HIF-1α Contributes to Hypoxia-induced Invasion and Metastasis of Esophageal Carcinoma via Inhibiting E-cadherin and Promoting MMP-2 Expression

Hypoxia-inducible factor-1α (HIF-1α) has been found to enhance tumor invasion and metastasis, but no study has reported its action in esophageal carcinoma. The goal of this study was to explore the probable mechanism of HIF-1α in the invasion and metastasis of esophageal carcinoma Eca109 cells in vitro and in vivo. mRNA and protein expression of HIF-1α, E-cadherin and matrix metalloproteinase-2 (MMP-2) under hypoxia were detected by RT-PCR and Western blotting. The effects of silencing HIF-1α on E-cadherin, MMP-2 mRNA and protein expression under hypoxia or normoxia were detected by RT-PCR and Western blotting, respectively. The invasive ability of Eca109 cells was tested using a transwell chambers. We established an Eca109-implanted tumor model and observed tumor growth and lymph node metastasis. The expression of HIF-1α, E-cadherin and MMP-2 in xenograft tumors was detected by Western blotting. After exposure to hypoxia, HIF-1α protein was up-regulated, both mRNA and protein levels of E-cadherin were down-regulated and MMP-2 was up-regulated, while HIF-1α mRNA showed no significant change. SiRNA could block HIF-1α effectively, increase E-cadherin expression and inhibit MMP-2 expression. The number of invading cells decreased after HIF-1α was silenced. Meanwhile, the tumor volume was much smaller, and the metastatic rate of lymph nodes and the positive rate were lower in vivo. Our observations suggest that HIF-1α inhibition might be an effective strategy to weaken invasion and metastasis in the esophageal carcinoma Eca109 cell line

Combined analysis of endometrial thickness and pattern in predicting outcome of in vitro fertilization and embryo transfer: a retrospective cohort study

<p>Abstract</p> <p>Objective</p> <p>To evaluate the combined effect of endometrial thickness and pattern on clinical outcome in patients undergoing in vitro fertilization/intracytoplasmic sperm injection and embryo transfer (IVF/ICSI-ET).</p> <p>Methods</p> <p>Cycles of IVF/ICSI-ET conducted between January 2003 and December 2008 at a university-based reproductive center were reviewed retrospectively. Endometrial ultrasonographic characteristics were recorded on the day of hCG administration. In the combined analysis, endometrial thickness groups (group 1: equal or <7 mm; group 2: 7-14 mm; group 3: >14 mm) were subdivided into two endometrial patterns (pattern A: triple-line; pattern B: no-triple line). Clinical pregnancy rate (CPR) and early miscarriage rate in different groups were analyzed.</p> <p>Results</p> <p>A total of 2896 cycles were reviewed. Clinical pregnancy rate (CPR) was 24.4% in group1-A. There were no second trimester pregnancies in group 1-B. Miscarriage rate in group 2-A was significantly lower compared to group 2-B (P < 0.01), although CPR did not show any significant differences between the groups. A no-triple line endometrial pattern with moderate endometrial thickness (7-14 mm) had a detrimental effect on pregnancy outcome, but not the occurrence of pregnancy. In group 3, there was no difference in CPR and miscarriage rates between the two patterns; adequate endometrial thickness (>14 mm) seemed to mitigate the detrimental impact (high miscarriage rate) of pattern B.</p> <p>Conclusion</p> <p>Combined analysis of endometrial thickness and pattern on the day of hCG administration was a better predictor of the outcome of IVF/ICSI-ET and may be more helpful for patient counseling than the separate analyses.</p

Revealing metabolite biomarkers for acupuncture treatment by linear programming based feature selection

