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With the development of precision medicine and genetic testing technologies, the treatment mode of non-small cell lung cancer (NSCLC) has shifted from the previous simple model to a complex personalized therapeutic strategy. Precise genetic typing has revolutionized NSCLC, transforming it from a disease into a highly heterogeneous group of diseases, emphasizing thecritical need for individualized treatment plans. Rare mutation groups that were previously overlooked are currently receiving greater attention in personalized treatment approaches. In recent years, various treatment methods targeting rare mutations, such as small-molecule inhibitors, immunotherapy, and antibody-drug conjugates, have continuously emerged, bringing new hope to patients with rare mutations. This article aims to elucidate the latest research findings and treatment strategies for rare mutations in advanced NSCLC, expecting to contribute to achieving precise and personalized treatment approaches, thereby improving the quality of life and prognosis of patients.

IntroductionAnimal influenza viruses pose a danger to the general public. Eurasian avian-like H1N1 (EA H1N1) viruses have recently infected humans in several different countries and are often found in pigs in China, indicating that they have the potential to cause a pandemic. Therefore, there is an urgent need to develop a potent vaccine against EA H1N1.MethodsIn this study, we report the effective intramuscular (i.m.) and/or intranasal (i.n.) vaccination of mice with a subunit influenza vaccine utilizing safe adjuvant gram-positive enhancer matrix (GEM) particles derived from the food-grade bacterium Lactococcus lactis. The hemagglutinin (HA)-protein anchor (PA) subunit vaccine can be simply mixed with GEM particles to produce vaccines.ResultsAfter two booster injections, the i.m.+i.n. administered GEM subunit vaccine achieved hemagglutination inhibition titers in the serum that were equivalent to those observed using the conventional i.m. method. The mucosal and Th1-biased immune responses generated by the i.m. administered subunit vaccine alone were inferior to those induced by the i.n. and i.m.+i.n. administered subunit vaccines. Vaccinated mice were challenged with live viruses (G4 EA H1N1 and A/PR/8/34) to determine whether the adjuvant combination protected against the virus after vaccination with the influenza subunit vaccine. Compared to mice inoculated with HA alone, mice immunized with i.m.+i.n. or i.n. HA-PA-GEM displayed undetectable viral titers in the lungs, at 5 d after challenge.DiscussionOverall, this study not only offers other potential platforms for the generation of swine influenza vaccines, but also a theoretical foundation for vaccine vector platforms that can be utilized for future research on other infections.

Regulated cell death (RCD) is a type of cell death modulated by specific signal transduction pathways. Currently, known RCD types include apoptosis, autophagy, ferroptosis, necroptosis, cuproptosis, pyroptosis, and NETosis. Mutations in cancer cells may prevent the RCD pathway; therefore, targeting RCD in tumors has become a promising therapeutic approach. Sesquiterpene lactones represent a diverse and extensive class of plant-derived phytochemicals that serve as potential sources for developing various drugs. Recent studies have shown that sesquiterpene lactones have promising potential in cancer treatment. This review systematically summarizes recent progress in the study of sesquiterpene lactones as antitumor agents, highlighting their role in targeting various RCD pathways, including those involved in apoptosis, autophagy, ferroptosis, necroptosis, and cuproptosis. The primary purpose of the present review is to provide a clear picture of the regulation of RCD by sesquiterpene lactones against different targets in various cancers, which will facilitate the development of new strategies for cancer therapy.

