Architectural stripes tend to form at genomic regions harboring genes with salient roles in cell identity and function. Therefore, the accurate identification and quantification of these features are essential for understanding lineage-specific gene regulation. Here, we present Stripenn, an algorithm rooted in computer vision to systematically detect and quantitate architectural stripes from chromatin conformation measurements using various technologies. We demonstrate that Stripenn outperforms existing methods and highlight its biological applications in the context of B and T lymphocytes. By comparing stripes across distinct cell types and different species, we find that these chromatin features are highly conserved and form at genes with prominent roles in cell-type-specific processes. In summary, Stripenn is a computational method that borrows concepts from widely used image processing techniques to demarcate and quantify architectural stripes. Chromosome conformation capture techniques have recently revealed features beyond chromatin loops such as architectural stripes. Here the authors present their stripe detection tool ‘Stripenn’ to detect and quantitate stripes from any type of chromatin conformation capture data. They show that architectural stripes are enriched at transcriptionally active and accessible genomic regions. Chromosome conformation capture techniques, in particular Hi-C, suggest that the chromatin is folded into various length scales, forming a hierarchical structure5. Among these structures, topologically associating domains (TADs) are sub-megabase regions where stronger interactions are observed between loci inside each domain compared with loci in neighboring domains7. The spatial proximity of two genomic regions within TADs displaying high contact frequency in Hi-C maps is referred to as chromatin loops9. Loop formation, which is best described by the loop extrusion model, is mediated through sliding cohesin anchored by CTCF binding events in a convergent orientation11.The eukaryotic genome is tightly organized inside the nucleus by forming a complex of DNA and histone proteins called the chromatin14. Architectural stripes are thought to form through the loop extrusion process when a loop anchor interacts with the entire domain at high frequency13. Stripes have been reported as frequent features of diverse developmental programs15. It has been proposed that these unique structures, often associated with active enhancers and super-enhancers, can tether enhancers to cognate promoters, facilitating transcription and recombination13. Moreover, stripe anchors represent major hotspots for topoisomerase-mediated lesions, which may promote chromosomal translocations and cancer13. Since architectural stripes tend to form at genomic regions harboring genes with key roles in cell identity and function, it is essential to accurately detect these features from Hi-C or other chromatin conformation capture measurements16.Although TADs and chromatin loops as distinguishing features of Hi-C maps were described in pioneering studies, structures appearing as lines, flames or stripes attracted attention most recently21. The first reported stripe detection algorithm, referred to as Zebra, exploited the Poisson statistics and yielded thousands of stripes13. Although the original study reporting Zebra detects regions with stripy features, the algorithm suffers from three major limitations: (a) it has a high false-positive rate and detects some chromatin loops as stripes, (b) it lacks a quantitative assessment of stripes and has been reported to rely on manual curation, and (c) the code for the algorithm’s implementation in the original study13 is not publicly available. Recently, an implementation of the Zebra algorithm, referred to as StripeCaller22, was made available on Github by an independent group. However, the accuracy and quality of stripes detected by this implementation, which is not peer-reviewed, remains unknown.Numerous computational techniques have been developed to detect chromatin loops. Yet, the reliable identification of architectural stripes remains a challenge12. However, domainClassifyR assumes that stripes form exclusively at the boundaries of genomic domains defined by TAD callers. It is evident from Hi-C maps of diverse cell types that although some architectural stripes form at TAD boundaries, stripy features are also found inside TADs. Hence, intra-TAD stripes remain undetected by the domainClassifyR computational approach. Another tool called CHESS was recently developed to perform quantitative comparisons of chromatin contact data between two conditions using the structural similarity index23. Although CHESS has been developed to report differential features such as TADs, stripes, or loops between two conditions23, this method cannot be used to delineate architectural stripes in a cell type of interest. Another relevant method is Chromosight, which was developed to detect specific patterns such as loop and hairpin structures using computer vision21. Technically, Chromosight can also be applicable in discovering stripes using appropriate kernels. However, it remains unclear if this technique can extract stripe coordinates which is important for downstream biologically relevant investigations. Altogether, despite the availability of multiple computational techniques, there is a need to accurately and efficiently detect architectural stripes and assess the strength of stripes across cell types and conditions.Another computational approach, which is publicly available and referred to as domainClassifyR, was developed to comprehensively detect stripes and loops by first marking TADs and then measuring their stripe and loop scores24, one of the most popular edge detection algorithms in the mature field of computer vision. Stripenn can be applied to any chromatin conformation capture data such as Hi-C4, HiChIP25, and Micro-C26. Our method offers two scoring systems: P-value to filter low-quality stripes and stripiness to rank stripes based on the continuity of interaction signal. Here we show that Stripenn outperforms existing techniques including Zebra, Chromosight, and domainClassifyR when these techniques are applied on the same ultra-high coverage Hi-C dataset. Our systematic analysis of stripes from B and T lymphocytes using Stripenn indicates that the majority of stripes are on the transcriptionally active compartment. Moreover, cohesin loader NIPBL and active enhancer modifications are highly enriched at stripe domains, and active enhancers are biased to only one or few genes within stripes. Although hundreds of genes are differentially expressed between the two inbred mouse strains, most stripes are conserved and demonstrate comparable stripiness. In contrast, the comparison of B and T lymphocytes shows a large number of cell-type-specific stripes corresponding to cell-type-specific gene expression. Finally, the conserved stripes across human and mouse T cells harbor significantly more genes related to T cell biology than those in the conserved loops. Together, Stripenn, which is freely available on Github27, is a specialized tool dedicated for stripe detection, enabling the systematic and quantitative analysis of stripes.Here, we report the development of a specialized stripe detection tool called Stripenn, which borrows concepts from computer vision and image processing. The backbone of our method relies on Canny edge detection28, to a digital image. Next, contrast adjustment and noise reduction are applied to a sliding window of 400 pixels along a diagonal line of the image . An edge in any digital image can point to a variety of directions; hence, the Canny algorithm uses filters to detect horizontal, vertical, and diagonal edges. Considering that contact matrices are symmetrical about the diagonal line, Stripenn only reports vertical edges predicted by the edge detection algorithm. Since a stripe is defined by a genomic anchor positioned on the diagonal line, predicted vertical edges longer than 10 pixels are connected to the diagonal line. Canny edge detection predicts two edges for each stripe and adjacent lines within a pre-defined distance are paired, forming a single vertical stripe. Together, Stripenn adapts principles from digital image processing and edge detection techniques to demarcate architectural stripes.Stripenn systematically detects and quantitates architectural stripes from genome-wide chromatin conformation measurements. Our method applies principles from computer vision to detect genomic anchors that interact with entire domains at high frequencies Fig. . The proage Fig. . To enhaP-value of pixel contrast and stripiness  and right (R) neighboring pixels are calculated from 50 kbp × 50 kbp windows adjacent to a given row. To estimate the P-value of the difference between the mean intensity of neighboring windows from the center   predicted by Stripenn and Zebra. In all cases, predicted stripes by Stripenn had significantly higher stripiness than predicted stripes by Zebra, suggesting higher quality of predictions by Stripenn compared with those of Zebra . We examined the compartmentalization of stripes and found that stripes were frequently (~83%) formed on the transcriptionally active A compartment, which is consistent with the previous report using Micro-C measurements relying on stripy features at TAD boundaries26  thymocytes in C57BL/6J mice31 and detected 431 stripes (314 5′- and 117 3′-stripes) . Consistent with findings based on Hi-C maps of B cells, we confirmed that most stripes formed on the A compartment of DP thymocytes  and the pathogenesis of type 2 immune responses such as asthma. Another highly ranked gene, Ddx5, is required for the cytokine production of T helper cell type 17 (Th17). Moreover, Tcf7 a transcription factor for early T cell development setting up the chromatin accessibility landscape of T cells encompassed an architectural stripe32. Together, these data further corroborate