Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: By utilizing both protein and mRNA expression patterns, we can identify more detailed and diverse immune cells, providing insights into understanding the complex immune landscape in cancer ecosystems. Materials and Methods: This study was performed by obtaining publicly available Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) data of peripheral blood mononuclear cells (PBMCs) from the Gene Expression Omnibus database. A total of 94674 total cells were analyzed, of which 32412 were T cells. There were 228 protein features and 16262 mRNA features in the data.The Seurat package was used for quality control and preprocessing, principal component analysis was performed, and Uniform Manifold Approximation and Projection was used to visualize the clusters. Protein and mRNA levels in the CITE-seq were analyzed. Results: We observed that a subset of T cells in the clusters generated at the protein level divided better. By identifying mRNA markers that were highly correlated with the CD4 and CD8 proteins and cross-validating CD26 and CD99 markers using flow cytometry, we found that CD4 + and CD8+ T cells were better discriminated in PBMCs. Weighted Nearest Neighbor clustering results identified a previously unobserved T cell subset. Conclusion In this study, we used CITE-seq data to confirm that protein expression patterns could be used to identify cells more precisely. These findings will improve our understanding of the heterogeneity of immune cells in the future and provide valuable insights into the complexity of the immune response in health and disease.

Purpose: Evidence on factors influencing the variations of music’s effect on anxiety and pain in surgical patients is unclear. We aimed to elucidate the effects of music intervention on anxiety and pain throughstudy characteristics. Methods: We conducted a search on the PubMed, CINAHL, Embase, Cochrane, and Web of Science databases from March 7 to April 21, 2022, for randomized controlled trials (RCTs) for the effect of music intervention on anxiety, pain, and physiological responses in surgical patients. We included studies published within the last 10 years. We assessed the risk of bias in the study using the Cochrane risk of bias tool for randomized trials and performed meta-analyses using a random-effects model for all outcomes. We used change-from-baseline scores as summary statistics and computed bias-corrected standardized mean differences (Hedges'g) for anxiety and pain outcomes and mean differences (MD) for blood pressure and heart rate. Results: Of the 454 records retrieved, 30 RCTs involving 2280 participants were found to be eligible. Music intervention was found to be superior to standard care in reducing anxiety (Hedges' g = −1.48, 95% confidence interval: −1.97 to −0.98), pain (Hedges's g = −0.67, −1.11 to −0.23), systolic blood pressure (MD = −4.62, −7.38 to −1.86), and heart rate (MD = −3.37, −6.65 to −0.10) in surgical patients. The impact of music on anxiety and pain relief varied significantly depending on the duration of the intervention. The largest effect was observed in interventions lasting between 30 and 60 minutes, with a decrease in anxiety and pain. Conclusions Music intervention is an effective way to reduce anxiety, pain, and physiological responses in surgical patients. Future reviews examining the influence of different types of surgery on the effects of music would add to the body of knowledge in this field. This study has been registered on the International Prospective Register of Systematic Reviews (PROSPERO) under the number CRD42022340203, with a registration date of July 4, 2022.

