Database Search Engines Research Articles

Examining the State of Health Research on Pacific Rainbow Communities in New Zealand; Literatrure Review

Introduction: Pacific Rainbow/Queer Communities (PRCs) in New Zealand (NZ) have had scant attention paid to the specificities of their health and wellbeing needs in research. Recently, the Health Research Council of NZ funded its first Pacific-specific PRC project (The Manalagi Project) executed through the University of Auckland’s Centre for Pacific Studies. This paper reports a literature review conducted to ascertain the current state of health research on PRCs, Rainbow/Queer and Pacific communities’ health in NZ. Methods: A scoping review was conducted where relevant public health database search engines were accessed, which included PubMed and Medline to explore both national and international health research pertaining to PRCs, Pacific communities and Rainbow/Queer communities. Additional Google searches were undertaken to identify more ‘grey’ material such as reports, websites, other relevant government sources, as well as non-profit organisation and educational resources not visible via scientific databases. Findings/Outcome: The review identified published journal articles (n=20), books (n=1), reports (n=25) and theses (n=3) as well as other documents relevant to the study, such as websites and news articles pertaining to PRCs in NZ and abroad. It reveals a severe paucity of health research focused on PRCs domestically and internationally. Although more research is being conducted into the space of Pacific communities, as well as Rainbow/Queer communities, research that is PRC-focused is urgent and critical at this time. Conclusion: Both Pacific and Rainbow/Queer communities in NZ are socially marginalised, thus experience a raft of health challenges represented by a racist and cisnormative heterosexist health system. This literature review reveals a lack of understanding around the nuances that exist when these experiences intersect and coalesce in the body and experience of PRC members. It has identified a significant gap in Pacific health research that exists in NZ and abroad that urge us to frame future research to also be intersectionally-informed to capture the unique needs and context of PRCs.

Chimera Spectrum Diagnostics for Peptides Using Two-Dimensional Partial Covariance Mass Spectrometry.

The rate of successful identification of peptide sequences by tandem mass spectrometry (MS/MS) is adversely affected by the common occurrence of co-isolation and co-fragmentation of two or more isobaric or isomeric parent ions. This results in so-called `chimera spectra’, which feature peaks of the fragment ions from more than a single precursor ion. The totality of the fragment ion peaks in chimera spectra cannot be assigned to a single peptide sequence, which contradicts a fundamental assumption of the standard automated MS/MS spectra analysis tools, such as protein database search engines. This calls for a diagnostic method able to identify chimera spectra to single out the cases where this assumption is not valid. Here, we demonstrate that, within the recently developed two-dimensional partial covariance mass spectrometry (2D-PC-MS), it is possible to reliably identify chimera spectra directly from the two-dimensional fragment ion spectrum, irrespective of whether the co-isolated peptide ions are isobaric up to a finite mass accuracy or isomeric. We introduce ‘3-57 chimera tag’ technique for chimera spectrum diagnostics based on 2D-PC-MS and perform numerical simulations to examine its efficiency. We experimentally demonstrate the detection of a mixture of two isomeric parent ions, even under conditions when one isomeric peptide is at one five-hundredth of the molar concentration of the second isomer.

Proposed Models of Functional Heterogeneity in Cancer and the Effects of Microenvironmental Factors on Cancer Stem Cells: A Literature Review

