Search Output Research Articles

Publisher Correction: Internet image search outputs propagate climate change sentiment and impact policy support

Publisher Correction: Internet image search outputs propagate climate change sentiment and impact policy support

Factors associated with HPV vaccine acceptance and hesitancy in Africa: a systematic review protocol

IntroductionHuman papillomavirus (HPV) infection is the most prevalent sexually transmitted infection worldwide. HPV vaccination is an important tool to prevent and control HPV infection and its complications. Despite carrying the...

Internet image search outputs propagate climate change sentiment and impact policy support

AbstractA critical step in tackling climate change involves structural, system-level changes facilitating action. Despite their ubiquity, little is known about how internet search algorithms portray climate change, and how these portrayals impact concern and action. In a sample of 49 countries, we found that nationwide climate concern, but not nation-level climate impact, predicted the emotional arousal caused by climate change Google Image Search outputs, as rated by a naive sample (n = 383). In a follow-up experiment we randomly assigned another sample (n = 899) to receive the climate change image outputs resulting from searches conducted in countries high or low in pre-existing climate concern, and found that participants exposed to images from countries with high pre-existing concern (compared to low) became more concerned about climate change, supportive of climate policy and likely to act pro-environmentally, suggesting a cycle of climate sentiment propagation systemically facilitated by internet search algorithms. We discuss the implications of these findings for climate action interventions.

Assessment of Data-Independent Acquisition Mass Spectrometry (DIA-MS) for the Identification of Single Amino Acid Variants.

Proteogenomics integrates genomic and proteomic data to elucidate cellular processes by identifying variant peptides, including single amino acid variants (SAAVs). In this study, we assessed the capability of data-independent acquisition mass spectrometry (DIA-MS) to identify SAAV peptides in HeLa cells using various search engine pipelines. We developed a customised sequence database (DB) incorporating SAAV sequences from the HeLa genome and conducted searches using DIA-NN, Spectronaut, and Fragpipe-MSFragger. Our evaluation focused on identifying true positive SAAV peptides and false positives through entrapment DBs. This study revealed that DIA-MS provides reproducible and comprehensive coverage of the proteome, identifying a substantial proportion of SAAV peptides. Notably, the DIA-MS searches maintained consistent identification of SAAV peptides despite varying sizes of the entrapment DB. A comparative analysis showed that Fragpipe-MSFragger (FP-DIA) demonstrated the most conservative and effective performance, exhibiting the lowest false discovery match ratio (FDMR). Additionally, integrating DIA and data-dependent acquisition (DDA) MS data search outputs enhanced SAAV peptide identification, with a lower false discovery rate (FDR) observed in DDA searches. The validation using stable isotope dilution and parallel reaction monitoring (SID-PRM) confirmed the SAAV peptides identified by DIA-MS and DDA-MS searches, highlighting the reliability of our approach. Our findings underscore the effectiveness of DIA-MS in proteogenomic workflows for identifying SAAV peptides, offering insights into optimising search engine pipelines and DB construction for accurate proteomics analysis. These methodologies advance the understanding of proteome variability, contributing to cancer research and the identification of novel proteoform therapeutic targets.

Social network interventions for dietary adherence among adults with type 2 diabetes: a systematic review and meta-analysis protocol

IntroductionOptimal adherence to recommended diets is crucial to achieving long-term glycaemic control among individuals with type 2 diabetes (T2D) individuals. However, there is limited evidence on the effectiveness of interventions...

A temporal (phospho-)proteomic dataset of neurotrophic receptor tyrosine kinase signalling in neuroblastoma

Neurotrophic receptor tyrosine kinases (TrkA, TrkB, TrkC), despite their homology, contribute to the clinical heterogeneity of the childhood cancer neuroblastoma. TrkA expression is associated with low-stage disease and is often seen with spontaneous tumour regression. Conversely, TrkB is present in unfavourable neuroblastomas that often harbour amplification of the MYCN oncogene. The role of TrkC is less clearly defined, although some studies suggest its association with a favourable outcome. Understanding the differences in activity of Trk receptors that drive divergent clinical phenotypes as well as the influence of MYCN amplification on downstream Trk receptor signalling remains poorly understood. Here, we present a comprehensive label-free mass spectrometry-based total proteomics and phosphoproteomics dataset (432 raw files with FragPipe search outputs; available on PRIDE with accession number PXD054441) where we identified and quantified 4,907 proteins, 16,744 phosphosites and 5,084 phosphoproteins, derived from NGF/BDNF/NT-3 treated TrkA/B/C-overexpressing neuroblastoma cells with differential MYCN status. Analysing our dataset offers valuable insights into TrkA/B/C receptor signalling in neuroblastoma and its modulation by MYCN status; and holds potential for advancing therapeutic strategies in this challenging childhood cancer.

