EEG-VTTCNet: A loss joint training model based on the vision transformer and the temporal convolution network for EEG-based motor imagery classification.

Brain-computer interface (BCI) is a technology that directly connects signals between the human brain and a computer or other external device. Motor imagery electroencephalographic (MI-EEG) signals are considered a promising paradigm for BCI systems, with a wide range of potential applications in medical rehabilitation, human-computer interaction, and virtual reality. Accurate decoding of MI-EEG signals poses a significant challenge due to issues related to the quality of the collected EEG data and subject variability. Therefore, developing an efficient MI-EEG decoding network is crucial and warrants research. This paper proposes a loss joint training model based on the vision transformer (VIT) and the temporal convolutional network (EEG-VTTCNet) to classify MI-EEG signals. To take advantage of multiple modules together, the EEG-VTTCNet adopts a shared convolution strategy and a dual-branching strategy. The dual-branching modules perform complementary learning and jointly train shared convolutional modules with better performance. We conducted experiments on the BCI Competition IV-2a and IV-2b datasets, and the proposed network outperformed the current state-of-the-art techniques with an accuracy of 84.58% and 90.94%, respectively, for the subject-dependent mode. In addition, we used t-SNE to visualize the features extracted by the proposed network, further demonstrating the effectiveness of the feature extraction framework. We also conducted extensive ablation and hyperparameter tuning experiments to construct a robust network architecture that can be well generalized.

Stereopsis Following Implantation of Presbyopia-Correcting Intraocular Lenses: A Narrative Review.

Recent advancements in cataract surgery have broadened its scope from mere vision restoration to include correction of refractive errors and presbyopia. This evolution has introduced multifocal and extended depth-of-focus (EDOF) intraocular lenses (IOLs), allowing enhanced vision across multiple distances. However, the influence of these advanced IOLs on stereopsis remains controversial. Factors influencing stereopsis after surgery include visual acuity, interocular differences, residual astigmatism, and the type of IOL, etc. Binocular vision integration and neuroadaptation further affect stereopsis, especially in cases of presbyopia-correcting IOLs. It is widely acknowledged that bilateral implantation of presbyopia-correcting IOLs yield superior stereopsis compared to unilateral implantation. However, there remains no consensus on whether binocular implantation of multifocal or monofocal IOLs provides superior stereopsis. Most studies suggest no significant difference in stereopsis between these two types of implants. Among different types of multifocal IOLs, refractive multifocal IOLs may offer better stereopsis than diffractive multifocal IOLs when implanted bilaterally. Emerging EDOF and hybrid multifocal-EDOF IOLs also demonstrate promising postoperative stereopsis. Additionally, a mix-and-match strategy with different types of IOLs implanted in each eye may result in interocular differences in visual acuity at certain distances, potentially affecting stereopsis. Nevertheless, with appropriate selection, most patients can achieve satisfactory postoperative stereopsis. This review synthesizes current literature on the effects of presbyopia-correcting IOLs on postoperative stereopsis recovery following cataract surgery. Studies on stereopsis outcomes with different IOLs have yielded mixed results, urging further investigation for optimized surgical strategies and patient outcomes.

Classification Algorithm for fNIRS-based Brain Signals Using Convolutional Neural Network with Spatiotemporal Feature Extraction Mechanism.

Brain Computer Interface (BCI) is a highly promising human-computer interaction method that can utilize brain signals to control external devices. BCI based on functional near-infrared spectroscopy (fNIRS) is considered a relatively new and promising paradigm. fNIRS is a technique of measuring functional changes in cerebral hemodynamics. It detects changes in the hemodynamic activity of the cerebral cortex by measuring oxyhemoglobin and deoxyhemoglobin (HbR) concentrations and inversely predicts the neural activity of the brain. At the present time, Deep learning (DL) methods have not been widely used in fNIRS decoding, and there are fewer studies considering both spatial and temporal dimensions for fNIRS classification. To solve these problems, we proposed an end-to-end hybrid neural network for feature extraction of fNIRS. The method utilizes a spatial-temporal convolutional layer for automatic extraction of temporally valid information and uses a spatial attention mechanism to extract spatially localized information. A temporal convolutional network (TCN) is used to further utilize the temporal information of fNIRS before the fully connected layer. We validated our approach on a publicly available dataset including 29 subjects, including left-hand and right-hand motor imagery (MI), mental arithmetic (MA), and a baseline task. The results show that the method has few training parameters and high accuracy, providing a meaningful reference for BCI development.

