Deficits in the visual attention span (VAS) are thought to hamper reading performance in dyslexic individuals. However, the causal relationship between VAS deficits and reading disability remains unclear. The present study attempts to address this issue by using a VAS-based intervention to explore the possible influence of VAS on reading processes in Chinese children with dyslexia. Given the influence of the heterogeneity of dyslexia on intervention effects, VAS-impaired dyslexic and VAS-intact dyslexic individuals were separately trained. Therefore, there were five groups of participants in this study, including 10 trained dyslexic individuals with VAS deficits and 10 untrained dyslexic individuals with VAS dysfunction as the baseline reference, 10 trained and 10 untrained dyslexic individuals with an intact VAS, and fourteen age-matched normal readers for reference of normal level. All participants completed reading measures and a visual 1-back task, reflecting VAS capacity with non-verbal stimuli and non-verbal responses, before and after VAS-based training. VAS-based training tasks included a length estimation task regarding the bottom-up attention, visual search and digit cancelling tasks targeting top-down attentional modulation, and visual tracking tasks to train eye-movement control. The results showed that visual training only helped improve VAS skills in VAS-impaired dyslexic individuals receiving training. Meanwhile, their silent sentence reading accuracy improved after training, and there was a significant relationship between training improvements in VAS function and reading performance. The current findings suggest that VAS-based training has a far-transfer effect on linguistic level . These findings suggest the possibility that VAS-related training may help children with dyslexia improve their reading skills. DD has been found to be caused by a multifaceted disorder2 including linguistic-level problems  and dysfunction in basic cognitive processing such as visual perceptual analysis6 and visual spatial attention14. In particular, a specific deficit has been consistently observed in tasks that have a common aspect, that is, the paralleled processing of multiple visual elements 19. Multiple-element processing ability could be reflected by the visual attention span (VAS). Since reading partially begins with visual decoding that needs to process multi-letter/character strings, the VAS capacity of dyslexic readers has attracted increasing attention in recent years. Bosse et al.15 proposed the VAS deficit theory of dyslexia and indicated that VAS impairment might independently account for reading difficulties in dyslexic individuals to some extent. A number of studies using group comparisons between dyslexic readers and chronological-age-matched normal readers reported VAS impairments in dyslexic individuals23. However, it is not clear whether a VAS deficit is one of the critical causes of dyslexia or if it results from reading disabilities25. The present study attempts to address this question by utilizing a training method focused on VAS-related skills to explore the possible causality between VAS dysfunction and poor reading outcomes.Developmental dyslexia (DD) is one of the learning difficulties, especially in reading failure in accuracy, fluency and understanding that cannot be explained by problems in educational opportunity, general intelligence, general motivation, or sensory sensitivity15. In whole-report paradigms, participants are asked to orally report as many letters as possible regardless of the order after a five-letter string was briefly presented, and the number of correctly-reported string and the number of correctly-reported letters across all the trials were regarded as the test scores. In partial-report paradigms, the task requires the participants to orally report a particular letter within a string which appeared at a cued position, and the test scores were the number of correctly-reported letters15. The higher the score is, the better the visual attention span ability is. Later, position-based analyses on performance in VAS tasks were conducted to demonstrate the distribution pattern of visual attention span, and relevant findings revealed that visual attentional distribution might be modulated by age-related changes and reading experience28. For beginning readers or children with reading difficulty, the inter-position variability is remarkably able to show differences in identification sensitivity across positions28; the inter-position difference tends to decrease with increasing age and with the enhancement of reading ability, revealing an enlargement in the window size of the VAS27.Whole-/partial-report tasks with 5-letter strings as stimuli were typically utilized to measure VAS ability and to explore the VAS-reading relationship15 demonstrates a relationship between VAS disorders and poor reading outcomes, based on the connectionist multi-trace memory model of polysyllabic word reading29. The model indicated that there were two reading procedures  differing in the window size of visual attention from which the orthographic information of text input was taken. In global reading, the visual attention window contains the entire string, and then, the global phonological output is formed; in analytical reading, the window size of visual attention shrinks to serially process a portion of the visual word, and the phonological outputs thus correspond to the relevant parts within the string. Consequently, it could be proposed that the global reading mode requires a larger VAS than the analytical reading mode and that VAS dysfunction mainly restricts the number of parallel-processed letters during reading, which will further affect the global representation of orthographic and phonological information of the sequence15.Given that reading involves attentional allocation across letters, the number of stimuli that can be simultaneously processed  would exert an influence on reading efficiency. The VAS deficit hypothesiset al.30 first explored VAS capacity in two French children with dyslexia via whole- and partial-report tasks in which the target stimuli were five-letter strings with no meaning. Their findings revealed that one of the two dyslexic children exhibited poorer performance than chronological-age-matched controls did in both whole- and partial-report tasks, suggesting a possible VAS deficit in the dyslexic children. The following studies replicated this VAS impairment with a larger sample of dyslexic participants31. Relevant research found lower scores in whole-/partial-report tasks with 5-letter strings as stimuli among French, English and Portuguese children with dyslexia compared to their chronological age-matched controls31. Furthermore, position-based analysis indicated that the dyslexic individuals exhibited an abnormal pattern of visual attentional distribution in the VAS task27. However, most VAS-related tasks use letters as target stimuli, which has been suggested to involve language-related skills such as visual-to-verbal transfer; thus, the poor performance in dyslexic individuals in these visual tasks may reveal impaired symbol-sound mapping rather than a VAS deficit33. Lobier et al.17 designed a visual categorization task on the basis of a partial-report task with symbols as non-verbal stimuli and with non-verbal responses to purely examine the VAS-related processing. Their research excluded the possible influence of language processing and reported that French dyslexic adults responded less accurately than age-matched controls, revealing a pure VAS impairment34. A VAS intervention study on a French girl with dyslexia reported that VAS-based training could normalize her visual attentional distribution pattern in the VAS task, promote efficiency in word identification and improve text reading performance27. The training consisted of VAS tasks differing in difficulty levels, as well as tasks of visual search, discrimination, visual matching and visual parsing, which were all suggested to require simultaneous multi-element processing. Similarly, an intervention study35 on Italian dyslexic children found that training multi-letter processing  could improve participants’ accuracy and speed during word reading, revealing the benefit of VAS training on reading performance. Currently, Zoubrinetzky et al.36 designed the MAEVA programme targeting the VAS to train a group of French children with dyslexia and found training effects in both of VAS skills and word reading performance. These findings suggest a possible causal link between VAS deficit and reading disabilities.In the context of alphabetic languages, Valdois 39. The conflicting findings might be attributed, to some extent, to the heterogeneity of dyslexia. It has been reported that approximately 20–30% of children with dyslexia exhibit VAS impairment in the context of alphabetic languages19, especially individuals with surface dyslexia40. Thus, if pseudoword reading and other reading-related measurements substantially relying on phoneme identification and operation were used as the main screening criteria for dyslexia, it is probable that dyslexic individuals with phonological awareness deficits were selected. It has been reported that the prevalence of dyslexic individuals with a pure VAS deficit is approximately 34%, and 17% of dyslexic individuals showed a double disorder characterized by comorbid phonological deficits and VAS deficits18. As suggested by the connectionist multi-trace memory model29, some researchers indicated that VAS deficits in dyslexic individuals are independent of their phonological problems, in which the former corresponds to the global reading mode and the latter corresponds to the analytical reading mode. Accordingly, it could be proposed that if an individual with dyslexia exhibits an impairment in phonological processing , then this impairment would cause an obvious problem in letter-by-letter spelling through the sublexical route . Then, the occurrence probability of VAS dysfunction in this individual would be lower than that in dyslexic individuals without phonological deficits; that is, the existence of phonological problems may further decrease the possibility of the presence of VAS deficits in dyslexia. Therefore, future studies should take into account the subtypes of dyslexia.However, other studies did not report a significant relationship between VAS deficits and reading difficulty. With whole-/partial-report tasks and visual 1-back tasks to measure VAS capacity, it has been reported that 9-year-old German children and Hebrew adults with dyslexia did not differ from non-impaired readers in their VAS-related measurements, and further position-based analyses showed that the patterns of the visual attention window were similar between dyslexic and normal readers41. The orthographic depth of the native language may affect the pattern of the reading mode for beginning and developing readers. In languages with shallow orthographies, readers in early developmental stages maps small orthographic units onto relevant phonemes via the rules of grapheme-to-phoneme correspondence (GPC). By contrast, larger orthographic units are more phonologically regular than smaller ones in languages with deep orthographies42. It could be proposed that the VAS may exert a more notable influence on the coarse-grain strategy through the globally lexical route than on the small-grain strategy through the sub-lexical route and that reading in languages with deep orthographies may require a wider allocation of VAS resources than reading in languages with shallow orthographies43. Findings from cross-language research provided some evidences for the abovementioned inference. Lallier et al.26 found that French-Basque bilingual children performed better in VAS-related tasks than Spanish-Basque bilingual children, in which French belongs to a language with deep orthography while both of Basque and Spanish are