Preoperative Differentiation of HER2-Zero and HER2-Low from HER2-Positive Invasive Ductal Breast Cancers Using BI-RADS MRI Features and Machine Learning Modeling.

BACKGROUND: Accurate determination of human epidermal growth factor receptor 2 (HER2) is important for choosing optimal HER2 targeting treatment strategies. HER2-low is currently considered HER2-negative, but patients may be eligible to receive new anti-HER2 drug conjugates. PURPOSE: To use breast MRI BI-RADS features for classifying three HER2 levels, first to distinguish HER2-zero from HER2-low/positive (Task-1), and then to distinguish HER2-low from HER2-positive (Task-2). STUDY TYPE: Retrospective. POPULATION: 621 invasive ductal cancer, 245 HER2-zero, 191 HER2-low, and 185 HER2-positive. For Task-1, 488 cases for training and 133 for testing. For Task-2, 294 cases for training and 82 for testing. FIELD STRENGTH/SEQUENCE: 3.0 T; 3D T1-weighted DCE, short time inversion recovery T2, and single-shot EPI DWI. ASSESSMENT: Pathological information and BI-RADS features were compared. Random Forest was used to select MRI features, and then four machine learning (ML) algorithms: decision tree (DT), support vector machine (SVM), k-nearest neighbors (k-NN), and artificial neural nets (ANN), were applied to build models. STATISTICAL TESTS: Chi-square test, one-way analysis of variance, and Kruskal-Wallis test were performed. The P values <0.05 were considered statistically significant. For ML models, the generated probability was used to construct the ROC curves. RESULTS: Peritumoral edema, the presence of multiple lesions and non-mass enhancement (NME) showed significant differences. For distinguishing HER2-zero from non-zero (low + positive), multiple lesions, edema, margin, and tumor size were selected, and the k-NN model achieved the highest AUC of 0.86 in the training set and 0.79 in the testing set. For differentiating HER2-low from HER2-positive, multiple lesions, edema, and margin were selected, and the DT model achieved the highest AUC of 0.79 in the training set and 0.69 in the testing set. DATA CONCLUSION: BI-RADS features read by radiologists from preoperative MRI can be analyzed using more sophisticated feature selection and ML algorithms to build models for the classification of HER2 status and identify HER2-low. TECHNICAL EFFICACY: Stage 2.

Indoxyl sulphate-TNFα axis mediates uremic encephalopathy in rodent acute kidney injury.

Acute kidney injury (AKI) is often accompanied by uremic encephalopathy resulting from accumulation of uremic toxins in brain possibly due to impaired blood-brain barrier (BBB) function. Anionic uremic toxins are substrates or inhibitors of organic anionic transporters (OATs). In this study we investigated the CNS behaviors and expression/function of BBB OAT3 in AKI rats and mice, which received intraperitoneal injection of cisplatin 8 and 20 mg/kg, respectively. We showed that cisplatin treatment significantly inhibited the expressions of OAT3, synaptophysin and microtubule-associated protein 2 (MAP2), impaired locomotor and exploration activities, and increased accumulation of uremic toxins in the brain of AKI rats and mice. In vitro studies showed that uremic toxins neither alter OAT3 expression in human cerebral microvascular endothelial cells, nor synaptophysin and MAP2 expressions in human neuroblastoma (SH-SY5Y) cells. In contrast, tumour necrosis factor alpha (TNFα) and the conditioned medium (CM) from RAW264.7 cells treated with indoxyl sulfate (IS) significantly impaired OAT3 expression. TNFα and CM from IS-treated BV-2 cells also inhibited synaptophysin and MAP2 expressions in SH-SY5Y cells. The alterations caused by TNFα and CMs in vitro, and by AKI and TNFα in vivo were abolished by infliximab, a monoclonal antibody designed to intercept and neutralize TNFα, suggesting that AKI impaired the expressions of OAT3, synaptophysin and MAP2 in the brain via IS-induced TNFα release from macrophages or microglia (termed as IS-TNFα axis). Treatment of mice with TNFα (0.5 mg·kg-1·d-1, i.p. for 3 days) significantly increased p-p65 expression and reduced the expressions of Nrf2 and HO-1. Inhibiting NF-κB pathway, silencing p65, or activating Nrf2 and HO-1 obviously attenuated TNFα-induced downregulation of OAT3, synaptophysin and MAP2 expressions. Significantly increased p-p65 and decreased Nrf2 and HO-1 protein levels were also detected in brain of AKI mice and rats. We conclude that AKI inhibits the expressions of OAT3, synaptophysin and MAP2 due to IS-induced TNFα release from macrophages or microglia. TNFα impairs the expressions of OAT3, synaptophysin and MAP2 partly via activating NF-κB pathway and inhibiting Nrf2-HO-1 pathway.

