Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration.

The prowess that makes few-shot learning desirable in medical image analysis is the efficient use of the support image data, which are labelled to classify or segment new classes, a task that otherwise requires substantially more training images and expert annotations. This work describes a fully 3D prototypical few-shot segmentation algorithm, such that the trained networks can be effectively adapted to clinically interesting structures that are absent in training, using only a few labelled images from a different institute. First, to compensate for the widely recognised spatial variability between institutions in episodic adaptation of novel classes, a novel spatial registration mechanism is integrated into prototypical learning, consisting of a segmentation head and an spatial alignment module. Second, to assist the training with observed imperfect alignment, support mask conditioning module is proposed to further utilise the annotation available from the support images. Extensive experiments are presented in an application of segmenting eight anatomical structures important for interventional planning, using a data set of 589 pelvic T2-weighted MR images, acquired at seven institutes. The results demonstrate the efficacy in each of the 3D formulation, the spatial registration, and the support mask conditioning, all of which made positive contributions independently or collectively. Compared with the previously proposed 2D alternatives, the few-shot segmentation performance was improved with statistical significance, regardless whether the support data come from the same or different institutes.

Reduced-visit antenatal care model combined with telemedicine for low-risk pregnant women: protocol for a randomised controlled trial.

INTRODUCTION: Antenatal care (ANC) is a critical measure to reduce maternal and perinatal morbidity and mortality. However, there are issues of too many visits and cumbersome procedures of ANC in many maternity hospitals of China. In the past 2 years, reduced-visit ANC models combined with remote monitoring have been recommended and implemented at most hospitals in China during the COVID-19 pandemic. Nevertheless, due to limited evaluations of the cost-effectiveness, policy-makers remain confused on how to appropriately integrate online delivery strategies with routine models to improve ANC quality and efficiency sustainably at scale. This trial aims to evaluate the effectiveness, acceptability and cost of a reduced-visit ANC model combined with telemedicine. METHODS AND ANALYSIS: A single-blind, randomised controlled trial will be conducted among low-risk pregnant women at Peking University Third Hospital in Beijing. 1476 patients (738 in each group) would be required, and they will be randomly assigned in a 1:1 ratio to receive the reduced-visit ANC combined with telemedicine services or the routine ANC. The primary outcome is the composite rate of adverse maternal and perinatal outcomes which will be extracted from the medical records. Secondary outcomes include acceptability of ANC models, which is assessed by satisfaction with ANC, pregnancy-related stress and ANC costs measured from the perspectives of both service providers and demanders. Both intention-to-treat and per-protocol analyses will be performed. Non-inferiority tests will be used to compare the two ANC models for the primary outcome. A cost-effectiveness analysis comparing the two ANC models will be conducted by estimating the incremental cost-effectiveness ratios. ETHICS AND DISSEMINATION: This study was approved by the ethical review committee of the Peking University Third Hospital (Beijing, China). The results of this study will be published in peer-reviewed scientific journals and presented at relevant academic conferences. TRIAL REGISTRATION NUMBER: NCT05290467.

Effect of naringenin on the anti-inflammatory, vascularization, and osteogenesis differentiation of human periodontal ligament stem cells via the stromal cell-derived factor 1/C-X-C motif chemokine receptor 4 signaling axis stimulated by lipopolysaccharide.

OBJECTIVES: This study aimed to investigate how naringenin (Nar) affected the anti-inflammatory, vascula-rization, and osteogenesis differentiation of human periodontal ligament stem cells (hPDLSCs) stimulated by lipopolysaccharide (LPS) and to preliminarily explore the underlying mechanism. METHODS: Cell-counting kit-8 (CCK8), cell scratch test, and Transwell assay were used to investigate the proliferation and migratory capabilities of hPDLSCs. Alkaline phosphatase (ALP) staining, alizarin red staining, lumen-formation assay, enzyme-linked immunosorbent assay, quantitative timed polymerase chain reaction, and Western blot were used to measure the expression of osteopontin (OPN), Runt-related transcription factor 2 (RUNX2), vascular endothlial growth factor (VEGF), basic fibroblast growth factor (bFGF), von Willebrand factor (vWF), tumor necrosis factor-α (TNF-α), and interleukin (IL)-6. RESULTS: We observed that 10 µmol/L Nar could attenuate the inflammatory response of hPDLSCs stimulated by 10 µg/mL LPS and promoted their proliferation, migration, and vascularization differentiation. Furthermore, 0.1 µmol/L Nar could effectively restore the osteogenic differentiation of inflammatory hPDLSCs. The effects of Nar's anti-inflammatory and promotion of osteogenic differentiation significantly decreased and inflammatory vascularization differentiation increased after adding AMD3100 (a specific CXCR4 inhibitor). CONCLUSIONS: Nar demonstrated the ability to promote the anti-inflammatory, vascularization, and osteogenic effects of hPDLSCs stimulated by LPS, and the ability was associated with the stromal cell-derived factor/C-X-C motif chemokine receptor 4 signaling axis.

