In an exact-repetition condition, identical patterns were repeated; in two distorted-repetition conditions, one randomly chosen segment in each sound pattern was replaced either by white noise or by a wrong pitch. In a roving-standard paradigm, sound patterns were repeated 1–12 times (standards) in a row before a new pattern (deviant) occurred. The participants were not informed about the roving rule and had to detect rarely occurring loudness changes. Behavioral detectability of pattern changes was assessed in a subsequent behavioral task. Pattern changes (standard vs. deviant) elicited mismatch negativity (MMN) and P3a, and were behaviorally detected above the chance level in all conditions, suggesting that the auditory system extracts regularities despite distortions in the acoustic input. However, MMN and P3a amplitude were decreased by distortions. At the level of MMN, both types of distortions caused similar impairments, suggesting that auditory regularity extraction is largely determined by the stimulus statistics of matching information. At the level of P3a, wrong-pitch distortions caused larger decreases than white-noise distortions. Wrong-pitch distortions likely prevented the engagement of restoration mechanisms and the segregation of disrupted from true pattern segments, causing stronger informational interference with the relevant pattern information.The auditory system is able to recognize auditory objects and is thought to form predictive models of them even though the acoustic information arriving at our ears is often imperfect, intermixed, or distorted. We investigated implicit regularity extraction for acoustically intact versus disrupted six-tone sound patterns  Acoustic information, which arrives at ours ears and informs us about objects in the outer world, is often imperfect. Parts of the relevant object information might be obscured by extraneous noise from concurrent auditory sources, for instance, from some sudden, interfering background sounds like a honking car or a barking dog. In other instances, parts of the relevant auditory objects can be missing. Furthermore, particularly in the domains of speech and music, mistakes in production might lead to imperfect recurrences of the same object, for instance, when a familiar melody is played with a missing or a wrong note or a word is uttered with an incorrect phoneme. Such occurrences can intermix with or distort the acoustic input we are currently paying attention to, and might impede its intelligibility.Our ability to deal with such distortions and to interpret the acoustic environment, even if it is degraded to a certain degree, is a remarkable asset. One should note that, on the one hand, our auditory system is able to detect even slight variations in the acoustic input. Previous studies found that the auditory system is sensitive to very subtle acoustic changes , particularly if the respective varying sound event occurs after a row of invariant repetitions . On the Especially in speech and music research, perceptual restoration and filling-in processes are attributed to top-down influences . When phElectrophysiological markers like the mismatch negativity (MMN) can serve as an index for such implicit and automatic compensatory mechanisms of early processing stages . The MMNThese findings also align with studies on auditory object segregation. For example, The MMN component can be followed by a P3a component distributed over fronto-central scalp regions. Typically, P3a is interpreted as signaling an involuntary attentional switch from a primary task to the deviant stimulus . P3a is In the current study, we investigated the early phase of implicit auditory pattern learning. The presented sounds were attended; however, the pattern regularity rule was irrelevant for the task at hand. Thus, learning occurred incidentally rather than intentionally . During However, given that a lower quantity of unambiguous information guides the initial learning process, one might expect poorer pattern representation from distorted standard sounds as indicated by decreased MMN and P3a amplitude and possible latency delays. Given that an equal portion (five out of six tones) was unambiguously informative about the identity of the standard pattern in both distortion conditions, one might expect to find similar impairments in the two distortion conditions. Nevertheless, there are certainly qualitative differences between white noise and wrong pitch distortions. Noise contains the frequencies of the “true” pattern segment and can involve filling-in or restoration processes, once an internal representation of the standard pattern has been formed; whereas wrong pitch distortions might interfere with the formation of a pattern representation. Therefore, differential effects on MMN and/or P3a could be expected in the two distortion conditions, particularly with stronger impairments in the wrong-pitch condition. If that is the case, one can conclude that potentially different mechanisms rule the formation of pattern identity representations in the context of white noise or wrong pitch distortions. This would also be compatible with masking studies, showing stronger degrading effects on speech intelligibility when it is masked by similar stimulus material, such as irrelevant speech , than when it is masked by noise (as in the case of energetic masking) .Furthermore, if we observed such distortion-specific effects already at the level of MMN, this would argue in favor of an impact of our manipulation on relatively early merely perceptual and automatic processing levels. In contrast, if they were confined to the P3a level, this would indicate that distortion processing occurs only at a later stage in the course of more context-dependent novelty evaluation and automatic orienting of attention.vice versa for the P3a) as a function of the number of previous standards in a train  preceding a deviant was varied  in a roving-standard paradigm . Accordi a train . We willM = 6.6 years, SD = 4.2 years).The experimental protocol was approved by the Ethical Committee of the University of Leipzig and was in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki). The participants gave written informed consent before experimental sessions. All the subjects in the experiment participated for credit points or monetary compensation (€8 per hour). Of the 19 healthy subjects  that participated in this research, all reported normal hearing and 17 out of 19 participants were right-handed. All of them were Leipzig University students, and 84% reported to have played a musical instrument for some time . In each session, six blocks of each condition were presented in random order. In the exact-repetition condition, patterns were repeated 100% identically within a train. In the white-noise condition, during each presentation of a melodic pattern, one randomly chosen segment out of the six was replaced by a 50-ms snippet of white noise. In the wrong-pitch condition, the pitch of one segment in each pattern was changed to a randomly chosen new pitch, while keeping all other characteristics of that segment  unchanged. The randomly chosen pitch for the new segment could keep the contour of the pattern intact, or violate it with equal probability. Each position of a pattern (1–6) could be affected by this manipulation with equal probability in the two distortion conditions—randomly selected from trial to trial. The intensity of the white noise segment was root-mean-square equalized to the rest of the pattern. via the melody part of musical ear test (MET) of At the beginning of the first session, ability of the participants to tell whether two melodic phrases are the same or different was measured During the experimental sessions, the participants were seated in an electrically and acoustically shielded chamber in our laboratory at the Institute of Psychology of Leipzig University. To minimize eye movements, the participants fixated a cross on a computer screen placed behind a window outside the chamber 130 cm from the eyes of the participants. Auditory stimuli were presented binaurally over headphones (Sennheiser HD 25) at an intensity level of approximately 78 dB SPL. The participants were not informed about the roving rule. While listening to the presented sound patterns, the subjects performed a loudness change detection task in order to ensure their attention on the auditory stimulation. Occasionally, the sound patterns were presented with a higher volume  or with a lower volume . The participants pressed the left button of a response pad as soon as they detected a sound pattern of lower volume and the right button of the response pad as soon as they detected a sound pattern of higher volume. The targets were distributed randomly over each block with the restriction of at least two non-targets in between. After finishing a block, the participants received feedback on their performance . After each block, the subjects had a short break, allowing for movements.Additionally, at the end of the second experimental session, the participants performed an active pattern change detection task to measure behavioral detectability of pattern changes. In these active blocks, the SOA was prolonged to 1,100 ms for the participants to have sufficient time for solving the task. They were instructed to detect the onset of a new train while ignoring segment distortions. They pressed a button