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1. Biallelic CRELD1 variants cause a multisystem syndrome, including neurodevelopmental phenotypes, cardiac dysrhythmias, and frequent infections

Author

Borras, Silvia, Clark, Caroline, Dean, John, Miedzybrodzka, Zosia, Ross, Alison, Tennant, Stephen, Dabir, Tabib, Donnelly, Deirdre, Humphreys, Mervyn, Magee, Alex, McConnell, Vivienne, McKee, Shane, McNerlan, Susan, Morrison, Patrick J., Rea, Gillian, Stewart, Fiona, Cole, Trevor, Cooper, Nicola, Cooper-Charles, Lisa, Cox, Helen, Islam, Lily, Jarvis, Joanna, Keelagher, Rebecca, Lim, Derek, McMullan, Dominic, Morton, Jenny, Naik, Swati, O’Driscoll, Mary, Ong, Kai-Ren, Osio, Deborah, Ragge, Nicola, Turton, Sarah, Vogt, Julie, Williams, Denise, Bodek, Simon, Donaldson, Alan, Hills, Alison, Low, Karen, Newbury-Ecob, Ruth, Norman, Andrew M., Roberts, Eileen, Scurr, Ingrid, Smithson, Sarah, Tooley, Madeleine, Abbs, Steve, Armstrong, Ruth, Dunn, Carolyn, Holden, Simon, Park, Soo-Mi, Paterson, Joan, Raymond, Lucy, Reid, Evan, Sandford, Richard, Simonic, Ingrid, Tischkowitz, Marc, Woods, Geoff, Bradley, Lisa, Comerford, Joanne, Green, Andrew, Lynch, Sally, McQuaid, Shirley, Mullaney, Brendan, Berg, Jonathan, Goudie, David, Mavrak, Eleni, McLean, Joanne, McWilliam, Catherine, Reavey, Eleanor, Azam, Tara, Cleary, Elaine, Jackson, Andrew, Lam, Wayne, Lampe, Anne, Moore, David, Porteous, Mary, Baple, Emma, Baptista, Júlia, Brewer, Carole, Castle, Bruce, Kivuva, Emma, Owens, Martina, Rankin, Julia, Shaw-Smith, Charles, Turner, Claire, Turnpenny, Peter, Tysoe, Carolyn, Bradley, Therese, Davidson, Rosemarie, Gardiner, Carol, Joss, Shelagh, Kinning, Esther, Longman, Cheryl, McGowan, Ruth, Murday, Victoria, Pilz, Daniela, Tobias, Edward, Whiteford, Margo, Williams, Nicola, Barnicoat, Angela, Clement, Emma, Faravelli, Francesca, Hurst, Jane, Jenkins, Lucy, Jones, Wendy, Ajith Kumar, V.K., Lees, Melissa, Loughlin, Sam, Male, Alison, Morrogh, Deborah, Rosser, Elisabeth, Scott, Richard, Wilson, Louise, Beleza, Ana, Deshpande, Charu, Flinter, Frances, Holder, Muriel, Irving, Melita, Izatt, Louise, Josifova, Dragana, Mohammed, Shehla, Molenda, Aneta, Robert, Leema, Roworth, Wendy, Ruddy, Deborah, Ryten, Mina, Yau, Shu, Bennett, Christopher, Blyth, Moira, Campbell, Jennifer, Coates, Andrea, Dobbie, Angus, Hewitt, Sarah, Hobson, Emma, Jackson, Eilidh, Jewell, Rosalyn, Kraus, Alison, Prescott, Katrina, Sheridan, Eamonn, Thomson, Jenny, Bradshaw, Kirsty, Dixit, Abhijit, Eason, Jacqueline, Haines, Rebecca, Harrison, Rachel, Mutch, Stacey, Sarkar, Ajoy, Searle, Claire, Shannon, Nora, Sharif, Abid, Suri, Mohnish, Vasudevan, Pradeep, Canham, Natalie, Ellis, Ian, Greenhalgh, Lynn, Howard, Emma, Stinton, Victoria, Swale, Andrew, Weber, Astrid, Banka, Siddharth, Breen, Catherine, Briggs, Tracy, Burkitt-Wright, Emma, Chandler, Kate, Clayton-Smith, Jill, Donnai, Dian, Douzgou, Sofia, Gaunt, Lorraine, Jones, Elizabeth, Kerr, Bronwyn, Langley, Claire, Metcalfe, Kay, Smith, Audrey, Wright, Ronnie, Bourn, David, Burn, John, Fisher, Richard, Hellens, Steve, Henderson, Alex, Montgomery, Tara, Splitt, Miranda, Straub, Volker, Wright, Michael, Zwolinski, Simon, Allen, Zoe, Bernhard, Birgitta, Brady, Angela, Brooks, Claire, Busby, Louise, Clowes, Virginia, Ghali, Neeti, Holder, Susan, Ibitoye, Rita, Wakeling, Emma, Blair, Edward, Carmichael, Jenny, Cilliers, Deirdre, Clasper, Susan, Gibbons, Richard, Kini, Usha, Lester, Tracy, Nemeth, Andrea, Poulton, Joanna, Price, Sue, Shears, Debbie, Stewart, Helen, Wilkie, Andrew, Albaba, Shadi, Baker, Duncan, Balasubramanian, Meena, Johnson, Diana, Parker, Michael, Quarrell, Oliver, Stewart, Alison, Willoughby, Josh, Crosby, Charlene, Elmslie, Frances, Homfray, Tessa, Jin, Huilin, Lahiri, Nayana, Mansour, Sahar, Marks, Karen, McEntagart, Meriel, Saggar, Anand, Tatton-Brown, Kate, Butler, Rachel, Clarke, Angus, Corrin, Sian, Fry, Andrew, Kamath, Arveen, McCann, Emma, Mugalaasi, Hood, Pottinger, Caroline, Procter, Annie, Sampson, Julian, Sansbury, Francis, Varghese, Vinod, Baralle, Diana, Callaway, Alison, Cassidy, Emma J., Daniels, Stacey, Douglas, Andrew, Foulds, Nicola, Hunt, David, Kharbanda, Mira, Lachlan, Katherine, Mercer, Catherine, Side, Lucy, Temple, I. Karen, Wellesley, Diana, Ambrose, J.C., Arumugam, P., Baple, E.L., Bleda, M., Boardman-Pretty, F., Boissiere, J.M., Boustred, C.R., Caulfield, M.J., Chan, G.C., Craig, C.E.H., Daugherty, L.C., de Burca, A., Devereau, A., Elgar, G., Foulger, R.E., Fowler, T., FurióTarí, P., Hackett, J.M., Halai, D., Hamblin, A., Henderson, S., Holman, J.E., Hubbard, T.J.P., Ibáñez, K., Jackson, R., Jones, L.J., Kasperaviciute, D., Kayikci, M., Lahnstein, L., Lawson, K., Leigh, S.E.A., Leong, I.U.S., Lopez, F.J., MaleadyCrowe, F., Mason, J., McDonagh, E.M., Moutsianas, L., Mueller, M., Murugaesu, N., Need, A.C., Odhams, C.A., Patch, C., Perez-Gil, D., Polychronopoulos, D., Pullinger, J., Rahim, T., Rendon, A., Riesgo-Ferreiro, P., Rogers, T., Ryten, M., Savage, K., Sawant, K., Scott, R.H., Siddiq, A., Sieghart, A., Smedley, D., Smith, K.R., Sosinsky, A., Spooner, W., Stevens, H.E., Stuckey, A., Sultana, R., Thomas, E.R.A., Thompson, S.R., Tucci, A., Walsh, E., Watters, S.A., Welland, M.J., Williams, E., Witkowska, K., Acosta, Maria T., Adam, Margaret, Adams, David R., Agrawal, Pankaj B., Alejandro, Mercedes E., Alvey, Justin, Amendola, Laura, Andrews, Ashley, Ashley, Euan A., Azamian, Mahshid