languages with shallow orthographies. Moreover, a study of cross-language comparison reported that only the VAS skills of French adults were related to their scores on an oral reading fluency test, and there were no significant correlations between VAS and fluent reading in either Arabic or Spanish adults41, where French has deeper orthographic depth than Spanish and Arabic. Additionally, an intervention study on a French-Spanish bilingual girl indicated that VAS-based training could contribute more greatly to French reading than Spanish reading32. The above findings support that the VAS may primarily affect fluent reading in languages with deep orthographies. Consequently, a VAS deficit supposedly causes problems at the level of the global reading mode30, and the VAS impairment in dyslexic readers might be more discernible in languages with deep orthographies.Moreover, the orthographic transparency of the native language may potentially modulate the VAS-reading relationship44. It has been shown that VAS significantly contributes to Chinese sentence reading in skilled readers, revealing a close relationship between the VAS and Chinese reading45. Thus far, relevant reports about the relationship between the VAS and Chinese reading disability have been scarce and inconsistent. Mi46 used whole-/partial-report tasks with high-frequency Chinese characters as stimuli to measure the VAS skills. The results showed that the performance of Chinese dyslexic children in these VAS tasks did not differ from that of the age-matched normal readers. Given that the task, with a meaningless character sequence, might be similar to the character-list reading task, participants involuntarily utilized a character-by-character reading procedure in the analytical reading mode rather than regarding the character sequence as an entire representation. In a recent study22, researchers adopted a partial-report task with symbols as stimuli and non-verbal response to measure VAS capacity and observed a developmental increase in VAS deficit in Chinese dyslexic children from different primary school grades. The authors explored VAS skills among Chinese dyslexic children from low, middle, and high grades of primary schools, and the results showed that only the dyslexic children in high grades exhibited lower accuracy in the VAS task as compared to the normal readers22. Since both the abovementioned studies utilized an age-matched design, which cannot establish a causal link between VAS deficits and dyslexia, Chen et al.20 adopted a reading level-matched design to further explore whether VAS impairment in dyslexic readers was the result of their reduced reading experience. Their findings showed that dyslexic children performed worse than both the age-matched and reading level-matched controls in the VAS task, revealing that VAS deficits in Chinese dyslexic children cannot be explained only by poor reading abilities20. However, the visual stimuli in this study included Chinese characters, radicals, and digits that belonged to verbal materials. Processing these verbal stimuli would involve visual-to-phonological mapping, and individuals with dyslexia showed impairments in this ability. Accordingly, the poor performance in the abovementioned VAS task probably reflected problems in visual-to-verbal transfer rather than dysfunction in visual attentional processing. Moreover, this study only excluded the possibility that VAS dysfunction was the result of a poor reading outcome, but it remains unknown whether the VAS impairment was one of the causes of dyslexia. Therefore, future studies are required to examine whether a pure VAS deficit could  account for reading difficulties in Chinese individuals with dyslexia.In contrast to alphabetic languages, Chinese has a particularly deep orthography without strict GPC rules. As a logographic writing system, Chinese characters have complex visual features. The global processing of characters’ visual forms is critical for Chinese reading because it is conducive to establishing the connection between Chinese orthography and semantics and phonology through a whole-lexical routethe first aim of the present study was to investigate whether there is a causal link between the VAS and reading-related skills in dyslexic children reading Chinese  using a VAS-based intervention method to disentangle cause from effect in dyslexia. VAS skills were measured by a parallel visual processing task with non-verbal stimuli and non-verbal report  to reflect pure VAS capacity. Moreover, we divided the trained dyslexic individuals into two groups, VAS-impaired and VAS-intact individuals, and the second aim of the present study was to compare the intervention effect between these two groups and examine the possible influence of the heterogeneity of DD on the intervention effect. The two groups of dyslexic individuals received 10 training sessions focusing on VAS-related subcomponents regarding bottom-up stimulus-driven attention abilities and top-down controlled attention. The VAS and reading-related skills were tested before and after VAS-based training. In addition to the two trained groups, there were three control groups: nontrained dyslexic individuals with VAS deficits, nontrained dyslexic individuals with normal VAS function and age-matched normal readers with normal VAS function that were separately regarded as references for baseline and normal reading levels. By comparing differences in the training effects across groups, we expected to further uncover the possible influence of VAS dysfunction on Chinese reading disability and to examine the applicability of the visual attention span deficit hypothesis in Chinese, with its nonalphabetic writing system and particularly deep orthography. According to the relevant literature22, it was predicted that training focusing on VAS-related skills would contribute to improving VAS capacity and reading skills, particularly among dyslexic children with a VAS deficit.A number of studies have explored the VAS capacity in dyslexic readers by comparing them with chronological age-matched controls; however, there were conflicting findings and has been debated surrounding the causal relationship between VAS disorders and reading disabilities, which might be associated with differences in the orthographic depth of the native language and with stimuli properties and task design. Based on relevant studies with alphabetic languages, it could be inferred that the VAS might have a significant relationship with the global reading mode in the context of languages with deep orthographies, in which group differences in VAS capacities between dyslexic and normal readers would be remarkable. However, the use of letter stimuli and oral reports in most previous studies has been taken as evidence against the VAS accounting for poor performance in dyslexic individuals. Therefore, ps < 0.05) in some conditions  single-character reading speed of the untrained VAS-impaired individuals with DD), revealing that variables in some conditions exhibited skewed distributions. Moreover, our sample size was small. Accordingly, we used the non-parametric Wilcoxon signed-rank test to address the ability changes before and after the intervention within one group and the non-parametric Mann-Whitney U test to compare the performances between groups. To explore the relationship between improvements in the VAS and reading skills, Spearman correlation analyses were further adopted. For the performance in the visual 1-back task, we used accuracy instead of reaction time as the final dependent variable, which was consistent with previous literature22, because the response time in the visual 1-back task might include processes other than VAS skills, such as decision-making, selection of different keys, and motor action related to pressing the corresponding keys. Moreover, d-prime values were computed based on accuracy in each position of a string to further analyse VAS improvement from the position-based aspect. In line with previous studies47, the speed of single-character reading, judgement accuracy and reading speed in the sentence task were separately regarded as the dependent variables of fluent reading performance at the single-character and sentence levels.The present study first aimed to explore the possible causal link between VAS deficits and reading disability. To do this, we focused on examining whether there were significant improvements in both VAS capacity and reading skills after VAS-impaired dyslexic individuals received VAS-related training; in addition, we also investigated the correlation between the possible training effects on VAS ability and reading performance. Moreover, we included other control groups to better understand the training improvements in trained VAS-impaired individuals with DD. In detail, untrained VAS-impaired dyslexic individuals were recruited as a baseline reference group to exclude the possible influence of changes related to natural growth, and age-matched normal readers were recruited as a normal control reference group to examine whether VAS ability in the trained VAS-impaired individuals with DD approached or reached normal levels after the intervention. First, we conducted one-sample Kolmogorov-Smirnov tests to examine whether the d-prime values in the visual 1-back task, reading performance in each group and each time point showed normal distributions. The results showed significant effects , we recruited the trained and untrained groups of VAS-normal individuals with DD and ran similar tests to those previously mentioned to analyse their performance regarding VAS and reading tests.p = 0.03) but not in untrained VAS-impaired dyslexic individuals , as shown in Fig. p = 0.04; Fig. p = 0.83) in the pre-test condition; in contrast, the VAS skills of trained dyslexic individuals did not differ from those of the normal readers , showing better performance than untrained dyslexic individuals . However, compared to chronological age-matched controls, trained dyslexic individuals with VAS deficits still exhibited lower d’ values in the 2nd , 4th  and 5th  positions in the post-test. Referring to previous literature48, we further computed individual standard deviations across the five positions in the post-test condition to reflect the inter-position variability across the string and compared the scores between trained VAS-impaired individuals with DD and normal readers to explore their patterns of visual attentional distribution. The results of the Mann-Whitney test showed no significant group difference .The results of a Wilcoxon signed-rank test showed that there was a significant improvement in the mean accuracy between pre- and post-tests in trained VAS-impaired individuals with DD  and silent  modes, as well as on judgement accuracy in the oral  and silent  sentence reading tests . These originally lower reading scores of the trained VAS-impaired dyslexic individuals significantly improved after VAS-related training , their scores in most of the reading tests were similar as those of age-matched normal readers , revealing that they were close to the normal level. In contrast to the baseline control group of untrained VAS-impaired dyslexic individuals . These untrained dyslexic individuals showed lower accuracy  and slower responses  in silent sentence reading than trained VAS-impaired dyslexic individuals in the post-test.For reading measurements, in the pre-test condition, trained VAS-impaired dyslexic individuals performed worse than the age-matched normal readers on single character reading speed in both oral  as well as d-prime values of the 3rd position  in the visual 1-back task. Moreover, there was no other significant correlation (ps > 0.1). A follow-up test was conducted three months after training. The performance improvements in silent sentence reading accuracy and VAS capacity in the trained group of VAS-impaired dyslexic individuals were still apparent, as revealed by