Abstract Background Maedi-visna virus (MVV) is a lentivirus that infects monocyte/macrophage lineage cells in sheep, goats, and wild ruminants and causes pneumonia, mastitis, arthritis, and encephalitis. The immune response to MVV infection is complex, and a complete understanding of its infection and pathogenesis is lacking. This study investigated the in vivo transcriptomic patterns of lung tissues in sheep exposed to MVV using the RNA sequencing technology. Result The results indicated that 2,739 genes were significantly differentially expressed, with 1,643 downregulated genes and 1,096 upregulated genes. Many variables that could be unique to MVV infections were discovered. Gene Ontology analysis revealed that a significant proportion of genes was enriched in terms directly related to the immune system and biological responses to viral infections. Kyoto Encyclopedia of Genes and Genomes analysis revealed that the most enriched pathways were related to virus-host cell interactions and inflammatory responses. Numerous immune-related genes, including those encoding several cytokines and interferon regulatory factors, were identified in the protein-protein interaction network of differentially expressed genes (DEGs). The expression of DEGs was evaluated using real-time polymerase chain reaction and western blot analysis. CXCL13, CXCL6, CXCL11, CCR1, CXCL8, CXCL9, CXCL10, TNFSF8, TNFRSF8, IL7R, IFN-γ, CCL2, and MMP9 were upregulated. Immunohistochemical analysis was performed to identify the types of immune cells that infiltrated MVV-infected tissues. B cells, CD4+ and CD8+ T cells, and macrophages were the most prevalent immune cells correlated with MVV infection in the lungs. Conclusion Overall, the findings of this study provide a comprehensive understanding of the in vivo host response to MVV infection and offer new perspectives on the gene regulatory networks that underlie pathogenesis in natural hosts.

Abstract Background Despite the recognized therapeutic potential of programmed cell death protein 1/programmed death‐ligand 1 (PD‐1/PD‐L1) inhibitors in advanced esophageal squamous cell carcinoma (ESCC), their role in neoadjuvant therapy and reliable efficacy biomarkers remain elusive. Materials and Methods We retrospectively analyzed locally advanced ESCC patients who underwent surgery following a 2‐cycle platinum and paclitaxel‐based treatment, with or without PD‐1 inhibitors (January 2020–March 2023). We assessed peripheral blood indexes and tertiary lymphoid structures (TLS) density to evaluate their impact on pathological response and prognosis, leading to a clinical prediction model for treatment efficacy and survival. Results Of the 157 patients recruited, 106 received immunochemotherapy (ICT) and 51 received chemotherapy (CT) alone. The ICT group demonstrated a superior pathological response rate (PRR) (47.2% vs. 29.4%, p = 0.034) with comparable adverse events and postoperative complications. The ICT group also showed a median disease‐free survival (DFS) of 39.8 months, unattained by the CT group. The 1‐year DFS and overall survival (OS) rates were 73% and 91% for the ICT group, and 68% and 81% for the CT group, respectively. We found higher baseline activated T cells, lower baseline Treg cells, and a decreased posttreatment total lymphocyte and CD4+/CD8+ ratio predicted an enhanced PRR. Reduced posttreatment CD4+/CD8+ ratio and increased NK cells were associated with prolonged survival, while higher TLS density indicated poorer prognosis. Among ICT group, a lower posttreatment CD4+/CD8+ ratio indicated longer DFS and reduced posttreatment B cells indicated longer OS. A nomogram integrating these predictors was developed to forecast treatment efficacy and survival. Conclusion The combination of PD‐1 inhibitors and chemotherapy appears promising for locally advanced ESCC. Evaluating the differentiation status and dynamic changes of peripheral blood immune cells may provide valuable predictive insights into treatment efficacy and prognosis.

Certain amino acids changes in the human Na+/K+-ATPase pump, ATPase Na+/K+ transporting subunit alpha 1 (ATP1A1), cause Charcot-Marie-Tooth disease type 2 (CMT2) disease and refractory seizures. To develop in vivo models to study the role of Na+/K+-ATPase in these diseases, we modified the Drosophila gene homolog, Atpα, to mimic the human ATP1A1 gene mutations that cause CMT2. Mutations located within the helical linker region of human ATP1A1 (I592T, A597T, P600T, and D601F) were simultaneously introduced into endogenous Drosophila Atpα by CRISPR/Cas9-mediated genome editing, generating the AtpαTTTF model. In addition, the same strategy was used to generate the corresponding single point mutations in flies (AtpαI571T, AtpαA576T, AtpαP579T, and AtpαD580F). Moreover, a deletion mutation (Atpαmut) that causes premature termination of translation was generated as a positive control. Of these alleles, we found two that could be maintained as homozygotes (AtpαI571T and AtpαP579T). Three alleles (AtpαA576T, AtpαP579 and AtpαD580F) can form heterozygotes with the Atpαmut allele. We found that the Atpα allele carrying these CMT2-associated mutations showed differential phenotypes in Drosophila. Flies heterozygous for AtpαTTTF mutations have motor performance defects, a reduced lifespan, seizures, and an abnormal neuronal morphology. These Drosophila models will provide a new platform for studying the function and regulation of the sodium-potassium pump.

