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BMC Medical Informatics and Decision... Dec 2023Invasive detection methods such as liver biopsy are currently the gold standard for diagnosing liver cirrhosis and can be used to determine the degree of liver fibrosis... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Invasive detection methods such as liver biopsy are currently the gold standard for diagnosing liver cirrhosis and can be used to determine the degree of liver fibrosis and cirrhosis. In contrast, non-invasive diagnostic methods, such as ultrasonography, elastography, and clinical prediction scores, can prevent patients from invasiveness-related discomfort and risks and are often chosen as alternative or supplementary diagnostic methods for liver fibrosis or cirrhosis. However, these non-invasive methods cannot specify the pathological grading and early diagnosis of the lesions. Recent studies have revealed that gut microbiome-based machine learning can be utilized as a non-invasive diagnostic technique for liver cirrhosis or fibrosis, but there is no evidence-based support. Therefore, this study conducted a systematic review and meta-analysis for the first time to investigate the accuracy of machine learning based on the gut microbiota in the prediction of liver fibrosis and cirrhosis.
METHODS
A comprehensive and systematic search of publications published before April 2th, 2023 in PubMed, Cochrane Library, Embase, and Web of Science was conducted for relevant studies on the application of gut microbiome-based metagenomic sequencing modeling technology to the diagnostic prediction of liver cirrhosis or fibrosis. A bivariate mixed-effects model and Stata software 15.0 were adopted for the meta-analysis.
RESULTS
Ten studies were included in the present study, involving 11 prediction trials and 838 participants, 403 of whom were fibrotic and cirrhotic patients. Meta-analysis showed the pooled sensitivity (SEN) = 0.81 [0.75, 0.85], specificity (SEP) = 0.85 [0.77, 0.91], positive likelihood ratio (PLR) = 5.5 [3.6, 8.7], negative likelihood ratio (NLR) = 0.23 [0.18, 0.29], diagnostic odds ratio (DOR) = 24 [14, 41], and area under curve (AUC) = 0.86 [0.83-0.89]. The results demonstrated that machine learning methods had excellent potential to analyze gut microbiome data and could effectively predict liver cirrhosis or fibrosis. Machine learning provides a powerful tool for non-invasive prediction and diagnosis of liver cirrhosis or liver fibrosis, with broad clinical application prospects. However, these results need to be interpreted with caution due to limited clinical data.
CONCLUSION
Gut microbiome-based machine learning can be utilized as a practical, non-invasive technique for the diagnostic prediction of liver cirrhosis or fibrosis. However, most of the included studies applied the random forest algorithm in modeling, so a diversified prediction system based on microorganisms is needed to improve the non-invasive detection of liver cirrhosis or fibrosis.
Topics: Humans; Gastrointestinal Microbiome; Liver Cirrhosis; Fibrosis; Machine Learning
PubMed: 38115019
DOI: 10.1186/s12911-023-02402-1 -
Plants (Basel, Switzerland) Dec 2021Resurrection plants have an extraordinary ability to survive extreme water loss but still revive full metabolic activity when rehydrated. These plants are useful models... (Review)
Review
Resurrection plants have an extraordinary ability to survive extreme water loss but still revive full metabolic activity when rehydrated. These plants are useful models to understand the complex biology of vegetative desiccation tolerance. Despite extensive studies of resurrection plants, many details underlying the mechanisms of desiccation tolerance remain unexplored. To summarize the progress in resurrection plant research and identify unexplored questions, we conducted a systematic review of 15 model angiosperm resurrection plants. This systematic review provides an overview of publication trends on resurrection plants, the geographical distribution of species and studies, and the methodology used. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses protocol we surveyed all publications on resurrection plants from 2000 and 2020. This yielded 185 empirical articles that matched our selection criteria. The most investigated plants were (17.5%), (13.7%), (reclassified as ) (11.9%), (8.5%), and (8.1%), with all other species accounting for less than 8% of publications. The majority of studies have been conducted in South Africa, Bulgaria, Germany, and China, but there are contributions from across the globe. Most studies were led by researchers working within the native range of the focal species, but some international and collaborative studies were also identified. The number of annual publications fluctuated, with a large but temporary increase in 2008. Many studies have employed physiological and transcriptomic methodologies to investigate the leaves of resurrection plants, but there was a paucity of studies on roots and only one metagenomic study was recovered. Based on these findings we suggest that future research focuses on resurrection plant roots and microbiome interactions to explore microbial communities associated with these plants, and their role in vegetative desiccation tolerance.
