Search

The novel martensitic stainless steel 13CrU was developed based on 13CrS by adding trace alloying elements, such as Mo, Ni, and Ta. This study compares the mechanical and corrosion resistance properties of the two martensitic stainless steels to assess the effect of these alloying elements on 13CrU's performance. Experimental results show that increasing Mo by 0.67 wt% and Ni by 1.13 wt% improves the yield strength of 13CrU by 11.6% compared to 13CrS. The addition of Ta enhances the corrosion resistance of 13CrU beyond that of 13CrS. Overall, the addition of trace alloying elements significantly improves the mechanical properties of 13CrU and enhances its resistance to CO₂ corrosion. [ABSTRACT FROM AUTHOR]

Honey, a widely consumed food, is susceptible to contamination by various toxic substances during production. Tropane alkaloids, with their potent neurotoxicity, are frequently found in honey. Hence, there is an acute need for rapid and effective detection methods to monitor these alkaloids. Lateral flow immunoassay (LFIA), known for its simple operation, low cost, and reliable results, holds great promise. In this study, we developed an efficient and user-friendly analytical method for the simultaneous detection of six tropane alkaloids (atropine, L-hyoscyamine, scopolamine, anisodamine, homatropine, and apoatropine) in honey based on an AuNPs lateral flow immunoassay (AuNPs-LFIA) with broad-spectrum antibodies. Under optimal conditions, the calculated detection limits were 0.22, 0.29, 0.51, 6.34, 0.30, and 0.94 ng/mL, respectively. By diluting the honey sample five times, the contaminants can be readily detected using LFIA. Semi-quantitative and quantitative analyses can be completed within 17 min. This innovative method fills the void in LFIA for detecting tropane alkaloids and serves as a valuable reference for LFIA detection of honey samples, providing a crucial strategy for the accurate detection of these important compounds. [ABSTRACT FROM AUTHOR]

A novel sandwich-type photoelectrochemical (PEC) sensor for SCCA detection, based on a Ag2S-sensitized BiOI matrix and a AucorePdshell (AucPds) nanoflower label for signal amplification, was constructed for the ultrasensitive detection of the squamous cell carcinoma antigen (SCCA). By an in situ growth method, Ag2S was modified on the electrode coated with BiOI to obtain the BiOI/Ag2S composite. The BiOI/Ag2S matrix possesses an excellent photocurrent signal that is 90 times that of pure BiOI. The core–shell nanoflower-structured AucPds was utilized as a label to anchor secondary antibodies (AucPds@Ab2) to construct the ultrasensitive PEC sensor. The AucPds nanoflower can compete with the BiOI/Ag2S matrix for the absorption of visible-light to inhibit the electron transfer and then weaken the photocurrent signal of the BiOI/Ag2S matrix. After modification with the AucPds@Ab2 conjugate, the PEC signal was further reduced due to the efficient energy transfer process between the BiOI/Ag2S matrix and AucPds. Based on the above two influencing factors, the signal amplification strategy was fulfilled. Moreover, on the basis of specific recognition between antigen and antibody, an ultrasensitive PEC sensor for SCCA detection was successfully fabricated. On increasing the logarithm of the SCCA concentration in the range from 0.01 pg mL−1 to 100 ng mL−1, the photocurrent signals were linearly reduced and the detection limit was 1.6 fg mL−1. The fabricated sandwich-type PEC sensor has excellent sensitivity and distinguished stability, which are indicative of promising applications in clinical diagnoses, sensors and PEC analysis. [ABSTRACT FROM AUTHOR]

