CLEC11A, PRAME, AZU1, NREP, ARMH1, C1QBP, TRH), which we validate on independent datasets. The analysis reveals distinct clusters of Dx relapse- and continuous complete remission (CCR)-associated AML-blasts with differential expression of genes associated with survival. At Dx, relapse-associated samples have more exhausted T cells while CCR-associated samples have more inflammatory M1 macrophages. Post-therapy EOI residual blasts overexpress fatty acid oxidation, tumor growth, and stemness genes. Also, a post-therapy T-cell cluster associated with relapse samples exhibits downregulation of MHC Class I and T-cell regulatory genes. Altogether, this study deeply characterizes pediatric AML relapse- and CCR-associated samples to provide insights into the BM microenvironment landscape.Acute myeloid leukemia (AML) microenvironment exhibits cellular and molecular differences among various subtypes. Here, we utilize single-cell RNA sequencing (scRNA-seq) to analyze pediatric AML bone marrow (BM) samples from diagnosis (Dx), end of induction (EOI), and relapse timepoints. Analysis of Dx, EOI scRNA-seq, and TARGET AML RNA-seq datasets reveals an AML blasts-associated 7-gene signature ( Single-cell RNA-seq could help identify acute myeloid leukaemia (AML) patients at high risk of relapse after therapy. Here, the authors use single-cell RNA-seq from paediatric AML samples to construct a 7-gene signature that can identify malignant cells at diagnosis, which are distinctly associated with relapse or complete remission. Improvements in outcomes for children with AML, attributed to intensification of frontline therapy, hematopoietic stem cell (HSC) transplant, and better supportive care, have not kept pace with those for children with acute lymphoblastic leukemia (ALL). The prognosis and treatment of pediatric AML remain challenging because of disease heterogeneity, high relapse rates, and therapy-associated toxicity2. While measurable/minimal residual disease (MRD) status is critical for post-therapy patient stratification and clinical assessment, it is not infallible, with relapse occurring even after intense end of consolidation therapy. This may be partly due to inefficient determination of MRD positivity using current diagnostic techniques including bulk gene expression analysis and imaging. It is important to identify risk stratification strategies that can be used to better guide therapy decisions and improve clinical outcomes for pediatric AML patients. Deeper characterization of the disease is essential to overcome the above-mentioned limitations in AML prognosis and post-treatment assessment of response to therapy.Acute myeloid leukemia (AML) accounts for about 20% of childhood leukemia3. Molecular characterization of the bone marrow (BM) tumor microenvironment (TME) along with the identification of biomarkers/targets that distinguish AML blast cells (AML-blasts) from non-blast cells are critical for defining malignant cells clusters and/or changes in the transcriptional landscape. The cellular composition of the TME and the transcriptional states thereof may contribute to and be affected by the leukemic process at the time of diagnosis (Dx) and the presence of residual blast cells at the end of induction (EOI) chemotherapy. Recent studies using single-cell RNA sequencing (scRNA-seq) assays have revealed the molecular diversity in blast and non-blast cells in AML patients8. These studies underline the critical role of scRNA-seq analysis for revealing cellular and molecular changes in BM microenvironment as well as in peripheral sites of AML patients.The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) AML initiative and other large-scale genetic profiling studies have revealed that pediatric AML is a genetically diverse disease having various gene mutations, insertions, and fusions associated with poor prognosisIn this work, we perform comparative single-cell transcriptome analysis of baseline Dx as well as post-therapy EOI samples critical for characterizing the role of TME determinants in pediatric AML relapse or continuous complete remission (CCR). Utilizing integrated scRNA-seq data analysis of paired Dx, EOI samples as well as bulk RNA sequencing dataset 1 of TARGET AML initiative (TARGET AML-1), we identify a 7-gene signature that distinguishes AML-blasts from non-transformed cells. Next, we validate the ability of the 7-gene signature to distinguish AML blasts and non-blast cells in AML samples, i.e., to identify AML-blasts and non-blasts in independent AML BM aspirate samples. Further analysis of AML Dx samples reveals specific transcriptomic differences between relapse- and CCR-associated AML-blasts. Furthermore, distinct baseline characteristics of innate and adaptive immune cells at Dx correlate with either CCR (monocytes/macrophages augmentation) or relapse (exhausted T cells augmentation). We also identify post-therapy residual blasts in EOI samples and clinical outcome-associated differences in immune cells. With the identification of specific cell types and incidental genes and pathways at both Dx and EOI, associated with pediatric AML relapse/CCR, this study opens avenues for the development of better diagnostic and therapeutic targets in pediatric AML.Frozen BM samples obtained from the Children’s Healthcare of Atlanta (CHOA) pediatric biorepository were viably thawed and processed using 10x Genomics platform for single-cell profiling. A total of 31 BM samples were processed from 20 patients   , B cells , monocytes , macrophages , monocytes/macrophages , plasmacytoid dendritic cells , pre-B/plasma cells  and neutrophils (CD63+)  and/or multiple lineage genes  . After preprocessing, alignment, and quality control steps including removal of low-quality reads and cells, the remaining 19,350 cells were analyzed using unsupervised and supervised approaches. The unsupervised analysis of preprocessed and normalized scRNA-seq data using the Uniform Manifold Approximation and Projection (UMAP) approachers Fig. . Eleven ers Fig. . The remU+) Fig. . The dif3+) Fig. . The thrc.) Fig. . The splc.) Fig. . In summMPO+, CD34+, AZU+) and EOI enriched non-blast cell clusters from Dx and EOI time-points, respectively . To further refine the gene list, we performed external analysis using the TARGET AML bulk transcriptome dataset 1 (TARGET AML-1)3 that contains Dx BM samples with different proportions of blast cells and post-treatment EOI BM samples. The TARGET AML-1 Dx samples were partitioned into 3 bins based on the extent of disease burden  to determine the blast percentage associated expression patterns of the identified 232 scRNA-seq data blast-related genes. 44 genes were significantly overexpressed in high blasts samples (>60%) compared to EOI samples (FC > 1.8 and P < 0.03) as well as low blasts (<30%) samples (FC > 1.8 and P < 0.04) 12, growth factor for progenitor hematopoietic cells (CLEC11A)13, cell proliferation (CAPRIN1)14, and PPARα-induced proliferation and tumor growth (FABP5)15. Feature plots of two of the identified blast-associated genes (NREP and CLEC11A) displayed high expression in the three blast clusters identified in the paired Dx, EOI samples   that discriminated AML-associated blast cells from non-blast cells with an AUC of 0.968  were used to develop an AML-blast-specific gene signature. Differential expression of genes (DEG) analysis using Wilcoxon rank test, performed between the Dx enriched AML-blast cell clusters  and cluster 5 (AZU1+) displaying positive module scores  to be predominant in Dx  and Rel  samples, and minimally represented in EOI  samples . The clusters were annotated using top genes for AML-blasts , canonical immune and stromal cell marker genes, and Single R automatic labels  to be made up of mostly cells from AML samples  based on the 7-gene signature demonstrated significantly higher expression in the AML-blasts compared to non-blast cells as well as to healthy BM and normal HSC samples  of the 7-gene signature module score was observed in the AML-blast cell clusters as compared to the CMP cells from the normal HSCs , a healthy BM scRNA-seq dataset from young adultsels Fig. . The splles Fig. . In addi22 (v2.20) and established canonical immune and stromal cells markers  was used to identify blast cells and normal BM cells. Clusters 4, 10, 11, 13–16, 18, 20, and 21 were labeled as AML blast clusters based on the following factors: (i) substantial proportion cells in the clusters from AML samples . The split UMAP of paired Dx, EOI samples revealed Dx enriched clusters , which are reduced drastically in post-therapy EOI samples  were included in our correlation analysis. We observed a significant association between the Z-score enrichment value for the 7-gene signature and the BM blast percentage . The significant association of the 7-gene signature expression with clinically reported blast cells percentages further validates the AML-blasts specificity of the signature. Some of the individual genes in the 7-gene signature  also exhibited significant associations with BM blast percentage . The development and validation process of the 7-gene AML-blast signature is summarized in the flow chart presented in Supplementary Fig. Finally, we also validated the association between AML-blast cells and the 7-gene signature by evaluating their expression in an independent TARGET AML dataset 2 (TARGET AML-2), which contains both AML and normal BM samples  analysis of the cells from the blast clusters  using the InferCNV tool25. Comparison of cells from blast clusters to cells from healthy BM and normal HSCs revealed CNAs (amplifications and deletions) in the blast clusters /del(7q) displayed gain and loss of chromosome 7, AZU1+ blasts from patients 3 and 5 displayed deletions in chromosome 15. Chromosome 15 is known to be associated with myeloid malignancies. AZU1+ blasts displayed amplifications in chromosome 19 which is the chromosomal location of the AZU1 gene   and 8 with CCR (7D–14D)  and RFLNB/FAM101B  genes overexpressed in relapse-associated cell clusters were significantly associated with poor OS   and TRH (controls the secretion of thyroid-stimulating hormone) were associated with significantly better OS   and shorter EFS (log-rank P = 0.00094)  of multiple pathways including “RhoGDI signaling”, “eNOS signaling”, “Androgen Signaling”, and “Protein Kinase A signaling”  clustered next to each other and relapse-associated blast clusters  clustered together (except cluster 9) suggesting more similarity in transcriptome between the blast cells from similar clinical outcome i.e., relapse or CCR Fig. . Distinc01B Fig. . Decreasng” Fig. . These rng” Fig. . Furtherng” Fig. . Signifing” Fig. .Fig. 3AMP < 0.05) in the blasts of samples split into groups based on mutations or chromosomal alterations. Three of the Dx relapse-associated samples in this study had MLL rearrangements. MLL (KMT2A) rearrangement is one of the most common recurrent cytogenetic aberrations in pediatric AML30. We observed increased expression of a specific set of genes in MLL rearrangement patients including GRK2, KCNE5, AZU1, TRPM4, and C4orf48. G protein-coupled receptor kinase 2 (GRK2) has been shown to associate with HSP90 in AML cells31. GRK2/HDAC6 mediates tubulin acetylation regulation that promotes aberrant cellular adhesion, motility, and transformation31. Daunorubicin resistance has been reported to be induced by miRNA-125 by decreasing GRK232. C4orf48 is a protein secreting gene that has not yet been associated