Traumatic brain injuries (TBIs) are associated with high mortality and morbidity. Depressed skull fractures (DSFs) are a subset of fractures characterized by either direct or indirect brain damage, compressing brain tissue. Recent advances in implant use during primary reconstruction surgeries have shown to be effective. In this systematic review, we assess differences in titanium mesh, polyetheretherketone (PEEK) implants, autologous pericranial grafts, and methyl methacrylate (PMMA) implants for DSF treatment.A literature search was conducted in PubMed, Scopus, and Web of Science from their inception to September 2022 to retrieve articles regarding the use of various implant materials for depressed skull fractures. Inclusion criteria included studies specifically describing implant type/material within treatment of depressed skull fractures, particularly during duraplasty. Exclusion criteria were studies reporting only non-primary data, those insufficiently disaggregated to extract implant type, those describing treatment of pathologies other than depressed skull fractures, and non-English or cadaveric studies. The Newcastle-Ottawa Scale was utilized to assess for presence of bias in included studies.Following final study selection, 18 articles were included for quantitative and qualitative analysis. Of the 177 patients , mean age was 30.8 years with 82% implanted with autologous graft material, and 18% with non-autologous material. Data were pooled and analyzed with respect to the total patient set, and additionally stratified into those treated through autologous and non-autologous implant material.There were no differences between the two cohorts regarding mean time to encounter, pre-operative Glasgow coma scale (GCS), fracture location, length to cranioplasty, and complication rate. There were statistically significant differences in post-operative GCS (p < 0.0001), LOS (p = 0.0274), and minimum follow-up time (p = 0.000796).Differences in measurable post-operative outcomes between implant groups were largely minimal or none. Future research should aim to probe these basic results deeper with a larger, non-biased sample. Skull fractures vary in etiology as several factors influence the fracture such as bone mineralization and trauma type,4. Depressed skull fractures (DSFs) are a subset of fractures characterized by a portion of the inner table of the skull displacing and lying above the outer table,6. Incidence of depressed skull fractures (DSFs) within TBI patients ranges from 2% to 11%. In DSFs, there is often underlying brain damage of two different varieties: direct damage to tissue and indirect damage via hematomas compressing the brain tissue. Recent advancements of computed tomography (CT) and magnetic resonance imaging (MRI) provide better understanding of diagnosing DSFs and survival interventions.Traumatic brain injuries (TBIs) are a worldwide issue that is associated with high levels of mortality and morbidity,7. Previously, delayed cranioplasty was preferred due to reduction of infections such as meningitis and osteomyelitis. However, several limitations are presented in these patients’ lives. Furthermore, recent studies have shown no difference in infection rate between delayed cranioplasty and immediate titanium mesh reconstruction,9. Although it is preferable to use patients’ own bone material, due to several reasons, rather than artificial mesh during surgery, cases of DSF may be near impossible for bone material reconstruction,10. Furthermore, recent work has demonstrated a higher failure rate with autologous bone due to infection and bone flap necrosis,11. Urgent cranioplasty using artificial material such as titanium mesh, methyl methacrylate (PMMA), and several unique varieties has become more common.Treatment for DSFs includes either surgical interventions, such as cranioplasty or conservative treatment. Surgery is pursued based on indications, such as neurologic, infective, and cosmetic issues and open skull fractures are managed in two stages: through primary reconstruction or delayed cranioplasty. Variations and effectiveness of the different implants is a field of ongoing research. Differences in tissue tolerance, cost, and resistance to infections and other characteristics are considered when choosing the specific alloplastic material. Titanium mesh bone grafts have been seen to be effective in preventing an inflammatory reaction. PMMA, similarly, has been popular recently due to the ease of confirmation and application. Studies have shown no significant difference between these two alloplastic materials, and both have demonstrated similar results, both functionally and cosmetically,13. However, titanium mesh patients have been seen to develop less inflectional complications going forward,13.Primary reconstruction for DSF was developed to avoid delayed cranioplasty, prevent further CSF complications, and for cosmetic reasonsWith the goal of improving patient outcomes in addressing DSF, an effective route may involve optimization of the implantation approach required in surgical management. Specifically, the decision in implant material utilized can hold considerable weight. In the current review, outcome measures for the surgical management of DSF among various types of implant material are reported in a coherent fashion. We organized a systematic review by organizing the available data regarding outcomes of surgically treated DSF between different implant materials to address the question of how implant material may affect the post-operative outcomes of DSF patients.2.2.1.Retrospective cohort studies, case series, and case reports were included in this systematic review. Our analysis included the study design, country, number of patients, age, sex, preoperative Glasgow coma scale (GCS), fracture location, primary implant material, time to encounter, time to cranioplasty, presence of complications, postoperative GCS, length of stay, and follow-up duration. Inclusion criteria pertained to studies reporting use of specific implant material within treatment for depressed skull fractures. Exclusion criteria included studies not sufficiently disaggregated for extracting data pertaining to depressed skull fractures, those failing to specifically report surgical approach regarding implant material. Non-primary data including presentations, letters to the editor, editorials, and other sources that appeared non-peer-reviewed were strictly excluded. Articles written in languages other than English, or cadaver/non-human studies were excluded from the study. The selection process is shown in 2.2.. This review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The search strategy is (depressed skull fracture) AND (implant OR shunt OR inlay OR onlay OR patch OR mesh OR titanium OR cranioplasty). Study selection was performed by one reviewer (A.N.) and data extraction was performed by two reviewers . Accuracy of data extraction was ensured through the use of a third reviewer, who monitored all data entries for correctness. When disagreements pertaining to study selection arose, an additional reviewer (M.D.) mediated the final decision. Full articles were retrieved when titles and abstracts potentially relevant to the inclusion criteria were found. The data from each study was then extracted and analyzed. With regard to the data points of interest, the corresponding values were extracted and collected for future analysis in an Excel spreadsheet. If a study did not explicitly mention the presence of a clinical characteristic, it was assumed that the characteristic was not present in that patient set.A literature search was performed in Web of Science, Scopus, and PubMed from their inception to September 2022 to identify studies reporting the outcome of implant usage in subsequent duraplasty in treatment of depressed skull fractures. The search strategy was developed by one reviewer (A.N.) by consulting the peer review of electronic search strategies (PRESS) criteria2.3.Titles and abstracts were screened by two reviewers independently . Following individual screening, records identified through the searches were added to a database and duplicates were removed through Rayyan web app for systematic reviews.2.4.. The NOS cohort criteria allowed for a maximum of four stars in selection, two stars in comparability, and three stars in outcome: the total range was 0–9. Case reports and series were analyzed with NOS cohort guidelines without application of comparability questions, making their effective range 0–7. Two reviewers  conducted this assessment.To assess the quality and risk of bias of the studies eligible for inclusion, Newcastle-Ottawa Scale (NOS) criteria were used to rate our included cohort studies and case reports/series2.5.Data were analyzed using JMP Statistical Software (SAS). Quantitative variables were analyzed through two-tailed independent samples t-tests. p < 0.05 was considered to be significant. Data were quantitatively pooled to present statistics in a coherent manner representative of the total patient set. Following this, analysis was conducted similarly, stratifying the dataset by autologous and nonautologous implant material. The implant material specifically dichotomized as autologous versus nonautologous material, and their respective outcomes were considered to be the primary analysis of the current review. Precluding this analysis, differences in age, sex, time to encounter, pre-operative GCS, and fracture location were assessed to determine the presence of confounding variables.3.3.1.-9,16-30. Five studies were conducted in the United States, three in China, and one each in Brazil, Egypt, Germany, India, Indonesia, Japan, Nigeria, South Korea, Switzerland, and Turkey (10).3.2.The eighteen studies were assessed with appropriate guidelines to characterize their quality based on several criteria . NOS sco3.3.et al. Removal of this study in the same analysis revealed a transition to non-statistical significance of age. With this in mind, the study was included for outcome analysis acknowledging the large sample of younger patients in this study skewed autologous patient age toward the left.From the extracted data, potential confounders were analyzed with respect to the two categories of implant type, that is, autologous and nonautologous. This included the age, gender, duration to hospital encounter, preoperative GCS, and fracture location. With respect to all variables, barring age, there were no statistically significant differences observed between autologous versus non-autologous implant material. Age within the autologous patient sample set was skewed toward younger patients, particularly in a study by AbdelFatah 3.4.The sample size across all studies was 177 patients after application of inclusion and exclusion criteria. The mean age was 30.77 years. There were 152 males (85.9%). Regarding duraplasty implant material, 82% utilized autologous pericranial grafts, 16% titanium mesh, 1% polyetheretherketone (PEEK), and 1% PMMA. After dichotomization, 82% utilized autologous implant material and 18% non-autologous implants. In the autologous group, the mean age of subjects was 25.2 years old, and the proportion of male was 64%. In the non-autologous group, the mean age of subjects was 42.0 years old, and the proportion of males was 16.5%.3.5.In total, the mean pre-operative GCS was 13.5, and time to initial encounter was 1.9 days. The proportion of fracture location was 44% frontal, 30% parietal, 15% occipital, and 11% temporal across the total patient sample. With respect to the autologous group, mean preoperative GCS was 12.8. Mean time to encounter was 1.67 days. Location of fracture was 36% frontal, 33% parietal, 17% occipital, and 14% temporal. In the non-autologous group, pre-operative GCS was 14.8. Mean time to encounter was 2.68 days. Location of fracture was 68% frontal, 22% parietal, and 10% occipital. There was no statistically significant difference between the two groups for preoperative GCS (p = 0.1570), time to encounter (p = 0.4785), or fracture location (p = 0.09) .3.6.Decision for cranioplasty was reported in 97% of the surgically treated patients. Mean length to cranioplasty 11.4 days. In the autologous group, mean length to cranioplasty was 10.3 days. The non-autologous group had a mean length to cranioplasty of 16.1 days. There was no difference between the two groups for days to cranioplasty (p = 0.4780) .3.7.The overall complication rate was 4.0%% including two cases of intraoperative epidural hematoma and postoperative wound infection. The mean post-operative GCS was 14.95. The mean length of stay was 18.6 days for the total sample size. Finally, the overall minimum follow-up time was 1.2 years. In the autologous group, the mean postoperative GCS was 15, while the non-autologous group had a mean of 14.74. In the autologous group, complication rate was 4.14%, and in the non-autologous group, the rate was 3.13%. There was no difference in complication rate (p = 0.8584). The autologous group had an average LOS of 36.3 days, and the non-autologous group had a LOS of 16.7 days. In the autologous group, minimum follow-up time was 1.21 years, and in the non-autologous group, the rate was 0.93 years . There w4.