Background: Amyloid deposition is common in dementia with Lewy bodies, but its pathophysiological significance is unclear.Objective: The objective of this study was to investigate the relationship between amyloid deposition and clinical profile, gray matter volume, and brain perfusion in dementia with Lewy bodies.Methods: Dementia with Lewy bodies (n = 37), Alzheimer's disease (n = 20), and controls (n = 20) underwent a thorough clinical assessment, 3T MRI, and early‐ and late‐phase 18F‐Florbetapir PET‐CT to assess cortical perfusion and amyloid deposition, respectively. Amyloid scans were visually categorized as positive or negative. Image analysis was carried out using statistical parametric mapping (SPM) 8.Results: There were no significant differences between amyloid‐positive and amyloid‐negative dementia with Lewy bodies cases in age (P = .78), overall cognitive impairment (P = .83), level of functional impairment (P = .80), or any other clinical or cognitive scale. There were also no significant differences in hippocampal or gray matter volumes. However, amyloid‐positive dementia with Lewy bodies cases had lower medial temporal lobe perfusion (P = .03) than amyloid‐negative cases, although a combination of medial temporal lobe perfusion, hippocampal volume, and cognitive measures was unable to accurately predict amyloid status in dementia with Lewy bodies.Conclusions: Amyloid deposition was not associated with differences in clinical or neuropsychological profiles in dementia with Lewy bodies, but was associated with imaging evidence of medial temporal lobe dysfunction. The presence of amyloid in dementia with Lewy bodies cannot be identified on the basis of clinical and other imaging features and will require direct assessment via PET imaging or CSF. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society. Dementia with Lewy bodies (DLB) is the second most common type of neurodegenerative dementia. When compared with Alzheimer's disease (AD), it is associated with distinct cognitive, neuropsychiatric, and motor symptoms and characteristic imaging findings.The pathological hallmarks of DLB are the presence of Lewy bodies and Lewy neurites, but many cases also display AD pathology postmortem.We examined amyloid deposition in patients with DLB who had detailed neuropsychological and clinical evaluations to assess the impact of amyloid on clinical profile. We hypothesized that in DLB, a positive amyloid PET scan would be associated with clinical and imaging findings similar to AD, that is, poorer memory function, hippocampal atrophy, and reduced medial temporal lobe perfusion. We also hypothesized that amyloid deposition in DLB would be intermediate between AD patients and healthy controls.Participants were recruited prospectively between June 2013 and February 2016 from secondary care services in the North of England. Control participants were recruited through a research case register or were partners of participants. All participants were ≥60 years old. Dementia patients had a diagnosis of probable DLB or probable AD confirmed by 2 clinicians based on contemporaneous diagnostic criteria,Participants were excluded if they had a major concurrent psychiatric illness, severe physical illness, contraindications to PET‐CT imaging, a history of other significant neurological illness including stroke, previous experimental treatment with an amyloid‐targeting agent, or current treatment with any other investigational agent.Participants with capacity gave their written informed consent to take part in the study. For those with dementia who lacked capacity, their participation in the study was discussed with a consultee in accordance with the Mental Capacity Act. The study received ethical approval from the National Research Ethics Service Committee North East—Newcastle & North Tyneside 2 (Research Ethics Committee Identification Number 13/NE/0064).–Cognitive impairment  followed immediately by a 5‐minute scan for perfusion images, with a 15‐minute scan (3 × 5 minute frames) starting 30 to 50 minutes after injection to image amyloid distribution. Images were reconstructed using iterative reconstruction , with a 168 × 168 matrix size, 2.04 × 2.04mm pixel size, 3‐mm slice thickness, and 3‐mm postreconstruction Gaussian filter. Attenuation correction was performed using CT scan data.Imaging was performed using a Siemens Biograph‐40 PET‐CT scanner  in list mode. Participants were given a 370 MBq intravenous injection of CT scans were obtained immediately before the PET images. CT dose was minimized using the Siemens CARE Dose 4D protocol with 50 mAsec target dose, 0.5‐second gantry rotation time, 0.8‐mm beam pitch, 0.6‐mm slice thickness, and a scan duration of 19 seconds. Images were reconstructed with 3‐mm slice thickness to match the PET images. For participants without magnetic resonance imaging (MRI), CT scans were also reconstructed with a 1‐mm slice thickness for use as a background scan for visual rating.MRI scans were performed on all patients unless contraindicated because of metal implants (n = 7). Scans were acquired on a 3T whole‐body MR scanner , with body coil transmission and 8‐channel head coil receiver. Images acquired included a 3‐dimentional sagittal magnetization‐prepared rapid gradient echo sequence . The sagittal acquisition matrix was 216 × 240, giving a voxel size of 1 × 1 × 1 mm.http://www.fil.ion.ucl.ac.uk/spm/software/spm8/). A mean amyloid PET image was obtained by coregistering the 3 5‐minute scans undertaken 30 to 50 minutes postinjection. This mean scan was then coregistered with the native‐space MRI. MRI images were segmented into white matter, gray matter, and CSF. Gray and white matter images were smoothed using a 4‐mm, full‐width, half‐maximum Gaussian kernel to match the PET resolution. Region of interest maps were developed to mirror those used in the AD Neuroimaging Initiativehttp://www.marsbar.sourceforge.net) region map (Supplementary Table 1).All analyses of MRI and PET images were performed using SPM 8  and fluorodeoxyglucose (FDG) PET, we found that regions of interest in the parietal lobe (angular gyrus), medial occipital cortex, and medial temporal lobe had good specificity and sensitivity for distinguishing between dementia groups.Amyloid PET images were reviewed by 5 raters , all of whom had completed certified training in amyloid image reading. Raters were blinded to all clinical data. Scans were classified as positive or negative based on the method developed by the manufacturer.http://www-03.ibm.com/software/products/en/spss-statistics; IBM, New York). Normality was tested using the Shapiro‐Wilk test. Comparisons between diagnostic groups were carried out using one‐way analysis of variance or Kruskall‐Wallis tests with post hoc pairwise comparisons where significant (Bonferroni test α = .05). χ2 or Fisher's exact tests were used for categorical variables. Comparisons between amyloid‐positive and amyloid‐negative DLB cases were carried out using the general linear model and logistic regression; linear regression was used to investigate associations with mean cortical SUVR. Age and years in education were included as covariates for cognitive variables; age, sex, and years in education were included as covariates for imaging variables.Statistical analysis was completed using SPSS Statistics software  were initially identified, followed by a cluster‐based family‐wise error correction (α = .05).Voxel‐wise analyses were performed on the smoothed normalized images using the general linear model in SPM, with covariates of participant age and sex and (for MRI) total intracranial volume. Significant voxels  between the groups with 80% power.A total of 87 volunteers agreed to enter the study, of which 77 met the eligibility criteria and completed their assessment. Supplementary Table 2 summarizes the group characteristics. The groups were well matched for age and sex, and the dementia groups were well matched for level of cognitive impairment.P = .01).DLB cases performed more poorly than controls on all cognitive tests (Supplementary Tables 2 and 3). The only difference between DLB and AD on cognitive testing was the digit vigilance task, with DLB cases displaying worse attention (digit vigilance number correct P = .01), but significantly lower than AD .The proportion of DLB cases with a positive‐amyloid PET scan on visual rating was 20/37 (54%). This was significantly higher than controls . Amyloid deposition was significantly higher in AD than controls in every cortical region, but there were no significant differences between AD and DLB cases in any region.Mean cortical amyloid deposition in DLB was intermediate between AD and controls, although it was not significantly different from either group Table . DLB casP = .052).SPM analysis of amyloid PET images found widespread amyloid deposition in AD when compared with controls, particularly in the frontal, temporal, and parietal areas . Deposition in DLB was less marked, but followed a similar distribution . There were few areas of higher deposition in AD when compared with DLB , none of which survived family‐wise error correction for significant clusters, although an occipital cluster approached significance (P = .04), greater medial temporal lobe perfusion (P < .001), and a lower occipital:medial temporal lobe perfusion ratio . DLB patients had less left medial temporal lobe atrophy, higher medial temporal and orbitofrontal perfusion, and lower perfusion in a part of the occipital cortex when compared with the AD patients .P = .05; Table The amyloid‐positive and amyloid‐negative DLB groups were similar in age, although the amyloid‐positive group approached having significantly more years in education There were no differences between the amyloid‐positive and amyloid‐negative DLB groups in hippocampal volume or total gray matter volume  apart from an association with increased cortical SUVR and lower simple reaction time  and lower simple reaction time coefficient of variation . There was no significant correlation between mean cortical SUVR and Neuropsychiatric Inventory hallucinations, Clinician Assessment of Fluctuations, Dementia Cognitive Fluctuations Scale, or UPDRS total, gait, rigidity, rest tremor, or postural stability scores.When entered into linear regression with age and years in education, there was no correlation between mean cortical SUVR and any symptom scale or cognitive test  and a higher occipital:medial temporal lobe ratio .When entered into linear regression with age, sex, and years in education as independent variables, increased amyloid deposition was associated with lower medial temporal lobe perfusion . There were no significant associations between striatal SUVR and any other cognitive test or measure of functional impairment.Striatal amyloid deposition has been linked to the severity of cognitive impairment in postmortem studies.P = .07, family‐wise error cluster‐wise corrected; Fig. Analysis of voxel‐based correlation between mean cortical amyloid deposition and gray matter density found no statistically significant clusters. However, there was an almost significant cluster of negative correlation between amyloid deposition and perfusion in the right hippocampus (P = .22) to identify amyloid‐positive cases. A model of age and occipital:medial temporal lobe perfusion gave a lower sensitivity (50%) but the same specificity (Wilk's lambda P = .18). A more complex model including age, medial temporal lobe perfusion, hippocampal volume, years in education, simple reaction time, and simple reaction time coefficient of variation yielded a sensitivity of 73% and a specificity of 64% (Wilk's lambda P = .07).A post hoc discriminant analysis was carried out to test whether amyloid‐positive DLB cases could be identified without amyloid imaging. A simple model of age and medial temporal lobe perfusion yielded a sensitivity of 60% and specificity of 65%  Research project: A. Conception, B. Organization, C. Execution; 2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; 3) Manuscript: A. Writing of the first draft, B. Review and Critique.P.C.D.: 1B, 1C, 2A, 2B, 3AM.F.: 1A, 1B, 1C, 2A, 2B, 2C, 3BA.J.T.: 1A, 1B, 2C, 3BJ.L.: 1B, 2C, 3BG.P.: 1B, 2C, 3BN.B.: 1B, 1C, 3BK.O.: 1B, 1C, 3BJ.T.O.: 1A, 1B, 1C, 2A, 2C, 3BP.C.D. received funding from Lilly to attend a “Support for Physicians Involved in Research who are In Training” meeting. A.J.T. received support from GE Healthcare, the manufacturer of FP CIT (DaTSCAN), for investigator‐led research. G.P. received honoraria from GE Healthcare for delivering talks/training. J.T.O. has acted as a consultant for Lilly, has received research grant support from Avid/Lilly, and is supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre. M.F., J.L., N.B., and K.O. report no disclosures.Additional Supporting Information may be found in the online version of this article at the publisher's website.Supplementary Table 1. Cortical regions of interest and corresponding MarsBar regionsClick here for additional data file.Supplementary Table 2. Baseline demographic and cognitive test scores in DLB, AD and control groupsClick here for additional data file.Supplementary Table 3. Computerised test scores in DLB, AD and control groupsClick here for additional data file.Supplementary Table 4. Computerised test scores in amyloid positive and negative DLBClick here for additional data file.18F‐Florbetapir binding in Alzheimer's disease (AD), Dementia with Lewy bodies (DLB) and control cases.Supplementary Figure 1. Voxel‐based analysis of  There are widespread areas of significant cortical deposition in AD compared with controls (A), with less widespread significant deposition in DLB, despite the greater number of subjects in this group (B). AD cases approached having significantly greater deposition than DLB in the occipital cluster illustrated (p=0.052).AD = Alzheimer's disease; DLB = dementia with Lewy bodies. Voxelwise comparisons uncorrected at p=0.001 with Family‐Wise Error corrected clusters (α=0.05) except where stated.Click here for additional data file.Supplementary Figure 2. Voxel‐wise comparisons of control subjects with dementia with Lewy bodies and Alzheimer's disease. Compared with control cases, dementia with Lewy bodies displayed temporoparietal atrophy and posterior hypoperfusion. Alzheimer's disease cases displayed more widespread atrophy and temporoparietal hypoperfusion. Voxelwise comparisons uncorrected at p=0.001 with Family‐Wise Error corrected significant clusters (α=0.05).Click here for additional data file.Supplementary Figure 3. Voxel‐wise comparisons between dementia with Lewy bodies and Alzheimer's disease. When compared with Alzheimer's disease, dementia with Lewy bodies subjects had less left medial temporal lobe atrophy, higher medial temporal and orbitofrontal perfusion and a small area of lower perfusion in the occipital cortex. Voxelwise comparisons uncorrected at p=0.001 with Family‐Wise Error corrected significant clusters (α=0.05). Colour represents t statistic. Cross‐hairs are at MNI co‐ordinates .Click here for additional data file.


