bluuebunny/crossref_metadata_2025_split huggingface dataset:
Social Support Buffers the Effect of Social Deprivation on Comorbidity Burden in Adults with Cancer
Authors: Bellizzi Keith M , Fritzson Emily , Ligus Kaleigh , Park Crystal L 
Published: June 2024

Abstract

Background
Adults with cancer have higher rates of comorbidity compared to those without cancer, with excess burden in people from lower socioeconomic status (SES). Social deprivation, based on geographic indices, broadens the focus of SES to include the importance of “place” and its association with health. Further, social support is a modifiable resource found to have direct and indirect effects on health in adults with cancer, with less known about its impact on comorbidity.

Purpose
We prospectively examined associations between social deprivation and comorbidity burden and the potential buffering role of social support.

Methods
Our longitudinal sample of 420 adults (Mage = 59.6, SD = 11.6; 75% Non-Hispanic White) diagnosed with cancer completed measures at baseline (~6 months post-diagnosis) and four subsequent 3-month intervals for 1 year.

Results
Adjusting for age, cancer type, and race/ethnicity, we found a statistically significant interaction between social support and the effect of social deprivation on comorbidity burden (β = −0.11, p = 0.012), such that greater social support buffered the negative effect of social deprivation on comorbidity burden.

Conclusion
Implementing routine screening for social deprivation in cancer care settings can help identify patients at risk of excess comorbidity burden. Clinician recognition of these findings could trigger a referral to social support resources for individuals high on social deprivation.
What is military strategy?
Authors: Echevarria II Antulio J. 
Published: June 2024

Abstract
Military strategy is the practice of reducing an adversary’s physical capacity and willingness to fight, and continuing to do so until one’s aim is achieved. It takes place in wartime and peacetime and may involve using force, directly or indirectly, as a threat. Military strategy is often divided into four components: ends (objectives), ways (courses of action), means (resources), and risk. The practice of military strategy is described along with military power, which is augmented by nine “principles of war”: objective, maneuver, surprise, mass, economy of force, offensive, security, simplicity, and unity of command. A general will likely use combinations of military strategies, linking them into a series of operations or campaigns.
Decapitation and targeted killing
Authors: Echevarria II Antulio J. 
Published: June 2024

Abstract
The military strategies of decapitation and targeted killing derive from dislocation and attrition, respectively. Decapitation is the attempt to paralyze or destroy a group by removing its leadership, and targeted killing is the systematic elimination of an organization’s members, whether these individuals are in key positions of leadership or in the rank and file. Both strategies have been widely used to combat terrorists and insurgents. “Decapitation and targeted killing” shows that the use of these strategies has increased markedly since the twenty-first century began, particularly with the widespread production of remotely piloted vehicles, but they remain highly controversial as strategic techniques. They may not destroy an organization permanently, but they can temporarily degrade its effectiveness.
Malaria
Authors: McMillen Christian W. 
Published: June 2024

Abstract
Malaria originated in Africa and is caused by an infection with the plasmodium protozoan. Five types have infected humans; Plasmodium falciparum is the most lethal and is responsible for the vast majority of global malaria deaths. ‘Malaria’ outlines the spread of malaria from Africa, into Europe and the New World. Generally, agricultural and rural development has been responsible for the proliferation of malaria, but poor sanitation and stagnant water can make malaria an urban disease. Vector and parasite control is described, along with the World Health Organization’s Malaria Eradication Program and attempts to stem malaria with treated bed nets and more effective drugs.
Epilogue
Authors: McMillen Christian W. 
Published: June 2024

Abstract
There will be more pandemics. A pandemic might come from an old, familiar foe such as influenza or might emerge from a new source—a zoonosis that makes its way into humans. The epilogue asks how the world will confront pandemics in the future. It is likely that patterns established long ago will re-emerge. But how will new challenges, like climate change, affect future pandemics and our ability to respond? Will lessons learned from the past help with plans for the future? One thing is clear: in the face of a serious pandemic much of the developing world’s public health infrastructure will be woefully overburdened. This must be addressed.
Data-driven surveillance: new challenges
Authors: Lyon David 
Published: June 2024