ETCNet: An EEG-based motor imagery classification model combining efficient channel attention and temporal convolutional network.

Brain-computer interface (BCI) enables the control of external devices using signals from the brain, offering immense potential in assisting individuals with neuromuscular disabilities. Among the different paradigms of BCI systems, the motor imagery (MI) based electroencephalogram (EEG) signal is widely recognized as exceptionally promising. Deep learning (DL) has found extensive applications in the processing of MI signals, wherein convolutional neural networks (CNN) have demonstrated superior performance compared to conventional machine learning (ML) approaches. Nevertheless, challenges related to subject independence and subject dependence persist, while the inherent low signal-to-noise ratio of EEG signals remains a critical aspect that demands attention. Accurately deciphering intentions from EEG signals continues to present a formidable challenge. This paper introduces an advanced end-to-end network that effectively combines the efficient channel attention (ECA) and temporal convolutional network (TCN) components for the classification of motor imagination signals. We incorporated an ECA module prior to feature extraction in order to enhance the extraction of channel-specific features. A compact convolutional network model uses for feature extraction in the middle part. Finally, the time characteristic information is obtained by using TCN. The results show that our network is a lightweight network that is characterized by few parameters and fast speed. Our network achieves an average accuracy of 80.71% on the BCI Competition IV-2a dataset.

EEG-FMCNN: A fusion multi-branch 1D convolutional neural network for EEG-based motor imagery classification.

Motor imagery (MI) electroencephalogram (EEG) signal is recognized as a promising paradigm for brain-computer interface (BCI) systems and has been extensively employed in various BCI applications, including assisting disabled individuals, controlling devices and environments, and enhancing human capabilities. The high-performance decoding capability of MI-EEG signals is a key issue that impacts the development of the industry. However, decoding MI-EEG signals is challenging due to the low signal-to-noise ratio and inter-subject variability. In response to the aforementioned core problems, this paper proposes a novel end-to-end network, a fusion multi-branch 1D convolutional neural network (EEG-FMCNN), to decode MI-EEG signals without pre-processing. The utilization of multi-branch 1D convolution not only exhibits a certain level of noise tolerance but also addresses the issue of inter-subject variability to some extent. This is attributed to the ability of multi-branch architectures to capture information from different frequency bands, enabling the establishment of optimal convolutional scales and depths. Furthermore, we incorporate 1D squeeze-and-excitation (SE) blocks and shortcut connections at appropriate locations to further enhance the generalization and robustness of the network. In the BCI Competition IV-2a dataset, our proposed model has obtained good experimental results, achieving accuracies of 78.82% and 68.41% for subject-dependent and subject-independent modes, respectively. In addition, extensive ablative experiments and fine-tuning experiments were conducted, resulting in a notable 7% improvement in the average performance of the network, which holds significant implications for the generalization and application of the network.

Classification Algorithm for Electroencephalogram-based Motor Imagery Using Hybrid Neural Network with Spatio-temporal Convolution and Multi-head Attention Mechanism.

Motor imagery (MI) is a brain-computer interface (BCI) technique in which specific brain regions are activated when people imagine their limbs (or muscles) moving, even without actual movement. The technology converts electroencephalogram (EEG) signals generated by the brain into computer-readable commands by measuring neural activity. Classification of motor imagery is one of the tasks in BCI. Researchers have done a lot of work on motor imagery classification, and the existing literature has relatively mature decoding methods for two-class motor tasks. However, as the categories of EEG-based motor imagery tasks increase, further exploration is needed for decoding research on four-class motor imagery tasks. In this study, we designed a hybrid neural network that combines spatiotemporal convolution and attention mechanisms. Specifically, the data is first processed by spatiotemporal convolution to extract features and then processed by a Multi-branch Convolution block. Finally, the processed data is input into the encoder layer of the Transformer for a self-attention calculation to obtain the classification results. Our approach was tested on the well-known MI datasets BCI Competition IV 2a and 2b, and the results show that the 2a dataset has a global average classification accuracy of 83.3% and a kappa value of 0.78. Experimental results show that the proposed method outperforms most of the existing methods.

