Identification of two novel and one rare mutation in DYRK1A and prenatal diagnoses in three Chinese families with intellectual Disability-7

Background and purpose: Intellectual disability-7 (MRD7) is a subtype disorder of intellectual disability (MRD) involving feeding difficulties, hypoactivity, and febrile seizures at an age of early onset, then progressive intellectual and physical development deterioration. We purposed to identify the underlying causative genetic factors of three individuals in each Chinese family who presented with symptoms of intellectual disability and facial dysmorphic features. We provided prenatal diagnosis for the three families and genetic counseling for the prevention of this disease.Methods: We collected retrospective clinical diagnostic evidence for the three probands in our study, which included magnetic resonance imaging (MRI), computerized tomography (CT), electroencephalogram (EEG), and intelligence tests for the three probands in our study. Genetic investigation of the probands and their next of kin was performed by Trio-whole exome sequencing (WES). Sanger sequencing or quantitative PCR technologies were then used as the next step to verify the variants confirmed with Trio-WES for the three families. Moreover, we performed amniocentesis to explore the state of the three pathogenic variants in the fetuses by prenatal molecular genetic diagnosis at an appropriate gestational period for the three families.Results: The three probands and one fetus were clinically diagnosed with microcephaly and exhibited intellectual developmental disability, postnatal feeding difficulties, and facial dysmorphic features. Combining probands’ clinical manifestations, Trio-WES uncovered the three heterozygous variants in DYRK1A: a novel variant exon3_exon4del p.(Gly4_Asn109del), a novel variant c.1159C>T p.(Gln387*), and a previously presented but rare pathogenic variant c.1309C>T p.(Arg437*) (NM_001396.5) in three families, respectively. In light of the updated American College of Medical Genetic and Genomics (ACMG) criterion, the variant of exon3_exon4del and c.1159C>T were both classified as likely pathogenic (PSV1+PM6), while c1309C>T was identified as pathogenic (PVS1+PS2_Moderate+PM2). Considering clinical features and molecular testimony, the three probands were confirmed diagnosed with MRD7. These three discovered variants were considered as the three causal mutations for MRD7. Prenatal diagnosis detected the heterozygous dominant variant of c.1159C>T p.(Gln387*) in one of the fetuses, indicating a significant probability of MRD7, subsequently the gestation was intervened by the parents’ determination and professional obstetrical operation. On the other side, prenatal molecular genetic testing revealed wild-type alleles in the other two fetuses, and their parents both decided to sustain the gestation.Conclusion: We identified two novel and one rare mutation in DYRK1A which has broadened the spectrum of DYRK1A and provided evidence for the diagnosis of MRD7 at the molecular level. Besides, this study has supported the three families with MRD7 to determine the causative genetic factors efficiently and provide concise genetic counseling for the three families by using Trio-WES technology

Skywork: A More Open Bilingual Foundation Model

In this technical report, we present Skywork-13B, a family of large language models (LLMs) trained on a corpus of over 3.2 trillion tokens drawn from both English and Chinese texts. This bilingual foundation model is the most extensively trained and openly published LLMs of comparable size to date. We introduce a two-stage training methodology using a segmented corpus, targeting general purpose training and then domain-specific enhancement training, respectively. We show that our model not only excels on popular benchmarks, but also achieves \emph{state of the art} performance in Chinese language modeling on diverse domains. Furthermore, we propose a novel leakage detection method, demonstrating that test data contamination is a pressing issue warranting further investigation by the LLM community. To spur future research, we release Skywork-13B along with checkpoints obtained during intermediate stages of the training process. We are also releasing part of our SkyPile corpus, a collection of over 150 billion tokens of web text, which is the largest high quality open Chinese pre-training corpus to date. We hope Skywork-13B and our open corpus will serve as a valuable open-source resource to democratize access to high-quality LLMs

Association of Glomerular Filtration Rate with High-Sensitivity Cardiac Troponin T in a Community-Based Population Study in Beijing

BACKGROUND: Reduced renal function is an independent risk factor for cardiovascular disease mortality, and persistently elevated cardiac troponin T (cTnT) is frequently observed in patients with end-stage renal disease. In the general population the relationship between renal function and cTnT levels may not be clear because of the low sensitivity of the assay. In this study, we investigated the level of cTnT using a highly sensitive assay (hs-cTnT) and evaluated the association of estimated glomerular filtration rate (eGFR) with detectable hs-cTnT levels in a community-based population. METHODS: The serum hs-cTnT levels were measured in 1365 community dwelling population aged ≥45 years in Beijing, China. eGFR was determined by the Chinese modifying modification of diet in renal disease (C-MDRD) equation. RESULTS: With the highly sensitive assay, cTnT levels were detectable (≥3pg/mL) in 744 subjects (54.5%). The result showed that eGFR was associated with Log hs-cTnT (r = -0.14, P<0.001). After adjustment for the high predicted Framingham Coronary Heart Disease (CHD) risk (10-year risk >20%) and other prognostic indicators, moderate to severe reduced eGFR was independently associated with detectable hs-cTnT, whereas normal to mildly reduced eGFR was not independently associated with detectable hs-cTnT. In addition, after adjustment for other risk factors, the high predicted Framingham CHD risk was associated with detectable hs-cTnT in the subjects with different quartile levels of eGFR. CONCLUSION: The levels of hs-cTnT are detectable in a community-based Chinese population and low eGFR is associated with detectable hs-cTnT. Moreover, eGFR and high predicted Framingham CHD risk are associated with detectable hs-cTnT in subjects with moderate-to-severe reduced renal function

