Tag: pubmed

Diabetes Ther. 2023 Jul 14. doi: 10.1007/s13300-023-01444-y. Online ahead of print.

ABSTRACT

INTRODUCTION: This study utilized continuous glucose monitoring data to analyze the effects of switching to treatment with fast-acting insulin aspart (faster aspart) in adults with type 1 diabetes (T1D) in clinical practice.

METHODS: A noninterventional database review was conducted in Sweden among adults with T1D using multiple daily injection (MDI) regimens who had switched to treatment with faster aspart as part of basal-bolus treatment. Glycemic data were retrospectively collected during the 26 weeks before switching (baseline) and up to 32 weeks after switching (follow-up) to assess changes in time in glycemic range (TIR; 70-180 mg/dL), mean sensor glucose, glycated hemoglobin (HbA1c) levels, coefficient of variation, time in hyperglycemia (level 1, > 180 to ≤ 250 mg/dL; level 2, > 250 mg/dL), and time in hypoglycemia (level 1, ≥ 54 to < 70 mg/dL; level 2, < 54 mg/dL) (ClinicalTrials.gov Identifier NCT03895515).

RESULTS: Overall, 178 participants were included in the study cohort. The analysis population included 82 individuals (mean age 48.5 years) with adequate glucose sensor data. From baseline to follow-up, statistically significant improvements were reported for TIR (mean increase 3.3%-points [approximately 48 min/day]; p = 0.006) with clinically relevant improvement (≥ 5%) in 43% of participants. Statistically significant improvements from baseline were observed for mean sensor glucose levels, HbA1c levels, and time in hyperglycemia (levels 1 and 2), with no statistically significant changes in time spent in hypoglycemia.

CONCLUSIONS: Switching to faster aspart was associated with improvements in glycemic control without increasing hypoglycemia in adults with T1D using MDI in this real-world setting.

PMID:37450196 | DOI:10.1007/s13300-023-01444-y

Environ Sci Pollut Res Int. 2023 Jul 14. doi: 10.1007/s11356-023-28481-1. Online ahead of print.

ABSTRACT

The environment has become a growing concern for many countries, as pollution and other environmental degradation can harm human health, economic growth, and overall well-being. This paper probes into the asymmetrical implications of economic complexity and freedom on ecological quality in four South Asian countries from 1995 to 2019. Using Nonlinear Autoregressive Distributed Lag methodology approach, our findings indicate that carbon dioxide (CO₂) emissions are intensified by economic freedom both in the long and short term, while negative and positive shocks to economic complexity increase CO₂ emissions in the long term. However, a negative economic complexity shock increases CO₂ emissions, whereas a positive shock has the opposite effect in the short run. Moreover, our results confirm the validity of the environmental Kuznets curve (EKC) hypothesis in the long run. Furthermore, we find that renewable energy usage and the interaction of FDI and renewable energy usage can help reduce environmental damage in both the short and long run. The findings suggest that countries should focus on attracting foreign direct investment that promotes the use of renewable energy. Additionally, policies aimed at encouraging renewable energy use should be implemented. It is important to note that as economic freedom and complexity increase, there is a corresponding increase in CO₂ emissions. Therefore, South Asian policy makers are advised to prioritize the reduction in fossil fuels, the promotion of energy-saving technologies and efficient production, and trade that encourages the transition of renewable energy sources to reduce CO₂ emissions.

PMID:37450190 | DOI:10.1007/s11356-023-28481-1

Environ Sci Pollut Res Int. 2023 Jul 14. doi: 10.1007/s11356-023-28731-2. Online ahead of print.

ABSTRACT

We propose a climate change attention (CCA) index based on Google search volume index (GSVI) from 2004 to 2021 and show that it is an economically and statistically significant negative predictor for next month’s energy stock returns. The index is extracted using principal component analysis (PCA), but the results are similar by using the equal-weighted average method. Compared with 14 traditional macroeconomic predictors, CCA performs the best and provides complementary information when added into bivariate and multivariate macro predictive models. When further considering the effect of CCA’s forecasting power over different periods, strong evidence is shown that this outperformance is especially prominent in economic depressions and down market conditions. From the asset allocation perspective, CCA can provide a mean-variance investor with significant economic gains under alternative risk aversions. Our empirical results prove that investors’ attention to climate change contains predictive information for excess returns of global traditional energy stock index.

PMID:37450186 | DOI:10.1007/s11356-023-28731-2

Environ Sci Pollut Res Int. 2023 Jul 14. doi: 10.1007/s11356-023-28635-1. Online ahead of print.