Flapless one-knot suture: a novel surgical technique for transscleral fixation of C-loop intraocular lenses.

AIM: To describe a novel suture approach for transscleral fixation of C-loop intraocular lenses (IOL) and to compare the surgical outcomes with the four-haptics posterior chamber (PC)-IOL technique. METHODS: We retrospectively analyzed 16 eyes of 16 patients who underwent transscleral fixation of C-loop PC-IOLs using a flapless one-knot suture technique, which were followed up for longer than 17mo. In this technique, the capsulorless IOL was suspended using a single suture for transscleral fixation of four feet. Then we compared its surgical outcomes and complications with the four-haptics PC-IOLs using the Student's t test and Chi-square test. RESULTS: Sixteen patients of 16 eyes with a mean age of 58.3±10.1y (42-76y) who received transscleral C-loop IOL implantation due to trauma, vitrectomy, or cataract surgery with inadequate capsule support showed improved visual acuity. The difference was not significant between two IOLs except the surgery time (P>0.05). The mean operation times of C-loop IOL surgery was 24.1±1.83min and 31.3±4.47min of the four-haptics PC-IOL method (P<0.0001). In the C-loop IOLs group, there was statistical difference between the preoperative and the postoperative UCVA (logMAR, 1.20±0.50 vs 0.57±0.32, P=0.0003). There was no statistical difference between the preoperative and the postoperative BCVA (logMAR, 0.66±0.46 vs 0.40±0.23, P=0.056). However, there was no statistically significant difference in postoperative UCVA and BCVA between the two IOLs (P>0.05). We did not detect any optic capture, IOL decentration or dislocation, suture exposed, or cystoid macular edema in patients underwent C-loop IOLs surgery. CONCLUSION: The novel flapless one-knot suture technique for transscleral fixation of C-loop IOL is a simple, reliable, and stable technique.

A novel model based on a 1D-ResCNN and transfer learning for processing EEG attenuation.

EEG signals are valuable signals in clinical medicine, brain research, and the study of neurological illnesses. However, EEG signal attenuation may occur at any time from signal generation through BCI device acquisition due to defects in the brain-computer interface (BCI) devices, restrictions in the dynamic network, and individual variations across the subjects. The attenuation of EEG data will alter the data distribution and lead to information fuzziness, substantially influencing subsequent EEG research. A model based on one-dimensional residual convolutional neural networks (1D-ResCNN) and transfer learning is proposed in this article to reduce the negative impacts of EEG attenuation. An end-to-end manner maps an attenuated EEG signal to a normal EEG signal. The structure employs a multi-level residual connection structure with varying weight coefficients, transferring characteristics from the bottom to the top of the convolutional neural network, enhancing feature learning. In addition, we initialize the subsequent denoising model using the transfer learning method. The combination of these two networks can well solve the attenuation problem of EEG signals. Experiments are carried out using the EEG-denoisenet data set. According to the findings, the model can yield a clear waveform with a decent SNR and RRMSE value.

A Novel End-to-end Network Based on a bidirectional GRU and a Self-Attention Mechanism for Denoising of Electroencephalography Signals.

