Text Search Research Articles

Oncologic outcomes following radical nephroureterectomy for upper tract urothelial carcinoma: a literature review.

Radical nephroureterectomy (RNU) represents the gold standard treatment for non-metastatic upper tract urothelial cancer. We sought to provide a comprehensive review of reported oncologic outcomes of the RNU procedure and of factors that might impact these outcomes. A non-systematic review of the literature was conducted by performing an electronic literature search using PubMed with "radical nephroureterectomy" and "oncologic outcomes" as free text search terms. Both original articles and systematic reviews were considered. Search was limited to articles in English that were published in the last 20 years. Open and laparoscopic RNU offer comparable oncologic outcomes. In more recent years, the discussion has de facto shifted towards the "oncological safety" of robotic RNU, which also seems to offer comparable oncologic outcomes. Several studies have looked at the impact of different treatment-, patient- and tumor-related factors. Among treatment-related factors, attention has been given to diagnostic ureteroscopy and the risk of intravesical recurrence. Surgical wait time and perioperative blood transfusion have also been studied. Perioperative chemotherapy, specifically adjuvant therapy, was shown to improve survival. Among patient-related factors, baseline chronic kidney disease, diabetes mellitus, body mass index, and systemic inflammation have gained recent attention. Some tumor related factors, such as stage, grade, location, and multifocality may negatively impact survival outcomes. Lymphovascular invasion and histologic variants are clinically significant pathological findings. RNU is a procedure with measured long-term oncologic outcomes. Minimally invasive techniques have gained an established role as they seem to offer comparable oncologic "safety", although special attention is needed in relation to the method of bladder cuff excision. Robotic RNU is gaining popularity, and while evidence remains limited, the current literature supports the oncologic safety of this procedure. Several factors, which can be categorized as treatment-related, patient-related, and tumor-related, might impact the oncologic outcomes of UTUC patients undergoing RNU. These factors can provide crucial information to stratify patients based on their relative risk of disease recurrence and mortality which may guide clinical decision-making.

Śivagṛha: religious harmonization and the concept of unity in diversity

Prambanan Temple is a Hindu Nusantara Theological Archetype, where the name of the Parabrahman temple becomes Prambanan which means worship of the Supreme God, or the highest temple. The pattern of temple construction that uses the Vāstupuruṣamaṇḍala pattern and the concept of worship is characterized by Hindu Theology which is universal, overshadowing all isms. Relics in the form of Prambanan Temple, the grandest temple in Nusantara, illustrate the glory of Hinduism in the past and the theological concepts and ideas of diversity that are developing today. This qualitative research examines Prambanan Temple as an Archetype of Hindu Nusantara Theology that encourages religious harmonization and upholds the concept of unity amid differences. The research was conducted in several locations, such as the Prambanan Temple Complex, the Indonesian National Museum, the Jakarta National Library, and the Yogyakarta Archaeological Agency. Data analysis was carried out using qualitative analysis known as Ethnographic Content Analysis (ECA), a combination of objective content analysis with participant observation. The original name of Prambanan Temple is Śivagrha which means House of Śiva or Śivalaya-nature of Śiva, as well as the temple of Lord Śiva. Śivagrha is a temple complex worshiping the Tri Murti, namely Brahma, Visnu, and Śiva, as the Creator, Sustainer, and Demolisher. From the structure of the building and the text search, this temple has a Śivaistic concept, namely Śiva is worshiped as the highest Devata. However, it also attracted other devotees and united them with the construction of other deities worshiped in the various temples in this complex. Thus Prambanan became a center of worship, a center for study, a center for Brahmin activities, and a spiritual center or a yatra destination for the wider community.

Gesture retrieval and its application to the study of multimodal communication

Comprehending communication is dependent on analyzing the different modalities of conversation, including audio, visual, and others. This is a natural process for humans, but in digital libraries, where preservation and dissemination of digital information are crucial, it is a complex task. A rich conversational model, encompassing all modalities and their co-occurrences, is required to effectively analyze and interact with digital information. Currently, the analysis of co-speech gestures in videos is done through manual annotation by linguistic experts based on textual searches. However, this approach is limited and does not fully utilize the visual modality of gestures. This paper proposes a visual gesture retrieval method using a deep learning architecture to extend current research in this area. The method is based on body keypoints and uses an attention mechanism to focus on specific groups. Experiments were conducted on a subset of the NewsScape dataset, which presents challenges such as multiple people, camera perspective changes, and occlusions. A user study was conducted to assess the usability of the results, establishing a baseline for future gesture retrieval methods in real-world video collections. The results of the experiment demonstrate the high potential of the proposed method in multimodal communication research and highlight the significance of visual gesture retrieval in enhancing interaction with video content. The integration of visual similarity search for gestures in the open-source multimedia retrieval stack, vitrivr, can greatly contribute to the field of computational linguistics. This research advances the understanding of the role of the visual modality in co-speech gestures and highlights the need for further development in this area.