-33. With the goal of improving outcomes in patients presenting to the emergency department with DSFs, the authors conducted a systematic review to explore the outcomes and operative considerations associated with DSF reconstruction achieved through use of either autologous or non- autologous implant material , which may support the hypothesis that autologous implants are preferred in cases of greater interventional urgency . Although autologous implants show desirable biomimetic properties, they display a variable reabsorption rate between 3% and 50%, leading to failure of the implant (Y). Nonautologous implants may overcome these disadvantages of autologous material; however they may be associated with their own shortcomings such as higher infection rate or higher costs. Due to these proposed differences, we analyzed post-operative complication rates between patients utilizing autologous or nonautologous graft material . Although hospital length of stay is commonly used as a measure of quality of care, there were no significant differences in post-operative complication rates with longer hospital stay following cranioplasty with an autologous implant when compared with shorter hospital stay in the nonautologous implant group.In addition, post-operative outcomes were analyzed between patients with autologous or nonautologous implant material. The previous literature has shown no significant difference in post-operative outcomes between different implant materialsmaterial . Of 145 We confer there were few limitations to the present systematic review. Due to the stringency of the chosen inclusion criteria, a minority of studies that met the requirements were included in the present analysis. The relationship between perioperative characteristics and outcomes were also difficult to establish across groups due to the variable length of follow-up across studies. Moreover, a larger, non-homogeneous sample is desired to resolve a generalizable relationship between patient outcomes related to receiving autologous or nonautologous implants. The autologous patient population was predominantly young adult males, whereas the non-autologous patient population was predominantly middle-aged females . In addiWith the goal of improving patient outcomes in addressing DSF, we hope to address how implant material may affect post-operative outcomes. Future research should be conducted, adjusting for standard of care across national health systems, patient socio-demographic factors, and patient comorbidities. We also require a clearer focus on primary outcomes evaluated to better compare across groups.5.The current study represents a scoping systematic review of the Web of Science, Scopus, and PubMed databases. Here, we provide novel efforts to elucidate depressed skull fracture outcomes in patients receiving autologous-based interventions compared to non-autologous-based interventions. We identified trends toward autologous implant usage among low preoperative-GCS patients, though DSF patients receiving autologous grafts reported greater likelihood of postoperative complication. Still, however, these data largely corroborate previous research indicating little-to-no statistically significant contributions of selected implant material towards post-operative complication rates among neurosurgical patients. Limitations of the present review include uncontrolled cofounders in patient and hospital factors, distinctly heterogenous patient cohorts, and inconsistent follow-up times. Future investigation of implant considerations for depressed skull fractures should focus its efforts on studying large, non-biased treatment cohorts with adequate control measures in place for differences attributable to interacting factors.


Complex two-dimensional warranty equipment is usually composed of many multi-component systems, which include several key components. During the warranty period, conducting maintenance according to the preventive maintenance plan of each component will increase the warranty costs. Opportunistic maintenance is an effective approach to combine the preventive maintenance of each individual component, which can reduce the warranty cost and improve the system availability. This study explored the optimal opportunistic maintenance scheme of multi-component systems. Firstly, the failure rate model and reliability evaluation model of the multi-component system considering failure dependence were established. Secondly, the preventive maintenance plan of each individual component was determined, with the goal of obtaining the lowest warranty cost per unit time in the component life cycle. Thirdly, the preventive maintenance work of each individual component was combined, and the two-dimensional warranty cost model of the multi-component system was established according to the reliability threshold when performing opportunistic maintenance. In the experimental verification and result analysis, the genetic algorithm was used to find the optimal opportunistic maintenance scheme for the power transmission device. The comparative analysis results show that the opportunistic maintenance scheme reduced the warranty cost by 5.5% and improved the availability by 10%, which fully verified the effectiveness of the opportunistic maintenance strategy. Warranty refers to the maintenance conducted by the manufacturer after equipment has been put into use . With thNew complex equipment is usually composed of many multi-component systems, and warranty activities are usually carried out for individual components constituting multi-component systems. Two-dimensional warranty strategies are widely adopted in new complex equipment, in which one dimension represents calendar time and one dimension represents usage degree (such as driving mileage or usage time). When the warranty period of any dimension reaches the predetermined period, the warranty ends . For exaMaking reasonable two-dimensional warranty decisions for complex equipment is a common concern of manufacturers and users. Two-dimensional warranty decisions mainly refer to determining a reasonable preventive maintenance scheme to reduce costs within a warranty period. Due to the different failure laws of components constituting a multi-component system, the isolated maintenance of each individual component will lead to excess maintenance and increase the frequency and cost of preventive maintenance. On the other hand, mechanically combining the preventive maintenance work of various components will lead to the advance of the overall preventive maintenance work and waste the use value of equipment . Most ofThis study adopts the opportunistic maintenance strategy and two-dimensional warranty method to determine the replacement cycle of each individual component in the component life cycle with the goal of achieving the lowest warranty cost per unit time.Through opportunistic maintenance, the preventive maintenance work of each individual component is adjusted according to the reliability threshold when carrying out opportunistic maintenance. Then, the opportunistic maintenance plan of the multi-component system is formed.In a case study, a power transmission device is used as an example for analysis. The reliability threshold for opportunistic maintenance of each component is solved using a genetic algorithm. Finally, the effectiveness of the proposed method is verified through comparative analysis.On the basis of existing research, this study expands the one-dimensional warranty to the two-dimensional warranty, and considers the failure dependence between multiple components, thus, broadening the scope of application of the model. The main problems solved in this paper are detailed as follows:This article is organized into seven sections. Before making warranty service decisions for a system, the system characteristics should first be analyzed, then the warranty strategy should be determined, and finally, the maintenance strategy should be determined. This paper mainly focuses on the failure dependence of multi-component systems, adopting a two-dimensional warranty strategy, as well as an opportunistic maintenance strategy. Therefore, the literature review was mainly performed in three parts: A “system” usually refers to an entity with certain structures and functions composed of a certain number of components or subsystems . System Warranty services are contractual relationships established between the manufacturer and the consumer (or user). If a product fails within the warranty period, the manufacturer is responsible for rectifying the product failure. Warranty services can not only guarantee the product performance, but also remove psychological worries of consumers about uncertain product quality. From the perspective of manufacturers, warranty services can not only improve consumers’ satisfaction and recognition of products, but also establish brand image and bring potential new customers; from the perspective of consumers, warranty services can not only protect their own rights and interests, but also reduce the product maintenance costs during the warranty period. Warranty strategies are key indicators to measure the quality of warranty services and are also important factors which influence consumers’ purchase decisions. The feature of two-dimensional warranties is that the warranty period includes two variables: calendar time and usage, which can usually be represented by an area on the two-dimensional plane. The warranty policy can change the shape of the warranty area. Wang  studied n, N) opportunistic maintenance strategy suitable for a two-component series system. The  strategy means that when the running time of a component reaches N, preventive replacement is performed. At the same time, it is judged whether the running time of other components reaches n; if so, opportunity replacement should be conducted. Zheng et al. [Opportunistic maintenance refers to the maintenance activities performed for the maintenance of one component bringing opportunities to perform the preventive maintenance of other components, to carry out some preventive maintenance work in advance. Berg  studied g et al.  proposedg et al.  studied g et al.  and otheg et al.  and otheg et al.  and otheIn this paper, the reliability index of each component is regarded as the basis of maintenance, and the reliability threshold when carrying out preventive maintenance and the reliability threshold when carrying out opportunistic maintenance are set, corresponding to the condition-based maintenance strategy and opportunistic maintenance strategy, respectively. Firstly, the preventive maintenance plan of each individual component is determined by the condition-based maintenance strategy; then, the preventive maintenance plan of each individual component is adjusted and combined with the opportunistic maintenance strategy. This study took the series multi-component system as the research object. During the two-dimensional warranty period (1)The initial reliability of the component is 1, i.e., it is put into use from new.(2)Maintenance resources are sufficient, and the situation of waiting for maintenance due to insufficient maintenance resources is not considered.(3)There is only one main failure mode of components; multiple failure modes are not considered.(4)The utilization rate can be obtained from historical data, and the usage habits of the same user remain unchanged during the basic warranty period, i.e., the utilization rate remains unchanged, and the utilization rates of different users obey uniform distribution.(5)When component (6)In cases of failure during the preventive maintenance interval, the corrective maintenance (minimum maintenance) shall be adopted for component S components in total. The direct construction approach in the univariate method was used to construct the two-dimensional failure rate model of a single component. Based on the construction method developed by Yun and Kang [The multi-component system contained and Kang , the faiStep 1: The component sample size is determined as Z (the number of samples used for the experiment was Z). ith  represents the warranty cost per unit time during the component life cycle, which is mainly composed of four parts. Here, By solving Equation (9), the optimal values of There have been many studies conducted on two-dimensional warranties. During the two-dimensional warranty period, there are many maintenance strategies available. For example, Iskandar and Murthy  divided In this study, the opportunistic maintenance strategy means that when preventive maintenance is carried out for a component at a certain time, multiple components with similar preventive maintenance times are subjected to preventive maintenance as well. Thus, opportunistic maintenance adjusts the maintenance time for certain components and leads to early component maintenance. It is common knowledge that performing maintenance ahead of schedule will reduce the failure risk of components and reduce the maintenance costs caused by component failure, although it will waste a certain use value of components. Therefore, it is necessary to control certain conditions when carrying out opportunistic maintenance. Thus, the reliability threshold when conducting opportunistic maintenance for components is introduced.t. If it is less than i is not considered. Comprehensively considering reducing expected failure maintenance costs and waste of use value caused by the premature preventive maintenance, it is determined whether component i should be subject to opportunistic maintenance at time 3t, as shown in The reliability threshold when carrying out opportunistic maintenance for component 3t. In 3t. Assuming a total of ih opportunistic maintenance procedures conducted for component iuth  preventive maintenance of the multi-component system happens to be the jth preventive maintenance of component i, the downtime of component i is:Suppose that l as an example, the downtime of component l when the yth preventive maintenance of the multi-component system is expressed as Equation (18). The preventive maintenance cost of component l is expressed as Equation (19).At the same time, other components are assessed for whether it is necessary to perform preventive