We observed significantly reduced cell numbers of circulating iNKT cells, NKTL cells and γδ T cells in cerebral ischemia patients as compared with the healthy controls. Of note, we also demonstrated that numbers of peripheral blood iNKT and γδ T cells are significantly reduced in patients with ACI when compared among different cerebral ischemia patient groups. Moreover, the reduced number of iNKT cells is significantly associated with the disease severity and recovery in cerebral ischemia patients. Our results demonstrate for the first time the reduction of peripheral blood NKTL, iNKT and γδ T cells in patients with the cerebral ischemia, and particularly reduced iNKT and γδ T cells in the acute phase. The reduction of iNKT cells seems to be significantly associated with the disease severity and recovery. We hope that our findings might lead to the identification of predictive and prognostic values of human peripheral unconventional T cell subsets in the cerebral ischemia.Immune reactions provoked by cerebral ischemia play crucial roles in the pathogenesis of brain damage and contribute to tissue regeneration processes. While functions of many immune cell types in post-ischemic inflammation have been well studied in experimental stroke, the exact roles played by unconventional T cells in pathogenesis of the clinical stroke remain to be precisely determined. In the present study, we investigated the frequencies and absolute cell numbers of peripheral blood T lymphocyte subpopulations including those of invariant natural killer T (iNKT) cells, CD3 Although tremendous efforts have been elaborated in attempt to understand the pathologic processes underlying the IS, it remains to be thoroughly investigated regarding the prevention, early diagnosis, and treatment of IS.Ischemic stroke (IS) is one of the leading causes of death and disability worldwide, with a high incidence and recurrence rate in aged population3. It is reported that changes in composition and numbers of immune cells are not only present in brain, but also observed in peripheral sites during IS4. Activation and re-distribution of immune cells occurs shortly after the cerebral ischemia. Microglia in the central nervous system (CNS) and peripheral immune cells, including monocytes/macrophages, neutrophils and lymphocytes, are recruited into the ischemic cerebral hemisphere that are thought to induce local inflammatory responses6. It is now well accepted that the peripheral immune cells infiltrating the post-ischemic brain play an essential role in pathophysiology of stroke and contribute to secondary neuro-degeneration8. The long-lasting immunological communication between brain and periphery seems to result in extremely complex effects on the progression of ischemic brain injury and the following tissue regeneration processes10. It is reported that among various T cell populations recruited to the stroke brain in addition to the conventional CD4 T cells11 and CD8 T cells12, the unconventional T lymphocytes such as γδ T cells13, regulatory T cells (Treg)14, as well as natural killer T (NKT) cells15 play important roles in IS pathology. While functions of peripheral immune cells in post-ischemic inflammation were well studied using animal models of the experimental stroke, their roles in the pathology of the clinical stroke remain to be investigated.Immune reactions followed by cerebral ischemia play a critical role in the pathogenesis of tissue damage caused by IS. To date number of studies on murine models of the experimental cerebral ischemia have described different lymphocyte subpopulations that play diverse roles during the pathogenesis of IS16, Parkinson’s Disease17, as well as spinal cord injury18. These changes usually correlate with disease severity and are considered to be predictive for above-mentioned pathologies. Acute ischemic stroke (AIS) was reported to correlate with the peripheral immune depression20, and the stroke prognosis and outcomes were also linked to changes of circulating peripheral lymphocyte cell numbers22. However, it should be noted that the limitation of most of studies was a small sample size and mainly focused investigation on the AIS. In addition, although changes of conventional T cell subsets during the clinical stroke were well-studied, it still needs to be investigated regarding alterations of unconventional T cell subpopulations in peripheral blood of stroke patients and their association with disease outcomes.Alterations in the composition of peripheral immune cell subsets have been reported in several central nervous system (CNS) disorders, such as multiple sclerosis+CD56+ NKT-like (NKTL) cells, and γδ T cells in the peripheral blood of patients with acute cerebral infarction (ACI), chronic cerebrovascular disease (CCD), and chronic cerebral circulation insufficiency (CCI), and analyzed their association with the disease severity and outcomes. Our findings will hopefully provide evidence that could be useful in identifying predictive and prognostic values of peripheral immune cells in the clinical cerebral ischemia.In the present study, we assessed the frequencies and absolute cell numbers of unconventional T cell subpopulations, including invariant NKT (iNKT) cells, CD323 and Barthel Index scores24 were recorded on patient admission and discharge. The exclusion criteria were: (1) age ≥ 80; (2) severe heart and lung dysfunction; (3) allergies; (4) known inflammatory disease or systemic infections; (5) cancer; (6) hematology diseases; (7) immune compromised diseases; (8) diseases of the connective tissue; (9) undergoing steroid or immunosuppressive therapies. The study protocol was approved by the ethics committee of the Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, China. All participants gave fully informed consent directly or through a surrogate when appropriate.Study participants were consecutively recruited from August 2017 to May 2019 from inpatients in the Department of Neurology who were diagnosed with acute cerebral infarction , chronic cerebrovascular disease , or chronic cerebral circulation insufficiency , and the healthy controls (HC) who underwent a routine health checkup procedure at the Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, China. Cerebral ischemia was diagnosed according to World Health Organization stroke criteria. National Institutes of Health Stroke Scale (NIHSS)+, CD19−), iNKT cells , NKTL cells , γδ T cells   used for flow cytometry detection were: PE anti-CD3, APC anti-TCR Vα24-Jα18, APC anti-CD56, FITC anti-TCR γδ, Percp anti-CD19. Samples were analyzed with Mindray BriCyte E6 (Mindray). Immune cell subpopulations analyzed in this study were defined as follows: T cells . The ordered logistic regression adjusting for subjects’ age and sex was performed to test the association of cell subsets with disease severity measured by NIHSS and Barthel Index scores. As the cell count and percentage were highly correlated, we have performed the regression separately for the cell count and percentage. All the subjects provided the written consent, and the study protocol was in accordance to the Declaration of Helsinki and was approved by the institution review board (IRB) of Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, China.P > 0.05). Among the patients, the mean age of ACI, CCD, and CCI groups were 62.0 ± 11.3, 64.4 ± 9.9 and 53.4 ± 10.7 years old, respectively, where significant differences among the three stroke groups were observed (P < 0.05). Of note, the CCI group had the lowest mean age and significantly lower than ACI and CCD groups (both P < 0.05), however there is no significant difference between ACI and CCD group in age (P > 0.05). Significant differences in gender among the three stroke groups were also observed (P < 0.05), of which only significance between ACI and CCD group was detected. There was no significant difference in the prevalence of comorbidities between patient and HC groups (P > 0.05). Among the three patient groups, significant differences in smoking, hypertension, and diabetes were detected (P < 0.05) , 106 with chronic cerebrovascular disease (CCD), and 34 with chronic cerebral circulation insufficiency (CCI), as well as 62 healthy controls (HC) were recruited in the present study. The demographic and clinical characteristics of all study participants are summarized in Table P < 0.05). Lower Barthel index was also recorded in ACI group, both at the admission and discharge (80(0–100) and 90(0–100), respectively) (P < 0.05)  and Barthel Index. The NIHSS scores of ACI group at admission and discharge were 5(0–35) and 2(0–35), respectively, which were significantly higher than those of CCD and CCI groups (rge (800–00 and 90P < 0.046), while there was no significant difference in the cell number and proportion of total T lymphocytes between patients and HC groups (P > 0.05)  Table .Table 2PP = 0.009 vs CCD, and P = 0.004 vs CCI)  (Table P = 0.004) and frequencies (P = 0.02) of γδ T cells compared to the CCD group  Table a and perI) Table b in the s P = 0.0 of γδ T P > 0.103), negative correlation of iNKT cells with age (P < 0.01), and positive correlation of γδ T cells with gender  (P < 0.05). Therefore, we next tested the association of iNKT and γδ T cells with the acute phase of cerebral ischemia using an ordered logistic regression model with the age and sex adjustments to exclude the influence of these factors. As shown in Table Since we observed significantly decreased iNKT and γδ T cells in patients with ACI when compared among patient groups, however, significant differences in age, gender, as well as comorbidities including smoking, hypertension and diabetes were also observed among patient groups. In order to clarify whether iNKT and γδ T cells are associated with the acute phase of cerebral ischemia, we firstly performed linear regression analysis to test the association of age, gender, as well as comorbidities  with iNKT and γδ T cells in all of patients. We found no correlation of iNKT and γδ T cells with smoking, hypertension and diabetes P > 0.10, negativP = 0.036) and discharge  in all patients with cerebral ischemia. On the contrary, no significant association with NIHSS scores was observed for the rest of peripheral cell subpopulations. In addition, there was also no significant correlation for all of the three T cell subsets with the clinical severity of cerebral ischemia estimated by the Barthel Index.Furthermore, we examined whether peripheral iNKT, γδ T, and NKTL cells are associated with the disease severity of cerebral ischemia using an ordered logistic regression model with the adjustments of age and sex. We found the cell counts of peripheral iNKT cells to be negatively associated with NIHSS scores at admission    or absence (NIHSS score = 0) of neurological impairment at admission. Results showed significantly decreased iNKT cell counts in patients with impaired neurological functions (NIHSS score > 0) (28) Fig. a. In addP = 0.015 and 0.004 for cell frequency and cell count, respectively). These results suggest that the reduced numbers of peripheral iNKT cells in cerebral ischemia patients might be associated with the disease severity and