Discriminator-Enhanced Knowledge-Distillation Networks

Query auto-completion (QAC) serves as a critical functionality in contemporary textual search systems by generating real-time query completion suggestions based on a user’s input prefix. Despite the prevalent use of language models (LMs) in QAC candidate generation, LM-based approaches frequently suffer from overcorrection issues during pair-wise loss training and efficiency deficiencies. To address these challenges, this paper presents a novel framework—discriminator-enhanced knowledge distillation (Dis-KD)—for the QAC task. This framework combines three core components: a large-scale pre-trained teacher model, a lightweight student model, and a discriminator for adversarial learning. Specifically, the discriminator aids in discerning generative-level differences between the teacher and the student models. An additional discriminator score loss is amalgamated with the traditional knowledge-distillation loss, resulting in enhanced performance of the student model. Contrary to the stepwise evaluation of each generated word, our approach assesses the entire generation sequence. This method alleviates the prevalent overcorrection issue in the generation process. Consequently, our proposed framework boasts improvements in model accuracy and a reduction in parameter size. Empirical results highlight the superiority of Dis-KD over established baseline methods, with the student model surpassing the teacher model in QAC tasks for sub-word languages.

Interdisciplinary Approach to Identify and Characterize COVID-19 Misinformation on Twitter: Mixed Methods Study.

Studying COVID-19 misinformation on Twitter presents methodological challenges. A computational approach can analyze large data sets, but it is limited when interpreting context. A qualitative approach allows for a deeper analysis of content, but it is labor-intensive and feasible only for smaller data sets. We aimed to identify and characterize tweets containing COVID-19 misinformation. Tweets geolocated to the Philippines (January 1 to March 21, 2020) containing the words coronavirus, covid, and ncov were mined using the GetOldTweets3 Python library. This primary corpus (N=12,631) was subjected to biterm topic modeling. Key informant interviews were conducted to elicit examples of COVID-19 misinformation and determine keywords. Using NVivo (QSR International) and a combination of word frequency and text search using key informant interview keywords, subcorpus A (n=5881) was constituted and manually coded to identify misinformation. Constant comparative, iterative, and consensual analyses were used to further characterize these tweets. Tweets containing key informant interview keywords were extracted from the primary corpus and processed to constitute subcorpus B (n=4634), of which 506 tweets were manually labeled as misinformation. This training set was subjected to natural language processing to identify tweets with misinformation in the primary corpus. These tweets were further manually coded to confirm labeling. Biterm topic modeling of the primary corpus revealed the following topics: uncertainty, lawmaker's response, safety measures, testing, loved ones, health standards, panic buying, tragedies other than COVID-19, economy, COVID-19 statistics, precautions, health measures, international issues, adherence to guidelines, and frontliners. These were categorized into 4 major topics: nature of COVID-19, contexts and consequences, people and agents of COVID-19, and COVID-19 prevention and management. Manual coding of subcorpus A identified 398 tweets with misinformation in the following formats: misleading content (n=179), satire and/or parody (n=77), false connection (n=53), conspiracy (n=47), and false context (n=42). The discursive strategies identified were humor (n=109), fear mongering (n=67), anger and disgust (n=59), political commentary (n=59), performing credibility (n=45), overpositivity (n=32), and marketing (n=27). Natural language processing identified 165 tweets with misinformation. However, a manual review showed that 69.7% (115/165) of tweets did not contain misinformation. An interdisciplinary approach was used to identify tweets with COVID-19 misinformation. Natural language processing mislabeled tweets, likely due to tweets written in Filipino or a combination of the Filipino and English languages. Identifying the formats and discursive strategies of tweets with misinformation required iterative, manual, and emergent coding by human coders with experiential and cultural knowledge of Twitter. An interdisciplinary team composed of experts in health, health informatics, social science, and computer science combined computational and qualitative methods to gain a better understanding of COVID-19 misinformation on Twitter.

