R2 = 0.010) and event density (R2 = 0.011) were positively associated with the groove ratings. These effects were stronger in participants who were music professionals, compared to amateur musicians or mere listeners. A categorisation of the stimuli according to structural aspects was also associated with groove (R2 = 0.018). Beat salience, residual microtiming and rhythmic variability showed no effect on the groove ratings. Participants’ familiarity with a drum pattern had a positive influence on the groove ratings (η2 = 0.051). The largest isolated effect was measured for participants’ style bias (R2 = 0.123): groove ratings tended to be high if participants had the impression that the drum pattern belonged to a style they liked. Combined, the effects of style bias and familiarity (R2 = 0.152) exceeded the other effects as predictors for groove by a wide margin. We conclude that listeners’ taste, musical biographies and expertise have a strong effect on their groove experience. This motivates groove research not to focus on the music alone, but to take the listeners into account as well.Music psychology defines groove as humans’ pleasureable urge to move their body in synchrony with music. Past research has found that rhythmic syncopation, event density, beat salience, and rhythmic variability are positively associated with groove. This exploratory study investigates the groove effect of 248 reconstructed drum patterns from different popular music styles . It aims at identifying factors that might be relevant for groove and worth investigating in a controlled setting in the future. Drum patterns of eight bars duration, chosen from 248 popular music tracks, have been transcribed and audio reconstructions have been created on the basis of sound samples. During an online listening experiment, 665 participants rated the reconstructions a total of 8,329 times using a groove questionnaire. Results show that, among 15 tested variables, syncopation ( The fto groove [A groove may mean certain aspects of the composition, a “multi-layered pattern” [riff or a vamp). Such patterns have been analysed in musicology and ethnomusicology [has groove, they mean that the music is aesthetically pleasing to them, it does invite body movement, and creates a state of flow and effortlessness [The groove concept originally emerged within the communities of Western popular music styles like funk, soul, R&B, rock and jazz –8. In tho groove . A groovpattern”  that consicology , 9–16. Flessness .Music psychology narrowed the scope of the groove concept by defining it exclusively as the pleasurable urge to body movement triggered by music. In this very precise sense, the groove phenomenon is not limited to Western popular music, since synchronised body movement behaviour as response to music is widespread across many cultures. Whenever jazz has “swing” , AmericaIn this sense, the groove experience contributes to arousal and mood regulation by definition, which have been identified as primary reasons why many humans engage with music : music wGroove and its near relative swing have been a topic in musicology and ethnomusicology at least since the 1950s [Microtiming: Many jazz musicians have stated [e stated , 17, 41 e stated , 43), are stated , 44, 45.e stated –49, Cubae stated , Brazilie stated –53, Norwe stated , Malian e stated –57, R&B,e stated  and in de stated –61.Several empirical studies investigated the effect of microtiming on the groove experience. Some reported that microtiming seemed to be of little importance for groove , 62, 63.Syncopation arises when accented notes are played on weak positions of the underlying metrical structure [tructure –72. Synctructure , 73 and tructure  showed ttructure , 74, whotructure  model detructure  monitoreBeat Salience, Event Density, Rhythmic Variability, Tempo: Four studies explored how selected audio features were associated with groove. In 2011, Madison et al. [n et al.  let listn et al.  who addin et al.  studied n et al.  found thhe 1950s , 40. TheListener-related factors and their association with groove have also been investigated in the past. But the role of these variables  differs across studies.Expertise: Listeners’ musical expertise was studied under the assumption that music expert listeners would be more sensitive to musical phenomena (like microtiming deviations or syncopation) than listeners with less expertise. Some studies concluded that listeners’ expertise did not influence the experience of groove within the context of their investigations [igations , 69, 73.igations , 67, 68 igations . In theiigations  observedTaste: Musical taste or style preference is a major topic in music psychology, and, generally, taste was found to be a good predictor for a listener’s aesthetic appreciation of music . The roiew, see  observediew, see  showed iFamiliarity: The relationship between groove ratings and listeners’ familiarity with the repertoire, from which the experimental stimuli were derived, was considered in several studies. Madison et al. [Familiarity with the stimuli and found that familiarity ratings were positively correlated with the groove ratings. Janata et al. [n et al.  asked paa et al. , in theia et al.  considera et al. , in theia et al.  found thProneness to dancing: Witek et al. [k et al.  showed iThis paper presents results from an online listening experiment in which participants assessed the groove quality of 248 popular music drum patterns. These patterns have been reconstructed from Western popular music recordings and represent a cross section of popular music drumming across several decades and styles.Temporal Regularity: Clayton [ Clayton  and coll Clayton  defined  Clayton ). FactorMotivation/Interest: Listeners may also be more or less motivated to entrain their body movements with music. Consequently, factors that increase listeners’ interest in the music and motivate entrainment are likely to be positively associated with groove. These factors, again, may be related to the stimuli  or to the listeners themselves .The paper studies the effect of fifteen stimuli- and participant-related predictor variables on the groove ratings. The choice of these variables was based on two ideas concerning the influence of the stimuli’s rhythmic properties on groove:Beat Salience, Event Density) or to musical methods for creating rhythmic interest .The music-related factors discussed in previous research either relate to the regularity of the stimuli  specifies that health-related studies must obtain approval by the regional Ethics Commissions . Our study is not a health study as defined by the law  and does therefore not require to be approved by the regional Ethics Commission.Participants gave informed consent and had the opportunity to give their e-mail-address in case they wanted to be updated about the study’s results or receive invitations to new surveys. E-mail addresses were stored separately from the experimental data in order to guarantee anonymity. No IP addresses were collected during the survey.Rolling Stone Magazine, Drummer World websites, or on similar resources). Additionally, we contacted nine professional drummers from our personal networks and from the Lucerne School of Music faculty. These experts belonged to different musical scenes, and they were asked to provide their personal list of the most important drummers in Western popular music.We compiled a list of fifty highly renowned popular music drummers, using the following selection method: drummer names were collected from approximately a dozen different drummer rankings presented on dedicated internet sources  appeared on most or even all of the lists; 62 names were mentioned at least five times. These 62 names were further reduced due to practical considerations, mostly connected to the subsequent selection of tracks and excerpts. This resulted in the final selection of 50 drummers who were included in the experiment.The selection of drummers showed extreme gender bias: only one female drummer was mentioned multiple times in any of the lists , but her name was mentioned less than five times, so she was not included in the final list. The male predominance in the sample is likely to be connected to an instrument selection bias (boys are much more likely to pick up the drums than girls), deeply rooted in Western society –94.It was not our intention to select the fifty “best” drummers in Western popular music. But we are confident that our selection unites drummers that have an excellent reputation throughout the field. They form a representative sample of highly competent musicians within the genres of rock, funk, R&B, pop, disco, soul, heavy metal and rock’n’roll.Supporting Information section  were likely to be chosen. We also consulted chart listings  and encyclopaedia entries about the drummers, their bands or bandleaders, searching for lists of influential tracks. If drummers had published records under their own name, we chose at least one track from these recordings. These tracks often feature particularly elaborate and non-generic drum patterns. The selection resulted in a list of 250 tracks, which is presented in this paper’s  section . The selFrom each of the chosen tracks, we selected an excerpt of eight bars. A core criterium for the selection of the passage was that the drummer played a consistent and at least partly repetitive rhythmic pattern (drum solos were excluded from the selection), and that the drum voice was well audible within the sound of the band. Since the tracks have different tempi, the resulting eight-bar selections also differed in duration.Transcribe! software (version 8.00.3). The transcribers attributed one of four loudness levels to each drum stroke by ear . They revised each others’ transcriptions and discussed differences between the transcriptions until they reached a consensus. The consolidated transcriptions were typeset in Finale (version 2014.5).Two researchers, who are also professional jazz