Abstract
This chapter explores the challenges of data-driven surveillance. It provides an overview of platforms that depend on data, gathered from multiple sources wherein data-gathering relies on the everyday involvement of people going about their daily lives in digital environments. Data are deliberately gathered to be analysed through algorithms for the various purposes that platform companies have in mind. The chapter elaborates on the spread of surveillance capitalism, which erodes the limits and legal regulations by the government that were once placed on commercial practices. It also introduces the notion of predictive policing, which is about how data may be used to say what sorts of criminal activity are likely to occur, where, and when.
Small World derived index to distinguish Alzheimer’s type dementia and healthy subjects
Authors: Vecchio Fabrizio , Miraglia Francesca , Pappalettera Chiara , Nucci Lorenzo , Cacciotti Alessia , Rossini Paolo Maria 
Published: June 2024

Abstract

Background
This article introduces a novel index aimed at uncovering specific brain connectivity patterns associated with Alzheimer's disease (AD), defined according to neuropsychological patterns.

Methods
Electroencephalographic (EEG) recordings of 370 people, including 170 healthy subjects and 200 mild-AD patients, were acquired in different clinical centres using different acquisition equipment by harmonising acquisition settings. The study employed a new derived Small World (SW) index, SWcomb, that serves as a comprehensive metric designed to integrate the seven SW parameters, computed across the typical EEG frequency bands. The objective is to create a unified index that effectively distinguishes individuals with a neuropsychological pattern compatible with AD from healthy ones.

Results
Results showed that the healthy group exhibited the lowest SWcomb values, while the AD group displayed the highest SWcomb ones.

Conclusions
These findings suggest that SWcomb index represents an easy-to-perform, low-cost, widely available and non-invasive biomarker for distinguishing between healthy individuals and AD patients.
Development and validation of a frailty index for use in the osteoarthritis initiative
Authors: O’Brien Myles W , Maxwell Selena P , Moyer Rebecca , Rockwood Kenneth , Theou Olga 
Published: June 2024

Abstract

Background
The Osteoarthritis Initiative (OAI) evaluates the development and progression of osteoarthritis. Frailty captures the heterogeneity in aging. Use of this resource-intensive dataset to answer aging-related research questions could be enhanced by a frailty measure.

Objective
To: (i) develop a deficit accumulation frailty index (FI) for the OAI; (ii) examine its relationship with age and compare between sexes, (iii) validate the FI versus all-cause mortality and (iv) compare this association with mortality with a modified frailty phenotype.

Design
OAI cohort study.

Setting
North America.

Subjects
An FI was determined for 4,755/4,796 and 4,149/4,796 who had a valid FI and frailty phenotype.

Methods
Fifty-nine-variables were screened for inclusion. Multivariate Cox regression evaluated the impact of FI or phenotype on all-cause mortality at follow-up (up to 146 months), controlling for age and sex.

Results
Thirty-one items were included. FI scores (0.16 ± 0.09) were higher in older adults and among females (both, P &lt; 0.001). By follow-up, 264 people had died (6.4%). Older age, being male, and greater FI were associated with a higher risk of all-cause mortality (all, P &lt; 0.001). The model including FI was a better fit than the model including the phenotype (AIC: 4,167 vs. 4,178) and was a better predictor of all-cause mortality than the phenotype with an area under receiver operating characteristic curve: 0.652 vs. 0.581.