S., Bacino, Carlos A., Bademci, Guney, Baker, Eva, Balasubramanyam, Ashok, Baldridge, Dustin, Bale, Jim, Bamshad, Michael, Barbouth, Deborah, Bayrak-Toydemir, Pinar, Beck, Anita, Beggs, Alan H., Behrens, Edward, Bejerano, Gill, Bennet, Jimmy, Berg-Rood, Beverly, Bernstein, Jonathan A., Berry, Gerard T., Bican, Anna, Bivona, Stephanie, Blue, Elizabeth, Bohnsack, John, Bonnenmann, Carsten, Bonner, Devon, Botto, Lorenzo, Boyd, Brenna, Briere, Lauren C., Brokamp, Elly, Brown, Gabrielle, Burke, Elizabeth A., Burrage, Lindsay C., Butte, Manish J., Byers, Peter, Byrd, William E., Carey, John, Carrasquillo, Olveen, Peter Chang, Ta Chen, Chanprasert, Sirisak, Chao, Hsiao-Tuan, Clark, Gary D., Coakley, Terra R., Cobban, Laurel A., Cogan, Joy D., Coggins, Matthew, Cole, F. Sessions, Colley, Heather A., Cooper, Cynthia M., Craigen, William J., Crouse, Andrew B., Cunningham, Michael, D'Souza, Precilla, Dai, Hongzheng, Dasari, Surendra, Davids, Mariska, Dayal, Jyoti G., Deardorff, Matthew, Dell'Angelica, Esteban C., Dhar, Shweta U., Dipple, Katrina, Doherty, Daniel, Dorrani, Naghmeh, Douine, Emilie D., Draper, David D., Duncan, Laura, Earl, Dawn, Eckstein, David J., Emrick, Lisa T., Eng, Christine M., Esteves, Cecilia, Estwick, Tyra, Falk, Marni, Fernandez, Liliana, Ferreira, Carlos, Fieg, Elizabeth L., Findley, Laurie C., Fisher, Paul G., Fogel, Brent L., Forghani, Irman, Fresard, Laure, Gahl, William A., Glass, Ian, Godfrey, Rena A., Golden-Grant, Katie, Goldman, Alica M., Goldstein, David B., Grajewski, Alana, Groden, Catherine A., Gropman, Andrea L., Gutierrez, Irma, Hahn, Sihoun, Hamid, Rizwan, Hanchard, Neil A., Hassey, Kelly, Hayes, Nichole, High, Frances, Hing, Anne, Hisama, Fuki M., Holm, Ingrid A., Hom, Jason, Horike-Pyne, Martha, Huang, Alden, Huang, Yong, Isasi, Rosario, Jamal, Fariha, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Johnston, Jean M., Karaviti, Lefkothea, Kelley, Emily G., Kennedy, Jennifer, Kiley, Dana, Kohane, Isaac S., Kohler, Jennefer N., Krakow, Deborah, Krasnewich, Donna M., Kravets, Elijah, Korrick, Susan, Koziura, Mary, Krier, Joel B., Lalani, Seema R., Lam, Byron, Lam, Christina, Lanpher, Brendan C., Lanza, Ian R., Lau, C. Christopher, LeBlanc, Kimberly, Lee, Brendan H., Lee, Hane, Levitt, Roy, Lewis, Richard A., Lincoln, Sharyn A., Liu, Pengfei, Liu, Xue Zhong, Longo, Nicola, Loo, Sandra K., Loscalzo, Joseph, Maas, Richard L., Macnamara, Ellen F., MacRae, Calum A., Maduro, Valerie V., Majcherska, Marta M., Mak, Bryan, Malicdan, May Christine V., Mamounas, Laura A., Manolio, Teri A., Mao, Rong, Maravilla, Kenneth, Markello, Thomas C., Marom, Ronit, Marth, Gabor, Martin, Beth A., Martin, Martin G., Martínez-Agosto, Julian A., Marwaha, Shruti, McCauley, Jacob, McCormack, Colleen E., McCray, Alexa T., McGee, Elisabeth, Mefford, Heather, Merritt, J. Lawrence, Might, Matthew, Mirzaa, Ghayda, Morava, Eva, Moretti, Paolo M., Morimoto, Marie, Mulvihill, John J., Murdock, David R., Nakano-Okuno, Mariko, Nath, Avi, Nelson, Stan F., Newman, John H., Nicholas, Sarah K., Nickerson, Deborah, Nieves-Rodriguez, Shirley, Novacic, Donna, Oglesbee, Devin, Orengo, James P., Pace, Laura, Pak, Stephen, Pallais, J. Carl, Papp, Jeanette C., Parker, Neil H., Phillips, John A., Posey, Jennifer E., Potocki, Lorraine, Pusey, Barbara N., Quinlan, Aaron, Raskind, Wendy, Raja, Archana N., Rao, Deepak A., Renteria, Genecee, Reuter, Chloe M., Rives, Lynette, Robertson, Amy K., Rodan, Lance H., Rosenfeld, Jill A., Rosenwasser, Natalie, Ruzhnikov, Maura, Sacco, Ralph, Sampson, Jacinda B., Samson, Susan L., Saporta, Mario, Scott, C. Ron, Schaechter, Judy, Schedl, Timothy, Scott, Daryl A., Sharma, Prashant, Shin, Jimann, Signer, Rebecca, Sillari, Catherine H., Silverman, Edwin K., Sinsheimer, Janet S., Sisco, Kathy, Smith, Edward C., Smith, Kevin S., Solem, Emily, Solnica-Krezel, Lilianna, Stoler, Joan M., Stong, Nicholas, Sullivan, Jennifer A., Sun, Angela, Sutton, Shirley, Sweetser, David A., Sybert, Virginia, Tabor, Holly K., Tamburro, Cecelia P., Tekin, Mustafa, Telischi, Fred, Thorson, Willa, Tifft, Cynthia J., Toro, Camilo, Tran, Alyssa A., Tucker, Brianna M., Urv, Tiina K., Vanderver, Adeline, Velinder, Matt, Viskochil, Dave, Vogel, Tiphanie P., Wahl, Colleen E., Wallace, Stephanie, Walley, Nicole M., Walsh, Chris A., Walker, Melissa, Wambach, Jennifer, Wan, Jijun, Wang, Lee-Kai, Wangler, Michael F., Ward, Patricia A., Wegner, Daniel, Wener, Mark, Wenger, Tara, Perry, Katherine Wesseling, Westerfield, Monte, Wheeler, Matthew T., Whitlock, Jordan, Wolfe, Lynne A., Woods, Jeremy D., Yamamoto, Shinya, Yang, John, Yu, Guoyun, Zastrow, Diane B., Zhao, Chunli, Zuchner, Stephan, Jeffries, Lauren, Mis, Emily K., McWalter, Kirsty, Donkervoort, Sandra, Brodsky, Nina N., Carpier, Jean-Marie, Ji, Weizhen, Ionita, Cristian, Roy, Bhaskar, Morrow, Jon S., Darbinyan, Armine, Iyer, Krishna, Aul, Ritu B., Chao, Katherine R., Cobbold, Laura, Cohen, Stacey, Custodio, Helena M., Drummond-Borg, Margaret, Finanger, Erika, Hainline, Bryan E., Helbig, Ingo, Hewson, Stacy, Hu, Ying, Jackson, Adam, Konstantino, Monica, Leach, Meganne E., McCormick, David, Nelson, Stanley, Nguyen, Joanne, Nugent, Kimberly, Ortega, Lucy, Goodkin, Howard P., Roeder, Elizabeth, Roy, Sani, Sapp, Katie, Saade, Dimah, Sisodiya, Sanjay M., Stals, Karen, Towner, Shelley, Wilson, William, Khokha, Mustafa K., Bönnemann, Carsten G., Lucas, Carrie L., and Lakhani, Saquib A.