ABSTRACT

Cutinase, a multifunctional enzyme, has shown great potential in environmental applications such as degradation of plastics and some commonly used insecticides. To overcome these environmental threatening problems, attempts should be made to enhance enzyme production. In the present study, a cutinolytic fungus was isolated from the soil. Based on 18 s rDNA sequencing, it was found that isolate AR08 belongs to the genus Fusarium and clades with Fusarium verticillioides. Optimization of medium composition for enhancement in cutinase production was done using. classical and statistical methods. Firstly, key factors were selected by one variable at a time (OVAT) method, then by Plackett- Burman design. Concentration of these important factors was optimized by Central Composite design. A total of 30 experiments were conducted and the optimized concentration of sodium nitrate, dipotassium hydrogen phosphate, flaxseed oil and zinc sulphate were found to be 0.455%, 0.305%, 2% and 0.0355% respectively. The result of ANOVA (analysis of variance) test revealed that p value was significant for the model. Interaction between flaxseed oil and sodium nitrate was found to have a positive effect on cutinase production. A 14.57 fold increase in enzyme activity was found under optimized conditions with the maximum cutinase activity of 626.6 IUml^-1.

PMID:37450178 | DOI:10.1007/s11356-023-28635-1

Methods Mol Biol. 2023;2690:335-354. doi: 10.1007/978-1-0716-3327-4_27.

ABSTRACT

Proteins are rapidly and dynamically post-transcriptionally modified as cells respond to changes in their environment. For example, protein phosphorylation is mediated by kinases while dephosphorylation is mediated by phosphatases. Quantifying and predicting interactions between kinases, phosphatases, and target proteins over time will aid the study of signaling cascades under a variety of environmental conditions. Here, we describe methods to statistically analyze label-free phosphoproteomic data and infer posttranscriptional regulatory networks over time. We provide an R-based method that can be used to normalize and analyze label-free phosphoproteomic data using variance stabilizing normalization and a linear mixed model across multiple time points and conditions. We also provide a method to infer regulator-target interactions over time using a discretization scheme followed by dynamic Bayesian modeling computations to validate our conclusions. Overall, this pipeline is designed to perform functional analyses and predictions of phosphoproteomic signaling cascades.

PMID:37450158 | DOI:10.1007/978-1-0716-3327-4_27

Methods Mol Biol. 2023;2690:299-310. doi: 10.1007/978-1-0716-3327-4_25.

ABSTRACT

Affinity purification coupled to mass spectrometry (AP-MS) is a powerful method to analyze protein-protein interactions (PPIs). The AP-MS approach provides an unbiased analysis of the entire protein complex and is useful to identify indirect interactors. However, reliable protein identification from the complex AP-MS experiments requires appropriate control of false identifications and rigorous statistical analysis. Another challenge that can arise from AP-MS analysis is to distinguish bona fide interacting proteins from the non-specifically bound endogenous proteins or the “background contaminants” that co-purified by the bait experiments. In this chapter, we will first describe the protocol for performing in-solution trypsinization for the samples from the AP experiment followed by LC-MS/MS analysis. We will then detail the MaxQuant workflow for protein identification and quantification for the PPI data derived from the AP-MS experiment. Finally, we describe the CRAPome interface to process the data by filtering against contaminant lists, score the interactions and visualize the protein interaction networks.

PMID:37450156 | DOI:10.1007/978-1-0716-3327-4_25

Methods Mol Biol. 2023;2690:179-192. doi: 10.1007/978-1-0716-3327-4_17.

ABSTRACT

Proteins are the building blocks of life, and a vast array of cellular processes is handled by protein-protein interactions (PPIs). The protein complexes formed via PPIs lead to tangled networks that, with their continuous remodeling, build up systematic functional units. Over the years, PPIs have become an area of interest for many researchers, leading to the development of multiple in vitro and in vivo methods to reveal these interactions. The yeast-two-hybrid (Y2H) system is a potent genetic way to map PPIs in both a micro- and high-throughput manner. Y2H is a technique that involves using modified yeast cells to identify protein-protein interactions. For Y2H, the yeast cells are engineered only to grow when there is a significant interaction between a specific protein with its interacting partner. PPIs are identified in the Y2H system by stimulating reporter genes in response to a restored transcription factor. However, Y2H results may be constrained by stringency requirements, as the limited number of colony screenings through this technique could result in the possible elimination of numerous genuine interactions. Therefore, DEEPN (dynamic enrichment for evaluation of protein networks) can be used, offering the potential to study the multiple static and transient protein interactions in a single Y2H experiment. DEEPN utilizes next-generation DNA sequencing (NGS) data in a high-throughput manner and subsequently applies computational analysis and statistical modeling to identify interacting partners. This protocol describes customized reagents and protocols through which DEEPN analysis can be utilized efficiently and cost-effectively.

