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1.
Horm Metab Res ; 55(11): 758-764, 2023 Nov.
Article in English | MEDLINE | ID: mdl-37903496

ABSTRACT

The abnormal hemoglobin (HGB) and serum lipid concentrations during pregnancy will increase the risk of preterm delivery. Our study aimed to explore the correlation between prenatal HGB and serum lipid levels and preterm delivery. We enrolled 215 mother-infant pairs in a pilot cohort study. The logistic regression model and Restricted Cubic Spline model (RCS) were used to investigate the levels of prenatal blood HGB and serum lipid such as triglyceride (TG), total cholesterol, high-density lipoprotein, low density lipoprotein and preterm delivery. The results showed that moderate levels of prenatal blood HGB (OR=0.28; 95%CI: 0.10, 0.75, p-trend=0.018) and high level of serum TG (OR=0.29; 95%CI: 0.10, 0.84, p-trend=0.022) level were negatively associated with the risk of preterm delivery. The joint effect results showed that compared with lower level of prenatal blood HGB (≤123.13 g/l) and TG (≤3.7 mmol/l), we found that high levels prenatal blood HGB and serum TG (OR=0.32, 95%CI: 0.12, 0.89) had a negative association with the risk of preterm delivery. Moreover, prenatal blood HGB and serum TG levels had negative linear dose-effect relationships with the risk of preterm delivery in overall and girl group (p<0.05). Moderate levels of prenatal blood HGB and high level of serum TG were negatively associated with the risk of preterm delivery. The joint effect of high levels prenatal HGB and prenatal serum TG in the normal range were negatively correlated with preterm delivery. Moreover, the underlying mechanisms should be clarified in future studies.


Subject(s)
Premature Birth , Pregnancy , Infant, Newborn , Female , Humans , Pilot Projects , Triglycerides , Lipoproteins, HDL , Hemoglobins
2.
Heliyon ; 10(18): e37778, 2024 Sep 30.
Article in English | MEDLINE | ID: mdl-39328519

ABSTRACT

Background: Hemoglobin (HGB) was the most important factors which could cause dysmenorrhea in women. Metals exposure and hemoglobin level in dysmenorrhea female was unclear. We aimed to explore the associations of multi-metal exposure and HGB level in female college students with dysmenorrhea. Methods: 253 female students who had dysmenorrhea was included in our study. The Last Absolute Shrinkage and Selection Operator (LASSO) regression, generalized linear model (GLM), and Bayesian Kernel Machine Regression (BKMR) models were used to explore the associations of multi-metal exposure and HGB levels in female college students with dysmenorrhea. Results: GLM results showed that plasma Fe, Ni and Rb was positively associated with HGB and plasma Co was negatively associated with HGB. In menarche age ≤13 years old group, plasma Co and Rb only was negatively and positively associated with HGB level, respectively, and plasma Ni had positive association with HGB level in menarche age >13 years old group. BKMR results showed the reverse U-shaped relationship between the five metals mixture (Co, Fe, Ni, Cu and Rb) and HGB levels in overall and menarche age ≤13 years old group. However, there were positive association between the five metals mixture and HGB levels in menarche age >13 years old group. Conclusion: Our present study revealed that metals (Fe, Ni, Co, Rb, Cu) mixture exposure could effect HGB levels in female college students with dysmenorrhea. And the relationships were different during different menarche age in female college students.

3.
Sci Total Environ ; 925: 171736, 2024 May 15.
Article in English | MEDLINE | ID: mdl-38494026

ABSTRACT

Studies on the relationships between metal mixtures exposure and cognitive impairment in elderly individuals are limited, particularly the mechanism with metabolite. Few studies are available on the potential sex and age specific associations between metal exposure, metabolites and cognitive impairment. We examined plasma metal and blood metabolite concentrations among 1068 urban elderly participants. Statistical analysis included a battery of variable selection approaches, logistic regression for metal/metabolite associations, and Bayesian kernel machine regression (BKMR) to identify mixed effects of metals/metabolites on cognitive impairment risk. Our results showed that As was positively associated with cognitive impairment in the female (OR 95 % CI = 2.21 (1.36, 3.57)) and 60- to 70-year-old (OR 95 % CI = 2.60 (1.54, 4.41)) groups, Cr was positively associated with cognitive impairment in the male (OR 95 % CI = 2.15 (1.27, 3.63)) and 60- to 70-year-old (OR 95 % CI = 2.10 (1.24, 3.57)) groups, and Zn was negatively associated with cognitive impairment, especially in the female (OR 95 % CI = 0.46 (0.25, 0.84)), 60- to 70-year-old (OR 95 % CI =0.24 (0.12, 0.45)) and ≥ 80-year-old (OR 95 % CI = 0.19 (0.04, 0.86)) groups. Positive associations were observed between combined metals (Cr, Cu and As) and cognitive impairment, but Zn alleviated this tendency, especially in elderly individuals aged ≥80 years. Negative associations were observed between metabolites and cognitive impairment, especially in male, female and 60-70 years old groups. The mediation effects of metabolites on the association between metal exposure and cognitive impairment were observed, and the percentages of these effects were 15.60 % (Glu-Cr), 23.00 % (C5:1-Cu) and 16.36 % (Glu-Zn). Cr, Cu, and Zn could increase cognitive impairment risk through the "Malate-Aspartate Shuttle", "Glucose-Alanine Cycle", etc., pathways. Overall, we hypothesize that metabolites have mediation effects on the relationship between multi-metal exposure and cognitive impairment and that there are sex and age differences.


Subject(s)
Glucose , Metals , Aged , Humans , Male , Female , Middle Aged , Aged, 80 and over , Bayes Theorem
4.
Front Microbiol ; 13: 963488, 2022.
Article in English | MEDLINE | ID: mdl-36033885

ABSTRACT

The coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). According to the World Health Organization statistics, more than 500 million individuals have been infected and more than 6 million deaths have resulted worldwide. Although COVID-19 mainly affects the respiratory system, considerable evidence shows that the digestive, cardiovascular, nervous, and reproductive systems can all be involved. Angiotensin-converting enzyme 2 (AEC2), the target of SARS-CoV-2 invasion of the host is mainly distributed in the respiratory and gastrointestinal tract. Studies found that microbiota contributes to the onset and progression of many diseases, including COVID-19. Here, we firstly conclude the characterization of respiratory, gut, and oral microbial dysbiosis, including bacteria, fungi, and viruses. Then we explore the potential mechanisms of microbial involvement in COVID-19. Microbial dysbiosis could influence COVID-19 by complex interactions with SARS-CoV-2 and host immunity. Moreover, microbiota may have an impact on COVID-19 through their metabolites or modulation of ACE2 expression. Subsequently, we generalize the potential of microbiota as diagnostic markers for COVID-19 patients and its possible association with post-acute COVID-19 syndrome (PACS) and relapse after recovery. Finally, we proposed directed microbiota-targeted treatments from the perspective of gut microecology such as probiotics and prebiotics, fecal transplantation and antibiotics, and other interventions such as traditional Chinese medicine, COVID-19 vaccines, and ACE2-based treatments.

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