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Chimeric antigen receptor T (CAR-T) cell therapy is regarded as an effective solution for relapsed or refractory tumors, particularly for hematological malignancies. Although the initially approved anti-CD19 CAR-T therapy has produced impressive outcomes, setbacks such as high relapse rates and resistance were experienced, driving the need to discover engineered CAR-T cells that are more effective for therapeutic use. Innovations in the structure and manufacturing of CAR-T cells have resulted in significant improvements in efficacy and persistence, particularly with the development of fourth-generation CAR-T cells. Paired with an immune modifier, the use of fourth-generation and next-generation CAR-T cells will not be limited because of cytotoxic effects and will be an efficient tool for overcoming the tumor microenvironment. In this review, we summarize the recent transformations in the ectodomain, transmembrane domain, and endodomain of the CAR structure, which, together with innovative manufacturing technology and improved cell sources, improve the prospects for the future development of CAR-T cell therapy.

Chimeric antigen receptor redirected T cells (CAR-T cells) have achieved inspiring outcomes in patients with B cell malignancies, and are now being investigated in other hematologic malignancies and solid tumors. CAR-T cells are generated by the T cells from patients’ or donors’ blood. After the T cells are expanded and genetically modified, they are reinfused into the patients. However, many challenges still need to be resolved in order for this technology to gain widespread adoption. In this review, we first discuss the structure and evolution of chimeric antigen receptors. We then report on the tools used for production of CAR-T cells. Finally, we address the challenges posed by CAR-T cells.

In a randomized trial of fractional flow reserve versus IVUS to guide PCI, the use of FFR resulted in fewer coronary interventions and was noninferior to IVUS with respect to clinical outcomes at 2 years.

The fluid‐flow properties of fractures have received increasing attention regarding the role of geofluids in the genesis of slow and fast earthquakes and recent advances in geoengineering developments. Geophysical observations are promising tools to remotely estimate crustal permeability changes; however, quantitative interpretations are limited by the rock‐physical models' paucity for fractures. This study investigated changes in permeability, resistivity, and their respective relationships at elevated stress by performing numerical simulations of different fracture models with varying fracture size, roughness, and shear displacement. Numerical results and microscopic flow analysis demonstrate that permeability–resistivity relationships are controlled by percolation and are less dependent on fracture geometric characteristics. Our finding suggests that the permeability evolution of fractures can be formulated with resistivity changes independent of both fracture size and microstructure, the trends of which can be predicted using Archie's exponent. The extension to the electro‐mechanical relationship further derives the potential applications of estimating stress changes. Plain Language Summary Monitoring the flow of fluids through underground fractures is important for developing earth resources and understanding the generation of both slow and fast earthquakes. This can be realized by observing physical properties underground such as electrical resistivity; however, the relationships between electrical and hydraulic properties are poorly understood because we have limited data on rock fractures. Thus, in this study, we explored changes in the hydraulic and electrical properties of synthetic rock fractures by subjecting them to increasing normal stress and shear displacement while varying the properties of the fracture surface topographies and length scales referring to natural data. We formulated the relationship between electrical resistivity and permeability invariant of fracture size, roughness, shear displacement, and normal stress based on both the theoretical model and empirical Archie's equation. We found that the rigorous relationship is controlled by the local connection of the fluid‐flow paths based on the microscopic flow analysis. The proposed formula can estimate the permeability evolution of fractures using resistivity data and is a better approach compared to porosity estimation because resistivity–porosity relationship can change depending on the tortuosity or connectivity. The extension to the electro‐mechanical relationship also derives the potential applications of estimating changes in pore pressure. Key Points Numerical results clarify the dependencies of fracture size, roughness, shear displacement, and stress on permeability and resistivity Flow path percolation can be correlated with tortuosity, which controls the rigorous resistivity–porosity and –permeability relationships Archie's exponent is constant for a percolated single fracture and can be used for monitoring permeability and pore pressure change

Long-read RNA sequencing (RNA-seq) technologies can sequence full-length transcripts, facilitating the exploration of isoform-specific gene expression over short-read RNA-seq. We present LIQA to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read direct mRNA sequencing or cDNA sequencing data. LIQA incorporates base pair quality score and isoform-specific read length information in a survival model to assign different weights across reads, and uses an expectation-maximization algorithm for parameter estimation. We apply LIQA to long-read RNA-seq data from the Universal Human Reference, acute myeloid leukemia, and esophageal squamous epithelial cells and demonstrate its high accuracy in profiling alternative splicing events.

Using the techniques of neural networks (NN), we study the three-dimensional (3D) five-state ferromagnetic Potts model on the cubic lattice as well as the two-dimensional (2D) three-state antiferromagnetic Potts model on the square lattice. Unlike the conventional approach, here we follow the idea employed by Li et al (2018 Ann. Phys., NY 391 312-331). Specifically, instead of numerically generating numerous objects for the training, the whole or part of the theoretical ground state configurations of the studied models are considered as the training sets. Remarkably, our investigation of these two models provides convincing evidence for the effectiveness of the method of preparing training sets used in this study. In particular, the results of the 3D model obtained here imply that the NN approach is as efficient as the traditional method since the signal of a first order phase transition, namely tunneling between two channels, determined by the NN method is as strong as that calculated with the Monte Carlo technique. Furthermore, the outcomes associated with the considered 2D system indicate even little partial information of the ground states can lead to conclusive results regarding the studied phase transition. The achievements reached in our investigation demonstrate that the performance of NN, using certain amount of the theoretical ground state configurations as the training sets, is impressive.