Radiomics analysis for the prediction of locoregional recurrence of locally advanced oropharyngeal cancer and hypopharyngeal cancer.

PURPOSE: By radiomic analysis of the postcontrast CT images, this study aimed to predict locoregional recurrence (LR) of locally advanced oropharyngeal cancer (OPC) and hypopharyngeal cancer (HPC). METHODS: A total of 192 patients with stage III-IV OPC or HPC from two independent cohort were randomly split into a training cohort with 153 cases and a testing cohort with 39 cases. Only primary tumor mass was manually segmented. Radiomic features were extracted using PyRadiomics, and then the support vector machine was used to build the radiomic model with fivefold cross-validation process in the training data set. For each case, a radiomics score was generated to indicate the probability of LR. RESULTS: There were 94 patients with LR assigned in the progression group and 98 patients without LR assigned in the stable group. There was no significant difference of TNM staging, treatment strategies and common risk factors between these two groups. For the training data set, the radiomics model to predict LR showed 83.7% accuracy and 0.832 (95% CI 0.72, 0.87) area under the ROC curve (AUC). For the test data set, the accuracy and AUC slightly declined to 79.5% and 0.770 (95% CI 0.64, 0.80), respectively. The sensitivity/specificity of training and test data set for LR prediction were 77.6%/89.6%, and 66.7%/90.5%, respectively. CONCLUSIONS: The image-based radiomic approach could provide a reliable LR prediction model in locally advanced OPC and HPC. Early identification of those prone to post-treatment recurrence would be helpful for appropriate adjustments to treatment strategies and post-treatment surveillance.

Magnetic Resonance Imaging Features Associated with a High and Low Expression of Tumor-Infiltrating Lymphocytes: A Stratified Analysis According to Molecular Subtypes.

A total of 457 patients, including 241 HR+/HER2- patients, 134 HER2+ patients, and 82 TN patients, were studied. The percentage of TILs in the stroma adjacent to the tumor cells was assessed using a 10% cutoff. The low TIL percentages were 82% in the HR+ patients, 63% in the HER2+ patients, and 56% in the TN patients (p < 0.001). MRI features such as morphology as mass or non-mass enhancement (NME), shape, margin, internal enhancement, presence of peritumoral edema, and the DCE kinetic pattern were assessed. Tumor sizes were smaller in the HR+/HER2- group (p < 0.001); HER2+ was more likely to present as NME (p = 0.031); homogeneous enhancement was mostly seen in HR+ (p < 0.001); and the peritumoral edema was present in 45% HR+, 71% HER2+, and 80% TN (p < 0.001). In each subtype, the MR features between the high- vs. low-TIL groups were compared. In HR+/HER2-, peritumoral edema was more likely to be present in those with high TILs (70%) than in those with low TILs (40%, p < 0.001). In TN, those with high TILs were more likely to present a regular shape (33%) than those with low TILs (13%, p = 0.029) and more likely to present the circumscribed margin (19%) than those with low TILs (2%, p = 0.009).

Differential diagnosis of prostate cancer and benign prostatic hyperplasia based on DCE-MRI using bi-directional CLSTM deep learning and radiomics.

Dynamic contrast-enhanced MRI (DCE-MRI) is routinely included in the prostate MRI protocol for a long time; its role has been questioned. It provides rich spatial and temporal information. However, the contained information cannot be fully extracted in radiologists' visual evaluation. More sophisticated computer algorithms are needed to extract the higher-order information. The purpose of this study was to apply a new deep learning algorithm, the bi-directional convolutional long short-term memory (CLSTM) network, and the radiomics analysis for differential diagnosis of PCa and benign prostatic hyperplasia (BPH). To systematically investigate the optimal amount of peritumoral tissue for improving diagnosis, a total of 9 ROIs were delineated by using 3 different methods. The results showed that bi-directional CLSTM with ± 20% region growing peritumoral ROI achieved the mean AUC of 0.89, better than the mean AUC of 0.84 by using the tumor alone without any peritumoral tissue (p = 0.25, not significant). For all 9 ROIs, deep learning had higher AUC than radiomics, but only reaching the significant difference for ± 20% region growing peritumoral ROI (0.89 vs. 0.79, p = 0.04). In conclusion, the kinetic information extracted from DCE-MRI using bi-directional CLSTM may provide helpful supplementary information for diagnosis of PCa.