Construction of Artificial Light-Harvesting Systems Based on Aggregation-Induced Emission Type Supramolecular Self-Assembly Metallogels.

A method for preparing new artificial light-harvesting systems (ALHSs) based on supramolecular metallogels was proposed. Various metal ions were introduced into a solution of a bi-benzimidazole compound (P) in ethylene glycol, and P exhibited high selectivity toward Al3+, as indicated by the noticeable red shift (49 nm) observed in the fluorescence spectra of P after the addition of Al3+. Interestingly, the gelator, P, could self-assemble into a stable supramolecular gel (P-gel) that exhibits strong aggregation-induced emission in ethylene glycol. Thus, two ALHSs were successfully prepared in a gel environment. The P-Al3+ assembly acts as the donor in the ALHSs, while BODIPY 505/515 (BDP) and rhodamine 6G (Rh6G), which are loaded onto the P-Al3+ assembly, act as acceptors. In these two diverse systems, the occurrence of an energy transfer process is confirmed from the P-Al3+ assembly to BDP and Rh6G. The findings of this study will enable the design and fabrication of ALHSs.

Artificial light-harvesting systems based on supramolecular self-assembly multi-component metallogels.

This paper proposes a strategy for fabricating new artificial light-harvesting systems (ALHSs) based on supramolecular multi-component metallogels. Al3+ was introduced into a solution of an acylhydrazone compound (L) in DMSO or DMF to form the L-Al3+ assembly. After adding Al3+ to the L solution, a noticeable blue shift appeared in the fluorescence spectra of L. Moreover, L could form a gel (L-B-gel) with 1,3:2,4-dibenzylidene sorbitol (B) in a DMSO-H2O binary solution. Finally, we obtained a multi-component metallogel (L-Al3+-B-gel) and successfully fabricated two ALHSs (L-Al3+/rhodamine 6G (Rh6G) and L-Al3+/rhodamine B (RhB)). In these systems, the L-Al3+ supramolecular assembly acts as the donor, while Rh6G and RhB act as acceptors. Additionally, we confirmed an energy-transfer process from the L-Al3+ component to Rh6G and RhB separately. The proposed fabrication strategy will facilitate the development of ALHSs.

Ultra-confined Propagating Exciton-Plasmon Polaritons Enabled by Cavity-Free Strong Coupling: Beating Plasmonic Trade-Offs.

Hybrid coupling systems consisting of transition metal dichalcogenides (TMD) and plasmonic nanostructures have emerged as a promising platform to explore exciton-plasmon polaritons. However, the requisite cavity/resonator for strong coupling introduces extra complexities and challenges for waveguiding applications. Alternatively, plasmonic nano-waveguides can also be utilized to provide a non-resonant approach for strong coupling, while their utility is limited by the plasmonic confinement-loss and confinement-momentum trade-offs. Here, based on a cavity-free approach, we overcome these constraints by theoretically strong coupling of a monolayer TMD to a single metal nanowire, generating ultra-confined propagating exciton-plasmon polaritons (PEPPs) that beat the plasmonic trade-offs. By leveraging strong-coupling-induced reformations in energy distribution and combining favorable properties of surface plasmon polaritons (SPPs) and excitons, the generated PEPPs feature ultra-deep subwavelength confinement (down to 1-nm level with mode areas ~ 10-4 of λ2), long propagation length (up to ~ 60 µm), tunable dispersion with versatile mode characters (SPP- and exciton-like mode characters), and small momentum mismatch to free-space photons. With the capability to overcome the trade-offs of SPPs and the compatibility for waveguiding applications, our theoretical results suggest an attractive guided-wave platform to manipulate exciton-plasmon interactions at the ultra-deep subwavelength scale, opening new horizons for waveguiding nano-polaritonic components and devices.

