Somatic mutations and progressive monosomy modify SAMD9-related phenotypes in humans

It is well established that somatic genomic changes can influence phenotypes in cancer, but the role of adaptive changes in developmental disorders is less well understood. Here we have used next-generation sequencing approaches to identify de novo heterozygous mutations in sterile α motif domain–containing protein 9 (SAMD9, located on chromosome 7q21.2) in 8 children with a multisystem disorder termed MIRAGE syndrome that is characterized by intrauterine growth restriction (IUGR) with gonadal, adrenal, and bone marrow failure, predisposition to infections, and high mortality. These mutations result in gain of function of the growth repressor product SAMD9. Progressive loss of mutated SAMD9 through the development of monosomy 7 (–7), deletions of 7q (7q–), and secondary somatic loss-of-function (nonsense and frameshift) mutations in SAMD9 rescued the growth-restricting effects of mutant SAMD9 proteins in bone marrow and was associated with increased length of survival. However, 2 patients with –7 and 7q– developed myelodysplastic syndrome, most likely due to haploinsufficiency of related 7q21.2 genes. Taken together, these findings provide strong evidence that progressive somatic changes can occur in specific tissues and can subsequently modify disease phenotype and influence survival. Such tissue-specific adaptability may be a more common mechanism modifying the expression of human genetic conditions than is currently recognized

TAG: Learning Circuit Spatial Embedding From Layouts

Analog and mixed-signal (AMS) circuit designs still rely on human design expertise. Machine learning has been assisting circuit design automation by replacing human experience with artificial intelligence. This paper presents TAG, a new paradigm of learning the circuit representation from layouts leveraging text, self-attention and graph. The embedding network model learns spatial information without manual labeling. We introduce text embedding and a self-attention mechanism to AMS circuit learning. Experimental results demonstrate the ability to predict layout distances between instances with industrial FinFET technology benchmarks. The effectiveness of the circuit representation is verified by showing the transferability to three other learning tasks with limited data in the case studies: layout matching prediction, wirelength estimation, and net parasitic capacitance prediction.Comment: Accepted by ICCAD 202

Case Report Anaplastic Large-Cell Lymphoma in a Child with Type I Diabetes and Unrecognised Coeliac Disease

Screening for coeliac disease is recommended for children from certain risk groups, with implications for diagnostic procedures and dietetic management. The risk of a malignant complication in untreated coeliac disease is not considered high in children. We present the case of a girl with type I diabetes who developed weight loss, fatigue, and inguinal lymphadenopathy. Four years before, when she was asymptomatic, a screening coeliac tTG test was positive, but gluten was not eliminated from her diet. Based on clinical examination, a duodenal biopsy, and an inguinal lymph node biopsy were performed, which confirmed both coeliac disease and an anaplastic large-cell lymphoma. HLA-typing demonstrated that she was homozygous for HLA-DQ8, which is associated with higher risk for celiac disease, more severe gluten sensitivity, and diabetes susceptibility. She responded well to chemotherapy and has been in remission for over 4 years. She remains on a gluten-free diet. This is the first case reporting the association of coeliac disease, type I diabetes, and anaplastic large-cell lymphoma in childhood. The case highlights the malignancy risk in a genetically predisposed individual, and the possible role of a perpetuated immunologic response by prolonged gluten exposure

ChipNeMo: Domain-Adapted LLMs for Chip Design

ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we instead adopt the following domain adaptation techniques: domain-adaptive tokenization, domain-adaptive continued pretraining, model alignment with domain-specific instructions, and domain-adapted retrieval models. We evaluate these methods on three selected LLM applications for chip design: an engineering assistant chatbot, EDA script generation, and bug summarization and analysis. Our evaluations demonstrate that domain-adaptive pretraining of language models, can lead to superior performance in domain related downstream tasks compared to their base LLaMA2 counterparts, without degradations in generic capabilities. In particular, our largest model, ChipNeMo-70B, outperforms the highly capable GPT-4 on two of our use cases, namely engineering assistant chatbot and EDA scripts generation, while exhibiting competitive performance on bug summarization and analysis. These results underscore the potential of domain-specific customization for enhancing the effectiveness of large language models in specialized applications.Comment: Updated results for ChipNeMo-70B mode

Acute renal failure associated with Gemella haemolysans pneumonia

We describe a 13-year-old boy who developed acute renal failure associated with Gemella haemolysans pneumonia. At presentation he was found to have macroscopic hematuria associated with lobar pneumonia. Gemella haemolysans was isolated from blood cultures. Renal failure was detected on admission, progressed and dialysis was required until day 18. Renal impairment had resolved by 3 months after the initial presentation. Histopathology of a renal biopsy showed focal proliferative glomerulonephritis, but the predominant abnormality was tubular damage associated with erythrocyte casts in tubular lumina. We believe that tubular damage due to hematuria rather than the glomerular changes was the most likely cause of renal failure.</p

Anaplastic Large-Cell Lymphoma in a Child with Type I Diabetes and Unrecognised Coeliac Disease

Screening for coeliac disease is recommended for children from certain risk groups, with implications for diagnostic procedures and dietetic management. The risk of a malignant complication in untreated coeliac disease is not considered high in children. We present the case of a girl with type I diabetes who developed weight loss, fatigue, and inguinal lymphadenopathy. Four years before, when she was asymptomatic, a screening coeliac tTG test was positive, but gluten was not eliminated from her diet. Based on clinical examination, a duodenal biopsy, and an inguinal lymph node biopsy were performed, which confirmed both coeliac disease and an anaplastic large-cell lymphoma. HLA-typing demonstrated that she was homozygous for HLA-DQ8, which is associated with higher risk for celiac disease, more severe gluten sensitivity, and diabetes susceptibility. She responded well to chemotherapy and has been in remission for over 4 years. She remains on a gluten-free diet. This is the first case reporting the association of coeliac disease, type I diabetes, and anaplastic large-cell lymphoma in childhood. The case highlights the malignancy risk in a genetically predisposed individual, and the possible role of a perpetuated immunologic response by prolonged gluten exposure