bluuebunny/crossref_metadata_2025_split huggingface dataset:
Biological biomarkers in muscle diseases relevant for follow-up and evaluation of treatment
Authors: Stemmerik Mads G , Tasca Giorgio , Gilhus Nils Erik , Servais Laurent , Vicino Alex , Maggi Lorenzo , Sansone Valeria , Vissing John 
Published: October 2024

Abstract
Muscle diseases cover a diverse group of disorders that, in most cases, are hereditary. The rarity of the individual muscle diseases provides a challenge for researchers when wanting to establish natural history of the conditions and when trying to develop diagnostic tools, therapies, and outcome measures to evaluate disease progression. With emerging molecular therapies in many genetic muscle diseases, as well as biological therapies for the immune-mediated diseases, biological biomarkers play an important role in both drug development and evaluation.
In this review, we focus on the role of biological biomarkers in muscle diseases and discuss their utility as surrogate end points in therapeutic trials. We categorize these as either (i) disease unspecific markers; (ii) markers of specific pathways that may be used for more than one disease; or (iii) disease-specific markers. We also propose that evaluation of specific therapeutic interventions benefits from biological markers that match the intervention.
Impact of tildrakizumab on the quality of life of patients with moderate-to-severe psoriasis: a 36-week prospective monocentric real-life observational study
Authors: Cacciapuoti Sara , Battista Teresa , Potestio Luca , Scalvenzi Massimiliano , Megna Matteo , Ruggiero Angelo 
Published: October 2024

Abstract

Background
Psoriasis may significantly affect the health-related quality of life (HRQoL) of patients. Clinical assessment has been combined with HRQoL scores to evaluate the ways in which cutaneous disease affects patients. Tildrakizumab is a humanized IgG1 monoclonal antibody that targets the p19 subunit of interleukin-23 and is approved for the management of moderate-to-severe plaque psoriasis.

Objectives
To evaluate the impact of tildrakizumab treatment on the psychological symptoms experienced by patients with moderate-to-severe plaque psoriasis.

Methods
A 36-week observational study that enrolled patients with psoriasis who initiated treatment with tildrakizumab 100 mg was carried out. The Dermatology Life Quality Index (DLQI) and Skindex-16 questionnaires were administered at baseline and at weeks 12, 24 and 36. Psoriasis Area Severity Index (PASI), body surface area (BSA) involvement (%) and a visual analogue scale for pruritus (p-VAS) were also assessed at baseline and at each follow-up visit.

Results
Thirty-four patients were enrolled. Baseline mean (SD) PASI score and BSA involvement were 28.4 (5.6) and 38.8 (21.4), respectively. The mean (SD) DLQI, Skindex-16 and p-VAS scores at baseline were 26.4 (3.2), 68 (5.8) and 8.2 (SD not available for p-VAS). Clinical improvement was assessed at weeks 12 [PASI: 12.4 (4.2); BSA involvement: 16.5 (7.3)], 24 [PASI: 4.2 (2.8); BSA involvement: 6.1 (3.1)] and 36 [PASI: 3.6 (3.2); BSA involvement: 4.2 (1.37)]. Clinical improvement was accompanied by an improvement in quality of life at weeks 16 [DLQI: 15.5 (2.9); Skindex-16: 28.2 (4.2); p-VAS: 3.8], 24 [DLQI: 8.2 (1.4); Skindex-16: 16.2 (3.6); p-VAS: 2.6] and 36 [DLQI: 3.1 (2.4); Skindex-16: 9.3 (2.8); p-VAS: 2.8]. Our study also confirmed the safety of tildrakizumab in real-life settings, with no treatment discontinuation due to inefficacy or adverse events.

