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Journal of Taibah University Medical... Aug 2023This systematic review and meta-analysis was aimed at determining differentially expressed protein-based biomarkers detectable in the saliva for the diagnosis of major... (Review)
Review
OBJECTIVE
This systematic review and meta-analysis was aimed at determining differentially expressed protein-based biomarkers detectable in the saliva for the diagnosis of major periodontal diseases.
METHODS
A literature review was conducted through January 31, 2022. The methodological quality and risk of bias were assessed with the Newcastle-Ottawa scale for case-control studies. Heterogeneity among studies was analysed with the Q statistical test and the I test. p-values lower than 0.10 and I values higher than 50% indicated high heterogeneity among studies; therefore, the random-effects model was used. The analysis of biological pathways associated with the differentially expressed protein markers was performed with the STITCH integration analysis tool and was limited to interactions with high confidence levels (0.7).
RESULTS
Of all protein-based biomarkers detected, 12 were suitable for meta-analysis: IL-1β, MIP-1α, albumin, TNF-α, ICTP, Ig-A, lactoferrin, MMP-8, IL-6, IL-8, IL-17 and PGE2. The salivary markers with high applicability were IL-1β for differentiating patients with chronic periodontal disease from patients with gingivitis with an OE = 73.5 pg/mL; ICTP for differentiating patients with chronic periodontal disease from healthy control patients with an OE = 0.091 ng/mL; and PGE2 for differentiating patients with chronic periodontal disease from healthy control patients with an OE = 36.3 pg/mL.
CONCLUSIONS
The biomarkers with the highest differential expression and the greatest potential for clinical applicability are IL-1β for differentiating periodontitis from gingivitis, and ICTP and PGE2 for differentiating periodontitis from healthy status.
PubMed: 36852252
DOI: 10.1016/j.jtumed.2022.12.004 -
Gastroenterology and Hepatology From... 2022This systematic review and meta-analysis evaluated the subtyped sp. isolated from humans in Iran. (Review)
Review
AIM
This systematic review and meta-analysis evaluated the subtyped sp. isolated from humans in Iran.
BACKGROUND
sp. is an anaerobic intestinal protozoan that infects humans as well as domestic and wild animals, i.e. mammals, amphibians, reptiles, and arthropods.
METHODS
A comprehensive search for papers published before April 2022 was undertaken utilizing English and Persian databases. The following MeSH keywords were used in the electronic search: ( sp.) AND (molecular OR subtype) AND (prevalence OR epidemiology) AND Iran. The quality of the included studies was evaluated. Thereafter, a random-effects meta-analysis was conducted to estimate the pooled prevalence and odds ratios regarding the included studies.
RESULTS
A total of 32 studies comprised of five case-control studies and 27 cross-sectional studies met the eligibility criteria. The overall pooled prevalence of subtyped sp. in Iran was estimated to be 10% (95% confidence interval: 6 to 15%). Eight subtypes of sp. (ST1- ST7 and ST9) were identified in our study, of which ST3 was the most common subtype (0.04); 0.02-0.07). The difference in subtypes between two case and control groups in reported studies was not significant, but the odds ratio of infection by ST3 (0.98; 95% CI, 0.30 to 3.20) was higher in cases.
CONCLUSION
The current systematic review showed that with the exception of ST8 and ST12, all human sp. subtypes reported in the world are found in different parts of Iran.
PubMed: 36762220
DOI: 10.22037/ghfbb.v15i4.2475 -
Heliyon Feb 2024Type 2 diabetes (T2D) is a complex metabolic ailment marked by a global high prevalence and significant attention in primary healthcare settings due to its elevated...
BACKGROUND
Type 2 diabetes (T2D) is a complex metabolic ailment marked by a global high prevalence and significant attention in primary healthcare settings due to its elevated morbidity and mortality rates. The pathophysiological mechanisms underlying the onset and progression of this disease remain subjects of ongoing investigation. Recent evidence underscores the pivotal role of the intricate intercellular communication network, wherein cell-derived vesicles, commonly referred to as extracellular vesicles (EVs), emerge as dynamic regulators of diabetes-related complications. Given that the protein cargo carried by EVs is contingent upon the metabolic conditions of the originating cells, particular proteins may serve as informative indicators for the risk of activating or inhibiting signaling pathways crucial to the progression of T2D complications.
METHODS
In this study, we conducted a systematic review to analyze the published evidence on the proteome of EVs from the plasma or serum of patients with T2D, both with and without complications (PROSPERO: CRD42023431464).
