BertTCR: a Bert-based deep learning framework for predicting cancer-related immune status based on T cell receptor repertoire.

The T cell receptor (TCR) repertoire is pivotal to the human immune system, and understanding its nuances can significantly enhance our ability to forecast cancer-related immune responses. However, existing methods often overlook the intra- and inter-sequence interactions of T cell receptors (TCRs), limiting the development of sequence-based cancer-related immune status predictions. To address this challenge, we propose BertTCR, an innovative deep learning framework designed to predict cancer-related immune status using TCRs. BertTCR combines a pre-trained protein large language model with deep learning architectures, enabling it to extract deeper contextual information from TCRs. Compared to three state-of-the-art sequence-based methods, BertTCR improves the AUC on an external validation set for thyroid cancer detection by 21 percentage points. Additionally, this model was trained on over 2000 publicly available TCR libraries covering 17 types of cancer and healthy samples, and it has been validated on multiple public external datasets for its ability to distinguish cancer patients from healthy individuals. Furthermore, BertTCR can accurately classify various cancer types and healthy individuals. Overall, BertTCR is the advancing method for cancer-related immune status forecasting based on TCRs, offering promising potential for a wide range of immune status prediction tasks.

An efficient ultrasonic wavenumber-domain plane wave imaging method towards the inspection of curved structures.

Ultrasonic phased array testing is commonly employed for inspecting curved structures. Conventional plane wave imaging techniques, based on delay-and-sum in the time-domain, offer high image quality and inspection accuracy but suffer from low frame rates due to their high computational complexity. In this work, an efficient wavenumber-domain imaging method that combines non-stationary wavefield extrapolation and f-k migration is proposed for curved structure inspection. Special emission focal laws are designed to generate a sequence of steered plane waves through the curved interface. The raw data is then extrapolated to the top boundary of the region of interest, followed by f-k migration to reconstruct images with high time efficiency. Simulation and experimental evaluations demonstrate a time reduction by a factor of up to 32.24 compared to conventional time-domain plane wave image reconstruction with equivalent image quality, highlighting its potential for monitoring flaws in real-time.

Nonlinear optical signatures of topological Dirac fermion.

Dirac fermion in topological materials exhibits intriguing nonlinear optical responses. However, their direct correlation with the linearly dispersed band remains elusive experimentally. Here, we take topological semimetal ZrSiS as a paradigm, unveiling three unique nonlinear optical signatures of Dirac fermion. These signatures include strong quadrupolar response, quantum interference effect, and exponential divergent four-wave mixing (FWM), all of which are described by the prominent third-order nonlinear optical susceptibility. Resonantly enhanced by linear bands, quadrupolar second harmonic generation in centrosymmetric bulk overwhelms the electric-dipole contribution at the surface with inherent inversion symmetry breaking. Furthermore, owing to the interference between multiple resonant transition pathways within linear bands, difference-frequency FWM is several orders of magnitude stronger than sum-frequency FWM and third harmonic generation. The difference-frequency FWM further displays an inverse-square divergence toward degenerate excitation, whose scaling law perfectly matches with the long-sought behavior of Dirac fermion. These signatures lay the solid foundation toward the practical applications of topological materials in nonlinear optoelectronics and photonics.

Creep level qualitative evaluating of crushed rock based on uncertainty measurement theory and hierarchical analysis.

A large number of tectonically mixed rock belts and complex tectonic zones are distributed in the southwestern part of China. In these areas, high geostress and tectonic stresses have caused some underground rock layers to be crushed and broken, eventually forming crushed rock zones. Which may undergo creep deformation under long-term loads. The manuscript is based on a typical crushed rock in the southwestern China. Firstly, the factors affecting creep deformation were analysed, and the response law of each influencing factor to rock creep is demonstrated. Then, the theory of uncorroborated measures and hierarchical analysis were used to systematically correlate the factors influencing creep. Thereby, a creep level qualitative evaluating model of crushed rock is established. Finally, this model was used to qualitatively evaluate the creep level of the crushed rock in the study area. It is concluded that the creep level qualitative evaluating of this crushed rock is rated as Class II, which is characterised by a low creep level and small creep deformations (0-10 mm). The research results can provide a reference for the creep analysis of crushed rock and provide a basis for the safe construction of engineering slopes.

