domain: scco shs

text:
Laurianne Cabrera
email: laurianne.cabrera@parisdescartes.fr

Lorna F Halliday

Relationship between sensitivity to temporal fine structure and spoken language abilities in children with mild-to-moderate sensorineural hearing loss

Keywords: sensorineural hearing loss, hearing impairment, auditory perception, language development, temporal fine structure, envelope

Relationship between sensitivity to temporal fine structure and spoken language abilities in children with mild-to-moderate sensorineural hearing loss

Laurianne Cabrera, Lorna

I. INTRODUCTION

Auditory perception plays a fundamental role in language development. The acoustic components of speech are known to convey important linguistic information. Like any complex auditory signal, speech signals are decomposed by the auditory system into an array of overlapping frequency bands. The resulting narrowband signals are decomposed further into at least two temporal fluctuation rates [START_REF] Poeppel | Speech perception at the interface of neurobiology and linguistics[END_REF][START_REF] Rosen | Temporal information in speech: acoustic, auditory and linguistic aspects[END_REF]. The envelope (E) comprises the slow oscillations (2-50 Hz) in the overall amplitude of a narrowband auditory signal, and is evident in the acoustic properties of intensity, amplitude modulation (AM), and the rise (onset) and fall (offset) times of sounds [START_REF] Rosen | Temporal information in speech: acoustic, auditory and linguistic aspects[END_REF]. In contrast, temporal fine structure (TFS) comprises the rapid oscilliations (0.6-10 kHz) in the amplitude of a narrowband signal over short time intervals (< 1 s), and carries information about the frequency content of a sound, including the formant spectra of speech [START_REF] Rosen | Temporal information in speech: acoustic, auditory and linguistic aspects[END_REF][START_REF] Smith | Chimaeric sounds reveal dichotomies in auditory perception[END_REF]. For those with normal hearing (NH), the E has been argued to play a crucial role in the comprehension of speech in quiet [START_REF] Drullman | Temporal envelope and fine structure cues for speech intelligibility[END_REF][START_REF] Shannon | Speech recognition with primarily temporal cues[END_REF][START_REF] Smith | Chimaeric sounds reveal dichotomies in auditory perception[END_REF][START_REF] Xu | Distorting temporal fine structure by phase shifting and its effects on speech intelligibility and neural phase locking[END_REF][START_REF] Zeng | On the dichotomy in auditory perception between temporal envelope and fine structure cues[END_REF]. In turn, sensitivity to E cues has been proposed to contribute to language development in children with NH [START_REF] Goswami | Speech rhythm and language acquisition: an amplitude modulation phase hierarchy perspective[END_REF]. Indeed, such is the importance of E cues that children with severe-to-profound sensorineural hearing loss who wear cochlear implants -which provide poor access to TFS cuescan still acquire oral language [START_REF] Tomblin | A comparison of language achievement in children with cochlear implants and children using hearing aids[END_REF]. However, for children with mild-to-moderate sensorineural hearing loss (MMHL), who typically wear hearing aids and not cochlear implants, the perception of the acoustic cues of speech is also likely to be degraded, albeit to a lesser extent.

The current study asked whether the auditory perception of TFS and E cues was associated with language development in children with MMHL, compared to those with NH.

The role of E cues in the acquisition of phonological representations and in learning to read has long been argued for children with NH (e.g., [START_REF] Goswami | Amplitude envelope onsets and developmental dyslexia: A new hypothesis[END_REF]. For example, children with dyslexia have been shown to perform more poorly than normal readers on tasks assessing sensitivity to the sound E, including AM detection, rise time discrimination, and rhythm perception (for review, see [START_REF] Goswami | A temporal sampling framework for developmental dyslexia[END_REF], as well as neural correlates of E encoding [START_REF] De Vos | Atypical neural synchronization to speech envelope modulations in dyslexia[END_REF]Hämäläinen et al., 2008;[START_REF] Power | Neural encoding of the speech envelope by children with developmental dyslexia[END_REF]. Moreover, individual differences in sensitivity to these acoustic features have been shown to be predictive of concurrent and longitudinal reading abilities [START_REF] Goswami | Amplitude envelope onsets and developmental dyslexia: A new hypothesis[END_REF]Goswami et al., 2012;c.f. Rosen, 2003). However, more recently it has been argued that sensitivity to E cues may also play a role in the acquisition of spoken language (for review, see [START_REF] Goswami | Speech rhythm and language acquisition: an amplitude modulation phase hierarchy perspective[END_REF]. Consistent with this view, deficits in sensitivity to rise time, sound duration, and rhythm perception have been found in children with specific language impairment (SLI; now known as developmental language disorder or DLD; [START_REF] Corriveau | Basic auditory processing skills and specific language impairment: a new look at an old hypothesis[END_REF][START_REF] Corriveau | Rhythmic motor entrainment in children with speech and language impairments: tapping to the beat[END_REF]. Recently, sensitivity to rise time at 7 and 10 months was shown to be predicted by vocabulary, but not phonological processing skills, at 3 years of age [START_REF] Kalashnikova | Sensitivity to amplitude envelope rise time in infancy and vocabulary development at 3 years: A significant relationship[END_REF].

In contrast to the literature on children with NH, the role of auditory perception in the language development of children with sensorineural hearing loss has received somewhat less attention. This is perhaps surprising, because we have known for many years that sensorineural hearing loss is associated with abnormal performance on psychoacoustic tasks (for a review, see [START_REF] Moore | Cochlear Hearing Loss: Physiological, Psychological and Technical Issues[END_REF][START_REF] Tomblin | The influence of hearing aids on the speech and language development of children with hearing loss[END_REF]. For example, individuals with sensorineural hearing loss have been shown to exhibit poorer frequency selectivity (i.e. a reduced ability to resolve the spectral components of a complex sound), owing to a broadening of auditory filters [START_REF] Peters | Auditory filter shapes at low center frequencies in young and elderly hearing-impaired subjects[END_REF][START_REF] Rance | Perceptual characterization of children with auditory neuropathy[END_REF]. In addition, sensorineural hearing loss has been linked to reduced sensitivity to TFS, evidenced by the poorer performance of both adults and children with MMHL on tasks such as frequency discrimination, fundamental frequency (F0) discrimination, and frequency modulation detection [START_REF] Halliday | Is poor frequency modulation detection linked to literacy problems? A comparison of specific reading disability and mild to moderate sensorineural hearing loss[END_REF][START_REF] Henry | Effects of sensorineural hearing loss on temporal coding of narrowband and broadband signals in the auditory periphery[END_REF][START_REF] Moore | Auditory processing of temporal fine structure: Effects of age and hearing loss[END_REF][START_REF] Rance | Perceptual characterization of children with auditory neuropathy[END_REF]. However, sensorineural hearing loss appears to leave E processing relatively intact, as demonstrated by the normal or enhanced performance of adults and children with MMHL on tasks such as AM detection (e.g. [START_REF] Rance | Perceptual characterization of children with auditory neuropathy[END_REF][START_REF] Wallaert | Sensorineural hearing loss enhances auditory sensitivity and temporal integration for amplitude modulation[END_REF].

There is increasing evidence that these changes in auditory perception may contribute to the poorer speech discrimination abilities of individuals with sensorineural hearing loss. In hearingaid users, positive correlations between frequency selectivity and speech perception have been found [START_REF] Davies-Venn | Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearing[END_REF][START_REF] Dreschler | Relations between psychophysical data and speech perception for hearing-impaired subjects. II[END_REF][START_REF] Henry | Spectral peak resolution and speech recognition in quiet: normal hearing, hearing impaired, and cochlear implant listeners[END_REF], although not consistently [START_REF] Hopkins | The effects of age and cochlear hearing loss on temporal fine structure sensitivity, frequency selectivity, and speech reception in noise[END_REF][START_REF] Rance | Perceptual characterization of children with auditory neuropathy[END_REF][START_REF] Summers | Suprathreshold auditory processing and speech perception in noise: Hearing-impaired and normalhearing listeners[END_REF][START_REF] Ter Keurs | Limited resolution of spectral contrast and hearing loss for speech in noise[END_REF]. More consistent have been reports of correlations between measures of TFS perception and speech perception in quiet and noise, which have been demonstrated in both children and adults with MMHL (adults: [START_REF] Hopkins | The effects of age and cochlear hearing loss on temporal fine structure sensitivity, frequency selectivity, and speech reception in noise[END_REF][START_REF] Johannesen | The influence of cochlear mechanical dysfunction, temporal processing deficits, and age on the intelligibility of audible speech in noise for hearing-impaired listeners[END_REF][START_REF] Mehraei | Spectrotemporal modulation sensitivity for hearing-impaired listeners: Dependence on carrier center frequency and the relationship to speech intelligibility[END_REF][START_REF] Papakonstantinou | Relations between perceptual measures of temporal processing, auditory-evoked brainstem responses and speech intelligibility in noise[END_REF][START_REF] Summers | Suprathreshold auditory processing and speech perception in noise: Hearing-impaired and normalhearing listeners[END_REF]children: Rance et al., 2004).

Importantly, impaired sensitivity to TFS has been argued to play a critical role in the speech-innoise perception difficulties of adults with sensorineural hearing loss, by interfering with their ability to "listen in the dips" of the background noise [START_REF] Hopkins | Effects of moderate cochlear hearing loss on the ability to benefit from temporal fine structure information in speech[END_REF][START_REF] Lorenzi | Speech perception problems of the hearing impaired reflect inability to use temporal fine structure[END_REF][START_REF] Swaminathan | Psychophysiological analyses demonstrate the importance of neural envelope coding for speech perception in noise[END_REF]. Given the role of speech perception in the acquisition of spoken language [START_REF] Tsao | Speech perception in infancy predicts language development in the second year of life: a longitudinal study[END_REF], individual variability in TFS processing may contribute to the variable language outcomes seen in children with sensorineural hearing loss.

