Category: Nevin Manimala

Int J Fertil Steril. 2024 Feb 2;18(2):146-152. doi: 10.22074/ijfs.2023.560780.1357.

ABSTRACT

BACKGROUND: There is a definite shift in assisted reproductive centres from cleavage-stage embryo transfer (ET) to blastocyst transfer that is attributed to improvements in laboratory environments and advances in the development of embryo culture media. The aim of the study was to investigate the reproductive outcomes of thawed cleavage-stage ET versus blastocysts derived from an extended culture of these embryos.

MATERIALS AND METHODS: This open-label, randomised, parallel group clinical trial study enrolled 182 women aged ≤37 years who underwent frozen-thawed ET from November 2015 to June 2020 at Royan Institute Research Centre, Tehran, Iran. The women were randomly assigned to either the thawed cleavage ET group (n=110) or the post-thaw extended culture blastocysts group (n=72). The primary outcome measure was the clinical pregnancy rate. Secondary outcome measures were implantation rate, live birth rate (LBR), and miscarriage rate. A P<0.05 indicated statistical significance.

RESULTS: There were no significant differences between the two groups in terms of demographic characteristics. Both the mean numbers of embryos transferred and good quality embryos transferred were significantly lower in the postthaw extended culture blastocysts group compared to thawed cleavage-stage ET cycles. However, the post-thaw extended culture blastocysts group had higher clinical pregnancy (56.94 vs. 40.91%, P=0.034), implantation (34.43 vs. 19.84%, P=0.001) and live birth (49.3 vs. 33.63%, P=0.036) rates compared to the thawed cleavage-stage ET group. Miscarriage and multiple gestations rates were comparable between the groups.

CONCLUSION: These results allow us to take a position in favour of post-thaw extended culture blastocysts; thus, it is important to improve the post-thawing extended culture technique (registration number: NCT02681029).

PMID:38368518 | DOI:10.22074/ijfs.2023.560780.1357

Int J Fertil Steril. 2024 Feb 2;18(2):128-134. doi: 10.22074/ijfs.2023.1972708.1398.

ABSTRACT

BACKGROUND: The aim of this study was to evaluate the effects of thiamine (vitamin B1) on general health and infertility treatment outcomes in women with polycystic ovary syndrome (PCOS).

MATERIALS AND METHODS: The study is a triple-blinded, randomized, placebo-controlled clinical trial performed on 64 infertile women with PCOS referred to Sarem Hospital in Tehran, Iran. The primary outcomes of the study were general health and infertility treatment outcomes. Eligible women were randomly assigned to the vitamin B1 group (n=32, vitamin B1 tablet at a dose of 300 mg/day for 4 weeks) or the placebo group (n=32, placebo tablet daily for 4 weeks). A general health questionnaire was completed before and after the intervention by both groups, and treatment success was evaluated at the end of the study. Data were analyzed using SPSS software ver.16 P<0.05 was considered statistically significant.

RESULTS: The mean age of participants in the vitamin B1 (VB1) group was 30.4 ± 3.27 years and in the placebo (Pl) group was 29.1 ± 2.66 years with the mean duration of marriage 12.7 ± 3.01 and 13.2 ± 2.97 years respectively. Our results showed that there were significant differences between the two groups in overall score (P<0.001) and scores for all domains of the general health questionnaire including somatic symptoms (P<0.001), anxiety and insomnia (P<0.001), social dysfunction (P=0.028), and severe depression (P<0.001) after the intervention. Four weeks consumption of vitamin B1 also resulted in higher numbers of positive pregnancy tests (P=0.006), although the number of fetuses was not significantly different between the two groups after the intervention.

CONCLUSION: The results of the current study support a possible favourable effect of vitamin B1 on improving general health, infertility treatment outcome, and retrieved follicle count without changing the number of fetuses in women with polycystic ovary syndrome (registration number: IRCT201510266917N3).

PMID:38368515 | DOI:10.22074/ijfs.2023.1972708.1398

Int J Fertil Steril. 2024 Feb 2;18(2):123-127. doi: 10.22074/ijfs.2023.555447.1314.

