A Novel Mis-Seg-Focus Loss Function Based on a Two-Stage nnU-Net Framework for Accurate Brain Tissue Segmentation.

Brain tissue segmentation plays a critical role in the diagnosis, treatment, and study of brain diseases. Accurately identifying these boundaries is essential for improving segmentation accuracy. However, distinguishing boundaries between different brain tissues can be challenging, as they often overlap. Existing deep learning methods primarily calculate the overall segmentation results without adequately addressing local regions, leading to error propagation and mis-segmentation along boundaries. In this study, we propose a novel mis-segmentation-focused loss function based on a two-stage nnU-Net framework. Our approach aims to enhance the model's ability to handle ambiguous boundaries and overlapping anatomical structures, thereby achieving more accurate brain tissue segmentation results. Specifically, the first stage targets the identification of mis-segmentation regions using a global loss function, while the second stage involves defining a mis-segmentation loss function to adaptively adjust the model, thus improving its capability to handle ambiguous boundaries and overlapping anatomical structures. Experimental evaluations on two datasets demonstrate that our proposed method outperforms existing approaches both quantitatively and qualitatively.

Comparative proteomics analyses of whey proteins from breastmilk collected from two ethnic groups in northeast China.

The current study aims to investigate differences in whey protein of breastmilk of volunteered mother collected from two ethnic groups (Korean and Han) in China using data-independent acquisition (DIA) based proteomics technique. The total detected 624 proteins were principally allocated to cellular process of biological process (BP), cell and cell part of cell component (CC) and binding of molecular function (MF) according to Gene Ontology (GO) annotation; and carbohydrate metabolism of Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Among the 54 differently expressed proteins, 8 were related with immunity. Enrichment data showed that intracellular of GO functions and viral myocarditis of KEGG pathways were most significantly enriched (p < 0.05). Protein-protein interaction (PPI) network suggested that 40S ribosomal protein S27a and 60S ribosomal protein L10a which interacted most with other proteins ranked the top two hub proteins by MCC (Maximal Clique Centrality) method. This study may have guiding role for development of infant formula powder for specific infants of Han or Korean groups according to responding breastmilk composition.

Changes in plant inputs alter soil carbon and microbial communities in forest ecosystems.

Global changes can alter plant inputs from both above- and belowground, which, thus, may differently affect soil carbon and microbial communities. However, the general patterns of how plant input changes affect them in forests remain unclear. By conducting a meta-analysis of 3193 observations from 166 experiments worldwide, we found that alterations in aboveground litter and/or root inputs had profound effects on soil carbon and microbial communities in forest ecosystems. Litter addition stimulated soil organic carbon (SOC) pools and microbial biomass, whereas removal of litter, roots or both (no inputs) decreased them. The increased SOC under litter addition suggested that aboveground litter inputs benefit SOC sequestration despite accelerated decomposition. Unlike root removal, litter alterations and no inputs altered particulate organic carbon, whereas all detrital treatments did not significantly change mineral-associated organic carbon. In addition, detrital treatments contrastingly altered soil microbial community, with litter addition or removal shifting it toward fungi, whereas root removal shifting it toward bacteria. Furthermore, the responses of soil carbon and microbial biomass to litter alterations positively correlated with litter input rate and total litter input, suggesting that litter input quantity is a critical controller of belowground processes. Taken together, these findings provide critical insights into understanding how altered plant productivity and allocation affects soil carbon cycling, microbial communities and functioning of forest ecosystems under global changes. Future studies can take full advantage of the existing plant detritus experiments and should focus on the relative roles of litter and roots in forming SOC and its fractions.

Design of a Wearable 12-Lead Noncontact Electrocardiogram Monitoring System.

A standard 12-lead electrocardiogram (ECG) is an important tool in the diagnosis of heart diseases. Here, Ag/AgCl electrodes with conductive gels are usually used in a 12-lead ECG system to access biopotentials. However, using Ag/AgCl electrodes with conductive gels might be inconvenient in a prehospital setting. In previous studies, several dry electrodes have been developed to improve this issue. However, these dry electrodes have contact with the skin directly, and they might be still unsuitable for patients with wounds. In this study, a wearable 12-lead electrocardiogram monitoring system was proposed to improve the above issue. Here, novel noncontact electrodes were also designed to access biopotentials without contact with the skin directly. Moreover, by using the mechanical design, this system allows the user to easily wear and take off the device and to adjust the locations of the noncontact electrodes. The experimental results showed that the proposed system could exactly provide a good ECG signal quality even while walking and could detect the ECG features of the patients with myocardial ischemia, installation pacemaker, and ventricular premature contraction.