bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interhospital variability of risk-adjusted mortality rates and associated structural factors in patients undergoing emergency laparotomy: England and Wales population-level analysis
Authors: Darbyshire Alexander R. , Mercer Stuart J. , Arora Sonal , Pucher Philip H. 
Published: September 2024

BACKGROUND
Emergency surgical admissions represent the majority of general surgical workload. Interhospital variations in outcomes are well recognized. This analysis of a national laparotomy data set compared the best- and worst-performing hospitals according to 30-day mortality and examined differences in process and structural factors.

METHODS
A retrospective multicenter cohort study was performed using data from the England and Wales National Emergency Laparotomy Audit (December 2013 to November 2020). The data set was divided into quintiles based on the risk-adjusted mortality calculated using the National Emergency Laparotomy Audit score risk prediction model. Primary outcome was 30-day mortality. Hospital-level factors were compared across all five quintiles, and logistic regression analysis was conducted comparing the lowest with the highest risk-adjusted mortality quintiles.

RESULTS
Risk-adjusted 30-day mortality in the poorest performing quintile was significantly higher than that of the best performing (11.4% vs. 6.6%) despite equivalent predicted mortality (9.4% vs. 9.7%). The best-performing quintile was more likely to be a tertiary surgical (49.5% vs. 37.1%, p < 0.001) or medical school-affiliated center (26.4% vs. 18.0%, p < 0.001). In logistic regression analysis, the strongest associations were for surgery performed in a tertiary center (odds ratio, 0.690 [95% confidence interval, 0.652–0.731], p < 0.001) and if surgery was performed by a gastrointestinal specialist (0.655 [0.626–0.685], p < 0.001). Smaller differences were seen for postoperative intensive care stay (0.848 [0.808–0.890], p < 0.001) and consultant anesthetist involvement (0.900 [0.837–0.967], p = 0.004).

DISCUSSION
This study has identified significant variability in postoperative mortality across hospitals. Structural factors such as gastrointestinal specialist delivered emergency laparotomy and tertiary surgical center status appear to be associated with improved outcomes.

LEVEL OF EVIDENCE
Prognostic and Epidemiological; Level III.
A machine learning–based Coagulation Risk Index predicts acute traumatic coagulopathy in bleeding trauma patients
Authors: Richards Justin E. , Yang Shiming , Kozar Rosemary A. , Scalea Thomas M. , Hu Peter 
Published: September 2024

BACKGROUND
Acute traumatic coagulopathy (ATC) is a well-described phenomenon known to begin shortly after injury. This has profound implications for resuscitation from hemorrhagic shock, as ATC is associated with increased risk for massive transfusion (MT) and mortality. We describe a large-data machine learning–based Coagulation Risk Index (CRI) to test the early prediction of ATC in bleeding trauma patients.

METHODS
Coagulation Risk Index was developed using continuous vital signs (VSs) available during the first 15 minutes after admission at a single trauma center over 4 years. Data to compute the CRI were derived from continuous features of photoplethymographic and electrocardiographic waveforms, oximetry values, and blood pressure trends. Two groups of patients at risk for ATC were evaluated: critical administration threshold and patients who received an MT. Acute traumatic coagulopathy was evaluated in separate models and defined as an international normalized ratio (INR) >1.2 and >1.5 upon arrival. The CRI was developed using 2 years of cases for training and 2 years for testing. The accuracy of the models is described by area under the receiver operator curve with 95% confidence intervals.

RESULTS
A total of 17,567 patients were available for analysis with continuous VS data, 52.8% sustained blunt injury, 30.2% were female, and the mean age was 44.6 years. The ability of CRI to predict ATC in critical administration threshold patients was excellent. The true positive and true negative rates were 95.6% and 88.3%, and 94.9% and 89.2% for INR >1.2 and INR >1.5, respectively. The CRI also demonstrated excellent accuracy in patients receiving MT; true positive and true negative rates were 92.8% and 91.3%, and 100% and 88.1% for INR >1.2 and INR >1.5, respectively.