musicians (a drummer and a saxophonist), independently transcribed the drum pattern for each of the 250 excerpts using the LARA (version 2.6.3), using spectrograms and oscillograms. The measurement accuracy was additionally checked by ear using LARA’s timing marker playback function. Onset measurement is estimated to be accurate to ±3 ms for most of the music excerpts. For a subset of 19 stimuli, onset detection was difficult, because either the drum stroke onsets were hard to identify against the background of the other voices, or the sound quality of the recording was compromised, which mostly occurred in older recordings. But even in these problematic cases, we expect the timing measurement error to rarely exceed ±10ms. The rhythmic patterns with instrumentation, timing, and dynamics data were exported from LARA as text files.The timing of each drum stroke onset was measured in MySQL (version 5.5.2.4) database. A MIDI file was created from each of the 250 rhythm patterns. The files represented the timing measurements exactly . The dynamic information with the four loudness levels was mapped onto MIDI velocity values with a separate mapping rule for each instrument of the drum set such that the resulting audio tracks sounded natural.The text files were uploaded to a Avid Pro Tools (version 12.1). One set of drum sound samples  was selected from the Toontrack Superior Drummer (version 2.4.4) Custom & Vintage audio samples library, and all stimuli were reconstructed using these samples. The sampled drum set was chosen to be neutral in the sense that it did not have sound characteristics that are typical for one of the styles, while sounding strange in the context of other styles.Subsequently, the 250 MIDI files were imported into Toontrack’s Latin Percussion library and also integrated into the stimuli using Pro Tools. Five stimuli featured hand claps that were not available in the Custom & Vintage and Latin Percussion libraries. The hand claps were recorded by the four researchers during an impromptu recording session in June 2016.In some patterns, additional percussion instruments  play an important role. They were chosen from Pro Tools in mp3 audio file format.Light reverberation was uniformly added to every audio reconstruction. This created the illusion that all stimuli were played on the same drum set and in the same room acoustics. The goal was to eliminate timbre as a variable from the stimuli as much as possible. The stimuli were exported from www.grooveresearch.ch.During the experimental run, we noticed that the tambourine had been forgotten in the reconstruction of Steve Gadd’s drum part for Paul Simon’s “50 Ways to Leave Your Lover.” A corrected version of this pattern and an additional reconstruction of another excerpt from the same tune was added into the pool of stimuli, expanding the number of stimuli to a total of 252. The stimuli can be downloaded under SoSci Survey (www.soscisurvey.de), a research platform for online experiments. Participants used a laptop or desktop computer and followed an internet link to start the experiment. All information and texts were presented in Basic English [The survey was created on  English  as far aOn the welcome page, participants were informed about the general purpose of the experiment , about the procedure of the survey, about data collection and anonymisation, and about the scholarly use of the gathered data. Participants then read a declaration of consent and expressed their consent by clicking a button. They answered a series of personal questions concerning their age, country of residence, gender, and musical experience. They indicated their musical taste by expressing their liking for 21 musical styles, using mouse-operated sliders on a 101-point Likert-type scale . Participants were told to leave the slider marker on the “No answer” box (default feedback), if they did not have an opinion on a style or were not familiar with it. The style preference questionnaire was a slightly adapted version of the Short Test of Music Preferences (STOMP) questionnaire , 96, 97.Participants were encouraged to use headphones throughout the experiment. They listened to one stimulus during the trial run and adjusted the loudness to a comfortable level. They completed two simple audiometry tests (counting triangle and bass drum sounds of different loudness) which indicated to the researchers whether the participant’s playback situation and equipment had been adequate for performing the listening test.Response Variables below), also on a 101-point Likert-type scale. By default, all sliders were set to a neutral position , and the extreme positions were labeled . Using radio buttons, participants indicated whether or not they thought they knew the band or song featured in the audio clip. And they guessed the musical style/genre of the clip from a genre list (ticking multiple choice boxes). This style list was identical to the list used to assess listeners’ style preferences, except that classical and modern art music were now omitted. When participants had completed their feedback to a stimulus, they were informed about the original recording from which the stimulus had been derived . Subsequently, participants had the option to either continue to the next music example, or to terminate their participation. On the final screen, participants were thanked for their contribution, and they could volunteer to give their e-mail address in order to be sent information about the study’s results or invitations to future surveys.Subsequently, participants proceeded to the experimental stimuli: a clip, randomly chosen from the 252 stimuli, was presented to the participant who gave a feedback about her/his experience while listening. Participants rated their agreement with six statements , the researchers invited people from their personal networks through e-mails and social media. Additionally, research managers and department chairs of music departments at Swiss and German universities were contacted and asked to distribute the invitation among their institutions’ students and academic staff. A media information about the project was sent out by the Lucerne University of Applied Sciences and Arts, which was published or mentioned over 50 times in the Swiss and German consumer press  and in the specialised press (drum magazines).These recruiting activities, the media reports in particular, triggered a large number of participations. As can be seen in the flowchart of Response Variables below), and the corresponding observations were removed from the data set. The data set used for analysis consisted of 8,329 observations on 248 stimuli, given by 665 participants. Each of the 248 drum patterns was rated by a mean of 33.6 participants.The mean groove ratings of 4 stimuli were statistical outliers (see s = 13.7). 194 of the participants declared to be professional musicians; 280 self-identified as amateur musicians; 179 stated to be music listeners. 317 participants stated that Switzerland was their country of residence, 279 indicated living in Germany, 51 individuals participated from other, predominantly European countries.Of the 665 participants, 145 were female, 511 male, 1 self-identified as a different gender, and 8 refused to answer. Participants had an age range between 18 and 77 years . Amateurs and listeners on the other hand had a high opinion of rock and rock-related styles, compared to the professionals.Participants’ mean style preferences are presented in Upon listening to a reconstructed drum pattern, participants used sliders to indicate their agreement with six statements related to the groove experience .The first item, S1 (“I would like to dance to this music.”), prompts participants to comment on their entrainment response while listening to a stimulus. With response S2 (“I like to listen to this music.”) participants signalled their pleasure or enjoyment while listening. Finally, response S3 (“This music is great for a party.”) invokes a social situation which is frequently associated with both dancing/entrainment and pleasure. Entrainment and pleasure are the core components of the canonic definition of groove in music psychology , 5.α = 0.81) load on one factor that represents 60% of the variance in the three variables. The Groove scale is defined as the first principal component of items S1, S2, and S3. It estimates the strength of participants’ groove experience and represents the primary outcome variable used in the analysis. The distribution of the Groove ratings was fairly symmetric (skewness γ1 = −0.263) and not excessively platykurtic (kurtosis γ2 = −0.427). As expected, the Groove scale was strongly correlated with S1, S2, and S3 , in which they subjectively assessed how easily they captured the beat in the stimuli. This variable operationalises participants’ ease of perceiving temporal regularities in the stimuli, outlined as a precondition for entrainment in the Introduction.The Beat Recognition and Groove was positive, as we would expect, but surprisingly weak . Potentially, this weak association was a consequence of participants’ general familiarity with the stimuli. Most of the participants lived in central European countries. We may expect them to know the Western popular music repertoire and to easily detect the beat. The empirical data seems to confirm this: the Beat Recognition ratings were negatively skewed (γ1 = −0.525), indicating that the participants generally had little trouble finding the beat in the stimuli. Thus, the necessary precondition for entrainment was satisfied most of the time.The Pearson correlation between Rhythmic Interest variable consists of participants’ responses to item S5 (“This music has an interesting rhythm”), in which they indicated the interest they experienced while listening to a stimulus. This variable operationalises the interest/motivation topic from the Introduction. As expected, Rhythmic Interest was positively correlated with Groove . This