recovery.Next, we grouped patients with the NIHSS score > 0 at admission into two groups according to NIHSS scores at discharge focusing whether their scores were improved or not, and then assessed the cell counts and frequencies of iNKT cells between the two patient groups. As shown in Fig. 9. It is now generally accepted that T cells contribute to the pathogenesis of many neurological diseases by inducing innate or adaptive immune responses. In particular, unconventional T lymphocyte subsets such as iNKT and γδT cells were shown to play important roles in the immune regulation that act mainly by bridging the innate and acquired immune responses26. Emerging studies using animal models of the experimental stroke suggest presence of a link between unconventional T lymphocyte subsets and the IS pathology. In this regard, it was reported that γδ T cells contribute to stroke damage by their production of IL-17 in an IL-23-dependent manner in tMCAO13, and NKT cells, including iNKT and NKTL cells were found to infiltrate into the ischemic brain of tMCAO and pMCAO mouse models27. However, it should be noted that precise roles of unconventional T cell subtypes in human cerebral ischemia remain unclear. In the present study we demonstrate that cerebral ischemia patients possess significantly reduced numbers of circulating iNKT cells, NKTL cells and γδ T cells when compared with the healthy controls. Of note, we also demonstrated that peripheral blood iNKT and γδ T cell numbers are significantly reduced in patients with ACI when compared among cerebral ischemia patient groups. Furthermore, peripheral blood iNKT and γδ T cell counts appears to be negatively correlated with ACI, which might imply to the possibility of accumulating of these cells to the damaged areas in the CNS of cerebral ischemia patients. Thus, our results strongly suggest the possible involvement of NKT and γδ T cells in the cerebral ischemia pathogenesis, particularly in the AIS.Post-ischemic immune reactions play essential roles in the progression of ischemic brain injury and tissue regeneration processes28, we have investigated the correlation of peripheral T cell subsets with the clinical severity of the cerebral ischemia. Our results demonstrate that the cell counts of peripheral iNKT cells are negatively associated with the clinical severity of the cerebral ischemia estimated by NIHSS scores at admission and discharge. Moreover, our data indicate that patients with impaired neurological functions and activity of daily living show significantly decreased numbers of iNKT cells . We also observed that the patients with unimproved NIHSS scores at discharge have significantly lower numbers and frequencies of peripheral blood iNKT cells than those patients with improved scores at discharge, which suggests that the reduced numbers of peripheral iNKT cells in cerebral ischemia patients might be associated with the disease severity and recovery. Our present results might imply for the possibility of iNKT cells to be used as a monitoring or prediction index for the treatment of the cerebral ischemia patients.Since we observed significant differences in iNKT and γδ T cells among different phases of the cerebral ischemia and since altered numbers and functions of circulating lymphocytes are known to be associated with the stroke outcome25, the precise role of iNKT cells in cerebral ischemia could be immensely complex and diverse. Some conflicting results derived from animal experimental models were reported regarding the role of iNKT cells on severity of the cerebral stroke. Using pMCAO mouse model, Wang et al. reported that α-galactosylceramide  activated iNKT cells contribute to brain infarction through their increased pro-inflammatory cytokine production15. In contrast, a minor role for iNKT cells in the brain infarction after tMCAO was reported using CD1d-deficient mouse that lacks both CD1d-dependent Vα14 invariant and variant NKT cells. In addition, it was also reported that the selective production of Th2-type cytokines by NKT cells prevents mice from post-stroke infections30. To date, although there is scarce information regarding human iNKT cell involvement in the cerebral stroke, it was proposed that activated iNKT cells induced by the stroke might relinquish an immunosuppressive response by releasing the immunosuppressive cytokine IL-1031. However, it should be pointed that correlation of iNKT cells with the disease severity was not addressed in the above-mentioned study, and their data on unchanged numbers of circulating iNKT cells seems to be inconsistent with our data demonstrated in the present study. The possible explanation for these seemingly contrary conclusions might be related to the sample size differences, where smaller sample size was applied in the report by Wong et al.31, and to the difference in patient selection criteria, where, in contrast to patients selected by Wong et al.31, patients with manifestations of infection were excluded from our present study.As iNKT cells are known to directly regulate immune responses through their rapid and massive production of a wide range of cytokines, or indirectly through their regulation of other immune cell types, and as iNKT cells can be further divided into functional subgroups based on their cytokine producing characteristicsAs an observational study, our work does not provide mechanistic insights into the roles of unconventional T lymphocyte subpopulations such as iNKT and γδ T cells in the development of cerebral ischemia. Nonetheless, we believe our results warrant the necessity for further investigations aimed to study the precise roles of different functional subsets of iNKT cells or γδ T cells both in human cerebral ischemia and in animal models. We also believe our findings will hopefully stimulate the research area bringing into attention the importance of studying unconventional T-lymphocytes in the pathogenesis of central nervous system disorders.In summary, this is the first study to characterize the profiles of circulating unconventional T lymphocyte subpopulations in patients with different phases of cerebral ischemia. Our results demonstrate for the first time the reduction of peripheral blood NKTL, iNKT and γδ T cells in patients with the cerebral ischemia, and particularly reduced iNKT and γδ T cells in the acute phase. The reduction of iNKT cells seems to be significantly associated with the disease severity and recovery in cerebral ischemia patients. In summary, our findings derived from detailed flow cytometric analyses of peripheral blood immune cell subpopulations might provide important insights which could be useful in identifying predictive and prognostic values of the cerebral ischemia.Supplementary Information.


Pure red-cell aplasia (PRCA) is a syndrome associated with reduced erythroid precursors. This report presents the case of an elderly PRCA patient with significantly proliferated γδT cells and clonal T-cell receptor (TCR) gene rearrangement. The cause of this patient’s PRCA was confirmed to be an autoimmune disorder rather than malignancy on the basis of flow cytometry, TCR gene rearrangement, and positron emission tomography/computed tomography (PET/CT) findings. Moreover, the γδT cell group identified in this case was captured for the first time under the microscope; this CD4+/CD8− (extremely high CD4/CD8 ratio) population is rare in PRCA patients. Our patient with a monoclonal and polyclonal hybrid of TCR gene rearrangement was sensitive to cyclosporin A (CsA), despite previous reports suggesting that patients with TCR clonal rearrangement may respond poorly to this drug. Overall, this case presents valuable clinical findings for the future diagnosis and management of PRCA caused by autoimmune conditions and further research on γδT cells’ autoimmune pathophysiology and gene rearrangement. Pure red-cell aplasia (PRCA) is a rare disorder and one cause of severe normochromic and normocytic anemia. PRCA can be congenital or acquired. Acquired PRCA can result from autoimmune disorders with or without lymphoproliferative disorders, exposure to certain drugs, and infections, particularly human parvovirus B19 , 3. γδT The present report describes the case of a 77-year-old PRCA patient who presented with fatigue, dizziness, syncope, and skin itchiness. A significant proliferation of multiclonal γδT cells was identified in the patient’s bone marrow and peripheral blood. PRCA cases with CD4+/CD8− (extremely high CD4/CD8 ratio) γδT cells were rare in previous reports –3. TCR g12/L , and reticulocyte fraction was 0.34% . The white cell count was 3.3 × 109/L , and the platelet count was 181 × 109/L . The patient was immediately transfused until his symptoms resolved. When questioned about his history, the patient reported 6 months of recurrent fatigue, dizziness, syncope, and skin itchiness. Anemia was first noticed in him 1 year prior with a hemoglobin level of 99 g/L and a red cell count of 2.58 × 1012/L, but he did not report any dizziness or syncope at that time, and no treatment was provided.A 77-year-old male patient visited the emergency department of our hospital on 11 September 2020 due to recurrent syncopal episodes. At the time of review, he was afebrile and showed no signs of cardiovascular diseases, such as abnormal heart sounds. Other physical examinations showed pallor with no bleeding or bruises, lymphadenopathy, hepatosplenomegaly, or jaundice. The patient’s hemoglobin level was 37 g/L , red cell count was 0.9 × 10The patient had multiple presentations in the subsequent 3 months with recurrent fatigue, dizziness, and syncope. He continued to show low hemoglobin levels (lowest at 25 g/L). Transfusion was ordered as immediate management, and the causes of his anemia were screened. The patient tested negative for human parvovirus B19, cytomegalovirus, human immunodeficiency viruses, hepatitis C virus, hepatitis B virus, and Epstein–Barr virus. His vitamin B12, folate, and iron levels were normal, and he was negative for autoantibodies (including the anti-erythropoietin antibody).Bone marrow aspiration was then ordered. The bone marrow aspirate smear showed an absence of erythroblasts with normal distribution and differentiation of other hematopoietic lineages. PRCA was thus diagnosed. T-cell lymphoproliferative disorders were screened due to the negative results in the aforementioned investigations. T-cell receptor (TCR) gene rearrangement testing  of the bone marrow samples and flow cytometry analyses of the peripheral blood and bone marrow were conducted.Flow cytometry revealed the proliferation of γδT cells in the peripheral blood and bone marrow, accounting for 14.075% and 11.162% of all nucleated cells, respectively S2. The Consistent with the aforementioned flow cytometry results and TCR rearrangement, a characteristic population of lymphoid cells was found in the peripheral blood and bone marrow smears . One month later, the follow-up blood test revealed that the patient’s hemoglobin level was 60 g/L, his red cell count was 1.52 × 10This brief report describes a PRCA patient with benign γδT cell proliferation and complex clonal TCR rearrangement in whom CsA corrected skin symptoms