Conclusions
Our results confirm tildrakizumab as an effective treatment option for improving the HRQoL of patients with psoriasis.
A status report on human odorant receptors and their allocated agonists
Authors: Lalis Maxence , Hladiš Matej , Abi Khalil Samar , Deroo Christophe , Marin Christophe , Bensafi Moustafa , Baldovini Nicolas , Briand Loïc , Fiorucci Sébastien , Topin Jérémie 
Published: October 2024

Abstract
Olfactory perception begins when odorous substances interact with specialized receptors located on the surface of dedicated sensory neurons. The recognition of smells depends on a complex mechanism involving a combination of interactions between an odorant and a set of odorant receptors (ORs), where molecules are recognized according to a combinatorial activation code of ORs. Although these interactions have been studied for decades, the rules governing this ligand recognition remain poorly understood, and the complete combinatorial code is only known for a handful of odorants. We have carefully analyzed experimental results regarding the interactions between ORs and molecules to provide a status report on the deorphanization of ORs, i.e. the identification of the first agonist for a given sequence. This meticulous analysis highlights the influence of experimental methodology (cell line or readout) on molecule–receptor association results and shows that 83% of the results are conserved regardless of experimental conditions. The distribution of another key parameter, EC50, indicates that most OR ligand activities are in the micromolar range and that impurities could lead to erroneous conclusions. Focusing on the human ORs, our study shows that 88% of the documented sequences still need to be deorphanized. Finally, we also estimate the size of the ORs’ recognition range, or broadness, as the number of odorants activating a given OR. By analogously estimating molecular broadness and combining the two estimates we propose a basic framework that can serve as a comparison point for future machine learning algorithms predicting OR-molecule activity.
2-D transdimensional joint inversion of radio magnetotelluric and electrical resistivity tomography data
Authors: Singh Arun , Yogeshwar Pritam , Israil Mohammad , Tezkan Bülent 
Published: October 2024

SUMMARY
The joint inversion of radio magnetotelluric and electrical resistivity tomography data has the potential to reduce the uncertainties in the subsurface conductivity model. This is particularly beneficial when the data sets offer complementary information about the subsurface. However, the traditional gradient-based inversion methods pose challenges in quantifying uncertainty, as they yield a single model with limited appraisal of parameter uncertainty. The Bayesian inversion approach stands out for its capacity to provide quantitative assessments of uncertainty in the inverted model parameters. This is accomplished by generating an ensemble of models, leading to a posterior distribution that encapsulates both prior information concerning model parameters and the data set information. We have implemented a transdimensional Markov chain Monte Carlo algorithm to perform the joint inversion of radio magnetotelluric and electrical resistivity tomography data. Through synthetic data studies, we illustrate how the inclusion of two complementary data sets can effectively reduce uncertainties in model parameters and how the model parameter uncertainties can be quantified. Subsequently, the developed algorithm is tested using exemplary field data from a waste site near Roorkee, India. Intensive prior geoelectric and transient electromagnetic as well as radio magnetotelluric studies investigated possible waste water seepage with a potential to contaminate the shallow aquifers. The derived subsurface structure from our transdimensional Bayesian results compare well with the deterministic results for the exemplary profile, but in addition provide comprehensive uncertainty estimates.
How has health literacy and digital health literacy scholarship evolved? A global, qualitative study
Authors: Yelton Brooks , Sakhuja Mayank , Kavarana Simone , Schaurer Lauren , Arent Michelle A , Donelle Lorie , Macauda Mark M , Noblet Samuel , Friedman Daniela B 
Published: October 2024

Abstract
Health literacy (HL) is a key social determinant of health (SDoH) and is of increasing importance in public health research and intervention for improved health outcomes. Definitions of HL and digital health literacy (DHL) have evolved over time as the field has expanded conceptualization from an individual focus to the broader community and organizational levels. Careful consideration of HL and DHL for a variety of contexts and audiences is critical given increased global adoption of digital technologies and responses to emerging public health challenges. This study aimed to capture researchers’ conceptualizations of HL/DHL and their motivations to engage in this research with attention to SDoH and equity principles. We developed a survey comprising 32 open-ended and multiple-choice questions from which we present participant demographics and overall research affiliations (n = 193), and results from two multiple-choice and three open-ended questions. The three open-ended questions were inductively reviewed and coded using thematic analysis and iterative discussions between multiple coders, while the two multiple-choice questions were descriptively analyzed via SPSS. Findings are situated within the context of the coronavirus disease 2019 (COVID-19) pandemic and inform the international field of HL/DHL research by highlighting momentum and opportunities for increased scholarship.
Comparative analysis of personal protective equipment nonadherence detection: computer vision versus human observers
Authors: Kim Mary S , Park Beomseok , Sippel Genevieve J , Mun Aaron H , Yang Wanzhao , McCarthy Kathleen H , Fernandez Emely , Linguraru Marius George , Sarcevic Aleksandra , Marsic Ivan , Burd Randall S 
Published: October 2024

Abstract

Objectives
Human monitoring of personal protective equipment (PPE) adherence among healthcare providers has several limitations, including the need for additional personnel during staff shortages and decreased vigilance during prolonged tasks. To address these challenges, we developed an automated computer vision system for monitoring PPE adherence in healthcare settings. We assessed the system performance against human observers detecting nonadherence in a video surveillance experiment.

