bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Passes to Florence
Authors: Havely Nick 
Published: April 2024

Abstract
Chapter 4 is the second of those addressing the history and perceptions of the routes over the Apennine ridge between Bologna and Florence. It begins by describing the stretch of the GEA between Il Giogo and the Passo della Futa, its convergence with the Via degli Dei walking route from Bologna, and some of the difficulties of wayfinding at this point. At the Passo della Futa World War II is again recalled by a visit to the German military cemetery; then the rest of the chapter concentrates on the travellers who crossed the pass on their way to or from Florence between the mid eighteenth century and the end of the nineteenth. Major figures include Goethe, Humphrey Davy, Beckford, Hazlitt, Fenimore Cooper, Lear, and Garibaldi, but a number of lesser known travellers are cited, and responses to Apennine landscape and the risks of travel (weather, brigandry) are a recurrent theme.
Introduction
Authors: Schellenberg J L 
Published: April 2024

AbstractThe Introduction explains the objectives of the book and describes its structure and content. Development is regarded as evolution that has resulted in some improvement. The book examines what various arguments from development show concerning the truth or falsity of classical Christian doctrine. Christian doctrine is conceived as holding that human beings are mired in sin, that we require deliverance and salvation, and that God has arranged for that deliverance through the sacrificial suffering, death, and resurrection of Jesus Christ, who was both a man and the divine Son of God. The Introduction notes that, as it formulates arguments against this doctrine, the book pays attention to recent social and ethical developments. The Introduction also pre-emptively answers a critique of the book’s approach, associated with the work of Tom Holland and based on the idea that Christianity is itself responsible for the forms of development here used to criticize it.
On the Divine Jesus
Authors: Schellenberg J L 
Published: April 2024

AbstractThis chapter introduces the Big Narrative, argues that God would have been opposed to it, and shows how we can conclude that the doctrine of the divinity of Jesus is false. The Big Narrative of the Bible centrally features important deficiencies. Given what God would always have known, God would have been opposed to it. Four arguments making use of this idea go further: if God would be opposed to the Big Narrative then God Incarnate would be opposed to it; God would not have wished to confirm the Big Narrative in the minds of people who heard of God’s action; the view of Jesus as the Son of God and as the Messiah, stands or falls with the Big Narrative; and there would have had to be some way, apart from one bound up with the Big Narrative, for a divine action of incarnation in Jesus to be justified.
What God Would Have Known
Authors: Schellenberg J L 
Published: April 2024

AbstractThe final chapter reconceives the arguments from development previously stated, and then shows how a new argument for the denial of theism can be formulated. This is the Argument Against Theism from the Cultural Success of Christianity. It holds that if God exists, then the salvific needs of the world are met. But if that’s so then no false salvation plan has gone into the world under God’s name and dominated the understanding of many humans for thousands of years, introducing new harms and deepening the need for real salvation. And yet this precisely is what we have given the cultural success of Christianity, which brought a supposed revelation from God bearing a misleading picture of theistic salvation that dictated the terms of salvation to a large part of human culture for 2,000 years. Thus the salvific needs of the world have not been met, and God does not exist.
Conclusion
Authors: Schellenberg J L 
Published: April 2024

AbstractThis short concluding statement clarifies the central position that the book is held to support, reflects on how easily Christians are prevented from seeing the relevance to that position of what God would have known, answers a query concerning what was left out of the book, and points in the direction of relevant further investigation. My position is that at least one of the twenty arguments from development formulated in previous chapters is sound. Even if only one of the arguments is right, the problem of contrary development is fatal to Christian doctrine. What God would have known can be seen to support these conclusions in several different ways. And there are interesting further questions that now suggest themselves: What might humans still do, in the religious realm, if classical Christian doctrine is intellectually a failure? What might Christians do, without ceasing to count as Christians?
National trends in prescription drug expenditures and projections for 2024
Authors: Tichy Eric M , Hoffman James M , Tadrous Mina , Rim Matthew H , Cuellar Sandra , Clark John S , Newell Mary Kate , Schumock Glen T 
Published: April 2024

Abstract

Purpose
To report historical patterns of pharmaceutical expenditures, to identify factors that may influence future spending, and to predict growth in drug spending in 2024 in the United States, with a focus on the nonfederal hospital and clinic sectors.

