137 research outputs found
Advancing Medical Imaging with Language Models: A Journey from N-grams to ChatGPT
In this paper, we aimed to provide a review and tutorial for researchers in
the field of medical imaging using language models to improve their tasks at
hand. We began by providing an overview of the history and concepts of language
models, with a special focus on large language models. We then reviewed the
current literature on how language models are being used to improve medical
imaging, emphasizing different applications such as image captioning, report
generation, report classification, finding extraction, visual question
answering, interpretable diagnosis, and more for various modalities and organs.
The ChatGPT was specially highlighted for researchers to explore more potential
applications. We covered the potential benefits of accurate and efficient
language models for medical imaging analysis, including improving clinical
workflow efficiency, reducing diagnostic errors, and assisting healthcare
professionals in providing timely and accurate diagnoses. Overall, our goal was
to bridge the gap between language models and medical imaging and inspire new
ideas and innovations in this exciting area of research. We hope that this
review paper will serve as a useful resource for researchers in this field and
encourage further exploration of the possibilities of language models in
medical imaging
Valence Band Offsets of ZnO/SrTiO3, ZnO/BaTiO3, InN/SrTiO3, and InN/BaTiO3 Heterojunctions Measured by X-Ray Photoelectron Spectroscopy
Molecular insights into structural and dynamic properties of water molecules in calcium silicate hydrate nanopores: The roles of pore size and temperature
Calcium silicate hydrate is the primary hydration product of Portland cement and plays a crucial role in determining the strength of cement-based materials. The structural and dynamic properties of water molecules within calcium silicate hydrate nanopores have significant implications for the mechanical and durability performance of these materials. However, the influences of pore size and temperature on the properties of water molecules have not been fully explored. In this work, using molecular dynamics simulations and theoretical analysis, the evolution and mechanisms of the structural and dynamic properties of water molecules in different scenarios with various pore sizes and temperatures are systematically investigated. It is shown that the diffusion coefficients of water molecules increase with both pore size and temperature. Moreover, water molecules have a tendency to adsorb onto calcium silicate hydrate substrates, forming a distinct layered structure. As a result, the water molecules near the surfaces of calcium silicate hydrate substrates exhibit limited mobility, leading to smaller diffusion coefficients compared to those in other regions. Additionally, the distinctions in properties between water molecules and Ca2+ ions are elucidated and the underlying mechanisms behind these differences are also unveiled. The results and findings in this work deepen the understanding of structural and dynamic properties of water molecules within calcium silicate hydrate nanopores, providing valuable insights for improving the mechanical and durability performance of cement-based materials.Document Type: Original articleCited as: Liu, S., A, H., Tang, S., Kai, M., Yang, Z. Molecular insights into structural and dynamic properties of water molecules in Calcium silicate hydrate nanopores: The roles of pore size and temperature. Capillarity, 2023, 8(2): 23-33. https://doi.org/10.46690/capi.2023.08.0
Methanol extract of Aruncus dioicus exerts antidiabetic effect via PCSK9/LDLR pathway
Purpose: To investigate the antidiabetic effect of methanol extract of Aruncus dioicus, and the underlying mechanism(s).
Methods: Twenty-four adult female albino mice were randomly assigned to four groups of six mice each: normal control group, diabetic control group and two treatment groups. With the exception of normal control group, the diabetic control and treatment groups consisted of leptin receptor-deficient (db/db) type 2 diabetic mice. The diabetic control group was not treated, while the treatment groups received 200 or 400 mg/kg extract/day orally for 4 weeks. The effect of the extract on fasting blood glucose (FBG), proprotein convertase subtilisin/kexin type 9 (PCSK9), glycogen and lipid profiles were determined. The expressions of PCSK9, low-density lipoprotein receptor (LDL-R) and glucokinase (GCK) were determined in liver tissues using western blotting and real-time quantitative polymerase chain reaction (qRT-PCR).
Results: Fasting blood glucose (FBG) was significantly and dose-dependently reduced in the treatment groups, relative to diabetic control group at different time-points (p < 0.05). Total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) were significantly higher in the diabetic control group than in normal control group (p < 0.05). However, treatment with methanol extract of A. dioicus significantly and dose-dependently reversed the changes in the levels of these parameters (p < 0.05). The expressions of LDLR and GCK were significantly down-regulated in diabetic control group, when compared with normal control group, but their expressions were significantly dose-dependently upregulated in the treatment groups (p < 0.05). Treatment with the extract significantly and dose-dependently down-regulated PCSK9 expression (p < 0.05). Liver injury characterized by large distended lipid droplets and fat accumulation was seen in diabetic mice, but treatment with methanol extract of A. dioicus significantly reversed the histopathological changes induced by DM.