CONCLUSION
Using continuous VSs and large-data machine learning capabilities, the CRI accurately predicts early ATC in bleeding patients. Clinical application may guide early hemostatic resuscitation. Extension of this technology into the prehospital setting could provide earlier treatment of ATC.

LEVEL OF EVIDENCE
Retrospective, Prognostic Study; Level III.
Brainwaves Monitoring via Human Midbrain Organoids Microphysiological Analysis Platform: MAP
Authors: Hong SoonGweon , Song Minsun , Yang Woo Sub , Park In-Hyun , Lee Luke P. 
Published: September 2024

ABSTRACTUnderstanding the development and pathogenesis of the human midbrain is critical for developing diagnostics and therapeutics for incurable neurological disorders including Parkinson’s disease (PD)1–3. While organoid models are introduced to delineate midbrain-related pathogenesis based on experimental flexibility4–6, there is currently a lack of tools with high fidelity for tracing the long-term dynamics of intact brain networks— an essential portrait of physiological states7,8. Here, we report a brain organoid microphysiological analysis platform (MAP) designed for long-term physiological development and in-situ real-time monitoring, akin to electroencephalogram (EEG), of midbrain organoids. We successfully achieved the on-chip homogeneous organogenesis of midbrain organoids and in-situ, non-disturbing electrophysiological tracking of the midbrain network activities. Throughout our long-term EEG monitoring via MAP, we captured the early-stage electrophysiological evolution of midbrain development, transitioning from discontinuous brief brainwave bursts to complex broadband activities. Furthermore, our midbrain organoid MAP facilitated the modeling and monitoring of neurotoxin-induced Parkinsonism, replicating the pathological dynamics of midbrain circuitry and exhibiting PD-like alterations in beta oscillation. We envision that the modeling and monitoring of brain organoid MAP will significantly enhance our understanding of human neurophysiology, neuropathogenesis, and drug discovery of neurodegenerative diseases.
Targeted single cell expression profiling identifies integrators of sleep and metabolic state
Authors: Shih Meng-Fu Maxwell , Zhang Jiwei , Brown Elizabeth B. , Dubnau Joshua , Keene Alex C. 
Published: September 2024

AbstractAnimals modulate sleep in accordance with their internal and external environments. Metabolic cues are particularly potent regulators of sleep, allowing animals to alter their sleep timing and amount depending on food availability and foraging duration. The fruit fly,Drosophila melanogaster, suppresses sleep in response to acute food deprivation, presumably to forage for food. This process is dependent on a single pair of Lateral Horn Leucokinin (LHLK) neurons, that secrete the neuropeptide Leucokinin. These neurons signal to insulin producing cells and suppress sleep under periods of starvation. The identification of individual neurons that modulate sleep-metabolism interactions provides the opportunity to examine the cellular changes associated with sleep modulation. Here, we use single-cell sequencing of LHLK neurons to examine the transcriptional responses to starvation. We validate that a Patch-seq approach selectively isolates RNA from individual LHLK neurons. Single-cell CEL-Seq comparisons of LHLK neurons between fed and 24-hr starved flies identified 24 genes that are differentially expressed in accordance with starvation state. In total, 12 upregulated genes and 12 downregulated genes were identified. Gene-ontology analysis showed an enrichment forAttacins, a family of anti-microbial peptides, along with several transcripts with diverse roles in regulating cellular function. Targeted knockdown of differentially expressed genes identified multiple genes that function within LHLK neurons to regulate sleep-metabolism interactions. Functionally validated genes include an essential role for the E3 ubiquitin Ligaseinsomniac,the sorbitol dehydrogenaseSodh1,as well asAttacinCandAttacinBin starvation-induced sleep suppression. Taken together, these findings provide a pipeline for identifying novel regulators of sleep-metabolism interactions within individual neurons.
Evaluating the Effects of Aircraft Noise on Hearing and Physiological Indicators: A Study of Military Personnel Using iTRAQ Proteomics and Cognitive Assessments
Authors: Shukla Manish , Patel Jai Chand , Nayak Devasharma , Shukla Meenakshi , Chakravarti Shutanu , Kapoor Neeru 
Published: September 2024