Abstract Cancer stem cells (CSCs) are believed to be crucial in the initiation, progression, and recurrence of cancer. CSCs are also known to be more resistant to cancer treatments. However, the interaction between CSCs and the immune microenvironment is complex and not fully understood. In current study we used single cell RNA sequence (scRNA-Seq, public dataset) technology to identify the characteristic of CSCs. We found that the lung adenocarcinoma cancer stem population is highly inflammatory and remodels the tumor microenvironment by secreting inflammatory factors, specifically the acute phase protein serum amyloid A (SAA). Next, we developed an ex-vivo autologous patient-derived organoids (PDOs) and peripheral blood mononuclear cells (PBMCs) co-culture model to evaluate the immune biological impact of SAA. We found that SAA not only promotes chemoresistance by inducing cancer stem transformation, but also restricts anti-tumor immunity and promotes tumor fibrosis by driving type 2 immunity, and α-SAA neutralization antibody could restrict treatment resistant and tumor fibrosis. Mechanically, we found that the malignant phenotype induced by SAA is dependent on P2X7 receptor. Our data indicate that cancer stem cells secreted SAA have significant biological impact to promote treatment resistant and tumor fibrosis by driving cancer stemness transformation and type 2 immunity polarization via P2X7 receptor. Notably, α-SAA neutralization antibody shows therapeutic potential by restricting these malignant phenotypes.

Background: Malignant tumours, particularly non-small cell lung cancer (NSCLC), pose a significant threat to human health due to their prevalence and lethality. Treatment methods for NSCLC vary greatly among individuals, making it crucial to identify predictive markers. Moreover, during tumour initiation and progression, tumour cells can release signaling molecules to induce polarization of macrophages towards a more tumour friendly M2 phenotype, which can promote tumour growth, metastasis, and drug resistance. Methods: We employed a comprehensive approach, combining bulk RNA-seq and single-cell sequencing analysis. Results: In our study, we used bulk RNA-seq and single-cell sequencing methods to analyze differential cells in NSCLC and adjacent tissues, searching for relevant marker genes that can predict prognosis and drug efficacy. We scrutinized biological phenomena such as macrophage-related gene methylation, copy number variation, and alternative splicing. Additionally, we utilized a co-culture technique of immune and tumour cells to explore the role of these genes in macrophage polarization. Our findings revealed distinct differences in macrophages between cancerous and adjacent tissues. We identified ANP32A, CCL20, ERAP2, MYD88, TMEM126B, TUBB6, and ZNF655 as macrophage-related genes that correlate with NSCLC patient prognosis and immunotherapy efficacy. Notably, ERAP2, TUBB6, CCL20, and TMEM126B can induce macrophage M0 to M2 polarization, promoting tumour proliferation. Conclusion: These findings significantly contribute to our understanding of the NSCLC tumour immune microenvironment. They pave the way for further research into the potential of these genes as targets for regulating tumour occurrence and development.

