Tag: pubmed

Circ Cardiovasc Interv. 2024 Dec 27:e014610. doi: 10.1161/CIRCINTERVENTIONS.124.014610. Online ahead of print.

ABSTRACT

BACKGROUND: In the era of first-generation drug-eluting stents and angiography-guided percutaneous coronary intervention (PCI), the presence of a bifurcation lesion was associated with adverse outcomes after PCI. In contrast, the presence of a bifurcation lesion had no impact on outcomes following coronary artery bypass grafting (CABG). Therefore, the presence of a coronary bifurcation lesion requires special attention when choosing between CABG and PCI. The aim of this study is to assess whether the presence of a bifurcation lesion still influences clinical outcomes after contemporary PCI using second-generation drug-eluting stent and fractional flow reserve (FFR) guidance versus CABG.

METHODS: The randomized FAME 3 trial (Fractional Flow Reserve Versus Angiography for Multivessel Evaluation) compared FFR-guided PCI using current drug-eluting stents with CABG in patients with 3-vessel coronary artery disease. The prespecified key end point at 3-year follow-up was the composite of death, myocardial infarction, or stroke. In this substudy, the impact of bifurcation lesions on outcomes after FFR-guided PCI and CABG was investigated.

RESULTS: The FAME 3 trial enrolled 1500 patients and 653 (45.2%) patients had at least 1 true bifurcation lesion. There was no difference in the composite of death, myocardial infarction, or stroke at the 3-year follow-up between patients with or without at least 1 true bifurcation lesion (11.6% versus 10.0%; hazard ratio, 1.17 [95% CI, 0.86-1.61]; P=0.32), regardless of revascularization strategy. The composite end point was not statistically different between FFR-guided PCI and CABG in patients with at least 1 true bifurcation lesion (hazard ratio, 1.27 [95% CI, 0.80-2.00]) or without a true bifurcation lesion (hazard ratio, 1.36 [95% CI, 0.87-2.12]), with no significant interaction (P_interaction=0.81).

CONCLUSIONS: In patients with 3-vessel coronary artery disease, the presence of a true bifurcation lesion was not associated with a different treatment effect after FFR-guided PCI with contemporary drug-eluting stent versus CABG.

PMID:39727036 | DOI:10.1161/CIRCINTERVENTIONS.124.014610

Brief Bioinform. 2024 Nov 22;26(1):bbae672. doi: 10.1093/bib/bbae672.

ABSTRACT

Identifying phage-host interactions (PHIs) is a crucial step in developing phage therapy, which is the promising solution to addressing the issue of antibiotic resistance in superbugs. However, the lifestyle of phages, which strongly depends on their host for life activities, limits their cultivability, making the study of predicting PHIs time-consuming and labor-intensive for traditional wet lab experiments. Although many deep learning (DL) approaches have been applied to PHIs prediction, most DL methods are predominantly based on sequence information, failing to comprehensively model the intricate relationships within PHIs. Moreover, most existing approaches are limited for sub-optimal performance, due to the potential risk of overfitting induced by the highly data sparsity in the task of PHIs prediction. In this study, we propose a novel approach called MI-RGC, which introduces mutual information for feature augmentation and employs regional graph convolution to learn meaningful representations. Specifically, MI-RGC treats the presence status of phages in environmental samples as random variables, and derives the mutual information between these random variables as the dependency relationships among phages. Consequently, a mutual information-based heterogeneous network is construted as feature augmentation for sequence information of phages, which is utilized for building a sequence information-based heterogeneous network. By considering the different contributions of neighboring nodes at varying distances, a regional graph convolutional model is designed, in which the neighboring nodes are segmented into different regions and a regional-level attention mechanism is employed to derive node embeddings. Finally, the embeddings learned from these two networks are aggregated through an attention mechanism, on which the prediction of PHIs is condcuted accordingly. Experimental results on three benchmark datasets demonstrate that MI-RGC derives superior performance over other methods on the task of PHIs prediction.

PMID:39727002 | DOI:10.1093/bib/bbae672

J Hum Lact. 2024 Dec 27:8903344241304623. doi: 10.1177/08903344241304623. Online ahead of print.

ABSTRACT

Secondary data analysis has emerged as an important approach for researchers seeking to explore new research questions using existing datasets. These datasets often comprise large and diverse, as well as longitudinal data, enabling comprehensive analyses that might be impractical through primary data collection alone. This paper discusses the importance of secondary data analysis in breastfeeding research, provides examples of publicly available and restricted datasets containing breastfeeding variables, outlines the methodological steps in conducting secondary data analysis, and discusses common limitations associated with this approach. By emphasizing both the utility and challenges of secondary data analysis, the paper aims to encourage informed use of secondary data analysis to advance knowledge and address important research questions in breastfeeding.

