OBJECTIVE: To investigate the pregnancy outcomes in a cohort of women who failed to obtain a result in non-invasive prenatal testing (NIPT).DESIGN: Historical cohort study.SETTING: A multicentre private practice in Sydney, Australia.POPULATION: Women who failed to obtain a result from NIPT (n = 131).METHODS: The maternal characteristics, antenatal investigations and pregnancy outcomes for these women were compared with those who obtained a result at the same practice and to the general Australian obstetric population.MAIN OUTCOME MEASURES: Antenatal investigations: pregnancy-associated plasma protein-A (PAPP-A), free β-human chorionic gonadotrophin (β-hCG), placental growth factor (PlGF), uterine artery pulsatility index (PI), mean arterial pressure (MAP). Pregnancy outcomes: chromosomal abnormality, pre-eclampsia, gestational diabetes, small-for-gestational-age (SGA), preterm delivery.RESULTS: Only 1.1% of NIPT samples failed to return a result. This cohort was significantly older and had significantly increased weight compared with the general Australian obstetric population. Pregnancy outcomes were available for 94% of the cohort. There were significantly higher rates of chromosomal aneuploidies (6.5% versus 0.2%, P < 0.0001), pre-eclampsia (11% versus 1.5%, P < 0.0001) and gestational diabetes (23% versus 7.5%, P < 0.0001) compared with the general obstetric population. Rates of preterm delivery and SGA were elevated but did not reach significance. Antenatal investigations demonstrated decreased PAPP-A MoM (0.75 versus 1.14, P < 0.0001), decreased free β-hCG (0.71 versus 1.01, P < 0.0001) and increased uterine artery PI (1.79 versus 1.65, P = 0.02).CONCLUSION: Women who fail to obtain a result from NIPT are at increased risk of adverse pregnancy outcomes, in particular chromosomal aneuploidy, gestational diabetes and pre-eclampsia.FUNDING: None received.TWEETABLE ABSTRACT: Women who fail to obtain a result from cell-free DNA NIPT are at increased risk of adverse pregnancy outcomes. <<<

Xuelei Lin, Yongxin Xu, Dongzhi Wang, Yiman Yang, Xiaoyu Zhang, Xiaomin Bie, Lixuan Gui, Zhongxu Chen, Yiliang Ding, Long Mao, Xueyong Zhang, Fei Lu, Xiansheng Zhang, Cristobal Uauy, Xiangdong Fu, Jun Xiao <<<

The spike architecture of wheat plays a crucial role in determining grain number, making it a key trait for optimization in wheat breeding programs. In this study, we used a multi-omic approach to analyze the transcriptome and epigenome profiles of the young spike at eight developmental stages, revealing coordinated changes in chromatin accessibility and H3K27me3 abundance during the flowering transition. We constructed a core transcriptional regulatory network (TRN) that drives wheat spike formation and experimentally validated a multi-layer regulatory module involving TaSPL15, TaAGLG1, and TaFUL2. By integrating the TRN with genome-wide association studies, we identified 227 transcription factors, including 42 with known functions and 185 with unknown functions. Further investigation of 61 novel transcription factors using multiple homozygous mutant lines revealed 36 transcription factors that regulate spike architecture or flowering time, such as TaMYC2-A1, TaMYB30-A1, and TaWRKY37-A1. Of particular interest, TaMYB30-A1, downstream of and repressed by WFZP, was found to regulate fertile spikelet number. Notably, the excellent haplotype of TaMYB30-A1, which contains a C allele at the WFZP binding site, was enriched during wheat breeding improvement in China, leading to improved agronomic traits. Finally, we constructed a free and open access Wheat Spike Multi-Omic Database (http://39.98.48.156:8800/#/). Our study identifies novel and high-confidence regulators and offers an effective strategy for dissecting the genetic basis of wheat spike development, with practical value for wheat breeding. <<<