Introduction: Functional heterogeneity in cancer may result in the metastasis of various types of tumour cells throughout the body. Attempting to explain functional heterogeneity in cancer cells has given rise to two models. The Cancer Stem Cell model proposes that a subset of tumour cells self-replicate and that heterogeneity is a progeny of various cancer stem cells (CSCs). The Clonal Evolution Model proposes heterogeneity as a product of mutations across tumour cells that accumulate and metastasize linearly or branching. Methods: Research was conducted through open-access journals and information was compiled surrounding CSC models using the Google Scholar and McMaster Library database search engines. Inclusions were sources that detailed the relationship between both models of functional heterogeneity and microenvironments and treatments. Literature that did not center around tumour microenvironments was not included in this literature review. Results: The two main models of tumour proliferation were explored and related to hypoxic tumour microenvironments. Various markers, etiologic agents and toxins were identified that contribute to tumour progression. Cell signalling and pathways that contribute to major cellular functions were identified, along with possible disruptions and epigenetic changes that lead to tumour and CSC proliferation. Discussion: This study reveals that the tumour microenvironment plays a large role in the proliferation of CSCs. Although the therapies targeting microenvironments are in early stages of development, focusing on these CSC targeted- therapies may lead to better treatments for cancer or more effective combination therapies. Strengths of the paper include the compilation of major contributing areas to CSC proliferation, whereas limitations encompass the high variability of tumour cells that are not all covered in this review. Conclusion: While no definitively eradicating treatment for CSCs currently exist, the recent developments in cancer research indicate promising new techniques for its management. Implications: By further studying malignant CSCs, highly effective cancer treatments may result, leading to the advancement of CSC recognition and combination therapy.

Comprehensive search filters for retrieving publications on nonhuman primates for literature reviews (filterNHP).

Nonhuman primates (NHPs) are widely studied across many scientific disciplines using a variety of techniques in diverse environments. Due to the wide scope of NHP research, substantial overlap in research topics and questions can occur, whose resulting scientific evidence is synthesized by literature reviews. Identifying all relevant research on a particular topic involving NHPs can be difficult and time consuming. By adopting objective search development techniques from systematic reviews, we developed search filters to detect all scientific publications involving NHPs in PubMed, PsycINFO (via EBSCOhost), and Web of Science. We compared the performance of our comprehensive NHP search filters to search strings typical of a novice database user (i.e., NHP simple search strings) and validated their sensitivity by combining these searches with a topic search of cortisol related studies. For all comparisons, our comprehensive NHP search filters retrieved considerably more scientific publications than the NHP simple search strings. Importantly, our comprehensive NHP search filters are easy to use (text can be copied and pasted into the database search engine) and detect the most recent publications that have yet to be indexed by the bibliographic databases queried. Additionally, we developed filterNHP, an R package and web-based application (https://filterNHP.dpz.eu), for researchers interested in literature searches involving a taxonomic sub-group of NHPs. filterNHP alleviates time necessary for adapting our comprehensive NHP search filters for a particular NHP sub-group by automatizing the creation of these search filters. Altogether, our comprehensive NHP search filters and those for taxonomic sub-groups generated by filterNHP will enable swift and easy retrieval of the available scientific literature involving NHPs, and thereby help enhance the quality of new NHP literature reviews that guide future scientific research (new experiments) and public policy (e.g., on welfare and conservation).

Investigating the effect of lab bias on long-term stream chemistry data

AbstractLong-term (LT) stream chemistry studies are used to examine changes in and responses to the environment. Much of the data collected over long periods of time goes through changes in instrumentation, methods, and personnel potentially resulting in changing values. A data user must understand these measures of data quality through quality control (QC) results to know with certainty if trends are real or attributable to other factors. We used the Web of Science database search engine to search for LT stream chemistry studies. For each study, we then determined: record or study length; if QC was reported; and if QC was used. We found that 33% of papers reported QC in the method, and 12% presented the QC in the results. Next, we conducted a case study on 46 years of stream chemistry data to evaluate the data with and without the application of QC protocols from two watersheds (WS) at Coweeta Hydrologic Laboratory; WS 7; clear-cut in 1967–77 and adjacent WS 2 which serves as a reference. We focused on nitrogen and sulfur due to their importance in understanding the forest ecosystem response to disturbance (NO3) and acid deposition (SO4). We determined average annual dissolved inorganic nitrogen (DIN) export (NH4 + NO3 = DIN) using three methods for censoring values below the method detection limit (mdl): (1) the found value, (2) the value of zero, and (3) one-half the mdl value. We found that DIN export for WS 2/WS 7 was (1) 66.9/831.4 (g ha−1 yr−1), (2) 45.4/808.0 (g ha−1 yr−1), and (3) 72.1/823.2 (g ha−1 yr−1) using the three censoring methods, and that the export estimate was significantly different for WS 2 but not for WS 7 (P = 0.001). We found that on average stream NH4 concentrations were below the mdl 58% of the time until an instrument change in 1994 resulted in improved mdls resulting in fewer data points below detection. We found increased bias for stream SO4 concentration following an instrumentation change from segmented flow analysis to ion chromatography. As a result, stream SO4 concentration data that were bias-corrected declined more rapidly in WS 2 compared with non-bias-corrected data, but not in WS 7. We conclude that including QC results with LT data is essential to verify data validity and give the data user a full understanding of the results.