PMID:39726998 | DOI:10.1177/08903344241304623

Glob Chang Biol. 2024 Dec;30(12):e70013. doi: 10.1111/gcb.70013.

ABSTRACT

In fire-prone regions such as the Mediterranean biome, fire seasons are becoming longer, and fires are becoming more frequent and severe. Post-fire recovery dynamics is a key component of ecosystem resilience and stability. Even though Mediterranean ecosystems can tolerate high exposure to extreme temperatures and recover from fire, changes in climate conditions and fire intensity or frequency might contribute to loss of ecosystem resilience and increase the potential for irreversible changes in vegetation communities. In this study, we assess the recovery rates of burned vegetation after recurrent fires across Mediterranean regions globally, based on remotely sensed Enhanced Vegetation Index (EVI) data, a proxy for vegetation status, from 2001 to 2022. Recovery rates are quantified through a statistical model of EVI time-series. This approach allows resolving recovery dynamics in time and space, overcoming the limitations of space-for-time approaches typically used to study recovery dynamics through remote sensing. We focus on pixels burning repeatedly over the study period and evaluate how fire severity, pre-fire vegetation greenness, and post-fire climate conditions modulate vegetation recovery rates of different vegetation types. We detect large contrasts between recovery rates, mostly explained by regional differences in vegetation type. Particularly, needle-leaved forests tend to recover faster following the second event, contrasting with shrublands that tend to recover faster from the first event. Our results also show that fire severity can promote a faster recovery across forested ecosystems. An important modulating role of pre-fire fuel conditions on fire severity is also detected, with pixels with higher EVI before the fire resulting in stronger relative greenness loss. In addition, post-fire climate conditions, particularly air temperature and precipitation, were found to modulate recovery speed across all regions, highlighting how direct impacts of fire can compound with impacts from climate anomalies in time and likely destabilise ecosystems under changing climate conditions.

PMID:39726993 | DOI:10.1111/gcb.70013

Front Microbiol. 2024 Dec 12;15:1504742. doi: 10.3389/fmicb.2024.1504742. eCollection 2024.

ABSTRACT

This study aimed to screen native methionine gamma-lyase (L-methioninase) producing bacteria from soil samples and optimize the culture media for enhanced enzyme production using statistical design. Three bacteria, Pseudomonas mosselii, Ralstonia solanacearum, and Cytobacillus kochii, were identified as novel L-methioninase producers, which alternative source of L-methioninase for cancer treatment could be utilized alongside other therapeutic agents. The bacteria were isolated from various garden soils and cultured on a modified M9 medium and screened by Nessler reagent. According to Bergey’s manual of systematic bacteriology, identification tests determined the morphological, physiological, and biochemical characterizations. Further identification was performed using the analysis of the 16 s rDNA gene sequences using PCR and universal bacterial primers. The optimization of medium constituents for L-methioninase production was performed in two steps using Response Surface Methodology (RSM). The first step used the “one factor at a time” method to screen and identify critical medium components for L-methioninase production. The second step used the Box-Behnken design to assess quadratic effects and two-way interactions between variables and determine the response’s nonlinear nature. The study found that three isolates produced L-methioninase, namely Pseudomonas mosselii spp.MN02 (GenBank PP431975), Ralstonia solanacearum spp.MN02 (GenBank PP431636), and Cytobacillus kochii spp.MN02 (GenBank PP432622). Among these, Pseudomonas mosselii spp.MN02 produced the highest amount of L-methioninase and was therefore chosen for enzyme production optimization process. The maximum L-methioninase production of 1.5 ± 0.1 U/mL was obtained at a pH 6, and the best nitrogen source was yeast extract (1% concentration). The influence of different carbon sources revealed that glucose was the best carbon source for L-methioninase production (3.25 ± 0.1 U/mL). The optimization experiments using the Box-Behnken design predicted that L-methioninase would have an activity of 12.56 U/mL under optimal conditions, including 2% glucose, 2% yeast extract, pH 6, and temperature at 30°C. In conclusion, this study presents a promising new methods for identifying potential L-methioninase producers and optimizing the culture medium for more enzyme production by microbial fermentation. This could pave the way for developing a drug that assists in human cancers treatment.

PMID:39726960 | PMC:PMC11669666 | DOI:10.3389/fmicb.2024.1504742

Front Microbiol. 2024 Dec 11;15:1491551. doi: 10.3389/fmicb.2024.1491551. eCollection 2024.