AdversarialWord Dilution as Text Data Augmentation in Low-Resource Regime

Data augmentation is widely used in text classification, especially in the low-resource regime where a few examples for each class are available during training. Despite the success, generating data augmentations as hard positive examples that may increase their effectiveness is under-explored. This paper proposes an Adversarial Word Dilution (AWD) method that can generate hard positive examples as text data augmentations to train the low-resource text classification model efficiently. Our idea of augmenting the text data is to dilute the embedding of strong positive words by weighted mixing with unknown-word embedding, making the augmented inputs hard to be recognized as positive by the classification model. We adversarially learn the dilution weights through a constrained min-max optimization process with the guidance of the labels. Empirical studies on three benchmark datasets show that AWD can generate more effective data augmentations and outperform the state-of-the-art text data augmentation methods. The additional analysis demonstrates that the data augmentations generated by AWD are interpretable and can flexibly extend to new examples without further training.Comment: Preprint, Accepted by AAAI 202

Adversarial Word Dilution as Text Data Augmentation in Low-Resource Regime

Data augmentation is widely used in text classification, especially in the low-resource regime where a few examples for each class are available during training. Despite the success, generating data augmentations as hard positive examples that may increase their effectiveness is under-explored. This paper proposes an Adversarial Word Dilution (AWD) method that can generate hard positive examples as text data augmentations to train the low-resource text classification model efficiently. Our idea of augmenting the text data is to dilute the embedding of strong positive words by weighted mixing with unknown-word embedding, making the augmented inputs hard to be recognized as positive by the classification model. We adversarially learn the dilution weights through a constrained min-max optimization process with the guidance of the labels. Empirical studies on three benchmark datasets show that AWD can generate more effective data augmentations and outperform the state-of-the-art text data augmentation methods. The additional analysis demonstrates that the data augmentations generated by AWD are interpretable and can flexibly extend to new examples without further training

Plasma homocysteine is associated with aortic arterial stiffness but not wave reflection in Chinese hypertensive subjects.

OBJECTIVE: Elevated plasma total homocysteine (tHcy) acts synergistically with hypertension to exert a multiplicative effect on cardiovascular diseases risk. The aim of this study was to determine the relationship between tHcy concentration and blood pressure, and to evaluate the role of plasma tHcy in arterial stiffness and wave reflection in hypertension. METHODS: In this cross-sectional study, a community-based sample of 1680 subjects (mean age 61.6 years) was classified into four groups according to tHcy level (<21.6 vs. ≥ 21.6 µmol/l) and blood pressure (hypertensive vs. normotensive). Levels of plasma tHcy and other biochemical parameters (e.g., lipids, glucose) were determined. Central arterial blood pressure, reflected pressure wave, and carotid-femoral pulse wave velocity (cf-PWV) were assessed by tonometry within 2 days of obtaining the blood specimen. RESULTS: Neither peripheral nor central blood pressure differed according to tHcy levels in normotensive and hypertensive subjects. Differences in cf-PWV according to tHcy were observed only in hypertensive subjects; differences in cf-PWV in normotensive subjects were not significant after adjusting for confounding factors. Central augmentation index did not differ according to tHcy level in either normotensive or hypertensive subjects. Results of univariate analysis revealed significant correlations between blood pressure parameters and tHcy concentration only among normotensive subjects; however, these correlations were not significant in a partial correlation analysis. Results of multiple regression analysis showed that plasma tHcy levels were independently correlated with cf-PWV in hypertensive subjects (β = 0.713, P = 0.004). The independent relationship between tHcy and central augmentation index was not significant by further multiple analyses in normotensive or hypertensive individuals. CONCLUSIONS: Plasma tHcy level is strongly and independently correlated with arterial stiffness measured as cf-PWV only in hypertensive subjects. Thus, hypertension is a major link between tHcy and aortic arterial stiffness

New development of non-rigid registration

We propose a new nonrigid registration algorithm which is based on the optimal control approach. In our previously proposed methods, the Jacobian determinant and the curl vector were used as control functions. In this algorithm, we use a new set of control functions. A main advantage of using the new controls is that the positivity and normalization of the Jacobian determinant are satisfied automatically. Numerical results on large deformation brain images are provided to show the accuracy and efficiency of the algorithm. doi:10.1017/S144618111400009