The existing three-dimensional (3D) x-ray reconstruction methods for lung cancer tissue reconstruct the investigated objects based on a series of two-dimensional (2D) image sections and a chosen 3D reconstruction algorithm. However, because these procedures apply the same segmentation method for all 2D image sections, they may not achieve the optimal segmentation for each section. As a result, the reconstructed 3D images have limited spatial resolution. Furthermore, the existing 3D reconstruction method is time-consuming and results in a limited time resolution. This research presents an innovation of 3D reconstruction by reformulating two main components of the method. First, a validity index for fuzzy clustering is used to obtain the optimal segmentations of any 2D x-ray image. The process is realized by automatically determining the optimal number of clusters for the image. Second, unlike the existing 3D reconstruction methods, a fast-FCM algorithm is used to speed up the 2D image segmenting process, thereby raising the time resolution of the 3D reconstruction process. With the aid of commonly used VTK software, the proposed method has been used to visualize four classes of typical lung cancer tissues: adenocarcinoma, large cell carcinoma, small cell carcinoma, and squamous cell carcinoma. Experimental results validate the effectiveness and efficiency of the proposed algorithm. Thus, the method contributes a useful tool for x-ray-based 3D image reconstruction. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC), a type of liver cancer, ranks as the sixth most prevalent cancer globally and represents the third leading cause of cancer-related deaths. Approximately half of HCC patients miss the opportunity for curative treatment and are then limited to undergoing systemic therapies. Currently, systemic therapy has entered the era of immunotherapy, particularly with the advent of immune-checkpoint inhibitors (ICIs), which have significantly enhanced outcomes for patients with advanced HCC. Neoadjuvant treatment for HCC has become a possibility-findings from the IMbrave 050 trial indicated that ICIs offer the benefit of recurrence-free survival for high-risk HCC patients post-resection or local ablation. However, only a small fraction of individuals benefit from systemic therapy. Consequently, there is an urgent need to identify predictive biomarkers for treatment response and outcome assessment. This study reviewed the historical progression of systemic therapy for HCC, highlighting notable therapeutic advancements. This study examined the development of systemic therapies involving conventional drugs and clinical trials utilized in HCC treatment, as well as potential predictive biomarkers for advanced and/or locally advanced HCC. Various studies have revealed potential biomarkers in the context of HCC treatment. These include the association of dendritic cells (DCs) with a favorable response to neoadjuvant therapy, the presence of enriched T effector cells and tertiary lymphoid structures, the identification of CD138+ plasma cells, and distinct spatial arrangements of B cells in close proximity to T cells among responders with locally advanced HCC receiving neoadjuvant cabozantinib and nivolumab treatment. Furthermore, pathological response has been associated with intratumoral cellular triads consisting of progenitor CD8+ T cells and CXCL13+ CD4+ T helper cells surrounding mature DCs in patients receiving neoadjuvant cemiplimab for resectable HCC. Despite no widely recognized predictive biomarkers for HCC individualized treatment, we believe neoadjuvant trials hold the most promise in identifying and validating them. This is because they can collect multiple samples from resectable HCC patients across stages, especially with multi-omics, bridging preclinical and clinical gaps., Competing Interests: The 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 Wang, Wei, Sun, Qiu, Yu, Sun, Zhi, Li, Fan, Lv and Wang.)

The endoplasmic reticulum (ER) is a crucial organelle that orchestrates key cellular functions like protein folding and lipid biosynthesis. However, it is highly sensitive to disturbances that lead to ER stress. In response, the unfolded protein response (UPR) activates to restore ER homeostasis, primarily through three sensors: IRE1, ATF6, and PERK. ERAD and autophagy are crucial in mitigating ER stress, yet their dysregulation can lead to the accumulation of misfolded proteins. Cisplatin, a commonly used chemotherapy drug, induces ER stress in tumor cells, activating complex signaling pathways. Resistance to cisplatin stems from reduced drug accumulation, activation of DNA repair, and anti-apoptotic mechanisms. Notably, cisplatin-induced ER stress can dualistically affect tumor cells, promoting either survival or apoptosis, depending on the context. ERAD is crucial for degrading misfolded proteins, whereas autophagy can protect cells from apoptosis or enhance ER stress-induced apoptosis. The complex interaction between ER stress, cisplatin resistance, ERAD, and autophagy opens new avenues for cancer treatment. Understanding these processes could lead to innovative strategies that overcome chemoresistance, potentially improving outcomes of cisplatin-based cancer treatments. This comprehensive review provides a multifaceted perspective on the complex mechanisms of ER stress, cisplatin resistance, and their implications in cancer therapy., Competing Interests: The 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 Mu, Zhi, Zhou, Wang, Chai, Fan and Lv.)