Essential components of a definition for early antibiotic treatment failure: A scoping review.

Despite the broad global use of antibiotics, there is no established definition of early antibiotic treatment failure (EATF) to aid clinical evaluation of treatment, which leads to inconsistent assessments of drug effectiveness. This scoping review aims to identify common components of EATF definitions by synthesizing studies mentioning EATF and its relevant thesaurus matches. Scoping review. This scoping review was conducted following the PRISMA Scoping review guidelines. A systematic literature search was conducted using MEDLINE (PubMed), CENTRAL, CINAHL, and Web of Science, as well as a manual Google search. Search terms were EATF and its thesaurus matches. After removing duplications, candidate studies were screened by title and abstract prior to full text searches, and quality analysis was performed on eligible studies using the Critical Appraisal Skills Programme. From each eligible study, the timing of evaluation, basic components, and detailed information for each definition of EATF were collected. The components of each definition for EATF were then summarized and counted, and finally the most common essential components were identified. Our systematic literature search found 2,472 candidate studies. After title and abstract screening, full text search and quality assessment, 61 studies, including 56 original studies and five reviews, were eligible for our analysis. Of these 56 original studies, 43 mentioned the timing of EATF evaluation 72 hours after the start of treatment with antibiotics. From these 43 studies, the most common indicators of EATF were extracted, among which a set of essential components for a definition of EATF were identified: mortality, vital signs, fever, symptoms, and additional treatment. Our scoping review uncovered five essential factors for EATF. Further study is needed to evaluate the validity of our findings.

P-554 Examination of Mobile Applications Specific to Infertile Couples Through the “APPLICATIONS” Scoring System in Holistic and Utility Perspectives

Abstract Study question Does mobile applications (apps) developed for infertile couples have a holistic and utility characteristic? Summary answer Many mobil apps developed in the field of fertility have limited features and very few relevant, understandable, and holistic apps were present for infertile individuals. What is known already In an increasingly technological world, mobile apps offer promising alternatives to support couples’ fertility treatment. Infertile couples can use these apps with aim to manage lifestyle, learn about fertility, follow clinical appointments, receive psychological support, or to seek peer support. For increasing efficiency of this applications, holistic approach should be considered. Human is a whole with biological, physiological, psychological, social and spiritual dimensions and in fertility treatment process all dimensions are highly crucial. Thus, the purpose of this study was to evaluate the utility and holistic perspectives of apps developed for infertile couples by using “APPLICATIONS” mobile app scoring system. Study design, size, duration The study was a systematic evaluation of apps related to fertility and it was conducted via mobile applications platform. To determine relevant apps search was conducted on Google Play and Apple App Store by using “infertility”, “fertility”, “in vitro fertilization”, “IVF”, “sterility” and “fecundity” key words.The search was conducted twice in 1-year intervals, in February 2021 and March 2022. In total from 1917 reached apps; 1841 apps were excluded, and 76 eligible app were evaluated. Participants/materials, setting, methods Mobile apps were independently evaluated by two authors via using APPLICATIONS scoring system. The APPLICATIONS scoring system consists objective criteria such as comprehensiveness (holistic approach), fee, subscription, use of evidence-based information, purchasing, connection, advertising, text search area, interplatform suitability, use of images/shapes or videos, and app-specific features are objective scoring criteria and subjective criteria for instance subjective presentation and ease of navigation in the app. Consequently the maximum score of APPLICATIONS scoring system is 17. Main results and the role of chance The study reached 1917 applications from the search with its keywords. Seventy-six mobile applications meeting the inclusion criteria were analyzed according to the “APPLICATIONS” scoring system. Of the 76 applications in the analysis, 18 were available only in the Apple App Store (23%), 28 were available only in the Google Play Store (36%), and 30 were available on both platforms (41%). Among analyzed app, we determined that one app received 16 points out of maximum 17 points, and two apps received 15 points each. Also, the lowest scoring app earned 4 points. According to overall composite scores, evaluable apps in our study showed scores in the middle range of possible scores with an average score of 9 out of 17, indicating insufficient quality in mobile apps. Besides that, only six apps (%7.8) meet all holistic comprehensiveness criteria and received full scores. Of 76 mobile applications, 31.5% were developed by a healthcare professional, 31.5% by a software company, and 38% by an unknown entity. In addition, 48% of the applications evaluated were specific to infertile couples, 45% were specific to infertile women, and 7% were specific to infertile men. Limitations, reasons for caution Because of the nature of the digital environment, mobile apps are in a continuously changing and rapidly developing internet environment, and currently, newly developed mobile apps were not present in the analysis. This was the limitation of our study. Wider implications of the findings Using mobile health apps can help infertile couples to improve treatment outcomes. Healthcare professionals should be aware of the widespread use of apps and correct the faulty practice recommendations that patients may encounter, and couples should be guided to the correct practices. Trial registration number not applicable