of the response pad as soon as they detected a change to a new sound pattern. After short training, each subject performed one block of each distortion condition, consisting of 200 trials each . The order of conditions was counterbalanced over the participants.1.Electroencephalography data were collected continuously from 64 Ag/AgCl active electrodes. The electrodes were positioned according to the international 10–20 system in a nylon cap. The vertical and horizontal electrooculograms (EOG) were measured with external electrodes placed above and below the right eye and at the outer canthi of both eyes, respectively. As possible offline references, additional electrodes were placed on the tip of the nose and over each mastoid. All electrode signals were (DC) amplified and continuously sampled with a rate of 512 Hz  by BioSemi Active-Two amplifiers. No high-pass filter was applied online. The BioSemi system uses the common mode sense (CMS) and the driven right leg (DRL) electrode—placed at different sites at the back of the head—to reference the recording to the CMS–DRL ground while minimizing the effect of external noise sourcesOffline, EEG data were re-referenced to the average signal of the two mastoids  and filtp < 0.05). About 1,000 permutations were run for each test, and dependent samples t-tests quantified the effect. These analyses and the creation of topographical scalp plots were run in FieldTrip  and for standard sounds (the last corresponding pattern of the preceding train) in each condition. Difference waves were computed by subtracting the standard from the deviant ERPs. To compare ERP effects, in general, between the three conditions, we pooled the deviant and standard ERPs of train lengths 3, 6, and 12 in order to extract a general difference waveform in each condition . Train lengths 1 and 2 were not included in the general analysis, because former studies showed that perceptual regularity extraction requires at least two repetitions  of the standard before unexpected complex sound patterns elicit an MMN . With noieldTrip .For the statistical assessment, amplitude measures were derived from the individual ERPs as the mean signal amplitude in the component time interval for combined conditions . An estimate of relative slope of each component at the latency for which 75% of the peak amplitude was reached was determined, using the jackknife approach .post hoc logarithmic trend analyses were run for difference waveforms, deviant and standard ERPs, separately. The standardized regression coefficient r and its 95% confidence interval (lower and upper bounds) were reported. All ANOVAs generalized eta squared (η2) served as an estimate of effect size (dfs were reported). All parametric statistical analyses and the creation of figures were run with RStudio (RStudio. PBC. Version 1.3.1073).The MMN and P3a amplitude were separately subjected to a repeated measures analysis of variance (ANOVA) with the factors condition , stimulus type , and train length  as within-subject factors. For the MMN, maximal peak deflections were distributed over different electrodes in central-parietal regions . Following a data-driven approach, we focused our MMN analyses on this region with maximal amplitude, and we discuss this rather unexpected topography later (see Discussion). To examine possible topography differences, the factor electrode  was added to the ANOVA. P3a measures were taken from electrode FCz because amplitude deflected maximally at this electrode in all conditions. Three condition-wise repeated measures ANOVAs, with the factors stimulus type  and train length , and two stimulus-type-wise repeated measures ANOVAs, with the factors condition  and train length , were run to explore the three-way interactions for MMN and P3a. To investigate in more detail whether and how amplitude of MMN and P3a, as well as the contribution of deviant and standard stimuli to amplitude of both components, changed systematically as a function of train length; ect size , and thed′ according to d′ was adjusted for extreme hit or false alarm rates to avoid infinite d′ values by adding 0.5 to all response counts  and train length  and via logarithmic trend analysis to investigate behavioral effects condition-wise and as a function of the number of previous standard repetitions.The active pattern change detection task at the end of the second EEG session was analyzed in terms of the signal detection theory, by extracting an index of sensitivity d′  and corrd′ . ReactioSD = 12%, 17/19 subjects scored above chance). In the loudness change detection task, which participants performed during the EEG recordings, the targets were discriminated with high accuracy. In the first session, averaged sensitivity over the participants (N = 19) was d′ = 3.71 (SD = 0.58) in the exact-repetition condition, d′ = 3.45 (SD = 0.64) in the white-noise condition, and d′ = 3.60 (SD = 0.70) in the wrong-pitch condition. In the second session, averaged sensitivity over the participants (N = 19) was d′ = 3.92 (SD = 0.52) in the exact-repetition condition, d′ = 3.80 (SD = 0.51) in the white-noise condition, and d′ = 3.92 (SD = 0.58) in the wrong-pitch condition. A repeated measures ANOVA with the factors session  and condition  revealed the main effect of session  but no significant effect of condition . No interaction between condition and sessions was found .In the MET, the participants scored, on average, 72% correct (range: 42–88% M = 634 ms (SD = 50 ms) in the exact-repetition condition, M = 664 ms (SD = 53 ms) in the white-noise condition, and M = 631 ms (SD = 49 ms) in the wrong-pitch condition. In the second session, reaction times for correctly detected target sounds were M = 609 ms (SD = 59 ms) in the exact-repetition condition, M = 628 ms (SD = 58 ms) in the white-noise condition, and M = 617 ms (SD = 54 ms) in the wrong-pitch condition. A two-way repeated measures ANOVA revealed a significant effect of condition  and of session . These main effects were not qualified by an additional interaction . Bonferroni-corrected two-tailed t-tests showed that, across the sessions, the reaction times in the white-noise condition differed significantly from the exact-repetition condition and the wrong-pitch condition .In the first session, reaction times for correctly detected target sounds were d′ = 3.12 (SD = 0.77)]. The sensitivity in the white-noise condition was d′ = 1.90 (SD = 0.47) and in the wrong-pitch condition d′ = 0.96 (SD = 0.28). Repeated measures ANOVA comparing the three conditions revealed a significant effect of condition . Bonferroni-corrected two-tailed t-tests showed significant differences between each condition pair .The participants showed a high sensitivity in the active pattern change detection task at the end of the EEG recordings in the exact-repetition condition . Bonferroni-corrected two-tailed t-tests revealed significant differences between exact vs. wn: t(18) = −3.94, p = 0.003, d = –1.86 and exact vs. wp: t(18) = –3.90, p < 0.003, d = 1.84. The difference in reaction times between the white noise and the wrong-pitch condition was not significant . The results of sensitivity and reaction time analysis can be seen in On average, reaction times for correctly detected target sounds were F = 103.98, p < 0.001, η2 = 0.48] and a significant main effect of train length . These main effects were qualified by an additional interaction . A highly significant logarithmic trend for the train length effect was revealed for each condition . Logarithmic regression analyses revealed a steeper increase of the hit rates with increasing train length in the white-noise condition than in the wrong-pitch condition, as confidence intervals did not overlap . A ceiling effect in the exact-repetition condition caused a non-optimal fit of the logarithmic regression and, therefore, an overlap with the confidence interval of the wrong-pitch condition, but not so with the white-noise condition . Mean hit rates are depicted in A repeated measures ANOVA on the hit rates, including the factors condition  and train length  showed a significant main effect of condition  nor any three-way interaction, including the factors electrode and condition  that would point to topographical differences between conditions.A four-way repeated measures ANOVA with the factors condition , stimulus type , train length  and electrode  for mean amplitudes in the MMN time window (200 to 300 ms after the stimulus onset) neither revealed a significant 4-way interaction  and significant two-way interactions . All those effects were qualified by a three-way interaction condition × stimulus type × train length: F = 2.54, p = 0.01, η2 = 0.03.Instead, the ANOVA revealed significant main effects  and the interaction stimulus type × train length  were significant in each condition. Particularly, the stimulus type × train length interactions resulted from increasingly negative MMN amplitudes of the deviant minus standard difference with train length  and whether this difference developed with increasing train length (interaction stimulus type × train length). Both the stimulus type effect  and train length effect  and a significant condition × train length interaction . However, for standards, the two-way ANOVA revealed only a train length effect . The condition effect  and the condition × train length interaction  were not significant. This indicates a similar development