Spin-resolved counting statistics as a sensitive probe of spin correlation in transport through a quantum dot spin valve.

We investigate the noise in spin transport through a single quantum dot (QD) tunnel coupled to ferromagnetic (FM) electrodes with noncollinear magnetizations. Based on a spin-resolved quantum master equation, auto- and cross-correlations of spin-resolved currents are analyzed to reveal the underlying spin transport dynamics and characteristics for various polarizations. We find the currents of majority and minority spins could be strongly autocorrelated despite uncorrelated charge transfer. The interplay between tunnel coupling and the Coulomb interaction gives rise to an exchange magnetic field, leading to the precession of the accumulated spin in the QD. It strongly suppresses the bunching of spin tunneling events and results in a unique double-peak structure in the noise of the net spin current. The spin autocorrelation is found to be susceptible to magnetization alignments, which may serve as a sensitive tool to measure the magnetization directions between the FM electrodes.

Telomere length as a modifier in the relationship between phthalate metabolites exposure and glucose homeostasis.

Given the rising concern over the potential impact of environmental factors on metabolic heath, we conducted a cross-sectional analysis among 645 adults aged 20 and older in the National Health and Nutrition Examination Survey (NHANES), examining the association between nine phthalate metabolites (Mono-n-butyl phthalate (MBP), Mono-ethyl phthalate (MEP), Mono-(2-ethyl)-hexyl phthalate (MEHP), Mono-benzyl phthalate (MBzP), Mono-n-methyl phthalate (MnMP), Mono-(3-carboxy propyl) phthalate (MCPP), Mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), Mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), Mono-isobutyl phthalate (MiBP)) and six glucose homeostasis indices (fasting glucose, fasting insulin, hemoglobin A1C (HbA1C), homeostatic model assessment of insulin resistance (HOMA-IR), single Point Insulin Sensitivity Estimator (SPISE), and HOMA-ß). Latent Class Analysis identified three phthalate metabolites exposure patterns: high MEP-low MEOHP (n = 282), high MBzP-low MEHHP (n = 214), and high MEHHP, MEOHP (n = 149). The high MBzP-low MEHHP and high MEHHP, MEOHP, versus the high MEP-low MEOHP, exposure groups showed significantly higher levels of fasting insulin (ß = 0.126, 95% CI: 0.023-0.228), SPISE (ß = 0.091, 95% CI: 0.018-0.164), and HOMA-IR (ß = 0.091, 95% CI: 0.018-0.164). In the shorter telomere length group, high MEHHP, MEOHP exposure showed an increase in SPISE levels (ß = 0.153, 95% CI: 0.037-0.269), while in the overweight/obese subgroup, high MEHHP, MEOHP exposure was significantly positively associated with HOMA-IR (ß = 0.392, 95% CI: 0.150-0.735). Bayesian kernel machine regression analyses showed positive associations between higher combined phthalate exposure and increased glucose homeostasis indices (fasting glucose, HbA1C, fasting insulin, SPISE, and HOMA-IR). The quantile of g-calculation analysis also supported the positive associations with HbA1C, HOMA-IR, and fasting insulin. Our findings indicate that phthalate exposure was positively associated with glucose homeostasis indices, which strengthen the call for proactive measures to reduce phthalate exposure and mitigate potential risks to glucose metabolism.

Ancient and Modern Genomes Reveal Microsatellites Maintain a Dynamic Equilibrium Through Deep Time.

Microsatellites are widely used in population genetics, but their evolutionary dynamics remain poorly understood. It is unclear whether microsatellite loci drift in length over time. This is important because the mutation processes that underlie these important genetic markers are central to the evolutionary models that employ microsatellites. We identify more than 27 million microsatellites using a novel and unique dataset of modern and ancient Adélie penguin genomes along with data from 63 published chordate genomes. We investigate microsatellite evolutionary dynamics over 2 timescales: one based on Adélie penguin samples dating to ∼46.5 ka and the other dating to the diversification of chordates aged more than 500 Ma. We show that the process of microsatellite allele length evolution is at dynamic equilibrium; while there is length polymorphism among individuals, the length distribution for a given locus remains stable. Many microsatellites persist over very long timescales, particularly in exons and regulatory sequences. These often retain length variability, suggesting that they may play a role in maintaining phenotypic variation within populations.

Genomic characterization and risk stratification of esophageal squamous dysplasia.

Objectives: The majority of esophageal squamous dysplasia (ESD) patients progress slowly, while a subset of patients can undergo recurrence rapidly or progress to invasive cancer even after proper treatment. However, the molecular mechanisms underlying these clinical observations are still largely unknown. Methods: By sequencing the genomic data of 160 clinical samples from 49 tumor-free ESD patients and 88 esophageal squamous cell carcinoma (ESCC) patients, we demonstrated lower somatic mutation and copy number alteration (CNA) burden in ESD compared with ESCC. Results: Cross-species screening and functional assays identified ACSM5 as a novel driver gene for ESD progression. Furthermore, we revealed that miR-4292 promoted ESD progression and could serve as a non-invasive diagnostic marker for ESD. Conclusions: These findings largely expanded our understanding of ESD genetics and tumorigenesis, which possessed promising significance for improving early diagnosis, reducing overtreatment, and identifying high-risk ESD patients.