Engineering covalently bonded 2D layered materials by self-intercalation.

Two-dimensional (2D) materials1-5 offer a unique platform from which to explore the physics of topology and many-body phenomena. New properties can be generated by filling the van der Waals gap of 2D materials with intercalants6,7; however, post-growth intercalation has usually been limited to alkali metals8-10. Here we show that the self-intercalation of native atoms11,12 into bilayer transition metal dichalcogenides during growth generates a class of ultrathin, covalently bonded materials, which we name ic-2D. The stoichiometry of these materials is defined by periodic occupancy patterns of the octahedral vacancy sites in the van der Waals gap, and their properties can be tuned by varying the coverage and the spatial arrangement of the filled sites7,13. By performing growth under high metal chemical potential14,15 we can access a range of tantalum-intercalated TaS(Se)y, including 25% Ta-intercalated Ta9S16, 33.3% Ta-intercalated Ta7S12, 50% Ta-intercalated Ta10S16, 66.7% Ta-intercalated Ta8Se12 (which forms a Kagome lattice) and 100% Ta-intercalated Ta9Se12. Ferromagnetic order was detected in some of these intercalated phases. We also demonstrate that self-intercalated V11S16, In11Se16 and FexTey can be grown under metal-rich conditions. Our work establishes self-intercalation as an approach through which to grow a new class of 2D materials with stoichiometry- or composition-dependent properties.

DeepFormer: a hybrid network based on convolutional neural network and flow-attention mechanism for identifying the function of DNA sequences.

Identifying the function of DNA sequences accurately is an essential and challenging task in the genomic field. Until now, deep learning has been widely used in the functional analysis of DNA sequences, including DeepSEA, DanQ, DeepATT and TBiNet. However, these methods have the problems of high computational complexity and not fully considering the distant interactions among chromatin features, thus affecting the prediction accuracy. In this work, we propose a hybrid deep neural network model, called DeepFormer, based on convolutional neural network (CNN) and flow-attention mechanism for DNA sequence function prediction. In DeepFormer, the CNN is used to capture the local features of DNA sequences as well as important motifs. Based on the conservation law of flow network, the flow-attention mechanism can capture more distal interactions among sequence features with linear time complexity. We compare DeepFormer with the above four kinds of classical methods using the commonly used dataset of 919 chromatin features of nearly 4.9 million noncoding DNA sequences. Experimental results show that DeepFormer significantly outperforms four kinds of methods, with an average recall rate at least 7.058% higher than other methods. Furthermore, we confirmed the effectiveness of DeepFormer in capturing functional variation using Alzheimer's disease, pathogenic mutations in alpha-thalassemia and modification in CCCTC-binding factor (CTCF) activity. We further predicted the maize chromatin accessibility of five tissues and validated the generalization of DeepFormer. The average recall rate of DeepFormer exceeds the classical methods by at least 1.54%, demonstrating strong robustness.

COL3A1-positive endothelial cells influence LUAD prognosis and regulate LUAD carcinogenesis by NCL-PI3K-AKT axis.

BACKGROUND: Lung adenocarcinoma (LUAD), as the most common type of lung cancer, poses a significant threat to public health. Tumor heterogeneity plays a crucial role in carcinogenesis, which could be largely deciphered by next-generation sequencing (NGS). METHODS: We obtained and screened single-cell RNA sequencing (scRNA-seq) data from 16 LUAD samples, and endothelial cells (ECs) were grouped into three clusters. The origin of EC differentiation was explored by pseudo-time analysis. CellChat analysis was used to detect potential communication between ECs and malignant cells, and gene regulatory network analysis was used to identify changes in transcription factor activity. We explored the prognosis of specific ECs clusters and their effects on the tumor microenvironment (TME) at the bulk transcriptome level. 5-Ethynyl-2'- deoxyuridine (EdU) and Ki-67 staining were conducted to study the proliferative phenotype of LUAD cell lines. Western blotting targeting the phosphorylation of PI3K-AKT proteins was utilized for determination of the downstream pathway of NCL. RESULTS: COL3A1-positive ECs showed the highest crosstalk interaction with malignant cells, indicating that they have important effects on driving LUAD carcinogenesis. Vascular endothelial growth factor (VEGF) signaling pathway was identified as the main signaling pathway, mediating signal transduction from malignant cells. The TME-related genes of COL3A1-positive ECs were significantly more highly expressed. COL3A1-positive ECs showed unique metabolic and immune characteristics, as well as highly activated metabolic signaling pathways and inflammatory responses. Importantly, LUAD patients with low COL3A1-positive ECs scores displayed an inferior prognosis outcome and a higher risk of metastasis. The key target gene NCL, which is involved in the interaction between epithelial cells and cancer cells, has been identified through screening. Flow cytometry showed that knockdown of NCL prompted the apoptosis of A549 and NCI-H1299. Western blotting showed that knockdown of NCL decreased the phosphorylation of AKT and PI3K, which identified the downstream pathway of NCL. CONCLUSIONS: COL3A1-positive ECs have important effects on the development of LUAD and the formation of an immune microenvironment. Furthermore, we identified a key target gene, NCL, which is involved in the interaction between endothelial cells and cancer cells. NCL also affected the apoptosis and proliferation in LUAD through the PI3K-AKT pathway.