Deep proteomic analysis of plasma exosomes in patients with advanced, hormone receptor-positive breast cancer treated with palbociclib and tamoxifen.

1030 Background: Combining a CDK4/6 inhibitor (CDK4/6i) with endocrine therapy (ET) in advanced, hormone receptor (HR)-positive, HER2-negative breast cancer (BC) doubles median progression-free survival, but eventually drug resistance and disease progression occur. For most patients, the mechanism of resistance is unknown. Exosomes are membrane-bound extracellular vesicles that contain lipids, proteins, and nucleic acids, and are released from tumors as a form of intercellular communication. Exosomes can be recovered from plasma, and analysis of their cargo provides a dynamic read-out of biological pathways that are activated in cancer cells. Proteomic analysis of plasma exosomes may provide insight into mechanisms of resistance that emerge during treatment with CDK4/6i-ET. Methods: The Big Ten Cancer Research Consortium conducted a single arm, phase II trial of palbociclib plus tamoxifen as first line therapy for advanced, HR+/HER2- BC (NCT02668666). Whole blood was collected in Streck tubes from study participants (n = 49) at baseline, at disease progression, and at time points during study treatment. Plasma was separated and stored at -80C within 48 hours of collection. Exosomes were isolated from thawed plasma using commercially available kits and ultracentrifugation. Exosome extraction and purification was optimized for protein recovery. Purified exosomes were processed for proteomic analysis and labeled with TMT10 (tandem mass tag 10plex) and quantified with the QExactive HF mass spectrometer. Ultrasensitive mass spectrometry provided deep proteomic coverage of exosomal proteins and detected various post-translational modifications (PTM). Data were analyzed with a pipeline developed in our lab using an improved SEQUEST/ProLuCID database search engine and Percolator data filtering toolchain. Exosome protein expression was determined at baseline, at best response and at the time of progression. Results: With our ultrasensitive proteomic method, we detected more than 500 exosome proteins from as little as 100 ng of purified exosomes. A significant enrichment of exosome specific markers was observed when comparing patient samples with healthy donor samples. Enrichment of surface glycoproteins (e.g. CD44) was seen in BC patient samples, as in previous reports. Ultrasensitive proteomics also detected PTM including phosphorylation, methylation, oxidation, deamidation, and glycosylation. Differential proteomic and PTM profiles comparing samples collected from responding patients at baseline vs. at progression will be presented. Conclusions: Our innovative method provided an unparalleled portrait of the proteomic landscape of plasma exosomes during treatment with CDK4/6i-ET. This powerful approach may provide novel insights into mechanisms of resistance that emerge during treatment. This study was funded by Pfizer. Clinical trial information: NCT02668666 .

MS Amanda 2.0: Advancements in the standalone implementation.

RationaleDatabase search engines are the preferred method to identify peptides in mass spectrometry data. However, valuable software is in this context not only defined by a powerful algorithm to separate correct from false identifications, but also by constant maintenance and continuous improvements.MethodsIn 2014, we presented our peptide identification algorithm MS Amanda, showing its suitability for identifying peptides in high‐resolution tandem mass spectrometry data and its ability to outperform widely used tools to identify peptides. Since then, we have continuously worked on improvements to enhance its usability and to support new trends and developments in this fast‐growing field, while keeping the original scoring algorithm to assess the quality of a peptide spectrum match unchanged.ResultsWe present the outcome of these efforts, MS Amanda 2.0, a faster and more flexible standalone version with the original scoring algorithm. The new implementation has led to a 3–5× speedup, is able to handle new ion types and supports standard data formats. We also show that MS Amanda 2.0 works best when using only the most common ion types in a particular search instead of all possible ion types.ConclusionsMS Amanda is available free of charge from https://ms.imp.ac.at/index.php?action=msamanda.