Transfer Learning for Modeling Plasmonic Nanowire Waveguides.

Retrieving waveguiding properties of plasmonic metal nanowires (MNWs) through numerical simulations is time- and computational-resource-consuming, especially for those with abrupt geometric features and broken symmetries. Deep learning provides an alternative approach but is challenging to use due to inadequate generalization performance and the requirement of large sets of training data. Here, we overcome these constraints by proposing a transfer learning approach for modeling MNWs under the guidance of physics. We show that the basic knowledge of plasmon modes can first be learned from free-standing circular MNWs with computationally inexpensive data, and then reused to significantly improve performance in predicting waveguiding properties of MNWs with various complex configurations, enabling much smaller errors (~23-61% reduction), less trainable parameters (~42% reduction), and smaller sets of training data (~50-80% reduction) than direct learning. Compared to numerical simulations, our model reduces the computational time by five orders of magnitude. Compared to other non-deep learning methods, such as the circular-area-equivalence approach and the diagonal-circle approximation, our approach enables not only much higher accuracies, but also more comprehensive characterizations, offering an effective and efficient framework to investigate MNWs that may greatly facilitate the design of polaritonic components and devices.

Effects of Wx Genotype, Nitrogen Fertilization, and Temperature on Rice Grain Quality.

Quality is a complex trait that is not only the key determinant of the market value of the rice grain, but is also a major constraint in rice breeding. It is influenced by both genetic and environmental factors. However, the combined effects of genotypes and environmental factors on rice grain quality remain unclear. In this study, we used a three-factor experimental design to examine the grain quality of different Wx genotypes grown under different nitrogen fertilization and temperature conditions during grain development. We found that the three factors contributed differently to taste, appearance, and nutritional quality. Increased Wx function and nitrogen fertilization significantly reduced eating quality, whereas high temperature (HT) had almost no effect. The main effects of temperature on appearance quality and moderate Wx function at low temperatures (LTs) contributed to better appearance, and higher nitrogen fertilization promoted appearance at HTs. With regard to nutritional quality, Wx alleles promoted amylose content (AC) as well as starch-lipids content (SLC); nitrogen fertilization increased storage protein content (PC); and higher temperature increased lipid content but decreased the PC. This study helps to broaden the understanding of the major factors that affect the quality of rice and provides constructive messages for rice quality improvement and the cultivation of high-quality rice varieties.

Preparation of a multifunctional organogel and its electrochemical properties.

A facile methodology to fabricate a highly elastic organogel for supercapacitors is demonstrated. A stable polymer organogel was obtained in DMSO by a simple esterification reaction. This organogel showed high mechanical performance, flexibility, high elasticity, luminous performance and conductivity, as well as high potential values for application in the energy sector.

qFC6, a major gene for crude fat content and quality in rice.

KEY MESSAGE: qFC6, a major quantitative trait locus for rice crude fat content, was fine mapped to be identical with Wx. FC6 negatively regulates crude fat content and rice quality. Starch, protein and lipids are the three major components in rice endosperm. The lipids content in rice influences both storage and quality. In this study, we identified a quantitative trait locus (QTL), qFC6, for crude fat (free lipids) content through association analysis and linkage analysis. Gene-based association analysis revealed that LOC_Os06g04200, also known as Wx, was the candidate gene for qFC6. Complementation and knockout transgenic lines revealed that Wx negatively regulates crude fat content. Lipid composition and content analysis by gas chromatography and taste evaluation analysis showed that FC6 positively influenced bound lipids content and negatively affected both free lipids content and taste. Besides, higher free lipids content rice varieties exhibit more lustrous appearance after cooking and by adding extra oil during cooking could improve rice luster and taste score, indicating that higher free lipids content may make rice more lustrous and delicious. Together, we cloned a QTL coordinating rice crude fat content and eating quality and assisted in uncovering the genetic basis of rice lipid content and in the improvement of rice eating quality.

Task model-specific operator skill assessment in routine fetal ultrasound scanning.

