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Critical Reviews in Biochemistry and... Oct 2021Amyloidosis is a disease caused by pathological fibril aggregation and deposition of proteins in different tissues and organs. Thirty-six fibril-forming proteins have...
Amyloidosis is a disease caused by pathological fibril aggregation and deposition of proteins in different tissues and organs. Thirty-six fibril-forming proteins have been identified. So far, proteomic evaluation of amyloid focused on the detection and characterization of fibril proteins mainly for diagnostic purposes or to find novel fibril-forming proteins. However, amyloid deposits are a complex mixture of constituents that show organ-, tissue-, and amyloid-type specific patterns, that is the amyloid proteome. We carried out a comprehensive literature review on publications investigating amyloid via liquid chromatography coupled to tandem mass spectrometry, including but not limited to sample preparation by laser microdissection. Our review confirms the complexity and dynamics of the amyloid proteome, which can be divided into four functional categories: amyloid proteome-category 1 (APC1) includes exclusively fibrillary proteins found in the patient; APC2 includes potential fibril-forming proteins found in other types of amyloid; and APC3 and APC4 summarizes non-fibril proteins-some being amyloid signature proteins. Our categorization may help to systemically explore the nature and role of the amyloid proteome in the manifestation, progression, and clearance of disease. Further exploration of the amyloid proteome may form the basis for the development of novel diagnostic tools, thereby enabling the development of novel therapeutic targets.
Topics: Amyloid; Amyloidosis; Humans; Proteome; Proteomics
PubMed: 34311636
DOI: 10.1080/10409238.2021.1937926 -
Microbiological Research Jun 2023Innumerable pathogens including RNA viruses have catastrophic pandemic propensity, in turn, SARS-CoV-2 infection is highly contagious. Emergence of SARS-CoV-2 variants... (Review)
Review
Innumerable pathogens including RNA viruses have catastrophic pandemic propensity, in turn, SARS-CoV-2 infection is highly contagious. Emergence of SARS-CoV-2 variants with high mutation rate additionally codifies infectious ability of virus and arisen clinical imputations to human health. Although, our knowledge of mechanism of virus infection and its impact on host system has been substantially demystified, uncertainties about the emergence of virus are still not fully understood. To date, there are no potentially curative drugs are identified against the viral infection. Even though, drugs are repurposed in the initial period of infection, many are significantly negative in clinical trials. Moreover, the infection is dependent on organ status, co-morbid conditions, variant of virus and geographic region. This review article aims to comprehensively describe the SARS-CoV-2 infection and the impacts in the host cellular system. This review also briefly provides an overview of genome, proteome and metabolome associated risk to infection and the advancement of therapeutics in SARS-CoV-2 infection management.
Topics: Humans; COVID-19; SARS-CoV-2; Antiviral Agents; Mutation Rate
PubMed: 36989761
DOI: 10.1016/j.micres.2023.127364 -
The Journal of Maternal-fetal &... Jul 2022Pre-eclampsia (PE) is a serious pregnancy status characterized by high blood pressure. Although visfatin is usually associated with PE. Observational studies evaluating... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
Pre-eclampsia (PE) is a serious pregnancy status characterized by high blood pressure. Although visfatin is usually associated with PE. Observational studies evaluating the relationship between circulating visfatin and pre-eclampsia have reported inconsistent results. We conducted this systematic review and meta-analysis to summarize published data on the association between visfatin and pre-eclampsia.
METHODS
Electronic databases PubMed, ISI web of science, EMBASE, Scopus and the Cochrane library were comprehensively searched for selection of eligible studies until January 5, 2020. A random-effects model and the generic inverse variance method were used for quantitative data synthesis. The assessment of study quality was performed using the e Newcastle-Ottawa scale and the Agency for Healthcare Research and Quality. Sensitivity analyses and prespecified subgroup were conducted to evaluate potential heterogeneity. Random-effects meta-regression was conducted to assess the impact of potential confounders on the estimated effect sizes. The protocol for this study was registered in PROSPERO (No. CRD42018105861) in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).