Our ability to generate mental representation of magnitude from sensory information affects how we perceive and experience the world. Reduced resolution of the mental representations formed from sensory inputs may generate impairment in the proximal and distal information processes that utilize these representations. Impairment of spatial and temporal information processing likely underpins the non-verbal cognitive impairments observed in 22q11.2 deletion syndrome (22q11DS). The present study builds on prior research by seeking to quantify the resolution of spatial and temporal representation in children with 22q11DS, sex chromosome aneuploidy (SCA), and a typically developing (TD) control group.Children  responded to visual or auditory stimuli with varying difference ratios. The participant’s task was to identify which of two sequentially presented stimuli was of larger magnitude in terms of, size, duration, or auditory frequency. Detection threshold was calculated as the minimum difference ratio between the “standard” and the “target” stimuli required to achieve 75% accuracy in detecting that the two stimuli were different.spatial stimuli for accurate identification compared with both the SCA and TD groups . Temporal detection threshold was also higher for the 22q11DS group to both visual  and auditory  stimuli compared with both the SCA and TD groups, while the SCA and TD groups displayed equivalent performance on these measures (p's > 0.05). Pitch detection threshold did not differ among the groups (p's > 0.05).Children with 22q11DS required larger magnitude difference between The observation of higher detection thresholds to spatial and temporal stimuli indicates further evidence for reduced resolution in both spatial and temporal magnitude representation in 22q11DS, that does not extend to frequency magnitude representation (pitch detection), and which is not explained by generalized cognitive impairment alone. These findings generate further support for the hypothesis that spatiotemporal hypergranularity of mental representations contributes to the non-verbal cognitive impairment seen in 22q11DS. Individuals with one of a range of genetic neurodevelopmental disorders, including chromosome 22q11.2 deletion syndrome (22q11DS), Turner syndrome , Fragile22q11DS is a genetic neurodevelopmental disorder caused by a de novo deletion on the long arm of chromosome 22, and it has an estimated prevalence of 1:2000–4000 live births , 15. TheTo estimate and compare quantities of time, space, and number, perceptual and attentional systems need to interact in order to generate mental representations. These, in combination with the acquisition of numerical conceptual knowledge , provide a means of quantification by which values are assigned that convert continuous magnitudes into categorical units. Resolution of mental representations reflects the “minimum spacing at which attention can select individual items” . Put simWhen attention resources fail to adequately individuate items, this produces a phenomenon referred to as “crowding.” Likened to the resolution of a digital image, Simon  introducIn 22q11DS, evidence of spatial and temporal processing impairments are reflected in difficulties compared with their typically developing peers in goal-directed spatial selective attention , 29, ideIn the present study, we sought to identify impairments in spatial and temporal processing in a sample of children with 22q11DS as well as to quantify the degree of this impairment  relative to a group of typically developing (TD) control participants. We used an adaptive algorithm during the task to allow us to determine the minimum ratio that was required for each participant to discriminate between two magnitudes with an accuracy of 75% or greater. This minimum ratio of magnitude discrimination performance is considered a—necessarily—indirect measure of the resolution of the mental representations  generated in order to make a response selection.To examine whether the predicted impairments are the consequence of lower resolution  spatiotemporal representations in 22q11DS or whether they are a consequence of general cognitive impairment, we recruited children with sex chromosome aneuploidies (SCA) as a second comparison group. SCA results from an abnormal number of X- or Y-chromosomes and includes the polysomy conditions 47,XXY (Klinefelter) syndrome in males and 47,XXX (Trisomy/Triple X) in females. Individuals diagnosed with a Klinefelter or Trisomy X syndromes tend to display average to low average full-scale IQ with difficulties concentrated in the verbal domain with non-verbal IQ typically reported in the normal range –36. The We administered several simplified psychophysics experiments to quantify the difference in spatiotemporal resolution of children with 22q11DS compared with SCA and TD control groups. We expected that, despite lower IQ in both neurodevelopmental disorder groups, spatial and temporal detection thresholds would differ between the 22q11DS and TD or SCA groups, but not between the TD and SCA groups. Furthermore, we examined whether lower  resolution in 22q11DS is specific to spatiotemporal representation or whether it manifests in other domains of representation. If the spatiotemporal hypergranularity hypothesis holds, we would expect that because pitch characteristics of sounds are less reliant on spatial and temporal properties, differences between the groups in terms of the resolution of mental representations would be specific to spatial and temporal, but not pitch minimum magnitude detection thresholds. Furthermore, other populations with spatial and temporal impairments resulting from brain injury  do not n = 30 female, mean age = 11.3 years, SD ± 2.4, mean IQ = 73.3, SD ± 13.4), 46 children with SCA  and 49 TD children . No significant difference in mean age  = 1.2, p = 0.3) or gender distribution (χ2 (2) = 1.1, p = 0.6) was present between the groups; however, statistically significant differences between all groups were present for IQ  = 114, p < 0.001; 22q11DS < SCA < TD: p's < 0.001) (see Table Participants were 70 children with 22q11DS (n = 6), attention deficit hyperactivity disorder (ADHD) (n = 20), generalized anxiety disorder (n = 10), obsessive-compulsive disorder (n = 4), mood disorder (n = 5), sensory processing disorder (n = 1). Sixteen individuals were currently on some form of psychiatric medication: antipsychotics: (n = 6), methylphenidate or other stimulants (n = 14), SSRIs (n = 3).Children diagnosed with 22q11DS and TD participants were recruited through the UC Davis MIND Institute, postings on online discussion groups, foundation newsletters, and by word of mouth. SCA participants were recruited through the “eXtraordinarY kids clinic” at Children’s Hospital Colorado (by author NT). Deletion of chromosome 22q11.2 was confirmed using fluorescence in situ hybridisation (FISH) or similar test, and positive 47,XXY or 47,XXX status was confirmed via review of genetic testing results. For the 22q11DS group, parents reported their child’s psychiatric diagnostic status at the time of testing. Twenty-six individuals with 22q11DS were identified as having psychiatric diagnoses including: autism spectrum disorder (ASD) , a history of head injury and moderate/severe intellectual impairment (WISC IQ < 50).Exclusion criteria for children with 22q11DS included the presence of the clinical phenotype of 22q11DS n = 3, SCA: n = 5, TD: n = 28) or the Wechsler Intelligence Scale for Children  was used to assess intellectual functioning and to calculate verbal, performance, and full-scale IQ. Several participants were missing IQ data .The Wechsler Abbreviated Scale of Intelligence (WASI ) (22q: n(WISC-IV ) . If a child could maintain 75% accuracy when the target was 85% the size of the standard (or 192 pixels in length), but not when the target was larger, that child’s minimum magnitude detection threshold (herein referred to as “detection threshold”) would be 15%. In all tasks, participants were seated 60 cm (screen resolution 1024 × 768) from the computer screen and completed demonstration and practice items before commencing each of the tasks.Participants compared two sequentially presented stimuli  and were asked to indicate which one was longer. One bar  remained constant in length, while the other  varied in length according to a parameter estimation algorithm  that usAdapted from Debbané et al. , particiThe temporal duration judgment-auditory (TDJ-A) task was similar to temporal duration judgment-visual (TDJ-V) task; however, in this task, visual and auditory cues were presented together, though visual stimuli were presented before auditory stimuli to ensure that participants were attending to the task prior to the onset of auditory stimuli. Participants were asked to determine which of two sounds was longer. Two 1000-Hz tones with volume set at 50 dB were presented sequentially. A fixation point was presented center of screen for 1000 ms and ISI was set to 1000 ms. The standard stimulus duration was 400 ms, while the target stimulus duration was adjusted based on PEST (range 401–912 ms). Standard and target stimuli were presented in a randomized order for a total 36 trials .The structure of the adaptive pitch comparison (APC) task was similar to the adaptive magnitude comparison (AMC) task; however, pitch stimuli accompanied the two visual stimuli. Participants were asked to identify which of two sequentially presented sounds was higher pitched. Two sequentially presented visual stimuli were delivered for 2000 ms each with pitch stimuli then accompanying the image for an additional 1500 ms with ISI set to 1500 ms. Visual stimuli were presented before pitch stimuli to ensure participants were attending to the task prior to the onset of pitch stimuli . The standard pitch remained constant (1800 Hz). Target stimuli began at 1000 Hz (range 1000–1787 Hz) with a total 24 trials .https://www.r-project.org). Between-group differences in age and IQ were assessed using analysis of variance followed by post-hoc pairwise comparisons adjusted for multiple comparisons using FDR, while differences in gender were assessed using a chi-squared (χ2) test. On all tasks, individuals that did not reach ≥ 50% accuracy in discriminating magnitudes with the largest difference (referred to throughout as Block 1) were excluded from primary analysis because this level of accuracy was below chance