Methods
Historical patterns were assessed by examining data on drug purchases from manufacturers using the IQVIA National Sales Perspectives database. Factors that may influence drug spending in hospitals and clinics in 2024 were reviewed—including new drug approvals, patent expirations, and potential new policies or legislation. Focused analyses were conducted for biosimilars, cancer drugs, endocrine drugs, generics, and specialty drugs. For nonfederal hospitals, clinics, and overall (all sectors), estimates of growth of pharmaceutical expenditures in 2024 were based on a combination of quantitative analyses and expert opinion.

Results
In 2023, overall pharmaceutical expenditures in the US grew 13.6% compared to 2022, for a total of $722.5 billion. Utilization (a 6.5% increase), new drugs (a 4.2% increase) and price (a 2.9% increase) drove this increase. Semaglutide was the top drug in 2023, followed by adalimumab and apixaban. Drug expenditures were $37.1 billion (a 1.1% decrease) and $135.7 billion (a 15.0% increase) in nonfederal hospitals and clinics, respectively. In clinics, increased utilization drove growth, with a small impact from price and new products. In nonfederal hospitals, a drop in utilization led the decrease in expenditures, with price and new drugs modestly contributing to growth in spending. Several new drugs that will influence spending are expected to be approved in 2024. Specialty, endocrine, and cancer drugs will continue to drive expenditures.

Conclusion
For 2024, we expect overall prescription drug spending to rise by 10.0% to 12.0%, whereas in clinics and hospitals we anticipate an 11.0% to 13.0% increase and a 0% to 2.0% increase, respectively, compared to 2023. These national estimates of future pharmaceutical expenditure growth may not be representative of any health system because of the myriad of local factors that influence actual spending.
Eravacycline, an antibacterial drug, repurposed for pancreatic cancer therapy: insights from a molecular-based deep learning model
Authors: Jabarin Adi , Shtar Guy , Feinshtein Valeria , Mazuz Eyal , Shapira Bracha , Ben-Shabat Shimon , Rokach Lior 
Published: April 2024

Abstract

Background
Pancreatic ductal adenocarcinoma (PDAC) remains a serious threat to health, with limited effective therapeutic options, especially due to advanced stage at diagnosis and its inherent resistance to chemotherapy, making it one of the leading causes of cancer-related deaths worldwide. The lack of clear treatment directions underscores the urgent need for innovative approaches to address and manage this deadly condition. In this research, we repurpose drugs with potential anti-cancer activity using machine learning (ML).

Methods
We tackle the problem by using a neural network trained on drug–target interaction information enriched with drug–drug interaction information, which has not been used for anti-cancer drug repurposing before. We focus on eravacycline, an antibacterial drug, which was selected and evaluated to assess its anti-cancer effects.

Results
Eravacycline significantly inhibited the proliferation and migration of BxPC-3 cells and induced apoptosis.

Conclusion
Our study highlights the potential of drug repurposing for cancer treatment using ML. Eravacycline showed promising results in inhibiting cancer cell proliferation, migration and inducing apoptosis in PDAC. These findings demonstrate that our developed ML drug repurposing models can be applied to a wide range of new oncology therapeutics, to identify potential anti-cancer agents. This highlights the potential and presents a promising approach for identifying new therapeutic options.
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network
Authors: Hu Xiaowen , Zhang Pan , Liu Dayun , Zhang Jiaxuan , Zhang Yuanpeng , Dong Yihan , Fan Yanhao , Deng Lei 
Published: April 2024