Several large-scale studies have assessed the speech and language development of children with sensorineural hearing loss in recent years. A consistent finding from these studies is that of a large degree of variability in the spoken language outcomes of these children. A number of demographic factors have been identified that appear to contribute to this variability, including severity of hearing loss [START_REF] Ching | Introduction to the Longitudinal Outcomes of Children with Hearing Impairment (LOCHI) study: Background, design, sample characteristics[END_REF][START_REF] Tomblin | Language outcomes in young children with mild to severe hearing loss[END_REF][START_REF] Wake | Parent-reported healthrelated quality of life in children with congenital hearing loss: a population study[END_REF][START_REF] Wake | Hearing impairment: A population study of age at diagnosis, severity, and language outcomes at 7-8 years[END_REF], age of detection and/or age of first fitting of cochlear implants or hearing aids [START_REF] Ching | Introduction to the Longitudinal Outcomes of Children with Hearing Impairment (LOCHI) study: Background, design, sample characteristics[END_REF][START_REF] Wake | Hearing impairment: A population study of age at diagnosis, severity, and language outcomes at 7-8 years[END_REF][START_REF] Yoshinaga-Itano | Language of early-and later-identified children with hearing loss[END_REF], and hearing device audibility, quality, and use [START_REF] Mccreery | Speech recognition and parent-ratings from auditory development questionnaires in children who are hard of hearing[END_REF][START_REF] Tomblin | The influence of hearing aids on the speech and language development of children with hearing loss[END_REF][START_REF] Tomblin | Language outcomes in young children with mild to severe hearing loss[END_REF]. In addition, some studies have suggested a possible role for genetic predisposition to co-occurring language disorders in those children with sensorineural hearing loss who show particular weaknesses in language acquisition [START_REF] Gilbertson | Novel word learning in children with hearing impairment[END_REF]Halliday et al., 2017a). However, a key finding is that these factors do not appear to fully account for the extent of variability in language outcomes experienced by this group. To our knowledge, the possibility that specific deficits in auditory perception might contribute to this variability has not yet been examined.

A series of previous studies assessed the auditory perceptual and language abilities of fortysix 8-16-year-old children with MMHL and 44 age-matched NH controls [START_REF] Halliday | Impaired sensitivity to temporal fine structure but not the envelope for children with mild-to-moderate sensorineural hearing loss[END_REF](Halliday et al., , 2017a[START_REF] Halliday | Auditory processing deficits are sometimes necessary and sometimes sufficient for language difficulties in children: Evidence from mild to moderate sensorineural hearing loss[END_REF]. Auditory psychophysical thresholds were obtained on a battery of tasks, including those designed to assess sensitivity to the TFS (frequency discrimination and detection of modulations in the F0), and E (rise time discrimination and AM detection) of simple and complex sounds. To assess the mediating role of amplification on auditory perception, children with MMHL were tested both while they were wearing their hearing aids and while they were not. For both hearing-aid conditions, the MMHL group performed more poorly than NH controls on the two psychophysical tasks designed to measure sensitivity to TFS [START_REF] Halliday | Impaired sensitivity to temporal fine structure but not the envelope for children with mild-to-moderate sensorineural hearing loss[END_REF]. However, performance on the two measures of E processing did not differ between groups. The same children with MMHL also showed poorer and more variable performance than controls on a variety of measures of spoken language but not reading (Halliday et al., 2017a). However, to date, the relationship between sensitivity to E and TFS cues and individual differences in language abilities, both spoken and reading, has not been assessed.

The current study examined whether performance on these behavioural measures of TFS and E processing was linked to the spoken or written language abilities of these same groups of children with MMHL and NH controls. Based on previous findings for children [START_REF] Rance | Perceptual characterization of children with auditory neuropathy[END_REF], and adults (e.g. [START_REF] Lorenzi | Speech perception problems of the hearing impaired reflect inability to use temporal fine structure[END_REF] with sensorineural hearing loss, it was predicted that unaided sensitivity to TFS would correlate with, and significantly account for a proportion of the variance in, the spoken language (but not reading) abilities of children with MMHL. Based on evidence from children with NH [START_REF] Goswami | Speech rhythm and language acquisition: an amplitude modulation phase hierarchy perspective[END_REF], it was hypothesized that sensitivity to E cues would play a greater role in the spoken language and reading abilities of controls. Finally, this study also examined whether aided sensitivity to TFS or E cues was more important in accounting for individual differences in the language abilities of children with MMHL. Because hearing aids increase the audibility of important components of speech, one possibility was that the relationship between aided thresholds and language would be similar to that of NH controls. Alternatively, because the MMHL group still showed deficits in sensitivity to TFS cues even when they were wearing their hearing aids [START_REF] Halliday | Impaired sensitivity to temporal fine structure but not the envelope for children with mild-to-moderate sensorineural hearing loss[END_REF], it was possible that the relationship between aided thresholds and language would be the same as for the unaided condition.

II. METHODS

Audiometric, psychophysical, and psychometric testing took place at University College London (UCL) over two sessions, each lasting around 90 minutes, and separated by at least a week.

Each child was tested by a single experimenter. Audiometric and psychophysical testing was conducted in a sound-attenuated booth, whereas psychometric testing was conducted in an adjacent quiet room. The parents/guardians of all participants completed an in-house questionnaire concerning their child's demographic, developmental, and medical background. The project received ethical approval from the University College London (UCL) Research Ethics Committee, and informed written consent was obtained from the parent/guardian of each child.

A. Participants

Forty-six children with MMHL (27 boys, 19 girls; MM group) and 44 age-matched NH controls (19 boys; 25 girls; NH group) participated in this study (see Table I). Children were aged 8-16 years-old at the time of testing, and children in the NH group were age-matched to within 6 months to at least one child in the MM group. All children were from monolingual Englishspeaking backgrounds and all communicated solely via the oral/aural modality (i.e. they did not use sign language, as is typical for children with MMHL). Non-verbal IQ was measured for all participants using the Block Design subtest of the Wechsler Abbreviated Scale of Intelligence (WASI; [START_REF] Wechsler | Abbreviated scale of intelligence[END_REF]. All had non-verbal IQ scores within the normal range (IQ-equivalent standard scores of ≥ 85, equivalent to T-scores ≥ 40), although scores were significantly higher for the NH group than the MM group (see Table I). Maternal education level (age in years at which the mother left full-time education) was used as a proxy for socio-economic status and did not differ significantly between groups. Finally, family history of language difficulties was scored bimodally as either having, or not having, a first-degree relative (parent or sibling) with a childhood history of spoken or written language difficulties unrelated to a hearing loss. Family history of language difficulties did not differ between groups.

Unaided pure-tone air-conduction thresholds were obtained for both ears for all children using an Interacoustics AC33 audiometer with Telephonics TDH-39 headphones (see Figure 1).

For the MM group, 19 children were identified as having mild hearing loss, and 27 as moderate hearing loss, where mild was defined as a better-ear pure-tone-average (BEPTA) audiometric threshold of 21-40 dB HL across octave frequencies 0.25-4 kHz, and moderate as a BEPTA threshold of 41-70 dB HL (British Society of Audiology, 2011). Children with NH had mean audiometric thresholds of ≤ 20 dB HL across the octave frequencies for both ears, and thresholds of ≤ 25 dB HL at any particular frequency. For the MM group, age of detection of hearing loss ranged from 2 months to 14 years (median = 57 months), although in all cases, the hearing loss was thought to be congenital and could not be attributed to a syndrome or neurological impairment (including auditory neuropathy spectrum disorder), or any known post-natal event (e.g. measles). Forty-three of the MM group were fitted with bilateral prescription hearing aids, although one child was refusing to wear their aids. Age of first hearing aid fitting was from 3 months to 15 years (median = 65 months).

B. Auditory processing tests

Auditory processing was assessed using four psychophysical tasks. TFS is thought to carry information about both the frequency of sinusoidal stimuli and the F0 of complex stimuli, for carriers below 4-5 kHz [START_REF] Hopkins | Effects of moderate cochlear hearing loss on the ability to benefit from temporal fine structure information in speech[END_REF][START_REF] Moore | Frequency difference limens at high frequencies: Evidence for a transition from a temporal to a place code[END_REF]. Therefore, sensitivity to TFS was assessed using a frequency discrimination (FD) task for a 1-kHz sinusoid, and a F0 modulation detection task for a complex harmonic sound [START_REF] Moore | Frequency difference limens at high frequencies: Evidence for a transition from a temporal to a place code[END_REF][START_REF] Moore | Resolvability of components in complex tones and implications for theories of pitch perception[END_REF]. In contrast, the E carries information about the slow fluctuations (between 2-50 Hz) in the amplitude of an auditory signal. Thus, sensitivity to E cues was assessed using a rise time (RT) discrimination task for a 1-kHz sinusoid, and a slow-rate (2-Hz) AM detection (AMD) task for a complex harmonic sound.

Stimuli

For each task, a continuum of stimuli was created, ranging from a fixed, repeated standard sound to a maximum, variable, deviant sound. All stimuli were 500 ms in duration, and were rootmean-square (rms)-normalised for intensity. All were ramped on and off with a 15-ms linear ramp, apart from the RT task (see below).

For the FD task, the target sounds were generated with frequency differences spaced in the ratio of 1/√2 downwards from a starting point of 1.5 kHz. Detection of modulation in F0 (F0 task) was assessed using a complex harmonic carrier generated by passing a waveform containing 50 equal-amplitude harmonics (at a F0 of 100 Hz) through three simple resonators. The resonators were centred at 500, 1500, and 2500 Hz with a 100 Hz-bandwidth. The F0 was modulated at 4 Hz.

For target stimuli, the depth of modulation varied from ±0.16 Hz to ±16 Hz in logarithmic steps.

For the RT task, the on-ramp of the target sounds ranged logarithmically from 15 ms (the standard) to 435 ms (the maximal deviant) across 100 stimuli, whereas off-ramps were fixed at 50 ms. For the AMD task, the standard stimulus was unmodulated and identical to that used in the F0 task. Deviant stimuli for this task were amplitude modulated at a rate of 2 Hz, with modulation depth ranging from 80% to 5% across 100 stimuli in logarithmic steps.

Stimuli were presented free-field, in a sound-attenuating booth, at a fixed sound pressure level of 70 dB SPL, via a single speaker that was positioned facing the child approximately one metre away from their head.