with AML. It is a neuropeptide that has been suggested to play a role in the differentiation of cells33. Dysregulation of myeloid differentiation associated AZU1 has been reported in t AML34. Transient Receptor Potential cation channel subfamily M member 4 (TRPM4) gene codes for a calcium-activated ion channel has been shown to be overexpressed in MLL-rearranged AML and therapeutic blockade suggested as an alternative approach to treat patients with high TRPM435. The RUNX+  RUNX1-RUNX1T1) patients  achieved CCR outcome. These RUNX+ patients displayed overexpression of a specific set of genes as well as genes expressed in other AML genetic subtypes. Overexpressed genes in the RUNX+ patient’s Dx blast cells included IFITM1, IFITM3, TRH, MPO, TUBB, and CD74. While interferon-inducible transmembrane proteins member, IFITM3, has been reported to be associated with adverse AML prognosis in adults when only chemotherapy is given36, it may have a different role in pediatric AML-blasts. CD74 reported to be expressed in AML, plays a critical role in MHC class II processing37. CD74 is also a transcriptional regulator controlling immune regulation pathways38 as well as HSC maintenance39. Other highly expressed genes like MPO and TRH were shown to be associated with better OS in this study  is associated with tumor cell migration, colony formation, and resistance to apoptosis41. Of the two 7q (7/add(7q)/del(7q) cases in this study, one was relapse-associated (patient 6) and the other remission-associated (patient 16). A distinct set of genes were overexpressed in these two 7q(del/add) cases with relapse patient overexpressing genes like IFITM1, IFI6, and ALDOA while CCR patient overexpressed SNHG29, FTH1, and IFITM3 genes. Along with subtype-specific gene overexpression, we observed that many genes  were overexpressed in multiple subtypes . Supplementary Fig. udy Fig. . One pat23 revealed patient-specific CNAs. Amplifications and deletions were observed in many chromosomes with prominent CNAs in chromosomes 1, 4, 6, 11, 13, 14, 16, 19, and 21 in AML-blast cells. To demonstrate the location of cells with CNAs on a UMAP in relation to the blast and T-cells from each patient, we generated a feature plot with the CNA chromosome count metric (excluding chromosome 6) and a UMAP with patient blast and T-cell locations . A large study on 466 pediatric AML samples depicted CNAs to be associated with survival in standard-risk group. Additional studies with larger patient cohorts are needed to determine role of CNAs in pediatric AML as well as post-therapy clinical outcomes.CNA analysis of Dx AML-blast cells and normal T cells compared to healthy BM/normal HSCs  subclusters 2, 4, and 7 have significant expression of cytotoxic T cell marker   in relapse-associated samples compared to CCR-associated samples  were observed in the CCR-associated T cell subsets , ubiquitin gene; UBC associated with cell differentiation and certain immune cell functions49, inflammation associated and mitogen inducible gene, DUSP250. On the other hand, CCR-associated clusters showed higher expression of naive T cell marker genes , microtubule-associated gene; RPL4151, scaffold protein gene; ABLIM1  of multiple immune regulatory pathways including Th1 pathway, calcium-induced T lymphocyte apoptosis, and to a lesser extent, upregulation of T cell exhaustion pathway with downregulation of PD-1 and PD-L1 cancer immunotherapy pathways  , while cluster 6 expresses more premature genes   revealed that CCR-associated samples had significantly (P < 0.0001) more M1 macrophages compared to relapse-associated samples  identified three monocyte/macrophage cell clusters with differential proportions of samples from those with CCR and those with relapse Fig. . Clusterles Fig. . DEGs anmer Fig. . Systemsmer Fig. . The anamer Fig. . SAMHD1 les Fig. . To summHOPX, SELENOP/SEPP1, and FAM30A/C1orf11055. Survival analysis on these post-therapy residual tumor cells overexpressed genes in the TARGET AML-1 dataset showed significant association with poor OS as well as lower EFS  and one EOI sample (patient 15 whose Dx sample was not available). Dx and EOI samples integrated well with clusters 4, 6, and 8 enriched in Dx samples Fig. . FurtherP < 0.001) and significant M2 macrophages enrichment in relapse-associated EOI samples (P < 0.05)  higher enrichment in the relapse-associated EOI samples  from the above Dx, EOI dataset and re-clustered them to obtain distinct cell clusters that were grouped and annotated based on expression of canonical marker genes Fig. . We focu05) Fig. . The T c05) Fig. . Naive Tles Fig. . The comles Fig. . Pathwayles Fig. . In summ56 and TARGET AML-2 dataset). The samples from bulk RNA-seq datasets were divided into different risk groups  based on leukemic stem cell 6 (LSC6) scores. LSC6 score, calculated using expression of six genes , depicted significant prognostic ability and estimation of EFS for pediatric AML57. We assessed various immune cell types in bulk RNA-seq datasets by employing a single sample gene set enrichment analysis (ssGSEA) approach. The immune cell types investigated included M1 Macrophages , naive T-cells , effector T-cells , exhausted T-cells , and regulatory T-cells . In Fornerod et al., AML dataset, M1 Macrophages depicted a significant (P = 1.2e−05) negative correlation with the LSC6 score indicating lower enrichment in high-risk samples  positive correlation with the LSC6 score . Exhausted T-cells were significantly enriched in the medium-risk samples as compared to low-risk samples (P < 0.05)  as compared to the other two categories .Immune cell-focused analysis of scRNA-seq data reveals a link between exhausted T-cells and poor pediatric AML outcome Fig. , while eP = 7.3e−11) as well as naive T-cells (P = 9.8e−11). Exhausted T-cells depicted a significant (P = 5.7e−09) positive correlation with the LSC6 risk score  and naive T-cells (P < 0.05) compared to the high-risk samples. On the other hand, the high-risk AML samples were significantly enriched in exhausted T cells compared to the low-risk samples (P < 0.001) , myeloid differentiation factor (AZU1), cell development (NREP), and transcription factor (PRAME). TRH has been shown to have high expression in AML62 while the function associated with ARMH1 is not known yet. The functional variability of the 7-gene signature capable of distinguishing AML-blasts from non-blast cells is suggestive of multiple synergistic pathways being modulated in AML-blasts. Significant association of the 7-gene signature overexpression with poor OS in some AML patients can be attributed to the associated regulation of myriad cell functions that promote tumor growth, proliferation, and migration21. This 7-gene signature identified blast cells on a validation set of additional pediatric AML samples as well as on an external pediatric AML dataset strengthening its utility as a pediatric AML diagnostics and prognostics biomarker. Comparative gene expression analysis with healthy BM and HSCs also depicted that 7-gene signature is specifically overexpressed in the AML-blasts, strengthening its association with leukemogenesis. Analysis of longitudinal samples  showed that blast cells identified at Dx reduced significantly at EOI and reappeared in Rel samples. The blast cells in the samples collected at relapse and disease diagnosis depicted significant similarity indicating expansion of certain therapy-resistant rare Dx blast cells clones that might be responsible for disease relapse. We postulate that after further validation on larger datasets, the 7-gene signature can be used in conjugation with current immunophenotyping-based AML diagnosis and prognosis with better accuracy.Our analysis of BM samples from pediatric AML patients comprising of various genetic subtypes  associated with poor clinical outcome. Cytoskeleton proteins affect various tumor cell characteristics like cellular proliferation and migration to promote drug resistance, invasiveness, and metastasis63. Also, actin cytoskeleton remodeling can change physical and functional interactions at the immunological synapse64. Microtubule targeting or disrupting agents have been tested for a variety of therapy-resistant cancers65. RFLNB belonging to the refilin family, are short lived F-actin regulators, that control cell fate specification and differentiation66. RFLNB promoter binds transcription factor PKNOX1/PREP1 that regulates embryonic development and determines cell fate67. RFLNB and PKNOX1 are also known to modulate responsiveness to TGFβ and promote epithelial–mesenchymal transition68. RFLNB targets FLNA to organize a perinuclear network and stabilize nuclear shape69. FLNA is known to interact with integrin, ITGB7 that interacts with VCAM170. Therefore, overexpression of FLNA, RFLNB in relapse-associated blasts cells may modulate the cell structure and subsequent interactions with immune cells. These changes may influence cell junction organization, cell motility, and activate nuclear transcription programs that may contribute to AML relapse. The genes overexpressed in the relapse-associated blasts cells were found to correlate with the upregulation of multiple pathways including RhoGDI, eNOS, and protein kinase A signaling. Rho GDP-dissociation inhibitor (RhoGDI) pathway activation has been shown to enhance chemoresistance in cancer cell lines and animal models71. Studies also show that endothelial NOS (eNOS) can affect tumor processes such as resistance, angiogenesis, invasion, and metastasis. An increase in eNOS expression is found to have associations with poor relapse-free and overall survival as well72. In contrast, Dx blasts from samples with CCR showed significant upregulation of genes like MPO and TRH that are associated with better survival outcomes. Previously TRH expression has been shown to be increased in t AML subtype and this high expression is associated with better clinical outcomes73. TRH has been implicated to have a role in the immune system74, but its role in AML-blasts is not clear. MPO is the key enzyme of myeloid lineage commitment and is associated with a favorable prognosis in AML55. These gene-level differences identified in relapse- and CCR-associated blasts and subsequent differential regulation of pathways and upstream key transcriptional regulators may contribute to differences in hematopoietic niches that result in AML relapse/CCR. We observed CNAs in multiple chromosomes indicative of AML-associated chromosomal aberrations. Future in-depth CNA analysis along with correlation to transcriptome changes in pediatric AMP patients might provide a better understanding of the role of copy number alterations in disease onset, progression as well as post-therapy response.Further scRNA-seq data analysis revealed distinct gene expression profiles at Dx of blasts from patients that are destined to relapse vs. patients that remain in CCR. The blast cells of relapse-associated samples even at the time of disease diagnosis depicted upregulation of multiple genes related to cytoskeleton formation (SELENOP), metabolism, and stemness . The higher expression of HOPX is associated with higher platelet counts, lower white blood cell counts, lower lactate dehydrogenase levels, lower complete remission rates, and poor overall survival53. SELENOP encodes for a selenoprotein that mediates microenvironmental changes that influence tumor growth and prognosis across multiple solid tumors such as prostate and breast cancers54. Similarly, the