bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of decision support to wean patients from mechanical ventilation in intensive care: a prospective study reporting clinical and physiological outcomes
Authors: Vizcaychipi Marcela P. , Karbing Dan S. , Martins Laura , Gupta Amandeep , Moreno-Cuesta Jeronimo , Naik Manu , Welters Ingeborg , Singh Suveer , Randell Georgina , Osman Leyla , Rees Stephen E. 
Published: November 2024

AbstractThis study investigated the clinical and physiological response to use of the BEACON Caresystem, a bedside open-loop decision support system providing advice to guide clinicians when weaning patients from invasive mechanical ventilation. Multicenter prospective study conducted in five adult intensive care units in the UK. Following screening and assent, intubated patients mechanically ventilated for > 24 h were randomized to intervention or usual care. Intervention consisted of application of the BEACON Caresystem’s advice on tidal volume/inspiratory pressure, inspired oxygen, respiratory rate and PEEP. Usual care was defined as local clinical practice. The primary outcome was duration of mechanical ventilation. Secondary outcomes quantified prolonged intubation and survival; adverse events; ventilator settings and physiological state; time spent in ventilator modes; links to other therapy; the frequency of advice utilization and time spent outside normal physiological limits. The study was terminated early with a total of 112 patients included. Fifty-four were randomised to the intervention arm and fifty-eight to usual care. The study was underpowered and no significant differences were seen in duration of mechanical ventilation (p = 0.773), prolonged intubation or survival. Intervention arm patients had lower rates of adverse events (p = 0.016), including fewer hypoxaemic events (p = 0.008) and lower values of PEEP (p = 0.030) and tidal volume (p = 0.042). Values of peak inspiratory pressure and pressure support were reduced but at the boarder of statistical significance (p = 0.104, p = 0.093, respectively). No differences were seen for time in ventilator mode or other therapy. Advice presented by the decision support system was applied at the beside an average of 88% of occasions, with a significantly increased number of changes only in inspired oxygen fraction. No significant differences were seen in time spent outside physiological limits. This study investigated the use of the BEACON Caresystem, an open loop clinical decision support system providing advice on ventilator settings. It was terminated early, with no significant difference shown in duration of mechanical ventilation, the primary outcome. Application of advice indicated potential for fewer adverse events and improved physiological status. (Trial registration ClinicalTrials.gov under NCT03249623. Registered 22nd June 2017)
PASE: Pro-active Service Embedding in The Mobile Edge
Authors: Kolosov Oleg , Yadgar Gala , Breitgand David , Lorenz Dean H. 
Published: November 2024

Abstract
Mobile edge computing offers ultra-low latency, high bandwidth, and high reliability. Thus, it can support a plethora of emerging services that can be placed in close proximity to the user. One of the fundamental problems in this context is maximizing the benefit from the placement of networked services, while meeting bandwidth and latency constraints. In this study, we propose an adaptive and predictive resource allocation strategy for virtual-network function placement comprising services at the mobile edge. Our study focuses on maximizing the service provider’s benefit under user mobility, i.e., uncertainty. This problem is NP-hard. Therefore, we propose a heuristic solution: we exploit local knowledge about the likely movements of users to speculatively allocate service functions. We allow the service functions to be allocated at different edge nodes, as long as latency and bandwidth constraints are met. We evaluate our proposal against a theoretically optimal algorithm as well as against recent previous work, using widely used simulation tools. Through an extensive simulation study, we demonstrate that under realistic scenarios, an adaptive and proactive strategy coupled with flexible placement can achieve close-to-optimal benefit.
Design, synthesis, and anti-breast cancer activity evaluation of novel 3-cyanopyridine derivatives as PIM-1 inhibitors
Authors: Hussein Bahgat R. M. , Mohammed Hayam H. , Ahmed Eman A. , Alshazly Omar , Mohamed Mamdouh F. A. , Omran Omran A. 
Published: November 2024