supports the notion from the Introduction that interest might create motivation in listeners to entrain to music. Rhythmic Interest was most strongly correlated with S2 (“I like to listen to this music”), the component of the Groove scale that is most related to pleasure . This makes sense in the light of recent neuro-scientific research, which found a close connection between pleasure and interest in aesthetic experiences [The eriences .Disturbance. This variable registered when participants became irritated by some aspect of a stimulus, and it can be understood as an indicator for poor stimulus reconstruction. The ratings of four stimuli , finally, form a control variable we called Groove, Beat Recognition, Rhythmic Interest, Disturbance) of the remaining 8,329 observations by 665 participants on 248 stimuli were z-standardised, i.e. centralised to a mean of 0 and scaled to a variance of 1.The four outcome variables  and by the rhythmic interest the music creates in them.The selection of this study’s fifteen predictor variables was guided by the two theoretical arguments outlined in the Tempo (in bpm) of a stimulus was derived from the model’s linear coefficient.Three tempo-related variables were calculated using quadratic regression models, which relate physical onset times (in seconds) and metrical onset times (in beats) for each stimulus. The initial Groove. This hypothesis has been confirmed in recent research by Etani et al. [Tempo and Groove has several facets: a good tempo for finger tapping might be too fast for the periodic movement of larger and heavier body parts, like bobbing the head or swaying the torso.Previous research showed that medium tempi around 100 bpm are particularly well suited for entrained behaviour like walking to music –104. Lisi et al. . Howeveri et al. , 106. ThTempo Change was derived from the tempo model’s quadratic term: this variable indicates how much the tempo slows down  or accelerates  across the stimulus. It is measured in beats per square minute (or bpm2). Tempo Instability is defined as the absolute value of Tempo Change: Tempo Instability increases with both stronger accelerando or ritardando. We expect higher Tempo Instability to decrease listeners’ sense of regularity in a stimulus, and we hypothesise that Tempo Instability is negatively associated with Groove.th Note Swing8 refers to the swing ratio on the level of the eighth note, which stands for the mean ratio between the durations of the onbeat and offbeat eighth notes [th Note Swing16 is a similar measure for the swing ratio between sixteenth notes. It was calculated if there were at least 32 offbeat sixteenth notes in the whole pattern, which was the case for 146 stimuli. Rhythms with greater swing ratios  are thought to improve the perception of the beat [Groove.Three measures of microtiming magnitudes were calculated for each stimulus: th notes , 107. Ththe beat  and, conResidual Microtiming magnitude, a grid of expected time positions was calculated using the quadratic tempo model (see Tempo and Tempo Change above) and the th Note8 and th Note Swing Ratios16 (if applicable). For each stimulus, the Residual Microtiming variable represents the density-adjusted standard timing deviation  of the  Madison . Accordi Madison , ResiduaBeat Salience was derived from the method described by Madison et al. [Beat Salience is a measure of how well the beat is audible in a stimulus, and we expect it to relate quite directly to listeners’ perception of temporal regularity. Consequently, we hypothesise that Beat Salience is positively associated with Groove, in line with previous research [Our method to measure n et al. . It is bresearch : the morEvent Density is the average number of drum strokes per beat. The number of strokes in a stimulus was counted on the basis of the transcription. High Event Density is likely to increase both listeners’ notion of temporal regularity (because listeners frequently obtain metric and rhythmic information) and the rhythmic interest created by the pattern [Event Density to be positively associated with Groove. pattern , 109. ThSyncopation was measured using a slightly modified version of the method presented by Witek et al. [k et al. , which ik et al. . Witek ek et al.  and a cok et al. ) attacheSyncopation was carried out according to the rules of Witek et al. [Syncopation variable, which is given as mean syncopation per beat and can be used independently from pattern length.The contributions of the bass drum and the snare drum to k et al. . We madeSyncopation, even though these voices were rhythmically varied in this study’s stimuli. Losing the contribution of the hi-hat to the syncopation variable is regrettable, but it can be justified to a certain extent: as can be seen in the transcriptions of The cymbals  were not considered for the calculation of Syncopation is an interesting factor with respect to the temporal regularity and interest/motivation topics: on one hand, we can expect Syncopation to add rhythmic interest to a drum pattern and therefore increase listeners’ motivation to move along with the music. On the other hand, we expect Syncopation to challenge listeners’ sense of the beat by definition and to undermine their perception of temporal regularity. Witek et al.’s idea that the relationship between Syncopation and Groove potentially follows a ∩-shaped Wundt curve may be understood as a conflicting influence of temporal regularity and interest. Patterns with low Syncopation show clear temporal regularity but may be boring to the listener, whereas patterns with high Syncopation are more interesting, but may confuse listeners’ sense of regularity and meter.th triplet and binary 32nd notes. A stroke on a drum or cymbal was coded in the matrix as a “1”, whereas an empty position was coded as “0”. The matrix was reshaped in several ways to form three-dimensional arrays with the third dimension representing sub-patterns of one, two, or four bars length. Distance measurements . We expect patterns with a shorter period to have greater temporal regularity than patterns with a longer period. Conversely, patterns with a longer period might be considered to be more interesting than patterns with a shorter period.The rhythmic information of each pattern given in the transcription was stored in form of a matrix. Dimensions of the matrix coded the different instruments of the drum set, and all possible metric positions to the level of the 16distance ) betweenRhythmic Periodicity category was additionally stored for each pattern as a measure of Rhythmic Variability: high mean distances indicate that the pattern changes a lot between the iterations of the one-, two-, or four-bar sub-patterns. A mean distance of zero means that the sub-pattern repeats identically in each iteration. Patterns with high Rhythmic Variability can be expected to show less temporal regularity and create more rhythmic interest than patterns with low Rhythmic Variability.The corresponding mean Jaccard distance among sub-phrases of the chosen Rhythmic Periodicity and Rhythmic Variability relate to Groove.We do not have a clear expectation how the two predictors Groove. Participants’ self-identification with either the professional musician, amateur musician, or listener groups constituted an Expertise predictor variable . We expect the professional musicians to have greater ease detecting temporal regularities in a stimulus compared to the amateur musicians, who in turn can be expected to detect regularities more easily than the listeners. Conversely, the professional and amateur musicians might more easily get bored with a simple rhythm, compared to the listeners.We tested three participant-related variables for their associations with Familiarity predictor variable (familiar/unfamiliar). Participants were not asked to prove their familiarity by writing down the song title or the band. We expect participants to be more motivated to entrain with a stimulus, if they have the impression to know the music .Style Bias, which represents how much a participant likes the style she/he thinks a drum pattern belongs to. This variable combines information from different parts of the survey: in the early stage of the experiment, participants rated their preferences with respect to 21 musical styles  is a novelty in groove research. Accordingly, we will take some care describing the definition of this variable and its categories in sufficient detail.Downbeat layer normally features the bass drum [The ass drum , 89. In Backbeat layer is often played on the snare drum [The are drum , 89, andPulse layer is usually played on the hi-hat cymbals or the ride cymbal [The e cymbal , 89, 90.At its core, a Western popular music drum pattern usually consists of three rhythmic layers:These three core layers may be complemented by other elements: in many patterns, the drummer plays fills (virtuoso gestures often played on tom drums) and crashed cymbal strokes to mark the end of larger formal units (mostly 4-bar or 8-bar units). Additional percussion instruments may lend a special flavour to a pattern. Sometimes, these percussion instruments are played by additional musicians, whereas the fills and cymbal accents are played by the drumset player himself.Pattern Category variable classifies the drum patterns according to the properties of the three core rhythmic layers using a semi-automatic, iterative classification method that is based on calculating the proportion of off-beat positions played in the respective layer. As a result, each pattern is assigned to one category in each layer.The Downbeat layer: the D1 generic category unites patterns, in which the bass drum quite exclusively plays the two downbeats of the bar (beats 1 and 3), and nothing else. In the D2 four to the floor category, the bass drum plays on all four beats. Patterns in the D3 eighth and D4 sixteenth categories show a substantial proportion of off-beat eighth and sixteenth notes, respectively. A few patterns