Published
2024
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2. Dirac Assisted Tree Method for 1D Heterogeneous Helmholtz Equations with Arbitrary Variable Wave Numbers

Author

Han, Bin, Michelle, Michelle, and Wong, Yau Shu

Subjects
Mathematics - Numerical Analysis, 65L12, 65N06, 35J05
Abstract

In this paper we introduce a new method called the Dirac Assisted Tree (DAT) method, which can handle 1D heterogeneous Helmholtz equations with arbitrarily large variable wave numbers. DAT breaks an original global problem into many parallel tree-structured small local problems, which are linked together to form a global solution by solving small linking problems. To solve the local problems in DAT, we propose a compact finite difference method (FDM) with arbitrarily high accuracy order and low numerical dispersion for piecewise smooth coefficients and variable wave numbers. This compact FDM is particularly appealing for DAT, because the local problems and their fluxes in DAT can be computed with high accuracy. DAT with such compact FDMs can solve heterogeneous Helmholtz equations with arbitrarily large variable wave numbers accurately by solving small linear systems - $4 \times 4$ matrices in the extreme case - with tridiagonal coefficient matrices in a parallel fashion. Several numerical examples are provided to illustrate the effectiveness of DAT using the $M$th order compact FDMs with $M=6,8$ for numerically solving heterogeneous Helmholtz equations with variable wave numbers. We shall also discuss how to solve some special 2D Helmholtz equations using DAT.