Abstract Background Pulmonary arterial hypertension is a common complication in patients with congenital heart disease. In the absence of early diagnosis and treatment, pediatric patients with PAH has a poor survival rate. Here, we explore serum biomarkers for distinguishing children with pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD) from CHD. Methods Samples were analyzed by nuclear magnetic resonance spectroscopy-based metabolomics and 22 metabolites were further quantified by ultra-high-performance liquid chromatography–tandem mass spectroscopy. Results Serum levels of betaine, choline, S-Adenosyl methionine (SAM), acetylcholine, xanthosine, guanosine, inosine and guanine were significantly altered between CHD and PAH-CHD. Logistic regression analysis showed that combination of serum SAM, guanine and N-terminal pro-brain natriuretic peptide (NT-proBNP), yielded the predictive accuracy of 157 cases was 92.70% with area under the curve of the receiver operating characteristic curve value of 0.9455. Conclusion We demonstrated that a panel of serum SAM, guanine and NT-proBNP is potential serum biomarkers for screening PAH-CHD from CHD.

Abstract Objectives Programmed Cell Death-1/ Programmed Death-ligand 1 (PD-1 / PD-L1) inhibitor therapies targeting immunocytes induce persistent tumor remission in various cancers. However, the appropriate biomarkers for the therapeutic efficacy of PD-L1 and PD-1 blockade remain elusive. Materials and methods For a comprehensive analysis of peri-treatment lymphocyte differentiation, in the current study, we enrolled 146 non-small cell lung cancer patients who received α-PD-1 therapies for exploring the peripheral blood lymphocyte differentiation pattern at baseline and post-treatment (dynamic changes) by flow cytometry. Results At baseline, CD4+ / CD8+ T cell ratio predicts good responses and outcomes, but activated T cell and cytotoxic T cell counts predict poor responses and outcomes. And for dynamic changes, after 6 weeks of immune checkpoint blockade (ICB) treatment, compared with baseline level, the elevation of total T and B cell counts indicate poor responses, and total T and TH cell counts indicate poor prognosis while activated T cell predicts good prognosis. And after 12 weeks, elevated total lymphocyte, cytotoxic T cell counts, and decreased total T cell counts and CD4+ / CD8+ T cell ratio predict good responses / outcomes. Our clinical predicting model shows good performance in predicting ICB treatment responses / outcomes. Conclusion Patients with favorable clinical responses / outcomes have distinctive peripheral blood immunocyte differentiation characteristics, indicating the potential of utilizing the peripheral immunocyte differentiation patterns for predicting ICB responses / outcomes.

With the growing prominence of UAV-based low-altitude remote sensing in agriculture, the acquisition and processing of high-quality UAV remote sensing images is paramount. The purpose of this study is to investigate the impact of various parameter settings on image quality and optimize these parameters for UAV operations to enhance efficiency and image quality. The study examined the effects of three parameter settings (exposure time, flight altitudes and forward overlap (OF)) on image quality and assessed images obtained under various conditions using signal-to-noise ratio (SNR) and BRISQUE algorithms. The results indicate that the setting of exposure time during UAV image acquisition directly affects image quality, with shorter exposure times resulting in lower SNR. The optimal exposure times for the RGB and MS cameras have been determined as 0.8 ms to 1.1 ms and 4 ms to 16 ms, respectively. Additionally, the best image quality is observed at flight altitudes between 15 and 35 m. The setting of UAV OF complements exposure time and flight altitude; to ensure the completeness of image acquisition, it is suggested that the flight OF is set to approximately 75% at a flight altitude of 25 m. Finally, the proposed image redundancy removal method has been demonstrated as a feasible approach for reducing image mosaicking time (by 84%) and enhancing the quality of stitched images (by 14%). This research has the potential to reduce flight costs, improve image quality, and significantly enhance agricultural production efficiency.