Conclusion
We developed an FI using the OAI and validated it in relation to all-cause mortality. The FI may be used to study aging on clinical, functional and structural aspects of osteoarthritis included in the OAI.
Invited commentary: motivating better methods—and better data collection—for measuring the prevalence of drug misuse
Authors: Kiang Mathew V , Alexander Monica J 
Published: June 2024

Abstract
The United States continues to suffer a drug overdose crisis that has resulted in over 100 000 deaths annually since 2021. Despite decades of attention, estimates of the prevalence of drug use at the spatiotemporal resolutions necessary for resource allocation and intervention evaluation are lacking. Current approaches for measuring the prevalence of drug use, such as population surveys, capture–recapture, and multiplier methods, have significant limitations. In a recent article, Santaella-Tenorio et al (Am J Epidemiol. 2024;193(7):959-967) used a novel joint bayesian spatiotemporal modeling approach to estimate the county-level prevalence of opioid misuse in New York State from 2007 to 2018 and identify significant intrastate variation. By leveraging 5 data sources and simultaneously modeling different opioid-related outcomes—such as numbers of deaths, emergency department visits, and treatment visits—they obtained policy-relevant insights into the prevalence of opioid misuse and opioid-related outcomes at high spatiotemporal resolutions. The study provides future researchers with a sophisticated modeling approach that will allow them to incorporate multiple data sources in a rigorous statistical framework. The limitations of the study reflect the constraints of the broader field and underscore the importance of enhancing current surveillance with better, newer, and more timely data that are both standardized and easily accessible to inform public health policies and interventions.
This article is part of a Special Collection on Mental Health.
Jingle–Jangle Fallacies in L2 Motivational Self System Research: A Response to Al-Hoorie et al. (2024)
Authors: Henry Alastair , Liu Meng 
Published: June 2024

Abstract
In a systematic examination of scales commonly used in L2 Motivational Self System (L2MSS) research, Al-Hoorie et al. (2024) found discriminant validity problems. Raising jangle fallacy concerns, they argue that substantive research should be paused until validity issues are ironed out. However, validity at the measurement level is dependent on validity at the construct level. Replication attempts can fail when models are poorly theorized. To resolve problems at the measurement level, problems at the construct level need to be addressed.
Future Perspective of Risk Prediction in Aesthetic Surgery: Is Artificial Intelligence Reliable?
Authors: Duran Alpay , Cortuk Oguz , Ok Bora 
Published: June 2024

Abstract

Background
Artificial intelligence (AI) techniques are showing significant potential in the medical field. The rapid advancement in artificial intelligence methods suggests their soon-to-be essential role in physicians’ practices.

Objectives
In this study, we sought to assess and compare the readability, clarity, and precision of medical knowledge responses provided by 3 large language models (LLMs) and informed consent forms for 14 common aesthetic surgical procedures, as prepared by the American Society of Plastic Surgeons (ASPS).

Methods
The efficacy, readability, and accuracy of 3 leading LLMs, ChatGPT-4 (OpenAI, San Francisco, CA), Gemini (Google, Mountain View, CA), and Copilot (Microsoft, Redmond, WA), was systematically evaluated with 14 different prompts related to the risks of 14 common aesthetic procedures. Alongside these LLM responses, risk sections from the informed consent forms for these procedures, provided by the ASPS, were also reviewed.

Results
The risk factor segments of the combined general and specific operation consent forms were rated highest for medical knowledge accuracy (P &lt; .05). Regarding readability and clarity, the procedure-specific informed consent forms, including LLMs, scored highest scores (P &lt; .05). However, these same forms received the lowest score for medical knowledge accuracy (P &lt; .05). Interestingly, surgeons preferred patient-facing materials created by ChatGPT-4, citing superior accuracy and medical information compared to other AI tools.

Conclusions
Physicians prefer patient-facing materials created by ChatGPT-4 over other AI tools due to their precise and comprehensive medical knowledge. Importantly, adherence to the strong recommendation of ASPS for signing both the procedure-specific and the general informed consent forms can avoid potential future complications and ethical concerns, thereby ensuring patients receive adequate information.
Characterization of chloroplastic thioredoxin dependent glutathione peroxidase like protein in Euglena gracilis: biochemical and functional perspectives
Authors: Raihan Md Topu , Tanaka Yasuhiro , Ishikawa Takahiro 
Published: June 2024