PrCRS: a prediction model of severe CRS in CAR-T therapy based on transfer learning.

BACKGROUND: CAR-T cell therapy represents a novel approach for the treatment of hematologic malignancies and solid tumors. However, its implementation is accompanied by the emergence of potentially life-threatening adverse events known as cytokine release syndrome (CRS). Given the escalating number of patients undergoing CAR-T therapy, there is an urgent need to develop predictive models for severe CRS occurrence to prevent it in advance. Currently, all existing models are based on decision trees whose accuracy is far from meeting our expectations, and there is a lack of deep learning models to predict the occurrence of severe CRS more accurately. RESULTS: We propose PrCRS, a deep learning prediction model based on U-net and Transformer. Given the limited data available for CAR-T patients, we employ transfer learning using data from COVID-19 patients. The comprehensive evaluation demonstrates the superiority of the PrCRS model over other state-of-the-art methods for predicting CRS occurrence. We propose six models to forecast the probability of severe CRS for patients with one, two, and three days in advance. Additionally, we present a strategy to convert the model's output into actual probabilities of severe CRS and provide corresponding predictions. CONCLUSIONS: Based on our findings, PrCRS effectively predicts both the likelihood and timing of severe CRS in patients, thereby facilitating expedited and precise patient assessment, thus making a significant contribution to medical research. There is little research on applying deep learning algorithms to predict CRS, and our study fills this gap. This makes our research more novel and significant. Our code is publicly available at https://github.com/wzy38828201/PrCRS . The website of our prediction platform is: http://prediction.unicar-therapy.com/index-en.html .

Contrast-enhanced phase-resolved second harmonic generation microscopy.

The characterization of inverted structures (crystallographic, ferroelectric, or magnetic domains) is crucial in the development and application of novel multi-state devices. However, determining these inverted structures needs a sensitive probe capable of revealing their phase correlation. Here a contrast-enhanced phase-resolved second harmonic generation (SHG) microscopy is presented, which utilizes a phase-tunable Soleil-Babinet compensator and the interference between the SHG fields from the inverted structures and a homogeneous reference. By this means, such inverted structures are correlated through the π-phase difference of SHG, and the phase difference is ultimately converted into the intensity contrast. As a demonstration, we have applied this microscopy in two scenarios to determine the inverted crystallographic domains in two-dimensional van der Waals material MoS2. Our method is particularly suitable for applying in vacuum and cryogenic environments while providing optical diffraction-limited resolution and arbitrarily adjustable contrast. Without loss of generality, this contrast-enhanced phase-resolved SHG microscopy can also be used to resolve other non-centrosymmetric inverted structures, e.g. ferroelectric, magnetic, or multiferroic phases.

Meta-DHGNN: method for CRS-related cytokines analysis in CAR-T therapy based on meta-learning directed heterogeneous graph neural network.

Chimeric antigen receptor T-cell (CAR-T) immunotherapy, a novel approach for treating blood cancer, is associated with the production of cytokine release syndrome (CRS), which poses significant safety concerns for patients. Currently, there is limited knowledge regarding CRS-related cytokines and the intricate relationship between cytokines and cells. Therefore, it is imperative to explore a reliable and efficient computational method to identify cytokines associated with CRS. In this study, we propose Meta-DHGNN, a directed and heterogeneous graph neural network analysis method based on meta-learning. The proposed method integrates both directed and heterogeneous algorithms, while the meta-learning module effectively addresses the issue of limited data availability. This approach enables comprehensive analysis of the cytokine network and accurate prediction of CRS-related cytokines. Firstly, to tackle the challenge posed by small datasets, a pre-training phase is conducted using the meta-learning module. Consequently, the directed algorithm constructs an adjacency matrix that accurately captures potential relationships in a more realistic manner. Ultimately, the heterogeneous algorithm employs meta-photographs and multi-head attention mechanisms to enhance the realism and accuracy of predicting cytokine information associated with positive labels. Our experimental verification on the dataset demonstrates that Meta-DHGNN achieves favorable outcomes. Furthermore, based on the predicted results, we have explored the multifaceted formation mechanism of CRS in CAR-T therapy from various perspectives and identified several cytokines, such as IFNG (IFN-γ), IFNA1, IFNB1, IFNA13, IFNA2, IFNAR1, IFNAR2, IFNGR1 and IFNGR2 that have been relatively overlooked in previous studies but potentially play pivotal roles. The significance of Meta-DHGNN lies in its ability to analyze directed and heterogeneous networks in biology effectively while also facilitating CRS risk prediction in CAR-T therapy.

