Several factors, both patient- and disease-related, are essential to accurately estimate acute myeloid leukemia (AML) prognosis. The rapidly evolving field, from both the genetic and therapeutic standpoints, and the availability of measurable residual disease (MRD) data have made traditional prognostic factors less reliable. Consequently, updated recommendations are trying to recapitulate the current scenario, but several questions remain to be answered, including the impact of complex co-mutational patterns and the role of clonal architecture. In the present review, we summarize established and new AML risk factors, and we discuss the emerging comprehensive approaches to effectively integrate all relevant prognostic data to better inform patient care.An accurate estimation of AML prognosis is complex since it depends on patient-related factors, AML manifestations at diagnosis, and disease genetics. Furthermore, the depth of response, evaluated using the level of MRD, has been established as a strong prognostic factor in several AML subgroups. In recent years, this rapidly evolving field has made the prognostic evaluation of AML more challenging. Traditional prognostic factors, established in cohorts of patients treated with standard intensive chemotherapy, are becoming less accurate as new effective therapies are emerging. The widespread availability of next-generation sequencing platforms has improved our knowledge of AML biology and, consequently, the recent ELN 2022 recommendations significantly expanded the role of new gene mutations. However, the impact of rare co-mutational patterns remains to be fully disclosed, and large international consortia such as the HARMONY project will hopefully be instrumental to this aim. Moreover, accumulating evidence suggests that clonal architecture plays a significant prognostic role. The integration of clinical, cytogenetic, and molecular factors is essential, but hierarchical methods are reaching their limit. Thus, innovative approaches are being extensively explored, including those based on “knowledge banks”. Indeed, more robust prognostic estimations can be obtained by matching each patient’s genomic and clinical data with the ones derived from very large cohorts, but further improvements are needed. The estimation of prognosis in acute myeloid leukemia (AML) is the result of a multilayered, integrated evaluation, which should consider several factors, both clinical, such as patient characteristics and disease manifestations at time of presentation, and biological ones . In addition to baseline variables evaluable at diagnosis, prognostic stratification of AML patients should consider evolutive parameters, such as measurable residual disease (MRD) at different pre-defined time points during therapy .Several steps contribute to AML outcome, including early death rate, refractoriness to induction, disease relapse, response after salvage therapy, and treatment-related mortality, and distinct prognostic variables impact differently on them. Indeed, disease characteristics at diagnosis and patient clinical conditions strongly impact early mortality, while the AML genetic background could predict the likelihood of achieving remission and the risk of relapse. Importantly, the impact of each prognostic factor can be influenced by therapy, and several discrepancies among published studies could be due to differences in treatment intensity or the drugs used, both in induction and during post-remission therapy . This concept has become even more relevant in recent years, since new agents have been added to standard intensive chemotherapy regimens  and novel formulations of drugs have been approved , which may modify the prognostic value of different clinical and biological factors. In addition, effective combinations of non-intensive treatments, such as hypomethylating agents (HMAs) plus venetoclax, are being increasingly used (mostly) for unfit patients, but assuming that traditional prognostic factors could play the same role in this new therapeutic context without adequate validation could be misleading. Treatment decisions are highly influenced by prognostic stratification, in particular, the allocation to HCT is usually limited to patients predicted to have a high risk of relapse with chemotherapy consolidation. However, it is important to consider that prognostic stratification in a specific therapeutic context significantly differs from a theragnostic-oriented approach. In the present review, we will focus on prognosis only, as an extensive discussion on how prognostic factors influence treatment choices can be found elsewhere ,2.Biological prognostication of AML has relied mostly on cytogenetics for a long time. In recent years, an increasing number of gene mutations have emerged as prognostic-relevant, initially in patients with normal karyotype and then regardless of cytogenetics, challenging conventional hierarchical risk stratification models. Furthermore, other factors such as gene expression signatures and clonal architecture are being confirmed as extremely relevant to further improve stratification accuracy. Finally, the role of a dynamic parameter such as MRD and its integration with baseline factors is being actively explored. Here, we review the established AML prognostic factors, and we discuss the emerging ones, focusing on innovative comprehensive approaches aiming to integrate and weight them. Summarizing the prognostic risk stratification of AML in specific contexts, such as children or relapsed patients, goes beyond the scope of this review, and these subjects have been recently reviewed elsewhere ,4.Age has been confirmed as one of the most relevant determinants of AML outcome in virtually all published studies, with 5-year survival for patients above 60 years not exceeding 10–15% even in recent reports, and particularly dismal results for those above 70 years .On the other hand, older patients often present with poor performance status and several comorbidities, which increase the chance of early death and treatment-related complications, also reducing the possibilities of effective salvage treatment in case of relapse or refractoriness to initial therapy ,8.Performance status is an easy and instantaneous picture of general conditions, with a clear impact on early mortality, the chance to achieve a complete response, and long-term survival . Indeed,Comorbidities are evaluated using different scores able to identify patients who would not benefit from intensive chemotherapy , which cIn the context of AML, hyperleukocytosis  is present in 5–20% of cases, and it is associated with an elevated risk of complications and early death . Indeed,Extramedullary disease, including central nervous system localizations, is associated with hyperleukocytosis, but its prognostic relevance is not firmly established. Indeed, the largest report published so far did not find an independent prognostic value after accounting for genetics and leukocyte count .Considering prior disease history, two ontological families can be distinguished: de novo and secondary AML (sAML).Secondary AML is itself a heterogeneous group, which includes AML deriving from an antecedent hematological disorder, namely myelodysplastic syndrome (MDS), myeloproliferative neoplasm (MPN), or aplastic anemia (AA), and therapy-related AML (t-AML), as a late adverse effect of prior cytotoxic chemotherapy or radiotherapy .TP53 and PPMD1 mutations [Inferior outcomes and lower response rates to intensive chemotherapy have been consistently reported ,24, withutations .Although globally associated with inferior outcomes, response to treatment and prognosis can vary considerably among patients. Along with clinical differences , should also be recognized, since it is characterized by particularly poor outcomes .The advances in understanding the biological mechanisms behind AML oncogenesis have uncovered complex interactions between cytogenetic aberrations and gene mutations, which are essential for an accurate prognostic estimation. Thus, risk classifications have moved away from a hierarchical approach, in which gene mutations were only considered in cytogenetically normal AML, to a more integrated one.Cytogenetic lesions and copy number alterations are reported in 50–60% of AML, and their role in determining risk stratification is a mainstay in biology-driven medicine , being cThe best example of good cytogenetic risk leukemia is represented by acute promyelocytic leukemia (APL), identified with t in the vast majority of cases . Given tRUNX1::RUNX1T1 and CBFB::MYH11, respectively [RUNX1::RUNX1T1 and CBFB::MYH11 AML [CBFB::MYH11 [The other recognized favorable cytogenetic risk group is represented by CBF leukemias, including AML with t and inv(16)(p13.1q22) or t, whose fusion products are ectively ,46. CBF ectively . HoweverYH11 AML ,49,50. GB::MYH11 ,51,52, tB::MYH11 ,48,53,54CBFB::MYH11 cases [In the pivotal Medical Research Council (MRC) cytogenetic study on 5876 young adults with AML, including 705 cases of CBF leukemias , no sign11 cases ,55,56,57c-KIT has been the most widely studied, and its negative impact in RUNX1::RUNX1T1 AML emerged in several [Among co-occurring gene mutations,  several ,59,60,61 several ,63 reporFLT3-ITD mutations are present in 10–20% of CBF leukemias [FLT3-ITD was of negligible clinical significance in this context [eukemias , and someukemias ,64, posseukemias , or when context ,65.KMT2A (MLL) rearrangements occur in roughly 5% of AML, in the context of balanced translocations involving 11q23 breakpoints with various possible partner loci [ner loci .KMT2A-rearranged AML, t/KMT2A::MLLT3 are associated with a higher response rate to intensive chemotherapy compared to other translocations [KMT2A-rearranged subtypes [Among ocations  and are subtypes .DEK::NUP214 is frequently characterized by bone marrow dysplasia and additional cytogenetic abnormalities. The frequent (70–80% of the cases) co-occurring FLT3-ITD aberrations lack a confirmed prognostic significance in this already poor-risk group [Among adverse cytogenetic lesions, t/sk group ,68.MECOM (EVI1) gene as well, are also associated with dismal prognosis and were added to the 2022 ELN adverse risk group [AML with inv(q21.3q26.2) or t depicts a subset of particular poor-outcome with long-term survival chances extremely unlikely with conventional treatments ,69,70. Osk group ,71.BCR::ABL1 is now recognized by the fifth WHO and the ICC classification [AML with t9;22)//onfirmed ,76.Among partial deletions and monosomies, those involving chromosomes 5, 7, and 17 are well-established poor prognostic factors ,41,42. ATP53 mutations, and atypical CK, which is associated with slightly better outcomes [Complex karyotype (CK) is commonly defined by the presence of three or more cytogenetic unrelated chromosome abnormalities in the absence of other recurring class-defining genomic lesions and is invariably associated with poor prognosis ,43,78,79outcomes .The importance of monosomies has been confirmed both within and outside CK, in particular in cases with a monosomal karyotype (MK), defined by Breems and colleagues as the presence of two or more monosomies or autosomal monosomy together with at least another karyotype abnormality . Indeed,Finally, chromosome trisomies appear to exert a different impact, being more often associated with intermediate risk , with isFLT3) occur in approximately 30% of AML and are frequently associated with normal karyotype, NPM1 mutations (40%), and DEK::NUP214-AML (70%) [FLT3-ITD), while the remaining ones harbor point mutations in the tyrosine kinases domain (TKD), more frequently in the D835 residue.Mutations in FMS-like tyrosine kinase 3 (ML (70%) . More thFLT3-ITD has been consistently associated with poor prognosis and high relapse risk, which can vary according to its AR , size (longer being worse), and location of ITD insertion (TKD1 site being worse) [g worse) ,89,90,91FLT3-ITD showed independent prognostic information in each genic class and could upgrade risk for all intermediate-risk patients to adverse-risk [Recently, in the genetic classification proposed by Tazi and colleagues, rse-risk .FLT3-TKD mutations do not exert an independent prognostic impact [CBF, NPM1 vs. KMT2A-PTD-positive