RESULTS
Thirteen studies comprising a total of 536 subjects were included in this meta-analysis. We observed that the pre-eclampsia risk is associated with a statistically significant elevation of visfatin level [SMD (1.33 µg/l) (95% CI 0.37, 2.2) = .007]. No significant publication bias was observed in the meta-analysis. Subgroup and sensitivity analyses indicated that the pooled effects size were affected by systolic blood pressure [SMD (1.82 µg/l) 95% CI (0.94, 2.7), < .05], gestational age [SMD (2.01 µg/l) 95% CI (0.57, 3.4), = .006], body mass index [SMD (1.6 µg/l) 95% CI (0.37, 3), < .05] and pregnancy trimesters[SMD (2.3 µg/l) 95% CI (0.95, 3.7), = .001]. Random-effects meta-regression showed a significant association of visfatin level with potential confounders including systolic blood pressure, gestational age and birth weight at delivery of pre-eclampsia patients.
CONCLUSIONS
Collectively, our data revealed that the increase of visfatin level can be associated with the risk of pre-eclampsia. However, further studies on pre-eclampsia populations are warranted for corroboration of our findings.
Topics: Body Mass Index; Female; Humans; Nicotinamide Phosphoribosyltransferase; Pre-Eclampsia; Pregnancy; Pregnancy Trimesters
PubMed: 32635792
DOI: 10.1080/14767058.2020.1789581 -
The British Journal of Surgery Jan 2024Many survivors of a first primary cancer (FPCs) are at risk of developing a second primary cancer (SPC), with effects on patient prognosis. Primary cancers have... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Many survivors of a first primary cancer (FPCs) are at risk of developing a second primary cancer (SPC), with effects on patient prognosis. Primary cancers have different frequencies of specific SPC development and the development of SPCs may be closely related to the FPC. The aim of this study was to explore possible correlations between SPCs and FPCs.
METHODS
Relevant literature on SPCs was retrospectively searched and screened from four databases, namely, PubMed, EMBASE, Web of Science, and PMC. Data on the number of patients with SPC in 28 different organ sites were also collected from The Surveillance, Epidemiology, and End Results (SEER) 8 Registry and NHANES database.
RESULTS
A total of 9 617 643 patients with an FPC and 677 430 patients with an SPC were included in the meta-analysis. Patients with a first primary gynaecological cancer and thyroid cancer frequently developed a second primary breast cancer and colorectal cancer. Moreover, those with a first primary head and neck cancer, anal cancer and oesophageal cancer developed a second primary lung cancer more frequently. A second primary lung cancer and prostate cancer was also common among patients with first primary bladder cancer and penile cancer. Patients with second primary bladder cancer accounted for 56% of first primary ureteral cancer patients with SPCs.
CONCLUSIONS
This study recommends close clinical follow-up, monitoring and appropriate interventions in patients with relevant FPCs for better screening and early diagnosis of SPCs.
Topics: Humans; Incidence; Lung Neoplasms; Neoplasms, Second Primary; Nutrition Surveys; Prostatic Neoplasms; Retrospective Studies; Risk Factors; Urinary Bladder Neoplasms
PubMed: 38055899
DOI: 10.1093/bjs/znad377 -
Journal of Reproduction & Infertility 2017Currently, there are 20,197 human protein-coding genes in the most expertly curated database (UniProtKB/Swiss-Pro). Big efforts have been made by the international... (Review)
Review
Currently, there are 20,197 human protein-coding genes in the most expertly curated database (UniProtKB/Swiss-Pro). Big efforts have been made by the international consortium, the Chromosome-Centric Human Proteome Project (C-HPP) and independent researchers, to map human proteome. In brief, anno 2017 the human proteome was outlined. The male factor contributes to 50% of infertility in couples. However, there are limited human spermatozoa proteomic studies. Firstly, the development of the mapping of the human spermatozoa was analyzed. The human spermatozoa have been used as a model for missing proteins. It has been shown that human spermatozoa are excellent sources for finding missing proteins. Y chromosome proteome mapping is led by Iran. However, it seems that it is extremely challenging to map the human spermatozoa Y chromosome proteins based on current mass spectrometry-based proteomics technology. Post-translation modifications (PTMs) of human spermatozoa proteome are the most unexplored area and currently the exact role of PTMs in male infertility is unknown. Additionally, the clinical human spermatozoa proteomic analysis, anno 2017 was done in this study.
