The adjuvant treatment role of ω-3 fatty acids by regulating gut microbiota positively in the acne vulgaris.

Objectives:We aimed to explore the potential role of omega-3 (ω-3) fatty acids on acne vulgaris by modulating gut microbiota.Materials and Methods:We randomly divided the untreated acne patients into two groups with or without ω-3 fatty acids intervention for 12 weeks. The Sprague Dawley (SD) rats with acne model were given isotretinoin, ω-3 fatty acids or their combination respectively. Then the colonic contents samples of the drug intervention SD rats were transferred to the pseudo sterile rats with acne model. The severity of the disease was assessed by the Global Acne Grading System (GAGS) score of the patients, and the swelling rate of auricle and the pathological section of the rat with acne model. The 16S rDNA gene sequencing was performed to detect the alteration of the gut microbiota.Results:ω-3 fatty acids could increase the diversity of the gut microbiota and regulate the flora structure positively both in the patients and rats, increase the abundance of butyric acid producing bacteria and GAGS score in the patients, and alleviate the inflammation and comedones of rats.Conclusion:Supplementation of ω-3 fatty acids could alleviate the inflammation of acne vulgaris by increasing the abundance of butyric acid producing bacteria.

MSS-UNet: A Multi-Spatial-Shift MLP-based UNet for skin lesion segmentation.

Multilayer perceptron (MLP) networks have become a popular alternative to convolutional neural networks and transformers because of fewer parameters. However, existing MLP-based models improve performance by increasing model depth, which adds computational complexity when processing local features of images. To meet this challenge, we propose MSS-UNet, a lightweight convolutional neural network (CNN) and MLP model for the automated segmentation of skin lesions from dermoscopic images. Specifically, MSS-UNet first uses the convolutional module to extract local information, which is essential for precisely segmenting the skin lesion. We propose an efficient double-spatial-shift MLP module, named DSS-MLP, which enhances the vanilla MLP by enabling communication between different spatial locations through double spatial shifts. We also propose a module named MSSEA with multiple spatial shifts of different strides and lighter external attention to enlarge the local receptive field and capture the boundary continuity of skin lesions. We extensively evaluated the MSS-UNet on ISIC 2017, 2018, and PH2 skin lesion datasets. On three datasets, the method achieves IoU metrics of 85.01%±0.65, 83.65%±1.05, and 92.71%±1.03, with a parameter size and computational complexity of 0.33M and 15.98G, respectively, outperforming most state-of-the-art methods.The code is publicly available at https://github.com/AirZWH/MSS-UNet.

KISS-1 knockdown inhibits cell growth, migration, and invasion in HTR-8/SVneo cells by regulating the GRP54-mediated PI3K/AKT signaling pathway.

Recurrent spontaneous abortions (RSA) affect reproductive health and increase the risk of subsequent abortions. To investigate the role of KISS-1/GPR-54 signaling in RSA progression. Villus tissue was collected from RSA patients, and human trophoblastic HTR-8/SVneo cells were used. KISS-1 and GRP54 levels were detected using RT-qPCR and immunohistochemistry. Western blotting was performed to analyze ZO-1 and ZEB1 levels. Cell proliferation was determined via CCK-8 and cell clone formation assays. Transwell assays were performed to assess cell migration and invasion abilities. KISS-1 was down-regulated in the villus tissues of RSA patients. KISS-1 overexpression dramatically inhibited trophoblast proliferation, migration, and invasion. Mechanistically, ZEB1 expression was down-regulated, whereas ZO-1 expression was up-regulated, after KISS-1 overexpression. GPR54 silencing neutralized the effect of KISS-1 in HTR-8/SVneo cells. Additionally, KISS-1 overexpression inactivated the PI3K/AKT signaling pathway through GRP54. The KISS-1/GPR-54 signaling axis regulates RSA progression by regulating the PI3K/AKT signaling pathway.

Rhizosphere Microbe Affects Soil Available Nitrogen and Its Implication for the Ecological Adaptability and Rapid Growth of Dendrocalamus sinicus, the Strongest Bamboo in the World.

