Biology subjects

Jie, T.

Publications and source records attributed to Jie, T..

5 recordsLinked to original sources

bioRxiv2026

Phase-noise tolerant fully-coherent optical coherence tomography angiography for high-contrast 3D microvasculature mapping

Optical coherence tomography angiography (OCTA) has been extensively explored for the detection of pathological retinal changes arising in various ophthalmological diseases. Due to phase instability of conventional systems, most OCTA signal processing methods to date have relied on intensity-based averaging, despite the resulting lower contrast and dynamic range compared to coherent averaging approaches. In this work, we (1) present a novel computation pipeline that enables fully-coherent processing in any phase-stable or phase-unstable system, and (2) demonstrate the first angiography metric with integrated signal-to-noise ratio (SNR) correction and coherent spatiotemporal ensemble averaging effective in any OCT system. Our method does not rely on 2D en face projections or binarization to produce high-contrast en face views and it significantly enhances the contrast-to-noise ratio of computed OCTA volumes, particularly in regions with reduced SNR levels. Our OCTA volumes also have high cross-sectional quality, enabling the use of single-depth en face views and the localization of capillary paths in the axial dimension. We can now identify capillaries below the retinal pigment epithelium, near the lamina cribrosa in the optic cup, which was not previously possible due to low SNR. We also conducted an analysis of strategies for bias reduction in OCTA and developed the optimal method utilizing coherent spatiotemporal ensemble averaging. Because our method leverages coherent averaging across all dimensions, it provides flexibility in shaping the averaging kernel to target specific workflows. The value of this additional degree of freedom is illustrated in our vessel tracing investigations, in which the depth resolution was maximized by limiting coherent ensemble averaging to the two lateral dimensions even in presence of strong phase noise, enabling the identification of 3D features such as overlapping capillary paths.

bioengineering↗

bioRxiv2022

Exosome-derived lncRNA HOXA-AS3 promotes castration resistance and progression of prostate cancer via the miR-29b-3p/Mcl-1/STAT3 axis

Prostate cancer is one of the leading causes of cancer-related deaths in men. While endocrine therapy is effective in the early stage of metastasis, significantly inhibits the progression of metastatic prostate cancer, most patients eventually develop CRPC. Tumor microenvironment are involved in the progression of prostate cancer as an "accomplice", cancer cell-secreted exosomes were identified as crucial messengers can carry lncRNAs to participate in intercellular communication. we revealed PC-3-derived exosomes promote androgen resistance in LNCaP cells. HOXA-AS3 as a ceRNA of miRNA-29b-3p affects the proliferation and invasion ability of prostate cancer cells. A series of molecular experiments, cell experiments and clinical tissue verification experiments confirmed that HOXA-AS3 participates in the castration resistance and progression of prostate cancer through regulating the miR-29b-3p/Mcl-1/STAT3/Cytochrome C/caspases-9 pathway. Dysregulation of HOXA-AS3 is observed in many cancer types, and this study shows the importance of this lncRNA in controlling prostate cancer cell progression, thus highlighting it as a potential biomarker for inhibiting prostate cancer progression and a target for immunotherapy.

genomics↗

bioRxiv2020

Inhibition of Sphingosine-1-Phosphate signaling in pancreatic ductal adenocarcinoma leads to downregulation of growth and invasion

BackgroundDeregulated phosphorylation of sphingosine by the sphingosine kinases and signaling through the EDG family of receptors enhances growth and survival in many cell types. Therefore, we sought to elucidate the effect of alterations in the ceramide/sphingosine/S1P rheostat on driving human pancreatic ductal adenocarcinoma towards a malignant phenotype. MethodsPancreatic cancer cell lines were treated with exogenous S1P, FTY720, and siRNA to Sphk1. Migration was evaluated by wound healing assays, cell growth by MTT assays, and invasion by tumorsphere assays. Expression of S1PR1, S1PR3, Sphk1, and Sphk2 were measured by quantitative PCR, western blot, and immunohistochemistry. ResultsS1PR1, S1PR3, and Sphk2 were overexpressed in all pancreatic cancer cell lines. Sphk1 translocated from the cytoplasm to the nucleus in cells located at the leading edge of cell clusters. Exogenous S1P increased cell migration while treatment with FTY720 and Sphk1 siRNA decreased cell growth and invasion. ConclusionsOur results suggest that increased S1PR1 expression may be an early event in pancreatic cancer pathogenesis. Additionally, altered Sphk1 localization may provide a mechanism through which pancreatic ductal adenocarcinoma cells at the leading edge invade into the surrounding matrix. Finally, inhibition of sphingosine-1-phosphate signaling may provide a novel therapeutic target for patients with metastatic disease.

cancer biology↗

bioRxiv2020

Cell intrinsic signaling in MEN1 mutant pancreatic neuroendocrine tumors unveils novel signaling pathways associated with de-differentiation

ObjectivesPreliminary genomic analysis of primary pancreatic neuroendocrine tumors revealed a complex mutational landscape with four common oncogenic events; however, critical activation pathways responsible for pancreatic neuroendocrine tumor progression and metastasis have yet to be elucidated. Here, we analyzed six primary pancreatic neuroendocrine tumors to determine which pathways are deregulated and responsible for progression. MethodsSelected genomic profiling of six primary pancreatic neuroendocrine tumors was performed using the Ion Torrent Comprehensive Cancer Panel with matched transcriptomes analyzed by Affymetrix Clariom D arrays. Validation of gene expression changes were measured by quantitative PCR using TaqMan assays and immunohistochemistry on tumor specimens. ResultsMEN1 was mutated in half (50%) of our sequenced tumors while FGFR3 was mutated in 2/6 (33%). Transcriptome analysis revealed that ITGA2 and EZH2 were overexpressed in MEN1 mutant tumors whereas ALK and VEGFA were overexpressed in FGFR3 mutant tumors. Immunohistochemistry revealed increased nuclear ITGA2 and EZH2 staining along with increased VE-Cadherin staining and loss of membranous E-cadherin localization in MEN1 and FGFR3 mutant tumors. ConclusionsOur results suggest that pancreatic neuroendocrine tumors containing MEN1 and FGFR3 mutations are more aggressive and de-differentiated than their wild-type counterparts. Additionally, we provide novel chemotherapeutic target FGFR3 for patients with this disease.

cancer biology↗

bioRxiv2019

Predicting the risk of sarcopenia in elderly patients with patellar fracture: Development and assessment of a new predictive nomogram

PurposeThis study was aimed at developing a risk prediction model for postoperative dysplasia in elderly patients with patellar fractures in China.\n\nPatients and methodsWe conducted a community survey of patients aged [≥]55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (Lasso analysis). The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We conducted internal sampling methods for qualitative assessment.\n\nResultWe recruited 61 participants (males: 20, mean age: 68.1 years). Various risk factors were assessed, and low body mass index and diabetes mellitus were identified as the most important risk factors (P<0.05). The model showed a good prediction rate (C-index: 0.909; 95% confidence interval: 0.81-1.00) and good correction effect. The C-index remained high (0.828) even after internal sample verification. Decision curve analysis showed that the risk of sarcopenia was 8.3-80.0%, suggesting good clinical practicability.\n\nConclusionOur prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, longer postoperative hospital stay, no higher education, no postoperative rehabilitation, removal of internal fixation, and less outdoor exercise.

bioinformatics↗