Zizhen Yao, Cindy T J van Velthoven, Thuc Nghi Nguyen, Jeff Goldy, Adriana E Sedeno-Cortes, Fahimeh Baftizadeh, Darren Bertagnolli, Tamara Casper, Megan Chiang, Kirsten Crichton, Song-Lin Ding, Olivia Fong, Emma Garren, Alexandra Glandon, Nathan W Gouwens, James Gray, Lucas T Graybuck, Michael J Hawrylycz, Daniel Hirschstein, Matthew Kroll, Kanan Lathia, Changkyu Lee, Boaz Levi, Delissa McMillen, Stephanie Mok, Thanh Pham, Qingzhong Ren, Christine Rimorin, Nadiya Shapovalova, Josef Sulc, Susan M Sunkin, Michael Tieu, Amy Torkelson, Herman Tung, Katelyn Ward, Nick Dee, Kimberly A Smith, Bosiljka Tasic, Hongkui Zeng <<<

The isocortex and hippocampal formation (HPF) in the mammalian brain play critical roles in perception, cognition, emotion, and learning. We profiled ∼1.3 million cells covering the entire adult mouse isocortex and HPF and derived a transcriptomic cell-type taxonomy revealing a comprehensive repertoire of glutamatergic and GABAergic neuron types. Contrary to the traditional view of HPF as having a simpler cellular organization, we discover a complete set of glutamatergic types in HPF homologous to all major subclasses found in the six-layered isocortex, suggesting that HPF and the isocortex share a common circuit organization. We also identify large-scale continuous and graded variations of cell types along isocortical depth, across the isocortical sheet, and in multiple dimensions in hippocampus and subiculum. Overall, our study establishes a molecular architecture of the mammalian isocortex and hippocampal formation and begins to shed light on its underlying relationship with the development, evolution, connectivity, and function of these two brain structures. <<<

Darcy L Fehlings, Mehdi Zarrei, Worrawat Engchuan, Neal Sondheimer, Bhooma Thiruvahindrapuram, Jeffrey R MacDonald, Edward J Higginbotham, Ritesh Thapa, Tarannum Behlim, Sabrina Aimola, Lauren Switzer, Pamela Ng, John Wei, Prakroothi S Danthi, Giovanna Pellecchia, Sylvia Lamoureux, Karen Ho, Sergio L Pereira, Jill de Rijke, Wilson W L Sung, Alireza Mowjoodi, Jennifer L Howe, Thomas Nalpathamkalam, Roozbeh Manshaei, Siavash Ghaffari, Joseph Whitney, Rohan V Patel, Omar Hamdan, Rulan Shaath, Brett Trost, Shannon Knights, Dawa Samdup, Anna McCormick, Carolyn Hunt, Adam Kirton, Anne Kawamura, Ronit Mesterman, Jan Willem Gorter, Nomazulu Dlamini, Daniele Merico, Murto Hilali, Kyle Hirschfeld, Kritika Grover, Nelson X Bautista, Kara Han, Christian R Marshall, Ryan K C Yuen, Padmaja Subbarao, Meghan B Azad, Stuart E Turvey, Piush Mandhane, Theo J Moraes, Elinor Simons, George Maxwell, Michael Shevell, Gregory Costain, Jacques L Michaud, Fadi F Hamdan, Julie Gauthier, Kevin Uguen, Dimitri J Stavropoulos, Richard F Wintle, Maryam Oskoui, Stephen W Scherer <<<

We performed whole-genome sequencing (WGS) in 327 children with cerebral palsy (CP) and their biological parents. We classified 37 of 327 (11.3%) children as having pathogenic/likely pathogenic (P/LP) variants and 58 of 327 (17.7%) as having variants of uncertain significance. Multiple classes of P/LP variants included single-nucleotide variants (SNVs)/indels (6.7%), copy number variations (3.4%) and mitochondrial mutations (1.5%). The COL4A1 gene had the most P/LP SNVs. We also analyzed two pediatric control cohorts (n = 203 trios and n = 89 sib-pair families) to provide a baseline for de novo mutation rates and genetic burden analyses, the latter of which demonstrated associations between de novo deleterious variants and genes related to the nervous system. An enrichment analysis revealed previously undescribed plausible candidate CP genes (SMOC1, KDM5B, BCL11A and CYP51A1). A multifactorial CP risk profile and substantial presence of P/LP variants combine to support WGS in the diagnostic work-up across all CP and related phenotypes. <<<