Avadhūta: Examining the Emergence and Institutionalisation of an Antinomian Ascetic

Abstract In numerous historical and contemporary cases, and in various textual and lived traditions, several Hindu ascetics have been called avadhūtas. Yet, there is little scholarly research on this ascetic designation. Based on an ‘iterative’ textual search of early and medieval Hindu texts, this article examines the literary emergence and early reception of the avadhūta ascetic. I argue that the avadhūta label emerged in the late first-millennium CE and was institutionalised within the āśrama system in the early second-millennium CE. I further posit that the avadhūta’s emergence is probably connected to the systematisation of the jīvanmukti or liberation-while-living doctrine, and that the institutionalisation of the antinomian avadhūta ascetic as a legitimate saṃnyāsin or renouncer correlates with two interrelated factors: medieval advaitins defending the avadhūta from anti-jīvanmukti critics and the increasing theological importance of the āśrama system.

The perception of life and death in patients with end-of-life stage cancer: A systematic review of qualitative research

PurposeThis study aims to clarify the perceptions on life and death among patients with the end-of-life stage cancer through a systematic review. MethodsThe search strategy combined MeSH terminology with free text searches, and was applied to the PubMed, CINAHL, Embase, and ICHUSHI (Japan Medical Abstracts Society) databases covering from 2010 to 5/2022. To ensure the quality of the research included, the Critical Appraisal Skills Program Qualitative Studies Checklist was used. Data relating to the perceptions of life and death of patients with the end-of-life stage cancer was extracted and analyzed with reference to qualitative meta-synthesis methods. ResultsUltimately, 50 studies were included. Five themes were derived based on the perceptions of life and death of patients with the end-of-life stage cancer: despair, making sense of death, how to live the rest of life, special feelings for loved ones, and fluctuation. By making sense of death in their own way, and reconciling it with their current situation, patients with the end-of-life stage cancer, even in despair over their impending death, look ahead into the future and their surroundings and consider how they would live the remaining time they have. During this time, the special feelings they have for their loved ones make an impact. ConclusionsAn important new finding from this study lies in the fact that the patients’ desire to live as ordinary people who were not patients were expressed as a face that they hid from their families. Further research is needed in low-income countries/regions.

Að blóta á íslensku

Swearing in Icelandic is the topic of this article. The main focus is on the grammatical aspects of swear words, i.e. their morphological and syntactic characteristics and behaviour, emphasizing how one swears rather than why. The Tagged Icelandic Corpus (MÍM), containing searchable texts from the early 21st century, is the primary source for the analysis. Even if the vocabulary of swear words is relatively small and swearing is a formulaic use of language, the results show that there can be considerable flexibility in Icelandic swearing and that there are creative means to modify and extend both the vocabulary and the syntactic constructions typical of swearing. The vocabulary extensions are partly based on word-formation (in some cases with unusual methods) and partly by borrowing, especially from English nowadays. In the syntax, certain forms of nouns used in swearing have acquired new functions, e.g. by using them adverbially, and nominal phrases can be extended by adding attributes preceeding the head-noun, adding to their diversity and effect. In such phrases, the genitive forms of swear nouns ‒ usually preceeding the head counter to genitive attributes in other nominal phrases — have been reinterpreted as adjectives allowing them to be freely coordinated in a string of attributes without conjoining them by conjunctions.