FAM30A gene has been recently shown to be associated with leukemia stemness and high-risk pediatric AML57. The pathways analysis of post-therapy residual blast cells showed upregulation of multiple pathways including fatty acid oxidation, and PPARα network. Fatty acid oxidation has been linked to enrichment and survival of leukemic stem cells resulting in disease progression and relapse75. Furthermore, the resistance of AML to conventional and metabolically oriented therapies (Venetoclax) has also shown an association with upregulation of fatty acid oxidation in the leukemic stem cells (LSCs)77. Therefore, our preliminary data support targeting fatty acid metabolism in AML LSCs for achieving CCR, though more validation is required.In addition, the investigation of paired Dx and EOI samples led to the identification and characterization of residual blast cells after treatment and provided the opportunity to characterize them. The residual blast cells depicted overexpression of multiple genes associated with tumor growth  may be influenced by the type of residual blasts present in these samples. The analysis of innate immune cells depicted enrichment of inflammatory M1 macrophages in Dx and EOI samples of patients with CCR compared to samples of patients with relapse, indicating that the presence of these adaptive immune cells may contribute to remission as well maintain it. Leukemia-associated macrophages (LAM) have been associated with survival and drug resistance of AML cells80. It has been shown that targeting IRF7/SAPK/JNK pathway can promote M1 characteristics in LAM resulting in prolonged survival of leukemic mice82. Conversely, relapse-associated EOI samples had significantly fewer M1 macrophages that may not clear up the residual blast cells that drive disease relapse. These findings indicate a potential role of innate immune cells in achieving sustained remission and exploration for therapeutic intervention.While AML is mainly characterized by enrichment of immature myeloblasts, immune cells in the TME play an integral role in the disease progression and outcomeARMH1 in AML-blasts is important for diagnostic purposes and may have therapeutic potential. Using scRNA-seq data analysis we were able to identify AML-blast-specific gene signatures, identify and characterize AML-associated blasts and delineate immune cells make-up in the BM microenvironment of children with different clinical outcomes.In conclusion, common transcriptome/pathways present in the various AML genetic sub-types enabled the development of a 7-gene signature for diagnosis and prognosis of pediatric AML. At the same time, distinct differences were identified in AML-associated blasts as well as non-blast cells that distinguished samples with relapse from samples with CCR. We uncovered the presence of patient-specific blasts at Dx, post-therapy residual blasts at EOI, and the presence/activation of different arms of the immune system (monocyte/macrophage and T cells) in pediatric AML samples from those with relapse and those with CCR at both Dx and EOI. The identification of upregulation of less studied genes like https://www.cancer.gov/ccg/research/ genome-sequencing/target). The 7-gene signature established using Dx, EOI matched samples from patients 3, 5, 6, 14 was validated using paired Dx, EOI single-cell profiling data from patients 16–20. In addition, we also validated the diagnostic performance of the 7-gene signature in a publicly available dataset containing eight AML and four healthy human BM samples7. We also performed comparative analysis on normal HSC by downloading Human Cell Atlas HSC scRNA-seq dataset from https://data.humancellatlas.org/explore/projects/cc95ff89-2e68-4a08-a234-480eca21ce79. We further validated the 7-gene signature expression in another set of samples from TARGET AML resource, i.e., TARGET AML-2; normal BM (n = 324), ≤30% blasts (n = 169), 30–60% blasts (n = 342), ≥60% blasts (n = 826) (https://www.cancer.gov/ccg/research/genome-sequencing/ target). Samples that did not have associated BM blast percentages (n = 61) were excluded from this analysis. The focused single-cell analysis at Dx were performed on samples from 14 patients: six with relapse (1D–6D) and eight with CCR (7D–14D). For EOI, the analysis was performed on five patients’ samples: three with relapse  and two with CCR . The independent validation of immune cells signature was performed in two publicly available RNA-seq datasets: 1. Fornerod et al., AML dataset56 (n = 132), 2. TARGET AML-2 dataset (n = 1398).Samples were obtained as part of a precision medicine study of Aflac Cancer and Blood Disorder Center from Children’s Healthcare of Atlanta Pediatric Biorepository that was approved by the institutional review board at Emory University, Atlanta, GA. Signed consent was provided by parents or legal guardians for pediatric patients to permit the use of biological material in accordance with a protocol that was approved by the institutional review board. BM samples were obtained at the initial presentation of AML (Dx), at the time of therapy remission; post-therapy (EOI), and at the time of relapse (Rel) as part of routine hematopathology evaluation. The study was performed on 20 patients, out of which 14 patients remained in CCR, and six patients relapsed. To identify the AML-blasts associated gene signature, we analyzed scRNA-seq data of Dx and EOI samples from four patients  and the TARGET AML RNA-seq dataset 1 (TARGET AML-1)  based on shared embedding using harmony Bioconductor package84. Further quality control, preprocessing, unsupervised, and supervised analysis of the data was performed using various R and Bioconductor packages. The quality filtering on scRNA-seq data was performed by multiple filtering parameters including filtering out cells with >25% of mitochondrial genes and lower genes expression capture (<200 genes), and genes only uniquely expressed in <3 cells in the dataset.Raw scRNA-seq data was demultiplexed, aligned to the human reference genome (hg38), and processed for single-cell gene counting using the Cell Ranger Software from 10x Genomics Inc (v3.0.2). The single-cell count data was normalized using the SCTransform function in Seurat v3.0 Bioconductor packageCD3+), B cells , macrophages (CD68+), monocytes (CD14+), and other immune cells based on expression of specific well-established genes. The putative blasts cell clusters were annotated using top expressed genes. The comparative analysis of single-cell landscape of AML blasts and non-blasts during separate phases of disease  was performed using split UMAP plots, determining heterogeneity (based on clusters of cells) and enrichment of cell types. To understand differences in the TME between relapse- and CCR-associated samples, we performed a comparative analysis of the abundance of various canonical cell types  as well as the blast cells. Further, to determine changes in cellular states or activation in relapsed and remission samples, comparative analysis of specific cell types marker genes was performed using dot plot function83. In an unbiased approach, cell types and subtypes signatures were generated by comparing the expression profile of target cell type with the rest of the cells using the non-parametric Wilcoxon rank test (P < 0.01) and fold change >1.2.The unsupervised analysis using principal component analysis (PCA) was performed on variable genes to identify principal components with significant variation. The PCs with significant variations were used as input for UMAP analysis, to determine the overall relationship among the cells. The cells with similar transcriptome profiles clustered together and subsequently annotated to different cell types such as T cells (P < 0.01). To reduce the false positives and identify robust AML blast-associated genes, we evaluated their pattern on the external pediatric AML dataset from TARGET initiative (TARGET AML-1 dataset). The study contains bulk RNA sequencing data generated from BM samples of more than 300 AML subjects that include infants (<3 years old), children (3–14 years old), and adolescents/young adults (15–39 years old). The raw TARGET AML-1 dataset was normalized using VOOM algorithm85. To explore the expression pattern of single-cell profiling identified AML-blast-associated genes in the TARGET AML-1 dataset, we binned the Dx datasets into separate groups based on percentages of blast cells . We hypothesized that genes that are specifically expressed by blast cells will depict a progressive downregulation pattern from high to low blast % and EOI samples. The significance of progressive downregulation from high to low blast%/EOI groups was determined using unpaired Student t-test (P). Genes with fold change >1.8 (high blast % vs. low blast % samples) and P < 0.04 were considered significantly associated with blast cells. The resultant genes from this analysis were further evaluated for expression in normal BM microenvironment cell types in single-cell data from paired Dx and EOI patients. Genes with high expression in normal BM microenvironment cells were filtered out. The workflow for generation of blast-associated signatures is shown in Supplementary Fig. 86.The preliminary comparative analysis of AML Dx enriched clusters and EOI-enriched clusters (mainly immune cells) identified a lengthy list of 232 AML-enriched genes that are overexpressed in AML blast cells . The classifier was trained using normalized and preprocessed single-cell data . The classifier was trained using a linear SVM kernel along with a recursive feature elimination approach for developing the best model with the most important features in discriminating the pediatric AML-blast cells from non-blast cells. The performance of the classifier during training was determined using an out-of-bag (OOB) cross-validation approach using the MetaboAnalyst package87. The SVM classifier identifies the most “important” features by considering their relative contribution to the classification task, as indicated by the error rates. During the training, multiple SVM models with varying numbers of genes from 5 to 15 were generated by removing features with the least importance. The features were ranked based on their inclusion in the SVM models for classifying AML blast vs non-blast cells. The performance of classifiers was measured using threshold-independent receiver operating characteristic (ROC) analysis. The analysis assisted in identifying a minimal set of genes that can distinguish blast cells from other cells with high Area Under Curve (AUC) from ROC analysis. We selected the seven most important genes for the final model as they depicted performance comparable to models developed based on higher number of genes.To identify the key genes associated with AML blasts we developed a classifier using a support vector machine (SVM) model82. The expression of the genes was visualized in our AML, healthy BM, and normal HSC clusters by generating violin plots.AML-blast-specific expression of the 7-gene signature was validated by checking expression in healthy BM and normal HSCs. Healthy BM cells and HSCs were integrated with AML paired Dx, EOI samples  and normalized using the SCTransform function in Seurat v3.0. Batch effect corrections were made using HarmonyMPO +, CD34 +, AZU +) and SingleR automatic annotation22 . After preprocessing, normalization and unsupervised analysis, blast and non-blast cells were annotated based on expression of canonical normal cell