comprehensive analysis of tissue genomics and blood quantitative LC/MSMS metabolic data shed light on the metabolic reprogramming underlying OC pathophysiology. These findings offer new insights into the potential diagnostic utility of the SDMA-to-arginine ratio for OC assessment. Further validation studies using adequately powered OC cohorts are warranted to fully establish the clinical effectiveness of this diagnostic test.

Limimaricola litoreus sp. nov., isolated from intertidal sand of the Yellow Sea.

A novel species of the genus Limimaricola, designated ASW11-118T, was isolated from an intertidal sand sample of the Yellow Sea, PR China. Growth of strain ASW11-118T occurred at 10-40 °C (optimum, 28 °C), pH 5.5-8.5 (optimum, pH 7.5) and with 0.5-8.0 % (w/v) NaCl (optimum, 1.5%). Strain ASW11-118T has the highest 16S rRNA gene sequence similarity to Limimaricola cinnabarinus LL-001T (98.8%) and 98.6 % to Limimaricola hongkongensis DSM 17492T. Phylogenetic analysis based on genomic sequences indicated that strain ASW11-118T belongs to the genus Limimaricola. The genome size of strain ASW11-118T was 3.8 Mb and DNA G+C content was 67.8 mol%. The average nucleotide identity and digital DNA-DNA hybridization values between strain ASW11-118T and other members of the genus Limimaricola were below 86.6 and 31.3 %, respectively. The predominant respiratory quinone was ubiquinone-10. The predominant cellular fatty acid was C18 : 1 ω7c. The major polar lipids were phosphatidylglycerol, diphosphatidylglycerol, phosphatidylcholine and one unknown aminolipid. On the basis of the data presented, strain ASW11-118T is considered to represent a novel species of the genus Limimaricola, for which the name Limimaricola litoreus sp. nov. is proposed. The type strain is ASW11-118T (=MCCC 1K05581T=KCTC 82494T).

An electronic tongue based on conjugated polymers for the discrimination and quantitative detection of tetracyclines.

A fluorescent sensor array has been developed based on conjugated polymers (CPs) having six different skeletons for the detection of tetracyclines (TCs), which are known as environmental pollutants. CPs were synthesized from confined nanoreactors in a controlled manner. The fluorescent response occurs through the fluorescence resonance energy transfer (FRET) effect. By utilizing linear discriminant analysis (LDA), effective differentiation of TCs was accomplished with a very low detection concentration (66 nM). Moreover, the sensor array exhibited a highly sensitive ability to quantitatively distinguish different concentrations of TCs. Finally, the sensor array's potential for detecting TCs in aqueous solutions has been successfully demonstrated, widening its applications in practical environments. With simple preparation process, a low cost of detection and high sensitivity, the experimental results indicate that the CP-based sensor array is a promising platform for the sensitive and quantitative detection of TCs, and provides a good reference for future scientific research.

Advances in research on virulence factors of Acinetobacter baumannii and their potential as novel therapeutic targets.

Acinetobacter baumannii is a strictly aerobic, nonmotile, nonfermenting, gram-negative bacillus. It is a highly infectious and invasive pathogen with high mortality and morbidity rates among immunodeficient patients. Due to increasing levels of drug resistance and the inefficiency of existing antimicrobial treatments, it is crucial to develop novel agents to control this pathogen. Several recent studies have investigated virulence factors that are associated with the pathogenesis of A. baumannii, and could thus serve as novel therapeutic targets. The present review comprehensively summarizes the current understanding of these virulence factors and their mechanisms in A. baumannii. We also highlight factors that could be potential therapeutic targets, as well as list candidate virulence factors for future researchers and clinical practitioners.

A pretreatment prediction model of grade 3 tumors classed by the IASLC grading system in lung adenocarcinoma.

PURPOSE: The new grading system for invasive nonmucinous lung adenocarcinoma (LUAD) in the 2021 World Health Organization Classification of Thoracic Tumors was based on a combination of histologically predominant subtypes and high-grade components. In this study, a model for the pretreatment prediction of grade 3 tumors was established according to new grading standards. METHODS: We retrospectively collected 399 cases of clinical stage I (cStage-I) LUAD surgically treated in Tianjin Chest Hospital from 2015 to 2018 as the training cohort. Besides, the validation cohort consists of 216 patients who were collected from 2019 to 2020. These patients were also diagnosed with clinical cStage-I LUAD and underwent surgical treatment at Tianjin Chest Hospital. Univariable and multivariable logistic regression analyses were used to select independent risk factors for grade 3 adenocarcinomas in the training cohort. The nomogram prediction model of grade 3 tumors was established by R software. RESULTS: In the training cohort, there were 155 grade 3 tumors (38.85%), the recurrence-free survival of which in the lobectomy subgroup was better than that in the sublobectomy subgroup (P = 0.034). After univariable and multivariable analysis, four predictors including consolidation-to-tumor ratio, CEA level, lobulation, and smoking history were incorporated into the model. A nomogram was established and internally validated by bootstrapping. The Hosmer-Lemeshow test result was χ2 = 7.052 (P = 0.531). The C-index and area under the receiver operating characteristic curve were 0.708 (95% CI: 0.6563-0.7586) for the training cohort and 0.713 (95% CI: 0.6426-0.7839) for the external validation cohort. CONCLUSIONS: The nomogram prediction model of grade 3 LUAD was well fitted and can be used to assist in surgical or adjuvant treatment decision-making.

The value of frozen section diagnosis of tumor spread through air spaces in small-sized (≤ 2 cm) non-small cell lung cancer.

BACKGROUND: The current accuracy of frozen section diagnosis of tumor spread through air spaces (STAS) in non-small cell lung cancer (NSCLC) is poor. However, the accuracy and prognostic value of STAS assessment on frozen sections in small-sized NSCLC (diameter ≤ 2 cm) is unknown. METHODS: Three hundred fifty-two patients with clinical stage I NSCLC (≤ 2 cm) were included, of which the paraffin sections and frozen sections were reviewed. The accuracy of STAS diagnosis in frozen sections was assessed using paraffin sections as the gold standard. The relationship between STAS on frozen sections and prognosis was assessed by the Kaplan-Meier method and log-rank tests. RESULTS: STAS on frozen sections in 58 of 352 patients could not be evaluated. In the other 294 patients, 36.39% (107/294) was STAS-positive on paraffin sections and 29.59% (87/294) on frozen sections. The accuracy of frozen section diagnosis of STAS was 74.14% (218/294), sensitivity was 55.14% (59/107), specificity was 85.02% (159/187) and agreement was moderate (K = 0.418). In subgroup analysis, the Kappa values for frozen section diagnosis of STAS in the consolidation-to-tumor ratio (CTR) ≤ 0.5 group and CTR > 0.5 group were 0.368, 0.415, respectively. In survival analysis, STAS-positive frozen sections were associated with worse recurrence-free survival in the CTR > 0.5 group (P < 0.05). CONCLUSIONS: The moderate accuracy and prognostic significance of frozen section diagnosis of STAS in clinical stage I NSCLC (≤ 2 cm in diameter; CTR > 0.5) suggests that frozen section assessment of STAS can be applied to the treatment strategy of small-sized NSCLC with CTR > 0.5.