Spatially resolved transcriptomic profiling of placental development in dairy cow.

The placenta plays a crucial role in successful mammalian reproduction. Ruminant animals possess a semi-invasive placenta characterized by a highly vascularized structure formed by maternal endometrial caruncles and fetal placental cotyledons, essential for full-term fetal development. The cow placenta harbors at least two trophoblast cell populations: uninucleate (UNC) and binucleate (BNC) cells. However, the limited capacity to elucidate the transcriptomic dynamics of the placental natural environment has resulted in a poor understanding of both the molecular and cellular interactions between trophoblast cells and niches, and the molecular mechanisms governing trophoblast differentiation and functionalization. To fill this knowledge gap, we employed Stereo-seq to map spatial gene expression patterns at near single-cell resolution in the cow placenta at 90 and 130 days of gestation, attaining high-resolution, spatially resolved gene expression profiles. Based on clustering and cell marker gene expression analyses, key transcription factors, including YBX1 and NPAS2, were shown to regulate the heterogeneity of trophoblast cell subpopulations. Cell communication and trajectory analysis provided a framework for understanding cell-cell interactions and the differentiation of trophoblasts into BNCs in the placental microenvironment. Differential analysis of cell trajectories identified a set of genes involved in regulation of trophoblast differentiation. Additionally, spatial modules and co-variant genes that help shape specific tissue structures were identified. Together, these findings provide foundational insights into important biological pathways critical to the placental development and function in cows.

Physical activity attenuates the association of long-term exposure to nitrogen dioxide with sleep quality and its dimensions in Chinese rural older adults.

BACKGROUND: Joint impacts of air pollution and physical activity (PA) on sleep quality remain unaddressed. We aimed to investigate whether PA attenuates the association of long-term exposure to nitrogen dioxide (NO2) with sleep quality and its dimensions in older adults. METHODS: This study included 3408 Chinese rural older adults. Annual NO2 was estimated using the Space-Time Extra-Trees model. PA was assessed by International Physical Activity Questionnaire. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI) scale. Linear regression models were used to assess the associations of long-term NO2 exposure and PA with sleep quality and its dimensions, and interaction plots were used to depict the attenuating effect of PA on associations of NO2 with sleep quality and its dimensions. RESULTS: Three-year (3-y) average NO2 (per 0.64-µg/m3 increment) was positively associated with global PSQI (ß = 0.41, 95 % CI: 0.23, 0.59), sleep duration (ß = 0.16, 95 % CI: 0.11, 0.21), and habitual sleep efficiency (ß = 0.22, 95 % CI: 0.17, 0.27), while PA was negatively associated with global PSQI (ß = -0.33, 95 % CI: -0.46, -0.20) and five domains of PSQI other than sleep duration and sleep disturbances. The associations of NO2 with global PSQI, sleep duration, and habitual sleep efficiency were attenuated with increased PA (Pinteraction were 0.037, 0.020, and 0.079, respectively). CONCLUSIONS: PA attenuates the adverse impacts of long-term NO2 exposure on sleep quality, especially on sleep duration, and habitual sleep efficiency, in Chinese rural elderly people. Participating in PA should be encouraged in this population, and continued efforts are still needed to reduce air pollution.

The Association Between Essential Metal Element Mixture and Sleep Quality in Chinese Community-Dwelling Older Adults.

Previous studies have related single essential metal elements (EMEs) to sleep quality among older adults, however, the association of the EME mixture with sleep quality remained poorly understood. This study aimed to investigate the relationships between single EMEs and the EME mixture and sleep quality in older adults living in Chinese communities. This study consisted of 3957 older adults aged 60 years or over. Urinary concentrations of cobalt (Co), vanadium (V), selenium (Se), molybdenum (Mo), strontium (Sr), calcium (Ca), and magnesium (Mg) were detected using inductively coupled plasma mass spectrometry. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI). The associations of single EMEs and EME mixture with sleep quality were assessed using logistic regression and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted single-element logistic regression models showed that Mo (OR = 0.927, 95%CI:0.867-0.990), Sr (OR = 0.927, 95%CI:0.864-0.994), and Mg (OR = 0.934, 95%CI:0.873-0.997) were negatively related to poor sleep quality. BKMR models exhibited similar results. Also, higher levels of the EME mixture in urine were inversely related to the odds of poor sleep quality after adjustment for covariates, and Mo had the largest conditional posterior inclusion probability (condPIP) value in the mixture. Mo, Sr, and Mg were negatively related to poor sleep quality, separately and as the mixture. The EME mixture in urine was associated with decreased odds of poor sleep quality in older adults, and Mo was the greatest contributor within the mixture. Additional cohort research is warranted to clarify the relationship of multiple EMEs with sleep quality.

