Cortical speech processing is dependent on the mutual interdependence of two distinctive processing streams supporting sound-to-meaning  and sound-to-articulation  mapping. Here, we compared the strengths of intracranial functional connectivity between two main hubs of the dorsal stream, namely the left auditory-related cortex (ARC) and Broca’s region, in a sample of simultaneous interpreters (SIs) and multilingual control subjects while the participants performed a mixed and unmixed auditory semantic decision task. Under normal listening conditions such kind of tasks are known to initiate a spread of activation along the ventral stream. However, due to extensive and specific training, here we predicted that SIs will more strongly recruit the dorsal pathway in order to pre-activate the speech codes of the corresponding translation. In line with this reasoning, EEG results demonstrate increased left-hemispheric theta phase synchronization in SLI compared to multilingual control participants during early task-related processing stages. In addition, within the SI group functional connectivity strength in the left dorsal pathway was positively related to the cumulative number of training hours across lifespan, and inversely correlated with the age of training commencement. Hence, we propose that the alignment of neuronal oscillations between brain regions involved in “hearing” and “speaking” results from an intertwining of training, sensitive period, and predisposition. Different experimental approaches have demonstrated that the speech perception and production systems are tightly coupled  is part of the dorsal processing stream  to German L1), totally 12, 10 women, mean age = 37.9 years, SD = 6.9 years] and multilingual controls participants . All participants were consistently right-handed, as revealed by the Annett Handedness Inventory Annett, , and wer, totallyIn the context of a block design , the participants performed four runs of a mixed [German-English (GE) and English-German (EG)] and unmixed [German-German (GG) and English-English (EE)] semantic decision task, consisting in judging whether two consecutive presented disyllabic nouns are semantically congruent  or incongruent  by pressing the corresponding response keys  was recorded with a sampling rate of 500 Hz and a high pass filter of 0.1 Hz by using an EEG-amplifier . The electrodes (sintered silver/silver-chloride) were located at frontal, temporal, parietal and occipital scalp sites according to the international 10–10 system . The online reference electrode was placed over the left mastoid (TP9), and electrode impedance was reduced to <10 kΩ by using electrogel conductant. For all pre-processing steps, we used the Brain Vision Analyser Software Package . Data were re-referenced offline to an average reference, filtered from 0.1 to 30 Hz, and artifacts were corrected by using an independent component analysis  in the left hemisphere Figure . These tp > 0.25). Normal The data were analyzed by using analyses of variance (ANOVA) as well as parametric correlations (according to Pearson’s r). Since the cumulative number of training hours as well as functional connectivity is dependent on age  were tested for normal distribution by using the Kolmogorov-Smirnov procedure (t(22) = −0.452, p = 0.656, two-tailed), in age of L2 acquisition (t(22) = −0.971, p = 0.342, two-tailed), nor in L2 listening comprehension .The two groups did not differ in age  = 28.142, p = 0.000025) and “group”  = 7.935, p = 0.010) as well as a significant “language direction” × “group” interaction effect  = 8.439, p = 0.008). Post hoct-tests for independent samples only reached significance in the language direction English-English (EE: t(22) = −3.723, p = 0.001; EG: t(22) = −0.921, p = 0.367; GE: t(22) = −0.875, p = 0.391; GG: t(22) = 0.054, p = 0.12; two–tailed). Taken together, the most errors were committed in the EE condition, whereas the main effect of “group” as well as the “group” × “language direction” interaction effect originated from a better performance of SIs during the EE condition . This procedure revealed significant effects of “language direction”  = 26.266, p = 0.001) as well as a significant “group” × “hemisphere” × “processing stage” interaction  = 5.511, p = 0.028). Additional separate 2 × 2 × 4 analyses for each hemispheres  = 4.908, p = 0.037), of “processing stage”  = 15.907, p = 0.001), as well as a significant significant “group” × “processing stage” interaction effect  = 6.959, p = 0.015) in the left hemisphere. Figure F = 14.254, p = 0.001), irrespective of group.Functional connectivity data were subjected to an omnibus 2 × 2 × 2 × 4 ANOVA . Results revealed a main effect of “processing stage” . In addition, we revealed a significant positive correlation between mean connectivity and the cumulative number of training hours across lifespan . These results indicate that the increased functional connectivity we observed in professional SIs results from an intertwining of sensitive period and training intensity , whereas the correlation between age of commencement and mean connectivity failed to reach significance .Based on the results, we additionally investigated putative relationships between mean functional connectivity during the first processing stage  and age of commencement of interpreting training. Furthermore, in order to address training-related changes in functional connectivity, we performed partial correlations (corrected for the influence of age) between left-hemispheric connectivity and the cumulative number of training hours across lifespan. Results demonstrate a negative relationship between age of commencement and mean functional connectivity (Person’s y Figure . HoweverThe main assumption of the present work was that the strong demands placed on sensory-to-articulation mapping mechanisms in SIs will have a distinctive influence on the temporal alignment of neural oscillations between the left ARC and Broca’s region. Therefore, here we evaluated θ phase synchronization between these two main hubs of the dorsal stream in both hemispheres while participants performed a mixed and unmixed auditory semantic decision task. Usually, in similar linguistic conditions brain activity spreads along the ventral processing stream by initiating a cascade of neuronal processes mirroring lexical-semantic representations (Visser and Lambon Ralph, per se. In particular, we propose that professional interpreting training leads to an automatic co-activation of these two brain regions which are involved in a variety of linguistic, articulatory, and cognitive processes.Certainly, simultaneous translation constitutes a linguistic task that places demands on the ventral pathway in order to access lexical-semantic knowledge in the target language. However, this is even true for multilingual participants, especially when they do not differ in age of L2 acquisition and are characterized by a comparable L2 proficiency level (Perani and Abutalebi, It results obvious that the extreme processing demands placed on simultaneous language translation cannot simply be considered as a magnification of the processing requirements engaged in multilingual speech processing. Otherwise, this perspective enables to set important premises for better understanding the neuronal circuits underlying speech processing in association with expertise. In this context, important steps forward have been made regarding the cortical representation of multiple languages (for an overview consider Sebastian et al., Most relevant for the the present work are especially studies providing evidence for a selective influence of multilingual speech processing and language expertise on the functional-anatomical architecture of the dorsal part of the ARC and Broca’s region. This perspective is driven by the reasoning that the ramification of multilingual speech processing on the functional-anatomical malleability of these two specific brain regions constitutes the bearing skeleton beyond the increased phase alignment we observed in SIs. In this context, there are at least some studies in earnest showing such an influence. For example, Simmonds et al.  performeThere is evidence showing that language translation is strongly dependent on the recruitment of the left dorsal pathway, in both SIs (Rinne et al., In summary, based on our results, we propose that in SIs “hearing” and “speaking” are tightly coupled in time, in such a manner that this distinctive and training-related electrophysiological signature can saliently be detected by evaluating functional connectivity in the left dorsal pathway. This is an important step toward a holistic and integrative understanding of the speech perception and production systems in the context of multilingual speech processing. Certainly, the reciprocal influence of the ventral and dorsal pathway on the two main hubs described, as well as the contribution of working memory functions, have to be described in more detail. The same is true for the influence of auto-biographical and genetic features and its relationships to functional and structural plasticity.SE collected the data, performed the statistical analyses, and wrote the manuscript. JK was involved in the connectivity analyses.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Nat. Biotech.2012,30, 1240–1243). More recent approaches employ nanowires (NWs) able to penetrate the cellular membrane and to record extra- and intracellular electrical signals, in some cases with subcellular resolution . Such techniques include nanoelectric scaffolds containing free-standing silicon NWs  or NW field-effect transistors , vertically aligned gallium phosphide NWs  or individually contacted, electrically active carbon nanofibers. The latter of these approaches is capable of recording electrical responses from oxidative events occurring in intercellular regions of neuronal cultures . Employing monocrystalline gold, nanoelectrode interfaces, we have now achieved stable, functional access to the electrochemical machinery of individual Physarum polycephalum slime mold cells. We demonstrate the “symbionic” union, allowing for electrophysiological measurements, functioning as autonomous sensors and capable of producing nanowatts of electric power. This represents a further step towards the future development of groundbreaking, cell-based technologies, such as bionic sensory systems or miniaturized energy sources to power various devices, or even “intelligent implants”, constantly refueled by their surrounding nutrients.The functional fusion of “living” biomaterial (such as cells) with synthetic systems has developed into a principal ambition for various scientific disciplines. In particular, emerging fields such as bionics and nanomedicine integrate advanced nanomaterials with biomolecules, cells and organisms in order to develop novel strategies for applications, including energy production or real-time diagnostics utilizing biomolecular machineries “perfected” during billion years of evolution. To date, hardware–wetware interfaces that sample or modulate bioelectric potentials, such as neuroprostheses or implantable energy harvesters, are mostly based on microelectrodes brought into the closest possible contact with the targeted cells. Recently, the possibility of using electrochemical gradients of the inner ear for technical applications was demonstrated using implanted electrodes, where 1.12 nW of electrical power was harvested from the guinea pig endocochlear potential for up to 5 h (Mercier, P.; Lysaght, A.; Bandyopadhyay, S.; Chandrakasan, A.; Stankovic, K.  Alf 100 nm , 5. Finaf 100 nm , 6.2 on the glass coverslip covered with 1 × 106 electrodes/cm2 with an average length of 2 ± 0.3 µm and diameter of 102 ± 12 nm (Scanning electron microscopy (SEM) analysis of the final NEI surface , 1 shows ± 12 nm , 2. The  ± 12 nm , 3 and a ± 12 nm , 4. All Physarum polycephalum  mounted on a nonconductive holding platform  to enforce membrane penetration and overcome the low proportion and stochastic nature of nanoelectrode penetration observed for mammalian CHO cells using hollow alumina nanostraws [To demonstrate the ability of our NEIs to mediate functional access to the interior of living cells, we fused them with macroplasmodia of the slime mold cephalum . This decephalum , these pplatform ,b. As Phhe setup , FG to enostraws . The elePhysarum p. sandwiched between a PGE and an NEI resulted in two distinctive states. In a first set of experiments, a mean voltage of −40 ± 6 mV was detected .In the second set of experiments, a mean voltage of +20 ± 8 mV was detectable , green. Physarum p. and closely related to its oscillating cytoplasmic shuttle streaming that develops over a similar time frame [Interestingly, during “extracellular” NEI measurements, sinusoidal potential changes frequently became detectable , green. me frame . When come frame –14, highPhysarum/NEI preparation as an “autonomous” humidity sensor, employing the cell’s intrinsic capability to respond to environmental humidity changes [Physarum/NEI sandwiches were prepared as described and the potential was recorded over time , our changes .In summary, we have demonstrated functional access to the electrochemical machinery of a eukaryotic cell system that may open the door to innovative sensor and energy harvesting applications. By employing a cell’s intrinsic signal processing and amplifying strategies, based on receptors, ion channels and signaling cascades, future applications of these technologies may attain molecular precision and/or improved energy conversion efficiency. Furthermore, since NEI analysis is not limited to single or small numbers of cells, it also allows for electrophysiological measurements and potential recordings from complete cell layers. This could compensate for individual variation and serve to amplify weak electric output for improved detection of functions such as intercellular communication.File 1Additional experimental information.