of the standard amplitudes with train length independently of condition and a different development of deviant amplitudes with train length in dependence of condition. Furthermore, we observed a significant logarithmic trend for the increase in deviant negativity with increasing train length in all three conditions   than in the white noise  and wrong-pitch condition   see .F = 6.47, p = 0.004, η2 = 0.01]. Furthermore, the main effect of stimulus type  and the main effect of train length  were found. The two-way interactions condition × stimulus type  and train length × stimulus type , as well as the interaction condition × train length , were significant. However, the main effects and the two-way interactions were qualified by an additional three-way interaction of the factors condition × stimulus type × train length: .A repeated measures ANOVA with the factors condition , stimulus type  and train length  for mean amplitudes in the P3a time window (400 to 500 ms after the stimulus onset) revealed a significant main effect of condition  and an interaction between stimulus type and train length  for each experimental condition. Particularly, the stimulus type × train length interactions resulted from increasing positive P3a amplitudes of the deviant minus standard difference with train length  and train length  revealed the main effect of stimulus type  and train length effect , which was qualified by a significant condition × train length interaction . For standards, the two-way ANOVA revealed a train length effect  and a condition effect . Also, the condition × train length interaction  was significant. Despite significant effects and interactions for deviants and standards, the effects differed between conditions in their strength as post hoc logarithmic trend analysis shows  = 47.90, p < 0.001, η2 = 0.73; wn: F = 75.38, p < 0.001, η2 = 0.81; wp: F = 6.51, p = 0.02, η2 = 0.27]. Logarithmic regression analyses revealed a steeper increase in positivity for deviants in the exact-repetition condition  compared with the wrong-pitch condition . Confidence intervals in the white-noise condition  overlapped with the increase in the exact-repetition condition and the wrong-pitch condition. For standards, we did not find a significant logarithmic trend in the wrong-pitch condition  in contrast to the exact-repetition condition  and the white-noise condition . The difference waves of the wrong-pitch condition also developed less steeply than in the exact-repetition condition and in the white-noise condition as confidence intervals did not overlap   see .In this study, we investigated the implicit memory formation for repeated auditory objects in situations in which single occurrences of the same object were subject to variability. More specifically, in three conditions, we studied how repetitions of unfamiliar short sound patterns lead to the formation of pattern-specific auditory sensory memory representations when single instances of pattern repetitions are identical (exact) or when they contain small distortions by replacing a segment of the pattern information either by white noise (wn) or by a wrong pitched segment (wp). The participants were not explicitly focusing on the pattern-repetition rule and, instead, performed the task of detecting occasionally occurring loudness changes in the auditory sequence. They performed this task with high accuracy and in the second session of the experiment with increased sensitivity and faster reaction times, likely due to familiarity and learning effects. Sensitivity of the participants to detect loudness changes was not affected by condition. However, the reaction times were significantly slower in the white-noise condition. It is possible the white-noise insertions were stronger distractors from the task, because these segments differed in sound quality from all the other segments of the sound pattern.As expected, the occurrence of a new sound pattern elicited an MMN and a subsequent P3a; both of which appeared with their typical time course according to previous studies, using an auditory oddball  and roviThe MMM implies that the regularity of repeated complex sound patterns was encoded into a predictive model, and that a change in the overall pattern was detected . This waYet MMN amplitude was larger in the condition without distortions compared with the conditions with distortions in the standard patterns. This suggests that the certainty about the repetition regularity must be higher in the exact-repetition condition, which results in more pronounced deviant-related negativity. In particular, MMN amplitudes increased as a function of preceding number of standards, following a logarithmic trend in all conditions, suggesting a fast buildup of pattern representations, particularly with the initial pattern repetitions see also . In geneWhile change detection was affected by whether distortions were introduced or not, it was not modulated by the type of distortion (noise or wrong pitch information). It seems to be mainly the number of intact segments within the sound patterns, guiding the fundamental process of extracting pattern identity representations as generative predictors under uncertainty, at least on this early processing stage.Subsequent to the MMN, a P3a component with typical fronto-central distribution was elicited, and systematic repetition-related modulations of amplitudes were found in all the conditions see also . P3a ampThe growth of P3a as a function of train length resulted from both an increasing positivity for deviant ERPs and an increasing negativity for standard ERPs in the respective P3a time window. For both stimulus types, the growth function was modulated by condition. At the level of the difference waveform, the steepest logarithmic increase in P3a amplitudes with train length was found in the exact-repetition condition. The logarithmic growth of P3a amplitudes in the wrong-pitch condition was distinctly less steep compared with the white noise and the exact-repetition condition. Thus, the growth of P3a activity with increasing number of preceding standards seems to be lowest in the condition with wrong pitch information. Consequently, pattern changes in the context of exact repetitions and white noise distortions might need fewer standard presentations to evaluate deviants as potential novels or targets and to trigger a call for attention of equal strength than pattern changes occurring among repetitions with wrong pitch distortions. Condition differences between P3a growths were partly due to the processing of the standard events. In the wrong-pitch condition, standard responses in the P3a time window did not show a logarithmic repetition-related modulation as opposed to the exact repetition and the white-noise-distortion condition. The amplitude decreases with the number of repetitions seems relatively flat, but confidence intervals overlapped with the exact repetition and the white-noise-distortion condition. Overall, the processing of deviating events had a stronger contribution to the condition differences on the P3a level (similar to what we found for the MMN). In the exact-repetition condition, the logarithmic trend of systematic amplitude modulations was much steeper than in the wrong-pitch condition.Despite the pronounced differences in P3a amplitude, estimated component latencies were not affected by our experimental manipulation. The time needed to internally evaluate pattern identity seems not higher with noise or wrong pitch insertions. Here, the auditory system seems equally quick in classifying the stimuli, in evaluating the novelty of the deviance, and in automatically orienting attention toward the task-irrelevant novel patterns .The behavioral performance in the active pattern change detection task showed highest accuracy in the exact-repetition condition, less accuracy in the white-noise condition, and least accuracy in the wrong pitch segment condition. The development of the hit rates as a function of train length also followed a logarithmic trend in all conditions with the hit rates in the exact-repetition condition, developing quickly toward a ceiling effect and most slowly in the wrong-pitch condition, mirroring the pattern of results at the level of P3a.Effects in the MMN time range did not distinguish between the two types of distortions that we introduced in the sequences. In both cases, when a pattern segment was occasionally replaced by white noise or by a differently pitched segment, the typical negativity observed for deviant responses grew less steeply compared with the condition with exact pattern repetitions. As the portion of matching pattern segments was similar for both conditions (five out of six), one could speculate that, at this early processing stage, the strength of regularity encoding mainly depends on the probability of matching information in spectrotemporal space. A previous study revealed that object representations can be retrieved from repetitions embedded in different backgrounds and suggested the correlation of input spectrograms between several non-perfect repetitions as a potential mechanism to achieve this .In contrast to the MMN findings, the type of distortion (white noise or wrong pitch information) seems to have a greater impact on evaluation processes at the stage of P3a. Here, we observed a clear disadvantage for the wrong pitch compared with the exact-repetition