Biomedical subjects

Yun Peng

Publications and source records attributed to Yun Peng.

8 recordsLinked to original sources

PubMed2025

Genomic subtypes of non-muscle-invasive bladder cancer: guiding immunotherapy decision-making for patients exposed to aristolochic acid.

BACKGROUND: The limited genomic data on non-muscle-invasive bladder cancer (NMIBC) hampers our understanding of its carcinogenesis and development. Specifically, Aristolochic acid (AA), a potent human carcinogenic compound from aristolochia plants and commonly found in Chinese herbal medicine, has been extensively documented as being closely associated with the onset and progression of bladder cancer. However, the field of AA-induced NMIBC remains largely unexplored in terms of its genomic and molecular characteristics, as well as clinical therapeutic strategies. METHODS: To bridge this knowledge gap, we conducted a comprehensive study using a cohort of 81 NMIBC samples. We performed whole-exome sequencing (WES) and RNA sequencing (RNA-seq) to obtain detailed genomic and transcriptomic data. We subjected these datasets to genomic analysis and subtype analysis to gain valuable insights into NMIBC. RESULTS: By temporally dissecting mutations in NMIBC specimens, we identified a comprehensive mutational landscape of NMIBC and the associations of these mutations with recurrence-free survival. Additionally, we discerned four genomic subtypes of NMIBC: AA-like, FGFR3/HRAS, FGFR3 & chr9Del, and genome instability (GI). The AA-like subtype presented a high frequency of gene mutations along with a pronounced AA mutagenesis signature of SBS22 (Fisher test: P-value 3.5e-4, OR 25.25) even after temporal dissection. The FGFR3/HRAS subtype exhibited FGFR3 or HRAS mutations with few copy number alterations (CNAs). The FGFR3 & chr9Del subtype was characterized by the co-occurrence of chr9p and chr9q deletions as well as FGFR3 mutations, while the GI subtype showed a high frequency of CNAs. Notably, the AA-like and GI subtypes demonstrated better outcomes after immunotherapy, whereas the FGFR3/HRAS subtype showed poorer outcomes. CONCLUSIONS: Our findings provide novel perspectives on the genomics of NMIBC, unveiling four prominent genomic subtypes, each showing different outcomes following immunotherapy. TRIAL REGISTRATION: No. 2019PHB268-01 (retrospectively registered on February 14, 2020).

Humans↗

PubMed2005

Generalization of a prototype intelligent hybrid system for hard gelatin capsule formulation development.

The aim of this project was to expand a previously developed prototype expert network for use in the analysis of multiple biopharmaceutics classification system (BCS) class II drugs. The model drugs used were carbamazepine, chlorpropamide, diazepam, ibuprofen, ketoprofen, naproxen, and piroxicam. Recommended formulations were manufactured and tested for dissolution performance. A comprehensive training data set for the model drugs was developed and used to retrain the artificial neural network. The training and the system were validated based on the comparison of predicted and observed performance of the recommended formulations. The initial test of the system resulted in high error values, indicating poor prediction capabilities for drugs other than piroxicam. A new data set, containing 182 batches, was used for retraining. Ten percent of the test batches were used for cross-validation, resulting in models with R2 > or = 70%. The comparison of observed performance to the predicted performance found that the system predicted successfully. The hybrid network was generally able to predict the amount of drug dissolved within 5% for the model drugs. Through validation, the system was proven to be capable of designing formulations that met specific drug performance criteria. By including parameters to address wettability and the intrinsic dissolution characteristics of the drugs, the hybrid system was shown to be suitable for analysis of multiple BCS class II drugs.

Artificial Intelligence↗

PubMed2005

Comparison of statistical analysis and Bayesian Networks in the evaluation of dissolution performance of BCS Class II model drugs.

This project compared the effect of formulation variables on the dissolution performance of model Biopharmaceutics Classification System (BCS) Class II drugs from hard gelatin capsules using statistical analysis and Bayesian networks. The drugs chosen for this study were carbamazepine (CAR), chlorpropamide (CHL), diazepam (DIA), ketoprofen (KET), and naproxen (NAP). Formulations contained anhydrous lactose, microcrystalline cellulose, sodium stearyl fumerate, sodium lauryl sulfate, and croscarmellose sodium. A Box-Behnken experimental design was used in the statistical analysis. The weakly acidic drugs were tested using USP apparatus II with capsule sinkers in 0.1M pH 6.8 Potassium Phosphate buffer. The weakly basic drugs were tested using USP apparatus I in 0.1N HCl buffer. Mean dissolution profiles were compared via calculation of the similarity factor. The Box-Behnken experimental design was found to be useful in assessing primary and secondary excipient effects on dissolution. The Bayesian Network developed for the dataset mirrored the key excipient effects on dissolution performance.

Bayes Theorem↗

PubMed2005

[A medical ultrasonic image filtering method based on anisotropic diffusion].

OBJECTIVE: To remove the speckle noise in ultrasonic images by using anisotropic diffusion method. METHOD: Based on anisotropic diffusion, a partial differential equation, of which the initial data was the input images, was transformed into differential forms and solved with iterations. The speckle scale function of the equation was modified to make better use in filtering medical ultrasonic images. RESULT: By comparing the results with other three filters, the anisotropic diffusion method could smooth the speckles very well and the edge of the image was also clear. CONCLUSION: Anisotropic diffusion can remove the speckle noise effectively and has great potential in filtering medical ultrasonic images.