High-frequency episodic migraine: Time for its recognition as a migraine subtype?

High-frequency episodic migraine (HFEM) has gained attention in the field of headache research and clinical practice. In this narrative review, we analyzed the available literature to assess the evidence that could help decide whether HFEM may represent a distinct clinical and/or biological entity within the migraine spectrum. The output of the literature search included 61 papers that were allocated to one of the following topics: (i) socio-demographic features and burden; (ii) clinical and therapeutic aspects; (iii) pathophysiology; and (iv) classification. Multiple features differentiate subjects with HFEM from low-frequency episodic migraine and from chronic migraine: education, employment rates, quality of life, disability and psychiatric comorbidities load. Some evidence also suggests that HFEM bears a specific profile of activation of cortical and spinal pain-related pathways, possibly related to maladaptive plasticity. Subjects with HFEM bear a distinctive clinical and socio-demographic profile within the episodic migraine group, with a higher disease burden and an increased risk of transitioning to chronic migraine. Recognizing HFEM as a distinct entity is an opportunity for the better understanding of migraine and the spectrum of frequency with which it can manifest, as well as for stimulating further research and more adequate public health approaches.

Double-negative T cells in pediatric rheumatic diseases.

Double-negative (CD4-CD8-) T (DNT) cells have been implicated in Autoimmune Lymphoproliferative Syndrome (ALPS), where their expansion inside the circulating pool of T cells represents a diagnostic criterion. Recent experimental evidence has supported the immunomodulatory roles of DNT cells, and studies in adult patients have suggested that they may be altered in some immune-mediated conditions. This study aimed to retrieve available data on circulating DNT cells in pediatric rheumatic disorders that do not arise in the context of ALPS through a systematic literature review of three scientific databases (PubMed, Scopus, and Web of Science). The final output of the systematic literature search consisted of eight manuscripts, including cross-sectional (n=6) and longitudinal (n=2) studies. Overall, the pooled population of patients includes children affected with pediatric Systemic Lupus Erythematosus (n=104), Juvenile Idiopathic Arthritis (n=92), Behçet's disease (n=15), mixed connective tissue disease (n=8), Juvenile Dermatomyositis (n=6), and Kawasaki disease/multisystem inflammatory disease in children (n=1 and n=14, respectively); moreover, one study also included 11 children with a high titer of antinuclear antibody but no diagnosis of rheumatic disease. All studies except one included a control group. The number of DNT cells were increased in most studies of children with rheumatic diseases. Even if such a limited number of studies and their great heterogeneity in several methodological aspects do not allow for reliable conclusions about the relevance of DNT cells in specific rheumatic conditions in children, this cell population deserves further investigation in this pathological setting through well-designed clinical studies.

The burden of iatrogenic obstetric fistulas in Sub-Saharan Africa: Systematic review and meta-analysis protocol.

Obstetric fistulas are abnormal open connection(s) between the vagina and the urinary tract or the rectum resulting from tragic injuries sustained by mothers during childbirth that lead to urine and/or faecal incontinence. Due to the rapidly growing middle class in sub-Saharan Africa (SSA) and the corresponding quest for hospital delivery and caesarean section, surgery-related (iatrogenic) obstetric fistulas are on the rise. Worryingly, there is scanty data on surgery-related fistulas. This review aims to collate empirical evidence on the magnitude of iatrogenic obstetric fistulas in SSA, generate country-specific data and explore factors that influence obstetric surgery-related fistulas. All relevant databases, PubMed, LILACS, CINAHL, SCOPUS and Google Scholar will be searched from 1st January 2000 to 31st March 2024 using search terms developed from the major concepts in the title without restrictions by language. The Cochrane Library, African Journals Online, Data Base of African Thesis and Dissertations Including Research (DATAD-R D Space) and preprint repositories will also be searched. Reference lists of relevant studies will be searched and experts in the field will be contacted for additional (unpublished) studies. The search output will be exported to Endnote where duplicate studies will be removed. The deduplicated studies will be exported to Rayyan where study screening and selection will be conducted. At least two authors will independently select studies, extract data and assess quality in the included studies using pretested tools. Disagreements between reviewers will be resolved through discussion. Data analysis will be performed with RevMan 5.4. Comparative binary outcomes will be reported as odds ratio (OR) or risk ratio (RR) and for continuous outcomes, mean difference and standard deviations (SDs) will be used. Non-comparative studies will be analysed as weighted proportions. Heterogeneity between studies will be assessed graphically and statistically, and where a significant level is detected, the random-effects model meta-analysis will be performed. All estimates will be reported with their 95% confidence intervals (CIs). Where data permit, we will conduct subgroup and sensitivity analyses to test the robustness of the estimates on key quality domains. The overall quality of the evidence will be assessed using GRADE (Grading of Recommendations Assessment, Development and Evaluation). This systematic review and meta-analysis uses rigorous methods and best practices to attempt to collate all empirical evidence and estimate country-specific proportions of iatrogenic (surgery-related) fistulas among obstetric fistula patients across countries in SSA. This review will explore context-specific variables, provide insights into their impact and relate them to the type and experience of personnel performing the obstetric procedures that lead to obstetric fistulas. The findings of the full review are expected to inform the development of national and regional Training Programs for Medical Officers, support the development of a consensus "minimum acceptable standard of care" and inform quality assurance standards for clinicians involved in the provision of surgical obstetric care.

