bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-time prediction of distance and PGA from P-wave features using Gradient Boosting Regressor for on-site earthquake early warning applications
Authors: Iaccarino Antonio Giovanni , Cristofaro Amalia , Picozzi Matteo , Spallarossa Daniele , Scafidi Davide 
Published: November 2023

SUMMARY
On-site earthquake early warning (EEW) systems represent an important way to reduce seismic hazard. Since these systems are fast in providing an alert and reliable in the prediction of the ground motion intensity at targets, they are particularly suitable in the areas where the seismogenic zones are close to cities and infrastructures, such as Central Italy.
In this work, we use Gradient Boosting Regressor (GBR) to predict peak ground acceleration (PGA), and hypocentral distance (D) starting from P-wave features. We use two data sets of waveforms from two seismic sequences in Central Italy: L'Aquila sequence (2009) and the Amatrice–Norcia–Visso sequence (2016–2017), for a total of about 80 000 three-component waveforms. We compute 60 different features related to the physics of the earthquake using three different time windows (1 s, 2 s and 3 s). We validate and train our models using the 2016–2017 data sets (the bigger one) and we test it on the 2009 data set.
We study the performances of GBR predicting D and PGA in terms of prediction scores, finding that the models can well predict both targets even using 1 s window, and that, as expected, the results improve using longer time windows. Moreover, we perform a residual analysis on the test set finding that the PGA can be predicted without any bias, while the D prediction presents a correlation with the moment magnitude.
In the end, we propose a prototype for a probabilistic on-site EEW system based on the prediction of D and PGA. The proposed system is a threshold-based approach and it releases an alert on four possible levels, from 0 (far and small event) to 3 (close and strong event). The system computes the probability related to each alert level. We test two different set of thresholds: the Felt Alert and the Damage Alert. Furthermore, we consider the lead time (LT) of the PGA to distinguish between useful alerts (positive LT) and Missed Alerts (MA). In the end, we analyse the performance of such a system considering four possible scenarios: Successful Alert (SA), Missed Alert (MA), Overestimated Alert (OA) and Underestimated Alert (UA). We find that the system obtains SA rate about 80 per cent at 1 s, and that it decreases to about 65 per cent due to the increase in MA. This result shows how the proposed system is already reliable at 1 s, which would be a huge advantage for seismic prone regions as Central Italy, an area characterized by moderate-to-large earthquakes (Mw &lt; 7).
Exploring motivations for engagement with the Healthy Lunch Box campaign on social media
Authors: Chan Lilian , Freeman Becky , Hughes Clare , Richmond Korina , Dibbs Jane , O’Hara Blythe J 
Published: November 2023

Abstract
Many health organisations seek social media engagement through their online health promotion campaigns, but there is little understanding of what engagement means in relation to the uptake of health messages. To understand the relevance of social media engagement, we need to look at the reasons why people engage with health content via social media. This exploratory study examined people’s motivations for engaging with health content through a case study of the Healthy Lunch Box campaign. Data was collected via online focus groups (n = 7), with participants being a convenience sample of people who had seen or engaged with the Healthy Lunch Box resources (n = 24). The discussions covered reasons for engaging with the Healthy Lunch Box campaign, and more broadly with health content on social media in general. The data was analysed using a reflexive approach to thematic analysis, with themes developed inductively. The study found that some of the reasons for engagement aligned with the paradigm of social media engagement being an intermediary step in the process towards health behaviour change. However, people also described other reasons, such as alignment with their personal values, consideration of their online presentation, or as a way of curating the content they wanted to be shown on social media. These results demonstrate that people’s decision to engage with health-related social media content involves more than consideration about the usefulness of the content, suggesting the need for a deeper examination of the assumptions made about the value of social media engagement in health campaign evaluations.
Public perception of the resumption of HPV vaccine recommendation in Japan: Twitter content analysis
Authors: Terada Marina , Okuhara Tsuyoshi , Nagasawa Tomomi , Okada Hiroko , Goto Eiko , Kiuchi Takahiro 
Published: November 2023