that architectural stripes favor highly accessible and active chromatin states at genes with prominent roles in cell-type-specific processes.To further assess the quality of architectural stripes detected by chromosome conformation techniques other than Hi-C , ‘adaptive immune system, downstream TCR signaling’ , and ‘oxidative phosphorylation’37 , compared with genes on non-stripy TADs 41. Similar to Cxcr4, Socs1 required to suppress the cytokine signaling, regulating T cell proliferation, activation, and function42, resides in the middle of a stripy TAD and is preferentially located near the boundary of two nested TADs. The selective enrichment of T cell-associated genes within architectural stripes of T cells further confirms the potential cell-type-specific regulatory role of stripes.To assess the association between stripe formation and transcriptional outputs, we compared the expression levels of genes located on 156 stripy TADs versus 144 non-stripy TADs within the A compartment of DP thymocytes. On average, we did not find any significant difference between the expression levels of genes located on stripy vs. non-stripy TADs Fig. . Nonethe7ac Fig. . Since CADs Fig. . This ancs1 Fig. . The gen43  mice. Using SMC1 HiChIP measurements in DP thymocytes, Stripenn was able to detect 953 and 1151 stripes in C57BL/6J and NOD mice, respectively43 Fig. . To compted Fig. . The visKlr) gene family located on chromosome 6 . Nonetheless, we were not able to detect a significant difference in interactions of stripy regions between the two strains accommodating differentially expressed genes . Although the architectural stripe formed at this locus was detected by Stripenn in both strains, the stripiness of this stripe was ~2 times higher in NOD compared with C57BL/6J  and performed Hi-C experiments in a T cell line representing T cell progenitors (DN3)  of predicted stripes between T and B lymphocytes showed low correlation  Fig. . StripenN3) Fig. . The strBcl2 and Bcl11b genes were two representative stripes that demonstrated strong cell-type-specific stripe formation and transcription in B and T cells, respectively  and Th2, facilitating the elimination of distinct pathogens49. We generated ultra-deep Hi-C maps in CD4+ Th1 cells in mice and CD4+ T cells in humans. Stripenn was able to detect 1528 stripes in mouse CD4+ T cells while 805 stripes were detected in human CD4+ T cells. First, we defined the stripe anchors in mouse CD4+ T cells that had orthologous regions in the human genome . We found that 14.2% of mouse stripe anchors were conserved as human stripe anchors while 29.0% were conserved within human stripe domains . Among the 2041 loops detected in mouse T cells, which were not predicted as stripes, 398 loops were conserved as loops in human T cells, showing similar a conservation level , was a kind gift from Warren Pear’s lab. These cells were grown in RPMI 1640 medium (Invitrogen), supplemented with 10% fetal bovine serum (FisherScientific), 1 mM sodium pyruvate (Gibco), 1% non-essential amino acids (Gibco), 2 mM L-Glutamine (Lonza), 1% penicillin–streptomycin and 0.1% 2-Mercaptoethanol (Gibco). All cells were grown at 37 °C and 5% CO2.Scid.adh cell line, a pro-T (DN3 stage) cell line derived from spontaneous thymic lymphomas , part of the Human Islet Research Network (https://hirnetwork.org/), with approval from the University of Florida Institutional Review Board (IRB # 201600029) and the United Network for Organ Sharing (UNOS). All the specimens or data come from cadavers or otherwise deceased individuals, hence the University of Florida Institutional Review Board has determined that our study is not considered human subjects research and has therefore waived the need for informed consent and exempted the requirement to be conducted in accordance with the declaration of Helsinki. Human CD4+ T cells were sorted out lymph nodes of a healthy human donor collected by HPAP.Total cells were isolated from mouse spleen and lymph nodes and naive CD4+ T cells were enriched using negative selection beads . These cells were cultured in RPMI 1640 medium (Invitrogen), supplemented with 10% fetal bovine serum (FisherScientific), 1 mM sodium pyruvate (Gibco), 1% non-essential amino acids (Gibco), 1X GlutaMAX (Gibco), 1% HEPES (Gibco), 1% penicillin–streptomycin and 0.1% 2-Mercaptoethanol (Gibco) and in-vitro polarized to Th1 cells by treating with 1ug/ml anti-CD3 , 1ug/ml anti-CD28 , 10 ng/ml recombinant IL-12, 1 ng/ml recombinant IL-2 for 6 days. All animal work was in accordance with the Institutional Animal Care and Use Committee of the University of Pennsylvania in accordance with NIH guidelines. Human tissues were procured by the HPAP consortium  and Accel-NGS @S Plus DNA Library kit (21024 Swift Biosciences), according to the manufacturer’s recommendations. Libraries were validated for quality and size distribution using Qubit dsDNA HS Assay Kit  and TapeStation 2200 (Agilent). Libraries were paired-end sequenced (66 bp+66 bp) on NovaSeq 6000 (Illumina).Hi-C libraries were generated on 10Hi-C in Th1 cells: Total cells were isolated from mouse spleen and lymph nodes and naive CD4+ T cells were enriched using EasySep Mouse naive CD4+ T cell Isolation kit . These cells were cultured in RPMI 1640 medium (Invitrogen), supplemented with 10% fetal bovine serum (HyClone), 1 mM sodium pyruvate (Gibco), 1% non-essential amino acids (Gibco), 1X GlutaMAX (Gibco), 1% HEPES (Gibco), 1% penicillin–streptomycin and 0.1% 2-mercaptoethanol (Gibco) and in-vitro polarized to Th1 cells by treating with 1 μg/ml anti-CD3 , 1 μg/ml anti-CD28 , 10 ng/ml recombinant IL-12 , 1 ng/ml recombinant IL-2  for 6 days.Human CD4+ T cells were sorted out from pancreatic lymph nodes. Sorting was done after gating on Aqua- (live cells), CD14− CD19− (not B cells) CD3+ (T cells) CD4− CD4+ cells, using antibodies anti-human CD3 , anti-human CD14 , anti-human CD19 , anti-human CD8 , anti-human CD4 .P-value and stripiness. Stripenn can be installed via pip (or pip3) and more information on installation and usage is described on the GitHub page (https://github.com/VahediLab/stripenn).Stripenn detects architectural stripes from chromatin conformation capture data using image processing principles and scores them with median Input and output: The input of Stripenn is in a cooler file format (.cool or.mcool) that contains a genomic matrix such as the Hi-C contact frequency matrix28. The output is a table of stripe coordinates, sizes, and measures . Stripenn runs through three steps to generate the output: (1) to search for candidate stripes, (2) to measure median P-value, and (3) to measure stripiness.To search for candidate stripes: For each chromosome, stripes are searched within a series of windows of 400 pixels that are moving along a diagonal line of contact frequency heatmap using the step size of 200 pixels. In each window, referred to as submatrix hereinafter, rows and columns composed of only zeros are removed and the corresponding genomic regions are deleted. Stripenn follows eight steps to find candidate stripes in each submatrix:Convert matrix to image: A submatrix is converted to an image, as shown in Fig. maximum pixel value, to visualize the 3D chromatin structure properly. This step is important since extremely low or high maximum pixel value makes the image covered with only red or white pixels, which does not give any information. Because the stripe detection is sensitive to the maximum pixel value, Stripenn can search stripes for multiple maximum pixel values. These are determined by the percentiles of positive contact frequencies that the users provide as input. For example, the option ‘-m 0.93,0.95,0.97’ in the command line enables to set the maximum pixel values as top 7%, 5%, and 3% of the positive contact frequency values of each chromosome . These percentiles should be set differently for different data based on the sequencing depth of the data. Stripenn’s ‘seeimage’ function helps the users decide the percentile values by visualizing a contact frequency matrix of given coordinates for a given percentile. Once maximum pixel value (M) is determined, each pixel value (P) in submatrix is then converted to RGB codes such asmerge function in opencv-python package54 to create an image.Brightness adjustment: Next, we adjust the brightness to increase the contrast between the signal and noise of the image. Because the optimal brightness that best reveals the 3D structure in the image is not known, we adjust the brightness for multiple levels and find stripes for each level. To do this, MATLAB’s imadjust function55 is implemented in python and used with changing high_in parameters from 0.5 to 1.0 increasing by 0.1.Blur effect: Next, the mean filter can be applied to further reduce the noise of the image by changing the kernel size option (bfilter). Here, the filter2D function of the opencv-python package is used and a 3 × 3 two-dimensional matrix filled with 1/9 is used as a default kernel. The kernel size option can be set as 1 to turn off the blur effect.Canny edge detection: The image is then converted to grayscale using the cvtColor function in the opencv-python package to apply Canny edge detection. It is the most widely used edge detection method because it searches optimal edges that satisfy three criteria of an optimal edge: (1) edge with a low error rate, (2) optimal localization, and (3) only one strong signal is detected. The edge image E is extracted using the canny function (default sigma = 2.0) in Scikit-image package56.Vertical line detection: Because Hi-C data is symmetric about the diagonal line, horizontal stripes are automatically detected if corresponding vertical stripes are found. Thus, we search for only vertical stripes here. To do this, pixels whose orientations are not between 60° and 120° are removed. The orientation θ of each pixel 57.x- and y-direction, and convolve2d function in SciPy package58 and arctan2 function in NumPy package59 are used. Because the orientations