maintenance. Taking component y-th preventive maintenance procedure of the multi-component system is:Then, the downtime of the The total downtime of preventive maintenance of a multi-component system during the warranty period is:The total downtime of corrective maintenance of a multi-component system during the warranty period is:The warranty cost of a multi-component system during the warranty period is:Availability is an important index to measure the proportion of normal working time within the total time of multi-component systems throughout a certain period. Users have high requirements for the availability of multi-component systems. The availability of a multi-component system during the warranty period is:Under availability constraints, the opportunistic maintenance model of multi-component systems aiming for the lowest warranty cost during the warranty period Here, i, the greater the possibility of performing preventive maintenance on or the replacement of component i in advance. The original preventive maintenance plan of the component is changed, and the preventive maintenance interval will become longer, which increases the probability of unexpected failure of the component. Therefore, the corrective maintenance cost and corrective maintenance downtime loss of the system will become higher. The smaller the value of the reliability threshold i, the more the system will be subject to excess preventive maintenance, which will lead to higher preventive maintenance costs and increased downtime of the system. The reliability threshold The greater the value of reliability threshold According to the single-component preventive maintenance interval determined in Step 1: The utilization rate range of a multi-component system is divided into b intervals on average, the probability bP of each interval is calculated according to the distribution of the utilization rate, and the mean value g(r) is the probability density function that the utilization rate obeys:x is the lower limit of the utilization rate interval and y is the upper limit of the utilization rate interval.Step 2: On the premise that the utilization rate is in of a single component; then, the preventive maintenance interval Step 3: The preventive maintenance time a is the number of imperfect preventive maintenance procedures performed on the system, and 0t = 0, a = 1, respectively.Step 4: Preventive maintenance is carried out on component i at time at, and other components are assessed as to whether it is necessary to conduct opportunistic maintenance  is used to calculate the downtime Step 5: The array at time is deleted. If a +t1 is deleted, the time after at is marked as a +t1.Step 6: The corrective maintenance downtime of each individual component in the  is calculated, and the corrective maintenance downtime of all components is summed to obtain the corrective maintenance downtime a−t1, at).Step 7: The total downtime a−t1, at) is calculated. a = a + 1. Return to Step 4 until Step 8: The corrective maintenance downtime ot the end of the warranty period is calculated. Then, the total downtime Step 9: The expected warranty cost The expected warranty cost Step 10: The availability is judged as to whether it meets the constraints. If so, the cost value is stored as well as the corresponding reliability threshold when carrying out opportunistic maintenance; if not, the cost value is eliminated as well as the corresponding reliability threshold when performing opportunistic maintenance. The reliability threshold when conducting opportunistic maintenance is changed to find the scheme that minimizes the warranty cost.The algorithm flow chart is shown in An example of a power transmission device produced by an engine manufacturer in China illustrates the application procedure of the proposed model. All data are from the manufacturer’s historical data or reliability tests. Except for the parameters included in the failure rate function, other parameters can be obtained directly from the manufacturer. The power transmission device was composed of four key components: the valve train component, the lubrication system component, the fuel supply system component, and the starting system component. The component numbers are shown in The manufacturer is responsible for the power transmission device warranty. Generally, preventive maintenance is carried out independently for each component according to the failure law of each component. However, the manufacturer responded that this maintenance method may lead to wasted maintenance costs, mainly because the preventive maintenance work times of some components are similar. If this preventive maintenance is conducted at the same time, the total number of preventive maintenance procedures of the system will be greatly reduced, thus, reducing the maintenance cost. In view of this, the opportunistic maintenance strategy proposed in this paper is adopted in this case, and the advantages of opportunistic maintenance are demonstrated through comparative analysis. The logic of this case is shown in Each component has a trend in degradation in the two dimensions of calendar time and driving mileage. As the mileage increases, the failure rate of the power transmission device will increase; on the other hand, when the engine does not work for a long time, the phenomenon of dry friction or semi-dry friction is more serious when it is restarted, which will accelerate the wear and degradation of components. Therefore, the calendar time and driving mileage affect the reliability of the power transmission device at the same time. Preventive maintenance should pay attention to the calendar time and driving mileage at the same time. The distribution of the service life of each component is as follows:Z is 500, and the estimated parameters of the failure rate function of each component are shown in 4 KM / year) follows the uniform distribution of (0.1 ~ 10). Thus, explicit expressions of g(r) and G(r) are:The parameters of the above formula can be estimated by the method proposed in 4 KM. During the warranty period, the regular preventive maintenance strategy is adopted for each component of the power transmission device, and the corrective maintenance (minimum maintenance) strategy is adopted for unexpected failures within the preventive maintenance interval. When the preventive maintenance of each component reaches a certain number of times, the preventive replacement is implemented. The increasing age factor and decreasing failure rate factor of each component are the same, both At the same time, it was known that the power transmission device had a two-dimensional warranty period of 2 years, 2 × 10In this case, the failure dependence coefficient is estimated by the manufacturer’s experience. The failure dependence coefficient matrix of the power transmission device is:Other parameter settings are shown in It was known that the power transmission device had a two-dimensional warranty period. A year is calculated as 365 days. Firstly, according to the model detailed in r as 1 × 104 KM/year as an example: when opportunistic maintenance is not considered, the preventive maintenance intervals of each individual component for the dimensions of calendar time and mileage are shown in 4 KM/year, the preventive maintenance time of each component for the dimensions of calendar time and mileage  can be calculated as shown in As can be seen in A total of 21 preventive maintenance activities were carried out for the power transmission device. After calculation, the total expected warranty cost of the multi-component system was CNY 535,820 and the availability of the multi-component system was 0.8123. With a high number of preventive maintenance procedures, the preventive maintenance downtime increases, resulting in the waste of warranty cost. It can be seen from Firstly, the genetic algorithm proposed in Without considering the opportunistic maintenance, according to the maintenance plan of each individual component detailed in In order to demonstrate the advantages of GA, it was compared with the particle swarm optimization (PSO) algorithm and simulated annealing algorithm (SAA). Next, the PSO algorithm and SAA were used for optimization. For the PSO algorithm, the number of iterations was 270 and the population size was 100. The inertia weight of the PSO algorithm was 0.9, the self-adjustment weight was 1.49, and the social-adjustment weight was 1.49. The initial value of The minimum warranty cost calculated by the PSO algorithm was CNY 523,685, and the corresponding optimal Through comparison, it was found that the GA can achieve lower warranty costs, and converges earlier with higher operational efficiency; therefore, it has more advantages in solving this model.At this time, the maintenance plan of the power transmission device needs to be adjusted. According to the opportunistic maintenance strategy of multi-component systems detailed in Abbreviations, the maintenance plan of power transmission devices is adjusted, as shown in In Opportunistic maintenance combines preventive maintenance performed at different times, effectively reducing the number of preventive maintenance procedures of a multi-component system, thus, reducing the preventive maintenance downtime of multi-component systems during the warranty period and reducing the shutdown loss. Opportunistic maintenance not only reduces the number of preventive maintenance procedures, but also reduces the minimum number of maintenance procedures. This is mainly because opportunistic maintenance advances the time of preventive maintenance for components, which effectively avoids the occurrence of potential failures. The comparison of power transmission device warranty cost and availability between situations with opportunistic maintenance and without opportunistic maintenance is shown in As shown in When the failure dependence between the components of the power transmission device is not considered, i.e., when the failure dependence coefficient matrix It can be seen from 4 KM. The warranty period of one-dimensional warranties consists of one dimension, which is usually calendar time. When a one-dimensional warranty is adopted, the warranty area changes from a rectangle to an open area with an opening above, which means that the warranty period remains unchanged for 2 years, no matter how the utilization rate changes. The warranty period of two-dimensional warranties consists of two dimensions, one of which is calendar time and the other of which is usage. In this example, the warranty period of the power transmission device was 2 years: 2 years × 10As can be seen from TJ, the preventive maintenance time of each component is adjusted to an integral multiple of the preventive maintenance benchmark interval so as to achieve the result of combining the preventive maintenance of each component. Reference [This paper adopted the opportunistic maintenance strategy to combine the preventive maintenance of each individual component so as to reduce the warranty cost and improve the system availability. In addition to the opportunistic maintenance strategy, the grouping maintenance strategy is another widely used maintenance strategy. By introducing the preventive maintenance benchmark interval eference  adopted eference , the varIt can be seen from It can be seen from (1)The two-dimensional warranty cost of the power transmission device is significantly reduced, and the availability is significantly improved after implementing the opportunistic maintenance strategy, which fully verifies the effectiveness of this strategy.(2)The assumption of failure independence will lead to serious analysis errors and decision-making errors, meaning that it is difficult to provide support for the formulation of a warranty scheme.(3)The two-dimensional warranty method helps manufacturers save on warranty costs. With the increase in the utilization rate, the advantages of two-dimensional warranties are more obvious compared with one-dimensional warranties.(4)Compared with grouping maintenance, opportunistic maintenance has more advantages in reducing warranty costs and improving system availability.This paper considered an opportunistic maintenance strategy for two-dimensional warranty equipment based on the failure dependence of multiple components with the aim of minimizing the manufacturer’s warranty cost. Taking a power transmission device as an example, the results show that:In practice, in addition to imperfect preventive maintenance and replacement, the preventive maintenance strategy includes a function inspection strategy and a failure detection strategy. Function detection strategies assume that there is a process of functional degradation of components, and its theoretical basis is the delay time model; the failure detection strategy considers the existence of hidden failure modes of the equipment. Adding these preventive maintenance measures to the two-dimensional warranty service decision-making model will greatly improve the applicability of the model, but the modeling process will be more complex, and it is worthy of further study. In future studies, we will consider adding the concept of performance into two-dimensional warranty services. The core aim is to present the warranty service provider with certain rewards or punishments through evaluations of the warranty effect, so as to improve the enthusiasm of the warranty service provider and improve the warranty effect. Considering that it is highly necessary to purchase extended warranty services for some new complex equipment, it is necessary to study the extended warranties offered. Making decisions on complex two-dimensional warranties for equipment with failure dependence will be the focus of future studies.


