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"Shen, Chao"
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High RRM2 expression has poor prognosis in specific types of breast cancer
RRM2 plays an important role in different malignant tumors, but there are few studies in breast cancer. Public databases were used to analyze the expression of RRM2 in breast cancer and its prognostic value.
A total of 2,509 breast cancer samples were downloaded from the METABRIC database. The relationship between RRM2 expression and clinical pathology was evaluated. Using the BCIP database and real-time-PCR, and western blotting, RRM2 mRNA and protein expression of RRM2 in breast cancer tissues and cell lines were evaluated. Univariate and multivariate analysis defined independent prognostic factors that affected the overall survival of patients with breast cancer. The Kaplan-Meier method was used to study the relationship between the high expression of RRM2 and overall survival and distant metastasis-free survival (DMFS) of breast cancer patients. Finally, We performed Gene Set Enrichment Analysis (GSEA) and obtained the relevant pathways associated with high expression of RRM2 potentially influencing breast cancer progression.
RRM2 expression was significantly correlated with age, tumor size, grade, menopausal status, molecular typing, ER, PR, and Her-2 of patients with breast cancer(P<0.05). Univariate and multivariate regression analysis showed that RRM2, the number of positive lymph nodes, ER, Her-2, tumor size, and tumor stage can be used as independent prognostic factors for overall survival of patients with breast cancer. Kaplan-Meier analysis showed that in patients with Luminal A and Normal like breast cancers and Stage1 and stage2 breast cancers, patients with high expression of RRM2 had worse overall survival and DMFS. The analysis of the GSEA pathway showed that RRM2 is mainly enriched in the ERBB signaling pathway and other pathways.
The high expression of RRM2 has a worse prognosis in patients with breast cancer with specific features. It can be used as a biomarker for the prognosis of breast cancer.
Journal Article
Analysis and review of trichomes in plants
Background
Trichomes play a key role in the development of plants and exist in a wide variety of species.
Results
In this paper, it was reviewed that the structure and morphology characteristics of trichomes, alongside the biological functions and classical regulatory mechanisms of trichome development in plants. The environment factors, hormones, transcription factor, non-coding RNA, etc., play important roles in regulating the initialization, branching, growth, and development of trichomes. In addition, it was further investigated the atypical regulation mechanism in a non-model plant, found that regulating the growth and development of tea (
Camellia sinensis
) trichome is mainly affected by hormones and the novel regulation factors.
Conclusions
This review further displayed the complex and differential regulatory networks in trichome initiation and development, provided a reference for basic and applied research on trichomes in plants.
Journal Article
Analysis of Complex Traits and Molecular Selection in Annual Crops
Annual crops, which include staple crops like rice [...]
Journal Article
Laser cooling of organic–inorganic lead halide perovskites
Optical irradiation with suitable energy can cool solids, a phenomenon known as optical refrigeration, first proposed in 1929 and experimentally achieved in ytterbium-doped glasses in 1995. Since then, considerable progress has been made in various rare earth element-doped materials, with a recent record of cooling to 91 K directly from ambient temperatures. For practical use and to suit future applications of optical refrigeration, the discovery of materials with facile and scalable synthesis and high cooling power density will be required. Herein we present the realization of a net cooling of 23.0 K in micrometre-thick 3D CH
3
NH
3
PbI
3
(MAPbI
3
) and 58.7 K in exfoliated 2D (C
6
H
5
C
2
H
4
NH
3
)
2
PbI
4
(PhEPbI
4
) perovskite crystals directly from room temperature. We found that the perovskite crystals exhibit strong photoluminescence upconversion and near unity external quantum efficiency, properties that are responsible for the realization of net laser cooling. Our findings indicate that solution-processed perovskite thin films may be a highly suitable candidate for constructing integrated optical cooler devices.
Perovskite crystals are shown to be highly efficient materials for optical refrigeration, supporting cooling of up to 58 K when exposed to laser light.
Journal Article
Multiple Attention Mechanism Enhanced YOLOX for Remote Sensing Object Detection
The object detection technologies of remote sensing are widely used in various fields, such as environmental monitoring, geological disaster investigation, urban planning, and military defense. However, the detection algorithms lack the robustness to detect tiny objects against complex backgrounds. In this paper, we propose a Multiple Attention Mechanism Enhanced YOLOX (MAME-YOLOX) algorithm to address the above problem. Firstly, the CBAM attention mechanism is introduced into the backbone of the YOLOX, so that the detection network can focus on the saliency information. Secondly, to identify the high-level semantic information and enhance the perception of local geometric feature information, the Swin Transformer is integrated into the YOLOX’s neck module. Finally, instead of GIOU loss, CIoU loss is adopted to measure the bounding box regression loss, which can prevent the GIoU from degenerating into IoU. The experimental results of three publicly available remote sensing datasets, namely, AIBD, HRRSD, and DIOR, show that the algorithm proposed possesses better performance, both in relation to quantitative and qualitative aspects.