ABSTRACT

BACKGROUND: Myometrial thickness has been expected to be a prognosticator for lower uterine segment function. An abnormal function of the uterine muscle layer can cause common and important reproductive problems. This study aimed to evaluate the relationship between baseline myometrial thickness and assisted reproductive technologies (ART) outcomes.

MATERIALS AND METHODS: In this prospective cohort study, 453 infertile women undergoing ART cycles without any obvious uterine pathology, participated in this prospective cohort study from February 2013 to May 2015. In order to measure the myometrial thickness in the anterior and posterior of the uterine, trans-vaginal ultrasounds were conducted on days 2-4 of the cycle (menstrual phase) preceding ovarian stimulation and the day of human chorionic gonadotropin (hCG) injection. We defined three groups based on the baseline myometrial thickness in the anterior and posterior, including (A) <25 mm, (B) 25-29.9 mm and (C) ≥30 mm. Ovarian stimulation, oocyte retrieval and luteal phase support were performed in accordance with the standard long protocol. Two weeks after embryo transfer, the patients underwent a pregnancy test by checking their serum β-hCG levels. The primary outcome measure was clinical pregnancy rate. Secondary outcome measures were, implantation rate, abortion rate and live birth rate.

RESULTS: The clinical pregnancy (P=0.013) and implantation (P=0.003) rates were significantly lower in group A than in two other groups. Although the live birth rate was lower in group A than two other groups, this decrease was not statistically significant (P=0.058).

CONCLUSION: The findings may be a way for clinicians to draw focus on providing therapeutic strategies and a specific supportive care for women with a baseline myometrial thickness <25 mm in order to improve the reproductive outcome of in vitro fertilization/intracytoplasmic sperm injection (IVF-ICSI).

PMID:38368514 | DOI:10.22074/ijfs.2023.555447.1314

J Community Health Nurs. 2024 Feb 17:1-13. doi: 10.1080/07370016.2024.2314076. Online ahead of print.

ABSTRACT

PURPOSE: This study aimed to explore help-seeking preference categories and crucial influencing factors among community nurses exposed to COVID-19 in China using a new person-centered approach.

DESIGN: A cross-sectional design including an online self-reported questionnaire survey was used.

METHODS: A total of 667 nurses who participated in COVID-19 prevention and control work were recruited. Latent class analysis and logistic regression were used to analyze the data using Mplus and SPSS.

FINDINGS: Two latent classes of help-seeking preferences were identified: high help-seeking preferences (33.58%) and low help-seeking preferences (66.42%). Most sampled nurses had relatively low help-seeking preferences when facing psychological threats during COVID-19. Logistic regression showed that career duration, perceived social support, online help-seeking intention, and social media exposure negatively affected low help-seeking preferences.

CONCLUSIONS: Career duration, perceived social support, online help-seeking intention, and social media exposure could be key factors influencing help-seeking preferences among Chinese nurses exposed to public emergencies. It is necessary to implement relevant intervention measures, such as focusing on nurses whose career durations are shorter, improving nurses’ perceived social support, strengthening positive media publicity, and developing comprehensive online mental health services that promote nurses’ help-seeking preferences and behaviors to reduce mental illness during public health emergencies.

CLINICAL EVIDENCE: Help-seeking preferences are relatively low among Chinese nurses during public emergencies. Based on the major influencing factors of help-seeking preferences, including social support and social media exposure, more interventions must be developed for prompting psychological help-seeking intentions among Chinese nurses.

PMID:38368504 | DOI:10.1080/07370016.2024.2314076

Sci Rep. 2024 Feb 17;14(1):3954. doi: 10.1038/s41598-024-54571-2.