and indicated that they were unable to perform the task. Chi-square tests or Fisher’s exact tests were used to explore between groups differences in participant’s ability to perform the first block above chance. The primary outcome measure was the participant’s level of ability to accurately detect difference between stimuli (detection threshold). Kolmogorov-Smirnov values and visual inspection of data distribution indicated that the AMC and APC were non-normally distributed. Cubic and squared transformations of AMC and APC data respectively were performed and linear regression analysis was conducted on all tasks. Age , gender, and group were included in the models, unless otherwise noted. The authors concur with Dennis and colleagues [Statistical analysis was carried out in R ; SCA: n = 3/46 (7%)). These participants (n = 13) were omitted from the primary analysis. Age and gender did not contribute to the linear regression (cube transform) model and were removed. The final model indicated that children with 22q11DS displayed a significantly higher detection thresholds for spatial magnitude (pixels) than children in the TD and SCA groups (detection threshold (%): 22q11DS = 14; SCA = 8; TD = 7; F  = 8.42, p < 0.001). Pairwise comparisons showed threshold detection differences between the 22q11DS and TD groups (t = − 3.8(92.5), p < 0.001, d = 0.74) and 22q11DS and SCA groups (t = − 2.88(99.6), p = 0.015, d = 0.58) but not the SCA and TD groups (p = 0.52). Mean group detection thresholds are displayed in Table Block 1 accuracy between the groups indicated significantly more below chance responses from children with 22q11DS compared with children with SCA and the TD group ; SCA: n = 3/26 (10%); TD: n = 1/31 (3%)). These were identified and omitted from primary analysis (n = 22). Data were normally distributed and since age and gender did not contribute to the regression model they were removed (ps > 0.05). The final model showed that children with 22q11DS had a higher detection threshold when comparing visual duration (ms) than the SCA and TD groups (detection threshold (%): 22q11DS = 31; SCA = 22; TD = 17; F  = 8.33, p < 0.001). Pairwise comparisons showed differences between 22q11DS and TD groups (t = − 4.04(48.9), p < 0.001, d = 0.87) and 22q11DS and SCA groups (t = − 2.31(35.9), p < 0.04, d = 0.53) but not the SCA and TD groups (p = 0.14) , SCA = 2/29 (7%)). These participants were excluded from primary analysis (n = 16). Data were normally distributed. Overall, the group but not age or gender significantly contributed to the regression model and children with 22q11DS showed higher auditory duration (ms) detection thresholds compared with children in the TD and SCA groups (detection threshold (%): 22q11DS = 23; SCA = 12; TD = 8; F  =8.99, p < 0.001). Pairwise comparisons indicated detection threshold differences between children with 22q11DS and TD (t = − 4.057(65.9), p < 0.0001, d = 0.89); and children in the 22q11DS and SCA groups (t = − 2.53(63.65), p = 0.03, d = 0.61), but not SCA and TD groups (t = − 1.058(49.7), p = 0.29, d = 0.28)  = 1.59, p = 0.45; 22q11DS: n = 11/70 (16%); SCA: 4/46 (9%); TD: 4/48 (8%)). These participants (n = 19) were omitted from the primary analysis. Linear regression (square transform) indicated that neither age, gender, nor group membership influenced pitch (Hz) detection threshold (detection threshold (%): 22q11DS = 21; SCA = 18; TD = 20, ps > 0.05) . Age and gender did not contribute to any of the regression models and were removed.t = 2.3, p = 0.02; t = 2.2, p = 0.03) and IQ  contributed significantly to the model showing that children with 22q11DS and SCA displayed significantly higher detection thresholds for spatial magnitude (pixels) than children in the TD group  = 4.95, p < 0.001). IQ was also significant for all groups, i.e., detection threshold decreased with increasing IQ scores . Finally, interaction effects indicate that this increase in performance with higher IQ was less profound in both the groups with 22q11DS and SCA compared with the TD group .Group (22q11DS: p's > 0.05)  = 4.9, p < 0.001; TDJ-V: F  = 3.6, p = 0.006).When IQ was added as a predictor to both the TDJ-A and TDJ-V models, none of the individual predictors contributed significantly to the model  and IQ  contributed significantly to the regression model  = 3.4, p = 0.006). Children with SCA, but not those with 22q11DS, showed significantly lower pitch detection thresholds compared with children in the TD group.Group  and measures of spatial, temporal and frequency detection were completed. These show different patterns of association among the groups   was significantly positively correlated with all measures of IQ , while frequency detection (APC) was associated with FSIQ and PIQ, but not VIQ. No association was observed between IQ and temporal representation measures .We sought to quantify the resolution of spatiotemporal representation and to compare performance among two groups of children with neurodevelopment disorders (22q11DS and SCA) and TD controls. Using tasks designed to examine spatial and temporal magnitude estimation, we replicated and extended previous findings reported by Debbané  and SimoIt is important to note that compared with age- and gender-matched TD peers and those with SCA, more children with 22q11DS  than those with SCA or TD children (0–10%) were unable to perform each task. That is, they were unable to perform above chance when the magnitude difference between stimuli was largest. These children may represent a sub-group of children within the larger 22q11DS sample who present with severe impairment in magnitude comparison. However, it is important to note that when examined on a case-by-case basis, the severe impairment sub-group was not comprised of the same participants across the different spatial, temporal, and pitch comparison tasks.A significant difference in detection threshold between the TD group and children with 22q11DS and between the SCA group and children with 22q11DS clearly showed that children with 22q11DS needed the differences between the spatial and temporal extent of the standard and target bars to be significantly larger than was required for the children in the TD and SCA groups in order to be able to perform at the same level of accuracy . Since our psychophysics-like tasks held performance constant and adjusted detection thresholds, our results allow us to produce the first estimates of the “degree of hypergranularity,” or severity of impairment causing reduction in resolution of spatial and temporal representations that is experienced by our sample of children with 22q11DS. As expected, the SCA group displayed comparable performance to the TD group on tasks of spatial, temporal, and pitch detection. On the spatial resolution task, given the smallest standard/target difference for TD children was 7% and the smallest ratio for children with SCAs was 8%, the 14% ratio for our 22q11DS group suggests that their mental resolutions for spatial extent were 6–7% less complete than was true for the other groups.Overall, all groups demonstrated poorer temporal magnitude detection threshold compared with the spatial magnitude threshold. On the temporal detection tasks, participants reported higher detection thresholds and more participants were excluded for failing to respond above chance. Given the smallest standard/target ratio for TD children on the temporal duration judgment was between 8% (auditory) and 17% , and the smallest ratio for children with SCAs was between 12% (auditory) and 22% , a standard/target ratio between 23% (auditory) and 31%  for our 22q11DS group suggests that their mental resolutions for spatial extent were between 9 and 15% less complete than was true for the other groups. Further, it is important to note that the 22q11DS group performed comparably with both SCA and TD groups on the pitch detection task .Though methodological differences prevent direct comparison between studies, our findings are consistent with those reported by Debbané et al.  on measuOur findings indicate that processes related to forming frequency-based mental representation and detecting difference between auditory pitches is equivalent in 22q11DS to children with SCA and TD peers. These findings show that properties of the representation of spatial and temporal stimuli that are not found in pitch stimuli are specifically impaired in 22q11DS, and that performance on these tasks is not the secondary consequence of task design. Further, we interpret these findings to indicate that children with 22q11DS present with specific impairment in spatiotemporal magnitude estimation that does not extend to pitch detection.As mentioned previously, the broad cognitive phenotype of 22q11DS is characterized by impairment in the non-verbal domain , 37, 38.A methodological strength of the present study is the addition of the pitch detection paradigm (APC) with identical PEST algorithm and design to the spatial magnitude comparison task (AMC). Thus, if task performance was the consequence of general working memory and/or attention impairment, we could reasonably expect similar patterns of performance across tasks. However, as stated above, when compared with age- and gender-matched children with a different NDD (SCA) or the TD group, children with 22q11DS demonstrated comparable ability to generate mental representations of frequency estimation to discriminate between tones. Thus, the cognitive impairment associated with 22q11DS does not impede the ability to represent and compare frequency information.The profile of performance reported here by children with 22q11DS is consistent with what would be expected from a developmental impairment in spatiotemporal mental representation and relatively intact mental representation of pitch. This hypothesis was tested with the spatial magnitude comparison task, temporal duration tasks , and a pitch comparison task. This study advanced the hypothesis of specific spatiotemporal hypergranularity in 22q11DS, first by demonstrating evidence of reduced resolution of spatial and temporal mental representations on a series of simple psychophysics comparison tasks, and secondly by demonstrating uneven magnitude estimation performance across sensory domains, demonstrating relatively intact pitch perception abilities compared with children with SCA and TD controls. Thus, impairment was specific to spatiotemporal task