BackgroundNoise pollution poses a significant public health risk, with prolonged exposure to high levels of noise linked to various adverse outcomes such as annoyance, sleep disturbances, cognitive impairment, hypertension, and cardiovascular diseases. Noise-induced hearing loss (NIHL) is a prominent concern in noisy occupational settings.MethodThis study investigated NIHL among 621 male Air Force soldiers aged 18-45, exposed to intense aircraft noise. Auditory assessments included pure-tone audiometry (125 Hz to 8 kHz) to categorize hearing into normal, mild, moderate, and severe impairment. Distortion product otoacoustic emissions (DPOAE) and auditory brainstem response (ABR) were used to evaluate cochlear and auditory nerve function. Heart rate variability (HRV) provided insights into autonomic responses. Cognitive functions were assessed through computerized tests, and blood plasma was analyzed for cardiac biomarkers, oxidative stress indicators, inflammatory markers, and neurotransmitters. Proteomic analysis used iTRAQ labeling, MudPIT, and MALDI-TOF/TOF mass spectrometry for protein quantification and identification, with validation through ELISA.ResultsThe audiometric tests revealed varying degrees of hearing impairment, with significant threshold differences at 2000, 3000, 4000, and 6000 Hz, especially pronounced at 6000 Hz. The right ear showed greater impairment, and a characteristic high-frequency notch was observed, consistent with noise exposure. Proteomic analysis indicated that NIHL is associated with oxidative stress and systemic inflammation, with differential protein expression related to hearing, coagulation, and inflammation.ConclusionThis study highlights the severe impact of aircraft noise on hearing and systemic health, demonstrating correlations between hearing impairment and biochemical markers. It emphasizes the role of oxidative stress and inflammation in NIHL development and underscores the need for effective noise management and protective measures in noisy work environments.
Reporting and justification of sample size in translational chronic variable stress procedures: A systematic review
Authors: Jordan Crispin , Romanò Nicola , Menzies John 
Published: September 2024

AbstractAllin vivostudies using laboratory animals should be guided by the Three Rs: Replacement, Reduction and Refinement. The concept of Reduction is important in sample size estimation; the sample size used should allow the detection of a biologically meaningful effect size using appropriate statistical tests, but not at the expense of animal suffering. Because studies using chronic variable stress (CVS) procedures deliberately impose suffering, we reasoned that Three Rs principles would be a strong consideration in experimental design. To explore this, we conducted a systematic review of CVS studies to ask whether a biologically meaningful effect size was used to determine the sample size. Only one article in our sample of 385 reported doing this. Accordingly, it is questionable whether most of these studies align strongly with the principle of Reduction. While determining a biologically meaningful effect size is not always straightforward, we believe it is central to making biologically informed decisions about study design and interpretation, and we discuss possible ways forward.
Examination of Lipid Distributions in Hydrogel-Expanded Mouse Brain Tissue Using Imaging Mass Spectrometry
Authors: Samuel Jacob M. , Yan Tingting , Liang Zhongling , Prentice Boone M. 
Published: September 2024

ABSTRACTImaging is an essential tool in biological research, and imaging mass spectrometry uniquely provides a label-free approach with high molecular specificity. However, imaging mass spectrometry is limited in spatial resolution, which in turn limits the biological structures and processes that can be studied at small dimensions. Custom lens setups and altered optical paths have been used to shrink the diameter of the incident laser beam probe in matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry to achieve high spatial resolutions (< 5 μm). However, these research-grade instruments are complex and expensive, making high spatial resolution imaging experiments unrealistic for the broader community. An alternative method for improving spatial resolution is through physical magnification of the substrate, which has been well established in the subfield of expansion microscopy (ExM). ExM leverages superabsorbent hydrogels for isotropic expansion of tissues and retention of analytes containing fluorescent tags. While typical ExM involves covalently anchoring the analyte of interest to the hydrogel network, lipid retention without anchoring has been recently demonstrated for imaging mass spectrometry. Herein, we demonstrate expansion imaging mass spectrometry (ExIMS) of expanded, whole brain tissue and examine lipid distributions in both positive and negative ion mode across multiple brain structures. A linear expansion factor of 4.5-fold is achieved and used to obtain high spatial resolution images of mouse brain cerebellum. Approximately 95% of lipids in both positive and negative ion mode are retained in expanded tissue compared to unexpanded tissue. Additionally, the majority of lipid distributions across the brain are maintained post-expansion. Alterations to the hydrogel formulation (e.g., crosslinker density) can significantly affect the ability of ExIMS to maintain accurate lipid distributions in expanded tissue.
Designing
TaC
Virtual Substrates for Vertical
AlxGa1−xN
Power Electronics Devices
Authors: Roberts Dennice M. , Hachtel Jordan A. , Haegel Nancy M. , Miller Moira K. , Rice Anthony D. , Tellekamp M. Brooks 
Published: September 2024