AML) [c impact , albeit c impact ,93, possive AML) ,90,94.NPM1) mutation is a class-defining genetic lesion, as consistently confirmed [Nuclophosmine 1 , but their genetic signature and prognosis overlapped with that of de novo NPM1-mutated AML, outlining the genetic and prognostic diversity between t-NPM1 and t-AML [NPM1-mutated AML as such, independently of the previous clinical history [Rarely, nd t-AML . In accond t-AML , the cur history ,38.CEBPA) mutations are found in roughly 10% of AML patients [CEBPA site were associated with good prognosis, irrespective of their occurrence as biallelic or monoallelic, prompting a modification of the current classifications and prognostic stratifications [CCAAT/enhancer binding protein α  frequently presents with a higher rate of additional chromosomal abnormalities compared to monoallelic/single-hit mutation and significantly worse prognosis [TP53 was also shown in AML [TP53 variant allele frequency (VAF) [In MDS, multi-hit rognosis . Indeed,n in AML ,116,117,cy (VAF) . Howevercy (VAF) , suggestRUNX1 mutations have been associated with reduced response and survival in several studies [ASXL1 aberrations consistently showed an adverse prognostic impact [RUNX1 and other epigenetic modifiers. Thus, both gene mutations were introduced as poor prognostic markers in the ELN 2017 risk classification [ studies ,121,122, studies . Similarc impact ,123,124,fication .BCOR, EZH2, SF3B1, SRSF2, STAG2, U2AF1, and ZRSR2 were recognized in the ICC as determinants for the entity of “AML with myelodysplasia-related gene mutations” irrespective of previous disease history [SETBP1 and KMT2A-PTD aberrations), the association with adverse prognosis was specific to patients with ≥two mutations  while the minority of patients with a single gene mutation experienced an intermediate outcome  [More recently, these genes together with  history , and the history ,39. Howe of 37%) . Further of 37%) ,127.The role of several gene mutations has been explored in the last decade, mostly with inconclusive results ,128,129.DNMT3A mutations, strongly associated with age-related clonal hematopoiesis, were associated with unfavorable outcomes in older studies [DNMT3A mutations were shown to be useful to refine the 2017 ELN stratification, since their presence worsen the prognosis in each subgroup [ studies ,131, but studies ,122,132.subgroup .KMT2A (KMT2A-PTD), which was associated with unfavorable prognosis in several studies [Roughly 5% of AML cases harbor partial tandem duplication of  studies ,133. How studies , possibl studies  and some studies ,134. As  studies .WT1 prognostic role has been suggested in some studies, but the inconsistency among reports prevented its uniform acceptance [WT1 mutations in the absence of other classifying events identified a specific AML cluster with intermediate risk [The ceptance ,135,136.ate risk ,137.PTPN11, a regulator involved in RAS signaling, have been associated with poor prognosis in three recent reports [PTPN11 appeared restricted to NPM1-wild-type patients in one report [Mutations of  reports ,139,140.CREBBP gene is rarely disrupted in AML and mainly rearranged with different translocation partners, most frequently KAT6A at 8p11 [CREBBP-disrupted cases experience worse event-free survival and increased relapse risk compared to wild type ones [The  at 8p11 ,141, seeype ones . HoweverDDX41 are the most common ones and are often found in advanced age. Recently, DDX41 mutations have been associated with increased complete remission rates and rather favorable survival, both in real-life analyses and prospective clinical trials [Among germline mutations predisposing to MDS and AML, those affecting l trials ,144.DNMT3A, TET2, ASXL1) or in germline predisposition syndromes . Moreover, mutations in signaling pathway genes  likely represent residual leukemia when detected, but being often sub-clonal, they have a low negative predictive value. Finally, most studies exploring the prognostic value of MRD in AML are heterogeneous in terms of the patient population (age and AML subtypes), the timing of MRD assessment, and the source  [Although it is widely agreed that residual leukemic cells lead to recurrent disease in acute leukemias, the recognition of the role of MRD in AML has been slower compared to acute lymphoblastic leukemia (ALL), a disease in which MRD has been accepted as the strongest prognostic factor . MRD ass marrow) . However marrow) , and in  marrow) . Indeed, marrow) . Given t marrow)  (Table 1 marrow) .While the prognostic role of MRD is established in young and fit patients receiving intensive chemotherapy, there is limited evidence for its clinical significance in patients treated with low-intensity prolonged regimens, probably reflecting the low chances of deep and prolonged remissions. Recently, the introduction of venetoclax-based combinations led to increased CR rates and response durations, prompting researchers to evaluate MRD impact in this setting as well .In the VIALE-A study, MRD-negative responses were achieved in 41% (67/164) of patients obtaining composite CR, with significantly prolonged remission duration and survival compared to MRD-positive cases. Multivariate analysis confirmed that MRD-negative CR was a strong independent predictor of OS . The rolSeveral studies have shown that patients undergoing HCT in MRD-positive CR have worse survival and increased relapse risk compared to MRD-negative ones ,153. BucRisk stratification algorithms are widely used to estimate AML patients’ prognoses and make therapeutic decisions. Indeed, these simplified systems are built to summarize the available evidence and, importantly, to identify prognostic factors whose role is robust and reproducible enough to inform clinical practice. The classification proposed by ELN is probably the most widely used, including by the last version of the NCCN guidelines, and it has recently been updated ,125,155.FLT3-ITD AR and its interaction with NPM1. Patients harboring FLT3-ITD with low AR  with NPM1 mutations and those without NPM1 aberrations but with FLT3-ITD with high AR were categorized as favorable and adverse-risk using the 2017 classification, respectively [FLT3-ITD patients lacking favorable cytogenetics or adverse genetic lesions in the intermediate risk group, given the challenges posed by the standardization of the assay measuring AR, the evidence of a beneficial impact of midostaurin-based regimens in FLT3-ITD AML irrespective of AR and NPM1 mutational status, and the increased role of MRD [Probably the most relevant changes regarded ectively . Converse of MRD ,156.CEBPA mutations are now considered favorable-risk irrespective of CEBPA biallelic or monoallelic mutational status.Patients with in-frame bZIP NPM1-mutated patients with adverse cytogenetics are considered at adverse risk.Hyperdiploid karyotypes with three or more trisomies without structural abnormalities are excluded from the group of CK.RUNX1 and ASXL1, other MDS-related gene mutations  are added as poor-risk prognostic markers in the absence of favorable risk genetics.In addition to MECOM and t/KAT6A::CREBB.New high-risk rearrangements are included, namely t/TP53-mutated.At least a 10% VAF is required to classify patients as Furthermore, the ELN 2022 considered several of the studies discussed above to update its classification:Recently, the updated classification was validated in large cohorts of intensively treated younger de novo AML patients ,157, altTP53, N/K RAS, and FLT3-ITD, which requires validation [Conversely, a recent analysis of the VIALE-A outlined how the ELN classification does not adequately stratify patients treated with HMA and venetoclax, confirming that different prognostic algorithms will be needed in this therapeutic context. Thus, the author proposed a stratification system based on the mutational status of lidation .Finally, dynamic parameters, i.e., treatment response including MRD, are increasingly stressed in the guidelines , as they significantly modify baseline prognostic stratification, in addition to informing treatment decisions .The prognostic impact of several biological factors has been explored in AML, although they have not entered clinical practice yet.Long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs) are three noncoding RNA molecules that regulate DNA transcription and translation . The expMiRNAs are involved in tumorigenesis both as oncogenes and tumor suppressors. In rather old studies, the up-regulation of miR-181a was associated with a favorable prognosis, while higher expression of miR-155, miR-196b, and miR-644 was associated with a shorter OS ,168,169.MYC amplification, but survival implications are yet to be proven [Finally, circular RNAs (circRNAs) can be overexpressed in AML, but data are scantier. CircPVT1 was shown to be overexpressed in AML harboring oncogene e proven .DNMT3A, TET2, IDH1/2) being among the most frequently mutated in AML [DNA hypermethylation and the subsequent inactivation of tumor suppressor genes play a key role in AML pathogenesis, with methylation genes  plays a pivotal role in driving AML relapse; thus, assessing AML LSC gene expression signatures has been proposed as a method to further refine prognosis. Indeed, several signatures and scores have been proposed ,179,180.MDR1 gene product), whose hyperexpression was mostly associated with worse prognosis [The impact of protein expression in AML has long been studied, with an early focus on proteins involved in chemotherapy resistance, such as P-glycoprotein  was characterized by high expression of mitochondrial proteins and was associated with poor prognosis, with low CR rates and shortened survival after intensive chemotherapy. Finally, functional analyses suggested that Mito-AML could be more responsive to venetoclax-based treatments .BH3 profiling is a functional approach that can predict the cellular dependence on anti-apoptotic proteins like BCL-2 or MCL-1, based on mitochondria depolarization in response to a panel of BH3 sensitizer peptides. BH3 profiling was hypothesized to predict response to chemotherapy in AML some years ago , and recTP53, as discussed above. Specific combinations seem to be synergistic, such as DNMT3A and IDH1/2, as they frequently co-occur in AML [Beyond the prognostic impact of individual mutations in AML, their association with a patient could refine prognosis prediction . Allelicr in AML , are assr in AML , and conr in AML ,197. Higr in AML  or inferr in AML , have alr in AML ,200. Brar in AML . Most ofr in AML ,201. Sinr in AML . Emerginr in AML ,204.Despite the effectiveness of current prognostic stratification algorithms, such as the ELN2022 one, other clinical parameters, such as age, leukocytosis, or performance status exert a relevant prognostic impact, as previously discussed. Indeed, they interact with genetic lesions and can influence patients’ outcomes .Another strategy to integrate cytogenetic, molecular, and clinical factors has been the development of scoring systems , which, FLT3 (ITD vs. TKD), but this may also be the case for DNMT3A (R882 vs. others) [KIT (exon 8 vs. 17) [Clearly, hierarchical step-by-step integration approaches including cytogenetic and molecular aberrations are no longer able to recapitulate the full spectrum of AML. First, not all mutations in a given gene exert the same impact, as clearly established for  others)  or KIT ( vs. 17) . Second, vs. 17) ,208. ThiThus, in recent years, machine learning approaches have been proposed to overcome these issues.NPM1-mutated patients, applying a machine learning algorithm developed to identify combinations of up to four co-mutated genes with a potential impact on OS. Using a heuristic search algorithm and bootstrap sampling, they estimated the impact of all possible gene combinations on OS. Combining the mutational status of a few genes, namely TP53, FLT3-ITD, IDH, DNMT3A, PTPN11, N/K RAS, and RAD21, the authors stratified NPM1-mutated cases into four groups with significantly different outcomes, thus proposing a new genetic stratification model for these patients [In the context of the European Union-funded HARMONY project, Hernández Sánchez and colleagues analyzed 1093 intensively treated patients .https://cancer.sanger.ac.uk/aml-multistage, accessed