and hemoglobin levels. The main points of this interesting case are as follows. First, in this case, the γδT cell group associated with erythropoiesis suppression had unique morphological features and was captured for the first time under the microscope. In addition, this CD4+/CD8− (extremely high CD4/CD8 ratio) population is rare in PRCA patients. Second, our findings reveal the possibility that some PRCA patients may have clonal TCR rearrangement without a detectable malignant lymphoproliferative disease, and they are expected to respond to CsA with a good prognosis.via systematic exclusion of various alternative etiologies. The reasoning and techniques throughout the diagnostic process of our case were instructive and provided insights into the future diagnosis of PRCA patients and the underlying cause of the disease.PRCA is a bone marrow failure with a marked reduction in erythroblasts caused by a T-lymphocyte-mediated autoimmune attack on erythropoietic stem cells . No exisInsufficient bone marrow erythropoiesis was highly suspected because of low reticulocyte levels and the exclusion of common causes of anemia. Bone marrow aspirate is the gold standard for PRCA diagnosis, while revealing the underlying cause of the disease is a process of exclusion. Human parvovirus B19, anti-erythropoietin antibodies, and thymoma were all excluded from investigations. Flow cytometry is a sensitive and specific technique that can identify any significant increase in a certain cell population and should be regarded as a norm for exploring PRCA causes. The significantly reduced level of this same group of γδT cells in the flow cytometry results after CsA treatment, together with the improved anemia and skin symptoms, confirmed the hypothesis that this group of proliferated γδT cells caused the patient’s PRCA.Skin itchiness is a clinical sign that deserves more attention in practice, especially when observed in a PRCA patient or, more generally, a patient at risk of autoimmune or lymphoproliferative disorders. Skin itchiness is a potential sign of γδT cell proliferation in these patients. This assumption is further supported by skin irritation or inflammation commonly reported in cases of γδT cell proliferation or lymphoma; these cells reside in the skin tissue and play autoimmune roles when their homeostasis is disrupted . HoweverThe γδT cells responsible for the patient’s disease were an atypical subtype. The most reported type of γδT cells in lymphoproliferative disorders that cause PRCA is large granular lymphocyte (LGL) , whose mThere are several possible mechanisms by which this observed group of γδT cells is associated with erythropoiesis suppression. The most discussed theory is the disrupted balance between the proliferated innate immune cells and the physiological downregulation of HLA class I antigen on red-cell progenitors. The cells proliferated in our case were positive for CD94, one of the killer-cell inhibitory receptors (KIRs) that causes MHC-unrestricted cell death and only spares cells with adequate HLA class I antigen . AlthougTCR clonal rearrangement is generally seen in malignant lymphoproliferative diseases but is also found in patients with Epstein–Barr virus infection, autoimmune diseases, immunodeficiency, and bone marrow transplantation . RearranThis rare case of PRCA in an elderly patient with benign proliferative γδT cells and clonal TCR rearrangement provides new insights into the diagnosis and management of PRCA in patients through flow cytometry and gene rearrangement in investigations. Furthermore, for PRCA cases in which a group of benign γδT cells is confirmed responsible, the number of these cells before and after treatment can provide a new basis for therapeutic efficacy and monitoring. However, more evidence on the specific mechanism by which this unique cell subset causes PRCA is needed.The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.The studies involving human participants were reviewed and approved by The Medical Ethics Committee of The Second Affiliated Hospital, College of Medicine, Zhejiang University. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.XL, XYZ, and WW contributed to the design and conception of the study. XL and XYZ contributed to data collection. XL contributed to writing the initial drafting of the manuscript. XHZ and WW reviewed and edited the original draft. All authors contributed to the manuscript revision and read and approved the submitted version.


Objectives: To determine the metabolic effects of cancer-conditioned media on myotube metabolism and to understand whether the variability of these effects is associated with cancer cachexia progression.Materials and methods: We established single-cell clones from murine Lewis lung carcinoma (LLC) cells and generated conditioned media from each clonal line. Differentiated primary mouse myotubes were incubated with conditioned media derived from each individual clonal cell line. After initial analysis, we selected a specific LLC clonal cell line that failed to induce metabolic stress in myotubes for further investigation in vitro and in vivo.Results: Short-term incubation with conditioned media from 10/34 LLC clonal cells failed to affect oxygen consumption rate (OCR) in myotubes. Incubation with parental LLC-conditioned media decreased protein content and changed the expression of key regulators of muscle function in myotubes, but the incubation of conditioned media from a selected clone that failed to affect OCR in myotubes also did not affect protein content and expression of muscle regulators. Mice injected with parental LLC cells had a significantly reduced body mass and muscle wasting compared to the mice injected with cells derived from this selected LLC clone.Conclusion: Factors secreted by LLC cells induce metabolic stress in primary myotubes and induce cancer cachexia in mice. However, a selected clonal LLC cell line that failed to induce metabolic stress in myotubes also promoted weaker catabolism in mice. These novel findings establish that early disruption of muscle oxidative metabolism is associated with cancer cachexia progression. Cancer cachexia is characterized by progressive skeletal muscle wasting and is associated with a poor prognosis in several cancer types . HypermeHere, we applied a combination of cell cloning and extracellular flux experiments to determine the metabolic effects of cancer-secreted factors directly in myotubes. Since the progression of cancer cachexia is usually a heterogeneous process, we have established multiple clonal cell lines from Lewis lung carcinoma (LLC) and B16-F10 melanoma (B16) cells, which are two models commonly used to study cancer cachexia in mice . Our maiThis study was approved by the Ethical Committee of the School of Physical Education and Sport at the University of Sao Paulo and by the Joslin Diabetes Center Institutional Animal Care and Use Committee (IACUC). All procedures were performed in accordance with NIH guidelines. Primary mouse myoblasts were isolated and differentiated into myotubes as previously described . B16 andHprt expression, which showed similar Ct values across samples. Primer sequences are Hprt F: AGTCCCAGCGTCGTGATTAG; Hprt R: TTTCCAAATCCTCGGCATAATGA; Fbxo32 F: TCAGAGAGGCAGATTCGCAA; Fbxo32 R: GGGTGACCCCATACTGCTCT; MyoD F: CGGGACATAGACTTGACAGGC; MyoD R: TCGAAACACGGGTCATCATAGA; Ppargc1a F: TGATGTGAATGACTTGGATACAGACA; Ppargc1a R: GCTCATTGTTGTACTGGTTGGATATG.Oxygen consumption rate (OCR) was measured in myotubes using extracellular flux analysis  in sodium bicarbonate-free DMEM supplemented with 31.7 mM NaCl, 10 mM glucose, and 2 mM glutamax (pH 7.4 adjusted using NaOH). Protein content was determined with Pierce™ BCA Protein Assay Kit . Reduction of the MTS tetrazolium compound was determined with CellTiter 96 AQueous One Solution Cell Proliferation Assay (MTS) . To determine the expression of key regulators of muscle function, RNA was isolated, reverse transcribed and amplified as previously described . For eacin vivo experiments, twelve‐week‐old male C57BL/6 mice were used. Mice were injected subcutaneously with 105 LLC cells diluted in serum-free DMEM medium as previously described . One-way analysis of variance (ANOVA) was used to compare groups followed by Fisher’s least significance difference test whenever significant effects were found in ANOVA. Statistical significance was set at We have previously demonstrated that short-term exposure to LLC-conditioned media increases basal OCR in primary myotubes . Here, wAs an additional metabolic parameter, we evaluated the reduction of the MTS tetrazolium compound, which is produced by dehydrogenase enzymes in the presence of NADPH or NADH in metabolically active cells. Incubation with parental LLC-conditioned media remarkably increased the reduction of MTS tetrazolium. However, incubation with LLC-conditioned media derived from clone #10 showed similar values to the controls . NeitherFbxo32 (Atrogin-1), MyoD, and Ppargc1a   with parental LLC-conditioned media decreased total protein content in myotubes, suggesting cell death and/or muscle atrophy over time . However1-alpha) . While ise genes . Taken tin vivo, we compared the effects of subcutaneous injections of clonal LLC line #10 and parental LLC cells in wild-type mice. Both cell lines generated solid tumors in mice and there was no difference between groups in tumor growth at 21 days post injection , a time point at which we do not observe cell death. Our single clone approach demonstrates that some LLC clonal lines lose the capacity to produce those factors that affect myotube metabolism. A similar approach was previously performed by another group to study the effects of tumor-derived factors primarily in adipose tissue and they demonstrated variability in the effects induced by different LLC clones . Our datAtrogin-1 levels and a drastic decrease in MyoD levels. Atrogin-1 is a E3 ubiquitin ligase induced in catabolic states (MyoD is a regulator of skeletal muscle differentiation downregulated in a pro-inflammatory environment such as cancer cachexia (in vitro and in mice.In this study, a selected clonal LLC cell line that failed to induce metabolic stress in myotubes also promoted weaker catabolism in myotubes and in mice, indicating that disruption of muscle oxidative metabolism is associated with cancer cachexia progression. Additional indicators of myotubes atrophy include a 3-fold increase in c states  and MyoDcachexia . These ccachexia , fatty acachexia , microvecachexia , and othcachexia  and PTHrcachexia . In thisWe performed a similar approach using the B16 cell line that was previously found to not affect basal OCR in primary myotubes . We hypoIn summary, by conducting experiments with single clones derived from the LLC cells, we demonstrate for the first time that a specific clonal LLC cell line, whose conditioned media does not induce metabolic stress in myotubes, also fails to promote cancer cachexia in mice. These novel findings provide new insights that early disruption of muscle oxidative metabolism is associated with cancer cachexia progression and should be considered in future clinical cohort studies, trials, and practice.