Materials and Methods
The automated system was trained to detect 15 classes of eyewear, masks, gloves, and gowns using an object detector and tracker. To assess how the system performs compared to human observers in detecting nonadherence, we designed a video surveillance experiment under 2 conditions: variations in video durations (20, 40, and 60 seconds) and the number of individuals in the videos (3 versus 6). Twelve nurses participated as human observers. Performance was assessed based on the number of detections of nonadherence.

Results
Human observers detected fewer instances of nonadherence than the system (parameter estimate −0.3, 95% CI −0.4 to −0.2, P &lt; .001). Human observers detected more nonadherence during longer video durations (parameter estimate 0.7, 95% CI 0.4-1.0, P &lt; .001). The system achieved a sensitivity of 0.86, specificity of 1, and Matthew’s correlation coefficient of 0.82 for detecting PPE nonadherence.

Discussion
An automated system simultaneously tracks multiple objects and individuals. The system performance is also independent of observation duration, an improvement over human monitoring.

Conclusion
The automated system presents a potential solution for scalable monitoring of hospital-wide infection control practices and improving PPE usage in healthcare settings.
An Integrated Strategy for Establishing the Chemical Profile of Premna Microphylla Turcz. Leaves and Metabolites in Vivo
Authors: Cai Jinhong , Guan Shenghong , Hu Xueli , Chen Xuezhao , Liu Xiaosun , Li Shouxin , Tian Jingkui , Wang Ping , Gu Hua , Zhang Xiaoyong 
Published: October 2024

Abstract

Background
Premna microphylla Turcz. (PMT) is a traditional food and medicinal plant, which has been used to treat cure hemostasis, rheumatism, and dysentery. However, there is still a lack of a clear understanding of the chemical profile of PMT and its metabolites in vivo.

Objective
To establish a rapid and efficient analytical method for the identification of phytochemicals in PMT and their metabolites in vivo.

Methods
First, the fingerprint of PMT was established by HPLC with method validation. Then, the phytochemical composition of PMT leaves was identified using ultra-performance liquid chromatography–quadrupole time-of-flight-tandem mass spectrometry (UPLC–QTOF-MS/MS). Finally, the prototype and correlated metabolites were detected after oral administration in mice to understand the absorption and metabolism of phytochemicals in vivo.

Results
The results showed that the established HPLC method for fingerprint evaluation of PMT has good precision, repeatability, and stability. Additionally, a total of 103 phytochemicals were identified in PMT, including mainly flavonoids and terpenoids. Then, 37 prototype components and 20 derived metabolites in vivo were detected.

Conclusion
In this study, we constructed a fingerprint method, which has good stability, precision, and repeatability, and the fingerprint of PMT was established. Then, the chemical profile of PMT in vitro and in vivo was determined. The results showed that flavonoids and terpenoids were the main phytochemicals in PMT, and methylation, sulfonation, and dihydroxylation were the main metabolic pathway in vivo.

Highlights
The present study provides the phytochemical basis for subsequent study of pharmacological activity.
Long-term Physical and Mental Health Outcomes of Older Adults Following a Major Burn Injury: A Burn Model System Investigation
Authors: Hong Aaron , Stewart Barclay T , Orton Caitlin , Carrougher Gretchen J , Schneider Jeffrey C , Solis-Beach Kyra , Bamer Alyssa , Kowalske Karen , Mandell Samuel 
Published: October 2024