PURPOSE: For highly operator-dependent ultrasound scanning, skill assessment approaches evaluate operator competence given available data, such as acquired images and tracked probe movement. Operator skill level can be quantified by the completeness, speed, and precision of performing a clinical task, such as biometry. Such clinical tasks are increasingly becoming assisted or even replaced by automated machine learning models. In addition to measurement, operators need to be competent at the upstream task of acquiring images of sufficient quality. To provide computer assistance for this task requires a new definition of skill. METHODS: This paper focuses on the task of selecting ultrasound frames for biometry, for which operator skill is assessed by quantifying how well the tasks are performed with neural network-based frame classifiers. We first develop a frame classification model for each biometry task, using a novel label-efficient training strategy. Once these task models are trained, we propose a second task model-specific network to predict two skill assessment scores, based on the probability of identifying positive frames and accuracy of model classification. RESULTS: We present comprehensive results to demonstrate the efficacy of both the frame-classification and skill-assessment networks, using clinically acquired data from two biometry tasks for a total of 139 subjects, and compare the proposed skill assessment with metrics of operator experience. CONCLUSION: Task model-specific skill assessment is feasible and can be predicted by the proposed neural networks, which provide objective assessment that is a stronger indicator of task model performance, compared to existing skill assessment methods.

A physics-based machine learning approach for modeling the complex reflection coefficients of metal nanowires.

Metal nanowires are attractive building blocks for next-generation plasmonic devices with high performance and compact footprint. The complex reflection coefficients of the plasmonic waveguides are crucial for estimation of the resonating, lasing, or sensing performance. By incorporating physics-guided objective functions and constraints, we propose a simple approach to convert the specific reflection problem of nanowires to a universal regression problem. Our approach is able to efficiently and reliably determine both the reflectivity and reflection phase of the metal nanowires with arbitrary geometry parameters, working environments, and terminal shapes, merging the merits of the physics-based modeling and the data-driven modeling. The results may provide valuable reference for building comprehensive datasets of plasmonic architectures, facilitating theoretical investigations and large-scale designs of nanophotonic components and devices.

Boronate affinity-based template-immobilization surface imprinted quantum dots as fluorescent nanosensors for selective and sensitive detection of myricetin.

In order to prepare a kind of efficient fluorescence sensors for determination of cis-diol-containing flavonoids, novel imprinted quantum dots for myricetin (Myr) were prepared based on boronate affinity-based template-immobilization surface imprinting. The obtained boronate affinity-based surface imprinted silica (imprinted APBA-functionalized CdTe QDs) was used as recognition elements. The quantum dots were used as signal-transduction materials. Under the optimum conditions, according to fluorescence quenching of imprinted APBA-functionalized CdTe QDs by Myr, the imprinting factor (IF) for Myr was evaluated to be 7.88. The result indicated that the boronate affinity functionalized quantum dots coated with imprinted silica were successfully prepared. The prepared imprinted APBA-functionalized CdTe QDs exhibited good sensitivity and selectivity for Myr. The fluorescence intensity was inversely proportional to the concentration of Myr in the 0.30-40 µM concentration range. And its detection limit was obtained to be 0.08 µM. Using the fluorescence sensors, the detection of Myr in real samples was successfully carried out, and the concentration of Myr in green tea and apple juice samples was evaluated to be 2.26 mg/g and 0.73 mg/g, respectively. The recoveries for the spiked green tea and apple juice samples were 95.2-105.0% and 91.5-111.0%, respectively. This study also provides an efficient fluorescent detection method for cis-diol-containing flavonoids in real samples.

A new strategy for constructing artificial light-harvesting systems: supramolecular self-assembly gels with AIE properties.

An artificial light-harvesting system (ALHS) has been designed and constructed based on supramolecular organogels made of a simple hydrazide-functionalized benzimidazole derivative (HB), as well as the fluorescent dye rhodamine B (RhB). RhB acted as a good acceptor to realize the energy-transfer process with good efficiency based on a HB/RhB assembly, which showed considerable fluorescence resonance energy transfer (FRET) efficiency of 53% for the energy transfer process. Remarkably, the obtained system showed superior color conversion abilities, converting blue light into orange light. By properly tuning the donor to acceptor ratio, bright orange light emission was achieved with a high fluorescence quantum yield of 35.5%. This system exhibited promise for applications relating to visible-light photo-transformation.