condition, whereas the response pattern in the white-noise condition resembled that of the exact-repetition condition. This suggests that the higher cognitive evaluation process and the attentional switch toward a deviant pattern are not substantially impaired in the white-noise condition. This could be explained by processes related to stream segregation or perceptual filling-in. Firstly, the white noise segments differed substantially from the other five segments in their spectral composition, leading to a vastly different timbre percept. This could have assisted the segregation of pattern and distracter information, allowing the later stages of evaluating a newly incoming pattern to be less disturbed. Secondly, white noise insertions could even lead to a partial restoration of the perceptual continuity of an intact standard pattern , 1988, pOverall, our two types of manipulations might remind of energetic and informational masking. During energetic masking, the processing of a sensory event is degraded typically by a noise masker, where, mainly, the energy relation between the signal and the masker determines their separability and the amount of difficulty in perceiving the signal . During In the present study, we demonstrated that the auditory system is able to form pattern representations and predictions even in the context of uncertainty. MMN and P3a were elicited in response to deviants in all conditions at similar latency estimations. Independent of distorted segments, an implicit and automatic buildup of regularity representations and deviance detection, with a following call for attention toward the stimuli, can be assumed. However, we found a general advantage for the exact-repetition condition over the two distorted repetition conditions. This is shown by steeper logarithmic amplitude changes on MMN and the P3a level, with increasing number of repetitions, as well as in the behavioral performance in the active pattern change detection task. The processing on the MMN level does not seem to differentiate between the qualities of the distortions but reacts to general (mis-)matching statistics between the sound patterns. At the level of P3a, we observed an influence of the type of distortion. On this processing stage, white-noise distortions may not have impeded stimulus processing to such an extent as wrong pitch distortions did. This is evidenced by the distinct degradation of the P3a, which also goes along with the behavioral findings in the active pattern change detection task. Additionally, our results revealed that deviant processing is more affected by our experimental manipulations compared with standard processing.To sum up, our findings indicate that the auditory system is able to quickly extract regularities and generate reliable predictions, even when the to-be-extracted patterns contain distortions. However, higher cognitive processing and the involvement of an attentional network might give the basis for the subtler evaluation of the acoustic input with regard to the type of distortion. The segregation between informative pattern segments and the distorting element, as well as the accessibility of a possible interpolation mechanism (like the one discussed for the continuity illusion), might explain the facilitated processing of white noise compared with wrong-pitch distortions on later processing stages that govern the elicitation of P3a and guide behavioral responses.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.This studies involving human participants were reviewed and approved by the Ethics Committee of the University of Leipzig, Germany. The patients/participants provided their written informed consent to participate in this study.SG and ES: conceptualization, supervision, and resources. MB: data curation, visualization, and writing—original draft. MB and SG: formal analysis, investigation, software, and project administration. SG: funding acquisition. SG, ES, and MB: methodology, writing, review, and editing, and validation. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


For many patients with hematologic, genetic, and immune diseases, HSPC transplants can be a life-saving treatment. There are over 20,000 patients in the US receiving HSPC transplantation yearly [ex vivo expansion of cord blood will be highly beneficial for the clinical application of HSPC transplants. In addition, there is a growing need for culturing PBSC in vitro for transplant-related applications such as gene therapy or genome-editing via TALENs or CRISPR/Cas9 [in vitro culture technique can be used for HSCP expansion for poor autologous mobilizations to avoid additional collections. Establishing culture conditions that can maintain and expand HSPCs from PBSC ex vivo will be beneficial to these clinical applications.Currently, there is a growing need for culturing hematopoietic stem/progenitor cells (HSPCs) n yearly . About tSPR/Cas9 . FurtherExpansion of HSPCs in culture, in general, is at the expense of “stemness”. Since the fate of a HSPC is governed by genetic and epigenetic factors, and we and others have proposed that the fate of a HSPC can be redirected or reprogrammed through modifications of key factors. Many efforts have been applied to identify and understand the key players in HSPC cell fate switching process through celltype-specific gene expression profile, cellular surface markers and functional studies. Genes and pathways that are functionally linked to self-renewal of HSCs include CEBPα , Notch lex vivo culture condition that can maintain and expand PBSCs without the loss of their “stemness”. We utilized a 3- to 5-day assay that can be easily modified to use in the current clinical HSPC transplantation setting, and co-expression of CD34 and CD90 to identify compounds with potentials for PBSC expansion [+CD90+ cells. Five compounds were histone deacetylase inhibitors (HDACis), and they are trichostatin A (TSA), DLS3, valproic acid (VPA), vorinostat also known as suberanilohydroxamic acid (SAHA), and Merk60. Especially, treatment of CD34+ PBSCs with a single dose of TSA ex vivo yielded the greatest expansion (11.7-fold) of CD34+CD90+ cells when compared to the control group. Additionally, TSA-treated PBSC CD34+ cells had a statistically significant higher engraftment rate than the control-treated group in xenotransplantation experiments.We have searched for a robust and short-term xpansion . After s+CD90+ cells could maintain stem/progenitor cell properties based on our in vitro and in vivo experiment results, we next asked whether the expansion of CD34+CD90+ cells by TSA could affect the lentiviral transduction efficacy during ex vivo culture. A transfer vector encoding a green fluorescent protein (GFP) was used for the evaluation of lentiviral transduction. PBSC CD34+ cells were cultured with or without TSA for 3 days, followed by lentiviral transduction with protamin twice for 48 hours  and histone deacetylase (HDAC) enzymes. The HDACi treatments of cells in general lead to a more open chromatin and gene activation. We propose that since the HSPC fate is governed by key transcription factors, which are downregulated during HSPC ex vivo expansion; by adding HDACi to the culture medium, we can keep the chromatin in a relative “open” state, and maintain the expression of these key factors, therefore, maintain the “stemness” of the expanded HSPCs. We further demonstrate that among multiple key regulators involving in the self-renewal property of HSPCs, SALL4 is important for this TSA-mediated ex vivo CD34+CD90+ HSPC expansion process [We are intrigued by the finding that HDACi is enriched as a class of molecules that can be used to expand HSPCs  process .spalt  [+ (HSPCs) [+ cells increased ex vivo expansion efficiency by more than 10,000 fold for CD34+/CD38− and CD34+/CD38+ with appropriate cytokines [+ non-human primate HSCs [+HSCs compared to the control group [SALL4 was originally cloned based on its DNA sequence homology to the homeotic gene in Drosophila, lt  -23. Sevelt  -26. Similt  . One exc (HSPCs) . It has ate HSCs  and Mossol group . In addiol group . These sHOXA9 through its interaction with Mixed-Lineage Leukemia (MLL) protein [Further studies are needed to understand the mechanism(s) SALL4 function in HSPCs and to apply for the clinical setting. The mechanism(s) of SALL4 in gene regulation, at least in part, is through its interaction with epigenetic complexes . SALL4 can function as a gene repressor and activator through its interactions with both gene-activating and repressing epigenetic complexes. More specifically, SALL4 can repress its target genes through its interaction with the Nucleosome Remodeling and Deacetylase complex (NuRD) -35, an H protein , which i


