Summary of biological research on hepatoblastoma: a scoping review.

Background: Hepatoblastoma is the most prevalent primary hepatic malignancy in children, comprising 80% of pediatric hepatic malignancies and 1% of all pediatric malignancies. However, traditional treatments have proven inadequate in effectively curing hepatoblastoma, leading to a poor prognosis. Methods: A literature search was conducted on multiple electronic databases (PubMed and Google Scholar). A total of 86 articles were eligible for inclusion in this review. Result: This review aims to consolidate recent developments in hepatoblastoma research, focusing on the latest advances in cancer-associated genomics, epigenetic studies, transcriptional programs and molecular subtypes. We also discuss the current treatment approaches and forthcoming strategies to address cancer-associated biological challenges. Conclusion: To provide a comprehensive summary of the molecular mechanisms associated with hepatoblastoma occurrence, this review highlights three key aspects: genomics, epigenetics, and transcriptomics. Our review aims to facilitate the exploration of novel molecular mechanisms and the development of innovative clinical treatment strategies for hepatoblastoma.

Severe congenital neutropenia and liver abscess: Surgical treatment breaks the vicious cycle.

Here, we present a case with genetically confirmed SCN. The main symptom of the child was recurring fever. The combination of antibiotics combined with G-CSF injection was proved to be insufficient, and the patient developed "solid" liver abscess. After undergoing surgical anatomical hepatic lobectomy, the child's infection symptoms showed improvement. The postoperative culture of the purulent material from the liver infection lesion revealed an infection with Staphylococcus aureus. Our case raises the possibility of pathogen sources and routes of infection, clinical characteristics, and effective treatment for SCN patients with concomitant liver abscess.

A comparative proteomic study identified calreticulin and prohibitin up-regulated in adrenocortical carcinomas.

BACKGROUND: Identifying novel tumor biomarkers to develop more effective diagnostic and therapeutic strategies for patients with ACC is urgently needed. The aim of the study was to compare the proteomic profiles between adrenocortical carcinomas (ACC) and normal adrenocortical tissues in order to identify novel potential biomarkers for ACC. METHODS: The protein samples from 12 ACC tissues and their paired adjacent normal adrenocortical tissues were profiled with two-dimensional electrophoresis; and differentially expressed proteins were identified by mass spectrometry. Expression patterns of three differently expressed proteins calreticulin, prohibitin and HSP60 in ACC, adrenocortical adenomas (ACA) and normal adrenocortical tissues were further validated by immunohistochemistry. RESULTS: In our proteomic study, we identified 20 up-regulated and 9 down-regulated proteins in ACC tissues compared with paired normal controls. Most of the up-regulated proteins were focused in protein binding and oxidoreductase activity in Gene Ontology (GO) molecular function classification. By immunohistochemistry, two biomarkers calreticulin and prohibitin were validated to be overexpressed in ACC compared with adrenocortical adenomas (ACA) and normal tissues, but also calreticulin overexpression was significantly associated with tumor stages of ACC. CONCLUSION: For the first time, calreticulin and prohibitin were identified to be novel candidate biomarkers for ACC, and their roles during ACC carcinogenesis and clinical significance deserves further investigation. VIRTUAL SLIDES: The virtual slides for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1897372598927465.

Wavelet-based ECG data compression system with linear quality control scheme.

Maintaining reconstructed signals at a desired level of quality is crucial for lossy ECG data compression. Wavelet-based approaches using a recursive decomposition process are unsuitable for real-time ECG signal recoding and commonly obtain a nonlinear compression performance with distortion sensitive to quantization error. The sensitive response is caused without compromising the influences of word-length-growth (WLG) effect and unfavorable for the reconstruction quality control of ECG data compression. In this paper, the 1-D reversible round-off nonrecursive discrete periodic wavelet transform is applied to overcome the WLG magnification effect in terms of the mechanisms of error propagation resistance and significant normalization of octave coefficients. The two mechanisms enable the design of a multivariable quantization scheme that can obtain a compression performance with the approximate characteristics of linear distortion. The quantization scheme can be controlled with a single control variable. Based on the linear compression performance, a linear quantization scale prediction model is presented for guaranteeing reconstruction quality. Following the use of the MIT-BIH arrhythmia database, the experimental results show that the proposed system, with lower computational complexity, can obtain much better reconstruction quality control than other wavelet-based methods.

A linear quality control design for high efficient wavelet-based ECG data compression.

In ECG data compression, maintaining reconstructed signal with desired quality is crucial for clinical application. In this paper, a linear quality control design based on the reversible round-off non-recursive discrete periodized wavelet transform (RRO-NRDPWT) is proposed for high efficient ECG data compression. With the advantages of error propagation resistance and octave coefficient normalization, RRO-NRDPWT enables the non-linear quantization control to obtain an approximately linear distortion by using a single control variable. Based on the linear programming, a linear quantization scale prediction model is presented for the quality control of reconstructed ECG signal. Following the use of the MIT-BIH arrhythmia database, the experimental results show that the proposed system, with lower computational complexity, can obtain much better quality control performance than that of other wavelet-based systems.

High efficient ECG compression based on reversible round-off non-recursive 1-D discrete periodized wavelet transform.

Error propagation and word-length-growth are two intrinsic effects influencing the performance of wavelet-based ECG data compression methods. To overcome these influences, a non-recursive 1-D discrete periodized wavelet transform (1-D NRDPWT) and a reversible round-off linear transformation (RROLT) theorem are developed. The 1-D NRDPWT can resist truncation error propagation in decomposition processes. By suppressing the word- length-growth effect, RROLT theorem enables the 1-D NRDPWT process to obtain reversible octave coefficients with minimum dynamic range (MDR). A non-linear quantization algorithm with high compression ratio (CR) is also developed. This algorithm supplies high and low octave coefficients with small and large decimal quantization scales, respectively. Evaluation is based on the percentage root-mean-square difference (PRD) performance measure, the maximum amplitude error (MAE), and visual inspection of the reconstructed signals. By using the MIT-BIH arrhythmia database, the experimental results show that this new approach can obtain a superior compression performance, particularly in high CR situations.

A novel ECG data compression method based on nonrecursive discrete periodized wavelet transform.

In this paper, a novel electrocardiogram (ECG) data compression method with full wavelet coefficients is proposed. Full wavelet coefficients involve a mean value in the termination level and the wavelet coefficients of all octaves. This new approach is based on the reversible round-off nonrecursive one-dimensional (1-D) discrete periodized wavelet transform (1-D NRDPWT), which performs overall stages decomposition with minimum register word length and resists truncation error propagation. A nonlinear word length reduction algorithm with high compression ratio (CR) is also developed. This algorithm supplies high and low octave coefficients with small and large decimal quantization scales, respectively. This quantization process can be performed without an extra divider. The two performance parameters, CR and percentage root mean square difference (PRD), are evaluated using the MIT-BIH arrhythmia database. Compared with the SPIHT scheme, the PRD is improved by 14.95% for 4 < or = CR < or = 12 and 17.6% for 14 < or = CR < or = 20.