Identification of prognostic value of anoikis-related gene score model combined with tumor microenvironment score models in esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) has poor survival. Effective prognostic models with high application value remain lack. METHODS: Bulk RNA seq and single cell RNA-seq data were retrieved from the XENA-TCGA-ESCC cohort and GSE188900. The anoikis-related gene score (ANO score) model and tumor microenvironment score (TME score) model were constructed and merged into three subgroups. Functional annotation was analyzed by Gene Ontology terms. Univariate and multivariate Cox regression analysis, least absolute shrinkage and selection operator regression analysis and weighted gene coexpression network analysis were performed to construct prognostic prediction models and identify prognostic value. Kaplan-Meier survival curves were drawn for evaluating the overall survival (OS) of patients classified by different score subgroups. Immunotherapy response and mutation analyses were also conducted. RESULTS: In the ANO score model, TNFSF10 was an independent factor for the prognosis of ESCC patients. The area under the curve values of the ANO-TME score model in predicting the OS were 0.638 at 5 years and 0.632 at 7 years. Patients in the ANO low score-TME high score group had a much longer OS than patients in any other ANO-TME score subgroup (p < 0.001), suggesting a higher prognostic value. The differentially expressed genes of the ANO low score-TME high score group were mainly involved in cell adhesion molecules, nucleotide excision repair, the TGF-ß signaling pathway and mismatch repair. TP53 (92%), TTN (38%) and NFE2L2 (31%) were the top genes with highest mutant frequency in the ANO low score-TME high score group. CONCLUSIONS: A novel prognostic prediction model with high application value was constructed and identified for ESCC patients, which may provide evidence for immunotherapy in the treatment of ESCC.

Highly Efficient Spin Injection and Readout Across Van Der Waals Interface.

Spin injection, transport, and detection across the interface between a ferromagnet and a spin-carrying channel are crucial for energy-efficient spin logic devices. However, interfacial conductance mismatch, spin dephasing, and inefficient spin-to-charge conversion significantly reduce the efficiency of these processes. In this study, it is demonstrated that an all van der Waals heterostructure consisting of a ferromagnet (Fe3GeTe2) and Weyl semimetal enables a large spin readout efficiency. Specifically, a nonlocal spin readout signal of 150 mΩ and a local spin readout signal of 7.8 Ω is achieved, which reach the signal level useful for practical spintronic devices. The remarkable spin readout signal is attributed to suppressed spin dephasing channels at the vdW interfaces, long spin diffusion, and efficient charge-spin interconversion in Td-MoTe2. These findings highlight the potential of vdW heterostructures for spin Hall effect-enabled spin detection with high efficiency, opening up new possibilities for spin-orbit logic devices using vdW interfaces.

Deep learning empowers photothermal microscopy with super-resolution capabilities.