Psychophysical procedure

The auditory processing tasks were delivered in a computer-game format and responses were recorded via a touch-screen. A three-interval, three-alternative forced-choice (3I-3AFC) procedure was used. On each trial, participants were presented with three sounds, each represented on the screen by a different cartoon character and separated by a silent 500-ms inter-stimulus interval. Two of the sounds were the same (standard) sound, and one was a different (deviant) sound. Children were instructed to select the "odd-one-out" by pressing the character that "made the different sound". For all tasks, an initial one-down, one-up rule was used to adapt the task difficulty until the first reversal. Subsequently, a three-down one-up procedure was used, targeting 79.4% correct on the psychometric function [START_REF] Levitt | Transformed up-down methods in psychoacoustics[END_REF]. The step size decreased over the first three reversals and then remained constant.

For the FD task, the frequency difference between the standard and the deviant was initially 50% (i.e. 1 kHz vs. 1.5 kHz). The initial step size was equivalent to a factor of 0.5, reduced to 1/√2 after the first reversal. For the F0 task, the difference in modulation depth of the F0 between the standard and the deviant was initially ±16 Hz. The step size was initially 12 steps along the continuum, which reduced to four after the first reversal. For the RT task, difference in rise time between the standard and deviant was initially 420 ms. The initial step size was 12 steps along the continuum, reducing to six after the first reversal. Finally, for the AMD task, the initial difference in amplitude modulation depth was 80%. The initial step size was 21 stimulus steps along the continuum, reducing to seven after the first reversal.

For all tasks, tracks terminated after 50 trials, or after four reversals had been achieved (whichever came first). Children were required to repeat a run if their threshold was at ceiling (0.3 % of runs for the NH group, 2.1 % for the MM group), or if they had achieved fewer than four reversals at the final step size (1.1 % of runs for the NH group, 0.9 % for the MM group). In these cases, the repeated run was used to estimate threshold. Participants were given unlimited time to respond and visual feedback was provided after each response. Participants undertook a minimum of five practice trials for each task, where they were asked to discriminate between the endpoints of each continuum (i.e. the easiest discrimination). Participants were required to achieve a ratio of at least 4/5 correct practice trials before testing began, with a maximum of 15 practice trials per task.

Each child completed two runs per task, separated across two sessions. For the children with MMHL who wore hearing aids, one run was completed whilst they were wearing their hearing aids (aided condition), and another when they were not (unaided condition). Hearing aids were set to the children's usual settings for aided testing. The order of tasks and conditions was counterbalanced between children.

Threshold calculations and auditory composite thresholds

For each task, thresholds were calculated as the mean value of the target stimulus at the last four reversals for each adaptive track, equivalent to the geometric mean. Psychophysical thresholds were log-transformed (base 10) to normalise the data. Normalised thresholds for children with MMHL were then age-transformed against the thresholds of the NH group to provide an age-standardised threshold (M = 0; SD = 1). Sensitivity to TFS and E was calculated separately for the MM and NH groups as the arithmetic mean age-standardised thresholds for the FD and F0 tasks (TFS composite) and for the RT and AMD tasks (E composite), respectively.

Composite thresholds were calculated for both aided and unaided conditions for children with MMHL who wore hearing aids (n = 42). For each composite threshold, a higher number corresponded to poorer performance.

C. Language tasks

Language abilities were assessed using a battery of seven standardised psychometric tests, the majority of which had been recently standardised using UK norms (the exception being repetition of nonsense words; see below). Children with MMHL who normally wore hearing aids did so during psychometric testing, using their standard hearing aid settings. For all tests except repetition of nonsense words (see below), scores were converted to z scores (M = 0, SD = 1) based on the age-normed standardised scores of each individual test. Spoken language skills were assessed using receptive and expressive vocabulary tests, receptive and expressive grammar tests, as well as a test evaluating phonological processing and memory. Reading skills were assessed using word reading and pseudoword decoding tests.

Standardized language tests

Spoken language receptive vocabulary was assessed using the British Picture Vocabulary Scale 3 rd Edition (BPVS; [START_REF] Dunn | The British picture vocabulary scale[END_REF]. For this test, children were presented with four pictures on each trial, and required to select the one that best illustrated the meaning of a word said by the experimenter. Expressive vocabulary was assessed using the Expressive Vocabulary (for children aged 8-9 years) and Word Definitions (for children aged ≥ 10 years) subtests of the Clinical Evaluation of Language Fundamentals (CELF) 4 th UK Edition [START_REF] Semel | Clinical Evaluation of Language Fundamentals, 4th Edn; UK Standardisation (CELF-4 UK)[END_REF], respectively.

For the Expressive Vocabulary subtest, children were shown a series of pictures, and for each one asked to say a word that best corresponded to the picture. For the Word Definitions subtest, the experimenter would say a word, and then use that word in a sentence. Children were required to define each target word.

Receptive grammar was assessed using a computerized version of the Test for the Reception of Grammar (TROG; [START_REF] Bishop | Test for reception of grammar: TROG-2 version 2[END_REF], which assesses understanding of 20 different grammatical contrasts. Children were presented on each trial with four pictures, and a sentence that was spoken by a female native Southern British English speaker via the speaker of a laptop.

The task was to select the picture that best depicted the spoken target sentence from the remaining three foil pictures that depicted sentences that were altered in grammatical/lexical structure.

Expressive grammar was assessed using the Recalling Sentences subtest of the CELF [START_REF] Semel | Clinical Evaluation of Language Fundamentals, 4th Edn; UK Standardisation (CELF-4 UK)[END_REF]. For this test, sentences of increasing length and complexity were spoken by a different female native Southern British English speaker and presented via the laptop speaker. Children were asked to repeat back each sentence verbatim.

Phonological processing and memory was assessed using the Repetition of Nonsense Words subtest from the neuropsychological assessment NEPSY [START_REF] Korkman | A developmental NEuroPSYchological assessment (NEPSY)[END_REF]. The thirteen original nonword items from this subtest were re-recorded by a female native speaker of Southern British English and presented via a computer at a comfortable listening level. Nonwords ranged from two to five syllables in length, and the child's task was to repeat each nonword out loud. Responses were recorded and marked offline. Because the norms for the NEPSY only go up to 12 years, 11 months, z-scores were calculated for this test from the age-normed scores for the NH group.

Reading abilities were assessed using the Word Reading and Pseudoword Decoding subtests of the Wechsler Individual Achievement Test (WIAT, [START_REF] Wechsler | Wechsler Individual Achievement Test (WIAT-II UK)[END_REF]. For both tests, children were presented with a series of written words or pseudowords and asked to read them out loud as accurately as possible, in their own time.

Language composite scores

Scores on the spoken language and reading individual tests were combined to form two composite language measures: a spoken language composite measure, and a reading composite measure. The spoken language composite measure was calculated as the mean age-standardized score for each child based on the z scores obtained for the five different spoken language tests of receptive and expressive vocabulary, receptive and expressive grammar, and phonological processing and memory. The reading composite measure was calculated as the mean standardized score for each child based on the z scores obtained for the two reading tests. Each composite score was therefore equivalent to the mean age-standardised score for each child across the spoken language and reading measures, expressed as a z-score (M = 0; SD = 1).

D. Missing data

It was not possible to obtain a pure-tone average threshold for one child in the NH group owing to poor compliance with the test protocol. For this child, a screening procedure confirmed normal hearing, and the child's audiometric thresholds were not included in the study. One child with MMHL was unable to complete the auditory processing tasks in the unaided condition.

Thresholds for this child were therefore included for the aided condition only. Thresholds on the RT task were not obtained for six children with MMHL in the unaided condition and one in the aided condition, owing to failure to pass the practice trials and/or fewer than four reversals being achieved at the final step size. RT thresholds for these children were therefore not included and composite E thresholds calculated from the AMD task only. Questionnaire data recording the age at which the mother left full-time education was missing for five participants (four MM, one NH).

All missing data were examined and it was deemed unlikely that the data were missing at random. Therefore, missing data was not replaced.

E. Data analysis

Data were analysed using linear mixed models because of missing data in some conditions.

Analyses were conducted using RStudio version 1.2.1578 (RStudio Team, 2019) and R version 3.6.1 (R Core Team, 2019). Utilized packages included LME4 [START_REF] Bates | lme4: Linear mixed-effects models using Eigen and S4[END_REF] and ggplot2 [START_REF] Wickham | ggplot2: create elegant data visualisations using the grammar of graphics[END_REF] packages.

III. RESULTS

A. Auditory processing and language measures

Composite TFS and E thresholds for the NH and MM groups (unaided and aided conditions) are shown in Figure 2. To assess whether the groups differed in their auditory processing thresholds, two linear mixed models were run, fitting unaided thresholds for the MM and NH groups (unaided condition), and aided and unaided thresholds for the MM and NH groups respectively (aided condition). For each condition, auditory processing (TFS vs E) and group (MM vs NH), along with their interaction, were included as fixed factors, and participants were included as random effects. For the unaided condition, the effects of group and auditory processing were not significant [β = 0.29, t(125.60) = 1.27 , p = .206; and β = 1.60e-15, t(87) = 0 , p > .999, respectively]. However, there was a significant group x auditory processing interaction [β = 1.24, t(87) = 6.20, p < .001]. For the aided condition, while the effect of group was not significant [β = -0.28, t(124.61) = -1.25, p = .212], the effect of auditory processing was [β = 0.77, t(84) = 5.37, p < .001], as was the group x auditory processing interaction [β = -0.77, t(84) = -3.84, p < .001]. In both the unaided and aided conditions, independent samples t-tests (Welsh) confirmed that the interactions were due to the MM group obtaining higher (poorer) thresholds on the TFS composite relative to controls [unaided: t(70.20) = -6.46, 95% CI [-2.0, -1.1], p <.001, r = 0.61; aided: t(66.24) = -4.46, 95% CI [-1.52, -0.58], p <.001, r = 0.48], but not on the E composite [unaided: t(82.43) = -1.33, 95% CI [-0.73, 0.14], p = .188, r = 0.14; aided: t(80.60) = -1.32, 95% CI [-0.70, 0.14], p = .191, r = 0.15].