Abstract
On 12 November 2021, after a stagnation of 8.5 years, Japan decided to resume proactive recommendations for HPV vaccines. However, it is not known how the public reacted to the resumption of proactive recommendations for HPV vaccines, which are key elements in health communication that promote HPV vaccination. This study aimed to capture discussions on HPV vaccination on Twitter and to identify user characteristics, sentiments, discussed themes and their potential reach before and after 12 November 2021, when the Ministry of Health, Labour, and Welfare’s decision to resume proactive recommendation for HPV vaccines was first reported by the media in Japan. This study conducted a content analysis of tweets related to HPV vaccines posted on 11 November and 12 November 2021. Tweets were coded in terms of user characteristics, sentiments (i.e. positive, negative and neutral) and themes. Reach was measured by the number of retweets, likes and followers. A total of 3623 tweets were identified. The results showed that approximately 50% of health professionals and researchers tweeted neutral content about HPV vaccines. The most frequently discussed theme was the safety and side effects of HPV vaccines, which was accompanied by mainly negative sentiments. Although health professionals and researchers are influential on Twitter, half of them tweeted neutrally about HPV vaccines. Influential professionals, such as health professionals and researchers, are expected to disseminate accurate information to correct misinformation and recommend HPV vaccination on Twitter to overcome the HPV vaccination crisis, which is characterized by the low vaccination rates.
Subtyping and prognostic model construction based on vesicle-mediated transport-related genes in colorectal cancer
Authors: Wu Wei , Huang Tong , Li Shengwen , Gong Guangwei , Zhao Dan , Qiu Yue 
Published: November 2023

Abstract

Background
Colorectal cancer (CRC) is impacted by various environmental and genetic variables. Dysregulation of vesicle-mediated transport-related genes (VMTRGs) has been observed in many malignancies, but their effect on prognosis in CRC remains unclear.

Methods
CRC samples were clustered into varying subtypes per differential expression of VMTRGs. R package was utilized to explore differences in survival, immune, and drug sensitivity among different disease subtypes. According to differentially expressed genes (DEGs) between subtypes, regression analysis was employed to build a riskscore model and identify independent prognostic factors. The model was validated through a Gene Expression Omnibus (GEO) dataset. Immune landscape, immunophenoscore (IPS), and Tumor Immune Dysfunction and Exclusion (TIDE) scores for different risk groups were calculated.

Results
Two subtypes of CRC were identified based on VMTRGs, which showed significant differences in survival rates, immune cell infiltration abundance, immune functional activation levels, and immune checkpoint expression levels. Cluster2 exhibited higher sensitivity to anti-tumor drugs such as Nilotinib, Cisplatin, and Oxaliplatin compared to Cluster1. DEGs were mainly enriched in biological processes such as epidermis development, epidermal cell differentiation, and receptor-ligand activity, and signaling pathways like pancreatic secretion. The constructed 13-gene riskscore model demonstrated good predictive ability for CRC patients’ prognosis. Furthermore, differences in immune landscape, IPS, and TIDE scores were observed among different risk groups.

Conclusion
This study successfully obtained two CRC subtypes with distinct survival statuses and immune levels based on differential expression of VMTRGs. A 13-gene risk model was constructed. The findings had important implications for prognosis and treatment of CRC.
Vulnerability, Care Ethics and the Protection of Socioeconomic Rights via Article 3 ECHR
Authors: Morris Katie 
Published: November 2023

Abstract
Vulnerability analysis serves a distinct purpose within adjudication of Article 3 of the European Convention of Human Rights ('ECHR'), in that it has been used by the European Court of Human Rights (‘ECtHR’ or ‘the Court’) to lower the threshold for a finding of ill-treatment from which positive obligations relating to socioeconomic rights have arisen. However, the group-based notion of vulnerability invoked by the Court is extremely limited, producing minimal protection from deprivation whilst equally paternalizing and essentializing the populations it deems vulnerable. In light of these failings, this article proposes a new element to be incorporated within the Court’s vulnerability analysis which can deliver greater protection of socioeconomic rights via Article 3: the political theory of care. By highlighting care’s potential to transform the concepts of vulnerability and state responsibility whilst empowering the care-receiver, it argues that care can overcome the limitations of the Court’s current approach as a means of targeting destitution.
Single Nucleotide Polymorphisms of the MEFV Gene E148Q Are Highly Associated With Disease Phenotype in Crohn’s Disease
Authors: Yamada Satoshi , Honzawa Yusuke , Yamamoto Shuji , Matsuura Minoru , Kitamoto Hiroki , Okabe Makoto , Kakiuchi Nobuyuki , Toyonaga Takahiko , Kobayashi Taku , Hibi Toshifumi , Seno Hiroshi , Nakase Hiroshi 
Published: November 2023