Anisotropy↗

PubMed2003

Generation of hepatocyte-like cells from human embryonic stem cells.

Use of human hepatocytes for therapeutic and drug discovery applications is hampered by limited tissue source and the inability of hepatocytes to proliferate and maintain function long term in vitro. Human embryonic stem (hES) cells are immortal and pluripotent and may provide a cell source for functional human hepatocytes. We report here that hES cells can be induced to differentiate into hepatocyte-like cells. Treatment with sodium butyrate induced hepatic differentiation as well as significant cell death, resulting in approximately 10-15% yield of a homogeneous population of cells. The differentiated cells have morphological features similar to that of primary hepatocytes and 70-80% of the cells express liver-associated proteins (albumin, alpha-1-antitrypsin, cytokeratin 8 and 18), accumulate glycogen, have inducible cytochrome P450 activity, and do not express alpha-fetoprotein. Because of the inherent proliferative capacity of hES cells, these cells may provide a reliable source of normal human hepatocytes for research and transplantation.

Adult↗

PubMed2002

Conserved N-terminal motifs of telomerase reverse transcriptase required for ribonucleoprotein assembly in vivo.

Telomerase is a ribonucleoprotein (RNP) reverse transcriptase responsible for the maintenance of one strand of the telomere terminal repeats. The key protein subunit of the telomerase complex, known as TERT, possesses reverse transcriptase (RT)-like motifs that directly mediate nucleotide addition. The RT motifs are located in the C-terminal region of the polypeptide. Sequence alignments also revealed the existence of four conserved motifs (named GQ, CP, QFP, and T) in the N-terminal region of TERT. The GQ motif of yeast TERT has been demonstrated previously to be essential for telomerase catalysis and may participate in RNP formation. In this report, we show that substitution of conserved residues in the CP, QFP, and T motifs of yeast TERT also impairs both telomere maintenance and telomerase activity, thus confirming the validity of the sequence alignment. The extent of telomere shortening correlates with the extent of reduction in the level of telomerase activity, TERT protein, and TERT-associated TLC1 RNA. Overexpression of the mutant proteins does not result in telomere shortening, implying that assembly rather than catalytic function was affected. This notion was further supported by comparing the efficiency of RNP formation in the wild type and the overexpression strains. Taken together, our results show that three of the four N-terminal motifs are required for efficient telomerase RNP formation in vivo but not for the enzymatic function of telomerase. We also show that the majority of telomerase-associated TLC1 RNA has a more upstream 3' end than previously reported, consistent with additional processing events during RNP maturation.

Amino Acid Motifs↗

PubMedDate not supplied

Two-dimensional/ATR infrared correlation spectroscopic study on water diffusion in a poly(epsilon-caprolactone) matrix.

In the present contribution, two-dimensional ATR-FTIR spectroscopy was used to study the diffusion of water in poly(epsilon-caprolactone) (PCL). In the spectral region of the nu(OH) stretching vibration of water, four absorption bands (3635, 3560, 3411, and 3220 cm(-1)) can be identified. The higher wavenumber band pair at 3635 and 3560 cm(-1) is assigned to the antisymmetric and symmetric OH stretching vibrations, respectively, of water which is partially hydrogen-bonded to the carbonyl groups of PCL, whereas the lower frequency band pair at 3411 (antisymmetric) and 3220 cm(-1) (symmetric) is attributed to the OH stretching vibrations of bulk water which is fully hydrogen-bonded to other water molecules. From the asynchronous map of a 2D correlation analysis of spectra recorded during the diffusion of water into PCL, it was concluded that during the diffusion process the water molecules first penetrate into the free volume (microvoids) of the PCL matrix or are molecularly dispersed in the polymer matrix and then form hydrogen bonds with the C=O groups of the polymer.

Biocompatible Materials↗

PubMedDate not supplied

A neural network approach to approximating MAP in belief networks.

Bayesian belief networks (BBN) are a widely studied graphical model for representing uncertainty and probabilistic interdependence among variables. One of the factors that restricts the model's wide acceptance in practical applications is that the general inference with BBN is NP-hard. This is also true for the maximum a posteriori probability (MAP) problem, which is to find the most probable joint value assignment to all uninstantiated variables, given instantiation of some variables in a BBN. To circumvent the difficulty caused by MAP's computational complexity, we suggest in this paper a neural network approximation approach. With this approach, a BBN is treated as a neural network without any change or transformation of the network structure, and the node activation functions are derived based on an energy function defined over a given BBN. Three methods are developed. They are the hill-climbing style discrete method, the simulated annealing method, and the continuous method based on the mean field theory. All three methods are for BBN of general structures, with the restriction that nodes of BBN are binary variables. In addition, rules for applying these methods to noisy-or networks are also developed, which may lead to more efficient computation in some cases. These methods' convergence is analyzed, and their validity tested through a series of computer experiments with two BBN of moderate size and complexity. Although additional theoretical and empirical work is needed, the analysis and experiments suggest that this approach may lead to effective and accurate approximation for MAP problems.

Algorithms↗