GNL3 gene) is a nucleolar–nucleoplasm shuttling GTPase whose levels are high in stem cells and rapidly decrease upon differentiation. NS levels are also high in several solid and hematological neoplasms, including acute myeloid leukaemia (AML). While a role in telomere maintenance, response to stress stimuli and favoring DNA repair has been proposed in solid cancers, little or no information is available as to the role of nucleostemin in AML. Here, we investigate this issue via a proteomics approach. We use as a model system the OCI-AML 3 cell line harboring a heterozygous mutation at the NPM1 gene, which is the most frequent driver mutation in AML . We show that NS is highly expressed in this cell line, and, contrary to what has previously been shown in other cancers, that its presence is dispensable for cell growth and viability. However, proteomics analysis of the OCI-AML 3 cell line before and after nucleostemin (NS) silencing showed several effects on different biological functions, as highlighted by ingenuity pathway analysis (IPA). In particular, we report an effect of down-regulating DNA repair through homologous recombination, and we confirmed a higher DNA damage rate in OCI-AML 3 cells when NS is depleted, which considerably increases upon stress induced by the topoisomerase II inhibitor etoposide. The data used are available via ProteomeXchange with the identifier PXD034012.Nucleostemin (NS; a product of the  GNL3 gene) is a nucleolar–nucleoplasm shuttling protein, mainly resident in nucleoli, which belongs to the Ylqf/YawG family of circularly permutated GTPases. NS levels are high in stem cells, while its expression rapidly decreases upon differentiation [Nucleostemin  is the most frequently mutated, accounting for approximately 30% of all AML cases and 60% of those with normal karyotype. Mutations drive the destabilization or total unfolding of the protein C-terminal domain ,20,21, wWhile a good mechanistic insight has been gained into the role of NS in different solid tumours, as highlighted before, the same cannot be said for haematological cancers. In particular, NS has never been investigated before in the context of AML with NPM1 mutation.Here, we address this issue by taking as a model system the OCI-AML 3 cell line, which bears the most common heterozygous NPM1 mutation . We asseIn order to investigate the role of NS in AML with NPM1 mutation, we used as a model system the OCI-AML 3 cell line bearing the most common NPM1 mutation, i.e., type A. Preliminarily, we assessed basal NS expression in a panel of AML cell lines for comparison . We founKnockdown of NS was performed using a stable and inducible silencing system expressing a short-hairpin RNA (shRNA) specifically targeting NS mRNA (shNS), whose expression is induced only in the presence of doxycycline. First of all, we observed a strong expression of NS in OCI-AML 3 SCR control cells, which was markedly reduced after 72 h of doxycycline treatment. Under this condition, NS protein levels were less than 10% in shNS OCI-AML 3 cells in comparison with the SCR control A. In addp-value < 0.05) were determined via t-test. In particular, in To further shed light on the role of NS expression in OCI-AML 3 cells, we performed shotgun proteomics analysis of shNS cells and their SCR control. We could identify and quantify 1298 proteins for OCI-AML 3 SCR and 1452 proteins for OCI-AML 3 shNS. Among them, 1245 proteins were in common between the two conditions, as reported in the Venn diagram of Quantitative proteomics data obtained with MaxQuant software were used for functional GO reclassification analysis. The protein ratio (OCI-AML 3 shNS/OCI-AML 3 SCR) was subjected to “Core Analysis” through the Ingenuity Pathway Analysis (IPA) bioinformatics tool. The most relevant downstream biological processes that we found are reported in Moreover, NS silencing in OCI-AML 3 resulted in the up-regulation, although not in a significant way, of downstream functions associated with protein translation, degranulation of cells and DNA damage see . We thenE2F1 was predicted to be slightly inhibited, while the retinoblastoma-associated protein RB1 was predicted to be directly activated by CDKN1A/p21 (z-score = 2.12). Moreover, from the IPA analysis, the tumour suppressor p53 (TP53) was also predicted to be activated, though not in a significant manner (z-score = 1.32)  A. We the = 1.32) B. Given  = 1.32) C.homologous recombination” biological function , which is known to elicit DNA damage by inducing double-strand breaks (DSBs) through the inhibition of topoisomerase II  Figure . We firsIn order to evaluate whether impaired homologous recombination in NS-silenced OCI-AML 3 cells resulted in altered proliferation and cell viability under stress conditions due to higher induced DNA damage, we treated both OCI-AML 3 SCR and OCI-AML 3 shNS cells with the same concentrations of etoposide used for immunofluorescence assays to evaluate their ability to proliferate in the presence of this DNA-damage-inducing agent. After confirming that proliferation of NS-silenced OCI-AML 3 cells was unchanged in comparison with SCR control cells in unstressed conditions A, consisCDKN1A/p21 that was predicted to be significantly upregulated. Indeed, p21 was found to be increased in NS-silenced cells, both at the protein and mRNA levels, albeit only modestly. This was also reflected in a modest increase in p53 levels, also predicted by the upstream regulators analysis, although not significantly. These variations might reflect a putative role of NS in protecting rapidly proliferating OCI-AML 3 cells from excessive DNA damage by enhancing their DNA-repair capabilities. This hypothesis would be in line with what was previously observed in other cancers [NS is a relatively recently discovered protein whose multifaceted properties are yet to be fully disclosed. Given its abundant expression in stem cells, it is frequently used as a marker of stemness in laboratory practice. However, while its levels rapidly decrease in differentiated cells, they remain high in multiple cancers ,6,8,9,10 cancers ; howeverIn conclusion, in this work we have started to investigate the role of NS in AML with NPM1 mutation, the most common AML subtype, taking advantage of a proteomic approach. Our data are in line with what has already been shown for other solid tumours, including recent work on breast , hepatocv/v) fetal serum bovine (FBS) ; HL-60 cells were grown in Iscove’s modified Dulbecco’s medium , Italy; #ECB2072) supplemented with 20% (v/v) of FBS ; THP-1 cells were grown in RPMI  supplemented with 10% (v/v) FBS . HEK 293T were grown in DMEM  supplemented with 10% (v/v) FBS  and penicillin–streptomycin 10,000 U/mL . All the cell lines were grown at 37 °C in a humidified atmosphere of 5% (v/v) CO2. Etoposide  was resuspended in DMSO  as stock solution at 500 µM.All AML cell lines used were grown in suspension. OCI-AML 3 and 2 were grown in alpha-MEM  supplemented with 20% (GNL3 (shNS) (clone ID: V2THS_251446) were purchased from Horizon. pTRIPZ plasmid inducible co-express short-hairpin RNAs together with TurboRFP protein were used to monitor levels of induction under doxycycline treatment. Lentiviruses were produced by transient co-transfection of packaging cell line HEK 293T with a three-plasmid expression system using a calcium phosphate transfection kit . Lentiviral plasmids pTRIPZ non-silencing (SCR) and sh5 OCI-AML 3 cells were plated in six-well plates  with viral particles together with 4 µg/mL of polybrene to increase transduction efficiency. Plates were centrifuged at 1800 rpm for 45′ and then incubated at 37 °C for 75′ in a 5% (v/v) CO2 humidified incubator. After this, cells were washed twice and resuspended with fresh medium. Then, 72 h post-transduction, cells were selected with puromycin 1 µg/mL treatment for a week. Induction of silencing systems was performed by treating cells with 2 µg/mL doxycycline for 72 h; the brightest RFP+ cells were sorted with fluorescence-activated single cell sorting (FACS). Silencing efficiency was assessed by WB and quantitative real-time PCR (qPCR).HEK 293T cells were incubated for 6 h with transfection reagents. Lentiviral particles were collected after 48 h and filtered through 0.45 µm pore sterile filters . Then, 3 × 106 cells were collected. Pellets were washed twice with ice-cold phosphate-buffered saline (PBS) solution and proteins were then extracted with a lysis buffer  containing a protease inhibitor cocktail , a phosphatase inhibitor cocktail  and Na3VO4 . Otherwise, to obtain cellular lysates for proteomic analysis, pellets were washed once with medium without serum and three times with ice-cold PBS and then lysed. Equal amounts of total protein lysates were separated through SDS–PAGE electrophoresis and electrotransferred to nitrocellulose membranes for Western blot analysis. Membranes were blocked for 1 h at RT with 5% (v/v) non-fat dry milk in PBS with 0.1% (v/v) Tween 20 and incubated overnight with the following primary antibodies: anti-Nucleostemin (E-8) sc-166460 (1:1000), anti-p53 (DO-1) sc-126 (1:1000) , anti-p21 (DCS60) #2946 (1:1000), anti-β-tubulin #2128 (1:1000), anti-GAPDH (D16H11) XP #5174 (1:2000)  and anti-β-actin (AC-15) #A5441  . After three washes, the membranes were hybridized with horseradish peroxidase-conjugated secondary antibodies . Detection of signal bands was performed with Clarity Western ECL substrate  or with a SuperSignal West Dura extended duration substrate kit . Images of membranes were acquired with a UvitecFire reader  and analysed with Alliance Uvitec software . The original membranes of each blot are reported in In the case of OCI-AML 3 SCR and shNS, cells were induced with doxycycline for 72 h, whereas for the panel of AML lines, cells were harvested when confluent; for each condition, 3 × 10NS For 5′-GGGAAGATAACCAAGCGTGTG-3′,NS Rev 5′-CCTCCAAGAAGTTTCCAAAGG-3′;CDKN1A/p21 For 5′-CGAAGTCAGTTCCTTGTGGAG-3’,CDKN1A/p21 Rev 5′-CATGGGTTCTGACGGACAT-3’;TP53/p53 For 5′-AGGCCTTGGAACTCAAGGAT-3’,TP53/p53 Rev 5′-CCCTTTTTGGACTTCAGGTG-3’;B2M For 5′-GCTCGCGCTACTCTCTCTTT-3′,B2M Rev 5′-TGTCGGATGGATGAAACCCA-3′;β-actin For 5′-CAGCTCACCATGGATGATGATATC-3’,β-actin Rev 5′-AAGCCGGCCTTGCACAT-3’.OCI-AML 3, OCI-AML 2, HL-60 and THP-1 cellular pellets were collected for each condition, after 72 h induction with doxycycline in the case of OCI-AML 3 SCR and shNS, and lysed in QIAzol Lysis Reagent . Total RNA was extracted and quantified. One microgram of RNA was reverse transcribed using a High-Capacity cDNA Reverse Transcription kit , according to the manufacturer’s instructions. Real-time qPCR was performed with a CFX96 Touch Real-Time PCR Detection system  using SsoAdvanced Universal SYBR Green supermix , according to manufacturer’s instructions, and DNA was amplified in 96-well plates . The primers used at a final concentration of 350 nM were:Each sample analysis was performed in triplicate. As a negative control, a sample without a template was used. Cycling parameters consisted of an