RESULTS
Nine eligible articles were systematically identified from the databases, and the proteins featured in these articles underwent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. We identified changes in the level of 426 proteins, with CST6, CD55, HBA1, S100A8, and S100A9 reported to have high levels, while FGL1 exhibited low levels.
CONCLUSION
These proteins are implicated in pathophysiological mechanisms such as inflammation, complement, and platelet activation, suggesting their potential as risk markers for T2D development and progression. Further studies are required to explore this topic in greater detail.
PubMed: 38356516
DOI: 10.1016/j.heliyon.2024.e25537 -
Frontiers in Immunology 2022Tryptophan (TRP) is an essential amino acid that must be provided in the diet. The kynurenine pathway (KP) is the main route of TRP catabolism into nicotinamide... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Tryptophan (TRP) is an essential amino acid that must be provided in the diet. The kynurenine pathway (KP) is the main route of TRP catabolism into nicotinamide adenosine dinucleotide (NAD), and metabolites of this pathway may have protective or degenerative effects on the nervous system. Thus, the KP may be involved in neurodegenerative diseases.
OBJECTIVES
The purpose of this systematic review and meta-analysis is to assess the changes in KP metabolites such as TRP, kynurenine (KYN), kynurenic acid (KYNA), Anthranilic acid (AA), 3-hydroxykynurenine (3-HK), 5-Hydroxyindoleacetic acid (5-HIAA), and 3-Hydroxyanthranilic acid (3-HANA) in Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD) patients compared to the control group.
METHODS
We conducted a literature search using PubMed/Medline, Scopus, Google Scholar, Web of Science, and EMBASE electronic databases to find articles published up to 2022. Studies measuring TRP, KYN, KYNA, AA, 3-HK, 5-HIAA, 3-HANA in AD, PD, or HD patients and controls were identified. Standardized mean differences (SMDs) were used to determine the differences in the levels of the KP metabolites between the two groups.
RESULTS
A total of 30 studies compromising 689 patients and 774 controls were included in our meta-analysis. Our results showed that the blood levels of TRP was significantly lower in the AD (SMD=-0.68, 95% CI=-0.97 to -0.40, p=0.000, I2 = 41.8%, k=8, n=382), PD (SMD=-0.77, 95% CI=-1.24 to -0.30, p=0.001, I2 = 74.9%, k=4, n=352), and HD (SMD=-0.90, 95% CI=-1.71 to -0.10, p=0.028, I2 = 91.0%, k=5, n=369) patients compared to the controls. Moreover, the CSF levels of 3-HK in AD patients (p=0.020) and the blood levels of KYN in HD patients (p=0.020) were lower compared with controls.
CONCLUSION
Overall, the findings of this meta-analysis support the hypothesis that the alterations in the KP may be involved in the pathogenesis of AD, PD, and HD. However, additional research is needed to show whether other KP metabolites also vary in AD, PD, and HD patients. So, the metabolites of KP can be used for better diagnosing these diseases.
Topics: Humans; Kynurenine; Kynurenic Acid; Tryptophan; Hydroxyindoleacetic Acid; Alzheimer Disease; Parkinson Disease; Huntington Disease; 3-Hydroxyanthranilic Acid; NAD; Adenosine; Niacinamide
PubMed: 36263032
DOI: 10.3389/fimmu.2022.997240 -
Toxics Aug 2023Persistent Organic Pollutants (POPs) such as dichlorodimethyltrichloroethane (DDT) are present and ubiquitous in the environment due to their resilient nature. DDT is a... (Review)
Review
Persistent Organic Pollutants (POPs) such as dichlorodimethyltrichloroethane (DDT) are present and ubiquitous in the environment due to their resilient nature. DDT is a prevalent endocrine disruptor still found in detectable amounts in organisms and the environment even after its use was banned in the 1970s. Medline and Google Scholar were systematically searched to detect all relevant animal and human studies published in the last 20 years (January 2003 to February 2023) in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. In total, 38 studies were included for qualitative synthesis. This systematic search and review indicated that exposure to DDT is associated with female reproductive health issues, such as reduced fecundability; increased risk of preterm/premature deliveries; increased periods of gestation; alterations in the synthesis of crucial reproductive hormones (Progesterone and Oxytocin) through ion imbalances and changes in prostaglandin synthesis, myometrial and stromal hypertrophy, and edema; and variations in uterine contractions through increased uterine wet weight. There was also limited evidence indicating DDT as a carcinogen sufficient to instigate reproductive cancers. However, this review only takes into account the in vitro studies that have established a possible pathway to understand how DDT impacts female infertility and leads to reproductive cancers. Links between the pathways described in various studies have been developed in this review to produce a summarized picture of how one event might lead to another. Additionally, epidemiological studies that specifically targeted the exposure to DDT of females belonging to various ethnicities have been reviewed to develop an overall picture of prevailing female reproductive health concerns in different nations.