Published
2020
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3. A novel custom high density-comparative genomic hybridization array detects common rearrangements as well as deep intronic mutations in dystrophinopathies

Author

Falzarano Maria S, Brioschi Simona, Spitali Pietro, Bassi Elena, Martoni Elena, Venturoli Anna, Trabanelli Cecilia, Fabris Marina, Fini Sergio, Neri Marcella, Bovolenta Matteo, Rimessi Paola, Ciccone Roberto, Ashton Emma, McCauley Joanne, Yau Shu, Abbs Stephen, Muntoni Francesco, Merlini Luciano, Gualandi Francesca, and Ferlini Alessandra

Subjects
Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background The commonest pathogenic DMD changes are intragenic deletions/duplications which make up to 78% of all cases and point mutations (roughly 20%) detectable through direct sequencing. The remaining mutations (about 2%) are thought to be pure intronic rearrangements/mutations or 5'-3' UTR changes. In order to screen the huge DMD gene for all types of copy number variation mutations we designed a novel custom high density comparative genomic hybridisation array which contains the full genomic region of the DMD gene and spans from 100 kb upstream to 100 kb downstream of the 2.2 Mb DMD gene. Results We studied 12 DMD/BMD patients who either had no detectable mutations or carried previously identified quantitative pathogenic changes in the DMD gene. We validated the array on patients with previously known mutations as well as unaffected controls, we identified three novel pure intronic rearrangements and we defined all the mutation breakpoints both in the introns and in the 3' UTR region. We also detected a novel polymorphic intron 2 deletion/duplication variation. Despite the high resolution of this approach, RNA studies were required to confirm the functional significance of the intronic mutations identified by CGH. In addition, RNA analysis identified three intronic pathogenic variations affecting splicing which had not been detected by the CGH analysis. Conclusion This novel technology represents an effective high throughput tool to identify both common and rarer DMD rearrangements. RNA studies are required in order to validate the significance of the CGH array findings. The combination of these tools will fully cover the identification of causative DMD rearrangements in both coding and non-coding regions, particularly in patients in whom standard although extensive techniques are unable to detect a mutation.

Published
2008
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4. Wavelet-based Methods for Numerical Solutions of Differential Equations

Author

Han, Bin, Michelle, Michelle, and Wong, Yau Shu

Subjects
Mathematics - Numerical Analysis
Abstract

Wavelet theory has been well studied in recent decades. Due to their appealing features such as sparse multiscale representation and fast algorithms, wavelets have enjoyed many tremendous successes in the areas of signal/image processing and computational mathematics. This paper primarily intends to shed some light on the advantages of using wavelets in the context of numerical differential equations. We shall identify a few prominent problems in this field and recapitulate some important results along these directions. Wavelet-based methods for numerical differential equations offer the advantages of sparse matrices with uniformly bounded small condition numbers. We shall demonstrate wavelets' ability in solving some one-dimensional differential equations: the biharmonic equation and the Helmholtz equation with high wave numbers (of magnitude $O(10^4)$ or larger).

Published
2019

5. Toward an Individualized Neural Assessment of Receptive Language in Children

Author

Petit, Selene, Badcock, Nicholas A., Grootswagers, Tijl, Rich, Anina N., Brock, Jon, Nickels, Lyndsey, Moerel, Denise, Dermody, Nadene, Yau, Shu, Schmidt, Elaine, and Woolgar, Alexandra

Abstract

Purpose: We aimed to develop a noninvasive neural test of language comprehension to use with nonspeaking children for whom standard behavioral testing is unreliable (e.g., minimally verbal autism). Our aims were threefold. First, we sought to establish the sensitivity of two auditory paradigms to elicit neural responses in individual neurotypical children. Second, we aimed to validate the use of a portable and accessible electroencephalography (EEG) system, by comparing its recordings to those of a research-grade system. Third, in light of substantial interindividual variability in individuals' neural responses, we assessed whether multivariate decoding methods could improve sensitivity. Method: We tested the sensitivity of two child-friendly covert N400 paradigms. Thirty-one typically developing children listened to identical spoken words that were either strongly predicted by the preceding context or violated lexical-semantic expectations. Context was given by a cue word (Experiment 1) or sentence frame (Experiment 2), and participants either made an overall judgment on word relatedness or counted lexical-semantic violations. We measured EEG concurrently from a research-grade system, Neuroscan's SynAmps2, and an adapted gaming system, Emotiv's EPOC+. Results: We found substantial interindividual variability in the timing and topology of N400-like effects. For both paradigms and EEG systems, traditional N400 effects at the expected sensors and time points were statistically significant in around 50% of individuals. Using multivariate analyses, detection rate increased to 88% of individuals for the research-grade system in the sentences paradigm, illustrating the robustness of this method in the face of interindividual variations in topography. Conclusions: There was large interindividual variability in neural responses, suggesting interindividual variation in either the cognitive response to lexical--semantic violations and/or the neural substrate of that response. Around half of our neurotypical participants showed the expected N400 effect at the expected location and time points. A low-cost, accessible EEG system provided comparable data for univariate analysis but was not well suited to multivariate decoding. However, multivariate analyses with a research-grade EEG system increased our detection rate to 88% of individuals. This approach provides a strong foundation to establish a neural index of language comprehension in children with limited communication.

Published
2020
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6. Impaired P1 Habituation and Mismatch Negativity in Children with Autism Spectrum Disorder

Author

Ruiz-Martínez, Francisco J., Rodríguez-Martínez, Elena I., Wilson, C. Ellie, Yau, Shu, Saldaña, David, and Gómez, Carlos M.

Abstract

Passive testing of auditory function is an important objective in individuals with ASD due to known difficulties in understanding and/or following task instructions. In present study the habituation to standard tones following deviants and the auditory discriminative processes were examined in two conditions: electronic and human sounds, in a sample of 16 ASD children. ASD children presented a reduced habituation in the P1 component and a decrease in the amplitude of the mismatch negativity indicating a lower auditory discrimination with respect to controls. MMN amplitude was related to sensory sensitivity. Results suggest an increased activation to repeatedly auditory stimulus and a poor auditory discrimination, for both: electronic and human sounds with consequences on the impaired sensory behavior of ASD subjects.

Published
2020
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7. Comparing and contrasting barriers in augmentative alternative communication use in nonspeaking autism and complex communication needs: multi-stakeholder perspectives.