did not meet the threshold of any category. They ended up in a catch-all category that will not be used in the analysis. The categories can broadly be defined by the metric grid they require in notation: patterns in the D2 four to the floor category can be notated with quarter notes only; for those in the D3 eighth category, an eighth note grid must be used; and patterns in the D4 sixteenth category require a sixteenth note level.There are four options for the categorisation of a pattern’s Backbeat layer: in the B1 generic category, both backbeats (on 2 and 4) are played, but not much else. Denser rhythmic snare drum patterns were assigned to the B2 quarter, B3 eighth, and B4 sixteenth categories. Finally, there were three categories for the Pulse layer: P2 quarter, P3 eighth, P4 sixteenth.The categorisation procedure was similarly and independently carried out for the In theory, there are 48 possible feature combinations, see Pattern Category variable, each representing a specific combination of Downbeat, Backbeat, and Pulse features. Downbeat in the bass drum with strokes on beats 1 and 3 (D1). The “Billie Jean” pattern also features a generic Backbeat with snare drum strokes on beats 2 and 4 of the beat (B1), and an eighth-note based Pulse in the hi-hat (P2). The transcriptions of We defined these eleven large groups to be the eleven categories of the Groove ratings for all 248 stimuli as a function of their recording year. Each symbol shape encodes the Downbeat category, while the symbol colour denotes the Backbeat layer, and the symbol size represents the category of the Pulse. The “archetypical rock pattern,” for example, is represented by medium-sized blue triangles. It can be seen that, in our sample, it shows up frequently during the rock’n’roll era of the 1950s up to the 1980s.Backbeat on beats 2 and 4 (B1), and eighth note patterns in the Downbeat layer (D3). These patterns are frequently associated with rock: examples are Ian Paice’s drum pattern on Deep Purple’s “Highway Star” , Stewart Copeland’s pattern on the Police hit “Roxanne” , or Neil Peart’s pattern on Rush’s “Far Cry” .Each of the eleven pattern categories is loosely associated with specific styles: the blue crosses, for example, stand for patterns with a generic Backbeat layer based on a sixteenth note grid (B4) is typical for funk drum patterns; these patterns are represented as red symbols. Clyde Stubblefield’s pattern on James Brown’s “Cold Sweat”  shows this kind of Backbeat, but also Billy Martin’s highly elaborate and dense pattern on “Jelly Belly” , or Billy Cobham’s drum pattern on “Now That You’ve Gone” . As can be seen in A complex, syncopated Backbeats (B1) and a bassdrum kick on every quarter note  are typical for disco, and they are represented in Patterns with generic Downbeat layer (D4) but a generic Backbeat (B1) are often associated with rap or hip hop (blue stars). A typical example is Questlove’s drum pattern for D’Angelo’s “Chicken Grease” . However, funk/soul tracks may also feature this kind of drum pattern, like Bernard Purdie’s pattern on “Soul Clappin’” .Patterns with a complex sixteenth-note-based Pattern Categories with a total of 200 stimuli were used as a categorial predictor for Groove. Note that the remaining 48 stimuli are represented in Downbeat/Backbeat/Pulse combinations span the whole post-war era until today, and the whole range of Groove ratings. In fact, the pattern with nominally the highest Groove ratings throughout the entire experiment  belongs to one of these rare combinations.The eleven Pattern Categories that allow for fine subdivisions of the beat to offer opportunities for original and/or complex rhythm. We anticipate that, in general, patterns with sixteenth note subdivisions in one or more of the layers are rhythmically interesting and therefore obtain high Groove ratings. Conversely, we expect participants to more easily perceive temporal regularities when listening to stimuli with generic Downbeats and Backbeats, which in turn might also affect the Groove ratings positively.We expect R (version 3.3.1), and RStudio (version 1.0.136). Data visualisations and plots were created with the R library ggplot2 (version 2.2.1). The significance level was set to α = 0.05.The statistical analyses were carried out using Groove is estimated. There will be no attempt at creating one comprehensive model that integrates all relevant effects. Such an attempt would be futile due to a number of problems: some predictors only have valid values for a subset of the observations, and group sizes are unbalanced. In some cases, however, the joint effect of two or more variables is analysed in order to investigate interactions and dependencies between predictors. Only significant interactions will be reported in the Results section.The analysis offers an overview of the relative effects of the fifteen predictor variables. Each predictor is primarily studied on its own, and its isolated effect on η2. Group sizes are almost always unbalanced, but according to [R2. Following rules of thumb formulated by Cohen [η2 = 0.01 to be small, η2 = 0.06 represents a medium effect, and effects of η2 = 0.14 and greater are large. Note that both, η2 and R2, give the effect size as a proportion of explained variance and are hence comparable with each other.Effects of categorial variables are measured using analysis of variance, and corresponding effect sizes are given as rding to , a lack by Cohen  and Mileby Cohen , we consGroove ratings that are explained by the fifteen predictor variables. No statistically significant effect on Groove was measured for Beat Salience, Residual Microtiming or Pattern Variability.The effect sizes given in Tempo Change, Tempo, Expertise, th Note Swing16, th Note Swing8 and Tempo Instability were statistically significant, but tiny. Tempo Instability seems to be negatively associated with Groove, indicating that participants had a slight tendency to give higher Groove ratings to stimuli with stable tempo, compared to stimuli with either accelerating or decelerating tempo. Also, th Note Swing16 appears to be positively related with Groove, whereas th Note Swing8 was negatively associated with Groove: participants indicated that a stronger shuffle on the sixteenth-note level was weakly positive for Groove, whereas the shuffle on the eighth-note level was negative.Effects of Tempo and Groove was minuscule and negative. We observed no convex, curved relationship suggesting the existence of an optimal tempo for groove . HoweveSyncopation measurements was positively skewed (γ1 = 0.924). The distribution became approximately symmetric (γ1 = 0.153) after a square root power transformation. Syncopation was positively correlated with Rhythmic Interest (r = 0.381) and negatively with Beat Recognition (r = −0.168). This supports our assumption that Syncopation makes a drum pattern more interesting to the listeners, but it makes it more difficult to keep track of the beat.Across the sample of stimuli, the distribution of Event Density was positively skewed (γ1 = 0.656). This distribution was made more symmetric using a log-transformation prior to the analysis (γ1 = 0.039). Event Density was positively correlated with Rhythmic Interest (r = 0.302), but it was unrelated to Beat Recognition (r = −0.080). This confirms our assumption that a more dense rhythm is likely to be perceived as more interesting. However, unlike assumed earlier, rhythmic density does not seem to affect listeners’ beat recognition.Similarly, Syncopation and Groove (R2 = 0.010), and between Event Density and Groove (R2 = 0.011). The relationships can be inspected in Groove ratings for each stimulus, whereas the grey dots in the background represent single observations.There were weak associations between Groove were positive: Groove ratings tended to increase as Syncopation or Event Density increased. In either case, quadratic models did not have a significantly better fit with the data than simple linear models.For both predictors, the associations with Syncopation and Event Density were mutually positively correlated (r = 0.500) with each other. Their combined effect (R2 = 0.013) on Groove is only slightly larger than the effect of each variable alone. We conclude that the two variables share much of their explanatory power for Groove. . Specifically, Syncopation had the strongest positive effect on professional musicians , a smaller positive effect on the amateur musicians , but no significant effect on the music listeners (p = 0.612).Expertise explains only very little of the Groove ratings’ variance . The effect of Event Denstity was very small and positive for both the listener  and amateur  groups, but much larger and positive for the professionals . The combined effect of Syncopation, Event Density, and Expertise accounted for a total of 2.0% of the variance in the Groove variable (R2 = 0.020).A similar interaction can be observed for Pattern Category was measured on the basis of a subset of the data that had been assigned to one of the eleven large Pattern Categories . On its own, the Pattern Category variable explained 1.8% of the Groove variance (η2 = 0.018), slightly more than Syncopation and Event Density combined. In general, Pattern Categories with a 16th-note based Backbeat  or Pulse layer  had a tendency to obtain a higher Groove response than their 8th-note- or quarter-note-based counterparts.The effect of Beat Recognition and Rhythmic Interest values are given in Pattern Category. We observe that mean Groove ratings are positively associated with mean Rhythmic Interest: categories with interesting patterns have also a tendency to be rated high on Groove. The association between mean Beat Recognition and Groove seems to be inverted: categories with easily understood patterns obtained lower mean Groove ratings than categories in which the beat was harder to track.Mean D2 B1 P4 category (large blue squares): the small group of patterns with a four-to-the-floor