In the past two decades, photothermal microscopy (PTM) has achieved sensitivity at the level of a single particle or molecule and has found applications in the fields of material science and biology. PTM is a far-field imaging method; its resolution is restricted by the diffraction limits. In our previous work, the modulated difference PTM (MDPTM) was proposed to improve the lateral resolution, but its resolution improvement was seriously constrained by information loss and artifacts. In this Letter, a deep learning approach of the cycle generative adversarial network (Cycle GAN) is employed for further improving the resolution of PTM, called DMDPTM. The point spread functions (PSFs) of both PTM and MDPTM are optimized and act as the second generator of Cycle GAN. Besides, the relationship between the sample's volume and the photothermal signal is utilized during dataset construction. The images of both PTM and MDPTM are utilized as the inputs of the Cycle GAN to incorporate more information. In the simulation, DMDPTM quantitatively distinguishes a distance of 60 nm between two nanoparticles (each with a diameter of 60 nm), demonstrating a 4.4-fold resolution enhancement over the conventional PTM. Experimentally, the super-resolution capability of DMDPTM is verified by restored images of Au nanoparticles, achieving the resolution of 114 nm. Finally, the DMDPTM is successfully employed for the imaging of carbon nanotubes. Therefore, the DMDPTM will serve as a powerful tool to improve the lateral resolution of PTM.

Feedback regulation of the isoprenoid pathway by SsdTPS overexpression has the potential to enhance plant tolerance to drought stress.

In order to maintain the dynamic physiological balance, plants are compelled to adjust their energy metabolism and signal transduction to cope with the abiotic stresses caused by complex and changeable environments. The diterpenoid natural compound and secondary metabolites, sclareol, derived from Salvia sclarea, has gained significant attention owing to its economic value as a spice material and diverse physiological activities. Here, we focused on the roles and regulatory mechanisms of the sclareol diterpene synthase gene SsdTPS in the resistance of S. sclarea to abiotic stresses. Our results suggested that abiotic stresses could induce the response and upregulation of SsdTPS expression and isoprenoid pathway in S. sclarea. Ectopic expression of SsdTPS conferred drought tolerance in transgenic Arabidopsis, compared with wild-type. Overexpression of SsdTPS enhanced the transcription of ABA signal transduction synthetic regulators and induced the positive feedback upregulating key regulatory genes in the MEP pathway, thereby promoting the increase of ABA content and improving drought tolerance in transgenic plants. In addition, SsdTPS-overexpressed transgenic Arabidopsis improved the responses of stomatal regulatory genes and ROS scavenging enzyme activities and gene expression to drought stress. This promoted the stomatal closure and ROS reduction, thus enhancing water retention capacity and reducing oxidative stress damage. These findings unveil the potentially positive role of SsdTPS in orchestrating multiple regulatory mechanisms and maintaining homeostasis for improved abiotic stress resistance in S. sclarea, providing a novel insight into strategies for promoting drought resistance and cultivating highly tolerant plants.

The Global Environmental Impacts of China's Accession to the WTO: A 20-Year Review.

Robust empirical assessments of the long-term cumulative global effects of free trade and economic globalization on the environment are limited. This account fills this gap by constructing a dynamic computable general equilibrium model to estimate the environmental effects of a milestone in the recent history of trade liberalization: China's 20-year World Trade Organization (WTO) accession. The modeling shows that China's accession could have resulted in an increase in the global cumulative greenhouse gases (GHGs), sulfur dioxide (SO2), and nitrogen oxide (NOx) emissions by roughly 14,000 Mt CO2-eq, 64 Mt, and 46 Mt, respectively. The global production scale effect contributed to most of these estimated increases. The regional total output composition effect also caused higher emissions. Meanwhile, the sectoral output composition effect helped reduce total emissions to a limited extent. Fortunately, a package of emission abatement measures led to a decrease in emission factors and a drop in the global cumulative emissions of GHGs, SO2, and NOx. The findings suggest that to enjoy the free trade and economic globalization benefits and minimize the induced emission increases, it is vitally important to systemically reduce emissions across the entire economy and nurture a low-carbon trade regime.

Study of the microscopic mechanism of stepwise charge injection in co-sensitive DSSCs in the framework of a D-π-A dye and chlorophyll.