ABSTRACT

Yak (Bos grunniens) is a large ruminant endemic to the Tibetan plateau. The addition of enzyme complexes to feed can significantly improve their growth performance. Therefore, studying the effects of ruminant compound enzyme preparations dosage on yak rumen microorganisms and production performance is crucial to promoting the development of the yak industry. This study aimed to determine the effects of feeding yaks with different doses of ruminant enzyme compounds on the performance, meat quality, and rumen microorganisms of yaks. Three kinds of experimental diets with doses of 0.5 g/kg (LE group), 1 g/kg (ME group), and 2 g/kg (HE group) were selected to determine the growth index, meat quality, serum biochemical indexes, rumen fluid pH and other indexes of the three experimental groups. Metagenomics studies were used to investigate the differences in rumen microbial composition and function among yak groups, and transcriptome sequencing of the longest dorsal muscle was performed to reveal the expression of differential genes among different groups. It was determined that the levels of dietary enzyme complexes significantly affected growth performance, rumen fluid pH, and serum biochemical indices. At the phylum level, the dominant phylum in all three treatment groups was Bacteroidota, Bacillota, Kiritimatiellota, and Pseudomonadota. At the genus level, Prevotella, Methanobrevibacter, Oscillibacter. Fibrobacter showed statistically significant differences in abundance (p < 0.05). CAZymes family analysis revealed significant differences in GHs, CTs, and CEs among the three groups. Genome-wide differential gene expression in the longest muscle of the yak back was analyzed by RNA-seq between the three experimental groups. Some DEGs were found to be enriched in the ECM, PI3K-Akt, PPAR, and protein digestion and absorption receptor pathways. Combined metagenomics and transcriptomics analyses revealed that some microorganisms were significantly associated with the genes COL11A1, POSTN, and PTHLH, which are involved in growth metabolism. In summary, this study investigated the effects and interrelationships of ruminant complex enzymes on yak performance, meat quality, and rumen environment. The results of this study provide a scientific basis for adding ruminant enzymes to yaks.

PMID:39726957 | PMC:PMC11670318 | DOI:10.3389/fmicb.2024.1491551

Front Genet. 2024 Dec 12;15:1488425. doi: 10.3389/fgene.2024.1488425. eCollection 2024.

ABSTRACT

BACKGROUND: Noonan syndrome (NS) is a rare group of autosomal genetic disorders. In recent years, with the exploration and development of molecular diagnostic techniques, more and more researchers have begun to pay attention to NS. However, there is still a lack of reports on the bibliometric analysis of NS worldwide. This study aims to assess the current research status and development trend of NS, to explore the research hotspots and emerging topics, and to point out the direction for future scientific research.

METHODS: Web of Science Core Collection was selected as the search database for bibliometric analysis of NS-related publications from 1998 to 2023. Statistical and visual analysis of the number of publications, countries, institutions, authors, journals, keywords, and references were analyzed using Citespace, VOSviewer, Scimago Graphica, and BibliometrixR.

RESULTS: A total of 2041 articles were included in this study. The United States had the highest number of publications, and Istituto Superiore di Sanità, Italy, was the institution with the highest number of publications. TARTAGLIA M was the scientist with the highest number of publications and citations. Among the journals, AMERICAN JOURNAL OF MEDICAL GENETICS PART A has the highest output, and Nature Genetics is the most frequently cited. The reference with the highest outburst intensity is Roberts AE, LANCET, 2013. the cluster diagram divides all the keywords into seven categories, with the most vigorous outburst being “of function mutations.”

CONCLUSION: Research hotspots in the field of NS focus on the correspondence between NS genotype and phenotype and the precise diagnosis of NS. Future research efforts will explore more deeply from the perspective of long-term intervention strategies for NS. There is an urgent need to rely on significant research countries, institutions, journals, and authors to lead the construction of a more robust global collaborative network that will enhance research efficacy.

PMID:39726952 | PMC:PMC11669677 | DOI:10.3389/fgene.2024.1488425

Front Cardiovasc Med. 2024 Dec 12;11:1475483. doi: 10.3389/fcvm.2024.1475483. eCollection 2024.

ABSTRACT

BACKGROUND AND OBJECTIVES: The optimal timing for complete revascularization (CR) in patients with acute myocardial infarction (AMI) and multivessel disease (MVD) remain uncertain.

METHODS: This post-hoc analysis of the FRAME-AMI trial included AMI patients with MVD (n = 549). They were classified into immediate (n = 329) and staged CR (n = 220) groups. All percutaneous coronary interventions were performed during inex hospitalization. The primary endpoint was a composite of all-cause death, acute myocardial infarction, and repeated revascularization. Secondary endpoints included each component of the primary endpoint. Additional comparisons for the outcomes in ST-segment elevation myocardial infarction (STEMI) and non-STEMI (NSTEMI) were also performed.