Carbapenems for the Treatment of Pneumonia: A literature review regarding resistance, risk factors, and mortality

Carbapenem is one of antibiotic to treat respiratory infections such as pneumonia that frequently used in tertiary care facilities and started to create resistances. This study aims to review the resistance of carbapenems, assess the risk factors for resistance that leads to mortality, and the more effective antibiotic treatment options to overcome the resistance. Assessment of the use of carbapenems in pneumonia through previous studies were carried out by searching the articles in search engine databases in 2011 to 2021. Articles reporting carbapenems resistance, risk factors, and mortality were selected based on inclusion and exclusion criteria. Of 14 articles included in inclusion criteria, 4 studies reported the occurrence of resistance to gram-negative bacteria such as Acinetobacter aumanii, Pseudomonas aeruginosa, and Klebsiella pneumoniae, and 10 articles reported risk factors and mortality. The risk factors for carbapenems resistance are the history of carbapenems use, duration of hospitalization, use of mechanical ventilation, high Simplified Acute Physiology Score (SAPS) scores, and high Acute Physiologic and Chronic Health Evaluation (APACHE). Carbapenems resistance causes mortality such as septic shock, high Sequential Organ Failure Assessment (SOFA) scores, and elevated risk at > 60 years of age, female sex, and inappropriate choice of antibiotics. The results showed that imipenem has higher resistance than other carbapenems members, the risk factors for carbapenems resistance are dominated by a history of carbapenems use, mortality caused by high score SOFA, and colistin can be the current choice to overcome carbapenems resistance.

Comparative database search engine analysis on massive tandem mass spectra of pork-based food products for halal proteomics

Mass spectrometry-based proteomics relies on dedicated software for peptide and protein identification. These software include open-source or commercial-based search engines; wherein, they employ different algorithms to establish their scoring and identified proteins. Although previous comparative studies have differentiated the proteomics results from different software, there are still yet studies specifically been conducted to compare and evaluate the search engine in the field of halal analysis. This is important because the halal analysis is often using commercial meat samples that have been subjected to various processing, further complicating its analysis. Thus, this study aimed to assess three open-source search engines (Comet, X! Tandem, and ProteinProspector) and a commercial-based search engine (ProteinPilot™) against 135 raw tandem mass spectrometry data files from 15 types of pork-based food products for halal analysis. Each database search engine contained high false-discovery rate (FDR); however, a post-searching algorithm called PeptideProphet managed to reduce the FDR, except for ProteinProspector and ProteinPilot™. From this study, the combined database search engine (executed by iProphet) reveals a thorough protein list for pork-based food products; wherein the most abundant proteins are myofibrillar proteins. Thus, this proteomics study will aid the identification of potential peptide and protein biomarkers for future precision halal analysis. SignificanceA critical challenge of halal proteomics is the availability of a database to confirm the inferential peptides as well as proteins. Currently, the established database such as UniProtKB is related to animal proteome; however, the halal proteomics is related to the highly processed meat-based food products. This study highlights the use of different database search engines (Comet, X! Tandem, ProteinProspector, and ProteinPilot™) and their respective algorithms to analyse 135 raw tandem mass spectrometry data files from 15 types of pork-based food products. This is the first attempt that has compared different database search engines in the context of halal proteomics to ensure the effectiveness of controlling the FDR. Previous studies were just focused on the advantages of a certain algorithm over another. Moreover, other previous studies also have mainly reported the use of mass spectrometry-based shotgun proteomics for meat authentication (the most similar field to halal analysis), but none of the studies were reported on halal aspects that used samples originated from highly processed food products. Hence, a systematic comparative study is duly needed for a more comprehensive and thorough proteomics analysis for such samples. In this study, our combinatorial approach for halal proteomics results from the different search engines used (Comet, X! Tandem, and ProteinProspector) has successfully generated a comprehensive spectral library for the pork-based meat products. This combined spectral library is freely available at https://data.mendeley.com/datasets/6dmm8659rm/3. Thus far, this is the first and new attempt at establishing a spectral library for halal proteomics. We also believe this study is a pioneer for halal proteomics that aimed at non-conventional and non-model organism proteomics, protein analytics, protein bioinformatics, and potential biomarker discovery.