initial denaturation at 95° for 30 s, followed by 40 cycles of denaturation at 95 °C 15 s and annealing/extension at 57 °C for 30 s. In order to verify the specificity of the amplification, a melting-curve analysis was performed immediately after the amplification protocol. RT-qPCR results were calculated using the ΔΔCt method, with B2M (beta-2-microglobulin) or β-actin used as housekeeping reference genes.4 OCI-AML 3 silenced (shNS) or not (SCR), as well as treated or not, where indicated, were spotted on microscope slides with cytospin centrifugation at 900 rpm for 3 min. Cells were fixed with 4% (w/v) paraformaldehyde in PBS for 10 min, then permeabilized with 0.1% Triton X-100 in PBS for 10 min and blocked for 1 h with 10% goat serum. At this point, microscope slides were incubated overnight at 4 °C with rabbit anti-p-γH2AX  properly diluted in blocking solution. The day after, cells were washed three times with PBS 1X and incubated for 1 h with secondary antibody goat anti-rabbit AlexaFluor488  and Hoechst 33342 properly diluted in blocking solution. Cells were washed and then mounted with coverslips. Finally, a ZEISS LSM800 confocal microscope was used for confocal imaging, a 63× numerical aperture lens was chosen to acquire images and a pinhole of 135 µm was used. Images were then analyzed with ZEN blue 3.2 software . For DNA foci damage analysis, FoCo software [After 72 h of doxycycline induction, 8 × 105 OCI-AML 3 cells/well were seeded onto 12-well plates . Viable and dead cell counts were performed with Trypan Blue reagent  at the indicated time points, considering 72 h post-induction with doxycycline as the starting point. For cell proliferation curves, only viable cells were considered as part of the total number counted for each well considered. The same assays were performed under treatments with different concentrations of etoposide for the time points indicated. For dose–response cell viability assays, 2 × 104 cells per well were seeded onto 96-well plates  once incubated with etoposide treatments at indicated concentrations or vehicle solutions at 72 h post-induction with doxycycline, considered as a starting point. At the indicated time points, cells were incubated for 2 h with CellTiter-Blue Cell Viability assay , according to manufacturer’s instructions, and then the plates were acquired with the microplate reader Synergy H1 Gen5 .After 72 h of doxycycline induction, 2 × 10TM 3000 UPLC  chromatographic system coupled to the Orbitrap FusionTM TribridTM  mass spectrometer, as already reported in our previous work [We performed a shotgun proteomics analysis to evaluate the effect of NS silencing on the OCI-AML 3 cell lines carrying NPM1 mutation A (expressing NPM1c+). Cellular pellets were lysed by sonication in a lysis buffer . After centrifugation of cell debris, the supernatants were tested for protein concentration via Bradford assay  using Bovine Serum Albumin  standard for the calibration curve in order to digest 50 µg of proteins for each different condition according to the filter-aided sample preparation (FASP) method. For protein label-free identification and quantification, a tryptic digestion was carried out overnight at 37 °C . Tryptic peptides from each sample were analyzed in triplicate with LC–MS/MS using the UltiMateous work . Moreoveous work  partner Proteomics raw data were processed using the Andromeda peptide search engine in a free computational platform, MaxQuant version 1.6.6.0  to match the spectra against the UniProt FASTA database , as already reported in our previous works ,41. LFQ 2-transformed to facilitate the calculation of protein expression. Variability between the two different cellular treatments was reported as density plot with Pearson correlation (R2) values of mean LFQ intensities value-transformed to log2 scale . IPA is a tool that can statistically map modulated proteins for their functional annotations, such as canonical pathways, upstream regulators and downstream effects networks, through gene ontology and pathway analysis [Bioinformatics analysis was performed with Perseus version 1.6.10.50 . LFQ intensities were logg2 scale . The Volanalysis . In thisStatistical analyses were performed for each type of experiment by using GraphPad Prism .


Mentoring relationships play a critical but poorly understood role in mentoring’s overall success. To overcome these knowledge gaps, a study of mentee experiences in the Palliative Medicine Initiative, a structured research-based mentoring program, is proposed. The program’s clearly described mentoring approach, competency-based mentoring stages and curated mentoring environment ensure a consistent mentoring experience. It provides a unique platform to study mentoring relationships longitudinally and its implications on professional identity formation.The Tool Design Systematic Evidence-Based Approach methodology is used to map and employ current understanding. A review of recent reviews on mentoring processes, mentoring’s effects, professional identity formation and professional identity formation assessment tools lay the foundation for the design of semi-structured interviews and mentoring diaries to evaluate the characteristics of successful mentoring relationships and mentoring’s impact on professional identity formation. The data accrued from these tools were evaluated using this methodology whilst changes in professional identity formation were assessed using the Ring Theory of Personhood.The semi-structured interviews revealed four themes: stakeholders, mentoring stages, mentoring relationships and professional identity formation whilst the mentoring diaries revealed two: mentoring processes and mentoring relationships. Two final domains emerged – mentoring relationships and professional identity formation.The Palliative Medicine Initiative’s structured stage-based mentoring approach, trained stakeholders, curated environment, assessment-directed and personalized mentoring support reveal seven developmental stages of mentoring relationships. These culminate in changes to the values, beliefs and principles that shape how mentees see, feel and act as professionals. These findings suggest that mentoring programs may help to further develop and fine-tune their professional identity formation.The online version contains supplementary material available at 10.1186/s12909-023-04021-w. Mentoring’s ability to furnish personalized, holistic, timely and appropriate support cultivates deep and trusting mentoring relationships between mentee, mentor and the host organization (henceforth stakeholders) –9. Sng eThe Palliative Medicine Initiative (PMI) hosted by the Divisions of Supportive and Palliative Care (DSPC) and Cancer Education (DCE) at the National Cancer Centre Singapore (NCCS) provides an opportunity to study mentoring relationships in a structured research mentoring program and curated mentoring environment , 9, 21. Within the PMI, the host organization oversees and structures the mentoring program. Senior mentors are trained clinicians, well-versed in the CNEP mentoring approach, and experienced in research mentoring and medical education. In turn, peer mentors are experienced mentees who have successfully completed at least one PMI project and trained to provide complementary mentoring support to new mentees.Just as the PMI offers a unique opportunity to study mentoring relationships within a structured mentoring program, recent developments in the study of moral distress , dignityUnderpinning the utilization of a RToP-based tool is the notion that how a mentee feels, acts, and sees themselves as professionals and in their mentoring roles is shaped by their beliefs, values and principles (henceforth the belief system). This belief system is said to be fashioned by their self-concepts of personhood . It is aThere is growing evidence that Krishna’s Ring Theory of Personhood is able to map changes in self-concepts of personhood and identity. Such discernment requires careful appreciation of competing considerations shaping the mentee’s response to their mentoring, clinical, personal and research experiences. To this end, each of the RToP’s Innate, Individual, Relational and Societal Rings captures specific aspects of the mentee’s belief system Fig. .Fig. 1ThThe Innate Ring’s belief system is rooted in spiritual, religious, moral, and ethical values, beliefs, and principles. The Individual Ring’s belief system draws on elements of conscious function. The Relational Ring’s belief system is fashioned by the values, beliefs, and principles that underpin the mentee’s personal and important relationships. The belief system within the Societal ring is structured by sociocultural, professional, organizational, clinical, ethical and legal influences within the wider community.These belief systems evolve as a mentee progresses through the mentoring program. When encountering experiences that are consistent with the mentee’s belief system there is ‘resonance’. When ‘resonant’ belief systems within one or more rings are adapted to better align with current practice, there is ‘synchrony’. However when experiences are in conflict with the belief system in one ring, there is ‘disharmony’. If these conflicts with regnant belief systems extend to more than one ring there is ‘dyssynchrony’. Appreciating the presence of resonance, synchrony, disharmony and dyssynchrony and their effects provides a means of mapping changing concepts of identity with PIF.What are the characteristics of a successful mentoring relationship?” and “What impact does mentoring have on Professional Identity Formation (PIF)?”, necessitates the design of a PIF assessment tool.The research questions, “The Tool design SEBA methodology designed around Krishna’s Systematic Evidence Based Approach (SEBA) was adopted to guide this two-staged study Fig.  1, 4, 8, 38–42. An expert team of experienced researchers guide the research team and oversee the stages of the Tool Design SEBA methodology.Tool design will be informed by a review of current reviews of mentoring and PIF. The detail of this SEBA guided process is provided in Appendix The combined information from the SSRs in SEBA were supplemented with data from earlier studies on the PMI to contextualize the tool design. The design of the semi-structured interviews and mentoring diaries were also guided by a review of Teo et al. ‘s reviewPurposive sampling of PMI mentees was conducted and the participant information sheet containing the information on the aims of the study, and the participant’s rights to privacy, anonymity and to withdraw from the study at any point without prejudice were included in the email invite. The 30–45 min audio-recorded semi-structured interviews conducted over the Zoom video conferencing platform were carried out between February and May 2021 by experienced and trained interviewers, AP and CQWL. The mentoring diaries were conducted on Google Forms and were completed between March to December 2021.Ethics approval  was obtained