AbstractA novel series of cyanopyridines 7a-j were synthesized via a one-pot multicomponent reaction of arylidene 4 with ammonium acetate 5 and respective methylaryl/heterylketones 6a-j in ethanol using vanillin as a natural starting material. Moreover, the regioselective alkylation reaction was studied by the treatment of cyanopyridines 7a-f and 7j with CH3I in the presence of K2CO3 in DMF to afford O-methylcyanopyridines 8a-g (major) and N-methylcyanopyridines 9a-g (minor), whereas bipyridine 7h gave bipyridinium iodide salt 10. All of the designed cyanopyridines were evaluated as anti-breast cancer (MCF-7) cell lines via PIM Kinase inhibitory activity, and the results displayed that some of them showed high activities, especially compounds 7h and 8f, which showed excellent activities against MCF-7 with IC50 values of 1.89 and 1.69 μM, respectively, more potent than the reference drug doxorubicin. Mechanistically, compounds 7h and 8f exhibited strong in vitro PIM-1 kinase inhibitory activity with an IC50 of 0.281 and 0.58 μM, respectively, compared to the reference staurosporine. Moreover, compound 7h arrested the tumor cells at the S phase and caused cell death mainly by inducing early and late apoptosis. Molecular docking studies against PIM-1 revealed good binding modes of the synthesized compound and showed agreement with the biological results.
Graphical abstract
Beyond Preferences in AI Alignment
Authors: Zhi-Xuan Tan , Carroll Micah , Franklin Matija , Ashton Hal 
Published: November 2024

AbstractThe dominant practice of AI alignment assumes (1) that preferences are an adequate representation of human values, (2) that human rationality can be understood in terms of maximizing the satisfaction of preferences, and (3) that AI systems should be aligned with the preferences of one or more humans to ensure that they behave safely and in accordance with our values. Whether implicitly followed or explicitly endorsed, these commitments constitute what we term apreferentistapproach to AI alignment. In this paper, we characterize and challenge the preferentist approach, describing conceptual and technical alternatives that are ripe for further research. We first survey the limits of rational choice theory as a descriptive model, explaining how preferences fail to capture the thick semantic content of human values, and how utility representations neglect the possible incommensurability of those values. We then critique the normativity of expected utility theory (EUT) for humans and AI, drawing upon arguments showing how rational agents need not comply with EUT, while highlighting how EUT is silent on which preferences are normatively acceptable. Finally, we argue that these limitations motivate a reframing of the targets of AI alignment: Instead of alignment with the preferences of a human user, developer, or humanity-writ-large, AI systems should be aligned with normative standards appropriate to their social roles, such as the role of a general-purpose assistant. Furthermore, these standards should be negotiated and agreed upon by all relevant stakeholders. On this alternative conception of alignment, a multiplicity of AI systems will be able to serve diverse ends, aligned with normative standards that promote mutual benefit and limit harm despite our plural and divergent values.
Development of a prediction model for clinically-relevant fatigue: a multi-cancer approach
Authors: Adiprakoso Dhirendra , Katsimpokis Dimitris , Oerlemans Simone , Ezendam Nicole P. M. , van Maaren Marissa C. , van Til Janine A. , van der Heijden Thijs G. W. , Mols Floortje , Aben Katja K. H. , Vink Geraldine R. , Koopman Miriam , van de Poll-Franse Lonneke V. , de Rooij Belle H. 
Published: November 2024

Abstract

Purpose
Fatigue is the most prevalent symptom across cancer types. To support clinicians in providing fatigue-related supportive care, this study aims to develop and compare models predicting clinically relevant fatigue (CRF) occurring between two and three years after diagnosis, and to assess the validity of the best-performing model across diverse cancer populations.

Methods
Patients with non-metastatic bladder, colorectal, endometrial, ovarian, or prostate cancer who completed a questionnaire within three months after diagnosis and a subsequent questionnaire between two and three years thereafter, were included. Predictor variables included clinical, socio-demographic, and patient-reported variables. The outcome was CRF (EORTC QLQC30 fatigue ≥ 39). Logistic regression using LASSO selection was compared to more advanced Machine Learning (ML) based models, including Extreme gradient boosting (XGBoost), support vector machines (SVM), and artificial neural networks (ANN). Internal–external cross-validation was conducted on the best-performing model.