Abstract
Accurately delineating the connection between short nucleolar RNA (snoRNA) and disease is crucial for advancing disease detection and treatment. While traditional biological experimental methods are effective, they are labor-intensive, costly and lack scalability. With the ongoing progress in computer technology, an increasing number of deep learning techniques are being employed to predict snoRNA–disease associations. Nevertheless, the majority of these methods are black-box models, lacking interpretability and the capability to elucidate the snoRNA–disease association mechanism. In this study, we introduce IGCNSDA, an innovative and interpretable graph convolutional network (GCN) approach tailored for the efficient inference of snoRNA–disease associations. IGCNSDA leverages the GCN framework to extract node feature representations of snoRNAs and diseases from the bipartite snoRNA-disease graph. SnoRNAs with high similarity are more likely to be linked to analogous diseases, and vice versa. To facilitate this process, we introduce a subgraph generation algorithm that effectively groups similar snoRNAs and their associated diseases into cohesive subgraphs. Subsequently, we aggregate information from neighboring nodes within these subgraphs, iteratively updating the embeddings of snoRNAs and diseases. The experimental results demonstrate that IGCNSDA outperforms the most recent, highly relevant methods. Additionally, our interpretability analysis provides compelling evidence that IGCNSDA adeptly captures the underlying similarity between snoRNAs and diseases, thus affording researchers enhanced insights into the snoRNA–disease association mechanism. Furthermore, we present illustrative case studies that demonstrate the utility of IGCNSDA as a valuable tool for efficiently predicting potential snoRNA–disease associations. The dataset and source code for IGCNSDA are openly accessible at: https://github.com/altriavin/IGCNSDA.
Detection of SARS-CoV-2 B.1.1.529 (Omicron) variant by SYBR Green-based RT-qPCR
Authors: Abdel-Sater Fadi , Makki Rawan , Khalil Alia , Hussein Nader , Borghol Nada , Abi Khattar Ziad , Hamade Aline , Khreich Nathalie , El Homsi Mahoumd , Kanaan Hussein , Raad Line , Skafi Najwa , Al-Nemer Fatima , Ghandour Zeinab , El-Zein Nabil , Abou-Hamdan Mhamad , Akl Haidar , Hamade Eva , Badran Bassam , Hamze Kassem 
Published: April 2024

Abstract
The coronavirus disease 2019 (COVID-19) pandemic is unceasingly spreading across the globe, and recently a highly transmissible Omicron SARS-CoV-2 variant (B.1.1.529) has been discovered in South Africa and Botswana. Rapid identification of this variant is essential for pandemic assessment and containment. However, variant identification is mainly being performed using expensive and time-consuming genomic sequencing. In this study, we propose an alternative RT-qPCR approach for the detection of the Omicron BA.1 variant using a low-cost and rapid SYBR Green method. We have designed specific primers to confirm the deletion mutations in the spike (S Δ143-145) and the nucleocapsid (N Δ31-33) which are characteristics of this variant. For the evaluation, we used 120 clinical samples from patients with PCR-confirmed SARS-CoV-2 infections, and displaying an S-gene target failure (SGTF) when using TaqPath COVID-19 kit (Thermo Fisher Scientific, Waltham, USA) that included the ORF1ab, S, and N gene targets. Our results showed that all the 120 samples harbored S Δ143-145 and N Δ31-33, which was further confirmed by whole-genome sequencing of 10 samples, thereby validating our SYBR Green-based protocol. This protocol can be easily implemented to rapidly confirm the diagnosis of the Omicron BA.1 variant in COVID-19 patients and prevent its spread among populations, especially in countries with high prevalence of SGTF profile.
Real-World Patterns and Economic Burden Associated With Treatment Failure With Advanced Therapies in Patients With Moderate-to-Severe Ulcerative Colitis
Authors: Lee Scott D , Betts Keith A , Xiaoyan Du Ella , Nie Xiaoyu , Gupte-Singh Komal , Ritter Timothy 
Published: April 2024

Abstract

Background
Some patients lose response during treatment for moderate-to-severe ulcerative colitis (UC). We aimed to characterize real-world treatment failure patterns and associated economic burdens during use of first-line advanced therapies for UC.

Methods
IBM MarketScan Commercial and Medicare Supplemental Databases were used to identify adults initiating ≥ 1 advanced therapy for UC (January 1, 2010–September 30, 2019). Treatment failure was defined as augmentation with non-advanced therapy, discontinuation, dose escalation/interval shortening, failure to taper corticosteroids, UC-related surgery, or UC-related urgent care ≤ 12 months after treatment initiation. The index date was the date of treatment failure (treatment failure cohort) or 12 months after treatment initiation (persistent cohort). Treatment failure rates were assessed using Kaplan–Meier analyses. All-cause and UC-related healthcare resource utilization (HCRU) and costs 12 months post-index were also assessed.