ABSTRACT

This study investigates the impact of water levels and soil texture on the migration and transformation of nitrate (NO₃^–-N) and ammonium (NH₄⁺-N) within a soil column. The concentrations of NO₃^–-N gradually decreased from an initial concentration of 34.19 ± 0.86 mg/L to 14.33 ± 0.77 mg/L on day 70, exhibiting fluctuations and migration influenced by water levels and soil texture. Higher water levels were associated with decreased NO₃^–-N concentrations, while lower water levels resulted in increased concentrations. The retention and absorption capacity for NO₃^–-N were highest in fine sand soil, followed by medium sand and coarse sand, highlighting the significance of soil texture in nitrate movement and retention. The analysis of variance (ANOVA) confirmed statistically significant variations in pH, dissolve oxygen and oxidation-reduction potential across the soil columns (p < 0.05). Fluctuating water levels influenced the migration and transformation of NO₃^–-N, with distinct patterns observed in different soil textures. Water level fluctuations also impacted the migration and transformation of NH₄⁺-N, with higher water levels associated with increased concentrations and lower water levels resulting in decreased concentrations. Among the soil types considered, medium sand exhibited the highest absorption capacity for NH₄⁺-N. These findings underscore the significant roles of water levels, soil texture, and soil type in the migration, transformation, and absorption of nitrogen compounds within soil columns. The results contribute to a better understanding of nitrogen dynamics under varying water levels and environmental conditions, providing valuable insights into the patterns of nitrogen migration and transformation in small-scale soil column experiments.

PMID:38368500 | DOI:10.1038/s41598-024-54571-2

Sci Rep. 2024 Feb 17;14(1):3980. doi: 10.1038/s41598-024-54679-5.

ABSTRACT

This study examined the impact of the COVID-19 pandemic on marriage, divorce, birth, and death rates using the Poisson regression model and an interrupted time-series Poisson regression model. Before the pandemic, marriage and birth rates were decreasing, while divorce and death rates were increasing, with only the trend in birth rates being statistically significant. The immediate effect of the pandemic was a significant decrease in the divorce rate, but there were non-significant effects on birth and marriage rates. However, in the months following the onset of the pandemic, there was a statistically significant sustained effect on increasing death and divorce rates. Forecasts based on pre-pandemic data showed that by the end of 2020, marriage, divorce, death, and birth rates were higher compared to pre-pandemic levels. In conclusion, the pandemic has greatly impacted society, particularly in terms of death and divorce rates. Birth rates were not immediately affected to the time lag between decisions and actual births. Fear of COVID-19 may have increased death rates as people avoided seeking medical help. Vaccination and effective treatment strategies are vital in reducing the pandemic’s impact on mortality. Supporting families financially is important due to the role of economic issues in couples’ decisions.

PMID:38368489 | DOI:10.1038/s41598-024-54679-5

Sci Rep. 2024 Feb 17;14(1):3984. doi: 10.1038/s41598-024-54541-8.

ABSTRACT

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia in the elderly worldwide. The exact etiology of AD, particularly its genetic mechanisms, remains incompletely understood. Traditional genome-wide association studies (GWAS), which primarily focus on single-nucleotide polymorphisms (SNPs) with main effects, provide limited explanations for the “missing heritability” of AD, while there is growing evidence supporting the important role of epistasis. In this study, we performed a genome-wide SNP-SNP interaction detection using a linear regression model and employed multiple GPUs for parallel computing, significantly enhancing the speed of whole-genome analysis. The cerebrospinal fluid (CSF) phosphorylated tau (P-tau)/amyloid-[Formula: see text] (A[Formula: see text]) ratio was used as a quantitative trait (QT) to enhance statistical power. Age, gender, and clinical diagnosis were included as covariates to control for potential non-genetic factors influencing AD. We identified 961 pairs of statistically significant SNP-SNP interactions, explaining a high-level variance of P-tau/A[Formula: see text] level, all of which exhibited marginal main effects. Additionally, we replicated 432 previously reported AD-related genes and found 11 gene-gene interaction pairs overlapping with the protein-protein interaction (PPI) network. Our findings may contribute to partially explain the “missing heritability” of AD. The identified subnetwork may be associated with synaptic dysfunction, Wnt signaling pathway, oligodendrocytes, inflammation, hippocampus, and neuronal cells.