of edges in minL’. Since the edges are usually not straight in reality, we allow each pixel in a straight line to shift left or right by 1 pixel. These continuous lines are then extended to the diagonal line.Line refinement: After step 5, several lines can be combined since we allow a 1-pixel shift. To find the representative line among them, we first converted pixel one  in each line to zero (background) if it is originally zero in the edge image Adjacent line pairing: Next, we pair two vertical lines if their distance is less than N pixels (default: 8 pixels). If there are multiple lines within a narrow window, those lines are paired in a serial way. Then, each pair is evaluated with a median P-value to filter low-quality stripes. The maximum stripe width should change according to the data resolution. For example, we recommend using 8 pixels and 16 pixels as maximum widths for 10 kb and 5 kb, respectively.Merging stripes: Searching stripes from overlapping submatrices with multiple brightness parameters results in several duplicated stripes. In the last step of candidate stripe search, these are merged into one as the stripes having the largest length/width value.P-value is devised to filter candidate stripes based on a pixel contrast between stripes and their backgrounds. Simply, the median P-value is a median of a series of P-values evaluated from each stripe row. The P-value of each stripe row is estimated as described in Supplementary Fig. width pixels, where N × N pixels right next to the testing row. Since the P-value estimates the significance of P-value, we choose the less significant value. Stripenn output reports a list of stripes of which P-value is less than 0.1 as a default.The median P-value measures the significance of the contrast between the stripe and the background; however, this metric does not reflect the contact frequency and continuity of intensity within the stripe. To make up for these shortcomings of median P-value, stripiness has been devised. Stripiness (S) is estimated on the observed/expected contact frequency matrix, and it is defined asth stripe row. The gradient change x-direction (across stripe and background) and y-direction (within stripe). Since larger gradient in the x-direction and smaller gradient in the y-direction are features of strong stripes, we define th stripe row and adjacent left/right background rows (width = 50 kb), respectively. The gradient in y-direction Median Based on the definition, negative stripiness represents low-quality stripes since the contrast between the stripe and its background is weaker than the pixel continuity along with the stripe domain. Thus, we recommend excluding the stripes with negative stripiness to construct a reliable set of stripes.13. We processed these calls to merge the adjacent calls and connect each call to the diagonal line of the contact frequency matrix. To run domainClassifyR12, we used three R packages . TAD coordinates, required for this program, were assessed using two Perl scripts named ‘matrix2insulation.pl’ and ‘insulation2tads.pl’ from the cworld-Dekker Github page60. All parameters were set as defaults. Then calls with forward or reverse z-score >5 were used in the analysis to have enough calls for comparison. Chromosight version 1.6.1 was installed and 5′- and 3-stripes were detected using the following command lines, respectively.For competitive benchmarking, we used Hi-C data of 72 h-activated B cell (GSE82144). Zebra stripe calls were directly obtained from the author of the original paper13. Time and memory usage of each method were measured using ‘time’ with -v option (/usr/bin/time -v). This comparison was performed on a server computer of which CPU model was Intel ® Xeon® Gold 5115 CPU @ 2.40 GHz having 394.9 GB RAM.61 where ‘--local –rescale --unbalanced’ options were used. Similarly, in Supplementary Fig. Pileup plot analysis: In Fig. : For Zebra and Stripenn, which provide exact stripe coordinates, we compared stripiness and the average observed/expected contact frequency of common and unique stripes. We regarded two stripes were overlapping if they shared at least one genomic bin.Common and unique stripesHere, we used the Hi-C map with a resolution of 5 kb. Then we removed redundant pixels indicating the same stripes. In other words, if two pixels are located on the same line, the one that was closer to the diagonal line was eliminated. StripeCaller, the Github implementation of Zebra, was also performed using default parameters. Here, additional information such as TADs and loops was not provided for a fair comparison. Similar to Zebra, adjacent calls from StripeCaller were merged and extended to diagonal line. Stripenn stripes were called from unnormalized, 5kb-resolution data since the observed signals in Zebra calls were detected from the raw Hi-C ligation counts62 to obtain 212.8 million valid pairs. The downsampling of this dataset was performed to identify the minimum level of valid pairs to run Stripenn. Among 212.8 M valid pairs, 200 M, 175 M, 150 M, 125 M, 100 M, 75 M, 50 M, 25 M valid pairs were sampled using the shuf function. Each shuffled file was converted to.hic format using Juicer18 and then converted to.cool format using hic2cool version 0.8.363. Stripes were predicted from each.cool file for chromosome 1 with different maximum pixel quantile parameters (0.9 to 0.995 with step 0.1), and the running time was measured. The number of threads was fixed to ten.The FASTQ file of the Hi-C data of 72 h-activated B cell (GSE82144) was downloaded and processed in HiC-pro64.The example stripes in Supplementary Fig. 17 was applied to normalize Hi-C of mouse 30 hours-activated B cell data13, CH12 B cell lymphoma cell line13, mouse DN3 T cell line, mouse Th1 cells, human CD4+ cells, and HiChIP data of DP thymocytes of C57BL/6J and NOD strains31. Square root vanilla coverage normalization (5103 stripes) performs better than Vanilla coverage , KR balancing normalization (4361 stripes) in terms of the number of stripes detected when applied to the micro-C of human foreskin fibroblasts.Square root vanilla coverage method20 with 50 kb resolution. The regions with positive and negative PC values were regarded as A and B compartments, respectively.Principal component (PC) analysis was performed using HOMEROur custom R code generated the protein binding intensity heatmaps in Supplementary Figs. 5-stripes have anchors at 5′-end of the stripe domains, and vice versa.33. To facilitate the Omics data analysis, it integrates functional enrichment, interactome, gene annotation, and membership search analysis from over 40 independent knowledge databases such as Gene Ontology66, MSigDB68, KEGG69, Reactome, etc. A prominent characteristic of the Metascape is the comparative analysis across multiple independent and orthogonal experiments. Taking advantage of this, we performed the comparative gene ontology analysis of the most highly expressed genes in non-stripy and stripy TAD of mouse DP thymocytes. Both input and analysis species were set as Mus musculus. In addition, gene set analyses for individual gene lists were performed for the most highly expressed genes in B and T cells (species: mus musculus) and those in conserved stripes and loops across humans and mice (species: homo sapiens).Metascape is an effective and efficient web portal designed for experimentalistsTwo mouse strains: The stripes from NOD and C57BL/6J DP thymocyte HiChIP data were compared. First, the stripes were searched from both 5 kb and 10 kb resolution data and then filtered based on median P-value < 0.1. Stripes from four datasets  were then merged as follows. First, stripes from the same strain but different resolution data were combined. For overlapping stripes, stripes with the largest stripiness were selected. Next, stripes from different strains were combined. For combined stripes, stripiness and median P-values were recalculated based on NOD and C57BL/6J HiChIP data with 5 kb resolution using Stripenn’s score function.B and T cells: The stripes were predicted from the Hi-C measurements of CH12 B lymphoma cell lines and DN3 T cells, respectively, using Stripenn . Similar to the two mouse strain comparison, the stripes from two datasets were merged, and then their stripiness and median P-values on each Hi-C data were estimated using Stripenn’s score function.In this study, the cell-type-specific stripes were defined as those with stripiness >2 in one condition and stripiness <0 in the other condition.49, we estimated typical and super-enhancers of mouse DP thymocytes from the H3K27ac ChIP-seq of C57BL/6 J strain. Briefly, the H3K27ac peaks were merged for every genomic bin  and then ranked. In Fig. GenomicRanges70. The significance of the overlap between stripes and super-enhancer was estimated using the hypergeometric distribution.Using the previously reported strategy+ T cells and mouse Th1 cells were detected using Mustache version 1.2.051, and FDR < 0.01 was used as the cutoff. Loops overlapping with stripe domains were excluded from the analysis.Loops from Hi-C measurements (5kb-resolution) of human CD4LiftOver71. The minMatch parameter was set as 0.1.The genome coordinates of the mouse (mm10) stripe anchors, defined as the +50 kb region from the stripe start site, were converted to human (hg38) coordinates using Triangle heatmaps and corresponding tracks were generated by R package Sushi.P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.Statistical significance was tested using two-sided Wilcoxon rank sum test. *Further information on research design is available in the Supplementary InformationReporting Summary


The authors regret that in Table 1, the site BSA was sampled in the years 2008 and 2010, and it was not sampled in the 2015 year. Data of 2015 in the site BSA belong to site Ca. Therefore, the site Ca has data in the years 2010, 2011, 2014 and 2015 and the site BSA has data in the years 2008, 2010.The authors would like to apologise for any inconvenience caused.