The incidence of diabetic osteoporosis is increasing. This article evaluates the effect of combination treatment with the hypoglycemic drug exendin-4 (Ex-4) and the vitamin D analog eldecalcitol (ED-71) on improving diabetic osteoporosis and explores the relevant mechanism of action.Micro-CT, HE staining, immunohistochemistry, qPCR and ELISA were used to evaluate the impact of Ex-4 and ED-71 on bone formation and macrophage polarization in a mouse model of diabetic osteoporosis in vivo. Immunofluorescence, flow cytometry and qPCR were used to characterize the polarization type of macrophages treated with Ex-4 and ED-71 in vitro. A co-culture system of BMSCs and macrophages was established. Subsequently, crystal violet staining, alkaline phosphatase staining and alizarin red staining were used to evaluate the migration and osteogenesis differentiation of BMSCs.Ex-4 combined with ED-71 significantly reduced blood glucose levels and enhanced bone formation in mice with diabetic osteoporosis. In addition, Ex-4 synergized with ED-71 to induce the polarization of macrophages into M2 through the PI3K/AKT pathway. Macrophages treated with the combination of Ex-4 and ED-71 can significantly induce the osteogenic differentiation of BMSCs.Ex-4 synergized with ED-71 to reduce blood glucose levels significantly. And this combination therapy can synergistically induce osteogenic differentiation of BMSCs by promoting M2 macrophages polarization, thereby improving diabetic osteoporosis. Therefore, the combination of Ex-4 and ED-71 may be a new strategy for the treatment of diabetic osteoporosis. Diabetic osteoporosis is a serious global public health issue. Both patients with type I diabetes mellitus T1DM) and those with type II diabetes mellitus T2DM) may be at increased risk for developing osteoporosis due to the loss of bone mass   for 10 min. F4/80-FITC  and CD206-PE  were used to incubate at 4 °C in the dark for 60 min. Then, 5 mL 0.1% BSA in PBS was added to resuspend cells and centrifuged at 300g for 5 min. The supernatant was discarded. Repeat washing 2 times. Finally, 0.5 mL 0.1% BSA in PBS was added to resuspend cells, and the polarization types of macrophages were identified by flow cytometer .Flow cytometry was performed according to the instructions of the manufacturer of the flow cytometer. Briefly, a suspension of RAW264.7 cells was prepared in 0.1% BSA in PBS and centrifuged at 300g for 5 min. Subsequently, the supernatant was discarded after centrifugation at 300g for 5 min, and the samples were washed twice. Finally, 500 μL 0.1% BSA in PBS was used to resuspend the cells again. The purity of BMSCs was identified by flow cytometer as above.According to the manufacturer's protocol, BMSCs were digested with trypsin, and the digestion was terminated at an appropriate time. Centrifugation was performed at 2000 rpm for 5 min. Then, the supernatant was discarded and the cells were resuspended in 100 μL 0.1% BSA in PBS. The cells were incubated with CD34-FITC , CD45-PE , CD73-PE  and CD105-FITC  at 4 °C in the dark for 60 min. 5 mL 0.1% BSA in PBS was added to resuspend cells and centrifuged at 300M-MLV RT Reverse Transcription kit II  Co., Ltd., China). SYBR Green Pro Taq HS premixed qPCR kit  Co., Ltd., China) was used to perform qPCR in real-time fluorescence quantitative PCR system . The primer sequences are shown in Table −∆∆CT method.For the isolation of RNA from bone, the bones of sacrificed mice with cervical dislocation were ground quickly. During this period, liquid nitrogen was continuously added to prevent the sample from melting until the sample became powder. For RNA isolation from RAW264.7 cells, the medium was discarded, and cells were rinsed 3 times with precooled PBS. Subsequently, Trizol reagent  Co., Ltd., China) was used to extract RNA from bone samples and RAW264.7 cells. According to the manufacturer's protocol, cDNA was synthesized by using the Evo The co-cultured BMSCs were fixed with 4% paraformaldehyde for 20 min and then stained with crystal violet for 15 min to detect the migration of BMSCs. Areas of interest were selected under the optical microscope .To evaluate the ALP activity of BMSCs, the co-cultured BMSCs were fixed with 4% paraformaldehyde for 15 min and stained with ALP solution according to the manufacturer's protocol. Imaging was obtained through an optical microscope . To evaluate the deposited minerals, the co-cultured BMSCs were fixed with 4% paraformaldehyde for 15 min and then stained with 1% AR staining solution  to detect the degree of mineralization. Subsequently, AR was further isolated with cetylpyridinium chloride and was detected using a spectrophotometer .RIPA Lysis Buffer  was used to extract proteins according to the manufacturer's instructions. The protein concentrations were determined by using the BCA protein concentration assay kit . The protein samples were mixed with 1/4 volume of 5 × SDS loading buffer and heated at 95 °C for 5 min. Equal amounts of proteins were separated by 10% SDS-PAGE gel electrophoresis and transferred onto a polyvinylidene fluoride (PVDF) membrane. After blocking with 5% BSA-TBST at room temperature for 1 h, the membranes were incubated overnight at 4 °C with the following primary antibodies: rabbit anti-p-PI3K , rabbit anti-p-AKT , rabbit anti-β-catenin  and rabbit anti-GAPDH . Samples were then incubated with horseradish peroxidase-conjugated goat anti-rabbit IgG  for 1 h. Enhanced chemiluminescence reagent  was used to detect immunoreactive bands. Images were captured using a gel imaging system .t-tests. The differences between three or more groups were tested by one-way analysis of variance (ANOVA). Differences for which p < 0.05 were considered significant.The data were presented as mean values ± standard deviation and contained at least three independent biological copies. Statistical analyses were conducted with GraphPad Prism 6.0 software . The differences between two groups were identified by Student’s The effect of Ex-4 and ED-71 on bone formation was investigated in db/db mice. Micro-CT showed that bone formation was significantly increased in db/db mice treated with Ex-4 or ED-71, especially in mice given the combination of Ex-4 and ED-71 . However, after the treatment with Ex-4 or ED-71, the proportions of F4/80+CD206+ cells were increased slightly. Specifically, the ratio of F4/80+CD206+ cells reached 4.6% after the administration of Ex-4, and it increased to 9.0% after ED-71 administration. Furthermore, the proportions of F4/80+CD206+ cells in the combination group increased to 22.9%  and red (CD206) fluorescence intensity was observed in Ex-4 group, a much stronger green (CD163) and red (CD206) fluorescence was detected in ED-71 group, while the strongest green (CD163) and red (CD206) fluorescence was detected in the combination group  as demonstrated through crystal violet staining Fig. A, ALP stThus, we demonstrated that Ex-4 and ED-71 synergistically activate the PI3K/AKT pathway to polarize macrophages into M2, thereby causing osteogenesis differentiation of BMSCs (Fig. 3, can prevent the decrease of bone biomechanical strength, improve bone mineral density and prevent diabetes-induced deterioration of trabecular microstructure in diabetic rats [The cause of diabetic osteoporosis can be divided into two categories. On one hand, the osteogenic differentiation of BMSCs is inhibited , and thetic rats . TherefoIn this study, db/db mice treated with the combination of Ex-4 and ED-71 showed significantly enhanced bone formation and upregulated expression of related osteogenic factors. ALP, a factor of early osteoblast differentiation, was increased slightly in Ex-4 or ED-71 groups, but was significantly increased in the combination group, suggesting that Ex-4 and ED-71 could synergistically induce early osteoblast differentiation. Col I, a marker of advanced osteogenic differentiation, was significantly increased in mice treated with the combination of Ex-4 and ED-71, suggesting that these two drugs could rescue collagen fibers from damage caused by high glucose levels and play a synergistic role in the process of late osteogenesis. Thus, Ex-4 and ED-71 could synergistically promote bone formation in diabetic osteoporosis mice.Furthermore, it was found that macrophages are increasingly polarized into M2 after treatment with ED-71 in db/db mice, and the combined application of Ex-4 and ED-71 could further increase this differentiation. It has been shown that communication between macrophages and BMSCs plays a role in bone regeneration. In particular, M2 macrophages can significantly promote osteogenesis mediated by BMSCs . Our finMultiple signaling pathways can regulate the polarization of macrophages into different phenotypes , among wIn addition to these relatively direct mechanisms, we believe that the synergistic reduction of blood glucose also contributes to the impact of Ex-4 and ED-71 on the promotion of bone formation. Vitamin D supplementation can effectively reduce the risk of developing T2DM . SeveralImportantly, treatment with the drug combination was well tolerated by the mice. However, it must be noted that the most common adverse drug reaction of ED-71 is hypercalcemia , and we There is a limitation in this subject. Although Ex-4 and ED-71 were only applied to RAW264.7 in the co-culture system, BMSCs were directly exposed to these two drugs simultaneously due to the permeability of the transwell membrane. The direct effect of drugs on BMSCs was not fully considered in this study. And this will be our new research direction.We investigated the bone repair effect of Ex-4 combined with ED-71 in the treatment of diabetic osteoporosis. This bone repair effect may be related to the communication between macrophages and BMSCs. Ex-4 and ED-71 synergistically promote osteogenic differentiation of BMSCs through M2 macrophage polarization via the PI3K/AKT pathway. In addition, combination treatment is associated with a synergistic decrease in blood glucose levels. Therefore, the combined application of Ex-4 and ED-71 may be a potential treatment for diabetic osteoporosis.