non-significant differences in Wilcoxon signed-rank tests between the post-test and the follow-up test (ps > 0.1). Especially for the follow-up tests, these trained dyslexics exhibited better performance in the silent sentence reading performance  and VAS skill  as compared to the untrained dyslexics with impaired VAS. These untrained dyslexics did not show significant improvements in either silent sentence reading or VAS capacity, while they only showed an increased speed in silent character reading after training. Accordingly, we also examined the stability of the improvements in silent character reading in untrained dyslexic individuals, and the results showed that the reading performance in the follow-up test was worse than that in the post-test  but was better than that in the pre-test , and this result was probably due to a practice effect.Given that only VAS-impaired dyslexic individuals exhibited training effects on VAS and reading skills, the relationship between the training effects of VAS and reading skills was explored. Based on the abovementioned significant improvements, we computed the differences in the mean accuracy on the visual 1-back task and the d-prime values in the 1p = 0.26). The VAS capacity of these trained dyslexic individuals was similar to that of age-matched normal readers in the pre-  and post-  conditions .We further analysed the data of trained VAS-normal dyslexic individuals to explore the possible influence of the heterogeneity of DD on the intervention effect. The results of Wilcoxon signed-rank tests Fig.  showed nons Fig. . Additiop = 0.02), which was also observed in untrained VAS-normal dyslexic individuals . Compared to the normal level reference group, trained VAS-normal dyslexic individuals performed worse in oral character reading and oral/silent sentence reading in the pre-test condition ; in addition, these group differences were maintained in the post-test .These trained VAS-normal dyslexic individuals showed an improvement in their character reading speed in the oral mode , and there were no other significant group differences (ps > 0.1).Additionally, to directly compare the group differences in the training effects, chi-square tests were conducted to compare the number of participants who exhibited improvements in the VAS or reading performance after training  across groups. Fisher’s exact test was adopted to analyse the data. Relevant results showed a significant group difference in the percentage of the improved individuals for both VAS skills ”, such as “一年有十三个月”, meaning “There are thirteen months in a year” . Previous studies usually used a paper-by-pencil test to measure sentence reading fluency73, in which participants needed to silently read and judge the correctness of each of the sentences in a list within a time limit . The final scores of the test included the number of correctly-judged sentences or the total number of characters in the corrected marked sentences. However, this task included not only fluent reading but also judgement making. Consistent with previous studies51, the current study thus applied a computerized test of reading fluency, in which the reading fluency procedure and correctness judgements were separate from each other. Accordingly, the relevant indexes of this reading fluency test included speed for the fluent reading procedure and judgement accuracy, similar to previous studies. Referring to relevant literature51, the details of each trial in the sentence reading test were as follows: a 500-ms centrally-presented fixation cross was first presented, which was followed by the complete appearance of a sentence that was one line long. Participants needed to read the sentence aloud or silently as accurately and quickly as possible and to press the space bar once they had finished reading this sentence. The reading duration was recorded as the interval between the onset of the sentence the time of pressing the space bar. We could then compute the sentence reading speed as the ratio between the number of characters in one sentence and the corresponding reading duration, and the unit of the reading speed was also converted to the number of characters read in one minute (c/min). After pressing the space bar, participants were asked to judge the correctness of the sentence by pressing the “f” key for true sentences and the “j” key for false sentences. The accuracy of the correctness judgement was also recorded. This test was programmed by Eprime 1.1 in a Dell laptop, and the reading speed and judgement accuracy were further analysed.A sentence verification task was utilized to measure sentence reading performance74, including bottom-up stimulus-driven attention abilities  and top-down controlled attention . Accordingly, we utilized training tasks involving the two abovementioned types of attentional capacities. Namely, a length estimation task was applied to train the visual short-term memory storage to address bottom-up attention, and visual search and digit cancelling tasks were used to target the top-down attentional modulation and control. In addition, given that eye movements during VAS tasks might exert an influence on the final performance37, the present intervention also included visual tracking tasks to train eye-movement control. Detailed information on each training task is included below.It has been suggested that a reduced visual attention span might potentially arise from different types of underlying mechanismsA length estimation task using the constant stimuli method was designed to train the largest amount of distinct visual elements that could be parallelly processed in a multielement array. The stimuli were the same 15 figures used in the visual 1-back task in the pre- and post-tests. A list of 130 figure strings was created using the 15 figures . No string included the same figure twice. The horizontal length of the string ranged from 4 to 15 figures, with 10 trials for each length condition. The visual angle of each figure was 0.8° × 0.8°, and the centre-to-centre distance between each adjacent figure was 1.7° at a viewing distance of 50 cm. This test was programmed using E-Prime 1.1 on a Dell laptop and presented in black on a white screen. The display resolution was set at 1024 × 768 with a monitor refresh rate of 75 Hz. Each trial followed the presentation format as below Fig. : a 500-mDigit cancelling and visual search tasks were used to target top-down attention related to visual attention span.Thedigit cancelling task was a paper-and-pencil test67 in which participants were required to search for a certain digit (a random integer between 0 and 9) rapidly in a 100-digit matrix (10 across by 10 down) within a time limit of 20 s , and identifying the target oval with 3/4 height of the circle’s diameter from the background circles required substantial involvement of visual attention due to the high similarity between this type of target oval and background circles. Therefore, in addition to examining the mean performance in the visual search, we also explored the learning effect in the 3/4 height condition within the two trained groups.als Fig. . The visial Fig. , a 250-mPaper-and-pencil puzzle tasks (including a line puzzle and maze puzzle) were used. In the line puzzle task Fig. , partici51, oral and silent reading tasks for each level were separated by the VAS test  during the experiment to reduce possible practice effects due to using the same materials for the two reading modes. Therefore, there were three sessions in the pre- and post-tests: the 1st session contained the character reading fluency and sentence reading fluency task in oral or silent modes; the 2nd session was about the VAS task; the 3rd session included the character reading fluency and sentence reading fluency task in the reversed reading mode to that in the 1st session. For example, if character reading fluency in the silent mode and sentence reading fluency in the oral mode were tested in the 1st session, then oral character reading and silent sentence reading were examined in the 3rd session. There was about a 1-min rest between successive sessions. The testing time for one participant was approximately 45–50 minutes in total.There are four stages in the present study, including a pre-test, a VAS training period, a post-test, and a follow-up test. The pre-test and post-test were conducted within two weeks before and after training, and the follow-up test was conducted three months after the VAS intervention to explore whether the training effect was long-lasting. The training lasted for 4 weeks and included 10 training sessions (two or three sessions per week), and each session took approximately 30 minutes. During the training period, two training groups of dyslexic children with impaired VAS and normal VAS function received the 10 training sessions, while the two groups of non-trained dyslexic individuals and age-matched normal readers performed free activities. In the pre-, post- and follow-up tests, reading skills and the visual 1-back task were submitted to all groups with similar testing procedures. Participants were tested individually in a quiet room. At the beginning of the experiment, the experimenter explained the procedure in detail from a standard script. According to previous researchSupplementary materials for training procedure and relevant results


Lactobacillus and Bifidobacterium plus 10 digestive enzymes, in protecting the human gastrointestinal tract from chemotherapy and an antibiotic. We used the Simulator of Human Intestinal Microbial Ecosystem (SHIME) model, an in vitro model of a stable colon microbiota, and introduced 5-fluorouracil (5-FU) and vancomycin as microbiome-disrupting drugs. The probiotic with digestive enzymes supplement, added in capsules at in vivo doses, improved fermentation activity in the colon reactors and accelerated the recovery of microbial populations following 5-FU/vancomycin treatment. The supplement restored the Bacteroidetes to Firmicutes ratios in the colon reactors, increased the diversity of microbiota, and induced the production of microbial metabolites that elicited anti-inflammatory cytokines in an in vitro model of intestinal inflammation. In the proximal colon, preventative administration of the supplement resulted in full recovery of the gut microbial community after cessation of 5-FU and vancomycin treatment. These results identify a probiotic with digestive enzymes formulation that protects against drug-induced gut dysbiosis, highlighting its potential utility as a component of routine cancer care.There are numerous downstream consequences of marketed drugs like antineoplastic agents on the gut microbiome, an effect that is suggested to contribute to adverse event profiles and may also influence drug responses. In cancer, progress is needed toward modulation of the host microbiome to prevent off-target side effects of drugs such as gastrointestinal mucositis that result from gut dysbiosis. The objective of this study was evaluation of the bioactivity of a supplement consisting of capsules with a blend of 9 probiotic organisms of the genera  The human gut microbiome is dominated by four main phyla: Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria [Bacteroidetes phylum while butyrate is mainly produced by Firmicutes. However, despite the proportional increases in Firmicutes in colon cancer, butyrate concentrations, which functions in many contexts including mitigating inflammation, are decreased during colon carcinogenesis; therefore, it is possible that specific beneficial species within this phylum may be less predominant. Indeed, studies have shown that strains of Lactobacillus (Phylum: Firmicutes) and Bifidobacterium (Phylum: Actinobacteria) are diminished in colorectal cancer [The microbiome in the human gut is composed of 500–1000 distinct bacterial species and up to 10bacteria . Specifibacteria . It is abacteria , irritabbacteria , and colbacteria . In thesbacteria . Of partbacteria . The mecl cancer . On thisBifidobacteria, a common probiotic strain, were found to be abundant in the colons of experimental animals that exhibited effective immunity against melanoma [Lactobacillus, and a coordinate reduction in known pathogenic strains [Clostridium difficile, the most prevalent cause of healthcare-associated infectious diarrhea in developed countries. In cancer patients, bacterial infections occur through diagnostic and therapeutic procedures, for example, due to placement of central venous catheters, and may have particularly serious consequences owing to the underlying immunosuppression. During vancomycin therapy, most intestinal microbiota genera are depleted [Intestinal microorganisms may determine the outcome of cancer treatments as well as being themselves affected by the treatments. Immunotherapeutic drugs, such as checkpoint inhibitor antibodies designed to unmask the cancer patient's immune system, rely on a degree of endogenous immunity for their effectiveness, which is shown in several recent papers to be heavily influenced by the intestinal microbiome. For example, gut dysbiosis, evaluated based on stool samples, predicted resistance to immunotherapeutic interventions in melanoma patients . Low divmelanoma . These lmelanoma . 