Allochromatium tepidum provides a unique model for investigating various intermediate phenotypes observed between those of thermophilic and mesophilic counterparts. The core light-harvesting (LH1) complex from A. tepidum exhibits an absorption maximum at 890 nm and mildly enhanced thermostability, both of which are Ca2+-dependent. However, it is unknown what structural determinants might contribute to these properties. Here, we present a cryo-EM structure of the reaction center–associated LH1 complex at 2.81 Å resolution, in which we identify multiple pigment-binding α- and β-polypeptides within an LH1 ring. Of the 16 α-polypeptides, we show that six (α1) bind Ca2+ along with β1- or β3-polypeptides to form the Ca2+-binding sites. This structure differs from that of fully Ca2+-bound LH1 from Thermochromatium tepidum, enabling determination of the minimum structural requirements for Ca2+-binding. We also identified three amino acids  in the C-terminal region of the A. tepidum α1-polypeptide that ligate each Ca ion, forming a Ca2+-binding WxxDxI motif that is conserved in all Ca2+-bound LH1 α-polypeptides from other species with reported structures. The partial Ca2+-bound structure further explains the unusual phenotypic properties observed for this bacterium in terms of its Ca2+-requirements for thermostability, spectroscopy, and phototrophic growth, and supports the hypothesis that A. tepidum may represent a “transitional” species between mesophilic and thermophilic purple sulfur bacteria. The characteristic arrangement of multiple αβ-polypeptides also suggests a mechanism of molecular recognition in the expression and/or assembly of the LH1 complex that could be regulated through interactions with reaction center subunits.The mildly thermophilic purple phototrophic bacterium  Thermochromatium tepidum, a phototroph isolated from a hot spring microbial mat in Yellowstone National Park (USA) and capable of growth up to 57 °C (y transition) at 915 nm (T. tepidum LH1 in a reaction center (RC)-associated form identified 16 Ca2+-binding sites in the LH1 complex  of purple phototrophic bacteria, the first thoroughly investigated case was that of the thermophilic sulfur bacterium,  of purplt 915 nm , 4, 5, 6olecules . This Caredshift , 11.2+ in affecting LH1 properties was also demonstrated in a second case where the mesophilic purple sulfur bacterium Thiorhodovibrio (Trv.) strain 970 was shown to integrate Ca2+ into its LH1 complex  a-containing species. A recent cryo-EM structure of the Trv. strain 970 LH1–RC complex revealed that 16 Ca2+ are present in the LH1 C-terminal domain and a Ca2+-facilitated hydrogen-bonding network forms the structural basis of the unique LH1 redshift  and mesophilic Allochromatium vinosum (∼30 °C). The LH1–RC complex purified from A. tepidum shows an LH1-Qy absorption at 890 nm β(outer)-polypeptides, 32 BChls a, and 16 all-trans spirilloxanthins that are uniformly distributed around the RC -8 at the QA site, and a ubiquinone (UQ)-8 at the QB site. The RC fits the shape of the inner LH1 α-ring with the L- and M-subunits in close proximity to the LH1 α2-polypeptides in the transmembrane region , we were able to distinguish all three forms of the α-polypeptides in the A. tepidum LH1 from the cryo-EM density map: six α1, nine α2, and one α3 (A and B). Only α1-polypeptides bind Ca ions using their mainchain oxygen atoms of Trp44 and Ile49 and sidechain carboxyl group of Asp47 as ligands (C and 3A). This WxxDxI Ca2+-binding motif is not present in the A. tepidum LH1 α2- and α3-polypeptides (D). However, comparative analyses showed that the motif is conserved in all Ca2+-bound LH1 α-polypeptides of T. tepidum (Trv. strain 970 (E). The Ile in this motif is essential because the corresponding residue in the A. vinosum LH1 α1-polypeptide is a Val , and the LH1 does not bind Ca2+ . Superpositions of the α1-polypeptide with α2- and α3-polypeptides revealed that the C-terminus of the shortest α2-polypeptide would disrupt the Ca-binding site (C) while the longest α3-polypeptide adopted a different conformation from that of the α1-polypeptide around the Ca-binding site (D). As a result, both α2- and α3-polypeptides are unable to bind Ca2+. Despite this specificity of Ca2+-binding, its effect on overall LH1 BChl a organization is likely limited. Only torsion angles of the C3-acetyl group are affected and tend to have smaller values for the BChl a associated with Ca2+-binding polypeptides than those that do not bind Ca2+  coordination, and the length of the hydrogen bond for the Trp and BChl a C3-acetyl group. Comparisons of the Mg–Mg and His–Mg distances with those from other bacteria are given in The Caf BChl a B. Superping site C while ting site D. As a rind Ca2+ . The torn energy , 20. TheA. tepidum genome are highly similar to those of the corresponding A. vinosum LH1 polypeptides , indicating a mechanism of molecular recognition between the polypeptide chains. The α1/β3 pairs are mainly stabilized through π-π stacking and cation-π interactions in the N-terminal domains, while α2/β1 and α3/β1 pairs lack the cation-π interaction in the N-terminal domains (Rhodobacter sphaeroides (B). These α1/β3 and α2/β1 (including α3/β1) subunits roughly divided into two groups, respectively, and align on the two sides of the LH1 ellipse (B). The arrangement is characterized by specific interactions between the shortest LH1 α2-polypeptides and the RC L- and M-subunits in the transmembrane region (B).Amino acid sequences of the LH1 polypeptides encoded in the peptides  17). Am. AmA. te complex . It is nosum LH1 . The α1-peptides B, indica domains . The sinaeroides  22) and andA. teaeroides B. These  ellipse B. The are region B.A. tepidum LH1 α1- and α3-polypeptides have no significant interactions with the RC subunits in the transmembrane region, these polypeptides have longer chain lengths and are able to interact with the RC C-subunit through their membrane-extruded C-terminal regions (A). The C-terminal domain of the α3-polypeptide is deeply entangled with the membrane-extruded N- and C-terminal regions of the C-subunit (B). The membrane-extruded entity of the RC C-subunit is largely tilted toward one side of the LH1 ring where the α3-polypeptide and two of the α1-polypeptides  are located. Together with the characteristic position of the LH1 α2-polypeptides, the results lead to the conclusion that the unique arrangement of the A. tepidum LH1 α-polypeptides is defined by specific interactions with the RC subunits.Although  regions A. The C--subunit . One of -subunit B. The meA. tepidum Ca2+-bound α1-polypeptide and T. tepidum α-polypeptide revealed an insertion (Thr40) in the C-terminal region of the A. tepidum α1-polypeptide (E). A similar insertion (Ala) is also present at the same position in the A. vinosum LH1 α1-polypeptide. Because this position is close to both the BChl a-coordinating site within the membrane and the Ca2+-binding site on the membrane surface, the insertion was thought to influence the LH1 absorption maximum (Qy transition) (A. tepidum LH1 shows that the insertion in the α1-polypeptide is located in a loop region immediately following the transmembrane α-helix (A). The effect of the inserted residue was minimized by forming a slightly more extended loop whose influence was essentially limited to a very narrow range (Thr39–Phe42) without significantly affecting both BChl a-coordinating and Ca2+-binding sites (B). Therefore, an insertion (in A. tepidum and A. vinosum) or deletion (in T. tepidum) in this loop region should not have a significant effect on the LH1-Qy transition in any of these phototrophs. However, the small but distinct difference in the loop size between A. tepidum and T. tepidum suggests that the LH1 complex of the thermophilic T. tepidum may have evolved to adopt a shorter loop in this region in order to reduce thermal fluctuations and improve stability; such would help the T. tepidum LH1 to remain functional at temperatures above that supporting growth of A. tepidum.Alignment of amino acid sequences between the ypeptide E. A siminsition) , 23. Her α-helix A. The efng sites B. TherefA. tepidum offers a unique model system to investigate the minimum structural requirement for Ca2+-binding in bacterial photosynthetic LH1 complexes. This was challenging with the fully Ca2+-bound LH1s reported previously from T. tepidum  in the C-terminal region of A. tepidum α1-polypeptide were identified as the Ca2+-ligating residues that form a Ca2+-binding WxxDxI motif. This structural motif represents the minimum requirement for an LH1 polypeptide to be able to bind Ca2+ and is conserved in all Ca2+-bound α-polypeptides with reported structures. It is notable that the WxxDxI motif is also present in the LH1 α-polypeptides of Trv. winogradskyi DSM 6702T and Lamprocystis purpurea (Amoebobacter purpureus) DSM 4197T  but far from that of T. tepidum (915 nm). The Ca2+-requirements for an LH1-Qy redshift, LH1–RC thermostability, and phototrophic growth of A. tepidum were also less strict than those of T. tepidum  are 2.9 Å and 3.1 Å for the A. tepidum α- and β-polypeptides, respectively. These lengths are longer than the 2.8 Å and 2.9 Å measured for the corresponding T. tepidum α- and β-polypeptides (PDB: 5Y5S), confirming that the hydrogen bonds formed in A. tepidum LH1 are weaker than those in T. tepidum. The weakened hydrogen bonding incorporated with a partial Ca2+-binding in A. tepidum LH1 likely contribute to its relatively lower thermostability than that of T. tepidum LH1. Our structural information combined with biochemical and spectroscopic analyses indicates that these properties are correlated with the Ca2+ content of the LH1 and is consistent with previous conclusions that Ca ions tightly lock the LH1 rings by forming a Ca2+-connected network that strongly contributes to both thermostability and the LH1-Qy redshift , as measured from the BChl