A Novel Informatics Tool to Detect Periprocedural Antibiotic Allergy Adverse Events for Near Real-time Surveillance to Support Audit and Feedback

Standardized processes for identifying when allergic-type reactions occur and linking reactions to drug exposures are limited. To develop an informatics tool to improve detection of antibiotic allergic-type events. This retrospective cohort study was conducted from October 1, 2015, to September 30, 2019, with data analyzed between July 1, 2021, and January 31, 2022. The study was conducted across Veteran Affairs hospitals among patients who underwent cardiovascular implantable electronic device (CIED) procedures and received periprocedural antibiotic prophylaxis. The cohort was split into training and test cohorts, and cases were manually reviewed to determine presence of allergic-type reaction and its severity. Variables potentially indicative of allergic-type reactions were selected a priori and included allergies entered in the Veteran Affair's Allergy Reaction Tracking (ART) system (either historical [reported] or observed), allergy diagnosis codes, medications administered to treat allergic reactions, and text searches of clinical notes for keywords and phrases indicative of a potential allergic-type reaction. A model to detect allergic-type reaction events was iteratively developed on the training cohort and then applied to the test cohort. Algorithm test characteristics were assessed. Preprocedural and postprocedural prophylactic antibiotic administration. Antibiotic allergic-type reactions. The cohort of 36 344 patients included 34 703 CIED procedures with antibiotic exposures (mean [SD] age, 72 [10] years; 34 008 [98%] male patients); median duration of postprocedural prophylaxis was 4 days (IQR, 2-7 days; maximum, 45 days). The final algorithm included 7 variables: entries in the Veteran Affair's hospitals ART, either historic (odds ratio [OR], 42.37; 95% CI, 11.33-158.43) or observed (OR, 175.10; 95% CI, 44.84-683.76); PheCodes for "symptoms affecting skin" (OR, 8.49; 95% CI, 1.90-37.82), "urticaria" (OR, 7.01; 95% CI, 1.76-27.89), and "allergy or adverse event to an antibiotic" (OR, 11.84, 95% CI, 2.88-48.69); keyword detection in clinical notes (OR, 3.21; 95% CI, 1.27-8.08); and antihistamine administration alone or in combination (OR, 6.51; 95% CI, 1.90-22.30). In the final model, antibiotic allergic-type reactions were identified with an estimated probability of 30% or more; positive predictive value was 61% (95% CI, 45%-76%); and sensitivity was 87% (95% CI, 70%-96%). In this retrospective cohort study of patients receiving periprocedural antibiotic prophylaxis, an algorithm with a high sensitivity to detect incident antibiotic allergic-type reactions that can be used to provide clinician feedback about antibiotic harms from unnecessarily prolonged antibiotic exposures was developed.

Lexicon-based probabilistic indexing of handwritten text images

Keyword Spotting (KWS) is here considered as a basic technology for Probabilistic Indexing (PrIx) of large collections of handwritten text images to allow fast textual access to the contents of these collections. Under this perspective, a probabilistic framework for lexicon-based KWS in text images is presented. The presentation aims at providing formal insights which help understanding classical statements of KWS (from which PrIx borrows fundamental concepts), as well as the relative challenges entailed by these statements. The development of the proposed framework makes it clear that word recognition or classification implicitly or explicitly underlies any formulation of KWS. Moreover, it suggests that the same statistical models and training methods successfully used for handwriting text recognition can advantageously be used also for PrIx, even though PrIx does not generally require or rely on any kind of previously produced image transcripts. Experiments carried out using these approaches support the consistency and the general interest of the proposed framework. Results on three datasets traditionally used for KWS benchmarking are significantly better than those previously published for these datasets. In addition, good results are also reported on two new, larger handwritten text image datasets (Bentham and Plantas), showing the great potential of the methods proposed in this paper for indexing and textual search in large collections of untranscribed handwritten documents. Specifically, we achieved the following Average Precision values: IAMDB: 0.89, George Washington: 0.91, Parzival: 0.95, Bentham: 0.91 and Plantas: 0.92.

Digitally transforming FM standards and their development process: Allowing experts to focus on what matters

For many years, standardization has been a driver of innovation and the acceleration of societal developments, both generally and within the built environment (BE) and facility management (FM). Recently, new acceleration factors – digitalization and digital transformation – have presented valuable opportunities for the industry of standardization (i.e. ISO, CEN, BS, IFMA, etc.) that may have a rippling effect on other industries; for example, increased standardization and digitalization are seen as key in reducing carbon footprints, and the digitalization of standards is believed to be particularly beneficial as it will improve required information flow. The purpose of this research was to identify the opportunity space for digitalization and digital transformation within standardization by investigating the nature of the life cycle of standards and the requirements for digitally transforming them. Two types of experts were interviewed: FM standardization experts who are well acquainted with standardization processes and digital experts working primarily with information and communication technologies (ICT). The interviews revealed that many see a need for digitalization and that machine-readable standards, AI-based text search tools and more are viewed as valuable possibilities. Two ways to look at digitalization opportunities in standardization were identified: the digitalisation of standardization work and standards enabling digital FM practice. The digitalization of standards offers excellent opportunities to improve the quality of standards, increase efficiency of both the use of and the development of standard, including improving the experience of subject matter experts involved in the process of standardization. Jointly, these efforts may be the catalyst for FM’s digital transformation.