Proper isolation and restoration of class V subgingival cavities are technique sensitive, thus the resin composite restoration is liable to contamination. This in vitro study was conducted to evaluate the surface microhardness and compressive strength of bulk-fill flowable resin composite after being contaminated during its packing.Resin composite discs were prepared using split mold. The contaminated specimens were allocated into four groups (n = 20) according to the contaminant used: hemostatic agent (Group 1), alcohol (Group 2), artificial saliva (Group 3) and powdered gloves (Group 4). The non-contaminated specimens (n = 20) were used as control group. The surface microhardness and compressive strength of each group were tested 1-day post-photocuring (n = 5) and 1 month post-photocuring (n = 5). Values were presented as mean, standard deviation values and confidence intervals.p = 0.001). The highest compressive strength mean values at 1 day and 1 month post-photocuring were recorded in control groups (110.42 MPa and 172.87 MPa respectively), followed by alcohol groups, then hemostatic agent groups, followed by artificial saliva with the least value recorded in powdered gloves groups (56.71 MPa and 49.5 MPa respectively).The surface microhardness of all groups didn’t show a significant difference for different tested groups except for alcohol which showed a significant reduction on surface microhardness compared to control at 1 day post-photocuring (Contamination of bulk-fill flowable resin composite with hemostatic agent, alcohol, artificial saliva, or powdered gloves during its packing decreased its compressive strength after 1 month post-photocuring rather than affecting its surface microhardness.The online version contains supplementary material available at 10.1186/s12903-022-02495-6. Assessing the mechanical properties of resin composite is essential to evaluate the ability of material to survive all challenges present in the oral environment. One of the most useful properties to assess is the surface microhardness because it is correlated with resistance to abrasion . AdditioContamination of bulk-fill resin composite during packing could happen accidently when complete proper isolation is difficult to obtain, especially when used to restore class II or class V subgingival caries. Salivary contamination of the cavity can have adverse effects on the longevity of the restoration and may lead to microleakage, sensitivity, tooth discoloration and finally, loss of the restoration . Many stThe materials used in this study are shown in Table Experimental in vitro study design was used to investigate the effects of contamination of bulk-fill flowable resin composite during packing with different contaminants.A total of 100 specimen of disc-shaped resin composite were prepared using Teflon split mold. The contaminated specimens were allocated into four groups (n = 20) according to the contaminant type used. The non-contaminated specimens (n = 20) were used as control group. Each group was further subdivided into two subgroups of ten specimens each to test the microhardness (n = 10) and the compressive strength (n = 10) at 1-day post-photocuring (n = 5) and 1 month post-photocuring (n = 5).Control Group (Non-contaminated group): 20 specimens were prepared by injecting the bulk-fill flowable resin composite into the central hole of Teflon split mold (4 mm diameter × 6 mm height) placed on a clean dry glass slab followed by adequate packing.2. The curing protocol performed was standard irradiation at a continuous light-intensity for 40 s, with the light curing tip positioned directly onto the celluloid strip at zero distance.The top surface of the resin composite was covered with a celluloid matrix strip (0.05 mm thick); the excess material was removed by pressing a glass slab against the strip . FinallyGroup 1–4 (contaminated groups): 20 specimens of each group were prepared by injecting half the specimen height (3 mm) in the lower half of the mold followed by adequate packing. The top surface of the lower half resin composite was contaminated with hemostatic agent (Group 1), alcohol (Group 2), artificial saliva (Group 3) and powdered gloves (Group 4). Groups 1–3; one drop of each contaminant agent was applied on the resin composite surface for 10 s using a clean microbrush in a circular motion. Group 4; powdered gloves were cut into 20 pieces of 1 × 1 cm each [HV = 1.854 P/d2 where, HV is Vickers hardness in Kgf/mm2, P is the load in Kgf and d is the length of the diagonals in mm.The microhardness of each group was tested 1-day post-photocuring (n = 5) and 1 month post-photocuring (n = 5). The specimens were tested using Digital Display Vickers Microhardness Tester  with a Vickers diamond indenter and a 20X objective lens. A load of 100 g was applied on the surface of each specimen for 20 s. Three indentations were made on the surface of each specimen. The indentations were equally placed over a circle, not closer than 0.5 mm to the adjacent indentations. The diagonals length of the indentations was measured by built in scaled microscope and Vickers values were converted into microhardness values. Microhardness was calculated using the following equation: 2, where P is the load (N) at the fracture point and d is the diameter (mm) of the cylindrical specimen.The compressive strength of each group was tested 1-day post-photocuring (n = 5) and 1 month post-photocuring (n = 5) using Bluehill® Lite, Instron Instruments. All samples were individually and vertically mounted on a computer-controlled materials testing machine  with a loadcell of 5 kN and data were recorded using computer software . Then the samples were statically loaded (in compression manner) using stainless-steel rod ended with flat plate (40 × 60 mm) attached to the upper movable compartment of the machine at a crosshead speed of 0.5 mm/min until failure. The maximum failure load was recorded in N and converted into MPa. The compressive strength was calculated from the recorded peak load divided by sample surface according to the following equation: Compressive strength (CS) = 4P/πdValues were presented as mean, standard deviation (SD) values and confidence intervals. The results of Kolmogorov–Smirnov and Shapiro–Wilk tests indicated that data were normally distributed, therefore Repeated measures analysis of variance (ANOVA) was performed to evaluate the effect of one between-subject variable (groups-contaminants) and one within-subject variable (1 day vs. 1 month). Multiple comparisons with Tukey’s post hoc test was used for comparison between groups (α = 0.05). Statistical analysis was performed with SPSS . The original data can be accessed in Additional file p = 0.023) while different groups tested and the interaction between groups and storage time resulted in an insignificant effect on the surface microhardness . The surface microhardness results of tested groups are presented in Table p = 0.001). While for all other groups, insignificant difference between each other’s resulted (p > 0.05). At 1 month post-photocuring, insignificant difference between tested groups resulted at p = 0.718. For all groups, insignificant change in surface microhardness resulted after 1 month post-photocuring (p > 0.05) except with alcohol group which showed a significant increase in the surface microhardness (p = 0.002).The repeated measures ANOVA revealed that storge time had a significant effect on the surface microhardness p = 0.03 while dp < 0.001) and storge time (p = 0.018) had a significant effect on the compressive strength (MPa) while the interaction between groups and storage time resulted in an insignificant effect on the compressive strength (MPa) (p = 0.090). The compressive strength (MPa) results of tested groups are presented in Table p = 0.01 and 0.028). Artificial saliva and hemostatic agent groups showed an insignificant difference compared to all other groups (p > 0.05). At 1-month post-photocuring, control group showed the significantly high compressive strength (MPa) value compared to all groups (p < 0.05). Alcohol resulted in significant high compressive strength (MPa) compared to artificial saliva and gloves powder (p = 0.043 and 0.003) with insignificant difference between artificial saliva and gloves powder. Hemostatic agent showed insignificant results compared to all other groups except control (p < 0.001). One-month post-photocuring resulted in significant increase in the compressive strength for control group only (p = 0.001), while for other groups, it didn’t affect he compressive strength significantly (p > 0.05).The repeated measures ANOVA revealed that different tested groups  is one of the hemostatic agents used at a concentration between 0 and 25% to promote hemostasis before placement of a restoration by protein precipitation and constriction of blood vessels [The current study used artificial saliva among the used contaminants; because salivary contamination to resin composite during packing is common in some clinics where rubber dam is not used; or when leakage occurs due to improper use of rubber dam. The study also used alcohol among contaminants because many dentists may use alcohol to lubricate the composite instruments to facilitate its handling . Alumini vessels . Alumini vessels . Many clMicrohardness is one of the most useful properties to assess because it is closely correlated with resistance to abrasion when used for restoration in load bearing areas . CompresIt was observed that the tested contaminants did not affect the resin composite surface microhardness at 1 day and 1 month post-photocuring except of alcohol at 1-day. However, the compressive strength of resin composite was significantly decreased after being contaminated with the tested contaminants at 1-day and 1-month post-photocuring. This might be due to the application of the contaminants between the two increments, not on the surface of the specimen. Vickers hardness test could only assess the surface microhardness of resin composite specimen . Moreove. [Our results were inconsistent with Widiandini et al.  who demo.  stated t.  found thThe Food and Drug Administration (FDA) defined ethanol as a liquid that simulates fatty foods and alcoholic beverages. In several studies, ethanol led to degradation or “softening” of composites and reduction of its microhardness . It was It was previously postulated that manual manipulation of resin composite with powdered latex gloves should be avoided . Martins3 used as hemostatic agent resulted in smear layer removal, and dentin etching effects [It was previously demonstrated that the acidic pH of AlCl effects , 14. SimAt 1-month post-photocuring, the control group recorded a significantly higher compressive strength mean value when compared to 1-day post-photocuring value. Our findings confirmed the results of Gornig et al. . HoweverThe findings of this in vitro study have to be seen in light of some limitations such as small sample size, absence of humidity and pH conditions of the oral cavity. However, the current study raises the importance of the clinician awareness to avoid contamination of resin composite during its packing inside the prepared cavity to enhance the restoration longevity.Under the limitations of the current study, it was concluded that contamination of bulk-fill flowable nanohybrid resin composite during packing with either hemostatic agent, alcohol, artificial saliva, or powdered gloves decreased the compressive strength at one-day and 1-month post-photocuring. Whereas contamination of resin composite did not significantly affect its surface microhardness.Further studies are recommended to evaluate the effect of contamination of bulk-fill resin composite on its color stability, physical and mechanical properties.Additional file 1. Original Data of microhardness and compressive strength.