The well-established memory bias for arousing-negative stimuli seems to be enhanced in high trait-anxious persons and persons suffering from anxiety disorders. We monitored the emergence and development of such a bias during and after learning, in high and low trait anxious participants. A word-learning paradigm was applied, consisting of spoken pseudowords paired either with arousing-negative or neutral pictures. Learning performance during training evidenced a short-lived advantage for arousing-negative associated words, which was not present at the end of training. Cued recall and valence ratings revealed a memory bias for pseudowords that had been paired with arousing-negative pictures, immediately after learning and two weeks later. This held even for items that were not explicitly remembered. High anxious individuals evidenced a stronger memory bias in the cued-recall test, and their ratings were also more negative overall compared to low anxious persons. Both effects were evident, even when explicit recall was controlled for. Regarding the memory bias in anxiety prone persons, explicit memory seems to play a more crucial role than implicit memory. The study stresses the need for several time points of bias measurement during the course of learning and retrieval, as well as the employment of different measures for learning success. A hallmark finding in emotion research is that emotional items receive preferential processing. This has been evidenced by behavioral and neurophysiological methods for emotional scenes and faces e.g. , but alsInterestingly, this bias in the processing of, and memory for, emotional  stimuli is more strongly expressed in persons suffering from anxiety disorders e.g.  or in peThis is why the current study investigates the emergence of memory bias for stimuli with a recently acquired arousing-negative connotation  in high and low trait anxious persons. Learning involved the pairing of novel, word-like stimuli (pseudowords such as “muxo” or “binu”) with arousing-negative or neutral pictures. The development of the bias is monitored during learning, immediately after learning and in a follow-up two weeks later with several measures for memory performance.How is a memory bias for emotional items best assessed? Most studies investigate this bias immediately after a learning phase, and only few studies focus on the consolidation phase after learning. During consolidation, initial memory traces are stabilized, and newly acquired memory traces are integrated into existing cortical and subcortical memory networks . ExperimWhen measuring memory performance, a major distinction is drawn between explicit and implicit memory. Explicit or declarative memory is knowledge that can be consciously accessed, involving personal and world knowledge, such as trying to recall someone's name. In experimental learning contexts, it is most often measured by asking the participant to freely recall or recognize items from an earlier learned list. In contrast, implicit or non-declarative memory refers to memory that cannot be consciously accessed. Implicit memory is often measured indirectly, for example by word-fragment completion Taken together, there is evidence for the existence of a memory bias on the explicit recall of emotional stimulus material  anxiety), while evidence for an implicit bias is less clear. Despite the large body of literature on the topic, we are confident that we can add to this field by addressing the following issues. First, we measure (the emergence of) bias for neutral stimuli that gain their emotional connotation through learning. We thus avoid stimuli that already possess a particular valence  that was acquired during the participants' lifetime, or may even be innate. It is obviously impossible to have control over the emotional content of such stimuli. By using initially neutral stimuli – meaningless pseudowords - we aim at a better control of learning histories, learning strategies and depth of encoding. Second, we perform follow-up assessments with memory- and valence-related measures, to target consolidation processes. Until now, recognition or recall performance was most often measured immediately after the relevant task, although there is strong evidence for memory-enhancing effects at later post-training stages cf. . Third, We thus investigated memory biases in a situation where the negative valence of stimuli was acquired under controlled conditions. Using an associative statistical learning paradigm The associative statistical word-learning paradigm is taken as a model for language-acquisition in children and adults cf. , and offEqual groups of participants, either high or low in trait-anxiety, were tested. To measure potentially biased memories, we applied a cued-recall test and a valence rating. The recall test, a translation task, explicitly tested the newly acquired meaning of the pseudowords. The valence ratings entailed a spontaneous evaluation of the pseudowords' valence, used to assess the transfer of valence from the emotionally arousing pictures to the originally neutral pseudowords. This rating was considered to tap into implicit memory for the pseudowords' meaning, especially when explicitly remembered items were removed from the data. The valence feature is considered to be part of its semantic representation e.g.  and therGiven the current literature, we expected enhanced memory effects for aversive material during learning, directly after the training, and a potentiation of this bias after an additional time delay that allows for consolidation. We expected more pronounced effects in persons with high levels of anxiety, particularly in the explicit measurements. The tests were carried out before, directly after and two weeks after the training. If consolidation has a differential impact on the bias development in high and low-anxiety groups, differences between the two groups should increase with time.All procedures were cleared by the ethical review board of the Ärztekammer Westfalen-Lippe and subjects gave informed consent to participate. All clinical investigation has been conducted according to the principles expressed in the Declaration of Helsinki.The Spielberger State Trait Anxiety Inventory http://commons.wikimedia.org) and from the International Affective Picture System Sixty pseudowords  served as key materials and were presented auditorily. . These pseudowords were legal consonant-vowel combinations of German, taken from Breitenstein and Knecht t (49) = 15.127, p<.001; arousal: t (49) = 16.176, p<.001). Accordingly, these thirty arousing-negative pictures were rated more negative and more arousing  than the final thirty neutral non-arousing pictures . These sixty pictures served as materials in the main experiment. According to the German version of CELEX-Database t (49) = −.366, p = .716. Note that participants who performed the pre-test rating did not take part in the main experiment.A pre-test was carried out to ensure neutral or arousing-negative appraisal of the pictures. Thirty participants (psychology students from the University of Münster) were presented with 100 pictures . Subjects rated valence and arousal of all pictures via Self-Assessment Manikin (SAM)-scales During learning , the subject's task was to decide intuitively by button-press whether a spoken pseudoword and a visually presented object (color picture) matched, and were invited to guess. Participants were not informed about the upcoming recall and valence tests and received no feedback on their responses during training. The training consisted of five learning passes. During each learning pass, participants were confronted with one matching “correct” and one mismatching “incorrect” pseudoword-picture pair, separated by at least one other pair. Hence, at the end of learning pass five, participants had heard each pseudoword ten times, five times paired correctly (the same pseudoword-object combination) and five times paired incorrectly (the pseudoword paired with five different other objects that were pseudo-randomly chosen). Note that all pseudowords used in “incorrect” pairing were “correctly” paired with other pictures. Thus, all presented pseudowords could be associated with meaning, and all pseudowords and pictures appeared equally often. There were 120 pseudoword-picture pairs per learning pass , and a total of 600 pairs per training. A single learning pass lasted approximately nine minutes. The entire training lasted about fifty minutes with a pause of five minutes after the first half of the third learning pass. All trials began with a fixation cross, positioned in the centre of the screen (500 ms) Next, a pseudoword was presented via loudspeakers (≈700 ms). Another fixation cross (300 ms) and a picture (1000 ms) followed. A red exclamation mark (2500 ms) ended the trial, providing sufficient time for the subjects to decide whether pseudoword and pictured object matched. If no answer was given, the trial ended after this 2500 ms interval, and the next trial was initiated. If a button was pressed within the 2500 ms interval, the next trial began immediately.The explicit outcome of the training was assessed via cued recall. Subjects were presented with the pseudowords in written format (cues) and were asked to write down the corresponding German word (comparable with a translation or vocabulary test). A pseudoword-valence rating served as an assessment of the transfer of valence from objects to pseudowords, and served as a measurement of access to the concept's valence by means of the paired pseudoword. Subjects were asked to spontaneously and intuitively rate the pseudowords in terms of valence. Scaling ranged from minus five (very negative) to five (very positive), with zero marked as neutral.http://www.limesurvey.org/). All assessments on the first day took place in the Institute for Biomagnetism and Biosignalanalysis, affiliated to the Faculty of Medicine (Münster University). On day one, participants received written instructions but were not informed about the fact that their memory for the pseudowords would be tested.Participants were tested before, immediately after, and two weeks after training. Before training, subjects completed the first valence rating of all 60 pseudowords, immediately followed by the training. After training, the second valence rating and the first cued-recall (translation) test were administered. Two weeks later, participants were confronted with the third valence rating and the second cued-recall test. This second session was carried out online  served as a within factor, and trait anxiety (high vs. low) served as a between factor. There was an additional within-factor in each ANOVA, varying between tests, which will be described with each analysis.Performance during the training, valence rating of pseudowords and responses of the cued-recall test were analyzed by mixed design ANOVAs with repeated measures. In all three analyses, the transfer of valence of the correctly paired object to the pseudoword, labeled pseudoword affect) × 5 (learning pass) × 2 (trait anxiety) design was employed. The ANOVA and post-hoc t-tests tested the effectiveness of the training, effects of valence, and potential group differences during the learning of the pseudowords (acquisition bias).For analysis of performance during-training, the sensitivity index d' was calculated from hits, correct rejections, misses and false alarms session as an additional factor, with two levels . This resulted in a 2 (pseudoword affect) × 2 (session) × 2 (trait anxiety) mixed within/between design.Answers in the cued-recall test (translation of pseudowords into German) were treated as correct if they described the intended object , were synonyms , or subordinate-category responses that were correct descriptions of the depicted object . Responses were regarded incorrect if they described the superordinate category , semantically related objects  or unrelated objects . Incorrect answers and misses (no answer given) were excluded from further analyses. The