Results
Analysis of treatment failure patterns included data from 6745 patients; HCRU and cost analyses included data from 5302 patients (treatment failure cohort, n = 4295; persistent cohort, n = 1007). In the overall population, 75% experienced treatment failure within the first 12 months (median: 5.1 months). Augmentation with non-advanced therapy (39%) was the most common first treatment failure event. The treatment failure cohort had significantly (P &lt; .001) higher mean costs than the persistent cohort (all-cause, $74 995 vs $56 169; UC-related, $57 096 vs $47 347) mainly attributed to inpatient admissions and outpatient visits. Dose escalation/interval shortening accounted for the highest total costs ($101 668) across treatment failure events.

Conclusions
Advanced therapies for moderate-to-severe UC are associated with high rates of treatment failure and significant economic burden. More efficacious and durable treatments are needed.
Unconventional diagnosis of bradyarrhythmic syncope in Brugada syndrome: a case report
Authors: Esposito Francesca , Nappi Felice , Urraro Francesco , Vitillo Paolo , Rotondi Francesco 
Published: April 2024

Abstract

Background
The Brugada syndrome (BrS) is an inherited disorder associated with the risk of ventricular fibrillation and sudden cardiac death (SCD). The current main therapy is an implantable cardioverter-defibrillator (ICD). However, the risk stratification and management of patients remain challenging. Here, we present a case of BrS representative of the pitfalls that clinicians may encounter in the management of Brugada patients in routine clinical practice.

Case summary
A 39-year-old man with BrS and recurring syncope was implanted with a subcutaneous ICD (S-ICD) (EMBLEM MRI S-ICD, Boston Scientific). Syncope recurred some months later. Subcutaneous ICD interrogation showed no arrhythmic events, but SMART Pass (high-pass filter) deactivation was noted. A query was sent to Boston Scientific clinical service, unveiling an extremely long asystolic pause as syncope determinant. Subcutaneous ICD was explanted and replaced by conventional single chamber ICD in the pre-pectoral region.

Discussion
Brugada syndrome patients with high-risk features are candidates for ICD implantation to prevent SCD. Recent evidence highlighted that symptomatic patients carry a substantially higher risk compared with asymptomatic ones. Syncope may represent a pivotal symptom in BrS patients, but young patients with Type 1 Brugada pattern may experience syncope other than from tachyarrhythmias. Subcutaneous ICD is an advisable option in young ICD recipients to avoid lifetime complication related to standard transvenous systems. However, S-ICD lacks pacing capabilities and, therefore, is not indicated when an anti-bradycardia system is needed. The diagnostic workup of syncope in Brugada patients may be ineffective in elucidating the underlying aetiology whose understanding is essential to offer a personalized therapeutic approach.
Unlocking the potential of artificial intelligence in electrocardiogram biometrics: age-related changes, anomaly detection, and data authenticity in mobile health platforms
Authors: Mangold Kathryn E , Carter Rickey E , Siontis Konstantinos C , Noseworthy Peter A , Lopez-Jimenez Francisco , Asirvatham Samuel J , Friedman Paul A , Attia Zachi I 
Published: April 2024

Abstract

Aims
Mobile devices such as smartphones and watches can now record single-lead electrocardiograms (ECGs), making wearables a potential screening tool for cardiac and wellness monitoring outside of healthcare settings. Because friends and family often share their smart phones and devices, confirmation that a sample is from a given patient is important before it is added to the electronic health record.

Methods and results
We sought to determine whether the application of Siamese neural network would permit the diagnostic ECG sample to serve as both a medical test and biometric identifier. When using similarity scores to discriminate whether a pair of ECGs came from the same patient or different patients, inputs of single-lead and 12-lead medians produced an area under the curve of 0.94 and 0.97, respectively.

Conclusion
The similar performance of the single-lead and 12-lead configurations underscores the potential use of mobile devices to monitor cardiac health.
A data-centric perspective on exposomics data analysis
Authors: Chang Le , Ewald Jessica , Hui Fiona , Bayen Stéphane , Xia Jianguo 
Published: April 2024