Results
3160 patients were included. The logistic regression model had the highest C-statistic (0.77) and balanced accuracy (0.65), both indicating good discrimination between patients with and without CRF. However, sensitivity was low across all models (0.22–0.37). Following internal–external validation, performance across cancer types was consistent (C-statistics 0.73–0.82).

Conclusion
Although the models’ discrimination was good, the low balanced accuracy and poor calibration in the presence of CRF indicates a relatively high likelihood of underdiagnosis of future CRF. Yet, the clinical applicability of the model remains uncertain. The logistic regression performed better than the ML-based models and was robust across cohorts, suggesting an advantage of simpler models to predict CRF.
Centenarians of the Basque Country are resilient to cancer
Authors: Cruces-Salguero Sara , Larrañaga Igor , Mar Javier , Matheu Ander 
Published: November 2024

AbstractCancer is one of the leading causes of death and its prevalence increases with age. While centenarians exhibit extreme longevity and potential to avoid or delay aging-related diseases, their response to cancer is still barely explored. Our study took advantage of the Electronic Health Records to retrospectively compare the severity of cancer in centenarians (n = 649) and non-centenarians (n = 62,753) in the Basque Country (province of Gipuzkoa), Spain, through analyzing all the recorded diagnoses throughout their lifetime. Descriptive statistics were applied to discern differences between the two population groups in terms of prevalence of tumor types, number of diagnoses, and treatments. Survival analysis was performed through Kaplan–Meier estimator. We found that centenarians had fewer cancer diagnoses (17.1%, n = 111) than non-centenarians (40.5%, n = 25,405), and notably avoided the most aggressive cancer types and did not develop metastasis. Furthermore, they barely had records of treatments or drugs and had extended survival both since the first and last diagnosis of cancer. These results suggest resilience of the centenarians against malignant cancers explaining, in part, their extended longevity.
MINARO DRS: usability study of a robotic-assisted laminectomy
Authors: Vossel Manuel , Theisgen Lukas , Wickel Noah , Phlippen Lovis , Pjontek Rastislav , Drobinsky Sergey , Clusmann Hans , Radermacher Klaus , Blume Christian , de la Fuente Matías 
Published: November 2024

Abstract

Purpose
Although the literature shows that robotic assistance can support the surgeon, robotic systems are not widely spread in clinics. They often incorporate large robotic arms adopted from the manufacturing industry, imposing safety hazards when in contact with the patient or surgical staff. We approached this limitation with a modular dual robot consisting of an ultra-lightweight carrier robot for rough prepositioning and small, highly dynamic, application-specific, interchangeable tooling robots.

Methods
A formative usability study with N = 10 neurosurgeons was conducted using a prototype of a novel tooling robot for laminectomy to evaluate the system’s usability. The participants were asked to perform three experiments using the robotic system: (1) prepositioning with the carrier robot and milling into (2) a block phantom as well as (3) a spine model.

Results
All neurosurgeons could perform a simulated laminectomy on a spine phantom using the robotic system. On average, they rated the usability of this first prototype already between good and excellent (SUS-Score above 75%). Eight out of the ten participants preferred robotic-assisted milling over manual milling. For prepositioning, the developed haptic guidance showed significantly higher effectiveness and efficiency than visual navigation.