The associations of non-essential metal mixture with fasting plasma glucose among Chinese older adults without diabetes.

The evidence about the effect of non-essential metal mixture on fasting plasma glucose (FPG) levels among older adults without diabetes is limited. This study aims to estimate the individual and joint relationship between five non-essential metals and FPG levels in Chinese older adults without diabetes. This study included 2362 older adults without diabetes. Urinary concentrations of five non-essential metals, i.e., cesium (Cs), aluminum (Al), thallium (Tl), cadmium (Cd), and arsenic (As), were detected by inductively coupled plasma mass spectrometry (ICP-MS). The associations of single metals and the metal mixture with FPG levels were assessed using linear regression and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted single-metal linear regression models showed positive associations of urinary Al (ß = 0.016, 95%CI: 0.001-0.030) and Cs (ß = 0.018, 95%CI: 0.006-0.031) with FPG levels. When comparing the 2th, 3th, and 4th quartiles of urine Cs to its 1th quartile, the significant associations between Cs and FPG levels were found and presented as an "inverted U" trend (ßQ2 vs. Q1: 0.034; ßQ3 vs. Q1:0.054; ßQ4 vs. Q1: 0.040; all P<0.05). BKMR analyses showed urinary level of Cs exhibited an "inverted U" shape association with FPG levels. Moreover, the FPG levels increased linearly with the raised levels of the non-essential metal mixture, and the posterior inclusion probability (PIP) of Cs was the highest (0.92). Potential positive interaction of As and Cs on FPG levels was found in BKMR model. Stratified analysis displayed significant interactions of hyperlipidemia and urine Cs or Tl on FPG levels. An inverse U-shaped association between Cs and FPG was found, individually and as mixture. The FPG levels increased with the raised levels of the non-essential metal mixture, and Cs was the most contributor to FPG levels. Further research is required to confirm the correlation between non-essential metals and FPG levels and to clarify the underlying mechanisms.

The association between the essential metal mixture and fasting plasma glucose in Chinese community-dwelling elderly people.

BACKGROUND: Epidemiological studies about the effect of essential metal mixture on fasting plasma glucose (FPG) levels among elderly people are sparse. The object of this study was to examine the associations of single essential metals and essential metal mixture with FPG levels in Chinese community-dwelling elderly people. METHODS: The study recruited 2348 community-dwelling elderly people in total. Inductively coupled plasma-mass spectrometry was adopted to detect the levels of vanadium (V), selenium (Se), magnesium (Mg), cobalt (Co), calcium (Ca), and molybdenum (Mo) in urine. The relationships between single essential metals and essential metal mixture and FPG levels were evaluated by linear regression and Bayesian kernel machine regression (BKMR) models, respectively. RESULTS: In multiple-metal linear regression models, urine V and Mg were negatively related to the FPG levels (ß = - 0.016, 95 % CI: - 0.030 to - 0.003 for V; ß = - 0.021, 95 % CI: - 0.033 to - 0.009 for Mg), and urine Se was positively related to the FPG levels (ß = 0.024, 95 % CI: 0.014-0.034). In BKMR model, the significant relationships of Se and Mg with the FPG levels were also found. The essential metal mixture was negatively associated with FPG levels in a dose-response pattern, and Mg had the maximum posterior inclusion probability (PIP) value (PIP = 1.0000), followed by Se (PIP = 0.9968). Besides, Co showed a significant association with decreased FPG levels in older adults without hyperlipemia and in women. CONCLUSIONS: Both Mg and Se were associated with FPG levels, individually and as a mixture. The essential metal mixture displayed a linear dose-response relationship with reduced FPG levels, with Mg having the largest contribution to FPG levels, followed by Se. Further prospective investigations are necessary to validate these exploratory findings.