The interaction between soil microbes and plants has a significant effect on soil microbial structure and function, as well as plant adaptability. However, the effect of soil micro-organisms on ecological adaption and rapid growth of woody bamboos remains unclear. Here, 16S rRNA and ITS rRNA genes of rhizosphere micro-organisms were sequenced, and the soil properties of three different types of Dendrocalamus sinicus were determined at the dormancy and germination stages of rhizome buds. The result showed that each type of D. sinicus preferred to absorb ammonia nitrogen (NH4+-N) rather than nitrate nitrogen (NO3--N) and required more NH4+-N at germination or rapid growth period than during the dormancy period. In total, nitrogen fixation capacity of soil bacteria in the straight type was significantly higher than that in the introduced straight type, while the ureolysis capacity had an opposite trend. Saprophytic fungi were the dominant fungal functional taxa in habitat soils of both straight and introduced straight type. Our findings are of great significance in understanding how soil microbes affect growth and adaptation of woody bamboos, but also for soil management of bamboo forests in red soil.

Mutant IAA21 genes from Dendrocalamus sinicus Chia et J. L. Sun inhibit stem and root growth in transgenic tobacco by interacting with ARF5.

Woody bamboos are important resource of industrial fibres. Auxin signaling plays a key role in multiple plant developmental processes, as yet the role of auxin/indole acetic acid (Aux/IAA) in culm development of woody bamboos has not been previously characterized. Dendrocalamus sinicus Chia et J. L. Sun is the largest woody bamboo documented in the world. Here, we identified two alleles of DsIAA21 gene (sIAA21 and bIAA21) from the straight- and bent-culm variants of D. sinicus, respectively, and studied how the domains I, i, and II of DsIAA21 affect the gene transcriptional repression. The results showed that bIAA21 expression was rapidly induced by exogenous auxin in D. sinicus. In transgenic tobacco, sIAA21 and bIAA21 mutated in domains i, and II significantly regulated plant architecture and root development. Stem cross sections revealed that parenchyma cells were smaller in transgenic plants than that in wild type plants. Domain i mutation changed the leucine and proline at position 45 to proline and leucine (siaa21L45P and biaa21P45L) strongly repressed cell expansion and root elongation by reducing the gravitropic response. Substitution of isoleucine with valine in domain II of the full length DsIAA21 resulted in dwarf stature in transgenic tobacco plants. Furthermore, the DsIAA21 interacted with auxin response factor 5 (ARF5) in transgenic tobacco plants, suggesting that DsIAA21 might inhibit stem and root elongation via interacting with ARF5. Taken together, our data indicated that DsIAA21 was a negative regulator of plant development and suggested that amino acid differences in domain i of sIAA21 versus bIAA21 affected their response to auxin, and might play a key role in the formation of the bent culm variant in D. sinicus. Our results not only shed a light on the morphogenetic mechanism in D. sinicus, but also provided new insights into versatile function of Aux/IAAs in plants.

Cellular Senescence: Ageing and Androgenetic Alopecia.

Androgenetic alopecia (AGA) is the most common type of hair loss and features progressive miniaturization of hair follicles. Generally, the occurrence of AGA has long been thought to be driven by genetic and androgen predisposition. However, increasingly, data proposed ageing and AGA are intimately linked. Elevated senescent cell burden and androgen and oxidative stress-induced senescence mechanisms in ageing may be initial targets to improve AGA. This review summarizes the biological links between ageing and AGA, with special focus on cellular senescence. In addition, we discuss the potential therapeutic strategies for improving cellular senescence in AGA, such as inhibiting dermal papilla cells and hair follicle stem cells senescence driven by androgen and reactive oxygen species, removing senescent cell, and reducing senescence-associated secretory phenotype (SASP).

Semi-supervised medical image segmentation via cross-guidance and feature-level consistency dual regularization schemes.

BACKGROUND: Semi-supervised learning is becoming an effective solution for medical image segmentation because of the lack of a large amount of labeled data. PURPOSE: Consistency-based strategy is widely used in semi-supervised learning. However, it is still a challenging problem because of the coupling of CNN-based isomorphic models. In this study, we propose a new semi-supervised medical image segmentation network (DRS-Net) based on a dual-regularization scheme to address this challenge. METHODS: The proposed model consists of a CNN and a multidecoder hybrid Transformer, which adopts two regularization schemes to extract more generalized representations for unlabeled data. Considering the difference in learning paradigm, we introduce the cross-guidance between CNN and hybrid Transformer, which uses the pseudo label output from one model to supervise the other model better to excavate valid representations from unlabeled data. In addition, we use feature-level consistency regularization to effectively improve the feature extraction performance. We apply different perturbations to the feature maps output from the hybrid Transformer encoder and keep an invariance of the predictions to enhance the encoder's representations. RESULTS: We have extensively evaluated our approach on three typical medical image datasets, including CT slices from Spleen, MRI slices from the Heart, and FM Nuclei. We compare DRS-Net with state-of-the-art methods, and experiment results show that DRS-Net performs better on the Spleen dataset, where the dice similarity coefficient increased by about 3.5%. The experimental results on the Heart and Nuclei datasets show that DRS-Net also improves the segmentation effect of the two datasets. CONCLUSIONS: The proposed DRS-Net enhances the segmentation performance of the datasets with three different medical modalities, where the dual-regularization scheme extracts more generalized representations and solves the overfitting problem.