Deep Learning-based Automatic Diagnosis of Breast Cancer on MRI Using Mask R-CNN for Detection Followed by ResNet50 for Classification.

RATIONALE AND OBJECTIVES: Diagnosis of breast cancer on MRI requires, first, the identification of suspicious lesions; second, the characterization to give a diagnostic impression. We implemented Mask Reginal-Convolutional Neural Network (R-CNN) to detect abnormal lesions, followed by ResNet50 to estimate the malignancy probability. MATERIALS AND METHODS: Two datasets were used. The first set had 176 cases, 103 cancer, and 73 benign. The second set had 84 cases, 53 cancer, and 31 benign. For detection, the pre-contrast image and the subtraction images of left and right breasts were used as inputs, so the symmetry could be considered. The detected suspicious area was characterized by ResNet50, using three DCE parametric maps as inputs. The results obtained using slice-based analyses were combined to give a lesion-based diagnosis. RESULTS: In the first dataset, 101 of 103 cancers were detected by Mask R-CNN as suspicious, and 99 of 101 were correctly classified by ResNet50 as cancer, with a sensitivity of 99/103 = 96%. 48 of 73 benign lesions and 131 normal areas were identified as suspicious. Following classification by ResNet50, only 16 benign and 16 normal areas remained as malignant. The second dataset was used for independent testing. The sensitivity was 43/53 = 81%. Of the total of 121 identified non-cancerous lesions, only 6 of 31 benign lesions and 22 normal tissues were classified as malignant. CONCLUSION: ResNet50 could eliminate approximately 80% of false positives detected by Mask R-CNN. Combining Mask R-CNN and ResNet50 has the potential to develop a fully-automatic computer-aided diagnostic system for breast cancer on MRI.

Endometrial microstimulation effects on endometrial receptivity assessed by transvaginal color Doppler sonography.

OBJECTIVE: This study investigated the effect of endometrial microstimulation (EM) on endometrial receptivity using transvaginal color Doppler sonography (TVCDS). METHOD: Women of childbearing age who were preparing to conceive (n = 90) were randomly divided into the EM group (n = 30), who were examined by EM on days 3-5 of the menstrual cycle, and the control group (n = 60). TVCDS was conducted during the implantation window phase, and endometrial thickness, endometrial pattern, endometrial movement, blood flow type, and uterine and spiral arterial hemodynamic parameter measurements were made. The groups were compared to identify differences. RESULTS: Endometrial thickness (0.97 ± 0.18 cm and 0.95 ± 0.17 cm), endometrial movement (type 1: 46.7% and 51.7%; type 2: 30.0% and 28.3%; type 3: 6.7% and 5.0%; type 5: 16.7% and 15.0%), and hemodynamic parameters of the uterine (pulsatility index [PI]: 2.46 ± 0.50 and 2.41 ± 0.48; resistance index [RI]: 0.85 ± 0.05 and 0.84 ± 0.05) and spiral (PI: 1.11 ± 0.32 and 1.19 ± 0.33; RI: 0.48 ± 0.11 and 0.51 ± 0.08) arteries did not differ significantly between groups (P > 0.05). However, the endometrial pattern (a trilaminar pattern: 80.0% and 58.3%; P = 0.041) and blood flow type (type I: 16.7% and 43.3%; type II: 63.3% and 40.0%; type III 20.0% and 16.7%; P = 0.038) differed significantly between groups. CONCLUSION: Endometrial microstimulation did not alter endometrial pathological staging, endometrial thickness, or movement, nor did it affect uterine and spiral arterial blood flow parameters. However, it may be able to abrade abnormal endometrial tissue, optimizing the endometrial pattern. Endometrial microstimulation may support local spiral artery regeneration and increase endometrial blood supply in new cycles.