demands and was not accounted for by more general attentional or working memory aspects of the task design.n = 14/53), visual: 22q11DS: 34% (n = 18/53)). While worth noting, this outcome may not necessarily represent a methodological weakness. Results showed, across all groups, the same pattern of poorer performance on the TDJ-A/V tasks. Therefore, while children with 22q11DS demonstrated impaired performance, the threshold of > 50% accuracy for inclusion in the primary analysis indicated that participants included in analysis understood the requirements of the task. Furthermore, it does not appear that task difficulty explains the TDJ-A/V exclusion rates in the 22q11DS group. We report that only one TD participant failed to meet block 1 accuracy thresholds for these tasks compared with n = 4 (8%) of TD participants who failed to meet block 1 threshold on the APC task.Before we address the potential contribution of intellectual impairment on task performance, there are several limitations associated with the current study. These relate primarily to task characteristics as well as the measurement of IQ. It should be noted that the number of trials in each task was relatively small compared with typical psychophysiology studies. While this was an intentional methodological decision to minimize participant fatigue, replication with additional trials is recommended. However, similarities between our findings and previous studies utilizing similar paradigms  coupledThe primary limitation of this study relates to several aspects to do with the measurement and treatment of IQ. Participants completed either the 4-subscale WASI-2 or the more comprehensive WISC-IV assessment. Although the comparability of these measures is acceptable, with correlation coefficients of 0.82 (PRI), 0.85 (VCI), and 0.91 (FSIQ) respectively, this may have resulted in slightly higher WASI scores compared with their WISC-IV equivalent. Another limitation to the study relates to IQ and the NDD groups. In addition to characterizing spatial and temporal representation abilities in a group of children with SCA, the inclusion of an SCA group was intended to address several methodological matters common to neurodevelopmental disorders research. Matching samples on IQ runs the risk that IQ-matched group heterogeneity will impede meaningful comparisons, while controlling for features (such as IQ) that are highly correlated with group membership creates similar impediments to interpreting findings. Thus, in the present study, we recruited participants from a cohort with a defined chromosomal duplication with mild intellectual impairment and a cognitive profile “opposite” to 22q11DS. Though statistically different from both the 22q11DS and TD groups—the SCA group had a mean FSIQ within the average range. Thus, our NDD contrast group was not FSIQ matched to our 22q11DS group and did not present with mild intellectual impairment at the group level. Furthermore, our 22q11DS group did not display relative strengths in VIQ and members of our TD control group had FSIQ well above average. Together, these factors limited our interpretation of the data in relation to the effect of IQ on task performance.For these reasons, we chose to run analysis with and without IQ included as a predictor in the regression model, and performed correlational analysis to examine the patterns of association of general functional ability (IQ) and our experimental measures. It is our contention that IQ is a group-defining characteristic of 22q11DS. Moreover, we consider IQ largely unsuited as a covariate in neurocognitive studies of individuals with NDDs . It is difficult to explain why PIQ would be associated with the auditory measure of temporal representation but not the visual. Participants with 22q11DS reported poorest and least variable performance on TDJ-V; however, though it was not associated with PIQ, better performance was significantly positively correlated with FSIQ and VIQ on this measure in the 22q11DS group only.Methodological strengths of the study relate to the inclusion of age- and gender-matched TD and SCA groups as well as the addition of the pitch detection task that allowed us to explore the specificity of spatiotemporal representation impairment in these groups. Finally, the application of PEST instead of reaction time measures, which are more typical to psychophysical and behavioral paradigms, allowed us to quantify each individual’s detection threshold. Reaction time is notably heterogeneous, often age-dependent, and not normally distributed in neurodevelopmental disorders. Thus, the PEST method allowed us to more directly measure the cognitive feature that we were most interested in  rather than an indirect manifestation of detection threshold .Clinical implications primarily relate to the potential for remediation of the cognitive processes underpinning spatiotemporal representation. Specifically, we will be interested to know whether targeted training can improve spatiotemporal resolution; whether improvements generalize to related cognitive skills; what is the optimal “dose” of cognitive training required to yield improved performance; and importantly, whether training can translate to improve functioning in everyday life.The elevated thresholds for spatial and temporal but not pitch representation indicate that neither working memory load nor general attention impairment adequately accounts for the pattern of performance by the 22q11DS group, and that these impairments relate specifically to the spatial and temporal characteristics of the stimuli. Furthermore, these difficulties were not observed in the SCA group, which suggests that spatiotemporal processing difficulties do not generalize to all neurodevelopmental disorders. Finally, we conclude that in the current study, spatiotemporal impairment is not a corollary of general working memory or attention impairment and is a promising opportunity for targeted remediation.


The enteroinsular axis (EIA) comprises intestinal factors (incretins) that stimulate insulin release after PO ingestion of nutrients. Glucose‐dependent insulinotropic polypeptide (GIP) and glucagon‐like peptide‐1 (GLP‐1) are the main incretins. The EIA has not been investigated in healthy neonatal foals but should be important because energy demands are high in healthy foals and dysregulation is frequent in sick foals.To evaluate the EIA response to carbohydrates or fasting in newborn foals. We hypothesized that incretin secretion would be higher after PO versus IV carbohydrate administration or fasting.Thirty‐six healthy Standardbred foals ≤4 days of age.Prospective study. Blood was collected before and after a PO glucose test , an IV glucose test , a PO lactose test , and fasting. Foals were muzzled for 240 minutes. Blood was collected over 210 minutes glucose, insulin, GIP, and GLP‐1 concentrations were measured.P < .05). All IV glucose doses induced hyperglycemia and hyperinsulinemia. Concentrations of GIP and GLP‐1 decreased until foals nursed (P < .05), at which time rapid increases in glucose, insulin, GIP, and GLP‐1 concentrations occurred (P < .05).Only PO lactose caused a significant increase in blood glucose concentration (Healthy newborn foals have a functional EIA that is more responsive to milk and lactose than glucose. Non‐carbohydrate factors in mare's milk may be important for EIA activity. Constant exposure of intestinal cells to nutrients to maintain EIA activity could be relevant to management of sick foals. Foals can be fasted for 4 hours without experiencing hypoglycemia. Glucose‐dependent insulinotropic polypeptide (GIP) and glucagon‐like peptide‐1 (GLP‐1) are the main incretins. Incretins are secreted by enteroendocrine cells  in response to the PO intake of nutrients . They bind to their respective cell membrane receptors in pancreatic β‐cells to enhance insulin secretion and facilitate glucose disposal.Insulin is considered a central hormone for energy regulation. It increases cellular glucose uptake, stimulates glycogenesis, promotes lipogenesis, and decreases lipolysis and proteolysis. Although blood glucose is a major stimulus for insulin release in the horse, GLP‐1 and GIP contribute to the overall insulin response in healthy and insulin‐dysregulated ponies and horses after ingestion of soluble carbohydrates.Problems of energy dysregulation are frequent in critically ill foals, with up to 70% of foals presenting to a neonatal intensive care unit having a blood glucose concentration outside of the reference range.Considering that energy disturbances and gastrointestinal disorders are common in critically ill foals, but information on intestinal factors that regulate pancreatic endocrine function is lacking, our goal was to investigate the response of the EIA  in healthy newborn foals exposed to both PO and IV glucose, PO lactose, and fasting. We hypothesized that incretin secretion in response to PO carbohydrates would be higher than the same dose of glucose administered IV or when compared to a similar period of fasting. We also hypothesized that this incretin response would be linked proportionately to insulin concentrations. Understanding the biology of the EIA in healthy foals could have clinical implications in the management of foals with energy dysregulation and gastrointestinal disease.22.1Thirty‐six Standardbred foals ≤4 days of age, owned by a private breeding farm, were included in this prospective, randomized study. Foals were considered healthy based on physical examination findings, normal CBC, and serum immunoglobulin G (IgG) concentration (>800 mg/dL). Testing took place over two 6‐week periods from March to April during the 2017 (n = 17) and 2018 (n = 19) foaling seasons. Each foal was randomly assigned to the dextrose, lactose, or fasted experimental group. Foals receiving dextrose (n = 24) were randomly assigned to PO or IV route of administration of a low, medium, or high dose in a crossover design, with the alternative route of administration occurring the next day. Foals in the lactose and fasted groups were only sampled on day 1. Care was taken to minimize stress on these foals. Foals remained confined to stalls with their mares between sampling times.At 60 minutes before initiation of the experimental period, foals were muzzled and an IV catheter  was placed in the jugular vein using local anesthesia. Foals were manually restrained, and no sedative medications