Downbeat, a generic Backbeat and sixteenth notes in the Pulse . The interaction of the two predictors can be studied in Pattern Category had a substantially greater effect on the professionals (η2 = 0.054) than on the amateurs (η2 = 0.011) or listeners (η2 = 0.015).We measured a significant and quite sizeable interaction effect between professionals gave high Groove ratings to stimuli based on a sixteenth-notes grid in at least one of the rhythmic layers; their ratings peaked when all three layers of a pattern were based on sixteenth-notes (D4 B4 P4). These patterns were also those with a tendency to show high Syncopation and Event Density values  and to the only pattern category with a quarter-note based Pulse, D3 B1 P2 , that is frequently used in rock and heavy metal.listeners were in many respects complementary to the professionals’ ratings. In general, listeners gave lower Groove ratings to the rhythmically more complex patterns with 16th-note based Downbeat and Backbeat layers, compared to the professionals. Conversely, listeners had a tendency to give relatively high ratings to categories with simple patterns, for example, the “archetypical rock pattern” D1 B1 P3 (medium blue triangle), and the disco beats D2 B1 P3 (medium blue squares) and D2 B1 P4 (large blue squares).The ratings of those participants who self-identified as mere music Familiarity variable had a small-to-medium effect on the Groove ratings  obtained mean Groove ratings of 0.433, whereas the 6,549 unfamiliar observations had lower mean Groove ratings of −0.118. Participants considered the familiar patterns to also raise more Rhythmic Interest (0.162), compared to the unfamiliar patterns (−0.044). Participants further indicated that Beat Recognition was easier in familiar (0.268) compared to unfamiliar patterns (−0.066).The binary Style Bias, was positively associated with the Groove ratings (r = 0.351) and had a medium to large effect on Groove (R2 = 0.123). Style Bias was uncorrelated with Beat Recognition (r = 0.024), but positively associated with Rhythmic Interest (r = 0.262). So, participants gave high Groove ratings to stimuli they thought belong to a style they like, and they considered these patterns to be rhythmically interesting.Familiarity and Style Bias qualifies as a large effect (R2 = 0.152) according to guidelines concerning the interpretation of effect sizes [Syncopation or Event Density by a factor of approximately 15.The combined effect of ct sizes , 114. ThFamiliarity and Style Bias can be studied in Groove as a function of Style Bias. Observations on stimuli that were unfamiliar to the participants are printed as small orange dots, whereas the observations on familiar stimuli are presented as small purple dots. .The effects of Familiarity categories. The main effect of Familiarity shows in the offset between the two linear models: when participants thought “that they might know the band or the piece” (familiar) they had a tendency to give high Groove ratings (purple regression line). Conversely, unfamiliar stimuli obtained lower Groove ratings in the mean (orange regression line). Style Bias shows in the models’ slopes: participants rated stimuli high on Groove if they thought it belonged to a style they liked , and low if they disliked the style (low Style Bias).Linear regression models were fitted to the data, split according to the two Familiarity and Style Bias are not independent from each other: observations on familiar stimuli have a higher mean Style Bias (large purple dot in unfamiliar stimuli (large orange dot). This is no surprise: listeners are more likely to know a song or band from a style they appreciate (and presumably listen to more often) compared to a style they do not like.Expertise as a third participant-related predictor did not significantly improve the model fit. The effect of Style Bias and Familiarity on Groove does not seem to depend on the Expertise of the participants.Including Groove experience as a response to listening to reconstructions of Western popular music drum patterns. Fifteen stimuli- and participant-related variables were investigated as potential predictors for Groove. Most predictors were either related to participants’ perception of temporal regularities in the stimuli (which is thought to be a necessary condition for entrainment) or to the rhythmic interest triggered in the participants by the stimuli (which might in turn motivate bodily entrainment).This study measured the strength of participants’ Groove  were also positively associated with Rhythmic Interest. Listeners’ interest triggered by the music apparently was a relevant catalyst for groove.The results showed that the strongest predictors for Beat Recognition played a less important role in the study. This, however, does not mean that the perception of temporal regularities is irrelevant for groove: in this study, participants had a predominantly central European background, many of them were amateur or even professional musicians. Under these circumstances we can expect participants to easily grasp the temporal regularities of the music, and the precondition for entrainment (listeners understanding of these regularities) is generally satisfied.Variables chosen due to their relation to Groove: Residual Microtiming , Beatrast to ), PatterSyncopation and Groove: more syncopated drum patterns had a tendency to obtain higher Groove ratings. This result resonates with the findings of Madison & Sioros [Syncopation was positively associated with Groove. We have found evidence for an interaction between musical Expertise and Syncopation: for professional musicians, the positive correlation between Syncopation and Groove was greater than for amateur musicians; and the listeners’ ratings were not affected by Syncopation.We observed a generally positive relationship between & Sioros  and Sior& Sioros  who alsoSyncopation and Groove might best be described by a ∩-shaped, curved model predicting a maximum Groove response for an intermediary level of Syncopation, and a lesser response for stimuli with either more or less Syncopation. Our data does not support this result: we found little evidence that a curved quadratic model with a maximum at a medium level of Syncopation had a better fit with the data than the simple first-order linear model.In their 2014 study, Witek et al.  hypothesSyncopation (R2 = 0.010) on Groove than Witek et al. They measured R2 = 0.347 for their Move response variable and R2 = 0.427 for Pleasure . ance see , leavingSyncopation as explanatory variable. Syncopation accounted for 15% of the variance among the 248 stimuli’s mean Groove ratings (R2 = 0.145). This amounts to a bit less than half the effect that Witek et al. [Move variable, and about a third of the effect they measured for Pleasure.In order to compare our results with those reported by Witek et al. , we carrEvent Density was positively associated with Groove, which confirms previous findings by Madison et al. [Event Density obtained higher Groove ratings, because they sounded fuller and more complete.n et al. . PotentiEvent Density (similar to Syncopation) was substantially moderated by musical Expertise: music professionals’ Groove ratings reacted more positively to stimuli with high Event Density, compared to the ratings of the amateur and listener groups. As in the case of Syncopation, Event Density does not seem to be a universal musical factor that increases the Groove experience for all (or at least most) listener groups. Rather the effect of Event Density depends on Expertise, a participant-related factor.The effect of Pattern Category variable accounts for certain aspects of a drum pattern’s musical composition or arrangement. These features are by far more basic than the properties described in the musicological and ethnomusicological literature on the structure of “grooves” as multi-layered rhythmic patterns [Pattern Category predictor explained a non-negligible portion of the variance in the Groove ratings. This indicates that it might be worthwhile studying aspects of composition and arrangement more thoroughly in order to better understand musical factors influencing the groove experience.The patterns , 12, 14.Expertise plays a relevant moderating role: music professionals had a tendency to give high Groove ratings to Pattern Categories that allow for greater rhythmic complexity  seem to depend on Expertise.The moderating effect of Familiarity and Style Bias on the experience of Groove: people gave high groove ratings to music they thought they knew and to music they thought belongs to a style they liked.We measured relatively large effects of Groove response agrees with common sense. It is reasonable to assume that listeners’ susceptibility to bodily entrainment as a response to music is strengthened when the music agrees with their taste. Since listeners’ activities and preferences differ substantially, it is no surprise that the same stimulus might trigger diverse groove reactions in different people. Consequently, we would expect listeners’ Style Bias to play a role in moderating their groove response.The notion that listeners’ musical taste affects their Familiarity with a stimulus is relevant to its Groove effect. In a recent study, Madison & Schiölde [Familiarity with a stimulus, our data suggests that a similar claim holds for Groove.Also, we may expect that listeners’ Schiölde  showed tGroove than the most relevant music-related factors in the study. The combined participant-related effects of Style Bias and Familiarity (R2 = 0.152) exceeded the largest purely stimuli-related factor  by almost a magnitude.Yet, it came as a surprise that these two listener-related factors were so much more important for Style Bias and Familiarity on Groove might be even stronger when participants are confronted with the original recordings.This was even more surprising considering that the stimuli consisted of drum pattern reconstructions only. The stimuli lacked much of the