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Gaseous oil fume is complex in composition and contains a large number of harmful volatile organic compounds (VOCs), which are one of the major pollutants in indoor air and also the major source of oil fume odor, with aldehydes accounting for the major proportion. This paper reviews the formation and composition of cooking oil fume, the hazards of and the detection methods for volatile aldehydes in cooking oil fume, and the factors influencing their formation. It also summarizes the current techniques to control the formation of aldehydes in cooking oil fume to provide a theoretical basis for the scientific regulation of aldehydes pollution from cooking oil fume.

Objective: To investigate the effect of body mass index (BMI) on progesterone (P) level on trigger day in gonadotropin-releasing hormone antagonist (GnRH-ant) cycles. Methods: This study was a retrospective cohort study. From October 2017 to April 2022, 412 in-vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) patients who were treated with GnRH-ant protocol for controlled ovarian hyperstimulation (COH) in the reproductive center of our hospital were selected as the research objects. Patients were divided into three groups according to BMI level: normal weight group (n = 230):18.5 kg/m2≤BMI < 24 kg/m2; overweight group (n = 122): 24 kg/m2≤BMI < 28 kg/m2; Obesity group (n = 60): BMI ≥ 28 kg/m2. Variables with p <.10 in univariate analysis (BMI, basal FSH, basal P, FSH days, Gn starting dose and E2 level on trigger day) and variables that may affect P level on trigger day (infertility factors, basal LH, total FSH, HMG days and total HMG) were included in the multivariate logistic regression model to analyze the effect of BMI on P level on trigger day of GnRH-ant protocol. Results: After adjustment for confounding factors, compared with that in normal weight patients, the risk of serum P elevation on trigger day was significantly lower in overweight and obese patients (OR = 0.434 and 0.199, respectively, p <.05). Conclusion: The risk of P elevation on trigger day in GnRH-ant cycles decreased with the increase of BMI, and BMI could be used as one of the predictors of P level on trigger day in GnRH-ant cycles. [ABSTRACT FROM AUTHOR]

Background: Epithelial ovarian cancer (EOC) remains an unmet medical challenge due to its insidious onset, atypical symptoms, and increasing resistance to conventional chemotherapeutic agents. It is imperative to explore novel biomarkers and generate innovative target drugs. Methods: To identify potential proteins with causal association to EOC subtypes, we conducted a Mendelian Randomization (MR) analysis using 15,419 protein quantitative trait loci (pQTLs) associated with 2015 proteins. Bayesian colocalization analysis, Summary-data-based MR, and Heterogeneity in Dependent Instruments tests were employed for validation. Enrichment and druggability analyses were performed to assess the biological significance and therapeutic potential of identified proteins. Results: Our analysis identified 455 unique proteins associated with at least one EOC subtype, with 14 protein-cancer associations confirmed by further validation. Ten proteins were prioritized as potential therapeutic targets, including α 1B-glycoprotein (A1BG) and ephrin-A1 (EFNA1), which interact with the known drug targets human epidermal growth factor receptor 2 (HER2) and vascular endothelial growth factor receptor (VEGFR). Conclusion: This study elucidated the plasma proteins causally associated with EOC subtypes, potentially offering easily detectable biomarkers and promising therapeutic targets. A1BG and EFNA1 were identified as druggable targets and confirmed to correspond with current pharmacological targets. Targeting these proteins in drug development potentially offers an avenue for innovative treatment strategies. [ABSTRACT FROM AUTHOR]

Magnetite nanoparticles (Fe3O4 NPs) have garnered significant attention over the past twenty years, primarily due to their superparamagnetic properties. These properties allow the NPs to respond to external magnetic fields, making them particularly useful in various technological applications. One of the most fascinating aspects of Fe3O4 NPs is their ability to self-assemble into complex structures. Research over this period has focused heavily on how these nanoparticles can be organized into a variety of superstructures, classified by their dimensionality—namely one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) configurations. Despite a wealth of studies, the literature lacks a systematic review that synthesizes these findings. This review aims to fill that gap by providing a thorough overview of the recent progress made in the fabrication and organization of Fe3O4 NP assemblies via a bottom-up self-assembly approach. This methodology enables the controlled construction of assemblies at the nanoscale, which can lead to distinctive functionalities compared to their individual counterparts. Furthermore, the review explores the diverse applications stemming from these nanoparticle assemblies, particularly emphasizing their contributions to important areas such as imaging, drug delivery, and the diagnosis and treatment of cancer. [ABSTRACT FROM AUTHOR]

Aims: To investigate the association between the number of oocytes and the polyspermy rate following in vitro fertilization (IVF) treatment. Materials and methods: 376 IVF cycles with gonadotropin-releasing hormone (GnRH) antagonist protocol in the reproductive center of our hospital were retrospectively included in the analysis, which were divided into five groups according to the number of oocytes retrieved. Group A (78 cases):1–5 oocytes, group B (118 cases): 6–10 oocytes, group C (94 cases): 11–15 oocytes, group D (55 cases): 16–20 oocytes, group E (31 cases): ≥21 oocytes. According to polyspermy rate, 376 IVF cycles were then divided into two groups. Normal level polyspermy group (170 cases): polyspermy rate<6%, and high level polyspermy group (206 cases): polyspermy rate ≥ 6%. The variables with p <.10 in univariate analysis were incorporated into the multiple logistic regression model to control the confounding, and the effect of the number of oocytes on the increase of polyspermy rate was analyzed. Results: Multiple logistic regression analysis showed that after adjustment for confounding factor, the increase risk of polyspermy rate in group B, C, D and E was 1.763, 3.804, 2.021 and 3.208 times of that in group A respectively (OR = 1.763, p =.085; OR = 3.804, p =.001; OR = 2.021, p =.158; OR = 3.208, p =.068, respectively). Conclusion: This result demonstrated that when the oocyte number is 15 or less, the more the oocyte number, the greater the increase risk of polyspermy rate. While, there appears to be little increase risk of polyspermy rate when the oocyte number is more than 15. [ABSTRACT FROM AUTHOR]