Consequently, this study identified a desirable banana  crop containing large amounts of edible carbohydrates and completely digestible lignocellulose, which could be combined to achieve the highest bioethanol yields of 31–38% (% dry matter), compared with previously reported ones in other bioenergy crops. Chemical analysis further indicated that the cellulose CrI and lignin G-monomer should be two major recalcitrant factors affecting biomass enzymatic saccharification in banana pseudostems and rachis. Therefore, this study not only examined rich edible carbohydrates for food in the banana pseudostems but also detected digestible lignocellulose for bioethanol production in rachis tissue, providing a strategy applicable for genetic breeding and biomass processing in banana crops.Banana is a major fruit crop throughout the world with abundant lignocellulose in the pseudostem and rachis residues for biofuel production. In this study, we collected a total of 11 pseudostems and rachis samples that were originally derived from different genetic types and ecological locations of banana crops and then examined largely varied edible carbohydrates  and lignocellulose compositions. By performing chemical (H Banana is one of the most consumed fruits in the world. However, it not only provides a high yield of edible carbohydrates with high nutrition but also produces large amounts of pseudostem and rachis residues rich in lignocellulose . Hence, Due to global warming and fossil energy overconsumption, lignocellulose is increasingly considered as a sustainable biomass resource, and cellulosic bioethanol has been evaluated as a promising solution for partial replacement of fossil fuels ,7,8. HowBiomass recalcitrance is in principle determined by wall polymer feature and wall network construction ,12. In gIn the past few years, various physical and chemical pretreatments have been carried out to enhance sequential enzymatic hydrolysis and final bioethanol production ,20,21,22In the present study, therefore, we collected a total of 11 pseudostem and rachis samples derived from eight distinct genetic types and original locations of banana crops and determined largely varied edible carbohydrates  contents and lignocellulose compositions. We then performed mild chemical  and LHW pretreatments to compare biomass enzymatic saccharification and bioethanol production among all banana samples examined. This study also detected major wall polymer features to explain why the desirable banana samples were of high biomass saccharification and bioethanol production.As banana is a fruit plant grown worldwide in different ecological regions, this study collected nine pseudostems and two rachis samples from Haikou experimental fields, which are originally derived from six countries with eight distinct genetic types . Among tMeanwhile, the 11 total banana samples showed much-varied starch levels from 1.8% to 13.7% with CV at 54% b. In parFurthermore, we examined a remarkably varied wall polymer composition such as 21.2–38.7% cellulose (% dry matter), 10.4–15.7% hemicellulose, 7.9–15.7% lignin, and 3.4–6.6% pectin with CV values of 18%, 12%, 20%, and 21%, respectively c. Hence,2SO4) and measured the hexoses yields, which ranged from 14.4% to 21.1% (% cellulose), and total sugars yields, which ranged from 19.3% to 58.3% (% dry matter) with CV at 28% and 20% among the 11 total banana samples  released from enzymatic hydrolysis of pretreated lignocellulose or total sugars (hexoses and pentoses) yield (% dry matter) obtained from both enzymatic hydrolysis and pretreatment. Using our previously established condition, this work performed acid pretreatments at low concentrations  and rachis (RC-2) samples of Refen1 banana crop showed much higher total sugar yields  than those of all other banana samples (19.3–43.2%), suggesting that this banana crop should be of the desirable lignocellulose substrate for biomass enzymatic saccharification under acid pretreatment. However, compared to other grassy crops examined in the previous studies ,28,29,30Since the acid pretreatment caused relatively low enzymatic saccharification, this study performed alkali pretreatment with all 11 banana samples. As a result, the banana samples showed largely varied biomass enzymatic saccharification with the hexoses yields ranging from 12.6% to 30.52% (% cellulose) and total sugars yields ranging from 20.4% to 65.2% (% dry matter) with CV at 22% and 20% after 1% NaOH pretreatment with the mild (50 °C for 1 h) condition a,b.Furthermore, this study performed pretreatments with high concentrations of alkali  in two representative banana pseudostems samples , which respectively represent the highest and lowest hexoses yields from the 1% NaOH pretreatment performed above. Under 4% NaOH pretreatments, two banana samples showed the hexoses yields of 96% and 98% for almost complete biomass enzymatic saccharification c. Hence,Provided that the alkali pretreatment at high concentration could cause almost complete biomass enzymatic saccharification in the banana samples examined above, it remains to recycle all chemicals and other wastes. In this study, we further performed green-like  LHW pretreatments with all banana samples at a time course  using our previously established condition .Under the 4 min LHW pretreatment, all banana samples showed the hexoses yields at more than 50% (% cellulose) with CV at 19% a. NotablUsing total hexoses obtained from enzymatic saccharification, this study conducted a classic yeast fermentation to achieve bioethanol production from eight representative banana samples .Their results showed bioethanol yields of the banana samples from 1.3% to 14.4% (% dry matter), with CV at 46%, by using hexoses released from enzymatic hydrolysis upon 1% NaOH pretreatment a, which Because the pseudostems and rachis residues of banana crops showed distinct biomass enzymatic saccharification under chemical and LHW pretreatments , this stHowever, as the lignin deposition contributes to lignocellulose recalcitrance against biomass enzymatic saccharification ,38,39, tTo test this assumption, this study examined cellulose crystallinity, which has been considered as the key negative factor on lignocellulose’s recalcitrant property ,14. CompA total of nine distinct banana crops were grown in the Fruit Experimental Field of Haikou Experimental Station, Chinese Academy of Tropical Agricultural Sciences (CATAS) in Danzhou city, Hainan province, China. After banana fruits were harvested, the remaining pseudostem and rachis residues were chopped and dried at 60 °C until constant weight. The dried biomass samples were ground into powders, passed through a 40-mesh screen, and stored in a dry container until use.v/v), DMSO–water , and ammonium oxalate 0.5% (w/v), the soluble sugars, lipid, starch, and pectin of biomass samples were sequentially removed. The remaining residue was then extracted with 4 M KOH containing 1.0 mg mL−1 sodium borohydride for the KOH-extractable hemicelluloses. The final pellet was dissolved with H2SO4  to determine cellulose and non-KOH-extractable hemicelluloses levels. All experimental analyses were completed as independent biological triplicate.The cell wall fractionation of the banana sample was conducted as previously described . Using p2SO4 [m-hydroxybiphenyl/NaOH method [2SO4 method. The hemicelluloses were calculated by determining the total hexoses and pentoses of the hemicelluloses fraction. The hexoses, pentoses, and uronic acids of the pectin fraction were calculated as total pectin. All experimental analyses were completed in independent triplicate.UV–VIS Spectrometer  was applied for hexoses, pentoses, and uronic acids assay as previously described . Hexoses2SO4  and orci2SO4  methods.H method . For staA two-step acid hydrolysis method was used for total lignin assay, according to the Laboratory Analytical Procedure of the National Renewable Energy Laboratory . Three lmyo-inositol were obtained from Aladdin Reagent Inc . 