from the Singhealth Combined Institutional Review Board. Informed written and oral consent was obtained from all the participants.nderstanding the fluid nature of personhood - the ring theory of personhood” and Kuek, Ngiam  me” (M9). Mentees were motivated to participate for the opportunity to be mentored along research process (M2) as the PMI would “hold your hand and walk through the entire research process” (M12).This stage sees the initiation of the mentoring relationship between the host organization, mentor (henceforth SM), peer-mentor and the mentee.Mentees were matched to appropriate projects depending on their interests, project availability and SM’s research interests. The project’s learning outcomes, timelines, and deliverables as well as personalized project specific goals, learning objectives, assessment timepoints and endpoints were discussed and agreed upon. Mentee (M11) noted that mentors provided “a succinct explanation of what the project was, and what my learning outcomes [would be]…a very broad overview of what was expected of me, and what I would learn.” Mentee (M1) saw these initial interactions as the start of a personalized mentoring relationships stating “he makes the effort to get to know you better... he took the first steps in rapport building.”This stage saw mentored immersion into the research process with new mentees supported by their peer-mentors and SMs. Whilst being the most intense and longest stage of the research process SMs and peer-mentors were accessible and provided individualized support “if you needed any help [with] even the smallest questions, they wouldn’t deem it as a stupid question” (M4). This helped mentees overcome their initial anxieties and lack of knowledge, skills and confidence (M12).Timely: “They were very open to answering and they gave super prompt replies.” (M4)Responsive: “It just piled up after a while but…there was a lot of guidance along the way.” (M1)Accessible: “As busy as [the SM] is, he always makes himself available for his students.” (MD7)Mentoring support was alsoThese features supported the mentee’s assumption of new responsibilities in the mentoring project.This stage saw mentees undertaking data analysis and synthesis and more active role in the projects shifting from “They told me to…” to “I did/suggested…” statements (M5). This process was supported by mentors who “contributed to greater confidence, greater belief in my own capabilities, and what I can do as a medical student” (M5) and who role modelled positive practices (MD2).Active participation in the program developed still further in the manuscript preparation stage with mentee (M7) stating “It was like pitching to the SM my original idea for the paper.”During this stage, communication remained personalized and adaptive to the mentee’s needs: “It [interactions with the mentor and peer-mentor] is just right and it gives me the space and time to work…at the same time [I am able to] check in with him to make sure that I am on the right path.” (MD14). This facilitated deeper connections with mentees seeking guidance in non-research related areas and personal issues (MD17).) and in their personal contribution to clinical practice (M7). It also allowed mentees to appreciate “what good mentoring [was] like” (M2), where free communication (M7) and a non-judgmental learning environment were provided (M4) and reflect on its effects on their development (M4). Mentees also described taking on the values espoused by their mentors such as “personal management, self -discipline.” (M5) and adopt new practices such as how they interact with their juniors and how they “build rapport.” (M1).Reflecting upon their PMI experiences, mentees reported a sense of pride in the personal and professional development , poor communications , limited guidance  from busy clinicians, and ‘stunted’ mentoring relationships due to large group sizes .Seen through the RToP the mentoring process provides a longitudinal perspective of professional identity formation (PIF) and the impact of resonance, synchrony, disharmony and dissonance.Innate Ring: There were shifts in perspectives on spirituality and/or their moral compass – “I’m a Buddhist and [the research mentoring journey] did reinforce some of the philosophies behind it.” (M2)Individual Ring: Mentees re-evaluated their values, beliefs, hopes, self-expression, and self-awareness – “I started to ask myself…What were my qualities? What do I want in life?” (M7)Relational Ring: Mentees reported changes in how they interact with their families especially in the context of end-of-life care – “[It] made me think about how I should start planning…myself and my family members, what would they want out of their care?” (M7)Societal Ring: Mentees were able to apply their learning to their professional roles as medical professionals – “When I saw what the Senior Mentor was like, I was thinking, that’s the kind of doctor I want to be that kind of level of EQ and level of interaction with patients.”(M10)Between Societal and Relational Rings: “Learning how to draw boundaries reasonably and communicating effectively…extended to my personal relationships as well within my family... it’s made the relationship a lot healthier…” (M1)Between Societal and Innate Rings: “Learning about death and dying patients, and the process at the end of life…reinforced my religious beliefs.” (M2)Between Societal and Individual Rings: “I wouldn’t say [beliefs about my work and career] changed dramatically…it reaffirmed and consolidated what I knew about myself.” (M10)Between Individual and Relational Rings: “Now I’m thinking about things maybe in terms of relational aspects” (M7)Dyssynchrony between societal and individual ring saw challenges in striking a healthy work-life balance: “It’s hard (to) manage your time with it when you have other commitments as well… that’s really a compromise and sleep, your health, your social life and your schoolwork.” (M6).Disharmony was especially evident within the societal ring. This saw differing views on responsibilities. “I think a good doctor needs to be able to connect with patients and understand them. But there isn’t that obligation to teach [this in school].” (M12) In addition, the medical hierarchy led to difficulties in connecting with the younger mentees: “How I actually interact with my juniors...is affected by a sort of power imbalance in a sense and sometimes the juniors may not be ready [for it].” (M1).What are the characteristics of a successful mentoring relationship?”, this study reveals seven stages in the development of mentoring relationships.In answering the question, “Stage one concerns the mentoring relationship platform. This platform is shaped by the mentoring framework employed by the host organization. The mentoring framework maps the mentoring curriculum, process, approach, assessments and support mechanisms. Given the PMI’s goal of guiding mentees towards primary authorship in research publications, the mentoring framework encourages mentees to move from a peripheral to a more central role in the research process by providing them with training, guidance, feedback and support.Stage two sees the integration of support mechanisms within the mentoring relationship platform. This includes robust and accessible two-way open communication channels, protected time for mentoring and ‘goodness of fit’. ‘Goodness of fit’ requires tailoring the mentoring approach, working styles, timelines, expectations, roles, responsibilities and meeting schedules to accommodate the mentee’s changing goals, needs, abilities, experience and availabilities.Stage three focuses on nurturing enduring mentoring ties through adaptable and personalized support. Responsive, timely, accessible, holistic, and longitudinal support by trained mentors introduce ‘flexibility’ to the mentoring framework. ‘Balancing’ ensures that flexibility does not compromise compliance to parameters set out by codes of conduct.Stage four highlights the importance of the mentoring dynamics between stakeholders. These dynamics reflect the quality of mentoring interactions Fig. .Fig. 3AnMentoring dynamics pivot on the personalization of mentoring relationships provided by the ‘mentoring umbrella’. In the initial mentoring stages where role modelling, teaching, and coaching personalize the mentoring experience, counselling and advising later give way to assessment-based coaching and project supervision Fig. . This miStage five assesses the mentoring relationship. This is done at each mentoring stage and considers evolutions in the mentee’s beliefs system, practice and outlook.Stage six sees the employ of assessment data to guide mentoring support and shape adaptations to the mentoring approach.What impact does mentoring have on Professional Identity Formation (PIF)?”. In their mentoring diaries, mentees suggest that a change occurs in the manner they feel, see and act about their role in the PMI as mentors guide and role model pertinent values, beliefs and principles to the mentees, tutor them in the appropriate knowledge and competencies required, coach them in research skills and team-based practice, supervise them throughout the research process and direct longitudinal and personalized mentoring support within the confines of the mentoring framework. These features provide evidence of mentoring’s impact upon identity formation. These features are summarized in Fig. Stage seven helps address the research question “Progress through the mentoring stages reveals the presence of synchrony, resonance, disharmony and dyssynchrony. This reflects the impact of new practices, values, beliefs and principles upon the mentee’s current belief system.These changes affirm mentoring’s impact on PIF. Figure Whilst the data accrued from the semi-structured interviews and mentoring diaries were drawn from 29 mentees and echoed the findings of large-scale reviews on mentoring relationships, programs and the mentoring environment, the mentees were interviewed at a single time point, often after completion of a project or at the later stages of their research process. This may have led to recall bias and the halo effect. Whilst the use of diaries to triangulate the interview data added depth to the analysis, there were limited entries.The Palliative Medicine Initiative’s structured stage-based mentoring approach, trained stakeholders, curated environment, assessment-directed and personalized mentoring support reveal seven developmental stages of mentoring relationships. These culminate in changes to the values, beliefs and principles that shape how mentees see, feel and act as professionals. These findings suggest that structured mentoring programs may help to further develop and fine-tune their professional identity formation. We posit that portfolios containing mentoring diaries, reflections and regular assessments of their mentoring progress could provide a better appreciation of mentoring’s relationship with professional identity formation.Additional file 1.