To assess whether the performance of children in the MM group differed between the unaided and aided conditions, a linear mixed effects model was run with auditory processing (TFS vs E) and condition (aided vs unaided) along with their interaction as fixed factors, and participants as random effects. The effect of auditory processing was significant, [β = 0.77, t(124.35) = 4.04 , p < .001], but the effect of condition was not [β = 0.02, t(126.45) = 0.11, p =.914], and the condition x auditory processing interaction just missed significance [β = 0.47, t(124.35) = 1.76 , p = .081]. Post-hoc exploration (paired-samples t-tests) of the marginally non-significant interaction indicated that thresholds were lower (better) in the aided compared to the unaided condition for TFS, [t(40) = 2.92, 95% CI [0.16, 0.89], p = .006, r = .42], but not for E, [t(40) = -0.03, 95% CI [-0.39, 0.38], p = .977, r = .00] for children with MMHL who wore hearing aids.

Composite spoken language and reading scores for the NH and MM groups are shown in Figure 3. A linear mixed model, with language modality (spoken vs reading) and group (NH vs MM) plus their interaction as fixed factors, and participants as random effects, revealed significant effects of both language modality and group [β = -0.24, t(88) = 2.81, p = .006, and β = -1.12, t(120.42) = -7.55, p < .001, respectively] as well as a significant modality x group interaction [β = 0.70, t(88) = 5.87, p < .001]. Welch two-sample t-tests showed that the MM group performed more poorly than the NH group on both the spoken language and reading measures [difference for spoken scores = 1.12, 95% CI [0.82, 1.43], t(80) = 7.34, p < .001, r = .63; difference for reading scores = 0.42, 95% CI [0.14, 0.71], t(87) = 2.96, p = .004, r = .30]. However, paired-samples t-tests showed that whereas the NH group exhibited significantly lower scores for reading than for spoken language [difference = 0.24, 95% CI [0.08, 0.40], t( 43

B. Relationship between auditory processing and language measures

To explore the relationship between the auditory processing and language measures, twotailed Pearson's correlations were conducted between the TFS and E composite thresholds and spoken language and reading composite scores (see Figure 4). Correlations were examined separately for the NH and MM groups, and for the unaided and aided conditions for the MM group. Relationships with other known audiological (unaided BEPTA thresholds, a measure of severity of hearing loss), demographic (maternal education, a measure of socio-economic status), and cognitive (nonverbal IQ) predictors of language were also examined. Significance levels were adjusted to control for multiple comparisons, with Bonferroni-corrections applied at a family-wise level (i.e. for comparisons between auditory versus language scores and between the other known predictors versus language scores; both a = .004).

For the MM group, there was a significant correlation between unaided TFS composite thresholds and spoken language composite scores [r(45) = -.46, 95% CI [-.66, -.19], p = .002].

Lower (better) unaided TFS thresholds were associated with higher (better) spoken language scores. In addition, there was a marginally significant correlation between aided E composite thresholds and spoken language scores [r(42) = -.43, 95% CI [-.65, -.15], p = .004], with better E thresholds being associated with better spoken language. Finally, for the MM group, higher nonverbal IQ was associated with higher spoken language and reading scores [r( 46

C. Modelling of language scores

To assess whether sensitivity to TFS or E cues contributed to the variance in spoken language and/or reading abilities over and above other known predictors of language, a series of multi-level linear models was run, for the MM group (unaided and aided conditions) and NH group separately.

Four generic models were used. In Model 1, BEPTA thresholds, nonverbal IQ, maternal education levels, and family history of language/reading difficulties were entered into the model as fixed effects, with participants as random effects. In Model 2, TFS composite thresholds were added to Model 1 to investigate whether TFS processing made an independent contribution to the dependent variables. In Model 3, E composite thresholds were added to Model 1 to investigate whether E processing made an independent contribution to the dependent variables. Finally, in Model 4, both TFS and E composite thresholds were added to Model 1. Analysis of variance (ANOVA) was used to determine the best fitting model for each group (MM and NH), condition (unaided and aided), and dependent variable (spoken language and reading). For each analysis, see supplementary material at [URL will be inserted by AIP] for Table IV summarizing model comparisons and Figures 5, 6 and 7 representing the effect of each independent variable on spoken language scores for the best models.

Table II shows the estimates of the best fitting models for each group and condition for the spoken language composite measure. For the MM group in the unaided condition, adding TFS composite thresholds (Model 2) significantly improved Model 1 (likelihood-ratio test (LRT) = 10.08, p = .002), whereas adding E composite thresholds failed to improve either Model 1 (Model 3; LRT = 3.67, p = .056), or Model 2 (Model 4; LRT = 0.001, p = .970). As shown in Table II, for the MM group for the unaided condition, a significant amount of the variance in spoken language scores was accounted for by individual variance in nonverbal IQ, family history of language difficulties, and unaided TFS composite thresholds, but not by BEPTA thresholds, maternal education levels, or E thresholds.

For the MM group for the aided condition, a slightly different pattern of results was observed for spoken language. Aided TFS thresholds (Model 2) also significantly improved Model 1 (LRT = 6.36, p = .012), but so did aided E thresholds (Model 3, LRT = 7.27, p = .007). However, adding both aided TFS and aided E thresholds (Model 4) did not significantly improve Model 2 (LRT = 3.55, p = .059), or Model 3 (LRT = 2.64, p = .104). For this condition therefore, variance in spoken language scores was significantly and independently accounted for by nonverbal IQ, family history of language difficulties, and either aided TFS or aided E thresholds (but not both;

see Table II).

For the NH group, the best fitting model for spoken language was Model 3. Adding TFS (Model 2) did not improve the fit of Model 1 (LRT = 2.77, p = .096), whereas adding E (Model 3) did (LRT = 9.40, p = .002). Adding E to Model 2 also significant improved the fit (Model 4; LRT = 7.11, p = .008), but adding TFS to Model 3 did not (LRT = 0.48, p = .487), suggesting that only E thresholds made a significant contribution to the model fit. The estimates of the final best model are shown Table II, and suggest that maternal education levels and E composite thresholds both made significant, independent contributions to the variability in spoken language scores for the NH group, whereas BEPTA thresholds, nonverbal IQ, and family history of language difficulties did not.

Finally, the estimates of the best fitting models for the reading composite measure are shown in Table III. For the MM group, adding TFS or E thresholds failed to improve Model 1 for either the unaided or aided conditions. The same was true for the NH group. The final models indicated that nonverbal IQ and family history of language difficulties contributed significantly to reading scores for the MM group, whereas maternal education only contributed in children with NH.

IV. DISCUSSION

The primary goal of the present study was to examine whether sensitivity to the TFS or E of sounds was associated with language outcomes in children with sensorineural hearing loss. In addition, the study examined whether these relationships were the same for children with NH, and for children with hearing loss while they were wearing their hearing aids, and while they were not.

As sensorineural hearing loss is associated with reduced sensitivity to TFS but not E cues [START_REF] Buss | Temporal fine-structure cues to speech and pure tone modulation in observers with sensorineural hearing loss[END_REF][START_REF] Hopkins | The effects of age and cochlear hearing loss on temporal fine structure sensitivity, frequency selectivity, and speech reception in noise[END_REF][START_REF] Lorenzi | Speech perception problems of the hearing impaired reflect inability to use temporal fine structure[END_REF], it was hypothesised that TFS, but not E sensitivity, would be associated with the spoken language (but less so reading) abilities of children with MMHL. For children with NH, it was hypothesised that sensitivity to E (but not TFS) cues would relate to both spoken language and reading abilities [START_REF] Goswami | Speech rhythm and language acquisition: an amplitude modulation phase hierarchy perspective[END_REF][START_REF] Kalashnikova | Sensitivity to amplitude envelope rise time in infancy and vocabulary development at 3 years: A significant relationship[END_REF].

Our first hypothesis was supported by data from the unaided condition, in which sensitivity to TFS and E cues was measured for children with MMHL while they were not wearing their hearing aids. It is important to note that unaided BEPTA thresholds were significantly correlated with TFS thresholds, suggesting that elevated TFS thresholds were associated with worsening cochlear damage. However, the models showed that unaided TFS thresholds significantly contributed to the variance in spoken language (but not reading) scores for children with hearing loss, even after BEPTA thresholds and other predictors of language had been controlled for. In contrast, unaided sensitivity to E cues did not improve the model fit for spoken language scores in this condition. Our findings therefore suggest that deficits in TFS processing may relate to poorer spoken language outcomes for children with MMHL, over and above conventional measures such as unaided BEPTA thresholds. This is consistent with previous studies, with adults with hearing loss showing significant correlations between speech recognition scores and frequency modulation detection at 1000 Hz when audibility (BEPTA) was statistically controlled for [START_REF] Buss | Temporal fine-structure cues to speech and pure tone modulation in observers with sensorineural hearing loss[END_REF].

The direction and nature of this relationship remains to be determined. One possibility is that the unaided TFS thresholds were reflective of the extent of cochlear damage experienced by the children with MMHL. However, it is also possible that these findings demonstrate a relationship between TFS perception and language development per se in children with sensorineural hearing loss. This relationship may be direct, with reduced sensitivity to TFS leading to poorer perception of both the F0 and formants of speech, with subsequent consequences for spoken language acquisition. Indeed, speech perception is a known predictor of spoken language development both in children with NH [START_REF] Tsao | Speech perception in infancy predicts language development in the second year of life: a longitudinal study[END_REF][START_REF] Ziegler | Deficits in speech perception predict language learning impairment[END_REF] and in those with hearing loss [START_REF] Blamey | Relationships among speech perception, production, language, hearing loss, and age in children with impaired hearing[END_REF][START_REF] Davidson | Factors contributing to speech perception scores in long-term pediatric CI users[END_REF]. Alternatively, the relationship may be more indirect, via impaired speech in noise perception. To that end, previous research in adults has shown that sensorineural hearing loss-induced deficits in sensitivity to TFS cues may limit the ability to utilise periods of quiet ("dips") in a background noise for accurate speech perception [START_REF] Ardoint | Effects of lowpass and highpass filtering on the intelligibility of speech based on temporal fine structure or envelope cues[END_REF][START_REF] Hopkins | Effects of moderate cochlear hearing loss on the ability to benefit from temporal fine structure information in speech[END_REF][START_REF] Hopkins | The importance of temporal fine structure information in speech at different spectral regions for normal-hearing and hearingimpaired subjects[END_REF][START_REF] Lorenzi | Speech perception problems of the hearing impaired reflect inability to use temporal fine structure[END_REF][START_REF] Summers | Suprathreshold auditory processing and speech perception in noise: Hearing-impaired and normalhearing listeners[END_REF]. For children with hearing loss, it is plausible that this decreased ability to listen to speech in background noise plays a specific role in hindering the acquisition of spoken language. Consistent with this idea, speech perception in noise has been shown to be particularly problematic for children with sensorineural hearing loss [START_REF] Goldsworthy | Pediatric hearing loss and speech recognition in quiet and in different types of background noise[END_REF], and associated with vocabulary development in this group [START_REF] Klein | Vocabulary facilitates speech perception in children with hearing aids[END_REF][START_REF] Mccreery | Auditory, cognitive, and linguistic factors predict speech recognition in adverse listening conditions for children with hearing loss[END_REF][START_REF] Walker | Longitudinal Speech Recognition in Noise in Children: Effects of Hearing Status and Vocabulary[END_REF]. Given that much spoken language learning occurs in suboptimal, noisy environments [START_REF] Dockrell | Acoustical barriers in classrooms: The impact of noise on performance in the classroom[END_REF], it may be that deficits in TFS perception negatively impact upon this process for children with hearing loss, by impairing their ability to perceive speech under such conditions.