mean of correctly translated pseudowords was subjected to an ANOVA with the factor session, with three levels . Mean valence ratings were calculated for arousing-negatively and neutrally linked pseudowords. With a 2 (pseudoword affect) × 3 (session) × 2 (trait anxiety) mixed within/between design, the development of valence ratings was investigated over time, for arousing-negatively and neutrally linked pseudowords in both anxiety groups.For analysis of the pseudoword valence ratings, the additional factor was To assess implicit effects of pseudoword affect, for those pseudowords that were not explicitly remembered, an additional repeated-measures ANOVA with the same design was performed on the valence data, after removing all explicitly remembered stimuli for each participant individually. Since the first valence rating took place before training , all sixty items  entered the analysis at this time point in all cases. For the second (directly after training) and third (two weeks after training) session, the following number of items entered the analysis: High trait anxious persons, directly after training, arousing-negative words: MEAN = 23.8, SD = 5.0, range = 11–30; neutral words: MEAN = 24.81, SD = 4.7, range = 13–30; two weeks after training, arousing-negative words: MEAN = 26.9, SD = 2.8, range = 19–30; neutral words: MEAN = 28.7, SD = 1.9, range = 21–30. Low trait anxious persons, directly after training, arousing-negative words: MEAN = 23.8, SD = 4.4, range = 16–30; neutral words: MEAN = 24.1, SD = 4.0, range = 15–30; two weeks after training, arousing-negative words: MEAN = 28.3, SD = 2.0, range = 24–30; neutral words: MEAN = 28.5, SD = 1.2, range = 26–30.learning pass, F  = 80.477; p<.001, best described as a linear F  = 106.024; p<.001 and a quadratic trend F  = 4.975; p<.030, which provided evidence for the general effectiveness of the training. However, there were no main effects for pseudoword affect or trait anxiety. Moreover, there were no significant interaction effects, except for pseudoword affect by learning pass, F  = 3.875; p = .005. There was no difference between arousing-negative and neutral affect on learning passes 1, t (53) = 1.098; p = .277 and learning pass 5, t (53) = 1.405; p = .166 There were insignificant trends in learning pass 2, t (53) = 1.701; p = .095, and 4, t (53) = −1.847; p = .070. A significant difference emerged only in learning pass 3, t (53) = 2.285; p = .026, with better learning for arousing-negatively linked than for neutrally linked pseudowords. In all, there was little evidence for an immediate overall acquisition bias for arousing-negatively linked pseudowords, and no immediate acquisition differences between high- and low-anxiety subjects.During training, accuracy rates (hits and correct rejections) continuously increased, while false alarms and misses continuously decreased see . The abipseudoword affect, F  = 8.787; p = .005. Also, recall rates were higher immediately after training than two weeks after training, as evident from the main effect of session F  = 89.760; p<.001. Moreover, the predicted interaction between pseudoword affect and trait anxiety also reached significance F  = 4.687; p = .035. As hypothesized, high-anxiety subjects recalled significantly more arousing-negatively linked pseudowords than neutrally linked ones t (26) = 3.123; p = .004. This explicit memory bias is not seen in the low-anxiety group t (26) = 0.700; p = .490. No other main effects or interactions reached significance.session , pseudoword affect, and trait anxiety showed a main effect of pseudoword affect, F  = 34.534; p<.001. Overall, subjects rated arousing-negatively associated pseudowords more negative than neutrally linked pseudowords. The rating behavior changed significantly over time, indicated by a main effect for factor session F  = 11.030; p<.001, best described as a linear trend, F  = 18.920; p<.001. The interaction between these two factors was also significant F  = 28.697; p<.001. Before training, participants did not differentiate between pseudoword affects , t (53) = 0.206; p = 0.837, confirming that pseudowords were equally neutral prior to learning. However, immediately after learning t (53) = 7.071; p<.001, and two weeks after learning t (53) = 4.024; p<.001, participants rated arousing-negatively linked pseudowords significantly more negative than neutrally linked pseudowords. There was a main effect for trait anxiety F  = 7.153; p = .010, indicating that subjects with high levels of anxiety gave generally more negative ratings than low-anxiety persons. The group ratings were contrasted to a neutral value. Prior to training, low anxious participants rated the pseudowords as more positive than this baseline  = 2.696; p = .012). Immediately after learning  =  −.884; p = .385) and two weeks later  =  −.136; p = .893) ratings did not differ from baseline. Before the training, ratings of the high anxious persons did not differ from baseline  =  −.501; p = .621). Immediately after learning  =  −2.400; p = .024) and two weeks later  =  −5.219; p<.001), ratings were negative and differed significantly from baseline.trait anxiety × session, trait anxiety × pseudoword affect and trait anxiety × session × pseudoword affect did not reach significance. Importantly, the analysis of items that were not explicitly remembered showed identical results. All significant main effects and interactions remained  = 10.740; p<.001; pseudoword affect, F  = 6.985; p = .011; anxiety, F  = 6.402; p = .014; session by pseudoword affect, F  = 4.012; p = .021). No other interaction reached significance.  yielded qualitatively the same results).The interactions We monitored the development of a memory bias for arousing-negative pseudowords during and after learning in high and low trait-anxious individuals. The results demonstrate that no more than five learning instances in an associative statistical word-learning paradigm result in a memory bias for arousing-negatively linked pseudowords, in comparison to neutral pseudowords. This bias became evident in a cued-recall test immediately after training, as well as two weeks later. Valence ratings were more negative for arousing-negatively paired pseudowords at both time points. The bias was even present for stimuli that could not be explicitly remembered. Persons with high levels of anxiety displayed a strong memory bias in the cued-recall test. Moreover, they generally rated all pseudowords as more negative than low-anxiety persons. We discuss each of these aspects in turn.As expected, only five correct and five incorrect pairings in an associative learning paradigm resulted in a memory bias for pseudowords that were paired with arousing-negative content. This once more evidences the high effectiveness of this paradigm for word learning, and its long-lasting effects Immediately after learning and two-weeks later, a memory bias became apparent in the cued-recall task. Participants were able to “translate” more learned pseudowords to German when these had been paired with negative concepts. This nicely replicates earlier findings for an explicit memory bias for emotional stimuli e.g. , but as However, the valence ratings did reveal differences between pseudowords that were paired with arousing-negative or neutral content, both immediately after learning and two weeks later. Because this bias remained even when explicitly remembered items were removed from the analysis, it rather seems to reflect implicit memory. Following our argumentation above, valence ratings must not necessarily activate elaborate associations, even when explicit recall fails. This might also explain why mere recognition of items as an explicit task failed to demonstrate a memory bias Turning to differences as a function of trait anxiety, the memory bias was present in the high trait-anxiety group but not in the low trait-anxiety group. As for all participants, and as previously reported We interpret both, the more negative judgment before learning and the over-extension of negative ratings to all pseudoword stimuli as a generalization effect, which is currently considered a core feature of the anxiety pathology e.g. . AdditioFrom a methodological viewpoint, our study stresses the importance of measurements at multiple time points before, during and after learning, as well as the employment of different methods to assess learning and memory.Although some criticisms to earlier studies have been dealt with in the current study, we should point out some limitations, and make suggestions for future studies. First, we analyzed two extreme groups , a design that is well established and often applied in similar studies. However, It would be interesting to know whether persons with moderate trait anxiety exhibit a memory bias in our type of learning paradigm. Thus, future studies should include a group with average trait anxiety scores. Second, we carefully controlled individual learning histories by applying pseudoword stimuli in our training. However, the pictures that were used to link the formerly neutral pseudowords with aversive and neutral content might have evoked emotional associations of quite varying intensity in our participants. The pictures were neither presented in the cued recall test nor in the valence rating, so there are no data on this issue. Yet it is likely that the acquired emotionality varied for the pseudoword material. Stimuli that are not perceived equally frightening by all participants provide a general and challenging problem. Even loud tones and electric shocks, which might at first glance seem objectively similar and free from individual leaning histories, are perceived differently due to individually differing pain thresholds. Third, pseudowords, when paired incorrectly, were combined with both neutral and arousing-negative pictures, and thus with mixed valence. The pairing in the correct condition was always with the same picture, and thus with the same valence. Given that the differentiation between arousing-negatively and neutrally linked pseudowords was significant in the middle of training but disappeared towards the end, it can be speculated that the increasing mixture of valences in the incorrect condition caused a confusion that diminished the initial immediate memory bias effect. Future studies could check for this by keeping the valence of correct and incorrect pairings constant. Fourth, we cannot be sure that our participants did not apply an explicit memory strategy during word learning. If this is the case, the word learning would have been rather explicit and the learning of the pseudo words happened via translation of the pictures to German words. However, because we controlled for the word frequency of German words, this does not explain the observed differences between emotional and neutral words. We also performed the analyses concerning valence by excluding the explicitly remembered words. Because results did qualitatively not differ, we strongly assume that the observed effects are not due to a retrieval of corresponding German word forms. In fact we chose a short and relatively shallow learning history in order to perform these analyses. The brevity was intended to keep the participants from in-depth learning of the stimulus material. Such deep learning took place in our earlier studies In sum, our data demonstrates that only few learning instances evoke a memory bias for pseudowords paired with arousing-negative meaning. This bias is evident in explicit and implicit tests of memory, and is more strongly expressed in persons with high levels of anxiety. The learning paradigm with its associations between emotional content and neutral linguistic stimuli goes beyond classical, operant and evaluative conditioning paradigms mainly used so far in emotion research. It allows monitoring the development of a memory bias during learning, and how it evolves after learning. As such, we consider the paradigm highly suitable for the investigation of affective disorders and how they come into existence.


