Kidney Outcomes in the Very Low Birth Weight Population

From the Washington University Office of Undergraduate Research Digest (WUURD), Vol. 12, 05-01-2017. Published by the Office of Undergraduate Research. Joy Zalis Kiefer, Director of Undergraduate Research and Associate Dean in the College of Arts & Sciences; Lindsey Paunovich, Editor; Helen Human, Programs Manager and Assistant Dean in the College of Arts and Sciences Mentor: T. Keefe Davi

MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks

Recently, there has been a rapid advancement in research on Large Language Models (LLMs), resulting in significant progress in several Natural Language Processing (NLP) tasks. Consequently, there has been a surge in LLM evaluation research to comprehend the models' capabilities and limitations. However, much of this research has been confined to the English language, leaving LLM building and evaluation for non-English languages relatively unexplored. There has been an introduction of several new LLMs, necessitating their evaluation on non-English languages. This study aims to expand our MEGA benchmarking suite by including six new datasets to form the MEGAVERSE benchmark. The benchmark comprises 22 datasets covering 81 languages, including low-resource African languages. We evaluate several state-of-the-art LLMs like GPT-3.5-Turbo, GPT4, PaLM2, and Llama2 on the MEGAVERSE datasets. Additionally, we include two multimodal datasets in the benchmark and assess the performance of the LLaVa-v1.5 model. Our experiments suggest that GPT4 and PaLM2 outperform the Llama models on various tasks, notably on low-resource languages, with GPT4 outperforming PaLM2 on more datasets than vice versa. However, issues such as data contamination must be addressed to obtain an accurate assessment of LLM performance on non-English languages.Comment: 23 pages, 30 figures and 1 tabl

Differential gene expression analysis in germinating and dormant teliospores of Tilletia indica using RNA seq approach

Karnal bunt of wheat is an important quarantine disease that interrupts India’s wheat trade in the international market. The whole transcriptome of germinating and dormant teliospores of Tilletia indica was performed using the RNA Seq approach to identify germination-related genes. Approximately 63 million reads were generated using the RNA sequencing by the Illumina NextSeq500 platform. The high-quality reads were deposited in NCBI SRA database (accession: PRJNA522347). The unigenes from the pooled teliospores were 16,575 having unigenes length of 28,998,753 bases. The high-quality reads of germinating teliospores mapped on to 21,505 predicted CDSs. 9,680 CDSs were common between dormant and germinating teliospores of T. indica. 11,825 CDSs were found to be in germinating teliospores while only 91 were unique in dormant spores of pathogen. The pathway analysis showed the highest number of pathways was found in germinating spores than dormant spores. The highest numbers of CDSs were found to be associated with translation (431 in number), transport and catabolism (340), signal transduction (326), and carbohydrate metabolism (283). The differential expression analysis (DESeq) of germinating and dormant teliospores showed that 686 CDS were up-regulated and 114 CDS were down-regulated in the germinating teliospores. Significant germination-related genes in the spores were validated using qPCR analysis. Ten genes viz. Ti3931, Ti6828, Ti7098, Ti7462, Ti7522, Ti 9289, Ti 8670, Ti 7959, Ti 7809,and Ti10095 were highly up-regulated in germinated teliospores which may have role in germination of spores.Further, these differentially expressed genes provide insights into the molecular events. This first study of transcriptome will be helpful to devise better management strategies to manage Karnal bunt disease

Curcumin, inflammation, and neurological disorders: How are they linked?

Background: Despite the extensive research in recent years, the current treatment modalities for neurological disorders are suboptimal. Curcumin, a polyphenol found in Curcuma genus, has been shown to mitigate the pathophysiology and clinical sequalae involved in neuroinflammation and neurodegenerative diseases. Methods: We searched PubMed database for relevant publications on curcumin and its uses in treating neurological diseases. We also reviewed relevant clinical trials which appeared on searching PubMed database using ‘Curcumin and clinical trials’. Results: This review details the pleiotropic immunomodulatory functions and neuroprotective properties of curcumin, its derivatives and formulations in various preclinical and clinical investigations. The effects of curcumin on neurodegenerative diseases such as Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), brain tumors, epilepsy, Huntington's disorder (HD), ischemia, Parkinson's disease (PD), multiple sclerosis (MS), and traumatic brain injury (TBI) with a major focus on associated signalling pathways have been thoroughly discussed. Conclusion: This review demonstrates curcumin can suppress spinal neuroinflammation by modulating diverse astroglia mediated cascades, ensuring the treatment of neurological disorders

Design and delivery of the Refractive Errors Among Children (REACH) school-based eye health programme in India

Clinical relevance: Optimisation of vision screening programmes can result the detection of refractive anomalies in a high proportion of school children. Background: The Refractive Errors Among Children (REACH) programme aims to optimise outcomes of school-based vision screening in India by collaborating with hospitals and monitoring eye care throughout school attendance. Methods: REACH delivers school vision screening using pocket vision screeners (cards presenting rows of seven 0.2 logMAR Sloan letters at a 3 m viewing distance) in five states across India. Children who fail screening are referred for detailed evaluation including refraction, those requiring cycloplegic refraction are referred to partner hospitals. Spectacles are dispensed as needed and compliance is assessed. All data are recorded electronically. Results: Out of 2,240,805 children aged 5 to 18 (mean 11.5; SD ±3.3) years, 2,024,053 have undergone REACH screening in 10,309 schools predominantly in rural locations (78.7%) and government-funded (76%). Of those screened, 174,706 (8.6%) underwent detailed evaluation. A higher proportion of children in private or urban schools (11.8% and 10.4% respectively) were referred for detailed evaluation than those in government-funded or rural schools (5.9% and 7.2%, respectively; p < 0.001). The proportion referred for detailed evaluation differed by state (p < 0.001), from 4.0% in West Bengal to 14.4% in Kerala. Conclusion: The REACH programme screened a high proportion of school children, providing further care and follow-up to optimise visual outcomes