Twist Phase Matching in Two-Dimensional Materials.

Optical phase matching involves establishing a proper phase relationship between the fundamental excitation and generated waves to enable efficient optical parametric processes. It is typically achieved through birefringence or periodic polarization. Here, we report that the interlayer twist angle in two-dimensional (2D) materials creates a nonlinear geometric phase that can compensate for the phase mismatch, and the vertical assembly of the 2D layers with a proper twist sequence generates a nontrivial "twist-phase-matching" (twist-PM) regime. The twist-PM model provides superior flexibility in the design of optical crystals, which can be applied for twisted layers with either periodic or random thickness distributions. The designed crystal from the twisted rhombohedral boron nitride films within a thickness of only 3.2 µm is capable of producing a second-harmonic generation with conversion efficiency of ∼8% and facile polarization controllability that is absent in conventional crystals. Our methodology establishes a platform for the rational design and atomic manufacturing of nonlinear optical crystals based on abundant 2D materials.

Mechanisms of Actinidia chinensis Planch in treating colon cancer based on the integration of network pharmacology, molecular docking, and experimental verification.

BACKGROUND: As an anticancer Chinese herbal medicine, the effective components and mechanism of Actinidia chinensis Planch (ACP, Tengligen) in the treatment of colon cancer are still unclear. In the present study, the integration of network pharmacology, molecular docking, and cell experiments was employed to study the effective mechanism of ACP against colon cancer. METHODS: The Venn diagram and STRING database were used to construct the protein-protein interaction network (PPI) of ACP-colon cancer, and further topological analysis was used to obtain the key target genes of ACP in colon cancer. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to visualize the related functions and pathways. Molecular docking between key targets and compounds was determined using software such as AutoDockTools. Finally, the effect of ACP on CT26 cells was observed in vitro. RESULTS: The study identified 40 ACP-colon key targets, including CASP3, CDK2, GSK3B, and PIK3R1. GO and KEGG enrichment analyses found that these genes were involved in 211 biological processes and 92 pathways, among which pathways in cancer, PI3K-Akt, p53, and cell cycle might be the main pathways of ACP against colon cancer. Molecular docking verified that the key components of ACP could stably bind to the corresponding targets. The experimental results showed that ACP could inhibit proliferation, induce apoptosis, and downregulate the phosphorylation of PIK3R1, Akt, and GSK3B in CT26 cells. CONCLUSION: ACP is an anti-colon cancer herb with multiple components, and involvement of multiple target genes and signaling pathways. ACP can significantly inhibit proliferation and induce apoptosis of colon cancer cells, which may be closely related to the regulation of PI3K/AKT/GSK3B signal transduction.

Extrinsic Nonlinear Kerr Rotation in Topological Materials under a Magnetic Field.