A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet.

PURPOSE: To improve the performance of less experienced clinicians in the diagnosis of benign and malignant spinal fracture on MRI, we applied the ResNet50 algorithm to develop a decision support system. METHODS: A total of 190 patients, 50 with malignant and 140 with benign fractures, were studied. The visual diagnosis was made by one senior MSK radiologist, one fourth-year resident, and one first-year resident. The MSK radiologist also gave the binary score for 15 qualitative imaging features. Deep learning was implemented using ResNet50, using one abnormal spinal segment selected from each patient as input. The T1W and T2W images of the lesion slice and its two neighboring slices were considered. The diagnostic performance was evaluated using tenfold cross-validation. RESULTS: The overall reading accuracy was 98, 96, and 66% for the senior MSK radiologist, fourth-year resident, and first-year resident, respectively. Of the 15 imaging features, 10 showed a significant difference between benign and malignant groups with p < = 0.001. The accuracy achieved by using the ResNet50 deep learning model for the identified abnormal vertebral segment was 92%. Compared to the first-year resident's reading, the model improved the sensitivity from 78 to 94% (p < 0.001) and the specificity from 61 to 91% (p < 0.001). CONCLUSION: Our deep learning-based model may provide information to assist less experienced clinicians in the diagnosis of spinal fractures on MRI. Other findings away from the vertebral body need to be considered to improve the model, and further investigation is required to generalize our findings to real-world settings.

BI-RADS Reading of Non-Mass Lesions on DCE-MRI and Differential Diagnosis Performed by Radiomics and Deep Learning.

BACKGROUND: A wide variety of benign and malignant processes can manifest as non-mass enhancement (NME) in breast MRI. Compared to mass lesions, there are no distinct features that can be used for differential diagnosis. The purpose is to use the BI-RADS descriptors and models developed using radiomics and deep learning to distinguish benign from malignant NME lesions. MATERIALS AND METHODS: A total of 150 patients with 104 malignant and 46 benign NME were analyzed. Three radiologists performed reading for morphological distribution and internal enhancement using the 5th BI-RADS lexicon. For each case, the 3D tumor mask was generated using Fuzzy-C-Means segmentation. Three DCE parametric maps related to wash-in, maximum, and wash-out were generated, and PyRadiomics was applied to extract features. The radiomics model was built using five machine learning algorithms. ResNet50 was implemented using three parametric maps as input. Approximately 70% of earlier cases were used for training, and 30% of later cases were held out for testing. RESULTS: The diagnostic BI-RADS in the original MRI report showed that 104/104 malignant and 36/46 benign lesions had a BI-RADS score of 4A-5. For category reading, the kappa coefficient was 0.83 for morphological distribution (excellent) and 0.52 for internal enhancement (moderate). Segmental and Regional distribution were the most prominent for the malignant group, and focal distribution for the benign group. Eight radiomics features were selected by support vector machine (SVM). Among the five machine learning algorithms, SVM yielded the highest accuracy of 80.4% in training and 77.5% in testing datasets. ResNet50 had a better diagnostic performance, 91.5% in training and 83.3% in testing datasets. CONCLUSION: Diagnosis of NME was challenging, and the BI-RADS scores and descriptors showed a substantial overlap. Radiomics and deep learning may provide a useful CAD tool to aid in diagnosis.

Real-Time Intracellular Measurements of ROS and RNS in Living Cells with Single Core-Shell Nanowire Electrodes.

Nanoelectrodes allow precise and quantitative measurements of important biological processes at the single living-cell level in real time. Cylindrical nanowire electrodes (NWEs) required for intracellular measurements create a great challenge for achieving excellent electrochemical and mechanical performances. Herein, we present a facile and robust solution to this problem based on a unique SiC-core-shell design to produce cylindrical NWEs with superior mechanical toughness provided by the SiC nano-core and an excellent electrochemical performance provided by the ultrathin carbon shell that can be used as such or platinized. The use of such NWEs for biological applications is illustrated by the first quantitative measurements of ROS/RNS in individual phagolysosomes of living macrophages. As the shell material can be varied to meet any specific detection purpose, this work opens up new opportunities to monitor quantitatively biological functions occurring inside cells and their organelles.

Dose Conversion Coefficients Based on Taiwanese Reference Phantoms and Monte Carlo Simulations for Use in External Radiation Protection.