Dual encoder network with transformer-CNN for multi-organ segmentation.

Medical image segmentation is a critical step in many imaging applications. Automatic segmentation has gained extensive concern using a convolutional neural network (CNN). However, the traditional CNN-based methods fail to extract global and long-range contextual information due to local convolution operation. Transformer overcomes the limitation of CNN-based models. Inspired by the success of transformers in computer vision (CV), many researchers focus on designing the transformer-based U-shaped method in medical image segmentation. The transformer-based approach cannot effectively capture the fine-grained details. This paper proposes a dual encoder network with transformer-CNN for multi-organ segmentation. The new segmentation framework takes full advantage of CNN and transformer to enhance the segmentation accuracy. The Swin-transformer encoder extracts global information, and the CNN encoder captures local information. We introduce fusion modules to fuse convolutional features and the sequence of features from the transformer. Feature fusion is concatenated through the skip connection to smooth the decision boundary effectively. We extensively evaluate our method on the synapse multi-organ CT dataset and the automated cardiac diagnosis challenge (ACDC) dataset. The results demonstrate that the proposed method achieves Dice similarity coefficient (DSC) metrics of 80.68% and 91.12% on the synapse multi-organ CT and ACDC datasets, respectively. We perform the ablation studies on the ACDC dataset, demonstrating the effectiveness of critical components of our method. Our results match the ground-truth boundary more consistently than the existing models. Our approach gains more accurate results on challenging 2D images for multi-organ segmentation. Compared with the state-of-the-art methods, our proposed method achieves superior performance in multi-organ segmentation tasks. Graphical Abstract The key process in medical image segmentation.

Tryptophan, an important link in regulating the complex network of skin immunology response in atopic dermatitis.

Atopic dermatitis (AD) is a common chronic relapsing inflammatory skin disease, of which the pathogenesis is a complex interplay between genetics and environment. Although the exact mechanisms of the disease pathogenesis remain unclear, the immune dysregulation primarily involving the Th2 inflammatory pathway and accompanied with an imbalance of multiple immune cells is considered as one of the critical etiologies of AD. Tryptophan metabolism has long been firmly established as a key regulator of immune cells and then affect the occurrence and development of many immune and inflammatory diseases. But the relationship between tryptophan metabolism and the pathogenesis of AD has not been profoundly discussed throughout the literatures. Therefore, this review is conducted to discuss the relationship between tryptophan metabolism and the complex network of skin inflammatory response in AD, which is important to elucidate its complex pathophysiological mechanisms, and then lead to the development of new therapeutic strategies and drugs for the treatment of this frequently relapsing disease.

TDD-UNet:Transformer with double decoder UNet for COVID-19 lesions segmentation.

The outbreak of new coronary pneumonia has brought severe health risks to the world. Detection of COVID-19 based on the UNet network has attracted widespread attention in medical image segmentation. However, the traditional UNet model is challenging to capture the long-range dependence of the image due to the limitations of the convolution kernel with a fixed receptive field. The Transformer Encoder overcomes the long-range dependence problem. However, the Transformer-based segmentation approach cannot effectively capture the fine-grained details. We propose a transformer with a double decoder UNet for COVID-19 lesions segmentation to address this challenge, TDD-UNet. We introduce the multi-head self-attention of the Transformer to the UNet encoding layer to extract global context information. The dual decoder structure is used to improve the result of foreground segmentation by predicting the background and applying deep supervision. We performed quantitative analysis and comparison for our proposed method on four public datasets with different modalities, including CT and CXR, to demonstrate its effectiveness and generality in segmenting COVID-19 lesions. We also performed ablation studies on the COVID-19-CT-505 dataset to verify the effectiveness of the key components of our proposed model. The proposed TDD-UNet also achieves higher Dice and Jaccard mean scores and the lowest standard deviation compared to competitors. Our proposed method achieves better segmentation results than other state-of-the-art methods.