5-FU dimelanoma . In factmelanoma . In anot strains . Other ddepleted . The ratOn the basis of this evidence, it has been widely suggested that modulation of the gut microbiome may be a useful therapeutic approach for improving the toxic side effects of cancer treatments, thereby possibly altering the trajectory of cancer. While a range or individual probiotic microorganisms or other supplements have been widely touted as having the capacity to modulate the gut microbiome, the challenge in the field has been the lack of validation of specific products. This is of particular significance for indications where patients are immunocompromised and undergoing treatment with cytotoxic agents since it has even been suggested that probiotics could induce bacteremia in certain populations –25. TherLactobacillus and Bifidobacterium, as well as 10 digestive enzymes, for its efficacy at protecting the gastrointestinal (GI) tract from the combined effects of 5-Fluorouracil (5-FU) and vancomycin. The probiotic with digestive enzymes supplement was evaluated using the Simulator of Human Intestinal Microbial Ecosystem (SHIME), a stable and reproducible in vitro system, to analyze its influence chemotherapy plus antibiotic-induced changes in microbial community activity and composition. The present experiments provided a very stringent test for the effects of this dietary supplement since the dysbiosis created in this system represented a “two-hit” system implementing two known microbiome-disrupting agents. We report that the probiotic with digestive enzymes supplement beneficially modulated the gut microbiome under healthy conditions, and, most significantly, improved recovery from 5-FU/vancomycin treatment when administered to the SHIME system. Improvements in microbial fermentation and attenuation of microbial community dysbiosis elicited by 5-FU/vancomycin were observed when the probiotic with digestive enzymes supplement was given in a curative context (i.e. beginning at the time of 5-FU/vancomycin treatment) but particularly when given in a preventative context (i.e. starting prior to 5-FU/vancomycin).To address the need for a probiotic formulation that protects against gut dysbiosis, this study evaluated a proprietary blend of 9 probiotic organisms of the genera in vitro model system was designed to create a stabilized microbiota community to allow for collection of samples from the different intestinal regions for analysis. Several microbial parameters were monitored throughout the SHIME experiment to assess the performance of the model and the basic changes in the microbial community composition and activity due to the probiotic with digestive enzymes supplement. After the first week during the stabilization period, reproducibility between each of the three SHIME units was determined in order to confirm initiation of preventive treatment in arm 3 of the SHIME. Reproducibility was confirmed by analysis of SCFA levels, which were 85.8% similar between the SHIME units. During the control period, stability and reproducibility of the other two SHIME units was determined. SCFA levels were stable within (on average 86.8% similar between consecutive time points in control period) and reproducible between the two SHIME units (on average 86.8% similar), clearly indicating stability and reproducibility of the microbial community in terms of activity and composition. On this basis, it was concluded that the effects that would be observed during the subsequent treatment period could be attributable to the probiotic with digestive enzymes supplement rather than due to variability in the system itself.The SHIME The consumption of acid and base reflects the overall microbial activity in the SHIME reactors representing the proximal and distal colon. Generally speaking, there are distinct bacterial populations that are native to the proximal and distal colon regions, reflecting the different requirements for digestion in each segment. Figure in vivo, more bacterial fermentation activity also occurs in the proximal colon where substrate availability is higher [As per Figure s higher . In the The abundant SCFA, acetate, propionate and butyrate, are generated by fermentation of dietary fibers by gut microbiota. SCFA have a plethora of health-promoting effects through their interactions with metabolite-sensing G protein-coupled receptors on the gut epithelium and on immune cells . In thesBacteroides and Bifidobacteria, and exerts anti-inflammatory effects [Figure  effects . ChemothIn Figure Clostridium clusters IV and XIVa (phylum Firmicutes). In vivo, butyrate is largely metabolized by intestinal epithelial cells where it serves as an energy source as well as a homeostatic factor for normal colonic cell turnover and repair processes [Figure rocesses . In the To further evaluate the impact of the probiotic with digestive enzymes supplement, the next series of experiments utilized qPCR to identify changes the microbial composition in the SHIME reactors representing the proximal and distal colon. These analyses focused on looking at the rates of recovery of healthy microbiota following the administration of 5-FU/vancomycin during treatment week 1  prior to 5-FU/vancomycin treatment, overall Lactobacilli and Bifidobacteria did not increase in the PC or the DC.Specific strains of ucositis –33. In aWe also assessed the composition of Bacteroidetes and Firmicutes, the predominant phyla in the healthy human gut, to determine how they are influenced by the probiotic with digestive enzymes supplement in the SHIME. The results showed that Bacteroidetes levels were particularly depleted during the 5-FU/vancomycin treatment period. Significantly, we observed that administration of the probiotic with digestive enzymes supplement also resulted in faster recovery of Bacteroidetes after 5-FU/vancomycin (after TR1) as compared to the control arm, an effect that was the greatest for the preventative arm of supplementation over the curative arm Figure . Remarka16S-targeted Illumina sequencing was used whereby amplified 16S rRNA marker gene sequences are clustered into taxonomic units of bacteria. When the data had been processed at the phylum and family levels, and the Simpson diversity index was calculated. The lowest possible value of the index is 1, representing a community consisting of only one Operational Taxonomic Unit (OTU). The highest possible value is the total number of OTUs, and the higher the index, the larger the diversity and the larger the evenness. Table Lastly, 16S-targeted Illumina sequencing was used to evaluate the differences in microbial compositions at the phylum level in the proximal and distal colons caused by the probiotic with digestive enzymes supplement. In Figure Following 5-FU/vancomycin treatment, the microbiome in the distal colon did not differ at the phylum level for the control, curative or preventative arms  and THP-1 macrophages [in vitro. These experiments allow examination of the influence of the microbial fermentations-derived products following preventive and curative administration of the probiotic with digestive enzymes supplement in the face of 5-FU/vancomycin treatment.We next asked how the probiotic with digestive enzymes supplement alters the composition of bacterial-derived metabolites having the potential to impact immune function as a means of offsetting the negative effects of 5-FU/vancomycin. To this end, we leveraged an rophages . Caco-2 rophages . THP-1 cThe results of the Caco-2/THP-1 co-culture experiments are provided in Figure Lactobacillus and Bifidobacterium genera, as well as 10 digestive enzymes contained in capsules that were administered in an in vitro system to recapitulate the gut microbiome using doses of the product that would be administered clinically. Using the SHIME model platform, where the gut microbiota can be cultured under representative conditions of the different intestinal regions, we successfully demonstrated that the probiotic with digestive enzymes supplement was capable of modulating the effects of 5-FU/vancomycin when administered in a preventative context. We also noticed positive changes in the microbial activity and composition using the probiotic with digestive enzymes supplement added to the SHIME beginning at the same time as 5-FU/vancomycin (i.e. the curative arm), including the production of metabolites that induced anti-inflammatory cytokine production in the Caco-2/THP-1 model. Based on studies that are ongoing, we believe that a longer duration of curative supplementation than was performed in the SHIME would have achieved at least a similar magnitude of beneficial effects as the preventative arm.The objective of this study was to evaluate the potential benefits of a proprietary probiotic with digestive enzymes supplement in preventing the gut dysbiosis caused a chemotherapy treatment and an antibiotic in a pre-clinical analysis of bioactivity. The test product contains a blend of 9 probiotic organisms of the in vitro analysis is advisable [Lactobacillus strains in addition to improving nutritional status [Lactobacillus isolates in the glycogen breakdown products that cannot grow in absence of the enzyme [The present study bridges the large gap that exists between the extensive microbiome research taking place and the lack of validation for specific products that are on the market. To this point, one DNA-based analysis of bifidobacterial species in commercial probiotic products demonstrated that only one of sixteen tested products matched the bifidobacterial label claim, and pill-to-pill and lot-to-lot variation was observed . The autdvisable . Anotherl status . In a ste enzyme . These sFusobacterium [Lactobacillus species reduced the expression of markers of atrophy in the muscles as well as inflammatory cytokines including IL-6 [Bifidobacterium, which coincided with metabolic shifts in the periphery and a delay in tumor-induced cachexia [Cancer patients undergoing chemotherapy, radiation therapy or other drug treatments experience a plethora of adverse events related to their treatments including nausea, vomiting, diarrhea, and loss of appetite, leading to a lower dietary intake, weight loss, and susceptibility to infections. These symptoms can be directly linked to the disturbed intestinal microbiome. During gut dysbiosis, parameters such as water volume, ion concentrations, osmotic pressure and pH are often abnormal, leading to growth of bacteria that further contribute to homeostatic imbalances and mediate aggressive inflammation . This inacterium , potentiacterium . By intracterium . Cancer ing IL-6 . Similarcachexia . ConservA separate and related issue is the role of the gut