Electroencephalography (EEG) signals are nonlinear and non-stationary sequences that carry much information. However, physiological signals from other body regions may readily interfere with EEG signal capture, having a significant unfavorable influence on subsequent analysis. Therefore, signal denoising is a crucial step in EEG signal processing. This paper proposes a bidirectional gated recurrent unit (GRU) network based on a self-attention mechanism (BG-Attention) for extracting pure EEG signals from noise-contaminated EEG signals. The bidirectional GRU network can simultaneously capture past and future information while processing continuous time sequence. And by paying different levels of attention to the content of varying importance, the model can learn more significant feature of EEG signal sequences, highlighting the contribution of essential samples to denoising. The proposed model is evaluated on the EEGdenoiseNet data set. We compared the proposed model with a fully connected network (FCNN), the one-dimensional residual convolutional neural network (1D-ResCNN), and a recurrent neural network (RNN). The experimental results show that the proposed model can reconstruct a clear EEG waveform with a decent signal-to-noise ratio (SNR) and the relative root mean squared error (RRMSE) value. This study demonstrates the potential of BG-Attention in the pre-processing phase of EEG experiments, which has significant implications for medical technology and brain-computer interface (BCI) applications.

Construction and Identification of New Molecular Markers of Triple-Negative Breast Cancer Stem Cells.

Objective: We screened the TNBC stem cells using phage display (PD) and acquired the specific binding clones; and then the positive phage DNAs were amplified and extracted, synthesized with specific polypeptides, and labeled with fluorescein isothiocyanate (FITC). Finally, we identified the specificity of the polypeptides in vitro and in vivo. Methods: Human breast cancer cell line MDA-MB-231 and human mammary gland cell line hs578bst were chosen in our study, and MDA-MB-231 breast cancer stem cells (BCSCs) were cultured and identified by flow cytometry. The phage peptide library was screened using MDA-MB-231 BCSCs, the positive phage clones were identified by ELISA, and the DNA of the positive phages was extracted and sent to a biotechnology company for sequencing. According to the sequencing results, a specific polypeptide was synthesized and labeled with FITC. In the end, the specificity of a polypeptide to BCSCs was identified in vivo and in vitro. Results: The MDA-MB-231 BCSCs were cultured and enriched with the "serum and serum-free alternate" method. The BCSCs were found to have characteristics of CD44+/CD24-/low epithelial surface antigen (ESA) and ALDH+ with flow cytometry. The phage was enriched to 200-fold after three rounds of screening for MDA-MB-231 BCSCs. The positive phages were sequenced; then a polypeptide named M58 was synthesized according to sequencing results. Polypeptide M58 has a specific affinity to MDA-MB-231 BCSCs in vivo and in vitro. Conclusion: Specific polypeptides binding to MDA-MB-231 BCSCs were screened out by PD screening method, which laid a theoretical foundation for the targeted therapy and further research of BCSCs.

Bronchiolar adenoma with diffuse pulmonary nodules: a extremely rare case report and review of literature.

BACKGROUND: Bronchiolar adenoma(BA) is a recently recognized, rare tumor of the bronchioles. It can be divided into proximal and distal types according to the proportion of mucinous and ciliated cells on the luminal surface. BA is often misdiagnosed because it has similar ultrasonographic, gross and histological presentations as other diseases. Here, we report a rare case of BA characterized by many fused nodules. CASE PRESENTATION: A 68-year-old woman attended the Tianjin Taida Hospital surgical Clinic mainly because of "intermittent cough for >1 month". Chest computed tomography (CT) showed multiple solid nodules in the upper and lower left lung. The nodules had irregular outlines, with a maximum diameter of 65 mm. A double needle lung biopsy specimen was removed guided by ultrasound under local anesthesia. Histologically, the biopsy specimen was finally diagnosed as the distal type of BA. CONCLUSION: BA with diffuse pulmonary nodules is rare. Diagnosis of BA needs comprehensive analysis of imaging, gross specimen analysis, histopathology, and immunohistochemical staining to make a correct diagnosis and avoid misdiagnosis. There are few studies on prognosis, which needs close follow-up and more data accumulation.

Simple Technique for Transscleral Fixation of a Foldable Posterior Chamber Intraocular Lens Using a Single Suture.

