Re-Benchmarking Pool-Based Active Learning for Binary Classification

Active learning is a paradigm that significantly enhances the performance of machine learning models when acquiring labeled data is expensive. While several benchmarks exist for evaluating active learning strategies, their findings exhibit some misalignment. This discrepancy motivates us to develop a transparent and reproducible benchmark for the community. Our efforts result in an open-sourced implementation (https://github.com/ariapoy/active-learning-benchmark) that is reliable and extensible for future research. By conducting thorough re-benchmarking experiments, we have not only rectified misconfigurations in existing benchmark but also shed light on the under-explored issue of model compatibility, which directly causes the observed discrepancy. Resolving the discrepancy reassures that the uncertainty sampling strategy of active learning remains an effective and preferred choice for most datasets. Our experience highlights the importance of dedicating research efforts towards re-benchmarking existing benchmarks to produce more credible results and gain deeper insights

Investigating Zero-Shot Generalizability on Mandarin-English Code-Switched ASR and Speech-to-text Translation of Recent Foundation Models with Self-Supervision and Weak Supervision

This work evaluated several cutting-edge large-scale foundation models based on self-supervision or weak supervision, including SeamlessM4T, SeamlessM4T v2, and Whisper-large-v3, on three code-switched corpora. We found that self-supervised models can achieve performances close to the supervised model, indicating the effectiveness of multilingual self-supervised pre-training. We also observed that these models still have room for improvement as they kept making similar mistakes and had unsatisfactory performances on modeling intra-sentential code-switching. In addition, the validity of several variants of Whisper was explored, and we concluded that they remained effective in a code-switching scenario, and similar techniques for self-supervised models are worth studying to boost the performance of code-switched tasks.Comment: Submitted to ICASSP 2024 Self-supervision in Audio, Speech and Beyond worksho

The association of dimethylarginine dimethylaminohydrolase 1 gene polymorphism with type 2 diabetes: a cohort study

<p>Abstract</p> <p>Background</p> <p>Elevated plasma levels of asymmetric dimethylarginine (ADMA) has been reported to be associated with insulin resistance and micro/macrovascular diabetic complications, and may predict cardiovascular events in type 2 diabetic patients. Dimethylarginine dimethylaminohydrolase 1 (DDAH1) is the major enzyme eliminating ADMA in humans, but the effect of genetic variations in <it>DDAH1 </it>on type 2 diabetes and its long-term outcome are unknown.</p> <p>Methods</p> <p>From July 2006 to June 2009, we assessed the association between polymorphisms in <it>DDAH1 </it>and type 2 diabetes in 814 consecutive unrelated subjects, including 309 type 2 diabetic patients and 505 non-diabetic individuals. Six single nucleotide polymorphisms (SNPs) in <it>DDAH1</it>, rs233112, rs1498373, rs1498374, rs587843, rs1403956, and rs1241321 were analyzed. Plasma ADMA levels were determined by high performance liquid chromatography. Insulin sensitivity was assessed by the homeostasis model assessment of insulin resistance (HOMA-IR).</p> <p>Results</p> <p>Among the 6 SNPs, only rs1241321 was significantly associated with a decreased risk of type 2 diabetes (AA <it>vs </it>GG+AG, OR = 0.64, 95% CI 0.47-0.86, p = 0.004). The association remained unchanged after adjustment for plasma ADMA level. The fasting plasma glucose and log HOMA-IR tended to be lower in subjects carrying the homozygous AA genotype of rs1241321 compared with the GG+AG genotypes. Over a median follow-up period of 28.2 months, there were 44 all-cause mortality and 50 major adverse cardiovascular events (MACE, including cardiovascular death, non-fatal myocardial infarction and stroke). Compared with the GG and AG genotypes, the AA genotype of rs1241321 was associated with reduced risk of MACE (HR = 0.31, 95% CI: 0.11-0.90, p = 0.03) and all-cause mortality (HR = 0.18, 95% CI: 0.04-0.80, p = 0.02) only in subgroup with type 2 diabetes. One common haplotype (GGCAGC) was found to be significantly associated with a decreased risk of type 2 diabetes (OR = 0.67, 95% CI = 0.46-0.98, p = 0.04).</p> <p>Conclusions</p> <p>Our results provide the first evidence that SNP rs1241321 in <it>DDAH1 </it>is associated with type 2 diabetes and its long-term outcome.</p

Mixed Spices at Culinary Doses Have Prebiotic Effects in Healthy Adults: A Pilot Study.