PubMed: 34961255
DOI: 10.3390/plants10122784 -
Cancers May 2023Oesophagogastric cancer is the fifth most common cancer worldwide, with poor survival outcomes. The role of bacteria in the pathogenesis of oesophagogastric cancer... (Review)
Review
OBJECTIVE
Oesophagogastric cancer is the fifth most common cancer worldwide, with poor survival outcomes. The role of bacteria in the pathogenesis of oesophagogastric cancer remains poorly understood.
DESIGN
A systematic search identified studies assessing the oesophagogastric cancer microbiome. The primary outcome was to identify bacterial enrichment specific to oesophagogastric cancer. Secondary outcomes included appraisal of the methodology, diagnostic performance of cancer bacteria and the relationship between oral and tissue microbiome.
RESULTS
A total of 9295 articles were identified, and 87 studies were selected for analysis. Five genera were enriched in gastric cancer: , , , and . No clear trends were observed in oesophageal adenocarcinoma. , and were abundant in oesophageal squamous cell carcinoma. Functional analysis supports the role of immune cells, localised inflammation and cancer-specific pathways mediating carcinogenesis. STORMS reporting assessment identified experimental deficiencies, considering batch effects and sources of contamination prevalent in low-biomass samples.
CONCLUSIONS
Functional analysis of cancer pathways can infer tumorigenesis within the cancer-microbe-immune axis. There is evidence that study design, experimental protocols and analytical techniques could be improved to achieve more accurate and representative results. Whole-genome sequencing is recommended to identify key metabolic and functional capabilities of candidate bacteria biomarkers.
PubMed: 37345006
DOI: 10.3390/cancers15102668 -
Seminars in Liver Disease Nov 2017The authors conducted a meta-analysis of the prevalence of small intestinal bacterial overgrowth (SIBO) in patients with chronic liver disease (CLD) and controls. Using... (Meta-Analysis)
Meta-Analysis Review
The authors conducted a meta-analysis of the prevalence of small intestinal bacterial overgrowth (SIBO) in patients with chronic liver disease (CLD) and controls. Using the search terms "small intestinal bacterial overgrowth (SIBO)" and "chronic liver disease (CLD)" or "cirrhosis," 19 case-control studies were identified. Utilizing breath tests, the prevalence of SIBO in CLD was 35.80% (95% CI, 32.60-39.10) compared with 8.0% (95% CI, 5.70-11.00) in controls. Using culture techniques, the prevalence was 68.31% (95% CI, 59.62-76.00) in CLD patients as compared with 7.94% (95% CI, 3.44-12.73) in controls. No difference between cirrhotic and noncirrhotic patients was found. SIBO is significantly more frequent in CLD patients as compared with controls. The association of SIBO and CLD was not confined to patients with advanced CLD, suggesting that SIBO is not a consequence of advanced liver disease but may play a role in the progression of CLD.
Topics: Bacteria; Disease Progression; Dysbiosis; Gastrointestinal Microbiome; Host-Pathogen Interactions; Humans; Intestine, Small; Liver Diseases; Prevalence; Prognosis; Risk Factors
PubMed: 29272899
DOI: 10.1055/s-0037-1608832 -
Water Research Apr 2021The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies... (Review)
Review
The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.
Topics: Cyanobacteria; Harmful Algal Bloom; High-Throughput Nucleotide Sequencing; Wastewater; Water
PubMed: 33610927
DOI: 10.1016/j.watres.2021.116907 -
Frontiers in Physiology 2021Our understanding of human gut microbiota has expanded in recent years with the introduction of high-throughput sequencing methods. These technologies allow for the...