Objective: To explore the simplified technique for transscleral fixation of a foldable posterior chamber intraocular lens (IOLs) in patients with aphakia or inadequate posterior capsule support. Methods: A review was conducted of 18 eyes of eighteen patients with the absence of-or inadequate-capsule support, after the simplified technique of using a foldable posterior chamber intraocular lens (PC IOLs) with stable four-point transscleral fixation, as performed by a skilled surgeon. This technique uses only a single suture and a knot to fix a PC IOL firmly without creating a scleral flap. The mean follow-up time was 18 ± 5.8 months (ranging from 12 to 24 months). Results: All patients exhibited improved visual acuity. No IOL tilt or dislocation or iris capture was observed, and all patients exhibited stable and centered IOL after surgery. No complex complications, such as suture shedding and exposure, corneal endothelial decompensation, persistent uveitis, or retinal detachment and endophthalmitis were observed. Conclusion: The simplified technique proposed here is a reliable, economical, and reproducible method of treating patients with aphakia or inadequate posterior capsule support. It provides excellent IOL stability, reduces surgical duration and complexity, and prevents certain complications.

Screening and identification of novel specific markers of breast cancer stem cells.

Breast cancer is the leading cause of death among women worldwide. Until recent years, triple negative breast cancer could be divided into 6 types according to different biomarkers with the development of sequence and microarray technology. However, these results rarely have therapeutic impact and still lack validation with the string criteria of clinical studies. Therefore, the present study aimed to screen novel markers of breast cancer stem cells and to verify the specificity in vitro and in vivo. In the present study, screening for phages specifically binding to breast cancer stem cells was performed, positive phage DNAs were extracted, and polypeptides were synthesized and labeled with FITC. The specificity of the polypeptides was identified in vitro and in vivo. Breast cancer stem cells were cultured and identified by flow cytometry. A phage random-peptide library was amplified and screened by culturing with breast cancer cells and breast cancer stem cells. The positive phage was identified by ELISA, and positive phage DNA was extracted. The DNA pellet was isolated and sent for external sequencing with the primer -96 gIII. Based on the sequencing results, a polypeptide was synthesized and labeled with FITC. The specificity to breast cancer stem cells was identified in vivo and vitro. Following three rounds of screening, the phage was enriched ~200-fold. Immunofluorescence demonstrated that two randomly selected phage clones, B8 and A3, had specific affinity to breast cancer stem cells. The results of the present study indicated that phage polypeptides that specifically bind to breast cancer stem cells were successfully screened through stem cell enrichment and phage display technology, which may be beneficial for targeted therapy and further study of breast cancer stem cells.

Screening specific polypeptides of breast cancer stem cells from a phage display random peptide library.

The present study aimed to identify polypeptides that specifically bond to breast cancer stem cells from a phage display random 12 peptide library, in addition to the affinity and specificity of polypeptides. A phage display random 12 peptide library was screened using breast cancer stem cells as targets isolated from the MDA-MB-231 cell line using the serum-free culture technique with hs578bst and MDA-MB-231 cells as subtract-screening cells. Positive and specific binding clones were amplified and sent for sequencing. The affinity and specificity of the positive clones were subsequently identified by ELISA and 3,3'-diaminobenzidine staining. The results demonstrated that phages were gathered ~500 times following three rounds of biopanning. ELISA identified that the affinity to breast cancer stem cells of the no. 6 phage was 6.14 times higher than that in the control group. In addition, immunohistochemistry observed that the no. 6 phage exhibited high-specificity bonding to breast cancer stem cells, and the peptide sequence of the positive phage was GYSASRSTIPGK following DNA sequencing and translation. Thus, the present study isolated a specific peptide that bonds to breast cancer stem cells from a phage display random peptide library, which may facilitate further studies regarding the stem cell-targeted therapy of breast cancer.

Knockdown of metadherin inhibits angiogenesis in breast cancer.

Angiogenesis plays an important role in cancer growth, invasion and metastasis. It has been confirmed that metadherin (MTDH) is associated with angiogenesis. However, the detailed mechanism of MTDH on angiogenesis has not yet been reported. In this study, we demonstrate the anti-angiogenic function of MTDH in breast cancer. With RNA interference strategies, we found that knockdown of MTDH inhibits cellular angiogenesis both in vitro and ex vivo. Furthermore, we revealed that ERK1/2 pathway is involved in the anti-angiogenic function of MTDH, and the function can be partially reversed via upregulation of microRNA-21 (miR-21). In conclusion, knockdown of MTDH can inhibit angiogenesis in breast cancer. These results show that MTDH is a viable therapeutic target for anti-angiogenesis in breast cancer.