on 1 June 2023). Huet and colleagues were later able to validate the KB approach in a real-life setting, confirming that it outperformed the survival prediction achieved with current risk classifications and the robustness of the algorithm to missing data [https://www.aml-risk-model.com/calculator, accessed on 1 June 2023).A different emerging approach, aiming to integrate the most available prognostic information layers without relying on studies on specific genetic interactions, was first reported by Gerstung and colleagues. The authors developed a multistage model based on matched clinical and genomic data from more than 1500 AML patients , which cing data . More reing data . The Paping data . An onliNPM1 MRD. Finally, the authors devised an online decision tool  [Focusing on its ability to guide HCT decisions in first CR1, Fenwarth and colleagues analyzed the performance of the KB approach for intensively treated younger patients in the context of the ALFA-0702 clinical trial. Not only were the authors able to demonstrate the superiority of this method to standard prognostic stratifications, but a personalized and appropriate HCT decision was derived using the integration of the KB approach with ELN 2017 risk score and, importantly, ne 2023) . A Frencne 2023) ,215. IndKB-based approaches have been shown to improve tailored therapeutic decisions; however, several limitations still exist. Since new effective treatments are being approved , the surFurthermore, inclusive cohorts are required, to avoid overlooking certain subgroups . Importantly, when focusing on a particular setting such as HCT, specific factors should ideally be considered, such as donor type and conditioning regimens .NPM1-mutated AML patients, higher relative drug activity was associated with an independent positive impact on event-free survival in that cohort [Despite its enormous prognostic relevance, a detailed genetic characterization and its integration with clinical data cannot fully depict AML behavior, as all the aforementioned methods are far from reaching perfect accuracy. Indeed, functional assays could complement genetic risk stratification to identify patients achieving long-term survival with intensive therapy. With this approach, the direct exposure of patients’ AML primary cells at diagnosis to several drugs can undercover specific vulnerabilities and resistance patterns, which could be used to personalize therapeutic choices . In theit cohort . AlthougHuge advances in AML biology have led to an increasing complexity in prognostic estimation, as newly discovered factors are entering an already challenging scenario. Furthermore, several new treatments have been approved in the last years, and the impact of prognostic factors established in cohorts of conventionally treated patients should be confirmed in the new therapeutic context, both with intensive and non-intensive therapies.Thus, new machine learning-based tools are being developed to integrate established prognostic factors in an evolving therapeutic scenario of a relatively rare disease, hopefully increasing the prediction accuracy of current models, which remain limited at the single-patient level , to whom


Simulating physical dynamics to solve hard combinatorial optimization has proven effective for medium- to large-scale problems. The dynamics of such systems is continuous, with no guarantee of finding optimal solutions of the original discrete problem. We investigate the open question of when simulated physical solvers solve discrete optimizations correctly, with a focus on coherent Ising machines (CIMs). Having established the existence of an exact mapping between CIM dynamics and discrete Ising optimization, we report two fundamentally distinct bifurcation behaviors of the Ising dynamics at the first bifurcation point: either all nodal states simultaneously deviate from zero (synchronized bifurcation) or undergo a cascade of such deviations (retarded bifurcation). For synchronized bifurcation, we prove that when the nodal states are uniformly bounded away from the origin, they contain sufficient information for exactly solving the Ising problem. When the exact mapping conditions are violated, subsequent bifurcations become necessary and often cause slow convergence. Inspired by those findings, we devise a trapping-and-correction (TAC) technique to accelerate dynamics-based Ising solvers, including CIMs and simulated bifurcation. TAC takes advantage of early bifurcated “trapped nodes” which maintain their sign throughout the Ising dynamics to reduce computation time effectively. Using problem instances from open benchmark and random Ising models, we validate the superior convergence and accuracy of TAC. Physical and physics-inspired computation is emerging as a new paradigm for tackling hard optimization problems. In this work, the authors establish rigorous mathematical conditions together with new design principles for physical as well as simulated dynamical systems to solve general Ising models. Solving QUBOs was shown to be NP-hard8, limiting scalability of good solutions to the order of hundreds to thousands of variables—even for approximate algorithms11.Quadratic unconstrained binary optimization problems (QUBOs) are of great importance for a large variety of disciplines—encompassing systematic drug design14 from the 1980’s, with more general dynamics and control mechanisms, allowing for stronger scalability and convergence properties22. As experimental realizations of so-called Ising machines deem challenging26, the system dynamics have commonly been simulated on conventional computers30. Such approach has proven successful for medium- to large-scale optimizations of up to hundreds of thousand variables32, and even lead to special-purpose chip hardware implementations37.Alternative approaches based on the encoding of problems into the dynamics of physical systems have been proposed, drawing inspiration from the Hopfield and Hopfield-Tank neural networks39 suggested an intriguing interplay between nonlinearity of the dynamics (with a focus on coherent Ising machines (CIMs)) and structure of the coupling network in determining the success of solving the discrete Ising problem. Generally, relaxations of integers to reals often lead to suboptimal solutions42, due to a continuous interpolation of the discrete optimization landscape. Since the landscape changes dynamically during the evolution, it is essential to understand when Ising machines are able to identify correct solutions of the QUBO39. These insights would lead to lower bounds of the algorithm run-time, which can (1) prevent failure of the optimization because of too short evolutions, and (2) serve as a stopping indicator to avoid long execution times. Yet, such lower bounds have not been reported and are generally unknown.Despite the reported performances, the simulated dynamics is accompanied by a fundamental issue: the equations of motion of Ising machines are continuous , while the QUBO problem is discrete (binary). In particular, empirical observations as reported in refs. synchronized bifurcation of all nodal states. This scenario is found to impose lower bounds on the magnitudes of the nodal variables. Unlike previously reported, we show that individual nodal variables in Ising machines often do not bifurcate synchronously, but rather undergo a sequential cascade of instabilities. Such delayed bifurcation behavior constitutes a phenomenon which we refer to as retarded bifurcation. We attribute such retardations to the presence of swing nodes, which are subject to geometrical frustrations in the Ising machine. Swing nodes are found to oscillate in values around zero, potentially leading to unfeasible run-times and suboptimal solutions. Importantly, we show that the number of swing nodes in the state of the Ising machine at the first bifurcation point constitutes a key indicator for the deviation from the exact mapping threshold. Finally, we build upon these insights to design a trapping-and-correction (TAC) approach based on defrustration and stabilization mechanisms to accelerate convergence and enhance the performances of simulated physical solvers.In this work, we address the very question of when an Ising machine derived from continuous dynamics solves its corresponding discrete Ising model. Many of the findings are based on analysis of the simulated dynamics from the perspective of dynamical systems and bifurcation theory. We show that exact mapping between an Ising machine and the corresponding QUBO can only emerge when the control parameter of the evolution crosses a critical threshold. We prove sufficient conditions for exact solvability for the simulated dynamics, and attribute the conditions to a 43,σ ∈ {−1, +1}n is the vector of n interacting spins σ1, σ2, . . . , σn and G represents a symmetric coupling matrix. Configurations σ* which yield the minimum Ising energy are known as the ground states, and the corresponding HIsing(σ*) is the energy of the ground state. It was shown that many NP-complete and NP-hard problems can be cast in the form of minimizing HIsing(σ) in Eq.  as − ∇ U = F, and the functions fi and gij implement the self and interactive couplings, respectively. This work focuses on coherent Ising machines (CIM) as a quantum-photonic implementation of physical Ising machines27, and we note that the derived results could be extended to other dynamics characterized by the general form of Eq. . By setting p appropriately, it was shown that CIMs can successfully solve certain intermediate to large scale QUBOs27.So-called n in Eq.  into a c38, shedding light on the intrinsic challenges caused by the complex topological structure of the phase space of the CIM dynamics and the interruptions in the adiabatic trajectories of fixed points. Success of the CIM strongly depends on the mapping between the continuous dynamics as in Eq.  can be mapped to the ground state of HIsing(σ) after binarization for certain control parameter values50 , at which the qualitative dynamical behavior of the system is affected by instabilities51. Here, p0 denotes the first bifurcation point, p1 the second, and so on. Furthermore, we denote x* as any fixed point of Eqs.  of the CIM. It is the unique solution until the first bifurcation point p = p0 at which the state x0 loses its stability, i.e., when the largest eigenvalue of p0 can be computed as G. The bifurcation direction x0 is the eigenvector of J corresponding to the zero eigenvalue, denoted as p is further increased, subsequent bifurcations may occur at (both stable and unstable) fixed points x* if For fixed entclass1pt{minimap on the ability of the Ising machine to find the correct ground state of HIsing, we consider random instances of connected graphs consisting of n = 5 variables with random symmetric coupling matrices G ∈ {+1, 0, −1}n×n. In the following, we use p* to denote the minimum pump rate p under which there exists a local minimum x* of U whose binarization yields the ground state of the Ising problem (see Methods section for details of determinations of p*). Note that sometimes the system may not strictly undergo a bifurcation at p* but instead some nodal states cross over to change its sign leading eventually to the optimal solution after binarization , and of an outlier (p* > p0) . Note that x1 are more centralized away from zero, the larger the value of α2(x1). Then for any Ising Hamiltonian H(σ)  and H0 of the ground state of HIsing(σ), and let G. Ifσ1 = sign(x1) attains the energy of ground state, i.e.Given a non-zero real symmetric matrix s in Eq. . Let \doentclass1pt{minimaIM (Eqs. )—which i with p* = p0 and p* > p0 respectively. See Supplementary Note p* = p0. It can be seen that no components are close to zero, corroborated by the observation that 88% of instances satisfy the sufficient condition in Theorem 1 and the average degree of synchronization is 〈α2(x1)〉 = 0.90, compared to the average threshold x1) tends to yield the optimal solution to the problem. We also confirm experimentally  Instances with p* > p0. The distribution of magnitudes becomes bimodal: the components ∣xi1,∣ of the system state constitute an additional peak in counts for values around zero, with an average degree