Conclusion: These results indicate that the antidiabetic effect of methanol extract of A. dioicus is exerted via a mechanism involving PCSK9/LDLR pathway
Overexpression of lncRNA-MEG3 inhibits endometrial cell proliferation and invasion via miR-21–5p/DNMT3B/Twist
Recent studies have found that lncRNA-MEG3(MEG3) plays an important role in the development of EMs (Endometriosis), but the specific mechanism needs to be further explored. This study aimed to investigate the effect of MEG3 on the proliferation, invasion of EMs cells. The authors used RT-qPCR to detect the expression of MEG3 and miR-21–5p in EMs tissues and hESCs cells, MTT and Transwell to detect cell proliferation and invasion, western blotting assay to detect the expression of DNMT3B and Twist, MSP to detect the methylation of Twist. The present study's detection results showed that MEG3 was lowly expressed in EMs tissues and hESCs cells, and overexpression of MEG3 could down-regulate miR-21–5p and inhibit endometrial cell proliferation and invasion. In addition, overexpression of MEG3 upregulated the expression of DNMT3B and promoted the methylation of TWIST. In conclusion, the present findings suggest that MEG3 is downregulated in EMs tissues, and overexpression of MEG3 can promote the activity of DNA methyltransferase DNMT3B by downregulating miR-21–5p, thereby promoting the methylation of Twist, downregulating Twist level to inhibits hESCs cells proliferation and invasion
Differential expression of decorin, EGFR and cyclin D1 during mammary gland carcinogenesis in TA2 mice with spontaneous breast cancer
<p>Abstract</p> <p>Background</p> <p>The Tientsin Albino 2 (TA2) mouse is an inbred strain originating from the Kunming strain. It has a high incidence of spontaneous breast cancer without the need for external inducers or carcinogens. Until now, the mechanism of carcinogenesis has remained unclear. In this study, we investigate differential gene expression, especially the expression of decorin, EGFR and cyclin D1, during mammary gland epithelial cell carcinogenesis in TA2 mice.</p> <p>Methods</p> <p>Gene expression profiles of spontaneous breast cancer and matched normal mammary gland tissues in TA2 mice were ascertained using an Affymetrix Mouse 430 2.0 array. Twelve mammary tissue samples from five month-old female TA2 mice (Group A), as well as 28 samples from mammary (Group B) and cancer tissues (Group C) of spontaneous breast cancer-bearing TA2 mice, were subsequently used to detect the expression of decorin, EGFR and cyclin D1 by real-time PCR and immunohistochemical methods.</p> <p>Results</p> <p>Several imprinted genes, oncogenes and tumor suppressor genes were differentially expressed between normal mammary gland tissues and breast cancer tissues of TA2 mice. The imprinted gene decorin and the oncogene EGFR were down-regulated in tumor tissues, while the oncogene cyclin D1 was up-regulated. Immunohistochemistry showed that samples in Group A showed high decorin expression more frequently than those in Group B (<it>P </it>< 0.05). More tissue samples in Group B than Group A were positive for nuclear EGFR, and tissue samples in Group B more frequently showed high nuclear EGFR expression than those in Group A or Group C (<it>P </it>< 0.05). The labeling index for cyclin D1 in Group C was significantly higher than in Group B. Mammary tissues of Group A expressed the highest level of decorin mRNA (<it>P </it>< 0.05), and mammary tissues of Group B expressed the highest level of EGFR mRNA (<it>P </it>< 0.05), while cancer tissues expressed the highest level of cyclin D1 mRNA (<it>P </it>< 0.05).</p> <p>Conclusions</p> <p>The expression of decorin, EGFR and cyclin D1 in mammary epithelial cells changes with increasing age. The abnormal expression of them may partly contribute to the genesis of spontaneous breast cancer in TA2 mice.</p
Valence band offset of InN/BaTiO3 heterojunction measured by X-ray photoelectron spectroscopy
X-ray photoelectron spectroscopy has been used to measure the valence band offset of the InN/BaTiO(3 )heterojunction. It is found that a type-I band alignment forms at the interface. The valence band offset (VBO) and conduction band offset (CBO) are determined to be 2.25 ± 0.09 and 0.15 ± 0.09 eV, respectively. The experimental VBO data is well consistent with the value that comes from transitivity rule. The accurate determination of VBO and CBO is important for use of semiconductor/ferrroelectric heterojunction multifunctional devices
Data-Driven Volumetric Image Generation from Surface Structures using a Patient-Specific Deep Leaning Model
The advent of computed tomography significantly improves patient health
regarding diagnosis, prognosis, and treatment planning and verification.
However, tomographic imaging escalates concomitant radiation doses to patients,
inducing potential secondary cancer. We demonstrate the feasibility of a
data-driven approach to synthesize volumetric images using patient surface
images, which can be obtained from a zero-dose surface imaging system. This
study includes 500 computed tomography (CT) image sets from 50 patients.
Compared to the ground truth CT, the synthetic images result in the evaluation
metric values of 26.9 Hounsfield units, 39.1dB, and 0.965 regarding the mean
absolute error, peak signal-to-noise ratio, and structural similarity index
measure. This approach provides a data integration solution that can
potentially enable real-time imaging, which is free of radiation-induced risk
and could be applied to image-guided medical procedures
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