C3-acetyl oxygen. Substitution experiments revealed that these Ca ions indeed alter the electrostatic interaction network and in doing so, influence the LH1 Qy transition . There are no α1/β1- and α2/β3-subunits in the A. tepidum LH1 complex. By contrast, multiple copies of both α1- and α3-polypeptides in Trv. strain 970 form subunits with either β1- or β4-polypeptides (B) . In the A. tepidum LH1, a split of the clustered Ca2+-bound α1/β3(β1) pairs into two groups may also weaken the effects of Ca2+-binding on thermostability and LH1-Qy because both properties are highly collective over all αβ pairs in the LH1 ring. The characteristic arrangement of the A. tepidum LH1 αβ-polypeptides is likely regulated in its expression and/or assembly processes through multiple specific interactions within the LH1 complex  and between LH1 and the RC .The arrangement of multiple α/β-polypeptides within the rain 970  in (i) hpeptides B 14). T. TA. tepe region B. In theA. tepidum LH1 complex, an amino acid insertion of (Thr40) in the C-terminal region of the Ca2+-bound α1-polypeptide turned out to have no significant effect on structures near the BChl a-coordinating and Ca2+-binding sites  the inserted Ala in the mutant T. tepidum LH1 α-polypeptide may have a different effect from that of Thr in the A. tepidum LH1 α1-polypeptide as seen in the Ca2+-binding motif where the sidechain was shown to play an important role for Ca2+-binding (E). To clarify this issue, structural details would be required on the native A. vinosum LH1 complex (E).In our cryo-EM structure of the ng sites . On the t 899 nm . These s-binding E. To cla complex E.A. tepidum were cultivated phototrophically (anoxic/light) at 43 °C for 7 days under incandescent light (60W). Preparation of the A. tepidum LH1–RC followed the procedures described previously , which had been treated in a DII-29020HD (JEOL) for 40 s, and then plunged into liquid ethane at –178 °C using an EM GP2 plunger . The applied parameters were blotting time 6s and 90% humidity at 4 °C. The data were collected on a CRYO-ARM300 (JEOL) electron microscope at 300 kV equipped with a K3 camera (Gatan). An in-column energy filter with a slit width of 20 eV was inserted for acquisition of movie frames. The movies were recorded using JADAS software (JEOL)  at a nomAll of the stacked frames were subjected to motion correction with MotionCor2 , and defT. tepidum LH1–RC (PDB code 5Y5S) was fitted to the cryo-EM map obtained for the A. tepidum LH1–RC using Chimera (ab-initio based on their density. The manually modified model was real-space-refined on PHENIX (The atomic model of the  Chimera . Amino a Chimera . The C-tn PHENIX , and then PHENIX  were chen PHENIX  and UCSFn PHENIX .7VRJ. All other data are available from the authors upon reasonable request.Map and model have been deposited in the EMDB and PDB with the accession codes: EMD-32100 and PDB-This article contains Authors K. K., N. H., I. I., and Y. O. are employees of JEOL Ltd. This does not alter the authors’ adherence to all policies on sharing data and materials. The authors declare that they have no conflicts of interest with the contents of the article.


We findthat the assembly of the CHR–NHR SHB is facilitated in Ca2+-containing media and impaired in CIM mutants. Of note, theclinically approved, gp41-derived fusion inhibitor T20, which doesnot contain the CIM motif, exhibits reduced inhibitory efficiencywhen challenged with calcium. This finding could have important implicationsfor the development of better fusion inhibitors for HIV.The HIV envelope protein gp160 comprises two subunits,gp120 andgp41, responsible for receptor binding and membrane fusion duringviral entry, respectively. In the course of the membrane fusion process,gp41 undergoes a conformational change, leading to the formation ofa six-helix bundle (SHB), which ultimately drives membrane fusion.The gp41 C-terminal and N-terminal heptad repeats (CHR and NHR) interactwith one another to form the SHB, and this step can be targeted bypeptide inhibitors, which are used in the clinic to mitigate HIV infection.Here, we discover the calcium interaction motifs (CIMs) in the gp41CHR and NHR regions  The Blumenthalgroup was likely the first to describe that Env-mediated membranefusion is impaired in the absence of Ca2+, whereas receptorbinding was found to be unaffected.9 Additionaldata support the notion that calcium plays a role in HIV infection,possibly in the fusion process involving SHB formation.13 However, to date, no direct evidence has been provided showing themechanistic role of calcium in this process.A numberof previous publications have reported an involvementof Ca2+ ions , as well as incellulo, by comparing their ability to inhibit HIV cell–cellfusion in the presence or absence of Ca2+ and Mg2+ as a control. We found that Ca2+ promoted SHB formationbetween the wildtype (WT) CHR (C34) and NHR (N36) motifs both in vitro and in cell culture. A mutationin C34 enhanced its SHB oligomerization and cell–cell fusionat high Ca2+ levels, whereas N36 mutations were eithernot affected or abrogated in their ability to form a SHB invitro and in cellulo. Mg2+ hadno effect, suggesting a Ca2+-specific interaction. Lastly,we compared C34 to the clinically used T20 (Enfuvirtide). T20 is agp41-derived peptide that shares a large portion of its sequence withC34 but only partially overlaps with the calcium-binding site  spectroscopy, we have identified amino acids withinthe CHR and NHR that interact with Ca2+ ions 1. Based 2+ ions 1. To evaing site 1. We sho14 on a Liberty Blue peptide synthesizer CEM. Allpeptides were cleaved from the resin by a trifluoric acid, ddw, andTFA/DDW/TES [93.1:4.9:2 (v/v)] mixture, and purified by reverse-phasehigh-performance liquid chromatography (RP-HPLC) to >95% homogeneity.The molecular weight of the peptides was confirmed by platform LCAelectrospray mass spectrometry. The day before administration of peptidesinto biological assays, peptides were dissolved in 95% TFA that wasthen evaporated by N2. Next, peptides were dissolved in50% acetonitrile and lyophilized overnight. Before administrationof peptides into in vitro and in cellulo cell culture experiments, peptides were dissolved in DMSO. Cellswere cultured in a medium not exceeding 0.5% DMSO concentrations.Peptides were synthesized on RinkAmide MBHA resin by using the F-moc strategy as previously described2O was added for locking in NMR experiments. 1D 1H NMR spectra were recorded at 308 K on a Bruker AVANCE 900-MHzNMR spectrometer equipped with a cryoprobe. 64 scans were acquired,and 3 Hz line broadening was used for processing the data. 2D totalcorrelated spectroscopy (TOCSY) NMR spectra were acquired using thefollowing parameters: 80 ms mixing time, 1 s recycle delay, 16 numberof scans, and 512 t1 points. A spectral width of 12 ppm was used.All spectra were processed using Bruker Topspin 2.0 . The TOCSY spectra were analyzed using Sparky.All NMR experiments were performedusing 200 μM peptide. 10 mM Tris-D11, pH 7.4 buffer was used.10% DCD measurements were performed byusing an Applied Photo physics spectropolarimeter. The spectra werescanned using a thermostatic quartz cuvette with a path length of1 mm. Wavelength scans were performed at 25 °C; the average recordingtime was 7 s, in 1 nm steps, in the wavelength range of 190–260nm and recordings were done in triplicates. Each peptide concentrationof 25 μM was tested in a PBS without calcium or magnesium orwith the addition of calcium or magnesium as detailed for each experiment.4 cells/wellovernight in 96-well plates. The medium was then aspirated from eachwell and replaced with serum-free DMEM containing 40 μg/mL DEAE-dextran.Stock dilutions of each peptide were prepared in DMSO so that eachfinal concentration was achieved with 1% dilution. Upon addition ofthe peptides, the HL2-3 cells were added to the TZM-bl cells in serum-freeDMEM containing 40 μg/mL DEAE-dextran at a 1:1 cell ratio. Thecells were cocultured at 37 °C for 6 h to allow the fusion tooccur. Luciferase activity was analyzed using the Steady-Glo luciferaseassay kit (Promega). Fitting of the data points was performed accordingto the following equation, derived from Hills’ equationEffector cells were the Envexpressing cells HL2-3, a HeLa-derived cell line which constitutivelyexpresses the HXB2 strain of the HIV-1 Env glycoprotein along theTat protein, and as target cells, TZM-bl cells were used. The fusionof HL2-3 cells with TZM-bl cells was assessed through luciferase expression.The TZM-bl cells were seeded at 2 × 10B is the maximum value; therefore, it equals 100% fusion, A is the value of an inhibitory concentration at 50% viralinfectivity (IC50), and c represents Hill’scoefficient. For the fitting, we uploaded the X and Y values of the data into a nonlinear least-square regression(curve fitter) program that provided the IC50 value (parameter A).In brief, in this equation, T-test was used. P < 0.05 was consideredsignificant. Analyses were done using GraphPad Prism  version 6.05 .Results are displayed as mean ± SEM.A one-tailed Student’s 2+) on SHB, we performed1D 1H NMR experiments in the presence of Ca2+ .In the presence of Mg2+, the SHB structure was severelycompromised, suggesting structural instability. Nevertheless, thisshows that the effect observed with Ca2+ is specific andnot due to the presence of a bivalent ion.Tostudy the effect of calcium ions (Ca of Ca2+ 1A. Changperiment 1B. The T2+ binding on the SHB: (i) D682in the CHR and G622 in the NHR that sit across from one another; (ii)R607, E610, and H614 that sit in the center of the NHR and protrudeoutward away from the NHR trimer , showing that theshift in secondary structure occurs during SHB formation and doesnot stem from an induced change in the peptide’s intrinsicsecondary structure. We further scrutinized the interaction by comparingtheoretical spectra of the WT and mutant SHBs