were administered at any point. Foals were muzzled for 240 minutes (−60 to 180 minutes).This study was approved by the Ohio State University Institutional Animal Care and Use Committee and adhered to the principles of humane treatment of animals in veterinary clinical investigations as stated by the American College of Veterinary Internal Medicine and National Institute of Health guidelines.2.2Foals were given a 50% dextrose solution  at the preassigned dosages: 300 mg/kg , 500 mg/kg , or 1000 mg/kg . The dextrose was administered PO using a 60‐mL catheter‐tip syringe over a period of 1 minute. Care was taken to minimize spillage.2.3Foals were given a 50% dextrose solution  through an IV catheter at the preassigned dosages: 300 mg/kg , 500 mg/kg , or 1000 mg/kg . Administration occurred over a period of 1 minute and the IV catheter was irrigated with 20 mL heparinized saline after administration.2.4Foals given lactose  as a 20% solution in water at a dosage of 1000 mg/kg (n = 6) by nasogastric intubation over 1 minute.2.5A group of foals (n = 6) did not receive any sugar enterally or parenterally and remained muzzled and unable to nurse for the duration of the study (240 minutes).2.6Blood samples were collected at time 0 (before carbohydrate administration) and at 5, 10, 15, 30, 45, 60, 90, 120, 150, and 180 minutes. After 180 minutes, all foals were unmuzzled, allowed to nurse from the mare ad libitum, and additional blood samples in most (n = 22) foals were collected at 195 and 210 minutes.g for 10 minutes at 4°C. Within 6 hours of collection, plasma was aliquoted and stored at −80°C until analysis. Blood samples for CBC and IgG concentrations were processed within 4 hours of collection.Blood samples (4 mL) were placed in prechilled ethylenediaminetetraacetic acid (EDTA) tubes containing aprotinin  and diprotin A . Aprotinin (500 kU/mL of blood) was added to inhibit protease‐mediated degradation of peptide hormones and diprotin A (50 μmol/mL of blood) is a dipeptidyl peptidase‐4 (DPP‐4) protease inhibitor added to decrease degradation of GIP and GLP‐1. The EDTA‐aprotinin‐DPP‐4 inhibitor tubes immediately were placed on ice for at least 20 minutes. Tubes were centrifuged at 10002.7Blood glucose concentrations were measured immediately after collection using a portable glucometer  previously validated for horses.2.8P < .05.Data sets were tested for normality using the Shapiro‐Wilk normality test and were not normally distributed. Therefore, median and interquartile ranges were calculated. Comparisons among groups were carried out with the Kruskal‐Wallis statistic, and Dunn's post hoc test was used to compare each time point individually within the group. Comparisons over time were performed using the Friedman test. Peak concentrations were measured for each foal (Cmax) and areas under the curve (AUCs) for glucose (glucose‐AUC), insulin (insulin‐AUC), GIP (GIP‐AUC), and GLP‐1 (GLP‐1‐AUC) were calculated using the nonoverlapping trapezoid method. Results are presented as values relative to time 0 and absolute values. Statistical analysis was performed using commercial statistical software . Statistical significance was set at 33.1Thirty‐six Standardbred foals ≤4 days of age were used. The median age of foals at the time of study participation was 24 hours . Fourteen foals <24 hours of age were included in the study. Three each were used in the 500 mg/kg, 1000 mg/kg and lactose study groups, whereas only 1 foal <24 hours of age was included in the 300 mg/kg group and 4 foals were included in the fasted group. The median IgG concentration was 1700 mg/dL . Twenty‐three of 36 foals (64%) were fillies and 13/36 (36%) were colts.3.2P < .01). Foals in the IVGT‐300, IVGT‐500, and IVGT‐1000 groups had significant increases in blood glucose concentrations at 5‐15 minutes compared to time 0 . Foals in the OLT group had a significant increase in blood glucose concentration at 30 minutes compared to time 0 . Fasted foals had a significant decrease in blood glucose concentration from 60 to 180 minutes (P < .05). However, glucose concentrations remained within the reference range, foals were active, and no foal showed signs of hypoglycemia. After foals were allowed to nurse, a significant increase in glucose concentration was evident within 15 minutes .Median baseline blood glucose concentration for all foals was 140 mg/dL . Compared to baseline results, blood glucose concentrations in fasted foals decreased by 16% at 180 minutes (P < .05).When changes in blood glucose concentrations were adjusted to baseline results, the maximum concentration (which was observed at variable time points) increased by 1.8, 22.5, 36.8, and 41.9% over baseline for the OGT‐300, OGT‐500, OGT‐1000, and OLT groups, respectively . The IV administration of dextrose produced significant increases in insulin concentrations between 5 and 15 minutes compared to time 0 (P < .05).Baseline plasma insulin concentration for all foals was 10.7 μIU/mL . For the IVGT‐300, IVT‐500, and IVGT‐1000 groups, insulin concentrations increased by 802, 309.9, and 4238%, respectively . Compared to baseline results, insulin concentrations in fasted foals decreased by 72.5% at 180 minutes.As a relative percentage change from baseline, insulin concentrations increased by 10.7, 33.4, 110.6, and 220.3% for the OGT‐300, OGT‐500, OGT‐1000, and OLT groups, respectively . In the IVGT‐300, IVGT‐500, and IVGT‐1000 groups, GIP concentrations decreased earlier and longer .Baseline GIP concentration for all foals was 238.2 pg/mL . For the IVGT‐300, IVGT‐500, and IVGT‐1000 groups, GIP concentrations decreased by 74.3, 74.6, and 59.4%, respectively , at 180 minutes. Compared to baseline, GIP concentrations in fasted foals decreased by 75.5% at 180 minutes.As a relative percentage change from baseline, GIP concentrations decreased by 67.83, 73.4, 53.4, and 68% for the OGT‐300, OGT‐500, OGT‐1000, and OLT groups, respectively, at 180 minutes . Plasma GLP‐1 concentrations showed a statistically significant decrease in the OGT‐300 (120 minutes) and OGT‐500 (180 minutes) groups (P < .05). Plasma GLP‐1 concentrations also decreased in the IVGT‐300 and IVGT‐500 groups from 30 to 180 minutes . Foals in the OLT group had significantly lower GLP‐1 concentrations from 120 to 180 minutes . For the IVGT‐300, IVT‐500, and IVGT‐1000 groups, GLP‐1 concentrations decreased by 31.6, 22.3, and 16.6%, respectively , at 180 minutes. Compared to baseline, GLP‐1 concentrations in fasted foals decreased by 14.6% at 180 minutes. Figure As a relative percentage change from baseline, GLP‐1 concentrations decreased by 12.4, 46.38, 7.8, and 34.8% for the OGT‐300, OGT‐500, OGT‐1000, and OLT groups, respectively, at 180 minutes . Insulin‐AUC was not different among groups, except for the OLT group, which had a higher AUC compared to the fasted group (P < .05). For GIP, the AUC was not different between treated and fasted foals, but, when comparing equivalent PO and IV doses, the AUC for PO glucose was larger (P < .05). No significant difference for GIP‐AUC was found between fasted foals and the other study groups.The glucose‐AUC and GIP‐AUC were statistically different among study groups Table . Foals i3.7P < .05). These increases were larger than those seen after PO oral dextrose or lactose administration. The increase in GIP concentrations was more evident than for GLP‐1 concentrations.Access to free choice nursing resulted in a rapid and significant increase in blood glucose (34.6% at 195 minutes and 76% at 210 minutes), insulin (551% at 195 minutes and 637% at 210 minutes), GIP (137% at 195 minutes and 268% at 210 minutes), and GLP‐1 (21% at 195 minutes and 39.8% at 210 minutes) concentrations compared to 180 minutes  than for GLP‐1 (approximately 40%). Potential explanations for this increase could be that GLP‐1 is degraded faster by DPP‐4, that GIP is stimulated differently by various dietary components as compared to GLP‐1 as previously demonstrated in humans, rats, and swineIncretin and insulin dynamic changes may be different in older foals and may represent transition from in utero to extrauterine life. Maturation of the energy endocrine axis in foals continues in the postpartum period. Foals are inherently insulin resistant in the first days after birth and this finding has been attributed to activation of the hypothalamic‐pituitary‐adrenal axis and increased cortisol concentrations,Regarding clinical relevance, our research sheds light on the importance of constant exposure of intestinal cells to nutrients to maintain a functional EIA, because impaired incretin secretion can further complicate glucose regulation in critically ill foals. In addition, conditions that damage intestinal epithelial cells such as ischemia and infections  can indirectly disturb the endocrine pancreas and energy metabolism. Many foals admitted to equine hospitals with evidence of energy dysregulation may have a dysfunctional EIA that goes unnoticed because these factors are not measured clinically. In support of this hypothesis, we recently found that foals with severe sepsis tend to have lower insulin and GIP concentrations .Another point of interest regarding neonatal endocrinology is the >5‐fold increase in GLP‐1 and GIP concentrations in the foals of our study compared to results reported using the same assays for adult ponies and horses.Limitations of our study include the relatively small sample size considering variations in hormone concentrations in the first 48 hours after birth, different methods of PO carbohydrate administration, as well as the concentrations and volumes of PO solutions used (50% dextrose versus 20% lactose). Pancreatic β‐cell response to glucose is low immediately postpartum compared to foals 5‐7 days of age,In conclusion, we documented that healthy newborn foals have a functional EIA. Although activation of the EIA was minimal in response to PO glucose and lactose at doses up to 1000 mg/kg, rapid and significant increases in GIP and GLP‐1 concentrations were noted when foals were allowed to resume nursing ad libitum. Future research on the EIA in foals should focus on other substrates that may stimulate incretin release and their potential therapeutic implications.Authors declare no conflict of interest.Authors declare no off‐label use of antimicrobials.Approval from The Ohio State IACUC, number 2008A0170.Authors declare human ethics approval was not needed for this study.