Background Long-read RNA-Seq techniques can generate reads that encompass a large proportion or the entire mRNA/cDNA molecules, so they are expected to address inherited limitations of short-read RNA-Seq techniques that typically generate < 150 bp reads. However, there is a general lack of software tools for gene fusion detection from long-read RNA-seq data, which takes into account the high basecalling error rates and the presence of alignment errors. Results In this study, we developed a fast computational tool, LongGF, to efficiently detect candidate gene fusions from long-read RNA-seq data, including cDNA sequencing data and direct mRNA sequencing data. We evaluated LongGF on tens of simulated long-read RNA-seq datasets, and demonstrated its superior performance in gene fusion detection. We also tested LongGF on a Nanopore direct mRNA sequencing dataset and a PacBio sequencing dataset generated on a mixture of 10 cancer cell lines, and found that LongGF achieved better performance to detect known gene fusions over existing computational tools. Furthermore, we tested LongGF on a Nanopore cDNA sequencing dataset on acute myeloid leukemia, and pinpointed the exact location of a translocation (previously known in cytogenetic resolution) in base resolution, which was further validated by Sanger sequencing. Conclusions In summary, LongGF will greatly facilitate the discovery of candidate gene fusion events from long-read RNA-Seq data, especially in cancer samples. LongGF is implemented in C++ and is available at https://github.com/WGLab/LongGF .

The high-temperature stability and mechanical properties of refractory molybdenum alloys are highly desirable for a wide range of critical applications. However, a long-standing problem for these alloys is that they suffer from low ductility and limited formability. Here we report a nanostructuring strategy that achieves Mo alloys with yield strength over 800 MPa and tensile elongation as large as ~ 40% at room temperature. The processing route involves a molecular-level liquid–liquid mixing/doping technique that leads to an optimal microstructure of submicrometre grains with nanometric oxide particles uniformly distributed in the grain interior. Our approach can be readily adapted to large-scale industrial production of ductile Mo alloys that can be extensively processed and shaped at low temperatures. The architecture engineered into such multicomponent alloys offers a general pathway for manufacturing dispersion-strengthened materials with both high strength and ductility. Although molybdenum alloys — often used in turbines and fusion reactors — can be easily hardened, they suffer from low ductility and toughness. Now, a nanostructuring processing route that leads to a microstructure consisting of submicrometre grains with nanometric oxide particles uniformly distributed in the grain interior achieves high-strength molybdenum alloys with large tensile elongation at room temperature.

Epithelial–mesenchymal transition (EMT) has been recognized as a key element of cell migration and invasion in lung cancer; however, the underlying mechanisms are not fully elucidated. Recently, emerging evidence suggest that miRNAs have crucial roles in control of EMT and EMT-associated traits such as migration, invasion and chemoresistance. Here, we found that miR-218 expression levels were significantly downregulated in lung cancer tissues compared with adjacent non-cancerous tissues, and the levels of miR-218 were significantly associated with histological grades and lymph node metastasis. Overexpression of miR-218 inhibited cell migration and invasion as well as the EMT process. Of particular importance, miR-218 was involved in the metastatic process of lung cancer cells in vivo by suppressing local invasion and distant colonization. We identified Slug and ZEB2 as direct functional targets of miR-218. Inverse correlations were observed between miR-218 levels and Slug/ZEB2 levels in cancer tissue samples. In addition, overexpression of miR-218 in H1299 increased chemosensitivity of cells to cisplatin treatment through suppression of Slug and ZEB2. These findings highlight an important role of miR-218 in the regulation of EMT-related traits and metastasis of lung cancer in part by modulation of Slug/ZEB2 signaling, and provide a potential therapeutic strategy by targeting miR-218 in NSCLC.

Background and purpose Nitrous oxide (N2O) induced neurological symptoms are increasingly encountered. Our aim is to provide clinical and diagnostic characteristics with a focus on electrodiagnostic studies. Methods Patients with neurological sequelae due to N2O presenting in our hospital between November 2018 and December 2021 reporting clinical and diagnostic data were retrospectively reviewed. Results Seventy patients (median 22 years) were included. Median N2O usage was 4 kg/week during 12 months. Patients’ history revealed a higher rate of sensory symptoms compared to motor (97% vs. 57%) and 77% walking difficulties. Clinical diagnosis was polyneuropathy (PNP) in 44%, subacute combined degeneration (SCD) of the spine in 19%, both in 37%. Median vitamin B12 level was low (159 pmol/L), normal in 16%. The median methylmalonic acid was increased (2.66 μmol/L). Electrodiagnostic abnormalities were observed in 91%, with 72% fulfilling axonal PNP criteria, 20% showing mild to intermediate slowing. One patient fulfilled demyelinating PNP criteria not related to N2O abuse (Charcot−Marie−Tooth type 1a). More prominent motor nerve conduction abnormalities were found; lower limbs were more affected. In 64% with normal conduction, myography showed signs of axonal loss. Magnetic resonance imaging showed cervical myelopathy in 58% involving generally five to six segments. Conclusions Nitrous oxide (N2O) leads to neurological symptoms by causing PNP and/or SCD primarily involving the legs. Distinguishing PNP and SCD clinically was shown to be insufficient. Electrodiagnostic studies showed axonal PNP. Demyelinating PNP due to N2O abuse was not present in our cohort. Therefore, further diagnostic work‐up is warranted if demyelinating features are present.