The present analyses showed a slightly different pattern of results when children with MMHL wore their hearing aids for the auditory tasks. In this, aided condition, either sensitivity to TFS or sensitivity to the E -but not both -significantly improved the model for spoken language scores after controlling for the other predictors. A possible explanation for these findings is that our results may simply reflect an improvement in the audibility of stimuli in the aided compared to the unaided condition. Indeed, whilst hearing aids would not have provided additional TFS cues, the increased sensation level is likely to have contributed to the improvement in aided TFS thresholds relative to unaided TFS thresholds in the current study (see also [START_REF] Wier | Frequency discrimination as a function of frequency and sensation level[END_REF].

Aided audibility has been shown to significantly contribute to the speech and language outcomes of children with sensorineural hearing loss, over and above other known predictors for this group [START_REF] Mccreery | Speech recognition and parent-ratings from auditory development questionnaires in children who are hard of hearing[END_REF][START_REF] Mccreery | Auditory, cognitive, and linguistic factors predict speech recognition in adverse listening conditions for children with hearing loss[END_REF][START_REF] Tomblin | Language outcomes in young children with mild to severe hearing loss[END_REF]. For instance, a recent, large cohort study indicated that variability in spoken language abilities for 8-10-year-old children with mild-to-severe sensorineural hearing loss was moderated by an interaction between BEPTA thresholds and aided hearing levels [START_REF] Tomblin | Aided hearing moderates the academic outcomes of children with mild to severe hearing loss[END_REF]. Moreover, higher daily use of hearing aids has been associated

with better listening comprehension, but not vocabulary, reading, or morphological awareness, in children with mild hearing loss aged between 9 and 11 years [START_REF] Walker | Language and reading outcomes in fourth-grade children with mild hearing loss compared to age-matched hearing peers[END_REF]. Aided audibility was not measured in the present study, so its possible relations with language for children with hearing loss cannot be assessed here. However, a relationship between aided audibility and speech perception has not consistently been found in children with sensorineural hearing loss [START_REF] Klein | Vocabulary facilitates speech perception in children with hearing aids[END_REF], raising the possibility that other factors may also play a role.

One such factor may be that specific aspects of aided auditory perception also impact upon the spoken language development of children with sensorineural hearing loss who wear hearing aids. In this respect, the wearing of hearing aids appeared to make the results of children with MMHL more similar to those of NH controls. For children with NH, E composite thresholds significantly contributed to the variance in spoken language abilities, whereas TFS thresholds did not. In contrast, children with MMHL in the aided condition resembled both children with NH, and themselves in the unaided condition, in terms of their pattern of results. Thus, it is possible that where TFS sensitivity is normal (as for children with NH), sensitivity to E cues may be related to spoken language abilities, by contributing to the syllabic and prosodic (stress) representation of the speech signal (see [START_REF] Kalashnikova | Sensitivity to amplitude envelope rise time in infancy and vocabulary development at 3 years: A significant relationship[END_REF]). However, where TFS is degraded, as is the case for children with hearing loss, this may place an upper limit on the utility of E cues in contributing to spoken language outcomes. Nevertheless, E thresholds did contribute to the variance in spoken language outcomes in the aided condition for children with hearing loss, suggesting that these cues may still play a role when TFS cues are more audible. Alternatively, it may be that those children who showed greater deficits in unaided TFS perception were able to benefit more from the enhancement of E cues in the aided condition. Further research is needed to determine whether improvements in the aided perception of TFS and E cues contribute to the better language outcomes of children with hearing loss who wear hearing aids, and whether this relationship is mediated by aided audibility (see [START_REF] Tomblin | The influence of hearing aids on the speech and language development of children with hearing loss[END_REF][START_REF] Tomblin | Language outcomes in young children with mild to severe hearing loss[END_REF][START_REF] Tomblin | Aided hearing moderates the academic outcomes of children with mild to severe hearing loss[END_REF].

While auditory processing skills significantly improved the models for spoken language for the different groups and conditions, this was not the case for reading, contrary to our hypothesis for the NH group. Previous studies have reported a relationship between sensitivity to E cues and reading in children with NH, particularly for those with dyslexia [START_REF] Goswami | Speech rhythm and language acquisition: an amplitude modulation phase hierarchy perspective[END_REF][START_REF] Goswami | Amplitude envelope onsets and developmental dyslexia: A new hypothesis[END_REF]. The current results for children with NH showing no reading difficulties, did not reveal such relationship. It is possible that the two tests used to assess reading skills in this study were not sufficient, or fine-grained enough, to observe a link between auditory perception and reading in children with NH, or that a such relationship is stronger for children with dyslexia. Alternatively, it is possible that reading abilities are not directly related to the E and TFS tasks used here, or that other mechanisms mediate this relationship [START_REF] Rosen | Auditory processing in dyslexia and specific language impairment: is there a deficit? What is its nature? Does it explain anything?[END_REF]. Lastly, it may be that the children in the current study were too old for such a relationship to be observed, which may well be expected to lessen as children get older and the reciprocal relationship between spoken language and reading acquisition takes hold [START_REF] Ricketts | Reading and Oral Vocabulary Development in Early Adolescence[END_REF]. Whatever the reason, it is of interest that the children with MMHL in the current study showed both normal E processing and generally normal reading abilities. Therefore, it appears that for children with MMHL at least, sensitivity to TFS may better relate to spoken language development than it does to learning to read (see also [START_REF] Halliday | Frequency discrimination and literacy skills in children with mild to moderate sensorineural hearing loss[END_REF], for similar results regarding a lack of relationship between frequency discrimination and reading for children with MMHL).

The current study had a number of limitations that ought to be considered. First, while the auditory tasks were designed to be predominantly reliant upon sensitivity to TFS and E cues [START_REF] Halliday | Impaired sensitivity to temporal fine structure but not the envelope for children with mild-to-moderate sensorineural hearing loss[END_REF], it remains possible that other auditory processes were involved. For instance, for the TFS tasks it is difficult to rule out the possible impact of reduced frequency selectivity due to broader auditory filters in the hearing loss group [START_REF] Oxenham | Can temporal fine structure represent the fundamental frequency of unresolved harmonics?[END_REF]. It is therefore possible that the findings reflect an added effect of both TFS and frequency selectivity on language outcomes in children with sensorineural hearing loss. Second, owing to equipment failure it was not possible to measure hearing aid fit or aided audibility for the children with MMHL. It is therefore possible that the hearing aids of the hearing loss group were not optimally fitted, or were not functioning optimally on the day of testing, and so did not provide sufficient auditory input during the aided tasks. Further research is therefore needed to investigate the role of aided audibility on the abilities of children with sensorineural hearing loss who wear hearing aids to process the auditory temporal modulations of speech. Third, the present study included a single sample of children with MMHL. Future research is needed to replicate these findings. Finally, the current study employed a cross-sectional design, which limits the ability to infer causal relationships between auditory perception and language outcomes. Longitudinal designs are therefore needed to investigate the causal direction of the relationship between auditory perception and language in children with sensorineural hearing loss.

V. CONCLUSIONS

Children with mild-to-moderate (MMHL) present with deficits in the processing of the fastest temporal modulations of sounds, the temporal fine structure (TFS), and show generally poorer language outcomes than their normally hearing (NH) peers. The present study indicated that the auditory processing of temporal modulations may play a role in the spoken language development of children with MMHL, and also children with NH. We found that unaided sensitivity to the TFS of sounds contributed to variance in the spoken language abilities of children with MMHL, and that measures of TFS sensitivity were more related to spoken language than pure-tone audiometry in this group. When children with MMHL used their hearing aids for the auditory tasks, aided sensitivity to either the TFS or envelope (E) of sounds (but not both) contributed to the spoken language variability of the same group of children. Finally, for children with NH, sensitivity to E cues (but not TFS) was a better predictor of spoken language abilities. We suggest that the poorer spoken language abilities of children with sensorineural hearing loss may in part be a consequence of their reduced sensitivity to TFS, which may lead to poorer speech perception, particularly in noise. In contrast, for children with NH, or those with hearing loss who are wearing their hearing aids, sensitivity to E cues may play a more important role. Thus, children with sensorineural hearing loss who show greater deficits in TFS perception may be at greater risk of spoken language difficulties than those with better TFS perception. TFS sensitivity may therefore be a useful measure to investigate individual variability in spoken language outcomes for children with sensorineural hearing loss. Further research is needed to better understand the potential role of aided audibility in mediating this relationship. a Models 2 and 3 both fit the data better than Model 1 for the MM group in the aided condition, but could not be distinguished from one another. For simplicity, we report the full model for Model 2 (aided TFS), and the specific additional contribution made by aided E for Model 3.

Figure 1 :

 1 Figure 1: Individual (thin blue lines) and mean (thick blue lines) air-conduction pure-tone

  ) = 2.95, p = .005, r = .41], the MM group showed the opposite pattern [difference = -0.46, 95% CI [-0.64, -0.29], t(45) = -5.31, p < .001, r = .62].