The monitoring of crop growth, particularly the estimation of Leaf Area Index (LAI) using optical remote sensing techniques, has been a continuous area of research. However, it has become a challenge to accurately and rapidly interpret the spatial variation of LAI under nitrogen stress. To tackle these issues, this study aimed to explore the potential for precise LAI estimation by integrating multiple features, such as average spectral reflectance (ASR), vegetation index, and textures, obtained through an unmanned aerial vehicle (UAV). The study employed the partial least squares method (PLS), extreme learning machine (ELM), random forest (RF), and support vector machine (SVM) to build the LAI estimation model under nitrogen stress. The findings of this study revealed the following: (i) texture features generally exhibited greater sensitivity to LAI compared to ASR and VIs. (ii) Utilizing a multi-source feature fusion strategy enhanced the model’s accuracy in predicting LAI compared to using a single feature. The best RP2 and RMSEP of the estimated LAI were 0.78 and 0.49, respectively, achieved by RF through the combination of ASR, VIs, and textures. (iii) Among the four machine learning algorithms, RF and SVM displayed strong potential in estimating LAI of rice crops under nitrogen stress. The RP2 of the estimated LAI using ASR + VIs + texture, in descending order, were 0.78, 0.73, 0.67, and 0.62, attained by RF, SVM, PLS, and ELM, respectively. This study analyzed the spatial variation of LAI in rice using remote sensing techniques, providing a crucial theoretical foundation for crop management in the field.

Objective: The aim of this study was to compare the pharmacokinetics and steady-state serum concentrations of lenvatinib in adult and juvenile rats.Experimental study: An ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method was developed to quantify lenvatinib in the serum and liver of rats. Six juvenile and six adult rats in each group were orally administered with a single dose of 7.0 mg/kg lenvatinib suspension for pharmacokinetics. Another 12 juvenile and adult rats were subjected to oral gavage with 7.0 mg/kg lenvatinib once daily for 5 days. Biofluild samples were pre-treated by protein precipitation and sorafenib was used as the internal standard for UPLC-MS analysis. The pharmacokinetic parameters were estimated by compartment and statistical model. The mRNA expression of CYP3A2 and SLC22A1 in liver of adult and juvenile rats was measured by real-time fluorescence quantitative PCR (RT-qPCR).Results: The UPLC-MS method met the requirements for quantitative analysis of lenvatinib in serum and liver. The pharmacokinetic results showed that the mean retention time (MRT(0-∞)) was 19.64 ± 7.64 h and 126.38 ± 130.18 h, with AUC(0-∞) values of 3.97 ± 0.73 μg‧mL-1 h and 5.95 ± 2.27 μg mL-1 h in adult and juvenile rats, respectively. When comparing adult rats (0.35 ± 0.15 μg/mL) to juvenile rats, no significant differences were observed in steady-state serum lenvatinib (0.32 ± 0.11 μg/mL), but a noteworthy decrease to one-third of steady-state liver lenvatinib was observed after multiple oral doses of lenvatinib in juvenile rats. Additional findings revealed that the mRNA expression of CYP3A2 and SLC22A1 was notably increased by 6.86 and 14.67 times, respectively, in juvenile rats compared to adult rats.Conclusion: Juvenile rats exhibit lower levels of lenvatinib in the liver’s steady-state, potentially due to the disparity in CYP3A2 mRNA expression. These results imply that the dosage of lenvatinib for pediatric patients may need to be augmented in order to attain the desired clinical outcome.

Abstract Background Lung cancer is among the major diseases threatening human health. Although the immune response plays an important role in tumor development, its exact mechanisms are unclear. Materials and methods Here, we used CIBERSORT and ESTIMATE algorithms to determine the proportion of tumor-infiltrating immune cells (TICs) as well as the number of immune and mesenchymal components from the data of 474 lung cancer patients from the Gene Expression Omnibus database. And we used data from The Cancer Genome Atlas database (TCGA) for validation. Results We observed that immune, stromal, and assessment scores were only somewhat related to survival with no statistically significant differences. Further investigations revealed these scores to be associated with different pathology types. GO and KEGG analyses of differentially expressed genes revealed that they were strongly associated with immunity in lung cancer. In order to determine whether the signaling pathways identified by GO and KEGG signaling pathway enrichment analyses were up- or down-regulated, we performed a gene set enrichment analysis using the entire matrix of differentially expressed genes. We found that signaling pathways involved in hallmark allograft rejection, hallmark apical junction, hallmark interferon gamma response, the hallmark P53 pathway, and the hallmark TNF-α signaling via NF-ĸB were up-regulated in the high-ESTIMATE-score group. CIBERSORT analysis for the proportion of TICs revealed that different immune cells were positively correlated with the ESTIMATE score. Cox regression analysis of the differentially expressed genes revealed that CPA3, C15orf48, FCGR1B, and GNG4 were associated with patient prognosis. A prognostic model was constructed wherein patients with high-risk scores had a worse prognosis (p