Our understanding of human gut microbiota has expanded in recent years with the introduction of high-throughput sequencing methods. These technologies allow for the study of metagenomic, metatranscriptomic, and metabolomic bacterial alterations as they relate to human disease. Work in this area has described the human gut microbiome in both healthy individuals and those with chronic gastrointestinal diseases, such as eosinophilic esophagitis (EoE). A systematic review of the current available literature on metagenomic, metatranscriptomic, and metabolomic changes in EoE was performed. This review was performed following the PRISMA guidelines for reporting systematic reviews and meta-analyses. All relevant publications up to March 2021 were retrieved using the search engines PubMed, Google Scholar, and Web of Science. They were then extracted, assessed, and reviewed. Only original studies published in English were included. A total of 46 potential manuscripts were identified for review. Twelve met criteria for further review based on relevance screening and 9 met criteria for inclusion, including 6 studies describing the microbiome in EoE and 3 detailing metabolomic/tissue biochemistry alterations in EoE. No published studies examined metatranscriptomic changes. Samples for microbiome analysis were obtained via esophageal biopsy ( = 3), esophageal string test ( = 1), salivary sampling ( = 1), or stool specimen ( = 1). Samples analyzing tissue biochemistry were obtained via esophageal biopsy ( = 2) and blood plasma ( = 1). There were notable differences in how samples were collected and analyzed. Metabolomic and tissue biochemical alterations were described using Raman spectroscopy, which demonstrated distinct differences in the spectral intensities of glycogen, lipid, and protein content compared to controls. Finally, research in proteomics identified an increase in the pro-fibrotic protein thrombospondin-1 in patients with EoE compared with controls. While there are notable changes in the microbiome, these differ with the collection technique and method of analysis utilized. Techniques characterizing metabolomics and tissue biochemistry are now being utilized to further study patients with EoE. The lack of published data related to the human microbiome, metagenome, metatranscriptome, and metabolome in patients with EoE highlights the need for further research in these areas.
PubMed: 34566693
DOI: 10.3389/fphys.2021.731034 -
Frontiers in Cellular and Infection... 2023Clinical values of metagenomic next-generation sequencing (mNGS) in patients with severe pneumonia remain controversial. Therefore, we conduct this meta-analysis to... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Clinical values of metagenomic next-generation sequencing (mNGS) in patients with severe pneumonia remain controversial. Therefore, we conduct this meta-analysis to evaluate the diagnostic performance of mNGS for pathogen detection and its role in the prognosis of severe pneumonia.
METHODS
We systematically searched the literature published in PubMed, Embase, Cochrane Library, Web of Science, Clinical Trials.gov, CNKI, Wanfang Data, and CBM from the inception to the 28th September 2022. Relevant trials comparing mNGS with conventional methods applied to patients with severe pneumonia were included. The primary outcomes of this study were the pathogen-positive rate, the 28-day mortality, and the 90-day mortality; secondary outcomes included the duration of mechanical ventilation, the length of hospital stay, and the length of stay in the ICU.
RESULTS
Totally, 24 publications with 3220 patients met the inclusion criteria and were enrolled in this study. Compared with conventional methods (45.78%, 705/1540), mNGS (80.48%, 1233/1532) significantly increased the positive rate of pathogen detection [ = 6.81, 95% (4.59, 10.11, < 0.001]. The pooled 28-day and 90-day mortality in mNGS group were 15.08% (38/252) and 22.36% (36/161), respectively, which were significantly lower than those in conventional methods group 33.05% (117/354) [ = 0.35, 95% (0.23, 0.55), < 0.001, = 0%] and 43.43%(109/251) [ = 0.34, 95% (0.21, 0.54), < 0.001]. Meanwhile, adjusted treatment based on the results of mNGS shortened the length of hospital stay [MD = -2.76, 95% (- 3.56, - 1.96), P < 0.001] and the length of stay in ICU [ = -4.11, 95% (- 5.35, - 2.87), < 0.001].
CONCLUSION
The pathogen detection positive rate of mNGS was much higher than that of conventional methods. Adjusted treatment based on mNGS results can reduce the 28-day and 90-day mortality of patients with severe pneumonia, and shorten the length of hospital and ICU stay. Therefore, mNGS advised to be applied to severe pneumonia patients as early as possible in addition to conventional methods to improve the prognosis and reduce the length of hospital stay.
Topics: Humans; High-Throughput Nucleotide Sequencing; Hospitals; Metagenome; Metagenomics; Pneumonia; Sensitivity and Specificity
PubMed: 37091676
DOI: 10.3389/fcimb.2023.1106859 -
Journal of Oral & Maxillofacial Research 2016To describe the microbial profiles of peri-implant diseases and the main detection methods. (Review)
Review
OBJECTIVES
To describe the microbial profiles of peri-implant diseases and the main detection methods.
MATERIAL AND METHODS
A literature search was performed in MEDLINE via PubMed database to identify studies on microbial composition of peri-implant surfaces in humans published in the last 5 years. Studies had to have clear implant status definition for health, peri-implant mucositis and/or peri-implantitis and specifically study microbial composition of the peri-implant sulcus.