Abstract

Background
Single nucleotide polymorphisms (SNPs) of the MEFV gene may modify inflammatory bowel disease (IBD) activity. The prevalence of MEFV gene SNPs in IBD patients and their involvement in IBD pathophysiology remains unclear.

Methods
We analyzed 12 MEFV gene SNPs in peripheral leukocytes of Japanese IBD patients (Crohn’s disease [CD]: 69 patients, ulcerative colitis: 32 patients) by polymerase chain reaction using next-generation DNA sequencing and evaluated their prevalence and association with the disease characteristics. Inflammasome activity and mature interleukin (IL)-1β and IL-18 production were evaluated in peripheral blood mononuclear cells obtained from CD patients stimulated with lipopolysaccharides and adenosine triphosphate, and compared between those with and without the E148Q SNP. COL1A1 and HSP47 gene expression was analyzed in CCD-18Co cells costimulated with IL-1β and other inflammatory cytokines.

Results
The prevalence of MEFV gene SNPs in IBD patients was similar to that in the human gene database. E148Q was the most common SNP. Compared with CD patients without E148Q, those with E148Q had a significantly greater frequency of the stricture phenotype, and their peripheral blood mononuclear cells exhibited significantly higher IL-1β and IL-18 levels and higher caspase-1 activity. IL-1β and IL-17A synergistically increased COL1A1 and HSP47 gene expression.

Conclusions
MEFV gene SNPs, including E148Q, modify the behavior of CD. IL-1β and IL-18 are produced through enhanced caspase-1 activity in monocytes of CD patients with E148Q. IL-1β promotes gene expression of fibrosis-related genes by cooperating with IL-17A in myofibroblasts. Therefore, E148Q might be a disease-modifying gene associated with the fibrostenosis phenotype in CD patients.
On Experiencing Music from Within
Authors: Skow Bradford 
Published: November 2023

Abstract
Experiencing the emotion in a piece of music “from within” involves imagining feeling that emotion, but just what does one imagine, and why? It has been suggested that one imagines, of one’s experience of hearing the sounds, that it is one’s feeling the emotion. This suggestion, it is argued here, is unworkable. A better idea is that one imagines oneself to be expressing one’s emotion in the sounds of the music. But imagining, by itself, is subject to few constraints; it is possible, with enough effort, to listen to an anxious piece of music, and imagine oneself expressing one’s joy through it. To vindicate the idea, then, the constraints under which one imagines when one listens “from within” must be described. It is argued that one imagines feeling, for example, sad when listening to sad music from within, because one begins by imagining one’s hearing the sounds to be one’s perceiving one’s own behavior, and then allows this imaginative episode to unfold involuntarily. An imagining that one feels sad is then generated, in part, by an offline-running of one’s disposition to infer what emotion one feels from internal perceptions of one’s behavior.
Insulting Religion: Penal Secularism and the Government of Feeling
Authors: Scott J Barton 
Published: November 2023