Accumulating evidence suggests that impaired SERCA function is associated with disruption of intracellular Ca2+ homeostasis and induction of ER stress, leading to different chronic pathological conditions. Therefore, appropriate strategies to control Ca2+ homeostasis via modulation of either SERCA pump activity/expression or relevant signaling pathways may represent a useful approach to combat pathological states associated with ER stress. Natural dietary polyphenolic compounds, such as resveratrol, gingerol, ellagic acid, luteolin, or green tea polyphenols, with a number of health-promoting properties, have been described either to increase SERCA activity/expression directly or to affect Ca2+ signaling pathways. In this review, potential Ca2+-mediated effects of the most studied polyphenols on SERCA pumps or related Ca2+ signaling pathways are summarized, and relevant mechanisms of their action on Ca2+ regulation with respect to various ER stress-related states are depicted. All data were collected using scientific search tools .Sarco/endoplasmic reticulum Ca Aberrations in Ca2+ homeostasis have been linked to the development of various pathophysiological conditions, such as cardiovascular diseases [2+ concentrations [(Ca2+)i] must be maintained within very low concentrations (~10–100 nmol/L), which are regulated by a number of Ca2+ transport systems, such as pumps and channels ~100 to 800 μmol/L) in an ATP-dependent manner i is maintained due to the action of the plasma membrane Ca2+-ATPase (PMCA) and Na+/Ca2+-exchanger (NCX), which are responsible for the extrusion of Ca2+ from the cell. Upon elevated [Ca2+]i, the SERCA pump is activated to maintain the required [Ca2+]i by sequestering Ca2+ from the cytosol into the ER i. In certain tissues, SERCA sequesters more than 70% of the cytosolic Ca2+ ER, rather than the increased [Ca2+]i, triggers apoptosis, it has been suggested that maintaining ER Ca2+ homeostasis via ER-localized pumps and channels represents a primary stimulus in triggering mechanisms leading to aberrations of intracellular Ca2+ homeostasis, as well as to the onset of ER-stress-related diseases i by depletion of intracellular Ca2+ stores, mainly due to the activation of capacitative Ca2+ entry and the involvement of other Ca2+-permeable channels i leads to mTOR inhibition, inducing the process of autophagy  is a major biologically active constituent of ginger. This polyketide is found in the Zingiberaceae family and in the grains of paradise as well as an African ginger species. It has been described to exhibit various effects—most importantly anticancer, anti-inflammatory, and antioxidant properties . The ant2+ uptake into the SR lead to aberrant Ca2+ handling in failing hearts, including abnormalities in systolic and diastolic functions . The highest SERCA activity is gained at high systolic [Ca2+] or when PLB is phosphorylated i, independently of SERCA [2+]i, which was correlated with the inhibition of SERCA activity [2+ transport in cardiac SR vesicles. EGCG increased the Ca2+-sensitivity of Ca2+ uptake into cardiac SR vesicles in a concentration-dependent manner, which was affected by the interaction between SERCA and PLB [2+ loading into the SR, and facilitated the release of Ca2+ through RyR2 without affecting SERCA2 activity or L-type Ca2+ currents. Enhanced activity of RyR2 promoted increased amplitude of Ca2+ transients. Moreover, EGCG in nanomolar concentrations caused a positive inotropic effect [Green tea is a rich source of polyphenols, of which EGCG is the best-studied tea component, with multiple beneficial actions in different human pathological states. EGCG was described as affecting second messenger Caof SERCA . Indeed,of SERCA . On the activity . Kargaciactivity  studied  and PLB . In anotc effect . Possiblc effect .50 ≈ 0.3 μmol/L) were observed to stimulate Ca2+ uptake and ATP hydrolysis in cardiac SR, while higher concentrations (IC50 ≈ 3 μmol/L) inhibited SERCA2 activity in both cardiac and skeletal muscle SR. Therefore, the observed SERCA stimulation seems to result from removing the inhibition of SERCA by PLB, similarly to that observed by EA. The inhibitory effect of tannin was attributed to competitive inhibition of nucleotide binding [2+ overload [2+ due to its galloyl groups [2+ dysregulation.Tannins are polyphenolic compounds found in a variety of plant-based foods and beverages, including tea. Low tannin concentrations  is a phenolic phytonutrient classified as a hydroxycinnamic acid, which can be found in abundance in various plants, and possesses a wide range of beneficial properties. CA was shown to have positive impacts on vascular function and blood pressure by potentiating SERCA2a activity in the vascular smooth muscle cells. Binding of CA to SERCA was accompanied by the formation of strong hydrogen bonds. Specifically, CA restored the thapsigargin-induced rise in [Cao the SR . Anothero the SR .Citrus bergamia), a citrus fruit rich in the polyphenols neoeriocitrin, neohesperidin, naringin, bruteridin, and melitidin, exerts various pharmacologically beneficial properties—especially cardioprotective and antidiabetic effects [2+-regulating properties in endothelial cells. They concluded that bergamot increased the intracellular Ca2+ concentration via the release of Ca2+ from the intracellular Ca2+ stores, as well as through SOCE, suggesting protective effects on endothelial dysfunction [Bergamot , are able to interact with SERCA and affect a wide range of intracellular events. Based on the reviewed information, polyphenolic substances may be beneficial in the management of chronic disease conditions associated with SERCA downregulation, such as cardiovascular diseases, diabetes, metabolic disorders, and neuropathological conditions.Ca2+ homeostasis, it is noteworthy to highlight the following:(i)Upregulation of SERCA expression, specifically via AMPK/SIRT activation;(ii)Increase in SERCA activity and stability;(iii)Relieving SERCA2 from the SERCA–PLB complex;(iv)Enhancing RyR1 and RyR2 activity/expression,(v)2+-dependent channels, such as L-type and T-type VGCCs, Ca2+-activated K+ channels, or SOCs.Affecting CaTo summarize the key mechanisms of polyphenols’ protective action with respect to impaired intracellular Ca2+ overload as well as relieving the load on the underlying adaptive Ca2+ regulatory pathways and, thus, contributing to the management of diseases associated with ER stress. Activation and upregulation of SERCA2 seems to be included within the core Ca2+-dependent mechanisms, whereby polyphenols manifest their cardioprotective and antidiabetic actions. However, additional studies  are required to address the detailed mechanisms of polyphenol-mediated action with respect to polyphenol–SERCA interactions and downstream Ca2+ signaling pathways to contribute in the management of various pathophysiological conditions.Increasing SERCA activity/expression via specific SERCA activators may help to ameliorate ER stress while reducing cytosolic Ca


Vasculogenic mimicry (VM) is an endothelium-independent tumor microcirculation that provides adequate blood supply for tumor growth. The presence of VM greatly hinders the treatment of glioblastoma (GBM) with anti-angiogenic drugs. Therefore, targeting VM formation may be a feasible therapeutic strategy for GBM. The research aimed to evaluate the roles of BUD13, CDK12, MBNL1 in regulating VM formation of GBM. BUD13 and CDK12 were upregulated and MBNL1 was downregulated in GBM tissues and cells. Knockdown of BUD13, CDK12, or overexpression of MBNL1 inhibited GBM VM formation. METTL3 enhanced the stability of BUD13 mRNA and upregulated its expression through m6A methylation. BUD13 enhanced the stability of CDK12 mRNA and upregulated its expression. CDK12 phosphorylated MBNL1, thereby regulating VM formation of GBM. The simultaneous knockdown of BUD13, CDK12, and overexpression of MBNL1 reduced the volume of subcutaneously transplanted tumors in nude mice and prolonged the survival period. Thus, the BUD13/CDK12/MBNL1 axis plays a crucial role in regulating VM formation of GBM and provides a potential target for GBM therapy. Glioblastoma (GBM) is one of the most common primary malignant tumors in the central nervous system . DespiteRNA-binding proteins (RBPs) form ribonucleoprotein complexes by binding to double-stranded RNA through RNA structural domains  to regulBUD13 homolog (BUD13) is the subunit of the retention and splicing (RES) complex, which affects the retention of pre-mRNA in yeast cells . BUD13 rN6-methyladenosine (m6A) methylation mainly occurs on adenosine of the RRACH  sequence . The m6ACyclin dependent kinase 12 (CDK12) is a member of the serine/threonine kinase family. It regulates a variety of biological processes, such as C-Myc expression, Wnt/β-catenin signaling pathway, RNA splicing, MAPK signaling pathway, and DNA damage response . CDK12 iMuscleblind-like 1 (MBNL1) is a highly conserved protein belonging to the tissue-specific RNA metabolism regulation family, which controls RNA shearing function and drives large transcriptome changes during cell differentiation . By geneMatrix metallopeptidase 2 (MMP2) belongs to the matrix metalloproteinase family, which can degrade the tumor-mediated extracellular matrix. It plays an important role in the invasion and metastasis of tumor cells and promotes tumor cells VM formation through a variety of mechanisms , 27. In In the study, we firstly clarified the expression of BUD13, CDK12, and MBNL1 in GBM tissues and cells and further analyzed the regulatory relationship between the above factors on VM formation in GBM cell. This study aims to identify new therapeutic targets for GBM and bring new references for treatment and prognosis.n = 9) with traumatic brain trauma in neurosurgery at Shengjing Hospital affiliated to China Medical University were selected as negative control group, and tissues with postoperative pathological examination as glioma in patients with brain tumors were selected as experimental group. Glioma are classified according to the WHO classification into low-grade  and high-grade glioma . This study was confirmed by the Ethics Committee of Shengjing Hospital affiliated to China Medical University, and was approved by the patients and the families with informed consent obtained. Glioma inclusion criteria: (1) age superior to 18 years; (2) first onset, imaging  identified intracranial mass lesions, hospitalization for surgical treatment and postoperative pathology diagnosis; (3) without radiotherapy, chemotherapy, and other treatments before surgery. Glioma exclusion criteria: (1) combined with hematologic disorders; (2) combined with other malignant tumors; (3) combined with other organs abnormal function; (4) combined with immune system diseases or connective tissue lesions. Negative control group inclusion criteria: (1) brain trauma; (2) without related diseases such as intracranial tumors, cerebral hemorrhage, and cerebral infarction before injury. Negative control group exclusion criteria: (1) other serious underlying diseases such as: coronary heart disease, cirrhosis, renal insufficiency; (2) other tumors. All the tissue samples were immediately frozen in liquid nitrogen after