RESULTS
A total of 194 studies were screened and 47 included. Peri-implant sites are reported to be different microbial ecosystems compared to periodontal sites. However, differences between periodontal and peri-implant health and disease are not consistent across all studies, possibly due to the bias introduced by the microbial detection technique. New methods non species-oriented are being used to find 'unexpected' microbiota not previously described in these scenarios.
CONCLUSIONS
Microbial profile of peri-implant diseases usually includes classic periodontopathogens. However, correlation between studies is difficult, particularly because of the use of different detection methods. New metagenomic techniques should be promoted for future studies to avoid detection bias.
PubMed: 27833735
DOI: 10.5037/jomr.2016.7310 -
Microorganisms Dec 2022The 5- and 10-year implant success rates in dentistry are nearly 90%. Prevalence of peri-implant diseases is 10% for peri-implantitis and 50% for peri-implant mucositis....
The 5- and 10-year implant success rates in dentistry are nearly 90%. Prevalence of peri-implant diseases is 10% for peri-implantitis and 50% for peri-implant mucositis. To better understand these inflammatory pathologies of infectious origin, it is important to know if the composition of the peri-implant microbiota is comparable with the periodontal microbiota in healthy and pathological conditions. New generation sequencing (NGS) is a recent metagenomic method that analyzes the overall microorganisms present in an ecological niche by exploiting their genome. These methods are of two types: 16S rRNA sequencing and the shotgun technique. For several years, they have been used to explore the oral, periodontal, and, more specifically, peri-implant microbiota. The aim of this systematic review is to analyze the recent results of these new explorations by comparing the periodontal and peri-implant microbiota in patients with healthy and diseased sites and to explore the microbiological characteristics of peri-implantitis. A better knowledge of the composition of the peri-implant microbiota would enable us to optimize our therapeutic strategies. An electronic systematic search was performed using the medical databases PubMed/Medline, Cochrane Library, and ScienceDirect, and . The selected articles were published between January 2015 and March 2021. Inclusion criteria included clinical studies comparing healthy and pathological periodontal and peri-implant microbiota exclusively using 16S rRNA sequencing or shotgun sequencing, with enrolled populations free of systemic pathology, and studies without substantial bias. Eight articles were selected and reviewed. All of them used 16S rRNA sequencing exclusively. The assessment of these articles demonstrates the specific character of the peri-implant microbiota in comparison with the periodontal microbiota in healthy and pathological conditions. Indeed, peri-implant diseases are defined by dysbiotic bacterial communities that vary from one individual to another, including known periodontopathogens such as () and genera less mentioned in the periodontal disease pattern such as . Examination of peri-implant microbiota with 16S rRNA sequencing reveals differences between the periodontal and peri-implant microbiota under healthy and pathological conditions in terms of diversity and composition. The pattern of dysbiotic drift is preserved in periodontal and peri-implant diseases, but when comparing the different types of pathological sites, the peri-implant microbiota has a specificity in the presence of bacteria proper to peri-implantitis and different relative proportions of the microorganisms present.
PubMed: 36557719
DOI: 10.3390/microorganisms10122466 -
Scientific Reports Dec 2022Many common pathogens are difficult or impossible to detect using conventional microbiological tests. However, the rapid and untargeted nature of metagenomic... (Meta-Analysis)
Meta-Analysis
Many common pathogens are difficult or impossible to detect using conventional microbiological tests. However, the rapid and untargeted nature of metagenomic next-generation sequencing (mNGS) appears to be a promising alternative. To perform a systematic review and meta-analysis of evidence regarding the diagnostic accuracy of mNGS in patients with infectious diseases. An electronic literature search of Embase, PubMed and Scopus databases was performed. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Summary receiver operating characteristics (sROC) and the area under the curve (AUC) were calculated; A random-effects model was used in cases of heterogeneity. A total of 20 papers were eligible for inclusion and synthesis. The sensitivity and specificity of diagnostic mNGS were 75% and 68%, respectively. The AUC from the SROC was 85%, corresponding to excellent performance. mNGS demonstrated satisfactory diagnostic performance for infections and yielded an overall detection rate superior to conventional methods.
Topics: Humans; Metagenomics; High-Throughput Nucleotide Sequencing; Communicable Diseases; Sensitivity and Specificity; Metagenome
PubMed: 36470909
DOI: 10.1038/s41598-022-25314-y