of synchronization 〈α2(x1)〉 = 0.73, compared to the average threshold H(σ1) attains the ground state energy, there exists an index j such that p0, then p* > p0 and further bifurcations at larger values of p are necessary to fully determine the signs of those variables, c.f. Fig. swing nodes, as they are observed to oscillate between negative and positive values around origin until a bifurcation traps them  =  and  resulting in the same topological configuration. The degeneracy of these two states causes the stationarity of  at the bifurcation point, and further increase of the pump rate is required to break the symmetry. Furthermore, we analyzed an additional 1000 random instances with n = 5 and found that whenever the first bifurcation state contains a zero component, it belongs to at least one frustrated loop. This constitutes a necessary condition for the occurrence of a swing node. We caution that the condition is necessary but not sufficient. Specifically, there are frustrated loops that do not result in swing nodes.The occurrence of swing nodes indicates the presence of frustration in the system. Frustrations, which are known to generate multiplicity of local minima in combinatorial optimization, generally make the problem hard and cause high algorithmic complexityp* > p0, it is generally difficult to classify the complexity of the problem, as the dynamics of the optimizer add an own layer of complexity to the problem20. The presence of retarded bifurcation and swing nodes become more significant with growing problem size n, leading to increasing deviations of the binarized first non-trivial state of the CIM from the optimal solution  Suboptimal solutions. Without exact knowledge of p* there is no guarantee to stop the evolution precisely when the system is in the ground state. If p < p*, the fluctuations of swing nodes around zero assigns random values to the variables; for p > p* the probability of finding the ground state by the CIM dynamics decreases with increasing p as more local minima emerge16; (ii) Long run-times. For retarded bifurcations in larger optimization problems many bifurcations might be needed to decide all swing nodes—often accompanied by unfeasible execution times; (iii) Insufficiency of the heuristics. With growing problem size, variables with small amplitudes are increasingly common  and its variants, including ballistic SB (bSB) and discrete SB (dSB)We now show how the above insights allow us to develop an acceleration technique which improves the speed of convergence when combined with dynamics-based Ising machines. This approach, which we term trapping-and-correction (TAC), is visualized in Fig. 19 (an improved version of SB which is robust and can achieve better results) to demonstrate how the TAC approach works. In TAC-CIM and TAC-bSB, the system is first evolved according to the dynamical equations in Eq. . Then, nodes are classified into trapped and swing nodes based on a cut-off threshold k being a tunable parameter. Trapped nodes, whose amplitudes are larger than the cut-off, are set to bit values according to their signs. Swing nodes, whose amplitudes are less than the cut-off, are randomly sequentially assigned binary values based on the interaction fields due to their neighbors. Then, every node is individually stabilized by examining the change in energy of the global state under bit flips. Note that this TAC approach is not restrictive to a particular form of dynamics, and can generally be used in other continuous-dynamics based Ising machines by simply adapting Eq.  we prove that the continuous dynamics solves the discrete optimization; on the other hand, when there is a partial set of nodes whose states remain ϵ-close to zero (retarded bifurcation) then further increase of the control parameter is necessary for the continuous system to evolve towards the desired discrete optimum. Such retardation in bifurcations constitutes a previously unnoted phenomenon, which correlates with the complexity of the problem and strongly impacts the performance of the Ising machine. We attribute retarded bifurcations to frustrations that are commonly inherent in the Hamiltonian, and necessitate the presence of small-amplitude components in the maximum eigenvector of the coupling matrix. The respective variables are called swing nodes whose values oscillate around the origin. Consequently, further bifurcations are necessary to determine the correct binary values of the nodes. In order to iteratively eliminate swing nodes, we develop a procedure that sequentially assigns binary values to swing nodes according to their local interactions in the network. The proposed trapping-and-correction (TAC) approach—drawing structural insights from CIM dynamics—was found to be effective in a number of dynamics-based Ising machines including CIM, SB, bSB and dSB, when extended to larger systems, yielding increased probability of finding ground states and reduced run-times. These results provide important insights regarding the link between continuous physical dynamics and discrete combinatorial optimization, and can potentially lead to enhanced parameter control schemes for nonlinear and physics-inspired optimization approaches.The emerging computational paradigm of utilizing continuous physical dynamics for solving combinatorial optimization problems proves to be a promising alternative to conventional algorithms. The ultimate success of this approach relies on understanding when evolving such continuous dynamics becomes equivalent to minimizing objectives with discrete variables. In this work we investigate this open question by analyzing the bifurcation dynamics of coherent Ising machines. We find that the Ising dynamics at the first bifurcation point fundamentally determines optimality of the continuous solution. At the first bifurcation, if all nodal states simultaneously change from zero to values that are n binary variables 55q(z) is minimized over all binary strings of length n, with a total of 2n possible choices. Many NP-complete and NP-hard problems can be cast in the form of Eq.  into an Ising Hamiltonian HIsing of n interacting spins43σi ∈ {−1, +1} is the i-th spin value and coefficient Gij denotes the coupling strength between spins i and j. The single-spin terms hi can be absorbed by introducing one auxiliary spin σn+1 and extending G by one row and one column to incorporate hi. Minimizing the energy of HIsing then solves the corresponding QUBO. The explicit form of certain NP-complete problems as Ising Hamiltonians was derived in ref. 44.Given p* as the minimum p such that there exists a local minimum U whose binarization leads to the ground state of the Ising problem. That is, let For the dynamics-based Ising machine Eq. , we defip* generally cannot be computed analytically, and requires numerical approximation methods. For the examples shown in this study, we manage to provide estimation for small-scale graphs, where the ground state Ising energy p*, starting with an initial interval  where we typically choose pl = p0 ≤ p* and pr be a sufficiently large number (to ensure that pr > p*). Middle point of the interval pm = (pl + pr)/2 is examined, by using a large number of random states followed by Newton’s method to obtain an approximation pm ≥ p* and update the right side of the interval pm ← pr, otherwise we have pm < p* and we update the left side of the interval instead as pl ← pr. This process continues until a pre-set resolution limit ϵ is met: ∣pl − pr∣ < ϵ. The terminal value pm is then used as an approximation of p*.The exact value of p* = p0 or p* > p0 needs to be decided, such as the example in Supplementary Note G to determine p* = p0, and otherwise p* > p0).For the cases where only A = 10−3 and θi is uniformed sampled from ; For bSB and dSB, xi(0) and yi(0) are uniformed sampled from range .During the simulations, the settings of the parameters are as follows: For SB, Hi when flipping one spin σi ∈ {−1, 1} as σi) = sign(yi), with k is set to the value sign(yk). The stability criterion is used both for the defrustration of swing nodes  approach which improves the performance of standard CIM and bSB both in convergence time and precision. The TAC approach consists of two main stages, defrustration and stabilization. In the following we explain the local stability criterion which is used for defrustration of the nodes, as well as stabilization of the system configuration. We consider the energy difference ΔSupplementary Information


Oryctolagus cuniculus) is a local breed in Indonesia. We reveal the mitochondrial genome sequence of the Indonesian local Rabbit for the first time. A better understanding of the mechanisms underlying these beneficial aspects of local breeds over imported ones requires detailed genetic investigations, of which mtDNA genome sequencing is of particular importance. Such an investigation will solve the major issues of misidentification with Javanese hares (Lepus nigricollis) and maternal lineage. In addition, this information will guide better statistics on the Indonesian local rabbit breed population and strategies for its conservation and breeding plans. This study aimed to identify and explore the characteristics of the mtDNA genomes of Indonesian local rabbits.Indonesian local rabbit , 22 transfer RNA genes , 13 protein-coding genes (PCGs) , a replication origin, and a noncoding control region (D-loop).Oryctolagus cuniculus. Other specific differences were also found in the percentage of nucleotides and variation in most of the PCGs when they were aligned with Oryctolagus cuniculus references from GenBank. Indonesian local Rabbits strongly suspected brought from Europe during the colonial period in Indonesia.mtDNA genome of Indonesian local rabbit was the longest and had the most extended D-loop sequence among the other references of The online version contains supplementary material available at 10.1186/s43141-023-00546-1. Oryctolagus cuniculus) has high economic value and a significant contribution to food and livelihood security, with the potential to be raised at the commercial level. Rabbit breeds in Indonesia are dominated by imported rabbit breeds and their crossbreeds, such as New Zealand White, Rex, Flemish Giant, Satin, and Angora [Rabbit  and maternal lineage. In addition, this information will guide better statistics on the local rabbit breed population and strategies for its conservation and breeding plans. The results of this study are expected to provide information for additional examination of mtDNA sequences in favor of rabbit genetic research. Additionally, mtDNA genome sequencing analysis offers a fresh perspective on the genetic makeup of rabbits.The mtDNA sequencing is of paramount importance in determining the maternal lineage and tracing the origin of locally available local rabbit breeds. In addition, it can determine the genetic distance and genetic relationship between Indonesian local rabbits and other rabbit breeds. White et al.  demonstrThe experimental procedures were approved by the Animal Research Ethics Committee of the Faculty of Animal and Agricultural Sciences, Universitas Diponegoro (No. 59–01/A-01/KEP-FPP).Oryctolagus cuniculus) isolated from the liver tissue. The rabbit was slaughtered and dissected to collect the liver tissue. Tissue samples (10 g) were stored in Falcon tubes containing ethanol. Tissue samples were used to obtain gDNA. gDNA was extracted according to the manufacturer’s standard protocol using the Quick-DNA Magbead Plus Kit . The collected gDNA was then selected based on quality and quantity, and genomic mtDNA enrichment was conducted using the REPLI-g Mitochondrial DNA Kit . The library preparation process used the enhanced mtDNA.This study used gDNA from an Indonesian local rabbit . MitoZ (v2.4) was used to annotate and visualize the final sequences [mtDNA sequencing was performed using WGS mtDNA analysis with nanopore technology , 13 by Oi et al. ); MN9536i et al. ); MH9858i et al. ) and MN2i et al. ). Flye , 22 transfer RNA genes , 13 protein-coding genes (PCGs) , a replication origin, and a noncoding control region (D-loop) Fig. . The genThe total length of 13 protein-coding genes (PCGs) in this study was 11.323 bp, from the shortest to the longest sequence (bp), and