Background and objective Lung cancer is the leading cause of cancer-related death, of which non-small cell lung cancer (NSCLC) is the most common type. Immune checkpoint inhibitors (ICIs) have now become one of the main treatments for advanced NSCLC. This paper retrospectively investigated the effect of peripheral blood inflammatory indexes on the efficacy of immunotherapy and survival of patients with advanced non-small cell lung cancer, in order to find strategies to guide immunotherapy in NSCLC. Methods Patients with advanced non-small cell lung cancer who were hospitalized in The Affiliated Cancer Hospital of Nanjing Medical University from October 2018 to August 2019 were selected to receive anti-PD-1 (pembrolizumab, sintilimab or toripalimab) monotherapy or combination regimens. And were followed up until 10 December 2020, and the efficacy was evaluated according to RECIST1.1 criteria. Progression-free survival (PFS) and overall survival (OS) were followed up for survival analysis. A clinical prediction model was constructed to analyze the predictive value of neutrophil-to-lymphocyte ratio (NLR) based on NLR data at three different time points: before treatment, 6 weeks after treatment and 12 weeks after treatment (0w, 6w and 12w), and the accuracy of the model was verified. Results 173 patients were finally included, all of whom received the above treatment regimen, were followed up for a median of 19.7 months. The objective response rate (ORR) was 27.7% (48/173), the disease control rate (DCR) was 89.6% (155/173), the median PFS was 8.3 months (7.491-9.109) and the median OS was 15.5 months (14.087-16.913). The chi-square test and logistic multi-factor analysis showed that NLR6w was associated with ORR and NLR12w was associated with ORR and DCR. Further Cox regression analysis showed that NLR6w and NLR12w affected PFS and NLR0w, NLR6w and NLR12w were associated with OS. Conclusion In patients with advanced non-small cell lung cancer, NLR values at different time points are valid predictors of response to immunotherapy, and NLR

BackgroundHepatocellular carcinoma (HCC) is the most common pathological type of primary liver cancer. The lack of prognosis indicators is one of the challenges in HCC. In this study, we investigated the combination of tertiary lymphoid structure (TLS) and several systemic inflammation parameters as a prognosis indicator for HCC.Materials and MethodsWe retrospectively recruited 126 postoperative patients with primary HCC. The paraffin section was collected for TLS density assessment. In addition, we collected the systemic inflammation parameters from peripheral blood samples. We evaluated the prognostic values of those parameters on overall survival (OS) using Kaplan-Meier curves, univariate and multivariate Cox regression. Last, we plotted a nomogram to predict the survival of HCC patients.ResultsWe first found TLS density was positively correlated with HCC patients’ survival (HR=0.16, 95% CI: 0.06 − 0.39, p < 0.0001), but the power of TLS density for survival prediction was found to be limited (AUC=0.776, 95% CI:0.772 − 0.806). Thus, we further introduced several systemic inflammation parameters for survival analysis, we found neutrophil-to-lymphocyte ratio (NLR) was positively associated with OS in univariate Cox regression analysis. However, the combination of TLS density and NLR better predicts patient’s survival (AUC=0.800, 95% CI: 0.698-0.902, p < 0.001) compared with using any single indicator alone. Last, we incorporated TLS density, NLR, and other parameters into the nomogram to provide a reproducible approach for survival prediction in HCC clinical practice.ConclusionThe combination of TLS density and NLR was shown to be a good predictor of HCC patient survival. It also provides a novel direction for the evaluation of immunotherapies in HCC.