PDeepXL: MS/MS Spectrum Prediction for Cross-Linked Peptide Pairs by Deep Learning.

In cross-linking mass spectrometry, the identification of cross-linked peptide pairs heavily relies on the ability of a database search engine to measure the similarities between experimental and theoretical MS/MS spectra. However, the lack of accurate ion intensities in theoretical spectra impairs the performance of search engines, in particular, on proteome scales. Here we introduce pDeepXL, a deep neural network to predict MS/MS spectra of cross-linked peptide pairs. To train pDeepXL, we used the transfer-learning technique because it facilitated the training with limited benchmark data of cross-linked peptide pairs. Test results on more than ten data sets showed that pDeepXL accurately predicted the spectra of both noncleavable DSS/BS3/Leiker cross-linked peptide pairs (>80% of predicted spectra have Pearson's r values higher than 0.9) and cleavable DSSO/DSBU cross-linked peptide pairs (>75% of predicted spectra have Pearson's r values higher than 0.9). pDeepXL also achieved the accurate prediction on unseen data sets using an online fine-tuning technique. Lastly, integrating pDeepXL into a database search engine increased the number of identified cross-link spectra by 18% on average.

Benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers: a case study of pancreatic cancer.

Pancreatic cancer is a highly malignant tumor of the digestive tract that is difficult to diagnose and treat. It is more common in developed countries and has become one of the main causes of death in some countries and regions. Currently, pancreatic cancer generally has a poor prognosis, partly due to the lack of symptoms in the early stages of pancreatic cancer. Therefore, most cases are diagnosed at advanced stage. With the continuous in-depth research of glycoproteomics in precision medical diagnosis, there have been some reports on quantitative analysis of cancer-related cells, plasma or tissues to find specific biomarkers for targeted therapy. This research is based on the developed complete N-linked glycopeptide database search engine GPSeeker, combined with liquid-mass spectrometry and stable diethyl isotope labeling, providing a benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers. With spectrum-level FDR ≤1%, 20,038 intact N-Glycopeptides corresponding to 4518 peptide backbones, 228N-glycan monosaccharide compositions 1026N-glycan putative structures, 4460N-glycosites and 3437 intact N-glycoproteins were identified. With the criteria of ≥1.5-fold change and p value<0.05, 52 differentially expressed intact N-glycopeptides (DEGPs) were found in pancreatic cancer tussues relative to control, where 38 up-regulated and 14 down-regulated, respectively.

Ototoxicity: A review of South African studies

BackgroundOtotoxicity is damage to cells in the inner ear after administering a toxic drug, with a resultant hearing loss. Drugs used to treat illnesses such as cancer, tuberculosis, human immuno-deficiency virus (HIV) and infections are potentially ototoxic. South Africa has one of the highest rates of HIV and tuberculosis, and thus a potentially greater degree of the population is being affected by hearing loss from the medications used to treat these illnesses.MethodsTo determine the current status of research in ototoxicity, a systematic literature review was carried out to determine the focus areas of South African studies for the period 1989–2019. From the database search engines used (Science Direct, Ebscohost and Proquest), a total of 33 relevant articles were identified, including the themes of pharmacology, audiology and knowledge.ResultsStudies were conducted in the three most resourced provinces in South Africa. Findings indicate that there is a need for educating doctors regarding ototoxicity and a delineation of the role of the audiologist in monitoring and management of ototoxic hearing loss. There is a resultant need for audiology training on the pharmacology of ototoxic medication, otoprotective strategies and adherence to recommended guidelines. This has implications for university audiology training programmes and curriculum planning. The need for development of South Africa-specific audiology guidelines was highlighted.ConclusionWhilst it is noted that there is a lack of resources for effective implementation of ototoxicity-monitoring protocols, it is also noted that there are measures and otoprotective strategies that can be put in place without additional resources.