amino acid (aa) lengths were as follows: ATP8 , ND4L , ND3 , ND6 , ATP6 , COX2 , COX3 , ND1 , ND2 , CYTB , COX1 , ND5 , and ND4 . Nine of the 13 PCGs begin with the start codon ATG, while the rest start with the start codons ATA (ND3) and ATT . The stop codons in the Indonesian local rabbit sequence were dominated by TAG , while the rest were TAA , AGG (CYTB and ND6), and TAT (ND4).Oryctolagus cuniculus) in this study showed variation in most of the PCGs when they were aligned with all references (Supplementary data th (C➔T). However, this mutation was silent and did not alter the amino acid sequence. The ND3 gene sequence of the Indonesian local rabbit had length 357 bp. At the same time, when aligned with all references, there were a silent transition mutation at site 9th (A➔G) and the insertion of a 10 bp nucleotide (TGATAATTAG) in the end section of the ND3 gene.The Indonesian local rabbit (nd (G➔A) in the Indonesian local rabbit as a silent mutation. Similar to the ND4L gene results, the ND5 gene of the Indonesian local rabbit showed the same length in all references (1378 bp). However, when it came to alignment, there were several point mutations at certain sites, namely 187th (C➔G), 321st (C➔T), 891st (T➔C). The point mutation at site 187th (C➔G) was a transversion mutation, which was interpreted as a missense mutation and was located in the first codon. This resulted in different amino acid sequences between leucine (CTA) in the Indonesian local rabbit and valine (GTA) in all references. Mutations at sites 321st (C➔T) and 891st (T➔C) were transition mutations identified as silent mutations. Moreover, ND6, a missense point mutation, was found at site 16th (G➔A) when the Indonesian local rabbit was aligned with all references. This mutation in the first codon caused a difference in the Indonesian local rabbit with amino acid aspartic acid (GAT), compared to all references with asparagine (AAT).The alignment results of the ND4L gene sequence showed that the Indonesian local rabbit had the same length compared to all references (297 bp). Nevertheless, when the Indonesian local rabbit ND4L gene sequence was aligned with all references, a transitional point mutation was found at site 162th (A➔C) as a transversion mutation and at 1479 (G➔A) as a transition mutation; however, both mutations were silent. The sequence of the COX2 gene of the Indonesian local rabbit was 684 bp in length, which is similar to all references. However, there was a silent point mutation at site 207th (G➔A). Furthermore, an insertion was found in the end section of the COX3 gene in the Indonesian local rabbit that was 20 bp long with the sequence ACTCTTTTAGTATCAACTAG in the end section of the COX3 gene. Thus, the COX3 gene in the Indonesian local rabbit is 804 bp in length.The alignment results of the COX1 gene sequence of the Indonesian local rabbit showed the same length in all references (1542 bp) but varied at specific sites. These variations were found at site 1017st (G➔A), which was interpreted as a missense mutation. This mutation in the first codon caused a difference in the amino acid sequence; the Indonesian local rabbit showed alanine (GCT), whereas all references showed threonine (ACT).Further variations were also observed in ATP6. This study showed a 681 bp in length of ATP6 gene with the insertion of a 1 bp nucleotide at the end section of the ATP6 gene in an Indonesian local rabbit in the form of adenine. Conversely, the ATP8 gene of the Indonesian local rabbit showed no variation when aligned with all references, and it also had the same length (204 bp). The CYTB gene of the Indonesian local rabbit in this study was 1140 bp in length. When the CYTB gene sequence of the Indonesian local rabbit was aligned with all the references, there was a point mutation at site 571th (T➔C). Furthermore, sequencing results showed that the 16S rRNA sequence of the Indonesian local rabbit was 1581 bp, flanked by trnV and trnL. Moreover, the alignment results showed that there was variation at site 1110th in the 16S rRNA sequence caused by the transition mutation. This was C in an Indonesian local rabbit, whereas all references showed T. The total length of the 22 tRNA sequences of the Indonesian local rabbits was 1505 bp, with an average length of 68 bp. All tRNAs were distributed among PCGs, rRNA, and D_loop regions, with length ranging from 59 bp (trnS) to 75 bp (trnL). The D-loop sequence of the Indonesian local rabbit was located between trnF (gaa) and trnP (ugg). The Indonesian local rabbit D-loop sequence was 2.023 bp long. It were consisting of the specific sequence along 20 bp in length that was repeated 11 times and the specific sequence along 151 bp in length that was repeated five times.This study showed that the Indonesian local rabbit had a 12S rRNA sequence 957 bp in length and was between trnF and trnV. Furthermore, the alignment results between the Indonesian local rabbit and all references of the 12S RNA sequence showed a point mutation at site 587Oryctolagus cuniculus) and other 9 species of Leporidae family by the Maximum Likelihood method. Where bootstrap was set at 1000 for phylogeny test  and close to Lepus sp. and Brachylagus sp. While Cavia sp. and Ochotona sp. were in different main clade.A phylogenetic tree was constructed based on the comparison of complete mitochondrial genome sequences of the Indonesian local rabbit , and the percentage of T was 2–3% higher than that of other rabbits and outgroups. However, the percentage of C was two-fold less than that of other rabbits and outgroups (26% vs. 13%), and the percentage of T was 2–3% lower than that in other rabbits and outgroups.Result showed that the mtDNA genome of Indonesian local rabbit 17.469 bp) in this study was longer than that of CR rabbits (17.174 bp), YW rabbits (16.740 bp), and fractionally longer than that of New Zealand White rabbits (17.418 bp) .469 bp i. Result The difference result of the stop and start codons in PCGs of mtDNA genome of YW rabbits was reported by Yao et al.  that theth (C➔T) and 791st (T➔C). The mutation at site 316th (C➔T) was a silent mutation, and the mutation at site 791st (T➔C) was a missense mutation located in the second codon. Proline (CCC) was detected in the CR rabbits and leucine (CTC) in The Indonesian rabbits. The ND3 gene sequence of the Indonesian local rabbit had the same length as the NZW2 rabbit ND3 gene sequence, which was 357 bp [When the ND1 gene sequence of the Indonesian local rabbit was aligned with only CR rabbits , and vars 357 bp . While ts 357 bp , 19. Thend (T➔C) as a transition mutation, which was also indicated as a silent mutation. However, this mutation was found when the Indonesian local rabbit was aligned with the CR rabbits [th and 267th as A➔G when the Indonesian rabbits in this study were aligned with CR rabbits [th of the first codon caused a difference in the amino acid sequence between isoleucine (ATT) in the Indonesian local rabbit and valine (GTT) in CR rabbits, while the mutation at site 267th was a silent mutation. In contrast, a mutation in ND4 was found at site 1370th (C➔T) only when the Indonesian local rabbit was aligned with the NZW1 and NZW2 rabbits [The ND4L and ND5 gene sequence had the same length with all references –19 and f rabbits . Further rabbits . These m rabbits , 18. The rabbits , 19. Bas rabbits , all ND  rabbits .th (T➔C) and 1463rd (C➔T) in the second codon and 1252nd (T➔C) in the first codon, all of which were missense mutations. There were point mutations causing differences between isoleucine (ATC), phenylalanine (TTT), and threonine (ACA) in the Indonesian local rabbit, and threonine (ACC), leucine (CTT), and isoleucine (ATA) in the CR rabbit at sites 569th, 1252nd, and 1463rd, respectively. As another comparison between the Indonesian local rabbit with NZW1 rabbits and NZW2 rabbits [th (C➔G) as transversion mutation that interpreted as a missense mutation. This mutation in the first codon led to differences in the amino acid proline (CCC) in the Indonesian local rabbit and alanine (GCC) in the NZW1 and NZW2 rabbits. At the same site, YW and CR rabbits showed no differences [th (G➔A) only when the Indonesian local rabbit was aligned with CR rabbits [Moreover, when COX1 gene sequence of the Indonesian local rabbit was aligned with only CR rabbits , three p rabbits , 18, a pferences , 19. Dif rabbits . These w rabbits , COX encATP6 gene sequence in this study showed a 681 bp in length and was the same as that in NZW2 rabbits and CR rabbits , 18. Othst (A➔G) and 1103rd (T➔C) as missense mutations; however, these mutations were only found when the CYTB gene of the Indonesian local rabbit was aligned with CR rabbits [st (A➔G) and 1103rd (T➔C) in the second codon was causing a difference in amino acid sequence, where the Indonesian local rabbits showed Asparagine (AAC) and Leucine (CTC), whereas CR rabbits showed Serine (AGC) and Proline (CCC), respectively.CYTB codes for the production of cytochrome b protein. This protein is one of 11 components of a group of proteins called complex III. It performs one step in the OXPHOS process, in which oxygen and simple sugars are used to create adenosine triphosphate (ATP) as the cell's main energy source . The CYT rabbits . Mutationd (A➔G), 726th (T➔A), 771st (A➔T), and 791st (T➔C), but these mutations were present only when the Indonesian local rabbit was aligned with CR rabbits [According to Yang et al. , ribosom rabbits . On the st (T➔C), 636th (A➔G), and 982nd (A➔G).Furthermore, sequencing results showed that the 16S rRNA sequence of the Indonesian local rabbit was 1581 bp, flanked by trnV and trnL. Prior researchers have reported results different from those of this study. NZW1 and CR rabbits were 1579 bp in length . The diftRNAs are mitochondrial components essential for the maturation of RNA into polycistronic transcripts. They decode an RNA molecule that aids in translating messenger RNA (mRNA) sequences into proteins . These gResult of D-loop gene sequence in this study was highly different from NZW1 rabbits, particularly in terms of sequence length and character . The IndFurthermore, another study reported that the D-loop sequence lengths were 2.010 bp in NZW2 rabbits, which showed nine repetitions of 20 bp of repetition sequence and three repetitions of 151 bp of repetition sequence ; 1.743 bOryctolagus cuniculus, the Indonesian local rabbit was in different branch and separated with NZW, YW and CR rabbit breed. The different among breed was in line with the morphologically distinctive among these rabbits. Indonesian local rabbits have short, coarse fur that is either black, white, agouty, or any mix of those colors. They have medium-sized of body with a maximum mature weight is only 2.5 kg [The phylogenic tree described that within sub-species y 2.5 kg . NZW andy 2.5 kg , 53. They 2.5 kg .Oryctolagus cuniculus known as European rabbit was separated but closely from Pentalagus, Caprolagus and Bunolagus. Based on geographical cluster, Pentalagus, Caprolagus, Bunolagus, and Oryctolagus were originated from South Asia, India, South Africa and Europe, respectively. In the level of subspecies, the study in Egypt reported that Baladi Black, California, Chinchilla, Flander, New Zealand white and Rex were grouped as Oryctolagus cuniculus [This difference of branch was an evidence and a consequence of the unique specific sequences possessed by only Indonesian local rabbits in this study. The study reported phylogeny of rabbits from complete mtDNA genome was limited. The specific genes have been used for phylogeny studies were Cytochrome b, 12SrNA, 16S rRNA MGF, PRKCI, SPTBN1, THY, and TG –57. Theyuniculus . Based oOryctolagus cuniculus. Other specific differences were also found in the percentage of nucleotides and variation in most of the PCGs when they were aligned with Oryctolagus cuniculus references from GenBank. According to phylogeny analysis Indonesian local Rabbits strongly suspected brought from Europe during the colonial period in Indonesia.mtDNA genome of Indonesian local rabbit was the longest and had the most extended D-loop sequence among the other references of Additional file 1. Genetic characteristics of complete mtDNA genome sequence of Indonesian Local rabbit (Oryctolagus cuniculus) (2023).