to the experimentalones obtained in this study with and without 5 mM Ca2+.The theoretical spectrum portrays the additive spectra of the twopeptides, which are input manually based on the spectra of each peptidealone and portrays the theoretical situation of both peptides in solutionwithout interacting. The experimental spectra are obtained by measuringthe peptides when mixed together. Hence, a shift between the theoreticaland experimental spectra suggests a bona fide interaction and notone that results from both peptides just being in the same solution.All but one of the SHB derivatives tested in this study showed a bonafide interaction . The onlyexception was the SHB comprising WT C34 and N36 G-A without Ca2+, which showed no shift between theoretical and experimentalspectra, suggesting no SHB formation. Since SHB formation was observedwith N36 G-A 5 mM Ca2+, it is plausible that Ca2+ can drive the SHB formation of this mutant despite the mutation.Next, we mixed the C34 D-A mutant with either ofthe two N36 mutantsas described above and analyzed their CD spectra. When C34 and N36mutant peptides were used, Ca mM Mg2+ 2B. This in vitro experiments,we wanted to assess the impact of Ca2+ on membrane fusion in cellulo. NHR- and CHR-derived peptides act as competitorsfor SHB assembly. Therefore, their ability to bind counterpart SHBcomponents can be assessed by their inhibitory effect on gp41 mediatedcell–cell fusion, as previously described.21 Jernigan andco-workers have shown that calcium can enhance viral cell fusion ofboth HIV-1 and HIV-2.13 Therefore, we initiallytested the effect of Ca2+ on an Env-dependent cell–cellfusion system. As expected, the addition of Ca2+ significantlyincreased the amount of cell–cell fusion observed when comparedto media lacking Ca2+. A slight but nonsignificant effectwas seen when Ca2+ levels were raised from 2 to 5 mM, suggestingsaturation of the system . Next,we assessed the effect of the WT and mutant SHB-derived peptides oncell–cell fusion in the absence of calcium and with the additionof either 2 mM or 5 mM calcium  via CD spectroscopy. As a control, weused C34 and N36 (annotated SHB) . We further tested this in cellulo via cell–cellfusion assay as described for versus theWT CHR.Since SHB formation is crucial for successful HIV infection, it hasemerged as a common drug target. One such clinically used drug thattargets SHB assembly is the CHR-derived T20 (Enfuvirtide).is study1. Therefis study4A and mais studyS5 via CDis studyS5 via CD24 and the structural mechanics as well asthe molecular dynamics of the Env-mediated membrane fusion are todaywell understood. Before exposure to cellular receptors, Env existsin a native state on the surface of the virus or infected cells. HIVmembrane fusion is initiated by conformational rearrangements in Envthat are triggered by binding of gp120 to the receptor, CD4, and acoreceptor, CCR5 or CXCR4.25 This allowsgp41 then to insert its amino-terminal FP domain into the cell membrane,forming a transient pre-hairpin intermediate that exposes two keyhelical regions (NHR and CHR).26 Subsequently,in its fusogenic conformation, gp41 positions the N and C helicesin an antiparallel manner, called trimer-of-hairpins, the formationof which is mediated by intramolecular interactions between CHR andNHR. These interactions ultimately facilitate the juxtaposition ofthe virus and cell membranes, leading to membrane fusion and successfulvirus entry. The pre-hairpin intermediate is highly vulnerable totherapeutic intervention by inhibitory peptides mimicking heptad repeatregions. Such peptides block the intramolecular binding sites in adominant negative manner, thus effectively halting the ensuing membranefusion process.26Enveloped viruses encapsulated their genomeand proteins in lipidbilayers, derived from host cell membranes. A key step during theirviral entry is the initial binding of the cellular surface receptor,followed by fusion between the virus envelope and target cell membranes.The entry of HIV is exclusively mediated by the trimeric HIV envelopeprotein (Env), consisting of the surface subunit gp120 and the transmembraneprotein gp41. Env is a prototypical class I viral membrane fusionprotein,2+-responsive motifsin the gp41 CHR and NHR (termed CIMs), providing structural evidencefrom NMR spectroscopy for direct interactions between both heptadrepeat regions and Ca2+ ions. CD revealed that SHB formationis Ca2+-sensitive and that mutations in the putative Ca2+ binding sites affect CHR–NHR interactions. In addition,a CHR-derived peptide, resembling the FDA-approved HIV fusion inhibitorT20, which lacks a CIM, exhibited a higher IC50 when applied to thecell–cell fusion assay in calcium-containing media.In this study,we have discovered Ca2+ chelators, yet, without affectingthe binding of gp120 to CD4, suggesting that calcium is directly involvedin fusion.9 Following studies have identifieda possible calcium-binding site within the extracellular part of gp41that resembles the calcium-binding EF-hand structure, indicating thatgp41 is a calcium-binding protein.10 Interestingly,HIV-1 infection of peripheral blood mononuclear cells has been suggestedto be calcium-dependent,11 and some evidenceindicates a distinct effect of Ca2+ on different typesof HIV, as calcium ions have been shown to be crucial for HIV-1 butnot for HIV-2 fusion.13 Yet, although Ca2+ is not required for HIV-2 fusion, the process is enhancedin the presence of Ca2+.13 Moreover,a recent study has demonstrated that the formation of the prefusionEnv-CD4-coreceptor complexes triggers cell surface exposure of phosphatidylserine(PS) that is mediated through Ca2+ signaling, further demonstratingthe role Ca2+ ions play in the HIV fusion process.12Overthe past 2 decades, several studies have established a linkbetween the HIV fusion process and calcium ions. It was shown thatfusion can be blocked by Ca29 Among the most studied peptides in this context is the clinicallyused T20 (Enfuvirtide)30 that blocks the formation ofthe SHB by binding the NHR region of gp41. A peptide encompassingthe putative calcium-binding site in gp41 was shown to be a potentfusion inhibitor, yet, mutations in the calcium-binding site withinthis peptide or deletion of this site results in a lack of antiviralactivity.31 The same peptide was shownto be dependent on calcium to bind the HIV mucosal receptor galactosylceramide.Numerous studies have attempted to generateHIV-1 fusion inhibitorsbased on peptides derived from different regions of gp412+ dependency of viral entry from other virus species.Dube and co-workershave recently reported Ca2+ involvement in the membranefusion and entry of the Rubella virus from the family of Matonaviridae.32 The Rubella virus envelope protein E1 is a classII fusion protein and it was demonstrated that Ca2+, butnot other bivalent cations, shape interactions of the protein’smembrane penetrating FPs. Interestingly, a similar Ca2+ dependency was reported for the FP of SARS CoV and SARS CoV-2 spikeprotein.34 Importantly, Straus et al. were able to repurpose pharmacological calcium channel blockers,which showed promise as a novel class of antivirals inhibiting SARSCoV-2 entry and spread.33 This result demonstratesthat Ca2+-dependent entry can serve as a therapeutic targetand could be exploited for the development of effective pan-viraldrugs with beneficial pharmacological properties.Noteworthily, there is very limited evidence for aCa


P = 3.31e−05) and validation (P = 0.000464) sets. The wp-score was also significantly associated with genetic risk stratification and displayed dynamic changes with varied disease burden. Moreover, we found that high wp-scores in a single gene, BMS1 and GEMIN5 predicted OS in AML patients in both the training set  and validation set . Lastly, our study demonstrated the genome-wide landscape of DNA hydroxymethylation in AML and revealed critical genes and pathways related to AML diagnosis and prognosis. Our data reveal plasma cfDNA 5hmC signatures as sensitive and accurate markers for AML diagnosis and prognosis. Plasma cfDNA 5hmC analysis will be an effective and minimally invasive tool for AML management.Aberrant changes in 5-hydroxymethylcytosine (5hmC) are a unique epigenetic feature in many cancers including acute myeloid leukemia (AML). However, genome-wide analysis of 5hmC in plasma cell-free DNA (cfDNA) remains unexploited in AML patients. We used a highly sensitive and robust nano-5hmC-Seal technology and profiled genome-wide 5hmC distribution in 239 plasma cfDNA samples from 103 AML patients and 81 non-cancer controls. We developed a 5hmC diagnostic model that precisely differentiates AML patients from controls with high sensitivity and specificity. We also developed a 5hmC prognostic model that accurately predicts prognosis in AML patients. High weighted prognostic scores (wp-scores) in AML patients were significantly associated with adverse overall survival (OS) in both training ( Mutations in epigenetic regulators are significantly overrepresented in pre-leukemic states and present in the majority of AML patients2. Although molecular profiling by next-generation sequencing (NGS) has been widely used for AML risk classification, its application for early diagnosis is limited3. Many prognostic factors, including age, cytogenetic and molecular abnormalities, white blood cell count, serum lactate dehydrogenase, and the presence of antecedent hematologic disorders are used to select appropriate therapy for AML patients5. However, the 5-year survival rate for AML patients 20 years and older is only 25% (Cancer.Net). Therefore, additional markers that provide early detection and accurate prognosis prediction to guide therapy are urgently needed.Acute myeloid leukemia (AML) is a devastating hematological malignancy characterized by epigenetic aberrations6. 