This goal, however, is challenged by gaps in traditionally employed sediment-hosted geochemical proxy data. Here, we propose an independent strategy—machine learning with global mafic igneous geochemistry big data to explore atmospheric oxygenation over the last 4.0 billion years. We observe an overall two-step rise of atmospheric O2 similar to the published curves derived from independent sediment-hosted paleo-oxybarometers but with a more detailed fabric of O2 fluctuations superimposed. These additional, shorter-term fluctuations are also consistent with previous but less well-established suggestions of O2 variability. We conclude from this agreement that Earth’s oxygenated atmosphere may therefore be at least partly a natural consequence of mantle cooling and specifically that evolving mantle melts collectively have helped modulate the balance of early O2 sources and sinks.Reconstructing historical atmospheric oxygen (O Earth’s oxygenation history can be reconstructed using machine learning and mafic igneous geochemical data. Agreement with independent proxy predictions for surface conditions implies that interior processes are critical in atmospheric oxygenation. As such, resolving various geoscience conundrums relies on deductive or inductive reasoning  based on  observations and experiments. However, given the vast and ever-expanding global geo-databases available , we are now in a unique position to use big data analytical techniques to answer fundamental geoscience questions via an abductive model3. This opportunity lies with data mining of increasingly large and intensive geo-datasets and from computationally intensive simulations5. In other words, although geoscientists can use logical reasoning to analyze and interpret geo-data, abductive reasoning based on machine learning with big data can facilitate data-driven discovery of previously hidden correlations or patterns that escape human intuition3. At the core of artificial intelligence and data science, machine learning methods guided by training experiences can be are exceptionally good at processing big data and making decisions and predictions7. This advantage elevates their relevance in geoscience research9, where high-resolution measurements and observations over long periods of geological time have produced vast numbers of diverse and complex data bases.An important goal for geoscientists is to decode the long-term evolution of Earth geosphere, atmosphere, and biosphere, as well as their interactions Fig. . However–7–10–5 of the present atmospheric level [PAL]) for the first half of Earth history and then rose to something like 10–3–10–1 PAL during the Great Oxidation Event (GOE)12 around 2.5 to 2.0 billion years ago (Ga), although the magnitude, fabric,  and timing of this jump are not well known—with ongoing debate14. Afterward, it remained at intermediate but still relatively low levels (10–4–10–1 PAL) for the “boring” billion years during the mid-Proterozoic15 and then rose a second time during the Neoproterozoic Oxidation Event (NOE), achieving current oxygen levels (~1 PAL) during the Phanerozoic12. However, despite agreement about the first-order pattern of atmospheric oxygenation, the controls on this evolution and the second-order variations remain poorly known and are subject to debate.Atmospheric oxygenation is critical to the development of Earth’s habitability. Oxygen levels, as shown in Fig. 16. The reason for this apparent time lag remains a topic of considerable debate. Various hypotheses rely on the notion that atmosphere oxygen levels are determined by a kinetic balance between O2 production and sinks18. One possibility is that photosynthetic production of O2 could increase as a result of enhanced nutrients  availability, and this possibility has been invoked for both GOE and NOE through the weathering of large igneous provinces (LIPs)20. Yet the rate of organic matter burial (forg) has remained approximately constant for most of Earth history21, rather than showing significant changes that correspond with dramatic, long-term steps in biosphere oxygenation.Earth’s oxygenation derives from the emergence of oxygenic photosynthesis; however, the GOE likely followed the initiation of this innovation by several hundred million years2 sinks from the perspective of purely abiotic controls, rather than by an increase in O2 flux23. Proposed mechanisms that could significantly reduce O2 consumption during GOE include a change in the fraction of subaerial magma degassing17, mantle oxygen fugacity24, and/or crustal composition25, all of which would influence the atmosphere oxygen level via the flux and redox state of reductants  emanating from the solid Earth. In general, the redox state of these reductants was controlled by the upper mantle melt26 and/or its subsequent magma differentiation27. It has been suggested that mantle redox did not change significantly through time as evidenced by V/Sc ratios in basalts28, leading to its frequent dismissal as a key driver of the atmospheric O2 evolution for two decades. Recent studies, however, suggest that the mantle may have gradually oxidized from the Archaean onwards30, resulting in a decline of oxidizable volcanic gases that could have trigged the GOE23. Moreover, the rapid formation of felsic continent through plate tectonics could largely reduce the flux of mantle-derived reductants , ultimately allowing atmospheric O2 to accumulate during the GOE18. These many and often competing arguments leave open the need for novel perspectives.Alternatively, it has been proposed that early atmospheric oxygenation  was driven by a secular decline of efficient O31, thus playing a crucial role in both O2 production and sinks. Global data compilations for igneous rocks  provide much higher temporal resolution of variations in geochemical concentrations throughout Earth history32 compared to geochemical proxies preserved in sedimentary repositories 33. These large datasets for igneous rocks include dozens of elements and ages ranging from 4.0 Ga to the present, as shown in Figs. 27, supercontinent cycles32, and historical trends in plate tectonics34. Moreover, integrated analysis of diverse data resources using machine learning, in contrast to separate treatment of each physicochemical property, can lead to more evidence-based predictions about many aspects of Earth system and its relationship with surface environmental change35.Mafic rocks like basalts act as key probes of Earth’s interior and redox state, and their formation and geochemical evolution are directly related to the flux of nutrients and reductants to Earth’s surface36. In this paper, using unsupervised learning methods (including self-organizing map (SOM) and principal component analysis (PCA)), we find that the state of mafic igneous composition evolved chemically through the four major stages, with geochemical transition periods at both ends of the Proterozoic, corresponding with the timing of GOE and NOE, respectively. Second, the supervised methods ) based on Monte Carlo simulations were applied to the same dataset to “predict” atmospheric oxygen levels since 4.0 Ga quantitatively. Our independent method successfully revealed a high-resolution two-step pattern of increasing atmospheric oxygen level and identified many second-order fluctuations since 4.0 Ga, most of which agree with local observations based on sediment-hosted paleo-oxybarometers. We hypothesize from these observations that secular geochemical evolution of mafic igneous systems, as a result of mantle cooling over time27, could have played an important role in the secular change of atmospheric oxygen levels on Earth.With this goal in mind, we focus on reconstructing atmospheric oxygen variation over deep time using machine learning based on global mafic igneous geochemistry big data. Nonetheless, it should be emphasized that rigorous screening of rock samples  is essential when applying big data approaches to global geo-databases37 and PCA38 are the two most widely used unsupervised learning methods. They can effectively reduce a high-dimensional dataset into relatively few representative samples that can be more easily visualized, quantified, and interpreted. In our study, the utility of SOM lies with its ability to delineate major trends, jumps, and clusters in the global igneous geochemical time series dataset. We used PCA to supplement SOM results by investigating the details of temporal variations observed via the first principal component (PCA1). Additional detailed information about the practical implementation of SOM and PCA in this study can be found in the “Methods” and Supplementary information. First, SOM analysis of global mafic igneous data for 44 elements has identified four major classes of mafic composition, reflecting four distinct time intervals since 4.0 Ga . Class 2 spans ~2.5 Ga to 1.8 Ga and represents a transition period of mafic igneous compositions for most elements during the Paleoproterozoic time. Class 3 spans ~1.8 Ga to 0.7 Ga and represents a relatively stationary state of mafic igneous compositions for most elements during Earth’s middle age. Class 4 represents ~0.7 Ga to the present and is characterized by relatively lower concentrations of compatible elements and higher concentrations of incompatible elements. The secular change in concentration of compatible elements (decrease) and incompatible elements (increase) in mafic igneous rocks reflects degrees of mantle melting controlled by mantle cooling through time27. Therefore, the identified four broad steps of mafic igneous geochemistry evolution through SOM analysis reflect the first-order response of decreasing mantle melting degree over the course of Earth history.We employed unsupervised machine learning to examine the first-order pattern of mafic igneous geochemical evolution through time from concentration data for 44 elements. SOM Ga Fig. . Class 139 and thinner crust40 compared to the present day  leads us to speculate that deep geochemical processes may have been connected to both of the two great oxidation events on Earth’s surface—not just to the GOE27. During the earliest stage, high-degree mantle melting resulted in high concentrations of highly compatible elements and low concentrations of incompatible elements in mafic igneous rocks  as well as a limited nutrient supply  and persists to ~1.8 Ga. The geochemical transition at ~1.8 Ga, the onset of the third stage, is linked to a possible oxygenation event during the assembly of the Columbia supercontinent46 and the beginning of the “boring” billion.Figure cks Fig. , which i15 may relate to sluggish evolution of mafic igneous geochemistry and corresponding limitations in nutrient supply and reductant release, thereby maintaining the balance of O2 supply and sinks at relatively low levels for both. For example, sluggish evolution of macronutrients  during the “boring” billion suggests a limited supply from mantle-derived melts that could have limited primary productivity47. Moreover, the temporal coincidence of the igneous geochemistry transition and atmospheric oxygenation patterns around 0.7 Ga has not been reported previously. Tectonically, this geochemical transition corresponds to the onset of a cold subduction style of plate tectonics that could have intensified mantle cooling43, likely resulting in a second abrupt response to the degree of mantle melt expressed in the ~0.7 Ga transition in mafic igneous geochemistry. As such, the increase in continental nutrient inventory . It has been suggested that the second-order variations in mafic igneous geochemical concentrations also reflect changes in mantle potential temperature and melting