ABSTRACT
Euglena gracilis, a fascinating organism in the scientific realm, exhibits characteristics of both animals and plants. It maintains redox homeostasis through a variety of enzymatic and non-enzymatic antioxidant molecules. In contrast to mammals, Euglena possesses nonselenocysteine glutathione peroxidase homologues that regulate its intracellular pools of reactive oxygen species. In the present study, a full-length cDNA of chloroplastic EgGPXL-1 was isolated and subjected to biochemical and functional characterization. Recombinant EgGPXL-1 scavenged H2O2 and t-BOOH, utilizing thioredoxin as an electron donor rather than glutathione. Despite its monomeric nature, EgGPXL-1 exhibits allosteric behavior with H2O2 as the electron acceptor and follows typical Michaelis–Menten kinetics with t-BOOH. Suppression of EgGPXL-1 gene expression under normal and high-light conditions did not induce critical situations in E. gracilis, suggesting the involvement of compensatory mechanisms in restoring normal conditions.
Isolation of 2,2′-azoxybisbenzyl alcohol from Agaricus subrutilescens and its inhibitory activity against bacterial biofilm formation
Authors: De Padua Jewel C , Tanaka Tomoya , Ueno Kotomi , dela Cruz Thomas Edison E , Ishihara Atsushi 
Published: June 2024

Abstract
Virulence pathways in pathogenic bacteria are regulated by quorum sensing mechanisms, particularly biofilm formation through autoinducer (AI) production and sensing. In this study, the culture filtrate extracted from an edible mushroom, Agaricus subrutilescens, was fractionated to isolate a compound that inhibits biofilm formation. Four gram-negative bacteria (Klebsiella pneumoniae, Escherichia coli, Proteus mirabilis, and Enterobacter cloacae) and two gram-positive bacteria (Enterococcus faecalis and Staphylococcus aureus) were used for the bioassay. The bioassay-guided chromatographic separations of the culture filtrate extract resulted in the isolation of the compound. Further, spectroscopic analyses revealed the identity of the compound as 2,2′-azoxybisbenzyl alcohol (ABA). The minimum inhibitory and sub-inhibitory concentrations of the compound were also determined. Azoxybisbenzyl alcohol was significantly effective in inhibiting biofilm formation in all tested bacteria, with half-maximal inhibitory concentrations of 3–11 µg/mL. Additionally, the bioactivity of ABA was confirmed through the bioassays for the inhibition of exopolysaccharide matrixes and AI activities.
Effect of phenolic-hydroxy-group incorporation on the biological activity of a simplified aplysiatoxin analog with an (R)-(−)-carvone-based core
Authors: Yanagita Ryo C , Suzuki Yoshiyuki , Kawanami Yasuhiro , Hanaki Yusuke , Irie Kazuhiro 
Published: June 2024

Abstract
We synthesized a phenolic hydroxy group-bearing version (1) of a simplified analog of aplysiatoxin comprising a carvone-based conformation-controlling unit. Thereafter, we evaluated its antiproliferative activity against human cancer cell lines and its binding affinity to protein kinase C (PKC) isozymes. The antiproliferative activity and PKC-binding ability increased with the introduction of the phenolic hydroxy group. The results of molecular dynamics simulations and subsequent relative binding free-energy calculations conducted using an alchemical transformation procedure showed that the phenolic hydroxy group in 1 could form a hydrogen bond with a phospholipid and the PKC. The former hydrogen bonding formation facilitated the partitioning of the compound from water to the phospholipid membrane and the latter compensated for the loss of hydrogen bond with the phospholipid upon binding to the PKC. This information may facilitate the development of rational design methods for PKC ligands with additional hydrogen bonding groups.
Optimizing in silico drug discovery: simulation of connected differential expression signatures and applications to benchmarking
Authors: Gonzalez Gomez Catalina , Rosa-Calatrava Manuel , Fouret Julien 
Published: June 2024

Abstract

Background
We present a novel simulation method for generating connected differential expression signatures. Traditional methods have struggled with the lack of reliable benchmarking data and biases in drug–disease pair labeling, limiting the rigorous benchmarking of connectivity-based approaches.

Objective
Our aim is to develop a simulation method based on a statistical framework that allows for adjustable levels of parametrization, especially the connectivity, to generate a pair of interconnected differential signatures. This could help to address the issue of benchmarking data availability for connectivity-based drug repurposing approaches.