Deficiency risks for Fe are lower than expected (5%). However, ‘cut-point’ approaches for Fe are sensitive to assumptions regarding requirements; e.g. estimates of Fe deficiency risks are 43% under very low bioavailability scenarios consistent with high-phytate, low-animal protein diets. Fertilization and breeding strategies could greatly reduce certain MNDs. For example, meeting harvestplus breeding targets for Zn would reduce dietary Zn deficiency risk by 90% based on supply data. Dietary diversification or direct fortification is likely to be needed to address Ca deficiency risks.Dietary micronutrient deficiencies (MNDs) are widespread, yet their prevalence can be difficult to assess. Here, we estimate MND risks due to inadequate intakes for seven minerals in Africa using food supply and composition data, and consider the potential of food-based and agricultural interventions. Food Balance Sheets (FBSs) for 46 countries were integrated with food composition data to estimate per capita supply of calcium (Ca), copper (Cu), iron (Fe), iodine (I), magnesium (Mg), selenium (Se) and zinc (Zn), and also phytate. Deficiency risks were quantified using an estimated average requirement (EAR) ‘cut-point’ approach. Deficiency risks are highest for Ca (54% of the population), followed by Zn (40%), Se (28%) and I . The risk of Cu (1%) and Mg (<1%) deficiency are low. Deficiency risks are generally lower in the north and west of Africa. Multiple MND risks are high in many countries. The population-weighted mean phytate supply is 2770 mg capita For some micronutrients, such as Fe, Se and Zn, mineral status can be analyzed directly via whole blood or plasma fractions or indirectly via activities of micronutrient-responsive enzymes , including calcium (Ca), copper (Cu), iron (Fe), iodine (I), magnesium (Mg), selenium (Se) and zinc (Zn) are likely to be widespread in global terms , which is distributed normally around the estimated national mean per capita supply.An alternative method for estimating MND risks at wide scales is to use per capita food supplies from food balance sheets (FBSs) as a proxy for food consumption  in Africa  content of seeds occurs as mixed salts of phytic acid −1  and Zn  were based on ‘low dietary bioavailability’ which is appropriate for most diets in developing countries and assumes 10% bioavailability for Fe and 15% for Zn ; during lactation, the EAR for Zn was the weighted average of 0–3, 3–6 and 6+ months, assuming 24 months of lactation (i.e. 12.8 mg day−1). For pregnant and lactating women aged 15–19 years, the Zn EARs during both the third trimester and 0–3 months of lactation periods were assumed to be double to those of non-pregnant women of the same age group  using WHO and Institute of Medicine (IOM) data IOM , because WHO/FAO . Use of  WHO/FAO , p. 264. WHO/FAO , p. 238.microsoft access 2010, Microsoft Corporation, Redmond, WA). A per capita supply of each micronutrient was estimated for each country in Africa based on the product of food supply and composition (Table S6). Daily intake within populations was assumed to follow a normal distribution based on mean per capita supply and a cv of 25% to account for inter-individual variation in intake, as in a previous study . Subsequently, FBS items were assigned to six high-level food groups  so that the contribution of each food group to micronutrient supplies could be assessed.The risks of MNDs were estimated using an EAR ‘cut-point’, and those at risk are assumed to be the proportion of the population with intakes below the EAR  to 3851 (Egypt) kcal capita−1 day−1 (Table S7). Energy supply was considerably lower in the Middle and Eastern regions than in the Northern, Western and Southern regions  was 2937 kcal capita−1 day−1, the mean Ca supply (population-weighted) was 645 mg capita−1 day−1, ranging from 190 (Lesotho) to 1518 mg capita−1 day−1 (Uganda). The median national Ca supply was 574 mg capita−1 day−1. Among the higher level food groups, ‘Animal Products’ provided the greatest single contribution to Ca supply . If all of Africa was to meet its RNI for Ca, this would require 769 t day−1 of mineral Ca, approximately 130 t more than the current supply. This is the equivalent of 60–120 million L day−1 of milk depending on its Ca concentration.The estimated mean risk of dietary Ca deficiency throughout Africa was 54%, the greatest deficiency risk of all micronutrients studied Tables and S6 a−1 day−1, mean Cu supply (population-weighted) was 2.11 mg capita−1 day−1, ranging from 0.60 (Liberia) to 3.46 mg capita−1 day−1 (Niger). The median national Cu supply was 1.84 mg capita−1 day−1. On average, ‘Cereals’ contributed 45% of Cu supply throughout Africa .The mean estimated risk of Cu deficiency was 1.1%  was 27.6 mg capita−1 day−1, ranging from 7.9 (Madagascar) to 87.1 mg capita−1 day−1 (Niger). The median national Fe supply was 22.8 mg capita−1 day−1, of which ‘Cereals’ provided 57% .The mean estimated risk of Fe deficiency was 5% and was greatest in the Eastern region 14%) followed by the Southern (5%), Northern (2%), Middle (2%) and Western (<1%) regions  was 171 µg capita−1 day−1, ranging from 52 (Djibouti) to 300 µg capita−1 day−1 (Tunisia). The median national I supply was 157 µg capita−1 day−1. The supply of I was dominated by iodized salt, which contributed 63% of the total supply in Africa. Estimates of the use of sufficiently iodized salt (>15 ppm) ranged from 0% of households (Djibouti) to 98% (Kenya). Without I supply through salt, 89% of the population of Africa would be at risk of I deficiency due to inadequate dietary supply. The contribution of food to total I supply is important as ‘Cereals’ and ‘Animal Products’ contributed 19 and 11%, respectively, of the total I supply in Africa (Tables S8–S10). This high contribution of cereals to I intake is perhaps surprising given that this element is not readily translocated to cereal grains; there is need for further grain I composition data to confirm this finding. National per capita energy and I supply  were positively correlated .The mean estimated risk of I deficiency  was 19% and was greatest in the Middle region (33%), followed by the Eastern (26%), Southern (26%), Northern (19%) and Western (5%) regions  was 678 mg capita−1 day−1, ranging from 179 (Eritrea) to 1797 mg capita−1 day−1 (Burkina Faso); the median national Mg supply was 569 mg capita−1 day−1. ‘Cereals’ and ‘Roots and Tubers’ contributed 65 and 11%, respectively, of the Mg supply across the continent .The mean estimated risk of Mg deficiency was 0.7% Tables and S6. −1 day−1, the mean Se supply (population-weighted) for Africa was 55 µg capita−1 day−1, ranging from 23 (Liberia) to 93 µg capita−1 day−1 (Burkina Faso). The median national Se supply was 50 µg capita−1 day−1. ‘Cereals’ contributed 52% of Se supply throughout Africa .The mean estimated risk of Se deficiency was 28% and was greatest in the Eastern region (52%), followed by the Middle (49%), Southern (26%), Northern 12%) and Western (6%) regions  was 12.9 mg capita−1 day−1, ranging from 6.0 (Eritrea) to 26.9 mg capita−1 day−1 (Niger). The median national Zn supply was 11.5 mg capita−1 day−1. ‘Cereals’ contributed 56% of Zn supply across the continent .The mean estimated risk of Zn deficiency was 40% Tables and S6 a−1 day−1, ranging from 1004 (Congo) to 4769 mg capita−1 day−1 (Niger) (−1 day−1. Phytate:Zn molar ratios ranged from 7.2 (Gabon) to 37.7  with mean and national median ratios of 22.6 and 19.9, respectively (Table S11). The mean national contribution of ‘Cereals’ to phytate supply was 68%, with a further 17% from ‘Pulses and Beans’ and 7% from ‘Roots and Tubers’ (Table S8–S10).The mean supply of phytate (population-weighted) was 2770 mg capita−1 day−1, ranging from 290 (Eritrea) to 719 g capita−1 day−1 (Ghana). The mean national contribution of ‘Cereals’ to available carbohydrate supply was 55%, with ‘Roots and Tubers’ contributing a further 23%. The mean supply of protein (population-weighted) was 77 g capita−1 day−1, ranging from 30 (DRC) to 123 g capita−1 day−1 (Tunisia). The mean national contribution of ‘Cereals’ to protein supply was 50%, with ‘Animal Products’ contributing a further 25%. The mean supply of fat (population-weighted) was 58 g capita−1 day−1, ranging from 20 (Burundi) to 94 g capita−1 day−1 (Libya). The mean national contribution of ‘Animal Products’ to fat supply was 25%, with ‘Other foods’ contributing a further 33%, mainly due to cooking oils.The national supplies of macronutrients are given in Table S7, while the contributions of higher level food groups to macronutrient supply are given in Tables S8–S10. The mean supply of available carbohydrate (population-weighted) was 488 g capitaThe risk of MNDs is estimated to be high in Africa based on dietary supply as calculated from FBSs and food composition tables, notably Ca , Zn (40%), Se (28%) and I . Calcium and I deficiency risks are highest in the Southern region, Zn deficiency risks are highest in the Eastern region and Se deficiency risks are highest in the Eastern and Middle regions. Many countries have high multiple MND risks. For example, in Ethiopia, the estimated deficiency risks for Ca, I, Se and Zn are 100, 64, 36 and 81%, respectively; the corresponding risks for Malawi are 61, 27, 64 and 33%, respectively Tables, p. 156 −1 day−1 in Egypt and Eritrea, respectively), probably due to inaccurate supply data. Inherent weaknesses in FBS data have been discussed extensively −1 FW in the Southern region composition table, which was also used for the Northern region. These differences in food composition data result from the inclusion or non-inclusion of small bones which have higher Ca concentrations than fish meat. Interestingly, if a ‘Freshwater Fish’ Ca concentration of 2360 mg (100 g)−1 FW was used in the Northern region composition table, Ca supply would increase from 599 to 796 mg capita−1 day−1, whereas a similar change for the Southern region would have minimal effect (from 353 to 357 mg capita−1 day−1) due to low supply of ‘Freshwater Fish’ in national FBSs for this region. If this higher concentration was used for all regions, the estimated risk of Ca deficiency across Africa would decrease from 54 to 48%. Conversely, if the Ca composition of ‘Freshwater Fish’ used in the Western and Eastern region composition tables was reduced to 86 mg (100 g)−1, Ca supply would decrease in the Eastern region from 583 to 359 mg capita−1 day−1, in the Western region from 746 to 541 mg capita−1 day−1 and in the Middle region from 764 to 492 mg capita−1 day−1. If this lower concentration was used for all regions, the estimated risk of Ca deficiency across Africa would increase markedly from 54 to 80%.For Ca, the FBS category ‘Freshwater Fish’ provided 40, 37 and 28% of total supply in the Eastern, Middle and Western regions, respectively, while only contributing <2% in the Southern and Northern regions, primarily due to differences in food composition values between regions. Thus, Ca concentrations for ‘Freshwater Fish’ are 2360 and 2814 mg (100 g)−1 in the Western region composition table, considerably higher than in the Southern or Eastern region composition tables, which use the same value of 2.6 µg (100 g)−1. Chilimba et al. −1 on calcareous vertisols. The effect of soil conditions on Se concentration of other food items is not known, but will clearly affect estimates of dietary Se supply greatly.The FBS category ‘Maize’ has a Se concentration of 16 µg (100 g)a et al.  showed t−1 day−1) and given that acute and chronic inflammation can impair absorption of Fe from the gut, it might be more appropriate to assume 5% dietary bioavailability. At 10% bioavailability, the EAR for Fe for pregnant women is 41.2 mg capita−1 day−1 while that for non-pregnant women of childbearing age is 13.4 mg capita−1 day−1; at 5% bioavailability, the corresponding EARs are 82.4 and 26.8 mg capita−1 day−1  were used in preference to WHO  on the basis of recent research  to give an adult EAR of 625 mg capita−1 day−1  and narrower (cv = 20%) distributions of intakes on estimated risks of deficiency.Our study assumes that intake of each micronutrient in each country follows a normal distribution centered on mean dietary supply, with a nd Brown  to estimnd Brown  to estim−1 day−1, respectively, with