Modeling the potential distribution of different types of Dendrocalamus sinicus, the strongest woody bamboo in the world, with MaxEnt model.

Climate change will significantly affect the distribution area of species. Through establishing distribution model, we can simulate the current and future potential distribution range and provide reference for the introduction and cultivation planning of rare or economic plants. Dendrocalamus sinicus, endemic to Yunnan Province of China, is the strongest woody bamboo in the world. In the present study, the MaxEnt model was performed to simulate the distribution of different types of D. sinicus in China and neighboring countries or regions. The results suggested that the suitable distribution range of "straight type", the main type for cultivation and utilization, was 8°-30°N and 73°-122°E under the current climate conditions, while the potential distribution range of "bending type" was 6°-31°N and 79°-109°E. The two most key climate variables associated with distribution of "straight type" were "Temperature Annual Range" with 36.6% contribution rate and "Temperature Seasonality" (32.4%), while "Isothermality" (47.8%) and "Precipitation of Driest Month" (24.8%) for "bending type". Under different climate change scenarios (SSP1-2.6, SSP5-8.5) and periods (2050, 2090), the potential distribution area of the "straight type" were apparently different, indicating that the distribution area of D. sinicus will be affected significantly by climate changes in the future. Our findings would be not only beneficial to understanding limiting factors for natural distribution of D. sinicus, but also helpful for further germplasm conservation, introduction and cultivation planning of this rare woody bamboo.

Potential roles of gut microbial tryptophan metabolites in the complex pathogenesis of acne vulgaris.

Acne vulgaris is a chronic inflammatory skin disease in which the influence of gut microbiota has been implicated but without clarification of mechanisms. Gut microbiota may exert such an influence via metabolites, particularly those of tryptophan. End metabolites of tryptophan activate receptors, including aryl hydrocarbon, G protein-coupled, and pregnane X receptors to stabilize the immune microenvironment and intestinal mucosal homeostasis. Any impact on the pathogenesis of acne vulgaris remains unclear. The current review collates recent advances concerning potential roles of tryptophan metabolism in mediating skin inflammation, follicular sebaceous gland function and intestinal permeability, all of which influence the pathogenesis of acne vulgaris. The aim was to improve understanding of the pathogenesis of acne vulgaris and to expose therapeutic opportunities.

A regularization-driven Mean Teacher model based on semi-supervised learning for medical image segmentation.

Objective.A semi-supervised learning method is an essential tool for applying medical image segmentation. However, the existing semi-supervised learning methods rely heavily on the limited labeled data. The generalization performance of image segmentation is improved to reduce the need for the number of labeled samples and the difficulty of parameter tuning by extending the consistency regularization.Approach.We propose a new regularization-driven Mean Teacher model based on semi-supervised learning for medical image segmentation in this work. We introduce a regularization-driven strategy with virtual adversarial training to improve segmentation performance and the robustness of the Mean Teacher model. We optimize the unsupervised loss function and the regularization term with an entropy minimum to smooth the decision boundary.Main results.We extensively evaluate the proposed method on the International Skin Imaging Cooperation 2017(ISIC2017) and COVID-19 CT segmentation datasets. Our proposed approach gains more accurate results on challenging 2D images for semi-supervised medical image segmentation. Compared with the state-of-the-art methods, the proposed approach has significantly improved and is superior to other semi-supervised segmentation methods.Significance.The proposed approach can be extended to other medical segmentation tasks and can reduce the burden of physicians to some extent.

The influence of benzoyl peroxide on skin microbiota and the epidermal barrier for acne vulgaris.

The disordered skin microbiome has been reported to contribute to the pathogenesis of acne vulgaris, for which benzoyl peroxide (BPO) has long been recommended as the first-line therapy. However, there are no data regarding the effect of BPO treatment on skin microbiota and the epidermal barrier in young adults with acne vulgaris. Thirty-three patients with acne vulgaris and 19 healthy controls were enrolled in the study. All patients received topical treatment with BPO 5% gel for 12 weeks. The epidermal barrier was analyzed at baseline and after treatment. Microbial diversity was analyzed using a high-throughput sequencing approach targeting the V3-V4 region of 16S rRNA genes. After receiving treatment with BPO, patients had significant improvement in their Global Acne Grading System (GAGS) score, porphyrin, and red areas (p < 0.05), and the presence of sebum, stratum corneum hydration (SCH), and transepidermal water loss (TEWL) increased (p < 0.05). When compared with baseline, microbial diversity was significantly reduced after treatment, as calculated by the goods coverage (p = 0.0017), Shannon (p = 0.0094), and Simpson (p = 0.0017) diversity indices. The prevalence of the genus Cutibacterium (before treatment: 5.64 [3.50, 7.78] vs. after treatment: 2.43 [1.81, 3.05], p = 0.011) was significantly reduced after treatment while Staphylococcus (before treatment: 43.80 [36.62, 50.98] vs. after treatment: 53.38 [44.88, 61.87], p = 0.075) tended to increase. The abundance of Staphylococcus was negatively associated with SCH (p = 0.008, r = -0.286). Despite its contribution to an improved GAGS score, BPO treatment for acne vulgaris may reduce microbial diversity and damage the epidermal barrier.