Models, theoretical design and formal evaluation of integrated specialist community health service provision for the first 2000 days: a scoping review

ObjectiveThis scoping review identifies evidence for design, models and evaluation of integrated care service provision for families and children in the first 2000 days, in the context of community-based specialised...

Commentary on Jones et al.: We must consider emergency medical services data an opportunity for a view into a community.

Jones et al. demonstrate that through hard work and thoughtful review, even disparate data can assist the advancement of public health and public policy across jurisdictions. An emergency medical services industry-led focus on documentation standards and data integration can make this easier and more effective for our patients. Jones et al. have taken on the challenging task of identifying the characteristics of opioid-related incidents (ORI) from emergency medical services (EMS) calls to assess the impact of opioids in Massachusetts. They responded to a legislative mandate to review EMS records by creating a free text search and a five-tier severity cascade where opioid use can be identified, even without overdoses [1]. These researchers demonstrate the need to review all available data despite the fact that Massachusetts [2], like much of the United States, utilizes multiple EMS documentation platforms, written in disparate documentation styles, then aggregated through the National EMS Information System (NEMSIS) [3]. Authors have focused previously upon the use of naloxone to identify a non-fatal overdose [4-6], but many ORI do not receive naloxone [7]. Jones et al. used a free text search for terms in the narrative to point to specific types of ORI. This search function was elegantly designed to go beyond the discrete variables of NEMSIS and search for ORI by intoxicant name and concerning symptoms. Jones et al. have previously demonstrated gender disparity with EMS naloxone administration, indicating why it is vital to use narrative data to identify ORI [8]. The strength of this search and the ORI severity cascade is further demonstrated, as 29% of the opioid intoxications and 36% of all ORI did not receive naloxone. The OTHER ORI allows a broad range of conditions that can factor into the impact of opioid use disorder and serve as a further marker for opportunity for intervention and change. EMS records are the first chapter of the story of nearly every critical patient encounter and assist in the care of vulnerable patients. However, when hospital systems implement an electronic health record they frequently save money by not integrating local EMS data. When embedded in the health-care continuum, EMS data can help to advance public health and public policy. Jones et al.’s multi-tiered approach to ORI is an important step towards realizing this goal. Michael Winter Dailey: Writing—original draft (lead); writing—review and editing (equal). Emma Furlano: Writing—original draft (supporting); writing—review and editing (equal).

AAJS: An Anti-Malicious Attack Graphic Similarity Judgment System in Cloud Computing Environments

With the rapid development of cloud computing and other modern technologies, collaborative computing between data is increasing, and privacy protection and secure multi-party computation are also attracting more attention. The emergence of cloud computing provides new options for data holders to perform complex computing problems and to store images; however, data privacy issues cannot be ignored. If a graphic is encrypted and stored in the cloud, the cloud server will perform confidential similar matching when the user searches. At present, most research on searchable encryption is focused on text search, with few schemes researched on how to finish the graphic search. To solve this problem, this paper proposes a secure search protocol based on graph shape under the semi-honest model. Using the cut-choose method and zero-knowledge proof, further designs of the anti-malicious attack graphic similarity judgment system (AAJS) based on the Paillier encryption algorithm, can achieve the secure search and matching of the graph while resisting malicious adversary attacks. The proposed protocol’s security is proved by the real/ideal model paradigm. This paper conducts performance analysis and experimental simulation on the existing scheme and the experiments demonstrate that the system achieves high execution efficiency.

SEARCHING FOR (AND FINDING) NEOCOLONIAL FANTASIES: SEXUALIZATION OF WOMEN FROM THE GLOBAL SOUTH AND THE GLOBAL EAST IN GOOGLE'S TEXT SEARCH RESULTS

Search engines serve as information gatekeepers on a multitude of topics dealing with different aspects of society. However, the ways search engines filter and rank information are prone to biases related to gender, ethnicity, and race. In this paper, we conduct a systematic algorithm audit to examine how one specific form of misrepresentation bias, namely, sexualization, is manifested in Google's text search results about different national and gender groups. We find evidence of sexualization of women, particularly those from the Global South and East in search outputs. This is amplified by contextual advertisements pushed by Google in response to different search queries.