a phytate:Zn molar ratio of 21.3 This compares to our estimate of mean Zn and phytate supplies (population-weighted) for the Eastern, Southern, Western and Middle regions of 12.0 mg and 2728 g capita−1 day−1 and a mean phytate:Zn molar ratio of 23.8. These differences in Zn supply data are likely to originate from the food composition data. Wessells and Brown  in the diets of 113 adult women. These values are generally lower than our estimates for Fe and Zn supplies in Malawi  and phytate:Zn molar ratio (37.7); this was the highest ratio observed for Africa based on supply data and was driven by the high phytate supply (4510 mg capita−1 day−1), approximately 65% of which comes from maize. In general, it is expected that FBSs will overestimate supply, including that of micronutrients and phytate, compared to dietary surveys or analyzed diet composites given that losses during food processing and preparation and household waste are not considered. Andersson et al. . The micronutrient and macronutrient composition of these food groups was calculated at a national scale, weighted according to the supply of the constituent items within each group and the appropriate regional food composition table. In addition to national-level EARs, national mean RNIs were calculated using WHO intake requirement data for Ca, Fe, I, Mg and Zn WHO/FAO  and IOM d EU SCF . A TUL fMicrosoft Excel 2010 (Microsoft Corporation) was used to minimize the ‘Total Error’ term. Energy supply was constrained to remain below the starting value and above a level defined as national mean daily energy requirement, which is the quantity of food energy needed to balance energy expenditure and maintain body size, body composition and a level of necessary and desirable physical activity consistent with long-term good health, assuming light work (Table S5) (FAO/WHO 2001). A standard physical activity level of 1.9 and mean body weights of 70 and 65 kg were assumed for adult men and women, respectively; WHO reference weights were used for children and adolescents , fat supply was constrained so as not to increase further. Salt (NaCl) supply was not allowed to increase beyond 5 g capita−1 day−1, the intake target set by WHO (WHO/FAO −1 day−1) and Malawi (8.2 g capita−1 day−1) both had high initial supplies of salt and were therefore constrained not to increase further.The supply of each of the 17 higher level food groups was allowed to increase or decrease by one- to two-fold, relative to 2009 supply. The Solver function of  FAO/WHO . A stand FAO/WHO , and pro FAO/WHO . PregnanRDAs IOM . Fat intRDAs IOM , p. 941.RDAs IOM , p. 941. WHO/FAO , p 90. NFor Malawi, the ‘Total Error’ term was 2.40 for 2009 supply data. The main sources of error were an undersupply of Ca (0.59), Se (0.61), Zn (0.39), fat (0.43) and I (0.35). Using a constraint of 1.3-fold, the ‘Total Error’ term decreased to 1.86, indicating that the average Malawi diet could theoretically be ‘improved’ in terms of micronutrient supply through dietary diversification . This im−1 day−1 compared to the mean population TUL of 43 mg capita−1 day−1. Using a constraint of 1.3-fold, the ‘Total Error’ term decreased to 0.76, mainly through a decreased supply of Fe-rich food groups including millet and sorghum, but also through increased supply of Ca-rich groups including dairy and fish. Using constraints of 1.6- and 2-fold, the ‘Total Error’ term decreased to 0.53 and 0.32, respectively.For Nigeria, the ‘Total Error’ term was 1.07 for 2009 supply data. The main sources of error were Fe (0.64), Ca (0.28) and Zn (0.12). The errors for Ca and Zn resulted from insufficient dietary supply, with 27 and 10% respectively, being below the EAR. The error for Fe, however, resulted from a high proportion of the population (63%) being above the TUL due to a supply of 47 mg capita−1, respectively) which, combined with their relatively high Fe concentrations, supply 8.8 mg capita−1 day−1 and 13.6 mg capita−1 day−1 of Fe. However, as estimated energy supply in Nigeria was improbably high , the supply data are likely to have been overestimated. Contaminant Fe from soil is a potentially large source of dietary intake via a wide range of crops  maize flour of approximately 30 mg kg−1 . Thus, 0.1% soil contamination would approximately double Fe intakes from maize, primarily in ferric (Fe3+) oxide forms whose bioavailability is uncertain. Siyame et al. , with smaller undersupplies of I (0.29), Se (0.16), Zn (0.10) and Fe (0.09). Using a constraint of 1.3-fold, the ‘Total Error’ term decreased to 1.29 but undersupply of Ca (0.91) still dominated. The supply of Ca-rich food groups, including animal-sourced foods  and ‘Pulses and Beans’, all increased to their constrained maxima. Using a constraint of twofold, the ‘Total Error’ term decreased to 0.73 and the undersupply of Ca (0.54) still dominated, with 25% of the population below the national mean LRNI for this element, and 31% between the LRNI and EAR.−1 day−1, rising to 18 and 7% of females and males aged 11–18 years, respectively , despite a large consumption of dairy products which would be unachievable in the short term for many African households. In the UK, almost three-quarters of Ca intake comes from dairy products and cereals −1) and wheat malt flour. Although flour fortification programs exist or are under development in several African countries, levels of compliance are often poor  per capita supply of dietary I would fall from 171 to 125 µg day−1, with the estimated risk of dietary I deficiency increasing from 19 to 35% of the population. In addition, increased Na intake may increase urinary excretion of Ca, with a 1 g increase in Na intake increasing Ca excretion by approximately 30 mg , gypsum (CaSO4), Ca-phosphates, Ca(NO3)2 and a range of foliar products could potentially be used to increase Ca concentration in crops such as leafy vegetables, while addition of manure and charcoal can increase soil Ca concentration and decrease leaching in highly weathered tropical soils  in polished rice, 59 and 38 µg g−1 DM in wheat, 60 and 38 µg g−1 DM in maize, 88 and 66 µg g−1 DM in pearl millet, 107 and 56 µg g−1 DM in beans, 45 and 34 µg g−1 DM in cassava roots and 85 and 70 µg g−1 DM in the roots of sweet potato, respectively (Bouis and Welch −1 (Table S12) and mean estimated risk of Zn deficiency in Africa would decrease from 40 to 23%. Mean phytate:Zn molar ratio would also decrease from 22.6 to 18.3 and would be >15 in 38 of the 46 countries instead of the current 42. If HarvestPlus breeding targets for Zn were met for rice, wheat, maize, pearl millet, beans, cassava roots  and sweet potato , mean (population-weighted) per capita supply of dietary Zn would increase to 22.7 mg day−1 and the estimated risk of deficiency in Africa would decrease to just 4%. Only seven countries  would have a mean phytate:Zn molar ratio of >15.Plant breeding offers another feasible biofortification strategy to increase the dietary supply of micronutrients essential in the human diet by (1) increasing micronutrient uptake by crops from the soil, (2) increasing the their translocation from leaves to the grain or fruit of crops or (3) reducing the biosynthesis of compounds which inhibit absorption of micronutrients in the gut, such as phytate  and Ca2+-binding proteins such as calreticulin. Interestingly, if Ca concentrations of the single FBS category ‘Vegetables, other’ could be doubled in all regions through breeding or agronomy, the mean (population-weighted) supply of dietary Ca would increase from 645 to 683 mg capita−1 day−1 and the mean estimated risk of Ca deficiency would decrease from 54 to 48%. However, it should be noted that the FBS category ‘Vegetables, other’ encompasses a wide range of leafy and non-leafy vegetables which vary in Ca concentration and bioavailability, e.g. due to varying levels of oxalic acid. It is currently thought that breeding crops for increased Se uptake using conventional means is unlikely to be effective based on observed genetic variation among cereal germplasm collections  and a mean phytate:Zn molar ratio of 22.6, it may be appropriate to consider lower phytate cereals and beans to complement other agricultural strategies such as biofortification through micronutrient fertilization or lower phytate breeding  have also been reported in a range of crops including wheat, maize, rice and soybean  have potential for low phytate breeding based on extensive genetic variation in seed phytate concentration among germplasm collections (reviewed by White and Broadley −1 day−1. Mean (population-weighted) phytate:Zn molar ratio would be 14.6 and would be >15 in only 16 of the 46 countries studied. However, in addition to the possible reduced agronomic performance of crops, any attempts to reduce phytate in human diets should proceed with caution because dietary phytate intake has been linked to health benefits including reduced risk of cancer and osteoporosis  supply of dietary phytate would decrease from 2770 to 1782 mg capitaMNDs are a widespread public health problem affecting billions of people worldwide. While data and methodologies exist to determine the prevalence of some MNDs, there is a dearth of estimates of country-level prevalence rates for others. We combined data from FAO FBSs, regional food composition tables and salt iodization to estimate dietary mineral supplies of Ca, Cu, Fe, I, Mg, Se and Zn for 46 countries in Africa. We then estimated the risk of MNDs due to inadequate dietary intake using an EAR ‘cut-point’ approach. There are high risks of MNDs in Africa for Ca (54% of population), Zn (40%), Se (28%) and I (19%), whereas the risks of deficiency for Fe (5%), Cu (1%) and Mg (<1%) are much lower.Of course, these estimated MND risks are contingent on major caveats and assumptions, including the quality of the input data and the validity of the dietary requirements used. For example, the estimated Fe deficiency risk is based on intake requirements which assume that 10% of Fe is bioavailable in food. Estimates of Fe deficiency risks are much greater (43%) if Fe absorption is assumed to be 5%, which is plausible based on high phytate supply and other factors. This example illustrates that, while supply-based approaches are a useful framework, they must be interpreted with caution. Further studies are needed to determine how, and to what extent, our methodology can be used, especially for Fe deficiency.We have shown how a supply-based methodology can provide evidence to address crucial questions regarding how to address hidden hunger in Africa or elsewhere. To demonstrate this, we assessed the possible influence of dietary diversification and dietary change within realistic boundaries by simulating an alteration of the food supply in Malawi, Nigeria and South Africa. This analysis showed – unsurprisingly – that if the current consumption of cereals and cassava was partially replaced by other food groups, especially animal products and vegetables, the risk of dietary deficiencies could be reduced. However, dietary diversification on its own is still unlikely to meet all mineral requirements in the region.Given the growing interest in using agriculture-based strategies to address MNDs, we also simulated a scenario in which current rice, wheat, maize, pearl millet, beans, cassava and sweet potato varieties are biofortified with Zn. As breeding of such varieties is currently taking place, knowing whether this is a potentially effective intervention is important. Our analysis suggests that such an improvement in the dietary quality of key crops could reduce the risk of inadequate dietary Zn supply in Africa from 40% to just 4%. A complementary intervention is the application of mineral fertilizer to staple food crops to increase the supply and uptake of crucial nutrients. Further studies of such approaches are needed, in particular regarding the potential coverage and costs of interventions, whether through breeding or fertilizer application. Finally, we believe that Tables S1–S12 provide a useful ‘audit trail’ so that: (1) potential errors can be identified, (2) additional nutrients (or antinutrients/contaminants) can be added to the analysis and (3) alternative food composition data can be incorporated at different spatial scales.