BACKGROUND: There is divergence in the rate at which people age. The concept of biological age is postulated to capture this variability, and hence to better represent an individual's true global physiological state than chronological age. Biological age predictors are often generated based on cross-sectional data, using biochemical or molecular markers as predictor variables. It is assumed that the difference between chronological and predicted biological age is informative of one's chronological age-independent aging divergence ∆.METHODS: We investigated the statistical assumptions underlying the most popular cross-sectional biological age predictors, based on multiple linear regression, the Klemera-Doubal method or principal component analysis. We used synthetic and real data to illustrate the consequences if this assumption does not hold.RESULTS: The most popular cross-sectional biological age predictors all use the same strong underlying assumption, namely that a candidate marker of aging's association with chronological age is directly informative of its association with the aging rate ∆. We called this the identical-association assumption and proved that it is untestable in a cross-sectional setting. If this assumption does not hold, weights assigned to candidate markers of aging are uninformative, and no more signal may be captured than if markers would have been assigned weights at random.CONCLUSIONS: Cross-sectional methods for predicting biological age commonly use the untestable identical-association assumption, which previous literature in the field had never explicitly acknowledged. These methods have inherent limitations and may provide uninformative results, highlighting the importance of researchers exercising caution in the development and interpretation of cross-sectional biological age predictors. <<<

Chao Zhang, Zihan Xu, Shangda Yang, Guohuan Sun, Lumeng Jia, Zhaofeng Zheng, Quan Gu, Wei Tao, Tao Cheng, Cheng Li, Hui Cheng <<<

Spatiotemporal chromatin reorganization during hematopoietic differentiation has not been comprehensively characterized, mainly because of the large numbers of starting cells required for current chromatin conformation capture approaches. Here, we introduce a low-input tagmentation-based Hi-C (tagHi-C) method to capture the chromatin structures of hundreds of cells. Using tagHi-C, we are able to map the spatiotemporal dynamics of chromatin structure in ten primary hematopoietic stem, progenitor, and differentiated cell populations from mouse bone marrow. Our results reveal that changes in compartment dynamics and the Rabl configuration occur during hematopoietic cell differentiation. We identify gene-body-associating domains (GADs) as general structures for highly expressed genes. Moreover, we extend the body of knowledge regarding genes influenced by genome-wide association study (GWAS) loci through spatial chromatin looping. Our study provides the tagHi-C method for studying the three-dimensional (3D) genome of a small number of cells and maps the comprehensive 3D chromatin landscape of bone marrow hematopoietic cells. <<<

Confocal Raman spectroscopy (CRS) is a powerful tool that has been widely used for biological tissue analysis because of its noninvasive nature, high specificity, and rich biochemical information. However, current commercial CRS systems suffer from limited detection regions (450-1750 cm), bulky sizes, nonflexibilities, slow acquisitions by consecutive excitations, and high costs if using a Fourier transform (FT) Raman spectroscopy with an InGaAs detector, which impede their adoption in clinics. In this study, we developed a portable CRS system with a simultaneous dual-wavelength source and a miniaturized handheld probe (120 mm × 60 mm × 50 mm) that can acquire spectra in both fingerprint (FP, 450-1750 cm) and high wavenumber (HW, 2800-3800 cm) regions simultaneously. An innovative design combining 671 and 785 nm lasers for simultaneous excitation through a compact and high-efficiency (>90%) wavelength combiner was implemented. Moreover, to decouple the fused FP and HW spectra, a first-of-its-kind precise Raman spectra separation algorithm (PRSSA) was developed based on the maximum probability (MAP) estimate. The accuracy of spectra separation was greater than 99%, demonstrated in both phantom experiments and human skin measurements. The total data acquisition time was reduced by greater than 50% compared to other CRS systems. The results proved our proposed CRS system and PRSSA's superior capability in fast and ultrawideband spectra acquisition will significantly improve the integration of CRS in the clinical workflow. <<<

The relation between children's lie-telling and their social and cognitive development was examined. Children (3-8 years) were told not to peek at a toy. Most children peeked and later lied about peeking. Children's subsequent verbal statements were not always consistent with their initial denial and leaked critical information revealing their deceit. Children's conceptual moral understanding of lies, executive functioning, and theory-of-mind understanding were also assessed. Children's initial false denials were related to their first-order belief understanding and their inhibitory control. Children's ability to maintain their lies was related to their second-order belief understanding. Children's lying was related to their moral evaluations. These findings suggest that social and cognitive factors may play an important role in children's lie-telling abilities. <<<

