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Mass spectrometry data may be affected by random noise and baseline drift due to experimental instruments and conditions, posing significant challenges for detecting spectral peaks, particularly when identifying weak and separating overlapping peaks. To increase the sensitivity and enhance the resolution, we propose a mass spectral peak detection algorithm that integrates resolution enhancement and image segmentation. Initially, the extended Mexican hat wavelet is proposed by integrating the peak sharpening method with its wavelet. This approach accurately transforms mass spectra into wavelet space using the continuous wavelet transform. Subsequently, the triangular single-peak thresholding method, a more suitable threshold segmentation approach for spectral analysis, is introduced to identify ridges in the two-dimensional wavelet space. Compared to traditional Otsu and its improved variants, long-tailed single-peaked histograms are more effectively processed by this method with lower computational complexity, enabling faster identification of segmentation thresholds and image segmentation. Ultimately, peak positions are determined by utilizing ridge and valley lines in wavelet space along with the original spectrum. To evaluate the performance of the peak recognition algorithm, two metrics are introduced: the receiver operating characteristic (ROC) curve and the balanced F score (F1 score). When compared to multi-scale peak detection (MSPD), continuous wavelet transform and image segmentation (CWT-IS), the developed approach is more suitable for weak and highly overlapping peaks. The robustness and practicality of the method are verified through peak detection using matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectra. [ABSTRACT FROM AUTHOR]

The belief in the people is a constant conviction of Li Dazhao, a major founder of Chinese Communist Party. This belief is an important theoretical basis and an ideological weapon for Li to pay attention to people's livelihood, to comment on social and political issues, and to ultimately establish Chinese Communist Party. The essence of Li's belief in the people resides in his determination to raise peopled quality, protect peopled livelihood, and respect people's initiatives. To review Li's belief in the people and to rely closely on the vast majority of the people is of significant theoretical and practical value to steadily promote China's reforming and construction, and to give China an invincible position in the process of social transition. [ABSTRACT FROM AUTHOR]

Purpose: Early and rapid diagnosis of mild cognitive impairment (MCI) has important clinical value in improving the prognosis of Alzheimer's disease (AD). The hippocampus and parahippocampal gyrus play crucial roles in the occurrence of cognitive function decline. In this study, deep learning and radiomics techniques were used to automatically detect MCI from healthy controls (HCs)., Method: This study included 115 MCI patients and 133 normal individuals with 3D-T1 weighted MR structural images from the ADNI database. The identification and segmentation of the hippocampus and parahippocampal gyrus were automatically performed with a VB-net, and radiomics features were extracted. Relief, Minimum Redundancy Maximum Correlation, Recursive Feature Elimination and the minimum absolute shrinkage and selection operator (LASSO) were used to reduce the dimensionality and select the optimal features. Five independent machine learning classifiers including Support Vector Machine (SVM), Random forest (RF), Logistic Regression (LR), Bagging Decision Tree (BDT), and Gaussian Process (GP) were trained on the training set, and validated on the testing set to detect the MCI. The Delong test was used to assess the performance of different models., Result: Our VB-net could automatically identify and segment the bilateral hippocampus and parahippocampal gyrus. After four steps of feature dimensionality reduction, the GP models based on combined features (11 features from the hippocampus, and 4 features from the parahippocampal gyrus) showed the best performance for the MCI and normal control subject discrimination. The AUC of the training set and test set were 0.954 (95% CI: 0.929-0.979) and 0.866 (95% CI: 0.757-0.976), respectively. Decision curve analysis showed that the clinical benefit of the line graph model was high., Conclusion: The GP classifier based on 15 radiomics features of bilateral hippocampal and parahippocampal gyrus could detect MCI from normal controls with high accuracy based on conventional MR images. Our fully automatic model could rapidly process the MRI data and give results in 1 minute, which provided important clinical value in assisted diagnosis., Competing Interests: FS and YX were employed by Shanghai United Imaging Intelligence, Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yang, Meng, Wu, Shi, Xia, Feng, Zhang and Li.)

Objective: To study on the inhibitory effects of juice of tomato on the growth of human prostate carcinoma PC-3 cells and its possible mechanism., Methods: PC-3 cells were treated with the juice of tomato in different concentration (40, 80, 120 ul/ml) for 48h; the proliferation of PC-3 cells were measured by MTT assay, the comet assay was used to measure the DNA damage of PC-3 cells., Results: Juice of tomato could inhibit the proliferation of PC-3 cells, the growth inhibitory rate of experimental groups were significantly higher than that of control group, with very statistical significance; and it could induce the breakage of DNA single strand of PC-3 cells and resulted in comet cells with tail, Rate of DNA tail and the tail length of DNA increased with the increasing of concentration of juice of tomato, showing the obvious dose effect relationship., Conclusion: Juice of tomato could lead to DNA damage of PC-3 cells, it was related to that could inhibit the proliferation of PC-3 cells.