A SARS-CoV-2 Peptide Spectral Library Enables Rapid, Sensitive Identification of Virus Peptides in Complex Biological Samples.

On the basis of an analysis of (i) SARS-CoV-2 virions, (ii) SARS-CoV-2-infected VeroE6 cell lysates, and (iii) recombinant SARS-CoV-2 proteins expressed in HEK 293 cells, here we present a comprehensive SARS-CoV-2 peptide spectrum compendium, comprising 1682 high confidence peptide consensus spectra derived from 1170 peptides (of various charge states) spanning 23 virus proteins. This high quality reference set can be used, e.g., for the selection of commonly observed virus peptides for use in targeted proteomics or data-independent acquisition (DIA) approaches. Using this rich resource, we also demonstrate that a spectral matching search approach yields improved performance over the use of standard database search engines alone for the identification of virus peptides in complex biological samples.

PSpecteR: A User-Friendly and Interactive Application for Visualizing Top-Down and Bottom-Up Proteomics Data in R.

Visual examination of mass spectrometry data is necessary to assess data quality and to facilitate data exploration. Graphics provide the means to evaluate spectral properties, test alternative peptide/protein sequence matches, prepare annotated spectra for publication, and fine-tune parameters during wet lab procedures. Visual inspection of LC-MS data is constrained by proteomics visualization software designed for particular workflows or vendor-specific tools without open-source code. We built PSpecteR, an open-source and interactive R Shiny web application for visualization of LC-MS data, with support for several steps of proteomics data processing, including reading various mass spectrometry files, running open-source database search engines, labeling spectra with fragmentation patterns, testing post-translational modifications, plotting where identified fragments map to reference sequences, and visualizing algorithmic output and metadata. All figures, tables, and spectra are exportable within one easy-to-use graphical user interface. Our current software provides a flexible and modern R framework to support fast implementation of additional features. The open-source code is readily available (https://github.com/EMSL-Computing/PSpecteR), and a PSpecteR Docker container (https://hub.docker.com/r/emslcomputing/pspecter) is available for easy local installation.

Substantiating Clinical Effectiveness and Potential Barriers to the Widespread Implementation of Spinal Cord Injury Telerehabilitation: A Systematic Review and Qualitative Synthesis of Randomized Trials in the Recent Past Decade

Introduction: Telemedicine across many specialties in clinical practice has been established in the literature regarding technology platforms, privacy issues, cost, and clinical effectiveness. However, the lack of data in these areas applicable to spinal cord injury telerehabilitation (teleSCI) still exists. The gaps in these knowledge areas continue to hinder its widespread implementation and serve as pathways for focused efforts in teleSCI research.Objective: This systematic review aims to substantiate the clinical effectiveness and potential barriers to teleSCI implementation by verifying the statistical significance of various clinical outcomes from randomized trials published within the recent past decade.Methods: A qualitative synthesis of randomized studies, conducted across various regions, was systematically reviewed after identifying relevant records from database search engines. Applied filters in the search included publication dates (2010–2020), humans, full-text, and no language preference. The 13 studies were selected per Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram, and the risk of bias across studies was evaluated by using the Physiotherapy Evidence Database scale of quality assessment.Results: Quantitative outcome measurements demonstrated positive impact across studies: 79.1% (34/43) of all measurements were statistically significant for positive outcomes and 18.6% (8/43) yielded no effect but were significant. Primary outcomes addressed various spinal cord injury (SCI) management areas; 38.5% (5/13) of studies also assessed secondary outcomes. Interventional platforms were conventional technologies used in telemedicine. One study (7.7%) achieved data encryption; no studies presented cost-analysis data.Conclusion: The majority of studies demonstrated significant positive outcomes to validate teleSCI clinical effectiveness through conventional technology. These results further expand our understanding of teleSCI's impact and its demonstrated potential for improving SCI individuals' lives. However, heterogeneity of selected studies limits the conclusive recommendations to address potential barriers to its widespread implementation. Moreover, the development of new data is warranted to promote “buy-in” of widespread teleSCI implementation.