markers from lymphoid, myeloid, and erythroid lineages. The blast cells were identified based on: (1) classification as myeloid progenitor cell types by SingleR22, (2) patient or AML-specific clusters that overexpress established blast markers  . In the validation set, blast cell clusters were identified  using Bioconductor/R packages including TCGAutils and tidyverse. The AML Dx samples were binned into separate groups based on the BM blast cell percentages: <30% (n = 169), ≥30%–<60% (n = 342), and ≥60% (n = 826). AML samples (n = 61) without information about blast cells percentages were excluded from the analysis. The Z-score of enrichment of the 7-gene signature for each sample in the dataset was calculated using Gene Set Variation Analysis (GSVA) and comparative analysis across groups performed. In addition, the variation in individual gene expression (log[FPKM + 1]) for the 7-gene signature was also evaluated by generating boxplots. The Wilcoxon rank sum test was used to perform comparisons between groups to determine significant differences in expression profiles.Additional validation was performed using an external bulk RNA-Seq dataset from the TARGET AML cohort. We developed the TARGET AML-2 dataset by filtering out samples used during the development of the 7-gene signature. The TARGET AML-2 dataset contains 1398 AML primary BM samples and 324 normal BM samples. We downloaded FPKM values from the GDC Data Portal  using the web-based platform, Survival Genie 26. The primary pediatric BM (n = 145) were collected at Dx with available clinical survival data and normalized FPKM expression counts. We examined the association of both the combined and individual effects of blast genes on clinical outcomes in the TARGET AML-1 cohort. For gene analysis, we used the median (50th percentile) cut-off or an optimal cut point (cutp) estimated based on martingale residuals88 using the ‘survMisc’ package in Bioconductor/R to separate the patients into high and low gene expression groups. For combined analysis, we used the non-parametric method, ssGSEA, as implemented in the GSVA package89 to obtain a gene-set enrichment score to obtain a gene-set enrichment score. Tumor samples were categorized into high and low gene expression groups using either the median or a cutp of the ssGSEA score as cut-off. OS or EFS statistical analysis was performed using the ‘survival’ R package. Kaplan–Meier survival curves were used to estimate the OS/EFS with survfit function and a log-rank test was done to compute differences in OS between the high and low gene expression groups. Univariate analysis with Cox proportional hazards regression was performed on the dataset using the coxph function. The results were considered significant if the P values from log-rank and Wald test were below .05.To determine the association of blast genes with clinical outcomes in AML, we performed survival analysis on the bulk RNA-Seq TARGET AML-1 dataset from the GDC Data Portal  and was plotted on a UMAP to show the distribution of cells with predicted alterations.Malignant phenotype of the AML blast cells is associated with somatic copy number alterations resulting in gene amplifications and gene deletions. In this study to predict the copy number alterations in blast cells identified in single-cell data, we used InferCNV algorithm, v1.3.3https://www.ingenuity.com). Furthermore, systems biology analysis was performed using upstream regulators enrichment approach to identify the upstream transcriptional regulators that can explain observed transcriptome changes. Regulatory analysis helps in identifying significantly activated or inhibited transcriptional regulators based on upregulation or downregulation of its target genes. The significance of transcriptional regulators activation/inhibition was determined using one-tailed Fisher’s Exact test. The regulators with P < 0.01 and absolute Z-score of ±1.5 were considered statistically significant.To precisely characterize the AML blast cells and understand the molecular mechanism of disease progression, we performed pathways enrichment and systems biology analysis. Pathways and systems biology analysis was performed using the Ingenuity Pathway Analysis software package (IPA 9.0) (Qiagen). A detailed description of IPA analysis is available at the Ingenuity Systems’ website  score represents the degree to which the genes in a particular gene set are coordinately up- or down-regulated within a cell cluster, which could serve as an indicator of gene set activity. To interrogate the pathways/gene sets that are differentially enriched in one cell type vs. other, we performed statistical analysis using student t-test or LIMMAhttps://www.cancer.gov/ccg/research/genome-sequencing/target) with 1398 samples. The Fornerod et al., AML dataset includes LSC6 risk score57 information for each sample and corresponding LSC6 risk categories . We calculated the LSC6 score for the TARGET AML-2 samples and stratified them into risk categories based on the same thresholds used in the Fornerod et al. AML dataset. The LSC6 score for the TARGET AML-2 samples was calculated using the formula from Elsayed et al.57. The dataset contained 175 low-risk (LSC6 score <0.95), 467 medium-risk (LSC6 score ≥0.95 and <1.9), and 756 high-risk (LSC6 score ≥1.9) samples. We tested the enrichment of M1 Macrophage , naive T-cell , effector T-cell , exhausted T-cell , and regulatory T-cell  in the bulk RNA-seq datasets by calculating ssGSEA score for each immune cell type. The Pearson’s correlation was calculated between the LSC6 and ssGSEA scores for each immune cell type, and the corresponding P-values to determine associations. We also evaluated the association between categorized scores  and ssGSEA immune cell enrichment scores by performing Wilcoxon signed-rank test.We assessed enrichment of immune cells/phenotypes derived from scRNA-seq analysis into two independent bulk RNA-seq datasets: Fornerod et al., AML dataset with 132 samples and TARGET AML dataset 2 (Further information on research design is available in the Supplementary InformationPeer Review FileReporting SummarySource Data


In this commentary, we provide an overview summarizing the studies dealing with the relationship of FLT3 and CXCR4. Taken together, the current research status is not sufficient to answer the question whether FLT3 and CXCR4 act together or independently in leukemia progression. Systematic analyses in model cell systems are needed to understand the interplay between FLT3 and CXCR4, since this knowledge could lead to the development of more effective treatment strategies for AML patients.FLT3 mutations are very frequent in AML and utilization of FLT3 inhibitors as approved treatment options are very common. Despite the initial success of inhibitor treatment, the development of resistances against this treatment is a major challenge in AML therapy. One of the mechanisms causing resistance is the homing of the leukemic cells in the protective niche of the bone marrow microenvironment (BMM). A pathway mediating homing to the BMM and leukemic cell survival is the CXCL12/CXCR4 axis. The analysis of patient samples in several independent studies indicated that FLT3-ITD expression led to higher CXCR4 surface expression. However, several  It is characterized by the uncontrolled proliferation of abnormal myeloid progenitors which are impaired in their differentiation into mature blood cells . DespiteThe FMS-like tyrosine kinase 3  is expressed on the surface of hematopoietic stem and progenitor cells and is involved in the regulation of cell survival, proliferation, and differentiation –4. FLT3 The ITD mutations are the most common mutations of FLT3 found in AML patients and are associated with a poor prognosis, increased relapse rates, and decreased overall survival , 11. The2One of the mechanisms causing resistance to inhibitor treatment is the association of leukemic cells with the bone marrow microenvironment (BMM). The bone marrow provides a protective niche for AML cells impeding the effective elimination by FLT3 inhibitors.The stromal cells of the bone marrow produce and secrete CXCL12 [previously known as stromal cell-derived factor-1 (SDF-1)], the ligand for the C-X-C chemokine receptor type 4 . The G protein-coupled receptor CXCR4 is expressed on the surface of hematopoietic cells, where it plays a crucial role in chemotactic migration to the bone marrow, as well as cellular proliferation and survival . Moreove3Since CXCR4 contributes to the survival of leukemic cells in the BMM, the combinatorial treatment of CXCR4 antagonists and FLT3 inhibitors may lead to improved therapeutic outcomes in AML. For example, Kim et al. have demonstrated that the combination of the CXCR4 antagonist LY2510924 and the FLT3 inhibitor quizartinib reversed the stroma-mediated resistance against the FLT3 inhibitor and induced the mobilization and differentiation of AML cells in mice, resulting in enhanced anti-leukemia effects . In addiA different approach, using a CXCL12 knock out mouse model also resulted in enhanced targeting of AML cells by FLT3 inhibitors and chemotherapy treatment as compared to mice with normal CXCL12 expression . This st4Until now, several studies have examined the interplay of FLT3 and CXCR4. For instance, Rombouts et al. found that AML patient samples with FLT3-ITD mutation have a higher expression of surface CXCR4 . Similarin vitro experiments have been conducted, but they reveal contrasting findings. Moreover, the used cell models and experimental setups are very diverse. To elucidate the current research status, the findings of several publications will be recited in the following.In addition to the analysis of patient samples, multiple In 2005, Fukuda et al. presented data where the effects of CXCL12 and FLT3 ligand (FL) co-stimulation were analyzed . They reIn 2009, the PIM1 kinase was introduced as a possible factor influencing the CXCR4 surface expression, but not the mRNA level of CXCR4 . PIM1 isShorty after, Jacobi et al. present their results: They found a reduction of CXCR4 protein and mRNA levels if FLT3-ITD was overexpressed . InteresCao et al. addressed the question of interplay by analyzing the CXCR4 levels in two different hematopoietic cell lines representing FLT3-ITD expression (MV4-11 cells) or FLT3-WT expression . In contrast to the above-mentioned studies, they report that FLT3-WT expressing cells do not express CXCR4 whereas the FLT3-ITD expressing cell line does . NeverthA recently published study by Jia et al. suggests that FLT3-ITD signaling could inhibit CXCR4 expression as it reports that treatment of FLT3-ITD expressing MOLM-14 cells with a FLT3 inhibitor resulted in an upregulation of CXCR4 on the cell surface, as well as on the mRNA level . If this5It has been clearly shown that the level of CXCR4 expression in AML patient samples does have prognostic value and that targeting CXCR4 in AML could be a promising strategy to eliminate leukemic cells hiding in the bone marrow niche.However, contrasting findings on the influence of FLT3-ITD on the surface expression of CXCR4 were reported and simplified results are summarized in In any way, the more detailed information would be available, the better the treatment strategies could be optimized to improve the prognosis of patients suffering from AML.JD: Conceptualization, Funding acquisition, Writing – original draft, Writing – review & editing. LK: Writing – original draft, Writing – review & editing.