musical information  that helps participants recognise the music and its style. We must assume that participants had only weak style associations while listening to the reconstructed drum patterns. These associations are likely to be stronger when participants are confronted with the original music, which offers more explicit clues to associate a stimulus with a song or a style. Hence, the effects of Groove and the Style Bias and Familiarity variables. .Familiarity, Style Preference, and Expertise) have not been considered in this study, yet they probably have a considerable impact on groove: listeners’ positive attitude to dancing (or other activities that require bodily entrainment) is likely to coincide with a strong groove response, as shown by Witek et al. [Two further listener-related factors  seem to contradict each other. The studies used different methodologies and investigated different repertoires, which might account for some of the discrepancies. But the studies also sampled their participants from different populations with specific cultural backgrounds. The differences among the surveyed populations might additionally account for a relevant portion of the discrepancies.Groove research, including our own, has investigated a multitude of potential factors that influence groove. Many results , and discuss the effect of style-specific musical properties within these groups.Conversely, if a study investigates whether a factor has an universal effect in a more general population, it might be necessary to stratify the sample of participants according to proportions in the target population for better representativeness.S1 Table(XLSX)Click here for additional data file.


This efficiency is 2.6 times higher than that of the device based on the conventional red exciplex emitter, proving the superiority of our novel strategy to construct TADF exciplexes with phosphors.Exciplexes are ideal candidates as effective thermally activated delayed fluorescence (TADF) emitters. However, efficient orange and red TADF exciplexes have been reported seldomly, because their significant non-radiative (NR) decay of excited states lead to unavoidable energy loss. Herein, we propose a novel strategy to construct efficient red TADF exciplexes by introducing phosphor as one component. Due to the strong spin–orbit coupling of heavy metal  ion cores, the NR decays will be evidently decreased for both singlet and triplet excitons, reducing the undesired exciton waste. Moreover, compared with the conventional exciplexes, phosphorescence plays an important role for such novel exciplexes, further improving the exciton utilization. Based on this strategy, we fabricated a red exciplex containing 1,3,5-triazine-2,4,6-triyl)tristris(diphenylphosphine oxide) (PO-T2T) and tris(2-phenylpyridine) iridium(III) (Ir(ppy) By using high-T1 component molecules to avoid the triplet excitons loss, exciplexes commonly exhibit TADF characteristics. In the past few years, great progress has been made for exciplex-based TADF OLEDs  based on thermally activated delayed fluorescence (TADF) emitters are considered the new generation of OLEDs Adachi,  and have1 to T1 and phosphorescent decay from T1 to S0], allowing heavy metal complexes to achieve phosphorescence efficiently  as components, which exhibits typical TADF characteristic with an extremely small ΔEST of 0.026 eV. In device, PO-T2T:Ir(ppy)3 exciplex shows a red emission with a peak at 604 nm and a CIE coordinate of , and realizes a high maximum external quantum efficiency (EQE) of 5%. As a comparison, the conventional TADF exciplex consisting of PO-T2T and 1,3-di(10H-phenoxazin-10-yl)benzene (13PXZB) only achieves a maximum EQE of 1.9% in device. These results not only demonstrate exciplexes can also be formed by using a phosphor component, but also indicate that the NR decays of excited states can be significantly suppressed for phosphor-based exciplexes by the SOC effect of heavy metal ion core from phosphor. Although noble metal Ir is contained in our system, we believe efficient but low-cost phosphor-based exciplex emitters can be developed by using other cheap heave metal-based phosphors, like Cu, et al.In this study, we proposed a novel strategy to construct efficient red exciplexes by introducing a phosphor as one component. As we known, phosphors are generally heavy metal complexes. The spin–orbit coupling (SOC) of heavy metal  ion cores will significantly enhance the energy transfer processes between singlet and triplet states  (TAPC) and PO-T2T are respectively used as the hole-transporting layer (HTL) and electron-transporting layer, ITO (indium tin oxide) and LiF/Al work as the anode and the cathode, respectively. A thin layer of 10 nm 13PXZB is inserted between HTL and the emitting layer (EML) aiming to avoid additional exciplex formed between TAPC and PO-T2T. The doping concentration of 13PXZB in EML is optimized to 40 wt% for Device 1. As shown in −2) of 2.5 V and stable red EL emission at different luminances with a peak at 592 nm and a CIE coordinate of , indicating that we have successfully constructed a red exciplex with a conventional material system of PO-T2T and 13PXZB. However, the maximum current efficiency (CE), power efficiency (PE), and EQE of Device 1 are only 4.2 cd A−1, 2.0 lm W−1 and 1.9%, respectively. Such low device efficiency should be ascribed to the evident NR decays of S1 and T1 states for conventional red exciplexes.To evaluate the electroluminescence (EL) performance of the two exciplex, both PO-T2T:Ir(ppy)3 are electron transporting materials. As shown in 3 is significantly better than its hole transporting capacity. Thus, an electron-blocking layer (EBL) is needed to benefit carrier recombination in the device. We first constructed Device 2 with a structure of ITO/TAPC (35 nm)/mCP (10 nm)/PO-T2T:x wt% Ir(ppy)3 (30 nm)/PO-T2T (45 nm)/LiF (1 nm)/Al (100 nm). 3-bis(9H-carbazol-9-yl)benzene (mCP) is used as EBL due to its unipolar hole transporting capacity. And the doping concentration of Ir(ppy)3 is optimized to 8 wt%. However, as shown in 3. This phenomenon is consistent with the PL spectrum as shown in 3 and PO-T2T:Ir(ppy)3. In Device 2, the excitons are generated at the interface of mCP/PO-T2T:Ir(ppy)3. Beyond PO-T2T:Ir(ppy)3, the excited states of mCP:PO-T2T exciplex is also unavoidably generated. The energy of mCP:PO-T2T exciplex is around 2.63 eV 3. The competition between Ir(ppy)3 and PO-T2T:Ir(ppy)3 should be leaded by the energy transfers from mCP:PO-T2T to Ir(ppy)3 and PO-T2T:Ir(ppy)3.Different from PO-T2T:13PXZB exciplex, both PO-T2T and Ir(ppy)3 should be suppressed. Thus, we designed an optimized a device structure by changing mCP EBL to 13PXZB. At the 13PXZB/PO-T2T:Ir(ppy)3 interface, the excited states of PO-T2T:13PXZB can also generate. But the energy of PO-T2T:13PXZB is in between that of Ir(ppy)3 and PO-T2T:Ir(ppy)3, which can prevent the exciton harvest of Ir(ppy)3and thus suppress the green emission. To further prove this point, we also fabricated a device with a structure of ITO/TAPC (35 nm)/13PXZB (10 nm)/PO-T2T (75 nm)/LiF (1 nm)/Al (100 nm) (Device 3). As shown in −1 for CE, 2.9 lm W−1 for PE and 1.6% for EQE. The reason is that Ir(ppy)3 cannot harvest the excitons from the red exciplex PO-T2T:13PXZB.To avoid the harmful green emission, the exciton harvest of Ir(ppy)3 exciplex, Device 4 was finally constructed with a structure of ITO/TAPC (35 nm)/13PXZB (10 nm)/PO-T2T:x wt% Ir(ppy)3 (30 nm)/PO-T2T (45 nm)/LiF (1 nm)/Al (100 nm). And the optimized doping concentration of Ir(ppy)3 in EML is also 8 wt%. As shown in 3 nearly disappeared in the spectra, indicating the feasibility of our device optimization. As shown in 3 exciplex, but also effective energy transfer is proved from PO-T2T:13PXZB to PO-T2T:Ir(ppy)3. As listed in −1, 11.6 lm W−1 and 5%, respectively. Such high EQE is 2.6 times and 3.1 times higher than that of Device 1 and 3, respectively. And EQE value of 5% is the highest result for red TADF OLEDs based on exiplex emitters. Considering both PO-T2T:13PXZB and PO-T2T:Ir(ppy)3 possess the same PLQY value of about 4% under triplet excitons quenched condition, the evident efficiency difference between Device 1, 3, and 4 indicates much higher triplet exciton utilization of PO-T2T:Ir(ppy)3, which should be ascribed to the beneficial effect of heavy metal ion core in the phosphor component. The SOC effect of heavy metal ion core can not only effectively suppress the NR decays of excited states for red TADF exciplexes, but also induce phosphorescence and make great contribution to EL emission. Our study provides a novel approach to develop efficient red TADF exciplexes with phosphors.Thus, for PO-T2T:Ir(ppy)3 is constructed accordingly, which exhibits high maximum efficiencies of 9.3 cd A−1 CE, 11.6 lm W−1 PE, and 5% EQE in the device. Such high EQE is 2.6 times higher than that of the device based on the comparative conventional red TADF exciplex PO-T2T:13PXZB and the best performance among reported red TADF OLEDs based on exciplex emitters. These results not only provide a new pathway to develop efficient exciplex emitters with vast phosphors, but also demonstrate the superiority of phosphor-based exciplexes.In summary, we present a novel strategy to construct efficient red TADF exciplexes by introducing phosphor as one component. The SOC effect of heavy metal ion core in phosphor can suppressed the NR decays of excited states and induced phosphorescence makes great contribution to total emission, thus improving the exciton utilization. Red TADF exciplex PO-T2T:Ir(ppy)C-JZ and X-HZ designed whole work. MZ, KW, and Y-ZS characterize the physical properties of compounds. MZ, KW, and HL fabricated and optimized the devices. D-QW and XL synthesized the new organic compound. MZ and KW wrote the paper with support from C-JZ, S-LT, and X-HZ. All authors contributed to the general discussion.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.