Conclusion
The proposed dual robot system showed the potential to increase safety in the operating room because of the synergistic hands-on control and the ultra-lightweight design of the carrier robot. The modular design allows for easy adaptation to various surgical procedures. However, improvements are needed in the ergonomics of the tooling robot and the complexity of the virtual fixtures. The cooperative dual robot system can subsequently be tested in a cadaver laboratory and in vivo on animals.
Prediction of cardiovascular events after carotid endarterectomy using pathological images and clinical data
Authors: Ishida Shuya , Morita Kento , Hatakeyama Kinta , Ren Nice , Watanabe Shogo , Kobashi Syoji , Iihara Koji , Wakabayashi Tetsushi 
Published: November 2024

Abstract
Purpose
Carotid endarterectomy (CEA) is a surgical treatment for carotid artery stenosis. After CEA, some patients experience cardiovascular events (myocardial infarction, stroke, etc.); however, the prognostic factor has yet to be revealed. Therefore, this study explores the predictive factors in pathological images and predicts cardiovascular events within one year after CEA using pathological images of carotid plaques and patients’ clinical data.

Method
This paper proposes a two-step method to predict the prognosis of CEA patients. The proposed method first computes the pathological risk score using an anomaly detection model trained using pathological images of patients without cardiovascular events. By concatenating the obtained image-based risk score with a patient’s clinical data, a statistical machine learning-based classifier predicts the patient’s prognosis.

Results
We evaluate the proposed method on a dataset containing 120 patients without cardiovascular events and 21 patients with events. The combination of autoencoder as the anomaly detection model and XGBoost as the classification model obtained the best results: area under the receiver operating characteristic curve, accuracy, sensitivity, specificity, and F1-score were 81.9%, 84.1%, 79.1%, 86.3%, and 76.6%, respectively. These values were superior to those obtained using pathological images or clinical data alone.

Conclusion
We showed the feasibility of predicting CEA patient’s long-term prognosis using pathological images and clinical data. Our results revealed some histopathological features related to cardiovascular events: plaque hemorrhage (thrombus), lymphocytic infiltration, and hemosiderin deposition, which will contribute to developing preventive treatment methods for plaque development and progression.
Observing sustainability through the mindfulness lens: a conceptual framework based on a bibliometric review analysis
Authors: Barbir Jelena , Baars Caterina , Eustachio João H. P. P. , Sharifi Ayyoob , Demarzo Marcelo , Filho Walter Leal 
Published: November 2024

Abstract
To shift human behaviour towards sustainability, a complete comprehension of the approaches that lead to it is required. This study aims to review potential connections between the mindfulness state and trait and changes in human behaviour toward sustainability. Using bibliometric analysis as an innovative approach in this field, combined with an expert-driven literature review, the research builds on previous works regarding sustainability and mindfulness and fosters the research field by exploring six thematic clusters, each containing a set of specific mediators that could bridge this connection. To illustrate the relationship between mindfulness and sustainable development, a framework was developed, illustrating how mindfulness-based skills could positively influence these mediators and which dimensions of sustainable development could be further impacted by it. Moreover, a mindfulness program focused on sustainability and planetary health may be an innovative way to develop competencies related to the variables identified as mediators.
Do Statins Affect Cognitive Health? A Narrative Review and Critical Analysis of the Evidence
Authors: Kazibwe Richard , Rikhi Rishi , Mirzai Saeid , Ashburn Nicklaus P. , Schaich Christopher L. , Shapiro Michael 
Published: November 2024

Abstract
Purpose of Review
Statins are the first-line treatment for hypercholesterolemia and play a key role in the prevention of cardiovascular disease (CVD). Current studies report mixed effects of statins on cognitive health, including harmful, neutral, and protective outcomes. However, these ongoing controversies about the potential cognitive adverse effects of statins may compromise their use in CVD prevention. Several factors may influence how statins affect cognition, including the unique cholesterol homeostasis in the brain, the limited permeability of the blood-brain barrier to lipoproteins, and the varying lipophilicity of different statins. This review examines the evidence linking statins to cognitive function and considers the effect of different dosages and treatment durations.

Recent Findings
Earlier studies suggested cognitive disturbances with statins, but recent evidence does not strongly support a link between statins and cognitive impairment. In fact, observational studies suggest potential neuroprotective benefits, though biases like selection bias, confounding and reverse causation limit definitive conclusions. Two large randomized controlled trials, STAREE and PREVENTABLE, are underway, and their results are expected to address some of these gaps in the literature.