The PT is a Ca2+-dependent permeability increase in the inner mitochondrial membrane whose function and underlying molecular mechanisms have challenged scientists for the last 70 years. Although most of our knowledge about the PTP comes from studies in mammals, recent data obtained in other species highlighted substantial differences that could be perhaps attributed to specific features of F-ATP synthase and/or ANT. Strikingly, the anoxia and salt-tolerant brine shrimp Artemia franciscana does not undergo a PT in spite of its ability to take up and store Ca2+ in mitochondria, and the anoxia-resistant Drosophila melanogaster displays a low-conductance, selective Ca2+-induced Ca2+ release channel rather than a PTP. In mammals, the PT provides a mechanism for the release of cytochrome c and other proapoptotic proteins and mediates various forms of cell death. In this review, we cover the features of the PT (or lack thereof) in mammals, yeast, Drosophila melanogaster, Artemia franciscana and Caenorhabditis elegans, and we discuss the presence of the intrinsic pathway of apoptosis and of other forms of cell death. We hope that this exercise may help elucidate the function(s) of the PT and its possible role in evolution and inspire further tests to define its molecular nature.The demonstration that F Sin2+ , Ca2+ isith Ca2+ . In mamme [Ca2+] , probable [Ca2+] ,112 and c to the intermembrane space , the changes occurring in mitochondria are similar to those observed in mammals including cristae remodeling, increased ROS levels, matrix swelling and cytochrome c release [2+] and the onset of oxidative stress—mitochondria can accumulate enough Ca2+ to undergo the PT in spite of the absence of the MCU. Once PTP opening occurs, cytosolic and matrix Ca2+ equilibrate stabilizing the PTP in the open conformation, which is followed by osmotic swelling of the matrix, outer membrane damage and release of intermembrane proteins that participate in the process of cell death by favoring activation of the metacaspase Ycap1  requires matrix Ca2+ loading and is favored by inner membrane depolarization, thiol oxidation and treatment with millimolar concentrations of N-ethylmaleimide, by Bz-423 and enforced mitochondrial expression of human CyPD [Drosophila species is insensitive to ADP and, as mentioned above, does not mediate mitochondrial swelling, an arrangement that may fit the features of apoptosis in this organism.The properties of the man CyPD ,148; likman CyPD ; at variDrosophila, but the role of mitochondria in Drosophila cell death remains controversial [Drosophila melanogaster possesses two cytochrome c proteins (DC3 and DC4), the latter having the highest homology with cytochrome c of other species [c is required for apoptosome formation with Apaf-1 and therefore for caspase 9 activation [Drosophila apoptosis, rupture of the outer mitochondrial membrane and release of cytochrome c do not occur even if mitochondrial fragmentation is observed [c may rather be displayed on the outer membrane [c, silencing of DC3 and DC4 did not affect the processing of dApaf, activation of the caspases DRONC and DrICE  ied back , and  released by females. Under extreme conditions , females become oviparous and release gastrulae in diapause, a partially arrested developmental state of dormancy with metabolic activity decreased by 97%. When conditions return to be favorable, the development of larvae resumes [Artemia franciscana can resist for many years under anoxia by reducing ATP levels and heat production, and this metabolic arrest appears to be due to the reduction of mitochondrial transcription [Artemia franciscana accumulate large amounts of Ca2+ without undergoing a PT [2+ could not induce the PT in two other crustaceans, the brown shrimp Crangon crangon and the common prawn Palaemon serratus [Drosophila, cytochrome c is not required for caspase 9 activation in Artemia franciscana extracts [Artemia franciscana embryos with 20 μM HgCl2 in hypotonic solutions opens a CsA-insensitive permeability pathway with a size exclusion limit of 540 Da, the identity of which was not defined [Artemia unspecific permeability can be explained by modification of metabolite carriers, and whether it can take place under normal conditions remains to be established. resumes . Artemiacription . Hand aning a PT  with theing a PT . Remarkaserratus , in keepserratus ,174. Simextracts . It is textracts . It shou defined . Interes defined ,178. WheArtemia ANT presents a peculiar feature that differentiates it from its mammalian counterpart, i.e., lack of sensitivity to BKA, a feature that appears to depend on the 198–225 amino acid region [Artemia ANT in lieu of AAC2 in Saccharomyces cerevisiae AAC1-AAC3 KO strain restores BKA sensitivity [Artemia ANT on the yeast lipidome was evaluated. It was found that Artemia ANT influences the yeast mitochondrial membrane inducing changes in lysolipids [d region . Surprissitivity , a findisolipids , which aCaenorhabditis elegans [c is not required for activation of CED-3 by oligomers of CED-4, and yet essential proapoptotic factors such as WAH-1 (homolog of AIF) and CPS-6 (homolog of Endo-G) are released from mitochondria to execute cell death [Caenorhabditis elegans.The first caspase was identified in the nematode  elegans ,182, an  elegans . In this elegans  , indicating that mitochondrial permeabilization turns the normally protective process of autophagy into a death pathway [Caenorhabditis elegans demonstrated that OSCP downregulation in adult but not in developing worms was able to trigger PTP opening and the mitochondrial unfolded protein response causing decreased life span, which could be normalized by PTP inactivation by both silencing of the c-ring or peripheral stalk subunits (including subunit e) and treatment with CsA [Autophagy is usually required for lifespan extension in model organisms including  elegans . Unexpec elegans . Normal  pathway , an even pathway . A recenwith CsA . These rwith CsA .O region and include subunits e and g, which in yeast are strictly associated with dimers [Saccharomyces cerevisiae [Drosophila melanogaster [2+ release channel [ANT proteins are highly conserved both in primary sequence and overall architecture, in the sense that the typical three homologous domains (which probably arose from duplication events) are conserved from yeast to mammals, implying that the duplication events occurred before the divergence of fungi, metazoa and plantae . This seh dimers ,197 and h dimers . Structuh dimers ,199,200.h dimers , 300 pS revisiae  and 53 pnogaster , where a channel . What isSaccharomyces cerevisiae [Burkholderia pseudomallei [Saccharomyces cerevisiae, the deletion of subunits e and g together with the α-helical portion of subunit b (which removes the wedge region) completely prevented the formation of a high-conductance channel [Mutations in subunit c affect the PTP ,201. Everevisiae . The c-rdomallei . Further channel . (ii) Ar channel ,202 and  channel . (iii) D channel .Drosophila melanogaster [Saccharomyces cerevisiae arginine 107 of subunit g is the sole responsible for the effect of phenylglyoxal [Saccharomyces cerevisiae confers the human phenotype to the yeast PT, with phenylglyoxal becoming now an inducer rather than an inhibitor [Another intriguing set of observations points to the importance of the wedge region in imparting species-specific features to the PTP. Treatment of rat liver mitochondria with 2,3-butanedione or phenylglyoxal results in strong inhibition of the PTP through stable chemical modification of critical matrix arginine residue(s) . The effnogaster . Given tlglyoxal , by explnhibitor .An important contribution could come from subunit e . The GXXDanio rerio), the PTPs of which are indistinguishable [Drosophila melanogaster the protein terminates with a histidine immediately following a lysine. Caenorhabditis elegans, Saccharomyces cerevisiae and Yarrowia lipolytica have unique C-termini ending with aspartic acid, threonine and alanine, respectively  of these proteins across species. Yet, by matching known features of the PTPs to mechanisms of cell death, in particular the presence of the mitochondrial pathway to apoptosis, we have outlined a working hypothesis that largely hinges on the presence of a PT in yeast, mammals and worms and its absence in crustaceans, and on what appears to be an intermediate case in Drosophila melanogaster, i.e., the presence of a Ca2+-selective Ca2+ release channel that shares some of the regulatory features of the bona fide PTP. Given that in mammals the PT provides a mechanism for the release of Ca2+, but can also trigger the release of cytochrome c and other proapoptotic proteins, we suggest that lack of a PT in crustaceans contributes to their resistance to anoxia (which is partly shared by Drosophila) and to dehydration, and that Drosophila has retained the Ca2+-release properties of the PTP but not its ability to permeabilize the inner membrane to solutes and to mediate the release of proapoptotic proteins. From an evolutionary perspective, it is interesting to note that there is no evidence for the activation of caspases by cytochrome c in non-vertebrates, suggesting that during evolution the apoptotic pathway appeared only once and that some features of the canonical pathways seen in higher species were lost in other species [Drosophila DC3 and DC4 induce caspase activation in human cells, while human cytochrome c could not promote caspase activity in Drosophila cells [2+ homeostasis and apoptosis in a process of molecular exaptation [In this review, we have tried to assess the potential role(s) of the PT through the analysis of selected organisms in which our understanding of Ca species . Consistla cells . It is tla cells , may havaptation .


Four different types of new materials were manufactured with the use of a specially designed pressing device and differed in the fiber type  and weight fraction (wf) ratio, but they had the same number of layers and the same stacking sequence. A vertical machining center Avia VMC800HS was used for drilling holes with a two-edge carbide diamond coated drill. Measurements of the cutting force zF in the drilling process conducted with variable technological parameters were carried out on a special test stand, 9257B, from Kistler. The new ink penetration method, involving covering the drilled hole surface with a colored liquid that spreads over the inner surface of the hole showing damage, was used to determine the delamination area. The cause-and-effect relationship between the drilling parameters was simulated with the use of five machine learning (ML) regression models . Gradient Boosting Regressor results showed that the feed per tooth had the greatest impact on delamination—the higher the feed was, the greater the delamination became. Push-out delamination factors had higher values for materials that were made of plain woven fibers. The lowest amplitude of the cutting force component zF was obtained for the lowest tested feed per tooth of 0.04 mm for all tested materials, with the lowest values obtained for the materials with twill fibers.The aim of the research presented in this paper was to simulate the relationship between selected technological drilling parameters (cutting speed,  Composite materials, especially polymer composites, are widely used in almost every industry. Polymer composites are divided into thermosets and thermoplastics, and they can be reinforced by different types of fibers such as carbon fibers (CF), organic fibers, and glass fibers (GF) , etc. GFPolymer composites often require machining of composite parts at the final stage of production in order to meet the required shape and dimensional tolerances  and to cThe most common damage modes caused by machining GFRP composites are fiber pullouts, interlaminar delamination, fiber/matrix debonding, fuzzing, matrix melting, and softening . DelaminMany previous studies focused on factors influencing delamination. Generally, researchers investigate how machining parameters, tool materials, geometry, and tool types affect delamination. In relation to machining parameters, R. Bhat et al.  investig® Helica-coated (SCBH) twist drills with a higher speed. Also Hy et al. [Malik et al.  studied y et al.  also fouy et al.  present y et al. . Sun Z. y et al.  analyzedIn addition to the influence of technological processing parameters, attention should also be paid to the influence of the manufacturing and assembly stages on residual stresses, because they reduce the strength of the structure and affect deformations. Vedernikov A.N. et al.  conducteDue to increasing competition, the manufacturing industry is looking for new solutions that will reduce costs, save time, improve product quality, and reduce the amount of waste. An increasingly popular solution is the optimization of systems in manufacturing industries through the use of machine learning (ML). ML allows computers to learn from data and prior experiences, so that they can find patterns and predict future events without human interaction. ML is used