Spices were used as food preservatives prior to the advent of refrigeration, suggesting the possibility of effects on microbiota. Previous studies have shown prebiotic activities in animals and in vitro, but there has not been a demonstration of prebiotic or postbiotic effects at culinary doses in humans. In this randomized placebo-controlled study, we determined in twenty-nine healthy adults the effects on the gut microbiota of the consumption daily of capsules containing 5 g of mixed spices at culinary doses by comparison to a matched control group consuming a maltodextrin placebo capsule. The 16S ribosomal RNA sequencing data were used for microbial characterization. Spice consumption resulted in a significant reduction in Firmicutes abundance (p &lt; 0.033) and a trend of enrichment in Bacteroidetes (p &lt; 0.097) compared to placebo group. Twenty-six operational taxonomic units (OTUs) were different between the spice and placebo groups after intervention. Furthermore, there was a significant negative correlation between fecal short-chain fatty acid propionate concentration and Firmicutes abundance in spice intervention group (p &lt; 0.04). The production of individual fecal short-chain fatty acid was not significantly changed by spice consumption in this study. Mixed spices consumption significantly modified gut microbiota, suggesting a prebiotic effect of spice consumption at culinary doses

Indomethacin protects rats from neuronal damage induced by traumatic brain injury and suppresses hippocampal IL-1β release through the inhibition of Nogo-A expression

BACKGROUND: Nogo-A is a member of the reticulon family of membrane-associated proteins and plays an important role in axonal remodeling. The present study aimed to investigate alterations in Nogo-A expression following traumatic brain injury (TBI)-induced inflammation and neuronal damage. METHODS: A weight-drop device was used to deliver a standard traumatic impact to rats. Western blot, RT-PCR and ELISA were used to analyze the expression of Nogo-A and IL-1β. Nogo-A antisense, and an irrelevant control oligonucleotide was intracerebroventricularly infused. We also performed H & E staining and luxol fast blue staining to evaluate the neuronal damage and demyelination resulting from TBI and various treatments. RESULTS: Based on RT-PCR and western blot analyses, the expression of Nogo-A was found to be significantly upregulated in the hippocampus beginning eight hours after TBI. In addition, TBI caused an apparent elevation in IL-1β levels and severe neuronal damage and demyelination in the tested animals. All of the TBI-associated molecular and cellular consequences could be effectively reversed by treating the animals with the anti-inflammatory drug indomethacin. More importantly, the TBI-associated stimulation in the levels of both Nogo-A and IL-1β could be effectively inhibited by a specific Nogo-A antisense oligonucleotide. CONCLUSIONS: Our findings suggest that the suppression of Nogo-A expression appears to be an early response conferred by indomethacin, which then leads to decreases in the levels of IL-1β and TBI-induced neuron damage

Single nucleotide polymorphisms of one-carbon metabolism and cancers of the esophagus, stomach, and liver in a Chinese population.

One-carbon metabolism (folate metabolism) is considered important in carcinogenesis because of its involvement in DNA synthesis and biological methylation reactions. We investigated the associations of single nucleotide polymorphisms (SNPs) in folate metabolic pathway and the risk of three GI cancers in a population-based case-control study in Taixing City, China, with 218 esophageal cancer cases, 206 stomach cancer cases, 204 liver cancer cases, and 415 healthy population controls. Study participants were interviewed with a standardized questionnaire, and blood samples were collected after the interviews. We genotyped SNPs of the MTHFR, MTR, MTRR, DNMT1, and ALDH2 genes, using PCR-RFLP, SNPlex, or TaqMan assays. To account for multiple comparisons and reduce the chances of false reports, we employed semi-Bayes (SB) shrinkage analysis. After shrinkage and adjusting for potential confounding factors, we found positive associations between MTHFR rs1801133 and stomach cancer (any T versus C/C, SB odds-ratio [SBOR]: 1.79, 95% posterior limits: 1.18, 2.71) and liver cancer (SBOR: 1.51, 95% posterior limits: 0.98, 2.32). There was an inverse association between DNMT1 rs2228612 and esophageal cancer (any G versus A/A, SBOR: 0.60, 95% posterior limits: 0.39, 0.94). In addition, we detected potential heterogeneity across alcohol drinking status for ORs relating MTRR rs1801394 to esophageal (posterior homogeneity P = 0.005) and stomach cancer (posterior homogeneity P = 0.004), and ORs relating MTR rs1805087 to liver cancer (posterior homogeneity P = 0.021). Among non-alcohol drinkers, the variant allele (allele G) of these two SNPs was inversely associated with the risk of these cancers; while a positive association was observed among ever-alcohol drinkers. Our results suggest that genetic polymorphisms related to one-carbon metabolism may be associated with cancers of the esophagus, stomach, and liver. Heterogeneity across alcohol consumption status of the associations between MTR/MTRR polymorphisms and these cancers indicates potential interactions between alcohol drinking and one-carbon metabolic pathway