Modelling and predicting population of core fungi through processing parameters in spontaneous starter (Daqu) fermentation.

Traditional fermented foods are usually produced by spontaneous fermentation with multiple microorganisms. Environmental factors play important roles in microbial succession. However, it is still unclear how the processing parameters regulate the microbiota during fermentation. Here, we reveal the effects of processing parameters on the core microbiota in spontaneous fermentation of Chinese liquor starter. Rhizopus, Pichia, Wickerhamomyces, Saccharomycopsis, Aspergillus and Saccharomyces were identified as core microbiota using amplicon sequencing and metaproteomics analysis. Fermentation moisture gradually decreased from 34.8% to 14.2%, and fermentation temperature varied between 17.0 °C and 35.3 °C during the fermentation. Mantel test showed that fermentation moisture (P < 0.001) and fermentation temperature (P < 0.05) significantly affected the core microbiota. Moreover, structural equation modelling analysis indicated that fermentation moisture (P < 0.001) and fermentation temperature (P < 0.001) were respectively influenced by the processing parameters, room humidity and room temperature. The succession of Rhizopus, Pichia, Wickerhamomyces, Saccharomycopsis and Aspergillus were significantly affected by room humidity (P < 0.05), and the succession of Saccharomyces was significantly affected by room temperature (P < 0.001). Further, models were constructed to predict the population of core microbiota by room humidity and room temperature, using Gaussian process regression and linear regression (P < 0.05). This work would be beneficial for regulating microorganisms via controlling processing parameters in spontaneous food fermentations.

Transcriptome-wide analysis reveals core transcriptional regulators associated with culm development and variation in Dendrocalamus sinicus, the strongest woody bamboo in the world.

Transcription factors (TFs) play indispensable roles in plant development and stress responses. As the largest woody bamboo species in the world, Dendrocalamus sinicus is endemic to Yunnan Province, China, and possesses two natural variants characterized by culm shape, namely straight or bent culms. Understanding the transcriptional regulation network of D. sinicus provides a unique opportunity to clarify the growth and development characteristics of woody bamboos. In this study, 10,236 TF transcripts belonging to 57 families were identified from transcriptome data of two variants at different developmental stages, from which we constructed a transcriptional regulatory network and unigene-coding protein-TFs interactive network of culm development for this attractive species. Gene function enrichment analysis revealed that hormone signaling and MAPK signaling pathways were two most enriched pathways in TF-regulated network. Based on PPI analysis, 50 genes interacting with nine TFs were screened as the core regulation components related to culm development. Of them, 18 synergistic genes of seven TFs, including nuclear cap-binding protein subunit 1, transcription factor GTE9-like, and ATP-dependent DNA helicase DDX11 isoform X1, involved in culm-shape variation. Most of these genes would interact with MYB, C3H, and ARF transcription factors. Six members with two each from ARF, C3H, and MYB transcription factor families and six key interacting genes (IAA3, IAA19, leucine-tRNA ligase, nuclear cap-binding protein subunit 1, elongation factor 2, and coiled-coil domain-containing protein 94) cooperate with these transcription factors were differentially expressed at development stage of young culms, and were validated by quantitative PCR. Our results represent a crucial step towards understanding the regulatory mechanisms of TFs involved in culm development and variation of D. sinicus.

The Effect of Intense Pulsed Light on the Skin Microbiota and Epidermal Barrier in Patients with Mild to Moderate Acne Vulgaris.