in different engineering applications ,35,36. TBased on the literature analysis presented above, it can be concluded that there are many factors that influence the machinability of GFRP composites and their defects. The most important include technological parameters, the type of tool , and the type of material and its dimensions . These factors are important to determine, especially when cutting new materials. This is why the purpose of this study was to analyze the relation between technological drilling parameters of drilling and cutting forces and the delamination types in the drilling of new GFRP composite types. The GFRP samples for this research were manufactured using an innovative method which was patented  and invoThis research evaluated GFRPs because these materials are transparent, and the phenomenon of layer delamination can be observed much more easily. The results of this study can also be applied to other types of transparent composites. In this case, the phenomenon of delamination of the layers cannot be observed, with the material being opaque. The similarity between these materials can only be applied if the same matrix and the same type of architecture and the same type of wire of the reinforcing material are used. This can be determined by modern methods of non-destructive testing.cv and the feed per tooth zf) and different types of GFRP materials  on the cutting forces and delamination in this process, in order to obtain high-quality drilled holes. Optimal technological parameters for GFRP drilling, that meet quality requirements can be determined based on these results. The aim of this study was to investigate the influence of selected technological drilling parameters , for measuring the components of cutting forces in three axes xF, yF, zF, a signal conditioning system, a DAQ module with an integrated A/D card, and dedicated software  was used for drilling holes, and coolant was not applied. The drilling process was carried out using a 2-edge carbide diamond coated drill (SD205A-12.726-56-14R1-C2) of diameter 12.726 mm produced by Seco . During the tests, holes in the samples made of different types of GFRPs were drilled with variable drilling parameters: cutting speeds software .The cutting force amplitude value was taken as a difference between the maximum value and the minimum value of the force signal. The monitoring and control of cutting forces occurring during drilling is important for process improvement. It is also important from the point of view of critical parts safety because a thorough analysis of the drilling process based, among others, on cutting force measurements is an important factor influencing the maximum production reliability.The standard deviation was calculated asThe next stage of the research involved delamination measurements.One of the aims of this study was to determine two types of delamination: peel-up delamination, which occurs on the drill entry surface, and push-out delamination, which occurs on the surface when the drill exits the material. Given that the tested GFRP materials were produced with a new pressing device, it was important from the point of view of their industrial application to determine the impact of drilling on delamination.Hole delamination was examined using a new ink method. The method consists of covering the surface of the hole with a colored liquid that spreads over the inner surface of the hole using a dropper. The method of covering the surface of the holes with ink is shown in The method allows easy identification of the delamination area. This is especially important for GFRP materials where delamination is not always easy to detect. The phenomenon of delamination is, however, very easy to detect in fabricated GFRP parts, which can be attributed to the transparency of the plates. The conclusions of this study can be extended to other types of composites such as CFRP or AFRP. This is if the type of fabrics or fabrics used is respected. In the case of another type of composite, the delamination cannot be observed.For research purposes, a mixture of navy blue ink and ethyl alcohol was used . An example of a hole  with a push-out delamination area without ink and ink-colored is shown in The delamination factor is calculated as ,44(3)FdThe nominal and maximum delaminated diameters were measured with the Keyence VHX-5000 optical microscope software at 10× magnification.zF parameter based on the type of material, the cv parameter, and the zf parameter. Only the component of the cutting force zF was an object of prediction models, because it plays the largest role in the drilling process and assumes the largest value. For this purpose, a data set was created consisting of previously indicated parameters. The dataset was divided in the proportions of 7:2:1 into a training, validation, and test set. In order to create a regression model for obtained data, the following methods were employed:The main goal of creating the model is to estimate the Linear Regression;Decision Tree Regressor;Decision Tree Regressor with Ada Boost ;XGBRF Regressor;Gradient Boosting Regressor.For the Decision Tree Regressor model, the maximum depth of the tree was defined as the point at which all leaves are pure or at which fewer than two samples are present in each leaf. Squared error was chosen as the function to measure the quality of split in this scenario. When utilizing the Ada Boost algorithm, the decision tree’s parameters were the same with the exception of the maximum depth, which was taken to be 3. Additionally, a parameter that indicated the number of boosting iterations—which was taken to be 100—was used. In the case of using the XGBRF Regressor algorithm, the number of iterations was also 100, the learning rate parameter was 1, and the division into subsamples was 0.8. For the Gradient Boosting Regressor model, the squared error was taken as the loss function, with a learning rate of 0.1, the target number of boosting stages to perform was 100, Friedman MSE was used as the function measuring the quality of the split, and the maximum depth of individual estimators was defined as 3.2; mean absolute error (MAE); and Root-Mean-Square Error (RMSE). Equations (4)–(6) represent the metrics previously described.To compare the performance of the models, the following metrics were used: coefficient of determination—RThe results of the cutting force and delamination factor analysis obtained in drilling for different types of GFRP samples are presented below.zF is the largest in the drilling process compared to other components (xF and yF), this section discusses the results of this component.Due to the fact that the share of the cutting force component zF as a function of the time t for sample A1, in a drilling process conducted with cv = 273 m/min and zf = 0.12 mm/tooth, is shown in zF  takes both positive and negative values. zF plays a major role in the drilling process. Other components of the cutting force xF and yF take lower values, which was confirmed by the research presented in [zF, and its value stabilizes over time due to full engagement of the cutting edges [zF due to fewer layers to be cut. In the exit zone, the tool exits the workpiece, which causes a decrease in the cutting force component zF. Periodic peaks can be observed in the force curve when the composite fibers are cut. zF course pattern.An example of the characteristics of the course of changes in the cutting force component ented in , which cng edges . This iszF and the technological cutting parameters in the drilling process of the four types of GFRP composites are presented in Results illustrating a relationship between the amplitude value of cutting force component cv and the cutting force component zF amplitude for four types of GFRP materials drilled with a constant feed per tooth of zf = 0.12 mm/tooth is shown in zF amplitude was obtained at the highest value of the cutting speed cv for material A1 and was equal to 309 N. The minimum value of 171 N was obtained for the A2 material at the cutting speed cv equal to 182 m/min. A comparison of the samples made of the same material but differing with the wf ratios of reinforced material reveals the following relationships. For almost every cutting speed value (except cv = 273 m/min), there is a noticeable decrease in the cutting forces component zF for the A2 material. For the cutting speed cv = 91 m/min, the difference in the zF values of the two materials is 16%, for cv = 182 m/min it is 38%, and for cv = 364 m/min it is 30%. This is due to the fact that for the A1 material containing a higher value of the weight fraction ratio of reinforced material, the forces needed to drill a hole and overcome the resistance of the fibers are higher than for the composite with a lower wf. An increase in the fiber volume fraction increases the thrust forces [zF for materials B1 and B2, taking into account the standard deviation, we cannot conclude that there are significant differences between the values obtained for these two materials characterized by different wf ratios of reinforced material.The relationship between different cutting speeds t forces . ConsidezF amplitude and different feeds per tooth zf in the drilling process for GFRP composites is presented in The relationship between the cutting force component zf on the cutting force component zF amplitude for different types of GFRPs. For each tested material, the amplitude of the cutting force component zF increases with increasing the feed per tooth zf. Other studies [zF were achieved for the lowest tested feed per tooth value of 0.04 mm/tooth for all tested materials , similar to in study [zf = 0.04 mm/tooth) and the highest feed per tooth (zf = 0.16 mm/tooth) demonstrates that the highest increase in the cutting force component zF amplitude (about 71%) was obtained for material A1, then for B2 (57%), and finally for B1 (34%), while it was the smallest for A2 . This means that the feed per tooth has the smallest impact on the cutting force component zF for the A2 material made of twill fibers and with a lower wf ratio of reinforced material. Increasing the feed rate increases the material removal rate (MRR) for all tested materials. The higher MRR means a higher volume to cut, which leads to higher friction because of the higher contact area between the cutting tool face and the workpiece causing the higher force. studies  also fouin study . A compacv and zf) in the drilling process for four types of GFRP composites are presented in Results illustrating the relationship between peel-up and push out delamination factors and certain technological cutting parameters (dF = 1.003) and B1 (dF = 1.017) materials with cv = 182 m/min. For these materials, an increase in the cutting speed (in the range cv = 182 ÷ 364) caused an increase in the delamination factor value by 8.87% for A2 and by 15.43% for B1. This is an almost linear increase, and similar to the findings reported in [cv = 182 m/min. For other cutting speeds for this material, the delamination factor values were comparable, ranging from 1.12 to 1.14. For the B2 samples, the peel-up delamination factor values were also comparable, ranging from 1.11 to 1.15. In case of the A1 material, we can clearly notice the influence of the wf ratio on the delamination factor. A1 characterized by a higher wf ratio of reinforced material causes the higher values of the peel-up delamination factor in the range of all cutting speeds.The relationship between the peel-up delamination factor and the cutting speed is presented in orted in , where azf and a constant cutting speed cv for different types of GFRP. The delamination factor values are the lowest for all the materials drilled with the lowest feed values . According to the diagram, the feed per tooth plays a significant role in the delamination factor for all GFRP samples, since the delamination factor increases with increasing the feed per tooth, which is consistent with the results reported in [orted in . A compaorted in .cv range of 91 ± 273 m/min, the push-out delamination factor increases, reaching the maximum at the cutting speed cv of 273 m/min first, and then, it begins to decrease. For the B2 material, this is an increase of 8.82% and for the B1 material of 6.52% (comparing the cutting speeds cv of 91 and 273 m/min). These materials are made of the same plain woven fiber but differ in the weight fraction ratio of reinforced material. We can therefore conclude that this is one of the indicators affecting delamination. For A1 and A2 materials, the increase in the push-out delamination factor is smaller and amounts to 4.03 and 4.23%, respectively . Therefore, it can be concluded that the A1 and A2 materials are characterized by lower delamination when the drilling process is conducted using a variable cutting speed.The data in 2 fibers, were characterized by the highest push-out delamination index, regardless of the adopted cutting parameters. This means that these materials are more susceptible to delamination in the tool exit zone. This is caused by the tool pushing out the