Naringenin promotes SDF-1/CXCR4 signaling pathway in BMSCs osteogenic differentiation.

INTRODUCTION: Naringenin, a dihydro-flavonoid compound that shows chemotactic activity, may have a good application prospect in repairing bone tissue, but its specific mechanism in bone regeneration, especially the osteogenic differentiation of stem cells, needs for a further study. The aim of this study was to investigate the effect of naringenin on the osteogenic differentiation and its roles in the C-X-C chemokine receptor type 4/stromal cell-derived factor 1 (SDF-1/CXCR4) signal pathway of bone marrow-derived mesenchymal stem cells (BMSCs). MATERIAL AND METHODS: BMSCs were harvested from the femurs and tibias of 4-to-6-week-old male Sprague-Dawley rats. Cell Counting kit-8 assay was used to determine cytotoxicity of naringenin. Alkaline phosphatase (ALP) activity was measured in cell's precipitates and alizarin-red staining was performed to determine the osteogenic differentiation capacity of the BMSCs. Real-time polymerase chain reaction, enzyme-linked immunosorbent assay and western blotting were adopted to determine the expression of genes and proteins. RESULTS: The cellular morphology was spindle-shaped, and arranged in radial and whorled patterns. The flow cytometric analysis have confirmed the presence of characteristic surface proteins in the harvested BMSCs. Different concentrations (0-200 µg/ml) of naringenin have no influence on the viability and proliferation rate of the BMSCs. The highest ALP activity was found at culture day 7 and 9 when the concentration of naringenin was 75 and 100 µg/ml. Positive red or dark red stained cells with mineralized nodules can be observed on day 14. The expression of ALP, Runt-related transcription factor 2, CXCR4 and SDF-1a at the gene and protein levels in naringenin-treated cells were significantly higher than those in the control cells. Moreover, AMD3100, an inhibitor of CXCR4, suppressed the expression of the studied genes and proteins. CONCLUSIONS: Naringenin does not show toxic effect on BMSCs. Naringenin promotes the expression of the SDF-1a gene and protein via the SDF-1/CXCR4 signaling pathway. A better understanding of the mechanisms of naringenin action would be helpful for developing specific therapeutic strategies to improve bone regeneration after injuries.

[Naringenin promotes osteogenic differentiation of BMSCs via SDF-1α/CXCR4 signaling axis].

PURPOSE: To explore the influence of naringenin on osteogenic differentiation of bone mesenchymal stem cells(BMSCs), and the role of SDF-1α/CXCR4 signaling axis in the osteogenic differentiation by naringenin. METHODS: BMSCs of the rats were isolated,cultured and tested. CCK-8 assay was used to explore the proliferation ability of BMSCs in different concentrations of naringenin, and alkaline phosphatase(ALP) activity was detected. RT-qPCR was used to detect the mRNA expression of ALP, OCN, CXCR4 and SDF-1α in different groups. The expressions of CXCR4 and SDF-1α protein in BMSCs during osteogenic differentiation in different experimental groups were detected by ELISA. SPSS 21.0 software package was used for statistical analysis of the data. RESULTS: The results of cell identification showed that the cultured cells were BMSCs. At 1 d and 3 d, all concentrations of naringenin had no significant effect on the proliferation of BMSCs; and at 5 d, 50 µg/mL of naringenin promoted proliferation of BMSCs；furthermore, at 7 d, all concentrations of naringenin promoted proliferation of BMSCs(P＜0.05). ALP activity value gradually increased in each concentration over time. From the RT-qPCR experiment, the mRNA expression of ALP, OCN, CXCR4 and SDF-1α in the naringenin group and the osteogenic induction group was significantly increased compared with the medium group(P＜0.05). ELISA assay showed that the protein expressions of CXCR4 and SDF-1α increased gradually in the four groups as time went on and the expression of two proteins was the highest in 100 µg/mL naringenin group. CONCLUSIONS: Naringenin can promote the proliferation and osteogenic differentiation of BMSCs. SDF-1α/CXCR4 signaling axis is involved in the osteogenic differentiation of BMSCs by naringenin,particularly in the early stage of BMSCs osteogenic differentiation.

Fine mapping of qWCR7, a grain chalkiness QTL in rice.