Author

Yau, Shu H., Choo, Kaylynn, Tan, Jane, Monson, Olivia, and Bovell, Stephanie

Subjects
MEANS of communication for people with disabilities, AUTISM, SCHOOL environment, THEMATIC analysis, ORAL communication
Abstract

Augmentative alternative communication (AAC) devices or systems are often prescribed to minimally verbal or nonspeaking autistic individuals and other individuals with complex communication needs to facilitate communication or as an alternative to spoken language. AAC use can result in communication gains and improved quality of life for minimally verbal or nonspeaking individuals. Despite this, AAC abandonment is high, limiting societal participation of the individual on the autism spectrum with complex communication needs. Our study is a novel exploration of the barriers of AAC use from a multi-stakeholder perspective, and a qualitative analysis of similarities and differences between stakeholders. We conducted semi-structured interviews and focus groups with 30 parent-carers, educators and clinicians currently supporting AAC users in Western Australia and analysed the data using reflexive thematic analysis. Barriers from each stakeholder group were coded, resulting in 17 subthemes forming five main themes common to all stakeholders: Stakeholder Knowledge, Stakeholder Attitudes and Stigma, Resources, AAC User Engagement, and Device Fit. Contrasting perspectives included actual and perceived stigma associated with AAC use (parent-carers vs clinicians); different struggles with resources and knowledge (parent-carers vs clinicians and educators); and a lack of clinician communication in the processes that determined AAC-fit for school environments (educators only). Findings are discussed in the context of improving inter-stakeholder collaboration and capacity building in Australian health service and practice to better support minimally verbal or nonspeaking autistic individuals and individuals with complex communication needs. Suggestions are also offered for communication partner training. [ABSTRACT FROM AUTHOR]

Published
2024
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13. The Relationship between Spoken Language and Speech and Nonspeech Processing in Children with Autism: A Magnetic Event-Related Field Study

Author

Yau, Shu Hui, Brock, Jon, and McArthur, Genevieve

Abstract

It has been proposed that language impairments in children with Autism Spectrum Disorders (ASD) stem from atypical neural processing of speech and/or nonspeech sounds. However, the strength of this proposal is compromised by the unreliable outcomes of previous studies of speech and nonspeech processing in ASD. The aim of this study was to determine whether there was an association between poor spoken language and atypical event-related field (ERF) responses to speech and nonspeech sounds in children with ASD (n = 14) and controls (n = 18). Data from this developmental population (ages 6-14) were analysed using a novel combination of methods to maximize the reliability of our findings while taking into consideration the heterogeneity of the ASD population. The results showed that poor spoken language scores were associated with atypical left hemisphere brain responses (200 to 400 ms) to both speech and nonspeech in the ASD group. These data support the idea that some children with ASD may have an immature auditory cortex that affects their ability to process both speech and nonspeech sounds. Their poor speech processing may impair their ability to process the speech of other people, and hence reduce their ability to learn the phonology, syntax, and semantics of their native language.

Published
2016
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16. Symplectic Numerical Schemes for Stochastic Systems Preserving Hamiltonian Functions

Author

Anton, Cristina, Wong, Yau Shu, Deng, Jian, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Dimov, Ivan, editor, Faragó, István, editor, and Vulkov, Lubin, editor

Published
2013
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21. Monte Carlo Approach for Switching State-Space Models

Author

Popescu, Cristina, Wong, Yau Shu, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Orchard, Bob, editor, Yang, Chunsheng, editor, and Ali, Moonis, editor

Published
2004
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24. Neural correlates of auditory processing and language impairment in children with autism spectrum disorders

Author

Yau, Shu Hui

Subjects
mental disorders, Other education not elsewhere classified, behavioral disciplines and activities
Abstract

The term autism spectrum disorders (ASD) refers to a group of neurodevelopmental disorders characterised by social and communication impairments, as well as restricted and repetitive patterns of behaviour. The thesis contains four studies using magnetoencephalography (MEG) to measure brain responses to auditory stimuli. The aim is to better understand the neural correlates of auditory processing defects in ASD, and determine how such deficits may be associated with spoken language impairment that affect many individuals on the autism spectrum.

Published
2022
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28. Evidence of digenic inheritance in Alport syndrome

Author

Mencarelli, Maria Antonietta, Heidet, Laurence, Storey, Helen, van Geel, Michel, Knebelmann, Bertrand, Fallerini, Chiara, Miglietti, Nunzia, Antonucci, Maria Fatima, Cetta, Francesco, Sayer, John A, van den Wijngaard, Arthur, Yau, Shu, Mari, Francesca, Bruttini, Mirella, Ariani, Francesca, Dahan, Karin, Smeets, Bert, Antignac, Corinne, Flinter, Frances, and Renieri, Alessandra

Published
2015
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29. The contribution of X-linked coding variation to severe developmental disorders