surgical resection and stored in liquid nitrogen until use.Normal brain tissues (NBTs) of patients  and 293T cells were purchased from the Shanghai Institutes for Biological Sciences Cell Resource Center. Normal human astrocytes (NHAs) were purchased from Sciencell Laboratory in the United States.RNA expression levels in the study were detected by quantitative real-time PCR (qRT-PCR). Trizol reagent  was used to extract RNA from various tissues and cells. The primers are displayed in Supplementary Table The overexpression plasmids, knockdown plasmids, and mutant plasmids of various indicators in the study were purchased from Gene-Pharama . For more details, please refer to Supplemental Materials and Methods. Sequence of shRNA are shown in Supplementary Table Microarray analysis, sample preparation and microarray hybridization were operated by Aksomics Biotech .Western blot was operated as previously described. For details of the experiment, please see Supplemental Materials and Methods.Cell viability assay was operated as previously described . For detThe capacity for migration in GBM cells was observed by the HoloMonitor M4 culture system  in vitro. For details of the experiment, please refer to Supplemental Materials and Methods.Cell invasion assay was operated as previously described . For detThree-dimensional tube formation assay was operated as previously described. For details of the experiment, please see Supplemental Materials and Methods .RNA immunoprecipitation (RIP) assay was operated as previously described . For detRNA pull-down assay was operated as previously described . For detThe nascent RNA capture assay was performed as previously described . For detCells were cultured in the medium containing 5 µg/mL actinomycin D . Total RNA was extracted from the cells and collected at different time points. The half-life of mRNA was detected at a certain time point compared with 0 h by qRT-PCR.The RNA was denatured by heating at 65 °C for 5 min and transferred to the nitrocellulose membrane  with Bio-Dot device . The membrane was UV-crosslinked, sealed, and incubated with m6A antibody  at 4 °C overnight. After washing with TTST, the membrane was incubated with HRP-conjugated goat anti-mouse IgG  for 1.5 h. Then visualizing by enhanced chemiluminescence . Staining the membrane with 0.02% methylene blue diluted in 0.3 M sodium acetate to ensure consistency across groups.Cells seeded on glass slides were fixed in 4% paraformaldehyde for 20 min and permeabilized with 0.2% TritonX-100 for 10 min and then blocked with 5% BSA for 2 h at room temperature. Next, the cell slides were incubated with primary antibodies at 4 °C overnight. Then, the cell slides were washed with PBST three times and incubated with fluorescent-conjugated secondary antibodies-Goat anti-Rabbit Alexa Fluor 488 or Goat anti-Mouse Alexa Fluor 647  for 2 h at room temperature away from the light. Finally, the nucleus were stained with DAPI for 5 min. Fluorescence was visualized under laser confocal microscopy.Co-immunoprecipitation (Co-IP) assay was performed using the Pierce Co-IP Kit  following the manufacturer’s instructions. Cell lysates were prepared and incubated with AminoLink Plus Coupling Resin immobilized primary antibody overnight at 4 °C. Then, the samples were washed three times with 200 μL Wash Buffer and eluted with Elution Buffer for 5 min. The eluates were finally analyzed by western blot.Prokaryotic expression plasmids fused with FLAG or GST tag were constructed including FLAG-CDK12, GST-MBNL1 (WT), GST-MBNL1-T6A (mut). These plasmids were transformed into Escherichia coli competent cell BL21  and protein expression was induced by 1 mM IPTG  at 25 °C and 200 rpm for 6 h. Then, cells were lysed, sonicated, and centrifuged. The proteins were purified using the BeyoMag™ anti-Flag Magnetic Beads and BeyoGold™ GST-tag Purification Resin  according to the manufacturer’s procedure. For GST pull-down assay, purified FLAG-CDK12 was incubated with purification resin coupled with GST-MBNL1 protein at 4 °C overnight. Then protein complexes were eluted by Elution Buffer and then subjected to SDS-PAGE and analyzed by western blot.In vitro kinase assay was performed at 30 °C for 20 min containing 10 μg MBNL1 protein, 5 μg CDK12 kinase , 50 μL kinase buffer , 50 mM ATP , 5 μCi [γ-32P]-ATP . Stop the kinase reaction with 1×SDS buffer , and perform autoradiography after SDS-PAGE electrophoresis. The loaded amount of substrate protein was shown by coomassie brilliant blue  staining.Cells were cultured in the medium containing 10 µM cycloheximide  to inhibit protein biosynthesis. Total protein was extracted at different time points, then detected by western blot.VM was detected by CD34-PAS in xenograft tumor tissue samples. The assay was performed as reported previously . For detThe constructed stably transfected GBM cells (U251 and U373) were used to establish xenograft models in nude mice. For more details, please see Supplemental Materials and Methods.P < 0.05.The experimental data were collected and presented as mean ± SD. Student’s t-test or one-way ANOVA was used in the statistical analysis by the GraphPad Prism v8.4 . Differences between groups were regarded as significant when The protein expression of BUD13 in GBM tissues was significantly higher than that in NBTs and was positively correlated with the pathological grade. Similarly, BUD13 protein expression in U251 and U373 cells was significantly higher than that in NHAs Fig. . To furtThe m6A methylation level and the METTL3 protein expression in U251 and U373 cells were significantly higher than that in NHAs Fig. . After MCompared with the Control group, the proliferation, migration, invasion, and tube formation abilities of the BUD13-m6A-WT group were significantly enhanced, while BUD13-m6A-mut group had no difference Fig. . CompareWith mRNA microarray analysis and qRT-PCR, we verified that CDK12 was significantly decreased in U251 and U373 cells treated with BUD13(-) Fig. . The proWe further confirmed CDK12 protein expression decreased after BUD13 knockdown Fig. . STARBASTo further investigated whether CDK12 was involved in the inhibitory effect of BUD13 knockdown on VM formation in GBM cells, CDK12(-), CDK12(+), and their NC plasmids were transfected into BUD13-knockdown plasmids in the study. CDK12 knockdown strengthened the inhibition of the proliferation, migration, invasion, and tube formation abilities induced by BUD13 knockdown, while CDK12 overexpression rescued the inhibition of the proliferation, migration, invasion, and tube formation abilities induced by BUD13 knockdown Fig. . And we To reveal the function of CDK12, CDK12-interacting proteins were coimmunoprecipitated for mass spectrometry analysis in U251 cells expressing FLAG-CDK12. Among the candidates, MBNL1 was selected for further study Fig. . The phoTo further investigate the mechanism between CDK12 and MBNL1, immunofluorescence assay was performed and showed that CDK12 colocalized with MBNL1 in the cytoplasm of U251 and U373 cells Fig. . Co-IP aTo further investigate whether MBNL1 was involved in the inhibitory effect of CDK12-knockdown on VM formation in GBM cells. The study transfected MBNL1(+), MBNL1(-) and their NC plasmids into CDK12-knockdown plasmids. MBNL1 overexpression strengthened the inhibition of proliferation, migration, invasion and tube formation abilities induced by CDK12 knockdown, while MBNL1 knockdown rescued the inhibition of proliferation, migration, invasion and tube formation abilities induced by CDK12 knockdown Fig. . And we To confirm the roles of BUD13, CDK12, and MBNL1 in tumor growth in vivo, we subcutaneously injected GBM BUD13(-) cells, CDK12(-) cells, MBNL1(+) cells, or a combination of the three cells to construct nude mice xenograft models. The average size of the xenograft was smaller in BUD13(-), CDK12(-), and MBNL1(+) mice than that in the Control mice Fig. . The xenThe study confirmed for the first time that BUD13 and CDK12 were upregulated and positively correlated with the pathological grade in GBM. MBNL1 was downregulated and negatively correlated with the pathological grade in GBM. METTL3 enhanced the stability of BUD13 mRNA and upregulated its expression through m6A methylation. BUD13 enhanced the stability of CDK12 mRNA and upregulated its expression. CDK12 phosphorylating MBNL1 regulated proliferation, migration, invasion, and tube formation of GBM.RNA-binding proteins (RBPs) play vital roles throughout the mRNA life cycle . The mecm6A methylation was first discovered in the 1970s and was the most common reversible epigenetic modification in mRNA . As an iBased on mRNA microarray analysis, we verified that CDK12 was significantly decreased in U251 and U373 cells after BUD13 knockdown. The study proved that CDK12 was upregulated in GBM tissues and cells, and knockdown of CDK12 might inhibit the proliferation, migration, invasion, and tube formation of GBM cells. CDK12 regulated transcription by binding to cycling K and phosphorylated RNA polymerase II Ser5 in vitro to regulate transcription initiation and was involved in DNA damage response, cell proliferation, and pre-RNA splicing. In diffuse large B-cell lymphoma, CDK12 activated MYC to inhibit miR-28-5p/EZH2 and amplify BCR signaling to promote its progression . StructuThe STARBASE database predicted that BUD13 bound to CDK12 mRNA. In the study, RIP and RNA pull-down assay confirmed the prediction. The nascent RNA and half-life experiments confirmed the stability of CDK12 mRNA decreased when BUD13 was knockdown, suggesting that BUD13 might intensify the stability of CDK12 mRNA. Previous research reported RBPs enhanced the mRNA stability or degradation of proto-oncogenes and tumor suppressor genes by forming complexes with them . For exaTo investigate the possible mechanisms by which CDK12 regulated VM formation in GBM, we performed Co-IP assay coupled with mass spectrometry and selected MBNL1, which has been reported regulated the expression of VM-related proteins MMP2 and LAMC2 through the TGF-β pathway thereby regulating VM formation. MBNL1 is an RBPs regulating RNA alternative splicing, localization, and integrity. Previous studies have found that MBNL1 was associated with ankylosing muscular dystrophy , but recMatrix metalloproteinases (MMPs) are proteolytic enzymes that degrade basement membranes and extracellular matrix. VM formation of tumor was dependent on extracellular matrix MMPs and laminin 5γ2, which could be cleaved into γ2 and γ2x by activated MMP2. These fragments promoted VM formation in 3D cultures . TGF-β iFurther, nude mice transplantation experiment in vivo found that knockdown of BUD13, CDK12, and overexpression of MBNL1 alone inhibited the growth of transplanted tumors, prolonged the survival time of nude mice, and inhibited the VM in transplanted tumors, and the effect of three coregulation was the most significant. These findings indicated that knockdown of BUD13 and CDK12 combined with overexpression of MBNL1 had potential clinical value.In conclusion, the study revealed the expression and interaction of BUD13, CDK12, and MBNL1 in GBM tissues and cells for the first time. Knockdown of BUD13, CDK12, and overexpression of MBNL1 significantly inhibited proliferation, migration, invasion, and tube formation of GBM cells. METTL3 enhanced the stability of BUD13 mRNA and upregulated its expression through m6A methylation. BUD13 enhanced the stability of CDK12 mRNA and upregulated its expression. CDK12 phosphorylated MBNL1, thereby regulating the proliferation, migration, invasion, and tube formation of GBM. The research provided not only a theoretical and experimental basis for the malignant progression of GBM, but also a new reference for molecular targeted therapy of GBM.Supplementary Materials and MethodsSupplementary TableOriginal western blotschecklistFigure S1Figure S2Figure S3Figure S4Figure S5Figure S6Supplementary Information