RESULTS: The incidence of the primary endpoint was not significantly different in any of the AMI patients [12.7% [immediate CR] vs. 17.4% [staged CR], p = 0.905, adjusted hazard ratio [HR] of staged CR = 0.81, 95% confidence interval = 0.43-1.53, p = 0.528]. Other secondary endpoints were also not significantly different. Analyses of STEMI and Neither the primary or secondary endpoints of NSTEMI patients were significantly different.

CONCLUSIONS: In this post-hoc analysis of the FRAME-AMI trial, no significant difference in clinical outcomes was observed between the immediate and staged CR strategies for AMI with MVD and the subgroups, such as STEMI or NSTEMI. However, the results should be interpreted carefully because of the many limitations, including a limited sample size and a lack of statistical power. Trial Registration: FRAME-AMI clinicaltrials.gov, identifier (NCT02715518).

PMID:39726942 | PMC:PMC11669547 | DOI:10.3389/fcvm.2024.1475483

J Sci Comput. 2024 Jul;100(1):17. doi: 10.1007/s10915-024-02535-z. Epub 2024 Jun 3.

ABSTRACT

The numerical solution of differential equations using machine learning-based approaches has gained significant popularity. Neural network-based discretization has emerged as a powerful tool for solving differential equations by parameterizing a set of functions. Various approaches, such as the deep Ritz method and physics-informed neural networks, have been developed for numerical solutions. Training algorithms, including gradient descent and greedy algorithms, have been proposed to solve the resulting optimization problems. In this paper, we focus on the variational formulation of the problem and propose a Gauss-Newton method for computing the numerical solution. We provide a comprehensive analysis of the superlinear convergence properties of this method, along with a discussion on semi-regular zeros of the vanishing gradient. Numerical examples are presented to demonstrate the efficiency of the proposed Gauss-Newton method.

PMID:39726935 | PMC:PMC11671159 | DOI:10.1007/s10915-024-02535-z

World J Clin Cases. 2024 Dec 26;12(36):6916-6925. doi: 10.12998/wjcc.v12.i36.6916.

ABSTRACT

BACKGROUND: Obesity and type 2 diabetes mellitus (T2DM) are frequent co-occurring disorders that affect regular metabolic functions. Obesity has also been linked to an increased risk of developing diabetes. Obesity and diabetes are on the rise, increasing healthcare costs and raising mortality rates. Research has revealed that the expression profile of microRNAs (miRNAs) changes as diabetes progresses. Furthermore, vitamin D may have an anti-obesity effect and inverse association with body weight and body mass index (BMI). Low vitamin D levels do not solely cause obesity, which could be a factor in the etiology of T2DM.

AIM: To evaluate miRNA-200a and miRNA-200b expression, and vitamin-D levels in obese and obese T2DM individuals.

METHODS: This study included 210 participants, of which, 82 were obese (BMI > 30 kg/m²) without T2DM, 28 were obese with T2DM, and 100 were healthy controls. BMI was evaluated and both fasting and postprandial blood glucose were used to confirm T2DM. Exosomal miRNA-200a and miRNA-200b expression were analyzed using real-time PCR using Taqman probes, and vitamin-D levels were evaluated using an electrochemiluminescence-based immunoassay technique. All data analyses were performed using SPSS 20.0 and GraphPad Prism 5 software.

RESULTS: Overall, a 2.20- and 4.40-fold increase in miRNA-200a and miRNA-200b expression was observed among participants compared to healthy controls. MiRNA-200a and miRNA-200b expression among obese participants increased 2.40-fold and 3.93-fold, respectively, while in obese T2DM participants these values were 2.67-fold, and 5.78-fold, respectively, and these differences were found to be statistically significant (P = 0.02) (P < 0.0001). Obese participants showed a vitamin D level of 34.27 ng/mL, while in obese-T2DM participants vitamin D level was 22.21 ng/mL (P < 0.0001). Vitamin D was negatively correlated with miRNA-200a (r = -0.22, P = 0.01) and miRNA-200b (r = -0.19, P = 0.04). MiRNA-200a sensitivity was 75%, and specificity was 57%, with a cutoff value of 2.07-fold. MiRNA-200b sensitivity was 75%, and specificity was 71% with a cutoff value of 4.12-fold, suggesting that miRNA-200a and miRNA-200b with an increased expression of 2.07- and 4.12-fold could be predictive indicators for the risk of diabetes in obese participants.

CONCLUSION: MiRNA-200a and miRNA-200b were higher in diabetic obese participants vs non-diabetic obese participants, and insufficient vitamin D levels in obese T2DM participants may be involved in poor clinical outcome.

PMID:39726924 | PMC:PMC11531979 | DOI:10.12998/wjcc.v12.i36.6916