BACKGROUND AND OBJECTIVES: The skin microbiota partly determined by epidermal barrier plays an important role in acne vulgaris and intense pulsed light (IPL) has been verified as a safe and effective therapeutic option for this disease. Nevertheless, the exact role of the IPL treatment on the skin microbiota and epidermal barrier for patients with acne vulgaris remains unclear. This article was designed to solve this problem. STUDY DESIGN/MATERIALS AND METHODS: Nineteen healthy controls and 20 patients with mild to moderate acne were enrolled in this study, who received IPL treatment for 12 weeks. The epidermal barrier and skin samples were collected at baseline and after treatment. The microbial diversity was analyzed based on a high-throughput sequencing approach, which targets the V3-V4 region of the bacteria 16S ribosomal RNA genes. RESULTS: After treatment of IPL, the Global Acne Grading System (GAGS) scores, sebum, sclererythrin, and red area of patients were significantly improved by IPL treatment (P < 0.05). Although there was no difference in microbiota diversity before and after IPL treatment, the Nonmetric Multidimension Scaling (NMDS) analysis showed that the samples of the acne patients before and after treatment could be divided into two different sets by skin microbiota (P = 0.011), which could be verified by heatmap analysis. Moreover, we found that the relative abundance of Staphylococcus epidermidis (S. epidermidis) significantly increased, but Cutibacterium acnes (C. acnes) decreased after IPL treatment. The sebum concentration was positively correlated with PH value (R = 0.525, P = 0.017), and the GAGS was positively associated with both sclererythrin (R = 0.477, P = 0.002) and red area (R = -0.503, P = 0.001). CONCLUSIONS: IPL could successfully improve the GAGS scores of acne vulgaris, as well as regulate the equilibrium between C. acnes and S. epidermidis, and inhibit the sebum secretion. Lasers Surg. Med. © 2021 The Authors. Lasers in Surgery and Medicine published by Wiley Periodicals LLC.

Clinicopathological Features, Prognostic Factors, Survival Trends, and Treatment of Malignant Ovarian Germ Cell Tumors: A SEER Database Analysis.

OBJECTIVE: The aim of this study was to investigate the clinicopathological prognostic factors of malignant ovarian germ cell tumors (MOGCT) and evaluate the survival trends of MOGCT by histotype. METHODS: We extracted data on 1,963 MOGCT cases diagnosed between 2000 and 2014 from the Surveillance, Epidemiology, and End Results (SEER) database and the histological classification of MOGCT, including 5 categories: dysgerminoma, embryonal carcinoma (EC), yolk sac tumor, malignant teratoma, and mixed germ cell tumor. We examined overall and disease-specific survival of the 5 histological types. Kaplan-Meier and Cox proportional hazards regression models were used to estimate survival curves and prognostic factors. We also estimated survival curves of MOGCT according to different treatments. RESULTS: There was a significant difference in prognosis among different histological classifications. Age, histotype, grade, SEER stage, and surgery were independent prognostic factors for survival of patients with MOGCT. For all histotypes, 1-, 3-, and 5-year survival rate estimates were >85%, except for EC, which had the worst outcomes at 1 year (55.6%), 3 years (44.4%), and 5 years (33.3%). In the distant SEER stage, both chemotherapy and surgery were associated with improved survival outcomes compared with surgery- and chemotherapy-only groups. CONCLUSIONS: Dysgerminoma patients had the most favorable outcomes, whereas EC patients had the worst survival. A young age, low grade, and surgery were all significant predictors for improved survival. In contrast, a distant SEER stage was a risk factor for poor survival. Chemotherapy combined with surgery contributed to longer survival times of patients with MOGCT in the distant SEER stage.

Cesarean scar pregnancy combined with arteriovenous malformation successfully treated with transvaginal fertility-sparing surgery: A case report and literature review.

INTRODUCTION: A cesarean scar pregnancy (CSP), when combined with an arteriovenous malformation (AVM), is a rare, but potentially life-threatening condition that may be associated with uncontrolled hemorrhage. Hysterectomy is indicated when conservative treatment fails. Preservation of fertility is challenging. PATIENT CONCERNS: We reported a 33-year-old woman with a CSP combined with an AVM who failed methotrexate administration as conservative treatment. DIAGNOSES: A CSP combined with an AVM was diagnosed via three-dimensional color Doppler angiogram and magnetic resonance imaging. INTERVENTIONS: Transvaginal removal of the ectopic gestation and repair of the uterine defect was performed without incident. OUTCOMES: The fertility of the patient was preserved and hysterectomy was avoided. CONCLUSION: Transvaginal fertility-sparing surgery may be successfully performed to prevent hysterectomy when conservative treatment fails in patients with a CSP combined with an AVM.