microbiome in tumor initiation since there is abundant evidence that chronic infection and the ensuing inflammation are contributing factors to tumor initiation . SCFA prLactobacillus and Bifidobacterium bacteremia [Saccharomyces cerevisiae [Clostridium difficile-associated diarrhea, have been reported to be associated with probiotic intake by ICU patients and individuals with immunodeficiency disorders. The amassed results from 17 studies revealed 5 case reports of probiotic-associated bacteremia or fungaemia based on blood culture tests. Another analysis [The limited evidence confirming the safety and benefits of these products in human clinical studies has led to a recommendation for cancer patients, who are immunocompromised, to take only moderate doses of dietary supplements or none at all . Isolatecteremia –25 as werevisiae , 51, a panalysis  concludeanalysis . We woulBifidobacterium infantis, Bifidobacterium bifidum, Lactobacillus acidophilus, Lactobacillus salivarius, Lactobacillus plantarum, Lactobacillus rhamnosus, Bifidobacterium longum, Lactobacillus casei, Lactobacillus paracasei, and digestive enzymes ; specifically, amylase, glucoamylase, lipase, bromelain, maltase, lactase, hemicellulose, xylanase, papain, and invertase.The probiotic with digestive enzymes supplement used herein comprises capsules is manufactured using proprietary methods and contains a blends of probiotics ; specifically, in vivo. The product was tested at an in vitro dose of 3 capsules/day before chemotherapy/antibiotic treatments, and 4 capsules/day during and after chemotherapy/antibiotic treatment (to be described below). This corresponds to an in vivo dosage of 6 capsules/day and 8 capsules/day before and after chemotherapy/antibiotic treatment, respectively.The capsules used herein are the same formulation that would be administered ProDigest  conducted the SHIME experiments and analysis. Briefly, the SHIME system consists of a series of double-jacketed vessels, simulating the digestive compartments that are initially inoculated with a fecal sample from a healthy adult donor using methods described previously .in vivo conditions in the different parts of the colon. Upon inoculation with fecal microbiota, these reactors simulate the ascending (V3), transverse (V4) and descending (V5) colon.The typical reactor setup consists of a succession of five reactors simulating the different parts of the human gastrointestinal tract. The first two reactors simulate different steps in food uptake and digestion, with peristaltic pumps adding a defined amount of SHIME feed (140 mL 3×/day) and pancreatic and bile liquid (60 mL 3×/day), respectively to the stomach (V1) and small intestine (V2) compartment and emptying the respective reactors after specified intervals . The lasThe present experiments employed an adapted SHIME setup to accommodate the following three treatment arms :Control Arm: Chemotherapy and antibiotics; no supplement given.Curative Arm: Chemotherapy and antibiotics; probiotic with digestive enzymes supplement added at the same time as the other agents.Preventative Arm: Chemotherapy and antibiotics; probiotic with digestive enzymes supplement added prior to the other agents.Accordingly, a TripleSHIME set-up was utilized wherein the colon reactors were limited to two instead of three to account for the additional test conditions required; specifically, reactors corresponding to PC-DC units  instead of AC-TC-DC units .The stages of the experiment are described below and also summarized in Table in vivo dose of 6 capsules/day).After inoculation of the colon reactors with an appropriate fecal sample, a two-week stabilization period allowed the microbial community to differentiate in the different reactors depending on the local environmental conditions. During this period, the basic nutritional matrix was provided to the SHIME to support diversity of the gut microbiota originally present in the fecal inoculum. The third arm of the SHIME setup , already received 3 capsules/day during the stabilization period (corresponding to an in vivo dose of 6 capsules/day).During this two-week reference period, the standard SHIME nutrient matrix was further dosed to the model. Analysis of samples in this period allows to determine the baseline microbial community composition and activity in the different reactors, which will be used as a reference for evaluating the treatment effects. The third arm of the SHIME setup (PREV), already received 3 capsules/day during the control period (~ in vivo dose of 8 capsules/day) at the start of the chemotherapy administration , whereas addition of the supplement for arm 3 of the SHIME was continued (at 4 capsules/day ~ in vivo dose of 8 capsules/day) (PREV).During this four-week period, the SHIME reactor was operated under nominal conditions, but each arm was treated as follows. During the first week, all arms received chemotherapy (10 μM of 5-fluorouracil (5-FU)) and vancomycin treatment (62.5 mg/L of vancomycin). During the subsequent weeks, it was considered a “recovery” period from the effects of 5-FU and vancomycin. Arm 1 of the SHIME did not receive any additional treatment . Arm 2 of the SHIME received the probiotic with digestive enzymes supplement : Bacteroidetes phylum, Firmicutes phylum, reported .16S ribosomal RNA (rRNA) sequencing was used to analyze samples from the SHIME reactors to identify and compare the microorganisms using similar methods as published elsewhere . The IllTo provide an ecological interpretation of these data, the Simpson reciprocal index was calculated as a measure of diversity and evenness of the microbiota as described previously . An incr5 cells/insert. Caco-2 monolayers were cultured for 14 days, with three medium changes/week, until a functional cell monolayer was obtained. Cells were maintained in Dulbecco's Modified Eagle Medium (DMEM) containing 25 mM glucose and 4 mM glutamine and supplemented with 10 mM HEPES and 20% (v/v) heat-inactivated (HI) fetal bovine serum (FBS).The co-culture experiment was performed as previously described  Briefly,5 cells/well and treated with 100 ng/mL of PMA for 48 hours (h). PMA induces the differentiation of the cells into macrophage-like cells.THP1 cells (InvivoGen) were maintained in Roswell Park Memorial Institute (RPMI) 1640 medium containing 11 mM glucose and 2 mM glutamine, supplemented with 10 mM HEPES, 1 mM sodium pyruvate and 10% (v/v) HI-FBS. THP1 cells were seeded in 24-well plates at a density of 5 × 10in vitro experiments were conducted based on previous studies by Satsu and colleagues [To mimic the interface between host immune cells and the fermentation products of the gut microbiome, lleagues . In thisEscherichia coli K12, InvivoGen). Cells were also stimulated at the basolateral side with LPS in combination with 1 μM hydrocortisone (HC) (Sigma-Aldrich) and medium without LPS (LPS-) in control experiments. Cultures were incubated at 37 degrees Celcius in a humidified atmosphere of air/CO2 . After 6 h of LPS stimulation, the basolateral supernatants were collected for cytokine measurement (human IL-6 and IL-10) by Luminex. multiplex (Affymetrix-eBioscience) according to the manufacturers’ instructions. All treatments were done in triplicate.Briefly, the apical compartment containing Caco-2 cells was filled with sterile-filtered (0.22 μm) colonic SHIME suspensions (diluted 1:5 (v/v) in Caco-2 complete medium). Cells were also treated apically with 12 mM Sodium butyrate (NaB) (Sigma-Aldrich) as a positive control in experiments establishing the system. The basolateral compartment containing THP1 cells was filled with Caco-2 complete medium. Cells were also exposed to Caco-2 complete medium in both chambers in control experiments. Cells were treated for 24 h, at which time the basolateral supernatant was discarded and THP-1 cells were stimulated with Caco-2 complete medium containing 500 ng/mL of ultrapure LPS (*) represents p < 0.05. All statistics were performed using GraphPad Prism version 7.02 for Windows .To evaluate the difference between the treatment sample and its respective control sample within each SHIME, a two-way ANOVA with Sidak's multiple comparisons test was performed. These results are presented on the graphs. To evaluate the difference between the SHIMES (CUR and PREV) compared to the CTRL SHIME within each colon compartment for both the control and the treatment phase, a two-way ANOVA with Dunnett's multiple comparisons test was performed. These results are presented in the figures where  compared to the CTRL SHIME using two-way ANOVA with Dunnett's multiple comparisons test was performed. Results were considered significant if


A number of mobile health  apps exist that focus specifically on promoting exercise behavior. To increase user engagement, prompts, such as text messages, emails, or push notifications, are often used. To date, little research has been done to understand whether, and for how long, these prompts influence exercise behavior.This study aimed to assess the impact of prompts on mHealth self-monitoring and self-reported exercise in the days following a prompt and whether these effects differ based on exercise modality.t tests.Of the possible 99 adults at risk for developing type II diabetes who participated in a diabetes prevention program, 69 were included in this secondary analysis. Participants were randomly assigned to 1 of the following 2 exercise conditions: high-intensity interval training or moderate-intensity continuous training. In the year following a brief, community-based diabetes prevention program involving counseling and supervised exercise sessions, all participants self-monitored their daily exercise behaviors on an mHealth app in which they were sent personalized prompts at varying frequencies. mHealth self-monitoring and self-reported exercise data from the app were averaged over 1, 3, 5, and 7 days preceding and following a prompt and subsequently compared using 68=6.82; P<.001; d=0.46) and self-reported exercise  significantly increased in the 3 days following a prompt compared with the 3 days preceding. Prompts were most effective in the first half of the year, and there were no differences in self-monitoring or self-reported exercise behaviors between exercise modalities . In the first half of the year, self-monitoring was significant in the 3 days following a prompt , and self-reported exercise was significant in the 3 days , 5 days , and 7 days  following a prompt, whereas no significant changes were found in the second half of the year.In the year following the diabetes prevention program, self-monitoring (tThis study provides preliminary evidence regarding the potential influence of prompts on mHealth self-monitoring and self-reported exercise and the duration for which prompts may be effective as exercise behavior change tools. Future studies should determine the optimal prompting frequency for influencing self-reported exercise behaviors. Optimizing prompt frequency can potentially reduce intervention costs and promote user engagement. Furthermore, it can encourage consumers to self-monitor using mHealth technology while ensuring prompts are sent when necessary and effective.DERR2-10.2196/11226 Mobile phones are ubiquitous and becoming an integral part of daily life. In 2015, global subscriptions of mobile phones were approximately 7 billion; this constitutes a substantial increase from 738 million subscriptions in 2000 [As the widespread adoption of mobile phones increases, so too does the opportunity for the development and implementation of theory-driven, cost-effective, evidence-based mobile phone apps  used to influence health behaviors. An mHealth app is any mobile phone app, which is used for tracking, guiding, teaching, or enabling individuals in any health-related behaviors and can range from tracking diet and exercise to guided meditation or monitoring of diabetic sugar level. The accessibility of these apps is also advantageous