Minimal residual disease monitoring in childhood Philadelphia chromosome-positive acute lymphoblastic leukemia: prognostic significance and correlation between multiparameter flow cytometry and real-time quantitative polymerase chain reaction

Not available.

ERBB3 targeting: A promising approach to overcoming cancer therapeutic resistance.

Human epidermal growth factor receptor-3 (ERBB3) is a member of the ERBB receptor tyrosine kinases (RTKs) and is expressed in many malignancies. Along with other ERBB receptors, ERBB3 is associated with regulating normal cell proliferation, apoptosis, differentiation, and survival, and has received increased research attention for its involvement in cancer therapies. ERBB3 expression or co-expression levels have been investigated as predictive factors for cancer prognosis and drug sensitivity. Additionally, the association between the elevated expression of ERBB3 and treatment failure in cancer therapy further established ERBB3-targeting therapy as a crucial therapeutic approach. This review delves into the molecular mechanisms of ERBB3-driven resistance to targeted therapeutics against ERBB2 and EGFR and other signal transduction inhibitors, endocrine therapy, chemotherapy, and radiotherapy. Using preclinical and clinical evidence, we synthesise and explicate how various aspects of aberrant ERBB3 activities-such as compensatory activation, signal crosstalk interactions, dysregulation in the endocytic pathway, mutations, ligand-independent activation, intrinsic kinase activity, and homodimerisation-can lead to resistance development and/or treatment failures. Several ERBB3-directed monoclonal antibodies, bispecific antibodies, and the emerging antibody-drug conjugate demonstrate encouraging clinical outcomes for improving therapeutic efficacy and overcoming resistance, especially when combined with other anti-cancer approaches. More research efforts are needed to identify appropriate biomarkers tailored for ERBB3-targeted therapies.

Effect of Fucoidan on Structure and Bioactivity of Chinese Steamed Bread.

Fucoidan refers to a group of sulphated polysaccharides obtained from brown seaweed, with numerous biological activities. In this study, fucoidan was fortified into Chinese steamed bread (CSB) at different concentrations (0, 1%, 3% and 5%) and the effect of fucoidan on the dough properties, structure properties and bioactivity were investigated. The results showed that fucoidan could change the viscosity of unfermented dough, and a high concentration of fucoidan could remove the free radicals produced by the SH-SS exchange reaction (GS-) in the dough, which significantly reduced the content of disulfide bond and reduced the expanded volume of fermented dough (p < 0.05). In addition, fucoidan forms a physical barrier on the surface of starch particles and hinders the reaction between protein-to-protein; therefore, fucoidan increased the hardness, gumminess and chewiness in CSB, and reduced the specific volume in CSB. Furthermore, the fucoidan-fortified CSB samples were found to have both the ability to significantly reduce the predicted glycemic index (pGI) (p < 0.05) and improve antioxidant activity (p < 0.05). Collectively, these findings could provide a theoretical basis for the applications of fucoidan as a functional component in fermented foods.

NeuroSim Simulator for Compute-in-Memory Hardware Accelerator: Validation and Benchmark.

Compute-in-memory (CIM) is an attractive solution to process the extensive workloads of multiply-and-accumulate (MAC) operations in deep neural network (DNN) hardware accelerators. A simulator with options of various mainstream and emerging memory technologies, architectures, and networks can be a great convenience for fast early-stage design space exploration of CIM hardware accelerators. DNN+NeuroSim is an integrated benchmark framework supporting flexible and hierarchical CIM array design options from a device level, to a circuit level and up to an algorithm level. In this study, we validate and calibrate the prediction of NeuroSim against a 40-nm RRAM-based CIM macro post-layout simulations. First, the parameters of a memory device and CMOS transistor are extracted from the foundry's process design kit (PDK) and employed in the NeuroSim settings; the peripheral modules and operating dataflow are also configured to be the same as the actual chip implementation. Next, the area, critical path, and energy consumption values from the SPICE simulations at the module level are compared with those from NeuroSim. Some adjustment factors are introduced to account for transistor sizing and wiring area in the layout, gate switching activity, post-layout performance drop, etc. We show that the prediction from NeuroSim is precise with chip-level error under 1% after the calibration. Finally, the system-level performance benchmark is conducted with various device technologies and compared with the results before the validation. The general conclusions stay the same after the validation, but the performance degrades slightly due to the post-layout calibration.

Role of circRNAs in viral infection and their significance for diagnosis and treatment (Review).

Circular RNAs (circRNAs) are a class of non­coding RNAs with a circular, covalent structure that lack both 5' ends and 3' poly(A) tails, which are stable and specific molecules that exist in eukaryotic cells and are highly conserved. The role of circRNAs in viral infections is being increasingly acknowledged, since circRNAs have been discovered to be involved in several viral infections (such as hepatitis B virus infection and human papilloma virus infection) through a range of circRNA/microRNA/mRNA regulatory axes. These findings have prompted investigations into the potential of circRNAs as targets for the diagnosis and treatment of viral infection­related diseases. The aim of the present review was to systematically examine and discuss the role of circRNAs in several common viral infections, as well as their potential as diagnostic markers and therapeutic targets.