PMID:38368488 | DOI:10.1038/s41598-024-54541-8

Sci Data. 2024 Feb 17;11(1):217. doi: 10.1038/s41597-024-03039-z.

ABSTRACT

In this paper, we present MatKG, a knowledge graph in materials science that offers a repository of entities and relationships extracted from scientific literature. Using advanced natural language processing techniques, MatKG includes an array of entities, including materials, properties, applications, characterization and synthesis methods, descriptors, and symmetry phase labels. The graph is formulated based on statistical metrics, encompassing over 70,000 entities and 5.4 million unique triples. To enhance accessibility and utility, we have serialized MatKG in both CSV and RDF formats and made these, along with the code base, available to the research community. As the largest knowledge graph in materials science to date, MatKG provides structured organization of domain-specific data. Its deployment holds promise for various applications, including material discovery, recommendation systems, and advanced analytics.

PMID:38368452 | DOI:10.1038/s41597-024-03039-z

Sci Rep. 2024 Feb 17;14(1):3957. doi: 10.1038/s41598-024-53576-1.

ABSTRACT

This article presents a study, intending to design a model with 90% reliability, which helps in the prediction of school dropouts in higher and secondary education institutions, implementing machine learning techniques. The collection of information was carried out with open data from the 2015 Intercensal Survey and the 2010 and 2020 Population and Housing censuses carried out by the National Institute of Statistics and Geography, which contain information about the inhabitants and homes. in the 32 federal entities of Mexico. The data were homologated and twenty variables were selected, based on the correlation. After cleaning the data, there was a sample of 1,080,782 records in total. Supervised learning was used to create the model, automating data processing with training and testing, applying the following techniques, Artificial Neural Networks, Support Vector Machines, Linear Ridge and Lasso Regression, Bayesian Optimization, Random Forest, the first two with a reliability greater than 99% and the last with 91%.

PMID:38368429 | DOI:10.1038/s41598-024-53576-1

Eur J Med Res. 2024 Feb 17;29(1):133. doi: 10.1186/s40001-024-01722-w.

ABSTRACT

BACKGROUND: Studies in many populations have reported associations between circulating cytokine levels and various physiological or pathological conditions. However, the reliability of cytokine measurements in population studies, which measure cytokines in multiple assays over a prolonged period, has not been adequately examined; nor has stability during sample storage or intra-individual variation been assessed.

METHODS: We assessed (1) analytical reliability in short- and long-term repeated measurements; (2) stability and analytical reliability during long-term sample storage, and (3) variability within individuals over seasons, of four cytokines-osteopontin (OPN), osteoprotegerin (OPG), vascular endothelial growth factor-A (VEGF-A), and interleukin-17A (IL-17A). Measurements in plasma or serum samples were made with commercial kits according to standard procedures. Estimation was performed by fitting a random or mixed effects linear model on the log scale.

RESULTS: In repeated assays over a short period, OPN, OPG, and VEGF-A had acceptable reliability, with intra- and inter-assay coefficients of variation (CV) less than 0.11. Reliability of IL-17A was poor, with inter- and intra-assay CV 0.85 and 0.43, respectively. During long-term storage, OPG significantly decayed (- 33% per year; 95% confidence interval [- 54, – 3.7]), but not OPN or VEGF-A (- 0.3% or – 6.3% per year, respectively). Intra- and inter-assay CV over a long period were comparable to that in a short period except for a slight increase in inter-assay CV of VEGF-A. Within-individual variation was small for OPN and VEGF-A, with intra-class correlations (ICC) 0.68 and 0.83, respectively, but large for OPG (ICC 0.11).

CONCLUSIONS: We conclude that OPN and VEGF-A can be reliably measured in a large population, that IL-17A is suitable only for small experiments, and that OPG should be assessed with caution due to degradation during storage and intra-individual variation. The overall results of our study illustrate the need for validation under relevant conditions when measuring circulating cytokines in population studies.

PMID:38368424 | DOI:10.1186/s40001-024-01722-w