PubMed: 29062791
DOI: No ID Found -
Frontiers in Oncology 2023Endometrial cancer is the most common gynaecological malignancy in developed countries. Over 382,000 new cases were diagnosed worldwide in 2018, and its incidence and... (Review)
Review
Endometrial cancer is the most common gynaecological malignancy in developed countries. Over 382,000 new cases were diagnosed worldwide in 2018, and its incidence and mortality are constantly rising due to longer life expectancy and life style factors including obesity. Two major improvements are needed in the management of patients with endometrial cancer, i.e., the development of non/minimally invasive tools for diagnostics and prognostics, which are currently missing. Diagnostic tools are needed to manage the increasing number of women at risk of developing the disease. Prognostic tools are necessary to stratify patients according to their risk of recurrence pre-preoperatively, to advise and plan the most appropriate treatment and avoid over/under-treatment. Biomarkers derived from proteomics and metabolomics, especially when derived from non/minimally-invasively collected body fluids, can serve to develop such prognostic and diagnostic tools, and the purpose of the present review is to explore the current research in this topic. We first provide a brief description of the technologies, the computational pipelines for data analyses and then we provide a systematic review of all published studies using proteomics and/or metabolomics for diagnostic and prognostic biomarker discovery in endometrial cancer. Finally, conclusions and recommendations for future studies are also given.
PubMed: 37091170
DOI: 10.3389/fonc.2023.1120178 -
Research in Veterinary Science Mar 2022Proteomic analysis is having a rapid development as a method for the detection of biomarkers of diseases in dogs. Dogs in addition to their importance as companion...
Proteomic analysis is having a rapid development as a method for the detection of biomarkers of diseases in dogs. Dogs in addition to their importance as companion animals, serve as important animal models for research. This study aims to systematically review evidence regarding the studies performed in proteomics in dogs, and specifically those made in serum, saliva, urine and/or plasma. Information searched in October 2020, January 2021 and August 2021, for English language publications of the last decade (2010-2020) were obtained from electronic databases. Screening, data extraction and risk of bias assessment were undertaken by two investigators. The risk of bias was evaluated using the Review Manager (RevMan 5) tool. Meta-analysis and case report studies were not included in this review. Through the screening process a total of 557 publications were identified after the removal of duplicates. Out of these, 65 were fully evaluated and 44 of these were included in the review. Most studies evaluated the proteome of disease and compared it with a healthy population, and most of the articles included were made on serum, followed by saliva. The overall risk of bias for all studies was high, due to an absence in the generation of random sequence. Overall proteomic analysis has allowed the discovery of new physiopathological pathways of diseases and potential biomarkers in the dog, which are addressed in this review.
Topics: Animals; Biomarkers; Databases, Factual; Dogs; Proteome; Proteomics; Saliva
PubMed: 35007798
DOI: 10.1016/j.rvsc.2021.12.026 -
Tumori Oct 2022People at high risk of morbidity and mortality from coronavirus disease 2019 (COVID-19), including patients dealing with malignancies and patients on immunosuppressive... (Review)
Review
People at high risk of morbidity and mortality from coronavirus disease 2019 (COVID-19), including patients dealing with malignancies and patients on immunosuppressive anticancer therapies, need to be followed carefully as the pandemic continues. Challenges in continuing cancer management and patient monitoring are of concern given the importance of timing in cancer therapy. Alternative treatment decisions and priorities are also important considerations. The efficacy and safety of various cancer treatments in patients with COVID-19 are other important considerations. In this systematic review, we summarize the potential risks and benefits of cancer treatments applied to patients with COVID-19 and malignant tumors. Using the PubMed and Scopus databases, we reviewed studies involving cancer therapy and COVID-19 to address the recent discoveries and related challenges of cancer therapy in patients with COVID-19 and cancer.