Antisense oligodeoxynucleotide against human telomerase reverse transcriptase inhibits the proliferation of Eca-109 esophageal carcinoma cells.

Previous studies have demonstrated that the growth of tumor cells may be inhibited by antisense oligonucleotides (ASODNs) targeted against human telomerase (hTR) or human telomerase reverse transcriptase (hTERT), resulting in antitumor activity in a wide variety of tumors. However, few studies have investigated the effect of hTERT gene-targeted ASODNs on telomerase activity and cell proliferation in human esophageal cancer. In the present study, an MTT assay was used to determine the growth inhibition rate of Eca-109 cells treated with a hTERT-targeted phosphorothioate-ASODN (PS-ASODN). An inverted microscope was used to observe the morphologic changes of the cells following treatment with 5 µM PS-ASODN for 10 days. Telomerase activity was detected using the silver staining semi-quantitative telomeric repeat amplification protocol (TRAP) assay. Following treatment with the PS-ASODN (1-5 µmol/l), the proliferation of the Eca-109 cells was inhibited. The differences in inhibition rate between the PS-ASODN and blank control groups were statistically significant (P<0.05) when the concentration of the PS-ASODN was ≥2 µmol/l, whereas no statistically significant difference was identified between the non-specific-ASODN and blank control groups. The inhibition rate increased gradually as the concentration of the PS-ASODN increased and with time, suggesting that the PS-ASODN inhibited the growth of Eca-109 cells in a concentration-dependent, time-dependent and sequence-specific manner. The growth rate of the cells incubated with the PS-ASODN was reduced compared with that of the control cells. Cells treated with the PS-ASODN became round, suspended and reduced in size. The PS-ASODN was also found to inhibit telomerase activity. The ability of the PS-ASODN to inhibit the telomerase activity and cell proliferation of the Eca-109 cell line suggests that ASODNs have the potential to be novel therapeutic agents for the treatment of esophageal cancer.

Intramyocardial injection of hypoxia-preconditioned adipose-derived stromal cells treats acute myocardial infarction: an in vivo study in swine.

Hypoxic preconditioning is a promising method for improving the anti-apoptotic and paracrine signaling capabilities of adipose-derived stromal cells (ADSCs). The purpose of this study was to analyze the influence of different hypoxic conditions on ADSCs and the therapeutic effects of hypoxia-preconditioned ADSCs (HPADSCs) on an animal model of myocardial infarction (MI). For the in vitro studies, ADSCs were divided into five groups and cultured in different oxygen concentrations (1, 3, 5, 10, and 21 %). After 24 h, RT-PCR and western blots showed that 3 % oxygen preconditioning could improve the viability and cytokine secretion of the ADSCs. A Matrigel assay indicated that the HPADSC-conditioned medium could stimulate endothelial cells to form capillary-like tubes. For the in vivo studies, MI was induced by coronary occlusion in 24 mature Chinese minipigs. The animals were divided into three groups and treated by intramyocardial injection with vehicle alone (saline group), with 1 × 10(8) ADSCs cultured in normoxic conditions (ADSCs group) or with 1 × 10(8) ADSCs precultured in 3 % oxygen (HPADSCs group). SPECT and echocardiography demonstrated that cardiac function was improved significantly in the HPADSC transplant group compared with the vehicle control group (P < 0.05). Immunofluorescence showed fewer apoptotic cells and more small- to medium-sized vessels in the HPADSC transplantation group (P < 0.05). Three percent oxygen is the optimum preconditioning treatment for ADSCs. HPADSC transplantation can prevent ventricular remodeling and reduce the infarct size.

Anticancer effect of salidroside on A549 lung cancer cells through inhibition of oxidative stress and phospho-p38 expression.