Draxin and misregulated astroglial and leptomeningeal proliferation as genetic and cellular factors for variable IHF remodelling and CCD in BTBR strains. These findings support a model where genetic events determine corpus callosum structure by influencing leptomeningeal-astroglial interactions at the IHF.Corpus callosum dysgenesis (CCD) is a congenital disorder that incorporates either partial or complete absence of the largest cerebral commissure. Remodelling of the interhemispheric fissure (IHF) provides a substrate for callosal axons to cross between hemispheres, and its failure is the main cause of complete CCD. However, it is unclear whether defects in this process could give rise to the heterogeneity of expressivity and phenotypes seen in human cases of CCD. We identify incomplete IHF remodelling as the key structural correlate for the range of callosal abnormalities in inbred and outcrossed BTBR mouse strains, as well as in humans with partial CCD. We identify an eight base-pair deletion in  The corpus callosum (CC) is the largest white matter tract that mediates information transfer between brain hemispheres in placental mammals. In humans, it fails to form normally in approximately 1:4000 live births, resulting in a group of conditions collectively termed CC dysgenesis CCD; . CCD incCC formation is dependent on a prior sequence of developmental processes: cellular proliferation, migration, axonal elongation, guidance, and targeting . CallosaDraxin as a favourable gene candidate that might underlie variable CC and HC formation  is frequently observed to co-occur with CCD in humans, indicating that these commissures rely on common developmental programs . Analogoormation . Draxin  in mice .Draxin, which truncates and ablates normal DRAXIN protein expression in BTBR mice. Inheritance of the Draxin mutation is a driver of defective IHF remodelling and subsequent CCD and HC dysgenesis in BTBR and BTBR × C57 mice. Mis-regulated cellular proliferation of MZG and leptomeningeal cells were both identified as the cellular correlates for failed MZG-mediated IHF remodelling and interhemispheric tract formation in BTBR mice. Finally, we identify incomplete IHF remodelling in a cohort of human individuals with partial CCD. Together, our results suggest that diverse CCD phenotypes can arise from a single genetic event that variably disrupts IHF remodelling and, consequently, the amount of substrate available for CC and HC axons to cross the midline, and therefore provides the first aetiology associated with partial CCD.Here, we investigate the underlying genetic and developmental mechanisms leading to diverse CCD phenotypes in BTBR mice and the BTBR × C57 cross. CCD severity and the extent of HC dysgenesis in these mouse strains is strongly associated with abnormal retention of the IHF, and thus the degree to which IHF remodelling is incomplete. Moreover, we describe an eight base-pair deletion in We previously demonstrated that BTBR × C57 N2 littermates display a spectrum of CCD phenotypes . Here, wTo investigate potential structural correlates of complete and partial CCD, we first examined the midline of BTBR and BTBR × C57 N2 mice. We previously demonstrated that remodelling of the IHF is a critical developmental step required for subsequent midline crossing of callosal axons, and that failure of this process to occur results in an unfused septum; an MRI feature that is strongly associated with complete CCD in humans . To deteC57 adult mice demonstrated a fused septum and IHF positioned anteriorly and superiorly to the CC and HC . In contAn unfused septum and deep IHF are invariably present in humans with complete CCD, who commonly have associated HC malformations . To deteIn neurotypical individuals, the CC extends dorsal, anterior, and posterior to the septum, which is fully fused except in a minority of individuals that demonstrate cavum septum pellucidum – a normal anatomical variant that forms ventral to the corpus callosum . PartialDraxin in the BTBR strain , but protein expression was undetectable in tissue using a polyclonal antibody generated from an immunogen of whole human DRAXIN via immunohistochemistry and western blot  on chromosome 4 (rs6397070), 7.795 megabases downstream of the Draxin deletion as a marker for the BTBR allele in a subset of complete CCD, partial CCD, and normal CC littermates . Additional SNPs were also sequenced at candidate loci on chromosome 9 (rs29890894) and chromosome 15 (rs31781085), which were previously judged to have a potential genetic influence on commissure size based on LOD scores that did not reach statistical significance 0. Time-mated females were obtained by housing male and female mice together overnight and the following morning was designated embryonic day (E)0. Animals were anaesthetised and collected as previously described . For EdUTTTATGGCTGGGGACTTCAG and reverse CGAATCCAAAGCTCTCTTGC; chromosome 9, SNP rs29890894, forward AGCTTGGTGGCATCCATATC, reverse GCACTCTCCCTACTGCTTGG; chromosome 15, SNP rs31781085, forward GATCGTTGCAGTGACCACAC, reverse GCTGATTGGCAGGTTCTGAT. Genotyping for the Draxin mutation was performed by PCR using the following primers: wildtype forward AGACGGTCCCTGCGTCTC, mutant forward GTCGCAGACGGTCCCTTG, and common reverse AGGCTTCCCAGATGACACTC. Sanger sequencing was performed at the Australian Genome Research Facility.Genotyping of BTBR × C57 N2 mice was performed by PCR of SNPs associated with CC size in the BTBR × C57 F2 intercross as previously described by us . AmplicoParticipants were enrolled in an ongoing study at The University of Queensland from October 2014 with approval from The University of Queensland Research Ethics committee. 10 individuals with partial CCD aged 21–72  and 9 neurotypical individuals  provided written informed consent. MRI scans of all participants were reviewed by a neuroradiologist (SM), who has extensive experience in human brain malformations. The groups did not differ significantly in either age or gender. Genetic information to determine cause of CCD was not collected for this study.MRI scanning was performed using the same parameters and cohort of BTBR × C57 N2 adult mice as described in Human participants underwent MRI at the Centre for Advanced Imaging (The University of Queensland) using a 7 Tesla Siemens Magnetom whole-body MRI scanner. Structural MRI data was acquired as described previously : at 7 T,Commissure and brain sizes were measured in OsiriX v 5.8.5; , blind tImmunohistochemistry was performed on 50 μm tissue sections as previously described . PrimaryDraxin mRNA in wildtype CD1 mice, the Draxin CDS was amplified by PCR using the following primer pairs from the Allen Brain Atlas (CAGGGAGGTTTAGGACAAACAG and TGTAGGAGCTGAGGGAAAGAAG. The Draxin CDS was subsequently cloned into the pGEM-T Vector (Promega USA) and sequences were verified. Digoxygenin-labelled  antisense riboprobes were also generated in a similar manner from the Draxin CDS amplified from BTBR and C57 E15 telencephalic midline tissue using the following primer pairs: CGACAGGGAGAGCCAATG and GTACTGGGCGTACACCTGCT.In situ hybridisation was performed as previously described , with thin Atlas : CAGGGAGDraxin CDS was amplified from BTBR and C57 E15 telencephalic midline tissue using the following primer pairs containing added EcoRI and NotI restriction sites: GAATTCGACAGGGAGAGCCAATG and GCGGCCGCGTACTGGGCGTACACCTGCT. The amplified sequence was digested with EcoRI and NotI and subsequently inserted into the pPBCAG-IRES-GFP (pPBCAGIG) expression plasmid . Images were cropped, sized, and contrast-brightness enhanced for presentation with ImageJ and Photoshop software (Adobe).The ratio of IHF length to total telencephalic midline length was quantified in ImageJ freeware  as previously described . The IHFStatistical tests were performed in GraphPad Prism (v.7 and v.8), and p<0.05 was considered significant. Statistical testing was performed for all quantitative analyses – the relevant statistical test performed, number of biological replicates, and level of significance are described for all quantitative results in figures or their legends, and in  In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:Your manuscript is a comprehensive study of the cellular and genetic mechanisms involved in the diversity of corpus callosum dysgenesis (CCD) phenotypes and associated hippocampal commissure (HC) malformations in humans with pathogenic variants in the DRAXIN receptor, DCC , in comparison to a mouse model with this mutation. This study extends your work over the years revealing that interhemispheric fissure (IHF) fusion is critical for proper formation of the corpus callosum and its failure is the main cause of complete CCD, and that the extent of aberrant IHF remodeling correlates with commissure dysgenesis severity. The range of CC phenotypes and associated HC malformations in the mouse mirror those in humans and are also variable, perhaps related to stochasticity on the mechanisms involved, or to the dependency on other allelic variants. In all, this is a fine study.Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Huda Zoghbi as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Cecilia Flores (Reviewer #1); Thomas Pratt (Reviewer #2).Thank you for submitting your article "DRAXIN regulates interhemispheric fissure remodelling to influence the extent of corpus callosum formation" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.eLife but that some conclusions require a modest amount of additional new data, as they do with your paper, we are asking that the manuscript be revised to either limit claims to those supported by data in hand, or to explicitly state that the relevant conclusions require additional supporting data.We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, when editors judge that a submitted work as a whole belongs in eLife, either of which would be linked to the original paper.Our expectation is that the authors will eventually carry out the additional experiments and report on how they affect the relevant conclusions either in a preprint on bioRxiv or medRxiv, or if appropriate, as a Research Advance in Summary:Your manuscript is an excellent account of the cellular and genetic mechanisms involved in the diversity of corpus callosum dysgenesis (CCD) phenotypes in humans and in a mouse model. Your work over the years has revealed that interhemispheric fissure (IHF) fusion is critical for proper formation of the callosum and its failure is the main cause of complete CCD. Here you nicely show that the extent of aberrant interhemispheric fissure (IHF) remodeling does in fact correlate with commissure dysgenesis severity, in inbred and outcrossed BTBR mouse strains, as well as in humans with partial CCD. The phenotypes in the mouse are very similar to what is found in humans, and also variable, perhaps related to stochasticity on the mechanisms involved, or to the dependency on other allelic variants.You also identify an eight base pair deletion in Draxin and misregulated astroglial and leptomeningeal proliferation as genetic and cellular factors for variable IHF remodelling and CCD in BTBR acallosal strains. The Draxin mutations interrupt the normal remodeling (closing) of interhemispheric fissure necessary for callosal axons to cross. Your study thus places the focus on midline cellular populations and away from axonal navigation as the main source of corpus callosum dysgenesis. The findings are important to understand what mutations cause CCD in humans and how, mechanistically, it occurs.eLife. Suggestions for amendments which were indicated both in the reviews and a Consultation Session with the reviewers, and include:The reviewers agreed that the data and experiments as they stand are sufficient for publication in Revisions for this paper:1. Draxin mutations interrupt the normal remodeling (closing) of interhemispheric fissure necessary for callosal axons to cross. One question is how, cellularly or molecularly, Draxin implements glial and leptomeningeal cells remodel the interhemispheric fissure. Proliferation by itself as shown in Figure 8 does not seem to explain the phenotypes. The model that you are proposing is not fully clear. Does Draxin affect cell-cell adhesion, cell-cell signaling, membrane processes, metaloproteinase activity? You could allude to these possibilities in the discussion.2. Reviewer 2 asks that the human data be more clearly integrated into the rest of the study. The phenotypes in the mouse are very similar to what is found in humans, and also variable, perhaps related to stochasticity on the mechanisms involved, or to the dependency on other allelic variants. MRI scans of human subjects with a spectrum of CC abnormalities, in addition, shows that commissure abnormalities correlate with midline fusion defects. The human data rely on adult phenotypes and do not relate to Draxin and although it is interesting in itself it gives little insight into the embryonic mechanisms that are so nicely explored in the mouse part of the study. In my opinion, the data should be included but the text in the Results and Discussion to better blend these two aspects.3. The reviewers thought that the use of BTBR x C57 N2 crosses where commissure phenotype is correlated with the Draxin mutation  is a nice illustration of unpicking variable penetrance. However, the description of the findings that prompted you to investigate the role of Draxin in CCD needs to be clearer.Also, It seems that the Draxin deletion does not affect HC formation. However, in the Results section you state that "To investigate how DRAXIN regulates CC and HC formation…". This is confusing. Also, it appears that the effect varies between BTRB mice and the BTRB x C57 cross, but this is not discussed clearly. One solution is to move the Draxin findings to the next to the lat last part of the Results, before the human results.eLife on Dcc and Netrin1 regulating intrahemispheric fusion and the midline zipper glia.4. As Reviewing Editor: You say that contrary to published evidence on Draxin as a known regulator of axon guidance, "Draxin was not found to regulate axon guidance in this context, but rather impacted the proliferation of astroglia and leptomeninges; two cell populations that are also not yet considered to play a major role in formation of commissures". And "while pathogenic variants in DRAXIN have not yet been reported in human individuals with CCD, a similar effect may underlie the spectrum of phenotypes observed in humans with DCC mutations, since Dcc and Draxin have been demonstrated to interact to determine the severity of CCD in mice ". In the Introduction and/or in the Discussion it would be welcome to mention the relationship of Draxin to DCC as receptors for Netrin , as well as your other submitted study that is on BioRxiv and submitted to 5. Statistics:a. For Figure 1, there is very little information about statistical analysis. For figure 1 C, it needs to be explained why the Welsh test was used instead of a one-way ANOVA. The errors on the bars do not seem to correspond to SEM; this needs to be clarified.b. For Figures 3 G and H, if the data are presented in single graphs, it is not clear why unpaired t tests or Mann-Whitney tests were conducted (instead of ANOVAs). Why a non-parametric test was used is not explained.c. Some of the data are not normally distributed  so it is not appropriate to show standard errors (the SEM bars could simply be removed), a non-parametic Kruskal-Wallis ANOVA has been used which is appropriate.Revisions expected in follow-up work:1. You could perform additional experiments on the glial cells in which Draxin is expressed, to better understand mechanism.2. A central contention of this study is that variable penetrance of the commissure phenotypes in the BTBR x C57 mice stems from an earlier midline fusion phenotype. It would have been useful to discern whether the (embryonic) midline fusion phenotype also showed the same partial penetrance in BTBR x C57 mice, perhaps also correlated with the WT/MUT Draxin alleles . This would be a testable prediction of the hypothesis that midline fusion mediates the Draxin phenotype. Revisions for this paper:1. Draxin mutations interrupt the normal remodeling (closing) of interhemispheric fissure necessary for callosal axons to cross. One question is how, cellularly or molecularly, Draxin implements glial and leptomeningeal cells remodel the interhemispheric fissure. Proliferation by itself as shown in Figure 8 does not seem to explain the phenotypes. The model that you are proposing is not fully clear. Does Draxin affect cell-cell adhesion, cell-cell signaling, membrane processes, metaloproteinase activity? You could allude to these possibilities in the discussion.Our current model is that IHF remodelling is a multi-step process involving (1) the generation and specification of MZG; (2) anchoring and extension of their (MZG) radial glial processes to the third ventricle  and to the IHF pial surface ; (3) MZG migration via somal translocation to the IHF; (4) MZG differentiation into multipolar astrocytes, including the elaboration of processes that penetrate the fissure; (5) the elimination of the leptomeninges and intervening cells within the fissure and finally; (6) the midline crossing of callosal and hippocampal commissure axons. Most of these steps are disrupted in the absence of DRAXIN, but we propose that the greatest impact on the overall phenotype of BTBR mice comes from its regulation of the earliest steps of IHF remodelling (steps 1-3). More MZG are generated early in development which accumulate at the third ventricle and migrate a shorter distance along the midline pial surface. These cells also have disorganised Nestin-positive radial processes, attached to an enlarged fissure that is filled with more leptomeningeal cells that increase their proliferation at early stages in the BTBR mouse.Comparing these data with those in DCC/NTN1 mutant mice (see our companion paper), DRAXIN may mediate steps 2-5 above via DCC signalling, but since DCC/NTN1 mutant mice do not show disrupted cellular proliferation of MZG or an expanded IHF, these effects must be mediated via a different pathway, such as by antagonizing canonical WNT signalling to elicit these effects.Draxin mutation model and Draxin knockout mice, as well as to further clarify our model while also discussing other potential mechanisms. We have modified our schemas in figure 8L and 8M to better explain this model.We have modified the discussion on pages 19-21 to draw parallels between the phenotype of our BTBR 2. Reviewer 2 asks that the human data be more clearly integrated into the rest of the study. The phenotypes in the mouse are very similar to what is found in humans, and also variable, perhaps related to stochasticity on the mechanisms involved, or to the dependency on other allelic variants. MRI scans of human subjects with a spectrum of CC abnormalities, in addition, shows that commissure abnormalities correlate with midline fusion defects. The human data rely on adult phenotypes and do not relate to Draxin and although it is interesting in itself it gives little insight into the embryonic mechanisms that are so nicely explored in the mouse part of the study. In my opinion, the data should be included but the text in the Results and Discussion to better blend these two aspects.We undertook a substantive rewrite of the results and discussion to better integrate the findings from human and mouse data. As indicated, we:– Clarified the rationale for studying humans with partial CCD in the Results section on page 13.