Cooperative activation of CaV1.2 channels within these clusters causes a local increase in intracellular Ca2+ that activates the juxtaposed ryanodine receptors. A salient feature of healthy cardiac function is the reliable and precise beat-to-beat pacemaking and amplitude of Ca2+ transients during EC coupling. In this review, we discuss recent discoveries suggesting that the exquisite reproducibility of this system emerges, paradoxically, from high variability at subcellular, cellular, and network levels. This variability is attributable to stochastic fluctuations in ion channel trafficking, clustering, and gating, as well as dyadic structure, which increase intracellular Ca2+ variance during EC coupling. Although the effects of these large, local fluctuations in function and organization are sometimes negligible at the macroscopic level owing to spatial–temporal summation within and across cells in the tissue, recent work suggests that the “noisiness” of these intracellular Ca2+ events may either enhance or counterintuitively reduce variability in a context-dependent manner. Indeed, these noisy events may represent distinct regulatory features in the tuning of cardiac contractility. Collectively, these observations support the importance of incorporating experimentally determined values of Ca2+ variance in all EC coupling models. The high reproducibility of cardiac contraction is a paradoxical outcome of high Ca2+ signaling variability at subcellular, cellular, and network levels caused by stochastic fluctuations in multiple processes in time and space. This underlying stochasticity, which counterintuitively manifests as reliable, consistent Ca2+ transients during EC coupling, also allows for rapid changes in cardiac rhythmicity and contractility in health and disease.Each heartbeat begins with the generation of an action potential in pacemaking cells in the sinoatrial node. This signal triggers contraction of cardiac muscle through a process termed excitation–contraction (EC) coupling. EC coupling is initiated in dyadic structures of cardiac myocytes, where ryanodine receptors in the junctional sarcoplasmic reticulum come into close apposition with clusters of Ca The cardiac cycle beings with production of an action potential by pacemaking cells in the sinoatrial (SA) node. These action potentials, which exhibit a characteristic waveform reflecting the rapid, transient depolarization of the membrane and subsequent repolarization and afterhyperpolarization, are generated by clusters of pacemaker cells and propagate via gap junctions to surrounding atrial myocytes . The atr2+ (CaV1.2) channels in the sarcolemma and ryanodine receptors (RYRs) expressed in the juxtaposed junctional sarcoplasmic reticulum (jSR). In ventricular myocytes, the majority of couplons are formed along invaginations of the sarcolemma termed transverse tubules (T-tubules). In atrial myocytes, which lack a highly developed T-tubular system, couplons are primarily formed in the surface sarcolemma.The process that links an action potential to cardiac muscle contraction is called excitation–contraction (EC) coupling, and the functional unit of EC coupling is called the “couplon” . A couplV1.2 channels in the sarcolemma of atrial and ventricular myocytes. This allows a small amount of Ca2+ to enter the cytosolic nanodomain that separates the sarcolemma and jSR, increasing the Ca2+ concentration in this intracellular compartment ([Ca2+]i). This increase in [Ca2+]i is sufficient to activate RYRs in the jSR via a Ca2+-induced Ca2+-release (CICR) mechanism  that initiates myocardial contraction  but also reflect stochastic behavior—that is, “noise”—of the couplon itself.The activation of couplons at sarcolemmal–jSR dyadic structures reflects Carocesses , 2013. I2+ and electrical signals resulting from the opening of a single channel often exhibit relatively large event-to-event fluctuations due to variations in the open time of the channel. For an ion channel with a single open state, the probability of closing per unit time is constant; thus, the channel’s stochastic lifetimes are exponentially distributed. Accordingly, the SD of their lifetimes is equal to the mean, resulting in a coefficient of variation (COV = SD/mean) = 1.Ca2+]i, reflecting the combined effects of CaV1.2-mediated Ca2+ influx and synchronous RYR-mediated SR Ca2+ release, is ∼0.12 in adult mouse ventricular myocytes and ∼0.18 in neonatal rat ventricular myocytes . The binomial distribution and related Poisson, exponential, and Gaussian distributions, which provide a theoretical framework for statistical analyses of stochastic processes, are defined below with representative examples of their applications.P is the probability of success, N is the number of successes, and q is the probability of failure . The binomial distribution has been used to analyze unitary events such as single-channel currents  produced by Ca2+ influx via single transient receptor potential vanilloid 4 (TRPV4) channels in endothelial cells  and variance are equal. Indeed, the Poisson distribution is a limiting case of a binomial distribution where the number of trials is very large  and the probability of success is small . These conditions are met by evoked Ca2+ sparks in ventricular myocytes. V1.2 channel–activated Ca2+ sparks occur randomly throughout ventricular myocytes. They found that the probability density function  of evoked Ca2+ sparks was generated by quantifying the number of occurrences  probability distribution of normally distributed stochastic processes. Indeed, the Gaussian distribution can be considered as another special case of the binomial, when the number of trials is sufficiently large. For this reason, the Gaussian distribution applies to a large number of variables.2+ sparklets—local elevations in [Ca2+]i produced by the opening of single CaV1.2 channels or a small cluster of channels—in cardiac and smooth muscle cells. The analysis begins by generating histograms of Ca2+ sparklet event amplitudes from [Ca2+]i records. Their Ca2+ sparklet amplitude histograms showed multiple peaks that could be fitted to the following multicomponent Gaussian function:a and b are constants, and Δ[Ca2+]i and q are the change in intracellular Ca2+ concentration and quantal unit of Ca2+ influx, respectively. This analysis allowed 2+ sparklet amplitude and conclude that large-amplitude events resulted from the synchronous activation of quantal Ca2+ sparklet events.Two relevant implementations of this analysis, one by 2+ influx and SR Ca2+ release, but cannot be definitively predicted. Instead, the state of the system may fluctuate around a mean value determined by the initial conditions, unless the system is multistable. This fluctuation, or deviation from the target state, is the result of the underlying stochasticity of all the processes involved.The behavior of a dynamic biological system such as a cardiac myocyte is subject to both intrinsic and extrinsic noise . Accordingly, under steady-state conditions, pacemaking and EC coupling are stochastic processes, and their properties may be represented statistically as probability distributions that are weighted toward achieving a mean level of action potential periodicity as well as Caf). An example of 1/f noise is fluctuation of the heartbeat period  would be low at low noise levels . ConsistFuture research should also determine the relationship between performance  and noise  and how activation of sympathetic and parasympathetic signaling affect the response. Two potential outcomes of these stochastic resonance experiments are illustrated in An additional, critically important experiment would involve elimination or attenuation of electrical signaling of the inferior section of the node (which is largely populated by cells that produce stochastic subthreshold voltage fluctuations) while recording action potential firing from the whole tissue. The stochastic resonance model predicts that doing so would lead to decreased pacemaking periodicity .Regardless of whether SA node pacemaking activity depends on entrainment or stochastic resonance, testing these models would provide important insights into mechanisms that lead to normal sinus rhythm.2+]i at this level and sufficient throughput to gather the volume of data needed for these noise analyses. Using these approaches, 2+]i transients (1-Hz stimulation rate) in adult mouse ventricular myocytes and neonatal rat ventricular myocytes (≤3 d old) and determined the time course of beat-to-beat variations in [Ca2+]i  during EC coupling in rabbit ventricular myocytes (2.5-Hz stimulation rate), implemented for this review  inhibitor thapsigargin, it was possible to determine the time course of [Ca2+]i variance during the action potential and the contribution of SR Ca2+ release to it  during an action potential. The variance was 3.9 ± 0.3 and 11.3 ± 2.3 nM2 at 100 and 600 nM free Ca2+, respectively. This shows that, at least in our system, the nonbiological component  of the variance at the higher [Ca2+]i levels and fluorescence intensities in the cell-free system was ∼27-fold smaller than the variance associated with the peak of the [Ca2+]i transient of a rabbit ventricular myocyte  during the action potential. Thus, although nonbiological noise increases as fluorescence intensities increase, under our experimental conditions, it is a relatively small fraction of the measured [Ca2+]i variance in a cell.An important consideration in this analysis is that an increase in the emission light intensity could translate into an increase in the shot noise associated with the photomultiplier tube (PMT) detector of the confocal microscope used in these experiments. To determine the magnitude of these fluctuations, we measured the variance of the fluorescence signals from two solutions with identical fluo-4 concentrations (100 μM) but with 100 or 600 nM free Ca2+ release from the SR plays a less prominent role in the [Ca2+]i transient of rat neonatal myocytes (∼60–70%) compared with rat adult myocytes  and Ca2+ influx (σ2influx). Thus, in principle, σ2transient and σ2influx could be experimentally determined from [Ca2+]i transients before and after application of thapsigargin such that σ2SR = σ2transient − σ2influx, as was done by 2+ release and Ca2+ influx are independent, so σ2influx must not be altered by elimination of SR Ca2+ release. Clearly, this is not the case: all the proteins involved in Ca2+ influx in these cells  are modulated by Ca2+. A key question is how much of this