TermineR: Extracting information on endogenous proteolytic processing from shotgun proteomics data.

State-of-the-art mass spectrometers combined with modern bioinformatics algorithms for peptide-to-spectrum matching (PSM) with robust statistical scoring allow for more variable features (i.e., post-translational modifications) being reliably identified from (tandem-) mass spectrometry data, often without the need for biochemical enrichment. Semi-specific proteome searches, that enforce a theoretical enzymatic digestion to solely the N- or C-terminal end, allow to identify of native protein termini or those arising from endogenous proteolytic activity (also referred to as "neo-N-termini" analysis or "N-terminomics"). Nevertheless, deriving biological meaning from these search outputs can be challenging in terms of data mining and analysis. Thus, we introduce TermineR, a data analysis approach for the (1) annotation of peptides according to their enzymatic cleavage specificity and known protein processing features, (2) differential abundance and enrichment analysis of N-terminal sequence patterns, and (3) visualization of neo-N-termini location. We illustrate the use of TermineR by applying it to tandem mass tag (TMT)-based proteomics data of a mouse model of polycystic kidney disease, and assess the semi-specific searches for biological interpretation of cleavage events and the variable contribution of proteolytic products to general protein abundance. The TermineR approach and example data are available as an R package at https://github.com/MiguelCos/TermineR.

Is Google driving us dumb? The introspective looping

Creativity is a key source of strategic advantage in nowadays knowledge-based society. However, reactive paradigms still dominate innovation theory: solutions follow well-known problems. But triggering radical innovation requires proactive creativity, implying using information to constantly find new problems to solve. Led by Google, personalization strategies use algorithms to obtain filtered information, meeting particular users’ expected preferences. This phenomenon, largely neglected by management research and practice, has received substantial criticism, around the concerns that it impoverishes social discourse, slows down human brain thinking capability, and eventually reduces creativity and innovation potential. Indeed, research has confirmed the positive impact that exposure to numerous and divergent external stimuli has on individual creativity. Thought-provoking questions emerge: Will customized search outputs affect companies’ competitive capabilities? If personalized search results reduce the diversity and overall wealth of stimuli received, will creativity and innovation in organizations be diminished? How can managers prevent this potentially dangerous process?

User Attitudes to Content Moderation in Web Search

Internet users highly rely on and trust web search engines, such as Google, to find relevant information online. However, scholars have documented numerous biases and inaccuracies in search outputs. To improve the quality of search results, search engines employ various content moderation practices such as interface elements informing users about potentially dangerous websites and algorithmic mechanisms for downgrading or removing low-quality search results. While the reliance of the public on web search engines and their use of moderation practices is well-established, user attitudes towards these practices have not yet been explored in detail. To address this gap, we first conducted an overview of content moderation practices used by search engines, and then surveyed a representative sample of the US adult population (N=398) to examine the levels of support for different moderation practices applied to potentially misleading and/or potentially offensive content in web search. We also analyzed the relationship between user characteristics and their support for specific moderation practices. We find that the most supported practice is informing users about potentially misleading or offensive content, and the least supported one is the complete removal of search results. More conservative users and users with lower levels of trust in web search results are more likely to be against content moderation in web search.

Spectra without stories: reporting 94% dark and unidentified ancient proteomes.