Journal Article
Box singularity conditions in box diagrams of decay processes
A
bstract
Since 1959, singularities in single-loop diagrams have been a subject of extensive study, as they are believed to play a crucial role in shaping our understanding of experimental observables. In this work, we investigate the singularities arising from box diagrams in decay processes, which can be categorized into two distinct types. We present a comprehensive analysis of these box singularities, deriving explicit conditional expressions that determine their occurrence and discussing the corresponding physical scenarios.
Journal Article
Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models
Graph neural networks (GNN) has been considered as an attractive modelling method for molecular property prediction, and numerous studies have shown that GNN could yield more promising results than traditional descriptor-based methods. In this study, based on 11 public datasets covering various property endpoints, the predictive capacity and computational efficiency of the prediction models developed by eight machine learning (ML) algorithms, including four descriptor-based models (SVM, XGBoost, RF and DNN) and four graph-based models (GCN, GAT, MPNN and Attentive FP), were extensively tested and compared. The results demonstrate that on average the descriptor-based models outperform the graph-based models in terms of prediction accuracy and computational efficiency. SVM generally achieves the best predictions for the regression tasks. Both RF and XGBoost can achieve reliable predictions for the classification tasks, and some of the graph-based models, such as Attentive FP and GCN, can yield outstanding performance for a fraction of larger or multi-task datasets. In terms of computational cost, XGBoost and RF are the two most efficient algorithms and only need a few seconds to train a model even for a large dataset. The model interpretations by the SHAP method can effectively explore the established domain knowledge for the descriptor-based models. Finally, we explored use of these models for virtual screening (VS) towards HIV and demonstrated that different ML algorithms offer diverse VS profiles. All in all, we believe that the off-the-shelf descriptor-based models still can be directly employed to accurately predict various chemical endpoints with excellent computability and interpretability.
Journal Article
Investigation of Cross-Contamination and Misidentification of 278 Widely Used Tumor Cell Lines
In recent years, biological research involving human cell lines has been rapidly developing in China. However, some of the cell lines are not authenticated before use. Therefore, misidentified and/or cross-contaminated cell lines are unfortunately commonplace. In this study, we present a comprehensive investigation of cross-contamination and misidentification for a panel of 278 cell lines from 28 institutes in China by using short tandem repeat profiling method. By comparing the DNA profiles with the cell bank databases of ATCC and DSMZ, a total of 46.0% (128/278) cases with cross-contamination/misidentification were uncovered coming from 22 institutes. Notably, 73.2% (52 out of 71) of the cell lines established by the Chinese researchers were misidentified and accounted for 40.6% of total misidentification (52/128). Further, 67.3% (35/52) of the misidentified cell lines established in laboratories of China were HeLa cells or a possible hybrid of HeLa with another kind of cell line. Furthermore, the bile duct cancer cell line HCCC-9810 and degenerative lung cancer Calu-6 exhibited 88.9% match in the ATCC database (9-loci), indicating that they were from the same origin. However, when we used 21-loci to compare these two cell lines with the same algorithm, the percent match was only 48.2%, indicating that these two cell lines were different. The SNP profiles of HCCC-9810 and Calu-6 also revealed that they were different cell lines. 150 cell lines with unique profiles demonstrated a wide range of in vitro phenotypes. This panel of 150 genomically validated cancer cell lines represents a valuable resource for the cancer research community and will advance our understanding of the disease by providing a standard reference for cell lines that can be used for biological as well as preclinical studies.
Journal Article
A metasurface-based full-color circular auto-focusing Airy beam transmitter for stable high-speed underwater wireless optical communications
Due to its unique intensity distribution, self-acceleration, and beam self-healing properties, Airy beam holds great potential for optical wireless communications in challenging channels, such as underwater environments. As a vital part of 6G wireless network, the Internet of Underwater Things requires high-stability, low-latency, and high-capacity underwater wireless optical communication (UWOC). Currently, the primary challenge of UWOC lies in the prevalent time-varying and complex channel characteristics. Conventional blue Gaussian beam-based systems face difficulties in underwater randomly perturbed links. In this work, we report a full-color circular auto-focusing Airy beams metasurface transmitter for reliable, large-capacity and long-distance UWOC links. The metasurface is designed to exhibits high polarization conversion efficiency over a wide band (440-640 nm), enabling an increased data transmission rate of 91% and reliable 4 K video transmission in wavelength division multiplexing (WDM) based UWOC data link. The successful application of this metasurface in challenging UWOC links establishes a foundation for underwater interconnection scenarios in 6G communication.
Authors present an adaptive underwater optical communication (UWOC) technology based on multi-wavelength lasers and a full-color metasurface for converting visible-band Gaussian to circular autofocusing Airy beams. The potential of Airy beams to mitigate optical power degradation is demonstrated, enabling stable data rate transmission via 4 K video transmission for these systems.
Journal Article