for researchers who can monitor consumer behaviors remotely, provide real-time feedback, and aggregate data so as to improve monitoring systems . DespiteThis lack of evidence-based mHealth apps may be because of the time-consuming nature of conventional methods of evaluation, such as randomized controlled trials (RCTs), being unable to keep up with the dynamic nature of mHealth app development, and the rapid advancement of mobile technologies . One appSelf-monitoring is a commonly used and robust BCT, which often involves participants logging target behaviors . A meta-Prompts within mHealth apps promote individual-app interaction . There is a growing body of evidence to support the use of prompts as either stand-alone interventions or supplementary features to increase the effectiveness of health interventions ,23. SpecThis paper analyzes mobile phone prompt data to promote exercise adherence for 1 year following a diabetes prevention program research study. Program participants were randomized to perform 1 of the following 2 exercise modalities: high-intensity interval training (HIIT) or moderate-intensity continuous training (MICT). HIIT has garnered attention as an exercise program primarily because of its shorter duration and similar cardiometabolic health effects when compared with MICT ,33. TherThe main objective of this study was to examine whether mHealth prompts influence self-monitoring and self-reported exercise in 1, 3, 5, or 7 days following a prompt. Prompts are meant to provide brief effects; therefore, we hypothesized that there would be initial increases in both mHealth self-monitoring and self-reported exercise behaviors. No specific hypotheses on whether prompt effects would last 1, 3, 5, or 7 days were made. Given the short follow-up durations of previous research and lack of literature addressing the impact of prompts on exercise prescriptions, we wanted to explore whether the effects of a prompt were consistent in the first and second half of the year following a diabetes prevention program and whether the impact of prompts differed between those randomized to HIIT or MICT.This paper presents a secondary analysis examining the effect of personalized mHealth prompts on self-monitoring and self-reported exercise behaviors within a diabetes prevention program. Complete details regarding the study design, methods, and procedures have been previously published . The proThe theory-based mHealth app used in the diabetes prevention program was designed using principles from social cognitive theory to help participants self-monitor their exercise behaviors . Participrompt was defined as any of the above message types in which there was a minimum of 6 days preceding it with no other message. This definition was determined to exclude any subsequent conversation resulting from a prompt in the analyses.The messaging platform within this mHealth app allowed for 2-way messaging between participants and their exercise counselors. Participants received personalized messages that encompassed counselors sending name-specific prompts using a series of message templates . These m2, and were cleared to engage in vigorous exercise using Canadian Society for Exercise Physiology Physical Activity Readiness Questionnaire-Plus [Of 99 adults participated in a diabetes prevention program, 69  were included in this analysis. Participants were eligible to participate if they were between the ages of 30 and 65 years, were inactive (defined as engaging in <3 bouts of moderate or vigorous aerobic exercise per week in the past 6 months), had a body mass index between 24 and 40 kg/mire-Plus . ParticiOutcome measures include frequency of both mHealth self-monitoring and self-reported exercise in the week before and after a prompt. mHealth self-monitoring was defined as any day in which a participant logged on the mHealth app; this includes days in which they engaged in purposeful exercise, rest days, and days in which they did not exercise and exceeded their number of rest days. Self-reported exercise was defined as only those days in which participants logged on the mHealth app that they engaged in purposeful exercise. Specifically, when a participant self-monitored “yes I exercised today,” they were able to type in the details of their exercise; however, for the purpose of this study, the level or type of logged exercise was not examined.. Throughout the free-living 1-year follow-up period, participants were sent personalized messages delivered through the app messaging system from their exercise counselor at a variable frequency. A prompt was defined as any message in which there was a minimum of 6 days preceding it with no other message. This means that any subsequent conversation resulting from a prompt was not included in the analyses.During the one-on-one counseling sessions, the exercise counselor created each participant’s profile on the mHealth app and taught participants how to self-monitor their exercise to ensure participants were confident in their ability to monitor their exercise mHealth self-monitoring (1-3=yes and 4=no) and self-reported exercise (1=yes and 2-4= no).The following procedures were completed using MATLAB  in to extract outcome measures from app data regarding daily activity; these measures include mean mHealth self-monitoring and self-reported exercise in the week before and after a prompt. Participants’ daily activity on the mHealth app was initially coded as (1) logged “yes I exercised today,” (2) logged “no I did not exercise today,” (3) logged “rest day,” and (4) did not log anything. Following this, participants logging was dichotomously categorized: t tests being run in an attempt to decrease type I error. Once averages for individual prompts were calculated, weekly averages were established for the whole year, months 1 to 6, and months 7 to 12; these time points are in line with the overall research study, which assessed all main outcomes at 6 and 12 months. The same procedures were followed to identify the average number of days for self-reported exercise.To determine if self-monitoring behaviors increased in the days following a prompt, the average number of days self-monitored in 1, 3, 5, and 7 days preceding and following a prompt was calculated. These days were selected to facilitate analysis on how the brief effects of a prompt on self-monitoring and self-reported exercise may vary over the week. Days 2, 4, and 6 were excluded to decrease the number of t tests were conducted to determine whether self-monitoring and self-reported exercise differed (1) in the day following a prompt compared with the day preceding a prompt, (2) in the 3 days following a prompt compared with the 3 days preceding a prompt, (3) in the 5 days following a prompt compared with the 5 days preceding a prompt, and (4) in the 7 days following a prompt compared with the 7 days preceding it. This analytic procedure was chosen as it aligns with the nature of our hypotheses examining differences before and after a prompt. Change scores for mHealth self-monitoring and self-reported exercise were calculated by taking the difference between the days before and after a prompt. Independent samples t tests were conducted to compare change scores between those randomized to HIIT and MICT. Analyses were completed independently for the whole year (months 1-12); the first half of the year (months 1-6) and the latter half of the year (months 7-12). All data were analyzed using SPSS statistics for Windows . Significance level was set at P<.05. Effect sizes were calculated using Cohen d.Paired samples Baseline measurements and demographics of the 69 inactive and overweight adults  whose data were included in this study are reported in In the year following a diabetes prevention program, there were no significant increases in mHealth self-monitoring or self-reported exercise in 1, 5, and 7 days following a prompt compared with the days preceding a prompt. Both mHealth self-monitoring and self-reported exercise did significantly increase in the 3 days following a prompt compared with the 3 days preceding it.There were no significant differences between exercise conditions (HIIT and MICT) for both mHealth self-monitoring and self-reported exercise in 1, 3, 5, and 7 days following a prompt. Descriptive statistics and inferential statistics are given in In months 1 to 6, a total of 226 prompts were sent to the HIIT group , and 283 prompts were sent to the MICT group .In the first 6 months following the program, mHealth self-monitoring significantly increased in the 3 days following a prompt compared with the 3 days preceding it but did not significantly differ in 1, 5, or 7 days following a prompt compared with preceding days. Self-reported exercise did not significantly increase in the day following a prompt compared with the day preceding it; however, it did significantly increase in 3, 5, and 7 days following a prompt compared with the respective preceding days.t tests conducted on change scores suggest that there was a significantly larger change in self-monitoring for those randomized to MICT compared with those randomized to HIIT , but no significant group differences for self-reported exercise . When looking at HIIT and MICT independently, both groups demonstrated significant increases between the 3 days before and after a prompt in mHealth self-monitoring . Additional information regarding descriptive statistics and inferential statistics are given in In 1, 5, and 7 days following a prompt compared with the days preceding it, there were no significant differences between HIIT and MICT groups for both mHealth self-monitoring and self-reported exercise. In the 3 days following a prompt compared with the 3 days preceding it, independent samples In months 7 to 12, a total of 143 prompts were sent to the HIIT group , and 182 prompts were sent to the MICT group .In the second half of the year following the program, there were no significant differences in either mHealth self-monitoring or self-reported exercise in 1, 3, 5, and 7 days following a prompt compared with the days preceding a prompt. There were no significant differences between exercise conditions (HIIT and MICT) for both mHealth self-monitoring and self-reported exercise in 1, 3, 5, and 7 days following a prompt in the second half of the year. Descriptive statistics and inferential statistics are presented in The primary objective of this secondary data analysis was to assess changes in mHealth self-monitoring and self-reported exercise in the days preceding and following a prompt. Secondary objectives of this research were to examine whether results differed based on exercise modality (HIIT vs MICT) and the differences between the first and second half of the year following a diabetes prevention program. Overall results suggest that both self-monitoring and self-reported exercise behaviors significantly increase in the 3 days following a prompt when compared with the 3 days preceding it, the greatest changes were observed in the first half of the year, and there were no differences between exercise modality.In the year following a diabetes prevention program, the observed differences in self-monitoring and self-reported exercise behaviors were most potent in the 3 days following a prompt, whereas there were no significant changes in 1, 5, or 7 days following a prompt. Exercise is a complex behavior that requires self-regulation such as scheduling and planning . As suchIn the first half of the year, self-reported exercise behavior significantly increased in 3, 5, and 7 days following a prompt, but not the day immediately following a prompt, whereas no significant changes were observed in the second half of the year. Reasons why prompts appeared to have no observed change on behaviors in the second half of the year are unknown and should be the focus of future research. In the first half of the year, a total of 226 prompts were sent, whereas in the second half of the