PubMed: 37755736
DOI: 10.3390/toxics11090725 -
Journal of the American Medical... Aug 2021To summarize how artificial intelligence (AI) is being applied in COVID-19 research and determine whether these AI applications integrated heterogenous data from... (Review)
Review
OBJECTIVE
To summarize how artificial intelligence (AI) is being applied in COVID-19 research and determine whether these AI applications integrated heterogenous data from different sources for modeling.
MATERIALS AND METHODS
We searched 2 major COVID-19 literature databases, the National Institutes of Health's LitCovid and the World Health Organization's COVID-19 database on March 9, 2021. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline, 2 reviewers independently reviewed all the articles in 2 rounds of screening.
RESULTS
In the 794 studies included in the final qualitative analysis, we identified 7 key COVID-19 research areas in which AI was applied, including disease forecasting, medical imaging-based diagnosis and prognosis, early detection and prognosis (non-imaging), drug repurposing and early drug discovery, social media data analysis, genomic, transcriptomic, and proteomic data analysis, and other COVID-19 research topics. We also found that there was a lack of heterogenous data integration in these AI applications.
DISCUSSION
Risk factors relevant to COVID-19 outcomes exist in heterogeneous data sources, including electronic health records, surveillance systems, sociodemographic datasets, and many more. However, most AI applications in COVID-19 research adopted a single-sourced approach that could omit important risk factors and thus lead to biased algorithms. Integrating heterogeneous data for modeling will help realize the full potential of AI algorithms, improve precision, and reduce bias.
CONCLUSION
There is a lack of data integration in the AI applications in COVID-19 research and a need for a multilevel AI framework that supports the analysis of heterogeneous data from different sources.
Topics: Algorithms; Artificial Intelligence; Biomedical Research; COVID-19; Databases as Topic; Humans; National Institutes of Health (U.S.); Proteomics; United States; World Health Organization
PubMed: 34151987
DOI: 10.1093/jamia/ocab098 -
International Journal of Reproductive... Apr 2018Uncontrolled increase of C-section is one of the major problems in Iranian health system, such that C-section is the most common surgical procedure in the entire... (Review)
Review
BACKGROUND
Uncontrolled increase of C-section is one of the major problems in Iranian health system, such that C-section is the most common surgical procedure in the entire country's hospitals in Obstetrics and Gynecology sections. A variety of complications also come along with cesarean.
OBJECTIVE
The aim of this study was to evaluate the prevalence, causes, and complications of cesarean in Iran.
MATERIALS AND METHODS
forty-one articles were considered with respect to certain criteria and were included in a systematic review to perform a meta-analysis study. The systematic review's search was conducted on SID, Iranmedx, Magiran, Medlib, PubMed, and Science Direct databases published between1999-2016. The weight of each included study was calculated according to its sample size and the reported prevalence of binomial distribution. A random-effects model using R and STATA (Version 11.2) software was utilized for analyzing data.
RESULTS
The total number of the sample was 197514 pregnant women with a mean age of 26.72 yr. The prevalence of cesarean in Iran was estimated at 48%. The main reasons for the prevalence of cesarean in this study were mothers' higher education, previous cesarean, and doctor recommendation. The most frequent complication in women undergoing cesarean was the muscular pain, and the most common fetal complications in newborns by caesarean delivery was transient tachypnea.
CONCLUSION
The prevalence of C-section in Iran is much higher than what WHO recommends. It is essential, to decrease such a phenomenon, making the mothers aware of the risks of cesarean delivery, and establishing counselling sessions as well to eliminate the mothers' fear of vaginal delivery.
PubMed: 29942930
DOI: No ID Found -
EClinicalMedicine Apr 2024Knowledge of gestational age (GA) is key in clinical management of individual obstetric patients, and critical to be able to calculate rates of preterm birth and small...
BACKGROUND
Knowledge of gestational age (GA) is key in clinical management of individual obstetric patients, and critical to be able to calculate rates of preterm birth and small for GA at a population level. Currently, the gold standard for pregnancy dating is measurement of the fetal crown rump length at 11-14 weeks of gestation. However, this is not possible for women first presenting in later pregnancy, or in settings where routine ultrasound is not available. A reliable, cheap and easy to measure GA-dependent biomarker would provide an important breakthrough in estimating the age of pregnancy. Therefore, the aim of this study was to determine the accuracy of prenatal and postnatal biomarkers for estimating gestational age (GA).