AbstractThis article revisits the Indian Penal Code’s restrictions on religious offense, especially Section 295A, with particular attention to nineteenth-century debates about secularizing the English common law of blasphemy. Building on scholarship that takes the histories of British and Indian secularisms as constitutively intertwined, I suggest that these entangled legal secularisms are best studied within a single analytic frame. I further suggest that this colonial secularism was, among other things, an affective apparatus. It linked the modern state to questions of sentiment or feeling, implicitly defining “religious feeling” as a species of affect with an intrinsic link to populational violence. Although colonial law ostensibly sought to reduce such violence, it instead had a more complex and perverse set of effects. Section 295A and its cousins turned law into a relay point for the circulation of affect, a mechanism for the transmission of populational pain.
Use of different anticholinergic scales and their correlation with anticholinergic symptom burden in a cohort of people living with HIV
Authors: Mazzitelli Maria , Trunfio Mattia , Coin Alessandra , Sasset Lolita , Farina Jacopo , Brundu Monica , Scaglione Vincenzo , Devita Maria , Sergi Giuseppe , Cattelan Anna M 
Published: November 2023

Abstract

Objectives
How to detect the clinical impact of anticholinergic (AC) burden in people with HIV (PWH) remains poorly investigated. We cross-sectionally described the prevalence and type of AC signs/symptoms and the screening accuracy of three AC scales in detecting their presence in a modern cohort of PWH.

Methods
We calculated AC Burden Scale (ABS), AC Risk Score (ARS) and AC Drug Score (ADS) in 721 adult PWH and recorded the presence of AC signs/symptoms over the previous 3 months. High AC risk was defined by ABS score ≥2, and ARS or ADS score ≥3. Comparisons among the scale were based on Cohen’s inter-rater agreement, and their screening accuracy was assessed by receiver operating characteristics (ROC) curves and performance measures.

Results
We enrolled 721 PWH, of whom 72.0% of participants were male; the median age was 53 years, and 164 participants (22.7%) were on at least one AC drug. Among these, 28.6% experienced at least one AC sign/symptom. Agreement in AC risk classification was substantial only between ARS and ADS (k = 0.6). Lower and higher risk of AC signs/symptoms was associated with dual regimens [adjusted OR (aOR) = 0.12 versus three-drug regimens, P = 0.002] and increasing number of AC drugs (aOR = 12.91, P &lt; 0.001). Depression and COPD were also associated with higher risk of AC signs/symptoms in analysis unadjusted for number of AC drugs. ABS and ADS showed the best area under the ROC curve (AUROC) of 0.85 (0.78–0.92) and 0.84 (0.75–0.92; P &lt; 0.001 for both). However, at the cut-off used for the general population, the sensitivity of all three scales was very low (34.0%, 46.8% and 46.8%).

Conclusions
Up to one-fourth of participants in our cohort were exposed to at least one AC drug, and among them AC signs/symptoms affected more than one-fourth. Both polypharmacy (as number of antiretrovirals and of co-medications with AC properties) and to a lesser extent specific comorbidities shaped the risk of developing AC signs/symptoms. Sensitive screenings for AC risk in PWH should prefer ABS or ADS based on lower cut-offs than those suggested for the general population.
Prediction of multiclass surgical outcomes in glaucoma using multimodal deep learning based on free-text operative notes and structured EHR data
Authors: Lin Wei-Chun , Chen Aiyin , Song Xubo , Weiskopf Nicole G , Chiang Michael F , Hribar Michelle R 
Published: November 2023

Abstract

Objective
Surgical outcome prediction is challenging but necessary for postoperative management. Current machine learning models utilize pre- and post-op data, excluding intraoperative information in surgical notes. Current models also usually predict binary outcomes even when surgeries have multiple outcomes that require different postoperative management. This study addresses these gaps by incorporating intraoperative information into multimodal models for multiclass glaucoma surgery outcome prediction.

Materials and methods
We developed and evaluated multimodal deep learning models for multiclass glaucoma trabeculectomy surgery outcomes using both structured EHR data and free-text operative notes. We compare those to baseline models that use structured EHR data exclusively, or neural network models that leverage only operative notes.

Results
The multimodal neural network had the highest performance with a macro AUROC of 0.750 and F1 score of 0.583. It outperformed the baseline machine learning model with structured EHR data alone (macro AUROC of 0.712 and F1 score of 0.486). Additionally, the multimodal model achieved the highest recall (0.692) for hypotony surgical failure, while the surgical success group had the highest precision (0.884) and F1 score (0.775).

