Design and durability analysis of marine concrete

Marine engineering is an important way for a country to go deep blue. In the marine environment, there are many factors that affect the durability of concrete, among which the most harmful one is chloride ion erosion. In order to improve the ability to resist chloride ion permeation, this paper designs, compares and selects the appropriate water cement ratio of marine concrete, with the use of new anticorrosive technologies such as epoxy coating and silane impregnation. The design service life and the chloride ion diffusion coefficient prediction are analysed by establishing models, and this paper verifies whether the engineering design meets the service life requirement

Case report: Pulmonary artery sarcoma diagnosed through rare brain metastases

We present the case of a 33-year-old male referred across several hospitals because of suspected chronic thromboembolic pulmonary hypertension (CTEPH). Initially admitted in October 2022 for a recurrent, severe cough and diagnosed with CTEPH, he received anticoagulant therapy. However, his symptoms worsened, necessitating a transfer to another facility for thrombolysis treatment. Following an episode of syncope, an MRI scan revealed a metastatic brain tumor. Subsequently, he experienced a third transfer to our hospital, emergency surgery was performed to alleviate cerebral edema and excise a lesion in the left frontal lobe. Postoperative pathology was inconclusive, but a multidisciplinary team meeting, aided by experienced radiologists, eventually confirmed a diagnosis of pulmonary artery sarcoma (PAS) with systemic metastases. This case underscores the necessity of promptly ruling out PAS in patients presenting with significant emboli in the central pulmonary arteries and suggests early referral to specialized centers for suspected cases

Multiparametric MRI-based radiomics combined with pathomics features for prediction of the efficacy of neoadjuvant chemotherapy in breast cancer

Purpose: The aim of this study is to investigate a new method that combines radiological and pathological breast cancer information to predict discrepancies in pathological responses for individualized treatment planning. We used baseline multiparametric magnetic resonance imaging and hematoxylin and eosin-stained biopsy slides to extract quantitative feature information and predict the pathological response to neoadjuvant chemotherapy in breast cancer patients. Methods: We retrospectively collected data from breast cancer patients who received neoadjuvant chemotherapy in our hospital from August 2016 to January 2018; multiparametric magnetic resonance imaging (contrast-enhanced T1-weighted imaging and diffusion-weighted imaging) and whole slide image of hematoxylin and eosin-stained biopsy sections were collected. Quantitative imaging features were extracted from the multiparametric magnetic resonance imaging and the whole slide image were used to construct a radiopathomics signature model powered by machine learning methods. Models based on multiparametric magnetic resonance imaging or whole slide image alone were also constructed for comparison and referred to as the radiomics signature and pathomics signature models, respectively. Four modeling methods were used to establish prediction models. Model performances were evaluated using receiver operating characteristic curve analysis and the area under the curve, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. Results: The radiopathomics signature model had favourable performance for the prediction of pathological complete response in the training set (the best value: area under the curve 0.83, accuracy 0.84, and sensitivity 0.87), and in the test set (the best value: area under the curve 0.91, accuracy 0.90, and sensitivity 0.88). In the test set, the radiopathomics signature model also significantly outperformed the radiomics signature (the best value: area under the curve 0.83, accuracy 0.64, and sensitivity 0.62), pathomics signature (the best value: area under the curve 0.60, accuracy 0.74, and sensitivity 0.62) (p > 0.05). Decision curve analysis and calibration curves confirmed the excellent performance of these prediction models in discrimination, calibration, and clinical usefulness. Conclusions: The results of this study suggest that radiopathomics, the combination of both radiological information regarding the whole tumor and pathological information at the cellular level, could potentially predict discrepancies in pathological response and provide evidence for rational treatment plans

High CTCF expression mediated by FGD5-AS1/miR-19a-3p axis is associated with immunosuppression and pancreatic cancer progression

The most common reason for cancer-related death globally is predicted to be pancreatic cancer (PC), one of the deadliest cancers. The CCCTC-binding factor (CTCF) regulates the three-dimensional structure of chromatin, was reported to be highly regulated in various malignancies. However, the underlying biological functions and possible pathways via which CTCF promotes PC progression remain unclear. Herein, we examined the CTCF function in PC and discovered that CTCF expression in PC tissues was significantly raised compared to neighboring healthy tissues. Additionally, Kaplan-Meier survival analysis demonstrated a strong connection between elevated CTCF expression and poor patient prognosis. A study of the ROC curve (receiver operating characteristic) revealed an AUC value for CTCF of 0.968. Subsequent correlation analysis exhibited a strong relationship between immunosuppression and CTCF expression in PC. CTCF knockdown significantly inhibited the malignant biological process of PC in vitro and in vivo, suggesting that CTCF may be a potential PC treatment target. We also identified the FGD5 antisense RNA 1 (FGD5-AS1)/miR-19a-3p axis as a possible upstream mechanism for CTCF overexpression. In conclusion, our data suggest that ceRNA-mediated CTCF overexpression contributes to the suppression of anti-tumor immune responses in PC and could be a predictive biomarker and potential PC treatment target

Role of Equilibrium Fluctuations in Light-Induced Order

Engineering novel states of matter with light is at the forefront of materials research. An intensely studied direction is to realize broken-symmetry phases that are "hidden" under equilibrium conditions but can be unleashed by an ultrashort laser pulse. Despite a plethora of experimental discoveries, the nature of these orders and how they transiently appear remain unclear. To this end, we investigate a nonequilibrium charge density wave (CDW) in rare-earth tritellurides, which is suppressed in equilibrium but emerges after photoexcitation. Using a pump-pump-probe protocol implemented in ultrafast electron diffraction, we demonstrate that the light-induced CDW consists solely of order parameter fluctuations, which bear striking similarities to critical fluctuations in equilibrium despite differences in the length scale. By calculating the dynamics of CDW fluctuations in a nonperturbative model, we further show that the strength of the light-induced order is governed by the amplitude of equilibrium fluctuations. These findings highlight photoinduced fluctuations as an important ingredient for the emergence of transient orders out of equilibrium. Our results further suggest that materials with strong fluctuations in equilibrium are promising platforms to host hidden orders after laser excitation