Unpublished clinical trials of common rheumatic diseases.

Randomized controlled trials (RCTs) provide high-quality evidence for treatment efficacy, but many RCTs remain unpublished. The objective of this study was to describe the proportion of unpublished RCTs in five rheumatic diseases and to identify factors associated with publication. Registered RCTs for five rheumatic diseases (SLE, vasculitis, spondyloarthritis, SS and PsA) with over 30 months since study completion were identified using ClinicalTrials.gov. Index publications were identified by NCT ID numbers and structured text searches of publication databases. The results of unpublished studies were identified in abstracts and press releases; reasons for non-publication were assessed by surveying corresponding authors. Out of 203 studies that met eligibility criteria, 17.2% remained unpublished, representing data from 4281 trial participants. Higher proportions of published trials were phase 3 RCTs (57.1% vs 28.6% unpublished, P < 0.05) or had a positive primary outcome measure (64.9% vs 25.7% unpublished, P < 0.001). In a multivariable Cox proportional hazards model, a positive outcome was independently associated with publication (hazard ratio 1.55; 95% CI: 1.09, 2.22). Corresponding authors of 10 unpublished trials cited ongoing preparation of the manuscript (50.0%), sponsor/funder issues (40.0%) and unimportant/negative result (20.0%) as reasons for lack of publication. Nearly one in five RCTs in rheumatology remain unpublished 2 years after trial completion, and publication is associated with positive primary outcome measures. Efforts to encourage universal publication of rheumatology RCTs and reanalysis of previously unpublished trials should be undertaken.

AODB: A comprehensive database for antioxidants including small molecules, peptides and proteins

Antioxidants are widely used in the fields of food, medicine, nutraceuticals, and cosmetics. Given their important roles in promoting and maintaining human health, a large number of antioxidants have been reported. Some antioxidant-related databases have been developed; however, the annotation of antioxidants and related information stored in existing databases is incomplete and requires more efficient retrieval methods. This study aimed to develop a manually curated comprehensive antioxidant database (AODB). Currently, it stores 56,666 small molecules tested for antioxidant activity, 1480 antioxidant peptides, and 998 antioxidant proteins, including their structures, names, antioxidant assay records, computable physicochemical and ADMET properties, and sources. AODB supports text search and mining, 2D and 3D chemical structure search, and BLAST-based protein sequence search, enabling users to retrieve antioxidant data quickly and easily. AODB, as a one-stop antioxidant database, can facilitate the exploration of antioxidants and potential applications. AODB is publicly available and updated annually at https://aodb.idruglab.cn/.

UniProt Tools: BLAST, Align, Peptide Search, and ID Mapping.

The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data (UniProt Consortium, 2023). The UniProt website receives about 800,000 unique visitors per month and is the primary means to access UniProt. Along with various datasets that you can search, UniProt provides four main tools. These are the "BLAST" tool for sequence similarity searching, the "Align" tool for multiple sequence alignment, the "Peptide Search" tool for retrieving proteins containing a short peptide sequence, and the "Retrieve/ID Mapping" tool for using a list of identifiers to retrieve UniProt Knowledgebase (UniProtKB) proteins and to convert database identifiers from UniProt to external databases or vice versa. This article provides four basic protocols and seven alternate protocols for using UniProt tools. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Basic local alignment search tool (BLAST) in UniProt Alternate Protocol 1: BLAST through UniProt text search results pages Alternate Protocol 2: BLAST through UniProt basket Basic Protocol 2: Multiple sequence alignment in UniProt Alternate Protocol 3: Align tool through UniProt results pages and entry pages Alternate Protocol 4: Align tool through UniProt basket Basic Protocol 3: Peptide search in UniProt Basic Protocol 4: Batch retrieval and ID mapping in UniProt Alternate Protocol 5: Retrieve/ID Mapping tool through UniProt text search results pages and BLAST and Align results pages Alternate Protocol 6: Retrieve/ID Mapping tool through UniProt basket Alternate Protocol 7: Retrieve/ID Mapping tool through UniProt search box.