Discussion
This study shows that operative notes are an important source of predictive information. The multimodal predictive model combining perioperative notes and structured pre- and post-op EHR data outperformed other models. Multiclass surgical outcome prediction can provide valuable insights for clinical decision-making.

Conclusions
Our results show the potential of deep learning models to enhance clinical decision-making for postoperative management. They can be applied to other specialties to improve surgical outcome predictions.
Complementary and Integrative Health Information in the literature: its lexicon and named entity recognition
Authors: Zhou Huixue , Austin Robin , Lu Sheng-Chieh , Silverman Greg Marc , Zhou Yuqi , Kilicoglu Halil , Xu Hua , Zhang Rui 
Published: November 2023

Abstract

Objective
To construct an exhaustive Complementary and Integrative Health (CIH) Lexicon (CIHLex) to help better represent the often underrepresented physical and psychological CIH approaches in standard terminologies, and to also apply state-of-the-art natural language processing (NLP) techniques to help recognize them in the biomedical literature.

Materials and methods
We constructed the CIHLex by integrating various resources, compiling and integrating data from biomedical literature and relevant sources of knowledge. The Lexicon encompasses 724 unique concepts with 885 corresponding unique terms. We matched these concepts to the Unified Medical Language System (UMLS), and we developed and utilized BERT models comparing their efficiency in CIH named entity recognition to well-established models including MetaMap and CLAMP, as well as the large language model GPT3.5-turbo.

Results
Of the 724 unique concepts in CIHLex, 27.2% could be matched to at least one term in the UMLS. About 74.9% of the mapped UMLS Concept Unique Identifiers were categorized as “Therapeutic or Preventive Procedure.” Among the models applied to CIH named entity recognition, BLUEBERT delivered the highest macro-average F1-score of 0.91, surpassing other models.

Conclusion
Our CIHLex significantly augments representation of CIH approaches in biomedical literature. Demonstrating the utility of advanced NLP models, BERT notably excelled in CIH entity recognition. These results highlight promising strategies for enhancing standardization and recognition of CIH terminology in biomedical contexts.
AutoCriteria: a generalizable clinical trial eligibility criteria extraction system powered by large language models
Authors: Datta Surabhi , Lee Kyeryoung , Paek Hunki , Manion Frank J , Ofoegbu Nneka , Du Jingcheng , Li Ying , Huang Liang-Chin , Wang Jingqi , Lin Bin , Xu Hua , Wang Xiaoyan 
Published: November 2023

Abstract

Objectives
We aim to build a generalizable information extraction system leveraging large language models to extract granular eligibility criteria information for diverse diseases from free text clinical trial protocol documents. We investigate the model’s capability to extract criteria entities along with contextual attributes including values, temporality, and modifiers and present the strengths and limitations of this system.

Materials and Methods
The clinical trial data were acquired from https://ClinicalTrials.gov/. We developed a system, AutoCriteria, which comprises the following modules: preprocessing, knowledge ingestion, prompt modeling based on GPT, postprocessing, and interim evaluation. The final system evaluation was performed, both quantitatively and qualitatively, on 180 manually annotated trials encompassing 9 diseases.

Results
AutoCriteria achieves an overall F1 score of 89.42 across all 9 diseases in extracting the criteria entities, with the highest being 95.44 for nonalcoholic steatohepatitis and the lowest of 84.10 for breast cancer. Its overall accuracy is 78.95% in identifying all contextual information across all diseases. Our thematic analysis indicated accurate logic interpretation of criteria as one of the strengths and overlooking/neglecting the main criteria as one of the weaknesses of AutoCriteria.

Discussion
AutoCriteria demonstrates strong potential to extract granular eligibility criteria information from trial documents without requiring manual annotations. The prompts developed for AutoCriteria generalize well across different disease areas. Our evaluation suggests that the system handles complex scenarios including multiple arm conditions and logics.

Conclusion
AutoCriteria currently encompasses a diverse range of diseases and holds potential to extend to more in the future. This signifies a generalizable and scalable solution, poised to address the complexities of clinical trial application in real-world settings.