Abstract
Exposomics represents a systematic approach to investigate the etiology of diseases by formally integrating individuals’ entire environmental exposures and associated biological responses into the traditional genotype-phenotype framework. The field is largely enabled by various omics technologies which offer practical means to comprehensively measure key components in exposomics. The bottleneck in exposomics has gradually shifted from data collection to data analysis. Effective and easy-to-use bioinformatics tools and computational workflows are urgently needed to help obtain robust associations and to derive actionable insights from the observational, heterogenous, and multi-omics datasets collected in exposomics studies. This data-centric perspective starts with an overview of the main components and common analysis workflows in exposomics. We then introduce six computational approaches that have proven effective in addressing some key analytical challenges, including linear modeling with covariate adjustment, dimensionality reduction for covariance detection, neural networks for identification of complex interactions, network visual analytics for organizing and interpreting multi-omics results, Mendelian randomization for causal inference, and cause-effect validation by coupling effect-directed analysis with dose-response assessment. Finally, we present a series of well-designed web-based tools, and briefly discuss how they can be used for exposomics data analysis.
Validation and forensic application of a new 36 X-STR loci multiplex system
Authors: Chen Kaiqin , Tao Ruiyang , Qu Yiling , Lu Junnan , Ping Yuan , Zhang Yilun , Chen Pengyu , Li Chengtao 
Published: April 2024

Abstract
X-chromosomal short tandem repeats (X-STRs) are indispensable in specific cases, distinct from autosomal and Y chromosome genetic markers. SureID® X37 is an innovative six-color fluorescence multiplex detection system that can simultaneously amplify 36 X-STR loci (including DXS6795, DXS7132, DXS8378, DXS10101, DXS10103, DXS10079, DXS10134, GATA172D05, HPRTB, DXS6810, DXS10135, DXS6797, DXS10074, DXS7424, DXS9902, DXS7423, DXS10148, DXS10162, DXS6809, GATA31E08, DXS6803, DXS10075, DXS6807, DXS10164, DXS6789, DXS10146, DXS981, DXS9895, DXS101, DXS6800 DXS907, and DXS8377) and the Amelogenin locus. In this study, we validated its suitability for forensic identification per SWGDAM (Scientific Working Group on DNA analysis methods) guidelines, including PCR conditions, precision, accuracy, case-type samples, sensitivity, repeatability, reproducibility, species specificity, stability, stutter calculation, and DNA mixtures. Additionally, 577 Han Chinese individuals were used to investigate the utility of the system in forensic population genetics. The results indicated that the system is sensitive, stable, and reliable, and is suitable for typical forensic case. Subsequent population investigations confirmed that it serves as a potent supplementary tool in forensic applications.
Texture analysis of apparent diffusion coefficient maps: can it identify nonresponse to neoadjuvant chemotherapy for additional radiation therapy in rectal cancer patients?
Authors: Wu Qianyu , Yi Yongju , Lai Bingjia , Li Jiao , Lian Yanbang , Chen Junhong , Wu Yue , Wang Xinhua , Cao Wuteng 
Published: April 2024

Abstract

Background
Neoadjuvant chemotherapy (NCT) alone can achieve comparable treatment outcomes to chemoradiotherapy in locally advanced rectal cancer (LARC) patients. This study aimed to investigate the value of texture analysis (TA) in apparent diffusion coefficient (ADC) maps for identifying non-responders to NCT.

Methods
This retrospective study included patients with LARC after NCT, and they were categorized into nonresponse group (pTRG 3) and response group (pTRG 0–2) based on pathological tumor regression grade (pTRG). Predictive texture features were extracted from pre- and post-treatment ADC maps to construct a TA model using RandomForest. The ADC model was developed by manually measuring pre- and post-treatment ADC values and calculating their changes. Simultaneously, subjective evaluations based on magnetic resonance imaging assessment of TRG were performed by two experienced radiologists. Model performance was compared using the area under the curve (AUC) and DeLong test.

Results
A total of 299 patients from two centers were divided into three cohorts: the primary cohort (center A; n = 194, with 36 non-responders and 158 responders), the internal validation cohort (center A; n = 49, with 9 non-responders) and external validation cohort (center B; n = 56, with 33 non-responders). The TA model was constructed by post_mean, mean_change, post_skewness, post_entropy, and entropy_change, which outperformed both the ADC model and subjective evaluations with an impressive AUC of 0.997 (95% confidence interval [CI], 0.975–1.000) in the primary cohort. Robust performances were observed in internal and external validation cohorts, with AUCs of 0.919 (95% CI, 0.805–0.978) and 0.938 (95% CI, 0.840–0.985), respectively.

Conclusions
The TA model has the potential to serve as an imaging biomarker for identifying nonresponse to NCT in LARC patients, providing a valuable reference for these patients considering additional radiation therapy.