Breast cancer (BC) significantly contributes to cancer-related mortality in women, underscoring the criticality of early detection for optimal patient outcomes. Mammography is a key tool for identifying and diagnosing breast abnormalities; however, accurately distinguishing malignant mass lesions remains challenging. To address this issue, we propose a novel deep learning approach for BC screening utilizing mammography images. Our proposed model comprises three distinct stages: data collection from established benchmark sources, image segmentation employing an Atrous Convolution-based Attentive and Adaptive Trans-Res-UNet (ACA-ATRUNet) architecture, and BC identification via an Atrous Convolution-based Attentive and Adaptive Multi-scale DenseNet (ACA-AMDN) model. The hyperparameters within the ACA-ATRUNet and ACA-AMDN models are optimized using the Modified Mussel Length-based Eurasian Oystercatcher Optimization (MML-EOO) algorithm. The performance is evaluated using a variety of metrics, and a comparative analysis against conventional methods is presented. Our experimental results reveal that the proposed BC detection framework attains superior precision rates in early disease detection, demonstrating its potential to enhance mammography-based screening methodologies.

Ribosome biogenesis (RiBi) plays a pivotal role in carcinogenesis by regulating protein translation and stress response. Here, we find that RRP15, a nucleolar protein critical for RiBi and checkpoint control, is frequently upregulated in primary CRCs and higher RRP15 expression positively correlated with TNM stage (P < 0.0001) and poor survival of CRC patients (P = 0.0011). Functionally, silencing RRP15 induces ribosome stress, cell cycle arrest, and apoptosis, resulting in suppression of cell proliferation and metastasis. Overexpression of RRP15 promotes cell proliferation and metastasis. Mechanistically, ribosome stress induced by RRP15 deficiency facilitates translation of TOP mRNA LZTS2 (Leucine zipper tumor suppressor 2), leading to the nuclear export and degradation of β-catenin to suppress Wnt/β-catenin signaling in CRC. In conclusion, ribosome stress induced by RRP15 deficiency inhibits CRC cell proliferation and metastasis via suppressing the Wnt/β-catenin pathway, suggesting a potential new target in high-RiBi CRC patients.

(1) Background: Cell proliferation (Ki-67) has important clinical value in the treatment and prognosis of non-small cell lung cancer (NSCLC). However, current detection methods for Ki-67 are invasive and can lead to incorrect results. This study aimed to explore a deep learning classification model for the prediction of Ki-67 and the prognosis of NSCLC based on FDG-PET/CT images. (2) Methods: The FDG-PET/CT scan results of 159 patients with NSCLC confirmed via pathology were analyzed retrospectively, and the prediction models for the Ki-67 expression level based on PET images, CT images and PET/CT combined images were constructed using Densenet201. Based on a Ki-67 high expression score (HES) obtained from the prediction model, the survival rate of patients with NSCLC was analyzed using Kaplan–Meier and univariate Cox regression. (3) Results: The statistical analysis showed that Ki-67 expression was significantly correlated with clinical features of NSCLC, including age, gender, differentiation state and histopathological type. After a comparison of the three models (i.e., the PET model, the CT model, and the FDG-PET/CT combined model), the combined model was found to have the greatest advantage in Ki-67 prediction in terms of AUC (0.891), accuracy (0.822), precision (0.776) and specificity (0.902). Meanwhile, our results indicated that HES was a risk factor for prognosis and could be used for the survival prediction of NSCLC patients. (4) Conclusions: The deep-learning-based FDG-PET/CT radiomics classifier provided a novel non-invasive strategy with which to evaluate the malignancy and prognosis of NSCLC.

Objective: To investigate the uptake and vaccination willingness of the COVID-19 vaccine among Chinese residents and analyze the difference and factors that impact vaccination. Methods: The snowball sampling method was used to distribute online questionnaires. Relevant sociodemographic data along with the circumstances of COVID-19 vaccination were collected from the respondents. The χ² test, independent samples t test and binary logistic regression analysis were used to analyze the data. Results: Among 786 respondents, 84.22% had been vaccinated. Over 80% of the vaccinated population have completed all the injections because of supporting the national vaccination policies of China, while the unvaccinated population (23.91%) is mainly due to personal health status. Meanwhile, statistical analysis revealed that the main predictors of not being vaccinated were younger age (3 to 18 years old), personal health status, and lower vaccinated proportion of family members and close friends (p < 0.05). Conclusions: There was a high level of uptake of the COVID-19 vaccine in China, and people who have not been vaccinated generally had a low willingness to vaccinate in the future. Based on our results, it suggested the next work to expand the coverage of the COVID-19 vaccination should be concentrated on targeted publicity and education for people who have not been vaccinated.

Copy number variations (CNVs) play a vital role in regulating genes expression and tumorigenesis. We explored the copy number alterations in early-stage lung adenocarcinoma using high-throughput sequencing and nucleic acid flight mass spectrometry technology, and found that 8q22.1-22.2 is frequently amplified in lung adenocarcinoma tissues. COX6C localizes on the region and its expression is notably enhanced that driven by amplification in lung adenocarcinoma. Knockdown of COX6C significantly inhibits the cell proliferation, and induces S-G2/M cell cycle arrest, mitosis deficiency and apoptosis. Moreover, COX6C depletion causes a deficiency in mitochondrial fusion, and impairment of oxidative phosphorylation. Mechanistically, COX6C-induced mitochondrial deficiency stimulates ROS accumulation and activates AMPK pathway, then leading to abnormality in spindle formation and chromosome segregation, activating spindle assemble checkpoint, causing mitotic arrest, and ultimately inducing cell apoptosis. Collectively, we suggested that copy amplification-mediated COX6C upregulation might serves as a prospective biomarker for prognosis and targeting therapy in patients with lung adenocarcinoma.