The newly synthesized dye molecules TY6 and CXC22 were selected to explain the influence of anthracene and acetylene groups on the power conversion efficiency (PCE) of the molecules at the microscopic level. Theoretical simulation was carried out to understand the properties of the two molecules, including frontier molecular orbitals, absorption spectra, light absorption efficiency, intramolecular charge transfer (ICT), dye regeneration, I-V prediction, etc. The results suggest that for CXC22, adding an anthracene and acetylene group in the conjugate bridge greatly enhances the molecule's absorption wavelength and molar extinction coefficient; CXC22 also has significant advantages in the intramolecular charge transfer and comparatively better dye regeneration and electron injection. These parameters cause CXC22 to have a higher PCE. Subsequently, CXC22 and the chlorophyll molecule (CHL7) were selected for co-sensitization to regulate performance. The stable structure in the co-sensitization configuration was screened, and the absorption spectrum characteristics and charge transfer mechanisms were revealed for the co-sensitization system. The designed evaluation model predicted that the PCE of CO1 (the cosensitive system of CXC22 and TY6 in H-H configuration is referred to as CO1) could reach 16.78%. This work provides an idea for developing an efficient dye-sensitized solar cell system.

UV communication cooperative formation UAV alliance capture algorithm.

The capture of target unmanned aerial vehicles (UAVs) by a UAV formation is one of the important and typical tasks in multi-UAV battlefield operations. In this paper, an ultraviolet (UV) light communication-assisted formation UAV alliance capture algorithm is proposed, which combines UV light communication technology with a capture algorithm. With the help of wireless UV light to assist UAV formation inter-UAV data confidentiality transmission and non-line-of-sight communication, the algorithm integrates the alliance generation algorithm with the region minimization strategy, solves the optimal alliance structure by using the dynamic programming method, and implements the aerial capture of the target UAVs by using the region minimization strategy, so as to complete the task of efficiently capturing multi-targets by the UAV formation in complex scenarios. Simulation comparisons were conducted between the region minimization strategy and the proposed UV communication-assisted formation UAV alliance capture algorithm. The results show that the proposed algorithm reduces energy consumption by 12.73% on average and decreases the average number of algorithm iterations by 27.49% during the UAV formation capture of multiple targets, which verifies its low energy consumption and high capture efficiency.

Early result of percutaneous full-endoscopic transforaminal lumbar interbody fusion in the treatment of single-level lumbar degenerative diseases: a retrospective study.

OBJECTIVE: The study aimed to evaluate the short-term clinical efficacy of percutaneous full-endoscopic transforaminal lumbar interbody fusion (Endo-TLIF) for lumbar degenerative diseases (LDD). METHODS: From July 2020 to July 2021, 93 patients who underwent single-level lumbar fusion procedure were retrospective analysis. The patients were divided into Endo-TLIF group and transforaminal lumbar interbody fusion (TLIF) group. General demographic and perioperative data were recorded, the clinical outcomes were evaluated using visual analogue scale (VAS) and oswestry disability index (ODI). The disk height (DH) was compared between the two groups. RESULTS: All of the surgical procedures were successfully completed, and the patients were followed for a minimum of 2 years. Intraoperative blood loss, drainage volume, time to independent ambulation and hospital length of stay in the Endo-TLIF group were significantly decreased in comparison with the open TLIF group (p < 0.05). The VAS for back pain on postoperative 7 day and ODI on postoperative 1 month were lower in the Endo-TLIF group than in the open TLIF group (P < 0.05), but no significant difference at 1 year and 2 years postoperatively (P > 0.05). The VAS score of leg pain had no demographic statistically significant differences between the groups (P > 0.05). The DH were significantly heightened after surgery compared to the preoperative height (p < 0.05). CONCLUSION: Endo-TLIF is a minimally invasive, safety surgery which can achieve comparable short-term effects as open TLIF. It may be a promising option for the treatment of LDD.

Is unilateral-approach full-endoscopic lumbar fusion effective for single-level lumbar spondylolisthesis with bilateral symptoms? A preliminary report of 43 CT analysis.