Ca2+ variance comes from the SR versus Ca2+ entry.i variance seen in rat neonatal myocytes upon elimination of SR Ca2+ release should not be considered a quantitatively accurate separation of σ2SR and σ2influx. Rather, the numbers suggest that, to a first approximation, SR Ca2+ release is likely a major driver of [Ca2+]i variance during EC coupling in rat neonatal myocytes.The functional consequences of SR Canificant . Thus, aV1.2 channel gating and SR Ca2+ release are not independent, as multiple studies have reported that SR Ca2+ release contributes to Ca2+-dependent inactivation of CaV1.2 currents in rat  and σ2SR ? Does activation of β-adrenergic receptor (βAR) signaling alter σ2transient, σ2SR, and/or σ2influx? Is σ2transient increased during hypertrophy and heart failure? Finally, what are the mechanisms leading to different [Ca2+]i noise values across species and developmental stages?These studies raise a series of interesting issues and challenges regarding the analysis of noise in cardiac EC coupling. First, what are the precise mechanisms that make SR Ca2+]i noise during EC coupling in ventricular myocytes under a wide range of physiological and pathological conditions. Importantly, these data will be critical for the generation of realistic mathematical models of EC coupling, because, as noted above, most models do not incorporate experimentally determined levels of biological noise.The development of new experimental and in silico methodologies is needed for accurate, quantitative determination of biological (as opposed to instrument or environment) sources of i transient fluctuations were larger in the simulations with fewer couplons  than in those with a larger number of couplons .To illustrate this point quantitatively, we performed simulations using a previously published model of cardiac EC coupling in which we varied the number of SR Case units . Fig. 8,2+]i transients are proportional to 1/√N, where N is the number of Ca2+-release units  than the experimentally determined mean peak [Ca2+]i variance during the action potential in such myocytes . Although instrument and environment sources of noise contribute to experimental [Ca2+]i variance, they are not likely the main drivers of the difference between experimental and model levels of noise. There are two reasons for this. Instrument and environment noise should be constant throughout the duration of the experiment, whereas diastolic [Ca2+]i variance is low  and increases during the action potential. Similarly, instrument and environment noise should be insensitive to thapsigargin, yet thapsigargin decreased [Ca2+]i variance nearly 10-fold during the rabbit action potential. The large discrepancy between in silico versus experimental noise raises the possibility that biologically driven [Ca2+]i noise is underestimated in computational models of EC coupling. It is therefore imperative that future models of EC models incorporate realistic levels of Ca2+ variance and examine its physiological implications, as done by the labs of Rodriguez, Clancy, and Smith  and interindividual variations in action potential waveform that manifest as dispersion in different sections of the electrocardiogram . This is2+]i instability during pathology. For example, 2+ transients are a result of T-tubule disorganization, which, in turn, is associated with a decrease in JPH2 expression  beat-to-beat variations in the amplitude of [Ca2+]i transients—are common sources of arrhythmogenic behavior. Early afterdepolarizations (EADs), which occur when inward currents exceed outward currents during the plateau phase of the action potential, can be caused by reactivation of CaV1.2 channels , as well as the strength of cell-to-cell coupling, can also be arrhythmogenic. For example, 2+ dynamics , electronic noise , and even analytically introduced noise . To accurately quantify biological noise, one must therefore eliminate, minimize, or account for these external sources of noise. Although a detailed analysis of nonbiological sources of noise and how they are treated is beyond the scope of this review, we include a brief discussion of this topic so that readers are aware of it.To this point, we have discussed how stochastic events contribute to variations in CaAny imaging recording is susceptible to contamination with photons produced by environmental light that enters the optical path and reaches the system’s photon detectors. Eliminating this noise simply involves turning off unnecessary lighting, using appropriate filters, and/or physically shielding the microscope from these sources of photons.2+ indicator is critical for any imaging experiment and requires consideration of multiple factors, including brightness, dynamic range, and apparent dissociation constant. Converting fluorescence values or ratios to concentration units is also important, not just for mechanistic reasons but also to accommodate the nonlinear relationship between Ca2+ concentration and fluorescence. In cases in which Ca2+ levels reach the flatter section of the sigmoidal Ca2+–fluorescence relationship, where small changes in fluorescence can translate to large changes in Ca2+ and hence greater [Ca2+]i variance, this conversion process is an often unappreciated source of variation that contributes Ca2+ noise. Furthermore, the magnitude of the noise recorded with a detector such as a PMT  increases with light intensity, adding noise to any recorded [Ca2+]i. While this source of noise could be a minor contributor to the overall level of [Ca2+]i variance in images, it must be taken into consideration during analysis.Careful selection of the fluorescent CaFluorescence microscopes and patch-clamp amplifiers are susceptible to other types of electronic noise produced by its components, such as shot noise, dielectric noise, and operational amplifier noise. Electrical noise from external sources can be almost completely eliminated in a well-designed system but can become the dominant source of noise if proper precautions are not taken. The most familiar form of electrical interference is line-frequency pickup (50 or 60 Hz and harmonics) from power supplies and fluorescent lights, among other sources. Well-designed instruments will not introduce significant amounts of interference from their internal power supplies. However, a typical laboratory environment is full of potential sources of interference from sources external to the electronic instrumentation involved in a particular measurement. In addition to line-frequency pickup, other potential sources of interference include nearby motors, elevators, radio and television stations, and video monitors of the researchers’ computers, which produce an annoying timing signal at frequencies of ≥16 kHz. High-impedance measurements, such as patch-clamp and intracellular microelectrode recordings, are particularly sensitive to such external interference. In most cases, such noise sources can be controlled by careful grounding, shielding, and filtering.2+]i transient that peaks 50 ms after activation, the cell needs to be imaged with a minimum time resolution of 22 ms , or 45 frames or linescans per second, to accurately capture the amplitude of the transient. Meeting Nyquist’s criteria is also important in capturing images with the highest spatial resolution possible with a given microscope configuration, keeping in mind that each pixel is at least 2.3 times smaller than the calculated resolution of the objective. Failure to meet Nyquist’s criteria leads to low spatial and temporal resolution due to undersampling and hence filtering of the signal, which could lead to distortion of the signal’s waveform, including its variance .A final consideration is embodied by Nyquist’s theorem, also known as the sampling theorem, which states that a periodic signal must be sampled at more than twice the highest frequency component of the signal. In imaging, the recommended sampling rate is at least 2.3 times the highest frequency. For example, for a ventricular myocyte with a i transient without restrictions in the action potential. Notably, the model suggests the existence of a feedback mechanism that sets the balance between Ca2+ and other conductances to determine the [Ca2+]i transient.The ability of highly heterogeneous cellular networks to generate highly periodic signals and respond to physiological stimuli is not unique to the heart, as exemplified by seminal work by Dr. Eve Marder and her colleagues on the mechanisms governing excitability in the crustacean stomatogastric ganglion  and genetic disease groups linked to inherited arrhythmia could then be used to test the conditions under which stochastic resonance fails.Computational modeling and simulation might also be extended to allow for quantitative investigation of the electrophysiological and Ca2+ signaling may offer a selective advantage by allowing for rapid change and adaptation to changing physiological needs. For instance, relatively fast trafficking events that insert and remove CaV1.2 channels into the sarcolemma of ventricular myocytes might decrease the channels’ membrane dwell time but could also facilitate the rapid delivery  of CaV1.2 channels during βAR signaling. The argument here is that if trafficking were a very slow process, it could take a long time to tune cardiac performance through changes in channel numbers. As shown by Dixon and colleagues (In an evolutionary context, the variance associated with action potential waveform, subthreshold voltage fluctuations, and Calleagues , this isAs highlighted above, this stochasticity, while large at the subcellular level, is usually negligible at the whole-cell level because of spatial-temporal summation of individual events within cells. That said, optimal levels of noise can, at least in principle, increase pacemaking at the multicellular level and enhance EC coupling performance at the cellular level.2+ signaling at these two organizational levels is not fully realized. Achieving this will require the development of a combination of experimental and in silico methodologies for accurately determining the amplitude and sources of [Ca2+]i variance during the action potential. These values can then be fed into mathematical models to generate more realistic simulations of the action potential and [Ca2+]i.Although there is a growing body of work demonstrating the massively dynamic nature of cellular processes in cardiac cells and regions, the significance of random fluctuations in electrical and CaAdditional questions that should be addressed using these experimental and in silico approaches in future studies include the following: What is the noise–performance relationship of the SA node and ventricular myocytes? Does the magnitude and optimal level of noise vary throughout the heart? How do regional variations in action potential waveform and βAR signaling contribute to noise heterogeneity? Is that changed by pathology, and if so, how? And how does loss of T-tubules and dyads alter the reproducibility of EC coupling in living myocytes? Addressing these questions will provide novel insights into the mechanisms that regulate EC coupling but will also require a shift in conceptual and experimental paradigms.