BACKGROUND: Acupuncture has been practiced in China for thousands of years as part of the Traditional Chinese Medicine (TCM) and has gradually accepted in western countries as an alternative or complementary treatment. However, the underlying mechanism of acupuncture, especially whether there exists any difference between varies acupoints, remains largely unknown, which hinders its widespread use. RESULTS: In this study, we develop a novel Linear Programming based Feature Selection method (LPFS) to understand the mechanism of acupuncture effect, at molecular level, by revealing the metabolite biomarkers for acupuncture treatment. Specifically, we generate and investigate the high-throughput metabolic profiles of acupuncture treatment at several acupoints in human. To select the subsets of metabolites that best characterize the acupuncture effect for each meridian point, an optimization model is proposed to identify biomarkers from high-dimensional metabolic data from case and control samples. Importantly, we use nearest centroid as the prototype to simultaneously minimize the number of selected features and the leave-one-out cross validation error of classifier. We compared the performance of LPFS to several state-of-the-art methods, such as SVM recursive feature elimination (SVM-RFE) and sparse multinomial logistic regression approach (SMLR). We find that our LPFS method tends to reveal a small set of metabolites with small standard deviation and large shifts, which exactly serves our requirement for good biomarker. Biologically, several metabolite biomarkers for acupuncture treatment are revealed and serve as the candidates for further mechanism investigation. Also biomakers derived from five meridian points, Zusanli (ST36), Liangmen (ST21), Juliao (ST3), Yanglingquan (GB34), and Weizhong (BL40), are compared for their similarity and difference, which provide evidence for the specificity of acupoints. CONCLUSIONS: Our result demonstrates that metabolic profiling might be a promising method to investigate the molecular mechanism of acupuncture. Comparing with other existing methods, LPFS shows better performance to select a small set of key molecules. In addition, LPFS is a general methodology and can be applied to other high-dimensional data analysis, for example cancer genomics

Nursing care in osteopetrosis treated by optic nerve decompression under image guidance system combined with endoscopic approach

AIM: To explore the nursing cooperation highlights of eight osteopetrosis patients underwent optic nerve decompression via transsphenoidal microsurgical approach instead of routine pathway, and to improve the quality of nursing cooperation. METHODS: We enrolled 8 cases(left eye in 3 cases, right eye in 5 cases)of osteopetrosis patients referred from the Eye Hospital of Wenzhou Medical University during February 2012 to November 2016. Patients received ophthalmic examinations including visual acuity and diagnostic imaging tests in pre-operation and post-operation. All eyes were performed surgical optic nerve decompression through endoscopic approach in assist of image guidance system. We retrospectively analyzed the clinical data and surgical cooperation procedure of these cases and summarized nursing cooperation experience. RESULTS: The operations of 8 patients were completed successfully without massive hemorrhage. Mean visual acuity improved from pre-operation(2.5±2.1)to post-operation(3.4±1.9). Cerebrospinal fluid leakage occurred in 1 patient and was instantly repaired during the operation. We performed the nursing strategy as postural drainage, condition monitoring and conscious assessment intra-and post-operation. CONCLUSION: It is the critical for this kind of surgery that both circulating nurse's high-skilled cooperation to the connection and operation of the navigation system, to treat with complication during the surgery, and scrub nurse's sufficient preparation of surgical instruments and consumables, proficient equipment delivery, meticulous management, use and maintenance of equipment

Capn2 Correlates With insulin Resistance States in Pcos as Evidenced By Multi-Dataset analysis

OBJECTIVE: IR emerges as a feature in the pathophysiology of PCOS, precipitating ovulatory anomalies and endometrial dysfunctions that contribute to the infertility challenges characteristic of this condition. Despite its clinical significance, a consensus on the precise mechanisms by which IR exacerbates PCOS is still lacking. This study aims to harness bioinformatics tools to unearth key IR-associated genes in PCOS patients, providing a platform for future therapeutic research and potential intervention strategies. METHODS: We retrieved 4 datasets detailing PCOS from the GEO, and sourced IRGs from the MSigDB. We applied WGCNA to identify gene modules linked to insulin resistance, utilizing IR scores as a phenotypic marker. Gene refinement was executed through the LASSO, SVM, and Boruta feature selection algorithms. qPCR was carried out on selected samples to confirm findings. We predicted both miRNA and lncRNA targets using the ENCORI database, which facilitated the construction of a ceRNA network. Lastly, a drug-target network was derived from the CTD. RESULTS: Thirteen genes related to insulin resistance in PCOS were identified via WGCNA analysis. LASSO, SVM, and Boruta algorithms further isolated CAPN2 as a notably upregulated gene, corroborated by biological verification. The ceRNA network involving lncRNA XIST and hsa-miR-433-3p indicated a possible regulatory link with CAPN2, supported by ENCORI database. Drug prediction analysis uncovered seven pharmacological agents, most being significant regulators of the endocrine system, as potential candidates for addressing insulin resistance in PCOS. CONCLUSIONS: This study highlights the pivotal role of CAPN2 in insulin resistance within the context of PCOS, emphasizing its importance as both a critical biomarker and a potential therapeutic target. By identifying CAPN2, our research contributes to the expanding evidence surrounding the CAPN family, particularly CAPN10, in insulin resistance studies beyond PCOS. This work enriches our understanding of the mechanisms underlying insulin resistance, offering insights that bridge gaps in the current scientific landscape