Topological properties in quantum materials are often governed by symmetry and tuned by crystal structure and external fields, and hence, symmetry-sensitive nonlinear optical measurements in a magnetic field are a valuable probe. Here, we report nonlinear magneto-optical second harmonic generation (SHG) studies of nonmagnetic topological materials including bilayer WTe2, monolayer WSe2, and bulk TaAs. The polarization-resolved patterns of optical SHG under a magnetic field show nonlinear Kerr rotation in these time-reversal symmetric materials. For materials with 3-fold rotational symmetric lattice structure, the SHG polarization pattern rotates just slightly in a magnetic field, whereas in those with mirror or 2-fold rotational symmetry, the SHG polarization pattern rotates greatly and distorts. These different magneto-SHG characters can be understood by considering the superposition of the magnetic field-induced time-noninvariant nonlinear optical tensor and the crystal-structure-based time-invariant counterpart. The situation is further clarified by scrutinizing the Faraday rotation, whose subtle interplay with crystal symmetry accounts for the diverse behavior of the extrinsic nonlinear Kerr rotation in different materials. Our work illustrates the application of magneto-SHG techniques to directly probe nontrivial topological properties, and underlines the importance of minimizing extrinsic nonlinear Kerr rotation in polarization-resolved magneto-optical studies.

Pyroptosis in renal inflammation and fibrosis: current knowledge and clinical significance.

Pyroptosis is a novel inflammatory form of regulated cell death (RCD), characterized by cell swelling, membrane rupture, and pro-inflammatory effects. It is recognized as a potent inflammatory response required for maintaining organismal homeostasis. However, excessive and persistent pyroptosis contributes to severe inflammatory responses and accelerates the progression of numerous inflammation-related disorders. In pyroptosis, activated inflammasomes cleave gasdermins (GSDMs) and generate membrane holes, releasing interleukin (IL)-1ß/18, ultimately causing pyroptotic cell death. Mechanistically, pyroptosis is categorized into caspase-1-mediated classical pyroptotic pathway and caspase-4/5/11-mediated non-classical pyroptotic pathway. Renal fibrosis is a kidney disease characterized by the loss of structural and functional units, the proliferation of fibroblasts and myofibroblasts, and extracellular matrix (ECM) accumulation, which leads to interstitial fibrosis of the kidney tubules. Histologically, renal fibrosis is the terminal stage of chronic inflammatory kidney disease. Although there is a multitude of newly discovered information regarding pyroptosis, the regulatory roles of pyroptosis involved in renal fibrosis still need to be fully comprehended, and how to improve clinical outcomes remains obscure. Hence, this review systematically summarizes the novel findings regarding the role of pyroptosis in the pathogenesis of renal fibrosis and discusses potential biomarkers and drugs for anti-fibrotic therapeutic strategies.

Giant electrically tunable magnon transport anisotropy in a van der Waals antiferromagnetic insulator.

Anisotropy is a manifestation of lowered symmetry in material systems that have profound fundamental and technological implications. For van der Waals magnets, the two-dimensional (2D) nature greatly enhances the effect of in-plane anisotropy. However, electrical manipulation of such anisotropy as well as demonstration of possible applications remains elusive. In particular, in-situ electrical modulation of anisotropy in spin transport, vital for spintronics applications, has yet to be achieved. Here, we realized giant electrically tunable anisotropy in the transport of second harmonic thermal magnons (SHM) in van der Waals anti-ferromagnetic insulator CrPS4 with the application of modest gate current. Theoretical modeling found that 2D anisotropic spin Seebeck effect is the key to the electrical tunability. Making use of such large and tunable anisotropy, we demonstrated multi-bit read-only memories (ROMs) where information is inscribed by the anisotropy of magnon transport in CrPS4. Our result unveils the potential of anisotropic van der Waals magnons for information storage and processing.

Exploring the components and mechanism of Solanum nigrum L. for colon cancer treatment based on network pharmacology and molecular docking.