– Rewrote the first paragraph of the discussion to explicitly outline the potential aetiological link between our findings in mice and humans (page 18).– Now outline the link between the neuroanatomy of human adults with CCD and possible embryonic development scenarios of the corpus callosum in the second discussion paragraph (page 18). Moreover, we also reference our findings from the mice (and previous studies in humans/mice) to strengthen and blend the adult/embryonic findings. Three references were added to the reference list on page 22 .Draxin mutation is a driver of these phenotypes in our third discussion paragraph (page 19). We draw on further evidence from other mouse models to support this. We then discuss how the variability in phenotype is likely due to other environmental and genetic influences (one candidate being DCC) and how this relates to what we observe in humans with CC malformations and DCC mutations.– Discuss the implications that the 3. The reviewers thought that the use of BTBR x C57 N2 crosses where commissure phenotype is correlated with the Draxin mutation  is a nice illustration of unpicking variable penetrance. However, the description of the findings that prompted you to investigate the role of Draxin in CCD needs to be clearer.Also, It seems that the Draxin deletion does not affect HC formation. However, in the Results section you state that "To investigate how DRAXIN regulates CC and HC formation…". This is confusing. Also, it appears that the effect varies between BTRB mice and the BTRB x C57 cross, but this is not discussed clearly. One solution is to move the Draxin findings to the next to the lat last part of the Results, before the human results.We thank the reviewers for these suggestions and have made the following additions:Draxin as a favourable candidate gene that is located at the chromosome 4 locus identified in our previous study , since Draxin is known to regulate both CC and HC formation in mice (page 4).– We introduce Draxin mutation allele, HC length was significantly reduced when the Draxin mutation was homozygous. We previously showed that IHF remodelling proceeds in a ventral to dorsal direction . Thus, we believe this explains why HC length is a more sensitive measure (than HC area) of abnormal HC development due to the loss of IHF remodelling, which occurs when Draxin is mutated. The HC length data was originally in the supplementary figure, but we have now moved it to the main figure 5, and removed the HC area data from the manuscript. This required updating of the figure legend on page 33 and the results text on pages 14-15.– While we showed that HC cross-sectional area was not significantly correlated with SNP allele composition or the 4. As Reviewing Editor: You say that contrary to published evidence on Draxin as a known regulator of axon guidance, "Draxin was not found to regulate axon guidance in this context, but rather impacted the proliferation of astroglia and leptomeninges; two cell populations that are also not yet considered to play a major role in formation of commissures". And "while pathogenic variants in DRAXIN have not yet been reported in human individuals with CCD, a similar effect may underlie the spectrum of phenotypes observed in humans with DCC mutations, since Dcc and Draxin have been demonstrated to interact to determine the severity of CCD in mice ". In the Introduction and/or in the Discussion it would be welcome to mention the relationship of Draxin to DCC as receptors for Netrin , as well as your other submitted study that is on BioRxiv and submitted to eLife on Dcc and Netrin1 regulating intrahemispheric fusion and the midline zipper glia.Draxin as a candidate gene that is known to regulate DCC signalling in the introduction on page 4 and included discussion of our companion paper on page 19 . We included our companion paper in the reference list on page 24.We have now introduced 5. Statistics:a. For Figure 1, there is very little information about statistical analysis. For figure 1 C, it needs to be explained why the Welsh test was used instead of a one-way ANOVA. The errors on the bars do not seem to correspond to SEM; this needs to be clarified.The reviewer is correct that the error bars were indeed representing standard deviation instead of SEM as stated in the figure legend – the error bars have been corrected to show SEM. We agree that a one-way ANOVA would be appropriate as all CCD groups shown in Figure 1C passed the D’Agostino and Pearson test for normality. The figure  has been amended to reflect the minor changes in statistical significance and the figure legend (page 27) has been updated. We have also described more clearly our statistical methods (page 10) and updated our supplementary statistics table .b. For Figures 3 G and H, if the data are presented in single graphs, it is not clear why unpaired t tests or Mann-Whitney tests were conducted (instead of ANOVAs). Why a non-parametric test was used is not explained.We chose unpaired t tests or Mann-Whitney tests and not the ANOVA because the data in these graphs are from two groups (control and pCCD), and not from three or more unrelated or independent observation. We have made clear in our methods that we choose our statistical tests based on whether they pass a normality test (page 10).c. Some of the data are not normally distributed  so it is not appropriate to show standard errors (the SEM bars could simply be removed), a non-parametic Kruskal-Wallis ANOVA has been used which is appropriate.We choose to show standard error of the mean since it depicts where the mean of the group should fall if the data was sampled again an infinite number of times. We feel this is informative, since even when the data is not normally distributed, it demonstrates where the mean of the population (rather than just one sample) would fall. The calculation of the standard error of the mean is based on the variance in the sample itself and the distribution of this variance does not have to be normally distributed for this to be accurate. We have not made any changes.Revisions expected in follow-up work:1. You could perform additional experiments on the glial cells in which Draxin is expressed, to better understand mechanism.We appreciate that this is a central question that remains from our study. There are a number of technical issues that do not make this possible in the short term. Firstly, we have not found a feasible system for ease of manipulation of genes in these glia. We have not found a Cre-expressing transgenic-line that is well expressed in these cells, that is not otherwise expressed in all progenitors in the forebrain. We have not yet been able to efficiently isolate and dissociate these cells into a culture system, since they become reactive and revert to a progenitor state. In slice culture, these glia also become reactive and do not behave in an in vivo state. We have had some success with in utero electroporation of the progenitors of these cells before, but have had issues with efficiency of knockdown of proteins in sufficient time to have an effect. We have been working on developing a better experimental paradigm to study these glia in more depth. We would like to perform single cell sequencing on these glia in order to identify candidate genes that are enriched in MZG to develop cell-specific driver lines for these cells.2. A central contention of this study is that variable penetrance of the commissure phenotypes in the BTBR x C57 mice stems from an earlier midline fusion phenotype. It would have been useful to discern whether the (embryonic) midline fusion phenotype also showed the same partial penetrance in BTBR x C57 mice, perhaps also correlated with the WT/MUT Draxin alleles . This would be a testable prediction of the hypothesis that midline fusion mediates the Draxin phenotype.We have considered this experiment, but our current data suggest there are unpredictable variables  that would limit the accuracy of testing this hypothesis. Given the incomplete penetrance of complete and partial CCD in the BTBR x C57 N2 cross, it is not possible to predict on an individual animal level, based on genotype, the final postnatal CC phenotype. It follows that the way in which we would test this hypothesis is to determine whether the ratios of CCD phenotypes detected postnatally  correspond to similar ratios of embryonic cellular phenotypes . This presupposes that the measurable cellular phenotypes in embryos can be disaggregated into categorical variables, or clearly delineated quantitative measures, which correspond to adult phenotypes. Given the multifactorial nature of CCD in this model, which could incorporate multiple modulatory genetic factors , and multiple cellular factors , we anticipate that such a neat outcome would be unlikely and any measures of cellular phenotypes for a given genotype will fall into a distribution without clear boundaries between expected subgroups. We would anticipate that there would indeed be cut-offs within this cellular phenotype distribution which correspond to final callosal phenotype, but these would need to be inferred from the ratios observed from the final genotypes, and so the logic in identifying these would be circular. A final consideration is that the number of mice required for testing the hypothesis with this number of expected variables is expected to be in the hundreds.