Background: It has been demonstrated that scutellarin, a natural flavone compound from Scutellaria lateriflora and Scutellaria barbata, exerts selective cytotoxicity against a range of cancer cells. However, the underlining mechanism of scutellarin on acute myeloid leukemia (AML) remains elusive.Methods: In this study, the combination of network pharmacology and experimental verification was performed to identify the pharmacological mechanisms of scutellarin for AML therapy. The public databases, such as PharmMapper, UniProt, OMIM, GeneCards, DrugBank and PharmGkb database, were used to sceen the potential targets of scutellarin and AML. The protein-protein interaction (PPI), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted to uncover the mechanism of scutellarin in the treatment of AML. Finally, the network pharmacological results were further confirmed by in vitro and in vivo experiments.Results: First and foremost, we totally obtained 289 target genes for scutellarin and 10998 disease targets for AML. 253 overlapping genes were preliminarily considered the potential targets of scutellarin for AML treatment. The results of PPI network analysis, GO analysis and KEGG pathway enrichment demonstrated that the anti-AML effect of scutellarin may focused on MAPK signaling pathway. Furthermore, the cytologic tests suggested that scutellarin can inhibit AML cells proliferation through the mediation of JNK/Caspase-3 pathway. Meanwhile, pretreatment with the JNK inhibitor SP600125 rescued scutellarin-induced apoptosis. Similarly, scutellarin obviously suppressed subcutaneous xenograft growth in nude mice via regulating the JNK/Caspase-3 signaling pathway.Conclusion: In this study, we integrated network pharmacology-based prediction and experimental validation and revealed the importance of the JNK pathway in scutellarin-mediated AML treatment. Acute myeloid leukemia (AML), a typical blood cancer, is featured by changes in hematopoietic cells, such as blocked differentiation, increased proliferation, or accumulation of blasts . As the The ″3 + 7″ regimen, 3 days of daunorubicin followed by 7 days of cytarabine, is the standard treatment for AML. The overall survival rate in patients with AML under this standard regimen is only 40%, and the 5-years survival rate (5y-SR) of patients (≥60 years) is even lower, less than 10–15% M.. In the Scutellaria barbata and Scutellaria lateriflora, herbs that have a long history in TCM  has been widely used in clinical for thousands of years and is one of the most abundant resources for the discovery of anticancer drugs. As is well known, TCM treated diseases in a holistic concept and possessed the characteristics of multi-target and multi-approach, which coincides with the prevention and treatment strategy of cancer . For a ly in TCM . Researcy in TCM . In the y in TCM . Variousy in TCM . It has y in TCM , and viay in TCM . Scutelly in TCM . HoweverAccompanying with the quick development of system biology and bioinformatics, network pharmacology provides a new method for revealing the complex mechanism of TCM and the interrelationships among drugs, targets and diseases . In linein vitro and in vivo experimental validation. The workflow is shown in In our study, network pharmacology was employed to elucidate the molecular mechanisms of scutellarin for AML therapy, which was confirmed by Human AML cell lines  were obtained from the US Model Culture Collection . THP-1 human AML cells were purchased from the Chinese Academy of Sciences Cell Bank. THP-1, HL-60, KG-1 cells were cultured in RPMI-1640 medium (Gibco) supplemented with 10% fetal bovine serum , 1% penicillin (pen) and streptomycin (strep).Scutellarin (CAS#27740-01-8) was provided by Weiqi Biological Technology Co. Ltd. Breviscapine was provided by Yunnan Plant Pharmaceutical Co. Ltd. . Z-VAD (OMe)-FMK , SP600125 , CCK-8 kit , Annexin V-FITC Apoptosis Detection Kit I .Western blot immunoassay was performed with antibodies against p-JNK(Cat.#9251S), JNK (Cat.#9252S), cleaved caspase-3(Cat.#9664), cleaved PARP (Cat.#5625), anti-rabbit secondary antibody (Cat.#7074) and anti-mouse secondary antibody (Cat.#7076). The above antibodies were all provided by Cell Signaling Technology. Αnti-β-actin (Cat.#A5441) was provided by Sigma Aldrich.4 cells/well), THP-1 (1.5×104 cells/well) and KG-1 (1.5×104 cells/well) cells were inoculated in 96-well plates at a volume of 90 μL/well. Then 10 μl medium containing various doses of scutellarin was added and incubated for 72 h at 37°C. Next, 5 μl/well CCK-8 solution was added and incubated for 4 h at 37°C. The SpectraMax 190 microplate reader (Molecular Devices) was used to measure the absorbency at 450 nm. The relative cell growth rate was calculated with the following equation: Relative Growth (%) = [OD (treated) -OD (blank)]/[OD (control)-OD (blank)] ×100%. The IC50 of scutellarin was counted by Graph Pad Prism 8.0 software.Cell proliferation assay was assessed with the CCK-8 kit  on leukemia cell lines. HL-60 (2×10https://pubchem.ncbi.nlm.nih.gov/) was applied to obtained chemical structure of scutellarin. The PharmMapper database (http://www.lilab-ecust.cn/pharmmapper/) was utilized to generate targets with high scores. Then, the protein target names were converted to corresponding gene symbols in UniProt database (http://www.uniprot.org/). The disease targets of AML were retrieved from OMIM, GeneCards, DrugBank and PharmGkb databases. The targets associated with AMLwere obtained by merging the targets of the four databases. Finally, the predicted targets of scutellarin against AML were collected by intersection of the drug and disease targets.The PubChem database (http://www.cytoscape.org/).Based on the above analyses, the potential target genes of scutellarin were matched with the disease targets of AML to obtain the common targets. The network diagram between the scutellarin and AML-related targets was established from Cytoscape 3.8.0 (https://string-db.org/). Then, the interaction information was further visually analysed by Cytoscape3.8.0. In the PPI network, the key genes based on degree scores were screened using the Cytohubba plug-in.The PPI network was constructed by importing the targets of scutellarin against AML to the STRING database  language. Statistical significance was set at q value ≤ 0.05.5 cells/well and treated with scutellarin of indicated concentrations. Then cells were centrifuged in the tube after 24 h, rinsed twice with pre-cold PBS buffer, then incubated with 5 µl PI and 5 µl FITC Annexin V in 100 µl 1×Binding Buffer at room temperature in the dark for 20 min. Next, the cells were resuspended in 400 μl 1×Binding Buffer. Cellular apoptosis was assessed with Annexin V-FITC Apoptosis Detection Kit I (BD Bioscience). The cells were analyzed by a flow cytometer (BD Bioscience) after passing through a filter. The data were analyzed by FlowJo 7.6 software.HL-60 cells were seeded in 6-well plates at 5×10HL-60 cells were inoculated in 6-well plates and incubated in a medium containing scutellarin for indicated time point. Cell lysates were prepared with RIPA buffer supplemented with phosphatase inhibitor (Roche) and protease inhibitor cocktail (Roche). Protein concentrations were quantified by the BCA protein assay kit . Protein samples were heated at 95°C for 10 min following diluted in 5 x loading buffer. Then, 30 µg of each sample was fractionated on SDS-PAGE gels, transferred to PVDF membrane (Millipore) and incubated with different primary antibodies overnight at 4 C. Next, HRP-conjugated secondary antibodies (1:10000) were added at room temperature and the membranes were washed with 1×TBST. Proteins were visualized with SuperSignal West Pico Chemiluminescent Substrate or SuperSignal West Dura Extended Duration Substrate (Thermo Scientific).6 HL-60 cells were inoculated subcutaneously into both hind limbs of nude mice. we randomly divided the mice into two groups: vehicle , Breviscapine  when tumor volumes reached 100 mm3. The therapy lasted for 21 days and the tumor size and body weight were monitored every other day. The tumor volumes were calculated as All mice used in the animal experiments were 4-6 weeks old female nude mice. 5×102 × length)/2 (Volume = (widthength)/2 .All animal studies were approved by the Animal Ethical Committee of Affiliated Hospital of Southwest Medical University.t-test was selected to compare two groups. * represents p < 0.05, ** represents p < 0.01, *** represents p < 0.001, **** represents p < 0.0001.All data were shown as mean ± standard deviation (SD). And statistical analyses were performed through Graph Pad Prism 8.0 software. The data were analyzed by one-way analysis of variance (ANOVA) if comparing between more than two groups. The student’s A total of 289 potential targets for scutellarin were retrieved from the PharmMapper database by querying the structure of scutellarin . SimilarTo analyze the protein-protein interaction network, we interrogated the 253 target genes, with high confidence set to 0.7, in the STRING database . The corTo gain more insights into the cellular function of scutellarin in AML cells, we performed a GO term enrichment analysis of the 253 targets. A total of 2201 GO terms were obtained. Among them, there are 1935 entries for biological process (BP), 52 entries for cellular composition (CC), and 214 entries for molecular function (MF). The top-10 significantly enriched terms in each category are shown in in vitro and in vivo to confirm whether it contributed to the anti-AML effects of scutellarin by inducing apoptosis.KEGG pathway enrichment analysis of the 253 targets enriched in 150 signaling pathways. It verified AML-related pathways involving the PI3K-Akt signaling pathway (hsa04151), MAPK signaling pathway (hsa04010), and Ras signaling pathway (hsa04014) . The topTo investigate the cytotoxic effects of scutellarin, we treated AML cell lines for 72 h with various concentrations of scutellarin, and CCK-8 assay was employed to test the cell viability. As illutrated in To confirm the molecular mechanism of scutellarin on AML cells, we focused on HL-60 cells, which was more sensitive to scutellarin relative to other cell lines. The pro-apoptotic effect of scutellarin on HL-60 cells was determined by flow cytometric analysis. After 24 h treatment with scutellarin at indicated concentrations, the apoptosis in HL-60 cells obviously increased in a dose-dependent manner . FurtherAccording to network pharmacology analysis, the JNK/Caspase-3 pathway is the key signaling axis associated with the effect of scutellarin against AML. Thus, we analyzed the protein levels in this pathway by Western blotting. As shown in in vitro findings, p-JNK, cleaved Caspase-3 and cleaved PARP were significantly increased (Next, we explored whether scutellarin was still effective in the animal models of AML. HL-60 cells were inoculated subcutaneously into both hind limbs of nude mice, and breviscapine, containing scutellarin ≥90%, was administered at 60 mg/kg/d orally, which was corresponding to the maximum dose in humans per the guide for dose conversion between humans and mice . Breviscncreased .AML is a rapidly progressing hematopoietic malignancy whose global prevalence is rising. Although TCM has been proved to be a good choice for AML treatment, inferring the mechanism of action is challenging due to the complex chemical composition. The coincidence of the concept of network pharmacology and the theory of TCM makes the former suitable for the study of the mechanism of action of the latter .in vitro and in vivo experimental validation. First, we screened 289 potential targets for scutellarin from the PharmMapper database and retrieved 10998 AML-related genes from the OMIM, GeneCards, DrugBank, and PharmGkb databases. By merging targets of scutellarin with those of AML, a total of 253 overlapping genes were identified. Next, The results of PPI network analysis, GO and KEGG pathway analysis, revealed MAPK signaling pathway was critical for scutellarin-induced apoptosis. Thus, we chose the key proteins of MAPK and Caspase-3, a typical apoptosis-related protein for subsequent experimental validation.This study employed a network pharmacology-based approach to infer the underlying molecular mechanism of scutellarin for treating AML, and also performed via the transcriptional regulation or phosphorylation of the key mitochondrial pro- and anti-apoptotic proteins (The JNK signaling pathway regulates multiple cellular functions, such as apoptosis, survival, aging, cell proliferation, differentiation, and inflammation . It promproteins . Modulatproteins , especiaproteins .in vitro and in vivo experiments. We found that scutellarin significantly induces apoptosis in AML cells. Additionally, Z-VAD-FMK, a specific inhibitor of apoptosis, significantly attenuated the pro-apoptotic effects of scutellarin. Accordingly, well-known apoptosis markers (in vitro data, scutellarin suppressed subcutaneous xenograft growth in nude mice, and the change of the protein levels in the JNK/Caspase-3 pathway was also recapitulated.To verify the analysis of network pharmacology, we did  markers , such asThis study integrated network pharmacology-based prediction and experimental validation to uncover the importance of the JNK pathway in scutellarin-mediated AML treatment.