RUNX1 mutation is characterised by certain clinicopathological features with poor prognosis and adverse risk by the European LeukemiaNet recommendation. Though initially considered as provisional category, the recent World Health Organisation (WHO) classification of 2022 removed RUNX1-mutated AML from the unique entity. However, the significance of RUNX1 mutation in paediatric AML remains unclear. We retrospectively analysed a German cohort of 488 paediatric patients with de novo AML, enroled in the AMLR12 or AMLR17 registry of the AML-BFM Study Group . A total of 23 paediatric AML patients (4.7%) harboured RUNX1 mutations, 18 of which (78%) had RUNX1 mutation at initial diagnosis. RUNX1 mutations were associated with older age, male gender, number of coexisting alterations and presence of FLT3-ITD but mutually exclusive of KRAS, KIT and NPM1 mutation. RUNX1 mutations did not prognostically impact overall or event-free survival. Response rates did not differ between patients with and without RUNX1 mutations. This comprehensive study, comprising the largest analysis of RUNX1 mutation in a paediatric cohort to date, reveals distinct but not unique clinicopathologic features, with no prognostic significance of RUNX1-mutated paediatric AML. These results broaden the perspective on the relevance of RUNX1 alterations in leukaemogenesis in AML.In acute myeloid leukaemia (AML)  Acute myeloid leukaemia (AML) is a genetically heterogeneous disease. Analyses of genetic aberrations helped to unravel a complex genetic landscape and improved our knowledge of AML pathogenesis, leading to refined, risk-adapted treatment allocation –4. In paRUNX1) have been associated with distinct clinical and genetic features as well as inferior prognosis in adult AML [RUNX1” as new provisional entity of the World Health Organisation (WHO) classification as part of the revision in 2016 [th edition of the WHO classification [RUNX1-mutated AML into the adverse risk category [Intragenic mutations of the runt-related transcription factor-1 , leading to the leukaemia-initiating RUNX1::RUNX1T1 fusion, predicting favourable prognosis [RUNX1 was found to critically promote leukaemogenesis in t AML [The RUNX1 transcription factor, encoded on chromosome 21q22.3, is crucial for early lineage differentiation and indispensable for definite hematopoiesis . In AML,rognosis . Native ;21) AML .RUNX1 gene were preliminary reported in MDS, secondary and therapy-related AML, radiation exposed myelodysplastic syndrome (MDS) and AML [RUNX1 mutation were found to cause familial platelet disorder (FPD) with a propensity to MDS and AML [RUNX1 mutation in paediatric AML [Intragenic mutations of the  and AML –28. Inhe and AML –31. To dtric AML –35.RUNX1 mutation in a substantial paediatric AML cohort. By targeted sequencing, we assess concomitant genetic changes and their impact in development of paediatric AML.This retrospective study elucidates the pathological and clinical implication of A paediatric cohort of 488 patients (0–18 years), diagnosed with de-novo AML between 2015 and 2021 was included. The cohort represents a German paediatric AML population, excluding patients with acute promyelocytic leukaemia (FAB M3), Down syndrome (ML-DS), secondary and treatment-related AML. All included patients were enroled and treated either according to the AMLR12 registry (EudraCT number: 2013-000018-39) or AMLR17 registry (DRKS number: DRKS00013030) of the AML-BFM Study Group. The ethical committees and institutional review boards of the university hospital of Hannover and Essen approved both registries according to the declaration of Helsinki. Informed consent was obtained from patients and their legal guardians prior to treatment participation. Initial and follow-up diagnostics including morphological, immunophenotypic and molecular genetic testing were performed centrally by the German AML-BFM reference laboratory Essen according to standard procedures. Analysis for classical cytogenetics and fluorescence in situ hybridisation (FISH) were carried out by the Institute of Human Genetics in Hannover Medical School. The treatment recommendations of analysed registries included similar cytarabine- and daunorubicin-based induction chemotherapy . DependiTM software . RUNX1 mutations were confirmed by PCR and subsequent Sanger sequencing.Primary bone marrow or peripheral blood samples from paediatric patients were subjected to molecular genetic screening at the time of diagnosis by next generation sequencing (NGS) using the TruSight® Myeloid Panel . Using the standard NGS technology, the mutational screening included 54 different leukaemia-associated genes  according to manufacturer’s recommendations. Classical karyotyping was performed following the International System for Human Cytogenetic .p-value of less than 0.05 was considered to indicate statistical significance. Survival analysis included Overall survival (OS), defined as the time from diagnosis to death or last follow-up, Event-free survival (EFS), defined as the time from diagnosis to relapse, secondary malignancy, death, or the time of last follow-up. Kaplan–Meier curves were calculated for OS and EFS. The log-rank test was obtained to compare survival differences. To identify prognostic variables, Cox-models were used for univariate and multivariate regression analyses. Results were reported as hazard risk ratios with 95% confidence intervals (CI) indicated. Following complexity and dimensionality reduction to a reasonable, recommended number of 50 principal components (PCs), the unsupervised clustered data were visualised using t-distributed stochastic neighbourhood embedding (t-SNE) according to recent recommendations [http://www.Rproject.org). Illustrations were generated using Graphpad Prism™ 8.3, R software version 4.0.2, Python 3.9.13 and DOG 2.0 [Patient characteristics between groups were compared using Pearson chi-square or Fisher’s exact test for categorical variables and Mann–Whitney U test for continuous variables. A ndations  using Se DOG 2.0 .RUNX1 mutations (OMIM No. 151385) were detected of which 24 mutations were distinct from each other . Among eight patient-matched paired diagnosis and relapse samples, RUNX1 mutations were detectable only at relapse in five cases , 27 her Fig. . Within RUNX1 coding sequence alterations, the majority were characterised as frameshift (48.1%), followed by nine missense (33.3%) and two different deletion-insertions (delins) in five cases (18.5%). Four patients were found to have two different RUNX1 mutations, three of which shared the same combinatorial pattern , including the sample with RUNX1 mutation only at diagnosis. Among the five relapsed samples harbouring RUNX1 mutation only at relapse, three frameshifts, two missenses, and the repeatedly occurring mutational combination were found. Considering the distribution on the RUNX1 gene  > 30% were selected for germline-testing. Since one of which never reached remission, samples at remission were available for nine patients. The suspected RUNX1 mutation was not detectable in any of the remission samples, confirming the somatic origin.Considering all 27 detected RUNX1 wildtype (wt) (n = 470), patients with RUNX1-mutated de novo AML (n = 18) were significantly older at diagnosis , . In terms of the AML morphology, RUNX1-mutated were more likely to be myelomonocytic compared to non-mutated samples , followed by AML with minimal differentiation and without maturation . In contrast, the number of samples evaluated as acute monocytic leukaemia  and AML with maturation  were lower in the mutated cohort. None of the six patients with acute erythroid leukaemia harboured RUNX1 mutation. The RUNX1-mutated patient samples showed no significant difference in terms of median haemoglobin level, white blood cell, platelet, bone marrow and peripheral blast count at diagnosis. Involvement of the central nervous system (CNS) at diagnosis was almost equal in both groups.Compared to is (11.7 –17 vs. 8RUNX1-mutated and 460 (98%) RUNX1 wt-patients . Frequent cytogenetic aberrations accompanying the RUNX1 mutation were t and trisomy +8, showing almost equal distribution . RUNX1 mutation tends to associate with −7/7q, . RUNX1 mutation did not co-occur together with KMT2A rearrangement (KMT2Ar), . The recurrent aberration inv(16)/t was present in one patient sample . In addition, RUNX1 mutations did not occur together with other recurrent cytogenetic changes, namely the t, −5/5q, trisomy +11 or +13.Cytogenetic data were available for all 18 ts Table . PrevaleRUNX1-mutated and 470 wt-cases were evaluated for 53 additional AML-related genes assayed by targeted NGS  compared with the wt-cohort , (p = 0.02). Whereas the largest proportion of wt-patients (32%) had one detectable mutation, most RUNX1-mutated cases (50 %) harboured two additional, accompanying mutations.Addressing the mutational spectrum of co-occurring mutations, all 18 NGS Fig. . The aveRUNX1 mutation was correlated with the presence of FLT3 with internal tandem duplication (FLT3-ITD), being the most common co-occurring genetic aberration in the RUNX1-mutated cohort . The second most frequent RUNX1 accompanying mutation was in Wilms-tumor1 (WT1) gene, which was found in 4 of the 18 RUNX1-mutated cases . Whereas NRAS mutations occurred as second most common mutations in wt-patients, it was rarely found in RUNX1-mutated samples . CEBPA aberrations were detected in two RUNX1-mutated samples and were slightly more commonly mutated in the RUNX1-mutated cohort . Upon further differentiation of all 27 CEBPA-mutant samples, CEBPA aberration was biallelic in 15 patients, including two RUNX1-mutated . RUNX1 mutations were mutually exclusive of recurrent alterations in KRAS, KIT and NPM1 . Other mutations studied were more evenly distributed in both cohorts, with no tendency for a specific correlation.RUNX1-mutated and 50% among wt-cases. Mutations affiliated to epigenetic regulator occurred more frequently together with RUNX1 mutation (22 vs 10%). Alterations of transcription factors, excluding RUNX1, were the second most common aberrations among wt-cases, showing comparable frequency in RUNX1-mutated and wt-cohort (13 vs. 15%). Aberrations of tumour suppressor genes were evenly distribution between RUNX1-mutated and wt-cohorts (16 vs. 12%). Together, there was no clear association between RUNX1 mutations and any of the other genetic groups. Accordingly, RUNX1-mutated samples projected scattered without showing definable, separate clustering in the t-SNE plot, which contrasts with the well-known distinct entity of CBF in AML . None of RUNX1-mutated, but 20 of wt-cases suffered early death (4%) . Likewise, number of patients transplanted as salvage therapy were almost equal in both groups  and EFS . Frequency of the associated outcome parameter death and relapse were comparable between RUNX1-mutated and wt-cohorts  or EFS  nor of death (HR 4.2 p = 0.17). Since RUNX1 mutation was significantly associated with FLT3-ITD, increased patient age and number of mutations, subgroup analyses were performed to separately assess the relative prognostic relevance of RUNX1 mutation within these subgroups  or EFS . In children younger than 12-years at diagnosis, RUNX1-mutated and wt patients showed comparable outcome . In older paediatric patients (>12-years) RUNX1 mutation tends to associate with increased OS , but not EFS . Among patients harbouring more than two additional genetic alterations, RUNX1 mutation neither impact OS , nor EFS . When separately assessing impact of RUNX1 mutation in the context of SCT, patients with and without RUNX1 mutation, receiving SCT in first CR achieved comparable survival rates . Separate survival analyses, conducted for standard-, intermediate-, and high-risk groups revealed no strong difference of survival by RUNX1 mutation for risk-associated groups . In comparison, in adult AML, a frequency of ~5–13% has been reported, with highest prevalence when including elderly patients (>60 years) [RUNX1 mutation was lower in younger patients and an association with patients age has been shown before [RUNX1 mutation was found more frequently in older children. Consistent with previous findings our results confirm a positive correlation to male gender in paediatrics. Unlike previous studies [RUNX1 mutations have been frequently described, where in case of heterozygous RUNX1 mutation, a deletion on the other allele is suggested to result in a functional inactivation of RUNX1 [RUNX1 mutation in a FAB M4 sample, without evidence of further biallelic mutation.This retrospective study evaluates 0 years) , 39. Accn before –14, 33.  