The occurrence of hydrogen atom-ordered form of ice Ih, ice XI, in the outer Solar System has been discussed based on laboratory experiments because its ferroelectricity influences the physical processes in the outer Solar System. However, the formation of ice XI in that region is still unknown due to a lack of formation conditions at temperatures higher than 72 K and the effect of UV-rays on the phase transition from ice I to ice XI. As a result, we observed the UV-irradiation process on ice Ih and ice Ic using a newly developed ultra-high vacuum cryogenic transmission electron microscope. We found that ice Ih transformed to ice XI at temperatures between 75 and 140 K with a relatively small UV dose. Although ice Ic partially transformed to ice XI at 83 K, the rate of transformation was slower than for ice Ih. These findings point to the formation of ice XI at temperatures greater than 72 K via UV irradiation of ice I crystals in the Solar System; icy grains and the surfaces of icy satellites in the Jovian and Saturnian regions. At temperatures lower than 72 K, the hydrogen atom-ordered form of ice Ih, ice XI, becomes a thermodynamically stable phase . As a meon e.g., . When am− ions, derived from KOH, substitute H2O sites and speeds up the phase transition even at 70 K. Neutron diffraction studies have been carried out extensively for the structural analysis of ice XI to locate the position of H (D) atoms  cryo-TEM with UV sources to study the phase transition of ices in space is highly desirable.As demonstrated by some researchers that cryo-TEM is powerful apparatus to investigate the phase transitions between ice polymorphs e.g., . Howeverin situ deposition and observation of ices and related materials following We developed a 200-kV UHV-TEM  for 6 electron gun, 75 L/s IP and ∼400 L/s Ti-sublimation pump (TSP) for CM and stage/OL, 20 L/s IP for CL and IL/PL, and 340 L/s turbo-molecular pump  for a camera, are used. For roughening evacuation of the column, another same TMP2 is used. Although we used ultra-low vibration type TMPs (TMP1 and TMP2), three dumpers in tandem are used between the column and TMP to minimize the effect of vibration from TMP.A microscope column is consisting of six chambers as shown in 2 should be put in two shrouds. About 1 hour before TEM operation, TSPs should be operated for few minutes. In this case, pressure attained is around ∼2 × 10–7 Pa. When such UHV is not necessary (∼1 × 10–6 Pa), a simple operation using only IPs could be applied. In this case, we could use the TEM every day without baking. Because the IPs used in the TEM column could not evacuate rare gases and methane, TMP2 is used as the main pump instead of IPs when rare gases or methane are observed. A nude ionization gauge  mounted between the OL chamber and the IP4/TSP measures pressure near the stage. A sample was surrounded by a liquid nitrogen shroud. Another shroud was put beneath the lower pole piece. Therefore, real pressure near the specimen is lower than measured pressure.We could operate TEM by the combination of these pumps depending on the purpose of experiments and the kind of gases used. When UHV is needed, TEM should be operated as follows. After baking at around 100°C for at least 3 days with the operation of TMPs, IPs should be operated for 3 days, then liquid Nin situ studies as shown in 3 gas bottles, a diaphragm gauge , and a glass tube containing liquid water. To eliminate vibration from TMP3, another TMP  is connected to a thin wall vacuum flexible tube . Between a stop valve and the flexible tube, a homemade PTFE center ring with Viton O-ring and a plastic clump  are used for the electrical isolation. The other two ports are now used as a UV lamp  and a quadrupole mass spectrometer. Before setting the lamp to TEM, the UV flux was measured in advance using another vacuum chamber to be ∼2 × 1013 photons cm−2 s−1. UV-rays from the D2 lamp were collimated using a mirror-finished pure Al collimator.Three ICF 70 ports are directed at the sample surface with an incident angle of 55°, which are used as We used a commercially available liquid-He cooling holder  for specimen cooling. Because this holder is not made for use in UHV-TEM, the pressure of TEM increased gradually due to the tiny leak of the holder. TMP3 continuously evacuates the holder except during observation , 2, allo2 is used instead of liquid-He, the minimum temperature attained is about 70 K, and the duration of cooling is about 3 hours. In this case, the diaphragm pump in When we observe constant temperature, e.g., at 10 and 20 K, we could operate for around 70 and 90 min using fully contained with liquid-He, respectively. In this case, the temperature is mainly controlled by the flow rate of He gas with additional use of the heater . When a 2. At low temperatures, such as 10–20 K, the temperature difference between the specimen and the temperature sensor is around 3 K (the temperature of the specimen is higher than the temperature sensor), and at high temperatures, such as 30 K, there is almost no temperature difference. Errors of temperature measurement at 10–30 K and >30 K are about ±1.2 K and ±0.5 K, respectively.Because the heater and a temperature sensor are not in the same position as the specimen, the temperature of the specimen differs from that of the sensor. The temperature of the specimen is calibrated using vapor pressures of crystalline Ne, CO, Ar, and CO3 W m−1 K−1  were used as the substrate for the sample deposition because of the following reasons: 1) Thermal conductivity of the Si single crystal at 10–200 K is larger than 10 m−1 K−1  and a-Si2 were deposited onto ice. This enabled us to adjust focus on the surface side as shown in We measured the thickness of the ice samples by the method shown in 2O was deposited at lower temperatures than 100 K, we could measure the thickness of the samples as described in section 2.3.1, because the sticking coefficient of H2O vapor onto the substrate is almost unity under the pressure of ∼1 × 10–6 Pa, and because the sample is uniform film. For the deposition of ice Ih and Ic, temperatures of the substrate should be >150 K, and ∼140 K, respectively. H2O vapor does not condense such high temperatures under the pressure of ∼1 × 10–6 Pa , and low-magnification observation . We could not see any image on the fluorescent screen when the electron beam intensity was this low. Using a CCD camera , we were able to observe TEM images as well as electron diffraction patterns. All electron diffraction patterns were collected in the central 700-nm circular region of TEM images. We only observed samples at 5–15 min intervals while they were being exposed to UV light. Electron diffraction patterns were indexed by comparison with ice Ih , the TEM image shows that the area where ice is present has increased, implying that the heights of islands have decreased while their area has increased (16 photons cm−2) than 75 K as shown in ncreased . The samncreased . Additioncreased , which c17 photons cm−2), 131 diffraction spots of ice XI were observed  consists of a Lyman-α (122 nm) and molecular D2 emission bands (115–400 nm). Qualitatively similar UV absorption spectra were reported for ice Ih and amorphous H2O  in the 120–165 nm (10.33–7.51 eV) spectral region. Hence, the optical depth of Lyman-α photons is about 63 nm, considering a typical density of crystalline ice (0.92 g cm−3), the mean molecular mass of H2O (18.015 g mol−1), and Avogadro constant (6.0221 × 1023 mol−1) (Photoionization of water ice has a wavelength dependence . The emihous H2O . Cruz-Di3 mol−1) . The opt2, O2, and H2O2) and their yields, reaction mechanisms, and energy partitioning in the reaction products are reviewed by in situ TEM study focuses on this topic. Details of the photolysis of water ice such as identification of photoproducts  for 10–60 min (1.2–7.2 × 1016 photons cm−2). 18 photons cm−2 dose. UV-induced amorphization of ice Ih has yet to be studied experimentally, in part due to the difficulty of preparing pure ice Ih using the vapor-deposition method in UHV conditions, but it is likely to occur at low temperatures as ice Ic, given the small energy difference between ices Ic and Ih (13–160 J mol−1 (0.1–1.7 meV) depending on measurements) (rements) .Ice Ih 17 photons cm−2.16 photons cm−2) at the temperature range of 75–140 K.Moreover, it is found that ice XI can be more easily formed from ice Ih by UV-irradiation (4 × 10Schemes (3) and (4) are novel routes for the formation of ice XI at temperatures above 72 K, that is, the phase boundary between ices Ih and XI . More ef2O into ice Ih in the laboratory (>140 K). The phase transition from ice Ic to ice Ih and ice XI was not positively confirmed at high temperatures of 100–140 K (trace amounts of ice Ih were detected), implying that the photoirradiation lattice structure can be thermally recovered to the original ice Ic structure. In this study, UV-irradiation experiments on ice Ih failed to positively confirm the stacking fault (it was below the detection limit). This suggests that the reverse change of stacking sequence of oxygen layer from ABABAB (ices Ih and XI) to ABCABC (ice Ic) is inefficient by UV irradiation at 75–140 K, i.e., scheme (5).Although scheme (3) is relatively inefficient compared with scheme (4), the occurrence of scheme (3) indicates that UV photons can induce the non-thermal crystallization, that is, the change of stacking sequence of oxygen layer from ABCABC of ice Ic to ABABAB of ice Ih and ice XI at 83 K, which is well below the thermal crystallization temperature of a-HNon-observation of ice Ic from ice Ih at 140 K also indirectly implies that ice Ih is not amorphized efficiently by UV photons, because amorphized ice can be thermally crystallized to ice Ic at 140 K, i.e., scheme (6).Thus, the phase transition to ice XI from ice Ih, scheme (4), may directly occur by the re-orientation of water molecules without involving the change of lattice structure at least at 140 K.