last layers of the composite.A comparison of the results in Based on Since the delamination factor predominantly depends on the feed per tooth, in Based on the above images  capturedzf = 0.16 mm/tooth (d), where the introduced ink precisely colors the delamination range. For the holes photographed without ink, it is difficult to determine whether the different color of the sample is due to delamination or microscope illumination of the sample.Based on the images shown in 2; mean absolute error (MAE); and Root-Mean-Square Error (RMSE). The linear regression model had the lowest coefficient of determination (0.352), it also achieved the highest average absolute error of 24.05 and the highest Root-Mean-Square Error of 29.92. To compare the performance of the models, the following metrics were used: the coefficient of determination—R2 score of 0.860 with an RMSE of 13.89 and MAE of 10.87. In order to improve the performance of the model, the Ada Boost algorithm was used. This allowed for an improvement of the R2 score to 0.927 with a mean absolute error of 8.37 and RMSE of 10.07. The Decision Tree Regressor model achieved an R2 of 0.893 with an MAE of 10.16 and a Root-Mean-Square Error of 12.18. The XGBRF Regressor model achieved lower metrics than the previous models. This model has an RThe Gradient Boosting Regressor model has the best metrics values. It achieved the coefficient of determination of 0.948 with an MAE of 6.13 and RMSE of 8.46. A comparison of this model and the other ones is given in 2 score was greater than 0.5, an analysis of the importance of features was performed. The Ada Boost Regressor model among the tested models shows the least importance for the zf parameter, which is 0.42, and the XGBRF Regressor model assigned the highest importance of 0.61 for this parameter. The Gradient Boosting Regressor model assigned an importance value of 0.51 to the zf parameter, 0.18 to the cv parameter, and an importance value of 0.31 for the material type. The importance of features for the indicated models is shown in For the models presented in 2 score metric and the smallest MAE and RMSE metrics. In order to check that the model does not exhibit overfitting, the RMSE value curve for a given iteration is presented in The target model, Gradient Boosting Regressor, was selected due to the largest R2 score of 0.931, with an MSE of 6.10 and RMSE of 8.43.As can be seen from the chart presented above, the model does not show any tendency to overfitting. The feature value for both the training and test sets is minimized. In order to present the differences between the measurements and the values predicted by the Gradient Boosting Regressor model for the test set, a 3D chart was created . The GraThe novelty of this study consists of a method for determining delamination by introducing ink on the surface of the drilled hole in four types of GFRP samples and the study of the machinability of these materials. Since our study is the first to use the ink method for delamination determination and to test the machinability of these new GFRP materials, it fills the knowledge gap in this field. In addition, the optimal parameters of the drilling process ensuring reduced delamination were determined.The study investigated GFRP materials that were fabricated with different wf ratios using an epoxy matrix made by a special technique and specified machining parameters. These aspects have not yet been investigated from the point of view of delamination of the drilling process.The results of the study investigating cutting forces and delamination in GFRP drilling lead to the following conclusions:The new method for assessing delamination by applying ink on the surface of the drilled hole to penetrate the delamination area can be used for both peel-up and push-out delamination assessment. This method also allows for the easy identification of other damage modes, e.g., fiber pullouts, which may go unnoticed due to the color of GFRP composites;The method of assessing delamination by applying ink on the composite surface can potentially be used to assess elements of aircraft structures made of GFRP that have undergone, for example, mechanical damage in order to assess delamination and further qualify these parts for repair or replacement;The factor having the greatest impact on delamination is the feed rate; the higher the feed rate, the greater the delamination becomes. This mechanism can be related to the rise in the axial thrust force due to the expanding cross-sectional area, which also increased when the feed was increased;Push-out delamination has a greater range than peel-up delamination, regardless of the tested material;The push-out delamination factors were higher for materials from group B, regardless of the technological cutting parameters (feed per tooth and cutting speed). A comparison of the lowest and the highest feed per tooth values for materials A1 and B1 with different fiber types but the same weight fraction ratios of reinforced material demonstrated that the delamination factor increased by 18.11% for B1 and by 7.63% for A1. It has been found that delamination depends on the type of fabric used. The thicker the type of fabric and the thicker the threads are (threads made up of a larger number of monofilaments), the more pronounced the delamination becomes;zF in the drilling process primarily depends on the feed rate, rather than on the cutting speed. The amplitude of the cutting force component zF increases with the increasing feed per tooth zf;The cutting force zF were achieved for the lowest tested feed per tooth value of 0.04 mm/tooth for all tested materials . The cutting force was the highest for type B materials that also showed the highest push-out delamination factor;The lowest amplitude values of the cutting force component zF of about 71% was obtained for material A1, it was 57% for B2 and 34% for B1, while the lowest zF increase of 26% was obtained for A2. This means that the feed per tooth has the lowest impact on the cutting force component zF in the case of the A2 material made of twill fibers and characterized by a lower wf ratio of reinforced material;A comparison of the lowest and the highest values of feed per tooth demonstrated that the largest increase in the amplitude of the cutting force component Material A2 made of twill woven fibers, containing 45% of reinforced material, is characterized by the lowest delamination factor, regardless of the type of delamination and technological parameters applied in tests. This also indicates that delamination depends on the wf ratio of reinforced material on delamination;zF as a function of technological parameters. One of the potential applications of the Gradient Boosting Regression model in the industry is to predict the value of the zF parameter before starting the process, which will allow for optimizing the selection of cutting conditions from the point of view of its energy consumption and minimizing delamination processes. Knowledge of zF allows for predicting the occurrence of this phenomenon and controlling the process in such a way as to obtain the smallest possible defects in the holes made.The Gradient Boosting Regressor model has the best metric values from all analyzed models. It achieved the coefficient of determination of 0.948 with an MAE of 6.13 and RMSE of 8.46, which implies that machine learning techniques are a suitable tool for modeling the cutting force component Based on the obtained results, it can generally be concluded that lower cutting forces occur for type A materials made of twill type fibers, at lower feed per tooth values, and that these materials are also characterized by lower push-out delamination. The delamination detection method by introducing ink into the surface of the drilled hole is an effective method for assessing the damage to GFRP composites.Future studies can investigate the problem of delamination with respect to thinner or thicker layers of reinforcing material (with higher mass and thicker threads), the use of drill types with special geometry, different material thicknesses or matrix types, as well as process parameters of different manufactures. The conclusions of this study can be a simplifying hypothesis for other types of FRP having the same architectural arrangement of the layers and the same type of fabric or matrix. The authors also plan to conduct research on a new method of determining delamination using ink, by comparing its effectiveness with conventional methods of assessing delamination, so that it can be used in aviation to assess delamination of composite parts after mechanical damage.


Ligamentum teres (LT) has traditionally been considered a vestigial or redundant structure in humans; however, based on new studies and the evolution of hip arthroscopy, the LT injury has been viewed as a source of hip pain. Therefore, LT reconstruction can be beneficial in some cases. Rabbits have been frequently used as a model for cranial cruciate ligament reconstruction but few studies are available for ligamentum teres reconstruction.To evaluate the semitendinosus tendon to replace ligamentum teres with the toggle technique, using rabbits as an experimental model.Twenty-six female Norfolk rabbits with approximately 3 months of age were divided into two equal groups after excision of ligamentum teres (LT) from the right hip joint: G1—no reconstruction of LT and capsulorrhaphy; G2—double—bundle reconstruction of the LT using semitendinosus tendon autograft. In both groups, the LT was removed from the right hip joint. In G2 the autograft was harvested from the left hind limb of the same rabbit. The rabbits were evaluated clinically at different time intervals; before surgery (M1), 48 h (M2), 15 days (M3), 30 days (M4) and 90 days (M5) after surgery.The rabbits supported their limbs on the ground in both the groups. As complications of the procedure, four hip joints showed subluxations in the radiographic evaluation of G1; three at M4 and one at M5. In G2; two luxations of hip joints at M3 and one subluxation at M4 were seen. On ultrasound, irregular articular surface was seen in 30.8% of the rabbits that had subluxation of hip joints. Gross evaluation identified tendon graft integrity in 76.92% of the rabbits. Histological analysis revealed graft adhesion to the bone in the early phase comprised of sharpey-like collagen fibers.The double-bundle reconstruction of the LT using autologous semitendinosus tendon associated with the toggle rod shows an early phase of tendon graft ligamentization at 90 days post-operatively in young rabbits, but biomechanical bias suffered by the tendon during gait must be considered. In humans, the ligament of the femoral head or ligamentum teres (LT) has traditionally been considered a vestigial or redundant structure, with no biomechanical function or even vascularity, especially in the hip joint of adult individuals . BecauseThree groups of LT injuries have been determined based on arthroscopic analysis: complete rupture, usually associated with a traumatic episode or surgical procedure; partial rupture, seen in patients with a previous history of joint pain and degenerated ligament rupture associated with osteoarthritis . Some auOn the other hand, an increase in displacement of the hip joint was observed after splitting LT in animal models . Hip disRabbits have been frequently used as a model for cranial cruciate ligament reconstruction  but few Twenty-six female Norfolk rabbits, approximately 3 months of age, weighing from 1.6 to 2.9 kg were used. The animals were obtained from the experimental animal center (EAC) from Sao Paulo State University (UNESP), Botucatu Campus. The EAC is associated with the department of animal science—rabbits and bioterium animals from the same institution.The rabbits were randomly divided into two equal groups after a blood cell count (BCC) exam to evaluated previous health status: G1—no reconstruction of LT and capsulorrhaphy, G2—reconstruction of the LT using semitendinosus tendon autograft. Each rabbit was placed in an individual cage (60 × 60 × 60 cm) clear of the ground and with no restriction of movement, in an environment of approximately 27 °C temperature, controlled by exhaust fans and illumination for 12 h daily. The animals and the cages were identified with the number and the group of the rabbits. Environment was enriched with nipple-piped water, clay feed pot and banana tree leaf. Pinecone was given once a week. All the procedures of this study were executed in the Veterinary Hospital of UNESP.2 fraction (EtCO2) (multi-parameter monitor), non-invasive systolic arterial blood pressure (Doppler ultrasound), and rectal temperature .Rabbits were given ketamine  in combination with morphine  and midazolam  intramuscularly. Approximately 10 min after, epidural anesthesia was performed with 2% lidocaine . Then, rabbits were intubated for maintainance of anesthesia with isoflurane  by a certified anesthetist. Anesthesia monitorization comprised heart and respiratory rate, peripheral hemoglobin oxygen saturation, expired