INTRODUCTION: Three doses of SARS-CoV-2 mRNA vaccines have been recommended for cancer patients to reduce the risk of severe disease. Anti-neoplastic treatment, such as chemotherapy, may affect long-term vaccine immunogenicity. METHOD: Patients with solid or haematological cancer were recruited from 2 hospitals between July 2021 and March 2022. Humoral response was evaluated using GenScript cPASS surrogate virus neutralisation assays. Clinical outcomes were obtained from medical records and national mandatory-reporting databases. RESULTS: A total of 273 patients were recruited, with 40 having haematological malignancies and the rest solid tumours. Among the participants, 204 (74.7%) were receiving active cancer therapy, including 98 (35.9%) undergoing systemic chemotherapy and the rest targeted therapy or immunotherapy. All patients were seronegative at baseline. Seroconversion rates after receiving 1, 2 and 3 doses of SARS-CoV-2 mRNA vaccination were 35.2%, 79.4% and 92.4%, respectively. After 3 doses, patients on active treatment for haematological malignancies had lower antibodies (57.3%±46.2) when compared to patients on immunotherapy (94.1%±9.56, P<0.05) and chemotherapy (92.8%±18.1, P<0.05). SARS-CoV-2 infection was reported in 77 (28.2%) patients, of which 18 were severe. No patient receiving a third dose within 90 days of the second dose experienced severe infection. CONCLUSION This study demonstrates the benefit of early administration of the third dose among cancer patients.
Humans ; SARS-CoV-2 ; COVID-19/prevention & control* ; Treatment Outcome ; Neoplasms/drug therapy* ; Hematologic Neoplasms ; Vaccination ; RNA, Messenger ; Antibodies, Viral ; Immunogenicity, Vaccine

Aims: This study was designed to examine the enzyme activity of selected virulent isolates of Ganoderma boninense against oil palm. In a separate in vitro assessment, the effect of macronutrients on the mycelial growth of four selected Ganoderma spp. was also tested. Methodology and results: The study involved a comparison of ligninolytic enzymes; lignin peroxidase (LiP), manganese peroxidase (MnP) and laccase (Lac) profiling of eight isolates of G. boninense, categorized into three levels of aggressiveness, with two control isolates (G. boninense PER71 and G. tornatum NPG1) using solid-state fermentation (SSF). The Principal Component Analysis (PCA) revealed that the isolates had a significant production of ligninolytic enzymes on day 80. The most aggressive isolate, ET61 had the highest Lac production. As for the macronutrient test, mycelial growth for all the Ganoderma spp. was highly affected by potassium (K). Conclusion, significance and impact of study The findings of this study elucidated the characteristics of G. boninense in relation to enzyme production for the degradation of oil palm lignin and the identification of essential nutrients involved in the survival and growth of Ganoderma spp. The study provides vital information on the pathogenic characteristics of G. boninense isolates involved in biomass degradation along with the role of nutrient on the growth of Ganoderma spp. that may influence basal stem rot (BSR) management in the field.
Enzymes ; Ganoderma ; Palm Oil

Background: Microvascular ultrasonography (MVUS) is a third-generation Doppler technique that was developed to increase sensitivity compared to conventional Doppler. The purpose of this study was to compare MVUS with conventional color Doppler (CD) and power Doppler (PD) imaging to distinguish Graves’ disease (GD) from destructive thyroiditis (DT). Methods: This prospective study included 101 subjects (46 GDs, 47 DTs, and eight normal controls) from October 2020 to November 2021. All ultrasonography examinations were performed using microvascular flow technology (MV-Flow). The CD, PD, and MVUS images were semi-quantitatively graded according to blood flow patterns. On the MVUS images, vascularity indices (VIs), which were the ratio (%) of color pixels in the total grayscale pixels in a defined region of interest, were obtained automatically. Receiver operating characteristic curve analysis was performed to verify the diagnostic performance of MVUS. The interclass correlation coefficient and Cohen’s kappa analysis were used to analyze the reliability of MVUS (ClinicalTrials.gov:NCT04879173). Results: The area under the curve (AUC) for CD, PD, MVUS, and MVUS-VI was 0.822, 0.844, 0.808, and 0.852 respectively. The optimal cutoff value of the MVUS-VI was 24.95% for distinguishing GD and DT with 87% sensitivity and 80.9% specificity. We found a significant positive correlation of MVUS-VI with thyrotropin receptor antibody (r=0.554) and with thyroid stimulating immunoglobulin bioassay (r=0.841). MVUS showed high intra- and inter-observer reliability from various statistical method. Conclusion In a real time and quantitative manner, MVUS-VI could be helpful to differentiate GD from thyroiditis in thyrotoxic patients, with less inter-observer variability.