The BSA-IrO2 NPs exhibits uniform size (40 nm), superb biocompatibility and high drug loading capacity for doxorubicin (27.4 wt%). Under near-infrared (NIR) laser irradiation, the as-prepared BSA-IrO2 NPs exhibited high photothermal conversion ability (54.3%) and good photostability. The in vitro drug release experiments displayed pH and NIR laser -triggered DOX release profiles, which could enhance the therapeutic anticancer effect. By utilizing this DOX loaded nanoplatform, effective synergistic chemo-photothermal therapy against human osteosarcoma can be realized, which has been systematically verified both in vitro and in vivo. Notably, in vivo pharmacokinetics studies showed that BSA-IrO2@DOX had prolonged blood circulation time due to the BSA component can improve the stealthiness of the nanoparticles during the blood circulation. Meanwhile, in vitro and in vivo toxicity studies demonstrated that the BSA-IrO2 NPs can act as biocompatible agents for drug delivery and cancer therapy. Therefore, this work presents a biomineralized iridium-based NPs with remarkable features and be used as a very potential therapeutic nanoplatform for cancer treatment.Protein-based nanocarriers with inherent biocompatibility have been widely served as building blocks to construct versatile therapeutic nanoplatforms. Herein, bovine serum albumin-iridium oxide nanoparticles (denoted BSA-IrO Cancer becomes one of the primary hazards to human health worldwide. With the developments in our understanding of cancer biology, tremendous effective methods have been extensively explored for cancer therapy, including chemotherapy, radiotherapy, and surgery  NPs by using albumin as both a sulfur donator and a template  with BSA in alkaline conditions. In this process, Ir3+ would be anchored to BSA to form albumin-Ir complexes through the affinity of the active groups (amino and carboxy groups) of BSA toward metal ions. Subsequently, the pH value of system was adjusted to ∼12 with NaOH and Ir3+ is oxidized into IrO2. The resultant BSA-iridium oxide nanoparticles (BSA-IrO2 NPs) were then used as a drug nanocarrier to load chemotherapeutic agent doxorubicin (DOX) for chemotherapy. Meanwhile, the BSA-IrO2 NPs can be also served as photothermal agents for cancer PTT due to their superior photothermal conversion efficiency of BSA-IrO2 NPs (54.3%). Based on this, the as-prepared BSA-IrO2@DOX NPs were then used as a therapeutic nanoplatform for cancer chemo-photothermal synergistic therapy -based biomineralization strategy by incubating iridium ion (Ir therapy . The com3) was acquired from Aladdin Reagent Co. . Doxorubicin hydrochloride , phosphate buffered saline (PBS), fetal bovine serum (FBS), calcein acetoxymethyl ester  and propidium iodide (PI) were obtained from Sigma-Aldrich . Cell counting lit-8 (CCK-8) was ordered from Dojindo Laboratory . Dulbecco’s modified Eagle medium (DMEM), penicillin, and streptomycin were obtained from Gibco . The Human osteosarcoma cancer cell line (Saos-2 cells) and A549 cells were obtained from the Institute of Basic Medical Sciences Chinese Academy of Medical Sciences . Milli-Q water was prepared using a Milli-Q system . All chemicals were used as received without further purification.Bovine serum albumin (BSA) and sodium hydroxide (NaOH) were purchased from Sinopharm Chemical Reagent Co., Ltd . Iridium trichloride  was dissolved in 4 mL of deionized water. Then, 10.0 mL of solution A and 2.0 mL of solution B were mixed adequately and stirred for 30 min. Subsequently, a certain volume of NaOH solution (2.0 M) was introduced to adjust the pH of the mixture to ∼12, and the mixture was stirred at 80 °C. After 12 h reaction, the solution was dialyzed (membrane cutoff Mw: 100 KD) against deionized water for 48 h to remove excess precursors. Finally, the mixture was freeze-dried, harvested and re-dispersed in 10 mL of water for further use.BSA-IrO2@DOX NPs were fabricated by the absorption method. 5 mg of BSA-IrO2 NPs were dispersed into 10 mL of phosphate buffer saline (PBS) and then different concentrations of DOX solution (0.2–1.0 mg/mL) were mixed. After stirring for 24 h under dark condition at room temperature, the resulting BSA-IrO2@DOX NPs were collected by centrifugation and the product was washed with PBS repeatedly to remove the excess DOX. Meanwhile, the supernatant was collected and measured by UV-Vis spectroscopy at 490 nm. The DOX loading capacity (LC) was calculated as: /the amount of BSA-IrO2.BSA-IrOThe morphology of NPs was observed by JEOL-2100 transmission electron microscopy . UV-1800 Spectrophotometer was used to record UV-vis absorption spectra with a 1 cm cuvette . An IR Prestige-21 spectrometer was used to record the Fourier transform infrared (FTIR) spectrum . X-ray photoelectron spectras (XPS) were measured with EscaLab 250Xi electron spectrometer from VG Scientific using 300 W Al Kα radiations . The hydrodynamic diameters and Zeta potential were conducted on Malvern Zetasizer Nanoseries . The content of Ir was detected by inductively coupled plasma-atomic emission spectroscopy . Thermal images were also captured with the TI100 infrared thermal imaging camera .2 NPs, 0.2 mL of BSA-IrO2 NPs PBS aqueous solutions with different concentrations (Ir: 0.5–6 mM) were introduced into a centrifugation tube and fixed on a retort stand. All samples were irradiated with an 808 nm NIR laser  at power density of 1.0 W cm−2 for 5 min. Also, the BSA-IrO2 NPs dispersion at Ir concentration of 3 mM was exposed with a different power density  over a period of 5 min. The temperature changes of dispersion were recorded using a digital thermometer  and infrared thermal imaging camera. Meanwhile, the thermal stability of BSA-IrO2 was evaluated by irradiating for 5 min each time with five on-off cycles. Also, the photothermal conversion efficiency (η) of BSA-IrO2 NPs was calculated by the previous methods  in PBS buffers was divided into four groups: (a) pH 5.0 in dark, (b) pH 7.4 in dark, (c) pH 5.0 and (d) pH 7.4 with irradiation  at different time intervals . At the indicated time interval, 0.2 mL of NPs suspension was taken out, centrifuged at 10000 rpm for 10 min and equal volume of PBS was added to the system again. The cumulative amount of released DOX from the BSA-IrO2@DOX was determined according to the UV-Vis absorption of DOX at 490 nm in the supernatant. All the release experiments were repeated three times.To investigate the pH and NIR laser promoted DOX drug release, the dispersion of BSA-IrO2 at 37 °C. To evaluate the cytotoxicity of BSA-IrO2 NPs, Saos-2 and A549 cells (5000 cells/well) seeded in 96-well plates and incubated for 24 h. Subsequently, the old culture medium was replaced with fresh culture medium (200 μL) containing different concentrations of BSA-IrO2 NPs  and incubation for another 24 h. The cells were washed with PBS for three times and the cell viability was determined by using the CCK-8 proliferation assay according to the manufacture’s protocol.Saos-2 and A549 cells were incubated in DMEM medium supplemented with 10% FBS and 1% antibiotics (penicillin-streptomycin), and cultured in a humidified atmosphere with 5% CO2@DOX was evaluated by confocal laser scanning microscopy (CLSM), flow cytometry and ICP-AES analysis. For CLSM, Saos-2 cells were seeded into confocal culture dish with a density of 5 × 105 cells/mL−1 and incubated for 24 h, followed by the addition of BSA-IrO2@DOX or free DOX (DOX: 5 μg mL−1) with or without 5 min laser irradiation (after 2 h incubation) and an incubation for another 6 h. After that, the cells were washed with PBS and stained with DAPI (2 μg mL−1) for 20 min. The fluorescent images were obtained by using a CLSM . For the flow cytometry analysis, Saos-2 cells were seeded in glass-bottom culture dishes (1 × 105 cells per dish) for 24 h, followed by the addition of free DOX and BSA-IrO2@DOX at a DOX concentration of 5 µg mL−1 with or without 5 min laser irradiation (after 2 h incubation) and an incubation for another 6 h. Afterward, the cells in all groups were digested with trypsin, followed by centrifugation. After washing by PBS and resuspending in PBS, the intracellular fluorescence of DOX was studied by using a FACScan flow cytometry . Furthermore, half of the cells were washed, trypsinized, and digested by 1 mL of aqua regia overnight and diluted with 1 mL of water. Then, the intracellular Ir content in every cell samples was determined by ICP-AES assay.The cellular uptake of BSA-IrO2@DOX NPs, Saos-2 cells were seeded in 96-well plates (1 × 104 cells/well) and incubated for 24 h. The cells were incubated with different concentrations of DOX, BSA-IrO2 and BSA-IrO2@DOX. After that, part of cells treated with BSA-IrO2 and BSA-IrO2@DOX were irradiated with an 808 nm laser  after 6 h incubation. The cells were then incubated for totally 24 h and the cell viability was measured by using the CCK-8 proliferation assay.To evaluate the combined PTT and chemotherapy of BSA-IrO2@DOX NPs was evaluated by cell live/dead assays. Saos-2 cells were seeded onto 6-well plates (5 × 105 cells per well) and treated as mentioned previously. After that, the cells after different treatments were washed with PBS, stained by calcein-AM (5 μg mL−1) and PI (10 μg mL−1) and incubated for 30 min at 37 °C. Then, the cells were washed with PBS for three times and imaged by an inverted fluorescence microscope (Nikon ECLIPSE Ts2R).The in vitro antitumor efficiency of BSA-IrO6) on the right flank of each mouse. Mice were used for the following in vivo experiments when the tumor volume grew to ∼100 mm3.Female Balb/c nude mice (15–20 g) and female Kunming mice (200-220 g) were provided by the Beijing Vital River Laboratory Animal Technology Co., Ltd. All animal experiments were approved by the institutional ethical committee of the Harbin Medical University. The tumor models were set up by subcutaneous injection of Saos-2 cells (5 × 10n = 5) as follows: (1) PBS, (2) BSA-IrO2 NPs, (3) free DOX (5 mg kg−1), (4) BSA-IrO2@DOX NPs (5 mg kg−1 of