studies , 33, we of RUNX1 , 40. HowRUNX1 mutation according to different functional domains and clustered mutations at the N´-terminus was previously reported in adult AML, whilst Greif et al. detect a greater proportion of missense mutation in cytogenetically normal AML [RUNX1 mutation has been discussed controversially [RUNX1 mutation in remission, suggesting a germline mutation (data not shown). To our knowledge, except for the increased dosing effect of RUNX1 in ML-DS, no increased prevalence and no specific mechanism of interaction between altered RUNX1 and GATA1 has been described [The mutational spectrum revealed a higher proportion of frameshift mutations and a clustering of missense mutations at the N’-terminus, especially in RHD. A similar distribution of rmal AML –16. Unexersially , 42. In ersially , 31. Intescribed –45.RUNX1 mutation and the recurrent CBF-defining abnormalities t and inv(16)/t. Consistent with reports in adult AML, RUNX1 mutation weakly associated with the unbalanced abnormality −7/7q [RUNX1 mutation did not correlate with trisomy +8 [RUNX1-mutated paediatric cohort [RUNX1-mutated patients had normal karyotype, whilst +8 and complex KT were present in one patient [RUNX1-mutated paediatric AML did not show a distinct cytogenetic pattern, particularly with respect to the overlap with prognostically favourable subgroup CBF-AML, arguing against RUNX1 mutation as a distinct AML type in paediatrics.Regarding cytogenetics, we could not affirm an inverse correlation of ty −7/7q , 16, whiisomy +8 , 46, tric cohort , 15, 47. patient . UltimatRUNX1-mutated AML completely lacks KMT2Ar, indicating that RUNX1 mutation most probably do not contribute to leukaemogenesis in KMT2Ar AML in paediatrics. In fact, in AML mouse models harbouring KMT2Ar, RUNX1 activity mediated leukaemic cell growth and survival [RUNX1 was determined as transcriptional target in KMT2A::AFF1, previously known as MLL::AF4, AML by Wilkinson et al. [RUNX1 activity cooperates with KMT2Ar to promote AML development. Considering the determined exclusivity of RUNX1 mutation and KMT2Ar, this could also be true for paediatric AML.survival , 49. SimRUNX1 mutations alone are highly unlikely to be sufficient to cause complete leukaemic transformation [RUNX1-mutated AML. Increased number of co-occurring mutations indicates a more complex genetic evolution of RUNX1-mutated AML, requiring a broad range of additional mutations.Given that ormation , investiFLT3-ITD was the most common co-occurring mutation and significantly associated with RUNX1 mutation in paediatric AML, which may suggest cooperativity between these two mutations. An early report indicated a link between RUNX1 mutation and FLT3-ITD contributing to leukaemogenesis in AML M0, in which RUNX1 mutations predominated [FLT3-ITD frequently occurred in RUNX1-mutated adult AML, albeit evenly distributed and without correlation with RUNX1 mutation [RUNX1 mutation and FLT3-ITD, which may be specific to paediatric AML [RUNX1 mutations were almost exclusive of alterations involved in other activated-signalling pathways, namely NRAS, KRAS and KIT, which in contrast, were relatively common in the wt-cohort. These results may point at a reassortment in the functional group of activated-signalling, shifted towards FLT3-ITD, supporting the suggestion, that RUNX1 mutation preferably contributes to leukaemogenesis by cooperating with the activating FLT3-ITD, instead of other activating pathways in paediatric AML. Despite the fact that FLT3-ITD has long been known to associate with poor prognosis [FLT3-ITD with RUNX1 mutation did not affect outcomes in paediatric AML, which is consistent with results in adult AML [ominated . In compmutation , 39, suptric AML . RUNX1 mrognosis , 54, in dult AML .BCORL1, EZH2, and KDM6A. A propensity for association was noted for spliceosome U2AF1, whereas other spliceosome-related genetic aberrations were absent in RUNX1-mutated paediatric AML. In contrast, RUNX1-mutated adult AML has been associated with mutations in the spliceosome and cohesion complex, in addition to epigenetic modifiers [Despite the small number of patients, which makes the accurate assessment of additional genetic associations more difficult, concurrent genetic aberrations occurred more frequently in epigenetic modifiers, with a trend towards odifiers , consistodifiers , 56. ThiNPM1 were completely absent in the RUNX1-mutated paediatric cohort. NPM1 mutation is considered as founding genetic event in AML with certain biological and clinical features, warranting its own entity [NPM1 and RUNX1 mutation in AML might suggest that RUNX1 mutation shares a similar role with NPM1 mutations in leukaemia development. In two cases we observed that RUNX1 mutation overlaps with double mutated CEBPA in paediatrics, contradicting the notion that RUNX1-mutated AML represents a distinct entity. Thus, according to the results of this cohort, previously reported characteristic features, favouring the concept of considering RUNX1-mutated AML as a distinct entity [RUNX1 mutation lacks these mutational features and overlaps with AML defining mutational patterns.Consistent with previous studies –15, 57, n entity , 58. Thet entity , 17, canRUNX1 mutation was stated as a late event in leukaemia development [RUNX1 mutations as early events in leukemognenesis [RUNX1 mutations in six out of eight paired diagnosis-relapse samples in this paediatric cohort, indicates instability, suggesting that RUNX1 mutation rather is a late genetic event contributing to advanced clonal evolution. Moreover, the detected high number of additional aberrations accompanying RUNX1 mutation and the observed overlap with the AML-causing events CBF-fusions or NPM1 mutation in the assessed paediatric patients, further support the concept that RUNX1 mutations are more likely to contribute to the late-stage leukaemia development.In the recent ELN-recommendation, elopment , which cgnenesis , 50. TheRUNX1 mutation did not show a prognostic significance for outcomes and survival. These results contrast with previous data on RUNX1 mutation in AML, indicating that RUNX1 is a negative prognosticator [et al. assessed the prognostic impact of RUNX1-mutated de novo AML according to the WHO definition and detected no differences in outcome [et al. proved negative prognostic significance in elderly (> 60 years) cytogenetically normal AML, whereas this could not be confirmed for younger patients [RUNX1 mutation. This observation could be strengthened by our results, where RUNX1 mutation showed no predictive relevance in paediatric AML. However, we did not observe a strong difference when separately assessing age-depending prognostic impact of RUNX1 mutation in paediatric patients. Since the survival was not affected by RUNX1 mutation in different risk groups, there seems to be no relevance for including RUNX1 mutations in the risk stratification of paediatric AML. In terms of indication for SCT, survival was comparable in patients with and without SCT in first CR, suggesting that the presence of RUNX1 mutation does not require modification in eligibility criteria in paediatric AML.In this study, sticator –14, 33.  outcome , which ipatients , suggestRUNX1 mutation in a well characterised paediatric AML cohort and provides new insights into its clinicopathological relevance. Although this study evaluates RUNX1 mutations in the largest paediatric cohort studied to date, analyses are still limited due to small sample sizes for some analysis-subgroups and the retrospective dataset, necessitating further validation to confirm these observations.This analysis uncovers the impact of RUNX1 mutations did not impact outcomes in this paediatric AML cohort, suggesting a clinical impact that differs from that reported in adult AML. Importantly, RUNX1 mutations lacked clinical characteristics and genetic features, which would justify a separate WHO entity. Therefore, the previously stated provisional WHO entity ‘RUNX1 mutated AML’, is not appropriate in paediatric AML. The results of this study agree with the recently published fifth edition of the WHO classification which removed RUNX1 mutations as distinct entities in AML [In conclusion, s in AML .Supplementary Material


Introduction: Endothelial cells (ECs), being located at the interface between flowing blood and vessel wall, maintain cardiovascular homeostasis by virtue of their ability to integrate chemical and physical cues through a spatio-temporally coordinated increase in their intracellular Ca2+ concentration ([Ca2+]i). Endothelial heterogeneity suggests the existence of spatially distributed functional clusters of ECs that display different patterns of intracellular Ca2+ response to extracellular inputs. Characterizing the overall Ca2+ activity of the endothelial monolayer in situ requires the meticulous analysis of hundreds of ECs. This complex analysis consists in detecting and quantifying the true Ca2+ events associated to extracellular stimulation and classifying their intracellular Ca2+ profiles (ICPs). The injury assay technique allows exploring the Ca2+-dependent molecular mechanisms involved in angiogenesis and endothelial regeneration. However, there are true Ca2+ events of nearly undetectable magnitude that are almost comparable with inherent instrumental noise. Moreover, undesirable artifacts added to the signal by mechanical injury stimulation complicate the analysis of intracellular Ca2+ activity. In general, the study of ICPs lacks uniform criteria and reliable approaches for assessing these highly heterogeneous spatial and temporal events.Methods: Herein, we present an approach to classify ICPs that consists in three stages: 1) identification of Ca2+ candidate events through thresholding of a feature termed left-prominence; 2) identification of non-true events, known as artifacts; and 3) ICP classification based upon event temporal location.Results: The performance assessment of true-events identification showed competitive sensitivity = , specificity =  and accuracy =  improvements of 2x and 14x, respectively, compared with other methods. The ICP classifier enhanced by artifact detection showed 0.9252 average accuracy with the ground-truth sets provided for validation.Discussion: Results indicate that our approach ensures sturdiness to experimental protocol maneuvers, besides it is effective, simple, and configurable for different studies that use unidimensional time dependent signals as data. Furthermore, our approach would also be effective to analyze the ICPs generated by other cell types, other dyes, chemical stimulation or even signals recorded at higher frequency. Currently, most measurements are intensity averages of defined regions of interests (ROIs) drawn around cells loaded with a Ca2+-sensitive fluorophore, at a sampling rate that depends on the frequency or rate of increase of the Ca2+ signal.Many efforts have been devoted to elucidate the bewildering complexity of the endothelial Cachanisms . Most of2+ signaling at the tissue level. Collaborative sensory networks have recently been reported in the vascular endothelium exposed to multiple chemical cues  from those that stimulate migration   .