Objective: Serum uric acid is associated with tumor progression and hepatocarcinogenesis. Here, we aimed to determine whether serum uric acid is related to the survival time of patients with hepatocellular carcinoma (HCC) and whether the inhibition of uric acid production affects the progression and survival of rats with HCC.Methods: The follow-up data of 288 patients with advanced HCC were analyzed. Ten purine metabolites in serum and liver samples of diethylnitrosamine (DEN)-induced HCC rats were quantitatively determined by an established UPLC-MS/MS method. On this basis, febuxostat, a specific inhibitor of xanthine oxidase (XOD), was used to interfere with HCC rats.Results: The serum uric acid level of HCC patients was significantly negatively correlated with survival days (r = -0.155). The median survival time was 133.5 days in the high uric acid group (>360 μmol/L, n = 80) and 176.0 days in the normal serum uric acid group (

BackgroundPD-1 inhibitors have been routinely used in the treatment of advanced non-small cell lung cancer (NSCLC), and have demonstrated to significantly improve survivorship when combining with other conventional therapies, such as chemotherapy and anti-angiogenesis therapy. PD-L1 is the most commonly used biomarker to select benefiting groups, while not all patients with high PD-L1 expression benefit from immunotherapy. Therefore, identifying other prognostic and predictive biomarkers, including peripheral blood indexes, is essential.MethodsWe retrospectively collected medical records and hematological data of 151 patients with advanced NSCLC treated with PD-1 inhibitor-based combination therapy in our hospital. The peripheral blood indexes of interest were NLR, PLR, PAR, Hb, LDH, CEA, and NSE. The association between peripheral blood indexes and treatment responses or survival outcomes was examined by multivariable logistic regression and Cox regression, respectively.ResultsThe decreased CEA at week 6 (OR = 4.209, 95%CI: 1.287-13.758) or 12 (OR = 7.267, 95%CI: 1.508-35.006) post-treatment was related to a higher disease control rate. The decrease or NLR at week 6 (OR = 3.081, 95%CI: 1.464-6.483) or 12 (OR = 3.304, 95%CI: 1.560-7.001) post-treatment, or CEA at week 12 post-treatment (OR = 2.469, 95%CI: 1.134-5.375), was associated with a higher objective response rate. Patients whose NLR (HR = 0.610, 95%CI: 0.411-0.907) or CEA (HR = 0.477, 95%CI: 0.320-0.710) decreased at week 6 post-treatment tended to have longer progression-free survival, and similar results were found in those with decreased NLR (HR = 0.587, 95%CI: 0.388-0.886) or CEA (HR = 0.406, 95%CI: 0.270-0.609) at week 12 post-treatment. Patients whose CEA (HR = 0.543, 95%CI: 0.339-0.871) or NSE (HR = 0.619, 95%CI: 0.386-0.994) decreased after 6 weeks post-treatment appeared to have longer overall survival, and the same was found for those whoseCEA (HR = 0.620, 95%CI: 0.390-0.986) or NSE (HR = 0.578, 95%CI: 0.353-0.947) was decreased at 12 weeks after treatment.ConclusionPost-treatment NLR, CEA and NSE changes are suggestive indicators for the prognosis of NSCLC patients after immunotherapy.

Rapid and accurate discrimination of Chrysanthemum varieties is very important for producers, consumers and market regulators. The feasibility of using hyperspectral imaging combined with deep convolutional neural network (DCNN) algorithm to identify Chrysanthemum varieties was studied in this paper. Hyperspectral images in the spectral range of 874⁻1734 nm were collected for 11,038 samples of seven varieties. Principal component analysis (PCA) was introduced for qualitative analysis. Score images of the first five PCs were used to explore the differences between different varieties. Second derivative (2nd derivative) method was employed to select optimal wavelengths. Support vector machine (SVM), logistic regression (LR), and DCNN were used to construct discriminant models using full wavelengths and optimal wavelengths. The results showed that all models based on full wavelengths achieved better performance than those based on optimal wavelengths. DCNN based on full wavelengths obtained the best results with an accuracy close to 100% on both training set and testing set. This optimal model was utilized to visualize the classification results. The overall results indicated that hyperspectral imaging combined with DCNN was a very powerful tool for rapid and accurate discrimination of Chrysanthemum varieties. The proposed method exhibited important potential for developing an online Chrysanthemum evaluation system.