Summary
Due to insufficient evidence in the current literature, well-designed randomized controlled trials are needed for a better understanding of statins’ effects on cognition. More data is needed regarding statin type, dose intensity, and treatment duration, which may affect cognitive outcomes. Future studies are also needed to examine how statins may affect cognition in specific high-risk groups, such as individuals with mild cognitive impairment, diabetes, cardiovascular disease, or chronic kidney disease.
Burnout and Post-traumatic Stress Disorders in Police Officers: Systematic Review and Meta-analysis
Authors: Ugwu Lawrence E. , Idemudia Erhabor Sunday 
Published: November 2024

AbstractThe occupational environment of law enforcement officers, characterised by high-stress situations and critical societal roles, necessitates continuous monitoring of their mental health. This systematic review and meta-analysis aims to explore the associations and impacts of burnout and PTSD among police officers, shedding light on how these conditions are influenced by evolving job demands and societal expectations. Adhering to PRISMA guidelines, we searched four databases PubMed, PsycINFO, and CINAHL from January 2000 to January 2024. Studies involving active-duty police officers that assessed burnout and PTSD using validated tools were included. A risk of bias was assessed using an eight-criteria scale, focusing on methodological strengths and weaknesses across studies. We analysed data from 10 studies comprising 4572 officers worldwide. The results indicated variable relationships between burnout, PTSD, and their impacts on occupational functioning, with significant heterogeneity across studies (I2 > 75%). Despite the variability, there was a consistent trend showing that occupational stressors are linked to both burnout and PTSD, suggesting a pervasive influence of job-related demands on officer mental health. The findings reveal a complex interaction between burnout and PTSD in police officers, influenced by both individual and occupational factors. This interplay highlights the need for interventions that are sensitive to cultural and contextual nuances of policing. Future strategies should prioritise individual, organisational, and societal dimensions to reduce the psychological burden and enhance resilience among officers.
Multi-scale inhomogeneity and anomalous mechanical response of nanoscale metallic glass pillar by cryogenic thermal cycling
Authors: Liu Xiao , Di Si-Yi , Zhou Jing , Miao Fang , Wang Hong-Ze , Wu Yi , Wang Hao-Wei , Ke Hai-Bo , Li Qiang 
Published: November 2024

The mechanical responses and structure variations of Ta80Co20 nanoscale metallic glass (MG) film samples upon cryogenic thermal cycling (CTC) treatment were studied. The simultaneous improvements of strength and deformation ability bring about a super-high strength of 4.5 GPa and a large plastic strain of about 80% after CTC treatment. The significant increase in inter-element bonding and hardness makes the activation and percolation of shear transformation zones to be more difficult and delays the yielding event, leading to the ultra-high strength. Although the TaCo MG pillar reaches a relaxation energy state, the micro- and nanoscale inhomogeneities remain induced by the local densely packed units along with crystal-like ordering embedded in the matrix. The multi-scale inhomogeneity can effectively hinder the sliding of the shear bands and improve their propagation stability, which is considered to be the origin of its excellent plasticity. Our study reveals another prospect of CTC treatment on nanoscale MG samples of constructing an anomalous inhomogeneous structure and obtaining simultaneous enhancement of strength and plasticity.
Graphical abstract
Synthetic Media Detection, the Wheel, and the Burden of Proof
Authors: Harris Keith Raymond 
Published: November 2024

AbstractDeepfakes and other forms of synthetic media are widely regarded as serious threats to our knowledge of the world. Various technological responses to these threats have been proposed. The reactive approach proposes to use artificial intelligence to identify synthetic media. The proactive approach proposes to use blockchain and related technologies to create immutable records of verified media content. I argue that both approaches, but especially the reactive approach, are vulnerable to a problem analogous to the ancient problem of the criterion—a line of argument with skeptical implications. I argue that, while the proactive approach is relatively resistant to this objection, it faces its own serious challenges. In short, the proactive approach would place a heavy burden on users to verify their own content, a burden that is exacerbated by and is likely to exacerbate existing inequalities.