DNA has been pursued as a compelling medium for digital data storage during the past decade. While large-scale data storage and random access have been achieved in artificial DNA, the synthesis cost keeps hindering DNA data storage from popularizing into daily life. In this study, we proposed a more efficient paradigm for digital data compressing to DNA, while excluding arbitrary sequence constraints. Both standalone neural networks and pre-trained language models were used to extract the intrinsic patterns of data, and generated probabilistic portrayal, which was then transformed into constraint-free nucleotide sequences with a hierarchical finite state machine. Utilizing these methods, a 12%-26% improvement of compression ratio was realized for various data, which directly translated to up to 26% reduction in DNA synthesis cost. Combined with the progress in DNA synthesis, our methods are expected to facilitate the realization of practical DNA data storage. <<<

The endoplasmic reticulum (ER) presents unique properties to establishing bacterium symbiosis in eukaryotic cells since it synthesizes and glycosylates essential molecules like proteins and lipids. Tunicamycin (TM) is an antibiotic that inhibits the first step in the N-linked glycosylation in eukaryotes and has been used as an ER stress inducer to activate the Unfolded Protein Response (UPR). Mutualistic symbiosis in trypanosomatids is characterized by structural adaptations and intense metabolic exchanges, thus we investigated the effects of TM in the association between Angomonas deanei and its symbiotic bacterium, through ultrastructural and proteomic approaches. Cells treated with the inhibitor showed a decrease in proliferation, enlargement of the ER and Golgi cisternae and an increased distance between the symbiont and the ER. TM proved to be an important tool to better understand ER stress in trypanosomatids, since changes in protein composition were observed in the host protozoan, especially the expression of the Hsp90 chaperone. Furthermore, data obtained indicates the importance of the ER for the adaptation and maintenance of symbiotic associations between prokaryotes and eukaryotes, considering that this organelle has recognized importance in the biogenesis and division of cell structures. <<<

The hippocampal-entorhinal system encodes a map of space that guides spatial navigation. Goal-directed behaviour outside of spatial navigation similarly requires a representation of abstract forms of relational knowledge. This information relies on the same neural system, but it is not known whether the organisational principles governing continuous maps may extend to the implicit encoding of discrete, non-spatial graphs. Here, we show that the human hippocampal-entorhinal system can represent relationships between objects using a metric that depends on associative strength. We reconstruct a map-like knowledge structure directly from a hippocampal-entorhinal functional magnetic resonance imaging adaptation signal in a situation where relationships are non-spatial rather than spatial, discrete rather than continuous, and unavailable to conscious awareness. Notably, the measure that best predicted a behavioural signature of implicit knowledge and blood oxygen level-dependent adaptation was a weighted sum of future states, akin to the successor representation that has been proposed to account for place and grid-cell firing patterns. <<<

Schizophrenia is a heterogeneous psychiatric disorder that is poorly treated with current therapies. In this brief review, we provide an update regarding the use of animal models to study schizophrenia in an attempt to understand its aetiology and develop novel therapeutic strategies. Tremendous progress has been made developing and validating rodent models that replicate the aetiologies, brain pathologies, and behavioural abnormalities associated with schizophrenia in humans. Here, models are grouped into 3 categories-developmental, drug induced, and genetic-to reflect the heterogeneous risk factors associated with schizophrenia. Each of these models is associated with varied but overlapping pathophysiology, endophenotypes, behavioural abnormalities, and cognitive impairments. Studying schizophrenia using multiple models will permit an understanding of the core features of the disease, thereby facilitating preclinical research aimed at the development and validation of better pharmacotherapies to alter the progression of schizophrenia or alleviate its debilitating symptoms. <<<