5hmC is the first oxidative product in the demethylation of 5-methylcytosine (5mC), which is catalyzed by ten-eleven-translocation proteins 7. Unlike 5mC, which displays relatively constant levels in genomes across tissues, 5hmC is an active DNA demethylation mark enriched mostly in active genomic loci. 5hmC can be highly tissue-specific and stable but may also function as a transient intermediate8. Global loss of 5hmC has been observed in AML and many other cancers12 and is associated with TET2, IDH1, and IDH2 mutations in some13 but not all16 patients. Recently, a selective chemical labeling method, termed nano-hmC-Seal technology, enables precise mapping of genome-wide 5hmC distributions with input DNA as low as 1–2 ng17. In conjunction with NGS, nano-hmC-Seal has been applied to plasma cell-free DNA (cfDNA) and revealed 5hmC as a promising diagnostic and prognostic marker in many cancers, including colorectal, gastric, thyroid, lung, liver, esophageal, pancreatic cancers, and lymphoma22. Whole-genome 5hmC maps in 19 human tissues have recently been reported, demonstrating tissue-specific 5hmC marks on tissue-specific gene bodies and enhancers23. However, genome-wide profiling of 5hmC in the plasma cfDNA of AML patients has not yet been reported.Recent evidence indicates that 5-hydroxymethylcytosine (5hmC) correlates with tumorigenesis and gene expression25. As AML originates in the bone marrow (BM) and extends to blood, most molecular analyses require blood and BM. However, many studies on hematological malignancies found that some clinically significant mutations were present in cfDNA but not BM or blood, though most mutations could be detected in all three sources32. A DNA methylation study in patients with myelodysplastic syndromes (MDS) showed earlier detection with cfDNA relative to BM33. Serial analysis of cfDNA has also demonstrated the utility of monitoring clonal dynamics and therapeutic response in chronic lymphocytic leukemia and multiple myeloma35. Taken together, these results indicate that cfDNA is an equivalent or superior molecular diagnostic tool that contains more comprehensive tumor information than blood or BM biopsy samples. BM biopsy is invasive and samples may not capture all of the malignant clones and surrounding microenvironment involved in the disease.cfDNA contains DNA fragments originating from normal and tumor cells undergoing apoptosis, necrosis, or active secretionTo investigate the role of 5hmC in AML, we collected 239 blood samples from 103 AML patients and 81 non-cancer controls and used the highly sensitive and specific nano-hmC-Seal method combined with NGS  to profile the genome-wide distribution of 5hmC from plasma cfDNA. We evaluated the association of 5hmC with disease status, genetic characteristics, and survival of AML patients, and developed 5hmC models for diagnosis and prognosis.23 and cfDNA from solid tumors, including lung, pancreatic, and colorectal cancers8.Normalized total 5hmC peak numbers for each sample were comparable in AML patients and controls, though we observed a wide range in AML samples  with concordant 5hmC and RNA expression levels  (FDR < 0.05) and 454 DhMGs with reduced 5hmC levels and RNA downregulation. Among the concordant DhMGs, those with increased 5hmC levels were significantly enriched in signaling pathways and function categories related to cell proliferation, apoptosis, and immune regulation  with increased 5hmC levels and 1678 DhMGs with decreased 5hmC levels in AML patient samples with overt leukemia at registration time . In these candidates, we further discovered a signature of 70 genes (Table S4) that separated AML samples at registration time  and validation set  at a 6 to 4 ratio . These genes were enriched in signaling pathways and disease and functional categories related to cancer, hematological diseases, hematopoiesis, and cell growth and proliferation  that was significantly associated with OS in the training set  or did not receive (P = 9.34e−05) HSCT , we randomly split the AML samples collected before 2020 and at registration time points into a training set (n = 50) and validation set  but not significantly different compared to the favorable group  recommendationsups Fig. c. Wp-scoP = 0.51; Fig. The survival-related 5hmC signature of three genes was also significantly associated with disease burden. Compared to controls, wp-scores were significantly higher in patients who did not achieve CR Fig. a. There P < 0.05), but only 19 genes showed significant association with OS in the validation set (P < 0.05). Among the 19 genes, BMS1 and GEMIN5 were the top two predictors. Both genes showed significantly reduced 5hmC levels as well as decreased gene expression in AML samples compared to controls  and validation set , we calculated a wp-score of each gene for each sample and determined a cutoff for each gene to classify the patients into a high or low-risk group. We then validated the performance of the wp-scores in the validation set (n = 26). The wp-scores of 157 genes significantly predicted OS in the training set . In contrast to whole blood analysis, 5hmC analysis may capture trace amounts of malignant cfDNA released by AML cells in BM before full-blown leukemia develops in peripheral blood. Plasma cfDNA 5hmC analysis also shows advantages over molecular profiling, which is confounded by clonal hematopoiesis of indeterminate potential3 for early diagnosis of AML. Along with other approaches, sensitive plasma cfDNA 5hmC analysis may facilitate accurate and early diagnosis of AML.We present a 5hmC diagnostic model in plasma cfDNA that accurately distinguishes AML samples from controls. Aberrant DNA methylation occurs early in neoplastic development and has been investigated as a diagnostic marker in AML5. Recent studies have demonstrated that epigenetic markers can be valuable for disease classification and clinical outcome prognosis in AML patients40. High global 5hmC levels are associated with inferior OS13. Our predictive model developed using a 5hmC gene signature or a single gene can significantly separate AML patients with a favorable prognosis from those with an adverse prognosis. The prediction was applicable to patients receiving chemotherapy alone or combined with HSCT. The wp-score of the three gene signatures in post-HSCT patients also predicted whether the patient would relapse at a later time. Based on the wp-score of the three gene signatures, patients in the intermediate-risk group classified by ELN recommendations were further separated into favorable and adverse groups. The 5hmC prediction was also independent of age and sex for AML prognosis. This result indicates potential for the 5hmC predictive model in a wide range of AML patients, working as either an independent prognosis predictor or in conjunction with other tests to facilitate the selection of treatment regimens for AML patients.We also discovered a 5hmC signature in plasma cfDNA that was significantly associated with AML prognosis. AML is a heterogeneous malignancy with complex mechanisms and multiple biomarkers may be needed for disease prognosis. Currently, cytogenetic and molecular markers are the most important for risk stratification and treatment of AML patients41. Using the sensitive 5hmC detection method, plasma cfDNA 5hmC may serve as a potential marker for real-time patient monitoring, MRD detection, and therapeutic response prediction.We observed plasma cfDNA 5hmC levels change dynamically with disease burden in AML patients as demonstrated by both the diagnostic and predictive models. The half-life of plasma is very short, within a few hours42, and we found that 5hmC enrichment in AML is higher in chromatin marks associated with transcriptionally active genes, such as H3K4me1 and H3K27ac (in cis-regulatory enhancer elements), H3K4me3 (in promoters), and H3K36me3 (in gene bodies). However, 5hmC levels in chromatin marks associated with repressed genes (H3K9me3 and H3K27me3) were comparable between AML and control samples. Our findings provide additional evidence of the critical role of DNA demethylation in biological processes and diseases.Our study also revealed the genome-wide landscape of DNA hydroxymethylation in the plasma cfDNA of AML patients and found that 5hmC is enriched in functional regions in both AML and control samples. We discovered AML-specific gains or losses of hydroxymethylation. In AML patients, 5hmC enrichment was significantly higher in cis-regulatory elements compared to controls. Histone marks also regulate gene transcriptionCEBPA, NFKB1, RARA, and SPI1), tyrosine kinases (FLT3 and KIT), the growth factor KITLG, phosphoinositide 3-kinase (PI3K) family members  and the cell cycle regulator CCNA1 in AML patients. Consistent with the 5hmC enrichment, these genes were upregulated in AML samples (Table S1) and play essential roles in the regulation of cell survival and proliferation, programmed cell death, cell migration, intracellular protein trafficking, hematopoiesis, and stem cell maintenance. The survival signature genes, ODF3B, AC092691.1, and AC009035.1, all showed significant enrichment of 5hmC in AML patients compared to controls (Table S1). However, the function of these genes has not been well studied in cancer yet. Moreover, we discovered that 5hmC levels of BMS1 and GEMIN5 predicted OS in AML patients. BMS1 is a ribosomal biogenesis factor and highly conserved across species43. GEMIN5 is an RNA-binding protein and is an essential component of spliceosomes44. The 5hmC levels and gene expression of BMS1 and GEMIN5 are both reduced in AML compared to controls, supporting the tumor suppressor nature of these genes. Our study provided new insights for the understanding of the underlying molecular mechanisms and revealed novel targets for future therapeutic interventions in AML.Identification of new AML biomarkers may also contribute to a better understanding of the molecular basis of the disease. In DhMGs involved in AML signaling, 5hmC