Scientific Reportshttps://doi.org/10.1038/s41598-022-21987-7, published online 16 November 2022Correction to: The original version of this Article contained errors in the legends of Figure 8 and 10.41 matches, (d) shows RootSIFT28 matches,  shows EpicFlow10 and HybridFlow results. © His Majesty the King in Right of Canada, as represented by the Minister of National Defence, 2022.”Figure 8. “Density of matches. The first row  shows an example of the input image frames, copyright of Valcarier DRDC, (c) shows SIFTnow reads:41 matches, (d) shows RootSIFT28 matches,  shows EpicFlow10 and HybridFlow results.”Figure 8. “Density of matches. The first row  shows an example of the input image frames, © His Majesty the King in Right of Canada, as represented by the Minister of National Defence, 2022., (c) shows SIFTFigure 10. “ Are two consecutive large-scale aerial images of a downtown urban area with resolution 6600 × 44006600 × 4400, copyright of Valcarier DRDC. (c) HybridFlow is the only top-performing variational method that can handle high-resolution images. Deep learning techniques cannot be applied due to the fixed input size of the networks as explained in the text. (d) Image resampled from (a) using HybridFlow flows in (c) to form (b). (e) Reconstructed pointcloud using 320 images. © His Majesty the King in Right of Canada, as represented by the Minister of National Defence, 2022.”now reads:Figure 10. “ Are two consecutive large-scale aerial images of a downtown urban area with resolution 6600 × 4400, © His Majesty the King in Right of Canada, as represented by the Minister of National Defence, 2022. (c) HybridFlow is the only top-performing variational method that can handle high-resolution images. Deep learning techniques cannot be applied due to the fixed input size of the networks as explained in the text. (d) Image resampled from (a) using HybridFlow flows in (c) to form (b). (e) Reconstructed pointcloud using 320 images.The original Article has been corrected.


Prunus avium L.) fruit is a labor-intensive process. The mechanical harvesting of sweet cherry fruit is feasible; however, it is dependent on the formation of an abscission zone at the fruit–pedicel junction. The natural propensity for pedicel—fruit abscission zone (PFAZ) activation varies by cultivar, and the general molecular basis for PFAZ activation is not well characterized. In this study, ethylene-inducible change in pedicel fruit retention force (PFRF) was recorded in a developmental time-course with a concomitant analysis of the PFAZ transcriptome from three sweet cherry cultivars. In ‘Skeena’, mean PFRF for both control and treatment fruit dropped below the 0.40 kg-force (3.92 N) threshold for mechanical harvesting, indicating the activation of a discrete PFAZ. In ‘Bing’, mean PFRF for both control and treatment groups decreased over time. However, a mean PFRF conducive to mechanical harvesting was achieved only in the ethylene-treated fruit. While in ‘Chelan’ the mean PFRF of the control and treatment groups did not meet the threshold required for efficient mechanical harvesting. Transcriptome analysis of the PFAZ region followed by the functional annotation, differential expression analysis, and gene ontology (GO) enrichment analyses of the data facilitated the identification of phytohormone-responsive and abscission-related transcripts, as well as processes that exhibited differential expression and enrichment in a cultivar-dependent manner over the developmental time-course. Additionally, read alignment-based variant calling revealed several short variants in differentially expressed genes, associated with enriched gene ontologies and associated metabolic processes, lending potential insight into the genetic basis for different abscission responses between the cultivars. These results provide genetic targets for the induction or inhibition of PFAZ activation, depending on the desire to harvest the fruit with or without the stem attached. Understanding the genetic mechanisms underlying the development of the PFAZ will inform future cultivar development while laying a foundation for mechanized sweet cherry harvest.The harvesting of sweet cherry ( In. In34]. 2.4.g at 4 °C for 15 min, and the aqueous upper phase was transferred to a sterile 1.5 mL microcentrifuge tube. To this, 600μL 2-propanol was added, inverted 5–6 times, and incubated at RT for 10 min. Samples were centrifuged at 17,000× g at 4 °C for 10 min, and the supernatant decanted. Then, 1 mL 75% DEPC ethanol was added to the pellet, vortexed for 10 s, and centrifuged at 9500× g at 4 °C for 5 min. Pellets were suspended in RNase free water and incubated at 37 °C with RNase free DNaseI for 30 min, which was subsequently inactivated .Excised sweet cherry abscission-zone-region tissue derived from ten fruits representing ten biological replicates/cultivar/time point was pooled, pulverized and homogenized into a single sample using a SPEX SamplePrep FreezerMill 6870  and transferred to storage at −80 °C. Total RNA was extracted using an acid guanidinium thiocyanate phenol chloroform extraction method similar to that previously described . BrieflyExtracted RNA was quantified, and its quality was checked using the Bio-Rad  Experion system using the Experion RNA High Sensitivity Analysis kit or the Agilent  2100 Bioanalyzer system using the RNA NanoChip and Plant RNA Nano Assay Class.2.5.RNA samples that passed the quality threshold of RIN 8.0 were sequenced at the Michigan State University Genomics Service Center for library preparation and sequencing. The Illumina Hi Seq 2000 sequencing platform  was used to sequence 2 × 100 PE reads from the cDNA libraries generated from the above RNA extractions, representing a single sample derived from 10 biological replicates of each cultivar, treatment, and time point. cDNA and final sequencing library molecules were generated with Illumina’s TruSeq RNA Sample Preparation v2 kit  and instructions with minor modifications. Modifications to the published protocol include a decrease in the mRNA fragmentation incubation time from 8 min to 30 s to create the final library of proper molecule size range. Additionally, an Aline Biosciences’  DNA SizeSelector-I bead-based size selection system was utilized to target the final library molecules for a mean size of 450 base pairs. All libraries were quantified on a Life Technologies  Qubit Fluorometer and qualified on an Agilent  2100 Bioanalyzer.Read preprocessing and assembly were conducted in CLC Genomics Workbench (8.5.1). Briefly, RNAseq read datasets were processed with the CLC Create Sequencing QC Report tool to assess read quality. The CLC Trim Sequence process was used to trim the first 16 bases due to GC ratio variability and for a Phred score of 30. All read datasets were trimmed of ambiguous bases. Illumina reads were then processed through the CLC Merge Overlapping Pairs tool, and all reads were de novo assembled to produce contiguous sequences (contigs). A single master assembly was generated from the combined read data from the ‘Bing’, ‘Chelan’, and ‘Skeena’ cultivars at each time point . Assembl2.6.A two-pronged approach, using Kal’s Z-test and the NOIseq-sim R package, was employed to identify contigs with the highest likelihood of being differentially expressed –38. OnlyGenes with the highest probability of being differentially expressed were first identified using the NOISeq-sim package in OmicsBox, which is designed to infer the probability of differential expression by modeling biological replications in silico for RNAseq experiments –39. ThisNext, Kal’s Z-tests were performed in CLC Genomics Workbench 8.5.1 to add another level of stringency to the identification of differentially expressed genes. A paired experiment comparing the read count values for ethephon treatment to control values corresponding to each cultivar was performed.p-value < 0.05  |log2FC| > 1, (2) NOIseq probability of DE > 0.8, (3) Kal’s Z-test FDR corrected e < 0.05 .2.7.Assembled sweet cherry contigs were annotated using the Blast2GO feature in Omics-Box (version 1.2.4). Contigs were blasted for greatest sequence homology against the NCBI Viridiplantae database and subsequently assigned to their corresponding gene ontology (GO) terms as described previously –44.p-value < 0.05, and |logFC| > 1 at the harvest time point were produced. These lists served as the treatment datasets for enrichment analyses, and the master annotated transcriptome was used as the reference dataset , and 10 μL of iTAQ SYBR Green Supermix with ROX. The RT-qPCR reactions were performed on a Stratagene MX3005 using the following parameters: 95 °C 5 min; 50 cycles of 95 °C 30 s, 57 °C 30 s, 72 °C 30 s; 72 °C 5 min. Fluorescence readings were taken at the end of each elongation step. A melting step was performed following the cycles at 95 °C for 30 s, 54 °C for 30 s and ramp up to 95 °C to produce a dissociation curve.Library preparation, target amplification, and expression analysis were conducted in accordance with previously published methods, with minor modifications . The Invitrogen  VILO cDNA synthesis kit was used to generate three biological replicates of cDNA from three independent RNA samples isolated for each time point per manufacturer’s instructions. Replicate cDNAs were then pooled into a single sample (50 ng/uL). At least 4–6 technical replicate RT-qPCR reactions were performed using iTAQ with ROX and SYBR (BioRad), and 20 μL reactions were prepared as per the manufacturer recommendations. A total of 2 μL of cDNA diluted to 50 ng/μL RNA equivalents was used per reaction with 5 μL HTo capture PCR efficiency in the data, Cq values and efficiencies were calculated for each reaction using the LinRegPCR tool . Cq values resulting from efficiencies below 1.80 or above 2.20 were judged unacceptable and were treated as unsuccessful or undetected amplifications. Cq values with efficiency values that were within expected parameters but exceeded  40.00 were also deemed unacceptable and disregarded in downstream analysis. In the same manner, Cq values of 35.00–39.99 were determined to be of low confidence and were marked for special consideration in downstream analysis. Fold-change expression was determined from the Cq values of all gene targets  among the ‘Bing’, ‘Chelan’, and ‘Skeena’ cultivars using the Pfaffl method . Expression values were determined with reference to the luciferase spiked gene .2.9.The GATK best practices pipeline for short variant discovery was used to identify SNPs and indels in key, differentially expressed ethylene- and auxin-associated contigs, with