degree32, with termination of the GOE linked to a 2.06 Ga LIP event50, as shown in Fig. 2+, S2−, and reduced volcanic gases), perhaps contributing to  decreases in surface oxygen levels over relatively short time intervals.Moving forward, PCA of the global mafic igneous geochemical data for 44 elements has identified the most significant principal component, PCA1, which accounts for 78% of the total variance  as well as in the SOM and PCA1 patterns of mafic composition at ~1.8 Ga , and 2 through reductants derived from Earth’s interior. At times of low oxygen levels, ma—specifically, 54, an oxygen sink. The production of O2  in marine sedimentary rocks to guide paleo-oxybarometers48. Nevertheless, preservation bias is inescapable in sedimentary rocks, and the resulting temporal coverage of suitable sedimentary archives is patchy, especially in the Precambrian, leading to an interpolated O2 curve across the last 4.0 Gyrs with large uncertainties. As such, robust quantitative estimates of atmospheric O2 levels require data compilation of paleo-oxybarometers on a global scale  and better evidence-based predictions using more integrated approaches55.Traditional estimates of ocean redox and atmospheric O6 without any specific physicochemical model. For simplicity, we assume a nonparametric multivariate transform, directly relating F represents some fixed but unknown function of F) that maps input predictor  from the training label pair , and once training is done it can be used further to map the known element contents  algorithm was used to prepare the training dataset and make predictions. Specifically, the scheme for preparing the training label pairs involves labeling random numbers of ages (bins) with stochastic O2 contents within the confidence intervals of three recognized O2 base levels, while using corresponding geochemical concentrations of all 44 elements as predictors. More details about the practical training, validation, and implementation of machine learning in this study are described in the “Methods”.We first use a SVRmentclass2pt{minimR2 > 0.9) and mean square error (<0.01) , this two-step rise temporal pattern of atmospheric O2 evolution path can be recovered through our machine learning modeling  found in the sedimentary record at that time  of global igneous geochemical composition is required to explore the possibility of these oscillations through the GOE with confidence when using our machine learning model.The background atmospheric O–3 to 10–1 PAL, and this range is in agreement with previous estimates15. As mentioned above, whether O2 levels were persistently low for a billion years following the GOE remains controversial51. Our results suggest that the atmosphere during the “boring” billion maintained intermediate but still low O2 levels. However, this prolonged period of low O2 could have been punctuated by episodes of elevated O2 relative to a lower baseline, perhaps analogous to the whiff events leading up to the GOE. Such episodic features are suggested at ~1.8 Ga, ~1.4 Ga, and ~1.1 Ga in Fig. 2 estimates <0.1 PAL. At face value, both peaks can be explained by increases in concentration of macronutrient phosphorus and decrease of reductants concentration in mafic rocks, and ~1.8 Ga and ~1.1 Ga events are coupled with supercontinent assemblies.During the “boring” billion, the prediction of atmospheric oxygen levels varies within a range of 102 level around 1.8 Ga is consistent with the disappearance of iron formations at that time 52, although debate about the specifics remains63. Additional evidence consistent with possible increasing atmospheric O2 around 1.1 Ga includes suggestions of increased sulfate concentrations in the oceans64 and a pronounced peak in Cr isotopic composition of carbonates65 and Re concentrations in organic-rich shales66. Although this “event” is still only suggested by the sediment-hosted geochemical data51, its agreement with our findings should spawn additional work.The possibility of increased atmospheric Oime Fig. 61, as th67 and phosphorus-limited conditions68. We posit that these possible deoxygenations, particularly those following the GOE, are closely related to decrease in flux of nutrients supply  and increase of oxygen-consuming agents related to enhanced mantle activity . Moreover, our results suggest a short-term return of relatively low O2 levels after the NOE 69, which can also be attributed to an increase of P2O5 concentration in mafic rocks  did not correspond to supercontinent assembly but do coincide well with igneous geochemical transitions as shown in Fig. 2 sources and sinks.In addition, the possible transient oxygenation events suggested at ~2.5 Ga, ~1.8 Ga, ~1.1 Ga, and ~0.4 Ga are temporally coupled with supercontinent assemblies  and trace elements  from mantle-derived magmas could have played important roles in atmospheric oxygenation owing to their effects on the biosphere70.As an additional step, we have tested the sensitivity of our oxygen reconstruction to different ML algorithms. As shown in Supplementary Fig. 2 production, as this production in our model is linked only to the flux of nutrient supply from mafic igneous rocks and not recycled from sedimentary sources. For example, as seen in Fig. 2 level during this period 18 and/or deep sequestration of organic carbon71. In this regard, an amplification of our O2 predictions can be expected (at least) during GOE as linked to rapid rise of continents and major glaciations that increased nutrient inputs and net sequestration of organic C, but we can also predict increased volcanic CO2 emissions due to sediment-enhanced subduction activity72.Our model may underestimate O2 sinks, as it does not include processes like organic matter remineralization in the water column and weathering of ancient fossil organics in rocks and aerobic respiration, especially during the Phanerozoic. Moreover, mantle cooling increased the oxidation state of both mantle melts and equilibrated volatile species73, and the latter could amplify consumption of O2. Again, our overarching hypothesis is that mafic geochemical transitions as a result of secular mantle cooling could play an important role in the rise of atmospheric oxygen. Overall, given that mafic igneous geochemical data alone can quantitatively recover the classic two-step rise model of atmospheric O2 level, as well as the order-of-magnitude of O2 increase previously predicted for the GOE, NOE, and even the POE, we can conclude that atmospheric oxygenation may therefore be at least partly a natural consequence of mantle cooling and specifically played the role of evolving mantle melts in modulating the balance of early O2 sources and sinks.Our model also underestimates OData-driven machine-learning algorithms with big data provide an additional technique to explore Earth’s long-term evolution. An essential benefit of data-driven discovery models is their potential to reveal correlations among massive dataset and whether or not there are causation and thus mechanistic drivers nested within these relationships. Because these datasets can be diverse, high-dimensional, and noisy, machine learning algorithms are needed to handle big datasets to expose previously hidden patterns. Given that applications of artificial intelligence in Earth science have not yet reached the level of cognitive intelligence  and often suffer from a black box problem of ML algorithms (lack of transparency), we emphasize the need to blend human learning and artificial intelligence when searching for the causation that underlies correlation.3. For example, the two-step rise model of atmospheric oxygen is well known, but how Earth’s atmosphere became oxygenated remains a topic of considerable debate. In the present study, the unsupervised machine learning of global igneous geochemical time series data recognized three major stages of its secular evolution, which correlate well with two-step increases in atmospheric oxygen levels over time. This synchronization helps us link the two-step rise and perhaps second-order fluctuations in atmospheric O2 level to deep Earth geochemical processes through mantle cooling and magmatism systems , which includes PetDB, GEOROC, NAVDAT, and USGS databases. This new database contains ~54,000 whole-rock analyses of major, trace, and rare earth elements from mafic igneous rocks  with chemical compositions of 43–51% SiO2 and MgO < 18%. In addition, we have eliminated outliers in the geochemical concentration data for each element by using a Large-scale community geo-data sources, such as EarthChem, GEOROC, PetDB, and Macrostrat are especially relevant for promoting data-driven discoveries in statistical petrology, geochemistry, mineralogy, and sedimentology. Here, we have compiled global mafic igneous composition data from the EarthChem data repository  to calculate the time series of global mean mafic igneous geochemistry composition. The emerging curves of geochemical concentration time series , while these compatible and incompatible elements show remarkable negative correlation. According to the efficiency of mantle convection, long-term cooling of mantle results in decreasing degrees of the mantle melt fraction and more felsic crust through time27. Therefore, mafic rock samples record a fluctuating decrease in compatible element concentration  and a corresponding increase in incompatible element concentration values  through time  on the map, thereby preserving the topological structure of the data. SOM analysis mainly involves two stages, training and mapping phases. In this study, the goal of SOM analysis is to represent igneous geochemistry big data with 44 dimensions as one-dimensional time series data. Several parameters, such as iteration step, learning rate, and structural function should be specified by the user prior to training the network. Nevertheless, they have little influence on patterns produced on the SOM maps.We used unsupervised machine learning (including SOM and PCA) to reduce the high dimensionality of global geochemistry big data (spanning 44 elements) and to explore the first-order relationships of mafic igneous geochemistry evolution through time. SOM is an unsupervised machine learning algorithm that draws on the basis of neural networks using competitive learning rather than the error-correction learningN = 4) by using Davies-Bouldin (DB) analysis74. As a result, SOM analysis identifies four broad steps of mafic igneous geochemistry evolution through time  do the opposite. We performed the SOM analysis of mafic igneous geochemical data using the compiled MATLAB code based on the open SOM Toolbox available at http://www.cis.hut.fi/projects/somtoolbox/.We selected time series data of all 44 elements as input data, and a min-max algorithm was used for data normalization. The unified distance matrix (U-Matrix)  that are not apparent without statistical analysis. In this study, the goal for PCA was to extract the important temporal variations within a large igneous geochemical time series dataset (spanning 44 elements) and to express this temporal information using the first few principal components.2O, Na2O, P2O5, Th, and U) have positive loading values for PCA1, whereas compatible elements  have negative loading values. Most of the selected elements make equally significant contribution to the PCA1 pattern, with TiO2, Cr, Ni, and Y being slightly more important.As shown in Supplementary Fig. 2 content as a supervised machine learning regression problem, we can label O2 levels in specific time intervals using the published O2 model with uncertainties and employ multiple lines of evidence for oxidation as input. The goal of using machine learning