Enhancing Open Modification Searches via a Combined Approach Facilitated by Ursgal.

The identification of peptide sequences and their post-translational modifications (PTMs) is a crucial step in the analysis of bottom-up proteomics data. The recent development of open modification search (OMS) engines allows virtually all PTMs to be searched for. This not only increases the number of spectra that can be matched to peptides but also greatly advances the understanding of the biological roles of PTMs through the identification, and the thereby facilitated quantification, of peptidoforms (peptide sequences and their potential PTMs). Whereas the benefits of combining results from multiple protein database search engines have been previously established, similar approaches for OMS results have been missing so far. Here we compare and combine results from three different OMS engines, demonstrating an increase in peptide spectrum matches of 8-18%. The unification of search results furthermore allows for the combined downstream processing of search results, including the mapping to potential PTMs. Finally, we test for the ability of OMS engines to identify glycosylated peptides. The implementation of these engines in the Python framework Ursgal facilitates the straightforward application of the OMS with unified parameters and results files, thereby enabling yet unmatched high-throughput, large-scale data analysis.

A narrative review of the pathophysiology of COVID-19 infection among cancer patients: Current evidence and research perspectives.

IntroductionThe mechanism by which a suppressed immune system of a cancer patient makes them susceptible to COVID‐19 is still unclear. Any delay or discontinuation of cancer care due to the pandemic is expected to have a detrimental impact on the outcome of cancer. A few studies have addressed the incidence of COVID‐19 among cancer patients, but the small sample size of such studies makes it difficult to draw inference to the general population.MethodsFor our review, ‘Pubmed’ database and Google search engines were used for searching the relevant articles. The criterion used for review includes their relevance to the defined review question, which is the pathophysiological mechanism of COVID‐19 among cancer patients and the relevant therapeutic interventions therewith. This review includes 20 studies and other relevant literature which address the determinants of COVID‐19 among Cancer patients.ResultsDelay in cancer diagnosis will increase the stage progression of cancer patients and increased mortality in the future. A short delay in administering cancer related treatment to aid the odds of patient surviving the acute SARS‐CoV‐2 infection, should be at the discretion of the treating Physician. Oncologists dilemma in the current situation includes titrating the density of drug doses and intensity of treatment regimen, for the optimal management of metastatic and adjuvant cancer patients. Patients are thus subjected to suboptimal treatment and undetected disease recurrence, To circumvent the immunosuppressive effects of chemotherapy, Providers need to consider staggered regimen or alternate therapies such as biological/immunotherapy, targeted therapy, anti‐angiogenic drugs, hormone therapy and/or antibody‐based therapeutics.ConclusionThis review provides insights on the pathogenesis of SARS‐CoV‐2, which could enable Physicians in formulating therapeutic strategies for the management of severe patients, more so in Oncology settings, thus reducing the mortality. The key is to balance the continuation of urgent cancer care, but rationing the elective treatment according to the circumstances.

Elderly's food security and its associated socioeconomic determinants in Tehran: A cross-sectional study.