year, 143 prompts were sent. Although the difference in frequency of prompts sent between the first and second half of the year could have influenced the observed changes, additional research is required to examine the role of prompt frequency in changing self-monitoring and self-reported exercise behavior.Similar to self-reported exercise, the impact of prompts on mHealth self-monitoring was only observed in the first half of the year. Specifically, in the first half of the year following a diabetes prevention program, mHealth self-monitoring significantly increased in the 3 days following a prompt compared with the 3 days preceding a prompt, but not in 1, 5, or 7 days following a prompt. Individuals included in this analysis self-monitored an average of 286 days in the 12-month follow-up period. It may be the case that prompts are not needed for individuals who regularly self-monitor. However, it is difficult to discern the impact of a prompt on daily self-monitoring behaviors, given that the majority of participants were self-monitoring on a daily basis, and there was no control group.There is a growing body of evidence suggesting HIIT may be a viable exercise alternative to MICT ,33. TherSystematic reviews of the literature have shown that individuals who received prompts had greater weight loss and increased PA compared with nonprompt controls ,31. Despt tests without adjustment. All participants using the mHealth app received prompts, and there was no experimental manipulation of prompts. Another limitation was that there had been no validation of this mHealth app as an exercise measure. However, the information participants report on the mHealth app is similar to the information contained in validated measures , no a priori sample size calculation, and conducting multiple ionnaire ). AlthouOne final limitation regarding the criteria for prompts to be included in the analyses. Our analyses examined the effects of a prompt on self-monitoring and self-reported exercise behaviors and did not include any subsequent conversation resulting from a prompt in the analysis. There is a possibility that the amount of interaction between a participant and their exercise counselor on the mHealth app influenced their behaviors.Despite this preliminary evidence that prompts may influence self-monitoring and self-reported exercise behaviors, future research is needed to examine the causal impact of prompt frequency on self-monitoring and self-reported exercise behavior in an attempt to elucidate an optimal prompt frequency for behavior change.These analyses used only those participants who were engaging with the app and individuals self-monitored approximately 80% of the time. In addition, we were unable to analyze whether the level of virtual interaction between exercise counselors and participants influenced the effect of a prompt on self-monitoring and self-reported exercise behaviors. Future studies should address the impact of prompts on less consistent self-monitors while also examining the role that social interaction may play on self-monitoring and self-reported exercise.The duration of prompts’ impact on self-reported exercise behaviors was relatively short . Future studies should examine the optimal prompt frequency and timing for cueing self-reported exercise behavior following behavior change programs. Utilization of optimization trials or n-of-1 trials may be 1 possible means to examine dose-response relationship between app-delivered prompts and exercise.Within this analysis, we provided evidence regarding the observed changes in self-monitoring and self-reported exercise behavior following a prompt and the duration for which prompts may be effective as exercise behavior change tools. Future studies assessing prompts should examine causal factors relating to the observed decrease in prompt effectiveness on self-reported exercise behaviors in the 7 to 12 months following an exercise behavior change program. Understanding how to optimally intervene through prompts can decrease intervention cost and time as researchers may limit unnecessary prompts while continually encouraging consumers to use mHealth technology to change health behaviors.


Label-free in vivo imaging is crucial for elucidating the underlying mechanisms of many important biological systems in their most native states. However, the applicability of existing modalities has been limited to either superficial layers or early developmental stages due to tissue turbidity. Here, we report a synchronous angular scanning microscope for the rapid interferometric recording of the time-gated reflection matrix, which is a unique matrix characterizing full light-specimen interaction. By applying single scattering accumulation algorithm to the recorded matrix, we removed both high-order sample-induced aberrations and multiple scattering noise with the effective aberration correction speed of 10,000 modes/s. We demonstrated in vivo imaging of whole neural network throughout the hindbrain of the larval zebrafish at a matured stage where physical dissection used to be required for conventional imaging. Our method will expand the scope of applications for optical imaging, where fully non-invasive interrogation of living specimens is critical. A major challenge of in vivo imaging is imaging deeper, including in turbid tissue. The authors report an adaptive optics based microscope that uses coherent single scattering signal to reduce sample-induced aberrations and enable fast deep-tissue imaging of in vivo larval zebrafish brain. Typical AO microscopy for deep-tissue imaging has been designed to work for fluorescence imaging, and it has played a pivotal role in elucidating the underlying mechanisms of biological systems that could not otherwise be visualized. It identifies the sample-induced aberration by either direct wavefront sensing12 or feedback control of wavefront-shaping devices16. However, in both cases, it is necessary to iteratively update the aberration correction to enhance the signal of interest, which is initially lower than the background fluorescence noise induced by multiple scattering in the case of deep-tissue imaging. Owing to the incoherent nature of fluorescence emission, this corrective update can only be made by multiple image acquisitions at each iteration step, which slows down the overall image acquisition speed. It typically takes more than 10 s to complete the entire sequence of aberration correction, during which the sample must be stationary. An important trend in recent years has been to mitigate the speed limitation by simultaneously correcting multiple sub-pupils17 or sub-areas18 in the large view field. This has effectively increased the image acquisition speed in terms of the corrected area per unit time. Equivalently, the number of corrected modes per unit time has been increased to approximately 50 modes/s, but the minimum image acquisition time has remained the same.Light waves propagating in biological tissues experience wavefront distortion due to the complex spatial heterogeneity of the refractive index. The wavefront distortion, excluding the severe multiple-scattering noise, is often called a sample-induced aberration, which manifests itself as the phase retardation of propagating waves depending on their propagation angles. Considering that a focused spot is formed by the coherent superposition of many angular waves, it is evident that this sample-induced aberration causes the improper formation of a focus, thereby reducing both the resolving power and signal to the multiple-scattering noise ratio. In recent years, various methods have been proposed to deterministically make use of multiple-scattered waves23. Notably, software-based AO microscopy has been developed, where aberration correction is applied after the image acquisition27. This is available only for the coherent imaging modalities because the phase of the scattered waves is recorded. These software-based AO imaging methods can be much faster than the hardware-based AO imaging because sample needs to be stationary only during the one-time image acquisition. Furthermore, the cost of building a system can be reduced owing to the exemption of the wavefront-shaping devices. However, most of the developed algorithms require point-like structures that can serve as guiding stars because of their inability to distinguish the aberrations on the way to the specimens from those on the way out. Alternatively, an illumination beam with narrow angular divergence was used to minimize the aberration on the way in, and image metrics such as image sharpness and intensity were optimized by adding corrective phases to the Fourier-transformed map of the acquired image30. Because these approaches cannot easily distinguish signals from multiple-scattering noise, they are susceptible to the multiple-scattering noise. For this reason, the applications of AO coherent imaging have been confined to weak-scattering cases such as retinal imaging. To overcome strong multiple scattering noise and sample-induced aberration, time-gated reflection matrix approaches32 have been investigated, which is composed of a set of wide-field and time-gated complex field maps of intrinsic elastic backscattering taken for various illumination angles. However, this approach has been inapplicable for the in vivo imaging because a slow liquid-crystal spatial light modulator should be used for the recording of the time-gated reflection matrix.AO has also been applied to coherent imaging modalities such as confocal reflectance imaging, optical coherence tomography, and digital holographic microscopy for the applications where administration of labeling agents needs special care. For instance, individual photoreceptor cells in the retina of a living eye were clearly visualized by sensing and correcting the ocular aberrationsHere we develop an adaptive optical synchronous angular scanning microscope (AO-SASM) for in vivo deep-tissue imaging free from any labeling agents. In AO-SASM, we realized the high-speed recording of a time-gated reflection matrix by synchronously scanning the angle of the sample and reference waves from a supercontinuum laser. This strategy ensures the uniform interference over the wide view field even when both temporal pulse front and wavefront are rotated by fast scanning mirrors. By processing this matrix in such a way to coherently accumulate single scattering signal, we removed both multiple scattering noise and local high-order sample-induced aberration. In doing so, we significantly reduced the image acquisition time per depth from a few minutes to 0.22 s and enhanced the effective aberration correction speed excluding the data processing time to 10,000 modes/s  because it makes the pulse front of the modulated beam remain parallel to the surface of the SLM even with the scanning of S1) Fig. . The pulS1) Fig. , f, espe32, in which sample-induced aberrations are identified from the measured time-gated reflection matrix, preferably in such a way to maximize the single-scattered waves over multiple-scattering noise. Conventional confocal reflectance/fluorescence microscopy was set up on the top of the AO-SASM for the comparison of the imaging performance  of 0.8 was used to deliver the planar illumination to the sample and capture backscattered waves. Therefore, single-depth recording of complex-field images can cover a depth range of 15 μm by the axial resolution of 2.0 μm set by confocal gating with the use of the computational refocusing. A camera recorded the interferogram formed by the backscattered wave from the sample and a reference wave with a magnification of 120× . Angular scanning of the illumination uniformly covered the entire NA of the objective lens, and the number of illumination angles 33. However, as a zebrafish ages, pigmented scales, complex skin architectures, and internal organs significantly deteriorate the resolving power of conventional high-resolution