Chalkiness is one of the key determinants of rice quality and is a highly undesirable trait for breeding and marketing. In this study, qWCR7, a major quantitative trait locus (QTL) of white-core rate (WCR), was genetically validated using a BC3F2 segregation population and further fine mapped using a near isogenic line (NIL) population, of which both were derived from a cross between the donor parent DL208 and the recurrent parent ZS97. qWCR7 was finally narrowed to a genomic interval of ~ 68 kb, containing seven annotated genes. Among those, two genes displayed markedly different expression levels in endosperm of NILs. Transcriptome analysis showed that the synthesis and accumulation of metabolites played a key role in chalkiness formation. The contents of storage components and expression levels of related genes were detected, suggesting that starch and storage protein were closely related to white-core trait. Our findings have laid the foundation of map-based cloning of qWCR7, which may have potential value in quality improvement during rice breeding. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01260-x.

Differentiating Operator Skill during Routine Fetal Ultrasound Scanning using Probe Motion Tracking.

In this paper, we consider differentiating operator skill during fetal ultrasound scanning using probe motion tracking. We present a novel convolutional neural network-based deep learning framework to model ultrasound probe motion in order to classify operator skill levels, that is invariant to operators' personal scanning styles. In this study, probe motion data during routine second-trimester fetal ultrasound scanning was acquired by operators of known experience levels (2 newly-qualified operators and 10 expert operators). The results demonstrate that the proposed model can successfully learn underlying probe motion features that distinguish operator skill levels during routine fetal ultrasound with 95% accuracy.

Mapping anatomical related entities to human body parts based on wikipedia in discharge summaries.

*: Background Consisting of dictated free-text documents such as discharge summaries, medical narratives are widely used in medical natural language processing. Relationships between anatomical entities and human body parts are crucial for building medical text mining applications. To achieve this, we establish a mapping system consisting of a Wikipedia-based scoring algorithm and a named entity normalization method (NEN). The mapping system makes full use of information available on Wikipedia, which is a comprehensive Internet medical knowledge base. We also built a new ontology, Tree of Human Body Parts (THBP), from core anatomical parts by referring to anatomical experts and Unified Medical Language Systems (UMLS) to make the mapping system efficacious for clinical treatments. *: Result The gold standard is derived from 50 discharge summaries from our previous work, in which 2,224 anatomical entities are included. The F1-measure of the baseline system is 70.20%, while our algorithm based on Wikipedia achieves 86.67% with the assistance of NEN. *: Conclusions We construct a framework to map anatomical entities to THBP ontology using normalization and a scoring algorithm based on Wikipedia. The proposed framework is proven to be much more effective and efficient than the main baseline system.

Mitochondrial translocation of estrogen receptor ß affords resistance to oxidative insult-induced apoptosis and contributes to the pathogenesis of endometriosis.

Endometriosis is the major cause of female infertility and has been linked to the action of estrogen and estrogen receptor (ER). A new pool of ERß locates within mitochondria, which regulates the endometriotic cell withstanding external insults, but its effect remains controversial. We hypothesize that mitochondrial estrogen receptor ERß (mtERß) is a pivotal regulator in estradiol-mediated cell protection leading to the endometriotic progression. We observed elevated levels of ERß in the endometriotic tissues. A dramatic increase of ERß in mitochondria (mtERß) was found in the ectopic endometriotic tissues, or the estradiol-primed primary endometriotic cells. We analyzed the mtERß-specific overexpressing clone (mtsERß), which exhibited higher mitochondrial bioenergetics and lower reactive oxygen species (ROS) generation. The mtsERß-overexpressed endometriotic cells displayed an enhanced migration phenotype, whereas significantly attenuated migration by mitochondrial respiratory inhibitor (oligomycin) or ERß deficiency by shERß. Further investigations revealed that ERß directly modulated mitochondrial DNA (mtDNA) gene expression by interacting with mtDNA D-loop and polymerase γ. The mtsERß afforded a resistance to oxidative insult-induced apoptosis through the induction of the ROS scavenger enzyme Mn-superoxide dismutase and anti-apoptotic protein Bcl-2. Collectively, the demonstration of mtERß responses in restoration of mitochondrial bioenergetics and inhibition of mitochondria-dependent apoptotic events provides insight into the pathogenesis of endometriosis, suggesting ERß-selective estrogen receptor modulator may serve as novel therapeutics of endometriosis in the future.