Abstract
Older adults are at a higher risk of complications after burn injuries since many physical and mental changes are compounded by increasing age. Few studies have targeted the long-term effects of burns on older adults. Therefore, this study will investigate the long-term physical and mental health outcomes in older adults. About 3129 participants from the Burn Model System Database were divided into 3 cohorts based on their age at injury (18-54, 55-64, and 65+). Physical Component Summary (PCS) and Mental Component Summary (MCS) scores were derived from the 12-item Short Form (SF-12) and the Veterans RAND 12-item (VR-12) health surveys and analyzed to measure recovery at preinjury, discharge, 2-year follow-up, and 5-year follow-up. ANOVA, T-score analysis, and linear mixed-effects models were utilized to assess for significant differences in outcome scores. PCS scores were significantly different between the 18-54 cohort and 65+ cohorts at the preinjury and 2-year time intervals (P &lt; .001 and P &lt; .001, respectively) but not at the 5-year follow-up (P = .28). MCS scores were significantly different between the 18-54 cohort and 65+ cohorts at all time intervals measured (P = .001, P &lt; .001, P &lt; .001, and P = .005, respectively), though the change in MCS scores over time was not significantly different between age cohorts across time (P = .088). This supports that patients 65 years and older have a different physical function recovery trajectory when compared to patients under 64 years. These findings underscore the belief that for physical recovery after a burn injury, individualized physical rehabilitation plans will provide the most benefit for patients across all ages.
Polarization of the memory B-cell response
Authors: Pérez-Pérez Lizzette , Laidlaw Brian J 
Published: October 2024

Abstract
Memory B cells are long-lived cells that are induced following infection or vaccination. Upon antigen re-encounter, memory B cells rapidly differentiate into antibody-secreting or germinal center B cells. While memory B cells are an important component of long-term protective immunity following vaccination, they also contribute to the progression of diseases such as autoimmunity and allergy. Numerous subsets of memory B cells have been identified in mice and humans that possess important phenotypic and functional differences. Here, we review the transcriptional circuitry governing memory B-cell differentiation and function. We then summarize emerging evidence that the inflammatory environment in which memory B cells develop has an important role in shaping their phenotype and examine the pathways regulating the development of memory B cells during a type 1-skewed and type 2-skewed immune response.
The immune landscape in brain metastasis
Authors: Schreurs Luca D , vom Stein Alexander F , Jünger Stephanie T , Timmer Marco , Noh Ka-Won , Buettner Reinhard , Kashkar Hamid , Neuschmelting Volker , Goldbrunner Roland , Nguyen Phuong-Hien 
Published: October 2024

Abstract
The prognosis for patients with brain metastasis remains dismal despite intensive therapy including surgical resection, radiotherapy, chemo-, targeted, and immunotherapy. Thus, there is a high medical need for new therapeutic options. Recent advances employing high-throughput and spatially resolved single-cell analyses have provided unprecedented insights into the composition and phenotypes of the diverse immune cells in the metastatic brain, revealing a unique immune landscape starkly different from that of primary brain tumors or other metastatic sites. This review summarizes the current evidence on the composition and phenotypes of the most prominent immune cells in the brain metastatic niche, along with their dynamic interactions with metastatic tumor cells and each other. As the most abundant immune cell types in this niche, we explore in detail the phenotypic heterogeneity and functional plasticity of tumor-associated macrophages, including both resident microglia and monocyte-derived macrophages, as well as the T-cell compartment. We also review preclinical and clinical trials evaluating the therapeutic potential of targeting the immune microenvironment in brain metastasis. Given the substantial evidence highlighting a significant role of the immune microenvironmental niche in brain metastasis pathogenesis, a comprehensive understanding of the key molecular and cellular factors within this niche holds great promise for developing novel therapeutic approaches as well as innovative combinatory treatment strategies for brain metastasis.
The Role of the Gut Microbiome in the Development and Progression of Type 2 Diabetes and Liver Disease
Authors: Guraka Asha , Sreedharan Sreejesh , Arasaradnam Ramesh , Tripathi Gyan , Kermanizadeh Ali 
Published: October 2024

Abstract
Type 2 diabetes mellitus (T2DM) and progressive liver disease are 2 of the most significant global health concerns, and they have alarming and ever-increasing prevalence. A growing body of literature has demonstrated a potential multilateral link between gut microbiome dysbiosis and the development and progression of the above-mentioned conditions. Modulation of gut microbial composition from the norm is due to changes in diet allied with external factors such as age, genetics, and environmental changes. In this comprehensive review, we recapitulate the research to date investigating the links between gut microbiome dysbiosis and T2DM or liver disease, with special attention to the importance of diet. Additionally, we review the most commonly used tools and methodologies of investigating changes in the gut microbiome, highlighting the advantages and limitations of each strategy, before introducing a novel in vitro approach to the problem. Finally, the review offers recommendations for future research in this field that will allow better understanding of how the gut microbiota affects disease progression and of the prospects for intestinal microbiota-based therapeutic options.
Emerging innovative treatment strategies for advanced clear cell renal cell carcinoma
Authors: Choi Sharon H , Chen Yu-Wei , Panian Justine , Yuen Kit , McKay Rana R 
Published: October 2024