Reference phantoms are widely applied to evaluate the radiation dose for external exposure. However, the frequently used reference phantoms are based on Caucasians. Dose estimation for Asians using a Caucasian phantom can result in significant errors. This study recruited 40 volunteers whose body sizes are close to the average Taiwanese population. Magnetic resonance imaging was performed to obtain the organ volume for construction of the Taiwanese reference man (TRM) and Taiwanese reference woman (TRW). The dose conversion coefficients (DCC) resulting from photo beams in anterior-posterior, posterior-anterior, right-lateral, left-lateral, and isotropic irradiation geometries were estimated. In the anterior-posterior geometry, the mean DCC differences among organs between the TRM and ORNL phantom at 0.1, 1, and 10 MeV were 7.3%, 5.8%, and 5.2%, respectively. For the TRW, the mean differences from the ORNL phantom at the three energies were 10.6%, 7.4%, and 8.3%. The DCCs of the Taiwanese reference phantoms and the ORNL phantom presented similar trends in other geometries. The torso size of the phantom and the mass and geometric location of the organ have a significant influence on the DCC. The Taiwanese reference phantoms can be used to establish dose guidelines and regulations for radiation protection from external exposure.

Temperature-dependent elastic properties of brain tissues measured with the shear wave elastography method.

Determining the mechanical properties of brain tissues is essential in such cases as the surgery planning and surgical training using virtual reality based simulators, trauma research and the diagnosis of some diseases that alter the elastic properties of brain tissues. Here, we suggest a protocol to measure the temperature-dependent elastic properties of brain tissues in physiological saline using the shear wave elastography method. Experiments have been conducted on six porcine brains. Our results show that the shear moduli of brain tissues decrease approximately linearly with a slope of -0.041±0.006kPa/°C when the temperature T increases from room temperature (~23°C) to body temperature (~37°C). A case study has been further conducted which shows that the shear moduli are insensitive to the temperature variation when T is in the range of 37 to 43°C and will increase when T is higher than 43°C. With the present experimental setup, temperature-dependent elastic properties of brain tissues can be measured in a simulated physiological environment and a non-destructive manner. Thus the method suggested here offers a unique tool for the mechanical characterization of brain tissues with potential applications in brain biomechanics research.

Capsaicin Supplementation Reduces Physical Fatigue and Improves Exercise Performance in Mice.

Chili pepper is used as a food, seasoning and has been revered for its medicinal and health claims. It is very popular and is the most common spice worldwide. Capsaicin (CAP) is a major pungent and bioactive phytochemical in chili peppers. CAP has been shown to improve mitochondrial biogenesis and adenosine triphosphate (ATP) production. However, there is limited evidence around the effects of CAP on physical fatigue and exercise performance. The purpose of this study was to evaluate the potential beneficial effects of CAP on anti-fatigue and ergogenic functions following physiological challenge. Female Institute of Cancer Research (ICR) mice from four groups (n = 8 per group) were orally administered CAP for 4 weeks at 0, 205, 410, and 1025 mg/kg/day, which were respectively designated the vehicle, CAP-1X, CAP-2X, and CAP-5X groups. The anti-fatigue activity and exercise performance was evaluated using forelimb grip strength, exhaustive swimming time, and levels of serum lactate, ammonia, glucose, BUN (blood urea nitrogen) and creatine kinase (CK) after a 15-min swimming exercise. The grip strength and exhaustive swimming time of the CAP-5X group were significantly higher than other groups. CAP supplementation dose-dependently reduced serum lactate, ammonia, BUN and CK levels, and increased glucose concentration after the 15-min swimming test. In addition, CAP also increased hepatic glycogen content, an important energy source for exercise. The possible mechanism was relevant to energy homeostasis and the physiological modulations by CAP supplementation. Therefore, our results suggest that CAP supplementation may have a wide spectrum of bioactivities for promoting health, performance improvement and fatigue amelioration.

Construction of Taiwanese Adult Reference Phantoms for Internal Dose Evaluation.