PURPOSE: To investigate the clinical results and radiological parameters changes after unilateral-approach endoscopic lumbar interbody fusion (Endo-LIF) for lumbar spondylolisthesis with bilateral symptoms. METHODS: 43 single-level lumbar spondylolisthesis patients with bilateral lower limb symptoms were included from June 2020 to May 2022. All patients underwent unilateral-approach Endo-LIF and postoperative computed tomography. Radiological parameters including disk height (DH), degree of upper vertebral slip (DUVS), and foramen intervertebral parameters including bilateral foraminal height (FH), contralateral foraminal areas (FA) were evaluated. The clinical outcomes including low back pain and bilateral leg pain were evaluated using Visual Analog Scale (VAS) and the Oswestry Disability Index (ODI) before and after surgery. RESULTS: All cases were successfully completed surgery and followed for average 15.16 ± 5.2 months. DH (44% ± 11%) and DUVS were significantly improvement postoperatively compared with preoperatively (p < 0.05). Statistically significant increases in bilateral FH (25% ± 11% on the surgical side, 17% ± 8% on the contralateral side) and contralateral FA (26% ± 6%) were observed (p < 0.05). The VAS and the ODI scores were significantly decreased in comparison with the preoperative scores (p < 0.05). CONCLUSION: Unilateral-approach with contralateral indirect decompression in Endo-LIF can acquire satisfactory clinical outcomes. Therefore, unilateral-approach Endo-LIF may be a promising option for lumbar spondylolisthesis with bilateral symptoms.

Surface Superconductivity with High Transition Temperatures in Layered CanBn+1Cn+1 Films.

Proposed by Ginzberg nearly 60 years ago, surface superconductivity refers to the emergent phenomenon that the electrons on or near the surface of a material becomes superconducting despite its bulk is nonsuperconducting. Here, based on first-principles calculations within density functional theory, we predict that the superconducting transition temperature Tc at the surfaces of CanBn+1Cn+1 (n = 1, 2, 3, ...) films can be drastically enhanced to ∼90 K from 8 K for bulk CaBC. Our detailed analyses reveal that structural symmetry reduction at surfaces induces pronounced carrier self-doping into the surface B-C layer of the films and shifts the σ-bonding states toward the Fermi level; furthermore, the in-plane stretching modes of the surface layers experience significant softening. These two effects work collaboratively to strongly enhance the electron-phonon coupling, which in turn results in much higher Tc values than the McMillian limit. These findings point to new material platforms for realizing unusually high-Tc surface superconductivity.

Integrated Transcriptome and Proteome Analysis Reveals the Regulatory Mechanism of Root Growth by Protein Disulfide Isomerase in Arabidopsis.

Protein disulfide isomerase (PDI, EC 5.3.4.1) is a thiol-disulfide oxidoreductase that plays a crucial role in catalyzing the oxidation and rearrangement of disulfides in substrate proteins. In plants, PDI is primarily involved in regulating seed germination and development, facilitating the oxidative folding of storage proteins in the endosperm, and also contributing to the formation of pollen. However, the role of PDI in root growth has not been previously studied. This research investigated the impact of PDI gene deficiency in plants by using 16F16 [2-(2-Chloroacetyl)-2,3,4,9-tetrahydro-1-methyl-1H-pyrido[3,4-b]indole-1-carboxylic acid methyl ester], a small-molecule inhibitor of PDI, to remove functional redundancy. The results showed that the growth of Arabidopsis roots was significantly inhibited when treated with 16F16. To further investigate the effects of 16F16 treatment, we conducted expression profiling of treated roots using RNA sequencing and a Tandem Mass Tag (TMT)-based quantitative proteomics approach at both the transcriptomic and proteomic levels. Our analysis revealed 994 differentially expressed genes (DEGs) at the transcript level, which were predominantly enriched in pathways associated with "phenylpropane biosynthesis", "plant hormone signal transduction", "plant-pathogen interaction" and "starch and sucrose metabolism" pathways. Additionally, we identified 120 differentially expressed proteins (DEPs) at the protein level. These proteins were mainly enriched in pathways such as "phenylpropanoid biosynthesis", "photosynthesis", "biosynthesis of various plant secondary metabolites", and "biosynthesis of secondary metabolites" pathways. The comprehensive transcriptome and proteome analyses revealed a regulatory network for root shortening in Arabidopsis seedlings under 16F16 treatment, mainly involving phenylpropane biosynthesis and plant hormone signal transduction pathways. This study enhances our understanding of the significant role of PDIs in Arabidopsis root growth and provides insights into the regulatory mechanisms of root shortening following 16F16 treatment.

Surface-enhanced Raman scattering spectroscopy monitoring and degradation of organic pollutants using a novel nanowire.