Landmark power conversion efficiency (PCE) over 14% has been accomplished for single‐junction polymer solar cells (PSCs). However, the inevitable fracture of inorganic transporting layers and deficient interlayer adhesion are critical challenges to achieving the goal of flexible PSCs. Here, a bendable and thickness‐insensitive Al‐doped ZnO (AZO) modified by polydopamine (PDA) has emerged as a promising electron transporting layer (ETL) in PSCs. It has special ductility and adhesion to the active layer for improving the mechanical durability of the device. Nonfullerenes PSCs based on PBDB‐T‐2F:IT‐4F with AZO:1.5% PDA (80 nm) ETL yield the best PCE of 12.7%. More importantly, a prominent PCE, approaching 11.5%, is reached for the fully flexible device based on Ag‐mesh flexible electrode, and the device retains >91% of its initial PCE after bending for 1500 cycles. Such thickness insensitivity, mechanical durability, and interfacial adhesion properties for the inorganic ETLs are desired for the development of flexible and wearable PSCs with reliable photovoltaic performance and large‐area roll‐to‐roll printing manufacture. Polymer solar cells (PSCs), as an attractive alternative for the development of sustainable photovoltaic technology, have been investigated in depth as they can be fabricated by large‐area solution processing while maintaining the features of light weight, flexibility, tunable transparency, etc.In contrast to poly:poly(styrenesulfonate) (PEDOT:PSS) hole transporting layer (HTL) with hygroscopicity and acidity,2O3) precursor formulation solution and processing at 225 °C to achieve polycrystalline films.Unfortunately, the inherent brittleness and low adhesion of the inorganic AZO still limits its practical application in flexible and wearable PSCs. This is because the inevitable existence of AZO ETL cracking and AZO/active layer interfacial delamination upon blending can seriously deteriorate the charge transportation and extraction in PSCs. However, to our knowledge, there is no report regarding this important topic. Facchetti and co‐workers reported that the ultraflexible and transparent metal oxide transistors can be realized by doping insulating polymer polyvinylphenole (PVP) into indium oxide  into AZO. We find that PDA can effectively passivate surface defect sites of AZO through formation of strong intermolecular hydrogen‐bonding interactions. The PDA‐modified AZO exhibit high electron mobility under low temperature process and excellent mechanical properties in terms of flexural endurance and interfacial adhesion to the upper organic active layer. Nonfullerene PSCs based on PBDB‐T‐2F:IT‐4F with AZO:1.5% PDA (80 nm) ETL yield the best PCE of 12.7%. Furthermore, a prominent PCE, approaching 11.5%, has been accomplished for the fully flexible PSCs. To our best knowledge, this is the highest efficiency among reported flexible PSCs.Figure2− ions in Zn—O bonds and oxygen deficiency, respectively. As for PDA‐modified AZO, a distinct decline in the intensity of the second peak at 531.5 eV confirms that defects and traps of AZO have been effectively passivated by the PDA.3/2 for the PDA‐modified AZO shifting toward a higher binding energy again demonstrates the interaction between AZO and PDA through the N—Zn bond.In order to explore the effect of incorporating insulated PDA, transmittance and photoluminescence (PL) measurements have been conducted to investigate the optical properties of AZO and the PDA‐modified AZO. As shown in µe) of AZO and the PDA‐modified AZO ETLs in electron‐only devices has been estimated by using space‐charge‐limited‐current (SCLC) method on the basis of the Mott–Gurney equation,µe, based on AZO:1.5% PDA (4.2 × 10−3 cm2 V−1 s−1), compared to the corresponding AZO‐based devices (6.1 × 10−4 cm2 V−1 s−1). The same variation has also been observed from the conductivity values, as summarized in Table S2 in the Supporting Information, which is tentatively ascribed to defect passivation of the PDA‐modified AZO.To the best of our knowledge, most of the highly efficient PSCs are fabricated based on very thin ETLs (≈2–10 nm) due to its relatively low conductivity, which is highly problematic in high‐throughput processing methods. Accordingly, increasing attention has been paid recently to the development of new ETL materials with high charge mobility,71BM‐based inverted PSCs  with AZO and PDA‐modified AZO ETLs were investigated. The current density–voltage (J–V) curves and incident photon‐to‐current efficiency (IPCE) spectra are given in Figure S8 in the Supporting Information, while the detailed photovoltaic characteristics are listed in Table S3 in the Supporting Information. The PSCs based on PBDB‐T:ITIC with AZO:1.5% PDA (80 nm) yield higher PCE of 10.3%, with a short circuit current density (Jsc) of 17.68 mA cm−2, an open‐circuit voltage (Voc) of 0.886 V, and a fill factor (FF) of 65.3%. The integrated Jsc values from IPCE spectra are 16.01, 16.60, 16.93, and 16.31 mA cm−2 for the devices with the ETLs of AZO, AZO:1.0% PDA, AZO:1.5% PDA, and AZO:2.0% PDA, respectively, which are well in agreement with those obtained from J–V curves (≈4% mismatch). Then, the long‐term stabilities of the inverted PSCs based on PBDB‐T:ITIC and AZO or AZO:PDA ETLs were evaluated. The PCE degradation as a function of storage time in nitrogen‐filled glove box is shown in Figure S9 in the Supporting Information. The unencapsulated PSCs based on AZO:1.5% PDA ETL exhibit superior stability and maintain >85% of the original PCE value after storage for 30 d. Such pre‐eminent stability can be attributed to excellent interfacial interaction between AZO:PDA and active layer. Moreover, in order to demonstrate universality of the PDA modified AZO ETL, PBDB‐T‐2F:IT‐4F active layer was used to fabricate inverted PSCs on both glass and plastic substrate. As shown in FigureTableJsc of 21.74 mA cm−2, Voc of 0.83 V, and FF of 70.4%, is achieved by employing AZO:1.5% PDA ETL on ITO glass substrate. This PCE value is higher than that of the PSCs device with AZO ETL (12.3%). The integrated Jsc values from IPCE spectra are 20.75 and 20.81 mA cm−2 for AZO and AZO:1.5% PDA . Obviously, the active layer was easily detached from the unmodified AZO film after peeling 5 times, which is due to the poor adhesion between active layer and AZO. The well‐formed active layer on AZO:1.5% PDA is barely peeled off even after 10 times, due to the excellent interfacial adhesion promoted by strong intermolecular interactions between the functional groups of PDA and organic active layer. Furthermore, UV–vis absorption measurement has been used to verify the absorption intensity variation of the active layer before and after the peeling process. As seen from Figure 71BM for clearly observing intermolecular interaction. As shown in Figure−1 and at ≈1750 cm−1 was assigned to the symmetric stretching vibrations of —NH and —OH (ν(N—H) and ν (O—H)), and —C=O (ν(C=O)) in PDA, respectively. The PTB7‐Th:PC71BM:PDA blend film showed a stronger and wider ν(N—H) and ν(O—H) than those of pure PDA film indicating the formed hydrogen bond between PDA and PTB7‐Th/PC71BM. This behavior was further confirmed by the shifted symmetric stretching vibrations of —C=O (ν(C=O)) toward short wavenumber, which can also be attributed to the formed hydrogen bond.71BM, which could enhance interaction between active layer and interfacial layer, thus improving the mechanical adhesion and durability of the resulting devices. These excellent characteristics including bendability and interfacial adhesion of the PDA‐elasticized AZO ETLs offer a new opportunity to realize the goal of flexible and wearable PSCs with reliable performance.Another key factor affecting mechanical properties of PSCs is the adhesion property between functional layers in device. In this work, we carried out the peeling process via 3M tape to test the interfacial adhesion, which is similar to the approach that used for peeling perovskite layer from ZnO with scotch tape.In conclusion, a bendable and thickness‐insensitive ETL with adhesiveness has been in situ fabricated by introducing PDA into AZO as cross‐linking agent among nanocrystals. The PDA‐incorporated AZO exhibits superiority in the following several aspects: a) superior optoelectronic properties with high transparency and conductivity, which can be applied as thickness‐insensitive ETL; b) enhancing the flexural endurance of inorganic ETL upon bending, which is beneficial to the flexibility of the PSC devices; and c) endowing strong interfacial adhesion between organic active layer and inorganic ETL, which is in favor of enhancement of device durability. The best PCE of 12.7%, based on the PBDB‐T‐2F:IT‐4F system, has been achieved by employing the AZO:1.5% PDA ETL with thickness of 80 nm, which is superior to PCE of the devices with such thick interlayer reported to date. More importantly, a champion PCE of 11.5% has been obtained for fully flexible PSCs based on PET/Ag‐mesh electrode, and the device retains >91% of its initial PCE after bending for 1500 cycles. Such excellent mechanical durability and thickness‐insensitivity of inorganic ETLs are beneficial to roll‐to‐roll fabrication of large‐area flexible and wearable PSCs.The authors declare no conflict of interest.SupplementaryClick here for additional data file.SupplementaryClick here for additional data file.SupplementaryClick here for additional data file.SupplementaryClick here for additional data file.SupplementaryClick here for additional data file.


Actinomyces odontolitycus and Veillonella atypica due to a dental caries in an immunocompetent 65‐year‐old man patient.Actinomycosis is a rare, chronic granulomatous infection, frequently associated with immunocompromised states, but it can also affect healthy people. Here, we report a case of a pulmonary infection by  Actinomyces majerii, Actinomyces odontolyticus, and particularly Actinomyces israelii and Actinomyces graevenitziiActinomyces species are predominantly anaerobic, non‐motile, gram‐positive bacteria commonly found in human mucosae, particularly in the oral cavity and gastrointestinal and urogenital tracts 3/μL with a predominant neutrophil count of 89% and for a C‐reactive protein (CRP) of 158.2 mg/L.A 65‐year‐old male was admitted in June 2016 to our Lung Unit with a history of productive cough and intermittent fever in the last month and dyspnoea on exertion in the last week. No haemoptysis or chest pain was reported. He was a farmer and an active smoker of 35 pack‐years. His medical history was negative for previous relevant conditions; thus, he was not on any medication. He denied drug abuse or allergies. Poor oral hygiene and an irregular diet with a frequent consumption of alcohol with meals (one or two glasses of wine) were reported by the patient. At admission, cyanosis and clubbing were absent. Blood pressure was 120/80 mmHg, pulse was 97 beats/min, respiratory rate was 21 breaths/min, temperature was 37.2°C, and oxygen peripheral saturation was 96% in room air. Physical examination showed absence of lung sound in the upper and medium area of the right haemithorax. Initial laboratory exams were remarkable for a white cell count of 15.4·10A. odontolyticus and Veillonella atypica. Matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry for the identification of pathogens was performed. The Periodic Acid Schiff (PAS)  Fig. A and GroAS) Fig. B colouraThe patient was started on empiric antibiotic therapy with metronidazole (1500 mg/day) and piperacillin‐tazobactam (13.5 g/day) for a duration of three weeks. His clinical condition improved significantly, CRP dropped to 3.15 mg/L, and the chest X‐ray showed , potentially disseminating the infection to peripheral muscles and subcutaneous tissue. Currently, there are no guidelines in the literature for the treatment; however, the recommended therapy for actinomyces infections is two to six weeks of intravenous penicillin followed by 6–12 months of oral therapy A. odontolyticus and V. atypica in an immunocompetent patient with dental caries as the direct cause of infection. The collection of an infected sample by bronchoscopy was crucial for the diagnosis.Thoracic actinomycosis represents around 15–20% of Actinomyces infections Appropriate written informed consent was obtained for publication of this case report and accompanying images.