Figure 2 .Figure 3 .

 23 Figure 2. Performance on the TFS and E composite measures for the NH in grey (TFS: M =0, SD = 0.78; E: M = 0, SD =0.89), aided MM in orange (TFS: M = 1.53, SD = 1.37; E: M = 0.29, SD = 1.16), and MM unaided in blue (TFS: M =1.05, SD =1.32; E: M = 0.28, SD =1.05). Higher thresholds correspond to poorer performance. Boxplots represent the 25 th , 50 th and 75 th percentile for each group/condition while the violin plots illustrate kernel

Figure 4 .

 4 Figure 4. Correlograms representing the correlation coefficients between the auditory processing, language, BETPA, demographic, and cognitive

  associated with higher (better) spoken language scores. In addition, higher maternal education was significantly associated with better spoken language scores [r(43) = .52, 95% CI [.26, .71], p < .001]. None of the other correlations between language (spoken or reading) and auditory processing or other known predictors reached significance for the NH group after controlling for multiple comparisons.

	) = .54 , 95%
	CI [.29, .72], p < .001; and r(46) = .54, 95% CI [.29, .72], p < .001, respectively]. None of the other
	correlations between the auditory processing versus language composite scores or between the
	other known predictors and language scores reached significance for the MM group after
	correcting for multiple comparisons.
	For the NH group, a slightly different pattern was observed. After controlling for multiple
	comparisons, both E composite thresholds and TFS composite thresholds were significantly

correlated with spoken language composite scores [r(44) = -.50, 95% CI [-.69, -.24], p < .001, and r(44) = -.43, 95% CI

[-.65, -.16

], p = .003, respectively]. Lower (better) auditory processing thresholds were

TABLE I .

 I Mean (SD) and ratio participant characteristics for the NH and MM groups and between-groups comparisons.

	Variable a	NH (N = 44)	MM (N = 46)	t	df	p	r/OR	95% CI
	Age (years)	11.54 (2.05)	11.44 (2.16)	0.23	88	.821	0.02	-0.78, 0.98
	BEPTA thresholds (dB HL)	7.33 (3.95)	43.37 (12.01)	-19.28	55	<.001	0.93	-39.79, -32.30
	Maternal education (years)	20.47 (2.89)	19.33 (2.65)	1.88	83	.063	0.20	-0.06, 2.33
	Non-verbal IQ (T-score)	60.64 (8.48)	55.63 (8.71)	2.76	88	.007	0.28	1.40, 8.61
	Family history (0:1)	35:9	35:11	---	1	.802	1.22	0.45, 3.32

a. NH = normally hearing group; MM = mild-to-moderate hearing loss group; OR = odds ratio; CI = confidence interval; BEPTA = betterear pure-tone average thresholds. Parametric tests were two-sample Welsh t-tests; Non-parametric tests were Fisher's Exact Test.

TABLE II .

 II Best fitting multi-level linear models for spoken language composite scores for the MM group for the unaided and aided conditions, and for the NH group. Significant parameters (p < .05) are in boldface.

	Model/ Predictors	Estimate	SE	df	t	p
	MM group-unaided
	Intercept	-3.06	1.04	35	-2.94	.006
	BEPTA	0.02	0.01	35	1.54	.132
	Maternal education	0.03	0.04	35	0.69	.494
	Nonverbal IQ	0.03	0.01	35	2.66	.012
	Family history	-0.56	0.25	35	-2.27	.030
	TFS unaided (Model 2)	-0.28	0.09	35	-3.12	.004
	MM group-aided
	Intercept	-3.05	1.16	32	-2.65	.013
	BEPTA	0.01	0.01	32	1.07	.293
	Maternal education	0.00	0.05	32	0.07	.948
	Nonverbal IQ	0.04	0.01	32	3.05	.005
	Family history	-0.65	0.28	32	-2.37	.024
	TFS unaided (Model 2) a	-0.25	0.10	32	-2.41	.022
	E aided (Model 3) a	-0.32	0.12	32	-2.60	.014
	NH group
	Intercept	-1.06	0.68	36	-1.55	.130
	BEPTA	-0.02	0.02	36	-0.99	.329
	Maternal education	0.08	0.02	36	3.13	.003
	Nonverbal IQ	0.00	0.01	36	0.47	.639
	Family history	-0.38	0.17	36	-2.18	.036
	E (Model 3)	-0.25	0.08	36	-3.01	.005

ACKNOWLEGEMENTS

The authors would like to thank Stuart Rosen for constructing the stimuli and assisting with extracting psychophysical thresholds, Steve Nevard for his assistance with setting up the laboratory facilities, Michael Coleman for the development of the psychophysical testing software SHAPS, Páraic Scanlon and Outi Tuomainen for participant testing, and Axelle Calcus for help with Figure 1. The authors are especially grateful to all the children who participated, along with their parents, as well as the Local Educational Authorities and schools who assisted with recruitment. This work was supported by an ESRC First Grants Award (RES-061-25-0440) and MRC Senior Fellowship in Hearing Research (MR/S002464/1) to Lorna F. Halliday, and the FP7 people programme (Marie Curie Actions), REA grant agreement no FP7-607139 (improving Children's Auditory REhabilitation, iCARE). Laurianne Cabrera was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no 659204 and is now supported by the Agence National de la Recherche, France, under grant ANR-ANR-17-CE28-0008 DESIN.

Data Sharing Statement. The data that support the findings of this study as well as R codes used for the analyses are available from Lorna Halliday (lorna.halliday@mrc-cbu.cam.ac.uk) upon reasonable request.


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Core-modified coelenterazine luciferin analogues, synthesis and chemiluminescence properties

Keywords: Core-modified coelenterazine luciferin analogues, synthesis and chemiluminescence properties Homogeneous catalysis, Synthesis design, Chemiluminescence, Luciferin, Bioluminescence 10

Introduction

Chemiluminescence as well as bioluminescence, [1] its luciferase-catalyzed version, are based on remarkable oxidation reactions of luciferins leading to products in an excited electronic state, which can then relax either by non-radiative processes or by a photon emission. [2] This phenomenon has found numerous applications, especially for detection purposes. In life sciences, a great variety of bioluminescent reporting systems have thus been constructed out of a luciferin and a luciferase. Amongst them, systems based on the marine luciferin coelenterazine (1) and the corresponding luciferases or photoproteins from a remarkably diverse number of sea dwelling species [1a, 3] are increasingly used. [4] The mechanism at the source of the photon emission by these systems is depicted in scheme 1. The first step is a reaction with dioxygen leading to the peroxide 2 which, unless stabilized, [5] undergoes a rearrangement into the endoperoxide 3 and then decomposes into carbon dioxide and coelenteramide (4). The latter product occurs in an excited electronic state which can relax back to its ground state via the emission of a photon at a "short" wavelength corresponding to a blue color (between 450 and 480 nm), the most visible undersea. Contrary to firefly luciferins, which require an ATP-based activation, this oxidation can also be achieved without a luciferase in the presence of oxygen under a variety of conditions and will lead, via the same mechanism, [6] to a usually far less efficient photon emission phenomenon which is called chemiluminescence. Some current avenue of research are focusing on the design of luciferin/luciferase reporting systems, still based on coelenterazine using enzymes, but emitting a photon at a higher wavelength which is more suitable for in vivo studies. [7] This is due to the fact that a red photon will be detectable through the living tissues of a small animal, contrary to a blue one. In the present report, we planned on the use of mutants of luciferases such as nanoKAZ/NanoLuc, which is already accepting a rather large array of imidazo [1,2b]pyridazin-3(5H)-ones as substrates, [7i, 8] and designed analogues featuring an altered heterocyclic core which we also "dressed" with the phenyl/bisbenzyls residues found in actual substrates of the nanoKAZ/NanoLuc luciferase. We thus sought accesses to unprecedented 2-a]pyridin-3-ol 7 which could theoretically undergo an electronic cascade leading to the occurrence of hydroperoxide intermediates as depicted for coelenterazine (1). The synthesis of a "deaza" coelenterazine analog featuring this last heterocyclic core has actually been reported previously. [9] We also prepared some imidazo[1,2-a]quinoxalin-1(5H)-ones 8 which have been the subject of an untranslated patent for their chemiluminescence properties although no mention of the wavelength of the emitted photon appears to be mentioned. [10] A single derivative featuring this ring system has also been claimed in a more recent patent. [11] The synthesis of analogues featuring a benzo [f]imidazo[1,2-a]quinoxalin-3(11H)-one skeleton 9 or imidazo [1',2':1,6]pyrazino [2,3-c]quinolin-3(11H)-one 10 were also explored as a similar heterocyclic system is found in the structure of v-coelenterazine (11), a luciferin analogue which is a substrate of the soft coral Renilla reniformis luciferase [12] and some of its mutants, [7b] as well as the photoprotein found in the Aequorea jellyfish. [13] Finally, we replaced the additional pyridine ring of compound 11 by a pyran ring and designed an access to an unprecedented 5,11dihydro-3H-chromeno[4,3-e]imidazo[1,2-a]pyrazin-3-one 12 derivative.

derivatives of imidazo[1,2-b]pyridazin-3(5H)-one 5, imidazo[2,1-f][1,2,4]triazin-7(1H)-one 6 or imidazo[1,

Syntheses

We have previously reported improvements of the nanoKAZ/NanoLuc-based reporting system using an original synthetic pathway leading to enhanced luciferin analogues. [8c, 14] As depicted in scheme 2, these compounds were obtained from chloropyrazines 13 and amino esters 14 via a key N-arylation step to give the stable esters 15a. Upon treatment with sodium hydroxide under an inert atmosphere, these gave the corresponding sodium salts 15b and the addition of an excess of acetic anhydride led, via the imidazo[1,2-a]pyrazin-3(7H)-ones 16, to the far more stable Oacetylated luciferins 17. Then, when required, the proluciferins 17 can be hydrolyzed back into the luciferins 16 under mild conditions to give, after further dilution in appropriate buffer, readyto-use solution for bioluminescence-based studies.

Scheme 2. Previously reported [8c, 14b] synthesis of O-acetyl imidazo[1,2-a]pyrazin-3(7H)-one luciferins.