is to parameterize the complex relationship between such training labels and igneous geochemical proxy data (in the training data process) to quantitatively estimate O2 content over the course of Earth history. SVR is a regression algorithm that draws on support vector machine (SVM)56 with the basic idea of separating between classes in a dataset within an optimal hyperplane that maximizes boundaries between classes. SVM and SVR have been widely used for classification and regression problems, respectively. Data used to train and evaluate supervised machine learning algorithms are generally divided into training set and testing set. In this study, all data were scaled between 0 and 1 prior to inputting into the SVR, and a Gaussian radial basis function kernel was used because this is a reasonable first choice for most applications. The performance of SVR is also controlled by the value of the penalty term (C) and parameter of the kernel function—for example, width (γ) of the radial function as used in this study. Note that very large penalty (C) or width (γ) may lead to over-fitting and poor generalization capability, even if it shows high accuracy in data training.Framing the estimate of OC and γ values. In the stochastic modeling, we undersampled the training samples from the originally prepared (input and output) dataset (within the periods of 0–500 Ma and 2500–4000 Ma) for each SVR training and then divided them into five subsets of the same size. In each training round, one subset was selected successively as the test dataset and the rest as training datasets. The above process was repeated five times so that all subset data could be included for testing and validation. The final performance was evaluated by averaging results from all repeated training rounds. We compiled Python codes to implement the reconstruction of historic atmospheric O2 levels using supervised machine learning based on Sklearn library .A five-fold cross-validation approach was used in this study to avoid the over-fitting problem in data training and to determine the optimal C and γ values in SVR modeling for one MC. The root-mean-square-error (RMSE) generally converge to 0.01 in stochastic SVR modeling, as shown in Supplementary Fig. 2 prediction when using O2 different base level as training labels have been evaluated. The results in Supplementary Fig. 2 base level with different error ranges post 0.5 Ga and pre 2.5 Ga did not affect the final prediction of temporal variation of atmospheric O2 level, nor the order-of-magnitude of O2 increase during the GOE and NOE.Supplementary Fig. 2 level between RAR filtered and non-RAR filtered datasets did not show notable differences in temporal trends, except for the slight differences in amplitudes, most of which fall in the uncertainty range provided by MCs. As shown in Supplementary Fig. 2 modeling is robust with or without the less relevant elements  transformed datasets. First, as shown in Fig. 2 contents using the earlier database of Keller and Schoene. As shown in Supplementary Fig. 2 pattern is mostly a close match with predictions using the updated database assembled for this study, suggesting that O2 modeling using the global mafic rock database is robust. Moreover, we have used the CLR-transformation to address the problem of spurious correlations faced in geochemical compositional data analysis75. It is beyond the scope of this study to interpret the CLR-transformed concentration values for each element, but the results in Supplementary Fig. 2 curves whether using raw geochemical data or the  CLR-transformed dataset.We have tested our SVR modeling of O2 history using different machine learning methods, including ANN and RF. As shown in Supplementary Fig. 2 levels discussed above remain unchanged. The results suggest that reconstructing atmospheric oxygenation history using machine learning with mafic igneous geochemistry data is robust—independent of machine learning algorithms . Notably, the RF approach76 provides an assessment of feature importance for all 44 elements in terms of how each composition variable influences the final model for atmospheric oxygen levels (see Supplementary Fig. 2 levels and variability suggested previously by sedimentary proxies.We tested additional schemes for reconstructing atmospheric OSupplementary InformationPeer Review File


Remote epitaxy is a promising approach for synthesizing exfoliatable crystalline membranes and enabling epitaxy of materials with large lattice mismatch. However, the atomic scale mechanisms for remote epitaxy remain unclear. Here we experimentally demonstrate that GaSb films grow on graphene-terminated GaSb (001) via a seeded lateral epitaxy mechanism, in which pinhole defects in the graphene serve as selective nucleation sites, followed by lateral epitaxy and coalescence into a continuous film. Remote interactions are not necessary in order to explain the growth. Importantly, the small size of the pinholes permits exfoliation of continuous, free-standing GaSb membranes. Due to the chemical similarity between GaSb and other III-V materials, we anticipate this mechanism to apply more generally to other materials. By combining molecular beam epitaxy with in-situ electron diffraction and photoemission, plus ex-situ atomic force microscopy and Raman spectroscopy, we track the graphene defect generation and GaSb growth evolution a few monolayers at a time. Our results show that the controlled introduction of nanoscale openings in graphene provides an alternative route towards tuning the growth and properties of 3D epitaxial films and membranes on 2D material masks. Remote epitaxy represents a promising method for the synthesis of thin films on lattice-mismatched substrates, but its atomic-scale mechanisms are still unclear. Here, the authors demonstrate the growth of exfoliatable GaSb films on graphene-terminated GaSb (001) via seeded lateral epitaxy, showing that pinhole defects in graphene serve as selective nucleation sites. For example, the weak van der Waals interaction between the film and graphene creates new strain relaxation pathways for highly mismatched growth3 and enables exfoliation of free-standing crystalline membranes for flexible devices4 and tuning properties via strain in novel geometries5. Since the first demonstrations for compound semiconductors6, epitaxy and exfoliation from graphene have been demonstrated for a variety of other materials including transition metal oxides7, simple metals8, halide perovskites3, and intermetallic compounds5. These films are typically thought to grow via a remote epitaxy mechanism6, in which epitaxial registry between film and substrate is achieved via remote interactions that permeate through graphene.Remote epitaxy of three-dimensional materials on graphene-terminated surfaces8. However, the magnitude of the potential fluctuations is only Δϕ = 0–40 meV, which is smaller than the kBT ~ 70 meV thermal energy at typical growth temperatures 500 ∘C. Experimentally, the ability to grow and exfoliate crystalline films from graphene is often cited as evidence for growth via these remote (screened) interactions7. In practice, however, it remains an outstanding challenge to fabricate defect-free graphene or perfect graphene/substrate interfaces, especially because graphene cannot be grown directly on arbitrary substrates. Additional layer transfer steps are often required. The effects of native and transfer-induced defects in graphene, which are difficult to control12, are generally overlooked in the remote epitaxy mechanism. Microscopic measurements during growth are required to understand the atomic-scale mechanisms for growth under realistic conditions.The atomic scale mechanisms of remote epitaxy, however, remain unclear. Model calculations suggest that for perfect graphene/substrate interfaces, the substrate lattice potential permeates through graphene and may be sufficient to template epitaxial growth13, we find that pinholes are created by native oxide desorption from the substrate. GaSb nucleates directly from the underlying GaSb substrate in the pinholes, followed by lateral overgrowth and coalescence of a continuous film. The resulting films have similar structural quality as previous reports8 and can be exfoliated to produce free-standing membranes. Since GaSb shares similar bonding character, constituent vapor pressures, surface diffusion coefficients, and growth conditions as other III-V materials, we anticipate that the seeded lateral epitaxy mechanism may explain the growth of other materials on transferred graphene. We experimentally track the evolution of GaSb films grown on graphene/GaSb(001) by combining molecular beam epitaxy (MBE) synthesis with in-situ electron diffraction and photoemission spectroscopy (XPS), plus ex-situ atomic force microscopy (AFM) and scanning electron microscopy (SEM).Here we experimentally demonstrate that pinhole-seeded lateral epitaxy explains the growth of atomically smooth, exfoliatable GaSb films on a graphene-terminated GaSb (001) substrate. Using the same graphene transfer procedures as previous reports2 to seed growth18. It improves upon conventional ELO in two key ways. First, due to the weak Van der Waals interactions and small pinholes (10–300 nm diameter), graphene masks permit the etch-free exfoliation of large scale single-crystalline GaSb membranes for applications in flexible electronics. Second, the atomic thinness of graphene is an attractive feature compared to conventional ELO masks, for applications where an electronically transparent interface is desired, e.g. a tunnel junction20. Seeded lateral epitaxy also carries an advantage over purely remote epitaxy: whereas remote epitaxy is only expected to apply for substrates with polar bonding6, seeded lateral epitaxy can produce epitaxial films on nonpolar substrates15. Remote epitaxy also requires clean graphene/substrate interfaces, free from interfacial oxides or other contaminants1. Our experiments demonstrate that the introduction of defects provides powerful knob for controlling epitaxial growth of covalent 3D materials on 2D materials surfaces, similar to recent work on growth of 2D materials on patterned 2D masks22.This growth mode is conceptually similar to selective area epitaxy and epitaxial lateral overgrowth (ELO), that employ openings in a dielectric mask such as SiO13 (Methods). HCl25 and HCl+H2O2 solutions27 are also commonly used to etch native oxides from GaSb. The other half of the sample has an exposed GaSb surface for direct epitaxy.We first demonstrate the epitaxy and exfoliation of single crystalline GaSb films on a graphene-terminated GaSb 001) substrate. Figure  substrat∘C in an Sb2/Sb1 flux to desorb the native oxides from the substrate. On the bare GaSb side, the native oxide removal is confirmed by the appearance of bright semi-streaky spots in the RHEED pattern. The graphene-terminated side looks qualitatively similar, although the pattern is not as bright and there is diffuse intensity around the specular reflection. We attribute these differences in part to scattering through monolayer graphene that is randomly oriented in-plane.Immediately prior to growth we follow the standard procedure of annealing at 520 c(2 × 6) reconstruction of GaSb (001) [Fig. ω = 0, we observe a second peak shifted by ω = −15 arc seconds. The full width at half maxima (fwhm) of these two peaks are 10.44 and 12.59 arc seconds, respectively, compared to a width of 6.74 arc seconds for a homoepitaxial film. In addition, photoluminescence measurements reveal similar materials quality between films grown on graphene/GaSb (001) and a bare GaSb substrate . Figure We now show that GaSb films