Author

Martin, Hilary C., Gardner, Eugene J., Samocha, Kaitlin E., Kaplanis, Joanna, Akawi, Nadia, Sifrim, Alejandro, Eberhardt, Ruth Y., Tavares, Ana Lisa Taylor, Neville, Matthew D. C., Niemi, Mari E. K., Gallone, Giuseppe, McRae, Jeremy, Wright, Caroline F., FitzPatrick, David R., Firth, Helen V., Hurles, Matthew E., Borras, Silvia, Clark, Caroline, Dean, John, Miedzybrodzka, Zosia, Ross, Alison, Tennant, Stephen, Dabir, Tabib, Donnelly, Deirdre, Humphreys, Mervyn, Magee, Alex, McConnell, Vivienne, McKee, Shane, McNerlan, Susan, Morrison, Patrick J., Rea, Gillian, Stewart, Fiona, Cole, Trevor, Cooper, Nicola, Cooper-Charles, Lisa, Cox, Helen, Islam, Lily, Jarvis, Joanna, Keelagher, Rebecca, Lim, Derek, McMullan, Dominic, Morton, Jenny, Naik, Swati, O’Driscoll, Mary, Ong, Kai-Ren, Osio, Deborah, Ragge, Nicola, Turton, Sarah, Vogt, Julie, Williams, Denise, Bodek, Simon, Donaldson, Alan, Hills, Alison, Low, Karen, Newbury-Ecob, Ruth, Norman, Andrew M., Roberts, Eileen, Scurr, Ingrid, Smithson, Sarah, Tooley, Madeleine, Abbs, Steve, Armstrong, Ruth, Dunn, Carolyn, Holden, Simon, Park, Soo-Mi, Paterson, Joan, Raymond, Lucy, Reid, Evan, Sandford, Richard, Simonic, Ingrid, Tischkowitz, Marc, Woods, Geoff, Bradley, Lisa, Comerford, Joanne, Green, Andrew, Lynch, Sally, McQuaid, Shirley, Mullaney, Brendan, Berg, Jonathan, Goudie, David, Mavrak, Eleni, McLean, Joanne, McWilliam, Catherine, Reavey, Eleanor, Azam, Tara, Cleary, Elaine, Jackson, Andrew, Lam, Wayne, Lampe, Anne, Moore, David, Porteous, Mary, Baple, Emma, Baptista, Júlia, Brewer, Carole, Castle, Bruce, Kivuva, Emma, Owens, Martina, Rankin, Julia, Shaw-Smith, Charles, Turner, Claire, Turnpenny, Peter, Tysoe, Carolyn, Bradley, Therese, Davidson, Rosemarie, Gardiner, Carol, Joss, Shelagh, Kinning, Esther, Longman, Cheryl, McGowan, Ruth, Murday, Victoria, Pilz, Daniela, Tobias, Edward, Whiteford, Margo, Williams, Nicola, Barnicoat, Angela, Clement, Emma, Faravelli, Francesca, Hurst, Jane, Jenkins, Lucy, Jones, Wendy, Kumar, V.K.Ajith, Lees, Melissa, Loughlin, Sam, Male, Alison, Morrogh, Deborah, Rosser, Elisabeth, Scott, Richard, Wilson, Louise, Beleza, Ana, Deshpande, Charu, Flinter, Frances, Holder, Muriel, Irving, Melita, Izatt, Louise, Josifova, Dragana, Mohammed, Shehla, Molenda, Aneta, Robert, Leema, Roworth, Wendy, Ruddy, Deborah, Ryten, Mina, Yau, Shu, Bennett, Christopher, Blyth, Moira, Campbell, Jennifer, Coates, Andrea, Dobbie, Angus, Hewitt, Sarah, Hobson, Emma, Jackson, Eilidh, Jewell, Rosalyn, Kraus, Alison, Prescott, Katrina, Sheridan, Eamonn, Thomson, Jenny, Bradshaw, Kirsty, Dixit, Abhijit, Eason, Jacqueline, Haines, Rebecca, Harrison, Rachel, Mutch, Stacey, Sarkar, Ajoy, Searle, Claire, Shannon, Nora, Sharif, Abid, Suri, Mohnish, Vasudevan, Pradeep, Canham, Natalie, Ellis, Ian, Greenhalgh, Lynn, Howard, Emma, Stinton, Victoria, Swale, Andrew, Weber, Astrid, Banka, Siddharth, Breen, Catherine, Briggs, Tracy, Burkitt-Wright, Emma, Chandler, Kate, Clayton-Smith, Jill, Donnai, Dian, Douzgou, Sofia, Gaunt, Lorraine, Jones, Elizabeth, Kerr, Bronwyn, Langley, Claire, Metcalfe, Kay, Smith, Audrey, Wright, Ronnie, Bourn, David, Burn, John, Fisher, Richard, Hellens, Steve, Henderson, Alex, Montgomery, Tara, Splitt, Miranda, Straub, Volker, Wright, Michael, Zwolinski, Simon, Allen, Zoe, Bernhard, Birgitta, Brady, Angela, Brooks, Claire, Busby, Louise, Clowes, Virginia, Ghali, Neeti, Holder, Susan, Ibitoye, Rita, Wakeling, Emma, Blair, Edward, Carmichael, Jenny, Cilliers, Deirdre, Clasper, Susan, Gibbons, Richard, Kini, Usha, Lester, Tracy, Nemeth, Andrea, Poulton, Joanna, Price, Sue, Shears, Debbie, Stewart, Helen, Wilkie, Andrew, Albaba, Shadi, Baker, Duncan, Balasubramanian, Meena, Johnson, Diana, Parker, Michael, Quarrell, Oliver, Stewart, Alison, Willoughby, Josh, Crosby, Charlene, Elmslie, Frances, Homfray, Tessa, Jin, Huilin, Lahiri, Nayana, Mansour, Sahar, Marks, Karen, McEntagart, Meriel, Saggar, Anand, Tatton-Brown, Kate, Butler, Rachel, Clarke, Angus, Corrin, Sian, Fry, Andrew, Kamath, Arveen, McCann, Emma, Mugalaasi, Hood, Pottinger, Caroline, Procter, Annie, Sampson, Julian, Sansbury, Francis, Varghese, Vinod, Baralle, Diana, Callaway, Alison, Cassidy, Emma J., Daniels, Stacey, Douglas, Andrew, Foulds, Nicola, Hunt, David, Kharbanda, Mira, Lachlan, Katherine, Mercer, Catherine, Side, Lucy, Temple, I. Karen, Wellesley, Diana, Martin, Hilary C. [0000-0002-4454-9084], Gardner, Eugene J. [0000-0001-9671-1533], Samocha, Kaitlin E. [0000-0002-1704-3352], Eberhardt, Ruth Y. [0000-0001-6152-1369], Tavares, Ana Lisa Taylor [0000-0001-7089-0502], Neville, Matthew D. C. [0000-0001-5816-7936], Niemi, Mari E. K. [0000-0003-0696-6175], Wright, Caroline F. [0000-0003-2958-5076], Hurles, Matthew E. [0000-0002-2333-7015], and Apollo - University of Cambridge Repository

Subjects
631/208/366, 49/23, article, 631/208/1516, 631/208/205
Abstract

Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders.

