Background: Patients with diabetic hindfoot ulcers typically harbor significant concerns regarding their prospects for healing or the potential for major amputation. Nonetheless, a scarcity of data addressing this prevalent and critical query exists. Thus, the aim of this study was to create an initial risk-scoring system to forecast the prognosis of individuals with diabetic hindfoot ulcers, leveraging assessments of ischemia and infection severity, which are recognized as the principal risk factors for amputation. Methods: Ischemia severity was categorized as iS0, iS1, or iS2 based on transcutaneous partial oxygen tension values, while infection severity was classified as iN0, iN1, or iN2 according to the results of tissue and bone biopsy cultures. Risk scores were determined by summing the scores for ischemia and infection severity, yielding a range of 0 to 4. Wound healing outcomes were graded as either healed with or without major amputation. Wound healing outcomes were assessed based on the assigned risk scores. Results: With ascending risk scores, the proportion of patients subjected to major amputation also increased (P value for trend < 0.001). Univariable logistic regression analysis revealed a significant positive correlation between escalating risk scores and major amputation incidence. Patients with a risk score of 4 exhibited a 41-fold higher likelihood of undergoing major amputation compared to those with a risk score of 0. Conclusion Risk scores can serve as a reliable predictor of the major amputation rate in patients with diabetic hindfoot ulcers.

Background: Patients with diabetic hindfoot ulcers typically harbor significant concerns regarding their prospects for healing or the potential for major amputation. Nonetheless, a scarcity of data addressing this prevalent and critical query exists. Thus, the aim of this study was to create an initial risk-scoring system to forecast the prognosis of individuals with diabetic hindfoot ulcers, leveraging assessments of ischemia and infection severity, which are recognized as the principal risk factors for amputation. Methods: Ischemia severity was categorized as iS0, iS1, or iS2 based on transcutaneous partial oxygen tension values, while infection severity was classified as iN0, iN1, or iN2 according to the results of tissue and bone biopsy cultures. Risk scores were determined by summing the scores for ischemia and infection severity, yielding a range of 0 to 4. Wound healing outcomes were graded as either healed with or without major amputation. Wound healing outcomes were assessed based on the assigned risk scores. Results: With ascending risk scores, the proportion of patients subjected to major amputation also increased (P value for trend < 0.001). Univariable logistic regression analysis revealed a significant positive correlation between escalating risk scores and major amputation incidence. Patients with a risk score of 4 exhibited a 41-fold higher likelihood of undergoing major amputation compared to those with a risk score of 0. Conclusion Risk scores can serve as a reliable predictor of the major amputation rate in patients with diabetic hindfoot ulcers.

Background: Patients with diabetic hindfoot ulcers typically harbor significant concerns regarding their prospects for healing or the potential for major amputation. Nonetheless, a scarcity of data addressing this prevalent and critical query exists. Thus, the aim of this study was to create an initial risk-scoring system to forecast the prognosis of individuals with diabetic hindfoot ulcers, leveraging assessments of ischemia and infection severity, which are recognized as the principal risk factors for amputation. Methods: Ischemia severity was categorized as iS0, iS1, or iS2 based on transcutaneous partial oxygen tension values, while infection severity was classified as iN0, iN1, or iN2 according to the results of tissue and bone biopsy cultures. Risk scores were determined by summing the scores for ischemia and infection severity, yielding a range of 0 to 4. Wound healing outcomes were graded as either healed with or without major amputation. Wound healing outcomes were assessed based on the assigned risk scores. Results: With ascending risk scores, the proportion of patients subjected to major amputation also increased (P value for trend < 0.001). Univariable logistic regression analysis revealed a significant positive correlation between escalating risk scores and major amputation incidence. Patients with a risk score of 4 exhibited a 41-fold higher likelihood of undergoing major amputation compared to those with a risk score of 0. Conclusion Risk scores can serve as a reliable predictor of the major amputation rate in patients with diabetic hindfoot ulcers.

Background: Patients with diabetic hindfoot ulcers typically harbor significant concerns regarding their prospects for healing or the potential for major amputation. Nonetheless, a scarcity of data addressing this prevalent and critical query exists. Thus, the aim of this study was to create an initial risk-scoring system to forecast the prognosis of individuals with diabetic hindfoot ulcers, leveraging assessments of ischemia and infection severity, which are recognized as the principal risk factors for amputation. Methods: Ischemia severity was categorized as iS0, iS1, or iS2 based on transcutaneous partial oxygen tension values, while infection severity was classified as iN0, iN1, or iN2 according to the results of tissue and bone biopsy cultures. Risk scores were determined by summing the scores for ischemia and infection severity, yielding a range of 0 to 4. Wound healing outcomes were graded as either healed with or without major amputation. Wound healing outcomes were assessed based on the assigned risk scores. Results: With ascending risk scores, the proportion of patients subjected to major amputation also increased (P value for trend < 0.001). Univariable logistic regression analysis revealed a significant positive correlation between escalating risk scores and major amputation incidence. Patients with a risk score of 4 exhibited a 41-fold higher likelihood of undergoing major amputation compared to those with a risk score of 0. Conclusion Risk scores can serve as a reliable predictor of the major amputation rate in patients with diabetic hindfoot ulcers.

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.