Abstract There are various indicators i.e. Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD) , Stochastic Oscillator which have advantages in applications to determine not only market movements with buying and selling decisions in Computational Finance, but have significant drawbacks that discrepancies are easy to match against the best trading times due to fixed order-triggering boundaries and delay problems. For example, RSI ’s 70 and 30 overbuy and oversell are fixed boundaries. Orders can only be triggered when RSI’s value exceeds one of the boundaries. Its computation only considers past market situation prompting indicators like RSI to trigger orders with delay. In this paper, we proposed a method to reduce these problems with advanced AI technologies to generate indicators’ buy and sell signals executed in the best trading time. Recurrent Neural Network (RNN) has outstanding performance to learn time-series data automatic with long-time sequences but ordinary RNN units such as Long-Short-Term-Memory(LSTM) are unable to decipher the relationships between time units, so-called context. Hence, researchers have proposed an algorithm based on RNNs’ Attention Mechanism allowing RNNs to learn information such as chaotic attributes and Quantum properties contained in time sequences. Chaos Theory and Quantum Finance Theory (QFT) are also proposed to simulate these two features. One of the well-performed QFT models is Quantum Price Level (QPL) to simulate all possible vibration levels to locate price. The system used in this paper consists of two components - neural network and fuzzy logic. Neural networks are used to predict future data and to solve indicators lagging problem whereas fuzzy logic is used to solve fixed order-triggering boundaries problem. By combining these two core components, the proposed model has obtained remarkable results in backtesting previous data that it is possible for these methods to make better investment decisions when market changes constantly. <<<

Taila Hartley, Deborah Marshall, Meryl Acker, Katharine Fooks, Meredith K Gillespie, E Magda Price, Ian D Graham, Alexandre White-Brown, Layla MacKay, Stella K Macdonald, Lauren Brady, Angela Y Hui, Joseph D Andrews, Ashfia Chowdhury, Erika Wall, Élisabeth Soubry, Grace U Ediae, Samantha Rojas, Daniel Assamad, David Dyment, Mark Tarnopolsky, Sarah L Sawyer, Caitlin Chisholm, Gabrielle Lemire, Kimberly Amburgey, Joanna Lazier, Roberto Mendoza-Londono, James J Dowling, Tugce B Balci, Christine M Armour, Priya T Bhola, Gregory Costain, Lucie Dupuis, Melissa Carter, Lauren Badalato, Julie Richer, Christie Boswell-Patterson, Peter Kannu, Dawn Cordeiro, Jodi Warman-Chardon, Gail Graham, Victoria Mok Siu, Cheryl Cytrynbaum, Alison Rusnak, Ritu B Aul, Grace Yoon, Hernan Gonorazky, Vanda McNiven, Saadet Mercimek-Andrews, Andrea Guerin, Ashish R Deshwar, Ashish Marwaha, Rosanna Weksberg, Natalya Karp, Maggie Campbell, Sarah Al-Qattan, Andrew Y Shuen, Michal Inbar-Feigenberg, Ronald Cohn, Anna Szuto, Cara Inglese, Myriam Poirier, Lauren Chad, Beth Potter, Kym M Boycott, Robin Hayeems, Care4Rare Canada Consortium <<<

PURPOSE: To evaluate the diagnostic utility of publicly funded clinical exome sequencing (ES) for patients with suspected rare genetic diseases.METHODS: We prospectively enrolled 297 probands who met eligibility criteria and received ES across 5 sites in Ontario, Canada, and extracted data from medical records and clinician surveys. Using the Fryback and Thornbury Efficacy Framework, we assessed diagnostic accuracy by examining laboratory interpretation of results and assessed diagnostic thinking by examining the clinical interpretation of results and whether clinical-molecular diagnoses would have been achieved via alternative hypothetical molecular tests.RESULTS: Laboratories reported 105 molecular diagnoses and 165 uncertain results in known and novel genes. Of these, clinicians interpreted 102 of 105 (97%) molecular diagnoses and 6 of 165 (4%) uncertain results as clinical-molecular diagnoses. The 108 clinical-molecular diagnoses were in 104 families (35% diagnostic yield). Each eligibility criteria resulted in diagnostic yields of 30% to 40%, and higher yields were achieved when >2 eligibility criteria were met (up to 45%). Hypothetical tests would have identified 61% of clinical-molecular diagnoses.CONCLUSION: We demonstrate robustness in eligibility criteria and high clinical validity of laboratory results from ES testing. The importance of ES was highlighted by the potential 40% of patients that would have gone undiagnosed without this test. <<<