Down-regulation of Stargazin Inhibits the Enhanced Surface Delivery of α-Amino-3-hydroxy-5-methyl-4-isoxazole Propionate Receptor GluR1 Subunit in Rat Dorsal Horn and Ameliorates Postoperative Pain

Stargazin is the first transmembrane protein known to regulate synaptic targeting of α-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA) receptors. Yet, it is unclear whether regulation of the surface delivery of spinal AMPA receptor subunits by stargazin contributes to postoperative pain development

Detection of the introgression loci in Triticum aestivum transferred from Aegilops tauschii by simple sequence repeat (SSR) markers

Aegilops tauschii possesses many valuable traits or genes. The introgression loci transferred from A. tauschii in populations of 64 lines of BC1F2 and 147 advanced lines of BC1F2-F7 derived from the cross of Chinese Spring (CS; Triticum aestivum) /SQ-214 (A. tauschii) //SW3243 (T. aestivum) was characterized using simple sequence repeat (SSR) markers. 68 polymorphic loci covering the D genome were used to analyze the distribution of A. tauschii SQ-214 introgression loci in the two derived populations. The result shows that 82.35% loci of A. tauschii SQ-214 were detected in BC1F2 population, while the frequency of introgression loci was 51.47% in the advanced lines of BC1F2-F7 after artificial selection for stripe rust resistance and agronomic traits. Significant changes of the distribution frequency for the same introgression loci between BC1F2 and BC1F2-F7 populations were observed, and seven selective advantage loci from A. tauschii (Xgdm128-3D, Xgdm8-3D, Xgdm72-3D, Xgwm341-3D, Xgdm63-5D, Xgdm132-6D and Xgdm36-6D) were found, which introgression loci distribution frequency increased from 29.69 to 53.91% (BC1F2) to 94.22 to 100% (BC1F2-F7). The selective advantage loci could be used to evaluate the desirable genes or traits derived from A. tauschii SQ-214.Key words: Aegilops tauschii, Triticum aestivum, introgression locus

MiniZero: Comparative Analysis of AlphaZero and MuZero on Go, Othello, and Atari Games

This paper presents MiniZero, a zero-knowledge learning framework that supports four state-of-the-art algorithms, including AlphaZero, MuZero, Gumbel AlphaZero, and Gumbel MuZero. While these algorithms have demonstrated super-human performance in many games, it remains unclear which among them is most suitable or efficient for specific tasks. Through MiniZero, we systematically evaluate the performance of each algorithm in two board games, 9x9 Go and 8x8 Othello, as well as 57 Atari games. For two board games, using more simulations generally results in higher performance. However, the choice of AlphaZero and MuZero may differ based on game properties. For Atari games, both MuZero and Gumbel MuZero are worth considering. Since each game has unique characteristics, different algorithms and simulations yield varying results. In addition, we introduce an approach, called progressive simulation, which progressively increases the simulation budget during training to allocate computation more efficiently. Our empirical results demonstrate that progressive simulation achieves significantly superior performance in two board games. By making our framework and trained models publicly available, this paper contributes a benchmark for future research on zero-knowledge learning algorithms, assisting researchers in algorithm selection and comparison against these zero-knowledge learning baselines. Our code and data are available at https://rlg.iis.sinica.edu.tw/papers/minizero.Comment: Submitted to IEEE Transactions on Games, under revie