Preparation of an imidazo [1,2-b]pyridazin-3(5H)-one derivative. As depicted in scheme 3, the O-acetylated compound 26 featuring an imidazo[1,2-b]pyridazine ring system was synthesized in 5 steps from phenylpyridazine 18, readily available from 3-chloro-6-methoxypyridazine and phenylboronic acid using a Suzuki-Miyaura coupling reaction. [15] From this compound, a regioselective deprotonation using lithium diisopropylamide (LDA) followed by the addition of benzaldehyde led to alcohol 19. The reduction of the hydroxyl function to produce compound 21 turned out to be fraught with difficulties as an over-hydrogenation was often observed. An acceptable yield was eventually found via a palladium-catalyzed hydrogenation of the brominebearing 3-hydroxypyridazine 20 readily prepared by treatment of alcohol 19 with hydrogen bromide in acetic acid. From the reduced compound 21, the 3-chloropyridazine 22 was then obtained upon its treatment with hot phenylphosphonic dichloride. Then, we tried to prepare the N-arylated derivative of phenylalanine ethyl ester (23) using our previously published method. [8c, 14b] Unexpectedly, under these conditions the corresponding ester 24 directly underwent a cyclization into the corresponding imidazo [1,2-b]pyridazin-3(5H)-one 25. However, due its Preparation of an imidazo [2,1-f][1,2,4]triazin-7(1H)-one derivative. As depicted in scheme 4, to reach an imidazo [2,1-f][1,2,4]triazine analogue the corresponding 6-hydroxytriazine 30 was made in 3 steps from hippuric acid ( 27) using a previously described method. [START_REF] Wermuth | Adir et compagnie[END_REF] Unexpectedly, transformation of the 6-hydroxytriazine 30 into the corresponding 6-chlorotriazine 31 turned out to be difficult as low yield and/or decomposition were observed when trying various chlorination agents: thionyl chloride, phosphorus oxychloride, or phenylphosphonic dichloride. The use of mild conditions (phosphorus oxychloride diluted in acetonitrile in the presence of solid potassium carbonate at reflux) led to a rather modest 19-22% yield of the target compound 31. The ensuing N-arylation of phenyl alanine ethyl ester ( 23) also turned out to be problematic as an extensive decomposition was observed. Out of the many side products occurring, a minute amount (4%) of the pyrrolotriazine 32, resulting from a condensation of acetonitrile, was isolated. Switching to toluene at 90 °C actually led to the isolation of the expected amino ester 33 but in a very poor 11% yield. Moreover, the target compound 33 turned out to be unstable in open air under various conditions, such as when left in solution in CDCl3, as seen by LC/MS analysis (m/z = 453 and 455). An alternative was eventually designed as we found that the slow uncatalyzed N-arylation of phenylalanine ethyl ester ( 23) by compound 31 was also possible. Indeed, upon heating at 120 °C these compounds in N-methylpyrrolidine (NMP) using triethylamine as a base for 14 days led directly to a solution containing the unstable luciferin 34. Its in situ treatment with an excess of acetic anhydride and additional triethylamine allowed the isolation of the target proluciferin 35 in an 8% overall yield from compound 31.

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Preparation of an imidazo[1,2-a]pyridin-3-ol derivative.

The original preparation of compound 42 depicted in scheme 5 started with the readily available 2-methoxypyridine derivative 36. [START_REF] Spinner | [END_REF] It turned out that a regiospecific Negishi reaction was possible even when using 1.5 equivalents of benzylzincbromide, and the C-3 benzylated derivative 37 was isolated in a 47% yield.

Preparation of an imidazo[1,2-a]quinoxalin-1(5H)-one derivative.

As depicted in scheme 6, an original preparation of luciferin analogues featuring an imidazoquinoxaline ring system was developed. For this, we used the quinoxalinol 45a made from the condensation between ophenylenediamine (43a) and phenylpyruvic acid (44) in the presence of hydrochloric acid and 2mercaptoethanol [18] which led to 79% of 45a. Of interest is the fact that a control experiment without 2-mercaptoethanol still provided 62% of compound 45a. From this quinoxalinol, the corresponding 2-chloroquinoxaline 46a was then obtained in a 90% yield and this was followed by its N-arylation with phenylalanine ethyl ester (23) to give 71% of compound 47a. The ensuing ester hydrolysis using sodium hydroxide followed by a cyclisation using an excess of acetic This article is protected by copyright. All rights reserved.

anhydride finally gave 69% of the target O-acetylated imidazo[1,2-a]quinoxaline 48a. Although a more extensive purification procedure was required to obtain 46% of compound 46b from the difluorinated o-phenylenediamine 43b, the same synthetic pathway led to the analogue 48b in a 12% overall yield. Of note was the far slower N-arylation of phenylalanine ethyl ester (23) with the fluorine-bearing 2-chloroquinoxaline 46b as only an 11% yield of the N-arylester 47b was obtained in 12 hours of heating whereas a 38% yield was achieved when heating for 27 hours.

Scheme 6. i: EtOH, HSCH2CH2OH, 2N H3O + Cl -, reflux. ii: PhPOCl2, 100 °C. iii: Pd(OAc)2, BINAP, Cs2CO3, toluene, 90 °C. iv: 1) NaOH, THF, 20 °C, 2) Ac2O, 20 °C.

Preparation of benzo [f]imidazo [1,2-a]quinoxalin-3(11H)-one derivatives. As depicted in scheme 7, an original [13,19] synthesis of such analogues was designed via the use of three distinct

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quantitative amidification of these esters, using methanolic ammonia in a pressure vessel at 100 °C, which gave the amides 52a and 52b. From these, an intramolecular Buchwald-Hartwig reaction was envisaged using Xantphos as the palladium ligand. [20] However, from the bisbrominated derivative 52a, trials pointed out an extensive decomposition and very little occurrence of compounds 53a or 54a, probably due to an un-selective palladium insertion in the carbon-bromine bounds. On the other hand, from the 2-bromo-4-fluoro amide 52b, the same reaction led to a chromatographic fraction containing mixture of compound 53b, resulting from the planned cyclization, and compound 54b resulting from the aromatization of some 53b. This aromatization was then completed using peracetic acid as the oxidant and compound 54b was isolated in 54% yield from 52b. The ensuing chlorination with hot phenylphosphonic dichloride gave 67% of compound 55 which was subjected to the last Buchwald-Hartwig reaction to yield 71% of the N-arylated phenylalanine ethyl esters 56. The last two steps, hydrolysis of the ester function followed in situ by a cyclization with an excess of acetic anhydride, gave 65% of the target O-acetylated luciferins analogue 57. Preparation of an imidazo [1',2':1,6]pyrazino [2,3-c]quinolin-3(11H)-one derivative. The synthetic pathway described above was used again to prepare the nitrogen-bearing analogue, starting with 4-bromoquinoline (58) as depicted in scheme 8. If the first four steps, including the first two Buchwald-Hartwig reactions, proceeded without any difficulties, the aromatization step of compound 62 required sulfur in boiling decaline and gave 67% of the target compound 63. In the next step, chlorination in hot phenylphosphonic dichloride to obtain compound 65 turned out to be very slow, even at 100 °C. Raising the temperature to 150 °C led to 2.6% of the unexpected 10.1002/chem.202004311

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compound 64 resulting from an oxidative dimerization process along with 17% of the target compound 65. It is only by running the reaction as thoroughly as possible under an argon atmosphere and adding potassium carbonate (presumably to quench any evolving hydrochloric acid) that compound 65 could be obtained in a 38% yield although 19% of the dimer 64 and some unreacted material (less than 8%) were also isolated. This unexpected methylene reactivity, somehow reminiscent of what we previously observed with the chlorotriazine 31 depicted in scheme 4, probably had also some effect on the last Buchwald-Hartwig N-arylation as we could isolate the resulting α-amino ester 66 in only 43% yield. Moreover, a rather high incidence of decomposition was observed in the course of the last synthetic steps and the target O-acetylated luciferin analogue 67 was obtained in only a 35% yield.

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Scheme 8. i: PheOEt (23), Pd(OAc)2, BINAP, Cs2CO3, toluene, 95 °C. ii: NBS, CH2Cl2, 0-20 °C.

iii: 7N NH3/MeOH, 100 °C. iv: Pd(OAc) 2, Xantphos, Cs2CO3, THF, 120 °C. v: S8, decaline, reflux. vi: PhPOCl2, K2CO3, 150 °C, argon. vii: PheOEt (23), Pd(OAc)2, BINAP, Cs2CO3, MeCN, 60 °C. viii: 1) NaOH, THF, 20 °C, 2) Ac2O, 20 °C.

Preparation of a 5,11-dihydro-3H-chromeno[4,3-e]imidazo [1,2-a]pyrazin-3-one derivative. In an attempt to design an alternative pathway to benzo [f]imidazo[1,2-a]quinoxalin-3(11H)-one 14, we initially contemplated to use our previously reported preparation of chloropyrazines starting with a 1,4-addition of phenyl alanine ethyl ester ( 23) as a free base on nitrostyrene. [8c, 14b] Accordingly, as depicted in scheme 9, we started with the bridged derivative 3-nitro-1,2-dihydronaphthalene (68a), readily prepared by nitration of dihydronaphtalene using tetranitromethane. [21] Unexpectedly and despite many trials, no 1,4-addition was observed with this substrate. On the other hand, this 1,4-addition readily took place on 3-nitro-2H-chromene (68b) [22] to give the pyran-bearing 1,4-adduct 69b. We do not have a satisfying explanation for this difference of reactivity although the only example reported of a nitrogen-bearing nucleophilic 1,4-addition on 3-nitro-1,2-dihydronaphthalene (68a) involved a far more nucleophilic specie. [23] In any case, from compound 69b, a reduction of its nitro function using zinc and hydrochloric acid followed by a thermal cyclisation of the resulting amine gave the tetrahydrochromeno [3,4-b]pyrazin-3(4H)-one 70 as a mixture of diastereoisomers. Many attempts were made to achieve its aromatization, using sulfur in boiling 1,3-dichlorobenzene, iodine as well as other oxidants with a very limited success. [14a] We thus resorted to the preparation of the quite unstable nitrone 71.