Background: Solanum nigrum L. (SNL) (Longkui) is a Chinese herb that can be used to treat colon cancer. The present study explored the components and mechanisms of SNL in treating colon cancer by using network pharmacology and molecular docking. Methods: The components of SNL were collected from the TCMSP, ETCM, HERB, and NPASS databases. Meanwhile, the target proteins of these ingredients were collected/predicted by the TCMSP, SEA, SwissTargetPrediction, and the STITCH databases colon cancer-related target genes were identified from TCGA and GTEx databases. The interaction networks were established via Cytoscape 3.7.2. Gene Ontology and KEGG pathways were enriched by using the David 6.8 online tool. Finally, the binding of key components and targets was verified by molecular docking, and the cellular thermal shift assay (CETSA) was used to detect the efficiency of apigenin and kaempferol binding to the AURKB protein in CT26 cells. Results: A total of 37 SNL components, 796 SNL targets, 5,356 colon cancer genes, and 241 shared targets of SNL and colon cancer were identified. A total of 43 key targets were obtained through topology analysis. These key targets are involved in multiple biological processes, such as signal transduction and response to drug and protein phosphorylation. At the same time, 104 signaling pathways, such as pathways in cancer, human cytomegalovirus infection, and PI3K-Akt signaling pathway, are also involved. The binding of the four key components (i.e., quercetin, apigenin, kaempferol, and luteolin) and the key targets was verified by molecular docking. The CETSA results showed that apigenin and kaempferol were able to bind to the AURKB protein to exert anti-CRC effects. Conclusions: Quercetin, apigenin, kaempferol, and luteolin are the main components of SNL in treating colon cancer. SNL regulates multiple bioprocesses via signaling pathways, such as pathways in cancer, PI3K-Akt, and cell cycle signaling pathways.

Traditional Chinese medicine for colorectal cancer treatment: potential targets and mechanisms of action.

Colorectal cancer (CRC) is a disease with complex pathogenesis, it is prone to metastasis, and its development involves abnormalities in multiple signaling pathways. Surgery, chemotherapy, radiotherapy, target therapy, and immunotherapy remain the main treatments for CRC, but improvement in the overall survival rate and quality of life is urgently needed. Traditional Chinese medicine (TCM) has a long history of preventing and treating CRC. It could affect CRC cell proliferation, apoptosis, cell cycle, migration, invasion, autophagy, epithelial-mesenchymal transition, angiogenesis, and chemoresistance by regulating multiple signaling pathways, such as PI3K/Akt, NF-κB, MAPK, Wnt/ß-catenin, epidermal growth factor receptors, p53, TGF-ß, mTOR, Hedgehog, and immunomodulatory signaling pathways. In this paper, the main signaling pathways and potential targets of TCM and its active ingredients in the treatment of CRC were systematically summarized, providing a theoretical basis for treating CRC with TCM and new ideas for further exploring the pathogenesis of CRC and developing new anti-CRC drugs.

Efficient Coarse-Grained Superplasticity of a Gigapascal Lightweight Refractory Medium Entropy Alloy.

Superplastic metals that exhibit exceptional ductility (>300%) are appealing for use in high-quality engineering components with complex shapes. However, the wide application of most superplastic alloys has been constrained due to their poor strength, the relatively long superplastic deformation period, and the complex and high-cost grain refinement processes. Here these issues are addressed by the coarse-grained superplasticity of high-strength lightweight medium entropy alloy (Ti43.3 V28 Zr14 Nb14 Mo0.7 , at.%) with a microstructure of ultrafine particles embedded in the body-centered-cubic matrix. The results demonstrate that the alloy reached a high coarse-grained superplasticity greater than ≈440% at a high strain rate of 10-2 s-1 at 1173 K and with a gigapascal residual strength. A consecutively triggered deformation mechanism that sequences of dislocation slip, dynamic recrystallization, and grain boundary sliding in such alloy differs from conventional grain-boundary sliding in fine-grained materials. The present results open a pathway for highly efficient superplastic forming, broaden superplastic materials to the high-strength field, and guide the development of new alloys.

Fourfold Symmetric Superconductivity in Spinel Oxide LiTi2O4(001) Thin Films.

The charge frustration with the mixed-valence state inherent to LiTi2O4, which is found to be the only oxide superconductor with spinel structure, is the impetus for paying special attention to unveil the underlying intriguing superconducting properties. Here, we report a pronounced fourfold rotational symmetry of the superconductivity in high-quality single-crystalline LiTi2O4(001) thin films. Both the magnetoresistivity and upper critical field under an applied magnetic field manifest striking fourfold oscillations deep inside the superconducting state, whereas the anisotropy vanishes in the normal state, demonstrating that it is an intrinsic property of the superconducting phase. We attribute this behavior to the unconventional d-wave superconducting Cooper pairs with the irreducible representation of Eg protected by the Oh point group in cubic LiTi2O4. Our findings show the nontrivial character of the pairing interaction in a three-dimensional spinel oxide superconductor.