A multifunctional Ag/AlOOH nanowires (ANW) composite substrate was constructed, which not only accomplishes highly sensitive detection of organic dye molecules, but also has excellent performance in the degradation of pollutants. The ANW in the Ag/ANW substrate possesses a high aspect ratio, which extends the distribution area of Ag and enables a large number of hot spots on the active substrate. Additionally, due to the abundant OH groups on the ANW, there is an increased number of anchor sites for adsorbed metal ions in the Ag/ANW compound, thus contributing to the enhancement and degradation of molecules. Moreover, the constructed multifunctional Ag/ANW nanocomplexes also show great promise for practical applications, providing a reference for the detection and degradation of contaminants.

Association between Statin Use and Chemotherapy-Induced Cardiotoxicity: A Meta-Analysis.

Background: Chemotherapy-induced cardiac dysfunction (CIC) is a significant and concerning complication observed among cancer patients. Despite the demonstrated cardioprotective benefits of statins in various cardiovascular diseases, their effectiveness in mitigating CIC remains uncertain. Objective: This meta-analysis aims to comprehensively evaluate the potential cardioprotective role of statins in patients with CIC. Methods: A systematic literature search was conducted using PubMed, Embase, and Scopus databases to identify relevant articles published from inception until 10th May 2023. The outcomes were assessed using pooled odds ratio (OR) for categorical data and mean difference (MD) for continuous data, with corresponding 95% confidence intervals (95% CIs). Results: This meta-analysis comprised nine studies involving a total of 5532 patients, with 1904 in the statin group and 3628 in the non-statin group. The pooled analysis of primary outcome shows that patients who did not receive statin suffer a greater decline in the LVEF after chemotherapy compared to those who receive statin (MD, 3.55 (95% CI: 1.04-6.05), p = 0.01). Likewise, we observed a significantly higher final mean LVEF among chemotherapy patients with statin compared to the non-statin group of patients (MD, 2.08 (95% CI: 0.86-3.30), p > 0.001). Additionally, there was a lower risk of incident heart failure in the statin group compared to the non-statin group of patients (OR, 0.41 (95% CI: 0.27-0.62), p < 0.001). Lastly, the change in the mean difference for LVEDV was not statistically significant between the statin and non-statin groups (MD, 1.55 (95% CI: -5.22-8.33), p = 0.65). Conclusion: Among patients of CIC, statin use has shown cardioprotective benefits by improving left ventricular function and reducing the risk of heart failure.

Mucosal-associated invariant T cells in digestive tract: Local guardians or destroyers?

Mucosa-associated invariant T cells (MAIT) are a class of innate-like T lymphocytes mainly presenting CD8+ phenotype with a semi-invariant αß T-cell receptor, which specifically recognises MR1-presented biosynthetic derivatives of riboflavin synthesis produced by various types of microbiomes. As innate-like T lymphocytes, MAIT can be activated by a variety of cytokines, leading to immediate immune responses to infection and tumour cues. As an organ that communicates with the external environment, the digestive tract, especially the gastrointestinal tract, contains abundant microbial populations. Communication between MAIT and local microbiomes is important for the homeostasis of mucosal immunity. In addition, accumulating evidence suggests changes in the abundance and structure of the microbial community during inflammation and tumorigenesis plays a critical role in disease progress partly through their impact on MAIT development and function. Therefore, it is essential for the understanding of MAIT response and their interaction with microbiomes in the digestive tract. Here, we summarised MAIT characteristics in the digestive tract and its alteration facing inflammation and tumour, raising that targeting MAIT can be a candidate for treatment of gastrointestinal diseases.

Peripheral blood inflammatory biomarkers dynamics reflect treatment response and predict prognosis in non-small cell lung cancer patients with neoadjuvant immunotherapy.