Data-dependent, bottom-up proteomics is widely used for identifying proteins and peptides. However, one key challenge is that 70% of fragment ion spectra consistently fail to be assigned by conventional database searching. This 'dark matter' of bottom-up proteomics seems to affect fields where non-model organisms, low-abundance proteins, non-tryptic peptides, and complex modifications may be present. While palaeoproteomics may appear as a niche field, understanding and reporting unidentified ancient spectra require collaborative innovation in bioinformatics strategies. This may advance the analysis of complex datasets. 14.97 million high-impact ancient spectra published in Nature and Science portfolios were mined from public repositories. Identification rates, defined as the proportion of assigned fragment ion spectra, were collected as part of deposited database search outputs or parsed using open-source python packages. We report that typically 94% of the published ancient spectra remain unidentified. This phenomenon may be caused by multiple factors, notably the limitations of database searching and the selection of user-defined reference data with advanced modification patterns. These 'spectra without stories' highlight the need for widespread data sharing to facilitate methodological development and minimise the loss of often irreplaceable ancient materials. Testing and validating alternative search strategies, such as open searching and de novo sequencing, may also improve overall identification rates. Hence, lessons learnt in palaeoproteomics may benefit other fields grappling with challenging data.

Mass spectrometry-based proteomics data from thousands of HeLa control samples

Here we provide a curated, large scale, label free mass spectrometry-based proteomics data set derived from HeLa cell lines for general purpose machine learning and analysis. Data access and filtering is a tedious task, which takes up considerable amounts of time for researchers. Therefore we provide machine based metadata for easy selection and overview along the 7,444 raw files and MaxQuant search output. For convenience, we provide three filtered and aggregated development datasets on the protein groups, peptides and precursors level. Next to providing easy to access training data, we provide a SDRF file annotating each raw file with instrument settings allowing automated reprocessing. We encourage others to enlarge this data set by instrument runs of further HeLa samples from different machine types by providing our workflows and analysis scripts.

Frailty in acute coronary syndromes. A systematic review and narrative synthesis of frailty assessment tools and interventions from randomised controlled trials

AimWe aimed to review all randomised controlled trial (RCT) data to explore optimal identification and treatment strategies of frail patients with Acute Coronary Syndromes (ACS). MethodsThe protocol was preregistered (PROSPERO - CRD42021250235). We performed a systematic review including RCT's that 1; used at least one frailty assessment tool to assess frailty and its impact on outcomes in patients diagnosed with ACS and 2; used at least one intervention where change in frailty was measured in patients diagnosed with ACS. The Cochrane Central Register of Controlled Trials, MEDLINE and EMBASE were searched on the 1st April 2021 and updated on 4th July 2023. Owing to low search output results are presented as a narrative synthesis of available evidence. ResultsA single RCT used a frailty assessment tool. A single RCT specifically targeted frailty with their intervention. This precluded further quantitative analysis. There was indication of selection bias against frail participants, and a signal of value for physical activity measurement in frail ACS patients. There was a high level of uncertainty and low level of robustness of this evidence. ConclusionsData from RCT's alone is inadequate in answering the reviews question. Future RCT's need to address ways to incorporate frail participants, whilst mitigating selection biases. Physical performance aspects of the frailty syndrome appear to be high yield modifiable targets that improve outcomes. Intervention trials should consider using change in frailty status as an outcome measure. Any trials that include frail participants should present data specifically attributable to this group.

Literature search in systematic reviews: How much is good enough?

BackgroundSystematic reviews focus on performing exhaustive literature searches to address specific research questions. However, in practice, many reviews search a limited number of databases. ObjectiveThis analysis was undertaken to identify the potential impact of searching a limited number of databases in systematic reviews. MethodsTwo recently published systematic reviews addressing the same research question, but using different search strategies, were utilized as a case study. Both were published in 2023, less than 6 months apart. One of these searched Pubmed and Embase; whereas the other searched through Pubmed and the Cochrane Library. Information on the review characteristics, detailed methodology, search strategy, reviewers’ results and conclusions; were extracted. Both reviews were appraised for methodological quality using the AMSTAR-2 checklist. ResultsThe search output of the two reviews was vastly different. Using a step-wise screening process, the two reviews finally included 16 and 11 studies. Among these, only 4 studies were included in both reviews, suggesting that both reviews missed multiple eligible studies. The data on the primary outcomes were also very different in the two reviews, suggesting that neither could be considered completely reliable for decision-making by stakeholders. ConclusionThis analysis highlights the risk of bias arising in systematic reviews undertaking limited literature searches, especially limited number of databases for published literature. The commonly employed practice of searching two databases in systematic reviews, needs to be rectified urgently.

Evaluation of the Needs and Experiences of Patients with Hypertriglyceridemia: Social Media Listening Infosurveillance Study.

