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

Spectrometer‐free Optical Hydrogen Sensing Based on Fano‐like Spatial Distribution of Transmission in a Metal−Insulator−Metal Plasmonic Doppler Grating

Optical nanosensors are promising for hydrogen sensing because they are small, free from spark generation, and feasible for remote optical readout. Conventional optical nanosensors require broadband excitation and spectrometers, rendering the devices bulky and complex. An alternative is spatial intensity-based optical sensing, which only requires an imaging system and a smartly designed platform to report the spatial distribution of analytical optical signals. Here, a spatial intensity-based hydrogen sensing platform is presented based on Fano-like spatial distribution of the transmission in a Pd-Al2O3-Au metal-insulator-metal plasmonic Doppler grating (MIM-PDG). The MIM-PDG manifests the Fano resonance as an asymmetric spatial transmission intensity profile. The absorption of hydrogen changes the spatial Fano-like transmission profiles, which can be analyzed with a “spatial” Fano resonance model and the extracted Fano resonance parameters can be used to establish analytical calibration lines. While gratings sensitive to hydrogen absorption are suitable for hydrogen sensing, hydrogen insensitive gratings are also found, which provide an unperturbed reference signal and may find applications in nanophotonic devices that require a stable optical response under fluctuating hydrogen atmosphere. The MIM-PDG platform is a spectrometer-free and intensity-based optical sensor that requires only an imaging system, making it promising for cellphone-based optical sensing applications. © 2021 The Authors. Advanced Optical Materials published by Wiley-VCH GmbH

PEFT for Speech: Unveiling Optimal Placement, Merging Strategies, and Ensemble Techniques

Parameter-Efficient Fine-Tuning (PEFT) is increasingly recognized as an effective method in speech processing. However, the optimal approach and the placement of PEFT methods remain inconclusive. Our study conducts extensive experiments to compare different PEFT methods and their layer-wise placement adapting Differentiable Architecture Search (DARTS). We also explore the use of ensemble learning to leverage diverse PEFT strategies. The results reveal that DARTS does not outperform the baseline approach, which involves inserting the same PEFT method into all layers of a Self-Supervised Learning (SSL) model. In contrast, an ensemble learning approach, particularly one employing majority voting, demonstrates superior performance. Our statistical evidence indicates that different PEFT methods learn in varied ways. This variation might explain why the synergistic integration of various PEFT methods through ensemble learning can harness their unique learning capabilities more effectively compared to individual layer-wise optimization.Comment: Accepted to ICASSP 2024 Self-supervision in Audio, Speech and Beyond (SASB) worksho

Comparison and Identification of Estrogen-Receptor Related Gene Expression Profiles in Breast Cancer of Different Ethnic Origins

The interactions between genetic variants in estrogen receptor (ER) have been identified to be associated with an increased risk of breast cancer. Available evidence indicates that genetic variance within a population plays a crucial role in the occurrence of breast cancer. Thus, the comparison and identification of ER-related gene expression profiles in breast cancer of different ethnic origins could be useful for the development of genetic variant cancer therapy. In this study, we performed microarray experiment to measure the gene expression profiles of 59 Taiwanese breast cancer patients; and through comparative bioinformatics analysis against published U.K. datasets, we revealed estrogen-receptor (ER) related gene expression between Taiwanese and British patients. In addition, SNP databases and statistical analysis were used to elucidate the SNPs associated with ER status. Our microarray results indicate that the expression pattern of the 65 genes in ER+ patients was dissimilar from that of the ER- patients. Seventeen mutually exclusive genes in ER-related breast cancer of the two populations with more than one statistically significant SNP in genotype and allele frequency were identified. These 17 genes and their related SNPs may be important in population-specific ER regulation of breast cancer. This study provides a global and feasible approach to study population-unique SNPs in breast cancer of different ethnic origins