Failure to precisely distinguish malignant from healthy tissue has severe implications for breast cancer surgical outcomes. Clinical prognoses depend on precisely distinguishing healthy from malignant tissue during surgery. Laser Raman spectroscopy (LRS) has been previously shown to differentiate benign from malignant tissue in real time. However, the cost, assembly effort, and technical expertise needed for construction and implementation of the technique have prohibited widespread adoption. Recently, Raman spectrometers have been developed for non-medical uses and have become commercially available and affordable. Here we demonstrate that this current generation of Raman spectrometers can readily identify cancer in breast surgical specimens. We evaluated two commercially available, portable, near-infrared Raman systems operating at excitation wavelengths of either 785 nm or 1064 nm, collecting a total of 164 Raman spectra from cancerous, benign, and transitional regions of resected breast tissue from six patients undergoing mastectomy. The spectra were classified using standard multivariate statistical techniques. We identified a minimal set of spectral bands sufficient to reliably distinguish between healthy and malignant tissue using either the 1064 nm or 785 nm system. Our results indicate that current generation Raman spectrometers can be used as a rapid diagnostic technique distinguishing benign from malignant tissue during surgery. While improvements in screening have enabled the early diagnoses of many breast cancers, the significant number of diagnoses that eventually lead to death (~20% at 15 years) provide the primary impetus for advances in surgical intervention5.Breast cancer is the leading cause of cancer death among females worldwide, accounting for 25% of all cancer cases and 15% of all cancer deaths6. These positive surgical margins following lumpectomy are well-documented risk factors for local recurrence and disease-specific mortality. For invasive breast cancer, a positive margin is defined as tumor touching the inked margin7, and is typically discovered during postoperative microscopic pathologic assessment. Unfortunately, pathologic assessment of margins may take 1–2 weeks, is resource-intensive, and requires support from both a pathologist and a well-funded laboratory9. The belated finding of positive margins requires secondary surgery, potential surgical complications, patient discomfort, and financial burden for both the patient and the operating institution10.Complete excision of tumors represents a potentially curative option for treatment. However, in >30% of breast tumor excisions, the surgeon inadvertently cuts into tumor tissue and leaves cancer behind, in vivo, non-destructive detection of many types of cancer15. Raman generates biochemical fingerprints reflecting a tissue’s current biological composition and activity17. Multiple groups have demonstrated that healthy and malignant breast tissue produce distinct Raman spectra20. These differences are attributed to biochemical composition alterations in malignant tissue relative to healthy tissue, such as a reduced fatty-acid concentration, variable collagen content, and increases in spectral signatures associated with elevated concentrations of DNA, RNA, and peri-nuclear proteins in tumor sites when compared to healthy tissue22. Although previous generations of Raman spectroscopy systems have successfully detected specific biochemical signatures of cancer, our experience is that they have been too expensive, fragile, and/or cumbersome to deploy into widespread clinical use.Raman spectroscopy has emerged as a promising biochemical technique for real-time24. Fortunately, the use of Raman techniques in multiple disciplines has prompted the development of increasingly inexpensive commercial Raman systems and hand-held probes capable of safely interrogating biological targets29. Here we show that relatively inexpensive, off-the-shelf infrared Raman devices can be used to differentiate between malignant and healthy regions in resected breast tissue with a high degree of certainty.An inexpensive, portable Raman system capable of surveying cancer margins during initial surgery in real-time is desirable in both first and third world settingsi-Raman Ex 1064 nm and i-Raman Plus 785 nm, both manufactured and distributed commercially by B&W Tek . Both systems can be operated in microscopic or hand-held probe modes , the 1064 nm system produces a fluorescence background level of ~39.9 counts per second (cps) compared to 83.7 cps for the 785 nm system.Our first evaluation focused on the impact of tissue fluorescence on Raman signatures. Two tissue samples resected during breast conserving surgery for breast cancer were analyzed, one using the 785 nm system, the other using the 1064 nm device. All tumor spectra were collected from specimens containing invasive ductal carcinoma of the breast. Figure −1) and the high wavenumber region . The FP region provides information on the complex interactions between multiple bonds including a strong peak at 785 cm−1 associated with DNA and RNA nucleotides, broad peaks around 840 cm−1 and 941 cm−1associated with both collagen and glycogen, a sharp peak at 1004 cm−1 associated with the aromatic amino acid phenylalanine, another strong peak at 1092 cm−1 associated with the PO4 backbone, and bands characterizing lipid concentration and protein secondary structure such as the Amide I (C=O stretch near 1650 cm−1), Amide II (N–H bend + C–N stretch near 1550 cm−1) and Amide III bands (C–N stretch + N–H bend near 1300 cm−1), see Table et al. 2005). Tissue composition studies using Raman spectroscopy have been reported, and molecular signatures have been identified for major cellular constituents. Lipid peaks indicating the presence of fat appear at 1267, 1301, 1444, and 1450 cm−1 31. Carbon-hydrogen stretching in lipids result in broad peaks between 2800 cm−1 and 3000 cm−1, specifically at 2854, 2888, 2926, 2940, and 3009 cm−1 32. Proteins also contribute to peaks in this region, specifically at 2905 cm−1 for non-acetylated C-H vibrations and at 2942 cm−1 for acetylated functional groups in malignant cells8. Amino acids from proteins exhibit peaks at 1243, 1245, 1265, 1305, 1430, 1653, 1663, and 1671 cm−135. Carotenoids, levels of which are altered in malignant tissue relative to healthy tissue, have pronounced peaks at 1004, 1006, 1152, 1158, 1259, and 1518 cm−1 41. Degree of vascularization associated with tumor growth may be measurable via the hemoglobin peak at 1560 cm−138.Following fluorescence correction and area normalization, spectra for the two systems were evaluated for the presence of features distinguishing malignant from healthy tissue. Two regions in the Raman spectra are of potential interest for cancer diagnostics: the Raman fingerprint region FP, 400–1800 cm800 cm−1 −1 spectra for the 785 nm system including the HW region (2800–3200 cm−1). Gray vertical bands highlight 17 regions for the 785 nm spectra  accounting for >99% of the variance in 12 bands from the 1064 nm system and 17 bands from the 785 nm device were extracted by Principal Component Analysis (PCA). Eigenvector loadings >±0.4 have been highlighted in bold to give a qualitative indication of important contributors to the discrimination of these spectra. The first 3 PCs account for >98.0% of the variance in both the 1064 nm and 785 nm data.−1 and 1453 cm−1, spectral regions assigned to CH2 bending modes in normal and malignant tissue, and the 1303 cm−1 band assigned to δ(CH2) twisting of lipids, fatty acids, and/or collagen. PC2 includes information from 1663 cm−1 assigned to nucleic acid modes, and 1683 cm−1 assigned to amide I disorder and collagen. PC3 contains information from 941 cm−1 assigned to collagen backbone and polysaccharides, and 1063 cm−1 assigned to O-P-O stretch in DNA and RNA. PC4 includes contributions from 1006 cm−1 assigned to νs(C-C) phenylalanine ring breathing mode and 1453 cm−1 assigned to CH2 bending modes in malignant tissue. PC5 represents information from 1627 cm−1 assigned to amide I, and 941 cm−1 assigned to collagen backbone and polysaccharides. PC6 is dominated by contributions from 1063 cm−1 assigned to O-P-O stretch in DNA and RNA and 941 cm−1 assigned to collagen backbone and polysaccharides.For the 1064 nm data, PC1 includes strong contributions from bands at 1443 cm−1, a spectral region assigned to CH2 bending modes in normal breast tissue. PC2 includes information from 1331 cm−1 assigned to DNA and phospholipids, and 1302 cm−1 assigned to δ(CH2) twisting of lipids, fatty acids, and/or collagen. PC3 contains information from 1448 cm−1 assigned to CH2 bending modes in malignant breast tissue and 941 cm−1 assigned to collagen backbone and polysaccharides. PC4 includes contributions from 1302 cm−1 assigned to δ(CH2) twisting of lipids, fatty acids, and/or collagen and 1439 cm−1 assigned to CH2 bending modes in normal breast tissue. PC5 represents information from 941 cm−1 assigned to collagen backbone and polysaccharides. PC6 is dominated by contributions from 1657 cm−1 assigned to the C=C of lipids in healthy tissue.For the 785 nm microscope data, PC1 includes strong contributions from 1439 cm−1 and 1448 cm−1 bands, spectral regions assigned to CH2 bending modes in normal and malignant breast tissue, respectively. PC2 includes information from 742 cm−1 a region that can be assigned to the ring breathing mode of DNA and RNA bases, or the symmetric breathing of tryptophan, and 1302 cm−1 assigned to δ(CH2) twisting of lipids, fatty acids, and/or collagen. PC3 contains information from 1331 cm−1 assigned to DNA and phospholipids. PC4 includes a strong contribution from 742 cm−1 assigned to the ring breathing mode of DNA and RNA bases and/or the symmetric breathing of tryptophan. PC5 represents information from 1331 cm−1 assigned to DNA and phospholipids and 1082 cm−1 assigned to nucleic acids as well as the C-C and C-O stretching modes in phospholipids. PC6 is dominated by contributions from 1657 cm−1 assigned to the C=C of lipids in healthy tissue.For the 785 nm handheld probe data Table , PC1 incThe first 3 PCA factors accounting for more than 98% of the variance in the data for both the 1064 nm and 785 nm systems were used as inputs for Linear Discriminant Analysis (LDA) classification. The combination of these multivariate techniques for feature extraction and classification will be referred to as PCA-LDA. Bands employed to generate the principal components used by LDA refer to those displayed in Table ) or healthy . We utilized 3 PCA factors  were mapped on the photomicrograph of the H&E image using QuPath.In this experiment, the 785 nm system in microscope mode collected spectra along four transects designed to move sequentially across the visible boundaries between healthy and cancerous tissue. Figure 2 region around targets s6 , s8 , and s11 . The Raman probe samples a circular area with a diameter of approximately 50–85 μm. Figure Figure left panel), spectra s1- s5  plus spectra from sites s6 and s7 were acquired in what appeared macroscopically in visible light to be pale yellow healthy tissue. Morphological data from H&E stains  visual inspection revealed only one small area of potentially healthy tissue at s24. H&E stains identify both healthy and tumor cells in this region. The Raman spectrum shows changes in the fingerprint and high wavenumber regions characteristic of a mixture of tumor and healthy. For Transit 4 visual inspection, Raman spectra and histology code sites s29, s30, s31, s32 as tumor . For the five remaining sites (s33 to s37) visible light images shows a gradual shift from dark red-brown near the center of the sample to a light yellow and green at the periphery. The H&E stain shows a patchwork of red and purple indicating that the region is a mixture of healthy and tumor tissues. The Raman spectra show relatively strong lipid signatures from sites s33, s34, and s35, while spectra from sites s36 and s37 clearly exhibit spectral signatures characteristic of tumor.For Transit 3  and with data collection time limited to 10 seconds.The i-Raman probe head when removed from the microscope can either be used hand-held in the operating theater employing an embedded trigger to initiate spectral acquisition, or it can be securely fastened into a small stand  with an integrated XY-stage to systematically interrogate excised samples while documenting XY-coordinates. For this experiment, data acquisition was accomplished with a single 10 second scan using the bare probe secured in the probe holder.