Topics: COVID-19; Humans; Immunotherapy; Neoplasms; Pandemics; SARS-CoV-2
PubMed: 34918602
DOI: 10.1177/03008916211063939 -
Frontiers in Endocrinology 2023Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity....
INTRODUCTION
Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in improving diagnostics. Thus, we performed a systematic review of literature to identify the utility of AI/ML in the diagnosis or classification of PCOS.
METHODS
We applied a search strategy using the following databases MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the Web of Science, and the IEEE Xplore Digital Library using relevant keywords. Eligible studies were identified, and results were extracted for their synthesis from inception until January 1, 2022.
RESULTS
135 studies were screened and ultimately, 31 studies were included in this study. Data sources used by the AI/ML interventions included clinical data, electronic health records, and genetic and proteomic data. Ten studies (32%) employed standardized criteria (NIH, Rotterdam, or Revised International PCOS classification), while 17 (55%) used clinical information with/without imaging. The most common AI techniques employed were support vector machine (42% studies), K-nearest neighbor (26%), and regression models (23%) were the commonest AI/ML. Receiver operating curves (ROC) were employed to compare AI/ML with clinical diagnosis. Area under the ROC ranged from 73% to 100% (n=7 studies), diagnostic accuracy from 89% to 100% (n=4 studies), sensitivity from 41% to 100% (n=10 studies), specificity from 75% to 100% (n=10 studies), positive predictive value (PPV) from 68% to 95% (n=4 studies), and negative predictive value (NPV) from 94% to 99% (n=2 studies).
CONCLUSION
Artificial intelligence and machine learning provide a high diagnostic and classification performance in detecting PCOS, thereby providing an avenue for early diagnosis of this disorder. However, AI-based studies should use standardized PCOS diagnostic criteria to enhance the clinical applicability of AI/ML in PCOS and improve adherence to methodological and reporting guidelines for maximum diagnostic utility.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/, identifier CRD42022295287.
Topics: Female; Humans; Artificial Intelligence; Polycystic Ovary Syndrome; Proteomics; Machine Learning; Cluster Analysis
PubMed: 37790605
DOI: 10.3389/fendo.2023.1106625 -
Journal of Diabetes and Metabolic... Jun 2022Due to growing concerns about the obesity pandemic as a worldwide phenomenon, a global effort has been made for managing it and associated disorders. Accordingly,... (Review)
Review
PURPOSE
Due to growing concerns about the obesity pandemic as a worldwide phenomenon, a global effort has been made for managing it and associated disorders. Accordingly, metabolomics as a promising field of "OMICS" is presented for investigating different molecular pathways in obesity and related disorders through the evaluation of specific metabolites in both animal and human subjects. Herein, the aim of the present study as the first systematic review is to evaluate all available studies about different mechanisms and their biomarkers discovery using metabolomics approaches.
METHOD
The study was designed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Using a comprehensive search strategy we searched in databases including; Web of Science, PubMed, and Scopus using specific keywords. Based on predefined inclusion/exclusion criteria study selection has been conducted considering the type of studies, participant, and outcome measures. Quality assessment was done using CASP (Critical Appraisal Skills Programme) checklist followed by data extraction according to a predefined data extraction sheet.
RESULTS
Among the articles that resulted from electronic search, a total of 74 articles met our inclusion criteria. The most prevalent studied metabolites were amino acids and lipid derivatives and both targeted and non-targeted approaches were applied for metabolomics studies.
CONCLUSION
This systematic review summarized a wide range of studies regardless of the age, history, language, and type of the study. Further studies are needed to compare the application of emerging methods in the treatment of obesity and related disorders.
SUPPLEMENTARY INFORMATION
The online version contains supplementary material available at 10.1007/s40200-021-00917-w.
PubMed: 35673462
DOI: 10.1007/s40200-021-00917-w