grow on graphene-terminated GaSb (001) via a lateral epitaxy, seeded at pinhole defects. We first examine the creation of pinhole defects in graphene, which form due to native oxide desorption from the substrate immediately prior to GaSb film growth.1. However, such clean interfaces can be difficult to fabricate in practice, especially for III-V semiconductor substrates like GaSb since III-Vs are typically terminated with an amorphous ~3 nm thick native oxide28. This oxide must be removed before film growth in order to reveal the underlying crystalline template for an epitaxial film. Although we adopt an HCl etching procedure to remove the substrate native oxides prior to forming the graphene/substrate interface (Methods), some residual oxides may remain.Figure p < 5 × 10−10 Torr). After a 350 °C ultrahigh vacuum anneal to clean surface adsorbates, we observe a significant O 1s intensity at binding energy of 531 eV. In addition, we observe a satellite to the Sb 3d3/2 core level at binding energy of 540 eV, indicative of Sb-oxides.Our in-situ photoemission spectroscopy measurements reveal that some interfacial oxides remain after the etch procedure. Figure 2/Sb1 flux, no oxide components are detected in the Sb 3d or Ga 3p core levels, suggesting that the GaSb-oxides have fully desorbed. We also observe a finite O 1s core level intensity that decreases as a result of the 515 °C anneal, and decreases further after the 540 °C anneal. At this point the chemical state of the remaining oxygen above 515 °C is unclear, since no oxide components are detected in the Ga 3p, Sb 3d, or C 1s core levels, suggesting that neither the GaSb substrate nor the graphene itself is oxidized  samples removes most of the oxides, despite the presence of the graphene overlayer. After annealing at 515 °C with an Sb∘C appears qualitatively smooth with no tears or holes observed in the SEM images  are well known to etch graphene29, particularly at edges and at extended defects like grain boundaries. In the present case, we expect that the larger strains around these protrusions may enhance the oxygen etch rate at these locations, compared to smoother regions of the graphene. Similar enhanced oxygen etching of graphene on other substrates has been attributed to roughness and impurities in the underlying substrate30.The pinholes appear to be localized at the bumps that were observed after annealing to 350 ∘C, the areal density and diameter of the pinholes increases as observed in the AFM images  13. Therefore, it appears that native oxides trapped at graphene/III-V interfaces are common to both wet (aqueous) and dry (in air)31 transfer procedures, due to the reactivity of III-V surfaces32. Further improvements in interfacial cleanliness may require in-vacuum or glovebox transfer procedures33.An important question is whether the presence of oxides and creation of pinholes upon annealing are unique to our wet graphene transfer process, or if the creation of pinholes is more general. Note that we use the same HCl etching procedure that has been used previously for transferred graphene on III-Vs35 or intercalation under the graphene37, as has been observed in other systems.These pinholes serve as nucleation sites for direct epitaxial growth. Figure After 2 ML of GaSb growth, nearly all of the holes have nucleated GaSb islands, which we further quantify in Supplemental Fig. ∘C, which is below the native oxide desorption temperature. We find that the resulting GaSb film grown at 350 ∘C is polycrystalline  sample for which we do not remove the interfacial oxides. For this sample, we anneal to 350 D and G modes on both the exfoliated membrane side and on the substrate side, indicating that exfoliation tears the graphene . These pinholes are created by native oxide desorption from the substrate. The resulting GaSb films have similar characteristics and structural quality as previous reports of remote epitaxyλ is long compared to the average spacing L between pinhole defects (λ >> L). Previous experiments on confinement heteroepitaxy demonstrate that the effective surface diffusion length for group-III metal adatoms on graphene is of order 10 microns, since metal adatoms preferentially nucleate at graphene defects over length scales of order 10 microns37. Our preliminary experiments on lithographically defined graphene stripes reveal a similar picture . Therefore, adatoms can sample enough of the surface to nucleate at pinhole defects, rather than on the inert graphene. Remote epitaxy would require a larger separation between defects, L > λ.Seeded lateral epitaxy occurs in the graphene/GaSb system because (1) graphene is chemically inert and (2) the surface diffusion length ∘C is less than unity. Similar behavior has been observed for selective area epitaxy of III-V films on patterned dielectric masks, such as SiO2 and SiNx14.The long effective surface diffusion length arises from a combination of long surface diffusion and a high adatom desorption rate Fig. a, since ϕ ~ 15 meV6, which is smaller than the thermal energy kBT ~ 70 meV at growth temperature 500∘C. An estimate of the free carrier screening from graphene also suggests this potential should be weak. For a free electron gas with density 1019 − 1020 cm−3, the same density as graphene (graphite)38, the Thomas-Fermi screening length is approximately 1/k0 ~ 2 Å. This is less than the film/substrate layer spacing of ~5 Å1, suggesting that the screened potential above the graphene is exponentially weak. In contrast, the potential modulation at a graphene pinhole is expected to be much larger, Δϕ ~ 1 eV, since this involves adatoms making chemical bonds to the graphene or to the underlying substrate. The pinholes provide the low energy sites for nucleation and growth. Epitaxial registry is obtained because the pinholes are locations of direct epitaxy to the substrate. Given these factors that favor seeded lateral epitaxy when there is a finite density of graphene defects (L << λ), our results suggest that previous demonstrations of remote epitaxy can alternatively be explained by a seeded lateral epitaxy mechanism.The relative size of potential modulations also explains the preferred nucleation and growth from pinholes Fig. b. On graL << λ), the defects dominate the growth mechanism. Due to the interfacial oxides, we expect that most graphene that is transferred to a foreign substrate will lie in this high defect density regime. Characterization of the graphene quality before the pre-growth anneal  and Supplementary Fig. ∘C) and Supplementary Fig. Our experiments demonstrate that in the presence of a high concentration of graphene defects (L > λ) immediately prior to film growth, i.e. including the pre-growth annealing. Graphene that is directly grown on the substrate of interest, rather than transferred, provides a cleaner starting point for such studies. III-nitride39 and metal films37 on epitaxial graphene/SiC, and III-arsenide films on CVD graphene/Ge  of ultra high purity CH4 at 1050 ∘C on Cu foil, as described in refs. 41. The graphene/Cu foils were then cut and and flattened using clean glass slides to match the dimensions of the semiconductor substrate. Approximately 200 nm of 950 K C2 PMMA  was spin coated on the graphene/Cu foil at 2000 RPM for 2 minutes and left to cure at room temperature for 24 hours. Graphene on the backside of the Cu foil was removed via reactive ion etching using 90 W O2 plasma at a pressure of 100 mTorr for 30 s. The Cu foil was then etched by placing the PMMA/graphene/Cu foil stack on the surface of an etch solution containing 1-part ammonium persulfate  and 3-parts H2O. After 16 hours of etching at room temperature, the floating PMMA/graphene membrane was scooped up with a clean glass slide and sequentially transferred onto five 5-min water baths to rinse any etch residuals.Our graphene synthesis and transfer procedure is a modified polymer-assisted wet transfer of CVD-grown graphene∘C for 15 minutes, then at 150 ∘C for another 15 min. The PMMA was dissolved by submerging the sample in an acetone bath at 80 ∘C for 3 h. This is followed by an IPA rinse and nitrogen drying. The sample is indium bonded onto a molybdenum puck and outgassed at 150 ∘C for 2 h in a loadlock at a pressure p < 5 × 10−7 Torr before introduction to the MBE growth chamber. Finally, the sample is annealed at ~350 ∘C for 1 h in the MBE chamber to desorb organic residuals.GaSb (001) substrates were etched in 38% HCl solution for 5 min followed by a 2-propanol rinse to remove some of the native oxides. We then used the etched GaSb substrate to scoop the PMMA/graphene stack from the final water bath. To remove water at the graphene/substrate interface, the samples were baked in air at 50 GaSb films were grown in a custom molecular beam epitaxy chamber (Mantis Deposition) using an effusion cell for Ga and a thermal cracker cell for Sb (MBE Komponenten). Temperatures were measured using a pyrometer that is calibrated to the native oxide desorption temperature of GaAs. In-situ reflection high energy electron diffraction (RHEED) measurements were performed using a Staib RHEED gun at 15 keV.p < 5 × 10−10 Torr) transfer chamber, such that samples are transferred in vacuum and are not exposed to air. We use a non-monochromated Al Kα x-ray source (1486.6 eV) and an Omicron EA125 hemispherical analyzer with an energy resolution of 1.08 eV. Samples were annealed in the MBE and measured in the XPS at room temperature.X-ray photoemission spectroscopy (XPS) measurements were performed in an XPS chamber that is connected to the MBE via an ultrahigh vacuum (μm2 area. Atomic force microscopy (AFM) measurements were performed using a Bruker Dimension Icon in tapping mode.Field emission scanning electron microscopy (SEM) was performed using a Zeiss GeminiSEM 450. Raman spectroscopy was performed using a 532 nm wavelength laser (Thermo Scientific DXR Raman Microscope). The laser power is kept below 5 mW in order to prevent damage to the graphene. In order to acquire representative raman spectra, 2600 spectra where captured and averaged over a 2500 Kα radiation. Symmetric ω − 2θ measurements (ω is the sample tilt in the scattering plane and 2θ is the Bragg angle) and azimuthal pole figure (ϕ) scans were performed using a 4 bounce Ge 220 monochromator on the incident radiation. Rocking curve measurements were performed using an additional 3 bounce Ge 220 analyzer crystal.X-ray diffraction measurements were performed using a four-circle Malvern Panalytical Empyrean diffractometer, using Cu p < 2 × 10−6 Torr). The film was then exfoliated with two methods. Crystalbond 509 adhesive, with a flow point of 120 ∘C, was gently smeared on glass slide on a hot plate at 150 ∘C. The sample is then placed film-side down on the adhesive and allowed to cool. The membrane can be easily exfoliated by gently dropping the glass slide from a height of approximately one foot onto a clean surface. The force from the drop is enough to release the substrate from the membrane, leaving the membrane adhered on the glass slide. Thermal release tape  was also used to exfoliate by stamping onto the sample, and then carefully peeling the tape away from the substrate.To exfoliate the GaSb epilayer, a 100 nm Ni stressor layer was deposited on the GaSb / graphene / GaSb (001) heterostructure at room temperature using a metal evaporator (Angstrom Engineering Inc.) in high-vacuum (2.Steady-state photoluminescence (PL) measurements were performed at 300 K with a CW Ar-ion pump laser at a wavelength of 514.5 nm, using a 1500 nm (600 gr/mm) grating and a liquid-nitrogen cooled Ge detector. The power density was approximately 6.96 watts/cmSupplementary InformationPeer Review File