Power electronics are critical for a sustainable energy future, playing a key role in electrification and integration of renewable energy sources into the grid. Advances in ultrawide band gap materials are needed to handle higher powers in smaller form factors while reducing electrical and thermal losses. High Al content AlxGa1−xN is theoretically capable of meeting these demands, but its impact in power electronics has been severely restricted by a lack of substrates that can satisfy conductivity, lattice matching, and/or thermal expansion requirements. We demonstrate that electrically conductive TaC can be used as a virtual substrate for AlxGa1−xN heteroepitaxy. Scaleably sputtered TaC grown on Al2O3, followed by high-temperature face-to-face annealing, produces a thin film TaC template with an effective hexagonal lattice constant matched to Al0.70Ga0.30N. Annealing of the TaC promotes recrystallization, significantly improving crystallinity and reducing crystalline defects from as-deposited columnar grains to a step-and-terrace surface morphology, enabling the subsequent growth of high-quality Al0.70Ga0.30N by molecular beam epitaxy. X-ray diffraction and scanning transmission electron microscopy confirm that the AlxGa1−xN layer is heteroepitaxially aligned, strain-free, and lattice-matched, transitioning abruptly from TaC to AlxGa1−xN without intermediate phases. These results demonstrate TaC virtual substrates as electrically conductive, lattice-matched, and thermally compatible templates for vertical AlxGa1−xN devices that can meet the growing power needs of a sustainable energy future.

Published by the American Physical Society
2024
How green marketing practices improve customer loyalty: the mediating role of green corporate image and the moderating role of green self-identity in the new energy vehicle market
Authors: Yang Kaixin , Bu Huimei , Huang Rui , Liu Matthew Tingchi 
Published: September 2024

PurposeThis research aims to explore the mechanisms by which green marketing practices (GMP) influence customer loyalty (CL) and how green self-identity (GSI) moderates the relationship between green corporate image (GCI) and customer loyalty in the new energy vehicle (NEV) market.Design/methodology/approachThe study surveyed individuals who had purchased new energy vehicle products through an online platform, resulting in 321 valid questionnaires obtained through a non-probability sampling method. The data were analyzed using the PLS-SEM method to test the proposed hypotheses.FindingsThe research found that green advertisement, green product quality, green product price, external green supply chain management and the salesperson’s green expertise are GMP by the company, and they had positive effects on GCI. Furthermore, GCI had a positive mediating effect between GMP and CL, while green self-identity served as a positive moderator between GMP and CL.Originality/valueThis paper addresses the research gap in the literature on green image and consumer markets, providing a deeper understanding of the mechanisms underpinning GMP and consumer behaviors. These insights can assist companies in shaping a GCI and enhancing CL in the NEV market.
The influences of internal work locus of control on knowledge loss and organizational performance: role of job rotation in Chinese construction firms
Authors: Nyallu Beatrice Audifasi , Deng Xiaopeng , Mgimba Melckzedeck Michael 
Published: September 2024