confocal imaging. For instance, dark area indicated by the yellow dashed box in Fig. 34, and the degradation of spatial resolution was inevitable for more matured zebrafish36, and studies for later developmental stages require physical dissection. In our study, a 21-dpf larval zebrafish introducing both strong aberration and multiple light scattering was placed under the objective lens . Zebrafish have served as a useful model platform for studying the neural development of vertebrates, mainly owing to the rapid development and transparency of the embryosens Fig. , and mulFor the aberration correction, the full view field was divided into 6 × 6 segments, as indicated by the yellow dotted boxes in Fig. ned Fig. . We tranWe conducted volumetric imaging for the hindbrain of two living larval zebrafishes, 6 and 10 dpf. A series of time-gated reflection matrices were recorded from dorsal to ventral to the depth of ~220 μm with a depth scanning step of 5 μm. After reconstructing an aberration-corrected slice image at each depth, numerical propagation was applied at an increment of 0.5 μm to fill the gap between the neighboring slices  larvae in which green fluorescent proteins are expressed at the membrane of oligodendrocytes that wrap around the axons, fluorescence signals effectively visualize the myelin that surrounds axons. For comparison, the MIP image of the AO-SASM image over the entire depth range of Fig. 39. Similar to the confocal fluorescence imaging, only dense fascicles were visible, and individual axonal branches remained missing in the volumetric confocal reflectance images taken at the same area  up to the depth where conventional imaging modalities fail. By dealing with both position-dependent sample-induced aberrations and multiple-scattering noise with no need for guiding stars and hardware feedback, AO-SASM noninvasively offered the atlas of the nervous system and the tomography of fine myelinated axon projections inside the hindbrain of a larval zebrafish in its native state. Recent studies demonstrated that the quantification of demyelination and remyelination processes is critical for assessing the physiological states of the nervous systems44. While our AO-SASM visualizes myelinated axons and cellular compartments having higher reflectivity than surrounding tissues with the use of elastic backscattering, fluorescence microscopy can visualize specific types of cells or molecules at the expense of special sample preparations. And often times, its volumetric imaging rate could be dramatically improved in the form of light-sheet microscopy45 and light-field microscopy46. And second- and third-harmonic-generation microscopy, while high excitation power is required, visualizes morphological context such as collagen fibers, skin cells, blood cells and lipid accumulations without the use of labeling agents. While these multi-photon microscopy techniques provide valuable molecular contrast, they suffer from the loss of spatial resolution due to the sample-induced aberrations especially when imaging zebrafishes. Unlike mouse brain tissues, many heterogeneous structures such as skin and internal organs in the zebrafish act as sources of aberration. According to the literatures reporting the use of multi-photon microscopy for studying the central nervous system of the zebrafish, the imaging depth was much shallower than 200 μm, and studies were limited to early developmental stages. On the contrary, AO-SASM reached the depth of 220 μm through a thick hindbrain with the spatial resolution close to the ideal diffraction limit. Therefore, the imaging depth of our method is better than or comparable to the state-of-the-art multi-photon microscopy if spatial resolution is accounted for in estimating the imaging depth. In this respect, AO-SASM can not only complement these existing imaging modalities in terms of information content, but also assist them to cope with the sample-induced aberration.In recent years, the application of multi-photon microscopy such as two/three-photon fluorescence microscopy and second/third-harmonic-generation microscopy for studying a zebrafish has drawn much attention due to its deep penetration through scattering tissues and diverse contrast mechanisms2, which is an order of magnitude lower than maximum permissible exposure level of 200 mW/cm2 in animal tissues. It requires relative weak excitation beam in comparison with multi-photon microscopy as elastic backscattering is used for imaging. Furthermore, wide-field detection configuration is used instead of pinhole gating, which makes the signal collection more efficient. The image acquisition speed per depth, mainly determined by the camera frame rate, was improved to 4 Hz in the present implementation and can further be increased to a video-rate if a commercially available high-speed complementary metal–oxide semiconductor camera is used. This will extend the proposed method to in vivo imaging of animal and human subjects for various applications, including myelin-associated physiology in neuroscience, retinal pathology in ophthalmology, and endoscopic interrogation of internal organs. With all these benefits, our method expands the scope of studies and diagnosis that optical imaging can offer.Irradiance of illumination used in AO-SASM was below 100 μW/mmIn the experimental setup shown in Fig. mentclass2pt{minim47 is that the reference wave rotates along with the sample wave. We must account for this difference before applying the aberration correction algorithm, which requires complex field maps in the laboratory frame. Let us consider a backscattered wave The main difference of AO-SASM from the conventional interference microscope and our earlier implementationsI with respect to in n times to find We employed AO correction to a sub-matrix )ko Fig. . After tclaudinK:gal4;uas:mgfp) embryos were raised at 28 °C in an E3 embryo medium . First, 24-h post fertilization, they were transferred to the E3 medium containing N-phenylthiourea (Sigma) for inhibiting pigmentation. After 6 to 21 dpf, zebrafishes were anesthetized by adding tricaine (Sigma) to the E3 medium. They were then immersed in 1.5% low-melting agarose (invitrogen) and mounted on a slide glass. We supplied the mounted specimen with the E3 medium containing tricaine to maintain anesthesia during the investigation under the microscope. The immersion solution was continuously warmed by a temperature controller  to maintain the temperature at 24–26 °C. All animal experiments were approved by the Korea University Institutional Animal Care & Use Committee.Zebrafish Tg(Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Movie 2


Furthermore, various machine-learning algorithms, including random forest regression (RFR), gradient-boosting regression (GBR), and adaptive boosting regression (ABR), were employed for estimating systolic blood pressure (SBP) and diastolic blood pressure (DBP) from the measured pulse-wave signals. Among these algorithms, the RFR-based method gave the best performance, with the coefficients of determination for the reference and estimated blood pressures being R2 = 0.871 for SBP and R2 = 0.794 for DBP, respectively.This work describes the development of a pressure-sensing array for noninvasive continuous blood pulse-wave monitoring. The sensing elements comprise a conductive polymer film and interdigital electrodes patterned on a flexible Parylene C substrate. The polymer film was patterned with microdome structures to enhance the acuteness of pressure sensing. The proposed device uses three pressure-sensing elements in a linear array, which greatly facilitates the blood pulse-wave measurement. The device exhibits high sensitivity (−0.533 kPa Various recent studies in epidemiology have reported that hypertension is one of the most common causes of cardiovascular disease ,2, and tAn invasive approach is capable of accurately and continuously measuring blood pressure ,6. The tIn recent years, research on noninvasive blood-pressure measurement has drawn wide attention. Various highly sensitive pressure sensors have been reported for continuously measuring blood pulse waves ,13,14,15The present work proposes a pressure-sensing array for noninvasive continuous blood pulse-wave monitoring. The sensing elements comprise a polydimethylsiloxane (PDMS) conductive polymer film, and three pairs of interdigital electrodes patterned onto a flexible Parylene C substrate. The polymer film has been patterned with microdome structures for enhancing the acuteness of pressure sensing . The proA schematic of the proposed blood-pressure monitoring system is shown in The proposed conductive polymer was fabricated by dispersing multi-wall carbon nanotubes (MWCNTs) in polydimethylsiloxane (PDMS) prepolymer. The prepolymer was prepared as follows: First, the PDMS prepolymer  was mixed with hexane at a ratio of 4:1. Next, the solution of MWCNTs with diameters of about 20 nm and lengths ranging from 10 to 50 μm was dispersed in the mixture at a concentration of 6% by weight. The prepolymer mixture was thoroughly stirred for 6 hr by a magnetic stirrer. The mixing performance was greatly improved by the hexane, which served as a dispersant. The PDMS-curing agent  was then added to the prepolymer at a ratio of 1:10, and stirred for 20 m. Finally, the prepolymer mixture was degassed in a vacuum chamber for 30 m to evaporate the solvent, readying it for the subsequent lithography process.The fabrication of the flexible interdigital electrodes is described in −1) at a low pressure range (below 2 kPa). However, when the applied pressure exceeded around 10 kPa, the resistance almost stopped decreasing, which may be due to the fact that the contact area between the microdome structures and the electrode pair reached a steady value.The dynamic response of the proposed sensing element was also measured and discussed. The experimental setup is shown in The continuous blood pulse-wave signals measured by the proposed sensing array are presented in In this study, the proposed device obtained blood pulse-wave signals from 23 participants. In addition, the reference blood pressures were measured simultaneously using a cuff sphygmomanometer . Hence, the measured pulse wave signals corresponded to the simultaneously measured systolic blood pressure (SBP) and diastolic blood pressure (DBP). In order to remove noise and artifacts from the raw pulse-wave signals, the Hilbert–Huang transform (HHT) method was employed to process the data ,24. In gThe processed pulse-wave signals (data) were split into two sets: 80% of the data were included in the dataset for training the regression models , and 20% of the data were included in the dataset for testing the regression models  in estimating the target SBP and DBP values. In this work, three blood-pressure estimation models were constructed, through three distinct regression algorithms, including RFR , GBR 2727, and A2 between the estimated SBP and the cuff-based SBP was 0.871, while the R2 between the estimated DBP and the cuff-based DBP was 0.794. Both R2 values  of the RFR model were highest when compared with those of the other two models.−1) and a fast dynamic response. Furthermore, three distinct machine-learning algorithms were employed to estimate the systolic and diastolic blood pressure from the measured pulse-wave signals. A performance comparison of the algorithms is provided.In this work, a pressure-sensing array for noninvasive continuous blood pulse-wave monitoring is presented. The propose device features a linear-array configuration in which three pressure-sensing elements are utilized. Each element comprises a conductive polymer film and an interdigital electrode pair on a flexible substrate. Microdome structures are patterned on the polymer film for enhancing the pressure-sensing sensitivity. The proposed array design greatly facilitates the measurement of blood pulse waves. The realized device exhibits high sensitivity (−0.533 kPa