® 184 Silicone Elastomer, Dow Corning, MI, United States) by using four 0.4-mm diameter pins. The procedure is shown in The intact endothelium was harvested from the thoracic and abdominal aorta of 1–3 month-old Wistar rats anesthetized with intraperitoneal ketamine–xylazine solution (0.2 mL per 100 g of weight). The aorta was first dissected and then perfused with physiological salt solution (PSS). Using a stereomicroscope , the connective and fatty tissues surrounding the aorta were removed. Subsequently, the aorta was cut into ∼5-mm-wide rings, stored in PSS at controlled room temperature (22°C–23 °C), and used within 5 h. Using a pair of microdissection scissors, the aortic rings were carefully cut open to obtain aortic strips with the intact endothelium. The aortic strips were loaded with 16 µmol Fura-2/AM for 60 min at room temperature, and then washed and fixed  to the bottom of a Petri dish covered by inert silicone (Sylgard 2 (1.2), glucose (6), CaCl2 (2.5), and HEPES (5). The solution was titrated to pH 7.4 with NaOH. All reagents were purchased from Sigma-Aldrich .The composition of the PSS expressed in mmol/L was NaCl (140), KCl (4.7), MgClin situ ECs were loaded with 16-µmol Fura 2/AM  and visualized using an upright epifluorescence Axiolab microscope , equipped with a Zeiss ×40 Achroplan objective . To monitor the changes in [Ca2+]i, ECs were excited alternately at 340 and 380 nm and the emitted light was detected at 510 nm. A neutral density filter  was coupled to the 380-nm filter to approach the intensity of the 340-nm light. A round diaphragm was used to increase the contrast. A filter wheel  commanded by a computer was positioned alternately along the optical path of the two filters that allowed the passage of light at 340 and 380 nm, respectively. Custom software, working in the LINUX environment, was used to drive the camera  and the filter wheel. The acquisition frequency was 0.33 Hz, and the fluorescence images obtained at 340 nm and 380 nm were stored in the hard disk, and data analysis was conducted later using MATLAB® R2020a.As described previously , in situ2+]i causes an increase in the 340/380 ratio.ROIs were placed automatically as rectangular bounding boxes, each enclosing a single cell. Time-dependent signals, also known as ICPs, were acquired as the mean of the pixel-to-pixel ratio of the emissions at 340 and 380 nm (340/380) within each ROI, frame to frame throughout all the image sequences. An increase in i events in the CPs was manually generated by two health science experts for all ICPs for each endothelium sample. First, each expert independently generated the CE-GT events’ sets; then, a final CE-GT was determined by consensus of both experts. The total amount of true events pointed out for the six tissue samples was equal to 1,683. It is worth noting that not all the ICPs present true events (CE-GT marks) due to the heterogeneous pattern between individual cells in the injured in situ endothelium .A second GT set (C-GT) was created to classify the ICPs according to the time of occurrence of the Caulus see . Basal r2+]i produced by the depletion of the main intracellular Ca2+ reservoir, the endoplasmic reticulum (ER), a 90-s window just after the mechanical stimulus was considered for classes 2 and 3. The CE-GT points within  were set at the beginning of the event rise (around 20% of its prominence) rather than at its peak  value in Eq. kth local maximum and minimum, respectively.To detect a true Calocal maximum  in an intracellular Ca2+ profile (icp) using left prominence thresholding.Identification of true CaDATA:2+ profilesicp: intracellular Calp_threshold: user defined left prominence thresholdRESULT:2+ eventstce: true CaMAIN PROGRAM:iFOR EACH icpFindLocalMaximumsLocation(icpi)local_max_index = FindLocalMinimumsLocation(icpi)local_min_index = kFOR EACH local_maxk=FindClosestLeftMinIndexlocal_min_indexi,k = icp- icptce_left_prominenceENDi = tce_left_prominencei >= lp_thresholdtceEND2+ events based on left prominence thresholdingListing 1. Pseudocode to detect true Ca2+ true events. The effects of the mechanical injury also impact the procedure of cell tracking that produces the difference between segmented cells and online cells shown in As mentioned previously, ICPs are prone to present complex structures and undesirable artifacts due to mechanical stimuli, extracellular perfusion solution change, or natural tissue contraction that may move fluorescence images out of focus. Therefore, manual focus adjustments are required along the experiment, thereby resulting in additional peaks in the ICPs that hinder the detection of relevant Ca2+ tracing, but they do not have to be classified as Ca2+ true events. An approach was designed to detect and remove these artifacts based on the frequency of Ca2+ events above the LP threshold at a given time point. An event frequency threshold 2+ event may be erroneously discarded, while false negatives may appear. For this reason, the artifact detection was disabled during a 30-frame window (90 s) starting by the injury time that was calculated, shown in Eq. i and j operate across ICPs and frames, respectively. All Ca2+ events inside the detected artifact regions were ignored for further analysis or classification processes.When an artifact appears, it impacts many cells in the visual field. Mechanical artifacts can, therefore, be added to Ca2+ true events. As per C-GT, the Ca2+ true events within the interval  were left shifted by our classifier as well to the Once the event candidates were thresholded with the left prominence (LPT) criterion and artifacts were discarded (AD) from the event candidates, the remaining event candidates were considered Ca2+ events resulting from our approach, and thus, evaluate its performance .Since the CE-GT was obtained manually, using a pc-mouse as the pointer, there is an inherent inaccuracy between the selected CE-GT points and the maxima of the actual true events. Therefore, a symmetric neighborhood of size 2 epsilon (units in seconds) was used as a tolerance to quantify the coincidences between the CE-GT and the true Caformance .2+ true events’ identification are shown in ε = 10 (approximately three samples’ length) for our approach in the left prominence section. Results with ε = 0 for each ICP baseline noise standard deviation (σbn) thresholding are reported in the second section, i.e., each ICP determined its own threshold. Meanwhile, an approach based on the minimum baseline noise standard deviation of the corresponding dataset in the last section (σbn lowest noise), i.e., the ICP with the lowest baseline noise, determined the threshold for the other ICPs. Comparison between approaches is addressed in the Discussion section. The maximum, minimum, and mean values obtained for the six datasets are reported for different threshold values.Performance measurements of Ca2+ true events with a sensitivity range of , whereas its specificity range  shows good performance on discarding the non-relevant activity. It should be noted that accuracy is in the range  across the six datasets. All the values were rounded to two decimals.The aforementioned results show that our approach properly identifies the Casubsection 2.8 (LPT + AD + ICP_C) was carried out based on the C-GT  sturdiness, since it can work regardless of the length of the ICP basal stage as left prominence is defined based on couples of local maxima and minima: this approach is applicable even in datasets where fluorescence artifacts can appear due to mechanical maneuvers generating tissue displacement, cell movement, and blurred optical field . Our proposal correctly classified 789/825 ICPs and showed better performance than the 4-class scheme reported by On top of the LP thresholding approach, a method was proposed and implemented to detect and discard undesirable artifacts of ICPs. This method relies on the frequency per frame of event candidates resulted from the LP thresholding process. Alongside, a 4-class classifier was implemented based on true events’ identification and their time location. Performance assessment showed 92.52% of average accuracy (4 classes) with outstanding capability to split datasets into responsive and non-responsive cells, while classes with Ca2+ activity. Furthermore, this approach would also be effective in analyzing the ICPs generated by other cell types, other dyes, or even signals recorded by chemical stimulation. It can handle any single-defined acquisition frequency signals for a given experiment, which may allow microdomain events’ detection on given proper experimental data; the system requires specifying the defined acquisition period to display signals in a proper time scale. Different experimental protocols may require custom pre- or post-processing algorithms to remove artifacts.Of note, our method would also work with healthy  and pathological  ECs, thereby presenting the potential to be extremely helpful to analyze whether and how endothelial dysfunction is associated with deregulated intracellular Ca2+ true events, removal of undesired artifacts, and event time location-based classification. This approach proved to be more precise, accurate, and reliable than previous proposals in performing automatic ICP detection, is suitable for cultured cells, and fully addressed all the challenges imposed by mechanical stimulation of the naïve endothelium. In addition to the Ca2+ signals evoked by mechanical stimulation, this approach would be suitable to detect ICPs induced by other modes of mechanical stimulation, such as changes in pulsatile pressure of shear stress. In addition, it could be efficiently employed for the automatic detection of ICPs evoked by neurohumoral stimulation. Finally, by enabling a more accurate evaluation of the ICPs occurring at the injury site in in situ endothelial cells, this approach could be instrumental in evaluating the role of intracellular Ca2+ signaling in endothelium regeneration processes and vasomotion.In conclusion, we have presented a proposal to assist with the bulk analysis of ICPs through the detection of Ca