IntroductionThe mechanism by which a suppressed immune system of a cancer patient makes them susceptible to COVID‐19 is still unclear. Any delay or discontinuation of cancer care due to the pandemic is expected to have a detrimental impact on the outcome of cancer. A few studies have addressed the incidence of COVID‐19 among cancer patients, but the small sample size of such studies makes it difficult to draw inference to the general population.MethodsFor our review, ‘Pubmed’ database and Google search engines were used for searching the relevant articles. The criterion used for review includes their relevance to the defined review question, which is the pathophysiological mechanism of COVID‐19 among cancer patients and the relevant therapeutic interventions therewith. This review includes 20 studies and other relevant literature which address the determinants of COVID‐19 among Cancer patients.ResultsDelay in cancer diagnosis will increase the stage progression of cancer patients and increased mortality in the future. A short delay in administering cancer related treatment to aid the odds of patient surviving the acute SARS‐CoV‐2 infection, should be at the discretion of the treating Physician. Oncologists dilemma in the current situation includes titrating the density of drug doses and intensity of treatment regimen, for the optimal management of metastatic and adjuvant cancer patients. Patients are thus subjected to suboptimal treatment and undetected disease recurrence, To circumvent the immunosuppressive effects of chemotherapy, Providers need to consider staggered regimen or alternate therapies such as biological/immunotherapy, targeted therapy, anti‐angiogenic drugs, hormone therapy and/or antibody‐based therapeutics.ConclusionThis review provides insights on the pathogenesis of SARS‐CoV‐2, which could enable Physicians in formulating therapeutic strategies for the management of severe patients, more so in Oncology settings, thus reducing the mortality. The key is to balance the continuation of urgent cancer care, but rationing the elective treatment according to the circumstances.

Müşteri Memnuniyeti ve Müşteri Sadakati Arasındaki İlişkiye Yönelik Bir Meta Analiz Çalışması

Bu araştırmada Türkiye’de müşteri memnuniyeti ve müşteri sadakati arasındaki ilişkileri inceleyen araştırmalarla bir meta analiz çalışması yapılmıştır. Bu doğrultuda Kafkas Üniversitesi Veri Tabanı ve DergiPark arama motoru üzerinden çalışmalara ulaşılmış ve ulaşılan çalışmalardan da toplam 15 çalışmanın araştırmaya dahil edilebilir olduğu tespit edilmiştir. Araştırmaya dâhil edilen çalışmalarda korelasyon değerleri ve örneklem büyüklükleri referans alınmış ve analizler CMA 3.0 (Comprehensive Meta Analysis 3.0) programıyla yapılmıştır. Çalışmada öncelikle yayın yanlılığının bulunup bulunmadığı incelenmiş ve bulgulardan yanlılığın olmadığı tespit edilmiştir. Sonraki aşamada çalışmada heterojen bir dağılımın olduğu belirlenmiş ve bu nedenle değişkenler arası ilişkide rastgele etki değerleri referans alınmıştır. Müşteri memnuniyeti ve müşteri sadakati arasındaki ilişkiye yönelik hem korelasyon hem Fisher’s Z rastgele etkiler modeli bulguları değerlendirildiğinde ise müşteri memnuniyeti ve müşteri sadakati arasında pozitif yönlü bir ilişkinin olduğu saptanmıştır.

Association of nationwide insurance data and Google Trends for seasonality of gout in South Korea

Aim of the workTo assess whether there is seasonality in the internet search volume related to gout and whether this reflects the seasonal variation of the actual number of gout cases in South Korea according to the nationwide insurance data. Patients and MethodsThe number of gout cases was obtained from the Health Insurance Review and Assessment Service (HIRA) in South Korea between January 2015 and December 2019. Internet search query data for the search terms “gout” and “uric acid” were obtained from a publicly available search engine database, Google Trends, during the same period. The cosinor analysis was conducted to assess a potential seasonality in the number of gout cases and gout-related search volumes (RSV) in Google Trends. ResultsThere was a significant seasonality in the number of gout cases and RSV for the search terms “gout” and “uric acid”. For both analyses, summer was the peak season, and winter was the trough season. The month with the most gout cases was July with February having the least number of cases. The RSV of the terms “gout” (r = 0.47; p < 0.001) and “uric acid” (r = 0.56; p < 0.001) significantly correlated with the number of gout cases. ConclusionThe number of gout cases and internet search data related to gout showed seasonality with a peak in the summer months in South Korea. Google Trends data for seasonality of gout were correlated with the nationwide insurance data. Internet search data has the potential to act as complementary tool for investigating and monitoring gout.