Oxidative stress is important in carcinogenesis and metastasis. Salidroside, a phenylpropanoid glycoside isolated from Rhodiola rosea L., shows potent antioxidant properties. The aim of the present study was to investigate the roles of salidroside in cell proliferation, the cell cycle, apoptosis, invasion and epithelial-mesenchymal transition (EMT) in A549 cells. The human alveolar adenocarcinoma cell line, A549, was incubated with various concentrations of salidroside (0, 1, 5, 10 and 20 µg/ml) and cell proliferation was detected by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. Propidium iodide (PI) staining was used to determine the cell cycle by flow cytometry. Cell apoptosis was detected by Annexin V-fluorescein isothiocyanate and PI double-staining, and tumor invasion was detected by Boyden chamber invasion assay. Western blot analysis was performed to detect the expression of EMT markers, Snail and phospho-p38. The results showed that salidroside significantly reduced the proliferation of A549 cells, inhibited cell cycle arrest in the G0/G1 phase and induced apoptosis. Salidroside inhibited transforming growth factor-ß-induced tumor invasion and suppressed the protein expression of Snail. As an antioxidant, salidroside inhibited the intracellular reactive oxygen species (ROS) formation in a dose-dependent manner in A549 cells, and depletion of intracellular ROS by vitamin C suppressed apoptosis by salidroside treatment. Salidroside was also found to inhibit the expression of phospho-p38 in A549 cells. In conclusion, salidroside inhibits cell proliferation, the cell cycle and metastasis and induces apoptosis, which may be due to its interference in the intracellular ROS generation, thereby, downregulating the ROS-phospho-p38 signaling pathway.

[Inheritance of the white-flower and its influence to related characters in eggplant (Solanum melongem Linn)].

The inheritance of the white-flower and its influence to related characters in eggplant were studied with the white-flowered mutant of XIANLVQIE and its maternal bred. Result showed that the flower color was attributed to a couple of complete dominance genes. Purple color flower "Col" was dominant to the white "col". Compared with the purple-flowered strain, the white-flowered strain not only grew more blooming, but also had more stamens in one flower, less pollens in one anther and less seeds in one fruit. In the meanwhile, in white-flowered eggplants, microspore and fruit was bigger, and yield was higher than purple-flowered. The white-flowered strain could be used as a variety and the white-flowered character could be used as a marker to appraise purity of hybrid in eggplant.

[In vitro killing effects of STI571 on esophageal carcinoma cell lines CE-48T and CE-81T].

BACKGROUND & OBJECTIVE: Tyrosine kinase mediates cell proliferation and differentiation, and plays important roles in tumorigenesis and development of esophageal carcinoma. STI571 is a tyrosine kinase inhibitor of platelet-derived growth factor receptor beta (PDGFR-beta) which is overexpressed in esophageal carcinoma. This study was to explore the in vitro killing effects of STI571 on esophageal carcinoma cell lines CE-48T and CE-81T. METHODS: The expression of PDGFR-alpha and PDGFR-beta in CE-48T and CE-81T cells was detected by Western blot. The killing effects of STI571 on CE-48T and CE-81T cells were evaluated by MTT assay. Cell apoptosis was analyzed by flow cytometry with Annexin V/PI labeling. The expression of p-PDGFR-beta was detected by Western blot before and after treatment of STI571. RESULTS: CE-48T cells expressed PDGFR-beta, but did not express PDGFR-alpha; CE-81T cells did not express both PDGFR-alpha and PDGFR-beta. The 50% inhibitory concentration (IC50) of STI571 was significantly lower for CE-48T cells than for CE-81T cells [(8.32+/-1.50) micromol/L vs. (41.02+/-7.64) micromol/L, P=0.002]. When treated with 10 micromol/L STI571 for 12 h, the apoptosis rate of CE-48T cells was (52.43+/-5.30)%, but the apoptosis rate did not increase as the treatment time and concentration increased. After treatment of STI571, the expression of p-PDGFR-beta was inhibited in CE-48T cells, but didn't change in CE-81T cells. CONCLUSIONS: STI-571 could induce the apoptosis of PDGFR-beta-positive esophageal carcinoma CE-48T cells. p-PDGFR-beta might be the target of STI571.