Published
2021
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30. Prevention in adolescent mental health: The development and evaluation of school-based interventions in disadvantaged communities

Author

Lewis, Andrew, Yau, Shu, Sae-Koew, Jonathan, Lewis, Andrew, Yau, Shu, and Sae-Koew, Jonathan

Abstract

School-based prevention frameworks for mental health in disadvantaged communities are essential for determining evidence-based action to address poorer adolescent mental health. Frameworks addressing vulnerability and sustained mental health problems in adolescence can be examined at several levels, ranging from structural and place-based factors to the role of community factors and proximal factors such as family and the school setting. The overall aim of this thesis was to develop recommendations for prevention-based practice by combining local and national predictors of depressive symptoms and then apply these recommendations to an evaluation of a school-based intervention. Study 1 examined a national dataset (N = 19,987) from the Communities That Care (CTC) study of 18 years of nationally representative data on adolescents to examine risk and protective factors predicting adolescent depressive symptoms. Results revealed several critical risk (self-blame, family conflict and friend’s use of drugs) and protective factors (good coping, school rewards for prosocial involvement and belief in the moral order) for depressive symptoms in adolescents at a national level. However, when examined in the context of several disadvantaged communities, profiles of risk and protection for depressive symptoms were found to differ. A measurement tool was developed for identifying young people with high levels of depressive symptoms based on these predictors. A prevention-focused framework was then applied to evaluating a school-based intervention, the Resilience, Emotional Awareness, Careers, and Health (REACH) program across three studies spanning 2015 to 2018. REACH aimed at targeting school- and individual-level risk and protective factors associated with mental health. Included empirical studies collected data from four yearly cohorts of students (N = 1098) who participated in the REACH program. Evaluation outcomes suggest that the REACH program was not effective for targeting

Published
2021

32. Dirac Assisted Tree Method for 1D Heterogeneous Helmholtz Equations with Arbitrary Variable Wave Numbers

Author

Michelle Michelle, Bin Han, and Yau Shu Wong

Subjects
Tridiagonal matrix, Helmholtz equation, Dirac (video compression format), Linear system, Compact finite difference, Numerical Analysis (math.NA), 010103 numerical & computational mathematics, 01 natural sciences, 65L12, 65N06, 35J05, 010101 applied mathematics, Computational Mathematics, Arbitrarily large, Computational Theory and Mathematics, Modeling and Simulation, FOS: Mathematics, Piecewise, Applied mathematics, Mathematics - Numerical Analysis, 0101 mathematics, Mathematics, Variable (mathematics)
Abstract

In this paper we introduce a new method called the Dirac Assisted Tree (DAT) method, which can handle 1D heterogeneous Helmholtz equations with arbitrarily large variable wave numbers. DAT breaks an original global problem into many parallel tree-structured small local problems, which are linked together to form a global solution by solving small linking problems. To solve the local problems in DAT, we propose a compact finite difference method (FDM) with arbitrarily high accuracy order and low numerical dispersion for piecewise smooth coefficients and variable wave numbers. This compact FDM is particularly appealing for DAT, because the local problems and their fluxes in DAT can be computed with high accuracy. DAT with such compact FDMs can solve heterogeneous Helmholtz equations with arbitrarily large variable wave numbers accurately by solving small linear systems — 4 × 4 matrices in the extreme case — with tridiagonal coefficient matrices in a parallel fashion. Several numerical examples are provided to illustrate the effectiveness of DAT using the Mth order compact FDMs with M = 6 , 8 for numerically solving heterogeneous Helmholtz equations with variable wave numbers. We shall also discuss how to solve some special 2D Helmholtz equations using DAT.

Published
2020

35. Nested Monte Carlo EM algorithm for switching state-space models

Author

Popescu, Cristina Adela and Yau Shu, Wong

Subjects
Monte Carlo method -- Research, Algorithms -- Research, Time-series analysis -- Research, Markov processes -- Research, Algorithm, Business, Computers, Electronics, Electronics and electrical industries
Abstract

Switching state-space models have been widely used in many applications arising from science, engineering, economic, and medical research. In this paper, we present a Monte Carlo Expectation Maximization (MCEM) algorithm for learning the parameters and classifying the states of a state-space model with a Markov switching. A stochastic implementation based on the Gibbs sampler is introduced in the expectation step of the MCEM algorithm. We study the asymptotic properties of the proposed algorithm, and we also describe how a nesting approach and the Rao-Blackwellized forms can be employed to accelerate the rate of convergence of the MCEM algorithm. Finally, the performance and the effectiveness of the proposed method are demonstrated by applications to simulated and physiological experimental data. Index Terms--Time series analysis, machine learning, Markov processes, Kalman filtering, probabilistic algorithms, parameter learning, Monte Carlo simulation.

Published
2005

36. ISPD gene mutations are a common cause of congenital and limb-girdle muscular dystrophies

Author

Cirak, Sebahattin, Foley, Aileen Reghan, Herrmann, Ralf, Willer, Tobias, Yau, Shu, Stevens, Elizabeth, Torelli, Silvia, Brodd, Lina, Kamynina, Alisa, Vondracek, Petr, Roper, Helen, Longman, Cheryl, Korinthenberg, Rudolf, Marrosu, Gianni, Nürnberg, Peter, Michele, Daniel E., Plagnol, Vincent, Hurles, Matt, Moore, Steven A., Sewry, Caroline A., Campbell, Kevin P., Voit, Thomas, and Muntoni, Francesco

Published
2013
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40. Evidence-Based Consensus and Systematic Review on Reducing the Time to Diagnosis of Duchenne Muscular Dystrophy

Author

Aartsma-Rus, Annemieke, Hegde, Madhuri, Ben-Omran, Tawfeg, Buccella, Filippo, Ferlini, Alessandra, Gallano, Pia, Howell, R. Rodney, Leturcq, France, Martin, Ann S., Potulska-Chromik, Anna, Saute, Jonas A., Schmidt, Wolfgang M., Sejersen, Thomas, Tuffery-Giraud, Sylvie, Uyguner, Zehra Oya, Witcomb, Luci A., Yau, Shu, and Nelson, Stanley F.