PurposeKnowledge loss (KL) is still an unfortunate fact, causing many challenges, including poor organisational performance, despite prior efforts to investigate knowledge retention methods. Therefore, this study identifies early approaches to combat KL and poor organisational performance, shifting focus on employee personality traits.Design/methodology/approachGrounded on the social exchange theory (SET) cross-section data from 400 Chinese construction knowledge employees were used to investigate the role of internal work locus of control (IWLC) on job rotation (JR), KL and organisational performance. The data were analysed through IBM SPSS Statistics 25 and SmartPLS 4 software.FindingsThe results demonstrated that IWLC minimises KL and positively influences JR. Then, JR negatively influences KL and decreases in organisational performance. The negative mediating effect of JR in the relationship between IWLC, KL and decreased organisational performance were also found. Finally, KL proved to positively influence a decrease in organisational performance.Research limitations/implicationsThis study contributes to the new understanding of individual behaviour and its influence on organisational outcome variables. Specifically, for ultimate KL prevention and organisational performance improvement, an organisation should understand its employees' behaviours to establish progressive collective learning and knowledge sharing.Practical implicationsThis study contributes to the new understanding of individual behaviour and its influence on organisational outcome variables. Specifically, for ultimate KL prevention and organisational performance improvement, an organisation should understand its employees’ behaviours to establish progressive collective learning and knowledge sharing.Originality/valueThis study is the first attempt to explore the influence of personality traits in the early minimisation of KL, particularly the role of IWLC and JR in combating KL and improving organisational performance.
Revisiting buyer–seller relationships in sustainable sourcing: advancing trust-commitment theory within the context of blockchain technology
Authors: Duan Yanji , Zhu Qingyun , Sarkis Joseph 
Published: September 2024

PurposeTrust-commitment theory has been fundamental in understanding interorganizational relationships in sustainable supply chain management. Trust-commitment dynamics can provide insights into sustainable sourcing outcomes. Despite recent extensions to trust-commitment theory, trust and commitment correlation and the mediation role of trust between antecedents (i.e. opportunism) and commitment remains fundamental. We revisit trust-commitment theoretical relationships within the context of blockchain technology—and specifically blockchain smart contracts.Design/methodology/approachWe conducted the scenario-based experiment with 100 business professionals from operations, supply chain and related fields to test the proposed hypotheses on how different governance mechanisms impact various managerial perceptions in a buyer–seller setting.FindingsFindings reveal that compared with the formal written contract, blockchain smart contract enhances affect-based trust—as the only significant trust dimension, secures buyer commitment and interestingly, encourages opportunistic behavior. The impact of blockchain smart contract on cognition-based and institution-based trust is not significant. The findings advance trust-commitment theory with valuable managerial insights within the blockchain and sustainable sourcing context.Originality/valueThis study serves as a foundation for future studies to further clarify blockchain technology on sustainable buyer–seller relationships using fundamental relationships of trust-commitment and other social exchange theories.
A triple bottom line decision framework for sustainable business location in the retail sector: a developing country perspective
Authors: Asante-Darko Disraeli , Osei Vivian , Agbodjah Sena 
Published: September 2024

Purpose
Retail location decision-making is considered a critical issue with substantial implications for operational success. Nevertheless, choosing an ideal location is a complex problem involving the consideration of several qualitative-quantitative factors, often in conflict. Currently, there is a paucity of decision frameworks that identify the critical triple bottom line (TBL) criteria to support sustainable retail location choices in developing nations. This study, therefore, aims to offer a TBL framework that establishes the critical set of social, economic and environmental factors and analyses their cause-and-effect relationships for achieving sustainability outcomes in retail location decisions.

Design/methodology/approach
The Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach was used to evaluate the TBL sustainability framework comprising 25 sub-factors based on data collected from decision-makers actively involved in retail location decisions in Ghana.

Findings
The research results show that all the TBL pillars are prominent and overlap to realise sustainability requirements in retail location decisions. Specifically, the findings reveal that economic criteria are the most prominent component in the TBL framework that drives the social and environmental dimensions toward sustainable retail location decisions. The causal relationships are also highlighted to offer insights into the relevance of the decision criteria and establish a strategic path for achieving sustainability in the location decisions of retail firms.

Originality/value
The research provides information on the prominent criteria and complex interplay among the TBL parameters to enable decision-makers to make informed location choices that will ultimately increase the sustainability of retail firms operating in developing nations toward improved competitive advantage.