Abstract
Dramatic advances in biological discoveries, since the 1990s, have continued to reshape the treatment paradigm of metastatic renal cell carcinoma (RCC). Von Hippel Lindau (VHL) gene alterations are associated with pro-angiogenic activity and are central to the pathogenesis of clear cell RCC (ccRCC), the most predominant histologic subtype of RCC. Antiangiogenic strategies revolving around this VHL/HIF/VEGF axis have been shown to improve survival in metastatic ccRCC. The discovery of immune checkpoints and agents that target their inhibition introduced a new treatment paradigm for patients with RCC. While initially approved as monotherapy, studies investigating immune checkpoint inhibitor combinations have led to their approval as the new standard of care, providing durable responses and unprecedented improvements in clinical outcome. Despite these advances, the projected 14 390 deaths in 2024 from RCC underscore the need to continue efforts in expanding and optimizing treatment options for patients with metastatic RCC. This article reviews key findings that have transformed the way we understand and treat metastatic RCC, in addition to highlighting novel treatment strategies that are currently under development.
An evaluation of the efficacy and side effects of a single dose of ketamine in major depressive disorder
Authors: Uyar Betül , Güneş Mehmet 
Published: October 2024

Abstract

Aim
This study aims to provide a comprehensive overview of the antidepressant and antisuicidal efficacy of ketamine in patients with unipolar depression, with a focus on the clinical evidence and safety profile.

Material-Method
In our study, the data of 120 major depressive disorder patients who received single-dose ketamine infusion therapy were evaluated retrospectively, with Montgomery-Asberg Depression Rating Scale (MADRS) applied by the clinician before treatment and at the 4th and 24th hours after treatment and side effects at 4 and 24 hours after treatment.

Results
There was a statistically significant difference between MADRS and MADRS-Suicide scores of all participants before the ketamine infusion (0th hour) and at the 4th and 24th hours after the ketamine infusion. Also, male and female, RAT(+) and RAT(−), and SA(+) and SA(−) participants have statistically significant differences on all three times for both MADRS and MADRS-S scores.

Conclusion
The findings of this study are in line with those from previous research that demonstrated the rapid and robust antidepressant effects of ketamine, even in individuals with severe, treatment-resistant depression. Moreover, the observed reduction in suicidal ideation is particularly noteworthy, given the critical need for interventions that can provide rapid relief in acute suicidal crises.
Key message What is already known on this topic – Ketamine is known for its rapid antidepressant and antisuicidal effects in treatment-resistant major depressive disorder, demonstrating significant symptom relief within hours of administration. What this study adds – This study provides additional evidence supporting ketamine’s rapid efficacy in reducing depressive symptoms and suicidal ideation, highlighting statistically significant improvements observed at 4 and 24 hours post-treatment. How this study might affect research, practice, or policy – The findings may encourage broader clinical adoption of ketamine for acute depressive episodes and suicidality, emphasizing the need for controlled medical settings to manage potential side effects, and could influence future research on optimizing dosing protocols and long-term safety.
Exploration of Sleep Health and Behaviors Among Undergraduate Nursing Students
Authors: McGuire Kelley , Andrews Angela , Bogle Melissa , Carril Adrienne 
Published: October 2024

Abstract
Nursing students experience inadequate sleep because of academic demands, with detrimental effects on academic performance. Objective and subjective data informed students’ sleep patterns. Actigraphy data revealed that students (n = 46) slept for 392 minutes per night. Among the 38 participants who completed actigraphy and demographic and survey data, Pearson correlation testing revealed significant relationships between self-efficacy and perceived stress (r = −.604, p = .001), as well as average sleep time (r = −.371, p = .022). Qualitative data revealed the impact sleep has on physical and mental well-being. Individual and environmental influences resulted in students achieving insufficient sleep.