Importance: Ovine pulmonary adenomatosis (OPA) and maedi-visna disease (MVD) are chronic and progressive infectious diseases in sheep caused by Jaagsiekte sheep retrovirus (JSRV) and maedi-visna virus (MVV), respectively. Objective: To investigate the pathological changes and conduct viral gene analysis of OPA and MVD co-occurrence in Inner Mongolia, China. Methods: Using gross pathology, histopathology, immunohistochemistry, ultrastructural pathology, PCR, and sequence analysis, we investigated the concurrent infection of JSRV and MVV in 319 Dorper rams slaughtered in a private slaughterhouse in Inner Mongolia, in 2022. Results: Of the 319 rams included, 3 showed concurrent JSRV and MVV infection. Gross lung pathology showed diffuse enlargement, consolidation, and greyish-white miliary nodules on the lung surface; the trachea was filled with a white foamy fluid; hilar and mediastinal lymph nodes were significantly enlarged. Histopathology results revealed typical OPA and MVD lesions in the lung tissue. Immunohistochemical results were positive for JSRV envelope protein (Env) in the tumor cells and MVV CA in alveolar macrophages. Transmission electron microscopy showed several virions and autophagosomes in the lung tissue, severely damaged mitochondria, and the induced mitophagy. Nucleotide sequences obtained for JSRV env and MVV gag showed the highest homology with the Inner Mongolian strains of JSRV env (JQ837489) and MVV gag (MW248464). Conclusions and Relevance: Our study confirmed that OPA and MVD co-occurrence and identified the pathological changes in Inner Mongolia, China, thereby providing references for the identification of concurrent JSRV and MVV infections. [ABSTRACT FROM AUTHOR]

Abstract In our previous study, the three-dimensional graphene-modified PbO2 (3DG-PbO2) anode was prepared for the effective degradation of perfluorooctanesulfonat (PFOS) by the electrochemical oxidation process. However, the mineralization efficiency of PFOS at the 3DG-PbO2 anode still needs to be further improved due to the recalcitrance of PFOS. Thus, in this study, the yttrium (Y) was doped into the 3DG-PbO2 film to further improve the electrochemical activity of the PbO2 anode. To optimize the doping amount of Y, three Y and 3DG codoped PbO2 anodes were fabricated with different Y3+ concentrations of 5, 15, and 30 mM in the electroplating solution, which were named Y/3DG-PbO2-5, Y/3DG-PbO2-15 and Y/3DG-PbO2-30, respectively. The results of morphological, structural, and electrochemical characterization revealed that doping Y into the 3DG-PbO2 anode further refined the β-PbO2 crystals, increased the oxygen evolution overpotential and active sites, and reduced the electron transfer resistance, resulting in a superior electrocatalytic activity. Among all the prepared anodes, the Y/3DG-PbO2-15 anode exhibited the best activity for electrochemical oxidation of PFOS. After 120 min of electrolysis, the TOC removal efficiency was 80.89% with Y/3DG-PbO2-15 anode, greatly higher than 69.13% with 3DG-PbO2 anode. In addition, the effect of operating parameters on PFOS removal was analyzed by response surface, and the obtained optimum values of current density, initial PFOS concentration, pH, and Na2SO4 concentration were 50 mA/cm2, 12.21 mg/L, 5.39, and 0.01 M, respectively. Under the optimal conditions, the PFOS removal efficiency reached up to 97.16% after 40 min of electrolysis. The results of the present study confirmed that the Y/3DG-PbO2 was a promising anode for electrocatalytic oxidation of persistent organic pollutants.