Neoadjuvant immunotherapy has significantly changed the therapeutic approach for treating patients with surgically resectable non-small cell lung cancer (NSCLC). Here, peripheral blood inflammation-based biomarkers as well as previously less focused eosinophil fraction, modified Glasgow prognostic score (mGPS), and prognostic nutritional index (PNI) were systematically included to comprehensively analyze their potential in predicting neoadjuvant immunotherapy efficacy and prognosis. We enrolled 189 patients (94 in training and 95 in validation cohorts) with stage I-III B surgically resectable NSCLC treated with neoadjuvant immunotherapy from the National Cancer Center of China. Baseline and post-treatment eosinophils fraction, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), monocyte-to-lymphocyte ratio (MLR), PNI, mGPS, and their changes were calculated and analyzed for correlation with neoadjuvant immunotherapy efficacy and prognosis. In patients in the major pathological response (MPR) group, the post-treatment eosinophil fraction was significantly high, and NLR, PLR, SII, and MLR were significantly lower compared to the non-MPR group in both the training and validation cohorts. The receiver operating characteristic curve showed that post-treatment, eosinophil fraction and SII and their changing were two of the most important factors. Univariate and multivariate logistic regression analyses showed that post-treatment eosinophil fraction, SII, mGPS, and ΔSII could independently predict MPR in patients treated with neoadjuvant immunotherapy. Survival analysis showed a significant correlation between high post-treatment NLR, PLR, SII, mGPS, and their changes in ΔNLR and ΔSII elevation with poor overall survival and event-free survival of patients. Our results suggest that inflammatory biomarkers could predict the patient's response to neoadjuvant immunotherapy and prognosis.

Association between radiotherapy and risk of second primary malignancies in patients with resectable lung cancer: a population-based study.

BACKGROUND: The most common form of treatment for non-metastatic lung cancer is surgery-based combination therapy, which may also include adjuvant radiotherapy or chemotherapy. Second primary malignancies (SPMs) are uncommon but significant radiation side effects in patients with resectable lung cancer, and SPMs have not been adequately investigated. Our study aims to assess the correlations of radiotherapy with the development of SPMs in patients with resectable lung cancer. METHODS: We screened for any primary malignancy that occurred more than five years after the diagnosis of resectable lung cancer. Based on the large cohort of the Surveillance, Epidemiology and End Results database, radiotherapy-correlated risks were estimated using the Poisson regression analysis and the cumulative incidence of SPMs was calculated using Fine-Gray competing risk regression analysis. RESULTS: Among the 62,435 patients with non-metastatic lung cancer undergoing surgery, a total of 11,341 (18.16%) patients have received radiotherapy. Our findings indicated that radiotherapy was substantially related to a high risk of main second solid malignancies (RR = 1.21; 95%CI, 1.08 to 1.35) and a negligible risk of main second hematologic malignancies (RR = 1.08; 95%CI, 0.84 to 1.37). With the greatest number of patients, the risk of acquiring a second primary gastrointestinal cancer was the highest overall (RR = 1.77; 95 percent CI, 1.44 to 2.15). The cumulative incidence and standardized incidence ratios of SPMs revealed similar findings. Furthermore, the young and the elderly may be more vulnerable, and the highest risk of acquiring most SPMs was seen more than ten years after lung cancer diagnosis. Additionally, more attention should be paid to the second primary gastrointestinal cancer in young individuals with resectable lung cancer. CONCLUSION: After receiving radiotherapy, an increased risk of developing second primary solid and gastrointestinal cancers was observed for patients with resectable lung cancer. The prevention of SPMs associated with radiotherapy requires further attention.

High-precision turning and ultra-smooth direct polishing of aluminum alloy mirrors.

Due to the high surface roughness requirements of aluminum alloy mirrors used in the visible light band, there are still great challenges in single point diamond turning of high-surface quality aluminum alloy mirrors. In this paper, a processing method for aluminum alloy mirrors is proposed. Based on single point diamond turning technology, the prediction model of aluminum alloy surface roughness was established. The mapping relationship between the surface roughness of the aluminum alloy mirror and each turning parameter was obtained, and the maximum possible surface quality was achieved. On the basis of the turning results, the method of small tool polishing was used to remove the turning texture generated by the copy effect of the tool arc radius, suppress errors of the medium and high-frequency, and reduce the surface roughness. The single abrasive removal efficiency model was established and mechanical removal in the polishing process was analyzed. Combined with the chemical action in the polishing process, two types of polishing liquid-acidic and neutral, were prepared and analyzed. The optimal polishing parameters were obtained through multiple single-factor experiments. On the basis of this, the surface roughness of the aluminum alloy after turning was optimized. The results show that the value was reduced from 4.811 to 1.482 nm, an increase of 69.2%. This method can effectively improve the machining accuracy of aluminum alloy mirrors and provide an important process guarantee for the application of aluminum alloy materials in visible-light systems.