DOX), (5) BSA-IrO2 NPs + laser and (6) BSA-IrO2@DOX NPs (5 mg kg−1 of DOX) + laser. Mice in laser irradiation group were exposed to 808 nm laser of 1.0 W/cm2 for 5 min after 12 h intravenous injection of NPs. Meanwhile, the temperature changes of the tumor sites were monitored using an infrared thermal camera during the treatment. The body weight and tumor size were measured every 3 days. The tumor volume was calculated by following equation: Volume = (length × width2)/2.The Saos-2 tumor-bearing mice were randomly divided into six treatment groups  and tumor were removed. The tumors were harvested, fixed in a 10% formalin solution, and embedded in paraffin for hematoxylin and eosin (H&E) and deoxynucleotidyltransferase-mediated dUTP nick end labeling (TUNEL) staining. To investigate the 2@DOX NPs (20 mg kg−1) in PBS (n = 4). At certain designated time intervals , ∼20 μL of blood was withdrawn from the treated mice and put into physiological saline (1 mL) containing heparin sodium (50 unit mL−1). The samples were then digested with aqua regia (HNO3: HCl = 1:3), and the amount of Ir in the blood was measured by ICP-AES. The blood terminal half-life of the BSA-IrO2@DOX NPs was calculated by using a two-compartment model. For the in vivo biodistribution study, the Saos-2 tumor-bearing mice (n = 3) were intravenously injected with BSA-IrO2@DOX (20 mg kg−1) in PBS. At varied time intervals , the tumor and main organs  of the mice were collected and homogenized, followed by ICP-AES measurement for measuring Ir concentration. The distribution of NPs in tumor and different organs were calculated as the percentage of injected dose per gram of tissue.For pharmacokinetic analysis, female Kunming mice were intravenously injected with BSA-IrOp < .05 was considered statistically significant .Experimental results were expressed as the mean ± standard deviation, and an analysis of variance (ANOVA) test was performed for statistical analysis. 2@DOX) NPs as therapeutic nanoplatform were fabricated for synergistic chemo-photothermal of tumor, which is illustrated in 2 NPs was prepared by incubating iridium ion (Ir3+) with BSA in alkaline conditions through biomineralization process, where BSA acted as the stabilizer and template. In this process, BSA in water was mixed with IrCl3 through electrostatic interactions between Ir3+ ions and the active groups (amino and carboxy groups) in BSA due to the great affinity of these groups. Subsequently, the pH value of system was adjusted to ∼12 with NaOH to cause expansive unfolded conformation and Ir3+ is oxidized into IrO2. Upon the introduction of NaOH, the mixed solution rapidly became purple-blue color , which may be attributed to the conformational transformation of protein  of BSA-IrO2 NPs demonstrated the existence of Ir, C, N, S, and O , which are propitious to prolong blood circulation time in the biomedical application.In this work, multifunctional biomineralized iridium-based  for 24 h at room temperature. The successful loading of DOX i was confirmed by UV-Vis spectroscopy and FT-IR spectra. From the UV-Vis spectrum of BSA-IrO2@DOX , which is due to the positively charged of DOX. Simultaneously, the hydrodynamic sizes of BSA-IrO2@DOX were increased to about 84.5 ± 2.1 nm, which is slightly increased compared to BSA-IrO2 . As shown in Figure S3, the saturation of DOX loading was reached to be 27.40% by weight. The BSA-IrO2@DOX NPs could be also well dispersed in PBS and cell culture medium, and the hydrodynamic size was almost unchanged after standing for 72 h, confirming the excellent stability of BSA-IrO2@DOX NPs .Since BSA have been proved as drug carriers to interact with various drug molecules  region with a maximal peak at 634 nm  could be increased to 69.8 °C after 5 min laser irradiation (1.2 Wcm−2). Meanwhile, the strong photothermal effect also provided excellent signal contrast for infrared thermal imaging  in the presence or absence of laser irradiation . As shown in 2@DOX at pH 7.4 after 24 h, while the released DOX amount reached ∼28% at pH 5.0 after 24 h, which can be attributed to the reduction of the electrostatic interaction between DOX molecules and BSA. Moreover, the effect of NIR laser irradiation on the DOX release was further examined. It can be found that DOX is quickly released and the cumulative release drastically increased to ≈46% and ≈68% at pH 7.4 and 5.0 upon laser irradiation, respectively. The NIR-triggered DOX release from BSA-IrO2@DOX is mainly ascribed to the local temperature induced by BSA-IrO2 NPs under NIR laser irradiation could disintegrate the DOX molecules from the nanoplatform. Such pH- and NIR-responsive drug release capacity could avoid premature release during the circulation, which presented a potential approach for on demand drug delivery by this albumin-biomineralized nanocomposite.The feasibility of the pH and NIR laser-triggered DOX release from BSA-IrO2@DOX, whereas free DOX exhibited significant weak fluorescence. The weaker fluorescent signal of free DOX was clearly ascribed to the lower cellular uptake. In comparison, the fluorescent signal was further enhanced after adding laser irradiation, because heat induced by IrO2 upon NIR laser irradiation can enhance the cell uptake of nanoparticles. The intracellular drug release was studied by incubating Saos-2 cells with the BSA-IrO2@DOX NPs, followed by flow cytometry analysis. As shown in 2@DOX were much stronger than that free DOX group, confirmed that BSA-IrO2@DOX could be efficiently uptake by Saos-2 cells. Similiarly, the DOX signal was enhanced after adding laser irradiation, which could be attributed to the heat induced by laser can enhance the cell uptake of NPs, as well as greatly promoted the DOX release  of BSA-IrO2@DOX is 6.21 µg mL−1, while the free DOX was detected at 19.24 µg mL−1, indicating remarkable antitumor effect of BSA-IrO2@DOX. These results were mainly due to the low uptake of free DOX as proved in flow cytometry analysis , confirming the high efficacy of synergistic chemo-photothermal therapy strategy. The chemo-photothermal antitumor efficiency of BSA-IrO2@DOX NPs was further evaluated by calcein AM/PI assay. Almost all cells remained alive were observed in control and BSA-IrO2 groups  after 12 h intravenous administration of BSA-IrO2 or BSA-IrO2@DOX dispersion. The temperature changes of the tumor sites in different groups were monitored using an infrared thermal camera  was conducted to further reveal the mechanism of the therapeutic efficacy  in group that treated with BSA-IrO2@DOX NPs + laser irradiation. These results clearly showed that, although the PTT- or chemotherapy-alone treatment identified favorable inhibition effect, it was much less effective than the synergistic therapy. Furthermore, the major organs including heart, spleen, liver, kidney and lung of the mice after treatment were collected and stained with H&E to investigate the in vivo toxicity . Clearly, no noticeable signal of inflammation or tissue damage was occurred in major organs from each group that treated with BSA-IrO2@DOX or BSA-IrO2, indicating that this multifunctional nanoplatform have excellent biosafety in vivo.To quantitatively estimate the antitumor efficacy, the tumor size was measured every 3 days during the following feeding period of two weeks. As shown in eatments , demonstin vivo anticancer performance of BSA-IrO2@DOX, the blood circulation time and biodistribution were further evaluated. The plasma levels of Ir were determined by ICP-AES at different time intervals following tail vein injection of BSA-IrO2@DOX NPs (20 mg kg−1). The blood levels of Ir concentrations decreased gradually over time and the blood circulation half time of BSA-IrO2@DOX was calculated to be 4.24 h . The prolonged circulation time of BSA-IrO2@DOX can facilitate their subsequent tumor accumulation via the EPR effect. For in vivo biodistribution study, BSA-IrO2@DOX NPs were administered to the Saos-2 tumor-bearing mice via intravenous injection at a dose of 20 mg kg−1, followed by measurements of Ir in tumor and different tissues at varied time intervals. It can be observed that BSA-IrO2@DOX could efficiently accumulate in tumor tissues and reached 9.5% ID/g at 24 h  after intravenous injection as determined by ICP-AES test, which can be ascribed to the tumor EPR effect. Meanwhile, high levels of BSA-IrO2@DOX NPs accumulated in liver and spleen was found, which could be attributed to the absorption of the reticuloendothelial system (Yang et al., 2@DOX exhibit efficient tumor accumulation due to their prolonged circulation time and passive targeting effect.Encouraged by the ideal 2 NPs for stimuli-responsive drug delivery and synergistic chemo-photothermal therapy. The BSA-IrO2 NPs was prepared through a simple biomineralization method. The as-prepared BSA-IrO2 NPs exhibit superb biocompatibility and excellent photothermal conversion capability upon NIR irradiation. The NPs can also be served as carrier for loading of small molecular drugs. Using DOX as a model drug, the BSA-IrO2 also showed considerable drug loading capacity, and the drug release could be triggered by NIR laser and acidic pH. Importantly, highly effective synergetic antitumor efficacy of the BSA-IrO2@DOX has been demonstrated both in vitro and in vivo, which is superior to that of either monotherapy alone. Further, in vivo experiments showed that BSA-IrO2@DOX had long blood circulation time and efficient tumor accumulation. Thus, such BSA-IrO2@DOX nanoparticles present great potential as a nanoplatform for the development of more efficient antitumor treatments. This work has focused on the direction of iridium-based nanomaterials for cancer therapy. Considering that this is the first time to employ the BSA-IrO2 nanoparticles as drug carrier, the protein-based nanocarriers strategy in this work shows general potential for the fabrication of other drug delivery systems.In conclusion, we have successfully developed a biocompatible nanoplatform based on BSA-IrO