METHODS
Systematic review prospectively registered with PROSPERO (CRD42020167727) and reported in accordance with the PRISMA-DTA. Medline, Embase, CINAHL, LILACS, and other databases were searched from inception until September 2023 for cohort or cross-sectional studies that reported on the accuracy of prenatal and postnatal biomarkers for estimating GA. In addition, we searched Google Scholar and screened proceedings of relevant conferences and reference lists of identified studies and relevant reviews. There were no language or date restrictions. Pooled coefficients of correlation and root mean square error (RMSE, average deviation in weeks between the GA estimated by the biomarker and that estimated by the gold standard method) were calculated. The risk of bias in each included study was also assessed.
FINDINGS
Thirty-nine studies fulfilled the inclusion criteria: 20 studies (2,050 women) assessed prenatal biomarkers (placental hormones, metabolomic profiles, proteomics, cell-free RNA transcripts, and exon-level gene expression), and 19 (1,738,652 newborns) assessed postnatal biomarkers (metabolomic profiles, DNA methylation profiles, and fetal haematological components). Among the prenatal biomarkers assessed, human chorionic gonadotrophin measured in maternal serum between 4 and 9 weeks of gestation showed the highest correlation with the reference standard GA, with a pooled coefficient of correlation of 0.88. Among the postnatal biomarkers assessed, metabolomic profiling from newborn blood spots provided the most accurate estimate of GA, with a pooled RMSE of 1.03 weeks across all GAs. It performed best for term infants with a slightly reduced accuracy for preterm or small for GA infants. The pooled RMSEs for metabolomic profiling and DNA methylation profile from cord blood samples were 1.57 and 1.60 weeks, respectively.
INTERPRETATION
We identified no antenatal biomarkers that accurately predict GA over a wide window of pregnancy. Postnatally, metabolomic profiling from newborn blood spot provides an accurate estimate of GA, however, as this is known only after birth it is not useful to guide antenatal care. Further prenatal studies are needed to identify biomarkers that can be used in isolation, as part of a biomarker panel, or in combination with other clinical methods to narrow prediction intervals of GA estimation.
FUNDING
The research was funded by the Bill and Melinda Gates Foundation (INV-000368). ATP is supported by the Oxford Partnership Comprehensive Biomedical Research Centre with funding from the NIHR Biomedical Research Centre funding scheme. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, the Department of Health, or the Department of Biotechnology. The funders of this study had no role in study design, data collection, analysis or interpretation of the data, in writing the paper or the decision to submit for publication.
PubMed: 38495518
DOI: 10.1016/j.eclinm.2024.102498 -
Frontiers in Plant Science 2022Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under...
Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.
PubMed: 36570904
DOI: 10.3389/fpls.2022.1062952 -
Proteomics. Clinical Applications Dec 2014Biomarker analysis and proteomic discovery in pediatric sickle cell disease has the potential to lead to important discoveries and improve care. The aim of this review... (Review)
Review
Biomarker analysis and proteomic discovery in pediatric sickle cell disease has the potential to lead to important discoveries and improve care. The aim of this review article is to describe proteomic and biomarker articles involving neurological and developmental complications in this population. A systematic review was conducted to identify relevant research publications. Articles were selected for children under the age of 21 years with the most common subtypes of sickle cell disease. Included articles focused on growth factors (platelet-derived growth factor), intra and extracellular brain proteins (glial fibrillary acidic protein, brain-derived neurotrophic factor), and inflammatory and coagulation markers (interleukin-1β, l-selectin, thrombospondin-1, erythrocyte, and platelet-derived microparticles). Positive findings include increases in plasma brain-derived neurotrophic factor and platelet-derived growth factor with elevated transcranial Dopplers velocities, increases in platelet-derived growth factor isoform AA with overt stroke, and increases in glial fibrillary acidic protein with acute brain injury. These promising potential neuro-biomarkers provide insight into pathophysiologic processes and clinical events, but their clinical utility is yet to be established. Additional proteomics research is needed, including broad-based proteomic discovery of plasma constituents and blood cell proteins, as well as urine and cerebrospinal fluid components, before, during and after neurological and developmental complications.
Topics: Anemia, Sickle Cell; Biomarkers; Brain-Derived Neurotrophic Factor; Child; Humans; Nervous System Diseases; Platelet-Derived Growth Factor; Proteome; Proteomics
PubMed: 25290359
DOI: 10.1002/prca.201400069