From this crude compound, a dehydration reaction using sodium hydroxide [14b] gave the desired 5H-chromeno [3,4-b]pyrazin-3-ol 72 in 52% yield from compound 70. The preparation of the corresponding chloro derivative using hot phenylphosphonic dichloride only led to minute amount of this compound. Accordingly, we used a milder alternative [24] via the preparation of the triflate ester 73, and a displacement reaction with sodium bromide which gave the bromo derivative 74 in 40% yield from the chromenopyrazinol 72. From compound 74, the ensuing Narylation of phenylalanine ethyl ester (23) led to 70% of the expected ester 75 and the final steps provided 80% of the target O-acetylated luciferin analogue 76.

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additional dimerization of compound 78. Solution of the compounds 1, 86 and 87 were also used as references. From the resulting solution of compound 78-85, no tangible bioluminescence was observed with compound 78-85 when using n nanoKAZ/NanoLuc luciferase under the usual conditions, [14b] contrary to coelenterazine (1), bisdeoxycoelenterazine (77), [8b] furimazine (86) [8a] or the enhanced analogue 87. [8c] On the other hand, the chemiluminescence properties of these compounds was somewhat more rewarding. In the past, the chemiluminescence properties of coelenterazine (1) or some of its analogues have been the focus of many studies. [25] The final concentration of the compounds used in these experiments is always low, varying between 1 µM, [25e] 3 µM, [25i] 10 µM [25a, c, d, f] or in two instances 50 µM. [25g, h] We quickly found out the reason as, at much higher concentration (i.e.: 1 mM final), we observed remarkable wavelength shift which could be only explained by resonance energy transfers to fluorescent substances arising from the light production process. Interestingly, this requirement for low concentration was not found necessary for the study of the chemiluminescence of firefly luciferins. [26] For our part, as depicted in table 1, for every compound made, their addition to a phosphate buffer (DPBS; pH = 7.4), leading to 5 µM final concentration, led to a chemiluminescence signal as measured by a HIDEX Triathler Gamma Counter. Of note is that the signal intensity varied widely according to the compound studied. Moreover, we confirmed the ammonium-based surfactant enhancement effect reported by Shimomura [1a] since quite remarkable intensity improvement was systematically achieved when adding of 2.5 mMol of cetyltrimethylammonium bromide (CTAB). Concerning the products resulting from this chemiluminescence, LC/MS analysis, using ammonium carbonate as a buffer, pointed out the occurrence of the expected ions typical of the light-producing reaction depicted in scheme 1 (see supplementary info). In the case of coelenterazine (1, m/z = 424), the ion corresponding to coelenteramide (4, m/z = 412) and, as reported, [27] the amine (m/z = 278) were observed. Concerning the emission spectra of the strong and medium emitters, the use of an Aqualog® (HORIBA Instruments, Inc.), a spectrometer endowed with a sensitive CCD detector (Water-Raman SNR > 20,000:1 -RMS method), gave good results but only upon adding 2.5 mMol of CTAB in the phosphate buffer. Concerning the weak emitters, such as compounds 78-81, we have yet to find a device sensitive enough to determine their emission spectra.

Interestingly, even at a 5 µM final concentration a degree of signal quench was observed in one instance (compound 87) but this was alleviated when measuring the spectra at a 2.5 µM final concentration.

Conclusion

In this study, we made an array of compounds which all produced a photon upon their reaction with oxygen via, as confirmed by LC/MS analysis, a mechanism plausibly similar to the one described for imidazo[1,2-a]pyrazin-3(7H)-one luciferins. Many of these analogues were prepared using our previously reported [8c, 14b] synthetic pathway although unexpected limits were encountered in their preparations. These limitations drove us to use and develop alternative conditions to produce the target compounds, notably using the fact that the N-arylations could sometime take place without a palladium-based catalyst along with a (not too) strong base or the observation that some the resulting esters could undergo a cyclisation into the target luciferin just upon heating. Again, trapping these relatively unstable substances under their O-acetylated form was instrumental in their proper isolation and the success of this work. Concerning their chemiluminescence properties when adding these compounds to a phosphate buffer, a very variable degree of signal intensities was observed. Of interest is the observation that a very strong chemiluminescence is observed for the most rigid analogues such as compound 83 and 85 but unexpectedly not for the "aza" analogue 84. Aside from a degree of instability (in comparison with other derivatives) which was noted for the O-acetylated precursors of compounds 78-80, it is more difficult to identify a reason for their very low chemiluminescence. Concerning the emission profiles of the compounds endowed with a chemiluminescence of sufficient intensity, the λmax were mainly situated in the blue region (438-472 nm) with the notable exception of the difluorinated derivative 82, endowed with a green signal at 513 nm. Previous and far more extensive, studies on the chemiluminescence properties of coelenterazine (1) have reported on the large impact on the signal wavelength when using a protic or an aprotic organic solvents as well when using a base. [25a] In our case we chose to use only a protic one (water) and a mild base (a phosphate buffer) since we observed little difference between the chemiluminescence (472 nm) 10.1002/chem.202004311

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This article is protected by copyright. All rights reserved. and bioluminescence (455 nm; [8c] with NanoLuc) of the reference compound furimazine (1). We thus retained only this set of condition to qualify the emission wavelength of these analogues as a plausibly predictive parameter of their eventual bioluminescence properties (if a luciferase, derived from nanoKAZ/NanoLuc, could be designed to consume them). However, the relatively modest chemiluminescence λmax shifts achieved here do not meet the criteria to initiate a research program aiming at designing a luciferase capable of catalyzing the light-producing combustion of one of these analogues. In any case, the results obtained are providing some additional clues on how to red-shift this type of luciferin and, probably more important, the experimental data presented here should be useful for the design and validation of computer-based models [2] of these light-producing reactions.

Scheme 4 .

 4 Scheme 4. i: PhCHO, AcONa, Ac2O, 65 -90 °C. ii: NH2NH2, EtOH, 20 °C. iii: NaOH 1.5N, reflux. iv: POCl3, K2CO3, MeCN, reflux. v: Pd(OAc)2, BINAP, Cs2CO3, MeCN, 60 °C. vi: Pd(OAc)2, BINAP, Cs2CO3, toluene, 90 °C. vii: NEt3, NMP, 120 °C, 14 days. viii: Ac2O, NEt3, 20 °C.

  Buchwald-Hartwig N-arylation reactions. The first one allowed the N-arylation of phenylalanine ethyl ester (23) by the 2-bromonaphthalene derivatives 49a and 49b. Rather long reaction time were required: 22 hours at 105 °C and 64 hours at 100 °C, to secure respectively 67 and 54% yield of compounds 50a and 50b. Bromination of the resulting products led selectively to the bisbrominated derivative 51a and the 2-bromo-4-fluoro derivative 51b. This was followed by a10.1002/chem.202004311

Scheme 9 .

 9 Scheme 9. i: PheOEt (23; free base), neat, 0 °C. ii: 1) Zn dust, 37% H3O + Cl -, dioxane, 0-20 °C, 2) neat, 140 °C. iii: 35% AcOOH/AcOH, AcOEt, 20 °C. iv: NaOH, EtOH, 20 °C. v: Tf2O, NEt3, CH2Cl2, 20 °C. vii: NaBr, TfOH, DMF, 120 °C. vii: PheOEt (23), Pd(OAc)2, BINAP, Cs2CO3, toluene, 85 °C. viii: 1) NaOH, THF, 20 °C, 2) Ac2O, 20 °C.

Figure 1 .

 1 Figure 1. Structures of the luciferin analogues 77-87.

  to require harsher conditions than expected and even heating the reaction at 150 °C for 22 hours gave an overall 56% of the 2-chloropyridine 40 from the C-3 benzylated derivative 37. The ensuing N-arylation step with phenylalanine ethyl ester(23) gave 60% of compound 41. From this ester, a hydrolysis using sodium hydroxide followed by a cyclisation in the presence of an excess of acetic anhydride led to 32% of the target O-acetylated imidazo[1,2-a]pyridine 42.

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The structure of this compound was established by long distance NMR correlation. From this intermediate, a Suzuki-Miyaura coupling provided the phenyl in position 5 and a cleavage of its methoxy group led to the 2-hydroxypiridine derivative 39. Chlorination of this compound turned This article is protected by copyright. All rights reserved. out Scheme 5. i: PhCH2ZnBr, Pd(OAc)2, XPhos, THF, 60 °C. ii: PhB(OH)2, Pd(OAc)2, SPhos, dioxane/H2O 5:1, 90 °C. iii: 33% HBr/AcOH, 100 °C. iv: PhPOCl2, 150 °C. vi: PheOEt (23), Pd(OAc)2, BINAP, Cs2CO3, toluene, 90 °C. vii: 1) NaOH, THF, 20 °C, 2) Ac2O, 20 °C.

Table 1 . Chemiluminescence spectra of the luciferins

 1

	Cpd	DPBS Imax	+2.5M CTAB Imax	λmax
	1	4.000	1.100.000	465
	77	65.000	2.400.000	462
	78	200	28.000 a	n.s.
	79	160	1.400	n.s.
	80	250	3.200	n.s.
	81	215	602.600 a	n.s.
	82	660	2.400.000	513 b
	83	26.000	19 million c	438

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Acknowledgement

This work was supported by the Agence Nationale de la Recherche (ANR), grant ANR-11-CRNT-0004, in the context of the investment program 'GLOBAL CARE', an association of the Instituts Carnot 'Pasteur-Maladies Infectieuses', 'Curie-Cancer', 'Voir et Entendre', 'Institut du Cerveau et de la moelle Épinière' and the 'Consortium pour l'Accélération de l'Innovation et de son Transfert dans le domaine du Lymphome' (CALYM). G.G. acknowledges a PhD fellowship from the Université Paris Descartes, Sorbonne Paris Cité and E.P.C. was supported by a fellowship from Global Care. This project also benefited from the Valoexpress funding call of the Institut Pasteur. Prof. Christian Bréchot and Drs. Muriel Delepierre and Daniel Larzul are acknowledged for their interest and support. Finally, we thank Florence Miller from Berthold Technologies for her support and Aline Rifflet from the Unité de Biologie et Génétique at the Institut Pasteur for her great help in LC/MS experiments.