Hypertriglyceridemia is a risk factor for cardiovascular diseases. Internet usage in China is increasing, giving rise to large-scale data sources, especially to access, disseminate, and discuss medical information. Social media listening (SML) is a new approach to analyze and monitor online discussions related to various health-related topics in diverse diseases, which can generate insights into users' experiences and expectations. However, to date, no studies have evaluated the utility of SML to understand patients' cognizance and expectations pertaining to the management of hypertriglyceridemia. The aim of this study was to utilize SML to explore the disease cognition level of patients with hypertriglyceridemia, choice of intervention measures, and the status quo of online consultations and question-and-answer (Q&A) search platforms. An infosurveillance study was conducted wherein a disease-specific comprehensive search was performed between 2004 and 2020 in Q&A search and online consultation platforms. Predefined single and combined keywords related to hypertriglyceridemia were used in the search, including disease, symptoms, diagnosis, and treatment indicators; lifestyle interventions; and therapeutic agents. The search output was aggregated using an aggregator tool and evaluated. Disease-specific consultation data (n=69,845) and corresponding response data (n=111,763) were analyzed from 20 data sources (6 Q&A search platforms and 14 online consultation platforms). Doctors from inland areas had relatively high voice volumes and appear to exert a substantial influence on these platforms. Patients with hypertriglyceridemia engaging on the internet have an average level of cognition about the disease and its intervention measures. However, a strong demand for the concept of the disease and "how to treat it" was observed. More emphasis on the persistence of the disease and the safety of medications was observed. Young patients have a lower willingness for drug interventions, whereas patients with severe hypertriglyceridemia have a clearer intention to use drug intervention and few patients have a strong willingness for the use of traditional Chinese medicine. Findings from this disease-specific SML study revealed that patients with hypertriglyceridemia in China actively seek information from both online Q&A search and consultation platforms. However, the integrity of internet doctors' suggestions on lifestyle interventions and the accuracy of drug intervention recommendations still need to be improved. Further, a combined prospective qualitative study with SML is required for added rigor and confirmation of the relevance of the findings.

Constructing the mathematical model of a recommender system for decentralized peer-to-peer computer networks

Recommender systems make it easier to search with a large amount of content, supplementing or replacing the classic search output with recommendations. In P2P networks, their use can have additional benefits. Because of indexing and search problems, previously added files may not be available to P2P network users. If the user cannot find the file he is looking for, one can provide him with a list of recommendations based on his preferences and search query. The object of research is the process of creating recommendations for users of decentralized P2P networks to facilitate data search. The urgent task of increasing the accuracy of mathematical modeling of recommender systems by taking into account the requirements for reliability and data security during changes in the structure of a decentralized P2P network is solved. An analytical model of the recommender system of a decentralized P2P network has been developed, the main feature of which is taking into account the requirements of reliability and security of recommendation messages. This was done by introducing the following indicators into the general model of the decentralized recommender system – the probability of reliable packet transmission and the probability of safe packet transmission. The developed analytical model makes it possible to conduct a comparative analysis of different methods of operation of recommender systems and to set acceptable parameters under which the degree of relevance does not fall below a certain threshold. The developed mathematical model of the system based on the GERT scheme differs from the known ones by taking into account the reliability and security requirements during changes in the structure of the decentralized P2P network. This has made it possible to improve the accuracy of simulation results up to 5 %. The proposed mathematical model could be used for prototyping recommender systems in various fields of activity

Cyber-security attack prediction using cognitive spectral clustering technique based on simulated annealing search

Data protection and security is a big challenging portion in a modern technical world against the cyber-attacks like; ransomware, man-in-the-middle, DDoS, etc. In order to overcome this scenario, there are lot of artificial intelligence framework have been introduced to detect and classify the cyber-attacks. In particular, neural networks, with their solid speculation execution ability, are capable to address an extensive variety of cyber-attacks. This article frames the training and testing of a neural network group such a way to deal with detection of cyber-attack using cognitive spectral clustering technique based on simulated annealing search method. The optimization of individual networks can be made by using adaptive memetic algorithm with simulated annealing search. It is used to enhance the neural network weights and hidden neurons respectively. This algorithm is a combination of both local and global search enhancement method and used to get rid of the premature convergence, and used to achieve the adaptive search output. The testing outcome of the proposed framework shows a better result 99.5% of overall accuracy, and effectively adaptive in terms of detecting the cyber-attacks.

MSR30 Comparison of Search Design and Output of Embase Using Two Different Search Interfaces: Embase.com and OVID

Different search interfaces use different search functionality and indexing. This research aimed to investigate the variances between the two most commonly used search interfaces and their impact on search results.