PMID:37450148 | DOI:10.1007/978-1-0716-3327-4_17

Carbon Balance Manag. 2023 Jul 14;18(1):13. doi: 10.1186/s13021-023-00232-2.

ABSTRACT

BACKGROUND: Understanding temporal trends and varying responses of water use efficiency (WUE) to environmental changes of diverse ecosystems is key to predicting vegetation growth. WUE dynamics of major ecosystem types (e.g., forest, grassland and cropland) have been studied using various WUE definitions/metrics, but a comparative study on WUE dynamics and their driving forces among different ecosystem types using multiple WUE metrics is lacking. We used eddy covariance measurements for 42 FLUXNET2015 sites (396 site years) from 1997 to 2014, as well as three commonly used WUE metrics (i.e., ecosystem, inherent, and underlying WUE) to investigate the commonalities and differences in WUE trends and driving factors among deciduous broadleaf forests (DBFs), evergreen needleleaf forests (ENFs), grasslands, and croplands.

RESULTS: Our results showed that the temporal trends of WUE were not statistically significant at 73.8% of the forest, grassland and cropland sites, and none of the three WUE metrics exhibited better performance than the others in quantifying WUE. Meanwhile, the trends observed for the three WUE metrics were not significantly different among forest, grassland and cropland ecosystems. In addition, WUE was mainly driven by atmospheric carbon dioxide concentration at sites with significant WUE trends, and by vapor pressure deficit (VPD) at sites without significant trends (except cropland).

CONCLUSIONS: Our findings revealed the commonalities and differences in the application of three WUE metrics in disparate ecosystems, and further highlighted the important effect of VPD on WUE change.

PMID:37450075 | DOI:10.1186/s13021-023-00232-2

Langenbecks Arch Surg. 2023 Jul 14;408(1):277. doi: 10.1007/s00423-023-03006-z.

ABSTRACT

PURPOSE: Sexual dysfunction after inguinal hernia complication is considered rare. However, its consequences impact on quality of life inevitably. Laparoscopic and open inguinal hernia repair may be comparable in terms of recurrent rate, overall complications, and chronic pain. Therefore, its complication is still questionable between these approaches. In this study, we compared sexual dysfunction and related complications between laparoscopic and open inguinal hernia repair.

METHODS: Systematic review and meta-analysis of randomized controlled trials (RCTs) studies were performed to compare laparoscopic and open inguinal hernia repair. Risk ratio (RR) and 95% confidence intervals (95% CI) were used as pooled effect size measures.

RESULT: Thirty RCTs (12,022 patients) were included. Overall, 6014 (50.02%) underwent laparoscopic hernia repair, and 6008 (49.98%) underwent open hernia repair. Laparoscopic approach provided non-significance benefit on pain during sexual activity (RR 0.57; 95% CI 0.18, 1.76), Vas deferens injury (RR 0.46; 95% CI 0.13, 1.63), orchitis (RR 0.84; CI 0.61,1.17), scrotal hematoma (RR 0.99; CI 0.62,1.60), and testicular atrophy (RR 0.46; CI 0.17,1.20). Meanwhile, the open inguinal hernia approach seems to perform better for cord seroma complications and testicular pain.

CONCLUSION: There is no advantage of laparoscopic inguinal hernia repair over an open approach concerning sexual dysfunction. On the contrary, there is an increasing risk of cord seroma after laparoscopic inguinal hernia repair with statistical significance.

PMID:37450061 | DOI:10.1007/s00423-023-03006-z

Int Immunopharmacol. 2023 Jul 11;122:110596. doi: 10.1016/j.intimp.2023.110596. Online ahead of print.

ABSTRACT

Corona Virus Disease 2019 (COVID-19) is an acute respiratory infection and a global public health event. The level of aβ₂GPI is significantly up-regulated in COVID-19 patients. The impact of inactivated vaccination against COVID-19 on aβ₂GPI and in vitro fertilization and embryo transfer (IVF-ET) remains unknown amidst the universal administration of COVID-19 vaccines. We conducted a retrospective study to assess the impact of COVID-19 inactivated vaccination on aβ₂GPI levels and its effect on superovulation and pregnancy outcomes. We found aβ₂GPI level is significantly up-regulated after vaccination. There was no statistical difference in mature egg rate, 2PN fertilization rate, day 3 high-quality embryo rate, blastocyst formation rate, embryo implantation rate and miscarriage rate between the vaccine group and control group. Our findings showed vaccination with COVID-19 inactivated vaccine can elevate the level of aβ₂GPI in peripheral blood but have no effect on the outcomes of controlled ovarian hyperstimulation and pregnancy in IVF-ET.

PMID:37441812 | DOI:10.1016/j.intimp.2023.110596