Two-Dimensional Superconductivity at the Titanium Sesquioxide Heterointerface.

The study of exotic superconductivity in two dimensions has been a central theme in the solid state and materials research communities. Experimentally exploring and identifying exotic, fascinating interface superconductors with a high transition temperature (Tc) are challenging. Here, we report an experimental observation of intriguing two-dimensional superconductivity with a Tc of up to 3.8 K at the interface between a Mott insulator Ti2O3 and polar semiconductor GaN. At the verge of superconductivity, we also observe a striking quantum metallic-like state, demonstrating that it is a precursor to the two-dimensional superconductivity as the temperature is decreased. Our work shows an exciting opportunity to exploit the underlying, emergent quantum phenomena at the heterointerfaces via heterostructure engineering.

Complete mitochondrial genome of the top hat blenny, Omobranchus fasciolatoceps Richardson (Blenniiformes: Blenniinae) in Southern China Coast.

The complete mitochondrial genome sequence of Omobranchus fasciolatoceps was firstly described in this article. The total length of mitogenome was 16,569 bp. It contains 13 protein-coding genes, 22 tRNA genes, and two ribosomal RNA genes. The overall base composition of H-strand was 29.04% A, 27.14% C, 27.89% T, and 15.93% G, with an A＋T bias of 56.93%. The phylogenetic analysis results showed that the O. fasciolatoceps was most closely related to O. elegans.

High-Performance Semitransparent Organic Solar Cells: From Competing Indexes of Transparency and Efficiency Perspectives.

Semitransparent organic solar cells (ST-OSCs) offer potentially more opportunities in areas of self-powered greenhouses and building-integrated photovoltaic systems. In this work, the effort to use a combination of solution-processable gold nanobipyramids (AuNBPs)-based hole transporting layer and a low/high dielectric constant double layer optical coupling layer (OCL) for improving the performance of ST-OSCs over the two competing indexes of power conversion efficiency (PCE) and average visible transmittance (AVT) is reported. The fabrication and characterization of the ST-OSCs are guided, at design and analyses level, using the theoretical simulation and experimental optimization. The use of a low/high dielectric constant double layer OCL helps enhancing the visible light transparency while reflecting the near-infrared (NIR) photons back into the photoactive layer for light harvesting. NIR absorption enhancement in the ST-OSCs is realized through the AuNBPs-induced localized surface plasmon resonance (LSPR). The weight ratio of the polymer donor to nonfullerene acceptor in the bulk heterojunction is adjusted to realize the maximum NIR absorption enhancement, enabled by the AuNBPs-induced LSPR, achieving the high-performance ST-OSCs with a high PCE of 13.15% and a high AVT of 25.9%.

Spin mapping of intralayer antiferromagnetism and field-induced spin reorientation in monolayer CrTe2.

Intrinsic antiferromagnetism in van der Waals (vdW) monolayer (ML) crystals enriches our understanding of two-dimensional (2D) magnetic orders and presents several advantages over ferromagnetism in spintronic applications. However, studies of 2D intrinsic antiferromagnetism are sparse, owing to the lack of net magnetisation. Here, by combining spin-polarised scanning tunnelling microscopy and first-principles calculations, we investigate the magnetism of vdW ML CrTe2, which has been successfully grown through molecular-beam epitaxy. We observe a stable antiferromagnetic (AFM) order at the atomic scale in the ML crystal, whose bulk is ferromagnetic, and correlate its imaged zigzag spin texture with the atomic lattice structure. The AFM order exhibits an intriguing noncollinear spin reorientation under magnetic fields, consistent with its calculated moderate magnetic anisotropy. The findings of this study demonstrate the intricacy of 2D vdW magnetic materials and pave the way for their in-depth analysis.