1-Methylimidazole was purchased from Sigma-Aldrich Co. LLC . Acetic anhydride and acetic acid were obtained from Sinopharm Chemical Reagent Co., Ltd .GC-MS (SHIMADZU GCMS-QP2010 Plus) was used for the detection of monosaccharide composition of hemicellulose as previously described . Trifluog for 5 min, the supernatant was collected, and its hexoses and pentoses were respectively detected by colorimetric assay as described above. All analyses were completed by three independent experiments.The biomass sample (0.300 g) was incubated with 6 mL potassium phosphate buffer (pH 4.8) in a boiling water bath for 1 h and shaken every 10 min. After centrifugation at 3000× X-ray diffraction method was applied to detect cellulose crystalline index (CrI) as previously described  using th2SO4 pretreatment: The biomass samples (0.300 g), through a 40 mesh sieve, were loaded with 6 mL H2SO4 at 1% (v/v) concentration. The sample tubes were sealed and heated at 121 °C for 20 min in autoclave (0.15 Mpa). After heating reaction, the samples were rinsed several times with distilled H2O until pH was 7.0, and the remaining residues were stored for enzymatic hydrolysis.Hw/v) shaken under 150 rpm at 50 °C for 2 h. The pellets were washed with 10 mL distilled water 5–6 times until pH was 7.0.NaOH pretreatment: The well-mixed biomass samples (0.300 g) were incubated with 6 mL NaOH at various concentrations  pretreatment: The well-mixed biomass samples (0.300 g) with 2.4 mL of distilled water were added into well-sealed stainless steel bombs and heated at 200 °C under 15 rpm shaking for 4, 8, 16, 32 min, respectively. Then, the sealed bombs were cooled down immediately and centrifuged at 3000× All supernatants were combined for pentoses and hexoses assay, and the remaining pellets were used for enzymatic hydrolysis as described below. All experiments were conducted in independent triplicate.−1) of mixed-cellulases  and shaken under 150 rpm for 48 h at 50 °C. The samples were centrifuged at 3000× g for 5 min, and the supernatants were collected for pentoses and hexoses assay. All experiments were carried out in independent triplicate.The remaining residues obtained from pretreatments were rinsed once more with 10 mL of mixed-cellulase reaction buffer . The washed residues were incubated with 6 mL  was suspended with 0.2 M phosphate buffer (pH 4.8) for 30 min for activation prior to use. The yeast powder was then added to the phosphate buffer to achieve a final concentration of 0.5 g L−1 in all fermentation tubes, and the fermentation was conducted at 37 °C for 48 h in the tubes. Ethanol was measured using the K2Cr2O7 method. The experiments were performed in independent triplicate.Yeast fermentation and ethanol measurement were conducted as previously described ,51. Yeast-test. The boxplot, histogram, and regression analysis for the best fit curve were generated using Origin 8.5 software . The average values were obtained from the original triplicate measurements for these analyses.Pair-wise comparisons were performed between two measurements by Student’s 2SO4, NaOH) and LHW pretreatments, a total of 11 banana samples also showed a diverse biomass enzymatic saccharification and bioethanol production. Notably, the desirable banana (Refen1) crop not only contained large amounts of edible carbohydrates, but also showed complete biomass enzymatic saccharification from mild alkali and LHW pretreatments, which could be integrated to achieve the highest bioethanol yields of 31–38% (% dry matter) in the pseudostems and rachis samples, compared to other bioenergy crops in the previous studies. Furthermore, this study sorted out two wall polymer features (cellulose CrI and lignin G-monomer) that may play a major role in lignocellulose enzymatic hydrolysis of banana pseudostems and rachis tissues. Hence, this work has identified a desirable banana crop that was of rich edible carbohydrates and digestible lignocellulose for bioethanol production.By collecting 11 total pseudostems and rachis samples of banana crops derived from different genetic types and ecological locations, this study found largely varied edible carbohydrates  and lignocellulose compositions. Under chemical (H


Musa spp.) plant produces elongated and edible fruit. The two main parthenocarpic species of banana are Musa accuminata Colla and Musa balbisiana Colla. There are several health-promoting and disease-preventing effects of Musa accuminata Colla, which are attributed to its important bioactive compounds, including phenolics, carotenoids, biogenic amines, phytosterols, and volatile oils, found in the stem, fruit, pseudostem, leaf, flower, sap, inner trunk, root, and inner core. Banana possesses numerous pharmacological activities, such as antioxidant, immunomodulatory, antimicrobial, antiulcerogenic, hypolipidemic, hypoglycemic, leishmanicidal, anthelmintic, and anticancer properties. Various individual studies have reported anticancer effects of different components of the banana plant. However, according to our understanding, an up-to-date, systematic, and critical analysis of existing scientific results has not yet been carried out.The banana (This review aims to include a thorough assessment of banana and its phytochemicals for cancer prevention and therapy with a focus on cellular and molecular mechanisms of action.The available research studies on anticancer activities of banana extracts, fractions and pure compounds were collected using various scholarly databases, such as PubMed, ScienceDirect, and Scopus, based on predetermined selection criteria.Various banana extracts, fractions, and phytoconstituents, including ferulic acid, protocatechualdehyde, 2-pentanone, 4-epicyclomusalenone, cycloeucalenol acetate, and chlorogenic acid, have been shown to exhibit cancer preventative and anticancer activities in breast, cervical, colorectal, esophageal, hepatic, oral, prostate, and skin cancers. Bioactive components present in bananas have exhibited antiproliferative, cell cycle arrest-inducing, apoptotic, anti-adhesive, anti-invasive, and antiangiogenic effects through modulation of diverse, dysregulated oncogenic signaling pathways.Based on the critical analysis of available literature, banana products and phytoconstituents show enormous potential for future development of drugs for cancer prevention and therapy. However, more mechanistic studies and well-designed clinical trials should be performed to establish its efficacy. While the precise cause for cancer initiation is still unclear, the most important contributing variables for this condition are toxins, pollution, radioactive substances, oncogenic viruses , Arthsastra (250 BC), and Chilappthikaram (500 AD), suggesting the fruit’s importance and demonstrating its ancient use in India. The genus name Musa was chosen to commemorate Roman physician and botanist Antonius Musa (63 BC-14 AD)  . Historiof India . At presof India .The banana is a perennial herb that looks like a tree .M. acuminate plants have been used to treat non-communicable as well as transmissible diseases, especially in Asia and Africa. It has been extensively used by indigenous people as both food and medicine  genotype of M. acuminata and M. balbisiana which have an epicatechin content of 114.44 mg/100 g dry weight basis and gallocatechin content of 591.41 mg/100 g dry weight basis. In addition to catechin compounds, protocatechuic acid, gallic acid, 7-O-neohesperoside naringenin, and hydroxycinnamic acids have additionally been identified in banana pulp  (2), vanillic acid (3), caffeic acid (4), ellagic acid (5), 13-octadecanoic acid (6), palmitic acid (7), oleic acid (8), linoleic acid (9), methyl palmitate (10), methyl oleate (11), methyl linoleate (12), stearic acid (13), carvacrol (14), pentadecanoic acid (15), palmitoleic acid (16), benzoic acid (17), tannic acid (18), cinnamic acid (19), ferulic acid (20), delphinidin-3-rutinoside (21), cyanidin-3-rutinoside (22), petunidin-3-rutinoside (23), peonidin-3-rutinoside (24), malvidin-3-rutinoside (25) (26), gallic acid (27), protocatechualdehyde (28), hydroxycinnamic acid (29), caffeoylquinic acid (30), quercetin (31), proanthocyanidin (32), catechin (33), gallocatechin (34), epicatechin (35), procyanidin (36), (+) catechin hydrate (37), apigenin (38), myricetin (39), kaempferol (40), endo-β-1,3-glucanase (Ban-Glu) (41), and α-tocopherol (42).A triterpenoid, namely cycloartenol (43), was extracted from the dichloromethane extract of ripe pulp of various banana cultivars  Figure 2mic acid , caffeoyuercetin , proanthBan-Glu) , and α-toartenol , was extultivars .Musa spp., namely, campesterol (44), stigmasterol (45), β-sitosterol (46) (47) (48) is present in ripe banana fruits (49) and epi-sesamin (50), have also been isolated and identified in the methanol extract of banana peel  Figure 4rol (46) . The met46) 47) . In addi . In add46) (47)  is prese51), and vitamin A (retinol) (52) are the most abundant antioxidants present in the banana pulp and peel (Musa spp. biomasses as well (53 and 54) (55) has additionally been found in bananas. Several additional novel compounds, such as 2-(4-hydroxyphenyl)-naphthalic anhydride (56), and methyl 2-benzimidazolecarbamate (57), were reported to be present in banana   . Zeaxantretinol)  are the 58), serotonin (59) and histamine (60) have all been detected in bananas and their by-products , 2-phenylethylamine (62), putrescine (63), cadaverine (64), and tyramine (65), are also present in banana , 5-(hydroxymethyl)-2-furancarboxyaldehyde (67), cis-9- hexadecenal (68), (S) (+)-naproxene (69) (70), Anigorufone (71), 2-pentanone (72), and N-acetylserotonin (73)  Figure 5nin (73) , 56–59. ene (69) , AnigoruM. acuminata) flower is used to prepare a popular Sri Lankan dish as a curry, boiled or deep-fried salad (M. acuminata) extracts in preclinical trials  revealed that M. acuminata flower extract was safe as well  showed potent nephroprotective activity in gentamicin-induced nephrotoxicity in mice. Cellulose nanofibers isolated from the banana peel (M. paradisiaca) exhibited no cytotoxicity against Caco-2 cell line  also did not induce any cytotoxicity in RAW 264.7 murine macrophage cell lines, which was evident from the presence of 70% viable cells   which isin vitro  peel and pulp was observed to be cytotoxic and blocked the proliferation of MCF-7 cells (Regarding poptosis . Anotherpoptosis . Additio00 μg/mL . Additio-7 cells .M. acuminate lectin (MAL) from the phloem exudates of M. acuminate pseudostem also demonstrated antitumor activity in Swiss albino mice bearing Erhlich carcinoma cells. Mechanistic studies showed initiation of apoptosis through the arrest of cell cycle progression at G2/M phase via stimulation of caspase-3, caspase-8 and caspase-9 with increased poly (ADP-ribose) polymerase (PARP) cleavage. It further triggered apoptosis through the phosphoinositide 3-kinase (PI3K)/Akt  signaling pathway, which inhibited the expression level of phosphorylated Akt (pAkt). MAL also blocked the phosphorylation of extracellular signal-regulated kinase 1 and 2 (ERK1/2) and c-Jun N-terminal kinase (JNK)  .M. paradisiaca) exhibited anticancer activity against HeLa cervical cancer cell line. The extract inhibited cellular proliferation and induced apoptosis, which was evident by the appearance of breaking up of the nuclei associated with significantly increased caspase-9 activity. The extract also blocked the cell cycle progression at the G0/G1 phase as well  peel and pulp exhibited in vitro anticancer activity against HCT-116 colon carcinoma cell line. It was observed that the peel and pulp extract arrested cell growth by inducing cytotoxicity and blocked the proliferation of HCT-116 cells -initiated cyclin D1 suppression. It also downregulated the transcriptional level of the cyclin D1 gene and reduced the expression level of cyclin-dependent kinase 4 (CDK4). Additionally, PCA attenuated the enzymatic activity of HDAC and reduced the expression of HDAC2, but not HDAC1, thereby inducing cell cycle arrest at the G1 to S phase in both the cell lines tested  and p38 mitogen-activated protein kinase (MAPK) proteins and cleavage of PARP (2) production and cyclooxygenase-2 (COX-2) protein expression in tumor necrosis factor-α (TNF-α)-stimulated colon cancer cells (HT29).The hexane fraction of banana  was used as a dietary supplement to evaluate its anticancer potency in 1,2-dimethylhydrazine (DMH)-induced colon carcinogenesis in male Swiss mice over a 12-week experimental period. In all treated groups, it reduced the number of aberrant crypt foci (a colon cancer biomarker) in the colorectal mucosa, suggesting anticarcinogenic efficacy although the detail mechanism of action was not reported  and increased reactive oxygen species (ROS) level  pseudostem and rhizome demonstrated cytotoxicity against HepG2 cell lines. Crude chloroform and acetone extracts of the banana pseudostem and rhizome exhibited substantial cytotoxicity against the cell line tested (An anticancer study on S) level . Anothere tested . BioactiM. paradisiaca) soft piths (BSPs) exhibited potent cytotoxic and antiproliferative activity against the human oral squamous cell carcinoma (OSCC) cell line (HSC-4) (Ethyl acetate sub-fraction of the ethanol extract of banana ( (HSC-4) .in vitro. The banana flower extract at a concentration of 2 mg/mL reduced the viability of BPH-1 cells through cell-cycle arrest at the G1 phase. Moreover, it reduced the expression level of cyclin D1 and cyclin-dependentkinase6 (Cdk6) and elevated the expression level of p53 and p27   and p27 . It furtactivity .M. cavendish green peel hydroalcoholic extract demonstrated antiproliferative and cytotoxic activity against A-375 human malignant melanoma cells at a concentration of 100 μg/mL  has gained a lot of interest, other parts of the banana plant, such as the leaf, flower, and stem, have also been investigated for anticancer purposes. In addition to banana extracts and fractions, some phytoconstituents, including ferulic acid, protocatechualdehyde, 2-pentanone, 4-epicyclomusalenone, cycloeucalenol acetate, and chlorogenic acid, have been shown to exhibit cancer preventative and anticancer therapeutic abilities. Cancer preventive studies are limited, although two such study is reported where consumption of banana can reduce the incidence of esophageal cancer . Different aspects, such as banana processing and variety, often affect bioavailability and accessibility.in vitro experiments. Breast, cervical, colorectal, esophageal, hepatic, oral, prostate, and skin cancers are only a few of the cancer types affected by banana and its phytochemicals. The reviewed literature reveals the promise that banana and its phytochemicals can be used in chemotherapy for different forms of cancer. The role of banana and its phytoconstituents on breast cancer and colon cancer have been studied extensively in both in vitro and in vivo research. Findings from in vivo studies on other cancer types and clinical situations are sparse. With encouraging preclinical data, mechanistic investigations on anticancer actions of the components of banana are warranted. The translation impact of available research findings is restricted by the lack of well-designed, prospective clinical studies and safety evaluation of banana extracts and constituents in humans. The potential pharmacokinetic constraints of banana phytochemicals highlight the need to establish efficient and well-regulated delivery mechanisms for optimized delivery systems against various malignancies. More experiments on novel molecular targets and signaling pathways of banana bioactive materials, in addition to well-controlled clinical trials, will increase the therapeutic potential of this popular and medicinal fruit for cancer prevention and treatment. According to the selective toxicity tests, bananas and their main components are safe. However, more research is to be carried out to see whether the same favourable safety profile occurs in human subjects, and to determine which banana secondary metabolites may be cytotoxic, if any. Moreover, banana-derived products may be utilized as an adjuvant to various chemotherapeutic drugs (which have many adverse side effects) for a variety of cancer subtypes.Despite the vast amount of research that has been performed and documented over the last few decades, the bulk of the findings cited in this review are focused on in vitro studies, more in vivo mechanistic experiments should be performed. Provided the positive anticancer findings presented in this study, randomized clinical trials involving banana phytochemicals should be carried out. However, further research into the anticancer ability of other important phytochemicals found in bananas is warranted. Characterization of different phytochemicals found in bananas that function alone or synergistically with other compounds or established drugs to have cancer ameliorative or protective effects is also required. In conclusion, based on our in-depth analysis of the existing literature, banana extracts and the isolated phytoconstituents found in banana present as promising medicinal agents for cancer prevention and these agents could also be developed as multi-targeted drugs for cancer pharmacotherapy.Our systematic study and review of limitations also identify various future research paths. Although numerous bioactive banana compounds have been identified, further research into the anticancer ability of these phytochemicals found in bananas is required. Furthermore, since the bulk of research is limited to The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.Conceptualization: AM. Literature search and collection: SBo, SBa, and PD. Writing—original draft preparation: AM, SBa, and ES. Writing—review and editing: AM, AA, and AB. Supervision: AM. Project administration: AB. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.