minor modifications ,46. Brie3.3.1.The application of ethephon at 80% of fruit development  ensured In ‘Skeena’, mean PFRF for both control and treatment fruit dropped below the 0.40 kg-force (3.92 N) threshold for mechanical harvesting, reaching final mean PFRF values of 0.29 kg-force (2.84 N) and 0.156 kg-force (1.53 N), respectively . These fSimilarly, for ‘Bing’, mean PFRF for both control and treatment groups decreased over time; however, a mean PFRF conducive to mechanical harvesting was only achieved in the ethephon-treated fruit, which reached a final PFRF value of 0.215 kg-force (2.11 N), significantly lower than the control value of 0.418 kg-force (4.1 N) . This su‘Chelan’ exhibited a statistically significant PFRF response at the time of harvest in the ethephon-treated fruit in comparison with the control; however, the final PFRF of 0.832 kg-force (8.16 N) of the treatment group was not reduced to the threshold required for efficient mechanical harvesting . These p3.2.The transcriptome assembly resulted in the generation of 82,587 contigs from 1,061,563,488 total trimmed reads. Contigs were subsequently filtered for >200 base length and >2x coverage, for a final total of 81,852 contigs for downstream processing . Functio3.3.Based on our NOIseq/Kal’s test approach, 1274 genes were identified to be differentially expressed in ethephon-treated ‘Bing’, 715 in ‘Skeena’, and 523 in ‘Chelan’ in at least one treatment/timepoint in comparison with the control. It is to be noted that NOISeq uses a multinomial distribution to simulate replications. Therefore, the replicates are an approximation and show genes with changes over a set statistical threshold in the samples analyzed. The differentially expressed genes identified in this study thus represent potential activators of abscission zone formation .p-value cutoff of 0.05. This strategy resulted in the identification of enriched GOs at 6-h post-ethephon and at harvest for all genotypes. No GOs were significantly enriched at the 0-h time point.To understand what biological processes, molecular functions, and cellular components were enriched across the three cultivars and thereby determine the pathways of greatest interest to this study, GO enrichment analysis of differentially expressed contigs was conducted, followed by filtering for the most specific ontologies using an FDR-corrected 3.3.1.From samples collected 6 h after treatment, 84 unique GOs were identified for ‘Bing’, 8 for ‘Chelan’, and 33 for ‘Skeena’  and 3A. In ‘Chelan’, a relatively small number of GO terms were enriched at 6 h post-ethephon. Among the few enriched terms was “negative regulation of endopeptidase activity”. As with plant chitinases, endopeptidases contribute to programmed cell death and cell wall breakdown  and have‘Skeena’ displayed a number of enriched ontologies associated with epigenetic modifications, including “chromatin binding”, “double-stranded methylated DNA binding”, “regulation of DNA methylation”, “gene silencing by RNA-directed DNA methylation”, “histone acetylation”, and “histone binding”. Such processes have previously been implicated in the abscission of citrus  and litc3.3.2.At harvest, 22 unique enriched ontologies were identified in ‘Bing’, 56 in ‘Chelan’, and 2 in ‘Skeena’  and 3B. In ‘Chelan’, a comparatively high number of terms was observed at harvest. Among the enriched GOs were “cell wall-related processes” and “methylation” . These aIn ‘Skeena’, at harvest, only two GO terms were uniquely enriched: “phenylpropanoid biosynthetic process” and “stress response”. The limited number of unique terms at the later time point indicates that the majority of impactful processes contributing to PFAZ activation likely take place earlier in development. Among the enriched ontologies, phenylpropanoid metabolism is involved in the production of lignin precursors and has been previously implicated in fruit abscission . Additio3.3.3.In addition to unique GOs, shared ontologies reveal PFAZ activation-associated processes that are similar between two or more cultivars following ethephon treatment . At harvAt the 6-h time point, all three genotypes shared the enriched GO term, “DNA-binding transcription factor activity”. This GO term, among which a number of ethylene-responsive transcription factors were identified , remainepatatin-like protein 2 (PLP2), which plays a role in programmed cell death, and protein walls-are-Thin 1 (WAT1), which, in addition to its role in auxin mobilization, plays a role in secondary cell wall formation and stability [The term “integral component of membrane” was shared between ‘Chelan’ and ‘Skeena’ at 6 h post-ethephon and between all three cultivars at harvest. A large number of differentially expressed genes were associated with this term ; among ttability ,64. As aOverall, the GO enrichment results provide a global picture of the processes underlying the natural abscission capacity of ‘Skeena’, the inducibility of the abscission process in ‘Bing’ and recalcitrance to PFAZ activation in ‘Chelan’. The examination of the differentially expressed genes associated with the enriched ontologies, described in the next section, lends further insight into the mechanisms underlying these three unique sweet cherry abscission phenotypes.3.4.The results of the GO enrichment analysis provided a basis for distinguishing pathways in which to observe the expression patterns of significant genes and to compare these patterns across cultivars following ethephon or control treatments.3.4.1.endochitinase EP3-like, endochitinase-like, and endochitinase 2-like were induced at the 6-h time point (abscisic acid receptor PYR1-like (PYR1-like), ethylene receptor 2 (ETR2), auxin-responsive protein IAA1-like (IAA1-like), and JA responsive proteinsTIFY5A-like and TIFY 9. While genes associated with chitinase activity, hormone signaling, and ROS response displayed consistently elevated fold-change expression in ‘Bing’, in the other two cultivars, the responses varied. In general, a trend of low or negative fold change expression in ethephon-treated versus control PFAZ tissues was observed for this gene set in ‘Chelan’ and ‘Skeena’; notably, however, PYR1-like and IAA1-like fold change expression was elevated in both ‘Bing’ and ‘Chelan’. The high expression of ABA-associated PYR1-like, which promotes senescence and stress responses leading up to abscission, in the PFAZ of ethephon-treated ‘Bing’ and ‘Chelan’ cherries suggests that, despite ultimately different abscission phenotypes, both cultivars possess upstream mechanics that precede PFAZ activation. Furthermore, the low abscission capacity of ‘Chelan’ may lie in a comparatively high auxin versus ethylene response, along with negative regulatory mechanisms that have been previously undescribed. Specifically, several transcripts corresponding to alpha-humulene 10-hydroxylase-like, associated with the GO term “negative regulation of endopeptidase activity”, were consistently downregulated in all three cultivars following ethephon treatment, but most drastically so in ‘Chelan’. The specific role of alpha-humulene hydroxylase-like proteins, which modulate plant secondary metabolites (mainly sesquiterpenes) in response to herbivory, in abscission remains to be elucidated; however, the unique expression pattern in ‘Chelan’ points towards a potentially novel mechanism of negative regulation of abscission zone activation.In ‘Bing’, a number of differentially expressed contigs corresponding to endochitinases, including several transcript variants of me point . At the increased DNA methylation 1 and two transcript variants corresponding to histone acetyltransferase HAC1-like isoform X1 (HAC1-like)  . These g3.4.2.laccase 15-like, laccase 7-like, and laccase 9  , which is also associated with the “plant organ morphogenesis” ontology  . LOB18 hthe PFAZ ,66. LOB8ontology , was sigsalicylic acid binding protein 2-like, which is associated with JA and SA metabolism, was observed at the harvest time point in ‘Bing’, indicating that JA signaling mechanisms remain active throughout development in ‘Bing’ following ethephon treatment. Similarly, the expression of JA-induced, chitinase-associated genes was also observed at the harvest.In addition to the genes that are directly involved in the modification of the PFAZ ultrastructure, the elevated expression of several transcript variants of corresponding to beta-galactosidase 8, pectinesterase-like, and two expansin genes, displayed significantly heightened expression at harvest. These genes are involved in cell wall loosening, the degradation of linkages between structural components, and the digestion of cell walls and middle lamella in the AZ [caffeic acid 3-O-methyltransferase-like (CAOMT) at harvest; conversely, this transcript displayed increased abundance in both ‘Bing’ and ‘Skeena’ at 6 h and at harvest. CAOMT lies upstream of the lignin biosynthetic process; decreased expression of this gene has been shown to lead to reduced lignification in poplar, and expression changes in CAOMT-like genes parallels PFAZ formation in citrus [In ‘Chelan’, several genes associated with cell wall modification, including n the AZ ,68–70. Wn citrus ,71,72.The expression patterns of genes corresponding to cell wall modifiers and lignin biosynthesis precursors that were identified in ‘Chelan’ lend insight regarding why this non-abscising cultivar displays reduced PFRF but fails to form a PFAZ that is discrete enough to facilitate mechanical harvesting; furthermore, low expression of other terminal abscission-associated genes, like the laccases displaying heightened expression in ‘Bing’ lend further credibility to this hypothesis.peroxidase 10, peroxidase 17-like, and 16.9 kDa class I heat shock protein 1-like. The elevated expression of stress-responsive genes indicates an increased need for ROS scavenging to prevent oxidative damage while these signal molecules serve the purpose of activating abscission-associated processes. Based on the pronounced decrease of stress-responsive genes in ‘Skeena’ following ethephon application and the observation that PFRF of ‘Skeena’ is reduced the least out of all the cultivars following treatment, it is plausible that ‘Skeena’ may only perceive the exogenous ethylene as environmental stress, whereas ‘Bing’ and ‘Chelan’ appear to host concerted, ethylene-induced signal transduction responses upstream of abscission in response to ethephon application. In conjunction with increased peroxidase gene expression, reduced expression of pathogen defense-associated transcripts corresponding to major latex protein (MLP-like protein) 28 and 43 was observed. This is consistent with a study of MLP-like expression patterns in peach abscission zones, wherein it was suggested that MLP-like genes play a role in the mitigation in defense in early AZ formation but display reduced expression immediately prior to abscission and are further downregulated in response to ethylene [dessication protectant protein Lea14 and defensin Ec-AMP-D2-like, in both ‘Skeena’ and ‘Bing’.Most notable among the differentially expressed genes in ‘Skeena’ were stress-response-associated ethylene . Similar3.5.1-aminocyclopropane-1-carboxylate oxidase 1 (ACO1) was highly elevated in expression, as were transcripts corresponding to ethylene receptor 2 (ETR2) and ethylene insensitive 2 (EIN2), two key genes involved in ethylene perception and signaling, respectively. The activation of ethylene biosynthesis that is observed to occur uniquely in ‘Bing’ suggests that exogenous ethephon stimulates the autocatalytic production of endogenous ethylene, which thereby accentuates the overall degree and impact of the ethylene response in this cultivar. Moreover, the naturally high expression of ETR2 and EIN2, which are augmented in the presence of exogenous ethephon, lend further testament to the responsiveness of ‘Bing’ to ethylene. A negative regulator of ethylene, reversion-to-ethylene-sensitivity 1 (RTE1), was induced in ‘Bing’ following ethephon application, but levels remained lower overall than in ‘Chelan’ and ‘Skeena’, an observation which is consistent with the comparatively high degree of sensitivity of ‘Bing’ to ethylene. In contrast to ‘Bing’, ‘Skeena’ and ‘Chelan’ displayed the basal levels of expression of ACO1 and ETR2 and elevated levels of RTE1, suggesting minimal ethylene response, endogenous production, and sensitivity  and ethylene insensitive 2-like (EIL) family of proteins. Upon the activation of ETRs by ethylene, the C-terminal domain of EIN2 is cleaved and translocated to the nucleus where it activates the transcription of ethylene-responsive factors (ERFs) involved in the regulation of downstream ripening responses ,75. Numereatment . In addi3.6.In addition to the differential ethylene responses, the ethephon-treated ‘Chelan’, ‘Bing’, and ‘Skeena’ PFAZ regions displayed a differential reduction in the expression of auxin-responsive genes in comparison to their respective controls. This suggests that the response to auxin and/or reduction in auxin transport was inhibited in the presence of exogenously applied ethylene.IAA11, IAA13, and IAA27, auxin transport facilitator WAT1, and auxin efflux carrier component 1c displayed comparatively low expression in ‘Skeena’, intermediate expression in ‘Bing’, and higher expression in ‘Chelan’ control PFAZ tissues at 6 h post-ethephon and at harvest. Ethephon treatment attenuated this expression in the PFAZ region for all three cultivars, but the same relative expression trend was maintained. IAA13, IAA27, and WAT1 displayed decreased expression at harvest in all ethephon-treated cultivars in comparison with their respective controls. Interestingly, ‘Chelan’ displayed a natural increase in the expression of these transcripts from the 0-h time point to harvest, which was inhibited and reversed by the application of ethephon , ethephon begins to deleteriously affect some sweet cherry cultivars by inducing unwanted leaf abscission and terminal shoot necrosis, although it is not reported to what extent ‘Chelan’ is impacted by such a concentration [While free auxin was not measured in this study, differences in the abundance of auxin-responsive and auxin mobilization-associated transcripts in the three sweet cherry cultivars over time lends to the extrapolation of information regarding cultivar-specific, endogenous free IAA concentrations. If free auxin levels are high, abundance and/or activity of auxin-responsive protein encoding transcripts  is expected to be higher to accommodate them. ‘Skeena’ does not require ethylene for abscission; however, ethephon application appeared to further offset the auxin to ethylene ratios in favor of ethylene to accelerate abscission in this cultivar. The ability of ‘Skeena’ to auto-abscise suggests that the endogenous accumulation of free auxin at the site of abscission may be naturally lower in this cultivar than it is for ‘Bing’ and ‘Chelan’. Conversely, the comparatively higher expression of transcripts associated with auxin response and movement proteins in ‘Chelan’ is suggestive of a naturally higher level of endogenous IAA. While the current industrial standard levels of ethephon application were insufficient to reduce the PFRF of ‘Chelan’ fruit to the threshold required for mechanical harvesting, both PFRF and auxin-associated transcript abundance in ‘Chelan’ did decrease as a result of ethephon application. Ethephon application rates as high as 5.8 L ha harvest . An earlntration ,11. Cons‘Bing’ PFAZ tissues displayed an abundance of auxin-associated transcripts intermediate to that of ‘Skeena’ and ‘Chelan’. Following ethephon treatment, the phenotypic observations of inducible abscission were supported at the gene expression level, with the responses greatly attenuated to lower than those of ‘Skeena’ ethephon-treated and control PFAZ tissues.3.7.Together, the GO enrichment and differential expression analysis results inform new, hypothetical models for abscission . In ‘Bin3.8.Variant calling using the GATK pipeline revealed several SNPs and indels in the ORFs of DE genes associated with key enriched GOs .AP2/ERF and B3 domain containing protein RAV1, wherein the deletion of a 6 bp segment results in the loss of two amino acid residues without impacting the reading frame. Interestingly, ‘Skeena’ was homozygous for this deletion; ‘Bing’ was heterozygous, and ‘Chelan’ did not possess the deletion. The resulting protein changes likely impact the natural propensity of the cultivars to transduce signals associated with stress and hormone responses upstream of PFAZ activation and could ultimately underlie differences in abscission phenotype. Additionally, an SNP, resulting in an amino acid substitution in the coding sequence of auxin efflux carrier component 1c, was identified in ‘Chelan’. This variant could impact the overall auxin responsiveness, which appears to be greater in ‘Chelan’ than ‘Bing’ or ‘Skeena’, at the genetic level.An INDEL was identified in “DNA-binding transcription factor activity”-associated 17.4 kDA class III heat shock protein, an INDEL in the epigenetic modification-associated gene polycomb group EMBRYONIC FLOWER 2 isoform x1, and an SNP in the 3′ UTR of the “chitinase activity”-associated endochitinase-like gene. A member of the diverse polycomb group (PcG) family, EMF2 is involved in the epigenetic silencing of developmental repressors and was significantly downregulated in ‘Skeena’ at the 6-h time point. While further work is needed to determine the precise nature of these variants and their impact on PFAZ activation, their presence in DE genes associated with enriched functions following ethephon application makes them key targets for understanding the activation of abscission in sweet cherry cultivars.Additional variants identified include a SNP in “ROS response”-associated 3.9.−(ΔΔCt) method) was consistent with that of the RNAseq-based expression (ethephon/control RPKM ratio) included genes associated with ethylene biosynthesis (ACS1 and ACO1), perception (ETR2), and response , as well as cell wall breakdown-associated polygalacturonase (PG)  .4.This study investigated the changes in PFRF, gene expression changes, and enriched biological processes underlying PFAZ activation in sweet cherry. The results provide transcriptomic insight regarding the gene-expression-level effects of exogenous ethylene application on the abscission phenotype and PFAZ development, which can be utilized by the industry to customize harvest strategies.Consistent with previous work, PFAZ activation was observed to occur in a cultivar-specific manner, and the abscission phenotype of each cultivar was affected to a different degree by the exogenous application of ethylene. The observation of unique, heightened expression of ethylene biosynthesis, perception, signaling, and response genes in ‘Bing’ at 6 h following ethephon application and at harvest parallels the decrease in PFRF and may be partially responsible for the inducibility of abscission in this cultivar. GO enrichment analysis revealed key biochemical pathways containing additional differentially expressed genes potentially underlying the unique abscission responses of each cultivar. Among these enriched pathways were a number of hormone-signaling pathways, ROS signaling, chitin metabolic processes, lignin biosynthesis, and DNA-binding transcription factor activity (among which were numerous ERFs).Overall, the results of this study point towards a potential genetic basis for the inducible abscission response in ‘Bing’, the auto-abscission of ‘Skeena’, and the recalcitrance to abscise displayed by ‘Chelan’. The natural abscission of ‘Skeena’, which is enhanced by ethephon, may result from naturally lower levels of free auxin, as evidenced by the low abundance of IAA/ARF-associated transcripts in comparison with ‘Bing’ and ‘Chelan’. Furthermore, ‘Skeena’ exhibited fewer significant gene expression changes than the other cultivars following ethephon application, which corresponded to fewer enriched ontologies at the time of harvest. In ‘Chelan’, the comparatively high abundance of auxin-associated transcripts in control fruit, which was attenuated following ethephon treatment, may indicate higher levels of endogenous free auxin. The increased capacity for auxin mobilization, indicated by IAA/ARF expression, antagonizes the abscission-promoting effects of exogenous ethylene. This observation, along with the PFRF results, provides insight regarding the recalcitrance of ‘Chelan’ fruit to abscise at the pedicel–fruit junction.The identification of cultivar-specific, differentially expressed genes and enriched GO terms involved in abscission, as well as ontologies that are shared across cultivars, provides information that will inform future efforts to promote the controlled, timely abscission of sweet cherries. This, in turn, will lead to the improvement and standardization of mechanical harvesting, thereby improving efficiency and increasing the economic profitability of the sweet cherry industry. Ultimately, the outcomes of this work may be extended to other crops where planned abscission can be useful in managing the harvest.Supplemental Material