−1. Of the 17 spectral regions of interest in the 785 nm system for detecting cancer, the ink currently in use in our operating theater only compromises data collection for the 1260 cm−1 band. Data analysis is accomplished using 3 bands from the high wavenumber region and 13 bands from the fingerprint region, omitting all data from the contaminated cm−1 band.Figure ) or healthy . We utilized 3 PCA factors  chips capable of more efficient performance beyond 1000 nm. Wide-spread availability of affordable 1064 nm Raman spectrometers with full spectrum bandwidth must await improvement in cost-effective manufacturing techniques for larger InGaAs sensors.While an ideal instrument for minimizing fluorescence and maximizing Raman information content may ultimately turn out to be a 1064 nm spectrometer with a 200–3200 cmin vivo use of commercially available technology to screen dozens to hundreds of sites in a surgical theater will require a significant increase in data acquisition rate beyond the current 90 seconds used for the transit experiments and even the 10 seconds required when using the hand-held probe.The 50–85 μm beam size of most commercial Raman spectrometers including the ones tested here is an excellent match for clean detection of approximately 15–20 clustered tumor cells, approximately the same number of cells required for reliable histological diagnostics. The transit exercise presented here indicates that 57. To utilize the diagnostic information that is widely distributed across multiple Raman peaks, factor analysis has taken a prominent role in breast cancer diagnostics over the last decade and has been of considerable utility in this study63. For example, Brozek-Pluska and coworkers employ 532 nm confocal Raman spectroscopy for the characterization of malignant and healthy tissue using paraffin-fixed thin sections with a specificity that makes it possible to identify subtle shifts in lipid composition18. Haka and her colleagues have developed basis spectra representing the major biological components of breast tissue, fit the bases to spectra collected from breast tissue, and then used fit coefficients to discriminate between healthy and malignant tissues19. Sathyavathi and coworkers have discriminated benign from malignant breast lesions by measuring micro-calcifications via the calcium carbonate Raman signature20. Our data support the findings of these investigations that laser Raman spectroscopy combined with PCA-LDA analytic techniques can identify significant differences between cancerous and healthy tissue.The preliminary data presented in this project confirms the work of multiple other groups documenting that near-infrared laser Raman spectroscopy can identify spectral signatures for healthy and neoplastic breast tissueIn our experiments, we collected malignant spectra from invasive ductal carcinoma of the breast (IDC). While IDC represents the most common type of breast cancer, invasive lobular carcinoma (ILC) represents a significant minority. ILC has a distinct morphology, and is typically subtly infiltrative and can be difficult to detect on routine H&E-stained pathology slides. In future work, we plan to evaluate the performance of Raman spectroscopy for the detection of ILC and other more uncommon types of breast cancer.16, the exceptional specificity of the technique will identify relatively small, but highly consistent shifts in selected bands reflecting the appearance of pre-cancerous lesions64, degree of cell transformation65, treatment response 67, and fatty acid32. Raman technology is unlikely to replace standard postoperative pathologic evaluation of breast cancer specimens. Rather, we envision a scenario where Raman offers the breast surgeon a method for rapid and accurate statistical assessment of positive margins at the time of surgery. Such a method would spare the patient additional surgery, anxiety, morbidity and healthcare expenditure.We expect that, with the increasing world-wide effort to introduce continued adoption of Raman technology for cancer diagnostics3 mW-seconds for both systems. Our first evaluation focused on the impact of tissue fluorescence on Raman signatures. Historically, the fluorescence response to laser excitation can be as much as three orders of magnitude greater than the Raman scattering signal. Evaluation requires analyzing the raw spectra generated by each system.We evaluated two commercial Raman systems. Both systems operate in the infrared, one using a 1024 nm laser excitation source and the other operating at 785 nm. Both wavelengths are known to be capable of interrogating biological systems without damaging target material. The 1064 nm systems probe more deeply into tissue than a 785 nm device and often generate significantly less fluorescence than shorter, more energetic laser wavelengths. That is a significant advantage since fluorescence can easily mask the weaker Raman signal. Unfortunately, systems operating at 1064 nm are significantly more expensive and usually exhibit a more limited spectral bandwidth and diminished spectral resolution. The two systems evaluated were the i-Raman Ex 1064 nm and i-Raman Plus 785 nm, both manufactured and distributed commercially by B&W Tek . Both systems can be operated in microscopic or hand-held probe modes. For initial evaluation, we employed the systems in microscopic mode and selected laser exposure times so that total laser exposure (laser excitation power x collection time) would equal 9 × 10−1 and a spectral coverage range of 150–2250 cm−1. The detector cooled temperature is −2 °C with a typical dynamic range of 50,000:1 and integration time ranging from 100 milliseconds − 30 minutes. The effective pixel size is 14 μm × 9 μm. The i-Raman EX system uses a thermoelectrically cooled, 512-pixel InGaAs array detector with coverage range of 100–2500 cm−1 and resolution of 9.5 cm−1. The detector cooling temperature is −20 °C with dynamic range greater than 100,000:1 and effective pixel size of 25 μm x 25 μm. Integration time can range from 200 μs to greater than 30 minutes.The i-Raman Plus system uses a high quantum efficiency 2048-pixel CCD array detector, with a spectral resolution of 4.5 cm−1 from 247.1–2499.69 cm−1, spans 428 pixels, and provides 5.07 cm-1resolution (inter-pixel distance) at 1600 cm−1. The 785 nm system has an effective bandwidth of ~3026 cm−1 between 174.79 and 3201.06 cm−1, spans 1804 pixels and produces a 1.78 cm−1resolution limit at 1600 cm−1.In each device the spectrometer housing connects via fiber optic cables to the BAC102 Raman Trigger Probe. The probe has a spot size of 50–85 um. Table Tissue samples were collected following surgical resection under IRB protocol at City of Hope (COH) in Duarte, California  and only after patients provided informed consent. Following resection, tissue samples were immediately frozen and stored at −80 °C for post-operative Raman evaluation. For spectral analysis samples were thawed ~5–10 minutes before data collection. The pathologist on our team (DS) identified three breast tissue zones on each sample by simple, macroscopic visual inspection: healthy, tumor, and the tissue that appeared between these two sites was deemed the transition zone. All excised tumors in our study were invasive ductal carcinomas of the breast. Once spectral data were obtained, standard hematoxylin and eosin (H&E) glass slides were prepared. These slides were digitally scanned at 20X magnification using a Ventana iScan HT slide scanner . The resulting whole slide images were assessed using the QuPath open source imaging application  to determine the microscopic heterogeneity of cancerous and healthy cells at target sites in the three macroscopic tissue zones.Clearly, perfect co-registration between the standard H&E 2-D slide and 3-D sample is not achievable for several reasons. First, a certain amount of tissue is discarded in the process of “facing up” the paraffin embedded tissue block to produce a square surface for microtome sectioning, thus introducing localization uncertainty in the z plane. In addition, slight differences in camera angles and specimen rotation in 3-D space during sectioning add geometric positioning and imaging uncertainty in the XY-plane. Following co-registration of the visible light microscopic images with our spectral target position grid, we assign 1 mm “best guess” error bars for positioning accuracy.−1 for the1064 nm system, and between 400 and 3200 cm−1 for the 785 nm system.Prior to data collection, calibration spectra were obtained using Teflon standard targets. During data acquisition, BWSpec, the software integral to the i-Raman Plus and i-Raman EX systems, applies a baseline subtraction for ambient noise, and filters cosmic ray anomalies. The data were then corrected for fluorescence using MATLAB’s msbackadj.m function. The function iteratively estimates the spectral baseline using shifted windows and regression with a spline approximation, then subtracts the predicted fluorescence contribution from the signal. The final spectrum is normalized to the area under the curve between 400 and 1800 cmTo implement a real-time machine learning system on a local data set that is sufficiently rigorous to identify tumor spectral signatures in a broader population of samples, we elected to minimize the number of potential input variables (428 in the case of the 1064 nm system and 1804 for the 785 nm device). First, we calculate the 95% confidence interval for spectra from healthy and cancerous tissue and identify the regions that maximize the area between the confidence interval boundaries. We also characterize and exclude from classification the spectral regions containing Raman activity originating from the dyes used to provide tissue landmarks during surgical excision.60 and Linear Discriminant Analysis (LDA)68 are employed in the experiments reported here for feature extraction and variable input reduction (PCA) and classification (LDA). PCA, also known as the Karhunen-Loéve or Hotelling transform, extracts significant information from a data set by identifying linear combinations of raw variables accounting for maximum variance in the data set. PCA identifies correlations or covariance between multiple variables and calculates a new variable, the first principal component, which accounts for as much variance in the data as possible. The process continues generating successive factors that account for decreasing fractions of the total variance. The method is robust to moderate amounts of noise since the covariance matrix is an average over many input vectors and the noise is uncorrelated from one data vector to the next. In most experiments, a practical balance between data compression and classification accuracy can be achieved by selecting eigenvectors that account for 75–95% of the eigenvalues. The new set of PCA factors encodes in compressed format the significant information content of the original data set. PCA is an unsupervised classifier, meaning it does not use a priori classification designations.Once the discriminating spectral bands were identified and the data were mean-centered, two multivariate techniques, Principal Component Analysis (PCA)14. These were employed to analyze the spectra and reliably distinguish malignant from benign tissue.LDA, also known as the Fisher discriminant, is a classification method that assumes different classes generate data based on differing Gaussian distributions. To train a classifier, the fitting function estimates the parameters of a Gaussian distribution for each class. To predict the classes of new data, the trained classifier finds the class with the smallest misclassification cost. Cross-validation using a leave on out format is employed for seamless training and testing of a data set. Both PCA and LDA are linear transformation techniques commonly used for multivariate data analysis. PCA in combination with LDA has been shown to improve Raman spectral classification sensitivity and specificitySupplementary Figure S1