− ions are considered to increase the mobility of protons. 2O ice XI using a low level (0.001 M) of KOD-doped D2O ice, which corresponds to the molar ratio of KOD/D2O = 1/52,800. They reported that the mass ratio of D2O ice XI to the KOD-doped ice Ih reached 0.59 after waiting for 135.30 h at 70 K. This means that over 30,000 water molecules were aligned around one OD− ion and the average distance between an OD− ion should be about 12 nm  was often used e.g., , becauseut 12 nm . The exp2O is 12.6 eV in the gas phase, whereas low-energy photoionization of water ice is reported, as observed in water clusters and liquid water molecules  defects on water ice following UV irradiation with an rf-powered Kr lamp having two emission spectral peaks at 10.03 and 10.64 eV. The population of produced H3O+ defects was reported to be about 1% of water molecules in amorphous ice at 55 K after UV irradiation of greater than 1.5 × 1016 photons cm−2. The production yield for the H3O+ defects is estimated as 7.1 × 10–3 photon−1 (16 photons cm−2) and ice Ic (∼2 × 1017 photons cm−2) are close to that for the saturation of the H3O+ defect formation in 16 photons cm−2), a similar amount (1% of water molecules) of the H3O+ defects can exist in the present ice samples. Therefore, although − in photolyzed ice, if a similar amount of the OH− defects to the H3O+ defects (1% of water molecules) is formed upon UV irradiation, it should be sufficiently large for the promotion of the ice XI transformation  and ice Ic (∼2 × 1017 photons cm−2) measured in the present study. Therefore, we conclude that the phase change from the ice I to ice XI by the UV-rays from the protosun occurred in the Jovian region within 106 years.Interstellar grains in molecular clouds consist of silicate, organic material, and a-Hn region . In the ly ∼40 K , and bec17 years . Equilibdiameter , corresp4 electrons nm−2 (0.2 MeV electron) or 107 electrons nm−2 (2 MeV electron). They suggested that the formation of ice XI might readily occur in space because 0.2–2 MeV electrons mimic cosmic rays. However, their conclusion is not correct, because the flux of 1 MeV cosmic rays is only 1 cm−2 s−1. To attain the doses of 104 nm−2 (= 1018 cm−2) and 107 nm−2 (= 1021 cm−2), irradiation times of 3 × 1010 years and 3 × 1013 years, respectively, should be needed in space. In addition, their experiments did not mimic irradiation of secondary electrons by 1 MeV H+, because the energy of secondary electrons is only ∼1 keV. We, therefore, conclude that experiments performed by Here, it should be noted the effect of cosmic ray irradiation on the formation of ice XI. The formation of ferroelectric  ice have been reported, when ice films were deposited on the Pt(111) at temperatures between 40 K and nearly 150 K e.g., . Su et a2O do not show uniformly-covered ice layer on the substrates but three-dimensional islands. They also suggested that there is only one ice polyhedral crystal on refractory grain, and the ice crystal should be in its equilibrium form. This is because the wetting of ice I crystals against all substrates is bad and because the surface diffusion coefficient of H2O on these substrates is large enough.Because the formation of ice XI would occur only in the Jovian region as discussed in the previous section, we will discuss the collision of grains covered with ice XI. To depict the morphology of ice XI on refractory grains, we must first determine the equilibrium form of ice XI. However, no research has been conducted on the equilibrium form of ice XI. As a result, we assume that the equilibrium form of ice XI is the same as that of ice Ih: a hexagonal prism with two basal faces (0001) and six prism faces (10-10).Aggregation of the icy grains leads to the formation of embryos of planets, planetesimals, through protoplanets to Jovian planets and icy satellites. For some reason, nebular gas dissipated after the formation of Jovian planets, resulting in strong UV-ray irradiation from the Sun onto the surface of icy satellites. Because of the strong magnetic fields of the Jovian planets, a magnetosphere formed. The interiors of icy satellites were heated by accretion energy, radiogenic heating, tidal heating, and other means e.g., . As a re9 photons cm−2 s−1  or 1021 e− cm−2 (2 MeV electron). These doses correspond to irradiation times of 3 × 102 years and 3 × 106 years, respectively. The present study showed that the critical UV-rays dose onto ice Ih was one order smaller than that onto ice Ic. We, therefore, suggest in the case of electron irradiation that the critical dose for the formation of ice XI onto ice Ih might be smaller than that onto ice Ic. The penetration depths of 0.2 and 2 MeV electrons are calculated to be 0.04 and 1 cm, respectively, using the ESTAR program (High-energy electron irradiation in the magnetosphere of Jovian planets leads to similar results to UV-irradiation. High-energy electron fluxes of 0.2 and 2 MeV around Europa are in order of 10y, e.g., . Kobayas program , which p program , the sur8 protons cm−2 s−1, (e.g., Because the flux of ∼1 MeV protons around the Europa is 101, e.g., , and bec1, e.g., , proton 1, e.g., . However


Craniotomy, cranioplasty, and craniofacial procedures may involve reoperation for additional treatment of the primary pathological condition or treatment of complications, requiring removal of previously placed hardware. During removal of the titanium hardware, there is a risk of losing, dropping, or misplacing the titanium screws because of their small size. There are also instances of difficulty disengaging the screw from the screwdriver. We describe the use of a plastic specimen cup in retrieving titanium screws after detaching them from the screwdriver by screwing the screw into the cup, thus rapidly and safely securing and storing screws for collection/discarding or possible reuse. When the empty screwdriver is used to retrieve and unscrew the titanium screw from the cranial flap or the skull bone, a plastic specimen cup should be placed adjacent to the site of screw removal. Once the screw is removed, while it is still fastened to the screwdriver, it is immediately re-screwed and secured onto the base of the plastic specimen cup, which is then placed into a second plastic specimen cup. This method prevents misplacement or dropping of the screw that may otherwise occur when manipulating the screw on or off the screwdriver and avoids perforating the surgeon’s glove during handling. We describe the adjunctive use of a plastic specimen cup when removing cranial screws and hardware to rapidly and safely detach the screw and prevent the misplacement, dropping, or loss of screws intraoperatively that results in additional operative time and personnel assistance. Cranioplasty procedures are associated with reoperation and complication rates ranging from 2% to 50% -5. RecurRationaleWhen a cranioplasty or craniofacial hardware revision takes place, the titanium or metal hardware screws need to be removed to subsequently remove the securing plates and ultimately the cranioplasty flap or bone. The first step to this procedure is removing the titanium screws; given a non-resorbable neuro-plating system was utilized . From thMethodWe present the simple use of a sterile plastic collection cup to be positioned next to the open cranial wound prior to the removal of screws to prevent the complication of lost or misplaced neuro-plating screws. When the screw is removed from its secure position within the cranial flap or the skull, the screw, while attached to the screwdriver, is immediately then screwed into the base of the plastic specimen cup Figure , disengaThe use of titanium hardware in securing bone and cranioplasty flaps to the native skull was initially described in the 1990s ,8. TitanCranioplasty procedures involving removal and replacement of bone carry a complication rate of 2-50% ,2. ComplWith the current widespread use of titanium craniofacial plates and screws for cranial procedures, there is a risk of losing or misplacing the titanium screws during the initial surgery or when patients need to undergo revision or redo surgery. As mentioned, this may result in prolonging the surgery and anesthesia time for the patient as well as additional radiation exposure to the patient if intraoperative skull fluoroscopy is needed to exclude misplacement of the hardware intracranially. To best avoid such complications and danger to the patient, we provided a simple method to rapidly collect and secure titanium screws when removed from the skull during cases such as cranial revision surgery. By collecting the screws in a plastic specimen cup, not only can they be reused but they can also be easily counted by the surgical technician at the end of the case, which could also aid in the closure of the case.During cranioplasty or craniofacial hardware revision, titanium or metal hardware screws need to be removed to remove the underlying plate, cranioplasty flap, or bone, and from the time the screw is removed to transfer to the surgical technician, the screw may drop out of place or it may be mishandled. We describe the adjunctive use of a plastic specimen cup when removing cranial screws and hardware to prevent the misplacement, dropping, and loss of screws intraoperatively, which also provides an opportunity for screws to be reloaded to an empty screwdriver for possible reuse. This method prevents the loss of screws intraoperatively after removal in hopes to save anesthesia and surgery time and prevent complications by avoiding misplacement of hardware intracranially.