In the internal dose evaluation, the specific absorbed fraction (SAF) and S-value are calculated from the reference phantom based on Caucasian data. The differences in height and weight between Caucasian and Asian may lead to inaccurate dose estimation. In this study, we developed the Taiwanese reference phantoms. 40 volunteers were recruited. Magnetic resonance images (MRI) were obtained, and the contours of 15 organs were drawn. The Taiwanese reference man (TRM) and Taiwanese reference woman (TRW) were constructed. For the SAF calculation, the differences in the self-absorption SAF (self-SAF) between the TRM, TRW, and Oak Ridge National Laboratory (ORNL) adult phantom were less than 10% when the difference in organ mass was less than 20%. The average SAF from liver to pancreas of TRM was 38% larger than that of the ORNL adult phantom, and the result of TRW was 2.02 times higher than that of the ORNL adult phantom. For the S-value calculation, the ratios of TRW and ORNL adult phantom ranged from 0.91 to 1.57, and the ratios of TRM and ORNL adult phantom ranged from 1.04 to 2.29. The SAF and S-value results were dominantly affected by the height, weight, organ mass, and geometric relationship between organs. By using the TRM and TRW, the accuracy of internal dose evaluation can be increased for radiation protection and nuclear medicine.

A graphene-based multifunctional affinity probe for selective capture and sequential identification of different biomarkers from biosamples.

A novel multifunctional graphene-based affinity probe has been explored for selective capture of two different types of peptides from the biosamples for sequential detection.

[Expression of proteasome ß5 subunit in human atherosclerotic plaque].

OBJECTIVE: To evaluate the expression of proteasome ß5 subunit in human atherosclerotic plaque. METHODS: The specimens of carotid endarterectomy were collected from 16 carotid stenosis patients. For the case group, they were divided into 2 groups: plaque (group A) and areas adjacent to plaque (group B). And carotid endarterium was obtained from 6 patients undergoing aortic replacement surgery. Relatively normal arterial intima (subclavian artery & innominate artery) was selected as the control group (group C). Content of proteasome ß5 subunit was evaluated by hematoxylin & eosin (HE) staining, immunohistochemistry and Western blot. RESULTS: (1) In patients with diabetes, hyperlipidemia and probable smoking, proteasome ß5 subunit was enhanced in all groups; (2) Proteasome ß5 subunit was demonstrated in both cytoplasm and nucleus of vascular smooth muscle cells, but mainly confined to cytoplasm; (3)The positive expression rate of ß5 was 9/16 in group A, 11/16 in group B and 6/6 in group C. There was significant divergence in the expression of ß5 in different sample sub-groups: group A (atherosclerotic plaque) < group B (areas adjacent to plaque) < group C (control group). CONCLUSION: The expression of ß5 decrease markedly in human atherosclerotic plaques.

Construction of self-cloning, indigenous wine strains of Saccharomyces cerevisiae with enhanced glycerol and glutathione production.

To improve wine taste and flavor stability, a novel indigenous strain of Saccharomyces cerevisiae with enhanced glycerol and glutathione (GSH) production for winemaking was constructed. ALD6 encoding an aldehyde dehydrogenases of the indigenous yeast was replaced by a GPD1 and CUP1 gene cassette, which are responsible for NAD-dependent glycerol-3-phosphatase dehydrogenase and copper resistance, respectively. Furthermore, the α-acetohydroxyacid synthase gene ILV2 of the indigenous yeast was disrupted by integration of the GSH1 gene which encodes γ-glutamylcysteine synthetase and the CUP1 gene cassette. The fermentation capacity of the recombinant was similar to that of the wild-type strain, with an increase of 21 and 19 % in glycerol and GSH production. No heterologous DNA was harbored in the recombinant in this study.

[Progress in Research on Embryonic Stem Cells]

Embryonic stem cells are continuously growing stem cell lines of embryonic origin. The distinguishing features of ES cells are their capacity to be maintained in an undifferentiated state indefinitely in culture and their potential to develop into various kinds of cells in the body. At molecular level, in vivo and in vitro differentiation of ES cells are similar in many ways. To date, ES cells can differentiate in vitro into myocytes and myocardial cells, neural precursor cells, hematopoietic cells and endothelial cells. Recent evidence suggests that hematopoietic stem cells (HSCs) originate from a region within the embryo proper. It is likely that the genesis of HSCs is regulated by embryonic growth factors, which have not been discovered yet. ES cells have provided a convenient and effective experimental approach to define early hematopoietic process within embryos. Research on ES cells has broad application prospect.