Methods
We first detailed the simulation process and how it reflected real biological variability and the interconnectedness of gene expression signatures. Then, we generated several datasets to enable the evaluation of different existing algorithms that compare differential expression signatures, providing insights into their performance and limitations.

Results
Our findings demonstrate the ability of our simulation to produce realistic data, as evidenced by correlation analyses and the log2 fold-change distribution of deregulated genes. Benchmarking reveals that methods like extreme cosine similarity and Pearson correlation outperform others in identifying connected signatures.

Conclusion
Overall, our method provides a reliable tool for simulating differential expression signatures. The data simulated by our tool encompass a wide spectrum of possibilities to challenge and evaluate existing methods to estimate connectivity scores. This may represent a critical gap in connectivity-based drug repurposing research because reliable benchmarking data are essential for assessing and advancing in the development of new algorithms. The simulation tool is available as a R package (General Public License (GPL) license) at https://github.com/cgonzalez-gomez/cosimu.
Stratifying TAD boundaries pinpoints focal genomic regions of regulation, damage, and repair
Authors: Chen Bijia , Ren Chao , Ouyang Zhangyi , Xu Jingxuan , Xu Kang , Li Yaru , Guo Hejiang , Bai Xuemei , Tian Mengge , Xu Xiang , Wang Yuyang , Li Hao , Bo Xiaochen , Chen Hebing 
Published: June 2024

Abstract
Advances in chromatin mapping have exposed the complex chromatin hierarchical organization in mammals, including topologically associating domains (TADs) and their substructures, yet the functional implications of this hierarchy in gene regulation and disease progression are not fully elucidated. Our study delves into the phenomenon of shared TAD boundaries, which are pivotal in maintaining the hierarchical chromatin structure and regulating gene activity. By integrating high-resolution Hi-C data, chromatin accessibility, and DNA double-strand breaks (DSBs) data from various cell lines, we systematically explore the complex regulatory landscape at high-level TAD boundaries. Our findings indicate that these boundaries are not only key architectural elements but also vibrant hubs, enriched with functionally crucial genes and complex transcription factor binding site–clustered regions. Moreover, they exhibit a pronounced enrichment of DSBs, suggesting a nuanced interplay between transcriptional regulation and genomic stability. Our research provides novel insights into the intricate relationship between the 3D genome structure, gene regulation, and DNA repair mechanisms, highlighting the role of shared TAD boundaries in maintaining genomic integrity and resilience against perturbations. The implications of our findings extend to understanding the complexities of genomic diseases and open new avenues for therapeutic interventions targeting the structural and functional integrity of TAD boundaries.
deTELpy: Python package for high-throughput detection of amino acid substitutions in mass spectrometry datasets
Authors: Landerer Cedric , Scheremetjew Maxim , Moon HongKee , Hersemann Lena , Toth-Petroczy Agnes 
Published: June 2024

Abstract

Motivation
Errors in the processing of genetic information during protein synthesis can lead to phenotypic mutations, such as amino acid substitutions, e.g. by transcription or translation errors. While genetic mutations can be readily identified using DNA sequencing, and mutations due to transcription errors by RNA sequencing, translation errors can only be identified proteome-wide using mass spectrometry.

Results
Here, we provide a Python package implementation of a high-throughput pipeline to detect amino acid substitutions in mass spectrometry datasets. Our tools enable users to process hundreds of mass spectrometry datasets in batch mode to detect amino acid substitutions and calculate codon-specific and site-specific translation error rates. deTELpy will facilitate the systematic understanding of amino acid misincorporation rates (translation error rates), and the inference of error models across organisms and under stress conditions, such as drug treatment or disease conditions.

Availability and implementation
deTELpy is implemented in Python 3 and is freely available with detailed documentation and practical examples at https://git.mpi-cbg.de/tothpetroczylab/detelpy and https://pypi.org/project/deTELpy/ and can be easily installed via pip install deTELpy.