Published
2019
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41. Diagnostic Yield of Rare Skeletal Dysplasia Conditions in the Radiogenomics Era – A UK Experience

Author

Sabir, Ataf H, primary, Morley, Elizabeth, additional, Sheikh, Jameela, additional, Calder, Alistair D, additional, Beleza-Meireles, Ana, additional, Cheung, Moira S, additional, Cocca, Alessandra, additional, Jansson, Mattias, additional, Lillis, Suzanne, additional, Patel, Yogen, additional, Yau, Shu, additional, Hall, Christine M, additional, Offiah, Amaka C, additional, and Irving, Melita, additional

Published
2020
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44. Marked Hemiatrophy in Carriers of Duchenne Muscular Dystrophy

Author

Rajakulendran, Sanjeev, Kuntzer, Thierry, Dunand, Murielle, Yau, Shu C., Ashton, Emma J., Storey, Helen, McCauley, Joanna, Abbs, Stephen, Thonney, Francine, Leturcq, France, Lobrinus, Johannes A., Yousry, Tarek, Farmer, Simon, Holton, Janice L., and Hanna, Michael G.

Published
2010

45. Solving Helmholtz equation at high wave numbers in exterior domains

Author

Kun Wang, Jizu Huang, and Yau Shu Wong

Subjects
Helmholtz equation, Applied Mathematics, Mathematical analysis, Spherical coordinate system, 010103 numerical & computational mathematics, Grid, 01 natural sciences, Domain (mathematical analysis), 010101 applied mathematics, Computational Mathematics, Classical mechanics, Feature (computer vision), Scheme (mathematics), Annulus (firestop), Wavenumber, 0101 mathematics, Mathematics
Abstract

This paper presents effective difference schemes for solving the Helmholtz equation at high wave numbers. Considering the problems in the polar and spherical coordinates, we show that pollution-free difference schemes can be constructed for annulus and hollow sphere domains, but the "pollution effect" cannot be avoided in the neighborhood of the origin of the coordinate. Using the fact that the "pollution effect" appears in a small neighborhood of the origin of the coordinate, we propose a local mesh refinement approach so that a fine grid is applied only for a small region near the origin of the coordinate and a much larger grid size is employed in the remaining domain. The most attractive feature of this approach is that the computational storage can be significantly reduced while keeping almost the same numerical accuracy. Moreover, by applying a two-level local refinement technique, we can further enhance the performance of the proposed scheme. Numerical simulations are reported to verify the effectiveness of the proposed schemes for the Helmholtz problem in exterior domains.

Published
2017

46. Is Pollution Effect of Finite Difference Schemes Avoidable for Multi-Dimensional Helmholtz Equations with High Wave Numbers?

Author

Kun Wang and Yau Shu Wong

Subjects
Physics and Astronomy (miscellaneous), Tridiagonal matrix, Helmholtz equation, Discretization, Separation of variables, Finite difference, Geometry, 010103 numerical & computational mathematics, 01 natural sciences, Numerical integration, law.invention, 010101 applied mathematics, symbols.namesake, law, Helmholtz free energy, symbols, Applied mathematics, Cartesian coordinate system, 0101 mathematics, Mathematics
Abstract

This paper presents an approach using the method of separation of variables applied to 2D Helmholtz equations in the Cartesian coordinate. The solution is then computed by a series solutions resulted from solving a sequence of 1D problems, in which the 1D solutions are computed using pollution free difference schemes. Moreover, non-polluted numerical integration formulae are constructed to handle the integration due to the forcing term in the inhomogeneous 1D problems. Consequently, the computed solution does not suffer the pollution effect. Another attractive feature of this approach is that a direct method can be effectively applied to solve the tridiagonal matrix resulted from numerical discretization of the 1D Helmholtz equation. The method has been tested to compute 2D Helmholtz solutions simulating electromagnetic scattering from an open large cavity and rectangular waveguide.

Published
2017

50. BTTB–RRCG method for downward continuation of potential field data

Author

Yuanfang Lin, Yile Zhang, and Yau Shu Wong

Subjects
Mathematical optimization, 010504 meteorology & atmospheric sciences, Computational complexity theory, Fast Fourier transform, Stability (learning theory), 010502 geochemistry & geophysics, 01 natural sciences, Regularization (mathematics), Synthetic data, Noise, Geophysics, Robustness (computer science), Conjugate gradient method, Algorithm, 0105 earth and related environmental sciences, Mathematics
Abstract

This paper presents a conjugate gradient (CG) method for accurate and robust downward continuation of potential field data. Utilizing the Block-Toeplitz Toeplitz-Block (BTTB) structure, the storage requirement and the computational complexity can be significantly reduced. Unlike the wavenumber domain regularization methods based on fast Fourier transform, the BTTB-based conjugate gradient method induces little artifacts near the boundary. The application of a re-weighted regularization in a space domain significantly improves the stability of the CG scheme for noisy data. The synthetic data with different levels of added noise and real field data are used to validate the effectiveness of the proposed scheme, and the computed results are compared with those based on recently proposed wavenumber domain methods and the Taylor series method. The simulation results verify that the proposed scheme is superior to the existing methods considered in this study in terms of accuracy and robustness. The proposed scheme is a powerful computational tool capable of applications for large scale data with modest computational cost.

Published
2016

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