was significantly enriched in transcription factors  in each subtype. Therefore, larger scale and prospective studies are warranted to confirm our findings.In summary, we demonstrated that plasma cfDNA 5hmC is an emerging marker for AML diagnosis and prognosis. We also illustrated the important role of DNA hydroxymethylation in AML and discovered new targets to deepen our understanding of AML mechanisms. This study provides a proof of concept for the utility of plasma cfDNA 5hmC analysis as an accurate, sensitive, and minimally invasive diagnostic and prognostic tool in AML.We evaluated 158 plasma samples from 103 adult patients diagnosed with AML (Table S7) and 81 plasma samples from 81 non-cancer individuals. For the entire analyses, 122 plasma samples collected from 2005 to 2019 from 76 AML patients were used. For 5hmC diagnostic model validation, 36 plasma samples collected in 2020 and 2021 from 27 AML patients were used. The ages of non-cancer control patients ranged from 21 to 93 years (median 60 years) in 38 males and 43 females. The ages of AML patients ranged from 27 to 94 years (median 61 years). OS of AML patients before 2020 ranged from 0.1 to 162 months (median 8.8 months). OS was defined as time of registration to death. EFS of AML patients before 2020 ranged from 3.0 to 68.5 months (median 8.3 months). Patient ethnicities included Hispanic (16.5%) and non-Hispanic (83.5%). Thirty-seven of the AML patients had multiple blood collection time points (Table S8). Patients with acute promyelocytic leukemia were excluded from the study. One patient did not have treatment information on record. All other patients received chemotherapy (3 days of anthracycline and 7 days of cytarabine and/or hypomethylating agent). Among the patients sampled before 2020, 33 received HSCT. Twenty-one blood samples were collected at CR and post-HSCT. Blood samples were collected at initial diagnosis and during or after treatment and stored in the Biorepository Core at the Houston Methodist Hospital. Chromosomal karyotypes based on cytogenetic analysis and molecular alterations based on DNA fragment analysis or NGS were available from standard clinical care . This study was approved by the institutional review board at Houston Methodist Hospital. All individuals signed informed consent forms to participate in the study.g for 10 min at 4 °C and stored at − 80 °C. Plasma cfDNA was extracted using QIAamp Circulating Nucleic Acid Kit  following manufacturer’s instructions. The cfDNA was quantified using the Qubit Fluorometer with dsDNA HS Assay Kit  and Bioanalyzer 2100 with Agilent High Sensitivity Assay Kit .Peripheral blood samples were collected in Vacutainer EDTA tubes  and stored at 4 °C before plasma isolation within 3 days. Plasma was separated from whole blood by centrifuge at 1350×17. Briefly, cfDNA was ligated with adaptors and was incubated with N3-UDP-azide-glucose and T4 Phage β-glucosyltransferase at 37 °C for 1 h. After purification, cfDNA was incubated with DBCO-PEG4-DBCO at 37 °C for 2 h. The captured DNA fragments were amplified and sequenced using the NextSeq 550 and NovaSeq 6000 instrument . All experiments were performed in accordance with relevant guidelines and regulations.5hmC library construction was performed as previously described45. High-quality reads were mapped to the reference genome (GRCh37) using bowtie2 with the end-to-end mode46. Reads with mapping quality score ≥ 20, insert size < 600 bp, up to 1 ambiguous base, and < 3 mismatches were retained. We removed PCR duplicates using SAMtools47. To identify 5hmC-enriched regions, 5hmC peaks were called using MACS2 48. Peaks within “blacklist regions”  and sex chromosomes were removed using bedtools49. We used HOMER annotatePeaks50 to analyze genomic feature enrichment. We obtained publicly available AML histone chromatin immunoprecipitation sequencing data and chromHMM segmentation data, an automated computational system for chromatin states, from the BLUEPRINT epigenome project . Plotting and statistical tests were performed using R language version 3.6.351.We evaluated the quality of raw reads and trimmed adaptors and low-quality reads using Trimmomatic52. Raw read counts were normalized using variance-stabilizing transformation with DESeq253. DhMGs (FDR < 0.01) were then identified using DESeq2 adjusted for sex and age. We performed unsupervised hierarchical clustering analysis using pheatmap (https://cran.r-project.org/web/packages/pheatmap/index.html). Metagene profiles of gene bodies and genomic regions associated with histone marks (AML data from BLUEPRINT project) were analyzed using ngsplot54 and deepTools55. Integrated genome viewer was used to visualize candidate genes of interest56. Gene enrichment analyses were performed with Ingenuity Pathway Analysis (IPA). AML differentially expressed genes were downloaded from the Gene Expression Profiling Interactive Analysis (GEPIA2) web server57.To identify DhMGs, the number of high-quality reads mapped to gene body regions were counted without strand information using featureCounts software21. Briefly, with a ratio of 6 to 4, we randomly split AML samples at initial collection time points (we excluded samples in CR) and control samples into a training set (37 AML and 25 control samples) and a validation set (25 AML and 17 control samples). Thirty-six AML samples collected in 2020 and 2021 and 39 controls were used as a test set. We performed univariate logistic regression analysis adjusted for age and sex from 37,468 genes and obtained 3048 informative markers with a cutoff P < 0.01 in the training set. To select the high confidence markers, the elastic net model was cross-validated for a grid of parameter values of α and λ  using glmnet. This selection process was repeated 100 times and a list of 70 genes cross-validated in over 95% of sampling times was selected for the final diagnostic model. We then applied a multivariate logistic regression model to calculate the regression coefficient for each of the 70 genes, and calculated weighted diagnostic scores (wd-score) for each sample in the training, validation, and test sets, where wd-score 22. βk is the coefficient from the multivariate logistic regression analysis for gene k, and Gk is the normalized 5hmC read counts of the kth marker gene. Principal component analysis (PCA) analysis was performed using the prcomp function of R. The AUC and 95% confidence interval were calculated to evaluate model performance using pROC. A cutoff score simultaneously maximized with sensitivity and specificity was determined using optimal.cutpoints in the training set58. Sensitivity and specificity were calculated based on the cutoff wd-score in the validation and test sets.To develop a plasma cfDNA 5hmC signature to classify AML from control samples, we used methods previously describedP < 0.05 and obtained 279 informative genes in the training set. Functional enrichment analysis of 279 genes was performed using IPA. We performed elastic net regularization on the multivariate analysis of selected genes using Cox proportional hazards model, adjusting for age and sex. We also performed feature selection using glmnet and cross-validated the elastic net model with a grid of parameter values for α (α range: 0.05–1 with 0.05 increment). This selection process was repeated 100 times. We identified ten genes by cross-validating in at least 95% iterations . We then performed multivariate analysis of the ten genes using Cox proportional hazards model and identified three genes  as final predictive markers that significantly contributed to OS. We calculated each wp-score based on the 3 genes for each sample in both training and validation sets, where wp-score 22. βk is the coefficient from the multivariate analysis using Cox proportional hazards model for gene k, and Gk is the normalized 5hmC read counts of the kth marker gene. The wp-score cutoff of 18.0 that simultaneously maximized sensitivity and specificity was determined in the training set using optimal.cutpoints. We then validated the performance of wp-score in the validation set. To evaluate whether 5hmC was an independent factor for AML survival, we performed multivariate Cox proportional hazards model analysis including age, sex, and wp-score.We selected samples at registration time points and randomly split them into a training set (50 AML samples) and validation set (26 AML samples). We performed univariate analysis of DhMGs using Cox proportional hazards model with a cutoff of 22. β is the coefficient of the gene from Cox proportional hazards model and G is the normalized 5hmC read counts of the gene. A wp-score cutoff that simultaneously maximized sensitivity and specificity was determined using optimal.cutpoints.To identify single gene markers for OS prediction, we used the same training (n = 50) and validation (n = 26) sets used for 5hmC survival prognostic model development. For the 279 survival-related genes, normalized 5hmC read counts of each gene were fitted with Cox proportional hazards model adjusting for age and sex. A wp-score was calculated for each gene in each sample with the equation wp-score = β × GP value < 0.05 was considered significant.For identification of 5hmC-enriched regions, plotting and statistical tests were performed using R language version 3.6.3. To identify DhMGs, DESeq2 was used to compare 5hmC levels between AML and control samples (FDR < 0.01). For survival analysis, a Kaplan–Meier estimator was used in patients with high or low wp-scores. The log-rank test was used to evaluate statistical significance for the Cox proportional hazards models. For all other statistical tests, the Wilcoxon rank-sum test was used. A This study was approved by the institutional review board at Houston Methodist Hospital. The informed consent was waived.Supplementary Information 1.Supplementary Table S1.Supplementary Table S2.Supplementary Table S10.