COIn G1, a craniolateral approach was used to approach the right hip joint. A partial tenotomy of the deep gluteal was done. The joint capsule was identified and incised along the ventral acetabular margin, taking care not to injure the cartilage. The LT was excised using a number 11 scalpel blade, and the femoral head was dislocated. After repositioning the femoral head in the acetabulum, the joint capsule was closed with a simple interrupted suture using polyglactin 910, in 5-0 size. A cruciate suture pattern was used to reattach the tendon of the deep gluteal muscle. The remaining closure was performed in a routine fashion.In G2, a 5 cm longitudinal incision was made in the medial aspect of the left hind limb, from the medial condyle of the femur to the medial malleolus. The semitendinosus tendon was identified, carefully dissected from the surroundings, and harvested for its whole length . The fasAfter harvesting, the tendon was folded into two equal parts . A loop In both groups, on induction of anesthesia and for 5 consecutive days after surgery enrofloxacin , tramadol chlorhydrate  and meloxicam  were administered subcutaneously.The rabbits were evaluated before surgery (M1), 48 h (M2), 15 days (M3), 30 days (M4) and at 90 days (M5) after surgery by using visual gait analysis (presence or absence of lameness and/or hopping motion) . For visExcept for M2, radiographic and ultrasound exams of the right hip joint were performed at the same time points. Radiographs were taken on extended ventrodorsal and right mediolateral projections. A digital radiography system  was used to obtain the images. The presence of hip dislocation or subluxation, toggle rod position, and signs of infection were assessed. Ultrasound  was used to assess joint capsule thickness, joint congruence, regularity of the articular surface, presence of osteophytes, and muscle organization. The images were obtained with an 8–13 MHz linear transducer. An experienced examiner evaluated the radiographic images and another one the ultrasound images.At 90 days after surgery, all rabbits were euthanized. For euthanasia, the rabbits were submitted to dissociate anesthesia with xylazine hydrochloride  and ketamine (50 mg/kg) administered in the same syringe intramuscularly. Subsequently, propofol  was used intravenously until the respiratory arrest, followed by 19.1% potassium chloride  intravenously until the cardiac arrest. All the animals from both groups were euthanized to achieve the comparison from both treatments in gross and histological examination, following the relevant statistic number of samples.In both groups the right hip joint was evaluated macroscopically for joint capsule thickness ; articular cartilage lesion of the femoral head  ; periartThe hip joint of the G2 was fixed in a 10% buffered formalin solution for 48 h followed by nitric acid solution until decalcification . NeutralThe body mass values were analyzed using Student’s t-test for independent samples.p < 0.05. Data were analyzed using Minitab statistical software.Statistical significance was set at There was no statistically significant difference in body mass between G1 (2 ± 0.4 kg) and G2 (2.2 ± 0.4 kg) . One rabIn the radiographic evaluation of G1, nine rabbits showed no complications  and 2B. The sonographic findings in G1 revealed that the joint surface had no irregularities in 69.2% of the rabbits. The irregular articular surface was seen in 30.8% of the rabbits that had subluxated hips. LT was not seen in M3, M4, and M5. Disorganization of the orientation of the muscle fibers was seen at M3 that improved at M4 and M5. Three rabbits with hip subluxation at M4 and one rabbit with hip luxation at M5 had thickening of the joint capsule at M5. In G2, the articular surface had no irregularities on ultrasound at M1. Disorganization of the orientation of the muscle fibers and two hip luxations were seen at M3. One hip subluxation with severe signs of osteoarthritis was observed at M4. Thickening of the joint capsule was detected in the two hip luxations, and in the one hip subluxation. Improved muscle fiber organization was seen at M5. The two hip luxations and the hip with osteoarthritis had irregular articular surfaces.The gross evaluation of G1 showed mild capsular thickness and mild remodeling of the femoral head in 30% and no alteration in 70% of rabbits. Articular cartilage lesions were classified as 23.1% of rabbits in Grade 0, 15.4% in Grade 1, 30.8% in Grade 2, and 30.8% in Grade 3, which also presented joint subluxation.The gross evaluation of G2 showed 53.8% mild, 46.2% moderate, and 15.4% intense capsular thickness. In addition, articular cartilage lesions were classified 30.8% rabbits in Grade 1, 38.4% Grade 2, and 30.8% Grade 3. Two rabbits with Grade 3 (15.4%) had hip luxation due to graft failure (resorption or toggle rod displacement). The integrity of the tendon graft  was veriHistological analysis revealed characteristics of the early phase of tendon graft ligamentization with widely diffuse and homogeneous multifocal areas of collagen fibers, consistent with sharpey fibers at the tendon-bone interface . The fibThe present study showed that the semitendinosus tendon graft may be used to replace LT using the toggle-rod technique; however, some complications were encountered. The LT was chosen due to the ease of harvest, length, and minimal donor site morbidity. The grafts of LT, semimembranosus tendon and patellar ligaments are the most commonly used in rabbits, especially for replacing the cranial cruciate ligament . LT is mThe tendon allograft was prepared using a double-bundle technique, similar to that described for LT replacement in human patients . HoweverThe visual gait analysis did not help to detect complications, since rabbits presenting hip luxation (G2) did not show lameness. On the other hand, non-weight bearing lameness was observed in a pet rabbit with hip luxation that was solved after using a toggle pin and nylon suture .n = 4). Hip luxations (n = 2) and subluxation (n = 1) found in G2 were due to toggle-rod displacement. Studies in dogs and cats using different types of toggle rods and suture material to replace the LT have also reported complications, including luxation, premature rupture of the suture, toggle rod pullout or breakage, and infection  had periosteal collagen fibers (sharpey’s fibers). In one study of rabbits with intraarticular semitendinosus autograft positioned through tibial and femoral holes observed the blending of the graft to the fibrous connective tissue over time that adhered to bony trabeculae . HealingThe joint capsule fibers had preserved architecture on histology. A biomechanical study did not detect differences between hip capsulorrhaphy in block suture whipstitch technique with polyglycolic acid or titanium anchors in rabbits . CapsulaThe present study has some limitations. The surgical approach to the hip joint required a longer incision for optimal exposure of the femoral head that contributed to postoperative hip luxation; however, an arthroscopic surgical procedure in the rabbit hip joint is technically difficult and semitendinosus graft length allows only the double-bundle technique. Thus, reconstruction needs to be tested with other tendon grafts.The double-bundle reconstruction of the LT using autologous semitendinosus tendon associated with toggle-rod shows an early phase of tendon graft at 90 days post-operatively in young rabbits. The potential for complications, such as femur fracture and graft/toggle failure, does exist and should be the focus of future studies.10.7717/peerj.14777/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.14777/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.14777/supp-3Supplemental Information 3Values in Group 1 and Group 2.Click here for additional data file.


Ruminiclostridium cellulolyticum, cellobiose is imported by the CuaABC ATP-binding cassette transporter containing the solute-binding protein (SBP) CuaA and is further degraded in the cytosol by the cellobiose phosphorylase CbpA. The genes encoding these proteins have been shown to be essential for cellobiose and cellulose utilization. Here, we show that a second SBP (CuaD), whose gene is adjacent to two genes encoding a putative two-component regulation system (CuaSR), forms a three-component system with CuaS and CuaR. Studies of mutant and recombinant strains of R. cellulolyticum have indicated that cuaD is important for the growth of strains on cellobiose and cellulose. Furthermore, the results of our RT-qPCR experiments suggest that both the three (CuaDSR)- and the two (CuaSR)-component systems are able to perceive the cellobiose signal. However, the strain producing the three-component system is more efficient in its cellobiose and cellulose utilization. As CuaD binds to CuaS, we propose an in-silico model of the complex made up of two extracellular domains of CuaS and two of CuaD. CuaD allows microorganisms to detect very low concentrations of cellobiose due to its high affinity and specificity for this disaccharide, and together with CuaSR, it triggers the expression of the cuaABC-cbpA genes involved in cellodextrins uptake.In  Cellulose is a renewable material and the most abundant polymer on Earth. Its degradation into mono/oligosaccharides by cellulolytic bacteria is a process of interest for many biotechnological purposes involving the conversion of cellulose into valuable chemicals. Cellulose is made up of chains of glucose units linked through β-1,4 glycosidic linkages. These chains are packed together to form crystalline fibers, making cellulose recalcitrant to enzymatic degradation. In plant cell walls, the release of glucose units from cellulose is therefore a challenging step. Specialized cellulolytic organisms secrete cellulases which allow them to grow on cellulose as their sole source of carbon and energy. In the case of many anaerobic cellulolytic clostridia, cellulases and related enzymes necessary for the degradation of other plant cell wall polysaccharides are gathered in multi-enzymatic complexes called cellulosomes ,3,4.Ruminiclostridium cellulolyticum . As. AsKD 20cuaSR leads to the slower growth of the strain on both cellobiose and cellulose. The continuation of the growth of this strain might be due to the expression of cuaABC and cbpA, which remains possible even in absence of CuaD, as revealed by the qRT-PCR and Western blot results. The expression of these genes could be explained by the overproduction of CuaS and CuaR, which might disturb the signaling pathway. Another explanation is the sensing of cellobiose by the sensor directly, as shown by the analysis of the expression level of the cua genes in the transformed mutant strains. However, this interaction between CuaS and the cellobiose is probably weak, and the signal transmission seems to be less efficient than that with the participation of CuaD. This was shown by the growth results of the recombinant strains producing the complete system.In summary, our results indicate that the three-component system is better adapted for the utilization of cellobiose and cellulose than the incomplete two-component system. Indeed, the absence of CuaD in the signaling system of the mutant strain containing the vector pSOScuaABC-cbpA gene induction.CuaD, CuaS, and CuaR thus form a three-component system in which the interaction of CuaD with its ligand triggers a regulation event through its interaction with CuaS. Several three-component systems, including a solute-binding protein (SBP) that interacts with a two-component system, have been described so far ,12,31,32Vibrio cholera and citrate import in Bordetella pertussis, only one SBP is encoded which is involved in both transport and signaling [Clostridium beijerinckii and Geobacillus stearothermophilus, both of which manage carbohydrate import, two SBPs are encoded as is the case for the cua system of R. cellulolyticum [KD of 20 nM) and high specificity to cellobiose. CuaA (the SBP for transport), on the other hand, binds to cellobiose and longer cellodextrins with sizes up to that of cellopentaose with lower affinity. These differences are supported by our modelling studies. Further information on ligand/protein interactions may be obtained in future molecular dynamics studies. With CuaD assisting CuaS, this three-component system might specifically detect very low concentrations of cellobiose and induce the expression of the genes dedicated to the import and metabolization of cellodextrins through the action of the regulator CuaR. Cellodextrins are efficiently imported by the CuaABC transporter during their growth with cellulose [cuaABC-cbpA genes during growth. Cellobiose induces the expression of the operon cuaABC-cbpA, which is consistent with the fact that cellobiose is the most abundant degradation product of cellulose released by cellulosomes [Among the three-component systems reported in the literature, four of them control the expression of genes encoding components of transporters ,31,32,33ignaling ,33. In tolyticum ,31. The ellulose . This efulosomes . In addi